The Role of Stroke Knowledge in Reading and Spelling in Chinese

ERIC Educational Resources Information Center

Lo, Lap-yan; Yeung, Pui-sze; Ho, Connie Suk-Han; Chan, David Wai-ock; Chung, Kevin

2016-01-01

The present study examined the types of orthographic knowledge that are important in learning to read and spell Chinese words in a 2-year longitudinal study following 289 Hong Kong Chinese children from Grade 1 to Grade 2. Multiple regression results showed that radical knowledge significantly predicted children's word reading and spelling…

Contributions of Emergent Literacy Skills to Name Writing, Letter Writing, and Spelling in Preschool Children

PubMed Central

Puranik, Cynthia S.; Lonigan, Christopher J.; Kim, Young-Suk

2011-01-01

The purpose of this study was to examine which emergent literacy skills contribute to preschool children’s emergent writing (name-writing, letter-writing, and spelling) skills. Emergent reading and writing tasks were administered to 296 preschool children aged 4–5 years. Print knowledge and letter-writing skills made positive contributions to name writing; whereas alphabet knowledge, print knowledge, and name writing made positive contributions to letter writing. Both name-writing and letter-writing skills made significant contributions to the prediction of spelling after controlling for age, parental education, print knowledge, phonological awareness, and letter-name and letter-sound knowledge; however, only letter-writing abilities made a significant unique contribution to the prediction of spelling when both letter-writing and name-writing skills were considered together. Name writing reflects knowledge of some letters rather than a broader knowledge of letters that may be needed to support early spelling. Children’s letter-writing skills may be a better indicator of children’s emergent literacy and developing spelling skills than are their name-writing skills at the end of the preschool year. Spelling is a developmentally complex skill beginning in preschool and includes letter writing and blending skills, print knowledge, and letter-name and letter-sound knowledge. PMID:21927537

A hybrid approach of gene sets and single genes for the prediction of survival risks with gene expression data.

PubMed

Seok, Junhee; Davis, Ronald W; Xiao, Wenzhong

2015-01-01

Accumulated biological knowledge is often encoded as gene sets, collections of genes associated with similar biological functions or pathways. The use of gene sets in the analyses of high-throughput gene expression data has been intensively studied and applied in clinical research. However, the main interest remains in finding modules of biological knowledge, or corresponding gene sets, significantly associated with disease conditions. Risk prediction from censored survival times using gene sets hasn't been well studied. In this work, we propose a hybrid method that uses both single gene and gene set information together to predict patient survival risks from gene expression profiles. In the proposed method, gene sets provide context-level information that is poorly reflected by single genes. Complementarily, single genes help to supplement incomplete information of gene sets due to our imperfect biomedical knowledge. Through the tests over multiple data sets of cancer and trauma injury, the proposed method showed robust and improved performance compared with the conventional approaches with only single genes or gene sets solely. Additionally, we examined the prediction result in the trauma injury data, and showed that the modules of biological knowledge used in the prediction by the proposed method were highly interpretable in biology. A wide range of survival prediction problems in clinical genomics is expected to benefit from the use of biological knowledge.

A Hybrid Approach of Gene Sets and Single Genes for the Prediction of Survival Risks with Gene Expression Data

PubMed Central

Seok, Junhee; Davis, Ronald W.; Xiao, Wenzhong

2015-01-01

Accumulated biological knowledge is often encoded as gene sets, collections of genes associated with similar biological functions or pathways. The use of gene sets in the analyses of high-throughput gene expression data has been intensively studied and applied in clinical research. However, the main interest remains in finding modules of biological knowledge, or corresponding gene sets, significantly associated with disease conditions. Risk prediction from censored survival times using gene sets hasn’t been well studied. In this work, we propose a hybrid method that uses both single gene and gene set information together to predict patient survival risks from gene expression profiles. In the proposed method, gene sets provide context-level information that is poorly reflected by single genes. Complementarily, single genes help to supplement incomplete information of gene sets due to our imperfect biomedical knowledge. Through the tests over multiple data sets of cancer and trauma injury, the proposed method showed robust and improved performance compared with the conventional approaches with only single genes or gene sets solely. Additionally, we examined the prediction result in the trauma injury data, and showed that the modules of biological knowledge used in the prediction by the proposed method were highly interpretable in biology. A wide range of survival prediction problems in clinical genomics is expected to benefit from the use of biological knowledge. PMID:25933378

Exploring the Associations Among Nutrition, Science, and Mathematics Knowledge for an Integrative, Food-Based Curriculum.

PubMed

Stage, Virginia C; Kolasa, Kathryn M; Díaz, Sebastián R; Duffrin, Melani W

2018-01-01

Explore associations between nutrition, science, and mathematics knowledge to provide evidence that integrating food/nutrition education in the fourth-grade curriculum may support gains in academic knowledge. Secondary analysis of a quasi-experimental study. Sample included 438 students in 34 fourth-grade classrooms across North Carolina and Ohio; mean age 10 years old; gender (I = 53.2% female; C = 51.6% female). Dependent variable = post-test-nutrition knowledge; independent variables = baseline-nutrition knowledge, and post-test science and mathematics knowledge. Analyses included descriptive statistics and multiple linear regression. The hypothesized model predicted post-nutrition knowledge (F(437) = 149.4, p < .001; Adjusted R = .51). All independent variables were significant predictors with positive association. Science and mathematics knowledge were predictive of nutrition knowledge indicating use of an integrative science and mathematics curriculum to improve academic knowledge may also simultaneously improve nutrition knowledge among fourth-grade students. Teachers can benefit from integration by meeting multiple academic standards, efficiently using limited classroom time, and increasing nutrition education provided in the classroom. © 2018, American School Health Association.

Help-seeking intentions in college students: an exploration of eating disorder specific help-seeking and general psychological help-seeking.

PubMed

Tillman, Kathleen S; Sell, Darcie M

2013-04-01

This study investigated help-seeking intentions for eating disorders and general psychological problems in college students. Participants reported that they would be more likely to seek help for a friend with an eating disorder than for themselves if they were experiencing an eating disorder. Multiple factors (i.e., sex, year in college, knowledge of eating disorders, and knowledge of available resources) were assessed to determine the prediction of help-seeking intentions. Only the knowledge of eating disorders significantly predicted whether or not a student would be willing to seek help for a friend with a general psychological disorder. None of these factors predicted willingness to seek help for friends with an eating disorder. Copyright © 2013 Elsevier Ltd. All rights reserved.

Tire Changes, Fresh Air, and Yellow Flags: Challenges in Predictive Analytics for Professional Racing.

PubMed

Tulabandhula, Theja; Rudin, Cynthia

2014-06-01

Our goal is to design a prediction and decision system for real-time use during a professional car race. In designing a knowledge discovery process for racing, we faced several challenges that were overcome only when domain knowledge of racing was carefully infused within statistical modeling techniques. In this article, we describe how we leveraged expert knowledge of the domain to produce a real-time decision system for tire changes within a race. Our forecasts have the potential to impact how racing teams can optimize strategy by making tire-change decisions to benefit their rank position. Our work significantly expands previous research on sports analytics, as it is the only work on analytical methods for within-race prediction and decision making for professional car racing.

[Knowledge of Emotion Regulation Strategies, Problem Behavior, and Prosocial Behavior in Preschool Age].

PubMed

Gust, Nicole; Koglin, Ute; Petermann, Franz

2015-01-01

The present study examines the relation between knowledge of emotion regulation strategies and social behavior in preschoolers. Knowledge of emotion regulation strategies of 210 children (mean age 55 months) was assessed. Teachers rated children's social behavior with SDQ. Linear regression analysis examined how knowledge of emotion regulation strategies influenced social behavior of children. Significant effects of gender on SDQ scales "prosocial behavior", "hyperactivity", "behavior problems", and SDQ total problem scale were identified. Age was a significant predictor of SDQ scales "prosocial behavior", "hyperactivity", "problems with peers" and SDQ total problem scale. Knowledge of emotion regulation strategies predicted SDQ total problem scores. Results suggest that deficits in knowledge of emotion regulation strategies are linked with increased problem behavior.

Evaluating pictogram prediction in a location-aware augmentative and alternative communication system.

PubMed

Garcia, Luís Filipe; de Oliveira, Luís Caldas; de Matos, David Martins

2016-01-01

This study compared the performance of two statistical location-aware pictogram prediction mechanisms, with an all-purpose (All) pictogram prediction mechanism, having no location knowledge. The All approach had a unique language model under all locations. One of the location-aware alternatives, the location-specific (Spec) approach, made use of specific language models for pictogram prediction in each location of interest. The other location-aware approach resulted from combining the Spec and the All approaches, and was designated the mixed approach (Mix). In this approach, the language models acquired knowledge from all locations, but a higher relevance was assigned to the vocabulary from the associated location. Results from simulations showed that the Mix and Spec approaches could only outperform the baseline in a statistically significant way if pictogram users reuse more than 50% and 75% of their sentences, respectively. Under low sentence reuse conditions there were no statistically significant differences between the location-aware approaches and the All approach. Under these conditions, the Mix approach performed better than the Spec approach in a statistically significant way.

Mother's Health Knowledge and Its Links with the Illness and Medical Care of Their Children in India

ERIC Educational Resources Information Center

Patra, Shraboni; Perianayagam, Arokiasamy; Goli, Srinivas

2016-01-01

Purpose: The level of mother's health knowledge influences not only her health, but also significantly predicts her children's health and medical care, and spending on medical care. This relationship has not yet been empirically assessed in India. The purpose of this paper is to measure the level of health knowledge of mothers in India and its…

Academic Admission Requirements as Predictors of Counseling Knowledge, Personal Development, and Counseling Skills

ERIC Educational Resources Information Center

Smaby, Marlowe H.; Maddux, Cleborne D.; Richmond, Aaron S.; Lepkowski, William J.; Packman, Jill

2005-01-01

The authors investigated whether undergraduates' scores on the Verbal and Quantitative tests of the Graduate Record Examinations and their undergraduate grade point average can be used to predict knowledge, personal development, and skills of graduates of counseling programs. Multiple regression analysis produced significant models predicting…

Examining perceived and actual diabetes knowledge among nurses working in a tertiary hospital.

PubMed

Alotaibi, Abdulellah; Gholizadeh, Leila; Al-Ganmi, Ali; Perry, Lin

2017-06-01

With the worldwide increase in the incidence and prevalence of diabetes, there has been an increase in the scope and scale of nursing care and education required for patients with diabetes. The high prevalence of diabetes in Saudi Arabia makes this a particular priority for this country. The aim of this study was to examine nurses' perceived and actual knowledge of diabetes and its care and management in Saudi Arabia. A convenience sample of 423 nurses working in Prince Sultan Medical Military City in Saudi Arabia was surveyed in this descriptive, cross-sectional study. Perceived knowledge was assessed using the Diabetes Self-Report Tool, while the Diabetes Basic Knowledge Tool was used to assess the actual knowledge of participants. The nurses generally had a positive view of their diabetes knowledge, with a mean score (SD) of 46.9 (6.1) (of maximum 60) for the Diabetes Self-Report Tool. Their actual knowledge scores ranged from 2 to 35 with a mean (SD) score of 25.4 (6.2) (of maximum of 49). Nurses' perceived and actual knowledge of diabetes varied according to their demographic and practice details. Perceived competency, current provision of diabetes care, education level and attendance at any diabetes education programs predicted perceived knowledge; these factors, with gender predicted, with actual diabetes knowledge scores. In this multi-ethnic workforce, findings indicated a significant gap between participants' perceived and actual knowledge. Factors predictive of high levels of knowledge provide pointers to ways to improve diabetes knowledge amongst nurses. Crown Copyright © 2017. Published by Elsevier Inc. All rights reserved.

Knowledge applied to new domains: the unconscious succeeds where the conscious fails.

PubMed

Scott, Ryan B; Dienes, Zoltan

2010-03-01

A common view holds that consciousness is needed for knowledge acquired in one domain to be applied in a novel domain. We present evidence for the opposite; where the transfer of knowledge is achieved only in the absence of conscious awareness. Knowledge of artificial grammars was examined where training and testing occurred in different vocabularies or modalities. In all conditions grammaticality judgments attributed to random selection showed above-chance accuracy (60%), while those attributed to conscious decisions did not. Participants also rated each string's familiarity and performed a perceptual task assessing fluency. Familiarity was predicted by repetition structure and was thus related to grammaticality. Fluency, though increasing familiarity, was unrelated to grammaticality. While familiarity predicted all judgments only those attributed to random selection showed a significant additional contribution of grammaticality, deriving primarily from chunk novelty. In knowledge transfer, as in visual perception (Marcel, 1993), the unconscious may outperform the conscious.

Factors associated with school nurses' HPV vaccine attitudes for school-aged youth.

PubMed

Rosen, Brittany L; DiClemente, Ralph; Shepard, Allie L; Wilson, Kelly L; Fehr, Sara K

2017-06-01

School nurses are at the intersection of the healthcare and school communities, thus, they can be considered opinion leaders in providing health advice - including information about the human papillomavirus (HPV) vaccine - to parents and students. This study examined school nurses' attitudes toward the HPV vaccine based on age, years as a school nurse, geographic location, urban vs. rural work setting, HPV and vaccine knowledge, perception of role as opinion leaders, and school district support in providing health education. Participants (n = 413) were systematically sampled from the National Association of School Nurses' membership and completed a web-based survey. Multiple regression was used to predict positive HPV vaccine attitudes. The model was statistically significant accounting for 50.8% of the variance (F [9, 400] = 45.96, p < .001). Positive attitudes regarding the HPV vaccine were predicted by higher HPV and vaccine knowledge (β = .096, p < .001) and stronger perceptions of role as opinion leaders for the vaccine (β = .665, p < .001). No other variables were found to be statistically significant. These results suggest knowledge is essential in predicting positive attitudes, but not the strongest predictor as perceptions of role as opinion leaders was more crucial in terms of predicting school nurses' positive attitudes towards HPV vaccine. Despite school nurses being seen as champions for adolescent vaccines, they need additional professional development to increase their HPV vaccine knowledge and attitudes to encourage parents and adolescents to consider the uptake of HPV vaccination. To engage school nurses' in promoting HPV vaccine uptake, interventions need to focus on increasing school nurses' perception of their role as opinion leaders for HPV vaccine and knowledge to increase positive attitudes towards HPV vaccination for youth.

Why Does Rapid Naming Predict Chinese Word Reading?

ERIC Educational Resources Information Center

Shum, Kathy Kar-man; Au, Terry Kit-fong

2017-01-01

Rapid automatized naming (RAN) robustly predicts early reading abilities across languages, but its underlying mechanism remains unclear. This study found that RAN associated significantly with processing speed but not with phonological awareness or orthographic knowledge in 89 Hong Kong Chinese second-graders. RAN overlaps more with processing…

Utilizing knowledge base of amino acids structural neighborhoods to predict protein-protein interaction sites.

PubMed

Jelínek, Jan; Škoda, Petr; Hoksza, David

2017-12-06

Protein-protein interactions (PPI) play a key role in an investigation of various biochemical processes, and their identification is thus of great importance. Although computational prediction of which amino acids take part in a PPI has been an active field of research for some time, the quality of in-silico methods is still far from perfect. We have developed a novel prediction method called INSPiRE which benefits from a knowledge base built from data available in Protein Data Bank. All proteins involved in PPIs were converted into labeled graphs with nodes corresponding to amino acids and edges to pairs of neighboring amino acids. A structural neighborhood of each node was then encoded into a bit string and stored in the knowledge base. When predicting PPIs, INSPiRE labels amino acids of unknown proteins as interface or non-interface based on how often their structural neighborhood appears as interface or non-interface in the knowledge base. We evaluated INSPiRE's behavior with respect to different types and sizes of the structural neighborhood. Furthermore, we examined the suitability of several different features for labeling the nodes. Our evaluations showed that INSPiRE clearly outperforms existing methods with respect to Matthews correlation coefficient. In this paper we introduce a new knowledge-based method for identification of protein-protein interaction sites called INSPiRE. Its knowledge base utilizes structural patterns of known interaction sites in the Protein Data Bank which are then used for PPI prediction. Extensive experiments on several well-established datasets show that INSPiRE significantly surpasses existing PPI approaches.

The Impact of Gatekeeper Training for Suicide Prevention on University Resident Assistants

ERIC Educational Resources Information Center

Taub, Deborah J.; Servaty-Seib, Heather L.; Miles, Nathan; Lee, Ji-Yeon; Wachter Morris, Carrie A.; Prieto-Welch, Susan L.; Werden, Donald

2013-01-01

Resident assistants (RAs) can serve as important suicide prevention gatekeepers. The purpose of the study was to determine if training improved RAs' crisis communications skills and suicide-related knowledge and to determine if the knowledge elements predicted crisis communications skills. New RAs showed significant improvement in all areas from…

Policy impacts of ecosystem services knowledge

PubMed Central

Posner, Stephen M.; McKenzie, Emily; Ricketts, Taylor H.

2016-01-01

Research about ecosystem services (ES) often aims to generate knowledge that influences policies and institutions for conservation and human development. However, we have limited understanding of how decision-makers use ES knowledge or what factors facilitate use. Here we address this gap and report on, to our knowledge, the first quantitative analysis of the factors and conditions that explain the policy impact of ES knowledge. We analyze a global sample of cases where similar ES knowledge was generated and applied to decision-making. We first test whether attributes of ES knowledge themselves predict different measures of impact on decisions. We find that legitimacy of knowledge is more often associated with impact than either the credibility or salience of the knowledge. We also examine whether predictor variables related to the science-to-policy process and the contextual conditions of a case are significant in predicting impact. Our findings indicate that, although many factors are important, attributes of the knowledge and aspects of the science-to-policy process that enhance legitimacy best explain the impact of ES science on decision-making. Our results are consistent with both theory and previous qualitative assessments in suggesting that the attributes and perceptions of scientific knowledge and process within which knowledge is coproduced are important determinants of whether that knowledge leads to action. PMID:26831101

Modernization and medicinal plant knowledge in a Caribbean horticultural village.

PubMed

Quinlan, Marsha B; Quinlan, Robert J

2007-06-01

Herbal medicine is the first response to illness in rural Dominica. Every adult knows several "bush" medicines, and knowledge varies from person to person. Anthropological convention suggests that modernization generally weakens traditional knowledge. We examine the effects of commercial occupation, consumerism, education, parenthood, age, and gender on the number of medicinal plants freelisted by individuals. All six predictors are associated with bush medical knowledge in bivariate analyses. Contrary to predictions, commercial occupation and consumerism are positively associated with herbal knowledge. Gender, age, occupation, and education are significant predictors in multivariate analysis. Women tend to recall more plants than do men. Education is negatively associated with plants listed; age positively associates with number of species listed. There are significant interactions among commercial occupation, education, age, and parenthood, suggesting that modernization has complex effects on knowledge of traditional medicine in Dominica.

The role of gender and sexual experience in predicting adolescent condom use intentions using the theory of planned behaviour.

PubMed

Rich, Antonia; Mullan, Barbara A; Sainsbury, Kirby; Kuczmierczyk, Andrzej R

2014-08-01

To examine how the prediction of condom-related cognitions, intentions, and behaviour amongst adolescents may differ according to gender and sexual experience within a theory of planned behaviour (TPB) framework. Adolescents (N = 306) completed questionnaires about sexual experience, condom use, TPB variables, perceived risk, and safe sex knowledge. Significant differences in TPB variables, perceived risk, and knowledge were found; males and sexually experienced participants were generally less positive about condom use. Twenty percent of the variance in attitudes was accounted for by four variables; specifically, female gender, no previous sexual experience, better safe sex knowledge, and greater risk perceptions were associated with more positive attitudes. The prediction of intentions separately amongst sexually experienced (R(2) = 0.468) and inexperienced (R(2) = 0.436) participants revealed that, for the former group, attitudes and subjective norms were the most important considerations. In contrast, among the inexperienced participants, attitudes and the gender-by-perceived risk interaction term represented significant influences. The results suggest that interventions designed to improve adolescents' intentions to use condoms and rates of actual condom use should consider differences in gender and sexual experience.

Combining Knowledge and Data Driven Insights for Identifying Risk Factors using Electronic Health Records

PubMed Central

Sun, Jimeng; Hu, Jianying; Luo, Dijun; Markatou, Marianthi; Wang, Fei; Edabollahi, Shahram; Steinhubl, Steven E.; Daar, Zahra; Stewart, Walter F.

2012-01-01

Background: The ability to identify the risk factors related to an adverse condition, e.g., heart failures (HF) diagnosis, is very important for improving care quality and reducing cost. Existing approaches for risk factor identification are either knowledge driven (from guidelines or literatures) or data driven (from observational data). No existing method provides a model to effectively combine expert knowledge with data driven insight for risk factor identification. Methods: We present a systematic approach to enhance known knowledge-based risk factors with additional potential risk factors derived from data. The core of our approach is a sparse regression model with regularization terms that correspond to both knowledge and data driven risk factors. Results: The approach is validated using a large dataset containing 4,644 heart failure cases and 45,981 controls. The outpatient electronic health records (EHRs) for these patients include diagnosis, medication, lab results from 2003–2010. We demonstrate that the proposed method can identify complementary risk factors that are not in the existing known factors and can better predict the onset of HF. We quantitatively compare different sets of risk factors in the context of predicting onset of HF using the performance metric, the Area Under the ROC Curve (AUC). The combined risk factors between knowledge and data significantly outperform knowledge-based risk factors alone. Furthermore, those additional risk factors are confirmed to be clinically meaningful by a cardiologist. Conclusion: We present a systematic framework for combining knowledge and data driven insights for risk factor identification. We demonstrate the power of this framework in the context of predicting onset of HF, where our approach can successfully identify intuitive and predictive risk factors beyond a set of known HF risk factors. PMID:23304365

How best to measure implementation of school health curricula: a comparison of three measures.

PubMed

Resnicow, K; Davis, M; Smith, M; Lazarus-Yaroch, A; Baranowski, T; Baranowski, J; Doyle, C; Wang, D T

1998-06-01

The impact of school health education programs is often attenuated by inadequate teacher implementation. Using data from a school-based nutrition education program delivered in a sample of fifth graders, this study examines the discriminant and predictive validity of three measures of curriculum implementation: class-room observation of fidelity, and two measures of completeness, teacher self-report questionnaire and post-implementation interview. A fourth measure, obtained during teacher observations, that assessed student and teacher interaction and student receptivity to the curriculum (labeled Rapport) was also obtained. Predictive validity was determined by examining the association of implementation measures with three study outcomes; health knowledge, asking behaviors related to fruit and vegetables, and fruit and vegetable intake, assessed by 7-day diary. Of the 37 teachers observed, 21 were observed for two sessions and 16 were observed once. Implementation measures were moderately correlated, an indication of discriminant validity. Predictive validity analyses indicated that the observed fidelity, Rapport and interview measures were significantly correlated with post-test student knowledge. The association between health knowledge and observed fidelity (based on dual observation only), Rapport and interview measures remained significant after adjustment for pre-test knowledge values. None of the implementation variables were significantly associated with student fruit and vegetable intake or asking behaviors controlling for pre-test values. These results indicate that the teacher self-report questionnaire was not a valid measure of implementation completeness in this study. Post-implementation completeness interviews and dual observations of fidelity and Rapport appear to be more valid, and largely independent methods of implementation assessment.

Human Papillomavirus (HPV) Vaccination and Adolescent Girls' Knowledge and Sexuality in Western Uganda: A Comparative Cross-Sectional Study.

PubMed

Turiho, Andrew Kampikaho; Muhwezi, Wilson Winston; Okello, Elialilia Sarikiaeli; Tumwesigye, Nazarius Mbona; Banura, Cecil; Katahoire, Anne Ruhweza

2015-01-01

The purpose of the study was to investigate the influence of human papillomavirus (HPV) vaccination on adolescent girls' knowledge of HPV and HPV vaccine, perception of sexual risk and intentions for sexual debut. This cross-sectional comparative study was conducted in Ibanda and Mbarara districts. Data was collected using a standardized self-administered questionnaire and analyzed using the Statistical Package for the Social Sciences computer software. Univariate, bivariate, and logistic regression analyses were conducted with significance level set at p < .05. Results showed that HPV vaccination was associated with being knowledgeable (Crude OR: 5.26, CI: 2.32-11.93; p = 0.000). Vaccination against HPV did not predict perception of sexual risk. Knowledge was low (only 87/385 or 22.6% of vaccinated girls were knowledgeable), but predicted perception of a high sexual risk (Adjusted OR: 3.12, CI: 1.37-3.63; p = 0.008). HPV vaccination, knowledge and perceived sexual risk did not predict sexual behaviour intentions. High parental communication was associated with adolescent attitudes that support postponement of sexual debut in both bivariate and multiple regression analyses. In conclusion, findings of this study suggest that HPV vaccination is not likely to encourage adolescent sexual activity. Influence of knowledge on sexual behaviour intentions was not definitively explained. Prospective cohort studies were proposed to address the emerging questions.

Health locus of control and assimilation of cervical cancer information in Deaf women.

PubMed

Wang, Regina; Aldridge, Arianna A; Malcarne, Vanessa L; Choe, Sun; Branz, Patricia; Sadler, Georgia Robins

2010-09-01

This study assessed the relationship between Deaf women's internal health locus of control (IHLC) and their cervical cancer knowledge acquisition and retention. A blind, randomized trial evaluated Deaf women's (N = 130) baseline cancer knowledge and knowledge gained and retained from an educational intervention, in relation to their IHLC. The Multidimensional Health Locus of Control scales measured baseline IHLC, and a cervical cancer knowledge survey evaluated baseline to post-intervention knowledge change. Women's IHLC did not significantly predict greater cervical cancer knowledge at baseline or over time. IHLC does not appear to be a characteristic that must be considered when creating Deaf women's cancer education programs.

Cigarette Smoking, Knowledge, Attitude and Prediction of Smoking Between Male Students, Teachers and Clergymen in Tehran, Iran, 2009

PubMed Central

Heydari, Gholamreza; Yousefifard, Mahmoud; Hosseini, Mostafa; Ramezankhani, Ali; Masjedi, Mohammad Reza

2013-01-01

Background: Students, clergymen and teachers as role models can be very important in encouragement or prevention of cigarette smoking in young people. The aim of this study was to compare prevalence of smoking in 3 male groups of teachers, clergymen and university students. Also, study their knowledge and attitude towards it and the prediction of their future consumption. Methods: In a cross sectional study in 2009 in Tehran, Iran, 1,271 male students, 549 clergymen and 551 teachers were randomly enrolled. Each participant completed the global adult tobacco survey questionnaire. Knowledge, attitude and prediction of smoking for the next 5 years were questioned in these 3 groups. Chi-squared test and logistic regression were used for analysis. P < 0.05 was considered significant. Results: Prevalence of cigarette smoking was 31.1%, 21.9% and 27.2% among students, clergymen and teachers, respectively. Smoking in students was not associated with poor knowledge but were in teachers and clergymen. The odds ratio of smoking in students, clergymen and teachers was higher among those with having inappropriate attitude towards it (OR = 1.6, 6.1 and 4.5). Those with poor knowledge had an inappropriate attitude and predicted higher chance of cigarette consumption in the next 5 years (P < 0.0001). Inappropriate attitude in all 3 groups resulted in higher prediction of future smoking (P = 0.008). Conclusions: This study revealed that the prevalence of smoking among male students and teachers was higher than general population and clergymen who equally smoked. Also, level of knowledge and attitude of students were lower than teachers and clergymen. PMID:23930167

Learning Temporal Statistics for Sensory Predictions in Aging.

PubMed

Luft, Caroline Di Bernardi; Baker, Rosalind; Goldstone, Aimee; Zhang, Yang; Kourtzi, Zoe

2016-03-01

Predicting future events based on previous knowledge about the environment is critical for successful everyday interactions. Here, we ask which brain regions support our ability to predict the future based on implicit knowledge about the past in young and older age. Combining behavioral and fMRI measurements, we test whether training on structured temporal sequences improves the ability to predict upcoming sensory events; we then compare brain regions involved in learning predictive structures between young and older adults. Our behavioral results demonstrate that exposure to temporal sequences without feedback facilitates the ability of young and older adults to predict the orientation of an upcoming stimulus. Our fMRI results provide evidence for the involvement of corticostriatal regions in learning predictive structures in both young and older learners. In particular, we showed learning-dependent fMRI responses for structured sequences in frontoparietal regions and the striatum (putamen) for young adults. However, for older adults, learning-dependent activations were observed mainly in subcortical (putamen, thalamus) regions but were weaker in frontoparietal regions. Significant correlations of learning-dependent behavioral and fMRI changes in these regions suggest a strong link between brain activations and behavioral improvement rather than general overactivation. Thus, our findings suggest that predicting future events based on knowledge of temporal statistics engages brain regions involved in implicit learning in both young and older adults.

Validity Evidence for Games as Assessment Environments. CRESST Report 773

ERIC Educational Resources Information Center

Delacruz, Girlie C.; Chung, Gregory K. W. K.; Baker, Eva L.

2010-01-01

This study provides empirical evidence of a highly specific use of games in education--the assessment of the learner. Linear regressions were used to examine the predictive and convergent validity of a math game as assessment of mathematical understanding. Results indicate that prior knowledge significantly predicts game performance. Results also…

Examining the links between therapeutic jurisprudence and mental health court completion.

PubMed

Redlich, Allison D; Han, Woojae

2014-04-01

Research demonstrates that mental health courts (MHCs) lead to improved outcomes compared to traditional criminal court processes. An underlying premise of MHCs is therapeutic jurisprudence (TJ). However, no research, to our knowledge, has examined whether MHC outcomes are predicted by TJ principles as theorized. In the present study, we examined whether principles measured at the onset of MHC enrollment (knowledge, perceived voluntariness, and procedural justice) predicted MHC completion (graduation). Using structural equation modeling with MHC participants from four courts, a significant, direct relationship between TJ and MHC completion was found, such that higher levels of TJ were associated with higher rates of success. Although this direct effect became nonsignificant when mediator variables were included, a significant indirect path remained, such that increased levels of initial perceived voluntariness and procedural justice, and MHC knowledge, led to decreased rates of new arrests, prison, MHC bench warrants, and increased court compliance, which, in turn, led to a higher likelihood of MHC graduation. PsycINFO Database Record (c) 2014 APA, all rights reserved.

The HOT (Healthy Outcome for Teens) project. Using a web-based medium to influence attitude, subjective norm, perceived behavioral control and intention for obesity and type 2 diabetes prevention.

PubMed

Muzaffar, Henna; Chapman-Novakofski, Karen; Castelli, Darla M; Scherer, Jane A

2014-01-01

We hypothesized that Theory of Planned Behavior (TPB) constructs (behavioral belief, attitude, subjective norm, perceived behavioral control, knowledge and behavioral intention) regarding preventive behaviors for obesity and type 2 diabetes will change favorably after completing the web-based intervention, HOT (Healthy Outcome for Teens) project, grounded in the TPB; and that passive online learning (POL) group will improve more than the active online learning (AOL) group. The secondary hypothesis was to determine to what extent constructs of the TPB predict intentions. 216 adolescents were recruited, 127 randomly allocated to the treatment group (AOL) and 89 to the control group (POL). The subjects completed a TPB questionnaire pre and post intervention. Both POL and AOL groups showed significant improvements from pretest to posttest survey. However, the results indicated no significant difference between POL and AOL for all constructs except behavioral belief. Correlational analysis indicated that all TPB constructs were significantly correlated with intentions for pretest and posttest for both groups. Attitude and behavioral control showed strongest correlations. Regression analysis indicated that TPB constructs were predictive of intentions and the predictive power improved post intervention. Behavioral control consistently predicted intentions for all categories and was the strongest predictor for pretest scores. For posttest scores, knowledge and attitude were the strongest predictors for POL and AOL groups respectively. Thus, HOT project improved knowledge and the TPB constructs scores for targeted behaviors, healthy eating and physical activity, for prevention of obesity and type 2 diabetes. Published by Elsevier Ltd.

What You Know Can Hurt You: Effects of Age and Prior Knowledge on the Accuracy of Judgments of Learning

PubMed Central

Toth, Jeffrey P.; Daniels, Karen A.; Solinger, Lisa A.

2011-01-01

How do aging and prior knowledge affect memory and metamemory? We explored this question in the context of a dual-process approach to Judgments of Learning (JOLs) which require people to predict their ability to remember information at a later time. Young and older adults (n's = 36, mean ages = 20.2 & 73.1) studied the names of actors that were famous in the 1950s or 1990s, providing a JOL for each. Recognition memory for studied and unstudied actors was then assessed using a Recollect/Know/No-Memory (R/K/N) judgment task. Results showed that prior knowledge increased recollection in both age groups such that older adults recollected significantly more 1950s actors than younger adults. Also, for both age groups and both decades, actors judged R at test garnered significantly higher JOLs at study than actors judged K or N. However, while the young showed benefits of prior knowledge on relative JOL accuracy, older adults did not, showing lower levels of JOL accuracy for 1950s actors despite having higher recollection for, and knowledge about, those actors. Overall, the data suggest that prior knowledge can be a double-edged sword, increasing the availability of details that can support later recollection, but also increasing non-diagnostic feelings of familiarity that can reduce the accuracy of memory predictions. PMID:21480715

Comparing the accuracy of personality judgements by the self and knowledgeable others.

PubMed

Kolar, D W; Funder, D C; Colvin, C R

1996-06-01

In this article we compare the accuracy of personality judgements by the self and by knowledgeable others. Self- and acquaintance judgements of general personality attributes were used to predict general, videotaped behavioral criteria. Results slightly favored the predictive validity of personality judgements made by single acquaintances over self-judgements, and significantly favored the aggregated personality judgements of two acquaintances over self-judgements. These findings imply that the most valid source for personality judgements that are relevant to patterns of overt behavior may not be self-reports but the consensus of the judgement of the community of one's peers.

Early Predictors of Middle School Fraction Knowledge

PubMed Central

Bailey, Drew H.; Siegler, Robert S.; Geary, David C.

2014-01-01

Recent findings that earlier fraction knowledge predicts later mathematics achievement raise the question of what predicts later fraction knowledge. Analyses of longitudinal data indicated that whole number magnitude knowledge in first grade predicted knowledge of fraction magnitudes in middle school, controlling for whole number arithmetic proficiency, domain general cognitive abilities, parental income and education, race, and gender. Similarly, knowledge of whole number arithmetic in first grade predicted knowledge of fraction arithmetic in middle school, controlling for whole number magnitude knowledge in first grade and the other control variables. In contrast, neither type of early whole number knowledge uniquely predicted middle school reading achievement. We discuss the implications of these findings for theories of numerical development and for improving mathematics learning. PMID:24576209

Combining PubMed knowledge and EHR data to develop a weighted bayesian network for pancreatic cancer prediction.

PubMed

Zhao, Di; Weng, Chunhua

2011-10-01

In this paper, we propose a novel method that combines PubMed knowledge and Electronic Health Records to develop a weighted Bayesian Network Inference (BNI) model for pancreatic cancer prediction. We selected 20 common risk factors associated with pancreatic cancer and used PubMed knowledge to weigh the risk factors. A keyword-based algorithm was developed to extract and classify PubMed abstracts into three categories that represented positive, negative, or neutral associations between each risk factor and pancreatic cancer. Then we designed a weighted BNI model by adding the normalized weights into a conventional BNI model. We used this model to extract the EHR values for patients with or without pancreatic cancer, which then enabled us to calculate the prior probabilities for the 20 risk factors in the BNI. The software iDiagnosis was designed to use this weighted BNI model for predicting pancreatic cancer. In an evaluation using a case-control dataset, the weighted BNI model significantly outperformed the conventional BNI and two other classifiers (k-Nearest Neighbor and Support Vector Machine). We conclude that the weighted BNI using PubMed knowledge and EHR data shows remarkable accuracy improvement over existing representative methods for pancreatic cancer prediction. Copyright © 2011 Elsevier Inc. All rights reserved.

Combining PubMed Knowledge and EHR Data to Develop a Weighted Bayesian Network for Pancreatic Cancer Prediction

PubMed Central

Zhao, Di; Weng, Chunhua

2011-01-01

In this paper, we propose a novel method that combines PubMed knowledge and Electronic Health Records to develop a weighted Bayesian Network Inference (BNI) model for pancreatic cancer prediction. We selected 20 common risk factors associated with pancreatic cancer and used PubMed knowledge to weigh the risk factors. A keyword-based algorithm was developed to extract and classify PubMed abstracts into three categories that represented positive, negative, or neutral associations between each risk factor and pancreatic cancer. Then we designed a weighted BNI model by adding the normalized weights into a conventional BNI model. We used this model to extract the EHR values for patients with or without pancreatic cancer, which then enabled us to calculate the prior probabilities for the 20 risk factors in the BNI. The software iDiagnosis was designed to use this weighted BNI model for predicting pancreatic cancer. In an evaluation using a case-control dataset, the weighted BNI model significantly outperformed the conventional BNI and two other classifiers (k-Nearest Neighbor and Support Vector Machine). We conclude that the weighted BNI using PubMed knowledge and EHR data shows remarkable accuracy improvement over existing representative methods for pancreatic cancer prediction. PMID:21642013

Declarative knowledge and professional vision in teacher education: effect of courses in teaching and learning.

PubMed

Stürmer, Kathleen; Könings, Karen D; Seidel, Tina

2013-09-01

Teachers' professional vision includes the ability to apply general pedagogical knowledge about components of effective teaching and learning to reason about significant features of classroom practice. It requires teachers to (a) describe, (b) explain, and (c) predict classroom situations. Although the acquisition of underling knowledge can be considered as a key element of university-based teacher education programmes, to date, there has been little empirical research on teacher candidates' development of professional vision. This study aims to improve understanding of how different university-based courses in teaching and learning impact the development of professional vision. Participants were teacher candidates (N= 53) attending the same teacher education programme at a German university. They were enrolled in one of three different compulsory courses in teaching and learning, lasting one semester. In a pre-test-post-test design, participants' declarative knowledge about teaching and learning was measured with a test, professional vision with the online tool Observer. Analysis of covariance and multivariate analysis of variance were conducted. Teacher candidates in all three courses showed significant gains both in declarative knowledge and professional vision. Patterns of results differed depending on the course attended. A video-based course with a focus on effective teaching resulted in highest gains in prediction of the consequences of observed events for student learning processes, which is the highest level of knowledge transfer. The development of professional vision is a strongly knowledge-guided process. In line with their content and aims, university-based courses can enhance teaching-relevant knowledge for teacher candidates. © 2012 The British Psychological Society.

Are public health professionals prepared for public health genomics? A cross-sectional survey in Italy

PubMed Central

2014-01-01

Background Public health genomics is an emerging multidisciplinary approach, which aims to integrate genome-based knowledge in a responsible and effective way into public health. Despite several surveys performed to evaluate knowledge, attitudes and professional behaviors of physicians towards predictive genetic testing, similar surveys have not been carried out for public health practitioners. This study is the first to assess knowledge, attitudes and training needs of public health professionals in the field of predictive genetic testing for chronic diseases. Methods A self-administered questionnaire was used to carry out a cross-sectional survey of a random sample of Italian public health professionals. Results A response rate of 67.4% (797 questionnaires) was achieved. Italian public health professionals have the necessary attitudinal background to contribute to the proper use of predictive genetic testing for chronic diseases, but they need additional training to increase their methodological knowledge. Knowledge significantly increases with exposure to predictive genetic testing during postgraduate training (odds ratio (OR) = 1.74, 95% confidence interval (CI) = 1.05–2.88), time dedicated to continuing medical education (OR = 1.53, 95% CI = 1.14–2.04) and level of English language knowledge (OR = 1.36, 95% CI = 1.07–1.72). Adequate knowledge is the strongest predictor of positive attitudes from a public health perspective (OR = 3.98, 95% CI = 2.44–6.50). Physicians show a lower level of knowledge and more public health attitudes than other public health professionals do. About 80% of public health professionals considered their knowledge inadequate and 86.0% believed that it should be improved through specific postgraduate training courses. Conclusions Specific and targeted training initiatives are needed to develop a skilled public health workforce competent in identifying genomic technology that is ready for use in population health and in modeling public health genomic programs and primary care services that need to be developed, implemented and evaluated. PMID:24885316

Early Predictors of Middle School Fraction Knowledge

ERIC Educational Resources Information Center

Bailey, Drew H.; Siegler, Robert S.; Geary, David C.

2014-01-01

Recent findings that earlier fraction knowledge predicts later mathematics achievement raise the question of what predicts later fraction knowledge. Analyses of longitudinal data indicated that whole number magnitude knowledge in first grade predicted knowledge of fraction magnitudes in middle school, controlling for whole number arithmetic…

Combining Modeling and Gaming for Predictive Analytics

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

Riensche, Roderick M.; Whitney, Paul D.

2012-08-22

Many of our most significant challenges involve people. While human behavior has long been studied, there are recent advances in computational modeling of human behavior. With advances in computational capabilities come increases in the volume and complexity of data that humans must understand in order to make sense of and capitalize on these modeling advances. Ultimately, models represent an encapsulation of human knowledge. One inherent challenge in modeling is efficient and accurate transfer of knowledge from humans to models, and subsequent retrieval. The simulated real-world environment of games presents one avenue for these knowledge transfers. In this paper we describemore » our approach of combining modeling and gaming disciplines to develop predictive capabilities, using formal models to inform game development, and using games to provide data for modeling.« less

Predicting fifth-grade students' understanding of ecological science concepts with motivational and cognitive variables

NASA Astrophysics Data System (ADS)

Alao, Solomon

The need to identify factors that contribute to students' understanding of ecological concepts has been widely expressed in recent literature. The purpose of this study was to investigate the relationship between fifth grade students' prior knowledge, learning strategies, interest, and learning goals and their conceptual understanding of ecological science concepts. Subject were 72 students from three fifth grade classrooms located in a metropolitan area of the eastern United States. Students completed the goal commitment, interest, and strategy use questionnaire (GISQ), and a knowledge test designed to assess their prior knowledge and conceptual understanding of ecological science concepts. The learning goals scale assessed intentions to try to learn and understand ecological concepts. The interest scale assessed the feeling and value-related valences that students ascribed to science and ecological science concepts. The strategy use scale assessed the use of two cognitive strategies (monitoring and elaboration). The knowledge test assessed students' understanding of ecological concepts (the relationship between living organisms and their environment). Scores on all measures were examined for gender differences; no significant gender differences were observed. The motivational and cognitive variables contributed to students' understanding of ecological concepts. After accounting for interest, learning goals, and strategy use, prior knowledge accounted for 28% of the total variance in conceptual understanding. After accounting for prior knowledge, interest, learning goals, and strategy use explained 7%, 6%, and 4% of the total variance in conceptual understanding, respectively. More importantly, these variables were interrelated to each other and to conceptual understanding. After controlling for prior knowledge, learning goals, and strategy use, interest did not predict the variance in conceptual understanding. After controlling for prior knowledge, interest, and strategy use, learning goals did not predict the variance in conceptual understanding. And, after controlling for prior knowledge, interest, and learning goals, strategy use did not predict the variance in conceptual understanding. Results of this study indicated that prior knowledge, interest, learning goals, and strategy use should be included in theoretical models design to explain and to predict fifth grade students' understanding of ecological concepts. Results of this study further suggested that curriculum developers and science teachers need to take fifth grade students' prior knowledge of ecological concepts, interest in science and ecological concepts; intentions to learn and understand ecological concepts, and use of cognitive strategies into account when designing instructional contexts to support these students' understanding of ecological concepts.

Health Locus of Control and Assimilation of Cervical Cancer Information in Deaf Women

PubMed Central

Wang, Regina; Aldridge, Arianna A.; Malcarne, Vanessa L.; Choe, Sun; Branz, Patricia

2010-01-01

This study assessed the relationship between Deaf women's internal health locus of control (IHLC) and their cervical cancer knowledge acquisition and retention. A blind, randomized trial evaluated Deaf women's (N = 130) baseline cancer knowledge and knowledge gained and retained from an educational intervention, in relation to their IHLC. The Multidimensional Health Locus of Control scales measured baseline IHLC, and a cervical cancer knowledge survey evaluated baseline to post-intervention knowledge change. Women's IHLC did not significantly predict greater cervical cancer knowledge at baseline or over time. IHLC does not appear to be a characteristic that must be considered when creating Deaf women's cancer education programs. PMID:20229077

Does Nutrition Knowledge and Practice of Athletes Translate to Enhanced Athletic Performance? Cross-Sectional Study Amongst Nigerian Undergraduate Athletes

PubMed Central

Folasire, Oluyemisi F.; Akomolafe, Abiola A.; Sanusi, Rasaki A.

2015-01-01

Introduction and Objectives: Nutrition knowledge of an athlete, as well as practice, is expected to influence athlete’s performance. The study assessed the nutrition knowledge and practice as well as athletes’ performance and identified the factors predicting the athletes’ performance. Methodology: A cross-sectional survey, involved 110 purposively selected undergraduate athletes (47 females, 63 males) of University of Ibadan, Nigeria, between July 2013 and December 2013. A semi-structured, self-administered questionnaire assessed the nutrition knowledge and practice. 24-hr diet recall and food frequency questionnaire were done. Anthropometric measurements were taken; body composition was determined by bioelectrical impedance analysis method. Handgrip strength (HGS), as an indirect measure of athlete performance, was assessed with the hand dynamometer. Chi-square and t-test analysis were used for the bivariate analysis. Pearson correlation and simple linear regression were used to determine relationships and predict athletic performance. The level of statistical significance was p<0.05. Results: More than half (58.2%) had good nutrition knowledge (NK), and 62.7% had good nutrition practices (NP). Majority (75.4%) had normal handgrip strength (HGS). More than 70.0% frequently do not consume cereals, roots and tubers, fruits and vegetables, legumes/nuts. About 30.0-40.0% frequently do not consume eggs/milk, meat/fish. Having good NK was significantly associated with good NP (χ2 = 15.520, p=0.000), but not with athlete’s performance (HGS). There is no significant correlation between NK, NP, and HGS. There is a significant positive correlation between HGS and lean muscle mass (LMM) (r=.670, p=0.000), weight (r=.492, p=0.000), height (r=.521, p=0.000) and energy intake (r=.386, p=0.000). There is a significant negative correlation between HGS and percentage body fat (r=-.400, p=0.000). Athletes’ performance was significantly predicted by the resting metabolic rate (β= .454 C.I=0.011 to 0.045, p=0.003), Lean muscle mass (β =.297 C.I=.059 to 0.562, p=0.024) and the weight (β =.228, C.I=1.852 to .489, p=0.047). Conclusion: Having good nutrition knowledge or practice did not directly determine athletic performance. However, there is the need for nutrition education interventions, to improve athlete’s performance by promoting adequate energy intake, lean muscle mass and appropriate weight gain in athletes. PMID:26156896

Combined and Relative Effect Levels of Perceived Risk, Knowledge, Optimism, Pessimism, and Social Trust on Anxiety among Inhabitants Concerning Living on Heavy Metal Contaminated Soil

PubMed Central

Tang, Zhongjun; Guo, Zengli; Zhou, Li; Xue, Shengguo; Zhu, Qinfeng; Zhu, Huike

2016-01-01

This research aims at combined and relative effect levels on anxiety of: (1) perceived risk, knowledge, optimism, pessimism, and social trust; and (2) four sub-variables of social trust among inhabitants concerning living on heavy metal contaminated soil. On the basis of survey data from 499 Chinese respondents, results suggest that perceived risk, pessimism, optimism, and social trust have individual, significant, and direct effects on anxiety, while knowledge does not. Knowledge has significant, combined, and interactive effects on anxiety together with social trust and pessimism, respectively, but does not with perceived risk and optimism. Social trust, perceived risk, pessimism, knowledge, and optimism have significantly combined effects on anxiety; the five variables as a whole have stronger predictive values than each one individually. Anxiety is influenced firstly by social trust and secondly by perceived risk, pessimism, knowledge, and optimism. Each of four sub-variables of social trust has an individual, significant, and negative effect on anxiety. When introducing four sub-variables into one model, trust in social organizations and in the government have significantly combined effects on anxiety, while trust in experts and in friends and relatives do not; anxiety is influenced firstly by trust in social organization, and secondly by trust in the government. PMID:27827866

Combined and Relative Effect Levels of Perceived Risk, Knowledge, Optimism, Pessimism, and Social Trust on Anxiety among Inhabitants Concerning Living on Heavy Metal Contaminated Soil.

PubMed

Tang, Zhongjun; Guo, Zengli; Zhou, Li; Xue, Shengguo; Zhu, Qinfeng; Zhu, Huike

2016-11-02

This research aims at combined and relative effect levels on anxiety of: (1) perceived risk, knowledge, optimism, pessimism, and social trust; and (2) four sub-variables of social trust among inhabitants concerning living on heavy metal contaminated soil. On the basis of survey data from 499 Chinese respondents, results suggest that perceived risk, pessimism, optimism, and social trust have individual, significant, and direct effects on anxiety, while knowledge does not. Knowledge has significant, combined, and interactive effects on anxiety together with social trust and pessimism, respectively, but does not with perceived risk and optimism. Social trust, perceived risk, pessimism, knowledge, and optimism have significantly combined effects on anxiety; the five variables as a whole have stronger predictive values than each one individually. Anxiety is influenced firstly by social trust and secondly by perceived risk, pessimism, knowledge, and optimism. Each of four sub-variables of social trust has an individual, significant, and negative effect on anxiety. When introducing four sub-variables into one model, trust in social organizations and in the government have significantly combined effects on anxiety, while trust in experts and in friends and relatives do not; anxiety is influenced firstly by trust in social organization, and secondly by trust in the government.

Which Preschool Mathematics Competencies Are Most Predictive of Fifth Grade Achievement?

PubMed

Nguyen, Tutrang; Watts, Tyler W; Duncan, Greg J; Clements, Douglas H; Sarama, Julie S; Wolfe, Christopher; Spitler, Mary Elaine

In an effort to promote best practices regarding mathematics teaching and learning at the preschool level, national advisory panels and organizations have emphasized the importance of children's emergent counting and related competencies, such as the ability to verbally count, maintain one-to-one correspondence, count with cardinality, subitize, and count forward or backward from a given number. However, little research has investigated whether the kind of mathematical knowledge promoted by the various standards documents actually predict later mathematics achievement. The present study uses longitudinal data from a primarily low-income and minority sample of children to examine the extent to which preschool mathematical competencies, specifically basic and advanced counting, predict fifth grade mathematics achievement. Using regression analyses, we find early numeracy abilities to be the strongest predictors of later mathematics achievement, with advanced counting competencies more predictive than basic counting competencies. Our results highlight the significance of preschool mathematics knowledge for future academic achievement.

Some types of parent number talk count more than others: relations between parents' input and children's cardinal-number knowledge.

PubMed

Gunderson, Elizabeth A; Levine, Susan C

2011-09-01

Before they enter preschool, children vary greatly in their numerical and mathematical knowledge, and this knowledge predicts their achievement throughout elementary school (e.g. Duncan et al., 2007; Ginsburg & Russell, 1981). Therefore, it is critical that we look to the home environment for parental inputs that may lead to these early variations. Recent work has shown that the amount of number talk that parents engage in with their children is robustly related to a critical aspect of mathematical development - cardinal-number knowledge (e.g. knowing that the word 'three' refers to sets of three entities; Levine, Suriyakham, Rowe, Huttenlocher & Gunderson, 2010). The present study characterizes the different types of number talk that parents produce and investigates which types are most predictive of children's later cardinal-number knowledge. We find that parents' number talk involving counting or labeling sets of present, visible objects is related to children's later cardinal-number knowledge, whereas other types of parent number talk are not. In addition, number talk that refers to large sets of present objects (i.e. sets of size 4 to 10 that fall outside children's ability to track individual objects) is more robustly predictive of children's later cardinal-number knowledge than talk about smaller sets. The relation between parents' number talk about large sets of present objects and children's cardinal-number knowledge remains significant even when controlling for factors such as parents' socioeconomic status and other measures of parents' number and non-number talk. © 2011 Blackwell Publishing Ltd.

Patients' intentions to seek medication information from pharmacists.

PubMed

Huston, Sally A

2013-01-01

To determine whether perceived medication use knowledge held and/or needed influenced intention to seek information from pharmacists, whether an information-intention relationship held after accounting for other variables, and whether asking medication use knowledge questions increased pharmacist information-seeking intention. Cross-sectional study. SETTING United States during July 2012. Qualtrics national panel members 21 years or older obtaining a new chronic medication within previous 30 days. Internet-administered survey. Medication information-seeking intention, medication knowledge held and needed, and pharmacist medication information-seeking intention. Although knowledge held and needed were initially significant, they became nonsignificant after adding affective and evaluative attitudes, perceived control, and risk. The final best-fitting model explained 21% of variance in pharmacist information-seeking intention. Patient intentions to seek information from pharmacists increased significantly after being asked medication use knowledge questions. Perceptions of medication risk, attitudes, and information-seeking control predict pharmacist information-seeking intention and offer pharmacists an opportunity to market information services.

Attitude of Israeli mothers with vaccination of their daughters against human papilloma virus.

PubMed

Ben Natan, Merav; Aharon, Osnat; Palickshvili, Sharon; Gurman, Vicky

2011-02-01

The purpose of the study is to examine whether the model based on the Theory of Reasoned Action (TRA) succeeds in predicting mothers' intention to vaccinate their daughters against the human papilloma virus infection. Questionnaires were distributed among convenience sample of 103 mothers of daughters 18 years and younger. Approximately 65% of mothers intend to vaccinate their daughters. Behavioral beliefs, normative beliefs, and level of knowledge had a significant positive effect on mothers' intention to vaccinate their daughters. High levels of religiosity were found to negatively affect mothers' intention to vaccinate their daughters. The TRA combined with level of knowledge and level of religiosity succeeds in predicting mothers' behavioral intentions regarding vaccinating daughters. This indicates the significance of nurses' roles in imparting information and increasing awareness among mothers. Copyright © 2011. Published by Elsevier Inc.

Competence with Fractions Predicts Gains in Mathematics Achievement

PubMed Central

Bailey, Drew H.; Hoard, Mary K.; Nugent, Lara; Geary, David C.

2012-01-01

Competence with fractions predicts later mathematics achievement, but the co-developmental pattern between fractions knowledge and mathematics achievement is not well understood. We assessed this co-development through examination of the cross-lagged relation between a measure of conceptual knowledge of fractions and mathematics achievement in sixth and seventh grade (n = 212). The cross-lagged effects indicated that performance on the sixth grade fractions concepts measure predicted one year gains in mathematics achievement (β = .14, p<.01), controlling for the central executive component of working memory and intelligence, but sixth grade mathematics achievement did not predict gains on the fractions concepts measure (β = .03, p>.50). In a follow-up assessment, we demonstrated that measures of fluency with computational fractions significantly predicted seventh grade mathematics achievement above and beyond the influence of fluency in computational whole number arithmetic, performance on number fluency and number line tasks, and central executive span and intelligence. Results provide empirical support for the hypothesis that competence with fractions underlies, in part, subsequent gains in mathematics achievement. PMID:22832199

Effects of entertainment (mis) education: exposure to entertainment television programs and organ donation intention.

PubMed

Yoo, Jina H; Tian, Yan

2011-03-01

This study investigates antecedents and outcomes of entertainment television consumption in organ donation with the Orientation₁-Stimulus-Orientation₂-Response (O₁-S-O₂ -R) model. It reveals that organ donation knowledge seems significantly related to recall of entertainment television programs and attitudes toward organ donation. Meanwhile, recall of entertainment television programs significantly predicts people's perception of medical mistrust, which in turn negatively predicts attitudes toward organ donation, while attitudes toward organ donation significantly predict behavioral intention in signing a donor card. It also suggests significant mediation relationships among the pre-orientation variable, stimulus, post-orientation variable, and attitudinal and behavioral outcomes. This study provides an integrative theoretical framework to study media effects on organ donation and empirical evidence for "entertainment miseducation" (Morgan, Harrison, Chewning, Davis, & DiCorcia, 2007).

Knowledge: a possible tool in shaping medical professionals' attitudes towards homosexuality.

PubMed

Dunjić-Kostić, Bojana; Pantović, Maja; Vuković, Vuk; Randjelović, Dunja; Totić-Poznanović, Sanja; Damjanović, Aleksandar; Jašović-Gašić, Miroslava; Ivković, Maja

2012-06-01

The attitudes of medical professionals towards homosexuals can influence their willingness to provide these individuals with medical help. The study evaluated the medical professionals' knowledge about homosexuality and their attitudes towards it. The sample consisted of 177 participants (physicians n=79 and students n=98). The study respondents anonymously completed three questionnaires (socio-demographic questionnaire, the questionnaire on knowledge, and the questionnaire on attitudes towards homosexuals). Male and religious participants showed a lower level of knowledge and a greater tendency to stigmatize. Furthermore, the subjects who knew more about homosexuality tended to hold less stigmatizing attitude. Age group, specialty (psychiatry, gynecology, internal medicine and surgery), and student's/physician's status had no effect on stigmatization. The study showed that the final year students/ residents had more knowledge than the second year students/specialists did. Knowledge had significant negative predictive effect on attitudes in the analyzed predictive model. To our knowledge, this has been the first study in Serbia and Eastern Europe, which provides information on knowledge and attitudes of health professionals towards homosexuality. We would like to point out the degree of knowledge on homosexuality as a possible, but not exclusive tool in shaping the attitudes towards homosexuals and reducing stigmatization. However, regardless of the personal attitude, knowledge and variable acceptance of the homosexuals' rights, medical professionals' main task is to resist discriminative behavior and provide professional medical help to both homosexual and heterosexual patients.

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

ERIC Educational Resources Information Center

Jensen, Jennifer

2014-01-01

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

Computational approaches to predict bacteriophage–host relationships

PubMed Central

Edwards, Robert A.; McNair, Katelyn; Faust, Karoline; Raes, Jeroen; Dutilh, Bas E.

2015-01-01

Metagenomics has changed the face of virus discovery by enabling the accurate identification of viral genome sequences without requiring isolation of the viruses. As a result, metagenomic virus discovery leaves the first and most fundamental question about any novel virus unanswered: What host does the virus infect? The diversity of the global virosphere and the volumes of data obtained in metagenomic sequencing projects demand computational tools for virus–host prediction. We focus on bacteriophages (phages, viruses that infect bacteria), the most abundant and diverse group of viruses found in environmental metagenomes. By analyzing 820 phages with annotated hosts, we review and assess the predictive power of in silico phage–host signals. Sequence homology approaches are the most effective at identifying known phage–host pairs. Compositional and abundance-based methods contain significant signal for phage–host classification, providing opportunities for analyzing the unknowns in viral metagenomes. Together, these computational approaches further our knowledge of the interactions between phages and their hosts. Importantly, we find that all reviewed signals significantly link phages to their hosts, illustrating how current knowledge and insights about the interaction mechanisms and ecology of coevolving phages and bacteria can be exploited to predict phage–host relationships, with potential relevance for medical and industrial applications. PMID:26657537

Sleep Spindle Density Predicts the Effect of Prior Knowledge on Memory Consolidation

PubMed Central

Lambon Ralph, Matthew A.; Kempkes, Marleen; Cousins, James N.; Lewis, Penelope A.

2016-01-01

Information that relates to a prior knowledge schema is remembered better and consolidates more rapidly than information that does not. Another factor that influences memory consolidation is sleep and growing evidence suggests that sleep-related processing is important for integration with existing knowledge. Here, we perform an examination of how sleep-related mechanisms interact with schema-dependent memory advantage. Participants first established a schema over 2 weeks. Next, they encoded new facts, which were either related to the schema or completely unrelated. After a 24 h retention interval, including a night of sleep, which we monitored with polysomnography, participants encoded a second set of facts. Finally, memory for all facts was tested in a functional magnetic resonance imaging scanner. Behaviorally, sleep spindle density predicted an increase of the schema benefit to memory across the retention interval. Higher spindle densities were associated with reduced decay of schema-related memories. Functionally, spindle density predicted increased disengagement of the hippocampus across 24 h for schema-related memories only. Together, these results suggest that sleep spindle activity is associated with the effect of prior knowledge on memory consolidation. SIGNIFICANCE STATEMENT Episodic memories are gradually assimilated into long-term memory and this process is strongly influenced by sleep. The consolidation of new information is also influenced by its relationship to existing knowledge structures, or schemas, but the role of sleep in such schema-related consolidation is unknown. We show that sleep spindle density predicts the extent to which schemas influence the consolidation of related facts. This is the first evidence that sleep is associated with the interaction between prior knowledge and long-term memory formation. PMID:27030764

Predictors and Effects of Knowledge Management in U.S. Colleges and Schools of Pharmacy

NASA Astrophysics Data System (ADS)

Watcharadamrongkun, Suntaree

Public demands for accountability in higher education have placed increasing pressure on institutions to document their achievement of critical outcomes. These demands also have had wide-reaching implications for the development and enforcement of accreditation standards, including those governing pharmacy education. The knowledge management (KM) framework provides perspective for understanding how organizations evaluate themselves and guidance for how to improve their performance. In this study, we explore knowledge management processes, how these processes are affected by organizational structure and by information technology resources, and how these processes affect organizational performance. This is done in the context of Accreditation Standards and Guidelines for the Professional Program in Pharmacy Leading to the Doctor of Pharmacy Degree (Standards 2007). Data were collected using an online census survey of 121 U.S. Colleges and Schools of Pharmacy and supplemented with archival data. A key informant method was used with CEO Deans and Assessment leaders serving as respondents. The survey yielded a 76.0% (92/121) response rate. Exploratory factor analysis was used to construct scales (and scales) describing core KM processes: Knowledge Acquisition, Knowledge Integration, and Institutionalization; all scale reliabilities were found to be acceptable. Analysis showed that, as expected, greater Knowledge Acquisition predicts greater Knowledge Integration and greater Knowledge Integration predicts greater Institutionalization. Predictive models were constructed using hierarchical multiple regression and path analysis. Overall, information technology resources had stronger effects on KM processes than did characteristics of organizational structure. Greater Institutionalization predicted better outcomes related to direct measures of performance (i.e., NAPLEX pass rates, Accreditation actions) but Institutionalization was unrelated to an indirect measure of performance (i.e., USNWR ratings). Several organizational structure characteristics (i.e., size, age, and being part of an academic health center) were significant predictors of organizational performance; in contrast, IT resources had no direct effects on performance. Findings suggest that knowledge management processes, organizational structures and IT resources are related to better performance for Colleges and Schools of Pharmacy. Further research is needed to understand mechanisms through which specific knowledge management processes translate into better performance and, relatedly, to establish how enhancing KM processes can be used to improve institutional quality.

Has the UK Clinical Aptitude Test improved medical student selection?

PubMed

Wright, Sarah R; Bradley, Philip M

2010-11-01

In 2006, the United Kingdom Clinical Aptitude Test (UKCAT) was introduced as a new medical school admissions tool. The aim of this cohort study was to determine whether the UKCAT has made any improvements to the way medical students are selected. Regression analysis was performed in order to study the ability of previous school type and gender to predict UKCAT, personal statement or interview scores in two cohorts of accepted students. The ability of admissions scores and demographic data to predict performance on knowledge and skills examinations was also studied. Previous school type was not a significant predictor of either interview or UKCAT scores amongst students who had been accepted onto the programme (n = 307). However, it was a significant predictor of personal statement score, with students from independent and grammar schools performing better than students from state-maintained schools. Previous school type, personal statements and interviews were not significant predictors of knowledge examination performance. UKCAT scores were significant predictors of knowledge examination performance for all but one examination administered in the first 2 years of medical school. Admissions data explained very little about performance on skills (objective structured clinical examinations [OSCEs]) assessments. The use of personal statements as a basis for selection results in a bias towards students from independent and grammar schools. However, no evidence was found to suggest that students accepted from these schools perform any better than students from maintained schools on Year 1 and 2 medical school examinations. Previous school type did not predict interview or UKCAT scores of accepted students. UKCAT scores are predictive of Year 1 and 2 examination performance at this medical school, whereas interview scores are not. The results of this study challenge claims made by other authors that aptitude tests do not have a place in medical school selection in the UK. © Blackwell Publishing Ltd 2010.

The effects of heuristic cues, motivation, and ability on systematic processing of information about breast cancer environmental factors.

PubMed

Smith, Sandi W; Hitt, Rose; Nazione, Samantha; Russell, Jessica; Silk, Kami; Atkin, Charles K

2013-01-01

The heuristic systematic model is used to investigate how ability, motivation, and heuristic message cues predict knowledge scores for individuals receiving messages written for different literacy levels about 3 environmental risk factors for breast cancer. The 3 risk factors were the roles of genetics, progesterone, and ingesting perfluorooctanoic acid in breast cancer risk. In this study, more than 4,000 women participated in an online survey. The results showed support for the hypotheses that ability (measured as education, number of science courses, and confidence in scientific ability) predict knowledge gain and that those individuals who presented with the lower literacy level message had significantly higher knowledge scores across all 3 message topics. There was little support for motivation or heuristic cues as direct predictors of knowledge gain across the 3 message topics, although they served as moderators for the perfluorooctanoic acid topic. The authors provide implications for health communication practitioners.

Correlates of HIV knowledge and Sexual risk behaviors among Female Military Personnel

PubMed Central

Essien, E. James; Monjok, Emmanuel; Chen, Hua; Abughosh, Susan; Ekong, Ernest; Peters, Ronald J.; Holmes, Laurens; Holstad, Marcia M.; Mgbere, Osaro

2010-01-01

Objective Uniformed services personnel are at an increased risk of HIV infection. We examined the HIV/AIDS knowledge and sexual risk behaviors among female military personnel to determine the correlates of HIV risk behaviors in this population. Method The study used a cross-sectional design to examine HIV/AIDS knowledge and sexual risk behaviors in a sample of 346 females drawn from two military cantonments in Southwestern Nigeria. Data was collected between 2006 and 2008. Using bivariate analysis and multivariate logistic regression, HIV/AIDS knowledge and sexual behaviors were described in relation to socio-demographic characteristics of the participants. Results Multivariate logistic regression analysis revealed that level of education and knowing someone with HIV/AIDS were significant (p<0.05) predictors of HIV knowledge in this sample. HIV prevention self-efficacy was significantly (P<0.05) predicted by annual income and race/ethnicity. Condom use attitudes were also significantly (P<0.05) associated with number of children, annual income, and number of sexual partners. Conclusion Data indicates the importance of incorporating these predictor variables into intervention designs. PMID:20387111

Development of Emergent Literacy and Early Reading Skills in Preschool Children: Evidence from a Latent-Variable Longitudinal Study.

ERIC Educational Resources Information Center

Lonigan, Christopher J.; Burgess, Stephen R.; Anthony, Jason L.

2000-01-01

Examined the joint and unique predictive significance of emergent literacy skills for later emergent literacy skills and reading in two samples of preschoolers. Structural equation modeling revealed significant developmental continuity of these skills, particularly for letter knowledge and phonological sensitivity from late preschool to early…

Development and validation of two influenza assessments: Exploring the impact of knowledge and social environment on health behaviors

NASA Astrophysics Data System (ADS)

Romine, William

Assessments of knowledge and perceptions about influenza were developed for high school students, and used to determine how knowledge, perceptions, and demographic variables relate to students taking precautions and their odds of getting sick. Assessments were piloted with 205 students and validated using the Rasch model. Data were then collected on 410 students from six high schools. Scores were calculated using the 2-parameter logistic model and clustered using the k-means algorithm. Kendall-tau correlations were evaluated at the alpha = 0.05 level, multinomial logistic regression was used to identify the best predictors and to test for interactions, and neural networks were used to test how well precautions and illness can be predicted using the significant correlates. Precautions and illness had more than one statistically significant correlate with small to moderate effect sizes. Knowledge was positively correlated to compliance with vaccination, hand washing frequency, and respiratory etiquette, and negatively correlated with hand sanitizer use. Perceived risk was positively correlated to compliance with flu vaccination; perceived complications to personal distancing and staying home when sick. Perceived risk and complications increased with reported illness severity. Perceived barriers decreased compliance with vaccination, hand washing, and respiratory etiquette. Factors such as gender, ethnicity, and school, had effects on more than one precaution. Hand washing quality and frequency could be predicted moderately well. Other predictions had small-to-negligible associations with actual values. Implications for future uses of the instruments and development of interventions regarding influenza in high schools are discussed.

Motor knowledge is one dimension for concept organization: further evidence from a Chinese semantic dementia case.

PubMed

Lin, Nan; Guo, Qihao; Han, Zaizhu; Bi, Yanchao

2011-11-01

Neuropsychological and neuroimaging studies have indicated that motor knowledge is one potential dimension along which concepts are organized. Here we present further direct evidence for the effects of motor knowledge in accounting for categorical patterns across object domains (living vs. nonliving) and grammatical domains (nouns vs. verbs), as well as the integrity of other modality-specific knowledge (e.g., visual). We present a Chinese case, XRK, who suffered from semantic dementia with left temporal lobe atrophy. In naming and comprehension tasks, he performed better at nonliving items than at living items, and better at verbs than at nouns. Critically, multiple regression method revealed that these two categorical effects could be both accounted for by the charade rating, a continuous measurement of the significance of motor knowledge for a concept or a semantic feature. Furthermore, charade rating also predicted his performances on the generation frequency of semantic features of various modalities. These findings consolidate the significance of motor knowledge in conceptual organization and further highlights the interactions between different types of semantic knowledge. Copyright © 2010 Elsevier Inc. All rights reserved.

Covariates of Tooth-brushing Frequency in Low-income African Americans From Grades 5 to 8

PubMed Central

Koerber, A.; Graumlich, S.; Punwani, I.C.; Berbaum, M.L.; Burns, J.L.; Levy, S.R.; Cowell, J.M.; Flay, B.R.

2009-01-01

Purpose The purpose of this study was to examine tooth-brushing frequency in 575 urban and nearby suburban African American children as part of a comprehensive risk-reduction study for students at high risk for violence, drugs, school delinquency, and unsafe sexual behaviors to determine which covariates predicted tooth-brushing frequency. Methods Students were surveyed 5 times, from the beginning of grade 5 and the end of each year through grade 8, and parents were surveyed at the beginning of grade 5. Peer influence, importance of being liked, self-esteem, attitudes towards tooth-brushing, oral health knowledge, self-efficacy, parental attitudes, and other covariates were examined for the ability to predict self-reporting of tooth-brushing frequency. Results In the fifth grade, peer influence, the importance of being liked, and physical self-esteem were the significant predictors, and peer influence continued to predict tooth-brushing in the eighth grade. Oral health knowledge and parental influence were not significant. Conclusion Peer influence is an important factor in tooth-brushing behavior in metropolitan African American preadolescent children. PMID:17249434

Covariates of tooth-brushing frequency in low-income African Americans from grades 5 to 8.

PubMed

Koerber, A; Graumlich, S; Punwani, I C; Berbaum, M L; Burns, J L; Levy, S R; Cowell, J M; Flay, B R

2006-01-01

The purpose of this study was to examine tooth-brushing frequency in 575 urban and nearby suburban African American children as part of a comprehensive risk-reduction study for students at high risk for violence, drugs, school delinquency, and unsafe sexual behaviors to determine which covariates predicted tooth-brushing frequency. Students were surveyed 5 times, from the beginning of grade 5 and the end of each year through grade 8, and parents were surveyed at the beginning of grade 5. Peer influence, importance of being liked, self-esteem, attitudes towards tooth-brushing, oral health knowledge, self-efficacy, parental attitudes, and other covariates were examined for the ability to predict self-reporting of tooth-brushing frequency. In the fifth grade, peer influence, the importance of being liked, and physical self-esteem were the significant predictors, and peer influence continued to predict tooth-brushing in the eighth grade. Oral health knowledge and parental influence were not significant. Peer influence is an important factor in tooth-brushing behavior in metropolitan African American preadolescent children.

How neglect and punitiveness influence emotion knowledge.

PubMed

Sullivan, Margaret Wolan; Carmody, Dennis P; Lewis, Michael

2010-06-01

To explore whether punitive parenting styles contribute to early-acquired emotion knowledge deficits observable in neglected children, we observed 42 preschool children's emotion knowledge, expression recognition time, and IQ. The children's mothers completed the Parent-Child Conflict Tactics Scales to assess the recent use of three types of discipline strategies (nonviolent, physically punitive, and psychological aggression), as well as neglectful parenting. Fifteen of the children were identified as neglected by Child Protective Services (CPS) reports; 27 children had no record of CPS involvement and served as the comparison group. There were no differences between the neglect and comparison groups in the demographic factors of gender, age, home language, minority status, or public assistance, nor on IQ. Hierarchical multiple regression modeling showed that neglect significantly predicted emotion knowledge. The addition of IQ contributed a significant amount of additional variance to the model and maintained the fit. Adding parental punitiveness in the final stage contributed little additional variance and did not significantly improve the fit. Thus, deficits in children's emotion knowledge may be due primarily to lower IQ or neglect. IQ was unrelated to speed of emotion recognition. Punitiveness did not directly contribute to emotion knowledge deficits but appeared in exploratory analysis to be related to speed of emotion recognition.

Morphological Awareness in Literacy Acquisition of Chinese Second Graders: A Path Analysis.

PubMed

Zhang, Haomin

2016-02-01

The present study tested a path diagram regarding the contribution of morphological awareness (MA) to early literacy acquisition among Chinese-speaking second graders ([Formula: see text]). Three facets of MA were addressed, namely derivational awareness, compound awareness and compound structure awareness. The model aimed to test a theory of causal order among measures of MA and literacy outcomes. Drawing upon multivariate path analysis, direct and indirect effects of MA were analyzed to identify their role in literacy performance among young children. Results revealed that all three facets of MA made significant contributions to lexical inference ability. In addition, compound awareness showed a unique and significant contribution to vocabulary knowledge. It was also observed that lexical inference ability had a mediating effect predictive of both vocabulary knowledge and reading comprehension. Moreover, vocabulary knowledge mediated the effect of MA on reading comprehension. However, no significant contribution of MA to reading comprehension was found after controlling for lexical inference ability and vocabulary knowledge.

Granularity refined by knowledge: contingency tables and rough sets as tools of discovery

NASA Astrophysics Data System (ADS)

Zytkow, Jan M.

2000-04-01

Contingency tables represent data in a granular way and are a well-established tool for inductive generalization of knowledge from data. We show that the basic concepts of rough sets, such as concept approximation, indiscernibility, and reduct can be expressed in the language of contingency tables. We further demonstrate the relevance to rough sets theory of additional probabilistic information available in contingency tables and in particular of statistical tests of significance and predictive strength applied to contingency tables. Tests of both type can help the evaluation mechanisms used in inductive generalization based on rough sets. Granularity of attributes can be improved in feedback with knowledge discovered in data. We demonstrate how 49er's facilities for (1) contingency table refinement, for (2) column and row grouping based on correspondence analysis, and (3) the search for equivalence relations between attributes improve both granularization of attributes and the quality of knowledge. Finally we demonstrate the limitations of knowledge viewed as concept approximation, which is the focus of rough sets. Transcending that focus and reorienting towards the predictive knowledge and towards the related distinction between possible and impossible (or statistically improbable) situations will be very useful in expanding the rough sets approach to more expressive forms of knowledge.

Relationship among knowledge acquisition, motivation to change, and self-efficacy in CME participants.

PubMed

Williams, Betsy W; Kessler, Harold A; Williams, Michael V

2015-01-01

The relationship among an individual's sense of self-efficacy, motivation to change, barriers to change, and the implementation of improvement programs has been reported. This research reports the relationship among self-efficacy, motivation to change, and the acquisition of knowledge in a continuing medical education (CME) activity. The measure of individual sense of self-efficacy was a 4-item scale. The measure of motivation was a 6-item scale following on the work of Prochaska and colleagues. The knowledge acquisition was measured in a simple post measure. The participants were enrolled in a CME activity focused on HIV.  The CME activities had a significant effect on knowledge. Preliminary analysis demonstrates a relationship among the self-efficacy measure, the motivation to change measure, and global intent to change. Specifically, as reported earlier, the sense of efficacy in effecting change in the practice environment is predictive of a high level of motivation to change that, in turn, is predictive of formation of intent to change practice patterns. Interestingly, there were also relationships among the self-efficacy measure, the motivation to change measure, and knowledge acquisition. Finally, as expected, there was a significant relationship between knowledge and intent to change practice.  Further inspection of the motivation to change construct suggests that it mediates the self-efficacy constructs' effect on intent as well as its effect on knowledge acquisition. This new finding suggests that the proximal construct motivation completely masks an important underlying causal relationship that appears to contribute to practice change as well as learning following CME-self-efficacy. © 2015 The Alliance for Continuing Education in the Health Professions, the Society for Academic Continuing Medical Education, and the Council on Continuing Medical Education, Association for Hospital Medical Education.

Looking on the bright side: children's knowledge about the benefits of positive versus negative thinking.

PubMed

Bamford, Christi; Lagattuta, Kristin Hansen

2012-01-01

Five- to 10-year-olds (N = 90) listened to 6 illustrated scenarios featuring 2 characters that jointly experience the same positive event (and feel good), negative event (and feel bad), or ambiguous event (and feel okay). Afterward, one character thinks a positive thought and the other thinks a negative thought. Children predicted and explained each character's emotions. Results showed significant development between 5 and 10 years in children's understanding that thinking positively improves emotions and thinking negatively makes one feel worse, with earliest knowledge demonstrated when reasoning about ambiguous and positive events. Individual differences in child and parental optimism and hope predicted children's knowledge about thought-emotion connections on some measures, including their beliefs about the emotional benefits of thinking positively in negative situations. © 2011 The Authors. Child Development © 2011 Society for Research in Child Development, Inc.

Hazard perception, risk perception, and the need for decontamination by residents exposed to soil pollution: the role of sustainability and the limits of expert knowledge.

PubMed

Vandermoere, Frédéric

2008-04-01

This case study examines the hazard and risk perception and the need for decontamination according to people exposed to soil pollution. Using an ecological-symbolic approach (ESA), a multidisciplinary model is developed that draws upon psychological and sociological perspectives on risk perception and includes ecological variables by using data from experts' risk assessments. The results show that hazard perception is best predicted by objective knowledge, subjective knowledge, estimated knowledge of experts, and the assessed risks. However, experts' risk assessments induce an increase in hazard perception only when residents know the urgency of decontamination. Risk perception is best predicted by trust in the risk management. Additionally, need for decontamination relates to hazard perception, risk perception, estimated knowledge of experts, and thoughts about sustainability. In contrast to the knowledge deficit model, objective and subjective knowledge did not significantly relate to risk perception and need for decontamination. The results suggest that residents can make a distinction between hazards in terms of the seriousness of contamination on the one hand, and human health risks on the other hand. Moreover, next to the importance of social determinants of environmental risk perception, this study shows that the output of experts' risk assessments-or the objective risks-can create a hazard awareness rather than an alarming risk consciousness, despite residents' distrust of scientific knowledge.

A Framework for Analyzing Biometric Template Aging and Renewal Prediction

DTIC Science & Technology

2009-03-01

databases has sufficient data to support template aging over an extended period of time. Another assumption is that there is significant variance to...mentioned above for enrollment also apply to verification. When combining enrollment and verification, there is a significant amount of variance that... significant advancement in the biometrics body of knowledge. This research presents the CTARP Framework, a novel foundational framework for methods of

Which Preschool Mathematics Competencies Are Most Predictive of Fifth Grade Achievement?

PubMed Central

Nguyen, Tutrang; Watts, Tyler W.; Duncan, Greg J.; Clements, Douglas H.; Sarama, Julie S.; Wolfe, Christopher; Spitler, Mary Elaine

2016-01-01

In an effort to promote best practices regarding mathematics teaching and learning at the preschool level, national advisory panels and organizations have emphasized the importance of children’s emergent counting and related competencies, such as the ability to verbally count, maintain one-to-one correspondence, count with cardinality, subitize, and count forward or backward from a given number. However, little research has investigated whether the kind of mathematical knowledge promoted by the various standards documents actually predict later mathematics achievement. The present study uses longitudinal data from a primarily low-income and minority sample of children to examine the extent to which preschool mathematical competencies, specifically basic and advanced counting, predict fifth grade mathematics achievement. Using regression analyses, we find early numeracy abilities to be the strongest predictors of later mathematics achievement, with advanced counting competencies more predictive than basic counting competencies. Our results highlight the significance of preschool mathematics knowledge for future academic achievement. PMID:27057084

Climate change 'understanding' and knowledge

NASA Astrophysics Data System (ADS)

Hamilton, L.

2011-12-01

Recent surveys find that many people report having "a great deal" of understanding about climate change. Self-assessed understanding does not predict opinions, however, because those with highest "understanding" tend also to be most polarized. These findings raise questions about the relationship between "understanding" and objectively-measured knowledge. In summer 2011 we included three new questions testing climate-change knowledge on a statewide survey. The multiple-choice questions address basic facts that are widely accepted by contrarian as well as mainstream scientists. They ask about trends in Arctic sea ice, in CO2 concentrations, and the meaning of "greenhouse effect." The questions say nothing about impacts, attribution or mitigation. Each has a clear and well-publicized answer that does not presume acceptance of anthropogenic change. About 30% of respondents knew all three answers, and 36% got two out of three. 34% got zero or one right. Notably, these included 31% of those who claimed to have "a great deal" of understanding. Unlike self-assessed understanding, knowledge scores do predict opinions. People who knew more were significantly more likely to agree that climate change is happening now, caused mainly by human activities. This positive relationship remains significant controlling for gender, age, education, partisanship and "understanding." It does not exhibit the interaction effects with partisanship that characterize self-assessed understanding. Following the successful statewide test, the same items were added to a nationwide survey currently underway. Analyses replicated across both surveys cast a new light on the problematic connections between "understanding," knowledge and opinions about climate science.

Competence with fractions predicts gains in mathematics achievement.

PubMed

Bailey, Drew H; Hoard, Mary K; Nugent, Lara; Geary, David C

2012-11-01

Competence with fractions predicts later mathematics achievement, but the codevelopmental pattern between fractions knowledge and mathematics achievement is not well understood. We assessed this codevelopment through examination of the cross-lagged relation between a measure of conceptual knowledge of fractions and mathematics achievement in sixth and seventh grades (N=212). The cross-lagged effects indicated that performance on the sixth grade fractions concepts measure predicted 1-year gains in mathematics achievement (ß=.14, p<.01), controlling for the central executive component of working memory and intelligence, but sixth grade mathematics achievement did not predict gains on the fractions concepts measure (ß=.03, p>.50). In a follow-up assessment, we demonstrated that measures of fluency with computational fractions significantly predicted seventh grade mathematics achievement above and beyond the influence of fluency in computational whole number arithmetic, performance on number fluency and number line tasks, central executive span, and intelligence. Results provide empirical support for the hypothesis that competence with fractions underlies, in part, subsequent gains in mathematics achievement. Copyright © 2012 Elsevier Inc. All rights reserved.

Student Success: An Investigation of the Role of the Pre-Admission Variables of Academic Preparation, Personal Attributes, and Demographic Characteristics Contribute in Predicting Graduation

ERIC Educational Resources Information Center

Briggs, Lianne

2012-01-01

Despite retention being a significant focus of higher education research, graduation rates remain of concern. Increased numbers of students are advancing to college bringing with them a wider range of abilities, attributes, and characteristics. There is much we know about what predicts success for these students but our knowledge is far from…

SOCIO-ECOLOGICAL PREDICTORS OF INTERCOURSE FREQUENCY AND NUMBER OF SEXUAL PARTNERS AMONG MALE AND FEMALE AFRICAN AMERICAN ADOLESCENTS

PubMed Central

Ritchwood, Tiarney D.; Traylor, Amy C.; Howell, Rebecca J.; Church, Wesley T.; Bolland, John M.

2015-01-01

The current study examined 14 waves of data derived from a large, community-based study of the sexual behavior of impoverished youth between 12 and 17 years of age residing in the Deep South. We used multilevel linear modeling to identify ecological predictors of intercourse frequency and number of sexual partners among gender-specific subsamples. Results indicated that predictors of adolescent sexual behavior differed by both type of sexual behavior and gender. For males, age, maternal warmth, parental knowledge, curfew, self-worth, and sense of community predicted intercourse frequency, while age, parental knowledge, curfew, self-worth, friend support, and sense of community were significantly associated with having multiple sexual partners. Among females, age, curfew, and self-worth exerted significant effects on intercourse frequency, while age, parental knowledge, curfew, and self-worth exerted significant effects on having multiple sexual partners. Implications and future directions are discussed. PMID:26401060

SOCIO-ECOLOGICAL PREDICTORS OF INTERCOURSE FREQUENCY AND NUMBER OF SEXUAL PARTNERS AMONG MALE AND FEMALE AFRICAN AMERICAN ADOLESCENTS.

PubMed

Ritchwood, Tiarney D; Traylor, Amy C; Howell, Rebecca J; Church, Wesley T; Bolland, John M

2014-09-01

The current study examined 14 waves of data derived from a large, community-based study of the sexual behavior of impoverished youth between 12 and 17 years of age residing in the Deep South. We used multilevel linear modeling to identify ecological predictors of intercourse frequency and number of sexual partners among gender-specific subsamples. Results indicated that predictors of adolescent sexual behavior differed by both type of sexual behavior and gender. For males, age, maternal warmth, parental knowledge, curfew, self-worth, and sense of community predicted intercourse frequency, while age, parental knowledge, curfew, self-worth, friend support, and sense of community were significantly associated with having multiple sexual partners. Among females, age, curfew, and self-worth exerted significant effects on intercourse frequency, while age, parental knowledge, curfew, and self-worth exerted significant effects on having multiple sexual partners. Implications and future directions are discussed.

Clinical implementation of a knowledge based planning tool for prostate VMAT.

PubMed

Powis, Richard; Bird, Andrew; Brennan, Matthew; Hinks, Susan; Newman, Hannah; Reed, Katie; Sage, John; Webster, Gareth

2017-05-08

A knowledge based planning tool has been developed and implemented for prostate VMAT radiotherapy plans providing a target average rectum dose value based on previously achievable values for similar rectum/PTV overlap. The purpose of this planning tool is to highlight sub-optimal clinical plans and to improve plan quality and consistency. A historical cohort of 97 VMAT prostate plans was interrogated using a RayStation script and used to develop a local model for predicting optimum average rectum dose based on individual anatomy. A preliminary validation study was performed whereby historical plans identified as "optimal" and "sub-optimal" by the local model were replanned in a blinded study by four experienced planners and compared to the original clinical plan to assess whether any improvement in rectum dose was observed. The predictive model was then incorporated into a RayStation script and used as part of the clinical planning process. Planners were asked to use the script during planning to provide a patient specific prediction for optimum average rectum dose and to optimise the plan accordingly. Plans identified as "sub-optimal" in the validation study observed a statistically significant improvement in average rectum dose compared to the clinical plan when replanned whereas plans that were identified as "optimal" observed no improvement when replanned. This provided confidence that the local model can identify plans that were suboptimal in terms of rectal sparing. Clinical implementation of the knowledge based planning tool reduced the population-averaged mean rectum dose by 5.6Gy. There was a small but statistically significant increase in total MU and femoral head dose and a reduction in conformity index. These did not affect the clinical acceptability of the plans and no significant changes to other plan quality metrics were observed. The knowledge-based planning tool has enabled substantial reductions in population-averaged mean rectum dose for prostate VMAT patients. This suggests plans are improved when planners receive quantitative feedback on plan quality against historical data.

Cardiovascular risk-factor knowledge and risk perception among HIV-infected adults.

PubMed

Cioe, Patricia A; Crawford, Sybil L; Stein, Michael D

2014-01-01

Cardiovascular disease (CVD) has emerged as a major cause of morbidity and mortality in HIV-infected adults. Research in noninfected populations has suggested that knowledge of CVD risk factors significantly influences perceptions of risk. This cross-sectional study describes CVD risk factor knowledge and risk perception in HIV-infected adults. We recruited 130 HIV-infected adults (mean age = 48 years, 62% male, 56% current smokers, mean years since HIV diagnosis, 14.7). The mean CVD risk factor knowledge score was fairly high. However, controlling for age, CVD risk factor knowledge was not predictive of perceived risk [F(1, 117) = 0.13, p > .05]. Estimated risk and perceived risk were weakly but significantly correlated; r (126) = .24, p = .01. HIV-infected adults are at increased risk for CVD. Despite having adequate risk-factor knowledge, CVD risk perception was inaccurate. Improving risk perception and developing CVD risk reduction interventions for this population are imperative. Copyright © 2014 Association of Nurses in AIDS Care. Published by Elsevier Inc. All rights reserved.

An automated decision-tree approach to predicting protein interaction hot spots.

PubMed

Darnell, Steven J; Page, David; Mitchell, Julie C

2007-09-01

Protein-protein interactions can be altered by mutating one or more "hot spots," the subset of residues that account for most of the interface's binding free energy. The identification of hot spots requires a significant experimental effort, highlighting the practical value of hot spot predictions. We present two knowledge-based models that improve the ability to predict hot spots: K-FADE uses shape specificity features calculated by the Fast Atomic Density Evaluation (FADE) program, and K-CON uses biochemical contact features. The combined K-FADE/CON (KFC) model displays better overall predictive accuracy than computational alanine scanning (Robetta-Ala). In addition, because these methods predict different subsets of known hot spots, a large and significant increase in accuracy is achieved by combining KFC and Robetta-Ala. The KFC analysis is applied to the calmodulin (CaM)/smooth muscle myosin light chain kinase (smMLCK) interface, and to the bone morphogenetic protein-2 (BMP-2)/BMP receptor-type I (BMPR-IA) interface. The results indicate a strong correlation between KFC hot spot predictions and mutations that significantly reduce the binding affinity of the interface. 2007 Wiley-Liss, Inc.

World Knowledge and Global Citizenship: Factual and Perceived World Knowledge as Predictors of Global Citizenship Identification

ERIC Educational Resources Information Center

Reysen, Stephen; Katzarska-Miller, Iva; Gibson, Shonda A.; Hobson, Braken

2013-01-01

We examine the influence of factual and perceived world knowledge on global citizenship identification. Perceived world knowledge directly predicted global citizenship identification, while factual world knowledge did not (Study 1). Students' factual (Study 1) and perceived (Study 2) world knowledge predicted students' normative environment…

The relationship between performance on the Infectious Diseases In-Training and Certification Examinations.

PubMed

Grabovsky, Irina; Hess, Brian J; Haist, Steven A; Lipner, Rebecca S; Hawley, Janine L; Woodward, Stephanie; Engleberg, N Cary

2015-03-01

The Infectious Diseases Society of America In-Training Examination (IDSA ITE) is a feedback tool used to help fellows track their knowledge acquisition during fellowship training. We determined whether the scores on the IDSA ITE and from other major medical knowledge assessments predict performance on the American Board of Internal Medicine (ABIM) Infectious Disease Certification Examination. The sample was 1021 second-year fellows who took the IDSA ITE and ABIM Infectious Disease Certification Examination from 2008 to 2012. Multiple regression analysis was used to determine if ABIM Infectious Disease Certification Examination scores were predicted by IDSA ITE scores, prior United States Medical Licensing Examination (USMLE) scores, ABIM Internal Medicine Certification Examination scores, fellowship director ratings of medical knowledge, and demographic variables. Logistic regression was used to evaluate if these same assessments predicted a passing outcome on the certification examination. IDSA ITE scores were the strongest predictor of ABIM Infectious Disease Certification Examination scores (β = .319), followed by prior ABIM Internal Medicine Certification Examination scores (β = .258), USMLE Step 1 scores (β = .202), USMLE Step 3 scores (β = .130), and fellowship directors' medical knowledge ratings (β = .063). IDSA ITE scores were also a significant predictor of passing the Infectious Disease Certification Examination (odds ratio, 1.017 [95% confidence interval, 1.013-1.021]). The significant relationship between the IDSA ITE score and performance on the ABIM Infectious Disease Certification Examination supports the use of the ITE as a valid feedback tool in fellowship training. © The Author 2014. Published by Oxford University Press on behalf of the Infectious Diseases Society of America. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Predicting links based on knowledge dissemination in complex network

NASA Astrophysics Data System (ADS)

Zhou, Wen; Jia, Yifan

2017-04-01

Link prediction is the task of mining the missing links in networks or predicting the next vertex pair to be connected by a link. A lot of link prediction methods were inspired by evolutionary processes of networks. In this paper, a new mechanism for the formation of complex networks called knowledge dissemination (KD) is proposed with the assumption of knowledge disseminating through the paths of a network. Accordingly, a new link prediction method-knowledge dissemination based link prediction (KDLP)-is proposed to test KD. KDLP characterizes vertex similarity based on knowledge quantity (KQ) which measures the importance of a vertex through H-index. Extensive numerical simulations on six real-world networks demonstrate that KDLP is a strong link prediction method which performs at a higher prediction accuracy than four well-known similarity measures including common neighbors, local path index, average commute time and matrix forest index. Furthermore, based on the common conclusion that an excellent link prediction method reveals a good evolving mechanism, the experiment results suggest that KD is a considerable network evolving mechanism for the formation of complex networks.

How Neglect and Punitiveness Influence Emotion Knowledge

PubMed Central

Sullivan, Margaret Wolan; Carmody, Dennis P.

2010-01-01

To explore whether punitive parenting styles contribute to early-acquired emotion knowledge deficits observable in neglected children, we observed 42 preschool children’s emotion knowledge, expression recognition time, and IQ. The children’s mothers completed the Parent–Child Conflict Tactics Scales to assess the recent use of three types of discipline strategies (nonviolent, physically punitive, and psychological aggression), as well as neglectful parenting. Fifteen of the children were identified as neglected by Child Protective Services (CPS) reports; 27 children had no record of CPS involvement and served as the comparison group. There were no differences between the neglect and comparison groups in the demographic factors of gender, age, home language, minority status, or public assistance, nor on IQ. Hierarchical multiple regression modeling showed that neglect significantly predicted emotion knowledge. The addition of IQ contributed a significant amount of additional variance to the model and maintained the fit. Adding parental punitiveness in the final stage contributed little additional variance and did not significantly improve the fit. Thus, deficits in children’s emotion knowledge may be due primarily to lower IQ or neglect. IQ was unrelated to speed of emotion recognition. Punitiveness did not directly contribute to emotion knowledge deficits but appeared in exploratory analysis to be related to speed of emotion recognition. PMID:20099078

Trust from the past: Bayesian Personalized Ranking based Link Prediction in Knowledge Graphs

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

Zhang, Baichuan; Choudhury, Sutanay; Al-Hasan, Mohammad

2016-02-01

Estimating the confidence for a link is a critical task for Knowledge Graph construction. Link prediction, or predicting the likelihood of a link in a knowledge graph based on prior state is a key research direction within this area. We propose a Latent Feature Embedding based link recommendation model for prediction task and utilize Bayesian Personalized Ranking based optimization technique for learning models for each predicate. Experimental results on large-scale knowledge bases such as YAGO2 show that our approach achieves substantially higher performance than several state-of-art approaches. Furthermore, we also study the performance of the link prediction algorithm in termsmore » of topological properties of the Knowledge Graph and present a linear regression model to reason about its expected level of accuracy.« less

Evaluation of a training curriculum for prehospital trauma ultrasound.

PubMed

Press, Gregory M; Miller, Sara K; Hassan, Iman A; Blankenship, Robert; del Junco, Deborah; Camp, Elizabeth; Holcomb, John B

2013-12-01

In the United States, ultrasound has rarely been incorporated into prehospital care, and scant descriptions of the processes used to train prehospital providers are available. Our objective was to evaluate the effectiveness of an extended focused assessment with sonography for trauma (EFAST) training curriculum that incorporated multiple educational modalities. We also aimed to determine if certain demographic factors predicted successful completion. All aeromedical prehospital providers (APPs) for a Level I trauma center took a 25-question computer-based test to ascertain baseline knowledge. Questions were categorized by content and format. Training over a 2-month period included a didactic course, a hands-on training session, proctored scanning sessions in the Emergency Department, six Internet-based training modules, pocket flashcards, a review session, and remedial training. At the conclusion of the training curriculum, the same test and an objective structured clinical examination were administered to evaluate knowledge gained. Thirty-three of 34 APPs completed training. The overall pre-test and post-test means and all content and format subsets showed significant improvement (p < 0.0001 for all). No APP passed the pre-test, and 28 of 33 passed the post-test with a mean score of 78%. No demographic variable predicted passing the post-test. Twenty-seven of 33 APPs passed the objective structured clinical examination, and the only predictive variable was passing the post-test (odds ratio 1.21, 95% confidence interval 1.00-1.25, p = 0.045). The implementation of a multifaceted EFAST prehospital training program is feasible. Significant improvement in overall and subset testing scores suggests that the test instrument was internally consistent and sufficiently sensitive to capture knowledge gained as a result of the training. Demographic variables were not predictive of test success. Copyright © 2013 Elsevier Inc. All rights reserved.

Utility of the theory of planned behavior to predict nursing staff blood pressure monitoring behaviours.

PubMed

Nelson, Joan M; Cook, Paul F; Ingram, Jennifer C

2014-02-01

To evaluate constructs from the theory of planned behavior (TPB, Ajzen 2002) - attitudes, sense of control, subjective norms and intentions - as predictors of accuracy in blood pressure monitoring. Despite numerous initiatives aimed at teaching blood pressure measurement techniques, many healthcare providers measure blood pressures incorrectly. Descriptive, cohort design. Medical assistants and licensed practical nurses were asked to complete a questionnaire on TPB variables. These nursing staff's patients had their blood pressures measured and completed a survey about techniques used to measure their blood pressure. We correlated nursing staff's responses on the TBP questionnaire with their intention to measure an accurate blood pressure and with the difference between their actual blood pressure measurement and a second measurement taken by a researcher immediately after the clinic visit. Patients' perceptions of MAs' and LPNs' blood pressure measurement techniques were examined descriptively. Perceived control and social norm predicted intention to measure an accurate blood pressure, with a negative relationship between knowledge and intention. Consistent with the TPB, intention was the only significant predictor of blood pressure measurement accuracy. Theory of planned behavior constructs predicted the healthcare providers' intention to measure blood pressure accurately and intention predicted the actual accuracy of systolic blood pressure measurement. However, participants' knowledge about blood pressure measurement had an unexpected negative relationship with their intentions. These findings have important implications for nursing education departments and organisations which traditionally invest significant time and effort in annual competency training focused on knowledge enhancement by staff. This study suggests that a better strategy might involve efforts to enhance providers' intention to change, particularly by changing social norms or increasing perceived control of the behaviour by nursing staff. © 2013 Blackwell Publishing Ltd.

Impact of a Mental Health Curriculum on Knowledge and Stigma Among High School Students: A Randomized Controlled Trial.

PubMed

Milin, Robert; Kutcher, Stanley; Lewis, Stephen P; Walker, Selena; Wei, Yifeng; Ferrill, Natasha; Armstrong, Michael A

2016-05-01

This study evaluated the effectiveness of a school-based mental health literacy intervention for adolescents on knowledge and stigma. A total of 24 high schools and 534 students in the regional area of Ottawa, Ontario, Canada participated in this randomized controlled trial. Schools were randomly assigned to either the curriculum or control condition. The curriculum was integrated into the province's grade 11 and 12 "Healthy Living" courses and was delivered by teachers. Changes in mental health knowledge and stigma were measured using pre- and posttest questionnaires. Descriptive analyses were conducted to provide sample characteristics, and multilevel modeling was used to examine study outcomes. For the curriculum condition, there was a significant change in stigma scores over time (p = .001), with positive attitudes toward mental illness increasing from pre to post. There was also a significant change in knowledge scores over time (p < .001), with knowledge scores increasing from pre to post. No significant changes in knowledge or stigma were found for participants in the control condition. A meaningful relationship was found whereby increases in knowledge significantly predicted increases in positive attitudes toward mental health (p < .001). This is the first large randomized controlled trial to demonstrate the effectiveness in mental health literacy of an integrated, manualized mental health educational resource for high school students on knowledge and stigma. Findings also support the applicability by teachers and suggest the potential for broad-based implementation of the educational curriculum in high schools. Replication and further studies are warranted. Clinical trial registration information-Impact of a Mental Health Curriculum for High School Students on Knowledge and Stigma; http://clinicaltrials.gov/; NCT02561780. Copyright © 2016 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.

Fine motor skills and early comprehension of the world: two new school readiness indicators.

PubMed

Grissmer, David; Grimm, Kevin J; Aiyer, Sophie M; Murrah, William M; Steele, Joel S

2010-09-01

Duncan et al. (2007) presented a new methodology for identifying kindergarten readiness factors and quantifying their importance by determining which of children's developing skills measured around kindergarten entrance would predict later reading and math achievement. This article extends Duncan et al.'s work to identify kindergarten readiness factors with 6 longitudinal data sets. Their results identified kindergarten math and reading readiness and attention as the primary long-term predictors but found no effects from social skills or internalizing and externalizing behavior. We incorporated motor skills measures from 3 of the data sets and found that fine motor skills are an additional strong predictor of later achievement. Using one of the data sets, we also predicted later science scores and incorporated an additional early test of general knowledge of the social and physical world as a predictor. We found that the test of general knowledge was by far the strongest predictor of science and reading and also contributed significantly to predicting later math, making the content of this test another important kindergarten readiness indicator. Together, attention, fine motor skills, and general knowledge are much stronger overall predictors of later math, reading, and science scores than early math and reading scores alone.

A Knowledge-Base for a Personalized Infectious Disease Risk Prediction System.

PubMed

Vinarti, Retno; Hederman, Lucy

2018-01-01

We present a knowledge-base to represent collated infectious disease risk (IDR) knowledge. The knowledge is about personal and contextual risk of contracting an infectious disease obtained from declarative sources (e.g. Atlas of Human Infectious Diseases). Automated prediction requires encoding this knowledge in a form that can produce risk probabilities (e.g. Bayesian Network - BN). The knowledge-base presented in this paper feeds an algorithm that can auto-generate the BN. The knowledge from 234 infectious diseases was compiled. From this compilation, we designed an ontology and five rule types for modelling IDR knowledge in general. The evaluation aims to assess whether the knowledge-base structure, and its application to three disease-country contexts, meets the needs of personalized IDR prediction system. From the evaluation results, the knowledge-base conforms to the system's purpose: personalization of infectious disease risk.

Prospective Effects of Parenting on Substance Use and Problems Across Asian/Pacific Islander and European American Youth: Tests of Moderated Mediation.

PubMed

Luk, Jeremy W; King, Kevin M; McCarty, Carolyn A; McCauley, Elizabeth; Vander Stoep, Ann

2017-07-01

Parental warmth and knowledge are protective factors against substance use, whereas parental psychological control is a risk factor. However, the interpretation of parenting and its effects on developmental outcomes may vary cross-culturally. This study examined direct and indirect effects of three parenting dimensions on substance use across Asian/Pacific Islander (API) and European Americans. A community sample of 97 API and 255 European Americans were followed from Grades 6 to 12. Participants reported on parenting in Grade 7, academic achievement and externalizing behaviors in Grades 7 and 8, and substance use behaviors in Grades 7, 9, and 12. Direct effects of parenting were not moderated by race. Overall, mother psychological control was a risk factor for substance use problems in Grade 9, whereas father knowledge was protective against alcohol use in Grade 9, substance use problems in Grades 9 and 12, and alcohol dependence in Grade 12. Moderated mediation analyses indicated significant mediational links among European Americans only: Mother knowledge predicted fewer externalizing problems in Grade 8, which in turn predicted fewer substance use problems in Grades 9 and 12. Father warmth predicted better academic achievement in Grade 8, which in turn predicted fewer substance use problems in Grades 9 and 12, as well as alcohol and marijuana dependence in Grade 12. Better academic achievement and fewer externalizing behaviors explain how positive parenting reduces substance use risk among European Americans. Promoting father knowledge of adolescents' whereabouts can reduce substance use risk among both European and API Americans.

Level and determinants of diabetes knowledge in patients with diabetes in Zimbabwe: a cross-sectional study

PubMed Central

Mufunda, Esther; Wikby, Kerstin; Björn, Albin; Hjelm, Katarina

2012-01-01

Introduction A previous study of beliefs about health and illness in Zimbabweans with diabetes mellitus indicated limited knowledge about diabetes and the body, affecting self-care and health-care seeking behaviour. The aim of this study was to assess the level of diabetes knowledge in Zimbabwean adults with diabetes mellitus, to determine the main gaps in knowledge and identify the socio-demographic and diabetes-related determinants that predict diabetes awareness and self-care practices. Methods A cross-sectional descriptive study was performed using a standardized self-report Diabetes Knowledge Test questionnaire (DKT) of 58 respondents, 32 women and 26 men. Results were analysed with descriptive and analytic statistical methods. Results The majority of the respondents scored average knowledge on all three sub-scales: general knowledge, insulin use and total knowledge, with an overall score of 63.1± 14, 2%. Major knowledge gaps were in areas related to diet, insulin use and glycaemic control. No significant differences in mean scores were detected in the diabetes knowledge sub-scales when comparisons were made of mean knowledge scores in relation to socio-demographic and diabetes-related characteristics. However, diabetes-related complications were significantly associated with lower total and general diabetes knowledge, and female gender was an independent determinant of low general knowledge. Conclusion Knowledge gaps were evident in areas regarding insulin use, diet and glycaemic control. Low diabetes knowledge was associated with female gender and could be a risk factor for development of diabetes-related complications. Knowledge gaps need to be addressed in diabetes education to prevent development of diabetes-related complications. PMID:23396799

Predicting hypothetical willingness to participate (WTP) in a future phase III HIV vaccine trial among high-risk adolescents.

PubMed

Giocos, Georgina; Kagee, Ashraf; Swartz, Leslie

2008-11-01

The present study sought to determine whether the Theory of Planned Behaviour predicted stated hypothetical willingness to participate (WTP) in future Phase III HIV vaccine trials among South African adolescents. Hierarchical logistic regression analyses showed that The Theory of Planned Behaviour (TPB) significantly predicted WTP. Of all the predictors, Subjective norms significantly predicted WTP (OR = 1.19, 95% C.I. = 1.06-1.34). A stepwise logistic regression analysis revealed that Subjective Norms (OR = 1.19, 95% C.I. = 1.07-1.34) and Attitude towards participation in an HIV vaccine trial (OR = 1.32, 95% C.I. = 1.00-1.74) were significant predictors of WTP. The addition of Knowledge of HIV vaccines and HIV vaccine trials, Perceived self-risk of HIV infection, Health-promoting behaviours and Attitudes towards HIV/AIDS yielded non-significant results. These findings provide support for the Theory of Reasoned Action (TRA) and suggest that psychosocial factors may play an important role in WTP in Phase III HIV vaccine trials among adolescents.

Gender, Religiosity, Sexual Activity, Sexual Knowledge, and Attitudes Toward Controversial Aspects of Sexuality.

PubMed

Sümer, Zeynep Hatipoğlu

2015-12-01

The purpose of this study is to examine the role of gender, religiosity, sexual activity, and sexual knowledge in predicting attitudes toward controversial aspects of sexuality among Turkish university students. Participants were 162 female and 135 male undergraduate students who were recruited on a volunteer basis from an urban state university in Turkey. The SKAT-A Attitude Scale along with background information form, sexual activities inventory, and sexual knowledge scale were administered to the participants. Simultaneous multiple regression analyses revealed that religiosity, particularly attendance to religious services was the most significant predictor in explaining university students' attitudes toward masturbation, abortion, homosexuality, pornography, and sexual coercion.

Correlates of sexually transmitted infection prevention knowledge among African American girls.

PubMed

Voisin, Dexter R; Tan, Kevin; Salazar, Laura F; Crosby, Richard; DiClemente, Ralph J

2012-08-01

To identify significant factors that distinguish African American girls who have high sexually transmitted infection (STI) prevention knowledge from those lacking such knowledge. We recruited a sample of 715 African American girls from three public health clinics in downtown Atlanta. Using audio computer-assisted self-interviewing (A-CASI) technology, we assessed for age, self-mastery, employment status, attendance at sex education classes, socioeconomic status, and STI prevention knowledge. Slightly more than one-third of the girls did not know that females are more susceptible to STI infections than males; and that having an STI increases the risk of contracting HIV. Almost half of the girls did not know if a man has an STI he will not have noticeable symptoms; and that most people who have AIDS look healthy. Logistic regression findings indicated that being older, having greater self-mastery, and being employed significantly predicted high STI knowledge. Health educators may especially target African American girls who are younger, unemployed, and experiencing low self-mastery for more tailored STI heath education. Copyright © 2012 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Friends' knowledge of youth internalizing and externalizing adjustment: accuracy, bias, and the influences of gender, grade, positive friendship quality, and self-disclosure.

PubMed

Swenson, Lance P; Rose, Amanda J

2009-08-01

Some evidence suggests that close friends may be knowledgeable of youth's psychological adjustment. However, friends are understudied as reporters of adjustment. The current study examines associations between self- and friend-reports of internalizing and externalizing adjustment in a community sample of fifth-, eighth-, and eleventh-grade youth. The study extends prior work by considering the degree to which friends' reports of youth adjustment are accurate (i.e., predicted by youths' actual adjustment) versus biased (i.e., predicted by the friend reporters' own adjustment). Findings indicated stronger bias effects than accuracy effects, but the accuracy effects were significant for both internalizing and externalizing adjustment. Additionally, friends who perceived their relationships as high in positive quality, friends in relationships high in disclosure, and girls perceived youths' internalizing symptoms most accurately. Knowledge of externalizing adjustment was not influenced by gender, grade, relationship quality, or self-disclosure. Findings suggest that friends could play an important role in prevention efforts.

Achievement goal orientation and situational motivation for a low-stakes test of content knowledge.

PubMed

Waskiewicz, Rhonda A

2012-05-10

To determine the extent of the relationship between students' inherent motivation to achieve in a doctor of pharmacy program and their motivation to achieve on a single low-stakes test of content knowledge. The Attitude Toward Learning Questionnaire (ATL) was administered to 66 third-year pharmacy students at the beginning of the spring 2011 semester, and the Student Opinion Scale (SOS) was administered to the same group immediately following completion of the Pharmacy Curricular Outcomes Assessment (PCOA). Significant differences were found in performance approach and work avoidance based on situational motivation scores. Situational motivation was also found to be directly correlated with performance and mastery approaches and inversely correlated with work avoidance. Criteria were met for predicting importance and effort from performance and mastery approaches and work avoidance scores of pharmacy students. The ability to predict pharmacy students' motivation to perform on a low-stakes standardized test of content knowledge increases the test's usefulness as a measure of curricular effectiveness.

Achievement Goal Orientation and Situational Motivation for a Low-Stakes Test of Content Knowledge

PubMed Central

2012-01-01

Objective. To determine the extent of the relationship between students’ inherent motivation to achieve in a doctor of pharmacy program and their motivation to achieve on a single low-stakes test of content knowledge. Method. The Attitude Toward Learning Questionnaire (ATL) was administered to 66 third-year pharmacy students at the beginning of the spring 2011 semester, and the Student Opinion Scale (SOS) was administered to the same group immediately following completion of the Pharmacy Curricular Outcomes Assessment (PCOA). Results. Significant differences were found in performance approach and work avoidance based on situational motivation scores. Situational motivation was also found to be directly correlated with performance and mastery approaches and inversely correlated with work avoidance. Criteria were met for predicting importance and effort from performance and mastery approaches and work avoidance scores of pharmacy students. Conclusions. The ability to predict pharmacy students’ motivation to perform on a low-stakes standardized test of content knowledge increases the test’s usefulness as a measure of curricular effectiveness. PMID:22611274

Parameter estimation and prediction for the course of a single epidemic outbreak of a plant disease.

PubMed

Kleczkowski, A; Gilligan, C A

2007-10-22

Many epidemics of plant diseases are characterized by large variability among individual outbreaks. However, individual epidemics often follow a well-defined trajectory which is much more predictable in the short term than the ensemble (collection) of potential epidemics. In this paper, we introduce a modelling framework that allows us to deal with individual replicated outbreaks, based upon a Bayesian hierarchical analysis. Information about 'similar' replicate epidemics can be incorporated into a hierarchical model, allowing both ensemble and individual parameters to be estimated. The model is used to analyse the data from a replicated experiment involving spread of Rhizoctonia solani on radish in the presence or absence of a biocontrol agent, Trichoderma viride. The rate of primary (soil-to-plant) infection is found to be the most variable factor determining the final size of epidemics. Breakdown of biological control in some replicates results in high levels of primary infection and increased variability. The model can be used to predict new outbreaks of disease based upon knowledge from a 'library' of previous epidemics and partial information about the current outbreak. We show that forecasting improves significantly with knowledge about the history of a particular epidemic, whereas the precision of hindcasting to identify the past course of the epidemic is largely independent of detailed knowledge of the epidemic trajectory. The results have important consequences for parameter estimation, inference and prediction for emerging epidemic outbreaks.

Contextual risk, maternal parenting and adolescent externalizing behaviour problems: the role of emotion regulation.

PubMed

Walton, A; Flouri, Eirini

2010-03-01

The objective of this study was to test if emotion regulation mediates the association between mothers' parenting and adolescents' externalizing behaviour problems (conduct problems and hyperactivity). The parenting dimensions were warmth, psychological control and behavioural control (measured with knowledge, monitoring and discipline). Adjustment was made for contextual risk (measured with the number of proximal adverse life events experienced), gender, age and English as an additional language. Data were from a UK community sample of adolescents aged 11-18 from a comprehensive school in a disadvantaged area. At the multivariate level, none of the parenting variables predicted hyperactivity, which was associated only with difficulties in emotion regulation, contextual risk and English as a first language. The parenting variables predicting conduct problems at the multivariate level were warmth and knowledge. Knowledge did not predict emotion regulation. However, warmth predicted emotion regulation, which was negatively associated with conduct problems. Contextual risk was a significant predictor of both difficulties in emotion regulation and externalizing behaviour problems. Its effect on conduct problems was independent of parenting and was not via its association with difficulties in emotion regulation. The findings add to the evidence for the importance of maternal warmth and contextual risk for both regulated emotion and regulated behaviour. The small maternal control effects on both emotion regulation and externalizing behaviour could suggest the importance of paternal control for adolescent outcomes.

Fire Effects, Education, and Expert Systems

Treesearch

Robert E. Martin

1987-01-01

Predicting the effects of fires in the year 2000 and beyond will be enhanced by the use of expert systems. Although our predictions may have broad confidence limits, expert systems should help us to improve the predictions and to focus on the areas where improved knowledge is most needed. The knowledge of experts can be incorporated into previously existing knowledge...

Assessment of Knowledge of Diabetes Mellitus in the Urban Areas of Klang District, Malaysia.

PubMed

Chinnappan, Sasikala; Sivanandy, Palanisamy; Sagaran, Rajenthina; Molugulu, Nagashekhara

2017-02-23

Diabetes is the most common cause of non-traumatic lower limb amputations and cardiovascular diseases. However, only a negligible percentage of the patients and subjects knew that the feet are affected in diabetes and diabetes affects the heart. Hence, a cross-sectional study was carried out to evaluate the knowledge of diabetes mellitus among the public of different age group, gender, ethnicity, and education level. A sample of 400 participants was randomly selected and data was collected using a structured questionnaire under non-contrived setting. The results showed that there is a statistically significant difference in knowledge on diabetes mellitus among different age groups and different ethnic origin but there is no significant difference in the knowledge among different gender and education level. Out of 400 respondents, 284 respondents (71%) knew that diabetes mellitus is actually a condition characterized by raised blood sugar. Age and education level of respondents were found to be the predominant predictive factors on diabetes knowledge, whereas the gender of respondents did not affect the findings of this study. An improved and well-structured educational programme that tackles the areas of weaknesses should be recommended to increase the level of knowledge on diabetes among Malaysians.

In silico prediction of pharmaceutical degradation pathways: a benchmarking study.

PubMed

Kleinman, Mark H; Baertschi, Steven W; Alsante, Karen M; Reid, Darren L; Mowery, Mark D; Shimanovich, Roman; Foti, Chris; Smith, William K; Reynolds, Dan W; Nefliu, Marcela; Ott, Martin A

2014-11-03

Zeneth is a new software application capable of predicting degradation products derived from small molecule active pharmaceutical ingredients. This study was aimed at understanding the current status of Zeneth's predictive capabilities and assessing gaps in predictivity. Using data from 27 small molecule drug substances from five pharmaceutical companies, the evolution of Zeneth predictions through knowledge base development since 2009 was evaluated. The experimentally observed degradation products from forced degradation, accelerated, and long-term stability studies were compared to Zeneth predictions. Steady progress in predictive performance was observed as the knowledge bases grew and were refined. Over the course of the development covered within this evaluation, the ability of Zeneth to predict experimentally observed degradants increased from 31% to 54%. In particular, gaps in predictivity were noted in the areas of epimerizations, N-dealkylation of N-alkylheteroaromatic compounds, photochemical decarboxylations, and electrocyclic reactions. The results of this study show that knowledge base development efforts have increased the ability of Zeneth to predict relevant degradation products and aid pharmaceutical research. This study has also provided valuable information to help guide further improvements to Zeneth and its knowledge base.

Knowledge integration, teamwork and performance in health care.

PubMed

Körner, Mirjam; Lippenberger, Corinna; Becker, Sonja; Reichler, Lars; Müller, Christian; Zimmermann, Linda; Rundel, Manfred; Baumeister, Harald

2016-01-01

Knowledge integration is the process of building shared mental models. The integration of the diverse knowledge of the health professions in shared mental models is a precondition for effective teamwork and team performance. As it is known that different groups of health care professionals often tend to work in isolation, the authors compared the perceptions of knowledge integration. It can be expected that based on this isolation, knowledge integration is assessed differently. The purpose of this paper is to test these differences in the perception of knowledge integration between the professional groups and to identify to what extent knowledge integration predicts perceptions of teamwork and team performance and to determine if teamwork has a mediating effect. The study is a multi-center cross-sectional study with a descriptive-explorative design. Data were collected by means of a staff questionnaire for all health care professionals working in the rehabilitation clinics. The results showed that there are significant differences in knowledge integration within interprofessional health care teams. Furthermore, it could be shown that knowledge integration is significantly related to patient-centered teamwork as well as to team performance. Mediation analysis revealed partial mediation of the effect of knowledge integration on team performance through teamwork. PRACTICAL/IMPLICATIONS: In practice, the results of the study provide a valuable starting point for team development interventions. This is the first study that explored knowledge integration in medical rehabilitation teams and its relation to patient-centered teamwork and team performance.

Adverse Childhood Experiences Predict Alcohol Consumption Patterns Among Kenyan Mothers.

PubMed

Goodman, Michael L; Grouls, Astrid; Chen, Catherine X; Keiser, Philip H; Gitari, Stanley

2017-04-16

We analyze whether adverse childhood experiences predict weekly alcohol consumption patterns of Kenyan mothers and their partners. Randomly selected respondents (n = 1,976) were asked about adverse childhood experiences and alcohol consumption patterns for themselves and their partners. Fixed effect models were used to determine odds of reporting weekly alcohol consumption and the number of beverages typically consumed, controlling for wealth, age, education, and partner alcohol consumption. Cumulative adverse childhood experiences predicted higher odds of weekly alcohol consumption of the respondent and her partner. Childhood exposure to physical abuse, emotional neglect, and mental illness in the household significantly increased odds of weekly alcohol consumption by the respondent. More drinks consumed per typical session were higher among respondents with more cumulative adversities. Physical and emotional abuse significantly predicted number of drinks typically consumed by the respondent. To our knowledge, this is the first study to explore and find associations between adverse childhood experiences and alcohol consumption in Kenya. Consistent with high-income settings, exposure to childhood adversities predicted greater alcohol consumption among Kenyan women.

Knowledge discovery for pancreatic cancer using inductive logic programming.

PubMed

Qiu, Yushan; Shimada, Kazuaki; Hiraoka, Nobuyoshi; Maeshiro, Kensei; Ching, Wai-Ki; Aoki-Kinoshita, Kiyoko F; Furuta, Koh

2014-08-01

Pancreatic cancer is a devastating disease and predicting the status of the patients becomes an important and urgent issue. The authors explore the applicability of inductive logic programming (ILP) method in the disease and show that the accumulated clinical laboratory data can be used to predict disease characteristics, and this will contribute to the selection of therapeutic modalities of pancreatic cancer. The availability of a large amount of clinical laboratory data provides clues to aid in the knowledge discovery of diseases. In predicting the differentiation of tumour and the status of lymph node metastasis in pancreatic cancer, using the ILP model, three rules are developed that are consistent with descriptions in the literature. The rules that are identified are useful to detect the differentiation of tumour and the status of lymph node metastasis in pancreatic cancer and therefore contributed significantly to the decision of therapeutic strategies. In addition, the proposed method is compared with the other typical classification techniques and the results further confirm the superiority and merit of the proposed method.

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

PubMed Central

Hannon, Brenda

2014-01-01

To-date, studies have examined simultaneously the relative predictive powers of two or three factors on GPA. The present study examines the relative powers of five social/personality factors, five cognitive/learning factors, and SAT scores to predict freshmen and non-freshmen (sophomores, juniors, seniors) academic success (i.e., GPA). The results revealed many significant predictors of GPA for both freshmen and non-freshmen. However, subsequent regressions showed that only academic self-efficacy, epistemic belief of learning, and high-knowledge integration explained unique variance in GPA (19%-freshmen, 23.2%-non-freshmen). Further for freshmen, SAT scores explained an additional unique 10.6% variance after the influences attributed to these three predictors was removed whereas for non-freshmen, SAT scores failed to explain any additional variance. These results highlight the unique and important contributions of academic self-efficacy, epistemic belief of learning and high-knowledge integration to GPA beyond other previously-identified predictors. PMID:25568884

Academic Skills of Boys With Fragile X Syndrome: Profiles and Predictors

ERIC Educational Resources Information Center

Roberts, Jane E.; Schaaf, Jennifer M.; Skinner, Martie; Wheeler, Anne; Hooper, Stephen; Hatton, Deborah D.; Bailey, Donald B., Jr.

2005-01-01

The academic achievement of boys with fragile X syndrome and the relation between several predictive factors and academic performance are reported. Boys with fragile X syndrome displayed significant deficits in all academic skill areas. Relative strengths were observed in general knowledge, reflecting the ability to integrate experiential…

Examining the Self-Development Test for Race and Gender Fairness

DTIC Science & Technology

1994-07-01

apication of kowledge and the MOS Knowledge item involved direct knowledge. SDT verion SSM(2) contained three such MOS Knowledge items. Two required...and not its purpose as an indicator of motivation and ability to learn, is what gives it its power to predict performance at the next rank. However...then it should not be used regardless of its fairness. Related to the predictive power of the SDT is the mechanism by which it predicts. If it predicts

Assessment of farmer knowledge of large ruminant health and production in developing village-level biosecurity in northern Lao PDR.

PubMed

Nampanya, S; Rast, L; Khounsy, S; Windsor, P A

2010-12-01

The purpose of this study was to determine baseline knowledge and identify knowledge gaps of farmers on biosecurity, risk of transmission of transboundary diseases and large ruminant health and production in three provinces of northern Laos, Hua Phan (HP), Luang Prabang (LPB) and Xieng Khoung (XK). The survey was conducted in six villages that are project sites for an Australian Centre for International Agricultural Research (ACIAR) project, with two villages located in each of the three provinces. A census survey was conducted by interview with all 238 farmers participating in the ACIAR project, using a structured questionnaire. The interviews were conducted in Lao language and took 1-2 h per farmer. The answers were recorded in Lao and the survey data were translated into English and transcribed into Microsoft Excel, and a linear mixed model in the Genstat statistical analysis package was used to compare quantitative traits between the target provinces. The results showed that the prediction mean of farmer knowledge scores on parasitic disorders, infectious disease, reproduction and nutrition management were significantly different between the target provinces. The prediction mean of farmer knowledge scores on infectious disease questions ranged between 5.11 in HP to 8.54 in XK of 24 marks (P < 0.001). The prediction mean of total knowledge scores was 13.48 in LPB and 19.29 in XK of 42 marks (P < 0.001). The results indicate both the need for and scope required to attain improvements in farmer knowledge of large ruminant health and production. It was concluded that a participatory research and extension programme to address village-level biosecurity and reduce disease risks, plus enhance large ruminant production capabilities of smallholder producers, is a valid and potentially important strategy to address transboundary disease risk and rural poverty in northern Laos. © 2010 Blackwell Verlag GmbH.

Medicine is not science: guessing the future, predicting the past.

PubMed

Miller, Clifford

2014-12-01

Irregularity limits human ability to know, understand and predict. A better understanding of irregularity may improve the reliability of knowledge. Irregularity and its consequences for knowledge are considered. Reliable predictive empirical knowledge of the physical world has always been obtained by observation of regularities, without needing science or theory. Prediction from observational knowledge can remain reliable despite some theories based on it proving false. A naïve theory of irregularity is outlined. Reducing irregularity and/or increasing regularity can increase the reliability of knowledge. Beyond long experience and specialization, improvements include implementing supporting knowledge systems of libraries of appropriately classified prior cases and clinical histories and education about expertise, intuition and professional judgement. A consequence of irregularity and complexity is that classical reductionist science cannot provide reliable predictions of the behaviour of complex systems found in nature, including of the human body. Expertise, expert judgement and their exercise appear overarching. Diagnosis involves predicting the past will recur in the current patient applying expertise and intuition from knowledge and experience of previous cases and probabilistic medical theory. Treatment decisions are an educated guess about the future (prognosis). Benefits of the improvements suggested here are likely in fields where paucity of feedback for practitioners limits development of reliable expert diagnostic intuition. Further analysis, definition and classification of irregularity is appropriate. Observing and recording irregularities are initial steps in developing irregularity theory to improve the reliability and extent of knowledge, albeit some forms of irregularity present inherent difficulties. © 2014 John Wiley & Sons, Ltd.

Comparison of Basic Science Knowledge Between DO and MD Students.

PubMed

Davis, Glenn E; Gayer, Gregory G

2017-02-01

With the coming single accreditation system for graduate medical education, medical educators may wonder whether knowledge in basic sciences is equivalent for osteopathic and allopathic medical students. To examine whether medical students' basic science knowledge is the same among osteopathic and allopathic medical students. A dataset of the Touro University College of Osteopathic Medicine-CA student records from the classes of 2013, 2014, and 2015 and the national cohort of National Board of Medical Examiners Comprehensive Basic Science Examination (NBME-CBSE) parameters for MD students were used. Models of the Comprehensive Osteopathic Medical Licensing Examination-USA (COMLEX-USA) Level 1 scores were fit using linear and logistic regression. The models included variables used in both osteopathic and allopathic medical professions to predict COMLEX-USA outcomes, such as Medical College Admission Test biology scores, preclinical grade point average, number of undergraduate science units, and scores on the NBME-CBSE. Regression statistics were studied to compare the effectiveness of models that included or excluded NBME-CBSE scores at predicting COMLEX-USA Level 1 scores. Variance inflation factor was used to investigate multicollinearity. Receiver operating characteristic curves were used to show the effectiveness of NBME-CBSE scores at predicting COMLEX-USA Level 1 pass/fail outcomes. A t test at 99% level was used to compare mean NBME-CBSE scores with the national cohort. A total of 390 student records were analyzed. Scores on the NBME-CBSE were found to be an effective predictor of COMLEX-USA Level 1 scores (P<.001). The pass/fail outcome on COMLEX-USA Level 1 was also well predicted by NBME-CBSE scores (P<.001). No significant difference was found in performance on the NBME-CBSE between osteopathic and allopathic medical students (P=.322). As an examination constructed to assess the basic science knowledge of allopathic medical students, the NBME-CBSE is effective at predicting performance on COMLEX-USA Level 1. In addition, osteopathic medical students performed the same as allopathic medical students on the NBME-CBSE. The results imply that the same basic science knowledge is expected for DO and MD students.

MO-G-304-01: FEATURED PRESENTATION: Expanding the Knowledge Base for Data-Driven Treatment Planning: Incorporating Patient Outcome Models

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

Robertson, SP; Quon, H; Cheng, Z

2015-06-15

Purpose: To extend the capabilities of knowledge-based treatment planning beyond simple dose queries by incorporating validated patient outcome models. Methods: From an analytic, relational database of 684 head and neck cancer patients, 372 patients were identified having dose data for both left and right parotid glands as well as baseline and follow-up xerostomia assessments. For each existing patient, knowledge-based treatment planning was simulated for by querying the dose-volume histograms and geometric shape relationships (overlap volume histograms) for all other patients. Dose predictions were captured at normalized volume thresholds (NVT) of 0%, 10%, 20, 30%, 40%, 50%, and 85% and weremore » compared with the actual achieved doses using the Wilcoxon signed-rank test. Next, a logistic regression model was used to predict the maximum severity of xerostomia up to three months following radiotherapy. Baseline xerostomia scores were subtracted from follow-up assessments and were also included in the model. The relative risks from predicted doses and actual doses were computed and compared. Results: The predicted doses for both parotid glands were significantly less than the achieved doses (p < 0.0001), with differences ranging from 830 cGy ± 1270 cGy (0% NVT) to 1673 cGy ± 1197 cGy (30% NVT). The modelled risk of xerostomia ranged from 54% to 64% for achieved doses and from 33% to 51% for the dose predictions. Relative risks varied from 1.24 to 1.87, with maximum relative risk occurring at 85% NVT. Conclusions: Data-driven generation of treatment planning objectives without consideration of the underlying normal tissue complication probability may Result in inferior plans, even if quality metrics indicate otherwise. Inclusion of complication models in knowledge-based treatment planning is necessary in order to close the feedback loop between radiotherapy treatments and patient outcomes. Future work includes advancing and validating complication models in the context of knowledge-based treatment planning. This work is supported by Philips Radiation Oncology Systems.« less

Modeling Mode Choice Behavior Incorporating Household and Individual Sociodemographics and Travel Attributes Based on Rough Sets Theory

PubMed Central

Chen, Xuewu; Wei, Ming; Wu, Jingxian; Hou, Xianyao

2014-01-01

Most traditional mode choice models are based on the principle of random utility maximization derived from econometric theory. Alternatively, mode choice modeling can be regarded as a pattern recognition problem reflected from the explanatory variables of determining the choices between alternatives. The paper applies the knowledge discovery technique of rough sets theory to model travel mode choices incorporating household and individual sociodemographics and travel information, and to identify the significance of each attribute. The study uses the detailed travel diary survey data of Changxing county which contains information on both household and individual travel behaviors for model estimation and evaluation. The knowledge is presented in the form of easily understood IF-THEN statements or rules which reveal how each attribute influences mode choice behavior. These rules are then used to predict travel mode choices from information held about previously unseen individuals and the classification performance is assessed. The rough sets model shows high robustness and good predictive ability. The most significant condition attributes identified to determine travel mode choices are gender, distance, household annual income, and occupation. Comparative evaluation with the MNL model also proves that the rough sets model gives superior prediction accuracy and coverage on travel mode choice modeling. PMID:25431585

Hope and cardiovascular health-promoting behaviour: education alone is not enough.

PubMed

Feldman, David B; Sills, Jonathan R

2013-01-01

We investigated hope's ability to predict cardiovascular disease (CVD) knowledge and health-promoting behaviours. Snyder defined hope as the combination of goal-directed planning and motivation, and theorised that high-hope people seek knowledge relevant to goal pursuits. We surveyed 391 Latino and Asian participants undergoing CVD risk screening, nearly all immigrants to the USA. This was a particularly important sample because, in general, these populations are considered underserved and under-researched. Pre-screening hope levels were measured. After screening and education, participants rated perceived importance of behaviour change. Behaviour change (salt/fat intake, exercise, CVD information-seeking and visiting a physician) and CVD knowledge were assessed one month later by telephone. Unexpectedly, hope did not predict knowledge. However, hope predicted self-reported behaviour change, though results differed by ethnicity. Among Asian individuals, hope × knowledge predicted reduced salt/fat, CVD information-seeking and physician visits. Among Latino individuals, hope × perceived importance of diet change predicted reduced salt/fat and hope × perceived importance of exercise change predicted increased exercise.

An Analysis Pipeline with Statistical and Visualization-Guided Knowledge Discovery for Michigan-Style Learning Classifier Systems

PubMed Central

Urbanowicz, Ryan J.; Granizo-Mackenzie, Ambrose; Moore, Jason H.

2014-01-01

Michigan-style learning classifier systems (M-LCSs) represent an adaptive and powerful class of evolutionary algorithms which distribute the learned solution over a sizable population of rules. However their application to complex real world data mining problems, such as genetic association studies, has been limited. Traditional knowledge discovery strategies for M-LCS rule populations involve sorting and manual rule inspection. While this approach may be sufficient for simpler problems, the confounding influence of noise and the need to discriminate between predictive and non-predictive attributes calls for additional strategies. Additionally, tests of significance must be adapted to M-LCS analyses in order to make them a viable option within fields that require such analyses to assess confidence. In this work we introduce an M-LCS analysis pipeline that combines uniquely applied visualizations with objective statistical evaluation for the identification of predictive attributes, and reliable rule generalizations in noisy single-step data mining problems. This work considers an alternative paradigm for knowledge discovery in M-LCSs, shifting the focus from individual rules to a global, population-wide perspective. We demonstrate the efficacy of this pipeline applied to the identification of epistasis (i.e., attribute interaction) and heterogeneity in noisy simulated genetic association data. PMID:25431544

Emotion knowledge and autobiographical memory across the preschool years: a cross-cultural longitudinal investigation.

PubMed

Wang, Qi

2008-07-01

Knowledge of emotion situations facilitates the interpretation, processing, and organization of significant personal event information and thus may be an important contributor to the development of autobiographical memory. This longitudinal study tested the hypothesis in a cross-cultural context. The participants were native Chinese children, Chinese children from first-generation Chinese immigrant families in the U.S., and European American children. Children's developing emotion knowledge and autobiographical memory were assessed three times at home, when children were 3, 3.5, and 4.5 years of age. Children's emotion knowledge uniquely predicted their autobiographical memory ability across groups and time points. Emotion knowledge further mediated culture effects on autobiographical memory. The findings provide important insight into early autobiographical memory development, and extend current theoretical understandings of the emotion-memory interplay. They further have implications for the phenomenon of infantile amnesia and cross-cultural differences in childhood recollections.

Multiple network-constrained regressions expand insights into influenza vaccination responses.

PubMed

Avey, Stefan; Mohanty, Subhasis; Wilson, Jean; Zapata, Heidi; Joshi, Samit R; Siconolfi, Barbara; Tsang, Sui; Shaw, Albert C; Kleinstein, Steven H

2017-07-15

Systems immunology leverages recent technological advancements that enable broad profiling of the immune system to better understand the response to infection and vaccination, as well as the dysregulation that occurs in disease. An increasingly common approach to gain insights from these large-scale profiling experiments involves the application of statistical learning methods to predict disease states or the immune response to perturbations. However, the goal of many systems studies is not to maximize accuracy, but rather to gain biological insights. The predictors identified using current approaches can be biologically uninterpretable or present only one of many equally predictive models, leading to a narrow understanding of the underlying biology. Here we show that incorporating prior biological knowledge within a logistic modeling framework by using network-level constraints on transcriptional profiling data significantly improves interpretability. Moreover, incorporating different types of biological knowledge produces models that highlight distinct aspects of the underlying biology, while maintaining predictive accuracy. We propose a new framework, Logistic Multiple Network-constrained Regression (LogMiNeR), and apply it to understand the mechanisms underlying differential responses to influenza vaccination. Although standard logistic regression approaches were predictive, they were minimally interpretable. Incorporating prior knowledge using LogMiNeR led to models that were equally predictive yet highly interpretable. In this context, B cell-specific genes and mTOR signaling were associated with an effective vaccination response in young adults. Overall, our results demonstrate a new paradigm for analyzing high-dimensional immune profiling data in which multiple networks encoding prior knowledge are incorporated to improve model interpretability. The R source code described in this article is publicly available at https://bitbucket.org/kleinstein/logminer . steven.kleinstein@yale.edu or stefan.avey@yale.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Soil erosion assessment - Mind the gap

NASA Astrophysics Data System (ADS)

Kim, Jongho; Ivanov, Valeriy Y.; Fatichi, Simone

2016-12-01

Accurate assessment of erosion rates remains an elusive problem because soil loss is strongly nonunique with respect to the main drivers. In addressing the mechanistic causes of erosion responses, we discriminate between macroscale effects of external factors - long studied and referred to as "geomorphic external variability", and microscale effects, introduced as "geomorphic internal variability." The latter source of erosion variations represents the knowledge gap, an overlooked but vital element of geomorphic response, significantly impacting the low predictability skill of deterministic models at field-catchment scales. This is corroborated with experiments using a comprehensive physical model that dynamically updates the soil mass and particle composition. As complete knowledge of microscale conditions for arbitrary location and time is infeasible, we propose that new predictive frameworks of soil erosion should embed stochastic components in deterministic assessments of external and internal types of geomorphic variability.

What do I have to lose? Effects of a psycho-educational intervention on cancer patient preference for resuscitation.

PubMed

Sears, Sharon R; Woodward, Julia T; Twillman, Robert K

2007-12-01

This original empirical study examined effects of a psycho-educational intervention on cancer patients' knowledge, concern, and preferences for cardiopulmonary resuscitation (CPR). We examined message framing as one factor that might impact subsequent decision making. In addition, we examined personality and coping style as predictors and moderators of patients' reactions to an informational intervention. As hypothesized, participants initially underestimated CPR complications and overestimated survival rates. The intervention significantly increased concern, improved knowledge, and decreased preference for CPR, particularly for participants receiving both numerical and descriptive information. Message framing of survival data did not uniquely affect CPR preference. Higher optimism predicted less increase in concern about CPR, and higher hope predicted greater decrease in preference for CPR. More approach coping related to increased concern about CPR and decreased preference for CPR.

Effective heart disease prediction system using data mining techniques.

PubMed

Singh, Poornima; Singh, Sanjay; Pandi-Jain, Gayatri S

2018-01-01

The health care industries collect huge amounts of data that contain some hidden information, which is useful for making effective decisions. For providing appropriate results and making effective decisions on data, some advanced data mining techniques are used. In this study, an effective heart disease prediction system (EHDPS) is developed using neural network for predicting the risk level of heart disease. The system uses 15 medical parameters such as age, sex, blood pressure, cholesterol, and obesity for prediction. The EHDPS predicts the likelihood of patients getting heart disease. It enables significant knowledge, eg, relationships between medical factors related to heart disease and patterns, to be established. We have employed the multilayer perceptron neural network with backpropagation as the training algorithm. The obtained results have illustrated that the designed diagnostic system can effectively predict the risk level of heart diseases.

Computational toxicology: Its essential role in reducing drug attrition.

PubMed

Naven, R T; Louise-May, S

2015-12-01

Predictive toxicology plays a critical role in reducing the failure rate of new drugs in pharmaceutical research and development. Despite recent gains in our understanding of drug-induced toxicity, however, it is urgent that the utility and limitations of our current predictive tools be determined in order to identify gaps in our understanding of mechanistic and chemical toxicology. Using recently published computational regression analyses of in vitro and in vivo toxicology data, it will be demonstrated that significant gaps remain in early safety screening paradigms. More strategic analyses of these data sets will allow for a better understanding of their domain of applicability and help identify those compounds that cause significant in vivo toxicity but which are currently mis-predicted by in silico and in vitro models. These 'outliers' and falsely predicted compounds are metaphorical lighthouses that shine light on existing toxicological knowledge gaps, and it is essential that these compounds are investigated if attrition is to be reduced significantly in the future. As such, the modern computational toxicologist is more productively engaged in understanding these gaps and driving investigative toxicology towards addressing them. © The Author(s) 2015.

The Impact of Human Patient Simulation on Nursing Clinical Knowledge

ERIC Educational Resources Information Center

Shinnick, Mary Ann

2010-01-01

Public health relies on well trained nurses and clinical experience is an important component of that training. However, clinical experience training for student nurses also has significant challenges, as it can place patients at risk. Also it is difficult to schedule/predict patient conditions and procedures. Human patient simulation (HPS) can…

Behavioral and Social Science Research: A National Resource. Part II.

ERIC Educational Resources Information Center

Adams, Robert McC., Ed.; And Others

Areas of behavioral and social science research that have achieved significant breakthroughs in knowledge or application or that show future promise of achieving such breakthroughs are discussed in 12 papers. For example, the paper on formal demography shows how mathematical or statistical techniques can be used to explain and predict change in…

Applying psychological theories to evidence-based clinical practice: identifying factors predictive of placing preventive fissure sealants.

PubMed

Bonetti, Debbie; Johnston, Marie; Clarkson, Jan E; Grimshaw, Jeremy; Pitts, Nigel B; Eccles, Martin; Steen, Nick; Thomas, Ruth; Maclennan, Graeme; Glidewell, Liz; Walker, Anne

2010-04-08

Psychological models are used to understand and predict behaviour in a wide range of settings, but have not been consistently applied to health professional behaviours, and the contribution of differing theories is not clear. This study explored the usefulness of a range of models to predict an evidence-based behaviour -- the placing of fissure sealants. Measures were collected by postal questionnaire from a random sample of general dental practitioners (GDPs) in Scotland. Outcomes were behavioural simulation (scenario decision-making), and behavioural intention. Predictor variables were from the Theory of Planned Behaviour (TPB), Social Cognitive Theory (SCT), Common Sense Self-regulation Model (CS-SRM), Operant Learning Theory (OLT), Implementation Intention (II), Stage Model, and knowledge (a non-theoretical construct). Multiple regression analysis was used to examine the predictive value of each theoretical model individually. Significant constructs from all theories were then entered into a 'cross theory' stepwise regression analysis to investigate their combined predictive value. Behavioural simulation - theory level variance explained was: TPB 31%; SCT 29%; II 7%; OLT 30%. Neither CS-SRM nor stage explained significant variance. In the cross theory analysis, habit (OLT), timeline acute (CS-SRM), and outcome expectancy (SCT) entered the equation, together explaining 38% of the variance. Behavioural intention - theory level variance explained was: TPB 30%; SCT 24%; OLT 58%, CS-SRM 27%. GDPs in the action stage had significantly higher intention to place fissure sealants. In the cross theory analysis, habit (OLT) and attitude (TPB) entered the equation, together explaining 68% of the variance in intention. The study provides evidence that psychological models can be useful in understanding and predicting clinical behaviour. Taking a theory-based approach enables the creation of a replicable methodology for identifying factors that may predict clinical behaviour and so provide possible targets for knowledge translation interventions. Results suggest that more evidence-based behaviour may be achieved by influencing beliefs about the positive outcomes of placing fissure sealants and building a habit of placing them as part of patient management. However a number of conceptual and methodological challenges remain.

[Neuropsychology of psychoeducation in schizophrenia: results of the Munich COGPIP study].

PubMed

Pitschel-Walz, G; Gsottschneider, A; Froböse, T; Kraemer, S; Bäuml, J; Jahn, T

2013-01-01

The aim of the study was to examine whether the efficacy of psychoeducation in patients with schizophrenia is dependent on their cognitive performance and if a preceding cognitive training can enhance the therapeutic effects of psychoeducation. A total of 116 inpatients were randomly assigned to either a standardized cognitive training (COGPACK) or to routine occupational therapy, followed by a psychoeducational group program of 8 sessions within 4 weeks for all study patients. The effects of cognitive training and psychoeducation were assessed directly afterwards and in a follow-up after 9 months. The patient knowledge and compliance improved. Neurocognition and especially memory acquisition significantly predicted illness knowledge after psychoeducation, whereas psychopathology did not. No differential effects of the COGPACK training were found. After 9 months 75% of the patients showed a very good compliance and the readmission rate was 18%. The results were comparable under both study conditions. Besides baseline illness knowledge neurocognition was the only significant predictor for illness knowledge after psychoeducation. Patients with cognitive deficits can profit from psychoeducation in the long run as well. In future it should be examined whether a modified cognitive training program could achieve a faster improvement of the illness knowledge.

Improving First Aid Management of Epilepsy by Trainee Teachers of the Federal College of Education (Technical), Akoka - Lagos, South West Nigeria--Can Health Education have an Effect?

PubMed

Eze, Christian N; Ebuehi, Olufunke M

2013-01-01

lt is estimated that epilepsy affects approximately 50 million people worldwide and about 40 million of them live in developing countries. Studies have indicated high rates of poor knowledge, negative attitude and poor first aid management skills of students with epilepsy among practicing teachers. However, there is paucity of such studies on trainee teachers to ascertain any similarities or differences (if any) and the effect of educational interventions. To determine the effect of a health education intervention on trainee teachers' knowledge, attitude and first aid management of epilepsy. The effect of a health education intervention in first aid management of epilepsy was assessed among 226 trainee teachers, attending the Federal College of Education (Technical), Akoka. This was done using a quasi-experimental study design. Data were analyzed using the SPSS version 15. The respondents had a median age of 22 years with a range of 18 to 56 years. The majority of them were females (68.6%), single (79.2%), Christians (81.9%), Yoruba (70.4%) and in first year (100 level) of their study (69.9%). The highest proportion was from the Accounting department (46.0%). A consistent increase in responses to items on knowledge, attitude and first aid management of epileptic seizure items from baseline to post-intervention was observed. For instance, the proportion of responses that epileptic seizures originate from the brain significantly (p = 0.025) increased from 62.5% at baseline to 74.1% after intervention. Generally, slightly more than two-fifths (44.2%) and about two thirds (61.9%) of the respondents were observed to have poor knowledge and negative attitude to epilepsy respectively at baseline. Overall, giving health education on epilepsy led to a reduction in the proportion of respondents with poor knowledge by 15.5% (increase of good knowledge by 29.6%), decrease of negative attitude by 16.4% and increase of good first aid management skill by 25.0%. The knowledge scores were significantly associated with age (p = 0.001), marital status (p = 0.003) and department (p = 0.004) while the attitude scores were significantly associated with teaching duration (p = 0.020). The knowledge was predicted by department (p = 0.001) while the attitude was predicted by teaching duration (p = 0.036). This study reveals that health education could improve the knowledge, attitude. and first aid management of students with epilepsy among trainee teachers. It is therefore proposed that an intervention programme on baseline knowledge of epilepsy and its first aid management be incorporated into the teacher-training curriculum, particularly those in health-related programmes, to address their deficiencies in knowledge, attitude and first aid management of students with epilepsy.

Exploring the knowledge behind predictions in everyday cognition: an iterated learning study.

PubMed

Stephens, Rachel G; Dunn, John C; Rao, Li-Lin; Li, Shu

2015-10-01

Making accurate predictions about events is an important but difficult task. Recent work suggests that people are adept at this task, making predictions that reflect surprisingly accurate knowledge of the distributions of real quantities. Across three experiments, we used an iterated learning procedure to explore the basis of this knowledge: to what extent is domain experience critical to accurate predictions and how accurate are people when faced with unfamiliar domains? In Experiment 1, two groups of participants, one resident in Australia, the other in China, predicted the values of quantities familiar to both (movie run-times), unfamiliar to both (the lengths of Pharaoh reigns), and familiar to one but unfamiliar to the other (cake baking durations and the lengths of Beijing bus routes). While predictions from both groups were reasonably accurate overall, predictions were inaccurate in the selectively unfamiliar domains and, surprisingly, predictions by the China-resident group were also inaccurate for a highly familiar domain: local bus route lengths. Focusing on bus routes, two follow-up experiments with Australia-resident groups clarified the knowledge and strategies that people draw upon, plus important determinants of accurate predictions. For unfamiliar domains, people appear to rely on extrapolating from (not simply directly applying) related knowledge. However, we show that people's predictions are subject to two sources of error: in the estimation of quantities in a familiar domain and extension to plausible values in an unfamiliar domain. We propose that the key to successful predictions is not simply domain experience itself, but explicit experience of relevant quantities.

Teacher spatial skills are linked to differences in geometry instruction.

PubMed

Otumfuor, Beryl Ann; Carr, Martha

2017-12-01

Spatial skills have been linked to better performance in mathematics. The purpose of this study was to examine the relationship between teacher spatial skills and their instruction, including teacher content and pedagogical knowledge, use of pictorial representations, and use of gestures during geometry instruction. Fifty-six middle school teachers participated in the study. The teachers were administered spatial measures of mental rotations and spatial visualization. Next, a single geometry class was videotaped. Correlational analyses revealed that spatial skills significantly correlate with teacher's use of representational gestures and content and pedagogical knowledge during instruction of geometry. Spatial skills did not independently correlate with the use of pointing gestures or the use of pictorial representations. However, an interaction term between spatial skills and content and pedagogical knowledge did correlate significantly with the use of pictorial representations. Teacher experience as measured by the number of years of teaching and highest degree did not appear to affect the relationships among the variables with the exception of the relationship between spatial skills and teacher content and pedagogical knowledge. Teachers with better spatial skills are also likely to use representational gestures and to show better content and pedagogical knowledge during instruction. Spatial skills predict pictorial representation use only as a function of content and pedagogical knowledge. © 2017 The British Psychological Society.

Mentalizing about emotion and its relationship to empathy.

PubMed

Hooker, Christine I; Verosky, Sara C; Germine, Laura T; Knight, Robert T; D'Esposito, Mark

2008-09-01

Mentalizing involves the ability to predict someone else's behavior based on their belief state. More advanced mentalizing skills involve integrating knowledge about beliefs with knowledge about the emotional impact of those beliefs. Recent research indicates that advanced mentalizing skills may be related to the capacity to empathize with others. However, it is not clear what aspect of mentalizing is most related to empathy. In this study, we used a novel, advanced mentalizing task to identify neural mechanisms involved in predicting a future emotional response based on a belief state. Subjects viewed social scenes in which one character had a False Belief and one character had a True Belief. In the primary condition, subjects were asked to predict what emotion the False Belief Character would feel if they had a full understanding about the situation. We found that neural regions related to both mentalizing and emotion were involved when predicting a future emotional response, including the superior temporal sulcus, medial prefrontal cortex, temporal poles, somatosensory related cortices (SRC), inferior frontal gyrus and thalamus. In addition, greater neural activity in primarily emotion-related regions, including right SRC and bilateral thalamus, when predicting emotional response was significantly correlated with more self-reported empathy. The findings suggest that predicting emotional response involves generating and using internal affective representations and that greater use of these affective representations when trying to understand the emotional experience of others is related to more empathy.

Persistent Genetic and Family-Wide Environmental Contributions to Early Number Knowledge and Later Achievement in Mathematics.

PubMed

Garon-Carrier, Gabrielle; Boivin, Michel; Kovas, Yulia; Feng, Bei; Brendgen, Mara; Vitaro, Frank; Séguin, Jean R; Tremblay, Richard E; Dionne, Ginette

2017-12-01

This study investigated the stable and transient genetic and environmental contributions to individual differences in number knowledge in the transition from preschool (age 5) to Grade 1 (age 7) and to the predictive association between early number knowledge and later math achievement (age 10-12). We conducted genetic simplex modeling across these three time points. Genetic variance was transmitted from preschool number knowledge to late-elementary math achievement; in addition, significant genetic innovation (i.e., new influence) occurred at ages 10 through 12 years. The shared and nonshared environmental contributions decreased during the transition from preschool to school entry, but shared and nonshared environment contributed to the continuity across time from preschool number knowledge to subsequent number knowledge and math achievement. There was no new environmental contribution at time points subsequent to preschool. Results are discussed in light of their practical implications for children who have difficulties with mathematics, as well as for preventive intervention.

The recognition of mental health disorders and its association with psychiatric scepticism, knowledge of psychiatry, and the Big Five personality factors: an investigation using the overclaiming technique.

PubMed

Swami, Viren; Persaud, Raj; Furnham, Adrian

2011-03-01

The present study examined the general public's ability to recognise mental health disorders and this ability's association with psychiatric scepticism, knowledge of psychiatry, and the Big Five personality factors. A total of 477 members of the British general public completed an overclaiming scale, in which they were asked to rate the degree to which they believed 20 mental health disorders (of which five were foils designed to resemble real disorders) were real or fake. Participants also completed a novel scale measuring psychiatric scepticism, a single-item measure of knowledge of psychiatry, and a measure of the Big Five personality factors. Results showed that participants were significantly more likely to rate foils as fake disorders than real disorders. In addition, the difference between real and foil ratings was significantly predicted by knowledge of psychiatry, psychiatric scepticism, and the Big Five personality factors of agreeableness and openness to experience. These results are discussed in relation to the overclaiming technique as a novel method to study mental health literacy.

The impact of fraction magnitude knowledge on algebra performance and learning.

PubMed

Booth, Julie L; Newton, Kristie J; Twiss-Garrity, Laura K

2014-02-01

Knowledge of fractions is thought to be crucial for success with algebra, but empirical evidence supporting this conjecture is just beginning to emerge. In the current study, Algebra 1 students completed magnitude estimation tasks on three scales (0-1 [fractions], 0-1,000,000, and 0-62,571) just before beginning their unit on equation solving. Results indicated that fraction magnitude knowledge, and not whole number knowledge, was especially related to students' pretest knowledge of equation solving and encoding of equation features. Pretest fraction knowledge was also predictive of students' improvement in equation solving and equation encoding skills. Students' placement of unit fractions (e.g., those with a numerator of 1) was not especially useful for predicting algebra performance and learning in this population. Placement of non-unit fractions was more predictive, suggesting that proportional reasoning skills might be an important link between fraction knowledge and learning algebra. Copyright © 2013 Elsevier Inc. All rights reserved.

Concussion diagnosis and management

PubMed Central

Mann, Aneetinder; Tator, Charles H.; Carson, James D.

2017-01-01

Abstract Objective To assess the knowledge of, attitudes toward, and learning needs for concussion diagnosis and management among family medicine residents. Design E-mail survey. Setting University of Toronto in Ontario. Participants Family medicine residents (N = 348). Main outcome measures To describe relationships between awareness of concussion management and lifestyle, education background, and residency placement, t tests and 2 tests were used as appropriate. Linear regression was used to compare self-reported concussion knowledge with knowledge scores. Thematic analysis was used to interpret answers to the qualitative question asking residents to describe challenges they foresee physicians facing when diagnosing and managing concussion. Results The residents who responded (n = 73, response rate 21%) correctly answered an average of 5.2 questions out of 9 (58%) regarding the diagnosis and management of concussion. Postgraduate year, sex, personal history of concussion, and clinical exposure to concussion were not significant factors in predicting the number of correct answers. Several misconceptions and knowledge gaps were revealed. Of residents who responded, 71% did not recognize chronic traumatic encephalopathy and only 63% recognized second-impact syndrome as consequences of repetitive concussions. Moreover, 32% of residents did not think that every individual with a concussion should see a physician as part of management. Knowledge scores did not predict self-reported concussion knowledge. Thematic analysis revealed 4 themes related to the challenges of concussion diagnosis and management: the nonspecificity and vagueness of symptoms, lack of formal diagnostic criteria, patient compliance with management, and counseling patients with respect to return to play, work, or learning. Conclusion We found substantial gaps in knowledge surrounding concussion diagnosis and management among family medicine residents. This lack of knowledge should be addressed at both the undergraduate medical education level and the residency training level to improve concussion-related care and patient outcomes. PMID:28615399

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

PubMed

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

2017-11-24

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

Predictive validity of pre-admission assessments on medical student performance

PubMed Central

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

2017-01-01

Objectives To examine the predictive validity of pre-admission variables on students’ performance in a medical school in Saudi Arabia.  Methods In this retrospective study, we collected admission and college performance data for 737 students in preclinical and clinical years. Data included high school scores and other standardized test scores, such as those of the National Achievement Test and the General Aptitude Test. Additionally, we included the scores of the Test of English as a Foreign Language (TOEFL) and the International English Language Testing System (IELTS) exams. Those datasets were then compared with college performance indicators, namely the cumulative Grade Point Average (cGPA) and progress test, using multivariate linear regression analysis. Results In preclinical years, both the National Achievement Test (p=0.04, B=0.08) and TOEFL (p=0.017, B=0.01) scores were positive predictors of cGPA, whereas the General Aptitude Test (p=0.048, B=-0.05) negatively predicted cGPA. Moreover, none of the pre-admission variables were predictive of progress test performance in the same group. On the other hand, none of the pre-admission variables were predictive of cGPA in clinical years. Overall, cGPA strongly predict-ed students’ progress test performance (p<0.001 and B=19.02). Conclusions Only the National Achievement Test and TOEFL significantly predicted performance in preclinical years. However, these variables do not predict progress test performance, meaning that they do not predict the functional knowledge reflected in the progress test. We report various strengths and deficiencies in the current medical college admission criteria, and call for employing more sensitive and valid ones that predict student performance and functional knowledge, especially in the clinical years. PMID:29176032

The effects of utility evaluations, biomedical knowledge and modernization on intention to exclusively use biomedical health facilities among rural households in Mozambique.

PubMed

Mukolo, Abraham; Cooil, Bruce; Victor, Bart

2015-08-01

In resource-limited settings, the choice between utilizing biomedical health services and/or traditional healers is critical to the success of the public health mission. In the literature, this choice has been predicted to be influenced by three major factors: knowledge about biomedical etiologies; cultural modernization; and rational choice. The current study investigated all three of these predicted determinants, applying data from a general household survey conducted in 2010 in Zambézia Province of Mozambique involving 1045 randomly sampled rural households. Overall, more respondents (N = 802) intended to continue to supplement their biomedical healthcare with traditional healer services in comparison with those intending to utilize biomedical care exclusively (N = 243). The findings strongly supported the predicted association between rational utility (measured as satisfaction with the quality of service and results from past care) with the future intention to continue to supplement or utilize biomedical care exclusively. Odds of moving away from supplementation increase by a factor of 2.5 if the respondent reported seeing their condition improve under government/private biomedical care. Odds of staying with supplementation increase by a factor 3.1 if the respondent was satisfied with traditional care and a factor of 16 if the condition had improved under traditional care. Modernization variables (education, income, religion, and Portuguese language skills) were relevant and provided a significant component of the best scientific model. Amount of biomedical knowledge was not a significant predictor of choice. There was a small effect on choice from knowing the limitations of biomedical care. The findings have implications for public healthcare promotion activities in areas where biomedical care is introduced as an alternative to traditional healing. Copyright © 2015 Elsevier Ltd. All rights reserved.

Identifying Medical Students Likely to Exhibit Poor Professionalism and Knowledge During Internship

PubMed Central

Durning, Steven J.; Cohen, Daniel L.; Cruess, David; Jackson, Jeffrey L.

2007-01-01

CONTEXT Identifying medical students who will perform poorly during residency is difficult. OBJECTIVE Determine whether commonly available data predicts low performance ratings during internship by residency program directors. DESIGN Prospective cohort involving medical school data from graduates of the Uniformed Services University (USU), surveys about experiences at USU, and ratings of their performance during internship by their program directors. SETTING Uniformed Services University. PARTICIPANTS One thousand sixty-nine graduates between 1993 and 2002. MAIN OUTCOME MEASURE(S) Residency program directors completed an 18-item survey assessing intern performance. Factor analysis of these items collapsed to 2 domains: knowledge and professionalism. These domains were scored and performance dichotomized at the 10th percentile. RESULTS Many variables showed a univariate relationship with ratings in the bottom 10% of both domains. Multivariable logistic regression modeling revealed that grades earned during the third year predicted low ratings in both knowledge (odds ratio [OR] = 4.9; 95%CI = 2.7–9.2) and professionalism (OR = 7.3; 95%CI = 4.1–13.0). USMLE step 1 scores (OR = 1.03; 95%CI = 1.01–1.05) predicted knowledge but not professionalism. The remaining variables were not independently predictive of performance ratings. The predictive ability for the knowledge and professionalism models was modest (respective area under ROC curves = 0.735 and 0.725). CONCLUSIONS A strong association exists between the third year GPA and internship ratings by program directors in professionalism and knowledge. In combination with third year grades, either the USMLE step 1 or step 2 scores predict poor knowledge ratings. Despite a wealth of available markers and a large data set, predicting poor performance during internship remains difficult. PMID:17952512

The engine of thought is a hybrid: roles of associative and structured knowledge in reasoning.

PubMed

Bright, Aimée K; Feeney, Aidan

2014-12-01

Across a range of domains in psychology different theories assume different mental representations of knowledge. For example, in the literature on category-based inductive reasoning, certain theories (e.g., Rogers & McClelland, 2004; Sloutsky & Fisher, 2008) assume that the knowledge upon which inductive inferences are based is associative, whereas others (e.g., Heit & Rubinstein, 1994; Kemp & Tenenbaum, 2009; Osherson, Smith, Wilkie, López, & Shafir, 1990) assume that knowledge is structured. In this article we investigate whether associative and structured knowledge underlie inductive reasoning to different degrees under different processing conditions. We develop a measure of knowledge about the degree of association between categories and show that it dissociates from measures of structured knowledge. In Experiment 1 participants rated the strength of inductive arguments whose categories were either taxonomically or causally related. A measure of associative strength predicted reasoning when people had to respond fast, whereas causal and taxonomic knowledge explained inference strength when people responded slowly. In Experiment 2, we also manipulated whether the causal link between the categories was predictive or diagnostic. Participants preferred predictive to diagnostic arguments except when they responded under cognitive load. In Experiment 3, using an open-ended induction paradigm, people generated and evaluated their own conclusion categories. Inductive strength was predicted by associative strength under heavy cognitive load, whereas an index of structured knowledge was more predictive of inductive strength under minimal cognitive load. Together these results suggest that associative and structured models of reasoning apply best under different processing conditions and that the application of structured knowledge in reasoning is often effortful. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Clusters of Behaviors and Beliefs Predicting Adolescent Depression: Implications for Prevention

PubMed Central

Paunesku, David; Ellis, Justin; Fogel, Joshua; Kuwabara, Sachiko A; Gollan, Jackie; Gladstone, Tracy; Reinecke, Mark; Van Voorhees, Benjamin W.

2009-01-01

OBJECTIVE Risk factors for various disorders are known to cluster. However, the factor structure for behaviors and beliefs predicting depressive disorder in adolescents is not known. Knowledge of this structure can facilitate prevention planning. METHODS We used the National Longitudinal Study of Adolescent Health (AddHealth) data set to conduct an exploratory factor analysis to identify clusters of behaviors/experiences predicting the onset of major depressive disorder (MDD) at 1-year follow-up (N=4,791). RESULTS Four factors were identified: family/interpersonal relations, self-emancipation, avoidant problem solving/low self-worth, and religious activity. Strong family/interpersonal relations were the most significantly protective against depression at one year follow-up. Avoidant problem solving/low self-worth was not predictive of MDD on its own, but significantly amplified the risks associated with delinquency. CONCLUSION Depression prevention interventions should consider giving family relationships a more central role in their efforts. Programs teaching problem solving skills may be most appropriate for reducing MDD risk in delinquent youth. PMID:20502621

A collaborative filtering-based approach to biomedical knowledge discovery.

PubMed

Lever, Jake; Gakkhar, Sitanshu; Gottlieb, Michael; Rashnavadi, Tahereh; Lin, Santina; Siu, Celia; Smith, Maia; Jones, Martin R; Krzywinski, Martin; Jones, Steven J M; Wren, Jonathan

2018-02-15

The increase in publication rates makes it challenging for an individual researcher to stay abreast of all relevant research in order to find novel research hypotheses. Literature-based discovery methods make use of knowledge graphs built using text mining and can infer future associations between biomedical concepts that will likely occur in new publications. These predictions are a valuable resource for researchers to explore a research topic. Current methods for prediction are based on the local structure of the knowledge graph. A method that uses global knowledge from across the knowledge graph needs to be developed in order to make knowledge discovery a frequently used tool by researchers. We propose an approach based on the singular value decomposition (SVD) that is able to combine data from across the knowledge graph through a reduced representation. Using cooccurrence data extracted from published literature, we show that SVD performs better than the leading methods for scoring discoveries. We also show the diminishing predictive power of knowledge discovery as we compare our predictions with real associations that appear further into the future. Finally, we examine the strengths and weaknesses of the SVD approach against another well-performing system using several predicted associations. All code and results files for this analysis can be accessed at https://github.com/jakelever/knowledgediscovery. sjones@bcgsc.ca. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

An investigation of meaningful understanding and effectiveness of the implementation of Piagetian and Ausubelian theories in physics instruction

NASA Astrophysics Data System (ADS)

Williams, Karen Ann

One section of college students (N = 25) enrolled in an algebra-based physics course was selected for a Piagetian-based learning cycle (LC) treatment while a second section (N = 25) studied in an Ausubelian-based meaningful verbal reception learning treatment (MVRL). This study examined the students' overall (concept + problem solving + mental model) meaningful understanding of force, density/Archimedes Principle, and heat. Also examined were students' meaningful understanding as measured by conceptual questions, problems, and mental models. In addition, students' learning orientations were examined. There were no significant posttest differences between the LC and MVRL groups for students' meaningful understanding or learning orientation. Piagetian and Ausubelian theories explain meaningful understanding for each treatment. Students from each treatment increased their meaningful understanding. However, neither group altered their learning orientation. The results of meaningful understanding as measured by conceptual questions, problem solving, and mental models were mixed. Differences were attributed to the weaknesses and strengths of each treatment. This research also examined four variables (treatment, reasoning ability, learning orientation, and prior knowledge) to find which best predicted students' overall meaningful understanding of physics concepts. None of these variables were significant predictors at the.05 level. However, when the same variables were used to predict students' specific understanding (i.e. concept, problem solving, or mental model understanding), the results were mixed. For forces and density/Archimedes Principle, prior knowledge and reasoning ability significantly predicted students' conceptual understanding. For heat, however, reasoning ability was the only significant predictor of concept understanding. Reasoning ability and treatment were significant predictors of students' problem solving for heat and forces. For density/Archimedes Principle, treatment was the only significant predictor of students' problem solving. None of the variables were significant predictors of mental model understanding. This research suggested that Piaget and Ausubel used different terminology to describe learning yet these theories are similar. Further research is needed to validate this premise and validate the blending of the two theories.

Effects of dialectical behavior therapy skills training on outcomes for mental health staff in a child and adolescent residential setting

PubMed Central

Haynos, Ann F.; Fruzzetti, Alan E.; Anderson, Calli; Briggs, David; Walenta, Jason

2017-01-01

Training in Dialectical Behavior Therapy (DBT) skills coaching is desirable for staff in psychiatric settings, due to the efficacy of DBT in treating difficult patient populations. In such settings, training resources are typically limited, and staff turnover is high, necessitating brief training. This study evaluated the effects of a brief training in DBT skills coaching for nursing staff working in a child and adolescent psychiatric residential program. Nursing staff (n = 22) completed assessments of DBT skill knowledge, burnout, and stigma towards patients with borderline personality disorder (BPD) before and after a six-week DBT skills coaching training. Repeated measure ANOVAs were conducted to examine changes on all measures from pre- to post- treatment and hierarchical linear regressions to examine relationships between pre- training DBT knowledge, burnout, and BPD stigma and these same measures post-training. The brief DBT skill coaching training significantly increased DBT knowledge (p = .007) and decreased staff personal (p = .02) and work (p = .03) burnout and stigma towards BPD patients (p = .02). Burnout indices and BPD stigma were highly correlated at both time points (p < .001); however, while pre-training BPD stigma significantly predicted post-training client burnout (p = .04), pre-training burnout did not predict post-training BPD stigma. These findings suggest that brief training of psychiatric nursing staff in DBT skills and coaching techniques can result in significant benefits, including reduced staff burnout and stigma toward patients with BPD-related problems, and that reducing BPD stigma may particularly promote lower burnout. PMID:28751925

Effects of dialectical behavior therapy skills training on outcomes for mental health staff in a child and adolescent residential setting.

PubMed

Haynos, Ann F; Fruzzetti, Alan E; Anderson, Calli; Briggs, David; Walenta, Jason

2016-04-01

Training in Dialectical Behavior Therapy (DBT) skills coaching is desirable for staff in psychiatric settings, due to the efficacy of DBT in treating difficult patient populations. In such settings, training resources are typically limited, and staff turnover is high, necessitating brief training. This study evaluated the effects of a brief training in DBT skills coaching for nursing staff working in a child and adolescent psychiatric residential program. Nursing staff ( n = 22) completed assessments of DBT skill knowledge, burnout, and stigma towards patients with borderline personality disorder (BPD) before and after a six-week DBT skills coaching training. Repeated measure ANOVAs were conducted to examine changes on all measures from pre- to post- treatment and hierarchical linear regressions to examine relationships between pre- training DBT knowledge, burnout, and BPD stigma and these same measures post-training. The brief DBT skill coaching training significantly increased DBT knowledge ( p = .007) and decreased staff personal ( p = .02) and work ( p = .03) burnout and stigma towards BPD patients ( p = .02). Burnout indices and BPD stigma were highly correlated at both time points ( p < .001); however, while pre-training BPD stigma significantly predicted post-training client burnout ( p = .04), pre-training burnout did not predict post-training BPD stigma. These findings suggest that brief training of psychiatric nursing staff in DBT skills and coaching techniques can result in significant benefits, including reduced staff burnout and stigma toward patients with BPD-related problems, and that reducing BPD stigma may particularly promote lower burnout.

The Outcome Evaluation of a CHW Cancer Prevention Intervention: Testing Individual and Multilevel Predictors Among Hispanics Living Along the Texas-Mexico Border.

PubMed

Nimmons, Katharine; Beaudoin, Christopher E; St John, Julie A

2017-03-01

This paper evaluates the effectiveness of community health workers/promotores (CHWs) in promoting cancer preventive behaviors in the 2011-2013 Education to Promote Improved Cancer Outcomes (ÉPICO) project. The ÉPICO project utilized CHWs to disseminate cancer education to predominately Spanish-speaking Hispanics living in colonias in the Lower Rio Grande Valley of Texas. The CHWs received training to become Texas-certified CHW instructors and specialized training in message tailoring, and they delivered more than 5000 units of resident education on cancer prevention/detection, treatment, and survivorship for breast, cervical, and colorectal cancer. Using panel data to examine overtime changes in cancer knowledge among Lower Rio Grande Valley residents, the evaluation found significant changes from baseline to both times 1 and 2. Additional individual-level analysis indicated that the increase in resident cancer knowledge was predicted by residents' perceptions of CHW credibility and intention to change their lifestyles. Multilevel analysis also showed that the increase in cancer prevention knowledge among residents was predicted by attributes of the CHWs who taught them. In particular, CHWs with higher education levels had the most impact on residents' increased knowledge over time. Unexpectedly, CHWs with more years of experience were less effective teachers than their early-career counterparts.

Motivational indicators of protective behaviour in response to urban water shortage threat

NASA Astrophysics Data System (ADS)

Mankad, Aditi; Greenhill, Murni; Tucker, David; Tapsuwan, Sorada

2013-05-01

The present study examined the role of protection motivation variables in predicting rainwater tank adoption among urban householders. A regression analysis found that subjective knowledge, threat appraisal, response efficacy, response costs, subjective norms and social norms significantly predicted adaptive behavioural intentions (F(6, 399) = 50.769, p < .001, Cohen's f2 = .763). The model accounted for 43% of the variance in intentions to install a rainwater tank as a protective measure against future water shortages. Results further indicated that several variables uniquely contributed to the prediction of rainwater tank adoption (listed in order of relative contribution: response efficacy, threat appraisal, response costs, subjective knowledge and subjective norms). This suggests that people who perceive there is a real water shortage threat, and believe that rainwater tanks are effective in relieving the threat and require minimal or manageable effort to obtain, are more likely to install a tank on their property as a protective measure. Implications of these results are discussed from a research and policy perspective. Recommendations for future motivational research in the area of urban decentralised system acceptance and adoption are presented.

Genetic Knowledge Among Participants in the Coriell Personalized Medicine Collaborative.

PubMed

Schmidlen, Tara J; Scheinfeldt, Laura; Zhaoyang, Ruixue; Kasper, Rachel; Sweet, Kevin; Gordon, Erynn S; Keller, Margaret; Stack, Cathy; Gharani, Neda; Daly, Mary B; Jarvis, Joseph; Christman, Michael F

2016-04-01

Genetic literacy is essential for the effective integration of genomic information into healthcare; yet few recent studies have been conducted to assess the current state of this knowledge base. Participants in the Coriell Personalized Medicine Collaborative (CPMC), a prospective study assessing the impact of personalized genetic risk reports for complex diseases and drug response on behavior and health outcomes, completed genetic knowledge questionnaires and other surveys through an online portal. To assess the association between genetic knowledge and genetic education background, multivariate linear regression was performed. 4 062 participants completed a genetic knowledge and genetic education background questionnaire. Most were older (mean age: 50), Caucasian (90 %), female (59 %), highly educated (69 % bachelor's or higher), with annual household income over $100 000 (49 %). Mean percent correct was 76 %. Controlling for demographics revealed that health care providers, participants previously exposed to genetics, and participants with 'better than most' self-rated knowledge were significantly more likely to have a higher knowledge score (p < 0.001). Overall, genetic knowledge was high with previous genetic education experience predictive of higher genetic knowledge score. Education is likely to improve genetic literacy, an important component to expanded use of genomics in personalized medicine.

Academic Language as a Predictor Of Reading Comprehension in Monolingual Spanish-Speaking Readers: Evidence from Chilean Early Adolescents

ERIC Educational Resources Information Center

Meneses, Alejandra; Uccelli, Paola; Santelices, María Verónica; Ruiz, Marcela; Acevedo, Daniela; Figueroa, Javiera

2018-01-01

Although literacy achievement has improved in Chile, adolescents' underperformance in reading comprehension is still a serious concern. In English, core academic-language skills (CALS) have been found to significantly predict reading comprehension, even controlling for academic vocabulary knowledge. CALS are high-utility language skills that…

Gender Schema, Gender Constancy, and Sex-Stereotype Knowledge: The Roles of Cognitive Factors in Sex-Stereotype Attributions.

ERIC Educational Resources Information Center

Levy, Gary D.; Carter, D. Bruce

The present study investigated relationships between cognitive components of children's sex-role development and the bases of their attributions of sex-stereotypes to a particular gender. Specifically, it was predicted that the number of sex-stereotypes children correctly attributed would be significantly related to gender differences between the…

The Role of Feedback in the Assimilation of Information in Prediction Markets

ERIC Educational Resources Information Center

Jolly, Richard Donald

2011-01-01

Leveraging the knowledge of an organization is an ongoing challenge that has given rise to the field of knowledge management. Yet, despite spending enormous sums of organizational resources on Information Technology (IT) systems, executives recognize there is much more knowledge to harvest. Prediction markets are emerging as one tool to help…

The Roles of Occupational Knowledge and Vocational Self-Concept Crystallization in Students' School-to-Work Transition.

ERIC Educational Resources Information Center

Taylor, M. Susan

1985-01-01

Examined predictors of college students' school-to-work transition difficulty, level of occupational knowledge, and crystallization of vocational self-concept. Occupational knowledge predicted whether students received at least one job offer before graduation and the total number of offers. Self-concept crystallization predicted at least one…

Bidirectional Relations of Phonological Sensitivity and Prereading Abilities: Evidence from a Preschool Sample.

ERIC Educational Resources Information Center

Burgess, Stephen R.; Lonigan, Christopher J.

1998-01-01

Examined the relationship between phonological sensitivity and letter knowledge in 4- and 5-year-olds in a one-year longitudinal study. Found that phonological sensitivity predicted letter knowledge growth, and letter knowledge predicted phonological sensitivity growth, when controlling for age and oral language abilities. Also found that the…

Enhancing the Performance of LibSVM Classifier by Kernel F-Score Feature Selection

NASA Astrophysics Data System (ADS)

Sarojini, Balakrishnan; Ramaraj, Narayanasamy; Nickolas, Savarimuthu

Medical Data mining is the search for relationships and patterns within the medical datasets that could provide useful knowledge for effective clinical decisions. The inclusion of irrelevant, redundant and noisy features in the process model results in poor predictive accuracy. Much research work in data mining has gone into improving the predictive accuracy of the classifiers by applying the techniques of feature selection. Feature selection in medical data mining is appreciable as the diagnosis of the disease could be done in this patient-care activity with minimum number of significant features. The objective of this work is to show that selecting the more significant features would improve the performance of the classifier. We empirically evaluate the classification effectiveness of LibSVM classifier on the reduced feature subset of diabetes dataset. The evaluations suggest that the feature subset selected improves the predictive accuracy of the classifier and reduce false negatives and false positives.

Cognitive components of a mathematical processing network in 9-year-old children.

PubMed

Szűcs, Dénes; Devine, Amy; Soltesz, Fruzsina; Nobes, Alison; Gabriel, Florence

2014-07-01

We determined how various cognitive abilities, including several measures of a proposed domain-specific number sense, relate to mathematical competence in nearly 100 9-year-old children with normal reading skill. Results are consistent with an extended number processing network and suggest that important processing nodes of this network are phonological processing, verbal knowledge, visuo-spatial short-term and working memory, spatial ability and general executive functioning. The model was highly specific to predicting arithmetic performance. There were no strong relations between mathematical achievement and verbal short-term and working memory, sustained attention, response inhibition, finger knowledge and symbolic number comparison performance. Non-verbal intelligence measures were also non-significant predictors when added to our model. Number sense variables were non-significant predictors in the model and they were also non-significant predictors when entered into regression analysis with only a single visuo-spatial WM measure. Number sense variables were predicted by sustained attention. Results support a network theory of mathematical competence in primary school children and falsify the importance of a proposed modular 'number sense'. We suggest an 'executive memory function centric' model of mathematical processing. Mapping a complex processing network requires that studies consider the complex predictor space of mathematics rather than just focusing on a single or a few explanatory factors.

Cognitive components of a mathematical processing network in 9-year-old children

PubMed Central

Szűcs, Dénes; Devine, Amy; Soltesz, Fruzsina; Nobes, Alison; Gabriel, Florence

2014-01-01

We determined how various cognitive abilities, including several measures of a proposed domain-specific number sense, relate to mathematical competence in nearly 100 9-year-old children with normal reading skill. Results are consistent with an extended number processing network and suggest that important processing nodes of this network are phonological processing, verbal knowledge, visuo-spatial short-term and working memory, spatial ability and general executive functioning. The model was highly specific to predicting arithmetic performance. There were no strong relations between mathematical achievement and verbal short-term and working memory, sustained attention, response inhibition, finger knowledge and symbolic number comparison performance. Non-verbal intelligence measures were also non-significant predictors when added to our model. Number sense variables were non-significant predictors in the model and they were also non-significant predictors when entered into regression analysis with only a single visuo-spatial WM measure. Number sense variables were predicted by sustained attention. Results support a network theory of mathematical competence in primary school children and falsify the importance of a proposed modular ‘number sense’. We suggest an ‘executive memory function centric’ model of mathematical processing. Mapping a complex processing network requires that studies consider the complex predictor space of mathematics rather than just focusing on a single or a few explanatory factors. PMID:25089322

Reciprocal Associations between Parental Monitoring Knowledge and Impaired Driving in Adolescent Novice Drivers

PubMed Central

Li, Kaigang; Simons-Morton, Bruce G.; Vaca, Federico E.; Hingson, Ralph

2015-01-01

Objective Adolescent driving while alcohol/drug impaired (DWI) and parental monitoring knowledge may have notable interplay. However, the magnitude and direction of causality are unclear. This study examined possible reciprocal associations among adolescents between DWI and parental monitoring knowledge. Methods The data were from waves 1, 2 and 3 (W1, W2 and W3) of the NEXT Generation Health Study, with longitudinal assessment of a nationally representative sample of 10th graders starting in 2009-2010 (n = 2,525 at W1) and analyzed in 2014. Those who had obtained an independent/unsupervised driving license were included for the analysis. Autoregressive cross-lagged path analysis was used to examine potential reciprocal associations between DWI and parental monitoring knowledge of both mothers and fathers, controlling for potential confounders. Results Stability of fathers' and mothers' monitoring knowledge across three consecutive interview waves was identified. W1 monitoring knowledge of both fathers and mothers was prospectively associated with DWI at W2, but not for W2 with W3. A significant negative association between adolescent DWI at W2 and mother's monitoring knowledge at W3 was found, but not between W1 and W2. None of the associations between DWI and father's monitoring knowledge from W1 to W2, and from W2 to W3 were significant. Conclusions Early (10th grade) parental monitoring knowledge may predict lower adolescent self-reported DWI in 11th grade. More notably, adolescent DWI did not seem to increase parental monitoring knowledge. Future interventions are needed to improve parental monitoring knowledge and enhance awareness of the DWI risk in their adolescent novice drivers. PMID:25941751

Fraction magnitude understanding and its unique role in predicting general mathematics achievement at two early stages of fraction instruction.

PubMed

Liu, Yingyi

2017-09-08

Prior studies on fraction magnitude understanding focused mainly on students with relatively sufficient formal instruction on fractions whose fraction magnitude understanding is relatively mature. This study fills a research gap by investigating fraction magnitude understanding in the early stages of fraction instruction. It extends previous findings to children with limited and primary formal fraction instruction. Thirty-five fourth graders with limited fraction instruction and forty fourth graders with primary fraction instruction were recruited from a Chinese primary school. Children's fraction magnitude understanding was assessed with a fraction number line estimation task. Approximate number system (ANS) acuity was assessed with a dot discrimination task. Whole number knowledge was assessed with a whole number line estimation task. General reading and mathematics achievements were collected concurrently and 1 year later. In children with limited fraction instruction, fraction representation was linear and fraction magnitude understanding was concurrently related to both ANS and whole number knowledge. In children with primary fraction instruction, fraction magnitude understanding appeared to (marginally) significantly predict general mathematics achievement 1 year later. Fraction magnitude understanding emerged early during formal instruction of fractions. ANS and whole number knowledge were related to fraction magnitude understanding when children first began to learn about fractions in school. The predictive value of fraction magnitude understanding is likely constrained by its sophistication level. © 2017 The British Psychological Society.

Science communication and vernal pool conservation: a study of local decision maker attitudes in a knowledge-action system.

PubMed

McGreavy, Bridie; Webler, Thomas; Calhoun, Aram J K

2012-03-01

In this study, we describe local decision maker attitudes towards vernal pools to inform science communication and enhance vernal pool conservation efforts. We conducted interviews with town planning board and conservation commission members (n = 9) from two towns in the State of Maine in the northeastern United States. We then mailed a questionnaire to a stratified random sample of planning board members in August and September 2007 with a response rate of 48.4% (n = 320). The majority of survey respondents favored the protection and conservation of vernal pools in their towns. Decision makers were familiar with the term "vernal pool" and demonstrated positive attitudes to vernal pools in general. General appreciation and willingness to conserve vernal pools predicted support for the 2006 revisions to the Natural Resource Protection Act regulating Significant Vernal Pools. However, 48% of respondents were unaware of this law and neither prior knowledge of the law nor workshop attendance predicted support for the vernal pool law. Further, concerns about private property rights and development restrictions predicted disagreement with the vernal pool law. We conclude that science communication must rely on specific frames of reference, be sensitive to cultural values, and occur in an iterative system to link knowledge and action in support of vernal pool conservation. Copyright © 2011 Elsevier Ltd. All rights reserved.

Approaches to highly parameterized inversion: A guide to using PEST for model-parameter and predictive-uncertainty analysis

USGS Publications Warehouse

Doherty, John E.; Hunt, Randall J.; Tonkin, Matthew J.

2010-01-01

Analysis of the uncertainty associated with parameters used by a numerical model, and with predictions that depend on those parameters, is fundamental to the use of modeling in support of decisionmaking. Unfortunately, predictive uncertainty analysis with regard to models can be very computationally demanding, due in part to complex constraints on parameters that arise from expert knowledge of system properties on the one hand (knowledge constraints) and from the necessity for the model parameters to assume values that allow the model to reproduce historical system behavior on the other hand (calibration constraints). Enforcement of knowledge and calibration constraints on parameters used by a model does not eliminate the uncertainty in those parameters. In fact, in many cases, enforcement of calibration constraints simply reduces the uncertainties associated with a number of broad-scale combinations of model parameters that collectively describe spatially averaged system properties. The uncertainties associated with other combinations of parameters, especially those that pertain to small-scale parameter heterogeneity, may not be reduced through the calibration process. To the extent that a prediction depends on system-property detail, its postcalibration variability may be reduced very little, if at all, by applying calibration constraints; knowledge constraints remain the only limits on the variability of predictions that depend on such detail. Regrettably, in many common modeling applications, these constraints are weak. Though the PEST software suite was initially developed as a tool for model calibration, recent developments have focused on the evaluation of model-parameter and predictive uncertainty. As a complement to functionality that it provides for highly parameterized inversion (calibration) by means of formal mathematical regularization techniques, the PEST suite provides utilities for linear and nonlinear error-variance and uncertainty analysis in these highly parameterized modeling contexts. Availability of these utilities is particularly important because, in many cases, a significant proportion of the uncertainty associated with model parameters-and the predictions that depend on them-arises from differences between the complex properties of the real world and the simplified representation of those properties that is expressed by the calibrated model. This report is intended to guide intermediate to advanced modelers in the use of capabilities available with the PEST suite of programs for evaluating model predictive error and uncertainty. A brief theoretical background is presented on sources of parameter and predictive uncertainty and on the means for evaluating this uncertainty. Applications of PEST tools are then discussed for overdetermined and underdetermined problems, both linear and nonlinear. PEST tools for calculating contributions to model predictive uncertainty, as well as optimization of data acquisition for reducing parameter and predictive uncertainty, are presented. The appendixes list the relevant PEST variables, files, and utilities required for the analyses described in the document.

Improving childcare staff management of acute asthma exacerbation - An Australian pilot study.

PubMed

Soo, Yien Yien; Luckie, Kate Helen; Saini, Bandana; Kritikos, Vicky; Brannan, John D; Moles, Rebekah Jane

2017-09-01

This study aimed to evaluate the effectiveness of an asthma first-aid training tool for childcare staff in Australia. The effects of training on both asthma knowledge and skills were assessed. A pre/post-study design was utilised to assess changes in asthma knowledge and asthma first-aid skills in childcare staff before and after an educational intervention. Asthma first-aid skills were assessed from the participant's response to two scenarios in which a child was having a severe exacerbation of asthma. Asthma knowledge and asthma skills scores were collected at base-line and 3 weeks post the education session, which involved feedback on each individual's skills and a brief lecture on asthma delivered via PowerPoint presentation. There was a significant improvement after intervention in asthma knowledge (Z = -3.638, p < 0.001) and asthma first-aid skills for both scenario 1 (Z = -6.012, p < 0.001) and scenario 2 (Z = -6.018, p < 0.001). In scenario 1 and 2, first-aid skills improved by 65% (p < 0.001) and 57% (p < 0.001), respectively. Asthma knowledge was high at baseline (79%) and increased by 7% (p < 0.001) after the educational intervention. These asthma knowledge results were not significant when adjusted for prior knowledge. Results suggest that knowledge assessment alone may not predict the practical skills needed for asthma first-aid. Skills assessment is a useful adjunct to knowledge assessment when gauging the ability of childcare staff to manage acute asthma exacerbation. Skills assessment could be considered for incorporation into future educational interventions to improve management of acute asthma exacerbation.

Predictors of Self-Efficacy for HIV Prevention Among Hispanic Women in South Florida

PubMed Central

Villegas, Natalia; Cianelli, Rosina; Gonzalez-Guarda, Rosa; Kaelber, Lorena; Ferrer, Lilian; Peragallo, Nilda

2012-01-01

Self-efficacy is a critical element for HIV prevention, however little is known about the predictors of self-efficacy for HIV prevention among Hispanic women. In this cross-sectional study we assessed if age, living with a partner, employment status, HIV knowledge, self-esteem, and intimate partner violence (IPV) predicted self-efficacy for HIV prevention in 548 Hispanic women in South Florida who participated in a randomized controlled trial (SEPA). The majority of Hispanic women reported high levels of self-efficacy for HIV prevention. Women who were older, living with a partner, with less HIV knowledge, and a history of IPV reported significantly lower levels of self-efficacy for HIV prevention. HIV knowledge was the most important predictor of self-efficacy for HIV prevention. Employment was not a significant predictor of self-efficacy for HIV prevention. Predictors identified in the study can be used to identify high-risk Hispanic women who are in need of HIV prevention interventions. PMID:22795758

Text messaging versus email for emergency medicine residents’ knowledge retention: a pilot comparison in the United States

PubMed Central

2016-01-01

We evaluated the effectiveness of text messaging versus email, as a delivery method to enhance knowledge retention of emergency medicine (EM) content in EM residents. We performed a multi-centered, prospective, randomized study consisting of postgraduate year (PGY) 1 to PGY 3 & 4 residents in three United States EM residency programs in 2014. Fifty eight residents were randomized into one delivery group: text message or email. Participants completed a 40 question pre- and post-intervention exam. Primary outcomes were the means of pre- and post-intervention exam score differences. Data were analyzed using descriptive statistics, paired t-test, and multiple linear regressions. No significant difference was found between the primary outcomes of the two groups (P=0.51). PGY 2 status had a significant negative effect (P=0.01) on predicted exam score difference. Neither delivery method enhanced resident knowledge retention. Further research on implementation of mobile technology in residency education is required. PMID:27780350

Text messaging versus email for emergency medicine residents' knowledge retention: a pilot comparison in the United States.

PubMed

Hoonpongsimanont, Wirachin; Kulkarni, Miriam; Tomas-Domingo, Pedro; Anderson, Craig; McCormack, Denise; Tu, Khoa; Chakravarthy, Bharath; Lotfipour, Shahram

2016-01-01

We evaluated the effectiveness of text messaging versus email, as a delivery method to enhance knowledge retention of emergency medicine (EM) content in EM residents. We performed a multi-centered, prospective, randomized study consisting of postgraduate year (PGY) 1 to PGY 3 & 4 residents in three United States EM residency programs in 2014. Fifty eight residents were randomized into one delivery group: text message or email. Participants completed a 40 question pre- and post-intervention exam. Primary outcomes were the means of pre- and post-intervention exam score differences. Data were analyzed using descriptive statistics, paired t-test, and multiple linear regressions. No significant difference was found between the primary outcomes of the two groups (P=0.51). PGY 2 status had a significant negative effect (P=0.01) on predicted exam score difference. Neither delivery method enhanced resident knowledge retention. Further research on implementation of mobile technology in residency education is required.

Cognitive person variables in the delay of gratification of older children at risk.

PubMed

Rodriguez, M L; Mischel, W; Shoda, Y

1989-08-01

The components of self-regulation were analyzed, extending the self-imposed delay of gratification paradigm to older children with social adjustment problems. Delay behavior was related to a network of conceptually relevant cognitive person variables, consisting of attention deployment strategies during delay, knowledge of delay rules, and intelligence. A positive relationship was demonstrated between concurrent indexes of intelligence, attention deployment, and actual delay time. Moreover, attention deployment, measured as an individual differences variable during the delay process, had a direct, positive effect on delay behavior. Specifically, as the duration of delay and the frustration of the situation increased, children who spent a higher proportion of the time distracting themselves from the tempting elements of the delay situation were able to delay longer. The effect of attention deployment on delay behavior was significant even when age, intelligence, and delay rule knowledge were controlled. Likewise, delay rule knowledge significantly predicted delay time, even when age, attention deployment, and intelligence were controlled.

Knowledge-driven genomic interactions: an application in ovarian cancer.

PubMed

Kim, Dokyoon; Li, Ruowang; Dudek, Scott M; Frase, Alex T; Pendergrass, Sarah A; Ritchie, Marylyn D

2014-01-01

Effective cancer clinical outcome prediction for understanding of the mechanism of various types of cancer has been pursued using molecular-based data such as gene expression profiles, an approach that has promise for providing better diagnostics and supporting further therapies. However, clinical outcome prediction based on gene expression profiles varies between independent data sets. Further, single-gene expression outcome prediction is limited for cancer evaluation since genes do not act in isolation, but rather interact with other genes in complex signaling or regulatory networks. In addition, since pathways are more likely to co-operate together, it would be desirable to incorporate expert knowledge to combine pathways in a useful and informative manner. Thus, we propose a novel approach for identifying knowledge-driven genomic interactions and applying it to discover models associated with cancer clinical phenotypes using grammatical evolution neural networks (GENN). In order to demonstrate the utility of the proposed approach, an ovarian cancer data from the Cancer Genome Atlas (TCGA) was used for predicting clinical stage as a pilot project. We identified knowledge-driven genomic interactions associated with cancer stage from single knowledge bases such as sources of pathway-pathway interaction, but also knowledge-driven genomic interactions across different sets of knowledge bases such as pathway-protein family interactions by integrating different types of information. Notably, an integration model from different sources of biological knowledge achieved 78.82% balanced accuracy and outperformed the top models with gene expression or single knowledge-based data types alone. Furthermore, the results from the models are more interpretable because they are framed in the context of specific biological pathways or other expert knowledge. The success of the pilot study we have presented herein will allow us to pursue further identification of models predictive of clinical cancer survival and recurrence. Understanding the underlying tumorigenesis and progression in ovarian cancer through the global view of interactions within/between different biological knowledge sources has the potential for providing more effective screening strategies and therapeutic targets for many types of cancer.

Language and theory of mind in autism spectrum disorder: the relationship between complement syntax and false belief task performance.

PubMed

Lind, Sophie E; Bowler, Dermot M

2009-06-01

This study aimed to test the hypothesis that children with autism spectrum disorder (ASD) use their knowledge of complement syntax as a means of "hacking out" solutions to false belief tasks, despite lacking a representational theory of mind (ToM). Participants completed a "memory for complements" task, a measure of receptive vocabulary, and traditional location change and unexpected contents false belief tasks. Consistent with predictions, the correlation between complement syntax score and location change task performance was significantly stronger within the ASD group than within the comparison group. However, contrary to predictions, complement syntax score was not significantly correlated with unexpected contents task performance within either group. Possible explanations for this pattern of results are considered.

Development and Evaluation of Season-ahead Precipitation and Streamflow Predictions for Sectoral Management in Western Ethiopia

NASA Astrophysics Data System (ADS)

Block, P. J.; Alexander, S.; WU, S.

2017-12-01

Skillful season-ahead predictions conditioned on local and large-scale hydro-climate variables can provide valuable knowledge to farmers and reservoir operators, enabling informed water resource allocation and management decisions. In Ethiopia, the potential for advancing agriculture and hydropower management, and subsequently economic growth, is substantial, yet evidence suggests a weak adoption of prediction information by sectoral audiences. To address common critiques, including skill, scale, and uncertainty, probabilistic forecasts are developed at various scales - temporally and spatially - for the Finchaa hydropower dam and the Koga agricultural scheme in an attempt to promote uptake and application. Significant prediction skill is evident across scales, particularly for statistical models. This raises questions regarding other potential barriers to forecast utilization at community scales, which are also addressed.

Active engagement in a web-based tutorial to prevent obesity grounded in Fuzzy-Trace Theory predicts higher knowledge and gist comprehension.

PubMed

Brust-Renck, Priscila G; Reyna, Valerie F; Wilhelms, Evan A; Wolfe, Christopher R; Widmer, Colin L; Cedillos-Whynott, Elizabeth M; Morant, A Kate

2017-08-01

We used Sharable Knowledge Objects (SKOs) to create an Intelligent Tutoring System (ITS) grounded in Fuzzy-Trace Theory to teach women about obesity prevention: GistFit, getting the gist of healthy eating and exercise. The theory predicts that reliance on gist mental representations (as opposed to verbatim) is more effective in reducing health risks and improving decision making. Technical information was translated into decision-relevant gist representations and gist principles (i.e., healthy values). The SKO was hypothesized to facilitate extracting these gist representations and principles by engaging women in dialogue, "understanding" their responses, and replying appropriately to prompt additional engagement. Participants were randomly assigned to either the obesity prevention tutorial (GistFit) or a control tutorial containing different content using the same technology. Participants were administered assessments of knowledge about nutrition and exercise, gist comprehension, gist principles, behavioral intentions and self-reported behavior. An analysis of engagement in tutorial dialogues and responses to multiple-choice questions to check understanding throughout the tutorial revealed significant correlations between these conversations and scores on subsequent knowledge tests and gist comprehension. Knowledge and comprehension measures correlated with healthier behavior and greater intentions to perform healthy behavior. Differences between GistFit and control tutorials were greater for participants who engaged more fully. Thus, results are consistent with the hypothesis that active engagement with a new gist-based ITS, rather than a passive memorization of verbatim details, was associated with an array of known psychosocial mediators of preventive health decisions, such as knowledge acquisition, and gist comprehension.

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

ERIC Educational Resources Information Center

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

2015-01-01

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

Prediction of Slot Shape and Slot Size for Improving the Performance of Microstrip Antennas Using Knowledge-Based Neural Networks.

PubMed

Khan, Taimoor; De, Asok

2014-01-01

In the last decade, artificial neural networks have become very popular techniques for computing different performance parameters of microstrip antennas. The proposed work illustrates a knowledge-based neural networks model for predicting the appropriate shape and accurate size of the slot introduced on the radiating patch for achieving desired level of resonance, gain, directivity, antenna efficiency, and radiation efficiency for dual-frequency operation. By incorporating prior knowledge in neural model, the number of required training patterns is drastically reduced. Further, the neural model incorporated with prior knowledge can be used for predicting response in extrapolation region beyond the training patterns region. For validation, a prototype is also fabricated and its performance parameters are measured. A very good agreement is attained between measured, simulated, and predicted results.

Prediction of Slot Shape and Slot Size for Improving the Performance of Microstrip Antennas Using Knowledge-Based Neural Networks

PubMed Central

De, Asok

2014-01-01

In the last decade, artificial neural networks have become very popular techniques for computing different performance parameters of microstrip antennas. The proposed work illustrates a knowledge-based neural networks model for predicting the appropriate shape and accurate size of the slot introduced on the radiating patch for achieving desired level of resonance, gain, directivity, antenna efficiency, and radiation efficiency for dual-frequency operation. By incorporating prior knowledge in neural model, the number of required training patterns is drastically reduced. Further, the neural model incorporated with prior knowledge can be used for predicting response in extrapolation region beyond the training patterns region. For validation, a prototype is also fabricated and its performance parameters are measured. A very good agreement is attained between measured, simulated, and predicted results. PMID:27382616

Predicting the Geometry Knowledge of Pre-Service Elementary Teachers

ERIC Educational Resources Information Center

Duatepe Aksu, Asuman

2013-01-01

In this study, the aim was to examine the factors that predict the geometry knowledge of pre-service elementary teachers. Data was collected on 387 pre-service elementary teachers from four universities by using a geometry knowledge test, the van Hiele geometric thinking level test, a geometry self efficacy scale and a geometry attitude scale.…

The effect of intimate exposure to alcohol abuse on the acquisition of knowledge about drinking.

PubMed

Rainer, J P

1994-01-01

This study explored how an alcohol education program might be structured to effectively educate college students about the consequences of alcohol use. The primary hypothesis tested stated that individuals would vary significantly in the amount of knowledge learned from a structured alcohol education workshop, based on the degree of familial or social exposure s/he has had to alcohol abuse. Social learning variables of locus of control, dogmatism, and expectancy for risk were tested for interaction with degree of exposure, to determine their influence on learning. A pretest-posttest control group was employed with a sample of 66 undergraduate college students. A four hour alcohol education program was administered to teach cognitive information and fact about alcohol, with a goal of facilitating responsible use/nonuse of alcohol. The Student Drinking Questionnaire measured acquisition of knowledge. The Adult Nowicki-Strickland Internal/External Scale measured locus of control, and Schultze's Short Dogmatism Scale measured dogmatism. The researcher developed an instrument for expectancy for risk. Multiple regression analyses yielded prediction equations for the variables under study. For the sample group, results demonstrated that a significant portion of the variance in the residualized posttest scores was accounted for by level of exposure and dogmatism. When the sample was blocked according to intimate or social exposure, dogmatism was the only construct entering the regression equation at a significant level for the intimate exposure group. None of the constructs were able to predict any of the residualized posttest scores for the social exposure group. It was concluded that: (1) Students in the sample learned differentially based on the degree of intimate exposure of alcohol; (2) Dogmatism is a moderating variable with acquisition of knowledge for those intimately exposed to alcohol abuse, but locus of control and expectancy for risk are not; and (3) Further research is needed to study the effects of differential learning goals set for different populations.

Do knowledge and cultural perceptions of modern female contraceptives predict male involvement in Ayete, Nigeria?

PubMed

Sanusi, A; Akinyemi, Oluwaseun O; Onoviran, Oghemetega O

2014-12-01

Male involvement is crucial to female contraceptive use. This study examined how male knowledge and cultural perceptions of modern female contraceptives influence involvement in contraceptive use. A cross-sectional survey of 389 men from Ayete, Nigeria was used to regress a continuous male involvement score on demographic variables, knowledge of at least one method of modern female contraception and a scored male perception variable using Ordinary Least Squares regression. Controlling for perception, the knowledge of at least one method of modern female contraception was not significantly associated with a change in male involvement (p=0.264). Increasing positive perception was associated with higher male involvement scores (p=0.001). Higher educated males, those with a current desire to have children and males whose partners were currently using a method had greater male involvement scores (p<0.05). Policy and intervention efforts should be focused on changing cultural perceptions, in addition to providing in-depth knowledge of contraceptive methods.

A knowledge-driven probabilistic framework for the prediction of protein-protein interaction networks.

PubMed

Browne, Fiona; Wang, Haiying; Zheng, Huiru; Azuaje, Francisco

2010-03-01

This study applied a knowledge-driven data integration framework for the inference of protein-protein interactions (PPI). Evidence from diverse genomic features is integrated using a knowledge-driven Bayesian network (KD-BN). Receiver operating characteristic (ROC) curves may not be the optimal assessment method to evaluate a classifier's performance in PPI prediction as the majority of the area under the curve (AUC) may not represent biologically meaningful results. It may be of benefit to interpret the AUC of a partial ROC curve whereby biologically interesting results are represented. Therefore, the novel application of the assessment method referred to as the partial ROC has been employed in this study to assess predictive performance of PPI predictions along with calculating the True positive/false positive rate and true positive/positive rate. By incorporating domain knowledge into the construction of the KD-BN, we demonstrate improvement in predictive performance compared with previous studies based upon the Naive Bayesian approach. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Investigating elementary principals' science beliefs and knowledge and its relationship to students' science outcomes

NASA Astrophysics Data System (ADS)

Khan, Uzma Zafar

The aim of this quantitative study was to investigate elementary principals' beliefs about reformed science teaching and learning, science subject matter knowledge, and how these factors relate to fourth grade students' superior science outcomes. Online survey methodology was used for data collection and included a demographic questionnaire and two survey instruments: the K-4 Physical Science Misconceptions Oriented Science Assessment Resources for Teachers (MOSART) and the Beliefs About Reformed Science Teaching and Learning (BARSTL). Hierarchical multiple regression analysis was used to assess the separate and collective contributions of background variables such as principals' personal and school characteristics, principals' science teaching and learning beliefs, and principals' science knowledge on students' superior science outcomes. Mediation analysis was also used to explore whether principals' science knowledge mediated the relationship between their beliefs about science teaching and learning and students' science outcomes. Findings indicated that principals' science beliefs and knowledge do not contribute to predicting students' superior science scores. Fifty-two percent of the variance in percentage of students with superior science scores was explained by school characteristics with free or reduced price lunch and school type as the only significant individual predictors. Furthermore, principals' science knowledge did not mediate the relationship between their science beliefs and students' science outcomes. There was no statistically significant variation among the variables. The data failed to support the proposed mediation model of the study. Implications for future research are discussed.

A strategy to establish Food Safety Model Repositories.

PubMed

Plaza-Rodríguez, C; Thoens, C; Falenski, A; Weiser, A A; Appel, B; Kaesbohrer, A; Filter, M

2015-07-02

Transferring the knowledge of predictive microbiology into real world food manufacturing applications is still a major challenge for the whole food safety modelling community. To facilitate this process, a strategy for creating open, community driven and web-based predictive microbial model repositories is proposed. These collaborative model resources could significantly improve the transfer of knowledge from research into commercial and governmental applications and also increase efficiency, transparency and usability of predictive models. To demonstrate the feasibility, predictive models of Salmonella in beef previously published in the scientific literature were re-implemented using an open source software tool called PMM-Lab. The models were made publicly available in a Food Safety Model Repository within the OpenML for Predictive Modelling in Food community project. Three different approaches were used to create new models in the model repositories: (1) all information relevant for model re-implementation is available in a scientific publication, (2) model parameters can be imported from tabular parameter collections and (3) models have to be generated from experimental data or primary model parameters. All three approaches were demonstrated in the paper. The sample Food Safety Model Repository is available via: http://sourceforge.net/projects/microbialmodelingexchange/files/models and the PMM-Lab software can be downloaded from http://sourceforge.net/projects/pmmlab/. This work also illustrates that a standardized information exchange format for predictive microbial models, as the key component of this strategy, could be established by adoption of resources from the Systems Biology domain. Copyright © 2015. Published by Elsevier B.V.

The Role of Knowledge and Risk Beliefs in Adolescent E-Cigarette Use: A Pilot Study

PubMed Central

Rohde, Jacob A.; Noar, Seth M.; Horvitz, Casey; Cornacchione Ross, Jennifer; Sutfin, Erin L.

2018-01-01

The use of e-cigarettes and other vaping devices among adolescents is an urgent public health problem due to the concern about adolescent exposure to nicotine. This study examined: (1) adolescents’ knowledge and beliefs about e-cigarette risks; and (2) whether knowledge and risk beliefs were associated with e-cigarette use. N = 69 adolescents completed a cross-sectional survey about e-cigarette knowledge, attitudes (i.e., risk beliefs), and behavior (KAB). Nearly half (47%) of the sample reported ever using e-cigarettes. The majority of adolescents knew about many of the risks of e-cigarettes, with no differences between never- and ever-users. However, risk beliefs, such as worrying about health risks of using e-cigarettes, varied across groups. Compared to never-users, e-cigarette ever-users were significantly less likely to worry about e-cigarette health risks, less likely to think that e-cigarettes would cause them negative health consequences, and less likely to believe that e-cigarette use would lead to addiction. In a multivariable logistic regression, prior combustible cigarette use, mother’s education, and addiction risk beliefs about e-cigarettes emerged as significant predictors of adolescents’ e-cigarette use. This study reveals that while knowledge is not associated with adolescent e-cigarette use, risk beliefs do predict use. PMID:29690606

The Role of Knowledge and Risk Beliefs in Adolescent E-Cigarette Use: A Pilot Study.

PubMed

Rohde, Jacob A; Noar, Seth M; Horvitz, Casey; Lazard, Allison J; Cornacchione Ross, Jennifer; Sutfin, Erin L

2018-04-23

The use of e-cigarettes and other vaping devices among adolescents is an urgent public health problem due to the concern about adolescent exposure to nicotine. This study examined: (1) adolescents’ knowledge and beliefs about e-cigarette risks; and (2) whether knowledge and risk beliefs were associated with e-cigarette use. N = 69 adolescents completed a cross-sectional survey about e-cigarette knowledge, attitudes (i.e., risk beliefs), and behavior (KAB). Nearly half (47%) of the sample reported ever using e-cigarettes. The majority of adolescents knew about many of the risks of e-cigarettes, with no differences between never- and ever-users. However, risk beliefs, such as worrying about health risks of using e-cigarettes, varied across groups. Compared to never-users, e-cigarette ever-users were significantly less likely to worry about e-cigarette health risks, less likely to think that e-cigarettes would cause them negative health consequences, and less likely to believe that e-cigarette use would lead to addiction. In a multivariable logistic regression, prior combustible cigarette use, mother’s education, and addiction risk beliefs about e-cigarettes emerged as significant predictors of adolescents’ e-cigarette use. This study reveals that while knowledge is not associated with adolescent e-cigarette use, risk beliefs do predict use.

Empirical models for the prediction of ground motion duration for intraplate earthquakes

NASA Astrophysics Data System (ADS)

Anbazhagan, P.; Neaz Sheikh, M.; Bajaj, Ketan; Mariya Dayana, P. J.; Madhura, H.; Reddy, G. R.

2017-07-01

Many empirical relationships for the earthquake ground motion duration were developed for interplate region, whereas only a very limited number of empirical relationships exist for intraplate region. Also, the existing relationships were developed based mostly on the scaled recorded interplate earthquakes to represent intraplate earthquakes. To the author's knowledge, none of the existing relationships for the intraplate regions were developed using only the data from intraplate regions. Therefore, an attempt is made in this study to develop empirical predictive relationships of earthquake ground motion duration (i.e., significant and bracketed) with earthquake magnitude, hypocentral distance, and site conditions (i.e., rock and soil sites) using the data compiled from intraplate regions of Canada, Australia, Peninsular India, and the central and southern parts of the USA. The compiled earthquake ground motion data consists of 600 records with moment magnitudes ranging from 3.0 to 6.5 and hypocentral distances ranging from 4 to 1000 km. The non-linear mixed-effect (NLMEs) and logistic regression techniques (to account for zero duration) were used to fit predictive models to the duration data. The bracketed duration was found to be decreased with an increase in the hypocentral distance and increased with an increase in the magnitude of the earthquake. The significant duration was found to be increased with the increase in the magnitude and hypocentral distance of the earthquake. Both significant and bracketed durations were predicted higher in rock sites than in soil sites. The predictive relationships developed herein are compared with the existing relationships for interplate and intraplate regions. The developed relationship for bracketed duration predicts lower durations for rock and soil sites. However, the developed relationship for a significant duration predicts lower durations up to a certain distance and thereafter predicts higher durations compared to the existing relationships.

In silico tools for sharing data and knowledge on toxicity and metabolism: derek for windows, meteor, and vitic.

PubMed

Marchant, Carol A; Briggs, Katharine A; Long, Anthony

2008-01-01

ABSTRACT Lhasa Limited is a not-for-profit organization that exists to promote the sharing of data and knowledge in chemistry and the life sciences. It has developed the software tools Derek for Windows, Meteor, and Vitic to facilitate such sharing. Derek for Windows and Meteor are knowledge-based expert systems that predict the toxicity and metabolism of a chemical, respectively. Vitic is a chemically intelligent toxicity database. An overview of each software system is provided along with examples of the sharing of data and knowledge in the context of their development. These examples include illustrations of (1) the use of data entry and editing tools for the sharing of data and knowledge within organizations; (2) the use of proprietary data to develop nonconfidential knowledge that can be shared between organizations; (3) the use of shared expert knowledge to refine predictions; (4) the sharing of proprietary data between organizations through the formation of data-sharing groups; and (5) the use of proprietary data to validate predictions. Sharing of chemical toxicity and metabolism data and knowledge in this way offers a number of benefits including the possibilities of faster scientific progress and reductions in the use of animals in testing. Maximizing the accessibility of data also becomes increasingly crucial as in silico systems move toward the prediction of more complex phenomena for which limited data are available.

The cure: design and evaluation of a crowdsourcing game for gene selection for breast cancer survival prediction.

PubMed

Good, Benjamin M; Loguercio, Salvatore; Griffith, Obi L; Nanis, Max; Wu, Chunlei; Su, Andrew I

2014-07-29

Molecular signatures for predicting breast cancer prognosis could greatly improve care through personalization of treatment. Computational analyses of genome-wide expression datasets have identified such signatures, but these signatures leave much to be desired in terms of accuracy, reproducibility, and biological interpretability. Methods that take advantage of structured prior knowledge (eg, protein interaction networks) show promise in helping to define better signatures, but most knowledge remains unstructured. Crowdsourcing via scientific discovery games is an emerging methodology that has the potential to tap into human intelligence at scales and in modes unheard of before. The main objective of this study was to test the hypothesis that knowledge linking expression patterns of specific genes to breast cancer outcomes could be captured from players of an open, Web-based game. We envisioned capturing knowledge both from the player's prior experience and from their ability to interpret text related to candidate genes presented to them in the context of the game. We developed and evaluated an online game called The Cure that captured information from players regarding genes for use as predictors of breast cancer survival. Information gathered from game play was aggregated using a voting approach, and used to create rankings of genes. The top genes from these rankings were evaluated using annotation enrichment analysis, comparison to prior predictor gene sets, and by using them to train and test machine learning systems for predicting 10 year survival. Between its launch in September 2012 and September 2013, The Cure attracted more than 1000 registered players, who collectively played nearly 10,000 games. Gene sets assembled through aggregation of the collected data showed significant enrichment for genes known to be related to key concepts such as cancer, disease progression, and recurrence. In terms of the predictive accuracy of models trained using this information, these gene sets provided comparable performance to gene sets generated using other methods, including those used in commercial tests. The Cure is available on the Internet. The principal contribution of this work is to show that crowdsourcing games can be developed as a means to address problems involving domain knowledge. While most prior work on scientific discovery games and crowdsourcing in general takes as a premise that contributors have little or no expertise, here we demonstrated a crowdsourcing system that succeeded in capturing expert knowledge.

Prediction of Protein Configurational Entropy (Popcoen).

PubMed

Goethe, Martin; Gleixner, Jan; Fita, Ignacio; Rubi, J Miguel

2018-03-13

A knowledge-based method for configurational entropy prediction of proteins is presented; this methodology is extremely fast, compared to previous approaches, because it does not involve any type of configurational sampling. Instead, the configurational entropy of a query fold is estimated by evaluating an artificial neural network, which was trained on molecular-dynamics simulations of ∼1000 proteins. The predicted entropy can be incorporated into a large class of protein software based on cost-function minimization/evaluation, in which configurational entropy is currently neglected for performance reasons. Software of this type is used for all major protein tasks such as structure predictions, proteins design, NMR and X-ray refinement, docking, and mutation effect predictions. Integrating the predicted entropy can yield a significant accuracy increase as we show exemplarily for native-state identification with the prominent protein software FoldX. The method has been termed Popcoen for Prediction of Protein Configurational Entropy. An implementation is freely available at http://fmc.ub.edu/popcoen/ .

Category and design fluency in mild cognitive impairment: Performance, strategy use, and neural correlates.

PubMed

Peter, Jessica; Kaiser, Jannis; Landerer, Verena; Köstering, Lena; Kaller, Christoph P; Heimbach, Bernhard; Hüll, Michael; Bormann, Tobias; Klöppel, Stefan

2016-12-01

The exploration and retrieval of words during category fluency involves different strategies to improve or maintain performance. Deficits in that task, which are common in patients with amnestic mild cognitive impairment (aMCI), mirror either impaired semantic memory or dysfunctional executive control mechanisms. Relating category fluency to tasks that place greater demands on either semantic knowledge or executive functions might help to determine the underlying cognitive process. The aims of this study were to compare performance and strategy use of 20 patients with aMCI to 30 healthy elderly controls (HC) and to identify the dominant component (either executive or semantic) for better task performance in category fluency. Thus, the relationship between category fluency, design fluency and naming was examined. As fluency tasks have been associated with the superior frontal gyrus (SFG), the inferior frontal gyrus (IFG), and the temporal pole, we further explored the relationship between gray matter volume in these areas and both performance and strategy use. Patients with aMCI showed significantly lower performance and significantly less strategy use during fluency tasks compared to HC. However, both groups equally improved their performance when repeatedly confronted with the same task. In aMCI, performance during category fluency was significantly predicted by design fluency performance, while in HC, it was significantly predicted by naming performance. In HC, volume of the SFG significantly predicted both category and design fluency performance, and strategy use during design fluency. In aMCI, the SFG and the IFG predicted performance during both category and design fluency. The IFG significantly predicted strategy use during category fluency in both groups. The reduced category fluency performance in aMCI seems to be primarily due to dysfunctional executive control mechanisms rather than impaired semantic knowledge. This finding is directly relevant to patients in the different stages of Alzheimer's disease as it links the known semantic fluency deficit in this population to executive functions. Although patients with aMCI are impaired in both performance and strategy use compared to HC, they are able to increase performance over time. However, only HC were able to significantly improve the utilization of fluency strategies in both category and design fluency over time. HC seem to rely more heavily on the SFG during fluency tasks, while in patients with aMCI additional frontal brain areas are involved, possibly reflecting compensational processes. Copyright © 2016 Elsevier Ltd. All rights reserved.

Move Your Lamp Post: Recent Data Reflects Learner Knowledge Better than Older Data

ERIC Educational Resources Information Center

Galyardt, April; Goldin, Ilya

2015-01-01

In educational technology and learning sciences, there are multiple uses for a predictive model of whether a student will perform a task correctly or not. For example, an intelligent tutoring system may use such a model to estimate whether or not a student has mastered a skill. We analyze the significance of data recency in making such…

Assessment of Preschool Early Literacy Skills: Linking Children's Educational Needs with Empirically Supported Instructional Activities

ERIC Educational Resources Information Center

Lonigan, Christopher J.; Allan, Nicholas P.; Lerner, Matthew D.

2011-01-01

The importance of the preschool period in becoming a skilled reader is highlighted by a significant body of evidence that preschool children's development in the areas of oral language, phonological awareness, and print knowledge is predictive of how well they will learn to read once they are exposed to formal reading instruction in elementary…

Current Knowledge on the Use of Computational Toxicology in Hazard Assessment of Metallic Engineered Nanomaterials.

PubMed

Chen, Guangchao; Peijnenburg, Willie; Xiao, Yinlong; Vijver, Martina G

2017-07-12

As listed by the European Chemicals Agency, the three elements in evaluating the hazards of engineered nanomaterials (ENMs) include the integration and evaluation of toxicity data, categorization and labeling of ENMs, and derivation of hazard threshold levels for human health and the environment. Assessing the hazards of ENMs solely based on laboratory tests is time-consuming, resource intensive, and constrained by ethical considerations. The adoption of computational toxicology into this task has recently become a priority. Alternative approaches such as (quantitative) structure-activity relationships ((Q)SAR) and read-across are of significant help in predicting nanotoxicity and filling data gaps, and in classifying the hazards of ENMs to individual species. Thereupon, the species sensitivity distribution (SSD) approach is able to serve the establishment of ENM hazard thresholds sufficiently protecting the ecosystem. This article critically reviews the current knowledge on the development of in silico models in predicting and classifying the hazard of metallic ENMs, and the development of SSDs for metallic ENMs. Further discussion includes the significance of well-curated experimental datasets and the interpretation of toxicity mechanisms of metallic ENMs based on reported models. An outlook is also given on future directions of research in this frontier.

The effects of speech production and vocabulary training on different components of spoken language performance.

PubMed

Paatsch, Louise E; Blamey, Peter J; Sarant, Julia Z; Bow, Catherine P

2006-01-01

A group of 21 hard-of-hearing and deaf children attending primary school were trained by their teachers on the production of selected consonants and on the meanings of selected words. Speech production, vocabulary knowledge, reading aloud, and speech perception measures were obtained before and after each type of training. The speech production training produced a small but significant improvement in the percentage of consonants correctly produced in words. The vocabulary training improved knowledge of word meanings substantially. Performance on speech perception and reading aloud were significantly improved by both types of training. These results were in accord with the predictions of a mathematical model put forward to describe the relationships between speech perception, speech production, and language measures in children (Paatsch, Blamey, Sarant, Martin, & Bow, 2004). These training data demonstrate that the relationships between the measures are causal. In other words, improvements in speech production and vocabulary performance produced by training will carry over into predictable improvements in speech perception and reading scores. Furthermore, the model will help educators identify the most effective methods of improving receptive and expressive spoken language for individual children who are deaf or hard of hearing.

Vocabulary Knowledge of Deaf and Hearing Postsecondary Students

PubMed Central

Sarchet, Thomastine; Marschark, Marc; Borgna, Georgianna; Convertino, Carol; Sapere, Patricia; Dirmyer, Richard

2014-01-01

Deaf children generally are found to have smaller English vocabularies than hearing peers, although studies involving children with cochlear implants have suggested that the gap may decrease or disappear with age. Less is known about the vocabularies of deaf and hard-of-hearing (DHH) postsecondary students or how their vocabulary knowledge relates to other aspects of academic achievement. This study used the Peabody Picture Vocabulary Test to examine the vocabulary knowledge of DHH and hearing postsecondary students as well as their awareness (predictions) of that knowledge. Relationships between vocabulary knowledge and print exposure, communication backgrounds, and reading and verbal abilities also were examined. Consistent with studies of children, hearing college students demonstrated significantly larger vocabularies than DHH students both with and without cochlear implants. DHH students were more likely to overestimate their vocabulary knowledge. Vocabulary scores were positively related to reading and verbal abilities but negatively related to sign language abilities. Among DHH students they also were positively related to measures of spoken language ability. Results are discussed in terms of related cognitive abilities, language fluency, and academic achievement of DHH students and implications for postsecondary education. PMID:25558473

Bio-knowledge based filters improve residue-residue contact prediction accuracy.

PubMed

Wozniak, P P; Pelc, J; Skrzypecki, M; Vriend, G; Kotulska, M

2018-05-29

Residue-residue contact prediction through direct coupling analysis has reached impressive accuracy, but yet higher accuracy will be needed to allow for routine modelling of protein structures. One way to improve the prediction accuracy is to filter predicted contacts using knowledge about the particular protein of interest or knowledge about protein structures in general. We focus on the latter and discuss a set of filters that can be used to remove false positive contact predictions. Each filter depends on one or a few cut-off parameters for which the filter performance was investigated. Combining all filters while using default parameters resulted for a test-set of 851 protein domains in the removal of 29% of the predictions of which 92% were indeed false positives. All data and scripts are available from http://comprec-lin.iiar.pwr.edu.pl/FPfilter/. malgorzata.kotulska@pwr.edu.pl. Supplementary data are available at Bioinformatics online.

Understanding the relationship between student attitudes and student learning

NASA Astrophysics Data System (ADS)

Cahill, Michael J.; McDaniel, Mark A.; Frey, Regina F.; Hynes, K. Mairin; Repice, Michelle; Zhao, Jiuqing; Trousil, Rebecca

2018-02-01

Student attitudes, defined as the extent to which one holds expertlike beliefs about and approaches to physics, are a major research topic in physics education research. An implicit but rarely tested assumption underlying much of this research is that student attitudes play a significant part in student learning and performance. The current study directly tested this attitude-learning link by measuring the association between incoming attitudes (Colorado Learning Attitudes about Science Survey) and student learning during the semester after statistically controlling for the effects of prior knowledge [early-semester Force Concept Inventory (FCI) or Brief Electricity and Magnetism Assessment (BEMA)]. This study spanned four different courses and included two complementary measures of student knowledge: late-semester concept inventory scores (FCI or BEMA) and exam averages. In three of the four courses, after controlling for prior knowledge, attitudes significantly predicted both late-semester concept inventory scores and exam averages, but in all cases these attitudes explained only a small amount of variance in concept-inventory and exam scores. Results indicate that after accounting for students' incoming knowledge, attitudes may uniquely but modestly relate to how much students learn and how well they perform in the course.

Predicting the conformations of peptides and proteins in early evolution. A review article submitted to Biology Direct

PubMed Central

Milner-White, E James; Russell, Michael J

2008-01-01

Considering that short, mainly heterochiral, polypeptides with a high glycine content are expected to have played a prominent role in evolution at the earliest stage of life before nucleic acids were available, we review recent knowledge about polypeptide three-dimensional structure to predict the types of conformations they would have adopted. The possible existence of such structures at this time leads to a consideration of their functional significance, and the consequences for the course of evolution. This article was reviewed by Bill Martin, Eugene Koonin and Nick Grishin. PMID:18226248

Investigating Predictors of Spelling Ability for Adults with Low Literacy Skills

PubMed Central

Talwar, Amani; Cote, Nicole Gilbert; Binder, Katherine S.

2014-01-01

This study examined whether the spelling abilities of adults with low literacy skills could be predicted by their phonological, orthographic, and morphological awareness. Sixty Adult Basic Education (ABE) students completed several literacy tasks. It was predicted that scores on phonological and orthographic tasks would explain variance in spelling scores, whereas scores on morphological tasks may not. Scores on all phonological tasks and on one orthographic task emerged as significant predictors of spelling scores. Additionally, error analyses revealed a limited influence of morphological knowledge in spelling attempts. Implications for ABE instruction are discussed. PMID:25364644

Are emotion and mind understanding differently linked to young children's social adjustment? Relationships between behavioral consequences of emotions, false belief, and SCBE.

PubMed

Deneault, Joane; Ricard, Marcelle

2013-01-01

According to empirical findings, emotional knowledge and false belief understanding seem to be differently linked to social adjustment. However, whereas false belief is assessed through the capacity to identify its behavioral consequences, emotion tasks usually rely on the comprehension of facial expressions and of the situational causes of emotions. The authors examined if the documented relationship between social adjustment and emotion knowledge in children extends to the understanding of behavioral consequences of emotions. Eighty French-speaking preschoolers undertook false belief and consequence-of-emotion tasks. Their social adjustment was measured by the Social Competence and Behavior Evaluation. Children's language ability, their parent's level of education, and the familial socioeconomic score were taken into account. Results showed that children's social adjustment was significantly predicted by their knowledge of emotion, but not by their understanding of false belief. The findings confirm the special status of emotion among mental states for social adaptation and specify which dimensions of adaptation to peers and adults are predicted by the child's emotion understanding. They also suggest that the distinction between mind and emotion understanding may be conceptual rather than methodological.

Seatbelt and seatback control for occupant protection in frontal automotive collisions

NASA Astrophysics Data System (ADS)

Mott, Michael; Sun, Zhen; Rajamani, Rajesh

2013-10-01

This paper investigates the potential benefits of an imminent collision prediction system for improving occupant protection in a frontal automotive crash. Knowledge of an impending unavoidable crash is assumed to be known 100 ms before the crash occurs. A three dof human occupant model is developed using a Lagrangian approach to represent occupant translation with respect to seat, torso rotation and neck rotation. The performance of traditional elastic seat belts is compared with that of an analytically calculated seat belt law in which the force values are calculated in real-time so as to just prevent collision with car interior. Simulations verify that the analytical seat belt force calculation results in less force on occupant for the same level of safety. Furthermore, results show that knowledge of a future collision can be used to pre-tension seat belts but can provide no additional benefits, if seat belts are the only means for active occupant protection. However, if seat tilt-back can be deployed using an on-off mechanism, such predictive knowledge of a future collision can provide significantly improved occupant protection in terms of preventing occupant collision with car interior.

Multiple Domains of Parental Secure Base Support During Childhood and Adolescence Contribute to Adolescents’ Representations of Attachment as a Secure Base Script

PubMed Central

Vaughn, Brian E.; Waters, Theodore E. A.; Steele, Ryan D.; Roisman, Glenn I.; Bost, Kelly K.; Truitt, Warren; Waters, Harriet S.; Booth-LaForce, Cathryn

2016-01-01

Although attachment theory claims that early attachment representations reflecting the quality of the child’s “lived experiences” are maintained across developmental transitions, evidence that has emerged over the last decade suggests that the association between early relationship quality and adolescents’ attachment representations is fairly modest in magnitude. We used aspects of parenting beyond sensitivity over childhood and adolescence and early security to predict adolescents’ scripted attachment representations. At age 18 years, 673 participants from the NICHD Study of Early Child Care and Youth Development (SECCYD) completed the Attachment Script Assessment (ASA) from which we derived an assessment of secure base script knowledge. Measures of secure base support from childhood through age 15 years (e.g., parental monitoring of child activity, father presence in the home) were selected as predictors and accounted for an additional 8% of the variance in secure base script knowledge scores above and beyond direct observations of sensitivity and early attachment status alone, suggesting that adolescents’ scripted attachment representations reflect multiple domains of parenting. Cognitive and demographic variables also significantly increased predicted variance in secure base script knowledge by 2% each. PMID:27032953

Prediction versus aetiology: common pitfalls and how to avoid them.

PubMed

van Diepen, Merel; Ramspek, Chava L; Jager, Kitty J; Zoccali, Carmine; Dekker, Friedo W

2017-04-01

Prediction research is a distinct field of epidemiologic research, which should be clearly separated from aetiological research. Both prediction and aetiology make use of multivariable modelling, but the underlying research aim and interpretation of results are very different. Aetiology aims at uncovering the causal effect of a specific risk factor on an outcome, adjusting for confounding factors that are selected based on pre-existing knowledge of causal relations. In contrast, prediction aims at accurately predicting the risk of an outcome using multiple predictors collectively, where the final prediction model is usually based on statistically significant, but not necessarily causal, associations in the data at hand.In both scientific and clinical practice, however, the two are often confused, resulting in poor-quality publications with limited interpretability and applicability. A major problem is the frequently encountered aetiological interpretation of prediction results, where individual variables in a prediction model are attributed causal meaning. This article stresses the differences in use and interpretation of aetiological and prediction studies, and gives examples of common pitfalls. © The Author 2017. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.

The nature of declarative and nondeclarative knowledge for implicit and explicit learning.

PubMed

Kirkhart, M W

2001-10-01

Using traditional implicit and explicit artificial-grammar learning tasks, the author investigated the similarities and differences between the acquisition of declarative knowledge under implicit and explicit learning conditions and the functions of the declarative knowledge during testing. Results suggested that declarative knowledge was not predictive of or required for implicit learning but was related to consistency in implicit learning performance. In contrast, declarative knowledge was predictive of and required for explicit learning and was related to consistency in performance. For explicit learning, the declarative knowledge functioned as a guide for other behavior. In contrast, for implicit learning, the declarative knowledge did not serve as a guide for behavior but was instead a post hoc description of the most commonly seen stimuli.

Schematic knowledge changes what judgments of learning predict in a source memory task.

PubMed

Konopka, Agnieszka E; Benjamin, Aaron S

2009-01-01

Source monitoring can be influenced by information that is external to the study context, such as beliefs and general knowledge (Johnson, Hashtroudi, & Lindsay, 1993). We investigated the extent to which metamnemonic judgments predict memory for items and sources when schematic information about the sources is or is not provided at encoding. Participants made judgments of learning (JOLs) to statements presented by two speakers and were informed of the occupation of each speaker either before or after the encoding session. Replicating earlier work, prior knowledge decreased participants' tendency to erroneously attribute statements to schematically consistent but episodically incorrect speakers. The origin of this effect can be understood by examining the relationship between JOLs and performance: JOLs were equally predictive of item and source memory in the absence of prior knowledge, but were exclusively predictive of source memory when participants knew of the relationship between speakers and statements during study. Background knowledge determines the information that people solicit in service of metamnemonic judgments, suggesting that these judgments reflect control processes during encoding that reduce schematic errors.

LigSearch: a knowledge-based web server to identify likely ligands for a protein target

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

Beer, Tjaart A. P. de; Laskowski, Roman A.; Duban, Mark-Eugene

LigSearch is a web server for identifying ligands likely to bind to a given protein. Identifying which ligands might bind to a protein before crystallization trials could provide a significant saving in time and resources. LigSearch, a web server aimed at predicting ligands that might bind to and stabilize a given protein, has been developed. Using a protein sequence and/or structure, the system searches against a variety of databases, combining available knowledge, and provides a clustered and ranked output of possible ligands. LigSearch can be accessed at http://www.ebi.ac.uk/thornton-srv/databases/LigSearch.

"I Still Haven't Found What I'm Looking For": Parental Privacy Invasion Predicts Reduced Parental Knowledge

ERIC Educational Resources Information Center

Hawk, Skyler T.; Keijsers, Loes; Frijns, Tom; Hale, William W., III; Branje, Susan; Meeus, Wim

2013-01-01

This 3-year, multi-informant study examined whether youths' perceptions of parental privacy invasion predicted lower parental knowledge over time, as a function of increased adolescent secrecy. Participants were 497 Dutch adolescents (Time 1 M = 13 years, SD = 0.5; 57% boys) and both parents. Higher youth-reported invasion predicted lower…

Perceived stigma in Korean adolescents with epilepsy: Effects of knowledge about epilepsy and maternal perception of stigma.

PubMed

Ryu, Han Uk; Lee, Sang-Ahm; Eom, Soyong; Kim, Heung-Dong

2015-01-01

There has been little research on whether the knowledge that adolescents with epilepsy (AWE) or their family have about the condition reduces their perception of stigma. In this study we determine the relation between AWE's perceived stigma of, and knowledge about, epilepsy and maternal perception of stigma. This was a cross-sectional multicenter study involving AWE and their mothers from 25 secondary or tertiary hospitals in Korea. The level of knowledge about epilepsy was assessed using 34 medical items of the Epilepsy Knowledge Profile-General (EKP-M). Additional questionnaires included the Child Stigma Scale, Parent Stigma Scale, and the Maternal Disclosure Management Scale. A total of 243 AWE and their mothers were included. The mean EKP-M score was 20.7 (range, 12-31) for AWE and 22.0 (range, 11-31) for their mothers. AWE and mothers had a neutral perception of stigma on average, but the maternal concealment behavior was high. Multiple linear regression indicated that AWE's knowledge about epilepsy was significantly related to their perception of stigma. Unexpectedly, AWE with a low level of knowledge reported a higher perception of stigma than those with a very low level of knowledge (β=0.280, p=0.040). In addition, higher maternal concealment behavior (β=0.070, p=0.002) and receiving polytherapy (β=0.240, p=0.046) were independent factors predicting higher perception of stigma in AWE. The knowledge that the AWE had about their epilepsy, maternal concealment behavior, and receiving polytherapy were significantly related to the AWE's perception of stigma. Copyright © 2014 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Accident occurrence and functional health patterns: a pilot study of relationships in a graduate population.

PubMed

Sheerin, Fintan K; Curtis, Elizabeth; de Vries, Jan

2012-06-01

This pilot study sought to examine the relationship between functional health patterns and accident proneness. A quantitative-descriptive design was employed assessing accident proneness by collecting data on the occurrence of accidents among a sample of university graduates, and examining this in relation to biographical data and information collated using the Functional Health Pattern Assessment Screening Tool (FHPAST). Data were analyzed using descriptive and inferential statistics. One FHPAST factor predicted more frequent sports accidents. Age was also shown to be a significant predictor but in a counterintuitive way, with greater age predicting less accident proneness. The FHPAST may have a role to play in accident prediction. Functional health pattern assessment may be useful for predicting accidents. © 2012, The Authors. International Journal of Nursing Knowledge © 2012, NANDA International.

The impact of Sun-weather research on forecasting

NASA Technical Reports Server (NTRS)

Larsen, M. F.

1979-01-01

The possible impact of Sun-weather research on forecasting is examined. The type of knowledge of the effect is evaluated to determine if it is in a form that can be used for forecasting purposes. It is concluded that the present understanding of the effect does not lend itself readily to applications for forecast purposes. The limits of present predictive skill are examined and it is found that skill is most lacking for prediction of the smallest scales of atmospheric motion. However, it is not expected that Sun-weather research will have any significant impact on forecasting the smaller scales since predictability at these scales is limited by the finite grid size resolution and the time scales of turbulent diffusion. The predictability limits for the largest scales are on the order of several weeks although presently only a one week forecast is achievable.

Predicting exposure-response associations of ambient particulate matter with mortality in 73 Chinese cities.

PubMed

Madaniyazi, Lina; Guo, Yuming; Chen, Renjie; Kan, Haidong; Tong, Shilu

2016-01-01

Estimating the burden of mortality associated with particulates requires knowledge of exposure-response associations. However, the evidence on exposure-response associations is limited in many cities, especially in developing countries. In this study, we predicted associations of particulates smaller than 10 μm in aerodynamic diameter (PM10) with mortality in 73 Chinese cities. The meta-regression model was used to test and quantify which city-specific characteristics contributed significantly to the heterogeneity of PM10-mortality associations for 16 Chinese cities. Then, those city-specific characteristics with statistically significant regression coefficients were treated as independent variables to build multivariate meta-regression models. The model with the best fitness was used to predict PM10-mortality associations in 73 Chinese cities in 2010. Mean temperature, PM10 concentration and green space per capita could best explain the heterogeneity in PM10-mortality associations. Based on city-specific characteristics, we were able to develop multivariate meta-regression models to predict associations between air pollutants and health outcomes reasonably well. Copyright © 2015 Elsevier Ltd. All rights reserved.

Relations Among Student Attention Behaviors, Teacher Practices, and Beginning Word Reading Skill

PubMed Central

Sáez, Leilani; Folsom, Jessica Sidler; Al Otaiba, Stephanie; Schatschneider, Christopher

2011-01-01

The role of student attention for predicting kindergarten word reading was investigated among 432 students. Using SWAN behavior rating scores, we conducted an exploratory factor analysis, which yielded three distinct factors that reflected selective attention. In this study, we focused on the role of one of these factors, which we labeled attention-memory behaviors, for predicting reading performance. Teacher ratings of attention predicted word reading above and beyond the contribution of phonological awareness and vocabulary knowledge. In addition, the relations between four teacher practices and attention ratings for predicting reading performance were examined. Using HLM, significant interactions between student attention and teacher practices observed during literacy instruction were found. In general, as ratings of attention improved, better kindergarten word reading performance was associated with high levels of classroom behavior management. However, by mid-year, better word reading performance was not associated with high levels of teacher task- orienting. A significant three-way interaction was also found among attention, individualized instruction, and teacher task re-directions. The role of regulating kindergarten student attention to support beginning word reading skill development is discussed. PMID:22207616

Neuroimaging-based biomarkers in psychiatry: clinical opportunities of a paradigm shift.

PubMed

Fu, Cynthia H Y; Costafreda, Sergi G

2013-09-01

Neuroimaging research has substantiated the functional and structural abnormalities underlying psychiatric disorders but has, thus far, failed to have a significant impact on clinical practice. Recently, neuroimaging-based diagnoses and clinical predictions derived from machine learning analysis have shown significant potential for clinical translation. This review introduces the key concepts of this approach, including how the multivariate integration of patterns of brain abnormalities is a crucial component. We survey recent findings that have potential application for diagnosis, in particular early and differential diagnoses in Alzheimer disease and schizophrenia, and the prediction of clinical response to treatment in depression. We discuss the specific clinical opportunities and the challenges for developing biomarkers for psychiatry in the absence of a diagnostic gold standard. We propose that longitudinal outcomes, such as early diagnosis and prediction of treatment response, offer definite opportunities for progress. We propose that efforts should be directed toward clinically challenging predictions in which neuroimaging may have added value, compared with the existing standard assessment. We conclude that diagnostic and prognostic biomarkers will be developed through the joint application of expert psychiatric knowledge in addition to advanced methods of analysis.

Knee joint forces: prediction, measurement, and significance

PubMed Central

D’Lima, Darryl D.; Fregly, Benjamin J.; Patil, Shantanu; Steklov, Nikolai; Colwell, Clifford W.

2011-01-01

Knee forces are highly significant in osteoarthritis and in the survival and function of knee arthroplasty. A large number of studies have attempted to estimate forces around the knee during various activities. Several approaches have been used to relate knee kinematics and external forces to internal joint contact forces, the most popular being inverse dynamics, forward dynamics, and static body analyses. Knee forces have also been measured in vivo after knee arthroplasty, which serves as valuable validation of computational predictions. This review summarizes the results of published studies that measured knee forces for various activities. The efficacy of various methods to alter knee force distribution, such as gait modification, orthotics, walking aids, and custom treadmills are analyzed. Current gaps in our knowledge are identified and directions for future research in this area are outlined. PMID:22468461

Preschool Interpersonal Relationships Predict Kindergarten Achievement: Mediated by Gains in Emotion Knowledge

PubMed Central

Torres, Marcela M.; Domitrovich, Celene E.; Bierman, Karen L.

2016-01-01

Using longitudinal data, this study tested a model in which preschool interpersonal relationships promoted kindergarten achievement in a pathway mediated by growth in emotion knowledge. The sample included 164 children attending Head Start (14% Hispanic-American, 30% African-American, 56% Caucasian; 56% girls). Preschool interpersonal relationships were indexed by student-teacher relationship closeness and positive peer interactions. Two measures of emotion knowledge (identifying emotions in photographs, recognizing emotions in stories) were assessed at the start and end of the preschool year. Structural equation models revealed that positive interpersonal relationships (with teachers and peers) predicted gains in emotion knowledge (identification, recognition) during the preschool year. Positive interpersonal relationships in preschool also predicted kindergarten achievement (controlling for initial preschool achievement); however, this association was mediated by gains in emotion knowledge during the preschool year. Implications are discussed for school readiness programs serving economically-disadvantaged children. PMID:27630379

Giant star seismology

NASA Astrophysics Data System (ADS)

Hekker, S.; Christensen-Dalsgaard, J.

2017-06-01

The internal properties of stars in the red-giant phase undergo significant changes on relatively short timescales. Long near-uninterrupted high-precision photometric timeseries observations from dedicated space missions such as CoRoT and Kepler have provided seismic inferences of the global and internal properties of a large number of evolved stars, including red giants. These inferences are confronted with predictions from theoretical models to improve our understanding of stellar structure and evolution. Our knowledge and understanding of red giants have indeed increased tremendously using these seismic inferences, and we anticipate that more information is still hidden in the data. Unraveling this will further improve our understanding of stellar evolution. This will also have significant impact on our knowledge of the Milky Way Galaxy as well as on exo-planet host stars. The latter is important for our understanding of the formation and structure of planetary systems.

An expert system based software sizing tool, phase 2

NASA Technical Reports Server (NTRS)

Friedlander, David

1990-01-01

A software tool was developed for predicting the size of a future computer program at an early stage in its development. The system is intended to enable a user who is not expert in Software Engineering to estimate software size in lines of source code with an accuracy similar to that of an expert, based on the program's functional specifications. The project was planned as a knowledge based system with a field prototype as the goal of Phase 2 and a commercial system planned for Phase 3. The researchers used techniques from Artificial Intelligence and knowledge from human experts and existing software from NASA's COSMIC database. They devised a classification scheme for the software specifications, and a small set of generic software components that represent complexity and apply to large classes of programs. The specifications are converted to generic components by a set of rules and the generic components are input to a nonlinear sizing function which makes the final prediction. The system developed for this project predicted code sizes from the database with a bias factor of 1.06 and a fluctuation factor of 1.77, an accuracy similar to that of human experts but without their significant optimistic bias.

An examination of the impact of non-formal and informal learning on adult environmental knowledge, attitudes, and behaviors

NASA Astrophysics Data System (ADS)

Digby, Cynthia Louise Barrett

The purpose of this research is to consider the environmental knowledge, attitudes, and behaviors, of adults in Minnesota, and possible factors that influence environmental literacy. Specifically, this study is designed to: (1) measure the environmental literacy of Minnesota adults, (2) explore possible relationships between Minnesota adults, environmental literacy variables and their demographic, non-formal and informal learning, and (3) determine the relative contribution of demographic and learning variables for predicting environmental knowledge, attitudes and behaviors. This research was accomplished by conducting a secondary data analysis of The Third Minnesota Report Card on Environmental Literacy: A Survey of Adult Environmental Knowledge, Attitudes and Behavior (Murphy & Olson, 2008). Phone interviews were completed between August and November 2007 with one thousand adults throughout Minnesota. Findings indicated that for age, education, and income, there was a weak positive relationship with environmental knowledge, attitude and behavior scores. There was a significant effect for gender and environmental knowledge scores, with males receiving higher environmental knowledge scores than females. There was a significant effect for gender and environmental attitudes, and behavior scores as well, with females receiving slightly higher environmental attitude and behavior scores than males. After controlling for the effects of demographic variables on environmental knowledge, attitudes and behaviors, non-formal learning participation appears to be a moderate contributor to both environmental knowledge and environmental behaviors. After controlling for the effects of demographic variables on environmental knowledge, attitudes and behaviors, informal learning participation appears to be a slight contributor to environmental attitudes, and a moderate contributor to environmental knowledge and behaviors. Overall, the results of this study suggest that participation in non-formal and informal education venues improved environmental knowledge, attitude and behavior models, providing evidence for the value and need for non-formal and informal environmental adult education venues.

Meteorological models for estimating phenology of corn

NASA Technical Reports Server (NTRS)

Daughtry, C. S. T.; Cochran, J. C.; Hollinger, S. E.

1984-01-01

Knowledge of when critical crop stages occur and how the environment affects them should provide useful information for crop management decisions and crop production models. Two sources of data were evaluated for predicting dates of silking and physiological maturity of corn (Zea mays L.). Initial evaluations were conducted using data of an adapted corn hybrid grown on a Typic Agriaquoll at the Purdue University Agronomy Farm. The second phase extended the analyses to large areas using data acquired by the Statistical Reporting Service of USDA for crop reporting districts (CRD) in Indiana and Iowa. Several thermal models were compared to calendar days for predicting dates of silking and physiological maturity. Mixed models which used a combination of thermal units to predict silking and days after silking to predict physiological maturity were also evaluated. At the Agronomy Farm the models were calibrated and tested on the same data. The thermal models were significantly less biased and more accurate than calendar days for predicting dates of silking. Differences among the thermal models were small. Significant improvements in both bias and accuracy were observed when the mixed models were used to predict dates of physiological maturity. The results indicate that statistical data for CRD can be used to evaluate models developed at agricultural experiment stations.

Prioritizing Therapeutics for Lung Cancer: An Integrative Meta-analysis of Cancer Gene Signatures and Chemogenomic Data

PubMed Central

Fortney, Kristen; Griesman, Joshua; Kotlyar, Max; Pastrello, Chiara; Angeli, Marc; Sound-Tsao, Ming; Jurisica, Igor

2015-01-01

Repurposing FDA-approved drugs with the aid of gene signatures of disease can accelerate the development of new therapeutics. A major challenge to developing reliable drug predictions is heterogeneity. Different gene signatures of the same disease or drug treatment often show poor overlap across studies, as a consequence of both biological and technical variability, and this can affect the quality and reproducibility of computational drug predictions. Existing algorithms for signature-based drug repurposing use only individual signatures as input. But for many diseases, there are dozens of signatures in the public domain. Methods that exploit all available transcriptional knowledge on a disease should produce improved drug predictions. Here, we adapt an established meta-analysis framework to address the problem of drug repurposing using an ensemble of disease signatures. Our computational pipeline takes as input a collection of disease signatures, and outputs a list of drugs predicted to consistently reverse pathological gene changes. We apply our method to conduct the largest and most systematic repurposing study on lung cancer transcriptomes, using 21 signatures. We show that scaling up transcriptional knowledge significantly increases the reproducibility of top drug hits, from 44% to 78%. We extensively characterize drug hits in silico, demonstrating that they slow growth significantly in nine lung cancer cell lines from the NCI-60 collection, and identify CALM1 and PLA2G4A as promising drug targets for lung cancer. Our meta-analysis pipeline is general, and applicable to any disease context; it can be applied to improve the results of signature-based drug repurposing by leveraging the large number of disease signatures in the public domain. PMID:25786242

Long-Range Reduced Predictive Information Transfers of Autistic Youths in EEG Sensor-Space During Face Processing.

PubMed

Khadem, Ali; Hossein-Zadeh, Gholam-Ali; Khorrami, Anahita

2016-03-01

The majority of previous functional/effective connectivity studies conducted on the autistic patients converged to the underconnectivity theory of ASD: "long-range underconnectivity and sometimes short-rang overconnectivity". However, to the best of our knowledge the total (linear and nonlinear) predictive information transfers (PITs) of autistic patients have not been investigated yet. Also, EEG data have rarely been used for exploring the information processing deficits in autistic subjects. This study is aimed at comparing the total (linear and nonlinear) PITs of autistic and typically developing healthy youths during human face processing by using EEG data. The ERPs of 12 autistic youths and 19 age-matched healthy control (HC) subjects were recorded while they were watching upright and inverted human face images. The PITs among EEG channels were quantified using two measures separately: transfer entropy with self-prediction optimality (TESPO), and modified transfer entropy with self-prediction optimality (MTESPO). Afterwards, the directed differential connectivity graphs (dDCGs) were constructed to characterize the significant changes in the estimated PITs of autistic subjects compared with HC ones. By using both TESPO and MTESPO, long-range reduction of PITs of ASD group during face processing was revealed (particularly from frontal channels to right temporal channels). Also, it seemed the orientation of face images (upright or upside down) did not modulate the binary pattern of PIT-based dDCGs, significantly. Moreover, compared with TESPO, the results of MTESPO were more compatible with the underconnectivity theory of ASD in the sense that MTESPO showed no long-range increase in PIT. It is also noteworthy that to the best of our knowledge it is the first time that a version of MTE is applied for patients (here ASD) and it is also its first use for EEG data analysis.

Developmental dyslexia: predicting individual risk

PubMed Central

Thompson, Paul A; Hulme, Charles; Nash, Hannah M; Gooch, Debbie; Hayiou-Thomas, Emma; Snowling, Margaret J

2015-01-01

Background Causal theories of dyslexia suggest that it is a heritable disorder, which is the outcome of multiple risk factors. However, whether early screening for dyslexia is viable is not yet known. Methods The study followed children at high risk of dyslexia from preschool through the early primary years assessing them from age 3 years and 6 months (T1) at approximately annual intervals on tasks tapping cognitive, language, and executive-motor skills. The children were recruited to three groups: children at family risk of dyslexia, children with concerns regarding speech, and language development at 3;06 years and controls considered to be typically developing. At 8 years, children were classified as ‘dyslexic’ or not. Logistic regression models were used to predict the individual risk of dyslexia and to investigate how risk factors accumulate to predict poor literacy outcomes. Results Family-risk status was a stronger predictor of dyslexia at 8 years than low language in preschool. Additional predictors in the preschool years include letter knowledge, phonological awareness, rapid automatized naming, and executive skills. At the time of school entry, language skills become significant predictors, and motor skills add a small but significant increase to the prediction probability. We present classification accuracy using different probability cutoffs for logistic regression models and ROC curves to highlight the accumulation of risk factors at the individual level. Conclusions Dyslexia is the outcome of multiple risk factors and children with language difficulties at school entry are at high risk. Family history of dyslexia is a predictor of literacy outcome from the preschool years. However, screening does not reach an acceptable clinical level until close to school entry when letter knowledge, phonological awareness, and RAN, rather than family risk, together provide good sensitivity and specificity as a screening battery. PMID:25832320

Using a knowledge-based planning solution to select patients for proton therapy.

PubMed

Delaney, Alexander R; Dahele, Max; Tol, Jim P; Kuijper, Ingrid T; Slotman, Ben J; Verbakel, Wilko F A R

2017-08-01

Patient selection for proton therapy by comparing proton/photon treatment plans is time-consuming and prone to bias. RapidPlan™, a knowledge-based-planning solution, uses plan-libraries to model and predict organ-at-risk (OAR) dose-volume-histograms (DVHs). We investigated whether RapidPlan, utilizing an algorithm based only on photon beam characteristics, could generate proton DVH-predictions and whether these could correctly identify patients for proton therapy. Model PROT and Model PHOT comprised 30 head-and-neck cancer proton and photon plans, respectively. Proton and photon knowledge-based-plans (KBPs) were made for ten evaluation-patients. DVH-prediction accuracy was analyzed by comparing predicted-vs-achieved mean OAR doses. KBPs and manual plans were compared using salivary gland and swallowing muscle mean doses. For illustration, patients were selected for protons if predicted Model PHOT mean dose minus predicted Model PROT mean dose (ΔPrediction) for combined OARs was ≥6Gy, and benchmarked using achieved KBP doses. Achieved and predicted Model PROT /Model PHOT mean dose R 2 was 0.95/0.98. Generally, achieved mean dose for Model PHOT /Model PROT KBPs was respectively lower/higher than predicted. Comparing Model PROT /Model PHOT KBPs with manual plans, salivary and swallowing mean doses increased/decreased by <2Gy, on average. ΔPrediction≥6Gy correctly selected 4 of 5 patients for protons. Knowledge-based DVH-predictions can provide efficient, patient-specific selection for protons. A proton-specific RapidPlan-solution could improve results. Copyright © 2017 Elsevier B.V. All rights reserved.

Learning to Predict Consequences as a Method of Knowledge Transfer in Reinforcement Learning.

PubMed

Chalmers, Eric; Contreras, Edgar Bermudez; Robertson, Brandon; Luczak, Artur; Gruber, Aaron

2017-04-17

The reinforcement learning (RL) paradigm allows agents to solve tasks through trial-and-error learning. To be capable of efficient, long-term learning, RL agents should be able to apply knowledge gained in the past to new tasks they may encounter in the future. The ability to predict actions' consequences may facilitate such knowledge transfer. We consider here domains where an RL agent has access to two kinds of information: agent-centric information with constant semantics across tasks, and environment-centric information, which is necessary to solve the task, but with semantics that differ between tasks. For example, in robot navigation, environment-centric information may include the robot's geographic location, while agent-centric information may include sensor readings of various nearby obstacles. We propose that these situations provide an opportunity for a very natural style of knowledge transfer, in which the agent learns to predict actions' environmental consequences using agent-centric information. These predictions contain important information about the affordances and dangers present in a novel environment, and can effectively transfer knowledge from agent-centric to environment-centric learning systems. Using several example problems including spatial navigation and network routing, we show that our knowledge transfer approach can allow faster and lower cost learning than existing alternatives.

A controlled evaluation of an eating disorders primary prevention videotape using the Elaboration Likelihood Model of Persuasion.

PubMed

Withers, Giselle F; Twigg, Kylie; Wertheim, Eleanor H; Paxton, Susan J

2002-11-01

The aim was to extend findings related to a previously reported eating disorders prevention program by comparing treatment and control groups, adding a follow-up, and examining whether receiver characteristics, personal relevance and need for cognition (NFC), could predict attitude change in early adolescent girls. Grade 7 girls were either shown a brief prevention videotape on dieting and body image (n = 104) or given no intervention (n = 114). All girls completed pre-, post- and 1-month follow-up questionnaires. The intervention group resulted in significantly more positive changes in attitude and knowledge at post-intervention, but only in knowledge at follow-up. There was no strong evidence that pre-intervention characteristics of recipients predicted responses to the videotape intervention when changes were compared to the control group. This prevention videotape appeared to have positive immediate effects, but additional intervention (e.g., booster sessions) may be required for longer-term change. Copyright 2002 Elsevier Science Inc.

Vincristine-induced peripheral neuropathy in pediatric cancer patients

PubMed Central

Mora, Erika; Smith, Ellen M Lavoie; Donohoe, Clare; Hertz, Daniel L

2016-01-01

Vincristine is a chemotherapeutic agent that is a component of many combination regimens for a variety of malignancies, including several common pediatric tumors. Vincristine treatment is limited by a progressive sensorimotor peripheral neuropathy. Vincristine-induced peripheral neuropathy (VIPN) is particularly challenging to detect and monitor in pediatric patients, in whom the side effect can diminish long term quality of life. This review summarizes the current state of knowledge regarding VIPN, focusing on its description, assessment, prediction, prevention, and treatment. Significant progress has been made in our knowledge about VIPN incidence and progression, and tools have been developed that enable clinicians to reliably measure VIPN in pediatric patients. Despite these successes, little progress has been made in identifying clinically useful predictors of VIPN or in developing effective approaches for VIPN prevention or treatment in either pediatric or adult patients. Further research is needed to predict, prevent, and treat VIPN to maximize therapeutic benefit and avoid unnecessary toxicity from vincristine treatment. PMID:27904761

Combining medical informatics and bioinformatics toward tools for personalized medicine.

PubMed

Sarachan, B D; Simmons, M K; Subramanian, P; Temkin, J M

2003-01-01

Key bioinformatics and medical informatics research areas need to be identified to advance knowledge and understanding of disease risk factors and molecular disease pathology in the 21 st century toward new diagnoses, prognoses, and treatments. Three high-impact informatics areas are identified: predictive medicine (to identify significant correlations within clinical data using statistical and artificial intelligence methods), along with pathway informatics and cellular simulations (that combine biological knowledge with advanced informatics to elucidate molecular disease pathology). Initial predictive models have been developed for a pilot study in Huntington's disease. An initial bioinformatics platform has been developed for the reconstruction and analysis of pathways, and work has begun on pathway simulation. A bioinformatics research program has been established at GE Global Research Center as an important technology toward next generation medical diagnostics. We anticipate that 21 st century medical research will be a combination of informatics tools with traditional biology wet lab research, and that this will translate to increased use of informatics techniques in the clinic.

The Impact of Early Classroom Inattention on Phonological Processing and Word-Reading Development.

PubMed

Dittman, Cassandra K

2016-08-01

The present study investigated the longitudinal relationships between inattention, phonological processing and word reading across the first 2 years of formal reading instruction. In all, 136 school entrants were administered measures of letter knowledge, phonological awareness, phonological memory, rapid naming, and word reading at the start and end of their 1st year of school, and the end of their 2nd year, while teachers completed rating scales of inattention. School entry inattentiveness predicted unique variance in word reading at the end of first grade, after controlling for verbal ability, letter knowledge, and phonological processing. End-of-first-grade inattention predicted a small but significant amount of unique variance in second-grade word reading and word-reading efficiency. Inattention, however, was not a reliable predictor of phonological processing in either first or second grade. Early classroom inattentiveness influences learning to read independent of critical developmental precursors of word-reading development. © The Author(s) 2013.

Integration of preclinical and clinical knowledge to predict intravenous PK in human: bilastine case study.

PubMed

Vozmediano, Valvanera; Ortega, Ignacio; Lukas, John C; Gonzalo, Ana; Rodriguez, Monica; Lucero, Maria Luisa

2014-03-01

Modern pharmacometrics can integrate and leverage all prior proprietary and public knowledge. Such methods can be used to scale across species or comparators, perform clinical trial simulation across alternative designs, confirm hypothesis and potentially reduce development burden, time and costs. Crucial yet typically lacking in integration is the pre-clinical stage. Prediction of PK in man, using in vitro and in vivo studies in different animal species, is increasingly well theorized but could still find wider application in drug development. The aim of the present work was to explore methods for bridging pharmacokinetic knowledge from animal species (i.v. and p.o.) and man (p.o.) into i.v. in man using the antihistamine drug bilastine as example. A model, predictive of i.v. PK in man, was developed on data from two pre-clinical species (rat and dog) and p.o. in man bilastine trials performed earlier. In the knowledge application stage, two different approaches were used to predict human plasma concentration after i.v. of bilastine: allometry (several scaling methods) and a semi-physiological method. Both approaches led to successful predictions of key i.v. PK parameters of bilastine in man. The predictive i.v. PK model was validated using later data from a clinical study of i.v. bilastine. Introduction of such knowledge in development permits proper leveraging of all emergent knowledge as well as quantification-based exploration of PK scenario, e.g. in special populations (pediatrics, renal insufficiency, comedication). In addition, the methods permit reduction or elimination and certainly optimization of learning trials, particularly those concerning alternative off-label administration routes.

DEEP--a tool for differential expression effector prediction.

PubMed

Degenhardt, Jost; Haubrock, Martin; Dönitz, Jürgen; Wingender, Edgar; Crass, Torsten

2007-07-01

High-throughput methods for measuring transcript abundance, like SAGE or microarrays, are widely used for determining differences in gene expression between different tissue types, dignities (normal/malignant) or time points. Further analysis of such data frequently aims at the identification of gene interaction networks that form the causal basis for the observed properties of the systems under examination. To this end, it is usually not sufficient to rely on the measured gene expression levels alone; rather, additional biological knowledge has to be taken into account in order to generate useful hypotheses about the molecular mechanism leading to the realization of a certain phenotype. We present a method that combines gene expression data with biological expert knowledge on molecular interaction networks, as described by the TRANSPATH database on signal transduction, to predict additional--and not necessarily differentially expressed--genes or gene products which might participate in processes specific for either of the examined tissues or conditions. In a first step, significance values for over-expression in tissue/condition A or B are assigned to all genes in the expression data set. Genes with a significance value exceeding a certain threshold are used as starting points for the reconstruction of a graph with signaling components as nodes and signaling events as edges. In a subsequent graph traversal process, again starting from the previously identified differentially expressed genes, all encountered nodes 'inherit' all their starting nodes' significance values. In a final step, the graph is visualized, the nodes being colored according to a weighted average of their inherited significance values. Each node's, or sub-network's, predominant color, ranging from green (significant for tissue/condition A) over yellow (not significant for either tissue/condition) to red (significant for tissue/condition B), thus gives an immediate visual clue on which molecules--differentially expressed or not--may play pivotal roles in the tissues or conditions under examination. The described method has been implemented in Java as a client/server application and a web interface called DEEP (Differential Expression Effector Prediction). The client, which features an easy-to-use graphical interface, can freely be downloaded from the following URL: http://deep.bioinf.med.uni-goettingen.de.

Knowledge Assisted Integrated Design of a Component and Its Manufacturing Process

NASA Astrophysics Data System (ADS)

Gautham, B. P.; Kulkarni, Nagesh; Khan, Danish; Zagade, Pramod; Reddy, Sreedhar; Uppaluri, Rohith

Integrated design of a product and its manufacturing processes would significantly reduce the total cost of the products as well as the cost of its development. However this would only be possible if we have a platform that allows us to link together simulations tools used for product design, performance evaluation and its manufacturing processes in a closed loop. In addition to that having a comprehensive knowledgebase that provides systematic knowledge guided assistance to product or process designers who may not possess in-depth design knowledge or in-depth knowledge of the simulation tools, would significantly speed up the end-to-end design process. In this paper, we propose a process and illustrate a case for achieving an integrated product and manufacturing process design assisted by knowledge support for the user to make decisions at various stages. We take transmission component design as an example. The example illustrates the design of a gear for its geometry, material selection and its manufacturing processes, particularly, carburizing-quenching and tempering, and feeding the material properties predicted during heat treatment into performance estimation in a closed loop. It also identifies and illustrates various decision stages in the integrated life cycle and discusses the use of knowledge engineering tools such as rule-based guidance, to assist the designer make informed decisions. Simulation tools developed on various commercial, open-source platforms as well as in-house tools along with knowledge engineering tools are linked to build a framework with appropriate navigation through user-friendly interfaces. This is illustrated through examples in this paper.

Cognitive and behavioral knowledge about insulin-dependent diabetes among children and parents.

PubMed

Johnson, S B; Pollak, R T; Silverstein, J H; Rosenbloom, A L; Spillar, R; McCallum, M; Harkavy, J

1982-06-01

Youngster's knowledge about insulin-dependent diabetes was assessed across three domains: (1) general information; (2) problem solving and (3) skill at urine testing and self-injection. These youngster's parents completed the general information and problem-solving components of the assessment battery. All test instruments were showed good reliability. The test of problem solving was more difficult than the test of general information for both parents and patients. Mothers were more knowledgeable than fathers and children. Girls performed more accurately than boys, and older children obtained better scores than did younger children. Nevertheless, more than 80% of the youngsters made significant errors on urine testing and almost 40% made serious errors in self-injection. A number of other knowledge deficits were also noted. Duration of diabetes was not related to any of the knowledge measures. Intercorrelations between scores on the assessment instruments indicated that skill at urine testing or self-injection was not highly related to other types of knowledge about diabetes. Furthermore, knowledge in one content are was not usually predictive of knowledge in another content area. The results of this study emphasize the importance of measuring knowledge from several different domains. Patient variables such as sex and age need to be given further consideration in the development and use of patient educational programs. Regular assessment of patients' and parents' knowledge of all critical aspects of diabetes home management seems essential.

Parenting Predictors of Cognitive Skills and Emotion Knowledge in Socioeconomically Disadvantaged Preschoolers

PubMed Central

Merz, Emily C.; Zucker, Tricia A.; Landry, Susan H.; Williams, Jeffrey M.; Assel, Michael; Taylor, Heather B.; Lonigan, Christopher J.; Phillips, Beth M.; Clancy-Menchetti, Jeanine; Barnes, Marcia A.; Eisenberg, Nancy; de Villiers, Jill

2014-01-01

This study examined the concurrent and longitudinal associations of parental responsiveness and inferential language input with cognitive skills and emotion knowledge among socioeconomically disadvantaged preschoolers. Parents and 2- to 4-year-old children (mean age = 3.21 years; N=284) participated in a parent-child free play session, and children completed cognitive (language, early literacy, early mathematics) and emotion knowledge assessments. One year later, children completed the same assessment battery. Parental responsiveness was coded from the videotaped parent-child free play sessions, and parental inferential language input was coded from transcripts of a subset of 127 of these sessions. All analyses controlled for child age, gender, and parental education, and longitudinal analyses controlled for initial skill level. Parental responsiveness significantly predicted all concurrent cognitive skills as well as literacy, math, and emotion knowledge one year later. Parental inferential language input was significantly positively associated with children's concurrent emotion knowledge. In longitudinal analyses, an interaction was found such that for children with stronger initial language skills, higher levels of parental inferential language input facilitated greater vocabulary development, whereas for children with weaker initial language skills, there was no association between parental inferential language input and change in children's vocabulary skills. These findings further our understanding of the roles of parental responsiveness and inferential language input in promoting children's school readiness skills. PMID:25576967

Development of predictive mapping techniques for soil survey and salinity mapping

NASA Astrophysics Data System (ADS)

Elnaggar, Abdelhamid A.

Conventional soil maps represent a valuable source of information about soil characteristics, however they are subjective, very expensive, and time-consuming to prepare. Also, they do not include explicit information about the conceptual mental model used in developing them nor information about their accuracy, in addition to the error associated with them. Decision tree analysis (DTA) was successfully used in retrieving the expert knowledge embedded in old soil survey data. This knowledge was efficiently used in developing predictive soil maps for the study areas in Benton and Malheur Counties, Oregon and accessing their consistency. A retrieved soil-landscape model from a reference area in Harney County was extrapolated to develop a preliminary soil map for the neighboring unmapped part of Malheur County. The developed map had a low prediction accuracy and only a few soil map units (SMUs) were predicted with significant accuracy, mostly those shallow SMUs that have either a lithic contact with the bedrock or developed on a duripan. On the other hand, the developed soil map based on field data was predicted with very high accuracy (overall was about 97%). Salt-affected areas of the Malheur County study area are indicated by their high spectral reflectance and they are easily discriminated from the remote sensing data. However, remote sensing data fails to distinguish between the different classes of soil salinity. Using the DTA method, five classes of soil salinity were successfully predicted with an overall accuracy of about 99%. Moreover, the calculated area of salt-affected soil was overestimated when mapped using remote sensing data compared to that predicted by using DTA. Hence, DTA could be a very helpful approach in developing soil survey and soil salinity maps in more objective, effective, less-expensive and quicker ways based on field data.

The nature and development of hypothetico-predictive argumentation with implications for science teaching

NASA Astrophysics Data System (ADS)

Lawson, Anton E.

2003-11-01

This paper explicates a pattern of scientific argumentation in which scientists respond to causal questions with the generation and test of alternative hypotheses through cycles of hypothetico-predictive argumentation. Hypothetico-predictive arguments are employed to test causal claims that exist on at least two levels (designated stage 4 in which the causal claims are perceptible, and stage 5 in which the causal claims are imperceptible). Origins of the ability to construct and comprehend hypothetico-predictive arguments at the highest level can be traced to pre-verbal reasoning of the sensory-motor child and the gradual internalization of verbally mediated arguments involving nominal, categorical, causal and, finally, theoretical propositions. Presumably, the ability to construct and comprehend hypothetico-predictive arguments (an aspect of procedural knowledge) is necessary for the construction of conceptual knowledge (an aspect of declarative knowledge) because such arguments are used during concept construction and conceptual change. Science instruction that focuses on the generation and debate of hypothetico-predictive arguments should improve students' conceptual understanding and their argumentative/reasoning skills.

A response to Edzi (AIDS): Malawi faith-based organizations' impact on HIV prevention and care.

PubMed

Lindgren, Teri; Schell, Ellen; Rankin, Sally; Phiri, Joel; Fiedler, Rachel; Chakanza, Joseph

2013-01-01

African faith-based organization (FBO) leaders influence their members' HIV knowledge, beliefs, and practices, but their roles in HIV prevention and care are poorly understood. This article expands the work of Garner (2000) to test the impact of FBO influence on member risk and care behaviors, embedding it in the Theory of Planned Behavior. Qualitative interviews and quantitative surveys were collected from five FBOs (Christian and Muslim) in Malawi and analyzed using mixed methods. Contrary to Garner, we found that the level of power and influence of the FBO had no significant impact on the risk-taking behaviors of members; however, leaders' HIV knowledge predicted members' behaviors. Stigmatizing attitudes of leaders significantly decreased members' care behaviors, but FBO hierarchy tended to increase members' care behaviors. The power of local church and mosque leaders to influence behavior could be exploited more effectively by nurses by providing support, knowledge, and encouragement to churches and mosques. Copyright © 2013 Association of Nurses in AIDS Care. Published by Elsevier Inc. All rights reserved.

Cigarette Litter: Smokers’ Attitudes and Behaviors

PubMed Central

Rath, Jessica M.; Rubenstein, Rebecca A.; Curry, Laurel E.; Shank, Sarah E.; Cartwright, Julia C.

2012-01-01

Cigarette butts are consistently the most collected items in litter clean-up efforts, which are a costly burden to local economies. In addition, tobacco waste may be detrimental to our natural environment. The tobacco industry has conducted or funded numerous studies on smokers’ littering knowledge and behavior, however, non-industry sponsored research is rare. We sought to examine whether demographics and smokers’ knowledge and beliefs toward cigarette waste as litter predicts littering behavior. Smokers aged 18 and older (n = 1,000) were interviewed about their knowledge and beliefs towards cigarette waste as litter. Respondents were members of the Research Now panel, an online panel of over three million respondents in the United States. Multivariate logistic regressions were conducted to determine factors significantly predictive of ever having littered cigarette butts or having littered cigarette butts within the past month (p-value < 0.05). The majority (74.1%) of smokers reported having littered cigarette butts at least once in their life, by disposing of them on the ground or throwing them out of a car window. Over half (55.7%) reported disposing of cigarette butts on the ground, in a sewer/gutter, or down a drain in the past month. Those who did not consider cigarette butts to be litter were over three and half times as likely to report having ever littered cigarette butts (OR = 3.68, 95%CI = 2.04, 6.66) and four times as likely to have littered cigarette butts in the past month (OR = 4.00, 95%CI = 2.53, 6.32). Males were significantly more likely to have littered cigarette butts in the past month compared to females (OR = 1.49, 95%CI = 1.14, 1.94). Holding the belief that cigarette butts are not litter was the only belief in this study that predicted ever or past-month littering of cigarette waste. Messages in anti-cigarette-litter campaigns should emphasize that cigarette butts are not just litter but are toxic waste and are harmful when disposed of improperly. PMID:22829798

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

NASA Astrophysics Data System (ADS)

Lavoie, Derrick R.; Good, Ron

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

Neither Basic Life Support knowledge nor self-efficacy are predictive of skills among dental students.

PubMed

Mac Giolla Phadraig, C; Ho, J D; Guerin, S; Yeoh, Y L; Mohamed Medhat, M; Doody, K; Hwang, S; Hania, M; Boggs, S; Nolan, A; Nunn, J

2017-08-01

Basic life support (BLS) is considered a core competence for the graduating dentist. This study aimed to measure BLS knowledge, self-efficacy and skills of undergraduate dental students in Dublin. This study consisted of a cross-sectional survey measuring BLS knowledge and self-efficacy, accompanied by a directly observed BLS skills assessment in a subsample of respondents. Data were collected in January 2014. Bivariate correlations between descriptive and outcome variables (knowledge, self-efficacy and skills) were tested using Pearson's chi-square. We included knowledge and self-efficacy as predictor variables, along with other variables showing association, into a binary logistic regression model with BLS skills as the outcome measure. One hundred and thirty-five students participated. Almost all (n = 133, 98.5%) participants had BLS training within the last 2 years. One hundred and four (77%) felt that they were capable of providing effective BLS (self-efficacy), whilst only 46 (34.1%) scored >80% of knowledge items correct. Amongst the skills (n = 85) subsample, 38.8% (n = 33) were found to pass the BLS skills assessment. Controlling for gender, age and skills assessor, the regression model did not identify a predictive relationship between knowledge or self-efficacy and BLS skills. Neither knowledge nor self-efficacy was predictive of BLS skills. Dental students had low levels of knowledge and skills in BLS. Despite this, their confidence in their ability to perform BLS was high and did not predict actual competence. There is a need for additional hands-on training, focusing on self-efficacy and BLS skills, particularly the use of AED. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Residents' and Fellows' Knowledge and Attitudes About Eating Disorders at an Academic Medical Center.

PubMed

Anderson, Kristen; Accurso, Erin C; Kinasz, Kathryn R; Le Grange, Daniel

2017-06-01

This study examined physician residents' and fellows' knowledge of eating disorders and their attitudes toward patients with eating disorders. Eighty physicians across disciplines completed a survey. The response rate for this survey across disciplines was 64.5 %. Participants demonstrated limited knowledge of eating disorders and reported minimal comfort levels treating patients with eating disorders. Psychiatry discipline (p = 0.002), eating disorder experience (p = 0.010), and having ≥4 eating disorder-continuing medical education credits (p = 0.037) predicted better knowledge of anorexia nervosa but not bulimia nervosa. Psychiatry residents (p = 0.041), and those who had treated at least one eating disorder patient (p = 0.006), reported significantly greater comfort treating patients with eating disorders. These results suggest that residents and fellows from this sample may benefit from training to increase awareness and confidence necessary to treat patients with eating disorders. Sufficient knowledge and comfort are critical since physicians are often the first health care provider to have contact with patients who have undiagnosed eating disorders.

Frequency, probability, and prediction: easy solutions to cognitive illusions?

PubMed

Griffin, D; Buehler, R

1999-02-01

Many errors in probabilistic judgment have been attributed to people's inability to think in statistical terms when faced with information about a single case. Prior theoretical analyses and empirical results imply that the errors associated with case-specific reasoning may be reduced when people make frequentistic predictions about a set of cases. In studies of three previously identified cognitive biases, we find that frequency-based predictions are different from-but no better than-case-specific judgments of probability. First, in studies of the "planning fallacy, " we compare the accuracy of aggregate frequency and case-specific probability judgments in predictions of students' real-life projects. When aggregate and single-case predictions are collected from different respondents, there is little difference between the two: Both are overly optimistic and show little predictive validity. However, in within-subject comparisons, the aggregate judgments are significantly more conservative than the single-case predictions, though still optimistically biased. Results from studies of overconfidence in general knowledge and base rate neglect in categorical prediction underline a general conclusion. Frequentistic predictions made for sets of events are no more statistically sophisticated, nor more accurate, than predictions made for individual events using subjective probability. Copyright 1999 Academic Press.

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

PubMed

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

2014-01-01

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

The impacts of data constraints on the predictive performance of a general process-based crop model (PeakN-crop v1.0)

NASA Astrophysics Data System (ADS)

Caldararu, Silvia; Purves, Drew W.; Smith, Matthew J.

2017-04-01

Improving international food security under a changing climate and increasing human population will be greatly aided by improving our ability to modify, understand and predict crop growth. What we predominantly have at our disposal are either process-based models of crop physiology or statistical analyses of yield datasets, both of which suffer from various sources of error. In this paper, we present a generic process-based crop model (PeakN-crop v1.0) which we parametrise using a Bayesian model-fitting algorithm to three different sources: data-space-based vegetation indices, eddy covariance productivity measurements and regional crop yields. We show that the model parametrised without data, based on prior knowledge of the parameters, can largely capture the observed behaviour but the data-constrained model greatly improves both the model fit and reduces prediction uncertainty. We investigate the extent to which each dataset contributes to the model performance and show that while all data improve on the prior model fit, the satellite-based data and crop yield estimates are particularly important for reducing model error and uncertainty. Despite these improvements, we conclude that there are still significant knowledge gaps, in terms of available data for model parametrisation, but our study can help indicate the necessary data collection to improve our predictions of crop yields and crop responses to environmental changes.

Variables that Correlate with Faculty Use of Research-Based Instructional Strategies

NASA Astrophysics Data System (ADS)

Henderson, Charles; Dancy, Melissa H.; Niewiadomska-Bugaj, Magdalena

2010-10-01

During the Fall of 2008 a web survey, designed to collect information about pedagogical knowledge and practices, was completed by a representative sample of 722 physics faculty across the United States (a 50.3% response rate). This paper examines how 20 predictor variables correlate with faculty knowledge about and use of research-based instructional strategies (RBIS). Profiles were developed for each of four faculty levels of knowledge about and use of RBIS. Logistic regression analysis was used to identify a subset of the variables that could predict group membership. Five significant predictor variables were identified. High levels of knowledge and use of RBIS were associated with the following characteristics: attendee of the physics and astronomy new faculty workshop, attendee of at least one talk or workshop related to teaching in the last two years, satisfaction with meeting instructional goals, regular reader of one or more journals related to teaching, and being female. High research productivity and large class sizes were not found to be barriers to use of at least some RBIS.

Fuzzy Expert System for Heart Attack Diagnosis

NASA Astrophysics Data System (ADS)

Hassan, Norlida; Arbaiy, Nureize; Shah, Noor Aziyan Ahmad; Afizah Afif@Afip, Zehan

2017-08-01

Heart attack is one of the serious illnesses and reported as the main killer disease. Early prevention is significant to reduce the risk of having the disease. The prevention efforts can be strengthen through awareness and education about risk factor and healthy lifestyle. Therefore the knowledge dissemination is needed to play role in order to distribute and educate public in health care management and disease prevention. Since the knowledge dissemination in medical is important, there is a need to develop a knowledge based system that can emulate human intelligence to assist decision making process. Thereby, this study utilized hybrid artificial intelligence (AI) techniques to develop a Fuzzy Expert System for Diagnosing Heart Attack Disease (HAD). This system integrates fuzzy logic with expert system, which helps the medical practitioner and people to predict the risk and as well as diagnosing heart attack based on given symptom. The development of HAD is expected not only providing expert knowledge but potentially become one of learning resources to help citizens to develop awareness about heart-healthy lifestyle.

Parental nutrition knowledge and attitudes as predictors of 5-6-year-old children's healthy food knowledge.

PubMed

Zarnowiecki, Dorota; Sinn, Natalie; Petkov, John; Dollman, James

2012-07-01

Young children's knowledge about healthy food may influence the formation of their eating behaviours, and parents have a major influence on the development of children's knowledge in the early years. We investigated the extent to which parental nutrition knowledge and attitudes around food predicted young children's knowledge of healthy foods, controlling for other influences such as socio-economic status (SES) and parent education levels in a cross-sectional research design. Children were given a healthy food knowledge activity and parents completed questionnaires. Twenty primary schools in Adelaide, Australia, stratified by SES. We recruited 192 children aged 5-6 years and their parents. Structural equation modelling showed that parent nutrition knowledge predicted children's nutrition knowledge (r = 0·30, P < 0·001) independently of attitudes, SES and education level. Nutrition education for parents, targeted at low-SES areas at higher risk for obesity, may contribute to the development of healthy food knowledge in young children.

The locus of adult intelligence: knowledge, abilities, and nonability traits.

PubMed

Ackerman, P L; Rolfhus, E L

1999-06-01

Some intelligence theorists (e.g., R. B. Cattell, 1943; D. O. Hebb, 1942) have suggested that knowledge is one aspect of human intelligence that is well preserved or increases during adult development. Very little is known about knowledge structures across different domains or about how individual differences in knowledge relate to other traits. Twenty academic and technology-oriented tests were administered to 135 middle-aged adults. In comparison with younger college students, the middle-aged adults knew more about nearly all of the various knowledge domains. Knowledge was partly predicted by general intelligence, by crystallized abilities, and by personality, interest, and self-concept. Implications of this work are discussed in the context of a developmental theory that focuses on the acquisition and maintenance of intelligence-as-knowledge, as well as the role of knowledge for predicting the vocational and avocational task performance of adults.

Predictors of cultural capital on science academic achievement at the 8th grade level

NASA Astrophysics Data System (ADS)

Misner, Johnathan Scott

The purpose of the study was to determine if students' cultural capital is a significant predictor of 8th grade science achievement test scores in urban locales. Cultural capital refers to the knowledge used and gained by the dominant class, which allows social and economic mobility. Cultural capital variables include magazines at home and parental education level. Other variables analyzed include socioeconomic status (SES), gender, and English language learners (ELL). This non-experimental study analyzed the results of the 2011 Eighth Grade Science National Assessment of Educational Progress (NAEP). The researcher analyzed the data using a multivariate stepwise regression analysis. The researcher concluded that the addition of cultural capital factors significantly increased the predictive power of the model where magazines in home, gender, student classified as ELL, parental education level, and SES were the independent variables and science achievement was the dependent variable. For alpha=0.05, the overall test for the model produced a R2 value of 0.232; therefore the model predicted 23.2% of variance in science achievement results. Other major findings include: higher measures of home resources predicted higher 2011 NAEP eighth grade science achievement; males were predicted to have higher 2011 NAEP 8 th grade science achievement; classified ELL students were predicted to score lower on the NAEP eight grade science achievement; higher parent education predicted higher NAEP eighth grade science achievement; lower measures of SES predicted lower 2011 NAEP eighth grade science achievement. This study contributed to the research in this field by identifying cultural capital factors that have been found to have statistical significance on predicting eighth grade science achievement results, which can lead to strategies to help improve science academic achievement among underserved populations.

Computational prediction of protein hot spot residues.

PubMed

Morrow, John Kenneth; Zhang, Shuxing

2012-01-01

Most biological processes involve multiple proteins interacting with each other. It has been recently discovered that certain residues in these protein-protein interactions, which are called hot spots, contribute more significantly to binding affinity than others. Hot spot residues have unique and diverse energetic properties that make them challenging yet important targets in the modulation of protein-protein complexes. Design of therapeutic agents that interact with hot spot residues has proven to be a valid methodology in disrupting unwanted protein-protein interactions. Using biological methods to determine which residues are hot spots can be costly and time consuming. Recent advances in computational approaches to predict hot spots have incorporated a myriad of features, and have shown increasing predictive successes. Here we review the state of knowledge around protein-protein interactions, hot spots, and give an overview of multiple in silico prediction techniques of hot spot residues.

Computational Prediction of Hot Spot Residues

PubMed Central

Morrow, John Kenneth; Zhang, Shuxing

2013-01-01

Most biological processes involve multiple proteins interacting with each other. It has been recently discovered that certain residues in these protein-protein interactions, which are called hot spots, contribute more significantly to binding affinity than others. Hot spot residues have unique and diverse energetic properties that make them challenging yet important targets in the modulation of protein-protein complexes. Design of therapeutic agents that interact with hot spot residues has proven to be a valid methodology in disrupting unwanted protein-protein interactions. Using biological methods to determine which residues are hot spots can be costly and time consuming. Recent advances in computational approaches to predict hot spots have incorporated a myriad of features, and have shown increasing predictive successes. Here we review the state of knowledge around protein-protein interactions, hot spots, and give an overview of multiple in silico prediction techniques of hot spot residues. PMID:22316154

Having Fun on Facebook?: Mothers' Enjoyment as a Moderator of Mental Health and Facebook Use.

PubMed

Kaufmann, Renee; Buckner, Marjorie M; Ledbetter, Andrew M

2017-08-01

This study reports results of a study that examined the extent to which contextual factors (i.e., income level and number of children) might predict a mother's mental health quality, which, in turn, may predict level of engagement with Facebook. Results supported this model, finding that mothers with more children and lower income possess lower mental health quality, and lower mental health quality predicted more frequent Facebook use. However, this pattern was qualified by a mother's level of enjoyment of Facebook, such that mental health quality did not significantly predict Facebook intensity when enjoyment of Facebook was low. This research extends practitioners' knowledge of mothers' mental health quality by identifying a behavior that may indicate lower mental health quality and enhance abilities to recognize mothers who may need support or treatment. Future directions for this research are included.

The Cure: Design and Evaluation of a Crowdsourcing Game for Gene Selection for Breast Cancer Survival Prediction

PubMed Central

Loguercio, Salvatore; Griffith, Obi L; Nanis, Max; Wu, Chunlei; Su, Andrew I

2014-01-01

Background Molecular signatures for predicting breast cancer prognosis could greatly improve care through personalization of treatment. Computational analyses of genome-wide expression datasets have identified such signatures, but these signatures leave much to be desired in terms of accuracy, reproducibility, and biological interpretability. Methods that take advantage of structured prior knowledge (eg, protein interaction networks) show promise in helping to define better signatures, but most knowledge remains unstructured. Crowdsourcing via scientific discovery games is an emerging methodology that has the potential to tap into human intelligence at scales and in modes unheard of before. Objective The main objective of this study was to test the hypothesis that knowledge linking expression patterns of specific genes to breast cancer outcomes could be captured from players of an open, Web-based game. We envisioned capturing knowledge both from the player’s prior experience and from their ability to interpret text related to candidate genes presented to them in the context of the game. Methods We developed and evaluated an online game called The Cure that captured information from players regarding genes for use as predictors of breast cancer survival. Information gathered from game play was aggregated using a voting approach, and used to create rankings of genes. The top genes from these rankings were evaluated using annotation enrichment analysis, comparison to prior predictor gene sets, and by using them to train and test machine learning systems for predicting 10 year survival. Results Between its launch in September 2012 and September 2013, The Cure attracted more than 1000 registered players, who collectively played nearly 10,000 games. Gene sets assembled through aggregation of the collected data showed significant enrichment for genes known to be related to key concepts such as cancer, disease progression, and recurrence. In terms of the predictive accuracy of models trained using this information, these gene sets provided comparable performance to gene sets generated using other methods, including those used in commercial tests. The Cure is available on the Internet. Conclusions The principal contribution of this work is to show that crowdsourcing games can be developed as a means to address problems involving domain knowledge. While most prior work on scientific discovery games and crowdsourcing in general takes as a premise that contributors have little or no expertise, here we demonstrated a crowdsourcing system that succeeded in capturing expert knowledge. PMID:25654473

Research and Prediction of the Application of Multimedia Teaching Aid in Teaching Technical Education on the 2nd Level of Primary Schools

ERIC Educational Resources Information Center

Stebila, Ján

2011-01-01

The purpose and the main aim of the pedagogic experiment were to practically verify the success of Multimedia Teaching Aid (MTA) in conditions of primary schools. We assumed that the use of our multimedia teaching aid in teaching technical education on the 2nd level of primary schools would significantly affect the level of knowledge of pupils…

Understanding HIV-related stigma among Indonesian nurses

PubMed Central

Waluyo, Agung; Culbert, Gabriel J.; Levy, Judith; Norr, Kathleen

2014-01-01

Evidence indicates widespread stigmatization of persons living with HIV (PLWH) in Indonesia. Such attitudes among health care workers could impede the country’s policies for effective diagnosis and medical treatment of PLWH. Nonetheless, research to guide interventions to reduce stigma in health care settings is lacking. Also, the contributions of workplace, religion, and HIV knowledge to nurses’ HIV-related stigma are poorly understood. Our cross-sectional study aimed to describe factors associated with nurses’ stigmatizing attitudes toward PLWH. Four hundred nurses recruited from 4 hospitals in Jakarta, Indonesia, were surveyed using the Nurse AIDS Attitude Scale (NAAS) to measure stigma. Stigmatizing attitudes were significantly predicted by education, HIV training, perceived workplace stigma, religiosity, Islamic religious identification, and affiliation with the Islamic hospital. HIV knowledge was not a significant predictor of stigmatizing attitudes. Organization changes fostering workplace diversity are likely to substantially reduce stigmatizing attitudes in nurses. PMID:24759060

Understanding HIV-related stigma among Indonesian nurses.

PubMed

Waluyo, Agung; Culbert, Gabriel J; Levy, Judith; Norr, Kathleen F

2015-01-01

Evidence indicates widespread stigmatization of persons living with HIV (PLWH) in Indonesia. Such attitudes among health care workers could impede the country's policies for effective diagnosis and medical treatment of PLWH. Nonetheless, research to guide interventions to reduce stigma in health care settings is lacking. Also, the contributions of workplace, religion, and HIV knowledge to nurses' HIV-related stigma are poorly understood. Our cross-sectional study aimed to describe factors associated with nurses' stigmatizing attitudes toward PLWH. Four hundred nurses recruited from four hospitals in Jakarta, Indonesia, were surveyed using the Nurse AIDS Attitude Scale to measure stigma. Stigmatizing attitudes were significantly predicted by education, HIV training, perceived workplace stigma, religiosity, Islamic religious identification, and affiliation with the Islamic hospital. HIV knowledge was not a significant predictor of stigmatizing attitudes. Organization changes fostering workplace diversity are likely to substantially reduce stigmatizing attitudes in nurses. Copyright © 2015 Association of Nurses in AIDS Care. Published by Elsevier Inc. All rights reserved.

Will sea ice thickness initialisation improve Arctic seasonal-to-interannual forecast skill?

NASA Astrophysics Data System (ADS)

Day, J. J.; Hawkins, E.; Tietsche, S.

2014-12-01

A number of recent studies have suggested that Arctic sea ice thickness is an important predictor of Arctic sea ice extent. However, coupled forecast systems do not currently use sea ice thickness observations in their initialization and are therefore missing a potentially important source of additional skill. A set of ensemble potential predictability experiments, with a global climate model, initialized with and without knowledge of the sea ice thickness initial state, have been run to investigate this. These experiments show that accurate knowledge of the sea ice thickness field is crucially important for sea ice concentration and extent forecasts up to eight months ahead. Perturbing sea ice thickness also has a significant impact on the forecast error in the 2m temperature and surface pressure fields a few months ahead. These results show that advancing capabilities to observe and assimilate sea ice thickness into coupled forecast systems could significantly increase skill.

Will Arctic sea ice thickness initialization improve seasonal forecast skill?

NASA Astrophysics Data System (ADS)

Day, J. J.; Hawkins, E.; Tietsche, S.

2014-11-01

Arctic sea ice thickness is thought to be an important predictor of Arctic sea ice extent. However, coupled seasonal forecast systems do not generally use sea ice thickness observations in their initialization and are therefore missing a potentially important source of additional skill. To investigate how large this source is, a set of ensemble potential predictability experiments with a global climate model, initialized with and without knowledge of the sea ice thickness initial state, have been run. These experiments show that accurate knowledge of the sea ice thickness field is crucially important for sea ice concentration and extent forecasts up to 8 months ahead, especially in summer. Perturbing sea ice thickness also has a significant impact on the forecast error in Arctic 2 m temperature a few months ahead. These results suggest that advancing capabilities to observe and assimilate sea ice thickness into coupled forecast systems could significantly increase skill.

Early development of abstract language knowledge: evidence from perception–production transfer of birth-language memory

PubMed Central

Cutler, Anne; Broersma, Mirjam

2017-01-01

Children adopted early in life into another linguistic community typically forget their birth language but retain, unaware, relevant linguistic knowledge that may facilitate (re)learning of birth-language patterns. Understanding the nature of this knowledge can shed light on how language is acquired. Here, international adoptees from Korea with Dutch as their current language, and matched Dutch-native controls, provided speech production data on a Korean consonantal distinction unlike any Dutch distinctions, at the outset and end of an intensive perceptual training. The productions, elicited in a repetition task, were identified and rated by Korean listeners. Adoptees' production scores improved significantly more across the training period than control participants' scores, and, for adoptees only, relative production success correlated significantly with the rate of learning in perception (which had, as predicted, also surpassed that of the controls). Of the adoptee group, half had been adopted at 17 months or older (when talking would have begun), while half had been prelinguistic (under six months). The former group, with production experience, showed no advantage over the group without. Thus the adoptees' retained knowledge of Korean transferred from perception to production and appears to be abstract in nature rather than dependent on the amount of experience. PMID:28280567

Memory and Language in Middle Childhood in Individuals with a History of Specific Language Impairment

PubMed Central

Hesketh, Anne; Conti-Ramsden, Gina

2013-01-01

This study reports on the sensitivity of sentence repetition as a marker of specific language impairment (SLI) in different subgroups of children in middle childhood and examines the role of memory and grammatical knowledge in the performance of children with and without language difficulties on this task. Eleven year old children, 197 with a history of SLI and 75 typically developing (TD) peers were administered sentence repetition, phonological short term memory (PSTM) and grammatical morphology tasks. Children with a history of SLI were divided into four subgroups: specific language impairment, non-specific language impairment, low cognition with resolved language and resolved. Performance on the sentence repetition task was significantly impaired in all four subgroups of children with a history of SLI when compared to their age peers. Regression analyses revealed grammatical knowledge was predictive of performance for TD children and children with a history of SLI. However, memory abilities were significantly predictive of sentence repetition task performance for children with a history of SLI only. Processes involved in sentence repetition are more taxing of PSTM for individuals with a history of SLI in middle childhood in a way that does not appear to be the case for TD children. PMID:23409172

[Academic performance in first year medical students: an explanatory multivariate model].

PubMed

Urrutia Aguilar, María Esther; Ortiz León, Silvia; Fouilloux Morales, Claudia; Ponce Rosas, Efrén Raúl; Guevara Guzmán, Rosalinda

2014-12-01

Current education is focused in intellectual, affective, and ethical aspects, thus acknowledging their significance in students´ metacognition. Nowadays, it is known that an adequate and motivating environment together with a positive attitude towards studies is fundamental to induce learning. Medical students are under multiple stressful, academic, personal, and vocational situations. To identify psychosocial, vocational, and academic variables of 2010-2011 first year medical students at UNAM that may help predict their academic performance. Academic surveys of psychological and vocational factors were applied; an academic follow-up was carried out to obtain a multivariate model. The data were analyzed considering descriptive, comparative, correlative, and predictive statistics. The main variables that affect students´ academic performance are related to previous knowledge and to psychological variables. The results show the significance of implementing institutional programs to support students throughout their college adaptation.

Data Mining and Knowledge Management in Higher Education -Potential Applications.

ERIC Educational Resources Information Center

Luan, Jing

This paper introduces a new decision support tool, data mining, in the context of knowledge management. The most striking features of data mining techniques are clustering and prediction. The clustering aspect of data mining offers comprehensive characteristics analysis of students, while the predicting function estimates the likelihood for a…

Health Literacy Predicts Cardiac Knowledge Gains in Cardiac Rehabilitation Participants

ERIC Educational Resources Information Center

Mattson, Colleen C.; Rawson, Katherine; Hughes, Joel W.; Waechter, Donna; Rosneck, James

2015-01-01

Objective: Health literacy is increasingly recognised as a potentially important patient characteristic related to patient education efforts. We evaluated whether health literacy would predict gains in knowledge after completion of patient education in cardiac rehabilitation. Method: This was a re-post observational analysis study design based on…

Paired-Associate and Feedback-Based Weather Prediction Tasks Support Multiple Category Learning Systems.

PubMed

Li, Kaiyun; Fu, Qiufang; Sun, Xunwei; Zhou, Xiaoyan; Fu, Xiaolan

2016-01-01

It remains unclear whether probabilistic category learning in the feedback-based weather prediction task (FB-WPT) can be mediated by a non-declarative or procedural learning system. To address this issue, we compared the effects of training time and verbal working memory, which influence the declarative learning system but not the non-declarative learning system, in the FB and paired-associate (PA) WPTs, as the PA task recruits a declarative learning system. The results of Experiment 1 showed that the optimal accuracy in the PA condition was significantly decreased when the training time was reduced from 7 to 3 s, but this did not occur in the FB condition, although shortened training time impaired the acquisition of explicit knowledge in both conditions. The results of Experiment 2 showed that the concurrent working memory task impaired the optimal accuracy and the acquisition of explicit knowledge in the PA condition but did not influence the optimal accuracy or the acquisition of self-insight knowledge in the FB condition. The apparent dissociation results between the FB and PA conditions suggested that a non-declarative or procedural learning system is involved in the FB-WPT and provided new evidence for the multiple-systems theory of human category learning.

Paired-Associate and Feedback-Based Weather Prediction Tasks Support Multiple Category Learning Systems

PubMed Central

Li, Kaiyun; Fu, Qiufang; Sun, Xunwei; Zhou, Xiaoyan; Fu, Xiaolan

2016-01-01

It remains unclear whether probabilistic category learning in the feedback-based weather prediction task (FB-WPT) can be mediated by a non-declarative or procedural learning system. To address this issue, we compared the effects of training time and verbal working memory, which influence the declarative learning system but not the non-declarative learning system, in the FB and paired-associate (PA) WPTs, as the PA task recruits a declarative learning system. The results of Experiment 1 showed that the optimal accuracy in the PA condition was significantly decreased when the training time was reduced from 7 to 3 s, but this did not occur in the FB condition, although shortened training time impaired the acquisition of explicit knowledge in both conditions. The results of Experiment 2 showed that the concurrent working memory task impaired the optimal accuracy and the acquisition of explicit knowledge in the PA condition but did not influence the optimal accuracy or the acquisition of self-insight knowledge in the FB condition. The apparent dissociation results between the FB and PA conditions suggested that a non-declarative or procedural learning system is involved in the FB-WPT and provided new evidence for the multiple-systems theory of human category learning. PMID:27445958

Measuring North Carolina pharmacists' support for expanded authority to administer human papillomavirus vaccines.

PubMed

Richman, Alice R; Swanson, Ryan S; Branham, Ashley R; Partridge, Brittney N

2013-12-01

To assess North Carolina pharmacists' level of support for expanded authority to administer human papillomavirus (HPV) vaccines to identify concerns/benefits about expanded authority and to understand what factors predict support for expanded authority. A 16-item electronic survey was e-mailed to all the pharmacists registered with the North Carolina Board of Pharmacy (n = 9502) between January and February 2011 (1600 pharmacists responded). The survey assessed HPV knowledge, level of support for expanded authority, and comfort level of HPV vaccine administration. Many (64%) pharmacists were supportive of a rule change/legislation that would authorize pharmacists to administer HPV vaccines. Younger pharmacists were more supportive of expansion when compared to older pharmacists (r = -.138, P < .001). Pharmacists with higher knowledge scores were more supportive of expansion (r = .223, P < .001). Reporting a higher level of comfort in administering HPV vaccines at their pharmacy was significantly and positively correlated with higher level of support for expansion (r = .624, P < .001). In the multivariate analysis, HPV knowledge, comfort level in administering vaccine, patient age, and type of pharmacy were all predictive of higher level of support for expanded authority where employed. A large proportion of pharmacists were supportive of an expanded role in providing HPV vaccines. Exploring alternate delivery mechanisms like this one is advantageous.

Longitudinal Relations Between Adolescent and Parental Behaviors, Parental Knowledge, and Internalizing Behaviors Among Urban Adolescents

PubMed Central

Garthe, Rachel C.; Sullivan, Terri; Kliewer, Wendy

2018-01-01

High prevalence rates of depression and anxiety among adolescents underscore the importance of identifying parental and adolescent behaviors that may lessen the risk for these outcomes. Previous research has shown that parental acceptance, parental knowledge, and child disclosure are negatively associated with internalizing behaviors. It is also important to explore the impact of internalizing behaviors on these parental and child constructs. The current study examined longitudinal relationships between parental acceptance, parental knowledge, child disclosure, and internalizing symptoms across a one-year time period. Participants were 358 adolescents (54 % female) and their primary caregivers, who were primarily African American (92 %). Parents and adolescents provided data through face-to-face interviews. Results showed that parental knowledge and parental acceptance predicted child disclosure, and child disclosure predicted parental knowledge one year later. Higher levels of parental acceptance predicted lower levels of adolescent-reported depressive symptoms, while higher levels of parental report of adolescents’ internalizing symptoms predicted lower levels of parental knowledge. No differences in the strength of these relationships were found across grade or gender. These findings highlight the role of the adolescent’s perceived acceptance by parents in promoting children’s disclosure, and the benefits of parental acceptance in decreasing depressive symptoms over time. Overall, these results show the impact that both adolescent and parental behaviors and internalizing behaviors have on each other across time. PMID:24609843

Importance of ligand reorganization free energy in protein-ligand binding-affinity prediction.

PubMed

Yang, Chao-Yie; Sun, Haiying; Chen, Jianyong; Nikolovska-Coleska, Zaneta; Wang, Shaomeng

2009-09-30

Accurate prediction of the binding affinities of small-molecule ligands to their biological targets is fundamental for structure-based drug design but remains a very challenging task. In this paper, we have performed computational studies to predict the binding models of 31 small-molecule Smac (the second mitochondria-derived activator of caspase) mimetics to their target, the XIAP (X-linked inhibitor of apoptosis) protein, and their binding affinities. Our results showed that computational docking was able to reliably predict the binding models, as confirmed by experimentally determined crystal structures of some Smac mimetics complexed with XIAP. However, all the computational methods we have tested, including an empirical scoring function, two knowledge-based scoring functions, and MM-GBSA (molecular mechanics and generalized Born surface area), yield poor to modest prediction for binding affinities. The linear correlation coefficient (r(2)) value between the predicted affinities and the experimentally determined affinities was found to be between 0.21 and 0.36. Inclusion of ensemble protein-ligand conformations obtained from molecular dynamic simulations did not significantly improve the prediction. However, major improvement was achieved when the free-energy change for ligands between their free- and bound-states, or "ligand-reorganization free energy", was included in the MM-GBSA calculation, and the r(2) value increased from 0.36 to 0.66. The prediction was validated using 10 additional Smac mimetics designed and evaluated by an independent group. This study demonstrates that ligand reorganization free energy plays an important role in the overall binding free energy between Smac mimetics and XIAP. This term should be evaluated for other ligand-protein systems and included in the development of new scoring functions. To our best knowledge, this is the first computational study to demonstrate the importance of ligand reorganization free energy for the prediction of protein-ligand binding free energy.

Process consistency in models: The importance of system signatures, expert knowledge, and process complexity

NASA Astrophysics Data System (ADS)

Hrachowitz, M.; Fovet, O.; Ruiz, L.; Euser, T.; Gharari, S.; Nijzink, R.; Freer, J.; Savenije, H. H. G.; Gascuel-Odoux, C.

2014-09-01

Hydrological models frequently suffer from limited predictive power despite adequate calibration performances. This can indicate insufficient representations of the underlying processes. Thus, ways are sought to increase model consistency while satisfying the contrasting priorities of increased model complexity and limited equifinality. In this study, the value of a systematic use of hydrological signatures and expert knowledge for increasing model consistency was tested. It was found that a simple conceptual model, constrained by four calibration objective functions, was able to adequately reproduce the hydrograph in the calibration period. The model, however, could not reproduce a suite of hydrological signatures, indicating a lack of model consistency. Subsequently, testing 11 models, model complexity was increased in a stepwise way and counter-balanced by "prior constraints," inferred from expert knowledge to ensure a model which behaves well with respect to the modeler's perception of the system. We showed that, in spite of unchanged calibration performance, the most complex model setup exhibited increased performance in the independent test period and skill to better reproduce all tested signatures, indicating a better system representation. The results suggest that a model may be inadequate despite good performance with respect to multiple calibration objectives and that increasing model complexity, if counter-balanced by prior constraints, can significantly increase predictive performance of a model and its skill to reproduce hydrological signatures. The results strongly illustrate the need to balance automated model calibration with a more expert-knowledge-driven strategy of constraining models.

Jointly learning word embeddings using a corpus and a knowledge base

PubMed Central

Bollegala, Danushka; Maehara, Takanori; Kawarabayashi, Ken-ichi

2018-01-01

Methods for representing the meaning of words in vector spaces purely using the information distributed in text corpora have proved to be very valuable in various text mining and natural language processing (NLP) tasks. However, these methods still disregard the valuable semantic relational structure between words in co-occurring contexts. These beneficial semantic relational structures are contained in manually-created knowledge bases (KBs) such as ontologies and semantic lexicons, where the meanings of words are represented by defining the various relationships that exist among those words. We combine the knowledge in both a corpus and a KB to learn better word embeddings. Specifically, we propose a joint word representation learning method that uses the knowledge in the KBs, and simultaneously predicts the co-occurrences of two words in a corpus context. In particular, we use the corpus to define our objective function subject to the relational constrains derived from the KB. We further utilise the corpus co-occurrence statistics to propose two novel approaches, Nearest Neighbour Expansion (NNE) and Hedged Nearest Neighbour Expansion (HNE), that dynamically expand the KB and therefore derive more constraints that guide the optimisation process. Our experimental results over a wide-range of benchmark tasks demonstrate that the proposed method statistically significantly improves the accuracy of the word embeddings learnt. It outperforms a corpus-only baseline and reports an improvement of a number of previously proposed methods that incorporate corpora and KBs in both semantic similarity prediction and word analogy detection tasks. PMID:29529052

Predictive top-down integration of prior knowledge during speech perception.

PubMed

Sohoglu, Ediz; Peelle, Jonathan E; Carlyon, Robert P; Davis, Matthew H

2012-06-20

A striking feature of human perception is that our subjective experience depends not only on sensory information from the environment but also on our prior knowledge or expectations. The precise mechanisms by which sensory information and prior knowledge are integrated remain unclear, with longstanding disagreement concerning whether integration is strictly feedforward or whether higher-level knowledge influences sensory processing through feedback connections. Here we used concurrent EEG and MEG recordings to determine how sensory information and prior knowledge are integrated in the brain during speech perception. We manipulated listeners' prior knowledge of speech content by presenting matching, mismatching, or neutral written text before a degraded (noise-vocoded) spoken word. When speech conformed to prior knowledge, subjective perceptual clarity was enhanced. This enhancement in clarity was associated with a spatiotemporal profile of brain activity uniquely consistent with a feedback process: activity in the inferior frontal gyrus was modulated by prior knowledge before activity in lower-level sensory regions of the superior temporal gyrus. In parallel, we parametrically varied the level of speech degradation, and therefore the amount of sensory detail, so that changes in neural responses attributable to sensory information and prior knowledge could be directly compared. Although sensory detail and prior knowledge both enhanced speech clarity, they had an opposite influence on the evoked response in the superior temporal gyrus. We argue that these data are best explained within the framework of predictive coding in which sensory activity is compared with top-down predictions and only unexplained activity propagated through the cortical hierarchy.

Learning to predict is spared in mild cognitive impairment due to Alzheimer's disease.

PubMed

Baker, Rosalind; Bentham, Peter; Kourtzi, Zoe

2015-10-01

Learning the statistics of the environment is critical for predicting upcoming events. However, little is known about how we translate previous knowledge about scene regularities to sensory predictions. Here, we ask whether patients with mild cognitive impairment due to Alzheimer's disease (MCI-AD) that are known to have spared implicit but impaired explicit recognition memory are able to learn temporal regularities and predict upcoming events. We tested the ability of MCI-AD patients and age-matched controls to predict the orientation of a test stimulus following exposure to sequences of leftwards or rightwards oriented gratings. Our results demonstrate that exposure to temporal sequences without feedback facilitates the ability to predict an upcoming stimulus in both MCI-AD patients and controls. Further, we show that executive cognitive control may account for individual variability in predictive learning. That is, we observed significant positive correlations of performance in attentional and working memory tasks with post-training performance in the prediction task. Taken together, these results suggest a mediating role of circuits involved in cognitive control (i.e. frontal circuits) that may support the ability for predictive learning in MCI-AD.

Adolescents' Thoughts and Feelings about AIDS in Relation to Cognitive Maturity.

ERIC Educational Resources Information Center

Peterson, Candida C.; Murphy, Lisa

1990-01-01

Studied adolescents' (N=163) formal operational reasoning in relation to Acquired Immune Deficiency Syndrome (AIDS) knowledge, AIDS fear, sexual knowledge, and reactions to AIDS victims. Found that advanced reasoning predicted better AIDS knowledge and general sexual knowledge. Advanced reasoning and AIDS knowledge were also linked with heightened…

The Effects of Motivation on Student Performance on Science Assessments

NASA Astrophysics Data System (ADS)

Glenn, Tina Heard

Academic achievement of public school students in the United States has significantly fallen behind other countries. Students' lack of knowledge of, or interest in, basic science and math has led to fewer graduates of science, technology, engineering, and math-related fields (STEM), a factor that may affect their career success and will certainly affect the numbers in the workforce who are prepared for some STEM jobs. Drawing from self-determination theory and achievement theory, the purpose of this correlational study was to determine whether there were significant relationships between high school academic performance in science classes, motivations (self-efficacy, self-regulation, and intrinsic and extrinsic goal orientation), and academic performance in an introductory online college biology class. Data were obtained at 2 points in time from a convenience multiethnic sample of adult male ( n =16) and female (n = 49) community college students in the southeast United States. Correlational analyses indicated no statistically significant relationships for intrinsic or extrinsic goal orientation, self-efficacy, or self-regulation with high school science mean-GPA nor college biology final course grade. However, high school academic performance in science classes significantly predicted college performance in an entry-level online biology class. The implications of positive social change include knowledge useful for educational institutions to explore additional factors that may motivate students to enroll in science courses, potentially leading to an increase in scientific knowledge and STEM careers.

Does Environmental Knowledge Inhibit Hominin Dispersal?

PubMed

Wren, Colin D; Costopoulos, Andre

2015-07-01

We investigated the relationship between the dispersal potential of a hominin population, its local-scale foraging strategies, and the characteristics of the resource environment using an agent-based modeling approach. In previous work we demonstrated that natural selection can favor a relatively low capacity for assessing and predicting the quality of the resource environment, especially when the distribution of resources is highly clustered. That work also suggested that the more knowledge foraging populations had about their environment, the less likely they were to abandon the landscape they know and disperse into novel territory. The present study gives agents new individual and social strategies for learning about their environment. For both individual and social learning, natural selection favors decreased levels of environmental knowledge, particularly in low-heterogeneity environments. Social acquisition of detailed environmental knowledge results in crowding of agents, which reduces available reproductive space and relative fitness. Agents with less environmental knowledge move away from resource clusters and into areas with more space available for reproduction. These results suggest that, rather than being a requirement for successful dispersal, environmental knowledge strengthens the ties to particular locations and significantly reduces the dispersal potential as a result. The evolved level of environmental knowledge in a population depends on the characteristics of the resource environment and affects the dispersal capacity of the population.

Self organising hypothesis networks: a new approach for representing and structuring SAR knowledge

PubMed Central

2014-01-01

Background Combining different sources of knowledge to build improved structure activity relationship models is not easy owing to the variety of knowledge formats and the absence of a common framework to interoperate between learning techniques. Most of the current approaches address this problem by using consensus models that operate at the prediction level. We explore the possibility to directly combine these sources at the knowledge level, with the aim to harvest potentially increased synergy at an earlier stage. Our goal is to design a general methodology to facilitate knowledge discovery and produce accurate and interpretable models. Results To combine models at the knowledge level, we propose to decouple the learning phase from the knowledge application phase using a pivot representation (lingua franca) based on the concept of hypothesis. A hypothesis is a simple and interpretable knowledge unit. Regardless of its origin, knowledge is broken down into a collection of hypotheses. These hypotheses are subsequently organised into hierarchical network. This unification permits to combine different sources of knowledge into a common formalised framework. The approach allows us to create a synergistic system between different forms of knowledge and new algorithms can be applied to leverage this unified model. This first article focuses on the general principle of the Self Organising Hypothesis Network (SOHN) approach in the context of binary classification problems along with an illustrative application to the prediction of mutagenicity. Conclusion It is possible to represent knowledge in the unified form of a hypothesis network allowing interpretable predictions with performances comparable to mainstream machine learning techniques. This new approach offers the potential to combine knowledge from different sources into a common framework in which high level reasoning and meta-learning can be applied; these latter perspectives will be explored in future work. PMID:24959206

Reducing cyberbullying: A theory of reasoned action-based video prevention program for college students.

PubMed

Doane, Ashley N; Kelley, Michelle L; Pearson, Matthew R

2016-01-01

Few studies have evaluated the effectiveness of cyberbullying prevention/intervention programs. The goals of the present study were to develop a Theory of Reasoned Action (TRA)-based video program to increase cyberbullying knowledge (1) and empathy toward cyberbullying victims (2), reduce favorable attitudes toward cyberbullying (3), decrease positive injunctive (4) and descriptive norms about cyberbullying (5), and reduce cyberbullying intentions (6) and cyberbullying behavior (7). One hundred sixty-seven college students were randomly assigned to an online video cyberbullying prevention program or an assessment-only control group. Immediately following the program, attitudes and injunctive norms for all four types of cyberbullying behavior (i.e., unwanted contact, malice, deception, and public humiliation), descriptive norms for malice and public humiliation, empathy toward victims of malice and deception, and cyberbullying knowledge significantly improved in the experimental group. At one-month follow-up, malice and public humiliation behavior, favorable attitudes toward unwanted contact, deception, and public humiliation, and injunctive norms for public humiliation were significantly lower in the experimental than the control group. Cyberbullying knowledge was significantly higher in the experimental than the control group. These findings demonstrate a brief cyberbullying video is capable of improving, at one-month follow-up, cyberbullying knowledge, cyberbullying perpetration behavior, and TRA constructs known to predict cyberbullying perpetration. Considering the low cost and ease with which a video-based prevention/intervention program can be delivered, this type of approach should be considered to reduce cyberbullying. © 2015 Wiley Periodicals, Inc.

Conceptual Knowledge Influences Decision Making Differently in Individuals with High or Low Cognitive Flexibility: An ERP Study.

PubMed

Dong, Xiaofei; Du, Xiumin; Qi, Bing

2016-01-01

Studies using the Iowa Gambling Task (IGT) have distinguished between good and bad decision makers and have provided an explanation for deficits in decision making. Previous studies have demonstrated a link between Wisconsin Card Sorting Test (WCST) performance and IGT performance, but the results were not consistent and failed to explain why WCST performance can predict IGT performance. The present study aimed to demonstrate that WCST performance can predict IGT performance and to identify the cognitive component of the WCST that affects IGT performance using event-related potentials (ERPs). In this study, 39 healthy subjects (5 subjects were excluded) were divided into a high group and a low group based on their global score on the WCST. A single-choice version of the IGT was used to eliminate the impact of retrieval strategies on the choice evaluation process and interference due to uncorrelated decks. Differences in the underlying neural mechanisms and explicit knowledge between the two groups during the three stages of the decision-making process were described. Based on the information processing perspective, we divided the decision-making process into three stages: choice evaluation, response selection, and feedback processing. The behavioral results showed that the highly cognitively flexible participants performed better on the IGT and acquired more knowledge of the task. The ERP results showed that during the choice evaluation stage, the P300 recorded from central and parietal regions when a bad deck appeared was larger in the high group participants than in the low group participants. During the response selection stage, the effect of choice type was significant only in the frontal region in the high group, with a larger effect for passing. During the feedback evaluation stage, a larger FRN was evoked for a loss than for a win in the high group, whereas the FRN effect was absent in the low group. Compared with the participants with low cognitive flexibility, the participants with high cognitive flexibility performed better on the IGT, acquired more knowledge of the task, and displayed more obvious somatic markers. The low group participants showed reduced working memory abilities during the choice evaluation stage. The appropriate somatic markers reflected by the DPN is formed only when conceptual knowledge is gained in the response selection stage. The absence of an FRN effect in the subjects who performed poorly on the WCST suggests a significant deficit in feedback learning and reward prediction.

Conceptual Knowledge Influences Decision Making Differently in Individuals with High or Low Cognitive Flexibility: An ERP Study

PubMed Central

Dong, Xiaofei; Du, Xiumin; Qi, Bing

2016-01-01

Objective Studies using the Iowa Gambling Task (IGT) have distinguished between good and bad decision makers and have provided an explanation for deficits in decision making. Previous studies have demonstrated a link between Wisconsin Card Sorting Test (WCST) performance and IGT performance, but the results were not consistent and failed to explain why WCST performance can predict IGT performance. The present study aimed to demonstrate that WCST performance can predict IGT performance and to identify the cognitive component of the WCST that affects IGT performance using event-related potentials (ERPs). Methods In this study, 39 healthy subjects (5 subjects were excluded) were divided into a high group and a low group based on their global score on the WCST. A single-choice version of the IGT was used to eliminate the impact of retrieval strategies on the choice evaluation process and interference due to uncorrelated decks. Differences in the underlying neural mechanisms and explicit knowledge between the two groups during the three stages of the decision-making process were described. Results Based on the information processing perspective, we divided the decision-making process into three stages: choice evaluation, response selection, and feedback processing. The behavioral results showed that the highly cognitively flexible participants performed better on the IGT and acquired more knowledge of the task. The ERP results showed that during the choice evaluation stage, the P300 recorded from central and parietal regions when a bad deck appeared was larger in the high group participants than in the low group participants. During the response selection stage, the effect of choice type was significant only in the frontal region in the high group, with a larger effect for passing. During the feedback evaluation stage, a larger FRN was evoked for a loss than for a win in the high group, whereas the FRN effect was absent in the low group. Conclusion Compared with the participants with low cognitive flexibility, the participants with high cognitive flexibility performed better on the IGT, acquired more knowledge of the task, and displayed more obvious somatic markers. The low group participants showed reduced working memory abilities during the choice evaluation stage. The appropriate somatic markers reflected by the DPN is formed only when conceptual knowledge is gained in the response selection stage. The absence of an FRN effect in the subjects who performed poorly on the WCST suggests a significant deficit in feedback learning and reward prediction. PMID:27479484

The unique role of lexical accessibility in predicting kindergarten emergent literacy.

PubMed

Verhoeven, Ludo; van Leeuwe, Jan; Irausquin, Rosemarie; Segers, Eliane

The goal of this longitudinal study was to examine how lexical quality predicts the emergence of literacy abilities in 169 Dutch kindergarten children before formal reading instruction has started. At the beginning of the school year, a battery of precursor measures associated with lexical quality was related to the emergence of letter knowledge and word decoding. Confirmatory factor analysis evidenced five domains related to lexical quality, i.e., vocabulary, phonological coding, phonological awareness, lexical retrieval and phonological working memory. Structural equation modeling showed that the development of letter knowledge during the year could be predicted from children's phonological awareness and lexical retrieval, and the emergence of word decoding from their phonological awareness and letter knowledge. It is concluded that it is primarily the accessibility of phonological representations in the mental lexicon that predicts the emergence of literacy in kindergarten.

Football gambling three arm-controlled study: gamblers, amateurs and laypersons.

PubMed

Huberfeld, Ronen; Gersner, Roman; Rosenberg, Oded; Kotler, Moshe; Dannon, Pinhas N

2013-01-01

Football (soccer) betting, as a strategic form of betting, became one of the favorite wagers for pathological gamblers. Previous studies demonstrated the psychological and biological significance of the 'illusion of control' (personal control) and 'near miss' results in gambling. In our study, we explored whether knowledge and expertise of pathological sports gamblers can ensure a successful bet. Participants were divided into three groups of individuals - pathological gamblers, amateurs and laypersons - and were asked to predict in advance the general result and the exact result of football matches in the European Champions League Round of 16. The 165 participants included 53 pathological sports gamblers (52 males and 1 female), 78 laypersons (45 females and 33 males) and 34 amateurs (all males). After a thorough statistical analysis, we found no significant differences between the groups, no matter what kind of previous knowledge they had acquired. This study demonstrates that the 'illusion of control' of pathological gamblers, attained by knowledge of the game and its latest data and information (especially in a strategic gamble as football betting), has no factual background. Moreover, our study demonstrates without a doubt that there is no significant difference between the male pathological sports gamblers group and the male/female laypersons group. Copyright © 2012 S. Karger AG, Basel.

In Silico Mining for Antimalarial Structure-Activity Knowledge and Discovery of Novel Antimalarial Curcuminoids.

PubMed

Viira, Birgit; Gendron, Thibault; Lanfranchi, Don Antoine; Cojean, Sandrine; Horvath, Dragos; Marcou, Gilles; Varnek, Alexandre; Maes, Louis; Maran, Uko; Loiseau, Philippe M; Davioud-Charvet, Elisabeth

2016-06-29

Malaria is a parasitic tropical disease that kills around 600,000 patients every year. The emergence of resistant Plasmodium falciparum parasites to artemisinin-based combination therapies (ACTs) represents a significant public health threat, indicating the urgent need for new effective compounds to reverse ACT resistance and cure the disease. For this, extensive curation and homogenization of experimental anti-Plasmodium screening data from both in-house and ChEMBL sources were conducted. As a result, a coherent strategy was established that allowed compiling coherent training sets that associate compound structures to the respective antimalarial activity measurements. Seventeen of these training sets led to the successful generation of classification models discriminating whether a compound has a significant probability to be active under the specific conditions of the antimalarial test associated with each set. These models were used in consensus prediction of the most likely active from a series of curcuminoids available in-house. Positive predictions together with a few predicted as inactive were then submitted to experimental in vitro antimalarial testing. A large majority from predicted compounds showed antimalarial activity, but not those predicted as inactive, thus experimentally validating the in silico screening approach. The herein proposed consensus machine learning approach showed its potential to reduce the cost and duration of antimalarial drug discovery.

Multiple dynamics in a single predator-prey system: experimental effects of food quality.

PubMed Central

Nelson, W A; McCauley, E; Wrona, F J

2001-01-01

Recent work with the freshwater zooplankton Daphnia has suggested that the quality of its algal prey can have a significant effect on its demographic rates and life-history patterns. Predator-prey theory linking food quantity and food quality predicts that a single system should be able to display two distinct patterns of population dynamics. One pattern is predicted to have high herbivore and low algal biomass dynamics (high HBD), whereas the other is predicted to have low herbivore and high algal biomass dynamics (low HBD). Despite these predictions and the stoichiometric evidence that many phytoplankton communities may have poor access to food of quality, there have been few tests of whether a dynamic predator-prey system can display both of these distinct patterns. Here we report, to the authors' knowledge, the first evidence for two dynamical patterns, as predicted by theory, in a single predator-prey system. We show that the high HBD is a result of food quantity effects and that the low HBD is a result of food quality effects, which are maintained by phosphorus limitation in the predator. These results provide an important link between the known effects of nutrient limitation in herbivores and the significance of prey quality in predator-prey population dynamics in natural zooplankton communities. PMID:11410147

A Unified Framework for Activity Recognition-Based Behavior Analysis and Action Prediction in Smart Homes

PubMed Central

Fatima, Iram; Fahim, Muhammad; Lee, Young-Koo; Lee, Sungyoung

2013-01-01

In recent years, activity recognition in smart homes is an active research area due to its applicability in many applications, such as assistive living and healthcare. Besides activity recognition, the information collected from smart homes has great potential for other application domains like lifestyle analysis, security and surveillance, and interaction monitoring. Therefore, discovery of users common behaviors and prediction of future actions from past behaviors become an important step towards allowing an environment to provide personalized service. In this paper, we develop a unified framework for activity recognition-based behavior analysis and action prediction. For this purpose, first we propose kernel fusion method for accurate activity recognition and then identify the significant sequential behaviors of inhabitants from recognized activities of their daily routines. Moreover, behaviors patterns are further utilized to predict the future actions from past activities. To evaluate the proposed framework, we performed experiments on two real datasets. The results show a remarkable improvement of 13.82% in the accuracy on average of recognized activities along with the extraction of significant behavioral patterns and precise activity predictions with 6.76% increase in F-measure. All this collectively help in understanding the users” actions to gain knowledge about their habits and preferences. PMID:23435057

Tell Me Why! Content Knowledge Predicts Process-Orientation of Math Researchers' and Math Teachers' Explanations

ERIC Educational Resources Information Center

Lachner, Andreas; Nückles, Matthias

2016-01-01

In two studies, we investigated the impact of instructors' different knowledge bases on the quality of their instructional explanations. In Study 1, we asked 20 mathematics teachers (with high pedagogical content knowledge, but lower content knowledge) and 15 mathematicians (with lower pedagogical content knowledge, but high content knowledge) to…

Memory plasticity in older adults: Cognitive predictors of training response and maintenance following learning of number-consonant mnemonic.

PubMed

Sandberg, Petra; Rönnlund, Michael; Derwinger-Hallberg, Anna; Stigsdotter Neely, Anna

2016-10-01

The study investigated the relationship between cognitive factors and gains in number recall following training in a number-consonant mnemonic in a sample of 112 older adults (M = 70.9 years). The cognitive factors examined included baseline episodic memory, working memory, processing speed, and verbal knowledge. In addition, predictors of maintenance of gains to a follow-up assessment, eight months later, were examined. Whereas working memory was a prominent predictor of baseline recall, the magnitude of gains in recall from pre- to post-test assessments were predicted by baseline episodic memory, processing speed, and verbal knowledge. Verbal knowledge was the only significant predictor of maintenance. Collectively, the results indicate the need to consider multiple factors to account for individual differences in memory plasticity. The potential contribution of additional factors to individual differences in memory plasticity is discussed.

Critical Thinking Disposition of Nurse Practitioners in Taiwan.

PubMed

Hsu, Hsiu-Ying; Chang, Shu-Chen; Chang, Ai-Ling; Chen, Shiah-Lian

2017-09-01

Critical thinking disposition (CTD) is crucial for nurse practitioners who face complex patient care scenarios. This study explored the CTD of nurse practitioners and related factors. The study was a cross-sectional descriptive design. A purposive sample was recruited from a medical center and its hospital branches in central Taiwan. A structured questionnaire was used to collect data from 210 nurse practitioners. The participants obtained the highest average score on systematicity and analyticity. CTD had a significant positive correlation with fundamental knowledge readiness, professional knowledge readiness, and confidence in making clinical decisions. Professional knowledge readiness, education level, and on-the-job training predicted the score of the participants on overall CTD. On-the-job training and education level may influence the CTD of nurse practitioners. Providing formal or on-the-job continuing education training to nurse practitioners may help enhance their CTD. J Contin Educ Nurs. 2017;48(9):425-430. Copyright 2017, SLACK Incorporated.

Approximate number word knowledge before the cardinal principle.

PubMed

Gunderson, Elizabeth A; Spaepen, Elizabet; Levine, Susan C

2015-02-01

Approximate number word knowledge-understanding the relation between the count words and the approximate magnitudes of sets-is a critical piece of knowledge that predicts later math achievement. However, researchers disagree about when children first show evidence of approximate number word knowledge-before, or only after, they have learned the cardinal principle. In two studies, children who had not yet learned the cardinal principle (subset-knowers) produced sets in response to number words (verbal comprehension task) and produced number words in response to set sizes (verbal production task). As evidence of approximate number word knowledge, we examined whether children's numerical responses increased with increasing numerosity of the stimulus. In Study 1, subset-knowers (ages 3.0-4.2 years) showed approximate number word knowledge above their knower-level on both tasks, but this effect did not extend to numbers above 4. In Study 2, we collected data from a broader age range of subset-knowers (ages 3.1-5.6 years). In this sample, children showed approximate number word knowledge on the verbal production task even when only examining set sizes above 4. Across studies, children's age predicted approximate number word knowledge (above 4) on the verbal production task when controlling for their knower-level, study (1 or 2), and parents' education, none of which predicted approximation ability. Thus, children can develop approximate knowledge of number words up to 10 before learning the cardinal principle. Furthermore, approximate number word knowledge increases with age and might not be closely related to the development of exact number word knowledge. Copyright © 2014 Elsevier Inc. All rights reserved.

Knowledge-guided gene prioritization reveals new insights into the mechanisms of chemoresistance.

PubMed

Emad, Amin; Cairns, Junmei; Kalari, Krishna R; Wang, Liewei; Sinha, Saurabh

2017-08-11

Identification of genes whose basal mRNA expression predicts the sensitivity of tumor cells to cytotoxic treatments can play an important role in individualized cancer medicine. It enables detailed characterization of the mechanism of action of drugs. Furthermore, screening the expression of these genes in the tumor tissue may suggest the best course of chemotherapy or a combination of drugs to overcome drug resistance. We developed a computational method called ProGENI to identify genes most associated with the variation of drug response across different individuals, based on gene expression data. In contrast to existing methods, ProGENI also utilizes prior knowledge of protein-protein and genetic interactions, using random walk techniques. Analysis of two relatively new and large datasets including gene expression data on hundreds of cell lines and their cytotoxic responses to a large compendium of drugs reveals a significant improvement in prediction of drug sensitivity using genes identified by ProGENI compared to other methods. Our siRNA knockdown experiments on ProGENI-identified genes confirmed the role of many new genes in sensitivity to three chemotherapy drugs: cisplatin, docetaxel, and doxorubicin. Based on such experiments and extensive literature survey, we demonstrate that about 73% of our top predicted genes modulate drug response in selected cancer cell lines. In addition, global analysis of genes associated with groups of drugs uncovered pathways of cytotoxic response shared by each group. Our results suggest that knowledge-guided prioritization of genes using ProGENI gives new insight into mechanisms of drug resistance and identifies genes that may be targeted to overcome this phenomenon.

Sustaining plants and people: traditional Q'eqchi' Maya botanical knowledge and interactive spatial modeling in prioritizing conservation of medicinal plants for culturally relative holistic health promotion.

PubMed

Pesek, Todd; Abramiuk, Marc; Garagic, Denis; Fini, Nick; Meerman, Jan; Cal, Victor

2009-03-01

Ethnobotanical surveys were conducted to locate culturally important, regionally scarce, and disappearing medicinal plants via a novel participatory methodology which involves healer-expert knowledge in interactive spatial modeling to prioritize conservation efforts and thus facilitate health promotion via medicinal plant resource sustained availability. These surveys, conducted in the Maya Mountains, Belize, generate ethnobotanical, ecological, and geospatial data on species which are used by Q'eqchi' Maya healers in practice. Several of these mountainous species are regionally scarce and the healers are expressing difficulties in finding them for use in promotion of community health and wellness. Based on healers' input, zones of highest probability for locating regionally scarce, disappearing, and culturally important plants in their ecosystem niches can be facilitated by interactive modeling. In the present study, this is begun by choosing three representative species to train an interactive predictive model. Model accuracy was then assessed statistically by testing for independence between predicted occurrence and actual occurrence of medicinal plants. A high level of accuracy was achieved using a small set of exemplar data. This work demonstrates the potential of combining ethnobotany and botanical spatial information with indigenous ecosystems concepts and Q'eqchi' Maya healing knowledge via predictive modeling. Through this approach, we may identify regions where species are located and accordingly promote for prioritization and application of in situ and ex situ conservation strategies to protect them. This represents a significant step toward facilitating sustained culturally relative health promotion as well as overall enhanced ecological integrity to the region and the earth.

Toward DNA-based facial composites: preliminary results and validation.

PubMed

Claes, Peter; Hill, Harold; Shriver, Mark D

2014-11-01

The potential of constructing useful DNA-based facial composites is forensically of great interest. Given the significant identity information coded in the human face these predictions could help investigations out of an impasse. Although, there is substantial evidence that much of the total variation in facial features is genetically mediated, the discovery of which genes and gene variants underlie normal facial variation has been hampered primarily by the multipartite nature of facial variation. Traditionally, such physical complexity is simplified by simple scalar measurements defined a priori, such as nose or mouth width or alternatively using dimensionality reduction techniques such as principal component analysis where each principal coordinate is then treated as a scalar trait. However, as shown in previous and related work, a more impartial and systematic approach to modeling facial morphology is available and can facilitate both the gene discovery steps, as we recently showed, and DNA-based facial composite construction, as we show here. We first use genomic ancestry and sex to create a base-face, which is simply an average sex and ancestry matched face. Subsequently, the effects of 24 individual SNPs that have been shown to have significant effects on facial variation are overlaid on the base-face forming the predicted-face in a process akin to a photomontage or image blending. We next evaluate the accuracy of predicted faces using cross-validation. Physical accuracy of the facial predictions either locally in particular parts of the face or in terms of overall similarity is mainly determined by sex and genomic ancestry. The SNP-effects maintain the physical accuracy while significantly increasing the distinctiveness of the facial predictions, which would be expected to reduce false positives in perceptual identification tasks. To the best of our knowledge this is the first effort at generating facial composites from DNA and the results are preliminary but certainly promising, especially considering the limited amount of genetic information about the face contained in these 24 SNPs. This approach can incorporate additional SNPs as these are discovered and their effects documented. In this context we discuss three main avenues of research: expanding our knowledge of the genetic architecture of facial morphology, improving the predictive modeling of facial morphology by exploring and incorporating alternative prediction models, and increasing the value of the results through the weighted encoding of physical measurements in terms of human perception of faces. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

College students' memory for vocabulary in their majors: evidence for a nonlinear relation between knowledge and memory.

PubMed

DeMarie, Darlene; Aloise-Young, Patricia A; Prideaux, Cheri L; Muransky-Doran, Jean; Gerda, Julie Hart

2004-09-01

The effect of domain knowledge on students' memory for vocabulary terms was investigated. Participants were 142 college students (94 education majors and 48 business majors). The measure of domain knowledge was the number of courses completed in the major. Students recalled three different lists (control, education, and business) of 20 words. Knowledge effects were estimated controlling for academic aptitude, academic achievement, and general memory ability. Domain-specific knowledge consistently predicted recall, above and beyond the effect of these control variables. Moreover, nonlinear models better represented the relation between knowledge and memory, with very similar functions predicting recall in both knowledge domains. Specifically, early in the majors more classes corresponded with increased memory performance, but a plateau period, when more classes did not result in higher recall, was evident for both majors. Longitudinal research is needed to explore at what point in learning novices' performance begins to resemble experts' performance.

The role of sex, attachment and autonomy-connectedness in personality functioning.

PubMed

Bachrach, Nathan; Croon, Marcel A; Bekker, Marrie H J

2015-11-01

Previous studies have found significant relationships among sex, attachment and autonomy-connectedness and DSM-IV personality characteristics. In the present study, we aimed to add to the current knowledge about attachment-related aspects of personality pathology, by examining the relationships of these same variables with dimensions of pathological personality structure as conceptualized by Kernberg. The study was performed among 106 ambulatory patients from a Dutch mental healthcare institute. A path model based upon neo-analytical object relation theory and attachment theory was tested. We expected significant associations among sex, attachment, autonomy and aspects of personality functioning. Both insecure attachment styles as well as the autonomy-connectedness components of sensitivity to others (SO) and capacity of managing new situations predicted general personality dysfunctioning significantly. More specifically, reality testing was negatively predicted by the autonomy component of capacity of managing new situations, and aggression was significantly predicted by sex as well as both insecure attachment styles. We advise scientists as well as clinicians to be alert on sex differences in autonomy-connectedness and aspects of personality dysfunctioning. Taking sex-specific variations in attachment and autonomy into account next to a more explicit focus on insecure attachment styles and autonomy problems may enhance, the current relatively low, treatment effectiveness for personality pathology. Copyright © 2015 John Wiley & Sons, Ltd.

Protection motivation theory in predicting intention to receive cervical cancer screening in rural Chinese women.

PubMed

Bai, Yang; Liu, Qing; Chen, Xinguang; Gao, Yanduo; Gong, Huiyun; Tan, Xiaodong; Zhang, Min; Tuo, Jiyu; Zhang, Yuling; Xiang, Qunying; Deng, Fenghua; Liu, Guiling

2018-02-01

Despite the significance of cervical cancer screening, motivating more women to participate remains a challenge in resource-limited settings. In this study, we tested the protection motivation theory (PMT) in predicting screening intentions. Participants were women from Wufeng, a typical rural county in China. Participants (n = 3000) with no cervical cancer history were recruited from 10 randomly selected villages. As mediating variables, 6 PMT constructs (Perceived Risk, Fear Arousal, Perceived Severity, Response Efficacy, Response Cost, and Self-Efficacy) were measured using the standardized questionnaire. Structural equation modeling (SEM) method was employed to test PMT-based prediction models. Of the total sample, 57.77% believed that regular screening may reduce cervical cancer risk, and 45.26% agreed that women should be screened regularly. Our data fit the PMT model well (GFI = 0.95, AGFI = 0.93, CFI = 0.90, RMSEA = 0.06, SRMR = 0.04, Chi-square/df = 2.47). Knowledge of screening was directly and positively associated with screening intention. Age, annual income, and awareness of and prior experience with screening were significantly associated with screening intention by enhancing cervical cancer risk perception and by reducing response cost (P<0.05 for both). PMT can be used as guidance to investigate cervical cancer screening intentions among rural women in China with focus on cancer knowledge, some demographic factors, and awareness of and previous experience with screening. These findings, if verified with longitudinal data, can be used for intervention program development. Copyright © 2017 John Wiley & Sons, Ltd.

Joint L2,1 Norm and Fisher Discrimination Constrained Feature Selection for Rational Synthesis of Microporous Aluminophosphates.

PubMed

Qi, Miao; Wang, Ting; Yi, Yugen; Gao, Na; Kong, Jun; Wang, Jianzhong

2017-04-01

Feature selection has been regarded as an effective tool to help researchers understand the generating process of data. For mining the synthesis mechanism of microporous AlPOs, this paper proposes a novel feature selection method by joint l 2,1 norm and Fisher discrimination constraints (JNFDC). In order to obtain more effective feature subset, the proposed method can be achieved in two steps. The first step is to rank the features according to sparse and discriminative constraints. The second step is to establish predictive model with the ranked features, and select the most significant features in the light of the contribution of improving the predictive accuracy. To the best of our knowledge, JNFDC is the first work which employs the sparse representation theory to explore the synthesis mechanism of six kinds of pore rings. Numerical simulations demonstrate that our proposed method can select significant features affecting the specified structural property and improve the predictive accuracy. Moreover, comparison results show that JNFDC can obtain better predictive performances than some other state-of-the-art feature selection methods. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Relations among student attention behaviors, teacher practices, and beginning word reading skill.

PubMed

Sáez, Leilani; Folsom, Jessica Sidler; Al Otaiba, Stephanie; Schatschneider, Christopher

2012-01-01

The role of student attention for predicting kindergarten word reading was investigated among 432 students. Using Strengths and Weaknesses of ADHD Symptoms and Normal Behavior Rating Scale behavior rating scores, the authors conducted an exploratory factor analysis, which yielded three distinct factors that reflected selective attention. In this study, the authors focused on the role of one of these factors, which they labeled attention-memory, for predicting reading performance. Teacher ratings of attention-memory predicted word reading above and beyond the contribution of phonological awareness and vocabulary knowledge. In addition, the relations between four teacher practices and attention ratings for predicting reading performance were examined. Using hierarchical linear modeling, the authors found significant interactions between student attention and teacher practices observed during literacy instruction. In general, as ratings of attention improved, better kindergarten word reading performance was associated with high levels of classroom behavior management. However, better word reading performance was not associated with high levels of teacher task orienting. A significant three-way interaction was also found among attention, individualized instruction, and teacher task redirections. The role of regulating kindergarten student attention to support beginning word reading skill development is discussed.

Shared reality in interpersonal relationships.

PubMed

Andersen, Susan M; Przybylinski, Elizabeth

2017-11-24

Close relationships afford us opportunities to create and maintain meaning systems as shared perceptions of ourselves and the world. Establishing a sense of mutual understanding allows for creating and maintaining lasting social bonds, and as such, is important in human relations. In a related vein, it has long been known that knowledge of significant others in one's life is stored in memory and evoked with new persons-in the social-cognitive process of 'transference'-imbuing new encounters with significance and leading to predictable cognitive, evaluative, motivational, and behavioral consequences, as well as shifts in the self and self-regulation, depending on the particular significant other evoked. In these pages, we briefly review the literature on meaning as interpersonally defined and then selectively review research on transference in interpersonal perception. Based on this, we then highlight a recent series of studies focused on shared meaning systems in transference. The highlighted studies show that values and beliefs that develop in close relationships (as shared reality) are linked in memory to significant-other knowledge, and thus, are indirectly activated (made accessible) when cues in a new person implicitly activate that significant-other knowledge (in transference), with these shared beliefs then actively pursued with the new person and even protected against threat. This also confers a sense of mutual understanding, and all told, serves both relational and epistemic functions. In concluding, we consider as well the relevance of co-construction of shared reality n such processes. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

PubMed

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

2015-04-01

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

Polygenic scores predict alcohol problems in an independent sample and show moderation by the environment.

PubMed

Salvatore, Jessica E; Aliev, Fazil; Edwards, Alexis C; Evans, David M; Macleod, John; Hickman, Matthew; Lewis, Glyn; Kendler, Kenneth S; Loukola, Anu; Korhonen, Tellervo; Latvala, Antti; Rose, Richard J; Kaprio, Jaakko; Dick, Danielle M

2014-04-10

Alcohol problems represent a classic example of a complex behavioral outcome that is likely influenced by many genes of small effect. A polygenic approach, which examines aggregate measured genetic effects, can have predictive power in cases where individual genes or genetic variants do not. In the current study, we first tested whether polygenic risk for alcohol problems-derived from genome-wide association estimates of an alcohol problems factor score from the age 18 assessment of the Avon Longitudinal Study of Parents and Children (ALSPAC; n = 4304 individuals of European descent; 57% female)-predicted alcohol problems earlier in development (age 14) in an independent sample (FinnTwin12; n = 1162; 53% female). We then tested whether environmental factors (parental knowledge and peer deviance) moderated polygenic risk to predict alcohol problems in the FinnTwin12 sample. We found evidence for both polygenic association and for additive polygene-environment interaction. Higher polygenic scores predicted a greater number of alcohol problems (range of Pearson partial correlations 0.07-0.08, all p-values ≤ 0.01). Moreover, genetic influences were significantly more pronounced under conditions of low parental knowledge or high peer deviance (unstandardized regression coefficients (b), p-values (p), and percent of variance (R2) accounted for by interaction terms: b = 1.54, p = 0.02, R2 = 0.33%; b = 0.94, p = 0.04, R2 = 0.30%, respectively). Supplementary set-based analyses indicated that the individual top single nucleotide polymorphisms (SNPs) contributing to the polygenic scores were not individually enriched for gene-environment interaction. Although the magnitude of the observed effects are small, this study illustrates the usefulness of polygenic approaches for understanding the pathways by which measured genetic predispositions come together with environmental factors to predict complex behavioral outcomes.

The predictive validity of selection for entry into postgraduate training in general practice: evidence from three longitudinal studies

PubMed Central

Patterson, Fiona; Lievens, Filip; Kerrin, Máire; Munro, Neil; Irish, Bill

2013-01-01

Background The selection methodology for UK general practice is designed to accommodate several thousand applicants per year and targets six core attributes identified in a multi-method job-analysis study Aim To evaluate the predictive validity of selection methods for entry into postgraduate training, comprising a clinical problem-solving test, a situational judgement test, and a selection centre. Design and setting A three-part longitudinal predictive validity study of selection into training for UK general practice. Method In sample 1, participants were junior doctors applying for training in general practice (n = 6824). In sample 2, participants were GP registrars 1 year into training (n = 196). In sample 3, participants were GP registrars sitting the licensing examination after 3 years, at the end of training (n = 2292). The outcome measures include: assessor ratings of performance in a selection centre comprising job simulation exercises (sample 1); supervisor ratings of trainee job performance 1 year into training (sample 2); and licensing examination results, including an applied knowledge examination and a 12-station clinical skills objective structured clinical examination (OSCE; sample 3). Results Performance ratings at selection predicted subsequent supervisor ratings of job performance 1 year later. Selection results also significantly predicted performance on both the clinical skills OSCE and applied knowledge examination for licensing at the end of training. Conclusion In combination, these longitudinal findings provide good evidence of the predictive validity of the selection methods, and are the first reported for entry into postgraduate training. Results show that the best predictor of work performance and training outcomes is a combination of a clinical problem-solving test, a situational judgement test, and a selection centre. Implications for selection methods for all postgraduate specialties are considered. PMID:24267856

The predictive validity of selection for entry into postgraduate training in general practice: evidence from three longitudinal studies.

PubMed

Patterson, Fiona; Lievens, Filip; Kerrin, Máire; Munro, Neil; Irish, Bill

2013-11-01

The selection methodology for UK general practice is designed to accommodate several thousand applicants per year and targets six core attributes identified in a multi-method job-analysis study To evaluate the predictive validity of selection methods for entry into postgraduate training, comprising a clinical problem-solving test, a situational judgement test, and a selection centre. A three-part longitudinal predictive validity study of selection into training for UK general practice. In sample 1, participants were junior doctors applying for training in general practice (n = 6824). In sample 2, participants were GP registrars 1 year into training (n = 196). In sample 3, participants were GP registrars sitting the licensing examination after 3 years, at the end of training (n = 2292). The outcome measures include: assessor ratings of performance in a selection centre comprising job simulation exercises (sample 1); supervisor ratings of trainee job performance 1 year into training (sample 2); and licensing examination results, including an applied knowledge examination and a 12-station clinical skills objective structured clinical examination (OSCE; sample 3). Performance ratings at selection predicted subsequent supervisor ratings of job performance 1 year later. Selection results also significantly predicted performance on both the clinical skills OSCE and applied knowledge examination for licensing at the end of training. In combination, these longitudinal findings provide good evidence of the predictive validity of the selection methods, and are the first reported for entry into postgraduate training. Results show that the best predictor of work performance and training outcomes is a combination of a clinical problem-solving test, a situational judgement test, and a selection centre. Implications for selection methods for all postgraduate specialties are considered.

Mathematical Learning Models that Depend on Prior Knowledge and Instructional Strategies

ERIC Educational Resources Information Center

Pritchard, David E.; Lee, Young-Jin; Bao, Lei

2008-01-01

We present mathematical learning models--predictions of student's knowledge vs amount of instruction--that are based on assumptions motivated by various theories of learning: tabula rasa, constructivist, and tutoring. These models predict the improvement (on the post-test) as a function of the pretest score due to intervening instruction and also…

Predicting First Grade Reading Achievement for Spanish-Speaking Kindergartners: Is Early Literacy Screening in English Valid?

ERIC Educational Resources Information Center

Ford, Karen L.; Invernizzi, Marcia A.; Huang, Francis

2014-01-01

This study explored the viability of using kindergarten measures of phonological awareness, alphabet knowledge, and orthographic knowledge, administered in English, to predict first grade reading achievement of Spanish-speaking English language learners. The primary research question was: Do kindergarten measures of early literacy skills in…

Validity of the MicroDYN Approach: Complex Problem Solving Predicts School Grades beyond Working Memory Capacity

ERIC Educational Resources Information Center

Schweizer, Fabian; Wustenberg, Sascha; Greiff, Samuel

2013-01-01

This study examines the validity of the complex problem solving (CPS) test MicroDYN by investigating a) the relation between its dimensions--rule identification (exploration strategy), rule knowledge (acquired knowledge), rule application (control performance)--and working memory capacity (WMC), and b) whether CPS predicts school grades in…

Pathways from parental knowledge and warmth to adolescent marijuana use: an extension to the theory of planned behavior.

PubMed

Lac, Andrew; Alvaro, Eusebio M; Crano, William D; Siegel, Jason T

2009-03-01

Despite research indicating that effective parenting plays an important protective role in adolescent risk behaviors, few studies have applied theory to examine this link with marijuana use, especially with national data. In the current study (N = 2,141), we hypothesized that parental knowledge (of adolescent activities and whereabouts) and parental warmth are antecedents of adolescents' marijuana beliefs-attitudes, subjective norms, and perceived behavioral control-as posited by the Theory of Planned Behavior (TPB; Ajzen 1991). These three types of beliefs were hypothesized to predict marijuana intention, which in turn was hypothesized to predict marijuana consumption. Results of confirmatory factor analyses corroborated the psychometric properties of the two-factor parenting structure as well as the five-factor structure of the TPB. Further, the proposed integrative predictive framework, estimated with a latent structural equation model, was largely supported. Parental knowledge inversely predicted pro-marijuana attitudes, subjective norms, and perceived behavioral control; parental warmth inversely predicted pro-marijuana attitudes and subjective norms, ps < .001. Marijuana intention (p < .001), but not perceived behavioral control, predicted marijuana use 1 year later. In households with high parental knowledge, parental warmth also was perceived to be high (r = .54, p < .001). Owing to the analysis of nationally representative data, results are generalizable to the United States population of adolescents 12-18 years of age.

Co-occurrence of antisocial behavior and substance use: testing for sex differences in the impact of older male friends, low parental knowledge and friends' delinquency.

PubMed

McAdams, Tom A; Salekin, Randall T; Marti, C Nathan; Lester, Whiney S; Barker, Edward D

2014-04-01

Delinquency and substance use (SU) are commonly comorbid during adolescence. In the present study we investigate this co-morbidity with 3 main objectives: 1. Evaluate reciprocal relationships between delinquency/SU across early adolescence. 2. Assess the impact of older male friends, low parental knowledge and friends' delinquency on subsequent development and inter-relationships of delinquency and SU. 3. Evaluate sex differences in these relationships. We applied cross-lagged structural equation models to the analysis of a longitudinal sample (n=3699). Findings demonstrated: (1) At ages 13-14 delinquency predicted SU more so than vice versa but effects became equal between ages 14 and 15. (2) Low parental knowledge and friends' delinquency predicted delinquency and SU. Older male friends predicted ASB. (3) Sex differences were present. For example, in the absence of antisocial friends low parent knowledge at age 12 indirectly predicted increased age 15 SU for girls more than boys. Copyright © 2014 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

Integrating technology, curriculum, and online resources: A multilevel model study of impacts on science teachers and students

NASA Astrophysics Data System (ADS)

Ye, Lei

This scale-up study investigated the impact of a teacher technology tool (Curriculum Customization Service, CCS), curriculum, and online resources on earth science teachers' attitudes, beliefs, and practices and on students' achievement and engagement with science learning. Participants included 73 teachers and over 2,000 ninth-grade students within five public school districts in the western U.S. To assess the impact on teachers, changes between pre- and postsurveys were examined. Results suggest that the CCS tool appeared to significantly increase both teachers' awareness of other earth science teachers' practices and teachers' frequency of using interactive resources in their lesson planning and classroom teaching. A standard multiple regression model was developed. In addition to "District," "Training condition" (whether or not teachers received CCS training) appeared to predict teachers' attitudes, beliefs, and practices. Teachers who received CCS training tended to have lower postsurvey scores than their peers who had no CCS training. Overall, usage of the CCS tool tended to be low, and there were differences among school districts. To assess the impact on students, changes were examined between pre- and postsurveys of (1) knowledge assessment and (2) students' engagement with science learning. Students showed pre- to postsurvey improvements in knowledge assessment, with small to medium effect sizes. A nesting effect (students clustered within teachers) in the Earth's Dynamic Geosphere (EDG) knowledge assessment was identified and addressed by fitting a two-level hierarchical linear model (HLM). In addition, significant school district differences existed for student post-knowledge assessment scores. On the student engagement questionnaire, students tended to be neutral or to slightly disagree that science learning was important in terms of using science in daily life, stimulating their thinking, discovering science concepts, and satisfying their own curiosity. Students did not appear to change their self-reported engagement level after the intervention. Additionally, three multiple regression models were developed. Factors from the district, teacher, and student levels were identified to predict student post-knowledge assessments and their engagement with science learning. The results provide information to both the research community and practitioners.

Going beyond the lesson: Self-generating new factual knowledge in the classroom

PubMed Central

Esposito, Alena G.; Bauer, Patricia J.

2016-01-01

For children to build a knowledge base, they must integrate and extend knowledge acquired across separate episodes of new learning. Children’s performance was assessed in a task requiring them to self-generate new factual knowledge from the integration of novel facts presented through separate lessons in the classroom. Whether self-generation performance predicted academic outcomes in reading comprehension and mathematics was also examined. The 278 participating children were in grades K-3 (mean age 7.7 years; range 5.5–10.3 years). Children self-generated new factual knowledge through integration in the classroom; age-related increases were observed. Self-generation performance predicted both reading comprehension and mathematics academic outcomes, even when controlling for caregiver education. PMID:27728784

A Bayesian framework for knowledge attribution: evidence from semantic integration.

PubMed

Powell, Derek; Horne, Zachary; Pinillos, N Ángel; Holyoak, Keith J

2015-06-01

We propose a Bayesian framework for the attribution of knowledge, and apply this framework to generate novel predictions about knowledge attribution for different types of "Gettier cases", in which an agent is led to a justified true belief yet has made erroneous assumptions. We tested these predictions using a paradigm based on semantic integration. We coded the frequencies with which participants falsely recalled the word "thought" as "knew" (or a near synonym), yielding an implicit measure of conceptual activation. Our experiments confirmed the predictions of our Bayesian account of knowledge attribution across three experiments. We found that Gettier cases due to counterfeit objects were not treated as knowledge (Experiment 1), but those due to intentionally-replaced evidence were (Experiment 2). Our findings are not well explained by an alternative account focused only on luck, because accidentally-replaced evidence activated the knowledge concept more strongly than did similar false belief cases (Experiment 3). We observed a consistent pattern of results across a number of different vignettes that varied the quality and type of evidence available to agents, the relative stakes involved, and surface details of content. Accordingly, the present findings establish basic phenomena surrounding people's knowledge attributions in Gettier cases, and provide explanations of these phenomena within a Bayesian framework. Copyright © 2015 Elsevier B.V. All rights reserved.

Predicting growth in English and French vocabulary: The facilitating effects of morphological and cognate awareness.

PubMed

D'Angelo, Nadia; Hipfner-Boucher, Kathleen; Chen, Xi

2017-07-01

The present study investigated the contribution of morphological and cognate awareness to the development of English and French vocabulary knowledge among young minority and majority language children who were enrolled in a French immersion program. Participating children (n = 75) were assessed in English and French on measures of morphological awareness, cognate awareness, and vocabulary knowledge from Grades 1 to 3. Hierarchical linear modeling was used to investigate linear trends in English and French vocabulary growth for minority and majority language children and to identify metalinguistic contributions to Grade 1 and Grade 3 English and French vocabulary performance and rate of growth. Results demonstrated a similar pattern of prediction for both groups of children. English and French morphological awareness and French-English cognate awareness significantly predicted concurrent and longitudinal vocabulary development after controlling for nonverbal reasoning, phonological awareness, and word identification. The contributions of morphological awareness to English vocabulary and cognate awareness to French vocabulary strengthened between Grades 1 and 2. These findings highlight the emerging importance of morphological and cognate awareness in children's vocabulary development and suggest that these metalinguistic factors can serve to broaden the vocabulary repertoire of children who enter school with limited language proficiency. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

White racial identity, color-blind racial attitudes, and multicultural counseling competence.

PubMed

Johnson, Alex; Jackson Williams, Dahra

2015-07-01

Multicultural counseling competence (awareness, knowledge, and skills) is necessary to provide effective psychotherapy to an increasingly diverse client population (Sue, 2001). Previous research on predictors of competency among White clinicians finds that above having multicultural training, exposure to racially diverse clients, and social desirability, that White racial identity stages predict multicultural counseling competence (Ottavi et al., 1994). Research also suggests that higher color-blind racial attitudes (denying or minimizing racism in society) correlates with less advanced White racial identity stages (Gushue & Constantine, 2007). However, no studies have examined these variables together as they relate to and possibly predict multicultural counseling competence. The current study aims to add to this literature by investigating the effects of these variables together as potential predictors of multicultural counseling competence among (N = 487) White doctoral students studying clinical, counseling, and school psychology. Results of 3 hierarchical multiple regressions found above the effects of social desirability, demographic variables, and multicultural training, that colorblind racial attitudes and White racial identity stages added significant incremental variance in predicting multicultural counseling knowledge, awareness, and skills. These results add to the literature by finding different predictors for each domain of multicultural competence. Implications of the findings for future research and the clinical training of White doctoral trainees are discussed. (c) 2015 APA, all rights reserved).

Predict-share-observe-explain learning activity for the Torricelli's tank experiment

NASA Astrophysics Data System (ADS)

Panich, Charunya; Puttharugsa, Chokchai; Khemmani, Supitch

2018-01-01

The purpose of this research was to study the students' scientific concept and achievement on fluid mechanics before and after the predict-share-observe-explain (PSOE) learning activity for the Torricelli's tank experiment. The 24 participants, who were selected by purposive sampling, were students at grade 12 at Nannakorn School, Nan province. A one group pre-test/post-test design was employed in the study. The research instruments were 1) the lesson plans using the PSOE learning activity and 2) two-tier multiple choice question and subjective tests. The results indicated that students had better scientific concept about Torricelli's tank experiment and the post-test mean score was significantly higher than the pre-test mean score at a 0.05 level of significance. Moreover, the students had retention of knowledge after the PSOE learning activity for 4 weeks at a 0.05 level of significance. The study showed that the PSOE learning activity is suitable for developing students' scientific concept and achievement.

The GP tests of competence assessment: which part best predicts fitness to practise decisions?

PubMed

Jayaweera, Hirosha Keshani; Potts, Henry W W; Keshwani, Karim; Valerio, Chris; Baker, Magdalen; Mehdizadeh, Leila; Sturrock, Alison

2018-01-02

The General Medical Council (GMC) conducts Tests of Competence (ToC) for doctors referred for Fitness to Practise (FtP) issues. GPs take a single best answer knowledge test, an Objective Structured Clinical Examination (OSCE), and a Simulated Surgery (SimSurg) assessment which is a simulated GP consultation. The aim of this study was to examine the similarities between OSCEs and SimSurg to determine whether each assessment contributed something unique to GP ToCs. A mixed methods approach was used. Data were collated on 153 GPs who were required to undertake a ToC as a part of being investigated for FtP issues between February 2010 and October 2016. Using correlation analysis, we examined to what degree performance on the knowledge test, OSCE, and SimSurg related to case examiner recommendations and FtP outcomes, including the unique predictive power of these three assessments. The outcome measures were case examiner recommendations (i) not fit to practise; ii) fit to practise on a limited basis; or iii) fit to practise) as well as FtP outcomes (i) erased/removed from the register; ii) having restrictions/conditions; or iii) be in good standing). For the qualitative component, 45 GP assessors were asked to rate whether they assess the same competencies and which assessment provides better feedback about candidates. There was significant overlap between OSCEs and SimSurg, p < 0.001. SimSurg had additional predictive power in the presence of OSCEs and the knowledge test (p = 0.030) in distinguishing doctors from different FtP categories, while OSCEs did not (p = 0.080). Both the OSCEs (p = 0.004) and SimSurg (p < 0.001) had significant negative correlations with case examiner recommendations when accounting for the effects of the other two assessments. Inductive thematic analysis of the responses to the questionnaire showed that assessors perceived OSCEs to be better suited to target specific knowledge and skills. SimSurg was thought to produce a more global picture as the scenarios more accurately portray a patient consultation. While all three assessments are strong predictors of both case examiner recommendations and FtP outcomes, our findings suggest that the efficiency of GP ToCs can be improved by removing some of this overlapping content.

Students' Metacomprehension Knowledge: Components That Predict Comprehension Performance

ERIC Educational Resources Information Center

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

2015-01-01

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

FMS Scores Change With Performers' Knowledge of the Grading Criteria-Are General Whole-Body Movement Screens Capturing "Dysfunction"?

PubMed

Frost, David M; Beach, Tyson A C; Callaghan, Jack P; McGill, Stuart M

2015-11-01

Deficits in joint mobility and stability could certainly impact individuals' Functional Movement Screen (FMS) scores; however, it is also plausible that the movement patterns observed are influenced by the performers' knowledge of the grading criteria. Twenty-one firefighters volunteered to participate, and their FMS scores were graded before and immediately after receiving knowledge of the movement patterns required to achieve a perfect score on the FMS. Standardized verbal instructions were used to administer both screens, and the participants were not provided with any coaching or feedback. Time-synchronized sagittal and frontal plane videos were used to grade the FMS. The firefighters significantly (p < 0.001) improved their FMS scores from 14.1 (1.8) to 16.7 (1.9) when provided with knowledge pertaining to the specific grading criteria. Significant improvements (p < 0.05) were also noted in the deep squat (1.4 [0.7]-2.0 [0.6]), hurdle step (2.1 [0.4]-2.4 [0.5]), in-line lunge (2.1 [0.4]-2.7 [0.5]), and shoulder mobility (1.8 [0.8]-2.4 [0.7]) tests. Because a knowledge of a task's grading criteria can alter a general whole-body movement screen score, FMS or otherwise, observed changes may not solely reflect "dysfunction." The instant that individuals are provided with coaching and feedback regarding their performance on a particular task, the task may lose its utility to evaluate the transfer of training or predict musculoskeletal injury risk.

Developmental Foundations of Children's Fraction Magnitude Knowledge.

PubMed

Mou, Yi; Li, Yaoran; Hoard, Mary K; Nugent, Lara D; Chu, Felicia W; Rouder, Jeffrey N; Geary, David C

2016-01-01

The conceptual insight that fractions represent magnitudes is a critical yet daunting step in children's mathematical development, and the knowledge of fraction magnitudes influences children's later mathematics learning including algebra. In this study, longitudinal data were analyzed to identify the mathematical knowledge and domain-general competencies that predicted 8 th and 9 th graders' (n=122) knowledge of fraction magnitudes and its cross-grade gains. Performance on the fraction magnitude measures predicted 9 th grade algebra achievement. Understanding and fluently identifying the numerator-denominator relation in 7 th grade emerged as the key predictor of later fraction magnitudes knowledge in both 8 th and 9 th grades. Competence at using fraction procedures, knowledge of whole number magnitudes, and the central executive contributed to 9 th but not 8 th graders' fraction magnitude knowledge, and knowledge of whole number magnitude contributed to cross-grade gains. The key results suggest fluent processing of numerator-denominator relations presages students' understanding of fractions as magnitudes and that the integration of whole number and fraction magnitudes occurs gradually.

The relationship between high residential density in student dormitories and anxiety, binge eating and Internet addiction: a study of Chinese college students.

PubMed

Tao, Zhuoli; Wu, Gao; Wang, Zeyuan

2016-01-01

Although various studies have indicated that high residential density may affect health and psychological outcomes, to our knowledge, there have been no studies regarding the predictive nature of crowded living conditions on binge eating and the use of the Internet as coping strategies. A total of 1048 Chinese college students (540 males and 508 females) were randomly selected and asked to complete a battery of questionnaires that included the Zung's Self-Rating Anxiety Scale, the Internet Addiction Test, and Rosenbaum's Self-Control Scale. Binge eating behaviors and compensatory behaviors were also reported, and variables about residential density were measured. Among female participants, binge eating scores were significantly predicted by anxiety caused by high-density living conditions (P = 0.008), and similarly, the frequency of compensatory behaviors was significantly predicted by anxiety caused by high-density living conditions (P = 0.000) and self-control (P = 0.003). Furthermore, the Internet Addiction Test scores were significantly predicted by the anxiety caused by high -density living conditions (P = 0.000) and self-control (P = 0.000). Among male participants, not only were the binge eating scores significantly predicted by the anxiety caused by high-density living conditions (P = 0.000) and self-control (P = 0.000), but the frequency of compensatory behaviors was also significantly predicted by the anxiety caused by high-density living conditions (P = 0.000) and self-control (P = 0.01). Furthermore, Internet Addiction Test scores were significantly predicted by anxiety caused by high-density living conditions (P = 0.000) and self-control (P = 0.000). It was further found that for both genders, subjective factors such as self-control, and the anxiety caused by high-density living conditions had a stronger impact on Internet addiction than objective factors, such as the size of the student's dormitory room. Moreover, self-control was found to act as a moderator in the relationship between anxiety and Internet addiction among male participants. Binge eating and Internet use could be considered coping strategies for Chinese college students facing high residential density in their dormitories.

Sphinx: merging knowledge-based and ab initio approaches to improve protein loop prediction

PubMed Central

Marks, Claire; Nowak, Jaroslaw; Klostermann, Stefan; Georges, Guy; Dunbar, James; Shi, Jiye; Kelm, Sebastian

2017-01-01

Abstract Motivation: Loops are often vital for protein function, however, their irregular structures make them difficult to model accurately. Current loop modelling algorithms can mostly be divided into two categories: knowledge-based, where databases of fragments are searched to find suitable conformations and ab initio, where conformations are generated computationally. Existing knowledge-based methods only use fragments that are the same length as the target, even though loops of slightly different lengths may adopt similar conformations. Here, we present a novel method, Sphinx, which combines ab initio techniques with the potential extra structural information contained within loops of a different length to improve structure prediction. Results: We show that Sphinx is able to generate high-accuracy predictions and decoy sets enriched with near-native loop conformations, performing better than the ab initio algorithm on which it is based. In addition, it is able to provide predictions for every target, unlike some knowledge-based methods. Sphinx can be used successfully for the difficult problem of antibody H3 prediction, outperforming RosettaAntibody, one of the leading H3-specific ab initio methods, both in accuracy and speed. Availability and Implementation: Sphinx is available at http://opig.stats.ox.ac.uk/webapps/sphinx. Contact: deane@stats.ox.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. PMID:28453681

Sphinx: merging knowledge-based and ab initio approaches to improve protein loop prediction.

PubMed

Marks, Claire; Nowak, Jaroslaw; Klostermann, Stefan; Georges, Guy; Dunbar, James; Shi, Jiye; Kelm, Sebastian; Deane, Charlotte M

2017-05-01

Loops are often vital for protein function, however, their irregular structures make them difficult to model accurately. Current loop modelling algorithms can mostly be divided into two categories: knowledge-based, where databases of fragments are searched to find suitable conformations and ab initio, where conformations are generated computationally. Existing knowledge-based methods only use fragments that are the same length as the target, even though loops of slightly different lengths may adopt similar conformations. Here, we present a novel method, Sphinx, which combines ab initio techniques with the potential extra structural information contained within loops of a different length to improve structure prediction. We show that Sphinx is able to generate high-accuracy predictions and decoy sets enriched with near-native loop conformations, performing better than the ab initio algorithm on which it is based. In addition, it is able to provide predictions for every target, unlike some knowledge-based methods. Sphinx can be used successfully for the difficult problem of antibody H3 prediction, outperforming RosettaAntibody, one of the leading H3-specific ab initio methods, both in accuracy and speed. Sphinx is available at http://opig.stats.ox.ac.uk/webapps/sphinx. deane@stats.ox.ac.uk. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press.

Validated Questionnaire of Maternal Attitude and Knowledge for Predicting Caries Risk in Children: Epidemiological Study in North Jakarta, Indonesia.

PubMed

Laksmiastuti, Sri Ratna; Budiardjo, Sarworini Bagio; Sutadi, Heriandi

2017-06-01

Predicting caries risk in children can be done by identifying caries risk factors. It is an important measure which contributes to best understanding of the cariogenic profile of the patient. Identification could be done by clinical examination and answering the questionnaire. We arrange the study to verify the questionnaire validation for predicting caries risk in children. The study was conducted on 62 pairs of mothers and their children, aged between 3 and 5 years. The questionnaire consists of 10 questions concerning mothers' attitude and knowledge about oral health. The reliability and validity test is based on Cronbach's alpha and correlation coefficient value. All question are reliable (Cronbach's alpha = 0.873) and valid (Corrected item-total item correlation >0.4). Five questionnaires of mother's attitude about oral health and five questionnaires of mother's knowledge about oral health are reliable and valid for predicting caries risk in children.

Predicting Children's Reading and Mathematics Achievement from Early Quantitative Knowledge and Domain-General Cognitive Abilities

PubMed Central

Chu, Felicia W.; vanMarle, Kristy; Geary, David C.

2016-01-01

One hundred children (44 boys) participated in a 3-year longitudinal study of the development of basic quantitative competencies and the relation between these competencies and later mathematics and reading achievement. The children's preliteracy knowledge, intelligence, executive functions, and parental educational background were also assessed. The quantitative tasks assessed a broad range of symbolic and nonsymbolic knowledge and were administered four times across 2 years of preschool. Mathematics achievement was assessed at the end of each of 2 years of preschool, and mathematics and word reading achievement were assessed at the end of kindergarten. Our goals were to determine how domain-general abilities contribute to growth in children's quantitative knowledge and to determine how domain-general and domain-specific abilities contribute to children's preschool mathematics achievement and kindergarten mathematics and reading achievement. We first identified four core quantitative competencies (e.g., knowledge of the cardinal value of number words) that predict later mathematics achievement. The domain-general abilities were then used to predict growth in these competencies across 2 years of preschool, and the combination of domain-general abilities, preliteracy skills, and core quantitative competencies were used to predict mathematics achievement across preschool and mathematics and word reading achievement at the end of kindergarten. Both intelligence and executive functions predicted growth in the four quantitative competencies, especially across the first year of preschool. A combination of domain-general and domain-specific competencies predicted preschoolers' mathematics achievement, with a trend for domain-specific skills to be more strongly related to achievement at the beginning of preschool than at the end of preschool. Preschool preliteracy skills, sensitivity to the relative quantities of collections of objects, and cardinal knowledge predicted reading and mathematics achievement at the end of kindergarten. Preliteracy skills were more strongly related to word reading, whereas sensitivity to relative quantity was more strongly related to mathematics achievement. The overall results indicate that a combination of domain-general and domain-specific abilities contribute to development of children's early mathematics and reading achievement. PMID:27252675

Predicting Children's Reading and Mathematics Achievement from Early Quantitative Knowledge and Domain-General Cognitive Abilities.

PubMed

Chu, Felicia W; vanMarle, Kristy; Geary, David C

2016-01-01

One hundred children (44 boys) participated in a 3-year longitudinal study of the development of basic quantitative competencies and the relation between these competencies and later mathematics and reading achievement. The children's preliteracy knowledge, intelligence, executive functions, and parental educational background were also assessed. The quantitative tasks assessed a broad range of symbolic and nonsymbolic knowledge and were administered four times across 2 years of preschool. Mathematics achievement was assessed at the end of each of 2 years of preschool, and mathematics and word reading achievement were assessed at the end of kindergarten. Our goals were to determine how domain-general abilities contribute to growth in children's quantitative knowledge and to determine how domain-general and domain-specific abilities contribute to children's preschool mathematics achievement and kindergarten mathematics and reading achievement. We first identified four core quantitative competencies (e.g., knowledge of the cardinal value of number words) that predict later mathematics achievement. The domain-general abilities were then used to predict growth in these competencies across 2 years of preschool, and the combination of domain-general abilities, preliteracy skills, and core quantitative competencies were used to predict mathematics achievement across preschool and mathematics and word reading achievement at the end of kindergarten. Both intelligence and executive functions predicted growth in the four quantitative competencies, especially across the first year of preschool. A combination of domain-general and domain-specific competencies predicted preschoolers' mathematics achievement, with a trend for domain-specific skills to be more strongly related to achievement at the beginning of preschool than at the end of preschool. Preschool preliteracy skills, sensitivity to the relative quantities of collections of objects, and cardinal knowledge predicted reading and mathematics achievement at the end of kindergarten. Preliteracy skills were more strongly related to word reading, whereas sensitivity to relative quantity was more strongly related to mathematics achievement. The overall results indicate that a combination of domain-general and domain-specific abilities contribute to development of children's early mathematics and reading achievement.

Predicting Future Reading Problems Based on Pre-reading Auditory Measures: A Longitudinal Study of Children with a Familial Risk of Dyslexia

PubMed Central

Law, Jeremy M.; Vandermosten, Maaike; Ghesquière, Pol; Wouters, Jan

2017-01-01

Purpose: This longitudinal study examines measures of temporal auditory processing in pre-reading children with a family risk of dyslexia. Specifically, it attempts to ascertain whether pre-reading auditory processing, speech perception, and phonological awareness (PA) reliably predict later literacy achievement. Additionally, this study retrospectively examines the presence of pre-reading auditory processing, speech perception, and PA impairments in children later found to be literacy impaired. Method: Forty-four pre-reading children with and without a family risk of dyslexia were assessed at three time points (kindergarten, first, and second grade). Auditory processing measures of rise time (RT) discrimination and frequency modulation (FM) along with speech perception, PA, and various literacy tasks were assessed. Results: Kindergarten RT uniquely contributed to growth in literacy in grades one and two, even after controlling for letter knowledge and PA. Highly significant concurrent and predictive correlations were observed with kindergarten RT significantly predicting first grade PA. Retrospective analysis demonstrated atypical performance in RT and PA at all three time points in children who later developed literacy impairments. Conclusions: Although significant, kindergarten auditory processing contributions to later literacy growth lack the power to be considered as a single-cause predictor; thus results support temporal processing deficits' contribution within a multiple deficit model of dyslexia. PMID:28223953

Perspective on pain management in the 21st century.

PubMed

Polomano, Rosemary C; Dunwoody, Colleen J; Krenzischek, Dina A; Rathmell, James P

2008-02-01

Pain is a predictable consequence of surgery or trauma. Untreated, it is associated with significant physiological, emotional, mental, and economic consequences. Despite the vast amount of current knowledge, uncontrolled postoperative pain is reported by approximately 50% of patients. Thus, techniques for effective acute pain management (APM) represent unmet educational needs. The significance of these unmet needs is reflected in the number of journal and textbook publications dedicated to disseminating research, evidence-based guidelines, and clinical information. Acknowledging the importance of APM, health care accrediting agencies and professional societies have become increasingly focused on ensuring that patients receive prompt and acceptable pain relief.

Use of bioimpedance vector analysis in critically ill and cardiorenal patients.

PubMed

Peacock, W Frank

2010-01-01

Prospective outcome prediction and volume status assessment are difficult tasks in the acute care environment. Rapidly available, non-invasive, bioimpedance vector analysis (BIVA) may offer objective measures to improve clinical decision-making and predict outcomes. Performed by the placement of bipolar electrodes at the wrist and ankle, data is graphically displayed such that short-term morality risk and volume status can be accurately quantified. BIVA is able to provide indices of general cellular health, which has significant prognostic implications, as well as total body volume. Knowledge of these parameters can provide insight as to the short-term prognosis, as well as the presenting volume status. 2010 S. Karger AG, Basel.

Status, emotional displays, and the relationally-based evaluation of criminals and their behavior.

PubMed

Dilks, Lisa M; McGrimmon, Tucker S; Thye, Shane R

2015-03-01

This research uses status characteristics theory to expand our knowledge of the effects of status variables (e.g., race, education) and emotional displays on the antecedents of sentencing - evaluations of offender dangerousness and offense seriousness. We present a theoretical formulation that combines three areas of status characteristics research - reward expectations, individual evaluative settings and valued personal characteristics. The result is a quantitative measure that aggregates relative differences in demographic and emotional characteristics between offenders and their victims. The significance of this expectation advantage measure (e) in predicting evaluations of offender dangerousness and offense severity is tested using data from a vignette study. We find empirical support that expectation advantage significantly predicts these sentencing antecedents but not sentencing outcomes directly. We conclude by discussing the implications of our findings for future status and criminological research. Copyright © 2014 Elsevier Inc. All rights reserved.

Mothers' Knowledge of Their Children's Evaluations of Discipline: The Role of Type of Discipline and Misdeed, and Parenting Practices

ERIC Educational Resources Information Center

Davidov, Maayan; Grusec, Joan E.; Wolfe, Janis L.

2012-01-01

Fifty-nine 6- to 9-year-old children evaluated three discipline strategies (reasoning, verbal power assertion, acknowledgment of feelings), and mothers were asked to predict their children's evaluations. Maternal knowledge scores were derived. Mothers were less accurate at predicting their children's perceptions of discipline when the misdeed in…

Category vs. Object Knowledge in Category-Based Induction

ERIC Educational Resources Information Center

Murphy, Gregory L.; Ross, Brian H.

2010-01-01

In one form of category-based induction, people make predictions about unknown properties of objects. There is a tension between predictions made based on the object's specific features (e.g., objects above a certain size tend not to fly) and those made by reference to category-level knowledge (e.g., birds fly). Seven experiments with artificial…

Internet Competency Predicts Practical Hearing Aid Knowledge and Skills in First-Time Hearing Aid Users.

PubMed

Maidment, David; Brassington, William; Wharrad, Heather; Ferguson, Melanie

2016-10-01

The purpose of the study was to assess whether Internet competency predicted practical hearing aid knowledge and handling skills in first-time hearing aid users. The design was a prospective, randomized controlled trial of a multimedia educational intervention consisting of interactive video tutorials (or reusable learning objects [RLOs]). RLOs were delivered through DVD for TV or PC, and online. Internet competency was measured at the hearing aid fitting appointment, whereas hearing aid knowledge and practical handling skills were assessed 6 weeks postfitting. Internet competency predicted practical hearing aid knowledge and handling skills, controlling for age, hearing sensitivity, educational status, and gender for the group that received the RLOs. Internet competency was inversely related to the number of times the RLOs were watched. Associations between Internet competency and practical hearing aid knowledge, handling skills, and watching the RLOs fewer times may have arisen because of improved self-efficacy. Therefore, first-time hearing aid users who are more competent Internet users may be better equipped to apply newly learned information to effectively manage their hearing loss.

Relationships between nutrition-related knowledge, self-efficacy, and behavior for fifth grade students attending Title I and non-Title I schools.

PubMed

Hall, Elisha; Chai, Weiwen; Albrecht, Julie A

2016-01-01

The Social Cognitive Theory (SCT) is a widely used theory for nutrition education programming. Better understanding the relationships between knowledge, self-efficacy, and behavior among children of various income levels can help to form and improve nutrition programs, particularly for socioeconomically disadvantaged youth. The purpose of this study was to determine the relationships between knowledge, self-efficacy, and behavior among fifth grade students attending Title I (≥40% of students receiving free or reduced school meals) and non-Title I schools (<40% of students receiving free or reduced school meals). A validated survey was completed by 55 fifth grade students from Title I and 122 from non-Title I schools. Differences in knowledge, self-efficacy, and behavior scores between groups were assessed using t test and adjusted for variations between participating schools. Regression analysis was used to determine the relationships between knowledge, self-efficacy, and behavior. In adjusted models, the Title I group had significantly lower scores on several knowledge items and summary knowledge (P = 0.04). The Title I group had significantly lower scores on several behavior variables including intakes of fruits (P = 0.02), vegetables (P = 0.0005), whole grains (P = 0.0003), and lean protein (P = 0.047), physical activity (P = 0.002) and summary behavior (P = 0.001). However the Title I group scored higher on self-efficacy for meal planning (P = 0.04) and choosing healthy snacks (P = 0.036). Both self-efficacy (β = 0.70, P < 0.0001) and knowledge (β = 0.35, P = 0.002) strongly predicted behavior; however, only self-efficacy remained significant in the Title I group (self-efficacy, β = 0.82, P = 0.0003; knowledge, β = 0.11, P = 0.59). Results demonstrate disparities in nutrition knowledge and behavior outcomes between students surveyed from Title I and non-Title I schools, suggesting more resources may be necessary for lower income populations. Findings suggest that future nutrition interventions should focus on facilitating the improvement of children's self-efficacy. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Macroscopy predicts tumor progression in gastric cancer: A retrospective patho-historical analysis based on Napoleon Bonaparte's autopsy report.

PubMed

Dawson, Heather; Novotny, Alexander; Becker, Karen; Reim, Daniel; Langer, Rupert; Gullo, Irene; Svrcek, Magali; Niess, Jan H; Tutuian, Radu; Truninger, Kaspar; Diamantis, Ioannis; Blank, Annika; Zlobec, Inti; Riddell, Robert H; Carneiro, Fatima; Fléjou, Jean-François; Genta, Robert M; Lugli, Alessandro

2016-11-01

The cause of Napoleon Bonaparte's death remains controversial. Originally suggested to be gastric cancer, whether this was truly neoplastic or a benign lesion has been recently debated. To interpret findings of original autopsy reports in light of the current knowledge of gastric cancer and to highlight the significance of accurate macroscopy in modern-day medicine. Using original autopsy documents, endoscopic images and data from current literature, Napoleon's gastric situation was reconstructed. In a multicenter collection of 2071 gastric cancer specimens, the relationship between tumor size and features of tumor progression was assessed. Greater tumor size was associated with advanced pT, nodal metastases and Borrmann types 3-4 (p<0.001). The best cut-off for predicting pT3-4 tumors was 6.5cm (AUC 0.8; OR 1.397, 95% CI 1.35-1.446), and 6cm for lymph node metastases (AUC 0.775; OR 1.389, 95% CI 1.338-1.442). The 6cm cut-off of had a positive predictive value of 0.820 for nodal metastases and a negative predictive value of 0.880 for distant metastases. This analysis combines Napoleon's autopsy with present-day knowledge to support gastric cancer as his terminal illness and emphasizes the role of macroscopy, which may provide valuable information on gastric cancer progression and aid patient management. Copyright © 2016 Editrice Gastroenterologica Italiana S.r.l. Published by Elsevier Ltd. All rights reserved.

Prior knowledge driven Granger causality analysis on gene regulatory network discovery

DOE PAGES

Yao, Shun; Yoo, Shinjae; Yu, Dantong

2015-08-28

Our study focuses on discovering gene regulatory networks from time series gene expression data using the Granger causality (GC) model. However, the number of available time points (T) usually is much smaller than the number of target genes (n) in biological datasets. The widely applied pairwise GC model (PGC) and other regularization strategies can lead to a significant number of false identifications when n>>T. In this study, we proposed a new method, viz., CGC-2SPR (CGC using two-step prior Ridge regularization) to resolve the problem by incorporating prior biological knowledge about a target gene data set. In our simulation experiments, themore » propose new methodology CGC-2SPR showed significant performance improvement in terms of accuracy over other widely used GC modeling (PGC, Ridge and Lasso) and MI-based (MRNET and ARACNE) methods. In addition, we applied CGC-2SPR to a real biological dataset, i.e., the yeast metabolic cycle, and discovered more true positive edges with CGC-2SPR than with the other existing methods. In our research, we noticed a “ 1+1>2” effect when we combined prior knowledge and gene expression data to discover regulatory networks. Based on causality networks, we made a functional prediction that the Abm1 gene (its functions previously were unknown) might be related to the yeast’s responses to different levels of glucose. In conclusion, our research improves causality modeling by combining heterogeneous knowledge, which is well aligned with the future direction in system biology. Furthermore, we proposed a method of Monte Carlo significance estimation (MCSE) to calculate the edge significances which provide statistical meanings to the discovered causality networks. All of our data and source codes will be available under the link https://bitbucket.org/dtyu/granger-causality/wiki/Home.« less

Osteoporosis Knowledge, Calcium Intake, and Weight-Bearing Physical Activity in Three Age Groups of Women.

ERIC Educational Resources Information Center

Terrio, Kate; Auld, Garry W.

2002-01-01

Determined the extent and integration of osteoporosis knowledge in three age groups of women, comparing knowledge to calcium intake and weight bearing physical activity (WBPA). Overall calcium intake was relatively high. There were no differences in knowledge, calcium intake, or WBPA by age, nor did knowledge predict calcium intake and WBPA. None…

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

Ahrens, J.S.

For over fifteen years Sandia National Laboratories has been involved in laboratory testing of biometric identification devices. The key concept of biometric identification devices is the ability for the system to identify some unique aspect of the individual rather than some object a person may be carrying or some password they are required to know. Tests were conducted to verify manufacturer`s performance claims, to determine strengths/weaknesses of devices, and to determine devices that meet the US Department of energy`s needs. However, during recent field installation, significantly different performance was observed than was predicted by laboratory tests. Although most people usingmore » the device believed it operated adequately, the performance observed was over an order of magnitude worse than predicted. The search for reasons behind this gap between the predicted and the actual performance has revealed many possible contributing factors. As engineers, the most valuable lesson to be learned from this experience is the value of scientists and engineers with (1) common sense, (2) knowledge of human behavior, (3) the ability to observe the real world, and (4) the capability to realize the significant differences between controlled experiments and actual installations.« less

Long-term follow-up of hypochondriasis after selective serotonin reuptake inhibitor treatment.

PubMed

Schweitzer, Pernilla J; Zafar, Uzma; Pavlicova, Martina; Fallon, Brian A

2011-06-01

: There is paucity of knowledge on the long-term outcome of hypochondriasis, with even less knowledge about the effect of treatment with a selective serotonin reuptake inhibitor (SSRI). : This prospective follow-up study included 58 patients with Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) hypochondriasis who had participated in a trial of SSRI treatment 4 to 16 years earlier (mean ± SD = 8.6 ± 4.5 years). : Information was obtained on 79.3% (n = 46) of the original group. At follow-up, 40% of the patients continued to meet full DSM-IV criteria for hypochondriasis. Persistence of hypochondriasis was individually predicted by longer duration of prior hypochondriasis (P = 0.003), history of childhood physical punishment (P = 0.01), and less usage of SSRIs during the interval period (P = 0.02). Remission status was not significantly predicted by demographic characteristics, baseline hypochondriasis severity, or psychiatric comorbidity. : A substantial proportion of patients with hypochondriasis who receive treatment with SSRIs achieve remission over the long term. Interim SSRI use may be a factor contributing to better prognosis.

Facilitating Preschoolers' Scientific Knowledge Construction via Computer Games Regarding Light and Shadow: The Effect of the Prediction-Observation-Explanation (POE) Strategy

NASA Astrophysics Data System (ADS)

Hsu, Chung-Yuan; Tsai, Chin-Chung; Liang, Jyh-Chong

2011-10-01

Educational researchers have suggested that computer games have a profound influence on students' motivation, knowledge construction, and learning performance, but little empirical research has targeted preschoolers. Thus, the purpose of the present study was to investigate the effects of implementing a computer game that integrates the prediction-observation-explanation (POE) strategy (White and Gunstone in Probing understanding. Routledge, New York, 1992) on facilitating preschoolers' acquisition of scientific concepts regarding light and shadow. The children's alternative conceptions were explored as well. Fifty participants were randomly assigned into either an experimental group that played a computer game integrating the POE model or a control group that played a non-POE computer game. By assessing the students' conceptual understanding through interviews, this study revealed that the students in the experimental group significantly outperformed their counterparts in the concepts regarding "shadow formation in daylight" and "shadow orientation." However, children in both groups, after playing the games, still expressed some alternative conceptions such as "Shadows always appear behind a person" and "Shadows should be on the same side as the sun."

Nurses' participation in personal knowledge transfer: the role of leader-member exchange (LMX) and structural empowerment.

PubMed

Davies, Alicia; Wong, Carol A; Laschinger, Heather

2011-07-01

The purpose of this study was to test Kanter's theory by examining relationships among structural empowerment, leader-member exchange (LMX) quality and nurses' participation in personal knowledge transfer activities. Despite the current emphasis on evidence-based practice in health care, research suggests that implementation of research findings in everyday clinical practice is unsystematic at best with mixed outcomes. This study was a secondary analysis of data collected using a non-experimental, predictive mailed survey design. A random sample of 400 registered nurses who worked in urban tertiary care hospitals in Ontario yielded a final sample of 234 for a 58.5% response rate. Hierarchical multiple linear regression analysis revealed that the combination of LMX and structural empowerment accounted for 9.1% of the variance in personal knowledge transfer but only total empowerment was a significant independent predictor of knowledge transfer (β=0.291, t=4.012, P<0.001). Consistent with Kanter's Theory, higher levels of empowerment and leader-member exchange quality resulted in increased participation in personal knowledge transfer in practice. The results reinforce the pivotal role of nurse managers in supporting empowering work environments that are conducive to transfer of knowledge in practice to provide evidence-based care. © 2011 The Authors. Journal compilation © 2011 Blackwell Publishing Ltd.

Novel nonlinear knowledge-based mean force potentials based on machine learning.

PubMed

Dong, Qiwen; Zhou, Shuigeng

2011-01-01

The prediction of 3D structures of proteins from amino acid sequences is one of the most challenging problems in molecular biology. An essential task for solving this problem with coarse-grained models is to deduce effective interaction potentials. The development and evaluation of new energy functions is critical to accurately modeling the properties of biological macromolecules. Knowledge-based mean force potentials are derived from statistical analysis of proteins of known structures. Current knowledge-based potentials are almost in the form of weighted linear sum of interaction pairs. In this study, a class of novel nonlinear knowledge-based mean force potentials is presented. The potential parameters are obtained by nonlinear classifiers, instead of relative frequencies of interaction pairs against a reference state or linear classifiers. The support vector machine is used to derive the potential parameters on data sets that contain both native structures and decoy structures. Five knowledge-based mean force Boltzmann-based or linear potentials are introduced and their corresponding nonlinear potentials are implemented. They are the DIH potential (single-body residue-level Boltzmann-based potential), the DFIRE-SCM potential (two-body residue-level Boltzmann-based potential), the FS potential (two-body atom-level Boltzmann-based potential), the HR potential (two-body residue-level linear potential), and the T32S3 potential (two-body atom-level linear potential). Experiments are performed on well-established decoy sets, including the LKF data set, the CASP7 data set, and the Decoys “R”Us data set. The evaluation metrics include the energy Z score and the ability of each potential to discriminate native structures from a set of decoy structures. Experimental results show that all nonlinear potentials significantly outperform the corresponding Boltzmann-based or linear potentials, and the proposed discriminative framework is effective in developing knowledge-based mean force potentials. The nonlinear potentials can be widely used for ab initio protein structure prediction, model quality assessment, protein docking, and other challenging problems in computational biology.

Introducing Agronomy Students to the Concepts of Indigenous and Cultural Knowledge.

ERIC Educational Resources Information Center

Schafer, John

1993-01-01

Presents a role for indigenous knowledge in extension education and research programs. Defines indigenous knowledge and then predicts efforts to utilize indigenous knowledge to facilitate the development of agriculture systems that will be agronomically, environmentally, and economically sound and enhance acceptance by practitioners because of the…

Microbial Functional Gene Diversity Predicts Groundwater Contamination and Ecosystem Functioning.

PubMed

He, Zhili; Zhang, Ping; Wu, Linwei; Rocha, Andrea M; Tu, Qichao; Shi, Zhou; Wu, Bo; Qin, Yujia; Wang, Jianjun; Yan, Qingyun; Curtis, Daniel; Ning, Daliang; Van Nostrand, Joy D; Wu, Liyou; Yang, Yunfeng; Elias, Dwayne A; Watson, David B; Adams, Michael W W; Fields, Matthew W; Alm, Eric J; Hazen, Terry C; Adams, Paul D; Arkin, Adam P; Zhou, Jizhong

2018-02-20

Contamination from anthropogenic activities has significantly impacted Earth's biosphere. However, knowledge about how environmental contamination affects the biodiversity of groundwater microbiomes and ecosystem functioning remains very limited. Here, we used a comprehensive functional gene array to analyze groundwater microbiomes from 69 wells at the Oak Ridge Field Research Center (Oak Ridge, TN), representing a wide pH range and uranium, nitrate, and other contaminants. We hypothesized that the functional diversity of groundwater microbiomes would decrease as environmental contamination (e.g., uranium or nitrate) increased or at low or high pH, while some specific populations capable of utilizing or resistant to those contaminants would increase, and thus, such key microbial functional genes and/or populations could be used to predict groundwater contamination and ecosystem functioning. Our results indicated that functional richness/diversity decreased as uranium (but not nitrate) increased in groundwater. In addition, about 5.9% of specific key functional populations targeted by a comprehensive functional gene array (GeoChip 5) increased significantly ( P < 0.05) as uranium or nitrate increased, and their changes could be used to successfully predict uranium and nitrate contamination and ecosystem functioning. This study indicates great potential for using microbial functional genes to predict environmental contamination and ecosystem functioning. IMPORTANCE Disentangling the relationships between biodiversity and ecosystem functioning is an important but poorly understood topic in ecology. Predicting ecosystem functioning on the basis of biodiversity is even more difficult, particularly with microbial biomarkers. As an exploratory effort, this study used key microbial functional genes as biomarkers to provide predictive understanding of environmental contamination and ecosystem functioning. The results indicated that the overall functional gene richness/diversity decreased as uranium increased in groundwater, while specific key microbial guilds increased significantly as uranium or nitrate increased. These key microbial functional genes could be used to successfully predict environmental contamination and ecosystem functioning. This study represents a significant advance in using functional gene markers to predict the spatial distribution of environmental contaminants and ecosystem functioning toward predictive microbial ecology, which is an ultimate goal of microbial ecology. Copyright © 2018 He et al.

Combining in silico and in cerebro approaches for virtual screening and pose prediction in SAMPL4.

PubMed

Voet, Arnout R D; Kumar, Ashutosh; Berenger, Francois; Zhang, Kam Y J

2014-04-01

The SAMPL challenges provide an ideal opportunity for unbiased evaluation and comparison of different approaches used in computational drug design. During the fourth round of this SAMPL challenge, we participated in the virtual screening and binding pose prediction on inhibitors targeting the HIV-1 integrase enzyme. For virtual screening, we used well known and widely used in silico methods combined with personal in cerebro insights and experience. Regular docking only performed slightly better than random selection, but the performance was significantly improved upon incorporation of additional filters based on pharmacophore queries and electrostatic similarities. The best performance was achieved when logical selection was added. For the pose prediction, we utilized a similar consensus approach that amalgamated the results of the Glide-XP docking with structural knowledge and rescoring. The pose prediction results revealed that docking displayed reasonable performance in predicting the binding poses. However, prediction performance can be improved utilizing scientific experience and rescoring approaches. In both the virtual screening and pose prediction challenges, the top performance was achieved by our approaches. Here we describe the methods and strategies used in our approaches and discuss the rationale of their performances.

Combining in silico and in cerebro approaches for virtual screening and pose prediction in SAMPL4

NASA Astrophysics Data System (ADS)

Voet, Arnout R. D.; Kumar, Ashutosh; Berenger, Francois; Zhang, Kam Y. J.

2014-04-01

The SAMPL challenges provide an ideal opportunity for unbiased evaluation and comparison of different approaches used in computational drug design. During the fourth round of this SAMPL challenge, we participated in the virtual screening and binding pose prediction on inhibitors targeting the HIV-1 integrase enzyme. For virtual screening, we used well known and widely used in silico methods combined with personal in cerebro insights and experience. Regular docking only performed slightly better than random selection, but the performance was significantly improved upon incorporation of additional filters based on pharmacophore queries and electrostatic similarities. The best performance was achieved when logical selection was added. For the pose prediction, we utilized a similar consensus approach that amalgamated the results of the Glide-XP docking with structural knowledge and rescoring. The pose prediction results revealed that docking displayed reasonable performance in predicting the binding poses. However, prediction performance can be improved utilizing scientific experience and rescoring approaches. In both the virtual screening and pose prediction challenges, the top performance was achieved by our approaches. Here we describe the methods and strategies used in our approaches and discuss the rationale of their performances.

Quality of courses evaluated by 'predictions' rather than opinions: Fewer respondents needed for similar results.

PubMed

Cohen-Schotanus, Janke; Schönrock-Adema, Johanna; Schmidt, Henk G

2010-01-01

A well-known problem with student surveys is a too low response rate. Experiences with predicting electoral outcomes, which required much smaller sample sizes, inspired us to adopt a similar approach to course evaluation. We expected that having respondents estimate the average opinions of their peers required fewer respondents for comparable outcomes than giving own opinions. Two course evaluation studies were performed among successive first-year medical students (N = 380 and 450, respectively). Study 1: Half the cohort gave opinions on nine questions, while the other half predicted the average outcomes. A prize was offered for the three best predictions (motivational remedy). Study 2: Half the cohort gave opinions, a quarter made predictions without a prize and a quarter made predictions with previous year's results as prior knowledge (cognitive remedy). The numbers of respondents required for stable outcomes were determined following an iterative process. Differences between numbers of respondents required and between average scores were analysed with ANOVA. In both studies, the prediction conditions required significantly fewer respondents (p < 0.001) for comparable outcomes. The informed prediction condition required the fewest respondents (N < 20). Problems with response rates can be reduced by asking respondents to predict evaluation outcomes rather than giving opinions.

Metamemory Judgments and the Benefits of Repeated Study: Improving Recall Predictions through the Activation of Appropriate Knowledge

ERIC Educational Resources Information Center

Tiede, Heather L.; Leboe, Jason P.

2009-01-01

Correspondence between judgments of learning (JOLs) and actual recall tends to be poor when the same items are studied and recalled multiple times (e.g., A. Koriat, L. Sheffer, & H. Ma'ayan, 2002). The authors investigated whether making relevant metamemory knowledge more salient would improve the association between actual and predicted recall as…

Predictive Power of Prospective Physical Education Teachers' Attitudes towards Educational Technologies for Their Technological Pedagogical Content Knowledge

ERIC Educational Resources Information Center

Varol, Yaprak Kalemoglu

2015-01-01

The aim of the research is to determine the predictive power of prospective physical education teachers' attitudes towards educational technologies for their technological pedagogical content knowledge. In this study, a relational research model was used on a study group that consisted of 529 (M[subscript age]=21.49, SD=1.44) prospective physical…

Differential Contributions of Development and Learning to Infants' Knowledge of Object Continuity and Discontinuity

ERIC Educational Resources Information Center

Bertenthal, Bennett I.; Gredeback, Gustaf; Boyer, Ty W.

2013-01-01

Sixty infants divided evenly between 5 and 7 months of age were tested for their knowledge of object continuity versus discontinuity with a predictive tracking task. The stimulus event consisted of a moving ball that was briefly occluded for 20 trials. Both age groups predictively tracked the ball when it disappeared and reappeared via occlusion,…

An improved distance-to-dose correlation for predicting bladder and rectum dose-volumes in knowledge-based VMAT planning for prostate cancer

NASA Astrophysics Data System (ADS)

Wall, Phillip D. H.; Carver, Robert L.; Fontenot, Jonas D.

2018-01-01

The overlap volume histogram (OVH) is an anatomical metric commonly used to quantify the geometric relationship between an organ at risk (OAR) and target volume when predicting expected dose-volumes in knowledge-based planning (KBP). This work investigated the influence of additional variables contributing to variations in the assumed linear DVH-OVH correlation for the bladder and rectum in VMAT plans of prostate patients, with the goal of increasing prediction accuracy and achievability of knowledge-based planning methods. VMAT plans were retrospectively generated for 124 prostate patients using multi-criteria optimization. DVHs quantified patient dosimetric data while OVHs quantified patient anatomical information. The DVH-OVH correlations were calculated for fractional bladder and rectum volumes of 30, 50, 65, and 80%. Correlations between potential influencing factors and dose were quantified using the Pearson product-moment correlation coefficient (R). Factors analyzed included the derivative of the OVH, prescribed dose, PTV volume, bladder volume, rectum volume, and in-field OAR volume. Out of the selected factors, only the in-field bladder volume (mean R  =  0.86) showed a strong correlation with bladder doses. Similarly, only the in-field rectal volume (mean R  =  0.76) showed a strong correlation with rectal doses. Therefore, an OVH formalism accounting for in-field OAR volumes was developed to determine the extent to which it improved the DVH-OVH correlation. Including the in-field factor improved the DVH-OVH correlation, with the mean R values over the fractional volumes studied improving from  -0.79 to  -0.85 and  -0.82 to  -0.86 for the bladder and rectum, respectively. A re-planning study was performed on 31 randomly selected database patients to verify the increased accuracy of KBP dose predictions by accounting for bladder and rectum volume within treatment fields. The in-field OVH led to significantly more precise and fewer unachievable KBP predictions, especially for lower bladder and rectum dose-volumes.

Media and memory: the efficacy of video and print materials for promoting patient education about asthma.

PubMed

Wilson, Elizabeth A H; Park, Denise C; Curtis, Laura M; Cameron, Kenzie A; Clayman, Marla L; Makoul, Gregory; Vom Eigen, Keith; Wolf, Michael S

2010-09-01

We examined the effects of presentation medium on immediate and delayed recall of information and assessed the effect of giving patients take-home materials after initial presentations. Primary-care patients received video-based, print-based or no asthma education about asthma symptoms and triggers and then answered knowledge-based questions. Print participants and half the video participants received take-home print materials. A week later, available participants completed the knowledge assessment again. Participants receiving either intervention outperformed controls on immediate and delayed assessments (p<0.001). For symptom-related information, immediate performance did not significantly differ between print and video participants. A week later, receiving take-home print predicted better performance (p<0.05), as did self-reported review among recipients of take-home print (p<0.01). For content about inhaler usage, although video watchers outperformed print participants immediately after seeing the materials (p<0.001), a week later these two groups' performance did not significantly differ. Among participants given take-home materials, review predicted marginally better recall (p=0.06). Video and print interventions can promote recall of health-related information. Additionally, reviewable materials, if they are utilized, may improve retention. When creating educational tools, providers should consider how long information must be retained, its content, and the feasibility of providing tangible supporting materials. Copyright (c) 2010. Published by Elsevier Ireland Ltd.

Predictors of Sexual Risk Reduction Among Mexican Female Sex Workers Enrolled in a Behavioral Intervention Study

PubMed Central

Strathdee, Steffanie A.; Mausbach, Brent; Lozada, Remedios; Staines-Orozco, Hugo; Semple, Shirley J.; Abramovitz, Daniela; Fraga-Vallejo, Miguel; de la Torre, Adela; Amaro, Hortensia; Martínez-Mendizábal, Gustavo; Magis-Rodríguez, Carlos; Patterson, Thomas L.

2009-01-01

Objective We recently showed efficacy of an intervention to increase condom use among female sex workers (FSWs) in Tijuana and Ciudad Juarez, situated on the Mexico–United States border. We determined whether increases in condom use were predicted by social cognitive theory and injection drug user status among women randomized to this intervention. Methods Four hundred nine HIV-negative FSWs aged ≥18 years having unprotected sex with clients within the prior 2 months received a brief individual counseling session integrating motivational interviewing and principles of behavior change (ie, HIV knowledge, self-efficacy for using condoms, and outcome expectancies). Results Increases in self-efficacy scores were associated with increases in percent condom use (P = 0.008), whereas outcome expectancies were not. Female sex workers who inject drugs (FSW-IDUs) increased condom use with clients but not to the same extent as other FSWs (P = 0.09). Change in HIV knowledge was positively associated with change in percent condom use among FSW-IDUs (P = 0.03) but not noninjection drug users. Conclusions Increases in self-efficacy significantly predicted increased condom use among FSWs, consistent with social cognitive theory. Increased HIV knowledge was also important among FSW-IDUs, but their changes in condom use were modest. Enhanced interventions for FSW-IDUs are needed, taking into account realities of substance use during sexual transactions that can compromise safer sex negotiation. PMID:19384101

Higher body mass index and lower intake of dairy products predict poor glycaemic control among Type 2 Diabetes patients in Malaysia

PubMed Central

Shu, Ping Soon; Chan, Yoke Mun; Huang, Soo Lee

2017-01-01

This cross-sectional study was designed to determine factors contributing to glyceamic control in order to provide better understanding of diabetes management among Type 2 Diabetes patients. A pre-tested structured questionnaire was used to obtain information on socio-demographic and medical history. As a proxy measure for glycaemic control, glycosylated haemoglobin (HbA1c) was obtained as secondary data from the medical reports. Perceived self-care barrier on diabetes management, diet knowledge and skills, and diet quality were assessed using pretested instruments. With a response rate of 80.3%, 155 subjects were recruited for the study. Mean HbA1c level of the subjects was 9.02 ± 2.25% with more than 70% not able to achieve acceptable level in accordance to WHO recommendation. Diet quality of the subjects was unsatisfactory especially for vegetables, fruits, fish and legumes as well as from the milk and dairy products group. Higher body mass index (BMI), poorer medication compliance, lower diet knowledge and skill scores and lower intake of milk and dairy products contributed significantly on poor glycaemic control. In conclusion, while perceived self-care barriers and diet quality failed to predict HbA1c, good knowledge and skill ability, together with appropriate BMI and adequate intake of dairy products should be emphasized to optimize glycaemic control among type 2 diabetes patients. PMID:28234927

Higher body mass index and lower intake of dairy products predict poor glycaemic control among Type 2 Diabetes patients in Malaysia.

PubMed

Shu, Ping Soon; Chan, Yoke Mun; Huang, Soo Lee

2017-01-01

This cross-sectional study was designed to determine factors contributing to glyceamic control in order to provide better understanding of diabetes management among Type 2 Diabetes patients. A pre-tested structured questionnaire was used to obtain information on socio-demographic and medical history. As a proxy measure for glycaemic control, glycosylated haemoglobin (HbA1c) was obtained as secondary data from the medical reports. Perceived self-care barrier on diabetes management, diet knowledge and skills, and diet quality were assessed using pretested instruments. With a response rate of 80.3%, 155 subjects were recruited for the study. Mean HbA1c level of the subjects was 9.02 ± 2.25% with more than 70% not able to achieve acceptable level in accordance to WHO recommendation. Diet quality of the subjects was unsatisfactory especially for vegetables, fruits, fish and legumes as well as from the milk and dairy products group. Higher body mass index (BMI), poorer medication compliance, lower diet knowledge and skill scores and lower intake of milk and dairy products contributed significantly on poor glycaemic control. In conclusion, while perceived self-care barriers and diet quality failed to predict HbA1c, good knowledge and skill ability, together with appropriate BMI and adequate intake of dairy products should be emphasized to optimize glycaemic control among type 2 diabetes patients.

The current state of resident training in genomic pathology: a comprehensive analysis utilizing the Resident In-Service Exam (RISE)

PubMed Central

Haspel, Richard L.; Rinder, Henry M.; Frank, Karen M.; Wagner, Jay; Ali, Asma M.; Fisher, Patrick B.; Parks, Eric R.

2014-01-01

Objectives To determine the current state of pathology resident training in genomic and molecular pathology. Methods The Training Residents in Genomics (TRIG) Working Group developed survey and knowledge questions for the 2013 Pathology Resident In-Service Examination (RISE). Sixteen demographic questions related to amount of training, current and predicted future use, and perceived ability in molecular pathology vs. genomic medicine were included along with five genomic pathology and 19 molecular pathology knowledge questions. Results A total of 2,506 pathology residents took the 2013 RISE with approximately 600 individuals per post-graduate year (PGY). For genomic medicine, 42% of PGY-4 respondents stated they had no training compared to 7% for molecular pathology (p<0.001). PGY-4 resident perceived ability in genomic medicine, comfort in discussing results, and predicted future use as a practicing pathologist were less than reported for molecular pathology (p<0.001). There was a greater increase by PGY in knowledge question scores for molecular than for genomic pathology. Conclusions The RISE is a powerful tool in assessing the state of resident training in genomic pathology and current results suggest a significant deficit. The results also provide a baseline to assess future initiatives to improve genomics education for pathology residents such as those developed by the TRIG Working Group. PMID:25239410

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

PubMed Central

Hengl, Tomislav; Heuvelink, Gerard B. M.; Kempen, Bas; Leenaars, Johan G. B.; Walsh, Markus G.; Shepherd, Keith D.; Sila, Andrew; MacMillan, Robert A.; Mendes de Jesus, Jorge; Tamene, Lulseged; Tondoh, Jérôme E.

2015-01-01

80% of arable land in Africa has low soil fertility and suffers from physical soil problems. Additionally, significant amounts of nutrients are lost every year due to unsustainable soil management practices. This is partially the result of insufficient use of soil management knowledge. To help bridge the soil information gap in Africa, the Africa Soil Information Service (AfSIS) project was established in 2008. Over the period 2008–2014, the AfSIS project compiled two point data sets: the Africa Soil Profiles (legacy) database and the AfSIS Sentinel Site database. These data sets contain over 28 thousand sampling locations and represent the most comprehensive soil sample data sets of the African continent to date. Utilizing these point data sets in combination with a large number of covariates, we have generated a series of spatial predictions of soil properties relevant to the agricultural management—organic carbon, pH, sand, silt and clay fractions, bulk density, cation-exchange capacity, total nitrogen, exchangeable acidity, Al content and exchangeable bases (Ca, K, Mg, Na). We specifically investigate differences between two predictive approaches: random forests and linear regression. Results of 5-fold cross-validation demonstrate that the random forests algorithm consistently outperforms the linear regression algorithm, with average decreases of 15–75% in Root Mean Squared Error (RMSE) across soil properties and depths. Fitting and running random forests models takes an order of magnitude more time and the modelling success is sensitive to artifacts in the input data, but as long as quality-controlled point data are provided, an increase in soil mapping accuracy can be expected. Results also indicate that globally predicted soil classes (USDA Soil Taxonomy, especially Alfisols and Mollisols) help improve continental scale soil property mapping, and are among the most important predictors. This indicates a promising potential for transferring pedological knowledge from data rich countries to countries with limited soil data. PMID:26110833

Developmental dyslexia: predicting individual risk.

PubMed

Thompson, Paul A; Hulme, Charles; Nash, Hannah M; Gooch, Debbie; Hayiou-Thomas, Emma; Snowling, Margaret J

2015-09-01

Causal theories of dyslexia suggest that it is a heritable disorder, which is the outcome of multiple risk factors. However, whether early screening for dyslexia is viable is not yet known. The study followed children at high risk of dyslexia from preschool through the early primary years assessing them from age 3 years and 6 months (T1) at approximately annual intervals on tasks tapping cognitive, language, and executive-motor skills. The children were recruited to three groups: children at family risk of dyslexia, children with concerns regarding speech, and language development at 3;06 years and controls considered to be typically developing. At 8 years, children were classified as 'dyslexic' or not. Logistic regression models were used to predict the individual risk of dyslexia and to investigate how risk factors accumulate to predict poor literacy outcomes. Family-risk status was a stronger predictor of dyslexia at 8 years than low language in preschool. Additional predictors in the preschool years include letter knowledge, phonological awareness, rapid automatized naming, and executive skills. At the time of school entry, language skills become significant predictors, and motor skills add a small but significant increase to the prediction probability. We present classification accuracy using different probability cutoffs for logistic regression models and ROC curves to highlight the accumulation of risk factors at the individual level. Dyslexia is the outcome of multiple risk factors and children with language difficulties at school entry are at high risk. Family history of dyslexia is a predictor of literacy outcome from the preschool years. However, screening does not reach an acceptable clinical level until close to school entry when letter knowledge, phonological awareness, and RAN, rather than family risk, together provide good sensitivity and specificity as a screening battery. © 2015 The Authors. Journal of Child Psychology and Psychiatry published by John Wiley & Sons Ltd on behalf of Association for Child and Adolescent Mental Health.

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

PubMed

Hengl, Tomislav; Heuvelink, Gerard B M; Kempen, Bas; Leenaars, Johan G B; Walsh, Markus G; Shepherd, Keith D; Sila, Andrew; MacMillan, Robert A; Mendes de Jesus, Jorge; Tamene, Lulseged; Tondoh, Jérôme E

2015-01-01

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

Educational intervention improves anticoagulation control in atrial fibrillation patients: the TREAT randomised trial.

PubMed

Clarkesmith, Danielle E; Pattison, Helen M; Lip, Gregory Y H; Lane, Deirdre A

2013-01-01

Stroke prevention in atrial fibrillation (AF), most commonly with warfarin, requires maintenance of a narrow therapeutic target (INR 2.0 to 3.0) and is often poorly controlled in practice. Poor patient-understanding surrounding AF and its treatment may contribute to the patient's willingness to adhere to recommendations. A theory-driven intervention, developed using patient interviews and focus groups, consisting of a one-off group session (1-6 patients) utilising an "expert-patient" focussed DVD, educational booklet, self-monitoring diary and worksheet, was compared in a randomised controlled trial (ISRCTN93952605) against usual care, with patient postal follow-ups at 1, 2, 6, and 12-months. Ninety-seven warfarin-naïve AF patients were randomised to intervention (n=46, mean age (SD) 72.0 (8.2), 67.4% men), or usual care (n=51, mean age (SD) 73.7 (8.1), 62.7% men), stratified by age, sex, and recruitment centre. Primary endpoint was time within therapeutic range (TTR); secondary endpoints included knowledge, quality of life, anxiety/depression, beliefs about medication, and illness perceptions. Intervention patients had significantly higher TTR than usual care at 6-months (76.2% vs. 71.3%; p=0.035); at 12-months these differences were not significant (76.0% vs. 70.0%; p=0.44). Knowledge increased significantly across time (F (3, 47) = 6.4; p<0.01), but there were no differences between groups (F (1, 47) = 3.3; p = 0.07). At 6-months, knowledge scores predicted TTR (r=0.245; p=0.04). Patients' scores on subscales representing their perception of the general harm and overuse of medication, as well as the perceived necessity of their AF specific medications predicted TTR at 6- and 12-months. A theory-driven educational intervention significantly improves TTR in AF patients initiating warfarin during the first 6-months. Adverse clinical outcomes may potentially be reduced by improving patients' understanding of the necessity of warfarin and reducing their perception of treatment harm. Improving education provision for AF patients is essential to ensure efficacious and safe treatment. The trial is registered with Current Controlled Trials, ISRCTN93952605, and details are available at www.controlled-trials.com/ISRCTN93952605.

Factors influencing consumer dietary health preventative behaviours.

PubMed

Petrovici, Dan A; Ritson, Christopher

2006-09-01

The deterioration of the health status of the Romanian population during the economic transition from a centrally planned to a free market economy has been linked to lifestyles factors (e.g. diet) regarded as a main determinants of the disparity in life expectancy between Eastern and Western Europe. Reforms in the health care system in this transition economy aim to focus on preventive action. The purpose of this study was to identify the factors that impact on the individual decision to engage in Dietary Health Preventive Behaviour (DHPB) and investigate their influence in the context of an adapted health cognition model. A population-based study recruited 485 adult respondents using random route sampling and face-to-face administered questionnaires. Respondents' health motivation, beliefs that diet can prevent disease, knowledge about nutrition, level of education attainment and age have a positive influence on DHPB. Perceived barriers to healthy eating have a negative impact on alcohol moderation. The information acquisition behaviour (frequency of reading food labels) is negatively predicted by age and positively predicted by health motivation, education, self-reported knowledge about nutrition and household financial status. A significant segment of respondents believe they are not susceptible to the elicited diseases. Health promotion strategies should aim to change the judgments of health risk. The adaptation of the Health Belief Model and the Theory of Health Preventive Behaviour represents a valid framework of predicting DHPB. The negative sign of perceived threat of disease on DHPB may suggest that, under an income constraint, consumers tend to trade off long-term health benefits for short-term benefits. This cautions against the use of negative messages in public health campaigns. Raising the awareness of diet-disease relationships, knowledge about nutrition (particularly sources and risks associated with dietary fat and cholesterol) may induce people to adopt preventive dietary habits.

Distribution of the Habitat Suitability of the Main Malaria Vector in French Guiana Using Maximum Entropy Modeling.

PubMed

Moua, Yi; Roux, Emmanuel; Girod, Romain; Dusfour, Isabelle; de Thoisy, Benoit; Seyler, Frédérique; Briolant, Sébastien

2017-05-01

Malaria is an important health issue in French Guiana. Its principal mosquito vector in this region is Anopheles darlingi Root. Knowledge of the spatial distribution of this species is still very incomplete due to the extent of French Guiana and the difficulty to access most of the territory. Species distribution modeling based on the maximal entropy procedure was used to predict the spatial distribution of An. darlingi using 39 presence sites. The resulting model provided significantly high prediction performances (mean 10-fold cross-validated partial area under the curve and continuous Boyce index equal to, respectively, 1.11-with a level of omission error of 20%-and 0.42). The model also provided a habitat suitability map and environmental response curves in accordance with the known entomological situation. Several environmental characteristics that had a positive correlation with the presence of An. darlingi were highlighted: nonpermanent anthropogenic changes of the natural environment, the presence of roads and tracks, and opening of the forest. Some geomorphological landforms and high altitude landscapes appear to be unsuitable for An. darlingi. The species distribution modeling was able to reliably predict the distribution of suitable habitats for An. darlingi in French Guiana. Results allowed completion of the knowledge of the spatial distribution of the principal malaria vector in this Amazonian region, and identification of the main factors that favor its presence. They should contribute to the definition of a necessary targeted vector control strategy in a malaria pre-elimination stage, and allow extrapolation of the acquired knowledge to other Amazonian or malaria-endemic contexts. © The Authors 2016. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Complex networks as a unified framework for descriptive analysis and predictive modeling in climate

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

Steinhaeuser, Karsten J K; Chawla, Nitesh; Ganguly, Auroop R

The analysis of climate data has relied heavily on hypothesis-driven statistical methods, while projections of future climate are based primarily on physics-based computational models. However, in recent years a wealth of new datasets has become available. Therefore, we take a more data-centric approach and propose a unified framework for studying climate, with an aim towards characterizing observed phenomena as well as discovering new knowledge in the climate domain. Specifically, we posit that complex networks are well-suited for both descriptive analysis and predictive modeling tasks. We show that the structural properties of climate networks have useful interpretation within the domain. Further,more » we extract clusters from these networks and demonstrate their predictive power as climate indices. Our experimental results establish that the network clusters are statistically significantly better predictors than clusters derived using a more traditional clustering approach. Using complex networks as data representation thus enables the unique opportunity for descriptive and predictive modeling to inform each other.« less

Predictive factors for the Nursing Diagnoses in people living with Acquired Immune Deficiency Syndrome 1

PubMed Central

da Silva, Richardson Augusto Rosendo; Costa, Romanniny Hévillyn Silva; Nelson, Ana Raquel Cortês; Duarte, Fernando Hiago da Silva; Prado, Nanete Caroline da Costa; Rodrigues, Eduardo Henrique Fagundes

2016-01-01

Abstract Objective: to identify the predictive factors for the nursing diagnoses in people living with Acquired Immune Deficiency Syndrome. Method: a cross-sectional study, undertaken with 113 people living with AIDS. The data were collected using an interview script and physical examination. Logistic regression was used for the data analysis, considering a level of significance of 10%. Results: the predictive factors identified were: for the nursing diagnosis of knowledge deficit-inadequate following of instructions and verbalization of the problem; for the nursing diagnosis of failure to adhere - years of study, behavior indicative of failure to adhere, participation in the treatment and forgetfulness; for the nursing diagnosis of sexual dysfunction - family income, reduced frequency of sexual practice, perceived deficit in sexual desire, perceived limitations imposed by the disease and altered body function. Conclusion: the predictive factors for these nursing diagnoses involved sociodemographic and clinical characteristics, defining characteristics, and related factors, which must be taken into consideration during the assistance provided by the nurse. PMID:27384466

Prediction and characterization of novel epitopes of serotype A foot-and-mouth disease viruses circulating in East Africa using site-directed mutagenesis

PubMed Central

Bari, Fufa Dawo; Parida, Satya; Asfor, Amin S.; Haydon, Daniel T.; Reeve, Richard; Paton, David J.

2015-01-01

Epitopes on the surface of the foot-and-mouth disease virus (FMDV) capsid have been identified by monoclonal antibody (mAb) escape mutant studies leading to the designation of four antigenic sites in serotype A FMDV. Previous work focused on viruses isolated mainly from Asia, Europe and Latin America. In this study we report on the prediction of epitopes in African serotype A FMDVs and testing of selected epitopes using reverse genetics. Twenty-four capsid amino acid residues were predicted to be of antigenic significance by analysing the capsid sequences (n = 56) using in silico methods, and six residues by correlating capsid sequence with serum–virus neutralization data. The predicted residues were distributed on the surface-exposed capsid regions, VP1–VP3. The significance of residue changes at eight of the predicted epitopes was tested by site-directed mutagenesis using a cDNA clone resulting in the generation of 12 mutant viruses involving seven sites. The effect of the amino acid substitutions on the antigenic nature of the virus was assessed by virus neutralization (VN) test. Mutations at four different positions, namely VP1-43, VP1-45, VP2-191 and VP3-132, led to significant reduction in VN titre (P value = 0.05, 0.05, 0.001 and 0.05, respectively). This is the first time, to our knowledge, that the antigenic regions encompassing amino acids VP1-43 to -45 (equivalent to antigenic site 3 in serotype O), VP2-191 and VP3-132 have been predicted as epitopes and evaluated serologically for serotype A FMDVs. This identifies novel capsid epitopes of recently circulating serotype A FMDVs in East Africa. PMID:25614587

Advancement in Watershed Modelling Using Dynamic Lateral and Longitudinal Sediment (Dis)connectivity Prediction

NASA Astrophysics Data System (ADS)

Mahoney, D. T.; al Aamery, N. M. H.; Fox, J.

2017-12-01

The authors find that sediment (dis)connectivity has seldom taken precedence within watershed models, and the present study advances this modeling framework and applies the modeling within a bedrock-controlled system. Sediment (dis)connectivity, defined as the detachment and transport of sediment from source to sink between geomorphic zones, is a major control on sediment transport. Given the availability of high resolution geospatial data, coupling sediment connectivity concepts within sediment prediction models offers an approach to simulate sediment sources and pathways within a watershed's sediment cascade. Bedrock controlled catchments are potentially unique due to the presence of rock outcrops causing longitudinal impedance to sediment transport pathways in turn impacting the longitudinal distribution of the energy gradient responsible for conveying sediment. Therefore, the authors were motivated by the need to formulate a sediment transport model that couples sediment (dis)connectivity knowledge to predict sediment flux for bedrock controlled catchments. A watershed-scale sediment transport model was formulated that incorporates sediment (dis)connectivity knowledge collected via field reconnaissance and predicts sediment flux through coupling with the Partheniades equation and sediment continuity model. Sediment (dis)connectivity was formulated by coupling probabilistic upland lateral connectivity prediction with instream longitudinal connectivity assessments via discretization of fluid and sediment pathways. Flux predictions from the upland lateral connectivity model served as an input to the instream longitudinal connectivity model. Disconnectivity in the instream model was simulated via the discretization of stream reaches due to barriers such as bedrock outcroppings and man-made check dams. The model was tested for a bedrock controlled catchment in Kentucky, USA for which extensive historic water and sediment flux data was available. Predicted sediment flux was validated via sediment flux measurements collected by the authors. Watershed configuration and the distribution of lateral and longitudinal impedances to sediment transport were found to have significant influence on sediment connectivity and thus sediment flux.

Sexual knowledge, attitudes and activity of older people in Taipei, Taiwan.

PubMed

Wang, Tze-Fang; Lu, Chwen-Hwa; Chen, I-Ju; Yu, Shu

2008-02-01

We examined sexual activity and predictive factors among older people in Taipei, Taiwan. We aimed to characterize the older population engaged in sexual activity and determine influencing factors, exploring aspects of sexuality that may influence elders' health and quality of life (QOL). Studies of sexual attitudes and behaviour have found that sexual difficulties are common among mature adults worldwide, influenced in men and women by physical health, ageing, psychosocial and cultural factors. We conducted a community-based retrospective study involving a random sample of 412 men and 204 women over age 65. A questionnaire on demographics and social situations was administered, along with a Sexuality Knowledge and Attitudes Scale; 34 questions evaluated sexual knowledge and 18 evaluated sexual attitudes. Two-hundred and twenty participants were sexually active (35.7%), 185 mainly with spouses (84.1%); frequency was 21.4 (SD 16.9) times per year (range: 1-120). Multiple logistic regressions identified five significant predictors of sexual activity: gender, age, being with spouse, sexual knowledge and sexual attitudes. Sexual activity was significantly associated with higher education levels, lower stress and more self-reported daily activities. Our results agreed with Western studies linking sexual activity with better health and higher QOL in older adults. Older peoples' stress and daily activity levels are recognized quality-of-life measures; lower stress and more daily activities among sexually active older people suggests a connection between sexual activity and higher QOL. Increasing knowledge and improving attitudes about sexuality may help older people build healthier relationships and enhance health and QOL. Relevance to clinical practice. If healthcare professionals possess greater understanding of older peoples' sexuality, healthcare systems may find ways to increase sexual knowledge and foster healthier attitudes and relationships to improve older peoples' overall health and QOL.

Role of family support and women's knowledge on pregnancy-related risks in adherence to maternal iron-folic acid supplementation in Indonesia.

PubMed

Wiradnyani, Luh Ade Ari; Khusun, Helda; Achadi, Endang L; Ocviyanti, Dwiana; Shankar, Anuraj H

2016-10-01

To examine whether women's knowledge of pregnancy-related risks and family support received during pregnancy are associated with adherence to maternal iron-folic acid (IFA) supplementation. Secondary data analysis of the 2002-03, 2007 and 2012 Indonesia Demographic and Health Survey. Analysis of the association between factors associated with adherence (consuming ≥90 IFA tablets), including the women's knowledge and family support, was performed using multivariate logistic regression. National household survey. Women (n 19 133) who had given birth within 2 years prior to the interview date. Knowledge of pregnancy-related risks was associated with increased adherence to IFA supplementation (adjusted OR=1·8; 95 % CI 1·6, 2·0), as was full family (particularly husband's) support (adjusted OR=1·9; 95 % CI 1·6, 2·3). Adequate antenatal care (ANC) visits (i.e. four or more) was associated with increased adherence (adjusted OR=2·2; 95 % CI 2·0, 2·4). However, ANC providers missed opportunities to distribute tablets and information, as among women with adequate ANC visits, 15 % reported never having received/bought any IFA tablets and 30 % had no knowledge of pregnancy-related risks. A significant interaction was observed between family support and the women's educational level in predicting adherence. Family support significantly increased the adherence among women with <9 years of education. Improving women's knowledge of pregnancy-related risks and involving family members, particularly the husband and importantly for less-educated women, improved adherence to IFA supplementation. ANC visit opportunities must be optimized to provide women with sufficient numbers of IFA tablets along with health information (especially on pregnancy-related risks) and partner support counselling.

Knowledge of Previous Tasks: Task Similarity Influences Bias in Task Duration Predictions

PubMed Central

Thomas, Kevin E.; König, Cornelius J.

2018-01-01

Bias in predictions of task duration has been attributed to misremembering previous task duration and using previous task duration as a basis for predictions. This research sought to further examine how previous task information affects prediction bias by manipulating task similarity and assessing the role of previous task duration feedback. Task similarity was examined through participants performing two tasks 1 week apart that were the same or different. Duration feedback was provided to all participants (Experiment 1), its recall was manipulated (Experiment 2), and its provision was manipulated (Experiment 3). In all experiments, task similarity influenced bias on the second task, with predictions being less biased when the first task was the same task. However, duration feedback did not influence bias. The findings highlight the pivotal role of knowledge about previous tasks in task duration prediction and are discussed in relation to the theoretical accounts of task duration prediction bias. PMID:29881362

The Effects of Prior Knowledge Activation on Free Recall and Study Time Allocation.

ERIC Educational Resources Information Center

Machiels-Bongaerts, Maureen; And Others

The effects of mobilizing prior knowledge on information processing were studied. Two hypotheses, the cognitive set-point hypothesis and the selective attention hypothesis, try to account for the facilitation effects of prior knowledge activation. These hypotheses predict different recall patterns as a result of mobilizing prior knowledge. In…

Knowledge of Conditional Spelling Patterns Supports Word Spelling among Danish Fifth Graders

ERIC Educational Resources Information Center

Nielsen, Anne-Mette Veber

2017-01-01

Graphotactic knowledge and word-specific orthographic knowledge have been shown to account for unique variance in concurrent spelling skills beyond phonological skills in the early school years.The present study examined whether knowledge of spelling patterns conditioned by phonological context would add to the concurrent prediction of spelling…

A Comparison of Experienced and Preservice Elementary School Teachers' Content Knowledge and Pedagogical Content Knowledge about Electric Circuits

ERIC Educational Resources Information Center

Lin, Jing-Wen

2017-01-01

This study investigated the differences between Taiwanese experienced and preservice elementary school science teachers' content knowledge (CK) about electric circuits and their ability to predict students' preconceptions about electric circuits as an indicator of their pedagogical content knowledge (PCK). An innovative web-based recruitment and…

Self-directed versus traditional classroom training for neonatal resuscitation.

PubMed

Weiner, Gary M; Menghini, Karin; Zaichkin, Jeanette; Caid, Ann E; Jacoby, Carrie J; Simon, Wendy M

2011-04-01

Neonatal Resuscitation Program instructors spend most of their classroom time giving lectures and demonstrating basic skills. We hypothesized that a self-directed education program could shift acquisition of these skills outside the classroom, shorten the duration of the class, and allow instructors to use their time to facilitate low-fidelity simulation and debriefing. Novice providers were randomly allocated to self-directed education or a traditional class. Self-directed participants received a textbook, instructional video, and portable equipment kit and attended a 90-minute simulation session with an instructor. The traditional class included 6 hours of lectures and instructor-directed skill stations. Outcome measures included resuscitation skill (megacode assessment score), content knowledge, participant satisfaction, and self-confidence. Forty-six subjects completed the study. There was no significant difference between the study groups in either the megacode assessment score (23.8 [traditional] vs 24.5 [self-directed]; P = .46) or fraction that passed the "megacode" (final skills assessment) (56% [traditional] vs 65% [self-directed]; P = .76). There were no significant differences in content knowledge, course satisfaction, or postcourse self-confidence. Content knowledge, years of experience, and self-confidence did not predict resuscitation skill. Self-directed education improves the educational efficiency of the neonatal resuscitation course by shifting the acquisition of cognitive and basic procedural skills outside of the classroom, which allows the instructor to add low-fidelity simulation and debriefing while significantly decreasing the duration of the course.

Automatic knowledge extraction from chemical structures: the case of mutagenicity prediction.

PubMed

Ferrari, T; Cattaneo, D; Gini, G; Golbamaki Bakhtyari, N; Manganaro, A; Benfenati, E

2013-01-01

This work proposes a new structure-activity relationship (SAR) approach to mine molecular fragments that act as structural alerts for biological activity. The entire process is designed to fit with human reasoning, not only to make the predictions more reliable but also to permit clear control by the user in order to meet customized requirements. This approach has been tested on the mutagenicity endpoint, showing marked prediction skills and, more interestingly, bringing to the surface much of the knowledge already collected in the literature as well as new evidence.

Developmental Foundations of Children’s Fraction Magnitude Knowledge

PubMed Central

Mou, Yi; Li, Yaoran; Hoard, Mary K.; Nugent, Lara D.; Chu, Felicia W.; Rouder, Jeffrey N.; Geary, David C.

2016-01-01

The conceptual insight that fractions represent magnitudes is a critical yet daunting step in children’s mathematical development, and the knowledge of fraction magnitudes influences children’s later mathematics learning including algebra. In this study, longitudinal data were analyzed to identify the mathematical knowledge and domain-general competencies that predicted 8th and 9th graders’ (n=122) knowledge of fraction magnitudes and its cross-grade gains. Performance on the fraction magnitude measures predicted 9th grade algebra achievement. Understanding and fluently identifying the numerator-denominator relation in 7th grade emerged as the key predictor of later fraction magnitudes knowledge in both 8th and 9th grades. Competence at using fraction procedures, knowledge of whole number magnitudes, and the central executive contributed to 9th but not 8th graders’ fraction magnitude knowledge, and knowledge of whole number magnitude contributed to cross-grade gains. The key results suggest fluent processing of numerator-denominator relations presages students’ understanding of fractions as magnitudes and that the integration of whole number and fraction magnitudes occurs gradually. PMID:27773965

G-LoSA for Prediction of Protein-Ligand Binding Sites and Structures.

PubMed

Lee, Hui Sun; Im, Wonpil

2017-01-01

Recent advances in high-throughput structure determination and computational protein structure prediction have significantly enriched the universe of protein structure. However, there is still a large gap between the number of available protein structures and that of proteins with annotated function in high accuracy. Computational structure-based protein function prediction has emerged to reduce this knowledge gap. The identification of a ligand binding site and its structure is critical to the determination of a protein's molecular function. We present a computational methodology for predicting small molecule ligand binding site and ligand structure using G-LoSA, our protein local structure alignment and similarity measurement tool. All the computational procedures described here can be easily implemented using G-LoSA Toolkit, a package of standalone software programs and preprocessed PDB structure libraries. G-LoSA and G-LoSA Toolkit are freely available to academic users at http://compbio.lehigh.edu/GLoSA . We also illustrate a case study to show the potential of our template-based approach harnessing G-LoSA for protein function prediction.

Risk factors influencing dentists' hepatitis B-related knowledge and attitudes and their willingness to treat hepatitis B positive patients.

PubMed

Khosravanifard, B; Rakhshan, V; Sherafat, S; Najafi-Salehi, L

2015-02-25

This study assessed factors that could predict dentists' knowledge, attitudes and behaviour towards hepatitis B virus (HBV). A total of 300 dentists in Tehran, Islamic Republic of Iran were surveyed and their demographic, educational and office characteristics were analysed in relation to their scores on knowledge about HBV, self-reported attitudes towards treating people infected with HBV and actual behaviour towards treating simulated HBV-positive patients. Having a Master's degree, faculty membership, taking ≥ 3 continuing education courses, wearing eye-shields, spending more time on preparing dental units and higher self-confidence about knowledge predicted better knowledge. A positive attitude was associated with having attended more courses and working in group practice. The number of courses and a shorter dental unit preparation time positively affected dentists' behaviour.

Key Future Engineering Capabilities for Human Capital Retention

NASA Astrophysics Data System (ADS)

Sivich, Lorrie

Projected record retirements of Baby Boomer generation engineers have been predicted to result in significant losses of mission-critical knowledge in space, national security, and future scientific ventures vital to high-technology corporations. No comprehensive review or analysis of engineering capabilities has been performed to identify threats related to the specific loss of mission-critical knowledge posed by the increasing retirement of tenured engineers. Archival data from a single diversified Fortune 500 aerospace manufacturing engineering company's engineering career database were analyzed to ascertain whether relationships linking future engineering capabilities, engineering disciplines, and years of engineering experience could be identified to define critical knowledge transfer models. Chi square, logistic, and linear regression analyses were used to map patterns of discipline-specific, mission-critical knowledge using archival data of engineers' perceptions of engineering capabilities, key developmental experiences, and knowledge learned from their engineering careers. The results from the study were used to document key engineering future capabilities. The results were then used to develop a proposed human capital retention plan to address specific key knowledge gaps of younger engineers as veteran engineers retire. The potential for social change from this study involves informing leaders of aerospace engineering corporations on how to build better quality mentoring or succession plans to fill the void of lost knowledge from retiring engineers. This plan can secure mission-critical knowledge for younger engineers for current and future product development and increased global competitiveness in the technology market.

Improved accuracy of supervised CRM discovery with interpolated Markov models and cross-species comparison

PubMed Central

Kazemian, Majid; Zhu, Qiyun; Halfon, Marc S.; Sinha, Saurabh

2011-01-01

Despite recent advances in experimental approaches for identifying transcriptional cis-regulatory modules (CRMs, ‘enhancers’), direct empirical discovery of CRMs for all genes in all cell types and environmental conditions is likely to remain an elusive goal. Effective methods for computational CRM discovery are thus a critically needed complement to empirical approaches. However, existing computational methods that search for clusters of putative binding sites are ineffective if the relevant TFs and/or their binding specificities are unknown. Here, we provide a significantly improved method for ‘motif-blind’ CRM discovery that does not depend on knowledge or accurate prediction of TF-binding motifs and is effective when limited knowledge of functional CRMs is available to ‘supervise’ the search. We propose a new statistical method, based on ‘Interpolated Markov Models’, for motif-blind, genome-wide CRM discovery. It captures the statistical profile of variable length words in known CRMs of a regulatory network and finds candidate CRMs that match this profile. The method also uses orthologs of the known CRMs from closely related genomes. We perform in silico evaluation of predicted CRMs by assessing whether their neighboring genes are enriched for the expected expression patterns. This assessment uses a novel statistical test that extends the widely used Hypergeometric test of gene set enrichment to account for variability in intergenic lengths. We find that the new CRM prediction method is superior to existing methods. Finally, we experimentally validate 12 new CRM predictions by examining their regulatory activity in vivo in Drosophila; 10 of the tested CRMs were found to be functional, while 6 of the top 7 predictions showed the expected activity patterns. We make our program available as downloadable source code, and as a plugin for a genome browser installed on our servers. PMID:21821659

A biological network-based regularized artificial neural network model for robust phenotype prediction from gene expression data.

PubMed

Kang, Tianyu; Ding, Wei; Zhang, Luoyan; Ziemek, Daniel; Zarringhalam, Kourosh

2017-12-19

Stratification of patient subpopulations that respond favorably to treatment or experience and adverse reaction is an essential step toward development of new personalized therapies and diagnostics. It is currently feasible to generate omic-scale biological measurements for all patients in a study, providing an opportunity for machine learning models to identify molecular markers for disease diagnosis and progression. However, the high variability of genetic background in human populations hampers the reproducibility of omic-scale markers. In this paper, we develop a biological network-based regularized artificial neural network model for prediction of phenotype from transcriptomic measurements in clinical trials. To improve model sparsity and the overall reproducibility of the model, we incorporate regularization for simultaneous shrinkage of gene sets based on active upstream regulatory mechanisms into the model. We benchmark our method against various regression, support vector machines and artificial neural network models and demonstrate the ability of our method in predicting the clinical outcomes using clinical trial data on acute rejection in kidney transplantation and response to Infliximab in ulcerative colitis. We show that integration of prior biological knowledge into the classification as developed in this paper, significantly improves the robustness and generalizability of predictions to independent datasets. We provide a Java code of our algorithm along with a parsed version of the STRING DB database. In summary, we present a method for prediction of clinical phenotypes using baseline genome-wide expression data that makes use of prior biological knowledge on gene-regulatory interactions in order to increase robustness and reproducibility of omic-scale markers. The integrated group-wise regularization methods increases the interpretability of biological signatures and gives stable performance estimates across independent test sets.

Anticipatory control through associative learning of subliminal relations: invisible may be better than visible.

PubMed

Farooqui, Ausaf A; Manly, Tom

2015-03-01

We showed that anticipatory cognitive control could be unconsciously instantiated through subliminal cues that predicted enhanced future control needs. In task-switching experiments, one of three subliminal cues preceded each trial. Participants had no conscious experience or knowledge of these cues, but their performance was significantly improved on switch trials after cues that predicted task switches (but not particular tasks). This utilization of subliminal information was flexible and adapted to a change in cues predicting task switches and occurred only when switch trials were difficult and effortful. When cues were consciously visible, participants were unable to discern their relevance and could not use them to enhance switch performance. Our results show that unconscious cognition can implicitly use subliminal information in a goal-directed manner for anticipatory control, and they also suggest that subliminal representations may be more conducive to certain forms of associative learning. © The Author(s) 2015.

Does a better model yield a better argument? An info-gap analysis

NASA Astrophysics Data System (ADS)

Ben-Haim, Yakov

2017-04-01

Theories, models and computations underlie reasoned argumentation in many areas. The possibility of error in these arguments, though of low probability, may be highly significant when the argument is used in predicting the probability of rare high-consequence events. This implies that the choice of a theory, model or computational method for predicting rare high-consequence events must account for the probability of error in these components. However, error may result from lack of knowledge or surprises of various sorts, and predicting the probability of error is highly uncertain. We show that the putatively best, most innovative and sophisticated argument may not actually have the lowest probability of error. Innovative arguments may entail greater uncertainty than more standard but less sophisticated methods, creating an innovation dilemma in formulating the argument. We employ info-gap decision theory to characterize and support the resolution of this problem and present several examples.

Electrochemistry-based Battery Modeling for Prognostics

NASA Technical Reports Server (NTRS)

Daigle, Matthew J.; Kulkarni, Chetan Shrikant

2013-01-01

Batteries are used in a wide variety of applications. In recent years, they have become popular as a source of power for electric vehicles such as cars, unmanned aerial vehicles, and commericial passenger aircraft. In such application domains, it becomes crucial to both monitor battery health and performance and to predict end of discharge (EOD) and end of useful life (EOL) events. To implement such technologies, it is crucial to understand how batteries work and to capture that knowledge in the form of models that can be used by monitoring, diagnosis, and prognosis algorithms. In this work, we develop electrochemistry-based models of lithium-ion batteries that capture the significant electrochemical processes, are computationally efficient, capture the effects of aging, and are of suitable accuracy for reliable EOD prediction in a variety of usage profiles. This paper reports on the progress of such a model, with results demonstrating the model validity and accurate EOD predictions.

Predicting Causes of Data Quality Issues in a Clinical Data Research Network.

PubMed

Khare, Ritu; Ruth, Byron J; Miller, Matthew; Tucker, Joshua; Utidjian, Levon H; Razzaghi, Hanieh; Patibandla, Nandan; Burrows, Evanette K; Bailey, L Charles

2018-01-01

Clinical data research networks (CDRNs) invest substantially in identifying and investigating data quality problems. While identification is largely automated, the investigation and resolution are carried out manually at individual institutions. In the PEDSnet CDRN, we found that only approximately 35% of the identified data quality issues are resolvable as they are caused by errors in the extract-transform-load (ETL) code. Nonetheless, with no prior knowledge of issue causes, partner institutions end up spending significant time investigating issues that represent either inherent data characteristics or false alarms. This work investigates whether the causes (ETL, Characteristic, or False alarm) can be predicted before spending time investigating issues. We trained a classifier on the metadata from 10,281 real-world data quality issues, and achieved a cause prediction F1-measure of up to 90%. While initially tested on PEDSnet, the proposed methodology is applicable to other CDRNs facing similar bottlenecks in handling data quality results.

The state of rhizospheric science in the era of multi-omics: A practical guide to omics technologies

DOE PAGES

White, Richard Allen; Rivas-Ubach, Albert; Borkum, Mark I.; ...

2017-05-06

Over the past century, the significance of the rhizosphere has been increasingly recognized by the scientific community. Furthermore, this complex biological system is comprised of vast interconnected networks of microbial organisms that interact directly with their plant hosts, including archaea, bacteria, fungi, picoeukaryotes, and viruses. The rhizosphere provides a nutritional base to the terrestrial biosphere, and is integral to plant growth, crop production, and ecosystem health. There is little mechanistic understanding of the rhizosphere, but, and that constitutes a critical knowledge gap. It inhibits our ability to predict and control the terrestrial ecosystem to achieve desirable outcomes, such as bioenergymore » production, crop yield maximization, and soil-based carbon sequestration. Multi-omics have the potential to significantly advance our knowledge of rhizospheric science. Our review covers multi-omic techniques and technologies; methods and protocols for specific rhizospheric science questions; and the challenges to be addressed during this century of rhizospheric science.« less

The state of rhizospheric science in the era of multi-omics: A practical guide to omics technologies

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

White, Richard Allen; Rivas-Ubach, Albert; Borkum, Mark I.

Over the past century, the significance of the rhizosphere has been increasingly recognized by the scientific community. Furthermore, this complex biological system is comprised of vast interconnected networks of microbial organisms that interact directly with their plant hosts, including archaea, bacteria, fungi, picoeukaryotes, and viruses. The rhizosphere provides a nutritional base to the terrestrial biosphere, and is integral to plant growth, crop production, and ecosystem health. There is little mechanistic understanding of the rhizosphere, but, and that constitutes a critical knowledge gap. It inhibits our ability to predict and control the terrestrial ecosystem to achieve desirable outcomes, such as bioenergymore » production, crop yield maximization, and soil-based carbon sequestration. Multi-omics have the potential to significantly advance our knowledge of rhizospheric science. Our review covers multi-omic techniques and technologies; methods and protocols for specific rhizospheric science questions; and the challenges to be addressed during this century of rhizospheric science.« less

The state of rhizospheric science in the era of multi-omics: A practical guide to omics technologies

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

White, Richard Allen; Rivas-Ubach, Albert; Borkum, Mark I.

Over the past century, the significance of the rhizosphere as a complex, biological system, comprised of vast, interconnected networks of microbial organisms that interact directly with their plant hosts (e.g., archæa, bacteria, fungi, eukaryotes, and viruses) has been increasingly recognized by the scientific community. Providing a nutritional base to the terrestrial biosphere, the rhizosphere is integral to plant growth, crop production and ecosystem health. Lack of mechanistic understanding of the rhizosphere constitutes a critical knowledge gap, inhibiting our ability to predict and control the terrestrial ecosystem in order to achieve desirable outcomes (e.g., bioenergy production, crop yield maximization, and soilbasedmore » carbon sequestration). Application of multi-omics has the potential to significantly advance our knowledge of rhizospheric science. This review covers: cutting- and bleeding-edge, multi-omic techniques and technologies; methods and protocols for specific rhizospheric science questions; and, challenges to be addressed during this century of rhizospheric science.« less

Contribution of neurocognition to 18-month employment outcomes in first-episode psychosis.

PubMed

Karambelas, George J; Cotton, Sue M; Farhall, John; Killackey, Eóin; Allott, Kelly A

2017-10-27

To examine whether baseline neurocognition predicts vocational outcomes over 18 months in patients with first-episode psychosis enrolled in a randomized controlled trial of Individual Placement and Support or treatment as usual. One-hundred and thirty-four first-episode psychosis participants completed an extensive neurocognitive battery. Principal axis factor analysis using PROMAX rotation was used to determine the underlying structure of the battery. Setwise (hierarchical) multiple linear and logistic regressions were used to examine predictors of (1) total hours employed over 18 months and (2) employment status, respectively. Neurocognition factors were entered in the models after accounting for age, gender, premorbid IQ, negative symptoms, treatment group allocation and employment status at baseline. Five neurocognitive factors were extracted: (1) processing speed, (2) verbal learning and memory, (3) knowledge and reasoning, (4) attention and working memory and (5) visual organization and memory. Employment status over 18 months was not significantly predicted by any of the predictors in the final model. Total hours employed over 18 months were significantly predicted by gender (P = .027), negative symptoms (P = .032) and verbal learning and memory (P = .040). Every step of the regression model was a significant predictor of total hours worked overall (final model: P = .013). Verbal learning and memory, negative symptoms and gender were implicated in duration of employment in first-episode psychosis. The other neurocognitive domains did not significantly contribute to the prediction of vocational outcomes over 18 months. Interventions targeting verbal memory may improve vocational outcomes in early psychosis. © 2017 John Wiley & Sons Australia, Ltd.

Age effects on sensory-processing abilities and their impact on handwriting.

PubMed

Engel-Yeger, Batya; Hus, Sari; Rosenblum, Sara

2012-12-01

Sensory-processing abilities are known to deteriorate in the elderly. As a result, daily activities such as handwriting may be impaired. Yet, knowledge about sensory-processing involvement in handwriting characteristics among older persons is limited. To examine how age influences sensory-processing abilities and the impact on handwriting as a daily performance. The study participants were 118 healthy, independently functioning adults divided into four age groups: 31-45, 46-60, 61-75 and 76+ years. All participants completed the Adolescent/ Adult Sensory Profile (AASP). Handwriting process was documented using the Computerized Handwriting Penmanship Evaluation Tool (ComPET). Age significantly affects sensory processing and handwriting pressure as well as temporal and spatial measures. Both handwriting time and spatial organization of the written product were predicted by sensory seeking. When examining age contribution to the prediction of handwriting by sensory processing, sensory seeking showed a tendency for predicting handwriting pressure (p = .06), while sensory sensitivity significantly predicted handwriting velocity. Age appears to influence sensory-processing abilities and affect daily performance tasks, such as handwriting, for which sensitivity and seeking for sensations are essential. Awareness of clinicians to sensory-processing deficits among older adults and examining their impact on broader daily activities are essential to improve daily performance and quality of life.

Microbial Functional Gene Diversity Predicts Groundwater Contamination and Ecosystem Functioning

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

He, Zhili; Zhang, Ping; Wu, Linwei

Contamination from anthropogenic activities has significantly impacted Earth’s biosphere. However, knowledge about how environmental contamination affects the biodiversity of groundwater microbiomes and ecosystem functioning remains very limited. Here, we used a comprehensive functional gene array to analyze groundwater microbiomes from 69 wells at the Oak Ridge Field Research Center (Oak Ridge, TN), representing a wide pH range and uranium, nitrate, and other contaminants. We hypothesized that the functional diversity of groundwater microbiomes would decrease as environmental contamination (e.g., uranium or nitrate) increased or at low or high pH, while some specific populations capable of utilizing or resistant to those contaminantsmore » would increase, and thus, such key microbial functional genes and/or populations could be used to predict groundwater contamination and ecosystem functioning. Our results indicated that functional richness/diversity decreased as uranium (but not nitrate) increased in groundwater. In addition, about 5.9% of specific key functional populations targeted by a comprehensive functional gene array (GeoChip 5) increased significantly (P < 0.05) as uranium or nitrate increased, and their changes could be used to successfully predict uranium and nitrate contamination and ecosystem functioning. Here, this study indicates great potential for using microbial functional genes to predict environmental contamination and ecosystem functioning.« less

Microbial Functional Gene Diversity Predicts Groundwater Contamination and Ecosystem Functioning

PubMed Central

Zhang, Ping; Wu, Linwei; Rocha, Andrea M.; Shi, Zhou; Wu, Bo; Qin, Yujia; Wang, Jianjun; Yan, Qingyun; Curtis, Daniel; Ning, Daliang; Van Nostrand, Joy D.; Wu, Liyou; Watson, David B.; Adams, Michael W. W.; Alm, Eric J.; Adams, Paul D.; Arkin, Adam P.

2018-01-01

ABSTRACT Contamination from anthropogenic activities has significantly impacted Earth’s biosphere. However, knowledge about how environmental contamination affects the biodiversity of groundwater microbiomes and ecosystem functioning remains very limited. Here, we used a comprehensive functional gene array to analyze groundwater microbiomes from 69 wells at the Oak Ridge Field Research Center (Oak Ridge, TN), representing a wide pH range and uranium, nitrate, and other contaminants. We hypothesized that the functional diversity of groundwater microbiomes would decrease as environmental contamination (e.g., uranium or nitrate) increased or at low or high pH, while some specific populations capable of utilizing or resistant to those contaminants would increase, and thus, such key microbial functional genes and/or populations could be used to predict groundwater contamination and ecosystem functioning. Our results indicated that functional richness/diversity decreased as uranium (but not nitrate) increased in groundwater. In addition, about 5.9% of specific key functional populations targeted by a comprehensive functional gene array (GeoChip 5) increased significantly (P < 0.05) as uranium or nitrate increased, and their changes could be used to successfully predict uranium and nitrate contamination and ecosystem functioning. This study indicates great potential for using microbial functional genes to predict environmental contamination and ecosystem functioning. PMID:29463661

Microbial Functional Gene Diversity Predicts Groundwater Contamination and Ecosystem Functioning

DOE PAGES

He, Zhili; Zhang, Ping; Wu, Linwei; ...

2018-02-20

Contamination from anthropogenic activities has significantly impacted Earth’s biosphere. However, knowledge about how environmental contamination affects the biodiversity of groundwater microbiomes and ecosystem functioning remains very limited. Here, we used a comprehensive functional gene array to analyze groundwater microbiomes from 69 wells at the Oak Ridge Field Research Center (Oak Ridge, TN), representing a wide pH range and uranium, nitrate, and other contaminants. We hypothesized that the functional diversity of groundwater microbiomes would decrease as environmental contamination (e.g., uranium or nitrate) increased or at low or high pH, while some specific populations capable of utilizing or resistant to those contaminantsmore » would increase, and thus, such key microbial functional genes and/or populations could be used to predict groundwater contamination and ecosystem functioning. Our results indicated that functional richness/diversity decreased as uranium (but not nitrate) increased in groundwater. In addition, about 5.9% of specific key functional populations targeted by a comprehensive functional gene array (GeoChip 5) increased significantly (P < 0.05) as uranium or nitrate increased, and their changes could be used to successfully predict uranium and nitrate contamination and ecosystem functioning. Here, this study indicates great potential for using microbial functional genes to predict environmental contamination and ecosystem functioning.« less

Intermittent use of sulphadoxine-pyrimethamine for malaria prevention: a cross-sectional study of knowledge and practices among Ugandan women attending an urban antenatal clinic.

PubMed

Odongo, Charles O; Bisaso, Ronald K; Byamugisha, Josaphat; Obua, Celestino

2014-10-11

The WHO recommends supervised administration of sulphadoxine-pyrimethamine (SP) as intermittent preventive treatment for malaria (IPTp) during pregnancy. Logistical constraints have however favoured unsupervised intake of SP-IPTp, casting doubts whether recent guidelines requiring more frequent intake can be effectively implemented. To propose strategies for enhancing compliance under limited supervision, this study sought to identify pregnant women's knowledge and practices gaps as well as determine predictors of compliance with SP-IPTp, given under limited supervision. A cross-sectional study of 700 women used exit interviews at an urban clinic in Uganda to obtain a descriptive summary of demographic and obstetric characteristics, including knowledge, practice and experiences with SP. Predictors of compliance with SP intake instructions were explored using logistic regression. Median age of respondents was 25 (IQR 22-28) and median parity was two (IQR one to three) while median number of antenatal clinic (ANC) visits was 3.0 (IQR three to four). Most women had completed primary (36%) or ordinary secondary education (25.6%) while 16.1% had not completed primary education. Awareness about SP was high (99.4%) although correct knowledge regarding its use in pregnancy was low (57%), with 15.4% thinking it was used to treat malaria and 26.7% lacking any idea about its use. Correct knowledge on SP use during pregnancy significantly predicted compliance with SP-IPTp instructions (OR 1.98, C.I. 1.12-3.55), while age, education level, parity, number of ANC visits, or history of unwanted effects with SP did not. SP was mostly accessed from hospitals (64.4%) followed by private clinics (16.9%) both for preventive and treatment purposes. SP was considered safe by most women, who were willing to take it again in future, without supervision. Despite high awareness, knowledge of SP as an intervention for malaria prevention in pregnancy was low. Correct knowledge on use of SP predicted compliance with SP-IPTp intake instructions. Focused malaria-related education during ANC visits may improve compliance with SP intake amidst limited supervision.

The relation between receptive grammar and procedural, declarative, and working memory in specific language impairment.

PubMed

Conti-Ramsden, Gina; Ullman, Michael T; Lum, Jarrad A G

2015-01-01

What memory systems underlie grammar in children, and do these differ between typically developing (TD) children and children with specific language impairment (SLI)? Whilst there is substantial evidence linking certain memory deficits to the language problems in children with SLI, few studies have investigated multiple memory systems simultaneously, examining not only possible memory deficits but also memory abilities that may play a compensatory role. This study examined the extent to which procedural, declarative, and working memory abilities predict receptive grammar in 45 primary school aged children with SLI (30 males, 15 females) and 46 TD children (30 males, 16 females), both on average 9;10 years of age. Regression analyses probed measures of all three memory systems simultaneously as potential predictors of receptive grammar. The model was significant, explaining 51.6% of the variance. There was a significant main effect of learning in procedural memory and a significant group × procedural learning interaction. Further investigation of the interaction revealed that procedural learning predicted grammar in TD but not in children with SLI. Indeed, procedural learning was the only predictor of grammar in TD. In contrast, only learning in declarative memory significantly predicted grammar in SLI. Thus, different memory systems are associated with receptive grammar abilities in children with SLI and their TD peers. This study is, to our knowledge, the first to demonstrate a significant group by memory system interaction in predicting grammar in children with SLI and their TD peers. In line with Ullman's Declarative/Procedural model of language and procedural deficit hypothesis of SLI, variability in understanding sentences of varying grammatical complexity appears to be associated with variability in procedural memory abilities in TD children, but with declarative memory, as an apparent compensatory mechanism, in children with SLI.

Correlates of parental feeding practices with pre-schoolers: Parental body image and eating knowledge, attitudes, and behaviours.

PubMed

Damiano, Stephanie R; Hart, Laura M; Paxton, Susan J

2016-06-01

Parental feeding practices have been linked to eating and weight status in young children; however, more research is needed to understand what influences these feeding practices. The aim of this study was to examine how parental feeding practices that are linked to unhealthy eating patterns in young children, are related to parental body image and eating knowledge, attitudes, and behaviours . Participants were 330 mothers of a 2- to 6-year-old child. Mothers completed measures of knowledge of child body image and eating patterns, overvaluation of weight and shape, internalization of general media and athletic ideals, dieting, and parental feeding practices. Higher maternal knowledge of strategies to promote positive child body image and eating patterns predicted lower weight restriction, instrumental, emotional, and pushing to eat feeding practices. Overvaluation of weight and shape predicted use of fat restriction. Maternal internalization of the athletic ideal predicted instrumental and pushing to eat feeding practices. As these feeding practices have been associated with long-term risk of children's weight gain and/or disordered eating, these findings highlight the need for prevention interventions to target knowledge, attitudes, and behaviours of parents of pre-schoolers. Copyright © 2016 Elsevier Ltd. All rights reserved.

Predictability of Road Traffic and Congestion in Urban Areas

PubMed Central

Wang, Jingyuan; Mao, Yu; Li, Jing; Xiong, Zhang; Wang, Wen-Xu

2015-01-01

Mitigating traffic congestion on urban roads, with paramount importance in urban development and reduction of energy consumption and air pollution, depends on our ability to foresee road usage and traffic conditions pertaining to the collective behavior of drivers, raising a significant question: to what degree is road traffic predictable in urban areas? Here we rely on the precise records of daily vehicle mobility based on GPS positioning device installed in taxis to uncover the potential daily predictability of urban traffic patterns. Using the mapping from the degree of congestion on roads into a time series of symbols and measuring its entropy, we find a relatively high daily predictability of traffic conditions despite the absence of any priori knowledge of drivers' origins and destinations and quite different travel patterns between weekdays and weekends. Moreover, we find a counterintuitive dependence of the predictability on travel speed: the road segment associated with intermediate average travel speed is most difficult to be predicted. We also explore the possibility of recovering the traffic condition of an inaccessible segment from its adjacent segments with respect to limited observability. The highly predictable traffic patterns in spite of the heterogeneity of drivers' behaviors and the variability of their origins and destinations enables development of accurate predictive models for eventually devising practical strategies to mitigate urban road congestion. PMID:25849534

An Approach for Predicting Essential Genes Using Multiple Homology Mapping and Machine Learning Algorithms.

PubMed

Hua, Hong-Li; Zhang, Fa-Zhan; Labena, Abraham Alemayehu; Dong, Chuan; Jin, Yan-Ting; Guo, Feng-Biao

Investigation of essential genes is significant to comprehend the minimal gene sets of cell and discover potential drug targets. In this study, a novel approach based on multiple homology mapping and machine learning method was introduced to predict essential genes. We focused on 25 bacteria which have characterized essential genes. The predictions yielded the highest area under receiver operating characteristic (ROC) curve (AUC) of 0.9716 through tenfold cross-validation test. Proper features were utilized to construct models to make predictions in distantly related bacteria. The accuracy of predictions was evaluated via the consistency of predictions and known essential genes of target species. The highest AUC of 0.9552 and average AUC of 0.8314 were achieved when making predictions across organisms. An independent dataset from Synechococcus elongatus , which was released recently, was obtained for further assessment of the performance of our model. The AUC score of predictions is 0.7855, which is higher than other methods. This research presents that features obtained by homology mapping uniquely can achieve quite great or even better results than those integrated features. Meanwhile, the work indicates that machine learning-based method can assign more efficient weight coefficients than using empirical formula based on biological knowledge.

Relationship of college student characteristics and inquiry-based geometrical optics instruction to knowledge of image formation with light-ray tracing

NASA Astrophysics Data System (ADS)

Isik, Hakan

This study is premised on the fact that student conceptions of optics appear to be unrelated to student characteristics of gender, age, years since high school graduation, or previous academic experiences. This study investigated the relationships between student characteristics and student performance on image formation test items and the changes in student conceptions of optics after an introductory inquiry-based physics course. Data was collected from 39 college students who were involved in an inquiry-based physics course teaching topics of geometrical optics. Student data concerning characteristics and previous experiences with optics and mathematics were collected. Assessment of student understanding of optics knowledge for pinholes, plane mirrors, refraction, and convex lenses was collected with, the Test of Image Formation with Light-Ray Tracing instrument. Total scale and subscale scores representing the optics instrument content were derived from student pretest and posttest responses. The types of knowledge, needed to answer each optics item correctly, were categorized as situational, conceptual, procedural, and strategic knowledge. These types of knowledge were associated with student correct and incorrect responses to each item to explain the existences and changes in student scientific and naive conceptions. Correlation and stepwise multiple regression analyses were conducted to identify the student characteristics and academic experiences that significantly predicted scores on the subscales of the test. The results showed that student experience with calculus was a significant predictor of student performance on the total scale as well as on the refraction subscale of the Test of Image Formation with Light-Ray Tracing. A combination of student age and previous academic experience with precalculus was a significant predictor of student performance on the pretest pinhole subscale. Student characteristic of years since high school graduation significantly predicted the gain in student scores on pinhole and plane-mirror items from the pretest to the posttest with those students who were most recent graduates from high school doing better. Multivariate and univariate analyses of variance of the Test of Image Formation with Light-Ray Tracing pinhole scale and individual item changes from the pretest to the posttest resulted in statistically significant mean differences between total scores as well as between various individual pinhole items. There were no significant changes for individual plane-mirror items from pretest to posttest. Results revealed that there is a perceivable relationship between student optics-content knowledge and the types of knowledge required by items. At the pretest, the greatest selection of wrong responses related to the items requiring situational type of knowledge and the fewest selection of wrong responses was relate to the items requiring procedural type of knowledge. Student selection of wrong options for each item revealed the following naive optics conceptions: pinholes do not create reversed images (pretest), size and sharpness of pinhole images are related to the focus of a pinhole camera (pretest and posttest); propagation of light rays are interpreted as being radial rather than directional (pretest and posttest); no conception of image formation and observation for parallel mirrors (pretest and posttest), the place of an image depends on the position of the observer (pretest and posttest), a plane mirror reflects the images of the objects placed at one side of the mirror and the observers who were positioned at the other side of the mirror can see them (pretest and posttest); applying the law of reflection to plane mirrors without considering the variations in angles of incidence and reflection (pretest and posttest), and image observation is confused with the image formation in mirrors placed perpendicular to one another (pretest and posttest). Future research should focus on the acquisition, development, and identification of reliable measures of optics concepts, processes, types of knowledge, and specific optics understanding (i.e., pinhole, plane-mirror). Future research should focus on the identification of the more critical concepts such as changes in size and sharpness of pinhole images, image observation, image formation in general, and image formation and observation in parallel mirrors. Future research can be conducted with a larger set of participants so as to compare different instructional methods and address instructional deficiencies using more efficient statistical methods. Comparative studies can be conducted to investigate the relations of various instructional strategies on student conceptions of optics.

Detection of chaos: New approach to atmospheric pollen time-series analysis

NASA Astrophysics Data System (ADS)

Bianchi, M. M.; Arizmendi, C. M.; Sanchez, J. R.

1992-09-01

Pollen and spores are biological particles that are ubiquitous to the atmosphere and are pathologically significant, causing plant diseases and inhalant allergies. One of the main objectives of aerobiological surveys is forecasting. Prediction models are required in order to apply aerobiological knowledge to medical or agricultural practice; a necessary condition of these models is not to be chaotic. The existence of chaos is detected through the analysis of a time series. The time series comprises hourly counts of atmospheric pollen grains obtained using a Burkard spore trap from 1987 to 1989 at Mar del Plata. Abraham's method to obtain the correlation dimension was applied. A low and fractal dimension shows chaotic dynamics. The predictability of models for atomspheric pollen forecasting is discussed.

Qualitative simulation for process modeling and control

NASA Technical Reports Server (NTRS)

Dalle Molle, D. T.; Edgar, T. F.

1989-01-01

A qualitative model is developed for a first-order system with a proportional-integral controller without precise knowledge of the process or controller parameters. Simulation of the qualitative model yields all of the solutions to the system equations. In developing the qualitative model, a necessary condition for the occurrence of oscillatory behavior is identified. Initializations that cannot exhibit oscillatory behavior produce a finite set of behaviors. When the phase-space behavior of the oscillatory behavior is properly constrained, these initializations produce an infinite but comprehensible set of asymptotically stable behaviors. While the predictions include all possible behaviors of the real system, a class of spurious behaviors has been identified. When limited numerical information is included in the model, the number of predictions is significantly reduced.

Knowledge boosting: a graph-based integration approach with multi-omics data and genomic knowledge for cancer clinical outcome prediction

PubMed Central

Kim, Dokyoon; Joung, Je-Gun; Sohn, Kyung-Ah; Shin, Hyunjung; Park, Yu Rang; Ritchie, Marylyn D; Kim, Ju Han

2015-01-01

Objective Cancer can involve gene dysregulation via multiple mechanisms, so no single level of genomic data fully elucidates tumor behavior due to the presence of numerous genomic variations within or between levels in a biological system. We have previously proposed a graph-based integration approach that combines multi-omics data including copy number alteration, methylation, miRNA, and gene expression data for predicting clinical outcome in cancer. However, genomic features likely interact with other genomic features in complex signaling or regulatory networks, since cancer is caused by alterations in pathways or complete processes. Methods Here we propose a new graph-based framework for integrating multi-omics data and genomic knowledge to improve power in predicting clinical outcomes and elucidate interplay between different levels. To highlight the validity of our proposed framework, we used an ovarian cancer dataset from The Cancer Genome Atlas for predicting stage, grade, and survival outcomes. Results Integrating multi-omics data with genomic knowledge to construct pre-defined features resulted in higher performance in clinical outcome prediction and higher stability. For the grade outcome, the model with gene expression data produced an area under the receiver operating characteristic curve (AUC) of 0.7866. However, models of the integration with pathway, Gene Ontology, chromosomal gene set, and motif gene set consistently outperformed the model with genomic data only, attaining AUCs of 0.7873, 0.8433, 0.8254, and 0.8179, respectively. Conclusions Integrating multi-omics data and genomic knowledge to improve understanding of molecular pathogenesis and underlying biology in cancer should improve diagnostic and prognostic indicators and the effectiveness of therapies. PMID:25002459

Knowledge boosting: a graph-based integration approach with multi-omics data and genomic knowledge for cancer clinical outcome prediction.

PubMed

Kim, Dokyoon; Joung, Je-Gun; Sohn, Kyung-Ah; Shin, Hyunjung; Park, Yu Rang; Ritchie, Marylyn D; Kim, Ju Han

2015-01-01

Cancer can involve gene dysregulation via multiple mechanisms, so no single level of genomic data fully elucidates tumor behavior due to the presence of numerous genomic variations within or between levels in a biological system. We have previously proposed a graph-based integration approach that combines multi-omics data including copy number alteration, methylation, miRNA, and gene expression data for predicting clinical outcome in cancer. However, genomic features likely interact with other genomic features in complex signaling or regulatory networks, since cancer is caused by alterations in pathways or complete processes. Here we propose a new graph-based framework for integrating multi-omics data and genomic knowledge to improve power in predicting clinical outcomes and elucidate interplay between different levels. To highlight the validity of our proposed framework, we used an ovarian cancer dataset from The Cancer Genome Atlas for predicting stage, grade, and survival outcomes. Integrating multi-omics data with genomic knowledge to construct pre-defined features resulted in higher performance in clinical outcome prediction and higher stability. For the grade outcome, the model with gene expression data produced an area under the receiver operating characteristic curve (AUC) of 0.7866. However, models of the integration with pathway, Gene Ontology, chromosomal gene set, and motif gene set consistently outperformed the model with genomic data only, attaining AUCs of 0.7873, 0.8433, 0.8254, and 0.8179, respectively. Integrating multi-omics data and genomic knowledge to improve understanding of molecular pathogenesis and underlying biology in cancer should improve diagnostic and prognostic indicators and the effectiveness of therapies. © The Author 2014. Published by Oxford University Press on behalf of the American Medical Informatics Association.

Comprehensible knowledge model creation for cancer treatment decision making.

PubMed

Afzal, Muhammad; Hussain, Maqbool; Ali Khan, Wajahat; Ali, Taqdir; Lee, Sungyoung; Huh, Eui-Nam; Farooq Ahmad, Hafiz; Jamshed, Arif; Iqbal, Hassan; Irfan, Muhammad; Abbas Hydari, Manzar

2017-03-01

A wealth of clinical data exists in clinical documents in the form of electronic health records (EHRs). This data can be used for developing knowledge-based recommendation systems that can assist clinicians in clinical decision making and education. One of the big hurdles in developing such systems is the lack of automated mechanisms for knowledge acquisition to enable and educate clinicians in informed decision making. An automated knowledge acquisition methodology with a comprehensible knowledge model for cancer treatment (CKM-CT) is proposed. With the CKM-CT, clinical data are acquired automatically from documents. Quality of data is ensured by correcting errors and transforming various formats into a standard data format. Data preprocessing involves dimensionality reduction and missing value imputation. Predictive algorithm selection is performed on the basis of the ranking score of the weighted sum model. The knowledge builder prepares knowledge for knowledge-based services: clinical decisions and education support. Data is acquired from 13,788 head and neck cancer (HNC) documents for 3447 patients, including 1526 patients of the oral cavity site. In the data quality task, 160 staging values are corrected. In the preprocessing task, 20 attributes and 106 records are eliminated from the dataset. The Classification and Regression Trees (CRT) algorithm is selected and provides 69.0% classification accuracy in predicting HNC treatment plans, consisting of 11 decision paths that yield 11 decision rules. Our proposed methodology, CKM-CT, is helpful to find hidden knowledge in clinical documents. In CKM-CT, the prediction models are developed to assist and educate clinicians for informed decision making. The proposed methodology is generalizable to apply to data of other domains such as breast cancer with a similar objective to assist clinicians in decision making and education. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

PubMed

Lee, Ming; Vermillion, Michelle

2018-02-01

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

Preexposure to Objects That Contrast in Familiarity Improves Young Children's Lexical Knowledge Judgment

ERIC Educational Resources Information Center

Hartin, Travis L.; Stevenson, Colleen M.; Merriman, William E.

2016-01-01

The ability to judge the limits of one's own knowledge may play an important role in knowledge acquisition. The current study tested the prediction that preschoolers would judge the limits of their lexical knowledge more accurately if they were first exposed to a few objects of contrasting familiarity. Such preexposure was hypothesized to increase…

Prevalence of metabolic syndrome and associated risk factors in Asian Indians.

PubMed

Balasubramanyam, Ajay; Rao, Shaun; Misra, Ranjita; Sekhar, Rajagopal V; Ballantyne, Christie M

2008-08-01

This study examined the association between metabolic syndrome, lifestyle behaviors, and perception and knowledge of current health and cardiovascular disease (CVD) among Asian Indians in the US. The sample comprised of 143 adult Asian Indians recruited through health fairs for survey and bioclinical measures. The prevalence of metabolic syndrome was 32%, much higher than other ethnic groups, did not vary by gender but increased with age. Respondents had high physical inactivity and poor knowledge of CVD risk factors. Dietary behavior, age, number of years lived in the US, self-rated physical and mental health and BMI were significant predictors and explained 40.1% of variance in metabolic syndrome score. Poorer physical health status had the greatest predictive influence on metabolic syndrome. Asian Indians are a high risk group for CVD.

Modern Advances in Genetic Testing: Ethical Challenges and Training Implications for Current and Future Psychologists

PubMed Central

Richmond-Rakerd, Leah S.

2014-01-01

The ethical implications for psychological practice of genetic testing are largely unexplored. Predictive testing can have a significant impact on health and well-being, and increasing numbers of individuals with knowledge of their risk for various disorders are likely to present for psychotherapy. In addition, more people will struggle with the decision of whether to obtain information regarding their genetic material. Psychologists will need to have the appropriate knowledge and clinical skills to effectively counsel this population. This article highlights the relevant ethical issues surrounding psychological treatment of individuals pursuing or considering undergoing genetic testing. These issues are extended to psychologists working in research, education, and policy domains. Recommendations for graduate training programs to facilitate current and future practitioner competence are also discussed. PMID:24707160

Predicting Reading and Spelling Disorders: A 4-Year Prospective Cohort Study.

PubMed

Bigozzi, Lucia; Tarchi, Christian; Caudek, Corrado; Pinto, Giuliana

2016-01-01

In this 4-year prospective cohort study, children with a reading and spelling disorder, children with a spelling impairment, and children without a reading and/or spelling disorder (control group) in a transparent orthography were identified in third grade, and their emergent literacy performances in kindergarten compared retrospectively. Six hundred and forty-two Italian children participated. This cohort was followed from the last year of kindergarten to third grade. In kindergarten, the children were assessed in phonological awareness, conceptual knowledge of writing systems and textual competence. In third grade, 18 children with a reading and spelling impairment and 13 children with a spelling impairment were identified. Overall, conceptual knowledge of the writing system was the only statistically significant predictor of the clinical samples. No differences were found between the two clinical samples.

Towards Cooperative Predictive Data Mining in Competitive Environments

NASA Astrophysics Data System (ADS)

Lisý, Viliam; Jakob, Michal; Benda, Petr; Urban, Štěpán; Pěchouček, Michal

We study the problem of predictive data mining in a competitive multi-agent setting, in which each agent is assumed to have some partial knowledge required for correctly classifying a set of unlabelled examples. The agents are self-interested and therefore need to reason about the trade-offs between increasing their classification accuracy by collaborating with other agents and disclosing their private classification knowledge to other agents through such collaboration. We analyze the problem and propose a set of components which can enable cooperation in this otherwise competitive task. These components include measures for quantifying private knowledge disclosure, data-mining models suitable for multi-agent predictive data mining, and a set of strategies by which agents can improve their classification accuracy through collaboration. The overall framework and its individual components are validated on a synthetic experimental domain.

Estimation of the Ideal Lumbar Lordosis to Be Restored From Spinal Fusion Surgery: A Predictive Formula for Chinese Population.

PubMed

Xu, Leilei; Qin, Xiaodong; Zhang, Wen; Qiao, Jun; Liu, Zhen; Zhu, Zezhang; Qiu, Yong; Qian, Bang-ping

2015-07-01

A prospective, cross-sectional study. To determine the independent variables associated with lumbar lordosis (LL) and to establish the predictive formula of ideal LL in Chinese population. Several formulas have been established in Caucasians to estimate the ideal LL to be restored for lumbar fusion surgery. However, there is still a lack of knowledge concerning the establishment of such predictive formula in Chinese population. A total of 296 asymptomatic Chinese adults were prospectively recruited. The relationships between LL and variables including pelvic incidence (PI), age, sex, and body mass index were investigated to determine the independent factors that could be used to establish the predictive formula. For the validation of the current formula, other 4 reported predictive formulas were included. The absolute value of the gap between the actual LL and the ideal LL yielded by these formulas was calculated and then compared between the 4 reported formulas and the current one to determine its reliability in predicting the ideal LL. The logistic regression analysis showed that there were significant associations of LL with PI and age (R = 0.508, P < 0.001 for PI; R = 0.088, P = 0.03 for age). The formula was, therefore, established as follows: LL = 0.508 × PI - 0.088 × Age + 28.6. When applying our formula to these subjects, the gap between the predicted ideal LL and the actual LL was averaged 3.9 ± 2.1°, which was significantly lower than that of the other 4 formulas. The calculation formula derived in this study can provide a more accurate prediction of the LL for the Chinese population, which could be used as a tool for decision making to restore the LL in lumbar corrective surgery. 3.

SuperPhy: predictive genomics for the bacterial pathogen Escherichia coli.

PubMed

Whiteside, Matthew D; Laing, Chad R; Manji, Akiff; Kruczkiewicz, Peter; Taboada, Eduardo N; Gannon, Victor P J

2016-04-12

Predictive genomics is the translation of raw genome sequence data into a phenotypic assessment of the organism. For bacterial pathogens, these phenotypes can range from environmental survivability, to the severity of human disease. Significant progress has been made in the development of generic tools for genomic analyses that are broadly applicable to all microorganisms; however, a fundamental missing component is the ability to analyze genomic data in the context of organism-specific phenotypic knowledge, which has been accumulated from decades of research and can provide a meaningful interpretation of genome sequence data. In this study, we present SuperPhy, an online predictive genomics platform ( http://lfz.corefacility.ca/superphy/ ) for Escherichia coli. The platform integrates the analytical tools and genome sequence data for all publicly available E. coli genomes and facilitates the upload of new genome sequences from users under public or private settings. SuperPhy provides real-time analyses of thousands of genome sequences with results that are understandable and useful to a wide community, including those in the fields of clinical medicine, epidemiology, ecology, and evolution. SuperPhy includes identification of: 1) virulence and antimicrobial resistance determinants 2) statistical associations between genotypes, biomarkers, geospatial distribution, host, source, and phylogenetic clade; 3) the identification of biomarkers for groups of genomes on the based presence/absence of specific genomic regions and single-nucleotide polymorphisms and 4) in silico Shiga-toxin subtype. SuperPhy is a predictive genomics platform that attempts to provide an essential link between the vast amounts of genome information currently being generated and phenotypic knowledge in an organism-specific context.

Influencers and preference predictors of HPV vaccine uptake among US male and female young adult college students.

PubMed

LaJoie, A Scott; Kerr, Jelani C; Clover, Richard D; Harper, Diane M

2018-06-01

The purpose of the study was to assess the knowledge, attitudes and beliefs of male and female college students in Kentucky about HPV associated diseases and vaccines, and to determine which parameters predicted self-reported uptake of HPV vaccination. A self-selected cross-sectional sample of college students completed an evidence-based online survey. Of approximately 1200 potential respondents, 585 completed the survey. The average age was 20.6 (SD 3.15) and 78% were female; 84% of the population had had one or more sexual partners. Concern for HPV vaccine safety and potential need for boosters did not significantly deter vaccine uptake. Likewise, knowledge about HPV associated cancers was not predictive of vaccine uptake. On the other hand, parental influence for vaccination was a strong predictor for vaccine uptake (aOR = 5.32, 2.71-13.03), and free vaccine nearly doubled the likelihood of being vaccinated (aOR 1.90, 1.05-3.41). In addition, the strong preference for the respondent's partner to be HPV vaccinated predicted vaccine uptake (aOR = 4.04, 95% CI: 2.31-7.05), but the lack of preference for partner vaccination predicted an unvaccinated self (aOR = 0.50, 0.27-0.93). HPV vaccination has been successful in young adult college students in Kentucky. Young adults prefer their partners to be HPV vaccinated regardless of whether they themselves are vaccinated. Parental influence and free vaccine were positive predictors for vaccine uptake in this population. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Knowledge of Alzheimer's disease, feelings of shame, and awareness of services among Korean American elders.

PubMed

Yuri Jang; Kim, Giyeon; Chiriboga, David

2010-06-01

To explore predictors of knowledge of Alzheimer's disease (AD), feelings of shame if a family member were to have AD, and awareness of AD-related services among Korean American elders. Using data from 675 Korean American elders (mean age = 70.2, SD = 6.87), the study estimates hierarchical linear or logistic regression models. Greater knowledge of AD is predicted by higher levels of education and acculturation. Feelings of shame associated with family members having AD are more likely to be reported by individuals with lower levels of education, acculturation, and knowledge of AD. Those who are married have greater levels of education and acculturation, and those who have a family member with AD are more aware of AD-related services. The study findings underscore the pivotal role of education and acculturation in predicting knowledge of AD, feelings of shame, and awareness of AD-related services.

The Jekyll and Hyde of emotional intelligence: emotion-regulation knowledge facilitates both prosocial and interpersonally deviant behavior.

PubMed

Côté, Stéphane; Decelles, Katherine A; McCarthy, Julie M; Van Kleef, Gerben A; Hideg, Ivona

2011-08-01

Does emotional intelligence promote behavior that strictly benefits the greater good, or can it also advance interpersonal deviance? In the investigation reported here, we tested the possibility that a core facet of emotional intelligence--emotion-regulation knowledge--can promote both prosocial and interpersonally deviant behavior. Drawing from research on how the effective regulation of emotion promotes goal achievement, we predicted that emotion-regulation knowledge would strengthen the effects of other-oriented and self-oriented personality traits on prosocial behavior and interpersonal deviance, respectively. Two studies supported our predictions. Among individuals with higher emotion-regulation knowledge, moral identity exhibited a stronger positive association with prosocial behavior in a social dilemma (Study 1), and Machiavellianism exhibited a stronger positive association with interpersonal deviance in the workplace (Study 2). Thus, emotion-regulation knowledge has a positive side and a dark side.

Leveraging 35 years of Pinus taeda research in the southeastern US to constrain forest carbon cycle predictions: regional data assimilation using ecosystem experiments

Treesearch

R. Quinn Thomas; Evan B. Brooks; Annika L. Jersild; Eric J. Ward; Randolph H. Wynne; Timothy J. Albaugh; Heather Dinon-Aldridge; Harold E. Burkhart; Jean-Christophe Domec; Timothy R. Fox; Carlos A. Gonzalez-Benecke; Timothy A. Martin; Asko Noormets; David A. Sampson; Robert O. Teskey

2017-01-01

Predicting how forest carbon cycling will change in response to climate change and management depends on the collective knowledge from measurements across environmental gradients, ecosystem manipulations of global change factors, and mathematical models. Formally integrating these sources of knowledge through data assimilation, or model–data fusion, allows the use of...

Knowledge-guided fuzzy logic modeling to infer cellular signaling networks from proteomic data

PubMed Central

Liu, Hui; Zhang, Fan; Mishra, Shital Kumar; Zhou, Shuigeng; Zheng, Jie

2016-01-01

Modeling of signaling pathways is crucial for understanding and predicting cellular responses to drug treatments. However, canonical signaling pathways curated from literature are seldom context-specific and thus can hardly predict cell type-specific response to external perturbations; purely data-driven methods also have drawbacks such as limited biological interpretability. Therefore, hybrid methods that can integrate prior knowledge and real data for network inference are highly desirable. In this paper, we propose a knowledge-guided fuzzy logic network model to infer signaling pathways by exploiting both prior knowledge and time-series data. In particular, the dynamic time warping algorithm is employed to measure the goodness of fit between experimental and predicted data, so that our method can model temporally-ordered experimental observations. We evaluated the proposed method on a synthetic dataset and two real phosphoproteomic datasets. The experimental results demonstrate that our model can uncover drug-induced alterations in signaling pathways in cancer cells. Compared with existing hybrid models, our method can model feedback loops so that the dynamical mechanisms of signaling networks can be uncovered from time-series data. By calibrating generic models of signaling pathways against real data, our method supports precise predictions of context-specific anticancer drug effects, which is an important step towards precision medicine. PMID:27774993

Adolescents’ Functional Numeracy Is Predicted by Their School Entry Number System Knowledge

PubMed Central

Geary, David C.; Hoard, Mary K.; Nugent, Lara; Bailey, Drew H.

2013-01-01

One in five adults in the United States is functionally innumerate; they do not possess the mathematical competencies needed for many modern jobs. We administered functional numeracy measures used in studies of young adults’ employability and wages to 180 thirteen-year-olds. The adolescents began the study in kindergarten and participated in multiple assessments of intelligence, working memory, mathematical cognition, achievement, and in-class attentive behavior. Their number system knowledge at the beginning of first grade was defined by measures that assessed knowledge of the systematic relations among Arabic numerals and skill at using this knowledge to solve arithmetic problems. Early number system knowledge predicted functional numeracy more than six years later (ß = 0.195, p = .0014) controlling for intelligence, working memory, in-class attentive behavior, mathematical achievement, demographic and other factors, but skill at using counting procedures to solve arithmetic problems did not. In all, we identified specific beginning of schooling numerical knowledge that contributes to individual differences in adolescents’ functional numeracy and demonstrated that performance on mathematical achievement tests underestimates the importance of this early knowledge. PMID:23382934

Student Use of Physics to Make Sense of Incomplete but Functional VPython Programs in a Lab Setting

NASA Astrophysics Data System (ADS)

Weatherford, Shawn A.

2011-12-01

Computational activities in Matter & Interactions, an introductory calculus-based physics course, have the instructional goal of providing students with the experience of applying the same set of a small number of fundamental principles to model a wide range of physical systems. However there are significant instructional challenges for students to build computer programs under limited time constraints, especially for students who are unfamiliar with programming languages and concepts. Prior attempts at designing effective computational activities were successful at having students ultimately build working VPython programs under the tutelage of experienced teaching assistants in a studio lab setting. A pilot study revealed that students who completed these computational activities had significant difficultly repeating the exact same tasks and further, had difficulty predicting the animation that would be produced by the example program after interpreting the program code. This study explores the interpretation and prediction tasks as part of an instructional sequence where students are asked to read and comprehend a functional, but incomplete program. Rather than asking students to begin their computational tasks with modifying program code, we explicitly ask students to interpret an existing program that is missing key lines of code. The missing lines of code correspond to the algebraic form of fundamental physics principles or the calculation of forces which would exist between analogous physical objects in the natural world. Students are then asked to draw a prediction of what they would see in the simulation produced by the VPython program and ultimately run the program to evaluate the students' prediction. This study specifically looks at how the participants use physics while interpreting the program code and creating a whiteboard prediction. This study also examines how students evaluate their understanding of the program and modification goals at the beginning of the modification task. While working in groups over the course of a semester, study participants were recorded while they completed three activities using these incomplete programs. Analysis of the video data showed that study participants had little difficulty interpreting physics quantities, generating a prediction, or determining how to modify the incomplete program. Participants did not base their prediction solely from the information from the incomplete program. When participants tried to predict the motion of the objects in the simulation, many turned to their knowledge of how the system would evolve if it represented an analogous real-world physical system. For example, participants attributed the real-world behavior of springs to helix objects even though the program did not include calculations for the spring to exert a force when stretched. Participants rarely interpreted lines of code in the computational loop during the first computational activity, but this changed during latter computational activities with most participants using their physics knowledge to interpret the computational loop. Computational activities in the Matter & Interactions curriculum were revised in light of these findings to include an instructional sequence of tasks to build a comprehension of the example program. The modified activities also ask students to create an additional whiteboard prediction for the time-evolution of the real-world phenomena which the example program will eventually model. This thesis shows how comprehension tasks identified by Palinscar and Brown (1984) as effective in improving reading comprehension are also effective in helping students apply their physics knowledge to interpret a computer program which attempts to model a real-world phenomena and identify errors in their understanding of the use, or omission, of fundamental physics principles in a computational model.

The Relationship Between Speech, Language, and Phonological Awareness in Preschool-Age Children With Developmental Disabilities.

PubMed

Barton-Hulsey, Andrea; Sevcik, Rose A; Romski, MaryAnn

2018-05-03

A number of intrinsic factors, including expressive speech skills, have been suggested to place children with developmental disabilities at risk for limited development of reading skills. This study examines the relationship between these factors, speech ability, and children's phonological awareness skills. A nonexperimental study design was used to examine the relationship between intrinsic skills of speech, language, print, and letter-sound knowledge to phonological awareness in 42 children with developmental disabilities between the ages of 48 and 69 months. Hierarchical multiple regression was done to determine if speech ability accounted for a unique amount of variance in phonological awareness skill beyond what would be expected by developmental skills inclusive of receptive language and print and letter-sound knowledge. A range of skill in all areas of direct assessment was found. Children with limited speech were found to have emerging skills in print knowledge, letter-sound knowledge, and phonological awareness. Speech ability did not predict a significant amount of variance in phonological awareness beyond what would be expected by developmental skills of receptive language and print and letter-sound knowledge. Children with limited speech ability were found to have receptive language and letter-sound knowledge that supported the development of phonological awareness skills. This study provides implications for practitioners and researchers concerning the factors related to early reading development in children with limited speech ability and developmental disabilities.

A comparison of knowledge of diabetes mellitus between patients with diabetes and healthy adults: a survey from north Malaysia.

PubMed

Yun, Lai Shin; Hassan, Yahaya; Aziz, Noorizan Abd; Awaisu, Ahmed; Ghazali, Rozina

2007-12-01

The primary objective of this study was to assess and compare the knowledge of diabetes mellitus possessed by patients with diabetes and healthy adult volunteers in Penang, Malaysia. A cross-sectional study was conducted from 20 February 2006 to 31 March 2006. We randomly selected 120 patients with diabetes mellitus from a diabetic clinic at the General Hospital Penang, Malaysia and 120 healthy adults at a shopping complex in Penang. Each participant was interviewed face-to-face by a pharmacist using a validated questionnaire, and they were required to answer a total of 30 questions concerning knowledge about diabetes mellitus using Yes, No or Unsure as the only response. The results showed that patients with diabetes mellitus were significantly more knowledgeable than the healthy volunteers about risk factors, symptoms, chronic complications, treatment and self-management, and monitoring parameters. Educational level was the best predictive factor for diabetes mellitus and public awareness. Knowledge about diabetes mellitus should be improved among the general population. This study has major implications for the design of an educational programme for diabetics and a health promotion programme as a primary prevention measure for the healthy population in general, and especially for those at high risk. The results could be useful in the design of future studies for evaluating patients' and the general public's knowledge about diabetes mellitus.

Cognitive Predictors of Verbal Memory in a Mixed Clinical Pediatric Sample

PubMed Central

Jordan, Lizabeth L.; Tyner, Callie E.; Heaton, Shelley C.

2013-01-01

Verbal memory problems, along with other cognitive difficulties, are common in children diagnosed with neurological and/or psychological disorders. Historically, these “memory problems” have been poorly characterized and often present with a heterogeneous pattern of performance across memory processes, even within a specific diagnostic group. The current study examined archival neuropsychological data from a large mixed clinical pediatric sample in order to understand whether functioning in other cognitive areas (i.e., verbal knowledge, attention, working memory, executive functioning) may explain some of the performance variability seen across verbal memory tasks of the Children’s Memory Scale (CMS). Multivariate analyses revealed that among the cognitive functions examined, only verbal knowledge explained a significant amount of variance in overall verbal memory performance. Further univariate analyses examining the component processes of verbal memory indicated that verbal knowledge is specifically related to encoding, but not the retention or retrieval stages. Future research is needed to replicate these findings in other clinical samples, to examine whether verbal knowledge predicts performance on other verbal memory tasks and to explore whether these findings also hold true for visual memory tasks. Successful replication of the current study findings would indicate that interventions targeting verbal encoding deficits should include efforts to improve verbal knowledge. PMID:25379253

How Knowledge Powers Reading

ERIC Educational Resources Information Center

Lemov, Doug

2017-01-01

Recent research shows that reading comprehension relies heavily on prior knowledge. Far more than generic "reading skills" like drawing inferences, making predictions, and knowing the function of subheads, how well students learn from a nonfiction text depends on their background knowledge of the text's subject matter. And in a cyclical…

Computer Experiences, Self-Efficacy and Knowledge of Students Enrolled in Introductory University Agriculture Courses.

ERIC Educational Resources Information Center

Johnson, Donald M.; Ferguson, James A.; Lester, Melissa L.

1999-01-01

Of 175 freshmen agriculture students, 74% had prior computer courses, 62% owned computers. The number of computer topics studied predicted both computer self-efficacy and computer knowledge. A substantial positive correlation was found between self-efficacy and computer knowledge. (SK)

Predictive value of Tokuhashi scoring systems in spinal metastases, focusing on various primary tumor groups: evaluation of 448 patients in the Aarhus spinal metastases database.

PubMed

Wang, Miao; Bünger, Cody Eric; Li, Haisheng; Wu, Chunsen; Høy, Kristian; Niedermann, Bent; Helmig, Peter; Wang, Yu; Jensen, Anders Bonde; Schättiger, Katrin; Hansen, Ebbe Stender

2012-04-01

We conducted a prospective cohort study of 448 patients with spinal metastases from a variety of cancer groups. To determine the specific predictive value of the Tokuhashi scoring system (T12) and its revised version (T15) in spinal metastases of various primary tumors. The life expectancy of patients with spinal metastases is one of the most important factors in selecting the treatment modality. Tokuhashi et al formulated a prognostic scoring system with a total sum of 12 points for preoperative prediction of life expectancy in 1990 and revised it in 2005 to a total sum of 15 points. There is a lack of knowledge about the specific predictive value of those scoring systems in patients with spinal metastases from a variety of cancer groups. We included 448 patients with vertebral metastases who underwent surgical treatment during November 1992 to November 2009 in Aarhus University Hospital NBG. Data were retrieved from Aarhus Metastases Database. Scores based on T12 and T15 were calculated prospectively for each patient. We divided all the patients into different groups dictated by the site of their primary tumor. Predictive value and accuracy rate of the 2 scoring systems were compared in each cancer group. Both the T12 and T15 scoring systems showed statistically significant predictive value when the 448 patients were analyzed in total (T12, P < 0.0001; T15, P < 0.0001). The accuracy rate was significantly higher in T15 (P < 0.0001) than in T12. The further analyses by primary cancer groups showed that the predictive value of T12 and T15 was primarily determined by the prostate (P = 0.0003) and breast group (P = 0.0385). Only T12 displayed predictive value in the colon group (P = 0.0011). Neither of the scoring systems showed significant predictive value in the lung (P > 0.05), renal (P > 0.05), or miscellaneous primary tumor groups (P > 0.05). The accuracy rate of prognosis in T15 was significantly improved in the prostate (P = 0.0032) and breast group (P < 0.0001). Both T12 and T15 showed significant predictive value in patients with spinal metastases. T15 has a statistically higher accuracy rate than T12. Among the various cancer groups, the 2 scoring systems are especially reliable in prostate and breast metastases groups. T15 is recommended as superior to T12 because of its higher accuracy rate.

Predictive Factors of Spontaneous Reporting of Adverse Drug Reactions among Community Pharmacists.

PubMed

Yu, Yun Mi; Lee, Euni; Koo, Bon Sun; Jeong, Kyeong Hye; Choi, Kyung Hee; Kang, Lee Kyung; Lee, Mo Se; Choi, Kwang Hoon; Oh, Jung Mi; Shin, Wan Gyoon

2016-01-01

To evaluate the association between spontaneous reporting (SR) and the knowledge, attitude, and needs of community pharmacists (CPs), using a questionnaire following a conceptual model known as the mixed model of knowledge-attitude-practices and the satisfaction of needs. Self-administered questionnaires were used with a nationwide convenience sample of CPs between September 1, 2014 and November 25, 2014 in Korea. The association between SR and the predictive factors was evaluated using multivariate logistic regression analysis. In total, 1,001 questionnaires were analyzed. The mean age of the respondents and the number of years spent in community pharmacy practice were 45.6 years and 15.3 years, respectively. CPs with experience of SR was 29.4%. Being older than 60 (ORadj, 0.16; 95% CI, 0.06-0.42), having prior experience with adverse drug reactions (ADR) (ORadj, 6.46; 95% CI, 2.46-16.98), having higher specific knowledge of SR (ORadj, 3.58; 95% CI, 1.96-6.56), and having less concern about the obstacles to SR (ORadj, 0.36; 95% CI, 0.23-0.57) were significant contributing factors to SR. The main obstacles to SR included perception of ADRs as 'not serious ADR' (77.9%), 'already well known ADR' (81.5%), and 'uncertain about causality' (73.3%). CPs without reporting experience had greater concerns related to the reporting method and the liability of the pharmacy than those with reporting experience (p<0.05). Findings from our study showed around one in three CPs had ADR reporting experience in Korea, while 87.1% had prior experience with ADR cases. The knowledge of SR, prior experience of ADR, and less concern about the obstacles to SR were contributing factors for reporting levels.

Predictive Factors of Spontaneous Reporting of Adverse Drug Reactions among Community Pharmacists

PubMed Central

Yu, Yun Mi; Lee, Euni; Koo, Bon Sun; Jeong, Kyeong Hye; Choi, Kyung Hee; Kang, Lee Kyung; Lee, Mo Se; Choi, Kwang Hoon; Oh, Jung Mi; Shin, Wan Gyoon

2016-01-01

Purpose To evaluate the association between spontaneous reporting (SR) and the knowledge, attitude, and needs of community pharmacists (CPs), using a questionnaire following a conceptual model known as the mixed model of knowledge-attitude-practices and the satisfaction of needs. Methods Self-administered questionnaires were used with a nationwide convenience sample of CPs between September 1, 2014 and November 25, 2014 in Korea. The association between SR and the predictive factors was evaluated using multivariate logistic regression analysis. Results In total, 1,001 questionnaires were analyzed. The mean age of the respondents and the number of years spent in community pharmacy practice were 45.6 years and 15.3 years, respectively. CPs with experience of SR was 29.4%. Being older than 60 (ORadj, 0.16; 95% CI, 0.06–0.42), having prior experience with adverse drug reactions (ADR) (ORadj, 6.46; 95% CI, 2.46–16.98), having higher specific knowledge of SR (ORadj, 3.58; 95% CI, 1.96–6.56), and having less concern about the obstacles to SR (ORadj, 0.36; 95% CI, 0.23–0.57) were significant contributing factors to SR. The main obstacles to SR included perception of ADRs as ‘not serious ADR’ (77.9%), ‘already well known ADR’ (81.5%), and ‘uncertain about causality’ (73.3%). CPs without reporting experience had greater concerns related to the reporting method and the liability of the pharmacy than those with reporting experience (p<0.05). Conclusions Findings from our study showed around one in three CPs had ADR reporting experience in Korea, while 87.1% had prior experience with ADR cases. The knowledge of SR, prior experience of ADR, and less concern about the obstacles to SR were contributing factors for reporting levels. PMID:27192159

The Neural Correlates of Hierarchical Predictions for Perceptual Decisions.

PubMed

Weilnhammer, Veith A; Stuke, Heiner; Sterzer, Philipp; Schmack, Katharina

2018-05-23

Sensory information is inherently noisy, sparse, and ambiguous. In contrast, visual experience is usually clear, detailed, and stable. Bayesian theories of perception resolve this discrepancy by assuming that prior knowledge about the causes underlying sensory stimulation actively shapes perceptual decisions. The CNS is believed to entertain a generative model aligned to dynamic changes in the hierarchical states of our volatile sensory environment. Here, we used model-based fMRI to study the neural correlates of the dynamic updating of hierarchically structured predictions in male and female human observers. We devised a crossmodal associative learning task with covertly interspersed ambiguous trials in which participants engaged in hierarchical learning based on changing contingencies between auditory cues and visual targets. By inverting a Bayesian model of perceptual inference, we estimated individual hierarchical predictions, which significantly biased perceptual decisions under ambiguity. Although "high-level" predictions about the cue-target contingency correlated with activity in supramodal regions such as orbitofrontal cortex and hippocampus, dynamic "low-level" predictions about the conditional target probabilities were associated with activity in retinotopic visual cortex. Our results suggest that our CNS updates distinct representations of hierarchical predictions that continuously affect perceptual decisions in a dynamically changing environment. SIGNIFICANCE STATEMENT Bayesian theories posit that our brain entertains a generative model to provide hierarchical predictions regarding the causes of sensory information. Here, we use behavioral modeling and fMRI to study the neural underpinnings of such hierarchical predictions. We show that "high-level" predictions about the strength of dynamic cue-target contingencies during crossmodal associative learning correlate with activity in orbitofrontal cortex and the hippocampus, whereas "low-level" conditional target probabilities were reflected in retinotopic visual cortex. Our findings empirically corroborate theorizations on the role of hierarchical predictions in visual perception and contribute substantially to a longstanding debate on the link between sensory predictions and orbitofrontal or hippocampal activity. Our work fundamentally advances the mechanistic understanding of perceptual inference in the human brain. Copyright © 2018 the authors 0270-6474/18/385008-14$15.00/0.

Temporal dynamics of the knowledge-mediated visual disambiguation process in humans: a magnetoencephalography study.

PubMed

Urakawa, Tomokazu; Ogata, Katsuya; Kimura, Takahiro; Kume, Yuko; Tobimatsu, Shozo

2015-01-01

Disambiguation of a noisy visual scene with prior knowledge is an indispensable task of the visual system. To adequately adapt to a dynamically changing visual environment full of noisy visual scenes, the implementation of knowledge-mediated disambiguation in the brain is imperative and essential for proceeding as fast as possible under the limited capacity of visual image processing. However, the temporal profile of the disambiguation process has not yet been fully elucidated in the brain. The present study attempted to determine how quickly knowledge-mediated disambiguation began to proceed along visual areas after the onset of a two-tone ambiguous image using magnetoencephalography with high temporal resolution. Using the predictive coding framework, we focused on activity reduction for the two-tone ambiguous image as an index of the implementation of disambiguation. Source analysis revealed that a significant activity reduction was observed in the lateral occipital area at approximately 120 ms after the onset of the ambiguous image, but not in preceding activity (about 115 ms) in the cuneus when participants perceptually disambiguated the ambiguous image with prior knowledge. These results suggested that knowledge-mediated disambiguation may be implemented as early as approximately 120 ms following an ambiguous visual scene, at least in the lateral occipital area, and provided an insight into the temporal profile of the disambiguation process of a noisy visual scene with prior knowledge. © 2014 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Meal frequencies in early adolescence predict meal frequencies in late adolescence and early adulthood.

PubMed

Pedersen, Trine Pagh; Holstein, Bjørn E; Flachs, Esben Meulengracht; Rasmussen, Mette

2013-05-04

Health and risk behaviours tend to be maintained from adolescence into adulthood. There is little knowledge on whether meal frequencies in adolescence are maintained into adulthood. We investigated whether breakfast, lunch and evening meal frequencies in early adolescence predicted meal frequencies in late adolescence and in early adulthood. Further, the modifying effect of gender and adolescent family structure were investigated. National representative sample of 15-year-olds in Denmark with 4 and 12 year follow-up studies with measurement of breakfast, lunch and evening meal frequencies. A total of 561 persons completed questionnaires at age 15 years (baseline 1990, n=847, response rate 84.6%), age 19 years (n=729, response rate 73.2%) and age 27 years (n=614, response rate 61.6%). Low meal frequencies at age 15 years was a significant predictor for having low meal frequencies at age 19 years (odds ratio (OR, 95% CI)) varying between 2.11, 1.33-3.34 and 7.48, 3.64-15.41). Also, low meal frequencies at age 19 years predicted low meal frequencies at age 27 years (OR varying between 2.26, 1.30-3.91 and 4.38, 2.36-8.13). Significant predictions over the full study period were seen for low breakfast frequency and low lunch frequency (OR varying between 1.78, 1.13-2.81 and 2.58, 1.31-5.07). Analyses stratified by gender showed the same patterns (OR varying between 1.88, 1.13-3.14 and 8.30, 2.85-24.16). However, the observed predictions were not statistical significant among men between age 15 and 27 years. Analyses stratified by adolescent family structure revealed different lunch predictions in strata. Having low meal frequencies in early adolescence predicted low meal frequencies in late adolescence and early adulthood. We propose that promotion of regular meals become a prioritised issue within health education.

Structured Semantic Knowledge Can Emerge Automatically from Predicting Word Sequences in Child-Directed Speech

PubMed Central

Huebner, Philip A.; Willits, Jon A.

2018-01-01

Previous research has suggested that distributional learning mechanisms may contribute to the acquisition of semantic knowledge. However, distributional learning mechanisms, statistical learning, and contemporary “deep learning” approaches have been criticized for being incapable of learning the kind of abstract and structured knowledge that many think is required for acquisition of semantic knowledge. In this paper, we show that recurrent neural networks, trained on noisy naturalistic speech to children, do in fact learn what appears to be abstract and structured knowledge. We trained two types of recurrent neural networks (Simple Recurrent Network, and Long Short-Term Memory) to predict word sequences in a 5-million-word corpus of speech directed to children ages 0–3 years old, and assessed what semantic knowledge they acquired. We found that learned internal representations are encoding various abstract grammatical and semantic features that are useful for predicting word sequences. Assessing the organization of semantic knowledge in terms of the similarity structure, we found evidence of emergent categorical and hierarchical structure in both models. We found that the Long Short-term Memory (LSTM) and SRN are both learning very similar kinds of representations, but the LSTM achieved higher levels of performance on a quantitative evaluation. We also trained a non-recurrent neural network, Skip-gram, on the same input to compare our results to the state-of-the-art in machine learning. We found that Skip-gram achieves relatively similar performance to the LSTM, but is representing words more in terms of thematic compared to taxonomic relations, and we provide reasons why this might be the case. Our findings show that a learning system that derives abstract, distributed representations for the purpose of predicting sequential dependencies in naturalistic language may provide insight into emergence of many properties of the developing semantic system. PMID:29520243

Scoring annual earthquake predictions in China

NASA Astrophysics Data System (ADS)

Zhuang, Jiancang; Jiang, Changsheng

2012-02-01

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

Predictive models of poly(ethylene-terephthalate) film degradation under multi-factor accelerated weathering exposures

PubMed Central

Ngendahimana, David K.; Fagerholm, Cara L.; Sun, Jiayang; Bruckman, Laura S.

2017-01-01

Accelerated weathering exposures were performed on poly(ethylene-terephthalate) (PET) films. Longitudinal multi-level predictive models as a function of PET grades and exposure types were developed for the change in yellowness index (YI) and haze (%). Exposures with similar change in YI were modeled using a linear fixed-effects modeling approach. Due to the complex nature of haze formation, measurement uncertainty, and the differences in the samples’ responses, the change in haze (%) depended on individual samples’ responses and a linear mixed-effects modeling approach was used. When compared to fixed-effects models, the addition of random effects in the haze formation models significantly increased the variance explained. For both modeling approaches, diagnostic plots confirmed independence and homogeneity with normally distributed residual errors. Predictive R2 values for true prediction error and predictive power of the models demonstrated that the models were not subject to over-fitting. These models enable prediction under pre-defined exposure conditions for a given exposure time (or photo-dosage in case of UV light exposure). PET degradation under cyclic exposures combining UV light and condensing humidity is caused by photolytic and hydrolytic mechanisms causing yellowing and haze formation. Quantitative knowledge of these degradation pathways enable cross-correlation of these lab-based exposures with real-world conditions for service life prediction. PMID:28498875

Association between knowledge of caries preventive practices, preventive oral health habits of parents and children and caries experience in children resident in sub-urban Nigeria.

PubMed

Folayan, Morenike O; Kolawole, Kikelomo A; Oyedele, Titus; Chukwumah, Nneka M; Chukumah, Nneka M; Onyejaka, Nneka; Agbaje, Hakeem; Oziegbe, Elizabeth O; Oshomoji, Olusegun V; Osho, Olusegun V

2014-12-16

The objectives of this study were to assess the association between children and parents' knowledge of caries preventive practices, the parents' caries preventive oral health behaviours and children's caries preventive oral health behaviour and caries experience. Three hundred and twenty four participants aged 8-12 years, 308 fathers and 318 mothers were recruited through a household survey conducted in Suburban Nigeria. A questionnaire was administered to generate information on fathers, mothers and children's knowledge of caries prevention measures and their oral health behaviour. Clinical examination was conducted on the children to determine their dmft/DMFT. Analysis was conducted to determine the predictors of the children's good oral health behaviour. The mothers' oral health behaviours were significant predictors of the children's oral health behaviours. Children who had good knowledge of caries prevention measures had significant increased odds of brushing their teeth twice daily or more. The children's caries prevalence was 13.9%, the mean dmft was 0.2 and the mean DMFT was 0.09. None of the dependent variables could predict the presence of caries in children. The study highlights the effect of maternal oral health behaviour on the oral health behaviour of children aged 8 years to 12 years in suburban Nigeria. A pilot study is needed to evaluate how enhanced maternal preventive oral health practices can improve the oral health preventive practices of children.

Promoting broad and stable improvements in low-income children's numerical knowledge through playing number board games.

PubMed

Ramani, Geetha B; Siegler, Robert S

2008-01-01

Theoretical analyses of the development of numerical representations suggest that playing linear number board games should enhance young children's numerical knowledge. Consistent with this prediction, playing such a game for roughly 1 hr increased low-income preschoolers' (mean age = 5.4 years) proficiency on 4 diverse numerical tasks: numerical magnitude comparison, number line estimation, counting, and numeral identification. The gains remained 9 weeks later. Classmates who played an identical game, except for the squares varying in color rather than number, did not improve on any measure. Also as predicted, home experience playing number board games correlated positively with numerical knowledge. Thus, playing number board games with children from low-income backgrounds may increase their numerical knowledge at the outset of school.

A framework for evaluating forest landscape model predictions using empirical data and knowledge

Treesearch

Wen J. Wang; Hong S. He; Martin A. Spetich; Stephen R. Shifley; Frank R. Thompson; William D. Dijak; Qia Wang

2014-01-01

Evaluation of forest landscape model (FLM) predictions is indispensable to establish the credibility of predictions. We present a framework that evaluates short- and long-term FLM predictions at site and landscape scales. Site-scale evaluation is conducted through comparing raster cell-level predictions with inventory plot data whereas landscape-scale evaluation is...

Prediction of residue-residue contact matrix for protein-protein interaction with Fisher score features and deep learning.

PubMed

Du, Tianchuan; Liao, Li; Wu, Cathy H; Sun, Bilin

2016-11-01

Protein-protein interactions play essential roles in many biological processes. Acquiring knowledge of the residue-residue contact information of two interacting proteins is not only helpful in annotating functions for proteins, but also critical for structure-based drug design. The prediction of the protein residue-residue contact matrix of the interfacial regions is challenging. In this work, we introduced deep learning techniques (specifically, stacked autoencoders) to build deep neural network models to tackled the residue-residue contact prediction problem. In tandem with interaction profile Hidden Markov Models, which was used first to extract Fisher score features from protein sequences, stacked autoencoders were deployed to extract and learn hidden abstract features. The deep learning model showed significant improvement over the traditional machine learning model, Support Vector Machines (SVM), with the overall accuracy increased by 15% from 65.40% to 80.82%. We showed that the stacked autoencoders could extract novel features, which can be utilized by deep neural networks and other classifiers to enhance learning, out of the Fisher score features. It is further shown that deep neural networks have significant advantages over SVM in making use of the newly extracted features. Copyright © 2016. Published by Elsevier Inc.

Early detection of emerald ash borer infestation using multisourced data: a case study in the town of Oakville, Ontario, Canada

NASA Astrophysics Data System (ADS)

Zhang, Kongwen; Hu, Baoxin; Robinson, Justin

2014-01-01

The emerald ash borer (EAB) poses a significant economic and environmental threat to ash trees in southern Ontario, Canada, and the northern states of the USA. It is critical that effective technologies are urgently developed to detect, monitor, and control the spread of EAB. This paper presents a methodology using multisourced data to predict potential infestations of EAB in the town of Oakville, Ontario, Canada. The information combined in this study includes remotely sensed data, such as high spatial resolution aerial imagery, commercial ground and airborne hyperspectral data, and Google Earth imagery, in addition to nonremotely sensed data, such as archived paper maps and documents. This wide range of data provides extensive information that can be used for early detection of EAB, yet their effective employment and use remain a significant challenge. A prediction function was developed to estimate the EAB infestation states of individual ash trees using three major attributes: leaf chlorophyll content, tree crown spatial pattern, and prior knowledge. Comparison between these predicted values and a ground-based survey demonstrated an overall accuracy of 62.5%, with 22.5% omission and 18.5% commission errors.

An Investigation of Factors Affecting the Degree of Naïve Impetus Theory Application

NASA Astrophysics Data System (ADS)

Liu, Xiufeng; MacIsaac, Dan

2005-03-01

This study investigates factors affecting the degree of novice physics students' application of the naïve impetus theory. Six hundred and fourteen first-year university engineering physics students answered the Force Concept Inventory as a pre-test for their calculus-based course. We examined the degree to which students consistently applied the naïve impetus theory across different items. We used a 2-way repeated measures ANOVA and linear regression to analyze data coded from incorrect student responses. It was found that there were statistically significant main effects for item familiarity and item requirement for explanation vs. prediction on the measured degree of impetus theory application. Student course grades had no significant effect on impetus theory application. When faced with items that were unfamiliar and predictive, students appeared to rely on non-theoretical, knowledge-in-pieces reasoning. Reasoning characteristic of naïve theories was more frequently applied when students were completing familiar problem tasks that required explanation. When considering all the above factors simultaneously, we found that the degree of naïve impetus theory application by students is attributable to variables in the following order: familiarity, prediction, and explanation.

Longitudinal Relations Among Parental Monitoring Strategies, Knowledge, and Adolescent Delinquency in a Racially Diverse At-Risk Sample.

PubMed

Bendezú, Jason J; Pinderhughes, Ellen E; Hurley, Sean M; McMahon, Robert J; Racz, Sarah J

2016-04-04

Parents raising youth in high-risk communities at times rely on active, involved monitoring strategies in order to increase both knowledge about youth activities and the likelihood that adolescents will abstain from problem behavior. Key monitoring literature suggests that some of these active monitoring strategies predict increases in adolescent problem behavior rather than protect against it. However, this literature has studied racially homogenous, low-risk samples, raising questions about generalizability. With a diverse sample of youth (N = 753; 58% male; 46% Black) and families living in high-risk neighborhoods, bidirectional longitudinal relations were examined among three aspects of monitoring (parental discussions of daily activities, parental curfew rules, and adolescent communication with parents), parental knowledge, and youth delinquency. Parental discussion of daily activities was the strongest predictor of parental knowledge, which negatively predicted delinquency. However, these aspects of monitoring did not predict later delinquency. Findings were consistent across gender and race/urbanicity. Results highlight the importance of active and involved parental monitoring strategies in contexts where they are most needed.

A ligand predication tool based on modeling and reasoning with imprecise probabilistic knowledge.

PubMed

Liu, Weiru; Yue, Anbu; Timson, David J

2010-04-01

Ligand prediction has been driven by a fundamental desire to understand more about how biomolecules recognize their ligands and by the commercial imperative to develop new drugs. Most of the current available software systems are very complex and time-consuming to use. Therefore, developing simple and efficient tools to perform initial screening of interesting compounds is an appealing idea. In this paper, we introduce our tool for very rapid screening for likely ligands (either substrates or inhibitors) based on reasoning with imprecise probabilistic knowledge elicited from past experiments. Probabilistic knowledge is input to the system via a user-friendly interface showing a base compound structure. A prediction of whether a particular compound is a substrate is queried against the acquired probabilistic knowledge base and a probability is returned as an indication of the prediction. This tool will be particularly useful in situations where a number of similar compounds have been screened experimentally, but information is not available for all possible members of that group of compounds. We use two case studies to demonstrate how to use the tool. 2009 Elsevier Ireland Ltd. All rights reserved.

Predicting Mycobacterium tuberculosis Complex Clades Using Knowledge-Based Bayesian Networks

PubMed Central

Bennett, Kristin P.

2014-01-01

We develop a novel approach for incorporating expert rules into Bayesian networks for classification of Mycobacterium tuberculosis complex (MTBC) clades. The proposed knowledge-based Bayesian network (KBBN) treats sets of expert rules as prior distributions on the classes. Unlike prior knowledge-based support vector machine approaches which require rules expressed as polyhedral sets, KBBN directly incorporates the rules without any modification. KBBN uses data to refine rule-based classifiers when the rule set is incomplete or ambiguous. We develop a predictive KBBN model for 69 MTBC clades found in the SITVIT international collection. We validate the approach using two testbeds that model knowledge of the MTBC obtained from two different experts and large DNA fingerprint databases to predict MTBC genetic clades and sublineages. These models represent strains of MTBC using high-throughput biomarkers called spacer oligonucleotide types (spoligotypes), since these are routinely gathered from MTBC isolates of tuberculosis (TB) patients. Results show that incorporating rules into problems can drastically increase classification accuracy if data alone are insufficient. The SITVIT KBBN is publicly available for use on the World Wide Web. PMID:24864238

A Quantile Regression Approach to Understanding the Relations Between Morphological Awareness, Vocabulary, and Reading Comprehension in Adult Basic Education Students

PubMed Central

Tighe, Elizabeth L.; Schatschneider, Christopher

2015-01-01

The purpose of this study was to investigate the joint and unique contributions of morphological awareness and vocabulary knowledge at five reading comprehension levels in Adult Basic Education (ABE) students. We introduce the statistical technique of multiple quantile regression, which enabled us to assess the predictive utility of morphological awareness and vocabulary knowledge at multiple points (quantiles) along the continuous distribution of reading comprehension. To demonstrate the efficacy of our multiple quantile regression analysis, we compared and contrasted our results with a traditional multiple regression analytic approach. Our results indicated that morphological awareness and vocabulary knowledge accounted for a large portion of the variance (82-95%) in reading comprehension skills across all quantiles. Morphological awareness exhibited the greatest unique predictive ability at lower levels of reading comprehension whereas vocabulary knowledge exhibited the greatest unique predictive ability at higher levels of reading comprehension. These results indicate the utility of using multiple quantile regression to assess trajectories of component skills across multiple levels of reading comprehension. The implications of our findings for ABE programs are discussed. PMID:25351773

Glacier calving, dynamics, and sea-level rise. Final report

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

Meier, M.F.; Pfeffer, W.T.; Amadei, B.

1998-08-01

The present-day calving flux from Greenland and Antarctica is poorly known, and this accounts for a significant portion of the uncertainty in the current mass balance of these ice sheets. Similarly, the lack of knowledge about the role of calving in glacier dynamics constitutes a major uncertainty in predicting the response of glaciers and ice sheets to changes in climate and thus sea level. Another fundamental problem has to do with incomplete knowledge of glacier areas and volumes, needed for analyses of sea-level change due to changing climate. The authors proposed to develop an improved ability to predict the futuremore » contributions of glaciers to sea level by combining work from four research areas: remote sensing observations of calving activity and iceberg flux, numerical modeling of glacier dynamics, theoretical analysis of the calving process, and numerical techniques for modeling flow with large deformations and fracture. These four areas have never been combined into a single research effort on this subject; in particular, calving dynamics have never before been included explicitly in a model of glacier dynamics. A crucial issue that they proposed to address was the general question of how calving dynamics and glacier flow dynamics interact.« less

Integrating machine learning and physician knowledge to improve the accuracy of breast biopsy.

PubMed

Dutra, I; Nassif, H; Page, D; Shavlik, J; Strigel, R M; Wu, Y; Elezaby, M E; Burnside, E

2011-01-01

In this work we show that combining physician rules and machine learned rules may improve the performance of a classifier that predicts whether a breast cancer is missed on percutaneous, image-guided breast core needle biopsy (subsequently referred to as "breast core biopsy"). Specifically, we show how advice in the form of logical rules, derived by a sub-specialty, i.e. fellowship trained breast radiologists (subsequently referred to as "our physicians") can guide the search in an inductive logic programming system, and improve the performance of a learned classifier. Our dataset of 890 consecutive benign breast core biopsy results along with corresponding mammographic findings contains 94 cases that were deemed non-definitive by a multidisciplinary panel of physicians, from which 15 were upgraded to malignant disease at surgery. Our goal is to predict upgrade prospectively and avoid surgery in women who do not have breast cancer. Our results, some of which trended toward significance, show evidence that inductive logic programming may produce better results for this task than traditional propositional algorithms with default parameters. Moreover, we show that adding knowledge from our physicians into the learning process may improve the performance of the learned classifier trained only on data.

Analysis of uncertainties in turbine metal temperature predictions

NASA Technical Reports Server (NTRS)

Stepka, F. S.

1980-01-01

An analysis was conducted to examine the extent to which various factors influence the accuracy of analytically predicting turbine blade metal temperatures and to determine the uncertainties in these predictions for several accuracies of the influence factors. The advanced turbofan engine gas conditions of 1700 K and 40 atmospheres were considered along with those of a highly instrumented high temperature turbine test rig and a low temperature turbine rig that simulated the engine conditions. The analysis showed that the uncertainty in analytically predicting local blade temperature was as much as 98 K, or 7.6 percent of the metal absolute temperature, with current knowledge of the influence factors. The expected reductions in uncertainties in the influence factors with additional knowledge and tests should reduce the uncertainty in predicting blade metal temperature to 28 K, or 2.1 percent of the metal absolute temperature.

Understanding of multigene test results among males undergoing germline testing for inherited prostate cancer: Implications for genetic counseling.

PubMed

Giri, Veda N; Obeid, Elias; Hegarty, Sarah E; Gross, Laura; Bealin, Lisa; Hyatt, Colette; Fang, Carolyn Y; Leader, Amy

2018-04-14

Genetic testing (GT) for prostate cancer (PCA) is rising, with limited insights regarding genetic counseling (GC) needs of males. Genetic Evaluation of Men (GEM) is a prospective multigene testing study for inherited PCA. Men undergoing GC were surveyed on knowledge of cancer risk and genetics (CRG) and understanding of personal GT results to identify GC needs. GEM participants with or high-risk for PCA were recruited. Pre-test GC was in-person, with video and handout, or via telehealth. Post-test disclosure was in-person, by phone, or via telehealth. Clinical and family history data were obtained from participant surveys and medical records. Participants completed measures of knowledge of CRG, literacy, and numeracy pre-test and post-test. Understanding of personal genetic results was assessed post-test. Factors associated with knowledge of CRG and understanding of personal genetic results were examined using multivariable linear regression or McNemar's test. Among 109 men who completed pre- and post-GT surveys, multivariable analysis revealed family history meeting hereditary cancer syndrome (HCS) criteria was significantly predictive of higher baseline knowledge (P = 0.040). Of 101 men who responded definitively regarding understanding of results, 13 incorrectly reported their result (McNemar's P < 0.001). Factors significantly associated with discordance between reported and actual results included having a variant of uncertain significance (VUS) (P < 0.001) and undergoing GC via pre-test video and post-test phone disclosure (P = 0.015). While meeting criteria for HCS was associated with higher knowledge of CRG, understanding of personal GT results was lacking among a subset of males with VUS. A more exploratory finding was lack of understanding of results among men who underwent GC utilizing video and phone. Studies optimizing GC strategies for males undergoing multigene testing for inherited PCA are warranted. © 2018 Wiley Periodicals, Inc.

Internal Medicine Residents Do Not Accurately Assess Their Medical Knowledge

ERIC Educational Resources Information Center

Jones, Roger; Panda, Mukta; Desbiens, Norman

2008-01-01

Background: Medical knowledge is essential for appropriate patient care; however, the accuracy of internal medicine (IM) residents' assessment of their medical knowledge is unknown. Methods: IM residents predicted their overall percentile performance 1 week (on average) before and after taking the in-training exam (ITE), an objective and well…

Student Metacognitive Monitoring: Predicting Test Achievement from Judgment Accuracy

ERIC Educational Resources Information Center

Valdez, Alfred

2013-01-01

Metacognitive monitoring processes have been shown to be critical determinants of human learning. Metacognitive monitoring consist of various knowledge estimates that enable learners to engage in self-regulatory processes important for both the acquisition of knowledge and the monitoring of one's knowledge when engaged in assessment. This study…

Early Predictors of High School Mathematics Achievement

ERIC Educational Resources Information Center

Siegler, Robert S.; Duncan, Greg J.; Davis-Kean, Pamela E.; Duckworth, Kathryn; Claessens, Amy; Engel, Mimi; Susperreguy, Maria Ines; Meichu, Chen

2012-01-01

Identifying the types of mathematics content knowledge that are most predictive of students' long-term learning is essential for improving both theories of mathematical development and mathematics education. To identify these types of knowledge, we examined long-term predictors of high school students' knowledge of algebra and overall mathematics…

Children's Prosociality and Metacognitive Knowledge of Effective Helping.

ERIC Educational Resources Information Center

Nakazawa, Jun

Two studies examined the relationship between metacognitive knowledge and performance among Japanese children. It was predicted that highly prosocial children would have more appropriate knowledge of helping than would children who were low in prosocial behavior. The first study involved 109 third graders and 129 fifth graders and examined the…

Knowledge Strategies for Enhancing School Learning Capacity

ERIC Educational Resources Information Center

Cheng, Eric

2012-01-01

Purpose: The purpose of this paper is to identify the knowledge strategies applied in aided secondary schools in Hong Kong and to explore the predictive relationship between knowledge strategies and school learning capacity. Design/methodology/approach: A cross-sectional quantitative survey was designed to collect data from 427 teachers at 15…

Change in Age-Specific, Psychosocial Correlates of Risky Sexual Behaviors Among Youth: Longitudinal Findings From a Deep South, High-Risk Sample

PubMed Central

Howell, Rebecca J.; Traylor, Amy C.; Church, Wesley T.; Bolland, John M.

2015-01-01

The current study examined psychosocial predictors of change in intercourse frequency and number of sexual partners among youth within a socio-ecological framework and assessed whether these determinants vary by stage of adolescent development. Longitudinal data were derived from a large, community study of adolescent risky behavior among predominantly high-risk, African American youth. Significant predictors of intercourse frequency for early adolescents included age, gender, self-worth, and familial factors; for older youth, age, gender, self-worth, curfews, and sense of community exerted significant effects. Among early adolescents, age, gender, self-worth, familial factors, and sense of community predicted change in the number of sexual partners in the previous year, while age, gender, self-worth, parental knowledge, curfews, and sense of community were predictive of change in the number of sexual partners in the previous year among older youth. Study implications and future directions are discussed. PMID:26388682

Alzheimer's Therapeutics: Translation of Preclinical Science to Clinical Drug Development

PubMed Central

Savonenko, Alena V; Melnikova, Tatiana; Hiatt, Andrew; Li, Tong; Worley, Paul F; Troncoso, Juan C; Wong, Phil C; Price, Don L

2012-01-01

Over the past three decades, significant progress has been made in understanding the neurobiology of Alzheimer's disease. In recent years, the first attempts to implement novel mechanism-based treatments brought rather disappointing results, with low, if any, drug efficacy and significant side effects. A discrepancy between our expectations based on preclinical models and the results of clinical trials calls for a revision of our theoretical views and questions every stage of translation—from how we model the disease to how we run clinical trials. In the following sections, we will use some specific examples of the therapeutics from acetylcholinesterase inhibitors to recent anti-Aβ immunization and γ-secretase inhibition to discuss whether preclinical studies could predict the limitations in efficacy and side effects that we were so disappointed to observe in recent clinical trials. We discuss ways to improve both the predictive validity of mouse models and the translation of knowledge between preclinical and clinical stages of drug development. PMID:21937983

Distinctions between manipulation and function knowledge of objects: evidence from functional magnetic resonance imaging.

PubMed

Boronat, Consuelo B; Buxbaum, Laurel J; Coslett, H Branch; Tang, Kathy; Saffran, Eleanor M; Kimberg, Daniel Y; Detre, John A

2005-05-01

A prominent account of conceptual knowledge proposes that information is distributed over visual, tactile, auditory, motor and verbal-declarative attribute domains to the degree to which these features were activated when the knowledge was acquired [D.A. Allport, Distributed memory, modular subsystems and dysphagia, In: S.K. Newman, R. Epstein (Eds.), Current perspectives in dysphagia, Churchill Livingstone, Edinburgh, 1985, pp. 32-60]. A corollary is that when drawing upon this knowledge (e.g., to answer questions), particular aspects of this distributed information is re-activated as a function of the requirements of the task at hand [L.J. Buxbaum, E.M. Saffran, Knowledge of object manipulation and object function: dissociations in apraxic and non-apraxic subjects. Brain and Language, 82 (2002) 179-199; L.J. Buxbaum, T. Veramonti, M.F. Schwartz, Function and manipulation tool knowledge in apraxia: knowing 'what for' but not 'how', Neurocase, 6 (2000) 83-97; W. Simmons, L. Barsalou, The similarity-in-topography principle: Reconciling theories of conceptual deficits, Cognitive Neuropsychology, 20 (2003) 451-486]. This account predicts that answering questions about object manipulation should activate brain regions previously identified as components of the distributed sensory-motor system involved in object use, whereas answering questions about object function (that is, the purpose that it serves) should activate regions identified as components of the systems supporting verbal-declarative features. These predictions were tested in a functional magnetic resonance imaging (fMRI) study in which 15 participants viewed picture or word pairs denoting manipulable objects and determined whether the objects are manipulated similarly (M condition) or serve the same function (F condition). Significantly greater and more extensive activations in the left inferior parietal lobe bordering the intraparietal sulcus were seen in the M condition with pictures and, to a lesser degree, words. These findings are consistent with the known role of this region in skilled object use [K.M. Heilman, L.J. Gonzalez Rothi, Apraxia, In: K.M. Heilman, E. Valenstein (Eds.), Clinical Neuropsychology, Oxford University Press, New York, 1993, pp. 141-150] as well as previous fMRI results [M. Kellenbach, M. Brett, K. Patterson, Actions speak louder than functions: the importance of manipulability and action in tool representation, Journal of Cognitive Neuroscience, 15 (2003) 30-46] and behavioral findings in brain-lesion patients [L.J. Buxbaum, E.M. Saffran, Knowledge of object manipulation and object function: dissociations in apraxic and non-apraxic subjects, Brain and Language, 82 (2002) 179-199]. No brain regions were significantly more activated in the F than M condition. These data suggest that brain regions specialized for sensory-motor function are a critical component of distributed representations of manipulable objects.

Stress hormones at rest and following exercise testing predict coronary artery disease severity and outcome.

PubMed

Popovic, Dejana; Damjanovic, Svetozar; Djordjevic, Tea; Martic, Dejana; Ignjatovic, Svetlana; Milinkovic, Neda; Banovic, Marko; Lasica, Ratko; Petrovic, Milan; Guazzi, Marco; Arena, Ross

2017-09-01

Despite considerable knowledge regarding the importance of stress in coronary artery disease (CAD) pathogenesis, its underestimation persists in routine clinical practice, in part attributable to lack of a standardized, objective assessment. The current study examined the ability of stress hormones to predict CAD severity and prognosis at basal conditions as well as during and following an exertional stimulus. Forty Caucasian subjects with significant coronary artery lesions (≥50%) were included. Within 2 months of coronary angiography, cardiopulmonary exercise testing (CPET) on a recumbent ergometer was performed in conjunction with stress echocardiography (SE). At rest, peak and after 3 min of recovery following CPET, plasma levels of cortisol, adrenocorticotropic hormone (ACTH) and NT-pro-brain natriuretic peptide (NT-pro-BNP) were measured by immunoassay sandwich technique, radioimmunoassay, and radioimmunometric technique, respectively. Subjects were subsequently followed a mean of 32 ± 10 months. Mean ejection fraction was 56.7 ± 9.6%. Subjects with 1-2 stenotic coronary arteries (SCA) demonstrated a significantly lower plasma cortisol levels during CPET compared to those with 3-SCA (p < .05), whereas ACTH and NT-pro-BNP were not significantly different (p > .05). Among CPET, SE, and hormonal parameters, cortisol at rest and during CPET recovery demonstrated the best predictive value in distinguishing between 1-, 2-, and 3-SCA [area under ROC curve 0.75 and 0.77 (SE = 0.11, 0.10; p = .043, .04) for rest and recovery, respectively]. ΔCortisol peak/rest predicted cumulative cardiac events (area under ROC curve 0.75, SE = 0.10, p = .049). Cortisol at rest and following an exercise test holds predictive value for CAD severity and prognosis, further demonstrating a link between stress and unwanted cardiac events.

Pharmacokinetics and Drug Interactions Determine Optimum Combination Strategies in Computational Models of Cancer Evolution.

PubMed

Chakrabarti, Shaon; Michor, Franziska

2017-07-15

The identification of optimal drug administration schedules to battle the emergence of resistance is a major challenge in cancer research. The existence of a multitude of resistance mechanisms necessitates administering drugs in combination, significantly complicating the endeavor of predicting the evolutionary dynamics of cancers and optimal intervention strategies. A thorough understanding of the important determinants of cancer evolution under combination therapies is therefore crucial for correctly predicting treatment outcomes. Here we developed the first computational strategy to explore pharmacokinetic and drug interaction effects in evolutionary models of cancer progression, a crucial step towards making clinically relevant predictions. We found that incorporating these phenomena into our multiscale stochastic modeling framework significantly changes the optimum drug administration schedules identified, often predicting nonintuitive strategies for combination therapies. We applied our approach to an ongoing phase Ib clinical trial (TATTON) administering AZD9291 and selumetinib to EGFR-mutant lung cancer patients. Our results suggest that the schedules used in the three trial arms have almost identical efficacies, but slight modifications in the dosing frequencies of the two drugs can significantly increase tumor cell eradication. Interestingly, we also predict that drug concentrations lower than the MTD are as efficacious, suggesting that lowering the total amount of drug administered could lower toxicities while not compromising on the effectiveness of the drugs. Our approach highlights the fact that quantitative knowledge of pharmacokinetic, drug interaction, and evolutionary processes is essential for identifying best intervention strategies. Our method is applicable to diverse cancer and treatment types and allows for a rational design of clinical trials. Cancer Res; 77(14); 3908-21. ©2017 AACR . ©2017 American Association for Cancer Research.

Global Network Alignment in the Context of Aging.

PubMed

Faisal, Fazle Elahi; Zhao, Han; Milenkovic, Tijana

2015-01-01

Analogous to sequence alignment, network alignment (NA) can be used to transfer biological knowledge across species between conserved network regions. NA faces two algorithmic challenges: 1) Which cost function to use to capture "similarities" between nodes in different networks? 2) Which alignment strategy to use to rapidly identify "high-scoring" alignments from all possible alignments? We "break down" existing state-of-the-art methods that use both different cost functions and different alignment strategies to evaluate each combination of their cost functions and alignment strategies. We find that a combination of the cost function of one method and the alignment strategy of another method beats the existing methods. Hence, we propose this combination as a novel superior NA method. Then, since human aging is hard to study experimentally due to long lifespan, we use NA to transfer aging-related knowledge from well annotated model species to poorly annotated human. By doing so, we produce novel human aging-related knowledge, which complements currently available knowledge about aging that has been obtained mainly by sequence alignment. We demonstrate significant similarity between topological and functional properties of our novel predictions and those of known aging-related genes. We are the first to use NA to learn more about aging.

Correlates of HIV risk-taking behaviors among African-American college students: the effect of HIV knowledge, motivation, and behavioral skills.

PubMed Central

Bazargan, M.; Kelly, E. M.; Stein, J. A.; Husaini, B. A.; Bazargan, S. H.

2000-01-01

This study identifies theoretically based predictors of condom use in a sample of 253 sexually active African-American college students recruited from two historically African-American colleges. The Information-Motivation-Behavioral (IMB) skills model of AIDS-preventive behavior was employed to delineate the roles of HIV/AIDS knowledge, experiences with and attitudes toward condom use, peer influences, perceived vulnerability, monogamy, and behavioral skills. A predictive structural equation model revealed significant predictors of more condom use including: male gender, more sexual HIV knowledge, positive experiences and attitudes about condom use, nonmonogamy, and greater behavioral skills. Results imply that attention to behavioral skills for negotiating safer sex and training in the proper use of condoms are key elements in reducing high risk behaviors. Increasing the specific knowledge level of college students regarding the subtleties of sexual transmission of HIV is important and should be addressed. Heightening students' awareness of the limited protection of serial monogamy, and the need to address gender-specific training regarding required behavior change to reduce transmission of HIV should be an additional goal of college health professionals. PMID:10992684

Vocabulary knowledge mediates the link between socioeconomic status and word learning in grade school.

PubMed

Maguire, Mandy J; Schneider, Julie M; Middleton, Anna E; Ralph, Yvonne; Lopez, Michael; Ackerman, Robert A; Abel, Alyson D

2018-02-01

The relationship between children's slow vocabulary growth and the family's low socioeconomic status (SES) has been well documented. However, previous studies have often focused on infants or preschoolers and primarily used static measures of vocabulary at multiple time points. To date, there is no research investigating whether SES predicts a child's word learning abilities in grade school and, if so, what mediates this relationship. In this study, 68 children aged 8-15 years performed a written word learning from context task that required using the surrounding text to identify the meaning of an unknown word. Results revealed that vocabulary knowledge significantly mediated the relationship between SES (as measured by maternal education) and word learning. This was true despite the fact that the words in the linguistic context surrounding the target word are typically acquired well before 8 years of age. When controlling for vocabulary, word learning from written context was not predicted by differences in reading comprehension, decoding, or working memory. These findings reveal that differences in vocabulary growth between grade school children from low and higher SES homes are likely related to differences in the process of word learning more than knowledge of surrounding words or reading skills. Specifically, children from lower SES homes are not as effective at using known vocabulary to build a robust semantic representation of incoming text to identify the meaning of an unknown word. Copyright © 2017 Elsevier Inc. All rights reserved.

Triangulation of the neurocomputational architecture underpinning reading aloud

PubMed Central

Hoffman, Paul; Lambon Ralph, Matthew A.; Woollams, Anna M.

2015-01-01

The goal of cognitive neuroscience is to integrate cognitive models with knowledge about underlying neural machinery. This significant challenge was explored in relation to word reading, where sophisticated computational-cognitive models exist but have made limited contact with neural data. Using distortion-corrected functional MRI and dynamic causal modeling, we investigated the interactions between brain regions dedicated to orthographic, semantic, and phonological processing while participants read words aloud. We found that the lateral anterior temporal lobe exhibited increased activation when participants read words with irregular spellings. This area is implicated in semantic processing but has not previously been considered part of the reading network. We also found meaningful individual differences in the activation of this region: Activity was predicted by an independent measure of the degree to which participants use semantic knowledge to read. These characteristics are predicted by the connectionist Triangle Model of reading and indicate a key role for semantic knowledge in reading aloud. Premotor regions associated with phonological processing displayed the reverse characteristics. Changes in the functional connectivity of the reading network during irregular word reading also were consistent with semantic recruitment. These data support the view that reading aloud is underpinned by the joint operation of two neural pathways. They reveal that (i) the ATL is an important element of the ventral semantic pathway and (ii) the division of labor between the two routes varies according to both the properties of the words being read and individual differences in the degree to which participants rely on each route. PMID:26124121

Self-supervised ARTMAP.

PubMed

Amis, Gregory P; Carpenter, Gail A

2010-03-01

Computational models of learning typically train on labeled input patterns (supervised learning), unlabeled input patterns (unsupervised learning), or a combination of the two (semi-supervised learning). In each case input patterns have a fixed number of features throughout training and testing. Human and machine learning contexts present additional opportunities for expanding incomplete knowledge from formal training, via self-directed learning that incorporates features not previously experienced. This article defines a new self-supervised learning paradigm to address these richer learning contexts, introducing a neural network called self-supervised ARTMAP. Self-supervised learning integrates knowledge from a teacher (labeled patterns with some features), knowledge from the environment (unlabeled patterns with more features), and knowledge from internal model activation (self-labeled patterns). Self-supervised ARTMAP learns about novel features from unlabeled patterns without destroying partial knowledge previously acquired from labeled patterns. A category selection function bases system predictions on known features, and distributed network activation scales unlabeled learning to prediction confidence. Slow distributed learning on unlabeled patterns focuses on novel features and confident predictions, defining classification boundaries that were ambiguous in the labeled patterns. Self-supervised ARTMAP improves test accuracy on illustrative low-dimensional problems and on high-dimensional benchmarks. Model code and benchmark data are available from: http://techlab.eu.edu/SSART/. Copyright 2009 Elsevier Ltd. All rights reserved.

Extending (Q)SARs to incorporate proprietary knowledge for regulatory purposes: A case study using aromatic amine mutagenicity.

PubMed

Ahlberg, Ernst; Amberg, Alexander; Beilke, Lisa D; Bower, David; Cross, Kevin P; Custer, Laura; Ford, Kevin A; Van Gompel, Jacky; Harvey, James; Honma, Masamitsu; Jolly, Robert; Joossens, Elisabeth; Kemper, Raymond A; Kenyon, Michelle; Kruhlak, Naomi; Kuhnke, Lara; Leavitt, Penny; Naven, Russell; Neilan, Claire; Quigley, Donald P; Shuey, Dana; Spirkl, Hans-Peter; Stavitskaya, Lidiya; Teasdale, Andrew; White, Angela; Wichard, Joerg; Zwickl, Craig; Myatt, Glenn J

2016-06-01

Statistical-based and expert rule-based models built using public domain mutagenicity knowledge and data are routinely used for computational (Q)SAR assessments of pharmaceutical impurities in line with the approach recommended in the ICH M7 guideline. Knowledge from proprietary corporate mutagenicity databases could be used to increase the predictive performance for selected chemical classes as well as expand the applicability domain of these (Q)SAR models. This paper outlines a mechanism for sharing knowledge without the release of proprietary data. Primary aromatic amine mutagenicity was selected as a case study because this chemical class is often encountered in pharmaceutical impurity analysis and mutagenicity of aromatic amines is currently difficult to predict. As part of this analysis, a series of aromatic amine substructures were defined and the number of mutagenic and non-mutagenic examples for each chemical substructure calculated across a series of public and proprietary mutagenicity databases. This information was pooled across all sources to identify structural classes that activate or deactivate aromatic amine mutagenicity. This structure activity knowledge, in combination with newly released primary aromatic amine data, was incorporated into Leadscope's expert rule-based and statistical-based (Q)SAR models where increased predictive performance was demonstrated. Copyright © 2016 Elsevier Inc. All rights reserved.

Metacognition and Reading: Comparing Three Forms of Metacognition in Normally Developing Readers and Readers with Dyslexia.

PubMed

Furnes, Bjarte; Norman, Elisabeth

2015-08-01

Metacognition refers to 'cognition about cognition' and includes metacognitive knowledge, strategies and experiences (Efklides, 2008; Flavell, 1979). Research on reading has shown that better readers demonstrate more metacognitive knowledge than poor readers (Baker & Beall, 2009), and that reading ability improves through strategy instruction (Gersten, Fuchs, Williams, & Baker, 2001). The current study is the first to specifically compare the three forms of metacognition in dyslexic (N = 22) versus normally developing readers (N = 22). Participants read two factual texts, with learning outcome measured by a memory task. Metacognitive knowledge and skills were assessed by self-report. Metacognitive experiences were measured by predictions of performance and judgments of learning. Individuals with dyslexia showed insight into their reading problems, but less general knowledge of how to approach text reading. They more often reported lack of available reading strategies, but groups did not differ in the use of deep and surface strategies. Learning outcome and mean ratings of predictions of performance and judgments of learning were lower in dyslexic readers, but not the accuracy with which metacognitive experiences predicted learning. Overall, the results indicate that dyslexic reading and spelling problems are not generally associated with lower levels of metacognitive knowledge, metacognitive strategies or sensitivity to metacognitive experiences in reading situations. 2015 The Authors. Dyslexia Published by John Wiley & Sons Ltd.

Association of pain ratings with the prediction of early physical recovery after general and orthopaedic surgery-A quantitative study with repeated measures.

PubMed

Eriksson, Kerstin; Wikström, Lotta; Fridlund, Bengt; Årestedt, Kristofer; Broström, Anders

2017-11-01

To compare different levels of self-rated pain and determine if they predict anticipated early physical recovery in patients undergoing general and orthopaedic surgery. Previous research has indicated that average self-rated pain reflects patients' ability to recover the same day. However, there is a knowledge gap about the feasibility of using average pain ratings to predict patients' physical recovery for the next day. Descriptive, quantitative repeated measures. General and orthopaedic inpatients (n = 479) completed a questionnaire (October 2012-January 2015) about pain and recovery. Average pain intensity at rest and during activity was based on the Numeric Rating Scale and divided into three levels (0-3, 4-6, 7-10). Three out of five dimensions from the tool "Postoperative Recovery Profile" were used. Because few suffered severe pain, general and orthopaedic patients were analysed together. Binary logistic regression analysis showed that average pain intensity postoperative day 1 significantly predicted the impact on recovery day 2, except nausea, gastrointestinal function and bladder function when pain at rest and also nausea, appetite changes, and bladder function when pain during activity. High pain ratings (NRS 7-10) demonstrated to be a better predictor for recovery compared with moderate ratings (NRS 4-6), day 2, as it significantly predicted more items in recovery. Pain intensity reflected general and orthopaedic patients' physical recovery postoperative day 1 and predicted recovery for day 2. By monitoring patients' pain and impact on recovery, patients' need for support becomes visible which is valuable during hospital stays. © 2017 John Wiley & Sons Ltd.

IEA EBC annex 53: Total energy use in buildings—Analysis and evaluation methods

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

Yoshino, Hiroshi; Hong, Tianzhen; Nord, Natasa

One of the most significant barriers to achieving deep building energy efficiency is a lack of knowledge about the factors determining energy use. In fact, there is often a significant discrepancy between designed and real energy use in buildings, which is poorly understood but are believed to have more to do with the role of human behavior than building design. Building energy use is mainly influenced by six factors: climate, building envelope, building services and energy systems, building operation and maintenance, occupants’ activities and behavior, and indoor environmental quality. In the past, much research focused on the first three factors.more » However, the next three human-related factors can have an influence as significant as the first three. Annex 53 employed an interdisciplinary approach, integrating building science, architectural engineering, computer modeling and simulation, and social and behavioral science to develop and apply methods to analyze and evaluate the real energy use in buildings considering the six influencing factors. Finally, outcomes from Annex 53 improved understanding and strengthen knowledge regarding the robust prediction of total energy use in buildings, enabling reliable quantitative assessment of energy-savings measures, policies, and techniques.« less

IEA EBC annex 53: Total energy use in buildings—Analysis and evaluation methods

DOE PAGES

Yoshino, Hiroshi; Hong, Tianzhen; Nord, Natasa

2017-07-18

One of the most significant barriers to achieving deep building energy efficiency is a lack of knowledge about the factors determining energy use. In fact, there is often a significant discrepancy between designed and real energy use in buildings, which is poorly understood but are believed to have more to do with the role of human behavior than building design. Building energy use is mainly influenced by six factors: climate, building envelope, building services and energy systems, building operation and maintenance, occupants’ activities and behavior, and indoor environmental quality. In the past, much research focused on the first three factors.more » However, the next three human-related factors can have an influence as significant as the first three. Annex 53 employed an interdisciplinary approach, integrating building science, architectural engineering, computer modeling and simulation, and social and behavioral science to develop and apply methods to analyze and evaluate the real energy use in buildings considering the six influencing factors. Finally, outcomes from Annex 53 improved understanding and strengthen knowledge regarding the robust prediction of total energy use in buildings, enabling reliable quantitative assessment of energy-savings measures, policies, and techniques.« less

The Comparison of Dietary Behaviors among Rural Controlled and Uncontrolled Hypertensive Patients.

PubMed

Kamran, Aziz; Shekarchi, Ali Akbar; Sharifian, Elham; Heydari, Heshmatolah

2016-01-01

Nutrition is a dominant peripheral factor in increasing blood pressure; however, little information is available about the nutritional status of hypertensive patients in Iran. This study aimed to compare nutritional behaviors of the rural controlled and uncontrolled hypertensive patients and to determine the predictive power of nutritional behaviors from blood pressure. This cross-sectional study was conducted on 671 rural hypertensive patients, using multistage random sampling method in Ardabil city in 2013. Data were collected by a 3-day food record questionnaire. Nutritional data were extracted by Nutritionist 4 software and analyzed by the SPSS 18 software using Pearson correlation, multiple linear regression, ANOVA, and independent t-test. A significant difference was observed in the means of fat intake, cholesterol, saturated fat, sodium, energy, calcium, vitamin C, fiber, and nutritional knowledge between controlled and uncontrolled groups. In the controlled group, sodium, saturated fats, vitamin C, calcium, and energy intake explained 30.6% of the variations in blood pressure and, in the uncontrolled group, sodium, carbohydrate, fiber intake, and nutritional knowledge explained 83% of the variations in blood pressure. There was a significant difference in the nutritional behavior between the two groups and changes in blood pressure could be explained significantly by nutritional behaviors.

The conscious, the unconscious, and familiarity.

PubMed

Scott, Ryan B; Dienes, Zoltán

2008-09-01

This article examines the role of subjective familiarity in the implicit and explicit learning of artificial grammars. Experiment 1 found that objective measures of similarity (including fragment frequency and repetition structure) predicted ratings of familiarity, that familiarity ratings predicted grammaticality judgments, and that the extremity of familiarity ratings predicted confidence. Familiarity was further shown to predict judgments in the absence of confidence, hence contributing to above-chance guessing. Experiment 2 found that confidence developed as participants refined their knowledge of the distribution of familiarity and that differences in familiarity could be exploited prior to confidence developing. Experiment 3 found that familiarity was consciously exploited to make grammaticality judgments including those made without confidence and that familiarity could in some instances influence participants' grammaticality judgments apparently without their awareness. All 3 experiments found that knowledge distinct from familiarity was derived only under deliberate learning conditions. The results provide decisive evidence that familiarity is the essential source of knowledge in artificial grammar learning while also supporting a dual-process model of implicit and explicit learning. (c) 2008 APA, all rights reserved.

Modelling Chemical Reasoning to Predict and Invent Reactions.

PubMed

Segler, Marwin H S; Waller, Mark P

2017-05-02

The ability to reason beyond established knowledge allows organic chemists to solve synthetic problems and invent novel transformations. Herein, we propose a model that mimics chemical reasoning, and formalises reaction prediction as finding missing links in a knowledge graph. We have constructed a knowledge graph containing 14.4 million molecules and 8.2 million binary reactions, which represents the bulk of all chemical reactions ever published in the scientific literature. Our model outperforms a rule-based expert system in the reaction prediction task for 180 000 randomly selected binary reactions. The data-driven model generalises even beyond known reaction types, and is thus capable of effectively (re-)discovering novel transformations (even including transition metal-catalysed reactions). Our model enables computers to infer hypotheses about reactivity and reactions by only considering the intrinsic local structure of the graph and because each single reaction prediction is typically achieved in a sub-second time frame, the model can be used as a high-throughput generator of reaction hypotheses for reaction discovery. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Mothers and vaccination: knowledge, attitudes, and behaviour in Italy.

PubMed

Angelillo, I F; Ricciardi, G; Rossi, P; Pantisano, P; Langiano, E; Pavia, M

1999-01-01

The study evaluates knowledge, attitudes, and behaviour of mothers regarding the immunization of 841 infants who attended public kindergarten in Cassino and Crotone, Italy. Overall, 57.8% of mothers were aware about all four mandatory vaccinations for infants (poliomyelitis, tetanus, diphtheria, hepatitis B). The results of a multiple logistic regression analysis showed that this knowledge was significantly greater among mothers with a higher education level and among those who were older at the time of the child's birth. Respondents' attitudes towards the utility of vaccinations for preventing infectious diseases were very favourable. Almost all children (94.4%) were vaccinated with all three doses of diphtheria-tetanus (DT), oral poliovirus vaccine (OPV), and hepatitis B. The proportion of children vaccinated who received all three doses of OPV, DT or diphtheria-tetanus-pertussis (DTP), and hepatitis B vaccines within 1 month of becoming age-eligible ranged from 56.6% for the third dose of hepatitis B to 95.7% for the first dose of OPV. Results of the regression analysis performed on the responses of mothers who had adhered to the schedule for all mandatory vaccinations indicated that birth order significantly predicted vaccination nonadherence, since children who had at least one older sibling in the household were significantly less likely to be age-appropriately vaccinated. The coverage for the optional vaccines was only 22.5% and 31% for measles-mumps-rubella and for all three doses against pertussis, respectively. Education programmes promoting paediatric immunization, accessibility, and follow-up should be targeted to the entire population.

Writing Proficiency Level and Writing Development of Low-Achieving Adolescents: The Roles of Linguistic Knowledge, Fluency, and Metacognitive Knowledge

ERIC Educational Resources Information Center

Trapman, Mirjam; van Gelderen, Amos; van Schooten, Erik; Hulstijn, Jan

2018-01-01

In a longitudinal design, 51 low-achieving adolescents' development in writing proficiency from Grades 7 to 9 was measured. There were 25 native-Dutch and 26 language-minority students. In addition, the roles of (1) linguistic knowledge, (2) metacognitive knowledge, and (3) linguistic fluency in predicting both the level and development of writing…

The Contribution of Soil Moisture Information to Forecast Skill: Two Studies

NASA Technical Reports Server (NTRS)

Koster, Randal

2010-01-01

This talk briefly describes two recent studies on the impact of soil moisture information on hydrological and meteorological prediction. While the studies utilize soil moisture derived from the integration of large-scale land surface models with observations-based meteorological data, the results directly illustrate the potential usefulness of satellite-derived soil moisture information (e.g., from SMOS and SMAP) for applications in prediction. The first study, the GEWEX- and ClIVAR-sponsored GLACE-2 project, quantifies the contribution of realistic soil moisture initialization to skill in subseasonal forecasts of precipitation and air temperature (out to two months). The multi-model study shows that soil moisture information does indeed contribute skill to the forecasts, particularly for air temperature, and particularly when the initial local soil moisture anomaly is large. Furthermore, the skill contributions tend to be larger where the soil moisture initialization is more accurate, as measured by the density of the observational network contributing to the initialization. The second study focuses on streamflow prediction. The relative contributions of snow and soil moisture initialization to skill in streamflow prediction at seasonal lead, in the absence of knowledge of meteorological anomalies during the forecast period, were quantified with several land surface models using uniquely designed numerical experiments and naturalized streamflow data covering mUltiple decades over the western United States. In several basins, accurate soil moisture initialization is found to contribute significant levels of predictive skill. Depending on the date of forecast issue, the contributions can be significant out to leads of six months. Both studies suggest that improvements in soil moisture initialization would lead to increases in predictive skill. The relevance of SMOS and SMAP satellite-based soil moisture information to prediction are discussed in the context of these studies.

Familiarity mediates the relationship between emotional arousal and pleasure during music listening

PubMed Central

van den Bosch, Iris; Salimpoor, Valorie N.; Zatorre, Robert J.

2013-01-01

Emotional arousal appears to be a major contributing factor to the pleasure that listeners experience in response to music. Accordingly, a strong positive correlation between self-reported pleasure and electrodermal activity (EDA), an objective indicator of emotional arousal, has been demonstrated when individuals listen to familiar music. However, it is not yet known to what extent familiarity contributes to this relationship. In particular, as listening to familiar music involves expectations and predictions over time based on veridical knowledge of the piece, it could be that such memory factors plays a major role. Here, we tested such a contribution by using musical stimuli entirely unfamiliar to listeners. In a second experiment we repeated the novel music to experimentally establish a sense of familiarity. We aimed to determine whether (1) pleasure and emotional arousal would continue to correlate when listeners have no explicit knowledge of how the tones will unfold, and (2) whether this could be enhanced by experimentally-induced familiarity. In the first experiment, we presented 33 listeners with 70 unfamiliar musical excerpts in two sessions. There was no relationship between the degree of experienced pleasure and emotional arousal as measured by EDA. In the second experiment, 7 participants listened to 35 unfamiliar excerpts over two sessions separated by 30 min. Repeated exposure significantly increased EDA, even though individuals did not explicitly recall having heard all the pieces before. Furthermore, increases in self-reported familiarity significantly enhanced experienced pleasure and there was a general, though not significant, increase in EDA. These results suggest that some level of expectation and predictability mediated by prior exposure to a given piece of music play an important role in the experience of emotional arousal in response to music. PMID:24046738

Condom Use among Immigrant Latino Sexual Minorities: Multilevel Analysis after Respondent-Driven Sampling

PubMed Central

Rhodes, Scott D.; McCoy, Thomas P.

2014-01-01

This study explored correlates of condom use within a respondent-driven sample of 190 Spanish-speaking immigrant Latino sexual minorities, including gay and bisexual men, other men who have sex with men (MSM), and transgender person, in North Carolina. Five analytic approaches for modeling data collected using respondent-driven sampling (RDS) were compared. Across most approaches, knowledge of HIV and sexually transmitted infections (STIs) and increased condom use self-efficacy predicted consistent condom use and increased homophobia predicted decreased consistent condom use. The same correlates were not significant in all analyses but were consistent in most. Clustering due to recruitment chains was low, while clustering due to recruiter was substantial. This highlights the importance accounting for clustering when analyzing RDS data. PMID:25646728

Type 1 diabetes: New horizons in prediction and prevention.

PubMed

Razack, Natasha N; Wherrett, Diane K

2005-01-01

Significant advances have been made in our understanding of the pathogenesis of type 1 diabetes and our ability to predict risk for the condition. This knowledge is being used to develop new and innovative strategies to prevent type 1 diabetes or to prevent further destruction of beta cells in those who are newly diagnosed. Several multicentre studies are underway investigating the natural history of the disease, the genetics behind the disease and ways to stop the autoimmune reaction against beta cells (Type 1 Diabetes TrialNet, Type 1 Diabetes Genetics Consortium and the Trial to Reduce Diabetes in the Genetically at Risk [TRIGR] Study Group). The stage is set to find an agent or strategy to prevent type 1 diabetes or to preserve the residual beta cell mass in new-onset patients.

Neuro-symbolic representation learning on biological knowledge graphs.

PubMed

Alshahrani, Mona; Khan, Mohammad Asif; Maddouri, Omar; Kinjo, Akira R; Queralt-Rosinach, Núria; Hoehndorf, Robert

2017-09-01

Biological data and knowledge bases increasingly rely on Semantic Web technologies and the use of knowledge graphs for data integration, retrieval and federated queries. In the past years, feature learning methods that are applicable to graph-structured data are becoming available, but have not yet widely been applied and evaluated on structured biological knowledge. Results: We develop a novel method for feature learning on biological knowledge graphs. Our method combines symbolic methods, in particular knowledge representation using symbolic logic and automated reasoning, with neural networks to generate embeddings of nodes that encode for related information within knowledge graphs. Through the use of symbolic logic, these embeddings contain both explicit and implicit information. We apply these embeddings to the prediction of edges in the knowledge graph representing problems of function prediction, finding candidate genes of diseases, protein-protein interactions, or drug target relations, and demonstrate performance that matches and sometimes outperforms traditional approaches based on manually crafted features. Our method can be applied to any biological knowledge graph, and will thereby open up the increasing amount of Semantic Web based knowledge bases in biology to use in machine learning and data analytics. https://github.com/bio-ontology-research-group/walking-rdf-and-owl. robert.hoehndorf@kaust.edu.sa. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

How Do Organic Chemistry Students Understand and Apply Hydrogen Bonding?

NASA Astrophysics Data System (ADS)

Henderleiter, J.; Smart, R.; Anderson, J.; Elian, O.

2001-08-01

Students completing a year-long organic chemistry sequence were interviewed to assess how they understood, explained, and applied knowledge of hydrogen bonding to the physical behavior of molecules. Students were asked to define hydrogen bonding and explain situations in which hydrogen bonding could occur. They were asked to predict and explain how hydrogen bonding influences boiling point, the solubility of molecules, and NMR and IR spectra. Results suggest that although students may be able to give appropriate definitions of hydrogen bonding and may recognize when this phenomenon can occur, significant numbers cannot apply their knowledge of hydrogen bonding to physical properties of molecules or to the interpretation of spectral data. Some possess misconceptions concerning boiling points and the ability of molecules to induce hydrogen bonding. Instructional strategies must be adjusted to address these issues.

Predicting Reading and Spelling Disorders: A 4-Year Prospective Cohort Study

PubMed Central

Bigozzi, Lucia; Tarchi, Christian; Caudek, Corrado; Pinto, Giuliana

2016-01-01

In this 4-year prospective cohort study, children with a reading and spelling disorder, children with a spelling impairment, and children without a reading and/or spelling disorder (control group) in a transparent orthography were identified in third grade, and their emergent literacy performances in kindergarten compared retrospectively. Six hundred and forty-two Italian children participated. This cohort was followed from the last year of kindergarten to third grade. In kindergarten, the children were assessed in phonological awareness, conceptual knowledge of writing systems and textual competence. In third grade, 18 children with a reading and spelling impairment and 13 children with a spelling impairment were identified. Overall, conceptual knowledge of the writing system was the only statistically significant predictor of the clinical samples. No differences were found between the two clinical samples. PMID:27014145

Youth Sport Readiness: A Predictive Model for Success.

ERIC Educational Resources Information Center

Aicinena, Steven

1992-01-01

A model for predicting organized youth sport participation readiness has four predictive components: sport-related fundamental motor skill development; sport-specific knowledge; motivation; and socialization. Physical maturation is also important. The model emphasizes the importance of preparing children for successful participation through…

The Comparative Effects of Prediction/Discussion-Based Learning Cycle, Conceptual Change Text, and Traditional Instructions on Student Understanding of Genetics

NASA Astrophysics Data System (ADS)

Yilmaz, Diba; Tekkaya, Ceren; Sungur, Semra

2011-03-01

The present study examined the comparative effects of a prediction/discussion-based learning cycle, conceptual change text (CCT), and traditional instructions on students' understanding of genetics concepts. A quasi-experimental research design of the pre-test-post-test non-equivalent control group was adopted. The three intact classes, taught by the same science teacher, were randomly assigned as prediction/discussion-based learning cycle class (N = 30), CCT class (N = 25), and traditional class (N = 26). Participants completed the genetics concept test as pre-test, post-test, and delayed post-test to examine the effects of instructional strategies on their genetics understanding and retention. While the dependent variable of this study was students' understanding of genetics, the independent variables were time (Time 1, Time 2, and Time 3) and mode of instruction. The mixed between-within subjects analysis of variance revealed that students in both prediction/discussion-based learning cycle and CCT groups understood the genetics concepts and retained their knowledge significantly better than students in the traditional instruction group.

Intensity dependence of focused ultrasound lesion position

NASA Astrophysics Data System (ADS)

Meaney, Paul M.; Cahill, Mark D.; ter Haar, Gail R.

1998-04-01

Knowledge of the spatial distribution of intensity loss from an ultrasonic beam is critical to predicting lesion formation in focused ultrasound surgery. To date most models have used linear propagation models to predict the intensity profiles needed to compute the temporally varying temperature distributions. These can be used to compute thermal dose contours that can in turn be used to predict the extent of thermal damage. However, these simulations fail to adequately describe the abnormal lesion formation behavior observed for in vitro experiments in cases where the transducer drive levels are varied over a wide range. For these experiments, the extent of thermal damage has been observed to move significantly closer to the transducer with increasing transducer drive levels than would be predicted using linear propagation models. The simulations described herein, utilize the KZK (Khokhlov-Zabolotskaya-Kuznetsov) nonlinear propagation model with the parabolic approximation for highly focused ultrasound waves, to demonstrate that the positions of the peak intensity and the lesion do indeed move closer to the transducer. This illustrates that for accurate modeling of heating during FUS, nonlinear effects must be considered.

Predicting Hydrological Drought: Relative Contributions of Soil Moisture and Snow Information to Seasonal Streamflow Prediction Skill

NASA Technical Reports Server (NTRS)

Koster, R.; Mahanama, S.; Livneh, B.; Lettenmaier, D.; Reichle, R.

2011-01-01

in this study we examine how knowledge of mid-winter snow accumulation and soil moisture conditions contribute to our ability to predict streamflow months in advance. A first "synthetic truth" analysis focuses on a series of numerical experiments with multiple sophisticated land surface models driven with a dataset of observations-based meteorological forcing spanning multiple decades and covering the continental United States. Snowpack information by itself obviously contributes to the skill attained in streamflow prediction, particularly in the mountainous west. The isolated contribution of soil moisture information, however, is found to be large and significant in many areas, particularly in the west but also in region surrounding the Great Lakes. The results are supported by a supplemental, observations-based analysis using (naturalized) March-July streamflow measurements covering much of the western U.S. Additional forecast experiments using start dates that span the year indicate a strong seasonality in the skill contributions; soil moisture information, for example, contributes to kill at much longer leads for forecasts issued in winter than for those issued in summer.

A survey of heating and turbulent boundary layer characteristics of several hypersonic research aircraft configurations

NASA Technical Reports Server (NTRS)

Lawing, P. L.

1981-01-01

Four of the configurations investigated during a proposed NASA-Langley hypersonic research aircraft program were selected for phase-change-paint heat-transfer testing and forebody boundary layer pitot surveys. In anticipation of future hypersonic aircraft, both published and unpublished data and results are reviewed and presented with the purpose of providing a synoptic heat-transfer data base from the research effort. Engineering heat-transfer predictions are compared with experimental data on both a global and a local basis. The global predictions are shown to be sufficient for purposes of configuration development, and even the local predictions can be adequate when interpreted in light of the proper flow field. In that regard, cross flow in the forebody boundary layers was examined for significant heating and aerodynamic effect on the scramjet engines. A design philosophy which evolved from the research airplane effort is used to design a forebody shape that produces thin, uniform, forebody boundary layers on a hypersonic airbreathing missile. Finally, heating/boundary layer phenomena which are not predictable with state-of-the-art knowledge and techniques are shown and discussed.

Knowledge and implicature: modeling language understanding as social cognition.

PubMed

Goodman, Noah D; Stuhlmüller, Andreas

2013-01-01

Is language understanding a special case of social cognition? To help evaluate this view, we can formalize it as the rational speech-act theory: Listeners assume that speakers choose their utterances approximately optimally, and listeners interpret an utterance by using Bayesian inference to "invert" this model of the speaker. We apply this framework to model scalar implicature ("some" implies "not all," and "N" implies "not more than N"). This model predicts an interaction between the speaker's knowledge state and the listener's interpretation. We test these predictions in two experiments and find good fit between model predictions and human judgments. Copyright © 2013 Cognitive Science Society, Inc.

Development and evaluation of a regression-based model to predict cesium concentration ratios for freshwater fish.

PubMed

Pinder, John E; Rowan, David J; Rasmussen, Joseph B; Smith, Jim T; Hinton, Thomas G; Whicker, F W

2014-08-01

Data from published studies and World Wide Web sources were combined to produce and test a regression model to predict Cs concentration ratios for freshwater fish species. The accuracies of predicted concentration ratios, which were computed using 1) species trophic levels obtained from random resampling of known food items and 2) K concentrations in the water for 207 fish from 44 species and 43 locations, were tested against independent observations of ratios for 57 fish from 17 species from 25 locations. Accuracy was assessed as the percent of observed to predicted ratios within factors of 2 or 3. Conservatism, expressed as the lack of under prediction, was assessed as the percent of observed to predicted ratios that were less than 2 or less than 3. The model's median observed to predicted ratio was 1.26, which was not significantly different from 1, and 50% of the ratios were between 0.73 and 1.85. The percentages of ratios within factors of 2 or 3 were 67 and 82%, respectively. The percentages of ratios that were <2 or <3 were 79 and 88%, respectively. An example for Perca fluviatilis demonstrated that increased prediction accuracy could be obtained when more detailed knowledge of diet was available to estimate trophic level. Copyright © 2014 Elsevier Ltd. All rights reserved.

COMPUTING THERAPY FOR PRECISION MEDICINE: COLLABORATIVE FILTERING INTEGRATES AND PREDICTS MULTI-ENTITY INTERACTIONS.

PubMed

Regenbogen, Sam; Wilkins, Angela D; Lichtarge, Olivier

2016-01-01

Biomedicine produces copious information it cannot fully exploit. Specifically, there is considerable need to integrate knowledge from disparate studies to discover connections across domains. Here, we used a Collaborative Filtering approach, inspired by online recommendation algorithms, in which non-negative matrix factorization (NMF) predicts interactions among chemicals, genes, and diseases only from pairwise information about their interactions. Our approach, applied to matrices derived from the Comparative Toxicogenomics Database, successfully recovered Chemical-Disease, Chemical-Gene, and Disease-Gene networks in 10-fold cross-validation experiments. Additionally, we could predict each of these interaction matrices from the other two. Integrating all three CTD interaction matrices with NMF led to good predictions of STRING, an independent, external network of protein-protein interactions. Finally, this approach could integrate the CTD and STRING interaction data to improve Chemical-Gene cross-validation performance significantly, and, in a time-stamped study, it predicted information added to CTD after a given date, using only data prior to that date. We conclude that collaborative filtering can integrate information across multiple types of biological entities, and that as a first step towards precision medicine it can compute drug repurposing hypotheses.

COMPUTING THERAPY FOR PRECISION MEDICINE: COLLABORATIVE FILTERING INTEGRATES AND PREDICTS MULTI-ENTITY INTERACTIONS

PubMed Central

REGENBOGEN, SAM; WILKINS, ANGELA D.; LICHTARGE, OLIVIER

2015-01-01

Biomedicine produces copious information it cannot fully exploit. Specifically, there is considerable need to integrate knowledge from disparate studies to discover connections across domains. Here, we used a Collaborative Filtering approach, inspired by online recommendation algorithms, in which non-negative matrix factorization (NMF) predicts interactions among chemicals, genes, and diseases only from pairwise information about their interactions. Our approach, applied to matrices derived from the Comparative Toxicogenomics Database, successfully recovered Chemical-Disease, Chemical-Gene, and Disease-Gene networks in 10-fold cross-validation experiments. Additionally, we could predict each of these interaction matrices from the other two. Integrating all three CTD interaction matrices with NMF led to good predictions of STRING, an independent, external network of protein-protein interactions. Finally, this approach could integrate the CTD and STRING interaction data to improve Chemical-Gene cross-validation performance significantly, and, in a time-stamped study, it predicted information added to CTD after a given date, using only data prior to that date. We conclude that collaborative filtering can integrate information across multiple types of biological entities, and that as a first step towards precision medicine it can compute drug repurposing hypotheses. PMID:26776170

A comparison of attitude, personality, and knowledge predictors of service-oriented organizational citizenship behaviors.

PubMed

Bettencourt, L A; Gwinner, K P; Meuter, M L

2001-02-01

Attitude, personality, and customer knowledge antecedents were compared in their predictive ability of 3 service-oriented forms of employee organizational citizenship behaviors (OCBs): loyalty, service delivery, and participation. For the 1st study, 236 customer-contact employees provided data concerning their OCBs and the attitude, personality, and knowledge antecedents. The 2nd investigation relied on data provided by 144 contact employees from a network of university libraries. Using hierarchical regression in both studies, the authors found that each of the 3 types of service-oriented OCBs was best predicted by different subsets of the antecedents. Job attitudes accounted for the most unique variance in loyalty OCBs, personality accounted for the most unique variance in service delivery OCBs, and customer knowledge and personality jointly were the best predictors of participation OCBs.

A population survey on legislative measures to restrict smoking in Ontario: 4. Variables related to knowledge of active and passive smoking health effects and to predicted behavior of smokers and nonsmokers.

PubMed

Pederson, L L; Bull, S B; Ashley, M J; Lefcoe, N M

1989-01-01

Results from the further analysis of a population survey on legislative measures to restrict smoking revealed that identification of subgroups of smokers is more reliable than identification of subgroups of nonsmokers when a variety of attitudes were the measures of interest. A similar pattern emerged when analyses were carried out on knowledge of active and passive smoking health effects and on predicted personal and general compliance. Because distinct sets of variables were found to be related to distinct outcomes, program planning for changes in knowledge and behavior might, of necessity, have to be different. Media messages might be useful for changes in knowledge, while actual experience might be more important for attitude and behavior change.

Properties of the Bayesian Knowledge Tracing Model

ERIC Educational Resources Information Center

van de Sande, Brett

2013-01-01

Bayesian Knowledge Tracing is used very widely to model student learning. It comes in two different forms: The first form is the Bayesian Knowledge Tracing "hidden Markov model" which predicts the probability of correct application of a skill as a function of the number of previous opportunities to apply that skill and the model…

Preschool Spontaneous Focusing on Numerosity Predicts Rational Number Conceptual Knowledge 6 Years Later

ERIC Educational Resources Information Center

McMullen, Jake; Hannula-Sormunen, Minna M.; Lehtinen, Erno

2015-01-01

Recent evidence suggests that early natural number knowledge is a predictor of later rational number conceptual knowledge, even though students' difficulties with rational numbers have also been explained by the overuse of natural number concepts--often referred to as the natural number bias. Hannula and Lehtinen ("Learn Instr"…

Teachers' Knowledge of Children's Exposure to Family Risk Factors: Accuracy and Usefulness

ERIC Educational Resources Information Center

Dwyer, Sarah B.; Nicholson, Jan M.; Battistutta, Diana; Oldenburg, Brian

2005-01-01

Teachers' knowledge of children's exposure to family risk factors was examined using the Family Risk Factor Checklist-Teacher. Data collected for 756 children indicated that teachers had accurate knowledge of children's exposure to factors such as adverse life events and family socioeconomic status, which predicted children's mental health…

Preschoolers' Theory-of-Mind Knowledge Influences Whom They Trust about Others' Theories of Mind

ERIC Educational Resources Information Center

Van Reet, Jennifer; Green, Kathryn F.; Sobel, David M.

2015-01-01

Two experiments examined whether particular aspects of social-cognitive knowledge predicted how preschoolers would treat informants who displayed a more or less developed understanding of that knowledge. In Experiment 1, children's own success on false-belief measures correlated with the extent to which they endorsed information generated by a…