Sample records for selectively prevented learning
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Corbalan, Gemma; Kester, Liesbeth; van Merrienboer, Jeroen J. G.
2008-01-01
Complex skill acquisition by performing authentic learning tasks is constrained by limited working memory capacity [Baddeley, A. D. (1992). Working memory. "Science, 255", 556-559]. To prevent cognitive overload, task difficulty and support of each newly selected learning task can be adapted to the learner's competence level and perceived task…
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Preventing Learned Helplessness.
Hoy, Cheri
1986-01-01
To prevent learned helplessness in learning disabled students, teachers can share responsibilities with the students, train students to reinforce themselves for effort and self control, and introduce opportunities for changing counterproductive attitudes. (CL)
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Prevention of Learned Helplessness in Humans.
Klee, Steven; Meyer, Robert G.
1979-01-01
Explored prevention of learned helplessness through the use of thermal biofeedback training and varied explanations of performance. It was found that only in the biofeedback group receiving accurate feedback was there any prevention of the subsequent development of learned helplessness behavior. (Author)
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Selection as a learning experience: an exploratory study.
de Visser, Marieke; Laan, Roland F; Engbers, Rik; Cohen-Schotanus, Janke; Fluit, Cornelia
2018-01-01
Research on selection for medical school does not explore selection as a learning experience, despite growing attention for the learning effects of assessment in general. Insight in the learning effects allows us to take advantage of selection as an inclusive part of medical students' learning process to become competent professionals. The aims of this study at Radboud University Medical Center, the Netherlands, were 1) to determine whether students have learning experiences in the selection process, and, if so, what experiences; and 2) to understand what students need in order to utilize the learning effects of the selection process at the start of the formal curriculum. We used focus groups to interview 30 students admitted in 2016 about their learning experiences in the selection process. Thematic analysis was used to explore the outcomes of the interviews and to define relevant themes. In the selection process, students learned about the curriculum, themselves, their relation to others, and the profession they had been selected to enter, although this was not explicitly perceived as learning. Students needed a connection between selection and the curriculum as well as feedback to be able to really use their learning experiences for their further development. Medical school selection qualifies as a learning experience, and students as well as medical schools can take advantage of this. We recommend a careful design of the selection procedure, integrating relevant selection learning experiences into the formal curriculum, providing feedback and explicitly approaching the selection and the formal curriculum as interconnected contributors to students' development.
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Human-simulation-based learning to prevent medication error: A systematic review.
Sarfati, Laura; Ranchon, Florence; Vantard, Nicolas; Schwiertz, Vérane; Larbre, Virginie; Parat, Stéphanie; Faudel, Amélie; Rioufol, Catherine
2018-01-31
In the past 2 decades, there has been an increasing interest in simulation-based learning programs to prevent medication error (ME). To improve knowledge, skills, and attitudes in prescribers, nurses, and pharmaceutical staff, these methods enable training without directly involving patients. However, best practices for simulation for healthcare providers are as yet undefined. By analysing the current state of experience in the field, the present review aims to assess whether human simulation in healthcare helps to reduce ME. A systematic review was conducted on Medline from 2000 to June 2015, associating the terms "Patient Simulation," "Medication Errors," and "Simulation Healthcare." Reports of technology-based simulation were excluded, to focus exclusively on human simulation in nontechnical skills learning. Twenty-one studies assessing simulation-based learning programs were selected, focusing on pharmacy, medicine or nursing students, or concerning programs aimed at reducing administration or preparation errors, managing crises, or learning communication skills for healthcare professionals. The studies varied in design, methodology, and assessment criteria. Few demonstrated that simulation was more effective than didactic learning in reducing ME. This review highlights a lack of long-term assessment and real-life extrapolation, with limited scenarios and participant samples. These various experiences, however, help in identifying the key elements required for an effective human simulation-based learning program for ME prevention: ie, scenario design, debriefing, and perception assessment. The performance of these programs depends on their ability to reflect reality and on professional guidance. Properly regulated simulation is a good way to train staff in events that happen only exceptionally, as well as in standard daily activities. By integrating human factors, simulation seems to be effective in preventing iatrogenic risk related to ME, if the program is
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Theory of mind selectively predicts preschoolers' knowledge-based selective word learning.
Brosseau-Liard, Patricia; Penney, Danielle; Poulin-Dubois, Diane
2015-11-01
Children can selectively attend to various attributes of a model, such as past accuracy or physical strength, to guide their social learning. There is a debate regarding whether a relation exists between theory-of-mind skills and selective learning. We hypothesized that high performance on theory-of-mind tasks would predict preference for learning new words from accurate informants (an epistemic attribute), but not from physically strong informants (a non-epistemic attribute). Three- and 4-year-olds (N = 65) completed two selective learning tasks, and their theory-of-mind abilities were assessed. As expected, performance on a theory-of-mind battery predicted children's preference to learn from more accurate informants but not from physically stronger informants. Results thus suggest that preschoolers with more advanced theory of mind have a better understanding of knowledge and apply that understanding to guide their selection of informants. This work has important implications for research on children's developing social cognition and early learning. © 2015 The British Psychological Society.
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Theory of mind selectively predicts preschoolers’ knowledge-based selective word learning
Brosseau-Liard, Patricia; Penney, Danielle; Poulin-Dubois, Diane
2015-01-01
Children can selectively attend to various attributes of a model, such as past accuracy or physical strength, to guide their social learning. There is a debate regarding whether a relation exists between theory-of-mind skills and selective learning. We hypothesized that high performance on theory-of-mind tasks would predict preference for learning new words from accurate informants (an epistemic attribute), but not from physically strong informants (a non-epistemic attribute). Three- and 4-year-olds (N = 65) completed two selective learning tasks, and their theory of mind abilities were assessed. As expected, performance on a theory-of-mind battery predicted children’s preference to learn from more accurate informants but not from physically stronger informants. Results thus suggest that preschoolers with more advanced theory of mind have a better understanding of knowledge and apply that understanding to guide their selection of informants. This work has important implications for research on children’s developing social cognition and early learning. PMID:26211504
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Gao, Yuan; Liu, Tzu-Chien; Paas, Fred
2016-01-01
This study compared the effects of effortless selection of target plants using quick respond (QR) code technology to effortful manual search and selection of target plants on learning about plants in a mobile device supported learning environment. In addition, it was investigated whether the effectiveness of the 2 selection methods was…
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Selective social learning in infancy: looking for mechanisms.
Crivello, Cristina; Phillips, Sara; Poulin-Dubois, Diane
2018-05-01
Although there is mounting evidence that selective social learning begins in infancy, the psychological mechanisms underlying this ability are currently a controversial issue. The purpose of this study is to investigate whether theory of mind abilities and statistical learning skills are related to infants' selective social learning. Seventy-seven 18-month-olds were first exposed to a reliable or an unreliable speaker and then completed a word learning task, two theory of mind tasks, and a statistical learning task. If domain-general abilities are linked to selective social learning, then infants who demonstrate superior performance on the statistical learning task should perform better on the selective learning task, that is, should be less likely to learn words from an unreliable speaker. Alternatively, if domain-specific abilities are involved, then superior performance on theory of mind tasks should be related to selective learning performance. Findings revealed that, as expected, infants were more likely to learn a novel word from a reliable speaker. Importantly, infants who passed a theory of mind task assessing knowledge attribution were significantly less likely to learn a novel word from an unreliable speaker compared to infants who failed this task. No such effect was observed for the other tasks. These results suggest that infants who possess superior social-cognitive abilities are more apt to reject an unreliable speaker as informant. A video abstract of this article can be viewed at: https://youtu.be/zuuCniHYzqo. © 2017 John Wiley & Sons Ltd.
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Prenatal treatment prevents learning deficit in Down syndrome model.
Incerti, Maddalena; Horowitz, Kari; Roberson, Robin; Abebe, Daniel; Toso, Laura; Caballero, Madeline; Spong, Catherine Y
2012-01-01
Down syndrome is the most common genetic cause of mental retardation. Active fragments of neurotrophic factors release by astrocyte under the stimulation of vasoactive intestinal peptide, NAPVSIPQ (NAP) and SALLRSIPA (SAL) respectively, have shown therapeutic potential for developmental delay and learning deficits. Previous work demonstrated that NAP+SAL prevent developmental delay and glial deficit in Ts65Dn that is a well-characterized mouse model for Down syndrome. The objective of this study is to evaluate if prenatal treatment with these peptides prevents the learning deficit in the Ts65Dn mice. Pregnant Ts65Dn female and control pregnant females were randomly treated (intraperitoneal injection) on pregnancy days 8 through 12 with saline (placebo) or peptides (NAP 20 µg +SAL 20 µg) daily. Learning was assessed in the offspring (8-10 months) using the Morris Watermaze, which measures the latency to find the hidden platform (decrease in latency denotes learning). The investigators were blinded to the prenatal treatment and genotype. Pups were genotyped as trisomic (Down syndrome) or euploid (control) after completion of all tests. two-way ANOVA followed by Neuman-Keuls test for multiple comparisons, PDown syndrome-placebo; n = 11) did not demonstrate learning over the five day period. DS mice that were prenatally exposed to peptides (Down syndrome-peptides; n = 10) learned significantly better than Down syndrome-placebo (ptreatment with the neuroprotective peptides (NAP+SAL) prevented learning deficits in a Down syndrome model. These findings highlight a possibility for the prevention of sequelae in Down syndrome and suggest a potential pregnancy intervention that may improve outcome.
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Is there a place for e-learning in infection prevention?
Labeau, Sonia O
2013-11-01
In the last few decades, e-learning, a method which integrates information technology and the learning process by using materials delivered through the internet, has become widely used in educational initiatives for healthcare professionals. To evaluate whether there is a place for e-learning in the field of infection prevention. Non-comprehensive review of the literature. E-learning courses in the field of infection prevention and control are still scarce, often restricted to local initiatives and not specifically directed toward critical care providers. Although methodological flaws and potential biases hamper the generalizability of results from some currently available studies, findings related to both learners' satisfaction and effectiveness suggest that e-learning might prove an effective educational tool for the (continuing) education of healthcare providers. Further investigations, including research pertaining to the cost-effectiveness of e-learning, are required to provide a better insight in these issues. Further research is required to determine the (cost)effectiveness of e-learning in general, and in the field of infection prevention and control in particular. Current insights suggest that e-learning should be based Web 2.0 technologies to address a wide range of learning styles and to optimize interactivity. As a gap in the literature was detected with respect to e-learning modules on infection prevention and control which are specifically oriented toward critical care providers, it can be recommended to promote the development and subsequent assessment of such tools that meet high-quality standards. Copyright © 2013 Australian College of Critical Care Nurses Ltd. Published by Elsevier Ltd. All rights reserved.
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As the largest prostate cancer prevention trial ever undertaken, the Selenium and Vitamin E Cancer Prevention Trial (SELECT) has assembled a substantial biorepository of specimens. To help make SELECT resources available to a wider research community, NCI and the Southwest Oncology Group are developing a plan for prostate cancer biology and nutritional science and
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Does learning or instinct shape habitat selection?
Directory of Open Access Journals (Sweden)
Scott E Nielsen
Full Text Available Habitat selection is an important behavioural process widely studied for its population-level effects. Models of habitat selection are, however, often fit without a mechanistic consideration. Here, we investigated whether patterns in habitat selection result from instinct or learning for a population of grizzly bears (Ursus arctos in Alberta, Canada. We found that habitat selection and relatedness were positively correlated in female bears during the fall season, with a trend in the spring, but not during any season for males. This suggests that habitat selection is a learned behaviour because males do not participate in parental care: a genetically predetermined behaviour (instinct would have resulted in habitat selection and relatedness correlations for both sexes. Geographic distance and home range overlap among animals did not alter correlations indicating that dispersal and spatial autocorrelation had little effect on the observed trends. These results suggest that habitat selection in grizzly bears are partly learned from their mothers, which could have implications for the translocation of wildlife to novel environments.
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Suicide prevention e-learning modules designed for gatekeepers: A descriptive review
Ghoncheh, R.; Kerkhof, A.; Koot, H.M.
2014-01-01
Background: E-learning modules can be a useful method for educating gatekeepers in suicide prevention and awareness. Aims: To review and provide an overview of e-learning modules on suicide prevention designed for gatekeepers and assess their effectiveness. Method: Two strategies were used. First,
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Joint Feature Selection and Classification for Multilabel Learning.
Huang, Jun; Li, Guorong; Huang, Qingming; Wu, Xindong
2018-03-01
Multilabel learning deals with examples having multiple class labels simultaneously. It has been applied to a variety of applications, such as text categorization and image annotation. A large number of algorithms have been proposed for multilabel learning, most of which concentrate on multilabel classification problems and only a few of them are feature selection algorithms. Current multilabel classification models are mainly built on a single data representation composed of all the features which are shared by all the class labels. Since each class label might be decided by some specific features of its own, and the problems of classification and feature selection are often addressed independently, in this paper, we propose a novel method which can perform joint feature selection and classification for multilabel learning, named JFSC. Different from many existing methods, JFSC learns both shared features and label-specific features by considering pairwise label correlations, and builds the multilabel classifier on the learned low-dimensional data representations simultaneously. A comparative study with state-of-the-art approaches manifests a competitive performance of our proposed method both in classification and feature selection for multilabel learning.
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Wijnia, Lisette; Loyens, Sofie M.; Derous, Eva; Schmidt, Henk G.
2015-01-01
In problem-based learning students are responsible for their own learning process, which becomes evident when they must act independently, for example, when selecting literature resources for individual study. It is a matter of debate whether it is better to have students select their own literature resources or to present them with a list of…
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Stol, Daphne M; Hollander, Monika; Nielen, Markus M J; Badenbroek, Ilse F; Schellevis, François G; de Wit, Niek J
2018-03-01
Current guidelines acknowledge the need for cardiometabolic disease (CMD) prevention and recommend five-yearly screening of a targeted population. In recent years programs for selective CMD-prevention have been developed, but implementation is challenging. The question arises if general practices are adequately prepared. Therefore, the aim of this study is to assess the organizational preparedness of Dutch general practices and the facilitators and barriers for performing CMD-prevention in practices currently implementing selective CMD-prevention. Observational study. Dutch primary care. General practices. Organizational characteristics. General practices implementing selective CMD-prevention are more often organized as a group practice (49% vs. 19%, p = .000) and are better organized regarding chronic disease management compared to reference practices. They are motivated for performing CMD-prevention and can be considered as 'frontrunners' of Dutch general practices with respect to their practice organization. The most important reported barriers are a limited availability of staff (59%) and inadequate funding (41%). The organizational infrastructure of Dutch general practices is considered adequate for performing most steps of selective CMD-prevention. Implementation of prevention programs including easily accessible lifestyle interventions needs attention. All stakeholders involved share the responsibility to realize structural funding for programmed CMD-prevention. Aforementioned conditions should be taken into account with respect to future implementation of selective CMD-prevention. Key Points There is need for adequate CMD prevention. Little is known about the organization of selective CMD prevention in general practices. • The organizational infrastructure of Dutch general practices is adequate for performing most steps of selective CMD prevention. • Implementation of selective CMD prevention programs including easily accessible
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Efficient abstraction selection in reinforcement learning
Seijen, H. van; Whiteson, S.; Kester, L.
2013-01-01
This paper introduces a novel approach for abstraction selection in reinforcement learning problems modelled as factored Markov decision processes (MDPs), for which a state is described via a set of state components. In abstraction selection, an agent must choose an abstraction from a set of
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Selective Mutism: A Three-Tiered Approach to Prevention and Intervention
Busse, R. T.; Downey, Jenna
2011-01-01
Selective mutism is a rare anxiety disorder that prevents a child from speaking at school or other community settings, and can be detrimental to a child's social development. School psychologists can play an important role in the prevention and treatment of selective mutism. As an advocate for students, school psychologists can work with teachers,…
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Robot soccer action selection based on Q learning
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
This paper researches robot soccer action selection based on Q learning . The robot learn to activate particular behavior given their current situation and reward signal. We adopt neural network to implementations of Q learning for their generalization properties and limited computer memory requirements
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Novel Automatic Filter-Class Feature Selection for Machine Learning Regression
DEFF Research Database (Denmark)
Wollsen, Morten Gill; Hallam, John; Jørgensen, Bo Nørregaard
2017-01-01
With the increased focus on application of Big Data in all sectors of society, the performance of machine learning becomes essential. Efficient machine learning depends on efficient feature selection algorithms. Filter feature selection algorithms are model-free and therefore very fast, but require...... model in the feature selection process. PCA is often used in machine learning litterature and can be considered the default feature selection method. RDESF outperformed PCA in both experiments in both prediction error and computational speed. RDESF is a new step into filter-based automatic feature...
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Rapid e-Learning Tools Selection Process for Cognitive and Psychomotor Learning Objectives
Ku, David Tawei; Huang, Yung-Hsin
2012-01-01
This study developed a decision making process for the selection of rapid e-learning tools that could match different learning domains. With the development of the Internet, the speed of information updates has become faster than ever. E-learning has rapidly become the mainstream for corporate training and academic instruction. In order to reduce…
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Feature and Region Selection for Visual Learning.
Zhao, Ji; Wang, Liantao; Cabral, Ricardo; De la Torre, Fernando
2016-03-01
Visual learning problems, such as object classification and action recognition, are typically approached using extensions of the popular bag-of-words (BoWs) model. Despite its great success, it is unclear what visual features the BoW model is learning. Which regions in the image or video are used to discriminate among classes? Which are the most discriminative visual words? Answering these questions is fundamental for understanding existing BoW models and inspiring better models for visual recognition. To answer these questions, this paper presents a method for feature selection and region selection in the visual BoW model. This allows for an intermediate visualization of the features and regions that are important for visual learning. The main idea is to assign latent weights to the features or regions, and jointly optimize these latent variables with the parameters of a classifier (e.g., support vector machine). There are four main benefits of our approach: 1) our approach accommodates non-linear additive kernels, such as the popular χ(2) and intersection kernel; 2) our approach is able to handle both regions in images and spatio-temporal regions in videos in a unified way; 3) the feature selection problem is convex, and both problems can be solved using a scalable reduced gradient method; and 4) we point out strong connections with multiple kernel learning and multiple instance learning approaches. Experimental results in the PASCAL VOC 2007, MSR Action Dataset II and YouTube illustrate the benefits of our approach.
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McMurray, Bob; Horst, Jessica S.; Samuelson, Larissa K.
2013-01-01
Classic approaches to word learning emphasize the problem of referential ambiguity: in any naming situation the referent of a novel word must be selected from many possible objects, properties, actions, etc. To solve this problem, researchers have posited numerous constraints, and inference strategies, but assume that determining the referent of a novel word is isomorphic to learning. We present an alternative model in which referent selection is an online process that is independent of long-term learning. This two timescale approach creates significant power in the developing system. We illustrate this with a dynamic associative model in which referent selection is simulated as dynamic competition between competing referents, and learning is simulated using associative (Hebbian) learning. This model can account for a range of findings including the delay in expressive vocabulary relative to receptive vocabulary, learning under high degrees of referential ambiguity using cross-situational statistics, accelerating (vocabulary explosion) and decelerating (power-law) learning rates, fast-mapping by mutual exclusivity (and differences in bilinguals), improvements in familiar word recognition with development, and correlations between individual differences in speed of processing and learning. Five theoretical points are illustrated. 1) Word learning does not require specialized processes – general association learning buttressed by dynamic competition can account for much of the literature. 2) The processes of recognizing familiar words are not different than those that support novel words (e.g., fast-mapping). 3) Online competition may allow the network (or child) to leverage information available in the task to augment performance or behavior despite what might be relatively slow learning or poor representations. 4) Even associative learning is more complex than previously thought – a major contributor to performance is the pruning of incorrect associations
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Service-Learning in Higher Education: Focus on Eating Disorder Prevention
Roofe, Nina; Brinegar, Jennifer; Seymour, Gayle
2015-01-01
Interdisciplinary service-learning projects are mutually beneficial for communities and students. This service-learning project focused on eating disorder prevention and involved students majoring in nutrition, art, and psychology at a public Southern university. The nutrition majors completed the Eating Attitudes Test before and after the…
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Suicide prevention e-learning modules designed for gatekeepers: a descriptive review.
Ghoncheh, Rezvan; Koot, Hans M; Kerkhof, Ad J F M
2014-01-01
E-learning modules can be a useful method for educating gatekeepers in suicide prevention and awareness. To review and provide an overview of e-learning modules on suicide prevention designed for gatekeepers and assess their effectiveness. Two strategies were used. First, articles were systematically searched in databases of PubMed, Web of Science, and PsycINFO. Second, Google search was used to find e-learning modules on the Web. The literature search resulted in 448 papers, of which none met the inclusion criteria of this study. The Google search resulted in 130 hits, of which 23 met the inclusion criteria of this review. Organizations that owned the modules were contacted, of which 13 responded and nine were included in this study. The effectiveness of two e-learning modules is currently being tested in a randomized controlled trial (RCT), one organization is planning to test the effectiveness of their module, and one organization has compared their face-to-face training with their online training. Furthermore, the included modules have different characteristics. There is a need for RCTs to study the effectiveness of online modules in this area and to understand which characteristics are essential to create effective e-learning modules to educate gatekeepers in suicide prevention.
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Selection of appropriates E-learning personalization strategies from ontological perspectives
Directory of Open Access Journals (Sweden)
Fathi Essalmi
2010-10-01
Full Text Available When there are several personalization strategies of E-learning, authors of courses need to be supported for deciding which strategy will be applied for personalizing each course. In fact, the time, the efforts and the learning objects needed for preparing personalized learning scenarios depend on the personalization strategy to be applied. This paper presents an approach for selecting personalization strategies according to the feasibility of generating personalized learning scenarios with minimal intervention of the author. Several metrics are proposed for putting in order and selecting useful personalization strategies. The calculus of these metrics is automated based on the analyses of the LOM (Learning Object Metadata standard according to the semantic relations between data elements and learners’ characteristics represented in the Ontology for Selection of Personalization Strategies (OSPS.
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Computerized adaptive testing item selection in computerized adaptive learning systems
Eggen, Theodorus Johannes Hendrikus Maria; Eggen, T.J.H.M.; Veldkamp, B.P.
2012-01-01
Item selection methods traditionally developed for computerized adaptive testing (CAT) are explored for their usefulness in item-based computerized adaptive learning (CAL) systems. While in CAT Fisher information-based selection is optimal, for recovering learning populations in CAL systems item
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Embedded Incremental Feature Selection for Reinforcement Learning
2012-05-01
Prior to this work, feature selection for reinforce- ment learning has focused on linear value function ap- proximation ( Kolter and Ng, 2009; Parr et al...InProceed- ings of the the 23rd International Conference on Ma- chine Learning, pages 449–456. Kolter , J. Z. and Ng, A. Y. (2009). Regularization and feature
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Learning a New Selection Rule in Visual and Frontal Cortex.
van der Togt, Chris; Stănişor, Liviu; Pooresmaeili, Arezoo; Albantakis, Larissa; Deco, Gustavo; Roelfsema, Pieter R
2016-08-01
How do you make a decision if you do not know the rules of the game? Models of sensory decision-making suggest that choices are slow if evidence is weak, but they may only apply if the subject knows the task rules. Here, we asked how the learning of a new rule influences neuronal activity in the visual (area V1) and frontal cortex (area FEF) of monkeys. We devised a new icon-selection task. On each day, the monkeys saw 2 new icons (small pictures) and learned which one was relevant. We rewarded eye movements to a saccade target connected to the relevant icon with a curve. Neurons in visual and frontal cortex coded the monkey's choice, because the representation of the selected curve was enhanced. Learning delayed the neuronal selection signals and we uncovered the cause of this delay in V1, where learning to select the relevant icon caused an early suppression of surrounding image elements. These results demonstrate that the learning of a new rule causes a transition from fast and random decisions to a more considerate strategy that takes additional time and they reveal the contribution of visual and frontal cortex to the learning process. © The Author 2016. Published by Oxford University Press.
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Assessing the effectiveness of problem-based learning of preventive medicine education in China.
Ding, Xiaojie; Zhao, Liping; Chu, Haiyan; Tong, Na; Ni, Chunhui; Hu, Zhibin; Zhang, Zhengdong; Wang, Meilin
2014-05-30
Problem-based learning (PBL) is defined as a student-centered pedagogy which can provide learners more opportunities for application of knowledge acquired from basic science to the working situations than traditional lecture-based learning (LBL) method. In China, PBL is increasingly popular among preventive medicine educators, and multiple studies have investigated the effectiveness of PBL pedagogy in preventive medicine education. A pooled analysis based on 15 studies was performed to obtain an overall estimate of the effectiveness of PBL on learning outcomes of preventive medicine. Overall, PBL was associated with a significant increase in students' theoretical examination scores (SMD = 0.62, 95% CI = 0.41-0.83) than LBL. For the attitude- and skill-based outcomes, the pooled PBL effects were also significant among learning attitude (OR = 3.62, 95% CI = 2.40-5.16), problem solved skill (OR = 4.80, 95% CI = 2.01-11.46), self-directed learning skill (OR = 5.81, 95% CI = 3.11-10.85), and collaborative skill (OR = 4.21, 95% CI = 0.96-18.45). Sensitivity analysis showed that the exclusion of a single study did not influence the estimation. Our results suggest that PBL of preventive medicine education in China appears to be more effective than LBL in improving knowledge, attitude and skills.
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Bioinspired Architecture Selection for Multitask Learning
Directory of Open Access Journals (Sweden)
Andrés Bueno-Crespo
2017-06-01
Full Text Available Faced with a new concept to learn, our brain does not work in isolation. It uses all previously learned knowledge. In addition, the brain is able to isolate the knowledge that does not benefit us, and to use what is actually useful. In machine learning, we do not usually benefit from the knowledge of other learned tasks. However, there is a methodology called Multitask Learning (MTL, which is based on the idea that learning a task along with other related tasks produces a transfer of information between them, what can be advantageous for learning the first one. This paper presents a new method to completely design MTL architectures, by including the selection of the most helpful subtasks for the learning of the main task, and the optimal network connections. In this sense, the proposed method realizes a complete design of the MTL schemes. The method is simple and uses the advantages of the Extreme Learning Machine to automatically design a MTL machine, eliminating those factors that hinder, or do not benefit, the learning process of the main task. This architecture is unique and it is obtained without testing/error methodologies that increase the computational complexity. The results obtained over several real problems show the good performances of the designed networks with this method.
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System Quality Characteristics for Selecting Mobile Learning Applications
Directory of Open Access Journals (Sweden)
Mohamed SARRAB
2015-10-01
Full Text Available The majority of M-learning (Mobile learning applications available today are developed for the formal learning and education environment. These applications are characterized by the improvement in the interaction between learners and instructors to provide high interaction and flexibility to the learning process. M-learning is gaining increased recognition and adoption by different organizations. With the high number of M-learning applications available today, making the right decision about which, application to choose can be quite challenging. To date there is no complete and well defined set of system characteristics for such M-learning applications. This paper presents system quality characteristics for selecting M-learning applications based on the result of a systematic review conducted in this domain.
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Development of an HIV Prevention Videogame: Lessons Learned
Directory of Open Access Journals (Sweden)
Kimberly Hieftje
2016-06-01
Full Text Available The use of videogames interventions is becoming an increasingly popular and effective strategy in disease prevention and health promotion; however, few health videogame interventions have been scientifically rigorously evaluated for their efficacy. Moreover, few examples of the formative process used to develop and evaluate evidence-based health videogame interventions exist in the scientific literature. The following paper provides valuable insight into the lessons learned during the process of developing the risk reduction and HIV prevention videogame intervention for young adolescents, PlayForward: Elm City Stories.
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Erickson, Lucy C; Thiessen, Erik D; Godwin, Karrie E; Dickerson, John P; Fisher, Anna V
2015-10-01
Selective sustained attention is vital for higher order cognition. Although endogenous and exogenous factors influence selective sustained attention, assessment of the degree to which these factors influence performance and learning is often challenging. We report findings from the Track-It task, a paradigm that aims to assess the contribution of endogenous and exogenous factors to selective sustained attention within the same task. Behavioral accuracy and eye-tracking data on the Track-It task were correlated with performance on an explicit learning task. Behavioral accuracy and fixations to distractors during the Track-It task did not predict learning when exogenous factors supported selective sustained attention. In contrast, when endogenous factors supported selective sustained attention, fixations to distractors were negatively correlated with learning. Similarly, when endogenous factors supported selective sustained attention, higher behavioral accuracy was correlated with greater learning. These findings suggest that endogenously and exogenously driven selective sustained attention, as measured through different conditions of the Track-It task, may support different kinds of learning. Copyright © 2015 Elsevier Inc. All rights reserved.
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The Value of E-Learning for the Prevention of Healthcare-Associated Infections.
Labeau, Sonia O; Rello, Jordi; Dimopoulos, George; Lipman, Jeffrey; Sarikaya, Aklime; Oztürk, Candan; Vandijck, Dominique M; Vogelaers, Dirk; Vandewoude, Koenraad; Blot, Stijn I
2016-09-01
BACKGROUND Healthcare workers (HCWs) lack familiarity with evidence-based guidelines for the prevention of healthcare-associated infections (HAIs). There is good evidence that effective educational interventions help to facilitate guideline implementation, so we investigated whether e-learning could enhance HCW knowledge of HAI prevention guidelines. METHODS We developed an electronic course (e-course) and tested its usability and content validity. An international sample of voluntary learners submitted to a pretest (T0) that determined their baseline knowledge of guidelines, and they subsequently studied the e-course. Immediately after studying the course, posttest 1 (T1) assessed the immediate learning effect. After 3 months, during which participants had no access to the course, a second posttest (T2) evaluated the residual learning effect. RESULTS A total of 3,587 HCWs representing 79 nationalities enrolled: 2,590 HCWs (72%) completed T0; 1,410 HCWs (39%) completed T1; and 1,011 HCWs (28%) completed T2. The median study time was 193 minutes (interquartile range [IQR], 96-306 minutes) The median scores were 52% (IQR, 44%-62%) for T0, 80% (IQR, 68%-88%) for T1, and 74% (IQR, 64%-84%) for T2. The immediate learning effect (T0 vs T1) was +24% (IQR, 12%-34%; P300 minutes yielded the greatest residual effect (24%). CONCLUSIONS Moderate time invested in e-learning yielded significant immediate and residual learning effects. Decision makers could consider promoting e-learning as a supporting tool in HAI prevention. Infect Control Hosp Epidemiol 2016;37:1052-1059.
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Pollution prevention program for new projects -- Lessons learned
Energy Technology Data Exchange (ETDEWEB)
Lum, J. [Dept. of Energy, Washington, DC (United States)
1993-03-01
The purpose of this presentation is to relay the experience of the Office of New Production Reactors (NP) in developing and implementing its pollution prevention program. NP was established to plan, design, and construct a new safe and environmentally acceptable nuclear reactor capacity necessary to provide an assured supply of tritium to maintain the nation`s long-term deterrent capability. The Program offered the Department of Energy an opportunity to demonstrate its commitment to environmental protection via minimization of environmental releases; new design offers the best opportunity for pollution prevention. The NP pollution prevention program was never fully implemented because NP`s tritium production design activity was recovery terminated. The information in this paper represented lessons learned from the last three years of NP operation.
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Knowledge sharing and organizational learning in the context of hospital infection prevention.
Rangachari, Pavani
2010-01-01
Recently, hospitals that have been successful in preventing infections have labeled their improvement approaches as either the Toyota Production System (TPS) approach or the Positive Deviance (PD) approach. PD has been distinguished from TPS as being a bottom-up approach to improvement, as against top-down. Facilities that have employed both approaches have suggested that PD may be more effective than TPS for infection prevention. This article integrates organizational learning, institutional, and knowledge network theories to develop a theoretical framework for understanding the structure and evolution of effective knowledge-sharing networks in health care organizations, that is, networks most conducive to learning and improvement. Contrary to arguments put forth by hospital success stories, the framework suggests that networks rich in brokerage and hierarchy (ie, top-down, "TPS-like" structures) may be more effective for learning and improvement in health care organizations, compared with a networks rich in density (ie, bottom-up, "PD-like" structures). The theoretical framework and ensuing analysis help identify several gaps in the literature related to organization learning and improvement in the infection prevention context. This, in turn, helps put forth recommendations for health management research and practice.
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Adult Learners' Preferred Methods of Learning Preventative Heart Disease Care
Alavi, Nasim
2016-01-01
The purpose of this study was to investigate the preferred method of learning about heart disease by adult learners. This research study also investigated if there was a statistically significant difference between race/ethnicity, age, and gender of adult learners and their preferred method of learning preventative heart disease care. This…
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Fernández Río, Francisco Javier; Cecchini Estrada, José Antonio; Méndez Giménez, Antonio; Prieto Saborit, José Antonio
2017-01-01
Learning to learn and learning to cooperate are two important goals for individuals. Moreover, self regulation has been identified as fundamental to prevent school failure. The goal of the present study was to assess the interactions between self-regulated learning, cooperative learning and academic self-efficacy in secondary education students experiencing cooperative learning as the main pedagogical approach for at least one school year. 2.513 secondary education students (1.308 males, 1.20...
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Serial Entrepreneurship, Learning by Doing and Self-selection
DEFF Research Database (Denmark)
Rocha, Vera; Carneiro, Anabela; Varum, Celeste
2015-01-01
of the person-specific effect, using information on individuals’ past histories in paid employment, confirm that serial entrepreneurs exhibit, on average, a larger person-specific effect than non-serial business owners. Moreover, ignoring serial entrepreneurs’ self-selection overestimates learning by doing......It remains a question whether serial entrepreneurs typically perform better than their novice counterparts owing to learning by doing effects or mostly because they are a selected sample of higher-than-average ability entrepreneurs. This paper tries to unravel these two effects by exploring a novel...... empirical strategy based on continuous time duration models with selection. We use a large longitudinal matched employer-employee dataset that allows us to identify about 220,000 individuals who have left their first entrepreneurial experience, out of which over 35,000 became serial entrepreneurs. We...
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Learning for Climate Change Adaptation among Selected ...
African Journals Online (AJOL)
Learning for Climate Change Adaptation among Selected Communities of Lusaka ... This research was aimed at surveying perceptions of climate change and ... This work is licensed under a Creative Commons Attribution 3.0 License.
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Automatic learning-based beam angle selection for thoracic IMRT
International Nuclear Information System (INIS)
Amit, Guy; Marshall, Andrea; Purdie, Thomas G.; Jaffray, David A.; Levinshtein, Alex; Hope, Andrew J.; Lindsay, Patricia; Pekar, Vladimir
2015-01-01
Purpose: The treatment of thoracic cancer using external beam radiation requires an optimal selection of the radiation beam directions to ensure effective coverage of the target volume and to avoid unnecessary treatment of normal healthy tissues. Intensity modulated radiation therapy (IMRT) planning is a lengthy process, which requires the planner to iterate between choosing beam angles, specifying dose–volume objectives and executing IMRT optimization. In thorax treatment planning, where there are no class solutions for beam placement, beam angle selection is performed manually, based on the planner’s clinical experience. The purpose of this work is to propose and study a computationally efficient framework that utilizes machine learning to automatically select treatment beam angles. Such a framework may be helpful for reducing the overall planning workload. Methods: The authors introduce an automated beam selection method, based on learning the relationships between beam angles and anatomical features. Using a large set of clinically approved IMRT plans, a random forest regression algorithm is trained to map a multitude of anatomical features into an individual beam score. An optimization scheme is then built to select and adjust the beam angles, considering the learned interbeam dependencies. The validity and quality of the automatically selected beams evaluated using the manually selected beams from the corresponding clinical plans as the ground truth. Results: The analysis included 149 clinically approved thoracic IMRT plans. For a randomly selected test subset of 27 plans, IMRT plans were generated using automatically selected beams and compared to the clinical plans. The comparison of the predicted and the clinical beam angles demonstrated a good average correspondence between the two (angular distance 16.8° ± 10°, correlation 0.75 ± 0.2). The dose distributions of the semiautomatic and clinical plans were equivalent in terms of primary target volume
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Zeng, Xueqiang; Luo, Gang
2017-12-01
Machine learning is broadly used for clinical data analysis. Before training a model, a machine learning algorithm must be selected. Also, the values of one or more model parameters termed hyper-parameters must be set. Selecting algorithms and hyper-parameter values requires advanced machine learning knowledge and many labor-intensive manual iterations. To lower the bar to machine learning, miscellaneous automatic selection methods for algorithms and/or hyper-parameter values have been proposed. Existing automatic selection methods are inefficient on large data sets. This poses a challenge for using machine learning in the clinical big data era. To address the challenge, this paper presents progressive sampling-based Bayesian optimization, an efficient and automatic selection method for both algorithms and hyper-parameter values. We report an implementation of the method. We show that compared to a state of the art automatic selection method, our method can significantly reduce search time, classification error rate, and standard deviation of error rate due to randomization. This is major progress towards enabling fast turnaround in identifying high-quality solutions required by many machine learning-based clinical data analysis tasks.
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Facilitators and barriers to students' learning in an obesity prevention graduate program.
Do, Kieu Anh; Anderson-Knott, Mindy; de Guzman, Maria Rosario T; Boeckner, Linda; Koszewski, Wanda
2018-01-01
Childhood obesity is a major public health concern with underpinnings at the individual, family, community and societal levels. The Transdisciplinary Childhood Obesity Prevention Graduate Certificate Program (TOP) is an innovative graduate-level certificate program developed to train professionals to understand and address obesity from multiple perspectives using an interprofessional education (IPE) approach. Currently, there is limited knowledge on what promotes or hinders learning in IPE approaches dealing with obesity prevention. The goal of this report is to address this gap by describing facilitators and barriers to learning in a graduate-level training program. Using a qualitative research design, semi-structured interviews were collected from 23 professional students, as part of a larger program evaluation project for TOP. Thematic analysis revealed the challenges and strengths of the program that relate specifically to: its interprofessional approach, its structure, and its activities. Interprofessional exchanges were reported to expand students' learning, but adequate interprofessional representation must be maintained, and the complexity of interprofessional collaborations must also be well-coordinated. Standardising the program structure and courses for consistency across professions, and clear communication are critical to program success. Findings add to the existing literature on what promotes effective learning in a professional obesity prevention program using an IPE approach.
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Statistical learning and selective inference.
Taylor, Jonathan; Tibshirani, Robert J
2015-06-23
We describe the problem of "selective inference." This addresses the following challenge: Having mined a set of data to find potential associations, how do we properly assess the strength of these associations? The fact that we have "cherry-picked"--searched for the strongest associations--means that we must set a higher bar for declaring significant the associations that we see. This challenge becomes more important in the era of big data and complex statistical modeling. The cherry tree (dataset) can be very large and the tools for cherry picking (statistical learning methods) are now very sophisticated. We describe some recent new developments in selective inference and illustrate their use in forward stepwise regression, the lasso, and principal components analysis.
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Genetic tests in work place from the preventive selection to selective prevention
International Nuclear Information System (INIS)
Poissonnet, C.M.; Veron, M.
2004-01-01
The research in this area allows to better understand the mechanisms of illness trigger, to improve the knowledge in the relation exposure-illness, to detect the risk associated to low exposure among some particularly sensitive persons and to define the validity criteria. Inevitably these researches reach to define the most vulnerable persons. This designation could be a factor favorable to the prevention and to give a better sense of responsibility. The worker, well informed, can be particularly concerned by wearing the individual protections, and the person in charge of the installation by looking to reduce exposure. It can be also deviate and corresponds to a real discrimination with rejection of sensitive persons and selection of resistant individuals with which it could be possible to work in non optimal conditions. The problem is at this level the conflicts of interest exist between these ones that dream to use this possibility wisely and that ones for which the interests are elsewhere. (N.C.)
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Selenium and Vitamin E Cancer Prevention Trial (SELECT): Questions and Answers
... Prostate Cancer Prostate Cancer Screening Research Selenium and Vitamin E Cancer Prevention Trial (SELECT): Questions and Answers On ... of prostate cancer mean to men who take vitamin E but who were not SELECT participants? The incidence ...
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Best, Catherine A.; Yim, Hyungwook; Sloutsky, Vladimir M.
2013-01-01
Selective attention plays an important role in category learning. However, immaturities of top-down attentional control during infancy coupled with successful category learning suggest that early category learning is achieved without attending selectively. Research presented here examines this possibility by focusing on category learning in infants (6–8 months old) and adults. Participants were trained on a novel visual category. Halfway through the experiment, unbeknownst to participants, the to-be-learned category switched to another category, where previously relevant features became irrelevant and previously irrelevant features became relevant. If participants attend selectively to the relevant features of the first category, they should incur a cost of selective attention immediately after the unknown category switch. Results revealed that adults demonstrated a cost, as evidenced by a decrease in accuracy and response time on test trials as well as a decrease in visual attention to newly relevant features. In contrast, infants did not demonstrate a similar cost of selective attention as adults despite evidence of learning both to-be-learned categories. Findings are discussed as supporting multiple systems of category learning and as suggesting that learning mechanisms engaged by adults may be different from those engaged by infants. PMID:23773914
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Drupsteen, L.; Groeneweg, J.; Zwetsloot, G.I.J.M.
2013-01-01
Many incidents have occurred because organisations have failed to learn from lessons of the past. This means that there is room for improvement in the way organisations analyse incidents, generate measures to remedy identified weaknesses and prevent reoccurrence: the learning from incidents process.
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Service-Learning. National Dropout Prevention Center/Network Newsletter. Volume 22, Number 4
Duckenfield, Marty, Ed.
2011-01-01
The "National Dropout Prevention Newsletter" is published quarterly by the National Dropout Prevention Center/Network. This issue contains the following articles: (1) Dropouts and Democracy (Robert Shumer); (2) 2011 NDPN Crystal Star Winners; (3) Service-Learning as Dropout Intervention and More (Michael VanKeulen); and (4) Teacher…
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College Teaching and Community Outreaching: Service Learning in an Obesity Prevention Program
Himelein, Melissa; Passman, Liz; Phillips, Jessica M.
2010-01-01
Background: Service learning can enrich students' knowledge, skills and commitment to occupational goals while positively affecting communities. Undergraduate students in a course on obesity engaged in service learning by assisting with a family-based obesity prevention program, Getting Into Fitness Together (GIFT). Purpose: The impact of GIFT on…
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Pairwise Constraint-Guided Sparse Learning for Feature Selection.
Liu, Mingxia; Zhang, Daoqiang
2016-01-01
Feature selection aims to identify the most informative features for a compact and accurate data representation. As typical supervised feature selection methods, Lasso and its variants using L1-norm-based regularization terms have received much attention in recent studies, most of which use class labels as supervised information. Besides class labels, there are other types of supervised information, e.g., pairwise constraints that specify whether a pair of data samples belong to the same class (must-link constraint) or different classes (cannot-link constraint). However, most of existing L1-norm-based sparse learning methods do not take advantage of the pairwise constraints that provide us weak and more general supervised information. For addressing that problem, we propose a pairwise constraint-guided sparse (CGS) learning method for feature selection, where the must-link and the cannot-link constraints are used as discriminative regularization terms that directly concentrate on the local discriminative structure of data. Furthermore, we develop two variants of CGS, including: 1) semi-supervised CGS that utilizes labeled data, pairwise constraints, and unlabeled data and 2) ensemble CGS that uses the ensemble of pairwise constraint sets. We conduct a series of experiments on a number of data sets from University of California-Irvine machine learning repository, a gene expression data set, two real-world neuroimaging-based classification tasks, and two large-scale attribute classification tasks. Experimental results demonstrate the efficacy of our proposed methods, compared with several established feature selection methods.
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Best, Catherine A; Yim, Hyungwook; Sloutsky, Vladimir M
2013-10-01
Selective attention plays an important role in category learning. However, immaturities of top-down attentional control during infancy coupled with successful category learning suggest that early category learning is achieved without attending selectively. Research presented here examines this possibility by focusing on category learning in infants (6-8months old) and adults. Participants were trained on a novel visual category. Halfway through the experiment, unbeknownst to participants, the to-be-learned category switched to another category, where previously relevant features became irrelevant and previously irrelevant features became relevant. If participants attend selectively to the relevant features of the first category, they should incur a cost of selective attention immediately after the unknown category switch. Results revealed that adults demonstrated a cost, as evidenced by a decrease in accuracy and response time on test trials as well as a decrease in visual attention to newly relevant features. In contrast, infants did not demonstrate a similar cost of selective attention as adults despite evidence of learning both to-be-learned categories. Findings are discussed as supporting multiple systems of category learning and as suggesting that learning mechanisms engaged by adults may be different from those engaged by infants. Copyright © 2013 Elsevier Inc. All rights reserved.
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Development of an HIV Prevention Videogame: Lessons Learned
Kimberly Hieftje; Lynn E. Fiellin; Tyra Pendergrass; Lindsay R Duncan
2016-01-01
The use of videogames interventions is becoming an increasingly popular and effective strategy in disease prevention and health promotion; however, few health videogame interventions have been scientifically rigorously evaluated for their efficacy. Moreover, few examples of the formative process used to develop and evaluate evidence-based health videogame interventions exist in the scientific literature. The following paper provides valuable insight into the lessons learned during the process...
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Mobile Augmented Reality as Usability to Enhance Nurse Prevent Violence Learning Satisfaction.
Hsu, Han-Jen; Weng, Wei-Kai; Chou, Yung-Lang; Huang, Pin-Wei
2018-01-01
Violence in hospitals, nurses are at high risk of patient's aggression in the workplace. This learning course application Mobile Augmented Reality to enhance nurse to prevent violence skill. Increasingly, mobile technologies introduced and integrated into classroom teaching and clinical applications. Improving the quality of learning course and providing new experiences for nurses.
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A calpain-2 selective inhibitor enhances learning & memory by prolonging ERK activation.
Liu, Yan; Wang, Yubin; Zhu, Guoqi; Sun, Jiandong; Bi, Xiaoning; Baudry, Michel
2016-06-01
While calpain-1 activation is required for LTP induction by theta burst stimulation (TBS), calpain-2 activation limits its magnitude during the consolidation period. A selective calpain-2 inhibitor applied either before or shortly after TBS enhanced the degree of potentiation. In the present study, we tested whether the selective calpain-2 inhibitor, Z-Leu-Abu-CONH-CH2-C6H3 (3, 5-(OMe)2 (C2I), could enhance learning and memory in wild-type (WT) and calpain-1 knock-out (C1KO) mice. We first showed that C2I could reestablish TBS-LTP in hippocampal slices from C1KO mice, and this effect was blocked by PD98059, an inhibitor of ERK. TBS resulted in PTEN degradation in hippocampal slices from both WT and C1KO mice, and C2I treatment blocked this effect in both mouse genotypes. Systemic injection of C2I 30 min before training in the fear-conditioning paradigm resulted in a biphasic dose-response curve, with low doses enhancing and high doses inhibiting freezing behavior. The difference between the doses needed to enhance and inhibit learning matches the difference in concentrations producing inhibition of calpain-2 and calpain-1. A low dose of C2I also restored normal learning in a novel object recognition task in C1KO mice. Levels of SCOP, a ERK phosphatase known to be cleaved by calpain-1, were decreased in dorsal hippocampus early but not late following training in WT mice; C2I treatment did not affect the early decrease in SCOP levels but prevented its recovery at the later time-point and prolonged ERK activation. The results indicate that calpain-2 activation limits the extent of learning, an effect possibly due to temporal limitation of ERK activation, as a result of SCOP synthesis induced by calpain-2-mediated PTEN degradation. Copyright © 2016 Elsevier Ltd. All rights reserved.
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Is it better to select or to receive? Learning via active and passive hypothesis testing.
Markant, Douglas B; Gureckis, Todd M
2014-02-01
People can test hypotheses through either selection or reception. In a selection task, the learner actively chooses observations to test his or her beliefs, whereas in reception tasks data are passively encountered. People routinely use both forms of testing in everyday life, but the critical psychological differences between selection and reception learning remain poorly understood. One hypothesis is that selection learning improves learning performance by enhancing generic cognitive processes related to motivation, attention, and engagement. Alternatively, we suggest that differences between these 2 learning modes derives from a hypothesis-dependent sampling bias that is introduced when a person collects data to test his or her own individual hypothesis. Drawing on influential models of sequential hypothesis-testing behavior, we show that such a bias (a) can lead to the collection of data that facilitates learning compared with reception learning and (b) can be more effective than observing the selections of another person. We then report a novel experiment based on a popular category learning paradigm that compares reception and selection learning. We additionally compare selection learners to a set of "yoked" participants who viewed the exact same sequence of observations under reception conditions. The results revealed systematic differences in performance that depended on the learner's role in collecting information and the abstract structure of the problem.
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Community-based interventions for obesity prevention: lessons learned by Australian policy-makers
Directory of Open Access Journals (Sweden)
Haby Michelle M
2012-01-01
Full Text Available Abstract Background Interest in community-based interventions (CBIs for health promotion is increasing, with a lot of recent activity in the field. This paper aims, from a state government perspective, to examine the experience of funding and managing six obesity prevention CBIs, to identify lessons learned and to consider the implications for future investment. Specifically, we focus on the planning, government support, evaluation, research and workforce development required. Methods The lessons presented in this paper come from analysis of key project documents, the experience of the authors in managing the projects and from feedback obtained from key program stakeholders. Results CBIs require careful management, including sufficient planning time and clear governance structures. Selection of interventions should be based on evidence and tailored to local needs to ensure adequate penetration in the community. Workforce and community capacity must be assessed and addressed when selecting communities. Supporting the health promotion workforce to become adequately skilled and experienced in evaluation and research is also necessary before implementation. Comprehensive evaluation of future projects is challenging on both technical and affordability grounds. Greater emphasis may be needed on process evaluation complemented by organisation-level measures of impact and monitoring of nutrition and physical activity behaviours. Conclusions CBIs offer potential as one of a mix of approaches to obesity prevention. If successful approaches are to be expanded, care must be taken to incorporate lessons from existing and past projects. To do this, government must show strong leadership and work in partnership with the research community and local practitioners.
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Sultan, Sébastien; Rey, Nolwen; Sacquet, Joelle; Mandairon, Nathalie; Didier, Anne
2011-10-19
A role for newborn neurons in olfactory memory has been proposed based on learning-dependent modulation of olfactory bulb neurogenesis in adults. We hypothesized that if newborn neurons support memory, then they should be suppressed by memory erasure. Using an ecological approach in mice, we showed that behaviorally breaking a previously learned odor-reward association prematurely suppressed newborn neurons selected to survive during initial learning. Furthermore, intrabulbar infusions of the caspase pan-inhibitor ZVAD (benzyloxycarbonyl-Val-Ala-Asp) during the behavioral odor-reward extinction prevented newborn neurons death and erasure of the odor-reward association. Newborn neurons thus contribute to the bulbar network plasticity underlying long-term memory.
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Learning context conditions for BDI plan selection
Singh, D.; Sardina, S.; Padgham, L.; Airiau, S.; van der Hoek, W.; Kaminka, G.A.; Lespérance, Y.; Luck, M.; Sen, S.
2010-01-01
An important drawback to the popular Belief, Desire, and Intentions (BDI) paradigm is that such systems include no element of learning from experience. In particular, the so-called context conditions of plans, on which the whole model relies for plan selection, are restricted to be boolean formulas
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Stol, D.M.; Hollander, M.; Nielen, M.M.J.; Badenbroek, I.F.; Schellevis, F.G.; Wit, N.J. de
2018-01-01
Objective: Current guidelines acknowledge the need for cardiometabolic disease (CMD) prevention and recommend five-yearly screening of a targeted population. In recent years programs for selective CMD-prevention have been developed, but implementation is challenging. The question arises if general
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Fernandez-Rio, Javier; Cecchini, Jose A; Méndez-Gimenez, Antonio; Mendez-Alonso, David; Prieto, Jose A
2017-01-01
Learning to learn and learning to cooperate are two important goals for individuals. Moreover, self regulation has been identified as fundamental to prevent school failure. The goal of the present study was to assess the interactions between self-regulated learning, cooperative learning and academic self-efficacy in secondary education students experiencing cooperative learning as the main pedagogical approach for at least one school year. 2.513 secondary education students (1.308 males, 1.205 females), 12-17 years old ( M = 13.85, SD = 1.29), enrolled in 17 different schools belonging to the National Network of Schools on Cooperative Learning in Spain agreed to participate. They all had experienced this pedagogical approach a minimum of one school year. Participants were asked to complete the cooperative learning questionnaire, the strategies to control the study questionnaire and the global academic self-efficacy questionnaire. Participants were grouped based on their perceptions on cooperative learning and self-regulated learning in their classes. A combination of hierarchical and κ -means cluster analyses was used. Results revealed a four-cluster solution: cluster one included students with low levels of cooperative learning, self-regulated learning and academic self-efficacy, cluster two included students with high levels of cooperative learning, self-regulated learning and academic self-efficacy, cluster three included students with high levels of cooperative learning, low levels of self-regulated learning and intermediate-low levels of academic self-efficacy, and, finally, cluster four included students with high levels of self-regulated learning, low levels of cooperative learning, and intermediate-high levels of academic self-efficacy. Self-regulated learning was found more influential than cooperative learning on students' academic self-efficacy. In cooperative learning contexts students interact through different types of regulations: self, co, and
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Fernandez-Rio, Javier; Cecchini, Jose A.; Méndez-Gimenez, Antonio; Mendez-Alonso, David; Prieto, Jose A.
2017-01-01
Learning to learn and learning to cooperate are two important goals for individuals. Moreover, self regulation has been identified as fundamental to prevent school failure. The goal of the present study was to assess the interactions between self-regulated learning, cooperative learning and academic self-efficacy in secondary education students experiencing cooperative learning as the main pedagogical approach for at least one school year. 2.513 secondary education students (1.308 males, 1.205 females), 12–17 years old (M = 13.85, SD = 1.29), enrolled in 17 different schools belonging to the National Network of Schools on Cooperative Learning in Spain agreed to participate. They all had experienced this pedagogical approach a minimum of one school year. Participants were asked to complete the cooperative learning questionnaire, the strategies to control the study questionnaire and the global academic self-efficacy questionnaire. Participants were grouped based on their perceptions on cooperative learning and self-regulated learning in their classes. A combination of hierarchical and κ-means cluster analyses was used. Results revealed a four-cluster solution: cluster one included students with low levels of cooperative learning, self-regulated learning and academic self-efficacy, cluster two included students with high levels of cooperative learning, self-regulated learning and academic self-efficacy, cluster three included students with high levels of cooperative learning, low levels of self-regulated learning and intermediate-low levels of academic self-efficacy, and, finally, cluster four included students with high levels of self-regulated learning, low levels of cooperative learning, and intermediate-high levels of academic self-efficacy. Self-regulated learning was found more influential than cooperative learning on students’ academic self-efficacy. In cooperative learning contexts students interact through different types of regulations: self, co, and
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Selective Learning and Teaching among Japanese and German Children
Kim, Sunae; Paulus, Markus; Sodian, Beate; Itakura, Shoji; Ueno, Mika; Senju, Atsushi; Proust, Joëlle
2018-01-01
Despite an increasing number of studies demonstrating that young children selectively learn from others, and a few studies of children's selective teaching, the evidence almost exclusively comes from Western cultures, and cross-cultural comparison in this line of work is very rare. In the present research, we investigated Japanese and German…
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Trip Travel Time Forecasting Based on Selective Forgetting Extreme Learning Machine
Directory of Open Access Journals (Sweden)
Zhiming Gui
2014-01-01
Full Text Available Travel time estimation on road networks is a valuable traffic metric. In this paper, we propose a machine learning based method for trip travel time estimation in road networks. The method uses the historical trip information extracted from taxis trace data as the training data. An optimized online sequential extreme machine, selective forgetting extreme learning machine, is adopted to make the prediction. Its selective forgetting learning ability enables the prediction algorithm to adapt to trip conditions changes well. Experimental results using real-life taxis trace data show that the forecasting model provides an effective and practical way for the travel time forecasting.
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Feature Selection and Kernel Learning for Local Learning-Based Clustering.
Zeng, Hong; Cheung, Yiu-ming
2011-08-01
The performance of the most clustering algorithms highly relies on the representation of data in the input space or the Hilbert space of kernel methods. This paper is to obtain an appropriate data representation through feature selection or kernel learning within the framework of the Local Learning-Based Clustering (LLC) (Wu and Schölkopf 2006) method, which can outperform the global learning-based ones when dealing with the high-dimensional data lying on manifold. Specifically, we associate a weight to each feature or kernel and incorporate it into the built-in regularization of the LLC algorithm to take into account the relevance of each feature or kernel for the clustering. Accordingly, the weights are estimated iteratively in the clustering process. We show that the resulting weighted regularization with an additional constraint on the weights is equivalent to a known sparse-promoting penalty. Hence, the weights of those irrelevant features or kernels can be shrunk toward zero. Extensive experiments show the efficacy of the proposed methods on the benchmark data sets.
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Guided Learning at Workstations about Drug Prevention with Low Achievers in Science Education
Thomas, Heyne; Bogner, Franz X.
2012-01-01
Our study focussed on the cognitive achievement potential of low achieving eighth graders, dealing with drug prevention (cannabis). The learning process was guided by a teacher, leading this target group towards a modified learning at workstations which is seen as an appropriate approach for low achievers. We compared this specific open teaching…
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Panoz-Brown, Danielle; Carey, Lawrence M; Smith, Alexandra E; Gentry, Meredith; Sluka, Christina M; Corbin, Hannah E; Wu, Jie-En; Hohmann, Andrea G; Crystal, Jonathon D
2017-10-01
Chemotherapy is widely used to treat patients with systemic cancer. The efficacy of cancer therapies is frequently undermined by adverse side effects that have a negative impact on the quality of life of cancer survivors. Cancer patients who receive chemotherapy often experience chemotherapy-induced cognitive impairment across a variety of domains including memory, learning, and attention. In the current study, the impact of paclitaxel, a taxane derived chemotherapeutic agent, on episodic memory, prior learning, new learning, and reversal learning were evaluated in rats. Neurogenesis was quantified post-treatment in the dentate gyrus of the same rats using immunostaining for 5-Bromo-2'-deoxyuridine (BrdU) and Ki67. Paclitaxel treatment selectively impaired reversal learning while sparing episodic memory, prior learning, and new learning. Furthermore, paclitaxel-treated rats showed decreases in markers of hippocampal cell proliferation, as measured by markers of cell proliferation assessed using immunostaining for Ki67 and BrdU. This work highlights the importance of using multiple measures of learning and memory to identify the pattern of impaired and spared aspects of chemotherapy-induced cognitive impairment. Copyright © 2017 Elsevier Inc. All rights reserved.
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Kumar, David Devraj
2017-01-01
This paper reports an analysis of an interactive technology-supported, problem-based learning (PBL) project in science, technology, engineering and mathematics (STEM) from a Learning Sciences perspective using the Selected Learning Sciences Interest Areas (SLSIA). The SLSIA was adapted from the "What kinds of topics do ISLS [International…
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Feature selection is the ReliefF for multiple instance learning
Zafra, A.; Pechenizkiy, M.; Ventura, S.
2010-01-01
Dimensionality reduction and feature selection in particular are known to be of a great help for making supervised learning more effective and efficient. Many different feature selection techniques have been proposed for the traditional settings, where each instance is expected to have a label. In
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Preventing failure in distance learning: the use of Spector tool
Directory of Open Access Journals (Sweden)
Maciej Słomczyński
2012-12-01
Full Text Available In 2011 and 2012, University of Warsaw conducted a two-stage research which goals were: (1 to verify whether students’ access to information showing the characteristics of their learning organization is connected with a sense of efficacy, level of motivation, preferred learning forms and perceived teacher presence; (2 to examine the relations between organizational learning styles and the usage of Spector module. One of the means used in the project was introduction of a mechanism for teaching and learning management in an e-learning setting – Spector. This way, a support for prevention, diagnosis and learning failure therapy was introduced. The mechanism was implemented as a Moodle LMS extension. Its goal was to process activity reports gathered by Moodle and present them in an user-friendly way to both students and teachers. The first-stage research results did not confirm the correlation between mentioned variables, although the majority of students taking part in the research pointed out Spector’s importance to improving their motivation and planning their learning activities. Resolving of all the doubts set in the project required a further, more complex study (including organizational learning styles. The second stage of the research proved that students’ opinion about the usage of Spector is related to their current studies programme (Bachelor’s, Master’s or Doctoral.
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Manouselis, Nikos; Sampson, Demetrios
This paper focuses on the way a multi-criteria decision making methodology is applied in the case of agent-based selection of offered learning objects. The problem of selection is modeled as a decision making one, with the decision variables being the learner model and the learning objects' educational description. In this way, selection of…
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Code-specific learning rules improve action selection by populations of spiking neurons.
Friedrich, Johannes; Urbanczik, Robert; Senn, Walter
2014-08-01
Population coding is widely regarded as a key mechanism for achieving reliable behavioral decisions. We previously introduced reinforcement learning for population-based decision making by spiking neurons. Here we generalize population reinforcement learning to spike-based plasticity rules that take account of the postsynaptic neural code. We consider spike/no-spike, spike count and spike latency codes. The multi-valued and continuous-valued features in the postsynaptic code allow for a generalization of binary decision making to multi-valued decision making and continuous-valued action selection. We show that code-specific learning rules speed up learning both for the discrete classification and the continuous regression tasks. The suggested learning rules also speed up with increasing population size as opposed to standard reinforcement learning rules. Continuous action selection is further shown to explain realistic learning speeds in the Morris water maze. Finally, we introduce the concept of action perturbation as opposed to the classical weight- or node-perturbation as an exploration mechanism underlying reinforcement learning. Exploration in the action space greatly increases the speed of learning as compared to exploration in the neuron or weight space.
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Brants, Marijke; Bulthé, Jessica; Daniels, Nicky; Wagemans, Johan; Op de Beeck, Hans P
2016-02-15
Visual object perception is an important function in primates which can be fine-tuned by experience, even in adults. Which factors determine the regions and the neurons that are modified by learning is still unclear. Recently, it was proposed that the exact cortical focus and distribution of learning effects might depend upon the pre-learning mapping of relevant functional properties and how this mapping determines the informativeness of neural units for the stimuli and the task to be learned. From this hypothesis we would expect that visual experience would strengthen the pre-learning distributed functional map of the relevant distinctive object properties. Here we present a first test of this prediction in twelve human subjects who were trained in object categorization and differentiation, preceded and followed by a functional magnetic resonance imaging session. Specifically, training increased the distributed multi-voxel pattern information for trained object distinctions in object-selective cortex, resulting in a generalization from pre-training multi-voxel activity patterns to after-training activity patterns. Simulations show that the increased selectivity combined with the inter-session generalization is consistent with a training-induced strengthening of a pre-existing selectivity map. No training-related neural changes were detected in other regions. In sum, training to categorize or individuate objects strengthened pre-existing representations in human object-selective cortex, providing a first indication that the neuroanatomical distribution of learning effects depends upon the pre-learning mapping of visual object properties. Copyright © 2015 Elsevier Inc. All rights reserved.
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Hebbian Learning in a Random Network Captures Selectivity Properties of the Prefrontal Cortex
Lindsay, Grace W.
2017-01-01
Complex cognitive behaviors, such as context-switching and rule-following, are thought to be supported by the prefrontal cortex (PFC). Neural activity in the PFC must thus be specialized to specific tasks while retaining flexibility. Nonlinear “mixed” selectivity is an important neurophysiological trait for enabling complex and context-dependent behaviors. Here we investigate (1) the extent to which the PFC exhibits computationally relevant properties, such as mixed selectivity, and (2) how such properties could arise via circuit mechanisms. We show that PFC cells recorded from male and female rhesus macaques during a complex task show a moderate level of specialization and structure that is not replicated by a model wherein cells receive random feedforward inputs. While random connectivity can be effective at generating mixed selectivity, the data show significantly more mixed selectivity than predicted by a model with otherwise matched parameters. A simple Hebbian learning rule applied to the random connectivity, however, increases mixed selectivity and enables the model to match the data more accurately. To explain how learning achieves this, we provide analysis along with a clear geometric interpretation of the impact of learning on selectivity. After learning, the model also matches the data on measures of noise, response density, clustering, and the distribution of selectivities. Of two styles of Hebbian learning tested, the simpler and more biologically plausible option better matches the data. These modeling results provide clues about how neural properties important for cognition can arise in a circuit and make clear experimental predictions regarding how various measures of selectivity would evolve during animal training. SIGNIFICANCE STATEMENT The prefrontal cortex is a brain region believed to support the ability of animals to engage in complex behavior. How neurons in this area respond to stimuli—and in particular, to combinations of stimuli (
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A numeric comparison of variable selection algorithms for supervised learning
International Nuclear Information System (INIS)
Palombo, G.; Narsky, I.
2009-01-01
Datasets in modern High Energy Physics (HEP) experiments are often described by dozens or even hundreds of input variables. Reducing a full variable set to a subset that most completely represents information about data is therefore an important task in analysis of HEP data. We compare various variable selection algorithms for supervised learning using several datasets such as, for instance, imaging gamma-ray Cherenkov telescope (MAGIC) data found at the UCI repository. We use classifiers and variable selection methods implemented in the statistical package StatPatternRecognition (SPR), a free open-source C++ package developed in the HEP community ( (http://sourceforge.net/projects/statpatrec/)). For each dataset, we select a powerful classifier and estimate its learning accuracy on variable subsets obtained by various selection algorithms. When possible, we also estimate the CPU time needed for the variable subset selection. The results of this analysis are compared with those published previously for these datasets using other statistical packages such as R and Weka. We show that the most accurate, yet slowest, method is a wrapper algorithm known as generalized sequential forward selection ('Add N Remove R') implemented in SPR.
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Drupsteen, Linda; Groeneweg, Jop; Zwetsloot, Gerard I J M
2013-01-01
Many incidents have occurred because organisations have failed to learn from lessons of the past. This means that there is room for improvement in the way organisations analyse incidents, generate measures to remedy identified weaknesses and prevent reoccurrence: the learning from incidents process. To improve that process, it is necessary to gain insight into the steps of this process and to identify factors that hinder learning (bottlenecks). This paper presents a model that enables organisations to analyse the steps in a learning from incidents process and to identify the bottlenecks. The study describes how this model is used in a survey and in 3 exploratory case studies in The Netherlands. The results show that there is limited use of learning potential, especially in the evaluation stage. To improve learning, an approach that considers all steps is necessary.
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Prevention of the Teenage Pregnancy Epidemic: A Social Learning Theory Approach.
Hagenhoff, Carol; And Others
1987-01-01
The review provides a social learning model for explaining adolescent sexual behavior and use/nonuse of contraceptives. The model explains behavior patterns responsible for epidemic rates of teenage pregnancies, suggests research that will result in prevention of teenage pregnancies, and incorporates a range of social/cultural factors. (DB)
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STRATEGY FOR EVALUATION AND SELECTION OF SYSTEMS FOR ELECTRONIC LEARNING
Directory of Open Access Journals (Sweden)
Dubravka Mandušić
2012-12-01
Full Text Available Today`s technology supported and accelerated learning time requires constant and continuous acquisition of new knowledge. On the other hand, it does not leave enough time for additional education. Increasing number of E-learning systems, withdraws a need for precise evaluation of functionality that those systems provide; so they could be reciprocally compared. While implementing new systems for electronic learning, it is very important to pre-evaluate existing systems in order to select the one that meets all defined parameters, with low costs/investment. Proper evaluation can save time and money.
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Directory of Open Access Journals (Sweden)
Mu Qiao
2017-01-01
Full Text Available We propose a channel selection strategy with hybrid architecture, which combines the centralized method and the distributed method to alleviate the overhead of access point and at the same time provide more flexibility in network deployment. By this architecture, we make use of game theory and reinforcement learning to fulfill the optimal channel selection under different communication scenarios. Particularly, when the network can satisfy the requirements of energy and computational costs, the online decision algorithm based on noncooperative game can help each individual sensor node immediately select the optimal channel. Alternatively, when the network cannot satisfy the requirements of energy and computational costs, the offline learning algorithm based on reinforcement learning can help each individual sensor node to learn from its experience and iteratively adjust its behavior toward the expected target. Extensive simulation results validate the effectiveness of our proposal and also prove that higher system throughput can be achieved by our channel selection strategy over the conventional off-policy channel selection approaches.
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Evolution of learning and levels of selection: a lesson from avian parent-offspring communication.
Lotem, Arnon; Biran-Yoeli, Inbar
2014-02-01
In recent years, it has become increasingly clear that the evolution of behavior may be better understood as the evolution of the learning mechanisms that produce it, and that such mechanisms should be modeled and tested explicitly. However, this approach, which has recently been applied to animal foraging and decision-making, has rarely been applied to the social and communicative behaviors that are likely to operate in complex social environments and be subject to multi-level selection. Here we use genetic, agent-based evolutionary simulations to explore how learning mechanisms may evolve to adjust the level of nestling begging (offspring signaling of need), and to examine the possible consequences of this process for parent-offspring conflict and communication. In doing so, we also provide the first step-by-step dynamic model of parent-offspring communication. The results confirm several previous theoretical predictions and demonstrate three novel phenomena. First, negatively frequency-dependent group-level selection can generate a stable polymorphism of learning strategies and parental responses. Second, while conventional reinforcement learning models fail to cope successfully with family dynamics at the nest, a newly developed learning model (incorporating behaviors that are consistent with recent experimental results on learning in nestling begging) produced effective learning, which evolved successfully. Third, while kin-selection affects the frequency of the different learning genes, its impact on begging slope and intensity was unexpectedly negligible, demonstrating that evolution is a complex process, and showing that the effect of kin-selection on behaviors that are shaped by learning may not be predicted by simple application of Hamilton's rule. Copyright © 2013 Elsevier Inc. All rights reserved.
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Developing eLearning for pressure ulcer prevention and management.
Cameron, Rosie; Rodgers, Angela; Welsh, Lynn; McGown, Katrina
2014-08-12
The impact of pressure ulcers is psychologically, physically and clinically challenging for both patients and NHS staff. NHS Greater Glasgow and Clyde (NHS GGC), in line with the Scottish Best Practice Statement for the Prevention and Management of Pressure Ulcers ( Quality Improvement Scotland, 2009 ), and the NHS Health Improvement Scotland (2011) Preventing Pressure Ulcers Change Package, launched an awareness campaign throughout the organisation in April 2012 and has more recently adopted a 'zero-tolerance' approach to pressure damage. The tissue viability service in NHS GGC recognised that in order to achieve this aim, education of front-line staff is essential. An educational framework for pressure ulcer prevention was developed for all levels of healthcare staff involved in the delivery of patient care. As a means to support the framework, an initiative to develop web-based eLearning modules has been taken forward. This has resulted in the creation of an accessible, cost-effective, stimulating, relevant, and evidence-based education programme designed around the educational needs of all healthcare staff. In conjunction with the organisation's 'top ten tools' for pressure ulcer prevention and management, the modular online education programme addresses the aims of quality improvement and zero tolerance by supporting the provision of safe and effective person-centered care.
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Borenstein, Elhanan; Feldman, Marcus W; Aoki, Kenichi
2008-03-01
Cumulative cultural change requires organisms that are capable of both exploratory individual learning and faithful social learning. In our model, an organism's phenotype is initially determined innately (by its genotypic value) or by social learning (copying a phenotype from the parental generation), and then may or may not be modified by individual learning (exploration around the initial phenotype). The environment alternates periodically between two states, each defined as a certain range of phenotypes that can survive. These states may overlap, in which case the same phenotype can survive in both states, or they may not. We find that a joint social and exploratory individual learning strategy-the strategy that supports cumulative culture-is likely to spread when the environmental states do not overlap. In particular, when the environmental states are contiguous and mutation is allowed among the genotypic values, this strategy will spread in either moderately or highly stable environments, depending on the exact nature of the individual learning applied. On the other hand, natural selection often favors a social learning strategy without exploration when the environmental states overlap. We find only partial support for the "consensus" view, which holds that individual learning, social learning, and innate determination of behavior will evolve at short, intermediate, and long environmental periodicities, respectively.
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Directory of Open Access Journals (Sweden)
Onigbinde A. Teslim
2012-08-01
Full Text Available AIM: The aim of this study was to determine if in-patients in some selected Nigeria hospitals are at risk of developing pressure sore and to determine the preventive techniques adopted by Health Care Professionals. METHOD: A questionnaire was used for this study and it was divided into two parts. The part A is a structured questionnaire that took care of socio-demographic data and preventive techniques while part B is the Braden Scale which was used to assess the risk of developing pressure ulcer. Three hundred and eighteen (318 In-patients in five Nigeria purposively selected hospitals in southwest Nigeria volunteered to participate in this study. The statistical method that was employed was descriptive statistics. RESULTS: The result of the study showed that In-patients in the selected hospitals are “at risk” of developing pressure ulcers. Also, General Practitioners (50.47% and nursing staff (49.52% mostly prescribed at least one of the preventive techniques while few (31.23% reported that physiotherapists prescribed at least one of the preventive techniques. However, a considerable number of the patients (35.02% were never informed by any of the health staff on preventive measures. CONCLUSION: It was concluded that In-patients in Nigeria hospitals are “at risk” of developing pressure ulcers and that health care providers in Nigeria are not prescribing adequate preventive techniques to prevent pressure ulcers. [TAF Prev Med Bull 2012; 11(4.000: 415-420
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Machine learning etudes in astrophysics: selection functions for mock cluster catalogs
Energy Technology Data Exchange (ETDEWEB)
Hajian, Amir; Alvarez, Marcelo A.; Bond, J. Richard, E-mail: ahajian@cita.utoronto.ca, E-mail: malvarez@cita.utoronto.ca, E-mail: bond@cita.utoronto.ca [Canadian Institute for Theoretical Astrophysics, University of Toronto, Toronto, ON M5S 3H8 (Canada)
2015-01-01
Making mock simulated catalogs is an important component of astrophysical data analysis. Selection criteria for observed astronomical objects are often too complicated to be derived from first principles. However the existence of an observed group of objects is a well-suited problem for machine learning classification. In this paper we use one-class classifiers to learn the properties of an observed catalog of clusters of galaxies from ROSAT and to pick clusters from mock simulations that resemble the observed ROSAT catalog. We show how this method can be used to study the cross-correlations of thermal Sunya'ev-Zeldovich signals with number density maps of X-ray selected cluster catalogs. The method reduces the bias due to hand-tuning the selection function and is readily scalable to large catalogs with a high-dimensional space of astrophysical features.
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Machine learning etudes in astrophysics: selection functions for mock cluster catalogs
International Nuclear Information System (INIS)
Hajian, Amir; Alvarez, Marcelo A.; Bond, J. Richard
2015-01-01
Making mock simulated catalogs is an important component of astrophysical data analysis. Selection criteria for observed astronomical objects are often too complicated to be derived from first principles. However the existence of an observed group of objects is a well-suited problem for machine learning classification. In this paper we use one-class classifiers to learn the properties of an observed catalog of clusters of galaxies from ROSAT and to pick clusters from mock simulations that resemble the observed ROSAT catalog. We show how this method can be used to study the cross-correlations of thermal Sunya'ev-Zeldovich signals with number density maps of X-ray selected cluster catalogs. The method reduces the bias due to hand-tuning the selection function and is readily scalable to large catalogs with a high-dimensional space of astrophysical features
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Selection of suitable e-learning approach using TOPSIS technique with best ranked criteria weights
Mohammed, Husam Jasim; Kasim, Maznah Mat; Shaharanee, Izwan Nizal Mohd
2017-11-01
This paper compares the performances of four rank-based weighting assessment techniques, Rank Sum (RS), Rank Reciprocal (RR), Rank Exponent (RE), and Rank Order Centroid (ROC) on five identified e-learning criteria to select the best weights method. A total of 35 experts in a public university in Malaysia were asked to rank the criteria and to evaluate five e-learning approaches which include blended learning, flipped classroom, ICT supported face to face learning, synchronous learning, and asynchronous learning. The best ranked criteria weights are defined as weights that have the least total absolute differences with the geometric mean of all weights, were then used to select the most suitable e-learning approach by using TOPSIS method. The results show that RR weights are the best, while flipped classroom approach implementation is the most suitable approach. This paper has developed a decision framework to aid decision makers (DMs) in choosing the most suitable weighting method for solving MCDM problems.
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Weeks, Brian E.
College students often come to the study of evolutionary biology with many misconceptions of how the processes of natural selection and speciation occur. How to relinquish these misconceptions with learners is a question that many educators face in introductory biology courses. Constructivism as a theoretical framework has become an accepted and promoted model within the epistemology of science instruction. However, constructivism is not without its skeptics who see some problems of its application in lacking necessary guidance for novice learners. This study within a quantitative, quasi-experimental format tested whether guided online instruction in a video format of common misconceptions in evolutionary biology produced higher performance on a survey of knowledge of natural selection versus more constructivist style learning in the form of student exploration of computer simulations of the evolutionary process. Performances on surveys were also explored for a combination of constructivist and guided techniques to determine if a consolidation of approaches produced higher test scores. Out of the 94 participants 95% displayed at least one misconception of natural selection in the pre-test while the study treatments produced no statistically significant improvements in post-test scores except within the video (guided learning treatment). These overall results demonstrated the stubbornness of misconceptions involving natural selection for adult learners and the difficulty of helping them overcome them. It also bolsters the idea that some misconceptions of natural selection and evolution may be hardwired in a neurological sense and that new, more long-term teaching techniques may be warranted. Such long-term strategies may not be best implemented with constructivist techniques alone, and it is likely that some level of guidance may be necessary for novice adult learners. A more substantial, nuanced approach for undergraduates is needed that consolidates successful
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Raaijmakers, Steven F; Baars, Martine; Paas, Fred; van Merriënboer, Jeroen J G; van Gog, Tamara
2018-01-01
Students' ability to accurately self-assess their performance and select a suitable subsequent learning task in response is imperative for effective self-regulated learning. Video modeling examples have proven effective for training self-assessment and task-selection skills, and-importantly-such training fostered self-regulated learning outcomes. It is unclear, however, whether trained skills would transfer across domains. We investigated whether skills acquired from training with either a specific, algorithmic task-selection rule or a more general heuristic task-selection rule in biology would transfer to self-regulated learning in math. A manipulation check performed after the training confirmed that both algorithmic and heuristic training improved task-selection skills on the biology problems compared with the control condition. However, we found no evidence that students subsequently applied the acquired skills during self-regulated learning in math. Future research should investigate how to support transfer of task-selection skills across domains.
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Directory of Open Access Journals (Sweden)
Richard R Rosenkranz
2012-01-01
Full Text Available Service-learning is a type of experiential teaching and learning strategy combining classroom instruction and meaningful community service and guided activities for reflection. This educational approach has been used frequently in higher education settings, including an array of disciplines such as medicine, theology, public health, physical education, nutrition, psychology, anthropology, and sociology. The purpose of the present review paper was to provide guidance on the use of service-learning within higher education, relevant to the preventive medicine and public health topics of healthful eating, physical activity, and obesity prevention. In service-learning, coursework is structured to address community needs, and to benefit students through the real-world application of knowledge. The benefits for students include positive impacts on social skills, empathy, awareness, understanding, and concern regarding community issues, plus greater confidence and skills to work with diverse populations, increased awareness of community resources, improved motivation, and enhanced knowledge. Educational institutions may also benefit through improved "town and gown" relations, as strong ties, partnerships, and mutually beneficial activities take place. The present literature review describes several service-learning applications such as nutrition education for kids, dietary improvement for seniors, foodservice recipe modification on a college campus, an intergenerational physical activity program for nursing home residents, motor skill development in kindergarteners, organized elementary school recess physical activities, health education, and obesity prevention in children. From this review, service-learning appears to have great potential as a flexible component of academic coursework in the areas of preventive medicine and public health.
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Rosenkranz, Richard R
2012-10-01
Service-learning is a type of experiential teaching and learning strategy combining classroom instruction and meaningful community service and guided activities for reflection. This educational approach has been used frequently in higher education settings, including an array of disciplines such as medicine, theology, public health, physical education, nutrition, psychology, anthropology, and sociology. The purpose of the present review paper was to provide guidance on the use of service-learning within higher education, relevant to the preventive medicine and public health topics of healthful eating, physical activity, and obesity prevention. In service-learning, coursework is structured to address community needs, and to benefit students through the real-world application of knowledge. The benefits for students include positive impacts on social skills, empathy, awareness, understanding, and concern regarding community issues, plus greater confidence and skills to work with diverse populations, increased awareness of community resources, improved motivation, and enhanced knowledge. Educational institutions may also benefit through improved "town and gown" relations, as strong ties, partnerships, and mutually beneficial activities take place. The present literature review describes several service-learning applications such as nutrition education for kids, dietary improvement for seniors, foodservice recipe modification on a college campus, an intergenerational physical activity program for nursing home residents, motor skill development in kindergarteners, organized elementary school recess physical activities, health education, and obesity prevention in children. From this review, service-learning appears to have great potential as a flexible component of academic coursework in the areas of preventive medicine and public health.
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[Risk factors and coronary heart disease prevention in selected Lódź population--part II].
Kowalski, Jan; Kos, Małgorzata; Gburek, Jolanta; Wrocławski, Witold; Pawlicki, Lucjan
2005-12-01
Evaluation of the knowledge on CHD risk factors in selected Lódź population was made. Realization of primary and secondary CHD prevention principles was assessed. Over 20% of patients with CHD and over 38% of subjects without CHD did not realize the prevention principles. Hypolipemic therapy was effective only in 44.21% of patients with CHD and 35.9% of subjects without CHD. Antihypertensive therapy was successful in about 55% of patients with CHD and 35% of subjects without CHD. The results of our study have shown low effectiveness of both CHD prevention principles realization and hipolipemic and antihypertensive therapy in selected Lódź population.
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Lessons learned? Selected public acceptance case studies since Three Mile Island
Energy Technology Data Exchange (ETDEWEB)
Blee, D. [NAC International, Atlanta Corporate Headquarters, Atlanta, GA (United States)
2001-02-01
This paper will present an overview of the present situation, some recent polling survey information, and then look at lessons learned in terms of selected case studies and some global issues over the 22 years since the Three Mile Island (TMI) accident. That is quite an ambitious topic but there are some important lessons we can learn from the post-TMI era. (author)
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Kingston, Beverly; Bacallao, Martica; Smokowski, Paul; Sullivan, Terri; Sutherland, Kevin
2016-04-01
This paper describes the strategic efforts of six National Centers of Excellence in Youth Violence Prevention (YVPC), funded by the U.S. Centers for Disease Control and Prevention, to work in partnership with local communities to create comprehensive evidence-based program packages to prevent youth violence. Key components of a comprehensive evidence-based approach are defined and examples are provided from a variety of community settings (rural and urban) across the nation that illustrate attempts to respond to the unique needs of the communities while maintaining a focus on evidence-based programming and practices. At each YVPC site, the process of selecting prevention and intervention programs addressed the following factors: (1) community capacity, (2) researcher and community roles in selecting programs, (3) use of data in decision-making related to program selection, and (4) reach, resources, and dosage. We describe systemic barriers to these efforts, lessons learned, and opportunities for policy and practice. Although adopting an evidence-based comprehensive approach requires significant upfront resources and investment, it offers great potential for preventing youth violence and promoting the successful development of children, families and communities.
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2016-09-01
Workshop 2015 "Preventing, Understanding and Recovering from Nuclear Accidents"--lessons learned from Chernobyl and Fukushima Distribution Statement...by the factor to get the U.S. customary unit. “Preventing, Understanding and Recovering from Nuclear Accidents” – lessons learned from Chernobyl ...and Fukushima NUCLEAR SECURITY SUMMIT & WORKSHOP 2015 2 Background The 1986 Chernobyl and the 2011 Fukushima accidents provoked world-wide concern
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Biologically Predisposed Learning and Selective Associations in Amygdalar Neurons
Chung, Ain; Barot, Sabiha K.; Kim, Jeansok J.; Bernstein, Ilene L.
2011-01-01
Modern views on learning and memory accept the notion of biological constraints--that the formation of association is not uniform across all stimuli. Yet cellular evidence of the encoding of selective associations is lacking. Here, conditioned stimuli (CSs) and unconditioned stimuli (USs) commonly employed in two basic associative learning…
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International Nuclear Information System (INIS)
Ford, Eric C.; Smith, Koren; Harris, Kendra; Terezakis, Stephanie
2012-01-01
Purpose: A series of examples are presented in which potential errors in the delivery of radiation therapy were prevented through use of incident learning. These examples underscore the value of reporting near miss incidents. Methods: Using a departmental incident learning system, eight incidents were noted over a two-year period in which fields were treated “out-of-sequence,” that is, fields from a boost phase were treated, while the patient was still in the initial phase of treatment. As a result, an error-prevention policy was instituted in which radiation treatment fields are “hidden” within the oncology information system (OIS) when they are not in current use. In this way, fields are only available to be treated in the intended sequence and, importantly, old fields cannot be activated at the linear accelerator control console. Results: No out-of-sequence treatments have been reported in more than two years since the policy change. Furthermore, at least three near-miss incidents were detected and corrected as a result of the policy change. In the first two, the policy operated as intended to directly prevent an error in field scheduling. In the third near-miss, the policy operated “off target” to prevent a type of error scenario that it was not directly intended to prevent. In this incident, an incorrect digitally reconstructed radiograph (DRR) was scheduled in the OIS for a patient receiving lung cancer treatment. The incorrect DRR had an isocenter which was misplaced by approximately two centimeters. The error was a result of a field from an old plan being scheduled instead of the intended new plan. As a result of the policy described above, the DRR field could not be activated for treatment however and the error was discovered and corrected. Other quality control barriers in place would have been unlikely to have detected this error. Conclusions: In these examples, a policy was adopted based on incident learning, which prevented several errors
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Secure relay selection based on learning with negative externality in wireless networks
Zhao, Caidan; Xiao, Liang; Kang, Shan; Chen, Guiquan; Li, Yunzhou; Huang, Lianfen
2013-12-01
In this paper, we formulate relay selection into a Chinese restaurant game. A secure relay selection strategy is proposed for a wireless network, where multiple source nodes send messages to their destination nodes via several relay nodes, which have different processing and transmission capabilities as well as security properties. The relay selection utilizes a learning-based algorithm for the source nodes to reach their best responses in the Chinese restaurant game. In particular, the relay selection takes into account the negative externality of relay sharing among the source nodes, which learn the capabilities and security properties of relay nodes according to the current signals and the signal history. Simulation results show that this strategy improves the user utility and the overall security performance in wireless networks. In addition, the relay strategy is robust against the signal errors and deviations of some user from the desired actions.
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Dynamics of the evolution of learning algorithms by selection
International Nuclear Information System (INIS)
Neirotti, Juan Pablo; Caticha, Nestor
2003-01-01
We study the evolution of artificial learning systems by means of selection. Genetic programming is used to generate populations of programs that implement algorithms used by neural network classifiers to learn a rule in a supervised learning scenario. In contrast to concentrating on final results, which would be the natural aim while designing good learning algorithms, we study the evolution process. Phenotypic and genotypic entropies, which describe the distribution of fitness and of symbols, respectively, are used to monitor the dynamics. We identify significant functional structures responsible for the improvements in the learning process. In particular, some combinations of variables and operators are useful in assessing performance in rule extraction and can thus implement annealing of the learning schedule. We also find combinations that can signal surprise, measured on a single example, by the difference between predicted and correct classification. When such favorable structures appear, they are disseminated on very short time scales throughout the population. Due to such abruptness they can be thought of as dynamical transitions. But foremost, we find a strict temporal order of such discoveries. Structures that measure performance are never useful before those for measuring surprise. Invasions of the population by such structures in the reverse order were never observed. Asymptotically, the generalization ability approaches Bayesian results
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Healthy outcomes for teens project: diabetes prevention through distributed interactive learning.
Castelli, Darla M; Goss, David; Scherer, Jane; Chapman-Novakofski, Karen
2011-03-01
This study assessed whether distributed interactive learning via web-based modules and grounded in schema and social cognitive theory (treatment group, n = 101) would increase knowledge about diabetes prevention in adolescents from three middle schools to a greater extent than the control group (n = 80) and examined whether the school environment used to convey the education had an effect. The treatment group showed substantially greater increases in overall and individual modular content knowledge, with 72 voluntarily choosing to retake evaluations that significantly improved their scores. The treatment (t[3.8], β ≥ 0.30, P school, pull out from physical education, or health education curriculum) (t[3.41], β ≥ 0.24, P learning was more effective than its passive counterpart, and a more structured delivery enhanced knowledge, as did opportunities to self-regulate learning. Attention to these process components will facilitate effective interventions by educators in schools.
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Jointly Feature Learning and Selection for Robust Tracking via a Gating Mechanism.
Directory of Open Access Journals (Sweden)
Bineng Zhong
Full Text Available To achieve effective visual tracking, a robust feature representation composed of two separate components (i.e., feature learning and selection for an object is one of the key issues. Typically, a common assumption used in visual tracking is that the raw video sequences are clear, while real-world data is with significant noise and irrelevant patterns. Consequently, the learned features may be not all relevant and noisy. To address this problem, we propose a novel visual tracking method via a point-wise gated convolutional deep network (CPGDN that jointly performs the feature learning and feature selection in a unified framework. The proposed method performs dynamic feature selection on raw features through a gating mechanism. Therefore, the proposed method can adaptively focus on the task-relevant patterns (i.e., a target object, while ignoring the task-irrelevant patterns (i.e., the surrounding background of a target object. Specifically, inspired by transfer learning, we firstly pre-train an object appearance model offline to learn generic image features and then transfer rich feature hierarchies from an offline pre-trained CPGDN into online tracking. In online tracking, the pre-trained CPGDN model is fine-tuned to adapt to the tracking specific objects. Finally, to alleviate the tracker drifting problem, inspired by an observation that a visual target should be an object rather than not, we combine an edge box-based object proposal method to further improve the tracking accuracy. Extensive evaluation on the widely used CVPR2013 tracking benchmark validates the robustness and effectiveness of the proposed method.
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Valdivielso Chian, Alex; Miyamoto, Toshiyuki
In this letter, we introduce a knowledge reuse method to improve the performance of a learning algorithm developed to prevent interference in multi-car elevators. This method enables the algorithm to use its previously acquired experience in new learning processes. The simulation results confirm the improvement achieved in the algorithm's performance.
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Learning to Select Supplier Portfolios for Service Supply Chain.
Zhang, Rui; Li, Jingfei; Wu, Shaoyu; Meng, Dabin
2016-01-01
The research on service supply chain has attracted more and more focus from both academia and industrial community. In a service supply chain, the selection of supplier portfolio is an important and difficult problem due to the fact that a supplier portfolio may include multiple suppliers from a variety of fields. To address this problem, we propose a novel supplier portfolio selection method based on a well known machine learning approach, i.e., Ranking Neural Network (RankNet). In the proposed method, we regard the problem of supplier portfolio selection as a ranking problem, which integrates a large scale of decision making features into a ranking neural network. Extensive simulation experiments are conducted, which demonstrate the feasibility and effectiveness of the proposed method. The proposed supplier portfolio selection model can be applied in a real corporation easily in the future.
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Feature selection and multi-kernel learning for sparse representation on a manifold
Wang, Jim Jing-Yan
2014-03-01
Sparse representation has been widely studied as a part-based data representation method and applied in many scientific and engineering fields, such as bioinformatics and medical imaging. It seeks to represent a data sample as a sparse linear combination of some basic items in a dictionary. Gao etal. (2013) recently proposed Laplacian sparse coding by regularizing the sparse codes with an affinity graph. However, due to the noisy features and nonlinear distribution of the data samples, the affinity graph constructed directly from the original feature space is not necessarily a reliable reflection of the intrinsic manifold of the data samples. To overcome this problem, we integrate feature selection and multiple kernel learning into the sparse coding on the manifold. To this end, unified objectives are defined for feature selection, multiple kernel learning, sparse coding, and graph regularization. By optimizing the objective functions iteratively, we develop novel data representation algorithms with feature selection and multiple kernel learning respectively. Experimental results on two challenging tasks, N-linked glycosylation prediction and mammogram retrieval, demonstrate that the proposed algorithms outperform the traditional sparse coding methods. © 2013 Elsevier Ltd.
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Feature selection and multi-kernel learning for sparse representation on a manifold.
Wang, Jim Jing-Yan; Bensmail, Halima; Gao, Xin
2014-03-01
Sparse representation has been widely studied as a part-based data representation method and applied in many scientific and engineering fields, such as bioinformatics and medical imaging. It seeks to represent a data sample as a sparse linear combination of some basic items in a dictionary. Gao et al. (2013) recently proposed Laplacian sparse coding by regularizing the sparse codes with an affinity graph. However, due to the noisy features and nonlinear distribution of the data samples, the affinity graph constructed directly from the original feature space is not necessarily a reliable reflection of the intrinsic manifold of the data samples. To overcome this problem, we integrate feature selection and multiple kernel learning into the sparse coding on the manifold. To this end, unified objectives are defined for feature selection, multiple kernel learning, sparse coding, and graph regularization. By optimizing the objective functions iteratively, we develop novel data representation algorithms with feature selection and multiple kernel learning respectively. Experimental results on two challenging tasks, N-linked glycosylation prediction and mammogram retrieval, demonstrate that the proposed algorithms outperform the traditional sparse coding methods. Copyright © 2013 Elsevier Ltd. All rights reserved.
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Directory of Open Access Journals (Sweden)
Vachha Behroze
2005-11-01
Full Text Available Abstract Background Selective learning is the ability to select items of relevance from among less important items. Limited evidence exists regarding the efficiency with which children with spina bifida-myelomeningocele and shunted hydrocephalus (SB/SH are able to learn information. This report describes initial data related to components of learning and metacognitive skills in children with SB/SH. Methods Twenty six children with SB/SH and 26 controls (age: 7 – 16 y with average intelligence, and monolingual English-speaking backgrounds participated in the study. Exclusion criteria for the SB/SH group were: prior history of shunt infection, history of seizure or shunt malfunction within the previous three months, prior diagnoses of attention disorders and/or clinical depression. Children were presented lists of words with equal exemplars each of two distinct semantic categories (e.g. fruits, animals, and told to make as high a score as possible by learning the words. The value of the words was designated by category membership (e.g. animals = low value; fruits = high value. The total number of words learned across three learning trials was used to determine memory span. Selective learning efficiency (SLE was computed as the efficiency with which items of greater value were selectively learned across three trials. Results Children with SB/SH did worse than controls on memory span (P Conclusion Success in school is often dependent on the ability to recall important facts selectively and ignore less important information. Children with SB/SH in our study had a poor memory span and were unable to monitor and report an efficient and workable metacognitive strategy required to remember a list of words. Preliminary findings may begin to explain our previous clinical and research findings wherein children with SB/SH often focus on extraneous details, but demonstrate difficulty remembering the main gist of a story/event.
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Multi-level gene/MiRNA feature selection using deep belief nets and active learning.
Ibrahim, Rania; Yousri, Noha A; Ismail, Mohamed A; El-Makky, Nagwa M
2014-01-01
Selecting the most discriminative genes/miRNAs has been raised as an important task in bioinformatics to enhance disease classifiers and to mitigate the dimensionality curse problem. Original feature selection methods choose genes/miRNAs based on their individual features regardless of how they perform together. Considering group features instead of individual ones provides a better view for selecting the most informative genes/miRNAs. Recently, deep learning has proven its ability in representing the data in multiple levels of abstraction, allowing for better discrimination between different classes. However, the idea of using deep learning for feature selection is not widely used in the bioinformatics field yet. In this paper, a novel multi-level feature selection approach named MLFS is proposed for selecting genes/miRNAs based on expression profiles. The approach is based on both deep and active learning. Moreover, an extension to use the technique for miRNAs is presented by considering the biological relation between miRNAs and genes. Experimental results show that the approach was able to outperform classical feature selection methods in hepatocellular carcinoma (HCC) by 9%, lung cancer by 6% and breast cancer by around 10% in F1-measure. Results also show the enhancement in F1-measure of our approach over recently related work in [1] and [2].
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Instance Selection for Classifier Performance Estimation in Meta Learning
Directory of Open Access Journals (Sweden)
Marcin Blachnik
2017-11-01
Full Text Available Building an accurate prediction model is challenging and requires appropriate model selection. This process is very time consuming but can be accelerated with meta-learning–automatic model recommendation by estimating the performances of given prediction models without training them. Meta-learning utilizes metadata extracted from the dataset to effectively estimate the accuracy of the model in question. To achieve that goal, metadata descriptors must be gathered efficiently and must be informative to allow the precise estimation of prediction accuracy. In this paper, a new type of metadata descriptors is analyzed. These descriptors are based on the compression level obtained from the instance selection methods at the data-preprocessing stage. To verify their suitability, two types of experiments on real-world datasets have been conducted. In the first one, 11 instance selection methods were examined in order to validate the compression–accuracy relation for three classifiers: k-nearest neighbors (kNN, support vector machine (SVM, and random forest. From this analysis, two methods are recommended (instance-based learning type 2 (IB2, and edited nearest neighbor (ENN which are then compared with the state-of-the-art metaset descriptors. The obtained results confirm that the two suggested compression-based meta-features help to predict accuracy of the base model much more accurately than the state-of-the-art solution.
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The Role of Executive Control of Attention and Selective Encoding for Preschoolers' Learning
Roderer, Thomas; Krebs, Saskia; Schmid, Corinne; Roebers, Claudia M.
2012-01-01
Selectivity in encoding, aspects of attentional control and their contribution to learning performance were explored in a sample of preschoolers. While the children are performing a learning task, their encoding of relevant and attention towards irrelevant information was recorded through an eye-tracking device. Recognition of target items was…
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Kostons, Danny; van Gog, Tamara; Paas, Fred
For self-regulated learning to be effective, students need to be able to accurately assess their own performance on a learning task and use this assessment for the selection of a new learning task. Evidence suggests, however, that students have difficulties with accurate self-assessment and task
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Directory of Open Access Journals (Sweden)
Oksana Synekop
2017-09-01
Full Text Available In conditions of differentiation the learning materials selection will optimize the training English for Specific Purposes of the future professionals in the field of information technology at university level. The purpose of the article is to define the basic unit of learning material, the factors of influence on the learning material selection, principles, criteria and the procedure of learning material selection in this paper. Reviewing the scientific achievements in the learning material selection in teaching English has become a basis for defining the factors of influence, principles and criteria in the research. The basic unit of learning material (learning English text for professional purposes is outlined. The factors of influence and principles (correspondence of learning materials to professional interests and needs of information technology students; necessary ability and accessibility; regarding the linguistic and stylistic necessity and sufficiency; availability of Internet sources information of the learning material selection are defined. Also, the qualitative criteria (authenticity; professional significance, relevance and informativeness; conformity of foreign language level and intellectual development of students; variety of genres and forms of speech, their sufficient filling by linguistic material; coherence, integrity, consistency, semantic completeness; topic conformity; situation conformity; unlimited access, reliability and exemplarity of Internet sources and the quantitative criteria (the amount of material of the learning material selection are highlighted. The process of English for Specific Purposes material selection (defining the disciplines of different cycles; defining spheres and related topics; outlining situations, communicative roles and intentions of professional communication; specifying the sources of selection; evaluating the texts; analysis of the knowledge, skills and sub-skills required for the
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Building a learning culture and prevention of error - to near miss or not.
Arnold, Anthony
2017-09-01
This editorial provides an insight into learning and prevention of error through near miss event reporting. © 2017 The Author. Journal of Medical Radiation Sciences published by John Wiley & Sons Australia, Ltd on behalf of Australian Society of Medical Imaging and Radiation Therapy and New Zealand Institute of Medical Radiation Technology.
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An Adaptive Learning Based Network Selection Approach for 5G Dynamic Environments
Directory of Open Access Journals (Sweden)
Xiaohong Li
2018-03-01
Full Text Available Networks will continue to become increasingly heterogeneous as we move toward 5G. Meanwhile, the intelligent programming of the core network makes the available radio resource be more changeable rather than static. In such a dynamic and heterogeneous network environment, how to help terminal users select optimal networks to access is challenging. Prior implementations of network selection are usually applicable for the environment with static radio resources, while they cannot handle the unpredictable dynamics in 5G network environments. To this end, this paper considers both the fluctuation of radio resources and the variation of user demand. We model the access network selection scenario as a multiagent coordination problem, in which a bunch of rationally terminal users compete to maximize their benefits with incomplete information about the environment (no prior knowledge of network resource and other users’ choices. Then, an adaptive learning based strategy is proposed, which enables users to adaptively adjust their selections in response to the gradually or abruptly changing environment. The system is experimentally shown to converge to Nash equilibrium, which also turns out to be both Pareto optimal and socially optimal. Extensive simulation results show that our approach achieves significantly better performance compared with two learning and non-learning based approaches in terms of load balancing, user payoff and the overall bandwidth utilization efficiency. In addition, the system has a good robustness performance under the condition with non-compliant terminal users.
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The selective estrogen receptor modulators in breast cancer prevention.
Li, Fangxuan; Dou, Jinli; Wei, Lijuan; Li, Shixia; Liu, Juntian
2016-05-01
Persistently increased blood levels of estrogens are associated with an increased risk of breast cancer. Selective estrogen receptor modulators (SERMs) are a class of compounds that act on the estrogen receptor (ER). Several clinical trials have demonstrated the effectiveness of its prophylactic administration. Incidence of invasive ER-positive breast cancer was reduced by SERMs treatment, especially for those women with high risk of developing breast cancer. In this study, we reviewed the clinical application of SERMs in breast cancer prevention. To date, four prospective randomized clinical trials had been performed to test the efficacy of tamoxifen for this purpose. Concerning on the benefit and cost of tamoxifen, various studies from different countries demonstrated that chemoprevention with tamoxifen seemed to be cost-effective for women with a high risk of invasive breast cancer. Based above, tamoxifen was approved for breast cancer prevention by the US Food and Drug Administration in 1998. Raloxifene was also approved for postmenopausal women in 2007 for breast cancer prevention which reduces the risk of invasive breast cancer with a lower risk of unwanted stimulation of endometrium. Thus, raloxifene is considered to have a better clinical possesses as prophylactic agent. Several other agents, such as arzoxifene and lasofoxifene, are currently being investigated in clinic. The American Society of Clinical Oncology and National Comprehensive Cancer Network had published guidelines on breast cancer chemoprevention by SERMs. However, use of tamoxifen and raloxifene for primary breast cancer prevention was still low. A broader educational effort is needed to alert women and primary care physicians that SERMs are available to reduce breast cancer risk.
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Project Selection in the Design Studio: Absence of Learning Environments
Basa, Inci
2010-01-01
Project selection is an essential matter of design teaching. Based on observations of a specific curriculum, the author claims that a wide repertoire of subjects including offices, restaurants, hotels, and other public places are used to prepare design students, but that schools and other "learning environments/ schools" are similarly…
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Directory of Open Access Journals (Sweden)
Luis Fernando Cuartas Alvarez
2014-04-01
Full Text Available This article reports the results of an action-research project that examines enhancing students’ English learning processes through the selective use of their mother tongues with the aim of overcoming their reluctant attitudes toward learning English in the classroom. This study involves forty ninth-graders from an all-girls public school in Medellin, Colombia. The data gathered included field notes, questionnaires, and participants’ focus group interviews. The findings show that the mother tongue plays an important role in students’ English learning processes by fostering students’ affective, motivational, cognitive, and attitudinal aspects. Thus, the mother tongue serves as the foothold for further advances in learning English when used selectively.
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Wang, Jim Jing-Yan
2014-09-20
Nonnegative matrix factorization (NMF), a popular part-based representation technique, does not capture the intrinsic local geometric structure of the data space. Graph regularized NMF (GNMF) was recently proposed to avoid this limitation by regularizing NMF with a nearest neighbor graph constructed from the input data set. However, GNMF has two main bottlenecks. First, using the original feature space directly to construct the graph is not necessarily optimal because of the noisy and irrelevant features and nonlinear distributions of data samples. Second, one possible way to handle the nonlinear distribution of data samples is by kernel embedding. However, it is often difficult to choose the most suitable kernel. To solve these bottlenecks, we propose two novel graph-regularized NMF methods, AGNMFFS and AGNMFMK, by introducing feature selection and multiple-kernel learning to the graph regularized NMF, respectively. Instead of using a fixed graph as in GNMF, the two proposed methods learn the nearest neighbor graph that is adaptive to the selected features and learned multiple kernels, respectively. For each method, we propose a unified objective function to conduct feature selection/multi-kernel learning, NMF and adaptive graph regularization simultaneously. We further develop two iterative algorithms to solve the two optimization problems. Experimental results on two challenging pattern classification tasks demonstrate that the proposed methods significantly outperform state-of-the-art data representation methods.
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Selective bilateral amygdala lesions in rhesus monkeys fail to disrupt object reversal learning.
Izquierdo, Alicia; Murray, Elisabeth A
2007-01-31
Neuropsychological studies in nonhuman primates have led to the view that the amygdala plays an essential role in stimulus-reward association. The main evidence in support of this idea is that bilateral aspirative or radiofrequency lesions of the amygdala yield severe impairments on object reversal learning, a task that assesses the ability to shift choices of objects based on the presence or absence of food reward (i.e., reward contingency). The behavioral effects of different lesion techniques, however, can vary. The present study therefore evaluated the effects of selective, excitotoxic lesions of the amygdala in rhesus monkeys on object reversal learning. For comparison, we tested the same monkeys on a task known to be sensitive to amygdala damage, the reinforcer devaluation task. Contrary to previous results based on less selective lesion techniques, monkeys with complete excitotoxic amygdala lesions performed object reversal learning as quickly as controls. As predicted, however, the same operated monkeys were impaired in making object choices after devaluation of the associated food reinforcer. The results suggest two conclusions. First, the results demonstrate that the amygdala makes a selective contribution to stimulus-reward association; the amygdala is critical for guiding object choices after changes in reward value but not after changes in reward contingency. Second, the results implicate a critical contribution to object reversal learning of structures nearby the amygdala, perhaps the subjacent rhinal cortex.
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Endogenous information, adverse selection, and prevention: Implications for genetic testing policy.
Peter, Richard; Richter, Andreas; Thistle, Paul
2017-09-01
We examine public policy toward the use of genetic information by insurers. Individuals engage in unobservable primary prevention and have access to different prevention technologies. Thus, insurance markets are affected by moral hazard and adverse selection. Individuals can choose to take a genetic test to acquire information about their prevention technology. Information has positive decision-making value, that is, individuals may adjust their behavior based on the result of the test. However, testing also exposes individuals to uncertainty over the available insurance contract, so-called classification risk, which lowers the value of information. In our analysis we distinguish between four different policy regimes, determine the value of information under each regime and associated equilibrium outcomes on the insurance market. We show that the policy regimes can be Pareto ranked, with a duty to disclose being the preferred regime and an information ban the least preferred one. Copyright © 2017 Elsevier B.V. All rights reserved.
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When Average Is Not Good Enough: Students with Learning Disabilities at Selective, Private Colleges
Weis, Robert; Erickson, Celeste P.; Till, Christina H.
2017-01-01
Adolescents with learning disabilities disproportionately come from lower socioeconomic status backgrounds, show normative deficits in academic skills, and attend 2-year, public colleges instead of 4-year institutions. However, students with learning disabilities are well represented at the United States' most expensive and selective postsecondary…
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Goal selection versus process control while learning to use a brain-computer interface
Royer, Audrey S.; Rose, Minn L.; He, Bin
2011-06-01
A brain-computer interface (BCI) can be used to accomplish a task without requiring motor output. Two major control strategies used by BCIs during task completion are process control and goal selection. In process control, the user exerts continuous control and independently executes the given task. In goal selection, the user communicates their goal to the BCI and then receives assistance executing the task. A previous study has shown that goal selection is more accurate and faster in use. An unanswered question is, which control strategy is easier to learn? This study directly compares goal selection and process control while learning to use a sensorimotor rhythm-based BCI. Twenty young healthy human subjects were randomly assigned either to a goal selection or a process control-based paradigm for eight sessions. At the end of the study, the best user from each paradigm completed two additional sessions using all paradigms randomly mixed. The results of this study were that goal selection required a shorter training period for increased speed, accuracy, and information transfer over process control. These results held for the best subjects as well as in the general subject population. The demonstrated characteristics of goal selection make it a promising option to increase the utility of BCIs intended for both disabled and able-bodied users.
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Feldmann-Wüstefeld, Tobias; Uengoer, Metin; Schubö, Anna
2015-11-01
Besides visual salience and observers' current intention, prior learning experience may influence deployment of visual attention. Associative learning models postulate that observers pay more attention to stimuli previously experienced as reliable predictors of specific outcomes. To investigate the impact of learning experience on deployment of attention, we combined an associative learning task with a visual search task and measured event-related potentials of the EEG as neural markers of attention deployment. In the learning task, participants categorized stimuli varying in color/shape with only one dimension being predictive of category membership. In the search task, participants searched a shape target while disregarding irrelevant color distractors. Behavioral results showed that color distractors impaired performance to a greater degree when color rather than shape was predictive in the learning task. Neurophysiological results show that the amplified distraction was due to differential attention deployment (N2pc). Experiment 2 showed that when color was predictive for learning, color distractors captured more attention in the search task (ND component) and more suppression of color distractor was required (PD component). The present results thus demonstrate that priority in visual attention is biased toward predictive stimuli, which allows learning experience to shape selection. We also show that learning experience can overrule strong top-down control (blocked tasks, Experiment 3) and that learning experience has a longer-term effect on attention deployment (tasks on two successive days, Experiment 4). © 2015 Society for Psychophysiological Research.
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Griessman, B. Eugene; Bertrand, Alvin L.
Two rural Louisiana communities were selected to evaluate the effectiveness of certain types of communication in preventing man-caused forest fires. The communities were selected on the basis of differences in fire occurrence rates and other factors related to conservation. Questionnaires and personal interviews were utilized to determine views of…
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Erickson, Lucy C.; Thiessen, Erik D.; Godwin, Karrie E.; Dickerson, John P.; Fisher, Anna V.
2015-01-01
Selective sustained attention is vital for higher order cognition. Although endogenous and exogenous factors influence selective sustained attention, assessment of the degree to which these factors influence performance and learning is often challenging. We report findings from the Track-It task, a paradigm that aims to assess the contribution of…
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Hoek, Rianne J A; Havermans, Bo M; Houtman, Irene L D; Brouwers, Evelien P M; Heerkens, Yvonne F; Zijlstra-Vlasveld, Moniek C; Anema, Johannes R; van der Beek, Allard J; Boot, Cécile R L
2017-07-17
Adequate implementation of work-related stress management interventions can reduce or prevent work-related stress and sick leave in organizations. We developed a multifaceted integral stress-prevention strategy for organizations from several sectors that includes a digital platform and collaborative learning network. The digital platform contains a stepwise protocol to implement work-related stress-management interventions. It includes stress screeners, interventions and intervention providers to facilitate access to and the selection of matching work-related stress-management interventions. The collaborative learning network, including stakeholders from various organizations, plans meetings focussing on an exchange of experiences and good practices among organizations for the implementation of stress prevention measures. This paper describes the design of an integral stress-prevention strategy, Stress Prevention@Work, and the protocol for the evaluation of: 1) the effects of the strategy on perceived stress and work-related outcomes, and 2) the barriers and facilitators for implementation of the strategy. The effectiveness of Stress Prevention@Work will be evaluated in a cluster controlled trial, in a large healthcare organization in the Netherlands, at six and 12 months. An independent researcher will match teams on working conditions and size and allocate the teams to the intervention or control group. Teams in the intervention group will be offered Stress Prevention@Work. For each intervention team, one employee is responsible for applying the strategy within his/her team using the digital platform and visiting the collaborative learning network. Using a waiting list design, the control group will be given access to the strategy after 12 months. The primary outcome is the employees' perceived stress measured by the stress subscale of the Depression, Anxiety, and Stress Scale (DASS-21). Secondary outcome measures are job demands, job resources and the number
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Kostons, Danny; Van Gog, Tamara; Paas, Fred
2012-01-01
Kostons, D., Van Gog, T., & Paas, F. (2012). Training self-assessment and task-selection skills: A cognitive approach to improving self-regulated learning. Learning and Instruction, 22(2), 121-132. doi:10.1016/j.learninstruc.2011.08.004
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Instance Selection for Classifier Performance Estimation in Meta Learning
Marcin Blachnik
2017-01-01
Building an accurate prediction model is challenging and requires appropriate model selection. This process is very time consuming but can be accelerated with meta-learning–automatic model recommendation by estimating the performances of given prediction models without training them. Meta-learning utilizes metadata extracted from the dataset to effectively estimate the accuracy of the model in question. To achieve that goal, metadata descriptors must be gathered efficiently and must be inform...
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Academic-practice collaboration in nursing education: service-learning for injury prevention.
Alexander, Gina K; Canclini, Sharon B; Krauser, Debbie L
2014-01-01
Teams of senior-level baccalaureate nursing students at a private, urban university complete a population-focused public health nursing practicum through service-learning partnerships. Recently, students collaborated with local service agencies for Safe Communities America, a program of the National Safety Council in affiliation with the World Health Organization. This article describes the student-led process of community assessment, followed by systematic planning, implementation, and evaluation of evidence-based interventions to advance prescription drug overdose/poisoning prevention efforts in the community.
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[Prevention of cardiovascular diseases - Prophylactic program in a selected enterprise].
Siedlecka, Jadwiga; Gadzicka, Elżbieta; Szyjkowska, Agata; Siedlecki, Patryk; Szymczak, Wiesław; Makowiec-Dąbrowska, Teresa; Bortkiewicz, Alicja
2017-10-17
In Poland cardiovascular diseases (CVD), classified as work-related diseases, are responsible for 25% of disability and cause 50% of all deaths, including 26.9% of deaths in people aged under 65 years. The aim of the study was to analyze employee expectations regarding CVD- oriented prophylactic activities in the selected enterprise. A questionnaire, developed for this study, consists of: socio-demographic data, job characteristics, occupational factors, and questions about the respondents' expectations concerning the prevention program. The study group comprised 407 multi-profile company employees aged (mean) 46.7 years (standard deviation (SD) = 9.1), including 330 men (81.1%), mean age = 46.9 (SD = 9.2) and 77 women (18.9%), mean age = 45.9 (SD = 8.2) The study was performed using the method of auditorium survey. Employees declared the need for actions related to physical activity: use of gym, swimming pool, tennis (56.5%), smoking habits - education sessions on quitting smoking (24.6%). A few people were interested in activities related to healthy diet. According to the majority of the study group, the scope of preventive examinations should be expanded. Based on our own findings and literature data CVD- -oriented preventive program, addressed to the analyzed enterprise was prepared. The program will be presented in another paper. The results showed significant quantitative and qualitative differences in the classic and occupational CVD risk factors between men and women, as well as in preferences for participation in prevention programs. Therefore, gender differences should be taken into account when planning prevention programs. Med Pr 2017;68(6):757-769. This work is available in Open Access model and licensed under a CC BY-NC 3.0 PL license.
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Directory of Open Access Journals (Sweden)
H. lita
2002-11-01
The study therefore focused on the following objective: To identify the factors that influence the selection of learning opportunities for primary health care in hospital units. A qualitative research design utilising focus group discussions were used. The population consisted of conveniently selected lecturers, student nurses and registered nurses. The same initial question was asked in each focus group to initiate the discussions. The data were analysed according to Tesch's method. The results indicated that there is positive commitment from the lecturers and registered nurses to be involved in selecting appropriate learning opportunities. The student nurses also demonstrated a willingness to learn and to be exposed to learning opportunities in primary health care. There were however certain constraints that emerged as themes, namely: • Managerial constraints • Educational constraints Under the theme "managerial constraints" categories such as workload, nursing staff shortages and communication problems were identified. Under the theme "educational constraints" categories such as a lack of guidance, and the correlation of theory and practice emerged. Recommendations based on this research report include improvement of in-service education on managerial and educational aspects to facilitate the primary health care approach in hospitals.
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Nicastro, Holly L.; Dunn, Barbara K.
2013-01-01
The Selenium and Vitamin E Cancer Prevention Trial (SELECT) was conducted to assess the efficacy of selenium and vitamin E alone, and in combination, on the incidence of prostate cancer. This randomized, double-blind, placebo-controlled, 2 × 2 factorial design clinical trial found that neither selenium nor vitamin E reduced the incidence of prostate cancer after seven years and that vitamin E was associated with a 17% increased risk of prostate cancer compared to placebo. The null result was surprising given the strong preclinical and clinical evidence suggesting chemopreventive activity of selenium. Potential explanations for the null findings include the agent formulation and dose, the characteristics of the cohort, and the study design. It is likely that only specific subpopulations may benefit from selenium supplementation; therefore, future studies should consider the baseline selenium status of the participants, age of the cohort, and genotype of specific selenoproteins, among other characteristics, in order to determine the activity of selenium in cancer prevention. PMID:23552052
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Directory of Open Access Journals (Sweden)
Holly L. Nicastro
2013-04-01
Full Text Available The Selenium and Vitamin E Cancer Prevention Trial (SELECT was conducted to assess the efficacy of selenium and vitamin E alone, and in combination, on the incidence of prostate cancer. This randomized, double-blind, placebo-controlled, 2 × 2 factorial design clinical trial found that neither selenium nor vitamin E reduced the incidence of prostate cancer after seven years and that vitamin E was associated with a 17% increased risk of prostate cancer compared to placebo. The null result was surprising given the strong preclinical and clinical evidence suggesting chemopreventive activity of selenium. Potential explanations for the null findings include the agent formulation and dose, the characteristics of the cohort, and the study design. It is likely that only specific subpopulations may benefit from selenium supplementation; therefore, future studies should consider the baseline selenium status of the participants, age of the cohort, and genotype of specific selenoproteins, among other characteristics, in order to determine the activity of selenium in cancer prevention.
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Learning from Fables: Moral Values in Three Selected English Stories
Abrar, Mukhlash
2016-01-01
Fable is not just a fun story, but it certainly has the moral lesson(s) inside of the storyline. This research tries to portray ethical value(s) in three selected English fable stories as well as to let the readers know that they can learn something from the fables. With this study, the researcher also correlated the value(s) to real life and…
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The study of selective property of college student’s learning space
Nagai, Mizuki; Matsumoto, Yuji; Naka, Ryusuke
2018-05-01
These days, college students study not only at places designed for learning such as libraries in colleges, but also cafes in downtown while the number of facilities for learning run by colleges is increasing. Then I have researched facilities in college and those in downtown to find selective properties of college students’ learning space. First, I found by questionnaire survey that students chose “3rd place” such as cafes and fast food shops, second to their houses and libraries in college. Next, I found “psychological factor” were also affected their choice. Furthermore, they studied different subjects at different places. In experiments, I researched how effectively they studied each subject at every place. The results show that I find that places you like and places where learning efficiency is good are different. They learned the least effective at “3d place” regardless of what they learned. The result of how long they kept high-level intellectual activity at each place shows that they could work on the study with more motivation at their favorite place and 3rd place. On the other hand, at the 2nd place, they could study rather effectively, but could not keep concentration and motivation for a long time. In this way, college students have 2 patterns of choosing learning space.
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Judd, Terry; Elliott, Kristine
2017-10-02
Medical students have access to a wide range of learning resources, many of which have been specifically developed for or identified and recommended to them by curriculum developers or teaching staff. There is an expectation that students will access and use these resources to support their self-directed learning. However, medical educators lack detailed and reliable data about which of these resources students use to support their learning and how this use relates to key learning events or activities. The purpose of this study was to comprehensively document first-year medical student selection and use of online learning resources to support their bioscience learning within a case-based curriculum and assess these data in relation to our expectations of student learning resource requirements and use. Study data were drawn from 2 sources: a survey of student learning resource selection and use (2013 cohort; n=326) and access logs from the medical school learning platform (2012 cohort; n=337). The paper-based survey, which was distributed to all first-year students, was designed to assess the frequency and types of online learning resources accessed by students and included items about their perceptions of the usefulness, quality, and reliability of various resource types and sources. Of 237 surveys returned, 118 complete responses were analyzed (36.2% response rate). Usage logs from the learning platform for an entire semester were processed to provide estimates of first-year student resource use on an individual and cohort-wide basis according to method of access, resource type, and learning event. According to the survey data, students accessed learning resources via the learning platform several times per week on average, slightly more often than they did for resources from other online sources. Google and Wikipedia were the most frequently used nonuniversity sites, while scholarly information sites (eg, online journals and scholarly databases) were accessed
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Directory of Open Access Journals (Sweden)
Andreas L. Schulz
2016-01-01
Full Text Available Goal directed behavior and associated learning processes are tightly linked to neuronal activity in the ventral striatum. Mechanisms that integrate task relevant sensory information into striatal processing during decision making and learning are implicitly assumed in current reinforcementmodels, yet they are still weakly understood. To identify the functional activation of cortico-striatal subpopulations of connections during auditory discrimination learning, we trained Mongolian gerbils in a two-way active avoidance task in a shuttlebox to discriminate between falling and rising frequency modulated tones with identical spectral properties. We assessed functional coupling by analyzing the field-field coherence between the auditory cortex and the ventral striatum of animals performing the task. During the course of training, we observed a selective increase of functionalcoupling during Go-stimulus presentations. These results suggest that the auditory cortex functionally interacts with the ventral striatum during auditory learning and that the strengthening of these functional connections is selectively goal-directed.
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Evolution and natural selection: learning by playing and reflecting
Directory of Open Access Journals (Sweden)
David Herrero
2014-01-01
Full Text Available Scientific literacy is more than the simple reproduction of traditional school science knowledge and requires a set of skills, among them identifying scientific issues, explaining phenomena scientifically and using scientific evidence. Several studies have indicated that playing computer games in the classroom can support the development of students’ conceptual understanding about scientific phenomena and theories. Our paper presents a research study where the role of the video game Spore as a learning tool was analysed in a Biology class. An ethnographical perspective served as the framework for the organization and development of a workshop comprised of five sessions with 22 4th grade students, and their Biology teacher. The results show that this video game could become an interesting learning tool to improve students’ understanding of evolution and natural selection. The students could combine their previous knowledge with the academic knowledge obtained though the simulation presented by the video game. To sum up, an attempt has been made to give some empirical guidance about effective approaches to the utilisation of games in classrooms, additionally paying attention to a number of concerns related to the effectiveness of video games as learning tools.
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Learning by Exporting or Self Selection? Which Way for the Kenyan ...
African Journals Online (AJOL)
The results obtained show some significant differences between exporters and non exporters. The results also show some evidence for learning-by-doing hypothesis and evidence for self-selection of more efficient firms into exporting. On the policy front the paper calls for more focus on improving exports in order for Kenya ...
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Brown, Holden D.; Amodeo, Dionisio A.; Sweeney, John A.; Ragozzino, Michael E.
2011-01-01
Previous findings indicate treatment with a selective serotonin reuptake inhibitor (SSRI) facilitates behavioral flexibility when conditions require inhibition of a learned response pattern. The present experiment investigated whether acute treatment with the SSRI, escitalopram, affects behavioral flexibility when conditions require inhibition of a naturally-biased response pattern (elevated conflict test) and/or reversal of a learned response pattern (spatial reversal learning). An additional experiment was carried out to determine whether escitalopram, at doses that affected behavioral flexibility, also reduced anxiety as tested in the elevated plus-maze. In each experiment, Long-Evans rats received an intraperitoneal injection of either saline or escitalopram (0.03, 0.3 or 1.0 mg/kg) 30 minutes prior to behavioral testing. Escitalopram, at all doses tested, enhanced acquisition in the elevated conflict test, but did not affect performance in the elevated plus-maze. Escitalopram (0.3 and 1.0 mg/kg) did not alter acquisition of the spatial discrimination, but facilitated reversal learning. In the elevated conflict and spatial reversal learning test, escitalopram enhanced the ability to maintain the relevant strategy after being initially selected. The present findings suggest that enhancing serotonin transmission with a SSRI facilitates inhibitory processes when conditions require a shift away from either a naturally-biased response pattern or a learned choice pattern. PMID:22219222
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Chung, Joonho; Seok, Jeong-Ho; Kwon, Min A; Kim, Yong Bae; Joo, Jin-Yang; Hong, Chang-Ki
2016-01-01
We prospectively evaluated the effects of preventive surgery for unruptured intracranial aneurysms on attention, executive function, learning and memory. Between March 2012 and June 2013, 56 patients were recruited for this study. Fifty-one patients met the inclusion criteria and were enrolled. Inclusion criteria were as follows: (1) age ≤65 years and (2) planned microsurgery or endovascular surgery for unruptured intracranial aneurysm. Exclusion criteria were as follows: (1) preoperative intelligence quotient attention), WCT (executive function) and VLT (learning and memory) scores did not change significantly between the pre- and postoperative evaluations. The ACCPT, WCT, total VLT scores (verbal learning) and delayed VLT scores (memory) did not differ significantly between patients undergoing microsurgery and those undergoing endovascular surgery. However, ACCPT, WCT and delayed VLT scores decreased postoperatively in patients with leukoaraiosis on preoperative FLAIR images (OR 9.899, p = 0.041; OR 11.421, p = 0.006; OR 2.952, p = 0.024, respectively). Preventive surgery for unruptured intracranial aneurysms did not affect attention, executive function, learning or memory. However, patients with leukoaraiosis on FLAIR images might be prone to deficits in attention, executive function and memory postoperatively, whereas learning might not be affected.
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Niers, L. E. M.; Hoekstra, M. O.; Timmerman, H. M.; van Uden, N. O.; de Graaf, P. M. A.; Smits, H. H.; Kimpen, J. L. L.; Rijkers, G. T.
2007-01-01
Modification of intestinal microbiota early in life by administration of probiotic bacteria may be a potential approach to prevent allergic disease. To select probiotic bacteria for in vivo purposes, we investigated the capacity of probiotic bacteria to interact with neonatal dendritic cells (DC)
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Directory of Open Access Journals (Sweden)
Rianne J. A. Hoek
2017-07-01
Full Text Available Abstract Background Adequate implementation of work-related stress management interventions can reduce or prevent work-related stress and sick leave in organizations. We developed a multifaceted integral stress-prevention strategy for organizations from several sectors that includes a digital platform and collaborative learning network. The digital platform contains a stepwise protocol to implement work-related stress-management interventions. It includes stress screeners, interventions and intervention providers to facilitate access to and the selection of matching work-related stress-management interventions. The collaborative learning network, including stakeholders from various organizations, plans meetings focussing on an exchange of experiences and good practices among organizations for the implementation of stress prevention measures. This paper describes the design of an integral stress-prevention strategy, Stress Prevention@Work, and the protocol for the evaluation of: 1 the effects of the strategy on perceived stress and work-related outcomes, and 2 the barriers and facilitators for implementation of the strategy. Methods The effectiveness of Stress Prevention@Work will be evaluated in a cluster controlled trial, in a large healthcare organization in the Netherlands, at six and 12 months. An independent researcher will match teams on working conditions and size and allocate the teams to the intervention or control group. Teams in the intervention group will be offered Stress Prevention@Work. For each intervention team, one employee is responsible for applying the strategy within his/her team using the digital platform and visiting the collaborative learning network. Using a waiting list design, the control group will be given access to the strategy after 12 months. The primary outcome is the employees’ perceived stress measured by the stress subscale of the Depression, Anxiety, and Stress Scale (DASS-21. Secondary outcome measures
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Gebreeyesus Hadera, H; Boer, H; Kuiper, W A J M
2007-08-01
Various studies indicate that school- or university-based HIV prevention curricula can reduce the prevalence of sexual risk behaviour among adolescent youth in Sub-Saharan Africa. However, effective HIV/AIDS prevention education may be problematic, if the needs of youth are not served adequately. To date, little attention has been given to the motivation of youth to learn about HIV/AIDS and about their preferences for HIV/AIDS curriculum design options. The aim of this study was to get insight into the determinants of the motivation of youth to learn about HIV/AIDS prevention and to assess their curriculum design preferences. Students from a university in Tigray, Ethiopia, filled out a structured questionnaire, which assessed demographics, variables that according to the Theory of Planned Behaviour are related to the motivation to learn, and their preferences for independent, carrier and integrated HIV/AIDS curriculum designs. On average, participants were highly motivated to learn about HIV/AIDS. Motivation to learn was primarily related to social norms and was not related to self-efficacy to discuss HIV/AIDS in class. The often discussed reluctance to discuss sexuality and condom use in curricula in Sub-Saharan Africa, seems to be more related to existing negative social norms, than to lack of self-efficacy. Participants revealed a high preference for the independent, carrier and integrated curriculum design options. However, students with a higher motivation to learn about HIV/AIDS were more attracted to the independent course design.
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Yap, Tracey L; Kennerly, Susan M; Bergstrom, Nancy; Hudak, Sandra L; Horn, Susan D
2016-01-01
Pressure ulcers have consistently resisted prevention efforts in long-term care facilities nationwide. Recent research has described cueing innovations that-when selected according to the assumptions and resources of particular facilities-support best practices of pressure ulcer prevention. This article synthesizes that research into a unified, dynamic logic model to facilitate effective staff implementation of a pressure ulcer prevention program.
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Directory of Open Access Journals (Sweden)
Rodrigo Pessoa Cavalcanti Lira
2013-02-01
Full Text Available OBJECTIVE: To investigate if E-learning material improves the basal student knowledge level before attending the presential class of blindness prevention (BP and if helps to fix this information one-month after the class. METHODS: Fourth-year medical students were randomly assigned to have a presential class of BP (Traditional group = TG or to have a presential class of BP plus an additional E-learning material (E-learning group = ELG. This material was e-mailed one week before the presential class. The students were submitted to a multiple-choice test (with three options each with seven questions immediately before the presential class, immediately after the class, and one-month later. The three tests had the same questions; however, the answers options were distributed in different sequences. The primary outcome was immediate pretest score. The secondary outcomes were immediate posttest score and one-month posttest score. RESULTS: Among the 120 fourth-year medical students, a random sample of 34 students was assigned to the TG and 34 students was assigned to the ELG. The two groups showed similar immediate posttest score (TG=6.8 and ELG=6.9; P<.754, but the differences at the immediate pretest score (TG=3.6 and ELG=4.7; P<.001, and at the one-month posttest score, were significant (TG=6.1 and ELG=6.8; P<.001. CONCLUSIONS: The pretest and the one-month posttest results suggested that the E-learning material acts as an effective complementary tool of the presential class of blindness prevention.
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Basic webliography on health promotion and disease prevention
Directory of Open Access Journals (Sweden)
Mario Ferreira Junior
2009-12-01
Full Text Available Objectives: To introduce a basic webliography to access highly qualified evidence-based material on health promotion and disease prevention, aiming at the continuing education of health professionals. Methods: By means of Google® browser, applying the descriptors in sequence to progressively refine the search on Internet and key concepts to be learned, all previously defined by the authors themselves, we proceeded a qualitative analyses of the 20 first listed links for each searched issue and the final selection of the most scientifically relevant ones. Results: The 34 selected links are presented in 4 groups: 23 portals, 5 guides and recommendations, 4 scientific journals and 3 blogs that allow free access to health promotion and disease prevention related subjects, such as: concepts; national and international public policies; epidemiology, statistics and health indicators; diseases screening and prophylaxis; counseling for behavior change of health related habits; and interdisciplinary work. Among the selected links 10 (29% are written in English while the others are in Portuguese. Conclusions: The identification of reading materials on health promotion and disease prevention available on Internet, many in Portuguese, allowed us toselect relevant scientifically qualified literature and turn it accessible to health professionals, enabling the acquisition of new knowledge or quick update.
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Anil, Shirin; Zawahir, Mohamed Shukry; Al-Naggar, Redhwan Ahmed
2016-03-01
Preventive medicine has been incorporated in the medical school curriculum, but its effectiveness and the factors that affect it are yet to be widely looked into in the context of Malaysia. We aimed to measure the familiarity with, perception about the importance to learn, and the ability to practice preventive medicine as well as its determinants among the medical students in Malaysia. Thus, a cross sectional study was conducted through an anonymous online survey among 387 randomly selected final year medical students of four large public medical schools in Malaysia from March to September 2014. Of the total sample, 340 (response rate 87.8%) gave a written informed consent and took part in the survey. The familiarity of the sample with preventive medicine was measured in 19 preventive medicine areas, and their perception about the importance of preventive medicine and their ability to practice it were gauged on a Likert scale (low score indicates disagreement and high indicates agreement). Descriptive statistical analysis was performed, followed by logistic regression. The mean age of the respondents was 23.7 (SD 0.77) years, and 61.2% (n = 208) of them were females. Results showed that 22.9% of the sample (n = 78) had a low familiarity with preventive medicine, whereas 76.8% (n = 261) had a high familiarity. The study sample specified that among all the preventive medicine subjects, screening and control as well as smoking cessation and immunization are "extremely important to learn." In univariable analysis, being a female, medical school, family size, and perception about the importance to learn preventive medicine were associated with the ability to practice it. In multivariable analysis, the perception towards the importance to learn preventive medicine was the only significant determinant: aOR (adjusted odds ratio) for those who "agreed" 17.28 (95% CI aOR 4.44-67.26, P < 0.001) and for "strongly agreed" 35.87 (95% CI aOR 8.04-159.87, P < 0.001). Considering
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Felner, Robert D.; Favazza, Antoinette; Shim, Minsuk; Brand, Stephen; Gu, Kenneth; Noonan, Nancy
2001-01-01
Describes the School Transitional Environment Project and its successor, the Project on High Performance Learning Communities, that have contributed to building a model for school improvement called the High Performance Learning Communities. The model seeks to build the principles of prevention into whole school change. Presents findings from…
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Yap, Tracey L.; Kennerly, Susan M.; Bergstrom, Nancy; Hudak, Sandra L.; Horn, Susan D.
2015-01-01
Pressure ulcers (PrUs) have consistently resisted prevention efforts in long term care (LTC) facilities nationwide. Recent research has described cueing innovations that – when selected according to the assumptions and resources of particular facilities – support best practices of PrU prevention. This paper synthesizes that research into a unified, dynamic logic model to facilitate effective staff implementation of a PrU prevention program. PMID:26066791
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REM sleep selectively prunes and maintains new synapses in development and learning.
Li, Wei; Ma, Lei; Yang, Guang; Gan, Wen-Biao
2017-03-01
The functions and underlying mechanisms of rapid eye movement (REM) sleep remain unclear. Here we show that REM sleep prunes newly formed postsynaptic dendritic spines of layer 5 pyramidal neurons in the mouse motor cortex during development and motor learning. This REM sleep-dependent elimination of new spines facilitates subsequent spine formation during development and when a new motor task is learned, indicating a role for REM sleep in pruning to balance the number of new spines formed over time. Moreover, REM sleep also strengthens and maintains newly formed spines, which are critical for neuronal circuit development and behavioral improvement after learning. We further show that dendritic calcium spikes arising during REM sleep are important for pruning and strengthening new spines. Together, these findings indicate that REM sleep has multifaceted functions in brain development, learning and memory consolidation by selectively eliminating and maintaining newly formed synapses via dendritic calcium spike-dependent mechanisms.
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Fingerprint-Based Machine Learning Approach to Identify Potent and Selective 5-HT2BR Ligands
Directory of Open Access Journals (Sweden)
Krzysztof Rataj
2018-05-01
Full Text Available The identification of subtype-selective GPCR (G-protein coupled receptor ligands is a challenging task. In this study, we developed a computational protocol to find compounds with 5-HT2BR versus 5-HT1BR selectivity. Our approach employs the hierarchical combination of machine learning methods, docking, and multiple scoring methods. First, we applied machine learning tools to filter a large database of druglike compounds by the new Neighbouring Substructures Fingerprint (NSFP. This two-dimensional fingerprint contains information on the connectivity of the substructural features of a compound. Preselected subsets of the database were then subjected to docking calculations. The main indicators of compounds’ selectivity were their different interactions with the secondary binding pockets of both target proteins, while binding modes within the orthosteric binding pocket were preserved. The combined methodology of ligand-based and structure-based methods was validated prospectively, resulting in the identification of hits with nanomolar affinity and ten-fold to ten thousand-fold selectivities.
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International Nuclear Information System (INIS)
Schiff, Rachel; Chamness, Gary C; Brown, Powel H
2003-01-01
Intensive basic and clinical research over the past 20 years has yielded crucial molecular understanding into how estrogen and the estrogen receptor act to regulate breast cancer and has led to the development of more effective, less toxic, and safer hormonal therapy agents for breast cancer management and prevention. Selective potent aromatase inhibitors are now challenging the hitherto gold standard of hormonal therapy, the selective estrogen-receptor modulator tamoxifen. Furthermore, new selective estrogen-receptor modulators such as arzoxifene, currently under clinical development, offer the possibility of selecting one with a more ideal pharmacological profile for treatment and prevention of breast cancer. Two recent studies in preclinical model systems that evaluate mechanisms of action of these new drugs and suggestions about their optimal clinical use are discussed
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Greenwood, B N; Strong, P V; Foley, T E; Thompson, R S; Fleshner, M
2007-02-23
Reduced levels of brain-derived neurotrophic factor (BDNF) in the hippocampus have been implicated in human affective disorders and behavioral stress responses. The current studies examined the role of BDNF in the behavioral consequences of inescapable stress, or learned helplessness. Inescapable stress decreased BDNF mRNA and protein in the hippocampus of sedentary rats. Rats allowed voluntary access to running wheels for either 3 or 6 weeks prior to exposure to stress were protected against stress-induced reductions of hippocampal BDNF protein. The observed prevention of stress-induced deceases in BDNF, however, occurred in a time course inconsistent with the prevention of learned helplessness by wheel running, which is evident following 6 weeks, but not 3 weeks, of wheel running. BDNF suppression in physically active rats was produced by administering a single injection of the selective serotonin reuptake inhibitor fluoxetine (10 mg/kg) just prior to stress. Despite reduced levels of hippocampal BDNF mRNA following stress, physically active rats given the combination of fluoxetine and stress remained resistant against learned helplessness. Sedentary rats given both fluoxetine and stress still demonstrated typical learned helplessness behaviors. Fluoxetine by itself reduced BDNF mRNA in sedentary rats only, but did not affect freezing or escape learning 24 h later. Finally, bilateral injections of BDNF (1 mug) into the dentate gyrus prior to stress prevented stress-induced reductions of hippocampal BDNF but did not prevent learned helplessness in sedentary rats. These data indicate that learned helplessness behaviors are independent of the presence or absence of hippocampal BDNF because blocking inescapable stress-induced BDNF suppression does not always prevent learned helplessness, and learned helplessness does not always occur in the presence of reduced BDNF. Results also suggest that the prevention of stress-induced hippocampal BDNF suppression is not
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Ghoncheh, Rezvan; Gould, Madelyn S; Twisk, Jos Wr; Kerkhof, Ad Jfm; Koot, Hans M
2016-01-29
Face-to-face gatekeeper training can be an effective strategy in the enhancement of gatekeepers' knowledge and self-efficacy in adolescent suicide prevention. However, barriers related to access (eg, time, resources) may hamper participation in face-to-face training sessions. The transition to a Web-based setting could address obstacles associated with face-to-face gatekeeper training. Although Web-based suicide prevention training targeting adolescents exists, so far no randomized controlled trials (RCTs) have been conducted to investigate their efficacy. This RCT study investigated the efficacy of a Web-based adolescent suicide prevention program entitled Mental Health Online, which aimed to improve the knowledge and self-confidence of gatekeepers working with adolescents (12-20 years old). The program consisted of 8 short e-learning modules each capturing an important aspect of the process of early recognition, guidance, and referral of suicidal adolescents, alongside additional information on the topic of (adolescent) suicide prevention. A total of 190 gatekeepers (ages 21 to 62 years) participated in this study and were randomized to either the experimental group or waitlist control group. The intervention was not masked. Participants from both groups completed 3 Web-based assessments (pretest, posttest, and 3-month follow-up). The outcome measures of this study were actual knowledge, and participants' ratings of perceived knowledge and perceived self-confidence using questionnaires developed specifically for this study. The actual knowledge, perceived knowledge, and perceived self-confidence of gatekeepers in the experimental group improved significantly compared to those in the waitlist control group at posttest, and the effects remained significant at 3-month follow-up. The overall effect sizes were 0.76, 1.20, and 1.02, respectively, across assessments. The findings of this study indicate that Web-based suicide prevention e-learning modules can be an
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Yuniarti, E.; Fadilah, M.; Darussyamsu, R.; Nurhayati, N.
2018-04-01
The higher numbers of cases around sexual behavioral deviance on adolescence are significantly related to their knowledge level about the health of the reproduction system. Thus, teenagers, especially school-aged, have to receive the complete information which emphasizes on recognize promotion and prevention knowledge. This article aims to describe information about health promotion and prevention, which delivered by the teacher in Senior High School learning process on topic reproduction system. The data gained through focused observation using observation sheet and camera recorder. Further, data analyzed descriptively. The result show promotion and preventive approach have been inadequately presented. There are two reasons. Firstly, the promotion and preventive value are not technically requested in the final assessment. The second, the explanation tend to refer to consequences existed in the term of the social and religious norm rather than a scientific basis. It can be concluded suggestion to promote health reproduction and prevent the risk of health reproduction need to be implemented more practice with a scientific explanation which is included in a specific program for adolescence reproductive health improvement.
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Pisani, Anthony R.; Wyman, Peter A.; Mohr, David C.; Perrino, Tatiana; Gallo, Carlos; Villamar, Juan; Kendziora, Kimberly; Howe, George W.; Sloboda, Zili; Brown, C. Hendricks
2016-01-01
Internet-connected devices are changing the way people live, work, and relate to one another. For prevention scientists, technological advances create opportunities to promote the welfare of human subjects and society. The challenge is to obtain the benefits while minimizing risks. In this article, we use the guiding principles for ethical human subjects research and proposed changes to the Common Rule regulations, as a basis for discussing selected opportunities and challenges that new techn...
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Machine Learning and Conflict Prediction: A Use Case
Directory of Open Access Journals (Sweden)
Chris Perry
2013-10-01
Full Text Available For at least the last two decades, the international community in general and the United Nations specifically have attempted to develop robust, accurate and effective conflict early warning system for conflict prevention. One potential and promising component of integrated early warning systems lies in the field of machine learning. This paper aims at giving conflict analysis a basic understanding of machine learning methodology as well as to test the feasibility and added value of such an approach. The paper finds that the selection of appropriate machine learning methodologies can offer substantial improvements in accuracy and performance. It also finds that even at this early stage in testing machine learning on conflict prediction, full models offer more predictive power than simply using a prior outbreak of violence as the leading indicator of current violence. This suggests that a refined data selection methodology combined with strategic use of machine learning algorithms could indeed offer a significant addition to the early warning toolkit. Finally, the paper suggests a number of steps moving forward to improve upon this initial test methodology.
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Ndabarora, Eléazar; Mchunu, Gugu
2014-01-01
Various studies have reported that university students, who are mostly young people, rarely use existing HIV/AIDS preventive methods. Although studies have shown that young university students have a high degree of knowledge about HIV/AIDS and HIV modes of transmission, they are still not utilising the existing HIV prevention methods and still engage in risky sexual practices favourable to HIV. Some variables, such as awareness of existing HIV/AIDS prevention methods, have been associated with utilisation of such methods. The study aimed to explore factors that influence use of existing HIV/AIDS prevention methods among university students residing in a selected campus, using the Health Belief Model (HBM) as a theoretical framework. A quantitative research approach and an exploratory-descriptive design were used to describe perceived factors that influence utilisation by university students of HIV/AIDS prevention methods. A total of 335 students completed online and manual questionnaires. Study findings showed that the factors which influenced utilisation of HIV/AIDS prevention methods were mainly determined by awareness of the existing university-based HIV/AIDS prevention strategies. Most utilised prevention methods were voluntary counselling and testing services and free condoms. Perceived susceptibility and perceived threat of HIV/AIDS score was also found to correlate with HIV risk index score. Perceived susceptibility and perceived threat of HIV/AIDS showed correlation with self-efficacy on condoms and their utilisation. Most HBM variables were not predictors of utilisation of HIV/AIDS prevention methods among students. Intervention aiming to improve the utilisation of HIV/AIDS prevention methods among students at the selected university should focus on removing identified barriers, promoting HIV/AIDS prevention services and providing appropriate resources to implement such programmes.
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An Evaluation Model To Select an Integrated Learning System in a Large, Suburban School District.
Curlette, William L.; And Others
The systematic evaluation process used in Georgia's DeKalb County School System to purchase comprehensive instructional software--an integrated learning system (ILS)--is described, and the decision-making model for selection is presented. Selection and implementation of an ILS were part of an instructional technology plan for the DeKalb schools…
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Zhao, H; Ji, Z-H; Liu, C; Yu, X-Y
2015-04-02
Studies demonstrated that chronic high-dose homocysteine administration induced learning and memory impairment in animals. Atractylenolide III (Aen-III), a neuroprotective constituent of Atractylodis macrocephalae Koidz, was isolated in our previous study. In this study, we investigated potential benefits of Aen-III in preventing learning and memory impairment following chronic high-dose homocysteine administration in rats. Results showed that administration of Aen-III significantly ameliorated learning and memory impairment induced by chronic high-dose homocysteine administration in rats, decreased homocysteine-induced reactive oxygen species (ROS) formation and restored homocysteine-induced decrease of phosphorylated protein kinase C expression level. Moreover, Aen-III protected primary cultured neurons from apoptotic death induced by homocysteine treatment. This study provides the first evidence for the neuroprotective effect of Aen-III in preventing learning and impairment induced by chronic administration of homocysteine. Aen-III may have therapeutic potential in treating homocysteine-mediated cognitive impairment and neuronal injury. Copyright © 2015 IBRO. Published by Elsevier Ltd. All rights reserved.
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USING A MULTI CRITERIA DECISION MAKING APPROACH FOR OPEN AND DISTANCE LEARNING SYSTEM SELECTION
KAMIŞLI ÖZTÜRK, Zehra
2015-01-01
Today, there's a wide variety of open and distance learning (ODL) systems around the world. Herein, for lifelong learning how to select an ODL program becomes a critic question for a learner who wants to extent abilities on his/her career path. This is a complex decision problem with interdependent criteria. The Analytic Network Process (ANP) is a multicriteria decision making methodology that reflects these interdependencies. Within &...
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Can non-selective beta-blockers prevent hepatocellular carcinoma in patients with cirrhosis?
Thiele, Maja; Wiest, Reiner; Gluud, Lise Lotte; Albillos, Agustín; Krag, Aleksander
2013-11-01
Hepatocellular carcinoma is the main liver-related cause of death in patients with compensated cirrhosis. The early phases are asymptomatic and the prognosis is poor, which makes prevention essential. We propose that non-selective beta-blockers decrease the incidence and growth of hepatocellular carcinoma via a reduction of the inflammatory load from the gut to the liver and inhibition of angiogenesis. Due to their effect on the portal pressure, non-selective beta-blockers are used for prevention of esophageal variceal bleeding. Recently, non-hemodynamic effects of beta-blockers have received increasing attention. Blockage of β-adrenoceptors in the intestinal mucosa and gut lymphatic tissue together with changes in type and virulence of the intestinal microbiota lead to reduced bacterial translocation and a subsequent decrease in the portal load of pathogen-associated molecular patterns. This may reduce hepatic inflammation. Blockage of β-adrenoceptors also decrease angiogenesis by inhibition of vascular endothelial growth factors. Because gut-derived inflammation and neo-angiogenesis are important in hepatic carcinogenesis, non-selective beta-blockers can potentially reduce the development and growth of hepatocellular carcinoma. Rodent and in vitro studies support the hypothesis, but clinical verification is needed. Different study designs may be considered. The feasibility of a randomized controlled trial is limited due to the necessary large number of patients and long follow-up. Observational studies carry a high risk of bias. The meta-analytic approach may be used if the incidence and mortality of hepatocellular carcinoma can be extracted from trials on variceal bleeding and if the combined sample size and follow up is sufficient. Copyright © 2013 Elsevier Ltd. All rights reserved.
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Feature Selection Methods for Zero-Shot Learning of Neural Activity
Directory of Open Access Journals (Sweden)
Carlos A. Caceres
2017-06-01
Full Text Available Dimensionality poses a serious challenge when making predictions from human neuroimaging data. Across imaging modalities, large pools of potential neural features (e.g., responses from particular voxels, electrodes, and temporal windows have to be related to typically limited sets of stimuli and samples. In recent years, zero-shot prediction models have been introduced for mapping between neural signals and semantic attributes, which allows for classification of stimulus classes not explicitly included in the training set. While choices about feature selection can have a substantial impact when closed-set accuracy, open-set robustness, and runtime are competing design objectives, no systematic study of feature selection for these models has been reported. Instead, a relatively straightforward feature stability approach has been adopted and successfully applied across models and imaging modalities. To characterize the tradeoffs in feature selection for zero-shot learning, we compared correlation-based stability to several other feature selection techniques on comparable data sets from two distinct imaging modalities: functional Magnetic Resonance Imaging and Electrocorticography. While most of the feature selection methods resulted in similar zero-shot prediction accuracies and spatial/spectral patterns of selected features, there was one exception; A novel feature/attribute correlation approach was able to achieve those accuracies with far fewer features, suggesting the potential for simpler prediction models that yield high zero-shot classification accuracy.
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Williams, Jennifer A.; Schmitter-Edgecombe, Maureen; Cook, Diane J.
2016-01-01
Introduction Reducing the amount of testing required to accurately detect cognitive impairment is clinically relevant. The aim of this research was to determine the fewest number of clinical measures required to accurately classify participants as healthy older adult, mild cognitive impairment (MCI) or dementia using a suite of classification techniques. Methods Two variable selection machine learning models (i.e., naive Bayes, decision tree), a logistic regression, and two participant datasets (i.e., clinical diagnosis, clinical dementia rating; CDR) were explored. Participants classified using clinical diagnosis criteria included 52 individuals with dementia, 97 with MCI, and 161 cognitively healthy older adults. Participants classified using CDR included 154 individuals CDR = 0, 93 individuals with CDR = 0.5, and 25 individuals with CDR = 1.0+. Twenty-seven demographic, psychological, and neuropsychological variables were available for variable selection. Results No significant difference was observed between naive Bayes, decision tree, and logistic regression models for classification of both clinical diagnosis and CDR datasets. Participant classification (70.0 – 99.1%), geometric mean (60.9 – 98.1%), sensitivity (44.2 – 100%), and specificity (52.7 – 100%) were generally satisfactory. Unsurprisingly, the MCI/CDR = 0.5 participant group was the most challenging to classify. Through variable selection only 2 – 9 variables were required for classification and varied between datasets in a clinically meaningful way. Conclusions The current study results reveal that machine learning techniques can accurately classifying cognitive impairment and reduce the number of measures required for diagnosis. PMID:26332171
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Deep Learning Questions Can Help Selection of High Ability Candidates for Universities
Mellanby, Jane; Cortina-Borja, Mario; Stein, John
2009-01-01
Selection of students for places at universities mainly depends on GCSE grades and predictions of A-level grades, both of which tend to favour applicants from independent schools. We have therefore developed a new type of test that would measure candidates' "deep learning" approach since this assesses the motivation and creative thinking…
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Stochastic subset selection for learning with kernel machines.
Rhinelander, Jason; Liu, Xiaoping P
2012-06-01
Kernel machines have gained much popularity in applications of machine learning. Support vector machines (SVMs) are a subset of kernel machines and generalize well for classification, regression, and anomaly detection tasks. The training procedure for traditional SVMs involves solving a quadratic programming (QP) problem. The QP problem scales super linearly in computational effort with the number of training samples and is often used for the offline batch processing of data. Kernel machines operate by retaining a subset of observed data during training. The data vectors contained within this subset are referred to as support vectors (SVs). The work presented in this paper introduces a subset selection method for the use of kernel machines in online, changing environments. Our algorithm works by using a stochastic indexing technique when selecting a subset of SVs when computing the kernel expansion. The work described here is novel because it separates the selection of kernel basis functions from the training algorithm used. The subset selection algorithm presented here can be used in conjunction with any online training technique. It is important for online kernel machines to be computationally efficient due to the real-time requirements of online environments. Our algorithm is an important contribution because it scales linearly with the number of training samples and is compatible with current training techniques. Our algorithm outperforms standard techniques in terms of computational efficiency and provides increased recognition accuracy in our experiments. We provide results from experiments using both simulated and real-world data sets to verify our algorithm.
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Banas, Jennifer R.
2014-01-01
Background: Teachers and preservice teachers may neglect intervening into and/or leading efforts to prevent bullying because they the lack confidence to do so. Purpose: The purpose of this study was to determine the impact of authentic learning exercises on health education preservice teachers' self-efficacy to perform bullying prevention…
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Current approaches to prevent NSAID-induced gastropathy – COX selectivity and beyond
Becker, Jan C; Domschke, Wolfram; Pohle, Thorsten
2004-01-01
Gastrointestinal (GI) toxicity associated with nonsteroidal anti-inflammatory drugs (NSAIDs) is still an important medical and socio-economic problem – despite recent pharmaceutical advances. To prevent NSAID-induced gastropathy, three strategies are followed in clinical routine: (i) coprescription of a gastroprotective drug, (ii) use of selective COX-2 inhibitors, and (iii) eradication of Helicobacter pylori. Proton pump inhibitors are the comedication of choice as they effectively reduce gastrointestinal adverse events of NSAIDs and are safe even in long-term use. Co-medication with vitamin C has only been little studied in the prevention of NSAID-induced gastropathy. Apart from scavenging free radicals it is able to induce haeme-oxgenase 1 in gastric cells, a protective enzyme with antioxidant and vasodilative properties. Final results of the celecoxib outcome study (CLASS study) attenuated the initial enthusiasm about the GI safety of selective COX-2 inhibitors, especially in patients concomitantly taking aspirin for cardiovascular prophylaxis. Helicobacter pylori increases the risk for ulcers particularly in NSAID-naive patients and therefore eradication is recommended prior to long-term NSAID therapy at least in patients at high risk. New classes of COX-inhibitors are currently evaluated in clinical studies with very promising results: NSAIDs combined with a nitric oxide releasing moiety (NO-NSAID) and dual inhibitors of COX and 5-LOX. These drugs offer extended anti-inflammatory potency while sparing gastric mucosa. PMID:15563357
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Anca, Maria; Hategan, Carolina
2009-01-01
In the given study dyscalculia is approached in the context of learning difficulties, but also in relation with damaged psychic processes and functions. The practical part of the study describes intervention models from the perspective of dyscalculia prevention and therapymaterialized in personalized intervention programs.
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Prediction of Student Dropout in E-Learning Program Through the Use of Machine Learning Method
Mingjie Tan; Peiji Shao
2015-01-01
The high rate of dropout is a serious problem in E-learning program. Thus it has received extensive concern from the education administrators and researchers. Predicting the potential dropout students is a workable solution to prevent dropout. Based on the analysis of related literature, this study selected student’s personal characteristic and academic performance as input attributions. Prediction models were developed using Artificial Neural Network (ANN), Decision Tree (DT) and Bayesian Ne...
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Vos, H.M.M.; Delft, D.H. Van; Kleijn, M.J.J. de; Nielen, M.M.; Schellevis, F.G.; Lagro-Janssen, A.L.M.
2014-01-01
RATIONALE, AIMS AND OBJECTIVES: In 2011 the module cardiometabolic risk of the Prevention Consultation guideline was introduced in the Netherlands in order to prevent cardiometabolic diseases. We aimed to compare attitudes and working methods of Dutch general practitioners (GPs) towards selective
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Vos, H.M.M.; Delft, D.H.W.J.M. van; Kleijn, M.J.J. de; Nielen, M.M.J.; Schellevis, F.G.; Lagro-Janssen, A.L.M.
2014-01-01
Rationale, aims and objectives; In 2011 the module cardiometabolic risk of the Prevention Consultation guideline was introduced in the Netherlands in order to prevent cardiometabolic diseases. We aimed to compare attitudes and working methods of Dutch general practitioners (GPs) towards selective
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Vos, H.M.M.; Van Delft, D.H.W.J.; de Kleijn, M.J.J.; Nielen, M.M.J.; Schellevis, F.G.; Lagro-Janssen, A.L.M.
2014-01-01
Rationale, aims and objectives In 2011 the module cardiometabolic risk of the Prevention Consultation guideline was introduced in the Netherlands in order to prevent cardiometabolic diseases. We aimed to compare attitudes and working methods of Dutch general practitioners (GPs) towards selective
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Assessing Approaches to Learning in School Readiness
Directory of Open Access Journals (Sweden)
Otilia C. Barbu
2015-07-01
Full Text Available This study examines the psychometric properties of two assessments of children’s approaches to learning: the Devereux Early Childhood Assessment (DECA and a 13-item approaches to learning rating scale (AtL derived from the Arizona Early Learning Standards (AELS. First, we administered questionnaires to 1,145 randomly selected parents/guardians of first-time kindergarteners. Second, we employed confirmatory factor analysis (CFA with parceling for DECA to reduce errors due to item specificity and prevent convergence difficulties when simultaneously estimating DECA and AtL models. Results indicated an overlap of 55% to 72% variance between the domains of the two instruments and suggested that the new AtL instrument is an easily administered alternative to the DECA for measuring children’s approaches to learning. This is one of the first studies that investigated DECA’s approaches to learning dimension and explored the measurement properties of an instrument purposely derived from a state’s early learning guidelines.
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DEFF Research Database (Denmark)
Brønsted, Lone
In Denmark, crime prevention is embedded in state professional practices in kindergartens, schools and youth clubs. These welfare institutions are conceived as safe places that safeguard children and young people through inclusive learning environments, warm and empathic relationships between......-sectional cooperation called “SSP”. SSP is a locally anchored cooperation of the school (S), the social services (S) and the police (P) and its aim is to create a coordinated system of prevention, e.g., to prevent crime or school drop outs. In continuation of this, crime preventive work is understood as a practice...
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The role of manganese in etiopathogenesis and prevention of selected diseases
Directory of Open Access Journals (Sweden)
Katarzyna Zabłocka-Słowińska
2012-08-01
Full Text Available Manganese (Mn is an essential trace element, necessary for development and growth of the organism. The adequate content of this element in the body determines proper metabolism of amino acids, cholesterol and carbohydrates. This mineral influences activity of several enzymes involved in metabolic and redox processes. Mn absorption and retention disturbances may participate in etiopathogenesis of some diseases and disorders.This article is a review of knowledge about the role of Mn in etiopathogenesis and prevention of selected diseases: brain disorders, diabetes, lipid disturbances and cancers.
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Implicit visual learning and the expression of learning.
Haider, Hilde; Eberhardt, Katharina; Kunde, Alexander; Rose, Michael
2013-03-01
Although the existence of implicit motor learning is now widely accepted, the findings concerning perceptual implicit learning are ambiguous. Some researchers have observed perceptual learning whereas other authors have not. The review of the literature provides different reasons to explain this ambiguous picture, such as differences in the underlying learning processes, selective attention, or differences in the difficulty to express this knowledge. In three experiments, we investigated implicit visual learning within the original serial reaction time task. We used different response devices (keyboard vs. mouse) in order to manipulate selective attention towards response dimensions. Results showed that visual and motor sequence learning differed in terms of RT-benefits, but not in terms of the amount of knowledge assessed after training. Furthermore, visual sequence learning was modulated by selective attention. However, the findings of all three experiments suggest that selective attention did not alter implicit but rather explicit learning processes. Copyright © 2012 Elsevier Inc. All rights reserved.
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Huynh, Chi; Wong, Ian C K; Correa-West, Jo; Terry, David; McCarthy, Suzanne
2017-04-01
Since the publication of To Err Is Human: Building a Safer Health System in 1999, there has been much research conducted into the epidemiology, nature and causes of medication errors in children, from prescribing and supply to administration. It is reassuring to see growing evidence of improving medication safety in children; however, based on media reports, it can be seen that serious and fatal medication errors still occur. This critical opinion article examines the problem of medication errors in children and provides recommendations for research, training of healthcare professionals and a culture shift towards dealing with medication errors. There are three factors that we need to consider to unravel what is missing and why fatal medication errors still occur. (1) Who is involved and affected by the medication error? (2) What factors hinder staff and organisations from learning from mistakes? Does the fear of litigation and criminal charges deter healthcare professionals from voluntarily reporting medication errors? (3) What are the educational needs required to prevent medication errors? It is important to educate future healthcare professionals about medication errors and human factors to prevent these from happening. Further research is required to apply aviation's 'black box' principles in healthcare to record and learn from near misses and errors to prevent future events. There is an urgent need for the black box investigations to be published and made public for the benefit of other organisations that may have similar potential risks for adverse events. International sharing of investigations and learning is also needed.
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Javier, Joyce R.; Chamberlain, Lisa J.; Rivera, Kahealani K.; Gonzalez, Sarah E.; Mendoza, Fernando S.; Huffman, Lynne C.
2014-01-01
Background Filipino Americans have more adolescent pregnancies than other Asian-Pacific Islanders (APIs). Few community–academic collaborations have addressed adolescent pregnancy prevention in this community. Objectives We sought to describe the lessons learned from and impact of a community-based teen pregnancy prevention program for Filipino Americans implemented by a Filipina pediatrics resident. Methods We formed a community–academic partnership between the Filipino Youth Coalition, a community-based organization (CBO) in San Jose, California, and the Stanford School of Medicine’s Pediatric Advocacy Program. We developed a culturally tailored parent–teen conference addressing adolescent pregnancy prevention in Filipino Americans. We qualitatively and quantitatively evaluated this intervention by collecting both pre- and post-conference data using a convenience sample design. Lessons Learned Engaging particular aspects of Filipino culture (i.e., religion and intergenerational differences) helped to make this community–academic partnership successful. For physicians-in-training who are conducting community-based participatory research (CBPR), project challenges may include difficulties in building and maintaining academic–community relationships, struggles to promote sustainability, and conflicting goals of “community insiders” and “academic outsiders.” Authors offer insights and implications for residents interested in practicing CBPR. Conclusion CBPR is a key tool for exploring health issues in understudied populations. CBPR experiences can provide meaningful educational opportunities for physicians-in-training and can build sustained capacity in CBOs. They can also help residents to develop analytic skills, directly affect the health of the communities they serve, and, for minority physicians, give back to the communities they call home. PMID:21169708
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Norman, Kenneth A; Newman, Ehren L; Perotte, Adler J
2005-11-01
The stability-plasticity problem (i.e. how the brain incorporates new information into its model of the world, while at the same time preserving existing knowledge) has been at the forefront of computational memory research for several decades. In this paper, we critically evaluate how well the Complementary Learning Systems theory of hippocampo-cortical interactions addresses the stability-plasticity problem. We identify two major challenges for the model: Finding a learning algorithm for cortex and hippocampus that enacts selective strengthening of weak memories, and selective punishment of competing memories; and preventing catastrophic forgetting in the case of non-stationary environments (i.e. when items are temporarily removed from the training set). We then discuss potential solutions to these problems: First, we describe a recently developed learning algorithm that leverages neural oscillations to find weak parts of memories (so they can be strengthened) and strong competitors (so they can be punished), and we show how this algorithm outperforms other learning algorithms (CPCA Hebbian learning and Leabra at memorizing overlapping patterns. Second, we describe how autonomous re-activation of memories (separately in cortex and hippocampus) during REM sleep, coupled with the oscillating learning algorithm, can reduce the rate of forgetting of input patterns that are no longer present in the environment. We then present a simple demonstration of how this process can prevent catastrophic interference in an AB-AC learning paradigm.
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Dalton, James T; Taylor, Ryan P; Mohler, Michael L; Steiner, Mitchell S
2013-12-01
This review highlights selective androgen receptor modulators (SARMs) as emerging agents in late-stage clinical development for the prevention and treatment of muscle wasting associated with cancer. Muscle wasting, including a loss of skeletal muscle, is a cancer-related symptom that begins early in the progression of cancer and affects a patient's quality of life, ability to tolerate chemotherapy, and survival. SARMs increase muscle mass and improve physical function in healthy and diseased individuals, and potentially may provide a new therapy for muscle wasting and cancer cachexia. SARMs modulate the same anabolic pathways targeted with classical steroidal androgens, but within the dose range in which expected effects on muscle mass and function are seen androgenic side-effects on prostate, skin, and hair have not been observed. Unlike testosterone, SARMs are orally active, nonaromatizable, nonvirilizing, and tissue-selective anabolic agents. Recent clinical efficacy data for LGD-4033, MK-0773, MK-3984, and enobosarm (GTx-024, ostarine, and S-22) are reviewed. Enobosarm, a nonsteroidal SARM, is the most well characterized clinically, and has consistently demonstrated increases in lean body mass and better physical function across several populations along with a lower hazard ratio for survival in cancer patients. Completed in May 2013, results for the Phase III clinical trials entitled Prevention and treatment Of muscle Wasting in patiEnts with Cancer1 (POWER1) and POWER2 evaluating enobosarm for the prevention and treatment of muscle wasting in patients with nonsmall cell lung cancer will be available soon, and will potentially establish a SARM, enobosarm, as the first drug for the prevention and treatment of muscle wasting in cancer patients.
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... Sexual, & Bladder Problems Clinical Trials Preventing Type 2 Diabetes Perhaps you have learned that you have a ... I lower my chances of developing type 2 diabetes? Research such as the Diabetes Prevention Program shows ...
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Preventing Crime through Selective Incapacitation
Vollaard, B.A.
2010-01-01
Making the length of a prison sentence conditional on an individual’s offense history is shown to be a powerful way of preventing crime. Under a law adopted in the Netherlands in 2001, prolific offenders could be sentenced to a prison term that was some ten times longer than usual. We exploit
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Preventing Crime Through Selective Incapacitation
Vollaard, B.A.
2011-01-01
Making the length of a prison sentence conditional on an individual’s offense history is shown to be a powerful way of preventing crime. Under a law adopted in the Netherlands in 2001, prolific offenders could be sentenced to a prison term that was some ten times longer than usual. We exploit
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Energy Technology Data Exchange (ETDEWEB)
Richards, Joseph W.; Starr, Dan L.; Miller, Adam A.; Bloom, Joshua S.; Butler, Nathaniel R.; Berian James, J. [Astronomy Department, University of California, Berkeley, CA 94720-7450 (United States); Brink, Henrik [Dark Cosmology Centre, Juliane Maries Vej 30, 2100 Copenhagen O (Denmark); Long, James P.; Rice, John, E-mail: jwrichar@stat.berkeley.edu [Statistics Department, University of California, Berkeley, CA 94720-7450 (United States)
2012-01-10
Despite the great promise of machine-learning algorithms to classify and predict astrophysical parameters for the vast numbers of astrophysical sources and transients observed in large-scale surveys, the peculiarities of the training data often manifest as strongly biased predictions on the data of interest. Typically, training sets are derived from historical surveys of brighter, more nearby objects than those from more extensive, deeper surveys (testing data). This sample selection bias can cause catastrophic errors in predictions on the testing data because (1) standard assumptions for machine-learned model selection procedures break down and (2) dense regions of testing space might be completely devoid of training data. We explore possible remedies to sample selection bias, including importance weighting, co-training, and active learning (AL). We argue that AL-where the data whose inclusion in the training set would most improve predictions on the testing set are queried for manual follow-up-is an effective approach and is appropriate for many astronomical applications. For a variable star classification problem on a well-studied set of stars from Hipparcos and Optical Gravitational Lensing Experiment, AL is the optimal method in terms of error rate on the testing data, beating the off-the-shelf classifier by 3.4% and the other proposed methods by at least 3.0%. To aid with manual labeling of variable stars, we developed a Web interface which allows for easy light curve visualization and querying of external databases. Finally, we apply AL to classify variable stars in the All Sky Automated Survey, finding dramatic improvement in our agreement with the ASAS Catalog of Variable Stars, from 65.5% to 79.5%, and a significant increase in the classifier's average confidence for the testing set, from 14.6% to 42.9%, after a few AL iterations.
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International Nuclear Information System (INIS)
Richards, Joseph W.; Starr, Dan L.; Miller, Adam A.; Bloom, Joshua S.; Butler, Nathaniel R.; Berian James, J.; Brink, Henrik; Long, James P.; Rice, John
2012-01-01
Despite the great promise of machine-learning algorithms to classify and predict astrophysical parameters for the vast numbers of astrophysical sources and transients observed in large-scale surveys, the peculiarities of the training data often manifest as strongly biased predictions on the data of interest. Typically, training sets are derived from historical surveys of brighter, more nearby objects than those from more extensive, deeper surveys (testing data). This sample selection bias can cause catastrophic errors in predictions on the testing data because (1) standard assumptions for machine-learned model selection procedures break down and (2) dense regions of testing space might be completely devoid of training data. We explore possible remedies to sample selection bias, including importance weighting, co-training, and active learning (AL). We argue that AL—where the data whose inclusion in the training set would most improve predictions on the testing set are queried for manual follow-up—is an effective approach and is appropriate for many astronomical applications. For a variable star classification problem on a well-studied set of stars from Hipparcos and Optical Gravitational Lensing Experiment, AL is the optimal method in terms of error rate on the testing data, beating the off-the-shelf classifier by 3.4% and the other proposed methods by at least 3.0%. To aid with manual labeling of variable stars, we developed a Web interface which allows for easy light curve visualization and querying of external databases. Finally, we apply AL to classify variable stars in the All Sky Automated Survey, finding dramatic improvement in our agreement with the ASAS Catalog of Variable Stars, from 65.5% to 79.5%, and a significant increase in the classifier's average confidence for the testing set, from 14.6% to 42.9%, after a few AL iterations.
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Richards, Joseph W.; Starr, Dan L.; Brink, Henrik; Miller, Adam A.; Bloom, Joshua S.; Butler, Nathaniel R.; James, J. Berian; Long, James P.; Rice, John
2012-01-01
Despite the great promise of machine-learning algorithms to classify and predict astrophysical parameters for the vast numbers of astrophysical sources and transients observed in large-scale surveys, the peculiarities of the training data often manifest as strongly biased predictions on the data of interest. Typically, training sets are derived from historical surveys of brighter, more nearby objects than those from more extensive, deeper surveys (testing data). This sample selection bias can cause catastrophic errors in predictions on the testing data because (1) standard assumptions for machine-learned model selection procedures break down and (2) dense regions of testing space might be completely devoid of training data. We explore possible remedies to sample selection bias, including importance weighting, co-training, and active learning (AL). We argue that AL—where the data whose inclusion in the training set would most improve predictions on the testing set are queried for manual follow-up—is an effective approach and is appropriate for many astronomical applications. For a variable star classification problem on a well-studied set of stars from Hipparcos and Optical Gravitational Lensing Experiment, AL is the optimal method in terms of error rate on the testing data, beating the off-the-shelf classifier by 3.4% and the other proposed methods by at least 3.0%. To aid with manual labeling of variable stars, we developed a Web interface which allows for easy light curve visualization and querying of external databases. Finally, we apply AL to classify variable stars in the All Sky Automated Survey, finding dramatic improvement in our agreement with the ASAS Catalog of Variable Stars, from 65.5% to 79.5%, and a significant increase in the classifier's average confidence for the testing set, from 14.6% to 42.9%, after a few AL iterations.
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King, Adam C; Newell, Karl M
2015-10-01
The experiment investigated the effect of selectively augmenting faster time scales of visual feedback information on the learning and transfer of continuous isometric force tracking tasks to test the generality of the self-organization of 1/f properties of force output. Three experimental groups tracked an irregular target pattern either under a standard fixed gain condition or with selectively enhancement in the visual feedback display of intermediate (4-8 Hz) or high (8-12 Hz) frequency components of the force output. All groups reduced tracking error over practice, with the error lowest in the intermediate scaling condition followed by the high scaling and fixed gain conditions, respectively. Selective visual scaling induced persistent changes across the frequency spectrum, with the strongest effect in the intermediate scaling condition and positive transfer to novel feedback displays. The findings reveal an interdependence of the timescales in the learning and transfer of isometric force output frequency structures consistent with 1/f process models of the time scales of motor output variability.
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Gabay, Yafit; Goldfarb, Liat
2017-07-01
Although Attention-Deficit Hyperactivity Disorder (ADHD) is closely linked to executive function deficits, it has recently been attributed to procedural learning impairments that are quite distinct from the former. These observations challenge the ability of the executive function framework solely to account for the diverse range of symptoms observed in ADHD. A recent neurocomputational model emphasizes the role of striatal dopamine (DA) in explaining ADHD's broad range of deficits, but the link between this model and procedural learning impairments remains unclear. Significantly, feedback-based procedural learning is hypothesized to be disrupted in ADHD because of the involvement of striatal DA in this type of learning. In order to test this assumption, we employed two variants of a probabilistic category learning task known from the neuropsychological literature. Feedback-based (FB) and paired associate-based (PA) probabilistic category learning were employed in a non-medicated sample of ADHD participants and neurotypical participants. In the FB task, participants learned associations between cues and outcomes initially by guessing and subsequently through feedback indicating the correctness of the response. In the PA learning task, participants viewed the cue and its associated outcome simultaneously without receiving an overt response or corrective feedback. In both tasks, participants were trained across 150 trials. Learning was assessed in a subsequent test without a presentation of the outcome or corrective feedback. Results revealed an interesting disassociation in which ADHD participants performed as well as control participants in the PA task, but were impaired compared with the controls in the FB task. The learning curve during FB training differed between the two groups. Taken together, these results suggest that the ability to incrementally learn by feedback is selectively disrupted in ADHD participants. These results are discussed in relation to both
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Directory of Open Access Journals (Sweden)
Nortje, F. D.
2013-05-01
Full Text Available The Toyota Production System (TPS has been cited as being the pinnacle of continuous improvement approaches in manufacturing organisations, and many models of the TPS are well known. However, some authors question the effectiveness of established approaches, and propose Batesons theory of learning [1] to be an effective way to explain phenomena like the TPS. This paper investigates the degree to which TPS elements are found in selected South African organisations. It constructs a model of the TPS using Bateson's theory of learning as a framework. The adoption of TPS elements is investigated through multiple qualitative case studies in seven organisations. The analysis follows a clustering and cross-case approach combined with pattern matching. While elements vary in their use, the selected organisations practise the TPS substantially less than the model advocates, with the model being least practised in low volume job/batch manufacturing. Product-process differences and higher levels of the TPS model may clarify peculiar outcomes.
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LENUS (Irish Health Repository)
O'Neill, E
2011-12-01
An online infection prevention and control programme for medical students was developed and assessed. There was a statistically significant improvement (P<0.0001) in the knowledge base among 517 students after completing two modules. The majority of students who completed the evaluation were positive about the learning experience.
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Downing, David L.
2009-01-01
This study describes and implements a necessary preliminary strategic planning procedure, the Internal Environmental Scanning (IES), and discusses its relevance to strategic planning and university-sponsored lifelong learning program model selection. Employing a qualitative research methodology, a proposed lifelong learning-centric IES process…
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Extending the Peak Bandwidth of Parameters for Softmax Selection in Reinforcement Learning.
Iwata, Kazunori
2016-05-11
Softmax selection is one of the most popular methods for action selection in reinforcement learning. Although various recently proposed methods may be more effective with full parameter tuning, implementing a complicated method that requires the tuning of many parameters can be difficult. Thus, softmax selection is still worth revisiting, considering the cost savings of its implementation and tuning. In fact, this method works adequately in practice with only one parameter appropriately set for the environment. The aim of this paper is to improve the variable setting of this method to extend the bandwidth of good parameters, thereby reducing the cost of implementation and parameter tuning. To achieve this, we take advantage of the asymptotic equipartition property in a Markov decision process to extend the peak bandwidth of softmax selection. Using a variety of episodic tasks, we show that our setting is effective in extending the bandwidth and that it yields a better policy in terms of stability. The bandwidth is quantitatively assessed in a series of statistical tests.
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Directory of Open Access Journals (Sweden)
Dimka Karastoyanova
2012-01-01
Full Text Available The performance of business processes is measured and monitored in terms of Key Performance Indicators (KPIs. If the monitoring results show that the KPI targets are violated, the underlying reasons have to be identified and the process should be adapted accordingly to address the violations. In this paper we propose an integrated monitoring, prediction and adaptation approach for preventing KPI violations of business process instances. KPIs are monitored continuously while the process is executed. Additionally, based on KPI measurements of historical process instances we use decision tree learning to construct classification models which are then used to predict the KPI value of an instance while it is still running. If a KPI violation is predicted, we identify adaptation requirements and adaptation strategies in order to prevent the violation.
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Directory of Open Access Journals (Sweden)
R. Jegadeeshwaran
2015-03-01
Full Text Available In automobile, brake system is an essential part responsible for control of the vehicle. Any failure in the brake system impacts the vehicle's motion. It will generate frequent catastrophic effects on the vehicle cum passenger's safety. Thus the brake system plays a vital role in an automobile and hence condition monitoring of the brake system is essential. Vibration based condition monitoring using machine learning techniques are gaining momentum. This study is one such attempt to perform the condition monitoring of a hydraulic brake system through vibration analysis. In this research, the performance of a Clonal Selection Classification Algorithm (CSCA for brake fault diagnosis has been reported. A hydraulic brake system test rig was fabricated. Under good and faulty conditions of a brake system, the vibration signals were acquired using a piezoelectric transducer. The statistical parameters were extracted from the vibration signal. The best feature set was identified for classification using attribute evaluator. The selected features were then classified using CSCA. The classification accuracy of such artificial intelligence technique has been compared with other machine learning approaches and discussed. The Clonal Selection Classification Algorithm performs better and gives the maximum classification accuracy (96% for the fault diagnosis of a hydraulic brake system.
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Raaijmakers, Steven F.; Baars, Martine; Schaap, Lydia; Paas, Fred; van Merriënboer, Jeroen; van Gog, Tamara
2018-01-01
Self-assessment and task-selection skills are crucial in self-regulated learning situations in which students can choose their own tasks. Prior research suggested that training with video modeling examples, in which another person (the model) demonstrates and explains the cyclical process of problem-solving task performance, self-assessment, and…
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Kiewik, M.; Nagel, J.E.L. van der; Engels, R.C.M.E.; Jong, C.A.J. de
2017-01-01
Background and aims: Adolescents with Intellectual Disability (ID) are at risk for tobacco and alcohol use, yet little or no prevention programs are available for this group. 'Prepared on time' is an e-learning program based on the attitude - social influence - efficacy model originally developed
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System Quality Characteristics for Selecting Mobile Learning Applications
Sarrab, Mohamed; Al-Shihi, Hafedh; Al-Manthari, Bader
2015-01-01
The majority of M-learning (Mobile learning) applications available today are developed for the formal learning and education environment. These applications are characterized by the improvement in the interaction between learners and instructors to provide high interaction and flexibility to the learning process. M-learning is gaining increased…
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Kiewik, Marion; VanDerNagel, Joanne E L; Engels, Rutger C M E; DeJong, Cor A
2017-04-01
Adolescents with Intellectual Disability (ID) are at risk for tobacco and alcohol use, yet little or no prevention programs are available for this group. 'Prepared on time' is an e-learning program based on the attitude - social influence - efficacy model originally developed for fifth and sixth grades of mainstream primary schools. The goals of this study were (1) to examine the lifetime use of tobacco and alcohol among this target group and (2) to gain a first impression of the efficacy of 'Prepared on time' among 12-16-year old students with moderate or mild ID (MMID). Students form three secondary special-needs schools were assigned to the experimental (e-learning) group (n=37) or the control group (n=36). Pre-intervention and follow-up data (3 weeks after completion) were gathered using semi-structured interviews inquiring about substance use among students with MMID and the behavioral determinants of attitude, subjective norm, modelling, intention, and knowledge. The lifetime tobacco use and alcohol consumption rates in our sample were 25% and 59%, respectively. The e-learning program had a positive effect on the influence of modelling of classmates and friends. No significant effects were found on other behavioral determinants and knowledge. A substantial proportion of adolescents with MMID in secondary special-needs schools use tobacco or alcohol. This study showed that an e-learning prevention program can be feasible for adolescents with MMID. Copyright © 2016 Elsevier Ltd. All rights reserved.
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2013-01-01
This study examined how parenting and family characteristics targeted in a selective prevention program mediated effects on key youth proximal outcomes related to violence perpetration. The selective intervention was evaluated within the context of a multi-site trial involving random assignment of 37 schools to four conditions: a universal intervention composed of a student social-cognitive curriculum and teacher training, a selective family-focused intervention with a subset of high-risk students, a condition combining these two interventions, and a no-intervention control condition. Two cohorts of sixth-grade students (total N=1,062) exhibiting high levels of aggression and social influence were the sample for this study. Analyses of pre-post change compared to controls using intent-to-treat analyses found no significant effects. However, estimates incorporating participation of those assigned to the intervention and predicted participation among those not assigned revealed significant positive effects on student aggression, use of aggressive strategies for conflict management, and parental estimation of student’s valuing of achievement. Findings also indicated intervention effects on two targeted family processes: discipline practices and family cohesion. Mediation analyses found evidence that change in these processes mediated effects on some outcomes, notably aggressive behavior and valuing of school achievement. Results support the notion that changing parenting practices and the quality of family relationships can prevent the escalation in aggression and maintain positive school engagement for high-risk youth. PMID:21932067
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Tamiya, Satoshi
2014-01-01
Multilingualism poses unique psychiatric problems, especially in the field of child psychiatry. The author discusses several linguistic and transcultural issues in relation to Language Disorder, Specific Learning Disorder and Selective Mutism. Linguistic characteristics of multiple language development, including so-called profile effects and code-switching, need to be understood for differential diagnosis. It is also emphasized that Language Disorder in a bilingual person is not different or worse than that in a monolingual person. Second language proficiency, cultural background and transfer from the first language all need to be considered in an evaluation for Specific Learning Disorder. Selective Mutism has to be differentiated from the silent period observed in the normal successive bilingual development. The author concludes the review by remarking on some caveats around methods of language evaluation in a multilingual person.
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Stice, Eric; Rohde, Paul; Shaw, Heather; Marti, C. Nathan
2012-01-01
Objective: Evaluate a selective prevention program targeting both eating disorder symptoms and unhealthy weight gain in young women. Method: Female college students at high-risk for these outcomes by virtue of body image concerns (N = 398; M age = 18.4 years, SD = 0.6) were randomized to the Healthy Weight group-based 4-hr prevention program,…
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Yu, Jianbo
2016-11-01
The vibration signals of faulty machine are generally non-stationary and nonlinear under those complicated working conditions. Thus, it is a big challenge to extract and select the effective features from vibration signals for machinery fault diagnosis. This paper proposes a new manifold learning algorithm, joint global and local/nonlocal discriminant analysis (GLNDA), which aims to extract effective intrinsic geometrical information from the given vibration data. Comparisons with other regular methods, principal component analysis (PCA), local preserving projection (LPP), linear discriminant analysis (LDA) and local LDA (LLDA), illustrate the superiority of GLNDA in machinery fault diagnosis. Based on the extracted information by GLNDA, a GLNDA-based Fisher discriminant rule (FDR) is put forward and applied to machinery fault diagnosis without additional recognizer construction procedure. By importing Bagging into GLNDA score-based feature selection and FDR, a novel manifold ensemble method (selective GLNDA ensemble, SE-GLNDA) is investigated for machinery fault diagnosis. The motivation for developing ensemble of manifold learning components is that it can achieve higher accuracy and applicability than single component in machinery fault diagnosis. The effectiveness of the SE-GLNDA-based fault diagnosis method has been verified by experimental results from bearing full life testers.
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The attention habit: how reward learning shapes attentional selection.
Anderson, Brian A
2016-04-01
There is growing consensus that reward plays an important role in the control of attention. Until recently, reward was thought to influence attention indirectly by modulating task-specific motivation and its effects on voluntary control over selection. Such an account was consistent with the goal-directed (endogenous) versus stimulus-driven (exogenous) framework that had long dominated the field of attention research. Now, a different perspective is emerging. Demonstrations that previously reward-associated stimuli can automatically capture attention even when physically inconspicuous and task-irrelevant challenge previously held assumptions about attentional control. The idea that attentional selection can be value driven, reflecting a distinct and previously unrecognized control mechanism, has gained traction. Since these early demonstrations, the influence of reward learning on attention has rapidly become an area of intense investigation, sparking many new insights. The result is an emerging picture of how the reward system of the brain automatically biases information processing. Here, I review the progress that has been made in this area, synthesizing a wealth of recent evidence to provide an integrated, up-to-date account of value-driven attention and some of its broader implications. © 2015 New York Academy of Sciences.
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Centers for Disease Control (CDC) Podcasts
2015-01-08
Cervical cancer can be prevented. Listen as two friendsâone a doctorâtalk about screening tests and early detection. Learn what test you might need. Created: 1/8/2015 by National Center for Chronic Disease Prevention and Health Promotion (NCCDPHP). Date Released: 1/8/2015.
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Selective attention and recognition: effects of congruency on episodic learning.
Rosner, Tamara M; D'Angelo, Maria C; MacLellan, Ellen; Milliken, Bruce
2015-05-01
Recent research on cognitive control has focused on the learning consequences of high selective attention demands in selective attention tasks (e.g., Botvinick, Cognit Affect Behav Neurosci 7(4):356-366, 2007; Verguts and Notebaert, Psychol Rev 115(2):518-525, 2008). The current study extends these ideas by examining the influence of selective attention demands on remembering. In Experiment 1, participants read aloud the red word in a pair of red and green spatially interleaved words. Half of the items were congruent (the interleaved words had the same identity), and the other half were incongruent (the interleaved words had different identities). Following the naming phase, participants completed a surprise recognition memory test. In this test phase, recognition memory was better for incongruent than for congruent items. In Experiment 2, context was only partially reinstated at test, and again recognition memory was better for incongruent than for congruent items. In Experiment 3, all of the items contained two different words, but in one condition the words were presented close together and interleaved, while in the other condition the two words were spatially separated. Recognition memory was better for the interleaved than for the separated items. This result rules out an interpretation of the congruency effects on recognition in Experiments 1 and 2 that hinges on stronger relational encoding for items that have two different words. Together, the results support the view that selective attention demands for incongruent items lead to encoding that improves recognition.
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Directory of Open Access Journals (Sweden)
Liu Qingzhong
2011-12-01
Full Text Available Abstract Background Microarray data have a high dimension of variables and a small sample size. In microarray data analyses, two important issues are how to choose genes, which provide reliable and good prediction for disease status, and how to determine the final gene set that is best for classification. Associations among genetic markers mean one can exploit information redundancy to potentially reduce classification cost in terms of time and money. Results To deal with redundant information and improve classification, we propose a gene selection method, Recursive Feature Addition, which combines supervised learning and statistical similarity measures. To determine the final optimal gene set for prediction and classification, we propose an algorithm, Lagging Prediction Peephole Optimization. By using six benchmark microarray gene expression data sets, we compared Recursive Feature Addition with recently developed gene selection methods: Support Vector Machine Recursive Feature Elimination, Leave-One-Out Calculation Sequential Forward Selection and several others. Conclusions On average, with the use of popular learning machines including Nearest Mean Scaled Classifier, Support Vector Machine, Naive Bayes Classifier and Random Forest, Recursive Feature Addition outperformed other methods. Our studies also showed that Lagging Prediction Peephole Optimization is superior to random strategy; Recursive Feature Addition with Lagging Prediction Peephole Optimization obtained better testing accuracies than the gene selection method varSelRF.
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Healthy People 2020 Objectives for Violence Prevention and the Role of Nursing.
Simon, Thomas R; Hurvitz, Kimberly
2014-01-31
Violence, including child maltreatment, youth violence, intimate partner violence, and sexual violence, is a significant public health problem in the United States. A public health approach can help providers understand the health burden from violence, evaluate evidence for prevention strategies, and learn where to turn for information about planning and implementing prevention strategies for this preventable problem. For the past three decades, the U.S. Department of Health and Human Services has published "Healthy People" objectives for the next decade. The Healthy People 2020 initiative includes 13 measurable objectives related to violence prevention, one of which was selected as a Healthy People 2020 Leading Health Indicator. Progress to achieve these objectives can save thousands of lives, reduce the suffering of victims and their families, and decrease financial cost to the law enforcement and healthcare systems. The role that nurses can and do play in violence prevention is critical and extends beyond just caring for victims to also include preventing violence before it happens. This article summarizes the violence prevention objectives in Healthy People 2020 and the resources for prevention available to support nurses and others as they move prevention efforts forward in communities to stop violence before it starts.
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Gene selection for microarray data classification via subspace learning and manifold regularization.
Tang, Chang; Cao, Lijuan; Zheng, Xiao; Wang, Minhui
2017-12-19
With the rapid development of DNA microarray technology, large amount of genomic data has been generated. Classification of these microarray data is a challenge task since gene expression data are often with thousands of genes but a small number of samples. In this paper, an effective gene selection method is proposed to select the best subset of genes for microarray data with the irrelevant and redundant genes removed. Compared with original data, the selected gene subset can benefit the classification task. We formulate the gene selection task as a manifold regularized subspace learning problem. In detail, a projection matrix is used to project the original high dimensional microarray data into a lower dimensional subspace, with the constraint that the original genes can be well represented by the selected genes. Meanwhile, the local manifold structure of original data is preserved by a Laplacian graph regularization term on the low-dimensional data space. The projection matrix can serve as an importance indicator of different genes. An iterative update algorithm is developed for solving the problem. Experimental results on six publicly available microarray datasets and one clinical dataset demonstrate that the proposed method performs better when compared with other state-of-the-art methods in terms of microarray data classification. Graphical Abstract The graphical abstract of this work.
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Directory of Open Access Journals (Sweden)
Yang Sun
2018-01-01
Full Text Available Using Pareto optimization in Multi-Objective Reinforcement Learning (MORL leads to better learning results for network defense games. This is particularly useful for network security agents, who must often balance several goals when choosing what action to take in defense of a network. If the defender knows his preferred reward distribution, the advantages of Pareto optimization can be retained by using a scalarization algorithm prior to the implementation of the MORL. In this paper, we simulate a network defense scenario by creating a multi-objective zero-sum game and using Pareto optimization and MORL to determine optimal solutions and compare those solutions to different scalarization approaches. We build a Pareto Defense Strategy Selection Simulator (PDSSS system for assisting network administrators on decision-making, specifically, on defense strategy selection, and the experiment results show that the Satisficing Trade-Off Method (STOM scalarization approach performs better than linear scalarization or GUESS method. The results of this paper can aid network security agents attempting to find an optimal defense policy for network security games.
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Ghoncheh, Rezvan; Kerkhof, Ad J F M; Koot, Hans M
2014-02-08
Providing e-learning modules can be an effective strategy for enhancing gatekeepers' knowledge, self-confidence and skills in adolescent suicide prevention. The aim of this study was to test the effectiveness of an online training program called Mental Health Online which consists of eight short e-learning modules, each capturing an important aspect of the process of recognition, guidance and referral of suicidal adolescents (12-20 years). The primary outcomes of this study are participant's ratings on perceived knowledge, perceived self-confidence, and actual knowledge regarding adolescent suicidality. A randomized controlled trial will be carried out among 154 gatekeepers. After completing the first assessment (pre-test), participants will be randomly assigned to either the experimental group or the waitlist control group. One week after completing the first assessment the experimental group will have access to the website Mental Health Online containing the eight e-learning modules and additional information on adolescent suicide prevention. Participants in both conditions will be assessed 4 weeks after completing the first assessment (post-test), and 12 weeks after completing the post-test (follow-up). At post-test, participants from the experimental group are asked to complete an evaluation questionnaire on the modules. The waitlist control group will have access to the modules and additional information on the website after completing the follow-up assessment. Gatekeepers can benefit from e-learning modules on adolescent suicide prevention. This approach allows them to learn about this sensitive subject at their own pace and from any given location, as long as they have access to the Internet. Given the flexible nature of the program, each participant can compose his/her own training creating an instant customized course with the required steps in adolescent suicide prevention. Netherlands Trial Register NTR3625.
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Feature Selection with Conjunctions of Decision Stumps and Learning from Microarray Data.
Shah, M; Marchand, M; Corbeil, J
2012-01-01
One of the objectives of designing feature selection learning algorithms is to obtain classifiers that depend on a small number of attributes and have verifiable future performance guarantees. There are few, if any, approaches that successfully address the two goals simultaneously. To the best of our knowledge, such algorithms that give theoretical bounds on the future performance have not been proposed so far in the context of the classification of gene expression data. In this work, we investigate the premise of learning a conjunction (or disjunction) of decision stumps in Occam's Razor, Sample Compression, and PAC-Bayes learning settings for identifying a small subset of attributes that can be used to perform reliable classification tasks. We apply the proposed approaches for gene identification from DNA microarray data and compare our results to those of the well-known successful approaches proposed for the task. We show that our algorithm not only finds hypotheses with a much smaller number of genes while giving competitive classification accuracy but also having tight risk guarantees on future performance, unlike other approaches. The proposed approaches are general and extensible in terms of both designing novel algorithms and application to other domains.
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2012-10-01
PP65-11 provides two approaches for selecting preventive measures: (i) a performance approach based on laboratory testing, and (ii) a prescriptive approach based on a consideration of the reactivity of the aggregate, type and size of structure, expos...
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Hu, Jiehui; Qi, Song; Becker, Benjamin; Luo, Lizhu; Gao, Shan; Gong, Qiyong; Hurlemann, René; Kendrick, Keith M
2015-06-01
In male Caucasian subjects, learning is facilitated by receipt of social compared with non-social feedback, and the neuropeptide oxytocin (OXT) facilitates this effect. In this study, we have first shown a cultural difference in that male Chinese subjects actually perform significantly worse in the same reinforcement associated learning task with social (emotional faces) compared with non-social feedback. Nevertheless, in two independent double-blind placebo (PLC) controlled between-subject design experiments we found OXT still selectively facilitated learning with social feedback. Similar to Caucasian subjects this OXT effect was strongest with feedback using female rather than male faces. One experiment performed in conjunction with functional magnetic resonance imaging showed that during the response, but not feedback phase of the task, OXT selectively increased activity in the amygdala, hippocampus, parahippocampal gyrus and putamen during the social feedback condition, and functional connectivity between the amygdala and insula and caudate. Therefore, OXT may be increasing the salience and reward value of anticipated social feedback. In the PLC group, response times and state anxiety scores during social feedback were associated with signal changes in these same regions but not in the OXT group. OXT may therefore have also facilitated learning by reducing anxiety in the social feedback condition. Overall our results provide the first evidence for cultural differences in social facilitation of learning per se, but a similar selective enhancement of learning with social feedback under OXT. This effect of OXT may be associated with enhanced responses and functional connectivity in emotional memory and reward processing regions. © 2015 Wiley Periodicals, Inc.
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Basic webliography on health promotion and disease prevention - doi:10.5020/18061230.2009.p217
Directory of Open Access Journals (Sweden)
Ana Claudia Camargo Gonçalves da Silva
2012-01-01
Full Text Available Objectives: To introduce a basic webliography to access highly qualified evidence-based material on health promotion and disease prevention, aiming at the continuing education of health professionals. Methods: By means of Google® browser, applying the descriptors in sequence to progressively refine the search on Internet and key concepts to be learned, all previously defined by the authors themselves, we proceeded a qualitative analyses of the 20 first listed links for each searched issue and the final selection of the most scientifically relevant ones. Results: The 34 selected links are presented in 4 groups: 23 portals, 5 guides and recommendations, 4 scientific journals and 3 blogs that allow free access to health promotion and disease prevention related subjects, such as: concepts; national and international public policies; epidemiology, statistics and health indicators; diseases screening and prophylaxis; counseling for behavior change of health related habits; and interdisciplinary work. Among the selected links 10 (29% are written in English while the others are in Portuguese. Conclusions: The identification of reading materials on health promotion and disease prevention available on Internet, many in Portuguese, allowed us to select relevant scientifically qualified literature and turn it accessible to health professionals, enabling the acquisition of new knowledge or quick update.
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Baxter, Mark G; Bucci, David J; Gorman, Linda K; Wiley, Ronald G; Gallagher, Michela
2013-10-01
Male Long-Evans rats were given injections of either 192 IgG-saporin, an apparently selective toxin for basal forebrain cholinergic neurons (LES), or vehicle (CON) into either the medial septum and vertical limb of the diagonal band (MS/VDB) or bilaterally into the nucleus basalis magnocellularis and substantia innominata (nBM/SI). Place discrimination in the Morris water maze assessed spatial learning, and a trial-unique matching-to-place task in the water maze assessed memory for place information over varying delays. MS/VDB-LES and nBM/SI-LES rats were not impaired relative to CON rats in acquisition of the place discrimination, but were mildly impaired relative to CON rats in performance of the memory task even at the shortest delay, suggesting a nonmnemonic deficit. These results contrast with effects of less selective lesions, which have been taken to support a role for basal forebrain cholinergic neurons in learning and memory. 2013 APA, all rights reserved
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Directory of Open Access Journals (Sweden)
Kyla P McDonald
Full Text Available This research explored whether children judge the knowledge state of others and selectively learn novel information from them based on how they dress. The results indicated that 4- and 6-year-olds identified a formally dressed individual as more knowledgeable about new things in general than a casually dressed one (Study 1. Moreover, children displayed an overall preference to seek help from a formally dressed individual rather than a casually dressed one when learning about novel objects and animals (Study 2. These findings are discussed in relation to the halo effect, and may have important implications for child educators regarding how instructor dress might influence young students' knowledge attribution and learning preferences.
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Ferrante, Oscar; Patacca, Alessia; Di Caro, Valeria; Della Libera, Chiara; Santandrea, Elisa; Chelazzi, Leonardo
2018-05-01
The cognitive system has the capacity to learn and make use of environmental regularities - known as statistical learning (SL), including for the implicit guidance of attention. For instance, it is known that attentional selection is biased according to the spatial probability of targets; similarly, changes in distractor filtering can be triggered by the unequal spatial distribution of distractors. Open questions remain regarding the cognitive/neuronal mechanisms underlying SL of target selection and distractor filtering. Crucially, it is unclear whether the two processes rely on shared neuronal machinery, with unavoidable cross-talk, or they are fully independent, an issue that we directly addressed here. In a series of visual search experiments, participants had to discriminate a target stimulus, while ignoring a task-irrelevant salient distractor (when present). We systematically manipulated spatial probabilities of either one or the other stimulus, or both. We then measured performance to evaluate the direct effects of the applied contingent probability distribution (e.g., effects on target selection of the spatial imbalance in target occurrence across locations) as well as its indirect or "transfer" effects (e.g., effects of the same spatial imbalance on distractor filtering across locations). By this approach, we confirmed that SL of both target and distractor location implicitly bias attention. Most importantly, we described substantial indirect effects, with the unequal spatial probability of the target affecting filtering efficiency and, vice versa, the unequal spatial probability of the distractor affecting target selection efficiency across locations. The observed cross-talk demonstrates that SL of target selection and distractor filtering are instantiated via (at least partly) shared neuronal machinery, as further corroborated by strong correlations between direct and indirect effects at the level of individual participants. Our findings are compatible
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Baskin, Monica L.; Zunker, Christie; Worley, Courtney B.; Dial, Brenda; Kimbrough, Linda
2009-01-01
Purpose: This paper seeks to describe the design, implementation, and lessons learned from an obesity prevention pilot program delivered in a low resource school in the USA. Design/methodology/approach: A planned program evaluation was conducted to: document explicitly the process of designing and implementing the program; and assess the…
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Response selection difficulty modulates the behavioral impact of rapidly learnt action effects.
Directory of Open Access Journals (Sweden)
Uta eWolfensteller
2014-12-01
Full Text Available It is well established that we can pick up action effect associations when acting in a free-choice intentional mode. However, it is less clear whether and when action effect associations are learnt and actually affect behavior if we are acting in a forced-choice mode, applying a specific stimulus-response (S-R rule. In the present study, we investigated whether response selection difficulty imposed by S-R rules influences the initial rapid learning and the behavioral expression of previously learnt but weakly practiced action effect associations when those are re-activated by effect exposure. Experiment 1 showed that the rapid acquisition of action effect associations is not directly influenced by response selection difficulty. By contrast, the behavioral expression of re-activated action effect associations is prevented when actions are directly activated by highly over-learnt response cues and thus response selection difficulty is low. However, all three experiments showed that if response selection difficulty is sufficiently high during re-activation, the same action effect associations do influence behavior. Experiment 2 and 3 revealed that the effect of response selection difficulty cannot be fully reduced to giving action effects more time to prime an action, but seems to reflect competition during response selection. Finally, the present data suggest that when multiple novel rules are rapidly learnt in succession, which requires a lot of flexibility, action effect associations continue to influence behavior only if response selection difficulty is sufficiently high. Thus, response selection difficulty might modulate the impact of experiencing multiple learning episodes on action effect expression and learning, possibly via inducing different strategies.
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Skvortsova, Vasilisa; Degos, Bertrand; Welter, Marie-Laure; Vidailhet, Marie; Pessiglione, Mathias
2017-06-21
Instrumental learning is a fundamental process through which agents optimize their choices, taking into account various dimensions of available options such as the possible reward or punishment outcomes and the costs associated with potential actions. Although the implication of dopamine in learning from choice outcomes is well established, less is known about its role in learning the action costs such as effort. Here, we tested the ability of patients with Parkinson's disease (PD) to maximize monetary rewards and minimize physical efforts in a probabilistic instrumental learning task. The implication of dopamine was assessed by comparing performance ON and OFF prodopaminergic medication. In a first sample of PD patients ( n = 15), we observed that reward learning, but not effort learning, was selectively impaired in the absence of treatment, with a significant interaction between learning condition (reward vs effort) and medication status (OFF vs ON). These results were replicated in a second, independent sample of PD patients ( n = 20) using a simplified version of the task. According to Bayesian model selection, the best account for medication effects in both studies was a specific amplification of reward magnitude in a Q-learning algorithm. These results suggest that learning to avoid physical effort is independent from dopaminergic circuits and strengthen the general idea that dopaminergic signaling amplifies the effects of reward expectation or obtainment on instrumental behavior. SIGNIFICANCE STATEMENT Theoretically, maximizing reward and minimizing effort could involve the same computations and therefore rely on the same brain circuits. Here, we tested whether dopamine, a key component of reward-related circuitry, is also implicated in effort learning. We found that patients suffering from dopamine depletion due to Parkinson's disease were selectively impaired in reward learning, but not effort learning. Moreover, anti-parkinsonian medication restored the
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Crucial elements in suicide prevention strategies
DEFF Research Database (Denmark)
Nordentoft, Merete
2011-01-01
Ways of conceptualizing suicide prevention are reviewed briefly, and the preventive model: Universal, Selected, and Indicated prevention (USI) is chosen as the structure for the literature review, and the discussion. Universal preventive interventions are directed toward entire population......; selective interventions are directed toward individuals who are at greater risk for suicidal behaviour; and indicated preventions are targeted at individuals who have already begun self-destructive behaviour. On the universal prevention level, an overview of the literature is presented with focus...... on restrictions in firearms and carbon monoxide gas. At the selective prevention level, a review of risk of suicide in homelessness and schizophrenia and risk factors for suicide in schizophrenia is conducted and possible interventions are mentioned together with the evidence for their effect. Suicide rate...
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When does social learning become cultural learning?
Heyes, Cecilia
2017-03-01
Developmental research on selective social learning, or 'social learning strategies', is currently a rich source of information about when children copy behaviour, and who they prefer to copy. It also has the potential to tell us when and how human social learning becomes cultural learning; i.e. mediated by psychological mechanisms that are specialized, genetically or culturally, to promote cultural inheritance. However, this review article argues that, to realize its potential, research on the development of selective social learning needs more clearly to distinguish functional from mechanistic explanation; to achieve integration with research on attention and learning in adult humans and 'dumb' animals; and to recognize that psychological mechanisms can be specialized, not only by genetic evolution, but also by associative learning and cultural evolution. © 2015 John Wiley & Sons Ltd.
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Ward, Peggy
Although hailed as a powerful form of instruction, in most teaching and learning contexts, inquiry-based instruction is fraught with ambiguous and conflicting definitions and descriptions. Yet little has been written about the experiences preservice science teacher have regarding their learning to teach science through inquiry. This project sought to understand how select preservice secondary science teachers enrolled in three UTeach programs in Arkansas conceptualize inquiry instruction and how they rationalize its value in a teaching and learning context. The three teacher education programs investigated in this study are adoption sites aligned with the UTeach Program in Austin, TX that distinguishes itself in part by its inquiry emphasis. Using a mixed method investigation design, this study utilized two sources of data to explore the preservice science teachers' thinking. In the first phase, a modified version of the Pedagogy of Science teaching Tests (POSTT) was used to identify select program participants who indicated preferences for inquiry instruction over other instructional strategies. Secondly, the study used an open-ended questionnaire to explore the selected subjects' beliefs and conceptions of teaching and learning science in an inquiry context. The study also focused on identifying particular junctures in the prospective science teachers' education preparation that might impact their understanding about inquiry. Using a constant comparative approach, this study explored 19 preservice science teachers' conceptions about inquiry. The results indicate that across all levels of instruction, the prospective teachers tended to have strong student-centered teaching orientations. Except subjects in for the earliest courses, subjects' definitions and descriptions of inquiry tended toward a few of the science practices. More advanced subjects, however, expressed more in-depth descriptions. Excluding the subjects who have completed the program, multiple
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Piper, Tinka Markham; Rudenstine, Sasha; Stancliff, Sharon; Sherman, Susan; Nandi, Vijay; Clear, Allan; Galea, Sandro
2007-01-25
Fatal heroin overdose is a significant cause of mortality for injection drug users (IDUs). Many of these deaths are preventable because opiate overdoses can be quickly and safely reversed through the injection of Naloxone [brand name Narcan], a prescription drug used to revive persons who have overdosed on heroin or other opioids. Currently, in several cities in the United States, drug users are being trained in naloxone administration and given naloxone for immediate and successful reversals of opiate overdoses. There has been very little formal description of the challenges faced in the development and implementation of large-scale IDU naloxone administration training and distribution programs and the lessons learned during this process. During a one year period, over 1,000 participants were trained in SKOOP (Skills and Knowledge on Opiate Prevention) and received a prescription for naloxone by a medical doctor on site at a syringe exchange program (SEP) in New York City. Participants in SKOOP were over the age of 18, current participants of SEPs, and current or former drug users. We present details about program design and lessons learned during the development and implementation of SKOOP. Lessons learned described in the manuscript are collectively articulated by the evaluators and implementers of the project. There were six primary challenges and lessons learned in developing, implementing, and evaluating SKOOP. These include a) political climate surrounding naloxone distribution; b) extant prescription drug laws; c) initial low levels of recruitment into the program; d) development of participant appropriate training methodology; e) challenges in the design of a suitable formal evaluation; and f) evolution of program response to naloxone. Other naloxone distribution programs may anticipate similar challenges to SKOOP and we identify mechanisms to address them. Strategies include being flexible in program planning and implementation, developing evaluation
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HIA and pollution prevention control: What they can learn from each other
International Nuclear Information System (INIS)
Ahmad, Balsam; Pless-Mulloli, Tanja; Vizard, Catherine
2005-01-01
Following the implementation of the Pollution Prevention and Control (England and Wales) Regulations on 1st August 2000, health authorities (now Primary Care Trusts) became statutory consultees for permits issued to industry by the environmental regulators (the Environmental Agency, Local Authorities). The aims of this paper are to review the process of providing public health input in the light of its similarities to and differences from HIA and to identify the opportunities for both HIA and PPC to learn from each other's practice. We emphasise the challenges that are encountered by public health professionals who provide the public health input in the PPC. We use both our own experience of providing this input on behalf of health authorities and our expertise in HIA, environmental epidemiology and contaminated land
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Imbalzano, Giulio; Anelli, Andrea; Giofré, Daniele; Klees, Sinja; Behler, Jörg; Ceriotti, Michele
2018-06-01
Machine learning of atomic-scale properties is revolutionizing molecular modeling, making it possible to evaluate inter-atomic potentials with first-principles accuracy, at a fraction of the costs. The accuracy, speed, and reliability of machine learning potentials, however, depend strongly on the way atomic configurations are represented, i.e., the choice of descriptors used as input for the machine learning method. The raw Cartesian coordinates are typically transformed in "fingerprints," or "symmetry functions," that are designed to encode, in addition to the structure, important properties of the potential energy surface like its invariances with respect to rotation, translation, and permutation of like atoms. Here we discuss automatic protocols to select a number of fingerprints out of a large pool of candidates, based on the correlations that are intrinsic to the training data. This procedure can greatly simplify the construction of neural network potentials that strike the best balance between accuracy and computational efficiency and has the potential to accelerate by orders of magnitude the evaluation of Gaussian approximation potentials based on the smooth overlap of atomic positions kernel. We present applications to the construction of neural network potentials for water and for an Al-Mg-Si alloy and to the prediction of the formation energies of small organic molecules using Gaussian process regression.
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Hodson, Derek
2014-01-01
This opinion piece paper urges teachers and teacher educators to draw careful distinctions among four basic learning goals: learning science, learning about science, doing science and learning to address socio-scientific issues. In elaboration, the author urges that careful attention is paid to the selection of teaching/learning methods that…
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Khan, Maria R; Epperson, Matthew W; Gilbert, Louisa; Goddard, Dawn; Hunt, Timothy; Sarfo, Bright; El-Bassel, Nabila
2012-10-01
There is increasing excitement about multimedia sexually transmitted infection (STI) and HIV prevention interventions, yet there has been limited discussion of how use of multimedia technology may improve STI/HIV prevention efforts. The purpose of this paper is to describe the mechanisms through which multimedia technology may work to improve the delivery and uptake of intervention material. We present conceptual frameworks describing how multimedia technology may improve intervention delivery by increasing standardization and fidelity to the intervention material and the participant's ability to learn by improving attention, cognition, emotional engagement, skills-building, and uptake of sensitive material about sexual and drug risks. In addition, we describe how the non-multimedia behavioral STI/HIV prevention intervention, Project WORTH, was adapted into a multimedia format for women involved in the criminal justice system and provide examples of how multimedia activities can more effectively target key mediators of behavioral change in this intervention.
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Bierman, Karen L.; Coie, John D.; Dodge, Kenneth A.; Greenberg, Mark T.; Lochman, John E.; McMahon, Robert J.; Pinderhughes, Ellen
2010-01-01
Objective: This article examines the impact of a universal social-emotional learning program, the Fast Track PATHS (Promoting Alternative Thinking Strategies) curriculum and teacher consultation, embedded within the Fast Track selective prevention model. Method: The longitudinal analysis involved 2,937 children of multiple ethnicities who remained…
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McDonald, Kyla P.; Ma, Lili
2015-01-01
This research explored whether children judge the knowledge state of others and selectively learn novel information from them based on how they dress. The results indicated that 4- and 6-year-olds identified a formally dressed individual as more knowledgeable about new things in general than a casually dressed one (Study 1). Moreover, children displayed an overall preference to seek help from a formally dressed individual rather than a casually dressed one when learning about novel objects and animals (Study 2). These findings are discussed in relation to the halo effect, and may have important implications for child educators regarding how instructor dress might influence young students’ knowledge attribution and learning preferences. PMID:26636980
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Cellular and oscillatory substrates of fear extinction learning.
Davis, Patrick; Zaki, Yosif; Maguire, Jamie; Reijmers, Leon G
2017-11-01
The mammalian brain contains dedicated circuits for both the learned expression and suppression of fear. These circuits require precise coordination to facilitate the appropriate expression of fear behavior, but the mechanisms underlying this coordination remain unclear. Using a combination of chemogenetics, activity-based neuronal-ensemble labeling and in vivo electrophysiology, we found that fear extinction learning confers on parvalbumin-expressing (PV) interneurons in the basolateral amygdala (BLA) a dedicated role in the selective suppression of a previously encoded fear memory and BLA fear-encoding neurons. In addition, following extinction learning, PV interneurons enable a competing interaction between a 6-12 Hz oscillation and a fear-associated 3-6 Hz oscillation within the BLA. Loss of this competition increases a 3-6 Hz oscillatory signature, with BLA→medial prefrontal cortex directionality signaling the recurrence of fear expression. The discovery of cellular and oscillatory substrates of fear extinction learning that critically depend on BLA PV interneurons could inform therapies aimed at preventing the pathological recurrence of fear following extinction learning.
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Optimizing learning path selection through memetic algorithms
Acampora, G.; Gaeta, M.; Loia, V.; Ritrovato, P.; Salerno, S.
2008-01-01
e-Learning is a critical support mechanism for industrial and academic organizations to enhance the skills of employees and students and, consequently, the overall competitiveness in the new economy. The remarkable velocity and volatility of modern knowledge require novel learning methods offering
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Selection of Learning Media Mathematics for Junior School Students
Widodo, Sri Adi; Wahyudin
2018-01-01
One of the factors that determine the success of mathematics learning is the learning media used. Learning media can help students to create mathematical abstract mathematics that is abstract. In addition to media, meaningful learning is a learning that is adapted to the students' cognitive development. According to Piaget, junior high school…
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The educative prevention of the early stage of educationist’s formation.
Directory of Open Access Journals (Sweden)
Marta Alfonso Nazco
2010-04-01
Full Text Available The article introduces a characterization of the educative prevention stage at the early professional formation process of educacionist in Sancti Spìritus province. The study is done by the indication analysis of assistant, learning, permanence and behavior at youths who course pedagogical carrers, and haven’t expressed a desire stage yet. The main shown results dealt with the assumption of the searching variables and its indicators, the construction of instruments and the definition of aspects concerning the educative prevention at the early stage of educationist’s formation in the selected choosing. Theoretical, empirical and statistical- math, methods were used which were helped by the constructed instruments and the triangulations among them thus arriving to generalizations for the caracterization. The results have better the work at the area project of the educative prevention in adolescents and youths in the territory, witch mainly concern the desing and implementation of actions withing the pedagogical process, foccuse in the integration of institutions, socializer and educative agents functioning to eductive prevention.
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Schubart, Jane
2012-10-01
Pressure ulcers (PrUs) are the most common medical complication following spinal cord injury (SCI), as well as costly and potentially life-threatening. Every individual with SCI is at life-long risk for developing PrUs, yet many lack access to readily available, understandable, and effective PrU prevention strategies and practices. To address barriers to adequate PrU prevention education, an interactive e-learning program to educate adults with SCI about PrU prevention and management was developed and previously pilot-tested among inpatients. This recent pilot study was conducted to evaluate the feasibility of using the learning portion of the program by adults with SCI following discharge to home among 15 outpatients with SCI. Fourteen patients (nine men, five women, median age 37 years) completed the program intervention and pre- and follow-up questionnaires. The median score for pre-program knowledge and skin care management practice was 96 (possible score: 0 to 120; range 70-100). Post-program use median score was 107 (range 97-114). The greatest improvement was in the responses to knowledge and practice questions about skin checks and preventing skin problems (P effect of this e-learning program on PrU incidence. Internet interventions that are proven effective hold tremendous potential for bringing prevention education to groups who would otherwise not receive it.
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Drug Abuse Prevention Starts with Parents
... Stages Listen Español Text Size Email Print Share Drug Abuse Prevention Starts with Parents Page Content Article Body ... for a time when drugs may be offered. Drug abuse prevention starts with parents learning how to talk ...
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Colorectal Cancer Prevention (PDQ®)—Patient Version
Colorectal cancer prevention strategies can include avoiding known risk factors, having a healthy lifestyle, taking aspirin, and removing polyps. Learn more about preventing colorectal cancer in this expert-reviewed summary.
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Lung Cancer Prevention (PDQ®)—Patient Version
Lung cancer prevention approaches include avoiding exposure to risk factors like tobacco smoke, radon, radiation, asbestos, and other substances. Learn more about preventing lung cancer in this expert-reviewed summary.
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How to select the correct education strategy: when not to go online.
Klingbeil, Carol G; Johnson, Norah L; Totka, Joan P; Doyle, Lynn
2009-01-01
Screening for intimate partner violence is an important injury prevention strategy. Nurses who develop staff education, to promote screening, need to select a method that is sensitive to learners. Online learning, although convenient, is not well suited to sensitive topics such as screening for intimate partner violence. The purpose of this article is to describe a curriculum for intimate partner violence screening based on self-efficacy theory, which includes a hospital-produced video, a role play, and a discussion.
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Bergstra, Myrthe; DE Mulder, Hannah N M; Coopmans, Peter
2018-04-06
This study investigated how speaker certainty (a rational cue) and speaker benevolence (an emotional cue) influence children's willingness to learn words in a selective learning paradigm. In two experiments four- to six-year-olds learnt novel labels from two speakers and, after a week, their memory for these labels was reassessed. Results demonstrated that children retained the label-object pairings for at least a week. Furthermore, children preferred to learn from certain over uncertain speakers, but they had no significant preference for nice over nasty speakers. When the cues were combined, children followed certain speakers, even if they were nasty. However, children did prefer to learn from nice and certain speakers over nasty and certain speakers. These results suggest that rational cues regarding a speaker's linguistic competence trump emotional cues regarding a speaker's affective status in word learning. However, emotional cues were found to have a subtle influence on this process.
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Learners' experiences of learning support in selected Western Cape ...
African Journals Online (AJOL)
The learning support assisted in meeting learners' academic, social and emotional needs by addressing barriers to learning, creating conducive learning environments, enhancing learners' self-esteem and improving learners' academic performance. Keywords: academic needs; academic performance; barriers to learning; ...
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DeBate, Rita D; Severson, Herbert H; Cragun, Deborah L; Gau, Jeff M; Merrell, Laura K; Bleck, Jennifer R; Christiansen, Steve; Koerber, Anne; Tomar, Scott L; McCormack Brown, Kelli R; Tedesco, Lisa A; Hendricson, William
2013-06-01
Oral healthcare providers have a clinical opportunity for early detection of disordered eating behaviors because they are often the first health professionals to observe overt oral and physical signs. Curricula regarding early recognition of this oral/systemic medical condition are limited in oral health educational programs. Web-based learning can supplement and reinforce traditional learning and has the potential to develop skills. The study purpose was to determine the efficacy of a theory-driven Web-based training program to increase the capacity of oral health students to perform behaviors related to the secondary prevention of disordered eating behaviors. Using the Reach, Effectiveness, Adoption, Implementation and Maintenance evaluation framework, a longitudinal group-randomized controlled trial involving 27 oral health classes from 12 oral health education programs in the United States was implemented to assess the efficacy of the Web-based training on attitudes, knowledge, self-efficacy and skills related to the secondary prevention of disordered eating behaviors. Mixed-model analysis of covariance indicated substantial improvements among students in the intervention group (effect sizes: 0.51-0.83) on all six outcomes of interest. Results suggest that the Web-based training program may increase the capacity of oral healthcare providers to deliver secondary prevention of disordered eating behaviors. Implications and value of using the Reach, Effectiveness, Adoption, Implementation and Maintenance framework are discussed.
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CDC Vital Signs-Preventing Stroke Deaths
Centers for Disease Control (CDC) Podcasts
This podcast is based on the September 2017 CDC Vital Signs report. Each year, more than 140,000 people die and many survivors face disability. Eighty percent of strokes are preventable. Learn the signs of stroke and how to prevent them.
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Reinforcement Learning for Ramp Control: An Analysis of Learning Parameters
Directory of Open Access Journals (Sweden)
Chao Lu
2016-08-01
Full Text Available Reinforcement Learning (RL has been proposed to deal with ramp control problems under dynamic traffic conditions; however, there is a lack of sufficient research on the behaviour and impacts of different learning parameters. This paper describes a ramp control agent based on the RL mechanism and thoroughly analyzed the influence of three learning parameters; namely, learning rate, discount rate and action selection parameter on the algorithm performance. Two indices for the learning speed and convergence stability were used to measure the algorithm performance, based on which a series of simulation-based experiments were designed and conducted by using a macroscopic traffic flow model. Simulation results showed that, compared with the discount rate, the learning rate and action selection parameter made more remarkable impacts on the algorithm performance. Based on the analysis, some suggestionsabout how to select suitable parameter values that can achieve a superior performance were provided.
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Classifying smoking urges via machine learning.
Dumortier, Antoine; Beckjord, Ellen; Shiffman, Saul; Sejdić, Ervin
2016-12-01
Smoking is the largest preventable cause of death and diseases in the developed world, and advances in modern electronics and machine learning can help us deliver real-time intervention to smokers in novel ways. In this paper, we examine different machine learning approaches to use situational features associated with having or not having urges to smoke during a quit attempt in order to accurately classify high-urge states. To test our machine learning approaches, specifically, Bayes, discriminant analysis and decision tree learning methods, we used a dataset collected from over 300 participants who had initiated a quit attempt. The three classification approaches are evaluated observing sensitivity, specificity, accuracy and precision. The outcome of the analysis showed that algorithms based on feature selection make it possible to obtain high classification rates with only a few features selected from the entire dataset. The classification tree method outperformed the naive Bayes and discriminant analysis methods, with an accuracy of the classifications up to 86%. These numbers suggest that machine learning may be a suitable approach to deal with smoking cessation matters, and to predict smoking urges, outlining a potential use for mobile health applications. In conclusion, machine learning classifiers can help identify smoking situations, and the search for the best features and classifier parameters significantly improves the algorithms' performance. In addition, this study also supports the usefulness of new technologies in improving the effect of smoking cessation interventions, the management of time and patients by therapists, and thus the optimization of available health care resources. Future studies should focus on providing more adaptive and personalized support to people who really need it, in a minimum amount of time by developing novel expert systems capable of delivering real-time interventions. Copyright © 2016 Elsevier Ireland Ltd. All rights
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Can non-selective beta-blockers prevent hepatocellular carcinoma in patients with cirrhosis?
DEFF Research Database (Denmark)
Thiele, Maja; Wiest, Reiner; Gluud, Lise Lotte
2013-01-01
Hepatocellular carcinoma is the main liver-related cause of death in patients with compensated cirrhosis. The early phases are asymptomatic and the prognosis is poor, which makes prevention essential. We propose that non-selective beta-blockers decrease the incidence and growth of hepatocellular...... and growth of hepatocellular carcinoma. Rodent and in vitro studies support the hypothesis, but clinical verification is needed. Different study designs may be considered. The feasibility of a randomized controlled trial is limited due to the necessary large number of patients and long follow......-up. Observational studies carry a high risk of bias. The meta-analytic approach may be used if the incidence and mortality of hepatocellular carcinoma can be extracted from trials on variceal bleeding and if the combined sample size and follow up is sufficient....
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Lee, Y. J.; Bonfanti, C. E.; Trailovic, L.; Etherton, B.; Govett, M.; Stewart, J.
2017-12-01
At present, a fraction of all satellite observations are ultimately used for model assimilation. The satellite data assimilation process is computationally expensive and data are often reduced in resolution to allow timely incorporation into the forecast. This problem is only exacerbated by the recent launch of Geostationary Operational Environmental Satellite (GOES)-16 satellite and future satellites providing several order of magnitude increase in data volume. At the NOAA Earth System Research Laboratory (ESRL) we are researching the use of machine learning the improve the initial selection of satellite data to be used in the model assimilation process. In particular, we are investigating the use of deep learning. Deep learning is being applied to many image processing and computer vision problems with great success. Through our research, we are using convolutional neural network to find and mark regions of interest (ROI) to lead to intelligent extraction of observations from satellite observation systems. These targeted observations will be used to improve the quality of data selected for model assimilation and ultimately improve the impact of satellite data on weather forecasts. Our preliminary efforts to identify the ROI's are focused in two areas: applying and comparing state-of-art convolutional neural network models using the analysis data from the National Center for Environmental Prediction (NCEP) Global Forecast System (GFS) weather model, and using these results as a starting point to optimize convolution neural network model for pattern recognition on the higher resolution water vapor data from GOES-WEST and other satellite. This presentation will provide an introduction to our convolutional neural network model to identify and process these ROI's, along with the challenges of data preparation, training the model, and parameter optimization.
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Business waste prevention: a review of the evidence.
Wilson, David C; Parker, David; Cox, Jayne; Strange, Kit; Willis, Peter; Blakey, Nick; Raw, Lynn
2012-09-01
Waste prevention is a policy priority in many countries. For example, European Union member states are currently required to prepare a national Waste Prevention Programme. This article reports on a major international review of the evidence base for business waste prevention to underpin such policy-making. A strict definition of waste prevention is used, including waste avoidance, waste reduction at source or in process, and product reuse-recycling is outside the scope of this article. The review was organised with two key dimensions. Eight types of policy intervention were identified: standards, labelling, procurement, commitments and voluntary agreements, communication, incentives, waste minimisation clubs and other business support. Six illustrative sectors were selected: construction and demolition, food and drink, hospitality, retail, automotive and office-based services. Four broad approaches to business waste prevention have been distinguished and used as part of the analytical framework, classified into a two by two matrix, using supply- and demand-side drivers as one axis, and incremental versus radical change as the other. A fundamental focus was on attitudes and behaviours. A conceptual framework is presented to navigate the various behavioural influences on businesses, and to discuss those motivations and barriers for which the evidence is relatively robust. The results suggest that the (financial) benefits to business of waste prevention are potentially huge, and that some progress is being made, but measurement is a challenge. A taster of some of the learnings on the effectiveness of the different policy interventions to promote waste prevention is also presented.
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Directory of Open Access Journals (Sweden)
Hans Solli-Soether
2012-01-01
Full Text Available Knowledge and learning are important in combating financial crime generallyand white-collar crime in particular. The purpose of this research is to generateinsights into prevention approaches in practice that may reflect on acontingent approach. The five hundred largest business companies in termsof annual turnover were identified in Norway for our empirical study of whitecollarcrime. A paper letter was mailed to the chief financial officer (CFOasking him or her to fill in the questionnaire to be found on a web site usinga password found in the letter. The open-ended question in the questionnaireto CFOs about prevention of white-collar crime was formulated as follows:How can white-collar crime best be prevented in your company? Survey resultsindicate an even distribution of respondents emphasizing control and respondentsemphasizing influence. This empirical research steps back from manybest practice articles and provides insights into preferences of chief financialofficers on how to prevent white-collar crime in the company.
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Reinforcement learning modulates the stability of cognitive control settings for object selection
Directory of Open Access Journals (Sweden)
Anthony William Sali
2013-12-01
Full Text Available Cognitive flexibility reflects both a trait that reliably differs between individuals and a state that can fluctuate moment-to-moment. Whether individuals can undergo persistent changes in cognitive flexibility as a result of reward learning is less understood. Here, we investigated whether reinforcing a periodic shift in an object selection strategy can make an individual more prone to switch strategies in a subsequent unrelated task. Participants completed two different choice tasks in which they selected one of four objects in an attempt to obtain a hidden reward on each trial. During a training phase, objects were defined by color. Participants received either consistent reward contingencies in which one color was more often rewarded, or contingencies in which the color that was more often rewarded changed periodically and without warning. Following the training phase, all participants completed a test phase in which reward contingencies were defined by spatial location and the location that was more often rewarded remained constant across the entire task. Those participants who received inconsistent contingencies during training continued to make more variable selections during the test phase in comparison to those who received the consistent training. Furthermore, a difference in the likelihood to switch selections on a trial-by-trial basis emerged between training groups: participants who received consistent contingencies during training were less likely to switch object selections following an unrewarded trial and more likely to repeat a selection following reward. Our findings provide evidence that the extent to which priority shifting is reinforced modulates the stability of cognitive control settings in a persistent manner, such that individuals become generally more or less prone to shifting priorities in the future.
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Hirsch, David B.
2009-01-01
This slide presentation reviews selected lessons that were learned during the design, development, assembly and operation of the International Space Station. The critical importance of standards and common interfaces is emphasized to create a common operation environment that can lead to flexibility and adaptability.
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Morita, Kenji; Jitsev, Jenia; Morrison, Abigail
2016-09-15
Value-based action selection has been suggested to be realized in the corticostriatal local circuits through competition among neural populations. In this article, we review theoretical and experimental studies that have constructed and verified this notion, and provide new perspectives on how the local-circuit selection mechanisms implement reinforcement learning (RL) algorithms and computations beyond them. The striatal neurons are mostly inhibitory, and lateral inhibition among them has been classically proposed to realize "Winner-Take-All (WTA)" selection of the maximum-valued action (i.e., 'max' operation). Although this view has been challenged by the revealed weakness, sparseness, and asymmetry of lateral inhibition, which suggest more complex dynamics, WTA-like competition could still occur on short time scales. Unlike the striatal circuit, the cortical circuit contains recurrent excitation, which may enable retention or temporal integration of information and probabilistic "soft-max" selection. The striatal "max" circuit and the cortical "soft-max" circuit might co-implement an RL algorithm called Q-learning; the cortical circuit might also similarly serve for other algorithms such as SARSA. In these implementations, the cortical circuit presumably sustains activity representing the executed action, which negatively impacts dopamine neurons so that they can calculate reward-prediction-error. Regarding the suggested more complex dynamics of striatal, as well as cortical, circuits on long time scales, which could be viewed as a sequence of short WTA fragments, computational roles remain open: such a sequence might represent (1) sequential state-action-state transitions, constituting replay or simulation of the internal model, (2) a single state/action by the whole trajectory, or (3) probabilistic sampling of state/action. Copyright © 2016. Published by Elsevier B.V.
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Directory of Open Access Journals (Sweden)
Eckler Ursula
2017-11-01
Full Text Available Blended learning is characterised as a combination of face-to-face teaching and e-learning in terms of knowledge transfer, students’ learning activities and reduced presence at the teaching facility. The present cohort study investigated long-term effects of blended learning regarding cognitive outcomes as well as self-indicated estimates of immediate learning effects on the affective domain in the inter-professional field of occupational medicine. Physiotherapy students (bachelor degree at FH Campus Wien – University of Applied Sciences completed the course Occupational Medicine/Prevention either in a traditional teaching-learning setting entirely taught face-to-face (control-group, n=94, or with a blended learning model (intervention-group, n=93. Long-term effects (1.5 year follow-up on the cognitive learning outcomes were assessed according to four levels of Bloom’s learning objectives. In addition, students estimated potential benefits resulting from blended learning based on four Krathwohl’s learning objectives for the affective domain by means of a six-option Likert scale (n=282. Concerning cognitive outcomes, significant results favouring both groups were found with effect sizes from small to medium. The traditional teaching-learning setting resulted in significantly better results in the upmost aspired learning objective (analysis at the long-term (p<0,01; r=-0,33. In contrast, the intervention group resulted in significantly better long-term results on learning objective levels 1 (knowledge and 2 (understanding (p=0,01; r=-0,20 and, p=0,02; r=-0,17, respectively. Hence, no general recommendation favouring either the classical setting or blending learning can be drawn regarding the cognitive domain. However, students’ self-indications on the affective domain give preference to blended learning, particularly if inter-professional teamwork is a course objective.
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Cancer Prevention in the Precision Medicine Era | Division of Cancer Prevention
Speaker | Timothy R. Rebbeck, PhD will present "Cancer Prevention in the Precision Medicine Era" on March 20, 2018, from 11:00 am - 12:00 pm at the NCI Shady Grove Campus. Learn more about this lecture.
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Biomass accident investigations – missed opportunities for learning and accident prevention
DEFF Research Database (Denmark)
Hedlund, Frank Huess
2017-01-01
The past decade has seen a major increase in the production of energy from biomass. The growth has been mirrored in an increase of serious biomass related accidents involving fires, gas explosions, combustible dust explosions and the release of toxic gasses. There are indications that the number...... of bioenergy related accidents is growing faster than the energy production. This paper argues that biomass accidents, if properly investigated and lessons shared widely, provide ample opportunities for improving general hazard awareness and safety performance of the biomass industry. The paper examines...... selected serious accidents involving biogas and wood pellets in Denmark and argues that such opportunities for learning were missed because accident investigations were superficial, follow-up incomplete and information sharing absent. In one particularly distressing case, a facility saw a repeat accident...
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Prediction of Student Dropout in E-Learning Program Through the Use of Machine Learning Method
Directory of Open Access Journals (Sweden)
Mingjie Tan
2015-02-01
Full Text Available The high rate of dropout is a serious problem in E-learning program. Thus it has received extensive concern from the education administrators and researchers. Predicting the potential dropout students is a workable solution to prevent dropout. Based on the analysis of related literature, this study selected student’s personal characteristic and academic performance as input attributions. Prediction models were developed using Artificial Neural Network (ANN, Decision Tree (DT and Bayesian Networks (BNs. A large sample of 62375 students was utilized in the procedures of model training and testing. The results of each model were presented in confusion matrix, and analyzed by calculating the rates of accuracy, precision, recall, and F-measure. The results suggested all of the three machine learning methods were effective in student dropout prediction, and DT presented a better performance. Finally, some suggestions were made for considerable future research.
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Strong, Paul V; Greenwood, Benjamin N; Fleshner, Monika
2009-05-01
Rats exposed to an uncontrollable stressor demonstrate a constellation of behaviors such as exaggerated freezing and deficits in shuttle box escape learning. These behaviors in rats have been called learned helplessness and have been argued to model human stress-related mood disorders. Learned helplessness is thought to be caused by hyperactivation of serotonin (5-HT) neurons in the dorsal raphe nucleus (DRN) and a subsequent exaggerated release of 5-HT in DRN projection sites. Blocking 5-HT(2C) receptors in the face of an increase in serotonin can alleviate anxiety behaviors in some animal models. However, specific 5-HT receptor subtypes involved in learned helplessness remain unknown. The current experiments tested the hypothesis that 5-HT(2C) receptor activation is necessary and sufficient for the expression of learned helplessness. The selective 5-HT(2C) receptor antagonist SB 242084 (1.0 mg/kg) administered i.p. to adult male Fischer 344 rats prior to shuttle box behavioral testing, but not before stress, blocked stress-induced deficits in escape learning but had no effect on the exaggerated shock-elicited freezing. The selective 5-HT(2C) receptor agonist CP-809101 was sufficient to produce learned helplessness-like behaviors in the absence of prior stress and these effects were blocked by pretreatment with SB 242084. Results implicate the 5-HT(2C) receptor subtype in mediating the shuttle box escape deficits produced by exposure to uncontrollable stress and suggest that different postsynaptic 5-HT receptor subtypes underlie the different learned helplessness behaviors.
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Directory of Open Access Journals (Sweden)
Nandi Vijay
2007-01-01
Full Text Available Abstract Background Fatal heroin overdose is a significant cause of mortality for injection drug users (IDUs. Many of these deaths are preventable because opiate overdoses can be quickly and safely reversed through the injection of Naloxone [brand name Narcan], a prescription drug used to revive persons who have overdosed on heroin or other opioids. Currently, in several cities in the United States, drug users are being trained in naloxone administration and given naloxone for immediate and successful reversals of opiate overdoses. There has been very little formal description of the challenges faced in the development and implementation of large-scale IDU naloxone administration training and distribution programs and the lessons learned during this process. Methods During a one year period, over 1,000 participants were trained in SKOOP (Skills and Knowledge on Opiate Prevention and received a prescription for naloxone by a medical doctor on site at a syringe exchange program (SEP in New York City. Participants in SKOOP were over the age of 18, current participants of SEPs, and current or former drug users. We present details about program design and lessons learned during the development and implementation of SKOOP. Lessons learned described in the manuscript are collectively articulated by the evaluators and implementers of the project. Results There were six primary challenges and lessons learned in developing, implementing, and evaluating SKOOP. These include a political climate surrounding naloxone distribution; b extant prescription drug laws; c initial low levels of recruitment into the program; d development of participant appropriate training methodology; e challenges in the design of a suitable formal evaluation; and f evolution of program response to naloxone. Conclusion Other naloxone distribution programs may anticipate similar challenges to SKOOP and we identify mechanisms to address them. Strategies include being flexible in
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Pelrine, Eliza; Pasik, Sara Diana; Bayat, Leyla; Goldschmiedt, Debora; Bauer, Elizabeth P
2016-12-01
Selective serotonin reuptake inhibitors (SSRIs) are widely prescribed to treat anxiety and depression, yet they paradoxically increase anxiety during initial treatment. Acute administration of these drugs prior to learning can also enhance Pavlovian cued fear conditioning. This potentiation has been previously reported to depend upon the bed nucleus of the stria terminalis (BNST). Here, using temporary inactivation, we confirmed that the BNST is not necessary for the acquisition of cued or contextual fear memory. Systemic administration of the SSRI citalopram prior to fear conditioning led to an upregulation of the immediate early gene Arc (activity-regulated cytoskeleton-associated protein) in the oval nucleus of the BNST, and a majority of these neurons expressed the 5-HT2C receptor. Finally, local infusions of a 5-HT2C receptor antagonist directly into the oval nucleus of the BNST prevented the fear memory-enhancing effects of citalopram. These findings highlight the ability of the BNST circuitry to be recruited into gating fear and anxiety-like behaviors. Copyright © 2016 Elsevier Inc. All rights reserved.
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Vafaee Sharbaf, Fatemeh; Mosafer, Sara; Moattar, Mohammad Hossein
2016-06-01
This paper proposes an approach for gene selection in microarray data. The proposed approach consists of a primary filter approach using Fisher criterion which reduces the initial genes and hence the search space and time complexity. Then, a wrapper approach which is based on cellular learning automata (CLA) optimized with ant colony method (ACO) is used to find the set of features which improve the classification accuracy. CLA is applied due to its capability to learn and model complicated relationships. The selected features from the last phase are evaluated using ROC curve and the most effective while smallest feature subset is determined. The classifiers which are evaluated in the proposed framework are K-nearest neighbor; support vector machine and naïve Bayes. The proposed approach is evaluated on 4 microarray datasets. The evaluations confirm that the proposed approach can find the smallest subset of genes while approaching the maximum accuracy. Copyright © 2016 Elsevier Inc. All rights reserved.
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A Model for Predicting Learning Flow and Achievement in Corporate e-Learning
Joo, Young Ju; Lim, Kyu Yon; Kim, Su Mi
2012-01-01
The primary objective of this study was to investigate the determinants of learning flow and achievement in corporate online training. Self-efficacy, intrinsic value, and test anxiety were selected as learners' motivational factors, while perceived usefulness and ease of use were also selected as learning environmental factors. Learning flow was…
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Park, Sang Hyun; Gao, Yaozong; Shi, Yinghuan; Shen, Dinggang
2014-11-01
Accurate prostate segmentation is necessary for maximizing the effectiveness of radiation therapy of prostate cancer. However, manual segmentation from 3D CT images is very time-consuming and often causes large intra- and interobserver variations across clinicians. Many segmentation methods have been proposed to automate this labor-intensive process, but tedious manual editing is still required due to the limited performance. In this paper, the authors propose a new interactive segmentation method that can (1) flexibly generate the editing result with a few scribbles or dots provided by a clinician, (2) fast deliver intermediate results to the clinician, and (3) sequentially correct the segmentations from any type of automatic or interactive segmentation methods. The authors formulate the editing problem as a semisupervised learning problem which can utilize a priori knowledge of training data and also the valuable information from user interactions. Specifically, from a region of interest near the given user interactions, the appropriate training labels, which are well matched with the user interactions, can be locally searched from a training set. With voting from the selected training labels, both confident prostate and background voxels, as well as unconfident voxels can be estimated. To reflect informative relationship between voxels, location-adaptive features are selected from the confident voxels by using regression forest and Fisher separation criterion. Then, the manifold configuration computed in the derived feature space is enforced into the semisupervised learning algorithm. The labels of unconfident voxels are then predicted by regularizing semisupervised learning algorithm. The proposed interactive segmentation method was applied to correct automatic segmentation results of 30 challenging CT images. The correction was conducted three times with different user interactions performed at different time periods, in order to evaluate both the efficiency
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Teen Pregnancy Prevention: Implementation of a Multicomponent, Community-Wide Approach.
Mueller, Trisha; Tevendale, Heather D; Fuller, Taleria R; House, L Duane; Romero, Lisa M; Brittain, Anna; Varanasi, Bala
2017-03-01
This article provides an overview and description of implementation activities of the multicomponent, community-wide initiatives of the Teenage Pregnancy Prevention Program initiated in 2010 by the Office of Adolescent Health and the Centers for Disease Control and Prevention. The community-wide initiatives applied the Interactive Systems Framework for dissemination and implementation through training and technical assistance on the key elements of the initiative: implementation of evidence-based teen pregnancy prevention (TPP) interventions; enhancing quality of and access to youth-friendly reproductive health services; educating stakeholders about TPP; working with youth in communities most at risk of teen pregnancy; and mobilizing the community to garner support. Of nearly 12,000 hours of training and technical assistance provided, the majority was for selecting, implementing, and evaluating an evidence-based TPP program. Real-world implementation of a community-wide approach to TPP takes time and effort. This report describes implementation within each of the components and shares lessons learned during planning and implementation phases of the initiative. Copyright © 2016 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.
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Dopamine selectively remediates 'model-based' reward learning: a computational approach.
Sharp, Madeleine E; Foerde, Karin; Daw, Nathaniel D; Shohamy, Daphna
2016-02-01
Patients with loss of dopamine due to Parkinson's disease are impaired at learning from reward. However, it remains unknown precisely which aspect of learning is impaired. In particular, learning from reward, or reinforcement learning, can be driven by two distinct computational processes. One involves habitual stamping-in of stimulus-response associations, hypothesized to arise computationally from 'model-free' learning. The other, 'model-based' learning, involves learning a model of the world that is believed to support goal-directed behaviour. Much work has pointed to a role for dopamine in model-free learning. But recent work suggests model-based learning may also involve dopamine modulation, raising the possibility that model-based learning may contribute to the learning impairment in Parkinson's disease. To directly test this, we used a two-step reward-learning task which dissociates model-free versus model-based learning. We evaluated learning in patients with Parkinson's disease tested ON versus OFF their dopamine replacement medication and in healthy controls. Surprisingly, we found no effect of disease or medication on model-free learning. Instead, we found that patients tested OFF medication showed a marked impairment in model-based learning, and that this impairment was remediated by dopaminergic medication. Moreover, model-based learning was positively correlated with a separate measure of working memory performance, raising the possibility of common neural substrates. Our results suggest that some learning deficits in Parkinson's disease may be related to an inability to pursue reward based on complete representations of the environment. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
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Selected engagement factors and academic learning outcomes of undergraduate engineering students
Justice, Patricia J.
The concept of student engagement and its relationship to successful student performance and learning outcomes has a long history in higher education (Kuh, 2007). Attention to faculty and student engagement has only recently become of interest to the engineering education community. This interest can be attributed to long-standing research by George Kuh's, National Survey of Student Engagement (NSSE) at the Indiana University Center for Postsecondary Research. In addition, research projects sponsored by the National Science Foundation, the Academic Pathway Study (APS) at the Center for the Advancement of Engineering Education (CAEE) and the Center for the Advancement of Scholarship on Engineering Education (CASEE), Measuring Student and Faculty Engagement in Engineering Education, at the National Academy of Engineering. These research studies utilized the framework and data from the Engineering Change study by the Center for the Study of Higher Education, Pennsylvania State, that evaluated the impact of the new Accreditation Board of Engineering and Technology (ABET) EC2000 "3a through k" criteria identify 11 learning outcomes expected of engineering graduates. The purpose of this study was to explore the extent selected engagement factors of 1. institution, 2. social, 3. cognitive, 4. finance, and 5. technology influence undergraduate engineering students and quality student learning outcomes. Through the descriptive statistical analysis indicates that there maybe problems in the engineering program. This researcher would have expected at least 50% of the students to fall in the Strongly Agree and Agree categories. The data indicated that the there maybe problems in the engineering program problems in the data. The problems found ranked in this order: 1). Dissatisfaction with faculty instruction methods and quality of instruction and not a clear understanding of engineering majors , 2). inadequate Engineering faculty and advisors availability especially applicable
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Sherwood, Charles; Chambless, Martha
Relationships between reading achievement and perceptual skills as measured by selected subtests of the Detroit Tests of Learning Aptitude were investigated in a sample of 73 second graders. Verbal opposites, visual memory for designs, and visual attention span for letters were significantly correlated with both word meaning and vocabulary…
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Boat noise prevents soundscape-based habitat selection by coral planulae.
Lecchini, David; Bertucci, Frédéric; Gache, Camille; Khalife, Adam; Besson, Marc; Roux, Natacha; Berthe, Cecile; Singh, Shubha; Parmentier, Eric; Nugues, Maggy M; Brooker, Rohan M; Dixson, Danielle L; Hédouin, Laetitia
2018-06-18
Understanding the relationship between coral reef condition and recruitment potential is vital for the development of effective management strategies that maintain coral cover and biodiversity. Coral larvae (planulae) have been shown to use certain sensory cues to orient towards settlement habitats (e.g. the odour of live crustose coralline algae - CCA). However, the influence of auditory cues on coral recruitment, and any effect of anthropogenic noise on this process, remain largely unknown. Here, we determined the effect of protected reef (MPA), exploited reef (non-MPA) soundscapes, and a source of anthropogenic noise (boat) on the habitat preference for live CCA over dead CCA in the planula of two common Indo-Pacific coral species (Pocillopora damicornis and Acropora cytherea). Soundscapes from protected reefs significantly increased the phonotaxis of planulae of both species towards live CCA, especially when compared to boat noise. Boat noise playback prevented this preferential selection of live CCA as a settlement substrate. These results suggest that sources of anthropogenic noise such as motor boat can disrupt the settlement behaviours of coral planulae. Acoustic cues should be accounted for when developing management strategies aimed at maximizing larval recruitment to coral reefs.
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Burn Prevention for Families with Children with Special Needs
Full Text Available ... Burns and Scalds Burn Prevention for Families With Children With Special Needs Watch this video to learn ... know about burn prevention if you have a child with special needs. Read our burn prevention tips | ...
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Okada, Takeshi; Kawakita, Fumihiro; Nishikawa, Hirofumi; Nakano, Fumi; Liu, Lei; Suzuki, Hidenori
2018-05-31
There are no direct evidences showing the linkage between Toll-like receptor 4 (TLR4) and blood-brain barrier (BBB) disruption after subarachnoid hemorrhage (SAH). The purpose of this study was to examine if selective blockage of TLR4 prevents BBB disruption after SAH in mice and if the TLR4 signaling involves mitogen-activated protein kinases (MAPKs). One hundred and fifty-one C57BL/6 male mice underwent sham or endovascular perforation SAH operation, randomly followed by an intracerebroventricular infusion of vehicle or two dosages (117 or 585 ng) of a selective TLR4 antagonist IAXO-102 at 30 min post-operation. The effects were evaluated by survival rates, neurological scores, and brain water content at 24-72 h and immunoglobulin G immunostaining and Western blotting at 24 h post-SAH. IAXO-102 significantly prevented post-SAH neurological impairments, brain edema, and BBB disruption, resulting in improved survival rates. IAXO-102 also significantly suppressed post-SAH activation of a major isoform of MAPK p46 c-Jun N-terminal kinase (JNK) and matrix metalloproteinase-9 as well as periostin induction and preserved tight junction protein zona occludens-1. Another selective TLR4 antagonist TAK-242, which has a different binding site from IAXO-102, also showed similar effects to IAXO-102. This study first provided the evidence that TLR4 signaling is involved in post-SAH acute BBB disruption and that the signaling is mediated at least partly by JNK activation. TLR4-targeted therapy may be promising to reduce post-SAH morbidities and mortalities.
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Factors that Prevent Learning in Electrochemistry
Schmidt, Hans-Jurgen; Marohn, Annette; Harrison, Allan G.
2007-01-01
Electrochemistry plays an important role in curricula, textbooks, and in everyday life. The purpose of the present study was to identify and understand secondary-school students' problems in learning electrochemistry at an introductory chemistry level. The investigation covered four areas: (a) electrolytes, (b) transport of electric charges in…
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Cognitive components underpinning the development of model-based learning.
Potter, Tracey C S; Bryce, Nessa V; Hartley, Catherine A
2017-06-01
Reinforcement learning theory distinguishes "model-free" learning, which fosters reflexive repetition of previously rewarded actions, from "model-based" learning, which recruits a mental model of the environment to flexibly select goal-directed actions. Whereas model-free learning is evident across development, recruitment of model-based learning appears to increase with age. However, the cognitive processes underlying the development of model-based learning remain poorly characterized. Here, we examined whether age-related differences in cognitive processes underlying the construction and flexible recruitment of mental models predict developmental increases in model-based choice. In a cohort of participants aged 9-25, we examined whether the abilities to infer sequential regularities in the environment ("statistical learning"), maintain information in an active state ("working memory") and integrate distant concepts to solve problems ("fluid reasoning") predicted age-related improvements in model-based choice. We found that age-related improvements in statistical learning performance did not mediate the relationship between age and model-based choice. Ceiling performance on our working memory assay prevented examination of its contribution to model-based learning. However, age-related improvements in fluid reasoning statistically mediated the developmental increase in the recruitment of a model-based strategy. These findings suggest that gradual development of fluid reasoning may be a critical component process underlying the emergence of model-based learning. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.
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Morello, Giuseppe; Morris, P. W.; Van Dyk, S. D.; Marston, A. P.; Mauerhan, J. C.
2018-01-01
We have investigated and applied machine-learning algorithms for infrared colour selection of Galactic Wolf-Rayet (WR) candidates. Objects taken from the Spitzer Galactic Legacy Infrared Midplane Survey Extraordinaire (GLIMPSE) catalogue of the infrared objects in the Galactic plane can be classified into different stellar populations based on the colours inferred from their broad-band photometric magnitudes [J, H and Ks from 2 Micron All Sky Survey (2MASS), and the four Spitzer/IRAC bands]. The algorithms tested in this pilot study are variants of the k-nearest neighbours approach, which is ideal for exploratory studies of classification problems where interrelations between variables and classes are complicated. The aims of this study are (1) to provide an automated tool to select reliable WR candidates and potentially other classes of objects, (2) to measure the efficiency of infrared colour selection at performing these tasks and (3) to lay the groundwork for statistically inferring the total number of WR stars in our Galaxy. We report the performance results obtained over a set of known objects and selected candidates for which we have carried out follow-up spectroscopic observations, and confirm the discovery of four new WR stars.
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Feature selection for domain knowledge representation through multitask learning
CSIR Research Space (South Africa)
Rosman, Benjamin S
2014-10-01
Full Text Available represent stimuli of interest, and rich feature sets which increase the dimensionality of the space and thus the difficulty of the learning problem. We focus on a multitask reinforcement learning setting, where the agent is learning domain knowledge...
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Cerezo, Rebeca; Esteban, María; Sánchez-Santillán, Miguel; Núñez, José C
2017-01-01
Introduction: Research about student performance has traditionally considered academic procrastination as a behavior that has negative effects on academic achievement. Although there is much evidence for this in class-based environments, there is a lack of research on Computer-Based Learning Environments (CBLEs) . Therefore, the purpose of this study is to evaluate student behavior in a blended learning program and specifically procrastination behavior in relation to performance through Data Mining techniques. Materials and Methods: A sample of 140 undergraduate students participated in a blended learning experience implemented in a Moodle (Modular Object Oriented Developmental Learning Environment) Management System. Relevant interaction variables were selected for the study, taking into account student achievement and analyzing data by means of association rules, a mining technique. The association rules were arrived at and filtered through two selection criteria: 1, rules must have an accuracy over 0.8 and 2, they must be present in both sub-samples. Results: The findings of our study highlight the influence of time management in online learning environments, particularly on academic achievement, as there is an association between procrastination variables and student performance. Conclusion: Negative impact of procrastination in learning outcomes has been observed again but in virtual learning environments where practical implications, prevention of, and intervention in, are different from class-based learning. These aspects are discussed to help resolve student difficulties at various ages.
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Cerezo, Rebeca; Esteban, María; Sánchez-Santillán, Miguel; Núñez, José C.
2017-01-01
Introduction: Research about student performance has traditionally considered academic procrastination as a behavior that has negative effects on academic achievement. Although there is much evidence for this in class-based environments, there is a lack of research on Computer-Based Learning Environments (CBLEs). Therefore, the purpose of this study is to evaluate student behavior in a blended learning program and specifically procrastination behavior in relation to performance through Data Mining techniques. Materials and Methods: A sample of 140 undergraduate students participated in a blended learning experience implemented in a Moodle (Modular Object Oriented Developmental Learning Environment) Management System. Relevant interaction variables were selected for the study, taking into account student achievement and analyzing data by means of association rules, a mining technique. The association rules were arrived at and filtered through two selection criteria: 1, rules must have an accuracy over 0.8 and 2, they must be present in both sub-samples. Results: The findings of our study highlight the influence of time management in online learning environments, particularly on academic achievement, as there is an association between procrastination variables and student performance. Conclusion: Negative impact of procrastination in learning outcomes has been observed again but in virtual learning environments where practical implications, prevention of, and intervention in, are different from class-based learning. These aspects are discussed to help resolve student difficulties at various ages. PMID:28883801
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Directory of Open Access Journals (Sweden)
Rebeca Cerezo
2017-08-01
Full Text Available Introduction: Research about student performance has traditionally considered academic procrastination as a behavior that has negative effects on academic achievement. Although there is much evidence for this in class-based environments, there is a lack of research on Computer-Based Learning Environments (CBLEs. Therefore, the purpose of this study is to evaluate student behavior in a blended learning program and specifically procrastination behavior in relation to performance through Data Mining techniques.Materials and Methods: A sample of 140 undergraduate students participated in a blended learning experience implemented in a Moodle (Modular Object Oriented Developmental Learning Environment Management System. Relevant interaction variables were selected for the study, taking into account student achievement and analyzing data by means of association rules, a mining technique. The association rules were arrived at and filtered through two selection criteria: 1, rules must have an accuracy over 0.8 and 2, they must be present in both sub-samples.Results: The findings of our study highlight the influence of time management in online learning environments, particularly on academic achievement, as there is an association between procrastination variables and student performance.Conclusion: Negative impact of procrastination in learning outcomes has been observed again but in virtual learning environments where practical implications, prevention of, and intervention in, are different from class-based learning. These aspects are discussed to help resolve student difficulties at various ages.
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Pollution prevention projects in the Netherlands
de Bruijn, Theo; Coenen, Franciscus H.J.M.; Lulofs, Kristiaan R.D.
1996-01-01
As part of its waste matter prevention policy, the Dutch government has tried over the past few years to stimulate pollution prevention in firms by means of so-called stimulation and learning projects. To be able to determine the effectiveness of future policies, an extensive evaluation study was
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Breast Cancer Prevention (PDQ®)—Patient Version
Breast cancer prevention strategies include avoiding known risks, having a healthy lifestyle, and medications or surgery for those at high risk. Learn more about breast cancer prevention, risks and protective factors, and how to estimate risk in this expert-reviewed summary.
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Fraser, Katherine
This publication is a supplementary chapter to "Fit, Healthy, and Ready to Learn: A School Health Policy Guide; Part I: General School Health Policies, Physical Activity, Healthy Eating, and Tobacco-Use Prevention." It discusses various aspects of a complete school policy and plan to promote sun safety. The first section "Purpose…
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Burn Prevention for Families with Children with Special Needs
Full Text Available ... Scalds Burn Prevention for Families With Children With Special Needs Watch this video to learn what you need ... burn prevention if you have a child with special needs. Read our burn prevention tips | Visit our YouTube ...
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Meyers, Alysha R; Al-Tarawneh, Ibraheem S; Wurzelbacher, Steven J; Bushnell, P Timothy; Lampl, Michael P; Bell, Jennifer L; Bertke, Stephen J; Robins, David C; Tseng, Chih-Yu; Wei, Chia; Raudabaugh, Jill A; Schnorr, Teresa M
2018-01-01
This study leveraged a state workers' compensation claims database and machine learning techniques to target prevention efforts by injury causation and industry. Injury causation auto-coding methods were developed to code more than 1.2 million Ohio Bureau of Workers' Compensation claims for this study. Industry groups were ranked for soft-tissue musculoskeletal claims that may have been preventable with biomechanical ergonomic (ERGO) or slip/trip/fall (STF) interventions. On the basis of the average of claim count and rate ranks for more than 200 industry groups, Skilled Nursing Facilities (ERGO) and General Freight Trucking (STF) were the highest risk for lost-time claims (>7 days). This study created a third, major causation-specific U.S. occupational injury surveillance system. These findings are being used to focus prevention resources on specific occupational injury types in specific industry groups, especially in Ohio. Other state bureaus or insurers may use similar methods.
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Kemp, Patrice
2016-01-01
The focus of the milestone project is to focus on bridging the gap of bullying and classroom instruction methods. There has to be a defined expectations and level of accountability that has to be defined when supporting and implementing a plan linked to bullying prevention. All individuals involved in the student's learning have to be aware of…
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An introduction to machine learning with Scikit-Learn
CERN. Geneva
2015-01-01
This tutorial gives an introduction to the scientific ecosystem for data analysis and machine learning in Python. After a short introduction of machine learning concepts, we will demonstrate on High Energy Physics data how a basic supervised learning analysis can be carried out using the Scikit-Learn library. Topics covered include data loading facilities and data representation, supervised learning algorithms, pipelines, model selection and evaluation, and model introspection.
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Increasing the efficacy of cue exposure treatment in preventing relapse of addictive behavior.
Havermans, Remco C; Jansen, Anita T M
2003-07-01
Theoretically, cue exposure treatment should be able to prevent relapse by extinguishing conditioned drug responding (e.g. cue-elicited craving). According to contemporary learning theory, though, extinction does not eliminate conditioned responding. Analogous cue exposure with response prevention (CERP) as a treatment of addictive behavior might not eliminate the learned relation between drug-related cues and drug use. This does not necessarily mean that cue exposure cannot successfully prevent relapse. Various suggestions for increasing the efficacy of cue exposure treatment are being discussed from a contemporary learning theory perspective. It is suggested that cue exposure treatment incorporating retrieval cues can be a beneficial treatment in preventing relapse of addictive behavior.
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DEFF Research Database (Denmark)
Holtermann, A; Mork, P J; Andersen, L L
2010-01-01
the serratus anterior with visual EMG biofeedback, while the activity of four parts of the serratus anterior and four parts of the trapezius muscle was recorded. One subject was able to selectively activate both the upper and the lower serratus anterior respectively. Moreover, three subjects managed...... to selectively activate the lower serratus anterior, and two subjects learned to selectively activate the upper serratus anterior. During selective activation of the lower serratus anterior, the activity of this muscle part was 14.4+/-10.3 times higher than the upper serratus anterior activity (P....05). The corresponding ratio for selective upper serratus vs. lower serratus anterior activity was 6.4+/-1.7 (Ptimes higher synergistic activity of the lower trapezius compared with the upper trapezius (P
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Directory of Open Access Journals (Sweden)
Aimee eWong
2013-09-01
Full Text Available The DBA/2J mouse is a model of pigmentary glaucoma in humans as it shows age‐related increases in intraocular pressure, retinal ganglion cell death and visual impairment. Previously, we showed that visual ability declines from 9 ‐12 months of age and visual impairment is correlated with poor learning and memory performance in visuo‐spatial tasks but not in tasks that do not depend on visual cues. To test the sensory impairment hypothesis of aging, which postulates that sensory impaired individuals are disadvantaged in their performance on psychometric tests as a direct result of difficulties in sensory perception, we treated DBA/2J mice with a conventional glaucoma medication used in humans (Timoptic‐XE, 0.00, 0.25 or 0.50% daily from 9 weeks to 12 months of age to determine whether prevention of vision loss prevented the decline in visuo-spatial learning and memory performance. At all ages tested (3, 6, 9 and 12 months of age, mice treated with Timoptic-XE (0.25 and 0.50% maintained a high level of performance, while 12 month old control mice (0.00% exhibited impaired performance in visually‐dependent, but not non‐visual tasks. These results demonstrate that when sensory function is preserved, cognitive performance is normalized. Thus, as in many aging humans, DBA/2J mice show age-related decrements in performance on visually presented cognitive tests, not because of cognitive impairment but as a direct consequence of poor visual ability. Our results demonstrate that age-related impairment in performance in visuo-spatial tasks in DBA/2J mice can be prevented by the preservation of visual ability.
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Wong, Aimée A; Brown, Richard E
2013-01-01
The DBA/2J mouse is a model of pigmentary glaucoma in humans as it shows age-related increases in intraocular pressure (IOP), retinal ganglion cell death and visual impairment. Previously, we showed that visual ability declines from 9 to 12 months of age and visual impairment is correlated with poor learning and memory performance in visuo-spatial tasks but not in tasks that do not depend on visual cues. To test the "sensory impairment" hypothesis of aging, which postulates that sensory impaired individuals are disadvantaged in their performance on psychometric tests as a direct result of difficulties in sensory perception, we treated DBA/2J mice with a conventional glaucoma medication used in humans (Timoptic-XE, 0.00, 0.25, or 0.50%) daily from 9 weeks to 12 months of age to determine whether prevention of vision loss prevented the decline in visuo-spatial learning and memory performance. At all ages tested (3, 6, 9, and 12 months of age), mice treated with Timoptic-XE (0.25 and 0.50%) maintained a high level of performance, while 12 month old control mice (0.00%) exhibited impaired performance in visually-dependent, but not non-visual tasks. These results demonstrate that when sensory function is preserved, cognitive performance is normalized. Thus, as in many aging humans, DBA/2J mice show age-related decrements in performance on visually presented cognitive tests, not because of cognitive impairment but as a direct consequence of poor visual ability. Our results demonstrate that age-related impairment in performance in visuo-spatial tasks in DBA/2J mice can be prevented by the preservation of visual ability.
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Energy Technology Data Exchange (ETDEWEB)
Park, Sang Hyun [Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599 (United States); Gao, Yaozong, E-mail: yzgao@cs.unc.edu [Department of Computer Science, Department of Radiology, and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599 (United States); Shi, Yinghuan, E-mail: syh@nju.edu.cn [State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210023 (China); Shen, Dinggang, E-mail: dgshen@med.unc.edu [Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599 and Department of Brain and Cognitive Engineering, Korea University, Seoul 136-713 (Korea, Republic of)
2014-11-01
Purpose: Accurate prostate segmentation is necessary for maximizing the effectiveness of radiation therapy of prostate cancer. However, manual segmentation from 3D CT images is very time-consuming and often causes large intra- and interobserver variations across clinicians. Many segmentation methods have been proposed to automate this labor-intensive process, but tedious manual editing is still required due to the limited performance. In this paper, the authors propose a new interactive segmentation method that can (1) flexibly generate the editing result with a few scribbles or dots provided by a clinician, (2) fast deliver intermediate results to the clinician, and (3) sequentially correct the segmentations from any type of automatic or interactive segmentation methods. Methods: The authors formulate the editing problem as a semisupervised learning problem which can utilize a priori knowledge of training data and also the valuable information from user interactions. Specifically, from a region of interest near the given user interactions, the appropriate training labels, which are well matched with the user interactions, can be locally searched from a training set. With voting from the selected training labels, both confident prostate and background voxels, as well as unconfident voxels can be estimated. To reflect informative relationship between voxels, location-adaptive features are selected from the confident voxels by using regression forest and Fisher separation criterion. Then, the manifold configuration computed in the derived feature space is enforced into the semisupervised learning algorithm. The labels of unconfident voxels are then predicted by regularizing semisupervised learning algorithm. Results: The proposed interactive segmentation method was applied to correct automatic segmentation results of 30 challenging CT images. The correction was conducted three times with different user interactions performed at different time periods, in order to
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International Nuclear Information System (INIS)
Park, Sang Hyun; Gao, Yaozong; Shi, Yinghuan; Shen, Dinggang
2014-01-01
Purpose: Accurate prostate segmentation is necessary for maximizing the effectiveness of radiation therapy of prostate cancer. However, manual segmentation from 3D CT images is very time-consuming and often causes large intra- and interobserver variations across clinicians. Many segmentation methods have been proposed to automate this labor-intensive process, but tedious manual editing is still required due to the limited performance. In this paper, the authors propose a new interactive segmentation method that can (1) flexibly generate the editing result with a few scribbles or dots provided by a clinician, (2) fast deliver intermediate results to the clinician, and (3) sequentially correct the segmentations from any type of automatic or interactive segmentation methods. Methods: The authors formulate the editing problem as a semisupervised learning problem which can utilize a priori knowledge of training data and also the valuable information from user interactions. Specifically, from a region of interest near the given user interactions, the appropriate training labels, which are well matched with the user interactions, can be locally searched from a training set. With voting from the selected training labels, both confident prostate and background voxels, as well as unconfident voxels can be estimated. To reflect informative relationship between voxels, location-adaptive features are selected from the confident voxels by using regression forest and Fisher separation criterion. Then, the manifold configuration computed in the derived feature space is enforced into the semisupervised learning algorithm. The labels of unconfident voxels are then predicted by regularizing semisupervised learning algorithm. Results: The proposed interactive segmentation method was applied to correct automatic segmentation results of 30 challenging CT images. The correction was conducted three times with different user interactions performed at different time periods, in order to
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Ghoncheh, Rezvan; Kerkhof, Ad JFM; Koot, Hans M
2014-01-01
Background Providing e-learning modules can be an effective strategy for enhancing gatekeepers’ knowledge, self-confidence and skills in adolescent suicide prevention. The aim of this study was to test the effectiveness of an online training program called Mental Health Online which consists of eight short e-learning modules, each capturing an important aspect of the process of recognition, guidance and referral of suicidal adolescents (12–20 years). The primary outcomes of this study are par...
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Ghoncheh, R.; Kerkhof, A.J.F.M.; Koot, H.M.
2014-01-01
Background: Providing e-learning modules can be an effective strategy for enhancing gatekeepers' knowledge, self-confidence and skills in adolescent suicide prevention. The aim of this study was to test the effectiveness of an online training program called Mental Health Online which consists of eight short e-learning modules, each capturing an important aspect of the process of recognition, guidance and referral of suicidal adolescents (12-20 years). The primary outcomes of this study are pa...
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Corporate externalities: a challenge to the further success of prevention science.
Biglan, Anthony
2011-03-01
The full benefit of prevention science will not be realized until we learn how to influence organizational practices. The marketing of tobacco, alcohol, and food and corporate advocacy for economic policies that maintain family poverty are examples of practices we must influence. This paper analyzes the evolution of such practices in terms of their selection by economic consequences. A strategy for addressing these critical risk factors should include: (a) systematic research on the impact of corporate practices on each of the most common and costly psychological and behavior problems; (b) empirical analyses of the consequences that select harmful corporate practices; (c) assessment of the impact of policies that could affect problematic corporate practices; and (d) research on advocacy organizations to understand the factors that influence their growth and to help them develop effective strategies for influencing corporate externalities.
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Centers for Disease Control (CDC) Podcasts
2016-05-18
A man and a woman talk about how theyâve learned to protect their skin from the sun over the years. . Created: 5/18/2016 by National Center for Chronic Disease Prevention and Health Promotion (NCCDPHP). Date Released: 5/18/2016.
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Centers for Disease Control (CDC) Podcasts
2015-06-02
This 60 second public service announcement is based on the June 2015 CDC Vital Signs report. Skin cancer is the most common form of cancer in the U.S. In 2011, there were more than 65,000 cases of melanoma, the most deadly form of skin cancer. Learn how everyone can help prevent skin cancer. Created: 6/2/2015 by National Center for Chronic Disease Prevention and Health Promotion (NCCDPHP). Date Released: 6/2/2015.
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Supporting Children with Learning Disabilities
John k. McNamara
2010-01-01
This paper presents a prevention model for supporting children with learning disabilities. The model holds that children can be identified as at-risk for learning disabilities by identifying and supporting potential academic failure early in their elementary years. A prevention model includes two elements, identification and instruction. Identification entails recognizing those children at-risk for poor achievement in the early primary grades. The second component of the model is to...
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Torija, Antonio J; Ruiz, Diego P
2015-02-01
The prediction of environmental noise in urban environments requires the solution of a complex and non-linear problem, since there are complex relationships among the multitude of variables involved in the characterization and modelling of environmental noise and environmental-noise magnitudes. Moreover, the inclusion of the great spatial heterogeneity characteristic of urban environments seems to be essential in order to achieve an accurate environmental-noise prediction in cities. This problem is addressed in this paper, where a procedure based on feature-selection techniques and machine-learning regression methods is proposed and applied to this environmental problem. Three machine-learning regression methods, which are considered very robust in solving non-linear problems, are used to estimate the energy-equivalent sound-pressure level descriptor (LAeq). These three methods are: (i) multilayer perceptron (MLP), (ii) sequential minimal optimisation (SMO), and (iii) Gaussian processes for regression (GPR). In addition, because of the high number of input variables involved in environmental-noise modelling and estimation in urban environments, which make LAeq prediction models quite complex and costly in terms of time and resources for application to real situations, three different techniques are used to approach feature selection or data reduction. The feature-selection techniques used are: (i) correlation-based feature-subset selection (CFS), (ii) wrapper for feature-subset selection (WFS), and the data reduction technique is principal-component analysis (PCA). The subsequent analysis leads to a proposal of different schemes, depending on the needs regarding data collection and accuracy. The use of WFS as the feature-selection technique with the implementation of SMO or GPR as regression algorithm provides the best LAeq estimation (R(2)=0.94 and mean absolute error (MAE)=1.14-1.16 dB(A)). Copyright © 2014 Elsevier B.V. All rights reserved.
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Object learning improves feature extraction but does not improve feature selection.
Directory of Open Access Journals (Sweden)
Linus Holm
Full Text Available A single glance at your crowded desk is enough to locate your favorite cup. But finding an unfamiliar object requires more effort. This superiority in recognition performance for learned objects has at least two possible sources. For familiar objects observers might: 1 select more informative image locations upon which to fixate their eyes, or 2 extract more information from a given eye fixation. To test these possibilities, we had observers localize fragmented objects embedded in dense displays of random contour fragments. Eight participants searched for objects in 600 images while their eye movements were recorded in three daily sessions. Performance improved as subjects trained with the objects: The number of fixations required to find an object decreased by 64% across the 3 sessions. An ideal observer model that included measures of fragment confusability was used to calculate the information available from a single fixation. Comparing human performance to the model suggested that across sessions information extraction at each eye fixation increased markedly, by an amount roughly equal to the extra information that would be extracted following a 100% increase in functional field of view. Selection of fixation locations, on the other hand, did not improve with practice.
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DEFF Research Database (Denmark)
Dirckinck-Holmfeld, Lone; Svendsen, Brian Møller; Ponti, Marisa
The report documents and summarises the elements and dimensions that have been identified to describe and analyse the case studies collected in the Kaleidoscope Jointly Executed Integrating Research Project (JEIRP) on Conditions for productive learning in network learning environments.......The report documents and summarises the elements and dimensions that have been identified to describe and analyse the case studies collected in the Kaleidoscope Jointly Executed Integrating Research Project (JEIRP) on Conditions for productive learning in network learning environments....
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Education for Disaster Prevention in Elementary School in Japan
Shida, Masakuni
2013-04-01
Education for disaster prevention has become more and more important since the Great East Japan Earthquake and tsunami in 2011. More than 18 thousand people were killed or have not been found yet in the tragedy, however, in Kesn'numa, which is a city located in the seriously damaged area, there were few student victims of tsunami. This is because every school in Kesen'numa has excellent education systems for disaster prevention. They have several safety exercises and conducts emergency drills each year in unique ways which have been developed upon the tragic experiences of serious earthquakes and tsunami in the past. For disaster prevention education, we should learn two important points from the case in Kesen'numa; to learn from the ancient wisdom, and to ensure for students to have enough opportunities of safety exercises and emergency drills at school. In addition to these two points, another issue from the viewpoint of science education can be added, which is to learn about the mechanisms of earthquake. We have developed disaster prevention and reduction programs in educational context, taking these three points into consideration. First part of the program is to study local history, focusing on ancient wisdom. In Kesen'numa City, there were thirty-three monumental stones with cautionary lessons of the possible danger of tsunami before the great earthquake. The lessons were based on the disasters actually happened in the past and brought down to the current generation. Kesen'numa-Otani elementary school has conducted education for disaster prevention referring to this information with full of ancient wisdom. Second part of the program is to make sure that every student has enough and rich opportunities to simulate the worst situation of any disasters. For example, in the case of earthquake and tsunami, teachers take students to the safest place through the designated evacuation rout according to each school's original manual. Students can experience this
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Novak, Miranda; Mihić, Josipa; Bašić, Josipa; Nix, Robert L
2017-04-01
This study represents the first rigorous evaluation of a social-emotional learning curriculum, PATHS (Promoting Alternative Thinking Strategies; Kusché & Greenberg, 1994), in elementary schools in Croatia. This study randomly assigned 29 schools to receive the universal preventive intervention or continue with usual practices. Within those schools, this study included 57 classrooms and 568 children. Teachers rated nine child behaviours in the middle of first grade (pre-intervention) and near the end of second grade (post-intervention). Hierarchical linear models, nesting children within classrooms, revealed few changes in behaviour across the sample as a whole or among higher risk children. However, there were changes on eight of the nine behaviours for lower risk children. The findings are considered in the context of the classroom culture and teachers' preparation and readiness to implement a social-emotional learning curriculum in Croatia. This study highlights the need to supplement universal preventive interventions with selective preventive interventions that can provide more intensive and targeted skill practice for higher risk children. This study also highlights the nuanced effects of a universal preventive intervention in helping different children in different ways. © 2016 International Union of Psychological Science.
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Bias correction for selecting the minimal-error classifier from many machine learning models.
Ding, Ying; Tang, Shaowu; Liao, Serena G; Jia, Jia; Oesterreich, Steffi; Lin, Yan; Tseng, George C
2014-11-15
Supervised machine learning is commonly applied in genomic research to construct a classifier from the training data that is generalizable to predict independent testing data. When test datasets are not available, cross-validation is commonly used to estimate the error rate. Many machine learning methods are available, and it is well known that no universally best method exists in general. It has been a common practice to apply many machine learning methods and report the method that produces the smallest cross-validation error rate. Theoretically, such a procedure produces a selection bias. Consequently, many clinical studies with moderate sample sizes (e.g. n = 30-60) risk reporting a falsely small cross-validation error rate that could not be validated later in independent cohorts. In this article, we illustrated the probabilistic framework of the problem and explored the statistical and asymptotic properties. We proposed a new bias correction method based on learning curve fitting by inverse power law (IPL) and compared it with three existing methods: nested cross-validation, weighted mean correction and Tibshirani-Tibshirani procedure. All methods were compared in simulation datasets, five moderate size real datasets and two large breast cancer datasets. The result showed that IPL outperforms the other methods in bias correction with smaller variance, and it has an additional advantage to extrapolate error estimates for larger sample sizes, a practical feature to recommend whether more samples should be recruited to improve the classifier and accuracy. An R package 'MLbias' and all source files are publicly available. tsenglab.biostat.pitt.edu/software.htm. ctseng@pitt.edu Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
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The Impact of Learning Curve Model Selection and Criteria for Cost Estimation Accuracy in the DoD
2016-04-30
different in the future due to machines” • Heightened scrutiny of cost estimates • Budget Control Act of 2011 seeks to reduce federal deficit ...qÜáêíÉÉåíÜ=^ååì~ä= ^Åèìáëáíáçå=oÉëÉ~êÅÜ= póãéçëáìã= qÜìêëÇ~ó=pÉëëáçåë= sçäìãÉ=ff= = The Impact of Learning Curve Model Selection and Criteria for Cost...Assistant Division Director, Institute for Defense Analyses Bruce Harmon, Research Staff Member, Institute for Defense Analyses The Impact of Learning
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Learners' experiences of learning support in selected Western Cape schools
Directory of Open Access Journals (Sweden)
Olaniyi Bojuwoye
2014-01-01
Full Text Available The study explored Western Cape primary and secondary school learners' experiences regarding the provision and utilization of support services for improving learning. A qualitative interpretive approach was adopted and data gathered through focus group interviews involving 90 learners. Results revealed that learners received and utilized various forms of learning support from their schools, teachers, and peers. The learning support assisted in meeting learners' academic, social and emotional needs by addressing barriers to learning, creating conducive learning environments, enhancing learners' self-esteem and improving learners' academic performance.
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Bradfield, Laura A.; McNally, Gavan P.
2010-01-01
We studied the role of nucleus accumbens shell (AcbSh) in Pavlovian fear conditioning. Rats were trained to fear conditioned stimulus A (CSA) in Stage I, which was then presented in compound with a neutral stimulus and paired with shock in Stage II. AcbSh lesions had no effect on fear-learning to CSA in Stage I, but selectively prevented learning…
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Wu, Dongrui; Lance, Brent J; Parsons, Thomas D
2013-01-01
Brain-computer interaction (BCI) and physiological computing are terms that refer to using processed neural or physiological signals to influence human interaction with computers, environment, and each other. A major challenge in developing these systems arises from the large individual differences typically seen in the neural/physiological responses. As a result, many researchers use individually-trained recognition algorithms to process this data. In order to minimize time, cost, and barriers to use, there is a need to minimize the amount of individual training data required, or equivalently, to increase the recognition accuracy without increasing the number of user-specific training samples. One promising method for achieving this is collaborative filtering, which combines training data from the individual subject with additional training data from other, similar subjects. This paper describes a successful application of a collaborative filtering approach intended for a BCI system. This approach is based on transfer learning (TL), active class selection (ACS), and a mean squared difference user-similarity heuristic. The resulting BCI system uses neural and physiological signals for automatic task difficulty recognition. TL improves the learning performance by combining a small number of user-specific training samples with a large number of auxiliary training samples from other similar subjects. ACS optimally selects the classes to generate user-specific training samples. Experimental results on 18 subjects, using both k nearest neighbors and support vector machine classifiers, demonstrate that the proposed approach can significantly reduce the number of user-specific training data samples. This collaborative filtering approach will also be generalizable to handling individual differences in many other applications that involve human neural or physiological data, such as affective computing.
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Directory of Open Access Journals (Sweden)
Dongrui Wu
Full Text Available Brain-computer interaction (BCI and physiological computing are terms that refer to using processed neural or physiological signals to influence human interaction with computers, environment, and each other. A major challenge in developing these systems arises from the large individual differences typically seen in the neural/physiological responses. As a result, many researchers use individually-trained recognition algorithms to process this data. In order to minimize time, cost, and barriers to use, there is a need to minimize the amount of individual training data required, or equivalently, to increase the recognition accuracy without increasing the number of user-specific training samples. One promising method for achieving this is collaborative filtering, which combines training data from the individual subject with additional training data from other, similar subjects. This paper describes a successful application of a collaborative filtering approach intended for a BCI system. This approach is based on transfer learning (TL, active class selection (ACS, and a mean squared difference user-similarity heuristic. The resulting BCI system uses neural and physiological signals for automatic task difficulty recognition. TL improves the learning performance by combining a small number of user-specific training samples with a large number of auxiliary training samples from other similar subjects. ACS optimally selects the classes to generate user-specific training samples. Experimental results on 18 subjects, using both k nearest neighbors and support vector machine classifiers, demonstrate that the proposed approach can significantly reduce the number of user-specific training data samples. This collaborative filtering approach will also be generalizable to handling individual differences in many other applications that involve human neural or physiological data, such as affective computing.
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Directory of Open Access Journals (Sweden)
Samat Moldakarimov
2014-08-01
Full Text Available Perceptual learning has been used to probe the mechanisms of cortical plasticity in the adult brain. Feedback projections are ubiquitous in the cortex, but little is known about their role in cortical plasticity. Here we explore the hypothesis that learning visual orientation discrimination involves learning-dependent plasticity of top-down feedback inputs from higher cortical areas, serving a different function from plasticity due to changes in recurrent connections within a cortical area. In a Hodgkin-Huxley-based spiking neural network model of visual cortex, we show that modulation of feedback inputs to V1 from higher cortical areas results in shunting inhibition in V1 neurons, which changes the response properties of V1 neurons. The orientation selectivity of V1 neurons is enhanced without changing orientation preference, preserving the topographic organizations in V1. These results provide new insights to the mechanisms of plasticity in the adult brain, reconciling apparently inconsistent experiments and providing a new hypothesis for a functional role of the feedback connections.
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Memory Reactivation Enables Long-Term Prevention of Interference.
Herszage, Jasmine; Censor, Nitzan
2017-05-22
The ability of the human brain to successively learn or perform two competing tasks constitutes a major challenge in daily function. Indeed, exposing the brain to two different competing memories within a short temporal offset can induce interference, resulting in deteriorated performance in at least one of the learned memories [1-4]. Although previous studies have investigated online interference and its effects on performance [5-13], whether the human brain can enable long-term prevention of future interference is unknown. To address this question, we utilized the memory reactivation-reconsolidation framework [2, 12] stemming from studies at the synaptic level [14-17], according to which reactivation of a memory enables its update. In a set of experiments, using the motor sequence learning task [18] we report that a unique pairing of reactivating the original memory (right hand) in synchrony with novel memory trials (left hand) prevented future interference between the two memories. Strikingly, these effects were long-term and observed a month following reactivation. Further experiments showed that preventing future interference was not due to practice per se, but rather specifically depended on a limited time window induced by reactivation of the original memory. These results suggest a mechanism according to which memory reactivation enables long-term prevention of interference, possibly by creating an updated memory trace integrating original and novel memories during the reconsolidation time window. The opportunity to induce a long-term preventive effect on memories may enable the utilization of strategies optimizing normal human learning, as well as recovery following neurological insults. Copyright © 2017 Elsevier Ltd. All rights reserved.
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Learning to learn - intrinsic plasticity as a metaplasticity mechanism for memory formation.
Sehgal, Megha; Song, Chenghui; Ehlers, Vanessa L; Moyer, James R
2013-10-01
"Use it or lose it" is a popular adage often associated with use-dependent enhancement of cognitive abilities. Much research has focused on understanding exactly how the brain changes as a function of experience. Such experience-dependent plasticity involves both structural and functional alterations that contribute to adaptive behaviors, such as learning and memory, as well as maladaptive behaviors, including anxiety disorders, phobias, and posttraumatic stress disorder. With the advancing age of our population, understanding how use-dependent plasticity changes across the lifespan may also help to promote healthy brain aging. A common misconception is that such experience-dependent plasticity (e.g., associative learning) is synonymous with synaptic plasticity. Other forms of plasticity also play a critical role in shaping adaptive changes within the nervous system, including intrinsic plasticity - a change in the intrinsic excitability of a neuron. Intrinsic plasticity can result from a change in the number, distribution or activity of various ion channels located throughout the neuron. Here, we review evidence that intrinsic plasticity is an important and evolutionarily conserved neural correlate of learning. Intrinsic plasticity acts as a metaplasticity mechanism by lowering the threshold for synaptic changes. Thus, learning-related intrinsic changes can facilitate future synaptic plasticity and learning. Such intrinsic changes can impact the allocation of a memory trace within a brain structure, and when compromised, can contribute to cognitive decline during the aging process. This unique role of intrinsic excitability can provide insight into how memories are formed and, more interestingly, how neurons that participate in a memory trace are selected. Most importantly, modulation of intrinsic excitability can allow for regulation of learning ability - this can prevent or provide treatment for cognitive decline not only in patients with clinical disorders but
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Nguyen, Cao Thanh
2011-01-01
The paper will explore the challenges students from selected South East Asian countries (Vietnam, Thailand and Indonesia) face while studying English in Australia before entering into Australian University courses. These students must contend not only with different styles of teaching and learning, but also with the challenge of adapting to a new…
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Kajimoto, Masaki; Ledee, Dolena R; Olson, Aaron K; Isern, Nancy G; Robillard-Frayne, Isabelle; Des Rosiers, Christine; Portman, Michael A
2016-11-01
Deep hypothermic circulatory arrest is often required for the repair of complex congenital cardiac defects in infants. However, deep hypothermic circulatory arrest induces neuroapoptosis associated with later development of neurocognitive abnormalities. Selective cerebral perfusion theoretically provides superior neural protection possibly through modifications in cerebral substrate oxidation and closely integrated glutamate cycling. We tested the hypothesis that selective cerebral perfusion modulates glucose utilization, and ameliorates abnormalities in glutamate flux, which occur in association with neuroapoptosis during deep hypothermic circulatory arrest. Eighteen infant male Yorkshire piglets were assigned randomly to two groups of seven (deep hypothermic circulatory arrest or deep hypothermic circulatory arrest with selective cerebral perfusion for 60 minutes at 18℃) and four control pigs without cardiopulmonary bypass support. Carbon-13-labeled glucose as a metabolic tracer was infused, and gas chromatography-mass spectrometry and nuclear magnetic resonance were used for metabolic analysis in the frontal cortex. Following 2.5 h of cerebral reperfusion, we observed similar cerebral adenosine triphosphate levels, absolute levels of lactate and citric acid cycle intermediates, and carbon-13 enrichment among three groups. However, deep hypothermic circulatory arrest induced significant abnormalities in glutamate cycling resulting in reduced glutamate/glutamine and elevated γ-aminobutyric acid/glutamate along with neuroapoptosis, which were all prevented by selective cerebral perfusion. The data suggest that selective cerebral perfusion prevents these modifications in glutamate/glutamine/γ-aminobutyric acid cycling and protects the cerebral cortex from apoptosis. © The Author(s) 2016.
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Burn Prevention for Families with Children with Special Needs
... Safety Tips Video Special Needs Burns and Scalds Burn Prevention for Families With Children With Special Needs ... to learn what you need to know about burn prevention if you have a child with special ...
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Geraedts, Caspar L.; Boersma, Kerst Th.
2006-01-01
Although many research studies report students' Lamarckian misconceptions, only a few studies present learning and teaching strategies that focus on the successful development of the concept of natural selection. The learning and teaching strategy for upper secondary students (aged 15-16) presented in this study conducted in The Netherlands is…
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Use of social learning theory in the prevention of obesity with Roma people
Directory of Open Access Journals (Sweden)
Věra Olišarová
2016-12-01
Full Text Available Background: Education is one of the standard components of current nursing care. It is aimed at healthy and diseased and it aims to take responsibility for health. Constantly increasing prevalence of obesity is a global problem. As in the majority population in the Czech Republic and even serious situation of minorities. However, implemented intervention programs and strategies are targeted mainly at the majority population. The concept of social learning theory, however, offers the possibility of integrating previously neglected knowledge as it provides a social context that has a direct impact on the conduct of individuals. Objectives: The aim of this paper is to analyze the problems in the education of the Roma minority and to highlight the possibilities of using the concept of social learning theory in the development of intervention programs aimed at the prevention of overweight and obesity. Methods: This paper is based on data gathered in the implementation of qualitative research, where the research group consists of 25 Roma respondents older than eighteen years of age whose BMI was in the overweight or obese range (ie BMI ≥ 25 kg/m2. Among the respondents were 8 men and 17 women. The paper is also supported by the data obtained in the framework of the grant project aimed, inter alia, to determine the prevalence of these diagnoses among the Roma minority. Results: Culturally conditioned behavior patterns are a significant factor that can influence the effectiveness of implemented interventions. Already during the collection history with these patterns manifest themselves. Among other factors, are body image, social functions of eating, socioeconomic status and related dietary composition. Understanding the relationships between these factors and motivational elements of risk behaviors can go into nursing to bring a new dimension. Conclusions: Ethnicity is often a significant factor that affects the effectiveness of
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Transfer Learning with Convolutional Neural Networks for SAR Ship Recognition
Zhang, Di; Liu, Jia; Heng, Wang; Ren, Kaijun; Song, Junqiang
2018-03-01
Ship recognition is the backbone of marine surveillance systems. Recent deep learning methods, e.g. Convolutional Neural Networks (CNNs), have shown high performance for optical images. Learning CNNs, however, requires a number of annotated samples to estimate numerous model parameters, which prevents its application to Synthetic Aperture Radar (SAR) images due to the limited annotated training samples. Transfer learning has been a promising technique for applications with limited data. To this end, a novel SAR ship recognition method based on CNNs with transfer learning has been developed. In this work, we firstly start with a CNNs model that has been trained in advance on Moving and Stationary Target Acquisition and Recognition (MSTAR) database. Next, based on the knowledge gained from this image recognition task, we fine-tune the CNNs on a new task to recognize three types of ships in the OpenSARShip database. The experimental results show that our proposed approach can obviously increase the recognition rate comparing with the result of merely applying CNNs. In addition, compared to existing methods, the proposed method proves to be very competitive and can learn discriminative features directly from training data instead of requiring pre-specification or pre-selection manually.
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Directory of Open Access Journals (Sweden)
Virginia Songalia Sobremisana
2017-11-01
Full Text Available This research was focused on the development and evaluation of physics innovative device in enhancing students’ motivation and performance in learning selected concepts in physics. The Physics innovative device was developed based upon research on student difficulties in learning relevant concepts in physics and their attitudes toward the subject. Basic concepts in mechanics were also made as baselines in the development of the locally-produced Physics innovative learning device. Such learning devices are valuable resources when used either in lecture or demonstration classes. The developmental, descriptive and quasi-experimental research methods were utilized to determine the effectiveness, in terms of motivation and performance, of the innovative device in Physics. The instruments used for the data collection were the Instructional Materials Motivational Scale (IMMS developed by Keller and the students’ performance test. Pretest and posttest mean scores were measured to determine if there is a mean gain score difference between the experimental and control groups. The study revealed that the group taught with the Physics innovative device performed significantly better than those taught in the traditional method and also the use of Physics innovative device generally improved students’ understanding of concepts and led to higher academic achievements. Analysis of the students’ level of motivation showed that their interests were captured, the instructions they received were relevant to their personal goals and motives, their confidence to learn on their own were build-up, and learning for them was rewarding and important. In the four dimensions (ARCS of IMMS students were found to be attentive, confident, and in agreement in using the fun-learning tool having realize its applicability and relevance in learning their Physics lessons. Results of the study disclosed students and teachers consider the novel device acceptable because it is
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Matsumoto, Shokei; Jung, Kyoungwon; Smith, Alan; Coimbra, Raul
2018-06-23
To establish the preventable and potentially preventable death rates in a mature trauma center and to identify the causes of death and highlight the lessons learned from these cases. We analyzed data from a Level-1 Trauma Center Registry, collected over a 15-year period. Data on demographics, timing of death, and potential errors were collected. Deaths were judged as preventable (PD), potentially preventable (PPD), or non-preventable (NPD), following a strict external peer-review process. During the 15-year period, there were 874 deaths, 15 (1.7%) and 6 (0.7%) of which were considered PPDs and PDs, respectively. Patients in the PD and PPD groups were not sicker and had less severe head injury than those in the NPD group. The time-death distribution differed according to preventability. We identified 21 errors in the PD and PPD groups, but only 61 (7.3%) errors in the NPD group (n = 853). Errors in judgement accounted for the majority and for 90.5% of the PD and PPD group errors. Although the numbers of PDs and PPDs were low, denoting maturity of our trauma center, there are important lessons to be learned about how errors in judgment led to deaths that could have been prevented.
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Selecting practice management information systems.
Worley, R; Ciotti, V
1997-01-01
Despite enormous advances in information systems, the process by which most medical practices select them has remained virtually unchanged for decades: the request for proposal (RFP). Unfortunately, vendors have learned ways to minimize the value of RFP checklists to where purchasers now learn little about the system functionality. The authors describe a selection methodology that replaces the RFP with scored demos, reviews of vendor user manuals and mathematically structured reference checking. In a recent selection process at a major medical center, these techniques yielded greater user buy-in and favorable contract terms as well.
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Alzheimer's Prevention Education: If We Build It, Will They Come? www.AlzU.org.
Isaacson, R S; Haynes, N; Seifan, A; Larsen, D; Christiansen, S; Berger, J C; Safdieh, J E; Lunde, A M; Luo, A; Kramps, M; McInnis, M; Ochner, C N
2014-01-01
Internet-based educational interventions may be useful for impacting knowledge and behavioral change. However, in AD prevention, little data exists about which educational tools work best in terms of learning and interest in participating in clinical trials. Primary: Assess effectiveness of interactive webinars vs. written blog-posts on AD prevention learning. Secondary: Evaluate the effect of AD prevention education on interest in participating in clinical trials; Assess usability of, and user perceptions about, an online AD education research platform; Classify target populations (demographics, learning needs, interests). Observational. Online. Men/Women, aged 25+, recruited via facebook.com. Alzheimer's Universe (www.AlzU.org) education research platform. Pre/post-test performance, self-reported Likert-scale ratings, completion rates. Over two-weeks, 4268 visits were generated. 503 signed-up for a user account (11.8% join rate), 196 participated in the lessons (39.0%) and 100 completed all beta-testing steps (19.9%). Users randomized to webinar instruction about AD prevention and the stages of AD demonstrated significant increases (p=0.01) in pre vs. post-testing scores compared to blog-post intervention. Upon joining, 42% were interested in participating in a clinical trial in AD prevention. After completing all beta-test activities, interest increased to 86%. Users were primarily women and the largest category was children of AD patients. 66.3% joined to learn more about AD prevention, 65.3% to learn more about AD treatment. Webinar-based education led to significant improvements in learning about AD prevention and the stages of AD. AlzU.org participation more than doubled interest in AD prevention clinical trial participation. Subjects were quickly and cost-effectively recruited, and highly satisfied with the AD education research platform. Based on these data, we will further refine AlzU.org prior to public launch and aim to study the effectiveness of 25
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Fast algorithm selection using learning curves
Rijn, van J.N.; Abdulrahman, S.M.; Brazdil, P.; Vanschoren, J.; Fromont, E.; De Bie, T.; Leeuwen, van M.
2015-01-01
One of the challenges in Machine Learning to find a classifier and parameter settings that work well on a given dataset. Evaluating all possible combinations typically takes too much time, hence many solutions have been proposed that attempt to predict which classifiers are most promising to try. As
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Crucial elements in suicide prevention strategies
DEFF Research Database (Denmark)
Nordentoft, Merete
2011-01-01
; selective interventions are directed toward individuals who are at greater risk for suicidal behaviour; and indicated preventions are targeted at individuals who have already begun self-destructive behaviour. On the universal prevention level, an overview of the literature is presented with focus...... on restrictions in firearms and carbon monoxide gas. At the selective prevention level, a review of risk of suicide in homelessness and schizophrenia and risk factors for suicide in schizophrenia is conducted and possible interventions are mentioned together with the evidence for their effect. Suicide rate...
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Determination and prioritizing of addiction prevention factors in delfan city, iran.
Mirzaei, Davod; Zamani, Bibi Eshrat; Mousavi, Sayyed Hojat
2011-01-01
In recent decades, drug abuse has been one of the most important problems of human societies and has been imposing enormous charges to them. Exposing addicts to infectious diseases, social and economic harmful impacts, expensive and reversibility of treatment methods have caused that drug abuse prevention programs be more inexpensive and more effective than treatment. One of the most important methods of drug abuse prevention is identification and prioritization of them according to scientific methods. The purpose of this study was to investigate addiction prevention methods among adolescents and teenagers from the viewpoints of addicts, their parents, authorities and prioritizing the prevention methods based on analytical hierarchy process (AHP) model in Delfan city, Iran. Statistical samples included 17 authorities, 42 addicts, and 23 parents that have been selected through purposive sampling. Data collection instruments involved structured and semi-structured interviews. Data were analyzed based on quantitative and qualitative methods, encoding and categorization. In this study, AHP model was used for prioritizing the prevention methods. This model is one of the most efficient and comprehensive designed techniques for multi-criteria decision making; it formulates the possibility of natural complex problems as hierarchy. The results indicated that the most important methods of drug abuse prevention were using media, case studies, planning for leisure times, educating social skills, integrating drug prevention methods in religious customs and respect to teenagers. Among these factors, the media and respect to adolescents with weights 0.3321 and 0.2389 had the highest preferences for the prevention of drug addiction, respectively. Planning for leisure time with weight of 0.1349 had the lowest importance than media and teenager respectful factor and higher priority than religion customs, dating and learning lessons factors. On the contrary, integrating in religion
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Ghoncheh, R.; Kerkhof, A.J.F.M.; Koot, H.M.
2014-01-01
Background: Providing e-learning modules can be an effective strategy for enhancing gatekeepers' knowledge, self-confidence and skills in adolescent suicide prevention. The aim of this study was to test the effectiveness of an online training program called Mental Health Online which consists of
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2008-01-01
This study is aimed at providing the reader with a detailed description of the readiness of teachers to integrate Information and Communication Technology (ICT) for learning in a selected school in the GautengOnline (GoL) Project, through qualitative research design that used various data collecting methods: Questionnaire, observations and interview. A large number of teachers showed some interest in using ICT learning but had difficulties on how to get started due to the lack of suitable ICT...
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CDC Vital Signs-Preventing Melanoma
Centers for Disease Control (CDC) Podcasts
2015-06-02
This podcast is based on the June 2015 CDC Vital Signs report. Skin cancer is the most common form of cancer in the U.S. In 2011, there were more than 65,000 cases of melanoma, the most deadly form of skin cancer. Learn how everyone can help prevent skin cancer. Created: 6/2/2015 by National Center for Chronic Disease Prevention and Health Promotion (NCCDPHP). Date Released: 6/2/2015.
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Analysis of industrial pollution prevention programs in selected Asian countries
Energy Technology Data Exchange (ETDEWEB)
Chiu, S.Y. [Argonne National Lab., IL (United States). Environmental Assessment Div.]|[East-West Center, Honolulu, HI (United States)
1995-05-01
Industrialization in developing countries is causing increasing environmental damage. Pollution prevention (P2) is an emerging environmental concept that could help developing countries achieve leapfrog goals, bypassing old and pollutive technologies and minimizing traditional control practices. The current P2 promotion activities in Hong Kong, the Republic of Korea, the Philippines, Singapore, Taiwan, and Thailand are discussed. These programs, generally initiated in the last 5 years, are classified into five categories: awareness promotion, education and training, information transfer, technical assistance, and financial incentives. All important at the early stages of P2 promotion, these programs should inform industries of the benefits of P2 and help them identify applicable P2 measures. Participation in these programs is voluntary. The limited data indicate that adoption of P2 measures in these countries is not yet widespread. Recommendations for expanding P2 promotion activities include (1) strengthening the design and enforcement of environmental regulations; (2) providing P2 training and education to government workers, nongovernmental organizations and labor unions officials, university faculties, and news media; (3) tracking the progress of P2 programs; (4) implementing selected P2 mandatory measures; (5) identifying cleaner production technologies for use in new facilities; (6) implementing special programs for small and medium enterprises; and (7) expanding P2 promotion to other sectors, such as agriculture and transportation, and encouraging green design and green consumerism.
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Canal, Clinton E.; Stutz, Sonja J.; Gold, Paul E.
2005-01-01
The present experiments examined the effects of injecting glucose into the dorsal hippocampus or dorsolateral striatum on learning rates and on strategy selection in rats trained on a T-maze that can be solved by using either a hippocampus-sensitive place or striatum-sensitive response strategy. Percentage strategy selection on a probe trial…
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Burn Prevention for Families with Children with Special Needs
Full Text Available ... Safety Tips Video Special Needs Burns and Scalds Burn Prevention for Families With Children With Special Needs ... to learn what you need to know about burn prevention if you have a child with special ...
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Burn Prevention for Families with Children with Special Needs
Full Text Available ... Tips Video Special Needs Burns and Scalds Burn Prevention for Families With Children With Special Needs Watch ... learn what you need to know about burn prevention if you have a child with special needs. ...
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Learning from prescribing errors
Dean, B
2002-01-01
The importance of learning from medical error has recently received increasing emphasis. This paper focuses on prescribing errors and argues that, while learning from prescribing errors is a laudable goal, there are currently barriers that can prevent this occurring. Learning from errors can take place on an individual level, at a team level, and across an organisation. Barriers to learning from prescribing errors include the non-discovery of many prescribing errors, lack of feedback to th...
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Learning to learn – intrinsic plasticity as a metaplasticity mechanism for memory formation
Sehgal, Megha; Song, Chenghui; Ehlers, Vanessa L.; Moyer, James R.
2013-01-01
“Use it or lose it” is a popular adage often associated with use-dependent enhancement of cognitive abilities. Much research has focused on understanding exactly how the brain changes as a function of experience. Such experience-dependent plasticity involves both structural and functional alterations that contribute to adaptive behaviors, such as learning and memory, as well as maladaptive behaviors, including anxiety disorders, phobias, and posttraumatic stress disorder. With the advancing age of our population, understanding how use-dependent plasticity changes across the lifespan may also help to promote healthy brain aging. A common misconception is that such experience-dependent plasticity (e.g., associative learning) is synonymous with synaptic plasticity. Other forms of plasticity also play a critical role in shaping adaptive changes within the nervous system, including intrinsic plasticity – a change in the intrinsic excitability of a neuron. Intrinsic plasticity can result from a change in the number, distribution or activity of various ion channels located throughout the neuron. Here, we review evidence that intrinsic plasticity is an important and evolutionarily conserved neural correlate of learning. Intrinsic plasticity acts as a metaplasticity mechanism by lowering the threshold for synaptic changes. Thus, learning-related intrinsic changes can facilitate future synaptic plasticity and learning. Such intrinsic changes can impact the allocation of a memory trace within a brain structure, and when compromised, can contribute to cognitive decline during the aging process. This unique role of intrinsic excitability can provide insight into how memories are formed and, more interestingly, how neurons that participate in a memory trace are selected. Most importantly, modulation of intrinsic excitability can allow for regulation of learning ability – this can prevent or provide treatment for cognitive decline not only in patients with clinical
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Deep Learning for Population Genetic Inference.
Sheehan, Sara; Song, Yun S
2016-03-01
Given genomic variation data from multiple individuals, computing the likelihood of complex population genetic models is often infeasible. To circumvent this problem, we introduce a novel likelihood-free inference framework by applying deep learning, a powerful modern technique in machine learning. Deep learning makes use of multilayer neural networks to learn a feature-based function from the input (e.g., hundreds of correlated summary statistics of data) to the output (e.g., population genetic parameters of interest). We demonstrate that deep learning can be effectively employed for population genetic inference and learning informative features of data. As a concrete application, we focus on the challenging problem of jointly inferring natural selection and demography (in the form of a population size change history). Our method is able to separate the global nature of demography from the local nature of selection, without sequential steps for these two factors. Studying demography and selection jointly is motivated by Drosophila, where pervasive selection confounds demographic analysis. We apply our method to 197 African Drosophila melanogaster genomes from Zambia to infer both their overall demography, and regions of their genome under selection. We find many regions of the genome that have experienced hard sweeps, and fewer under selection on standing variation (soft sweep) or balancing selection. Interestingly, we find that soft sweeps and balancing selection occur more frequently closer to the centromere of each chromosome. In addition, our demographic inference suggests that previously estimated bottlenecks for African Drosophila melanogaster are too extreme.
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Marques, Yuri Bento; de Paiva Oliveira, Alcione; Ribeiro Vasconcelos, Ana Tereza; Cerqueira, Fabio Ribeiro
2016-12-15
MicroRNAs (miRNAs) are key gene expression regulators in plants and animals. Therefore, miRNAs are involved in several biological processes, making the study of these molecules one of the most relevant topics of molecular biology nowadays. However, characterizing miRNAs in vivo is still a complex task. As a consequence, in silico methods have been developed to predict miRNA loci. A common ab initio strategy to find miRNAs in genomic data is to search for sequences that can fold into the typical hairpin structure of miRNA precursors (pre-miRNAs). The current ab initio approaches, however, have selectivity issues, i.e., a high number of false positives is reported, which can lead to laborious and costly attempts to provide biological validation. This study presents an extension of the ab initio method miRNAFold, with the aim of improving selectivity through machine learning techniques, namely, random forest combined with the SMOTE procedure that copes with imbalance datasets. By comparing our method, termed Mirnacle, with other important approaches in the literature, we demonstrate that Mirnacle substantially improves selectivity without compromising sensitivity. For the three datasets used in our experiments, our method achieved at least 97% of sensitivity and could deliver a two-fold, 20-fold, and 6-fold increase in selectivity, respectively, compared with the best results of current computational tools. The extension of miRNAFold by the introduction of machine learning techniques, significantly increases selectivity in pre-miRNA ab initio prediction, which optimally contributes to advanced studies on miRNAs, as the need of biological validations is diminished. Hopefully, new research, such as studies of severe diseases caused by miRNA malfunction, will benefit from the proposed computational tool.
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Zhongqin, G.; Chen, Y.
2017-12-01
Abstract Quickly identify the spatial distribution of landslides automatically is essential for the prevention, mitigation and assessment of the landslide hazard. It's still a challenging job owing to the complicated characteristics and vague boundary of the landslide areas on the image. The high resolution remote sensing image has multi-scales, complex spatial distribution and abundant features, the object-oriented image classification methods can make full use of the above information and thus effectively detect the landslides after the hazard happened. In this research we present a new semi-supervised workflow, taking advantages of recent object-oriented image analysis and machine learning algorithms to quick locate the different origins of landslides of some areas on the southwest part of China. Besides a sequence of image segmentation, feature selection, object classification and error test, this workflow ensemble the feature selection and classifier selection. The feature this study utilized were normalized difference vegetation index (NDVI) change, textural feature derived from the gray level co-occurrence matrices (GLCM), spectral feature and etc. The improvement of this study shows this algorithm significantly removes some redundant feature and the classifiers get fully used. All these improvements lead to a higher accuracy on the determination of the shape of landslides on the high resolution remote sensing image, in particular the flexibility aimed at different kinds of landslides.
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Sensorimotor learning biases choice behavior: a learning neural field model for decision making.
Directory of Open Access Journals (Sweden)
Christian Klaes
Full Text Available According to a prominent view of sensorimotor processing in primates, selection and specification of possible actions are not sequential operations. Rather, a decision for an action emerges from competition between different movement plans, which are specified and selected in parallel. For action choices which are based on ambiguous sensory input, the frontoparietal sensorimotor areas are considered part of the common underlying neural substrate for selection and specification of action. These areas have been shown capable of encoding alternative spatial motor goals in parallel during movement planning, and show signatures of competitive value-based selection among these goals. Since the same network is also involved in learning sensorimotor associations, competitive action selection (decision making should not only be driven by the sensory evidence and expected reward in favor of either action, but also by the subject's learning history of different sensorimotor associations. Previous computational models of competitive neural decision making used predefined associations between sensory input and corresponding motor output. Such hard-wiring does not allow modeling of how decisions are influenced by sensorimotor learning or by changing reward contingencies. We present a dynamic neural field model which learns arbitrary sensorimotor associations with a reward-driven Hebbian learning algorithm. We show that the model accurately simulates the dynamics of action selection with different reward contingencies, as observed in monkey cortical recordings, and that it correctly predicted the pattern of choice errors in a control experiment. With our adaptive model we demonstrate how network plasticity, which is required for association learning and adaptation to new reward contingencies, can influence choice behavior. The field model provides an integrated and dynamic account for the operations of sensorimotor integration, working memory and action
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Phonological learning in semantic dementia.
Jefferies, Elizabeth; Bott, Samantha; Ehsan, Sheeba; Lambon Ralph, Matthew A
2011-04-01
Patients with semantic dementia (SD) have anterior temporal lobe (ATL) atrophy that gives rise to a highly selective deterioration of semantic knowledge. Despite pronounced anomia and poor comprehension of words and pictures, SD patients have well-formed, fluent speech and normal digit span. Given the intimate connection between phonological STM and word learning revealed by both neuropsychological and developmental studies, SD patients might be expected to show good acquisition of new phonological forms, even though their ability to map these onto meanings is impaired. In contradiction of these predictions, a limited amount of previous research has found poor learning of new phonological forms in SD. In a series of experiments, we examined whether SD patient, GE, could learn novel phonological sequences and, if so, under which circumstances. GE showed normal benefits of phonological knowledge in STM (i.e., normal phonotactic frequency and phonological similarity effects) but reduced support from semantic memory (i.e., poor immediate serial recall for semantically degraded words, characterised by frequent item errors). Next, we demonstrated normal learning of serial order information for repeated lists of single-digit number words using the Hebb paradigm: these items were well-understood allowing them to be repeated without frequent item errors. In contrast, patient GE showed little learning of nonsense syllable sequences using the same Hebb paradigm. Detailed analysis revealed that both GE and the controls showed a tendency to learn their own errors as opposed to the target items. Finally, we showed normal learning of phonological sequences for GE when he was prevented from repeating his errors. These findings confirm that the ATL atrophy in SD disrupts phonological processing for semantically degraded words but leaves the phonological architecture intact. Consequently, when item errors are minimised, phonological STM can support the acquisition of new phoneme
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Organizing knowledge for tutoring fire loss prevention
Daniel L. Schmoldt
1989-01-01
The San Bernardino National Forest in southern California has recently developed a systematic approach to wildfire prevention planning. However, a comprehensive document or other mechanism for teaching this process to other prevention personnel does not exist. An intelligent tutorial expert system is being constructed to provide a means for learning the process and to...
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Parental prey selection affects risk-taking behaviour and spatial learning in avian offspring.
Arnold, Kathryn E; Ramsay, Scot L; Donaldson, Christine; Adam, Aileen
2007-10-22
Early nutrition shapes life history. Parents should, therefore, provide a diet that will optimize the nutrient intake of their offspring. In a number of passerines, there is an often observed, but unexplained, peak in spider provisioning during chick development. We show that the proportion of spiders in the diet of nestling blue tits, Cyanistes caeruleus, varies significantly with the age of chicks but is unrelated to the timing of breeding or spider availability. Moreover, this parental prey selection supplies nestlings with high levels of taurine particularly at younger ages. This amino acid is known to be both vital and limiting for mammalian development and consequently found in high concentrations in placenta and milk. Based on the known roles of taurine in mammalian brain development and function, we then asked whether by supplying taurine-rich spiders, avian parents influence the stress responsiveness and cognitive function of their offspring. To test this, we provided wild blue tit nestlings with either a taurine supplement or control treatment once daily from the ages of 2-14 days. Then pairs of size- and sex-matched siblings were brought into captivity for behavioural testing. We found that juveniles that had received additional taurine as neonates took significantly greater risks when investigating novel objects than controls. Taurine birds were also more successful at a spatial learning task than controls. Additionally, those individuals that succeeded at a spatial learning task had shown intermediate levels of risk taking. Non-learners were generally very risk-averse controls. Early diet therefore has downstream impacts on behavioural characteristics that could affect fitness via foraging and competitive performance. Fine-scale prey selection is a mechanism by which parents can manipulate the behavioural phenotype of offspring.
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Adams, Kenneth Mark
The purpose of this research was to investigate the relationship between the learning style perceptual preferences of fourth grade urban students and the attainment of selected physical science concepts for three simple machines as taught using learning cycle methodology. The sample included all fourth grade children from one urban elementary school (N = 91). The research design followed a quasi-experimental format with a single group, equivalent teacher demonstration and student investigation materials, and identical learning cycle instructional treatment. All subjects completed the Understanding Simple Machines Test (USMT) prior to instructional treatment, and at the conclusion of treatment to measure student concept attainment related to the pendulum, the lever and fulcrum, and the inclined plane. USMT pre and post-test scores, California Achievement Test (CAT-5) percentile scores, and Learning Style Inventory (LSI) standard scores for four perceptual elements for each subject were held in a double blind until completion of the USMT post-test. The hypothesis tested in this study was: Learning style perceptual preferences of fourth grade students as measured by the Dunn, Dunn, and Price Learning Style Inventory (LSI) are significant predictors of success in the acquisition of physical science concepts taught through use of the learning cycle. Analysis of pre and post USMT scores, 18.18 and 30.20 respectively, yielded a significant mean gain of +12.02. A controlled stepwise regression was employed to identify significant predictors of success on the USMT post-test from among USMT pre-test, four CAT-5 percentile scores, and four LSI perceptual standard scores. The CAT -5 Total Math and Total Reading accounted for 64.06% of the variance in the USMT post-test score. The only perceptual element to act as a significant predictor was the Kinesthetic standard score, accounting for 1.72% of the variance. The study revealed that learning cycle instruction does not appear
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Storer, Heather L.; Casey, Erin A.; Carlson, Juliana; Edleson, Jeffrey L.; Tolman, Richard M.
2014-01-01
Engaging men in addressing violence against women (VAW) has become a strategy in the global prevention of gender-based violence. Concurrently, Western public health frameworks have been utilized to guide prevention agendas worldwide. Using qualitative methods, this study describes how global anti-violence organizations that partner with men conceptualize primary prevention in their work. Findings suggest that ‘primary prevention’ is not a fixed term in the context of VAW and that front-line prevention work challenges rigidly delineated distinctions between levels of prevention. Much can be learned from global organizations’ unique and contextualized approaches to the prevention of VAW. PMID:26333283
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Ultsch, Alfred; Kringel, Dario; Kalso, Eija; Mogil, Jeffrey S; Lötsch, Jörn
2016-12-01
The increasing availability of "big data" enables novel research approaches to chronic pain while also requiring novel techniques for data mining and knowledge discovery. We used machine learning to combine the knowledge about n = 535 genes identified empirically as relevant to pain with the knowledge about the functions of thousands of genes. Starting from an accepted description of chronic pain as displaying systemic features described by the terms "learning" and "neuronal plasticity," a functional genomics analysis proposed that among the functions of the 535 "pain genes," the biological processes "learning or memory" (P = 8.6 × 10) and "nervous system development" (P = 2.4 × 10) are statistically significantly overrepresented as compared with the annotations to these processes expected by chance. After establishing that the hypothesized biological processes were among important functional genomics features of pain, a subset of n = 34 pain genes were found to be annotated with both Gene Ontology terms. Published empirical evidence supporting their involvement in chronic pain was identified for almost all these genes, including 1 gene identified in March 2016 as being involved in pain. By contrast, such evidence was virtually absent in a randomly selected set of 34 other human genes. Hence, the present computational functional genomics-based method can be used for candidate gene selection, providing an alternative to established methods.
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2013-01-01
Background Machine learning techniques are becoming useful as an alternative approach to conventional medical diagnosis or prognosis as they are good for handling noisy and incomplete data, and significant results can be attained despite a small sample size. Traditionally, clinicians make prognostic decisions based on clinicopathologic markers. However, it is not easy for the most skilful clinician to come out with an accurate prognosis by using these markers alone. Thus, there is a need to use genomic markers to improve the accuracy of prognosis. The main aim of this research is to apply a hybrid of feature selection and machine learning methods in oral cancer prognosis based on the parameters of the correlation of clinicopathologic and genomic markers. Results In the first stage of this research, five feature selection methods have been proposed and experimented on the oral cancer prognosis dataset. In the second stage, the model with the features selected from each feature selection methods are tested on the proposed classifiers. Four types of classifiers are chosen; these are namely, ANFIS, artificial neural network, support vector machine and logistic regression. A k-fold cross-validation is implemented on all types of classifiers due to the small sample size. The hybrid model of ReliefF-GA-ANFIS with 3-input features of drink, invasion and p63 achieved the best accuracy (accuracy = 93.81%; AUC = 0.90) for the oral cancer prognosis. Conclusions The results revealed that the prognosis is superior with the presence of both clinicopathologic and genomic markers. The selected features can be investigated further to validate the potential of becoming as significant prognostic signature in the oral cancer studies. PMID:23725313
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Supporting Learning from Illustrated Texts: Conceptualizing and Evaluating a Learning Strategy
Schlag, Sabine; Ploetzner, Rolf
2011-01-01
Texts and pictures are often combined in order to improve learning. Many students, however, have difficulty to appropriately process text-picture combinations. We have thus conceptualized a learning strategy which supports learning from illustrated texts. By inducing the processes of information selection, organization, integration, and…
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Storer, Heather L; Casey, Erin A; Carlson, Juliana; Edleson, Jeffrey L; Tolman, Richard M
2016-02-01
Engaging men in addressing violence against women (VAW) has become a strategy in the global prevention of gender-based violence. Concurrently, Western public health frameworks have been utilized to guide prevention agendas worldwide. Using qualitative methods, this study describes how global anti-violence organizations that partner with men conceptualize primary prevention in their work. Findings suggest that "primary prevention" is not a fixed term in the context of VAW and that front-line prevention work challenges rigidly delineated distinctions between levels of prevention. Much can be learned from global organizations' unique and contextualized approaches to the prevention of VAW. © The Author(s) 2015.
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Deep Learning for Population Genetic Inference.
Directory of Open Access Journals (Sweden)
Sara Sheehan
2016-03-01
Full Text Available Given genomic variation data from multiple individuals, computing the likelihood of complex population genetic models is often infeasible. To circumvent this problem, we introduce a novel likelihood-free inference framework by applying deep learning, a powerful modern technique in machine learning. Deep learning makes use of multilayer neural networks to learn a feature-based function from the input (e.g., hundreds of correlated summary statistics of data to the output (e.g., population genetic parameters of interest. We demonstrate that deep learning can be effectively employed for population genetic inference and learning informative features of data. As a concrete application, we focus on the challenging problem of jointly inferring natural selection and demography (in the form of a population size change history. Our method is able to separate the global nature of demography from the local nature of selection, without sequential steps for these two factors. Studying demography and selection jointly is motivated by Drosophila, where pervasive selection confounds demographic analysis. We apply our method to 197 African Drosophila melanogaster genomes from Zambia to infer both their overall demography, and regions of their genome under selection. We find many regions of the genome that have experienced hard sweeps, and fewer under selection on standing variation (soft sweep or balancing selection. Interestingly, we find that soft sweeps and balancing selection occur more frequently closer to the centromere of each chromosome. In addition, our demographic inference suggests that previously estimated bottlenecks for African Drosophila melanogaster are too extreme.
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Deep Learning for Population Genetic Inference
Sheehan, Sara; Song, Yun S.
2016-01-01
Given genomic variation data from multiple individuals, computing the likelihood of complex population genetic models is often infeasible. To circumvent this problem, we introduce a novel likelihood-free inference framework by applying deep learning, a powerful modern technique in machine learning. Deep learning makes use of multilayer neural networks to learn a feature-based function from the input (e.g., hundreds of correlated summary statistics of data) to the output (e.g., population genetic parameters of interest). We demonstrate that deep learning can be effectively employed for population genetic inference and learning informative features of data. As a concrete application, we focus on the challenging problem of jointly inferring natural selection and demography (in the form of a population size change history). Our method is able to separate the global nature of demography from the local nature of selection, without sequential steps for these two factors. Studying demography and selection jointly is motivated by Drosophila, where pervasive selection confounds demographic analysis. We apply our method to 197 African Drosophila melanogaster genomes from Zambia to infer both their overall demography, and regions of their genome under selection. We find many regions of the genome that have experienced hard sweeps, and fewer under selection on standing variation (soft sweep) or balancing selection. Interestingly, we find that soft sweeps and balancing selection occur more frequently closer to the centromere of each chromosome. In addition, our demographic inference suggests that previously estimated bottlenecks for African Drosophila melanogaster are too extreme. PMID:27018908
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Blockchain learning: can crypto-currency methods be appropriated to enhance online learning?
Devine, Peter
2015-01-01
Blockchain is a distributed database that maintains a dynamic list of data records, hardened to prevent tampering and revision. It is the framework for cryptocurrencies like Bitcoin.\\ud \\ud A Blockchain learning tool would provide a secure and verifiable learning transaction ledger. Its decentralised nature would ensure a learner, rather than institution-centred record of achievements that would be difficult to tamper with, enabling parties, such as employers or learning institutions, to revi...
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Prediction of selective estrogen receptor beta agonist using open data and machine learning approach
Directory of Open Access Journals (Sweden)
Niu AQ
2016-07-01
Full Text Available Ai-qin Niu,1 Liang-jun Xie,2 Hui Wang,1 Bing Zhu,1 Sheng-qi Wang3 1Department of Gynecology, the First People’s Hospital of Shangqiu, Shangqiu, Henan, People’s Republic of China; 2Department of Image Diagnoses, the Third Hospital of Jinan, Jinan, Shandong, People’s Republic of China; 3Department of Mammary Disease, Guangdong Provincial Hospital of Chinese Medicine, the Second Clinical College of Guangzhou University of Chinese Medicine, Guangzhou, People’s Republic of China Background: Estrogen receptors (ERs are nuclear transcription factors that are involved in the regulation of many complex physiological processes in humans. ERs have been validated as important drug targets for the treatment of various diseases, including breast cancer, ovarian cancer, osteoporosis, and cardiovascular disease. ERs have two subtypes, ER-α and ER-β. Emerging data suggest that the development of subtype-selective ligands that specifically target ER-β could be a more optimal approach to elicit beneficial estrogen-like activities and reduce side effects. Methods: Herein, we focused on ER-β and developed its in silico quantitative structure-activity relationship models using machine learning (ML methods. Results: The chemical structures and ER-β bioactivity data were extracted from public chemogenomics databases. Four types of popular fingerprint generation methods including MACCS fingerprint, PubChem fingerprint, 2D atom pairs, and Chemistry Development Kit extended fingerprint were used as descriptors. Four ML methods including Naïve Bayesian classifier, k-nearest neighbor, random forest, and support vector machine were used to train the models. The range of classification accuracies was 77.10% to 88.34%, and the range of area under the ROC (receiver operating characteristic curve values was 0.8151 to 0.9475, evaluated by the 5-fold cross-validation. Comparison analysis suggests that both the random forest and the support vector machine are superior
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Speeding the growth of primary mental health prevention
Wissow, Lawrence S
2015-01-01
While there is a strong case for primary prevention of mental health problems, relatively little mental health scholarship has been devoted to it in the last decade. Efforts to accelerate prevention scholarship could potentially benefit from strengthening pathways for interdisciplinary research; developing new training and working models for mental health professionals; developing a common language for public, policy, and scientific discussion of prevention; learning how to measure the common...
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Directory of Open Access Journals (Sweden)
Sandrine Rossi
Full Text Available Reasoners make systematic logical errors by giving heuristic responses that reflect deviations from the logical norm. Influential studies have suggested first that our reasoning is often biased because we minimize cognitive effort to surpass a cognitive conflict between heuristic response from system 1 and analytic response from system 2 thinking. Additionally, cognitive control processes might be necessary to inhibit system 1 responses to activate a system 2 response. Previous studies have shown a significant effect of executive learning (EL on adults who have transferred knowledge acquired on the Wason selection task (WST to another isomorphic task, the rule falsification task (RFT. The original paradigm consisted of teaching participants to inhibit a classical matching heuristic that sufficed the first problem and led to significant EL transfer on the second problem. Interestingly, the reasoning tasks differed in inhibiting-heuristic metacognitive cost. Success on the WST requires half-suppression of the matching elements. In contrast, the RFT necessitates a global rejection of the matching elements for a correct answer. Therefore, metacognitive learning difficulty most likely differs depending on whether one uses the first or second task during the learning phase. We aimed to investigate this difficulty and various matching-bias inhibition effects in a new (reversed paradigm. In this case, the transfer effect from the RFT to the WST could be more difficult because the reasoner learns to reject all matching elements in the first task. We observed that the EL leads to a significant reduction in matching selections on the WST without increasing logical performances. Interestingly, the acquired metacognitive knowledge was too "strictly" transferred and discouraged matching rather than encouraging logic. This finding underlines the complexity of learning transfer and adds new evidence to the pedagogy of reasoning.
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Rossi, Sandrine; Cassotti, Mathieu; Moutier, Sylvain; Delcroix, Nicolas; Houdé, Olivier
2015-01-01
Reasoners make systematic logical errors by giving heuristic responses that reflect deviations from the logical norm. Influential studies have suggested first that our reasoning is often biased because we minimize cognitive effort to surpass a cognitive conflict between heuristic response from system 1 and analytic response from system 2 thinking. Additionally, cognitive control processes might be necessary to inhibit system 1 responses to activate a system 2 response. Previous studies have shown a significant effect of executive learning (EL) on adults who have transferred knowledge acquired on the Wason selection task (WST) to another isomorphic task, the rule falsification task (RFT). The original paradigm consisted of teaching participants to inhibit a classical matching heuristic that sufficed the first problem and led to significant EL transfer on the second problem. Interestingly, the reasoning tasks differed in inhibiting-heuristic metacognitive cost. Success on the WST requires half-suppression of the matching elements. In contrast, the RFT necessitates a global rejection of the matching elements for a correct answer. Therefore, metacognitive learning difficulty most likely differs depending on whether one uses the first or second task during the learning phase. We aimed to investigate this difficulty and various matching-bias inhibition effects in a new (reversed) paradigm. In this case, the transfer effect from the RFT to the WST could be more difficult because the reasoner learns to reject all matching elements in the first task. We observed that the EL leads to a significant reduction in matching selections on the WST without increasing logical performances. Interestingly, the acquired metacognitive knowledge was too "strictly" transferred and discouraged matching rather than encouraging logic. This finding underlines the complexity of learning transfer and adds new evidence to the pedagogy of reasoning.
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DEFF Research Database (Denmark)
Warring, Niels
2005-01-01
In November 2004 the Research Consortium on workplace learning under Learning Lab Denmark arranged the international conference “Workplace Learning – from the learner’s perspective”. The conference’s aim was to bring together researchers from different countries and institutions to explore...... and discuss recent developments in our understanding of workplace and work-related learning. The conference had nearly 100 participants with 59 papers presented, and among these five have been selected for presentation is this Special Issue....
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Directory of Open Access Journals (Sweden)
Gláucia Nolasco de Almeida Mello
2016-12-01
Full Text Available The last fifteen years, in Brazil, the number of engineering freshmen had a huge increased and, although the number of graduated also had increased over the same period, the percentage of engineering freshmen are by far higher than engineers graduated. In this context, there is a clear evidence of the high dropout rate in higher education courses of engineering in Brazil. Once most of developed researches about engineering courses dropout in Brazil are focused in the students and institutions point of view about factors that affect dropout rate, in this research it was investigated the professors perspective to answer the three questions: (1 What are the main factors which prevent success in teaching and learning process identified by professors of engineering during the classes? (2 How can professors to improve the teaching and learning process in higher education courses of engineering in Brazil? (3 How can Higher Education Institutions (HEI support the professors? The research data were collected through team activities developed with 134 professors of higher education courses of engineering. This research reveals that the most important factors that affect negatively the teaching and learning process are related to inadequate high school preparation and behaviour of students. Main suggestions of professors for improving the teaching and learning process and also students' motivation are related to pedagogical aspects such as: use of Information and Communication Technologies (ICTs as support of classes and implementation of professor and student support programs with significant participation of HEI.
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CDC Vital SignsâPreventing Stroke Deaths
Centers for Disease Control (CDC) Podcasts
2017-09-06
This podcast is based on the September 2017 CDC Vital Signs report. Each year, more than 140,000 people die and many survivors face disability. Eighty percent of strokes are preventable. Learn the signs of stroke and how to prevent them. Created: 9/6/2017 by Centers for Disease Control and Prevention (CDC). Date Released: 9/6/2017.
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77 FR 16645 - National Poison Prevention Week, 2012
2012-03-21
... Russian Federation on the Measures for the Further Reduction and Limitation of Strategic Offensive Arms... learning more about how to prevent and respond to poison emergencies. Though we have dramatically reduced... information 24 hours a day, seven days a week at 1-800-222-1222. To encourage Americans to learn more about...
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CREB Selectively Controls Learning-Induced Structural Remodeling of Neurons
Middei, Silvia; Spalloni, Alida; Longone, Patrizia; Pittenger, Christopher; O'Mara, Shane M.; Marie, Helene; Ammassari-Teule, Martine
2012-01-01
The modulation of synaptic strength associated with learning is post-synaptically regulated by changes in density and shape of dendritic spines. The transcription factor CREB (cAMP response element binding protein) is required for memory formation and in vitro dendritic spine rearrangements, but its role in learning-induced remodeling of neurons…
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National Research Council Canada - National Science Library
Halstead, John B
2006-01-01
.... The research uses a combination of statistical learning, feature selection methods, and multivariate statistics to determine the better prediction function approximation with features obtained...
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Directory of Open Access Journals (Sweden)
M Khademi
2015-08-01
Full Text Available The aim of this study was to investigate the effect of learned optimism on achievement motivation and academic resilience in female adolescents. This study was a quasi design, pre- and post-test control group and the subjects were selected among adolescents who were members of the Center for Intellectual Development of Children and Adolescents in Isfahan. These subjects selected by randomly style and divided into two experimental and control groups. They were 20 female adolescents aged between 13 to 15 years. The experimental group received optimism training in 7 sessions. Measuring tools were Hermance Achievement motivation questionnaire and Samuel’s academic resilience questionnaire. Data were analyzed by multivariate analysis of covariance (MANCOVA. The results showed that learned optimism had a significant effect on achievement motivation and it’s subscales (confidence and perseverance but it had no effect on other subscales (foresight and hard working. As well as learned optimism had no effect on academic resilience and it’s subscales (communication skills, orientation for the future, orientation for the problem-based. Based on these results focus on emotional and optimism in educational system leads to increase motivation in students and prevent failure and school drop.
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Benjaminse, Anne; Otten, Bert; Gokeler, Alli; Diercks, Ron L; Lemmink, Koen A P M
2017-08-01
Adding external focus of attention (EF, focus on the movement effect) may optimize current anterior cruciate ligament (ACL) injury prevention programmes. The purpose of the current study was to investigate the effects of an EF, by a visual stimulus and an internal focus, by a verbal stimulus during unexpected sidestep cutting in female and male athletes and how these effects remained over time. Ninety experienced basketball athletes performed sidestep cutting manoeuvres in three sessions (S1, S2 and S3). In this randomized controlled trial, athletes were allocated to three groups: visual (VIS), verbal (VER) and control (CTRL). Kinematics and kinetics were collected at the time of peak knee frontal plane moment. Males in the VIS group showed a larger vertical ground reaction force (S1: 25.4 ± 3.1 N/kg, S2: 25.8 ± 2.9 N/kg, S3: 25.2 ± 3.2 N/kg) and knee flexion moments (S1: -3.8 ± 0.9 Nm/kg, S2: -4.0 ± 1.2 Nm/kg, S3: -3.9 ± 1.3 Nm/kg) compared to the males in the VER and CTRL groups and to the females in the VIS group (p knee valgus moment and the females in the VER group reduced knee varus moment over time (n.s.). Male subjects clearly benefit from visual feedback. Females may need different feedback modes to learn a correct movement pattern. Sex-specific learning preferences may have to be acknowledged in day by day practice. Adding video instruction or feedback to regular training regimens when teaching athletes safe movement patterns and providing individual feedback might target suboptimal long-term results and optimize ACL injury prevention programmes. I.
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Active Learning Not Associated with Student Learning in a Random Sample of College Biology Courses
Andrews, T. M.; Leonard, M. J.; Colgrove, C. A.; Kalinowski, S. T.
2011-01-01
Previous research has suggested that adding active learning to traditional college science lectures substantially improves student learning. However, this research predominantly studied courses taught by science education researchers, who are likely to have exceptional teaching expertise. The present study investigated introductory biology courses randomly selected from a list of prominent colleges and universities to include instructors representing a broader population. We examined the relationship between active learning and student learning in the subject area of natural selection. We found no association between student learning gains and the use of active-learning instruction. Although active learning has the potential to substantially improve student learning, this research suggests that active learning, as used by typical college biology instructors, is not associated with greater learning gains. We contend that most instructors lack the rich and nuanced understanding of teaching and learning that science education researchers have developed. Therefore, active learning as designed and implemented by typical college biology instructors may superficially resemble active learning used by education researchers, but lacks the constructivist elements necessary for improving learning. PMID:22135373
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Can prevention classification be improved by considering the function of prevention?
Foxcroft, David R
2014-12-01
Universal, selective and indicated forms of prevention have been adopted as improvements on previous notions of primary and secondary prevention. However, some conceptual confusion remains concerning the placing of environmental, community-based or mass media preventive interventions within this typology. It is suggested that a new dimension of functional types of prevention, namely environmental, developmental and informational prevention should be specified alongside the forms of prevention in a taxonomy matrix. The main advantage of this new taxonomy is that a matrix combining the form and function dimensions of prevention can be used to identify and map out prevention strategies, to consider where research evidence is present and where more is needed, and to evaluate the relative effectiveness of different categories and components of prevention for specific health and social issues. Such evaluations would provide empirical evidence as to whether the different categories of prevention are related to outcomes or processes of prevention in ways that suggest the value of the taxonomy for understanding and increasing the impact of prevention science. This new prevention taxonomy has been useful for conceptualising and planning prevention activities in a case study involving the Swedish National Institute for Public Health. Future work should assess (1) the robustness of this new taxonomy and (2) the theoretical and empirical basis for profiling prevention investments across the various forms and functions of prevention.
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Learning through Teaching: A Microbiology Service-Learning Experience
Directory of Open Access Journals (Sweden)
Ginny Webb
2015-11-01
Full Text Available Service learning is defined as a strategy in which students apply what they have learned in the classroom to a community service project. Many educators would agree that students often learn best through teaching others. This premise was the motivation for a new service-learning project in which undergraduate microbiology students developed and taught hands-on microbiology lessons to local elementary school children. The lessons included teaching basic information about microbes, disease transmission, antibiotics, vaccines, and methods of disease prevention. This service-learning project benefitted the college students by enforcing their knowledge of microbiology and provided them an opportunity to reach out to children within their community. This project also benefitted the local schools by teaching the younger students about microbes, infections, and handwashing. In this paper, I discuss the development and implementation of this new microbiology service-learning project, as well as the observed impact it had on everyone involved.
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Brown, Dikla; Cinamon, Rachel Gali
2016-01-01
The current study focuses on the contribution of five personality traits to the development of self-efficacy and outcome expectations regarding selecting a high school major among adolescents with learning disabilities (LD). Social cognitive career theory and the Big Five personality traits model served as the theoretical framework. Participants…
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Learning: from association to cognition.
Shanks, David R
2010-01-01
Since the very earliest experimental investigations of learning, tension has existed between association-based and cognitive theories. Associationism accounts for the phenomena of both conditioning and "higher" forms of learning via concepts such as excitation, inhibition, and reinforcement, whereas cognitive theories assume that learning depends on hypothesis testing, cognitive models, and propositional reasoning. Cognitive theories have received considerable impetus in regard to both human and animal learning from recent research suggesting that the key illustration of cue selection in learning, blocking, often arises from inferential reasoning. At the same time, a dichotomous view that separates noncognitive, unconscious (implicit) learning from cognitive, conscious (explicit) learning has gained favor. This review selectively describes key findings from this research, evaluates evidence for and against associative and cognitive explanatory constructs, and critically examines both the dichotomous view of learning as well as the claim that learning can occur unconsciously.
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Forsström, J
1992-01-01
The ID3 algorithm for inductive learning was tested using preclassified material for patients suspected to have a thyroid illness. Classification followed a rule-based expert system for the diagnosis of thyroid function. Thus, the knowledge to be learned was limited to the rules existing in the knowledge base of that expert system. The learning capability of the ID3 algorithm was tested with an unselected learning material (with some inherent missing data) and with a selected learning material (no missing data). The selected learning material was a subgroup which formed a part of the unselected learning material. When the number of learning cases was increased, the accuracy of the program improved. When the learning material was large enough, an increase in the learning material did not improve the results further. A better learning result was achieved with the selected learning material not including missing data as compared to unselected learning material. With this material we demonstrate a weakness in the ID3 algorithm: it can not find available information from good example cases if we add poor examples to the data.
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Ayub, Ahmad Fauzi Mohd; Bakar, Kamariah Abu; Ismail, Rohayati
2012-05-01
Information communication Technology (ICT) has been a major influence in the Malaysian Education System, especially in the teaching of mathematics. Since 2003, the Malaysian Ministry of Education has provided incentives to mathematics teacher to motivate them to use ICT using English as the medium of instruction, during the teaching and learning process. However, there are barriers that prevented mathematics teachers from using ICT in the classrooms. This study is to determine factors that influenced the attitudes of Malaysian Mathematic Teachers in integrating ICT in their teaching and learning. One hundred ninety one mathematics teachers were randomly selected for the purpose of this study. The three factors investigated were school support, school facilities and school culture which had been selected to be correlated with teachers' attitudes towards integrating ICT in the teaching and learning of mathematics. Findings showed that significant positive relationships existed between teachers' attitudes toward integrating ICT in the teaching and learning and school support, school facilities and ICT culture and This finding indicated that, in order to develop teachers' attitudes in using ICT during their teaching and learning process, they needed support from the school principals and also their colleagues. Apart from that, school facilities and also ICT culture were also found to be essential.
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van Niekerk, Ashley; Tonsing, Susanne; Seedat, Mohamed; Jacobs, Roxanne; Ratele, Kopano; McClure, Roderick
2015-01-01
Background South Africa has a significant violence problem. The exposure of girls and women to interpersonal violence is widespread, and the victimization of men, especially to severe and homicidal forms of aggression, is of considerable concern, with male homicide eight times the global rate. In the last two decades, there have been a plethora of South African policies to promote safety. However, indications suggest that the policy response to violence is not coherently formulated, comprehensive, or evenly implemented. Objective This study examines selected South African national legislative instruments in terms of their framing and definition of violence and its typology, vulnerable populations, and prevention. Design This study comprises a directed content analysis of selected legislative documents from South African ministries mandated to prevent violence and its consequences or tasked with the prevention of key contributors to violence. Documents were selected using an electronic keyword search method and analyzed independently by two researchers. Results The legislative documents recognized the high levels of violence, confirmed the prioritization of selected vulnerable groups, especially women, children, disabled persons, and rural populations, and above all drew on criminological perspectives to emphasize tertiary prevention interventions. There is a policy focus on the protection and support of victims and the prosecution of perpetrators, but near absent recognition of men as victims. Conclusions There is a need to broaden the policy framework from primarily criminological and prosecutorial perspectives to include public health contributions. It is likewise important to enlarge the conceptions of vulnerability to include men alongside other vulnerable groups. These measures are important for shaping and resourcing prevention decisions and strengthening primary prevention approaches to violence. PMID:26228996
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Directory of Open Access Journals (Sweden)
Ashley van Niekerk
2015-07-01
Full Text Available Background: South Africa has a significant violence problem. The exposure of girls and women to interpersonal violence is widespread, and the victimization of men, especially to severe and homicidal forms of aggression, is of considerable concern, with male homicide eight times the global rate. In the last two decades, there have been a plethora of South African policies to promote safety. However, indications suggest that the policy response to violence is not coherently formulated, comprehensive, or evenly implemented. Objective: This study examines selected South African national legislative instruments in terms of their framing and definition of violence and its typology, vulnerable populations, and prevention. Design: This study comprises a directed content analysis of selected legislative documents from South African ministries mandated to prevent violence and its consequences or tasked with the prevention of key contributors to violence. Documents were selected using an electronic keyword search method and analyzed independently by two researchers. Results: The legislative documents recognized the high levels of violence, confirmed the prioritization of selected vulnerable groups, especially women, children, disabled persons, and rural populations, and above all drew on criminological perspectives to emphasize tertiary prevention interventions. There is a policy focus on the protection and support of victims and the prosecution of perpetrators, but near absent recognition of men as victims. Conclusions: There is a need to broaden the policy framework from primarily criminological and prosecutorial perspectives to include public health contributions. It is likewise important to enlarge the conceptions of vulnerability to include men alongside other vulnerable groups. These measures are important for shaping and resourcing prevention decisions and strengthening primary prevention approaches to violence.
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van Niekerk, Ashley; Tonsing, Susanne; Seedat, Mohamed; Jacobs, Roxanne; Ratele, Kopano; McClure, Roderick
2015-01-01
South Africa has a significant violence problem. The exposure of girls and women to interpersonal violence is widespread, and the victimization of men, especially to severe and homicidal forms of aggression, is of considerable concern, with male homicide eight times the global rate. In the last two decades, there have been a plethora of South African policies to promote safety. However, indications suggest that the policy response to violence is not coherently formulated, comprehensive, or evenly implemented. This study examines selected South African national legislative instruments in terms of their framing and definition of violence and its typology, vulnerable populations, and prevention. This study comprises a directed content analysis of selected legislative documents from South African ministries mandated to prevent violence and its consequences or tasked with the prevention of key contributors to violence. Documents were selected using an electronic keyword search method and analyzed independently by two researchers. The legislative documents recognized the high levels of violence, confirmed the prioritization of selected vulnerable groups, especially women, children, disabled persons, and rural populations, and above all drew on criminological perspectives to emphasize tertiary prevention interventions. There is a policy focus on the protection and support of victims and the prosecution of perpetrators, but near absent recognition of men as victims. There is a need to broaden the policy framework from primarily criminological and prosecutorial perspectives to include public health contributions. It is likewise important to enlarge the conceptions of vulnerability to include men alongside other vulnerable groups. These measures are important for shaping and resourcing prevention decisions and strengthening primary prevention approaches to violence.
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Sexually Transmitted Diseases (STDs) Prevention
... Fact Sheets 中文 (Chinese) Kreyòl (Haitian Creole) Русский (Russian) Tiẽng Viêt (Vietnamese) Prevention Success Stories Provider Pocket ... you protect yourself? What are the treatment options? Learn the answers to these questions by reading the ...
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STRATEGY FOR EVALUATION AND SELECTION OF SYSTEMS FOR ELECTRONIC LEARNING
Dubravka Mandušić; Lucija Blašković
2012-01-01
Today`s technology supported and accelerated learning time requires constant and continuous acquisition of new knowledge. On the other hand, it does not leave enough time for additional education. Increasing number of E-learning systems, withdraws a need for precise evaluation of functionality that those systems provide; so they could be reciprocally compared. While implementing new systems for electronic learning, it is very important to pre-evaluate existing systems in order to ...
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Directory of Open Access Journals (Sweden)
Bröning Sonja
2012-06-01
Full Text Available Abstract Children from substance-affected families show an elevated risk for developing own substance-related or other mental disorders. Therefore, they are an important target group for preventive efforts. So far, such programs for children of substance-involved parents have not been reviewed together. We conducted a comprehensive systematic review to identify and summarize evaluations of selective preventive interventions in childhood and adolescence targeted at this specific group. From the overall search result of 375 articles, 339 were excluded, 36 full texts were reviewed. From these, nine eligible programs documented in 13 studies were identified comprising four school-based interventions (study 1–6, one community-based intervention (study 7–8, and four family-based interventions (study 9–13. Studies’ levels of evidence were rated in accordance with the Scottish Intercollegiate Guidelines Network (SIGN methodology, and their quality was ranked according to a score adapted from the area of meta-analytic family therapy research and consisting of 15 study design quality criteria. Studies varied in program format, structure, content, and participants. They also varied in outcome measures, results, and study design quality. We found seven RCT’s, two well designed controlled or quasi-experimental studies, three well-designed descriptive studies, and one qualitative study. There was preliminary evidence for the effectiveness of the programs, especially when their duration was longer than ten weeks and when they involved children’s, parenting, and family skills training components. Outcomes proximal to the intervention, such as program-related knowledge, coping-skills, and family relations, showed better results than more distal outcomes such as self-worth and substance use initiation, the latter due to the comparably young age of participants and sparse longitudinal data. However, because of the small overall number of studies found
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Peng, Sheng; Sun, Haiyan; Zhang, Xiaoqing; Liu, Gongjian; Wang, Guanglei
2014-09-01
Phosphodiesterase-4 (PDE-4) regulates the intracellular level of cyclic adenosine monophosphate. Recent studies demonstrated that PDE-4 inhibitors can counteract deficits in long-term memory caused by aging or increased expression of mutant forms of human amyloid precursor proteins, and can influence the process of memory function and cognitive enhancement. Therapeutics, such as ketamine, a drug used in clinical anesthesia, can also cause memory deficits as adverse effects. Targeting PDE-4 with selective inhibitors may offer a novel therapeutic strategy to prevent, slow the progress, and, eventually, treat memory deficits.
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Centers for Disease Control (CDC) Podcasts
This 60 second public service announcement is based on the June 2015 CDC Vital Signs report. Skin cancer is the most common form of cancer in the U.S. In 2011, there were more than 65,000 cases of melanoma, the most deadly form of skin cancer. Learn how everyone can help prevent skin cancer.
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Tevendale, Heather D; Condron, D Susanne; Garraza, Lucas Godoy; House, L Duane; Romero, Lisa M; Brooks, Megan A M; Walrath, Christine
2017-03-01
This paper presents an overview of the key evaluation components for a set of community-wide teen pregnancy prevention initiatives. We first describe the performance measures selected to assess progress toward meeting short-term objectives on the reach and quality of implementation of evidence-based teen pregnancy prevention interventions and adolescent reproductive health services. Next, we describe an evaluation that will compare teen birth rates in intervention communities relative to synthetic control communities. Synthetic controls are developed via a data-driven technique that constructs control communities by combining information from a pool of communities that are similar to the intervention community. Finally, we share lessons learned thus far in the evaluation of the project, with a focus on those lessons that may be valuable for local communities evaluating efforts to reduce teen pregnancy. Copyright © 2016 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.
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Using Selective Redundancy and Testing to Optimize Learning from Multimedia Lessons
Yue, Carole Leigh
2014-01-01
Multimedia learning refers to learning from a combination of words and images. In the present dissertation, a multimedia lesson is defined as an animated, narrated educational video that depicts a scientific process--a format of instructional material becoming increasingly common in online, hybrid, and traditional classrooms. The overarching goal of the present research was to investigate how to optimize learning from multimedia lessons using two related theories of multimedia learning (the...
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Babalola, P A; Fitz, N F; Gibbs, R B; Flaherty, P T; Li, P-K; Johnson, D A
2012-10-01
Dehydroepiandrosterone sulfate (DHEAS), is an excitatory neurosteroid synthesized within the CNS that modulates brain function. Effects associated with augmented DHEAS include learning and memory enhancement. Inhibitors of the steroid sulfatase enzyme increase brain DHEAS levels and can also facilitate learning and memory. This study investigated the effect of steroid sulfatase inhibition on learning and memory in rats with selective cholinergic lesion of the septo-hippocampal tract using passive avoidance and delayed matching to position T-maze (DMP) paradigms. The selective cholinergic immunotoxin 192 IgG-saporin (SAP) was infused into the medial septum of animals and then tested using a step-through passive avoidance paradigm or DMP paradigm. Peripheral administration of the steroid sulfatase inhibitor, DU-14, increased step-through latency following footshock in rats with SAP lesion compared to both vehicle treated control and lesioned animals (pmemory associated with contextual fear, but impairs acquisition of spatial memory tasks in rats with selective lesion of the septo-hippocampal tract. Copyright © 2012 Elsevier Inc. All rights reserved.
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Foged, Mette Thrane; Vinter, Kirsten; Stauning, Louise; Kjær, Troels W; Ozenne, Brice; Beniczky, Sándor; Paulson, Olaf B; Madsen, Flemming Find; Pinborg, Lars H
2018-02-01
With the advent of new very selective techniques like thermal laser ablation to treat drug-resistant focal epilepsy, the controversy of resection size in relation to seizure outcome versus cognitive deficits has gained new relevance. The purpose of this study was to test the influence of the selective amygdalohippocampectomy (SAH) versus nonselective temporal lobe resection (TLR) on seizure outcome and cognition in patients with mesial temporal lobe epilepsy (MTLE) and histopathological verified hippocampal sclerosis (HS). We identified 108 adults (>16years) with HS, operated between 1995 and 2009 in Denmark. Exclusion criteria are the following: Intelligence below normal range, right hemisphere dominance, other native languages than Danish, dual pathology, and missing follow-up data. Thus, 56 patients were analyzed. The patients were allocated to SAH (n=22) or TLR (n=34) based on intraoperative electrocorticography. Verbal learning and verbal memory were tested pre- and postsurgery. Seizure outcome did not differ between patients operated using the SAH versus the TLR at 1year (p=0.951) nor at 7years (p=0.177). Verbal learning was more affected in patients resected in the left hemisphere than in the right (p=0.002). In patients with left-sided TLR, a worsening in verbal memory performance was found (p=0.011). Altogether, 73% were seizure-free for 1year and 64% for 7years after surgery. In patients with drug-resistant focal MTLE, HS and no magnetic resonance imaging (MRI) signs of dual pathology, selective amygdalohippocampectomy results in sustained seizure freedom and better memory function compared with patients operated with nonselective temporal lobe resection. Copyright © 2017 Elsevier Inc. All rights reserved.
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Skills Methods to Prevent Smoking.
Schinke, Steven Paul; And Others
1986-01-01
Describes an evaluation of the added value of skills methods for preventing smoking with sixth-grade students from two schools. Skills conditions subjects learned problem-solving, self-instruction, and interpersonal communication methods. The article discusses the strengths, limits, and implications of the study for other smoking prevention…
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Eunsuk Chong; Taejin Choi; Hyungmin Kim; Seung-Jong Kim; Yoha Hwang; Jong Min Lee
2017-07-01
We propose a novel approach of selecting useful input sensors as well as learning a mathematical model for predicting lower limb joint kinematics. We applied a feature selection method based on the mutual information called the variational information maximization, which has been reported as the state-of-the-art work among information based feature selection methods. The main difficulty in applying the method is estimating reliable probability density of input and output data, especially when the data are high dimensional and real-valued. We addressed this problem by applying a generative stochastic neural network called the restricted Boltzmann machine, through which we could perform sampling based probability estimation. The mutual informations between inputs and outputs are evaluated in each backward sensor elimination step, and the least informative sensor is removed with its network connections. The entire network is fine-tuned by maximizing conditional likelihood in each step. Experimental results are shown for 4 healthy subjects walking with various speeds, recording 64 sensor measurements including electromyogram, acceleration, and foot-pressure sensors attached on both lower limbs for predicting hip and knee joint angles. For test set of walking with arbitrary speed, our results show that our suggested method can select informative sensors while maintaining a good prediction accuracy.
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Apisitwasana, Nipaporn; Perngparn, Usaneya; Cottler, Linda B
2018-01-01
This study aimed to assess the effectiveness of Participatory Learning School and Family Based Intervention Program for Preventing Game Addiction by Developing Self-Regulation of gaming addiction among students of grades 4 and 5 in Bangkok. A quasi-experimental study was implemented among students of grades 4 and 5 at primary schools in Bangkok selected through multistage random sampling. Two comparable schools were randomly assigned to either the intervention or control group. Then, 310 students in the randomly selected classrooms were allocated to each group. The intervention group received the self-regulation program with school and family involvement to prevent gaming addiction. Master teachers attended in-house training on prevention of gaming addiction in children. Parents of these children received a gaming addiction prevention manual and guidelines. The program lasted 8 weeks. The control group received no intervention. Knowledge and Attitude About Gaming Questionnaire, Game Addiction Screening Test (GAST), and Game Addiction Protection Scale were utilized to assess subjects at baseline, immediately after, and 3 months post-intervention. Descriptive statistics, chi-square, and independent t -test were used to describe characteristics of the participants, and repeated measures ANOVA was analyzed to test the effectiveness of the intervention. The findings revealed that there were significant differences in knowledge, attitude, self-regulation, and gaming addiction behaviors ( p gaming addiction in students of grades 4 and 5 in Bangkok, Thailand.
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Speeding the growth of primary mental health prevention.
Wissow, Lawrence S
2015-01-01
While there is a strong case for primary prevention of mental health problems, relatively little mental health scholarship has been devoted to it in the last decade. Efforts to accelerate prevention scholarship could potentially benefit from strengthening pathways for interdisciplinary research; developing new training and working models for mental health professionals; developing a common language for public, policy, and scientific discussion of prevention; learning how to measure the common outcomes of heterogeneous interventions tailored to diverse communities.
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CONTEMPORARY PRINCIPLES OF SUICIDE PREVENTION.
Ljusic, Dragana; Ravanic, Dragan; Filipovic Danic, Snezana; Soldatovic, Ivan; Cvetkovic, Jovana; Stojanovic Tasic, Mirjana
2016-11-01
Suicide remains a significant public health problem worldwide. This study is aimed at analyzing and presenting contemporary methods in suicide prevention in the world as well as at identifying specific risk groups and risk factors in order to explain their importance. in suicide prevention. The literature search covered electronic databases PubMed, Web of Science and Scopus. In order to select the relevant articles, the authors searched for the combination of key-words which included the following medical subject heading terms (suicide or suicide ideation or attempted) and (prevention or risk factors) and (man or elders or mental disorders). Data analysis covered meta-analyses, systematic reviews and original scientific papers with different characteristics of suicide preventions, risk factors and risk groups. Worldwide evidence-based interventions for suicide prevention are divided in universal, selective and indicated interventions. Restricted approach to various methods of committing suicide as well as pharmacotherapy contributes to a lower suicide rate. Suicide risk factors can be categorized as proximal and distal. The following groups are at highest risk of committing suicide: males. older persons and persons with registered psychiatric disorders. There is a lot of evidence that suicide is preventable. It is known that only 28 coun tries in the world have national suicide prevention strategies and Serbia is not one of them.
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Ellickson, Phyllis L.
This paper describes the Project ALERT program (Adolescent Learning Experiences in Resistance Training) which was established by the Rand Corporation to prevent smoking and drug use among seventh graders. The program is based on the social influence model of drug use initiation. Curriculum features are described including motivation to resist and…
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Effects of gender and role selection in cooperative learning groups on science inquiry achievement
Affhalter, Maria Geralyn
An action research project using science inquiry labs and cooperative learning groups examined the effects of same-gender and co-educational classrooms on science achievement and teacher-assigned or self-selected group roles on students' role preferences. Fifty-nine seventh grade students from a small rural school district participated in two inquiry labs in co-educational classrooms or in an all-female classroom, as determined by parents at the beginning of the academic year. Students were assigned to the same cooperative groups for the duration of the study. Pretests and posttests were administered for each inquiry-based science lab. Posttest assessments included questions for student reflection on role assignment and role preference. Instruction did not vary and a female science teacher taught all class sections. The same-gender classroom and co-ed classrooms produced similar science achievement scores on posttests. Students' cooperative group roles, whether teacher-assigned or self-selected, produced similar science achievement scores on posttests. Male and female students shared equally in favorable and unfavorable reactions to their group roles during the science inquiry labs. Reflections on the selection of the leader role revealed a need for females in co-ed groups to be "in charge". When reflecting on her favorite role of leader, one female student in a co-ed group stated, "I like to have people actually listen to me".
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Men's Health: Prevent the Top Threats
... to reduce stress — or learn to deal with stress in healthy ways. Don't wait to visit the doctor until something is seriously wrong. Your doctor can be your best ally for preventing health problems. Follow your doctor's ...
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Understanding and Preventing Learned Helplessness in Children Who Are Congenitally Deaf-Blind.
Marks, S. B.
1998-01-01
Links the literature on learned helplessness with best practices in teaching children who are deaf-blind. Defines "learned helplessness" and "mastery motivation;" considers identification of learned helplessness; and offers suggestions such as rewarding independent rather than dependent behaviors and integrating orientation, mobility, and…
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Finch, Caroline F; Ullah, Shahid; McIntosh, Andrew S
2011-01-01
Several important methodological issues need to be considered when designing sports injury case-control studies. Major design goals for case-control studies include the accounting for prior injury risk exposure, and optimal definitions of both cases and suitable controls are needed to ensure this. This article reviews methodological aspects of published sports injury case-control studies, particularly with regard to the selection of controls. It argues for a new approach towards selecting controls for case-control studies that draws on an interface between epidemiological and biomechanical concepts. A review was conducted to identify sport injury case-control studies published in the peer-review literature during 1985-2008. Overall, 32 articles were identified, of which the majority related to upper or lower extremity injuries. Matching considerations were used for control selection in 16 studies. Specific mention of application of biomechanical principles in the selection of appropriate controls was absent from all studies, including those purporting to evaluate the benefits of personal protective equipment to protect against impact injury. This is a problem because it could lead to biased conclusions, as cases and controls are not fully comparable in terms of similar biomechanical impact profiles relating to the injury incident, such as site of the impact on the body. The strength of the conclusions drawn from case-control studies, and the extent to which results can be generalized, is directly influenced by the definition and recruitment of cases and appropriate controls. Future studies should consider the interface between epidemiological and biomechanical concepts when choosing appropriate controls to ensure that proper adjustment of prior exposure to injury risk is made. To provide necessary guidance for the optimal selection of controls in case-control studies of interventions to prevent sports-related impact injury, this review outlines a new case
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Project SAIL: An Evaluation of a Dropout Prevention Program.
Thompson, John L.; And Others
Project SAIL (Student Advocates Inspire Learning) is a Title IV-C Project located in Hopkins, Minnesota, designed to prevent students from dropping out of school by keeping them successfully involved in the mainstream environment. This study presents a review of other dropout prevention approaches, describes the intervention strategies involved in…
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DEFF Research Database (Denmark)
Kolbæk, Ditte; Lundh Snis, Ulrika
Abstract: This paper analyses an online community of master’s students taking a course in ICT and organisational learning. The students initiated and facilitated an educational design for organisational learning called Proactive Review in the organisation where they are employed. By using an online...... discussion forum on Google groups, they created new ways of reflecting and learning. We used netnography to select qualitative postings from the online community and expansive learning concepts for data analysis. The findings show how students changed practices of organisational learning...
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Crime Prevention through Environmental Design
Draper, Rick; Cadzow, Emma
2004-01-01
Applying CPTED (Crime Prevention Through Environmental Design) strategies to schools can significantly contribute to a safer learning environment by influencing the behaviour of students and visitors. CPTED has three overlapping primary concepts that are intended to reduce opportunities for crime as well as fear of crime: access control,…
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Newton, Nicola C.; Conrod, Patricia J.; Slade, Tim; Carragher, Natacha; Champion, Katrina E.; Barrett, Emma L.; Kelly, Erin V.; Nair, Natasha K.; Stapinski, Lexine; Teesson, Maree
2016-01-01
Background: This study investigated the long-term effectiveness of Preventure, a selective personality-targeted prevention program, in reducing the uptake of alcohol, harmful use of alcohol, and alcohol-related harms over a 3-year period. Methods: A cluster randomized controlled trial was conducted to assess the effectiveness of Preventure.…
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Multi-Label Learning via Random Label Selection for Protein Subcellular Multi-Locations Prediction.
Wang, Xiao; Li, Guo-Zheng
2013-03-12
Prediction of protein subcellular localization is an important but challenging problem, particularly when proteins may simultaneously exist at, or move between, two or more different subcellular location sites. Most of the existing protein subcellular localization methods are only used to deal with the single-location proteins. In the past few years, only a few methods have been proposed to tackle proteins with multiple locations. However, they only adopt a simple strategy, that is, transforming the multi-location proteins to multiple proteins with single location, which doesn't take correlations among different subcellular locations into account. In this paper, a novel method named RALS (multi-label learning via RAndom Label Selection), is proposed to learn from multi-location proteins in an effective and efficient way. Through five-fold cross validation test on a benchmark dataset, we demonstrate our proposed method with consideration of label correlations obviously outperforms the baseline BR method without consideration of label correlations, indicating correlations among different subcellular locations really exist and contribute to improvement of prediction performance. Experimental results on two benchmark datasets also show that our proposed methods achieve significantly higher performance than some other state-of-the-art methods in predicting subcellular multi-locations of proteins. The prediction web server is available at http://levis.tongji.edu.cn:8080/bioinfo/MLPred-Euk/ for the public usage.
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Energy Technology Data Exchange (ETDEWEB)
NONE
1998-08-01
Spectrally selective glazing is window glass that permits some portions of the solar spectrum to enter a building while blocking others. This high-performance glazing admits as much daylight as possible while preventing transmission of as much solar heat as possible. By controlling solar heat gains in summer, preventing loss of interior heat in winter, and allowing occupants to reduce electric lighting use by making maximum use of daylight, spectrally selective glazing significantly reduces building energy consumption and peak demand. Because new spectrally selective glazings can have a virtually clear appearance, they admit more daylight and permit much brighter, more open views to the outside while still providing the solar control of the dark, reflective energy-efficient glass of the past. This Federal Technology Alert provides detailed information and procedures for Federal energy managers to consider spectrally selective glazings. The principle of spectrally selective glazings is explained. Benefits related to energy efficiency and other architectural criteria are delineated. Guidelines are provided for appropriate application of spectrally selective glazing, and step-by-step instructions are given for estimating energy savings. Case studies are also presented to illustrate actual costs and energy savings. Current manufacturers, technology users, and references for further reading are included for users who have questions not fully addressed here.
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Cheng, Yu-Huei
2014-12-01
Specific primers play an important role in polymerase chain reaction (PCR) experiments, and therefore it is essential to find specific primers of outstanding quality. Unfortunately, many PCR constraints must be simultaneously inspected which makes specific primer selection difficult and time-consuming. This paper introduces a novel computational intelligence-based method, Teaching-Learning-Based Optimisation, to select the specific and feasible primers. The specified PCR product lengths of 150-300 bp and 500-800 bp with three melting temperature formulae of Wallace's formula, Bolton and McCarthy's formula and SantaLucia's formula were performed. The authors calculate optimal frequency to estimate the quality of primer selection based on a total of 500 runs for 50 random nucleotide sequences of 'Homo species' retrieved from the National Center for Biotechnology Information. The method was then fairly compared with the genetic algorithm (GA) and memetic algorithm (MA) for primer selection in the literature. The results show that the method easily found suitable primers corresponding with the setting primer constraints and had preferable performance than the GA and the MA. Furthermore, the method was also compared with the common method Primer3 according to their method type, primers presentation, parameters setting, speed and memory usage. In conclusion, it is an interesting primer selection method and a valuable tool for automatic high-throughput analysis. In the future, the usage of the primers in the wet lab needs to be validated carefully to increase the reliability of the method.
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Characterizing Reinforcement Learning Methods through Parameterized Learning Problems
2011-06-03
extraneous. The agent could potentially adapt these representational aspects by applying methods from feature selection ( Kolter and Ng, 2009; Petrik et al...611–616. AAAI Press. Kolter , J. Z. and Ng, A. Y. (2009). Regularization and feature selection in least-squares temporal difference learning. In A. P
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Coe, Laura J.; St. John, Julie Ann; Hariprasad, Santhi; Shankar, Kalpana N.; MacCulloch, Patricia A.; Bettano, Amy L.; Zotter, Jean
2017-01-01
Older adult falls continue to be a public health priority across the United States—Massachusetts (MA) being no exception. The MA Prevention and Wellness Trust Fund (PWTF) program within the MA Department of Public Health aims to reduce the physical and economic burdens of chronic health conditions by linking evidence-based clinical care with community intervention programs. The PWTF partnerships that focused on older adult falls prevention integrated the Centers for Disease Control and Prevention’s Stopping Elderly Accidents, Death and Injuries toolkit into clinical settings. Partnerships also offer referrals for home safety assessments, Tai Chi, and Matter of Balance programs. This paper describes the PWTF program implementation process involving 49 MA organizations, while highlighting the successes achieved and lessons learned. With the unprecedented expansion of the U.S. Medicare beneficiary population, and the escalating incidence of falls, widespread adoption of effective prevention strategies will become increasingly important for both public health and for controlling healthcare costs. The lessons learned from this PWTF initiative offer insights and recommendations for future falls prevention program development and implementation. PMID:28321393
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Brace, Jacalyn A; Schubart, Jane R
2010-08-01
Pressure ulcers are a common complication of spinal cord injury (SCI). Pressure ulcer education programs for spinal cord injured individuals have been found to have a positive effect on care protocol adherence. A prospective study was conducted among hospitalized spinal cord-injured men and women to determine if viewing the Pressure Ulcer Prevention and Management Education for Adults with Spinal Cord Injury: E-Learning Program affects their knowledge scores. A 20-question multiple-choice pre-/post learning test was developed and validated by 12 rehabilitation nurses. Twenty (20) patients (13 men, seven women; mean age 49 years, [SD: 18.26] with injuries to the cervical [seven], thoracic [six], and lumbar [six] regions) volunteered. Most (42%) had completed high school and time since SCI ranged from 2 weeks to 27 years. Eighteen (18) participants completed both the pre- and post test. Of those, 16 showed improvement in pressure ulcer knowledge scores. The median scores improved from 65 (range 25 to 100) pre-program to 92.5 (range 75 to 100) post-program. Descriptive statistics, Student's t-test, and analysis of variance (ANOVA) were used to analyze the data. The results suggest that a single viewing of this e-learning program could improve pressure ulcer knowledge of hospitalized adults with SCI. Research to ascertain the effects of this and other educational programs on pressure ulcer rates is needed.
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Inhibition of vicariously learned fear in children using positive modeling and prior exposure.
Askew, Chris; Reynolds, Gemma; Fielding-Smith, Sarah; Field, Andy P
2016-02-01
One of the challenges to conditioning models of fear acquisition is to explain how different individuals can experience similar learning events and only some of them subsequently develop fear. Understanding factors moderating the impact of learning events on fear acquisition is key to understanding the etiology and prevention of fear in childhood. This study investigates these moderators in the context of vicarious (observational) learning. Two experiments tested predictions that the acquisition or inhibition of fear via vicarious learning is driven by associative learning mechanisms similar to direct conditioning. In Experiment 1, 3 groups of children aged 7 to 9 years received 1 of 3 inhibitive information interventions-psychoeducation, factual information, or no information (control)-prior to taking part in a vicarious fear learning procedure. In Experiment 2, 3 groups of children aged 7 to 10 years received 1 of 3 observational learning interventions-positive modeling (immunization), observational familiarity (latent inhibition), or no prevention (control)-before vicarious fear learning. Results indicated that observationally delivered manipulations inhibited vicarious fear learning, while preventions presented via written information did not. These findings confirm that vicarious learning shares some of the characteristics of direct conditioning and can explain why not all individuals will develop fear following a vicarious learning event. They also suggest that the modality of inhibitive learning is important and should match the fear learning pathway for increased chances of inhibition. Finally, the results demonstrate that positive modeling is likely to be a particularly effective method for preventing fear-related observational learning in children. (c) 2016 APA, all rights reserved).
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Stomach Cancer Prevention (PDQ®)—Patient Version
Stomach (gastric) cancer risk factors include smoking and H. pylori. Learn about these and other risk factors for stomach cancer and how to prevent stomach cancer in this expert-reviewed and evidence-based summary.
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E-learning Paradigms and The Development of E-learning Strategy
DEFF Research Database (Denmark)
Duus, Henrik Johannsen
2006-01-01
The e-learning area is characterized by a magnitude of different products, systems and approaches. The variations can also be observed in differences in the views and notions of e-learning among business people, researchers and journalists. This article attempts to disentangle the area by using...... economic and sociological theories, the theories of marketing management and strategy as well as practical experience gained by the author while working with leading edge suppliers of e-learning. On this basis, a distinction between knowledge creation e-learning and knowledge transfer e-learning....... The selection of which paradigm to use in the development of an e-learning strategy may prove crucial for success. Implications for the development of an e-learning strategy in businesses and learning institutions are outlined....
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Learned Helplessness and Academic Failure.
Hayes, Carolyn
Some individuals more readily develop learned helplessness in the classroom, so it is necessary for the educational system to acknowledge it and develop teaching methods to prevent it. Creating awareness among educators of this condition could greatly decrease its occurrence. Children who have a high risk of developing learned helplessness,…
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CDC Vital Signs-Preventing Melanoma
Centers for Disease Control (CDC) Podcasts
This podcast is based on the June 2015 CDC Vital Signs report. Skin cancer is the most common form of cancer in the U.S. In 2011, there were more than 65,000 cases of melanoma, the most deadly form of skin cancer. Learn how everyone can help prevent skin cancer.
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Organizational Learning as a testbed for BPR
DEFF Research Database (Denmark)
Larsen, Michael Holm; Leinsdorff, Torben
1998-01-01
The fact that a company´s learning ability may prevent strategic drift and the fact that many companies are undertaking BPR projects lead us to inquire into whether all BPR activities promote organizational learning...
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Realising the organisational learning opportunities
International Nuclear Information System (INIS)
Pomfret, D.G.; Bradford, S.T.
2000-01-01
An aspect of proactive safety management is learning lessons from unforeseen events. As BNFL has expanded and extended its nuclear services to many more sites, the potential for organisational learning has grown, but sharing through informal networking has become progressively harder. This potential problem has been solved by implementing formalised company-wide arrangements to turn incidents and accidents into organisational learning opportunities through a system called 'Learning from Experience' (LFE). LFE enables event causes and corrective actions to be identified and shared across all BNFL's sites, initially in the UK but ultimately throughout the world. The result is prevention of events having similar causes, and development of a learning culture which breaks down the barriers to adopting best practice'. Key aspects of the system are: Applying root cause analysis to all significant events; Logging all events, their causes and corrective actions onto a Company-wide database; Screening the database regularly by locally appointed Feedback Co-ordinators trained in identifying learning opportunities and knowledgeable of their own business area, and; Placing and tracking actions to prevent similar events at local Event Review Meetings. The paper describes the implementation and initial experience in operation of the LFE system, which is seen as a significant step towards becoming an expanding and learning company with no accidents or incidents. (author)
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From mission to measures: performance measure development for a Teen Pregnancy Prevention Program.
Farb, Amy Feldman; Burrus, Barri; Wallace, Ina F; Wilson, Ellen K; Peele, John E
2014-03-01
The Office of Adolescent Health (OAH) sought to create a comprehensive set of performance measures to capture the performance of the Teen Pregnancy Prevention (TPP) program. This performance measurement system needed to provide measures that could be used internally (by both OAH and the TPP grantees) for management and program improvement as well as externally to communicate the program's progress to other interested stakeholders and Congress. This article describes the selected measures and outlines the considerations behind the TPP measurement development process. Issues faced, challenges encountered, and lessons learned have broad applicability for other federal agencies and, specifically, for TPP programs interested in assessing their own performance and progress. Published by Elsevier Inc.
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Vital Signs-Preventing Prescription Drug Overdose
Centers for Disease Control (CDC) Podcasts
This podcast is based on the July 2014 CDC Vital Signs report. Every day, 46 people in the U.S. die from an overdose of prescription opioid painkillers. Learn what can be done to make painkiller prescribing safer and help prevent overdoses.
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Directory of Open Access Journals (Sweden)
Timothy De Ver Dye
Full Text Available BACKGROUND: Many countries face severe scale-up barriers toward achievement of MDGs. We ascertained motivational and experiential dimensions of participation in a novel, rapid, "diagonal" Integrated Prevention Campaign (IPC in rural Kenya that provided prevention goods and services to 47,000 people within one week, aimed at rapidly moving the region toward MDG achievement. Specifically, the IPC provided interventions and commodities targeting disease burden reduction in HIV/AIDS, malaria, and water-borne illness. METHODS: Qualitative in-depth interviews (IDI were conducted with 34 people (18 living with HIV/AIDS and 16 not HIV-infected randomly selected from IPC attendees consenting to participate. Interviews were examined for themes and patterns to elucidate participant experience and motivation with IPC. FINDINGS: Participants report being primarily motivated to attend IPC to learn of their HIV status (through voluntary counseling and testing, and with receipt of prevention commodities (bednets, water filters, and condoms providing further incentive. Participants reported that they were satisfied with the IPC experience and offered suggestions to improve future campaigns. INTERPRETATION: Learning their HIV status motivated participants along with the incentive of a wider set of commodities that were rapidly deployed through IPC in this challenging region. The critical role of wanting to know their HIV status combined with commodity incentives may offer a new model for rapid scaled-up of prevention strategies that are wider in scope in rural Africa.
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Perceptual learning and human expertise.
Kellman, Philip J; Garrigan, Patrick
2009-06-01
We consider perceptual learning: experience-induced changes in the way perceivers extract information. Often neglected in scientific accounts of learning and in instruction, perceptual learning is a fundamental contributor to human expertise and is crucial in domains where humans show remarkable levels of attainment, such as language, chess, music, and mathematics. In Section 2, we give a brief history and discuss the relation of perceptual learning to other forms of learning. We consider in Section 3 several specific phenomena, illustrating the scope and characteristics of perceptual learning, including both discovery and fluency effects. We describe abstract perceptual learning, in which structural relationships are discovered and recognized in novel instances that do not share constituent elements or basic features. In Section 4, we consider primary concepts that have been used to explain and model perceptual learning, including receptive field change, selection, and relational recoding. In Section 5, we consider the scope of perceptual learning, contrasting recent research, focused on simple sensory discriminations, with earlier work that emphasized extraction of invariance from varied instances in more complex tasks. Contrary to some recent views, we argue that perceptual learning should not be confined to changes in early sensory analyzers. Phenomena at various levels, we suggest, can be unified by models that emphasize discovery and selection of relevant information. In a final section, we consider the potential role of perceptual learning in educational settings. Most instruction emphasizes facts and procedures that can be verbalized, whereas expertise depends heavily on implicit pattern recognition and selective extraction skills acquired through perceptual learning. We consider reasons why perceptual learning has not been systematically addressed in traditional instruction, and we describe recent successful efforts to create a technology of perceptual
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Perceptual learning and human expertise
Kellman, Philip J.; Garrigan, Patrick
2009-06-01
We consider perceptual learning: experience-induced changes in the way perceivers extract information. Often neglected in scientific accounts of learning and in instruction, perceptual learning is a fundamental contributor to human expertise and is crucial in domains where humans show remarkable levels of attainment, such as language, chess, music, and mathematics. In Section 2, we give a brief history and discuss the relation of perceptual learning to other forms of learning. We consider in Section 3 several specific phenomena, illustrating the scope and characteristics of perceptual learning, including both discovery and fluency effects. We describe abstract perceptual learning, in which structural relationships are discovered and recognized in novel instances that do not share constituent elements or basic features. In Section 4, we consider primary concepts that have been used to explain and model perceptual learning, including receptive field change, selection, and relational recoding. In Section 5, we consider the scope of perceptual learning, contrasting recent research, focused on simple sensory discriminations, with earlier work that emphasized extraction of invariance from varied instances in more complex tasks. Contrary to some recent views, we argue that perceptual learning should not be confined to changes in early sensory analyzers. Phenomena at various levels, we suggest, can be unified by models that emphasize discovery and selection of relevant information. In a final section, we consider the potential role of perceptual learning in educational settings. Most instruction emphasizes facts and procedures that can be verbalized, whereas expertise depends heavily on implicit pattern recognition and selective extraction skills acquired through perceptual learning. We consider reasons why perceptual learning has not been systematically addressed in traditional instruction, and we describe recent successful efforts to create a technology of perceptual
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Gelan, Anouk; Fastré, Greet; Verjans, Martine; Martin, Niels; Janssenswillen, Gert; Creemers, Mathijs; Lieben, Jonas; Depaire, Benoît; Thomas, Michael
2018-01-01
Learning analytics (LA) has emerged as a field that offers promising new ways to prevent drop-out and aid retention. However, other research suggests that large datasets of learner activity can be used to understand online learning behaviour and improve pedagogy. While the use of LA in language learning has received little attention to date,…
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The DELTA PREP Initiative: Accelerating Coalition Capacity for Intimate Partner Violence Prevention
Zakocs, Ronda; Freire, Kimberley E.
2018-01-01
Background The DELTA PREP Project aimed to build the prevention capacity of 19 state domestic violence coalitions by offering eight supports designed to promote prevention integration over a 3-year period: modest grant awards, training events, technical assistance, action planning, coaching hubs, the Coalition Prevention Capacity Assessment, an online workstation, and the online documentation support system. Objectives Using quantitative and qualitative data, we sought to explain how coalitions integrated prevention within their structures and functions and document how DELTA PREP supports contributed to coalitions’ integration process. Results We found that coalitions followed a common pathway to integrate prevention. First, coalitions exhibited precursors of organizational readiness, especially having prevention champions. Second, coalitions engaged in five critical actions: engaging in dialogue, learning about prevention, forming teams, soliciting input from the coalition, and action planning. Last, by engaging in these critical actions, coalitions enhanced two key organizational readiness factors—developing a common understanding of prevention and an organizational commitment to prevention. We also found that DELTA PREP supports contributed to coalitions’ abilities to integrate prevention by supporting learning about prevention, fostering a prevention team, and engaging in action planning by leveraging existing opportunities. Two DELTA PREP supports—coaching hubs and the workstation—did not work as initially intended. From the DELTA PREP experience, we offer several lessons to consider when designing future prevention capacity-building initiatives. PMID:26245934
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Schüpfer, G; Gfrörer, R; Schleppers, A
2007-10-01
In only a few contexts is the need for substantial learning more pronounced than in health care. For a health care provider, the ability to learn is essential in a changing environment. Although individual humans are programmed to learn naturally, organisations are not. Learning that is limited to individual professions and traditional approaches to continuing medical education is not sufficient to bring about substantial changes in the learning capacity of an institution. Also, organisational learning is an important issue for anaesthesia departments. Future success of an organisation often depends on new capabilities and competencies. Organisational learning is the capacity or processes within an organisation to maintain or improve performance based on experience. Learning is seen as a system-level phenomenon as it stays in the organisation regardless of the players involved. Experience from other industries shows that learning strategies tend to focus on single loop learning, with relatively little double loop learning and virtually no meta-learning or non-learning. The emphasis on team delivery of health care reinforces the need for team learning. Learning organisations make learning an intrinsic part of their organisations and are a place where people continually learn how to learn together. Organisational learning practice can help to improve existing skills and competencies and to change outdated assumptions, procedures and structures. So far, learning theory has been ignored in medicine, due to a wide variety of complex political, economic, social, organisational culture and medical factors that prevent innovation and resist change. The organisational culture is central to every stage of the learning process. Learning organisations move beyond simple employee training into organisational problem solving, innovation and learning. Therefore, teamwork and leadership are necessary. Successful organisations change the competencies of individuals, the systems
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Modeling Directional Selectivity Using Self-Organizing Delay-Aadaptation Maps
Tversky, Mr. Tal; Miikkulainen, Dr. Risto
2002-01-01
Using a delay adaptation learning rule, we model the activity-dependent development of directionally selective cells in the primary visual cortex. Based on input stimuli, a learning rule shifts delays to create synchronous arrival of spikes at cortical cells. As a result, delays become tuned creating a smooth cortical map of direction selectivity. This result demonstrates how delay adaption can serve as a powerful abstraction for modeling temporal learning in the brain.
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Sex selection: treating different cases differently.
Dickens, B M; Serour, G I; Cook, R J; Qiu, R-Z
2005-08-01
This paper contrasts ethical approaches to sex selection in countries where discrimination against women is pervasive, resulting in selection against girl children, and in countries where there is less general discrimination and couples do not prefer children of either sex. National sex ratio imbalances where discrimination against women is common have resulted in laws and policies, such as in India and China, to deter and prevent sex selection. Birth ratios of children can be affected by techniques of prenatal sex determination and abortion, preconception sex selection and discarding disfavored embryos, and prefertilization sperm sorting, when disfavored sperm remain unused. Incentives for son preference are reviewed, and laws and policies to prevent sex selection are explained. The elimination of social, economic and other discrimination against women is urged to redress sex selection against girl children. Where there is no general selection against girl children, sex selection can be allowed to assist families that want children of both sexes.
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Pazol, Karen; Robbins, Cheryl L; Black, Lindsey I; Ahrens, Katherine A; Daniels, Kimberly; Chandra, Anjani; Vahratian, Anjel; Gavin, Lorrie E
2017-10-27
Receipt of key preventive health services among women and men of reproductive age (i.e., 15-44 years) can help them achieve their desired number and spacing of healthy children and improve their overall health. The 2014 publication Providing Quality Family Planning Services: Recommendations of CDC and the U.S. Office of Population Affairs (QFP) establishes standards for providing a core set of preventive services to promote these goals. These services include contraceptive care for persons seeking to prevent or delay pregnancy, pregnancy testing and counseling, basic infertility services for those seeking to achieve pregnancy, sexually transmitted disease (STD) services, and other preconception care and related preventive health services. QFP describes how to provide these services and recommends using family planning and other primary care visits to screen for and offer the full range of these services. This report presents baseline estimates of the use of these preventive services before the publication of QFP that can be used to monitor progress toward improving the quality of preventive care received by women and men of reproductive age. 2011-2013. Three surveillance systems were used to document receipt of preventive health services among women and men of reproductive age as recommended in QFP. The National Survey of Family Growth (NSFG) collects data on factors that influence reproductive health in the United States since 1973, with a focus on fertility, sexual activity, contraceptive use, reproductive health care, family formation, child care, and related topics. NSFG uses a stratified, multistage probability sample to produce nationally representative estimates for the U.S. household population of women and men aged 15-44 years. This report uses data from the 2011-2013 NSFG. The Pregnancy Risk Assessment Monitoring System (PRAMS) is an ongoing, state- and population-based surveillance system designed to monitor selected maternal behaviors and experiences
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The importance of learning when making inferences
Directory of Open Access Journals (Sweden)
Jorg Rieskamp
2008-03-01
Full Text Available The assumption that people possess a repertoire of strategies to solve the inference problems they face has been made repeatedly. The experimental findings of two previous studies on strategy selection are reexamined from a learning perspective, which argues that people learn to select strategies for making probabilistic inferences. This learning process is modeled with the strategy selection learning (SSL theory, which assumes that people develop subjective expectancies for the strategies they have. They select strategies proportional to their expectancies, which are updated on the basis of experience. For the study by Newell, Weston, and Shanks (2003 it can be shown that people did not anticipate the success of a strategy from the beginning of the experiment. Instead, the behavior observed at the end of the experiment was the result of a learning process that can be described by the SSL theory. For the second study, by Br"oder and Schiffer (2006, the SSL theory is able to provide an explanation for why participants only slowly adapted to new environments in a dynamic inference situation. The reanalysis of the previous studies illustrates the importance of learning for probabilistic inferences.
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Directory of Open Access Journals (Sweden)
Andreja Hrašovec-Lampret
2016-07-01
Full Text Available With selecting K compatible blood for transfusion, we prevent K immunization and many unnecessary prenatal testing and gynecological examinations for at least 78% of pregnant women with K negative partners, whose fetus is not at risk of hemolytic disease of fetus and newborn. Abstract Background Kell antibodies are beside RhD and c antibodies one of most clinically important antibodies that can cause severe hemolytic disease of the fetus and newborn (HDFN in pregnancy,which is still remaining one of the major causes of perinatal morbidity and mortality. Therefore, pregnant women with eryhrocyte alloantibodies anti-K need many prenatal testing and gynecological examinations. The major cause for anti-K immunisation is transfusion of incompatible blood in the past. Methods We analysed retrospectively the data of 71 pregnant woman with alloantibodies anti-K, which were followed in Blood Transfusion Centre of Slovenia from 2004 -2014. We collected data of partner´s phenotype and woman´s transfusion history. Data were statistically analyzed with basic statistical methods. Results 61 out of 71 partners were tested (86% and 48 were K negative (78%.The transfusion history was available for only 23 women (32%. The transfusion history was available for 23 out of 48 women with K negative partner (48%. All of them were transfused. 78% received incompatible-K positive blood, for the rest 22% women donations they received were not K typed. Conclusions From the obtained data, we found that in 78% of cases cause for K alloimunnization is transfusion of K incompatible blood in past. With selecting K compatible blood for transfusion, we can prevent K immunization and many unnecessary prenatal testing and gynecological examinations for 78% pregnant women with K negative partners .
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Islam, Md. Aminul; Rahim, Noor Asliza Abdul; Liang, Tan Chee; Momtaz, Hasina
2011-01-01
This research attempted to find out the effect of demographic factors on the effectiveness of the e-learning system in a higher learning Institution. The students from this institution were randomly selected in order to evaluate the effectiveness of learning system in student's learning process. The primary data source is the questionnaires that…
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LEARNING AS A TOOL FOR CANCER PREVENTION THROUGH THE ACQUISITION OF NEW DIETARY HABITS AND BEHAVIORS
Directory of Open Access Journals (Sweden)
J. F. Brito
2015-08-01
Full Text Available The need to promote knowledge of health entails, in part, by encouraging healthy eating habits. The creation of popular science materials, especially at schools, by promoting guidance for the eating habits is presented as an important tool. Foods that contain bioactive compounds are called nutraceutical foods and about 35% of various cancers occur due to inadequate diets. Conventional therapies are used in the treatment of cancer, even though they are efficient in fighting tumors, to cause many harmful effects to the patient, and therefore the researches for alternative therapies have increased. Especially those act strengthening the immunologic system. The mushrooms are able to modulate carcinogenesis in all stages of the disease through different mechanisms of action of the bioactive compounds, thus having an antitumor effect that is assigned to restore and improve the immune response through stimulation of cellular immunity which are present polysaccharides the composition of the mushrooms, such as beta-glucans that besides the anticancer effect, it still has activity as immunostimulant, antioxidant, anti-inflammatory, which are already used in Japan as drugs for treating cancer patients. The aim of this work was to use learning as a tool for acquiring habits and eating behaviors in the general community and ownership and acquisition of knowledge about the antitumor potential of bioactive compounds in foods which are applied in cancer prevention through the scientific dissemination / education. Because it is a popular science work using written material and the dissemination of the material make for yourself the methodology used for the dissemination of scientific knowledge. Thus, the inclusion of consumption of mushrooms in the diet may represent an important step in the cancer prevention as the best form of prevention, and therefore it shows the need for available information to everyone, as it has proposed this work, disclosure.
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Selective effects of explanation on learning during early childhood.
Legare, Cristine H; Lombrozo, Tania
2014-10-01
Two studies examined the specificity of effects of explanation on learning by prompting 3- to 6-year-old children to explain a mechanical toy and comparing what they learned about the toy's causal and non-causal properties with children who only observed the toy, both with and without accompanying verbalization. In Study 1, children were experimentally assigned to either explain or observe the mechanical toy. In Study 2, children were classified according to whether the content of their response to an undirected prompt involved explanation. Dependent measures included whether children understood the toy's functional-mechanical relationships, remembered perceptual features of the toy, effectively reconstructed the toy, and (for Study 2) generalized the function of the toy when constructing a new one. Results demonstrate that across age groups, explanation promotes causal learning and generalization but does not improve (and in younger children can even impair) memory for causally irrelevant perceptual details. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.
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Exercise, learned helplessness, and the stress-resistant brain.
Greenwood, Benjamin N; Fleshner, Monika
2008-01-01
Exercise can prevent the development of stress-related mood disorders, such as depression and anxiety. The underlying neurobiological mechanisms of this effect, however, remain unknown. Recently, researchers have used animal models to begin to elucidate the potential mechanisms underlying the protective effects of physical activity. Using the behavioral consequences of uncontrollable stress or "learned helplessness" as an animal analog of depression- and anxiety-like behaviors in rats, we are investigating factors that could be important for the antidepressant and anxiolytic properties of exercise (i.e., wheel running). The current review focuses on the following: (1) the effect of exercise on the behavioral consequences of uncontrollable stress and the implications of these effects on the specificity of the "learned helplessness" animal model; (2) the neurocircuitry of learned helplessness and the role of serotonin; and (3) exercise-associated neural adaptations and neural plasticity that may contribute to the stress-resistant brain. Identifying the mechanisms by which exercise prevents learned helplessness could shed light on the complex neurobiology of depression and anxiety and potentially lead to novel strategies for the prevention of stress-related mood disorders.
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Intervention with the Selectively Mute Child.
Porjes, Michelle D.
1992-01-01
Defines selective mutism as describing children who actively choose to speak to few people in selected environments, noting it is most commonly used to describe nonverbal behavior in school setting. Reviews literature from psychoanalytic and learning theory approaches. Presents intervention strategies used with two selectively mute first graders.…
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Huelsmann, Martin; Neuhold, Stephanie; Resl, Michael; Strunk, Guido; Brath, Helmut; Francesconi, Claudia; Adlbrecht, Christopher; Prager, Rudolf; Luger, Anton; Pacher, Richard; Clodi, Martin
2013-10-08
The study sought to assess the primary preventive effect of neurohumoral therapy in high-risk diabetic patients selected by N-terminal pro-B-type natriuretic peptide (NT-proBNP). Few clinical trials have successfully demonstrated the prevention of cardiac events in patients with diabetes. One reason for this might be an inaccurate selection of patients. NT-proBNP has not been assessed in this context. A total of 300 patients with type 2 diabetes, elevated NT-proBNP (>125 pg/ml) but free of cardiac disease were randomized. The "control" group was cared for at 4 diabetes care units; the "intensified" group was additionally treated at a cardiac outpatient clinic for the up-titration of renin-angiotensin system (RAS) antagonists and beta-blockers. The primary endpoint was hospitalization/death due to cardiac disease after 2 years. At baseline, the mean age of the patients was 67.5 ± 9 years, duration of diabetes was 15 ± 12 years, 37% were male, HbA1c was 7 ± 1.1%, blood pressure was 151 ± 22 mm Hg, heart rate was 72 ± 11 beats/min, median NT-proBNP was 265.5 pg/ml (interquartile range: 180.8 to 401.8 pg/ml). After 12 months there was a significant difference between the number of patients treated with a RAS antagonist/beta-blocker and the dosage reached between groups (p titration of RAS antagonists and beta-blockers to maximum tolerated dosages is an effective and safe intervention for the primary prevention of cardiac events for diabetic patients pre-selected using NT-proBNP. (Nt-proBNP Guided Primary Prevention of CV Events in Diabetic Patients [PONTIAC]; NCT00562952). Copyright © 2013 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.
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Selective role for DNMT3a in learning and memory.
Morris, Michael J; Adachi, Megumi; Na, Elisa S; Monteggia, Lisa M
2014-11-01
Methylation of cytosine nucleotides is governed by DNA methyltransferases (DNMTs) that establish de novo DNA methylation patterns in early embryonic development (e.g., DNMT3a and DNMT3b) or maintain those patterns on hemimethylated DNA in dividing cells (e.g., DNMT1). DNMTs continue to be expressed at high levels in mature neurons, however their impact on neuronal function and behavior are unclear. To address this issue we examined DNMT1 and DNMT3a expression following associative learning. We also generated forebrain specific conditional Dnmt1 or Dnmt3a knockout mice and characterized them in learning and memory paradigms as well as for alterations in long-term potentiation (LTP) and synaptic plasticity. Here, we report that experience in an associative learning task impacts expression of Dnmt3a, but not Dnmt1, in brain areas that mediate learning of this task. We also found that Dnmt3a knockout mice, and not Dnmt1 knockouts have synaptic alterations as well as learning deficits on several associative and episodic memory tasks. These findings indicate that the de novo DNA methylating enzyme DNMT3a in postmitotic neurons is necessary for normal memory formation and its function cannot be substituted by the maintenance DNA methylating enzyme DNMT1. Copyright © 2014 Elsevier Inc. All rights reserved.
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Directory of Open Access Journals (Sweden)
Yücel Yılmaz
2016-04-01
Full Text Available The concept of learning has been increasingly gaining importance for individuals, businesses and communities in the age of information. On the other hand, developments in information and communication technologies take effect in the field of learning activities. With these technologies, barriers of time and space against the learning activities largely disappear and these technologies make it easier to carry out these activities more effectively. There remain a lot of questions regarding selection of learning management system (LMS to be used for the management of e-learning processes by all organizations conducing educational practices including universities, companies, non-profit organizations, etc. The main questions are as follows: Shall we choose open source LMS or commercial LMS? Can the selected LMS meet existing needs and future potential needs for the organization? What are the possibilities of technical support in the management of LMS? What kind of problems may be experienced in the use of LMS and how can these problems be solved? How much effective can officials in the organization be in the management of LMS? In this study, primarily e-learning and the concept of LMS will be discussed, and in the next section, as for answers to these questions, open source LMSs and centrally developed LMSs will be examined and their advantages and disadvantages relative to each other will be discussed.
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Directory of Open Access Journals (Sweden)
Newton Nicola C
2012-08-01
Full Text Available Abstract Background Alcohol misuse amongst young people is a serious concern. The need for effective prevention is clear, yet there appear to be few evidenced-based programs that prevent alcohol misuse and none that target both high and low-risk youth. The CAP study addresses this gap by evaluating the efficacy of an integrated approach to alcohol misuse prevention, which combines the effective universal internet-based Climate Schools program with the effective selective personality-targeted Preventure program. This article describes the development and protocol of the CAP study which aims to prevent alcohol misuse and related harms in Australian adolescents. Methods/Design A cluster randomized controlled trial (RCT is being conducted with Year 8 students aged 13 to 14-years-old from 27 secondary schools in New South Wales and Victoria, Australia. Blocked randomisation was used to assign schools to one of four groups; Climate Schools only, Preventure only, CAP (Climate Schools and Preventure, or Control (alcohol, drug and health education as usual. The primary outcomes of the trial will be the uptake and harmful use of alcohol and alcohol related harms. Secondary outcomes will include alcohol and cannabis related knowledge, cannabis related harms, intentions to use, and mental health symptomatology. All participants will complete assessments on five occasions; baseline; immediately post intervention, and at 12, 24 and 36 months post baseline. Discussion This study protocol presents the design and current implementation of a cluster RCT to evaluate the efficacy of the CAP study; an integrated universal and selective approach to prevent alcohol use and related harms among adolescents. Compared to students who receive the stand-alone universal Climate Schools program or alcohol and drug education as usual (Controls, we expect the students who receive the CAP intervention to have significantly less uptake of alcohol use, a reduction in average
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Lammers, Jeroen; Goossens, Ferry; Conrod, Patricia; Engels, Rutger; Wiers, Reinout W; Kleinjan, Marloes
2017-08-01
To explore whether specific groups of adolescents (i.e., scoring high on personality risk traits, having a lower education level, or being male) benefit more from the Preventure intervention with regard to curbing their drinking behaviour. A clustered randomized controlled trial, with participants randomly assigned to a 2-session coping skills intervention or a control no-intervention condition. Fifteen secondary schools throughout The Netherlands; 7 schools in the intervention and 8 schools in the control condition. 699 adolescents aged 13-15; 343 allocated to the intervention and 356 to the control condition; with drinking experience and elevated scores in either negative thinking, anxiety sensitivity, impulsivity or sensation seeking. Differential effectiveness of the Preventure program was examined for the personality traits group, education level and gender on past-month binge drinking (main outcome), binge frequency, alcohol use, alcohol frequency and problem drinking, at 12months post-intervention. Preventure is a selective school-based alcohol prevention programme targeting personality risk factors. The comparator was a no-intervention control. Intervention effects were moderated by the personality traits group and by education level. More specifically, significant intervention effects were found on reducing alcohol use within the anxiety sensitivity group (OR=2.14, CI=1.40, 3.29) and reducing binge drinking (OR=1.76, CI=1.38, 2.24) and binge drinking frequency (β=0.24, p=0.04) within the sensation seeking group at 12months post-intervention. Also, lower educated young adolescents reduced binge drinking (OR=1.47, CI=1.14, 1.88), binge drinking frequency (β=0.25, p=0.04), alcohol use (OR=1.32, CI=1.06, 1.65) and alcohol use frequency (β=0.47, p=0.01), but not those in the higher education group. Post hoc latent-growth analyses revealed significant effects on the development of binge drinking (β=-0.19, p=0.02) and binge drinking frequency (β=-0.10, p=0
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Preventing Prescription Drug Overdose PSA (:60)
Centers for Disease Control (CDC) Podcasts
This 60 second public service announcement is based on the July 2014 CDC Vital Signs report. Every day, 46 people in the U.S. die from an overdose of prescription opioid painkillers. Learn what can be done to make painkiller prescribing safer and help prevent overdoses.
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International Nuclear Information System (INIS)
Salcedo-Sanz, S.; Pastor-Sánchez, A.; Prieto, L.; Blanco-Aguilera, A.; García-Herrera, R.
2014-01-01
Highlights: • A novel approach for short-term wind speed prediction is presented. • The system is formed by a coral reefs optimization algorithm and an extreme learning machine. • Feature selection is carried out with the CRO to improve the ELM performance. • The method is tested in real wind farm data in USA, for the period 2007–2008. - Abstract: This paper presents a novel approach for short-term wind speed prediction based on a Coral Reefs Optimization algorithm (CRO) and an Extreme Learning Machine (ELM), using meteorological predictive variables from a physical model (the Weather Research and Forecast model, WRF). The approach is based on a Feature Selection Problem (FSP) carried out with the CRO, that must obtain a reduced number of predictive variables out of the total available from the WRF. This set of features will be the input of an ELM, that finally provides the wind speed prediction. The CRO is a novel bio-inspired approach, based on the simulation of reef formation and coral reproduction, able to obtain excellent results in optimization problems. On the other hand, the ELM is a new paradigm in neural networks’ training, that provides a robust and extremely fast training of the network. Together, these algorithms are able to successfully solve this problem of feature selection in short-term wind speed prediction. Experiments in a real wind farm in the USA show the excellent performance of the CRO–ELM approach in this FSP wind speed prediction problem
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2017-06-15
2, and 3). The selection scheme is implemented and released as an open-source active learning package. They have studied theories for designing...We have studied theories for designing algorithms for interactive learning with batch-like feedback (for 1) and algorithms for online digestion of... necessity on pre-training. The new idea provides layer-wise cost estimation with auxiliary nodes, and is applicable to a wider range of deep learning
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Centers for Disease Control (CDC) Podcasts
2011-11-16
Chronic obstructive pulmonary disease (COPD) is a serious lung disease that makes breathing very difficult and can affect your quality of life. Learn the causes of COPD and what you can do to prevent it. Created: 11/16/2011 by National Center for Chronic Disease Prevention and Health Promotion, Division of Adult and Community Health (NCCDPHP, DACH). Date Released: 11/16/2011.
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Seamons, Todd R; Hauser, Lorenz; Naish, Kerry A; Quinn, Thomas P
2012-01-01
Two strategies have been proposed to avoid negative genetic effects of artificially propagated individuals on wild populations: (i) integration of wild and captive populations to minimize domestication selection and (ii) segregation of released individuals from the wild population to minimize interbreeding. We tested the efficacy of the strategy of segregation by divergent life history in a steelhead trout, Oncorhynchus mykiss, system, where hatchery fish were selected to spawn months earlier than the indigenous wild population. The proportion of wild ancestry smolts and adults declined by 10–20% over the three generations since the hatchery program began. Up to 80% of the naturally produced steelhead in any given year were hatchery/wild hybrids. Regression model selection analysis showed that the proportion of hatchery ancestry smolts was lower in years when stream discharge was high, suggesting a negative effect of flow on reproductive success of early-spawning hatchery fish. Furthermore, proportions of hybrid smolts and adults were higher in years when the number of naturally spawning hatchery-produced adults was higher. Divergent life history failed to prevent interbreeding when physical isolation was ineffective, an inadequacy that is likely to prevail in many other situations. PMID:23144657
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Predicting and preventing organizational failure: learning, stability and safety culture
International Nuclear Information System (INIS)
Duffey, R.B.
2009-01-01
The physical definition of 'safety culture' is the creation of an organizational and operational structure that places unending emphasis on safety at every level. We propose and prefer the use of the term and the objective of sustaining a 'Learning Environment', where mistakes, outcomes and errors are used as learning vehicles to improve, and we can now define why that is true. Therefore we can manage and quantify safety effectively tracking and analyzing outcomes, using the trends to guide our needed organizational behaviors. (author)
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Development, Awareness and Inductive Selectivity
Hayes, Brett K.; Lim, Melissa
2013-01-01
Two studies examined whether adults and children could learn to make context-dependent inferences about novel stimuli and the role of awareness of context cues in such learning. Participants were trained to match probes to targets on the basis of shape or color with the relevant dimension shifting according to item context. A selective induction…
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Core Competencies for Injury and Violence Prevention
Stephens-Stidham, Shelli; Peek-Asa, Corinne; Bou-Saada, Ingrid; Hunter, Wanda; Lindemer, Kristen; Runyan, Carol
2009-01-01
Efforts to reduce the burden of injury and violence require a workforce that is knowledgeable and skilled in prevention. However, there has been no systematic process to ensure that professionals possess the necessary competencies. To address this deficiency, we developed a set of core competencies for public health practitioners in injury and violence prevention programs. The core competencies address domains including public health significance, data, the design and implementation of prevention activities, evaluation, program management, communication, stimulating change, and continuing education. Specific learning objectives establish goals for training in each domain. The competencies assist in efforts to reduce the burden of injury and violence and can provide benchmarks against which to assess progress in professional capacity for injury and violence prevention. PMID:19197083
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Preventing Stroke Deaths PSA (:60)
Centers for Disease Control (CDC) Podcasts
2017-09-06
This 60 second public service announcement is based on the July 2017 CDC Vital Signs report. Higher opioid prescribing puts patients at risk for addiction and overdose. Learn what can be done about this serious problem. Created: 9/6/2017 by Centers for Disease Control and Prevention (CDC). Date Released: 9/6/2017.
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Political learning among youth
DEFF Research Database (Denmark)
Solhaug, Trond; Kristensen, Niels Nørgaard
2014-01-01
This article focuses on students’ first political learning and explores the research question, what dynamic patterns of political learning can be explored among a selection of young, diverse Danish students’ first political interests? The authors use theories of learning in their analytical......, but are active constructors of their political life. Their emotions and social environment are highly important for their political orientation. It is recommended that further research focus on dynamic learning and on arenas for political learning rather than on “single agent studies.” Recommendations...
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Apisitwasana, Nipaporn; Perngparn, Usaneya; Cottler, Linda B
2018-01-01
Purpose This study aimed to assess the effectiveness of Participatory Learning School and Family Based Intervention Program for Preventing Game Addiction by Developing Self-Regulation of gaming addiction among students of grades 4 and 5 in Bangkok. Methods A quasi-experimental study was implemented among students of grades 4 and 5 at primary schools in Bangkok selected through multistage random sampling. Two comparable schools were randomly assigned to either the intervention or control group. Then, 310 students in the randomly selected classrooms were allocated to each group. The intervention group received the self-regulation program with school and family involvement to prevent gaming addiction. Master teachers attended in-house training on prevention of gaming addiction in children. Parents of these children received a gaming addiction prevention manual and guidelines. The program lasted 8 weeks. The control group received no intervention. Knowledge and Attitude About Gaming Questionnaire, Game Addiction Screening Test (GAST), and Game Addiction Protection Scale were utilized to assess subjects at baseline, immediately after, and 3 months post-intervention. Descriptive statistics, chi-square, and independent t-test were used to describe characteristics of the participants, and repeated measures ANOVA was analyzed to test the effectiveness of the intervention. Results The findings revealed that there were significant differences in knowledge, attitude, self-regulation, and gaming addiction behaviors (p effects of the intervention included increase in knowledge, attitude, and self-regulation, whereas the GAST score was significantly decreased (p effective for preventing gaming addiction in students of grades 4 and 5 in Bangkok, Thailand. PMID:29695939
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Personal Learning Environments for Supporting Out-of-Class Language Learning
Reinders, Hayo
2014-01-01
A Personal Learning Environment (PLE) it is a combination of tools (usually digital) and resources chosen by the learner to support different aspects of the learning process, from goal setting to materials selection to assessment. The importance of PLEs for teachers lies in their ability to help students develop autonomy and prepare them for…
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Unsupervised Feature Subset Selection
DEFF Research Database (Denmark)
Søndberg-Madsen, Nicolaj; Thomsen, C.; Pena, Jose
2003-01-01
This paper studies filter and hybrid filter-wrapper feature subset selection for unsupervised learning (data clustering). We constrain the search for the best feature subset by scoring the dependence of every feature on the rest of the features, conjecturing that these scores discriminate some ir...... irrelevant features. We report experimental results on artificial and real data for unsupervised learning of naive Bayes models. Both the filter and hybrid approaches perform satisfactorily....
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Maltreatment in early childhood: a scoping review of prevention, detection and treatment
Directory of Open Access Journals (Sweden)
Luis Lefio Celedón
2013-08-01
Full Text Available Purpose. To identify and synthesize the best available evidence on the effectiveness of interventions for universal prevention, detection and treatment of early childhood maltreatment (0-4 years. Design. Scoping Review. Data sources. MEDLINE, LILACS, PsycINFO, Psyclist, SciELO, ISI Web of Knowledge, Science Direct, EBSCO, EMBASE, Cochrane Library, DARE, Google Scholar and UNICEF Base. Methods. A variety of keywords were used to identify quantitative experimental and observational studies on detection, prevention and treatment strategies in different situations of child maltreatment. Sexual abuse was excluded. The search spanned from 2002 to 2012, in English and Spanish. Results. Of 105 articles, 36 met the selection criteria. In prevention, the best evaluated strategies were parenting programs based on cognitive or cognitive-behavioral approach and interactive learning strategies. In detection, only two instruments were identified with optimum specificity and positive predictive value. In treatment, a variety of treatment strategies were identified with favorable effects on behavioral, functional and psycho affective indicators. The population relevance of these interventions is unclear, as the differential effectiveness of these therapeutic approaches. Conclusions. There are many child maltreatment prevention strategies at the individual and family level. The instruments used for detection are not reliable for use at the collective level. Insofar as therapy, not enough evidence was found both in quality and quantity to favor one intervention over another. It is recommended to understand the problem from the public health perspective and to generate multisectoral and interdisciplinary approaches.
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Artini, Marco; Patsilinakos, Alexandros; Papa, Rosanna; Božović, Mijat; Sabatino, Manuela; Garzoli, Stefania; Vrenna, Gianluca; Tilotta, Marco; Pepi, Federico; Ragno, Rino; Selan, Laura
2018-02-23
Pseudomonas aeruginosa is a ubiquitous organism and opportunistic pathogen that can cause persistent infections due to its peculiar antibiotic resistance mechanisms and to its ability to adhere and form biofilm. The interest in the development of new approaches for the prevention and treatment of biofilm formation has recently increased. The aim of this study was to seek new non-biocidal agents able to inhibit biofilm formation, in order to counteract virulence rather than bacterial growth and avoid the selection of escape mutants. Herein, different essential oils extracted from Mediterranean plants were analyzed for their activity against P. aeruginosa . Results show that they were able to destabilize biofilm at very low concentration without impairing bacterial viability. Since the action is not related to a bacteriostatic/bactericidal activity on P. aeruginosa , the biofilm change of growth in presence of the essential oils was possibly due to a modulation of the phenotype. To this aim, application of machine learning algorithms led to the development of quantitative activity-composition relationships classification models that allowed to direct point out those essential oil chemical components more involved in the inhibition of biofilm production. The action of selected essential oils on sessile phenotype make them particularly interesting for possible applications such as prevention of bacterial contamination in the community and in healthcare environments in order to prevent human infections. We assayed 89 samples of different essential oils as P. aeruginosa anti-biofilm. Many samples inhibited P. aeruginosa biofilm at concentrations as low as 48.8 µg/mL. Classification of the models was developed through machine learning algorithms.
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Comparison of feature selection and classification for MALDI-MS data
Directory of Open Access Journals (Sweden)
Yang Mary
2009-07-01
Full Text Available Abstract Introduction In the classification of Mass Spectrometry (MS proteomics data, peak detection, feature selection, and learning classifiers are critical to classification accuracy. To better understand which methods are more accurate when classifying data, some publicly available peak detection algorithms for Matrix assisted Laser Desorption Ionization Mass Spectrometry (MALDI-MS data were recently compared; however, the issue of different feature selection methods and different classification models as they relate to classification performance has not been addressed. With the application of intelligent computing, much progress has been made in the development of feature selection methods and learning classifiers for the analysis of high-throughput biological data. The main objective of this paper is to compare the methods of feature selection and different learning classifiers when applied to MALDI-MS data and to provide a subsequent reference for the analysis of MS proteomics data. Results We compared a well-known method of feature selection, Support Vector Machine Recursive Feature Elimination (SVMRFE, and a recently developed method, Gradient based Leave-one-out Gene Selection (GLGS that effectively performs microarray data analysis. We also compared several learning classifiers including K-Nearest Neighbor Classifier (KNNC, Naïve Bayes Classifier (NBC, Nearest Mean Scaled Classifier (NMSC, uncorrelated normal based quadratic Bayes Classifier recorded as UDC, Support Vector Machines, and a distance metric learning for Large Margin Nearest Neighbor classifier (LMNN based on Mahanalobis distance. To compare, we conducted a comprehensive experimental study using three types of MALDI-MS data. Conclusion Regarding feature selection, SVMRFE outperformed GLGS in classification. As for the learning classifiers, when classification models derived from the best training were compared, SVMs performed the best with respect to the expected testing
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Learning Multirobot Hose Transportation and Deployment by Distributed Round-Robin Q-Learning.
Directory of Open Access Journals (Sweden)
Borja Fernandez-Gauna
Full Text Available Multi-Agent Reinforcement Learning (MARL algorithms face two main difficulties: the curse of dimensionality, and environment non-stationarity due to the independent learning processes carried out by the agents concurrently. In this paper we formalize and prove the convergence of a Distributed Round Robin Q-learning (D-RR-QL algorithm for cooperative systems. The computational complexity of this algorithm increases linearly with the number of agents. Moreover, it eliminates environment non sta tionarity by carrying a round-robin scheduling of the action selection and execution. That this learning scheme allows the implementation of Modular State-Action Vetoes (MSAV in cooperative multi-agent systems, which speeds up learning convergence in over-constrained systems by vetoing state-action pairs which lead to undesired termination states (UTS in the relevant state-action subspace. Each agent's local state-action value function learning is an independent process, including the MSAV policies. Coordination of locally optimal policies to obtain the global optimal joint policy is achieved by a greedy selection procedure using message passing. We show that D-RR-QL improves over state-of-the-art approaches, such as Distributed Q-Learning, Team Q-Learning and Coordinated Reinforcement Learning in a paradigmatic Linked Multi-Component Robotic System (L-MCRS control problem: the hose transportation task. L-MCRS are over-constrained systems with many UTS induced by the interaction of the passive linking element and the active mobile robots.
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DEFF Research Database (Denmark)
Keiding, Tina Bering
2007-01-01
This article offers a re-description of the concept of learning context. Drawing on Niklas Luhmann and Gregory Bateson it suggests an alternative to situated, social learning and activity theory. The conclusion is that learning context designates an individual's reconstruction of the environment...... through contingent handling of differences and that the individual emerge as learning through the actual construction. Selection of differences is influenced by the learner's actual knowledge, the nature of the environment and the current horizon of meaning in which the current adaptive perspective...... becomes a significant factor. The re-description contributes to didaktik through renewed understandings of participants' background in teaching and learning....
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Knowlden, Adam P; Sharma, Manoj
2014-09-01
Family-and-home-based interventions are an important vehicle for preventing childhood obesity. Systematic process evaluations have not been routinely conducted in assessment of these interventions. The purpose of this study was to plan and conduct a process evaluation of the Enabling Mothers to Prevent Pediatric Obesity Through Web-Based Learning and Reciprocal Determinism (EMPOWER) randomized control trial. The trial was composed of two web-based, mother-centered interventions for prevention of obesity in children between 4 and 6 years of age. Process evaluation used the components of program fidelity, dose delivered, dose received, context, reach, and recruitment. Categorical process evaluation data (program fidelity, dose delivered, dose exposure, and context) were assessed using Program Implementation Index (PII) values. Continuous process evaluation variables (dose satisfaction and recruitment) were assessed using ANOVA tests to evaluate mean differences between groups (experimental and control) and sessions (sessions 1 through 5). Process evaluation results found that both groups (experimental and control) were equivalent, and interventions were administered as planned. Analysis of web-based intervention process objectives requires tailoring of process evaluation models for online delivery. Dissemination of process evaluation results can advance best practices for implementing effective online health promotion programs. © 2014 Society for Public Health Education.
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Lessons to be learned from an analysis of ammonium nitrate disasters in the last 100 years
Energy Technology Data Exchange (ETDEWEB)
Pittman, William; Han, Zhe; Harding, Brian; Rosas, Camilo; Jiang, Jiaojun; Pineda, Alba; Mannan, M. Sam, E-mail: mannan@tamu.edu
2014-09-15
Highlights: • Root causes and contributing factors from ammonium nitrate incidents are categorized into 10 lessons. • The lessons learned from the past 100 years of ammonium nitrate incidents can be used to improve design, operation, and maintenance procedures. • Improving organizational memory to help improve safety performance. • Combating and changing organizational cultures. - Abstract: Process safety, as well as the safe storage and transportation of hazardous or reactive chemicals, has been a topic of increasing interest in the last few decades. The increased interest in improving the safety of operations has been driven largely by a series of recent catastrophes that have occurred in the United States and the rest of the world. A continuous review of past incidents and disasters to look for common causes and lessons is an essential component to any process safety and loss prevention program. While analyzing the causes of an accident cannot prevent that accident from occurring, learning from it can help to prevent future incidents. The objective of this article is to review a selection of major incidents involving ammonium nitrate in the last century to identify common causes and lessons that can be gleaned from these incidents in the hopes of preventing future disasters. Ammonium nitrate has been involved in dozens of major incidents in the last century, so a subset of major incidents were chosen for discussion for the sake of brevity. Twelve incidents are reviewed and ten lessons from these incidents are discussed.
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Lessons to be learned from an analysis of ammonium nitrate disasters in the last 100 years
International Nuclear Information System (INIS)
Pittman, William; Han, Zhe; Harding, Brian; Rosas, Camilo; Jiang, Jiaojun; Pineda, Alba; Mannan, M. Sam
2014-01-01
Highlights: • Root causes and contributing factors from ammonium nitrate incidents are categorized into 10 lessons. • The lessons learned from the past 100 years of ammonium nitrate incidents can be used to improve design, operation, and maintenance procedures. • Improving organizational memory to help improve safety performance. • Combating and changing organizational cultures. - Abstract: Process safety, as well as the safe storage and transportation of hazardous or reactive chemicals, has been a topic of increasing interest in the last few decades. The increased interest in improving the safety of operations has been driven largely by a series of recent catastrophes that have occurred in the United States and the rest of the world. A continuous review of past incidents and disasters to look for common causes and lessons is an essential component to any process safety and loss prevention program. While analyzing the causes of an accident cannot prevent that accident from occurring, learning from it can help to prevent future incidents. The objective of this article is to review a selection of major incidents involving ammonium nitrate in the last century to identify common causes and lessons that can be gleaned from these incidents in the hopes of preventing future disasters. Ammonium nitrate has been involved in dozens of major incidents in the last century, so a subset of major incidents were chosen for discussion for the sake of brevity. Twelve incidents are reviewed and ten lessons from these incidents are discussed
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Selective Reproductive Technologies
DEFF Research Database (Denmark)
Gammeltoft, Tine; Wahlberg, Ayo
2014-01-01
From a historical perspective, selective reproduction is nothing new. Infanticide, abandonment, and selective neglect of children have a long history, and the widespread deployment of sterilization and forced abortion in the twentieth century has been well documented. Yet in recent decades select......, discussing how selective reproduction engages with issues of long-standing theoretical concern in anthropology, such as politics, kinship, gender, religion, globalization, and inequality....... (ARTs), what we term selective reproductive technologies (SRTs) are of a more specific nature: Rather than aiming to overcome infertility, they are used to prevent or allow the birth of certain kinds of children. This review highlights anthropological research into SRTs in different parts of the world...
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White, Meagan; Shellenbarger, Teresa
E-learning provides an alternative approach to traditional professional development activities. A learning management system may help nursing professional development practitioners deliver content more efficiently and effectively; however, careful consideration is needed during planning and implementation. This article provides essential information in the selection and use of a learning management system for professional development.
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[An evaluation of a new Dutch suicide prevention tool (KEHR); datadriven evaluation and learning].
de Groot, M H; de Winter, R F P; van der Plas, W; Kerkhof, A J F M
2016-01-01
Multidisciplinary evaluation of suicide cases effectively decreases the suicide rate in mental health care. A new suicide prevention tool (KEHR) can be used in this connection. KEHR has been developed on the basis of the Dutch multidisciplinary practice guideline on the assessment and treatment of suicidal behaviour. The guideline can serve as a frame of reference for the multidisciplinary evaluation of suicide cases. KEHR aims to provide professionals with a better method for preventing suicide. To describe and evaluate the recently developed KEHR strategy for reducing the number of suicide cases in mental health care. Naturalistic and observational study. In the course of a year 22 out of 23 suicide cases that had occurred in the pilot institution were evaluated with the help of the KEHR system. Outcomes were discussed with members of multidisciplinary teams. Quantitative and qualitative methods were used in the evaluation process. Professionals from the main disciplines involved were very willing to use the new tool and were prepared to reflect on their views on the outcomes. The professionals were ready to learn from the suicide cases. Data collected with the tool provided information that can be used to improve guideline adherence. However, the use of KEHR did not lead automatically to the formulation of adjustments and improvements relating to suicidal patients. A specific procedure for improving individual and team performance needs to be developed and tested thoroughly. KEHR is a promising strategy for improving and enhancing the guideline on the diagnosis and treatment of suicidal behaviour of patients in mental health care. Special procedures need to be developed and studied in order to implement the improvements deemed necessary as a result of the pilot study. The KEHR tool (in the Dutch language) is accessible to mental health care workers after online registration (www.mijnkehr.nl).
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... well, such as tickets to a concert or movie. Alternative Names Prevention - learn to love exercise; Wellness - ... 23630089 www.ncbi.nlm.nih.gov/pubmed/23630089 . Review Date 5/21/2016 Updated by: Linda J. ...
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Bozkurt, Sinan
2018-01-01
There are several different methods of learning motor skills, like traditional (linear) and differential (nonlinear) learning training. The traditional motor learning approach proposes that learners improve a skill just by repeating it. According to the teaching principles, exercises are selected along continua from easy to hard and from simple to…
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Santa, Tomofumi; Kirino, Yutaka; Watanabe, Satoshi; Shirahata, Takaaki; Tsunoda, Makoto
2006-01-01
The terrestrial slug "Limax" is able to acquire short-term and long-term memories during aversive odor-taste associative learning. We investigated the effect of the selective serotonergic neurotoxin 5,7-dihydroxytryptamine (5,7-DHT) on memory. Behavioral studies indicated that 5,7-DHT impaired short-term memory but not long-term memory. HPLC…
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Active Learning by Querying Informative and Representative Examples.
Huang, Sheng-Jun; Jin, Rong; Zhou, Zhi-Hua
2014-10-01
Active learning reduces the labeling cost by iteratively selecting the most valuable data to query their labels. It has attracted a lot of interests given the abundance of unlabeled data and the high cost of labeling. Most active learning approaches select either informative or representative unlabeled instances to query their labels, which could significantly limit their performance. Although several active learning algorithms were proposed to combine the two query selection criteria, they are usually ad hoc in finding unlabeled instances that are both informative and representative. We address this limitation by developing a principled approach, termed QUIRE, based on the min-max view of active learning. The proposed approach provides a systematic way for measuring and combining the informativeness and representativeness of an unlabeled instance. Further, by incorporating the correlation among labels, we extend the QUIRE approach to multi-label learning by actively querying instance-label pairs. Extensive experimental results show that the proposed QUIRE approach outperforms several state-of-the-art active learning approaches in both single-label and multi-label learning.
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Centers for Disease Control (CDC) Podcasts
Chronic obstructive pulmonary disease (COPD) is a serious lung disease that makes breathing very difficult and can affect your quality of life. Learn the causes of COPD and what you can do to prevent it.
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Hooker, Carol E.
1976-01-01
Learned helplessness--the belief that a person's actions have no influence on the outcome of an event--is similar in many respects to the crisis state and depression. The author shows how this impaired social and psychological functioning occurs and identifies techniques that the social worker can use to prevent it. (Author)
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Mosaic model for sensorimotor learning and control.
Haruno, M; Wolpert, D M; Kawato, M
2001-10-01
Humans demonstrate a remarkable ability to generate accurate and appropriate motor behavior under many different and often uncertain environmental conditions. We previously proposed a new modular architecture, the modular selection and identification for control (MOSAIC) model, for motor learning and control based on multiple pairs of forward (predictor) and inverse (controller) models. The architecture simultaneously learns the multiple inverse models necessary for control as well as how to select the set of inverse models appropriate for a given environment. It combines both feedforward and feedback sensorimotor information so that the controllers can be selected both prior to movement and subsequently during movement. This article extends and evaluates the MOSAIC architecture in the following respects. The learning in the architecture was implemented by both the original gradient-descent method and the expectation-maximization (EM) algorithm. Unlike gradient descent, the newly derived EM algorithm is robust to the initial starting conditions and learning parameters. Second, simulations of an object manipulation task prove that the architecture can learn to manipulate multiple objects and switch between them appropriately. Moreover, after learning, the model shows generalization to novel objects whose dynamics lie within the polyhedra of already learned dynamics. Finally, when each of the dynamics is associated with a particular object shape, the model is able to select the appropriate controller before movement execution. When presented with a novel shape-dynamic pairing, inappropriate activation of modules is observed followed by on-line correction.
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Some social and health policy requirements for the prevention of AIDS.
Rosenbrock, R
1987-01-01
Given the present circumstances and considering the foreseeable development of medical knowledge, the primary prevention of AIDS is the sole field of health policy in which the spreading of the disease and the subsequent number of victims can be reduced. AIDS prevention as a time-stable behaviour control in potentially risky situations is therefore primarily a task which has to be tackled in a social scientific manner. It has to be handled on the basis of available medical knowledge of infectious disease situations. Viewed realistically, the prospective goal is not the elimination of the disease, but the greatest possible reduction and minimization of risk, both individually and epidemiologically. Proceeding from realistic estimates of the desired and undesired effects of health policy measures, this principle is being applied through the strategy (achieved through informational campaigns) of encouraging the use of condoms when having sexual intercourse in non-monogamous relationships and of informing intravenous drug abusers of the need to employ sterile hypodermic needles. Elements of this preventive strategy are discussed under four central questions: What should/must be learn? Who should/must learn? What objective and subjective factors facilitate or hinder this learning? How can this learning process most optimally be organized? The efficiency-reducing interference of other kinds of strategies (e.g. orientation toward zero risk concepts, repression, and mass screening for HIV-anti-bodies) is thereby worked out.
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de Smet, Anne Marie G. A.; Kluytmans, Jan A. J. W.; Blok, Hetty E. M.; Mascini, Ellen M.; Benus, Robin F. J.; Bernards, Alexandra T.; Kuijper, Ed J.; Leverstein-van Hall, Maurine A.; Jansz, Arjan R.; de Jongh, Bartelt M.; van Asselt, Gerard J.; Frenay, Ine H. M. E.; Thijsen, Steven F. T.; Conijn, Simon N. M.; Kaan, Jan A.; Arends, Jan P.; Sturm, Patrick D. J.; Bootsma, Martin C. J.; Bonten, Marc J. M.
Background Previously, we assessed selective digestive tract decontamination (SDD) and selective oropharyngeal decontamination (SOD) on survival and prevention of bacteraemia in patients in intensive-care units. In this analysis, we aimed to assess effectiveness of these interventions for prevention
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Fear and Guilt in HIV and AIDS Prevention | Gwandure | Africa Insight
African Journals Online (AJOL)
The social learning theory concepts of fear and guilt are regarded as inhibitory factors in disease prevention, and this article examines the possibility of incorporating fear and guilt training courses into HIV and AIDS prevention programmes. HIV and AIDS educators could help participants understand the role of fear and guilt ...
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Primary prevention of psychiatric illness in special populations.
Sajatovic, Martha; Sanders, Renata; Alexeenko, Lada; Madhusoodanan, Subramoniam
2010-11-01
Some populations appear to be particularly vulnerable to the development of psychiatric symptomatology related to life events and biologic or social/cultural factors. Such groups include individuals who have experienced traumatic events, military personnel, individuals with serious medical conditions, postpartum women, and immigrants. This study reviews the literature regarding primary prevention of psychiatric disorders in special populations and identifies a variety of universal, selective, and indicated prevention measures aimed at minimizing the psychiatric sequelae in these groups. The authors reviewed the literature regarding the prevention of psychiatric symptoms in trauma/abuse victims, individuals in the military, oncology patients, patients with diabetes, pregnant/postpartum women, and immigrants. The literature on primary prevention of psychiatric illness in the special populations identified is rather limited. Universal prevention may be beneficial in some instances through public awareness campaigns and disaster planning. In other instances, more specific and intensive interventions for individuals at high risk of psychiatric illness may improve outcomes, for example, crisis counseling for those who have experienced severe trauma. Primary prevention of psychiatric illness may be an attainable goal via implementation of specific universal, selected, and indicated primary prevention measures in special populations.
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Gender Differences in Alcohol Prevention Programming
Ogenchuk, Marcella J.; Hellsten, Laurie-Ann M.; Prytula, Michelle
2012-01-01
The purpose of this article is to describe a study of the outcomes of a school-based alcohol abuse prevention initiative. The initiative was focused on identifying, developing, disseminating, and evaluating information for high school students based on the school community needs. Student learning outcomes were measured using pre- and post-tests…
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Professional development as learning in relationships
Noworolnik-Mastalska, Monika
2013-01-01
The article presents a clasification of selected leading conceptions within professional development, using socio-cultural perspective of learning in different relationships. Beside drawing on the classical social theory of learning through interactions with others, another dimensions of learning are added: related to the self, personal dimension of learning through professional identity development and societal dimension, where learning results from the ability to respond comprehensively to ...
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Computer games: Apprehension of learning strategies
Directory of Open Access Journals (Sweden)
Carlos Antonio Bruno da Silva
2003-12-01
Full Text Available Computer games and mainly videogames have proved to be an important tendency in Brazilian children’s play. They are part of the playful culture, which associates modern technology to traditional play preserving the importance of the latter. Based on Vygotsky and Chadwick’s ideas, this work studies the alternatives in the use of videogame by the occupational therapist, educator or parents, aiming prevention of learning difficulty by means of apprehension of learning strategies. Sixty children were investigated under dialectic, descriptive qualitative/quantitative focus. There was a semi-structured interview, direct observation and focused group applied to this intentional sample. Out of the 60 children playing in 3 videogame rental shops in Fortaleza-CE and Quixadá-CE, 30 aged 4 to 6 years old and the other 30 aged 7 and 8. Results indicate that the determination that the videogame is played in-group favors the apprehension of learning and affective strategies, processing, and meta-cognition. Therefore, videogame can be considered an excellent resource in terms of preventing learning difficulties, enabling children to their reality.
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Building a Smart E-Portfolio Platform for Optimal E-Learning Objects Acquisition
Directory of Open Access Journals (Sweden)
Chih-Kun Ke
2013-01-01
Full Text Available In modern education, an e-portfolio platform helps students in acquiring e-learning objects in a learning activity. Quality is an important consideration in evaluating the desirable e-learning object. Finding a means of determining a high quality e-learning object from a large number of candidate e-learning objects is an important requirement. To assist student learning in a modern e-portfolio platform, this work proposed an optimal selection approach determining a reasonable e-learning object from various candidate e-learning objects. An optimal selection approach which uses advanced information techniques is proposed. Each e-learning object undergoes a formalization process. An Information Retrieval (IR technique extracts and analyses key concepts from the student’s previous learning contexts. A context-based utility model computes the expected utility values of various e-learning objects based on the extracted key concepts. The expected utility values of e-learning objects are used in a multicriteria decision analysis to determine the optimal selection order of the candidate e-learning objects. The main contribution of this work is the demonstration of an effective e-learning object selection method which is easy to implement within an e-portfolio platform and which makes it smarter.
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Directory of Open Access Journals (Sweden)
Nagi F Idris
2009-06-01
Full Text Available Recent studies in our laboratory have shown that PCP (phencyclidine and d-amphetamine induce a cognitive deficit in rats, in a paradigm of potential relevance for the pathology of schizophrenia. Atypical, but not classical antipsychotics and the anticonvulsant, lamotrigine have been shown to prevent a selective reversal learning deficit induced by PCP. In contrast, only haloperidol reversed the d-amphetamine-induced deficit. The present study aimed to explore the ability of two anticonvulsants with differing mechanism of action, valproate and phenytoin to attenuate the cognitive deficits induced by PCP and d-amphetamine in the reversal learning paradigm. PCP at 1.5mg/kg and d-amphetamine at 0.5mg/kg both produced a selective and significant reduction in performance of the reversal phase with no effect on the initial phase of the task in female-hooded Lister rats. Valproate (25-200mg/kg and phenytoin (25-50mg/kg had no effect on performance when administered alone. Valproate (100-200mg/kg, whose principle action is thought to be the enhancement of GABA transmission, was unable to prevent the cognitive deficit induced by either PCP or d-amphetamine. Conversely, phenytoin (50mg/kg, a use-dependent sodium channel inhibitor, significantly prevented the deficit induced by PCP, but not d-amphetamine. These results add to our earlier work with lamotrigine, and suggest that sodium channel blockade may be a mechanism by which some anticonvulsant drugs can prevent the PCP-induced deficit. These data have implications for the use of anticonvulsant drugs in the treatment of cognitive or psychotic disorders.
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Kleinman, Alan
2016-12-20
The random mutation and natural selection phenomenon act in a mathematically predictable behavior, which when understood leads to approaches to reduce and prevent the failure of the use of these selection pressures when treating infections and cancers. The underlying principle to impair the random mutation and natural selection phenomenon is to use combination therapy, which forces the population to evolve to multiple selection pressures simultaneously that invoke the multiplication rule of probabilities simultaneously as well. Recently, it has been seen that combination therapy for the treatment of malaria has failed to prevent the emergence of drug-resistant variants. Using this empirical example and the principles of probability theory, the derivation of the equations describing this treatment failure is carried out. These equations give guidance as to how to use combination therapy for the treatment of cancers and infectious diseases and prevent the emergence of drug resistance. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
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Machine learning-based methods for prediction of linear B-cell epitopes.
Wang, Hsin-Wei; Pai, Tun-Wen
2014-01-01
B-cell epitope prediction facilitates immunologists in designing peptide-based vaccine, diagnostic test, disease prevention, treatment, and antibody production. In comparison with T-cell epitope prediction, the performance of variable length B-cell epitope prediction is still yet to be satisfied. Fortunately, due to increasingly available verified epitope databases, bioinformaticians could adopt machine learning-based algorithms on all curated data to design an improved prediction tool for biomedical researchers. Here, we have reviewed related epitope prediction papers, especially those for linear B-cell epitope prediction. It should be noticed that a combination of selected propensity scales and statistics of epitope residues with machine learning-based tools formulated a general way for constructing linear B-cell epitope prediction systems. It is also observed from most of the comparison results that the kernel method of support vector machine (SVM) classifier outperformed other machine learning-based approaches. Hence, in this chapter, except reviewing recently published papers, we have introduced the fundamentals of B-cell epitope and SVM techniques. In addition, an example of linear B-cell prediction system based on physicochemical features and amino acid combinations is illustrated in details.
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Full Text Available ... Consequences of Drug Misuse Hepatitis (Viral) HIV/AIDS Mental ... suppress the virus and prevent or decrease symptoms of illness. To learn about current statistics of HIV in ...
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Evaluating Question, Persuade, Refer (QPR) Suicide Prevention Training in a College Setting
Mitchell, Sharon L.; Kader, Mahrin; Darrow, Sherri A.; Haggerty, Melinda Z.; Keating, Niki L.
2013-01-01
This study assesses short-term and long-term learning outcomes of Question, Persuade, Refer (QPR) suicide prevention training in a college setting. Two hundred seventy-three participants completed pretest, posttest, and follow-up surveys regarding suicide prevention knowledge, attitudes, and skills. Results indicated: (a) increases in suicide…
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77 FR 20493 - National Child Abuse Prevention Month, 2012
2012-04-05
... parents and caregivers who have support--from relatives, friends, neighbors, and their communities-- are... identify, treat, and prevent abuse. I encourage all Americans to learn more about what they can do at: www...
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Adult EFL Reading Selection: Influence on Literacy
Directory of Open Access Journals (Sweden)
Juan Sebastián Basallo Gómez
2016-01-01
Full Text Available This paper is about the impact of systematic reading selection used to promote English as foreign language learning in adult students. A qualitative action research methodology was used to carry out this project. Ten class sessions were designed to provide students an opportunity to select texts according to criteria based upon their language levels and personal/professional interests. The findings align with three categories of influence: motivation, engagement, and contextualization/interpretation of readings. The main objective of this project was to see how the students’ text selection processes, guided by systematically designed criteria and elaborated strategies, influenced learning and acquisition in terms of motivation, perceptions, and opinions towards reading in English.
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Reversal Learning in Humans and Gerbils: Dynamic Control Network Facilitates Learning.
Jarvers, Christian; Brosch, Tobias; Brechmann, André; Woldeit, Marie L; Schulz, Andreas L; Ohl, Frank W; Lommerzheim, Marcel; Neumann, Heiko
2016-01-01
Biologically plausible modeling of behavioral reinforcement learning tasks has seen great improvements over the past decades. Less work has been dedicated to tasks involving contingency reversals, i.e., tasks in which the original behavioral goal is reversed one or multiple times. The ability to adjust to such reversals is a key element of behavioral flexibility. Here, we investigate the neural mechanisms underlying contingency-reversal tasks. We first conduct experiments with humans and gerbils to demonstrate memory effects, including multiple reversals in which subjects (humans and animals) show a faster learning rate when a previously learned contingency re-appears. Motivated by recurrent mechanisms of learning and memory for object categories, we propose a network architecture which involves reinforcement learning to steer an orienting system that monitors the success in reward acquisition. We suggest that a model sensory system provides feature representations which are further processed by category-related subnetworks which constitute a neural analog of expert networks. Categories are selected dynamically in a competitive field and predict the expected reward. Learning occurs in sequentialized phases to selectively focus the weight adaptation to synapses in the hierarchical network and modulate their weight changes by a global modulator signal. The orienting subsystem itself learns to bias the competition in the presence of continuous monotonic reward accumulation. In case of sudden changes in the discrepancy of predicted and acquired reward the activated motor category can be switched. We suggest that this subsystem is composed of a hierarchically organized network of dis-inhibitory mechanisms, dubbed a dynamic control network (DCN), which resembles components of the basal ganglia. The DCN selectively activates an expert network, corresponding to the current behavioral strategy. The trace of the accumulated reward is monitored such that large sudden
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Skill learning and the evolution of social learning mechanisms.
van der Post, Daniel J; Franz, Mathias; Laland, Kevin N
2016-08-24
Social learning is potentially advantageous, but evolutionary theory predicts that (i) its benefits may be self-limiting because social learning can lead to information parasitism, and (ii) these limitations can be mitigated via forms of selective copying. However, these findings arise from a functional approach in which learning mechanisms are not specified, and which assumes that social learning avoids the costs of asocial learning but does not produce information about the environment. Whether these findings generalize to all kinds of social learning remains to be established. Using a detailed multi-scale evolutionary model, we investigate the payoffs and information production processes of specific social learning mechanisms (including local enhancement, stimulus enhancement and observational learning) and their evolutionary consequences in the context of skill learning in foraging groups. We find that local enhancement does not benefit foraging success, but could evolve as a side-effect of grouping. In contrast, stimulus enhancement and observational learning can be beneficial across a wide range of environmental conditions because they generate opportunities for new learning outcomes. In contrast to much existing theory, we find that the functional outcomes of social learning are mechanism specific. Social learning nearly always produces information about the environment, and does not always avoid the costs of asocial learning or support information parasitism. Our study supports work emphasizing the value of incorporating mechanistic detail in functional analyses.
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Individualized Vascular Disease Prevention in High-Risk Patients
Kaasenbrood, L
2016-01-01
In the pharmacologic prevention of vascular events, clinicians need to translate average effects from a clinical trial to the individual patient. Prediction models can contribute to individualized vascular disease prevention by selecting patients for treatment based on estimated risk or expected
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Liver (Hepatocellular) Cancer Prevention (PDQ®)—Patient Version
Liver cancer risk factors include hepatitis B and C, cirrhosis, and aflatoxin (poison from certain foods). Learn about these and other risk factors for liver cancer and how to prevent liver cancer in this expert-reviewed and evidence-based summary.
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Key issues in the prevention of obesity.
Gill, T P
1997-01-01
Obesity is a serious, chronic medical condition which is associated with a wide range of debilitating and life-threatening conditions. It imposes huge financial burdens on health care systems and the community at large. Obesity develops over time and once it has done so, is difficult to treat. Therefore, the prevention of weight gain offers the only truly effective means of controlling obesity. Very little research has directly addressed the issue of obesity prevention and previous efforts to prevent obesity amongst individuals, groups or whole communities have had very limited success. However, we have learned sufficient from past preventive activities to realise that the management of obesity will require a comprehensive range of strategies with actions that target those with existing weight problems, those at high risk of developing obesity as well as the community as a whole. The prevention and management of obesity in children should be considered a priority as there is a high risk of persistence into adulthood.
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Fernández, Alberto; Carmona, Cristobal José; José Del Jesus, María; Herrera, Francisco
2017-09-01
Imbalanced classification is related to those problems that have an uneven distribution among classes. In addition to the former, when instances are located into the overlapped areas, the correct modeling of the problem becomes harder. Current solutions for both issues are often focused on the binary case study, as multi-class datasets require an additional effort to be addressed. In this research, we overcome these problems by carrying out a combination between feature and instance selections. Feature selection will allow simplifying the overlapping areas easing the generation of rules to distinguish among the classes. Selection of instances from all classes will address the imbalance itself by finding the most appropriate class distribution for the learning task, as well as possibly removing noise and difficult borderline examples. For the sake of obtaining an optimal joint set of features and instances, we embedded the searching for both parameters in a Multi-Objective Evolutionary Algorithm, using the C4.5 decision tree as baseline classifier in this wrapper approach. The multi-objective scheme allows taking a double advantage: the search space becomes broader, and we may provide a set of different solutions in order to build an ensemble of classifiers. This proposal has been contrasted versus several state-of-the-art solutions on imbalanced classification showing excellent results in both binary and multi-class problems.
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Niu, Ai-Qin; Xie, Liang-Jun; Wang, Hui; Zhu, Bing; Wang, Sheng-Qi
2016-01-01
Estrogen receptors (ERs) are nuclear transcription factors that are involved in the regulation of many complex physiological processes in humans. ERs have been validated as important drug targets for the treatment of various diseases, including breast cancer, ovarian cancer, osteoporosis, and cardiovascular disease. ERs have two subtypes, ER-α and ER-β. Emerging data suggest that the development of subtype-selective ligands that specifically target ER-β could be a more optimal approach to elicit beneficial estrogen-like activities and reduce side effects. Herein, we focused on ER-β and developed its in silico quantitative structure-activity relationship models using machine learning (ML) methods. The chemical structures and ER-β bioactivity data were extracted from public chemogenomics databases. Four types of popular fingerprint generation methods including MACCS fingerprint, PubChem fingerprint, 2D atom pairs, and Chemistry Development Kit extended fingerprint were used as descriptors. Four ML methods including Naïve Bayesian classifier, k-nearest neighbor, random forest, and support vector machine were used to train the models. The range of classification accuracies was 77.10% to 88.34%, and the range of area under the ROC (receiver operating characteristic) curve values was 0.8151 to 0.9475, evaluated by the 5-fold cross-validation. Comparison analysis suggests that both the random forest and the support vector machine are superior for the classification of selective ER-β agonists. Chemistry Development Kit extended fingerprints and MACCS fingerprint performed better in structural representation between active and inactive agonists. These results demonstrate that combining the fingerprint and ML approaches leads to robust ER-β agonist prediction models, which are potentially applicable to the identification of selective ER-β agonists.
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Li, Tse Yan; Gao, Xiaoli; Wong, Kin; Tse, Christine Shuk Kwan; Chan, Ying Yee
2015-04-14
Various digital learning objects (DLOs) are available via the World Wide Web, showing the flow of clinical procedures. It is unclear to what extent these freely accessible Internet DLOs facilitate or hamper students' acquisition of clinical competence. This study aimed to understand the experience of undergraduate students across clinical disciplines-medicine, dentistry, and nursing-in using openly accessible Internet DLOs, and to investigate the role of Internet DLOs in facilitating their clinical learning. Mid-year and final-year groups were selected from each undergraduate clinical degree program of the University of Hong Kong-Bachelor of Medicine and Bachelor of Surgery (MBBS), Bachelor of Dental Surgery (BDS), and Bachelor of Nursing (BNurs). All students were invited to complete a questionnaire on their personal and educational backgrounds, and their experiences and views on using Internet DLOs in learning clinical procedures. The questionnaire design was informed by the findings of six focus groups. Among 439 respondents, 97.5% (428/439) learned a variety of clinical procedures through Internet DLOs. Most nursing students (107/122, 87.7%) learned preventive measures through Internet DLOs, with a lower percentage of medical students (99/215, 46.0%) and dental students (43/96, 45%) having learned them this way (both Plearning in the planned curriculum. This trend calls for a transformation of the educator's role from dispensing knowledge to guidance and support.
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Back-dropout Transfer Learning for Action Recognition
DEFF Research Database (Denmark)
Ren, Huamin; Kanhabua, Nattiya; Møgelmose, Andreas
2018-01-01
transfer learning being a promising approach, it is still an open question how to adapt the model learned from the source dataset to the target dataset. One big challenge is to prevent the impact of category bias on classification performance. Dataset bias exists when two images from the same category...
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Comparison of Selective Attention and Intelligence Profile in Bilingual and Monolingual Adolescents
Directory of Open Access Journals (Sweden)
Rahim Yousefi
2018-01-01
Conclusion Learning a foreign language (e.g. English may be an effective factor in selective attention and intelligence profile of adolescents. Therefore, the role of learning a foreign language should be considered in selective attention and intelligence profile of adolescents.
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Online feature selection with streaming features.
Wu, Xindong; Yu, Kui; Ding, Wei; Wang, Hao; Zhu, Xingquan
2013-05-01
We propose a new online feature selection framework for applications with streaming features where the knowledge of the full feature space is unknown in advance. We define streaming features as features that flow in one by one over time whereas the number of training examples remains fixed. This is in contrast with traditional online learning methods that only deal with sequentially added observations, with little attention being paid to streaming features. The critical challenges for Online Streaming Feature Selection (OSFS) include 1) the continuous growth of feature volumes over time, 2) a large feature space, possibly of unknown or infinite size, and 3) the unavailability of the entire feature set before learning starts. In the paper, we present a novel Online Streaming Feature Selection method to select strongly relevant and nonredundant features on the fly. An efficient Fast-OSFS algorithm is proposed to improve feature selection performance. The proposed algorithms are evaluated extensively on high-dimensional datasets and also with a real-world case study on impact crater detection. Experimental results demonstrate that the algorithms achieve better compactness and higher prediction accuracy than existing streaming feature selection algorithms.
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Basic, Josipa
2015-01-01
This article reviews the experience of implementing a community approach to drug use and youth delinquency prevention based on the 'Communities that Care' (CTC) system implemented in one Croatian county consisting of 12 communities, 2002 to 2013 (Hawkins, 1999; Hawkins & Catalano, 2004). This overview explores selected critical issues which are often not considered in substance use(r) community intervention planning, implementation as well as in associated process and outcome assessments. These issues include, among others, the mobilization process of adequate representation of people; the involvement of relevant key individual and organizational stakeholders and being aware of the stakeholders' willingness to participate in the prevention process. In addition, it is important to be aware of the stakeholders' knowledge and perceptions about the 'problems' of drug use and youth delinquency in their communities as well as the characteristics of the targeted population(s). Sometimes there are community members and stakeholders who block needed change and therefore prevention process enablers and 'bridges' should be involved in moving prevention programming forward. Another barrier that is often overlooked in prevention planning is community readiness to change and a realistic assessment of available and accessible resources for initiating the planned change(s) and sustaining them. All of these issues have been found to be potentially related to intervention success. At the end of this article, I summarize perspectives from prevention scientists and practitioners and lessons learned from communities' readiness research and practice in Croatian that has international relevance.
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Kaminski, Charles William
The purpose of this research was to investigate the formative use of Select and Fill-In (SAFI) maps in online instruction and the cognitive, metacognitive, and affective responses of students to their use. In particular, the implications of their use with students of different learning styles was considered. The research question investigated in this qualitative study was: How do students of different learning styles respond to online instruction in which SAFI maps are utilized? This question was explored by using an emergent, collective case study. Each case consisted of community college students who shared a dominant learning style and were enrolled in an online course in environmental studies. Cases in the study were determined using Kolb's Learning Style Inventory (LSI). Seven forms of data were collected during the study. During the first phase of data collection, dominant learning style and background information on student experience with concept mapping and online instruction was determined. In the second phase of data collection, participants completed SAFI maps and quiz items that corresponded to the content of the maps. Achievement data on the map activities and quiz and student responses to a post-SAFI survey and questionnaire were recorded to identify learner cognitive, metacognitive, and affective responses to the tasks. Upon completion of data collection, cases were constructed and compared across learning styles. Cases are presented using the trends, across participants sharing the same dominant learning style, in achievement, behaviors and attitudes as seen in the evidence present in the data. Triangulation of multiple data sources increased reliability and validity, through cross-case analyses, and produced a thick description of the relationship between the cases for each learning style. Evidence suggesting a cognitive response to the SAFI tasks was inconsistent across cases. However, learners with an affinity towards reflective learning
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Institute of Scientific and Technical Information of China (English)
静进; 王庆雄; 杨斌让; 陈学彬
2004-01-01
Background Children with nonverbal learning disabilities (NLD) usually manifest defective attention function. This study sought to investigate the neuropsychological characteristics of selective attention, such as attention control, working memory, and attention persistence of the frontal lobe in children with NLD. Methods Using the auditory detection test (ADT), Wisconsin card sorting test (WCST), and C-WISC, 27 children with NLD and 33 normal children in the control group were tested, and the results of C-WISC subtests were analyzed with factor analysis. Results Compared with the control group, the correct response rate in the auditory detection test in the NLD group was much lower (P<0.01), and the number of incorrect responses was much higher (P<0.01); NLD children also scored lower in WCST categories achieved (CA) and perseverative errors (PE) (P<0.05). Factor analysis showed that perceptual organization (PO) related to visual space and freedom from distractibility (FD) relating to attention persistence in the NLD group were obviously lower than in the control group (P<0.01). Conclusions Children with NLD have attention control disorder and working memory disorder mainly in the frontal lobe. We believe that the disorder is particularly prominent in the right frontal lobe.
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Seifi Moroudi, Reihane; Masoudi, Ali Akbar; Vaez Torshizi, Rasoul; Zandi, Mohammad
2014-12-01
One of the important behaviors of dogs is trainability which is affected by learning and memory genes. These kinds of the genes have not yet been identified in dogs. In the current research, these genes were found in animal models by mining the biological data and scientific literatures. The proteins of these genes were obtained from the UniProt database in dogs and humans. Not all homologous proteins perform similar functions, thus comparison of these proteins was studied in terms of protein families, domains, biological processes, molecular functions, and cellular location of metabolic pathways in Interpro, KEGG, Quick Go and Psort databases. The results showed that some of these proteins have the same performance in the rat or mouse, dog, and human. It is anticipated that the protein of these genes may be effective in learning and memory in dogs. Then, the expression pattern of the recognized genes was investigated in the dog hippocampus using the existing information in the GEO profile. The results showed that BDNF, TAC1 and CCK genes are expressed in the dog hippocampus, therefore, these genes could be strong candidates associated with learning and memory in dogs. Subsequently, due to the importance of the promoter regions in gene function, this region was investigated in the above genes. Analysis of the promoter indicated that the HNF-4 site of BDNF gene and the transcription start site of CCK gene is exposed to methylation. Phylogenetic analysis of protein sequences of these genes showed high similarity in each of these three genes among the studied species. The dN/dS ratio for BDNF, TAC1 and CCK genes indicates a purifying selection during the evolution of the genes.
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Stroke Prevention: Managing Modifiable Risk Factors
Directory of Open Access Journals (Sweden)
Silvia Di Legge
2012-01-01
Full Text Available Prevention plays a crucial role in counteracting morbidity and mortality related to ischemic stroke. It has been estimated that 50% of stroke are preventable through control of modifiable risk factors and lifestyle changes. Antihypertensive treatment is recommended for both prevention of recurrent stroke and other vascular events. The use of antiplatelets and statins has been shown to reduce the risk of recurrent stroke and other vascular events. Angiotensin-converting enzyme inhibitors (ACEIs and angiotensin II receptor blockers (ARBs are indicated in stroke prevention because they also promote vascular health. Effective secondary-prevention strategies for selected patients include carotid revascularization for high-grade carotid stenosis and vitamin K antagonist treatment for atrial fibrillation. The results of recent clinical trials investigating new anticoagulants (factor Xa inhibitors and direct thrombin inhibitors clearly indicate alternative strategies in stroke prevention for patients with atrial fibrillation. This paper describes the current landscape and developments in stroke prevention with special reference to medical treatment in secondary prevention of ischemic stroke.
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Campus, P; Colelli, V; Orsini, C; Sarra, D; Cabib, S
2015-02-01
The forced swimming test (FST) remains one of the most used tools for screening antidepressants in rodent models. Nonetheless, the nature of immobility, its main behavioral measure, is still a matter of debate. The present study took advantage of our recent finding that mice of the inbred DBA/2J strain require a functioning left dorsolateral striatum (DLS) to consolidate long-term memory of FST to test whether immobility is the outcome of stress-related learning. Infusion of the GABA-A agonist muscimol in the left DLS immediately after a single experience of FST prevented and infusion in the left or the right amygdala impaired recall of the acquired levels of immobility in a probe test performed 24h later. Post-training left DLS infusion of muscimol, at a dose capable of preventing retention of FST-induced immobility, did not influence 24h retention of inhibitory avoidance training or of the escape response acquired in a water T-maze. However, this same treatment prevented 24h retention of the extinction training of the consolidated escape response. These results indicate that a left DLS-centered memory system selectively mediates memory consolidation of FST and of escape extinction and support the hypothesis that immobility is the result of extinction-like inhibitory learning involving all available escape responses due to the inescapable/unavoidable nature of FST experience. Copyright © 2014 Elsevier B.V. All rights reserved.
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Does prevention for Alzheimer's disease exist?
Directory of Open Access Journals (Sweden)
Sonia Maria Dozzi Brucki
Full Text Available Abstract The prevention of Alzheimer's disease is a growing public health concern amidst an ageing population. Meanwhile, there is no effective or curative treatment available where prevention could greatly reduce health costs. This review was based on reports of potential preventive factors, including modifiable lifestyle factors, as well as preventive pharmacological strategies. Although the present review was not systematic, the reports selected from PubMed using "Alzheimer's disease" and "prevention" as key-words, allow us to affirm that pursuing a healthy lifestyle; physical, cognitive, leisure activities; good social engagement; a high consumption of fish, low consumption of dietary fat and moderate consumption of wine, and control of vascular risk factors appear to be potential factors for delaying dementia.
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Preventive Measures Adopted by Nigerian Farmers for the ...
African Journals Online (AJOL)
The study investigated the adoption of environmental hazards preventive measures among cocoa farmers in Nigeria. It specifically identified and evaluated the preventive measures adopted by the farmers against environmental hazards associated with cocoa farming. A multistage sampling procedure was used in selecting ...
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Development of Selective Attention in Reflective and Impulsive Children.
Weiner, Alan S.; Berzonsky, Michael D.
Selective attention was assessed in second, fourth, and sixth grade reflective and impulsive children with an incidental learning task using pictures (animal-household object pairs) or shapes (colored forms) as stimuli. By the sixth grade, reflective children displayed less incidental learning and greater central learning than impulsive children…
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Attention Cueing as a Means to Enhance Learning from an Animation
B.B. de Koning (Björn); H.K. Tabbers (Huib); R.M.J.P. Rikers (Remy); G.W.C. Paas (Fred)
2007-01-01
textabstractThe question how animations should be designed so that learning is optimised, is still under discussion. Animations are often cognitively very demanding, resulting in decreased learning outcomes. In this study, we tried to prevent cognitive overload and foster learning by focusing the
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E-Learning Systems, Environments and Approaches
Isaias, P.; Spector, J.M.; Ifenthaler, D.; Sampson, D.G.
2015-01-01
The volume consists of twenty-five chapters selected from among peer-reviewed papers presented at the CELDA (Cognition and Exploratory Learning in the Digital Age) 2013 Conference held in Fort Worth, Texas, USA, in October 2013 and also from world class scholars in e-learning systems, environments and approaches. The following sub-topics are included: Exploratory Learning Technologies (Part I), e-Learning social web design (Part II), Learner communities through e-Learning implementations (Par...
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Learning Outcomes and Affective Factors of Blended Learning of English for Library Science
Wentao, Chen; Jinyu, Zhang; Zhonggen, Yu
2016-01-01
English for Library Science is an essential course for students to command comprehensive scope of library knowledge. This study aims to compare the learning outcomes, gender differences and affective factors in the environments of blended and traditional learning. Around one thousand participants from one university were randomly selected to…
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Saffran, Jenny R.; Kirkham, Natasha Z.
2017-01-01
Perception involves making sense of a dynamic, multimodal environment. In the absence of mechanisms capable of exploiting the statistical patterns in the natural world, infants would face an insurmountable computational problem. Infant statistical learning mechanisms facilitate the detection of structure. These abilities allow the infant to compute across elements in their environmental input, extracting patterns for further processing and subsequent learning. In this selective review, we summarize findings that show that statistical learning is both a broad and flexible mechanism (supporting learning from different modalities across many different content areas) and input specific (shifting computations depending on the type of input and goal of learning). We suggest that statistical learning not only provides a framework for studying language development and object knowledge in constrained laboratory settings, but also allows researchers to tackle real-world problems, such as multilingualism, the role of ever-changing learning environments, and differential developmental trajectories. PMID:28793812