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Sample records for learning selectively conditioned

  1. Learning context conditions for BDI plan selection

    NARCIS (Netherlands)

    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

  2. Theoretical framework on selected core issues on conditions for productive learning in networked learning environments

    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....

  3. Learning conditional Gaussian networks

    DEFF Research Database (Denmark)

    Bøttcher, Susanne Gammelgaard

    This paper considers conditional Gaussian networks. The parameters in the network are learned by using conjugate Bayesian analysis. As conjugate local priors, we apply the Dirichlet distribution for discrete variables and the Gaussian-inverse gamma distribution for continuous variables, given...... a configuration of the discrete parents. We assume parameter independence and complete data. Further, to learn the structure of the network, the network score is deduced. We then develop a local master prior procedure, for deriving parameter priors in these networks. This procedure satisfies parameter...... independence, parameter modularity and likelihood equivalence. Bayes factors to be used in model search are introduced. Finally the methods derived are illustrated by a simple example....

  4. Maximum Likelihood Learning of Conditional MTE Distributions

    DEFF Research Database (Denmark)

    Langseth, Helge; Nielsen, Thomas Dyhre; Rumí, Rafael

    2009-01-01

    We describe a procedure for inducing conditional densities within the mixtures of truncated exponentials (MTE) framework. We analyse possible conditional MTE specifications and propose a model selection scheme, based on the BIC score, for partitioning the domain of the conditioning variables....... Finally, experimental results demonstrate the applicability of the learning procedure as well as the expressive power of the conditional MTE distribution....

  5. Learning strategies during fear conditioning

    OpenAIRE

    Carpenter, Russ E.; Summers, Cliff H.

    2009-01-01

    This paper describes a model of fear learning, in which subjects have an option of behavioral responses to impending social defeat. The model generates two types of learning: social avoidance and classical conditioning, dependent upon 1) escape from or 2) social subordination to an aggressor. We hypothesized that social stress provides the impetus as well as the necessary information to stimulate dichotomous goal-oriented learning. Specialized tanks were constructed to subject rainbow trout t...

  6. Conditional control in visual selection

    NARCIS (Netherlands)

    van Zoest, Wieske; Van der Stigchel, Stefan; Donk, Mieke

    2017-01-01

    Attention and eye movements provide a window into the selective processing of visual information. Evidence suggests that selection is influenced by various factors and is not always under the strategic control of the observer. The aims of this tutorial review are to give a brief introduction to eye

  7. Statistical learning and selective inference.

    Science.gov (United States)

    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.

  8. Learning Conditions for Non-Formal and Informal Workplace Learning

    Science.gov (United States)

    Kyndt, Eva; Dochy, Filip; Nijs, Hanne

    2009-01-01

    Purpose: The purpose of this research paper is to investigate the presence of learning conditions for non-formal and informal workplace learning in relation to the characteristics of the employee and the organisation he or she works for. Design/methodology/approach: The questionnaire developed by Clauwaert and Van Bree on learning conditions was…

  9. Evolution of conditional cooperation under multilevel selection.

    Science.gov (United States)

    Zhang, Huanren; Perc, Matjaž

    2016-03-11

    We study the emergence of conditional cooperation in the presence of both intra-group and inter-group selection. Individuals play public goods games within their groups using conditional strategies, which are represented as piecewise linear response functions. Accordingly, groups engage in conflicts with a certain probability. In contrast to previous studies, we consider continuous contribution levels and a rich set of conditional strategies, allowing for a wide range of possible interactions between strategies. We find that the existence of conditional strategies enables the stabilization of cooperation even under strong intra-group selection. The strategy that eventually dominates in the population has two key properties: (i) It is unexploitable with strong intra-group selection; (ii) It can achieve full contribution to outperform other strategies in the inter-group selection. The success of this strategy is robust to initial conditions as well as changes to important parameters. We also investigate the influence of different factors on cooperation levels, including group conflicts, group size, and migration rate. Their effect on cooperation can be attributed to and explained by their influence on the relative strength of intra-group and inter-group selection.

  10. Changing Conditions for Networked Learning?

    DEFF Research Database (Denmark)

    Ryberg, Thomas

    2011-01-01

    in describing the novel pedagogical potentials of these new technologies and practices (e.g. in debates around virtual learning environments versus personal learning environment). Likewise, I shall briefly discuss the notions of ‘digital natives’ or ‘the net generation’ from a critical perspective...... of social technologies. I argue that we are seeing the emergence of new architectures and scales of participation, collaboration and networking e.g. through interesting formations of learning networks at different levels of scale, for different purposes and often bridging boundaries such as formal...

  11. Conditional discrimination learning: A critique and amplification

    OpenAIRE

    Schrier, Allan M.; Thompson, Claudia R.

    1980-01-01

    Carter and Werner recently reviewed the literature on conditional discrimination learning by pigeons, which consists of studies of matching-to-sample and oddity-from-sample. They also discussed three models of such learning: the “multiple-rule” model (learning of stimulus-specific relations), the “configuration” model, and the “single-rule” model (concept learning). Although their treatment of the multiple-rule model, which seems most applicable to the pigeon data, is generally excellent, the...

  12. Dissociable Learning Processes Underlie Human Pain Conditioning.

    Science.gov (United States)

    Zhang, Suyi; Mano, Hiroaki; Ganesh, Gowrishankar; Robbins, Trevor; Seymour, Ben

    2016-01-11

    Pavlovian conditioning underlies many aspects of pain behavior, including fear and threat detection [1], escape and avoidance learning [2], and endogenous analgesia [3]. Although a central role for the amygdala is well established [4], both human and animal studies implicate other brain regions in learning, notably ventral striatum and cerebellum [5]. It remains unclear whether these regions make different contributions to a single aversive learning process or represent independent learning mechanisms that interact to generate the expression of pain-related behavior. We designed a human parallel aversive conditioning paradigm in which different Pavlovian visual cues probabilistically predicted thermal pain primarily to either the left or right arm and studied the acquisition of conditioned Pavlovian responses using combined physiological recordings and fMRI. Using computational modeling based on reinforcement learning theory, we found that conditioning involves two distinct types of learning process. First, a non-specific "preparatory" system learns aversive facial expressions and autonomic responses such as skin conductance. The associated learning signals-the learned associability and prediction error-were correlated with fMRI brain responses in amygdala-striatal regions, corresponding to the classic aversive (fear) learning circuit. Second, a specific lateralized system learns "consummatory" limb-withdrawal responses, detectable with electromyography of the arm to which pain is predicted. Its related learned associability was correlated with responses in ipsilateral cerebellar cortex, suggesting a novel computational role for the cerebellum in pain. In conclusion, our results show that the overall phenotype of conditioned pain behavior depends on two dissociable reinforcement learning circuits. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  13. Conditions for Productive Learning in Network Learning Environments

    DEFF Research Database (Denmark)

    Ponti, M.; Dirckinck-Holmfeld, Lone; Lindström, B.

    2004-01-01

    are designed without a deep understanding of the pedagogical, communicative and collaborative conditions embedded in networked learning. Despite the existence of good theoretical views pointing to a social understanding of learning, rather than a traditional individualistic and information processing approach......The Kaleidoscope1 Jointly Executed Integrating Research Project (JEIRP) on Conditions for Productive Networked Learning Environments is developing and elaborating conceptual understandings of Computer Supported Collaborative Learning (CSCL) emphasizing the use of cross-cultural comparative......: Pedagogical design and the dialectics of the digital artefacts, the concept of collaboration, ethics/trust, identity and the role of scaffolding of networked learning environments.   The JEIRP is motivated by the fact that many networked learning environments in various European educational settings...

  14. 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.

  15. Embedded Incremental Feature Selection for Reinforcement Learning

    Science.gov (United States)

    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

  16. Conditions of Practice in Perceptual Skill Learning

    Science.gov (United States)

    Memmert, D.; Hagemann, N.; Althoetmar, R.; Geppert, S.; Seiler, D.

    2009-01-01

    This study uses three experiments with different kinds of training conditions to investigate the "easy-to-hard" principle, context interference conditions, and feedback effects for learning anticipatory skills in badminton. Experiment 1 (N = 60) showed that a training program that gradually increases the difficulty level has no advantage over the…

  17. Spatial Learning: Conditions and Basic Effects

    Directory of Open Access Journals (Sweden)

    Victoria D. Chamizo

    2002-01-01

    Full Text Available A growing body of evidence suggests that the spatial and the temporal domains seem to share the same or similar conditions, basic effects, and mechanisms. The blocking, unblocking and overshadowing experiments (and also those of latent inhibition and perceptual learning reviewed by Prados and Redhead in this issue show that to exclude associative learning as a basic mechanism responsible for spatial learning is quite inappropriate. All these results, especially those obtained with strictly spatial tasks, seem inconsistent with O’Keefe and Nadel’s account of true spatial learning or locale learning. Their theory claims that this kind of learning is fundamentally different and develops with total independence from other ways of learning (like classical and instrumental conditioning -taxon learning. In fact, the results reviewed can be explained appealing on to a sophisticated guidance system, like for example the one proposed by Leonard and McNaughton (1990; see also McNaughton and cols, 1996. Such a system would allow that an animal generates new space information: given the distance and address from of A to B and from A to C, being able to infer the distance and the address from B to C, even when C is invisible from B (see Chapuis and Varlet, 1987 -the contribution by McLaren in this issue constitutes a good example of a sophisticated guidance system.

  18. Efficient abstraction selection in reinforcement learning

    NARCIS (Netherlands)

    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

  19. Some psycholinguistic conditions for second language learning

    Directory of Open Access Journals (Sweden)

    Bernard Spolsky

    2013-02-01

    Full Text Available The author discusses some psycho linguistic conditions for second language learning based on a preference rr ode! in linguistics. The outcome of second language learning depends on a number of conditions. Second language learning takes place in a social context, and social conditions determine a learner's attitudes. These attitudes are twofold in nature, namely those towards the community speaking the target language and those towards the learning situation. The two kinds of attitudes lead to motivation. The social context also provides opportunities for language learning and can be divided into formal and informal situations. There are also individual conditions of the learner. The author is concerned with the exploration of several specific psycholinguistic factors, as well as the kinds of rules which they contribute to the theory. Die skrywer bespreek enkele psigolinguistiese voorwaardes vir die aanleer van 'n tweede taal, gebaseer op 'n voorkeurmodel in die l!nguistiek. Die aanleer van 'n tweede taal geskied bin ne 'n sosiale konteks, en sosiale omstandighede bepaal 'n leerder se houding. Hierdie houding kan bestaan ten opsigte van die gemeenskap wat die teikentaal praat, sowel as ten opsigte van die leersituasie. Motivering word bepaal deur hierdie tweeledige houding. Die sosiale konteks bepaal ook geleenthede vir die aanleer van 'n taal en kan verdeel word in forme le en informele situasies. Verder is daar die individuele omstandighede van elke leerder. Die skrywer hou horn besig met 'n verkenning van spesifieke psigolinguistiese faktore, sowel as die soort reels wat hydra tot die teorie.

  20. 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.

  1. Conditioning and learning in relation to disease.

    Science.gov (United States)

    Ban, T A; Guy, W

    1985-12-01

    Of the two generally recognized processes through which learning occurs--imprinting and conditioning--only the latter with its two paradigms, classical and operant, has both practical and heuristic implications for disease. From the classical conditioning experiments of Pavlov's laboratory over 100 years ago to the later work in operant conditioning by Skinner and others in the past four decades has evolved much of the basis of modern learning theory and its applications to disease in the form of behavior therapy. Variants of behavior therapy have been employed in the treatment of wide variety of medical and psychiatric illnesses. Recent developments in the study of brain function and biochemistry have led to renewed interest in the conditioning paradigm and its value as tool in these areas of research.

  2. Biologically Predisposed Learning and Selective Associations in Amygdalar Neurons

    Science.gov (United States)

    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…

  3. Operant Conditioning and Learning: Examples, Sources, Technology.

    Science.gov (United States)

    Pedrini, Bonnie C.; Pedrini, D. T.

    The purpose of this paper is to relate psychology to teaching generally, and to relate behavior shaping to curriculum, specifically. Focusing on operant conditioning and learning, many studies are cited which illustrate some of the work being done toward effectively shaping or modifying student behavior whether in terms of subject matter or…

  4. 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.

  5. Creating conditions for cooperative learning: Basic elements

    Directory of Open Access Journals (Sweden)

    Ševkušić-Mandić Slavica G.

    2003-01-01

    Full Text Available Although a large number of research evidence speak out in favor of cooperative learning, its effectiveness in teaching does not depend only on teacher’s and students’ enthusiasm and willingness to work in such a manner. Creating cooperative situations in learning demands a serious preparation and engagement on the part of teacher who is structuring various aspects of work in the classroom. Although there exist a large number of models and techniques of cooperative learning, which vary in the way in which students work together, in the structure of learning tasks as well as in the degree to which cooperative efforts of students are coupled with competition among groups, some elements should be present in the structure of conditions irrespective of the type of group work in question. Potential effects of cooperation are not likely to emerge unless teachers apply five basic elements of cooperative structure: 1. structuring of the learning task and students’ positive interdependence, 2. individual responsibility, 3. upgrading of "face to face" interaction, 4. training of students’ social skills, and 5. evaluation of group processes. The paper discusses various strategies for establishing the mentioned elements and concrete examples for teaching practice are provided, which should be of assistance to teachers for as much successful cooperative learning application as possible in work with children.

  6. Feature and Region Selection for Visual Learning.

    Science.gov (United States)

    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.

  7. Informal Workplace Learning among Nurses: Organisational Learning Conditions and Personal Characteristics That Predict Learning Outcomes

    Science.gov (United States)

    Kyndt, Eva; Vermeire, Eva; Cabus, Shana

    2016-01-01

    Purpose: This paper aims to examine which organisational learning conditions and individual characteristics predict the learning outcomes nurses achieve through informal learning activities. There is specific relevance for the nursing profession because of the rapidly changing healthcare systems. Design/Methodology/Approach: In total, 203 nurses…

  8. Selection as a learning experience: an exploratory study.

    Science.gov (United States)

    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.

  9. Adapting AIC to conditional model selection

    NARCIS (Netherlands)

    T. van Ommen (Thijs)

    2012-01-01

    textabstractIn statistical settings such as regression and time series, we can condition on observed information when predicting the data of interest. For example, a regression model explains the dependent variables $y_1, \\ldots, y_n$ in terms of the independent variables $x_1, \\ldots, x_n$.

  10. Learning Conditions, Members' Motivation and Satisfaction: A Multilevel Analysis

    Science.gov (United States)

    Dimas, Isabel Dórdio; Rebelo, Teresa; Lourenço, Paulo Renato

    2015-01-01

    Purpose: The purpose of this paper was to contribute to the clarification of the conditions under which teams can be successful, especially those related to team learning. To attain this goal, in the present study, the mediating role played by team members' motivation on the relationship between team learning conditions (shared learning beliefs…

  11. Residential roof condition assessment system using deep learning

    Science.gov (United States)

    Wang, Fan; Kerekes, John P.; Xu, Zhuoyi; Wang, Yandong

    2018-01-01

    The emergence of high resolution (HR) and ultra high resolution (UHR) airborne remote sensing imagery is enabling humans to move beyond traditional land cover analysis applications to the detailed characterization of surface objects. A residential roof condition assessment method using techniques from deep learning is presented. The proposed method operates on individual roofs and divides the task into two stages: (1) roof segmentation, followed by (2) condition classification of the segmented roof regions. As the first step in this process, a self-tuning method is proposed to segment the images into small homogeneous areas. The segmentation is initialized with simple linear iterative clustering followed by deep learned feature extraction and region merging, with the optimal result selected by an unsupervised index, Q. After the segmentation, a pretrained residual network is fine-tuned on the augmented roof segments using a proposed k-pixel extension technique for classification. The effectiveness of the proposed algorithm was demonstrated on both HR and UHR imagery collected by EagleView over different study sites. The proposed algorithm has yielded promising results and has outperformed traditional machine learning methods using hand-crafted features.

  12. Selective social learning in infancy: looking for mechanisms.

    Science.gov (United States)

    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.

  13. Experienced teachers' informal workplace learning and perceptions of workplace conditions

    NARCIS (Netherlands)

    Hoekstra, A.; Korthagen, F.; Brekelmans, M.; Beijaard, D.; Imants, J.

    2009-01-01

    Purpose: The purpose of this paper is to explore in detail how teachers' perceptions of workplace conditions for learning are related to their informal workplace learning activities and learning outcomes. Design/methodology/approach: From a sample of 32 teachers, a purposeful sampling technique of

  14. Imaging learning and memory: classical conditioning.

    Science.gov (United States)

    Schreurs, B G; Alkon, D L

    2001-12-15

    The search for the biological basis of learning and memory has, until recently, been constrained by the limits of technology to classic anatomic and electrophysiologic studies. With the advent of functional imaging, we have begun to delve into what, for many, was a "black box." We review several different types of imaging experiments, including steady state animal experiments that image the functional labeling of fixed tissues, and dynamic human studies based on functional imaging of the intact brain during learning. The data suggest that learning and memory involve a surprising conservation of mechanisms and the integrated networking of a number of structures and processes. Copyright 2001 Wiley-Liss, Inc.

  15. Selective attention and recognition: effects of congruency on episodic learning.

    Science.gov (United States)

    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.

  16. Rapid learning dynamics in individual honeybees during classical conditioning

    Directory of Open Access Journals (Sweden)

    Evren ePamir

    2014-09-01

    Full Text Available Associative learning in insects has been studied extensively by a multitude of classical conditioning protocols. However, so far little emphasis has been put on the dynamics of learning in individuals. The honeybee is a well-established animal model for learning and memory. We here studied associative learning as expressed in individual behavior based on a large collection of data on olfactory classical conditioning (25 datasets, 3,298 animals. We show that the group-averaged learning curve and memory retention score confound three attributes of individual learning: the ability or inability to learn a given task, the generally fast acquisition of a conditioned response in learners, and the high stability of the conditioned response during consecutive training and memory retention trials. We reassessed the prevailing view that more training results in better memory performance and found that 24h memory retention can be indistinguishable after single-trial and multiple-trial conditioning in individuals. We explain how inter-individual differences in learning can be accommodated within the Rescorla-Wagner theory of associative learning. In both data-analysis and modeling we demonstrate how the conflict between population-level and single-animal perspectives on learning and memory can be disentangled.

  17. Robot soccer action selection based on Q learning

    Institute of Scientific and Technical Information of China (English)

    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

  18. Computerized adaptive testing item selection in computerized adaptive learning systems

    NARCIS (Netherlands)

    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

  19. Is it better to select or to receive? Learning via active and passive hypothesis testing.

    Science.gov (United States)

    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.

  20. Rapid learning dynamics in individual honeybees during classical conditioning.

    Science.gov (United States)

    Pamir, Evren; Szyszka, Paul; Scheiner, Ricarda; Nawrot, Martin P

    2014-01-01

    Associative learning in insects has been studied extensively by a multitude of classical conditioning protocols. However, so far little emphasis has been put on the dynamics of learning in individuals. The honeybee is a well-established animal model for learning and memory. We here studied associative learning as expressed in individual behavior based on a large collection of data on olfactory classical conditioning (25 datasets, 3298 animals). We show that the group-averaged learning curve and memory retention score confound three attributes of individual learning: the ability or inability to learn a given task, the generally fast acquisition of a conditioned response (CR) in learners, and the high stability of the CR during consecutive training and memory retention trials. We reassessed the prevailing view that more training results in better memory performance and found that 24 h memory retention can be indistinguishable after single-trial and multiple-trial conditioning in individuals. We explain how inter-individual differences in learning can be accommodated within the Rescorla-Wagner theory of associative learning. In both data-analysis and modeling we demonstrate how the conflict between population-level and single-animal perspectives on learning and memory can be disentangled.

  1. Conditioning Factors of an Organizational Learning Culture

    Science.gov (United States)

    Rebelo, Teresa Manuela; Gomes, Adelino Duarte

    2011-01-01

    Purpose: The aim of this study is to assess the relationship between some variables (organizational structure, organizational dimension and age, human resource characteristics, the external environment, strategy and quality) and organizational learning culture and evaluate the way they interact with this kind of culture.…

  2. Sex differences in learning processes of classical and operant conditioning.

    Science.gov (United States)

    Dalla, Christina; Shors, Tracey J

    2009-05-25

    Males and females learn and remember differently at different times in their lives. These differences occur in most species, from invertebrates to humans. We review here sex differences as they occur in laboratory rodent species. We focus on classical and operant conditioning paradigms, including classical eyeblink conditioning, fear-conditioning, active avoidance and conditioned taste aversion. Sex differences have been reported during acquisition, retention and extinction in most of these paradigms. In general, females perform better than males in the classical eyeblink conditioning, in fear-potentiated startle and in most operant conditioning tasks, such as the active avoidance test. However, in the classical fear-conditioning paradigm, in certain lever-pressing paradigms and in the conditioned taste aversion, males outperform females or are more resistant to extinction. Most sex differences in conditioning are dependent on organizational effects of gonadal hormones during early development of the brain, in addition to modulation by activational effects during puberty and adulthood. Critically, sex differences in performance account for some of the reported effects on learning and these are discussed throughout the review. Because so many mental disorders are more prevalent in one sex than the other, it is important to consider sex differences in learning when applying animal models of learning for these disorders. Finally, we discuss how sex differences in learning continue to alter the brain throughout the lifespan. Thus, sex differences in learning are not only mediated by sex differences in the brain, but also contribute to them.

  3. Optimizing learning path selection through memetic algorithms

    NARCIS (Netherlands)

    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

  4. Effects of Mode of Target Task Selection on Learning about Plants in a Mobile Learning Environment: Effortful Manual Selection versus Effortless QR-Code Selection

    Science.gov (United States)

    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…

  5. The conditions that promote fear learning: prediction error and Pavlovian fear conditioning.

    Science.gov (United States)

    Li, Susan Shi Yuan; McNally, Gavan P

    2014-02-01

    A key insight of associative learning theory is that learning depends on the actions of prediction error: a discrepancy between the actual and expected outcomes of a conditioning trial. When positive, such error causes increments in associative strength and, when negative, such error causes decrements in associative strength. Prediction error can act directly on fear learning by determining the effectiveness of the aversive unconditioned stimulus or indirectly by determining the effectiveness, or associability, of the conditioned stimulus. Evidence from a variety of experimental preparations in human and non-human animals suggest that discrete neural circuits code for these actions of prediction error during fear learning. Here we review the circuits and brain regions contributing to the neural coding of prediction error during fear learning and highlight areas of research (safety learning, extinction, and reconsolidation) that may profit from this approach to understanding learning. Crown Copyright © 2013. Published by Elsevier Inc. All rights reserved.

  6. On a selection method of imaging condition in scintigraphy

    International Nuclear Information System (INIS)

    Ikeda, Hozumi; Kishimoto, Kenji; Shimonishi, Yoshihiro; Ohmura, Masahiro; Kosakai, Kazuhisa; Ochi, Hironobu

    1992-01-01

    Selection of imaging condition in scintigraphy was evaluated using analytic hierarchy process. First, a method of the selection was led by determining at the points of image quantity and imaging time. Influence of image quality was thought to depend on changes of system resolution, count density, image size, and image density. Also influence of imaging time was thought to depend on changes of system sensitivity and data acquisition time. Phantom study was done for paired comparison of these selection factors, and relations of sample data and the factors, that is Rollo phantom images were taken by changing count density, image size, and image density. Image quality was shown by calculating the score of visual evaluation that done by comparing of a pair of images in clearer cold lesion on the scintigrams. Imaging time was shown by relative values for changes of count density. However, system resolution and system sensitivity were constant in this study. Next, using these values analytic hierarchy process was adapted for this selection of imaging conditions. We conclude that this selection of imaging conditions can be analyzed quantitatively using analytic hierarchy process and this analysis develops theoretical consideration of imaging technique. (author)

  7. Technical guide for monitoring selected conditions related to wilderness character

    Science.gov (United States)

    Peter Landres; Steve Boutcher; Liese Dean; Troy Hall; Tamara Blett; Terry Carlson; Ann Mebane; Carol Hardy; Susan Rinehart; Linda Merigliano; David N. Cole; Andy Leach; Pam Wright; Deb Bumpus

    2009-01-01

    The purpose of monitoring wilderness character is to improve wilderness stewardship by providing managers a tool to assess how selected actions and conditions related to wilderness character are changing over time. Wilderness character monitoring provides information to help answer two key questions about wilderness character and wilderness stewardship: 1. How is...

  8. Contingency learning in human fear conditioning involves the ventral striatum.

    Science.gov (United States)

    Klucken, Tim; Tabbert, Katharina; Schweckendiek, Jan; Merz, Christian Josef; Kagerer, Sabine; Vaitl, Dieter; Stark, Rudolf

    2009-11-01

    The ability to detect and learn contingencies between fearful stimuli and their predictive cues is an important capacity to cope with the environment. Contingency awareness refers to the ability to verbalize the relationships between conditioned and unconditioned stimuli. Although there is a heated debate about the influence of contingency awareness on conditioned fear responses, neural correlates behind the formation process of contingency awareness have gained only little attention in human fear conditioning. Recent animal studies indicate that the ventral striatum (VS) could be involved in this process, but in human studies the VS is mostly associated with positive emotions. To examine this question, we reanalyzed four recently published classical fear conditioning studies (n = 117) with respect to the VS at three distinct levels of contingency awareness: subjects, who did not learn the contingencies (unaware), subjects, who learned the contingencies during the experiment (learned aware) and subjects, who were informed about the contingencies in advance (instructed aware). The results showed significantly increased activations in the left and right VS in learned aware compared to unaware subjects. Interestingly, this activation pattern was only found in learned but not in instructed aware subjects. We assume that the VS is not involved when contingency awareness does not develop during conditioning or when contingency awareness is unambiguously induced already prior to conditioning. VS involvement seems to be important for the transition from a contingency unaware to a contingency aware state. Implications for fear conditioning models as well as for the contingency awareness debate are discussed.

  9. Conditioning Factors for Group Management in Blended Learning Scenarios

    NARCIS (Netherlands)

    Pérez-Sanagustín, Mar; Hernández-Leo, Davinia; Blat, Josep

    2009-01-01

    Pérez-Sanagustín, M., Hernández-Leo D., & Blat, J. (accepted). Conditioning Factors for Group Management in Blended Learning Scenarios. The 9th IEEE International Conference on Advanced Learning Technologies. July, 14-18, 2009, Riga, Latvia.

  10. Learning Mixtures of Polynomials of Conditional Densities from Data

    DEFF Research Database (Denmark)

    L. López-Cruz, Pedro; Nielsen, Thomas Dyhre; Bielza, Concha

    2013-01-01

    Mixtures of polynomials (MoPs) are a non-parametric density estimation technique for hybrid Bayesian networks with continuous and discrete variables. We propose two methods for learning MoP ap- proximations of conditional densities from data. Both approaches are based on learning MoP approximatio...

  11. 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.

  12. Collaborative learning in condition based maintenance

    NARCIS (Netherlands)

    Koochaki, J.; Ao, SI; Gelman, L; Hukins, DWL; Hunter, A; Korsunsky, AM

    2009-01-01

    In recent years, the importance of reliable and consistent production equipments has increased. As a result, companies are shifting their maintenance policy from preventive maintenance towards Condition Based Maintenance (CBM). Despite the growing trend in this area and success stories of CBM

  13. 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.

  14. Moment Conditions Selection Based on Adaptive Penalized Empirical Likelihood

    Directory of Open Access Journals (Sweden)

    Yunquan Song

    2014-01-01

    Full Text Available Empirical likelihood is a very popular method and has been widely used in the fields of artificial intelligence (AI and data mining as tablets and mobile application and social media dominate the technology landscape. This paper proposes an empirical likelihood shrinkage method to efficiently estimate unknown parameters and select correct moment conditions simultaneously, when the model is defined by moment restrictions in which some are possibly misspecified. We show that our method enjoys oracle-like properties; that is, it consistently selects the correct moment conditions and at the same time its estimator is as efficient as the empirical likelihood estimator obtained by all correct moment conditions. Moreover, unlike the GMM, our proposed method allows us to carry out confidence regions for the parameters included in the model without estimating the covariances of the estimators. For empirical implementation, we provide some data-driven procedures for selecting the tuning parameter of the penalty function. The simulation results show that the method works remarkably well in terms of correct moment selection and the finite sample properties of the estimators. Also, a real-life example is carried out to illustrate the new methodology.

  15. Selection Criteria in Regime Switching Conditional Volatility Models

    Directory of Open Access Journals (Sweden)

    Thomas Chuffart

    2015-05-01

    Full Text Available A large number of nonlinear conditional heteroskedastic models have been proposed in the literature. Model selection is crucial to any statistical data analysis. In this article, we investigate whether the most commonly used selection criteria lead to choice of the right specification in a regime switching framework. We focus on two types of models: the Logistic Smooth Transition GARCH and the Markov-Switching GARCH models. Simulation experiments reveal that information criteria and loss functions can lead to misspecification ; BIC sometimes indicates the wrong regime switching framework. Depending on the Data Generating Process used in the experiments, great care is needed when choosing a criterion.

  16. Endogenously and exogenously driven selective sustained attention: Contributions to learning in kindergarten children.

    Science.gov (United States)

    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.

  17. Fast algorithm selection using learning curves

    NARCIS (Netherlands)

    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

  18. Management of select bacterial and parasitic conditions of raptors.

    Science.gov (United States)

    Willette, Michelle; Ponder, Julia; Cruz-Martinez, Luis; Arent, Lori; Bueno Padilla, Irene; de Francisco, Olga Nicolas; Redig, Patrick

    2009-09-01

    Raptors are susceptible to a broad array of established and emerging bacterial and parasitic diseases, including babesiosis, chlamydiosis, clostridiosis, coccidiosis, cryptosporidiosis, malaria, mycobacteriosis, pasteurellosis, salmonellosis, trichomoniasis, and pododermatitis. Many of these conditions are opportunistic and can be easily managed or averted with proper preventive measures related to captive management, husbandry and diet, and veterinary care. Once infected, treatment must be prompt, appropriate, and judicious. This article examines the significance, diagnosis, management, and prevention of select bacterial and parasitic pathogens of raptors.

  19. Rapid e-Learning Tools Selection Process for Cognitive and Psychomotor Learning Objectives

    Science.gov (United States)

    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…

  20. Women's Learning in Contract Work: Practicing Contradictions in Boundaryless Conditions

    Science.gov (United States)

    Fenwick, Tara

    2008-01-01

    The general rise in contractors, particularly among knowledge workers negotiating "boundaryless" employment conditions, has generated interest in the nature and forms of contract work. This article explores the learning of contract workers as they negotiate these conditions, with a focus on women. Drawing from a qualitative study of…

  1. Selective Learning and Teaching among Japanese and German Children

    Science.gov (United States)

    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…

  2. Over-Selectivity as a Learned Response

    Science.gov (United States)

    Reed, Phil; Petrina, Neysa; McHugh, Louise

    2011-01-01

    An experiment investigated the effects of different levels of task complexity in pre-training on over-selectivity in a subsequent match-to-sample (MTS) task. Twenty human participants were divided into two groups; exposed either to a 3-element, or a 9-element, compound stimulus as a sample during MTS training. After the completion of training,…

  3. Learning a New Selection Rule in Visual and Frontal Cortex.

    Science.gov (United States)

    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.

  4. Joint Feature Selection and Classification for Multilabel Learning.

    Science.gov (United States)

    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.

  5. Reinforcement Learning Explains Conditional Cooperation and Its Moody Cousin.

    Directory of Open Access Journals (Sweden)

    Takahiro Ezaki

    2016-07-01

    Full Text Available Direct reciprocity, or repeated interaction, is a main mechanism to sustain cooperation under social dilemmas involving two individuals. For larger groups and networks, which are probably more relevant to understanding and engineering our society, experiments employing repeated multiplayer social dilemma games have suggested that humans often show conditional cooperation behavior and its moody variant. Mechanisms underlying these behaviors largely remain unclear. Here we provide a proximate account for this behavior by showing that individuals adopting a type of reinforcement learning, called aspiration learning, phenomenologically behave as conditional cooperator. By definition, individuals are satisfied if and only if the obtained payoff is larger than a fixed aspiration level. They reinforce actions that have resulted in satisfactory outcomes and anti-reinforce those yielding unsatisfactory outcomes. The results obtained in the present study are general in that they explain extant experimental results obtained for both so-called moody and non-moody conditional cooperation, prisoner's dilemma and public goods games, and well-mixed groups and networks. Different from the previous theory, individuals are assumed to have no access to information about what other individuals are doing such that they cannot explicitly use conditional cooperation rules. In this sense, myopic aspiration learning in which the unconditional propensity of cooperation is modulated in every discrete time step explains conditional behavior of humans. Aspiration learners showing (moody conditional cooperation obeyed a noisy GRIM-like strategy. This is different from the Pavlov, a reinforcement learning strategy promoting mutual cooperation in two-player situations.

  6. Machine learning techniques to select variable stars

    Directory of Open Access Journals (Sweden)

    García-Varela Alejandro

    2017-01-01

    Full Text Available In order to perform a supervised classification of variable stars, we propose and evaluate a set of six features extracted from the magnitude density of the light curves. They are used to train automatic classification systems using state-of-the-art classifiers implemented in the R statistical computing environment. We find that random forests is the most successful method to select variables.

  7. Conditional Mutual Information Based Feature Selection for Classification Task

    Czech Academy of Sciences Publication Activity Database

    Novovičová, Jana; Somol, Petr; Haindl, Michal; Pudil, Pavel

    2007-01-01

    Roč. 45, č. 4756 (2007), s. 417-426 ISSN 0302-9743 R&D Projects: GA MŠk 1M0572; GA AV ČR IAA2075302 EU Projects: European Commission(XE) 507752 - MUSCLE Grant - others:GA MŠk(CZ) 2C06019 Institutional research plan: CEZ:AV0Z10750506 Keywords : Pattern classification * feature selection * conditional mutual information * text categorization Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.402, year: 2005

  8. Relational databases for conditions data and event selection in ATLAS

    International Nuclear Information System (INIS)

    Viegas, F; Hawkings, R; Dimitrov, G

    2008-01-01

    The ATLAS experiment at LHC will make extensive use of relational databases in both online and offline contexts, running to O(TBytes) per year. Two of the most challenging applications in terms of data volume and access patterns are conditions data, making use of the LHC conditions database, COOL, and the TAG database, that stores summary event quantities allowing a rapid selection of interesting events. Both of these databases are being replicated to regional computing centres using Oracle Streams technology, in collaboration with the LCG 3D project. Database optimisation, performance tests and first user experience with these applications will be described, together with plans for first LHC data-taking and future prospects

  9. Relational databases for conditions data and event selection in ATLAS

    Energy Technology Data Exchange (ETDEWEB)

    Viegas, F; Hawkings, R; Dimitrov, G [CERN, CH-1211 Geneve 23 (Switzerland)

    2008-07-15

    The ATLAS experiment at LHC will make extensive use of relational databases in both online and offline contexts, running to O(TBytes) per year. Two of the most challenging applications in terms of data volume and access patterns are conditions data, making use of the LHC conditions database, COOL, and the TAG database, that stores summary event quantities allowing a rapid selection of interesting events. Both of these databases are being replicated to regional computing centres using Oracle Streams technology, in collaboration with the LCG 3D project. Database optimisation, performance tests and first user experience with these applications will be described, together with plans for first LHC data-taking and future prospects.

  10. Selection of the optimum condition for electron capture detector operation

    International Nuclear Information System (INIS)

    Lasa, J.; Korus, A.

    1974-01-01

    A method of determination of the optimal work conditions for the electron capture detector is presented in the paper. Physical phenomena which occur in the detector, as well as the energetic dependence of the electron attachment process are taken into consideration. The influence of the kind of carrier gas, temperature, and the parameters of the supplied voltage in both direct and pulse methods on average values of electron energy is described. Dependence of the sensitivity of the electron capture detector on the carrier gas and the polarizing voltage is illustrated for the Model DNW-300 electron capture detector produced in Poland. Practical indications for selecting optimal conditions of electron capture detector operation are given at the end of the paper. (author)

  11. On the Conditioning of Machine-Learning-Assisted Turbulence Modeling

    Science.gov (United States)

    Wu, Jinlong; Sun, Rui; Wang, Qiqi; Xiao, Heng

    2017-11-01

    Recently, several researchers have demonstrated that machine learning techniques can be used to improve the RANS modeled Reynolds stress by training on available database of high fidelity simulations. However, obtaining improved mean velocity field remains an unsolved challenge, restricting the predictive capability of current machine-learning-assisted turbulence modeling approaches. In this work we define a condition number to evaluate the model conditioning of data-driven turbulence modeling approaches, and propose a stability-oriented machine learning framework to model Reynolds stress. Two canonical flows, the flow in a square duct and the flow over periodic hills, are investigated to demonstrate the predictive capability of the proposed framework. The satisfactory prediction performance of mean velocity field for both flows demonstrates the predictive capability of the proposed framework for machine-learning-assisted turbulence modeling. With showing the capability of improving the prediction of mean flow field, the proposed stability-oriented machine learning framework bridges the gap between the existing machine-learning-assisted turbulence modeling approaches and the demand of predictive capability of turbulence models in real applications.

  12. 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.

  13. Second-order conditioning and conditioned inhibition: influences of speed versus accuracy on human causal learning.

    Directory of Open Access Journals (Sweden)

    Jessica C Lee

    Full Text Available In human causal learning, excitatory and inhibitory learning effects can sometimes be found in the same paradigm by altering the learning conditions. This study aims to explore whether learning in the feature negative paradigm can be dissociated by emphasising speed over accuracy. In two causal learning experiments, participants were given a feature negative discrimination in which the outcome caused by one cue was prevented by the addition of another. Participants completed training trials either in a self-paced fashion with instructions emphasising accuracy, or under strict time constraints with instructions emphasising speed. Using summation tests in which the preventative cue was paired with another causal cue, participants in the accuracy groups correctly rated the preventative cue as if it reduced the probability of the outcome. However, participants in the speed groups rated the preventative cue as if it increased the probability of the outcome. In Experiment 1, both speed and accuracy groups later judged the same cue to be preventative in a reasoned inference task. Experiment 2 failed to find evidence of similar dissociations in retrospective revaluation (release from overshadowing vs. mediated extinction or learning about a redundant cue (blocking vs. augmentation. However in the same experiment, the tendency for the accuracy group to show conditioned inhibition and the speed group to show second-order conditioning was consistent even across sub-sets of the speed and accuracy groups with equivalent accuracy in training, suggesting that second-order conditioning is not merely a consequence of poorer acquisition. This dissociation mirrors the trade-off between second-order conditioning and conditioned inhibition observed in animal conditioning when training is extended.

  14. Influence of visual observational conditions on tongue motor learning

    DEFF Research Database (Denmark)

    Kothari, Mohit; Liu, Xuimei; Baad-Hansen, Lene

    2016-01-01

    To investigate the impact of visual observational conditions on performance during a standardized tongue-protrusion training (TPT) task and to evaluate subject-based reports of helpfulness, disturbance, pain, and fatigue due to the observational conditions on 0-10 numerical rating scales. Forty...... regarding the level of disturbance, pain or fatigue. Self-observation of tongue-training facilitated behavioral aspects of tongue motor learning compared with model-observation but not compared with control....

  15. Role of classical conditioning in learning gastrointestinal symptoms

    OpenAIRE

    Stockhorst, Ursula; Enck, Paul; Klosterhalfen, Sibylle

    2007-01-01

    Nausea and/or vomiting are aversive gastrointestinal (GI) symptoms. Nausea and vomiting manifest unconditionally after a nauseogenic experience. However, there is correlative, quasiexperimental and experimental evidence that nausea and vomiting can also be learned via classical (Pavlovian) conditioning and might occur in anticipation of the nauseogenic event. Classical conditioning of nausea can develop with chemotherapy in cancer patients. Initially, nausea and vomiting occur during and afte...

  16. Are environmental conditions in South African classrooms conducive for learning?

    CSIR Research Space (South Africa)

    Gibberd, Jeremy T

    2013-10-01

    Full Text Available not provide an environment that promotes productivity and comfort for particular summer conditions, and therefore is unlikely to be conducive for learning. The paper draws a number of conclusions from the study and makes recommendations for further research....

  17. Online Learning in Higher Education: Necessary and Sufficient Conditions

    Science.gov (United States)

    Lim, Cher Ping

    2005-01-01

    The spectacular development of information and communication technologies through the Internet has provided opportunities for students to explore the virtual world of information. In this article, the author discusses the necessary and sufficient conditions for successful online learning in educational institutions. The necessary conditions…

  18. Variability in Second Language Learning: The Roles of Individual Differences, Learning Conditions, and Linguistic Complexity

    Science.gov (United States)

    Tagarelli, Kaitlyn M.; Ruiz, Simón; Vega, José Luis Moreno; Rebuschat, Patrick

    2016-01-01

    Second language learning outcomes are highly variable, due to a variety of factors, including individual differences, exposure conditions, and linguistic complexity. However, exactly how these factors interact to influence language learning is unknown. This article examines the relationship between these three variables in language learners.…

  19. Theory of mind selectively predicts preschoolers’ knowledge-based selective word learning

    Science.gov (United States)

    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

  20. Theory of mind selectively predicts preschoolers' knowledge-based selective word learning.

    Science.gov (United States)

    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.

  1. Force Sensor Based Tool Condition Monitoring Using a Heterogeneous Ensemble Learning Model

    Directory of Open Access Journals (Sweden)

    Guofeng Wang

    2014-11-01

    Full Text Available Tool condition monitoring (TCM plays an important role in improving machining efficiency and guaranteeing workpiece quality. In order to realize reliable recognition of the tool condition, a robust classifier needs to be constructed to depict the relationship between tool wear states and sensory information. However, because of the complexity of the machining process and the uncertainty of the tool wear evolution, it is hard for a single classifier to fit all the collected samples without sacrificing generalization ability. In this paper, heterogeneous ensemble learning is proposed to realize tool condition monitoring in which the support vector machine (SVM, hidden Markov model (HMM and radius basis function (RBF are selected as base classifiers and a stacking ensemble strategy is further used to reflect the relationship between the outputs of these base classifiers and tool wear states. Based on the heterogeneous ensemble learning classifier, an online monitoring system is constructed in which the harmonic features are extracted from force signals and a minimal redundancy and maximal relevance (mRMR algorithm is utilized to select the most prominent features. To verify the effectiveness of the proposed method, a titanium alloy milling experiment was carried out and samples with different tool wear states were collected to build the proposed heterogeneous ensemble learning classifier. Moreover, the homogeneous ensemble learning model and majority voting strategy are also adopted to make a comparison. The analysis and comparison results show that the proposed heterogeneous ensemble learning classifier performs better in both classification accuracy and stability.

  2. The selective serotonin reuptake inhibitor, escitalopram, enhances inhibition of prepotent responding and spatial reversal learning

    Science.gov (United States)

    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

  3. Selecting Learning Tasks: Effects of Adaptation and Shared Control on Learning Efficiency and Task Involvement

    Science.gov (United States)

    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…

  4. Conditional High-Order Boltzmann Machines for Supervised Relation Learning.

    Science.gov (United States)

    Huang, Yan; Wang, Wei; Wang, Liang; Tan, Tieniu

    2017-09-01

    Relation learning is a fundamental problem in many vision tasks. Recently, high-order Boltzmann machine and its variants have shown their great potentials in learning various types of data relation in a range of tasks. But most of these models are learned in an unsupervised way, i.e., without using relation class labels, which are not very discriminative for some challenging tasks, e.g., face verification. In this paper, with the goal to perform supervised relation learning, we introduce relation class labels into conventional high-order multiplicative interactions with pairwise input samples, and propose a conditional high-order Boltzmann Machine (CHBM), which can learn to classify the data relation in a binary classification way. To be able to deal with more complex data relation, we develop two improved variants of CHBM: 1) latent CHBM, which jointly performs relation feature learning and classification, by using a set of latent variables to block the pathway from pairwise input samples to output relation labels and 2) gated CHBM, which untangles factors of variation in data relation, by exploiting a set of latent variables to multiplicatively gate the classification of CHBM. To reduce the large number of model parameters generated by the multiplicative interactions, we approximately factorize high-order parameter tensors into multiple matrices. Then, we develop efficient supervised learning algorithms, by first pretraining the models using joint likelihood to provide good parameter initialization, and then finetuning them using conditional likelihood to enhance the discriminant ability. We apply the proposed models to a series of tasks including invariant recognition, face verification, and action similarity labeling. Experimental results demonstrate that by exploiting supervised relation labels, our models can greatly improve the performance.

  5. Statistical learning of action: the role of conditional probability.

    Science.gov (United States)

    Meyer, Meredith; Baldwin, Dare

    2011-12-01

    Identification of distinct units within a continuous flow of human action is fundamental to action processing. Such segmentation may rest in part on statistical learning. In a series of four experiments, we examined what types of statistics people can use to segment a continuous stream involving many brief, goal-directed action elements. The results of Experiment 1 showed no evidence for sensitivity to conditional probability, whereas Experiment 2 displayed learning based on joint probability. In Experiment 3, we demonstrated that additional exposure to the input failed to engender sensitivity to conditional probability. However, the results of Experiment 4 showed that a subset of adults-namely, those more successful at identifying actions that had been seen more frequently than comparison sequences-were also successful at learning conditional-probability statistics. These experiments help to clarify the mechanisms subserving processing of intentional action, and they highlight important differences from, as well as similarities to, prior studies of statistical learning in other domains, including language.

  6. Project Selection in the Design Studio: Absence of Learning Environments

    Science.gov (United States)

    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…

  7. Role of classical conditioning in learning gastrointestinal symptoms.

    Science.gov (United States)

    Stockhorst, Ursula; Enck, Paul; Klosterhalfen, Sibylle

    2007-07-07

    Nausea and/or vomiting are aversive gastrointestinal (GI) symptoms. Nausea and vomiting manifest unconditionally after a nauseogenic experience. However, there is correlative, quasiexperimental and experimental evidence that nausea and vomiting can also be learned via classical (Pavlovian) conditioning and might occur in anticipation of the nauseogenic event. Classical conditioning of nausea can develop with chemotherapy in cancer patients. Initially, nausea and vomiting occur during and after the administration of cytotoxic drugs (post-treatment nausea and vomiting) as unconditioned responses (UR). In addition, 20%-30% of cancer patients receiving chemotherapy report these side effects, despite antiemetic medication, when being re-exposed to the stimuli that usually signal the chemotherapy session and its drug infusion. These symptoms are called anticipatory nausea (AN) and/or anticipatory vomiting (ANV) and are explained by classical conditioning. Moreover, there is recent evidence for the assumption that post-chemotherapy nausea is at least partly influenced by learning. After summarizing the relevant assumptions of the conditioning model, revealing that a context can become a conditioned stimulus (CS), the present paper summarizes data that nausea and/or vomiting is acquired by classical conditioning and, consequently, may be alleviated by conditioning techniques. Our own research has focussed on two aspects and is emphasized here. First, a conditioned nausea model was established in healthy humans using body rotation as the nausea-inducing treatment. The validity of this motion-sickness model to examine conditioning mechanisms in the acquisition and alleviation of conditioned nausea and associated endocrine and immunological responses is summarized. Results from the rotation-induced motion sickness model showed that gender is an important moderator variable to be considered in further studies. This paper concludes with a review of the application of the

  8. [Parents' unemployment, selected life conditions, adolescents' wellbeing and perceived health].

    Science.gov (United States)

    Supranowicz, Piotr

    2005-01-01

    Unemployment in Poland is one of the most negative outcomes of the economical transformations taking place in the last decade of the XX and first years of the XXI century. Therefore, the study on an influence of parents' unemployment upon adolescents' life conditions and health was undertaken in Health Promotion and Postgraduate Training Department of the National Institute of Hygiene. The data were collected from randomly selected sample of 783 students aged 14-15 years attending to ten private and public secondary schools (gymnasiums) in Warsaw. A part of the questionnaire elaborated in Health Promotion and Postgraduate Department covered information about negative life events, which had occurred in the previous year, also about a loss of the job by father or mother. The self-assessment of health, and physical and psychical wellbeing measured the perceived health. The study showed that significantly higher percentage of the students, whose father or mother had lost a job in the previous year, noticed also occurrence of father and mother health disorders, lack of support from father and mother, frequent quarrels between parents, too much of home duties, worsening a housing conditions, lack of possibilities to travel away on vacation and lack of own money. The differences were higher, if both the parents were unemployed. Moreover, the children of unemployed parents significantly lower assessed their health, and physical and psychical wellbeing. It is necessary to help immediately the students, whose parents are unemployed, with financial and psychological support in frame of the programmes of unemployment overcoming.

  9. A Machine LearningFramework to Forecast Wave Conditions

    Science.gov (United States)

    Zhang, Y.; James, S. C.; O'Donncha, F.

    2017-12-01

    Recently, significant effort has been undertaken to quantify and extract wave energy because it is renewable, environmental friendly, abundant, and often close to population centers. However, a major challenge is the ability to accurately and quickly predict energy production, especially across a 48-hour cycle. Accurate forecasting of wave conditions is a challenging undertaking that typically involves solving the spectral action-balance equation on a discretized grid with high spatial resolution. The nature of the computations typically demands high-performance computing infrastructure. Using a case-study site at Monterey Bay, California, a machine learning framework was trained to replicate numerically simulated wave conditions at a fraction of the typical computational cost. Specifically, the physics-based Simulating WAves Nearshore (SWAN) model, driven by measured wave conditions, nowcast ocean currents, and wind data, was used to generate training data for machine learning algorithms. The model was run between April 1st, 2013 and May 31st, 2017 generating forecasts at three-hour intervals yielding 11,078 distinct model outputs. SWAN-generated fields of 3,104 wave heights and a characteristic period could be replicated through simple matrix multiplications using the mapping matrices from machine learning algorithms. In fact, wave-height RMSEs from the machine learning algorithms (9 cm) were less than those for the SWAN model-verification exercise where those simulations were compared to buoy wave data within the model domain (>40 cm). The validated machine learning approach, which acts as an accurate surrogate for the SWAN model, can now be used to perform real-time forecasts of wave conditions for the next 48 hours using available forecasted boundary wave conditions, ocean currents, and winds. This solution has obvious applications to wave-energy generation as accurate wave conditions can be forecasted with over a three-order-of-magnitude reduction in

  10. 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...

  11. Drosophila Courtship Conditioning As a Measure of Learning and Memory.

    Science.gov (United States)

    Koemans, Tom S; Oppitz, Cornelia; Donders, Rogier A T; van Bokhoven, Hans; Schenck, Annette; Keleman, Krystyna; Kramer, Jamie M

    2017-06-05

    Many insights into the molecular mechanisms underlying learning and memory have been elucidated through the use of simple behavioral assays in model organisms such as the fruit fly, Drosophila melanogaster. Drosophila is useful for understanding the basic neurobiology underlying cognitive deficits resulting from mutations in genes associated with human cognitive disorders, such as intellectual disability (ID) and autism. This work describes a methodology for testing learning and memory using a classic paradigm in Drosophila known as courtship conditioning. Male flies court females using a distinct pattern of easily recognizable behaviors. Premated females are not receptive to mating and will reject the male's copulation attempts. In response to this rejection, male flies reduce their courtship behavior. This learned reduction in courtship behavior is measured over time, serving as an indicator of learning and memory. The basic numerical output of this assay is the courtship index (CI), which is defined as the percentage of time that a male spends courting during a 10 min interval. The learning index (LI) is the relative reduction of CI in flies that have been exposed to a premated female compared to naïve flies with no previous social encounters. For the statistical comparison of LIs between genotypes, a randomization test with bootstrapping is used. To illustrate how the assay can be used to address the role of a gene relating to learning and memory, the pan-neuronal knockdown of Dihydroxyacetone phosphate acyltransferase (Dhap-at) was characterized here. The human ortholog of Dhap-at, glyceronephosphate O-acyltransferase (GNPT), is involved in rhizomelic chondrodysplasia punctata type 2, an autosomal-recessive syndrome characterized by severe ID. Using the courtship conditioning assay, it was determined that Dhap-at is required for long-term memory, but not for short-term memory. This result serves as a basis for further investigation of the underlying molecular

  12. 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

  13. 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.

  14. Pairwise Constraint-Guided Sparse Learning for Feature Selection.

    Science.gov (United States)

    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.

  15. The Role of Nucleus Accumbens Shell in Learning about Neutral versus Excitatory Stimuli during Pavlovian Fear Conditioning

    Science.gov (United States)

    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…

  16. 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

  17. LEARNING MATERIALS SELECTION FOR DIFFERENTIATED INSTRUCTION OF ENGLISH FOR SPECIFIC PURPOSES OF FUTURE PROFESSIONALS IN THE FIELD OF INFORMATION TECHNOLOGY

    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

  18. Learning to predict and control harmful events: chronic pain and conditioning.

    Science.gov (United States)

    Vlaeyen, Johan W S

    2015-04-01

    Pain is a biologically relevant signal and response to bodily threat, associated with the urge to restore the integrity of the body. Immediate protective responses include increased arousal, selective attention, escape, and facial expressions, followed by recuperative avoidance and safety-seeking behaviors. To facilitate early and effective protection against future bodily threat or injury, learning takes place rapidly. Learning is the observable change in behavior due to events in the internal and external environmental and includes nonassociative (habituation and sensitization) and associative learning (Pavlovian and operant conditioning). Once acquired, these knowledge representations remain stored in memory and may generalize to perceptually or functionally similar events. Moreover, these processes are not just a consequence of pain; they may directly influence pain perception. In contrast to the rapid acquisition of learned responses, their extinction is slow, fragile, context dependent and only occurs through inhibitory processes. Here, we review features of associative forms of learning in humans that contribute to pain, pain-related distress, and disability and discuss promising future directions. Although conditioning has a long and honorable history, a conditioning perspective still might open new windows on novel treatment modalities that facilitate the well-being of individuals with chronic pain.

  19. Word learning emerges from the interaction of online referent selection and slow associative learning

    Science.gov (United States)

    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

  20. Learning to Select Supplier Portfolios for Service Supply Chain.

    Science.gov (United States)

    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.

  1. Learning from Fables: Moral Values in Three Selected English Stories

    Science.gov (United States)

    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…

  2. Instance Selection for Classifier Performance Estimation in Meta Learning

    OpenAIRE

    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...

  3. Weed spectrum and selectivity of tembotrione under varying environmental conditions

    Directory of Open Access Journals (Sweden)

    Gatzweiler, Elmar

    2012-03-01

    Full Text Available Tembotrione is a novel HPPD maize herbicide effective against a wide range of broadleaf and grass weeds. Some characteristics of this compound are described in this paper linking weed and crop responses following tembotrione applications to environmental parameters or use conditions. The activity of HPPD herbicides is very much dependant on the availability of light. Increasing illumination intensities following application augmented the activity levels of several comparable HPPD compounds in a growth chamber experiment. Tembotrione was shown to be more efficacious at low and high illumination intensities compared to standard herbicides applied at the same rate. At the high intensity, tembotrione retained its high efficacy from two up to four weeks after application showing a rapid and strong herbicidal activity. The activity following post-emergent treatments of tembotrione against broadleaf weeds was influenced by soil characteristics such as soil texture and organic matter content in a glasshouse test. The level of weed suppression clearly declined stronger on heavier soils than on lighter soils at a rather low application rate of 12.5 g a.i./ha and lower. This is a clear indication of residual efficacy of tembotrione. The selectivity of tembotrione was tested on numerous maize varieties following post-emergent treatment with tembotrione alone or in mixture with the safener isoxadifen-ethyl under field conditions in Germany in comparison to a standard herbicide. The level of crop phytotoxicity tended to increase in the following order: Tembotrione plus safener, standard herbicide to tembotrione alone. Only the mixture of tembotrione with safener did not cause significant adverse effects on maize. Another field experiment in the USA examined crop phytotoxicity using one maize variety in a situation of infurrow soil insecticide treatment followed by a post-emergent application of tembotrione (plus/minus isoxadifen-ethyl and standard herbicides

  4. Evolution of learning in fluctuating environments: when selection favors both social and exploratory individual learning.

    Science.gov (United States)

    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.

  5. When congruence breeds preference: the influence of selective attention processes on evaluative conditioning.

    Science.gov (United States)

    Blask, Katarina; Walther, Eva; Frings, Christian

    2017-09-01

    We investigated in two experiments whether selective attention processes modulate evaluative conditioning (EC). Based on the fact that the typical stimuli in an EC paradigm involve an affect-laden unconditioned stimulus (US) and a neutral conditioned stimulus (CS), we started from the assumption that learning might depend in part upon selective attention to the US. Attention to the US was manipulated by including a variant of the Eriksen flanker task in the EC paradigm. Similarly to the original Flanker paradigm, we implemented a target-distracter logic by introducing the CS as the task-relevant stimulus (i.e. the target) to which the participants had to respond and the US as a task-irrelevant distracter. Experiment 1 showed that CS-US congruence modulated EC if the CS had to be selected against the US. Specifically, EC was more pronounced for congruent CS-US pairs as compared to incongruent CS-US pairs. Experiment 2 disentangled CS-US congruence and CS-US compatibility and suggested that it is indeed CS-US stimulus congruence rather than CS-US response compatibility that modulates EC.

  6. Selective role for DNMT3a in learning and memory.

    Science.gov (United States)

    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.

  7. Mechanisms of radiation-induced conditioned taste aversion learning

    International Nuclear Information System (INIS)

    Rabin, B.M.; Hunt, W.A.

    1986-01-01

    The literature on taste aversion learning is reviewed and discussed, with particular emphasis on those studies that have used exposure to ionizing radiation as an unconditioned stimulus to produce a conditioned taste aversion. The primary aim of the review is to attempt to define the mechanisms that lead to the initiation of the taste aversion response following exposure to ionizing radiation. Studies using drug treatments to produce a taste aversion have been included to the extent that they are relevant to understanding the mechanisms by which exposure to ionizing radiation can affect the behavior of the organism. 141 references

  8. Weather conditions drive dynamic habitat selection in a generalist predator

    DEFF Research Database (Denmark)

    Sunde, Peter; Thorup, Kasper; Jacobsen, Lars B.

    2014-01-01

    Despite the dynamic nature of habitat selection, temporal variation as arising from factors such as weather are rarely quantified in species-habitat relationships. We analysed habitat use and selection (use/availability) of foraging, radio-tagged little owls (Athene noctua), a nocturnal, year...... and quadratic effects of temperature. Even when controlling for the temporal context, both land cover types were used more evenly than predicted from variation in availability (functional response in habitat selection). Use of two other land cover categories (pastures and moist areas) increased linearly...... with temperature and was proportional to their availability. The study shows that habitat selection by generalist foragers may be highly dependent on temporal variables such as weather, probably because such foragers switch between weather dependent feeding opportunities offered by different land cover types...

  9. Selection of the initial conditions in the tunneling time definition

    International Nuclear Information System (INIS)

    Zajchenko, A.K.

    2004-01-01

    The necessity of changing of the initial conditions in the Olkhovsky - Recami definition of the tunneling time is justified. The new initial conditions are proposed which adequately taking into account the irreversibility of the wave packets spreading. The expression for the tunneling time with the new initial conditions is reduced to the form which is convenient for the performing and controlling the accuracy of calculations

  10. 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.

  11. Exploring the Relation between Teachers' Perceptions of Workplace Conditions and Their Professional Learning Goals

    Science.gov (United States)

    Louws, Monika L.; Meirink, Jacobiene A.; van Veen, Klaas; van Driel, Jan H.

    2017-01-01

    Schools' structural workplace conditions (e.g. learning resources and professional development policies) and cultural workplace conditions (e.g. school leadership, teachers' collaborative culture) have been found to affect the way teachers learn. It is not so much the objective conditions that support or impede professional learning but the way…

  12. The orexin component of fasting triggers memory processes underlying conditioned food selection in the rat.

    Science.gov (United States)

    Ferry, Barbara; Duchamp-Viret, Patricia

    2014-03-14

    To test the selectivity of the orexin A (OXA) system in olfactory sensitivity, the present study compared the effects of fasting and of central infusion of OXA on the memory processes underlying odor-malaise association during the conditioned odor aversion (COA) paradigm. Animals implanted with a cannula in the left ventricle received ICV infusion of OXA or artificial cerebrospinal fluid (ACSF) 1 h before COA acquisition. An additional group of intact rats were food-deprived for 24 h before acquisition. Results showed that the increased olfactory sensitivity induced by fasting and by OXA infusion was accompanied by enhanced COA performance. The present results suggest that fasting-induced central OXA release influenced COA learning by increasing not only olfactory sensitivity, but also the memory processes underlying the odor-malaise association.

  13. Brake fault diagnosis using Clonal Selection Classification Algorithm (CSCA – A statistical learning approach

    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.

  14. Selective visual scaling of time-scale processes facilitates broadband learning of isometric force frequency tracking.

    Science.gov (United States)

    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.

  15. Objective Method for Selecting Outdoor Reporting Conditions for Photovoltaic Performance

    International Nuclear Information System (INIS)

    Maish, A.

    1999-01-01

    Outdoor performance of photovoltaic modules and systems depends on prevailing conditions at the time of measurement. Outdoor test conditions must be relevant to device performance and readily attainable. Flat-plate, nonconcentrator PV device performance is reported with respect to fixed conditions referred to as Standard Reporting Conditions (SRC) of 1 kW/m plane of array total irradiance, 25 C device temperature, and a reference spectral distribution at air mass 1.5 under certain atmospheric conditions. We report a method of analyzing historical meteorological and irradiance data to determine the range of outdoor environmental parameters and solar irradiance components that affect solar collector performance when the SRC 1 kW/m total irradiance value occurs outdoors. We used data from the 30 year U.S. National Solar Radiation Data Base (NSRDB) , restricting irradiance conditions to within +/- 25 W/m of 1 kW/m on a solar tracking flat-plate collector. The distributions of environmental parameter values under these conditions are non-Gaussian and site dependent. Therefore the median, as opposed to the mean, of the observed distributions is chosen to represent appropriate outdoor reporting conditions. We found the average medians for the direct beam component (834 W/m), ambient temperature (24.4 C), total column water vapor (1.4 cm), and air mass (1.43) are near commonly used SRC values. Average median wind speed (4.4 m/s) and broadband aerosol optical depth (0.08) were significantly different from commonly used values

  16. The chemotherapeutic agent paclitaxel selectively impairs reversal learning while sparing prior learning, new learning and episodic memory.

    Science.gov (United States)

    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.

  17. 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.

  18. Stochastic subset selection for learning with kernel machines.

    Science.gov (United States)

    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.

  19. 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.

  20. How Important Are Student-Selected versus Instructor-Selected Literature Resources for Students' Learning and Motivation in Problem-Based Learning?

    Science.gov (United States)

    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…

  1. Indoor Environmental Conditions and Sanitary Practices in Selected ...

    African Journals Online (AJOL)

    Rapidly urbanizing cities are witnessing an increase in Day care centres (DCCs) whose environmental conditions are substandard. This scenario has negative consequences on the health of the DCC attendees and yet information on some of the indicators such as the level of sanitary practices is not adequately ...

  2. Socio-economic conditions in selected biosphere reserves

    Czech Academy of Sciences Publication Activity Database

    Kušová, Drahomíra; Těšitel, Jan; Matějka, K.; Bartoš, Michael

    2006-01-01

    Roč. 12, č. 3 (2006), s. 157-169 ISSN 1211-7420 R&D Projects: GA MŽP(CZ) SM/610/3/03 Institutional research plan: CEZ:AV0Z60870520 Keywords : nature protection * socio-economic conditions * biosphere reserves * sustainable development Subject RIV: EH - Ecology, Behaviour

  3. PLASTICITY OF SELECTED METALLIC MATERIALS IN DYNAMIC DEFORMATION CONDITIONS

    Directory of Open Access Journals (Sweden)

    Jacek PAWLICKI

    2014-06-01

    Full Text Available Characteristics of a modernized flywheel machine has been presented in the paper. The laboratory stand enables to perform dynamic tensile tests and impact bending with a linear velocity of the enforcing element in the range of 5÷40 m/s. A new data acquisition system, based on the tensometric sensors, allows for significant qualitative improvement of registered signals. Some preliminary dynamic forming tests were performed for the selected group of metallic materials. Subsequent microstructural examinations and identification of the fracture type enabled to describe a correlation between strain rate, strain and microstructure.

  4. Continuous Time Portfolio Selection under Conditional Capital at Risk

    Directory of Open Access Journals (Sweden)

    Gordana Dmitrasinovic-Vidovic

    2010-01-01

    Full Text Available Portfolio optimization with respect to different risk measures is of interest to both practitioners and academics. For there to be a well-defined optimal portfolio, it is important that the risk measure be coherent and quasiconvex with respect to the proportion invested in risky assets. In this paper we investigate one such measure—conditional capital at risk—and find the optimal strategies under this measure, in the Black-Scholes continuous time setting, with time dependent coefficients.

  5. Conditions for selection, training and placement of personnel

    International Nuclear Information System (INIS)

    Chrkavy, L.

    1983-01-01

    Methods applied in the choice of personnel include: the assessment of personnel files, references, interviews, examinations, long-term observation of the respective person. Investment intents go hand in hand with the concept of labour demands. The planned employment of personnel takes place from the very beginning of the construction of the power plant. At the Bohunice V-1 nuclear power plant 23 university graduates, 29 secondary school graduates and 64 graduates of vocational schools were employed every year. Social measures and complex care are being implemented. Personnel is being selected also on the basis of an assessment of their psychic qualities which are very important in view of the high personal and social responsibility of nuclear power plant personnel. The high technical standard of the equipment places high demands on the education level of all personnel, high demands on training, high remuneration and high level of allround care of personnel. (M.D.)

  6. Selected medical conditions and risk of pancreatic cancer.

    Science.gov (United States)

    Olson, Sara H

    2012-01-01

    We review the current evidence for associations of several medical conditions with risk of pancreatic cancer, including allergies, pancreatitis, gall bladder disease, cholecystectomy, ulcers, gastrectomy, appendectomy, and tonsillectomy. There are consistent findings of reduced risk associated with presence of self-reported allergies, particularly hay fever but not asthma; data on other allergies are limited and inconclusive. Several studies provide evidence that patients with pancreatic cancer are more likely than comparison groups to report pancreatitis. Those studies that investigated the time between onset of pancreatitis and diagnosis of pancreatic cancer found that risk estimates declined with longer periods of time; however, increased risks were noted for long-term pancreatitis, indicating that this condition is both a risk factor and a sign of early disease. Increased risk was reported in association with cholelithiasis, but the few studies that considered time before diagnosis of cancer did not find increased risk for cholelithiasis diagnosed in the more distant past. There is weak evidence that cholecystectomy 2 or more years before cancer diagnosis is related to risk, but this is based on only a few studies. There is no consistent association between ulcers and risk, while gastrectomy may increase risk. Overall, study of these conditions, particularly those that are rare, presents methodologic challenges. Time between diagnoses is likely to be important but is not considered in most studies. Lack of adequate control in several studies for risk factors such as smoking and heavy alcohol use also makes it difficult to draw firm conclusions about these results. Copyright © 2011 Wiley Periodicals, Inc.

  7. VALIDATION OF A SCALE OF LEVELS AND CONDITIONS OF ORGANIZATIONAL LEARNING

    Directory of Open Access Journals (Sweden)

    DELIO IGNACIO CASTAÑEDA

    2007-08-01

    Full Text Available Organizational learning has been studied from the perspective of levels of learning: individual, group and organizational,as well as from the needed conditions for learning in order to be produced. An instrument of six dimensions wasvalidated, three of them levels: individual, group and organizational, and three of them conditions: culture oforganizational learning, training and transmission of information. Participants were 845 workers of a public institution.From results support was found for the three levels of learning and for two conditions: culture of organizationallearning and training. Additionally a condition called strategic clarity was identified.

  8. Laser surgery for selected small animal soft-tissue conditions

    Science.gov (United States)

    Bartels, Kenneth E.

    1991-05-01

    With the acquisition of a Nd:YAG and a CO2 laser in the College of Veterinary Medicine at Oklahoma State University in 1989, over 100 small animal clinical cases have been managed with these modern modalities for surgical excision and tissue vaporization. Most procedures have been for oncologic problems, but inflammatory, infectious, or congenital conditions including vaporization of acral lick 'granulomas,' excision/vaporization of foreign body induced, infected draining tracts, and resection of elongated soft palates have been successfully accomplished. Laser excision or vaporization of both benign and malignant neoplasms have effectively been performed and include feline nasal squamous cell carcinoma, mast cell tumors, and rectal/anal neoplasms. Results to date have been excellent with animals exhibiting little postoperative pain, swelling, and inflammation. Investigations involving application of laser energy for tissue welding of esophageal lacerations and hepatitic interstitial hyperthermia for metastatic colorectal cancer have also shown potential. A review of cases with an emphasis on survival time and postoperative morbidity suggests that carefully planned laser surgical procedures in clinical veterinary practice done with standardized protocols and techniques offer an acceptable means of treating conditions that were previously considered extremely difficult or virtually impossible to perform.

  9. System Quality Characteristics for Selecting Mobile Learning Applications

    Science.gov (United States)

    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…

  10. Selection of Learning Media Mathematics for Junior School Students

    Science.gov (United States)

    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…

  11. Analysis of an Interactive Technology Supported Problem-Based Learning STEM Project Using Selected Learning Sciences Interest Areas (SLSIA)

    Science.gov (United States)

    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…

  12. Training self-assessment and task-selection skills to foster self-regulated learning: Do trained skills transfer across domains?

    Science.gov (United States)

    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.

  13. Learning outdoors: male lizards show flexible spatial learning under semi-natural conditions

    Science.gov (United States)

    Noble, Daniel W. A.; Carazo, Pau; Whiting, Martin J.

    2012-01-01

    Spatial cognition is predicted to be a fundamental component of fitness in many lizard species, and yet some studies suggest that it is relatively slow and inflexible. However, such claims are based on work conducted using experimental designs or in artificial contexts that may underestimate their cognitive abilities. We used a biologically realistic experimental procedure (using simulated predatory attacks) to study spatial learning and its flexibility in the lizard Eulamprus quoyii in semi-natural outdoor enclosures under similar conditions to those experienced by lizards in the wild. To evaluate the flexibility of spatial learning, we conducted a reversal spatial-learning task in which positive and negative reinforcements of learnt spatial stimuli were switched. Nineteen (32%) male lizards learnt both tasks within 10 days (spatial task mean: 8.16 ± 0.69 (s.e.) and reversal spatial task mean: 10.74 ± 0.98 (s.e.) trials). We demonstrate that E. quoyii are capable of flexible spatial learning and suggest that future studies focus on a range of lizard species which differ in phylogeny and/or ecology, using biologically relevant cognitive tasks, in an effort to bridge the cognitive divide between ecto- and endotherms. PMID:23075525

  14. A strategy for clone selection under different production conditions.

    Science.gov (United States)

    Legmann, Rachel; Benoit, Brian; Fedechko, Ronald W; Deppeler, Cynthia L; Srinivasan, Sriram; Robins, Russell H; McCormick, Ellen L; Ferrick, David A; Rodgers, Seth T; Russo, A Peter

    2011-01-01

    Top performing clones have failed at the manufacturing scale while the true best performer may have been rejected early in the screening process. Therefore, the ability to screen multiple clones in complex fed-batch processes using multiple process variations can be used to assess robustness and to identify critical factors. This dynamic ranking of clones' strategy requires the execution of many parallel experiments than traditional approaches. Therefore, this approach is best suited for micro-bioreactor models which can perform hundreds of experiments quickly and efficiently. In this study, a fully monitored and controlled small scale platform was used to screen eight CHO clones producing a recombinant monoclonal antibody across several process variations, including different feeding strategies, temperature shifts and pH control profiles. The first screen utilized 240 micro-bioreactors were run for two weeks for this assessment of the scale-down model as a high-throughput tool for clone evaluation. The richness of the outcome data enable to clearly identify the best and worst clone as well as process in term of maximum monoclonal antibody titer. The follow-up comparison study utilized 180 micro-bioreactors in a full factorial design and a subset of 12 clone/process combinations was selected to be run parallel in duplicate shake flasks. Good correlation between the micro-bioreactor predictions and those made in shake flasks with a Pearson correlation value of 0.94. The results also demonstrate that this micro-scale system can perform clone screening and process optimization for gaining significant titer improvements simultaneously. This dynamic ranking strategy can support better choices of production clones. Copyright © 2011 American Institute of Chemical Engineers (AIChE).

  15. Dynamic Educational e-Content Selection Using Multiple Criteria in Web-Based Personalized Learning Environments.

    Science.gov (United States)

    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…

  16. Mixed-Handedness Advantages in Episodic Memory Obtained under Conditions of Intentional Learning Extend to Incidental Learning

    Science.gov (United States)

    Christman, Stephen D.; Butler, Michael

    2011-01-01

    The existence of handedness differences in the retrieval of episodic memories is well-documented, but virtually all have been obtained under conditions of intentional learning. Two experiments are reported that extend the presence of such handedness differences to memory retrieval under conditions of incidental learning. Experiment 1 used Craik…

  17. The attention habit: how reward learning shapes attentional selection.

    Science.gov (United States)

    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.

  18. Exploring the relation between teachers’ perceptions of workplace conditions and their professional learning goals

    NARCIS (Netherlands)

    Louws, Monika L.; Meirink, Jacobiene A.; van Veen, Klaas; van Driel, Jan H.

    2017-01-01

    Schools’ structural workplace conditions (e.g. learning resources and professional development policies) and cultural workplace conditions (e.g. school leadership, teachers’ collaborative culture) have been found to affect the way teachers learn. It is not so much the objective conditions that

  19. Associative learning in humans--conditioning of sensory-evoked brain activity.

    Science.gov (United States)

    Skrandies, W; Jedynak, A

    2000-01-01

    A classical conditioning paradigm was employed in two experiments performed on 35 human volunteers. In nine subjects, the presentation of Landolt rings (conditioned stimuli, CS + ) was paired with an electric stimulus (unconditioned stimuli, UCS) applied to the left median nerve. Neutral visual control stimuli were full circles (CS -) that were not paired with the UCS. The skin conductance response (SCR) was determined in a time interval of 5 s after onset of the visual stimuli, and it was measured in the acquisition and test phase. Associative learning was reflected by a SCR occurring selectively with CS +. The same experiment was repeated with another group of 26 adults while electroencephalogram (EEG) was recorded from 30 electrodes. For each subject, mean evoked potentials were computed. In 13 of the subjects, a conditioning paradigm was followed while the other subjects served as the control group (non-contingent stimulation). There were somatosensory and visual brain activity evoked by the stimuli. Conditioned components were identified by computing cross-correlation between evoked somatosensory components and the averaged EEG. In the visual evoked brain activity, three components with mean latencies of 105.4, 183.2, and 360.3 ms were analyzed. Somatosensory stimuli were followed by major components that occurred at mean latencies of 48.8, 132.5, 219.7, 294.8, and 374.2 ms latency after the shock. All components were analyzed in terms of latency, field strength, and topographic characteristics, and were compared between groups and experimental conditions. Both visual and somatosensory brain activity was significantly affected by classical conditioning. Our data illustrate how associative learning affects the topography of brain electrical activity elicited by presentation of conditioned visual stimuli.

  20. 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; ...

  1. 42 CFR 482.90 - Condition of participation: Patient and living donor selection.

    Science.gov (United States)

    2010-10-01

    ... selected to receive a transplant, the center must document in the patient's medical record the patient... 42 Public Health 5 2010-10-01 2010-10-01 false Condition of participation: Patient and living... Condition of participation: Patient and living donor selection. The transplant center must use written...

  2. Conditions for sports activities in selected organisations for disabled individuals in the town Teplice

    OpenAIRE

    Shaymardanova, Karina

    2010-01-01

    3 ABSTRACT Name: Conditions for sports activities in selected organisations for disabled individuals in the town of Teplice. Aim of the work: Monitoring sports activities as a socialisation factor for integration and socialisation of individuals with disabilities caused by poliomyelitis in the selected town of Teplice. Another objective was to describe conditions of sports activities and to determine opinions of handicapped individuals on attendance at sports groups in selected centres as wel...

  3. Unweaving misconceptions: Guided learning, simulations, and misconceptions in learning principles of natural selection

    Science.gov (United States)

    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

  4. Relevance feature selection of modal frequency-ambient condition pattern recognition in structural health assessment for reinforced concrete buildings

    Directory of Open Access Journals (Sweden)

    He-Qing Mu

    2016-08-01

    Full Text Available Modal frequency is an important indicator for structural health assessment. Previous studies have shown that this indicator is substantially affected by the fluctuation of ambient conditions, such as temperature and humidity. Therefore, recognizing the pattern between modal frequency and ambient conditions is necessary for reliable long-term structural health assessment. In this article, a novel machine-learning algorithm is proposed to automatically select relevance features in modal frequency-ambient condition pattern recognition based on structural dynamic response and ambient condition measurement. In contrast to the traditional feature selection approaches by examining a large number of combinations of extracted features, the proposed algorithm conducts continuous relevance feature selection by introducing a sophisticated hyperparameterization on the weight parameter vector controlling the relevancy of different features in the prediction model. The proposed algorithm is then utilized for structural health assessment for a reinforced concrete building based on 1-year daily measurements. It turns out that the optimal model class including the relevance features for each vibrational mode is capable to capture the pattern between the corresponding modal frequency and the ambient conditions.

  5. 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...

  6. Machinery fault diagnosis using joint global and local/nonlocal discriminant analysis with selective ensemble learning

    Science.gov (United States)

    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.

  7. 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.

  8. Feature Selection and Kernel Learning for Local Learning-Based Clustering.

    Science.gov (United States)

    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.

  9. Conditional selectivity performance of Indian mutual fund schemes: An empirical study

    Directory of Open Access Journals (Sweden)

    Subrata Roy

    2015-06-01

    Full Text Available The present study seeks to examine the stock-selection performance of the sample open-ended equity mutual fund schemes of Birla Sun Life Mutual Fund Company based on traditional and conditional performance measures. It is generally expected that inclusion of some relevant predetermined public information variables in the conditional CAPM provides better performance estimates as compared to the traditional measures. The study reports that after inclusion of conditioning public information variables, the selectivity performances of the schemes have dramatically improved relative to the traditional measure and also found that conditional measure is superior to traditional measure in statistical test.

  10. 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...

  11. A calpain-2 selective inhibitor enhances learning & memory by prolonging ERK activation.

    Science.gov (United States)

    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.

  12. Learning a constrained conditional random field for enhanced segmentation of fallen trees in ALS point clouds

    Science.gov (United States)

    Polewski, Przemyslaw; Yao, Wei; Heurich, Marco; Krzystek, Peter; Stilla, Uwe

    2018-06-01

    In this study, we present a method for improving the quality of automatic single fallen tree stem segmentation in ALS data by applying a specialized constrained conditional random field (CRF). The entire processing pipeline is composed of two steps. First, short stem segments of equal length are detected and a subset of them is selected for further processing, while in the second step the chosen segments are merged to form entire trees. The first step is accomplished using the specialized CRF defined on the space of segment labelings, capable of finding segment candidates which are easier to merge subsequently. To achieve this, the CRF considers not only the features of every candidate individually, but incorporates pairwise spatial interactions between adjacent segments into the model. In particular, pairwise interactions include a collinearity/angular deviation probability which is learned from training data as well as the ratio of spatial overlap, whereas unary potentials encode a learned probabilistic model of the laser point distribution around each segment. Each of these components enters the CRF energy with its own balance factor. To process previously unseen data, we first calculate the subset of segments for merging on a grid of balance factors by minimizing the CRF energy. Then, we perform the merging and rank the balance configurations according to the quality of their resulting merged trees, obtained from a learned tree appearance model. The final result is derived from the top-ranked configuration. We tested our approach on 5 plots from the Bavarian Forest National Park using reference data acquired in a field inventory. Compared to our previous segment selection method without pairwise interactions, an increase in detection correctness and completeness of up to 7 and 9 percentage points, respectively, was observed.

  13. STRATEGY FOR EVALUATION AND SELECTION OF SYSTEMS FOR ELECTRONIC LEARNING

    OpenAIRE

    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 ...

  14. Drosophila Courtship Conditioning As a Measure of Learning and Memory

    NARCIS (Netherlands)

    Koemans, T.S.; Oppitz, C.; Donders, R.; Bokhoven, H. van; Schenck, A.; Keleman, K.; Kramer, J.M.

    2017-01-01

    Many insights into the molecular mechanisms underlying learning and memory have been elucidated through the use of simple behavioral assays in model organisms such as the fruit fly, Drosophila melanogaster. Drosophila is useful for understanding the basic neurobiology underlying cognitive deficits

  15. Estimators for initial conditions for optimisation in learning hydraulic systems

    NARCIS (Netherlands)

    Post, W.J.A.E.M.; Burrows, C.R.; Edge, K.A.

    1998-01-01

    In Learning Hydraulic Systems (LHS1. developed at the Eindhoven University of Technology, a specialised optimisation routine is employed In order to reduce energy losses in hydraulic systems. Typical load situations which can be managed by LHS are variable cyclic loads, as can be observed In many

  16. CREB Selectively Controls Learning-Induced Structural Remodeling of Neurons

    Science.gov (United States)

    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…

  17. The cost of selective attention in category learning: developmental differences between adults and infants.

    Science.gov (United States)

    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.

  18. The cost of selective attention in category learning: Developmental differences between adults and infants

    Science.gov (United States)

    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

  19. Selection of suitable e-learning approach using TOPSIS technique with best ranked criteria weights

    Science.gov (United States)

    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.

  20. Informative sensor selection and learning for prediction of lower limb kinematics using generative stochastic neural networks.

    Science.gov (United States)

    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.

  1. Under what conditions is recognition spared relative to recall after selective hippocampal damage in humans?

    Science.gov (United States)

    Holdstock, J S; Mayes, A R; Roberts, N; Cezayirli, E; Isaac, C L; O'Reilly, R C; Norman, K A

    2002-01-01

    The claim that recognition memory is spared relative to recall after focal hippocampal damage has been disputed in the literature. We examined this claim by investigating object and object-location recall and recognition memory in a patient, YR, who has adult-onset selective hippocampal damage. Our aim was to identify the conditions under which recognition was spared relative to recall in this patient. She showed unimpaired forced-choice object recognition but clearly impaired recall, even when her control subjects found the object recognition task to be numerically harder than the object recall task. However, on two other recognition tests, YR's performance was not relatively spared. First, she was clearly impaired at an equivalently difficult yes/no object recognition task, but only when targets and foils were very similar. Second, YR was clearly impaired at forced-choice recognition of object-location associations. This impairment was also unrelated to difficulty because this task was no more difficult than the forced-choice object recognition task for control subjects. The clear impairment of yes/no, but not of forced-choice, object recognition after focal hippocampal damage, when targets and foils are very similar, is predicted by the neural network-based Complementary Learning Systems model of recognition. This model postulates that recognition is mediated by hippocampally dependent recollection and cortically dependent familiarity; thus hippocampal damage should not impair item familiarity. The model postulates that familiarity is ineffective when very similar targets and foils are shown one at a time and subjects have to identify which items are old (yes/no recognition). In contrast, familiarity is effective in discriminating which of similar targets and foils, seen together, is old (forced-choice recognition). Independent evidence from the remember/know procedure also indicates that YR's familiarity is normal. The Complementary Learning Systems model can

  2. Selective Attention Enhances Beta-Band Cortical Oscillation to Speech under "Cocktail-Party" Listening Conditions.

    Science.gov (United States)

    Gao, Yayue; Wang, Qian; Ding, Yu; Wang, Changming; Li, Haifeng; Wu, Xihong; Qu, Tianshu; Li, Liang

    2017-01-01

    Human listeners are able to selectively attend to target speech in a noisy environment with multiple-people talking. Using recordings of scalp electroencephalogram (EEG), this study investigated how selective attention facilitates the cortical representation of target speech under a simulated "cocktail-party" listening condition with speech-on-speech masking. The result shows that the cortical representation of target-speech signals under the multiple-people talking condition was specifically improved by selective attention relative to the non-selective-attention listening condition, and the beta-band activity was most strongly modulated by selective attention. Moreover, measured with the Granger Causality value, selective attention to the single target speech in the mixed-speech complex enhanced the following four causal connectivities for the beta-band oscillation: the ones (1) from site FT7 to the right motor area, (2) from the left frontal area to the right motor area, (3) from the central frontal area to the right motor area, and (4) from the central frontal area to the right frontal area. However, the selective-attention-induced change in beta-band causal connectivity from the central frontal area to the right motor area, but not other beta-band causal connectivities, was significantly correlated with the selective-attention-induced change in the cortical beta-band representation of target speech. These findings suggest that under the "cocktail-party" listening condition, the beta-band oscillation in EEGs to target speech is specifically facilitated by selective attention to the target speech that is embedded in the mixed-speech complex. The selective attention-induced unmasking of target speech may be associated with the improved beta-band functional connectivity from the central frontal area to the right motor area, suggesting a top-down attentional modulation of the speech-motor process.

  3. Mountain Plains Learning Experience Guide: Heating, Refrigeration, & Air Conditioning.

    Science.gov (United States)

    Carey, John

    This Heating, Refrigeration, and Air Conditioning course is comprised of eleven individualized units: (1) Refrigeration Tools, Materials, and Refrigerant; (2) Basic Heating and Air Conditioning; (3) Sealed System Repairs; (4) Basic Refrigeration Systems; (5) Compression Systems and Compressors; (6) Refrigeration Controls; (7) Electric Circuit…

  4. You see what you have learned. Evidence for an interrelation of associative learning and visual selective attention.

    Science.gov (United States)

    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.

  5. 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.

  6. Oxytocin selectively facilitates learning with social feedback and increases activity and functional connectivity in emotional memory and reward processing regions.

    Science.gov (United States)

    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.

  7. Identifying the Goal, User model and Conditions of Recommender Systems for Formal and Informal Learning

    NARCIS (Netherlands)

    Drachsler, Hendrik; Hummel, Hans; Koper, Rob

    2008-01-01

    Drachsler, H., Hummel, H. G. K., & Koper, R. (2009). Identifying the Goal, User model and Conditions of Recommender Systems for Formal and Informal Learning. Journal of Digital Information, 10(2), 4-24.

  8. Extinction of Conditioned Fear is Better Learned and Recalled in the Morning than in the Evening

    OpenAIRE

    Pace-Schott, Edward F.; Spencer, Rebecca M.C.; Vijayakumar, Shilpa; Ahmed, Nafis; Verga, Patrick W.; Orr, Scott P.; Pitman, Roger K.; Milad, Mohammed R.

    2013-01-01

    Sleep helps emotional memories consolidate and may promote generalization of fear extinction memory. We examined whether extinction learning and memory might differ in the morning and evening due, potentially, to circadian and/or sleep-homeostatic factors. Healthy men (N=109) in 6 groups completed a 2-session protocol. In Session 1, fear conditioning was followed by extinction learning. Partial reinforcement with mild electric shock produced conditioned skin conductance responses (SCR) to 2 d...

  9. Condition-dependence, pleiotropy and the handicap principle of sexual selection in melanin-based colouration.

    Science.gov (United States)

    Roulin, Alexandre

    2016-05-01

    The signalling function of melanin-based colouration is debated. Sexual selection theory states that ornaments should be costly to produce, maintain, wear or display to signal quality honestly to potential mates or competitors. An increasing number of studies supports the hypothesis that the degree of melanism covaries with aspects of body condition (e.g. body mass or immunity), which has contributed to change the initial perception that melanin-based colour ornaments entail no costs. Indeed, the expression of many (but not all) melanin-based colour traits is weakly sensitive to the environment but strongly heritable suggesting that these colour traits are relatively cheap to produce and maintain, thus raising the question of how such colour traits could signal quality honestly. Here I review the production, maintenance and wearing/displaying costs that can generate a correlation between melanin-based colouration and body condition, and consider other evolutionary mechanisms that can also lead to covariation between colour and body condition. Because genes controlling melanic traits can affect numerous phenotypic traits, pleiotropy could also explain a linkage between body condition and colouration. Pleiotropy may result in differently coloured individuals signalling different aspects of quality that are maintained by frequency-dependent selection or local adaptation. Colouration may therefore not signal absolute quality to potential mates or competitors (e.g. dark males may not achieve a higher fitness than pale males); otherwise genetic variation would be rapidly depleted by directional selection. As a consequence, selection on heritable melanin-based colouration may not always be directional, but mate choice may be conditional to environmental conditions (i.e. context-dependent sexual selection). Despite the interest of evolutionary biologists in the adaptive value of melanin-based colouration, its actual role in sexual selection is still poorly understood.

  10. The Role of Executive Control of Attention and Selective Encoding for Preschoolers' Learning

    Science.gov (United States)

    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…

  11. When Average Is Not Good Enough: Students with Learning Disabilities at Selective, Private Colleges

    Science.gov (United States)

    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…

  12. 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)

  13. Inter-Labeler and Intra-Labeler Variability of Condition Severity Classification Models Using Active and Passive Learning Methods

    Science.gov (United States)

    Nissim, Nir; Shahar, Yuval; Boland, Mary Regina; Tatonetti, Nicholas P; Elovici, Yuval; Hripcsak, George; Moskovitch, Robert

    2018-01-01

    Background and Objectives Labeling instances by domain experts for classification is often time consuming and expensive. To reduce such labeling efforts, we had proposed the application of active learning (AL) methods, introduced our CAESAR-ALE framework for classifying the severity of clinical conditions, and shown its significant reduction of labeling efforts. The use of any of three AL methods (one well known [SVM-Margin], and two that we introduced [Exploitation and Combination_XA]) significantly reduced (by 48% to 64%) condition labeling efforts, compared to standard passive (random instance-selection) SVM learning. Furthermore, our new AL methods achieved maximal accuracy using 12% fewer labeled cases than the SVM-Margin AL method. However, because labelers have varying levels of expertise, a major issue associated with learning methods, and AL methods in particular, is how to best to use the labeling provided by a committee of labelers. First, we wanted to know, based on the labelers’ learning curves, whether using AL methods (versus standard passive learning methods) has an effect on the Intra-labeler variability (within the learning curve of each labeler) and inter-labeler variability (among the learning curves of different labelers). Then, we wanted to examine the effect of learning (either passively or actively) from the labels created by the majority consensus of a group of labelers. Methods We used our CAESAR-ALE framework for classifying the severity of clinical conditions, the three AL methods and the passive learning method, as mentioned above, to induce the classifications models. We used a dataset of 516 clinical conditions and their severity labeling, represented by features aggregated from the medical records of 1.9 million patients treated at Columbia University Medical Center. We analyzed the variance of the classification performance within (intra-labeler), and especially among (inter-labeler) the classification models that were induced by

  14. Inter-labeler and intra-labeler variability of condition severity classification models using active and passive learning methods.

    Science.gov (United States)

    Nissim, Nir; Shahar, Yuval; Elovici, Yuval; Hripcsak, George; Moskovitch, Robert

    2017-09-01

    Labeling instances by domain experts for classification is often time consuming and expensive. To reduce such labeling efforts, we had proposed the application of active learning (AL) methods, introduced our CAESAR-ALE framework for classifying the severity of clinical conditions, and shown its significant reduction of labeling efforts. The use of any of three AL methods (one well known [SVM-Margin], and two that we introduced [Exploitation and Combination_XA]) significantly reduced (by 48% to 64%) condition labeling efforts, compared to standard passive (random instance-selection) SVM learning. Furthermore, our new AL methods achieved maximal accuracy using 12% fewer labeled cases than the SVM-Margin AL method. However, because labelers have varying levels of expertise, a major issue associated with learning methods, and AL methods in particular, is how to best to use the labeling provided by a committee of labelers. First, we wanted to know, based on the labelers' learning curves, whether using AL methods (versus standard passive learning methods) has an effect on the Intra-labeler variability (within the learning curve of each labeler) and inter-labeler variability (among the learning curves of different labelers). Then, we wanted to examine the effect of learning (either passively or actively) from the labels created by the majority consensus of a group of labelers. We used our CAESAR-ALE framework for classifying the severity of clinical conditions, the three AL methods and the passive learning method, as mentioned above, to induce the classifications models. We used a dataset of 516 clinical conditions and their severity labeling, represented by features aggregated from the medical records of 1.9 million patients treated at Columbia University Medical Center. We analyzed the variance of the classification performance within (intra-labeler), and especially among (inter-labeler) the classification models that were induced by using the labels provided by seven

  15. Mechanisms of Radiation-Induced Conditioned Taste Aversion Learning

    Science.gov (United States)

    1986-01-01

    impairment of the synthesis of these cells, especially those in In addition to emesis. exposure to lower doses of ionizing bone marrow. However. since...pretreatment with fluoxetine in gustatory conditioning. 629-635. 1983. Pharmnat l Bioc/n-a 8,4,ui 17: 431-443. 1982. 100. Rabin. B. M. and J. S. Rabin

  16. Conditional Selection of Genomic Alterations Dictates Cancer Evolution and Oncogenic Dependencies.

    Science.gov (United States)

    Mina, Marco; Raynaud, Franck; Tavernari, Daniele; Battistello, Elena; Sungalee, Stephanie; Saghafinia, Sadegh; Laessle, Titouan; Sanchez-Vega, Francisco; Schultz, Nikolaus; Oricchio, Elisa; Ciriello, Giovanni

    2017-08-14

    Cancer evolves through the emergence and selection of molecular alterations. Cancer genome profiling has revealed that specific events are more or less likely to be co-selected, suggesting that the selection of one event depends on the others. However, the nature of these evolutionary dependencies and their impact remain unclear. Here, we designed SELECT, an algorithmic approach to systematically identify evolutionary dependencies from alteration patterns. By analyzing 6,456 genomes from multiple tumor types, we constructed a map of oncogenic dependencies associated with cellular pathways, transcriptional readouts, and therapeutic response. Finally, modeling of cancer evolution shows that alteration dependencies emerge only under conditional selection. These results provide a framework for the design of strategies to predict cancer progression and therapeutic response. Copyright © 2017 Elsevier Inc. All rights reserved.

  17. Progressive sampling-based Bayesian optimization for efficient and automatic machine learning model selection.

    Science.gov (United States)

    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.

  18. Learning a New Selection Rule in Visual and Frontal Cortex

    NARCIS (Netherlands)

    van der Togt, Chris; Stănişor, Liviu; Pooresmaeili, Arezoo; Albantakis, Larissa; Deco, Gustavo; Roelfsema, Pieter R

    2016-01-01

    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

  19. Examining Self Regulated Learning in Relation to Certain Selected Variables

    Science.gov (United States)

    Johnson, N.

    2012-01-01

    Self-regulation is the controlling of a process or activity by the students who are involved in Problem solving in Physics rather than by an external agency (Johnson, 2011). Selfregulated learning consists of three main components: cognition, metacognition, and motivation. Cognition includes skills necessary to encode, memorise, and recall…

  20. Understanding Sample Surveys: Selective Learning about Social Science Research Methods

    Science.gov (United States)

    Currin-Percival, Mary; Johnson, Martin

    2010-01-01

    We investigate differences in what students learn about survey methodology in a class on public opinion presented in two critically different ways: with the inclusion or exclusion of an original research project using a random-digit-dial telephone survey. Using a quasi-experimental design and data obtained from pretests and posttests in two public…

  1. Self-learning basic life support: A randomised controlled trial on learning conditions.

    Science.gov (United States)

    Pedersen, Tina Heidi; Kasper, Nina; Roman, Hari; Egloff, Mike; Marx, David; Abegglen, Sandra; Greif, Robert

    2018-05-01

    To investigate whether pure self-learning without instructor support, resulted in the same BLS-competencies as facilitator-led learning, when using the same commercially available video BLS teaching kit. First-year medical students were randomised to either BLS self-learning without supervision or facilitator-led BLS-teaching. Both groups used the MiniAnne kit (Laerdal Medical, Stavanger, Norway) in the students' local language. Directly after the teaching and three months later, all participants were tested on their BLS-competencies in a simulated scenario, using the Resusci Anne SkillReporter™ (Laerdal Medical, Stavanger, Norway). The primary outcome was percentage of correct cardiac compressions three months after the teaching. Secondary outcomes were all other BLS parameters recorded by the SkillReporter and parameters from a BLS-competence rating form. 240 students were assessed at baseline and 152 students participated in the 3-month follow-up. For our primary outcome, the percentage of correct compressions, we found a median of 48% (interquartile range (IQR) 10-83) for facilitator-led learning vs. 42% (IQR 14-81) for self-learning (p = 0.770) directly after the teaching. In the 3-month follow-up, the rate of correct compressions dropped to 28% (IQR 6-59) for facilitator-led learning (p = 0.043) and did not change significantly in the self-learning group (47% (IQR 12-78), p = 0.729). Self-learning is not inferior to facilitator-led learning in the short term. Self-learning resulted in a better retention of BLS-skills three months after training compared to facilitator-led training. Copyright © 2018 Elsevier B.V. All rights reserved.

  2. Effective Sensor Selection and Data Anomaly Detection for Condition Monitoring of Aircraft Engines

    Directory of Open Access Journals (Sweden)

    Liansheng Liu

    2016-04-01

    Full Text Available In a complex system, condition monitoring (CM can collect the system working status. The condition is mainly sensed by the pre-deployed sensors in/on the system. Most existing works study how to utilize the condition information to predict the upcoming anomalies, faults, or failures. There is also some research which focuses on the faults or anomalies of the sensing element (i.e., sensor to enhance the system reliability. However, existing approaches ignore the correlation between sensor selecting strategy and data anomaly detection, which can also improve the system reliability. To address this issue, we study a new scheme which includes sensor selection strategy and data anomaly detection by utilizing information theory and Gaussian Process Regression (GPR. The sensors that are more appropriate for the system CM are first selected. Then, mutual information is utilized to weight the correlation among different sensors. The anomaly detection is carried out by using the correlation of sensor data. The sensor data sets that are utilized to carry out the evaluation are provided by National Aeronautics and Space Administration (NASA Ames Research Center and have been used as Prognostics and Health Management (PHM challenge data in 2008. By comparing the two different sensor selection strategies, the effectiveness of selection method on data anomaly detection is proved.

  3. When a Fly Has to Fly to Reproduce: Selection against Conditional Recessive Lethals in "Drosophila"

    Science.gov (United States)

    Plunkett, Andrea D.; Yampolsky, Lev Y.

    2010-01-01

    We propose an experimental model suitable for demonstrating allele frequency change in Drosophila melanogaster populations caused by selection against an easily scorable conditional lethal, namely recessive flightless alleles such as apterous and vestigial. Homozygotes for these alleles are excluded from reproduction because the food source used…

  4. The Orexin Component of Fasting Triggers Memory Processes Underlying Conditioned Food Selection in the Rat

    Science.gov (United States)

    Ferry, Barbara; Duchamp-Viret, Patricia

    2014-01-01

    To test the selectivity of the orexin A (OXA) system in olfactory sensitivity, the present study compared the effects of fasting and of central infusion of OXA on the memory processes underlying odor-malaise association during the conditioned odor aversion (COA) paradigm. Animals implanted with a cannula in the left ventricle received ICV infusion…

  5. Relation between motility, accelerated aging and gene expression in selected Drosophila strains under hypergravity conditions

    NARCIS (Netherlands)

    Serrano, P.; van Loon, J.J.W.A.; Javier Medina, F.; Herranz, R.

    2013-01-01

    Motility and aging in Drosophila have proven to be highly modified under altered gravity conditions (both in space and ground simulation facilities). In order to find out how closely connected they are, five strains with altered geotactic response or survival rates were selected and exposed to an

  6. Noise sensitivity of portfolio selection in constant conditional correlation GARCH models

    Science.gov (United States)

    Varga-Haszonits, I.; Kondor, I.

    2007-11-01

    This paper investigates the efficiency of minimum variance portfolio optimization for stock price movements following the Constant Conditional Correlation GARCH process proposed by Bollerslev. Simulations show that the quality of portfolio selection can be improved substantially by computing optimal portfolio weights from conditional covariances instead of unconditional ones. Measurement noise can be further reduced by applying some filtering method on the conditional correlation matrix (such as Random Matrix Theory based filtering). As an empirical support for the simulation results, the analysis is also carried out for a time series of S&P500 stock prices.

  7. Selective effects of explanation on learning during early childhood.

    Science.gov (United States)

    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.

  8. Mixed-handedness advantages in episodic memory obtained under conditions of intentional learning extend to incidental learning.

    Science.gov (United States)

    Christman, Stephen D; Butler, Michael

    2011-10-01

    The existence of handedness differences in the retrieval of episodic memories is well-documented, but virtually all have been obtained under conditions of intentional learning. Two experiments are reported that extend the presence of such handedness differences to memory retrieval under conditions of incidental learning. Experiment 1 used Craik and Tulving's (1975) classic levels-of-processing paradigm and obtained handedness differences under incidental and intentional conditions of deep processing, but not under conditions of shallow incidental processing. Experiment 2 looked at incidental memory for distracter items from a recognition memory task and again found a mixed-handed advantage. Results are discussed in terms of the relation between interhemispheric interaction, levels of processing, and episodic memory retrieval. Copyright © 2011 Elsevier Inc. All rights reserved.

  9. Stochastic weather inputs for improved urban water demand forecasting: application of nonlinear input variable selection and machine learning methods

    Science.gov (United States)

    Quilty, J.; Adamowski, J. F.

    2015-12-01

    Urban water supply systems are often stressed during seasonal outdoor water use as water demands related to the climate are variable in nature making it difficult to optimize the operation of the water supply system. Urban water demand forecasts (UWD) failing to include meteorological conditions as inputs to the forecast model may produce poor forecasts as they cannot account for the increase/decrease in demand related to meteorological conditions. Meteorological records stochastically simulated into the future can be used as inputs to data-driven UWD forecasts generally resulting in improved forecast accuracy. This study aims to produce data-driven UWD forecasts for two different Canadian water utilities (Montreal and Victoria) using machine learning methods by first selecting historical UWD and meteorological records derived from a stochastic weather generator using nonlinear input variable selection. The nonlinear input variable selection methods considered in this work are derived from the concept of conditional mutual information, a nonlinear dependency measure based on (multivariate) probability density functions and accounts for relevancy, conditional relevancy, and redundancy from a potential set of input variables. The results of our study indicate that stochastic weather inputs can improve UWD forecast accuracy for the two sites considered in this work. Nonlinear input variable selection is suggested as a means to identify which meteorological conditions should be utilized in the forecast.

  10. An Evaluation Model To Select an Integrated Learning System in a Large, Suburban School District.

    Science.gov (United States)

    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…

  11. Endogenously- and Exogenously-Driven Selective Sustained Attention: Contributions to Learning in Kindergarten Children

    Science.gov (United States)

    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…

  12. Feature selection is the ReliefF for multiple instance learning

    NARCIS (Netherlands)

    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

  13. A decision-making support system to select forages according to environmental conditions in Colombia

    Directory of Open Access Journals (Sweden)

    Blanca Aurora Arce Barboza

    2013-07-01

    Full Text Available Low food supply is a major problem affecting a large percentage of the livestock population in Colombia and is largely associated to inappropriate choice of forage species; and thus not well adapted to the environmental conditions of a specific region. To mitigate this problem, without incurring increasing costs associated to changing environmental conditions, it is possible to match the adaptive capacity of species to the environment in which they grow. A decision support system was developed to select suitable forage species for a given environment. The system is based on the use of existing information about requirements of the species rather than specific experimentation. From the information gathered, a database was generated and implemented on ASP.NET in C # and SQL Server database. This system allows users to search and select pastures and forage species for specific soil and climatic conditions of a particular farm or region, through a user-friendly web platform.

  14. Examining the Conditions of Using an On-Line Dictionary to Learn Words and Comprehend Texts

    Science.gov (United States)

    Dilenschneider, Robert Francis

    2018-01-01

    This study investigated three look-up conditions for language learners to learn unknown target words and comprehend a reading passage when their attention is transferred away to an on-line dictionary. The research questions focused on how each look-up condition impacted the recall and recognition of word forms, word meanings, and passage…

  15. Code-specific learning rules improve action selection by populations of spiking neurons.

    Science.gov (United States)

    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.

  16. The effect of encoding conditions on learning in the prototype distortion task.

    Science.gov (United States)

    Lee, Jessica C; Livesey, Evan J

    2017-06-01

    The prototype distortion task demonstrates that it is possible to learn about a category of physically similar stimuli through mere observation. However, there have been few attempts to test whether different encoding conditions affect learning in this task. This study compared prototypicality gradients produced under incidental learning conditions in which participants performed a visual search task, with those produced under intentional learning conditions in which participants were required to memorize the stimuli. Experiment 1 showed that similar prototypicality gradients could be obtained for category endorsement and familiarity ratings, but also found (weaker) prototypicality gradients in the absence of exposure. In Experiments 2 and 3, memorization was found to strengthen prototypicality gradients in familiarity ratings in comparison to visual search, but there were no group differences in participants' ability to discriminate between novel and presented exemplars. Although the Search groups in Experiments 2 and 3 produced prototypicality gradients, they were no different in magnitude to those produced in the absence of stimulus exposure in Experiment 1, suggesting that incidental learning during visual search was not conducive to producing prototypicality gradients. This study suggests that learning in the prototype distortion task is not implicit in the sense of resulting automatically from exposure, is affected by the nature of encoding, and should be considered in light of potential learning-at-test effects.

  17. Learning-dependent plasticity in human auditory cortex during appetitive operant conditioning.

    Science.gov (United States)

    Puschmann, Sebastian; Brechmann, André; Thiel, Christiane M

    2013-11-01

    Animal experiments provide evidence that learning to associate an auditory stimulus with a reward causes representational changes in auditory cortex. However, most studies did not investigate the temporal formation of learning-dependent plasticity during the task but rather compared auditory cortex receptive fields before and after conditioning. We here present a functional magnetic resonance imaging study on learning-related plasticity in the human auditory cortex during operant appetitive conditioning. Participants had to learn to associate a specific category of frequency-modulated tones with a reward. Only participants who learned this association developed learning-dependent plasticity in left auditory cortex over the course of the experiment. No differential responses to reward predicting and nonreward predicting tones were found in auditory cortex in nonlearners. In addition, learners showed similar learning-induced differential responses to reward-predicting and nonreward-predicting tones in the ventral tegmental area and the nucleus accumbens, two core regions of the dopaminergic neurotransmitter system. This may indicate a dopaminergic influence on the formation of learning-dependent plasticity in auditory cortex, as it has been suggested by previous animal studies. Copyright © 2012 Wiley Periodicals, Inc.

  18. Learning spectrum's selection in OLAM network for analysis cement samples

    International Nuclear Information System (INIS)

    Huang Ning; Wang Peng; Tang Daiquan; Hu Renlan

    2010-01-01

    It uses OLAM artificial neural network to analyze the samples of cement raw material. Two kinds of spectrums are used for network learning: pure-element spectrum and mix-element spectrum. The output of pure-element method can be used to construct a simulate spectrum, which can be compared with the original spectrum and judge the shift of spectrum; the mix-element method can store more message and correct the matrix effect, but the multicollinearity among spectrums can cause some side effect to the results. (authors)

  19. Sex Role Learning: A Test of the Selective Attention Hypothesis.

    Science.gov (United States)

    Bryan, Janice Westlund; Luria, Zella

    This paper reports three studies designed to determine whether children show selective attention and/or differential memory to slide pictures of same-sex vs. opposite-sex models and activities. Attention was measured using a feedback EEG procedure, which measured the presence or absence of alpha rhythms in the subjects' brains during presentation…

  20. Evolution of learning and levels of selection: a lesson from avian parent-offspring communication.

    Science.gov (United States)

    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.

  1. Conditions for selective degradation of lignin by the fungus Ganoderma australis

    Energy Technology Data Exchange (ETDEWEB)

    Rios, S.; Eyzaguirre, J. (Universidad Catolica de Chile, Santiago (Chile). Lab. de Bioquimica)

    1992-08-01

    The white-rot fungus Ganoderma australis selectively degrades lignin in the ecosystem 'palo podrido'. Using conditions that simulate those of 'palo podrido' in the laboratory, it was found that low nitrogen content and low O{sub 2} tension stimulate the production of manganese peroxidase and lignin degradation, and depress cellulose degradation and cellulase production. The inverse is found at high nitrogen concentration and high O{sub 2} tension. This agrees with previous results indicating that low O{sub 2} tension and low nitrogen stimulate selective lignin degradation by this fungus. (orig.).

  2. How motivation and reward learning modulate selective attention.

    Science.gov (United States)

    Bourgeois, A; Chelazzi, L; Vuilleumier, P

    2016-01-01

    Motivational stimuli such as rewards elicit adaptive responses and influence various cognitive functions. Notably, increasing evidence suggests that stimuli with particular motivational values can strongly shape perception and attention. These effects resemble both selective top-down and stimulus-driven attentional orienting, as they depend on internal states but arise without conscious will, yet they seem to reflect attentional systems that are functionally and anatomically distinct from those classically associated with frontoparietal cortical networks in the brain. Recent research in human and nonhuman primates has begun to reveal how reward can bias attentional selection, and where within the cognitive system the signals providing attentional priority are generated. This review aims at describing the different mechanisms sustaining motivational attention, their impact on different behavioral tasks, and current knowledge concerning the neural networks governing the integration of motivational influences on attentional behavior. © 2016 Elsevier B.V. All rights reserved.

  3. Dissociation of learned helplessness and fear conditioning in mice: a mouse model of depression.

    Directory of Open Access Journals (Sweden)

    Dominic Landgraf

    Full Text Available The state of being helpless is regarded as a central aspect of depression, and therefore the learned helplessness paradigm in rodents is commonly used as an animal model of depression. The term 'learned helplessness' refers to a deficit in escaping from an aversive situation after an animal is exposed to uncontrollable stress specifically, with a control/comparison group having been exposed to an equivalent amount of controllable stress. A key feature of learned helplessness is the transferability of helplessness to different situations, a phenomenon called 'trans-situationality'. However, most studies in mice use learned helplessness protocols in which training and testing occur in the same environment and with the same type of stressor. Consequently, failures to escape may reflect conditioned fear of a particular environment, not a general change of the helpless state of an animal. For mice, there is no established learned helplessness protocol that includes the trans-situationality feature. Here we describe a simple and reliable learned helplessness protocol for mice, in which training and testing are carried out in different environments and with different types of stressors. We show that with our protocol approximately 50% of mice develop learned helplessness that is not attributable to fear conditioning.

  4. Dissociation of learned helplessness and fear conditioning in mice: a mouse model of depression.

    Science.gov (United States)

    Landgraf, Dominic; Long, Jaimie; Der-Avakian, Andre; Streets, Margo; Welsh, David K

    2015-01-01

    The state of being helpless is regarded as a central aspect of depression, and therefore the learned helplessness paradigm in rodents is commonly used as an animal model of depression. The term 'learned helplessness' refers to a deficit in escaping from an aversive situation after an animal is exposed to uncontrollable stress specifically, with a control/comparison group having been exposed to an equivalent amount of controllable stress. A key feature of learned helplessness is the transferability of helplessness to different situations, a phenomenon called 'trans-situationality'. However, most studies in mice use learned helplessness protocols in which training and testing occur in the same environment and with the same type of stressor. Consequently, failures to escape may reflect conditioned fear of a particular environment, not a general change of the helpless state of an animal. For mice, there is no established learned helplessness protocol that includes the trans-situationality feature. Here we describe a simple and reliable learned helplessness protocol for mice, in which training and testing are carried out in different environments and with different types of stressors. We show that with our protocol approximately 50% of mice develop learned helplessness that is not attributable to fear conditioning.

  5. Characterisation of mental health conditions in social media using Informed Deep Learning

    Science.gov (United States)

    Gkotsis, George; Oellrich, Anika; Velupillai, Sumithra; Liakata, Maria; Hubbard, Tim J. P.; Dobson, Richard J. B.; Dutta, Rina

    2017-03-01

    The number of people affected by mental illness is on the increase and with it the burden on health and social care use, as well as the loss of both productivity and quality-adjusted life-years. Natural language processing of electronic health records is increasingly used to study mental health conditions and risk behaviours on a large scale. However, narrative notes written by clinicians do not capture first-hand the patients’ own experiences, and only record cross-sectional, professional impressions at the point of care. Social media platforms have become a source of ‘in the moment’ daily exchange, with topics including well-being and mental health. In this study, we analysed posts from the social media platform Reddit and developed classifiers to recognise and classify posts related to mental illness according to 11 disorder themes. Using a neural network and deep learning approach, we could automatically recognise mental illness-related posts in our balenced dataset with an accuracy of 91.08% and select the correct theme with a weighted average accuracy of 71.37%. We believe that these results are a first step in developing methods to characterise large amounts of user-generated content that could support content curation and targeted interventions.

  6. Cue competition in evaluative conditioning as a function of the learning process.

    Science.gov (United States)

    Kattner, Florian; Green, C Shawn

    2015-11-01

    Evaluative conditioning (EC) is the change in the valence of a stimulus resulting from pairings with an affective (unconditioned) stimulus (US). With some exceptions, previous work has indicated that this form of conditioning might be insensitive to cue competition effects such as blocking and overshadowing. Here we assessed whether the extent of cue competition in EC depends upon the type of contingency learning during conditioning. Specifically, we contrasted a learning task that biased participants toward cognitive/inferential learning (i.e., predicting the US) with a learning task that prevented prolonged introspection (i.e., a rapid response made to the US). In all cases, standard EC effects were observed, with the subjective liking of stimuli changed in the direction of the valence of the US. More importantly, when inferential learning was likely, larger EC effects occurred for isolated stimuli than for compounds (indicating overshadowing). No blocking effects on explicit evaluations were observed for either learning task. Contingency judgments and implicit evaluations, however, were sensitive to blocking, indicating that the absence of a blocking effect on explicit evaluations might be due to inferences that occur during testing.

  7. Methodology for selection of attributes and operating conditions for SVM-Based fault locator's

    Directory of Open Access Journals (Sweden)

    Debbie Johan Arredondo Arteaga

    2017-01-01

    Full Text Available Context: Energy distribution companies must employ strategies to meet their timely and high quality service, and fault-locating techniques represent and agile alternative for restoring the electric service in the power distribution due to the size of distribution services (generally large and the usual interruptions in the service. However, these techniques are not robust enough and present some limitations in both computational cost and the mathematical description of the models they use. Method: This paper performs an analysis based on a Support Vector Machine for the evaluation of the proper conditions to adjust and validate a fault locator for distribution systems; so that it is possible to determine the minimum number of operating conditions that allow to achieve a good performance with a low computational effort. Results: We tested the proposed methodology in a prototypical distribution circuit, located in a rural area of Colombia. This circuit has a voltage of 34.5 KV and is subdivided in 20 zones. Additionally, the characteristics of the circuit allowed us to obtain a database of 630.000 records of single-phase faults and different operating conditions. As a result, we could determine that the locator showed a performance above 98% with 200 suitable selected operating conditions. Conclusions: It is possible to improve the performance of fault locators based on Support Vector Machine. Specifically, these improvements are achieved by properly selecting optimal operating conditions and attributes, since they directly affect the performance in terms of efficiency and the computational cost.

  8. Selection of tomato mutants (lycopersicon esculentum mill) under conditions of drought stress

    International Nuclear Information System (INIS)

    Gonzalez, Maria Caridad; Mansoor, Ali; Suarez, Lorenzo; Mukandama, Jean P.; Rodriguez, Yanet

    2001-01-01

    At the National Institute of Agricultural Sciences were evaluated under conditions of drought estres an M5 population obtained starting from the irradiation of seeds of the Amalia and INCA 9-1varieties with dose of 300 and 500 Gy of rays gamma of 60 Co. The number of clusters for plant, mass average of the fruits, number of fruits for plant and yield for plant, the content of total soluble solids and the acidity of the fruits was evaluated observing differ highly significant among the different ones lines and the respective donating studied. Promissory genotipos of high productive potential was selected under this condition

  9. From conditioning to learning communities: implications of fifty years of research in e-learning interaction design

    Directory of Open Access Journals (Sweden)

    Andrew Ravenscroft

    2003-12-01

    Full Text Available This paper will consider e-learning in terms of the underlying learning processes and interactions that are stimulated, supported or favoured by new media and the contexts or communities in which it is used. We will review and critique a selection of research and development from the past fifty years that has linked pedagogical and learning theory to the design of innovative e-learning systems and activities, and discuss their implications. It will include approaches that are, essentially, behaviourist (Skinner and Gagné, cognitivist (Pask, Piaget and Papert, situated (Lave, Wenger and Seely-Brown, socioconstructivist (Vygotsky, socio-cultural (Nardi and Engestrom and community-based (Wenger and Preece. Emerging from this review is the argument that effective elearning usually requires, or involves, high-quality educational discourse, that leads to, at the least, improved knowledge, and at the best, conceptual development and improved understanding. To achieve this I argue that we need to adopt a more holistic approach to design that synthesizes features of the included approaches, leading to a framework that emphasizes the relationships between cognitive changes, dialogue processes and the communities, or contexts for e-learning.

  10. Collaborative testing for key-term definitions under representative conditions: Efficiency costs and no learning benefits.

    Science.gov (United States)

    Wissman, Kathryn T; Rawson, Katherine A

    2018-01-01

    Students are expected to learn key-term definitions across many different grade levels and academic disciplines. Thus, investigating ways to promote understanding of key-term definitions is of critical importance for applied purposes. A recent survey showed that learners report engaging in collaborative practice testing when learning key-term definitions, with outcomes also shedding light on the way in which learners report engaging in collaborative testing in real-world contexts (Wissman & Rawson, 2016, Memory, 24, 223-239). However, no research has directly explored the effectiveness of engaging in collaborative testing under representative conditions. Accordingly, the current research evaluates the costs (with respect to efficiency) and the benefits (with respect to learning) of collaborative testing for key-term definitions under representative conditions. In three experiments (ns = 94, 74, 95), learners individually studied key-term definitions and then completed retrieval practice, which occurred either individually or collaboratively (in dyads). Two days later, all learners completed a final individual test. Results from Experiments 1-2 showed a cost (with respect to efficiency) and no benefit (with respect to learning) of engaging in collaborative testing for key-term definitions. Experiment 3 evaluated a theoretical explanation for why collaborative benefits do not emerge under representative conditions. Collectively, outcomes indicate that collaborative testing versus individual testing is less effective and less efficient when learning key-term definitions under representative conditions.

  11. The role of scenario, deontic conditionals and problem content in Wason´s selection task

    OpenAIRE

    Martín, Montserrat; Valiña, María Dolores; Evans, Jonathan St. B. T.

    2014-01-01

    This paper was presented at "The European Conference on Cognitive Science. Siena, Italy, October 1999" This experiment explores the influence of thematic content, the presence or absence of a scenario and the use of deontic or indicative framing of conditional rules on performance on Wason’s selection task. Logical performance was affected by the content used (permission rules were the best, neutral the worst and obligation rules intermediate) and by the use of scenario...

  12. Stability of selected volatile contact allergens in different patch test chambers under different storage conditions

    DEFF Research Database (Denmark)

    Mose, Kristian Fredløv; Andersen, Klaus Ejner; Christensen, Lars Porskjaer

    2012-01-01

    Background. Patch test preparations of volatile substances may evaporate during storage, thereby giving rise to reduced patch test concentrations. Objectives. To investigate the stability of selected acrylates/methacrylates and fragrance allergens in three different test chambers under different...... both storage conditions, whereas MMA and 2-HPA required cool storage for maintenance of the limit. Conclusion. The Van der Bend® transport container was the best device for storage of samples of volatile contact allergens....

  13. A diagnostic signal selection scheme for planetary gearbox vibration monitoring under non-stationary operational conditions

    International Nuclear Information System (INIS)

    Feng, Ke; Wang, KeSheng; Zhang, Mian; Ni, Qing; Zuo, Ming J

    2017-01-01

    The planetary gearbox, due to its unique mechanical structures, is an important rotating machine for transmission systems. Its engineering applications are often in non-stationary operational conditions, such as helicopters, wind energy systems, etc. The unique physical structures and working conditions make the vibrations measured from planetary gearboxes exhibit a complex time-varying modulation and therefore yield complicated spectral structures. As a result, traditional signal processing methods, such as Fourier analysis, and the selection of characteristic fault frequencies for diagnosis face serious challenges. To overcome this drawback, this paper proposes a signal selection scheme for fault-emphasized diagnostics based upon two order tracking techniques. The basic procedures for the proposed scheme are as follows. (1) Computed order tracking is applied to reveal the order contents and identify the order(s) of interest. (2) Vold–Kalman filter order tracking is used to extract the order(s) of interest—these filtered order(s) constitute the so-called selected vibrations. (3) Time domain statistic indicators are applied to the selected vibrations for faulty information-emphasized diagnostics. The proposed scheme is explained and demonstrated in a signal simulation model and experimental studies and the method proves to be effective for planetary gearbox fault diagnosis. (paper)

  14. Relation Between Motility, Accelerated Aging and Gene Expression in Selected Drosophila Strains under Hypergravity Conditions

    Science.gov (United States)

    Serrano, Paloma; van Loon, Jack J. W. A.; Medina, F. Javier; Herranz, Raúl

    2013-02-01

    Motility and aging in Drosophila have proven to be highly modified under altered gravity conditions (both in space and ground simulation facilities). In order to find out how closely connected they are, five strains with altered geotactic response or survival rates were selected and exposed to an altered gravity environment of 2 g. By analysing the different motile and behavioural patterns and the median survival rates, we show that altered gravity leads to changes in motility, which will have a negative impact on the flies' survival. Previous results show a differential gene expression between sessile samples and adults and confirm that environmentally-conditioned behavioural patterns constrain flies' gene expression and life span. Therefore, hypergravity is considered an environmental stress factor and strains that do not respond to this new environment experience an increment in motility, which is the major cause for the observed increased mortality also under microgravity conditions. The neutral-geotaxis selected strain (strain M) showed the most severe phenotype, unable to respond to variations in the gravitational field. Alternatively, the opposite phenotype was observed in positive-geotaxis and long-life selected flies (strains B and L, respectively), suggesting that these populations are less sensitive to alterations in the gravitational load. We conclude that the behavioural response has a greater contribution to aging than the modified energy consumption in altered gravity environments.

  15. USING A MULTI CRITERIA DECISION MAKING APPROACH FOR OPEN AND DISTANCE LEARNING SYSTEM SELECTION

    OpenAIRE

    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 &...

  16. New model for selection of applicants at the universities in the conditions Smart-society

    Directory of Open Access Journals (Sweden)

    Alexandr S. Molchanov

    2017-01-01

    Full Text Available Smart-society -– a new quality of society. The greatest value to society will be represented by people trained by the new technologies or who require minimal resources to study up to the required level. Universities will use the smarteducational technology, that will require a new level of training the applicant and the other search engines, selection and motivation of applicants. The paper proposes a new model of selection of applicants to universities, which will improve the selection process of students, focusing on the management of individual educational routes learner, since elementary school.The main beneficiaries are the selection system are applicants, potential employer, educational organization. The main core of the system -– its own route management. System functionality includes:– monitoring of the environment (demography, economics, education;– work with targets;– analysis of the previous route and its correlation with the target;– control and fixing the trajectory of learning;– additional control and validation competencies as the demand for an employer or educational institution, and at the request of the trainees;– forecasting and calculation of several route options, with a choice for the student’s request.Taking into account the changes in society and the division of labor, as well as a set of really existing and planned information systems, we can conclude the feasibility of practical implementation of the proposed model. The development of such system of selection of applicants can contribute to:– earlier determining of the future profession with the involvement of employers and educational institutions;– early professional self-determination of applicants;– improve the quality of education at the expense of formation of additional motivation to learn;– possibility of operative management request to the construction or design of the educational program for the educational institution

  17. Hebbian Learning in a Random Network Captures Selectivity Properties of the Prefrontal Cortex

    Science.gov (United States)

    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 (

  18. Design Criteria, Operating Conditions, and Nickel-Iron Hydroxide Catalyst Materials for Selective Seawater Electrolysis.

    Science.gov (United States)

    Dionigi, Fabio; Reier, Tobias; Pawolek, Zarina; Gliech, Manuel; Strasser, Peter

    2016-05-10

    Seawater is an abundant water resource on our planet and its direct electrolysis has the advantage that it would not compete with activities demanding fresh water. Oxygen selectivity is challenging when performing seawater electrolysis owing to competing chloride oxidation reactions. In this work we propose a design criterion based on thermodynamic and kinetic considerations that identifies alkaline conditions as preferable to obtain high selectivity for the oxygen evolution reaction. The criterion states that catalysts sustaining the desired operating current with an overpotential seawater-mimicking electrolyte. The catalyst was synthesized by a solvothermal method and the activity, surface redox chemistry, and stability were tested electrochemically in alkaline and near-neutral conditions (borate buffer at pH 9.2) and under both fresh seawater conditions. The Tafel slope at low current densities is not influenced by pH or presence of chloride. On the other hand, the addition of chloride ions has an influence in the temporal evolution of the nickel reduction peak and on both the activity and stability at high current densities at pH 9.2. Faradaic efficiency close to 100 % under the operating conditions predicted by our design criteria was proven using in situ electrochemical mass spectrometry. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  19. Feedback-based probabilistic category learning is selectively impaired in attention/hyperactivity deficit disorder.

    Science.gov (United States)

    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

  20. Multi-level gene/MiRNA feature selection using deep belief nets and active learning.

    Science.gov (United States)

    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].

  1. Emotional eating and Pavlovian learning: evidence for conditioned appetitive responding to negative emotional states.

    Science.gov (United States)

    Bongers, Peggy; Jansen, Anita

    2017-02-01

    Appetitive learning has been demonstrated several times using neutral cues or contexts as a predictor of food intake and it has been shown that humans easily learn cued desires for foods. It has, however, never been studied whether internal cues are also capable of appetitive conditioning. In this study, we tested whether humans can learn cued eating desires to negative moods as conditioned stimuli (CS), thereby offering a potential explanation of emotional eating (EE). Female participants were randomly presented with 10 different stimuli eliciting either negative or neutral emotional states, with one of these states paired with eating chocolate. Expectancy to eat, desire to eat, salivation, and unpleasantness of experiencing negative emotions were assessed. After conditioning, participants were brought into a negative emotional state and were asked to choose between money and chocolate. Data showed differential conditioned responding on the expectancy and desire measures, but not on salivation. Specific conditioned effects were obtained for participants with a higher BMI (body mass index) on the choice task, and for participants high on EE on the unpleasantness ratings. These findings provide the first experimental evidence for the idea that negative emotions can act as conditioned stimuli, and might suggest that classical conditioning is involved in EE.

  2. Robust Machine Learning Variable Importance Analyses of Medical Conditions for Health Care Spending.

    Science.gov (United States)

    Rose, Sherri

    2018-03-11

    To propose nonparametric double robust machine learning in variable importance analyses of medical conditions for health spending. 2011-2012 Truven MarketScan database. I evaluate how much more, on average, commercially insured enrollees with each of 26 of the most prevalent medical conditions cost per year after controlling for demographics and other medical conditions. This is accomplished within the nonparametric targeted learning framework, which incorporates ensemble machine learning. Previous literature studying the impact of medical conditions on health care spending has almost exclusively focused on parametric risk adjustment; thus, I compare my approach to parametric regression. My results demonstrate that multiple sclerosis, congestive heart failure, severe cancers, major depression and bipolar disorders, and chronic hepatitis are the most costly medical conditions on average per individual. These findings differed from those obtained using parametric regression. The literature may be underestimating the spending contributions of several medical conditions, which is a potentially critical oversight. If current methods are not capturing the true incremental effect of medical conditions, undesirable incentives related to care may remain. Further work is needed to directly study these issues in the context of federal formulas. © Health Research and Educational Trust.

  3. Emotional eating and Pavlovian learning: does negative mood facilitate appetitive conditioning?

    Science.gov (United States)

    Bongers, Peggy; van den Akker, Karolien; Havermans, Remco; Jansen, Anita

    2015-06-01

    Emotional eating has been suggested to be a learned behaviour; more specifically, classical conditioning processes might be involved in its development. In the present study we investigated whether a negative mood facilitates appetitive conditioning and whether trait impulsivity influences this process. After undergoing either a negative or neutral mood induction, participants were subjected to a differential classical conditioning procedure, using neutral stimuli and appetizing food. Two initially neutral distinctive vases with flowers were (CS+) or were not (CS-) paired with chocolate mousse intake. We measured participants' expectancy and desire to eat (4 CS+ and 4 CS- trials), salivation response, and actual food intake. The BIS-11 was administered to assess trait impulsivity. In both mood conditions, participants showed a classically conditioned appetite. Unexpectedly, there was no evidence of facilitated appetitive learning in a negative mood with regard to expectancy, desire, salivation, or intake. However, immediately before the taste test, participants in the negative mood condition reported a stronger desire to eat in the CS+ compared to the CS- condition, while no such effect occurred in the neutral group. An effect of impulsivity was found with regard to food intake in the neutral mood condition: high-impulsive participants consumed less food when presented with the CS+ compared to the CS-, and also less than low-impulsive participants. An alternative pathway to appetitive conditioning with regard to emotions is that it is not the neutral stimuli, but the emotions themselves that become conditioned stimuli and elicit appetitive responses. Copyright © 2015 Elsevier Ltd. All rights reserved.

  4. Optimal Channel Selection Based on Online Decision and Offline Learning in Multichannel Wireless Sensor Networks

    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.

  5. Mediating Global Reforms Locally: A Study of the Enabling Conditions for Promoting Active Learning in a Maldivian Island School

    Science.gov (United States)

    Di Biase, Rhonda

    2017-01-01

    This paper explores active learning reform in the small state of the Maldives. Acknowledging the implementation challenges of active learning approaches globally, the study explored the policy-practice intersection by examining the experiences of one island school and its approach to promoting active learning pedagogy. The school was selected for…

  6. How learning might strengthen existing visual object representations in human object-selective cortex.

    Science.gov (United States)

    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.

  7. Test-potentiated learning: three independent replications, a disconfirmed hypothesis, and an unexpected boundary condition.

    Science.gov (United States)

    Wissman, Kathryn T; Rawson, Katherine A

    2018-04-01

    Arnold and McDermott [(2013). Test-potentiated learning: Distinguishing between direct and indirect effects of testing. Journal of Experimental Psychology: Learning, Memory, and Cognition, 39, 940-945] isolated the indirect effects of testing and concluded that encoding is enhanced to a greater extent following more versus fewer practice tests, referred to as test-potentiated learning. The current research provided further evidence for test-potentiated learning and evaluated the covert retrieval hypothesis as an alternative explanation for the observed effect. Learners initially studied foreign language word pairs and then completed either one or five practice tests before restudy occurred. Results of greatest interest concern performance on test trials following restudy for items that were not correctly recalled on the test trials that preceded restudy. Results replicate Arnold and McDermott (2013) by demonstrating that more versus fewer tests potentiate learning when trial time is limited. Results also provide strong evidence against the covert retrieval hypothesis concerning why the effect occurs (i.e., it does not reflect differential covert retrieval during pre-restudy trials). In addition, outcomes indicate that the magnitude of the test-potentiated learning effect decreases as trial length increases, revealing an unexpected boundary condition to test-potentiated learning.

  8. Secure relay selection based on learning with negative externality in wireless networks

    Science.gov (United States)

    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.

  9. Learning of conditioned reflexes of the Wistar rat under intermittent action of low CO concentrations

    Energy Technology Data Exchange (ETDEWEB)

    Zorn, H.

    1972-04-01

    The influence of an intermittent long-time exposure to a concentration of 150 ppm carbon monoxide on the ability to learn conditioned reflexes was investigated with Wistar rats. Half the 80 rats employed and divided into intelligence groups were exposed to this concentration at night five times for 8 hr weekly. The carboxyhemoglobin level in the blood of these animals increased to 7-13 percent. After an adequate interval for CO elimination, the rats exposed and the control animals were trained to develop a conditioned flight reflex. At a later date, the results were ascertained. With regard to the progress in learning this action, the CO-exposed animals showed a significant reduction in performance (longer learning time, more frequent deficient behavior, and inclination for stupor and anxious denial).

  10. Dissociable Hippocampal and Amygdalar D1-like receptor contribution to Discriminated Pavlovian conditioned approach learning

    Science.gov (United States)

    Andrzejewski, Matthew E; Ryals, Curtis

    2016-01-01

    Pavlovian conditioning is an elementary form of reward-related behavioral adaptation. The mesolimbic dopamine system is widely considered to mediate critical aspects of reward-related learning. For example, initial acquisition of positively-reinforced operant behavior requires dopamine (DA) D1 receptor (D1R) activation in the basolateral amygdala (BLA), central nucleus of the amygdala (CeA), and the ventral subiculum (vSUB). However, the role of D1R activation in these areas on appetitive, non-drug-related, Pavlovian learning is not currently known. In separate experiments, microinfusions of the D1-like receptor antagonist SCH-23390 (3.0 nmol/0.5 μL per side) into the amygdala and subiculum preceded discriminated Pavlovian conditioned approach (dPCA) training sessions. D1-like antagonism in all three structures impaired the acquisition of discriminated approach, but had no effect on performance after conditioning was asymptotic. Moreover, dissociable effects of D1-like antagonism in the three structures on components of discriminated responding were obtained. Lastly, the lack of latent inhibition in drug-treated groups may elucidate the role of D1-like in reward-related Pavlovian conditioning. The present data suggest a role for the D1 receptors in the amygdala and hippocampus in learning the significance of conditional stimuli, but not in the expression of conditional responses. PMID:26632336

  11. Computer Mathematics Games and Conditions for Enhancing Young Children's Learning of Number Sense

    Science.gov (United States)

    Kermani, Hengameh

    2017-01-01

    Purpose: The present study was designed to examine whether mathematics computer games improved young children's learning of number sense under three different conditions: when used individually, with a peer, and with teacher facilitation. Methodology: This study utilized a mixed methodology, collecting both quantitative and qualitative data. A…

  12. Naïve and Robust: Class-Conditional Independence in Human Classification Learning

    Science.gov (United States)

    Jarecki, Jana B.; Meder, Björn; Nelson, Jonathan D.

    2018-01-01

    Humans excel in categorization. Yet from a computational standpoint, learning a novel probabilistic classification task involves severe computational challenges. The present paper investigates one way to address these challenges: assuming class-conditional independence of features. This feature independence assumption simplifies the inference…

  13. Simultaneous and Sequential Feature Negative Discriminations: Elemental Learning and Occasion Setting in Human Pavlovian Conditioning

    Science.gov (United States)

    Baeyens, Frank; Vervliet, Bram; Vansteenwegen, Debora; Beckers, Tom; Hermans, Dirk; Eelen, Paul

    2004-01-01

    Using a conditioned suppression task, we investigated simultaneous (XA-/A+) vs. sequential (X [right arrow] A-/A+) Feature Negative (FN) discrimination learning in humans. We expected the simultaneous discrimination to result in X (or alternatively the XA configuration) becoming an inhibitor acting directly on the US, and the sequential…

  14. Blockade of Dopamine Activity in the Nucleus Accumbens Impairs Learning Extinction of Conditioned Fear

    Science.gov (United States)

    Holtzman-Assif, Orit; Laurent, Vincent; Westbrook, R. Frederick

    2010-01-01

    Three experiments used rats to investigate the role of dopamine activity in learning to inhibit conditioned fear responses (freezing) in extinction. In Experiment 1, rats systemically injected with the D2 dopamine antagonist, haloperidol, froze more across multiple extinction sessions and on a drug-free retention test than control rats. In…

  15. Hyperresponsiveness of the Neural Fear Network During Fear Conditioning and Extinction Learning in Male Cocaine Users

    NARCIS (Netherlands)

    Kaag, A.M.; Levar, N.; Woutersen, K.; Homberg, J.R.; Brink, W. van den; Reneman, L.; Wingen, G. van

    2016-01-01

    OBJECTIVE: The authors investigated whether cocaine use disorder is associated with abnormalities in the neural underpinnings of aversive conditioning and extinction learning, as these processes may play an important role in the development and persistence of drug abuse. METHOD: Forty male regular

  16. Individual differences in discriminatory fear learning under conditions of ambiguity: a vulnerability factor for anxiety disorders?

    NARCIS (Netherlands)

    Arnaudova, I.; Krypotos, A.M.; Effting, M.; Boddez, Y.; Kindt, M.; Beckers, T.

    2013-01-01

    Complex fear learning procedures might be better suited than the common differential fear-conditioning paradigm for detecting individual differences related to vulnerability for anxiety disorders. Two such procedures are the blocking procedure and the protection-from-overshadowing procedure. Their

  17. Learning to Promote Health at an Emergency Care Department: Identifying Expansive and Restrictive Conditions

    Science.gov (United States)

    Gustavsson, Maria; Ekberg, Kerstin

    2015-01-01

    This article reports on the findings of a planned workplace health promotion intervention, and the aim is to identify conditions that facilitated or restricted the learning to promote health at an emergency care department in a Swedish hospital. The study had a longitudinal design, with interviews before and after the intervention and follow-up…

  18. Learning-based encoding with soft assignment for age estimation under unconstrained imaging conditions

    NARCIS (Netherlands)

    Alnajar, F.; Shan, C.; Gevers, T.; Geusebroek, J.M.

    2012-01-01

    In this paper we propose to adopt a learning-based encoding method for age estimation under unconstrained imaging conditions. A similar approach [Cao et al., 2010] is applied to face recognition in real-life face images. However, the feature vectors are encoded in hard manner i.e. each feature

  19. Conditions for Contingent Instructors Engaged in the Scholarship of Teaching and Learning

    Science.gov (United States)

    Vander Kloet, Marie; Frake-Mistak, Mandy; McGinn, Michelle K.; Caldecott, Marion; Aspenlieder, Erin D.; Beres, Jacqueline L.; Fukuzawa, Sherry; Cassidy, Alice; Gill, Apryl

    2017-01-01

    An increasingly large number of courses in Canadian postsecondary institutions are taught by contingent instructors who hold full- or part-time positions for contractually limited time periods. Despite strong commitments to advancing teaching and learning, the labour and employment conditions for contingent instructors affect the incentives and…

  20. The Effects of Hypertext Gloss on Comprehension and Vocabulary Retention under Incidental and Intentional Learning Conditions

    Science.gov (United States)

    Zandieh, Zeinab; Jafarigohar, Manoochehr

    2012-01-01

    The present study investigated comprehension, immediate and delayed vocabulary retention under incidental and intentional learning conditions via computer mediated hypertext gloss. One hundred and eighty four (N = 184) intermediate students of English as a foreign language at an English school participated in the study. They were randomly assigned…

  1. CHANGES IN SELECTIVITY OF GAMMA-AMINOBUTYRIC ACID FORMATION EFFECTED BY FERMENTATION CONDITIONS AND MICROORGANISMS RESOURCES

    Directory of Open Access Journals (Sweden)

    Kamila Kovalovská

    2011-10-01

    Full Text Available In this study we observe the effect of fermentation conditions and resources of microorganisms for production of γ-aminobutyric acid (GABA. The content of produced GABA depends on various conditions such as the amount of precursor, an addition of salt, enzyme and the effect of pH. The highest selectivity of GABA (74.0 % from the precursor (L-monosodium glutamate has been determinate in the follow conditions: in the presence of pre-cultured microorganisms from Encián cheese in amount 1.66 % (w/v the source of microorganisms/volume of the fermentation mixture, after the addition of 0.028 % (w/v of CaCl2/volume of the fermentation mixture, 100 μM of pyridoxal-5-phosphate (P-5-P and the GABA precursor concentration in the fermentation mixture 2.6 mg ml-1 in an atmosphere of gas nitrogen. Pure cultures of lactic acid bacteria increased the selectivity of GABA by an average of 20 % compared with bacteria from the path of Encián.

  2. Effect of encapsulation of selected probiotic cell on survival in simulated gastrointestinal tract condition

    Directory of Open Access Journals (Sweden)

    Hasiah Ayama

    2014-06-01

    Full Text Available The health benefits of probiotic bacteria have been led to their increasing use in foods. Encapsulation has been investigated to improve their survival. In this study, the selection, encapsulation and viability of lactic acid bacteria (LAB with probiotic properties in simulated gastrointestinal tract (GIT condition were investigated. One hundred and fifty isolates of LAB were obtained from 30 samples of raw cow and goat milk and some fermented foods. Nine isolates could survive under GIT condition and only 3 isolates exhibited an antimicrobial activity against all food-borne pathogenic bacteria. Among them, 2 isolates (CM21 and CM53 exhibited bile salt hydrolase activity on glycocholate and glycodeoxycholate agar plates and were identified as Lactobacillus plantarum. CM53 was selected for encapsulation using 1-3% alginate and 2% Hi-maize resistant starch by emulsion system. Viability and releasing ability of encapsulated CM53 in simulated GIT condition was increased in accordance to the alginate concentration and incubation time, respectively.

  3. Research on ration selection of mixed absorbent solution for membrane air-conditioning system

    International Nuclear Information System (INIS)

    Li, Xiu-Wei; Zhang, Xiao-Song; Wang, Fang; Zhao, Xiao; Zhang, Zhuo

    2015-01-01

    Highlights: • We derive models of the membrane air-conditioning system with mixed absorbents. • We make analysis on system COP, cost-effectiveness and economy. • The paper provides a new method for ideal absorbent selection. • The solutes concentration of 50% achieves the best cost-effectiveness and the economy. - Abstract: Absorption air-conditioning system is a good alternative to vapor compression system for developing low carbon society. To improve the performance of the traditional absorption system, the membrane air-conditioning system is configured and its COP can reach as high as 6. Mixed absorbents are potential for cost reduction of the membrane system while maintaining a high COP. On the purpose of finding ideal mixed absorbent groups, this paper makes analysis on COP, cost-effectiveness and economy of the membrane system with mixed LiBr–CaCl 2 absorbent solution. The models of the system have been developed for the analysis. The results show the COP is higher for the absorbent groups with lower concentration of the total solute and higher concentration ratio of LiBr. It also reveals when the total solutes concentration is about 50%, it achieves the best cost-effectiveness and the economy. The process of the analysis provides a useful method for mixed absorbents selection

  4. Life at extreme conditions: neutron scattering studies of biological molecules suggest that evolution selected dynamics

    International Nuclear Information System (INIS)

    Zaccai, Joseph Giuseppe

    2008-01-01

    The short review concentrates on recent work performed at the neutrons in biology laboratories of the Institut Laue Langevin and Institut de Biologie Structurale in Grenoble. Extremophile organisms have been discovered that require extreme conditions of temperature, pressure or solvent environment for survival. The existence of such organisms poses a significant challenge in understanding the physical chemistry of their proteins, in view of the great sensitivity of protein structure and stability to the aqueous environment and to external conditions in general. Results of neutron scattering measurements on the dynamics of proteins from extremophile organisms, in vitro as well as in vivo, indicated remarkably how adaptation to extreme conditions involves forces and fluctuation amplitudes that have been selected specifically, suggesting that evolutionary macromolecular selection proceeded via dynamics. The experiments were performed on a halophilic protein, and membrane adapted to high salt, a thermophilic enzyme adapted to high temperature and its mesophilic (adapted to 37 degC) homologue; and in vivo for psychrophilic, mesophilic, thermophilic and hyperthermophilic bacteria, adapted respectively to temperatures of 4 degC, 37 degC, 75 degC and 85 degC. Further work demonstrated the existence of a water component of exceptionally low mobility in an extreme halophile from the Dead Sea, which is not present in mesophile bacterial cells. (author)

  5. Learning to selectively attend from context-specific attentional histories: A demonstration and some constraints.

    Science.gov (United States)

    Crump, Matthew J C

    2016-03-01

    Multiple lines of evidence from the attention and performance literature show that attention filtering can be controlled by higher level voluntary processes and lower-level cue-driven processes (for recent reviews see Bugg, 2012; Bugg & Crump, 2012; Egner, 2008). The experiments were designed to test a general hypothesis that cue-driven control learns from context-specific histories of prior acts of selective attention. Several web-based flanker studies were conducted via Amazon Mechanical Turk. Attention filtering demands were induced by a secondary one-back memory task after each trial prompting recall of the last target or distractor letter. Blocking recall demands produced larger flanker effects for the distractor than target recall conditions. Mixing recall demands and associating them with particular stimulus-cues (location, colour, letter, and font) sometimes showed rapid, contextual control of flanker interference, and sometimes did not. The results show that subtle methodological parameters can influence whether or not contextual control is observed. More generally, the results show that contextual control phenomena can be influenced by other sources of control, including other cue-driven sources competing for control. (c) 2016 APA, all rights reserved).

  6. The Conditional Scope of Selective Exposure to Political Television Media, 1996-2012

    DEFF Research Database (Denmark)

    Robison, Joshua; Leeper, Thomas

    Pew Research Center data from 1996 to 2012, we document that exposure to ideological or partisan media is heavily conditioned by time, audience size, and individuals’ interest in national politics. Selective exposure seems to be limited to partisans with a high interest in politics viewing a handful......A considerable amount of research documents an ideological or partisan bias in media exposure: liberals and Democrats are more likely to be exposed to liberal-leaning media while conservatives and Republicans are more likely to be exposed to conservative-leaning media. Much of this research......, however, was conducted in the mid-2000’s, a politically contentious period in American politics. We argue that there are many reasons to expect this political context to be a period that encouraged high degrees of selective exposure, especially among partisans and those with high political interest. Using...

  7. A quantitative genetic model of reciprocal altruism: a condition for kin or group selection to prevail.

    Science.gov (United States)

    Aoki, K

    1983-01-01

    A condition is derived for reciprocal altruism to evolve by kin or group selection. It is assumed that many additively acting genes of small effect and the environment determine the probability that an individual is a reciprocal altruist, as opposed to being unconditionally selfish. The particular form of reciprocal altruism considered is TIT FOR TAT, a strategy that involves being altruistic on the first encounter with another individual and doing whatever the other did on the previous encounter in subsequent encounters with the same individual. Encounters are restricted to individuals of the same generation belonging to the same kin or breeding group, but first encounters occur at random within that group. The number of individuals with which an individual interacts is assumed to be the same within any kin or breeding group. There are 1 + i expected encounters between two interacting individuals. On any encounter, it is assumed that an individual who behaves altruistically suffers a cost in personal fitness proportional to c while improving his partner's fitness by the same proportion of b. Then, the condition for kin or group selection to prevail is [Formula: see text] if group size is sufficiently large and the group mean and the within-group genotypic variance of the trait value (i.e., the probability of being a TIT-FOR-TAT strategist) are uncorrelated. Here, C, Vb, and Tb are the population mean, between-group variance, and between-group third central moment of the trait value and r is the correlation between the additive genotypic values of interacting kin or of individuals within the same breeding group. The right-hand side of the above inequality is monotone decreasing in C if we hold Tb/Vb constant, and kin and group selection become superfluous beyond a certain threshold value of C. The effect of finite group size is also considered in a kin-selection model. PMID:6575395

  8. Molecular Dynamics Simulation and Analysis of Interfacial Water at Selected Sulfide Mineral Surfaces under Anaerobic Conditions

    Energy Technology Data Exchange (ETDEWEB)

    Jin, Jiaqi; Miller, Jan D.; Dang, Liem X.

    2014-04-10

    In this paper, we report on a molecular dynamics simulation (MDS) study of the behavior of interfacial water at selected sulfide mineral surfaces under anaerobic conditions. The study revealed the interfacial water structure and wetting characteristics of the pyrite (100) surface, galena (100) surface, chalcopyrite (012) surface, sphalerite (110) surface, and molybdenite surfaces (i.e., the face, armchair-edge, and zigzag-edge surfaces), including simulated contact angles, relative number density profiles, water dipole orientations, hydrogen-bonding, and residence times. For force fields of the metal and sulfur atoms in selected sulfide minerals used in the MDS, we used the universal force field (UFF) and another set of force fields optimized by quantum chemical calculations for interactions with interfacial water molecules at selected sulfide mineral surfaces. Simulation results for the structural and dynamic properties of interfacial water molecules indicate the natural hydrophobic character for the selected sulfide mineral surfaces under anaerobic conditions as well as the relatively weak hydrophobicity for the sphalerite (110) surface and two molybdenite edge surfaces. Part of the financial support for this study was provided by the U.S. Department of Energy (DOE) under Basic Science Grant No. DE-FG-03-93ER14315. The Division of Chemical Sciences, Geosciences, and Biosciences, Office of Basic Energy Sciences (BES), of the DOE, funded work performed by Liem X. Dang. Battelle operates Pacific Northwest National Laboratory for DOE. The calculations were carried out using computer resources provided by BES. The authors are grateful to Professor Tsun-Mei Chang for valuable discussions.

  9. Deep Learning Questions Can Help Selection of High Ability Candidates for Universities

    Science.gov (United States)

    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…

  10. Training Self-Regulated Learning Skills with Video Modeling Examples: Do Task-Selection Skills Transfer?

    Science.gov (United States)

    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…

  11. 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 ...

  12. Selecting Native Arbuscular Mycorrhizal Fungi to Promote Cassava Growth and Increase Yield under Field Conditions

    Science.gov (United States)

    Séry, D. Jean-Marc; Kouadjo, Z. G. Claude; Voko, B. R. Rodrigue; Zézé, Adolphe

    2016-01-01

    The use of arbuscular mycorrhizal fungal (AMF) inoculation in sustainable agriculture is now widespread worldwide. Although the use of inoculants consisting of native AMF is highly recommended as an alternative to commercial ones, there is no strategy to allow the selection of efficient fungal species from natural communities. The objective of this study was (i) to select efficient native AMF species (ii) evaluate their impact on nematode and water stresses, and (iii) evaluate their impact on cassava yield, an important food security crop in tropical and subtropical regions. Firstly, native AMF communities associated with cassava rhizospheres in fields were collected from different areas and 7 AMF species were selected, based upon their ubiquity and abundance. Using these criteria, two morphotypes (LBVM01 and LBVM02) out of the seven AMF species selected were persistently dominant when cassava was used as a trap plant. LBVM01 and LBVM02 were identified as Acaulospora colombiana (most abundant) and Ambispora appendicula, respectively, after phylogenetic analyses of LSU-ITS-SSU PCR amplified products. Secondly, the potential of these two native AMF species to promote growth and enhance tolerance to root-knot nematode and water stresses of cassava (Yavo variety) was evaluated using single and dual inoculation in greenhouse conditions. Of the two AMF species, it was shown that A. colombiana significantly improved the growth of the cassava and enhanced tolerance to water stress. However, both A. colombiana and A. appendicula conferred bioprotective effects to cassava plants against the nematode Meloidogyne spp., ranging from resistance (suppression or reduction of the nematode reproduction) or tolerance (low or no suppression in cassava growth). Thirdly, the potential of these selected native AMF to improve cassava growth and yield was evaluated under field conditions, compared to a commercial inoculant. In these conditions, the A. colombiana single inoculation and the

  13. Conditional maximum-entropy method for selecting prior distributions in Bayesian statistics

    Science.gov (United States)

    Abe, Sumiyoshi

    2014-11-01

    The conditional maximum-entropy method (abbreviated here as C-MaxEnt) is formulated for selecting prior probability distributions in Bayesian statistics for parameter estimation. This method is inspired by a statistical-mechanical approach to systems governed by dynamics with largely separated time scales and is based on three key concepts: conjugate pairs of variables, dimensionless integration measures with coarse-graining factors and partial maximization of the joint entropy. The method enables one to calculate a prior purely from a likelihood in a simple way. It is shown, in particular, how it not only yields Jeffreys's rules but also reveals new structures hidden behind them.

  14. Resting heart rate variability predicts safety learning and fear extinction in an interoceptive fear conditioning paradigm.

    Directory of Open Access Journals (Sweden)

    Meike Pappens

    Full Text Available This study aimed to investigate whether interindividual differences in autonomic inhibitory control predict safety learning and fear extinction in an interoceptive fear conditioning paradigm. Data from a previously reported study (N = 40 were extended (N = 17 and re-analyzed to test whether healthy participants' resting heart rate variability (HRV - a proxy of cardiac vagal tone - predicts learning performance. The conditioned stimulus (CS was a slight sensation of breathlessness induced by a flow resistor, the unconditioned stimulus (US was an aversive short-lasting suffocation experience induced by a complete occlusion of the breathing circuitry. During acquisition, the paired group received 6 paired CS-US presentations; the control group received 6 explicitly unpaired CS-US presentations. In the extinction phase, both groups were exposed to 6 CS-only presentations. Measures included startle blink EMG, skin conductance responses (SCR and US-expectancy ratings. Resting HRV significantly predicted the startle blink EMG learning curves both during acquisition and extinction. In the unpaired group, higher levels of HRV at rest predicted safety learning to the CS during acquisition. In the paired group, higher levels of HRV were associated with better extinction. Our findings suggest that the strength or integrity of prefrontal inhibitory mechanisms involved in safety- and extinction learning can be indexed by HRV at rest.

  15. Individual differences in discriminatory fear learning under conditions of ambiguity: A vulnerability factor for anxiety disorders?

    Directory of Open Access Journals (Sweden)

    Inna eArnaudova

    2013-05-01

    Full Text Available Complex fear learning procedures might be better suited than the common differential fear conditioning paradigm for detecting individual differences related to vulnerability for anxiety disorders. Two such procedures are the blocking procedure and the protection-from-overshadowing procedure. Their comparison allows for the examination of discriminatory fear learning under conditions of ambiguity. The present study examined the role of individual differences in such discriminatory fear learning. We hypothesized that heightened trait anxiety would be related to a deficit in discriminatory fear learning. Participants gave US-expectancy ratings as an index for the threat value of individual CSs following blocking and protection-from-overshadowing training. The difference in threat value at test between the protected-from-overshadowing CS and the blocked CS was negatively correlated with scores on a self-report tension-stress scale that approximates facets of generalized anxiety disorder (DASS-S, but not with other individual difference variables. In addition, a behavioral test showed that only participants scoring high on the DASS-S avoided the protected-from-overshadowing CS. This observed deficit in discriminatory fear learning for participants with high levels of tension-stress might be an underlying mechanism for fear overgeneralization in diffuse anxiety disorders such as generalized anxiety disorder.

  16. Schwarzian conditions for linear differential operators with selected differential Galois groups

    International Nuclear Information System (INIS)

    Abdelaziz, Y; Maillard, J-M

    2017-01-01

    We show that non-linear Schwarzian differential equations emerging from covariance symmetry conditions imposed on linear differential operators with hypergeometric function solutions can be generalized to arbitrary order linear differential operators with polynomial coefficients having selected differential Galois groups. For order three and order four linear differential operators we show that this pullback invariance up to conjugation eventually reduces to symmetric powers of an underlying order-two operator. We give, precisely, the conditions to have modular correspondences solutions for such Schwarzian differential equations, which was an open question in a previous paper. We analyze in detail a pullbacked hypergeometric example generalizing modular forms, that ushers a pullback invariance up to operator homomorphisms. We finally consider the more general problem of the equivalence of two different order-four linear differential Calabi–Yau operators up to pullbacks and conjugation, and clarify the cases where they have the same Yukawa couplings. (paper)

  17. Schwarzian conditions for linear differential operators with selected differential Galois groups

    Science.gov (United States)

    Abdelaziz, Y.; Maillard, J.-M.

    2017-11-01

    We show that non-linear Schwarzian differential equations emerging from covariance symmetry conditions imposed on linear differential operators with hypergeometric function solutions can be generalized to arbitrary order linear differential operators with polynomial coefficients having selected differential Galois groups. For order three and order four linear differential operators we show that this pullback invariance up to conjugation eventually reduces to symmetric powers of an underlying order-two operator. We give, precisely, the conditions to have modular correspondences solutions for such Schwarzian differential equations, which was an open question in a previous paper. We analyze in detail a pullbacked hypergeometric example generalizing modular forms, that ushers a pullback invariance up to operator homomorphisms. We finally consider the more general problem of the equivalence of two different order-four linear differential Calabi-Yau operators up to pullbacks and conjugation, and clarify the cases where they have the same Yukawa couplings.

  18. Simultaneous Fault Detection and Sensor Selection for Condition Monitoring of Wind Turbines

    Directory of Open Access Journals (Sweden)

    Wenna Zhang

    2016-04-01

    Full Text Available Data collected from the supervisory control and data acquisition (SCADA system are used widely in wind farms to obtain operation and performance information about wind turbines. The paper presents a three-way model by means of parallel factor analysis (PARAFAC for wind turbine fault detection and sensor selection, and evaluates the method with SCADA data obtained from an operational farm. The main characteristic of this new approach is that it can be used to simultaneously explore measurement sample profiles and sensors profiles to avoid discarding potentially relevant information for feature extraction. With K-means clustering method, the measurement data indicating normal, fault and alarm conditions of the wind turbines can be identified, and the sensor array can be optimised for effective condition monitoring.

  19. Selective and Stable Ethylbenzene Dehydrogenation to Styrene over Nanodiamonds under Oxygen-lean Conditions.

    Science.gov (United States)

    Diao, Jiangyong; Feng, Zhenbao; Huang, Rui; Liu, Hongyang; Hamid, Sharifah Bee Abd; Su, Dang Sheng

    2016-04-07

    For the first time, significant improvement of the catalytic performance of nanodiamonds was achieved for the dehydrogenation of ethylbenzene to styrene under oxygen-lean conditions. We demonstrated that the combination of direct dehydrogenation and oxidative dehydrogenation indeed occurred on the nanodiamond surface throughout the reaction system. It was found that the active sp(2)-sp(3) hybridized nanostructure was well maintained after the long-term test and the active ketonic carbonyl groups could be generated in situ. A high reactivity with 40% ethylbenzene conversion and 92% styrene selectivity was obtained over the nanodiamond catalyst under oxygen-lean conditions even after a 240 h test, demonstrating the potential of this procedure for application as a promising industrial process for the ethylbenzene dehydrogenation to styrene without steam protection. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  20. REM sleep selectively prunes and maintains new synapses in development and learning.

    Science.gov (United States)

    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.

  1. Classifier-ensemble incremental-learning procedure for nuclear transient identification at different operational conditions

    Energy Technology Data Exchange (ETDEWEB)

    Baraldi, Piero, E-mail: piero.baraldi@polimi.i [Dipartimento di Energia - Sezione Ingegneria Nucleare, Politecnico di Milano, via Ponzio 34/3, 20133 Milano (Italy); Razavi-Far, Roozbeh [Dipartimento di Energia - Sezione Ingegneria Nucleare, Politecnico di Milano, via Ponzio 34/3, 20133 Milano (Italy); Zio, Enrico [Dipartimento di Energia - Sezione Ingegneria Nucleare, Politecnico di Milano, via Ponzio 34/3, 20133 Milano (Italy); Ecole Centrale Paris-Supelec, Paris (France)

    2011-04-15

    An important requirement for the practical implementation of empirical diagnostic systems is the capability of classifying transients in all plant operational conditions. The present paper proposes an approach based on an ensemble of classifiers for incrementally learning transients under different operational conditions. New classifiers are added to the ensemble where transients occurring in new operational conditions are not satisfactorily classified. The construction of the ensemble is made by bagging; the base classifier is a supervised Fuzzy C Means (FCM) classifier whose outcomes are combined by majority voting. The incremental learning procedure is applied to the identification of simulated transients in the feedwater system of a Boiling Water Reactor (BWR) under different reactor power levels.

  2. Classifier-ensemble incremental-learning procedure for nuclear transient identification at different operational conditions

    International Nuclear Information System (INIS)

    Baraldi, Piero; Razavi-Far, Roozbeh; Zio, Enrico

    2011-01-01

    An important requirement for the practical implementation of empirical diagnostic systems is the capability of classifying transients in all plant operational conditions. The present paper proposes an approach based on an ensemble of classifiers for incrementally learning transients under different operational conditions. New classifiers are added to the ensemble where transients occurring in new operational conditions are not satisfactorily classified. The construction of the ensemble is made by bagging; the base classifier is a supervised Fuzzy C Means (FCM) classifier whose outcomes are combined by majority voting. The incremental learning procedure is applied to the identification of simulated transients in the feedwater system of a Boiling Water Reactor (BWR) under different reactor power levels.

  3. Biomarkers for Musculoskeletal Pain Conditions: Use of Brain Imaging and Machine Learning.

    Science.gov (United States)

    Boissoneault, Jeff; Sevel, Landrew; Letzen, Janelle; Robinson, Michael; Staud, Roland

    2017-01-01

    Chronic musculoskeletal pain condition often shows poor correlations between tissue abnormalities and clinical pain. Therefore, classification of pain conditions like chronic low back pain, osteoarthritis, and fibromyalgia depends mostly on self report and less on objective findings like X-ray or magnetic resonance imaging (MRI) changes. However, recent advances in structural and functional brain imaging have identified brain abnormalities in chronic pain conditions that can be used for illness classification. Because the analysis of complex and multivariate brain imaging data is challenging, machine learning techniques have been increasingly utilized for this purpose. The goal of machine learning is to train specific classifiers to best identify variables of interest on brain MRIs (i.e., biomarkers). This report describes classification techniques capable of separating MRI-based brain biomarkers of chronic pain patients from healthy controls with high accuracy (70-92%) using machine learning, as well as critical scientific, practical, and ethical considerations related to their potential clinical application. Although self-report remains the gold standard for pain assessment, machine learning may aid in the classification of chronic pain disorders like chronic back pain and fibromyalgia as well as provide mechanistic information regarding their neural correlates.

  4. The study of selective property of college student’s learning space

    Science.gov (United States)

    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.

  5. Predicting memory performance under conditions of proactive interference: immediate and delayed judgments of learning.

    Science.gov (United States)

    Wahlheim, Christopher N

    2011-07-01

    Four experiments examined the monitoring accuracy of immediate and delayed judgments of learning (JOLs) under conditions of proactive interference (PI). PI was produced using paired-associate learning tasks that conformed to variations of classic A-B, A-D paradigms. Results revealed that the relative monitoring accuracy of interference items was better for delayed than for immediate JOLs. However, delayed JOLs were overconfident for interference items, but not for items devoid of interference. Intrusions retrieved prior to delayed JOLs produced inflated predictions of performance. These results show that delayed JOLs enhance monitoring accuracy in PI situations, except when intrusions are mistaken for target responses.

  6. Extinction of conditioned fear is better learned and recalled in the morning than in the evening.

    Science.gov (United States)

    Pace-Schott, Edward F; Spencer, Rebecca M C; Vijayakumar, Shilpa; Ahmed, Nafis A K; Verga, Patrick W; Orr, Scott P; Pitman, Roger K; Milad, Mohammed R

    2013-11-01

    Sleep helps emotional memories consolidate and may promote generalization of fear extinction memory. We examined whether extinction learning and memory might differ in the morning and evening due, potentially, to circadian and/or sleep-homeostatic factors. Healthy men (N = 109) in 6 groups completed a 2-session protocol. In Session 1, fear conditioning was followed by extinction learning. Partial reinforcement with mild electric shock produced conditioned skin conductance responses (SCRs) to 2 differently colored lamps (CS+), but not a third color (CS-), within the computer image of a room (conditioning context). One CS+ (CS + E) but not the other (CS + U) was immediately extinguished by un-reinforced presentations in a different room (extinction context). Delay durations of 3 h (within AM or PM), 12 h (morning-to-evening or evening-to-morning) or 24 h (morning-to-morning or evening-to-evening) followed. In Session 2, extinction recall and contextual fear renewal were tested. We observed no significant effects of the delay interval on extinction memory but did observe an effect of time-of-day. Fear extinction was significantly better if learned in the morning (p = .002). Collapsing across CS + type, there was smaller morning differential SCR at both extinction recall (p = .003) and fear renewal (p = .005). Morning extinction recall showed better generalization from the CS + E to CS + U with the response to the CS + U significantly larger than to the CS + E only in the evening (p = .028). Thus, extinction is learned faster and its memory is better generalized in the morning. Cortisol and testosterone showed the expected greater salivary levels in the morning when higher testosterone/cortisol ratio also predicted better extinction learning. Circadian factors may promote morning extinction. Alternatively, evening homeostatic sleep pressure may impede extinction and favor recall of conditioned fear. Copyright © 2013 Elsevier Ltd. All rights reserved.

  7. 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

  8. 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.

  9. Goal selection versus process control while learning to use a brain-computer interface

    Science.gov (United States)

    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.

  10. The XRF spectrometer and the selection of analysis conditions (instrumental variables)

    International Nuclear Information System (INIS)

    Willis, J.P.

    2002-01-01

    Full text: This presentation will begin with a brief discussion of EDXRF and flat- and curved-crystal WDXRF spectrometers, contrasting the major differences between the three types. The remainder of the presentation will contain a detailed overview of the choice and settings of the many instrumental variables contained in a modern WDXRF spectrometer, and will discuss critically the choices facing the analyst in setting up a WDXRF spectrometer for different elements and applications. In particular it will discuss the choice of tube target (when a choice is possible), the kV and mA settings, tube filters, collimator masks, collimators, analyzing crystals, secondary collimators, detectors, pulse height selection, X-ray path medium (air, nitrogen, vacuum or helium), counting times for peak and background positions and their effect on counting statistics and lower limit of detection (LLD). The use of Figure of Merit (FOM) calculations to objectively choose the best combination of instrumental variables also will be discussed. This presentation will be followed by a shorter session on a subsequent day entitled - A Selection of XRF Conditions - Practical Session, where participants will be given the opportunity to discuss in groups the selection of the best instrumental variables for three very diverse applications. Copyright (2002) Australian X-ray Analytical Association Inc

  11. Training self-assessment and task-selection skills : A cognitive approach to improving self-regulated learning

    NARCIS (Netherlands)

    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

  12. Geotechnical conditions of Bulgaria and site selection for radioactive waste repository

    International Nuclear Information System (INIS)

    Iliev, I.; Tacheva, E.

    1993-01-01

    A comparative study of the complex structure of the Bulgarian lands and the engineering geological criteria for site selection of national repositories for high level radwastes is made. A detailed description of the following geotechnical conditions of Bulgaria's territory is given: genetic, lithological and engineering-geological types of rocks; physico-mechanical parameters of the most widespread rocky and semi-rocky engineering geological types; fissuring of the rocks; rock massifs; geodynamic processes. The number of promising variants for repositories have been classified according to the structure of the rock massif and the engineering-geological properties of the layers which are promising for the purpose. The following sites are investigated: 1) sites in one-type homogeneous rock massifs of high strength and elasticity; 2) sites of various type massifs with a promising layer of rocks with medium strength and elasticity; 3) sites in various type massifs with a promising layer of plastic rocks of low strength. It is concluded that the complexity of the geotechnical and other conditions in the territory of Bulgaria would predetermine the deficiency of the list of the properties required for the selected sites. The building up of engineering defence will be needed to offset that deficiency and their problems will be resolved after the specific site have been chosen. Geotechnical elements should be likewise envisaged within the general pattern of the monitoring needed. The designing, installing and putting into operation of the monitoring systems should be accomplished as early as the stage of the detailed investigation of the site selected. 19 refs., 2 suppls. (author)

  13. Selective Breeding under Saline Stressed Conditions of Canola Mutations Induced by Gamma Rays

    International Nuclear Information System (INIS)

    Amer, I.M.; Moustafa, H.A.M.; Mansour, M.F.

    2009-01-01

    Mutation breeding program has been initiated for inducing canola mutations tolerance to saline stressed conditions for growing at harsh land in Egypt. Therefore, seed lots of three cultivars and exotic variety (Bactol, Serow 4, Serow 6 and Evita) were subjected to 100,400 and 600 Gy of gamma rays. Mass selection with 20 % intensity for high number of pods per plant has been done in each treatment in M2 generation. However, individually plants with high number of pods / plant were selected from each variety in M3 generation for test under saline stressed conditions at Ras Sudr region in M4 (8600 and 8300 ppm salinity for soil and irrigation, respectively). The obtained results revealed that eight mutated families from 12- test families in M4 generation surpassed their parents in seed yield / plant and related characters ( plant height ,fruiting zone length , No. of branches , No. of pods / plant ). In addition, the mutant F93 characterized by fast growing and non shuttering pods reflecting 50.4% over Evita control in seed yield/ plant. Twelve mutant lines in M5 represented the mutant families were grown in sandy-loam soil at Inshas region. The three mutant lines (L 22, L 38 and L 45) continuously surpassed their parents in seed yield and related characters, but the increases were less than the previous generation. The increase was 22.3 %, 38.7 % and 36.7 % over seed yield of respective parents. Moreover, mutant L66 exhibited an increase in its yield components in M5 at Inshas only, suggesting that gene expression and genomic structure extremely influenced by environmental factors. Genetic stability for the obtained mutations could be done at different environmental conditions in further studies

  14. Selecting rice mutants with good agronomic performance under conditions of low water supplies

    International Nuclear Information System (INIS)

    González Cepero, María C.; Martínez Romero, Anirebis

    2016-01-01

    The present work is part of the researches that are carried out in the Regional Project of the International Organization of Atomic Energy (IAEA) Mutation Breeding of Alimentary Cultivations in Latin America where Cuba participates. The aim of this project is to obtain new rice varieties tolerant to drought using nuclear techniques, for that which is necessary to determine indicators for early selection of tolerant genotypes and to identify somaclones and/or mutants of good behavior under low water supply. For this study were used, 13 mutants obtained in the National Institute of Agricultural Sciences (INCA) as well as the rice varieties Amistad-82 and J-104. The response to the hydric stress under field conditions was determined, using irrigation during the first 45 days, interrupting later for the plant cycle, were determined: I) the height of the plant, II) weigh of 1000 grains, III) length of panicle, IV) number of full grains, V) vain grains, VI) number of panicle for lineal meter and VII) yield for square meter. Likewise in vitro the answers to the drought with a concentration of 5 g L-1 of PEG-6000 to simulate the hydric stress and the Relative Tolerance Index of root and of height were evaluated. Some indicators for early selection of tolerant genotypes starting from the existent correlation among the characters evaluated in the field in vivo and in vitro were also determined. The INCA genotypes LP-10 and 8552 showed a better behavior under conditions of low supplies of water and INCA LP 16 genotypes and mutant 8553 were the most susceptible because they could not panicular under the same conditions. (author)

  15. FACTORS THAT INFLUENCE THE SELECTION OF LEARNING OPPORTUNITIES FOR STUDENT NURSES IN PRIMARY HEALTH CARE

    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.

  16. Selective bilateral amygdala lesions in rhesus monkeys fail to disrupt object reversal learning.

    Science.gov (United States)

    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.

  17. Feature selection and multi-kernel learning for adaptive graph regularized nonnegative matrix factorization

    KAUST Repository

    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.

  18. Lean production tools and decision latitude enable conditions for innovative learning in organizations: a multilevel analysis.

    Science.gov (United States)

    Fagerlind Ståhl, Anna-Carin; Gustavsson, Maria; Karlsson, Nadine; Johansson, Gun; Ekberg, Kerstin

    2015-03-01

    The effect of lean production on conditions for learning is debated. This study aimed to investigate how tools inspired by lean production (standardization, resource reduction, visual monitoring, housekeeping, value flow analysis) were associated with an innovative learning climate and with collective dispersion of ideas in organizations, and whether decision latitude contributed to these associations. A questionnaire was sent out to employees in public, private, production and service organizations (n = 4442). Multilevel linear regression analyses were used. Use of lean tools and decision latitude were positively associated with an innovative learning climate and collective dispersion of ideas. A low degree of decision latitude was a modifier in the association to collective dispersion of ideas. Lean tools can enable shared understanding and collective spreading of ideas, needed for the development of work processes, especially when decision latitude is low. Value flow analysis played a pivotal role in the associations. Copyright © 2014 Elsevier Ltd and The Ergonomics Society. All rights reserved.

  19. The experiences of patients with Duchenne muscular dystrophy in facing and learning about their clinical conditions.

    Science.gov (United States)

    Fujino, Haruo; Iwata, Yuko; Saito, Toshio; Matsumura, Tsuyoshi; Fujimura, Harutoshi; Imura, Osamu

    2016-01-01

    Patients experience extreme difficulty when facing an intractable genetic disease. Herein, we examine the experiences of patients with Duchenne muscular dystrophy in facing and learning about their disease. A total of seven patients with Duchenne muscular dystrophy (age range: 20-48) participated. We conducted in-depth interviews with them about how they learned of their disease and how their feelings regarding the disease changed over time. Transcribed data were analysed using thematic analysis. The following themes emerged from this analysis: "experiences before receiving the diagnosis," "experiences when they learned of their condition and progression of the disease," "supports," and "desired explanations." Anxiety and worry were most pronounced when they had to transition to using wheelchairs or respirators due to disease progression; indeed, such transitions affect the patients psychological adjustment. In such times, support from significant others in their lives helped patients adjust.

  20. Selective transfer of visual working memory training on Chinese character learning.

    Science.gov (United States)

    Opitz, Bertram; Schneiders, Julia A; Krick, Christoph M; Mecklinger, Axel

    2014-01-01

    Previous research has shown a systematic relationship between phonological working memory capacity and second language proficiency for alphabetic languages. However, little is known about the impact of working memory processes on second language learning in a non-alphabetic language such as Mandarin Chinese. Due to the greater complexity of the Chinese writing system we expect that visual working memory rather than phonological working memory exerts a unique influence on learning Chinese characters. This issue was explored in the present experiment by comparing visual working memory training with an active (auditory working memory training) control condition and a passive, no training control condition. Training induced modulations in language-related brain networks were additionally examined using functional magnetic resonance imaging in a pretest-training-posttest design. As revealed by pre- to posttest comparisons and analyses of individual differences in working memory training gains, visual working memory training led to positive transfer effects on visual Chinese vocabulary learning compared to both control conditions. In addition, we found sustained activation after visual working memory training in the (predominantly visual) left infero-temporal cortex that was associated with behavioral transfer. In the control conditions, activation either increased (active control condition) or decreased (passive control condition) without reliable behavioral transfer effects. This suggests that visual working memory training leads to more efficient processing and more refined responses in brain regions involved in visual processing. Furthermore, visual working memory training boosted additional activation in the precuneus, presumably reflecting mental image generation of the learned characters. We, therefore, suggest that the conjoint activity of the mid-fusiform gyrus and the precuneus after visual working memory training reflects an interaction of working memory and

  1. A fully automated Drosophila olfactory classical conditioning and testing system for behavioral learning and memory assessment.

    Science.gov (United States)

    Jiang, Hui; Hanna, Eriny; Gatto, Cheryl L; Page, Terry L; Bhuva, Bharat; Broadie, Kendal

    2016-03-01

    Aversive olfactory classical conditioning has been the standard method to assess Drosophila learning and memory behavior for decades, yet training and testing are conducted manually under exceedingly labor-intensive conditions. To overcome this severe limitation, a fully automated, inexpensive system has been developed, which allows accurate and efficient Pavlovian associative learning/memory analyses for high-throughput pharmacological and genetic studies. The automated system employs a linear actuator coupled to an odorant T-maze with airflow-mediated transfer of animals between training and testing stages. Odorant, airflow and electrical shock delivery are automatically administered and monitored during training trials. Control software allows operator-input variables to define parameters of Drosophila learning, short-term memory and long-term memory assays. The approach allows accurate learning/memory determinations with operational fail-safes. Automated learning indices (immediately post-training) and memory indices (after 24h) are comparable to traditional manual experiments, while minimizing experimenter involvement. The automated system provides vast improvements over labor-intensive manual approaches with no experimenter involvement required during either training or testing phases. It provides quality control tracking of airflow rates, odorant delivery and electrical shock treatments, and an expanded platform for high-throughput studies of combinational drug tests and genetic screens. The design uses inexpensive hardware and software for a total cost of ∼$500US, making it affordable to a wide range of investigators. This study demonstrates the design, construction and testing of a fully automated Drosophila olfactory classical association apparatus to provide low-labor, high-fidelity, quality-monitored, high-throughput and inexpensive learning and memory behavioral assays. Copyright © 2015 Elsevier B.V. All rights reserved.

  2. Unemployment and health selection in diverging economic conditions: Compositional changes? Evidence from 28 European countries.

    Science.gov (United States)

    Heggebø, Kristian; Dahl, Espen

    2015-11-04

    Unemployment and health selection in diverging economic conditions: Compositional changes? Evidence from 28 european countries. People with ill health tend to be overrepresented among the unemployment population. The relationship between health and unemployment might, however, be sensitive to the overall economic condition. Specifically, the health composition of the unemployment population could change dramatically when the economy takes a turn for the worse. Using EU-SILC cross sectional data from 2007 (pre-crisis) and 2011 (during crisis) and linear regression models, this paper investigates the relationship between health and unemployment probabilities under differing economic conditions in 28 European countries. The countries are classified according to (i) the level of and (ii) increase in unemployment rate (i.e. >10 percent and doubling of unemployment rate = crisis country). Firstly, the unemployment likelihood for people with ill health is remarkably stable over time in Europe: the coefficients are very similar in pre-crisis and crisis years. Secondly, people with ill health have experienced unemployment to a lesser extent than those with good health status in the crisis year (when we pool the data and compare 2007 and 2011), but only in the countries with a high and rising unemployment rate. The health composition of the unemployment population changes significantly for the better, but only in those European countries that have been severely hit by the current economic crisis.

  3. Present and future assessment of growing degree days over selected Greek areas with different climate conditions

    Science.gov (United States)

    Paparrizos, Spyridon; Matzarakis, Andreas

    2017-10-01

    The determination of heat requirements in the first developing phases of plants has been expressed as Growing Degree Days (GDD). The current study focuses on three selected study areas in Greece that are characterised by different climatic conditions due to their location and aims to assess the future variation and spatial distribution of Growing Degree Days (GDD) and how these can affect the main cultivations in the study areas. Future temperature data were obtained and analysed by the ENSEMBLES project. The analysis was performed for the future periods 2021-2050 and 2071-2100 with the A1B and B1 scenarios. Spatial distribution was performed using a combination of dynamical and statistical downscaling technique through ArcGIS 10.2.1. The results indicated that for all the future periods and scenarios, the GDD are expected to increase. Furthermore, the increase in the Sperchios River basin will be the highest, followed by the Ardas and the Geropotamos River basins. Moreover, the cultivation period will be shifted from April-October to April-September which will have social, economical and environmental benefits. Additionally, the spatial distribution indicated that in the upcoming years the existing cultivations can find favourable conditions and can be expanded in mountainous areas as well. On the other hand, due to the rough topography that exists in the study areas, the wide expansion of the existing cultivations into higher altitudes is unaffordable. Nevertheless, new more profitable cultivations can be introduced which can find propitious conditions in terms of GDD.

  4. Stability of selected volatile contact allergens in different patch test chambers under different storage conditions.

    Science.gov (United States)

    Mose, Kristian F; Andersen, Klaus E; Christensen, Lars Porskjaer

    2012-04-01

    Patch test preparations of volatile substances may evaporate during storage, thereby giving rise to reduced patch test concentrations. To investigate the stability of selected acrylates/methacrylates and fragrance allergens in three different test chambers under different storage conditions. Petrolatum samples of methyl methacrylate (MMA), 2-hydroxyethyl methacrylate (2-HEMA), 2-hydroxypropyl acrylate (2-HPA), cinnamal and eugenol in patch test concentrations were stored in three different test chambers (IQ chamber™, IQ Ultimate™, and Van der Bend® transport container) at room temperature and in a refrigerator. The samples were analysed in triplicate with high-performance liquid chromatography. The decrease in concentration was substantial for all five allergens under both storage conditions in IQ chamber™ and IQ Ultimate™, with the exception of 2-HEMA during storage in the refrigerator. For these two chamber systems, the contact allergen concentration dropped below the stability limit in the following order: MMA, cinnamal, 2-HPA, eugenol, and 2-HEMA. In the Van der Bend® transport container, the contact allergens exhibited acceptable stability under both storage conditions, whereas MMA and 2-HPA required cool storage for maintenance of the limit. The Van der Bend® transport container was the best device for storage of samples of volatile contact allergens. © 2012 John Wiley & Sons A/S.

  5. Thermal conditions in selected urban and semi-natural habitats, important for the forensic entomology.

    Science.gov (United States)

    Michalski, Marek; Nadolski, Jerzy

    2018-06-01

    A long-term study on thermal conditions in selected urban and semi-natural habitats, where human corpses are likely to be found, was conducted in the city of Lodz (Central Poland). Thermal data were collected during two years at nine sites and compared with corresponding data from the nearest permanent meteorological station at Lodz Airport (ICAO code: EPLL). The conditions closest to those at the meteorological station prevailed in the deciduous forest, coefficient of determination R 2 for those sets of data was above 0.96. The open field was characterized by high daily amplitudes, especially during spring, while the site in the allotment gardens was characterized by relatively high winter temperatures. The conditions prevailing in all closed space sites were very diverse and only slightly similar to the external ones. The most distinct site was an unheated basement in a tenement house, where temperature was almost always above 0°C and daily amplitudes were negligible. Copyright © 2018 Elsevier B.V. All rights reserved.

  6. Machine-Learning Techniques for the Determination of Attrition of Forces Due to Atmospheric Conditions

    Science.gov (United States)

    2018-02-01

    selected as a proof of concept due to its vast number of data points. While this report does note some trends associated with temperature and dew...separate data sets for helicopters and airplanes, while selectively requesting the event IDs, descriptions of events, light conditions, temperature , dew...weather events) and the error rate for that class . The rows are labeled for the actual occurrence of those events. Thus, for every row–column

  7. Alignment Condition-Based Robust Adaptive Iterative Learning Control of Uncertain Robot System

    Directory of Open Access Journals (Sweden)

    Guofeng Tong

    2014-04-01

    Full Text Available This paper proposes an adaptive iterative learning control strategy integrated with saturation-based robust control for uncertain robot system in presence of modelling uncertainties, unknown parameter, and external disturbance under alignment condition. An important merit is that it achieves adaptive switching of gain matrix both in conventional PD-type feedforward control and robust adaptive control in the iteration domain simultaneously. The analysis of convergence of proposed control law is based on Lyapunov's direct method under alignment initial condition. Simulation results demonstrate the faster learning rate and better robust performance with proposed algorithm by comparing with other existing robust controllers. The actual experiment on three-DOF robot manipulator shows its better practical effectiveness.

  8. Pedunculopontine tegmental nucleus lesions impair stimulus--reward learning in autoshaping and conditioned reinforcement paradigms.

    Science.gov (United States)

    Inglis, W L; Olmstead, M C; Robbins, T W

    2000-04-01

    The role of the pedunculopontine tegmental nucleus (PPTg) in stimulus-reward learning was assessed by testing the effects of PPTg lesions on performance in visual autoshaping and conditioned reinforcement (CRf) paradigms. Rats with PPTg lesions were unable to learn an association between a conditioned stimulus (CS) and a primary reward in either paradigm. In the autoshaping experiment, PPTg-lesioned rats approached the CS+ and CS- with equal frequency, and the latencies to respond to the two stimuli did not differ. PPTg lesions also disrupted discriminated approaches to an appetitive CS in the CRf paradigm and completely abolished the acquisition of responding with CRf. These data are discussed in the context of a possible cognitive function of the PPTg, particularly in terms of lesion-induced disruptions of attentional processes that are mediated by the thalamus.

  9. [Cooperative learning for improving healthy housing conditions in Bogota: a case study].

    Science.gov (United States)

    Torres-Parra, Camilo A; García-Ubaque, Juan C; García-Ubaque, César A

    2014-01-01

    This was a community-based effort at constructing an educational proposal orientated towards self-empowerment aimed at improving the target population's sanitary, housing and living conditions through cooperative learning. A constructivist approach was adopted based on a programme called "Habitat community manger". The project involved working with fifteen families living in the Mochuelo Bajo barrio in Ciudad Bolívar in Bogotá, Colombia, for identifying the most relevant sanitary aspects for improving their homes and proposing a methodology and organisation for an educational proposal. Twenty-one poor housing-related epidemiological indicators were identified which formed the basis for defining specific problems and establishing a methodology for designing an educational proposal. The course which emerged from the cooperative learning experience was designed to promote the community's skills and education regarding health aimed at improving households' living conditions and ensuring a healthy environment which would allow them to develop an immediate habitat ensuring their own welfare and dignity.

  10. Unweaving Misconceptions: Guided Learning, Simulations, and Misconceptions in Learning Principles of Natural Selection

    Science.gov (United States)

    Weeks, Brian E.

    2013-01-01

    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…

  11. Lateralized implicit sequence learning in uni- and bi-manual conditions.

    Science.gov (United States)

    Schmitz, Rémy; Pasquali, Antoine; Cleeremans, Axel; Peigneux, Philippe

    2013-02-01

    It has been proposed that the right hemisphere (RH) is better suited to acquire novel material whereas the left hemisphere (LH) is more able to process well-routinized information. Here, we ask whether this potential dissociation also manifests itself in an implicit learning task. Using a lateralized version of the serial reaction time task (SRT), we tested whether participants trained in a divided visual field condition primarily stimulating the RH would learn the implicit regularities embedded in sequential material faster than participants in a condition favoring LH processing. In the first study, half of participants were presented sequences in the left (vs. right) visual field, and had to respond using their ipsilateral hand (unimanual condition), hence making visuo-motor processing possible within the same hemisphere. Results showed successful implicit sequence learning, as indicated by increased reaction time for a transfer sequence in both hemispheric conditions and lack of conscious knowledge in a generation task. There was, however, no evidence of interhemispheric differences. In the second study, we hypothesized that a bimanual response version of the lateralized SRT, which requires interhemispheric communication and increases computational and cognitive processing loads, would favor RH-dependent visuospatial/attentional processes. In this bimanual condition, our results revealed a much higher transfer effect in the RH than in the LH condition, suggesting higher RH sensitivity to the processing of novel sequential material. This LH/RH difference was interpreted within the framework of the Novelty-Routinization model [Goldberg, E., & Costa, L. D. (1981). Hemisphere differences in the acquisition and use of descriptive systems. Brain and Language, 14(1), 144-173] and interhemispheric interactions in attentional processing [Banich, M. T. (1998). The missing link: the role of interhemispheric interaction in attentional processing. Brain and Cognition, 36

  12. Cocaine induces state-dependent learning of sexual conditioning in male Japanese quail.

    Science.gov (United States)

    Gill, Karin E; Rice, Beth Ann; Akins, Chana K

    2015-01-01

    State dependent learning effects have been widely studied in a variety of drugs of abuse. However, they have yet to be studied in relation to sexual motivation. The current study investigated state-dependent learning effects of cocaine in male Japanese quail (Coturnix japonica) using a sexual conditioning paradigm. Cocaine-induced state-dependent learning effects were investigated using a 2×2 factorial design with training state as one factor and test state as the other factor. During a 14-day training phase, male quail were injected once daily with 10mg/kg cocaine or saline and then placed in a test chamber after 15min. In the test chamber, sexual conditioning trials consisted of presentation of a light conditioned stimulus (CS) followed by sexual reinforcement. During the state dependent test, half of the birds received a shift in drug state from training to testing (Coc→Sal or Sal→Coc) while the other half remained in the same drug state (Coc→Coc or Sal→Sal). Results showed that male quail that were trained and tested in the same state (Coc→Coc or Sal→Sal) showed greater sexual conditioning than male quail that were trained and tested in different states (Sal→Coc) except when cocaine was administered chronically prior to the test (Coc→Sal). For the latter condition, sexual conditioning persisted from cocaine training to the saline test. The findings suggest that state dependent effects may alter sexual motivation and that repeated exposure to cocaine during sexual activity may increase sexual motivation which, in turn, may lead to high risk sexual activities. An alternative explanation for the findings is also discussed. Copyright © 2014 Elsevier Inc. All rights reserved.

  13. Hippocampal theta activity is selectively associated with contingency detection but not discrimination in rabbit discrimination-reversal eyeblink conditioning.

    Science.gov (United States)

    Nokia, Miriam S; Wikgren, Jan

    2010-04-01

    The relative power of the hippocampal theta-band ( approximately 6 Hz) activity (theta ratio) is thought to reflect a distinct neural state and has been shown to affect learning rate in classical eyeblink conditioning in rabbits. We sought to determine if the theta ratio is mostly related to the detection of the contingency between the stimuli used in conditioning or also to the learning of more complex inhibitory associations when a highly demanding delay discrimination-reversal eyeblink conditioning paradigm is used. A high hippocampal theta ratio was not only associated with a fast increase in conditioned responding in general but also correlated with slow emergence of discriminative responding due to sustained responding to the conditioned stimulus not paired with an unconditioned stimulus. The results indicate that the neural state reflected by the hippocampal theta ratio is specifically linked to forming associations between stimuli rather than to the learning of inhibitory associations needed for successful discrimination. This is in line with the view that the hippocampus is responsible for contingency detection in the early phase of learning in eyeblink conditioning. (c) 2009 Wiley-Liss, Inc.

  14. An efficient heuristic method for dynamic portfolio selection problem under transaction costs and uncertain conditions

    Science.gov (United States)

    Najafi, Amir Abbas; Pourahmadi, Zahra

    2016-04-01

    Selecting the optimal combination of assets in a portfolio is one of the most important decisions in investment management. As investment is a long term concept, looking into a portfolio optimization problem just in a single period may cause loss of some opportunities that could be exploited in a long term view. Hence, it is tried to extend the problem from single to multi-period model. We include trading costs and uncertain conditions to this model which made it more realistic and complex. Hence, we propose an efficient heuristic method to tackle this problem. The efficiency of the method is examined and compared with the results of the rolling single-period optimization and the buy and hold method which shows the superiority of the proposed method.

  15. Selection of full-sib families of Panicum maximum Jacq under low light conditions

    Directory of Open Access Journals (Sweden)

    Douglas Mochi Victor

    2015-04-01

    Full Text Available The silvopastoral system is a viable technological alternative to extensive cattle grazing, however, for it to be successful, forage grass genotypes adapted to reduced light need to be identified. The objective of this study was to select progenies of Panicum maximum tolerant to low light conditions for use in breeding programs and to study the genetic control and performance of some traits associated with shade tolerance. Six full-sib progenies were evaluated in full sun, 50% and 70% of light reduction in pots and subjected to cuttings. Progeny genotypic values ​​(GV increased with light reduction in relation to plant height (H and specific leaf area (SLA. The traits total dry mass accumulation (DM and leaf dry mass accumulation (LDM had GV higher in 50% shade and intermediate in 70% shade. The GV of tiller number (TIL and root dry mass accumulation (RDM decreased with light reduction. The highest positive correlations were obtained for the traits H and RDM with SLA and DM; the highest negative correlations were between TIL and SLA and RDM, and H and LDM. The progenies showed higher tolerance to 50% light reduction and, among them, two stood out and will be used in breeding programs. It was also found that it is not necessary to evaluate some traits under all light conditions. All traits had high broad sense heritability and high genotypic correlation between progenies in all light intensities. There is genetic difference among the progenies regarding the response to different light intensities, which will allow selection for shade tolerance

  16. Multiatlas whole heart segmentation of CT data using conditional entropy for atlas ranking and selection.

    Science.gov (United States)

    Zhuang, Xiahai; Bai, Wenjia; Song, Jingjing; Zhan, Songhua; Qian, Xiaohua; Shi, Wenzhe; Lian, Yanyun; Rueckert, Daniel

    2015-07-01

    Cardiac computed tomography (CT) is widely used in clinical diagnosis of cardiovascular diseases. Whole heart segmentation (WHS) plays a vital role in developing new clinical applications of cardiac CT. However, the shape and appearance of the heart can vary greatly across different scans, making the automatic segmentation particularly challenging. The objective of this work is to develop and evaluate a multiatlas segmentation (MAS) scheme using a new atlas ranking and selection algorithm for automatic WHS of CT data. Research on different MAS strategies and their influence on WHS performance are limited. This work provides a detailed comparison study evaluating the impacts of label fusion, atlas ranking, and sizes of the atlas database on the segmentation performance. Atlases in a database were registered to the target image using a hierarchical registration scheme specifically designed for cardiac images. A subset of the atlases were selected for label fusion, according to the authors' proposed atlas ranking criterion which evaluated the performance of each atlas by computing the conditional entropy of the target image given the propagated atlas labeling. Joint label fusion was used to combine multiple label estimates to obtain the final segmentation. The authors used 30 clinical cardiac CT angiography (CTA) images to evaluate the proposed MAS scheme and to investigate different segmentation strategies. The mean WHS Dice score of the proposed MAS method was 0.918 ± 0.021, and the mean runtime for one case was 13.2 min on a workstation. This MAS scheme using joint label fusion generated significantly better Dice scores than the other label fusion strategies, including majority voting (0.901 ± 0.276, p ranking study, the proposed criterion based on conditional entropy yielded a performance curve with higher WHS Dice scores compared to the conventional schemes (p ranking algorithm and joint label fusion, the MAS scheme is able to generate accurate segmentation

  17. Selective anodic dissolution of cerium from aluminium alloys under potentiostatic conditions

    International Nuclear Information System (INIS)

    Gol'dshtejn, S.L.; Raspopin, S.P.; Seleznev, V.D.; Tunin, A.V.; Fedorov, V.A.

    1975-01-01

    A study was made of selective anodic dissolution of aluminum alloys containing cerium in concentrations from 0.5 to 10% by mass. The electropurification was carried out with the aid of a potentiostatic setup at 700 deg C in atmosphere of purified argon. Liquid aluminum served as the cathode, with chlorine half-cell as reference electrode and the melt of equimolar KCl-NaCl mixture as the electrolyte. The ''current-time'' plots are presented for selective ionization of cerium from aluminum alloys at preset potential values on the installation. For PHIsub(preset)=-2.04 v the current of potentiostatic electrolysis fades out to that of the supporting electrolyte, and the process itself proceeds at a rate that provides maximal extraction of cerium from the alloy (csub9finite)approximately equal to 0.002% by mass) at minimal ionization of the metalsolvent (Δ Msub(Al)approximately equal to 0.2). Alloys containing not less then 1% by mass of Ce exhibit a characteristic abrupt change of the attenuation coefficient apparently owing to nonlinear dependence of unbalance (ΔE) of signals at the input of the potentiostat. The ''ΔE-c'' function for Al alloy containing 0.5% by mass of Ce can be approximated by linear function. In this case the current of potentiostatic electrolysis approaches the value of the limiting diffusion current. To obtain the relationship between the magnitude of the limiting current of Ce ionization and the initial composition of the dissolving alloy, measurements were made under potentiodynamic conditions at a scanning rate of approximately equal to 500 mv/min. The results indicate that isub(intermediate) is directly proportional to csub(initial). It was shown that under the conditions employed, practically complete (csub(finite)<=0.004% by mass) extraction of the electronegative component is possible without noticeable ionization of the metal-solvent

  18. Spawning chronology, nest site selection and nest success of smallmouth bass during benign streamflow conditions

    Science.gov (United States)

    Dauwalter, D.C.; Fisher, W.L.

    2007-01-01

    We documented the nesting chronology, nest site selection and nest success of smallmouth bass Micropterus dolomieu in an upstream (4th order) and downstream (5th order) reach of Baron Fork Creek, Oklahoma. Males started nesting in mid-Apr. when water temperatures increased to 16.9 C upstream, and in late-Apr. when temperatures increased to 16.2 C downstream. Streamflows were low (77% upstream to 82% downstream of mean Apr. streamflow, and 12 and 18% of meanjun. streamflow; 47 and 55 y of record), and decreased throughout the spawning period. Larger males nested first upstream, as has been observed in other populations, but not downstream. Upstream, progeny in 62 of 153 nests developed to swim-up stage. Downstream, progeny in 31 of 73 nests developed to swim-up. Nesting densities upstream (147/km) and downstream (100/km) were both higher than any densities previously reported. Males selected nest sites with intermediate water depths, low water velocity and near cover, behavior that is typical of smallmouth bass. Documented nest failures resulted from human disturbance, angling, and longear sunfish predation. Logistic exposure models showed that water velocity at the nest was negatively related and length of the guarding male was positively related to nest success upstream. Male length and number of degree days were both positively related to nest success downstream. Our results, and those of other studies, suggest that biological factors account for most nest failures during benign (stable, low flow) streamflow conditions, whereas nest failures attributed to substrate mobility or nest abandonment dominate when harsh streamflow conditions (spring floods) coincide with the spawning season.

  19. Attentional Bias for Uncertain Cues of Shock in Human Fear Conditioning: Evidence for Attentional Learning Theory

    Directory of Open Access Journals (Sweden)

    Stephan Koenig

    2017-05-01

    Full Text Available We conducted a human fear conditioning experiment in which three different color cues were followed by an aversive electric shock on 0, 50, and 100% of the trials, and thus induced low (L, partial (P, and high (H shock expectancy, respectively. The cues differed with respect to the strength of their shock association (L < P < H and the uncertainty of their prediction (L < P > H. During conditioning we measured pupil dilation and ocular fixations to index differences in the attentional processing of the cues. After conditioning, the shock-associated colors were introduced as irrelevant distracters during visual search for a shape target while shocks were no longer administered and we analyzed the cues’ potential to capture and hold overt attention automatically. Our findings suggest that fear conditioning creates an automatic attention bias for the conditioned cues that depends on their correlation with the aversive outcome. This bias was exclusively linked to the strength of the cues’ shock association for the early attentional processing of cues in the visual periphery, but additionally was influenced by the uncertainty of the shock prediction after participants fixated on the cues. These findings are in accord with attentional learning theories that formalize how associative learning shapes automatic attention.

  20. Attentional Bias for Uncertain Cues of Shock in Human Fear Conditioning: Evidence for Attentional Learning Theory

    Science.gov (United States)

    Koenig, Stephan; Uengoer, Metin; Lachnit, Harald

    2017-01-01

    We conducted a human fear conditioning experiment in which three different color cues were followed by an aversive electric shock on 0, 50, and 100% of the trials, and thus induced low (L), partial (P), and high (H) shock expectancy, respectively. The cues differed with respect to the strength of their shock association (L H). During conditioning we measured pupil dilation and ocular fixations to index differences in the attentional processing of the cues. After conditioning, the shock-associated colors were introduced as irrelevant distracters during visual search for a shape target while shocks were no longer administered and we analyzed the cues’ potential to capture and hold overt attention automatically. Our findings suggest that fear conditioning creates an automatic attention bias for the conditioned cues that depends on their correlation with the aversive outcome. This bias was exclusively linked to the strength of the cues’ shock association for the early attentional processing of cues in the visual periphery, but additionally was influenced by the uncertainty of the shock prediction after participants fixated on the cues. These findings are in accord with attentional learning theories that formalize how associative learning shapes automatic attention. PMID:28588466

  1. Selective area growth of GaN rod structures by MOVPE: Dependence on growth conditions

    Energy Technology Data Exchange (ETDEWEB)

    Li, Shunfeng; Fuendling, Soenke; Wang, Xue; Erenburg, Milena; Al-Suleiman, Mohamed Aid Mansur; Wei, Jiandong; Wehmann, Hergo-Heinrich; Waag, Andreas [Institut fuer Halbleitertechnik, TU Braunschweig, Hans-Sommer-Strasse 66, 38106 Braunschweig (Germany); Bergbauer, Werner [Institut fuer Halbleitertechnik, TU Braunschweig, Hans-Sommer-Strasse 66, 38106 Braunschweig (Germany); Osram Opto Semiconductors GmbH, Leibnizstr. 4, 93055 Regensburg (Germany); Strassburg, Martin [Osram Opto Semiconductors GmbH, Leibnizstr. 4, 93055 Regensburg (Germany)

    2011-07-15

    Selective area growth of GaN nanorods by metalorganic vapor phase epitaxy is highly demanding for novel applications in nano-optoelectronic and nanophotonics. Recently, we report the successful selective area growth of GaN nanorods in a continuous-flow mode. In this work, as examples, we show the morphology dependence of GaN rods with {mu}m or sub-{mu}m in diameters on growth conditions. Firstly, we found that the nitridation time is critical for the growth, with an optimum from 90 to 180 seconds. This leads to more homogeneous N-polar GaN rods growth. A higher temperature during GaN rod growth tends to increase the aspect ratio of the GaN rods. This is due to the enhanced surface diffusion of growth species. The V/III ratio is also an important parameter for the GaN rod growth. Its increase causes reduction of the aspect ratio of GaN rods, which could be explained by the relatively lower growth rate on (000-1) N-polar top surface than it on {l_brace}1-100{r_brace} m-planes by supplying more NH{sub 3} (copyright 2011 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim) (orig.)

  2. Modulations of the processing of line discontinuities under selective attention conditions?

    Science.gov (United States)

    Giersch, Anne; Fahle, Manfred

    2002-01-01

    We examined whether the processing of discontinuities involved in figure-ground segmentation, like line ends, can be modulated under selective attention conditions. Subjects decided whether a gap in collinear or parallel lines was located to the right or left. Two stimuli were displayed in immediate succession. When the gaps were on the same side, reaction times (RTs) for the second stimulus increased when collinear lines followed parallel lines, or the reverse, but only when the two stimuli shared the same orientation and location. The effect did not depend on the global form of the stimuli or on the relative orientation of the gaps. A frame drawn around collinear elements affected the results, suggesting a crucial role of the "amodal" orthogonal lines produced when line ends are aligned. Including several gaps in the first stimulus also eliminated RT variations. By contrast, RT variations remained stable across several experimental blocks and were significant for interstimulus intervals from 50 to 600 msec between the two stimuli. These results are interpreted in terms of a modulation of the processing of line ends or the production of amodal lines, arising when attention is selectively drawn to a gap.

  3. Solving portfolio selection problems with minimum transaction lots based on conditional-value-at-risk

    Science.gov (United States)

    Setiawan, E. P.; Rosadi, D.

    2017-01-01

    Portfolio selection problems conventionally means ‘minimizing the risk, given the certain level of returns’ from some financial assets. This problem is frequently solved with quadratic or linear programming methods, depending on the risk measure that used in the objective function. However, the solutions obtained by these method are in real numbers, which may give some problem in real application because each asset usually has its minimum transaction lots. In the classical approach considering minimum transaction lots were developed based on linear Mean Absolute Deviation (MAD), variance (like Markowitz’s model), and semi-variance as risk measure. In this paper we investigated the portfolio selection methods with minimum transaction lots with conditional value at risk (CVaR) as risk measure. The mean-CVaR methodology only involves the part of the tail of the distribution that contributed to high losses. This approach looks better when we work with non-symmetric return probability distribution. Solution of this method can be found with Genetic Algorithm (GA) methods. We provide real examples using stocks from Indonesia stocks market.

  4. Dress Nicer = Know More? Young Children's Knowledge Attribution and Selective Learning Based on How Others Dress.

    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.

  5. 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.

  6. [Multilingualism and child psychiatry: on differential diagnoses of language disorder, specific learning disorder, and selective mutism].

    Science.gov (United States)

    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.

  7. Observation of melting conditions in selective laser melting of metals (SLM)

    Science.gov (United States)

    Thombansen, U.; Abels, Peter

    2016-03-01

    Process observation in 3D printing of metals currently is one of the central challenges. Many companies strive to employ this additive manufacturing process in their production chains in order to gain competitive advantages through added flexibility in product design and embedded features. The new degrees of freedom are accompanied with the challenge to manufacture every detail of the product to the predefined specifications. Products with filigree internal structures for example require a perfect build to deliver the performance that was designed into these structures. Melting conditions determine properties such as grain structure and density of the finished part before it is sent to post processing steps. Monitoring of such melting conditions is still a challenge where the use of photodiodes, pyrometry and camera systems contribute to an overall picture that might identify errors or deviations during the build process. Additional considerations must be made to decide if these sensors are applied coaxially or from a lateral perspective. Furthermore, setting parameters of focal plane array (FPA) sensors are discussed and events that are seen in the machine vision image are compared against the pyrometry data. The resume of the experiments suggests the application of multiple sensors to the selective laser melting process (SLM) as they jointly contribute to an identification of events. These events need to be understood in order to establish cause effect relationships in the future.

  8. Thermal Conditions in the City of Poznań (Poland during Selected Heat Waves

    Directory of Open Access Journals (Sweden)

    Marek Półrolniczak

    2018-01-01

    Full Text Available The aim of the study was to characterise the occurrence of hot days and heat waves in Poznań in the 1966–2015 period, as well as to describe the thermal conditions in the city during selected heat waves between 2008 and 2015. The basis of the study was the daily maximum and minimum air temperature values for Poznań–Ławica station from 1966–2015 and the daily values of air temperature from eight measuring points located in the city in various land types from 2008 to 2015. A hot day was defined as a day with Tmax above the 95th annual percentile (from 1966 to 2015, while a heat wave was assumed to be at least five consecutive hot days. The research study conducted shows the increase of Tmax, number of hot days and frequency of heat waves in Poznań over the last 50 years. Across the area of the city (differentiation of urban area types according to Urban Atlas 2012, there was a great diversity of thermal conditions during the heat waves analysed.

  9. Selection of hydrothermal pre-treatment conditions of waste sludge destruction using multicriteria decision-making.

    Science.gov (United States)

    Al-Shiekh Khalil, Wael; Shanableh, Abdullah; Rigby, Portia; Kokot, Serge

    2005-04-01

    The effectiveness of hydrothermal treatment for the destruction of the organic content of sludge waste was investigated. The sludge sampled in this study contained approximately 2% solids. The experimental program consisted of hydrothermal treatment experiments conducted in a batch reactor at temperatures between 100 and 250 degrees C, with the addition of an oxidant (hydrogen peroxide) in the range of 0-150% with reference to TCOD, and reaction times of up to 60 min. The results suggested that the availability of oxidant, reaction temperature and reaction time were the determining factors for COD removal. A significant fraction of the COD remaining after treatment consisted of the dissolved COD. The results confirmed that hydrothermal treatment proceeds through hydrolysis resulting in the production of dissolved organic products followed by COD removal through oxidation. Two MCDM chemometrics methods, PROMETHEE and GAIA, were applied to process the large data matrix so as to facilitate the selection of the most suitable hydrothermal conditions for sludge destruction. Two possible scenarios were produced from this analysis-one depended on the use of high temperatures and no oxidant, while the second offered a choice of compromise solutions at lower temperatures but with the use of at least some oxidant. Thus, for the final choice of operating conditions, the decision maker needs local knowledge of the costs and available infrastructure. In principle, such information could be added as further criteria to the data matrix and new rankings obtained.

  10. Extreme Hypoxic Conditions Induce Selective Molecular Responses and Metabolic Reset in Detached Apple Fruit

    Science.gov (United States)

    Cukrov, Dubravka; Zermiani, Monica; Brizzolara, Stefano; Cestaro, Alessandro; Licausi, Francesco; Luchinat, Claudio; Santucci, Claudio; Tenori, Leonardo; Van Veen, Hans; Zuccolo, Andrea; Ruperti, Benedetto; Tonutti, Pietro

    2016-01-01

    The ripening physiology of detached fruit is altered by low oxygen conditions with profound effects on quality parameters. To study hypoxia-related processes and regulatory mechanisms, apple (Malus domestica, cv Granny Smith) fruit, harvested at commercial ripening, were kept at 1°C under normoxic (control) and hypoxic (0.4 and 0.8 kPa oxygen) conditions for up to 60 days. NMR analyses of cortex tissue identified eight metabolites showing significantly different accumulations between samples, with ethanol and alanine displaying the most pronounced difference between hypoxic and normoxic treatments. A rapid up-regulation of alcohol dehydrogenase and pyruvate-related metabolism (lactate dehydrogenase, pyruvate decarboxylase, alanine aminotransferase) gene expression was detected under both hypoxic conditions with a more pronounced effect induced by the lowest (0.4 kPa) oxygen concentration. Both hypoxic conditions negatively affected ACC synthase and ACC oxidase transcript accumulation. Analysis of RNA-seq data of samples collected after 24 days of hypoxic treatment identified more than 1000 genes differentially expressed when comparing 0.4 vs. 0.8 kPa oxygen concentration samples. Genes involved in cell-wall, minor and major CHO, amino acid and secondary metabolisms, fermentation and glycolysis as well as genes involved in transport, defense responses, and oxidation-reduction appeared to be selectively affected by treatments. The lowest oxygen concentration induced a higher expression of transcription factors belonging to AUX/IAA, WRKY, HB, Zinc-finger families, while MADS box family genes were more expressed when apples were kept under 0.8 kPa oxygen. Out of the eight group VII ERF members present in apple genome, two genes showed a rapid up-regulation under hypoxia, and western blot analysis showed that apple MdRAP2.12 proteins were differentially accumulated in normoxic and hypoxic samples, with the highest level reached under 0.4 kPa oxygen. These data suggest

  11. Feature selection and multi-kernel learning for sparse representation on a manifold

    KAUST Repository

    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.

  12. Feature selection and multi-kernel learning for sparse representation on a manifold.

    Science.gov (United States)

    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.

  13. An improved segmentation-based HMM learning method for Condition-based Maintenance

    International Nuclear Information System (INIS)

    Liu, T; Lemeire, J; Cartella, F; Meganck, S

    2012-01-01

    In the domain of condition-based maintenance (CBM), persistence of machine states is a valid assumption. Based on this assumption, we present an improved Hidden Markov Model (HMM) learning algorithm for the assessment of equipment states. By a good estimation of initial parameters, more accurate learning can be achieved than by regular HMM learning methods which start with randomly chosen initial parameters. It is also better in avoiding getting trapped in local maxima. The data is segmented with a change-point analysis method which uses a combination of cumulative sum charts (CUSUM) and bootstrapping techniques. The method determines a confidence level that a state change happens. After the data is segmented, in order to label and combine the segments corresponding to the same states, a clustering technique is used based on a low-pass filter or root mean square (RMS) values of the features. The segments with their labelled hidden state are taken as 'evidence' to estimate the parameters of an HMM. Then, the estimated parameters are served as initial parameters for the traditional Baum-Welch (BW) learning algorithms, which are used to improve the parameters and train the model. Experiments on simulated and real data demonstrate that both performance and convergence speed is improved.

  14. Food approach conditioning and discrimination learning using sound cues in benthic sharks.

    Science.gov (United States)

    Vila Pouca, Catarina; Brown, Culum

    2018-07-01

    The marine environment is filled with biotic and abiotic sounds. Some of these sounds predict important events that influence fitness while others are unimportant. Individuals can learn specific sound cues and 'soundscapes' and use them for vital activities such as foraging, predator avoidance, communication and orientation. Most research with sounds in elasmobranchs has focused on hearing thresholds and attractiveness to sound sources, but very little is known about their abilities to learn about sounds, especially in benthic species. Here we investigated if juvenile Port Jackson sharks could learn to associate a musical stimulus with a food reward, discriminate between two distinct musical stimuli, and whether individual personality traits were linked to cognitive performance. Five out of eight sharks were successfully conditioned to associate a jazz song with a food reward delivered in a specific corner of the tank. We observed repeatable individual differences in activity and boldness in all eight sharks, but these personality traits were not linked to the learning performance assays we examined. These sharks were later trained in a discrimination task, where they had to distinguish between the same jazz and a novel classical music song, and swim to opposite corners of the tank according to the stimulus played. The sharks' performance to the jazz stimulus declined to chance levels in the discrimination task. Interestingly, some sharks developed a strong side bias to the right, which in some cases was not the correct side for the jazz stimulus.

  15. A Selective Role for Dopamine in Learning to Maximize Reward But Not to Minimize Effort: Evidence from Patients with Parkinson's Disease.

    Science.gov (United States)

    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

  16. Staged Inference using Conditional Deep Learning for energy efficient real-time smart diagnosis.

    Science.gov (United States)

    Parsa, Maryam; Panda, Priyadarshini; Sen, Shreyas; Roy, Kaushik

    2017-07-01

    Recent progress in biosensor technology and wearable devices has created a formidable opportunity for remote healthcare monitoring systems as well as real-time diagnosis and disease prevention. The use of data mining techniques is indispensable for analysis of the large pool of data generated by the wearable devices. Deep learning is among the promising methods for analyzing such data for healthcare applications and disease diagnosis. However, the conventional deep neural networks are computationally intensive and it is impractical to use them in real-time diagnosis with low-powered on-body devices. We propose Staged Inference using Conditional Deep Learning (SICDL), as an energy efficient approach for creating healthcare monitoring systems. For smart diagnostics, we observe that all diagnoses are not equally challenging. The proposed approach thus decomposes the diagnoses into preliminary analysis (such as healthy vs unhealthy) and detailed analysis (such as identifying the specific type of cardio disease). The preliminary diagnosis is conducted real-time with a low complexity neural network realized on the resource-constrained on-body device. The detailed diagnosis requires a larger network that is implemented remotely in cloud and is conditionally activated only for detailed diagnosis (unhealthy individuals). We evaluated the proposed approach using available physiological sensor data from Physionet databases, and achieved 38% energy reduction in comparison to the conventional deep learning approach.

  17. Formation of imines by selective gold-catalysed aerobic oxidative coupling of alcohols and amines under ambient conditions

    DEFF Research Database (Denmark)

    Kegnæs, Søren; Mielby, Jerrik Jørgen; Mentzel, Uffe Vie

    2010-01-01

    with excellent selectivity (above 98%) at moderate conversion under optimized conditions. The effect of catalytic amounts of different bases was studied, along with reaction temperature and time. Utilisation of a selective catalyst system that uses dioxygen as an oxidant and only produces water as by...

  18. Learning an operant conditioning task differentially induces gliogenesis in the medial prefrontal cortex and neurogenesis in the hippocampus.

    Directory of Open Access Journals (Sweden)

    Maximiliano Rapanelli

    Full Text Available Circuit modification associated with learning and memory involves multiple events, including the addition and remotion of newborn cells trough adulthood. Adult neurogenesis and gliogenesis were mainly described in models of voluntary exercise, enriched environments, spatial learning and memory task; nevertheless, it is unknown whether it is a common mechanism among different learning paradigms, like reward dependent tasks. Therefore, we evaluated cell proliferation, neurogenesis, astrogliogenesis, survival and neuronal maturation in the medial prefrontal cortex (mPFC and the hippocampus (HIPP during learning an operant conditioning task. This was performed by using endogenous markers of cell proliferation, and a bromodeoxiuridine (BrdU injection schedule in two different phases of learning. Learning an operant conditioning is divided in two phases: a first phase when animals were considered incompletely trained (IT, animals that were learning the task when they performed between 50% and 65% of the responses, and a second phase when animals were considered trained (Tr, animals that completely learned the task when they reached 100% of the responses with a latency time lower than 5 seconds. We found that learning an operant conditioning task promoted cell proliferation in both phases of learning in the mPFC and HIPP. Additionally, the results presented showed that astrogliogenesis was induced in the medial prefrontal cortex (mPFC in both phases, however, the first phase promoted survival of these new born astrocytes. On the other hand, an increased number of new born immature neurons was observed in the HIPP only in the first phase of learning, whereas, decreased values were observed in the second phase. Finally, we found that neuronal maturation was induced only during the first phase. This study shows for the first time that learning a reward-dependent task, like the operant conditioning, promotes neurogenesis, astrogliogenesis, survival and

  19. Visual perceptual learning by operant conditioning training follows rules of contingency

    Science.gov (United States)

    Kim, Dongho; Seitz, Aaron R; Watanabe, Takeo

    2015-01-01

    Visual perceptual learning (VPL) can occur as a result of a repetitive stimulus-reward pairing in the absence of any task. This suggests that rules that guide Conditioning, such as stimulus-reward contingency (e.g. that stimulus predicts the likelihood of reward), may also guide the formation of VPL. To address this question, we trained subjects with an operant conditioning task in which there were contingencies between the response to one of three orientations and the presence of reward. Results showed that VPL only occurred for positive contingencies, but not for neutral or negative contingencies. These results suggest that the formation of VPL is influenced by similar rules that guide the process of Conditioning. PMID:26028984

  20. Visual perceptual learning by operant conditioning training follows rules of contingency.

    Science.gov (United States)

    Kim, Dongho; Seitz, Aaron R; Watanabe, Takeo

    2015-01-01

    Visual perceptual learning (VPL) can occur as a result of a repetitive stimulus-reward pairing in the absence of any task. This suggests that rules that guide Conditioning, such as stimulus-reward contingency (e.g. that stimulus predicts the likelihood of reward), may also guide the formation of VPL. To address this question, we trained subjects with an operant conditioning task in which there were contingencies between the response to one of three orientations and the presence of reward. Results showed that VPL only occurred for positive contingencies, but not for neutral or negative contingencies. These results suggest that the formation of VPL is influenced by similar rules that guide the process of Conditioning.

  1. Selection of appropriate conditioning matrices for the safe disposal of radioactive waste

    International Nuclear Information System (INIS)

    Vance, E.R.

    2002-01-01

    The selection of appropriate solid conditioning matrices or wasteforms for the safe disposal of radioactive waste is dictated by many factors. The overriding issue is that the matrix incorporating the radionuclides, together with a set of engineered barriers in a near-surface or deep geological repository, should prevent significant groundwater transport of radionuclides to the biosphere. For high-level waste (HLW) from nuclear fuel reprocessing, the favored matrices are glasses, ceramics and glass-ceramics. Borosilicate glasses are presently being used in some countries, but there are strong scientific arguments why ceramics based on assemblages of natural minerals are advantageous for HLW. Much research has been carried out in the last 40 years around the world, and different matrices are more suitable than others for a given waste composition. However a major stumbling block for HLW immobilisation is the mall number of approved geological repositories for such matrices. The most appropriate matrices for Intermediate and low-level wastes are contentious and the selection criteria are not very well defined. The candidate matrices for these latter wastes are cements, bitumen, geopolymers, glasses, glass-ceramics and ceramics. After discussing the pros and cons of various candidate matrices for given kinds of radioactive wastes, the SYNROC research program at ANSTO will be briefly surveyed. Some of the potential applications of this work using a variety of SYNROC derivatives will be given. Finally the basic research program at ANSTO on radioactive waste immobilisation will be summarised. This comprises mainly work on solid state chemistry to understand ionic valences and co-ordinations for the chemical design of wasteforms, aqueous durability to study the pH and temperature dependence of solid-water reactions, radiation damage effects on structure and solid-water reactions. (Author)

  2. Capability of multiple selection criteria to evaluate contrasting spring wheat germplasms under arid conditions

    International Nuclear Information System (INIS)

    Al-Suhaibani, N. A.; SALAH, E.; El-Hendawy, S. E.; Al-Gaadi, K.; Rehman, S. U.

    2015-01-01

    Selection criteria that would evaluate a large number of germplasm in a rapid and non-destructive manner would be considered advantageous in plant breeding programs. Trade-off between traditional and non-destructive screening criteria in evaluating 90 wheat accessions under water shortage was tested using multivariate statistical techniques. Only three irrigations during the growing cycle of germplasm were applied with the amount of water totalling 2550 m /sup 3/ ha /sup -1/. Sequential path analysis identified one traditional trait (grain weight per plant) and two non-destructive traits (leaf area index and stomatal conductance) as important first-order traits that influenced final grain yield. The three traits, taken together, explained 96.8 percentage of the total variation in grain yield. Total dry weight per plant, green leaf area per plant, harvest index, grain number per plant, leaf water content and canopy temperature were identified as important second-order traits that influenced grain yield. Although canopy temperature was ranked as a second-order trait, it explained 64.4 percentage of the total variation in stomatal conductance. Approximately 78.0 percentage of the total variation in grain weight or leaf area index was explained by the leaf water content (66.2 percentage) and total dry weight (11.5 percentage). The 90 examined spring wheat germplasms were grouped into five clusters based on all agro-physiological traits using the centroid linkage method. The tested wheat germplasm that produce high grain yield under water shortage were characterised by good performance of certain rapid, easy and non-destructive physiological traits such as high leaf area index, high stomatal conductance and low canopy temperature. Therefore, these three traits could be used in combination as quick and easy screening criteria to select suitable genotypes for water-limiting conditions. (author)

  3. 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.

  4. Gene selection and classification for cancer microarray data based on machine learning and similarity measures

    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.

  5. Multiatlas whole heart segmentation of CT data using conditional entropy for atlas ranking and selection

    Energy Technology Data Exchange (ETDEWEB)

    Zhuang, Xiahai, E-mail: zhuangxiahai@sjtu.edu.cn; Qian, Xiaohua [SJTU-CU International Cooperative Research Center, Department of Engineering Mechanics, School of Naval Architecture Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240 (China); Bai, Wenjia; Shi, Wenzhe; Rueckert, Daniel [Biomedical Image Analysis Group, Department of Computing, Imperial College London, 180 Queens Gate, London SW7 2AZ (United Kingdom); Song, Jingjing; Zhan, Songhua [Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai 201203 (China); Lian, Yanyun [Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai 201210 (China)

    2015-07-15

    Purpose: Cardiac computed tomography (CT) is widely used in clinical diagnosis of cardiovascular diseases. Whole heart segmentation (WHS) plays a vital role in developing new clinical applications of cardiac CT. However, the shape and appearance of the heart can vary greatly across different scans, making the automatic segmentation particularly challenging. The objective of this work is to develop and evaluate a multiatlas segmentation (MAS) scheme using a new atlas ranking and selection algorithm for automatic WHS of CT data. Research on different MAS strategies and their influence on WHS performance are limited. This work provides a detailed comparison study evaluating the impacts of label fusion, atlas ranking, and sizes of the atlas database on the segmentation performance. Methods: Atlases in a database were registered to the target image using a hierarchical registration scheme specifically designed for cardiac images. A subset of the atlases were selected for label fusion, according to the authors’ proposed atlas ranking criterion which evaluated the performance of each atlas by computing the conditional entropy of the target image given the propagated atlas labeling. Joint label fusion was used to combine multiple label estimates to obtain the final segmentation. The authors used 30 clinical cardiac CT angiography (CTA) images to evaluate the proposed MAS scheme and to investigate different segmentation strategies. Results: The mean WHS Dice score of the proposed MAS method was 0.918 ± 0.021, and the mean runtime for one case was 13.2 min on a workstation. This MAS scheme using joint label fusion generated significantly better Dice scores than the other label fusion strategies, including majority voting (0.901 ± 0.276, p < 0.01), locally weighted voting (0.905 ± 0.0247, p < 0.01), and probabilistic patch-based fusion (0.909 ± 0.0249, p < 0.01). In the atlas ranking study, the proposed criterion based on conditional entropy yielded a performance curve

  6. A new system to reduce formaldehyde levels improves safety conditions during gross veterinary anatomy learning.

    Science.gov (United States)

    Nacher, Víctor; Llombart, Cristina; Carretero, Ana; Navarro, Marc; Ysern, Pere; Calero, Sebastián; Fígols, Enric; Ruberte, Jesús

    2007-01-01

    Dissection is a very useful method of learning veterinary anatomy. However, formaldehyde, which is widely used to preserve cadavers, is an irritant, and it has recently been classified as a carcinogen. In 1997, the Instituto Nacional de Seguridad e Higiene en el Trabajo [National Institute of Workplace Security and Hygiene] found that the levels of formaldehyde in our dissection room were above the threshold limit values. Unfortunately, no optimal substitute for formaldehyde is currently available. Therefore, we designed a new ventilation system that combines slow propulsion of fresh air from above the dissection table and rapid aspiration of polluted air from the perimeter. Formaldehyde measurements performed in 2004, after the introduction of this new system into our dissection laboratory, showed a dramatic reduction (about tenfold, or 0.03 ppm). A suitable propelling/aspirating air system successfully reduces the concentration of formaldehyde in the dissection room, significantly improving safety conditions for students, instructors, and technical staff during gross anatomy learning.

  7. Periparturient Period in Terms of Body Condition Score and Selected Parameters of Hormonal Profiles

    Directory of Open Access Journals (Sweden)

    Vargová M.

    2016-03-01

    Full Text Available The majority of all diseases in dairy cows occur during the period from three weeks before parturition to three weeks after parturition, in the periparturient or transitional period. The objective of this study was to evaluate the dynamics of selected parameters of: the hormonal profiles, the body condition score (BCS and their interrelationships. The study was carried out on 15 dairy cows of the Slovak Pied Cattle, from three weeks before to nine weeks after parturition, which were divided into six groups. The concentrations of leptin during ante partum increased from 23.08 ± 10.58 ng.ml−1 to 26.80 ± 11.47 ng.ml−1, then gradually decreased (P > 0.05, and conversely, the concentrations of ghrelin before parturition were found to be decreasing and during the postpartal period, the concentrations increased, with the highest value of 35.94 ± 16.85 pg.ml−1. In the case of insulin, we found the opposite tendency of ghrelin. We observed significantly higher values of BCS in dry cows than in cows after parturition (P < 0.001. Comparing the BCS and the parameter of the hormonal profiles, we found both positive and negative correlations: leptin and ghrelin (r = −0.235, P < 0.05, and BCS and insulin (r = 0.232, P < 0.05, and BCS and leptin (r = 0.360, P < 0.001. The interrelationships between the hormones and the body condition score, provided evidence that the variations in concentrations of leptin, ghrelin and insulin were related to variations in the BCS.

  8. Information system for selection of conditions and equipment for the cultivation of mammalian cells

    Directory of Open Access Journals (Sweden)

    D. R. Batyrgazieva

    2017-01-01

    Full Text Available The use of mammals cells and their products wide application, so the actual problem is a creation of an information system in the field of their cultivation for the organizing and structuring of information on process experimental data. This work is devoted the analysis of mammalian cell cultivation. The main technologies of cell cultivation, necessary equipment and matrices are considered. The main stages of database design and information system is described. The justification of software products are provided and the results of the database and information system implementation are done. The detailed description of all modules of the system, as well as a comparative analysis of the results of the search are in the system to verify correct operation of the system. The scientific and practical significance of the work lies in the fact that the effective tool for presenting knowledge and data for search by specific parameters is required. The convenience of the system is that it is not necessary to address in various data sources to get and conditions of cultivation of mammalian cells, it has already been collected and structured according to parameters. With help of the system, it is possible to select conditions for the cultivation of mammalian cells at the stage of scientific researches that will significantly reduce the time and cost of work, also to rank of recommended technological and hardware solutions. The system has a functional completeness, i.e. in a specific subject area, it ensures the fulfillment of user's requirements, and allows to accumulate and process information.

  9. 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.

  10. The Effect of Selected Conditions in a Thermoforming Process on Wall Thickness Variations

    Directory of Open Access Journals (Sweden)

    Emil Sasimowski

    2017-12-01

    Full Text Available The paper reports the results of a study on the effect of selected conditions in a thermoforming process for thin polystyrene sheet by vacuum assisted drape forming on the wall thickness non-uniformity of finished parts. The investigation was performed using Statistica’s DOE module for three variables: temperatures in the external and internal zones of the heater as well as heating time of the plastic sheet. The results demonstrate that the wall thickness in the finished parts at the measuring points is primarily affected by the heating time and the temperature in the internal zone of the heater, while the temperature in the external zone only affects some regions of the finished part. The results demonstrate that a short heating time and hence a lower temperature of the plastic sheet lead to a more uniform deformation of both the bottom and the side walls of the finished part, and as a consequence, to smaller variations in the wall thickness. The shortening of the heating time is however limited by the necessity of accurate reproduction of the shape of the finished part.

  11. Decorative values of selected cultivars of climbing roses (Rosa L. with regard to thermal conditions

    Directory of Open Access Journals (Sweden)

    Zofia Włodarczyk

    2012-12-01

    Full Text Available In the years 2004-2006 in Kraków, phenological observations of climbing roses were conducted in order to determine the length and dates of their flowering period. The diameters of their flowers were also compared. Eight flowering repeating cultivars were selected for the experiment: 'Climbing Souvenir de la Malmaison', 'Dortmund', 'Golden Showers', 'Goldstern', 'New Dawn', 'Parade', 'Sympathie' and 'White New Dawn'. During the studies, the shrub roses were not artificially watered in order to create conditions similar to those prevailing in public green areas. It was observed that irrespective of the air temperature pattern in a given year, the studied cultivars did not bloom before 15 June. In 2006 high temperatures (above 20oC, which continued throughout the whole flowering period, caused its shortening, and the interval between the first and the next flowering in the season lasted longer than in the previous years. In the years 2004-2006, the cultivar 'New Dawn' bloomed the longest. In 2005 the studied cultivars produced larger flowers than the next year. The cultivars 'Dortmund' and 'White New Dawn' were characterised by the smallest diameter of flowers, whereas 'Climbing Souvenir de la Malmaison', 'Golden Showers' and 'Parade' were marked by the largest diameter.

  12. Statistical Learning Framework with Adaptive Retraining for Condition-Based Maintenance

    International Nuclear Information System (INIS)

    An, Sang Ha; Chang, Soon Heung; Heo, Gyun Young; Seo, Ho Joon; Kim, Su Young

    2009-01-01

    As systems become more complex and more critical in our daily lives, the need for the maintenance based on the reliable monitoring and diagnosis has become more apparent. However, in reality, the general opinion has been that 'maintenance is a necessary evil' or 'nothing can be done to improve maintenance costs'. Perhaps these were true statements twenty years ago when many of the diagnostic technologies were not fully developed. The developments of microprocessor or computer based instrumentation that can be used to monitor the operating condition of plant equipment, machinery and systems have provided the means to manage the maintenance operation. They have provided the means to reduce or eliminate unnecessary repairs, prevent catastrophic machine failures and reduce the negative impact of the maintenance operation on the profitability of manufacturing and production plants. Condition-based maintenance (CBM) techniques help determine the condition of in-service equipment in order to predict when maintenance should be performed. Most of the statistical learning techniques are only valid as long as the physics of a system does not change. If any significant change such as the replacement of a component or equipment occurs in the system, the statistical learning model should be re-trained or re-developed to adapt the new system. In this research, authors will propose a statistical learning framework which can be applicable for various CBMs, and the concept of the adaptive retraining technique will be described to support the execution of the framework so that the monitoring system does not need to be re-developed or re-trained even though there are any significant changes in the system or component

  13. Selected road condition, vehicle and freight considerations in pavement life cycle assessment

    CSIR Research Space (South Africa)

    Steyn, WJ vdM

    2014-10-01

    Full Text Available road condition data from two corridors were collected and analyzed to determine the effect of the current road condition and potential changes in these road conditions on the economic and environmental impacts of the situation. Existing Vehicle...

  14. Selective Attention Enhances Beta-Band Cortical Oscillation to Speech under “Cocktail-Party” Listening Conditions

    Science.gov (United States)

    Gao, Yayue; Wang, Qian; Ding, Yu; Wang, Changming; Li, Haifeng; Wu, Xihong; Qu, Tianshu; Li, Liang

    2017-01-01

    Human listeners are able to selectively attend to target speech in a noisy environment with multiple-people talking. Using recordings of scalp electroencephalogram (EEG), this study investigated how selective attention facilitates the cortical representation of target speech under a simulated “cocktail-party” listening condition with speech-on-speech masking. The result shows that the cortical representation of target-speech signals under the multiple-people talking condition was specifically improved by selective attention relative to the non-selective-attention listening condition, and the beta-band activity was most strongly modulated by selective attention. Moreover, measured with the Granger Causality value, selective attention to the single target speech in the mixed-speech complex enhanced the following four causal connectivities for the beta-band oscillation: the ones (1) from site FT7 to the right motor area, (2) from the left frontal area to the right motor area, (3) from the central frontal area to the right motor area, and (4) from the central frontal area to the right frontal area. However, the selective-attention-induced change in beta-band causal connectivity from the central frontal area to the right motor area, but not other beta-band causal connectivities, was significantly correlated with the selective-attention-induced change in the cortical beta-band representation of target speech. These findings suggest that under the “cocktail-party” listening condition, the beta-band oscillation in EEGs to target speech is specifically facilitated by selective attention to the target speech that is embedded in the mixed-speech complex. The selective attention-induced unmasking of target speech may be associated with the improved beta-band functional connectivity from the central frontal area to the right motor area, suggesting a top-down attentional modulation of the speech-motor process. PMID:28239344

  15. From brain synapses to systems for learning and memory: Object recognition, spatial navigation, timed conditioning, and movement control.

    Science.gov (United States)

    Grossberg, Stephen

    2015-09-24

    This article provides an overview of neural models of synaptic learning and memory whose expression in adaptive behavior depends critically on the circuits and systems in which the synapses are embedded. It reviews Adaptive Resonance Theory, or ART, models that use excitatory matching and match-based learning to achieve fast category learning and whose learned memories are dynamically stabilized by top-down expectations, attentional focusing, and memory search. ART clarifies mechanistic relationships between consciousness, learning, expectation, attention, resonance, and synchrony. ART models are embedded in ARTSCAN architectures that unify processes of invariant object category learning, recognition, spatial and object attention, predictive remapping, and eye movement search, and that clarify how conscious object vision and recognition may fail during perceptual crowding and parietal neglect. The generality of learned categories depends upon a vigilance process that is regulated by acetylcholine via the nucleus basalis. Vigilance can get stuck at too high or too low values, thereby causing learning problems in autism and medial temporal amnesia. Similar synaptic learning laws support qualitatively different behaviors: Invariant object category learning in the inferotemporal cortex; learning of grid cells and place cells in the entorhinal and hippocampal cortices during spatial navigation; and learning of time cells in the entorhinal-hippocampal system during adaptively timed conditioning, including trace conditioning. Spatial and temporal processes through the medial and lateral entorhinal-hippocampal system seem to be carried out with homologous circuit designs. Variations of a shared laminar neocortical circuit design have modeled 3D vision, speech perception, and cognitive working memory and learning. A complementary kind of inhibitory matching and mismatch learning controls movement. This article is part of a Special Issue entitled SI: Brain and Memory

  16. Dutch care innovation units in elderly care: A qualitative study into students' perspectives and workplace conditions for learning.

    Science.gov (United States)

    Snoeren, Miranda; Volbeda, Patricia; Niessen, Theo J H; Abma, Tineke A

    2016-03-01

    To promote workplace learning for staff as well as students, a partnership was formed between a residential care organisation for older people and several nursing faculties in the Netherlands. This partnership took the form of two care innovation units; wards where qualified staff, students and nurse teachers collaborate to integrate care, education, innovation and research. In this article, the care innovation units as learning environments are studied from a student perspective to deepen understandings concerning the conditions that facilitate learning. A secondary analysis of focus groups, held with 216 nursing students over a period of five years, revealed that students are satisfied about the units' learning potential, which is formed by various inter-related and self-reinforcing affordances: co-constructive learning and working, challenging situations and activities, being given responsibility and independence, and supportive and recognisable learning structures. Time constraints had a negative impact on the units' learning potential. It is concluded that the learning potential of the care innovation units was enhanced by realising certain conditions, like learning structures and activities. The learning potential was also influenced, however, by the non-controllable and dynamic interaction of various elements within the context. Suggestions for practice and further research are offered. Copyright © 2015 Elsevier Ltd. All rights reserved.

  17. Structural Conditions for Collaboration and Learning in Innovation Networks: Using an Innovation System Performance Lens to Analyse Agricultural Knowledge Systems

    NARCIS (Netherlands)

    Hermans, F.; Klerkx, L.W.A.; Roep, D.

    2015-01-01

    Purpose: We investigate how the structural conditions of eight different European agricultural innovation systems can facilitate or hinder collaboration and social learning in multidisciplinary innovation networks. Methodology: We have adapted the Innovation System Failure Matrix to investigate the

  18. The role of conditioning, learning and dopamine in sexual behavior: a narrative review of animal and human studies

    NARCIS (Netherlands)

    Brom, Mirte; Both, Stephanie; Laan, Ellen; Everaerd, Walter; Spinhoven, Philip

    2014-01-01

    Many theories of human sexual behavior assume that sexual stimuli obtain arousing properties through associative learning processes. It is widely accepted that classical conditioning contributes to the etiology of both normal and maladaptive human behaviors. Despite the hypothesized importance of

  19. The role of conditioning, learning and dopamine in sexual behavior : A narrative review of animal and human studies

    NARCIS (Netherlands)

    Brom, M.; Both, S.; Laan, E.; Everaerd, W.; Spinhoven, P.

    Many theories of human sexual behavior assume that sexual stimuli obtain arousing properties through associative learning processes. It is widely accepted that classical conditioning contributes to the etiology of both normal and maladaptive human behaviors. Despite the hypothesized importance of

  20. Learning-induced Dependence of Neuronal Activity in Primary Motor Cortex on Motor Task Condition.

    Science.gov (United States)

    Cai, X; Shimansky, Y; He, Jiping

    2005-01-01

    A brain-computer interface (BCI) system such as a cortically controlled robotic arm must have a capacity of adjusting its function to a specific environmental condition. We studied this capacity in non-human primates based on chronic multi-electrode recording from the primary motor cortex of a monkey during the animal's performance of a center-out 3D reaching task and adaptation to external force perturbations. The main condition-related feature of motor cortical activity observed before the onset of force perturbation was a phasic raise of activity immediately before the perturbation onset. This feature was observed during a series of perturbation trials, but were absent under no perturbations. After adaptation has been completed, it usually was taking the subject only one trial to recognize a change in the condition to switch the neuronal activity accordingly. These condition-dependent features of neuronal activity can be used by a BCI for recognizing a change in the environmental condition and making corresponding adjustments, which requires that the BCI-based control system possess such advanced properties of the neural motor control system as capacity to learn and adapt.

  1. The influence of stress conditions on the growth of selected lactic acid bacteria

    International Nuclear Information System (INIS)

    Bok, H.E.

    1985-01-01

    A study was undertaken to determine the effects of certain stress conditions on selected lactic acid bacteria. Where recontamination occurred, lactic acid bacteria was already the dominant bacterial group, with counts of higher than 10 6 /g in vacuum-packaged 'shelf stable' meat products after 1 week storage at 25 and 37 degrees Celsius respectively. Some of the isolates were capable of growing at a pH of 3,9. The minimum pH for growth of a specific culture was dependant on the type of acid that was used to lower the pH. Lactic and acetic acid had the highest inhibitory action. Hydrochloric and citric acid showed similar inhibitory effects, while the effects when using ascorbic acid or gluconic acid for lowering the pH were also fairly similar. Increase in the activity of certain lactic acid bacteria was noticed where the ratio of undissociated to dissociated citric acid in the medium was increased. After exceeding a concentration of 0,048 moles/l undissosiated citric acid in the medium, the activity of the majority of cultures was progressively inhibited. This phenomenon was also found with acetic acid for certain cultures. Selected lactic acid bacteria were resistant to an water activity (a (sub w)) of 0,94 in MRS broth, where NaCl or glycerol was used as a humectant. The minimum a (sub w) for growth was dependent on the type of humectant used. Concentrations of sodium benzoate and potassium sorbate were necessary to inhibit the majority of strains. The % inhibition by sodium benzoate and methyl paraben did not significantly change with a lowering in the pH of the growth medium. Except in the case of lactic acid, the different acids used to lower the pH of the medium did not have a significant effect on the % inhibition by the chemical preservatives. For the cocci, gamma D 10 values of between 0,82 and 1,29 kGy were recorded, whereas the lactobacilli were less resistant to gamma rays, with D 10 values of between 0,21 and 0,54 kGy

  2. Social makes smart: rearing conditions affect learning and social behaviour in jumping spiders.

    Science.gov (United States)

    Liedtke, J; Schneider, J M

    2017-11-01

    There is a long-standing debate as to whether social or physical environmental aspects drive the evolution and development of cognitive abilities. Surprisingly few studies make use of developmental plasticity to compare the effects of these two domains during development on behaviour later in life. Here, we present rearing effects on the development of learning abilities and social behaviour in the jumping spider Marpissa muscosa. These spiders are ideally suited for this purpose because they possess the ability to learn and can be reared in groups but also in isolation without added stress. This is a critical but rarely met requirement for experimentally varying the social environment to test its impact on cognition. We split broods of spiders and reared them either in a physically or in a socially enriched environment. A third group kept under completely deprived conditions served as a 'no-enrichment' control. We tested the spiders' learning abilities by using a modified T-maze. Social behaviour was investigated by confronting spiders with their own mirror image. Results show that spiders reared in groups outperform their conspecifics from the control, i.e. 'no-enrichment', group in both tasks. Physical enrichment did not lead to such an increased performance. We therefore tentatively suggest that growing up in contact with conspecifics induces the development of cognitive abilities in this species.

  3. From Reactionary to Responsive: Applying the Internal Environmental Scan Protocol to Lifelong Learning Strategic Planning and Operational Model Selection

    Science.gov (United States)

    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…

  4. Training self-assessment and task-selection skills: A cognitive approach to improving self-regulated learning

    NARCIS (Netherlands)

    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

  5. Altering spatial priority maps via statistical learning of target selection and distractor filtering.

    Science.gov (United States)

    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

  6. Gene selection for microarray data classification via subspace learning and manifold regularization.

    Science.gov (United States)

    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.

  7. Physiotherapy students' perspectives of online e-learning for interdisciplinary management of chronic health conditions: a qualitative study.

    Science.gov (United States)

    Gardner, Peter; Slater, Helen; Jordan, Joanne E; Fary, Robyn E; Chua, Jason; Briggs, Andrew M

    2016-02-16

    To qualitatively explore physiotherapy students' perceptions of online e-learning for chronic disease management using a previously developed, innovative and interactive, evidence-based, e-learning package: Rheumatoid Arthritis for Physiotherapists e-Learning (RAP-eL). Physiotherapy students participated in three focus groups in Perth, Western Australia. Purposive sampling was employed to ensure maximum heterogeneity across age, gender and educational background. To explore students' perspectives on the advantages and disadvantages of online e-learning, ways to enhance e-learning, and information/learning gaps in relation to interdisciplinary management of chronic health conditions, a semi-structured interview schedule was developed. Verbatim transcripts were analysed using inductive methods within a grounded theory approach to derive key themes. Twenty-three students (78 % female; 39 % with previous tertiary qualification) of mean (SD) age 23 (3.6) years participated. Students expressed a preference for a combination of both online e-learning and lecture-style learning formats for chronic disease management, citing flexibility to work at one's own pace and time, and access to comprehensive information as advantages of e-learning learning. Personal interaction and ability to clarify information immediately were considered advantages of lecture-style formats. Perceived knowledge gaps included practical application of interdisciplinary approaches to chronic disease management and developing and implementing physiotherapy management plans for people with chronic health conditions. Physiotherapy students preferred multi-modal and blended formats for learning about chronic disease management. This study highlights the need for further development of practically-oriented knowledge and skills related to interdisciplinary care for people with chronic conditions among physiotherapy students. While RAP-eL focuses on rheumatoid arthritis, the principles of learning apply to

  8. Speech perception in older listeners with normal hearing:conditions of time alteration, selective word stress, and length of sentences.

    Science.gov (United States)

    Cho, Soojin; Yu, Jyaehyoung; Chun, Hyungi; Seo, Hyekyung; Han, Woojae

    2014-04-01

    Deficits of the aging auditory system negatively affect older listeners in terms of speech communication, resulting in limitations to their social lives. To improve their perceptual skills, the goal of this study was to investigate the effects of time alteration, selective word stress, and varying sentence lengths on the speech perception of older listeners. Seventeen older people with normal hearing were tested for seven conditions of different time-altered sentences (i.e., ±60%, ±40%, ±20%, 0%), two conditions of selective word stress (i.e., no-stress and stress), and three different lengths of sentences (i.e., short, medium, and long) at the most comfortable level for individuals in quiet circumstances. As time compression increased, sentence perception scores decreased statistically. Compared to a natural (or no stress) condition, the selectively stressed words significantly improved the perceptual scores of these older listeners. Long sentences yielded the worst scores under all time-altered conditions. Interestingly, there was a noticeable positive effect for the selective word stress at the 20% time compression. This pattern of results suggests that a combination of time compression and selective word stress is more effective for understanding speech in older listeners than using the time-expanded condition only.

  9. ACTIVE LEARNING TO OVERCOME SAMPLE SELECTION BIAS: APPLICATION TO PHOTOMETRIC VARIABLE STAR CLASSIFICATION

    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.

  10. ACTIVE LEARNING TO OVERCOME SAMPLE SELECTION BIAS: APPLICATION TO PHOTOMETRIC VARIABLE STAR CLASSIFICATION

    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.

  11. Active Learning to Overcome Sample Selection Bias: Application to Photometric Variable Star Classification

    Science.gov (United States)

    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.

  12. Comparison of in-hospital versus 30-day mortality assessments for selected medical conditions.

    Science.gov (United States)

    Borzecki, Ann M; Christiansen, Cindy L; Chew, Priscilla; Loveland, Susan; Rosen, Amy K

    2010-12-01

    In-hospital mortality measures such as the Agency for Healthcare Research and Quality (AHRQ) Inpatient Quality Indicators (IQIs) are easily derived using hospital discharge abstracts and publicly available software. However, hospital assessments based on a 30-day postadmission interval might be more accurate given potential differences in facility discharge practices. To compare in-hospital and 30-day mortality rates for 6 medical conditions using the AHRQ IQI software. We used IQI software (v3.1) and 2004-2007 Veterans Health Administration (VA) discharge and Vital Status files to derive 4-year facility-level in-hospital and 30-day observed mortality rates and observed/expected ratios (O/Es) for admissions with a principal diagnosis of acute myocardial infarction, congestive heart failure, stroke, gastrointestinal hemorrhage, hip fracture, and pneumonia. We standardized software-calculated O/Es to the VA population and compared O/Es and outlier status across sites using correlation, observed agreement, and kappas. Of 119 facilities, in-hospital versus 30-day mortality O/E correlations were generally high (median: r = 0.78; range: 0.31-0.86). Examining outlier status, observed agreement was high (median: 84.7%, 80.7%-89.1%). Kappas showed at least moderate agreement (k > 0.40) for all indicators except stroke and hip fracture (k ≤ 0.22). Across indicators, few sites changed from a high to nonoutlier or low outlier, or vice versa (median: 10, range: 7-13). The AHRQ IQI software can be easily adapted to generate 30-day mortality rates. Although 30-day mortality has better face validity as a hospital performance measure than in-hospital mortality, site assessments were similar despite the definition used. Thus, the measure selected for internal benchmarking should primarily depend on the healthcare system's data linkage capabilities.

  13. Selective visual attention and motivation: the consequences of value learning in an attentional blink task.

    Science.gov (United States)

    Raymond, Jane E; O'Brien, Jennifer L

    2009-08-01

    Learning to associate the probability and value of behavioral outcomes with specific stimuli (value learning) is essential for rational decision making. However, in demanding cognitive conditions, access to learned values might be constrained by limited attentional capacity. We measured recognition of briefly presented faces seen previously in a value-learning task involving monetary wins and losses; the recognition task was performed both with and without constraints on available attention. Regardless of available attention, recognition was substantially enhanced for motivationally salient stimuli (i.e., stimuli highly predictive of outcomes), compared with equally familiar stimuli that had weak or no motivational salience, and this effect was found regardless of valence (win or loss). However, when attention was constrained (because stimuli were presented during an attentional blink, AB), valence determined recognition; win-associated faces showed no AB, but all other faces showed large ABs. Motivational salience acts independently of attention to modulate simple perceptual decisions, but when attention is limited, visual processing is biased in favor of reward-associated stimuli.

  14. Parents' learning needs and preferences when sharing management of their child's long-term/chronic condition: A systematic review.

    Science.gov (United States)

    Nightingale, Ruth; Friedl, Simone; Swallow, Veronica

    2015-11-01

    This review aimed to (1) identify parents' learning needs and preferences when sharing the management of their child's long-term/chronic (long-term) condition and (2) inform healthcare professional support provided to parents across the trajectory. We conducted a literature search in seven health databases from 1990 to 2013. The quality of included studies was assessed using a critical appraisal tool developed for reviewing the strengths and weaknesses of qualitative, quantitative and mixed methods studies. Twenty-three studies met our criteria and were included in the review. Three themes emerged from synthesis of the included studies: (1) parents' learning needs and preferences (2) facilitators to parents' learning, and (3) barriers to parents' learning. Asking parents directly about their learning needs and preferences may be the most reliable way for healthcare professionals to ascertain how to support and promote individual parents' learning when sharing management of their child's long-term condition. With the current emphasis on parent-healthcare professional shared management of childhood long-term conditions, it is recommended that professionals base their assessment of parents' learning needs and preferences on identified barriers and facilitators to parental learning. This should optimise delivery of home-based care, thereby contributing to improved clinical outcomes for the child. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  15. Experience and Lessons Learned from Conditioning of Spent Sealed Sources in Singapore - 13107

    Energy Technology Data Exchange (ETDEWEB)

    Hong, Dae-Seok; Kang, Il-Sik; Jang, Kyung-Duk; Jang, Won-Hyuk [Korea Atomic Energy Research Institute, 1045 Daedeokdaero, Yuseong, Daejeon (Korea, Republic of); Hoo, Wee-Teck [National Environment Agency, 40 Scotts Road 228231 (Singapore)

    2013-07-01

    In 2010, IAEA requested KAERI (Korea Atomic Energy Research Institute) to support Singapore for conditioning spent sealed sources. Those that had been used for a lightning conductor, check source, or smoke detector, various sealed sources had been collected and stored by the NEA (National Environment Agency) in Singapore. Based on experiences for the conditioning of Ra-226 sources in some Asian countries since 2000, KAERI sent an expert team to Singapore for the safe management of spent sealed sources in 2011. As a result of the conditioning, about 575.21 mCi of Am-241, Ra-226, Co-60, and Sr-90 were safely conditioned in 3 concrete lining drums with the cooperation of the KAERI expert team, the IAEA supervisor, the NEA staff and local laborers in Singapore. Some lessons were learned during the operation: (1) preparations by a local authority are very helpful for an efficient operation, (2) a preliminary inspection by an expert team is helpful for the operation, (3) brief reports before and after daily operation are useful for communication, and (4) a training opportunity is required for the sustainability of the expert team. (authors)

  16. Corticostriatal circuit mechanisms of value-based action selection: Implementation of reinforcement learning algorithms and beyond.

    Science.gov (United States)

    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.

  17. Why do organizations not learn from incidents? Bottlenecks, causes and conditions for a failure to effectively learn

    DEFF Research Database (Denmark)

    Drupsteen, Linda; Hasle, Peter

    2014-01-01

    be studied.Difficulties were identified in multiple steps of the learning process, but most difficulties became visiblewhen planning actions, which is the phase that bridges the gap from incident investigation to actions forimprovement. The main causes for learning difficulties, which were identified...... learn. In sevenorganizations focus groups were held to discuss factors that according to employees contributed to thefailure to learn. By use of a model of the learning from incidents process, the steps, where difficulties forlearning arose, became visible, and the causes for these difficulties could...

  18. MDMA enhances hippocampal-dependent learning and memory under restrictive conditions, and modifies hippocampal spine density.

    Science.gov (United States)

    Abad, Sònia; Fole, Alberto; del Olmo, Nuria; Pubill, David; Pallàs, Mercè; Junyent, Fèlix; Camarasa, Jorge; Camins, Antonio; Escubedo, Elena

    2014-03-01

    Addictive drugs produce forms of structural plasticity in the nucleus accumbens and prefrontal cortex. The aim of this study was to investigate the impact of chronic MDMA exposure on pyramidal neurons in the CA1 region of hippocampus and drug-related spatial learning and memory changes. Adolescent rats were exposed to saline or MDMA in a regime that mimicked chronic administration. One week later, when acquisition or reference memory was evaluated in a standard Morris water maze (MWM), no differences were obtained between groups. However, MDMA-exposed animals performed better when the MWM was implemented under more difficult conditions. Animals of MDMA group were less anxious and were more prepared to take risks, as in the open field test they ventured more frequently into the central area. We have demonstrated that MDMA caused an increase in brain-derived neurotrophic factor (BDNF) expression. When spine density was evaluated, MDMA-treated rats presented a reduced density when compared with saline, but overall, training increased the total number of spines, concluding that in MDMA-group, training prevented a reduction in spine density or induced its recovery. This study provides support for the conclusion that binge administration of MDMA, known to be associated to neurotoxic damage of hippocampal serotonergic terminals, increases BDNF expression and stimulates synaptic plasticity when associated with training. In these conditions, adolescent rats perform better in a more difficult water maze task under restricted conditions of learning and memory. The effect on this task could be modulated by other behavioural changes provoked by MDMA.

  19. Self-regulated learning of important information under sequential and simultaneous encoding conditions.

    Science.gov (United States)

    Middlebrooks, Catherine D; Castel, Alan D

    2018-05-01

    Learners make a number of decisions when attempting to study efficiently: they must choose which information to study, for how long to study it, and whether to restudy it later. The current experiments examine whether documented impairments to self-regulated learning when studying information sequentially, as opposed to simultaneously, extend to the learning of and memory for valuable information. In Experiment 1, participants studied lists of words ranging in value from 1-10 points sequentially or simultaneously at a preset presentation rate; in Experiment 2, study was self-paced and participants could choose to restudy. Although participants prioritized high-value over low-value information, irrespective of presentation, those who studied the items simultaneously demonstrated superior value-based prioritization with respect to recall, study selections, and self-pacing. The results of the present experiments support the theory that devising, maintaining, and executing efficient study agendas is inherently different under sequential formatting than simultaneous. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  20. Clustering Words to Match Conditions: An Algorithm for Stimuli Selection in Factorial Designs

    Science.gov (United States)

    Guasch, Marc; Haro, Juan; Boada, Roger

    2017-01-01

    With the increasing refinement of language processing models and the new discoveries about which variables can modulate these processes, stimuli selection for experiments with a factorial design is becoming a tough task. Selecting sets of words that differ in one variable, while matching these same words into dozens of other confounding variables…

  1. Automatic selection of atomic fingerprints and reference configurations for machine-learning potentials

    Science.gov (United States)

    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.

  2. Feature Selection with Conjunctions of Decision Stumps and Learning from Microarray Data.

    Science.gov (United States)

    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.

  3. Extending the Peak Bandwidth of Parameters for Softmax Selection in Reinforcement Learning.

    Science.gov (United States)

    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.

  4. Applications of machine-learning algorithms for infrared colour selection of Galactic Wolf-Rayet stars

    Science.gov (United States)

    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.

  5. The Toyota Production Systems fundamental nature at selected South African organisations A learning perspective

    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.

  6. Pareto Optimal Solutions for Network Defense Strategy Selection Simulator in Multi-Objective Reinforcement Learning

    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.

  7. Selective immunotoxic lesions of basal forebrain cholinergic cells: effects on learning and memory in rats.

    Science.gov (United States)

    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

  8. 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.

  9. Using Deep Learning for Targeted Data Selection, Improving Satellite Observation Utilization for Model Initialization

    Science.gov (United States)

    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.

  10. Bias correction for selecting the minimal-error classifier from many machine learning models.

    Science.gov (United States)

    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.

  11. Selected engagement factors and academic learning outcomes of undergraduate engineering students

    Science.gov (United States)

    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

  12. On selecting a sensitive region thickness of a silicon semiconductor detector for operation under counting conditions

    International Nuclear Information System (INIS)

    Pronkin, N.S.; Khakhalin, V.V.

    1972-01-01

    The paper discusses the selection of a thickness of a sensitive area of a silicon semiconductor detector, used in the count regime based on the signal to noise ratio and β-radiation registration efficiency. (author)

  13. An Analysis of Conditional Dependencies of Covariance Matrices for Economic Processes in Selected EU Countries

    Directory of Open Access Journals (Sweden)

    Janiga-Ćmiel Anna

    2016-12-01

    Full Text Available The paper looks at the issues related to the research on and assessment of the contagion effect. Based on several examinations of two selected EU countries, Poland paired with one of the EU member states; it presents the interaction between their economic development. A DCC-GARCH model constructed for the purpose of the study was used to generate a covariance matrix Ht, which enabled the calculation of correlation matrices Rt. The resulting variance vectors were used to present a linear correlation model on which a further analysis of the contagion effect was based. The aim of the study was to test a contagion effect among selected EU countries in the years 2000–2014. The transmission channel under study was the GDP of a selected country. The empirical studies confirmed the existence of the contagion effect between the economic development of the Polish and selected EU economies.

  14. Learning Classification Models of Cognitive Conditions from Subtle Behaviors in the Digital Clock Drawing Test.

    Science.gov (United States)

    Souillard-Mandar, William; Davis, Randall; Rudin, Cynthia; Au, Rhoda; Libon, David J; Swenson, Rodney; Price, Catherine C; Lamar, Melissa; Penney, Dana L

    2016-03-01

    The Clock Drawing Test - a simple pencil and paper test - has been used for more than 50 years as a screening tool to differentiate normal individuals from those with cognitive impairment, and has proven useful in helping to diagnose cognitive dysfunction associated with neurological disorders such as Alzheimer's disease, Parkinson's disease, and other dementias and conditions. We have been administering the test using a digitizing ballpoint pen that reports its position with considerable spatial and temporal precision, making available far more detailed data about the subject's performance. Using pen stroke data from these drawings categorized by our software, we designed and computed a large collection of features, then explored the tradeoffs in performance and interpretability in classifiers built using a number of different subsets of these features and a variety of different machine learning techniques. We used traditional machine learning methods to build prediction models that achieve high accuracy. We operationalized widely used manual scoring systems so that we could use them as benchmarks for our models. We worked with clinicians to define guidelines for model interpretability, and constructed sparse linear models and rule lists designed to be as easy to use as scoring systems currently used by clinicians, but more accurate. While our models will require additional testing for validation, they offer the possibility of substantial improvement in detecting cognitive impairment earlier than currently possible, a development with considerable potential impact in practice.

  15. Joint Facial Action Unit Detection and Feature Fusion: A Multi-conditional Learning Approach.

    Science.gov (United States)

    Eleftheriadis, Stefanos; Rudovic, Ognjen; Pantic, Maja

    2016-10-05

    Automated analysis of facial expressions can benefit many domains, from marketing to clinical diagnosis of neurodevelopmental disorders. Facial expressions are typically encoded as a combination of facial muscle activations, i.e., action units. Depending on context, these action units co-occur in specific patterns, and rarely in isolation. Yet, most existing methods for automatic action unit detection fail to exploit dependencies among them, and the corresponding facial features. To address this, we propose a novel multi-conditional latent variable model for simultaneous fusion of facial features and joint action unit detection. Specifically, the proposed model performs feature fusion in a generative fashion via a low-dimensional shared subspace, while simultaneously performing action unit detection using a discriminative classification approach. We show that by combining the merits of both approaches, the proposed methodology outperforms existing purely discriminative/generative methods for the target task. To reduce the number of parameters, and avoid overfitting, a novel Bayesian learning approach based on Monte Carlo sampling is proposed, to integrate out the shared subspace. We validate the proposed method on posed and spontaneous data from three publicly available datasets (CK+, DISFA and Shoulder-pain), and show that both feature fusion and joint learning of action units leads to improved performance compared to the state-of-the-art methods for the task.

  16. Neuropsychological Test Selection for Cognitive Impairment Classification: A Machine Learning Approach

    Science.gov (United States)

    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

  17. Document page structure learning for fixed-layout e-books using conditional random fields

    Science.gov (United States)

    Tao, Xin; Tang, Zhi; Xu, Canhui

    2013-12-01

    In this paper, a model is proposed to learn logical structure of fixed-layout document pages by combining support vector machine (SVM) and conditional random fields (CRF). Features related to each logical label and their dependencies are extracted from various original Portable Document Format (PDF) attributes. Both local evidence and contextual dependencies are integrated in the proposed model so as to achieve better logical labeling performance. With the merits of SVM as local discriminative classifier and CRF modeling contextual correlations of adjacent fragments, it is capable of resolving the ambiguities of semantic labels. The experimental results show that CRF based models with both tree and chain graph structures outperform the SVM model with an increase of macro-averaged F1 by about 10%.

  18. The chemotherapeutic agent paclitaxel selectively impairs learning while sparing source memory and spatial memory.

    Science.gov (United States)

    Smith, Alexandra E; Slivicki, Richard A; Hohmann, Andrea G; Crystal, Jonathon D

    2017-03-01

    Chemotherapeutic agents are widely used to treat patients with systemic cancer. The efficacy of these therapies is undermined by their adverse side-effect profiles such as cognitive deficits that have a negative impact on the quality of life of cancer survivors. Cognitive side effects occur across a variety of domains, including memory, executive function, and processing speed. Such impairments are exacerbated under cognitive challenges and a subgroup of patients experience long-term impairments. Episodic memory in rats can be examined using a source memory task. In the current study, rats received paclitaxel, a taxane-derived chemotherapeutic agent, and learning and memory functioning was examined using the source memory task. Treatment with paclitaxel did not impair spatial and episodic memory, and paclitaxel treated rats were not more susceptible to cognitive challenges. Under conditions in which memory was not impaired, paclitaxel treatment impaired learning of new rules, documenting a decreased sensitivity to changes in experimental contingencies. These findings provide new information on the nature of cancer chemotherapy-induced cognitive impairments, particularly regarding the incongruent vulnerability of episodic memory and new learning following treatment with paclitaxel. Copyright © 2016 Elsevier B.V. All rights reserved.

  19. Extrusion conditions affect chemical composition and in vitro digestion of select food ingredients.

    Science.gov (United States)

    Dust, Jolene M; Gajda, Angela M; Flickinger, Elizabeth A; Burkhalter, Toni M; Merchen, Neal R; Fahey, George C

    2004-05-19

    An experiment was conducted to determine the effects of extrusion conditions on chemical composition and in vitro hydrolytic and fermentative digestion of barley grits, cornmeal, oat bran, soybean flour, soybean hulls, and wheat bran. Extrusion conditions altered crude protein, fiber, and starch concentrations of ingredients. Organic matter disappearance (OMD) increased for extruded versus unprocessed samples of barley grits, cornmeal, and soybean flour that had been hydrolytically digested. After 8 h of fermentative digestion, OMD decreased as extrusion conditions intensified for barley grits and cornmeal but increased for oat bran, soybean hulls, and wheat bran. Total short-chain fatty acid production decreased as extrusion conditions intensified for barley grits, soybean hulls, and soybean flour. These data suggest that the effects of extrusion conditions on ingredient composition and digestion are influenced by the unique chemical characteristics of individual substrates.

  20. Memory and selective learning in children with spina bifida-myelomeningocele and shunted hydrocephalus: A preliminary study

    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.

  1. Adaptive learning can result in a failure to profit from good conditions: implications for understanding depression.

    Science.gov (United States)

    Trimmer, Pete C; Higginson, Andrew D; Fawcett, Tim W; McNamara, John M; Houston, Alasdair I

    2015-04-26

    Depression is a major medical problem diagnosed in an increasing proportion of people and for which commonly prescribed psychoactive drugs are frequently ineffective. Development of treatment options may be facilitated by an evolutionary perspective; several adaptive reasons for proneness to depression have been proposed. A common feature of many explanations is that depressive behaviour is a way to avoid costly effort where benefits are small and/or unlikely. However, this viewpoint fails to explain why low mood persists when the situation improves. We investigate whether a behavioural rule that is adapted to a stochastically changing world can cause inactivity which appears similar to the effect of depression, in that it persists after the situation has improved. We develop an adaptive learning model in which an individual has repeated choices of whether to invest costly effort that may result in a net benefit. Investing effort also provides information about the current conditions and rates of change of the conditions. An individual following the optimal behavioural strategy may sometimes remain inactive when conditions are favourable (i.e. when it would be better to invest effort) when it is poorly informed about the current environmental state. Initially benign conditions can predispose an individual to inactivity after a relatively brief period of negative experiences. Our approach suggests that the antecedent factors causing depressed behaviour could go much further back in an individual s history than is currently appreciated. The insights from our approach have implications for the ongoing debate about best treatment options for patients with depressive symptoms. © The Author(s) 2015. Published by Oxford University Press on behalf of the Foundation for Evolution, Medicine, and Public Health.

  2. Overlapping neurobiology of learned helplessness and conditioned defeat: implications for PTSD and mood disorders.

    Science.gov (United States)

    Hammack, Sayamwong E; Cooper, Matthew A; Lezak, Kimberly R

    2012-02-01

    Exposure to traumatic events can increase the risk for major depressive disorder (MDD) as well as posttraumatic stress disorder (PTSD), and pharmacological treatments for these disorders often involve the modulation of serotonergic (5-HT) systems. Several behavioral paradigms in rodents produce changes in behavior that resemble symptoms of MDD and these behavioral changes are sensitive to antidepressant treatments. Here we review two animal models in which MDD-like behavioral changes are elicited by exposure to an acute traumatic event during adulthood, learned helplessness (LH) and conditioned defeat. In LH, exposure of rats to inescapable, but not escapable, tailshock produces a constellation of behavioral changes that include deficits in fight/flight responding and enhanced anxiety-like behavior. In conditioned defeat, exposure of Syrian hamsters to a social defeat by a more aggressive animal leads to a loss of territorial aggression and an increase in submissive and defensive behaviors in subsequent encounters with non-aggressive conspecifics. Investigations into the neural substrates that control LH and conditioned defeat revealed that increased 5-HT activity in the dorsal raphe nucleus (DRN) is critical for both models. Other key brain regions that regulate the acquisition and/or expression of behavior in these two paradigms include the basolateral amygdala (BLA), central nucleus of the amygdala (CeA) and bed nucleus of the stria terminalis (BNST). In this review, we compare and contrast the role of each of these neural structures in mediating LH and conditioned defeat, and discuss the relevance of these data in developing a better understanding of the mechanisms underlying trauma-related depression. This article is part of a Special Issue entitled 'Post-Traumatic Stress Disorder'. Copyright © 2011 Elsevier Ltd. All rights reserved.

  3. Selected Flight Test Results for Online Learning Neural Network-Based Flight Control System

    Science.gov (United States)

    Williams-Hayes, Peggy S.

    2004-01-01

    The NASA F-15 Intelligent Flight Control System project team developed a series of flight control concepts designed to demonstrate neural network-based adaptive controller benefits, with the objective to develop and flight-test control systems using neural network technology to optimize aircraft performance under nominal conditions and stabilize the aircraft under failure conditions. This report presents flight-test results for an adaptive controller using stability and control derivative values from an online learning neural network. A dynamic cell structure neural network is used in conjunction with a real-time parameter identification algorithm to estimate aerodynamic stability and control derivative increments to baseline aerodynamic derivatives in flight. This open-loop flight test set was performed in preparation for a future phase in which the learning neural network and parameter identification algorithm output would provide the flight controller with aerodynamic stability and control derivative updates in near real time. Two flight maneuvers are analyzed - pitch frequency sweep and automated flight-test maneuver designed to optimally excite the parameter identification algorithm in all axes. Frequency responses generated from flight data are compared to those obtained from nonlinear simulation runs. Flight data examination shows that addition of flight-identified aerodynamic derivative increments into the simulation improved aircraft pitch handling qualities.

  4. Effects of gender and role selection in cooperative learning groups on science inquiry achievement

    Science.gov (United States)

    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".

  5. Interactive prostate segmentation using atlas-guided semi-supervised learning and adaptive feature selection

    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

  6. Interactive prostate segmentation using atlas-guided semi-supervised learning and adaptive feature selection

    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

  7. Interactive prostate segmentation using atlas-guided semi-supervised learning and adaptive feature selection.

    Science.gov (United States)

    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

  8. Declarative virtual water maze learning and emotional fear conditioning in primary insomnia.

    Science.gov (United States)

    Kuhn, Marion; Hertenstein, Elisabeth; Feige, Bernd; Landmann, Nina; Spiegelhalder, Kai; Baglioni, Chiara; Hemmerling, Johanna; Durand, Diana; Frase, Lukas; Klöppel, Stefan; Riemann, Dieter; Nissen, Christoph

    2018-05-02

    Healthy sleep restores the brain's ability to adapt to novel input through memory formation based on activity-dependent refinements of the strength of neural transmission across synapses (synaptic plasticity). In line with this framework, patients with primary insomnia often report subjective memory impairment. However, investigations of memory performance did not produce conclusive results. The aim of this study was to further investigate memory performance in patients with primary insomnia in comparison to healthy controls, using two well-characterized learning tasks, a declarative virtual water maze task and emotional fear conditioning. Twenty patients with primary insomnia according to DSM-IV criteria (17 females, three males, 43.5 ± 13.0 years) and 20 good sleeper controls (17 females, three males, 41.7 ± 12.8 years) were investigated in a parallel-group study. All participants completed a hippocampus-dependent virtual Morris water maze task and amygdala-dependent classical fear conditioning. Patients with insomnia showed significantly delayed memory acquisition in the virtual water maze task, but no significant difference in fear acquisition compared with controls. These findings are consistent with the notion that memory processes that emerge from synaptic refinements in a hippocampal-neocortical network are particularly sensitive to chronic disruptions of sleep, while those in a basic emotional amygdala-dependent network may be more resilient. © 2018 European Sleep Research Society.

  9. Hydrazine selective dual signaling chemodosimetric probe in physiological conditions and its application in live cells

    Energy Technology Data Exchange (ETDEWEB)

    Nandi, Sandip; Sahana, Animesh; Mandal, Sandip [Department of Chemistry, The University of Burdwan, Burdwan, 713104 West Bengal (India); Sengupta, Archya; Chatterjee, Ansuman [Department of Zoology, Visva Bharati University, Santiniketan, West Bengal (India); Safin, Damir A., E-mail: damir.a.safin@gmail.com [Institute of Condensed Matter and Nanosciences, Molecules, Solids and Reactivity (IMCN/MOST), Université catholique de Louvain, Place L. Pasteur 1, 1348 Louvain-la-Neuve (Belgium); Babashkina, Maria G.; Tumanov, Nikolay A.; Filinchuk, Yaroslav [Institute of Condensed Matter and Nanosciences, Molecules, Solids and Reactivity (IMCN/MOST), Université catholique de Louvain, Place L. Pasteur 1, 1348 Louvain-la-Neuve (Belgium); Das, Debasis, E-mail: ddas100in@yahoo.com [Department of Chemistry, The University of Burdwan, Burdwan, 713104 West Bengal (India)

    2015-09-17

    A rhodamine–cyanobenzene conjugate, (E)-4-((2-(3′,6′-bis(diethylamino)-3-oxospiro[isoindoline-1,9′-xanthene] -2-yl)ethylimino)methyl)benzonitrile (1), which structure has been elucidated by single crystal X-ray diffraction, was synthesized for selective fluorescent “turn-on” and colorimetric recognition of hydrazine at physiological pH 7.4. It was established that 1 detects hydrazine up to 58 nM. The probe is useful for the detection of intracellular hydrazine in the human breast cancer cells MCF-7 using a fluorescence microscope. Spirolactam ring opening of 1, followed by its hydrolysis, was established as a probable mechanism for the selective sensing of hydrazine. - Highlights: • A selective rhodamine–cyanobenzene conjugate is synthesized. • The conjugate is a selective dual signaling chemodosimetric probe towards hydrazine. • Spirolactam ring opening of the probe, followed by its hydrolysis, is the sensing mechanism. • The probe detects hydrazine in the human breast cancer cells MCF-7 imaging.

  10. Phenotypic Changes in Different Spinach Varieties Grown and Selected under Organic Conditions

    Directory of Open Access Journals (Sweden)

    Nicolas Schermann

    2011-09-01

    Full Text Available Organic and low-input agriculture needs flexible varieties that can buffer environmental stress and adapt to the needs of farmers. We implemented an experiment to investigate the evolutionary capacities of a sample of spinach (Spinacia oleracea L. population varieties for a number of phenotypic traits. Three farmers cultivated, selected and multiplied one or several populations over two years on their farms. The third year, the versions of the varieties cultivated and selected by the different farmers were compared to the original seed lots they had been given. After two cycles of cultivation and on-farm mass selection, all the observed varieties showed significant phenotypic changes (differences between the original version and the version cultivated by farmers for morphological and phenological traits. When the divergence among versions within varieties was studied, the results show that the varieties conserved their identity, except for one variety, which evolved in such a way that it may now be considered two different varieties. The heterogeneity of the population varieties was assessed in comparison with a commercial F1 hybrid used as control, and we found no specific differences in phenotypic diversity between the hybrid and population varieties. The phenotypic changes shown by the population varieties in response to on-farm cultivation and selection could be useful for the development of specific adaptation. These results call into question the current European seed legislation and the requirements of phenotypic stability for conservation varieties.

  11. Selective increase of auditory cortico-striatal coherence during auditory-cued Go/NoGo discrimination learning.

    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.

  12. Selective Use of the Mother Tongue to Enhance Students’ English Learning Processes...Beyond the Same Assumptions

    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.

  13. Cognitive communication and cooperative hetnet coexistence selected advances on spectrum sensing, learning, and security approaches

    CERN Document Server

    Bader, Faouzi

    2014-01-01

    This book, written by experts from universities and major industrial research laboratories, is devoted to the very hot topic of cognitive radio and networking for cooperative coexistence of heterogeneous wireless networks. Selected highly relevant advanced research is presented on spectrum sensing and progress toward the realization of accurate radio environment mapping, biomimetic learning for self-organizing networks, security threats (with a special focus on primary user emulation attack), and cognition as a tool for green next-generation networks. The research activities covered include work undertaken within the framework of the European COST Action IC0902, which is geared towards the definition of a European platform for cognitive radio and networks. Communications engineers, R&D engineers, researchers, and students will all benefit from this complete reference on recent advances in wireless communications and the design and implementation of cognitive radio systems and networks.

  14. Identification of learning and memory genes in canine; promoter investigation and determining the selective pressure.

    Science.gov (United States)

    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.

  15. 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

  16. Multi-Label Learning via Random Label Selection for Protein Subcellular Multi-Locations Prediction.

    Science.gov (United States)

    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.

  17. Collaborative filtering for brain-computer interaction using transfer learning and active class selection.

    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.

  18. Collaborative filtering for brain-computer interaction using transfer learning and active class selection.

    Science.gov (United States)

    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.

  19. Parental prey selection affects risk-taking behaviour and spatial learning in avian offspring.

    Science.gov (United States)

    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.

  20. When bigger is not better: selection against large size, high condition and fast growth in juvenile lemon sharks.

    Science.gov (United States)

    Dibattista, J D; Feldheim, K A; Gruber, S H; Hendry, A P

    2007-01-01

    Selection acting on large marine vertebrates may be qualitatively different from that acting on terrestrial or freshwater organisms, but logistical constraints have thus far precluded selection estimates for the former. We overcame these constraints by exhaustively sampling and repeatedly recapturing individuals in six cohorts of juvenile lemon sharks (450 age-0 and 255 age-1 fish) at an enclosed nursery site (Bimini, Bahamas). Data on individual size, condition factor, growth rate and inter-annual survival were used to test the 'bigger is better', 'fatter is better' and 'faster is better' hypotheses of life-history theory. For age-0 sharks, selection on all measured traits was weak, and generally acted against large size and high condition. For age-1 sharks, selection was much stronger, and consistently acted against large size and fast growth. These results suggest that selective pressures at Bimini may be constraining the evolution of large size and fast growth, an observation that fits well with the observed small size and low growth rate of juveniles at this site. Our results support those of some other recent studies in suggesting that bigger/fatter/faster is not always better, and may often be worse.

  1. Selective N-alkylation of amines using nitriles under hydrogenation conditions: facile synthesis of secondary and tertiary amines.

    Science.gov (United States)

    Ikawa, Takashi; Fujita, Yuki; Mizusaki, Tomoteru; Betsuin, Sae; Takamatsu, Haruki; Maegawa, Tomohiro; Monguchi, Yasunari; Sajiki, Hironao

    2012-01-14

    Nitriles were found to be highly effective alkylating reagents for the selective N-alkylation of amines under catalytic hydrogenation conditions. For the aromatic primary amines, the corresponding secondary amines were selectively obtained under Pd/C-catalyzed hydrogenation conditions. Although the use of electron poor aromatic amines or bulky nitriles showed a lower reactivity toward the reductive alkylation, the addition of NH(4)OAc enhanced the reactivity to give secondary aromatic amines in good to excellent yields. Under the same reaction conditions, aromatic nitro compounds instead of the aromatic primary amines could be directly transformed into secondary amines via a domino reaction involving the one-pot hydrogenation of the nitro group and the reductive alkylation of the amines. While aliphatic amines were effectively converted to the corresponding tertiary amines under Pd/C-catalyzed conditions, Rh/C was a highly effective catalyst for the N-monoalkylation of aliphatic primary amines without over-alkylation to the tertiary amines. Furthermore, the combination of the Rh/C-catalyzed N-monoalkylation of the aliphatic primary amines and additional Pd/C-catalyzed alkylation of the resulting secondary aliphatic amines could selectively prepare aliphatic tertiary amines possessing three different alkyl groups. According to the mechanistic studies, it seems reasonable to conclude that nitriles were reduced to aldimines before the nucleophilic attack of the amine during the first step of the reaction.

  2. Conditions for the quality of primary education teachers’ collective learning at individual and group level

    NARCIS (Netherlands)

    Doppenberg, J.J.; Brok, den P.J.; Bergen, T.C.M.

    2009-01-01

    Collective teacher learning plays an important role in teachers' professional development and schools' innovative capacity. Despite this importance, collective learning in schools has been weakly conceptualised and little empirical evidence exists with respect to the contributions of collective

  3. Automatic machine-learning based identification of jogging periods from accelerometer measurements of adolescents under field conditions.

    Science.gov (United States)

    Zdravevski, Eftim; Risteska Stojkoska, Biljana; Standl, Marie; Schulz, Holger

    2017-01-01

    Assessment of health benefits associated with physical activity depend on the activity duration, intensity and frequency, therefore their correct identification is very valuable and important in epidemiological and clinical studies. The aims of this study are: to develop an algorithm for automatic identification of intended jogging periods; and to assess whether the identification performance is improved when using two accelerometers at the hip and ankle, compared to when using only one at either position. The study used diarized jogging periods and the corresponding accelerometer data from thirty-nine, 15-year-old adolescents, collected under field conditions, as part of the GINIplus study. The data was obtained from two accelerometers placed at the hip and ankle. Automated feature engineering technique was performed to extract features from the raw accelerometer readings and to select a subset of the most significant features. Four machine learning algorithms were used for classification: Logistic regression, Support Vector Machines, Random Forest and Extremely Randomized Trees. Classification was performed using only data from the hip accelerometer, using only data from ankle accelerometer and using data from both accelerometers. The reported jogging periods were verified by visual inspection and used as golden standard. After the feature selection and tuning of the classification algorithms, all options provided a classification accuracy of at least 0.99, independent of the applied segmentation strategy with sliding windows of either 60s or 180s. The best matching ratio, i.e. the length of correctly identified jogging periods related to the total time including the missed ones, was up to 0.875. It could be additionally improved up to 0.967 by application of post-classification rules, which considered the duration of breaks and jogging periods. There was no obvious benefit of using two accelerometers, rather almost the same performance could be achieved from

  4. Automatic machine-learning based identification of jogging periods from accelerometer measurements of adolescents under field conditions.

    Directory of Open Access Journals (Sweden)

    Eftim Zdravevski

    Full Text Available Assessment of health benefits associated with physical activity depend on the activity duration, intensity and frequency, therefore their correct identification is very valuable and important in epidemiological and clinical studies. The aims of this study are: to develop an algorithm for automatic identification of intended jogging periods; and to assess whether the identification performance is improved when using two accelerometers at the hip and ankle, compared to when using only one at either position.The study used diarized jogging periods and the corresponding accelerometer data from thirty-nine, 15-year-old adolescents, collected under field conditions, as part of the GINIplus study. The data was obtained from two accelerometers placed at the hip and ankle. Automated feature engineering technique was performed to extract features from the raw accelerometer readings and to select a subset of the most significant features. Four machine learning algorithms were used for classification: Logistic regression, Support Vector Machines, Random Forest and Extremely Randomized Trees. Classification was performed using only data from the hip accelerometer, using only data from ankle accelerometer and using data from both accelerometers.The reported jogging periods were verified by visual inspection and used as golden standard. After the feature selection and tuning of the classification algorithms, all options provided a classification accuracy of at least 0.99, independent of the applied segmentation strategy with sliding windows of either 60s or 180s. The best matching ratio, i.e. the length of correctly identified jogging periods related to the total time including the missed ones, was up to 0.875. It could be additionally improved up to 0.967 by application of post-classification rules, which considered the duration of breaks and jogging periods. There was no obvious benefit of using two accelerometers, rather almost the same performance could be

  5. Selection and Use of Online Learning Resources by First-Year Medical Students: Cross-Sectional Study.

    Science.gov (United States)

    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

  6. Do children go for the nice guys? The influence of speaker benevolence and certainty on selective word learning.

    Science.gov (United States)

    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.

  7. Food selection of the Malayan tapir (Tapirus indicus) under semi-wild conditions

    Science.gov (United States)

    Simpson, Boyd K.; Shukor, M. N.; Magintan, David

    2013-11-01

    A study on the selection of food plants by captive Malayan tapirs (Tapirus indicus) was undertaken in a 30 hectare natural forest enclosure at the Sungai Dusun Wildlife Reserve, Malaysia. Tapirs browsed on 217 species of plants (from 99 genera and 49 families) from a total of the 1142 specimens collected and identified. Food plants were heavily dominated by sapling trees and shrubs which comprised 93% of all plants taken, with the remainder comprising woody lianas, vines and herbaceous plants. Although tapirs browsed on a wide variety of plant species, the top 30 species consumed represented more than 60% of all the plants selected, whilst the vast majority of species were rarely eaten. More than 80 species of trees and shrubs were available, but not eaten at all. The most readily consumed species were the sub-canopy and understorey trees Xerospermum noronhianum, Aporosa prainiana and Baccaurea parviflora, while Aporosa, Knema and Xerospermum were the dominant plant genera. The Phyllanthaceae (leaf flowers), Myristicaceae (nutmegs) and Sapindaceae (rambutans) were the most commonly selected families comprising 45% of the diet. Tapirs fed on saplings trees up to 8.3 m in height, while plants taller than about 1.6 m were bent, broken or pushed to the ground to gain access to the foliage. Sapling stems up to 4.2 cm in diameter could be snapped by biting, while larger trees to 7 cm diameter could be pushed down. Tapirs typically fed on the newer leaves and shoots, however, often only consuming half of the available foliage on a plant. This study documents 160 new plant species suitable as Malayan tapir food, and is consistent with the generalist, but selective browsing nature of the Tapirus species in general.

  8. Microhabitat Conditions in Wyoming's Sage-Grouse Core Areas: Effects on Nest Site Selection and Success.

    Science.gov (United States)

    Dinkins, Jonathan B; Smith, Kurt T; Beck, Jeffrey L; Kirol, Christopher P; Pratt, Aaron C; Conover, Michael R

    2016-01-01

    The purpose of our study was to identify microhabitat characteristics of greater sage-grouse (Centrocercus urophasianus) nest site selection and survival to determine the quality of sage-grouse habitat in 5 regions of central and southwest Wyoming associated with Wyoming's Core Area Policy. Wyoming's Core Area Policy was enacted in 2008 to reduce human disturbance near the greatest densities of sage-grouse. Our analyses aimed to assess sage-grouse nest selection and success at multiple micro-spatial scales. We obtained microhabitat data from 928 sage-grouse nest locations and 819 random microhabitat locations from 2008-2014. Nest success was estimated from 924 nests with survival data. Sage-grouse selected nests with greater sagebrush cover and height, visual obstruction, and number of small gaps between shrubs (gap size ≥0.5 m and sage-grouse were selecting different nest sites in Core Areas relative to areas outside of Core. The Kaplan-Meier nest success estimate for a 27-day incubation period was 42.0% (95% CI: 38.4-45.9%). Risk of nest failure was negatively associated with greater rock and more medium-sized gaps between shrubs (gap size ≥2.0 m and <3.0 m). Within our study areas, Wyoming's Core Areas did not have differing microhabitat quality compared to outside of Core Areas. The close proximity of our locations within and outside of Core Areas likely explained our lack of finding differences in microhabitat quality among locations within these landscapes. However, the Core Area Policy is most likely to conserve high quality habitat at larger spatial scales, which over decades may have cascading effects on microhabitat quality available between areas within and outside of Core Areas.

  9. The Ghost Condition: Imitation Versus Emulation in Young Children's Observational Learning.

    Science.gov (United States)

    Thompson, Doreen E.; Russell, James

    2004-01-01

    Although observational learning by children may occur through imitating a modeler's actions, it can also occur through learning about an object's dynamic affordances- a process that M. Tomasello (1996) calls "emulation." The relative contributions of imitation and emulation within observational learning were examined in a study with 14- to…

  10. Conditions for the Effectiveness of Multiple Visual Representations in Enhancing STEM Learning

    Science.gov (United States)

    Rau, Martina A.

    2017-01-01

    Visual representations play a critical role in enhancing science, technology, engineering, and mathematics (STEM) learning. Educational psychology research shows that adding visual representations to text can enhance students' learning of content knowledge, compared to text-only. But should students learn with a single type of visual…

  11. Quality of the Home Learning Environment during Preschool Age--Domains and Contextual Conditions

    Science.gov (United States)

    Kluczniok, Katharina; Lehrl, Simone; Kuger, Susanne; Rossbach, Hans-Guenther

    2013-01-01

    The quality of the home learning environment has been proven to be of major importance for child development, but little is known about the role of domain specificity in promoting early childhood learning at home and its dependence on family background. This article presents a framework of the home learning environment in early childhood that…

  12. Microhabitat Conditions in Wyoming's Sage-Grouse Core Areas: Effects on Nest Site Selection and Success.

    Directory of Open Access Journals (Sweden)

    Jonathan B Dinkins

    Full Text Available The purpose of our study was to identify microhabitat characteristics of greater sage-grouse (Centrocercus urophasianus nest site selection and survival to determine the quality of sage-grouse habitat in 5 regions of central and southwest Wyoming associated with Wyoming's Core Area Policy. Wyoming's Core Area Policy was enacted in 2008 to reduce human disturbance near the greatest densities of sage-grouse. Our analyses aimed to assess sage-grouse nest selection and success at multiple micro-spatial scales. We obtained microhabitat data from 928 sage-grouse nest locations and 819 random microhabitat locations from 2008-2014. Nest success was estimated from 924 nests with survival data. Sage-grouse selected nests with greater sagebrush cover and height, visual obstruction, and number of small gaps between shrubs (gap size ≥0.5 m and <1.0 m, while selecting for less bare ground and rock. With the exception of more small gaps between shrubs, we did not find any differences in availability of these microhabitat characteristics between locations within and outside of Core Areas. In addition, we found little supporting evidence that sage-grouse were selecting different nest sites in Core Areas relative to areas outside of Core. The Kaplan-Meier nest success estimate for a 27-day incubation period was 42.0% (95% CI: 38.4-45.9%. Risk of nest failure was negatively associated with greater rock and more medium-sized gaps between shrubs (gap size ≥2.0 m and <3.0 m. Within our study areas, Wyoming's Core Areas did not have differing microhabitat quality compared to outside of Core Areas. The close proximity of our locations within and outside of Core Areas likely explained our lack of finding differences in microhabitat quality among locations within these landscapes. However, the Core Area Policy is most likely to conserve high quality habitat at larger spatial scales, which over decades may have cascading effects on microhabitat quality available

  13. Heightened condition-dependent growth of sexually selected weapons in the rhinoceros beetle, Trypoxylus dichotomus (Coleoptera: Scarabaeidae).

    Science.gov (United States)

    Johns, A; Gotoh, H; McCullough, E L; Emlen, D J; Lavine, L C

    2014-10-01

    The exaggerated weapons and ornaments of sexual selection are condition-dependent traits that often grow to exaggerated proportions. The horns of male rhinoceros beetles are extremely sensitive to the larval nutritional environment and are used by rival males in combat over access to females. In contrast to horns, other parts of the body, such as wings, eyes, and legs, scale proportionally with body size, whereas others, such as males' external genitalia, are invariant with body size, regardless of nutrition. We document how body parts of the Asian rhinoceros beetle, Trypoxylus dichotomus, exhibit plasticity and constraint in response to nutritional condition. We discuss the implications of these results for the evolution of condition-dependent and condition-independent traits in animals. © The Author 2014. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.

  14. The Evaluation of Unitary & Central Type Air-Conditioning Systems in Selected Florida Schools.

    Science.gov (United States)

    Bradley, William B.

    The study reported here was conducted in an effort to obtain data for comparing the combined owning and operating costs of two different types of air-conditioning systems in two elementary schools. Both schools were built during 1969-70 in the same geographical area along the southeast coast of Florida and are also served by the same electric…

  15. The Influence of Selected Societal, University, and School Conditions on the Preparation and Practice of Teachers.

    Science.gov (United States)

    Haberman, Martin

    An unresolved dilemma in teacher education is the organizational dislocation that occurs between the setting in which teachers are educated and those in which they are expected to practice. College students are conditioned to be independent and self-interested, while beginning teachers are expected to conform to and support their school system. In…

  16. Concept of diagnostic monitoring of condition of selected equipment for V-1 nuclear power plant

    International Nuclear Information System (INIS)

    Jaros, I.

    1981-01-01

    The vibroacoustic method based on picking up and processing vibrations, shocks and structural noise from the outer surface of equipment was chosen for testing the mechanical conditions of the reactor and of the main circulating pumps. The location of vibration pickups on the primary circuit components, their specifications, signal processing and evaluation are described. (M.D.)

  17. Self-ordered pointing and visual conditional associative learning tasks in drug-free schizophrenia spectrum disorder patients

    Directory of Open Access Journals (Sweden)

    Galluzzo Alessandro

    2008-01-01

    Full Text Available Abstract Background There is evidence of a link between schizophrenia and a deficit of working memory, but this has been derived from tasks not specifically developed to probe working memory per se. Our aim was to investigate whether working memory deficits may be detected across different paradigms using the self-ordered pointing task (SOPT and the visual conditional associative learning task (VCALT in patients with schizophrenia spectrum disorders and healthy controls. The current literature suggests deficits in schizophrenia spectrum disorder patients versus healthy controls but these studies frequently involved small samples, broad diagnostic criteria, inclusion of patients on antipsychotic medications, and were not controlled for symptom domains, severity of the disorder, etc. To overcome some of these limitations, we investigated the self-monitoring and conditional associative learning abilities of a numerically representative sample of healthy controls and a group of non-deteriorated, drug-free patients hospitalized for a schizophrenia spectrum disorder with florid, mainly positive psychotic symptoms. Methods Eighty-five patients with a schizophrenia spectrum disorder (DSM-IV-TR diagnosis of schizophrenia (n = 71 or schizophreniform disorder (n = 14 and 80 healthy controls entered the study. The clinical picture was dominated by positive symptoms. The healthy control group had a negative personal and family history of schizophrenia or mood disorder and satisfied all the inclusion and exclusion criteria other than variables related to schizophrenia spectrum disorders. Results Compared to controls, patients had worse performances on SOPT, VCALT and higher SOPT/VCALT ratios, not affected by demographic or clinical variables. ROC curves showed that SOPT, VCALT, and SOPT/VCALT ratio had good accuracy in discriminating patients from controls. The SOPT and VCALT scores were inter-correlated in controls but not in patients. Conclusion The

  18. Feature Selection for Motor Imagery EEG Classification Based on Firefly Algorithm and Learning Automata

    Directory of Open Access Journals (Sweden)

    Aiming Liu

    2017-11-01

    Full Text Available Motor Imagery (MI electroencephalography (EEG is widely studied for its non-invasiveness, easy availability, portability, and high temporal resolution. As for MI EEG signal processing, the high dimensions of features represent a research challenge. It is necessary to eliminate redundant features, which not only create an additional overhead of managing the space complexity, but also might include outliers, thereby reducing classification accuracy. The firefly algorithm (FA can adaptively select the best subset of features, and improve classification accuracy. However, the FA is easily entrapped in a local optimum. To solve this problem, this paper proposes a method of combining the firefly algorithm and learning automata (LA to optimize feature selection for motor imagery EEG. We employed a method of combining common spatial pattern (CSP and local characteristic-scale decomposition (LCD algorithms to obtain a high dimensional feature set, and classified it by using the spectral regression discriminant analysis (SRDA classifier. Both the fourth brain–computer interface competition data and real-time data acquired in our designed experiments were used to verify the validation of the proposed method. Compared with genetic and adaptive weight particle swarm optimization algorithms, the experimental results show that our proposed method effectively eliminates redundant features, and improves the classification accuracy of MI EEG signals. In addition, a real-time brain–computer interface system was implemented to verify the feasibility of our proposed methods being applied in practical brain–computer interface systems.

  19. Feature Selection for Motor Imagery EEG Classification Based on Firefly Algorithm and Learning Automata.

    Science.gov (United States)

    Liu, Aiming; Chen, Kun; Liu, Quan; Ai, Qingsong; Xie, Yi; Chen, Anqi

    2017-11-08

    Motor Imagery (MI) electroencephalography (EEG) is widely studied for its non-invasiveness, easy availability, portability, and high temporal resolution. As for MI EEG signal processing, the high dimensions of features represent a research challenge. It is necessary to eliminate redundant features, which not only create an additional overhead of managing the space complexity, but also might include outliers, thereby reducing classification accuracy. The firefly algorithm (FA) can adaptively select the best subset of features, and improve classification accuracy. However, the FA is easily entrapped in a local optimum. To solve this problem, this paper proposes a method of combining the firefly algorithm and learning automata (LA) to optimize feature selection for motor imagery EEG. We employed a method of combining common spatial pattern (CSP) and local characteristic-scale decomposition (LCD) algorithms to obtain a high dimensional feature set, and classified it by using the spectral regression discriminant analysis (SRDA) classifier. Both the fourth brain-computer interface competition data and real-time data acquired in our designed experiments were used to verify the validation of the proposed method. Compared with genetic and adaptive weight particle swarm optimization algorithms, the experimental results show that our proposed method effectively eliminates redundant features, and improves the classification accuracy of MI EEG signals. In addition, a real-time brain-computer interface system was implemented to verify the feasibility of our proposed methods being applied in practical brain-computer interface systems.

  20. 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.

  1. Modeling PM2.5 Urban Pollution Using Machine Learning and Selected Meteorological Parameters

    Directory of Open Access Journals (Sweden)

    Jan Kleine Deters

    2017-01-01

    Full Text Available Outdoor air pollution costs millions of premature deaths annually, mostly due to anthropogenic fine particulate matter (or PM2.5. Quito, the capital city of Ecuador, is no exception in exceeding the healthy levels of pollution. In addition to the impact of urbanization, motorization, and rapid population growth, particulate pollution is modulated by meteorological factors and geophysical characteristics, which complicate the implementation of the most advanced models of weather forecast. Thus, this paper proposes a machine learning approach based on six years of meteorological and pollution data analyses to predict the concentrations of PM2.5 from wind (speed and direction and precipitation levels. The results of the classification model show a high reliability in the classification of low (25 µg/m3 and low (<10 µg/m3 versus moderate (10–25 µg/m3 concentrations of PM2.5. A regression analysis suggests a better prediction of PM2.5 when the climatic conditions are getting more extreme (strong winds or high levels of precipitation. The high correlation between estimated and real data for a time series analysis during the wet season confirms this finding. The study demonstrates that the use of statistical models based on machine learning is relevant to predict PM2.5 concentrations from meteorological data.

  2. A Comparison of Participation Patterns in Selected Formal, Non-Formal, and Informal Online Learning Environments

    Science.gov (United States)

    Schwier, Richard A.; Seaton, J. X.

    2013-01-01

    Does learner participation vary depending on the learning context? Are there characteristic features of participation evident in formal, non-formal, and informal online learning environments? Six online learning environments were chosen as epitomes of formal, non-formal, and informal learning contexts and compared. Transcripts of online…

  3. Resource selection by the California condor (Gymnogyps californianus relative to terrestrial-based habitats and meteorological conditions.

    Directory of Open Access Journals (Sweden)

    James W Rivers

    Full Text Available Condors and vultures are distinct from most other terrestrial birds because they use extensive soaring flight for their daily movements. Therefore, assessing resource selection by these avian scavengers requires quantifying the availability of terrestrial-based habitats, as well as meteorological variables that influence atmospheric conditions necessary for soaring. In this study, we undertook the first quantitative assessment of habitat- and meteorological-based resource selection in the endangered California condor (Gymnogyps californianus within its California range and across the annual cycle. We found that condor use of terrestrial areas did not change markedly within the annual cycle, and that condor use was greatest for habitats where food resources and potential predators could be detected and where terrain was amenable for taking off from the ground in flight (e.g., sparse habitats, coastal areas. Condors originating from different release sites differed in their use of habitat, but this was likely due in part to variation in habitats surrounding release sites. Meteorological conditions were linked to condor use of ecological subregions, with thermal height, thermal velocity, and wind speed having both positive (selection and negative (avoidance effects on condor use in different areas. We found little evidence of systematic effects between individual characteristics (i.e., sex, age, breeding status or components of the species management program (i.e., release site, rearing method relative to meteorological conditions. Our findings indicate that habitat type and meteorological conditions can interact in complex ways to influence condor resource selection across landscapes, which is noteworthy given the extent of anthropogenic stressors that may impact condor populations (e.g., lead poisoning, wind energy development. Additional studies will be valuable to assess small-scale condor movements in light of these stressors to help minimize

  4. A selection of problems related to safe working conditions in nuclear power plants

    International Nuclear Information System (INIS)

    Brunner, K.H.

    1984-01-01

    Two representative examples were chosen to demonstrate that the problems related to safe working conditions can be solved with work being prepared extensively and in detail taking into consideration radiation protection and conventional job safety measures and with qualified staff. Most of the job safety problems in nuclear power plants are pretty much the same as in conventional plants. Despite successful implementation of employment and radiation protection in nuclear power plants, improvements in detail are possible and make sense. (orig.) [de

  5. Prediction of selective estrogen receptor beta agonist using open data and machine learning approach.

    Science.gov (United States)

    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.

  6. Selection of contact bearing couple materials for hip prosthesis using finite element analysis under static conditions

    Science.gov (United States)

    Arirajan, K. A.; Chockalingam, K.; Vignesh, C.

    2018-04-01

    Implants are the artificial parts to replace the missing bones or joints in human anatomy to give mechanical support. Hip joint replacement is an important issue in orthopaedic surgery. The main concern limiting the long-run success of the total hip replacement is the limited service life. Hip replacement technique is widely used in replacing the femur head and acetabular cup by materials that are highly biocompatible. The success of the artificial hip replacement depends upon proper material selection, structure, and shape of the hip prosthesis. Many orthopaedic analyses have been tried with different materials, but ended with partial success on the application side. It is a critical task for selecting the best material pair in the hip prosthesis design. This work develops the finite element analysis of an artificial hip implant to study highest von Mises stress, contact pressure and elastic strain occurs for the dissimilar material combination. The different bearing couple considered for the analysis are Metal on Metal, Metal on Plastic, Metal on Ceramic, Ceramic on Plastic, Ceramic on Ceramic combinations. The analysis is carried out at different static positions of a human (i.e) standing, sitting. The results reveals that the combination with metal in contact with plastic (i.e) Titanium femoral head paired with Ultra High Molecular Weight Poly Ethylene acetabular cup reduces maximum von Mises stress and also it gives lowest contact pressure than other combination of bearing couples.

  7. Inferior frontal gyrus preserves working memory and emotional learning under conditions of impaired noradrenergic signaling

    Directory of Open Access Journals (Sweden)

    Benjamin eBecker

    2013-12-01

    Full Text Available Compensation has been widely applied to explain neuroimaging findings in neuropsychiatric patients. Functional compensation is often invoked when patients display equal performance and increased neural activity in comparison to healthy controls. According to the compensatory hypothesis increased activity allows the brain to maintain cognitive performance despite underlying neuropathological changes. Due to methodological and pathology-related issues, however, the functional relevance of the increased activity and the specific brain regions involved in the compensatory response remain unclear. An experimental approach that allows a transient induction of compensatory responses in the healthy brain could help to overcome these issues. To this end we used the nonselective beta-blocker propranolol to pharmacologically induce sub-optimal noradrenergic signaling in healthy participants. In two independent fMRI experiments participants received either placebo or propranolol before they underwent a cognitive challenge (experiment 1: working memory; experiment 2: emotional learning: Pavlovian fear conditioning. In experiment 1 propranolol had no effects on working memory performance, but evoked stronger activity in the left inferior frontal gyrus (IFG. In experiment 2 propranolol produced no effects on emotional memory formation, but evoked stronger activity in the right IFG. The present finding that sub-optimal beta-adrenergic signaling did not disrupt performance and concomitantly increased IFG activity is consistent with, and extends, current perspectives on functional compensation. Together, our findings suggest that under conditions of impaired noradrenergic signaling, heightened activity in brain regions located within the cognitive control network, particularly the IFG, may reflect compensatory operations subserving the maintenance of behavioral performance.

  8. The Patient Educator Presentation in Dental Education: Reinforcing the Importance of Learning About Rare Conditions.

    Science.gov (United States)

    Edwards, Paul C; Graham, Jasmine; Oling, Rebecca; Frantz, Kate E

    2016-05-01

    The aim of this study was to determine whether a patient educator presentation (PEP) on pemphigus vulgaris would increase second-year dental students' awareness of the importance of learning about rare conditions and improve their retention of rare disease knowledge. The study involved students' subjective assessments of a PEP experience at two U.S. dental schools. In this mixed methods study, cross-sectional data were obtained by surveys and in-depth interviews. Questions focused on students' assessment of the messages acquired from the PEP and its likely impact on their future clinical care. At University 1, students completed paper surveys with open-ended questions and participated in a focus group. At University 2, students completed an online survey consisting of rating scale and open-ended questions. Responses to open-ended questions were categorized into themes. At University 1, 79 students (out of a possible 102; response rate 77.5%) completed the survey, and an additional ten students participated in a focus group. At University 2, 30 students (out of a possible 104; response rate 28.8%) completed the survey. At Universities 1 and 2, 88% and 100%, respectively, of respondents stated the PEP would influence their future clinical decision making. The vast majority of respondents (94% and 100% at University 1 and University 2, respectively) were of the opinion that the personal testimonial from a patient would help them recall information about pemphigus vulgaris in five years' time. Respondents from both universities commented that the PEP emphasized the importance of not dismissing a patient's concerns. These results suggest that a presentation by a patient with a rare condition can be an effective educational tool for preclinical dental students.

  9. CGBayesNets: conditional Gaussian Bayesian network learning and inference with mixed discrete and continuous data.

    Science.gov (United States)

    McGeachie, Michael J; Chang, Hsun-Hsien; Weiss, Scott T

    2014-06-01

    Bayesian Networks (BN) have been a popular predictive modeling formalism in bioinformatics, but their application in modern genomics has been slowed by an inability to cleanly handle domains with mixed discrete and continuous variables. Existing free BN software packages either discretize continuous variables, which can lead to information loss, or do not include inference routines, which makes prediction with the BN impossible. We present CGBayesNets, a BN package focused around prediction of a clinical phenotype from mixed discrete and continuous variables, which fills these gaps. CGBayesNets implements Bayesian likelihood and inference algorithms for the conditional Gaussian Bayesian network (CGBNs) formalism, one appropriate for predicting an outcome of interest from, e.g., multimodal genomic data. We provide four different network learning algorithms, each making a different tradeoff between computational cost and network likelihood. CGBayesNets provides a full suite of functions for model exploration and verification, including cross validation, bootstrapping, and AUC manipulation. We highlight several results obtained previously with CGBayesNets, including predictive models of wood properties from tree genomics, leukemia subtype classification from mixed genomic data, and robust prediction of intensive care unit mortality outcomes from metabolomic profiles. We also provide detailed example analysis on public metabolomic and gene expression datasets. CGBayesNets is implemented in MATLAB and available as MATLAB source code, under an Open Source license and anonymous download at http://www.cgbayesnets.com.

  10. Selection of Investment Projects by Monte Carlo Method in Risk Condition

    Directory of Open Access Journals (Sweden)

    M. E.

    2017-12-01

    Full Text Available The Monte Carlo method (also known as the Monte Carlo simulation was proposed by Nicholas Metropolis, S. Ulam and Jhon Von Neiman in 50-th years of the past century. The method can be widely applied to analysis of investment projects due to the advantages recognized both by practitioners and the academic community. The balance model of a project with discounted financial flows has been implemented for Microsoft Excel and Google Docs spread-sheet solutions. The Monte Carlo method for project with low and high correlated net present value (NPV parameters in the environment of the electronic tables of MS Excel/Google Docs. A distinct graduation of risk was identified. A necessity of account of correlation effects and the use of multivariate imitation during the project selection has been demonstrated.

  11. Economic values and expected effect of selection index for pathogen-specific mastitis under Danish conditions

    DEFF Research Database (Denmark)

    Sørensen, Lars Peter; Mark, Thomas; Sørensen, M.K.

    2010-01-01

    The objectives of this study were 1) to estimate costs related to 5 different pathogen-specific mastitis traits (susceptibility to different pathogens causing mastitis in dairy cattle) and unspecific mastitis, and 2) to compare selection differentials for an udder health index consisting of 5...... different pathogen-specific mastitis traits and lactation average somatic cell count from 5 to 170 d after first calving (LASCC170) with another index consisting of 1 unspecific mastitis trait and LASCC170. Economic values were estimated for mastitis caused by Staphylococcus aureus, Streptococcus...... dysgalactiae, Escherichia coli, coagulase-negative staphylococci, and Streptococcus uberis using a stochastic simulation model (SimHerd IV). Mastitis incidences for SimHerd IV were from incidences of mastitis treatments in primiparous Danish Holstein cows calving in 2007. Estimated costs ranged from 149 euro...

  12. 3D Imaging with a Sonar Sensor and an Automated 3-Axes Frame for Selective Spraying in Controlled Conditions

    Directory of Open Access Journals (Sweden)

    David Reiser

    2017-02-01

    Full Text Available Autonomous selective spraying could be a way for agriculture to reduce production costs, save resources, protect the environment and help to fulfill specific pesticide regulations. The objective of this paper was to investigate the use of a low-cost sonar sensor for autonomous selective spraying of single plants. For this, a belt driven autonomous robot was used with an attached 3-axes frame with three degrees of freedom. In the tool center point (TCP of the 3-axes frame, a sonar sensor and a spray valve were attached to create a point cloud representation of the surface, detect plants in the area and perform selective spraying. The autonomous robot was tested on replicates of artificial crop plants. The location of each plant was identified out of the acquired point cloud with the help of Euclidian clustering. The gained plant positions were spatially transformed from the coordinates of the sonar sensor to the valve location to determine the exact irrigation points. The results showed that the robot was able to automatically detect the position of each plant with an accuracy of 2.7 cm and could spray on these selected points. This selective spraying reduced the used liquid by 72%, when comparing it to a conventional spraying method in the same conditions.

  13. Under which conditions does ICT have a positive effect on teaching and learning? A Call to Action

    NARCIS (Netherlands)

    Voogt, Joke; Knezek, G.; Cox, M.; Knezek, D.; ten Brummelhuis, A.C.A.

    2013-01-01

    Under which conditions does ICT have a positive effect on teaching and learning?’ This was the leading question of the International EDUsummIT in The Hague, the Netherlands. The bases for the discussion were the scholarly findings of the International Handbook of Information Technology in Primary

  14. Under Which Conditions Does ICT Have a Positive Effect on Teaching and Learning? A Call to Action

    Science.gov (United States)

    Voogt, J.; Knezek, G.; Cox, M.; Knezek, D.; ten Brummelhuis, A.

    2013-01-01

    "Under which conditions does ICT have a positive effect on teaching and learning?" This was the leading question of the International EDUsummIT in The Hague, the Netherlands. The bases for the discussion were the scholarly findings of the International Handbook of Information Technology in Primary and Secondary Education, a synthesis of research…

  15. "It's Not Like a Normal 9 to 5!": The Learning Journeys of Media Production Apprentices in Distributed Working Conditions

    Science.gov (United States)

    Lahiff, Ann; Guile, David

    2016-01-01

    An apprenticeship in media production in England is at the centre of this case study exploration. The context is exemplified by the organisation of the process of production around project teams and the development of project-based working cultures. Given these developments, the working conditions and learning opportunities presented to…

  16. The Effect of Cooperative Learning Approach Based on Conceptual Change Condition on Students' Understanding of Chemical Equilibrium Concepts

    Science.gov (United States)

    Bilgin, Ibrahim; Geban, Omer

    2006-01-01

    The purpose of this study is to investigate the effects of the cooperative learning approach based on conceptual change conditions over traditional instruction on 10th grade students' conceptual understanding and achievement of computational problems related to chemical equilibrium concepts. The subjects of this study consisted of 87 tenth grade…

  17. Conditions for excellence in teaching in medical education: The Frankfurt Model to ensure quality in teaching and learning

    Directory of Open Access Journals (Sweden)

    Giesler, Marianne

    2017-10-01

    Full Text Available Background: There is general consensus that the organizational and administrative aspects of academic study programs exert an important influence on teaching and learning. Despite this, no comprehensive framework currently exists to describe the conditions that affect the quality of teaching and learning in medical education. The aim of this paper is to systematically and comprehensively identify these factors to offer academic administrators and decision makers interested in improving teaching a theory-based and, to an extent, empirically founded framework on the basis of which improvements in teaching quality can be identified and implemented.Method: Primarily, the issue was addressed by combining a theory-driven deductive approach with an experience based, “best evidence” one during the course of two workshops held by the GMA Committee on Personnel and Organizational Development in Academic Teaching (POiL in Munich (2013 and Frankfurt (2014. Two models describing the conditions relevant to teaching and learning (Euler/Hahn and Rindermann were critically appraised and synthesized into a new third model. Practical examples of teaching strategies that promote or hinder learning were compiled and added to the categories of this model and, to the extent possible, supported with empirical evidence.Based on this, a checklist with recommendations for optimizing general academic conditions was formulated.Results: The covers six categories: and These categories have been supplemented by the interests, motives and abilities of the actual teachers and students in this particular setting. The categories of this model provide the structure for a checklist in which recommendations for optimizing teaching are given.Conclusions: The checklist derived from the Frankfurt Model for ensuring quality in teaching and learning can be used for quality assurance and to improve the conditions under which teaching and learning take place in medical schools.

  18. Dopamine selectively remediates 'model-based' reward learning: a computational approach.

    Science.gov (United States)

    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.

  19. Dissecting children's observational learning of complex actions through selective video displays.

    Science.gov (United States)

    Flynn, Emma; Whiten, Andrew

    2013-10-01

    Children can learn how to use complex objects by watching others, yet the relative importance of different elements they may observe, such as the interactions of the individual parts of the apparatus, a model's movements, and desirable outcomes, remains unclear. In total, 140 3-year-olds and 140 5-year-olds participated in a study where they observed a video showing tools being used to extract a reward item from a complex puzzle box. Conditions varied according to the elements that could be seen in the video: (a) the whole display, including the model's hands, the tools, and the box; (b) the tools and the box but not the model's hands; (c) the model's hands and the tools but not the box; (d) only the end state with the box opened; and (e) no demonstration. Children's later attempts at the task were coded to establish whether they imitated the hierarchically organized sequence of the model's actions, the action details, and/or the outcome. Children's successful retrieval of the reward from the box and the replication of hierarchical sequence information were reduced in all but the whole display condition. Only once children had attempted the task and witnessed a second demonstration did the display focused on the tools and box prove to be better for hierarchical sequence information than the display focused on the tools and hands only. Copyright © 2013 Elsevier Inc. All rights reserved.

  20. Profiles of selected nutrients affecting skin condition in children with atopic dermatitis.

    Science.gov (United States)

    Strucińska, Małgorzata; Rowicka, Grażyna; Riahi, Agnieszka

    2015-01-01

    Atopic dermatitis (AD) is a chronic inflammation of the skin recognised to be one of the first clinical signs of allergy. In the first years of life, epidemiological evidence has demonstrated that common causative foods of a child's diet are: cow's milk, hen's eggs, wheat and soya. Children with AD being treated with elimination diets are at risk of nutritional deficiencies that include those nutrients required for ensuring proper skin structure and function. The aim of the study was to assess dietary intake of nutrients which affect skin condition in children with AD being treated with a milk-free diet. Subjects were 25 children aged 4-6 years with AD undergoing the milk exclusion diet and 25 age-matched healthy controls. The energy and nutritional value of diets were evaluated that included those components affecting skin condition; ie. vitamins A, D, E, B2 and C; minerals iron (Fe) and zinc (Zn); polyunsaturated fatty acids (PUFAs). The Dieta 5.0 programme was used for dietary assessment and outcomes were then related to dietary recommendations. There were no significant differences between groups in mean energy values and mean intakes of protein, fats and carbohydrates (p>0.05). The percentage of subjects with low energy value were 44% and 36% in respectively Groups I and II. Deficiencies of fat intake were observed in 60% in Group I and 44% in Group II. There were however no risks in the dietary intakes of protein, carbohydrate, vitamins A, B2 and C nor of Fe and Zn. Deficiencies of dietary intakes were observed in respectively Groups I and II in the following; vitamin E (24% vs 64%), vitamin D (36% vs 92%), linoleic acid (36% vs 72%), α-linolenic acid (36% vs 40%) and long chain PUFAs (96% in both groups). Ensuring recommended dietary supply of those nutrients affecting skin condition is required for both groups of children. Children with AD had better balanced diets in respect of the studied nutrients that may reflect the influence of continuous healthcare

  1. Challenges of Learning English in Australia towards Students Coming from Selected Southeast Asian Countries: Vietnam, Thailand and Indonesia

    Science.gov (United States)

    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…

  2. The Relationship Between Selected Subtests of the Detroit Tests of Learning Aptitude and Second Grade Reading Achievement.

    Science.gov (United States)

    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…

  3. Selected Lessons Learned through the ISS Design, Development, Assembly, and Operations: Applicability to International Cooperation for Standardization

    Science.gov (United States)

    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.

  4. Selective Activation of M4 Muscarinic Acetylcholine Receptors Reverses MK-801-Induced Behavioral Impairments and Enhances Associative Learning in Rodents

    Science.gov (United States)

    2015-01-01

    Positive allosteric modulators (PAMs) of the M4 muscarinic acetylcholine receptor (mAChR) represent a novel approach for the treatment of psychotic symptoms associated with schizophrenia and other neuropsychiatric disorders. We recently reported that the selective M4 PAM VU0152100 produced an antipsychotic drug-like profile in rodents after amphetamine challenge. Previous studies suggest that enhanced cholinergic activity may also improve cognitive function and reverse deficits observed with reduced signaling through the N-methyl-d-aspartate subtype of the glutamate receptor (NMDAR) in the central nervous system. Prior to this study, the M1 mAChR subtype was viewed as the primary candidate for these actions relative to the other mAChR subtypes. Here we describe the discovery of a novel M4 PAM, VU0467154, with enhanced in vitro potency and improved pharmacokinetic properties relative to other M4 PAMs, enabling a more extensive characterization of M4 actions in rodent models. We used VU0467154 to test the hypothesis that selective potentiation of M4 receptor signaling could ameliorate the behavioral, cognitive, and neurochemical impairments induced by the noncompetitive NMDAR antagonist MK-801. VU0467154 produced a robust dose-dependent reversal of MK-801-induced hyperlocomotion and deficits in preclinical models of associative learning and memory functions, including the touchscreen pairwise visual discrimination task in wild-type mice, but failed to reverse these stimulant-induced deficits in M4 KO mice. VU0467154 also enhanced the acquisition of both contextual and cue-mediated fear conditioning when administered alone in wild-type mice. These novel findings suggest that M4 PAMs may provide a strategy for addressing the more complex affective and cognitive disruptions associated with schizophrenia and other neuropsychiatric disorders. PMID:25137629

  5. The effects of area postrema lesions and selective vagotomy on motion-induced conditioned taste aversion

    Science.gov (United States)

    Fox, Robert A.; Sutton, R. L.; Mckenna, Susan

    1991-01-01

    Conditioned taste aversion (CTA) is one of several behaviors which was suggested as a putative measure of motion sickness in rats. A review is made of studies which used surgical disruption of area postrema or the vagus nerve to investigate whether CTA and vomiting induced by motion may depend on common neural pathways or structures. When the chemoreceptive function of the area postrema (AP) is destroyed by complete ablation, rats develop CTA and cats and monkeys develop CTA and vomit. Thus the AP is not crucially involved in either CTA or vomiting induced by motion. However, after complete denervation of the stomach or after labyrinthectomy rats do not develop CTA when motion is used as the unconditioned stimulus. Studies of brainstem projections of the vagus nerve, the area postrema, the periaqueductal grey, and the vestibular system are used as the basis for speculation about regions which could mediate both motion-induced vomiting and behavioral food aversion.

  6. Optimization and Performance Study of Select Heating Ventilation and Air Conditioning Technologies for Commercial Buildings

    Science.gov (United States)

    Kamal, Rajeev

    Buildings contribute a significant part to the electricity demand profile and peak demand for the electrical utilities. The addition of renewable energy generation adds additional variability and uncertainty to the power system. Demand side management in the buildings can help improve the demand profile for the utilities by shifting some of the demand from peak to off-peak times. Heating, ventilation and air-conditioning contribute around 45% to the overall demand of a building. This research studies two strategies for reducing the peak as well as shifting some demand from peak to off-peak periods in commercial buildings: 1. Use of gas heat pumps in place of electric heat pumps, and 2. Shifting demand for air conditioning from peak to off-peak by thermal energy storage in chilled water and ice. The first part of this study evaluates the field performance of gas engine-driven heat pumps (GEHP) tested in a commercial building in Florida. Four GEHP units of 8 Tons of Refrigeration (TR) capacity each providing air-conditioning to seven thermal zones in a commercial building, were instrumented for measuring their performance. The operation of these GEHPs was recorded for ten months, analyzed and compared with prior results reported in the literature. The instantaneous COPunit of these systems varied from 0.1 to 1.4 during typical summer week operation. The COP was low because the gas engines for the heat pumps were being used for loads that were much lower than design capacity which resulted in much lower efficiencies than expected. The performance of equivalent electric heat pump was simulated from a building energy model developed to mimic the measured building loads. An economic comparison of GEHPs and conventional electrical heat pumps was done based on the measured and simulated results. The average performance of the GEHP units was estimated to lie between those of EER-9.2 and EER-11.8 systems. The performance of GEHP systems suffers due to lower efficiency at

  7. Influence of bovine lactoferrin on the growth of selected probiotic bacteria under aerobic conditions.

    Science.gov (United States)

    Chen, Po-Wen; Ku, Yu-We; Chu, Fang-Yi

    2014-10-01

    Bovine lactoferrin (bLf) is a natural glycoprotein, and it shows broad-spectrum antimicrobial activity. However, reports on the influences of bLf on probiotic bacteria have been mixed. We examined the effects of apo-bLf (between 0.25 and 128 mg/mL) on both aerobic and anaerobic cultures of probiotics. We found that bLf had similar effects on the growth of probiotics under aerobic or anaerobic conditions, and that it actively and significantly (at concentrations of >0.25 mg/mL) retarded the growth rate of Bifidobacterium bifidum (ATCC 29521), B. longum (ATCC 15707), B. lactis (BCRC 17394), B. infantis (ATCC 15697), Lactobacillus reuteri (ATCC 23272), L. rhamnosus (ATCC 53103), and L. coryniformis (ATCC 25602) in a dose-dependent manner. Otherwise, minimal inhibitory concentrations (MICs) were 128 or >128 mg/mL against B. bifidum, B. longum, B. lactis, L. reuteri, and L. rhamnosus (ATCC 53103). With regard to MICs, bLf showed at least four-fold lower inhibitory effect on probiotics than on pathogens. Intriguingly, bLf (>0.25 mg/mL) significantly enhanced the growth of Rhamnosus (ATCC 7469) and L. acidophilus (BCRC 14065) by approximately 40-200 %, during their late periods of growth. Supernatants produced from aerobic but not anaerobic cultures of L. acidophilus reduced the growth of Escherichia coli by about 20 %. Thus, bLf displayed a dose-dependent inhibitory effect on the growth of most probiotic strains under either aerobic or anaerobic conditions. An antibacterial supernatant prepared from the aerobic cultures may have significant practical use.

  8. Microcultures and Informal Learning: A Heuristic Guiding Analysis of Conditions for Informal Learning in Local Higher Education Workplaces

    Science.gov (United States)

    Roxå, Torgny; Mårtensson, Katarina

    2015-01-01

    This article contributes to knowledge about learning in workgroups, so called "microcultures" in higher education. It argues that socially constructed and institutionalised traditions, recurrent practices, and tacit assumptions in the various microcultures influence academic teachers towards certain behaviour. In line with this…

  9. Determination of laser cutting process conditions using the preference selection index method

    Science.gov (United States)

    Madić, Miloš; Antucheviciene, Jurgita; Radovanović, Miroslav; Petković, Dušan

    2017-03-01

    Determination of adequate parameter settings for improvement of multiple quality and productivity characteristics at the same time is of great practical importance in laser cutting. This paper discusses the application of the preference selection index (PSI) method for discrete optimization of the CO2 laser cutting of stainless steel. The main motivation for application of the PSI method is that it represents an almost unexplored multi-criteria decision making (MCDM) method, and moreover, this method does not require assessment of the considered criteria relative significances. After reviewing and comparing the existing approaches for determination of laser cutting parameter settings, the application of the PSI method was explained in detail. Experiment realization was conducted by using Taguchi's L27 orthogonal array. Roughness of the cut surface, heat affected zone (HAZ), kerf width and material removal rate (MRR) were considered as optimization criteria. The proposed methodology is found to be very useful in real manufacturing environment since it involves simple calculations which are easy to understand and implement. However, while applying the PSI method it was observed that it can not be useful in situations where there exist a large number of alternatives which have attribute values (performances) very close to those which are preferred.

  10. Selective attention affects implicit and explicit memory for familiar pictures at different delay conditions.

    Science.gov (United States)

    Ballesteros, Soledad; Reales, José M; García, Eulalio; Carrasco, Marisa

    2006-02-01

    Three experiments investigated the effects of two variables -selective attention during encoding and delay between study and test- on implicit (picture fragment completion and object naming) and explicit (free recall and recognition) memory tests. Experiments 1 and 2 consistently indicated that (a) at all delays (immediate to 1 month), picture-fragment identification threshold was lower for the attended than the unattended pictures; (b) the attended pictures were recalled and recognized better than the unattended; and (c) attention and delay interacted in both memory tests. For implicit memory, performance decreased as delay increased for both attended and unattended pictures, but priming was more pronounced and lasted longer for the attended pictures; it was still present after a 1-month delay. For explicit memory, performance decreased as delay increased for attended pictures, but for unattended pictures performance was consistent throughout delay. By using a perceptual object naming task, Experiment 3 showed reliable implicit and explicit memory for attended but not for unattended pictures. This study indicates that picture repetition priming requires attention at the time of study and that neither delay nor attention dissociate performance in explicit and implicit memory tests; both types of memory require attention, but explicit memory does so to a larger degree.

  11. Diatom diet selectivity by early post-larval abalone Haliotis diversicolor supertexta under hatchery conditions

    Science.gov (United States)

    Zhang, Yuyu; Gao, Yahui; Liang, Junrong; Chen, Changping; Zhao, Donghai; Li, Xuesong; Li, Yang; Wu, Wenzhong

    2010-11-01

    Benthic diatoms constitute the primary diet of abalone during their early stages of development. To evaluate the dietary preferences of early post-larval abalone, Haliotis diversicolor supertexta, we analyzed the gut contents of post-larvae that settled on diatom films. We compared the abundance and species diversity of diatom assemblages in the gut to those of the epiphytic diatom assemblages on the attachment films, and identified 40 benthic diatom species in the gut contents of post-larvae 12 to 24 d after settlement. The most abundant taxa in the gut contents were Navicula spp., Amphora copulate, and Amphora coffeaeformis. Navicula spp. accounted for 64.0% of the cell density. In the attachment films, we identified 110 diatom species belonging to 38 genera. Pennate diatoms were the dominant members including the species Amphiprora alata, Cocconeis placentula var. euglypta, Cylindrotheca closterium, Navicula sp. 2, and A. coffeaeformis. Nano-diatoms (abalone seed. The difference of the composition and abundance of diatoms between in the guts and on the biofilms suggests that early post-larval grazing was selective. An early post-larval abalone preferred nano-diatoms and the genera Navicula and Amphora during the month after settlement.

  12. Efficient generation of long-distance conditional alleles using recombineering and a dual selection strategy in replicate plates

    Directory of Open Access Journals (Sweden)

    Liang Hong-Erh

    2009-07-01

    Full Text Available Abstract Background Conditional knockout mice are a useful tool to study the function of gene products in a tissue-specific or inducible manner. Classical approaches to generate targeting vectors for conditional alleles are often limited by the availability of suitable restriction sites. Furthermore, plasmid-based targeting vectors can only cover a few kB of DNA which precludes the generation of targeting vectors where the two loxP sites are placed far apart. These limitations have been overcome in the recent past by using homologous recombination of bacterial artificial chromosomes (BACs in Escherichia coli to produce large targeting vector containing two different loxP-flanked selection cassettes so that a single targeting event is sufficient to introduce loxP-sites a great distances into the mouse genome. However, the final targeted allele should be free of selection cassettes and screening for correct removal of selection cassettes can be a laborious task. Therefore, we developed a new strategy to rapidly identify ES cells containing the desired allele. Results Using BAC recombineering we generated a single targeting vector which contained two different selection cassettes that were flanked by loxP-loxP sites or by FRT-FRT/loxP sites so that they could be deleted sequentially by Cre- and FLPe-recombinases, respectively. Transfected ES cells were first selected in the presence of both antibiotics in vitro before correctly targeted clones were identified by Southern blot. After transfection of a Cre recombinase expression plasmid ES cell clones were selected on replicate plates to identify those clones which maintained the FRT-FRT/loxP flanked cassette and lost the loxP-loxP flanked cassette. Using this strategy facilitated the identification of ES cell clones containing the desired allele before blastocyst injection. Conclusion The strategy of ES cell cultures in replicate plates proved to be very efficient in identifying ES cells that had

  13. Protection measures for selected ITER magnet system off-normal conditions

    International Nuclear Information System (INIS)

    Yoshida, K.; Iida, F.; Gallix, R.; Britousov, N.; Mitchell, N.; Thome, R.J.

    1998-01-01

    The International Thermonuclear Experimental Reactor (ITER) magnet systems provide the magnetic field intensity and field geometry to contain and control plasma during the various phases of pulsed operation. During these pulses, the toroidal field (TF) coils operate with a constant current. The central solenoid (CS) and poloidal field (PF) coils, on the other hand, are each independently powered. The maximum terminal voltages during plasma operation and protective discharges are 15 kV for CS and 10 kV for TF and PF. The energy stored in the 20 TF coil system is 103 GJ; in each of the other coils it is approximately 10 GJ or less. This paper describes the protection requirements and selected design concepts being considered for the large superconducting coils for the ITER. Ground faults, short circuits and helium leaks are the major serious accidents to be prevented in the coils. All coils use a solid insulation system to avoid ground faults. The electrical circuits including coil and power supply are grounded through resistors that limit current in the event of a ground fault. In the case of a short circuit within the coil winding, a large energy would be dissipated close to the small shorted volume. The impact of the short circuit can be reduced by using a potential screen. Inside the cryostat, helium leakage is most likely at the electrical insulating breaks in the cryogenic cooling lines between the coils and helium manifolds. A double containment (metallic shield and glass-epoxy) is therefore provided for the insulation breaks to allow for the detection of small leaks and to limit the spread of helium to other locations. (orig.)

  14. Functional traits of selected mangrove species in Brazil as biological indicators of different environmental conditions

    Energy Technology Data Exchange (ETDEWEB)

    Arrivabene, Hiulana Pereira [Universidade Federal do Espírito Santo, Centro de Ciências Humanas e Naturais, Departamento de Ciências Biológicas, 29075-910 Vitória, Espírito Santo (Brazil); Souza, Iara [Universidade Federal de São Carlos, Centro de Ciências Biológicas e da Saúde, Departamento de Ciências Fisiológicas, 13565-905 São Carlos (Brazil); Có, Walter Luiz Oliveira [Associação Educational de Vitória, Departamento de Biologia, 29053-360 Vitória (Brazil); Rodella, Roberto Antônio [Universidade Estadual Paulista Júlio de Mesquita Filho, Campus de Botucatu, Instituto de Biociências, Departamento de Botânica, C. Postal 510, 18618-000 Botucatu, São Paulo (Brazil); Wunderlin, Daniel Alberto, E-mail: dwunder@fcq.unc.edu.ar [Instituto de Ciencia y Tecnología de Alimentos Córdoba (ICYTAC), CONICET, Dpto. Qca. Orgánica, Fac. Cs. Químicas, Universidad Nacional de Córdoba, Ciudad Universitaria, 5000, Córdoba (Argentina); and others

    2014-04-01

    Ecological studies on phenotypic plasticity illustrate the relevance of this phenomenon in nature. Conditions of biota reflect environmental changes, highlighting the adaptability of resident species that can be used as bioindicators of such changes. We report the morpho-anatomical plasticity of leaves of Avicennia schaueriana Stapf and Leechm. ex Moldenke, Laguncularia racemosa (L.) C.F.Gaertn. and Rhizophora mangle L., evaluated in three estuaries (Vitória bay, Santa Cruz and Itaúnas River; state of Espírito Santo, Brazil), considering five areas of mangrove ecosystems with diverse environmental issues. Two sampling sites are part of the Ecological Station Lameirão Island in Vitória bay, close to a harbor. A third sampling site in Cariacica (Vitória bay) is inside the Vitória harbor and also is influenced by domestic sewage. The fourth studied area (Santa Cruz) is part of Piraquê Mangrove Ecological Reservation, while the fifth (Itaúnas River) is a small mangrove, with sandy sediment and greater photosynthetically active radiation, also not strongly influenced by anthropic activity. Results pointed out the morpho-anatomical plasticity in studied species, showing that A. schaueriana and L. racemosa might be considered the most appropriate bioindicators to indicate different settings and environmental conditions. Particularly, the dry mass per leaf area (LMA) of A. schaueriana was the main biomarker measured. In our study, LMA of A. schaueriana was positively correlated with salinity (Spearman 0.71), Mn content (0.81) and pH (0.82) but negatively correlated with phosphorus content (− 0.63). Thus, the evaluation of modification in LMA of A. schaueriana pointed out changes among five studied sites, suggesting its use to reflect changes in the environment, which could be also useful in the future to evaluate the climate change. - Highlights: • We investigated adaptive modifications in plants in response to differences among three estuaries. • We used

  15. Functional traits of selected mangrove species in Brazil as biological indicators of different environmental conditions

    International Nuclear Information System (INIS)

    Arrivabene, Hiulana Pereira; Souza, Iara; Có, Walter Luiz Oliveira; Rodella, Roberto Antônio; Wunderlin, Daniel Alberto

    2014-01-01

    Ecological studies on phenotypic plasticity illustrate the relevance of this phenomenon in nature. Conditions of biota reflect environmental changes, highlighting the adaptability of resident species that can be used as bioindicators of such changes. We report the morpho-anatomical plasticity of leaves of Avicennia schaueriana Stapf and Leechm. ex Moldenke, Laguncularia racemosa (L.) C.F.Gaertn. and Rhizophora mangle L., evaluated in three estuaries (Vitória bay, Santa Cruz and Itaúnas River; state of Espírito Santo, Brazil), considering five areas of mangrove ecosystems with diverse environmental issues. Two sampling sites are part of the Ecological Station Lameirão Island in Vitória bay, close to a harbor. A third sampling site in Cariacica (Vitória bay) is inside the Vitória harbor and also is influenced by domestic sewage. The fourth studied area (Santa Cruz) is part of Piraquê Mangrove Ecological Reservation, while the fifth (Itaúnas River) is a small mangrove, with sandy sediment and greater photosynthetically active radiation, also not strongly influenced by anthropic activity. Results pointed out the morpho-anatomical plasticity in studied species, showing that A. schaueriana and L. racemosa might be considered the most appropriate bioindicators to indicate different settings and environmental conditions. Particularly, the dry mass per leaf area (LMA) of A. schaueriana was the main biomarker measured. In our study, LMA of A. schaueriana was positively correlated with salinity (Spearman 0.71), Mn content (0.81) and pH (0.82) but negatively correlated with phosphorus content (− 0.63). Thus, the evaluation of modification in LMA of A. schaueriana pointed out changes among five studied sites, suggesting its use to reflect changes in the environment, which could be also useful in the future to evaluate the climate change. - Highlights: • We investigated adaptive modifications in plants in response to differences among three estuaries. • We used

  16. Lack of effect of Pitressin on the learning ability of Brattleboro rats with diabetes insipidus using positively reinforced operant conditioning.

    Science.gov (United States)

    Laycock, J F; Gartside, I B

    1985-08-01

    Brattleboro rats with hereditary hypothalamic diabetes insipidus (BDI) received daily subcutaneous injections of vasopressin in the form of Pitressin tannate (0.5 IU/24 hr). They were initially deprived of food and then trained to work for food reward in a Skinner box to a fixed ratio of ten presses for each pellet received. Once this schedule had been learned the rats were given a discrimination task daily for seven days. The performances of these BDI rats were compared with those of rats of the parent Long Evans (LE) strain receiving daily subcutaneous injections of vehicle (arachis oil). Comparisons were also made between these two groups of treated animals and untreated BDI and LE rats studied under similar conditions. In the initial learning trial, both control and Pitressin-treated BDI rats performed significantly better, and manifested less fear initially, than the control or vehicle-injected LE rats when first placed in the Skinner box. Once the initial task had been learned there was no marked difference in the discrimination learning between control or treated BDI and LE animals. These results support the view that vasopressin is not directly involved in all types of learning behaviour, particularly those involving positively reinforced operant conditioning.

  17. Optimum selection of solar collectors for a solar-driven ejector air conditioning system by experimental and simulation study

    International Nuclear Information System (INIS)

    Zhang Wei; Ma Xiaoli; Omer, S.A.; Riffat, S.B.

    2012-01-01

    Highlights: ► Three solar collectors have been compared to drive ejector air conditioning system. ► A simulation program was constructed to study the effect parameters. ► The outdoor test were conducted to validate the solar collector modeling. ► Simulation program was found to predict solar collector performance accurately. ► The optimal design of solar collector system was carried out. - Abstract: In this paper, three different solar collectors are selected to drive the solar ejector air conditioning system for Mediterranean climate. The performance of the three selected solar collector are evaluated by computer simulation and lab test. Computer model is incorporated with a set of heat balance equations being able to analyze heat transfer process occurring in separate regions of the collector. It is found simulation and test has a good agreement. By the analysis of the computer simulation and test result, the solar ejector cooling system using the evacuated tube collector with selective surface and high performance heat pipe can be most economical when operated at the optimum generating temperature of the ejector cooling machine.

  18. Task Experience as a Boundary Condition for the Negative Effects of Irrelevant Information on Learning

    NARCIS (Netherlands)

    G. Rop (Gertjan); M. van Wermeskerken (Margot); J.A. de Nooijer (Jacqueline); P.P.J.L. Verkoeijen (Peter); T.A.J.M. van Gog (Tamara)

    2016-01-01

    textabstractResearch on multimedia learning has shown that learning is hampered when a multimedia message includes extraneous information that is not relevant for the task, because processing the extraneous information uses up scarce attention and working memory resources. However, eye-tracking

  19. Task Experience as a Boundary Condition for the Negative Effects of Irrelevant Information on Learning

    Science.gov (United States)

    Rop, Gertjan; van Wermeskerken, Margot; de Nooijer, Jacqueline A.; Verkoeijen, Peter P. J. L.; van Gog, Tamara

    2018-01-01

    Research on multimedia learning has shown that learning is hampered when a multimedia message includes extraneous information that is not relevant for the task, because processing the extraneous information uses up scarce attention and working memory resources. However, eye-tracking research suggests that task experience might be a boundary…

  20. Simulating Conditions of Learned Helplessness: The Effects of Interventions and Attributions.

    Science.gov (United States)

    Donovan, Wilberta L.; Leavitt, Lewis A.

    1985-01-01

    Using a version of the "learned helplessness" paradigm, assesses mothers' performance on a solvable task following pretreatments that involved exposure to an infant cry but that differed in the mothers' ability to exert control over termination of the cry. Proposes that learned helplessness models are relevant to the study of…

  1. Deep Learning as an Individual, Conditional, and Contextual Influence on First-Year Student Outcomes

    Science.gov (United States)

    Reason, Robert D.; Cox, Bradley E.; McIntosh, Kadian; Terenzini, Patrick T.

    2010-01-01

    For years, educators have drawn a distinction between deep cognitive processing and surface-level cognitive processing, with the former resulting in greater learning. In recent years, researchers at NSSE have created DEEP Learning scales, which consist of items related to students' experiences which are believed to encourage deep processing. In…

  2. The role of conditioning, learning and dopamine in sexual behavior: a narrative review of animal and human studies.

    Science.gov (United States)

    Brom, Mirte; Both, Stephanie; Laan, Ellen; Everaerd, Walter; Spinhoven, Philip

    2014-01-01

    Many theories of human sexual behavior assume that sexual stimuli obtain arousing properties through associative learning processes. It is widely accepted that classical conditioning contributes to the etiology of both normal and maladaptive human behaviors. Despite the hypothesized importance of basic learning processes in sexual behavior, research on classical conditioning of the sexual response in humans is scarce. In the present paper, animal studies and studies in humans on the role of pavlovian conditioning on sexual responses are reviewed. Animal research shows robust, direct effects of conditioning processes on partner- and place preference. On the contrast, the empirical research with humans in this area is limited and earlier studies within this field are plagued by methodological confounds. Although recent experimental demonstrations of human sexual conditioning are neither numerous nor robust, sexual arousal showed to be conditionable in both men and women. The present paper serves to highlight the major empirical findings and to renew the insight in how stimuli can acquire sexually arousing value. Hereby also related neurobiological processes in reward learning are discussed. Finally, the connections between animal and human research on the conditionability of sexual responses are discussed, and suggestions for future directions in human research are given. Copyright © 2013 Elsevier Ltd. All rights reserved.

  3. Contextual Change After Fear Acquisition Affects Conditioned Responding and the Time Course of Extinction Learning-Implications for Renewal Research.

    Science.gov (United States)

    Sjouwerman, Rachel; Niehaus, Johanna; Lonsdorf, Tina B

    2015-01-01

    Context plays a central role in retrieving (fear) memories. Accordingly, context manipulations are inherent to most return of fear (ROF) paradigms (in particular renewal), involving contextual changes after fear extinction. Context changes are, however, also often embedded during earlier stages of ROF experiments such as context changes between fear acquisition and extinction (e.g., in ABC and ABA renewal). Previous studies using these paradigms have however focused exclusively on the context switch after extinction (i.e., renewal). Thus, the possibility of a general effect of context switch on conditioned responding that may not be conditional to preceding extinction learning remains unstudied. Hence, the current study investigated the impact of a context switch between fear acquisition and extinction on immediate conditioned responding and on the time-course of extinction learning by using a multimodal approach. A group that underwent contextual change after fear conditioning (AB; n = 36) was compared with a group without a contextual change from acquisition to extinction (AA; n = 149), while measuring physiological (skin conductance and fear potentiated startle) measures and subjective fear ratings. Contextual change between fear acquisition and extinction had a pronounced effect on both immediate conditioned responding and on the time course of extinction learning in skin conductance responses and subjective fear ratings. This may have important implications for the mechanisms underlying and the interpretation of the renewal effect (i.e., contextual switch after extinction). Consequently, future studies should incorporate designs and statistical tests that disentangle general effects of contextual change from genuine ROF effects.

  4. Characterization of site conditions for selected seismic stations in eastern part of Romania

    Science.gov (United States)

    Grecu, B.; Zaharia, B.; Diaconescu, M.; Bala, A.; Nastase, E.; Constantinescu, E.; Tataru, D.

    2018-02-01

    Strong motion data are essential for seismic hazard assessment. To correctly understand and use this kind of data is necessary to have a good knowledge of local site conditions. Romania has one of the largest strong motion networks in Europe with 134 real-time stations. In this work, we aim to do a comprehensive site characterization for eight of these stations located in the eastern part of Romania. We make use of a various seismological dataset and we perform ambient noise and earthquake-based investigations to estimate the background noise level, the resonance frequencies and amplification of each site. We also derive the Vs30 parameter from the surface shear-wave velocity profiles obtained through the inversion of the Rayleigh waves recorded in active seismic measurements. Our analyses indicate similar results for seven stations: high noise levels for frequencies larger than 1 Hz, well defined fundamental resonance at low frequencies (0.15-0.29 Hz), moderate amplification levels (up to 4 units) for frequencies between 0.15 and 5-7 Hz and same soil class (type C) according to the estimated Vs30 and Eurocode 8. In contrast, the eighth station for which the soil class is evaluated of type B exhibits a very good noise level for a wide range of frequencies (0.01-20 Hz), a broader fundamental resonance at high frequencies ( 8 Hz) and a flat amplification curve between 0.1 and 3-4 Hz.

  5. Characterization and selection of location for resistance to sugarcane brown rust disease under cuban conditions

    Directory of Open Access Journals (Sweden)

    Joaquín Montalván Delgado

    2016-01-01

    Full Text Available The sugarcane brown rust disease is caused by fungus Puccinia melanocephala Sydow & P. Sydow and it is one of the more importance diseases. The environment where the sugarcane is cultivated is constituted by numerous factors and its combination contributes to the formation of different development and production conditions, what influences in the varietal disease resistance. With the objective of to characterize and to define the resistance tests location to the brown rust disease were carried out experiments in 6 location of the country. Eleven varieties and six patterns were studied. The climatic variables were analyzed during the period in each location and they were carried out evaluations in different ages of the plant and number of the leaves. The quantity of pustules, long of the most frequent pustules, size of the biggest pustules and area per - centage occupied by pustules were evaluated. The data were analyzed statistically. Differential behavior of the locations and the importance of the relative humidity and the temperatures in the manifestation of the disease symptoms were proven. All the locations were important although similarity exists between Matanzas and Villa Clara and between Camagüey and Holguín. Mayabeque and Santiago de Cuba didn’t present similarity with any other one. These 6 locations can be used for the resistance tests and to define the progenitors’ Santiago de Cuba, Holguín, Villa Clara and Mayabeque

  6. Quantifying Projected Heat Mortality Impacts under 21st-Century Warming Conditions for Selected European Countries.

    Science.gov (United States)

    Kendrovski, Vladimir; Baccini, Michela; Martinez, Gerardo Sanchez; Wolf, Tanja; Paunovic, Elizabet; Menne, Bettina

    2017-07-05

    Under future warming conditions, high ambient temperatures will have a significant impact on population health in Europe. The aim of this paper is to quantify the possible future impact of heat on population mortality in European countries, under different climate change scenarios. We combined the heat-mortality function estimated from historical data with meteorological projections for the future time laps 2035-2064 and 2071-2099, developed under the Representative Concentration Pathways (RCP) 4.5 and 8.5. We calculated attributable deaths (AD) at the country level. Overall, the expected impacts will be much larger than the impacts we would observe if apparent temperatures would remain in the future at the observed historical levels. During the period 2071-2099, an overall excess of 46,690 and 117,333 AD per year is expected under the RCP 4.5 and RCP 8.5 scenarios respectively, in addition to the 16,303 AD estimated under the historical scenario. Mediterranean and Eastern European countries will be the most affected by heat, but a non-negligible impact will be still registered in North-continental countries. Policies and plans for heat mitigation and adaptation are needed and urgent in European countries in order to prevent the expected increase of heat-related deaths in the coming decades.

  7. Using Selective Redundancy and Testing to Optimize Learning from Multimedia Lessons

    OpenAIRE

    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...

  8. Utilization of Smartphones in Science Teaching and Learning in Selected Universities in Ghana

    Science.gov (United States)

    Twum, Rosemary

    2017-01-01

    This study was designed to examine the use of mobile phone, a widespread technology, and determined how this technology influences science students' learning. The study intended to examine the use of smartphones in science teaching and learning and propose of model in the use of smartphones for teaching and learning. The research design employed…

  9. Greeting You Online: Selecting Web-Based Conferencing Tools for Instruction in E-Learning Mode

    Science.gov (United States)

    Li, Judy

    2014-01-01

    Academic distance learning programs have gained popularity and added to the demand for online library services. Librarians are now conducting instruction for distance learning students beyond their traditional work. Technology advancements have enhanced the delivery mode in distance learning across academic disciplines. Online conference tools…

  10. Sensitive and selective culture medium for detection of environmental Clostridium difficile isolates without requirement for anaerobic culture conditions.

    Science.gov (United States)

    Cadnum, Jennifer L; Hurless, Kelly N; Deshpande, Abhishek; Nerandzic, Michelle M; Kundrapu, Sirisha; Donskey, Curtis J

    2014-09-01

    Effective and easy-to-use methods for detecting Clostridium difficile spore contamination would be useful for identifying environmental reservoirs and monitoring the effectiveness of room disinfection. Culture-based detection methods are sensitive for detecting C. difficile, but their utility is limited due to the requirement of anaerobic culture conditions and microbiological expertise. We developed a low-cost selective broth medium containing thioglycolic acid and l-cystine, termed C. difficile brucella broth with thioglycolic acid and l-cystine (CDBB-TC), for the detection of C. difficile from environmental specimens under aerobic culture conditions. The sensitivity and specificity of CDBB-TC (under aerobic culture conditions) were compared to those of CDBB (under anaerobic culture conditions) for the recovery of C. difficile from swabs collected from hospital room surfaces. CDBB-TC was significantly more sensitive than CDBB for recovering environmental C. difficile (36/41 [88%] versus 21/41 [51%], respectively; P = 0.006). C. difficile latex agglutination, an enzyme immunoassay for toxins A and B or glutamate dehydrogenase, and a PCR for toxin B genes were all effective as confirmatory tests. For 477 total environmental cultures, the specificity of CDBB-TC versus that of CDBB based upon false-positive yellow-color development of the medium without recovery of C. difficile was 100% (0 false-positive results) versus 96% (18 false-positive results), respectively. False-positive cultures for CDBB were attributable to the growth of anaerobic non-C. difficile organisms that did not grow in CDBB-TC. Our results suggest that CDBB-TC provides a sensitive and selective medium for the recovery of C. difficile organisms from environmental samples, without the need for anaerobic culture conditions. Copyright © 2014, American Society for Microbiology. All Rights Reserved.

  11. Neuropsychological characteristics of selective attention in children with nonverbal learning disabilities

    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.

  12. Properties, promotive and obstructive conditions of multi-professional teaching and learning of health professions and non-health professions: an explorative survey from the perspective of teachers.

    Science.gov (United States)

    Schmitz, Daniela; Höhmann, Ulrike

    2016-01-01

    Care for people with dementia is considered a multi-professional challenge that requires a collaborative approach between health professionals and non-health professionals. Didactic strategies to ensure the same qualifications across these occupational groups are lacking. This article presents the joint learning of selected properties and promotive and obstructive conditions, using the example of a multi-professional Master's programme. It subsequently draws conclusions for didactic concepts. The perceptions of 12 teachers on this Master's programme, all representing different professions, were determined by using a qualitative exploratory survey on the three stated dimensions. With the aid of a summarising content analysis, their statements were condensed and abstracted so as to deduce appropriate requirements for methodical and didactic learning scenarios. In view of the fact that the students have very varied previous knowledge, the main challenge is finding a balance between expertise and tediousness. Establishing essential and common expertise, as well as sensitivity for different perspectives, is made particularly difficult by the fact that health and non-health professions differ greatly in terms of methods and approaches. For a successful outcome, the content focal points and didactic and methodical concepts for a learning group need to take into account the composition of that specific group. Recourse to didactic standard concepts is only possible to a limited extent. The aim of joint teaching and learning of health and non-health professionals is to enhance the understanding of a profession: This is done by making individuals aware of their role in the chain of care, so they can recognise and organise the mutual conditionality of their own and external professional contributions.

  13. Germination conditions affect selected quality of composite wheat-germinated brown rice flour and bread formulations.

    Science.gov (United States)

    Charoenthaikij, Phantipha; Jangchud, Kamolwan; Jangchud, Anuvat; Prinyawiwatkul, Witoon; Tungtrakul, Patcharee

    2010-08-01

    Brown rice has been reported to be more nutritious after germination. Germinated brown rice flours (GBRFs) from different steeping conditions (in distilled water [DI, pH 6.8] or in a buffer solution [pH 3] for either 24 or 48 h at 35 degrees C) were evaluated in this study. GBRF obtained from brown rice steeped at pH 3 for 48 h contained the highest amount of free gamma aminobutyric acid (GABA; 67 mg/100 g flour). The composite flour (wheat-GBRF) at a ratio of 70 : 30 exhibited significantly lower peak viscosity (PV) (56.99 - 132.45 RVU) with higher alpha-amylase activity (SN = 696 - 1826) compared with those of wheat flour (control) (PV = 136.46 RVU and SN = 1976). Bread formulations, containing 30% GBRF, had lower loaf volume and greater hardness (P rice flour (BRF). Acceptability scores for aroma, taste, and flavor of breads prepared with or without GBRFs (30% substitution) were not significantly different, with the mean score ranging from 6.1 (like slightly) to 7 (like moderately). Among the bread formulations containing GBRF, the one with GBRF prepared after 24 h steeping at pH 3 had a slightly higher (though not significant) overall liking score (6.8). This study demonstrated that it is feasible to substitute wheat flour with up to 30% GBRF in bread formulation without negatively affecting sensory acceptance. Practical Application: Our previous study revealed that flours from germinated brown rice have better nutritional properties, particularly gamma-aminobutyric acid (GABA), than the nongerminated one. This study demonstrated feasibility of incorporating up to 30% germinated brown rice flour in a wheat bread formulation without negatively affecting sensory acceptance. In the current United States market, this type of bread may be sold as frozen bread which would have a longer shelf life. Further study is thus needed.

  14. Local-learning-based neuron selection for grasping gesture prediction in motor brain machine interfaces

    Science.gov (United States)

    Xu, Kai; Wang, Yiwen; Wang, Yueming; Wang, Fang; Hao, Yaoyao; Zhang, Shaomin; Zhang, Qiaosheng; Chen, Weidong; Zheng, Xiaoxiang

    2013-04-01

    Objective. The high-dimensional neural recordings bring computational challenges to movement decoding in motor brain machine interfaces (mBMI), especially for portable applications. However, not all recorded neural activities relate to the execution of a certain movement task. This paper proposes to use a local-learning-based method to perform neuron selection for the gesture prediction in a reaching and grasping task. Approach. Nonlinear neural activities are decomposed into a set of linear ones in a weighted feature space. A margin is defined to measure the distance between inter-class and intra-class neural patterns. The weights, reflecting the importance of neurons, are obtained by minimizing a margin-based exponential error function. To find the most dominant neurons in the task, 1-norm regularization is introduced to the objective function for sparse weights, where near-zero weights indicate irrelevant neurons. Main results. The signals of only 10 neurons out of 70 selected by the proposed method could achieve over 95% of the full recording's decoding accuracy of gesture predictions, no matter which different decoding methods are used (support vector machine and K-nearest neighbor). The temporal activities of the selected neurons show visually distinguishable patterns associated with various hand states. Compared with other algorithms, the proposed method can better eliminate the irrelevant neurons with near-zero weights and provides the important neuron subset with the best decoding performance in statistics. The weights of important neurons converge usually within 10-20 iterations. In addition, we study the temporal and spatial variation of neuron importance along a period of one and a half months in the same task. A high decoding performance can be maintained by updating the neuron subset. Significance. The proposed algorithm effectively ascertains the neuronal importance without assuming any coding model and provides a high performance with different

  15. Modeling heat stress effect on Holstein cows under hot and dry conditions: selection tools.

    Science.gov (United States)

    Carabaño, M J; Bachagha, K; Ramón, M; Díaz, C

    2014-12-01

    component, a constant term that is not affected by temperature, representing from 64% of the variation for SCS to 91% of the variation for milk. The second component, showing a flat pattern at intermediate temperatures and increasing or decreasing slopes for the extremes, gathered 15, 11, and 24% of the variation for fat and protein yield and SCS, respectively. This component could be further evaluated as a selection criterion for heat tolerance independently of the production level. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  16. Optimization, selection and feasibility study of solar parabolic trough power plants for Algerian conditions

    International Nuclear Information System (INIS)

    Boukelia, T.E.; Mecibah, M.S.; Kumar, B.N.; Reddy, K.S.

    2015-01-01

    Highlights: • Evaluation of solar resources in the absence of measured data. • Optimization of 2 PTSTPPs integrated with TES and FBS and using oil and salt as HTFs. • 4E comparative study of the two optimized plants alongside the Andasol 1 plant. • The salt plant resulting as the best one and has been chosen for the viability study. • Tamanrasset is the best location for construction of PTSTPPs. - Abstract: In the present study, optimization of two parabolic trough solar thermal power plants integrated with thermal energy storage (TES), and fuel backup system (FBS) has been performed. The first plant uses Therminol VP-1 as heat transfer fluid in the solar field and the second plant uses molten salt. The optimization is carried out with solar multiple (SM) and full load hours of TES as the parameters, with an objective of minimizing the levelized cost of electricity (LCOE) and maximizing the annual energy yield. A 4E (energy–exergy–environment–economic) comparison of the optimized plants alongside the Andasol 1 as reference plant is studied. The molten salt plant resulting as the best technology, from the optimization and 4E comparative study has been chosen for the viability analysis of ten locations in Algeria with semi-arid and arid climatic conditions. The results indicate that Andasol 1 reference plant has the highest mean annual energy efficiency (17.25%) and exergy efficiency (23.30%). Whereas, the highest capacity factor (54.60%) and power generation (236.90 GW h) are exhibited by the molten salt plant. The molten salt plant has least annual water usage of about 800,482 m 3 , but demands more land for the operation. Nevertheless the oil plant emits the lowest amount of CO 2 gas (less than 40.3 kilo tonnes). From the economic viewpoint, molten salt seems to be the best technology compared to other plants due to its lowest investment cost (less than 360 million dollars) and lower levelized cost of electricity (LCOE) (8.48 ¢/kW h). The

  17. The use of EMG biofeedback for learning of selective activation of intra-muscular parts within the serratus anterior muscle

    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

  18. Identifying Chronic Conditions and Other Selected Factors That Motivate Physical Activity in World Senior Games Participants and the General Population.

    Science.gov (United States)

    Merrill, Ray M; Bowen, Elise; Hager, Ron L

    2015-01-01

    This study assesses chronic disease or disease-related conditions as motivators of physical activity. It also compares these and other motivators of physical activity between Senior Games participants (SGPs) and the general population. Analyses are based on an anonymous cross-sectional survey conducted among 666 SGPs and 177 individuals from the general population. SGPs experienced better general health and less obesity, diabetes, and depression, as well as an average of 14.7 more years of regular physical activity ( p mental health in the present, to prevent physical and cognitive decline in the future, and to increase social opportunities. The Senior Games reinforces extrinsic motivators to positively influence intrinsic promoters such as skill development, satisfaction of learning, enjoyment, and fun.

  19. Diet, Prey Selection, and Body Condition of Age-0 Delta Smelt, Hypomesus transpacificus, in the Upper San Francisco Estuary

    Directory of Open Access Journals (Sweden)

    Steven B. Slater

    2014-09-01

    Full Text Available Steven B. Slater and Randall D. Baxterdoi: http://dx.doi.org/10.15447/sfews.2014v12iss3art1The Delta Smelt, an endangered fish, has suffered a long-term decline in abundance, believed to result from, in part, to changes in the pelagic food web of the upper San Francisco Estuary. To investigate the current role of food as a factor in Delta Smelt well-being, we developed reference criteria for gut fullness and body condition based on allometric growth. We then examined monthly diet, prey selectivity, and gut fullness of larvae and juvenile Delta Smelt collected April through September in 2005 and 2006 for evidence of feeding difficulties leading to reduced body condition. Calanoid copepods Eurytemora affinis and Pseudodiaptomus forbesi remained major food items during spring and from early summer through fall, respectively. Other much larger copepods and macroinvertebrates contributed in lesser numbers to the diet of older juvenile fish from mid-summer through fall. In fall, juvenile Delta Smelt periodically relied heavily on very small prey and prey potentially associated with demersal habitat, suggesting typical pelagic food items were in short supply. We found a strong positive selection for E. affinis and P. forbesi, neutral to negative selection for evasive calanoid Sinocalanus doerrii, and neutral to negative selection for the small cyclopoid copepod Limnoithona tetraspina and copepod nauplii, which were consumed only when extremely numerous in the environment. Feeding incidence was significantly higher in 2006, but among successfully feeding fish we found no between year difference in gut fullness. However, we did detect differences in fullness across months in both years. We found no difference in body condition of Delta Smelt between years yet our sample sizes were low in September when Delta Smelt reverted to feeding on very small organisms and fullness declined, so the longer-term effect remains unknown. Our findings suggest that: Delta

  20. Radiological Conditions in Selected Areas of Southern Iraq with Residues of Depleted Uranium. Report by an International Group of Experts

    International Nuclear Information System (INIS)

    2010-01-01

    This publication describes the methods, assumptions and parameters used by the IAEA during the assessment of the post-conflict radiological conditions of the environment and populations in relation to the residues of depleted uranium munitions from 2003 that exist at four selected areas in southern Iraq. The studies conducted by the IAEA used the results of measurements provided by UNEP from the 2006-2007 environmental monitoring campaigns performed by the Iraqi Ministry for the Environment. It presents the data used, the results of the assessment, and the findings and conclusions in connection therewith.

  1. The Relationship Between the Learning Style Perceptual Preferences of Urban Fourth Grade Children and the Acquisition of Selected Physical Science Concepts Through Learning Cycle Instructional Methodology.

    Science.gov (United States)

    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

  2. Lexical selection in the semantically blocked cyclic naming task: The role of cognitive control and learning

    Directory of Open Access Journals (Sweden)

    Jason E. Crowther

    2014-01-01

    Full Text Available Studies of semantic interference in language production have provided evidence for a role of cognitive control mechanisms in regulating the activation of semantic competitors during naming. The present study investigated the relationship between individual differences in cognitive control abilities, for both younger and older adults, and the degree of semantic interference in a blocked cyclic naming task. We predicted that individuals with lower working memory capacity (as measured by word span, lesser ability to inhibit distracting responses (as measured by Stroop interference, and a lesser ability to resolve proactive interference (as measured by a recent negatives task would show a greater increase in semantic interference in naming, with effects being larger for older adults. Instead, measures of cognitive control were found to relate to specific indices of semantic interference in the naming task, rather than overall degree of semantic interference, and few interactions with age were found, with younger and older adults performing similarly. The increase in naming latencies across naming trials within a cycle were negatively correlated with word span for both related and unrelated conditions, suggesting a strategy of narrowing response alternatives based upon memory for the set of item names. Evidence for a role of inhibition in response selection was obtained, as Stroop interference correlated positively with the change in naming latencies across cycles for the related, but not unrelated, condition. In contrast, recent negatives interference correlated negatively with the change in naming latencies across unrelated cycles, suggesting that individual differences in this tap the degree of strengthening of links in a lexical network based upon prior exposure. Results are discussed in terms of current models of lexical selection and consequences for word retrieval in more naturalistic production.

  3. Selection of micro-organisms and fermentation conditions of oil palm empty fruit bunch (EFB) and palm press fibre (PPF)

    International Nuclear Information System (INIS)

    Mat Rasol Awang; Hassan Hamdani Mutaat; Tamikazu Kume; Hitoshi Ito

    1998-01-01

    The selection of useful microorganisms was made by trial cultivation of various cellulolytic fungi on EFB and PPF. Several fermentation conditions were performed involving adjusting alkali treatment conditions, pH, changing media composition and preparation technique of solid culture media. Basic the preparation of the solid culture media was made by dissolving inorganic salts together with micro-nutrients and then added to the alkali treated EFB and PPF. In the cultivation of mushrooms, the preparation of solid culture media was adopted from mushroom growers technique. The criteria of a good degradation ability of fungi were evaluated based on the percentage of crude fibre degradation of EFB and PPF by fungi. The nutritional values of the products such as protein was also characterised

  4. Expectancy bias in a selective conditioning procedure: trait anxiety increases the threat value of a blocked stimulus.

    Science.gov (United States)

    Boddez, Yannick; Vervliet, Bram; Baeyens, Frank; Lauwers, Stephanie; Hermans, Dirk; Beckers, Tom

    2012-06-01

    In a blocking procedure, a single conditioned stimulus (CS) is paired with an unconditioned stimulus (US), such as electric shock, in the first stage. During the subsequent stage, the CS is presented together with a second CS and this compound is followed by the same US. Fear conditioning studies in non-human animals have demonstrated that fear responding to the added second CS typically remains low, despite its being paired with the US. Accordingly, the blocking procedure is well suited as a laboratory model for studying (deficits in) selective threat appraisal. The present study tested the relation between trait anxiety and blocking in human aversive conditioning. Healthy participants filled in a trait anxiety questionnaire and underwent blocking treatment in the human aversive conditioning paradigm. Threat appraisal was measured through shock expectancy ratings and skin conductance. As hypothesized, trait anxiety was positively associated with shock expectancy ratings to the blocked stimulus. In skin conductance responding, no significant effects of stimulus type could be detected during blocking training or testing. The current study does not allow strong claims to be made regarding the theoretical process underlying the expectancy bias we observed. The observed shock expectancy bias might be one of the mechanisms leading to non-specific fear in individuals at risk for developing anxiety disorders. A deficit in blocking, or a deficit in selective threat appraisal at the more general level, indeed results in fear becoming non-specific and disconnected from the most likely causes or predictors of danger. Copyright © 2011 Elsevier Ltd. All rights reserved.

  5. Selecting boundary conditions in physiological strain analysis of the femur: Balanced loads, inertia relief method and follower load.

    Science.gov (United States)

    Heyland, Mark; Trepczynski, Adam; Duda, Georg N; Zehn, Manfred; Schaser, Klaus-Dieter; Märdian, Sven

    2015-12-01

    Selection of boundary constraints may influence amount and distribution of loads. The purpose of this study is to analyze the potential of inertia relief and follower load to maintain the effects of musculoskeletal loads even under large deflections in patient specific finite element models of intact or fractured bone compared to empiric boundary constraints which have been shown to lead to physiological displacements and surface strains. The goal is to elucidate the use of boundary conditions in strain analyses of bones. Finite element models of the intact femur and a model of clinically relevant fracture stabilization by locking plate fixation were analyzed with normal walking loading conditions for different boundary conditions, specifically re-balanced loading, inertia relief and follower load. Peak principal cortex surface strains for different boundary conditions are consistent (maximum deviation 13.7%) except for inertia relief without force balancing (maximum deviation 108.4%). Influence of follower load on displacements increases with higher deflection in fracture model (from 3% to 7% for force balanced model). For load balanced models, follower load had only minor influence, though the effect increases strongly with higher deflection. Conventional constraints of fixed nodes in space should be carefully reconsidered because their type and position are challenging to justify and for their potential to introduce relevant non-physiological reaction forces. Inertia relief provides an alternative method which yields physiological strain results. Copyright © 2015 IPEM. Published by Elsevier Ltd. All rights reserved.

  6. Learning classifier systems with memory condition to solve non-Markov problems

    OpenAIRE

    Zang, Zhaoxiang; Li, Dehua; Wang, Junying

    2012-01-01

    In the family of Learning Classifier Systems, the classifier system XCS has been successfully used for many applications. However, the standard XCS has no memory mechanism and can only learn optimal policy in Markov environments, where the optimal action is determined solely by the state of current sensory input. In practice, most environments are partially observable environments on agent's sensation, which are also known as non-Markov environments. Within these environments, XCS either fail...

  7. Expatriate’s and Host Country National’s Professional Learning in Adverse Conditions

    DEFF Research Database (Denmark)

    Romani, Laurence; Lorenzen, Julie; Holck, Lotte

    important professional learning, which leads them to become better officers once back in Denmark. This contribution, based on a qualitative case study, intends to elicit this unexpected finding and to contribute to further theory development in expatriate adjustment literature. In the present case, no cross-cultural....... This case provides an example of how an environment perceived as foreign and undesirable turns out to be beneficial for individual learning...

  8. Exploring the Metabolic and Perceptual Correlates of Self-Selected Walking Speed under Constrained and Un-Constrained Conditions

    Directory of Open Access Journals (Sweden)

    David T Godsiff, Shelly Coe, Charlotte Elsworth-Edelsten, Johnny Collett, Ken Howells, Martyn Morris, Helen Dawes

    2018-03-01

    Full Text Available Mechanisms underpinning self-selected walking speed (SSWS are poorly understood. The present study investigated the extent to which SSWS is related to metabolism, energy cost, and/or perceptual parameters during both normal and artificially constrained walking. Fourteen participants with no pathology affecting gait were tested under standard conditions. Subjects walked on a motorized treadmill at speeds derived from their SSWS as a continuous protocol. RPE scores (CR10 and expired air to calculate energy cost (J.kg-1.m-1 and carbohydrate (CHO oxidation rate (J.kg-1.min-1 were collected during minutes 3-4 at each speed. Eight individuals were re-tested under the same conditions within one week with a hip and knee-brace to immobilize their right leg. Deflection in RPE scores (CR10 and CHO oxidation rate (J.kg-1.min-1 were not related to SSWS (five and three people had deflections in the defined range of SSWS in constrained and unconstrained conditions, respectively (p > 0.05. Constrained walking elicited a higher energy cost (J.kg-1.m-1 and slower SSWS (p 0.05. SSWS did not occur at a minimum energy cost (J.kg-1.m-1 in either condition, however, the size of the minimum energy cost to SSWS disparity was the same (Froude {Fr} = 0.09 in both conditions (p = 0.36. Perceptions of exertion can modify walking patterns and therefore SSWS and metabolism/ energy cost are not directly related. Strategies which minimize perceived exertion may enable faster walking in people with altered gait as our findings indicate they should self-optimize to the same extent under different conditions.

  9. Successive and discrete spaced conditioning in active avoidance learning in young and aged zebrafish.

    Science.gov (United States)

    Yang, Peng; Kajiwara, Riki; Tonoki, Ayako; Itoh, Motoyuki

    2018-05-01

    We designed an automated device to study active avoidance learning abilities of zebrafish. Open source tools were used for the device control, statistical computing, and graphic outputs of data. Using the system, we developed active avoidance tests to examine the effects of trial spacing and aging on learning. Seven-month-old fish showed stronger avoidance behavior as measured by color preference index with discrete spaced training as compared to successive spaced training. Fifteen-month-old fish showed a similar trend, but with reduced cognitive abilities compared with 7-month-old fish. Further, in 7-month-old fish, an increase in learning ability during trials was observed with discrete, but not successive, spaced training. In contrast, 15-month-old fish did not show increase in learning ability during trials. Therefore, these data suggest that discrete spacing is more effective for learning than successive spacing, with the zebrafish active avoidance paradigm, and that the time course analysis of active avoidance using discrete spaced training is useful to detect age-related learning impairment. Copyright © 2017 Elsevier Ireland Ltd and Japan Neuroscience Society. All rights reserved.

  10. Duration of the Unconditioned Stimulus in Appetitive Conditioning of Honeybees Differentially Impacts Learning, Long-Term Memory Strength, and the Underlying Protein Synthesis

    Science.gov (United States)

    Marter, Kathrin; Grauel, M. Katharina; Lewa, Carmen; Morgenstern, Laura; Buckemüller, Christina; Heufelder, Karin; Ganz, Marion; Eisenhardt, Dorothea

    2014-01-01

    This study examines the role of stimulus duration in learning and memory formation of honeybees ("Apis mellifera"). In classical appetitive conditioning honeybees learn the association between an initially neutral, conditioned stimulus (CS) and the occurrence of a meaningful stimulus, the unconditioned stimulus (US). Thereby the CS…

  11. Deep learning for digital pathology image analysis: A comprehensive tutorial with selected use cases.

    Science.gov (United States)

    Janowczyk, Andrew; Madabhushi, Anant

    2016-01-01

    Deep learning (DL) is a representation learning approach ideally suited for image analysis challenges in digital pathology (DP). The variety of image analysis tasks in the context of DP includes detection and counting (e.g., mitotic events), segmentation (e.g., nuclei), and tissue classification (e.g., cancerous vs. non-cancerous). Unfortunately, issues with slide preparation, variations in staining and scanning across sites, and vendor platforms, as well as biological variance, such as the presentation of different grades of disease, make these image analysis tasks particularly challenging. Traditional approaches, wherein domain-specific cues are manually identified and developed into task-specific "handcrafted" features, can require extensive tuning to accommodate these variances. However, DL takes a more domain agnostic approach combining both feature discovery and implementation to maximally discriminate between the classes of interest. While DL approaches have performed well in a few DP related image analysis tasks, such as detection and tissue classification, the currently available open source tools and tutorials do not provide guidance on challenges such as (a) selecting appropriate magnification, (b) managing errors in annotations in the training (or learning) dataset, and (c) identifying a suitable training set containing information rich exemplars. These foundational concepts, which are needed to successfully translate the DL paradigm to DP tasks, are non-trivial for (i) DL experts with minimal digital histology experience, and (ii) DP and image processing experts with minimal DL experience, to derive on their own, thus meriting a dedicated tutorial. This paper investigates these concepts through seven unique DP tasks as use cases to elucidate techniques needed to produce comparable, and in many cases, superior to results from the state-of-the-art hand-crafted feature-based classification approaches. Specifically, in this tutorial on DL for DP image

  12. Deep learning for digital pathology image analysis: A comprehensive tutorial with selected use cases

    Directory of Open Access Journals (Sweden)

    Andrew Janowczyk

    2016-01-01

    Full Text Available Background: Deep learning (DL is a representation learning approach ideally suited for image analysis challenges in digital pathology (DP. The variety of image analysis tasks in the context of DP includes detection and counting (e.g., mitotic events, segmentation (e.g., nuclei, and tissue classification (e.g., cancerous vs. non-cancerous. Unfortunately, issues with slide preparation, variations in staining and scanning across sites, and vendor platforms, as well as biological variance, such as the presentation of different grades of disease, make these image analysis tasks particularly challenging. Traditional approaches, wherein domain-specific cues are manually identified and developed into task-specific "handcrafted" features, can require extensive tuning to accommodate these variances. However, DL takes a more domain agnostic approach combining both feature discovery and implementation to maximally discriminate between the classes of interest. While DL approaches have performed well in a few DP related image analysis tasks, such as detection and tissue classification, the currently available open source tools and tutorials do not provide guidance on challenges such as (a selecting appropriate magnification, (b managing errors in annotations in the training (or learning dataset, and (c identifying a suitable training set containing information rich exemplars. These foundational concepts, which are needed to successfully translate the DL paradigm to DP tasks, are non-trivial for (i DL experts with minimal digital histology experience, and (ii DP and image processing experts with minimal DL experience, to derive on their own, thus meriting a dedicated tutorial. Aims: This paper investigates these concepts through seven unique DP tasks as use cases to elucidate techniques needed to produce comparable, and in many cases, superior to results from the state-of-the-art hand-crafted feature-based classification approaches. Results : Specifically, in

  13. A new and selective cycle for dehydrogenation of linear and cyclic alkanes under mild conditions using a base metal

    Science.gov (United States)

    Solowey, Douglas P.; Mane, Manoj V.; Kurogi, Takashi; Carroll, Patrick J.; Manor, Brian C.; Baik, Mu-Hyun; Mindiola, Daniel J.

    2017-11-01

    Selectively converting linear alkanes to α-olefins under mild conditions is a highly desirable transformation given the abundance of alkanes as well as the use of olefins as building blocks in the chemical community. Until now, this reaction has been primarily the remit of noble-metal catalysts, despite extensive work showing that base-metal alkylidenes can mediate the reaction in a stoichiometric fashion. Here, we show how the presence of a hydrogen acceptor, such as the phosphorus ylide, when combined with the alkylidene complex (PNP)Ti=CHtBu(CH3) (PNP=N[2-P(CHMe2)2-4-methylphenyl]2-), catalyses the dehydrogenation of cycloalkanes to cyclic alkenes, and linear alkanes with chain lengths of C4 to C8 to terminal olefins under mild conditions. This Article represents the first example of a homogeneous and selective alkane dehydrogenation reaction using a base-metal titanium catalyst. We also propose a unique mechanism for the transfer dehydrogenation of hydrocarbons to olefins and discuss a complete cycle based on a combined experimental and computational study.

  14. Natural variation in learning and memory dynamics studied by artificial selection on learning rate in parasitic wasps

    NARCIS (Netherlands)

    Berg, van den M.; Duivenvoorde, L.; Wang, G.; Tribuhl, S.V.; Bukovinszky, T.; Vet, L.E.M.; Dicke, M.; Smid, H.M.

    2011-01-01

    Although the neural and genetic pathways underlying learning and memory formation seem strikingly similar among species of distant animal phyla, several more subtle inter- and intraspecific differences become evident from studies on model organisms. The true significance of such variation can only

  15. Body condition score of Nellore beef cows: a heritable measure to improve the selection of reproductive and maternal traits.

    Science.gov (United States)

    Fernandes, A F A; Neves, H H R; Carvalheiro, R; Oliveira, J A; Queiroz, S A

    2015-08-01

    Despite the economic importance of beef cattle production in Brazil, female reproductive performance, which is strongly associated with production efficiency, is not included in the selection index of most breeding programmes due to low heritability and difficulty in measure. The body condition score (BCS) could be used as an indicator of these traits. However, so far little is known about the feasibility of using BCS as a selection tool for reproductive performance in beef cattle. In this study, we investigated the sources of variation in the BCS of Nellore beef cows, quantified its association with reproductive and maternal traits and estimated its heritability. BCS was analysed using a logistic model that included the following effects: contemporary group at weaning, cow weight and hip height, calving order, reconception together with the weight and scores of conformation and early finishing assigned to calves at weaning. In the genetic analysis, variance components of BCS were estimated through Bayesian inference by fitting an animal model that also included the aforementioned effects. The results showed that BCS was significantly associated with all of the reproductive and maternal variables analysed. The estimated posterior mean of heritability of BCS was 0.24 (highest posterior density interval at 95%: 0.093 to 0.385), indicating an involvement of additive gene action in its determination. The present findings show that BCS can be used as a selection criterion for Nellore females.

  16. A Fuzzy Logic-Based Quality Function Deployment for Selection of E-Learning Provider

    Science.gov (United States)

    Kazancoglu, Yigit; Aksoy, Murat

    2011-01-01

    According to the Internet World Stats (2010), the growth rate of internet usage in the world is 444.8 % from 2000 to 2010. Since the number of internet users is rapidly increasing with each passed year, e-learning is often identified with web-based learning. The institutions, which deliver e-learning service via the use of computer and internet,…

  17. Macroinvertebrate-based assessment of biological condition at selected sites in the Eagle River watershed, Colorado, 2000-07

    Science.gov (United States)

    Zuellig, Robert E.; Bruce, James F.; Healy, Brian D.; Williams, Cory A.

    2010-01-01

    The U.S. Geological Survey (USGS), in cooperation with the Colorado River Water Conservation District, Eagle County, Eagle River Water and Sanitation District, Upper Eagle Regional Water Authority, Colorado Department of Transportation, City of Aurora, Town of Eagle, Town of Gypsum, Town of Minturn, Town of Vail, Vail Resorts, Colorado Springs Utilities, Denver Water, and the U.S. Department of Agriculture Forest Service (FS), compiled macroinvertebrate (73 sites, 124 samples) data previously collected in the Eagle River watershed from selected USGS and FS studies, 2000-07. These data were analyzed to assess the biological condition (that is, biologically ?degraded? or ?good?) at selected sites in the Eagle River watershed and determine if site class (for example, urban or undeveloped) described biological condition. An independently developed predictive model was applied to calculate a site-specific measure of taxonomic completeness for macroinvertebrate communities, where taxonomic completeness was expressed as the ratio of observed (O) taxa to those expected (E) to occur at each site. Macroinvertebrate communities were considered degraded at sites were O/E values were less than 0.80, indicating that at least 20 percent of expected taxa were not observed. Sites were classified into one of four classes (undeveloped, adjacent road or highway or both, mixed, urban) using a combination of riparian land-cover characteristics, examination of topographic maps and aerial imagery, screening for exceedances in water-quality standards, and best professional judgment. Analysis of variance was used to determine if site class accounted for variability in mean macroinvertebrate O/E values. Finally, macroinvertebrate taxa observed more or less frequently than expected at urban sites were indentified. This study represents the first standardized assessment of biological condition of selected sites distributed across the Eagle River watershed. Of the 73 sites evaluated, just over

  18. Use of Physics Innovative Device for Improving Students‟ Motivation and Performance in Learning Selected Concepts in Physics

    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

  19. Scale Dependence of Female Ungulate Reproductive Success in Relation to Nutritional Condition, Resource Selection and Multi-Predator Avoidance.

    Directory of Open Access Journals (Sweden)

    Jared F Duquette

    Full Text Available Female ungulate reproductive success is dependent on the survival of their young, and affected by maternal resource selection, predator avoidance, and nutritional condition. However, potential hierarchical effects of these factors on reproductive success are largely unknown, especially in multi-predator landscapes. We expanded on previous research of neonatal white-tailed deer (Odocoileus virginianus daily survival within home ranges to assess if resource use, integrated risk of 4 mammalian predators, maternal nutrition, winter severity, hiding cover, or interactions among these variables best explained landscape scale variation in daily or seasonal survival during the post-partum period. We hypothesized that reproductive success would be limited greater by predation risk at coarser spatiotemporal scales, but habitat use at finer scales. An additive model of daily non-ideal resource use and maternal nutrition explained the most (69% variation in survival; though 65% of this variation was related to maternal nutrition. Strong support of maternal nutrition across spatiotemporal scales did not fully support our hypothesis, but suggested reproductive success was related to dam behaviors directed at increasing nutritional condition. These behaviors were especially important following severe winters, when dams produced smaller fawns with less probability of survival. To increase nutritional condition and decrease wolf (Canis lupus predation risk, dams appeared to place fawns in isolated deciduous forest patches near roads. However, this resource selection represented non-ideal resources for fawns, which had greater predation risk that led to additive mortalities beyond those related to resources alone. Although the reproductive strategy of dams resulted in greater predation of fawns from alternative predators, it likely improved the life-long reproductive success of dams, as many were late-aged (>10 years old and could have produced multiple litters

  20. Dress Nicer = Know More? Young Children’s Knowledge Attribution and Selective Learning Based on How Others Dress

    Science.gov (United States)

    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