WorldWideScience

Sample records for learning mechanisms combined

  1. A Learning Log Analysis of an English-Reading e-Book System Combined with a Guidance Mechanism

    Science.gov (United States)

    Wu, Ting-Ting

    2016-01-01

    Learning English by reading articles on multimedia e-book devices can assist students in improving their vocabulary and in understanding the associations among vocabulary, textual meaning, and paragraph composition. Adaptive integration of reading technologies and strategies not only strengthens their language ability and reading comprehension,…

  2. Word learning mechanisms.

    Science.gov (United States)

    He, Angela Xiaoxue; Arunachalam, Sudha

    2017-07-01

    How do children acquire the meanings of words? Many word learning mechanisms have been proposed to guide learners through this challenging task. Despite the availability of rich information in the learner's linguistic and extralinguistic input, the word-learning task is insurmountable without such mechanisms for filtering through and utilizing that information. Different kinds of words, such as nouns denoting object concepts and verbs denoting event concepts, require to some extent different kinds of information and, therefore, access to different kinds of mechanisms. We review some of these mechanisms to examine the relationship between the input that is available to learners and learners' intake of that input-that is, the organized, interpreted, and stored representations they form. We discuss how learners segment individual words from the speech stream and identify their grammatical categories, how they identify the concepts denoted by these words, and how they refine their initial representations of word meanings. WIREs Cogn Sci 2017, 8:e1435. doi: 10.1002/wcs.1435 This article is categorized under: Linguistics > Language Acquisition Psychology > Language. © 2017 Wiley Periodicals, Inc.

  3. Circuit mechanisms of sensorimotor learning

    Science.gov (United States)

    Makino, Hiroshi; Hwang, Eun Jung; Hedrick, Nathan G.; Komiyama, Takaki

    2016-01-01

    SUMMARY The relationship between the brain and the environment is flexible, forming the foundation for our ability to learn. Here we review the current state of our understanding of the modifications in the sensorimotor pathway related to sensorimotor learning. We divide the process in three hierarchical levels with distinct goals: 1) sensory perceptual learning, 2) sensorimotor associative learning, and 3) motor skill learning. Perceptual learning optimizes the representations of important sensory stimuli. Associative learning and the initial phase of motor skill learning are ensured by feedback-based mechanisms that permit trial-and-error learning. The later phase of motor skill learning may primarily involve feedback-independent mechanisms operating under the classic Hebbian rule. With these changes under distinct constraints and mechanisms, sensorimotor learning establishes dedicated circuitry for the reproduction of stereotyped neural activity patterns and behavior. PMID:27883902

  4. Deep Learning Fluid Mechanics

    Science.gov (United States)

    Barati Farimani, Amir; Gomes, Joseph; Pande, Vijay

    2017-11-01

    We have developed a new data-driven model paradigm for the rapid inference and solution of the constitutive equations of fluid mechanic by deep learning models. Using generative adversarial networks (GAN), we train models for the direct generation of solutions to steady state heat conduction and incompressible fluid flow without knowledge of the underlying governing equations. Rather than using artificial neural networks to approximate the solution of the constitutive equations, GANs can directly generate the solutions to these equations conditional upon an arbitrary set of boundary conditions. Both models predict temperature, velocity and pressure fields with great test accuracy (>99.5%). The application of our framework for inferring and generating the solutions of partial differential equations can be applied to any physical phenomena and can be used to learn directly from experiments where the underlying physical model is complex or unknown. We also have shown that our framework can be used to couple multiple physics simultaneously, making it amenable to tackle multi-physics problems.

  5. Automotive Mechanics. Student Learning Guides.

    Science.gov (United States)

    Ridge Vocational-Technical Center, Winter Haven, FL.

    These 33 learning guides are self-instructional packets for 33 tasks identified as essential for performance on an entry-level job in automotive mechanics. Each guide is based on a terminal performance objective (task) and 1-9 enabling objectives. For each enabliing objective, some or all of these materials may be presented: learning steps…

  6. Learn new mechanisms from life

    International Nuclear Information System (INIS)

    Ji Qing; Luo Mingyan; Tong Xiaolin; Zhang Bo; Zhang Hui

    2005-01-01

    On the basis of the important experimental results of molecular motors, it was pointed out that the moving process of molecular motors is a coupling biological process of chemical-electrical-mechanical processes. This clever mechanism of energy conversion on the molecular level with several processes coupled together had never been observed before. The understanding of this new mechanism is an important step towards the understanding of life and an important content of what we can learn from life. The authors introduced here the status of the investigations on the mechanism for the force generation of kinesin and the studies of the authors in this field. (authors)

  7. Learning Predictive Statistics: Strategies and Brain Mechanisms.

    Science.gov (United States)

    Wang, Rui; Shen, Yuan; Tino, Peter; Welchman, Andrew E; Kourtzi, Zoe

    2017-08-30

    When immersed in a new environment, we are challenged to decipher initially incomprehensible streams of sensory information. However, quite rapidly, the brain finds structure and meaning in these incoming signals, helping us to predict and prepare ourselves for future actions. This skill relies on extracting the statistics of event streams in the environment that contain regularities of variable complexity from simple repetitive patterns to complex probabilistic combinations. Here, we test the brain mechanisms that mediate our ability to adapt to the environment's statistics and predict upcoming events. By combining behavioral training and multisession fMRI in human participants (male and female), we track the corticostriatal mechanisms that mediate learning of temporal sequences as they change in structure complexity. We show that learning of predictive structures relates to individual decision strategy; that is, selecting the most probable outcome in a given context (maximizing) versus matching the exact sequence statistics. These strategies engage distinct human brain regions: maximizing engages dorsolateral prefrontal, cingulate, sensory-motor regions, and basal ganglia (dorsal caudate, putamen), whereas matching engages occipitotemporal regions (including the hippocampus) and basal ganglia (ventral caudate). Our findings provide evidence for distinct corticostriatal mechanisms that facilitate our ability to extract behaviorally relevant statistics to make predictions. SIGNIFICANCE STATEMENT Making predictions about future events relies on interpreting streams of information that may initially appear incomprehensible. Past work has studied how humans identify repetitive patterns and associative pairings. However, the natural environment contains regularities that vary in complexity from simple repetition to complex probabilistic combinations. Here, we combine behavior and multisession fMRI to track the brain mechanisms that mediate our ability to adapt to

  8. Learning about Severe Combined Immunodeficiency (SCID)

    Science.gov (United States)

    ... immunodeficiency From The Journal of Allergy and Clinical Immunology Learning About Severe Combined Immunodeficiency (SCID) What is ... immunodeficiency From The Journal of Allergy and Clinical Immunology Get Email Updates Privacy Copyright Contact Accessibility Plug- ...

  9. Machine Learning and Quantum Mechanics

    Science.gov (United States)

    Chapline, George

    The author has previously pointed out some similarities between selforganizing neural networks and quantum mechanics. These types of neural networks were originally conceived of as away of emulating the cognitive capabilities of the human brain. Recently extensions of these networks, collectively referred to as deep learning networks, have strengthened the connection between self-organizing neural networks and human cognitive capabilities. In this note we consider whether hardware quantum devices might be useful for emulating neural networks with human-like cognitive capabilities, or alternatively whether implementations of deep learning neural networks using conventional computers might lead to better algorithms for solving the many body Schrodinger equation.

  10. Brain mechanisms of flavor learning.

    Science.gov (United States)

    Yamamoto, Takashi; Ueji, Kayoko

    2011-01-01

    Once the flavor of the ingested food (conditioned stimulus, CS) is associated with a preferable (e.g., good taste or nutritive satisfaction) or aversive (e.g., malaise with displeasure) signal (unconditioned stimulus, US), animals react to its subsequent exposure by increasing or decreasing ingestion to the food. These two types of association learning (preference learning vs. aversion learning) are known as classical conditioned reactions which are basic learning and memory phenomena, leading selection of food and proper food intake. Since the perception of flavor is generated by interaction of taste and odor during food intake, taste and/or odor are mainly associated with bodily signals in the flavor learning. After briefly reviewing flavor learning in general, brain mechanisms of conditioned taste aversion is described in more detail. The CS-US association leading to long-term potentiation in the amygdala, especially in its basolateral nucleus, is the basis of establishment of conditioned taste aversion. The novelty of the CS detected by the cortical gustatory area may be supportive in CS-US association. After the association, CS input is conveyed through the amygdala to different brain regions including the hippocampus for contextual fear formation, to the supramammillary and thalamic paraventricular nuclei for stressful anxiety or memory dependent fearful or stressful emotion, to the reward system to induce aversive expression to the CS, or hedonic shift from positive to negative, and to the CS-responsive neurons in the gustatory system to enhance the responsiveness to facilitate to detect the harmful stimulus.

  11. Learn Quantum Mechanics with Haskell

    Directory of Open Access Journals (Sweden)

    Scott N. Walck

    2016-11-01

    Full Text Available To learn quantum mechanics, one must become adept in the use of various mathematical structures that make up the theory; one must also become familiar with some basic laboratory experiments that the theory is designed to explain. The laboratory ideas are naturally expressed in one language, and the theoretical ideas in another. We present a method for learning quantum mechanics that begins with a laboratory language for the description and simulation of simple but essential laboratory experiments, so that students can gain some intuition about the phenomena that a theory of quantum mechanics needs to explain. Then, in parallel with the introduction of the mathematical framework on which quantum mechanics is based, we introduce a calculational language for describing important mathematical objects and operations, allowing students to do calculations in quantum mechanics, including calculations that cannot be done by hand. Finally, we ask students to use the calculational language to implement a simplified version of the laboratory language, bringing together the theoretical and laboratory ideas.

  12. Brain mechanisms of flavor learning

    Directory of Open Access Journals (Sweden)

    Takashi eYamamoto

    2011-09-01

    Full Text Available Once the flavor of the ingested food (conditioned stimulus, CS is associated with a preferable (e.g., good taste or nutritive satisfaction or aversive (e.g., malaise with displeasure signal (unconditioned stimulus, US, animals react to its subsequent exposure by increasing or decreasing ingestion to the food. These two types of association learning (preference learning vs. aversion learning are known as classical conditioned reactions which are basic learning and memory phenomena, leading selection of food and proper food intake. Since the perception of flavor is generated by interaction of taste and odor during food intake, taste and/or odor are mainly associated with bodily signals in the flavor learning. After briefly reviewing flavor learning in general, brain mechanisms of conditioned taste aversion is described in more detail. The CS-US association leading to long-term potentiation in the amygdala, especially in its basolateral nucleus, is the basis of establishment of conditioned taste aversion. The novelty of the CS detected by the cortical gustatory area may be supportive in CS-US association. After the association, CS input is conveyed through the amygdala to different brain regions including the hippocampus for contextual fear formation, to the supramammilary and thalamic paraventricular nuclei for stressful anxiety or memory dependent fearful or stressful emotion, to the reward system to induce aversive expression to the CS, or hedonic shift from positive to negative, and to the CS-responsive neurons in the gustatory system to enhance the responsiveness to facilitate to detect the harmful stimulus.

  13. Learning mechanisms to limit medication administration errors.

    Science.gov (United States)

    Drach-Zahavy, Anat; Pud, Dorit

    2010-04-01

    This paper is a report of a study conducted to identify and test the effectiveness of learning mechanisms applied by the nursing staff of hospital wards as a means of limiting medication administration errors. Since the influential report ;To Err Is Human', research has emphasized the role of team learning in reducing medication administration errors. Nevertheless, little is known about the mechanisms underlying team learning. Thirty-two hospital wards were randomly recruited. Data were collected during 2006 in Israel by a multi-method (observations, interviews and administrative data), multi-source (head nurses, bedside nurses) approach. Medication administration error was defined as any deviation from procedures, policies and/or best practices for medication administration, and was identified using semi-structured observations of nurses administering medication. Organizational learning was measured using semi-structured interviews with head nurses, and the previous year's reported medication administration errors were assessed using administrative data. The interview data revealed four learning mechanism patterns employed in an attempt to learn from medication administration errors: integrated, non-integrated, supervisory and patchy learning. Regression analysis results demonstrated that whereas the integrated pattern of learning mechanisms was associated with decreased errors, the non-integrated pattern was associated with increased errors. Supervisory and patchy learning mechanisms were not associated with errors. Superior learning mechanisms are those that represent the whole cycle of team learning, are enacted by nurses who administer medications to patients, and emphasize a system approach to data analysis instead of analysis of individual cases.

  14. Skill learning and the evolution of social learning mechanisms.

    Science.gov (United States)

    van der Post, Daniel J; Franz, Mathias; Laland, Kevin N

    2016-08-24

    Social learning is potentially advantageous, but evolutionary theory predicts that (i) its benefits may be self-limiting because social learning can lead to information parasitism, and (ii) these limitations can be mitigated via forms of selective copying. However, these findings arise from a functional approach in which learning mechanisms are not specified, and which assumes that social learning avoids the costs of asocial learning but does not produce information about the environment. Whether these findings generalize to all kinds of social learning remains to be established. Using a detailed multi-scale evolutionary model, we investigate the payoffs and information production processes of specific social learning mechanisms (including local enhancement, stimulus enhancement and observational learning) and their evolutionary consequences in the context of skill learning in foraging groups. We find that local enhancement does not benefit foraging success, but could evolve as a side-effect of grouping. In contrast, stimulus enhancement and observational learning can be beneficial across a wide range of environmental conditions because they generate opportunities for new learning outcomes. In contrast to much existing theory, we find that the functional outcomes of social learning are mechanism specific. Social learning nearly always produces information about the environment, and does not always avoid the costs of asocial learning or support information parasitism. Our study supports work emphasizing the value of incorporating mechanistic detail in functional analyses.

  15. Study on modeling of operator's learning mechanism

    International Nuclear Information System (INIS)

    Yoshimura, Seichi; Hasegawa, Naoko

    1998-01-01

    One effective method to analyze the causes of human errors is to model the behavior of human and to simulate it. The Central Research Institute of Electric Power Industry (CRIEPI) has developed an operator team behavior simulation system called SYBORG (Simulation System for the Behavior of an Operating Group) to analyze the human errors and to establish the countermeasures for them. As an operator behavior model which composes SYBORG has no learning mechanism and the knowledge of a plant is fixed, it cannot take suitable actions when unknown situations occur nor learn anything from the experience. However, considering actual operators, learning is an essential human factor to enhance their abilities to diagnose plant anomalies. In this paper, Q learning with 1/f fluctuation was proposed as a learning mechanism of an operator and simulation using the mechanism was conducted. The results showed the effectiveness of the learning mechanism. (author)

  16. Teaching Professionals Environmental Management: Combining Educational Learning and Practice Learning

    DEFF Research Database (Denmark)

    Jørgensen, Michael Søgaard; Jørgensen, Ulrik

    2003-01-01

    semesters. The target groups are professional environmental managers working in businesses including consultants, governmental institutions and organizations. To get access to the education the students must have a technical/nature science competence at master level or bachelor level combined with relevant...... job experience. Generally the participants have had 5-15 years of practical experience and many have been or are in the position of an internal or external job change towards new tasks that require new knowledge, methodologies or management skills. The education of "Masters of Environmental Management...... they can use in complex situations on the job is not simply a question of combining different university disciplines in the right blend and topping it with some experience. It involves combining science-based knowledge into thematic structures in carefully organized learning processes. The education...

  17. The Evolution of Learning Mechanisms.

    Science.gov (United States)

    Garcia, John; Garcia y Robertson, Rodrigo

    This paper introduces seven principles of learning, enduring over the last five centuries of psychological thought, to discuss the evolution of the "Biophyche" (the brain in action) in the development of humans and other large organisms. It describes the conditioning theories of Darwin, Pavlov, and Thorndike and critically reviews the…

  18. Combining Correlation-Based and Reward-Based Learning in Neural Control for Policy Improvement

    DEFF Research Database (Denmark)

    Manoonpong, Poramate; Kolodziejski, Christoph; Wörgötter, Florentin

    2013-01-01

    Classical conditioning (conventionally modeled as correlation-based learning) and operant conditioning (conventionally modeled as reinforcement learning or reward-based learning) have been found in biological systems. Evidence shows that these two mechanisms strongly involve learning about...... associations. Based on these biological findings, we propose a new learning model to achieve successful control policies for artificial systems. This model combines correlation-based learning using input correlation learning (ICO learning) and reward-based learning using continuous actor–critic reinforcement...... learning (RL), thereby working as a dual learner system. The model performance is evaluated by simulations of a cart-pole system as a dynamic motion control problem and a mobile robot system as a goal-directed behavior control problem. Results show that the model can strongly improve pole balancing control...

  19. The statistical mechanics of learning a rule

    International Nuclear Information System (INIS)

    Watkin, T.L.H.; Rau, A.; Biehl, M.

    1993-01-01

    A summary is presented of the statistical mechanical theory of learning a rule with a neural network, a rapidly advancing area which is closely related to other inverse problems frequently encountered by physicists. By emphasizing the relationship between neural networks and strongly interacting physical systems, such as spin glasses, the authors show how learning theory has provided a workshop in which to develop new, exact analytical techniques

  20. Combining Service and Learning in Higher Education

    National Research Council Canada - National Science Library

    Gray, Maryann

    1999-01-01

    .... Hundreds of college and university presidents, most of the major higher education associations, and a number of highly influential scholars actively support the development of service-learning...

  1. Crack assessment of pipe under combined thermal and mechanical load

    International Nuclear Information System (INIS)

    Song, Tae Kwang; Kim, Yun Jae

    2009-01-01

    In this paper, J-integral and transient C(t)-integral, which were key parameters in low temperature and high temperature fracture mechanics, under combined thermal and mechanical load were estimated via 3-dimensional finite element analyses. Various type of thermal and mechanical load, material hardening were considered to decrease conservatism in existing solutions. As a results, V-factor and redistribution time for combined thermal and mechanical load were proposed to calculate J-integral and C(t)-integral, respectively.

  2. Combining Service and Learning in Higher Education

    National Research Council Canada - National Science Library

    Gray, Maryann

    1999-01-01

    The Policy Debate In the past decade, colleges and universities have made greater efforts to involve students in community service, particularly service-learning, a special form of community service...

  3. The right time to learn: mechanisms and optimization of spaced learning

    Science.gov (United States)

    Smolen, Paul; Zhang, Yili; Byrne, John H.

    2016-01-01

    For many types of learning, spaced training, which involves repeated long inter-trial intervals, leads to more robust memory formation than does massed training, which involves short or no intervals. Several cognitive theories have been proposed to explain this superiority, but only recently have data begun to delineate the underlying cellular and molecular mechanisms of spaced training, and we review these theories and data here. Computational models of the implicated signalling cascades have predicted that spaced training with irregular inter-trial intervals can enhance learning. This strategy of using models to predict optimal spaced training protocols, combined with pharmacotherapy, suggests novel ways to rescue impaired synaptic plasticity and learning. PMID:26806627

  4. MOLECULAR MECHANISMS OF FEAR LEARNING AND MEMORY

    Science.gov (United States)

    Johansen, Joshua P.; Cain, Christopher K.; Ostroff, Linnaea E.; LeDoux, Joseph E.

    2011-01-01

    Pavlovian fear conditioning is a useful behavioral paradigm for exploring the molecular mechanisms of learning and memory because a well-defined response to a specific environmental stimulus is produced through associative learning processes. Synaptic plasticity in the lateral nucleus of the amygdala (LA) underlies this form of associative learning. Here we summarize the molecular mechanisms that contribute to this synaptic plasticity in the context of auditory fear conditioning, the form of fear conditioning best understood at the molecular level. We discuss the neurotransmitter systems and signaling cascades that contribute to three phases of auditory fear conditioning: acquisition, consolidation, and reconsolidation. These studies suggest that multiple intracellular signaling pathways, including those triggered by activation of Hebbian processes and neuromodulatory receptors, interact to produce neural plasticity in the LA and behavioral fear conditioning. Together, this research illustrates the power of fear conditioning as a model system for characterizing the mechanisms of learning and memory in mammals, and potentially for understanding fear related disorders, such as PTSD and phobias. PMID:22036561

  5. Molecular mechanisms of fear learning and memory.

    Science.gov (United States)

    Johansen, Joshua P; Cain, Christopher K; Ostroff, Linnaea E; LeDoux, Joseph E

    2011-10-28

    Pavlovian fear conditioning is a particularly useful behavioral paradigm for exploring the molecular mechanisms of learning and memory because a well-defined response to a specific environmental stimulus is produced through associative learning processes. Synaptic plasticity in the lateral nucleus of the amygdala (LA) underlies this form of associative learning. Here, we summarize the molecular mechanisms that contribute to this synaptic plasticity in the context of auditory fear conditioning, the form of fear conditioning best understood at the molecular level. We discuss the neurotransmitter systems and signaling cascades that contribute to three phases of auditory fear conditioning: acquisition, consolidation, and reconsolidation. These studies suggest that multiple intracellular signaling pathways, including those triggered by activation of Hebbian processes and neuromodulatory receptors, interact to produce neural plasticity in the LA and behavioral fear conditioning. Collectively, this body of research illustrates the power of fear conditioning as a model system for characterizing the mechanisms of learning and memory in mammals and potentially for understanding fear-related disorders, such as PTSD and phobias. Copyright © 2011 Elsevier Inc. All rights reserved.

  6. Sensorimotor Learning: Neurocognitive Mechanisms and Individual Differences.

    Science.gov (United States)

    Seidler, R D; Carson, R G

    2017-07-13

    Here we provide an overview of findings and viewpoints on the mechanisms of sensorimotor learning presented at the 2016 Biomechanics and Neural Control of Movement (BANCOM) conference in Deer Creek, OH. This field has shown substantial growth in the past couple of decades. For example it is now well accepted that neural systems outside of primary motor pathways play a role in learning. Frontoparietal and anterior cingulate networks contribute to sensorimotor adaptation, reflecting strategic aspects of exploration and learning. Longer term training results in functional and morphological changes in primary motor and somatosensory cortices. Interestingly, re-engagement of strategic processes once a skill has become well learned may disrupt performance. Efforts to predict individual differences in learning rate have enhanced our understanding of the neural, behavioral, and genetic factors underlying skilled human performance. Access to genomic analyses has dramatically increased over the past several years. This has enhanced our understanding of cellular processes underlying the expression of human behavior, including involvement of various neurotransmitters, receptors, and enzymes. Surprisingly our field has been slow to adopt such approaches in studying neural control, although this work does require much larger sample sizes than are typically used to investigate skill learning. We advocate that individual differences approaches can lead to new insights into human sensorimotor performance. Moreover, a greater understanding of the factors underlying the wide range of performance capabilities seen across individuals can promote personalized medicine and refinement of rehabilitation strategies, which stand to be more effective than "one size fits all" treatments.

  7. Learning as discourse change: A sociocultural mechanism

    Science.gov (United States)

    Wickman, Per-Olof; Östman, Leif

    2002-09-01

    This paper deals with a theoretical mechanism for learning and a methodological approach for analyzing meaning making in classroom talk and action. It examines the potential of the approach for illuminating learning on a discursive level, i.e., how discourses change and how individuals become participants of new practices. Our approach involves a high-resolution analysis of how meaningful relations are built in encounters between individuals and between individuals and the world. The approach is based mainly on the work of the later Wittgenstein, but also on pragmatism and sociocultural research. To demonstrate how our approach can be used, we analyze what university students learn during a practical on insects. We specifically demonstrate how the encounters with physical pinned insects contribute to the meaning students make and how these encounters interact with other experiences during laboratory work.

  8. Dissecting the mechanisms of squirrel monkey (Saimiri boliviensis) social learning.

    Science.gov (United States)

    Hopper, Lm; Holmes, An; Williams, LE; Brosnan, Sf

    2013-01-01

    Although the social learning abilities of monkeys have been well documented, this research has only focused on a few species. Furthermore, of those that also incorporated dissections of social learning mechanisms, the majority studied either capuchins (Cebus apella) or marmosets (Callithrix jacchus). To gain a broader understanding of how monkeys gain new skills, we tested squirrel monkeys (Saimiri boliviensis) which have never been studied in tests of social learning mechanisms. To determine whether S. boliviensis can socially learn, we ran "open diffusion" tests with monkeys housed in two social groups (N = 23). Over the course of 10 20-min sessions, the monkeys in each group observed a trained group member retrieving a mealworm from a bidirectional task (the "Slide-box"). Two thirds (67%) of these monkeys both learned how to operate the Slide-box and they also moved the door significantly more times in the direction modeled by the trained demonstrator than the alternative direction. To tease apart the underlying social learning mechanisms we ran a series of three control conditions with 35 squirrel monkeys that had no previous experience with the Slide-box. The first replicated the experimental open diffusion sessions but without the inclusion of a trained model, the second was a no-information control with dyads of monkeys, and the third was a 'ghost' display shown to individual monkeys. The first two controls tested for the importance of social support (mere presence effect) and the ghost display showed the affordances of the task to the monkeys. The monkeys showed a certain level of success in the group control (54% of subjects solved the task on one or more occasions) and paired controls (28% were successful) but none were successful in the ghost control. We propose that the squirrel monkeys' learning, observed in the experimental open diffusion tests, can be best described by a combination of social learning mechanisms in concert; in this case, those

  9. Tuning Cell and Tissue Development by Combining Multiple Mechanical Signals.

    Science.gov (United States)

    Sinha, Ravi; Verdonschot, Nico; Koopman, Bart; Rouwkema, Jeroen

    2017-10-01

    Mechanical signals offer a promising way to control cell and tissue development. It has been established that cells constantly probe their mechanical microenvironment and employ force feedback mechanisms to modify themselves and when possible, their environment, to reach a homeostatic state. Thus, a correct mechanical microenvironment (external forces and mechanical properties and shapes of cellular surroundings) is necessary for the proper functioning of cells. In vitro or in the case of nonbiological implants in vivo, where cells are in an artificial environment, addition of the adequate mechanical signals can, therefore, enable the cells to function normally as in vivo. Hence, a wide variety of approaches have been developed to apply mechanical stimuli (such as substrate stretch, flow-induced shear stress, substrate stiffness, topography, and modulation of attachment area) to cells in vitro. These approaches have not just revealed the effects of the mechanical signals on cells but also provided ways for probing cellular molecules and structures that can provide a mechanistic understanding of the effects. However, they remain lower in complexity compared with the in vivo conditions, where the cellular mechanical microenvironment is the result of a combination of multiple mechanical signals. Therefore, combinations of mechanical stimuli have also been applied to cells in vitro. These studies have had varying focus-developing novel platforms to apply complex combinations of mechanical stimuli, observing the co-operation/competition between stimuli, combining benefits of multiple stimuli toward an application, or uncovering the underlying mechanisms of their action. In general, they provided new insights that could not have been predicted from previous knowledge. We present here a review of several such studies and the insights gained from them, thereby making a case for such studies to be continued and further developed.

  10. Mind and activity. Psychic mechanism of learning

    Directory of Open Access Journals (Sweden)

    Zoya A. Reshetova

    2017-09-01

    Full Text Available The paper is devoted to the issue of mechanisms of learning for understanding the nature of the human mind. Learning is regarded as a special activity that is important for developing the human mind in a specific cultural and historical setting and indirect activity. The author’s understanding of the ideas developed by the psychological theory of activity for establishing the principles of developing the human mind is highlighted. Interpretation of dialectical connections of brain processes and mind, and also the objective activity that emerges them is provided. According to the activity theory, the causes of the students’ psychological difficulties and the low efficacy of learning within predominant reproductive method or the use of the trial and error method are revealed. Thus, a new understanding of the renowned didactic principles of scientific rigour, accessibility, objectivity, the connection of learning with life and others is offered. The contribution of the psychological theory in organizing and managing the studies, increasing teaching activity and awareness, and the growth of the internal causes of motivation are shown. Particular attention is paid to the issue of intellectual development and creative abilities. The author believes the creative abilities of the student and the way the latter are taught are interconnected. At the same time, the developers and educators should make efforts to develop in the students a systemic orientation in the subject, primarily mastering the method of system analysis. Once the method of system analysis has been mastered, it becomes a general intellectual and developing tool through which activities are organized to solve any teaching problems with whatever type of content and difficulty level. Summing up, the organization and disclosure to the student of the process of learning as an activity with its social, consciously transformative and sense shaping meaning, the conditions of its development

  11. [Learning and implicit memory: mechanisms and neuroplasticity].

    Science.gov (United States)

    Machado, S; Portella, C E; Silva, J G; Velasques, B; Bastos, V H; Cunha, M; Basile, L; Cagy, M; Piedade, R A; Ribeiro, P

    Learning and memory are complex processes that researchers have been attempting to unravel for over a century in order to gain a clear view of the underlying mechanisms. To review the basic cellular and molecular mechanisms involved in the process of procedural retention, to offer an overall view of the fundamental mechanisms involved in storing information by means of theories and models of memory, and to discuss the different types of memory and the role played by the cerebellum as a modulator of procedural memory. Experimental results from recent decades have opened up new areas of study regarding the participation of the biochemical and cellular processes related to the consolidation of information in the nervous system. The neuronal circuits involved in acquiring and consolidating memory are still not fully understood and the exact location of memory in the nervous system remains unknown. A number of intrinsic and extrinsic factors interfere in these processes, such as molecular (long-term potentiation and depression) and cellular mechanisms, which respond to communication and transmission between nerve cells. There are also factors that have their origin in the outside environment, which use the association of events to bring about the formation of new memories or may divert the subject from his or her main focus. Memory is not a singular occurrence; it is sub-divided into declarative and non-declarative or, when talking about the time it lasts, into short and long-term memory. Moreover, given its relation with neuronal mechanisms of learning, memory cannot be said to constitute an isolated process.

  12. Combining deep learning and satellite data to inform sustainable development

    Science.gov (United States)

    Lobell, D. B.

    2017-12-01

    Methods in machine learning, and in particular deep learning, are quickly advancing, in parallel with dramatic increases in the availability of fine resolution satellite data. The combination of both offers the possibility to improve understanding of some of the poorest regions of the world, where traditional data sources are limited. This talk will cover recent applications to track poverty at the village level in Africa, spot the onset of disease outbreaks in agriculture, and identify land use patterns and crop productivity.

  13. Technology of Rock Destruction by Combined Explosion-Mechanical Load

    Directory of Open Access Journals (Sweden)

    Oleg M. Terentiev

    2017-10-01

    Full Text Available Background. Rock drilling is characterized by an energy capacity of more than 120 kWh/m3. This is due to the fact that about 90 % of the energy is expended on the “preparation” of rocks for destruction. This study proposes to combine explosive and mechanical loads to reduce specific energy consumption of rock destruction. Objective. The aim of the paper is energy effective technology development for rock destruction by combined explosive-mechanical loads. Methods. Analytical studies; regression analysis; math modeling; experimental research; technical and economic analysis. Results. Specific energy decreasing for explosive-mechanical rock drilling by 4–16 % was experimentally proved. Conclusions. As a result of the implementation of explosive-mechanical rock drilling on the created full-sized experimental device, the efficiency coefficient increased from 77 to 80 %.

  14. Combination of biochemical and mechanical cues for tendon tissue engineering.

    Science.gov (United States)

    Testa, Stefano; Costantini, Marco; Fornetti, Ersilia; Bernardini, Sergio; Trombetta, Marcella; Seliktar, Dror; Cannata, Stefano; Rainer, Alberto; Gargioli, Cesare

    2017-11-01

    Tendinopathies negatively affect the life quality of millions of people in occupational and athletic settings, as well as the general population. Tendon healing is a slow process, often with insufficient results to restore complete endurance and functionality of the tissue. Tissue engineering, using tendon progenitors, artificial matrices and bioreactors for mechanical stimulation, could be an important approach for treating rips, fraying and tissue rupture. In our work, C3H10T1/2 murine fibroblast cell line was exposed to a combination of stimuli: a biochemical stimulus provided by Transforming Growth Factor Beta (TGF-β) and Ascorbic Acid (AA); a three-dimensional environment represented by PEGylated-Fibrinogen (PEG-Fibrinogen) biomimetic matrix; and a mechanical induction exploiting a custom bioreactor applying uniaxial stretching. In vitro analyses by immunofluorescence and mechanical testing revealed that the proposed combined approach favours the organization of a three-dimensional tissue-like structure promoting a remarkable arrangement of the cells and the neo-extracellular matrix, reflecting into enhanced mechanical strength. The proposed method represents a novel approach for tendon tissue engineering, demonstrating how the combined effect of biochemical and mechanical stimuli ameliorates biological and mechanical properties of the artificial tissue compared to those obtained with single inducement. © 2017 The Authors. Journal of Cellular and Molecular Medicine published by John Wiley & Sons Ltd and Foundation for Cellular and Molecular Medicine.

  15. Technology of combined chemical-mechanical fabrication of durable coatings

    Science.gov (United States)

    Smolentsev, V. P.; Ivanov, V. V.; Portnykh, A. I.

    2018-03-01

    The article presents the scientific fundamentals of methodology for calculating the modes and structuring the technological processes of combined chemical-mechanical fabrication of durable coatings. It is shown that they are based on classical patterns, describing the processes of simultaneous chemical and mechanical impact. The paper demonstrates the possibility of structuring a technological process, taking into account the systematic approach to impact management and strengthening the reciprocal positive influence of each impact upon the combined process. The combined processes have been planned for fabricating the model types of chemical-mechanical coatings of durable products in machine construction. The planning methodology is underpinned by a scientific hypothesis of a single source of impact management through energy potential of process components themselves, or by means of external energy supply through mechanical impact. The control of it is fairly thoroughly studied in the case of pulsed external strikes of hard pellets, similar to processes of vibroimpact hardening, thoroughly studied and mastered in many scientific schools of Russia.

  16. Effects of Elicited Reflections combined with Tutor or Peer Feedback on Self-Regulated Learning and Learning Outcomes

    NARCIS (Netherlands)

    Van den Boom, Gerard; Paas, Fred; Van Merriënboer, Jeroen

    2009-01-01

    Van den Boom, G., Paas, F., & Van Merriënboer, J. J. G. (2007). Effects of elicited reflections combined with tutor or peer feedback on self-regulated learning and learning outcomes. Learning and Instruction, 17, 532-548.

  17. Combining NDE and fracture mechanics by artifical intelligence expert systems techniques

    International Nuclear Information System (INIS)

    Mucciardi, A.N.; Riccardella, P.C.

    1986-01-01

    This paper reports on the development of a PC-based expert system for non-destructive evaluation. Software tools from the expert systems subfield of artificial intelligence are being used to combine both NDE and fracture mechanics algorithms into one, unified package. The system incorporates elements of computer-enhanced ultrasonic signal processing, featuring artificial intelligence learning capability, state-of-the-art fracture mechanics analytical tools, and all relevant metallurgical and design data necessary to emulate the decisions of the panel(s) of experts typically involved in generating and dispositioning NDE data

  18. Exploring the Learning Mechanism in Educational Games

    OpenAIRE

    Kiili, Kristian; Ketamo, Harri

    2007-01-01

    The main aim of this paper is to evaluate the problem based gaming model that tries to explain the learning process in educational games. The model was studied through Geometry game aimed for pre-school children (N = 24). The game relays on learning by teaching approach and involves AI-engine modeling the human concept learning structures. The qualitative analyses were used to explore participants learning processes and gaming strategies. The results indicated that the model well describes th...

  19. Synergistic mechanism of combinative application of bensulfuron and urea

    International Nuclear Information System (INIS)

    Yu Liuqing; Huang Shiwen; Zhou Hongjie; Ye Guibiao

    1998-01-01

    Nutrient culture study was initiated to examine the synergistic mechanism of combinative application of bensulfuron and urea for weed control. The absorption of 14 C-bensulfuron and their distribution in Lindernia procumbens (Krock.) Philcox were also investigated to determine the variation between two methods (combinative use of 14 C-bensulfuron plus urea and 14 C-bensulfuron alone). One hour after combinative application of 14 C-bensulfuron plus urea, the highest amount of 14 C-activity in L. procumbens were obtained. However, when 14 C-bensulfuron applied alone, total absorption of 14 C-activity was much lower in the 1st hour and then it slowly increased with time. The distribution of 14 C-bensulfuron in root of L. procumbens plant was the highest and that in leaves was the lowest

  20. A Blended Learning Approach to Teach Fluid Mechanics in Engineering

    Science.gov (United States)

    Rahman, Ataur

    2017-01-01

    This paper presents a case study on the teaching and learning of fluid mechanics at the University of Western Sydney (UWS), Australia, by applying a blended learning approach (BLA). In the adopted BLA, various flexible learning materials have been made available to the students such as online recorded lectures, online recorded tutorials, hand…

  1. Bonding mechanisms in spot welded three layer combinations

    DEFF Research Database (Denmark)

    Moghadam, Marcel; Tiedje, Niels Skat; Seyyedian Choobi, Mahsa

    2016-01-01

    this interface. It has been shown previously that such a joint can reach relatively high strength resulting in plug failure in tensileshear testing. Additional strength due to these bonding mechanisms is also obtained in common spot welds in the so-called corona band around the weld nugget.......The strength of a spot weld generally stems from fusion bonding of the metal layers, but other solid state bonding mechanisms also contribute to the overall strength. Metallographic analyses are presented to identify the phases formed near and across the weld interfaces and to identify...... the occurring bonding mechanisms. When welding a combination of three galvanized steel layers where one outer layer is a thin low-carbon steel it is a common challenge to obtain nugget penetration into the thin low-carbon steel. It therefore happens in real production that no nugget is formed across...

  2. Learning the mechanisms of chemical disequilibria

    Energy Technology Data Exchange (ETDEWEB)

    Nicholson, Schuyler B.; Alaghemandi, Mohammad [Department of Chemistry, University of Massachusetts Boston, Boston, Massachusetts 02125 (United States); Green, Jason R., E-mail: jason.green@umb.edu [Department of Chemistry, University of Massachusetts Boston, Boston, Massachusetts 02125 (United States); Department of Physics, University of Massachusetts Boston, Boston, Massachusetts 02125 (United States); Center for Quantum and Nonequilibrium Systems, University of Massachusetts Boston, Boston, Massachusetts 02125 (United States)

    2016-08-28

    When at equilibrium, large-scale systems obey thermodynamics because they have microscopic configurations that are typical. “Typical” states are a fraction of those possible with the majority of the probability. A more precise definition of typical states underlies the transmission, coding, and compression of information. However, this definition does not apply to natural systems that are transiently away from equilibrium. Here, we introduce a variational measure of typicality and apply it to atomistic simulations of a model for hydrogen oxidation. While a gaseous mixture of hydrogen and oxygen combusts, reactant molecules transform through a variety of ephemeral species en route to the product, water. Out of the exponentially growing number of possible sequences of chemical species, we find that greater than 95% of the probability concentrates in less than 1% of the possible sequences. Overall, these results extend the notion of typicality across the nonequilibrium regime and suggest that typical sequences are a route to learning mechanisms from experimental measurements. They also open up the possibility of constructing ensembles for computing the macroscopic observables of systems out of equilibrium.

  3. Learning the mechanisms of chemical disequilibria

    International Nuclear Information System (INIS)

    Nicholson, Schuyler B.; Alaghemandi, Mohammad; Green, Jason R.

    2016-01-01

    When at equilibrium, large-scale systems obey thermodynamics because they have microscopic configurations that are typical. “Typical” states are a fraction of those possible with the majority of the probability. A more precise definition of typical states underlies the transmission, coding, and compression of information. However, this definition does not apply to natural systems that are transiently away from equilibrium. Here, we introduce a variational measure of typicality and apply it to atomistic simulations of a model for hydrogen oxidation. While a gaseous mixture of hydrogen and oxygen combusts, reactant molecules transform through a variety of ephemeral species en route to the product, water. Out of the exponentially growing number of possible sequences of chemical species, we find that greater than 95% of the probability concentrates in less than 1% of the possible sequences. Overall, these results extend the notion of typicality across the nonequilibrium regime and suggest that typical sequences are a route to learning mechanisms from experimental measurements. They also open up the possibility of constructing ensembles for computing the macroscopic observables of systems out of equilibrium.

  4. The combination of appetitive and aversive reinforcers and the nature of their interaction during auditory learning.

    Science.gov (United States)

    Ilango, A; Wetzel, W; Scheich, H; Ohl, F W

    2010-03-31

    Learned changes in behavior can be elicited by either appetitive or aversive reinforcers. It is, however, not clear whether the two types of motivation, (approaching appetitive stimuli and avoiding aversive stimuli) drive learning in the same or different ways, nor is their interaction understood in situations where the two types are combined in a single experiment. To investigate this question we have developed a novel learning paradigm for Mongolian gerbils, which not only allows rewards and punishments to be presented in isolation or in combination with each other, but also can use these opposite reinforcers to drive the same learned behavior. Specifically, we studied learning of tone-conditioned hurdle crossing in a shuttle box driven by either an appetitive reinforcer (brain stimulation reward) or an aversive reinforcer (electrical footshock), or by a combination of both. Combination of the two reinforcers potentiated speed of acquisition, led to maximum possible performance, and delayed extinction as compared to either reinforcer alone. Additional experiments, using partial reinforcement protocols and experiments in which one of the reinforcers was omitted after the animals had been previously trained with the combination of both reinforcers, indicated that appetitive and aversive reinforcers operated together but acted in different ways: in this particular experimental context, punishment appeared to be more effective for initial acquisition and reward more effective to maintain a high level of conditioned responses (CRs). The results imply that learning mechanisms in problem solving were maximally effective when the initial punishment of mistakes was combined with the subsequent rewarding of correct performance. Copyright 2010 IBRO. Published by Elsevier Ltd. All rights reserved.

  5. Representation of Coordination Mechanisms in IMS Learning Design to Support Group-based Learning

    NARCIS (Netherlands)

    Miao, Yongwu; Burgos, Daniel; Griffiths, David; Koper, Rob

    2007-01-01

    Miao, Y., Burgos, D., Griffiths, D., & Koper, R. (2008). Representation of Coordination Mechanisms in IMS Learning Design to Support Group-based Learning. In L. Lockyer, S. Bennet, S. Agostinho & B. Harper (Eds.), Handbook of Research on Learning Design and Learning Objects: Issues, Applications and

  6. Distributional Language Learning: Mechanisms and Models of ategory Formation.

    Science.gov (United States)

    Aslin, Richard N; Newport, Elissa L

    2014-09-01

    In the past 15 years, a substantial body of evidence has confirmed that a powerful distributional learning mechanism is present in infants, children, adults and (at least to some degree) in nonhuman animals as well. The present article briefly reviews this literature and then examines some of the fundamental questions that must be addressed for any distributional learning mechanism to operate effectively within the linguistic domain. In particular, how does a naive learner determine the number of categories that are present in a corpus of linguistic input and what distributional cues enable the learner to assign individual lexical items to those categories? Contrary to the hypothesis that distributional learning and category (or rule) learning are separate mechanisms, the present article argues that these two seemingly different processes---acquiring specific structure from linguistic input and generalizing beyond that input to novel exemplars---actually represent a single mechanism. Evidence in support of this single-mechanism hypothesis comes from a series of artificial grammar-learning studies that not only demonstrate that adults can learn grammatical categories from distributional information alone, but that the specific patterning of distributional information among attested utterances in the learning corpus enables adults to generalize to novel utterances or to restrict generalization when unattested utterances are consistently absent from the learning corpus. Finally, a computational model of distributional learning that accounts for the presence or absence of generalization is reviewed and the implications of this model for linguistic-category learning are summarized.

  7. Virtual learning environment for interactive engagement with advanced quantum mechanics

    Directory of Open Access Journals (Sweden)

    Mads Kock Pedersen

    2016-04-01

    Full Text Available A virtual learning environment can engage university students in the learning process in ways that the traditional lectures and lab formats cannot. We present our virtual learning environment StudentResearcher, which incorporates simulations, multiple-choice quizzes, video lectures, and gamification into a learning path for quantum mechanics at the advanced university level. StudentResearcher is built upon the experiences gathered from workshops with the citizen science game Quantum Moves at the high-school and university level, where the games were used extensively to illustrate the basic concepts of quantum mechanics. The first test of this new virtual learning environment was a 2014 course in advanced quantum mechanics at Aarhus University with 47 enrolled students. We found increased learning for the students who were more active on the platform independent of their previous performances.

  8. Virtual Learning Environment for Interactive Engagement with Advanced Quantum Mechanics

    Science.gov (United States)

    Pedersen, Mads Kock; Skyum, Birk; Heck, Robert; Müller, Romain; Bason, Mark; Lieberoth, Andreas; Sherson, Jacob F.

    2016-06-01

    A virtual learning environment can engage university students in the learning process in ways that the traditional lectures and lab formats cannot. We present our virtual learning environment StudentResearcher, which incorporates simulations, multiple-choice quizzes, video lectures, and gamification into a learning path for quantum mechanics at the advanced university level. StudentResearcher is built upon the experiences gathered from workshops with the citizen science game Quantum Moves at the high-school and university level, where the games were used extensively to illustrate the basic concepts of quantum mechanics. The first test of this new virtual learning environment was a 2014 course in advanced quantum mechanics at Aarhus University with 47 enrolled students. We found increased learning for the students who were more active on the platform independent of their previous performances.

  9. Function approximation using combined unsupervised and supervised learning.

    Science.gov (United States)

    Andras, Peter

    2014-03-01

    Function approximation is one of the core tasks that are solved using neural networks in the context of many engineering problems. However, good approximation results need good sampling of the data space, which usually requires exponentially increasing volume of data as the dimensionality of the data increases. At the same time, often the high-dimensional data is arranged around a much lower dimensional manifold. Here we propose the breaking of the function approximation task for high-dimensional data into two steps: (1) the mapping of the high-dimensional data onto a lower dimensional space corresponding to the manifold on which the data resides and (2) the approximation of the function using the mapped lower dimensional data. We use over-complete self-organizing maps (SOMs) for the mapping through unsupervised learning, and single hidden layer neural networks for the function approximation through supervised learning. We also extend the two-step procedure by considering support vector machines and Bayesian SOMs for the determination of the best parameters for the nonlinear neurons in the hidden layer of the neural networks used for the function approximation. We compare the approximation performance of the proposed neural networks using a set of functions and show that indeed the neural networks using combined unsupervised and supervised learning outperform in most cases the neural networks that learn the function approximation using the original high-dimensional data.

  10. Combining traditional anatomy lectures with e-learning activities: how do students perceive their learning experience?

    Science.gov (United States)

    Lochner, Lukas; Wieser, Heike; Waldboth, Simone; Mischo-Kelling, Maria

    2016-02-21

    The purpose of this study was to investigate how students perceived their learning experience when combining traditional anatomy lectures with preparatory e-learning activities that consisted of fill-in-the-blank assignments, videos, and multiple-choice quizzes. A qualitative study was conducted to explore changes in study behaviour and perception of learning. Three group interviews with students were conducted and thematically analysed. Data was categorized into four themes: 1. Approaching the course material, 2. Understanding the material, 3. Consolidating the material, and 4. Perceived learning outcome. Students appreciated the clear structure of the course, and reported that online activities encouraged them towards a first engagement with the material. They felt that they were more active during in-class sessions, described self-study before the end-of-term exam as easier, and believed that contents would remain in their memories for a longer time. By adjusting already existing resources, lectures can be combined fairly easily and cost-effectively with preparatory e-learning activities. The creation of online components promote well-structured courses, can help minimize 'student passivity' as a characteristic element of lectures, and can support students in distributing their studies throughout the term, thus suggesting enhanced learning. Further research work should be designed to confirm the afore-mentioned findings through objective measurements of student learning outcomes.

  11. Combining traditional anatomy lectures with e-learning activities: how do students perceive their learning experience?

    Science.gov (United States)

    Wieser, Heike; Waldboth, Simone; Mischo-Kelling, Maria

    2016-01-01

    Objectives The purpose of this study was to investigate how students perceived their learning experience when combining traditional anatomy lectures with preparatory e-learning activities that consisted of fill-in-the-blank assignments, videos, and multiple-choice quizzes. Methods A qualitative study was conducted to explore changes in study behaviour and perception of learning. Three group interviews with students were conducted and thematically analysed. Results Data was categorized into four themes: 1. Approaching the course material, 2. Understanding the material, 3. Consolidating the material, and 4. Perceived learning outcome.  Students appreciated the clear structure of the course, and reported that online activities encouraged them towards a first engagement with the material. They felt that they were more active during in-class sessions, described self-study before the end-of-term exam as easier, and believed that contents would remain in their memories for a longer time. Conclusions By adjusting already existing resources, lectures can be combined fairly easily and cost-effectively with preparatory e-learning activities. The creation of online components promote well-structured courses, can help minimize ‘student passivity’ as a characteristic element of lectures, and can support students in distributing their studies throughout the term, thus suggesting enhanced learning. Further research work should be designed to confirm the afore-mentioned findings through objective measurements of student learning outcomes. PMID:26897012

  12. Neurobiological mechanisms underlying the blocking effect in aversive learning.

    Science.gov (United States)

    Eippert, Falk; Gamer, Matthias; Büchel, Christian

    2012-09-19

    Current theories of classical conditioning assume that learning depends on the predictive relationship between events, not just on their temporal contiguity. Here we employ the classic experiment substantiating this reasoning-the blocking paradigm-in combination with functional magnetic resonance imaging (fMRI) to investigate whether human amygdala responses in aversive learning conform to these assumptions. In accordance with blocking, we demonstrate that significantly stronger behavioral and amygdala responses are evoked by conditioned stimuli that are predictive of the unconditioned stimulus than by conditioned stimuli that have received the same pairing with the unconditioned stimulus, yet have no predictive value. When studying the development of this effect, we not only observed that it was related to the strength of previous conditioned responses, but also that predictive compared with nonpredictive conditioned stimuli received more overt attention, as measured by fMRI-concurrent eye tracking, and that this went along with enhanced amygdala responses. We furthermore observed that prefrontal regions play a role in the development of the blocking effect: ventromedial prefrontal cortex (subgenual anterior cingulate) only exhibited responses when conditioned stimuli had to be established as nonpredictive for an outcome, whereas dorsolateral prefrontal cortex also showed responses when conditioned stimuli had to be established as predictive. Most importantly, dorsolateral prefrontal cortex connectivity to amygdala flexibly switched between positive and negative coupling, depending on the requirements posed by predictive relationships. Together, our findings highlight the role of predictive value in explaining amygdala responses and identify mechanisms that shape these responses in human fear conditioning.

  13. Interactive Rhythm Learning System by Combining Tablet Computers and Robots

    Directory of Open Access Journals (Sweden)

    Chien-Hsing Chou

    2017-03-01

    Full Text Available This study proposes a percussion learning device that combines tablet computers and robots. This device comprises two systems: a rhythm teaching system, in which users can compose and practice rhythms by using a tablet computer, and a robot performance system. First, teachers compose the rhythm training contents on the tablet computer. Then, the learners practice these percussion exercises by using the tablet computer and a small drum set. The teaching system provides a new and user-friendly score editing interface for composing a rhythm exercise. It also provides a rhythm rating function to facilitate percussion training for children and improve the stability of rhythmic beating. To encourage children to practice percussion exercises, a robotic performance system is used to interact with the children; this system can perform percussion exercises for students to listen to and then help them practice the exercise. This interaction enhances children’s interest and motivation to learn and practice rhythm exercises. The results of experimental course and field trials reveal that the proposed system not only increases students’ interest and efficiency in learning but also helps them in understanding musical rhythms through interaction and composing simple rhythms.

  14. Cooperative Learning in a Soil Mechanics Course at Undergraduate Level

    Science.gov (United States)

    Pinho-Lopes, M.; Macedo, J.; Bonito, F.

    2011-01-01

    The implementation of the Bologna Process enforced a significant change on traditional learning models, which were focused mainly on the transmission of knowledge. The results obtained in a first attempt at implementation of a cooperative learning model in the Soil Mechanics I course of the Department of Civil Engineering of the University of…

  15. Implicit and Explicit Learning Mechanisms Meet in Monkey Prefrontal Cortex.

    Science.gov (United States)

    Chafee, Matthew V; Crowe, David A

    2017-10-11

    In this issue, Loonis et al. (2017) provide the first description of unique synchrony patterns differentiating implicit and explicit forms of learning in monkey prefrontal networks. Their results have broad implications for how prefrontal networks integrate the two learning mechanisms to control behavior. Copyright © 2017 Elsevier Inc. All rights reserved.

  16. Best practices for learning physiology: combining classroom and online methods.

    Science.gov (United States)

    Anderson, Lisa C; Krichbaum, Kathleen E

    2017-09-01

    Physiology is a requisite course for many professional allied health programs and is a foundational science for learning pathophysiology, health assessment, and pharmacology. Given the demand for online learning in the health sciences, it is important to evaluate the efficacy of online and in-class teaching methods, especially as they are combined to form hybrid courses. The purpose of this study was to compare two hybrid physiology sections in which one section was offered mostly in-class (85% in-class), and the other section was offered mostly online (85% online). The two sections in 2 yr ( year 1 and year 2 ) were compared in terms of knowledge of physiology measured in exam scores and pretest-posttest improvement, and in measures of student satisfaction with teaching. In year 1 , there were some differences on individual exam scores between the two sections, but no significant differences in mean exam scores or in pretest-posttest improvements. However, in terms of student satisfaction, the mostly in-class students in year 1 rated the instructor significantly higher than did the mostly online students. Comparisons between in-class and online students in the year 2 cohort yielded data that showed that mean exam scores were not statistically different, but pre-post changes were significantly greater in the mostly online section; student satisfaction among mostly online students also improved significantly. Education researchers must investigate effective combinations of in-class and online methods for student learning outcomes, while maintaining the flexibility and convenience that online methods provide. Copyright © 2017 the American Physiological Society.

  17. Use of the 5E learning cycle model combined with problem-based learning for a fundamentals of nursing course.

    Science.gov (United States)

    Jun, Won Hee; Lee, Eun Ju; Park, Han Jong; Chang, Ae Kyung; Kim, Mi Ja

    2013-12-01

    The 5E learning cycle model has shown a positive effect on student learning in science education, particularly in courses with theory and practice components. Combining problem-based learning (PBL) with the 5E learning cycle was suggested as a better option for students' learning of theory and practice. The purpose of this study was to compare the effects of the traditional learning method with the 5E learning cycle model with PBL. The control group (n = 78) was subjected to a learning method that consisted of lecture and practice. The experimental group (n = 83) learned by using the 5E learning cycle model with PBL. The results showed that the experimental group had significantly improved self-efficacy, critical thinking, learning attitude, and learning satisfaction. Such an approach could be used in other countries to enhance students' learning of fundamental nursing. Copyright 2013, SLACK Incorporated.

  18. Adaptive rival penalized competitive learning and combined linear predictor model for financial forecast and investment.

    Science.gov (United States)

    Cheung, Y M; Leung, W M; Xu, L

    1997-01-01

    We propose a prediction model called Rival Penalized Competitive Learning (RPCL) and Combined Linear Predictor method (CLP), which involves a set of local linear predictors such that a prediction is made by the combination of some activated predictors through a gating network (Xu et al., 1994). Furthermore, we present its improved variant named Adaptive RPCL-CLP that includes an adaptive learning mechanism as well as a data pre-and-post processing scheme. We compare them with some existing models by demonstrating their performance on two real-world financial time series--a China stock price and an exchange-rate series of US Dollar (USD) versus Deutschmark (DEM). Experiments have shown that Adaptive RPCL-CLP not only outperforms the other approaches with the smallest prediction error and training costs, but also brings in considerable high profits in the trading simulation of foreign exchange market.

  19. 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.

  20. Mechanisms underlying the social enhancement of vocal learning in songbirds.

    Science.gov (United States)

    Chen, Yining; Matheson, Laura E; Sakata, Jon T

    2016-06-14

    Social processes profoundly influence speech and language acquisition. Despite the importance of social influences, little is known about how social interactions modulate vocal learning. Like humans, songbirds learn their vocalizations during development, and they provide an excellent opportunity to reveal mechanisms of social influences on vocal learning. Using yoked experimental designs, we demonstrate that social interactions with adult tutors for as little as 1 d significantly enhanced vocal learning. Social influences on attention to song seemed central to the social enhancement of learning because socially tutored birds were more attentive to the tutor's songs than passively tutored birds, and because variation in attentiveness and in the social modulation of attention significantly predicted variation in vocal learning. Attention to song was influenced by both the nature and amount of tutor song: Pupils paid more attention to songs that tutors directed at them and to tutors that produced fewer songs. Tutors altered their song structure when directing songs at pupils in a manner that resembled how humans alter their vocalizations when speaking to infants, that was distinct from how tutors changed their songs when singing to females, and that could influence attention and learning. Furthermore, social interactions that rapidly enhanced learning increased the activity of noradrenergic and dopaminergic midbrain neurons. These data highlight striking parallels between humans and songbirds in the social modulation of vocal learning and suggest that social influences on attention and midbrain circuitry could represent shared mechanisms underlying the social modulation of vocal learning.

  1. MECHANICAL BEHAVIOR OF PRESTRESSED VISCOELASTIC ADHESIVE AREAS UNDER COMBINING LOADINGS

    Directory of Open Access Journals (Sweden)

    Halil Murat Enginsoy

    2017-12-01

    Full Text Available In this article, mechanical behaviors of adhesive tape VHB 4950 elastomeric material, which is an element of acrylic polymer group and which is in viscoelastic behavior, under different pre-stress conditions and complex forces of different geometric parameters created by combining loadings have been experimentally and numerically investigated. In experimental studies, loading-unloading cyclic tests, one of the different standardized tests for the mechanical characterization of viscoelastic material, have been applied which give the most suitable convergent optimization parameters for the finite element model. Different material models were also investigated by using the data obtained from loading-unloading test results in all numerical models. According to the experimental results, the most suitable material parameters were determined with the Abaqus Parallel Rheological Framework Model (PRF for 4 Yeoh Networks with Bergstrom-Boyce Flow model created in the Mcalibration software for finite element analysis. Subsequently, using these material parameters, finite element analysis was performed as three dimension non-linear viscoelastic with a commercial finite element software Abaqus. The finite element analysis results showed good correlation to the Force (N-Displacement (mm experimental data for maximum load-carrying capacity of structural specimens.

  2. Identification of learning mechanisms in a wild meerkat population.

    Directory of Open Access Journals (Sweden)

    Will Hoppitt

    Full Text Available Vigorous debates as to the evolutionary origins of culture remain unresolved due to an absence of methods for identifying learning mechanisms in natural populations. While laboratory experiments on captive animals have revealed evidence for a number of mechanisms, these may not necessarily reflect the processes typically operating in nature. We developed a novel method that allows social and asocial learning mechanisms to be determined in animal groups from the patterns of interaction with, and solving of, a task. We deployed it to analyse learning in groups of wild meerkats (Suricata suricatta presented with a novel foraging apparatus. We identify nine separate learning processes underlying the meerkats' foraging behaviour, in each case precisely quantifying their strength and duration, including local enhancement, emulation, and a hitherto unrecognized form of social learning, which we term 'observational perseverance'. Our analysis suggests a key factor underlying the stability of behavioural traditions is a high ratio of specific to generalized social learning effects. The approach has widespread potential as an ecologically valid tool to investigate learning mechanisms in natural groups of animals, including humans.

  3. Properties and mechanisms of olfactory learning and memory

    Directory of Open Access Journals (Sweden)

    Michelle T Tong

    2014-07-01

    Full Text Available Memories are dynamic physical phenomena with psychometric forms as well as characteristic timescales. Most of our understanding of the cellular mechanisms underlying the neurophysiology of memory, however, derives from one-trial learning paradigms that, while powerful, do not fully embody the gradual, representational, and statistical aspects of cumulative learning. The early olfactory system -- particularly olfactory bulb -- comprises a reasonably well-understood and experimentally accessible neuronal network with intrinsic plasticity that underlies both one-trial (adult aversive, neonatal and cumulative (adult appetitive odor learning. These olfactory circuits employ many of the same molecular and structural mechanisms of memory as, for example, hippocampal circuits following inhibitory avoidance conditioning, but the temporal sequences of post-conditioning molecular events are likely to differ owing to the need to incorporate new information from ongoing learning events into the evolving memory trace. Moreover, the shapes of acquired odor representations, and their gradual transformation over the course of cumulative learning, also can be directly measured, adding an additional representational dimension to the traditional metrics of memory strength and persistence. In this review, we describe some established molecular and structural mechanisms of memory with a focus on the timecourses of post-conditioning molecular processes. We describe the properties of odor learning intrinsic to the olfactory bulb and review the utility of the olfactory system of adult rodents as a memory system in which to study the cellular mechanisms of cumulative learning.

  4. Time to rethink the neural mechanisms of learning and memory.

    Science.gov (United States)

    Gallistel, Charles R; Balsam, Peter D

    2014-02-01

    Most studies in the neurobiology of learning assume that the underlying learning process is a pairing - dependent change in synaptic strength that requires repeated experience of events presented in close temporal contiguity. However, much learning is rapid and does not depend on temporal contiguity, which has never been precisely defined. These points are well illustrated by studies showing that the temporal relations between events are rapidly learned- even over long delays- and that this knowledge governs the form and timing of behavior. The speed with which anticipatory responses emerge in conditioning paradigms is determined by the information that cues provide about the timing of rewards. The challenge for understanding the neurobiology of learning is to understand the mechanisms in the nervous system that encode information from even a single experience, the nature of the memory mechanisms that can encode quantities such as time, and how the brain can flexibly perform computations based on this information. Copyright © 2013 Elsevier Inc. All rights reserved.

  5. Atomistic insight into the catalytic mechanism of glycosyltransferases by combined quantum mechanics/molecular mechanics (QM/MM) methods.

    Science.gov (United States)

    Tvaroška, Igor

    2015-02-11

    Glycosyltransferases catalyze the formation of glycosidic bonds by assisting the transfer of a sugar residue from donors to specific acceptor molecules. Although structural and kinetic data have provided insight into mechanistic strategies employed by these enzymes, molecular modeling studies are essential for the understanding of glycosyltransferase catalyzed reactions at the atomistic level. For such modeling, combined quantum mechanics/molecular mechanics (QM/MM) methods have emerged as crucial. These methods allow the modeling of enzymatic reactions by using quantum mechanical methods for the calculation of the electronic structure of the active site models and treating the remaining enzyme environment by faster molecular mechanics methods. Herein, the application of QM/MM methods to glycosyltransferase catalyzed reactions is reviewed, and the insight from modeling of glycosyl transfer into the mechanisms and transition states structures of both inverting and retaining glycosyltransferases are discussed. Copyright © 2014 Elsevier Ltd. All rights reserved.

  6. A blended learning approach to teach fluid mechanics in engineering

    Science.gov (United States)

    Rahman, Ataur

    2017-05-01

    This paper presents a case study on the teaching and learning of fluid mechanics at the University of Western Sydney (UWS), Australia, by applying a blended learning approach (BLA). In the adopted BLA, various flexible learning materials have been made available to the students such as online recorded lectures, online recorded tutorials, hand written tutorial solutions, discussion board and online practice quizzes. The lecture and tutorial class times have been primarily utilised to discuss confusing topics and engage students with practical issues in applying the theories learnt in fluid mechanics. Based on the data of over 734 students over a 4-year period, it has been shown that a BLA has improved the learning experience of the fluid mechanics students in UWS. The overall percentage of student satisfaction in this subject has increased by 18% in the BLA case compared with the traditional one.

  7. The Use of a Hybrid Strategy Combining Problem-based Learning and Magisterial Lectures to Enhance Learning

    Directory of Open Access Journals (Sweden)

    Carlos Alberto Acosta-Nassar

    2014-09-01

    Full Text Available This paper addresses the problem of capturing the attention of intermediate level students in the Thermodynamics 1 course from the Mechanical and Agricultural Engineering Program, with the purpose of helping students improve their learning process. A hybrid teaching strategy was proposed based on Problem-based Learning (PBL principles combined with magisterial lectures. Digital and traditional didactic resources were also used in order to find the best mean to minimize the lack of attention in learners. The strategy was developed by sensitizing students to get involved in their formation process. PowerPoint presentations, video clips, the traditional white board and an ultra slim digital tablet board were used to develop the theoretical issues and present the solutions to the problems chosen for the PBL strategy. Finally, the strategy was evaluated and results were analyzed, indicating that using a hybrid strategy combining PBL and traditional magisterial lectures is an optimal resource to improve the learning process of students taking Thermodynamics 1. In addition, it was also concluded that the ultra slim digital tablet board is the optimal didactic resource.

  8. Quantum opto-mechanics with micromirrors : combining nano-mechanics with quantum optics

    International Nuclear Information System (INIS)

    Groeblacher, S.

    2010-01-01

    This work describes more than four years of research on the effects of the radiation-pressure force of light on macroscopic mechanical structures. The basic system studied here is a mechanical oscillator that is highly reflective and part of an optical resonator. It interacts with the optical cavity mode via the radiation-pressure force. Both the dynamics of the mechanical oscillation and the properties of the light field are modified through this interaction. In our experiments we use quantum optical tools (such as homodyning and down-conversion) with the goal of ultimately showing quantum behavior of the mechanical center of mass motion. In this thesis we present several experiments that pave the way towards this goal and when combined should allow the demonstration of the envisioned quantum phenomena, including entanglement, teleportation and Schroeodinger cat states. The study of quantum behavior of truly macroscopic systems is a long outstanding goal, which will help to answer some of the most fundamental questions in quantum physics today: Why is the world around us classical and not quantum? Is there a size- or mass-limit to systems for them to behave according to quantum mechanics? Is quantum theory complete or do we have to extend it to include mechanisms such as decoherence? Can we use the quantum nature of macroscopic objects to, for example, improve the measurement precision of classical apparatuses? The experiments discussed in this thesis include the very first passive radiation-pressure cooling of a mechanical oscillator in a cryogenic optical resonator, as well as the experimental demonstration of radiation-pressure cooling close to the mechanical quantum ground state. Cooling of the mechanical motion is an important pre-condition for observing quantum effects of the mechanical oscillator. In another experiment, we have demonstrated that we are able to enter the strong-coupling regime of the optomechanical system a regime where coherent energy

  9. Adhesive wear mechanism under combined electric diamond grinding

    Directory of Open Access Journals (Sweden)

    Popov Vyacheslav

    2017-01-01

    Full Text Available The article provides a scientific substantiation of loading of metal-bond diamond grinding wheels and describes the mechanism of contact interaction (interlocking of wheels with tool steel as well as its general properties having an influence on combined electric diamond grinding efficiency. The study concluded that a loaded layer can be formed in a few stages different by nature. It is known, that one of the causes of grinding degradation is a continuous loading of active grits (abrasive grinding tool by workpiece chips. It all affects the diamond grinding wheels efficiency and grinding ability with a result in increase of tool pressure, contact temperature and wheels specific removal rate. Science has partially identified some various methods to minimize grinding wheel loading, however, as to loading of metal-bond diamond grinding wheels the search is still in progress. Therefore, research people have to state, that in spite of the fact that the wheels made of cubic boron nitride are of little use as applied to ceramic, ultrahard, hard-alloyed hard-to-machine and nano-materials of the time, but manufactures have to apply cubic boron nitride wheels wherein diamond ones preferable.

  10. Statistical learning: a powerful mechanism that operates by mere exposure.

    Science.gov (United States)

    Aslin, Richard N

    2017-01-01

    How do infants learn so rapidly and with little apparent effort? In 1996, Saffran, Aslin, and Newport reported that 8-month-old human infants could learn the underlying temporal structure of a stream of speech syllables after only 2 min of passive listening. This demonstration of what was called statistical learning, involving no instruction, reinforcement, or feedback, led to dozens of confirmations of this powerful mechanism of implicit learning in a variety of modalities, domains, and species. These findings reveal that infants are not nearly as dependent on explicit forms of instruction as we might have assumed from studies of learning in which children or adults are taught facts such as math or problem solving skills. Instead, at least in some domains, infants soak up the information around them by mere exposure. Learning and development in these domains thus appear to occur automatically and with little active involvement by an instructor (parent or teacher). The details of this statistical learning mechanism are discussed, including how exposure to specific types of information can, under some circumstances, generalize to never-before-observed information, thereby enabling transfer of learning. WIREs Cogn Sci 2017, 8:e1373. doi: 10.1002/wcs.1373 For further resources related to this article, please visit the WIREs website. © 2016 Wiley Periodicals, Inc.

  11. Learning Human Actions by Combining Global Dynamics and Local Appearance.

    Science.gov (United States)

    Luo, Guan; Yang, Shuang; Tian, Guodong; Yuan, Chunfeng; Hu, Weiming; Maybank, Stephen J

    2014-12-01

    In this paper, we address the problem of human action recognition through combining global temporal dynamics and local visual spatio-temporal appearance features. For this purpose, in the global temporal dimension, we propose to model the motion dynamics with robust linear dynamical systems (LDSs) and use the model parameters as motion descriptors. Since LDSs live in a non-Euclidean space and the descriptors are in non-vector form, we propose a shift invariant subspace angles based distance to measure the similarity between LDSs. In the local visual dimension, we construct curved spatio-temporal cuboids along the trajectories of densely sampled feature points and describe them using histograms of oriented gradients (HOG). The distance between motion sequences is computed with the Chi-Squared histogram distance in the bag-of-words framework. Finally we perform classification using the maximum margin distance learning method by combining the global dynamic distances and the local visual distances. We evaluate our approach for action recognition on five short clips data sets, namely Weizmann, KTH, UCF sports, Hollywood2 and UCF50, as well as three long continuous data sets, namely VIRAT, ADL and CRIM13. We show competitive results as compared with current state-of-the-art methods.

  12. Combining lived experience with the facilitation of enquiry-based learning: a 'trigger' for transformative learning.

    Science.gov (United States)

    Stacey, G; Oxley, R; Aubeeluck, A

    2015-09-01

    What is known on the subject The values underpinning recovery-orientated practice are recited in the literature and influential in the content of mental health nurse education internationally. However, scepticism exists regarding the degree to which students' assimilate the principles of recovery into their practice due to the troublesome and challenging nature of learning at a transformational level, also known as threshold concept learning. Evaluation suggests that this combination of educational approaches positively influences students' prior understandings, beliefs and values in relation to the prospect for people with significant mental health problems to recover. The components of threshold concepts are useful as a deductive framework for the evaluation of educational initiatives which attempt to initiate transformative learning. While this forum clearly holds significant potential for student development, support and preparation is needed for both the student and the facilitator in order to enable the possibility of learning which influences attitudes, beliefs and practice. The aim of this paper is to discuss the potential for combining lived experience of mental distress with the facilitation of enquiry-based learning (EBL) to act as a trigger for transformative learning in the context of promoting the understanding of mental health 'recovery' in nurse education.The values underpinning recovery-orientated practice are recited in the literature and influential in mental health nurse education internationally. However, scepticism exists regarding the degree to which students assimilate into their practice. An open-ended was distributed to a cohort of pre-registration nursing students receiving the co-facilitated EBL (n = 112). Data demonstrated how the specific attributes of this educational approach were identified by students as impacting positively on ill-informed preconceptions, understanding of complex theory and their future practice. Results were

  13. Application of ICT supported learning in fluid mechanics

    DEFF Research Database (Denmark)

    Brohus, Henrik; Svidt, Kjeld

    2004-01-01

    of tools for knowledge transfer facilitates deep understanding and increases learning efficiency. Air flow is by nature invisible and represents a further challenge in the effort of providing sufficient understanding of typical flow patterns and behaviour of room air flow. An example of visualisation......This paper focuses on the application of ICT, Information & Communication Technology, supported learning in the area of fluid mechanics education. Taking a starting point in a course in Ventilation Technology, including room air flow and contaminant distribution, it explains how ICT may be used...... actively in the learning environment to increase efficiency in the learning process. The paper comprises past experiences and lessons learnt as well as prospect for future development in the area. A model is presented that describes a high efficiency learning environment where ICT plays an important role...

  14. Neurocomputational mechanisms of prosocial learning and links to empathy.

    Science.gov (United States)

    Lockwood, Patricia L; Apps, Matthew A J; Valton, Vincent; Viding, Essi; Roiser, Jonathan P

    2016-08-30

    Reinforcement learning theory powerfully characterizes how we learn to benefit ourselves. In this theory, prediction errors-the difference between a predicted and actual outcome of a choice-drive learning. However, we do not operate in a social vacuum. To behave prosocially we must learn the consequences of our actions for other people. Empathy, the ability to vicariously experience and understand the affect of others, is hypothesized to be a critical facilitator of prosocial behaviors, but the link between empathy and prosocial behavior is still unclear. During functional magnetic resonance imaging (fMRI) participants chose between different stimuli that were probabilistically associated with rewards for themselves (self), another person (prosocial), or no one (control). Using computational modeling, we show that people can learn to obtain rewards for others but do so more slowly than when learning to obtain rewards for themselves. fMRI revealed that activity in a posterior portion of the subgenual anterior cingulate cortex/basal forebrain (sgACC) drives learning only when we are acting in a prosocial context and signals a prosocial prediction error conforming to classical principles of reinforcement learning theory. However, there is also substantial variability in the neural and behavioral efficiency of prosocial learning, which is predicted by trait empathy. More empathic people learn more quickly when benefitting others, and their sgACC response is the most selective for prosocial learning. We thus reveal a computational mechanism driving prosocial learning in humans. This framework could provide insights into atypical prosocial behavior in those with disorders of social cognition.

  15. Enhanced Mechanical Properties of Poplar Wood by a Combined-Hydro-Thermo-Mechanical (CHTM) Modification

    OpenAIRE

    Houri Sharifnia; Behbood Mohebbi

    2011-01-01

    The current research explains an innovated technique to enhanced mechanice properties of poplar wood by combination of two modification techniques, hydrothermal and mechanical. Blocks of 50×55×500mm3 were cut from poplar wood and treated in a reactor at 120, 150 and 180°C for 30 min. Afterwards, the blocks were pressed at 180°C for 20 min at a pressure of 80 bar to achieve a compression set of 60% in radial direction. Density and bending properties (moduli of elasticity and rupture) as well a...

  16. Unravelling salutogenic mechanisms in the workplace: the role of learning.

    Science.gov (United States)

    Pijpker, Roald; Vaandrager, Lenneke; Bakker, Evert Jan; Koelen, Maria

    To explore the moderating and mediating role(s) of learning within the relationship between sense of coherence (SOC) and generalized resistance resources. Cross-sectional study (N=481), using a self-administered questionnaire, of employees working in the healthcare sector in the Netherlands in 2017. Four residential healthcare settings and one healthcare-related Facebook group were involved. Multiple linear regression models were used to test for moderating and mediating effects of learning. Social relations, task significance, and job control significantly explained variance in SOC. Conceptual, social, and instrumental learning, combined, moderated the relationship between SOC and task significance. Instrumental learning moderated the relationship between job control and SOC. Social learning also mediated this relationship. Conceptual learning did not show any moderating or mediating effect. The relationship between SOC and the three GRRs seems to be strengthened or explained-to a certain extent-by instrumental and social learning. Healthcare organizations are recommended to promote learning through formal activities as well as through cooperation, feedback, sharing experiences, and job challenges. This requires employee participation and a multilevel interdisciplinary approach. Copyright © 2018 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.

  17. Self-Assessment Exercises in Continuum Mechanics with Autonomous Learning

    Science.gov (United States)

    Marcé-Nogué, Jordi; Gil, LLuís; Pérez, Marco A.; Sánchez, Montserrat

    2013-01-01

    The main objective of this work is to generate a set of exercises to improve the autonomous learning in "Continuum Mechanics" through a virtual platform. Students will have to resolve four exercises autonomously related to the subject developed in class and they will post the solutions on the virtual platform within a deadline. Students…

  18. A new approach to teaching and learning mechanics

    NARCIS (Netherlands)

    Westra, A.S.

    2006-01-01

    In this thesis a research project is described that took place from 2000 until 2004 in the Centre for Science and Mathematics Education in Utrecht. It involves a didactical research into the teaching and learning of an introduction to mechanics for fourth grade pre-university level students (Dutch:

  19. Exploring the mechanisms through which computers contribute to learning.

    NARCIS (Netherlands)

    Karasavvidis, I.; Karasavvidis, I.; Pieters, Julius Marie; Plomp, T.

    2003-01-01

    Even though it has been established that the incorporation of computers into the teaching and learning process enhances student performance, the underlying mechanisms through which this is accomplished have been largely unexplored. The present study aims to shed light on this issue. Two groups of 10

  20. Studying the mechanisms of language learning by varying the learning environment and the learner.

    Science.gov (United States)

    Goldin-Meadow, Susan

    Language learning is a resilient process, and many linguistic properties can be developed under a wide range of learning environments and learners. The first goal of this review is to describe properties of language that can be developed without exposure to a language model - the resilient properties of language - and to explore conditions under which more fragile properties emerge. But even if a linguistic property is resilient, the developmental course that the property follows is likely to vary as a function of learning environment and learner, that is, there are likely to be individual differences in the learning trajectories children follow. The second goal is to consider how the resilient properties are brought to bear on language learning when a child is exposed to a language model. The review ends by considering the implications of both sets of findings for mechanisms, focusing on the role that the body and linguistic input play in language learning.

  1. COMBINING COOPERATIVE LEARNING WITH READING ALOUD BY TEACHERS

    Directory of Open Access Journals (Sweden)

    George Jacobs

    2004-06-01

    Full Text Available This article begins with a section that describes cooperative learning and explains eight cooperative learning principles. The second section discusses the interface between cooperative learning and language pedagogy. Next is a section about the why and how of reading aloud by teachers. The heart of the article resides in the last and longest section which describes techniques for integrating cooperative learning with reading aloud by teachers. These techniques include ones that can be used before, while and after the teacher has read aloud to the class.

  2. Combining theories to reach multi-faceted insights into learning opportunities in doctoral supervision

    DEFF Research Database (Denmark)

    Kobayashi, Sofie; Rump, Camilla Østerberg

    The aim of this paper is to illustrate how theories can be combined to explore opportunities for learning in doctoral supervision. While our earlier research into learning dynamics in doctoral supervision in life science research (Kobayashi, 2014) has focused on illustrating learning opportunitie...

  3. The Effect of Known-and-Unknown Word Combinations on Intentional Vocabulary Learning

    Science.gov (United States)

    Kasahara, Kiwamu

    2011-01-01

    The purpose of this study is to examine whether learning a known-and-unknown word combination is superior in terms of retention and retrieval of meaning to learning a single unknown word. The term "combination" in this study means a two-word collocation of a familiar word and a word that is new to the participants. Following the results of…

  4. Parametrization of Combined Quantum Mechanical and Molecular Mechanical Methods: Bond-Tuned Link Atoms.

    Science.gov (United States)

    Wu, Xin-Ping; Gagliardi, Laura; Truhlar, Donald G

    2018-05-30

    Combined quantum mechanical and molecular mechanical (QM/MM) methods are the most powerful available methods for high-level treatments of subsystems of very large systems. The treatment of the QM-MM boundary strongly affects the accuracy of QM/MM calculations. For QM/MM calculations having covalent bonds cut by the QM-MM boundary, it has been proposed previously to use a scheme with system-specific tuned fluorine link atoms. Here, we propose a broadly parametrized scheme where the parameters of the tuned F link atoms depend only on the type of bond being cut. In the proposed new scheme, the F link atom is tuned for systems with a certain type of cut bond at the QM-MM boundary instead of for a specific target system, and the resulting link atoms are call bond-tuned link atoms. In principle, the bond-tuned link atoms can be as convenient as the popular H link atoms, and they are especially well adapted for high-throughput and accurate QM/MM calculations. Here, we present the parameters for several kinds of cut bonds along with a set of validation calculations that confirm that the proposed bond-tuned link-atom scheme can be as accurate as the system-specific tuned F link-atom scheme.

  5. Parametrization of Combined Quantum Mechanical and Molecular Mechanical Methods: Bond-Tuned Link Atoms

    Directory of Open Access Journals (Sweden)

    Xin-Ping Wu

    2018-05-01

    Full Text Available Combined quantum mechanical and molecular mechanical (QM/MM methods are the most powerful available methods for high-level treatments of subsystems of very large systems. The treatment of the QM−MM boundary strongly affects the accuracy of QM/MM calculations. For QM/MM calculations having covalent bonds cut by the QM−MM boundary, it has been proposed previously to use a scheme with system-specific tuned fluorine link atoms. Here, we propose a broadly parametrized scheme where the parameters of the tuned F link atoms depend only on the type of bond being cut. In the proposed new scheme, the F link atom is tuned for systems with a certain type of cut bond at the QM−MM boundary instead of for a specific target system, and the resulting link atoms are call bond-tuned link atoms. In principle, the bond-tuned link atoms can be as convenient as the popular H link atoms, and they are especially well adapted for high-throughput and accurate QM/MM calculations. Here, we present the parameters for several kinds of cut bonds along with a set of validation calculations that confirm that the proposed bond-tuned link-atom scheme can be as accurate as the system-specific tuned F link-atom scheme.

  6. Statistical mechanics of learning orthogonal signals for general covariance models

    International Nuclear Information System (INIS)

    Hoyle, David C

    2010-01-01

    Statistical mechanics techniques have proved to be useful tools in quantifying the accuracy with which signal vectors are extracted from experimental data. However, analysis has previously been limited to specific model forms for the population covariance C, which may be inappropriate for real world data sets. In this paper we obtain new statistical mechanical results for a general population covariance matrix C. For data sets consisting of p sample points in R N we use the replica method to study the accuracy of orthogonal signal vectors estimated from the sample data. In the asymptotic limit of N,p→∞ at fixed α = p/N, we derive analytical results for the signal direction learning curves. In the asymptotic limit the learning curves follow a single universal form, each displaying a retarded learning transition. An explicit formula for the location of the retarded learning transition is obtained and we find marked variation in the location of the retarded learning transition dependent on the distribution of population covariance eigenvalues. The results of the replica analysis are confirmed against simulation

  7. Improving Nursing Students' Learning Outcomes in Fundamentals of Nursing Course through Combination of Traditional and e-Learning Methods.

    Science.gov (United States)

    Sheikhaboumasoudi, Rouhollah; Bagheri, Maryam; Hosseini, Sayed Abbas; Ashouri, Elaheh; Elahi, Nasrin

    2018-01-01

    Fundamentals of nursing course are prerequisite to providing comprehensive nursing care. Despite development of technology on nursing education, effectiveness of using e-learning methods in fundamentals of nursing course is unclear in clinical skills laboratory for nursing students. The aim of this study was to compare the effect of blended learning (combining e-learning with traditional learning methods) with traditional learning alone on nursing students' scores. A two-group post-test experimental study was administered from February 2014 to February 2015. Two groups of nursing students who were taking the fundamentals of nursing course in Iran were compared. Sixty nursing students were selected as control group (just traditional learning methods) and experimental group (combining e-learning with traditional learning methods) for two consecutive semesters. Both groups participated in Objective Structured Clinical Examination (OSCE) and were evaluated in the same way using a prepared checklist and questionnaire of satisfaction. Statistical analysis was conducted through SPSS software version 16. Findings of this study reflected that mean of midterm (t = 2.00, p = 0.04) and final score (t = 2.50, p = 0.01) of the intervention group (combining e-learning with traditional learning methods) were significantly higher than the control group (traditional learning methods). The satisfaction of male students in intervention group was higher than in females (t = 2.60, p = 0.01). Based on the findings, this study suggests that the use of combining traditional learning methods with e-learning methods such as applying educational website and interactive online resources for fundamentals of nursing course instruction can be an effective supplement for improving nursing students' clinical skills.

  8. Combining Formal Logic and Machine Learning for Sentiment Analysis

    DEFF Research Database (Denmark)

    Petersen, Niklas Christoffer; Villadsen, Jørgen

    2014-01-01

    This paper presents a formal logical method for deep structural analysis of the syntactical properties of texts using machine learning techniques for efficient syntactical tagging. To evaluate the method it is used for entity level sentiment analysis as an alternative to pure machine learning...

  9. Combined quantum and molecular mechanics (QM/MM).

    Science.gov (United States)

    Friesner, Richard A

    2004-12-01

    We describe the current state of the art of mixed quantum mechanics/molecular mechanics (QM/MM) methodology, with a particular focus on modeling of enzymatic reactions. Over the past decade, the effectiveness of these methods has increased dramatically, based on improved quantum chemical methods, advances in the description of the QM/MM interface, and reductions in the cost/performance of computing hardware. Two examples of pharmaceutically relevant applications, cytochrome P450 and class C β-lactamase, are presented.: © 2004 Elsevier Ltd . All rights reserved.

  10. Developmental Changes in Learning: Computational Mechanisms and Social Influences

    Directory of Open Access Journals (Sweden)

    Florian Bolenz

    2017-11-01

    Full Text Available Our ability to learn from the outcomes of our actions and to adapt our decisions accordingly changes over the course of the human lifespan. In recent years, there has been an increasing interest in using computational models to understand developmental changes in learning and decision-making. Moreover, extensions of these models are currently applied to study socio-emotional influences on learning in different age groups, a topic that is of great relevance for applications in education and health psychology. In this article, we aim to provide an introduction to basic ideas underlying computational models of reinforcement learning and focus on parameters and model variants that might be of interest to developmental scientists. We then highlight recent attempts to use reinforcement learning models to study the influence of social information on learning across development. The aim of this review is to illustrate how computational models can be applied in developmental science, what they can add to our understanding of developmental mechanisms and how they can be used to bridge the gap between psychological and neurobiological theories of development.

  11. Neuromodulatory adaptive combination of correlation-based learning in cerebellum and reward-based learning in basal ganglia for goal-directed behavior control.

    Science.gov (United States)

    Dasgupta, Sakyasingha; Wörgötter, Florentin; Manoonpong, Poramate

    2014-01-01

    Goal-directed decision making in biological systems is broadly based on associations between conditional and unconditional stimuli. This can be further classified as classical conditioning (correlation-based learning) and operant conditioning (reward-based learning). A number of computational and experimental studies have well established the role of the basal ganglia in reward-based learning, where as the cerebellum plays an important role in developing specific conditioned responses. Although viewed as distinct learning systems, recent animal experiments point toward their complementary role in behavioral learning, and also show the existence of substantial two-way communication between these two brain structures. Based on this notion of co-operative learning, in this paper we hypothesize that the basal ganglia and cerebellar learning systems work in parallel and interact with each other. We envision that such an interaction is influenced by reward modulated heterosynaptic plasticity (RMHP) rule at the thalamus, guiding the overall goal directed behavior. Using a recurrent neural network actor-critic model of the basal ganglia and a feed-forward correlation-based learning model of the cerebellum, we demonstrate that the RMHP rule can effectively balance the outcomes of the two learning systems. This is tested using simulated environments of increasing complexity with a four-wheeled robot in a foraging task in both static and dynamic configurations. Although modeled with a simplified level of biological abstraction, we clearly demonstrate that such a RMHP induced combinatorial learning mechanism, leads to stabler and faster learning of goal-directed behaviors, in comparison to the individual systems. Thus, in this paper we provide a computational model for adaptive combination of the basal ganglia and cerebellum learning systems by way of neuromodulated plasticity for goal-directed decision making in biological and bio-mimetic organisms.

  12. Learning to Generate Sequences with Combination of Hebbian and Non-hebbian Plasticity in Recurrent Spiking Neural Networks.

    Science.gov (United States)

    Panda, Priyadarshini; Roy, Kaushik

    2017-01-01

    Synaptic Plasticity, the foundation for learning and memory formation in the human brain, manifests in various forms. Here, we combine the standard spike timing correlation based Hebbian plasticity with a non-Hebbian synaptic decay mechanism for training a recurrent spiking neural model to generate sequences. We show that inclusion of the adaptive decay of synaptic weights with standard STDP helps learn stable contextual dependencies between temporal sequences, while reducing the strong attractor states that emerge in recurrent models due to feedback loops. Furthermore, we show that the combined learning scheme suppresses the chaotic activity in the recurrent model substantially, thereby enhancing its' ability to generate sequences consistently even in the presence of perturbations.

  13. Combining University Student Self-Regulated Learning Indicators and Engagement with Online Learning Events to Predict Academic Performance

    Science.gov (United States)

    Pardo, Abelardo; Han, Feifei; Ellis, Robert A.

    2017-01-01

    Self-regulated learning theories are used to understand the reasons for different levels of university student academic performance. Similarly, learning analytics research proposes the combination of detailed data traces derived from technology-mediated tasks with a variety of algorithms to predict student academic performance. The former approach…

  14. Space Mechanisms Lessons Learned and Accelerated Testing Studies

    Science.gov (United States)

    Fusaro, Robert L.

    1997-01-01

    A number of mechanism (mechanical moving component) failures and anomalies have recently occurred on satellites. In addition, more demanding operating and life requirements have caused mechanism failures or anomalies to occur even before some satellites were launched (e.g., during the qualification testing of GOES-NEXT, CERES, and the Space Station Freedom Beta Joint Gimbal). For these reasons, it is imperative to determine which mechanisms worked in the past and which have failed so that the best selection of mechanically moving components can be made for future satellites. It is also important to know where the problem areas are so that timely decisions can be made on the initiation of research to develop future needed technology. To chronicle the life and performance characteristics of mechanisms operating in a space environment, a Space Mechanisms Lessons Learned Study was conducted. The work was conducted by the NASA Lewis Research Center and by Mechanical Technologies Inc. (MTI) under contract NAS3-27086. The expectation of the study was to capture and retrieve information relating to the life and performance of mechanisms operating in the space environment to determine what components had operated successfully and what components had produced anomalies.

  15. Characterizing representational learning: A combined simulation and tutorial on perturbation theory

    Directory of Open Access Journals (Sweden)

    Antje Kohnle

    2017-11-01

    Full Text Available Analyzing, constructing, and translating between graphical, pictorial, and mathematical representations of physics ideas and reasoning flexibly through them (“representational competence” is a key characteristic of expertise in physics but is a challenge for learners to develop. Interactive computer simulations and University of Washington style tutorials both have affordances to support representational learning. This article describes work to characterize students’ spontaneous use of representations before and after working with a combined simulation and tutorial on first-order energy corrections in the context of quantum-mechanical time-independent perturbation theory. Data were collected from two institutions using pre-, mid-, and post-tests to assess short- and long-term gains. A representational competence level framework was adapted to devise level descriptors for the assessment items. The results indicate an increase in the number of representations used by students and the consistency between them following the combined simulation tutorial. The distributions of representational competence levels suggest a shift from perceptual to semantic use of representations based on their underlying meaning. In terms of activity design, this study illustrates the need to support students in making sense of the representations shown in a simulation and in learning to choose the most appropriate representation for a given task. In terms of characterizing representational abilities, this study illustrates the usefulness of a framework focusing on perceptual, syntactic, and semantic use of representations.

  16. Characterizing representational learning: A combined simulation and tutorial on perturbation theory

    Science.gov (United States)

    Kohnle, Antje; Passante, Gina

    2017-12-01

    Analyzing, constructing, and translating between graphical, pictorial, and mathematical representations of physics ideas and reasoning flexibly through them ("representational competence") is a key characteristic of expertise in physics but is a challenge for learners to develop. Interactive computer simulations and University of Washington style tutorials both have affordances to support representational learning. This article describes work to characterize students' spontaneous use of representations before and after working with a combined simulation and tutorial on first-order energy corrections in the context of quantum-mechanical time-independent perturbation theory. Data were collected from two institutions using pre-, mid-, and post-tests to assess short- and long-term gains. A representational competence level framework was adapted to devise level descriptors for the assessment items. The results indicate an increase in the number of representations used by students and the consistency between them following the combined simulation tutorial. The distributions of representational competence levels suggest a shift from perceptual to semantic use of representations based on their underlying meaning. In terms of activity design, this study illustrates the need to support students in making sense of the representations shown in a simulation and in learning to choose the most appropriate representation for a given task. In terms of characterizing representational abilities, this study illustrates the usefulness of a framework focusing on perceptual, syntactic, and semantic use of representations.

  17. Thermo-mechanical properties of SOFC components investigated by a combined method

    DEFF Research Database (Denmark)

    Teocoli, Francesca; Esposito, Vincenzo; Ramousse, Severine

    , and differential thermo-mechanical behavior at each layer. The combination of such factors can have a critical effect on the final shape and microstructure, and on the mechanical integrity. Thermo-mechanical properties and sintering mechanisms of important SOFC materials (CGO, YSZ, ScYSZ) were systematically...

  18. 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

  19. The Application of Problem-Based Learning in Mechanical Engineering

    Science.gov (United States)

    Putra, Z. A.; Dewi, M.

    2018-02-01

    The course of Technology and Material Testing prepare students with the ability to do a variety of material testing in the study of mechanical engineering. Students find it difficult to understand the materials to make them unable to carry out the material testing in accordance with the purpose of study. This happens because they knowledge is not adequately supported by the competence to find and construct learning experience. In this study, quasy experiment research method with pre-post-test with control group design was used. The subjects of the study were students divided in two groups; control and experiment with twenty-two students in each group. Study result: their grades showed no difference in between the pre-test or post-test in control group, but the difference in grade existed between the pre-test and post-test in experiment group. Yet, there is no significant difference in the study result on both groups. The researcher recommend that it is necessary to develop Problem-Based Learning that suits need analysis on D3 Program for Mechanical Engineering Department at the State University of Padang, to ensure the compatibility between Model of Study and problems and need. This study aims to analyze how Problem-Based Learning effects on the course of Technology and Material Testing for the students of D3 Program of Mechanical Engineering of the State University of Padang.

  20. Mechanical injuries, burns and combination damage caused by reactor accidents

    International Nuclear Information System (INIS)

    Koslowski, L.

    1981-01-01

    In cases of combination damage the initial treatment of wounds is the same as with injuries without accompanying radiation exposure. In the beginning the general principles of surgical treatment apply. In case of a mass accident, the examination of the injured to decide on the necessary kind of treatment has priority. A common problem to all the decisions is that the extent of a radiation exposure that may have been sustained cannot be established at once. Whether the radiation exposure has been so heavy as to require the modification of the surgical measures can be seen only from the blood count, the bone marrow biopsy, the reticulocyte count or from a chromosome analysis. (DG) [de

  1. Combined holographic-mechanical optical tweezers: Construction, optimization, and calibration

    Science.gov (United States)

    Hanes, Richard D. L.; Jenkins, Matthew C.; Egelhaaf, Stefan U.

    2009-08-01

    A spatial light modulator (SLM) and a pair of galvanometer-mounted mirrors (GMM) were combined into an optical tweezers setup. This provides great flexibility as the SLM creates an array of traps, which can be moved smoothly and quickly with the GMM. To optimize performance, the effect of the incidence angle on the SLM with respect to phase and intensity response was investigated. Although it is common to use the SLM at an incidence angle of 45°, smaller angles give a full 2π phase shift and an output intensity which is less dependent on the magnitude of the phase shift. The traps were calibrated using an active oscillatory technique and a passive probability distribution method.

  2. Combined holographic-mechanical optical tweezers: Construction, optimization, and calibration

    International Nuclear Information System (INIS)

    Hanes, Richard D. L.; Jenkins, Matthew C.; Egelhaaf, Stefan U.

    2009-01-01

    A spatial light modulator (SLM) and a pair of galvanometer-mounted mirrors (GMM) were combined into an optical tweezers setup. This provides great flexibility as the SLM creates an array of traps, which can be moved smoothly and quickly with the GMM. To optimize performance, the effect of the incidence angle on the SLM with respect to phase and intensity response was investigated. Although it is common to use the SLM at an incidence angle of 45 deg., smaller angles give a full 2π phase shift and an output intensity which is less dependent on the magnitude of the phase shift. The traps were calibrated using an active oscillatory technique and a passive probability distribution method.

  3. A new semi-supervised learning model combined with Cox and SP-AFT models in cancer survival analysis.

    Science.gov (United States)

    Chai, Hua; Li, Zi-Na; Meng, De-Yu; Xia, Liang-Yong; Liang, Yong

    2017-10-12

    Gene selection is an attractive and important task in cancer survival analysis. Most existing supervised learning methods can only use the labeled biological data, while the censored data (weakly labeled data) far more than the labeled data are ignored in model building. Trying to utilize such information in the censored data, a semi-supervised learning framework (Cox-AFT model) combined with Cox proportional hazard (Cox) and accelerated failure time (AFT) model was used in cancer research, which has better performance than the single Cox or AFT model. This method, however, is easily affected by noise. To alleviate this problem, in this paper we combine the Cox-AFT model with self-paced learning (SPL) method to more effectively employ the information in the censored data in a self-learning way. SPL is a kind of reliable and stable learning mechanism, which is recently proposed for simulating the human learning process to help the AFT model automatically identify and include samples of high confidence into training, minimizing interference from high noise. Utilizing the SPL method produces two direct advantages: (1) The utilization of censored data is further promoted; (2) the noise delivered to the model is greatly decreased. The experimental results demonstrate the effectiveness of the proposed model compared to the traditional Cox-AFT model.

  4. Treating electrostatics with Wolf summation in combined quantum mechanical and molecular mechanical simulations.

    Science.gov (United States)

    Ojeda-May, Pedro; Pu, Jingzhi

    2015-11-07

    The Wolf summation approach [D. Wolf et al., J. Chem. Phys. 110, 8254 (1999)], in the damped shifted force (DSF) formalism [C. J. Fennell and J. D. Gezelter, J. Chem. Phys. 124, 234104 (2006)], is extended for treating electrostatics in combined quantum mechanical and molecular mechanical (QM/MM) molecular dynamics simulations. In this development, we split the QM/MM electrostatic potential energy function into the conventional Coulomb r(-1) term and a term that contains the DSF contribution. The former is handled by the standard machinery of cutoff-based QM/MM simulations whereas the latter is incorporated into the QM/MM interaction Hamiltonian as a Fock matrix correction. We tested the resulting QM/MM-DSF method for two solution-phase reactions, i.e., the association of ammonium and chloride ions and a symmetric SN2 reaction in which a methyl group is exchanged between two chloride ions. The performance of the QM/MM-DSF method was assessed by comparing the potential of mean force (PMF) profiles with those from the QM/MM-Ewald and QM/MM-isotropic periodic sum (IPS) methods, both of which include long-range electrostatics explicitly. For ion association, the QM/MM-DSF method successfully eliminates the artificial free energy drift observed in the QM/MM-Cutoff simulations, in a remarkable agreement with the two long-range-containing methods. For the SN2 reaction, the free energy of activation obtained by the QM/MM-DSF method agrees well with both the QM/MM-Ewald and QM/MM-IPS results. The latter, however, requires a greater cutoff distance than QM/MM-DSF for a proper convergence of the PMF. Avoiding time-consuming lattice summation, the QM/MM-DSF method yields a 55% reduction in computational cost compared with the QM/MM-Ewald method. These results suggest that, in addition to QM/MM-IPS, the QM/MM-DSF method may serve as another efficient and accurate alternative to QM/MM-Ewald for treating electrostatics in condensed-phase simulations of chemical reactions.

  5. Nonassociative learning promotes respiratory entrainment to mechanical ventilation.

    Directory of Open Access Journals (Sweden)

    Shawna M MacDonald

    Full Text Available BACKGROUND: Patient-ventilator synchrony is a major concern in critical care and is influenced by phasic lung-volume feedback control of the respiratory rhythm. Routine clinical application of positive end-expiratory pressure (PEEP introduces a tonic input which, if unopposed, might disrupt respiratory-ventilator entrainment through sustained activation of the vagally-mediated Hering-Breuer reflex. We suggest that this potential adverse effect may be averted by two differentiator forms of nonassociative learning (habituation and desensitization of the Hering-Breuer reflex via pontomedullary pathways. METHODOLOGY/PRINCIPAL FINDINGS: We tested these hypotheses in 17 urethane-anesthetized adult Sprague-Dawley rats under controlled mechanical ventilation. Without PEEP, phrenic discharge was entrained 1:1 to the ventilator rhythm. Application of PEEP momentarily dampened the entrainment to higher ratios but this effect was gradually adapted by nonassociative learning. Bilateral electrolytic lesions of the pneumotaxic center weakened the adaptation to PEEP, whereas sustained stimulation of the pneumotaxic center weakened the entrainment independent of PEEP. In all cases, entrainment was abolished after vagotomy. CONCLUSIONS/SIGNIFICANCE: Our results demonstrate an important functional role for pneumotaxic desensitization and extra-pontine habituation of the Hering-Breuer reflex elicited by lung inflation: acting as buffers or high-pass filters against tonic vagal volume input, these differentiator forms of nonassociative learning help to restore respiratory-ventilator entrainment in the face of PEEP. Such central sites-specific habituation and desensitization of the Hering-Breuer reflex provide a useful experimental model of nonassociative learning in mammals that is of particular significance in understanding respiratory rhythmogenesis and coupled-oscillator entrainment mechanisms, and in the clinical management of mechanical ventilation in

  6. Multiple-instance learning as a classifier combining problem

    DEFF Research Database (Denmark)

    Li, Yan; Tax, David M. J.; Duin, Robert P. W.

    2013-01-01

    In multiple-instance learning (MIL), an object is represented as a bag consisting of a set of feature vectors called instances. In the training set, the labels of bags are given, while the uncertainty comes from the unknown labels of instances in the bags. In this paper, we study MIL with the ass...

  7. Combined quantum mechanical and molecular mechanical reaction pathway calculation for aromatic hydroxylation by p-hydroxybenzoate-3-hydroxylase

    NARCIS (Netherlands)

    Ridder, L.; Mulholland, A.; Rietjens, I.M.C.M.; Vervoort, J.

    1999-01-01

    The reaction pathway for the aromatic 3-hydroxylation of p-hydroxybenzoate by the reactive C4a-hydroperoxyflavin cofactor intermediate in p-hydroxybenzoate hydroxylase (PHBH) has been investigated by a combined quantum mechanical and molecular mechanical (QM/MM) method. A structural model for the

  8. Interpreting Students’ Perceptions in Fluid Mechanics Learning Outcomes

    Directory of Open Access Journals (Sweden)

    Filomena SOARES

    2015-11-01

    Full Text Available The objective of this study is to analyse the impact of introducing a practical work in the learning process of the Fluid Transport Systems course in Chemical Engineering degree. The students, in groups of two or three elements, were free to choose the application case in order to develop the practical work proposed by the responsible teachers. The students selected a centrifugal pump to supply water to houses or buildings and designed the piping system. The practical work was evaluated through the written report. The students’ perceptions were analysed through a questionnaire. The learning outcomes were also considered in order to understand how the fluid mechanics concepts were acquired. In the teachers’ point of view the teamwork should enable the development of students’ soft skills and competencies, promoting the ability to integrate and work in teams. The students changed their learning processing and perception becoming more reflective and less accommodative, forcing them to think critically and share opinions. Regarding the Fluid Mechanics assessment, the practical work increased, in average, the final grade at least one value.

  9. Teaching-Learning-Based Optimization with Learning Enthusiasm Mechanism and Its Application in Chemical Engineering

    Directory of Open Access Journals (Sweden)

    Xu Chen

    2018-01-01

    Full Text Available Teaching-learning-based optimization (TLBO is a population-based metaheuristic search algorithm inspired by the teaching and learning process in a classroom. It has been successfully applied to many scientific and engineering applications in the past few years. In the basic TLBO and most of its variants, all the learners have the same probability of getting knowledge from others. However, in the real world, learners are different, and each learner’s learning enthusiasm is not the same, resulting in different probabilities of acquiring knowledge. Motivated by this phenomenon, this study introduces a learning enthusiasm mechanism into the basic TLBO and proposes a learning enthusiasm based TLBO (LebTLBO. In the LebTLBO, learners with good grades have high learning enthusiasm, and they have large probabilities of acquiring knowledge from others; by contrast, learners with bad grades have low learning enthusiasm, and they have relative small probabilities of acquiring knowledge from others. In addition, a poor student tutoring phase is introduced to improve the quality of the poor learners. The proposed method is evaluated on the CEC2014 benchmark functions, and the computational results demonstrate that it offers promising results compared with other efficient TLBO and non-TLBO algorithms. Finally, LebTLBO is applied to solve three optimal control problems in chemical engineering, and the competitive results show its potential for real-world problems.

  10. Neural mechanisms of human perceptual learning: electrophysiological evidence for a two-stage process.

    Science.gov (United States)

    Hamamé, Carlos M; Cosmelli, Diego; Henriquez, Rodrigo; Aboitiz, Francisco

    2011-04-26

    Humans and other animals change the way they perceive the world due to experience. This process has been labeled as perceptual learning, and implies that adult nervous systems can adaptively modify the way in which they process sensory stimulation. However, the mechanisms by which the brain modifies this capacity have not been sufficiently analyzed. We studied the neural mechanisms of human perceptual learning by combining electroencephalographic (EEG) recordings of brain activity and the assessment of psychophysical performance during training in a visual search task. All participants improved their perceptual performance as reflected by an increase in sensitivity (d') and a decrease in reaction time. The EEG signal was acquired throughout the entire experiment revealing amplitude increments, specific and unspecific to the trained stimulus, in event-related potential (ERP) components N2pc and P3 respectively. P3 unspecific modification can be related to context or task-based learning, while N2pc may be reflecting a more specific attentional-related boosting of target detection. Moreover, bell and U-shaped profiles of oscillatory brain activity in gamma (30-60 Hz) and alpha (8-14 Hz) frequency bands may suggest the existence of two phases for learning acquisition, which can be understood as distinctive optimization mechanisms in stimulus processing. We conclude that there are reorganizations in several neural processes that contribute differently to perceptual learning in a visual search task. We propose an integrative model of neural activity reorganization, whereby perceptual learning takes place as a two-stage phenomenon including perceptual, attentional and contextual processes.

  11. Combining Formal, Non-Formal and Informal Learning for Workforce Skill Development

    Science.gov (United States)

    Misko, Josie

    2008-01-01

    This literature review, undertaken for Australian Industry Group, shows how multiple variations and combinations of formal, informal and non-formal learning, accompanied by various government incentives and organisational initiatives (including job redesign, cross-skilling, multi-skilling, diversified career pathways, action learning projects,…

  12. Different mechanisms in learning different second languages: Evidence from English speakers learning Chinese and Spanish.

    Science.gov (United States)

    Cao, Fan; Sussman, Bethany L; Rios, Valeria; Yan, Xin; Wang, Zhao; Spray, Gregory J; Mack, Ryan M

    2017-03-01

    phonology in Chinese. In summary, our study suggests different mechanisms in learning different L2s, providing important insights into neural plasticity and important implications in second language education. Copyright © 2017 Elsevier Inc. All rights reserved.

  13. Combining generative and discriminative representation learning for lung CT analysis with convolutional restricted Boltzmann machines

    DEFF Research Database (Denmark)

    van Tulder, Gijs; de Bruijne, Marleen

    2016-01-01

    The choice of features greatly influences the performance of a tissue classification system. Despite this, many systems are built with standard, predefined filter banks that are not optimized for that particular application. Representation learning methods such as restricted Boltzmann machines may...... outperform these standard filter banks because they learn a feature description directly from the training data. Like many other representation learning methods, restricted Boltzmann machines are unsupervised and are trained with a generative learning objective; this allows them to learn representations from...... unlabeled data, but does not necessarily produce features that are optimal for classification. In this paper we propose the convolutional classification restricted Boltzmann machine, which combines a generative and a discriminative learning objective. This allows it to learn filters that are good both...

  14. Internal force corrections with machine learning for quantum mechanics/molecular mechanics simulations.

    Science.gov (United States)

    Wu, Jingheng; Shen, Lin; Yang, Weitao

    2017-10-28

    Ab initio quantum mechanics/molecular mechanics (QM/MM) molecular dynamics simulation is a useful tool to calculate thermodynamic properties such as potential of mean force for chemical reactions but intensely time consuming. In this paper, we developed a new method using the internal force correction for low-level semiempirical QM/MM molecular dynamics samplings with a predefined reaction coordinate. As a correction term, the internal force was predicted with a machine learning scheme, which provides a sophisticated force field, and added to the atomic forces on the reaction coordinate related atoms at each integration step. We applied this method to two reactions in aqueous solution and reproduced potentials of mean force at the ab initio QM/MM level. The saving in computational cost is about 2 orders of magnitude. The present work reveals great potentials for machine learning in QM/MM simulations to study complex chemical processes.

  15. From inverse problems to learning: a Statistical Mechanics approach

    Science.gov (United States)

    Baldassi, Carlo; Gerace, Federica; Saglietti, Luca; Zecchina, Riccardo

    2018-01-01

    We present a brief introduction to the statistical mechanics approaches for the study of inverse problems in data science. We then provide concrete new results on inferring couplings from sampled configurations in systems characterized by an extensive number of stable attractors in the low temperature regime. We also show how these result are connected to the problem of learning with realistic weak signals in computational neuroscience. Our techniques and algorithms rely on advanced mean-field methods developed in the context of disordered systems.

  16. Shared mechanisms of perceptual learning and decision making.

    Science.gov (United States)

    Law, Chi-Tat; Gold, Joshua I

    2010-04-01

    Perceptual decisions require the brain to weigh noisy evidence from sensory neurons to form categorical judgments that guide behavior. Here we review behavioral and neurophysiological findings suggesting that at least some forms of perceptual learning do not appear to affect the response properties of neurons that represent the sensory evidence. Instead, improved perceptual performance results from changes in how the sensory evidence is selected and weighed to form the decision. We discuss the implications of this idea for possible sites and mechanisms of training-induced improvements in perceptual processing in the brain. Copyright © 2009 Cognitive Science Society, Inc.

  17. Dropout Prediction in E-Learning Courses through the Combination of Machine Learning Techniques

    Science.gov (United States)

    Lykourentzou, Ioanna; Giannoukos, Ioannis; Nikolopoulos, Vassilis; Mpardis, George; Loumos, Vassili

    2009-01-01

    In this paper, a dropout prediction method for e-learning courses, based on three popular machine learning techniques and detailed student data, is proposed. The machine learning techniques used are feed-forward neural networks, support vector machines and probabilistic ensemble simplified fuzzy ARTMAP. Since a single technique may fail to…

  18. Improving Learning Analytics--Combining Observational and Self-Report Data on Student Learning

    Science.gov (United States)

    Ellis, Robert A.; Han, Feifei; Pardo, Abelardo

    2017-01-01

    The field of education technology is embracing a use of learning analytics to improve student experiences of learning. Along with exponential growth in this area is an increasing concern of the interpretability of the analytics from the student experience and what they can tell us about learning. This study offers a way to address some of the…

  19. Combining Face-to-Face Learning with Online Learning in Virtual Worlds

    Science.gov (United States)

    Berns, Anke; Gonzalez-Pardo, Antonio; Camacho, David

    2012-01-01

    This paper focuses on the development of videogame-like applications in a 3D virtual environment as a complement to the face-to-face teaching and learning. With the changing role of teaching and learning and the increasing use of "blended learning," instructors are increasingly expected to explore new ways to attend to the needs of their…

  20. Development and validation of a reduced combined biodiesel–diesel reaction mechanism

    DEFF Research Database (Denmark)

    Ng, Hoon Kiat; Gan, Suyin; Ng, Jo-Han

    2013-01-01

    In this study, a compact combined biodiesel–diesel (CBD) reaction mechanism for diesel engine simulations is proposed through the combination of three component mechanisms using a chemical class-based approach. The proposed mechanism comprises the reaction mechanisms of methyl crotonate (MC...... to characterise the combustion of fossil diesel. Here, the MC and MB mechanisms are reduced before integrating with a compact n-heptane mechanism. CHEMKIN-PRO is used as the solver for the zero-dimensional, closed homogenous reactor with a constant volume in this study. In the first phase, the mechanisms of MC...... ranging from initial temperatures of 750–1350 K, pressures of 40–60 bar and equivalence ratios of 0.4–1.5. The mechanism is generally found to accurately predict the timing and duration of ID for the combustion of each surrogate fuel. This model is also shown to be feasible for use with multidimensional...

  1. Motor learning in childhood reveals distinct mechanisms for memory retention and re-learning.

    Science.gov (United States)

    Musselman, Kristin E; Roemmich, Ryan T; Garrett, Ben; Bastian, Amy J

    2016-05-01

    Adults can easily learn and access multiple versions of the same motor skill adapted for different conditions (e.g., walking in water, sand, snow). Following even a single session of adaptation, adults exhibit clear day-to-day retention and faster re-learning of the adapted pattern. Here, we studied the retention and re-learning of an adapted walking pattern in children aged 6-17 yr. We found that all children, regardless of age, showed adult-like patterns of retention of the adapted walking pattern. In contrast, children under 12 yr of age did not re-learn faster on the next day after washout had occurred-they behaved as if they had never adapted their walking before. Re-learning could be improved in younger children when the adaptation time on day 1 was increased to allow more practice at the plateau of the adapted pattern, but never to adult-like levels. These results show that the ability to store a separate, adapted version of the same general motor pattern does not fully develop until adolescence, and furthermore, that the mechanisms underlying the retention and rapid re-learning of adapted motor patterns are distinct. © 2016 Musselman et al.; Published by Cold Spring Harbor Laboratory Press.

  2. Combining multi agent paradigm and memetic computing for personalized and adaptive learning experiences

    NARCIS (Netherlands)

    Acampora, G.; Gaeta, M.; Loia, V.

    2011-01-01

    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

  3. Development of radiation oncology learning system combined with multi-institutional radiotherapy database (ROGAD)

    International Nuclear Information System (INIS)

    Takemura, Akihiro; Iinuma, Masahiro; Kou, Hiroko; Harauchi, Hajime; Inamura, Kiyonari

    1999-01-01

    We have constructed and are operating a multi-institutional radiotherapy database ROGAD (Radiation Oncology Greater Area Database) since 1992. One of it's purpose is 'to optimize individual radiotherapy plans'. We developed Radiation oncology learning system combined with ROGAD' which conforms to that purpose. Several medical doctors evaluated our system. According to those evaluations, we are now confident that our system is able to contribute to improvement of radiotherapy results. Our final target is to generate a good cyclic relationship among three components: radiotherapy results according to ''Radiation oncology learning system combined with ROGAD.'; The growth of ROGAD; and radiation oncology learning system. (author)

  4. Combining Education and Practice Learning in Environmental Management and Cleaner Technology

    DEFF Research Database (Denmark)

    Jørgensen, Ulrik; Jørgensen, Michael Søgaard

    2004-01-01

    to overcome these problems are discussed. The educational principles are presented as a combination of educational learning and practice learning named as reflexive learning. The experience from working with reflexive learning is discussed and relation to the role it can play in creating profes......This chapter argues for a new role for universities in adding the training of (existing) professionals to the core agenda in parallel to academic education and scientific research. Based on experiences from Denmark new challenges both to academic knowledge and training are presented and way...

  5. Image Denoising Algorithm Combined with SGK Dictionary Learning and Principal Component Analysis Noise Estimation

    Directory of Open Access Journals (Sweden)

    Wenjing Zhao

    2018-01-01

    Full Text Available SGK (sequential generalization of K-means dictionary learning denoising algorithm has the characteristics of fast denoising speed and excellent denoising performance. However, the noise standard deviation must be known in advance when using SGK algorithm to process the image. This paper presents a denoising algorithm combined with SGK dictionary learning and the principal component analysis (PCA noise estimation. At first, the noise standard deviation of the image is estimated by using the PCA noise estimation algorithm. And then it is used for SGK dictionary learning algorithm. Experimental results show the following: (1 The SGK algorithm has the best denoising performance compared with the other three dictionary learning algorithms. (2 The SGK algorithm combined with PCA is superior to the SGK algorithm combined with other noise estimation algorithms. (3 Compared with the original SGK algorithm, the proposed algorithm has higher PSNR and better denoising performance.

  6. From Tootsie Rolls to Composites: Assessing a Spectrum of Active Learning Activities in Engineering Mechanics

    Science.gov (United States)

    2009-05-01

    The introduction of active learning exercises into a traditional lecture has been shown to improve students’ learning. Hands-on learning...opportunities in labs and projects provide are additional tools in the active learning toolbox. This paper presents a series of innovative hands-on active ... learning activities for mechanics of materials topics. These activities are based on a Methodology for Developing Hands-on Active Learning Activities, a

  7. Physicochemical Mechanisms of Synergistic Biological Action of Combinations of Aromatic Heterocyclic Compounds

    OpenAIRE

    Evstigneev, Maxim P.

    2013-01-01

    The mechanisms of synergistic biological effects observed in the simultaneous use of aromatic heterocyclic compounds in combination are reviewed, and the specific biological role of heteroassociation of aromatic molecules is discussed.

  8. Associative Mechanisms Allow for Social Learning and Cultural Transmission of String Pulling in an Insect

    Science.gov (United States)

    Zhu, Xingfu; Ingraham, Thomas; Søvik, Eirik

    2016-01-01

    Social insects make elaborate use of simple mechanisms to achieve seemingly complex behavior and may thus provide a unique resource to discover the basic cognitive elements required for culture, i.e., group-specific behaviors that spread from “innovators” to others in the group via social learning. We first explored whether bumblebees can learn a nonnatural object manipulation task by using string pulling to access a reward that was presented out of reach. Only a small minority “innovated” and solved the task spontaneously, but most bees were able to learn to pull a string when trained in a stepwise manner. In addition, naïve bees learnt the task by observing a trained demonstrator from a distance. Learning the behavior relied on a combination of simple associative mechanisms and trial-and-error learning and did not require “insight”: naïve bees failed a “coiled-string experiment,” in which they did not receive instant visual feedback of the target moving closer when tugging on the string. In cultural diffusion experiments, the skill spread rapidly from a single knowledgeable individual to the majority of a colony’s foragers. We observed that there were several sequential sets (“generations”) of learners, so that previously naïve observers could first acquire the technique by interacting with skilled individuals and, subsequently, themselves become demonstrators for the next “generation” of learners, so that the longevity of the skill in the population could outlast the lives of informed foragers. This suggests that, so long as animals have a basic toolkit of associative and motor learning processes, the key ingredients for the cultural spread of unusual skills are already in place and do not require sophisticated cognition. PMID:27701411

  9. A hypothesis on a role of oxytocin in the social mechanisms of speech and vocal learning.

    Science.gov (United States)

    Theofanopoulou, Constantina; Boeckx, Cedric; Jarvis, Erich D

    2017-08-30

    Language acquisition in humans and song learning in songbirds naturally happen as a social learning experience, providing an excellent opportunity to reveal social motivation and reward mechanisms that boost sensorimotor learning. Our knowledge about the molecules and circuits that control these social mechanisms for vocal learning and language is limited. Here we propose a hypothesis of a role for oxytocin (OT) in the social motivation and evolution of vocal learning and language. Building upon existing evidence, we suggest specific neural pathways and mechanisms through which OT might modulate vocal learning circuits in specific developmental stages. © 2017 The Authors.

  10. Learner Characteristic Based Learning Effort Curve Mode: The Core Mechanism on Developing Personalized Adaptive E-Learning Platform

    Science.gov (United States)

    Hsu, Pi-Shan

    2012-01-01

    This study aims to develop the core mechanism for realizing the development of personalized adaptive e-learning platform, which is based on the previous learning effort curve research and takes into account the learner characteristics of learning style and self-efficacy. 125 university students from Taiwan are classified into 16 groups according…

  11. PHYSIOLOGICAL QUALITY OF SOYBEAN SEEDS UNDER MECHANICAL INJURIES CAUSED BY COMBINES

    OpenAIRE

    FÁBIO PALCZEWSKI PACHECO; LÚCIA HELENA PEREIRA NÓBREGA; GISLAINE PICOLLO DE LIMA; MÁRCIA SANTORUM; WALTER BOLLER; LORIVAN FORMIGHIERI

    2015-01-01

    The mechanical harvesting causes injuries on seeds and may affect their quality. Different threshing mechanisms and their adjustments may also affect the intensity of impacts that machines cause on seeds. So, this study aimed at diagnosing and evaluating the effect of two combines: the first one with a threshing system of axial flow and the other one with a threshing system of tangential flow, under adjustments of concave opening (10 mm, 30 mm and 10 mm for a combine with axial ...

  12. Reconciling genetic evolution and the associative learning account of mirror neurons through data-acquisition mechanisms.

    Science.gov (United States)

    Lotem, Arnon; Kolodny, Oren

    2014-04-01

    An associative learning account of mirror neurons should not preclude genetic evolution of its underlying mechanisms. On the contrary, an associative learning framework for cognitive development should seek heritable variation in the learning rules and in the data-acquisition mechanisms that construct associative networks, demonstrating how small genetic modifications of associative elements can give rise to the evolution of complex cognition.

  13. Providing pervasive Learning eXperiences by Combining Internet of Things and e-Learning standards

    Directory of Open Access Journals (Sweden)

    Aroua TAAMALLAH

    2015-12-01

    Full Text Available Nowadays, learning is more and more taking place anywhere and anytime. This implies that e-learning environments are expanded from only virtual learning environments to both virtual and physical ones. Thanks to the evolution of Internet, ICT (Information and Communication Technology and Internet of Things, new learning scenarios could be experienced by learners either individually or collaboratively. These learning scenarios are Pervasive in such a way that they allow to mix virtual and physical learning environments as well. They are therefore characterized by possible interactions of the learner with the physical environment, the Learner's contextual data detection as well as the adaptation of pedagogical strategies and services according to this context. This paper aims to take advantage of this trend and keep up also with existing e-Learning standards such as IMS LD and LOM. The solution proposed is therefore to extend these standards models with that of Internet of Things and to provide an adaptation approach of learning activities based on learner's context and her/his track using the eXperience API. In this context and in order to allow both reasoning capabilities and interoperability between the proposed models Ontological representations and implementation are therefore proposed. Moreover a technical architecture highlighting the required software components and their interactions is provided. And finally, a relevant pervasive learning scenario is implemented and experimented.

  14. Honeybees in a virtual reality environment learn unique combinations of colour and shape.

    Science.gov (United States)

    Rusch, Claire; Roth, Eatai; Vinauger, Clément; Riffell, Jeffrey A

    2017-10-01

    Honeybees are well-known models for the study of visual learning and memory. Whereas most of our knowledge of learned responses comes from experiments using free-flying bees, a tethered preparation would allow fine-scale control of the visual stimuli as well as accurate characterization of the learned responses. Unfortunately, conditioning procedures using visual stimuli in tethered bees have been limited in their efficacy. In this study, using a novel virtual reality environment and a differential training protocol in tethered walking bees, we show that the majority of honeybees learn visual stimuli, and need only six paired training trials to learn the stimulus. We found that bees readily learn visual stimuli that differ in both shape and colour. However, bees learn certain components over others (colour versus shape), and visual stimuli are learned in a non-additive manner with the interaction of specific colour and shape combinations being crucial for learned responses. To better understand which components of the visual stimuli the bees learned, the shape-colour association of the stimuli was reversed either during or after training. Results showed that maintaining the visual stimuli in training and testing phases was necessary to elicit visual learning, suggesting that bees learn multiple components of the visual stimuli. Together, our results demonstrate a protocol for visual learning in restrained bees that provides a powerful tool for understanding how components of a visual stimulus elicit learned responses as well as elucidating how visual information is processed in the honeybee brain. © 2017. Published by The Company of Biologists Ltd.

  15. Combining Project-Based Learning and Community-Based Research in a Research Methodology Course: The Lessons Learned

    Science.gov (United States)

    Arantes do Amaral, João Alberto; Lino dos Santos, Rebeca Júlia Rodrigues

    2018-01-01

    In this article, we present our findings regarding the course "Research Methodology," offered to 22 first-year undergraduate students studying Administration at the Federal University of São Paulo, Osasco, Brazil. The course, which combined community-based research and project-based learning, was developed during the second semester of…

  16. Fabrication of microfibrillated cellulose gel from waste pulp sludge via mild maceration combined with mechanical shearing

    Science.gov (United States)

    Nusheng Chen; Junyong Zhu; Zhaohui Tong

    2016-01-01

    This article describes a facile route, which combines mild maceration of waste pulp sludge and a mechanical shearing process, to prepare microfibrillated cellulose (MFC) with a high storage modulus. In the maceration, the mixture of glacial acetic acid and hydrogen peroxide was used to extract cellulose from never-dried waste pulp sludge. Then, two different mechanical...

  17. 40 CFR 280.94 - Allowable mechanisms and combinations of mechanisms.

    Science.gov (United States)

    2010-07-01

    ... requirements of the financial test under this rule, the financial statements of the owner or operator are not consolidated with the financial statements of the guarantor. [53 FR 43370, Oct. 26, 1988, as amended at 58 FR... OPERATORS OF UNDERGROUND STORAGE TANKS (UST) Financial Responsibility § 280.94 Allowable mechanisms and...

  18. Learning to learn - intrinsic plasticity as a metaplasticity mechanism for memory formation.

    Science.gov (United States)

    Sehgal, Megha; Song, Chenghui; Ehlers, Vanessa L; Moyer, James R

    2013-10-01

    "Use it or lose it" is a popular adage often associated with use-dependent enhancement of cognitive abilities. Much research has focused on understanding exactly how the brain changes as a function of experience. Such experience-dependent plasticity involves both structural and functional alterations that contribute to adaptive behaviors, such as learning and memory, as well as maladaptive behaviors, including anxiety disorders, phobias, and posttraumatic stress disorder. With the advancing age of our population, understanding how use-dependent plasticity changes across the lifespan may also help to promote healthy brain aging. A common misconception is that such experience-dependent plasticity (e.g., associative learning) is synonymous with synaptic plasticity. Other forms of plasticity also play a critical role in shaping adaptive changes within the nervous system, including intrinsic plasticity - a change in the intrinsic excitability of a neuron. Intrinsic plasticity can result from a change in the number, distribution or activity of various ion channels located throughout the neuron. Here, we review evidence that intrinsic plasticity is an important and evolutionarily conserved neural correlate of learning. Intrinsic plasticity acts as a metaplasticity mechanism by lowering the threshold for synaptic changes. Thus, learning-related intrinsic changes can facilitate future synaptic plasticity and learning. Such intrinsic changes can impact the allocation of a memory trace within a brain structure, and when compromised, can contribute to cognitive decline during the aging process. This unique role of intrinsic excitability can provide insight into how memories are formed and, more interestingly, how neurons that participate in a memory trace are selected. Most importantly, modulation of intrinsic excitability can allow for regulation of learning ability - this can prevent or provide treatment for cognitive decline not only in patients with clinical disorders but

  19. Learning to learn – intrinsic plasticity as a metaplasticity mechanism for memory formation

    Science.gov (United States)

    Sehgal, Megha; Song, Chenghui; Ehlers, Vanessa L.; Moyer, James R.

    2013-01-01

    “Use it or lose it” is a popular adage often associated with use-dependent enhancement of cognitive abilities. Much research has focused on understanding exactly how the brain changes as a function of experience. Such experience-dependent plasticity involves both structural and functional alterations that contribute to adaptive behaviors, such as learning and memory, as well as maladaptive behaviors, including anxiety disorders, phobias, and posttraumatic stress disorder. With the advancing age of our population, understanding how use-dependent plasticity changes across the lifespan may also help to promote healthy brain aging. A common misconception is that such experience-dependent plasticity (e.g., associative learning) is synonymous with synaptic plasticity. Other forms of plasticity also play a critical role in shaping adaptive changes within the nervous system, including intrinsic plasticity – a change in the intrinsic excitability of a neuron. Intrinsic plasticity can result from a change in the number, distribution or activity of various ion channels located throughout the neuron. Here, we review evidence that intrinsic plasticity is an important and evolutionarily conserved neural correlate of learning. Intrinsic plasticity acts as a metaplasticity mechanism by lowering the threshold for synaptic changes. Thus, learning-related intrinsic changes can facilitate future synaptic plasticity and learning. Such intrinsic changes can impact the allocation of a memory trace within a brain structure, and when compromised, can contribute to cognitive decline during the aging process. This unique role of intrinsic excitability can provide insight into how memories are formed and, more interestingly, how neurons that participate in a memory trace are selected. Most importantly, modulation of intrinsic excitability can allow for regulation of learning ability – this can prevent or provide treatment for cognitive decline not only in patients with clinical

  20. Stochastic upscaling in solid mechanics: An excercise in machine learning

    International Nuclear Information System (INIS)

    Koutsourelakis, P.S.

    2007-01-01

    This paper presents a consistent theoretical and computational framework for upscaling in random microstructures. We adopt an information theoretic approach in order to quantify the informational content of the microstructural details and find ways to condense it while assessing quantitatively the approximation introduced. In particular, we substitute the high-dimensional microscale description by a lower-dimensional representation corresponding for example to an equivalent homogeneous medium. The probabilistic characteristics of the latter are determined by minimizing the distortion between actual macroscale predictions and the predictions made using the coarse model. A machine learning framework is essentially adopted in which a vector quantizer is trained using data generated computationally or collected experimentally. Several parallels and differences with similar problems in source coding theory are pointed out and an efficient computational tool is employed. Various applications in linear and non-linear problems in solid mechanics are examined

  1. Perceptual learning shapes multisensory causal inference via two distinct mechanisms.

    Science.gov (United States)

    McGovern, David P; Roudaia, Eugenie; Newell, Fiona N; Roach, Neil W

    2016-04-19

    To accurately represent the environment, our brains must integrate sensory signals from a common source while segregating those from independent sources. A reasonable strategy for performing this task is to restrict integration to cues that coincide in space and time. However, because multisensory signals are subject to differential transmission and processing delays, the brain must retain a degree of tolerance for temporal discrepancies. Recent research suggests that the width of this 'temporal binding window' can be reduced through perceptual learning, however, little is known about the mechanisms underlying these experience-dependent effects. Here, in separate experiments, we measure the temporal and spatial binding windows of human participants before and after training on an audiovisual temporal discrimination task. We show that training leads to two distinct effects on multisensory integration in the form of (i) a specific narrowing of the temporal binding window that does not transfer to spatial binding and (ii) a general reduction in the magnitude of crossmodal interactions across all spatiotemporal disparities. These effects arise naturally from a Bayesian model of causal inference in which learning improves the precision of audiovisual timing estimation, whilst concomitantly decreasing the prior expectation that stimuli emanate from a common source.

  2. Combining MLC and SVM Classifiers for Learning Based Decision Making: Analysis and Evaluations.

    Science.gov (United States)

    Zhang, Yi; Ren, Jinchang; Jiang, Jianmin

    2015-01-01

    Maximum likelihood classifier (MLC) and support vector machines (SVM) are two commonly used approaches in machine learning. MLC is based on Bayesian theory in estimating parameters of a probabilistic model, whilst SVM is an optimization based nonparametric method in this context. Recently, it is found that SVM in some cases is equivalent to MLC in probabilistically modeling the learning process. In this paper, MLC and SVM are combined in learning and classification, which helps to yield probabilistic output for SVM and facilitate soft decision making. In total four groups of data are used for evaluations, covering sonar, vehicle, breast cancer, and DNA sequences. The data samples are characterized in terms of Gaussian/non-Gaussian distributed and balanced/unbalanced samples which are then further used for performance assessment in comparing the SVM and the combined SVM-MLC classifier. Interesting results are reported to indicate how the combined classifier may work under various conditions.

  3. Combining MLC and SVM Classifiers for Learning Based Decision Making: Analysis and Evaluations

    Directory of Open Access Journals (Sweden)

    Yi Zhang

    2015-01-01

    Full Text Available Maximum likelihood classifier (MLC and support vector machines (SVM are two commonly used approaches in machine learning. MLC is based on Bayesian theory in estimating parameters of a probabilistic model, whilst SVM is an optimization based nonparametric method in this context. Recently, it is found that SVM in some cases is equivalent to MLC in probabilistically modeling the learning process. In this paper, MLC and SVM are combined in learning and classification, which helps to yield probabilistic output for SVM and facilitate soft decision making. In total four groups of data are used for evaluations, covering sonar, vehicle, breast cancer, and DNA sequences. The data samples are characterized in terms of Gaussian/non-Gaussian distributed and balanced/unbalanced samples which are then further used for performance assessment in comparing the SVM and the combined SVM-MLC classifier. Interesting results are reported to indicate how the combined classifier may work under various conditions.

  4. Potentials of Industrie 4.0 and Machine Learning for Mechanical Joining

    OpenAIRE

    Jäckel, Mathias

    2017-01-01

    -Sensitivity analysis of the influence of component properties and joining parameters on the joining result for self-pierce riveting -Possibilities to link mechanical joining technologies with the automotive process chain for quality and flexibility improvements -Potential of using machine learning to reduce automotive product development cycles in relation to mechanical joining -Datamining for machine learning at mechanical joining

  5. Virtual Learning Environment for Interactive Engagement with Advanced Quantum Mechanics

    Science.gov (United States)

    Pedersen, Mads Kock; Skyum, Birk; Heck, Robert; Müller, Romain; Bason, Mark; Lieberoth, Andreas; Sherson, Jacob F.

    2016-01-01

    A virtual learning environment can engage university students in the learning process in ways that the traditional lectures and lab formats cannot. We present our virtual learning environment "StudentResearcher," which incorporates simulations, multiple-choice quizzes, video lectures, and gamification into a learning path for quantum…

  6. A method of meta-mechanism combination and replacement based on motion study

    Directory of Open Access Journals (Sweden)

    Yadong Fang

    2015-01-01

    Full Text Available Lacking the effective methods to reduce labor and cost, many small- and medium-sized assembly companies are facing with the problem of high cost for a long time. In order to reduce costs of manual operations, the method of meta-mechanism combination and replacement is studied. In this paper, we mainly discuss assembling motion analysis, workpieces position information acquisition, motion library construction, assembling motion analysis by Maynard’s operation sequence technique, meta-mechanism database establishment, and match of motion and mechanism. At the same time, the principle, process, and system realization framework of mechanism replacement are introduced. Lastly, problems for low-cost automation of the production line are basically resolved by operator motion analysis and meta-mechanism combination and match.

  7. An approach for investigation of secure access processes at a combined e-learning environment

    Science.gov (United States)

    Romansky, Radi; Noninska, Irina

    2017-12-01

    The article discuses an approach to investigate processes for regulation the security and privacy control at a heterogenous e-learning environment realized as a combination of traditional and cloud means and tools. Authors' proposal for combined architecture of e-learning system is presented and main subsystems and procedures are discussed. A formalization of the processes for using different types resources (public, private internal and private external) is proposed. The apparatus of Markovian chains (MC) is used for modeling and analytical investigation of the secure access to the resources is used and some assessments are presented.

  8. micro-mechanical experimental investigation and modelling of strain and damage of argillaceous rocks under combined hydric and mechanical loads

    International Nuclear Information System (INIS)

    Wang, L.

    2012-01-01

    The hydro-mechanical behavior of argillaceous rocks, which are possible host rocks for underground radioactive nuclear waste storage, is investigated by means of micro-mechanical experimental investigations and modellings. Strain fields at the micrometric scale of the composite structure of this rock, are measured by the combination of environmental scanning electron microscopy, in situ testing and digital image correlation technique. The evolution of argillaceous rocks under pure hydric loading is first investigated. The strain field is strongly heterogeneous and manifests anisotropy. The observed nonlinear deformation at high relative humidity (RH) is related not only to damage, but also to the nonlinear swelling of the clay mineral itself, controlled by different local mechanisms depending on RH. Irreversible deformations are observed during hydric cycles, as well as a network of microcracks located in the bulk of the clay matrix and/or at the inclusion-matrix interface. Second, the local deformation field of the material under combined hydric and mechanical loadings is quantified. Three types of deformation bands are evidenced under mechanical loading, either normal to stress direction (compaction), parallel (microcracking) or inclined (shear). Moreover, they are strongly controlled by the water content of the material: shear bands are in particular prone to appear at high RH states. In view of understanding the mechanical interactions a local scale, the material is modeled as a composite made of non-swelling elastic inclusions embedded in an elastic swelling clay matrix. The internal stress field induced by swelling strain incompatibilities between inclusions and matrix, as well as the overall deformation, is numerically computed at equilibrium but also during the transient stage associated with a moisture gradient. An analytical micro-mechanical model based on Eshelby's solution is proposed. In addition, 2D finite element computations are performed. Results

  9. Examining the benefits of combining two learning strategies on recall of functional information in persons with multiple sclerosis.

    Science.gov (United States)

    Goverover, Yael; Basso, Michael; Wood, Hali; Chiaravalloti, Nancy; DeLuca, John

    2011-12-01

    Forgetfulness occurs commonly in people with multiple sclerosis (MS), but few treatments alleviate this problem. This study examined the combined effect of two cognitive rehabilitation strategies to improve learning and memory in MS: self-generation and spaced learning. The hypothesis was that the combination of spaced learning and self-generation would yield better learning and memory recall performance than spaced learning alone. Using a within groups design, 20 participants with MS and 18 healthy controls (HC) were presented with three tasks (learning names, appointment, and object location), each in three learning conditions (Massed, Spaced Learning, and combination of spaced and generated information). Participants were required to recall the information they learned in each of these conditions immediately and 30 min following the initial presentation. The combination of spaced learning and self-generation yielded better recall than did spaced learning alone. In turn, spaced learning resulted in better recall than the massed rehearsal condition. These findings reveal that the combination of these two learning strategies may possess utility as a cognitive rehabilitation strategy.

  10. Personal computer versus personal computer/mobile device combination users' preclinical laboratory e-learning activity.

    Science.gov (United States)

    Kon, Haruka; Kobayashi, Hiroshi; Sakurai, Naoki; Watanabe, Kiyoshi; Yamaga, Yoshiro; Ono, Takahiro

    2017-11-01

    The aim of the present study was to clarify differences between personal computer (PC)/mobile device combination and PC-only user patterns. We analyzed access frequency and time spent on a complete denture preclinical website in order to maximize website effectiveness. Fourth-year undergraduate students (N=41) in the preclinical complete denture laboratory course were invited to participate in this survey during the final week of the course to track login data. Students accessed video demonstrations and quizzes via our e-learning site/course program, and were instructed to view online demonstrations before classes. When the course concluded, participating students filled out a questionnaire about the program, their opinions, and devices they had used to access the site. Combination user access was significantly more frequent than PC-only during supplementary learning time, indicating that students with mobile devices studied during lunch breaks and before morning classes. Most students had favorable opinions of the e-learning site, but a few combination users commented that some videos were too long and that descriptive answers were difficult on smartphones. These results imply that mobile devices' increased accessibility encouraged learning by enabling more efficient time use between classes. They also suggest that e-learning system improvements should cater to mobile device users by reducing video length and including more short-answer questions. © 2016 John Wiley & Sons Australia, Ltd.

  11. Collaborative Learning in Architectural Education: Benefits of Combining Conventional Studio, Virtual Design Studio and Live Projects

    Science.gov (United States)

    Rodriguez, Carolina; Hudson, Roland; Niblock, Chantelle

    2018-01-01

    Combinations of Conventional Studio and Virtual Design Studio (VDS) have created valuable learning environments that take advantage of different instruments of communication and interaction. However, past experiences have reported limitations in regards to student engagement and motivation, especially when the studio projects encourage abstraction…

  12. Capstone Teaching Models: Combining Simulation, Analytical Intuitive Learning Processes, History and Effectiveness

    Science.gov (United States)

    Reid, Maurice; Brown, Steve; Tabibzadeh, Kambiz

    2012-01-01

    For the past decade teaching models have been changing, reflecting the dynamics, complexities, and uncertainties of today's organizations. The traditional and the more current active models of learning have disadvantages. Simulation provides a platform to combine the best aspects of both types of teaching practices. This research explores the…

  13. Combining Self-Explaining with Computer Architecture Diagrams to Enhance the Learning of Assembly Language Programming

    Science.gov (United States)

    Hung, Y.-C.

    2012-01-01

    This paper investigates the impact of combining self explaining (SE) with computer architecture diagrams to help novice students learn assembly language programming. Pre- and post-test scores for the experimental and control groups were compared and subjected to covariance (ANCOVA) statistical analysis. Results indicate that the SE-plus-diagram…

  14. Elemental representation and configural mappings: combining elemental and configural theories of associative learning.

    Science.gov (United States)

    McLaren, I P L; Forrest, C L; McLaren, R P

    2012-09-01

    In this article, we present our first attempt at combining an elemental theory designed to model representation development in an associative system (based on McLaren, Kaye, & Mackintosh, 1989) with a configural theory that models associative learning and memory (McLaren, 1993). After considering the possible advantages of such a combination (and some possible pitfalls), we offer a hybrid model that allows both components to produce the phenomena that they are capable of without introducing unwanted interactions. We then successfully apply the model to a range of phenomena, including latent inhibition, perceptual learning, the Espinet effect, and first- and second-order retrospective revaluation. In some cases, we present new data for comparison with our model's predictions. In all cases, the model replicates the pattern observed in our experimental results. We conclude that this line of development is a promising one for arriving at general theories of associative learning and memory.

  15. Development of radiation oncology learning system combined with multi-institutional radiotherapy database (ROGAD)

    Energy Technology Data Exchange (ETDEWEB)

    Takemura, Akihiro; Iinuma, Masahiro; Kou, Hiroko [Kanazawa Univ. (Japan). School of Medicine; Harauchi, Hajime; Inamura, Kiyonari

    1999-09-01

    We have constructed and are operating a multi-institutional radiotherapy database ROGAD (Radiation Oncology Greater Area Database) since 1992. One of it's purpose is 'to optimize individual radiotherapy plans'. We developed Radiation oncology learning system combined with ROGAD' which conforms to that purpose. Several medical doctors evaluated our system. According to those evaluations, we are now confident that our system is able to contribute to improvement of radiotherapy results. Our final target is to generate a good cyclic relationship among three components: radiotherapy results according to ''Radiation oncology learning system combined with ROGAD.'; The growth of ROGAD; and radiation oncology learning system. (author)

  16. The Effect of Contextual Teaching and Learning Combined with Peer Tutoring towards Learning Achievement on Human Digestive System Concept

    Directory of Open Access Journals (Sweden)

    Farhah Abadiyah

    2017-11-01

    Full Text Available This research aims to know the influence of contextual teaching and learning (CTL combined with peer tutoring toward learning achievement on human digestive system concept. This research was conducted at one of State Senior High School in South Tangerang in the academic year of 2016/2017. The research method was quasi experiment with nonequivalent pretest-postest control group design. The sample was taken by simple random sampling. The total of the sampels were 86 students which consisted of 44 students as a controlled group and 42 students as an experimental group. The research instrument was objective test which consisted of 25 multiple choice items of each pretest and posttest. The research also used observation sheets for teacher and students activity. The result of data analysis using t-test on the two groups show that the value of tcount was 2.40 and ttable was 1.99 on significant level α = 0,05, so that tcount > ttable.. This result indicated that there was influence of contextual teaching and learning (CTL combined with peer tutoring toward learning achievement on human digestive system concept.

  17. On Combining Multiple-Instance Learning and Active Learning for Computer-Aided Detection of Tuberculosis

    NARCIS (Netherlands)

    Melendez Rodriguez, J.C.; Ginneken, B. van; Maduskar, P.; Philipsen, R.H.H.M.; Ayles, H.; Sanchez, C.I.

    2016-01-01

    The major advantage of multiple-instance learning (MIL) applied to a computer-aided detection (CAD) system is that it allows optimizing the latter with case-level labels instead of accurate lesion outlines as traditionally required for a supervised approach. As shown in previous work, a MIL-based

  18. Learning Crisis Unit through Post-Crisis: Characteristics and Mechanisms

    Science.gov (United States)

    Chebbi, Hela; Pündrich, Aline Pereira

    2015-01-01

    Purpose: This paper aims to identify the characteristics that a crisis unit should have to achieve effective learning after crisis. Literature has identified many relations between learning organizations and crisis; yet, there is a dearth of research on specific studies about crisis units and their post-crisis learning features. Thus, this paper…

  19. Using Formal Game Design Methods to Embed Learning Outcomes into Game Mechanics and Avoid Emergent Behaviour

    Science.gov (United States)

    Grey, Simon; Grey, David; Gordon, Neil; Purdy, Jon

    2017-01-01

    This paper offers an approach to designing game-based learning experiences inspired by the Mechanics-Dynamics-Aesthetics (MDA) model (Hunicke et al., 2004) and the elemental tetrad model (Schell, 2008) for game design. A case for game based learning as an active and social learning experience is presented including arguments from both teachers and…

  20. 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.

  1. Effects of the Badge Mechanism on Self-Efficacy and Learning Performance in a Game-Based English Learning Environment

    Science.gov (United States)

    Yang, Jie Chi; Quadir, Benazir; Chen, Nian-Shing

    2016-01-01

    A growing number of studies have been conducted on digital game-based learning (DGBL). However, there has been a lack of attention paid to individuals' self-efficacy and learning performance in the implementation of DGBL. This study therefore investigated how the badge mechanism in DGBL enhanced users' self-efficacy in the subject domain of…

  2. Assessing learning outcomes in middle-division classical mechanics: The Colorado Classical Mechanics and Math Methods Instrument

    Science.gov (United States)

    Caballero, Marcos D.; Doughty, Leanne; Turnbull, Anna M.; Pepper, Rachel E.; Pollock, Steven J.

    2017-06-01

    Reliable and validated assessments of introductory physics have been instrumental in driving curricular and pedagogical reforms that lead to improved student learning. As part of an effort to systematically improve our sophomore-level classical mechanics and math methods course (CM 1) at CU Boulder, we have developed a tool to assess student learning of CM 1 concepts in the upper division. The Colorado Classical Mechanics and Math Methods Instrument (CCMI) builds on faculty consensus learning goals and systematic observations of student difficulties. The result is a 9-question open-ended post test that probes student learning in the first half of a two-semester classical mechanics and math methods sequence. In this paper, we describe the design and development of this instrument, its validation, and measurements made in classes at CU Boulder and elsewhere.

  3. Assessing learning outcomes in middle-division classical mechanics: The Colorado Classical Mechanics and Math Methods Instrument

    Directory of Open Access Journals (Sweden)

    Marcos D. Caballero

    2017-04-01

    Full Text Available Reliable and validated assessments of introductory physics have been instrumental in driving curricular and pedagogical reforms that lead to improved student learning. As part of an effort to systematically improve our sophomore-level classical mechanics and math methods course (CM 1 at CU Boulder, we have developed a tool to assess student learning of CM 1 concepts in the upper division. The Colorado Classical Mechanics and Math Methods Instrument (CCMI builds on faculty consensus learning goals and systematic observations of student difficulties. The result is a 9-question open-ended post test that probes student learning in the first half of a two-semester classical mechanics and math methods sequence. In this paper, we describe the design and development of this instrument, its validation, and measurements made in classes at CU Boulder and elsewhere.

  4. Lifetimes of organic photovoltaics: Combining chemical and physical characterisation techniques to study degradation mechanisms

    DEFF Research Database (Denmark)

    Norrman, K.; Larsen, N.B.; Krebs, Frederik C

    2006-01-01

    Degradation mechanisms of a photovoltaic device with an Al/C-60/C-12-PSV/PEDOT:PSS/ITO/glass geometry was studied using a combination of in-plane physical and chemical analysis techniques: TOF-SIMS, AFM, SEM, interference microscopy and fluorescence microscopy. A comparison was made between...

  5. A Hybrid Approach to Composite Damage and Failure Analysis Combining Synergistic Damage Mechanics and Peridynamics

    Science.gov (United States)

    2017-09-30

    other provision of law, no person shall be subject to any penalty for fai ling to comply with a collection of information if it does not display a...to Composite Damage and Fai lure Analysis Combining Synergistic Damage Mechanics and Peridynamics Sb. GRANT NUMBER NOOO 14-16-1-2173 Sc. PROGRAM

  6. Combination of low energy and mechanical cooling technologies for buildings in Central Europe

    NARCIS (Netherlands)

    Lain, M.; Hensen, J.L.M.

    2004-01-01

    This paper discusses options for incorporating low energy cooling technologies combined with standard mechanical cooling in buildings in central Europe. Case studies, design recommendations and role of computer simulation of building and system in the design process are presented. Applicability of

  7. Combining Digital Archives Content with Serious Game Approach to Create a Gamified Learning Experience

    Directory of Open Access Journals (Sweden)

    D.-T. Shih

    2015-08-01

    Full Text Available This paper presents an interdisciplinary to develop content-aware application that combines game with learning on specific categories of digital archives. The employment of content-oriented game enhances the gamification and efficacy of learning in culture education on architectures and history of Hsinchu County, Taiwan. The gamified form of the application is used as a backbone to support and provide a strong stimulation to engage users in learning art and culture, therefore this research is implementing under the goal of “The Digital ARt/ARchitecture Project”. The purpose of the abovementioned project is to develop interactive serious game approaches and applications for Hsinchu County historical archives and architectures. Therefore, we present two applications, “3D AR for Hukou Old ” and “Hsinchu County History Museum AR Tour” which are in form of augmented reality (AR. By using AR imaging techniques to blend real object and virtual content, the users can immerse in virtual exhibitions of Hukou Old Street and Hsinchu County History Museum, and to learn in ubiquitous computing environment. This paper proposes a content system that includes tools and materials used to create representations of digitized cultural archives including historical artifacts, documents, customs, religion, and architectures. The Digital ARt / ARchitecture Project is based on the concept of serious game and consists of three aspects: content creation, target management, and AR presentation. The project focuses on developing a proper approach to serve as an interactive game, and to offer a learning opportunity for appreciating historic architectures by playing AR cards. Furthermore, the card game aims to provide multi-faceted understanding and learning experience to help user learning through 3D objects, hyperlinked web data, and the manipulation of learning mode, and then effectively developing their learning levels on cultural and historical archives in

  8. Combining Digital Archives Content with Serious Game Approach to Create a Gamified Learning Experience

    Science.gov (United States)

    Shih, D.-T.; Lin, C. L.; Tseng, C.-Y.

    2015-08-01

    This paper presents an interdisciplinary to develop content-aware application that combines game with learning on specific categories of digital archives. The employment of content-oriented game enhances the gamification and efficacy of learning in culture education on architectures and history of Hsinchu County, Taiwan. The gamified form of the application is used as a backbone to support and provide a strong stimulation to engage users in learning art and culture, therefore this research is implementing under the goal of "The Digital ARt/ARchitecture Project". The purpose of the abovementioned project is to develop interactive serious game approaches and applications for Hsinchu County historical archives and architectures. Therefore, we present two applications, "3D AR for Hukou Old " and "Hsinchu County History Museum AR Tour" which are in form of augmented reality (AR). By using AR imaging techniques to blend real object and virtual content, the users can immerse in virtual exhibitions of Hukou Old Street and Hsinchu County History Museum, and to learn in ubiquitous computing environment. This paper proposes a content system that includes tools and materials used to create representations of digitized cultural archives including historical artifacts, documents, customs, religion, and architectures. The Digital ARt / ARchitecture Project is based on the concept of serious game and consists of three aspects: content creation, target management, and AR presentation. The project focuses on developing a proper approach to serve as an interactive game, and to offer a learning opportunity for appreciating historic architectures by playing AR cards. Furthermore, the card game aims to provide multi-faceted understanding and learning experience to help user learning through 3D objects, hyperlinked web data, and the manipulation of learning mode, and then effectively developing their learning levels on cultural and historical archives in Hsinchu County.

  9. Obtaining Global Picture From Single Point Observations by Combining Data Assimilation and Machine Learning Tools

    Science.gov (United States)

    Shprits, Y.; Zhelavskaya, I. S.; Kellerman, A. C.; Spasojevic, M.; Kondrashov, D. A.; Ghil, M.; Aseev, N.; Castillo Tibocha, A. M.; Cervantes Villa, J. S.; Kletzing, C.; Kurth, W. S.

    2017-12-01

    Increasing volume of satellite measurements requires deployment of new tools that can utilize such vast amount of data. Satellite measurements are usually limited to a single location in space, which complicates the data analysis geared towards reproducing the global state of the space environment. In this study we show how measurements can be combined by means of data assimilation and how machine learning can help analyze large amounts of data and can help develop global models that are trained on single point measurement. Data Assimilation: Manual analysis of the satellite measurements is a challenging task, while automated analysis is complicated by the fact that measurements are given at various locations in space, have different instrumental errors, and often vary by orders of magnitude. We show results of the long term reanalysis of radiation belt measurements along with fully operational real-time predictions using data assimilative VERB code. Machine Learning: We present application of the machine learning tools for the analysis of NASA Van Allen Probes upper-hybrid frequency measurements. Using the obtained data set we train a new global predictive neural network. The results for the Van Allen Probes based neural network are compared with historical IMAGE satellite observations. We also show examples of predictions of geomagnetic indices using neural networks. Combination of machine learning and data assimilation: We discuss how data assimilation tools and machine learning tools can be combine so that physics-based insight into the dynamics of the particular system can be combined with empirical knowledge of it's non-linear behavior.

  10. Neural robust stabilization via event-triggering mechanism and adaptive learning technique.

    Science.gov (United States)

    Wang, Ding; Liu, Derong

    2018-06-01

    The robust control synthesis of continuous-time nonlinear systems with uncertain term is investigated via event-triggering mechanism and adaptive critic learning technique. We mainly focus on combining the event-triggering mechanism with adaptive critic designs, so as to solve the nonlinear robust control problem. This can not only make better use of computation and communication resources, but also conduct controller design from the view of intelligent optimization. Through theoretical analysis, the nonlinear robust stabilization can be achieved by obtaining an event-triggered optimal control law of the nominal system with a newly defined cost function and a certain triggering condition. The adaptive critic technique is employed to facilitate the event-triggered control design, where a neural network is introduced as an approximator of the learning phase. The performance of the event-triggered robust control scheme is validated via simulation studies and comparisons. The present method extends the application domain of both event-triggered control and adaptive critic control to nonlinear systems possessing dynamical uncertainties. Copyright © 2018 Elsevier Ltd. All rights reserved.

  11. FACTORS INFLUENCING VICARIOUS LEARNING MECHANISM EFFECTIVENESS WITHIN ORGANIZATIONS

    OpenAIRE

    JOHN R. VOIT; COLIN G. DRURY

    2013-01-01

    As organizations become larger it becomes increasingly difficult to share lessons-learned across their disconnected units allowing individuals to learn vicariously from each other's experiences. This lesson-learned information is often unsolicited by the recipient group or individual and required an individual or group to react to the information to yield benefits for the organization. Data was collected using 39 interviews and 582 survey responses that proved the effects of information usefu...

  12. Orthographic learning in children with isolated and combined reading and spelling deficits.

    Science.gov (United States)

    Mehlhase, Heike; Bakos, Sarolta; Landerl, Karin; Schulte-Körne, Gerd; Moll, Kristina

    2018-05-07

    Dissociations between reading and spelling problems are likely to be associated with different underlying cognitive deficits, and with different deficits in orthographic learning. In order to understand these differences, the current study examined orthographic learning using a printed-word learning paradigm. Children (4th grade) with isolated reading, isolated spelling and combined reading and spelling problems were compared to children with age appropriate reading and spelling skills on their performance during learning novel words and symbols (non-verbal control condition), and during immediate and delayed reading and spelling recall tasks. No group differences occurred in the non-verbal control condition. In the verbal condition, initial learning was intact in all groups, but differences occurred during recall tasks. Children with reading fluency deficits showed slower reading times, while children with spelling deficits were less accurate, both in reading and spelling recall. Children with isolated spelling problems showed no difficulties in immediate spelling recall, but had problems in remembering the spellings 2 hours later. The results suggest that different orthographic learning deficits underlie reading fluency and spelling problems: Children with isolated reading fluency deficits have no difficulties in building-up orthographic representations, but access to these representations is slowed down while children with isolated spelling deficits have problems in storing precise orthographic representations in long-term memory.

  13. Combining bimodal presentation schemes and buzz groups improves clinical reasoning and learning at morning report.

    Science.gov (United States)

    Balslev, Thomas; Rasmussen, Astrid Bruun; Skajaa, Torjus; Nielsen, Jens Peter; Muijtjens, Arno; De Grave, Willem; Van Merriënboer, Jeroen

    2014-12-11

    Abstract Morning reports offer opportunities for intensive work-based learning. In this controlled study, we measured learning processes and outcomes with the report of paediatric emergency room patients. Twelve specialists and 12 residents were randomised into four groups and discussed the same two paediatric cases. The groups differed in their presentation modality (verbal only vs. verbal + text) and the use of buzz groups (with vs. without). The verbal interactions were analysed for clinical reasoning processes. Perceptions of learning and judgment of learning were reported in a questionnaire. Diagnostic accuracy was assessed by a 20-item multiple-choice test. Combined bimodal presentation and buzz groups increased the odds ratio of clinical reasoning to occur in the discussion of cases by a factor of 1.90 (p = 0.013), indicating superior reasoning for buzz groups working with bimodal materials. For specialists, a positive effect of bimodal presentation was found on perceptions of learning (p presentation on diagnostic accuracy was noted in the specialists (p presentation and buzz group discussion of emergency cases improves clinicians' clinical reasoning and learning.

  14. Models of intracellular mechanisms of plant bioelectrical potentials caused by combined stimulation

    Directory of Open Access Journals (Sweden)

    D. V. Chernetchenko

    2014-10-01

    Full Text Available This paper deals with bioelectrical potentials of the plants recorded during different types of stimuli and combined stimulus as well. All registrations were observed on the leaves of the corn. We used different stimuli, such as cold, heat, photo- and electrical stimulation, and certain combination of this stimuli. Hardware and software system for automated recording of bioelectrical potentials has been successfully used in this work. We proposed the universal pattern of bioelectrical potentials’ recording which allowed to detect the response of the biological object to different stimuli and various combinations of these stimuli. This pattern can be used for the deeper understanding of biological mechanisms of electrical potentials’ generation in cells and discovering of processes of accommodation of whole organisms to these stimuli. Integrated system of recording and biometrical processing was used for analysis of corn leaves electrical responses to the thermal stimuli. The dynamics of these potentials was studied, with the quantitative analysis of the potential level stabilization.We calculated the ratio of amplitude of response potentials to the first response amplitude. Mathematical models of the plant cell were used for studying of intracellular mechanisms of biopotentials gereration. As a result of modeling, we revealed that electrical response of the cells was based on selectiveconductivity of cell membrane for Н+ and Ca2+ ions. Therefore, we showed the biophysical relation of plant potentials to underlying intracellular biophysical mechanisms during thermal and combined stimulation.

  15. An Opportunistic Routing Mechanism Combined with Long-Term and Short-Term Metrics for WMN

    Directory of Open Access Journals (Sweden)

    Weifeng Sun

    2014-01-01

    Full Text Available WMN (wireless mesh network is a useful wireless multihop network with tremendous research value. The routing strategy decides the performance of network and the quality of transmission. A good routing algorithm will use the whole bandwidth of network and assure the quality of service of traffic. Since the routing metric ETX (expected transmission count does not assure good quality of wireless links, to improve the routing performance, an opportunistic routing mechanism combined with long-term and short-term metrics for WMN based on OLSR (optimized link state routing and ETX is proposed in this paper. This mechanism always chooses the highest throughput links to improve the performance of routing over WMN and then reduces the energy consumption of mesh routers. The simulations and analyses show that the opportunistic routing mechanism is better than the mechanism with the metric of ETX.

  16. An opportunistic routing mechanism combined with long-term and short-term metrics for WMN.

    Science.gov (United States)

    Sun, Weifeng; Wang, Haotian; Piao, Xianglan; Qiu, Tie

    2014-01-01

    WMN (wireless mesh network) is a useful wireless multihop network with tremendous research value. The routing strategy decides the performance of network and the quality of transmission. A good routing algorithm will use the whole bandwidth of network and assure the quality of service of traffic. Since the routing metric ETX (expected transmission count) does not assure good quality of wireless links, to improve the routing performance, an opportunistic routing mechanism combined with long-term and short-term metrics for WMN based on OLSR (optimized link state routing) and ETX is proposed in this paper. This mechanism always chooses the highest throughput links to improve the performance of routing over WMN and then reduces the energy consumption of mesh routers. The simulations and analyses show that the opportunistic routing mechanism is better than the mechanism with the metric of ETX.

  17. PHYSIOLOGICAL QUALITY OF SOYBEAN SEEDS UNDER MECHANICAL INJURIES CAUSED BY COMBINES

    Directory of Open Access Journals (Sweden)

    FÁBIO PALCZEWSKI PACHECO

    2015-01-01

    Full Text Available The mechanical harvesting causes injuries on seeds and may affect their quality. Different threshing mechanisms and their adjustments may also affect the intensity of impacts that machines cause on seeds. So, this study aimed at diagnosing and evaluating the effect of two combines: the first one with a threshing system of axial flow and the other one with a threshing system of tangential flow, under adjustments of concave opening (10 mm, 30 mm and 10 mm for a combine with axial flow and 3.0 mm, 15 mm and 3.0 mm for a combine with tangential flow and three cylinder rotations on the quality of soybean seeds harvested at two moisture contents. Soybean seeds of cultivar 'ND 4910' were harvested at 16.6% moisture (mid - morning and 13.7% moisture in the afternoon. The seeds quality was evaluated by germination tests, germination speed index (GSI, germination rate, moisture content, percentage of purity and vigor by tetrazolium test. Despite the combine, the results showed that the mechanical injury has most reduced seeds quality, at 16.6% moisture content, concave opening of 30 mm (axial and 10 mm (tangential and cylinder rotation of 1100 rpm (axial and 1000 (tangential, both with the highest rotations used. The combine with tangential flow had the highest degree of seeds purity. When seeds moisture content at harvest was close to 13.7%, there was the highest seed injury, while, at 16.6%, there was the highest number of crushed soybeans, regardless the combine adjustment.

  18. Steps toward Learning Mechanics Using Fan Cart Video Demonstrations

    Science.gov (United States)

    Lattery, Mark

    2011-01-01

    The Newtonian force concept is very difficult for introductory students to learn. One obstacle to learning is a premature focus on gravity-driven motions, such as vertical free fall, rolling motion on an inclined plane, and the Atwood's machine. In each case, the main agent of motion ("gravity") cannot be seen, heard, or controlled by the student.…

  19. Embedding Diagnostic Mechanisms in a Digital Game for Learning Mathematics

    Science.gov (United States)

    Huang, Yueh-Min; Huang, Shu-Hsien; Wu, Ting-Ting

    2014-01-01

    Mathematics is closely related to daily life, but it is also one of the lessons which often cause anxiety to primary school students. Digital game-based learning (DGBL) has been regarded as a sound learning strategy in raising learner willingness and interest in many disciplines. Thus, ways of designing a DGBL system to mitigate anxiety are well…

  20. Combined impact of exercise and temperature in learning and memory performance of fluoride toxicated rats.

    Science.gov (United States)

    Basha, P Mahaboob; Sujitha, N S

    2012-12-01

    In previous studies, we investigated a link between high fluoride exposure and functional IQ deficits in rats. This study is an extension conducted to explore the combined influence of physical exercise and temperature stress on the learning ability and memory in rats and to assess whether any positive modulation could be attenuated due to exercise regimen subjected to F-toxicated animals at different temperatures. Accumulation of ingested fluoride resulted significant inhibition in acetylcholinesterase activity (P learning phase [F (5, 35) = 19.065; P temperatures, high (35 °C) and low temperatures (20 °C) led to a slower acquisition and poor retention of the task when compared to thermo neutral temperatures (25 and 30 °C). Thus exercise up-regulate antioxidant defenses and promote learning abilities in fluorotic population.

  1. Representation and Integration: Combining Robot Control, High-Level Planning, and Action Learning

    DEFF Research Database (Denmark)

    Petrick, Ronald; Kraft, Dirk; Mourao, Kira

    We describe an approach to integrated robot control, high-level planning, and action effect learning that attempts to overcome the representational difficulties that exist between these diverse areas. Our approach combines ideas from robot vision, knowledgelevel planning, and connectionist machine......-level action specifications, suitable for planning, from a robot’s interactions with the world. We present a detailed overview of our approach and show how it supports the learning of certain aspects of a high-level lepresentation from low-level world state information....... learning, and focuses on the representational needs of these components.We also make use of a simple representational unit called an instantiated state transition fragment (ISTF) and a related structure called an object-action complex (OAC). The goal of this work is a general approach for inducing high...

  2. Monocular perceptual learning of contrast detection facilitates binocular combination in adults with anisometropic amblyopia.

    Science.gov (United States)

    Chen, Zidong; Li, Jinrong; Liu, Jing; Cai, Xiaoxiao; Yuan, Junpeng; Deng, Daming; Yu, Minbin

    2016-02-01

    Perceptual learning in contrast detection improves monocular visual function in adults with anisometropic amblyopia; however, its effect on binocular combination remains unknown. Given that the amblyopic visual system suffers from pronounced binocular functional loss, it is important to address how the amblyopic visual system responds to such training strategies under binocular viewing conditions. Anisometropic amblyopes (n = 13) were asked to complete two psychophysical supra-threshold binocular summation tasks: (1) binocular phase combination and (2) dichoptic global motion coherence before and after monocular training to investigate this question. We showed that these participants benefited from monocular training in terms of binocular combination. More importantly, the improvements observed with the area under log CSF (AULCSF) were found to be correlated with the improvements in binocular phase combination.

  3. Combining different Technologies in a Funerary Archaeology content and language integrated Learning (CLIL) Course

    OpenAIRE

    Cignoni, Laura; Fornaciari, Gino

    2009-01-01

    The aim of this paper is to describe a project in which Italian undergraduate students at the Palaeopathology Division of Pisa University will attend a two-year Content and Language Integrated Learning (CLIL) course combining the study of funerary archaeology with English as vehicular language. At the presence of a subject and language teacher working together, the trainees will use different types of technology including devices such as electronic blackboards and Word applications with user-...

  4. Monocular perceptual learning of contrast detection facilitates binocular combination in adults with anisometropic amblyopia

    OpenAIRE

    Chen, Zidong; Li, Jinrong; Liu, Jing; Cai, Xiaoxiao; Yuan, Junpeng; Deng, Daming; Yu, Minbin

    2016-01-01

    Perceptual learning in contrast detection improves monocular visual function in adults with anisometropic amblyopia; however, its effect on binocular combination remains unknown. Given that the amblyopic visual system suffers from pronounced binocular functional loss, it is important to address how the amblyopic visual system responds to such training strategies under binocular viewing conditions. Anisometropic amblyopes (n?=?13) were asked to complete two psychophysical supra-threshold binoc...

  5. Combining Unsupervised and Supervised Statistical Learning Methods for Currency Exchange Rate Forecasting

    OpenAIRE

    Vasiljeva, Polina

    2016-01-01

    In this thesis we revisit the challenging problem of forecasting currency exchange rate. We combine machine learning methods such as agglomerative hierarchical clustering and random forest to construct a two-step approach for predicting movements in currency exchange prices of the Swedish krona and the US dollar. We use a data set with over 200 predictors comprised of different financial and macro-economic time series and their transformations. We perform forecasting for one week ahead with d...

  6. Empowerment of Students Critical Thinking Skills Through Implementation of Think Talk Write Combined Problem Based Learning

    OpenAIRE

    Yanuarta, Lidya; Gofur, Abdul; Indriwati, Sri Endah

    2016-01-01

    Critical thinking is a complex reflection process that helps individuals become more analytical in their thinking. Empower critical thinking in students need to be done so that students can resolve the problems that exist in their life and are able to apply alternative solutions to problems in a different situations. Therefore, Think Talk Write (TTW) combined Problem Based Learning (PBL) were needed to empowered the critical thinking skills so that students were able to face the challenges of...

  7. Using video games to combine learning and assessment in mathematics education

    OpenAIRE

    Kristian Juha Mikael Kiili; Keith Devlin; Arttu Perttula; Pauliina Tuomi; Antero Lindstedt

    2015-01-01

    One problem with most education systems is that learning and (summative) assessment are generally treated as quite separate things in schools. We argue that video games can provide an opportunity to combine these processes in an engaging and effective way. The present study focuses on investigating the effectiveness and the assessment power of two different mathematics video games, Semideus and Wuzzit Trouble. In the current study, we validated the Semideus game as a rational number test inst...

  8. Design Learning of Teaching Factory in Mechanical Engineering

    Science.gov (United States)

    Putra, R. C.; Kusumah, I. H.; Komaro, M.; Rahayu, Y.; Asfiyanur, E. P.

    2018-02-01

    The industrial world that is the target of the process and learning outcomes of vocational high school (SMK) has its own character and nuance. Therefore, vocational education institutions in the learning process should be able to make the appropriate learning approach and in accordance with the industrial world. One approach to learning that is based on production and learning in the world of work is by industry-based learning or known as Teaching Factory, where in this model apply learning that involves direct students in goods or service activities are expected to have the quality so it is worth selling and accepted by consumers. The method used is descriptive approach. The purpose of this research is to get the design of the teaching factory based on the competency requirements of the graduates of the spouse industry, especially in the engineering department. The results of this study is expected to be one of the choice of model factory teaching in the field of machinery engineering in accordance with the products and competencies of the graduates that the industry needs.

  9. Angular approach combined to mechanical model for tool breakage detection by eddy current sensors

    OpenAIRE

    Ritou , Mathieu; Garnier , Sébastien; Furet , Benoît; Hascoët , Jean-Yves

    2014-01-01

    International audience; The paper presents a new complete approach for Tool Condition Monitoring (TCM) in milling. The aim is the early detection of small damages so that catastrophic tool failures are prevented. A versatile in-process monitoring system is introduced for reliability concerns. The tool condition is determined by estimates of the radial eccentricity of the teeth. An adequate criterion is proposed combining mechanical model of milling and angular approach. Then, a new solution i...

  10. On Combining Elements of Different Ways of Learning, Methods and Knowledge

    Directory of Open Access Journals (Sweden)

    Dušana Findeisen

    2013-12-01

    Full Text Available The paper deals with different thinkers' attitude towards methods in adult education. It examines the value of some elements of »trial and error learning« and »non-directive learning«. Like a multifaceted approach based on elements drawn from different methods, the way we learn can also be eclectic.  To illustrate this assertion, the author analyses the »anti method« used by Maurice Pialat, a French film director, contrasting it with methods in which the aim is set in advance and the process leading towards it is organised in sequences. This is most often the case in script-based shooting of films, directing a theatre performance or running adult education. Moreover, the author argues that learning about how to do something is combined with learning about how to be. She further emphasises that methods should not be used to impose one’s knowledge and one’s reality on the learner, thus destroying circumstances necessary for gaining or creating knowledge.

  11. Learning and Memory, Part II: Molecular Mechanisms of Synaptic Plasticity

    Science.gov (United States)

    Lombroso, Paul; Ogren, Marilee

    2009-01-01

    The molecular events that are responsible for strengthening synaptic connections and how these are linked to memory and learning are discussed. The laboratory preparations that allow the investigation of these events are also described.

  12. Learning Similar Actions by Reinforcement or Sensory-Prediction Errors Rely on Distinct Physiological Mechanisms.

    Science.gov (United States)

    Uehara, Shintaro; Mawase, Firas; Celnik, Pablo

    2017-09-14

    Humans can acquire knowledge of new motor behavior via different forms of learning. The two forms most commonly studied have been the development of internal models based on sensory-prediction errors (error-based learning) and success-based feedback (reinforcement learning). Human behavioral studies suggest these are distinct learning processes, though the neurophysiological mechanisms that are involved have not been characterized. Here, we evaluated physiological markers from the cerebellum and the primary motor cortex (M1) using noninvasive brain stimulations while healthy participants trained finger-reaching tasks. We manipulated the extent to which subjects rely on error-based or reinforcement by providing either vector or binary feedback about task performance. Our results demonstrated a double dissociation where learning the task mainly via error-based mechanisms leads to cerebellar plasticity modifications but not long-term potentiation (LTP)-like plasticity changes in M1; while learning a similar action via reinforcement mechanisms elicited M1 LTP-like plasticity but not cerebellar plasticity changes. Our findings indicate that learning complex motor behavior is mediated by the interplay of different forms of learning, weighing distinct neural mechanisms in M1 and the cerebellum. Our study provides insights for designing effective interventions to enhance human motor learning. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  13. Combining fMRI and behavioral measures to examine the process of human learning.

    Science.gov (United States)

    Karuza, Elisabeth A; Emberson, Lauren L; Aslin, Richard N

    2014-03-01

    Prior to the advent of fMRI, the primary means of examining the mechanisms underlying learning were restricted to studying human behavior and non-human neural systems. However, recent advances in neuroimaging technology have enabled the concurrent study of human behavior and neural activity. We propose that the integration of behavioral response with brain activity provides a powerful method of investigating the process through which internal representations are formed or changed. Nevertheless, a review of the literature reveals that many fMRI studies of learning either (1) focus on outcome rather than process or (2) are built on the untested assumption that learning unfolds uniformly over time. We discuss here various challenges faced by the field and highlight studies that have begun to address them. In doing so, we aim to encourage more research that examines the process of learning by considering the interrelation of behavioral measures and fMRI recording during learning. Copyright © 2013 Elsevier Inc. All rights reserved.

  14. On aging factors, aging mechanisms and their combinations in the primary circuit of NPPs

    International Nuclear Information System (INIS)

    Varga, T.; Brumovsky, M.

    1993-01-01

    Ageing is the dominating problem of elder nuclear power plant (NPP) components but still can not be neglected even for the newest ones. Ageing may express itself in different ways: irradiated steel parts may become embrittled, chromium alloy steels may decompose, fatigue life may become exhausted so that cracks may be formed and finally, corrosion attack may result in stress corrosion cracking. However, even synthetics and rubber parts may become inelastic, swell, shrink or crack, electric contacts may be oxydised, or isolations may lose their high electric resistance. Therefore, experts in the different components and their materials have collected and published not only plenty of observations, but also a number of more or less systematic approaches. A general picture, however, still seems to be lacking, due to the fact that ageing factors and mechanisms are not defined and used properly, i.e. - ageing factors act because of the service conditions of the components, as well as the characteristics of the materials which provoke ageing mechanisms - ageing mechanisms cause the changing of properties of the materials involved - combinations of single ageing mechanisms, which can be double, triple or multiple, change and accelerate the ageing process - the consequence of ageing mechanisms is the altering of the properties of the material depending on the lifetime. In this paper we shall try to show a systematic approach to a potential ageing analysis concerning the main metallic components of primary circuits of NPP's - connection between ageing factors, ageing mechanisms and their consequences/effects on component behaviour

  15. Combined quantum mechanical and molecular mechanical method for metal-organic frameworks: proton topologies of NU-1000.

    Science.gov (United States)

    Wu, Xin-Ping; Gagliardi, Laura; Truhlar, Donald G

    2018-01-17

    Metal-organic frameworks (MOFs) are materials with applications in catalysis, gas separations, and storage. Quantum mechanical (QM) calculations can provide valuable guidance to understand and predict their properties. In order to make the calculations faster, rather than modeling these materials as periodic (infinite) systems, it is useful to construct finite models (called cluster models) and use subsystem methods such as fragment methods or combined quantum mechanical and molecular mechanical (QM/MM) methods. Here we employ a QM/MM methodology to study one particular MOF that has been of widespread interest because of its wide pores and good solvent and thermal stability, namely NU-1000, which contains hexanuclear zirconium nodes and 1,3,6,8-tetrakis(p-benzoic acid)pyrene (TBAPy 4- ) linkers. A modified version of the Bristow-Tiana-Walsh transferable force field has been developed to allow QM/MM calculations on NU-1000; we call the new parametrization the NU1T force field. We consider isomeric structures corresponding to various proton topologies of the [Zr 6 (μ 3 -O) 8 O 8 H 16 ] 8+ node of NU-1000, and we compute their relative energies using a QM/MM scheme designed for the present kind of problem. We compared the results to full quantum mechanical (QM) energy calculations and found that the QM/MM models can reproduce the full QM relative energetics (which span a range of 334 kJ mol -1 ) with a mean unsigned deviation (MUD) of only 2 kJ mol -1 . Furthermore, we found that the structures optimized by QM/MM are nearly identical to their full QM optimized counterparts.

  16. Mechanical system reliability analysis using a combination of graph theory and Boolean function

    International Nuclear Information System (INIS)

    Tang, J.

    2001-01-01

    A new method based on graph theory and Boolean function for assessing reliability of mechanical systems is proposed. The procedure for this approach consists of two parts. By using the graph theory, the formula for the reliability of a mechanical system that considers the interrelations of subsystems or components is generated. Use of the Boolean function to examine the failure interactions of two particular elements of the system, followed with demonstrations of how to incorporate such failure dependencies into the analysis of larger systems, a constructive algorithm for quantifying the genuine interconnections between the subsystems or components is provided. The combination of graph theory and Boolean function provides an effective way to evaluate the reliability of a large, complex mechanical system. A numerical example demonstrates that this method an effective approaches in system reliability analysis

  17. College radio as a mechanism for participatory learning: Exploring the scope for online radio based learning among undergraduates

    Directory of Open Access Journals (Sweden)

    Bahaeldin Ibrahim

    2016-03-01

    Full Text Available This paper explores the prospects of online college radio at Sur College of Applied Sciences, its need among students and the possible scope of its contributions to student learning, engagement and community service. It explores the method of developing a holistic mechanism to capture the possibilities of maximizing learning experience by employing college radio as an educational tool to understand the micro-dynamics and localized necessities that deem it necessary or unnecessary. Through this, it attempts to locate an appropriate mechanism, and targeted use of the college radio in contributing to the learning outcomes and educational experience of the students. The study finds considerable scope for radio based learning at Sur College of Applied Sciences across a range of uses and gratification indicators consistent with the primary objectives of the college. The study discusses the theoretical and practical implications of the findings, and the pedagogical significance of the college radio as an alternative.

  18. Neuronal mechanisms of motor learning and motor memory consolidation in healthy old adults.

    Science.gov (United States)

    Berghuis, K M M; Veldman, M P; Solnik, S; Koch, G; Zijdewind, I; Hortobágyi, T

    2015-06-01

    It is controversial whether or not old adults are capable of learning new motor skills and consolidate the performance gains into motor memory in the offline period. The underlying neuronal mechanisms are equally unclear. We determined the magnitude of motor learning and motor memory consolidation in healthy old adults and examined if specific metrics of neuronal excitability measured by magnetic brain stimulation mediate the practice and retention effects. Eleven healthy old adults practiced a wrist extension-flexion visuomotor skill for 20 min (MP, 71.3 years), while a second group only watched the templates without movements (attentional control, AC, n = 11, 70.5 years). There was 40 % motor learning in MP but none in AC (interaction, p learn a new motor skill and consolidate the learned skill into motor memory, processes that are most likely mediated by disinhibitory mechanisms. These results are relevant for the increasing number of old adults who need to learn and relearn movements during motor rehabilitation.

  19. Mechanism of Sporicidal Activity for the Synergistic Combination of Peracetic Acid and Hydrogen Peroxide.

    Science.gov (United States)

    Leggett, Mark J; Schwarz, J Spencer; Burke, Peter A; McDonnell, Gerald; Denyer, Stephen P; Maillard, Jean-Yves

    2016-02-15

    There is still great interest in controlling bacterial endospores. The use of chemical disinfectants and, notably, oxidizing agents to sterilize medical devices is increasing. With this in mind, hydrogen peroxide (H2O2) and peracetic acid (PAA) have been used in combination, but until now there has been no explanation for the observed increase in sporicidal activity. This study provides information on the mechanism of synergistic interaction of PAA and H2O2 against bacterial spores. We performed investigations of the efficacies of different combinations, including pretreatments with the two oxidizers, against wild-type spores and a range of spore mutants deficient in the spore coat or small acid-soluble spore proteins. The concentrations of the two biocides were also measured in the reaction vessels, enabling the assessment of any shift from H2O2 to PAA formation. This study confirmed the synergistic activity of the combination of H2O2 and PAA. However, we observed that the sporicidal activity of the combination is largely due to PAA and not H2O2. Furthermore, we observed that the synergistic combination was based on H2O2 compromising the spore coat, which was the main spore resistance factor, likely allowing better penetration of PAA and resulting in the increased sporicidal activity. Copyright © 2016 Leggett et al.

  20. Combined Treatment With Environmental Enrichment and (-)-Epigallocatechin-3-Gallate Ameliorates Learning Deficits and Hippocampal Alterations in a Mouse Model of Down Syndrome.

    Science.gov (United States)

    Catuara-Solarz, Silvina; Espinosa-Carrasco, Jose; Erb, Ionas; Langohr, Klaus; Gonzalez, Juan Ramon; Notredame, Cedric; Dierssen, Mara

    2016-01-01

    Intellectual disability in Down syndrome (DS) is accompanied by altered neuro-architecture, deficient synaptic plasticity, and excitation-inhibition imbalance in critical brain regions for learning and memory. Recently, we have demonstrated beneficial effects of a combined treatment with green tea extract containing (-)-epigallocatechin-3-gallate (EGCG) and cognitive stimulation in young adult DS individuals. Although we could reproduce the cognitive-enhancing effects in mouse models, the underlying mechanisms of these beneficial effects are unknown. Here, we explored the effects of a combined therapy with environmental enrichment (EE) and EGCG in the Ts65Dn mouse model of DS at young age. Our results show that combined EE-EGCG treatment improved corticohippocampal-dependent learning and memory. Cognitive improvements were accompanied by a rescue of cornu ammonis 1 (CA1) dendritic spine density and a normalization of the proportion of excitatory and inhibitory synaptic markers in CA1 and dentate gyrus.

  1. Liraglutide, leptin and their combined effects on feeding: additive intake reduction through common intracellular signalling mechanisms.

    Science.gov (United States)

    Kanoski, S E; Ong, Z Y; Fortin, S M; Schlessinger, E S; Grill, H J

    2015-03-01

    To investigate the behavioural and intracellular mechanisms by which the glucagon like peptide-1 (GLP-1) receptor agonist, liraglutide, and leptin in combination enhance the food intake inhibitory and weight loss effects of either treatment alone. We examined the effects of liraglutide (a long-acting GLP-1 analogue) and leptin co-treatment, delivered in low or moderate doses subcutaneously (s.c.) or to the third ventricle, respectively, on cumulative intake, meal patterns and hypothalamic expression of intracellular signalling proteins [phosphorylated signal transducer and activator of transcription-3 (pSTAT3) and protein tyrosine phosphatase-1B (PTP1B)] in lean rats. A low-dose combination of liraglutide (25 µg/kg) and leptin (0.75 µg) additively reduced cumulative food intake and body weight, a result mediated predominantly through a significant reduction in meal frequency that was not present with either drug alone. Liraglutide treatment alone also reduced meal size; an effect not enhanced with leptin co-administration. Moderate doses of liraglutide (75 µg/kg) and leptin (4 µg), examined separately, each reduced meal frequency, cumulative food intake and body weight; only liraglutide reduced meal size. In combination these doses did not further enhance the anorexigenic effects of either treatment alone. Ex vivo immunoblot analysis showed elevated pSTAT3 in the hypothalamic tissue after liraglutide-leptin co-treatment, an effect which was greater than that of leptin treatment alone. In addition, s.c. liraglutide reduced the expression of PTP1B (a negative regulator of leptin receptor signalling), revealing a potential mechanism for the enhanced pSTAT3 response after liraglutide-leptin co-administration. Collectively, these results show novel behavioural and molecular mechanisms underlying the additive reduction in food intake and body weight after liraglutide-leptin combination treatment. © 2014 John Wiley & Sons Ltd.

  2. Visual diet versus associative learning as mechanisms of change in body size preferences.

    Directory of Open Access Journals (Sweden)

    Lynda G Boothroyd

    Full Text Available Systematic differences between populations in their preferences for body size may arise as a result of an adaptive 'prepared learning' mechanism, whereby cues to health or status in the local population are internalized and affect body preferences. Alternatively, differences between populations may reflect their 'visual diet' as a cognitive byproduct of mere exposure. Here we test the relative importance of these two explanations for variation in body preferences. Two studies were conducted where female observers were exposed to pictures of high or low BMI women which were either aspirational (healthy, attractive models in high status clothes or non-aspirational (eating disordered patients in grey leotards, or to combinations thereof, in order to manipulate their body-weight preferences which were tested at baseline and at post-test. Overall, results showed good support for visual diet effects (seeing a string of small or large bodies resulted in a change from pre- to post-test whether the bodies were aspirational or not and also some support for the associative learning explanation (exposure to aspirational images of overweight women induced a towards preferring larger bodies, even when accompanied by equal exposure to lower weight bodies in the non-aspirational category. Thus, both influences may act in parallel.

  3. Separation of atmospheric, oceanic and hydrological polar motion excitation mechanisms based on a combination of geometric and gravimetric space observations

    Science.gov (United States)

    Göttl, F.; Schmidt, M.; Seitz, F.; Bloßfeld, M.

    2015-04-01

    The goal of our study is to determine accurate time series of geophysical Earth rotation excitations to learn more about global dynamic processes in the Earth system. For this purpose, we developed an adjustment model which allows to combine precise observations from space geodetic observation systems, such as Satellite Laser Ranging (SLR), Global Navigation Satellite Systems, Very Long Baseline Interferometry, Doppler Orbit determination and Radiopositioning Integrated on Satellite, satellite altimetry and satellite gravimetry in order to separate geophysical excitation mechanisms of Earth rotation. Three polar motion time series are applied to derive the polar motion excitation functions (integral effect). Furthermore we use five time variable gravity field solutions from Gravity Recovery and Climate Experiment to determine not only the integral mass effect but also the oceanic and hydrological mass effects by applying suitable filter techniques and a land-ocean mask. For comparison the integral mass effect is also derived from degree 2 potential coefficients that are estimated from SLR observations. The oceanic mass effect is also determined from sea level anomalies observed by satellite altimetry by reducing the steric sea level anomalies derived from temperature and salinity fields of the oceans. Due to the combination of all geodetic estimated excitations the weaknesses of the individual processing strategies can be reduced and the technique-specific strengths can be accounted for. The formal errors of the adjusted geodetic solutions are smaller than the RMS differences of the geophysical model solutions. The improved excitation time series can be used to improve the geophysical modeling.

  4. Influences of combined traffic noise on the ability of learning and memory in mice

    Directory of Open Access Journals (Sweden)

    Guo-Qing Di

    2018-01-01

    Full Text Available Objective: The present study aimed to evaluate the influences of combined traffic noise (CTN on the ability of learning and memory in mice. Materials and Methods: The Institute of Cancer Research (ICR mice were exposed to CTN from highways and high-speed railways for 42 days, whose day–night equivalent continuous A-weighted sound pressure level (Ldn was 70 dB(A. On the basis of behavioral reactions in Morris water maze (MWM and the concentrations of amino acid neurotransmitters in the hippocampus, the impacts of CTN on learning and memory in mice were examined. Results: The MWM test showed that the ability of learning and memory in mice was improved after short-term exposure (6–10 days, the first batch to 70 dB(A CTN, which showed the excitatory effect of stimuli. Long-term exposure (26–30 days, the third batch; 36–40 days, the fourth batch led to the decline of learning and memory ability, which indicated the inhibitory effect of stimuli. Assays testing amino acid neurotransmitters showed that the glutamate level of the experimental group was higher than that of the control group in the first batch. However, the former was lower than the latter in the third and fourth batches. Both, behavioral reactions and the concentrations of amino acid neurotransmitters, testified that short-term exposure and long-term exposure resulted in excitatory effect and inhibitory effect on the ability of learning and memory, respectively. Conclusion: The effects of 70 dB(A CTN on the ability of learning and memory were closely related to the exposure duration. Furthermore, those effects were regulated and controlled by the level of glutamate in the hippocampus.

  5. Teacher Opinions on the Innovation Management Skills of School Administrators and Organizational Learning Mechanisms

    Science.gov (United States)

    Omur, Yunus Emre; Argon, Turkan

    2016-01-01

    Problem Statement: In modern society, schools, just as other institutions, are required to be innovative organizations. For this purpose, they must not only be learning organizations, they must also be innovative. In this sense, the purpose of this study is to discover the relationship between organizational learning mechanisms at schools and…

  6. Value innovation, deliberate learning mechanisms and information from supply chain partners

    NARCIS (Netherlands)

    Berghman, L.A.; Matthyssens, P.; Vandenbempt, K.

    2012-01-01

    Although marketing scholars have emphasized both the importance of internal learning mechanisms and of external learning through supply chain partners research findings on how these factors influence each other are merely lacking. Analyzing survey data of 182 industrial firms, we examine how

  7. Neuronal mechanisms of motor learning and motor memory consolidation in healthy old adults

    NARCIS (Netherlands)

    Berghuis, K. M. M.; Veldman, M. P.; Solnik, S.; Koch, G.; Zijdewind, I.; Hortobagyi, T.

    It is controversial whether or not old adults are capable of learning new motor skills and consolidate the performance gains into motor memory in the offline period. The underlying neuronal mechanisms are equally unclear. We determined the magnitude of motor learning and motor memory consolidation

  8. Restrained Proton Indicator in Combined Quantum-Mechanics/Molecular-Mechanics Dynamics Simulations of Proton Transfer through a Carbon Nanotube.

    Science.gov (United States)

    Duster, Adam W; Lin, Hai

    2017-09-14

    Recently, a collective variable "proton indicator" was purposed for tracking an excess proton solvated in bulk water in molecular dynamics simulations. In this work, we demonstrate the feasibility of utilizing the position of this proton indicator as a reaction coordinate to model an excess proton migrating through a hydrophobic carbon nanotube in combined quantum-mechanics/molecular-mechanics simulations. Our results indicate that applying a harmonic restraint to the proton indicator in the bulk solvent near the nanotube pore entrance leads to the recruitment of water molecules into the pore. This is consistent with an earlier study that employed a multistate empirical valence bond potential and a different representation (center of excess charge) of the proton. We attribute this water recruitment to the delocalized nature of the solvated proton, which prefers to be in high-dielectric bulk solvent. While water recruitment into the pore is considered an artifact in the present simulations (because of the artificially imposed restraint on the proton), if the proton were naturally restrained, it could assist in building water wires prior to proton transfer through the pore. The potential of mean force for a proton translocation through the water-filled pore was computed by umbrella sampling, where the bias potentials were applied to the proton indicator. The free energy curve and barrier heights agree reasonably with those in the literature. The results suggest that the proton indicator can be used as a reaction coordinate in simulations of proton transport in confined environments.

  9. Combined Mechanical Destruction and Alkaline Pretreatment of Wheat Straw for Enhanced Enzymatic Saccharification

    Directory of Open Access Journals (Sweden)

    Qianqian Wang

    2014-09-01

    Full Text Available Wheat straw was pretreated by combined mechanical destruction and alkaline pretreatments to enhance enzymatic saccharification. Four strategies were employed to evaluate the potential of wheat straw as a feedstock for fermentable sugar production. The effects of the pretreatments on the substrate morphology, size distribution, chemical composition, and cellulose crystallinity, along with the subsequent enzymatic digestibility, were investigated. Optical microscope images showed that mechanical pretreatment alone resulted in poor fiber defibrillation, wherein samples mostly consisted of rigid fiber bundles, while integrated mechanical destruction and alkaline pretreatment led to relatively good fiber defibrillation. Low temperature NaOH/urea pretreatment can fibrillate the rigid fiber bundles into a relatively loose network and alter the structure of the treated substrate to make cellulose more accessible. The glucan conversion rates were 77% and 95% for integrated mechanical destruction and alkaline pretreatments and mechanical destruction followed by low temperature NaOH/urea and ammonium/urea pretreatments, respectively, after 72 h of enzymatic hydrolysis with enzyme loadings of 10 FPU cellulase per g of oven-dry substrate.

  10. Learning and adaptation: neural and behavioural mechanisms behind behaviour change

    Science.gov (United States)

    Lowe, Robert; Sandamirskaya, Yulia

    2018-01-01

    This special issue presents perspectives on learning and adaptation as they apply to a number of cognitive phenomena including pupil dilation in humans and attention in robots, natural language acquisition and production in embodied agents (robots), human-robot game play and social interaction, neural-dynamic modelling of active perception and neural-dynamic modelling of infant development in the Piagetian A-not-B task. The aim of the special issue, through its contributions, is to highlight some of the critical neural-dynamic and behavioural aspects of learning as it grounds adaptive responses in robotic- and neural-dynamic systems.

  11. The evolution of social learning mechanisms and cultural phenomena in group foragers.

    Science.gov (United States)

    van der Post, Daniel J; Franz, Mathias; Laland, Kevin N

    2017-02-10

    Advanced cognitive abilities are widely thought to underpin cultural traditions and cumulative cultural change. In contrast, recent simulation models have found that basic social influences on learning suffice to support both cultural phenomena. In the present study we test the predictions of these models in the context of skill learning, in a model with stochastic demographics, variable group sizes, and evolved parameter values, exploring the cultural ramifications of three different social learning mechanisms. Our results show that that simple forms of social learning such as local enhancement, can generate traditional differences in the context of skill learning. In contrast, we find cumulative cultural change is supported by observational learning, but not local or stimulus enhancement, which supports the idea that advanced cognitive abilities are important for generating this cultural phenomenon in the context of skill learning. Our results help to explain the observation that animal cultures are widespread, but cumulative cultural change might be rare.

  12. Promise of combined hydrothermal/chemical and mechanical refining for pretreatment of woody and herbaceous biomass.

    Science.gov (United States)

    Kim, Sun Min; Dien, Bruce S; Singh, Vijay

    2016-01-01

    Production of advanced biofuels from woody and herbaceous feedstocks is moving into commercialization. Biomass needs to be pretreated to overcome the physicochemical properties of biomass that hinder enzyme accessibility, impeding the conversion of the plant cell walls to fermentable sugars. Pretreatment also remains one of the most costly unit operations in the process and among the most critical because it is the source of chemicals that inhibit enzymes and microorganisms and largely determines enzyme loading and sugar yields. Pretreatments are categorized into hydrothermal (aqueous)/chemical, physical, and biological pretreatments, and the mechanistic details of which are briefly outlined in this review. To leverage the synergistic effects of different pretreatment methods, conducting two or more pretreatments consecutively has gained attention. Especially, combining hydrothermal/chemical pretreatment and mechanical refining, a type of physical pretreatment, has the potential to be applied to an industrial plant. Here, the effects of the combined pretreatment (combined hydrothermal/chemical pretreatment and mechanical refining) on energy consumption, physical structure, sugar yields, and enzyme dosage are summarized.

  13. Exploring Bhavana samskara using Tinospora cordifolia and Phyllanthus emblica combination for learning and memory in mice

    Directory of Open Access Journals (Sweden)

    Harshad Onkarrao Malve

    2015-01-01

    Full Text Available Background: Current medications for dementia and enhancement of learning and memory are limited hence we need to explore traditional medicinal systems like Ayurveda to investigate agents that can improve learning and enhance memory. Objective: The present study was carried out to evaluate effects and mechanisms of Ayurveda drug formulations, Tinospora cordifolia (Tc and Phyllanthus emblica (Pe with and without Bhavana samskara on learning and memory of mice. Materials and Methods: After approval of Animal Ethics Committee, Swiss albino mice were divided into seven groups, administered orally: Distilled water, Rivastigmine (2.4 mg/kg, Tc (100 mg/kg, Pe (300 mg/kg, formulation 1 (Tc + Pe: 400 mg/kg and formulation 2 (Tc + Pe + Ocimum sanctum: 400 mg/kg daily for 15 days. Piracetam (200 mg/kg was injected daily intraperitoneally for 8 days. The mice underwent a learning session using elevated plus maze. Memory was tested 24 hours later. Results: Mice pretreated with all the drugs showed a trend toward reducing transfer latencies but values were comparable to vehicle control. In all drug-treated groups, a significant reduction in transfer latency was observed after 24 h. Improvement in learning and memory by both formulations were comparable to individual plant drugs, Tc and Pe. Conclusion: The plant drugs showed improvements in learning and memory. The fixed-dose formulations with Bhavana samskara, showed encouraging results as compared to individual agents but the difference was not statistically significant. Hence, the concept of Bhavana samskara could not be explored in the present study. However, these drugs showed comparable or better effects than the modern medicinal agents thus, their therapeutic potential as nootropics needs to be explored further.

  14. Improving students' meaningful learning on the predictive nature of quantum mechanics

    Directory of Open Access Journals (Sweden)

    Rodolfo Alves de Carvalho Neto

    2009-03-01

    Full Text Available This paper deals with research about teaching quantum mechanics to 3rd year high school students and their meaningful learning of its predictive aspect; it is based on the Master’s dissertation of one of the authors (CARVALHO NETO, 2006. While teaching quantum mechanics, we emphasized its predictive and essentially probabilistic nature, based on Niels Bohr’s complementarity interpretation (BOHR, 1958. In this context, we have discussed the possibility of predicting measurement results in well-defined experimental contexts, even for individual events. Interviews with students reveal that they have used quantum mechanical ideas, suggesting their meaningful learning of the essentially probabilistic predictions of quantum mechanics.

  15. Isobolographic analysis of the mechanisms of action of anticonvulsants from a combination effect.

    Science.gov (United States)

    Matsumura, Nobuko; Nakaki, Toshio

    2014-10-15

    The nature of the pharmacodynamic interactions of drugs is influenced by the drugs׳ mechanisms of action. It has been hypothesized that drugs with different mechanisms are likely to interact synergistically, whereas those with similar mechanisms seem to produce additive interactions. In this review, we describe an extensive investigation of the published literature on drug combinations of anticonvulsants, the nature of the interaction of which has been evaluated by type I and II isobolographic analyses and the subthreshold method. The molecular targets of antiepileptic drugs (AEDs) include Na(+) and Ca(2+) channels, GABA type-A receptor, and glutamate receptors such as NMDA and AMPA/kainate receptors. The results of this review indicate that the nature of interactions evaluated by type I isobolographic analyses but not by the two other methods seems to be consistent with the above hypothesis. Type I isobolographic analyses may be used not only for evaluating drug combinations but also for predicting the targets of new drugs. Copyright © 2014 Elsevier B.V. All rights reserved.

  16. Perceptual Organization of Visual Structure Requires a Flexible Learning Mechanism

    Science.gov (United States)

    Aslin, Richard N.

    2011-01-01

    Bhatt and Quinn (2011) provide a compelling and comprehensive review of empirical evidence that supports the operation of principles of perceptual organization in young infants. They also have provided a comprehensive list of experiences that could serve to trigger the learning of at least some of these principles of perceptual organization, and…

  17. Mapping learning and game mechanics for serious games analysis

    NARCIS (Netherlands)

    Arnab, S.; Lim, T.; Brandao Carvalho, M.; Bellotti, F.; De Freitas, S.; Louchart, S.; Suttie, N.; Berta, R.; De Gloria, A.

    2015-01-01

    Although there is a consensus on the instructional potential of Serious Games (SGs), there is still a lack of methodologies and tools not only for design but also to support analysis and assessment. Filling this gap is one of the main aims of the Games and Learning Alliance (http://www.galanoe.eu)

  18. Undergraduate Teaching and Learning Evaluation: Focus on the Mechanism

    Science.gov (United States)

    Dongmei, Zeng; Jiangbo, Chen

    2009-01-01

    It is obvious to all that the National Undergraduate Teaching and Learning Evaluation plan for higher education institutions launched in 2003 has promoted undergraduate teaching at universities and colleges. At the same time, however, the authors have also witnessed problems with the evaluation work itself, for example, unified evaluation…

  19. Statistical mechanics of learning: A variational approach for real data

    International Nuclear Information System (INIS)

    Malzahn, Doerthe; Opper, Manfred

    2002-01-01

    Using a variational technique, we generalize the statistical physics approach of learning from random examples to make it applicable to real data. We demonstrate the validity and relevance of our method by computing approximate estimators for generalization errors that are based on training data alone

  20. Mapping Learning and Game Mechanics for Serious Games Analysis

    Science.gov (United States)

    Arnab, Sylvester; Lim, Theodore; Carvalho, Maira B.; Bellotti, Francesco; de Freitas, Sara; Louchart, Sandy; Suttie, Neil; Berta, Riccardo; De Gloria, Alessandro

    2015-01-01

    Although there is a consensus on the instructional potential of Serious Games (SGs), there is still a lack of methodologies and tools not only for design but also to support analysis and assessment. Filling this gap is one of the main aims of the Games and Learning Alliance (http://www.galanoe.eu) European Network of Excellence on Serious Games,…

  1. E-Learning Optimization: The Relative and Combined Effects of Mental Practice and Modeling on Enhanced Podcast-Based Learning--A Randomized Controlled Trial

    Science.gov (United States)

    Alam, Fahad; Boet, Sylvain; Piquette, Dominique; Lai, Anita; Perkes, Christopher P.; LeBlanc, Vicki R.

    2016-01-01

    Enhanced podcasts increase learning, but evidence is lacking on how they should be designed to optimize their effectiveness. This study assessed the impact two learning instructional design methods (mental practice and modeling), either on their own or in combination, for teaching complex cognitive medical content when incorporated into enhanced…

  2. Using Optimal Combination of Teaching-Learning Methods (Open Book Assignment and Group Tutorials) as Revision Exercises to Improve Learning Outcome in Low Achievers in Biochemistry

    Science.gov (United States)

    Rajappa, Medha; Bobby, Zachariah; Nandeesha, H.; Suryapriya, R.; Ragul, Anithasri; Yuvaraj, B.; Revathy, G.; Priyadarssini, M.

    2016-01-01

    Graduate medical students of India are taught Biochemistry by didactic lectures and they hardly get any opportunity to clarify their doubts and reinforce the concepts which they learn in these lectures. We used a combination of teaching-learning (T-L) methods (open book assignment followed by group tutorials) to study their efficacy in improving…

  3. QSAR modelling using combined simple competitive learning networks and RBF neural networks.

    Science.gov (United States)

    Sheikhpour, R; Sarram, M A; Rezaeian, M; Sheikhpour, E

    2018-04-01

    The aim of this study was to propose a QSAR modelling approach based on the combination of simple competitive learning (SCL) networks with radial basis function (RBF) neural networks for predicting the biological activity of chemical compounds. The proposed QSAR method consisted of two phases. In the first phase, an SCL network was applied to determine the centres of an RBF neural network. In the second phase, the RBF neural network was used to predict the biological activity of various phenols and Rho kinase (ROCK) inhibitors. The predictive ability of the proposed QSAR models was evaluated and compared with other QSAR models using external validation. The results of this study showed that the proposed QSAR modelling approach leads to better performances than other models in predicting the biological activity of chemical compounds. This indicated the efficiency of simple competitive learning networks in determining the centres of RBF neural networks.

  4. Cooperative learning combined with short periods of lecturing: A good alternative in teaching biochemistry.

    Science.gov (United States)

    Fernández-Santander, Ana

    2008-01-01

    The informal activities of cooperative learning and short periods of lecturing has been combined and used in the university teaching of biochemistry as part of the first year course of Optics and Optometry in the academic years 2004-2005 and 2005-2006. The lessons were previously elaborated by the teacher and included all that is necessary to understand the topic (text, figures, graphics, diagrams, pictures, etc.). Additionally, a questionnaire was prepared for every chapter. All lessons contained three parts: objectives, approach and development, and the assessment of the topic. Team work, responsibility, and communication skills were some of the abilities developed with this new methodology. Students worked collaboratively in small groups of two or three following the teacher's instructions with short periods of lecturing that clarified misunderstood concepts. Homework was minimized. On comparing this combined methodology with the traditional one (only lecture), students were found to exhibit a higher satisfaction with the new method. They were more involved in the learning process and had a better attitude toward the subject. The use of this new methodology showed a significant increase in the mean score of the students' academic results. The rate of students who failed the subject was significantly inferior in comparison with those who failed in the previous years when only lecturing was applied. This combined methodology helped the teacher to observe the apprenticeship process of students better and to act as a facilitator in the process of building students' knowledge. Copyright © 2008 International Union of Biochemistry and Molecular Biology, Inc.

  5. Learning quantum field theory from elementary quantum mechanics

    International Nuclear Information System (INIS)

    Gosdzinsky, P.; Tarrach, R.

    1991-01-01

    The study of the Dirac delta potentials in more than one dimension allows the introduction within the framework of elementary quantum mechanics of many of the basic concepts of modern quantum field theory: regularization, renormalization group, asymptotic freedom, dimensional transmutation, triviality, etc. It is also interesting, by itself, as a nonstandard quantum mechanical problem

  6. Reliability of mechanical components subjected to combined alternating and mean stresses with a nonconstant stress ratio

    International Nuclear Information System (INIS)

    Kececioglu, D.; Lamarre, G.B.

    1979-01-01

    The reliability of reactor mechanical components and structural members, submitted to external loads which induce alternating bending stresses and mean shear stresses at the critical section where failure has a high probability of occurring, is predicted assuming that the ratio of the distributed alternating stress to the mean stress is also distributed and yields a bivariate failure-governing, combined alternating and mean, stress distribution. A computer programmed methodology is developed to calculate the reliability under these conditions given the associated distributional Goodman diagram for a reactor component or structural member. (orig.)

  7. Combining endoscopes with PIV and digital holography for the study of vessel model mechanics

    International Nuclear Information System (INIS)

    Arévalo, Laura; Palero, Virginia; Andrés, Nieves; Arroyo, M P; Lobera, Julia

    2015-01-01

    In this work traditional fluid and solid mechanics measurement techniques have been combined with endoscopes for the study of blood vessel models’ mechanical properties. Endoscopes have been used as the imaging part of a high-speed PIV system to obtain the velocity field in a vessel model immersed in a container with a refractive index-matching liquid. In this way, we take advantage of the fact that the endoscope tip can be immersed in liquid. Endoscopes have also been used as the imaging and illuminating part of a digital holographic set-up for wall deformation measurement. The novelty of this work is that only one endoscope was used for illuminating and observing the vessel model, using the endoscope’s own illuminating system as the illumination source. The performance of endoscopes in different vessel models has been tested. The results of flow velocity and wall deformation in the different blood vessel models are presented. (paper)

  8. TA Mentorship in Lecture significantly enhances students' learning in mechanics in large introductory physics classes

    Science.gov (United States)

    Cheng, K.; Caglar, Mehmet

    2011-10-01

    Lab is an important component of students' learning in a traditional lecture-lab setting of introductory physics courses. Using standard mechanics concepts and baseline surveys as well as independent classroom observations, the effects of TA mentorship in Lecture on students' learning of physics concepts and problem-solving skills among different student subgroups taught by other TAs and lecturers using different level of student interactive engagement in classes have been analyzed. Our data indicate that in lecture training of TA promotes lecture/lab synergism in improvement students' learning of mechanics in large introductory physics classes.

  9. Opioid Mechanism Involvement in the Synergism Produced by the Combination of Diclofenac and Caffeine in the Formalin Model

    OpenAIRE

    Flores-Ramos, Jos? Mar?a; D?az-Reval, M. Irene

    2013-01-01

    Analgesics can be administered in combination with caffeine for improved analgesic effectiveness in a process known as synergism. The mechanisms by which these combinations produce synergism are not yet fully understood. The aim of this study was to analyze whether the administration of diclofenac combined with caffeine produced antinociceptive synergism and whether opioid mechanisms played a role in this event. The formalin model was used to evaluate the antinociception produced by the oral ...

  10. Probabilistic Simulation of Combined Thermo-Mechanical Cyclic Fatigue in Composites

    Science.gov (United States)

    Chamis, Christos C.

    2011-01-01

    A methodology to compute probabilistically-combined thermo-mechanical fatigue life of polymer matrix laminated composites has been developed and is demonstrated. Matrix degradation effects caused by long-term environmental exposure and mechanical/thermal cyclic loads are accounted for in the simulation process. A unified time-temperature-stress-dependent multifactor-interaction relationship developed at NASA Glenn Research Center has been used to model the degradation/aging of material properties due to cyclic loads. The fast probability-integration method is used to compute probabilistic distribution of response. Sensitivities of fatigue life reliability to uncertainties in the primitive random variables (e.g., constituent properties, fiber volume ratio, void volume ratio, ply thickness, etc.) computed and their significance in the reliability-based design for maximum life is discussed. The effect of variation in the thermal cyclic loads on the fatigue reliability for a (0/+/-45/90)s graphite/epoxy laminate with a ply thickness of 0.127 mm, with respect to impending failure modes has been studied. The results show that, at low mechanical-cyclic loads and low thermal-cyclic amplitudes, fatigue life for 0.999 reliability is most sensitive to matrix compressive strength, matrix modulus, thermal expansion coefficient, and ply thickness. Whereas at high mechanical-cyclic loads and high thermal-cyclic amplitudes, fatigue life at 0.999 reliability is more sensitive to the shear strength of matrix, longitudinal fiber modulus, matrix modulus, and ply thickness.

  11. Quinolinic Acid, an Endogenous Molecule Combining Excitotoxicity, Oxidative Stress and Other Toxic Mechanisms

    Directory of Open Access Journals (Sweden)

    Verónica Pérez-De La Cruz

    2012-01-01

    Full Text Available Quinolinic acid (QUIN, an endogenous metabolite of the kynurenine pathway, is involved in several neurological disorders, including Huntington's disease, Alzheimer's disease, schizophrenia, HIV associated dementia (HAD etc. QUIN toxicity involves several mechanisms which trigger various metabolic pathways and transcription factors. The primary mechanism exerted by this excitotoxin in the central nervous system (CNS has been largely related with the overactivation of N-methyl-D-aspartate receptors and increased cytosolic Ca 2+ concentrations, followed by mitochondrial dysfunction, cytochrome c release, ATP exhaustion, free radical formation and oxidative damage. As a result, this toxic pattern is responsible for selective loss of middle size striatal spiny GABAergic neurons and motor alterations in lesioned animals. This toxin has recently gained attention in biomedical research as, in addition to its proven excitotoxic profile, a considerable amount of evidence suggests that oxidative stress and energetic disturbances are major constituents of its toxic pattern in the CNS. Hence, this profile has changed our perception of how QUIN-related disorders combine different toxic mechanisms resulting in brain damage. This review will focus on the description and integration of recent evidence supporting old and suggesting new mechanisms to explain QUIN toxicity.

  12. Development of a web-based learning medium on mechanism of labour for nursing students.

    Science.gov (United States)

    Gerdprasert, Sailom; Pruksacheva, Tassanee; Panijpan, Bhinyo; Ruenwongsa, Pintip

    2010-07-01

    This study aimed to develop a web-based learning media on the process and mechanism of labour for the third-year university nursing and midwifery students. This media was developed based on integrating principles of the mechanism of labour with the 5Es inquiry cycle and interactive features of information technology. In this study, the web-based learning unit was used to supplement the conventional lecture as in the traditional teaching. Students' achievements were assessed by using the pre- and post-test on factual knowledge and semi-structured interviews on attitude to the unit. Supplementation with this learning unit made learning significantly more effective than the traditional lecture by itself. The students also showed positive attitude toward the learning unit. Copyright 2009 Elsevier Ltd. All rights reserved.

  13. Unpacking "Active Learning": A Combination of Flipped Classroom and Collaboration Support Is More Effective but Collaboration Support Alone Is Not

    Science.gov (United States)

    Rau, Martina A.; Kennedy, Kristopher; Oxtoby, Lucas; Bollom, Mark; Moore, John W.

    2017-01-01

    Much evidence shows that instruction that actively engages students with learning materials is more effective than traditional, lecture-centric instruction. These "active learning" models comprise an extremely heterogeneous set of instructional methods: they often include collaborative activities, flipped classrooms, or a combination of…

  14. Statistical-Mechanical Analysis of Pre-training and Fine Tuning in Deep Learning

    Science.gov (United States)

    Ohzeki, Masayuki

    2015-03-01

    In this paper, we present a statistical-mechanical analysis of deep learning. We elucidate some of the essential components of deep learning — pre-training by unsupervised learning and fine tuning by supervised learning. We formulate the extraction of features from the training data as a margin criterion in a high-dimensional feature-vector space. The self-organized classifier is then supplied with small amounts of labelled data, as in deep learning. Although we employ a simple single-layer perceptron model, rather than directly analyzing a multi-layer neural network, we find a nontrivial phase transition that is dependent on the number of unlabelled data in the generalization error of the resultant classifier. In this sense, we evaluate the efficacy of the unsupervised learning component of deep learning. The analysis is performed by the replica method, which is a sophisticated tool in statistical mechanics. We validate our result in the manner of deep learning, using a simple iterative algorithm to learn the weight vector on the basis of belief propagation.

  15. Possible Peroxo State of the Dicopper Site of Particulate Methane Monooxygenase from Combined Quantum Mechanics and Molecular Mechanics Calculations.

    Science.gov (United States)

    Itoyama, Shuhei; Doitomi, Kazuki; Kamachi, Takashi; Shiota, Yoshihito; Yoshizawa, Kazunari

    2016-03-21

    Enzymatic methane hydroxylation is proposed to efficiently occur at the dinuclear copper site of particulate methane monooxygenase (pMMO), which is an integral membrane metalloenzyme in methanotrophic bacteria. The resting state and a possible peroxo state of the dicopper active site of pMMO are discussed by using combined quantum mechanics and molecular mechanics calculations on the basis of reported X-ray crystal structures of the resting state of pMMO by Rosenzweig and co-workers. The dicopper site has a unique structure, in which one copper is coordinated by two histidine imidazoles and another is chelated by a histidine imidazole and primary amine of an N-terminal histidine. The resting state of the dicopper site is assignable to the mixed-valent Cu(I)Cu(II) state from a computed Cu-Cu distance of 2.62 Å from calculations at the B3LYP-D/TZVP level of theory. A μ-η(2):η(2)-peroxo-Cu(II)2 structure similar to those of hemocyanin and tyrosinase is reasonably obtained by using the resting state structure and dioxygen. Computed Cu-Cu and O-O distances are 3.63 and 1.46 Å, respectively, in the open-shell singlet state. Structural features of the dicopper peroxo species of pMMO are compared with those of hemocyanin and tyrosinase and synthetic dicopper model compounds. Optical features of the μ-η(2):η(2)-peroxo-Cu(II)2 state are calculated and analyzed with TD-DFT calculations.

  16. A combination of HARMONIE short time direct normal irradiance forecasts and machine learning: The #hashtdim procedure

    Science.gov (United States)

    Gastón, Martín; Fernández-Peruchena, Carlos; Körnich, Heiner; Landelius, Tomas

    2017-06-01

    The present work describes the first approach of a new procedure to forecast Direct Normal Irradiance (DNI): the #hashtdim that treats to combine ground information and Numerical Weather Predictions. The system is centered in generate predictions for the very short time. It combines the outputs from the Numerical Weather Prediction Model HARMONIE with an adaptive methodology based on Machine Learning. The DNI predictions are generated with 15-minute and hourly temporal resolutions and presents 3-hourly updates. Each update offers forecasts to the next 12 hours, the first nine hours are generated with 15-minute temporal resolution meanwhile the last three hours present hourly temporal resolution. The system is proved over a Spanish emplacement with BSRN operative station in south of Spain (PSA station). The #hashtdim has been implemented in the framework of the Direct Normal Irradiance Nowcasting methods for optimized operation of concentrating solar technologies (DNICast) project, under the European Union's Seventh Programme for research, technological development and demonstration framework.

  17. Taste aversion learning produced by combined treatment with subthreshold radiation and lithium chloride

    International Nuclear Information System (INIS)

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

    1987-01-01

    These experiments were designed to determine whether treatment with two subthreshold doses of radiation or lithium chloride, either alone or in combination, could lead to taste aversion learning. The first experiment determined the thresholds for a radiation-induced taste aversion at 15-20 rad and for lithium chloride at 0.30-0.45 mEq/kg. In the second experiment it was shown that exposing rats to two doses of 15 rad separated by up to 3 hr produced a taste aversion. Treatment with two injections of lithium chloride (0.30 mEq/kg) did not produce a significant reduction in preference. Combined treatment with radiation and lithium chloride did produce a taste aversion when the two treatments were administered within 1 hr of each other. The results are discussed in terms of the implications of these findings for understanding the nature of the unconditioned stimuli leading to the acquisition of a conditioned taste aversion

  18. Automatic plankton image classification combining multiple view features via multiple kernel learning.

    Science.gov (United States)

    Zheng, Haiyong; Wang, Ruchen; Yu, Zhibin; Wang, Nan; Gu, Zhaorui; Zheng, Bing

    2017-12-28

    Plankton, including phytoplankton and zooplankton, are the main source of food for organisms in the ocean and form the base of marine food chain. As the fundamental components of marine ecosystems, plankton is very sensitive to environment changes, and the study of plankton abundance and distribution is crucial, in order to understand environment changes and protect marine ecosystems. This study was carried out to develop an extensive applicable plankton classification system with high accuracy for the increasing number of various imaging devices. Literature shows that most plankton image classification systems were limited to only one specific imaging device and a relatively narrow taxonomic scope. The real practical system for automatic plankton classification is even non-existent and this study is partly to fill this gap. Inspired by the analysis of literature and development of technology, we focused on the requirements of practical application and proposed an automatic system for plankton image classification combining multiple view features via multiple kernel learning (MKL). For one thing, in order to describe the biomorphic characteristics of plankton more completely and comprehensively, we combined general features with robust features, especially by adding features like Inner-Distance Shape Context for morphological representation. For another, we divided all the features into different types from multiple views and feed them to multiple classifiers instead of only one by combining different kernel matrices computed from different types of features optimally via multiple kernel learning. Moreover, we also applied feature selection method to choose the optimal feature subsets from redundant features for satisfying different datasets from different imaging devices. We implemented our proposed classification system on three different datasets across more than 20 categories from phytoplankton to zooplankton. The experimental results validated that our system

  19. Mechanisms of P-Glycoprotein Modulation by Semen Strychni Combined with Radix Paeoniae Alba

    Directory of Open Access Journals (Sweden)

    Li-Li Liu

    2017-01-01

    Full Text Available Semen Strychni has been extensively used as a Chinese herb, but its therapeutic window is narrowed by the strong toxicity of the compound, which limits its effectiveness. Radix Paeoniae Alba has been reported to reduce the toxic effects and increase the therapeutic effects of Semen Strychni, but the underlying mechanism remains unknown. This research aimed to explore the mechanism through which P-glycoprotein (P-gp is modulated by Semen Strychni combined with Radix Paeoniae Alba in vitro. An MTT assay was used to study cytotoxicity in an MDCK-MDR1 cell model. Rh123 efflux and accumulation were measured to assess P-gp function. The expression levels of MDR1 mRNA and P-gp protein in MDCK-MDR1 cells were investigated. A P-gp ATPase activity assay kit was applied to detect the effect on P-gp ATPase activity. Semen Strychni combined with Radix Paeoniae Alba could induce P-gp-mediated drug transport by inhibiting brucine and strychnine transport in MDCK-MDR1 cells, enhancing the P-gp efflux function, upregulating the P-gp expression and MDR1 mRNA levels, and stimulating P-gp ATPase activity.

  20. Simulation of Semi-Solid Material Mechanical Behavior Using a Combined Discrete/Finite Element Method

    Science.gov (United States)

    Sistaninia, M.; Phillion, A. B.; Drezet, J.-M.; Rappaz, M.

    2011-01-01

    As a necessary step toward the quantitative prediction of hot tearing defects, a three-dimensional stress-strain simulation based on a combined finite element (FE)/discrete element method (DEM) has been developed that is capable of predicting the mechanical behavior of semisolid metallic alloys during solidification. The solidification model used for generating the initial solid-liquid structure is based on a Voronoi tessellation of randomly distributed nucleation centers and a solute diffusion model for each element of this tessellation. At a given fraction of solid, the deformation is then simulated with the solid grains being modeled using an elastoviscoplastic constitutive law, whereas the remaining liquid layers at grain boundaries are approximated by flexible connectors, each consisting of a spring element and a damper element acting in parallel. The model predictions have been validated against Al-Cu alloy experimental data from the literature. The results show that a combined FE/DEM approach is able to express the overall mechanical behavior of semisolid alloys at the macroscale based on the morphology of the grain structure. For the first time, the localization of strain in the intergranular regions is taken into account. Thus, this approach constitutes an indispensible step towards the development of a comprehensive model of hot tearing.

  1. Active Learning in Fluid Mechanics: Youtube Tube Flow and Puzzling Fluids Questions

    Science.gov (United States)

    Hrenya, Christine M.

    2011-01-01

    Active-learning exercises appropriate for a course in undergraduate fluid mechanics are presented. The first exercise involves an experiment in gravity-driven tube flow, with small groups of students partaking in a contest to predict the experimental flow rates using the mechanical energy balance. The second exercise takes the form of an…

  2. Mechanism for Promoting Motivation, Confidence, and Autonomy through Synchronic Communication Sessions in Virtual Learning Environments

    Science.gov (United States)

    Valencia, Jorge Andrick Parra; Dallos, Adriana Rocío Lizcano; Ballesteros, Eliécer Pineda

    2017-01-01

    This study presents a mechanism which explains the effect of synchronous communication on students' perception of the training process in virtual learning methodology used in a postgraduate programme at the University of Santander. We use System Dynamics to design a mechanism that integrates motivation, confidence, trust, and autonomy in students.…

  3. Risks and chances of combined forestry and biomass projects under the Clean Development Mechanism

    Energy Technology Data Exchange (ETDEWEB)

    Dutschke, Michael; Kapp, Gerald; Lehmann, Anna; Schaefer, Volkmar (Hamburg Inst. International Economics (Germany))

    2006-06-15

    The Clean Development Mechanism (CDM) aims at reducing greenhouse gas (GHG) emissions, while at the same time taking up CO{sub 2} from the atmosphere in vegetation by means of afforestation and reforestation. In spite of these options being complementary, rules and modalities for both project classes are being treated separately in the relevant decisions by the Conference of the Parties to the UN Framework Convention on Climate Change. The present study reviews the state of bioenergy use in developing countries, modalities and procedures under the CDM, and the potential for transaction cost reduction in climate mitigation projects. There are four potential types of combinations in the matrix between small-scale - large-scale / afforestation and reforestation - bioenergy activities. We develop criteria for assessing sustainable development benefits and present an example project for each of the potential project types. We find that the individual risks of single-category projects do not increase when combining project categories and that each combination holds potential for integrated sustainability benefits. Risks for local livelihoods do increase with project size, but a transparent, participatory planning phase is able to counterbalance smallholders' lack of negotiation power. Further research will have to develop concrete project examples and blueprints with approved CDM methodologies, thereby decreasing transaction costs and risk for all potential project partners. (au)

  4. Into the Weeds: A Critical Analysis of Game Mechanics and Learning Goals in Games for Learning

    Science.gov (United States)

    Horstman, Theresa

    2013-01-01

    In the broadest scope, the purpose of this research is to expose the range and complexity of how educational games support learning. In a more narrowed scope, the purpose is to develop a method to help identify the qualities of educational video games that support learning. This is accomplished by analyzing the design of the game and the…

  5. Predicting protein complexes using a supervised learning method combined with local structural information.

    Science.gov (United States)

    Dong, Yadong; Sun, Yongqi; Qin, Chao

    2018-01-01

    The existing protein complex detection methods can be broadly divided into two categories: unsupervised and supervised learning methods. Most of the unsupervised learning methods assume that protein complexes are in dense regions of protein-protein interaction (PPI) networks even though many true complexes are not dense subgraphs. Supervised learning methods utilize the informative properties of known complexes; they often extract features from existing complexes and then use the features to train a classification model. The trained model is used to guide the search process for new complexes. However, insufficient extracted features, noise in the PPI data and the incompleteness of complex data make the classification model imprecise. Consequently, the classification model is not sufficient for guiding the detection of complexes. Therefore, we propose a new robust score function that combines the classification model with local structural information. Based on the score function, we provide a search method that works both forwards and backwards. The results from experiments on six benchmark PPI datasets and three protein complex datasets show that our approach can achieve better performance compared with the state-of-the-art supervised, semi-supervised and unsupervised methods for protein complex detection, occasionally significantly outperforming such methods.

  6. Mechanism of bacterial inactivation by (+-limonene and its potential use in food preservation combined processes.

    Directory of Open Access Journals (Sweden)

    Laura Espina

    Full Text Available This work explores the bactericidal effect of (+-limonene, the major constituent of citrus fruits' essential oils, against E. coli. The degree of E. coli BJ4 inactivation achieved by (+-limonene was influenced by the pH of the treatment medium, being more bactericidal at pH 4.0 than at pH 7.0. Deletion of rpoS and exposure to a sub-lethal heat or an acid shock did not modify E. coli BJ4 resistance to (+-limonene. However, exposure to a sub-lethal cold shock decreased its resistance to (+-limonene. Although no sub-lethal injury was detected in the cell envelopes after exposure to (+-limonene by the selective-plating technique, the uptake of propidium iodide by inactivated E. coli BJ4 cells pointed out these structures as important targets in the mechanism of action. Attenuated Total Reflectance Infrared Microspectroscopy (ATR-IRMS allowed identification of altered E. coli BJ4 structures after (+-limonene treatments as a function of the treatment pH: β-sheet proteins at pH 4.0 and phosphodiester bonds at pH 7.0. The increased sensitivity to (+-limonene observed at pH 4.0 in an E. coli MC4100 lptD4213 mutant with an increased outer membrane permeability along with the identification of altered β-sheet proteins by ATR-IRMS indicated the importance of this structure in the mechanism of action of (+-limonene. The study of mechanism of inactivation by (+-limonene led to the design of a synergistic combined process with heat for the inactivation of the pathogen E. coli O157:H7 in fruit juices. These results show the potential of (+-limonene in food preservation, either acting alone or in combination with lethal heat treatments.

  7. Mechanism of Bacterial Inactivation by (+)-Limonene and Its Potential Use in Food Preservation Combined Processes

    Science.gov (United States)

    Espina, Laura; Gelaw, Tilahun K.; de Lamo-Castellví, Sílvia; Pagán, Rafael; García-Gonzalo, Diego

    2013-01-01

    This work explores the bactericidal effect of (+)-limonene, the major constituent of citrus fruits' essential oils, against E. coli. The degree of E. coli BJ4 inactivation achieved by (+)-limonene was influenced by the pH of the treatment medium, being more bactericidal at pH 4.0 than at pH 7.0. Deletion of rpoS and exposure to a sub-lethal heat or an acid shock did not modify E. coli BJ4 resistance to (+)-limonene. However, exposure to a sub-lethal cold shock decreased its resistance to (+)-limonene. Although no sub-lethal injury was detected in the cell envelopes after exposure to (+)-limonene by the selective-plating technique, the uptake of propidium iodide by inactivated E. coli BJ4 cells pointed out these structures as important targets in the mechanism of action. Attenuated Total Reflectance Infrared Microspectroscopy (ATR-IRMS) allowed identification of altered E. coli BJ4 structures after (+)-limonene treatments as a function of the treatment pH: β-sheet proteins at pH 4.0 and phosphodiester bonds at pH 7.0. The increased sensitivity to (+)-limonene observed at pH 4.0 in an E. coli MC4100 lptD4213 mutant with an increased outer membrane permeability along with the identification of altered β-sheet proteins by ATR-IRMS indicated the importance of this structure in the mechanism of action of (+)-limonene. The study of mechanism of inactivation by (+)-limonene led to the design of a synergistic combined process with heat for the inactivation of the pathogen E. coli O157:H7 in fruit juices. These results show the potential of (+)-limonene in food preservation, either acting alone or in combination with lethal heat treatments. PMID:23424676

  8. Recolonization of the oral cavity by Streptococcus mutans after a combined mechanical/chemical antisepsis protocol.

    Science.gov (United States)

    Farina, R; Squarzoni, M A; Calura, G; Trombelli, L

    2009-06-01

    The bacterial colonization of teeth by Streptococcus mutans (StrepM) represents a major risk factor for the development of dental caries. At present, no clinical studies have explored the effect of a combined mechanical-chemical antisepsis protocol in a periodontally-healthy population and the pattern of recolonization of StrepM in subjects whose StrepM infection was successfully eradicated. The present study was designed in order to 1) determine the salivary and plaque changes in StrepM content after a combined mechanical/chemical antisepsis protocol; and 2) evaluate the pattern of recolonization when StrepM was successfully eradicated from saliva and plaque. Thirty-five periodontally-healthy and caries-susceptible subjects successfully entered and concluded the study. At baseline, non-surgical periodontal therapy was performed according to the principles of full mouth disinfection. Adjunctive home-based rinsing with a 0.2% chlorhexidine mouthrinse was requested for the following week. StrepM concentration was assessed in saliva and plaque at the initial contact appointment, at baseline, and 1-week, 1-month, 3-month and 6-month follow-up. A significant effect of ''time'' on StrepM concentration in saliva and plaque was observed (P<0.000). In subjects with successful eradication of StrepM at 1 week (N=17 plaque samples), StrepM infection recurrence occurred within 3-6 months. The results of the present study demonstrated that 1) the application of the investigated mechanical/chemical antisepsis protocol can effectively reduce StrepM colonies in saliva and plaque of periodontally healthy subjects; and 2) in plaque samples, StrepM infection recurrence tends to occur within 3-6 months.

  9. Synergistic target combination prediction from curated signaling networks: Machine learning meets systems biology and pharmacology.

    Science.gov (United States)

    Chua, Huey Eng; Bhowmick, Sourav S; Tucker-Kellogg, Lisa

    2017-10-01

    Given a signaling network, the target combination prediction problem aims to predict efficacious and safe target combinations for combination therapy. State-of-the-art in silico methods use Monte Carlo simulated annealing (mcsa) to modify a candidate solution stochastically, and use the Metropolis criterion to accept or reject the proposed modifications. However, such stochastic modifications ignore the impact of the choice of targets and their activities on the combination's therapeutic effect and off-target effects, which directly affect the solution quality. In this paper, we present mascot, a method that addresses this limitation by leveraging two additional heuristic criteria to minimize off-target effects and achieve synergy for candidate modification. Specifically, off-target effects measure the unintended response of a signaling network to the target combination and is often associated with toxicity. Synergy occurs when a pair of targets exerts effects that are greater than the sum of their individual effects, and is generally a beneficial strategy for maximizing effect while minimizing toxicity. mascot leverages on a machine learning-based target prioritization method which prioritizes potential targets in a given disease-associated network to select more effective targets (better therapeutic effect and/or lower off-target effects); and on Loewe additivity theory from pharmacology which assesses the non-additive effects in a combination drug treatment to select synergistic target activities. Our experimental study on two disease-related signaling networks demonstrates the superiority of mascot in comparison to existing approaches. Copyright © 2017 Elsevier Inc. All rights reserved.

  10. Motion mechanics of non-adherent giant liposomes with a combined optical and atomic force microscope

    Science.gov (United States)

    Moreno-Flores, Susana; Ortíz, Rocío

    2017-11-01

    Herein we present an investigation of the motional dynamics of single mesoscopic bodies of biological relevance with an AFM-based macromanipulation tool and an optical microscope. Giant liposomes are prominent case examples as minimal cell models; studying their mechanics provides a means to address the influence of structural components in the mechanical behaviour of living cells. However, they also pose an experimental challenge due to their lightness, fragility, and high mobility. Their entrapment in wells in a fluid of lower density allows their study under conditions of constrained motion, which enables the synchronous measurement of nanoforces with motion tracking. The procedure enables to estimate sliding friction coefficients and masses of vesicles, and sheds light upon the region between the vesicle and the underlying substrate. The present study paves the way for the investigation of motion and deformation mechanics with one combined technique and a single type of experiment traditionally vetoed to objects that can move as well as deform. Such an approach can be directly applied to cells in suspension, adherent cells or cellular 3D-assemblies so as to assess substrate biocompatibility, monitor adhesion, detachment, motility as well as deformability.

  11. Combined Ultrasonic Elliptical Vibration and Chemical Mechanical Polishing of Monocrystalline Silicon

    Directory of Open Access Journals (Sweden)

    Liu Defu

    2016-01-01

    Full Text Available An ultrasonic elliptical vibration assisted chemical mechanical polishing(UEV-CMP is employed to achieve high material removal rate and high surface quality in the finishing of hard and brittle materials such as monocrystalline silicon, which combines the functions of conventional CMP and ultrasonic machining. In theultrasonic elliptical vibration aided chemical mechanical polishingexperimental setup developed by ourselves, the workpiece attached at the end of horn can vibrate simultaneously in both horizontal and vertical directions. Polishing experiments are carried out involving monocrystalline silicon to confirm the performance of the proposed UEV-CMP. The experimental results reveal that the ultrasonic elliptical vibration can increase significantly the material removal rate and reduce dramatically the surface roughness of monocrystalline silicon. It is found that the removal rate of monocrystalline silicon polished by UEV-CMP is increased by approximately 110% relative to that of conventional CMP because a passive layer on the monocrystalline silicon surface, formed by the chemical action of the polishing slurry, will be removed not only by the mechanical action of CMP but also by ultrasonic vibration action. It indicates that the high efficiency and high quality CMP of monocrystalline silicon can be performed with the proposed UEV-CMP technique.

  12. Dynamic Response and Failure Mechanism of Brittle Rocks Under Combined Compression-Shear Loading Experiments

    Science.gov (United States)

    Xu, Yuan; Dai, Feng

    2018-03-01

    A novel method is developed for characterizing the mechanical response and failure mechanism of brittle rocks under dynamic compression-shear loading: an inclined cylinder specimen using a modified split Hopkinson pressure bar (SHPB) system. With the specimen axis inclining to the loading direction of SHPB, a shear component can be introduced into the specimen. Both static and dynamic experiments are conducted on sandstone specimens. Given carefully pulse shaping, the dynamic equilibrium of the inclined specimens can be satisfied, and thus the quasi-static data reduction is employed. The normal and shear stress-strain relationships of specimens are subsequently established. The progressive failure process of the specimen illustrated via high-speed photographs manifests a mixed failure mode accommodating both the shear-dominated failure and the localized tensile damage. The elastic and shear moduli exhibit certain loading-path dependence under quasi-static loading but loading-path insensitivity under high loading rates. Loading rate dependence is evidently demonstrated through the failure characteristics involving fragmentation, compression and shear strength and failure surfaces based on Drucker-Prager criterion. Our proposed method is convenient and reliable to study the dynamic response and failure mechanism of rocks under combined compression-shear loading.

  13. Motion mechanics of non-adherent giant liposomes with a combined optical and atomic force microscope

    International Nuclear Information System (INIS)

    Moreno-Flores, Susana; Ortíz, Rocío

    2017-01-01

    Herein we present an investigation of the motional dynamics of single mesoscopic bodies of biological relevance with an AFM-based macromanipulation tool and an optical microscope. Giant liposomes are prominent case examples as minimal cell models; studying their mechanics provides a means to address the influence of structural components in the mechanical behaviour of living cells. However, they also pose an experimental challenge due to their lightness, fragility, and high mobility. Their entrapment in wells in a fluid of lower density allows their study under conditions of constrained motion, which enables the synchronous measurement of nanoforces with motion tracking. The procedure enables to estimate sliding friction coefficients and masses of vesicles, and sheds light upon the region between the vesicle and the underlying substrate. The present study paves the way for the investigation of motion and deformation mechanics with one combined technique and a single type of experiment traditionally vetoed to objects that can move as well as deform. Such an approach can be directly applied to cells in suspension, adherent cells or cellular 3D-assemblies so as to assess substrate biocompatibility, monitor adhesion, detachment, motility as well as deformability. (paper)

  14. Combining Graphic Arts, Hollywood and the Internet to Improve Distance Learning in Science and Math

    Science.gov (United States)

    Tso-Varela, S.; Friedberg, R.; Lipnick, D.

    We on the Navajo Reservation face the daunting problem of trying to educate a widely scattered student population over a landmass (25,000+ sq. miles) larger than all the New England states combined. Compounding this problem is the fact that English is a second language for many students and that many of our students lack basic foundation skills. One of the obvious answers is Distance Learning Programs. But, in the past Distance Learning Programs have been notably ineffective on the Navajo Reservation. An experimental Internet Astronomy that we taught last summer showed conclusively that we must specifically tailor our Distance Learning courses to a Navajo audience. As with many college level science courses, our experimental course was English intensive and there lies the crux of the problem. With the help of our colleague institutions, Los Alamos National Laboratory, University of California at Berkeley, University of New Mexico, Kennesaw State University, and New Mexico Highlands University, we undertook to replace 90% of the traditional verbiage with art, an idiom much accepted on the Navajo Reservation. We used the Walt Disney Studios as a model. Specifically, we studied the Pvt. Snafu cartoons used by the War Department in World War II. We tried to emulate their style and techniques. We developed our own cartoon characters, Astroboy, Professor Tso and Roxanne. We combined high quality graphic art, animation, cartooning, Navajo cultural elements, Internet hyperlinks and voiceovers to tell the story of Astronomy 101 Lab. In addition we have added remedial math resources and other helpful resources to our web site. We plan to test initial efforts in an experimental Internet course this summer.

  15. The Conceptual Mechanism for Viable Organizational Learning Based on Complex System Theory and the Viable System Model

    Science.gov (United States)

    Sung, Dia; You, Yeongmahn; Song, Ji Hoon

    2008-01-01

    The purpose of this research is to explore the possibility of viable learning organizations based on identifying viable organizational learning mechanisms. Two theoretical foundations, complex system theory and viable system theory, have been integrated to provide the rationale for building the sustainable organizational learning mechanism. The…

  16. Uncovering the neural mechanisms underlying learning from tests.

    Directory of Open Access Journals (Sweden)

    Xiaonan L Liu

    Full Text Available People learn better when re-study opportunities are replaced with tests. While researchers have begun to speculate on why testing is superior to study, few studies have directly examined the neural underpinnings of this effect. In this fMRI study, participants engaged in a study phase to learn arbitrary word pairs, followed by a cued recall test (recall second half of pair when cued with first word of pair, re-study of each pair, and finally another cycle of cued recall tests. Brain activation patterns during the first test (recall of the studied pairs predicts performance on the second test. Importantly, while subsequent memory analyses of encoding trials also predict later accuracy, the brain regions involved in predicting later memory success are more extensive for activity during retrieval (testing than during encoding (study. Those additional regions that predict subsequent memory based on their activation at test but not at encoding may be key to understanding the basis of the testing effect.

  17. Mechanism of red mud combined with Fenton's reagent in sewage sludge conditioning.

    Science.gov (United States)

    Zhang, Hao; Yang, Jiakuan; Yu, Wenbo; Luo, Sen; Peng, Li; Shen, Xingxing; Shi, Yafei; Zhang, Shinan; Song, Jian; Ye, Nan; Li, Ye; Yang, Changzhu; Liang, Sha

    2014-08-01

    Red mud was evaluated as an alternative skeleton builder combined with Fenton's reagent in sewage sludge conditioning. The results show that red mud combined with Fenton's reagent showed good conditioning capability with the pH of the filtrate close to neutrality, indicating that red mud acted as a neutralizer as well as a skeleton builder when jointly used with Fenton's reagent. Through response surface methodology (RSM), the optimal dosages of Fe(2+), H2O2 and red mud were proposed as 31.9, 33.7 and 275.1 mg/g DS (dry solids), respectively. The mechanism of the composite conditioner could be illuminated as follows: (1) extracellular polymeric substances (EPS), including loosely bound EPS and tightly bound EPS, were degraded into dissolved organics, e.g., proteins and polysaccharides; (2) bound water was released and converted into free water due to the degradation of EPS; and (3) morphology of the conditioned sludge exhibited a porous structure in contrast with the compact structure of raw sludge, and the addition of red mud formed new mineral phases and a rigid lattice structure in sludge, allowing the outflow of free water. Thus, sludge dewatering performance was effectively improved. The economic assessment for a wastewater treatment plant of 370,000 equivalent inhabitants confirms that using red mud conditioning, combined with Fenton's reagent, leads to a saving of approximately 411,000 USD/y or 50.8 USD/t DS comparing with using lime and ordinary Portland cement combined with Fenton's reagent, and approximately 612,000 USD/y or 75.5 USD/t DS comparing with the traditional treatment. Copyright © 2014 Elsevier Ltd. All rights reserved.

  18. Immuno-pharmacodynamics for evaluating mechanism of action and developing immunotherapy combinations.

    Science.gov (United States)

    Parchment, Ralph E; Voth, Andrea Regier; Doroshow, James H; Berzofsky, Jay A

    2016-08-01

    Immunotherapy has become a major modality of cancer treatment, with multiple new classes of immunotherapeutics recently entering the clinic and obtaining market approval from regulatory agencies. While the promise of these therapies is great, so is the number of possible combinations not only with each other but also with small molecule therapeutics. Furthermore, the observation of unusual dose-response relationships suggests a critical dependency of drug effectiveness on the dosage regimen (dose and schedule). Clinical pharmacodynamic (PD) biomarkers will be useful endpoints for confirming drug mechanism of action, evaluating combination therapies for synergy or antagonism, and identifying optimal dosage regimens. In contrast to conventional PD in which drug action occurs entirely within a single target cell (ie, is self-contained within the malignant cell), immunotherapy involves a complex mechanism of action with sequential steps that propagate through multiple cell types, both normal and malignant. Its intercellular pharmacology begins with molecular target engagement either on an immune effector cell or a malignant cell, followed by stimulatory biochemical and biological signals in immune effector cells, and then finally ends with activation of cell death mechanisms in malignant cells lying within a certain distance from the activated effector cells (immune cell-tumor cell proximity). Evaluating such "trans-cellular pharmacology," in which different steps of drug action are distributed across multiple cell types, requires novel microscopy and image analysis tools capable of quantifying PD-biomarker responses, mapping the responses onto the cellular geography of the tumor using phenotypic biomarkers to identify specific cell types, and finally analyzing the spatial relationships between biomarkers in the context of each cell's biological role. We have termed this form of nearest neighbor image analysis of drug action "proximity PD microscopy," to indicate the

  19. Combination study of operation characteristics and heat transfer mechanism for pulsating heat pipe

    International Nuclear Information System (INIS)

    Cui, Xiaoyu; Zhu, Yue; Li, Zhihua; Shun, Shende

    2014-01-01

    Pulsating heat pipe (PHP) is becoming a promising heat transfer device for the application like electronics cooling. However, due to its complicated operation mechanism, the heat transfer properties of the PHP still have not been fully understood. This study experimentally investigated on a closed-loop PHP charged with four types of working fluids, deionized water, methanol, ethanol and acetone. Combined with the visualization experimental results from the open literature, the operation characteristics and the corresponding heat transfer mechanisms for different heat inputs (5 W up to 100 W) and different filling ratios (20% up to 95%) have been presented and elaborated. The results show that heat-transfer mechanism changed with the transition of operation patterns; before valid oscillation started, the thermal resistance was not like that described in the open literature where it decreased almost linearly, but would rather slowdown descending or even change into rise first before further decreasing (i.e. an inflection point existed); when the heat input further increased to certain level, e.g. 65 W or above, there presented a limit of heat-transfer performance which was independent of the types of working fluids and the filling ratios, but may be related to the structure, the material, the size and the inclination of the PHP. - Highlights: •The thermal mechanisms altered accordingly with the operation features in the PHP. •Unlike conventional heat pipes, continuous temperature soaring would not happen in the PHP. •Before the oscillation start-up, there existed a heat-transfer limit for the relatively stagnated flow in the PHP. •A limit of thermal performance existed in the PHP at relatively high heat inputs

  20. Combining D-cycloserine with appetitive extinction learning modulates amygdala activity during recall.

    Science.gov (United States)

    Ebrahimi, Claudia; Koch, Stefan P; Friedel, Eva; Crespo, Ilsoray; Fydrich, Thomas; Ströhle, Andreas; Heinz, Andreas; Schlagenhauf, Florian

    2017-07-01

    Appetitive Pavlovian conditioning plays a crucial role in the pathogenesis of drug addiction and conditioned reward cues can trigger craving and relapse even after long phases of abstinence. Promising preclinical work showed that the NMDA-receptor partial agonist D-cycloserine (DCS) facilitates Pavlovian extinction learning of fear and drug cues. Furthermore, DCS-augmented exposure therapy seems to be beneficial in various anxiety disorders, while the supposed working mechanism of DCS during human appetitive or aversive extinction learning is still not confirmed. To test the hypothesis that DCS administration before extinction training improves extinction learning, healthy adults (n=32) underwent conditioning, extinction, and extinction recall on three successive days in a randomized, double-blind, placebo-controlled fMRI design. Monetary wins and losses served as unconditioned stimuli during conditioning to probe appetitive and aversive learning. An oral dose of 50mg of DCS or placebo was administered 1h before extinction training and DCS effects during extinction recall were evaluated on a behavioral and neuronal level. We found attenuated amygdala activation in the DCS compared to the placebo group during recall of the extinguished appetitive cue, along with evidence for enhanced functional amygdala-vmPFC coupling in the DCS group. While the absence of additional physiological measures of conditioned responses during recall in this study prevent the evaluation of a behavioral DCS effect, our neuronal findings are in accordance with recent theories linking successful extinction recall in humans to modulatory top-down influences from the vmPFC that inhibit amygdala activation. Our results should encourage further translational studies concerning the usefulness of DCS to target maladaptive Pavlovian reward associations. Copyright © 2017 Elsevier Inc. All rights reserved.

  1. How are learning strategies reflected in the eyes? Combining results from self-reports and eye-tracking.

    Science.gov (United States)

    Catrysse, Leen; Gijbels, David; Donche, Vincent; De Maeyer, Sven; Lesterhuis, Marije; Van den Bossche, Piet

    2018-03-01

    Up until now, empirical studies in the Student Approaches to Learning field have mainly been focused on the use of self-report instruments, such as interviews and questionnaires, to uncover differences in students' general preferences towards learning strategies, but have focused less on the use of task-specific and online measures. This study aimed at extending current research on students' learning strategies by combining general and task-specific measurements of students' learning strategies using both offline and online measures. We want to clarify how students process learning contents and to what extent this is related to their self-report of learning strategies. Twenty students with different generic learning profiles (according to self-report questionnaires) read an expository text, while their eye movements were registered to answer questions on the content afterwards. Eye-tracking data were analysed with generalized linear mixed-effects models. The results indicate that students with an all-high profile, combining both deep and surface learning strategies, spend more time on rereading the text than students with an all-low profile, scoring low on both learning strategies. This study showed that we can use eye-tracking to distinguish very strategic students, characterized using cognitive processing and regulation strategies, from low strategic students, characterized by a lack of cognitive and regulation strategies. These students processed the expository text according to how they self-reported. © 2017 The British Psychological Society.

  2. Android Used in The Learning Innovation Atwood Machines on Lagrange Mechanics Methods

    Directory of Open Access Journals (Sweden)

    Shabrina Shabrina

    2017-12-01

    Full Text Available Android is one of the smartphone operating system platforms that is now widely developed in learning media. Android allows the learning process to be more flexible and not oriented to be teacher center, but it allows to be student center. The Atwood machines is an experimental tool that is often used to observe mechanical laws in constantly accelerated motion which can also be described by the Lagrange mechanics methods. As an innovative and alternative learning activity, Atwood Android-based learning apps are running for two experimental variations, which are variations in load in cart and load masses that are hung. The experiment of load-carrier mass variation found that the larger load mass in the cart, the smaller the acceleration experienced by the system. Meanwhile, the experiment on the variation of the loaded mass found that the larger the loaded mass, the greater the acceleration experienced by the system.

  3. Inner-Learning Mechanism Based Control Scheme for Manipulator with Multitasking and Changing Load

    Directory of Open Access Journals (Sweden)

    Fangzheng Xue

    2014-05-01

    Full Text Available With the rapid development of robot technology and its application, manipulators may face complex tasks and dynamic environments in the coming future, which leads to two challenges of control: multitasking and changing load. In this paper, a novel multicontroller strategy is presented to meet such challenges. The presented controller is composed of three parts: subcontrollers, inner-learning mechanism, and switching rules. Each subcontroller is designed with self-learning skills to fit the changing load under a special task. When a new task comes, switching rule reselects the most suitable subcontroller as the working controller to handle current task instead of the older one. Inner-learning mechanism makes the subcontrollers learn from the working controller when load changes so that the switching action causes smaller tracking error than the traditional switch controller. The results of the simulation experiments on two-degree manipulator show the proposed method effect.

  4. Efficient learning mechanisms hold in the social domain and are implemented in the medial prefrontal cortex.

    Science.gov (United States)

    Seid-Fatemi, Azade; Tobler, Philippe N

    2015-05-01

    When we are learning to associate novel cues with outcomes, learning is more efficient if we take advantage of previously learned associations and thereby avoid redundant learning. The blocking effect represents this sort of efficiency mechanism and refers to the phenomenon in which a novel stimulus is blocked from learning when it is associated with a fully predicted outcome. Although there is sufficient evidence that this effect manifests itself when individuals learn about their own rewards, it remains unclear whether it also does when they learn about others' rewards. We employed behavioral and neuroimaging methods to address this question. We demonstrate that blocking does indeed occur in the social domain and it does so to a similar degree as observed in the individual domain. On the neural level, activations in the medial prefrontal cortex (mPFC) show a specific contribution to blocking and learning-related prediction errors in the social domain. These findings suggest that the efficiency principle that applies to reward learning in the individual domain also applies to that in the social domain, with the mPFC playing a central role in implementing it. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  5. Achieving effective learning effects in the blended course: a combined approach of online self-regulated learning and collaborative learning with initiation.

    Science.gov (United States)

    Tsai, Chia-Wen

    2011-09-01

    In many countries, undergraduates are required to take at least one introductory computer course to enhance their computer literacy and computing skills. However, the application software education in Taiwan can hardly be deemed as effective in developing students' practical computing skills. The author applied online self-regulated learning (SRL) and collaborative learning (CL) with initiation in a blended computing course and examined the effects of different combinations on enhancing students' computing skills. Four classes, comprising 221 students, participated in this study. The online SRL and CL with initiation (G1, n = 53), online CL with initiation (G2, n = 68), and online CL without initiation (G3, n = 68) were experimental groups, and the last class, receiving traditional lecture (G4, n = 32), was the control group. The results of this study show that students who received the intervention of online SRL and CL with initiation attained significantly best grades for practical computing skills, whereas those that received the traditional lectures had statistically poorest grades among the four classes. The implications for schools and educators who plan to provide online or blended learning for their students, particularly in computing courses, are also provided in this study.

  6. The mechanism of combination with hemocoagulase and pantoprazole in upper gastrointestinal bleeding

    Directory of Open Access Journals (Sweden)

    Ming-Ke Yan

    2017-03-01

    Full Text Available Objective: Through the combination with hemocoagulase and pantoprazole on gastrointestinal bleeding, to observe the changes of serum BUN (blood urea nitrogen, LPO (LPO, NO (nitric oxide, TNF-α(TNF alpha, hs-CRP (high sensitivity C reactive protein and cortisol levels, and to explore the mechanism of combination. Methods: 110 cases of upper gastrointestinal bleeding in our hospital from January 2015 to September 2016 were selected and divided into the control group and the observation group, 55 cases for each group. Patients were treated with bed rest, fasting, intravenous nutrition, oxygen, and according to the individual situation actively supplement blood capacity, and the control group were treated with 40 mg intravenous pantoprazole treatment, 2 times/d; the patients in the observation group were treated with 2 kU hemocoagulase injection based on the treatment of control group, 2 times of intravenous injection per day, and all patients were treated for 3 d, and then the BUN, LPO, NO, TNF-α, hs-CRP and cortisol were detected. Results: (1 There were no significantly differences of the serum levels of BUN, LPO, and NO of the two groups before treatment (P>0.05. After treatment, the serum levels the two groups were significantly lower than before treatment, and LPO, BUN, and NO levels in the observation group were significantly better than the control group (P0.05. After treatment, the serum levels in the two groups were significantly lower than before treatment, and TNF-α, hs-CRP, and cortisol levels in the observation group were significantly better than the control group (P<0.05. Conclusions: The treatment of patients with combined use of hemocoagulase and pantoprazole on gastrointestinal bleeding, can significantly improve the serum levels of BUN, LPO, NO, TNF-α, hs-CRP and cortisol levels, and further illustrates the synergistic effect of the combination, also shows that the combination of two drugs for patients with upper

  7. Assessing regional lung mechanics by combining electrical impedance tomography and forced oscillation technique.

    Science.gov (United States)

    Ngo, Chuong; Spagnesi, Sarah; Munoz, Carlos; Lehmann, Sylvia; Vollmer, Thomas; Misgeld, Berno; Leonhardt, Steffen

    2017-08-29

    There is a lack of noninvasive pulmonary function tests which can assess regional information of the lungs. Electrical impedance tomography (EIT) is a radiation-free, non-invasive real-time imaging that provides regional information of ventilation volume regarding the measurement of electrical impedance distribution. Forced oscillation technique (FOT) is a pulmonary function test which is based on the measurement of respiratory mechanical impedance over a frequency range. In this article, we introduce a new measurement approach by combining FOT and EIT, named the oscillatory electrical impedance tomography (oEIT). Our oEIT measurement system consists of a valve-based FOT device, an EIT device, pressure and flow sensors, and a computer fusing the data streams. Measurements were performed on five healthy volunteers at the frequencies 3, 4, 5, 6, 7, 8, 10, 15, and 20 Hz. The measurements suggest that the combination of FOT and EIT is a promising approach. High frequency responses are visible in the derivative of the global impedance index ΔZeit(t,fos). $\\Delta {Z_{{\\text{eit}}}}(t,{f_{{\\text{os}}}}).$ The oEIT signals consist of three main components: forced oscillation, spontaneous breathing, and heart activity. The amplitude of the oscillation component decreases with increasing frequency. The band-pass filtered oEIT signal might be a new tool in regional lung function diagnostics, since local responses to high frequency perturbation could be distinguished between different lung regions.

  8. Collaborative Game-based Learning - Automatized Adaptation Mechanics for Game-based Collaborative Learning using Game Mastering Concepts

    OpenAIRE

    Wendel, Viktor Matthias

    2015-01-01

    Learning and playing represent two core aspects of the information and communication society nowadays. Both issues are subsumed in Digital Education Games, one major field of Serious Games. Serious Games combine concepts of gaming with a broad range of application fields: among others, educational sectors and training or health and sports, but also marketing, advertisement, political education, and other societally relevant areas such as climate, energy, and safety. This work focuses on colla...

  9. Bacterial radiosensitization by using radiation processing in combination with essential oil: Mechanism of action

    Energy Technology Data Exchange (ETDEWEB)

    Lacroix, Monique [Canadian Irradiation Center, Research Laboratory in Sciences Applied to Food, INRS-Institut Armand-Frappier, 531, Boulevard des Prairies, Laval, Quebec, H7V 1B7 (Canada)], E-mail: monique.lacroix@iaf.inrs.ca; Caillet, Stephane [Canadian Irradiation Center, Research Laboratory in Sciences Applied to Food, INRS-Institut Armand-Frappier, 531, Boulevard des Prairies, Laval, Quebec, H7V 1B7 (Canada); Shareck, Francois [INRS-Institut Armand-Frappier, 531, Boulevard des Prairies, Laval, Quebec, H7V 1B7 (Canada)

    2009-07-15

    Spice extracts under the form of essential oils were tested for their efficiency to increase the relative radiosensitivity of Listeria monocytogenes and Escherichia coli O157H7 in culture media. The two pathogens were treated by gamma-irradiation alone or in combination with oregano essential oil to evaluate their mechanism of action. The membrane murein composition, and the intracellular and extracellular concentration of ATP was determined. The bacterial strains were treated with two irradiation doses: 1.2 kGy to induce cell damage and 3.5 kGy to cause cell death for L. monocytogenes. A dose of 0.4 kGy to induce cell damages, 1.1 kGy to obtain viable but nonculturable (VBNC) state and 1.3 kGy to obtain a lethal dose was also applied on E. coli O157H7. Oregano essential oil was used at 0.020% and 0.025% (w/v), which is the minimum inhibitory concentration (MIC) for L. monocytogenes. For E. coli O157H7, a concentration of 0.006% and 0.025% (w/v) which is the minimum inhibitory concentration was applied. The use of essential oils in combination with irradiation has permitted an increase of the bacterial radiosensitization by more than 3.1 times. All treatments had also a significant effect (p{<=}0.05) on the murein composition, although some muropeptides did not seem to be affected by the treatment. Each treatment influenced differently the relative percentage and number of muropeptides. There was a significant (p{<=}0.05) correlation between the reduction of intracellular ATP and increase in extracellular ATP following treatment of the cells with oregano oil. The reduction of intracellular ATP was even more important when essential oil was combined with irradiation, but irradiation of L. monocytogenes alone induced a significant decrease (p{<=}0.05) of the internal ATP without affecting the external ATP.

  10. Bacterial radiosensitization by using radiation processing in combination with essential oil: Mechanism of action

    Science.gov (United States)

    Lacroix, Monique; Caillet, Stéphane; Shareck, Francois

    2009-07-01

    Spice extracts under the form of essential oils were tested for their efficiency to increase the relative radiosensitivity of Listeria monocytogenes and Escherichia coli O157H7 in culture media. The two pathogens were treated by gamma-irradiation alone or in combination with oregano essential oil to evaluate their mechanism of action. The membrane murein composition, and the intracellular and extracellular concentration of ATP was determined. The bacterial strains were treated with two irradiation doses: 1.2 kGy to induce cell damage and 3.5 kGy to cause cell death for L. monocytogenes. A dose of 0.4 kGy to induce cell damages, 1.1 kGy to obtain viable but nonculturable (VBNC) state and 1.3 kGy to obtain a lethal dose was also applied on E. coli O157H7. Oregano essential oil was used at 0.020% and 0.025% (w/v), which is the minimum inhibitory concentration (MIC) for L. monocytogenes. For E. coli O157H7, a concentration of 0.006% and 0.025% (w/v) which is the minimum inhibitory concentration was applied. The use of essential oils in combination with irradiation has permitted an increase of the bacterial radiosensitization by more than 3.1 times. All treatments had also a significant effect ( p⩽0.05) on the murein composition, although some muropeptides did not seem to be affected by the treatment. Each treatment influenced differently the relative percentage and number of muropeptides. There was a significant ( p⩽0.05) correlation between the reduction of intracellular ATP and increase in extracellular ATP following treatment of the cells with oregano oil. The reduction of intracellular ATP was even more important when essential oil was combined with irradiation, but irradiation of L. monocytogenes alone induced a significant decrease ( p⩽0.05) of the internal ATP without affecting the external ATP.

  11. Bacterial radiosensitization by using radiation processing in combination with essential oil: Mechanism of action

    International Nuclear Information System (INIS)

    Lacroix, Monique; Caillet, Stephane; Shareck, Francois

    2009-01-01

    Spice extracts under the form of essential oils were tested for their efficiency to increase the relative radiosensitivity of Listeria monocytogenes and Escherichia coli O157H7 in culture media. The two pathogens were treated by gamma-irradiation alone or in combination with oregano essential oil to evaluate their mechanism of action. The membrane murein composition, and the intracellular and extracellular concentration of ATP was determined. The bacterial strains were treated with two irradiation doses: 1.2 kGy to induce cell damage and 3.5 kGy to cause cell death for L. monocytogenes. A dose of 0.4 kGy to induce cell damages, 1.1 kGy to obtain viable but nonculturable (VBNC) state and 1.3 kGy to obtain a lethal dose was also applied on E. coli O157H7. Oregano essential oil was used at 0.020% and 0.025% (w/v), which is the minimum inhibitory concentration (MIC) for L. monocytogenes. For E. coli O157H7, a concentration of 0.006% and 0.025% (w/v) which is the minimum inhibitory concentration was applied. The use of essential oils in combination with irradiation has permitted an increase of the bacterial radiosensitization by more than 3.1 times. All treatments had also a significant effect (p≤0.05) on the murein composition, although some muropeptides did not seem to be affected by the treatment. Each treatment influenced differently the relative percentage and number of muropeptides. There was a significant (p≤0.05) correlation between the reduction of intracellular ATP and increase in extracellular ATP following treatment of the cells with oregano oil. The reduction of intracellular ATP was even more important when essential oil was combined with irradiation, but irradiation of L. monocytogenes alone induced a significant decrease (p≤0.05) of the internal ATP without affecting the external ATP.

  12. Dual mechanisms governing reward-driven perceptual learning [version 1; referees: 2 approved

    Directory of Open Access Journals (Sweden)

    Dongho Kim

    2015-09-01

    Full Text Available In this review, we explore how reward signals shape perceptual learning in animals and humans. Perceptual learning is the well-established phenomenon by which extensive practice elicits selective improvement in one’s perceptual discrimination of basic visual features, such as oriented lines or moving stimuli. While perceptual learning has long been thought to rely on ‘top-down’ processes, such as attention and decision-making, a wave of recent findings suggests that these higher-level processes are, in fact, not necessary.  Rather, these recent findings indicate that reward signals alone, in the absence of the contribution of higher-level cognitive processes, are sufficient to drive the benefits of perceptual learning. Here, we will review the literature tying reward signals to perceptual learning. Based on these findings, we propose dual underlying mechanisms that give rise to perceptual learning: one mechanism that operates ‘automatically’ and is tied directly to reward signals, and another mechanism that involves more ‘top-down’, goal-directed computations.

  13. Imitation Learning Based on an Intrinsic Motivation Mechanism for Efficient Coding

    Directory of Open Access Journals (Sweden)

    Jochen eTriesch

    2013-11-01

    Full Text Available A hypothesis regarding the development of imitation learning is presented that is rooted in intrinsic motivations. It is derived from a recently proposed form of intrinsically motivated learning (IML for efficient coding in active perception, wherein an agent learns to perform actions with its sense organs to facilitate efficient encoding of the sensory data. To this end, actions of the sense organs that improve the encoding of the sensory data trigger an internally generated reinforcement signal. Here it is argued that the same IML mechanism might also support the development of imitation when general actions beyond those of the sense organs are considered: The learner first observes a tutor performing a behavior and learns a model of the the behavior's sensory consequences. The learner then acts itself and receives an internally generated reinforcement signal reflecting how well the sensory consequences of its own behavior are encoded by the sensory model. Actions that are more similar to those of the tutor will lead to sensory signals that are easier to encode and produce a higher reinforcement signal. Through this, the learner's behavior is progressively tuned to make the sensory consequences of its actions match the learned sensory model. I discuss this mechanism in the context of human language acquisition and bird song learning where similar ideas have been proposed. The suggested mechanism also offers an account for the development of mirror neurons and makes a number of predictions. Overall, it establishes a connection between principles of efficient coding, intrinsic motivations and imitation.

  14. Characterization of Dispersion Strengthened Copper Alloy Prepared by Internal Oxidation Combined with Mechanical Alloying

    Science.gov (United States)

    Zhao, Ziqian; Xiao, Zhu; Li, Zhou; Zhu, Mengnan; Yang, Ziqi

    2017-11-01

    Cu-3.6 vol.% Al2O3 dispersion strengthened alloy was prepared by mechanical alloying (MA) of internal oxidation Cu-Al powders. The lattice parameter of Cu matrix decreased with milling time for powders milled in argon, while the abnormal increase of lattice parameter occurred in the air resulting from mechanochemical reactions. With a quantitative analysis, the combined method makes residual aluminum oxidized completely within 10-20 h while mechanical alloying method alone needs longer than 40 h. Lamellar structure formed and the thickness of lamellar structure decreased with milling time. The size of Al2O3 particles decreased from 46 to 22 nm after 40 h milling. After reduction, core-shell structure was found in MAed powders milled in the air. The compacted alloy produced by MAed powders milled in the argon had an average hardness and electrical conductivity of 172.2 HV and 82.1% IACS while the unmilled alloy's were 119.8 HV and 74.1% IACS due to the Al2O3 particles refinement and residual aluminum in situ oxidization.

  15. Criterion learning in rule-based categorization: simulation of neural mechanism and new data.

    Science.gov (United States)

    Helie, Sebastien; Ell, Shawn W; Filoteo, J Vincent; Maddox, W Todd

    2015-04-01

    In perceptual categorization, rule selection consists of selecting one or several stimulus-dimensions to be used to categorize the stimuli (e.g., categorize lines according to their length). Once a rule has been selected, criterion learning consists of defining how stimuli will be grouped using the selected dimension(s) (e.g., if the selected rule is line length, define 'long' and 'short'). Very little is known about the neuroscience of criterion learning, and most existing computational models do not provide a biological mechanism for this process. In this article, we introduce a new model of rule learning called Heterosynaptic Inhibitory Criterion Learning (HICL). HICL includes a biologically-based explanation of criterion learning, and we use new category-learning data to test key aspects of the model. In HICL, rule selective cells in prefrontal cortex modulate stimulus-response associations using pre-synaptic inhibition. Criterion learning is implemented by a new type of heterosynaptic error-driven Hebbian learning at inhibitory synapses that uses feedback to drive cell activation above/below thresholds representing ionic gating mechanisms. The model is used to account for new human categorization data from two experiments showing that: (1) changing rule criterion on a given dimension is easier if irrelevant dimensions are also changing (Experiment 1), and (2) showing that changing the relevant rule dimension and learning a new criterion is more difficult, but also facilitated by a change in the irrelevant dimension (Experiment 2). We conclude with a discussion of some of HICL's implications for future research on rule learning. Copyright © 2015 Elsevier Inc. All rights reserved.

  16. Elastomers in Combined Rolling-Sliding Contact; Wear and its Underlying Mechanisms

    Science.gov (United States)

    Rowe, Kyle Gene

    Elastomeric materials, specifically rubbers, being both of a practical and scientific importance, have been the subjects of vast amounts of research spanning well over two centuries. There is currently a large effort by tire manufacturers to design new rubber compounds with lower rolling resistance, higher sliding friction, and reduced or predictable wear. At present, these efforts are primarily based on a few empirical rules and very costly trial and error testing; only a basic understanding of the mechanisms involved in the wear of elastomeric materials exists despite rigorous study. In general, the only well controlled experiments have been for simple loading and sliding schemes. The aim of this work is to characterize the tribological properties of a carbon black filled natural rubber sample. This work explores (1) its behavior in unidirectional sliding, (2) contact mechanics, (3) traction properties in combined rolling and sliding, (4) frictional heating response, and (5) wear. It was found that the friction coefficient of this material was dependent upon sliding velocity, contact pressure, and surface roughness. The high friction coefficients also lead to a bifurcation of the contact area into two different pressure regimes at sliding velocities greater than 10 mm/s . The traction response of this material in combined rolling and sliding exhibited similar behavior, being a function of the contact pressure, but not rolling velocity. The wear of this material was found to be linearly dependent upon the global slip condition and occurred preferentially on the sample. Investigations of the worn surface revealed that the most likely mechanism of wear is the degradation of surface material in a confined layer a few micrometers thick. A simple spring-mass model was developed to offer an explanation of localized wear. It was found that the coupling of system elements in the normal direction helped to shift the load from wearing elements to non-wearing ones. The

  17. A Mobile Outdoor Augmented Reality Method Combining Deep Learning Object Detection and Spatial Relationships for Geovisualization.

    Science.gov (United States)

    Rao, Jinmeng; Qiao, Yanjun; Ren, Fu; Wang, Junxing; Du, Qingyun

    2017-08-24

    The purpose of this study was to develop a robust, fast and markerless mobile augmented reality method for registration, geovisualization and interaction in uncontrolled outdoor environments. We propose a lightweight deep-learning-based object detection approach for mobile or embedded devices; the vision-based detection results of this approach are combined with spatial relationships by means of the host device's built-in Global Positioning System receiver, Inertial Measurement Unit and magnetometer. Virtual objects generated based on geospatial information are precisely registered in the real world, and an interaction method based on touch gestures is implemented. The entire method is independent of the network to ensure robustness to poor signal conditions. A prototype system was developed and tested on the Wuhan University campus to evaluate the method and validate its results. The findings demonstrate that our method achieves a high detection accuracy, stable geovisualization results and interaction.

  18. A Mobile Outdoor Augmented Reality Method Combining Deep Learning Object Detection and Spatial Relationships for Geovisualization

    Directory of Open Access Journals (Sweden)

    Jinmeng Rao

    2017-08-01

    Full Text Available The purpose of this study was to develop a robust, fast and markerless mobile augmented reality method for registration, geovisualization and interaction in uncontrolled outdoor environments. We propose a lightweight deep-learning-based object detection approach for mobile or embedded devices; the vision-based detection results of this approach are combined with spatial relationships by means of the host device’s built-in Global Positioning System receiver, Inertial Measurement Unit and magnetometer. Virtual objects generated based on geospatial information are precisely registered in the real world, and an interaction method based on touch gestures is implemented. The entire method is independent of the network to ensure robustness to poor signal conditions. A prototype system was developed and tested on the Wuhan University campus to evaluate the method and validate its results. The findings demonstrate that our method achieves a high detection accuracy, stable geovisualization results and interaction.

  19. A Mobile Outdoor Augmented Reality Method Combining Deep Learning Object Detection and Spatial Relationships for Geovisualization

    Science.gov (United States)

    Rao, Jinmeng; Qiao, Yanjun; Ren, Fu; Wang, Junxing; Du, Qingyun

    2017-01-01

    The purpose of this study was to develop a robust, fast and markerless mobile augmented reality method for registration, geovisualization and interaction in uncontrolled outdoor environments. We propose a lightweight deep-learning-based object detection approach for mobile or embedded devices; the vision-based detection results of this approach are combined with spatial relationships by means of the host device’s built-in Global Positioning System receiver, Inertial Measurement Unit and magnetometer. Virtual objects generated based on geospatial information are precisely registered in the real world, and an interaction method based on touch gestures is implemented. The entire method is independent of the network to ensure robustness to poor signal conditions. A prototype system was developed and tested on the Wuhan University campus to evaluate the method and validate its results. The findings demonstrate that our method achieves a high detection accuracy, stable geovisualization results and interaction. PMID:28837096

  20. Machine Learning Approach to Optimizing Combined Stimulation and Medication Therapies for Parkinson's Disease.

    Science.gov (United States)

    Shamir, Reuben R; Dolber, Trygve; Noecker, Angela M; Walter, Benjamin L; McIntyre, Cameron C

    2015-01-01

    Deep brain stimulation (DBS) of the subthalamic region is an established therapy for advanced Parkinson's disease (PD). However, patients often require time-intensive post-operative management to balance their coupled stimulation and medication treatments. Given the large and complex parameter space associated with this task, we propose that clinical decision support systems (CDSS) based on machine learning algorithms could assist in treatment optimization. Develop a proof-of-concept implementation of a CDSS that incorporates patient-specific details on both stimulation and medication. Clinical data from 10 patients, and 89 post-DBS surgery visits, were used to create a prototype CDSS. The system was designed to provide three key functions: (1) information retrieval; (2) visualization of treatment, and; (3) recommendation on expected effective stimulation and drug dosages, based on three machine learning methods that included support vector machines, Naïve Bayes, and random forest. Measures of medication dosages, time factors, and symptom-specific pre-operative response to levodopa were significantly correlated with post-operative outcomes (P < 0.05) and their effect on outcomes was of similar magnitude to that of DBS. Using those results, the combined machine learning algorithms were able to accurately predict 86% (12/14) of the motor improvement scores at one year after surgery. Using patient-specific details, an appropriately parameterized CDSS could help select theoretically optimal DBS parameter settings and medication dosages that have potential to improve the clinical management of PD patients. Copyright © 2015 Elsevier Inc. All rights reserved.

  1. Combining Fog Computing with Sensor Mote Machine Learning for Industrial IoT.

    Science.gov (United States)

    Lavassani, Mehrzad; Forsström, Stefan; Jennehag, Ulf; Zhang, Tingting

    2018-05-12

    Digitalization is a global trend becoming ever more important to our connected and sustainable society. This trend also affects industry where the Industrial Internet of Things is an important part, and there is a need to conserve spectrum as well as energy when communicating data to a fog or cloud back-end system. In this paper we investigate the benefits of fog computing by proposing a novel distributed learning model on the sensor device and simulating the data stream in the fog, instead of transmitting all raw sensor values to the cloud back-end. To save energy and to communicate as few packets as possible, the updated parameters of the learned model at the sensor device are communicated in longer time intervals to a fog computing system. The proposed framework is implemented and tested in a real world testbed in order to make quantitative measurements and evaluate the system. Our results show that the proposed model can achieve a 98% decrease in the number of packets sent over the wireless link, and the fog node can still simulate the data stream with an acceptable accuracy of 97%. We also observe an end-to-end delay of 180 ms in our proposed three-layer framework. Hence, the framework shows that a combination of fog and cloud computing with a distributed data modeling at the sensor device for wireless sensor networks can be beneficial for Industrial Internet of Things applications.

  2. Combining Benford's Law and machine learning to detect money laundering. An actual Spanish court case.

    Science.gov (United States)

    Badal-Valero, Elena; Alvarez-Jareño, José A; Pavía, Jose M

    2018-01-01

    This paper is based on the analysis of the database of operations from a macro-case on money laundering orchestrated between a core company and a group of its suppliers, 26 of which had already been identified by the police as fraudulent companies. In the face of a well-founded suspicion that more companies have perpetrated criminal acts and in order to make better use of what are very limited police resources, we aim to construct a tool to detect money laundering criminals. We combine Benford's Law and machine learning algorithms (logistic regression, decision trees, neural networks, and random forests) to find patterns of money laundering criminals in the context of a real Spanish court case. After mapping each supplier's set of accounting data into a 21-dimensional space using Benford's Law and applying machine learning algorithms, additional companies that could merit further scrutiny are flagged up. A new tool to detect money laundering criminals is proposed in this paper. The tool is tested in the context of a real case. Copyright © 2017 Elsevier B.V. All rights reserved.

  3. Self-control over combined video feedback and modeling facilitates motor learning.

    Science.gov (United States)

    Post, Phillip G; Aiken, Christopher A; Laughlin, David D; Fairbrother, Jeffrey T

    2016-06-01

    Allowing learners to control the video presentation of knowledge of performance (KP) or an expert model during practice has been shown to facilitate motor learning (Aiken, Fairbrother, & Post, 2012; Wulf, Raupach, & Pfeiffer, 2005). Split-screen replay features now allow for the simultaneous presentation of these modes of instructional support. It is uncertain, however, if such a combination incorporated into a self-control protocol would yield similar benefits seen in earlier self-control studies. Therefore, the purpose of the present study was to examine the effects of self-controlled split-screen replay on the learning of a golf chip shot. Participants completed 60 practice trials, three administrations of the Intrinsic Motivation Inventory, and a questionnaire on day one. Retention and transfer tests and a final motivation inventory were completed on day two. Results revealed significantly higher form and accuracy scores for the self-control group during transfer. The self-control group also had significantly higher scores on the perceived competence subscale, reported requesting feedback mostly after perceived poor trials, and recalled a greater number of critical task features compared to the yoked group. The findings for the performance measures were consistent with previous self-control research. Copyright © 2016 Elsevier B.V. All rights reserved.

  4. Combining machine learning, crowdsourcing and expert knowledge to detect chemical-induced diseases in text.

    Science.gov (United States)

    Bravo, Àlex; Li, Tong Shu; Su, Andrew I; Good, Benjamin M; Furlong, Laura I

    2016-01-01

    Drug toxicity is a major concern for both regulatory agencies and the pharmaceutical industry. In this context, text-mining methods for the identification of drug side effects from free text are key for the development of up-to-date knowledge sources on drug adverse reactions. We present a new system for identification of drug side effects from the literature that combines three approaches: machine learning, rule- and knowledge-based approaches. This system has been developed to address the Task 3.B of Biocreative V challenge (BC5) dealing with Chemical-induced Disease (CID) relations. The first two approaches focus on identifying relations at the sentence-level, while the knowledge-based approach is applied both at sentence and abstract levels. The machine learning method is based on the BeFree system using two corpora as training data: the annotated data provided by the CID task organizers and a new CID corpus developed by crowdsourcing. Different combinations of results from the three strategies were selected for each run of the challenge. In the final evaluation setting, the system achieved the highest Recall of the challenge (63%). By performing an error analysis, we identified the main causes of misclassifications and areas for improving of our system, and highlighted the need of consistent gold standard data sets for advancing the state of the art in text mining of drug side effects.Database URL: https://zenodo.org/record/29887?ln¼en#.VsL3yDLWR_V. © The Author(s) 2016. Published by Oxford University Press.

  5. Mechanism of edaravone combined with urinary kallidinogenase for acute cerebral infarction patients

    Directory of Open Access Journals (Sweden)

    Chun-Yan Du

    2017-03-01

    Full Text Available Objective: To observe the effects of edaravone combined with urinary kallidinogenase on serum ox-LDL, PCT, hs-CRP, TNF-α and T cell subsets in patients with acute cerebral infarction, so as to explore the mechanisms of combination therapy on patients with acute cerebral infarction. Methods: 86 cases of patients with acute cerebral infarction in our hospital from March 2014 to May 2016 were randomly divided into two groups: control group and observation group, 43 cases in each group. All patients were given general treatment according to their own specific conditions, including hypoglycemic, pressure adjustment, prevention and treatment of complications, symptomatic support therapy, etc. The control group were given 30 mg Edaravone Injection on this basis with once per day for 14 d; The observation group was treated with 0. 15 PNA urinary kallidinogenase intravenous drip with once per day for 14 d on the basis of the control group. The levels of serum x-LDL, PCT, hs-CRP, TNF-α and CD3+, CD4+, CD8+, CD4+/CD8+ were detected and compared between the two groups. Results: (1 Before treatment, there was no significant difference between the two groups on the levels of serum ox-LDL, PCT, hs-CRP, and TNF-α; after treatment, the serum levels of ox-LDL, PCT, hs-CRP and TNF-α in the two groups were significantly lower than that before treatment, and the difference was significant (P<0.05; (2 Before treatment, there was no significant difference between the two groups on the levels of serum CD3+, CD4+, CD8+, CD4+/CD8+; after treatment, the serum levels of CD3+, CD4+ and CD4+/CD8+ were significantly increased in the two groups, and the level of CD8+ was significantly decreased compared with the same group before treatment, and the difference was significant (P<0.05; and the levels of serum CD3+, CD4+, CD8+ and CD4+/CD8+ in the observation group were significantly better than those in the control group, and the difference was significant (P<0

  6. Concurrence of rule- and similarity-based mechanisms in artificial grammar learning.

    Science.gov (United States)

    Opitz, Bertram; Hofmann, Juliane

    2015-03-01

    A current theoretical debate regards whether rule-based or similarity-based learning prevails during artificial grammar learning (AGL). Although the majority of findings are consistent with a similarity-based account of AGL it has been argued that these results were obtained only after limited exposure to study exemplars, and performance on subsequent grammaticality judgment tests has often been barely above chance level. In three experiments the conditions were investigated under which rule- and similarity-based learning could be applied. Participants were exposed to exemplars of an artificial grammar under different (implicit and explicit) learning instructions. The analysis of receiver operating characteristics (ROC) during a final grammaticality judgment test revealed that explicit but not implicit learning led to rule knowledge. It also demonstrated that this knowledge base is built up gradually while similarity knowledge governed the initial state of learning. Together these results indicate that rule- and similarity-based mechanisms concur during AGL. Moreover, it could be speculated that two different rule processes might operate in parallel; bottom-up learning via gradual rule extraction and top-down learning via rule testing. Crucially, the latter is facilitated by performance feedback that encourages explicit hypothesis testing. Copyright © 2015 Elsevier Inc. All rights reserved.

  7. Neural oscillatory mechanisms during novel grammar learning underlying language analytical abilities.

    Science.gov (United States)

    Kepinska, Olga; Pereda, Ernesto; Caspers, Johanneke; Schiller, Niels O

    2017-12-01

    The goal of the present study was to investigate the initial phases of novel grammar learning on a neural level, concentrating on mechanisms responsible for individual variability between learners. Two groups of participants, one with high and one with average language analytical abilities, performed an Artificial Grammar Learning (AGL) task consisting of learning and test phases. During the task, EEG signals from 32 cap-mounted electrodes were recorded and epochs corresponding to the learning phases were analysed. We investigated spectral power modulations over time, and functional connectivity patterns by means of a bivariate, frequency-specific index of phase synchronization termed Phase Locking Value (PLV). Behavioural data showed learning effects in both groups, with a steeper learning curve and higher ultimate attainment for the highly skilled learners. Moreover, we established that cortical connectivity patterns and profiles of spectral power modulations over time differentiated L2 learners with various levels of language analytical abilities. Over the course of the task, the learning process seemed to be driven by whole-brain functional connectivity between neuronal assemblies achieved by means of communication in the beta band frequency. On a shorter time-scale, increasing proficiency on the AGL task appeared to be supported by stronger local synchronisation within the right hemisphere regions. Finally, we observed that the highly skilled learners might have exerted less mental effort, or reduced attention for the task at hand once the learning was achieved, as evidenced by the higher alpha band power. Copyright © 2017 Elsevier Inc. All rights reserved.

  8. Action Reflected and Project Based Combined Methodology for the Appropriate Comprehension of Mechanisms in Industrial Design Education

    Science.gov (United States)

    Yavuzcan, H. Güçlü; Sahin, Damla

    2017-01-01

    In industrial design (ID) education, mechanics-based courses are mainly based on a traditional lecture approach and they are highly abstract for ID students to comprehend. The existing studies highlight the requirement of a new approach for mechanics-based courses in ID departments. This study presents a combined teaching model for mechanisms…

  9. Combining Human Computing and Machine Learning to Make Sense of Big (Aerial) Data for Disaster Response.

    Science.gov (United States)

    Ofli, Ferda; Meier, Patrick; Imran, Muhammad; Castillo, Carlos; Tuia, Devis; Rey, Nicolas; Briant, Julien; Millet, Pauline; Reinhard, Friedrich; Parkan, Matthew; Joost, Stéphane

    2016-03-01

    results suggest that the platform we have developed to combine crowdsourcing and machine learning to make sense of large volumes of aerial images can be used for disaster response.

  10. Identifying Human Phenotype Terms by Combining Machine Learning and Validation Rules

    Directory of Open Access Journals (Sweden)

    Manuel Lobo

    2017-01-01

    Full Text Available Named-Entity Recognition is commonly used to identify biological entities such as proteins, genes, and chemical compounds found in scientific articles. The Human Phenotype Ontology (HPO is an ontology that provides a standardized vocabulary for phenotypic abnormalities found in human diseases. This article presents the Identifying Human Phenotypes (IHP system, tuned to recognize HPO entities in unstructured text. IHP uses Stanford CoreNLP for text processing and applies Conditional Random Fields trained with a rich feature set, which includes linguistic, orthographic, morphologic, lexical, and context features created for the machine learning-based classifier. However, the main novelty of IHP is its validation step based on a set of carefully crafted manual rules, such as the negative connotation analysis, that combined with a dictionary can filter incorrectly identified entities, find missed entities, and combine adjacent entities. The performance of IHP was evaluated using the recently published HPO Gold Standardized Corpora (GSC, where the system Bio-LarK CR obtained the best F-measure of 0.56. IHP achieved an F-measure of 0.65 on the GSC. Due to inconsistencies found in the GSC, an extended version of the GSC was created, adding 881 entities and modifying 4 entities. IHP achieved an F-measure of 0.863 on the new GSC.

  11. Combining extreme learning machines using support vector machines for breast tissue classification.

    Science.gov (United States)

    Daliri, Mohammad Reza

    2015-01-01

    In this paper, we present a new approach for breast tissue classification using the features derived from electrical impedance spectroscopy. This method is composed of a feature extraction method, feature selection phase and a classification step. The feature extraction phase derives the features from the electrical impedance spectra. The extracted features consist of the impedivity at zero frequency (I0), the phase angle at 500 KHz, the high-frequency slope of phase angle, the impedance distance between spectral ends, the area under spectrum, the normalised area, the maximum of the spectrum, the distance between impedivity at I0 and the real part of the maximum frequency point and the length of the spectral curve. The system uses the information theoretic criterion as a strategy for feature selection and the combining extreme learning machines (ELMs) for the classification phase. The results of several ELMs are combined using the support vector machines classifier, and the result of classification is reported as a measure of the performance of the system. The results indicate that the proposed system achieves high accuracy in classification of breast tissues using the electrical impedance spectroscopy.

  12. Prediction of HDR quality by combining perceptually transformed display measurements with machine learning

    Science.gov (United States)

    Choudhury, Anustup; Farrell, Suzanne; Atkins, Robin; Daly, Scott

    2017-09-01

    We present an approach to predict overall HDR display quality as a function of key HDR display parameters. We first performed subjective experiments on a high quality HDR display that explored five key HDR display parameters: maximum luminance, minimum luminance, color gamut, bit-depth and local contrast. Subjects rated overall quality for different combinations of these display parameters. We explored two models | a physical model solely based on physically measured display characteristics and a perceptual model that transforms physical parameters using human vision system models. For the perceptual model, we use a family of metrics based on a recently published color volume model (ICT-CP), which consists of the PQ luminance non-linearity (ST2084) and LMS-based opponent color, as well as an estimate of the display point spread function. To predict overall visual quality, we apply linear regression and machine learning techniques such as Multilayer Perceptron, RBF and SVM networks. We use RMSE and Pearson/Spearman correlation coefficients to quantify performance. We found that the perceptual model is better at predicting subjective quality than the physical model and that SVM is better at prediction than linear regression. The significance and contribution of each display parameter was investigated. In addition, we found that combined parameters such as contrast do not improve prediction. Traditional perceptual models were also evaluated and we found that models based on the PQ non-linearity performed better.

  13. Effectiveness of teaching and learning mathematics for Thai university engineering students through a combination of activity and lecture based classroom

    Directory of Open Access Journals (Sweden)

    Parinya S. Ngiamsunthorn

    2014-04-01

    Full Text Available There are concerns of developing effective pedagogical practices for teaching mathematics for engineering students as many engineering students experience difficulties in learning compulsory mathematics subjects in their first and second years of the degree. This paper aims to investigate the effectiveness of using a variety of teaching and learning approaches including lecture based learning, activity based learning, e-learning via learning management system (LMS and practice or tutorial session in mathematics subjects for engineering students. This study was carried out on 160 students who need to enroll three basic mathematics subjects (MTH101, MTH102 and MTH201 for an engineering degree during academic year 2011 – 2012. The students were divided into three groups according to their majors of study. The first two groups of students were given a combination of various teaching approaches for only one semester (either MTH102 or MTH201, while the last group was given a combination of various teaching approaches for two semesters (both MTH102 and MTH201. To evaluate the effectiveness of teaching and learning, examination results, questionnaires on attitude towards teaching and learning, and a formal university teaching evaluation by students were collected and analyzed. It is found that different students perceive mathematics contents from different teaching methods according to their preferred learning styles. Moreover, most students in all groups performed at least the same or better in their final subject (MTH201. However, there is an interesting finding that low proficiency students in earlier mathematics subjects who received a combination of various teaching approaches for two semesters can improve their examination results better than other groups, on average. This is also reflected from an increasing average score on teaching evaluation from this group of students about teaching techniques.

  14. Implementation of Simulation Based-Concept Attainment Method to Increase Interest Learning of Engineering Mechanics Topic

    Science.gov (United States)

    Sultan, A. Z.; Hamzah, N.; Rusdi, M.

    2018-01-01

    The implementation of concept attainment method based on simulation was used to increase student’s interest in the subjects Engineering of Mechanics in second semester of academic year 2016/2017 in Manufacturing Engineering Program, Department of Mechanical PNUP. The result of the implementation of this learning method shows that there is an increase in the students’ learning interest towards the lecture material which is summarized in the form of interactive simulation CDs and teaching materials in the form of printed books and electronic books. From the implementation of achievement method of this simulation based concept, it is noted that the increase of student participation in the presentation and discussion as well as the deposit of individual assignment of significant student. With the implementation of this method of learning the average student participation reached 89%, which before the application of this learning method only reaches an average of 76%. And also with previous learning method, for exam achievement of A-grade under 5% and D-grade above 8%. After the implementation of the new learning method (simulation based-concept attainment method) the achievement of Agrade has reached more than 30% and D-grade below 1%.

  15. Strategies for adding adaptive learning mechanisms to rule-based diagnostic expert systems

    Science.gov (United States)

    Stclair, D. C.; Sabharwal, C. L.; Bond, W. E.; Hacke, Keith

    1988-01-01

    Rule-based diagnostic expert systems can be used to perform many of the diagnostic chores necessary in today's complex space systems. These expert systems typically take a set of symptoms as input and produce diagnostic advice as output. The primary objective of such expert systems is to provide accurate and comprehensive advice which can be used to help return the space system in question to nominal operation. The development and maintenance of diagnostic expert systems is time and labor intensive since the services of both knowledge engineer(s) and domain expert(s) are required. The use of adaptive learning mechanisms to increment evaluate and refine rules promises to reduce both time and labor costs associated with such systems. This paper describes the basic adaptive learning mechanisms of strengthening, weakening, generalization, discrimination, and discovery. Next basic strategies are discussed for adding these learning mechanisms to rule-based diagnostic expert systems. These strategies support the incremental evaluation and refinement of rules in the knowledge base by comparing the set of advice given by the expert system (A) with the correct diagnosis (C). Techniques are described for selecting those rules in the in the knowledge base which should participate in adaptive learning. The strategies presented may be used with a wide variety of learning algorithms. Further, these strategies are applicable to a large number of rule-based diagnostic expert systems. They may be used to provide either immediate or deferred updating of the knowledge base.

  16. Learning mechanisms in multidisciplinary teamwork with real customers and open-ended problems

    Science.gov (United States)

    Heikkinen, Juho; Isomöttönen, Ville

    2015-11-01

    Recently, there has been a trend towards adding a multidisciplinary or multicultural element to traditional monodisciplinary project courses in computing and engineering. In this article, we examine the implications of multidisciplinarity for students' learning experiences during a one-semester project course for real customers. We use a qualitative research approach and base our analysis on students' learning reports on three instances of a project course titled Multidisciplinary working life project. The main contribution of this article is the unified theoretical picture of the learning mechanisms stemming from multidisciplinarity. Our main conclusions are that (1) students generally have a positive view of multidisciplinarity; (2) multidisciplinary teams enable students to better identify their own expertise, which leads to increased occupational identity; and (3) learning experiences are not fixed, as team spirit and student attitude play an important role in how students react to challenging situations arising from introduction of the multidisciplinarity.

  17. Long-term potentiation in the amygdala: a cellular mechanism of fear learning and memory.

    Science.gov (United States)

    Sigurdsson, Torfi; Doyère, Valérie; Cain, Christopher K; LeDoux, Joseph E

    2007-01-01

    Much of the research on long-term potentiation (LTP) is motivated by the question of whether changes in synaptic strength similar to LTP underlie learning and memory. Here we discuss findings from studies on fear conditioning, a form of associative learning whose neural circuitry is relatively well understood, that may be particularly suited for addressing this question. We first review the evidence suggesting that fear conditioning is mediated by changes in synaptic strength at sensory inputs to the lateral nucleus of the amygdala. We then discuss several outstanding questions that will be important for future research on the role of synaptic plasticity in fear learning. The results gained from these studies may shed light not only on fear conditioning, but may also help unravel more general cellular mechanisms of learning and memory.

  18. Essential Features of Serious Games Design in Higher Education: Linking Learning Attributes to Game Mechanics

    Science.gov (United States)

    Lameras, Petros; Arnab, Sylvester; Dunwell, Ian; Stewart, Craig; Clarke, Samantha; Petridis, Panagiotis

    2017-01-01

    This paper consolidates evidence and material from a range of specialist and disciplinary fields to provide an evidence-based review and synthesis on the design and use of serious games in higher education. Search terms identified 165 papers reporting conceptual and empirical evidence on how learning attributes and game mechanics may be planned,…

  19. Introducing Innovative Approaches to Learning in Fluid Mechanics: A Case Study

    Science.gov (United States)

    Gynnild, Vidar; Myrhaug, Dag; Pettersen, Bjornar

    2007-01-01

    The purpose of the current article is to examine the impact of laboratory demonstrations and computer visualizations on learning in a third-year fluid mechanics course at Norwegian University of Science and Technology (NTNU). As a first step, on entering the course, students were exposed to a laboratory demonstration focusing on the nature of…

  20. Dense Neighborhoods and Mechanisms of Learning: Evidence from Children with Phonological Delay

    Science.gov (United States)

    Gierut, Judith A.; Morrisette, Michele L.

    2015-01-01

    There is a noted advantage of dense neighborhoods in language acquisition, but the learning mechanism that drives the effect is not well understood. Two hypotheses--long-term auditory word priming and phonological working memory--have been advanced in the literature as viable accounts. These were evaluated in two treatment studies enrolling twelve…

  1. "Gamestar Mechanic": Learning a Designer Mindset through Communicational Competence with the Language of Games

    Science.gov (United States)

    Games, Ivan Alex

    2010-01-01

    This article presents the results of a three-year study of "Gamestar Mechanic" (www.gamestarmechanic.com), a flash-based multiplayer online role-playing game developed for the MacArthur Foundation's digital media learning initiative by the University of Wisconsin-Madison, and Gamelab in New York. The game's objective is to help children…

  2. Assessing Cognitive Load Theory to Improve Student Learning for Mechanical Engineers

    Science.gov (United States)

    Impelluso, Thomas J.

    2009-01-01

    A computer programming class for students of mechanical engineering was redesigned and assessed: Cognitive Load Theory was used to redesign the content; online technologies were used to redesign the delivery. Student learning improved and the dropout rate was reduced. This article reports on both attitudinal and objective assessment: comparing…

  3. Auto Mechanics I. Learning Activity Packets (LAPs). Section E--Brakes.

    Science.gov (United States)

    Oklahoma State Board of Vocational and Technical Education, Stillwater. Curriculum and Instructional Materials Center.

    This document contains two learning activity packets (LAPs) that outline the study activities for the "brakes" instructional area for an Auto Mechanics I course. The two LAPs cover the following topics: brake systems and power disc brakes. Each LAP contains a cover sheet that describes its purpose, an introduction, and the tasks included…

  4. IMPLEMENTATION OF MULTIAGENT REINFORCEMENT LEARNING MECHANISM FOR OPTIMAL ISLANDING OPERATION OF DISTRIBUTION NETWORK

    DEFF Research Database (Denmark)

    Saleem, Arshad; Lind, Morten

    2008-01-01

    among electric power utilities to utilize modern information and communication technologies (ICT) in order to improve the automation of the distribution system. In this paper we present our work for the implementation of a dynamic multi-agent based distributed reinforcement learning mechanism...

  5. Using Game Mechanics to Measure What Students Learn from Programming Games

    Science.gov (United States)

    Denner, Jill; Werner, Linda; Campe, Shannon; Ortiz, Eloy

    2014-01-01

    Despite the growing popularity of teaching children to program games, little is known about the benefits for learning. In this article, the authors propose that game mechanics can be used as a window into how the children are thinking and describe a strategy for using them to analyze students' games. The study involved sixty 10-14 year old…

  6. Combined toxicity and underlying mechanisms of a mixture of eight heavy metals.

    Science.gov (United States)

    Zhou, Qi; Gu, Yuanliang; Yue, Xia; Mao, Guochuan; Wang, Yafei; Su, Hong; Xu, Jin; Shi, Hongbo; Zou, Baobo; Zhao, Jinshun; Wang, Renyuan

    2017-02-01

    With the rapid development of modernization and industrialization in China, a large quantity of heavy metals, including zinc, copper, lead, cadmium and mercury, have been entering the atmosphere, soil and water, the latter being the primary route of pollution. In the present study, in vitro experiments were performed to examine the joint toxicity and the underlying mechanisms of the eight most common heavy metals contaminating offshore waters on the eastern coast of Ningbo region. Using a cell cycle assay, cell apoptosis and reactive oxygen species (ROS) detection methods, the present study demonstrated that the heavy metal mixture arrested JB6 cells at the S phase, induced the generation of ROS and cell apoptosis. A luciferase assay indicated that the levels of activator protein‑1 and nuclear factor‑κB transcription factors were upregulated. Upregulation of the protein levels of C‑jun and p65 were detected in the JB6 cells by western blot analysis; these two genes have important roles in cell carcinogenesis. These results provide a useful reference for further investigations on the combined toxicity of the exposure to multiple heavy metals.

  7. Combining adhesive contact mechanics with a viscoelastic material model to probe local material properties by AFM.

    Science.gov (United States)

    Ganser, Christian; Czibula, Caterina; Tscharnuter, Daniel; Schöberl, Thomas; Teichert, Christian; Hirn, Ulrich

    2017-12-20

    Viscoelastic properties are often measured using probe based techniques such as nanoindentation (NI) and atomic force microscopy (AFM). Rarely, however, are these methods verified. In this article, we present a method that combines contact mechanics with a viscoelastic model (VEM) composed of springs and dashpots. We further show how to use this model to determine viscoelastic properties from creep curves recorded by a probe based technique. We focus on using the standard linear solid model and the generalized Maxwell model of order 2. The method operates in the range of 0.01 Hz to 1 Hz. Our approach is suitable for rough surfaces by providing a defined contact area using plastic pre-deformation of the material. The very same procedure is used to evaluate AFM based measurements as well as NI measurements performed on polymer samples made from poly(methyl methacrylate) and polycarbonate. The results of these measurements are then compared to those obtained by tensile creep tests also performed on the same samples. It is found that the tensile test results differ considerably from the results obtained by AFM and NI methods. The similarity between the AFM results and NI results suggests that the proposed method is capable of yielding results comparable to NI but with the advantage of the imaging possibilities of AFM. Furthermore, all three methods allowed a clear distinction between PC and PMMA by means of their respective viscoelastic properties.

  8. Ultrasound assisted extraction of food and natural products. Mechanisms, techniques, combinations, protocols and applications. A review.

    Science.gov (United States)

    Chemat, Farid; Rombaut, Natacha; Sicaire, Anne-Gaëlle; Meullemiestre, Alice; Fabiano-Tixier, Anne-Sylvie; Abert-Vian, Maryline

    2017-01-01

    This review presents a complete picture of current knowledge on ultrasound-assisted extraction (UAE) in food ingredients and products, nutraceutics, cosmetic, pharmaceutical and bioenergy applications. It provides the necessary theoretical background and some details about extraction by ultrasound, the techniques and their combinations, the mechanisms (fragmentation, erosion, capillarity, detexturation, and sonoporation), applications from laboratory to industry, security, and environmental impacts. In addition, the ultrasound extraction procedures and the important parameters influencing its performance are also included, together with the advantages and the drawbacks of each UAE techniques. Ultrasound-assisted extraction is a research topic, which affects several fields of modern plant-based chemistry. All the reported applications have shown that ultrasound-assisted extraction is a green and economically viable alternative to conventional techniques for food and natural products. The main benefits are decrease of extraction and processing time, the amount of energy and solvents used, unit operations, and CO 2 emissions. Copyright © 2016 Elsevier B.V. All rights reserved.

  9. Angular approach combined to mechanical model for tool breakage detection by eddy current sensors

    Science.gov (United States)

    Ritou, M.; Garnier, S.; Furet, B.; Hascoet, J. Y.

    2014-02-01

    The paper presents a new complete approach for Tool Condition Monitoring (TCM) in milling. The aim is the early detection of small damages so that catastrophic tool failures are prevented. A versatile in-process monitoring system is introduced for reliability concerns. The tool condition is determined by estimates of the radial eccentricity of the teeth. An adequate criterion is proposed combining mechanical model of milling and angular approach.Then, a new solution is proposed for the estimate of cutting force using eddy current sensors implemented close to spindle nose. Signals are analysed in the angular domain, notably by synchronous averaging technique. Phase shifts induced by changes of machining direction are compensated. Results are compared with cutting forces measured with a dynamometer table.The proposed method is implemented in an industrial case of pocket machining operation. One of the cutting edges has been slightly damaged during the machining, as shown by a direct measurement of the tool. A control chart is established with the estimates of cutter eccentricity obtained during the machining from the eddy current sensors signals. Efficiency and reliability of the method is demonstrated by a successful detection of the damage.

  10. Mirror reversal and visual rotation are learned and consolidated via separate mechanisms: recalibrating or learning de novo?

    Science.gov (United States)

    Telgen, Sebastian; Parvin, Darius; Diedrichsen, Jörn

    2014-10-08

    Motor learning tasks are often classified into adaptation tasks, which involve the recalibration of an existing control policy (the mapping that determines both feedforward and feedback commands), and skill-learning tasks, requiring the acquisition of new control policies. We show here that this distinction also applies to two different visuomotor transformations during reaching in humans: Mirror-reversal (left-right reversal over a mid-sagittal axis) of visual feedback versus rotation of visual feedback around the movement origin. During mirror-reversal learning, correct movement initiation (feedforward commands) and online corrections (feedback responses) were only generated at longer latencies. The earliest responses were directed into a nonmirrored direction, even after two training sessions. In contrast, for visual rotation learning, no dependency of directional error on reaction time emerged, and fast feedback responses to visual displacements of the cursor were immediately adapted. These results suggest that the motor system acquires a new control policy for mirror reversal, which initially requires extra processing time, while it recalibrates an existing control policy for visual rotations, exploiting established fast computational processes. Importantly, memory for visual rotation decayed between sessions, whereas memory for mirror reversals showed offline gains, leading to better performance at the beginning of the second session than in the end of the first. With shifts in time-accuracy tradeoff and offline gains, mirror-reversal learning shares common features with other skill-learning tasks. We suggest that different neuronal mechanisms underlie the recalibration of an existing versus acquisition of a new control policy and that offline gains between sessions are a characteristic of latter. Copyright © 2014 the authors 0270-6474/14/3413768-12$15.00/0.

  11. Modafinil combined with cognitive training is associated with improved learning in healthy volunteers--a randomised controlled trial.

    Science.gov (United States)

    Gilleen, J; Michalopoulou, P G; Reichenberg, A; Drake, R; Wykes, T; Lewis, S W; Kapur, S

    2014-04-01

    Improving cognition in people with neuropsychiatric disorders remains a major clinical target. By themselves pharmacological and non-pharmacological approaches have shown only modest effects in improving cognition. In the present study we tested a recently-proposed methodology to combine CT with a 'cognitive-enhancing' drug to improve cognitive test scores and expanded on previous approaches by delivering combination drug and CT, over a long intervention of repeated sessions, and used multiple tasks to reveal the cognitive processes being enhanced. We also aimed to determine whether gains from this combination approach generalised to untrained tests. In this proof of principle randomised-controlled trial thirty-three healthy volunteers were randomised to receive either modafinil or placebo combined with daily cognitive training over two weeks. Volunteers were trained on tasks of new-language learning, working memory and verbal learning following 200 mg modafinil or placebo for ten days. Improvements in trained and untrained tasks were measured. Rate of new-language learning was significantly enhanced with modafinil, and effects were greatest over the first five sessions. Modafinil improved within-day learning rather than between-day retention. No enhancement of gains with modafinil was observed in working memory nor rate of verbal learning. Gains in all tasks were retained post drug-administration, but transfer effects to broad cognitive abilities were not seen. This study shows that combining CT with modafinil specifically elevates learning over early training sessions compared to CT with placebo and provides a proof of principle experimental paradigm for pharmacological enhancement of cognitive remediation. Copyright © 2014 Elsevier B.V. and ECNP. All rights reserved.

  12. Combining Quality Work-Integrated Learning and Career Development Learning through the Use of the SOAR Model to Enhance Employability

    Science.gov (United States)

    Reddan, Gregory; Rauchle, Maja

    2017-01-01

    This paper presents students' perceptions of the benefits to employability of a suite of courses that incorporate both work-integrated learning (WIL) and career development learning (CDL). Field Project A and Field Project B are elective courses in the Bachelor of Exercise Science at Griffith University. These courses engage students in active and…

  13. Does Combining the Embodiment and Personalization Principles of Multimedia Learning Affect Learning the Culture of a Foreign Language?

    Science.gov (United States)

    Wang, Yanlin; Crooks, Steven M.

    2015-01-01

    The purpose of this study was to investigate how social cues associated with the personalization and embodiment principles in multimedia learning affect the learning and attitude of students studying the culture of a foreign language. University students were randomly assigned to one of two experimental conditions that consisted of an…

  14. High Gain Antenna System Deployment Mechanism Integration, Characterization, and Lessons Learned

    Science.gov (United States)

    Parong, Fil; Russell, Blair; Garcen, Walter; Rose, Chris; Johnson, Chris; Huber, Craig

    2014-01-01

    The integration and deployment testing of the High Gain Antenna System for the Global Precipitation Measurement mission is summarized. The HGAS deployment mechanism is described. The gravity negation system configuration and its influence on vertical, ground-based, deployment tests are presented with test data and model predictions. A focus is made on the late discovery and resolution of a potentially mission degrading deployment interference condition. The interaction of the flight deployment mechanism, gravity negation mechanism, and use of dynamic modeling is described and lessons learned presented.

  15. Feature combination networks for the interpretation of statistical machine learning models: application to Ames mutagenicity.

    Science.gov (United States)

    Webb, Samuel J; Hanser, Thierry; Howlin, Brendan; Krause, Paul; Vessey, Jonathan D

    2014-03-25

    A new algorithm has been developed to enable the interpretation of black box models. The developed algorithm is agnostic to learning algorithm and open to all structural based descriptors such as fragments, keys and hashed fingerprints. The algorithm has provided meaningful interpretation of Ames mutagenicity predictions from both random forest and support vector machine models built on a variety of structural fingerprints.A fragmentation algorithm is utilised to investigate the model's behaviour on specific substructures present in the query. An output is formulated summarising causes of activation and deactivation. The algorithm is able to identify multiple causes of activation or deactivation in addition to identifying localised deactivations where the prediction for the query is active overall. No loss in performance is seen as there is no change in the prediction; the interpretation is produced directly on the model's behaviour for the specific query. Models have been built using multiple learning algorithms including support vector machine and random forest. The models were built on public Ames mutagenicity data and a variety of fingerprint descriptors were used. These models produced a good performance in both internal and external validation with accuracies around 82%. The models were used to evaluate the interpretation algorithm. Interpretation was revealed that links closely with understood mechanisms for Ames mutagenicity. This methodology allows for a greater utilisation of the predictions made by black box models and can expedite further study based on the output for a (quantitative) structure activity model. Additionally the algorithm could be utilised for chemical dataset investigation and knowledge extraction/human SAR development.

  16. Reconstructing constructivism: causal models, Bayesian learning mechanisms, and the theory theory.

    Science.gov (United States)

    Gopnik, Alison; Wellman, Henry M

    2012-11-01

    We propose a new version of the "theory theory" grounded in the computational framework of probabilistic causal models and Bayesian learning. Probabilistic models allow a constructivist but rigorous and detailed approach to cognitive development. They also explain the learning of both more specific causal hypotheses and more abstract framework theories. We outline the new theoretical ideas, explain the computational framework in an intuitive and nontechnical way, and review an extensive but relatively recent body of empirical results that supports these ideas. These include new studies of the mechanisms of learning. Children infer causal structure from statistical information, through their own actions on the world and through observations of the actions of others. Studies demonstrate these learning mechanisms in children from 16 months to 4 years old and include research on causal statistical learning, informal experimentation through play, and imitation and informal pedagogy. They also include studies of the variability and progressive character of intuitive theory change, particularly theory of mind. These studies investigate both the physical and the psychological and social domains. We conclude with suggestions for further collaborative projects between developmental and computational cognitive scientists.

  17. Improvement of Learning and Memory Induced by Cordyceps Polypeptide Treatment and the Underlying Mechanism

    Directory of Open Access Journals (Sweden)

    Guangxin Yuan

    2018-01-01

    Full Text Available Our previous research revealed that Cordyceps militaris can improve the learning and memory, and although the main active ingredient should be its polypeptide complexes, the underlying mechanism of its activity remains poorly understood. In this study, we explored the mechanisms by which Cordyceps militaris improves learning and memory in a mouse model. Mice were given scopolamine hydrobromide intraperitoneally to establish a mouse model of learning and memory impairment. The effects of Cordyceps polypeptide in this model were tested using the Morris water maze test; serum superoxide dismutase activity; serum malondialdehyde levels; activities of acetyl cholinesterase, Na+-k+-ATPase, and nitric oxide synthase; and gamma aminobutyric acid and glutamate contents in brain tissue. Moreover, differentially expressed genes and the related cellular signaling pathways were screened using an mRNA expression profile chip. The results showed that the genes Pik3r5, Il-1β, and Slc18a2 were involved in the effects of Cordyceps polypeptide on the nervous system of these mice. Our findings suggest that Cordyceps polypeptide may improve learning and memory in the scopolamine-induced mouse model of learning and memory impairment by scavenging oxygen free radicals, preventing oxidative damage, and protecting the nervous system.

  18. Quantum Interactive Learning Tutorial on the Double-Slit Experiment to Improve Student Understanding of Quantum Mechanics

    Science.gov (United States)

    Sayer, Ryan; Maries, Alexandru; Singh, Chandralekha

    2017-01-01

    Learning quantum mechanics is challenging, even for upper-level undergraduate and graduate students. Research-validated interactive tutorials that build on students' prior knowledge can be useful tools to enhance student learning. We have been investigating student difficulties with quantum mechanics pertaining to the double-slit experiment in…

  19. Simultaneous learning and filtering without delusions: a Bayes-optimal combination of Predictive Inference and Adaptive Filtering.

    Science.gov (United States)

    Kneissler, Jan; Drugowitsch, Jan; Friston, Karl; Butz, Martin V

    2015-01-01

    Predictive coding appears to be one of the fundamental working principles of brain processing. Amongst other aspects, brains often predict the sensory consequences of their own actions. Predictive coding resembles Kalman filtering, where incoming sensory information is filtered to produce prediction errors for subsequent adaptation and learning. However, to generate prediction errors given motor commands, a suitable temporal forward model is required to generate predictions. While in engineering applications, it is usually assumed that this forward model is known, the brain has to learn it. When filtering sensory input and learning from the residual signal in parallel, a fundamental problem arises: the system can enter a delusional loop when filtering the sensory information using an overly trusted forward model. In this case, learning stalls before accurate convergence because uncertainty about the forward model is not properly accommodated. We present a Bayes-optimal solution to this generic and pernicious problem for the case of linear forward models, which we call Predictive Inference and Adaptive Filtering (PIAF). PIAF filters incoming sensory information and learns the forward model simultaneously. We show that PIAF is formally related to Kalman filtering and to the Recursive Least Squares linear approximation method, but combines these procedures in a Bayes optimal fashion. Numerical evaluations confirm that the delusional loop is precluded and that the learning of the forward model is more than 10-times faster when compared to a naive combination of Kalman filtering and Recursive Least Squares.

  20. Simultaneous Learning and Filtering without Delusions: A Bayes-Optimal Derivation of Combining Predictive Inference and AdaptiveFiltering

    Directory of Open Access Journals (Sweden)

    Jan eKneissler

    2015-04-01

    Full Text Available Predictive coding appears to be one of the fundamental working principles of brain processing. Amongst other aspects, brains often predict the sensory consequences of their own actions. Predictive coding resembles Kalman filtering, where incoming sensory information is filtered to produce prediction errors for subsequent adaptation and learning. However, to generate prediction errors given motor commands, a suitable temporal forward model is required to generate predictions. While in engineering applications, it is usually assumed that this forward model is known, the brain has to learn it. When filtering sensory input and learning from the residual signal in parallel, a fundamental problem arises: the system can enter a delusional loop when filtering the sensory information using an overly trusted forward model. In this case, learning stalls before accurate convergence because uncertainty about the forward model is not properly accommodated. We present a Bayes-optimal solution to this generic and pernicious problem for the case of linear forward models, which we call Predictive Inference and Adaptive Filtering (PIAF. PIAF filters incoming sensory information and learns the forward model simultaneously. We show that PIAF is formally related to Kalman filtering and to the Recursive Least Squares linear approximation method, but combines these procedures in a Bayes optimal fashion. Numerical evaluations confirm that the delusional loop is precluded and that the learning of the forward model is more than ten-times faster when compared to a naive combination of Kalman filtering and Recursive Least Squares.

  1. Latent memory facilitates relearning through molecular signaling mechanisms that are distinct from original learning.

    Science.gov (United States)

    Menges, Steven A; Riepe, Joshua R; Philips, Gary T

    2015-09-01

    A highly conserved feature of memory is that it can exist in a latent, non-expressed state which is revealed during subsequent learning by its ability to significantly facilitate (savings) or inhibit (latent inhibition) subsequent memory formation. Despite the ubiquitous nature of latent memory, the mechanistic nature of the latent memory trace and its ability to influence subsequent learning remains unclear. The model organism Aplysia californica provides the unique opportunity to make strong links between behavior and underlying cellular and molecular mechanisms. Using Aplysia, we have studied the mechanisms of savings due to latent memory for a prior, forgotten experience. We previously reported savings in the induction of three distinct temporal domains of memory: short-term (10min), intermediate-term (2h) and long-term (24h). Here we report that savings memory formation utilizes molecular signaling pathways that are distinct from original learning: whereas the induction of both original intermediate- and long-term memory in naïve animals requires mitogen activated protein kinase (MAPK) activation and ongoing protein synthesis, 2h savings memory is not disrupted by inhibitors of MAPK or protein synthesis, and 24h savings memory is not dependent on MAPK activation. Collectively, these findings reveal that during forgetting, latent memory for the original experience can facilitate relearning through molecular signaling mechanisms that are distinct from original learning. Copyright © 2015 Elsevier Inc. All rights reserved.

  2. Zebrafish and relational memory: Could a simple fish be useful for the analysis of biological mechanisms of complex vertebrate learning?

    Science.gov (United States)

    Gerlai, Robert

    2017-08-01

    Analysis of the zebrafish allows one to combine two distinct scientific approaches, comparative ethology and neurobehavioral genetics. Furthermore, this species arguably represents an optimal compromise between system complexity and practical simplicity. This mini-review focuses on a complex form of learning, relational learning and memory, in zebrafish. It argues that zebrafish are capable of this type of learning, and it attempts to show how this species may be useful in the analysis of the mechanisms and the evolution of this complex brain function. The review is not intended to be comprehensive. It is a short opinion piece that reflects the author's own biases, and it draws some of its examples from the work coming from his own laboratory. Nevertheless, it is written in the hope that it will persuade those who have not utilized zebrafish and who may be interested in opening their research horizon to this relatively novel but powerful vertebrate research tool. Copyright © 2017 Elsevier B.V. All rights reserved.

  3. Failing to learn from negative prediction errors: Obesity is associated with alterations in a fundamental neural learning mechanism.

    Science.gov (United States)

    Mathar, David; Neumann, Jane; Villringer, Arno; Horstmann, Annette

    2017-10-01

    Prediction errors (PEs) encode the difference between expected and actual action outcomes in the brain via dopaminergic modulation. Integration of these learning signals ensures efficient behavioral adaptation. Obesity has recently been linked to altered dopaminergic fronto-striatal circuits, thus implying impairments in cognitive domains that rely on its integrity. 28 obese and 30 lean human participants performed an implicit stimulus-response learning paradigm inside an fMRI scanner. Computational modeling and psycho-physiological interaction (PPI) analysis was utilized for assessing PE-related learning and associated functional connectivity. We show that human obesity is associated with insufficient incorporation of negative PEs into behavioral adaptation even in a non-food context, suggesting differences in a fundamental neural learning mechanism. Obese subjects were less efficient in using negative PEs to improve implicit learning performance, despite proper coding of PEs in striatum. We further observed lower functional coupling between ventral striatum and supplementary motor area in obese subjects subsequent to negative PEs. Importantly, strength of functional coupling predicted task performance and negative PE utilization. These findings show that obesity is linked to insufficient behavioral adaptation specifically in response to negative PEs, and to associated alterations in function and connectivity within the fronto-striatal system. Recognition of neural differences as a central characteristic of obesity hopefully paves the way to rethink established intervention strategies: Differential behavioral sensitivity to negative and positive PEs should be considered when designing intervention programs. Measures relying on penalization of unwanted behavior may prove less effective in obese subjects than alternative approaches. Copyright © 2017 Elsevier Ltd. All rights reserved.

  4. The Combined Use of Hypnosis and Sensory and Motor Stimulation in Assisting Children with Developmental Learning Problems.

    Science.gov (United States)

    Jampolsky, Gerald G.

    Hypnosis was combined with sensory and motor stimulation to remediate reversal problems in five children (6 1/2- 9-years-old). Under hypnosis Ss were given the suggestion that they learn their numbers through feel and then given 1 hour of structured instruction daily for 10 days. Instruction stressed conditioning, vibratory memory, touch memory,…

  5. Research on Motivation in Collaborative Learning: Moving beyond the Cognitive-Situative Divide and Combining Individual and Social Processes

    Science.gov (United States)

    Jarvela, Sanna; Volet, Simone; Jarvenoja, Hanna

    2010-01-01

    In this article we propose that in order to advance our understanding of motivation in collaborative learning we should move beyond the cognitive-situative epistemological divide and combine individual and social processes. Our claim is that although recent research has recognized the importance of social aspects in emerging and sustained…

  6. Reification in the Learning of Square Roots in a Ninth Grade Classroom: Combining Semiotic and Discursive Approaches

    Science.gov (United States)

    Shinno, Yusuke

    2018-01-01

    This paper reports on combining semiotic and discursive approaches to reification in classroom interactions. It focuses on the discursive characteristics and semiotic processes involved in the teaching and learning of square roots in a ninth grade classroom in Japan. The purpose of this study is to characterize the development of mathematical…

  7. Combined Effects of Note-Taking/-Reviewing on Learning and the Enhancement through Interventions: A Meta-Analytic Review

    Science.gov (United States)

    Kobayashi, Keiichi

    2006-01-01

    Meta-analyses of 33 studies were conducted to examine (1) how much the combination of taking and reviewing notes contributes to school learning, and (2) whether interventions in the note-taking/-reviewing procedure enhance note-taking/-reviewing effects, and if so, how much and under what conditions. Syntheses of findings from…

  8. Combining forces. Distributed Leadership and a professional learning community in primary and secondary education

    NARCIS (Netherlands)

    Hulsbos, Frank; Van Langevelde, Stefan; Evers, Arnoud

    2018-01-01

    This report describes an in depth case study of two good practice schools where a professional learning community and distributed leadership are highly developed. The goal of this study was to learn what conditions in the school support a professional learning community and distributed leadership.

  9. Module Seven: Combination Circuits and Voltage Dividers; Basic Electricity and Electronics Individualized Learning System.

    Science.gov (United States)

    Bureau of Naval Personnel, Washington, DC.

    In this module the student will learn to apply the rules previously learned for series and parallel circuits to more complex circuits called series-parallel circuits, discover the utility of a common reference when making reference to voltage values, and learn how to obtain a required voltage from a voltage divider network. The module is divided…

  10. Application and evaluation of a combination of socratice and learning through discussion techniques

    Directory of Open Access Journals (Sweden)

    EJ van Aswegen

    2001-09-01

    Full Text Available This article has its genesis in the inquirer’s interest in the need for internalizing critical thinking, creative thinking and reflective skills in adult learners. As part of a broader study the inquirer used a combination of two techniques over a period of nine months, namely: Socratic discussion/questioning and Learning Through Discussion Technique. The inquirer within this inquiry elected mainly qualitative methods, because they were seen as more adaptable to dealing with multiple realities and more sensitive and adaptable to the many shaping influences and value patterns that may be encountered (Lincoln & Guba, 1989. Purposive sampling was used and sample size (n =10 was determined by the willingness of potential participants to enlist in the chosen techniques. Feedback from participants was obtained: (1 verbally after each discussion session, and (2 in written format after completion of the course content. The final/ summative evaluation was obtained through a semi-structured questionnaire. This was deemed necessary, in that the participants were already studying for the end of the year examination. For the purpose of this condensed report the inquirer reflected only on the feedback obtained with the help of the questionnaire. The empirical study showed that in spite of various adaptation problems experienced, eight (8 of the ten (10 participants felt positive toward the applied techniques.

  11. Combining machine learning and matching techniques to improve causal inference in program evaluation.

    Science.gov (United States)

    Linden, Ariel; Yarnold, Paul R

    2016-12-01

    Program evaluations often utilize various matching approaches to emulate the randomization process for group assignment in experimental studies. Typically, the matching strategy is implemented, and then covariate balance is assessed before estimating treatment effects. This paper introduces a novel analytic framework utilizing a machine learning algorithm called optimal discriminant analysis (ODA) for assessing covariate balance and estimating treatment effects, once the matching strategy has been implemented. This framework holds several key advantages over the conventional approach: application to any variable metric and number of groups; insensitivity to skewed data or outliers; and use of accuracy measures applicable to all prognostic analyses. Moreover, ODA accepts analytic weights, thereby extending the methodology to any study design where weights are used for covariate adjustment or more precise (differential) outcome measurement. One-to-one matching on the propensity score was used as the matching strategy. Covariate balance was assessed using standardized difference in means (conventional approach) and measures of classification accuracy (ODA). Treatment effects were estimated using ordinary least squares regression and ODA. Using empirical data, ODA produced results highly consistent with those obtained via the conventional methodology for assessing covariate balance and estimating treatment effects. When ODA is combined with matching techniques within a treatment effects framework, the results are consistent with conventional approaches. However, given that it provides additional dimensions and robustness to the analysis versus what can currently be achieved using conventional approaches, ODA offers an appealing alternative. © 2016 John Wiley & Sons, Ltd.

  12. Teamwork: improved eQTL mapping using combinations of machine learning methods.

    Directory of Open Access Journals (Sweden)

    Marit Ackermann

    Full Text Available Expression quantitative trait loci (eQTL mapping is a widely used technique to uncover regulatory relationships between genes. A range of methodologies have been developed to map links between expression traits and genotypes. The DREAM (Dialogue on Reverse Engineering Assessments and Methods initiative is a community project to objectively assess the relative performance of different computational approaches for solving specific systems biology problems. The goal of one of the DREAM5 challenges was to reverse-engineer genetic interaction networks from synthetic genetic variation and gene expression data, which simulates the problem of eQTL mapping. In this framework, we proposed an approach whose originality resides in the use of a combination of existing machine learning algorithms (committee. Although it was not the best performer, this method was by far the most precise on average. After the competition, we continued in this direction by evaluating other committees using the DREAM5 data and developed a method that relies on Random Forests and LASSO. It achieved a much higher average precision than the DREAM best performer at the cost of slightly lower average sensitivity.

  13. Using video games to combine learning and assessment in mathematics education

    Directory of Open Access Journals (Sweden)

    Kristian Juha Mikael Kiili

    2015-12-01

    Full Text Available One problem with most education systems is that learning and (summative assessment are generally treated as quite separate things in schools. We argue that video games can provide an opportunity to combine these processes in an engaging and effective way. The present study focuses on investigating the effectiveness and the assessment power of two different mathematics video games, Semideus and Wuzzit Trouble. In the current study, we validated the Semideus game as a rational number test instrument. We used it as a pre- and a post-test for a three-hour intervention in which we studied the effectiveness of Wuzzit Trouble, a game built on whole number arithmetic and designed to enhance mathematical thinking and problem solving skills. The results showed that (1 games can be used to assess mathematical knowledge validly, and (2 even short game-based interventions can be very effective. Based on the results, we argue that game-based assessment can create a more complete picture of mathematical knowledge than simply measuring students' accuracy, providing indicators of student misconceptions and conceptual change processes

  14. Application and evaluation of a combination of socratice and learning through discussion techniques.

    Science.gov (United States)

    van Aswegen, E J; Brink, H I; Steyn, P J

    2001-11-01

    This article has its genesis in the inquirer's interest in the need for internalizing critical thinking, creative thinking and reflective skills in adult learners. As part of a broader study the inquirer used a combination of two techniques over a period of nine months, namely: Socratic discussion/questioning and Learning Through Discussion Technique. The inquirer within this inquiry elected mainly qualitative methods, because they were seen as more adaptable to dealing with multiple realities and more sensitive and adaptable to the many shaping influences and value patterns that may be encountered (Lincoln & Guba, 1989). Purposive sampling was used and sample size (n = 10) was determined by the willingness of potential participants to enlist in the chosen techniques. Feedback from participants was obtained: (1) verbally after each discussion session, and (2) in written format after completion of the course content. The final/summative evaluation was obtained through a semi-structured questionnaire. This was deemed necessary, in that the participants were already studying for the end of the year examination. For the purpose of this condensed report the inquirer reflected only on the feedback obtained with the help of the questionnaire. The empirical study showed that in spite of various adaptation problems experienced, eight (8) of the ten (10) participants felt positive toward the applied techniques.

  15. Learning with multiple representations: an example of a revision lesson in mechanics

    Science.gov (United States)

    Wong, Darren; Poo, Sng Peng; Eng Hock, Ng; Loo Kang, Wee

    2011-03-01

    We describe an example of learning with multiple representations in an A-level revision lesson on mechanics. The context of the problem involved the motion of a ball thrown vertically upwards in air and studying how the associated physical quantities changed during its flight. Different groups of students were assigned to look at the ball's motion using various representations: motion diagrams, vector diagrams, free-body diagrams, verbal description, equations and graphs, drawn against time as well as against displacement. Overall, feedback from students about the lesson was positive. We further discuss the benefits of using computer simulation to support and extend student learning.

  16. A Combination of Machine Learning and Cerebellar Models for the Motor Control and Learning of a Modular Robot

    DEFF Research Database (Denmark)

    Baira Ojeda, Ismael; Tolu, Silvia; Pacheco, Moises

    2017-01-01

    We scaled up a bio-inspired control architecture for the motor control and motor learning of a real modular robot. In our approach, the Locally Weighted Projection Regression algorithm (LWPR) and a cerebellar microcircuit coexist, forming a Unit Learning Machine. The LWPR optimizes the input space...... and learns the internal model of a single robot module to command the robot to follow a desired trajectory with its end-effector. The cerebellar microcircuit refines the LWPR output delivering corrective commands. We contrasted distinct cerebellar circuits including analytical models and spiking models...

  17. Combined therapeutic effect and molecular mechanisms of metformin and cisplatin in human lung cancer xenografts in nude mice

    OpenAIRE

    Yu-Qin Chen; Gang Chen

    2015-01-01

    Objective: This work was aimed at studying the inhibitory activity of metformin combined with the commonly used chemotherapy drug cisplatin in human lung cancer xenografts in nude mice. We also examined the combined effects of these drugs on the molecular expression of survivin, matrix metalloproteinase-2 (MMP-2), vascular endothelial growth factor-C (VEGF-C), and vascular endothelial growth factorreceptor-3 (VEGFR-3) to determine the mechanism of action and to explore the potential applicati...

  18. Change in catalase and peroxidase activity in rat blood in case of combined radiation and mechanical injuries

    International Nuclear Information System (INIS)

    Volkovaya, T.A.

    1982-01-01

    Changes of catalase and peroxide activity of blood in rats in case of irradiation at 2.0 and 7.0 Gy, mechanical injury of animal chest and combined radiation injury were studied. The given data testify to considerable increase of the above enzymes activity in case of all these effects. The less decrease of catalase and peroxide activity was observed after infliction of mechanical injury alone. Aggravating effect of mechanical injury on the irradiated organism leads to more noticeable decrease of catalase activity (at early periods of observation) in comparison with radiation effect. Peroxide changes in case of combined radiation and mechanical injury of rats differ slightly from similar factors observed in case of irradiation alone

  19. Neural mechanisms of reinforcement learning in unmedicated patients with major depressive disorder.

    Science.gov (United States)

    Rothkirch, Marcus; Tonn, Jonas; Köhler, Stephan; Sterzer, Philipp

    2017-04-01

    According to current concepts, major depressive disorder is strongly related to dysfunctional neural processing of motivational information, entailing impairments in reinforcement learning. While computational modelling can reveal the precise nature of neural learning signals, it has not been used to study learning-related neural dysfunctions in unmedicated patients with major depressive disorder so far. We thus aimed at comparing the neural coding of reward and punishment prediction errors, representing indicators of neural learning-related processes, between unmedicated patients with major depressive disorder and healthy participants. To this end, a group of unmedicated patients with major depressive disorder (n = 28) and a group of age- and sex-matched healthy control participants (n = 30) completed an instrumental learning task involving monetary gains and losses during functional magnetic resonance imaging. The two groups did not differ in their learning performance. Patients and control participants showed the same level of prediction error-related activity in the ventral striatum and the anterior insula. In contrast, neural coding of reward prediction errors in the medial orbitofrontal cortex was reduced in patients. Moreover, neural reward prediction error signals in the medial orbitofrontal cortex and ventral striatum showed negative correlations with anhedonia severity. Using a standard instrumental learning paradigm we found no evidence for an overall impairment of reinforcement learning in medication-free patients with major depressive disorder. Importantly, however, the attenuated neural coding of reward in the medial orbitofrontal cortex and the relation between anhedonia and reduced reward prediction error-signalling in the medial orbitofrontal cortex and ventral striatum likely reflect an impairment in experiencing pleasure from rewarding events as a key mechanism of anhedonia in major depressive disorder. © The Author (2017). Published by Oxford

  20. Performance evaluation of the machine learning algorithms used in inference mechanism of a medical decision support system.

    Science.gov (United States)

    Bal, Mert; Amasyali, M Fatih; Sever, Hayri; Kose, Guven; Demirhan, Ayse

    2014-01-01

    The importance of the decision support systems is increasingly supporting the decision making process in cases of uncertainty and the lack of information and they are widely used in various fields like engineering, finance, medicine, and so forth, Medical decision support systems help the healthcare personnel to select optimal method during the treatment of the patients. Decision support systems are intelligent software systems that support decision makers on their decisions. The design of decision support systems consists of four main subjects called inference mechanism, knowledge-base, explanation module, and active memory. Inference mechanism constitutes the basis of decision support systems. There are various methods that can be used in these mechanisms approaches. Some of these methods are decision trees, artificial neural networks, statistical methods, rule-based methods, and so forth. In decision support systems, those methods can be used separately or a hybrid system, and also combination of those methods. In this study, synthetic data with 10, 100, 1000, and 2000 records have been produced to reflect the probabilities on the ALARM network. The accuracy of 11 machine learning methods for the inference mechanism of medical decision support system is compared on various data sets.

  1. Performance Evaluation of the Machine Learning Algorithms Used in Inference Mechanism of a Medical Decision Support System

    Directory of Open Access Journals (Sweden)

    Mert Bal

    2014-01-01

    Full Text Available The importance of the decision support systems is increasingly supporting the decision making process in cases of uncertainty and the lack of information and they are widely used in various fields like engineering, finance, medicine, and so forth, Medical decision support systems help the healthcare personnel to select optimal method during the treatment of the patients. Decision support systems are intelligent software systems that support decision makers on their decisions. The design of decision support systems consists of four main subjects called inference mechanism, knowledge-base, explanation module, and active memory. Inference mechanism constitutes the basis of decision support systems. There are various methods that can be used in these mechanisms approaches. Some of these methods are decision trees, artificial neural networks, statistical methods, rule-based methods, and so forth. In decision support systems, those methods can be used separately or a hybrid system, and also combination of those methods. In this study, synthetic data with 10, 100, 1000, and 2000 records have been produced to reflect the probabilities on the ALARM network. The accuracy of 11 machine learning methods for the inference mechanism of medical decision support system is compared on various data sets.

  2. Quantum Mechanics/Molecular Mechanics Method Combined with Hybrid All-Atom and Coarse-Grained Model: Theory and Application on Redox Potential Calculations.

    Science.gov (United States)

    Shen, Lin; Yang, Weitao

    2016-04-12

    We developed a new multiresolution method that spans three levels of resolution with quantum mechanical, atomistic molecular mechanical, and coarse-grained models. The resolution-adapted all-atom and coarse-grained water model, in which an all-atom structural description of the entire system is maintained during the simulations, is combined with the ab initio quantum mechanics and molecular mechanics method. We apply this model to calculate the redox potentials of the aqueous ruthenium and iron complexes by using the fractional number of electrons approach and thermodynamic integration simulations. The redox potentials are recovered in excellent accordance with the experimental data. The speed-up of the hybrid all-atom and coarse-grained water model renders it computationally more attractive. The accuracy depends on the hybrid all-atom and coarse-grained water model used in the combined quantum mechanical and molecular mechanical method. We have used another multiresolution model, in which an atomic-level layer of water molecules around redox center is solvated in supramolecular coarse-grained waters for the redox potential calculations. Compared with the experimental data, this alternative multilayer model leads to less accurate results when used with the coarse-grained polarizable MARTINI water or big multipole water model for the coarse-grained layer.

  3. Neurocognitive mechanisms underlying social learning in infancy: infants' neural processing of the effects of others' actions.

    Science.gov (United States)

    Paulus, Markus; Hunnius, Sabine; Bekkering, Harold

    2013-10-01

    Social transmission of knowledge is one of the reasons for human evolutionary success, and it has been suggested that already human infants possess eminent social learning abilities. However, nothing is known about the neurocognitive mechanisms that subserve infants' acquisition of novel action knowledge through the observation of other people's actions and their consequences in the physical world. In an electroencephalogram study on social learning in infancy, we demonstrate that 9-month-old infants represent the environmental effects of others' actions in their own motor system, although they never achieved these effects themselves before. The results provide first insights into the neurocognitive basis of human infants' unique ability for social learning of novel action knowledge.

  4. Maize water status and physiological traits as affected by root endophytic fungus Piriformospora indica under combined drought and mechanical stresses.

    Science.gov (United States)

    Hosseini, Fatemeh; Mosaddeghi, Mohammad Reza; Dexter, Anthony Roger; Sepehri, Mozhgan

    2018-05-01

    Under combined drought and mechanical stresses, mechanical stress primarily controlled physiological responses of maize. Piriformospora indica mitigated the adverse effects of stresses, and inoculated maize experienced less oxidative damage and had better adaptation to stressful conditions. The objective of this study was to investigate the effect of maize root colonization by an endophytic fungus P. indica on plant water status, physiological traits and root morphology under combined drought and mechanical stresses. Seedlings of inoculated and non-inoculated maize (Zea mays L., cv. single cross 704) were cultivated in growth chambers filled with moistened siliceous sand at a matric suction of 20 hPa. Drought stress was induced using PEG 6000 solution with osmotic potentials of 0, - 0.3 and - 0.5 MPa. Mechanical stress (i.e., penetration resistances of 1.05, 4.23 and 6.34 MPa) was exerted by placing weights on the surface of the sand medium. After 30 days, leaf water potential (LWP) and relative water content (RWC), root and shoot fresh weights, root volume (RV) and diameter (RD), leaf proline content, leaf area (LA) and catalase (CAT) and ascorbate peroxidase (APX) activities were measured. The results show that exposure to individual drought and mechanical stresses led to higher RD and proline content and lower plant biomass, RV and LA. Moreover, increasing drought and mechanical stress severity increased APX activity by about 1.9- and 3.1-fold compared with the control. When plants were exposed to combined stresses, mechanical stress played the dominant role in controlling plant responses. P. indica-inoculated plants are better adapted to individual and combined stresses. The inoculated plants had greater RV, LA, RWC, LWP and proline content under stressful conditions. In comparison with non-inoculated plants, inoculated plants showed lower CAT and APX activities which means that they experienced less oxidative stress induced by stressful conditions.

  5. Combining Human and Machine Learning to Map Cropland in the 21st Century's Major Agricultural Frontier

    Science.gov (United States)

    Estes, L. D.; Debats, S. R.; Caylor, K. K.; Evans, T. P.; Gower, D.; McRitchie, D.; Searchinger, T.; Thompson, D. R.; Wood, E. F.; Zeng, L.

    2016-12-01

    In the coming decades, large areas of new cropland will be created to meet the world's rapidly growing food demands. Much of this new cropland will be in sub-Saharan Africa, where food needs will increase most and the area of remaining potential farmland is greatest. If we are to understand the impacts of global change, it is critical to accurately identify Africa's existing croplands and how they are changing. Yet the continent's smallholder-dominated agricultural systems are unusually challenging for remote sensing analyses, making accurate area estimates difficult to obtain, let alone important details related to field size and geometry. Fortunately, the rapidly growing archives of moderate to high-resolution satellite imagery hosted on open servers now offer an unprecedented opportunity to improve landcover maps. We present a system that integrates two critical components needed to capitalize on this opportunity: 1) human image interpretation and 2) machine learning (ML). Human judgment is needed to accurately delineate training sites within noisy imagery and a highly variable cover type, while ML provides the ability to scale and to interpret large feature spaces that defy human comprehension. Because large amounts of training data are needed (a major impediment for analysts), we use a crowdsourcing platform that connects amazon.com's Mechanical Turk service to satellite imagery hosted on open image servers. Workers map visible fields at pre-assigned sites, and are paid according to their mapping accuracy. Initial tests show overall high map accuracy and mapping rates >1800 km2/hour. The ML classifier uses random forests and randomized quasi-exhaustive feature selection, and is highly effective in classifying diverse agricultural types in southern Africa (AUC > 0.9). We connect the ML and crowdsourcing components to make an interactive learning framework. The ML algorithm performs an initial classification using a first batch of crowd-sourced maps, using

  6. Cognitive neuroepigenetics: the next evolution in our understanding of the molecular mechanisms underlying learning and memory?

    Science.gov (United States)

    Marshall, Paul; Bredy, Timothy W.

    2016-07-01

    A complete understanding of the fundamental mechanisms of learning and memory continues to elude neuroscientists. Although many important discoveries have been made, the question of how memories are encoded and maintained at the molecular level remains. So far, this issue has been framed within the context of one of the most dominant concepts in molecular biology, the central dogma, and the result has been a protein-centric view of memory. Here, we discuss the evidence supporting a role for neuroepigenetic mechanisms, which constitute dynamic and reversible, state-dependent modifications at all levels of control over cellular function, and their role in learning and memory. This neuroepigenetic view suggests that DNA, RNA and protein each influence one another to produce a holistic cellular state that contributes to the formation and maintenance of memory, and predicts a parallel and distributed system for the consolidation, storage and retrieval of the engram.

  7. Modulatory mechanisms of cortisol effects on emotional learning and memory: novel perspectives.

    Science.gov (United States)

    van Ast, Vanessa A; Cornelisse, Sandra; Marin, Marie-France; Ackermann, Sandra; Garfinkel, Sarah N; Abercrombie, Heather C

    2013-09-01

    It has long been known that cortisol affects learning and memory processes. Despite a wealth of research dedicated to cortisol effects on learning and memory, the strength or even directionality of the effects often vary. A number of the factors that alter cortisol's effects on learning and memory are well-known. For instance, effects of cortisol can be modulated by emotional arousal and the memory phase under study. Despite great advances in understanding factors that explain variability in cortisol's effects, additional modulators of cortisol effects on memory exist that are less widely acknowledged in current basic experimental research. The goal of the current review is to disseminate knowledge regarding less well-known modulators of cortisol effects on learning and memory. Since several models for the etiology of anxiety, such as post-traumatic stress disorder (PTSD), incorporate stress and the concomitant release of cortisol as important vulnerability factors, enhanced understanding of mechanisms by which cortisol exerts beneficial as opposed to detrimental effects on memory is very important. Further elucidation of the factors that modulate (or alter) cortisol's effects on memory will allow reconciliation of seemingly inconsistent findings in the basic and clinical literatures. The present review is based on a symposium as part of the 42nd International Society of Psychoneuroendocrinology Conference, New York, USA, that highlighted some of those modulators and their underlying mechanisms. Copyright © 2013 Elsevier Ltd. All rights reserved.

  8. On the mechanism of action of combination of thionocarbamates with xanthate during flotation of copper-molybdenum pyrite contained ores

    International Nuclear Information System (INIS)

    Nedosekina, T.V.; Glembotskij, A.V.; Bekhtle, G.A.; Novgorodova, Eh.Z.

    1985-01-01

    Investigation results of action mechanism of thionocarbamates combination with xanthate are described. It is established that these collectors are capable of co-adsorbing on pyrite surface, that is the reason for sharp increase of the floatability and disturbs the selectivity of copper-molybdenum pyrite-containing ore flotation

  9. REMEMBERING TO LEARN: INDEPENDENT PLACE AND JOURNEY CODING MECHANISMS CONTRIBUTE TO MEMORY TRANSFER

    OpenAIRE

    Bahar, Amir S.; Shapiro, Matthew L.

    2012-01-01

    The neural mechanisms that integrate new episodes with established memories are unknown. When rats explore an environment, CA1 cells fire in place fields that indicate locations. In goal-directed spatial memory tasks, some place fields differentiate behavioral histories (journey-dependent place fields) while others do not (journey-independent place fields). To investigate how these signals inform learning and memory for new and familiar episodes, we recorded CA1 and CA3 activity in rats train...

  10. Design, Qualification and Lessons Learned of the Shutter Calibration Mechanism for EnMAP Mission

    Science.gov (United States)

    Schmidt, Tilo; Muller, Silvio; Bergander, Arvid; Zajac, Kai; Seifart, Klaus

    2015-09-01

    The Shutter Calibration Mechanism (SCM) Assembly is one of three mechanisms which are developed by HTS for the EnMAP instrument in subcontract to OHB System AG Munich. EnMAP is the Environmental Mapping and Analysis Program of the German Space Agency DLR.The binary rotary encoder of the SCM using hall-effect sensors was already presented during ESMATS 2011. This paper summarizes the main functions and design features of the Hardware and focuses on qualification testing which has finished successfully in 2014. Of particular interest is the functional testing of the main drive including the precise hall-effect position sensing system and the test of the fail safe mechanism. In addition to standard test campaign required for QM also a shock emission measurement of the fail safe mechanism activation was conducted.Test conduction and results will be presented with focus on deviations from the expected behaviour, mitigation measures and on lessons learned.

  11. Learning outcomes afforded by self-assessed, segmented video–print combinations

    OpenAIRE

    Jack Koumi

    2015-01-01

    Learning affordances of video and print are examined in order to assess the learning outcomes afforded by hybrid video–print learning packages. The affordances discussed for print are: navigability, surveyability and legibility. Those discussed for video are: design for constructive reflection, provision of realistic experiences, presentational attributes, motivational influences and teacher personalisation. The video affordances are examined through a framework of pedagogic design principles...

  12. Assessing the Effectiveness of a Hybrid-Flipped Model of Learning on Fluid Mechanics Instruction: Overall Course Performance, Homework, and Far- and Near-Transfer of Learning

    Science.gov (United States)

    Harrison, David J.; Saito, Laurel; Markee, Nancy; Herzog, Serge

    2017-01-01

    To examine the impact of a hybrid-flipped model utilising active learning techniques, the researchers inverted one section of an undergraduate fluid mechanics course, reduced seat time, and engaged in active learning sessions in the classroom. We compared this model to the traditional section on four performance measures. We employed a propensity…

  13. Machine Learning on Images: Combining Passive Microwave and Optical Data to Estimate Snow Water Equivalent

    Science.gov (United States)

    Dozier, J.; Tolle, K.; Bair, N.

    2014-12-01

    We have a problem that may be a specific example of a generic one. The task is to estimate spatiotemporally distributed estimates of snow water equivalent (SWE) in snow-dominated mountain environments, including those that lack on-the-ground measurements. Several independent methods exist, but all are problematic. The remotely sensed date of disappearance of snow from each pixel can be combined with a calculation of melt to reconstruct the accumulated SWE for each day back to the last significant snowfall. Comparison with streamflow measurements in mountain ranges where such data are available shows this method to be accurate, but the big disadvantage is that SWE can only be calculated retroactively after snow disappears, and even then only for areas with little accumulation during the melt season. Passive microwave sensors offer real-time global SWE estimates but suffer from several issues, notably signal loss in wet snow or in forests, saturation in deep snow, subpixel variability in the mountains owing to the large (~25 km) pixel size, and SWE overestimation in the presence of large grains such as depth and surface hoar. Throughout the winter and spring, snow-covered area can be measured at sub-km spatial resolution with optical sensors, with accuracy and timeliness improved by interpolating and smoothing across multiple days. So the question is, how can we establish the relationship between Reconstruction—available only after the snow goes away—and passive microwave and optical data to accurately estimate SWE during the snow season, when the information can help forecast spring runoff? Linear regression provides one answer, but can modern machine learning techniques (used to persuade people to click on web advertisements) adapt to improve forecasts of floods and droughts in areas where more than one billion people depend on snowmelt for their water resources?

  14. The local enhancement conundrum: in search of the adaptive value of a social learning mechanism.

    Science.gov (United States)

    Arbilly, Michal; Laland, Kevin N

    2014-02-01

    Social learning mechanisms are widely thought to vary in their degree of complexity as well as in their prevalence in the natural world. While learning the properties of a stimulus that generalize to similar stimuli at other locations (stimulus enhancement) prima facie appears more useful to an animal than learning about a specific stimulus at a specific location (local enhancement), empirical evidence suggests that the latter is much more widespread in nature. Simulating populations engaged in a producer-scrounger game, we sought to deploy mathematical models to identify the adaptive benefits of reliance on local enhancement and/or stimulus enhancement, and the alternative conditions favoring their evolution. Surprisingly, we found that while stimulus enhancement readily evolves, local enhancement is advantageous only under highly restricted conditions: when generalization of information was made unreliable or when error in social learning was high. Our results generate a conundrum over how seemingly conflicting empirical and theoretical findings can be reconciled. Perhaps the prevalence of local enhancement in nature is due to stimulus enhancement costs independent of the learning task itself (e.g. predation risk), perhaps natural habitats are often characterized by unreliable yet highly rewarding payoffs, or perhaps local enhancement occurs less frequently, and stimulus enhancement more frequently, than widely believed. Copyright © 2013 Elsevier Inc. All rights reserved.

  15. Statistical learning and probabilistic prediction in music cognition: mechanisms of stylistic enculturation.

    Science.gov (United States)

    Pearce, Marcus T

    2018-05-11

    Music perception depends on internal psychological models derived through exposure to a musical culture. It is hypothesized that this musical enculturation depends on two cognitive processes: (1) statistical learning, in which listeners acquire internal cognitive models of statistical regularities present in the music to which they are exposed; and (2) probabilistic prediction based on these learned models that enables listeners to organize and process their mental representations of music. To corroborate these hypotheses, I review research that uses a computational model of probabilistic prediction based on statistical learning (the information dynamics of music (IDyOM) model) to simulate data from empirical studies of human listeners. The results show that a broad range of psychological processes involved in music perception-expectation, emotion, memory, similarity, segmentation, and meter-can be understood in terms of a single, underlying process of probabilistic prediction using learned statistical models. Furthermore, IDyOM simulations of listeners from different musical cultures demonstrate that statistical learning can plausibly predict causal effects of differential cultural exposure to musical styles, providing a quantitative model of cultural distance. Understanding the neural basis of musical enculturation will benefit from close coordination between empirical neuroimaging and computational modeling of underlying mechanisms, as outlined here. © 2018 The Authors. Annals of the New York Academy of Sciences published by Wiley Periodicals, Inc. on behalf of New York Academy of Sciences.

  16. Learning "Math on the Move": Effectiveness of a Combined Numeracy and Physical Activity Program for Primary School Children.

    Science.gov (United States)

    Vetter, Melanie; O'Connor, Helen; O'Dwyer, Nicholas; Orr, Rhonda

    2018-03-27

    Physically active learning that combines physical activity with core curriculum areas is emerging in school-based health interventions. This study investigates the effectiveness of learning an important numeracy skill of times tables (TT) while concurrently engaging in aerobic activity compared with a seated classroom approach. Grade-4 primary school students were randomly allocated to physical activity (P) or classroom (C) groups and received the alternate condition in the following term. P group received moderate to vigorous exercise (20 min, 3 times per week, 6 wk) while simultaneously learning selected TT. C group received similar learning, but seated. Changes in TT accuracy, general numeracy, aerobic fitness, and body mass index were assessed. Data were expressed as mean (SEM) and between-condition effect size (ES; 95% confidence interval). Participants [N = 85; 55% male, 9.8 (0.3) y, 36.4% overweight/obese] improved similarly on TT in both conditions [C group: 2.2% (1.1%); P group: 2.5% (1.3%); ES = 0.03; -0.30 to 0.36; P = .86]. Improvement in general numeracy was significantly greater for P group than C group [C group: 0.7% (1.2%); P group: 5.3% (1.4%); ES = 0.42; 0.08 to 0.75; P < .03]. An improvement in aerobic fitness for P group (P < .01) was not significantly greater than C group [C group: 0.8 (0.6); P group: 2.2 (0.5) mL·kg·min -1 ; ES = 0.32; -0.01 to 0.66; P = .06]. Body mass index was unchanged. Combined movement with learning TT was effective. Physically active learning paradigms may contribute to meeting daily physical activity guidelines while supporting or even boosting learning.

  17. Mechanisms of bioleaching and the visualization of these by combined AFM & EFM

    NARCIS (Netherlands)

    Sand, W.; Florian, B.; Noël, N.

    2009-01-01

    The understanding of mechanisms, by which microorganisms are effecting the dissolution of metal sulfides, what in general is called bioleaching, has progressed largely during the last 15 years. Whereas in the beginning of the nineties of the last century the direct and the indirect mechanisms were

  18. Mechanisms of Avian Influenza virus transmission between farms: combining data collection and mathematical modelling

    NARCIS (Netherlands)

    Ssematimba, A.

    2013-01-01

    The lack of sufficient knowledge on the mechanisms of between-farm spread of livestock diseases hampers the development of much needed effective and fast control strategies. Some of the mechanisms responsible for pathogen spread can be deduced from epidemic tracing reports and literature while

  19. The mechanism for the rhodium-catalyzed decarbonylation of aldehydes: A combined experimental and theoretical study

    DEFF Research Database (Denmark)

    Fristrup, Peter; Kreis, Michael; Palmelund, Anders

    2008-01-01

    that similar mechanisms are operating. A DFT (B3LYP) study of the catalytic cycle indicated a rapid oxidative addition into the C(O)-H bond followed by a rate-limiting extrusion of CO and reductive elimination. The theoretical kinetic isotope effects based on this mechanism were in excellent agreement...

  20. Application of Deep Learning Architectures for Accurate and Rapid Detection of Internal Mechanical Damage of Blueberry Using Hyperspectral Transmittance Data

    Directory of Open Access Journals (Sweden)

    Zhaodi Wang

    2018-04-01

    Full Text Available Deep learning has become a widely used powerful tool in many research fields, although not much so yet in agriculture technologies. In this work, two deep convolutional neural networks (CNN, viz. Residual Network (ResNet and its improved version named ResNeXt, are used to detect internal mechanical damage of blueberries using hyperspectral transmittance data. The original structure and size of hypercubes are adapted for the deep CNN training. To ensure that the models are applicable to hypercube, we adjust the number of filters in the convolutional layers. Moreover, a total of 5 traditional machine learning algorithms, viz. Sequential Minimal Optimization (SMO, Linear Regression (LR, Random Forest (RF, Bagging and Multilayer Perceptron (MLP, are performed as the comparison experiments. In terms of model assessment, k-fold cross validation is used to indicate that the model performance does not vary with the different combination of dataset. In real-world application, selling damaged berries will lead to greater interest loss than discarding the sound ones. Thus, precision, recall, and F1-score are also used as the evaluation indicators alongside accuracy to quantify the false positive rate. The first three indicators are seldom used by investigators in the agricultural engineering domain. Furthermore, ROC curves and Precision-Recall curves are plotted to visualize the performance of classifiers. The fine-tuned ResNet/ResNeXt achieve average accuracy and F1-score of 0.8844/0.8784 and 0.8952/0.8905, respectively. Classifiers SMO/ LR/RF/Bagging/MLP obtain average accuracy and F1-score of 0.8082/0.7606/0.7314/0.7113/0.7827 and 0.8268/0.7796/0.7529/0.7339/0.7971, respectively. Two deep learning models achieve better classification performance than the traditional machine learning methods. Classification for each testing sample only takes 5.2 ms and 6.5 ms respectively for ResNet and ResNeXt, indicating that the deep learning framework has great

  1. Application of Deep Learning Architectures for Accurate and Rapid Detection of Internal Mechanical Damage of Blueberry Using Hyperspectral Transmittance Data.

    Science.gov (United States)

    Wang, Zhaodi; Hu, Menghan; Zhai, Guangtao

    2018-04-07

    Deep learning has become a widely used powerful tool in many research fields, although not much so yet in agriculture technologies. In this work, two deep convolutional neural networks (CNN), viz. Residual Network (ResNet) and its improved version named ResNeXt, are used to detect internal mechanical damage of blueberries using hyperspectral transmittance data. The original structure and size of hypercubes are adapted for the deep CNN training. To ensure that the models are applicable to hypercube, we adjust the number of filters in the convolutional layers. Moreover, a total of 5 traditional machine learning algorithms, viz. Sequential Minimal Optimization (SMO), Linear Regression (LR), Random Forest (RF), Bagging and Multilayer Perceptron (MLP), are performed as the comparison experiments. In terms of model assessment, k-fold cross validation is used to indicate that the model performance does not vary with the different combination of dataset. In real-world application, selling damaged berries will lead to greater interest loss than discarding the sound ones. Thus, precision, recall, and F1-score are also used as the evaluation indicators alongside accuracy to quantify the false positive rate. The first three indicators are seldom used by investigators in the agricultural engineering domain. Furthermore, ROC curves and Precision-Recall curves are plotted to visualize the performance of classifiers. The fine-tuned ResNet/ResNeXt achieve average accuracy and F1-score of 0.8844/0.8784 and 0.8952/0.8905, respectively. Classifiers SMO/ LR/RF/Bagging/MLP obtain average accuracy and F1-score of 0.8082/0.7606/0.7314/0.7113/0.7827 and 0.8268/0.7796/0.7529/0.7339/0.7971, respectively. Two deep learning models achieve better classification performance than the traditional machine learning methods. Classification for each testing sample only takes 5.2 ms and 6.5 ms respectively for ResNet and ResNeXt, indicating that the deep learning framework has great potential for

  2. Application of Deep Learning Architectures for Accurate and Rapid Detection of Internal Mechanical Damage of Blueberry Using Hyperspectral Transmittance Data

    Science.gov (United States)

    Hu, Menghan; Zhai, Guangtao

    2018-01-01

    Deep learning has become a widely used powerful tool in many research fields, although not much so yet in agriculture technologies. In this work, two deep convolutional neural networks (CNN), viz. Residual Network (ResNet) and its improved version named ResNeXt, are used to detect internal mechanical damage of blueberries using hyperspectral transmittance data. The original structure and size of hypercubes are adapted for the deep CNN training. To ensure that the models are applicable to hypercube, we adjust the number of filters in the convolutional layers. Moreover, a total of 5 traditional machine learning algorithms, viz. Sequential Minimal Optimization (SMO), Linear Regression (LR), Random Forest (RF), Bagging and Multilayer Perceptron (MLP), are performed as the comparison experiments. In terms of model assessment, k-fold cross validation is used to indicate that the model performance does not vary with the different combination of dataset. In real-world application, selling damaged berries will lead to greater interest loss than discarding the sound ones. Thus, precision, recall, and F1-score are also used as the evaluation indicators alongside accuracy to quantify the false positive rate. The first three indicators are seldom used by investigators in the agricultural engineering domain. Furthermore, ROC curves and Precision-Recall curves are plotted to visualize the performance of classifiers. The fine-tuned ResNet/ResNeXt achieve average accuracy and F1-score of 0.8844/0.8784 and 0.8952/0.8905, respectively. Classifiers SMO/ LR/RF/Bagging/MLP obtain average accuracy and F1-score of 0.8082/0.7606/0.7314/0.7113/0.7827 and 0.8268/0.7796/0.7529/0.7339/0.7971, respectively. Two deep learning models achieve better classification performance than the traditional machine learning methods. Classification for each testing sample only takes 5.2 ms and 6.5 ms respectively for ResNet and ResNeXt, indicating that the deep learning framework has great potential for

  3. Blended Learning as a Potentially Winning Combination of Face-to-Face and Online Learning: An Exploratory Study

    Science.gov (United States)

    Auster, Carol J.

    2016-01-01

    Blended learning, in the form of screencasts to be viewed online outside of class, was incorporated into three sections of an introductory sociology course in a liberal arts college setting. The screencasts were used to introduce concepts and theories to provide more time for discussion in class and more opportunity for students to review concepts…

  4. Combining Machine Learning and Natural Language Processing to Assess Literary Text Comprehension

    Science.gov (United States)

    Balyan, Renu; McCarthy, Kathryn S.; McNamara, Danielle S.

    2017-01-01

    This study examined how machine learning and natural language processing (NLP) techniques can be leveraged to assess the interpretive behavior that is required for successful literary text comprehension. We compared the accuracy of seven different machine learning classification algorithms in predicting human ratings of student essays about…

  5. Combined in vivo and ex vivo analysis of mesh mechanics in a porcine hernia model.

    Science.gov (United States)

    Kahan, Lindsey G; Lake, Spencer P; McAllister, Jared M; Tan, Wen Hui; Yu, Jennifer; Thompson, Dominic; Brunt, L Michael; Blatnik, Jeffrey A

    2018-02-01

    Hernia meshes exhibit variability in mechanical properties, and their mechanical match to tissue has not been comprehensively studied. We used an innovative imaging model of in vivo strain tracking and ex vivo mechanical analysis to assess effects of mesh properties on repaired abdominal walls in a porcine model. We hypothesized that meshes with dissimilar mechanical properties compared to native tissue would alter abdominal wall mechanics more than better-matched meshes. Seven mini-pigs underwent ventral hernia creation and subsequent open repair with one of two heavyweight polypropylene meshes. Following mesh implantation with attached radio-opaque beads, fluoroscopic images were taken at insufflation pressures from 5 to 30 mmHg on postoperative days 0, 7, and 28. At 28 days, animals were euthanized and ex vivo mechanical testing performed on full-thickness samples across repaired abdominal walls. Testing was conducted on 13 mini-pig controls, and on meshes separately. Stiffness and anisotropy (the ratio of stiffness in the transverse versus craniocaudal directions) were assessed. 3D reconstructions of repaired abdominal walls showed stretch patterns. As pressure increased, both meshes expanded, with no differences between groups. Over time, meshes contracted 17.65% (Mesh A) and 0.12% (Mesh B; p = 0.06). Mesh mechanics showed that Mesh A deviated from anisotropic native tissue more than Mesh B. Compared to native tissue, Mesh A was stiffer both transversely and craniocaudally. Explanted repaired abdominal walls of both treatment groups were stiffer than native tissue. Repaired tissue became less anisotropic over time, as mesh properties prevailed over native abdominal wall properties. This technique assessed 3D stretch at the mesh level in vivo in a porcine model. While the abdominal wall expanded, mesh-ingrown areas contracted, potentially indicating stresses at mesh edges. Ex vivo mechanics demonstrate that repaired tissue adopts mesh properties, suggesting

  6. Learning biology through connecting mathematics to scientific mechanisms: Student outcomes and teacher supports

    Science.gov (United States)

    Schuchardt, Anita

    Integrating mathematics into science classrooms has been part of the conversation in science education for a long time. However, studies on student learning after incorporating mathematics in to the science classroom have shown mixed results. Understanding the mixed effects of including mathematics in science has been hindered by a historical focus on characteristics of integration tangential to student learning (e.g., shared elements, extent of integration). A new framework is presented emphasizing the epistemic role of mathematics in science. An epistemic role of mathematics missing from the current literature is identified: use of mathematics to represent scientific mechanisms, Mechanism Connected Mathematics (MCM). Building on prior theoretical work, it is proposed that having students develop mathematical equations that represent scientific mechanisms could elevate their conceptual understanding and quantitative problem solving. Following design and implementation of an MCM unit in inheritance, a large-scale quantitative analysis of pre and post implementation test results showed MCM students, compared to traditionally instructed students) had significantly greater gains in conceptual understanding of mathematically modeled scientific mechanisms, and their ability to solve complex quantitative problems. To gain insight into the mechanism behind the gain in quantitative problem solving, a small-scale qualitative study was conducted of two contrasting groups: 1) within-MCM instruction: competent versus struggling problem solvers, and 2) within-competent problem solvers: MCM instructed versus traditionally instructed. Competent MCM students tended to connect their mathematical inscriptions to the scientific phenomenon and to switch between mathematical and scientifically productive approaches during problem solving in potentially productive ways. The other two groups did not. To address concerns about teacher capacity presenting barriers to scalability of MCM

  7. A Hybrid Approach to Composite Damage and Failure Analysis Combining Synergistic Damage Mechanics and Peridynamics

    Science.gov (United States)

    2017-12-31

    Composite Damage and Failure Analysis Combinin Synergistic Damage Mechanics and Peridynamics 6. AUTHOR(S) 5b. GRANT NUMBER N00014-16-1-2173 5c...NUMBER 8. PERFORMING ORGANIZATION REPORT NUMBER Texas A&M Engineering Experiment Station (TEES) 400 Harvey Mitchell Parkway, Suite 300 College...1.3 related to Synergistic Damage Mechanics and Tasks 2.2 and 2.4 related to Peridynamics, as described in the project proposal. The activities

  8. Single or in Combination Antimicrobial Resistance Mechanisms of Klebsiella pneumoniae Contribute to Varied Susceptibility to Different Carbapenems

    Science.gov (United States)

    Tsai, Yu-Kuo; Liou, Ci-Hong; Fung, Chang-Phone; Lin, Jung-Chung; Siu, L. Kristopher

    2013-01-01

    Resistance to carbapenems has been documented by the production of carbapenemase or the loss of porins combined with extended-spectrum β-lactamases or AmpC β-lactamases. However, no complete comparisons have been made regarding the contributions of each resistance mechanism towards carbapenem resistance. In this study, we genetically engineered mutants of Klebsiella pneumoniae with individual and combined resistance mechanisms, and then compared each resistance mechanism in response to ertapenem, imipenem, meropenem, doripenem and other antibiotics. Among the four studied carbapenems, ertapenem was the least active against the loss of porins, cephalosporinases and carbapenemases. In addition to the production of KPC-2 or NDM-1 alone, resistance to all four carbapenems could also be conferred by the loss of two major porins, OmpK35 and OmpK36, combined with CTX-M-15 or DHA-1 with its regulator AmpR. Because the loss of OmpK35/36 alone or the loss of a single porin combined with bla CTX-M-15 or bla DHA-1-ampR expression was only sufficient for ertapenem resistance, our results suggest that carbapenems other than ertapenem should still be effective against these strains and laboratory testing for non-susceptibility to other carbapenems should improve the accurate identification of these isolates. PMID:24265784

  9. Mechanisms of n-3 fatty acid-mediated development and maintenance of learning memory performance.

    Science.gov (United States)

    Su, Hui-Min

    2010-05-01

    Docosahexaenoic acid (DHA, 22:6n-3) is specifically enriched in the brain and mainly anchored in the neuronal membrane, where it is involved in the maintenance of normal neurological function. Most DHA accumulation in the brain takes place during brain development in the perinatal period. However, hippocampal DHA levels decrease with age and in the brain disorder Alzheimer's disease (AD), and this decrease is associated with reduced hippocampal-dependent spatial learning memory ability. A potential mechanism is proposed by which the n-3 fatty acids DHA and eicosapentaenoic acid (20:5n-3) aid the development and maintenance of spatial learning memory performance. The developing brain or hippocampal neurons can synthesize and take up DHA and incorporate it into membrane phospholipids, especially phosphatidylethanolamine, resulting in enhanced neurite outgrowth, synaptogenesis and neurogenesis. Exposure to n-3 fatty acids enhances synaptic plasticity by increasing long-term potentiation and synaptic protein expression to increase the dendritic spine density, number of c-Fos-positive neurons and neurogenesis in the hippocampus for learning memory processing. In aged rats, n-3 fatty acid supplementation reverses age-related changes and maintains learning memory performance. n-3 fatty acids have anti-oxidative stress, anti-inflammation, and anti-apoptosis effects, leading to neuron protection in the aged, damaged, and AD brain. Retinoid signaling may be involved in the effects of DHA on learning memory performance. Estrogen has similar effects to n-3 fatty acids on hippocampal function. It would be interesting to know if there is any interaction between DHA and estrogen so as to provide a better strategy for the development and maintenance of learning memory. Copyright 2010 Elsevier Inc. All rights reserved.

  10. A Novel Teaching Tool Combined With Active-Learning to Teach Antimicrobial Spectrum Activity.

    Science.gov (United States)

    MacDougall, Conan

    2017-03-25

    Objective. To design instructional methods that would promote long-term retention of knowledge of antimicrobial pharmacology, particularly the spectrum of activity for antimicrobial agents, in pharmacy students. Design. An active-learning approach was used to teach selected sessions in a required antimicrobial pharmacology course. Students were expected to review key concepts from the course reader prior to the in-class sessions. During class, brief concept reviews were followed by active-learning exercises, including a novel schematic method for learning antimicrobial spectrum of activity ("flower diagrams"). Assessment. At the beginning of the next quarter (approximately 10 weeks after the in-class sessions), 360 students (three yearly cohorts) completed a low-stakes multiple-choice examination on the concepts in antimicrobial spectrum of activity. When data for students was pooled across years, the mean number of correct items was 75.3% for the items that tested content delivered with the active-learning method vs 70.4% for items that tested content delivered via traditional lecture (mean difference 4.9%). Instructor ratings on student evaluations of the active-learning approach were high (mean scores 4.5-4.8 on a 5-point scale) and student comments were positive about the active-learning approach and flower diagrams. Conclusion. An active-learning approach led to modestly higher scores in a test of long-term retention of pharmacology knowledge and was well-received by students.

  11. Transcriptome Analysis of Sunflower Genotypes with Contrasting Oxidative Stress Tolerance Reveals Individual- and Combined- Biotic and Abiotic Stress Tolerance Mechanisms.

    Directory of Open Access Journals (Sweden)

    Vemanna S Ramu

    Full Text Available In nature plants are often simultaneously challenged by different biotic and abiotic stresses. Although the mechanisms underlying plant responses against single stress have been studied considerably, plant tolerance mechanisms under combined stress is not understood. Also, the mechanism used to combat independently and sequentially occurring many number of biotic and abiotic stresses has also not systematically studied. From this context, in this study, we attempted to explore the shared response of sunflower plants to many independent stresses by using meta-analysis of publically available transcriptome data and transcript profiling by quantitative PCR. Further, we have also analyzed the possible role of the genes so identified in contributing to combined stress tolerance. Meta-analysis of transcriptomic data from many abiotic and biotic stresses indicated the common representation of oxidative stress responsive genes. Further, menadione-mediated oxidative stress in sunflower seedlings showed similar pattern of changes in the oxidative stress related genes. Based on this a large scale screening of 55 sunflower genotypes was performed under menadione stress and those contrasting in oxidative stress tolerance were identified. Further to confirm the role of genes identified in individual and combined stress tolerance the contrasting genotypes were individually and simultaneously challenged with few abiotic and biotic stresses. The tolerant hybrid showed reduced levels of stress damage both under combined stress and few independent stresses. Transcript profiling of the genes identified from meta-analysis in the tolerant hybrid also indicated that the selected genes were up-regulated under individual and combined stresses. Our results indicate that menadione-based screening can identify genotypes not only tolerant to multiple number of individual biotic and abiotic stresses, but also the combined stresses.

  12. Predictions of new AB O3 perovskite compounds by combining machine learning and density functional theory

    Science.gov (United States)

    Balachandran, Prasanna V.; Emery, Antoine A.; Gubernatis, James E.; Lookman, Turab; Wolverton, Chris; Zunger, Alex

    2018-04-01

    We apply machine learning (ML) methods to a database of 390 experimentally reported A B O3 compounds to construct two statistical models that predict possible new perovskite materials and possible new cubic perovskites. The first ML model classified the 390 compounds into 254 perovskites and 136 that are not perovskites with a 90% average cross-validation (CV) accuracy; the second ML model further classified the perovskites into 22 known cubic perovskites and 232 known noncubic perovskites with a 94% average CV accuracy. We find that the most effective chemical descriptors affecting our classification include largely geometric constructs such as the A and B Shannon ionic radii, the tolerance and octahedral factors, the A -O and B -O bond length, and the A and B Villars' Mendeleev numbers. We then construct an additional list of 625 A B O3 compounds assembled from charge conserving combinations of A and B atoms absent from our list of known compounds. Then, using the two ML models constructed on the known compounds, we predict that 235 of the 625 exist in a perovskite structure with a confidence greater than 50% and among them that 20 exist in the cubic structure (albeit, the latter with only ˜50 % confidence). We find that the new perovskites are most likely to occur when the A and B atoms are a lanthanide or actinide, when the A atom is an alkali, alkali earth, or late transition metal atom, or when the B atom is a p -block atom. We also compare the ML findings with the density functional theory calculations and convex hull analyses in the Open Quantum Materials Database (OQMD), which predicts the T =0 K ground-state stability of all the A B O3 compounds. We find that OQMD predicts 186 of 254 of the perovskites in the experimental database to be thermodynamically stable within 100 meV/atom of the convex hull and predicts 87 of the 235 ML-predicted perovskite compounds to be thermodynamically stable within 100 meV/atom of the convex hull, including 6 of these to

  13. Universal effect of dynamical reinforcement learning mechanism in spatial evolutionary games

    International Nuclear Information System (INIS)

    Zhang, Hai-Feng; Wu, Zhi-Xi; Wang, Bing-Hong

    2012-01-01

    One of the prototypical mechanisms in understanding the ubiquitous cooperation in social dilemma situations is the win–stay, lose–shift rule. In this work, a generalized win–stay, lose–shift learning model—a reinforcement learning model with dynamic aspiration level—is proposed to describe how humans adapt their social behaviors based on their social experiences. In the model, the players incorporate the information of the outcomes in previous rounds with time-dependent aspiration payoffs to regulate the probability of choosing cooperation. By investigating such a reinforcement learning rule in the spatial prisoner's dilemma game and public goods game, a most noteworthy viewpoint is that moderate greediness (i.e. moderate aspiration level) favors best the development and organization of collective cooperation. The generality of this observation is tested against different regulation strengths and different types of network of interaction as well. We also make comparisons with two recently proposed models to highlight the importance of the mechanism of adaptive aspiration level in supporting cooperation in structured populations

  14. Talker-specific learning in amnesia: Insight into mechanisms of adaptive speech perception.

    Science.gov (United States)

    Trude, Alison M; Duff, Melissa C; Brown-Schmidt, Sarah

    2014-05-01

    A hallmark of human speech perception is the ability to comprehend speech quickly and effortlessly despite enormous variability across talkers. However, current theories of speech perception do not make specific claims about the memory mechanisms involved in this process. To examine whether declarative memory is necessary for talker-specific learning, we tested the ability of amnesic patients with severe declarative memory deficits to learn and distinguish the accents of two unfamiliar talkers by monitoring their eye-gaze as they followed spoken instructions. Analyses of the time-course of eye fixations showed that amnesic patients rapidly learned to distinguish these accents and tailored perceptual processes to the voice of each talker. These results demonstrate that declarative memory is not necessary for this ability and points to the involvement of non-declarative memory mechanisms. These results are consistent with findings that other social and accommodative behaviors are preserved in amnesia and contribute to our understanding of the interactions of multiple memory systems in the use and understanding of spoken language. Copyright © 2014 Elsevier Ltd. All rights reserved.

  15. Learning-based adaptive prescribed performance control of postcapture space robot-target combination without inertia identifications

    Science.gov (United States)

    Wei, Caisheng; Luo, Jianjun; Dai, Honghua; Bian, Zilin; Yuan, Jianping

    2018-05-01

    In this paper, a novel learning-based adaptive attitude takeover control method is investigated for the postcapture space robot-target combination with guaranteed prescribed performance in the presence of unknown inertial properties and external disturbance. First, a new static prescribed performance controller is developed to guarantee that all the involved attitude tracking errors are uniformly ultimately bounded by quantitatively characterizing the transient and steady-state performance of the combination. Then, a learning-based supplementary adaptive strategy based on adaptive dynamic programming is introduced to improve the tracking performance of static controller in terms of robustness and adaptiveness only utilizing the input/output data of the combination. Compared with the existing works, the prominent advantage is that the unknown inertial properties are not required to identify in the development of learning-based adaptive control law, which dramatically decreases the complexity and difficulty of the relevant controller design. Moreover, the transient and steady-state performance is guaranteed a priori by designer-specialized performance functions without resorting to repeated regulations of the controller parameters. Finally, the three groups of illustrative examples are employed to verify the effectiveness of the proposed control method.

  16. Compositional and Mechanical Properties of Peanuts Roasted to Equivalent Colors using Different Time/Temperature Combinations

    Science.gov (United States)

    Peanuts in North America and Europe are primarily consumed after dry roasting. Standard industry practice is to roast peanuts to a specific surface color (Hunter L-value) for a given application; however, equivalent surface colors can be attained using different roast temperature/time combinations,...

  17. Possible mechanisms of the antifungal activity of fluconazole in combination with terbinafine against Candida albicans.

    Science.gov (United States)

    Khodavandi, Alireza; Alizadeh, Fahimeh; Vanda, Nasim Aghai; Karimi, Golgis; Chong, Pei Pei

    2014-12-01

    Candidiasis is a term describing infections by yeasts from the genus Candida, the majority Candida albicans. Treatment of such infections often requires antifungals such as the azoles, but increased use of these drugs has led to selection of yeasts with increased resistance to these drugs. Combination therapy would be one of the best strategies for the treatment of candidiasis due to increased resistance to azoles. The antifungal activities of fluconazole and terbinafine were evaluated in vitro alone and in combination using broth microdilution test and time kill study. Eventually the expression level of selected genes involved in ergosterol biosynthesis of Candida was evaluated using semi-quantitative RT-PCR. The obtained results showed the significant MICs ranging from 0.25 to 8 µg/mL followed by FICs ranged from 0.37 to 1 in combination with fluconazole/terbinafine. Our findings have demonstrated that the combination of fluconazole and terbinafine could also significantly reduce the expression of ERG1, 3, and 11 in the cell membrane of Candida in all concentrations tested ranging from 1.73- to 6.99-fold. This study was undertaken with the ultimate goal of finding the probable targets of fluconazole/terbinafine in C. albicans by looking at its effects on cell membrane synthesis.

  18. Combined Enzymatic and Mechanical Cell Disruption and Lipid Extraction of Green Alga Neochloris oleoabundans

    Science.gov (United States)

    Wang, Dongqin; Li, Yanqun; Hu, Xueqiong; Su, Weimin; Zhong, Min

    2015-01-01

    Microalgal biodiesel is one of the most promising renewable fuels. The wet technique for lipids extraction has advantages over the dry method, such as energy-saving and shorter procedure. The cell disruption is a key factor in wet oil extraction to facilitate the intracellular oil release. Ultrasonication, high-pressure homogenization, enzymatic hydrolysis and the combination of enzymatic hydrolysis with high-pressure homogenization and ultrasonication were employed in this study to disrupt the cells of the microalga Neochloris oleoabundans. The cell disruption degree was investigated. The cell morphology before and after disruption was assessed with scanning and transmission electron microscopy. The energy requirements and the operation cost for wet cell disruption were also estimated. The highest disruption degree, up to 95.41%, assessed by accounting method was achieved by the combination of enzymatic hydrolysis and high-pressure homogenization. A lipid recovery of 92.6% was also obtained by the combined process. The combined process was found to be more efficient and economical compared with the individual process. PMID:25853267

  19. Combined Enzymatic and Mechanical Cell Disruption and Lipid Extraction of Green Alga Neochloris oleoabundans

    Directory of Open Access Journals (Sweden)

    Dongqin Wang

    2015-04-01

    Full Text Available Microalgal biodiesel is one of the most promising renewable fuels. The wet technique for lipids extraction has advantages over the dry method, such as energy-saving and shorter procedure. The cell disruption is a key factor in wet oil extraction to facilitate the intracellular oil release. Ultrasonication, high-pressure homogenization, enzymatic hydrolysis and the combination of enzymatic hydrolysis with high-pressure homogenization and ultrasonication were employed in this study to disrupt the cells of the microalga Neochloris oleoabundans. The cell disruption degree was investigated. The cell morphology before and after disruption was assessed with scanning and transmission electron microscopy. The energy requirements and the operation cost for wet cell disruption were also estimated. The highest disruption degree, up to 95.41%, assessed by accounting method was achieved by the combination of enzymatic hydrolysis and high-pressure homogenization. A lipid recovery of 92.6% was also obtained by the combined process. The combined process was found to be more efficient and economical compared with the individual process.

  20. Combined radiolysis/GLC as a tool for the investigation of stabilizing mechanisms

    International Nuclear Information System (INIS)

    Koch, J.; Eckert, W.R.

    1977-01-01

    Combined radiolysis/GLC was used to prove the chemical incorporation of lauric acid from cadmium laurate into polyvinyl chloride. The samples were exposed for 10 days to x-rays at a dose rate of 0.345 Mrad/hr

  1. Combined centralised and distributed mechanism for utilisation of node association in broadband wireless network

    Science.gov (United States)

    Ulvan, A.; Ulvan, M.; Pranoto, H.

    2018-02-01

    Mobile broadband wireless access system has the stations that might be fixed, nomadic or mobile. Regarding the mobility, the node association procedure is critical for network entry as well as network re-entry during handover. The flexibility and utilisation of MAC protocols scheduling have an important role. The standard provides the Partition Scheme as the scheduling mechanism which separates the allocation of minislots for scheduling. However, minislots cannot be flexibly reserved for centralised and distributed scheduling. In this paper we analysed the scheduling mechanism to improve the utilisation of minislots allocation during the exchange of MAC massages. The centralised and distributed scheduling is implemented in some topology scenarios. The result shows the proposed mechanism has better performance for node association than partition scheme.

  2. Effects of Online Synchronous Instruction with an Attention Monitoring and Alarm Mechanism on Sustained Attention and Learning Performance

    Science.gov (United States)

    Chen, Chih-Ming; Wang, Jung-Ying

    2018-01-01

    Many studies have shown that learners' sustained attention strongly affects e-learning performance, particularly during online synchronous instruction. This work thus develops a novel attention monitoring and alarm mechanism (AMAM) based on brainwave signals to improve learning performance via monitoring the attention state of individual learners…

  3. Implementation of a Modular Hands-on Learning Pedagogy: Student Attitudes in a Fluid Mechanics and Heat Transfer Course

    Science.gov (United States)

    Burgher, J. K.; Finkel, D.; Adesope, O. O.; Van Wie, B. J.

    2015-01-01

    This study used a within-subjects experimental design to compare the effects of learning with lecture and hands-on desktop learning modules (DLMs) in a fluid mechanics and heat transfer class. The hands-on DLM implementation included the use of worksheets and one of two heat exchangers: an evaporative cooling device and a shell and tube heat…

  4. Underlying mechanisms of mistreatment in the surgical learning environment: A thematic analysis of medical student perceptions.

    Science.gov (United States)

    Brandford, Elena; Hasty, Brittany; Bruce, Janine S; Bereknyei Merrell, Sylvia; Shipper, Edward S; Lin, Dana T; Lau, James N

    2018-02-01

    Medical students experience more psychological distress than the general population. One contributing factor is mistreatment. This study aims to understand the mechanisms of mistreatment as perceived by medical students. Students completed anonymous surveys during the first and last didactic session of their surgery clerkship in which they defined and gave examples of mistreatment. Team-based thematic analysis was performed on responses. Between January 2014 and June 2016, 240 students participated in the surgery clerkship. Eighty-nine percent of students completed a survey. Themes observed included (1) Obstruction of Students' Learning, (2) Exploitation of Student Vulnerability, (3) Exclusion from the Medical Team, and (4) Contextual Amplifiers of Mistreatment Severity. The themes observed in this study improve our understanding of the students' perspective on mistreatment as it relates to their role in the clinical learning context, which can serve as a starting point for interventions that ultimately improve students' experiences in the clinical setting. Copyright © 2017 Elsevier Inc. All rights reserved.

  5. Angular distribution of electrons ejected by charged particles. IV. Combined classical and quantum-mechanical treatment

    NARCIS (Netherlands)

    Boesten, L.G.J.; Bonsen, T.F.M.

    1975-01-01

    Angular distributions of electrons ejected from helium by 100 and 300 keV protons have been calculated by a method which is a comination of the classical three-body collision theory and the quantum-mechanical Born approximation. The results of this theory have been compared with the corresponding

  6. Void coalescence mechanism for combined tension and large amplitude cyclic shearing

    DEFF Research Database (Denmark)

    Nielsen, Kim Lau; Andersen, Rasmus Grau; Tvergaard, Viggo

    2017-01-01

    Void coalescence at severe shear deformation has been studied intensively under monotonic loading conditions, and the sequence of micro-mechanisms that governs failure has been demonstrated to involve collapse, rotation, and elongation of existing voids. Under intense shearing, the voids are flat...

  7. Reduction of absorption loss in multicrystalline silicon via combination of mechanical grooving and porous silicon

    Energy Technology Data Exchange (ETDEWEB)

    Ben Rabha, Mohamed; Mohamed, Seifeddine Belhadj; Dimassi, Wissem; Gaidi, Mounir; Ezzaouia, Hatem; Bessais, Brahim [Laboratoire de Photovoltaique, Centre de Recherches et des Technologies de l' Energie, Technopole de Borj-Cedria, BP 95, 2050 Hammam-Lif (Tunisia)

    2011-03-15

    Surface texturing of silicon wafer is a key step to enhance light absorption and to improve the solar cell performances. While alkaline-texturing of single crystalline silicon wafers was well established, no efficient chemical solution has been successfully developed for multicrystalline silicon wafers. Thus, the use of alternative new methods for effective texturization of multicrystalline silicon is worth to be investigated. One of the promising texturing techniques of multicrystalline silicon wafers is the use of mechanical grooves. However, most often, physical damages occur during mechanical grooves of the wafer surface, which in turn require an additional step of wet processing-removal damage. Electrochemical surface treatment seems to be an adequate solution for removing mechanical damage throughout porous silicon formation. The topography of untreated and porous silicon-treated mechanically textured surface was investigated using scanning electron microscopy (SEM). As a result of the electrochemical surface treatment, the total reflectivity drops to about 5% in the 400-1000 nm wavelength range and the effective minority carrier diffusion length enhances from 190 {mu}m to about 230 {mu}m (copyright 2011 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim) (orig.)

  8. Investigation of combined effect of mixture variables on mechanical properties of cement treated demolition waste

    NARCIS (Netherlands)

    Xuan, D.; Houben, L.J.M.; Molenaar, A.A.A.; Shui, Z.

    2012-01-01

    One of high efficient ways to reuse the recycled construction and demolition waste (CDW) is to consider it as a road base material. The recycled CDW however is mainly a mix of recycled masonry and concrete with a wide variation in composition. This results that the mechanical properties of cement

  9. Combination oral and mechanical bowel preparations decreases complications in both right and left colectomy.

    Science.gov (United States)

    Midura, Emily F; Jung, Andrew D; Hanseman, Dennis J; Dhar, Vikrom; Shah, Shimul A; Rafferty, Janice F; Davis, Bradley R; Paquette, Ian M

    2018-03-01

    Before elective colectomy, many advocate mechanical bowel preparation with oral antibiotics, whereas enhanced recovery pathways avoid mechanical bowel preparations. The optimal preparation for right versus left colectomy is also unclear. We sought to determine which strategy for bowel preparation decreases surgical site infection (SSI) and anastomotic leak (AL). Elective colectomies from the National Surgical Quality Improvement Program colectomy database (2012-2015) were divided by (1) type of bowel preparation: no preparation (NP), mechanical preparation (MP), oral antibiotics (PO), or mechanical and oral antibiotics (PO/MP); and (2) type of colonic resection: right, left, or segmental colectomy. Univariate and multivariate analyses identified predictors of SSI and AL, and their risk-adjusted incidence was determined by logistic regression. When analyzed as the odds ratio compared with NP, the PO and PO/MP groups were associated with a decrease in SSI (PO = 0.70 [0.55-0.88] and PO/MP = 0.47 [0.42-0.53]; P < .01). Use of PO/MP was associated with a decrease in SSI across all types of resections (right colectomy = 0.40 [0.33-0.50], left colectomy = 0.57 [0.47-0.68], and segmental colectomy = 0.43 (0.34-0.54); P < .01). Similarly, use of PO/MP was associated with a decrease in AL in left colectomy = 0.50 ([0.37-0.69]; P < .01) and segmental colectomy = 0.53 ([0.36-0.80]; P < .01). Mechanical bowel preparation with oral antibiotics is the preferred preoperative preparation strategy in elective colectomy because of decreased incidence of SSI and AL. Copyright © 2017 Elsevier Inc. All rights reserved.

  10. Learning from doing: the case for combining normalisation process theory and participatory learning and action research methodology for primary healthcare implementation research.

    Science.gov (United States)

    de Brún, Tomas; O'Reilly-de Brún, Mary; O'Donnell, Catherine A; MacFarlane, Anne

    2016-08-03

    The implementation of research findings is not a straightforward matter. There are substantive and recognised gaps in the process of translating research findings into practice and policy. In order to overcome some of these translational difficulties, a number of strategies have been proposed for researchers. These include greater use of theoretical approaches in research focused on implementation, and use of a wider range of research methods appropriate to policy questions and the wider social context in which they are placed. However, questions remain about how to combine theory and method in implementation research. In this paper, we respond to these proposals. Focussing on a contemporary social theory, Normalisation Process Theory, and a participatory research methodology, Participatory Learning and Action, we discuss the potential of their combined use for implementation research. We note ways in which Normalisation Process Theory and Participatory Learning and Action are congruent and may therefore be used as heuristic devices to explore, better understand and support implementation. We also provide examples of their use in our own research programme about community involvement in primary healthcare. Normalisation Process Theory alone has, to date, offered useful explanations for the success or otherwise of implementation projects post-implementation. We argue that Normalisation Process Theory can also be used to prospectively support implementation journeys. Furthermore, Normalisation Process Theory and Participatory Learning and Action can be used together so that interventions to support implementation work are devised and enacted with the expertise of key stakeholders. We propose that the specific combination of this theory and methodology possesses the potential, because of their combined heuristic force, to offer a more effective means of supporting implementation projects than either one might do on its own, and of providing deeper understandings of

  11. Multi-Drug Resistance Transporters and a Mechanism-Based Strategy for Assessing Risks of Pesticide Combinations to Honey Bees.

    Science.gov (United States)

    Guseman, Alex J; Miller, Kaliah; Kunkle, Grace; Dively, Galen P; Pettis, Jeffrey S; Evans, Jay D; vanEngelsdorp, Dennis; Hawthorne, David J

    2016-01-01

    Annual losses of honey bee colonies remain high and pesticide exposure is one possible cause. Dangerous combinations of pesticides, plant-produced compounds and antibiotics added to hives may cause or contribute to losses, but it is very difficult to test the many combinations of those compounds that bees encounter. We propose a mechanism-based strategy for simplifying the assessment of combinations of compounds, focusing here on compounds that interact with xenobiotic handling ABC transporters. We evaluate the use of ivermectin as a model substrate for these transporters. Compounds that increase sensitivity of bees to ivermectin may be inhibiting key transporters. We show that several compounds commonly encountered by honey bees (fumagillin, Pristine, quercetin) significantly increased honey bee mortality due to ivermectin and significantly reduced the LC50 of ivermectin suggesting that they may interfere with transporter function. These inhibitors also significantly increased honey bees sensitivity to the neonicotinoid insecticide acetamiprid. This mechanism-based strategy may dramatically reduce the number of tests needed to assess the possibility of adverse combinations among pesticides. We also demonstrate an in vivo transporter assay that provides physical evidence of transporter inhibition by tracking the dynamics of a fluorescent substrate of these transporters (Rhodamine B) in bee tissues. Significantly more Rhodamine B remains in the head and hemolymph of bees pretreated with higher concentrations of the transporter inhibitor verapamil. Mechanism-based strategies for simplifying the assessment of adverse chemical interactions such as described here could improve our ability to identify those combinations that pose significantly greater risk to bees and perhaps improve the risk assessment protocols for honey bees and similar sensitive species.

  12. Antifungal mechanism of the combination of Cinnamomum verum and Pelargonium graveolens essential oils with fluconazole against pathogenic Candida strains.

    Science.gov (United States)

    Essid, Rym; Hammami, Majdi; Gharbi, Dorra; Karkouch, Ines; Hamouda, Thouraya Ben; Elkahoui, Salem; Limam, Ferid; Tabbene, Olfa

    2017-09-01

    The present study aimed to investigate the anti-Candida activity of ten essential oils (EOs) and to evaluate their potential synergism with conventional drugs. The effect on secreted aspartic protease (SAP) activity and the mechanism of action were also explored. The antifungal properties of essential oils were investigated using standard micro-broth dilution assay. Only Cinnamomum verum, Thymus capitatus, Syzygium aromaticum, and Pelargonium graveolens exhibited a broad spectrum of activity against a variety of pathogenic Candida strains. Chemical composition of active essential oils was performed by gas chromatography-mass spectrometry (GC-MS). Synergistic effect was observed with the combinations C. verum/fluconazole and P. graveolens/fluconazole, with FIC value 0.37. Investigation of the mechanism of action revealed that C. verum EO reduced the quantity of ergosterol to 83%. A total inhibition was observed for the combination C. verum/fluconazole. However, P. graveolens EO may disturb the permeability barrier of the fungal cell wall. An increase of MIC values of P. graveolens EO and the combination with fluconazole was observed with osmoprotectants (sorbitol and PEG6000). Furthermore, the combination with fluconazole may affect ergosterol biosynthesis and disturb fatty acid homeostasis in C. albicans cells as the quantity of ergosterol and oleic acid was reduced to 52.33 and 72%, respectively. The combination of P. graveolens and C. verum EOs with fluconazole inhibited 78.31 and 64.72% SAP activity, respectively. To our knowledge, this is the first report underlying the mechanism of action and the inhibitory effect of SAP activity of essential oils in synergy with fluconazole. Naturally occurring phytochemicals C. verum and P. graveolens could be effective candidate to enhance the efficacy of fluconazole-based therapy of C. albicans infections.

  13. Examining Change in Metacognitive Knowledge and Metacognitive Control During Motor Learning: What Can be Learned by Combining Methodological Approaches?

    Directory of Open Access Journals (Sweden)

    Claire Sangster Jokić

    2014-04-01

    Full Text Available Growing recognition of the importance of understanding metacognitive behaviour as it occurs in everyday learning situations has prompted an expansion of the methodological approaches used to examine metacognition. This becomes especially pertinent when examining the process of metacognitive change, where 'on-line' observational approaches able to capture metacognitive performance as it occurs during socially-mediated learning are being increasingly applied. This study applied a mixed methods approach to examine children's metacognitive performance as it was exhibited during participation in an intervention program aimed at addressing motor performance difficulties. Participants in the study were ten 7-9 year old children with developmental coordination disorder (DCD, a condition characterized by poor motor coordination and difficulty acquiring motor-based tasks. All participants engaged in a 10-session program in which children were taught to use a problem-solving strategy for addressing motor performance difficulties. To examine children's metacognitive performance, sessions were video-taped and subsequently analysed using a quantitative observational coding method and an in-depth qualitative review of therapist-child interactions. This allowed for a fine-grained analysis of children's demonstration of metacognitive knowledge and control and how such performance evolved over the course of the program. Of particular interest was the finding that while children were often able to express task-specific knowledge, they failed to apply this knowledge during practice. Conversely, children were often able to demonstrate performance-based evidence for metacognitive control but were not able to make conscious reports of such skill following practice. This finding is consistent with models of metacognitive development which suggest that the emergence of performance-based metacognitive skills precede the ability for the conscious expression of

  14. Effect and Mechanism of Mitomycin C Combined with Recombinant Adeno-Associated Virus Type II against Glioma

    Directory of Open Access Journals (Sweden)

    Hong Ma

    2013-12-01

    Full Text Available The effect of chemotherapy drug Mitomycin C (MMC in combination with recombinant adeno-associated virus II (rAAV2 in cancer therapy was investigated, and the mechanism of MMC affecting rAAV2’s bioactivity was also studied. The combination effect was evaluated by the level of GFP and TNF expression in a human glioma cell line, and the mechanism of MMC effects on rAAV mediated gene expression was investigated by AAV transduction related signal molecules. C57 and BALB/c nude mice were injected with rAAV-EGFP or rAAV-TNF alone, or mixed with MMC, to evaluate the effect of MMC on AAV-mediated gene expression and tumor suppression. MMC was shown to improve the infection activity of rAAV2 both in vitro and in vivo. Enhancement was found to be independent of initial rAAV2 receptor binding stage or subsequent second-strand synthesis of target DNA, but was related to cell cycle retardation followed by blocked genome degradation. In vivo injection of MMC combined with rAAV2 into the tumors of the animals resulted in significant suppression of tumor growth. It was thus demonstrated for the first time that MMC could enhance the expression level of the target gene mediated by rAAV2. The combination of rAAV2 and MMC may be a promising strategy in cancer therapy.

  15. Designing instruction to support mechanical reasoning: Three alternatives in the simple machines learning environment

    Science.gov (United States)

    McKenna, Ann Frances

    2001-07-01

    Creating a classroom environment that fosters a productive learning experience and engages students in the learning process is a complex endeavor. A classroom environment is dynamic and requires a unique synergy among students, teacher, classroom artifacts and events to achieve robust understanding and knowledge integration. This dissertation addresses this complex issue by developing, implementing, and investigating the simple machines learning environment (SIMALE) to support students' mechanical reasoning and understanding. SIMALE was designed to support reflection, collaborative learning, and to engage students in generative learning through multiple representations of concepts and successive experimentation and design activities. Two key components of SIMALE are an original web-based software tool and hands-on Lego activities. A research study consisting of three treatment groups was created to investigate the benefits of hands-on and web-based computer activities on students' analytic problem solving ability, drawing/modeling ability, and conceptual understanding. The study was conducted with two populations of students that represent a diverse group with respect to gender, ethnicity, academic achievement and social/economic status. One population of students in this dissertation study participated from the Mathematics, Engineering, and Science Achievement (MESA) program that serves minorities and under-represented groups in science and mathematics. The second group was recruited from the Academic Talent Development Program (ATDP) that is an academically competitive outreach program offered through the University of California at Berkeley. Results from this dissertation show success of the SIMALE along several dimensions. First, students in both populations achieved significant gains in analytic problem solving ability, drawing/modeling ability, and conceptual understanding. Second, significant differences that were found on pre-test measures were eliminated

  16. Transport mechanism of an initially spherical droplet on a combined hydrophilic/hydrophobic surface

    Energy Technology Data Exchange (ETDEWEB)

    Myong, Hyon Kook; Kwon, Young Hoo [Dept. of Mechanical Engineering, Kookmin University, Seoul (Korea, Republic of)

    2015-11-15

    Fluid transport is a key issue in the development of microfluidic systems. Recently, Myong (2014) has proposed a new concept for droplet transport without external power sources, and numerically validated the results for a hypothetical 2D shape, initially having a hemicylindrical droplet shape. Myong and Kwon (2015) have also examined the transport mechanism for an actual water droplet, initially having a 3D hemispherical shape, on a horizontal hydrophilic/hydrophobic surface, based on the numerical results of the time evolution of the droplet shape, as well as the total kinetic, gravitational, pressure and surface free energies inside the droplet. In this study, a 3D numerical analysis of an initially spherical droplet is carried out to establish a new concept for droplet transport. Further, the transport mechanism of an actual water droplet is examined in detail from the viewpoint of the capillarity force imbalance through the numerical results of droplet shape and various energies inside the droplet.

  17. Controller design for flexible, distributed parameter mechanical arms via combined state space and frequency domain techniques

    Science.gov (United States)

    Book, W. J.; Majett, M.

    1982-01-01

    The potential benefits of the ability to control more flexible mechanical arms are discussed. A justification is made in terms of speed of movement. A new controller design procedure is then developed to provide this capability. It uses both a frequency domain representation and a state variable representation of the arm model. The frequency domain model is used to update the modal state variable model to insure decoupled states. The technique is applied to a simple example with encouraging results.

  18. Predicting human splicing branchpoints by combining sequence-derived features and multi-label learning methods.

    Science.gov (United States)

    Zhang, Wen; Zhu, Xiaopeng; Fu, Yu; Tsuji, Junko; Weng, Zhiping

    2017-12-01

    Alternative splicing is the critical process in a single gene coding, which removes introns and joins exons, and splicing branchpoints are indicators for the alternative splicing. Wet experiments have identified a great number of human splicing branchpoints, but many branchpoints are still unknown. In order to guide wet experiments, we develop computational methods to predict human splicing branchpoints. Considering the fact that an intron may have multiple branchpoints, we transform the branchpoint prediction as the multi-label learning problem, and attempt to predict branchpoint sites from intron sequences. First, we investigate a variety of intron sequence-derived features, such as sparse profile, dinucleotide profile, position weight matrix profile, Markov motif profile and polypyrimidine tract profile. Second, we consider several multi-label learning methods: partial least squares regression, canonical correlation analysis and regularized canonical correlation analysis, and use them as the basic classification engines. Third, we propose two ensemble learning schemes which integrate different features and different classifiers to build ensemble learning systems for the branchpoint prediction. One is the genetic algorithm-based weighted average ensemble method; the other is the logistic regression-based ensemble method. In the computational experiments, two ensemble learning methods outperform benchmark branchpoint prediction methods, and can produce high-accuracy results on the benchmark dataset.

  19. The Effects of Alkyl Chain Combinations on the Structural and Mechanical Properties of Biomimetic Ion Pair Amphiphile Bilayers

    Directory of Open Access Journals (Sweden)

    Cheng-hao Chen

    2017-10-01

    Full Text Available Ion pair amphiphile (IPA, a lipid-like complex composed of a pair of cationic and anionic surfactants, has great potentials in various pharmaceutical applications. In this work, we utilized molecular dynamics (MD simulation to systematically examine the structural and mechanical properties of the biomimetic bilayers consist of alkyltrimethyl-ammonium-alkylsulfate (CmTMA+-CnS− IPAs with various alkyl chain combinations. Our simulations show an intrinsic one-atom offset for the CmTMA+ and CnS− alignment, leading to the asymmetric index definition of ΔC = m − (n + 1. Larger |ΔC| gives rise to higher conformational fluctuations of the alkyl chains with the reduced packing order and mechanical strength. In contrast, increasing the IPA chain length enhances the van der Waals interactions within the bilayer and thus improves the bilayer packing order and mechanical properties. Further elongating the CmTMA+-CnS− alkyl chains to m and n ≥ 12 causes the liquid disorder to gel phase transition of the bilayer at 298 K, with the threshold membrane properties of 0.45 nm2 molecular area, deuterium order parameter value of 0.31, and effective bending rigidity of 20 kBT, etc. The combined results provide molecular insights into the design of biomimetic IPA bilayers with wide structural and mechanical characteristics for various applications.

  20. Investigation of surface properties and adhesion mechanisms in the combination of different layers, with the aid of surface analysis methods

    International Nuclear Information System (INIS)

    Olschewski, T.

    1991-01-01

    The aim of the investigations was to characterize the surface properties of organic coating materials and inorganic substrates, which are relevant in the context of microstructure technique developments and to obtain information on the adhesion mechanisms present. Two systems were examined which play an important part in micro-technique, i.e.: for the LIGA process and in the development of micro-sensors based on Chem FET's for chemical analysis. For these systems, i.e.: PMMA/TiO 2 and PVC adipate/Si 3 N 4 , adhesion mechanisms were expected, which occur particularly frequently in adhesive combination of polymers with inorganic substrates, i.e.: the mechanical gearing between polymer molecules and substrate structures and a chemical interaction between the boundary layers of the organic top coating and the inorganic substrate. (orig./DG) [de

  1. Predictive information processing is a fundamental learning mechanism present in early development: evidence from infants.

    Science.gov (United States)

    Trainor, Laurel J

    2012-02-01

    Evidence is presented that predictive coding is fundamental to brain function and present in early infancy. Indeed, mismatch responses to unexpected auditory stimuli are among the earliest robust cortical event-related potential responses, and have been measured in young infants in response to many types of deviation, including in pitch, timing, and melodic pattern. Furthermore, mismatch responses change quickly with specific experience, suggesting that predictive coding reflects a powerful, early-developing learning mechanism. Copyright © 2011 Elsevier B.V. All rights reserved.

  2. Mechanisms of tramadol-related neurotoxicity in the rat: Does diazepam/tramadol combination play a worsening role in overdose?

    Energy Technology Data Exchange (ETDEWEB)

    Lagard, Camille, E-mail: camille.lagard@gmail.com [Inserm, U1144, Paris (France); UMR-S 1144, Paris-Descartes University, Paris (France); UMR-S 1144, Paris-Diderot University, Paris (France); Chevillard, Lucie, E-mail: luciechevillard@gmail.com [Inserm, U1144, Paris (France); UMR-S 1144, Paris-Descartes University, Paris (France); UMR-S 1144, Paris-Diderot University, Paris (France); Malissin, Isabelle, E-mail: isabellemalissin@gmail.com [Assistance Publique – Hôpitaux de Paris, Lariboisière Hospital, Department of Medical and Toxicological Critical Care, Paris (France); Risède, Patricia, E-mail: patricia.risede@inserm.fr [Inserm, U1144, Paris (France); UMR-S 1144, Paris-Descartes University, Paris (France); UMR-S 1144, Paris-Diderot University, Paris (France); Callebert, Jacques, E-mail: jacques.callebert@aphp.fr [Inserm, U1144, Paris (France); UMR-S 1144, Paris-Descartes University, Paris (France); UMR-S 1144, Paris-Diderot University, Paris (France); Assistance Publique – Hôpitaux de Paris, Lariboisière Hospital, Laboratory of Biochemistry and Molecular Biology, Paris (France); Labat, Laurence, E-mail: laurence.labat@aphp.fr [Inserm, U1144, Paris (France); UMR-S 1144, Paris-Descartes University, Paris (France); UMR-S 1144, Paris-Diderot University, Paris (France); Assistance Publique – Hôpitaux de Paris, Cochin Hospital, Laboratory of Toxicology, Paris (France); Launay, Jean-Marie, E-mail: jean-marie.launay@aphp.fr [Assistance Publique – Hôpitaux de Paris, Lariboisière Hospital, Laboratory of Biochemistry and Molecular Biology, Paris (France); Inserm, U942, Paris (France); and others

    2016-11-01

    Poisoning with opioid analgesics including tramadol represents a challenge. Tramadol may induce respiratory depression, seizures and serotonin syndrome, possibly worsened when in combination to benzodiazepines. Our objectives were to investigate tramadol-related neurotoxicity, consequences of diazepam/tramadol combination, and mechanisms of drug-drug interactions in rats. Median lethal-doses were determined using Dixon–Bruce's up-and-down method. Sedation, seizures, electroencephalography and plethysmography parameters were studied. Concentrations of tramadol and its metabolites were measured using liquid-chromatography-high-resolution-mass-spectrometry. Plasma, platelet and brain monoamines were measured using liquid-chromatography coupled to fluorimetry. Median lethal-doses of tramadol and diazepam/tramadol combination did not significantly differ, although time-to-death was longer with combination (P = 0.04). Tramadol induced dose-dependent sedation (P < 0.05), early-onset seizures (P < 0.001) and increase in inspiratory (P < 0.01) and expiratory times (P < 0.05). The diazepam/tramadol combination abolished seizures but significantly enhanced sedation (P < 0.01) and respiratory depression (P < 0.05) by reducing tidal volume (P < 0.05) in addition to tramadol-related increase in respiratory times, suggesting a pharmacodynamic mechanism of interaction. Plasma M1 and M5 metabolites were mildly increased, contributing additionally to tramadol-related respiratory depression. Tramadol-induced early-onset increase in brain concentrations of serotonin and norepinephrine was not significantly altered by the diazepam/tramadol combination. Interestingly neither pretreatment with cyproheptadine (a serotonin-receptor antagonist) nor a benserazide/5-hydroxytryptophane combination (enhancing brain serotonin) reduced tramadol-induced seizures. Our study shows that diazepam/tramadol combination does not worsen tramadol-induced fatality risk but alters its toxicity pattern

  3. Mechanisms of tramadol-related neurotoxicity in the rat: Does diazepam/tramadol combination play a worsening role in overdose?

    International Nuclear Information System (INIS)

    Lagard, Camille; Chevillard, Lucie; Malissin, Isabelle; Risède, Patricia; Callebert, Jacques; Labat, Laurence; Launay, Jean-Marie

    2016-01-01

    Poisoning with opioid analgesics including tramadol represents a challenge. Tramadol may induce respiratory depression, seizures and serotonin syndrome, possibly worsened when in combination to benzodiazepines. Our objectives were to investigate tramadol-related neurotoxicity, consequences of diazepam/tramadol combination, and mechanisms of drug-drug interactions in rats. Median lethal-doses were determined using Dixon–Bruce's up-and-down method. Sedation, seizures, electroencephalography and plethysmography parameters were studied. Concentrations of tramadol and its metabolites were measured using liquid-chromatography-high-resolution-mass-spectrometry. Plasma, platelet and brain monoamines were measured using liquid-chromatography coupled to fluorimetry. Median lethal-doses of tramadol and diazepam/tramadol combination did not significantly differ, although time-to-death was longer with combination (P = 0.04). Tramadol induced dose-dependent sedation (P < 0.05), early-onset seizures (P < 0.001) and increase in inspiratory (P < 0.01) and expiratory times (P < 0.05). The diazepam/tramadol combination abolished seizures but significantly enhanced sedation (P < 0.01) and respiratory depression (P < 0.05) by reducing tidal volume (P < 0.05) in addition to tramadol-related increase in respiratory times, suggesting a pharmacodynamic mechanism of interaction. Plasma M1 and M5 metabolites were mildly increased, contributing additionally to tramadol-related respiratory depression. Tramadol-induced early-onset increase in brain concentrations of serotonin and norepinephrine was not significantly altered by the diazepam/tramadol combination. Interestingly neither pretreatment with cyproheptadine (a serotonin-receptor antagonist) nor a benserazide/5-hydroxytryptophane combination (enhancing brain serotonin) reduced tramadol-induced seizures. Our study shows that diazepam/tramadol combination does not worsen tramadol-induced fatality risk but alters its toxicity pattern

  4. Additively manufactured metallic porous biomaterials based on minimal surfaces: A unique combination of topological, mechanical, and mass transport properties.

    Science.gov (United States)

    Bobbert, F S L; Lietaert, K; Eftekhari, A A; Pouran, B; Ahmadi, S M; Weinans, H; Zadpoor, A A

    2017-04-15

    Porous biomaterials that simultaneously mimic the topological, mechanical, and mass transport properties of bone are in great demand but are rarely found in the literature. In this study, we rationally designed and additively manufactured (AM) porous metallic biomaterials based on four different types of triply periodic minimal surfaces (TPMS) that mimic the properties of bone to an unprecedented level of multi-physics detail. Sixteen different types of porous biomaterials were rationally designed and fabricated using selective laser melting (SLM) from a titanium alloy (Ti-6Al-4V). The topology, quasi-static mechanical properties, fatigue resistance, and permeability of the developed biomaterials were then characterized. In terms of topology, the biomaterials resembled the morphological properties of trabecular bone including mean surface curvatures close to zero. The biomaterials showed a favorable but rare combination of relatively low elastic properties in the range of those observed for trabecular bone and high yield strengths exceeding those reported for cortical bone. This combination allows for simultaneously avoiding stress shielding, while providing ample mechanical support for bone tissue regeneration and osseointegration. Furthermore, as opposed to other AM porous biomaterials developed to date for which the fatigue endurance limit has been found to be ≈20% of their yield (or plateau) stress, some of the biomaterials developed in the current study show extremely high fatigue resistance with endurance limits up to 60% of their yield stress. It was also found that the permeability values measured for the developed biomaterials were in the range of values reported for trabecular bone. In summary, the developed porous metallic biomaterials based on TPMS mimic the topological, mechanical, and physical properties of trabecular bone to a great degree. These properties make them potential candidates to be applied as parts of orthopedic implants and/or as bone

  5. Towards Automatic Learning of Heuristics for Mechanical Transformations of Procedural Code

    Directory of Open Access Journals (Sweden)

    Guillermo Vigueras

    2017-01-01

    Full Text Available The current trends in next-generation exascale systems go towards integrating a wide range of specialized (co-processors into traditional supercomputers. Due to the efficiency of heterogeneous systems in terms of Watts and FLOPS per surface unit, opening the access of heterogeneous platforms to a wider range of users is an important problem to be tackled. However, heterogeneous platforms limit the portability of the applications and increase development complexity due to the programming skills required. Program transformation can help make programming heterogeneous systems easier by defining a step-wise transformation process that translates a given initial code into a semantically equivalent final code, but adapted to a specific platform. Program transformation systems require the definition of efficient transformation strategies to tackle the combinatorial problem that emerges due to the large set of transformations applicable at each step of the process. In this paper we propose a machine learning-based approach to learn heuristics to define program transformation strategies. Our approach proposes a novel combination of reinforcement learning and classification methods to efficiently tackle the problems inherent to this type of systems. Preliminary results demonstrate the suitability of this approach.

  6. Naringenin improves learning and memory in an Alzheimer's disease rat model: Insights into the underlying mechanisms.

    Science.gov (United States)

    Ghofrani, Saeed; Joghataei, Mohammad-Taghi; Mohseni, Simin; Baluchnejadmojarad, Tourandokht; Bagheri, Maryam; Khamse, Safoura; Roghani, Mehrdad

    2015-10-05

    Alzheimer's disease (AD) is one of the prevalent neurological disorders of the central nervous system hallmarked by increased beta-amyloid (Aβ) deposition and ensuing learning and memory deficit. In the present study, the beneficial effect of naringenin on improvement of learning and memory was evaluated in an Alzheimer's disease rat model. The Aβ-injected rats showed a lower alternation score in Y-maze task, impairment of retention and recall capability in passive avoidance test, and lower correct choices and higher errors in radial arm maze (RAM) task as compared to sham group in addition to enhanced oxidative stress and apoptosis. Naringenin, but not a combination of naringenin and fulvestrant (an estrogenic receptor antagonist) significantly improved the performance of Aβ-injected rats in passive avoidance and RAM tasks. Naringenin pretreatment of Aβ-injected rats also lowered hippocampal malondialdehyde (MDA) with no significant effect on nitrite and superoxide dismutase (SOD) activity in addition to lowering apoptosis. These results suggest naringenin pretreatment attenuates Aβ-induced impairment of learning and memory through mitigation of lipid peroxidation and apoptosis and its beneficial effect is somewhat mediated via estrogenic pathway. Copyright © 2015 Elsevier B.V. All rights reserved.

  7. [Synergism inhibition of curcumin combined with cisplatin on T24 bladder carcinoma cells and its related mechanism].

    Science.gov (United States)

    Zhang, Shao-nan; Yong, Qun; Wu, Xin-li; Liu, Xiao-ping

    2014-11-01

    To investigate the synergism inhibition of curcumin combined with cisplatin on T24 bladder carcinoma cells and the down-regulating effect of curcumin on the Keapl-Nrf2 pathway, a well recognized anti-drug pathway in almost drugged tumor cells. T24 cells were cultured and treated with increasing concentrations of curcumin(5 ,10 and 20 µmol/mL) combined with cisplatin(30 µg/mL) for 24 hours. The inhibitory effects on T24 cells were tested with MTI colorimetric assay. Nuclear Nrf2 and Keapl , cytoplasmic Keapl and two typical phase II enzymes (GSTP1 and NQOl) were checked with Western blotting. The proliferation of T24 cells was significantly inhibited by different concentrations of curcumin combined with cisplatin. After the treatment with different concentrations of curcumin, Nuclear Nrf2 was decreased but Keapl was increased, and GSTP1 and NQO1 were decreased. Synergism inhibition of curcumin combined with cisplatin on T24 bladder carcinoma cells is observed in this research. The Keapl-Nrf2 pathway in T24 cells is down-regulated by curcumin. The expression of typical phase I enzymes (GSTP1 and NQO1) mediated by Nrf2 are decreased by curcumin. The sensitivity of tumor cells to chemotherapeutic drugs is then enhanced. These may be the mechanism of synergism effect of curcumin combined with cisplatin.

  8. Combining brain stimulation and video game to promote long-term transfer of learning and cognitive enhancement.

    Science.gov (United States)

    Looi, Chung Yen; Duta, Mihaela; Brem, Anna-Katharine; Huber, Stefan; Nuerk, Hans-Christoph; Cohen Kadosh, Roi

    2016-02-23

    Cognitive training offers the potential for individualised learning, prevention of cognitive decline, and rehabilitation. However, key research challenges include ecological validity (training design), transfer of learning and long-term effects. Given that cognitive training and neuromodulation affect neuroplasticity, their combination could promote greater, synergistic effects. We investigated whether combining transcranial direct current stimulation (tDCS) with cognitive training could further enhance cognitive performance compared to training alone, and promote transfer within a short period of time. Healthy adults received real or sham tDCS over their dorsolateral prefrontal cortices during two 30-minute mathematics training sessions involving body movements. To examine the role of training, an active control group received tDCS during a non-mathematical task. Those who received real tDCS performed significantly better in the game than the sham group, and showed transfer effects to working memory, a related but non-numerical cognitive domain. This transfer effect was absent in active and sham control groups. Furthermore, training gains were more pronounced amongst those with lower baseline cognitive abilities, suggesting the potential for reducing cognitive inequalities. All effects associated with real tDCS remained 2 months post-training. Our study demonstrates the potential benefit of this approach for long-term enhancement of human learning and cognition.

  9. Exploration of problem-based learning combined with standardized patient in the teaching of basic science of ophthalmology

    Directory of Open Access Journals (Sweden)

    Jin Yan

    2015-08-01

    Full Text Available AIM:To investigate the effect of problem-based learning(PBLcombined with standardized patient(SPin the teaching of basic science of ophthalmology. METHODS: Sixty-four students of Optometry in grade 2012 were randomly divided into experimental group(n=32and control group(n=32. Traditional teaching method was implemented in control group while PBL combined with SP was applied in experimental group. At the end of term students were interviewed using self-administered questionnaire to obtain their evaluation for teaching effect. Measurement data were expressed as (-overx±s and analyzed by independent samples t test. Enumeration data were analyzed by χ2 test, and PRESULTS:The mean scores of theory test(83.22±3.75and experimental test(94.28±2.20in experimental group were significantly higher than theory test(70.72±3.95and experimental test(85.44±3.52in control group(all PPPCONCLUSION:Using PBL combined with SP teaching mode in basic science of ophthalmology can highly improve learning enthusiasm of students and cultivate self-learning ability of students, practice ability and ability of clinical analysis.

  10. E-learning optimization: the relative and combined effects of mental practice and modeling on enhanced podcast-based learning-a randomized controlled trial.

    Science.gov (United States)

    Alam, Fahad; Boet, Sylvain; Piquette, Dominique; Lai, Anita; Perkes, Christopher P; LeBlanc, Vicki R

    2016-10-01

    Enhanced podcasts increase learning, but evidence is lacking on how they should be designed to optimize their effectiveness. This study assessed the impact two learning instructional design methods (mental practice and modeling), either on their own or in combination, for teaching complex cognitive medical content when incorporated into enhanced podcasts. Sixty-three medical students were randomised to one of four versions of an airway management enhanced podcast: (1) control: narrated presentation; (2) modeling: narration with video demonstration of skills; (3) mental practice: narrated presentation with guided mental practice; (4) combined: modeling and mental practice. One week later, students managed a manikin-based simulated airway crisis. Knowledge acquisition was assessed by baseline and retention multiple-choice quizzes. Two blinded raters assessed all videos obtained from simulated crises to measure the students' skills using a key-elements scale, critical error checklist, and the Ottawa global rating scale (GRS). Baseline knowledge was not different between all four groups (p = 0.65). One week later, knowledge retention was significantly higher for (1) both the mental practice and modeling group than the control group (p = 0.01; p = 0.01, respectively) and (2) the combined mental practice and modeling group compared to all other groups (all ps = 0.01). Regarding skills acquisition, the control group significantly under-performed in comparison to all other groups on the key-events scale (all ps ≤ 0.05), the critical error checklist (all ps ≤ 0.05), and the Ottawa GRS (all ps ≤ 0.05). The combination of mental practice and modeling led to greater improvement on the key events checklist (p = 0.01) compared to either strategy alone. However, the combination of the two strategies did not result in any further learning gains on the two other measures of clinical performance (all ps > 0.05). The effectiveness of enhanced podcasts for

  11. Optimal design of planar slider-crank mechanism using teaching-learning-based optimization algorithm

    International Nuclear Information System (INIS)

    Chaudhary, Kailash; Chaudhary, Himanshu

    2015-01-01

    In this paper, a two stage optimization technique is presented for optimum design of planar slider-crank mechanism. The slider crank mechanism needs to be dynamically balanced to reduce vibrations and noise in the engine and to improve the vehicle performance. For dynamic balancing, minimization of the shaking force and the shaking moment is achieved by finding optimum mass distribution of crank and connecting rod using the equipemental system of point-masses in the first stage of the optimization. In the second stage, their shapes are synthesized systematically by closed parametric curve, i.e., cubic B-spline curve corresponding to the optimum inertial parameters found in the first stage. The multi-objective optimization problem to minimize both the shaking force and the shaking moment is solved using Teaching-learning-based optimization algorithm (TLBO) and its computational performance is compared with Genetic algorithm (GA).

  12. Optimal design of planar slider-crank mechanism using teaching-learning-based optimization algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Chaudhary, Kailash; Chaudhary, Himanshu [Malaviya National Institute of Technology, Jaipur (Malaysia)

    2015-11-15

    In this paper, a two stage optimization technique is presented for optimum design of planar slider-crank mechanism. The slider crank mechanism needs to be dynamically balanced to reduce vibrations and noise in the engine and to improve the vehicle performance. For dynamic balancing, minimization of the shaking force and the shaking moment is achieved by finding optimum mass distribution of crank and connecting rod using the equipemental system of point-masses in the first stage of the optimization. In the second stage, their shapes are synthesized systematically by closed parametric curve, i.e., cubic B-spline curve corresponding to the optimum inertial parameters found in the first stage. The multi-objective optimization problem to minimize both the shaking force and the shaking moment is solved using Teaching-learning-based optimization algorithm (TLBO) and its computational performance is compared with Genetic algorithm (GA).

  13. Exploring Student-Generated Animations, Combined with a Representational Pedagogy, as a Tool for Learning in Chemistry

    Science.gov (United States)

    Yaseen, Zeynep; Aubusson, Peter

    2018-02-01

    This article describes an investigation into teaching and learning with student-generated animations combined with a representational pedagogy. In particular, it reports on interactive discussions that were stimulated by the students' own animations as well as their critiques of experts' animations. Animations representing views of states of matter provided a vehicle by which to investigate learning in a series of lessons. The study was implemented with Year 11 high school students. After students constructed, presented and discussed their animations, they watched and critiqued experts' animations. They were then interviewed about the teaching-learning process. Most students (91%) spoke positively about follow-up discussion classes, saying that their previous conceptions and understanding of states of matter had improved. They explained that they had identified some alternative conceptions, which they had held regarding states of matter and explained how their conceptions had changed. They reported that the teaching/learning process had helped them to develop a deeper understanding of the changing states of matter.

  14. Parametric Analysis and Experimental Verification of a Hybrid Vibration Energy Harvester Combining Piezoelectric and Electromagnetic Mechanisms

    Directory of Open Access Journals (Sweden)

    Zhenlong Xu

    2017-06-01

    Full Text Available Considering coil inductance and the spatial distribution of the magnetic field, this paper developed an approximate distributed-parameter model of a hybrid energy harvester (HEH. The analytical solutions were compared with numerical solutions. The effects of load resistances, electromechanical coupling factors, mechanical damping ratio, coil parameters and size scale on performance were investigated. A meso-scale HEH prototype was fabricated, tested and compared with a stand-alone piezoelectric energy harvester (PEH and a stand-alone electromagnetic energy harvester (EMEH. The peak output power is 2.93% and 142.18% higher than that of the stand-alone PEH and EMEH, respectively. Moreover, its bandwidth is 108%- and 122.7%-times that of the stand-alone PEH and EMEH, respectively. The experimental results agreed well with the theoretical values. It is indicated that the linearized electromagnetic coupling coefficient is more suitable for low-level excitation acceleration. Hybrid energy harvesting contributes to widening the frequency bandwidth and improving energy conversion efficiency. However, only when the piezoelectric coupling effect is weak or medium can the HEH generate more power than the single-mechanism energy harvester. Hybrid energy harvesting can improve output power even at the microelectromechanical systems (MEMS scale. This study presents a more effective model for the performance evaluation and structure optimization of the HEH.

  15. On combining principal components with Fisher's linear discriminants for supervised learning

    NARCIS (Netherlands)

    Pechenizkiy, M.; Tsymbal, A.; Puuronen, S.

    2006-01-01

    "The curse of dimensionality" is pertinent to many learning algorithms, and it denotes the drastic increase of computational complexity and classification error in high dimensions. In this paper, principal component analysis (PCA), parametric feature extraction (FE) based on Fisher’s linear

  16. The Learning Environment Associated with Information Technology Education in Taiwan: Combining Psychosocial and Physical Aspects

    Science.gov (United States)

    Liu, Chia-Ju; Zandvliet, David B.; Hou, I.-Ling

    2012-01-01

    This study investigated perceptions of senior high school students towards the Taiwanese information technology (IT) classroom with the What Is Happening in this Class? (WIHIC) survey and explored the physical learning environment of the IT classroom using the Computerised Classroom Environment Inventory (CCEI). The participants included 2,869…

  17. Patterns of Learning in Verbal Discrimination as an Interaction of Social Reinforcement and Sex Combinations

    Science.gov (United States)

    Ratliff, Richard G.; And Others

    1976-01-01

    A total of 540 college students were run in two verbal discrimination learning studies (the second, a replication of the first) with one of three verbal reward conditions. In both studies, equal numbers of male and female subjects were run in each reward condition by each male and female experimenter. (MS)

  18. Combining Feminist Pedagogy and Transactional Distance to Create Gender-Sensitive Technology-Enhanced Learning

    Science.gov (United States)

    Herman, Clem; Kirkup, Gill

    2017-01-01

    In this paper, we argue for a new synthesis of two pedagogic theories: feminist pedagogy and transactional distance, which explain why and how distance education has been such a positive system for women in a national distance learning university. We illustrate this with examples of positive action initiatives for women. The concept of…

  19. Combining Generative and Discriminative Representation Learning for Lung CT Analysis With Convolutional Restricted Boltzmann Machines

    NARCIS (Netherlands)

    G. van Tulder (Gijs); M. de Bruijne (Marleen)

    2016-01-01

    textabstractThe choice of features greatly influences the performance of a tissue classification system. Despite this, many systems are built with standard, predefined filter banks that are not optimized for that particular application. Representation learning methods such as restricted Boltzmann

  20. Games and Machine Learning: A Powerful Combination in an Artificial Intelligence Course

    Science.gov (United States)

    Wallace, Scott A.; McCartney, Robert; Russell, Ingrid

    2010-01-01

    Project MLeXAI [Machine Learning eXperiences in Artificial Intelligence (AI)] seeks to build a set of reusable course curriculum and hands on laboratory projects for the artificial intelligence classroom. In this article, we describe two game-based projects from the second phase of project MLeXAI: Robot Defense--a simple real-time strategy game…

  1. Effects of Integrating an Active Learning-Promoting Mechanism into Location-Based Real-World Learning Environments on Students' Learning Performances and Behaviors

    Science.gov (United States)

    Hwang, Gwo-Jen; Chang, Shao-Chen; Chen, Pei-Ying; Chen, Xiang-Ya

    2018-01-01

    Engaging students in real-world learning contexts has been identified by educators as being an important way of helping them learn to apply what they have learned from textbooks to practical problems. The advancements in mobile and image-processing technologies have enabled students to access learning resources and receive learning guidance in…

  2. Combined effect of radiation and environmental contaminants on DNA repair mechanisms

    International Nuclear Information System (INIS)

    Altmann, H.

    1975-11-01

    Investigations on the influence of various environmental contamination agents on DNA repair (in combination with irradiation) were reviewed. The agents tested were: detergents (Tween 80, Nonidel P40, Cremophor), aflatoxin B 1 , furocumarines, drugs (indometacin, cyclophosphamide, vincristine, vinblastine, procarbacine), fluorides, irradiated food constituents, food additives (saccharin), metal ions (Cd, Hg), pesticides (2,4,5-trichlorophenoxyethanol) and infective agents (mycoplasmas). Most of the tests were carried out in vitro with γ-irradiated mouse spleen cells. The detergents and aflatoxin were tested also on E. coli, and irradiated glucose solutions were tested in vivo on Swiss albino mice injected with Salmonella typhimurium TA 1530. Most of the tested agents showed some kind of inhibitory or mutagenic effect. The experiments and results are explained briefly with references to earlier investigations

  3. Heparan Sulfate Induces Necroptosis in Murine Cardiomyocytes: A Medical-In silico Approach Combining In vitro Experiments and Machine Learning.

    Science.gov (United States)

    Zechendorf, Elisabeth; Vaßen, Phillip; Zhang, Jieyi; Hallawa, Ahmed; Martincuks, Antons; Krenkel, Oliver; Müller-Newen, Gerhard; Schuerholz, Tobias; Simon, Tim-Philipp; Marx, Gernot; Ascheid, Gerd; Schmeink, Anke; Dartmann, Guido; Thiemermann, Christoph; Martin, Lukas

    2018-01-01

    Life-threatening cardiomyopathy is a severe, but common, complication associated with severe trauma or sepsis. Several signaling pathways involved in apoptosis and necroptosis are linked to trauma- or sepsis-associated cardiomyopathy. However, the underling causative factors are still debatable. Heparan sulfate (HS) fragments belong to the class of danger/damage-associated molecular patterns liberated from endothelial-bound proteoglycans by heparanase during tissue injury associated with trauma or sepsis. We hypothesized that HS induces apoptosis or necroptosis in murine cardiomyocytes. By using a novel Medical- In silico approach that combines conventional cell culture experiments with machine learning algorithms, we aimed to reduce a significant part of the expensive and time-consuming cell culture experiments and data generation by using computational intelligence (refinement and replacement). Cardiomyocytes exposed to HS showed an activation of the intrinsic apoptosis signal pathway via cytochrome C and the activation of caspase 3 (both p  machine learning algorithms.

  4. Improved probabilistic inference as a general learning mechanism with action video games.

    Science.gov (United States)

    Green, C Shawn; Pouget, Alexandre; Bavelier, Daphne

    2010-09-14

    Action video game play benefits performance in an array of sensory, perceptual, and attentional tasks that go well beyond the specifics of game play [1-9]. That a training regimen may induce improvements in so many different skills is notable because the majority of studies on training-induced learning report improvements on the trained task but limited transfer to other, even closely related, tasks ([10], but see also [11-13]). Here we ask whether improved probabilistic inference may explain such broad transfer. By using a visual perceptual decision making task [14, 15], the present study shows for the first time that action video game experience does indeed improve probabilistic inference. A neural model of this task [16] establishes how changing a single parameter, namely the strength of the connections between the neural layer providing the momentary evidence and the layer integrating the evidence over time, captures improvements in action-gamers behavior. These results were established in a visual, but also in a novel auditory, task, indicating generalization across modalities. Thus, improved probabilistic inference provides a general mechanism for why action video game playing enhances performance in a wide variety of tasks. In addition, this mechanism may serve as a signature of training regimens that are likely to produce transfer of learning. Copyright © 2010 Elsevier Ltd. All rights reserved.

  5. Combined loading effects on the fracture mechanics behavior of line pipes

    Energy Technology Data Exchange (ETDEWEB)

    Bravo, R.E.; Cravero, S.; Ernst, H.A. [Tenaris Group, Campana (Argentina). SIDERCA R and D Center

    2009-12-19

    For certain applications, pipelines may be submitted to biaxial loading situations. In these cases, it is not clear the influence of the biaxial loading on the fracture mechanics behavior of cracked pipelines. For further understanding of biaxial loading effects, this work presents a numerical simulation of ductile tearing in a circumferentially surface cracked pipe under biaxial loading using the computational cell methodology. The model was adjusted with experimental results obtained in laboratory using single edge cracked under tension (SENT) specimens. These specimens appear as the better alternative to conventional fracture specimens to characterize fracture toughness of cracked pipes. The negligible effect of biaxial loadings on resistance curves was demonstrated. To guarantee the similarities of stress and strains fields between SENT specimens and cracked pipes subjected to biaxial loading, a constraint study using the J-Q methodology and the h parameter was used. The constraint study gives information about the characteristics of the crack-tip conditions. (author)

  6. Nonlinear mechanical response of the extracellular matrix: learning from articular cartilage

    Science.gov (United States)

    Kearns, Sarah; Das, Moumita

    2015-03-01

    We study the mechanical structure-function relations in the extracellular matrix (ECM) with focus on nonlinear shear and compression response. As a model system, our study focuses on the ECM in articular cartilage tissue which has two major mechanobiological components: a network of the biopolymer collagen that acts as a stiff, reinforcing matrix, and a flexible aggrecan network that facilitates deformability. We model this system as a double network hydrogel made of interpenetrating networks of stiff and flexible biopolymers respectively. We study the linear and nonlinear mechanical response of the model ECM to shear and compression forces using a combination of rigidity percolation theory and energy minimization approaches. Our results may provide useful insights into the design principles of the ECM as well as biomimetic hydrogels that are mechanically robust and can, at the same time, easily adapt to cues in their surroundings.

  7. VUV treatment combined with mechanical strain of stretchable polymer foils resulting in cell alignment

    Energy Technology Data Exchange (ETDEWEB)

    Barb, R.-A. [Institute of Applied Physics, Johannes Kepler University Linz (Austria); Magnus, B. [Innovacell Biotechnologie AG, Innsbruck (Austria); Innerbichler, S. [Innerbichler GmbH, Breitenbach am Inn (Austria); Greunz, T. [CDL-MS-MACH, Johannes Kepler University Linz (Austria); Wiesbauer, M. [Institute of Applied Physics, Johannes Kepler University Linz (Austria); Marksteiner, R. [Innovacell Biotechnologie AG, Innsbruck (Austria); Stifter, D. [CDL-MS-MACH, Johannes Kepler University Linz (Austria); Heitz, J., E-mail: johannes.heitz@jku.at [Institute of Applied Physics, Johannes Kepler University Linz (Austria)

    2015-01-15

    Highlights: • Elastic polyurethane (PU) foils were exposed to the vacuum-UV in reactive atmosphere. • The photomodification resulted in improved cytocompatibilty. • Parallel microgrooves formed on the irradiated PU surfaces after strong elongation. • Cells seeded onto microgrooves aligned their shapes in the direction of the grooves. • Elongation occurred also for cells on PU subjected to cyclic mechanical stretching. - Abstract: Cell-alignment along a defined direction can have a direct effect on the cell functionality and differentiation. Oriented micro- or nanotopographic structures on cell culture substrates can induce cell-alignment. Surface chemistry, wettability, and stiffness of the substrate are also important material features as they strongly influence the cell–substrate interactions. For improved bio-compatibility, highly elastic polyurethane (PU) foils were exposed to the vacuum-UV (VUV) light of a Xe{sub 2}{sup *} excimer lamp at 172 nm in a nitrogen containing atmosphere (N{sub 2} or NH{sub 3}). The irradiation resulted in a change in the chemical surface composition. Additionally, the formation of regular parallel microgrooves was observed on the irradiated surfaces after strong uni-axial deformation (i.e., more than about 50% strain) of the photo-modified PU foils. Cell seeding experiments demonstrated that the VUV modified polymer foils strongly enhance cell adhesion and proliferation. Cells seeded onto microgrooves aligned their shapes and elongated in the direction of the grooves. A similar effect was observed for cells seeded on photo-modified PU foils subjected to cyclic mechanical stretching at lower strain levels (i.e., typically 10% strain) without groove-formation. The cells had also here an elongated shape, however they not always align in a defined direction relative to the stretching.

  8. Developmental song learning as a model to understand neural mechanisms that limit and promote the ability to learn.

    Science.gov (United States)

    London, Sarah E

    2017-11-20

    Songbirds famously learn their vocalizations. Some species can learn continuously, others seasonally, and still others just once. The zebra finch (Taeniopygia guttata) learns to sing during a single developmental "Critical Period," a restricted phase during which a specific experience has profound and permanent effects on brain function and behavioral patterns. The zebra finch can therefore provide fundamental insight into features that promote and limit the ability to acquire complex learned behaviors. For example, what properties permit the brain to come "on-line" for learning? How does experience become encoded to prevent future learning? What features define the brain in receptive compared to closed learning states? This piece will focus on epigenomic, genomic, and molecular levels of analysis that operate on the timescales of development and complex behavioral learning. Existing data will be discussed as they relate to Critical Period learning, and strategies for future studies to more directly address these questions will be considered. Birdsong learning is a powerful model for advancing knowledge of the biological intersections of maturation and experience. Lessons from its study not only have implications for understanding developmental song learning, but also broader questions of learning potential and the enduring effects of early life experience on neural systems and behavior. Copyright © 2017. Published by Elsevier B.V.

  9. Effectiveness of hands-on tutoring and guided self-directed learning versus self-directed learning alone to educate critical care fellows on mechanical ventilation - a pilot project.

    Science.gov (United States)

    Ramar, Kannan; De Moraes, Alice Gallo; Selim, Bernardo; Holets, Steven; Oeckler, Richard

    2016-01-01

    Physicians require extensive training to achieve proficiency in mechanical ventilator (MV) management of the critically ill patients. Guided self-directed learning (GSDL) is usually the method used to learn. However, it is unclear if this is the most proficient approach to teaching mechanical ventilation to critical care fellows. We, therefore, investigated whether critical care fellows achieve higher scores on standardized testing and report higher satisfaction after participating in a hands-on tutorial combined with GSDL compared to self-directed learning alone. First-year Pulmonary and Critical Care Medicine (PCCM) fellows ( n =6) and Critical Care Internal Medicine (CCIM) ( n =8) fellows participated. Satisfaction was assessed using the Likert scale. MV knowledge assessment was performed by administering a standardized 25-question multiple choice pre- and posttest. For 2 weeks the CCIM fellows were exposed to GSDL, while the PCCM fellows received hands-on tutoring combined with GSDL. Ninety-three percentage (6 PCCM and 7 CCIM fellows, total of 13 fellows) completed all evaluations and were included in the final analysis. CCIM and PCCM fellows scored similarly in the pretest (64% vs. 52%, p =0.13). Following interventions, the posttest scores increased in both groups. However, no significant difference was observed based on the interventions (74% vs. 77%, p =0.39). The absolute improvement with the hands-on-tutoring and GSDL group was higher than GSDL alone (25% vs. 10%, p =0.07). Improved satisfaction scores were noted with hands-on tutoring. Hands-on tutoring combined with GSDL and GSDL alone were both associated with an improvement in posttest scores. Absolute improvement in test and satisfaction scores both trended higher in the hands-on tutorial group combined with GSDL group.

  10. Effectiveness of hands-on tutoring and guided self-directed learning versus self-directed learning alone to educate critical care fellows on mechanical ventilation – a pilot project

    Directory of Open Access Journals (Sweden)

    Kannan Ramar

    2016-09-01

    Full Text Available Background: Physicians require extensive training to achieve proficiency in mechanical ventilator (MV management of the critically ill patients. Guided self-directed learning (GSDL is usually the method used to learn. However, it is unclear if this is the most proficient approach to teaching mechanical ventilation to critical care fellows. We, therefore, investigated whether critical care fellows achieve higher scores on standardized testing and report higher satisfaction after participating in a hands-on tutorial combined with GSDL compared to self-directed learning alone. Methods: First-year Pulmonary and Critical Care Medicine (PCCM fellows (n=6 and Critical Care Internal Medicine (CCIM (n=8 fellows participated. Satisfaction was assessed using the Likert scale. MV knowledge assessment was performed by administering a standardized 25-question multiple choice pre- and posttest. For 2 weeks the CCIM fellows were exposed to GSDL, while the PCCM fellows received hands-on tutoring combined with GSDL. Results: Ninety-three percentage (6 PCCM and 7 CCIM fellows, total of 13 fellows completed all evaluations and were included in the final analysis. CCIM and PCCM fellows scored similarly in the pretest (64% vs. 52%, p=0.13. Following interventions, the posttest scores increased in both groups. However, no significant difference was observed based on the interventions (74% vs. 77%, p=0.39. The absolute improvement with the hands-on-tutoring and GSDL group was higher than GSDL alone (25% vs. 10%, p=0.07. Improved satisfaction scores were noted with hands-on tutoring. Conclusions: Hands-on tutoring combined with GSDL and GSDL alone were both associated with an improvement in posttest scores. Absolute improvement in test and satisfaction scores both trended higher in the hands-on tutorial group combined with GSDL group.

  11. PHYSICAL AND MECHANICAL BEHAVIOR OF PANELS MANUFACTURED WITH BAMBOO (Bambusa vulgaris Schr.-WOOD COMBINATION

    Directory of Open Access Journals (Sweden)

    Leandro Calegari

    2007-03-01

    Full Text Available Considering the importance of derived products from bamboo for some countries and the wood shortage in some areas of Brazil, this work analyzed the quality of boards composed by particles of Eucalyptus sp. and bamboo strips (Bambusa vulgaris Schr.. The panels were produced with a density of 0.60 g/cm³ and 10% of urea-formaldehyde adhesive. The influence of the epidermis on the properties of the panels was also evaluated. The panels were constituted by five layers: core (Eucalyptus sp. or bamboo particles, layers of reinforcement (bamboo strips and finish faces (particles of same nature as the core. The press time was 8 minutes, at 120ºC. None of the treatments satisfied the quality patterns established by A208.1 (ANSI, 1987 and DIN 68761 (1-1961, (3-1971 (GERMAN STANDARDS COMMITTEE, 1971 codes. However, particleboards produced exclusively by bamboo or combined with wood presented a similar behavior to those produced exclusively of wood, showing to be a viable alternative. The modulus of rupture (MOR and elasticity (MOE were approximately the same in all treatments due to the irregular distribution of the layers in the mattress. The absence of epidermis tended to reduce the thickness swelling (2 and 24 hours and internal bond strength, however, without significant statistical difference. Therefore, other parameters of production of boards using bamboo, such as density and adhesive content, should be investigated in order to check whether the removal of epidermis is a really advantageous procedure.

  12. A Design of Mechanical Frequency Converter Linear and Non-linear Spring Combination for Energy Harvesting

    International Nuclear Information System (INIS)

    Yamamoto, K; Fujita, T; Kanda, K; Maenaka, K; Badel, A; Formosa, F

    2014-01-01

    In this study, the improvement of energy harvesting from wideband vibration with random change by using a combination of linear and nonlinear spring system is investigated. The system consists of curved beam spring for non-linear buckling, which supports the linear mass-spring resonator. Applying shock acceleration generates a snap through action to the buckling spring. From the FEM analysis, we showed that the snap through acceleration from the buckling action has no relationship with the applied shock amplitude and duration. We use this uniform acceleration as an impulse shock source for the linear resonator. It is easy to obtain the maximum shock response from the uniform snap through acceleration by using a shock response spectrum (SRS) analysis method. At first we investigated the relationship between the snap-through behaviour and an initial curved deflection. Then a time response result for non-linear springs with snap through and minimum force that makes a buckling behaviour were obtained by FEM analysis. By obtaining the optimum SRS frequency for linear resonator, we decided its resonant frequency with the MATLAB simulator

  13. Combined therapeutic effect and molecular mechanisms of metformin and cisplatin in human lung cancer xenografts in nude mice

    Directory of Open Access Journals (Sweden)

    Yu-Qin Chen

    2015-01-01

    Full Text Available Objective: This work was aimed at studying the inhibitory activity of metformin combined with the commonly used chemotherapy drug cisplatin in human lung cancer xenografts in nude mice. We also examined the combined effects of these drugs on the molecular expression of survivin, matrix metalloproteinase-2 (MMP-2, vascular endothelial growth factor-C (VEGF-C, and vascular endothelial growth factorreceptor-3 (VEGFR-3 to determine the mechanism of action and to explore the potential applications of the new effective drug therapy in lung cancer. Materials and Methods: The nude mice model of lung cancer xenografts was established, and mice were randomly divided into the metformin group, the cisplatin group, the metformin + cisplatin group, and the control group. The animals were killed 42 days after drug administration, and the tumor tissues were then sampled to detect the messenger ribonucleic acid (mRNA and protein expression levels of survivin, MMP-2, VEGF-C, and VEGFR-3 by immunohistochemistry and reverse transcription polymerase chain reaction (RT-PCR. Results: The protein and mRNA expression levels of survivin, MMP-2, VEGF-C, and VEGFR-3 in the cisplatin group and the combined treatment group were lower than that in the control group (P < 0.05. In the metformin group, the expression of MMP-2 protein and mRNA was lower than that in the control group (P < 0.05. The protein and mRNA expression levels of survivin, MMP-2, VEGF-C, and VEGFR-3 in the combined treatment group were lower than that in the cisplatin group and the metformin group (P < 0.05. Conclusions: Metformin inhibited the expression of MMP-2, cisplatin and the combined treatment inhibited the expression of survivin, MMP-2, VEGF-C, and VEGFR-3, and the combined treatment of metformin with cisplatin resulted in enhanced anti-tumor efficacy.

  14. Combining Distance and Face-To Teaching and Learning in Spatial Computations

    Science.gov (United States)

    Gulland, E.-K.; Schut, A. G. T.; Veenendaal, B.

    2011-09-01

    Retention and passing rates as well as student engagement in computer programming and problem solving units are a major concern in tertiary spatial science courses. A number of initiatives were implemented to improve this. A pilot study reviews the changes made to the teaching and learning environment, including the addition of new resources and modifications to assessments, and investigates their effectiveness. In particular, the study focuses on the differences between students studying in traditional, oncampus mode and distance, e-learning mode. Student results and retention rates from 2009-2011, data from in-lecture clicker response units and two anonymous surveys collected in 2011 were analysed. Early results indicate that grades improved for engaged students but pass rates or grades of the struggling cohort of students did not improve significantly.

  15. Growing adaptive machines combining development and learning in artificial neural networks

    CERN Document Server

    Bredeche, Nicolas; Doursat, René

    2014-01-01

    The pursuit of artificial intelligence has been a highly active domain of research for decades, yielding exciting scientific insights and productive new technologies. In terms of generating intelligence, however, this pursuit has yielded only limited success. This book explores the hypothesis that adaptive growth is a means of moving forward. By emulating the biological process of development, we can incorporate desirable characteristics of natural neural systems into engineered designs, and thus move closer towards the creation of brain-like systems. The particular focus is on how to design artificial neural networks for engineering tasks. The book consists of contributions from 18 researchers, ranging from detailed reviews of recent domains by senior scientists, to exciting new contributions representing the state of the art in machine learning research. The book begins with broad overviews of artificial neurogenesis and bio-inspired machine learning, suitable both as an introduction to the domains and as a...

  16. F-SVM: Combination of Feature Transformation and SVM Learning via Convex Relaxation

    OpenAIRE

    Wu, Xiaohe; Zuo, Wangmeng; Zhu, Yuanyuan; Lin, Liang

    2015-01-01

    The generalization error bound of support vector machine (SVM) depends on the ratio of radius and margin, while standard SVM only considers the maximization of the margin but ignores the minimization of the radius. Several approaches have been proposed to integrate radius and margin for joint learning of feature transformation and SVM classifier. However, most of them either require the form of the transformation matrix to be diagonal, or are non-convex and computationally expensive. In this ...

  17. Combining video games and constructionist design to support deep learning in play

    OpenAIRE

    Holbert, Nathan; Weintrop, David; Wilensky, Uri; Sengupta, Pratim; Killingsworth, Stephen; Krinks, Kyra; Clark, Doug; Brady, Corey; Shapiro, R. Benjamin; Russ, Rosemary S.; Klopfer, Eric

    2014-01-01

    This effort has produced many interesting games though it is unclear if “educational video games” have achieved their promise. Similarly, for many years constructionists have engaged children in learning across a variety of contexts, including game design. While these programs have been successful, their exploratory nature leads to concerns about content coverage. In this symposium we discuss the potential of blending these two design traditions. Constructionist video games infuse tradi...

  18. Combining advanced networked technology and pedagogical methods to improve collaborative distance learning.

    Science.gov (United States)

    Staccini, Pascal; Dufour, Jean-Charles; Raps, Hervé; Fieschi, Marius

    2005-01-01

    Making educational material be available on a network cannot be reduced to merely implementing hypermedia and interactive resources on a server. A pedagogical schema has to be defined to guide students for learning and to provide teachers with guidelines to prepare valuable and upgradeable resources. Components of a learning environment, as well as interactions between students and other roles such as author, tutor and manager, can be deduced from cognitive foundations of learning, such as the constructivist approach. Scripting the way a student will to navigate among information nodes and interact with tools to build his/her own knowledge can be a good way of deducing the features of the graphic interface related to the management of the objects. We defined a typology of pedagogical resources, their data model and their logic of use. We implemented a generic and web-based authoring and publishing platform (called J@LON for Join And Learn On the Net) within an object-oriented and open-source programming environment (called Zope) embedding a content management system (called Plone). Workflow features have been used to mark the progress of students and to trace the life cycle of resources shared by the teaching staff. The platform integrated advanced on line authoring features to create interactive exercises and support live courses diffusion. The platform engine has been generalized to the whole curriculum of medical studies in our faculty; it also supports an international master of risk management in health care and will be extent to all other continuous training diploma.

  19. What we have learned about the Higgs boson from the bosonic channels and more inclusive combinations of data

    CERN Document Server

    Yuan, Li; The ATLAS collaboration

    2015-01-01

    This talk will review the status of what has been learned from LHC run-1 about the properties of the observed Higgs boson mostly from the bosonic decay channels, but also from latest/final inclusive analyses of the coupling structure. The focus of the talk should be the measurement of the Higgs boson mass (with focus on the combination of ATLAS and CMS), the status of the spin and CP properties and the analysis of the coupling structure. The talk is aimed to present the final LHC run-1 results from ATLAS and CMS.

  20. Fatigue crack propagation under combined cyclic mechanical loading and electric field in piezoelectric ceramics

    International Nuclear Information System (INIS)

    Shirakihara, Kaori; Tanaka, Keisuke; Akiniwa, Yoshiaki; Suzuki, Yasuyoshi; Mukai, Hirokatsu

    2006-01-01

    Fatigue crack propagation tests of PZT specimens were performed under cyclic four-point bending with and without superposition of electric fields. The specimens were poled in the longitudinal direction (PL specimens) perpendicular to the crack plane. The crack propagation rate for the case of open circuit was faster than that for the case of short circuit. The application of a negative or positive electric field parallel to the poling direction accelerated the crack propagation rate, and the amount of acceleration was larger for the case of the negative field. The change of the crack propagation rate with crack extension can be divided into three regions. In the region I, the crack propagation rate decreases with increasing crack length, and then turn to increase in the region III. In the region II, the propagation rate is nearly constant. The mechanisms of fatigue crack propagation were correlated to domain switching near the crack tip. The grain boundary fracture was predominant in the low-rate region, while transgranular fracture became abundant on the unstable fracture surface. (author)

  1. Combining mechanical foaming and thermally induced phase separation to generate chitosan scaffolds for soft tissue engineering.

    Science.gov (United States)

    Biswas, D P; Tran, P A; Tallon, C; O'Connor, A J

    2017-02-01

    In this paper, a novel foaming methodology consisting of turbulent mixing and thermally induced phase separation (TIPS) was used to generate scaffolds for tissue engineering. Air bubbles were mechanically introduced into a chitosan solution which forms the continuous polymer/liquid phase in the foam created. The air bubbles entrained in the foam act as a template for the macroporous architecture of the final scaffolds. Wet foams were crosslinked via glutaraldehyde and frozen at -20 °C to induce TIPS in order to limit film drainage, bubble coalescence and Ostwald ripening. The effects of production parameters, including mixing speed, surfactant concentration and chitosan concentration, on foaming are explored. Using this method, hydrogel scaffolds were successfully produced with up to 80% porosity, average pore sizes of 120 μm and readily tuneable compressive modulus in the range of 2.6 to 25 kPa relevant to soft tissue engineering applications. These scaffolds supported 3T3 fibroblast cell proliferation and penetration and therefore show significant potential for application in soft tissue engineering.

  2. Elementary mechanics using Matlab a modern course combining analytical and numerical techniques

    CERN Document Server

    Malthe-Sørenssen, Anders

    2015-01-01

    This book – specifically developed as a novel textbook on elementary classical mechanics – shows how analytical and numerical methods can be seamlessly integrated to solve physics problems. This approach allows students to solve more advanced and applied problems at an earlier stage and equips them to deal with real-world examples well beyond the typical special cases treated in standard textbooks. Another advantage of this approach is that students are brought closer to the way physics is actually discovered and applied, as they are introduced right from the start to a more exploratory way of understanding phenomena and of developing their physical concepts. While not a requirement, it is advantageous for the reader to have some prior knowledge of scientific programming with a scripting-type language. This edition of the book uses Matlab, and a chapter devoted to the basics of scientific programming with Matlab is included. A parallel edition using Python instead of Matlab is also available. Last but not...

  3. Elementary mechanics using Python a modern course combining analytical and numerical techniques

    CERN Document Server

    Malthe-Sørenssen, Anders

    2015-01-01

    This book – specifically developed as a novel textbook on elementary classical mechanics – shows how analytical and numerical methods can be seamlessly integrated to solve physics problems. This approach allows students to solve more advanced and applied problems at an earlier stage and equips them to deal with real-world examples well beyond the typical special cases treated in standard textbooks. Another advantage of this approach is that students are brought closer to the way physics is actually discovered and applied, as they are introduced right from the start to a more exploratory way of understanding phenomena and of developing their physical concepts. While not a requirement, it is advantageous for the reader to have some prior knowledge of scientific programming with a scripting-type language. This edition of the book uses Python, and a chapter devoted to the basics of scientific programming with Python is included. A parallel edition using Matlab instead of Python is also available. Last but not...

  4. Mechanical behavior of ultrafine-grained materials under combined static and dynamic loadings

    Directory of Open Access Journals (Sweden)

    Guo Y.Z.

    2015-01-01

    Full Text Available Ultrafine-grained (UFG materials have extensive prospects for engineering application due to their excellent mechanical properties. However, the grain size decrease reduces their strain hardening ability and makes UFG materials more susceptible to deformation instability such as shear localization. In most cases, critical shear strain is taken as the criterion for formation of shear localization under impact loading or adiabatic shear band (ASB. Recently, some researchers found that the formation of ASB was determined only by the dynamic loading process and had nothing to do with its static loading history. They proposed for coarse-grained metals a dynamic stored energy-based criterion for ASB and verified it by some experiments. In this study, we will focus on the shear localization behavior of UFG metals such as UFG titanium and magnesium alloy AZ31. Quasi-static loading and dynamic loading will be applied on the same specimen alternately. The shear localization behavior will be analyzed and the criterion of its formation will be evaluated.

  5. Combining 3D printed forms with textile structures - mechanical and geometrical properties of multi-material systems

    International Nuclear Information System (INIS)

    Sabantina, L; Kinzel, F; Ehrmann, A; Finsterbusch, K

    2015-01-01

    The 3D printing belongs to the rapidly emerging technologies which have the chance to revolutionize the way products are created. In the textile industry, several designers have already presented creations of shoes, dresses or other garments which could not be produced with common techniques. 3D printing, however, is still far away from being a usual process in textile and clothing production. The main challenge results from the insufficient mechanical properties, especially the low tensile strength, of pure 3D printed products, prohibiting them from replacing common technologies such as weaving or knitting. Thus, one way to the application of 3D printed forms in garments is combining them with textile fabrics, the latter ensuring the necessary tensile strength. This article reports about different approaches to combine 3D printed polymers with different textile materials and fabrics, showing chances and limits of this technique. (paper)

  6. Analysis and synthesis of a system for optimal automatic regulation of the process of mechanical cutting by a combine

    Energy Technology Data Exchange (ETDEWEB)

    Pop, E.; Coroescu, T.; Poanta, A.; Pop, M.

    1978-01-01

    Uncontrollable dynamic operating regime of a combine has a negative effect. A consequence of the uncontrolled change in productivity and rate during cutting is total decrease in productivity. The cutters of the cutting mechanism are prematurely worn out. The quality of the coal decreases. Complications with combine control reduce productivity. The motor is exposed to the maximum loads, its service life decreases, and there is an inefficient consumption of electricity. Studies of the optimal automatic regulation of the cutting process were made by the method of modeled analysis on digital and analog machines. The method uses an electronic-automatic device with integrating circuit of domestic production (A-741, A-723). This device controls and regulates the current parameters of the acting motor. The device includes primarily an element of information type of the Hall TH traductor type, the regulating element is an electronic relay, electronic power distributor, etc.

  7. [Mechanism and Prospect of Radiotherapy Combined with Apotatinib
in the Treatment of Non-small Cell Lung Cancer].

    Science.gov (United States)

    Liu, Guohui; Wang, Chunbo; E, Mingyan

    2017-12-20

    Non-small cell lung cancer is one of the most commom malignant tumor being harmful to people's life and health. Most of the patients have developed to the last stage which not suitable for surgical indications, so radiation and chemotherapy is the main treatment strategy. In recent years, with the theory of anti-angiogenesis therapy for malignant tumors, apatinib as a promising novel medicine to treat malignant tumors, represents synergistic antitumor effects in combination with radiotherapy. The underlying mechanisms may include make blood vessel normalization, alleviating inner hypoxia, and angiogenic factors regulation. Apatinib in combination with radiotherapy may become a new and effective treatment strategy of non-small cell lung cancer.

  8. System level mechanisms of adaptation, learning, memory formation and evolvability: the role of chaperone and other networks.

    Science.gov (United States)

    Gyurko, David M; Soti, Csaba; Stetak, Attila; Csermely, Peter

    2014-05-01

    During the last decade, network approaches became a powerful tool to describe protein structure and dynamics. Here, we describe first the protein structure networks of molecular chaperones, then characterize chaperone containing sub-networks of interactomes called as chaperone-networks or chaperomes. We review the role of molecular chaperones in short-term adaptation of cellular networks in response to stress, and in long-term adaptation discussing their putative functions in the regulation of evolvability. We provide a general overview of possible network mechanisms of adaptation, learning and memory formation. We propose that changes of network rigidity play a key role in learning and memory formation processes. Flexible network topology provides ' learning-competent' state. Here, networks may have much less modular boundaries than locally rigid, highly modular networks, where the learnt information has already been consolidated in a memory formation process. Since modular boundaries are efficient filters of information, in the 'learning-competent' state information filtering may be much smaller, than after memory formation. This mechanism restricts high information transfer to the 'learning competent' state. After memory formation, modular boundary-induced segregation and information filtering protect the stored information. The flexible networks of young organisms are generally in a 'learning competent' state. On the contrary, locally rigid networks of old organisms have lost their 'learning competent' state, but store and protect their learnt information efficiently. We anticipate that the above mechanism may operate at the level of both protein-protein interaction and neuronal networks.

  9. Manpower allocation in a cellular manufacturing system considering the impact of learning, training and combination of learning and training in operator skills

    Directory of Open Access Journals (Sweden)

    Masoud

    2017-01-01

    Full Text Available In this article, a manpower allocation and cell loading problem is studied, where demand is sto-chastic. The inter-cell and intra-cell movements are considered and attention is focused on as-signing operators with different skill levels to operations, because cell performance in addition to load cell is dependent on manpower. The purpose of this article is manpower allocation in cellu-lar manufacturing with consideration to learning and training policies. The manpower skill levels are determined in order to enhance production rate. The main contribution of this approach is the scenarios of training and learning in addition to the combination of training and learning being simulated. By using these three scenarios, the skill level of workers increase which reduces the processing time. In this regard cell layout is static where processing times and customer demand follow a normal distribution. As one of the significant costs of industrial unit is related to pro-duction cost, this study has attempted to reduce these costs by increasing the skill level of opera-tor which causes to reduce the processing time. Scenarios are evaluated by using a simulation method that finally attained results indicate this simulation provides better manpower assign-ments.

  10. Learning Activities That Combine Science Magic Activities with the 5E Instructional Model to Influence Secondary-School Students' Attitudes to Science

    Science.gov (United States)

    Lin, Jang-Long; Cheng, Meng-Fei; Chang, Ying-Chi; Li, Hsiao-Wen; Chang, Jih-Yuan; Lin, Deng-Min

    2014-01-01

    The purpose of this study was to investigate how learning materials based on Science Magic activities affect student attitudes to science. A quasi-experimental design was conducted to explore the combination of Science Magic with the 5E Instructional Model to develop learning materials for teaching a science unit about friction. The participants…

  11. Bioremediation mechanisms of combined pollution of PAHs and heavy metals by bacteria and fungi: A mini review.

    Science.gov (United States)

    Liu, Shao-Heng; Zeng, Guang-Ming; Niu, Qiu-Ya; Liu, Yang; Zhou, Lu; Jiang, Lu-Hua; Tan, Xiao-Fei; Xu, Piao; Zhang, Chen; Cheng, Min

    2017-01-01

    In recent years, knowledge in regard to bioremediation of combined pollution of polycyclic aromatic hydrocarbons (PAHs) and heavy metals by bacteria and fungi has been widely developed. This paper reviews the species of bacteria and fungi which can tackle with various types of PAHs and heavy metals entering into environment simultaneously or successively. Microbial activity, pollutants bioavailability and environmental factors (e.g. pH, temperature, low molecular weight organic acids and humic acids) can all affect the bioremediation of PAHs and heavy metals. Moreover, this paper summarizes the remediation mechanisms of PAHs and heavy metals by microbes via elucidating the interaction mechanisms of heavy metals with heavy metals, PAHs/PAHs metabolites with PAHs and PAHs with heavy metals. Based on the above reviews, this paper also discusses the potential research needs for this field. Copyright © 2016 Elsevier Ltd. All rights reserved.

  12. Metabolic and Target-Site Mechanisms Combine to Confer Strong DDT Resistance in Anopheles gambiae

    Science.gov (United States)

    Mitchell, Sara N.; Rigden, Daniel J.; Dowd, Andrew J.; Lu, Fang; Wilding, Craig S.; Weetman, David; Dadzie, Samuel; Jenkins, Adam M.; Regna, Kimberly; Boko, Pelagie; Djogbenou, Luc; Muskavitch, Marc A. T.; Ranson, Hilary; Paine, Mark J. I.; Mayans, Olga; Donnelly, Martin J.

    2014-01-01

    The development of resistance to insecticides has become a classic exemplar of evolution occurring within human time scales. In this study we demonstrate how resistance to DDT in the major African malaria vector Anopheles gambiae is a result of both target-site resistance mechanisms that have introgressed between incipient species (the M- and S-molecular forms) and allelic variants in a DDT-detoxifying enzyme. Sequencing of the detoxification enzyme, Gste2, from DDT resistant and susceptible strains of An. gambiae, revealed a non-synonymous polymorphism (I114T), proximal to the DDT binding domain, which segregated with strain phenotype. Recombinant protein expression and DDT metabolism analysis revealed that the proteins from the susceptible strain lost activity at higher DDT concentrations, characteristic of substrate inhibition. The effect of I114T on GSTE2 protein structure was explored through X-ray crystallography. The amino acid exchange in the DDT-resistant strain introduced a hydroxyl group nearby the hydrophobic DDT-binding region. The exchange does not result in structural alterations but is predicted to facilitate local dynamics and enzyme activity. Expression of both wild-type and 114T alleles the allele in Drosophila conferred an increase in DDT tolerance. The 114T mutation was significantly associated with DDT resistance in wild caught M-form populations and acts in concert with target-site mutations in the voltage gated sodium channel (Vgsc-1575Y and Vgsc-1014F) to confer extreme levels of DDT resistance in wild caught An. gambiae. PMID:24675797

  13. Longwing (Heliconius) butterflies combine a restricted set of pigmentary and structural coloration mechanisms.

    Science.gov (United States)

    Wilts, Bodo D; Vey, Aidan J M; Briscoe, Adriana D; Stavenga, Doekele G

    2017-11-21

    Longwing butterflies, Heliconius sp., also called heliconians, are striking examples of diversity and mimicry in butterflies. Heliconians feature strongly colored patterns on their wings, arising from wing scales colored by pigments and/or nanostructures, which serve as an aposematic signal. Here, we investigate the coloration mechanisms among several species of Heliconius by applying scanning electron microscopy, (micro)spectrophotometry, and imaging scatterometry. We identify seven kinds of colored scales within Heliconius whose coloration is derived from pigments, nanostructures or both. In yellow-, orange- and red-colored wing patches, both cover and ground scales contain wavelength-selective absorbing pigments, 3-OH-kynurenine, xanthommatin and/or dihydroxanthommatin. In blue wing patches, the cover scales are blue either due to interference of light in the thin-film lower lamina (e.g., H. doris) or in the multilayered lamellae in the scale ridges (so-called ridge reflectors, e.g., H. sara and H. erato); the underlying ground scales are black. In the white wing patches, both cover and ground scales are blue due to their thin-film lower lamina, but because they are stacked upon each other and at the wing substrate, a faint bluish to white color results. Lastly, green wing patches (H. doris) have cover scales with blue-reflecting thin films and short-wavelength absorbing 3-OH-kynurenine, together causing a green color. The pigmentary and structural traits are discussed in relation to their phylogenetic distribution and the evolution of vision in this highly interesting clade of butterflies.

  14. Effect of combined extrusion parameters on mechanical properties of basalt fiber-reinforced plastics based on polypropylene

    Science.gov (United States)

    Bashtannik, P. I.; Ovcharenko, V. G.; Boot, Yu. A.

    1997-11-01

    Basalt fibers are efficient reinforcing fillers for polypropylene because they increase both the mechanical and the tribotechnical properties of composites. Basalt fibers can compete with traditional fillers (glass and asbestos fibers) of polypropylene with respect to technological, economic, and toxic properties. The effect of technological parameters of producing polypropylene-based basalt fiber-reinforced plastics (BFRPs) by combined extrusion on their mechanical properties has been investigated. The extrusion temperature was found to be the main parameter determining the mechanical properties of the BFRPs. With temperature growth from 180 to 240°C, the residual length of the basalt fibers in the composite, as well as the adhesive strength of the polymer-fiber system, increased, while the composite defectiveness decreased. The tensile strength and elastic modulus increased from 35 to 42 MPa and 3.2 to 4.2 GPa, respectively. At the same time, the growth in composite solidity led to its higher brittleness. Thus, a higher temperature of extrusion allows us to produce materials which can be subjected to tensile and bending loads, while the materials produced at a lower temperature of extrusion are impact stable. The effect of the gap size between the extruder body and moving disks on the mechanical properties of the BFRPs is less significant than that of temperature. An increase of the gap size from 2 to 8 mm improves the impregnation quality of the fibers, but the extruder productivity diminishes. The possibility of controling the properties of reinforced polypropylene by varying the technological parameters of combined extrusion is shown. The polypropylene-based BFRPs produced by the proposed method surpass the properties of glass and asbestos fiber-reinforced plastics.

  15. Combined effects of scaffold stiffening and mechanical preconditioning cycles on construct biomechanics, gene expression, and tendon repair biomechanics.

    Science.gov (United States)

    Nirmalanandhan, Victor Sanjit; Juncosa-Melvin, Natalia; Shearn, Jason T; Boivin, Gregory P; Galloway, Marc T; Gooch, Cynthia; Bradica, Gino; Butler, David L

    2009-08-01

    Our group has previously reported that in vitro mechanical stimulation of tissue-engineered tendon constructs significantly increases both construct stiffness and the biomechanical properties of the repair tissue after surgery. When optimized using response surface methodology, our results indicate that a mechanical stimulus with three components (2.4% strain, 3000 cycles/day, and one cycle repetition) produced the highest in vitro linear stiffness. Such positive correlations between construct and repair stiffness after surgery suggest that enhancing structural stiffness before surgery could not only accelerate repair stiffness but also prevent premature failures in culture due to poor mechanical integrity. In this study, we examined the combined effects of scaffold crosslinking and subsequent mechanical stimulation on construct mechanics and biology. Autologous tissue-engineered constructs were created by seeding mesenchymal stem cells (MSCs) from 15 New Zealand white rabbits on type I collagen sponges that had undergone additional dehydrothermal crosslinking (termed ADHT in this manuscript). Both constructs from each rabbit were mechanically stimulated for 8h/day for 12 consecutive days with half receiving 100 cycles/day and the other half receiving 3000 cycles/day. These paired MSC-collagen autologous constructs were then implanted in bilateral full-thickness, full-length defects in the central third of rabbit patellar tendons. Increasing the number of in vitro cycles/day delivered to the ADHT constructs in culture produced no differences in stiffness or gene expression and no changes in biomechanical properties or histology 12 weeks after surgery. Compared to MSC-based repairs from a previous study that received no additional treatment in culture, ADHT crosslinking of the scaffolds actually lowered the 12-week repair stiffness. Thus, while ADHT crosslinking may initially stiffen a construct in culture, this specific treatment also appears to mask any benefits

  16. The mechanical properties of stored red blood cells measured by a convenient microfluidic approach combining with mathematic model.

    Science.gov (United States)

    Wang, Ying; You, Guoxing; Chen, Peipei; Li, Jianjun; Chen, Gan; Wang, Bo; Li, Penglong; Han, Dong; Zhou, Hong; Zhao, Lian

    2016-03-01

    The mechanical properties of red blood cells (RBCs) are critical to the rheological and hemodynamic behavior of blood. Although measurements of the mechanical properties of RBCs have been studied for many years, the existing methods, such as ektacytometry, micropipette aspiration, and microfluidic approaches, still have limitations. Mechanical changes to RBCs during storage play an important role in transfusions, and so need to be evaluated pre-transfusion, which demands a convenient and rapid detection method. We present a microfluidic approach that focuses on the mechanical properties of single cell under physiological shear flow and does not require any high-end equipment, like a high-speed camera. Using this method, the images of stretched RBCs under physical shear can be obtained. The subsequent analysis, combined with mathematic models, gives the deformability distribution, the morphology distribution, the normalized curvature, and the Young's modulus (E) of the stored RBCs. The deformability index and the morphology distribution show that the deformability of RBCs decreases significantly with storage time. The normalized curvature, which is defined as the curvature of the cell tail during stretching in flow, suggests that the surface charge of the stored RBCs decreases significantly. According to the mathematic model, which derives from the relation between shear stress and the adherent cells' extension ratio, the Young's moduli of the stored RBCs are also calculated and show significant increase with storage. Therefore, the present method is capable of representing the mechanical properties and can distinguish the mechanical changes of the RBCs during storage. The advantages of this method are the small sample needed, high-throughput, and easy-use, which make it promising for the quality monitoring of RBCs.

  17. Development of an advanced PFM code for the integrity evaluation of nuclear piping system under combined aging mechanisms

    International Nuclear Information System (INIS)

    Datta, Debashis

    2010-02-01

    A nuclear piping system is composed of several straight pipes and elbows joined by welding. These weld sections are usually the most susceptible failure parts susceptible to various degradation mechanisms. Whereas a specific location of a reactor piping system might fail by a combination of different aging mechanisms, e.g. fatigue and/or stress corrosion cracking, the majority of the piping probabilistic fracture mechanics (PFM) codes can only consider a single aging mechanism at a time. So, a probabilistic fracture mechanics computer code capable of considering multiple aging mechanisms was developed for an accurate failure analysis of each specific component of a nuclear piping section. The newly proposed crack morphology based probabilistic leak flow rate module is introduced in this code to separately treat fatigue and SCC type cracks. Improved models e.g. stressors models, elbow failure model, SIFs model, local seismic occurrence probability model, performance based crack detection models, etc., are also included in this code. Recent probabilistic fatigue (S-N) and SCC crack initiation (S-T) and subsequent crack growth rate models are coded. An integrated probabilistic risk assessment and probabilistic fracture mechanics methodology is proposed. A complete flow chart regarding the combined aging mechanism model is presented. The combined aging mechanism based module can significantly reduce simulation efforts and time. Two NUREG benchmark problems, e.g. reactor pressure vessel outlet nozzle section and a surge line elbow located just below the pressurizer are reinvestigated by this code. The results showed that, contribution of pre-existing cracks in addition to initiating cracks, can significantly increase the overall failure probability. Inconel weld location of reactor pressure vessel outlet nozzle section showed the weakest point in terms of relative through-wall leak failure probability in the order of about 10 -2 at the 40-year plant life. Considering

  18. Combining AI Methods for Learning Bots in a Real-Time Strategy Game

    OpenAIRE

    Robin Baumgarten; Simon Colton; Mark Morris

    2009-01-01

    We describe an approach for simulating human game-play in strategy games using a variety of AI techniques, including simulated annealing, decision tree learning, and case-based reasoning. We have implemented an AI-bot that uses these techniques to form a novel approach for planning fleet movements and attacks in DEFCON, a nuclear war simulation strategy game released in 2006 by Introversion Software Ltd. The AI-bot retrieves plans from a case-base of recorded games, then uses these to generat...

  19. The effect of flipped teaching combined with modified team-based learning on student performance in physiology.

    Science.gov (United States)

    Gopalan, Chaya; Klann, Megan C

    2017-09-01

    Flipped classroom is a hybrid educational format that shifts guided teaching out of class, thus allowing class time for student-centered learning. Although this innovative teaching format is gaining attention, there is limited evidence on the effectiveness of flipped teaching on student performance. We compared student performance and student attitudes toward flipped teaching with that of traditional lectures using a partial flipped study design. Flipped teaching expected students to have completed preclass material, such as assigned reading, instructor-prepared lecture video(s), and PowerPoint slides. In-class activities included the review of difficult topics, a modified team-based learning (TBL) session, and an individual assessment. In the unflipped teaching format, students were given PowerPoint slides and reading assignment before their scheduled lectures. The class time consisted of podium-style lecture, which was captured in real time and was made available for students to use as needed. Comparison of student performance between flipped and unflipped teaching showed that flipped teaching improved student performance by 17.5%. This was true of students in both the upper and lower half of the class. A survey conducted during this study indicated that 65% of the students changed the way they normally studied, and 69% of the students believed that they were more prepared for class with flipped learning than in the unflipped class. These findings suggest that flipped teaching, combined with TBL, is more effective than the traditional lecture. Copyright © 2017 the American Physiological Society.

  20. A Hybrid Machine Learning Method for Fusing fMRI and Genetic Data: Combining both Improves Classification of Schizophrenia

    Directory of Open Access Journals (Sweden)

    Honghui Yang

    2010-10-01

    Full Text Available We demonstrate a hybrid machine learning method to classify schizophrenia patients and healthy controls, using functional magnetic resonance imaging (fMRI and single nucleotide polymorphism (SNP data. The method consists of four stages: (1 SNPs with the most discriminating information between the healthy controls and schizophrenia patients are selected to construct a support vector machine ensemble (SNP-SVME. (2 Voxels in the fMRI map contributing to classification are selected to build another SVME (Voxel-SVME. (3 Components of fMRI activation obtained with independent component analysis (ICA are used to construct a single SVM classifier (ICA-SVMC. (4 The above three models are combined into a single module using a majority voting approach to make a final decision (Combined SNP-fMRI. The method was evaluated by a fully-validated leave-one-out method using 40 subjects (20 patients and 20 controls. The classification accuracy was: 0.74 for SNP-SVME, 0.82 for Voxel-SVME, 0.83 for ICA-SVMC, and 0.87 for Combined SNP-fMRI. Experimental results show that better classification accuracy was achieved by combining genetic and fMRI data than using either alone, indicating that genetic and brain function representing different, but partially complementary aspects, of schizophrenia etiopathology. This study suggests an effective way to reassess biological classification of individuals with schizophrenia, which is also potentially useful for identifying diagnostically important markers for the disorder.

  1. Effects of ginsenoside of stem and leaf combined with choline on learning and memory ability of rat models with Alzheimer diseases

    Institute of Scientific and Technical Information of China (English)

    Xiaomin Zhao; Xianglin Xie; Zuoli Xia; Yunsheng Gao; Yuyun Zhu; Hongxia Gu

    2006-01-01

    phase: (0.38±0.74), (2.63±1.06) times, P < 0.01]; moreover, effect was stronger than that inGSL group and choline group. The Q value was 1.07 and 1.59, respectively and it showed synergistic effect. ② Spatial localization task: Training times were more in model group than sham operation group, and there was significant difference [(2.9±2.5), (12.6±3.5) times; P < 0.01]. Training times were less in combination group than model group, and there was significant difference [(11.8±2.4), (27.9±2.5) times, P < 0.01]; moreover, effect was stronger than that in GSL group and choline group. The Q value was 1.07 and it showed synergistic effect. ③ Activity of choilne acetylase: Activity was lower in model group than sham operation group, and there was significant difference [(30.56±8.33), (61.11 ±8.33) nkat/g; P < 0.01]. Activity was higher in combination group than model group and there was significant difference [(50.00±8.33), (30.56±8.33) nkat/g, P < 0.01];moreover, effect was stronger than that in GSL group and choline group. The Q value was 1.5 and it showed synergistic effect.CONCLUSION: GSL in combination with choline can synergically improve the disorder of learning and memory of AD model rats. Its mechanism may be involved in enhancing the function of central cholinergic system.

  2. Combining structural modeling with ensemble machine learning to accurately predict protein fold stability and binding affinity effects upon mutation.

    Directory of Open Access Journals (Sweden)

    Niklas Berliner

    Full Text Available Advances in sequencing have led to a rapid accumulation of mutations, some of which are associated with diseases. However, to draw mechanistic conclusions, a biochemical understanding of these mutations is necessary. For coding mutations, accurate prediction of significant changes in either the stability of proteins or their affinity to their binding partners is required. Traditional methods have used semi-empirical force fields, while newer methods employ machine learning of sequence and structural features. Here, we show how combining both of these approaches leads to a marked boost in accuracy. We introduce ELASPIC, a novel ensemble machine learning approach that is able to predict stability effects upon mutation in both, domain cores and domain-domain interfaces. We combine semi-empirical energy terms, sequence conservation, and a wide variety of molecular details with a Stochastic Gradient Boosting of Decision Trees (SGB-DT algorithm. The accuracy of our predictions surpasses existing methods by a considerable margin, achieving correlation coefficients of 0.77 for stability, and 0.75 for affinity predictions. Notably, we integrated homology modeling to enable proteome-wide prediction and show that accurate prediction on modeled structures is possible. Lastly, ELASPIC showed significant differences between various types of disease-associated mutations, as well as between disease and common neutral mutations. Unlike pure sequence-based prediction methods that try to predict phenotypic effects of mutations, our predictions unravel the molecular details governing the protein instability, and help us better understand the molecular causes of diseases.

  3. Uncovering stability mechanisms in microbial ecosystems - combining microcosm experiments, computational modelling and ecological theory in a multidisciplinary approach

    Science.gov (United States)

    Worrich, Anja; König, Sara; Banitz, Thomas; Centler, Florian; Frank, Karin; Kästner, Matthias; Miltner, Anja; Thullner, Martin; Wick, Lukas

    2015-04-01

    Although bacterial degraders in soil are commonly exposed to fluctuating environmental conditions, the functional performance of the biodegradation processes can often be maintained by resistance and resilience mechanisms. However, there is still a gap in the mechanistic understanding of key factors contributing to the stability of such an ecosystem service. Therefore we developed an integrated approach combining microcosm experiments, simulation models and ecological theory to directly make use of the strengths of these disciplines. In a continuous interplay process, data, hypotheses, and central questions are exchanged between disciplines to initiate new experiments and models to ultimately identify buffer mechanisms and factors providing functional stability. We focus on drying and rewetting-cycles in soil ecosystems, which are a major abiotic driver for bacterial activity. Functional recovery of the system was found to depend on different spatial processes in the computational model. In particular, bacterial motility is a prerequisite for biodegradation if either bacteria or substrate are heterogeneously distributed. Hence, laboratory experiments focussing on bacterial dispersal processes were conducted and confirmed this finding also for functional resistance. Obtained results will be incorporated into the model in the next step. Overall, the combination of computational modelling and laboratory experiments identified spatial processes as the main driving force for functional stability in the considered system, and has proved a powerful methodological approach.

  4. Prediction of a Visible Plume from a Dry and Wet Combined Cooling Tower and Its Mechanism of Abatement

    Directory of Open Access Journals (Sweden)

    Kazutaka Takata

    2016-04-01

    Full Text Available Heated moist air from a cooling tower forms a visible plume and needs to be predicted, not only for the performance design of the cooling tower, but also for environmental impact assessments. In this study, a computational fluid dynamics analysis is conducted to predict the scale of a visible plume rising from a cross flow cooling tower with mechanical draft (provided by a rotating fan. The results of computational fluid dynamics analysis are verified by comparing predictions with an actual observed plume. The results show that the predicted visible plume represents the observed plume in an error range of 15%–20%, which is permissible for designing a cooling tower. Additionally, the mixing condition of heated dry air and moist air under dry and wet combined operation is examined, and the condition is thought to affect the scale of the visible plume. It is found that, in the case of a mechanical-draft cooling tower, the fan has a mixing function which performs the complete mixing of wet and dry air, and this suggests that the generation of the plume can be determined by the intersection of the operation line and saturation line. Additionally, the effect of external wind on the scale of the visible plume is large, especially for dry and wet combined operation.

  5. Combining AI Methods for Learning Bots in a Real-Time Strategy Game

    Directory of Open Access Journals (Sweden)

    Robin Baumgarten

    2009-01-01

    Full Text Available We describe an approach for simulating human game-play in strategy games using a variety of AI techniques, including simulated annealing, decision tree learning, and case-based reasoning. We have implemented an AI-bot that uses these techniques to form a novel approach for planning fleet movements and attacks in DEFCON, a nuclear war simulation strategy game released in 2006 by Introversion Software Ltd. The AI-bot retrieves plans from a case-base of recorded games, then uses these to generate a new plan using a method based on decision tree learning. In addition, we have implemented more sophisticated control over low-level actions that enable the AI-bot to synchronize bombing runs, and used a simulated annealing approach for assigning bombing targets to planes and opponent cities to missiles. We describe how our AI-bot operates, and the experimentation we have performed in order to determine an optimal configuration for it. With this configuration, our AI-bot beats Introversion's finite state machine automated player in 76.7% of 150 matches played. We briefly introduce the notion of ability versus enjoyability and discuss initial results of a survey we conducted with human players.

  6. Enhanced Quality Control in Pharmaceutical Applications by Combining Raman Spectroscopy and Machine Learning Techniques

    Science.gov (United States)

    Martinez, J. C.; Guzmán-Sepúlveda, J. R.; Bolañoz Evia, G. R.; Córdova, T.; Guzmán-Cabrera, R.

    2018-06-01

    In this work, we applied machine learning techniques to Raman spectra for the characterization and classification of manufactured pharmaceutical products. Our measurements were taken with commercial equipment, for accurate assessment of variations with respect to one calibrated control sample. Unlike the typical use of Raman spectroscopy in pharmaceutical applications, in our approach the principal components of the Raman spectrum are used concurrently as attributes in machine learning algorithms. This permits an efficient comparison and classification of the spectra measured from the samples under study. This also allows for accurate quality control as all relevant spectral components are considered simultaneously. We demonstrate our approach with respect to the specific case of acetaminophen, which is one of the most widely used analgesics in the market. In the experiments, commercial samples from thirteen different laboratories were analyzed and compared against a control sample. The raw data were analyzed based on an arithmetic difference between the nominal active substance and the measured values in each commercial sample. The principal component analysis was applied to the data for quantitative verification (i.e., without considering the actual concentration of the active substance) of the difference in the calibrated sample. Our results show that by following this approach adulterations in pharmaceutical compositions can be clearly identified and accurately quantified.

  7. Language Learning Enhanced by Massive Multiple Online Role-Playing Games (MMORPGs) and the Underlying Behavioral and Neural Mechanisms

    OpenAIRE

    Zhang, Yongjun; Song, Hongwen; Liu, Xiaoming; Tang, Dinghong; Chen, Yue-e; Zhang, Xiaochu

    2017-01-01

    Massive Multiple Online Role-Playing Games (MMORPGs) have increased in popularity among children, juveniles, and adults since MMORPGs’ appearance in this digital age. MMORPGs can be applied to enhancing language learning, which is drawing researchers’ attention from different fields and many studies have validated MMORPGs’ positive effect on language learning. However, there are few studies on the underlying behavioral or neural mechanism of such effect. This paper reviews the educational app...

  8. Uncovering the Mechanisms Responsible for Why Language Learning May Promote Healthy Cognitive Aging

    Directory of Open Access Journals (Sweden)

    Mark Antoniou

    2017-12-01

    Full Text Available One of the great challenges facing humankind in the 21st century is preserving healthy brain function in our aging population. Individuals over 60 are the fastest growing age group in the world, and by 2050, it is estimated that the number of people over the age of 60 will triple. The typical aging process involves cognitive decline related to brain atrophy, especially in frontal brain areas and regions that subserve declarative memory, loss of synaptic connections, and the emergence of neuropathological symptoms associated with dementia. The disease-state of this age-related cognitive decline is Alzheimer’s disease and other dementias, which may cause older adults to lose their independence and rely on others to live safely, burdening family members and health care systems in the process. However, there are two lines of research that offer hope to those seeking to promote healthy cognitive aging. First, it has been observed that lifestyle variables such as cognitive leisure activities can moderate the risk of Alzheimer’s disease, which has led to the development of plasticity-based interventions for older adults designed to protect against the adverse effects of cognitive decline. Second, there is evidence that lifelong bilingualism acts as a safeguard in preserving healthy brain function, possibly delaying the incidence of dementia by several years. In previous work, we have suggested that foreign language learning programs aimed at older populations are an optimal solution for building cognitive reserve because language learning engages an extensive brain network that is known to overlap with the regions negatively affected by the aging process. Here, we will outline potential future lines of research that may uncover the mechanism responsible for the emergence of language learning related brain advantages, such as language typology, bi- vs. multi-lingualism, age of acquisition, and the elements that are likely to result in the largest

  9. Uncovering the Mechanisms Responsible for Why Language Learning May Promote Healthy Cognitive Aging

    Science.gov (United States)

    Antoniou, Mark; Wright, Sarah M.

    2017-01-01

    One of the great challenges facing humankind in the 21st century is preserving healthy brain function in our aging population. Individuals over 60 are the fastest growing age group in the world, and by 2050, it is estimated that the number of people over the age of 60 will triple. The typical aging process involves cognitive decline related to brain atrophy, especially in frontal brain areas and regions that subserve declarative memory, loss of synaptic connections, and the emergence of neuropathological symptoms associated with dementia. The disease-state of this age-related cognitive decline is Alzheimer’s disease and other dementias, which may cause older adults to lose their independence and rely on others to live safely, burdening family members and health care systems in the process. However, there are two lines of research that offer hope to those seeking to promote healthy cognitive aging. First, it has been observed that lifestyle variables such as cognitive leisure activities can moderate the risk of Alzheimer’s disease, which has led to the development of plasticity-based interventions for older adults designed to protect against the adverse effects of cognitive decline. Second, there is evidence that lifelong bilingualism acts as a safeguard in preserving healthy brain function, possibly delaying the incidence of dementia by several years. In previous work, we have suggested that foreign language learning programs aimed at older populations are an optimal solution for building cognitive reserve because language learning engages an extensive brain network that is known to overlap with the regions negatively affected by the aging process. Here, we will outline potential future lines of research that may uncover the mechanism responsible for the emergence of language learning related brain advantages, such as language typology, bi- vs. multi-lingualism, age of acquisition, and the elements that are likely to result in the largest gains. PMID:29326636

  10. A bifurcation study to guide the design of a landing gear with a combined uplock/downlock mechanism.

    Science.gov (United States)

    Knowles, James A C; Lowenberg, Mark H; Neild, Simon A; Krauskopf, Bernd

    2014-12-08

    This paper discusses the insights that a bifurcation analysis can provide when designing mechanisms. A model, in the form of a set of coupled steady-state equations, can be derived to describe the mechanism. Solutions to this model can be traced through the mechanism's state versus parameter space via numerical continuation, under the simultaneous variation of one or more parameters. With this approach, crucial features in the response surface, such as bifurcation points, can be identified. By numerically continuing these points in the appropriate parameter space, the resulting bifurcation diagram can be used to guide parameter selection and optimization. In this paper, we demonstrate the potential of this technique by considering an aircraft nose landing gear, with a novel locking strategy that uses a combined uplock/downlock mechanism. The landing gear is locked when in the retracted or deployed states. Transitions between these locked states and the unlocked state (where the landing gear is a mechanism) are shown to depend upon the positions of two fold point bifurcations. By performing a two-parameter continuation, the critical points are traced to identify operational boundaries. Following the variation of the fold points through parameter space, a minimum spring stiffness is identified that enables the landing gear to be locked in the retracted state. The bifurcation analysis also shows that the unlocking of a retracted landing gear should use an unlock force measure, rather than a position indicator, to de-couple the effects of the retraction and locking actuators. Overall, the study demonstrates that bifurcation analysis can enhance the understanding of the influence of design choices over a wide operating range where nonlinearity is significant.

  11. A bifurcation study to guide the design of a landing gear with a combined uplock/downlock mechanism

    Science.gov (United States)

    Knowles, James A. C.; Lowenberg, Mark H.; Neild, Simon A.; Krauskopf, Bernd

    2014-01-01

    This paper discusses the insights that a bifurcation analysis can provide when designing mechanisms. A model, in the form of a set of coupled steady-state equations, can be derived to describe the mechanism. Solutions to this model can be traced through the mechanism's state versus parameter space via numerical continuation, under the simultaneous variation of one or more parameters. With this approach, crucial features in the response surface, such as bifurcation points, can be identified. By numerically continuing these points in the appropriate parameter space, the resulting bifurcation diagram can be used to guide parameter selection and optimization. In this paper, we demonstrate the potential of this technique by considering an aircraft nose landing gear, with a novel locking strategy that uses a combined uplock/downlock mechanism. The landing gear is locked when in the retracted or deployed states. Transitions between these locked states and the unlocked state (where the landing gear is a mechanism) are shown to depend upon the positions of two fold point bifurcations. By performing a two-parameter continuation, the critical points are traced to identify operational boundaries. Following the variation of the fold points through parameter space, a minimum spring stiffness is identified that enables the landing gear to be locked in the retracted state. The bifurcation analysis also shows that the unlocking of a retracted landing gear should use an unlock force measure, rather than a position indicator, to de-couple the effects of the retraction and locking actuators. Overall, the study demonstrates that bifurcation analysis can enhance the understanding of the influence of design choices over a wide operating range where nonlinearity is significant. PMID:25484601

  12. Education of the Mechanical Engineering Literacy by the Collaboration Learning of the Different Grade

    Science.gov (United States)

    Nakashima, Kenji; Nakaura, Shigeki; Morita, Hidetoshi; Matsuyama, Fuminori; Nishiguchi, Hiroshi; Fukuda, Takayuki

    We trained business ability of the students through the senior instructing younger student system by fourth year students in the class of the practical skill. The theme of the practical skill is the resolution and the assembling of the gasoline engine, the automatic control of the radio control car with the PLC, the learning of dynamics using Mini-Yonku and the operation of the laser cutter. For the fourth students, we can expect an effect of their ability in the future work. For the first students, we can expect an effect for them to be interested in mechanical engineering. Concerning the effects of this project, all the fourth students and teachers discussed, and the effect of the project was evaluated by a poster session. As a result, we have found that more effects than we had expected has been gained.

  13. Mechanisms for Creating a Psychologically Safe Learning Environment in an Educational Institution of General Education

    Directory of Open Access Journals (Sweden)

    Leonova O.I.,

    2014-11-01

    Full Text Available At the moment the question of how to create and maintain the psychological safety of the educational environment of the school is not sufficiently studied. Meanwhile, there has been proved its positive effect on the psychological health of students, their emotional and personal well-being, the formation of a meta-subjective and personal educational outcomes. This paper describes a study the purpose of which was to examine and verify empiricaly the features of management activities in the educational organization to create a psychologically safe learning environment. We studied personality traits of the Head of an educational organization by the procedure "Troubleshooting leadership abilities" (E. Zharikova, E. Krushelnytsky, techniques "Diagnosis of the level of burnout" (V.V. Boyko, methods of self-management style assessment (A.V. Agrashenkova, modified by E.P. Ilyin, and methods for rapid assessment of health, activity, mood (SAN. We proposed mechanisms to solve the problem of creating a comfortable and safe learning environment in the educational organization of general education

  14. Robust automated classification of first-motion polarities for focal mechanism determination with machine learning

    Science.gov (United States)

    Ross, Z. E.; Meier, M. A.; Hauksson, E.

    2017-12-01

    Accurate first-motion polarities are essential for determining earthquake focal mechanisms, but are difficult to measure automatically because of picking errors and signal to noise issues. Here we develop an algorithm for reliable automated classification of first-motion polarities using machine learning algorithms. A classifier is designed to identify whether the first-motion polarity is up, down, or undefined by examining the waveform data directly. We first improve the accuracy of automatic P-wave onset picks by maximizing a weighted signal/noise ratio for a suite of candidate picks around the automatic pick. We then use the waveform amplitudes before and after the optimized pick as features for the classification. We demonstrate the method's potential by training and testing the classifier on tens of thousands of hand-made first-motion picks by the Southern California Seismic Network. The classifier assigned the same polarity as chosen by an analyst in more than 94% of the records. We show that the method is generalizable to a variety of learning algorithms, including neural networks and random forest classifiers. The method is suitable for automated processing of large seismic waveform datasets, and can potentially be used in real-time applications, e.g. for improving the source characterizations of earthquake early warning algorithms.

  15. [Possible evolutionary mechanisms of 'culture' in animals: The hypothesis of distributed social learning].

    Science.gov (United States)

    Reznikova, Zh I; Panteleeva, S N

    2015-01-01

    There is a plethora of works on the origin and genesis of behavioral traditions in different animal species. Nevertheless, it still remains unclear as for which factors facilitate and which factors hinder the spreading those forms of behavior that are new for a population. Here, we present an analytical review on the topic, considering also the results of studies on 'culture' in animals and analyzing contradictions that arise when attempting to clarify the ethological mechanisms of cultural succession. The hypothesis of 'distributed social learning' is formulated, meaning that for spreading of complex behavioral stereotypes in a population the presence of few carriers of consistent stereotypes is enough under the condition that the rest of animals carry incomplete genetic programmes that start up these stereotypes. Existence of 'dormant' fragments of such programmes determines an inborn predisposition of their bearer to perform a certain sequence of acts. To complete the consistent stereotype, the simplest forms of social learning ('social alleviation') turn to be enough. The hypothesis is examined at the behavioral level and supported by experimental data obtained when studying the scenarios of hunting behavior development in ants Myrmica rubra L. It makes possible to explain the spreading of behavioral models in animal communities in a simpler way than cultural succession.

  16. Modulation of learning and memory by cytokines: signaling mechanisms and long term consequences.

    Science.gov (United States)

    Donzis, Elissa J; Tronson, Natalie C

    2014-11-01

    This review describes the role of cytokines and their downstream signaling cascades on the modulation of learning and memory. Immune proteins are required for many key neural processes and dysregulation of these functions by systemic inflammation can result in impairments of memory that persist long after the resolution of inflammation. Recent research has demonstrated that manipulations of individual cytokines can modulate learning, memory, and synaptic plasticity. The many conflicting findings, however, have prevented a clear understanding of the precise role of cytokines in memory. Given the complexity of inflammatory signaling, understanding its modulatory role requires a shift in focus from single cytokines to a network of cytokine interactions and elucidation of the cytokine-dependent intracellular signaling cascades. Finally, we propose that whereas signal transduction and transcription may mediate short-term modulation of memory, long-lasting cellular and molecular mechanisms such as epigenetic modifications and altered neurogenesis may be required for the long lasting impact of inflammation on memory and cognition. Copyright © 2014 Elsevier Inc. All rights reserved.

  17. eLearning course may shorten the duration of mechanical restraint among psychiatric inpatients: a cluster-randomized trial.

    Science.gov (United States)

    Kontio, Raija; Pitkänen, Anneli; Joffe, Grigori; Katajisto, Jouko; Välimäki, Maritta

    2014-10-01

    The management of psychiatric inpatients exhibiting severely disturbed and aggressive behaviour is an important educational topic. Well structured, IT-based educational programmes (eLearning) often ensure quality and may make training more affordable and accessible. The aim of this study was to explore the impact of an eLearning course for personnel on the rates and duration of seclusion and mechanical restraint among psychiatric inpatients. In a cluster-randomized intervention trial, the nursing personnel on 10 wards were randomly assigned to eLearning (intervention) or training-as-usual (control) groups. The eLearning course comprised six modules with specific topics (legal and ethical issues, behaviour-related factors, therapeutic relationship and self-awareness, teamwork and integrating knowledge with practice) and specific learning methods. The rates (incidents per 1000 occupied bed days) and durations of the coercion incidents were examined before and after the course. A total of 1283 coercion incidents (1143 seclusions [89%] and 140 incidents involving the use of mechanical restraints [11%]) were recorded on the study wards during the data collection period. On the intervention wards, there were no statistically significant changes in the rates of seclusion and mechanical restraint. However, the duration of incidents involving mechanical restraints shortened from 36.0 to 4.0 h (median) (P eLearning course, the duration of incidents involving the use of mechanical restraints decreased. However, more studies are needed to ensure that the content of the course focuses on the most important factors associated with the seclusion-related elements. The eLearning course deserves further development and further studies. The duration of coercion incidents merits attention in future research.

  18. Combined comparative and chemical proteomics on the mechanisms of levo-tetrahydropalmatine-induced antinociception in the formalin test.

    Science.gov (United States)

    Wang, Chen; Zhou, Jiangrui; Wang, Shuowen; Ye, Mingliang; Jiang, Chunlei; Fan, Guorong; Zou, Hanfa

    2010-06-04

    This study investigated the mechanisms involved in the antinociceptive action induced by levo-tetrahydropalmatine (l-THP) in the formalin test by combined comparative and chemical proteomics. Rats were pretreated with l-THP by the oral route (40 mg/kg) 1 h before formalin injection. The antinociceptive effect of l-THP was shown in the first and second phases of the formalin test. To address the mechanisms by which l-THP inhibits formalin-induced nociception in rats, the combined comparative and chemical proteomics were applied. A novel high-throughput comparative proteomic approach based on 2D-nano-LC-MS/MS was applied to simultaneously evaluate the deregulated proteins involved in the response of l-THP treatment in formalin-induced pain rats. Thousands of proteins were identified, among which 17 proteins survived the stringent filter criteria and were further included for functional discussion. Two proteins (Neurabin-1 and Calcium-dependent secretion activator 1) were randomly selected, and their expression levels were further confirmed by Western Blots. The results matched well with those of proteomics. In the present study, we also described the development and application of l-THP immobilized beads to bind the targets. Following incubation with cellular lysates, the proteome interacting with the fixed l-THP was identified. The results of comparative and chemical proteomics were quite complementary. Although the precise roles of these identified moleculars in l-THP-induced antinociception need further study, the combined results indicated that proteins associated with signal transduction, vesicular trafficking and neurotransmitter release, energy metabolism, and ion transport play important roles in l-THP-induced antinociception in the formalin test.

  19. Remembering to learn: independent place and journey coding mechanisms contribute to memory transfer.

    Science.gov (United States)

    Bahar, Amir S; Shapiro, Matthew L

    2012-02-08

    The neural mechanisms that integrate new episodes with established memories are unknown. When rats explore an environment, CA1 cells fire in place fields that indicate locations. In goal-directed spatial memory tasks, some place fields differentiate behavioral histories ("journey-dependent" place fields) while others do not ("journey-independent" place fields). To investigate how these signals inform learning and memory for new and familiar episodes, we recorded CA1 and CA3 activity in rats trained to perform a "standard" spatial memory task in a plus maze and in two new task variants. A "switch" task exchanged the start and goal locations in the same environment; an "altered environment" task contained unfamiliar local and distal cues. In the switch task, performance was mildly impaired, new firing maps were stable, but the proportion and stability of journey-dependent place fields declined. In the altered environment, overall performance was strongly impaired, new firing maps were unstable, and stable proportions of journey-dependent place fields were maintained. In both tasks, memory errors were accompanied by a decline in journey codes. The different dynamics of place and journey coding suggest that they reflect separate mechanisms and contribute to distinct memory computations. Stable place fields may represent familiar relationships among environmental features that are required for consistent memory performance. Journey-dependent activity may correspond with goal-directed behavioral sequences that reflect expectancies that generalize across environments. The complementary signals could help link current events with established memories, so that familiarity with either a behavioral strategy or an environment can inform goal-directed learning.

  20. Mechanical energy profiles of the combined ankle-foot system in normal gait: insights for prosthetic designs.

    Science.gov (United States)

    Takahashi, Kota Z; Stanhope, Steven J

    2013-09-01

    Over the last half-century, the field of prosthetic engineering has continuously evolved with much attention being dedicated to restoring the mechanical energy properties of ankle joint musculatures during gait. However, the contributions of 'distal foot structures' (e.g., foot muscles, plantar soft tissue) have been overlooked. Therefore, the purpose of this study was to quantify the total mechanical energy profiles (e.g., power, work, and work-ratio) of the natural ankle-foot system (NAFS) by combining the contributions of the ankle joint and all distal foot structures during stance in level-ground steady state walking across various speeds (0.4, 0.6, 0.8 and 1.0 statures/s). The results from eleven healthy subjects walking barefoot indicated ankle joint and distal foot structures generally performed opposing roles: the ankle joint performed net positive work that systematically increased its energy generation with faster walking speeds, while the distal foot performed net negative work that systematically increased its energy absorption with faster walking speeds. Accounting for these simultaneous effects, the combined ankle-foot system exhibited increased work-ratios with faster walking. Most notably, the work-ratio was not significantly greater than 1.0 during the normal walking speed of 0.8 statures/s. Therefore, a prosthetic design that strategically exploits passive-dynamic properties (e.g., elastic energy storage and return) has the potential to replicate the mechanical energy profiles of the NAFS during level-ground steady-state walking. Copyright © 2013 Elsevier B.V. All rights reserved.

  1. Combined quantum mechanics/molecular mechanics (QM/MM) simulations for protein-ligand complexes: free energies of binding of water molecules in influenza neuraminidase.

    Science.gov (United States)

    Woods, Christopher J; Shaw, Katherine E; Mulholland, Adrian J

    2015-01-22

    The applicability of combined quantum mechanics/molecular mechanics (QM/MM) methods for the calculation of absolute binding free energies of conserved water molecules in protein/ligand complexes is demonstrated. Here, we apply QM/MM Monte Carlo simulations to investigate binding of water molecules to influenza neuraminidase. We investigate five different complexes, including those with the drugs oseltamivir and peramivir. We investigate water molecules in two different environments, one more hydrophobic and one hydrophilic. We calculate the free-energy change for perturbation of a QM to MM representation of the bound water molecule. The calculations are performed at the BLYP/aVDZ (QM) and TIP4P (MM) levels of theory, which we have previously demonstrated to be consistent with one another for QM/MM modeling. The results show that the QM to MM perturbation is significant in both environments (greater than 1 kcal mol(-1)) and larger in the more hydrophilic site. Comparison with the same perturbation in bulk water shows that this makes a contribution to binding. The results quantify how electronic polarization differences in different environments affect binding affinity and also demonstrate that extensive, converged QM/MM free-energy simulations, with good levels of QM theory, are now practical for protein/ligand complexes.

  2. Theoretical Characterization of the Spectral Density of the Water-Soluble Chlorophyll-Binding Protein from Combined Quantum Mechanics/Molecular Mechanics Molecular Dynamics Simulations.

    Science.gov (United States)

    Rosnik, Andreana M; Curutchet, Carles

    2015-12-08

    Over the past decade, both experimentalists and theorists have worked to develop methods to describe pigment-protein coupling in photosynthetic light-harvesting complexes in order to understand the molecular basis of quantum coherence effects observed in photosynthesis. Here we present an improved strategy based on the combination of quantum mechanics/molecular mechanics (QM/MM) molecular dynamics (MD) simulations and excited-state calculations to predict the spectral density of electronic-vibrational coupling. We study the water-soluble chlorophyll-binding protein (WSCP) reconstituted with Chl a or Chl b pigments as the system of interest and compare our work with data obtained by Pieper and co-workers from differential fluorescence line-narrowing spectra (Pieper et al. J. Phys. Chem. B 2011, 115 (14), 4042-4052). Our results demonstrate that the use of QM/MM MD simulations where the nuclear positions are still propagated at the classical level leads to a striking improvement of the predicted spectral densities in the middle- and high-frequency regions, where they nearly reach quantitative accuracy. This demonstrates that the so-called "geometry mismatch" problem related to the use of low-quality structures in QM calculations, not the quantum features of pigments high-frequency motions, causes the failure of previous studies relying on similar protocols. Thus, this work paves the way toward quantitative predictions of pigment-protein coupling and the comprehension of quantum coherence effects in photosynthesis.

  3. Combined quantum-mechanics/molecular-mechanics dynamics simulation of A-DNA double strands irradiated by ultra-low-energy carbon ions

    Energy Technology Data Exchange (ETDEWEB)

    Ngaojampa, C.; Nimmanpipug, P. [Computer Simulation and Modeling Laboratory (CSML), Department of Chemistry and Center for Innovation Chemistry, Faculty of Science, Chiang Mai University, Chiang Mai 50200 (Thailand); Yu, L.D., E-mail: yuld@fnrf.science.cmu.ac.t [Plasma and Beam Physics Research Facility, Department of Physics and Materials Science, Faculty of Science, Chiang Mai University, Chiang Mai 50200 (Thailand); Thailand Center of Excellence in Physics, Commission on Higher Education, 328 Si Ayutthaya Road, Bangkok 10400 (Thailand); Anuntalabhochai, S. [Molecular Biology Laboratory, Department of Biology, Faculty of Science, Chiang Mai University, Chiang Mai 50200 (Thailand); Lee, V.S., E-mail: vannajan@gmail.co [Computer Simulation and Modeling Laboratory (CSML), Department of Chemistry and Center for Innovation Chemistry, Faculty of Science, Chiang Mai University, Chiang Mai 50200 (Thailand); Thailand Center of Excellence in Physics, Commission on Higher Education, 328 Si Ayutthaya Road, Bangkok 10400 (Thailand)

    2011-02-15

    In order to promote understanding of the fundamentals of ultra-low-energy ion interaction with DNA, molecular dynamics simulations using combined quantum-mechanics/molecular-mechanics of poly-AT and poly-GC A-DNA double strands irradiated by <200 eV carbon ions were performed to investigate the molecular implications of mutation bias. The simulations were focused on the responses of the DNA backbones and nitrogenous bases to irradiation. Analyses of the root mean square displacements of the backbones and non-hydrogen atoms of base rings of the simulated DNA structure after irradiation revealed a potential preference of DNA double strand separation, dependent on the irradiating energy. The results show that for the backbones, the large difference in the displacement between poly-GC and poly-AT in the initial time period could be the reason for the backbone breakage; for the nitrogenous base pairs, A-T is 30% more sensitive or vulnerable to ion irradiation than G-C, demonstrating a preferential, instead of random, effect of irradiation-induced mutation.

  4. Combined quantum-mechanics/molecular-mechanics dynamics simulation of A-DNA double strands irradiated by ultra-low-energy carbon ions

    International Nuclear Information System (INIS)

    Ngaojampa, C.; Nimmanpipug, P.; Yu, L.D.; Anuntalabhochai, S.; Lee, V.S.

    2011-01-01

    In order to promote understanding of the fundamentals of ultra-low-energy ion interaction with DNA, molecular dynamics simulations using combined quantum-mechanics/molecular-mechanics of poly-AT and poly-GC A-DNA double strands irradiated by <200 eV carbon ions were performed to investigate the molecular implications of mutation bias. The simulations were focused on the responses of the DNA backbones and nitrogenous bases to irradiation. Analyses of the root mean square displacements of the backbones and non-hydrogen atoms of base rings of the simulated DNA structure after irradiation revealed a potential preference of DNA double strand separation, dependent on the irradiating energy. The results show that for the backbones, the large difference in the displacement between poly-GC and poly-AT in the initial time period could be the reason for the backbone breakage; for the nitrogenous base pairs, A-T is 30% more sensitive or vulnerable to ion irradiation than G-C, demonstrating a preferential, instead of random, effect of irradiation-induced mutation.

  5. Tuned and Balanced Redistributed Charge Scheme for Combined Quantum Mechanical and Molecular Mechanical (QM/MM) Methods and Fragment Methods: Tuning Based on the CM5 Charge Model.

    Science.gov (United States)

    Wang, Bo; Truhlar, Donald G

    2013-02-12

    Tuned and balanced redistributed charge schemes have been developed for modeling the electrostatic fields of bonds that are cut by a quantum mechanical-molecular mechanical boundary in combined quantum mechanical and molecular mechanical (QM/MM) methods. First, the charge is balanced by adjusting the charge on the MM boundary atom to conserve the total charge of the entire QM/MM system. In the balanced smeared redistributed charge (BSRC) scheme, the adjusted MM boundary charge is smeared with a smearing width of 1.0 Å and is distributed in equal portions to the midpoints of the bonds between the MM boundary atom and the MM atoms bonded to it; in the balanced redistributed charge-2 (BRC2) scheme, the adjusted MM boundary charge is distributed as point charges in equal portions to the MM atoms that are bonded to the MM boundary atom. The QM subsystem is capped by a fluorine atom that is tuned to reproduce the sum of partial atomic charges of the uncapped portion of the QM subsystem. The new aspect of the present study is a new way to carry out the tuning process; in particular, the CM5 charge model, rather than the Mulliken population analysis applied in previous studies, is used for tuning the capping atom that terminates the dangling bond of the QM region. The mean unsigned error (MUE) of the QM/MM deprotonation energy for a 15-system test suite of deprotonation reactions is 2.3 kcal/mol for the tuned BSRC scheme (TBSRC) and 2.4 kcal/mol for the tuned BRC2 scheme (TBRC2). As was the case for the original tuning method based on Mulliken charges, the new tuning method performs much better than using conventional hydrogen link atoms, which have an MUE on this test set of about 7 kcal/mol. However, the new scheme eliminates the need to use small basis sets, which can be problematic, and it allows one to be more consistent by tuning the parameters with whatever basis set is appropriate for applications. (Alternatively, since the tuning parameters and partial charges

  6. Games and machine learning: a powerful combination in an artificial intelligence course

    Science.gov (United States)

    Wallace, Scott A.; McCartney, Robert; Russell, Ingrid

    2010-03-01

    Project MLeXAI (Machine Learning eXperiences in Artificial Intelligence (AI)) seeks to build a set of reusable course curriculum and hands on laboratory projects for the artificial intelligence classroom. In this article, we describe two game-based projects from the second phase of project MLeXAI: Robot Defense - a simple real-time strategy game and Checkers - a classic turn-based board game. From the instructors' prospective, we examine aspects of design and implementation as well as the challenges and rewards of using the curricula. We explore students' responses to the projects via the results of a common survey. Finally, we compare the student perceptions from the game-based projects to non-game based projects from the first phase of Project MLeXAI.

  7. Combining Machine Learning and Nanofluidic Technology To Diagnose Pancreatic Cancer Using Exosomes.

    Science.gov (United States)

    Ko, Jina; Bhagwat, Neha; Yee, Stephanie S; Ortiz, Natalia; Sahmoud, Amine; Black, Taylor; Aiello, Nicole M; McKenzie, Lydie; O'Hara, Mark; Redlinger, Colleen; Romeo, Janae; Carpenter, Erica L; Stanger, Ben Z; Issadore, David

    2017-11-28

    Circulating exosomes contain a wealth of proteomic and genetic information, presenting an enormous opportunity in cancer diagnostics. While microfluidic approaches have been used to successfully isolate cells from complex samples, scaling these approaches for exosome isolation has been limited by the low throughput and susceptibility to clogging of nanofluidics. Moreover, the analysis of exosomal biomarkers is confounded by substantial heterogeneity between patients and within a tumor itself. To address these challenges, we developed a multichannel nanofluidic system to analyze crude clinical samples. Using this platform, we isolated exosomes from healthy and diseased murine and clinical cohorts, profiled the RNA cargo inside of these exosomes, and applied a machine learning algorithm to generate predictive panels that could identify samples derived from heterogeneous cancer-bearing individuals. Using this approach, we classified cancer and precancer mice from healthy controls, as well as pancreatic cancer patients from healthy controls, in blinded studies.

  8. The Combined Effects of Classroom Teaching and Learning Strategy Use on Students' Chemistry Self-Efficacy

    Science.gov (United States)

    Cheung, Derek

    2015-02-01

    For students to be successful in school chemistry, a strong sense of self-efficacy is essential. Chemistry self-efficacy can be defined as students' beliefs about the extent to which they are capable of performing specific chemistry tasks. According to Bandura (Psychol. Rev. 84:191-215, 1977), students acquire information about their level of self-efficacy from four sources: performance accomplishments, vicarious experiences, verbal persuasion, and physiological states. No published studies have investigated how instructional strategies in chemistry lessons can provide students with positive experiences with these four sources of self-efficacy information and how the instructional strategies promote students' chemistry self-efficacy. In this study, questionnaire items were constructed to measure student perceptions about instructional strategies, termed efficacy-enhancing teaching, which can provide positive experiences with the four sources of self-efficacy information. Structural equation modeling was then applied to test a hypothesized mediation model, positing that efficacy-enhancing teaching positively affects students' chemistry self-efficacy through their use of deep learning strategies such as metacognitive control strategies. A total of 590 chemistry students at nine secondary schools in Hong Kong participated in the survey. The mediation model provided a good fit to the student data. Efficacy-enhancing teaching had a direct effect on students' chemistry self-efficacy. Efficacy-enhancing teaching also directly affected students' use of deep learning strategies, which in turn affected students' chemistry self-efficacy. The implications of these findings for developing secondary school students' chemistry self-efficacy are discussed.

  9. Two different motor learning mechanisms contribute to learning reaching movements in a rotated visual environment [version 2; referees: 2 approved, 1 approved with reservations

    Directory of Open Access Journals (Sweden)

    Virginia Way Tong Chu

    2014-12-01

    Full Text Available Practice of movement in virtual-reality and other artificially altered environments has been proposed as a method for rehabilitation following neurological injury and for training new skills in healthy humans.  For such training to be useful, there must be transfer of learning from the artificial environment to the performance of desired skills in the natural environment.  Therefore an important assumption of such methods is that practice in the altered environment engages the same learning and plasticity mechanisms that are required for skill performance in the natural environment.  We test the hypothesis that transfer of learning may fail because the learning and plasticity mechanism that adapts to the altered environment is different from the learning mechanism required for improvement of motor skill.  In this paper, we propose that a model that separates skill learning and environmental adaptation is necessary to explain the learning and aftereffects that are observed in virtual reality experiments.  In particular, we studied the condition where practice in the altered environment should lead to correct skill performance in the original environment. Our 2-mechanism model predicts that aftereffects will still be observed when returning to the original environment, indicating a lack of skill transfer from the artificial environment to the original environment. To illustrate the model prediction, we tested 10 healthy participants on the interaction between a simple overlearned motor skill (straight hand movements to targets in different directions and an artificially altered visuomotor environment (rotation of visual feedback of the results of movement.  As predicted by the models, participants show adaptation to the altered environment and after-effects on return to the baseline environment even when practice in the altered environment should have led to correct skill performance.  The presence of aftereffect under all conditions that

  10. Molecular mechanisms for inhibition of colon cancer cells by combined epigenetic-modulating epigallocatechin gallate and sodium butyrate

    Energy Technology Data Exchange (ETDEWEB)

    Saldanha, Sabita N., E-mail: sabivan@uab.edu [Department of Biology, University of Alabama at Birmingham, 175 Campbell Hall, 1300 University Boulevard, Birmingham, AL 35294 (United States); Department of Biological Sciences, Alabama State University, Montgomery, AL 36104 (United States); Kala, Rishabh [Department of Biology, University of Alabama at Birmingham, 175 Campbell Hall, 1300 University Boulevard, Birmingham, AL 35294 (United States); Tollefsbol, Trygve O., E-mail: trygve@uab.edu [Department of Biology, University of Alabama at Birmingham, 175 Campbell Hall, 1300 University Boulevard, Birmingham, AL 35294 (United States); Comprehensive Cancer Center, University of Alabama at Birmingham, Birmingham, AL 35294 (United States); Comprehensive Center for Healthy Aging, University of Alabama at Birmingham, Birmingham, AL 35294 (United States); Nutrition Obesity Research Center, University of Alabama at Birmingham, Birmingham, AL 35294 (United States); Comprehensive Diabetes Research Center, University of Alabama at Birmingham, Birmingham, AL 35294 (United States)

    2014-05-15

    Bioactive compounds are considered safe and have been shown to alter genetic and epigenetic profiles of tumor cells. However, many of these changes have been reported at molecular concentrations higher than physiologically achievable levels. We investigated the role of the combinatorial effects of epigallocatechin gallate (EGCG), a predominant polyphenol in green tea, and sodium butyrate (NaB), a dietary microbial fermentation product of fiber, in the regulation of survivin, which is an overexpressed anti-apoptotic protein in colon cancer cells. For the first time, our study showed that the combination treatment induced apoptosis and cell cycle arrest in RKO, HCT-116 and HT-29 colorectal cancer cells. This was found to be regulated by the decrease in HDAC1, DNMT1, survivin and HDAC activity in all three cell lines. A G2/M arrest was observed for RKO and HCT-116 cells, and G1 arrest for HT-29 colorectal cancer cells for combinatorial treatment. Further experimentation of the molecular mechanisms in RKO colorectal cancer (CRC) cells revealed a p53-dependent induction of p21 and an increase in nuclear factor kappa B (NF-κB)-p65. An increase in double strand breaks as determined by gamma-H2A histone family member X (γ-H2AX) protein levels and induction of histone H3 hyperacetylation was also observed with the combination treatment. Further, we observed a decrease in global CpG methylation. Taken together, these findings suggest that at low and physiologically achievable concentrations, combinatorial EGCG and NaB are effective in promoting apoptosis, inducing cell cycle arrest and DNA-damage in CRC cells. - Highlights: • EGCG and NaB as a combination inhibits colorectal cancer cell proliferation. • The combination treatment induces DNA damage, G2/M and G1 arrest and apoptosis. • Survivin is effectively down-regulated by the combination treatment. • p21 and p53 expressions are induced by the combination treatment. • Epigenetic proteins DNMT1 and HDAC1 are

  11. Molecular mechanisms for inhibition of colon cancer cells by combined epigenetic-modulating epigallocatechin gallate and sodium butyrate

    International Nuclear Information System (INIS)

    Saldanha, Sabita N.; Kala, Rishabh; Tollefsbol, Trygve O.

    2014-01-01

    Bioactive compounds are considered safe and have been shown to alter genetic and epigenetic profiles of tumor cells. However, many of these changes have been reported at molecular concentrations higher than physiologically achievable levels. We investigated the role of the combinatorial effects of epigallocatechin gallate (EGCG), a predominant polyphenol in green tea, and sodium butyrate (NaB), a dietary microbial fermentation product of fiber, in the regulation of survivin, which is an overexpressed anti-apoptotic protein in colon cancer cells. For the first time, our study showed that the combination treatment induced apoptosis and cell cycle arrest in RKO, HCT-116 and HT-29 colorectal cancer cells. This was found to be regulated by the decrease in HDAC1, DNMT1, survivin and HDAC activity in all three cell lines. A G2/M arrest was observed for RKO and HCT-116 cells, and G1 arrest for HT-29 colorectal cancer cells for combinatorial treatment. Further experimentation of the molecular mechanisms in RKO colorectal cancer (CRC) cells revealed a p53-dependent induction of p21 and an increase in nuclear factor kappa B (NF-κB)-p65. An increase in double strand breaks as determined by gamma-H2A histone family member X (γ-H2AX) protein levels and induction of histone H3 hyperacetylation was also observed with the combination treatment. Further, we observed a decrease in global CpG methylation. Taken together, these findings suggest that at low and physiologically achievable concentrations, combinatorial EGCG and NaB are effective in promoting apoptosis, inducing cell cycle arrest and DNA-damage in CRC cells. - Highlights: • EGCG and NaB as a combination inhibits colorectal cancer cell proliferation. • The combination treatment induces DNA damage, G2/M and G1 arrest and apoptosis. • Survivin is effectively down-regulated by the combination treatment. • p21 and p53 expressions are induced by the combination treatment. • Epigenetic proteins DNMT1 and HDAC1 are

  12. Suitability of a PLCL fibrous scaffold for soft tissue engineering applications: A combined biological and mechanical characterisation.

    Science.gov (United States)

    Laurent, Cédric P; Vaquette, Cédryck; Liu, Xing; Schmitt, Jean-François; Rahouadj, Rachid

    2018-04-01

    Poly(lactide-co-ε-caprolactone) (PLCL) has been reported to be a good candidate for tissue engineering because of its good biocompatibility. Particularly, a braided PLCL scaffold (PLL/PCL ratio = 85/15) has been recently designed and partially validated for ligament tissue engineering. In the present study, we assessed the in vivo biocompatibility of acellular and cellularised scaffolds in a rat model. We then determined its in vitro biocompatibility using stem cells issued from both bone marrow and Wharton Jelly. From a biological point of view, the scaffold was shown to be suitable for tissue engineering in all these cases. Secondly, while the initial mechanical properties of this scaffold have been previously reported to be adapted to load-bearing applications, we studied the evolution in time of the mechanical properties of PLCL fibres due to hydrolytic degradation. Results for isolated PLCL fibres were extrapolated to the fibrous scaffold using a previously developed numerical model. It was shown that no accumulation of plastic strain was to be expected for a load-bearing application such as anterior cruciate ligament tissue engineering. However, PLCL fibres exhibited a non-expected brittle behaviour after two months. This may involve a potential risk of premature failure of the scaffold, unless tissue growth compensates this change in mechanical properties. This combined study emphasises the need to characterise the properties of biomaterials in a pluridisciplinary approach, since biological and mechanical characterisations led in this case to different conclusions concerning the suitability of this scaffold for load-bearing applications.

  13. Structure property relationship of biological nano composites studies by combination of in-situ synchrotron scattering and mechanical tests

    International Nuclear Information System (INIS)

    Martinschitz, K.

    2005-06-01

    Biological materials represent hierarchical nano fibre composites with complicated morphology and architecture varying on the nm level. The mechanical response of those materials is influenced by many parameters like chemical composition and crystal structure of constituents, preferred orientation, internal morphology with specific sizes of features etc. In-situ wide-angle x-ray scattering (WAXS) combined with mechanical tests provide a unique means to evaluate structural changes in biological materials at specific stages of tensile experiments. In this way it is possible to identify distinct architectural/compositional elements responsible for specific mechanical characteristics of the biological materials. In this thesis, structure-property relationship is analyzed using in-situ WAXS in the tissues of Picea abies, coir fibre, bacterial cellulose and cellulose II based composites. The experiments were performed at the beamline ID01 of European synchrotron radiation facility in Grenoble, France. The tissues were strained in a tensile stage, while the structural changes were monitored using WAXS. Complex straining procedures were applied including cyclic straining. One of the main goals was to understand the stiffness recovery and strain hardening effects in the tissues. The results demonstrate that, in all cellulosics, the orientation of the cellulose crystallites is only the function of the external strain while the stiffness depends on the specific stage of the tensile experiment. Whenever the strain is increased, the tissues exhibit stiffness equal or larger than the initial one. The recovery of the mechanical function is attributed to the molecular mechanistic effects operating between the crystalline domains of the cellulose. (author)

  14. Prediction of hot spot residues at protein-protein interfaces by combining machine learning and energy-based methods

    Directory of Open Access Journals (Sweden)

    Pontil Massimiliano

    2009-10-01

    Full Text Available Abstract Background Alanine scanning mutagenesis is a powerful experimental methodology for investigating the structural and energetic characteristics of protein complexes. Individual amino-acids are systematically mutated to alanine and changes in free energy of binding (ΔΔG measured. Several experiments have shown that protein-protein interactions are critically dependent on just a few residues ("hot spots" at the interface. Hot spots make a dominant contribution to the free energy of binding and if mutated they can disrupt the interaction. As mutagenesis studies require significant experimental efforts, there is a need for accurate and reliable computational methods. Such methods would also add to our understanding of the determinants of affinity and specificity in protein-protein recognition. Results We present a novel computational strategy to identify hot spot residues, given the structure of a complex. We consider the basic energetic terms that contribute to hot spot interactions, i.e. van der Waals potentials, solvation energy, hydrogen bonds and Coulomb electrostatics. We treat them as input features and use machine learning algorithms such as Support Vector Machines and Gaussian Processes to optimally combine and integrate them, based on a set of training examples of alanine mutations. We show that our approach is effective in predicting hot spots and it compares favourably to other available methods. In particular we find the best performances using Transductive Support Vector Machines, a semi-supervised learning scheme. When hot spots are defined as those residues for which ΔΔG ≥ 2 kcal/mol, our method achieves a precision and a recall respectively of 56% and 65%. Conclusion We have developed an hybrid scheme in which energy terms are used as input features of machine learning models. This strategy combines the strengths of machine learning and energy-based methods. Although so far these two types of approaches have mainly been

  15. Using optimal combination of teaching-learning methods (open book assignment and group tutorials) as revision exercises to improve learning outcome in low achievers in biochemistry.

    Science.gov (United States)

    Rajappa, Medha; Bobby, Zachariah; Nandeesha, H; Suryapriya, R; Ragul, Anithasri; Yuvaraj, B; Revathy, G; Priyadarssini, M

    2016-07-08

    Graduate medical students of India are taught Biochemistry by didactic lectures and they hardly get any opportunity to clarify their doubts and reinforce the concepts which they learn in these lectures. We used a combination of teaching-learning (T-L) methods (open book assignment followed by group tutorials) to study their efficacy in improving the learning outcome. About 143 graduate medical students were classified into low (75%: group 3, n = 46) achievers, based on their internal assessment marks. After the regular teaching module on the topics "Vitamins and Enzymology", all the students attempted an open book assignment without peer consultation. Then all the students participated in group tutorials. The effects on the groups were evaluated by pre and posttests at the end of each phase, with the same set of MCQs. Gain from group tutorials and overall gain was significantly higher in the low achievers, compared to other groups. High and medium achievers obtained more gain from open book assignment, than group tutorials. The overall gain was significantly higher than the gain obtained from open book assignment or group tutorials, in all three groups. All the three groups retained the gain even after 1 week of the exercise. Hence, optimal use of novel T-L methods (open book assignment followed by group tutorials) as revision exercises help in strengthening concepts in Biochemistry in this oft neglected group of low achievers in graduate medical education. © 2016 by The International Union of Biochemistry and Molecular Biology, 44(4):321-325, 2016. © 2016 The International Union of Biochemistry and Molecular Biology.

  16. The Combined Influence of Air Pollution and Home Learning Environment on Early Cognitive Skills in Children

    Directory of Open Access Journals (Sweden)

    Lanair A. Lett

    2017-10-01

    Full Text Available Cognitive skills are one component of school readiness that reflect a child’s neurodevelopment and are influenced by environmental and social factors. Most studies assess the impact of these factors individually, without taking into consideration the complex interactions of multiple factors. The objective of this study was to examine the joint association of markers of environmental pollution and of social factors on early cognitive skills in an urban cohort of children. For this, we chose isophorone in ambient air as a marker of industrial air pollution. Low quality home learning environments was chosen as a marker of the social factors contributing to cognitive development. Using a subpopulation from the Early Childhood Longitudinal Study, Birth Cohort (N = 4050, isophorone exposure was assigned using the 2002 National Air Toxics Assessment. Home learning environment was assessed with a modified version of the Home Observation for Measurement of the Environment (HOME Inventory, and standardized math assessment scores were used as a measure of early cognitive skills. Multiple linear regression was used to estimate the effect of both exposures on math scores. After adjustment for confounders, children living in areas with ambient isophorone in the upper quintile of exposure (>0.49 ng/m3 had math scores that were 1.63 points lower than their less exposed peers [95% CI: −2.91, −0.34], and children with lower HOME scores (at or below 9 out of 12 had math scores that were 1.20 points lower than children with better HOME scores [95% CI: −2.30, −0.10]. In adjusted models accounting for identified confounders and both exposures of interest, both high isophorone exposure and low HOME score remained independently associated with math scores [−1.48, 95% CI: −2.79, −0.18; −1.05, 95% CI: −2.15, 0.05, respectively]. There was no statistical evidence of interaction between the two exposures, although children with both higher isophorone

  17. The Combined Influence of Air Pollution and Home Learning Environment on Early Cognitive Skills in Children.

    Science.gov (United States)

    Lett, Lanair A; Stingone, Jeanette A; Claudio, Luz

    2017-10-26

    Cognitive skills are one component of school readiness that reflect a child's neurodevelopment and are influenced by environmental and social factors. Most studies assess the impact of these factors individually, without taking into consideration the complex interactions of multiple factors. The objective of this study was to examine the joint association of markers of environmental pollution and of social factors on early cognitive skills in an urban cohort of children. For this, we chose isophorone in ambient air as a marker of industrial air pollution. Low quality home learning environments was chosen as a marker of the social factors contributing to cognitive development. Using a subpopulation from the Early Childhood Longitudinal Study, Birth Cohort (N = 4050), isophorone exposure was assigned using the 2002 National Air Toxics Assessment. Home learning environment was assessed with a modified version of the Home Observation for Measurement of the Environment (HOME) Inventory, and standardized math assessment scores were used as a measure of early cognitive skills. Multiple linear regression was used to estimate the effect of both exposures on math scores. After adjustment for confounders, children living in areas with ambient isophorone in the upper quintile of exposure (>0.49 ng/m³) had math scores that were 1.63 points lower than their less exposed peers [95% CI: -2.91, -0.34], and children with lower HOME scores (at or below 9 out of 12) had math scores that were 1.20 points lower than children with better HOME scores [95% CI: -2.30, -0.10]. In adjusted models accounting for identified confounders and both exposures of interest, both high isophorone exposure and low HOME score remained independently associated with math scores [-1.48, 95% CI: -2.79, -0.18; -1.05, 95% CI: -2.15, 0.05, respectively]. There was no statistical evidence of interaction between the two exposures, although children with both higher isophorone exposure and a low HOME score had a

  18. Effect of the fungus Piriformospora indica on physiological characteristics and root morphology of wheat under combined drought and mechanical stresses.

    Science.gov (United States)

    Hosseini, Fatemeh; Mosaddeghi, Mohammad Reza; Dexter, Anthony Roger

    2017-09-01

    This study was done to evaluate the effects of the root-colonizing endophytic fungus Piriformospora indica on wheat growth under combined drought and mechanical stresses. Inoculated (colonized) and non-inoculated (uncolonized) wheat (Triticum aestivum L. cv. Chamran) seedlings were planted in growth chambers filled with moist sand (at a matric suction of 20 hPa). Slight, moderate and severe mechanical stresses (i.e., penetration resistance, Q p , of 1.17, 4.17 and 5.96 MPa, respectively) were produced by a dead-load technique (i.e., placing a weight on the sand surface) in the root medium. Slight, moderate and severe drought stresses were induced using PEG 6000 solutions with osmotic potentials of 0, -0.3 and -0.5 MPa, respectively. After 30 days, plant physiological characteristics and root morphology were measured. An increase in Q p from 1.17 to 5.96 MPa led to greater leaf proline concentration and root diameter, and lower relative water content (RWC), leaf water potential (LWP), chlorophyll contents and root volume. Moreover, severe drought stress decreased root and shoot fresh weights, root volume, leaf area, RWC, LWP and chlorophyll content compared to control. Catalase (CAT) and ascorbate peroxidase (APX) activities under severe drought stress were about 1.5 and 2.9 times greater than control. Interaction of the stresses showed that mechanical stress primarily controls plant water status and physiological responses. However, endophyte presence mitigated the adverse effects of individual and combined stresses on plant growth. Colonized plants were better adapted and had greater root length and volume, RWC, LWP and chlorophyll contents under stressful conditions due to higher absorption sites for water and nutrients. Compared with uncolonized plants, colonized plants showed lower CAT activity implying that wheat inoculated with P. indica was more tolerant and experienced less oxidative damage induced by drought and/or mechanical stress. Copyright

  19. Comparison between effectiveness of Mechanical and Manual Traction combined with mobilization and exercise therapy in Patients with Cervical Radiculopathy.

    Science.gov (United States)

    Bukhari, Syed Rehan Iftikhar; Shakil-Ur-Rehman, Syed; Ahmad, Shakeel; Naeem, Aamer

    2016-01-01

    Cervical radiculopathy is a common neuro-musculo-skeletal disorder causing pain and disability. Traction is part of the evidence based manual physical therapy management due to its mechanical nature, type of traction and parameters related to its applicability and are still to be explored more through research. Our objective was to determine the Effects of Mechanical versus Manual Traction in Manual Physical Therapy combined with segmental mobilization and exercise therapy in the physical therapy management of Patients with Cervical Radiculopathy. This randomized control trial was conducted at department of physical therapy and rehabilitation, Rathore Hospital Faisalabad, from February to July 2015. Inclusion criteria were both male and female patients with evident symptoms of cervical spine radiculopathy and age ranged between 20-70 years. The exclusion criteria were Patients with history of trauma, neck pain without radiculopathy, aged less than 20 and more than 70. A total of 72 patients with cervical radiculopathy were screened out as per the inclusion criteria, 42 patients were randomly selected and placed into two groups by toss and trial method, and only 36 patients completed the study, while 6 dropped out. The mechanical traction was applied in group A and manual traction in group B along with common intervention of segmental mobilization and exercise therapy in both groups for 6 weeks. The patient's outcomes were assessed by self reported NPRS and NDI at the baseline and after completion of 06 weeks exercise program at 3 days per week. The data was analyzed through SPSS version-21, and paired T test was applied at 95% level significance to determine the statistical deference between two groups. Clinically the group of patients treated with mechanical traction managed pain (mean pre 6.26, mean post 1.43), and disability (mean pre 24.43 and mean post 7.26) more effectively as compared with the group of patients treated with manual traction (Pain mean pre 6

  20. Combining machine learning and ontological data handling for multi-source classification of nature conservation areas

    Science.gov (United States)

    Moran, Niklas; Nieland, Simon; Tintrup gen. Suntrup, Gregor; Kleinschmit, Birgit

    2017-02-01

    Manual field surveys for nature conservation management are expensive and time-consuming and could be supplemented and streamlined by using Remote Sensing (RS). RS is critical to meet requirements of existing laws such as the EU Habitats Directive (HabDir) and more importantly to meet future challenges. The full potential of RS has yet to be harnessed as different nomenclatures and procedures hinder interoperability, comparison and provenance. Therefore, automated tools are needed to use RS data to produce comparable, empirical data outputs that lend themselves to data discovery and provenance. These issues are addressed by a novel, semi-automatic ontology-based classification method that uses machine learning algorithms and Web Ontology Language (OWL) ontologies that yields traceable, interoperable and observation-based classification outputs. The method was tested on European Union Nature Information System (EUNIS) grasslands in Rheinland-Palatinate, Germany. The developed methodology is a first step in developing observation-based ontologies in the field of nature conservation. The tests show promising results for the determination of the grassland indicators wetness and alkalinity with an overall accuracy of 85% for alkalinity and 76% for wetness.