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Sample records for learning mechanisms component

Repurposing learning object components

NARCIS (Netherlands)

Verbert, K.; Jovanovic, J.; Gasevic, D.; Duval, E.; Meersman, R.

2005-01-01

This paper presents an ontology-based framework for repurposing learning object components. Unlike the usual practice where learning object components are assembled manually, the proposed framework enables on-the-fly access and repurposing of learning object components. The framework supports two
Design Optimization of Mechanical Components Using an Enhanced Teaching-Learning Based Optimization Algorithm with Differential Operator

Directory of Open Access Journals (Sweden)

B. Thamaraikannan

2014-01-01

Full Text Available This paper studies in detail the background and implementation of a teaching-learning based optimization (TLBO algorithm with differential operator for optimization task of a few mechanical components, which are essential for most of the mechanical engineering applications. Like most of the other heuristic techniques, TLBO is also a population-based method and uses a population of solutions to proceed to the global solution. A differential operator is incorporated into the TLBO for effective search of better solutions. To validate the effectiveness of the proposed method, three typical optimization problems are considered in this research: firstly, to optimize the weight in a belt-pulley drive, secondly, to optimize the volume in a closed coil helical spring, and finally to optimize the weight in a hollow shaft. have been demonstrated. Simulation result on the optimization (mechanical components problems reveals the ability of the proposed methodology to find better optimal solutions compared to other optimization algorithms.
Metacognitive components in smart learning environment

Science.gov (United States)

Sumadyo, M.; Santoso, H. B.; Sensuse, D. I.

2018-03-01

Metacognitive ability in digital-based learning process helps students in achieving learning goals. So that digital-based learning environment should make the metacognitive component as a facility that must be equipped. Smart Learning Environment is the concept of a learning environment that certainly has more advanced components than just a digital learning environment. This study examines the metacognitive component of the smart learning environment to support the learning process. A review of the metacognitive literature was conducted to examine the components involved in metacognitive learning strategies. Review is also conducted on the results of study smart learning environment, ranging from design to context in building smart learning. Metacognitive learning strategies certainly require the support of adaptable, responsive and personalize learning environments in accordance with the principles of smart learning. The current study proposed the role of metacognitive component in smart learning environment, which is useful as the basis of research in building environment in smart learning.
Components in models of learning: Different operationalisations and relations between components

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Mirkov Snežana

2013-01-01

Full Text Available This paper provides the presentation of different operationalisations of components in different models of learning. Special emphasis is on the empirical verifications of relations between components. Starting from the research of congruence between learning motives and strategies, underlying the general model of school learning that comprises different approaches to learning, we have analyzed the empirical verifications of factor structure of instruments containing the scales of motives and learning strategies corresponding to these motives. Considering the problems in the conceptualization of the achievement approach to learning, we have discussed the ways of operational sing the goal orientations and exploring their role in using learning strategies, especially within the model of the regulation of constructive learning processes. This model has served as the basis for researching learning styles that are the combination of a large number of components. Complex relations between the components point to the need for further investigation of the constructs involved in various models. We have discussed the findings and implications of the studies of relations between the components involved in different models, especially between learning motives/goals and learning strategies. We have analyzed the role of regulation in the learning process, whose elaboration, as indicated by empirical findings, can contribute to a more precise operationalisation of certain learning components. [Projekat Ministarstva nauke Republike Srbije, br. 47008: Unapređivanje kvaliteta i dostupnosti obrazovanja u procesima modernizacije Srbije i br. 179034: Od podsticanja inicijative, saradnje i stvaralaštva u obrazovanju do novih uloga i identiteta u društvu
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
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.
Component-Based Approach in Learning Management System Development

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Zaitseva, Larisa; Bule, Jekaterina; Makarov, Sergey

2013-01-01

The paper describes component-based approach (CBA) for learning management system development. Learning object as components of e-learning courses and their metadata is considered. The architecture of learning management system based on CBA being developed in Riga Technical University, namely its architecture, elements and possibilities are…
Statistical-Mechanical Analysis of Pre-training and Fine Tuning in Deep Learning

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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.
Assessment of learning components of management training course ...

African Journals Online (AJOL)

Assessment of learning components of any training course provides a benchmark through which training institutions or organizers could assess the effectiveness of the training. The study assessed learning components of agricultural research management training course organized for senior research managers in Nigeria.
Mechanical design of machine components

CERN Document Server

Ugural, Ansel C

2015-01-01

Mechanical Design of Machine Components, Second Edition strikes a balance between theory and application, and prepares students for more advanced study or professional practice. It outlines the basic concepts in the design and analysis of machine elements using traditional methods, based on the principles of mechanics of materials. The text combines the theory needed to gain insight into mechanics with numerical methods in design. It presents real-world engineering applications, and reveals the link between basic mechanics and the specific design of machine components and machines. Divided into three parts, this revised text presents basic background topics, deals with failure prevention in a variety of machine elements and covers applications in design of machine components as well as entire machines. Optional sections treating special and advanced topics are also included.Key Features of the Second Edition:Incorporates material that has been completely updated with new chapters, problems, practical examples...
Drosophila Learn Opposing Components of a Compound Food Stimulus

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Das, Gaurav; Klappenbach, Martín; Vrontou, Eleftheria; Perisse, Emmanuel; Clark, Christopher M.; Burke, Christopher J.; Waddell, Scott

2014-01-01

Summary Dopaminergic neurons provide value signals in mammals and insects [1–3]. During Drosophila olfactory learning, distinct subsets of dopaminergic neurons appear to assign either positive or negative value to odor representations in mushroom body neurons [4–9]. However, it is not known how flies evaluate substances that have mixed valence. Here we show that flies form short-lived aversive olfactory memories when trained with odors and sugars that are contaminated with the common insect repellent DEET. This DEET-aversive learning required the MB-MP1 dopaminergic neurons that are also required for shock learning [7]. Moreover, differential conditioning with DEET versus shock suggests that formation of these distinct aversive olfactory memories relies on a common negatively reinforcing dopaminergic mechanism. Surprisingly, as time passed after training, the behavior of DEET-sugar-trained flies reversed from conditioned odor avoidance into odor approach. In addition, flies that were compromised for reward learning exhibited a more robust and longer-lived aversive-DEET memory. These data demonstrate that flies independently process the DEET and sugar components to form parallel aversive and appetitive olfactory memories, with distinct kinetics, that compete to guide learned behavior. PMID:25042590
Circuit mechanisms of sensorimotor learning

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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
Use and limitations of learning curves for energy technology policy: A component-learning hypothesis

International Nuclear Information System (INIS)

Ferioli, F.; Schoots, K.; Zwaan, B.C.C. van der

2009-01-01

In this paper, we investigate the use of learning curves for the description of observed cost reductions for a variety of energy technologies. Starting point of our analysis is the representation of energy processes and technologies as the sum of different components. While we recognize that in many cases 'learning-by-doing' may improve the overall costs or efficiency of a technology, we argue that so far insufficient attention has been devoted to study the effects of single component improvements that together may explain an aggregated form of learning. Indeed, for an entire technology the phenomenon of learning-by-doing may well result from learning of one or a few individual components only. We analyze under what conditions it is possible to combine learning curves for single components to derive one comprehensive learning curve for the total product. The possibility that for certain technologies some components (e.g., the primary natural resources that serve as essential input) do not exhibit cost improvements might account for the apparent time dependence of learning rates reported in several studies (the learning rate might also change considerably over time depending on the data set considered, a crucial issue to be aware of when one uses the learning curve methodology). Such an explanation may have important consequences for the extent to which learning curves can be extrapolated into the future. This argumentation suggests that cost reductions may not continue indefinitely and that well-behaved learning curves do not necessarily exist for every product or technology. In addition, even for diffusing and maturing technologies that display clear learning effects, market and resource constraints can eventually significantly reduce the scope for further improvements in their fabrication or use. It appears likely that some technologies, such as wind turbines and photovoltaic cells, are significantly more amenable than others to industry-wide learning. For such
Shaking table testing of mechanical components

International Nuclear Information System (INIS)

Jurukovski, D.; Taskov, Lj.; Mamucevski, D.; Petrovski, D.

1995-01-01

Presented is the experience of the Institute of Earthquake Engineering and Engineering Seismology, Skopje, Republic of Macedonia in seismic qualification of mechanical components by shaking table testing. Technical data and characteristics for the three shaking tables available at the Institute are given. Also, for characteristic mechanical components tested at the Institute laboratories, basic data such as producer, testing investor, description of the component, testing regulation, testing equipment and final user of the results. (author)
Emotional Component in Teaching and Learning

Science.gov (United States)

Ponnambalam, Michael

2018-02-01

The laws of physics are often seen as objective truth, pure and simple. Hence, they tend to appear cerebral and cold. However, their presentation is necessarily subjective and may vary from being boring to being exciting. A detailed analysis of physics education reform efforts over the last three decades finds that interactive instruction results in greater learning gains than the traditional lecture format. In interactive engagement, the emotional component plays a far greater role than acknowledged by many. As an experienced physics teacher [(i) Four decades of teaching and research in four continents (teaching all courses to undergraduate physics majors and algebra-based physics to high school seniors as well as college freshmen), (ii) 11 years of volunteer work in Physics Popularization in six countries to many thousands of students in elementary, middle, and high schools as well as colleges and universities, and (iii) eight years as a Master Teacher and mentor], I feel that the emotional component in teaching and learning physics has been neglected. This paper presents the role of the emotional component in transforming ordinary teaching and learning of physics into an enjoyable and exciting experience for students as well as teachers.
Generating Multimedia Components for M-Learning

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Adriana REVEIU

2009-01-01

Full Text Available The paper proposes a solution to generate template based multimedia components for instruction and learning available both for computer based applications and for mobile devices. The field of research is situated at the intersection of computer science, mobile tools and e-learning and is generically named mobile learning or M-learning. The research goal is to provide access to computer based training resources from any location and to adapt the training content to the specific features of mobile devices, communication environment, users' preferences and users' knowledge. To become important tools in education field, the technical solutions proposed will follow to use the potential of mobile devices.
Learning Local Components to Understand Large Bayesian Networks

DEFF Research Database (Denmark)

Zeng, Yifeng; Xiang, Yanping; Cordero, Jorge

2009-01-01

(domain experts) to extract accurate information from a large Bayesian network due to dimensional difficulty. We define a formulation of local components and propose a clustering algorithm to learn such local components given complete data. The algorithm groups together most inter-relevant attributes......Bayesian networks are known for providing an intuitive and compact representation of probabilistic information and allowing the creation of models over a large and complex domain. Bayesian learning and reasoning are nontrivial for a large Bayesian network. In parallel, it is a tough job for users...... in a domain. We evaluate its performance on three benchmark Bayesian networks and provide results in support. We further show that the learned components may represent local knowledge more precisely in comparison to the full Bayesian networks when working with a small amount of data....
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.
TA Mentorship in Lecture significantly enhances students' learning in mechanics in large introductory physics classes

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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.
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.

Word learning mechanisms.

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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.
Fatigue characterization of mechanical components in service

Directory of Open Access Journals (Sweden)

G. Fargione

2013-10-01

Full Text Available The quickly identify of fatigue limit of a mechanical component with good approximation is currently a significant practical problem not yet resolved in a satisfactory way. Generally, for a mechanical component, the fatigue strength reduction factor (i is difficult to evaluate especially when it is in service.In this paper, the procedures for crack paths individuation and consequently damage evaluation (adopted in laboratory for stressed specimens with planned load histories are applied to mechanical components, already failed during service. The energy parameters, proposed by the authors for the evaluation of the fatigue behavior of the materials [1-5], are defined on specimens derived from a flange bolts. The flange connecting pipes at high temperature and pressure. Due to the loss of the seal, the bolts have been subjected to a hot flow steam addition to the normal stress.The numerical analysis coupled experimental analysis (measurement of surface temperature during static and dynamic tests of specimens taken from damaged tie rods, has helped to determine the causes of failure of the tie rods.The determination of an energy parameter for the evaluation of the damage showed that factors related to the heat release of the material (loaded may also help to understand the causes of failure of mechanical components.
Reliability-based sensitivity of mechanical components with arbitrary distribution parameters

International Nuclear Information System (INIS)

Zhang, Yi Min; Yang, Zhou; Wen, Bang Chun; He, Xiang Dong; Liu, Qiaoling

2010-01-01

This paper presents a reliability-based sensitivity method for mechanical components with arbitrary distribution parameters. Techniques from the perturbation method, the Edgeworth series, the reliability-based design theory, and the sensitivity analysis approach were employed directly to calculate the reliability-based sensitivity of mechanical components on the condition that the first four moments of the original random variables are known. The reliability-based sensitivity information of the mechanical components can be accurately and quickly obtained using a practical computer program. The effects of the design parameters on the reliability of mechanical components were studied. The method presented in this paper provides the theoretic basis for the reliability-based design of mechanical components
Structural mechanics of nuclear plant components

International Nuclear Information System (INIS)

Roche, R.

1986-10-01

Sound structural analysis are needed for designing safe and reliable components, hence his play is very important in nuclear industry. This report is a provisional writing on the good practice in structural mechanics. Emphasis is put on non elastic analysis, damage appraisal, fatigue, fracture mechanics and also on elevated temperature behaviour [fr
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)
Component Pin Recognition Using Algorithms Based on Machine Learning

Science.gov (United States)

Xiao, Yang; Hu, Hong; Liu, Ze; Xu, Jiangchang

2018-04-01

The purpose of machine vision for a plug-in machine is to improve the machine’s stability and accuracy, and recognition of the component pin is an important part of the vision. This paper focuses on component pin recognition using three different techniques. The first technique involves traditional image processing using the core algorithm for binary large object (BLOB) analysis. The second technique uses the histogram of oriented gradients (HOG), to experimentally compare the effect of the support vector machine (SVM) and the adaptive boosting machine (AdaBoost) learning meta-algorithm classifiers. The third technique is the use of an in-depth learning method known as convolution neural network (CNN), which involves identifying the pin by comparing a sample to its training. The main purpose of the research presented in this paper is to increase the knowledge of learning methods used in the plug-in machine industry in order to achieve better results.
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…
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.
Advances in independent component analysis and learning machines

CERN Document Server

Bingham, Ella; Laaksonen, Jorma; Lampinen, Jouko

2015-01-01

In honour of Professor Erkki Oja, one of the pioneers of Independent Component Analysis (ICA), this book reviews key advances in the theory and application of ICA, as well as its influence on signal processing, pattern recognition, machine learning, and data mining. Examples of topics which have developed from the advances of ICA, which are covered in the book are: A unifying probabilistic model for PCA and ICA Optimization methods for matrix decompositions Insights into the FastICA algorithmUnsupervised deep learning Machine vision and image retrieval A review of developments in the t
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.
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.
Identification of learning mechanisms in a wild meerkat population.

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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.
Shaking table qualification tests of mechanical and electrical components

International Nuclear Information System (INIS)

Jurukovski, D.

1993-01-01

This presentation covers the experience of the Institute of Earthquake Engineering and Engineering Seismology, Skopje, Republic of Macedonia in seismic qualification of mechanical components by shaking table testing. The characteristics of the biaxial seismic and single component shaking tables used at the Institute are given. Some examples of the experience from performed test for reactor components are included
Contactless Mechanical Components: Gears, Torque Limiters and Bearings

Directory of Open Access Journals (Sweden)

Jose Luis Perez-Diaz

2014-12-01

Full Text Available Contactless mechanical components are mechanical sets for conversion of torque/speed, whose gears and moving parts do not touch each other, but rather they provide movement with magnets and magnetic materials that exert force from a certain distance. Magneto-mechanical transmission devices have several advantages over conventional mechanisms: no friction between rotatory elements (no power losses or heat generation by friction so increase of efficiency, no lubrication is needed (oil-free mechanisms and no lubrication auxiliary systems, reduced maintenance (no lubricant so no need of oil replacements, wider operational temperature ranges (no lubricant evaporation or freezing, overload protection (if overload occurs magnet simply slides but no teeth brake, through-wall connection (decoupling of thermal and electrical paths and environmental isolation, larger operative speeds (more efficient operative conditions, ultralow noise and vibrations (no contact no noise generation. All these advantages permit us to foresee in the long term several common industrial applications in which including contactless technology would mean a significant breakthrough for their performance. In this work, we present three configurations of contactless mechanical passive components: magnetic gears, magnetic torque limiters and superconducting magnetic bearings. We summarize the main characteristic and range of applications for each type; we show experimental results of the most recent developments showing their performance.
Mechanical components design for PWR - control rod drive mechanism

International Nuclear Information System (INIS)

Leme, Francisco Louzano; Mattar Neto, Miguel

2002-01-01

The Control Rod Drive Mechanism (CRDM) is usually - a high precision - equipment incorporating mechanical and electrical components designed to move the control rods. The 'control rods' refer to all rods or assemblies that are moved to assess the performance of the reactor. The CRDM here presented is the Nut and Lead Screw type. This type is basically a power screw type magnetically coupled to a slow speed reluctance electric motor that provides a means of axially positioning the movable fuel assemblies in the reactor core for purpose of controlling core reactivity. A helically threaded lead screw assembly, comprising one element of power screw, is attached to a movable fuel assemblies. The CRDM usually has closer and more consistent contact with environment peculiar to the reactor than has only other machinery component. This environment includes not only the radiation field of the reactor, but also the temperature, pressure and chemical properties associated with the material used as the coolant for reactor fuel. Specific and special materials are needed because of the above mentioned application. Due to the importance of the above described CRDM functions, this paper will also consider the nuclear functions and their safety classes as well as the CRDM nuclear design criteria. (author)
Mechanisms of component diffusion in mercury cadmium telluride

International Nuclear Information System (INIS)

Tang, M.S.; Stevenson, D.A.

1989-01-01

The component diffusion coefficients for the Hg/sub 0.8/Cd/sub 0.2/Te (MCT) system are measured using radioactive tracers. Multiple branches are observed in the tracer diffusion profiles which are related to fast and slow-diffusing components. Diffusion models for each component are proposed based on the defect chemistry of MCT, a calculation of the thermodynamic factor, and the relationship between component diffusion coefficients and the interdiffusion coefficients for pseudobinary systems. The model provides insight into the thermodynamic properties of the system, the mechanisms for diffusion, and the practical application of tracer diffusion data to interdiffusion and p-to-n conversion by Hg annealing
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
Cognitive components underpinning the development of model-based learning.

Science.gov (United States)

Potter, Tracey C S; Bryce, Nessa V; Hartley, Catherine A

2017-06-01

Reinforcement learning theory distinguishes "model-free" learning, which fosters reflexive repetition of previously rewarded actions, from "model-based" learning, which recruits a mental model of the environment to flexibly select goal-directed actions. Whereas model-free learning is evident across development, recruitment of model-based learning appears to increase with age. However, the cognitive processes underlying the development of model-based learning remain poorly characterized. Here, we examined whether age-related differences in cognitive processes underlying the construction and flexible recruitment of mental models predict developmental increases in model-based choice. In a cohort of participants aged 9-25, we examined whether the abilities to infer sequential regularities in the environment ("statistical learning"), maintain information in an active state ("working memory") and integrate distant concepts to solve problems ("fluid reasoning") predicted age-related improvements in model-based choice. We found that age-related improvements in statistical learning performance did not mediate the relationship between age and model-based choice. Ceiling performance on our working memory assay prevented examination of its contribution to model-based learning. However, age-related improvements in fluid reasoning statistically mediated the developmental increase in the recruitment of a model-based strategy. These findings suggest that gradual development of fluid reasoning may be a critical component process underlying the emergence of model-based learning. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.
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.
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

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.
Autonomous learning in gesture recognition by using lobe component analysis

Science.gov (United States)

Lu, Jian; Weng, Juyang

2007-02-01

Gesture recognition is a new human-machine interface method implemented by pattern recognition(PR).In order to assure robot safety when gesture is used in robot control, it is required to implement the interface reliably and accurately. Similar with other PR applications, 1) feature selection (or model establishment) and 2) training from samples, affect the performance of gesture recognition largely. For 1), a simple model with 6 feature points at shoulders, elbows, and hands, is established. The gestures to be recognized are restricted to still arm gestures, and the movement of arms is not considered. These restrictions are to reduce the misrecognition, but are not so unreasonable. For 2), a new biological network method, called lobe component analysis(LCA), is used in unsupervised learning. Lobe components, corresponding to high-concentrations in probability of the neuronal input, are orientation selective cells follow Hebbian rule and lateral inhibition. Due to the advantage of LCA method for balanced learning between global and local features, large amount of samples can be used in learning efficiently.
Lessons Learned: Mechanical Component and Tribology Activities in Support of Return to Flight

Science.gov (United States)

Handschuh, Robert F.; Zaretsky, Erwin V.

2017-01-01

The February 2003 loss of the Space Shuttle Columbia resulted in NASA Management revisiting every critical system onboard this very complex, reusable space vehicle in a an effort to Return to Flight. Many months after the disaster, contact between NASA Johnson Space Center and NASA Glenn Research Center evolved into an in-depth assessment of the actuator drive systems for the Rudder Speed Brake and Body Flap Systems. The actuators are CRIT 1-1 systems that classifies them as failure of any of the actuators could result in loss of crew and vehicle. Upon further evaluation of these actuator systems and the resulting issues uncovered, several research activities were initiated, conducted, and reported to the NASA Space Shuttle Program Management. The papers contained in this document are the contributions of many researchers from NASA Glenn Research Center and Marshall Space Flight Center as part of a Lessons Learned on mechanical actuation systems as used in space applications. Many of the findings contained in this document were used as a basis to safely Return to Flight for the remaining Space Shuttle Fleet until their retirement.
Mechanical Components from Highly Recoverable, Low Apparent Modulus Materials

Science.gov (United States)

Padula, Santo, II (Inventor); Noebe, Ronald D. (Inventor); Stanford, Malcolm K. (Inventor); DellaCorte, Christopher (Inventor)

2015-01-01

A material for use as a mechanical component is formed of a superelastic intermetallic material having a low apparent modulus and a high hardness. The superelastic intermetallic material is conditioned to be dimensionally stable, devoid of any shape memory effect and have a stable superelastic response without irrecoverable deformation while exhibiting strains of at least 3%. The method of conditioning the superelastic intermetallic material is described. Another embodiment relates to lightweight materials known as ordered intermetallics that perform well in sliding wear applications using conventional liquid lubricants and are therefore suitable for resilient, high performance mechanical components such as gears and bearings.
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)
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.
Vocabulary Learning in Primary School Children: Working Memory and Long-Term Memory Components

Science.gov (United States)

Morra, Sergio; Camba, Roberta

2009-01-01

The goal of this study was to investigate which working memory and long-term memory components predict vocabulary learning. We used a nonword learning paradigm in which 8- to 10-year-olds learned picture-nonword pairs. The nonwords varied in length (two vs. four syllables) and phonology (native sounding vs. including one Russian phoneme). Short,…
EEG-Based Emotion Recognition Using Deep Learning Network with Principal Component Based Covariate Shift Adaptation

Directory of Open Access Journals (Sweden)

Suwicha Jirayucharoensak

2014-01-01

Full Text Available Automatic emotion recognition is one of the most challenging tasks. To detect emotion from nonstationary EEG signals, a sophisticated learning algorithm that can represent high-level abstraction is required. This study proposes the utilization of a deep learning network (DLN to discover unknown feature correlation between input signals that is crucial for the learning task. The DLN is implemented with a stacked autoencoder (SAE using hierarchical feature learning approach. Input features of the network are power spectral densities of 32-channel EEG signals from 32 subjects. To alleviate overfitting problem, principal component analysis (PCA is applied to extract the most important components of initial input features. Furthermore, covariate shift adaptation of the principal components is implemented to minimize the nonstationary effect of EEG signals. Experimental results show that the DLN is capable of classifying three different levels of valence and arousal with accuracy of 49.52% and 46.03%, respectively. Principal component based covariate shift adaptation enhances the respective classification accuracy by 5.55% and 6.53%. Moreover, DLN provides better performance compared to SVM and naive Bayes classifiers.
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.
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.
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.
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
Mechanical design assessments of structural components and auxiliaries of the Joint European Torus

International Nuclear Information System (INIS)

Sonnerup, L.

1986-01-01

The general design of the Joint European Torus (JET) is briefly described. The loads on its major structural components, at normal operation, and in cases of plasma instability and/or disruption, are discussed. The way these components have been assessed and optimised in relation to their loads is presented. A short account of mechanical design problems of auxiliary equipment is given. Finally, the state of operation of JET and its implications for the mechanical design is summarized. The mechanically most important components of the JET device are the support structure of the toroidal magnet, the vacuum vessel, the coils of the magnets and the pedestals supporting the weight of the torus. These components all participate in resisting and transmitting the primary forces during operation. (orig.)
Casting and stress-strain simulations of a cast ductile iron component using microstructure based mechanical behavior

International Nuclear Information System (INIS)

Olofsson, Jakob; Svensson, Ingvar L

2012-01-01

The industrial demand for increased component performance with concurrent reductions in component weight, development times and verifications using physical prototypes drives the need to use the full potential of casting and Finite Element Method (FEM) simulations to correctly predict the mechanical behavior of cast components in service. The mechanical behavior of the component is determined by the casting process, and factors as component geometry and casting process parameters are known to affect solidification and microstructure formation throughout the component and cause local variations in mechanical behavior as well as residual stresses. Though residual stresses are known to be an important factor in the mechanical behavior of the component, the importance of local mechanical behavior is not well established and the material is typically considered homogeneous throughout the component. This paper deals with the influence of solidification and solid state transformation on microstructure formation and the effect of local microstructure variations on the mechanical behavior of the cast component in service. The current work aims to investigate the coupling between simulation of solidification, microstructure and local variations in mechanical behavior and stress-strain simulation. This is done by performing several simulations of a ductile iron component using a recently developed simulation strategy, a closed chain of simulations for cast components, able to predict and describe the local variations in not only elastic but also plastic behavior throughout the component by using microstructural parameters determined by simulations of microstructural evolution in the component during the casting process. In addition the residual stresses are considered. The results show that the FEM simulation results are significantly affected by including microstructure based mechanical behavior. When the applied load is low and the component is subjected to stress levels
Nuclear Power Plant Mechanical Component Flooding Fragility Experiments Status

Energy Technology Data Exchange (ETDEWEB)

Pope, C. L. [Idaho State Univ., Pocatello, ID (United States); Savage, B. [Idaho State Univ., Pocatello, ID (United States); Johnson, B. [Idaho State Univ., Pocatello, ID (United States); Muchmore, C. [Idaho State Univ., Pocatello, ID (United States); Nichols, L. [Idaho State Univ., Pocatello, ID (United States); Roberts, G. [Idaho State Univ., Pocatello, ID (United States); Ryan, E. [Idaho State Univ., Pocatello, ID (United States); Suresh, S. [Idaho State Univ., Pocatello, ID (United States); Tahhan, A. [Idaho State Univ., Pocatello, ID (United States); Tuladhar, R. [Idaho State Univ., Pocatello, ID (United States); Wells, A. [Idaho State Univ., Pocatello, ID (United States); Smith, C. [Idaho National Lab. (INL), Idaho Falls, ID (United States)

2017-07-24

This report describes progress on Nuclear Power Plant mechanical component flooding fragility experiments and supporting research. The progress includes execution of full scale fragility experiments using hollow-core doors, design of improvements to the Portal Evaluation Tank, equipment procurement and initial installation of PET improvements, designation of experiments exploiting the improved PET capabilities, fragility mathematical model development, Smoothed Particle Hydrodynamic simulations, wave impact simulation device research, and pipe rupture mechanics research.
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
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.
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
Machine learning of frustrated classical spin models. I. Principal component analysis

Science.gov (United States)

Wang, Ce; Zhai, Hui

2017-10-01

This work aims at determining whether artificial intelligence can recognize a phase transition without prior human knowledge. If this were successful, it could be applied to, for instance, analyzing data from the quantum simulation of unsolved physical models. Toward this goal, we first need to apply the machine learning algorithm to well-understood models and see whether the outputs are consistent with our prior knowledge, which serves as the benchmark for this approach. In this work, we feed the computer data generated by the classical Monte Carlo simulation for the X Y model in frustrated triangular and union jack lattices, which has two order parameters and exhibits two phase transitions. We show that the outputs of the principal component analysis agree very well with our understanding of different orders in different phases, and the temperature dependences of the major components detect the nature and the locations of the phase transitions. Our work offers promise for using machine learning techniques to study sophisticated statistical models, and our results can be further improved by using principal component analysis with kernel tricks and the neural network method.
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

Mechanical design assessments of structural components and auxiliaries of the Joint European Torus

International Nuclear Information System (INIS)

Sonnerup, L.

1985-01-01

The general design of the Joint European Torus (JET) is briefly described. The loads on its major structural components, at normal operation, and in cases of plasma instability and/or disruption, are discussed. The way these components have been assessed and optimised in relation to their loads is presented. A short account of mechanical design problems of auxiliary equipment is given. Finally, the state of operation of JET and its implications for the mechanical design at the time of the conference will be summarized. The mechanically most important components of the JET device are the support structure of the toroidal magnet, th vacuum vessel, the coils of the magnets and the pedestals supporting the weight of the torus. These components all participate in resisting and transmitting the primary forces during operation. (orig.)
Vocabulary learning in primary school children: working memory and long-term memory components.

Science.gov (United States)

Morra, Sergio; Camba, Roberta

2009-10-01

The goal of this study was to investigate which working memory and long-term memory components predict vocabulary learning. We used a nonword learning paradigm in which 8- to 10-year-olds learned picture-nonword pairs. The nonwords varied in length (two vs. four syllables) and phonology (native sounding vs. including one Russian phoneme). Short, phonologically native nonwords were learned best, whereas learning long nonwords leveled off after a few presentation cycles. Linear structural equation analyses showed an influence of three constructs-phonological sensitivity, vocabulary knowledge, and central attentional resources (M capacity)-on nonword learning, but the extent of their contributions depended on specific characteristics of the nonwords to be learned. Phonological sensitivity predicted learning of all nonword types except short native nonwords, vocabulary predicted learning of only short native nonwords, and M capacity predicted learning of short nonwords but not long nonwords. The discussion considers three learning processes-effortful activation of phonological representations, lexical mediation, and passive associative learning-that use different cognitive resources and could be involved in learning different nonword types.
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
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.
Multi-center MRI carotid plaque component segmentation using feature normalization and transfer learning

DEFF Research Database (Denmark)

van Engelen, Arna; van Dijk, Anouk C; Truijman, Martine T.B.

2015-01-01

implementation of supervised methods. In this paper we segment carotid plaque components of clinical interest (fibrous tissue, lipid tissue, calcification and intraplaque hemorrhage) in a multicenter MRI study. We perform voxelwise tissue classification by traditional same-center training, and compare results...... not yield significant differences from that reference. We conclude that both extensive feature normalization and transfer learning can be valuable for the development of supervised methods that perform well on different types of datasets.......Automated segmentation of plaque components in carotid artery MRI is important to enable large studies on plaque vulnerability, and for incorporating plaque composition as an imaging biomarker in clinical practice. Especially supervised classification techniques, which learn from labeled examples...
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.
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.
Using the Internet to Study the Internet: An Active Learning Component.

Science.gov (United States)

Kohut, Dave; Sternberg, Joel

1995-01-01

Describes the Internet component of an undergraduate course at St. Xavier University (Illinois) in which a librarian helps mass communications students survey state-of-the-art technologies and predict future possibilities. Active learning techniques are discussed and examples of class exercises and the final assignment are included. (Author/LRW)
Regulatory components of carbon concentrating mechanisms in aquatic unicellular photosynthetic organisms.

Science.gov (United States)

Tomar, Vandana; Sidhu, Gurpreet Kaur; Nogia, Panchsheela; Mehrotra, Rajesh; Mehrotra, Sandhya

2017-11-01

This review provides an insight into the regulation of the carbon concentrating mechanisms (CCMs) in lower organisms like cyanobacteria, proteobacteria, and algae. CCMs evolved as a mechanism to concentrate CO 2 at the site of primary carboxylating enzyme Ribulose-1, 5-bisphosphate carboxylase oxygenase (Rubisco), so that the enzyme could overcome its affinity towards O 2 which leads to wasteful processes like photorespiration. A diverse set of CCMs exist in nature, i.e., carboxysomes in cyanobacteria and proteobacteria; pyrenoids in algae and diatoms, the C 4 system, and Crassulacean acid metabolism in higher plants. Prime regulators of CCM in most of the photosynthetic autotrophs belong to the LysR family of transcriptional regulators, which regulate the activity of the components of CCM depending upon the ambient CO 2 concentrations. Major targets of these regulators are carbonic anhydrase and inorganic carbon uptake systems (CO 2 and HCO 3 - transporters) whose activities are modulated either at transcriptional level or by changes in the levels of their co-regulatory metabolites. The article provides information on the localization of the CCM components as well as their function and participation in the development of an efficient CCM. Signal transduction cascades leading to activation/inactivation of inducible CCM components on perception of low/high CO 2 stimuli have also been brought into picture. A detailed study of the regulatory components can aid in identifying the unraveled aspects of these mechanisms and hence provide information on key molecules that need to be explored to further provide a clear understanding of the mechanism under study.
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.
Learning Algorithms for Audio and Video Processing: Independent Component Analysis and Support Vector Machine Based Approaches

National Research Council Canada - National Science Library

Qi, Yuan

2000-01-01

In this thesis, we propose two new machine learning schemes, a subband-based Independent Component Analysis scheme and a hybrid Independent Component Analysis/Support Vector Machine scheme, and apply...
Do quality improvement collaboratives' educational components match the dominant learning style preferences of the participants?

Science.gov (United States)

Weggelaar-Jansen, Anne Marie; van Wijngaarden, Jeroen; Slaghuis, Sarah-Sue

2015-06-20

Quality improvement collaboratives are used to improve healthcare by various organizations. Despite their popularity literature shows mixed results on their effectiveness. A quality improvement collaborative can be seen as a temporary learning organization in which knowledge about improvement themes and methods is exchanged. In this research we studied: Does the learning approach of a quality improvement collaborative match the learning styles preferences of the individual participants and how does that affect the learning process of participants? This research used a mixed methods design combining a validated learning style questionnaire with data collected in the tradition of action research methodology to study two Dutch quality improvement collaboratives. The questionnaire is based on the learning style model of Ruijters and Simons, distinguishing five learning style preferences: Acquisition of knowledge, Apperception from others, Discovery of new insights, Exercising in fictitious situations and Participation with others. The most preferred learning styles of the participants were Discovery and Participation. The learning style Acquisition was moderately preferred and Apperception and Exercising were least preferred. The educational components of the quality improvement collaboratives studied (national conferences, half-day learning sessions, faculty site visits and use of an online tool) were predominantly associated with the learning styles Acquisition and Apperception. We observed a decrease in attendance to the learning activities and non-conformance with the standardized set goals and approaches. We conclude that the participants' satisfaction with the offered learning approach changed over time. The lacking match between these learning style preferences and the learning approach in the educational components of the quality improvement collaboratives studied might be the reason why the participants felt they did not gain new insights and therefore ceased
Mechanical testing - designers need: a view at component design and operations stages

International Nuclear Information System (INIS)

Shrivastava, S.K.

2007-01-01

Mechanical design of any component requires knowledge of values of various material properties which designer(s) make(s) use in designing the component. In design of nuclear power plant components, it assumes even greater importance in view of degree of precision and accuracy with which the values of various properties are required. This is in turn demands, high accuracy in testing machines and measuring methods. In this paper, attempt has been made to bring out that even from conventional tension test, how designer today looks for availability of engineering stress-strain diagram preferably through digitally acquired data points during the test from which he can derive values of Ramberg-Osgood parameters for use in fracture mechanics based analysis. Attempt has been also made to provide account of some of important fracture mechanics related tests which have been evolved in last two decades and designers need for evolution of simple test techniques to measure many more fracture mechanics related parameters as well as cater to constraints such as shape and size of material available from the components. Nuclear power plant has been primarily kept in view and ASME. Section III NB, ASME Section XI and relevant ASTM Standards have been taken as standard references. Further pressure retaining materials of pressure vessels/Reactor Pressure Vessels have been kept in view. (author)
Academic workload management towards learning, components of academic work

OpenAIRE

Ocvirk, Aleksandra; Trunk Širca, Nada

2013-01-01

This paper deals with attributing time value to academic workload from the point of view of an HEI, management of teaching and an individual. We have conducted a qualitative study aimed at analysing documents on academic workload in terms of its definition, and at analysing the attribution of time value to components of academic work in relation to the proportion of workload devoted to teaching in the sense of ensuring quality and effectiveness of learning, and in relation to financial implic...
A Sociotechnical Negotiation Mechanism to Support Component Markets in Software Ecosystems

Directory of Open Access Journals (Sweden)

Rodrigo Santos

2017-12-01

Full Text Available Organizations have opened up their software platforms and reusable assets to others, including partners and third-party developers around the world, creating software ecosystems (SECOs. This perspective can contribute to minimize nontechnical barriers of software reuse in industry because it explores potential benefits from the relations among companies and stakeholders. An inhibitor is the complexity in defining value for reusable assets in a scenario where producers try to meet customers’ expectations, and vice-versa. In this paper, we present a value-based mechanism to support component negotiation and socialization processes in a reuse repository in the SECO context as an extension of the Brechó-EcoSys environment. Social resources were integrated into the mechanism in order to aid component negotiation. An evaluation of the negotiation mechanism was initially performed based on an analysis of its elements and functions against critical factors in the negotiation within a SECO, identified in a previous systematic literature review. In addition, an analysis of the social resources supporting the negotiation mechanism was performed against popular sociotechnical elements for SECOs, identified in a previous survey with experts in the field. Finally, the negotiation process and the potential support provided by sociotechnical resources were investigated through an observational study where participants were engaged in some tasks playing as consumer and producers using the sociotechnical negotiation mechanism at Brechó-EcoSys environment. We concluded that sociotechnical resources (e.g., forum and tag cloud support component producers and consumers with useful information from the SECO community.
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…
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.
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...
Development of a skeletal multi-component fuel reaction mechanism based on decoupling methodology

International Nuclear Information System (INIS)

Mohan, Balaji; Tay, Kun Lin; Yang, Wenming; Chua, Kian Jon

2015-01-01

Highlights: • A compact multi-component skeletal reaction mechanism was developed. • Combined bio-diesel and PRF mechanism was proposed. • The mechanism consists of 68 species and 183 reactions. • Well validated against ignition delay times, flame speed and engine results. - Abstract: A new coupled bio-diesel surrogate and primary reference fuel (PRF) oxidation skeletal mechanism has been developed. The bio-diesel surrogate sub-mechanism consists of oxidation sub-mechanisms of Methyl decanoate (MD), Methyl 9-decenoate (MD9D) and n-Heptane fuel components. The MD and MD9D are chosen to represent the saturated and unsaturated methyl esters respectively in bio-diesel fuels. Then, a reduced iso-Octane oxidation sub-mechanism is added to the bio-diesel surrogate sub-mechanism. Then, all the sub-mechanisms are integrated to a reduced C_2–C_3 mechanism, detailed H_2/CO/C_1 mechanism and reduced NO_x mechanism based on decoupling methodology. The final mechanism consisted of 68 species and 183 reactions. The mechanism was well validated with shock-tube ignition delay times, laminar flame speed and 3D engine simulations.
Mechanical testing of PHWR components at different fabrication stages

International Nuclear Information System (INIS)

Saibaba, N.

2007-01-01

Zirconium alloys are extensively used for reactor structural and cladding components for PHWRs and BWRs due to their low neutron absorption cross-section, corrosion resistance to high temperature aqueous environments, adequate mechanical properties and resistance to radiation damage. The coolant tube fabrication route consists of a series of intermediate process steps. The working parameters of each process have a definite bearing on the final properties of these tubes. In order to ascertain the effect of these parameters, mechanical testing is carried out at intermediate stage of coolant tube fabrication. The mechanical properties of the products can be correlated with process parameters and reflect the quality of the product to a great extent. These properties at intermediate stages can serve as process controlling parameters. This paper discusses the correlation of mechanical properties of pressure tubes between the intermediate stage and final stage. The effect of process parameters like annealing temperature, honing, sand blasting pressure and eccentricity on the final mechanical properties was highlighted. (author)

The radish gene reveals a memory component with variable temporal properties.

Directory of Open Access Journals (Sweden)

Holly LaFerriere

Full Text Available Memory phases, dependent on different neural and molecular mechanisms, strongly influence memory performance. Our understanding, however, of how memory phases interact is far from complete. In Drosophila, aversive olfactory learning is thought to progress from short-term through long-term memory phases. Another memory phase termed anesthesia resistant memory, dependent on the radish gene, influences memory hours after aversive olfactory learning. How does the radish-dependent phase influence memory performance in different tasks? It is found that the radish memory component does not scale with the stability of several memory traces, indicating a specific recruitment of this component to influence different memories, even within minutes of learning.
Motivational component profiles in university students learning histology: a comparative study between genders and different health science curricula.

Science.gov (United States)

Campos-Sánchez, Antonio; López-Núñez, Juan Antonio; Carriel, Víctor; Martín-Piedra, Miguel-Ángel; Sola, Tomás; Alaminos, Miguel

2014-03-10

The students' motivation to learn basic sciences in health science curricula is poorly understood. The purpose of this study was to investigate the influence of different components of motivation (intrinsic motivation, self-determination, self-efficacy and extrinsic -career and grade- motivation) on learning human histology in health science curricula and their relationship with the final performance of the students in histology. Glynn Science Motivation Questionnaire II was used to compare students' motivation components to learn histology in 367 first-year male and female undergraduate students enrolled in medical, dentistry and pharmacy degree programs. For intrinsic motivation, career motivation and self-efficacy, the highest values corresponded to medical students, whereas dentistry students showed the highest values for self-determination and grade motivation. Genders differences were found for career motivation in medicine, self-efficacy in dentistry, and intrinsic motivation, self-determination and grade motivation in pharmacy. Career motivation and self-efficacy components correlated with final performance in histology of the students corresponding to the three curricula. Our results show that the overall motivational profile for learning histology differs among medical, dentistry and pharmacy students. This finding is potentially useful to foster their learning process, because if they are metacognitively aware of their motivation they will be better equipped to self-regulate their science-learning behavior in histology. This information could be useful for instructors and education policy makers to enhance curricula not only on the cognitive component of learning but also to integrate students' levels and types of motivation into the processes of planning, delivery and evaluation of medical education.
Beliefs on Learning and Teaching Language Components: The Case of Iranian EAP and EFL Learners

Science.gov (United States)

Parsi, Gholamreza

2017-01-01

The present study intended to investigate the possible difference between EAP and EFL learners' beliefs concerning learning and teaching of language components, namely, vocabulary, pronunciation and grammar. Furthermore, this study examined the association between EAP and EFL learners' beliefs and their language components' development. To this…
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.
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.
Structure and Mechanism of the S Component of a Bacterial ECF Transporter

Energy Technology Data Exchange (ETDEWEB)

P Zhang; J Wang; Y Shi

2011-12-31

The energy-coupling factor (ECF) transporters, responsible for vitamin uptake in prokaryotes, are a unique family of membrane transporters. Each ECF transporter contains a membrane-embedded, substrate-binding protein (known as the S component), an energy-coupling module that comprises two ATP-binding proteins (known as the A and A' components) and a transmembrane protein (known as the T component). The structure and transport mechanism of the ECF family remain unknown. Here we report the crystal structure of RibU, the S component of the ECF-type riboflavin transporter from Staphylococcus aureus at 3.6-{angstrom} resolution. RibU contains six transmembrane segments, adopts a previously unreported transporter fold and contains a riboflavin molecule bound to the L1 loop and the periplasmic portion of transmembrane segments 4-6. Structural analysis reveals the essential ligand-binding residues, identifies the putative transport path and, with sequence alignment, uncovers conserved structural features and suggests potential mechanisms of action among the ECF transporters.
Document-Oriented E-Learning Components

Science.gov (United States)

Piotrowski, Michael

2009-01-01

This dissertation questions the common assumption that e-learning requires a "learning management system" (LMS) such as Moodle or Blackboard. Based on an analysis of the current state of the art in LMSs, we come to the conclusion that the functionality of conventional e-learning platforms consists of basic content management and…
Design and fabrication of a eccentric wheels based motorised alignment mechanism for cylindrical accelerator components

International Nuclear Information System (INIS)

Mundra, G.; Jain, V.; Karmarkar, Mangesh; Kotaiah, S.

2006-01-01

Precision alignment mechanisms with long term stability are required for accelerator components. For some of the components motorised and remotely operable alignment mechanism are required. An eccentric wheel mechanism based alignment system is very much suitable for such application. One such alignment system is designed, a prototype is machined/fabricated for SFDTL type accelerating structure and preliminary trial experiments have been done. (author)
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.
E-Learning as an Important Component in “Blended Learning” in School Development Projects in Norway

OpenAIRE

Aasen, Ann Margareth

2013-01-01

E-learning is an important component in ཿblended learning࿝ in all of SePU`s projects and is used for additional education and development of competences. Blended learning is defined as learning facilitated by the effective combination of different modes of delivery, models of teaching, styles of learning, and based on transparent communication among all parties involved in development competences. In general, one of the challenges with improving the workplace is linked to employee training an...
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.
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.
Motivational component profiles in university students learning histology: a comparative study between genders and different health science curricula

Science.gov (United States)

2014-01-01

Background The students’ motivation to learn basic sciences in health science curricula is poorly understood. The purpose of this study was to investigate the influence of different components of motivation (intrinsic motivation, self-determination, self-efficacy and extrinsic -career and grade- motivation) on learning human histology in health science curricula and their relationship with the final performance of the students in histology. Methods Glynn Science Motivation Questionnaire II was used to compare students’ motivation components to learn histology in 367 first-year male and female undergraduate students enrolled in medical, dentistry and pharmacy degree programs. Results For intrinsic motivation, career motivation and self-efficacy, the highest values corresponded to medical students, whereas dentistry students showed the highest values for self-determination and grade motivation. Genders differences were found for career motivation in medicine, self-efficacy in dentistry, and intrinsic motivation, self-determination and grade motivation in pharmacy. Career motivation and self-efficacy components correlated with final performance in histology of the students corresponding to the three curricula. Conclusions Our results show that the overall motivational profile for learning histology differs among medical, dentistry and pharmacy students. This finding is potentially useful to foster their learning process, because if they are metacognitively aware of their motivation they will be better equipped to self-regulate their science-learning behavior in histology. This information could be useful for instructors and education policy makers to enhance curricula not only on the cognitive component of learning but also to integrate students’ levels and types of motivation into the processes of planning, delivery and evaluation of medical education. PMID:24612878
Variational Bayesian Learning for Wavelet Independent Component Analysis

Science.gov (United States)

Roussos, E.; Roberts, S.; Daubechies, I.

2005-11-01

In an exploratory approach to data analysis, it is often useful to consider the observations as generated from a set of latent generators or "sources" via a generally unknown mapping. For the noisy overcomplete case, where we have more sources than observations, the problem becomes extremely ill-posed. Solutions to such inverse problems can, in many cases, be achieved by incorporating prior knowledge about the problem, captured in the form of constraints. This setting is a natural candidate for the application of the Bayesian methodology, allowing us to incorporate "soft" constraints in a natural manner. The work described in this paper is mainly driven by problems in functional magnetic resonance imaging of the brain, for the neuro-scientific goal of extracting relevant "maps" from the data. This can be stated as a `blind' source separation problem. Recent experiments in the field of neuroscience show that these maps are sparse, in some appropriate sense. The separation problem can be solved by independent component analysis (ICA), viewed as a technique for seeking sparse components, assuming appropriate distributions for the sources. We derive a hybrid wavelet-ICA model, transforming the signals into a domain where the modeling assumption of sparsity of the coefficients with respect to a dictionary is natural. We follow a graphical modeling formalism, viewing ICA as a probabilistic generative model. We use hierarchical source and mixing models and apply Bayesian inference to the problem. This allows us to perform model selection in order to infer the complexity of the representation, as well as automatic denoising. Since exact inference and learning in such a model is intractable, we follow a variational Bayesian mean-field approach in the conjugate-exponential family of distributions, for efficient unsupervised learning in multi-dimensional settings. The performance of the proposed algorithm is demonstrated on some representative experiments.
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.
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
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
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.
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…
Possible mechanisms underlying slow component of V̇O2 on-kinetics in skeletal muscle.

Science.gov (United States)

Korzeniewski, Bernard; Zoladz, Jerzy A

2015-05-15

A computer model of a skeletal muscle bioenergetic system is used to study the background of the slow component of oxygen consumption V̇O2 on-kinetics in skeletal muscle. Two possible mechanisms are analyzed: inhibition of ATP production by anaerobic glycolysis by progressive cytosol acidification (together with a slow decrease in ATP supply by creatine kinase) and gradual increase of ATP usage during exercise of constant power output. It is demonstrated that the former novel mechanism is potent to generate the slow component. The latter mechanism further increases the size of the slow component; it also moderately decreases metabolite stability and has a small impact on muscle pH. An increase in anaerobic glycolysis intensity increases the slow component, elevates cytosol acidification during exercise, and decreases phosphocreatine and Pi stability, although slightly increases ADP stability. A decrease in the P/O ratio (ATP molecules/O2 molecules) during exercise cannot also be excluded as a relevant mechanism, although this issue requires further study. It is postulated that both the progressive inhibition of anaerobic glycolysis by accumulating protons (together with a slow decrease of the net creatine kinase reaction rate) and gradual increase of ATP usage during exercise, and perhaps a decrease in P/O, contribute to the generation of the slow component of the V̇O2 on-kinetics in skeletal muscle. Copyright © 2015 the American Physiological Society.

In-situ measurement of mechanical properties of structural components using cyclic ball indentation technique

International Nuclear Information System (INIS)

Chatterjee, S.; Madhusoodanan, K.; Panwar, Sanjay; Rupani, B.B.

2007-01-01

Material properties of components change during service due to environmental conditions. Measurement of mechanical properties of the components is important for assessing their fitness for service. In many instances, it is not possible to remove sizable samples from the component for doing the measurement in laboratory. In-situ technique for measurement of mechanical properties has great significance in such cases. One of the nondestructive methods that can be adopted for in-situ application is based on cyclic ball indentation technique. It involves multiple indentation cycles (at the same penetration location) on a metallic surface by a spherical indenter. Each cycle consists of indentation, partial unload and reload sequences. Presently, commercial systems are available for doing indentation test on structural component for limited applications. But, there is a genuine need of remotely operable compact in-situ property measurement system. Considering the importance of such applications Reactor Engineering Division of BARC has developed an In-situ Property Measurement System (IProMS), which can be used for in-situ measurement of mechanical properties of a flat or tubular component. This paper highlights the basic theory of measurement, qualification tests on IProMS and results from tests done on flat specimens and tubular component. (author)
Mechanical integration of the detector components for the CBM silicon tracking system

Energy Technology Data Exchange (ETDEWEB)

Vasylyev, Oleg; Niebur, Wolfgang [GSI Helmholtzzentrum fuer Schwerionenforschung GmbH, Darmstadt (Germany); Collaboration: CBM-Collaboration

2016-07-01

The Compressed Baryonic Matter experiment (CBM) at FAIR is designed to explore the QCD phase diagram in the region of high net-baryon densities. The central detector component, the Silicon Tracking System (STS) is based on double-sided micro-strip sensors. In order to achieve the physics performance, the detector mechanical structures should be developed taking into account the requirements of the CBM experiments: low material budget, high radiation environment, interaction rates, aperture for the silicon tracking, detector segmentation and mounting precision. A functional plan of the STS and its surrounding structural components is being worked out from which the STS system shape is derived and the power and cooling needs, the connector space requirements, life span of components and installation/repair aspects are determined. The mechanical integration is at the point of finalizing the design stage and moving towards production readiness. This contribution shows the current processing state of the following engineering tasks: construction space definition, carbon ladder shape and manufacturability, beam-pipe feedthrough structure, prototype construction, cable routing and modeling of the electronic components.
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.
Nuclear plant aging research - an overview (electrical and mechanical components)

International Nuclear Information System (INIS)

Vora, J.P.

1985-01-01

As the operating nuclear power plants advance in age there must be a conscious national and international effort to understand the influence and safety implications of aging and service wear of components and structures in nuclear power plants and develop measures which are practical and cost effective for timely mitigation of aging degradation that could significantly affect plant safety. The Office of Nuclear Regulatory Research has, therefore, initiated a multi-year, multi-disciplinary program on Nuclear Plant Aging Research (NPAR). The overall goals identified for the program are as follows: 1) to identify and characterize aging and service wear effects associated with electrical and mechanical components, interfaces, and systems whose failure could impair plant safety; 2) to identify and recommend methods of inspection, surveillance and condition monitoring of electrical and mechanical components and systems which will be effective in detecting significant aging effects prior to loss of safety function so that timely maintenance and repair or replacement can be implemented; and, 3) to identify and recommend acceptable maintenance practices which can be undertaken to mitigate the effects of aging and to diminish the rate and extent of degradation caused by aging and service wear. The specific research activities to be implemented to achieve these goals are described
Honey Bees Modulate Their Olfactory Learning in the Presence of Hornet Predators and Alarm Component.

Directory of Open Access Journals (Sweden)

Zhengwei Wang

Full Text Available In Southeast Asia the native honey bee species Apis cerana is often attacked by hornets (Vespa velutina, mainly in the period from April to November. During the co-evolution of these two species honey bees have developed several strategies to defend themselves such as learning the odors of hornets and releasing alarm components to inform other mates. However, so far little is known about whether and how honey bees modulate their olfactory learning in the presence of the hornet predator and alarm components of honey bee itself. In the present study, we test for associative olfactory learning of A. cerana in the presence of predator odors, the alarm pheromone component isopentyl acetate (IPA, or a floral odor (hexanal as a control. The results show that bees can detect live hornet odors, that there is almost no association between the innately aversive hornet odor and the appetitive stimulus sucrose, and that IPA is less well associated with an appetitive stimulus when compared with a floral odor. In order to imitate natural conditions, e.g. when bees are foraging on flowers and a predator shows up, or alarm pheromone is released by a captured mate, we tested combinations of the hornet odor and floral odor, or IPA and floral odor. Both of these combinations led to reduced learning scores. This study aims to contribute to a better understanding of the prey-predator system between A. cerana and V. velutina.
[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.
Improving aerosol drug delivery during invasive mechanical ventilation with redesigned components.

Science.gov (United States)

Longest, P Worth; Azimi, Mandana; Golshahi, Laleh; Hindle, Michael

2014-05-01

Patients receiving invasive mechanical ventilation with an endotracheal tube (ETT) can often benefit from pharmaceutical aerosols; however, drug delivery through the ventilator circuit is known to be very inefficient. The objective of this study was to improve the delivery of aerosol through an invasive mechanical ventilation system by redesigning circuit components using a streamlining approach. Redesigned components were the T-connector interface between the nebulizer and ventilator line and the Y-connector leading to the ETT. The streamlining approach seeks to minimize aerosol deposition and loss by eliminating sharp changes in flow direction and tubing diameter that lead to flow disruption. Both in vitro experiments and computational fluid dynamic (CFD) simulations were applied to analyze deposition and emitted dose of drug for multiple droplet size distributions, flows, and ETT sizes used in adults. The experimental results demonstrated that the streamlined components improved delivery through the circuit by factors ranging from 1.3 to 1.5 compared with a commercial system for adult ETT sizes of 8 and 9 mm. The overall delivery efficiency was based on the bimodal aspect of the aerosol distributions and could not be predicted by median diameter alone. CFD results indicated a 20-fold decrease in turbulence in the junction region for the streamlined Y resulting in a maximum 9-fold decrease in droplet deposition. The relative effectiveness of the streamlined designs was found to increase with increasing particle size and increasing flow, with a maximum improvement in emitted dose of 1.9-fold. Streamlined components can significantly improve the delivery of pharmaceutical aerosols during mechanical ventilation based on an analysis of multiple aerosol generation devices, ETT sizes, and flows.
Principles of designing cyber-physical system of producing mechanical assembly components at Industry 4.0 enterprise

Science.gov (United States)

Gurjanov, A. V.; Zakoldaev, D. A.; Shukalov, A. V.; Zharinov, I. O.

2018-03-01

The task of developing principles of cyber-physical system constitution at the Industry 4.0 company of the item designing components of mechanical assembly production is being studied. The task has been solved by analyzing the components and technologies, which have some practical application in the digital production organization. The list of components has been defined and the authors proposed the scheme of the components and technologies interconnection in the Industry 4.0 of mechanical assembly production to make an uninterrupted manufacturing route of the item designing components with application of some cyber-physical systems.
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.
The Relationship between Epistemological Beliefs and Motivational Components of Self-Regulated Learning Strategies of Male and Female EFL Learners across

Directory of Open Access Journals (Sweden)

Roya Nayebi Limoodehi

2014-11-01

Full Text Available The purpose of the present study was to determine the relationship between five dimensions of the epistemological beliefs regarding structure of knowledge, stability of knowledge, source of knowledge, ability to learn and, speed of learning and six measures of the motivational components of self-regulated learning strategies (intrinsic goal orientation, extrinsic goal orientation, task value, self-efficacy, control of learning, and test anxiety among male and female EFL learners across years of study (freshman and sophomore students. The participants of this study were 101 EFL students studying English literature and English translation in the Islamic Azad University, Rasht Branch, Iran, during the spring semester of 2013. The participants completed Persian version of Motivated Strategies for Learning Questionnaire (MSLQ (Pintrich, Smith, Garcia & McKeachie, 1991 and Persian version of Epistemological Questionnaire (Schommer, 1990. Results showed that, in general, the more naïve the epistemological beliefs of students, the less likely they are to use motivational learning strategies. Moreover, there was no significant relationship between dimensions of epistemological beliefs and motivational components of self-regulated learning strategies among male and female students. On the other hand, a statistically significant relationship was found between dimensions of epistemological beliefs and motivational components of self-regulated learning strategies for both freshman and sophomore students.
Mechanical behaviour of textile-reinforced thermoplastics with integrated sensor network components

International Nuclear Information System (INIS)

Hufenbach, W.; Adam, F.; Fischer, W.-J.; Kunadt, A.; Weck, D.

2011-01-01

Highlights: → Consideration of two types of integrated bus systems for textile-reinforced thermoplastics with embedded sensor networks. → Specimens with bus systems made of flexible printed circuit boards show good mechanical performance compared to the reference. → Inhomogeneous interface and reduced stiffnesses and strengths for specimens with bus systems basing on single copper wires. -- Abstract: The embedding of sensor networks into textile-reinforced thermoplastics enables the design of function-integrative lightweight components suitable for high volume production. In order to investigate the mechanical behaviour of such functionalised composites, two types of bus systems are selected as exemplary components of sensor networks. These elements are embedded into glass fibre-reinforced polypropylene (GF/PP) during the layup process of unconsolidated weft-knitted GF/PP-preforms. Two fibre orientations are considered and orthotropic composite plates are manufactured by hot pressing technology. Micrograph investigations and computer tomography analyses show different interface qualities between the thermoplastic composite and the two types of bus systems. Mechanical tests under tensile and flexural loading indicate a significant influence of the embedded bus system elements on the structural stiffness and strength.
Words, rules, and mechanisms of language acquisition.

Science.gov (United States)

Endress, Ansgar D; Bonatti, Luca L

2016-01-01

We review recent artificial language learning studies, especially those following Endress and Bonatti (Endress AD, Bonatti LL. Rapid learning of syllable classes from a perceptually continuous speech stream. Cognition 2007, 105:247-299), suggesting that humans can deploy a variety of learning mechanisms to acquire artificial languages. Several experiments provide evidence for multiple learning mechanisms that can be deployed in fluent speech: one mechanism encodes the positions of syllables within words and can be used to extract generalization, while the other registers co-occurrence statistics of syllables and can be used to break a continuum into its components. We review dissociations between these mechanisms and their potential role in language acquisition. We then turn to recent criticisms of the multiple mechanisms hypothesis and show that they are inconsistent with the available data. Our results suggest that artificial and natural language learning is best understood by dissecting the underlying specialized learning abilities, and that these data provide a rare opportunity to link important language phenomena to basic psychological mechanisms. For further resources related to this article, please visit the WIREs website. © 2015 Wiley Periodicals, Inc.
The application of linear elastic fracture mechanics to thermally stressed welded components

International Nuclear Information System (INIS)

Green, D.

1981-01-01

Linear Elastic Fracture Mechanics techniques are applied to components constructed from brittle materials and operating at low or ambient temperatures. It is argued that these techniques can justifiably be applied to components at high temperature provided that stresses are thermally induced, self-equilibrating and cyclic. Such loading conditions occur for example in an LMFBR and a simple welded detail containing a crevice is taken as an example. Theoretical and experimental estimates of crack growth in this component are compared and good agreement is shown. (author)
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.
AGING MANAGMENT OF REACTOR COOLANT SYSTEM MECHANICAL COMPONENTS FOR LICENSE RENEWAL

International Nuclear Information System (INIS)

SUBUDHI, M.; MORANTE, R.; LEE, A.D.

2002-01-01

The reactor coolant system (RCS) mechanical components that require an aging management review for license renewal include the primary loop piping and associated connections to other support systems, reactor vessel, reactor vessel internals, pressurizer. steam generators, reactor coolant pumps, and all other inter-connected piping, pipe fittings, valves, and bolting. All major RCS components are located inside the reactor building. Based on the evaluation findings of recently submitted license renewal applications for pressurized water reactors, this paper presents the plant programs and/or activities proposed by the applicants to manage the effects of aging. These programs and/or activities provide reasonable assurance that the intended function(s) of these mechanical components will be maintained for the period of extended operation. The license renewal application includes identification of RCS subcomponents that are within the scope of license renewal and are vulnerable to age-related degradation when exposed to environmental and operational conditions. determination of the effects of aging on their intended safety functions. and implementation of the aging management programs and/or activities including both current and new programs. Industry-wide operating experience, including generic communication by the NRC, is part of the aging management review for the RCS components. In addition, this paper discusses time-limited aging analyses associated with neutron embrittlement of the reactor vessel beltline region and thermal fatigue
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.
Locking mechanism for in-vessel components of tokamak reactor

International Nuclear Information System (INIS)

Nishio, S.; Shimizu, K.; Koizumi, K.; Tada, E.

1992-01-01

The locking and unlocking mechanism for in-vessel replaceable components such as blanket modules, is one of the most critical issues of the tokamak fusion reactor, since the sufficient stiffness against the enormous electromagnetic loads and the easy replaceability are required. In this paper, the authors decide that a caulking cotter joint is worth initiating the R and D from veiwpoints of an effective use of space, a replaceability, a removability of nuclear heating, and a reliability. In this approach, the cotter driving (thrusting and plucking) mechanism is a critical technology. A flexible tube concept has been developed as the driving mechanism, where the stroke and driving force are obtained by a fat shape by the hydraulic pressure. The original normal tube is subjected to the working percentage of more than several hundreds percentage (from thickness of 1.2 mm to 0.2 mm) for plastically forming the flexible tube
Isolating Visual and Proprioceptive Components of Motor Sequence Learning in ASD.

Science.gov (United States)

Sharer, Elizabeth A; Mostofsky, Stewart H; Pascual-Leone, Alvaro; Oberman, Lindsay M

2016-05-01

In addition to defining impairments in social communication skills, individuals with autism spectrum disorder (ASD) also show impairments in more basic sensory and motor skills. Development of new skills involves integrating information from multiple sensory modalities. This input is then used to form internal models of action that can be accessed when both performing skilled movements, as well as understanding those actions performed by others. Learning skilled gestures is particularly reliant on integration of visual and proprioceptive input. We used a modified serial reaction time task (SRTT) to decompose proprioceptive and visual components and examine whether patterns of implicit motor skill learning differ in ASD participants as compared with healthy controls. While both groups learned the implicit motor sequence during training, healthy controls showed robust generalization whereas ASD participants demonstrated little generalization when visual input was constant. In contrast, no group differences in generalization were observed when proprioceptive input was constant, with both groups showing limited degrees of generalization. The findings suggest, when learning a motor sequence, individuals with ASD tend to rely less on visual feedback than do healthy controls. Visuomotor representations are considered to underlie imitative learning and action understanding and are thereby crucial to social skill and cognitive development. Thus, anomalous patterns of implicit motor learning, with a tendency to discount visual feedback, may be an important contributor in core social communication deficits that characterize ASD. Autism Res 2016, 9: 563-569. © 2015 International Society for Autism Research, Wiley Periodicals, Inc. © 2015 International Society for Autism Research, Wiley Periodicals, Inc.
Design of the Mechanical Components of a Dual Axis Solar Tracker

OpenAIRE

Romero Llanas, Amador

2013-01-01

This work is about the design of a solar tracker with the objective of following the sun throughout the day. In order to achieve that objective, the solar tracker has two degrees of freedom. The different mechanical components necessary to build the structure has been designed, calculated and verified. Apart from that, the whole structure has been drawn using the 3D mechanical CAD program SolidWorks. The plans have been drawn too.
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…

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.
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.
Analysis of soft rock mineral components and roadway failure mechanism

Institute of Scientific and Technical Information of China (English)

陈杰

2001-01-01

The mineral components and microstructure of soft rock sampled from roadway floor inXiagou pit are determined by X-ray diffraction and scanning electron microscope. Ccmbined withthe test of expansion and water softening property of the soft rock, the roadway failure mechanism is analyzed, and the reasonable repair supporting principle of roadway is put forward.
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
Exploring the molecular mechanisms of Traditional Chinese Medicine components using gene expression signatures and connectivity map.

Science.gov (United States)

Yoo, Minjae; Shin, Jimin; Kim, Hyunmin; Kim, Jihye; Kang, Jaewoo; Tan, Aik Choon

2018-04-04

Traditional Chinese Medicine (TCM) has been practiced over thousands of years in China and other Asian countries for treating various symptoms and diseases. However, the underlying molecular mechanisms of TCM are poorly understood, partly due to the "multi-component, multi-target" nature of TCM. To uncover the molecular mechanisms of TCM, we perform comprehensive gene expression analysis using connectivity map. We interrogated gene expression signatures obtained 102 TCM components using the next generation Connectivity Map (CMap) resource. We performed systematic data mining and analysis on the mechanism of action (MoA) of these TCM components based on the CMap results. We clustered the 102 TCM components into four groups based on their MoAs using next generation CMap resource. We performed gene set enrichment analysis on these components to provide additional supports for explaining these molecular mechanisms. We also provided literature evidence to validate the MoAs identified through this bioinformatics analysis. Finally, we developed the Traditional Chinese Medicine Drug Repurposing Hub (TCM Hub) - a connectivity map resource to facilitate the elucidation of TCM MoA for drug repurposing research. TCMHub is freely available in http://tanlab.ucdenver.edu/TCMHub. Molecular mechanisms of TCM could be uncovered by using gene expression signatures and connectivity map. Through this analysis, we identified many of the TCM components possess diverse MoAs, this may explain the applications of TCM in treating various symptoms and diseases. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.
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
Sensory-specific clock components and memory mechanisms: investigation with parallel timing.

Science.gov (United States)

Gamache, Pierre-Luc; Grondin, Simon

2010-05-01

A challenge for researchers in the time-perception field is to determine whether temporal processing is governed by a central mechanism or by multiple mechanisms working in concert. Behavioral studies of parallel timing offer interesting insights into the question, although the conclusions fail to converge. Most of these studies focus on the number-of-clocks issue, but the commonality of memory mechanisms involved in time processing is often neglected. The present experiment aims to address a straightforward question: do signals from different modalities marking time intervals share the same clock and/or the same memory resources? To this end, an interval reproduction task involving the parallel timing of two sensory signals presented either in the same modality or in different modalities was conducted. The memory component was tested by manipulating the delay separating the presentation of the target intervals and the moment when the reproduction of one of these began. Results show that there is more variance when only visually marked intervals are presented, and this effect is exacerbated with longer retention delays. Finally, when there is only one interval to process, encoding the interval with signals delivered from two modalities helps to reduce variance. Taken together, these results suggest that the hypothesis stating that there are sensory-specific clock components and memory mechanisms is viable.
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.
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.
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.
Model of components in a process of acoustic diagnosis correlated with learning

International Nuclear Information System (INIS)

Seballos, S.; Costabal, H.; Matamala, P.

1992-06-01

Using Linden's functional scheme as a theoretical reference framework, we define a matrix of component for clinical and field applications in the acoustic diagnostic process and correlations with audiologic, learning and behavioral problems. It is expected that the model effectively contributes to classify and provide a greater knowledge about this multidisciplinary problem. Although the exact nature of this component is at present a matter to be defined, its correlation can be hypothetically established. Applying this descriptive and integral approach in the diagnostic process it is possible if not to avoid, at least to decrease, the uncertainties and assure the proper solutions becoming a powerful tool applicable to environmental studies and/or social claims. (author). 8 refs, 2 figs
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.
Mechanical and materials engineering of modern structure and component design

CERN Document Server

Altenbach, Holm

2015-01-01

This book presents the latest findings on mechanical and materials engineering as applied to the design of modern engineering materials and components. The contributions cover the classical fields of mechanical, civil and materials engineering, as well as bioengineering and advanced materials processing and optimization. The materials and structures discussed can be categorized into modern steels, aluminium and titanium alloys, polymers/composite materials, biological and natural materials, material hybrids and modern nano-based materials. Analytical modelling, numerical simulation, state-of-the-art design tools and advanced experimental techniques are applied to characterize the materials’ performance and to design and optimize structures in different fields of engineering applications.
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.
Learning from neural control.

Science.gov (United States)

Wang, Cong; Hill, David J

2006-01-01

One of the amazing successes of biological systems is their ability to "learn by doing" and so adapt to their environment. In this paper, first, a deterministic learning mechanism is presented, by which an appropriately designed adaptive neural controller is capable of learning closed-loop system dynamics during tracking control to a periodic reference orbit. Among various neural network (NN) architectures, the localized radial basis function (RBF) network is employed. A property of persistence of excitation (PE) for RBF networks is established, and a partial PE condition of closed-loop signals, i.e., the PE condition of a regression subvector constructed out of the RBFs along a periodic state trajectory, is proven to be satisfied. Accurate NN approximation for closed-loop system dynamics is achieved in a local region along the periodic state trajectory, and a learning ability is implemented during a closed-loop feedback control process. Second, based on the deterministic learning mechanism, a neural learning control scheme is proposed which can effectively recall and reuse the learned knowledge to achieve closed-loop stability and improved control performance. The significance of this paper is that the presented deterministic learning mechanism and the neural learning control scheme provide elementary components toward the development of a biologically-plausible learning and control methodology. Simulation studies are included to demonstrate the effectiveness of the approach.
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:
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.
Coagulation mechanism of salt solution-extracted active component in Moringa oleifera seeds.

Science.gov (United States)

Okuda, T; Baes, A U; Nishijima, W; Okada, M

2001-03-01

This study focuses on the coagulation mechanism by the purified coagulant solution (MOC-SC-PC) with the coagulation active component extracted from M. oleifera seeds using salt solution. The addition of MOC-SC-PC tap water formed insoluble matters. This formation was responsible for kaolin coagulation. On the other hand, insoluble matters were not formed when the MOC-SC-PC was added into distilled water. The formation was affected by Ca2+ or other bivalent cations which may connect each molecule of the active coagulation component in MOC-SC-PC and form a net-like structure. The coagulation mechanism of MOC-SC-PC seemed to be an enmeshment of Kaolin by the insoluble matters with the net-like structure. In case of Ca2+ ion (bivalent cations), at least 0.2 mM was necessary for coagulation at 0.3 mgC l-1 dose of MOC-SC-PC. Other coagulation mechanisms like compression of double layer, interparticle bridging or charge neutralization were not responsible for the coagulation by MOC-SC-PC.
RCC-M: Design and construction rules for mechanical components of PWR nuclear islands

International Nuclear Information System (INIS)

2017-01-01

AFCEN's RCC-M code concerns the mechanical components designed and manufactured for pressurized water reactors (PWR). It applies to pressure equipment in nuclear islands in safety classes 1, 2 and 3, and certain non-pressure components, such as vessel internals, supporting structures for safety class components, storage tanks and containment penetrations. RCC-M covers the following technical subjects: sizing and design, choice of materials and procurement. Fabrication and control, including: associated qualification requirements (procedures, welders and operators, etc.), control methods to be implemented, acceptance criteria for detected defects, documentation associated with the different activities covered, and quality assurance. The design, manufacture and inspection rules defined in RCC-M leverage the results of the research and development work pioneered in France, Europe and worldwide, and which have been successfully used by industry to design and build PWR nuclear islands. AFCEN's rules incorporate the resulting feedback. Use: France's last 16 nuclear units (P'4 and N4); 4 CP1 reactors in South Africa (2) and Korea (2); 44 M310 (4), CPR-1000 (28), CPR-600 (6), HPR-1000 (4) and EPR (2) reactors in service or undergoing construction in China; 4 EPR reactors in Europe: Finland (1), France (1) and UK (2). Content: Section I - nuclear island components, subsection 'A': general rules, subsection 'B': class 1 components, subsection 'C': class 2 components, subsection 'D': class 3 components, subsection 'E': small components, subsection 'G': core support structures, subsection 'H': supports, subsection 'J': low pressure or atmospheric storage tanks, subsection 'P': containment penetration, subsection 'Q': qualification of active mechanical components, subsection 'Z': technical appendices; section II - materials; section III - examination
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.

Principal component reconstruction (PCR) for cine CBCT with motion learning from 2D fluoroscopy.

Science.gov (United States)

Gao, Hao; Zhang, Yawei; Ren, Lei; Yin, Fang-Fang

2018-01-01

This work aims to generate cine CT images (i.e., 4D images with high-temporal resolution) based on a novel principal component reconstruction (PCR) technique with motion learning from 2D fluoroscopic training images. In the proposed PCR method, the matrix factorization is utilized as an explicit low-rank regularization of 4D images that are represented as a product of spatial principal components and temporal motion coefficients. The key hypothesis of PCR is that temporal coefficients from 4D images can be reasonably approximated by temporal coefficients learned from 2D fluoroscopic training projections. For this purpose, we can acquire fluoroscopic training projections for a few breathing periods at fixed gantry angles that are free from geometric distortion due to gantry rotation, that is, fluoroscopy-based motion learning. Such training projections can provide an effective characterization of the breathing motion. The temporal coefficients can be extracted from these training projections and used as priors for PCR, even though principal components from training projections are certainly not the same for these 4D images to be reconstructed. For this purpose, training data are synchronized with reconstruction data using identical real-time breathing position intervals for projection binning. In terms of image reconstruction, with a priori temporal coefficients, the data fidelity for PCR changes from nonlinear to linear, and consequently, the PCR method is robust and can be solved efficiently. PCR is formulated as a convex optimization problem with the sum of linear data fidelity with respect to spatial principal components and spatiotemporal total variation regularization imposed on 4D image phases. The solution algorithm of PCR is developed based on alternating direction method of multipliers. The implementation is fully parallelized on GPU with NVIDIA CUDA toolbox and each reconstruction takes about a few minutes. The proposed PCR method is validated and
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.
A Learning Outcome-Oriented Approach towards Classifying Pervasive Games for Learning Using Game Design Patterns and Contextual Information

Science.gov (United States)

Schmitz, Birgit; Klemke, Roland; Specht, Marcus

2013-01-01

Mobile and in particular pervasive games are a strong component of future scenarios for teaching and learning. Based on results from a previous review of practical papers, this work explores the educational potential of pervasive games for learning by analysing underlying game mechanisms. In order to determine and classify cognitive and affective…
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.
Component simulation in problems of calculated model formation of automatic machine mechanisms

OpenAIRE

Telegin Igor; Kozlov Alexander; Zhirkov Alexander

2017-01-01

The paper deals with the problems of the component simulation method application in the problems of the automation of the mechanical system model formation with the further possibility of their CAD-realization. The purpose of the investigations mentioned consists in the automation of the CAD-model formation of high-speed mechanisms in automatic machines and in the analysis of dynamic processes occurred in their units taking into account their elasto-inertial properties, power dissipation, gap...
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.
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.
Design of Ontology-Based Sharing Mechanism for Web Services Recommendation Learning Environment

Science.gov (United States)

Chen, Hong-Ren

The number of digital learning websites is growing as a result of advances in computer technology and new techniques in web page creation. These sites contain a wide variety of information but may be a source of confusion to learners who fail to find the information they are seeking. This has led to the concept of recommendation services to help learners acquire information and learning resources that suit their requirements. Learning content like this cannot be reused by other digital learning websites. A successful recommendation service that satisfies a certain learner must cooperate with many other digital learning objects so that it can achieve the required relevance. The study proposes using the theory of knowledge construction in ontology to make the sharing and reuse of digital learning resources possible. The learning recommendation system is accompanied by the recommendation of appropriate teaching materials to help learners enhance their learning abilities. A variety of diverse learning components scattered across the Internet can be organized through an ontological process so that learners can use information by storing, sharing, and reusing it.
Research on the mechanical behaviour of an airplane component made by selective laser melting technology

Directory of Open Access Journals (Sweden)

Păcurar Răzvan

2017-01-01

Full Text Available The main objective of the presented research consists in the redesign of an airplane component to decrease its weight, without affecting the mechanical behaviour of the component, at the end. Femap NX Nastran and ANSYS FEA programs were used for the shape optimization and for the estimation of the mechanical behaviour of a fixing clamp that was used to sustain the hydraulic pipes that are passing through an airplane fuselage, taking into consideration two types of raw materials – Ti6Al4V and AlSi12 powder from which this component could be manufactured by using the selective laser melting (SLM technology. Based on the obtained results, the airplane component was finally manufactured from titanium alloy using the SLM 250 HL equipment that is available at SLM Solutions GmbH company from Luebeck, in Germany.
Multiple brain networks underpinning word learning from fluent speech revealed by independent component analysis.

Science.gov (United States)

López-Barroso, Diana; Ripollés, Pablo; Marco-Pallarés, Josep; Mohammadi, Bahram; Münte, Thomas F; Bachoud-Lévi, Anne-Catherine; Rodriguez-Fornells, Antoni; de Diego-Balaguer, Ruth

2015-04-15

Although neuroimaging studies using standard subtraction-based analysis from functional magnetic resonance imaging (fMRI) have suggested that frontal and temporal regions are involved in word learning from fluent speech, the possible contribution of different brain networks during this type of learning is still largely unknown. Indeed, univariate fMRI analyses cannot identify the full extent of distributed networks that are engaged by a complex task such as word learning. Here we used Independent Component Analysis (ICA) to characterize the different brain networks subserving word learning from an artificial language speech stream. Results were replicated in a second cohort of participants with a different linguistic background. Four spatially independent networks were associated with the task in both cohorts: (i) a dorsal Auditory-Premotor network; (ii) a dorsal Sensory-Motor network; (iii) a dorsal Fronto-Parietal network; and (iv) a ventral Fronto-Temporal network. The level of engagement of these networks varied through the learning period with only the dorsal Auditory-Premotor network being engaged across all blocks. In addition, the connectivity strength of this network in the second block of the learning phase correlated with the individual variability in word learning performance. These findings suggest that: (i) word learning relies on segregated connectivity patterns involving dorsal and ventral networks; and (ii) specifically, the dorsal auditory-premotor network connectivity strength is directly correlated with word learning performance. Copyright © 2015 Elsevier Inc. All rights reserved.
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.
RCC-M - Design and Conception Rules for Mechanical Components of PWR Nuclear Islands

International Nuclear Information System (INIS)

2007-01-01

The design and construction rules applicable to mechanical components of PWR Nuclear Islands (RCC-M) are a part of the collection of design and construction rules for nuclear power plants. It covers the rules applicable to the design and manufacture of pressure boundaries of mechanical equipment of pressurized water reactors (PWR). The pressure components subject to the RCC-M are specified in A 4000. They include the reactor fluid systems (primary, secondary and auxiliary systems) and other components which are not subject to pressure: vessel internals, supports for pressure components subject to the RCC-M, nuclear island storage tanks. When a pressure equipment is subject to the RCC-M, all its elements subject to pressure are also, in accordance with the provisions of A 4000, and these elements are the same class as the component. In this case all the provisions of the RCC-M are applicable: design, procurement, manufacture, inspection and pressure testing. Elements which are not subject to pressure and which are subject to the RCC-M may be covered within the Code by limited specific provisions (procurement of materials for example). The other rules applicable to this equipment must be in contractual form. The assemblies comprising pressure equipment assembled by a manufacturer to constitute an integrated and functional whole, shall be subject to the rules indicated in this Code. Main objectives of Code Requirements are to ensure the integrity and mechanical stability over the equipment design life. Function ability and operability of equipment are not directly addressed in the Code. The RCC-M contributes to ensuring compliance with regulatory requirements. These requirements depend on the applicable regulatory context. The RCC-M is representative of the state of the art as concerns the design and manufacture of PWR components, ensuring an overall safety level tested through experience. The RCC-M consists of five sections, which provide rules for the design and
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.
Lifetime management for mechanical systems, structures and components in nuclear power plants

International Nuclear Information System (INIS)

Roos, E.; Herter, K.-H.; Schuler, X.

2006-01-01

Guidelines, codes and standards contain regulations and requirements with respect to the quality of mechanical systems, structures and components (SSC) of nuclear power plants. These concern safe operation during the total lifetime (lifetime management), safety against ageing phenomena (ageing management) as well as proof of integrity (e.g. break exclusion or avoidance of fracture). Within this field the ageing management is a key element. Depending on the safety-relevance of the SSC under observation including preventive maintenance various tasks are required in particular to clarify the mechanisms which contribute system-specifically to the damage of the components and systems and to define their controlling parameters which have to be monitored and checked. Appropriate continuous or discontinuous measures are to be considered in this connection. The approach to ensure a high standard of quality in operation and the management of the technical and organisational aspects are demonstrated and explained
Effect of the addition of mixture of plant components on the mechanical properties of wheat bread

Science.gov (United States)

Wójcik, Monika; Dziki, Dariusz; Biernacka, Beata; Różyło, Renata; Miś, Antoni; Hassoon, Waleed H.

2017-10-01

Instrumental methods of measuring the mechanical properties of bread can be used to determine changes in the properties of it during storage, as well as to determine the effect of various additives on the bread texture. The aim of this study was to investigate the effect of the mixture of plant components on the physical properties of wheat bread. In particular, the mechanical properties of the crumb and crust were studied. A sensory evaluation of the end product was also performed. The mixture of plant components included: carob fiber, milled grain red quinoa and black oat (1:2:2) - added at 0, 5, 10, 15, 20, 25 % - into wheat flour. The results showed that the increase of the addition of the proposed additive significantly increased the water absorption of flour mixtures. Moreover, the use of the mixture of plant components above 5% resulted in the increase of bread volume and decrease of crumb density. Furthermore, the addition of the mixture of plant components significantly affected the mechanical properties of bread crumb. The hardness of crumb also decreased as a result of the mixture of plant components addition. The highest cohesiveness was obtained for bread with 10% of additive and the lowest for bread with 25% of mixture of plant components. Most importantly, the enrichment of wheat flour with the mixture of plant components significantly reduced the crust failure force and crust failure work. The results of sensory evaluation showed that the addition of the mixture of plant components of up to 10% had little effect on bread quality.
Focal mechanism of seismic events with a dipolar component

Directory of Open Access Journals (Sweden)

R. Console

1995-06-01

Full Text Available In this paper we model the geometry of a seismic source as a dislocation occurring on an elemental flat fault in an arbitrary direction with respect to the fault plane. This implies the use of a fourth parameter in addition to the three usual ones describing a simple double couple mechanism. We applied the radiation pattern obtained from the theory to a computer code written for the inversion of the observation data (amplitudes and polarities of the first onsets recorded by a network of stations. It allows the determination of the fault mechanism gener- alized in the above mentioned way. The computer code was verified on synthetic data and then applied to real data recorded by the seismic network operated by the Ente Nazionale per l'Energia Elettrica (ENEL, monitoring the geothermal field of Larderello. The experimental data show that for some events the source mechanism exhibits a significant dipolar component. However, due to the high standard deviation of the amplitude data, F-test applied to the results of the analysis shows that only for two events the confidence level for the general- ized model exceeds 90%.
Optimising mechanical properties of hot forged nickel superalloy 625 components

Science.gov (United States)

Singo, Nthambe; Coles, John; Rosochowska, Malgorzata; Lalvani, Himanshu; Hernandez, Jose; Ion, William

2018-05-01

Hot forging and subsequent heat treatment were resulting in substandard mechanical properties of nickel superalloy, Alloy 625, components. The low strength was found to be due to inadequate deformation during forging, excessive grain growth and precipitation of carbides during subsequent heat treatment. Experimentation in a drop forging company and heat treatment facility led to the establishment of optimal parameters to minimise grain size and mitigate the adverse effects of carbide precipitation, leading to successful fulfilment of mechanical property specifications. This was achieved by reducing the number of operations, maximising the extent of deformation by changing the slug dimensions and its orientation in the die, and minimising the time of exposure to elevated temperatures in both the forging and subsequent heat treatment processes to avoid grain growth.
Failure Predictions for VHTR Core Components using a Probabilistic Contiuum Damage Mechanics Model

Energy Technology Data Exchange (ETDEWEB)

Fok, Alex

2013-10-30

The proposed work addresses the key research need for the development of constitutive models and overall failure models for graphite and high temperature structural materials, with the long-term goal being to maximize the design life of the Next Generation Nuclear Plant (NGNP). To this end, the capability of a Continuum Damage Mechanics (CDM) model, which has been used successfully for modeling fracture of virgin graphite, will be extended as a predictive and design tool for the core components of the very high- temperature reactor (VHTR). Specifically, irradiation and environmental effects pertinent to the VHTR will be incorporated into the model to allow fracture of graphite and ceramic components under in-reactor conditions to be modeled explicitly using the finite element method. The model uses a combined stress-based and fracture mechanics-based failure criterion, so it can simulate both the initiation and propagation of cracks. Modern imaging techniques, such as x-ray computed tomography and digital image correlation, will be used during material testing to help define the baseline material damage parameters. Monte Carlo analysis will be performed to address inherent variations in material properties, the aim being to reduce the arbitrariness and uncertainties associated with the current statistical approach. The results can potentially contribute to the current development of American Society of Mechanical Engineers (ASME) codes for the design and construction of VHTR core components.
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.
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

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.
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…
Structural mechanics research and development for main components of chinese 300 MWe PWR NPPs: from design to life management

International Nuclear Information System (INIS)

Yao Weida; Dou Yikang; Xie Yongcheng; He Yinbiao; Zhang Ming; Liang Xingyun

2005-01-01

Qinshan Nuclear Power Plant (Unit I), is a 300 MWe prototype PWR independently developed by Chinese own efforts, from design, manufacture, construction, installation, commissioning, to operation, inspection, maintenance, ageing management and lifetime assessment. Shanghai Nuclear Engineering Research and Design Institute (SNERDI) has taken up with and involved in deeply the R and D to tackle problems of this type of reactor since very beginning in early 1970s. Structural mechanics is one of the important aspects to ensure the safety and reliability for NPP components. This paper makes a summary on role of structural mechanics for component safety and reliability assessment in different stages of design, commissioning, operation, as well as lifetime assessment on this type PWR NPPs, including Qinshan-I and Chashma-I, a sister plant in Pakistan designed by SNERDI. The main contents of the paper cover design by analysis for key components of NSSS; mechanical problems relating to safety analysis; special problems relating to pressure retaining components, such as fracture mechanics, sealing analysis and its test verifications, etc.; experimental research on flow-induced vibration; seismic qualification for components; component failure diagnosis and root cause analysis; vibration qualification and diagnosis technique; component online monitoring technique; development of defect assessment; methodology of aging management and lifetime assessment for key components of NPPs, etc. (authors)
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…
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
Applications and limits of application of fracture mechanics methods in assessing the safety of components

International Nuclear Information System (INIS)

Stahlberg, R.

1977-01-01

On the basis of fracture mechanics calculations and experimental investigations, it is shown how cracks of different shape and location behave under given static and cyclic loads. In particular, component safety with regard to spontaneous failure and crack growth behaviour in different components are discussed. [de
Thermal loads and their effect on integrity of mechanical systems and components

International Nuclear Information System (INIS)

Koenig, G.; Schoeckle, F.

2010-01-01

The initial step to establish a required quality status of systems and components is performed during the state of design. Main goal of the design is to consider every possible damage mechanism of the future operation (by specification of loads, medium and environment and the selection of the materials). The knowledge during the state of design determines the reliability of the component. Regarding the thermal loads, especially, only global parameters are specified usually (transients of flow and temperature connected to specified operation). These global transients are analyzed according to the standards. In operation, the safety (integrity) resp. remaining life of a component is determined by the real operation history. As experience showed, failures, defects and not specified (new) loads were discovered during operation, e.g. stratification effects in feedwater pipes and in surge lines or thermal effects in the region of valves due to switching or internal leakage. Standard surveillance in operation is performed using plant transducers that can only monitor global loads. However, problems usually are of local nature. Thermal loads like - turbulent temperatures due to mixing of media with different temperatures - temperature differences across shells or in regions of nozzles/thermal sleeves - temperature differences in piping cross sections (local and global stratification effects) - temperature differences along sections of piping systems have to be monitored by use of local instrumentation. During analysis, both the local loads and construction details have to be considered, in detail, using appropriate calculation / analysis tools. The complexity of the loads requires a comprehensive procedure: - determine the types of loads resulting from measured temperature transients - perform sensitivity studies to identify the load type that results in relevant stresses - evaluate the stresses of the significant loads - assess these stresses according to component
An empirical investigation of intellectual capital components on each others and organizational learning capabilities

Directory of Open Access Journals (Sweden)

Nabi ollah Nejatizadeh

2013-02-01

Full Text Available During the past few years, there have been growing interests on intellectual capital due to industrial changes on the market. Thus, identifying different ways to create, manage, and evaluate the impact of intellectual capital has remained an open area of research. One of the most important organizational capabilities, which could help organizations create and share knowledge is to effectively use knowledge to create competitive advantage. The primary objective of this study is to investigate the effects of intellectual capital on other components and their impacts on organizational learning capability using structural equation modeling. The statistical population includes 500 employees of an Iranian organization. The study uses a sample size including 273 people using Morgan statistical table. In our survey, human capital influences positively (0.330 on structural capital, human capital influences positively on relational capital (0.47 and relational capital influences positively on structural capital (0.455. In addition human capital influences positively on learning capabilities (0.06, structural capital impacts learning capabilities (0.355 and relational capital on learning capabilities (0.545.
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
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
Profiles of Automotive Suppliers Industries--Engineered Mechanical Components and Systems : Volume II, Appendices.

Science.gov (United States)

1981-09-01

The profile describes and analyzes that segment of the automotive supplier industry which provides engineered mechanical components/assemblies/systems to the prime auto manufacturers. It presents an overview of the role and structure of this industry...
Profiles of Automotive Suppliers Industries--Engineered Mechanical Components and Systems : Volume I, Text.

Science.gov (United States)

1981-09-01

This profile describes and analyzes that segment of the automotive supplier industry which provides engineered mechanical components/assemblies/systems to the prime auto manufacturers. It presents an overview of the role and structure of this industr...
General Description of the Mechanic Design of the Pressure Vessel and the Internal Mechanical Component of the CAREM Reactor

International Nuclear Information System (INIS)

Diez, F.; Horro, R.

2000-01-01

This paper presents a brief description of the CAREM reactor pressure vessel and its main internal mechanical components and summarizes the functional requirements and approaches applied for their design, together with a review of the normative applicable in each case
Mechanized inspection of steam generator components during manufacture

International Nuclear Information System (INIS)

Otte, H.-J.; Leupoldt, K.; Meister, W.

2009-01-01

Steam Generator (SG) parts are intensively inspected by UT in the course of the manufacturing process. These inspections - mostly performed manually using different codes - are time consuming and call for a sophisticated documentation, figuring part of the life time documentation package. In order to reduce time and costs mechanized inspection equipment is introduced, combining short inspection times, avoiding influence of the human factor and providing proper electronic storage of all inspection results prepared for comparison with data generated during in-service inspection. Since 2001 Cegelec delivered various UT systems for gas turbine disks and rotor ends called SIRO-MAN. Within only a few years the majority of important providers of such components successfully switched from manual inspection to mechanized inspection following the requirements of manufacturers like ALSTOM, GE and Siemens. The SIRO-MAN is now adapted to the needs of mechanized inspection of SG components. The inspection is performed on the products during rotation around the vertical axis. The multi - probe assemblies are manoeuvred on the products by a manipulator system backed by a NC control unit. Acoustic coupling of UT probes to the product surface is performed with oil or water in a closed circuit. UT and - if requested ET - data along with position information of the probe assembly provided by the control unit are acquired, processed and evaluated by an UT / ET electronic system delivered by either Olympus or ZETEC. As performed already on rotor ends a sequence of inspections using different parameter settings can be programmed with simple means (Teach In) so that such inspection sequence can be executed without operating personnel. Probe assemblies allow for individual operation of probes out of the probe assembly according to the individual needs. Conventional UT and phased array applications or combination of both techniques can be provided. The UT / ET electronic equipment offers
Facilitative Components of Collaborative Learning: A Review of Nine Health Research Networks.

Science.gov (United States)

Leroy, Lisa; Rittner, Jessica Levin; Johnson, Karin E; Gerteis, Jessie; Miller, Therese

2017-02-01

Collaborative research networks are increasingly used as an effective mechanism for accelerating knowledge transfer into policy and practice. This paper explored the characteristics and collaborative learning approaches of nine health research networks. Semi-structured interviews with representatives from eight diverse US health services research networks conducted between November 2012 and January 2013 and program evaluation data from a ninth. The qualitative analysis assessed each network's purpose, duration, funding sources, governance structure, methods used to foster collaboration, and barriers and facilitators to collaborative learning. The authors reviewed detailed notes from the interviews to distill salient themes. Face-to-face meetings, intentional facilitation and communication, shared vision, trust among members and willingness to work together were key facilitators of collaborative learning. Competing priorities for members, limited funding and lack of long-term support and geographic dispersion were the main barriers to coordination and collaboration across research network members. The findings illustrate the importance of collaborative learning in research networks and the challenges to evaluating the success of research network functionality. Conducting readiness assessments and developing process and outcome evaluation metrics will advance the design and show the impact of collaborative research networks. Copyright © 2017 Longwoods Publishing.
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
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.
Continual and One-Shot Learning Through Neural Networks with Dynamic External Memory

DEFF Research Database (Denmark)

Lüders, Benno; Schläger, Mikkel; Korach, Aleksandra

2017-01-01

it easier to find unused memory location and therefor facilitates the evolution of continual learning networks. Our results suggest that augmenting evolving networks with an external memory component is not only a viable mechanism for adaptive behaviors in neuroevolution but also allows these networks...... a new task is learned. This paper takes a step in overcoming this limitation by building on the recently proposed Evolving Neural Turing Machine (ENTM) approach. In the ENTM, neural networks are augmented with an external memory component that they can write to and read from, which allows them to store...... associations quickly and over long periods of time. The results in this paper demonstrate that the ENTM is able to perform one-shot learning in reinforcement learning tasks without catastrophic forgetting of previously stored associations. Additionally, we introduce a new ENTM default jump mechanism that makes...
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.
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

Motivational component profiles in university students learning histology: a comparative study between genders and different health science curricula

OpenAIRE

Campos-Sánchez, Antonio; López-Núñez, Juan Antonio; Carriel, Víctor; Martín-Piedra, Miguel-Ángel; Sola, Tomás; Alaminos, Miguel

2014-01-01

Background: The students' motivation to learn basic sciences in health science curricula is poorly understood. The purpose of this study was to investigate the influence of different components of motivation (intrinsic motivation, self-determination, self-efficacy and extrinsic -career and grade-motivation) on learning human histology in health science curricula and their relationship with the final performance of the students in histology. Methods: Glynn Science Motivation Questionnaire ...
Design and structural calculation of nuclear power plant mechanical components

International Nuclear Information System (INIS)

Amaral, J.A.R. do

1986-01-01

The mechanical components of a nuclear power plant must show high quality and safety due to the presence of radioactivity. Besides the perfect functioning during the rigid operating conditions, some postulated loadings are foreseen, like earthquake and loss of coolant accidents, which must be also considered in the design. In this paper, it is intended to describe the design and structural calculations concept and development, the interactions with the piping and civil designs, as well as their influences in the licensing process with the authorities. (Author) [pt
The mechanism of suppression: a component of general comprehension skill.

Science.gov (United States)

Gernsbacher, M A; Faust, M E

1991-03-01

We investigated whether the cognitive mechanism of suppression underlies differences in adult comprehension skill. Less skilled comprehenders reject less efficiently the inappropriate meanings of ambiguous words (e.g., the playing card vs. garden tool meaning of spade), the incorrect forms of homophones (e.g., patients vs. patience), the highly typical but absent members of scenes (e.g., a tractor in a farm scene), and words superimposed on pictures or pictures surrounding words. However, less skilled comprehenders are not less cognizant of what is contextually appropriate; in fact, they benefit from a biasing context just as much (and perhaps more) as more skilled comprehenders do. Thus, less skilled comprehenders do not have difficulty enhancing contextually appropriate information. Instead, we suggest that less skilled comprehenders suffer from a less efficient suppression mechanism, which we conclude is an important component of general comprehension skill.
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…
Proof of integrity and ageing management of mechanical components in nuclear power plants

International Nuclear Information System (INIS)

Roos, E.; Herter, K.-H.; Kockelmann, H.; Schuler, X.

2005-01-01

Demands and requirements for a safe operation of mechanical components during the whole operation life time (plant life management) to assure aging phenomena (aging management) and to prove the integrity (prove of integrity, e.g. in order to exclude large breaks) can be found in guidelines, codes and standards. In the present paper a general concept to proof the integrity as part of the ageing management of pressurized components and systems is presented. The concept is based on the actual material characteristics, the actual as-built configurations and the design of the components and systems including the knowledge of possible failure mechanism during operation. An important part of the assessment is the leak before break behavior and the break preclusion concept. Based on essential research results the developed procedures and methodologies for the assessment of the critical crack sizes as well as the critical loading conditions are reported and discussed. In detail the following aspects have to be treated: (a) evaluation of the as-built status of quality (design, construction, material, fabrication; results of recurrent non destructive examinations up to now, operational experience); (b) determination of the relevant loading conditions by means of in-service monitoring (monitoring of the mode of operation, the water chemistry, the mechanical and thermal stresses, the dynamic loading), emergency and faulted condition loads as specified; (c) evaluation of the actual status of quality with respect to the relevant loading conditions (stress analysis-limitation of the stresses; fatigue analysis-determination of the usage factor; fracture mechanics analysis-determination of crack growth, critical crack sizes and loading conditions); (d) evaluation and extent of the in-service monitoring and recurrent inspections to guarantee the succeeding operation (recurrent non destructive examination - minimum detectable flaw sizes, examination area, examination intervals; leak
Mechanical component design for upgrading of whole body counter ND7500

International Nuclear Information System (INIS)

Norizam Saad; Mohamad Annuar Assadat Husain; Ishak Mansor

2007-01-01

The Whole Body Counter (WBC) ND7500 is a bed type counting system that used for measuring radionuclide in the entire human body. Malaysian Nuclear Agency has this system, which savaged from Institute of Medical Research (IMR) in 1987. This system consists of a nuclear counting system and mechanical system that totally inoperable due to its counting system failures. In April 2003, both counting system and the mechanical system were tested. The mechanical component is working properly but needs some readjustment for the bed movement while for the counting system, only detectors can work but with a poor detecting capability. During IAEA expert visits on July 2003, both detectors were verified cannot be use any longer due to poor resolution and aging factor and a single (3 x 5 x 16) inches rectangular NaI(Tl) detector was then purchased in the end of 2004 to replace (3 x 5) inches cylindrical Na(Tl) detectors. The existing shielding cannot accommodate this new (3 x 5 x 16) inches dimension and the (5 x 16) inches detecting area. Therefore, shielding modification has been done based on effective detecting area and positioning test results. A new detector's entrance and detector stage were built at the bottom shielding. A new features, which is a detectors protection also been developed for detector safety. This upgrading task successfully accomplished as from experimental the design of positioning component can make system operated easily and also can give a good results to meets user's requirements. (Author)
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…
TENCompetence Learning Design Toolkit, Runtime component, ccsi_v3_2_10c_v1_4

NARCIS (Netherlands)

Sharples, Paul; Popat, Kris; Llobet, Lau; Santos, Patricia; Hernández-Leo, Davinia; Miao, Yongwu; Griffiths, David; Beauvoir, Phillip

2010-01-01

Sharples, P., Popat, K., Llobet, L., Santos, P., Hernandez-Leo, D., Miao, Y., Griffiths, D. & Beauvoir, P. (2009) TENCompetence Learning Design Toolkit, Runtime component, ccsi_v3_2_10c_v1_4 This release is composed of three files corresponding to CopperCore Service Integration (CCSI) v3.2-10cv1.4,
Reflections on Designing a MPA Service-Learning Component: Lessons Learned

Science.gov (United States)

Roman, Alexandru V.

2015-01-01

This article provides the "lessons learned" from the experience of redesigning two sections (face-to-face and online) of a core master of public administration class as a service-learning course. The suggestions made here can be traced to the entire process of the project, from the "seed idea" through its conceptualization and…
Aero Engine Component Fault Diagnosis Using Multi-Hidden-Layer Extreme Learning Machine with Optimized Structure

Directory of Open Access Journals (Sweden)

Shan Pang

2016-01-01

Full Text Available A new aero gas turbine engine gas path component fault diagnosis method based on multi-hidden-layer extreme learning machine with optimized structure (OM-ELM was proposed. OM-ELM employs quantum-behaved particle swarm optimization to automatically obtain the optimal network structure according to both the root mean square error on training data set and the norm of output weights. The proposed method is applied to handwritten recognition data set and a gas turbine engine diagnostic application and is compared with basic ELM, multi-hidden-layer ELM, and two state-of-the-art deep learning algorithms: deep belief network and the stacked denoising autoencoder. Results show that, with optimized network structure, OM-ELM obtains better test accuracy in both applications and is more robust to sensor noise. Meanwhile it controls the model complexity and needs far less hidden nodes than multi-hidden-layer ELM, thus saving computer memory and making it more efficient to implement. All these advantages make our method an effective and reliable tool for engine component fault diagnosis tool.
Other components

International Nuclear Information System (INIS)

Anon.

1993-01-01

This chapter includes descriptions of electronic and mechanical components which do not merit a chapter to themselves. Other hardware requires mention because of particularly high tolerance or intolerance of exposure to radiation. A more systematic analysis of radiation responses of structures which are definable by material was given in section 3.8. The components discussed here are field effect transistors, transducers, temperature sensors, magnetic components, superconductors, mechanical sensors, and miscellaneous electronic components
Theoretical physics 1 classical mechanics

CERN Document Server

Nolting, Wolfgang

2016-01-01

This textbook offers a clear and comprehensive introduction to classical mechanics, one of the core components of undergraduate physics courses. The book starts with a thorough introduction to the mathematical tools needed, to make this textbook self-contained for learning. The second part of the book introduces the mechanics of the free mass point and details conservation principles. The third part expands the previous to mechanics of many particle systems. Finally the mechanics of the rigid body is illustrated with rotational forces, inertia and gyroscope movement. Ideally suited to undergraduate students in their first year, the book is enhanced throughout with learning features such as boxed inserts and chapter summaries, with key mathematical derivations highlighted to aid understanding. The text is supported by numerous worked examples and end of chapter problem sets. About the Theoretical Physics series Translated from the renowned and highly successful German editions, the eight volumes of this series...
Pathways and mechanisms linking dietary components to cardiometabolic disease: thinking beyond calories.

Science.gov (United States)

Stanhope, K L; Goran, M I; Bosy-Westphal, A; King, J C; Schmidt, L A; Schwarz, J-M; Stice, E; Sylvetsky, A C; Turnbaugh, P J; Bray, G A; Gardner, C D; Havel, P J; Malik, V; Mason, A E; Ravussin, E; Rosenbaum, M; Welsh, J A; Allister-Price, C; Sigala, D M; Greenwood, M R C; Astrup, A; Krauss, R M

2018-05-14

Calories from any food have the potential to increase risk for obesity and cardiometabolic disease because all calories can directly contribute to positive energy balance and fat gain. However, various dietary components or patterns may promote obesity and cardiometabolic disease by additional mechanisms that are not mediated solely by caloric content. Researchers explored this topic at the 2017 CrossFit Foundation Academic Conference 'Diet and Cardiometabolic Health - Beyond Calories', and this paper summarizes the presentations and follow-up discussions. Regarding the health effects of dietary fat, sugar and non-nutritive sweeteners, it is concluded that food-specific saturated fatty acids and sugar-sweetened beverages promote cardiometabolic diseases by mechanisms that are additional to their contribution of calories to positive energy balance and that aspartame does not promote weight gain. The challenges involved in conducting and interpreting clinical nutritional research, which preclude more extensive conclusions, are detailed. Emerging research is presented exploring the possibility that responses to certain dietary components/patterns are influenced by the metabolic status, developmental period or genotype of the individual; by the responsiveness of brain regions associated with reward to food cues; or by the microbiome. More research regarding these potential 'beyond calories' mechanisms may lead to new strategies for attenuating the obesity crisis. © 2018 The Authors. Obesity Reviews published by John Wiley & Sons Ltd on behalf of World Obesity Federation.
Tax Mechanism of Influence on the Financial Component of Russians’ Living Standards

Directory of Open Access Journals (Sweden)

Leyla Akifovna Mytareva

2016-12-01

Full Text Available In a socially-oriented country the development standard is determined by the living standards of population. The article is devoted to a comprehensive presentation of tax mechanism influencing the quality of Russians’ life, based on the interdependence of tax revenue and spending. The article comprehensively presented and explained variable combination of tax techniques and tools, influencing the financial component of the living standard of the population (individuals not engaged in entrepreneurial activities, including: the type and level of tax required and elective elements of the tax, tax residency, tax audits and combating tax evasion. The author presents the elements of tax mechanism of influence on the financial component of the living standards of Russians. As the main indicator for evaluating the impact of the tax mechanism on the living standards, the author proposed the indicator of tax burden, calculated both as the total size and as a structure: the objects of taxation (income, property and indirect taxation and tax levels (Federal, regional and local. The author points to a slight increase in tax burden of the Russians since 2006 and 2015, against a significant growth of the amount of tax paid by them and the amount of cash income; predominance of income and Federal taxes in the structure of tax burden; a slight change in the structure of the tax burden on taxable items and tax rates.
Mechanical characterization of W-armoured plasma-facing components after thermal fatigue

International Nuclear Information System (INIS)

Serret, D; Richou, M; Missirlian, M; Loarer, T

2011-01-01

The future fusion device ITER is aimed at demonstrating the scientific and technical feasibility of fusion power. Tens of thousands of W-armoured plasma-facing components (PFCs) will be installed in the vertical targets of the ITER divertor and subjected to a high heat flux. The purpose of this paper is to present the results of mechanical and microstructural characterization of tungsten PFCs after thermal fatigue tests. On each component, Vickers hardness measurements are made. In parallel, the mean grain diameter in the corresponding zone of tungsten material is determined. The empirical Hall-Petch relation was adapted to experimental data. However, due to the plateau effect on recrystallization hardness, this relation does not seem to be relevant once recrystallization is complete: a new approach is proposed for predicting the margin to the tungsten melting onset.
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
Component simulation in problems of calculated model formation of automatic machine mechanisms

Directory of Open Access Journals (Sweden)

Telegin Igor

2017-01-01

Full Text Available The paper deals with the problems of the component simulation method application in the problems of the automation of the mechanical system model formation with the further possibility of their CAD-realization. The purpose of the investigations mentioned consists in the automation of the CAD-model formation of high-speed mechanisms in automatic machines and in the analysis of dynamic processes occurred in their units taking into account their elasto-inertial properties, power dissipation, gaps in kinematic pairs, friction forces, design and technological loads. As an example in the paper there are considered a formalization of stages in the computer model formation of the cutting mechanism in cold stamping automatic machine AV1818 and methods of for the computation of their parameters on the basis of its solid-state model.
The evolution of social learning mechanisms and cultural phenomena in group foragers.

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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.
Introductory Education for Mechanical Engineering by Exercise in Mechanical Disassembly

Science.gov (United States)

Matsui, Yoshio; Asakawa, Naoki; Iwamori, Satoru

An introductory program “Exercise for engineers in mechanical disassembly” is an exercise that ten students of every team disassemble a motor scooter to the components and then assemble again to the initial form in 15 weeks. The purpose of this program is to introduce mechanical engineering by touching the real machine and learning how it is composed from various mechanical parts to the students at the early period after the entrance into the university. Additional short lectures by young teachers and a special lecture by a top engineer in the industry encourage the students to combine the actual machine and the mechanical engineering subjects. Furthermore, various educations such as group leader system, hazard prediction training, parts filing are included in this program. As a result, students recognize the importance of the mechanical engineering study and the way of group working.
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…

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.
Component Energy Efficiencies in a Novel Linear to Rotary Motion Inter-conversion Hydro-mechanism Running a Solar Tracker

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Kant Eliab Kanyarusoke

2018-01-01

Full Text Available A new mechanism interconverting linear and rotary motion was investigated for energy transfers among its components. It employed a gear-rack set, a Hooke coupling and a specially designed bladder-valve system that regulated the motion. The purpose was to estimate individual component mechanical efficiencies as they existed in the prototype so that future reengineering of the mechanism could be properly targeted. Theoretical modelling of the mechanism was first done to obtain equations for efficiencies of the key components. Two-stage experimentation followed when running a solar tracker. The first stage produced data for inputting into the model to determine the efficiencies’ theoretical variation with the Hooke coupling shaft angle. The second one verified results of the Engineering Equation Solver (EES software solutions of the model. It was found that the energy transfer to focus on was that between the Hooke coupling and the output shaft because its efficiency was below 4%
Concurrence of rule- and similarity-based mechanisms in artificial grammar learning.

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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.
Unsupervised learning of facial expression components

OpenAIRE

Egede, Joy Onyekachukwu

2013-01-01

The face is one of the most important means of non-verbal communication. A lot of information can be gotten about the emotional state of a person just by merely observing their facial expression. This is relatively easy in face to face communication but not so in human computer interaction. Supervised learning has been widely used by researchers to train machines to recognise facial expressions just like humans. However, supervised learning has significant limitations one of which is the fact...
An optimized ensemble local mean decomposition method for fault detection of mechanical components

International Nuclear Information System (INIS)

Zhang, Chao; Chen, Shuai; Wang, Jianguo; Li, Zhixiong; Hu, Chao; Zhang, Xiaogang

2017-01-01

Mechanical transmission systems have been widely adopted in most of industrial applications, and issues related to the maintenance of these systems have attracted considerable attention in the past few decades. The recently developed ensemble local mean decomposition (ELMD) method shows satisfactory performance in fault detection of mechanical components for preventing catastrophic failures and reducing maintenance costs. However, the performance of ELMD often heavily depends on proper selection of its model parameters. To this end, this paper proposes an optimized ensemble local mean decomposition (OELMD) method to determinate an optimum set of ELMD parameters for vibration signal analysis. In OELMD, an error index termed the relative root-mean-square error ( Relative RMSE ) is used to evaluate the decomposition performance of ELMD with a certain amplitude of the added white noise. Once a maximum Relative RMSE , corresponding to an optimal noise amplitude, is determined, OELMD then identifies optimal noise bandwidth and ensemble number based on the Relative RMSE and signal-to-noise ratio (SNR), respectively. Thus, all three critical parameters of ELMD (i.e. noise amplitude and bandwidth, and ensemble number) are optimized by OELMD. The effectiveness of OELMD was evaluated using experimental vibration signals measured from three different mechanical components (i.e. the rolling bearing, gear and diesel engine) under faulty operation conditions. (paper)
An optimized ensemble local mean decomposition method for fault detection of mechanical components

Science.gov (United States)

Zhang, Chao; Li, Zhixiong; Hu, Chao; Chen, Shuai; Wang, Jianguo; Zhang, Xiaogang

2017-03-01

Mechanical transmission systems have been widely adopted in most of industrial applications, and issues related to the maintenance of these systems have attracted considerable attention in the past few decades. The recently developed ensemble local mean decomposition (ELMD) method shows satisfactory performance in fault detection of mechanical components for preventing catastrophic failures and reducing maintenance costs. However, the performance of ELMD often heavily depends on proper selection of its model parameters. To this end, this paper proposes an optimized ensemble local mean decomposition (OELMD) method to determinate an optimum set of ELMD parameters for vibration signal analysis. In OELMD, an error index termed the relative root-mean-square error (Relative RMSE) is used to evaluate the decomposition performance of ELMD with a certain amplitude of the added white noise. Once a maximum Relative RMSE, corresponding to an optimal noise amplitude, is determined, OELMD then identifies optimal noise bandwidth and ensemble number based on the Relative RMSE and signal-to-noise ratio (SNR), respectively. Thus, all three critical parameters of ELMD (i.e. noise amplitude and bandwidth, and ensemble number) are optimized by OELMD. The effectiveness of OELMD was evaluated using experimental vibration signals measured from three different mechanical components (i.e. the rolling bearing, gear and diesel engine) under faulty operation conditions.
DIANA: A Machine Learning Mechanism for Adjusting the TDD Uplink-Downlink Configuration in XG-PON-LTE Systems

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Panagiotis Sarigiannidis

2017-01-01

Full Text Available Modern broadband hybrid optical-wireless access networks have gained the attention of academia and industry due to their strategic advantages (cost-efficiency, huge bandwidth, flexibility, and mobility. At the same time, the proliferation of Software Defined Networking (SDN enables the efficient reconfiguration of the underlying network components dynamically using SDN controllers. Hence, effective traffic-aware schemes are feasible in dynamically determining suitable configuration parameters for advancing the network performance. To this end, a novel machine learning mechanism is proposed for an SDN-enabled hybrid optical-wireless network. The proposed architecture consists of a 10-gigabit-capable passive optical network (XG-PON in the network backhaul and multiple Long Term Evolution (LTE radio access networks in the fronthaul. The proposed mechanism receives traffic-aware knowledge from the SDN controllers and applies an adjustment on the uplink-downlink configuration in the LTE radio communication. This traffic-aware mechanism is capable of determining the most suitable configuration based on the traffic dynamics in the whole hybrid network. The introduced scheme is evaluated in a realistic environment using real traffic traces such as Voice over IP (VoIP, real-time video, and streaming video. According to the obtained numerical results, the proposed mechanism offers significant improvements in the network performance in terms of latency and jitter.
Learning representative features for facial images based on a modified principal component analysis

Science.gov (United States)

Averkin, Anton; Potapov, Alexey

2013-05-01

The paper is devoted to facial image analysis and particularly deals with the problem of automatic evaluation of the attractiveness of human faces. We propose a new approach for automatic construction of feature space based on a modified principal component analysis. Input data sets for the algorithm are the learning data sets of facial images, which are rated by one person. The proposed approach allows one to extract features of the individual subjective face beauty perception and to predict attractiveness values for new facial images, which were not included into a learning data set. The Pearson correlation coefficient between values predicted by our method for new facial images and personal attractiveness estimation values equals to 0.89. This means that the new approach proposed is promising and can be used for predicting subjective face attractiveness values in real systems of the facial images analysis.
Mind and activity. Psychic mechanism of learning

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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
Development of E-learning Software Based Multiplatform Components

OpenAIRE

Salamah, Irma; Ganiardi, M. Aris

2017-01-01

E-learning software is a product of information and communication technology used to help dynamic and flexible learning process between teacher and student. The software technology was first used in the development of e-learning software in the form of web applications. The advantages of this technology because of the ease in the development, installation, and distribution of data. Along with advances in mobile/wireless electronics technology, e-learning software is adapted to this technology...
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
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.
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
Comparison between Two Linear Supervised Learning Machines' Methods with Principle Component Based Methods for the Spectrofluorimetric Determination of Agomelatine and Its Degradants.

Science.gov (United States)

Elkhoudary, Mahmoud M; Naguib, Ibrahim A; Abdel Salam, Randa A; Hadad, Ghada M

2017-05-01

Four accurate, sensitive and reliable stability indicating chemometric methods were developed for the quantitative determination of Agomelatine (AGM) whether in pure form or in pharmaceutical formulations. Two supervised learning machines' methods; linear artificial neural networks (PC-linANN) preceded by principle component analysis and linear support vector regression (linSVR), were compared with two principle component based methods; principle component regression (PCR) as well as partial least squares (PLS) for the spectrofluorimetric determination of AGM and its degradants. The results showed the benefits behind using linear learning machines' methods and the inherent merits of their algorithms in handling overlapped noisy spectral data especially during the challenging determination of AGM alkaline and acidic degradants (DG1 and DG2). Relative mean squared error of prediction (RMSEP) for the proposed models in the determination of AGM were 1.68, 1.72, 0.68 and 0.22 for PCR, PLS, SVR and PC-linANN; respectively. The results showed the superiority of supervised learning machines' methods over principle component based methods. Besides, the results suggested that linANN is the method of choice for determination of components in low amounts with similar overlapped spectra and narrow linearity range. Comparison between the proposed chemometric models and a reported HPLC method revealed the comparable performance and quantification power of the proposed models.
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…
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.
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.
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…
Nacre in Abalone Shell: Organic and Inorganic Components and their effects to the Formation and Mechanical Properties

Science.gov (United States)

Lopez, Maria Isabel

Abalone nacre is a natural composite that exhibits exceptional mechanical properties due to its organization that extends to various levels of hierarchy. Most of the toughness has been attributed by nacre's third level of hierarchy which entitles a brick and mortar structure consisting of the CaCO3 tiles and organic interlayers. However, there are other important components that are vital to the structure and strength of red abalone nacre. The process of formation of red abalone (Haliotis rufescens) nacre following periods of growth interruption, taking into consideration important environmental factors (access to food and temperature) and to employ high-magnification characterization techniques (scanning electron microscopy and transmission electron microscopy) to better understand how the soft tissue (e.g. epithelium and organic membrane) influences the mechanism of growth. The structure-property relationship of red abalone (Haliotis rufescens) nacre, focusing in the individual constituents (isolated mineral and isolated organic component) and comparing that to the integrated structure. Mechanical tests such as, tensile tests, microscratch, and nanoindentation is performed on the isolated organic constituent and the isolated mineral of red abalone shell. Specimens are characterized by SEM to verify the toughening and deformation mechanisms. Results obtained from the isolated mineral validate the importance of the organic constituent as the mechanical properties decline greatly as the organic component is removed. This approach forms a general picture of the mechanical response of the organic interlayers and growth bands and their effect on the toughness of the abalone nacre. These results are significant to understand the important characteristics of abalone nacre, such as the structure and mechanical properties, and an attempt to aid in improving the latest attempts to produce novel nacre-inspired materials.
Reliability-based optimization of maintenance scheduling of mechanical components under fatigue

Science.gov (United States)

Beaurepaire, P.; Valdebenito, M.A.; Schuëller, G.I.; Jensen, H.A.

2012-01-01

This study presents the optimization of the maintenance scheduling of mechanical components under fatigue loading. The cracks of damaged structures may be detected during non-destructive inspection and subsequently repaired. Fatigue crack initiation and growth show inherent variability, and as well the outcome of inspection activities. The problem is addressed under the framework of reliability based optimization. The initiation and propagation of fatigue cracks are efficiently modeled using cohesive zone elements. The applicability of the method is demonstrated by a numerical example, which involves a plate with two holes subject to alternating stress. PMID:23564979

Formation Mechanism of Magnesium Ammonium Phosphate Stones: A Component Analysis of Urinary Nanocrystallites

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Xin-Yuan Sun

2015-01-01

Full Text Available The components of urinary nanocrystallites in patients with magnesium ammonium phosphate (MAP stones were analyzed by X-ray diffraction (XRD, Fourier-transform infrared (FT-IR spectrometer, high-resolution transmission electron microscopy (HRTEM, selected area electron diffraction (SAED, fast Fourier transformation (FFT, and energy-dispersive X-ray spectroscopy (EDS. The main components of the stones were MAP hexahydrate (MAP·6H2O, magnesium hydrogen phosphate trihydrate (MgHPO4·3H2O, and a small amount of calcium phosphate (CaP, while the main components of urinary nanocrystallites were MgHPO4·3H2O, CaP, and MAP monohydrate (MAP·H2O. MAP·H2O induced the formation of MAP stones as seed crystals. MgHPO4·3H2O was accompanied by the appearance of MAP·6H2O. The formation mechanism of MAP stones and influencing factors were discussed on the basis of the components of urine nanocrystallites. A model diagram of MAP stone formation was also put forward based on the results. Formation of MAP stones was closely related to the presence of high amounts of MAP crystallites in urine. Urinary crystallite condition and changes in urine components could indicate the activity of stone diseases.
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%.
Recognition of Prior Learning as an integral component of ...

African Journals Online (AJOL)

This is irrespective of whether that learning has been acquired through unstructured learning, performance development, off-the-job assessment, or skills and knowledge that meet workplace needs but have been gained through various previous learning experiences. The concept Recognition of Prior Learning (RPL) is ...
An empirical investigation on the effects of spiritual leadership components on organizational learning capacity: A case study of Payame Noor University

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Amir Hossein

2013-06-01

Full Text Available This paper presents an empirical investigation on the effects of spiritual leadership components on organizational learning capacity for a case study of Payame Noor University, Iran. The proposed study uses a standard questionnaire for measuring spirituality leadership proposed by Fry (2003 [Fry, L. W. (2003. Toward a theory of spiritual leadership. The leadership quarterly, 14(6, 693-727.] and for measuring the impact of organizational learning capacity, the proposed study uses another questionnaire proposed by Teo et al. (2006 [Teo, H. H., Wang, X., Wei, K. K., Sia, C. L., & Lee, M. K. (2006. Organizational learning capacity and attitude toward complex technological innovations: an empirical study. Journal of the American Society for Information Science and Technology, 57(2, 264-279.]. The results of our survey have indicated that all components of spiritual leadership, except love and altruism as meaningful, influence spirituality leadership, significantly.
Qualification methodologies for mechanical component, I and C, piping using test lab

International Nuclear Information System (INIS)

Ichikawa, Toshio

2001-01-01

There are many methods of verifying the intensity of a structure, a function, a vibration characteristics, etc. The seismic test which verifies the function during the earthquake of a components simple substance (seismic test which checks durability according to components types). How to verify the analysis technique by the scale model and to check the intensity of plant operating conditions by the scale model results. The model of the same size as the actual plant is created and there is a method of verifying intensity and the function directly. A seismic test is restrained by the frequency of an evaluation objective, and the capability of actuator equipment, and is carried out. Moreover, otherwise, restrictions are the size of a table, actuation power, environment, etc. Here, further examples are introduced, such as evaluation by the examination that combined analysis, experimental test use and analysis, and the experimental test, and the method of proving only by test, and have the seismic check method by test learned in this lecture. Typical examples are explained. Based on the seismic test result carried out with experimental research equipment, how to verify that the required function to components, such as a structure of reactor internals, is maintained at the time of an earthquake is explained. In this case, differences of the simulation environment of the model in. a test, earthquake conditions simulated by shaker table of test conditions and actual plant conditions are important for the evaluation method determination. In nuclear equipment, there is what is required to achieve the static function to hold pressure boundary to the high temperature inside apparatus piping - high-pressure flow, and dynamic functions, such as insertion of a valve, a pump, and a control rod. Moreover, in order to maintain and carry out the safe stop of the safe operation, there is I and C for controlling - supervising these components. In order for this functional maintenance
Beliefs on Learning and Teaching Language Components: The Case of Iranian EAP and EFL Learners

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Gholamreza Parsi

2017-06-01

Full Text Available The present study intended to investigate the possible difference between EAP and EFL learners’ beliefs concerning learning and teaching of language components, namely, vocabulary, pronunciation and grammar. Furthermore, this study examined the association between EAP and EFL learners’ beliefs and their language components’ development. To this end, 231 undergraduate EAP (117 and EFL (114 learners at Ferdowsi University took part in the study by completing a five-point Likert scale questionnaire adapted from Simon and Taverniers (2011. The face and content validity of the questionnaire was confirmed by the experts’ judgment and factor analysis. Moreover using Cronbach alpha coefficient the questionnaire was found acceptably reliable (α=0.88. Furthermore, for language components’ development, the EAP learners’ scores in English course and EFL learners’ average scores in their Basic English courses were taken into account. The results of an Independent Samples t-test revealed that there existed a statistically significant difference between EAP and EFL learners’ beliefs on learning and teaching language components. Furthermore, the results of Pearson correlation coefficients indicated a statistically significant positive association between EFL learners’ beliefs and their language components’ development, however no statistically significant correlation was found between EAP learners’ beliefs and their language components’ development.
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.
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…
Statistical mechanics of a one-component fluid of charged hard rods in 1D

International Nuclear Information System (INIS)

Vericat, F.; Blum, L.

1986-09-01

The statistical mechanics of a classical one component system of charged hard rods in a neutralizing background is investigated in 1D stressing on the effects of the hard core interactions over the thermodynamic and the structure of the system. The crystalline status of the system at all temperatures and densities and the absence of phase transitions is shown by extending previous results of Baxter and Kunz on the one-component plasma of point particles. Explicit expressions for the thermodynamic functions and the one-particle correlation function are given in the limits of small and strong couplings. (author)
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…
Theoretical physics 2 analytical mechanics

CERN Document Server

Nolting, Wolfgang

2016-01-01

This textbook offers a clear and comprehensive introduction to analytical mechanics, one of the core components of undergraduate physics courses.It follows on naturally from the previous volumes in this series, thus expanding the knowledge in classical mechanics. The book starts with a thorough introduction into Lagrangian mechanics, detailing the d’Alembert principle, Hamilton’s principle and conservation laws. It continues with an in-depth explanation of Hamiltonian mechanics, illustrated by canonical and Legendre transformation, the generalization to quantum mechanics through Poisson brackets and all relevant variational principles. Finally, the Hamilton-Jacobi theory and the transition to wave mechanics are presented in detail. Ideally suited to undergraduate students with some grounding in classical mechanics, the book is enhanced throughout with learning features such as boxed inserts and chapter summaries, with key mathematical derivations highlighted to aid understanding. The text is supported by ...
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.
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.
The puzzle of the 1996 Bárdarbunga, Iceland, earthquake: no volumetric component in the source mechanism

Science.gov (United States)

Tkalcic, Hrvoje; Dreger, Douglas S.; Foulger, Gillian R.; Julian, Bruce R.

2009-01-01

A volcanic earthquake with Mw 5.6 occurred beneath the Bárdarbunga caldera in Iceland on 29 September 1996. This earthquake is one of a decade-long sequence of events at Bárdarbunga with non-double-couple mechanisms in the Global Centroid Moment Tensor catalog. Fortunately, it was recorded well by the regional-scale Iceland Hotspot Project seismic experiment. We investigated the event with a complete moment tensor inversion method using regional long-period seismic waveforms and a composite structural model. The moment tensor inversion using data from stations of the Iceland Hotspot Project yields a non-double-couple solution with a 67% vertically oriented compensated linear vector dipole component, a 32% double-couple component, and a statistically insignificant (2%) volumetric (isotropic) contraction. This indicates the absence of a net volumetric component, which is puzzling in the case of a large volcanic earthquake that apparently is not explained by shear slip on a planar fault. A possible volcanic mechanism that can produce an earthquake without a volumetric component involves two offset sources with similar but opposite volume changes. We show that although such a model cannot be ruled out, the circumstances under which it could happen are rare.
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.
Coagulation mechanism of salt solution-extracted active component in Moringa oleifera seeds

OpenAIRE

Okuda, Tetsuji; Baes, Aloysius U.; Nishijima, Wataru; Okada, Mitsumasa

2001-01-01

This study focuses on the coagulation mechanism by the purified coagulant solution (MOC-SC-PC) with the coagulation active component extracted from M. oleifera seeds using salt solution. The addition of MOC-SC-PC into tap water formed insoluble matters. The formation was responsible for kaolin coagulation. On the other hand, insoluble matters were not formed when the MOC-SC-PC was added into distilled water. The formation was affected by Ca2+ or other bivalent cations which may connect each m...
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.
Modeling learning and memory using verbal learning tests: results from ACTIVE.

Science.gov (United States)

Gross, Alden L; Rebok, George W; Brandt, Jason; Tommet, Doug; Marsiske, Michael; Jones, Richard N

2013-03-01

To investigate the influence of memory training on initial recall and learning. The Advanced Cognitive Training for Independent and Vital Elderly study of community-dwelling adults older than age 65 (n = 1,401). We decomposed trial-level recall in the Auditory Verbal Learning Test (AVLT) and Hopkins Verbal Learning Test (HVLT) into initial recall and learning across trials using latent growth models. Trial-level increases in words recalled in the AVLT and HVLT at each follow-up visit followed an approximately logarithmic shape. Over the 5-year study period, memory training was associated with slower decline in Trial 1 AVLT recall (Cohen's d = 0.35, p = .03) and steep pre- and posttraining acceleration in learning (d = 1.56, p learning, d = 3.10, p memory-trained group had a higher level of recall than the control group through the end of the 5-year study period despite faster decline in learning. This study contributes to the understanding of the mechanisms by which training benefits memory and expands current knowledge by reporting long-term changes in initial recall and learning, as measured from growth models and by characterization of the impact of memory training on these components. Results reveal that memory training delays the worsening of memory span and boosts learning.
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.
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.

The Role and Mechanisms of Action of Glucocorticoid Involvement in Memory Storage

Science.gov (United States)

Sandi, Carmen

1998-01-01

Adrenal steroid hormones modulate learning and memory processes by interacting with specific glucocorticoid receptors at different brain areas. In this article, certain components of the physiological response to stress elicited by learning situations are proposed to form an integral aspect of the neurobiological mechanism underlying memory formation. By reviewing the work carried out in different learning models in chicks (passive avoidance learning) and rats (spatial orientation in the Morris water maze and contextual fear conditioning), a role for brain corticosterone action through the glucocorticoid receptor type on the mechanisms of memory consolidation is hypothesized. Evidence is also presented to relate post-training corticosterone levels to the strength of memory storage. Finally, the possible molecular mechanisms that might mediate the influences of glucocorticoids in synaptic plasticity subserving long-term memory formation are considered, mainly by focusing on studies implicating a steroid action through (i) glutamatergic transmission and (ii) cell adhesion molecules. PMID:9920681
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.
On-line Learning of Prototypes and Principal Components

NARCIS (Netherlands)

Biehl, M.; Freking, A.; Hölzer, M.; Reents, G.; Schlösser, E.; Saad, David

1998-01-01

We review our recent investigation of on-line unsupervised learning from high-dimensional structured data. First, on-line competitive learning is studied as a method for the identification of prototype vectors from overlapping clusters of examples. Specifically, we analyse the dynamics of the
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…
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.
Evolution of JAK-STAT pathway components: mechanisms and role in immune system development.

Directory of Open Access Journals (Sweden)

Clifford Liongue

Full Text Available BACKGROUND: Lying downstream of a myriad of cytokine receptors, the Janus kinase (JAK-Signal transducer and activator of transcription (STAT pathway is pivotal for the development and function of the immune system, with additional important roles in other biological systems. To gain further insight into immune system evolution, we have performed a comprehensive bioinformatic analysis of the JAK-STAT pathway components, including the key negative regulators of this pathway, the SH2-domain containing tyrosine phosphatase (SHP, Protein inhibitors against Stats (PIAS, and Suppressor of cytokine signaling (SOCS proteins across a diverse range of organisms. RESULTS: Our analysis has demonstrated significant expansion of JAK-STAT pathway components co-incident with the emergence of adaptive immunity, with whole genome duplication being the principal mechanism for generating this additional diversity. In contrast, expansion of upstream cytokine receptors appears to be a pivotal driver for the differential diversification of specific pathway components. CONCLUSION: Diversification of JAK-STAT pathway components during early vertebrate development occurred concurrently with a major expansion of upstream cytokine receptors and two rounds of whole genome duplications. This produced an intricate cell-cell communication system that has made a significant contribution to the evolution of the immune system, particularly the emergence of adaptive immunity.
Integrity evaluation of power plant components by fracture mechanics and related techniques

International Nuclear Information System (INIS)

Mukherjee, B.; Vanderglas, M.L.; Davies, P.H.

1982-01-01

Power plant components can be subject to unexpected failures with serious consequences, unless careful attention is paid to minute crack defects and their possible growth. The Linear Elastic Fracture Mechanics approach to structural integrity evaluation, as it appears in the ASME Code, is discussed. Projects related to material data generation and the development of structural analysis methods to make the above method usable are described. Several integrity-related questions outside the scope of the Code guidelines are documented, concluding with comments on possible future developments
Components of Self-Regulated Learning; Implications for School Performance

Science.gov (United States)

Mih, Codruta; Mih, Viorel

2010-01-01

Self-regulated school learning behavior includes the activation of a relatively large number of psychological dimensions. Among the most important self-regulation constructs that influence school learning are: learning goals, personal self-efficacy, metacognition and test-anxiety. The adaptive functioning of these is associated with high…
RSE-M: In-Service Inspection Rules for Mechanical Components of PWR Nuclear Islands

International Nuclear Information System (INIS)

2016-01-01

The RSE-M code defines in-service inspection operations. It applies to pressure equipment used in PWR plants, as well as spare parts for such equipment. The RSE-M code does not apply to equipment made from materials other than metal. It is based on the RCC-M code for requirements relating to the design and fabrication of mechanical components. Use: The inspection rules specified in the RSE-M code describe the standard requirements of best practice within the French nuclear industry, based on its own feedback from operating several nuclear units and partly supplemented with requirements stipulated by French regulations. To date, the 58 units in France's nuclear infrastructure enforce the in-service inspection rules of the RSE-M code. Operation of 30 commissioned units in China's nuclear infrastructure, corresponding to the M310, CPR-1000 and CPR-600 reactors, is based on the RSE-M code (since 2007, use of AFCEN codes has been required by NNSA for Generation II+ reactors). Contents of the 2016 Edition: Volume I - Rules: Section A - General rules, Section B - Specific rules for class 1 components, Section C - Specific rules for class 2 or 3 components, Section D - Specific rules for components not assigned to any particular RSE-M class; Volume II - Appendices 1 to 8: Appendices 1.0 to 1.9: supporting appendices for the general requirements, Appendix 2.1: appendix associated with chap. 2000 Requalifications, Hydraulic Proof Tests and Hydraulic Tests, Appendices 4.1 to 4.4: appendices associated with chap. 4000 Examination techniques, Appendices 5.1 to 5.8 and RPP2: appendices associated with chap. 5000 Mechanical and Materials, Appendices 8.1 to 8.2: appendices associated with chap. 8000 Maintenance Operations; Volume III: Appendix 3.1 - Visit tables: main primary and secondary systems, EPR pre-service inspection program, Class 2 or 3 vessels; Appendix 3.2 - Inspection Plans For Non-Nuclear Pressure Equipment
Mechanical Behaviour of Inconel 718 Thin-Walled Laser Welded Components for Aircraft Engines

Directory of Open Access Journals (Sweden)

Enrico Lertora

2014-01-01

Full Text Available Nickel alloys are very important in many aerospace applications, especially to manufacture gas turbines and aero engine components, where high strength and temperature resistance are necessary. These kinds of alloys have to be welded with high energy density processes, in order to preserve their high mechanical properties. In this work, CO2 laser overlap joints between Inconel 718 sheets of limited thickness in the absence of postweld heat treatment were made. The main application of this kind of joint is the manufacturing of a helicopter engine component. In particular the aim was to obtain a specific cross section geometry, necessary to overcome the mechanical stresses found in these working conditions without failure. Static and dynamic tests were performed to assess the welds and the parent material fatigue life behaviour. Furthermore, the life trend was identified. This research pointed out that a full joint shape control is possible by choosing proper welding parameters and that the laser beam process allows the maintenance of high tensile strength and ductility of Inconel 718 but caused many liquation microcracks in the heat affected zone (HAZ. In spite of these microcracks, the fatigue behaviour of the overlap welds complies with the technical specifications required by the application.
Understanding deformation mechanisms during powder compaction using principal component analysis of compression data.

Science.gov (United States)

Roopwani, Rahul; Buckner, Ira S

2011-10-14

Principal component analysis (PCA) was applied to pharmaceutical powder compaction. A solid fraction parameter (SF(c/d)) and a mechanical work parameter (W(c/d)) representing irreversible compression behavior were determined as functions of applied load. Multivariate analysis of the compression data was carried out using PCA. The first principal component (PC1) showed loadings for the solid fraction and work values that agreed with changes in the relative significance of plastic deformation to consolidation at different pressures. The PC1 scores showed the same rank order as the relative plasticity ranking derived from the literature for common pharmaceutical materials. The utility of PC1 in understanding deformation was extended to binary mixtures using a subset of the original materials. Combinations of brittle and plastic materials were characterized using the PCA method. The relationships between PC1 scores and the weight fractions of the mixtures were typically linear showing ideal mixing in their deformation behaviors. The mixture consisting of two plastic materials was the only combination to show a consistent positive deviation from ideality. The application of PCA to solid fraction and mechanical work data appears to be an effective means of predicting deformation behavior during compaction of simple powder mixtures. Copyright © 2011 Elsevier B.V. All rights reserved.
When in Rome ... Learn why the Romans do what they do: how multicultural learning experiences facilitate creativity.

Science.gov (United States)

Maddux, William W; Adam, Hajo; Galinsky, Adam D

2010-06-01

Research suggests that living in and adapting to foreign cultures facilitates creativity. The current research investigated whether one aspect of the adaptation process-multicultural learning-is a critical component of increased creativity. Experiments 1-3 found that recalling a multicultural learning experience: (a) facilitates idea flexibility (e.g., the ability to solve problems in multiple ways), (b) increases awareness of underlying connections and associations, and (c) helps overcome functional fixedness. Importantly, Experiments 2 and 3 specifically demonstrated that functional learning in a multicultural context (i.e., learning about the underlying meaning or function of behaviors in that context) is particularly important for facilitating creativity. Results showed that creativity was enhanced only when participants recalled a functional multicultural learning experience and only when participants had previously lived abroad. Overall, multicultural learning appears to be an important mechanism by which foreign living experiences lead to creative enhancement.
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…
The E-Learning Component of a Blended Learning Course

Science.gov (United States)

Olejarczuk, Edyta

2014-01-01

Using new technologies in the academic field has become more and more visible in Poland in the recent years. In the past, digital learning resources were used as supplementary materials helping to support face-to-face instruction. Nowadays, we have the opportunity not only to apply "traditional" methods but also to use more sophisticated…
Reactor component automatic grapple

International Nuclear Information System (INIS)

Greenaway, P.R.

1982-01-01

A grapple for handling nuclear reactor components in a medium such as liquid sodium which, upon proper seating and alignment of the grapple with the component as sensed by a mechanical logic integral to the grapple, automatically seizes the component. The mechanical logic system also precludes seizure in the absence of proper seating and alignment. (author)
Interaction effects between internal governance mechanisms on the components of initial returns during the IPO

Directory of Open Access Journals (Sweden)

Mediha Mezhoud

2012-12-01

Full Text Available Our work provides an analysis of the interaction effects between internal governance mechanisms on the components of initial returns during the listing period. The application of multivariate regressions on a sample of 110 IPO French companies during 2005-2010, has allowed us to conclude that the different interactions between these mechanisms significantly influence the level of under / overpricing. Indeed, the positive relationship between internal governance mechanisms and overpricing reflects a substitutability relationship. In contrast, the complementarity effect comes from the negative relationship characterizing the combination of governance mechanisms and the underpricing. Thus, the interactions effects between institutional ownership, board structure and under / overpricing are not conforming to the existence of a complementarity or substitutability relationship between these variables given the absence of a significant combination between these variables
Reversal Learning in Humans and Gerbils: Dynamic Control Network Facilitates Learning.

Science.gov (United States)

Jarvers, Christian; Brosch, Tobias; Brechmann, André; Woldeit, Marie L; Schulz, Andreas L; Ohl, Frank W; Lommerzheim, Marcel; Neumann, Heiko

2016-01-01

Biologically plausible modeling of behavioral reinforcement learning tasks has seen great improvements over the past decades. Less work has been dedicated to tasks involving contingency reversals, i.e., tasks in which the original behavioral goal is reversed one or multiple times. The ability to adjust to such reversals is a key element of behavioral flexibility. Here, we investigate the neural mechanisms underlying contingency-reversal tasks. We first conduct experiments with humans and gerbils to demonstrate memory effects, including multiple reversals in which subjects (humans and animals) show a faster learning rate when a previously learned contingency re-appears. Motivated by recurrent mechanisms of learning and memory for object categories, we propose a network architecture which involves reinforcement learning to steer an orienting system that monitors the success in reward acquisition. We suggest that a model sensory system provides feature representations which are further processed by category-related subnetworks which constitute a neural analog of expert networks. Categories are selected dynamically in a competitive field and predict the expected reward. Learning occurs in sequentialized phases to selectively focus the weight adaptation to synapses in the hierarchical network and modulate their weight changes by a global modulator signal. The orienting subsystem itself learns to bias the competition in the presence of continuous monotonic reward accumulation. In case of sudden changes in the discrepancy of predicted and acquired reward the activated motor category can be switched. We suggest that this subsystem is composed of a hierarchically organized network of dis-inhibitory mechanisms, dubbed a dynamic control network (DCN), which resembles components of the basal ganglia. The DCN selectively activates an expert network, corresponding to the current behavioral strategy. The trace of the accumulated reward is monitored such that large sudden
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.
Damping Oriented Design of Thin-Walled Mechanical Components by Means of Multi-Layer Coating Technology

Directory of Open Access Journals (Sweden)

Giuseppe Catania

2018-02-01

Full Text Available The damping behaviour of multi-layer composite mechanical components, shown by recent research and application papers, is analyzed. A local dissipation mechanism, acting at the interface between any two different layers of the composite component, is taken into account, and a beam model, to be used for validating the known experimental results, is proposed. Multi-layer prismatic beams, consisting of a metal substrate and of some thin coated layers exhibiting variable stiffness and adherence properties, are considered in order to make it possible to study and validate this assumption. A dynamical model, based on a simple beam geometry but taking into account the previously introduced local dissipation mechanism and distributed visco-elastic constraints, is proposed. Some different application examples of specific multi-layer beams are considered, and some numerical examples concerning the beam free and forced response are described. The influence of the multilayer system parameters on the damping behaviour of the free and forced response of the composite beam is investigated by means of the definition of some damping estimators. Some effective multi-coating configurations, giving a relevant increase of the damping estimators of the coated structure with respect to the same uncoated structure, are obtained from the model simulation, and the results are critically discussed.
Bone-femoral component interface gap after sagittal mechanical axis alignment is filled with new bone after cementless total knee arthroplasty.

Science.gov (United States)

Kuriyama, Shinichi; Hyakuna, Katsufumi; Inoue, Satoshi; Kawai, Yasutsugu; Tamaki, Yasuyuki; Ito, Hiromu; Matsuda, Shuichi

2018-05-01

This study retrospectively evaluated the fate of mismatch between an uncemented femoral component and each femoral cut surface (i.e., wedge-shaped gap) relative to sagittal mechanical alignment in total knee arthroplasty (TKA). Primary TKA was performed on 99 consecutive knees. The femoral components were aligned to the sagittal mechanical axis with CT-based navigation. All patients were assessed with postoperative true lateral radiographs. Bone-side surfaces of the uncemented femoral component were divided into five zones: anterior flange, anterior chamfer, posterior chamfer, posterior part, and distal part, which were defined as zones 1 to 5, respectively. Bone filling of wedge-shaped gaps in each zone was evaluated after 1 year. Femoral anterior notching did not occur. However, wedge-shaped gaps were observed in at least one zone in 23 of 99 knees (23%), most frequently in zone 5 (18%). There were 9 and 7 gaps in zones 1 and 2, respectively. The femoral component showed malpositioning of approximately 3° of flexion in cases with wedge-shaped gaps in zones 2 and/or 5. After one year, 67% (6/9) of zone 1, 100% (7/7) of zone 2, and 94% (17/18) of zone 5 wedge-shaped gaps were filled in with new bone. Femoral alignment relative to sagittal mechanical axis caused wedge-shaped gaps due to unstable anterior bone cutting through hard bone, but the small gaps were not clinically significant and filled in within one year. Sagittal setting of the femoral component should aim for the anatomical axis rather than the mechanical axis. IV.

Effect of the weld joint configuration on stressed components, residual stresses and mechanical properties

Energy Technology Data Exchange (ETDEWEB)

Cevik, Bekir; Oezer, Alpay; Oezcatalbas, Yusuf [Gazi Univ., Ankara (Turkey)

2014-03-01

The effect of the weld joint configuration on components has been studied, which are under service loads, under repair or construction and the residual stresses as well as the mechanical properties of the joint have been determined. For this purpose, a horizontal positioned tensile testing device and a semi-automatic MIG welding machine have been used and then the weld joints of the plates were subjected to different elastic stresses. When the temperature of the joined elements decreased to room temperature, applied elastic stresses were released. By this means, the effects of the existing tensile stresses in the joined parts and the tensile stresses created by the welding processes were investigated. The tensile stresses occurring in the joined elements were determined by using the photo-elasticity analysis method and the hole-drilling method. Also, tensile-shear tests were applied in order to determine the effect of permanent tensile loads on the mechanical properties of the joint. Experimental results showed that the application of corner welded lap joints for components under tensile loading significantly decrease the shear strength and yielding capacities of the joint. (orig.)
Independent component analysis: recent advances

OpenAIRE

Hyv?rinen, Aapo

2013-01-01

Independent component analysis is a probabilistic method for learning a linear transform of a random vector. The goal is to find components that are maximally independent and non-Gaussian (non-normal). Its fundamental difference to classical multi-variate statistical methods is in the assumption of non-Gaussianity, which enables the identification of original, underlying components, in contrast to classical methods. The basic theory of independent component analysis was mainly developed in th...
Maze learning by a hybrid brain-computer system.

Science.gov (United States)

Wu, Zhaohui; Zheng, Nenggan; Zhang, Shaowu; Zheng, Xiaoxiang; Gao, Liqiang; Su, Lijuan

2016-09-13

The combination of biological and artificial intelligence is particularly driven by two major strands of research: one involves the control of mechanical, usually prosthetic, devices by conscious biological subjects, whereas the other involves the control of animal behaviour by stimulating nervous systems electrically or optically. However, to our knowledge, no study has demonstrated that spatial learning in a computer-based system can affect the learning and decision making behaviour of the biological component, namely a rat, when these two types of intelligence are wired together to form a new intelligent entity. Here, we show how rule operations conducted by computing components contribute to a novel hybrid brain-computer system, i.e., ratbots, exhibit superior learning abilities in a maze learning task, even when their vision and whisker sensation were blocked. We anticipate that our study will encourage other researchers to investigate combinations of various rule operations and other artificial intelligence algorithms with the learning and memory processes of organic brains to develop more powerful cyborg intelligence systems. Our results potentially have profound implications for a variety of applications in intelligent systems and neural rehabilitation.
Maze learning by a hybrid brain-computer system

Science.gov (United States)

Wu, Zhaohui; Zheng, Nenggan; Zhang, Shaowu; Zheng, Xiaoxiang; Gao, Liqiang; Su, Lijuan

2016-09-01

The combination of biological and artificial intelligence is particularly driven by two major strands of research: one involves the control of mechanical, usually prosthetic, devices by conscious biological subjects, whereas the other involves the control of animal behaviour by stimulating nervous systems electrically or optically. However, to our knowledge, no study has demonstrated that spatial learning in a computer-based system can affect the learning and decision making behaviour of the biological component, namely a rat, when these two types of intelligence are wired together to form a new intelligent entity. Here, we show how rule operations conducted by computing components contribute to a novel hybrid brain-computer system, i.e., ratbots, exhibit superior learning abilities in a maze learning task, even when their vision and whisker sensation were blocked. We anticipate that our study will encourage other researchers to investigate combinations of various rule operations and other artificial intelligence algorithms with the learning and memory processes of organic brains to develop more powerful cyborg intelligence systems. Our results potentially have profound implications for a variety of applications in intelligent systems and neural rehabilitation.
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.…
Application of probabilistic fracture mechanics to the reliability analysis of pressure-bearing reactor components

International Nuclear Information System (INIS)

Schmitt, W.; Roehrich, E.; Wellein, R.

1977-01-01

Since no failures in the primary reactor components have been reported so far, it is impossible to estimate the failure probability of those components just by means of statistics. Therefore the way of probabilistic fracture mechanics has been proposed. Here the material properties, the loads and the crack distributions are treated as statistical variables with certain distributions. From the distributions of these data probability density functions can be established for the loading of a component (e.g. the stress intensity factor) as well as for the resistance of this component (e.g. the fracture toughness). From these functions the failure probability for a given failure mode (e.g. brittle fracture) is easily obtained either by the application of direct integration procedures which are shortly reviewed here, or by the use of Monte Carlo techniques. The most important part of the concept is the collection of a sufficiently large amount of raw data from different sources (departments within the company or external). These data need to be processed so that they can be transformed into probability density functions. The method of data collection and processing in terms of histograms, plots of probability density functions etc, is described. The choice of the various types of distribution functions is discussed. As an example the derivation of the probability density function for cracks of a given size in a component is presented. (Auth.)
The Component Operational Experience Degradation and Ageing Program (CODAP). Review and lessons learned (2011-2014)

International Nuclear Information System (INIS)

Dragea, Tudor; Riznic, Jovica R.

2015-01-01

The structural integrity of piping systems is crucial to continuous and safe operation of nuclear power plants. Across all designs, the pressure boundary and its related piping and components, form one of the many levels of defense in the continuous and safe operation of a nuclear power plant. It is therefore necessary to identify, understand, evaluate and catalogue all of the various degradation mechanisms and failures that affect various piping systems and components across all nuclear power plants (NPP's). This need was first recognized in 1994 by the Swedish Nuclear Power Inspectorate (SKI) which launched a five-year Research and Development (R and D) project to explore the viability of creating an international pipe failure database (SKI-PIPE) (Riznic, 2007). The project was considered to be very successful and in 2002, the Organization for Economic Co-operation and Development (OECD) Pipe Failure Data Exchange (OPDE) was created. OPDE was operated under the umbrella of the OECD Nuclear Energy Agency (NEA) and was created in order to produce an international database on the piping service experience applicable to commercial nuclear power plants. After the successful completion of OPDE, the OECD, as well as other international members, agreed to participate in OPDE's successor: the Component Operational Experience Degradation and Ageing Program (CODAP). The objective of CODAP is to collect information on all possible events related to the failure and degradation of passive metallic components in NPP's. With CODAP winding down to the completion of its first phase in December 2014, this report will focus on the conclusions and the lessons learned throughout the many years of CODAP's implementation. There are currently 14 countries participating in CODAP, many of whom are industry leaders (France, Canada, U.S.A., Germany, Japan, Korea etc.). This cooperation on an international scale provides a library of OPerational EXperience (OPEX) for all participating NPP
Associative learning and animal cognition.

Science.gov (United States)

Dickinson, Anthony

2012-10-05

Associative learning plays a variety of roles in the study of animal cognition from a core theoretical component to a null hypothesis against which the contribution of cognitive processes is assessed. Two developments in contemporary associative learning have enhanced its relevance to animal cognition. The first concerns the role of associatively activated representations, whereas the second is the development of hybrid theories in which learning is determined by prediction errors, both directly and indirectly through associability processes. However, it remains unclear whether these developments allow associative theory to capture the psychological rationality of cognition. I argue that embodying associative processes within specific processing architectures provides mechanisms that can mediate psychological rationality and illustrate such embodiment by discussing the relationship between practical reasoning and the associative-cybernetic model of goal-directed action.
The PCA learning effect: An emerging correlate of face memory during childhood.

Science.gov (United States)

Gao, Xiaoqing; Maurer, Daphne; Wilson, Hugh R

2015-10-01

Human adults implicitly learn the prototype and the principal components of the variability distinguishing faces (Gao & Wilson, 2014). Here we measured the implicit learning effect in adults and 9-year-olds, and with a modified child-friendly procedure, in 7-year-olds. All age groups showed the implicit learning effect by falsely recognizing the average (the prototype effect) and the principal component faces as having been seen (the PCA learning effect). The PCA learning effect, but not the prototype effect increased between 9years of age and adulthood and at both ages was the better predictor of memory for the actually studied faces. In contrast, for the 7-year-olds, the better predictor of face memory was the prototype effect. The pattern suggests that there may be a developmental change between ages 7 and 9 in the mechanism underlying memory for faces. We provide the first evidence that children as young as age 7 can extract the most important dimensions of variation represented by principal components among individual faces, a key ability that grows stronger with age and comes to underlie memory for faces. Copyright © 2015 Elsevier B.V. All rights reserved.
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…
Lessons learned from fatique failures in major FWR components

International Nuclear Information System (INIS)

Ware, A.G.; Shah, V.N.

1992-01-01

This paper evaluates the field fatigue failure experience and describes the lessons learned that can be employed in managing fatigue damage at the sites of these failures and at other susceptible sites. Fatigue damage has resulted in cracks on the inside surfaces of vessels and piping, and in some cases, through-wall cracks resulting in coolant leakage. All of the fatigue failures resulted from conditions or stressors that were not accounted for in the original design analyses. In some cases, it has proven difficult to discover fatigue cracks using conventional inservice inspection methods; several cracks were detected because of leakage. Supplementary monitoring and inspection techniques such as fatigue monitoring, acoustic emission monitoring, and time-of-flight-diffraction ultrasonic testing can be used to assist in identifying susceptible sites, estimating crack growth, and sizing existing fatigue cracks. It is important to identify the root cause of failures because once the stressors and degradation mechanisms are known, changes in operating procedures and designs can be implemented to mitigate future fatigue damage
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...
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.)
The complementary roles of fracture mechanics and non-destructive examination in the safety assessment of components

International Nuclear Information System (INIS)

1988-01-01

This document presents the various speeches of the workshop of the Committee on Safety of Nuclear Installations (CSNI) that took place in Wuerenligen, Switzerland, in October 1988. The speeches deal with the roles of Non-Destructive Examination (NDE) and Fracture Mechanics (FM) in the safety assessment of reactor components, such as pressure vessels. Some calibration standards and reference values of defects are presented, and several NDE and FM methods for the assessment of components are described. Separate abstracts were prepared for all the papers in this volume. (TEC)
The complementary roles of fracture mechanics and non-destructive examination in the safety assessment of components

Energy Technology Data Exchange (ETDEWEB)

NONE

1988-12-31

This document presents the various speeches of the workshop of the Committee on Safety of Nuclear Installations (CSNI) that took place in Wuerenligen, Switzerland, in October 1988. The speeches deal with the roles of Non-Destructive Examination (NDE) and Fracture Mechanics (FM) in the safety assessment of reactor components, such as pressure vessels. Some calibration standards and reference values of defects are presented, and several NDE and FM methods for the assessment of components are described. Separate abstracts were prepared for all the papers in this volume. (TEC).
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.
Classification of structural component and degradation mechanisms for containment systems

International Nuclear Information System (INIS)

Judge, R.C.B.

1994-01-01

UK licence requirements for operation of nuclear power plants is dependent, inter alia, upon the licensee making and implementing adequate arrangements for the regular and systematic examination, inspection, maintenance and testing of all plant which may affect safety (Licence Condition 28). Similarly, the US NRC's Maintenance Rule (published in 10CFR50.65) specifies that a maintenance programme should be developed for plant systems, structures and components determined to be sensitive to ageing which will be used for the balance of the current (and, if relevant, extended) operating licence period. Against this background, the plant operators are seeking to minimise operating and maintenance costs and to enhance plant availability. This leads to a need to optimise the plant inspection and monitoring regimes whilst meeting regulatory requirements. In this paper, a conceptual framework for classifying civil structures and significant ageing mechanisms is described. This provides a systematic approach to making quantitative assessments of the likelihood and of potential degradation mechanisms and forms a consistent framework and a logical basis for prioritising inspection and maintenance schedules. The proposed method is analogous to a fault tree assessment, in which the likelihood of degradation due to a specific mechanism is considered as an event. The structures are considered in terms of their subcomponents. For each subcomponent, the value assigned to the likelihood of degradation is progressively reduced by a sequence of factors which make allowance for the structural and safety significance of any degradation and for the potential for timely detection of any degradation. Illustrative values for these factors are quoted in the text; it is recommended that these values are reviewed following a trial application of the method. (author)
Repair process and a repaired component

Energy Technology Data Exchange (ETDEWEB)

Roberts, III, Herbert Chidsey; Simpson, Stanley F.

2018-02-20

Matrix composite component repair processes are disclosed. The matrix composite repair process includes applying a repair material to a matrix composite component, securing the repair material to the matrix composite component with an external securing mechanism and curing the repair material to bond the repair material to the matrix composite component during the securing by the external securing mechanism. The matrix composite component is selected from the group consisting of a ceramic matrix composite, a polymer matrix composite, and a metal matrix composite. In another embodiment, the repair process includes applying a partially-cured repair material to a matrix composite component, and curing the repair material to bond the repair material to the matrix composite component, an external securing mechanism securing the repair material throughout a curing period, In another embodiment, the external securing mechanism is consumed or decomposed during the repair process.
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.
Simulation-driven machine learning: Bearing fault classification

Science.gov (United States)

Sobie, Cameron; Freitas, Carina; Nicolai, Mike

2018-01-01

Increasing the accuracy of mechanical fault detection has the potential to improve system safety and economic performance by minimizing scheduled maintenance and the probability of unexpected system failure. Advances in computational performance have enabled the application of machine learning algorithms across numerous applications including condition monitoring and failure detection. Past applications of machine learning to physical failure have relied explicitly on historical data, which limits the feasibility of this approach to in-service components with extended service histories. Furthermore, recorded failure data is often only valid for the specific circumstances and components for which it was collected. This work directly addresses these challenges for roller bearings with race faults by generating training data using information gained from high resolution simulations of roller bearing dynamics, which is used to train machine learning algorithms that are then validated against four experimental datasets. Several different machine learning methodologies are compared starting from well-established statistical feature-based methods to convolutional neural networks, and a novel application of dynamic time warping (DTW) to bearing fault classification is proposed as a robust, parameter free method for race fault detection.

RCC-MRx: Design and construction rules for mechanical components in high-temperature structures, experimental reactors and fusion reactors

International Nuclear Information System (INIS)

2015-01-01

The RCC-MRx code was developed for sodium-cooled fast reactors (SFR), research reactors (RR) and fusion reactors (FR-ITER). It provides the rules for designing and building mechanical components involved in areas subject to significant creep and/or significant irradiation. In particular, it incorporates an extensive range of materials (aluminum and zirconium alloys in response to the need for transparency to neutrons), sizing rules for thin shells and box structures, and new modern welding processes: electron beam, laser beam, diffusion and brazing. The RCC-MR code was used to design and build the prototype Fast Breeder Reactor (PFBR) developed by IGCAR in India and the ITER Vacuum Vessel. The RCC-Mx code is being used in the current construction of the RJH experimental reactor (Jules Horowitz reactor). The RCC-MRx code is serving as a reference for the design of the ASTRID project (Advanced Sodium Technological Reactor for Industrial Demonstration), for the design of the primary circuit in MYRRHA (Multi-purpose hybrid Research Reactor for High-tech Applications) and the design of the target station of the ESS project (European Spallation Source). Contents of the 2015 edition of the RCC-MRx code: Section I General provisions; Section II Additional requirements and special provisions; Section III Rules for nuclear installation mechanical components: Volume I: Design and construction rules: Volume A (RA): General provisions and entrance keys, Volume B (RB): Class 1 components and supports, Volume C (RC): Class 2 components and supports, Volume D (RD): Class 3 components and supports, Volume K (RK): Examination, handling or drive mechanisms, Volume L (RL): Irradiation devices, Volume Z (Ai): Technical appendices; Volume II: Materials; Volume III: Examinations methods; Volume IV: Welding; Volume V: Manufacturing operations; Volume VI: Probationary phase rules
Reversal learning as a measure of impulsive and compulsive behavior in addictions.

Science.gov (United States)

Izquierdo, Alicia; Jentsch, J David

2012-01-01

Our ability to measure the cognitive components of complex decision-making across species has greatly facilitated our understanding of its neurobiological mechanisms. One task in particular, reversal learning, has proven valuable in assessing the inhibitory processes that are central to executive control. Reversal learning measures the ability to actively suppress reward-related responding and to disengage from ongoing behavior, phenomena that are biologically and descriptively related to impulsivity and compulsivity. Consequently, reversal learning could index vulnerability for disorders characterized by impulsivity such as proclivity for initial substance abuse as well as the compulsive aspects of dependence. Though we describe common variants and similar tasks, we pay particular attention to discrimination reversal learning, its supporting neural circuitry, neuropharmacology and genetic determinants. We also review the utility of this task in measuring impulsivity and compulsivity in addictions. We restrict our review to instrumental, reward-related reversal learning studies as they are most germane to addiction. The research reviewed here suggests that discrimination reversal learning may be used as a diagnostic tool for investigating the neural mechanisms that mediate impulsive and compulsive aspects of pathological reward-seeking and -taking behaviors. Two interrelated mechanisms are posited for the neuroadaptations in addiction that often translate to poor reversal learning: frontocorticostriatal circuitry dysregulation and poor dopamine (D2 receptor) modulation of this circuitry. These data suggest new approaches to targeting inhibitory control mechanisms in addictions.
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…
Two-component feedback loops and deformed mechanics

International Nuclear Information System (INIS)

Tourigny, David S.

2015-01-01

It is shown that a general two-component feedback loop can be viewed as a deformed Hamiltonian system. Some of the implications of using ideas from theoretical physics to study biological processes are discussed. - Highlights: • Two-component molecular feedback loops are viewed as q-deformed Hamiltonian systems. • Deformations are reversed using Jackson derivatives to take advantage of working in the Hamiltonian limit. • New results are derived for the particular examples considered. • General deformations are suggested to be associated with a broader class of biological processes
Characteristics of M-component in rocket-triggered lightning and a discussion on its mechanism

Science.gov (United States)

Jiang, Rubin; Qie, Xiushu; Yang, Jing; Wang, Caixia; Zhao, Yang

2013-09-01

The current and electric field pulses associated with M-component following dart leader-return stroke sequences in negative rocket-triggered lightning flashes were analyzed in detail by using the data from Shandong Artificially Triggering Lightning Experiment, conducted from 2005 to 2010. For 63 M-components with current waveforms superimposed on the relatively steady continuing current, the geometric mean values of the peak current, duration, and charge transfer were 276 A, 1.21 ms, and 101 mC, respectively. The behaviors of the channel base current versus close electric field changes and the observation facts by different authors were carefully examined for investigation on mechanism of the M-component. A modified model based on Rakov's "two-wave" theory is proposed and confirms that the evolution of M-component through the lightning channel involves a downward wave transferring negative charge from the upper to the lower channel and an upward wave draining the charge transported by the downward wave. The upward wave serves to deplete the negative charge by the downward wave at its interface and makes the charge density of the channel beneath the interface layer to be roughly zero. Such modified concept is recognized to be reasonable by the simulated results showing a good agreement between the calculated and the measured E-field waveforms.
Parametric Analysis to Study the Influence of Aerogel-Based Renders' Components on Thermal and Mechanical Performance.

Science.gov (United States)

Ximenes, Sofia; Silva, Ana; Soares, António; Flores-Colen, Inês; de Brito, Jorge

2016-05-04

Statistical models using multiple linear regression are some of the most widely used methods to study the influence of independent variables in a given phenomenon. This study's objective is to understand the influence of the various components of aerogel-based renders on their thermal and mechanical performance, namely cement (three types), fly ash, aerial lime, silica sand, expanded clay, type of aerogel, expanded cork granules, expanded perlite, air entrainers, resins (two types), and rheological agent. The statistical analysis was performed using SPSS (Statistical Package for Social Sciences), based on 85 mortar mixes produced in the laboratory and on their values of thermal conductivity and compressive strength obtained using tests in small-scale samples. The results showed that aerial lime assumes the main role in improving the thermal conductivity of the mortars. Aerogel type, fly ash, expanded perlite and air entrainers are also relevant components for a good thermal conductivity. Expanded clay can improve the mechanical behavior and aerogel has the opposite effect.
Parametric Analysis to Study the Influence of Aerogel-Based Renders’ Components on Thermal and Mechanical Performance

Directory of Open Access Journals (Sweden)

Sofia Ximenes

2016-05-01

Full Text Available Statistical models using multiple linear regression are some of the most widely used methods to study the influence of independent variables in a given phenomenon. This study’s objective is to understand the influence of the various components of aerogel-based renders on their thermal and mechanical performance, namely cement (three types, fly ash, aerial lime, silica sand, expanded clay, type of aerogel, expanded cork granules, expanded perlite, air entrainers, resins (two types, and rheological agent. The statistical analysis was performed using SPSS (Statistical Package for Social Sciences, based on 85 mortar mixes produced in the laboratory and on their values of thermal conductivity and compressive strength obtained using tests in small-scale samples. The results showed that aerial lime assumes the main role in improving the thermal conductivity of the mortars. Aerogel type, fly ash, expanded perlite and air entrainers are also relevant components for a good thermal conductivity. Expanded clay can improve the mechanical behavior and aerogel has the opposite effect.
Learning Theories In Instructional Multimedia For English Learning

OpenAIRE

Farani, Rizki

2016-01-01

Learning theory is the concept of human learning. This concept is one of the important components in instructional for learning, especially English learning. English subject becomes one of important subjects for students but learning English needs specific strategy since it is not our vernacular. Considering human learning process in English learning is expected to increase students' motivation to understand English better. Nowadays, the application of learning theories in English learning ha...
From feedback- to response-based performance monitoring in active and observational learning.

Science.gov (United States)

Bellebaum, Christian; Colosio, Marco

2014-09-01

Humans can adapt their behavior by learning from the consequences of their own actions or by observing others. Gradual active learning of action-outcome contingencies is accompanied by a shift from feedback- to response-based performance monitoring. This shift is reflected by complementary learning-related changes of two ACC-driven ERP components, the feedback-related negativity (FRN) and the error-related negativity (ERN), which have both been suggested to signal events "worse than expected," that is, a negative prediction error. Although recent research has identified comparable components for observed behavior and outcomes (observational ERN and FRN), it is as yet unknown, whether these components are similarly modulated by prediction errors and thus also reflect behavioral adaptation. In this study, two groups of 15 participants learned action-outcome contingencies either actively or by observation. In active learners, FRN amplitude for negative feedback decreased and ERN amplitude in response to erroneous actions increased with learning, whereas observational ERN and FRN in observational learners did not exhibit learning-related changes. Learning performance, assessed in test trials without feedback, was comparable between groups, as was the ERN following actively performed errors during test trials. In summary, the results show that action-outcome associations can be learned similarly well actively and by observation. The mechanisms involved appear to differ, with the FRN in active learning reflecting the integration of information about own actions and the accompanying outcomes.
Detailed analysis of surface asperity deformation mechanism in diffusion bonding of steel hollow structural components

Energy Technology Data Exchange (ETDEWEB)

Zhang, C. [School of Materials Science and Engineering, Northwestern Polytechnical University, Xi’an 710072 (China); Laboratoire de Mecanique des Contacts et des Structures (LaMCoS), INSA Lyon, 20 Avenue des Sciences, F-69621 Villeurbanne Cedex (France); Li, H. [School of Materials Science and Engineering, Northwestern Polytechnical University, Xi’an 710072 (China); Li, M.Q., E-mail: zc9997242256@126.com [School of Materials Science and Engineering, Northwestern Polytechnical University, Xi’an 710072 (China)

2016-05-15

Graphical abstract: This study focused on the detailed analysis of surface asperity deformation mechanism in diffusion bonding of steel hollow structural component. A special surface with regular patterns was processed to be joined so as to observe the extent of surface asperity deformation under different applied bonding pressures. Fracture surface characteristic combined with surface roughness profiles distinctly revealed the enhanced surface asperity deformation as the applied pressure increases. The influence of surface asperity deformation mechanism on joint formation was analyzed: (a) surface asperity deformation not only directly expanded the interfacial contact areas, but also released deformation heat and caused defects, indirectly accelerating atomic diffusion, then benefits to void shrinkage; (b) surface asperity deformation readily introduced stored energy difference between two opposite sides of interface grain boundary, resulting in strain induced interface grain boundary migration. In addition, the influence of void on interface grain boundary migration was analyzed in detail. - Highlights: • A high quality hollow structural component has been fabricated by diffusion bonding. • Surface asperity deformation not only expands the interfacial contact areas, but also causes deformation heat and defects to improve the atomic diffusion. • Surface asperity deformation introduces the stored energy difference between the two opposite sides of interface grain boundary, leading to strain induced interface grain boundary migration. • The void exerts a dragging force on the interface grain boundary to retard or stop interface grain boundary migration. - Abstract: This study focused on the detailed analysis of surface asperity deformation mechanism in similar diffusion bonding as well as on the fabrication of high quality martensitic stainless steel hollow structural components. A special surface with regular patterns was processed to be joined so as to
Evolution of social versus individual learning in a subdivided population revisited: comparative analysis of three coexistence mechanisms using the inclusive-fitness method.

Science.gov (United States)

Kobayashi, Yutaka; Ohtsuki, Hisashi

2014-03-01

Learning abilities are categorized into social (learning from others) and individual learning (learning on one's own). Despite the typically higher cost of individual learning, there are mechanisms that allow stable coexistence of both learning modes in a single population. In this paper, we investigate by means of mathematical modeling how the effect of spatial structure on evolutionary outcomes of pure social and individual learning strategies depends on the mechanisms for coexistence. We model a spatially structured population based on the infinite-island framework and consider three scenarios that differ in coexistence mechanisms. Using the inclusive-fitness method, we derive the equilibrium frequency of social learners and the genetic load of social learning (defined as average fecundity reduction caused by the presence of social learning) in terms of some summary statistics, such as relatedness, for each of the three scenarios and compare the results. This comparative analysis not only reconciles previous models that made contradictory predictions as to the effect of spatial structure on the equilibrium frequency of social learners but also derives a simple mathematical rule that determines the sign of the genetic load (i.e. whether or not social learning contributes to the mean fecundity of the population). Copyright © 2013 Elsevier Inc. All rights reserved.
The COD concept and its application to fracture mechanical evaluation of cracked components

International Nuclear Information System (INIS)

Kockelmann, H.

1984-01-01

Based on a comprehensive literature study, this report critically evaluates the current state of experiences with the COD concept in fracture mechanics. First the concept is explained and the procedure of materials testing with a view to fracture mechanics is discussed in detail with emphasis on: The definition of crack shape modification; the procedure to detect crack modification, with subsequent comparison; the determination of material characteristics; the impact on the characteristics of the crack tip opening and the dispersion of results. The correlation between crack tip opening characteristics and notch impact strength is explained, and the methods applied for analysis of the streses affecting the structural components are shown. The design-based and failure threshold curves and the treatment of real crack geometries are also discussed. Problems still to be solved are shown. (orig./HP) [de
Middle school students' learning of mechanics concepts through engagement in different sequences of physical and virtual experiments

Science.gov (United States)

Sullivan, Sarah; Gnesdilow, Dana; Puntambekar, Sadhana; Kim, Jee-Seon

2017-08-01

Physical and virtual experimentation are thought to have different affordances for supporting students' learning. Research investigating the use of physical and virtual experiments to support students' learning has identified a variety of, sometimes conflicting, outcomes. Unanswered questions remain about how physical and virtual experiments may impact students' learning and for which contexts and content areas they may be most effective. Using a quasi-experimental design, we examined eighth grade students' (N = 100) learning of physics concepts related to pulleys depending on the sequence of physical and virtual labs they engaged in. Five classes of students were assigned to either the: physical first condition (PF) (n = 55), where students performed a physical pulley experiment and then performed the same experiment virtually, or virtual first condition (VF) (n = 45), with the opposite sequence. Repeated measures ANOVA's were conducted to examine how physical and virtual labs impacted students' learning of specific physics concepts. While we did not find clear-cut support that one sequence was better, we did find evidence that participating in virtual experiments may be more beneficial for learning certain physics concepts, such as work and mechanical advantage. Our findings support the idea that if time or physical materials are limited, using virtual experiments may help students understand work and mechanical advantage.
Ripple-Triggered Stimulation of the Locus Coeruleus during Post-Learning Sleep Disrupts Ripple/Spindle Coupling and Impairs Memory Consolidation

Science.gov (United States)

Novitskaya, Yulia; Sara, Susan J.; Logothetis, Nikos K.; Eschenko, Oxana

2016-01-01

Experience-induced replay of neuronal ensembles occurs during hippocampal high-frequency oscillations, or ripples. Post-learning increase in ripple rate is predictive of memory recall, while ripple disruption impairs learning. Ripples may thus present a fundamental component of a neurophysiological mechanism of memory consolidation. In addition to…
Recognition of Prior Learning as an integral component of ...

African Journals Online (AJOL)

Erna Kinsey

In these theories, learning is seen as a lifelong developmental process which is ... According to Gawe (1999:23) many institutions of higher learning all over the ... the vocational sector as well as the education and training sector with different ...
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.
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.
Virtual laboratory learning media development to improve science literacy skills of mechanical engineering students on basic physics concept of material measurement

Science.gov (United States)

Jannati, E. D.; Setiawan, A.; Siahaan, P.; Rochman, C.

2018-05-01

This study aims to determine the description of virtual laboratory learning media development to improve science literacy skills of Mechanical Engineering students on the concept of basic Physics. Quasi experimental method was employed in this research. The participants of this research were first semester students of mechanical engineering in Majalengka University. The research instrument was readability test of instructional media. The results of virtual laboratory learning media readability test show that the average score is 78.5%. It indicates that virtual laboratory learning media development are feasible to be used in improving science literacy skill of Mechanical Engineering students in Majalengka University, specifically on basic Physics concepts of material measurement.
Neural mechanisms of reinforcement learning in unmedicated patients with major depressive disorder.

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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
Social learning through prediction error in the brain

Science.gov (United States)

Joiner, Jessica; Piva, Matthew; Turrin, Courtney; Chang, Steve W. C.

2017-06-01

Learning about the world is critical to survival and success. In social animals, learning about others is a necessary component of navigating the social world, ultimately contributing to increasing evolutionary fitness. How humans and nonhuman animals represent the internal states and experiences of others has long been a subject of intense interest in the developmental psychology tradition, and, more recently, in studies of learning and decision making involving self and other. In this review, we explore how psychology conceptualizes the process of representing others, and how neuroscience has uncovered correlates of reinforcement learning signals to explore the neural mechanisms underlying social learning from the perspective of representing reward-related information about self and other. In particular, we discuss self-referenced and other-referenced types of reward prediction errors across multiple brain structures that effectively allow reinforcement learning algorithms to mediate social learning. Prediction-based computational principles in the brain may be strikingly conserved between self-referenced and other-referenced information.

Remembering components of food in Drosophila

Directory of Open Access Journals (Sweden)

Gaurav eDas

2016-02-01

Full Text Available Remembering features of past feeding experience can refine foraging and food choice. Insects can learn to associate sensory cues with components of food, such as sugars, amino acids, water, salt, alcohol, toxins and pathogens. In the fruit fly Drosophila some food components activate unique subsets of dopaminergic neurons that innervate distinct functional zones on the mushroom bodies. This architecture suggests that the overall dopaminergic neuron population could provide a potential cellular substrate through which the fly might learn to value a variety of food components. In addition, such an arrangement predicts that individual component memories reside in unique locations. Dopaminergic neurons are also critical for food memory consolidation and deprivation-state dependent motivational control of the expression of food-relevant memories. Here we review our current knowledge of how nutrient-specific memories are formed, consolidated and specifically retrieved in insects, with a particular emphasis on Drosophila.
Statistical learning and probabilistic prediction in music cognition: mechanisms of stylistic enculturation.

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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.
The prominent role of the cerebellum in the learning, origin and advancement of culture.

Science.gov (United States)

Vandervert, Larry

2016-01-01

Vandervert described how, in collaboration with the cerebral cortex, unconscious learning of cerebellar internal models leads to enhanced executive control in working memory in expert music performance and in scientific discovery. Following Vandervert's arguments, it is proposed that since music performance and scientific discovery, two pillars of cultural learning and advancement, are learned through in cerebellar internal models, it is reasonable that additional if not all components of culture may be learned in the same way. Within this perspective strong evidence is presented that argues that the learning, maintenance, and advancement of culture are accomplished primarily by recently-evolved (the last million or so years) motor/cognitive functions of the cerebellum and not primarily by the cerebral cortex as previously assumed. It is suggested that the unconscious cerebellar mechanism behind the origin and learning of culture greatly expands Ito's conception of the cerebellum as "a brain for an implicit self." Through the mechanism of predictive sequence detection in cerebellar internal models related to the body, other persons, or the environment, it is shown how individuals can unconsciously learn the elements of culture and yet, at the same time, be in social sync with other members of culture. Further, this predictive, cerebellar mechanism of socialization toward the norms of culture is hypothesized to be diminished among children who experience excessive television viewing, which results in lower grades, poor socialization, and diminished executive control. It is concluded that the essential components of culture are learned and sustained not by the cerebral cortex alone as many traditionally believe, but are learned through repetitious improvements in prediction and control by internal models in the cerebellum. From this perspective, the following new explanations of culture are discussed: (1) how culture can be learned unconsciously but yet be socially
Optimisation of a machine learning algorithm in human locomotion using principal component and discriminant function analyses.

Science.gov (United States)

Bisele, Maria; Bencsik, Martin; Lewis, Martin G C; Barnett, Cleveland T

2017-01-01

Assessment methods in human locomotion often involve the description of normalised graphical profiles and/or the extraction of discrete variables. Whilst useful, these approaches may not represent the full complexity of gait data. Multivariate statistical methods, such as Principal Component Analysis (PCA) and Discriminant Function Analysis (DFA), have been adopted since they have the potential to overcome these data handling issues. The aim of the current study was to develop and optimise a specific machine learning algorithm for processing human locomotion data. Twenty participants ran at a self-selected speed across a 15m runway in barefoot and shod conditions. Ground reaction forces (BW) and kinematics were measured at 1000 Hz and 100 Hz, respectively from which joint angles (°), joint moments (N.m.kg-1) and joint powers (W.kg-1) for the hip, knee and ankle joints were calculated in all three anatomical planes. Using PCA and DFA, power spectra of the kinematic and kinetic variables were used as a training database for the development of a machine learning algorithm. All possible combinations of 10 out of 20 participants were explored to find the iteration of individuals that would optimise the machine learning algorithm. The results showed that the algorithm was able to successfully predict whether a participant ran shod or barefoot in 93.5% of cases. To the authors' knowledge, this is the first study to optimise the development of a machine learning algorithm.
Mechanical properties, reliability assessment and design of ceramic components used in high temperature assemblies

International Nuclear Information System (INIS)

Bendeich, P.J.

2002-01-01

The use of ceramic materials in high temperature structural components holds may advantages over conventional materials such as metals. These include high temperature strength, creep resistance, wear resistance, corrosion resistance, and stiffness. The tradeoff for these improved properties is the brittle nature of ceramics and their tendency for catastrophic failure and lack of damage tolerance. In this work some the various strategies available to overcome these limitations are reviewed. These include stochastic design strategies using the Weibull and Batdorf methods of failure probability prediction rather than the more familiar deterministic methods. Fracture mechanics analysis is also used extensively in this work to predict damage tolerance and failure conditions. A range of testing methods was utilised to provide material information for the methods outlined above. These included: flexural strength measurement for the determination of failure probability parameters; fracture toughness measurement using indentation methods and crack growth measurement; thermal expansion measurement; temperature dependant dynamic Young's modulus measurement; and thermal shock testing using a central heating laser. A new inverse method for measuring specific heat was developed and critically examined for practical use. This is particularly valuable in modelling transient thermal conditions for use in thermal shock analysis. A shape optimisation technique utilising a biological growth law was adapted for use with ceramic components utilising failure probability as the objective function. These methods were utilised in the design and subsequent failure analysis of a high temperature hotpress ram. The results of the failure probability analysis showed that the design had a very low probability of failure under normal operating conditions. Fracture mechanics analysis indicated that damage tolerance in the critical retaining bolt mechanism was high with damage likely to cause
The Psychometric Assessment of Children with Learning Disabilities: An Index Derived from a Principal Components Analysis of the WISC-R.

Science.gov (United States)

Lawson, J. S.; Inglis, James

1984-01-01

A learning disability index (LDI) for the assessment of intellectual deficits on the Wechsler Intelligence Scale for Children-Revised (WISC-R) is described. The Factor II score coefficients derived from an unrotated principal components analysis of the WISC-R normative data, in combination with the individual's scaled scores, are used for this…
Exploring the MACH Model's Potential as a Metacognitive Tool to Help Undergraduate Students Monitor Their Explanations of Biological Mechanisms

Science.gov (United States)

Trujillo, Caleb M.; Anderson, Trevor R.; Pelaez, Nancy J.

2016-01-01

When undergraduate biology students learn to explain biological mechanisms, they face many challenges and may overestimate their understanding of living systems. Previously, we developed the MACH model of four components used by expert biologists to explain mechanisms: Methods, Analogies, Context, and How. This study explores the implementation of…
Computation of the mechanical behaviour of nuclear reactor components

International Nuclear Information System (INIS)

Brosi, S.; Niffenegger, M.; Roesel, R.; Reichlin, K.; Duijvestijn, A.

1994-01-01

A possible limiting factor of the service life of a reactor is the mechanical load carrying margin, i.e. the excess of the load carrying capacity over the actual loading, of the central, heavy section components. This margin decreases during service but, for safety reasons, may not fall below a critical value. Therefore, it is essential to check and to control continuously the factors which cause the decrease. The reasons for the decrease are shown at length and in detail in an example relating to the test which almost achieved failure of a pipe emanating from a reactor pressure vessel, weakened by an artificial crack and undergoing a water-hammer loading. The latter was caused by a sudden valve closure supposed to follow upon a break far downstream. The computational and experimental difficulties associated with the simultaneous occurrence of an extreme weakening and an extreme loading in an already rather complicated geometry are explained. It is concluded that available computational tools and present know-how are sufficient to simulate the behaviour under such conditions as would prevail in normal service, and even to analyse departures from them, as long as not all difficulties arise simultaneously. (author) figs., tabs., refs
Metaphor and Second Language Learning: The State of the Field

Science.gov (United States)

Hoang, Ha

2014-01-01

Once considered a stylistic issue, metaphor is now considered a critical component of everyday and specialized language and most importantly, a fundamental mechanism of human conceptualizations of the world. The use of metaphor in language, thought and communication has been examined in second language (L2) learning. The body of literature that…
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…
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...
Non-destructive assay of mechanical components using gamma-rays and thermal neutrons

Energy Technology Data Exchange (ETDEWEB)

Souza, Erica Silvani; Avelino, Mila R. [PPG-EM/UERJ, R. Sao Francisco Xavier, 524, Maracana - Rio de Janeiro - RJ (Brazil); Almeida, Gevaldo L. de; Souza, Maria Ines S. [IEN/CNEN, Rua Helio de Almeida, 75, Ilha do Fundao, Rio de Janeiro - RJ (Brazil)

2013-05-06

This work presents the results obtained in the inspection of several mechanical components through neutron and gamma-ray transmission radiography. The 4.46 Multiplication-Sign 10{sup 5} n.cm{sup -2}.s{sup -1} thermal neutron flux available at the main port of the Argonauta research reactor in Instituto de Engenharia Nuclear has been used as source for the neutron radiographic imaging. The 412 keV {gamma}-ray emitted by {sup 198}Au, also produced in that reactor, has been used as interrogation agent for the gamma radiography. Imaging Plates - IP specifically designed to operate with thermal neutrons or with X-rays have been employed as detectors and storage devices for each of these radiations.
Derivation of the reduced reaction mechanisms of ozone depletion events in the Arctic spring by using concentration sensitivity analysis and principal component analysis

Directory of Open Access Journals (Sweden)

L. Cao

2016-12-01

Full Text Available The ozone depletion events (ODEs in the springtime Arctic have been investigated since the 1980s. It is found that the depletion of ozone is highly associated with an auto-catalytic reaction cycle, which involves mostly the bromine-containing compounds. Moreover, bromide stored in various substrates in the Arctic such as the underlying surface covered by ice and snow can be also activated by the absorbed HOBr. Subsequently, this leads to an explosive increase of the bromine amount in the troposphere, which is called the “bromine explosion mechanism”. In the present study, a reaction scheme representing the chemistry of ozone depletion and halogen release is processed with two different mechanism reduction approaches, namely, the concentration sensitivity analysis and the principal component analysis. In the concentration sensitivity analysis, the interdependence of the mixing ratios of ozone and principal bromine species on the rate of each reaction in the ODE mechanism is identified. Furthermore, the most influential reactions in different time periods of ODEs are also revealed. By removing 11 reactions with the maximum absolute values of sensitivities lower than 10 %, a reduced reaction mechanism of ODEs is derived. The onsets of each time period of ODEs in simulations using the original reaction mechanism and the reduced reaction mechanism are identical while the maximum deviation of the mixing ratio of principal bromine species between different mechanisms is found to be less than 1 %. By performing the principal component analysis on an array of the sensitivity matrices, the dependence of a particular species concentration on a combination of the reaction rates in the mechanism is revealed. Redundant reactions are indicated by principal components corresponding to small eigenvalues and insignificant elements in principal components with large eigenvalues. Through this investigation, aside from the 11 reactions identified as
A machine learning approach for predicting CRISPR-Cas9 cleavage efficiencies and patterns underlying its mechanism of action.

Science.gov (United States)

Abadi, Shiran; Yan, Winston X; Amar, David; Mayrose, Itay

2017-10-01

The adaptation of the CRISPR-Cas9 system as a genome editing technique has generated much excitement in recent years owing to its ability to manipulate targeted genes and genomic regions that are complementary to a programmed single guide RNA (sgRNA). However, the efficacy of a specific sgRNA is not uniquely defined by exact sequence homology to the target site, thus unintended off-targets might additionally be cleaved. Current methods for sgRNA design are mainly concerned with predicting off-targets for a given sgRNA using basic sequence features and employ elementary rules for ranking possible sgRNAs. Here, we introduce CRISTA (CRISPR Target Assessment), a novel algorithm within the machine learning framework that determines the propensity of a genomic site to be cleaved by a given sgRNA. We show that the predictions made with CRISTA are more accurate than other available methodologies. We further demonstrate that the occurrence of bulges is not a rare phenomenon and should be accounted for in the prediction process. Beyond predicting cleavage efficiencies, the learning process provides inferences regarding patterns that underlie the mechanism of action of the CRISPR-Cas9 system. We discover that attributes that describe the spatial structure and rigidity of the entire genomic site as well as those surrounding the PAM region are a major component of the prediction capabilities.
A machine learning approach for predicting CRISPR-Cas9 cleavage efficiencies and patterns underlying its mechanism of action.

Directory of Open Access Journals (Sweden)

Shiran Abadi

2017-10-01

Full Text Available The adaptation of the CRISPR-Cas9 system as a genome editing technique has generated much excitement in recent years owing to its ability to manipulate targeted genes and genomic regions that are complementary to a programmed single guide RNA (sgRNA. However, the efficacy of a specific sgRNA is not uniquely defined by exact sequence homology to the target site, thus unintended off-targets might additionally be cleaved. Current methods for sgRNA design are mainly concerned with predicting off-targets for a given sgRNA using basic sequence features and employ elementary rules for ranking possible sgRNAs. Here, we introduce CRISTA (CRISPR Target Assessment, a novel algorithm within the machine learning framework that determines the propensity of a genomic site to be cleaved by a given sgRNA. We show that the predictions made with CRISTA are more accurate than other available methodologies. We further demonstrate that the occurrence of bulges is not a rare phenomenon and should be accounted for in the prediction process. Beyond predicting cleavage efficiencies, the learning process provides inferences regarding patterns that underlie the mechanism of action of the CRISPR-Cas9 system. We discover that attributes that describe the spatial structure and rigidity of the entire genomic site as well as those surrounding the PAM region are a major component of the prediction capabilities.
Capabilities and limitations of fracture mechanics methods in the assessment of integrity of light water reactor components

Energy Technology Data Exchange (ETDEWEB)

Burdekin, F M

1988-12-31

This document deals with fracture mechanics methods used for the assessment of Light Water Reactor (LWR) components. The background to analysis methods using elastic plastic parameters is described. Several results obtained with these methods are presented as well as results of reliability analysis methods. (TEC). 27 refs.
Catecholaminergic Regulation of Learning Rate in a Dynamic Environment.

Directory of Open Access Journals (Sweden)

Marieke Jepma

2016-10-01

Full Text Available Adaptive behavior in a changing world requires flexibly adapting one's rate of learning to the rate of environmental change. Recent studies have examined the computational mechanisms by which various environmental factors determine the impact of new outcomes on existing beliefs (i.e., the 'learning rate'. However, the brain mechanisms, and in particular the neuromodulators, involved in this process are still largely unknown. The brain-wide neurophysiological effects of the catecholamines norepinephrine and dopamine on stimulus-evoked cortical responses suggest that the catecholamine systems are well positioned to regulate learning about environmental change, but more direct evidence for a role of this system is scant. Here, we report evidence from a study employing pharmacology, scalp electrophysiology and computational modeling (N = 32 that suggests an important role for catecholamines in learning rate regulation. We found that the P3 component of the EEG-an electrophysiological index of outcome-evoked phasic catecholamine release in the cortex-predicted learning rate, and formally mediated the effect of prediction-error magnitude on learning rate. P3 amplitude also mediated the effects of two computational variables-capturing the unexpectedness of an outcome and the uncertainty of a preexisting belief-on learning rate. Furthermore, a pharmacological manipulation of catecholamine activity affected learning rate following unanticipated task changes, in a way that depended on participants' baseline learning rate. Our findings provide converging evidence for a causal role of the human catecholamine systems in learning-rate regulation as a function of environmental change.
Catecholaminergic Regulation of Learning Rate in a Dynamic Environment.

Science.gov (United States)

Jepma, Marieke; Murphy, Peter R; Nassar, Matthew R; Rangel-Gomez, Mauricio; Meeter, Martijn; Nieuwenhuis, Sander

2016-10-01

Adaptive behavior in a changing world requires flexibly adapting one's rate of learning to the rate of environmental change. Recent studies have examined the computational mechanisms by which various environmental factors determine the impact of new outcomes on existing beliefs (i.e., the 'learning rate'). However, the brain mechanisms, and in particular the neuromodulators, involved in this process are still largely unknown. The brain-wide neurophysiological effects of the catecholamines norepinephrine and dopamine on stimulus-evoked cortical responses suggest that the catecholamine systems are well positioned to regulate learning about environmental change, but more direct evidence for a role of this system is scant. Here, we report evidence from a study employing pharmacology, scalp electrophysiology and computational modeling (N = 32) that suggests an important role for catecholamines in learning rate regulation. We found that the P3 component of the EEG-an electrophysiological index of outcome-evoked phasic catecholamine release in the cortex-predicted learning rate, and formally mediated the effect of prediction-error magnitude on learning rate. P3 amplitude also mediated the effects of two computational variables-capturing the unexpectedness of an outcome and the uncertainty of a preexisting belief-on learning rate. Furthermore, a pharmacological manipulation of catecholamine activity affected learning rate following unanticipated task changes, in a way that depended on participants' baseline learning rate. Our findings provide converging evidence for a causal role of the human catecholamine systems in learning-rate regulation as a function of environmental change.
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.
Tracking Active Learning in the Medical School Curriculum: A Learning-Centered Approach.

Science.gov (United States)

McCoy, Lise; Pettit, Robin K; Kellar, Charlyn; Morgan, Christine

2018-01-01

Medical education is moving toward active learning during large group lecture sessions. This study investigated the saturation and breadth of active learning techniques implemented in first year medical school large group sessions. Data collection involved retrospective curriculum review and semistructured interviews with 20 faculty. The authors piloted a taxonomy of active learning techniques and mapped learning techniques to attributes of learning-centered instruction. Faculty implemented 25 different active learning techniques over the course of 9 first year courses. Of 646 hours of large group instruction, 476 (74%) involved at least 1 active learning component. The frequency and variety of active learning components integrated throughout the year 1 curriculum reflect faculty familiarity with active learning methods and their support of an active learning culture. This project has sparked reflection on teaching practices and facilitated an evolution from teacher-centered to learning-centered instruction.

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
N-methyl-d-aspartate receptors, learning and memory: chronic intraventricular infusion of the NMDA receptor antagonist d-AP5 interacts directly with the neural mechanisms of spatial learning.

Science.gov (United States)

Morris, R G M; Steele, R J; Bell, J E; Martin, S J

2013-03-01

Three experiments were conducted to contrast the hypothesis that hippocampal N-methyl-d-aspartate (NMDA) receptors participate directly in the mechanisms of hippocampus-dependent learning with an alternative view that apparent impairments of learning induced by NMDA receptor antagonists arise because of drug-induced neuropathological and/or sensorimotor disturbances. In experiment 1, rats given a chronic i.c.v. infusion of d-AP5 (30 mm) at 0.5 μL/h were selectively impaired, relative to aCSF-infused animals, in place but not cued navigation learning when they were trained during the 14-day drug infusion period, but were unimpaired on both tasks if trained 11 days after the minipumps were exhausted. d-AP5 caused sensorimotor disturbances in the spatial task, but these gradually worsened as the animals failed to learn. Histological assessment of potential neuropathological changes revealed no abnormalities in d-AP5-treated rats whether killed during or after chronic drug infusion. In experiment 2, a deficit in spatial learning was also apparent in d-AP5-treated rats trained on a spatial reference memory task involving two identical but visible platforms, a task chosen and shown to minimise sensorimotor disturbances. HPLC was used to identify the presence of d-AP5 in selected brain areas. In Experiment 3, rats treated with d-AP5 showed a delay-dependent deficit in spatial memory in the delayed matching-to-place protocol for the water maze. These data are discussed with respect to the learning mechanism and sensorimotor accounts of the impact of NMDA receptor antagonists on brain function. We argue that NMDA receptor mechanisms participate directly in spatial learning. © 2013 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.
PASCAL, Probabilistic Fracture Mechanics Analysis of Structural Components in Aging LWR

International Nuclear Information System (INIS)

Shibata, Katsuyuki; Onizawa, Kunio; Li, Yinsheng; Kato, Daisuke

2005-01-01

A - Description of program or function: PASCAL (PFM analysis of Structural Components in Aging LWR) is a PFM (Probabilistic Fracture Mechanics) code for evaluating the failure probability of aged pressure components. PASCAL has been developed as a part of the JAERI's research program on aging and structural integrity of LWR components, in order to respond to the increasing need of the probabilistic methodology in the regulation and inspection of nuclear components with the objective to provide a rational tool for the evaluation of the reliability and integrity of structural components. In order to improve the accuracy and reliability of the analysis code, some new fracture mechanics models or computational techniques are introduced considering the recent progress in the state of the art and performance of PC. Thus some new analysis models and original methodologies were introduced in PASCAL such as the elastic-plastic fracture criterion based on R6 method, a new crack extension model of semi-elliptical crack evaluation and so on. Moreover a function to evaluate the effect of embrittlement recovery by annealing of irradiated RPV is also introduced in the code based on the USNRC R.G. 1.162(1996). The code has been verified through various failure analysis results and international PTS round robin analysis ICAS which had been organized by the Principal Working Group 3 of OECD/NEA/CSNI. In order to attain a high usability, PASCAL Ver.1 with GUI provides an exclusive FEM pre-processor Pre-PASCAL for generating the input load transient data, a GUI system for generating the input data for PASCAL main processor of main solver and post-processor for output data. - Pre-PASCAL: Pre-PASCAL is an exclusive 3-D FEM pre-processor for generating the input transient data provided with 3 RPV mesh models and two simple specimen mesh models, i.e. CT and CCP. Almost the same input data format with that of PASCAL main processor is used. Output data of temperature and stress distribution
Application of probabilistic fracture mechanics to the reliability analysis of pressure-bearing reactor components

International Nuclear Information System (INIS)

Schmitt, W.; Roehrich, E.; Wellein, R.

1977-01-01

Since no failures in the primary reactor components have been reported so far, it is impossible to estimate the failure probability of those components just by means of statistics. Therefore the way of probabilistic fracture mechanics has been proposed. Here the material properties, the loads and the crack distributions are treated as statistical variables with certain distributions. From the distributions of these data probability density functions can be established for the loading of a component as well as for the resistance of this component. From these functions the failure probability for a given failure mode is easily obtained either by the application of direct integration procedures which are shortly reviewed here, or by the use of Monte Carlo techniques. The most important part of the concept is the collection of a sufficiently large amount of raw data from different sources. These data need to be processed so that they can be transformed into probability density functions. The method of data collection and processing in terms of histograms, plots of probability density functions etc. is described. The choice of the various types of distribution functions is discussed. As an example, the derivation of the probability density function for cracks of a given size in a component is presented. Here the raw data, i.e. the ultrasonic results, are transformed into real crack sizes by means of a conservative conversion rule. The true distribution of the indications is obtained by taking into account a detection probability function. The final probability density function is influenced by the fact that indications exceeding certain values need to be re
Mechanical Properties Studies of Components Formulation for Mixing Process Contain of Polypropylene, Polyethylene, and Aluminium Powder

Science.gov (United States)

Hamsi, A.; Dinzi, R.

2017-03-01

Certain powder and others components can induce toxic reactions if not properly handled in the mixing stage. During handling, the small particles can become airborne and be trapped in the lungs, another concern is inhomogeneities in the mixing process. Uniform quantities of the particles of the components are needed in all portions of the mixture. This paper reports the results of mechanical properties studies of mixing three components formulation for mixing process. Contain of Polyethylene (PE), Polyprophylene (PP) and Aluminium Powder. Powder mixer, Autodesk mold flow and computer based on excell method was carried out to study the influence of each formulation component on the flow %, PE 20% and Aluminium powder 2%. Macroscopic optic and macro photo was carried out to identify the homogenity of mixing, tensile test for identify the strength of component after mixing. Finally the optimal tensile test with composition PP 785,PE 20% and Aluminium powder 2% at speed 52 rpm, temperature 1500C, the tensile strength 20,92 N/mm2. At temperature 1600C, speed 100 rpm the optimum tensile strength 17,91 N/mm2. The result of simulation autodesk mold flow adviser the filling time 6 seconds. Otherwise on manual hot hidraulic press the time of filling 10 seconds.
Engaging students as partners in developing online learning and feedback activities for first-year fluid mechanics

Science.gov (United States)

Brown, Alan

2018-01-01

Much learning takes place outside of formal class settings, yet students starting in higher education are not always well equipped with independent learning skills, appropriate self-knowledge or the required levels of intrinsic motivation This project used students as partners to develop resources that could be used by first-year undergraduates in fluid mechanics, using activities and receiving feedback through the virtual learning environment (VLE), in order to build these three attributes of independent learners. While there were significant benefits to the students who developed the resources, the target students saw much lower benefits as a result of poorer than expected engagement. The challenge this research presents is to develop activities that maximise engagement in large classes, as well as develop appropriate independent learning skills.
Study of the mechanical properties of the electric power station components: the punch test

International Nuclear Information System (INIS)

Isselin, J.

2003-03-01

The aging of the electric production park implies an increasing need of knowledge concerning the evolution of the mechanical properties of its components. With regard to this problem, the availability in material is more and more small. This work proposes to characterize these properties through a mechanical test called Punch test. The main characteristic of this test is to use very small volume samples. The development of this test has been carried out by the study of a 15 MDV 4-05 steel coming from a steam drum of a thermal power plant after 145000 hours of service. At first, we have measured the influence of the parameters of this test. Then, the study has dealt more particularly on the transition temperature of the material. With the finite element simulation method, the strain hardening coefficient of the material has been determined. (O.M.)
Tracking Active Learning in the Medical School Curriculum: A Learning-Centered Approach

Science.gov (United States)

McCoy, Lise; Pettit, Robin K; Kellar, Charlyn; Morgan, Christine

2018-01-01

Background: Medical education is moving toward active learning during large group lecture sessions. This study investigated the saturation and breadth of active learning techniques implemented in first year medical school large group sessions. Methods: Data collection involved retrospective curriculum review and semistructured interviews with 20 faculty. The authors piloted a taxonomy of active learning techniques and mapped learning techniques to attributes of learning-centered instruction. Results: Faculty implemented 25 different active learning techniques over the course of 9 first year courses. Of 646 hours of large group instruction, 476 (74%) involved at least 1 active learning component. Conclusions: The frequency and variety of active learning components integrated throughout the year 1 curriculum reflect faculty familiarity with active learning methods and their support of an active learning culture. This project has sparked reflection on teaching practices and facilitated an evolution from teacher-centered to learning-centered instruction. PMID:29707649
Preference Learning Style in Engineering Mathematics: Students' Perception of E-Learning

Science.gov (United States)

Tawil, Norngainy Mohd; Ismail, Nur Arzilah; Asshaari, Izamarlina; Othman, Haliza; Zaharim, Azami; Bahaludin, Hafizah

2013-01-01

Nowadays, traditional learning styles are assisted with e-learning components to ensure the effectiveness of the teaching and learning process, especially for the students. This approach is known as blended learning. Objective of this paper is to investigate and clarify the students' preferences in learning style, either traditional or e-learning.…
Problem-Based Learning: An Overview of its Process and Impact on Learning

Directory of Open Access Journals (Sweden)

Elaine H.J. Yew

2016-12-01

Full Text Available In this review, we provide an overview of the process of problem-based learning (PBL and the studies examining the effectiveness of PBL. We also discuss a number of naturalistic and empirical studies that have examined the process of PBL and how its various components impact students’ learning. We conclude that the studies comparing the relative effectiveness of PBL are generally consistent in demonstrating its superior efficacy for longer-term knowledge retention and in the application of knowledge. Studies on the process of PBL, however, are still inconclusive as to which component(s of PBL most significantly impact students’ learning, although causal studies have demonstrated that all the phases of PBL are necessary in influencing students’ learning outcomes.
Implementation of Learning Organization Components in Ardabil Social Security Hospital

Directory of Open Access Journals (Sweden)

Azadeh Zirak

2015-06-01

Full Text Available This study aimed to investigate the implementation of learning organization characteristics based on Marquardt systematic model in Ardabil Social Security Hospital. The statistical population of this research was 234 male and female employees of Ardabil Social Security Hospital. For data collection, Marquardt questionnaire was used in the present study which its validity and reliability had been confirmed. Statistical analysis of hypotheses based on independent samples t-test showed that learning organization characteristics were used more than average level in some subsystems of Marquardt model and there was a significant difference between current position and excellent position based on learning organization characteristic application. According to the research findings, more attention should be paid to the subsystems of learning organization establishment and balanced development of these subsystems.
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.
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.
Online neural monitoring of statistical learning.

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Batterink, Laura J; Paller, Ken A

2017-05-01

The extraction of patterns in the environment plays a critical role in many types of human learning, from motor skills to language acquisition. This process is known as statistical learning. Here we propose that statistical learning has two dissociable components: (1) perceptual binding of individual stimulus units into integrated composites and (2) storing those integrated representations for later use. Statistical learning is typically assessed using post-learning tasks, such that the two components are conflated. Our goal was to characterize the online perceptual component of statistical learning. Participants were exposed to a structured stream of repeating trisyllabic nonsense words and a random syllable stream. Online learning was indexed by an EEG-based measure that quantified neural entrainment at the frequency of the repeating words relative to that of individual syllables. Statistical learning was subsequently assessed using conventional measures in an explicit rating task and a reaction-time task. In the structured stream, neural entrainment to trisyllabic words was higher than in the random stream, increased as a function of exposure to track the progression of learning, and predicted performance on the reaction time (RT) task. These results demonstrate that monitoring this critical component of learning via rhythmic EEG entrainment reveals a gradual acquisition of knowledge whereby novel stimulus sequences are transformed into familiar composites. This online perceptual transformation is a critical component of learning. Copyright © 2017 Elsevier Ltd. All rights reserved.
Principal component analysis study of visual and verbal metaphoric comprehension in children with autism and learning disabilities.

Science.gov (United States)

Mashal, Nira; Kasirer, Anat

2012-01-01

This research extends previous studies regarding the metaphoric competence of autistic and learning disable children on different measures of visual and verbal non-literal language comprehension, as well as cognitive abilities that include semantic knowledge, executive functions, similarities, and reading fluency. Thirty seven children with autism (ASD), 20 children with learning disabilities (LD), and 21 typically developed (TD) children participated in the study. Principal components analysis was used to examine the interrelationship among the various tests in each group. Results showed different patterns in the data according to group. In particular, the results revealed that there is no dichotomy between visual and verbal metaphors in TD children but rather metaphor are classified according to their familiarity level. In the LD group visual metaphors were classified independently of the verbal metaphors. Verbal metaphoric understanding in the ASD group resembled the LD group. In addition, our results revealed the relative weakness of the ASD and LD children in suppressing irrelevant information. Copyright © 2011 Elsevier Ltd. All rights reserved.
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…
Guarantee of remaining life time. Integrity of mechanical components and control of ageing phenomena

International Nuclear Information System (INIS)

Schuler, X.; Herter, K.H.; Koenig, G.

2012-01-01

The life time of safety relevant systems, structures and components (SSC) of Nuclear Power Plants (NPP) is determined by two main principles. First of all the required quality has to be produced during the design and fabrication process. This means that quality has to be produced and can't be improved by excessive inspections (Basis Safety - quality through production principle). The second one is assigned to the initial quality which has to be maintained during operation. This concerns safe operation during the total life time (life time management), safety against ageing phenomena (AM - ageing management) as well as proof of integrity (e.g. break preclusion or avoidance of fracture for SSC with high safety relevance). Initiated by the Fukushima Dai-ichi event in Japan in spring 2011 for German NPP's Long Term Operation (LTO) is out of question. In June 2011 legislation took decision to phase-out from nuclear by 2022. As a fact safe operation shall be guaranteed for the remaining life time. Within this technical framework the ageing management is a key element. Depending on the safety-relevance of the SSC under observation including preventive maintenance various tasks are required in particular to clarify the mechanisms which contribute systemspecifically to the damage of the components and systems and to define their controlling parameters which have to be monitored and checked. Appropriate continuous or discontinuous measures are to be considered in this connection. The approach to ensure a high standard of quality in operation for the remaining life time and the management of the technical and organizational aspects are demonstrated and explained. The basis for ageing management to be applied to NNPs is included in Nuclear Safety Standard 1403 which describes the ageing management procedures. For SSC with high safety relevance a verification analysis for rupture preclusion (proof of integrity, integrity concept) shall be performed (Nuclear Safety Standard 3206
Component Fragility Research Program: Phase 1 component prioritization

International Nuclear Information System (INIS)

Holman, G.S.; Chou, C.K.

1987-06-01

Current probabilistic risk assessment (PRA) methods for nuclear power plants utilize seismic ''fragilities'' - probabilities of failure conditioned on the severity of seismic input motion - that are based largely on limited test data and on engineering judgment. Under the NRC Component Fragility Research Program (CFRP), the Lawrence Livermore National Laboratory (LLNL) has developed and demonstrated procedures for using test data to derive probabilistic fragility descriptions for mechanical and electrical components. As part of its CFRP activities, LLNL systematically identified and categorized components influencing plant safety in order to identify ''candidate'' components for future NRC testing. Plant systems relevant to safety were first identified; within each system components were then ranked according to their importance to overall system function and their anticipated seismic capacity. Highest priority for future testing was assigned to those ''very important'' components having ''low'' seismic capacity. This report describes the LLNL prioritization effort, which also included application of ''high-level'' qualification data as an alternate means of developing probabilistic fragility descriptions for PRA applications
When does social learning become cultural learning?

Science.gov (United States)

Heyes, Cecilia

2017-03-01

Developmental research on selective social learning, or 'social learning strategies', is currently a rich source of information about when children copy behaviour, and who they prefer to copy. It also has the potential to tell us when and how human social learning becomes cultural learning; i.e. mediated by psychological mechanisms that are specialized, genetically or culturally, to promote cultural inheritance. However, this review article argues that, to realize its potential, research on the development of selective social learning needs more clearly to distinguish functional from mechanistic explanation; to achieve integration with research on attention and learning in adult humans and 'dumb' animals; and to recognize that psychological mechanisms can be specialized, not only by genetic evolution, but also by associative learning and cultural evolution. © 2015 John Wiley & Sons Ltd.
Ageing degradation mechanisms in nuclear power plants: lessons learned from operating experience

International Nuclear Information System (INIS)

Bieth, M.; Zerger, B.; Duchac, A.

2014-01-01

This paper presents main results of a comprehensive study performed by the European Clearinghouse on Operating Experience Feedback of Nuclear Power Plants (NPP) with the support of IRSN (Institut de Surete Nucleaire et de Radioprotection) and GRS (Gesellschaft fuer Anlagen und Reaktorsicherheit mbH). Physical ageing mechanisms of Structures, Systems and Components (SSC) that eventually lead to ageing related systems and components failures at nuclear power plants were the main focus of this study. The analysis of ageing related events involved operating experience reported by NPP operators in France, Germany, USA and to the IAEA/NEA International Reporting System on operating experience for the past 20 years. A list of relevant ageing related events was populated. Each ageing related event contained in the list was analyzed and results of analysis were summarized for each ageing degradation mechanism which appeared to be the dominant contributor or direct cause. This paper provides insights into ageing related operating experience as well as recommendations to deal with the physical ageing of nuclear power plant SSC important to safety. (authors)

"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…
A probabilistic model for component-based shape synthesis

KAUST Repository

Kalogerakis, Evangelos

2012-07-01

We present an approach to synthesizing shapes from complex domains, by identifying new plausible combinations of components from existing shapes. Our primary contribution is a new generative model of component-based shape structure. The model represents probabilistic relationships between properties of shape components, and relates them to learned underlying causes of structural variability within the domain. These causes are treated as latent variables, leading to a compact representation that can be effectively learned without supervision from a set of compatibly segmented shapes. We evaluate the model on a number of shape datasets with complex structural variability and demonstrate its application to amplification of shape databases and to interactive shape synthesis. © 2012 ACM 0730-0301/2012/08-ART55.
Mechanisms of social avoidance learning can explain the emergence of adaptive and arbitrary behavioral traditions in humans.

Science.gov (United States)

Lindström, Björn; Olsson, Andreas

2015-06-01

Many nonhuman animals preferentially copy the actions of others when the environment contains predation risk or other types of danger. In humans, the role of social learning in avoidance of danger is still unknown, despite the fundamental importance of social learning for complex social behaviors. Critically, many social behaviors, such as cooperation and adherence to religious taboos, are maintained by threat of punishment. However, the psychological mechanisms allowing threat of punishment to generate such behaviors, even when actual punishment is rare or absent, are largely unknown. To address this, we used both computer simulations and behavioral experiments. First, we constructed a model where simulated agents interacted under threat of punishment and showed that mechanisms' (a) tendency to copy the actions of others through social learning, together with (b) the rewarding properties of avoiding a threatening punishment, could explain the emergence, maintenance, and transmission of large-scale behavioral traditions, both when punishment is common and when it is rare or nonexistent. To provide empirical support for our model, including the 2 mechanisms, we conducted 4 experiments, showing that humans, if threatened with punishment, are exceptionally prone to copy and transmit the behavior observed in others. Our results show that humans, similar to many nonhuman animals, use social learning if the environment is perceived as dangerous. We provide a novel psychological and computational basis for a range of human behaviors characterized by the threat of punishment, such as the adherence to cultural norms and religious taboos. (c) 2015 APA, all rights reserved).
Thermal-hydraulic and thermo-mechanical design of plasma facing components for SST-1 tokamak

International Nuclear Information System (INIS)

Chaudhuri, Paritosh; Santra, P.; Chenna Reddy, D.; Parashar, S.K.S.

2014-01-01

The Plasma Facing Components (PFCs) are one of the major sub-systems of ssT-1 tokamak. PFC of ssT-1 consisting of divertors, passive stabilizers, baffles and limiters are designed to be compatible for steady state operation. The main consideration in the design of the PFC cooling is the steady state heat removal of up to 1 MW/m 2 . The PFC has been designed to withstand the peak heat fluxes and also without significant erosion such that frequent replacement of the armor is not necessary. Design considerations included 2-D steady state and transient tile temperature distribution and resulting thermal loads in PFC during baking, and cooling, coolant parameters necessary to maintain optimum thermal-hydraulic design, and tile fitting mechanism. Finite Element (FE) models using ANSYS have been developed to carry out the heat transfer and stress analyses of the PFC to understand its thermal and mechanical behaviors. The results of the calculation led to a good understanding of the coolant flow behavior and the temperature distribution in the tube wall and the different parts of the PFC. Thermal analysis of the PFC is carried out with the purpose of evaluating the thermal mechanical behavior of PFCs. The detailed thermal-hydraulic and thermo-mechanical designs of PFCs of ssT-1 are discussed in this paper. (authors)
Development of a Mechanical Engineering Test Item Bank to promote learning outcomes-based education in Japanese and Indonesian higher education institutions

Directory of Open Access Journals (Sweden)

Jeffrey S. Cross

2017-11-01

Full Text Available Following on the 2008-2012 OECD Assessment of Higher Education Learning Outcomes (AHELO feasibility study of civil engineering, in Japan a mechanical engineering learning outcomes assessment working group was established within the National Institute of Education Research (NIER, which became the Tuning National Center for Japan. The purpose of the project is to develop among engineering faculty members, common understandings of engineering learning outcomes, through the collaborative process of test item development, scoring, and sharing of results. By substantiating abstract level learning outcomes into concrete level learning outcomes that are attainable and assessable, and through measuring and comparing the students’ achievement of learning outcomes, it is anticipated that faculty members will be able to draw practical implications for educational improvement at the program and course levels. The development of a mechanical engineering test item bank began with test item development workshops, which led to a series of trial tests, and then to a large scale test implementation in 2016 of 348 first semester master’s students in 9 institutions in Japan, using both multiple choice questions designed to measure the mastery of basic and engineering sciences, and a constructive response task designed to measure “how well students can think like an engineer.” The same set of test items were translated from Japanese into to English and Indonesian, and used to measure achievement of learning outcomes at Indonesia’s Institut Teknologi Bandung (ITB on 37 rising fourth year undergraduate students. This paper highlights how learning outcomes assessment can effectively facilitate learning outcomes-based education, by documenting the experience of Japanese and Indonesian mechanical engineering faculty members engaged in the NIER Test Item Bank project.First published online: 30 November 2017
Resting State EEG in Children With Learning Disabilities: An Independent Component Analysis Approach.

Science.gov (United States)

Jäncke, Lutz; Alahmadi, Nsreen

2016-01-01

In this study, the neurophysiological underpinnings of learning disabilities (LD) in children are examined using resting state EEG. We were particularly interested in the neurophysiological differences between children with learning disabilities not otherwise specified (LD-NOS), learning disabilities with verbal disabilities (LD-Verbal), and healthy control (HC) children. We applied 2 different approaches to examine the differences between the different groups. First, we calculated theta/beta and theta/alpha ratios in order to quantify the relationship between slow and fast EEG oscillations. Second, we used a recently developed method for analyzing spectral EEG, namely the group independent component analysis (gICA) model. Using these measures, we identified substantial differences between LD and HC children and between LD-NOS and LD-Verbal children in terms of their spectral EEG profiles. We obtained the following findings: (a) theta/beta and theta/alpha ratios were substantially larger in LD than in HC children, with no difference between LD-NOS and LD-Verbal children; (b) there was substantial slowing of EEG oscillations, especially for gICs located in frontal scalp positions, with LD-NOS children demonstrating the strongest slowing; (c) the estimated intracortical sources of these gICs were mostly located in brain areas involved in the control of executive functions, attention, planning, and language; and (d) the LD-Verbal children demonstrated substantial differences in EEG oscillations compared with LD-NOS children, and these differences were localized in language-related brain areas. The general pattern of atypical neurophysiological activation found in LD children suggests that they suffer from neurophysiological dysfunction in brain areas involved with the control of attention, executive functions, planning, and language functions. LD-Verbal children also demonstrate atypical activation, especially in language-related brain areas. These atypical
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.
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.
Using repetitive transcranial magnetic stimulation to study the underlying neural mechanisms of human motor learning and memory.

Science.gov (United States)

Censor, Nitzan; Cohen, Leonardo G

2011-01-01

In the last two decades, there has been a rapid development in the research of the physiological brain mechanisms underlying human motor learning and memory. While conventional memory research performed on animal models uses intracellular recordings, microfusion of protein inhibitors to specific brain areas and direct induction of focal brain lesions, human research has so far utilized predominantly behavioural approaches and indirect measurements of neural activity. Repetitive transcranial magnetic stimulation (rTMS), a safe non-invasive brain stimulation technique, enables the study of the functional role of specific cortical areas by evaluating the behavioural consequences of selective modulation of activity (excitation or inhibition) on memory generation and consolidation, contributing to the understanding of the neural substrates of motor learning. Depending on the parameters of stimulation, rTMS can also facilitate learning processes, presumably through purposeful modulation of excitability in specific brain regions. rTMS has also been used to gain valuable knowledge regarding the timeline of motor memory formation, from initial encoding to stabilization and long-term retention. In this review, we summarize insights gained using rTMS on the physiological and neural mechanisms of human motor learning and memory. We conclude by suggesting possible future research directions, some with direct clinical implications.
Mathematical sense-making in quantum mechanics: An initial peek

Science.gov (United States)

Dreyfus, Benjamin W.; Elby, Andrew; Gupta, Ayush; Sohr, Erin Ronayne

2017-12-01

Mathematical sense-making—looking for coherence between the structure of the mathematical formalism and causal or functional relations in the world—is a core component of physics expertise. Some physics education research studies have explored what mathematical sense-making looks like at the introductory physics level, while some historians and "science studies" have explored how expert physicists engage in it. What is largely missing, with a few exceptions, is theoretical and empirical work at the intermediate level—upper division physics students—especially when they are learning difficult new mathematical formalism. In this paper, we present analysis of a segment of video-recorded discussion between two students grappling with a quantum mechanics question to illustrate what mathematical sense-making can look like in quantum mechanics. We claim that mathematical sense-making is possible and productive for learning and problem solving in quantum mechanics. Mathematical sense-making in quantum mechanics is continuous in many ways with mathematical sense-making in introductory physics. However, in the context of quantum mechanics, the connections between formalism, intuitive conceptual schema, and the physical world become more compound (nested) and indirect. We illustrate these similarities and differences in part by proposing a new symbolic form, eigenvector eigenvalue, which is composed of multiple primitive symbolic forms.
Development and Evaluation of a Computer-Based Learning Environment for Teachers: Assessment of Learning Strategies in Learning Journals

Directory of Open Access Journals (Sweden)

Inga Glogger

2013-01-01

Full Text Available Training teachers to assess important components of self-regulated learning such as learning strategies is an important, yet somewhat neglected, aspect of the integration of self-regulated learning at school. Learning journals can be used to assess learning strategies in line with cyclical process models of self-regulated learning, allowing for rich formative feedback. Against this background, we developed a computer-based learning environment (CBLE that trains teachers to assess learning strategies with learning journals. The contents of the CBLE and its instructional design were derived from theory. The CBLE was further shaped by research in a design-based manner. Finally, in two evaluation studies, student teachers (N1=44; N2=89 worked with the CBLE. We analyzed satisfaction, interest, usability, and assessment skills. Additionally, in evaluation study 2, effects of an experimental variation on motivation and assessment skills were tested. We found high satisfaction, interest, and good usability, as well as satisfying assessment skills, after working with the CBLE. Results show that teachers can be trained to assess learning strategies in learning journals. The developed CBLE offers new perspectives on how to support teachers in fostering learning strategies as central component of effective self-regulated learning at school.
Euler principal component analysis

NARCIS (Netherlands)

Liwicki, Stephan; Tzimiropoulos, Georgios; Zafeiriou, Stefanos; Pantic, Maja

Principal Component Analysis (PCA) is perhaps the most prominent learning tool for dimensionality reduction in pattern recognition and computer vision. However, the ℓ 2-norm employed by standard PCA is not robust to outliers. In this paper, we propose a kernel PCA method for fast and robust PCA,
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.
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.
Needs Analysis of the English Writing Skill as the Base to Design the Learning Materials

Directory of Open Access Journals (Sweden)

Tenri Ampa Andi

2018-01-01

Full Text Available This research used a descriptive method. It was aimed at identifying students’ learning needs for the English writing skill as the base for designing the learning materials. Writing skill covered the analysis of the types of paragraph, types of text, the components of writing and paragraph development. The subjects of the research were the fourth semester students that consisted of 330 students. The samples were taken 15 % randomly, so the number of samples was 50 students. The research used a questionnaire as the instrument to get responses from the students about their learning needs. The results showed that the learning needs for the writing skills coped with the types of paragraph development, the types of text, and components of writing skill. The types of paragraph development included the ways by definition (79.7%, classification (67.0%, listing (59.3%, cause effect (47.7%, example (47.3%, and comparison (45.7%. The types of text consisted of description (66.0%, news items (59.7%, narration (58.7%, discussion (56.7%, recount (57.0%, and exposition (50.7%. The components of writing skill contained structure (79.6%, vocabulary (79.4%, content (62.0%, organisation (53.6% and mechanic (34.0%. The implication of the findings would be the base of teaching and learning process, especially in designing the learning materials for the English writing skill.
Computer-Aided College Algebra: Learning Components that Students Find Beneficial

Science.gov (United States)

Aichele, Douglas B.; Francisco, Cynthia; Utley, Juliana; Wescoatt, Benjamin

2011-01-01

A mixed-method study was conducted during the Fall 2008 semester to better understand the experiences of students participating in computer-aided instruction of College Algebra using the software MyMathLab. The learning environment included a computer learning system for the majority of the instruction, a support system via focus groups (weekly…
The Assurance of Learning Process Components and the Effects of Engaging Students in the Learning

Science.gov (United States)

Mosca, Joseph B.; Agacer, Gilder; Flaming, Linda; Buzza, John

2011-01-01

Assurance of learning process plays a major role in higher education and has increased the accountability on the part of instructors at all levels. This paper will discuss the role of assurance processes in teaching and the ways to measure these processes of student learning. The research focus will be to determine if student engagement in problem…
Professional development in sport psychology : relating learning experiences to learning outcomes

NARCIS (Netherlands)

Hutter, R. I. (Vana); Oldenhof-Veldman, Tanja; Pijpers, J. R. (Rob); Oudejans, Raôul R.D.

2017-01-01

To enhance the training of sport psychology consultants, it is important to know which learning experiences are useful for which components of professional development. We interviewed 15 novice consultants on their learning experiences related to 13 different topics. Traditional learning experiences
Brain and behavioral evidence for altered social learning mechanisms among women with assault-related posttraumatic stress disorder.

Science.gov (United States)

Cisler, Josh M; Bush, Keith; Scott Steele, J; Lenow, Jennifer K; Smitherman, Sonet; Kilts, Clinton D

2015-04-01

Current neurocircuitry models of PTSD focus on the neural mechanisms that mediate hypervigilance for threat and fear inhibition/extinction learning. Less focus has been directed towards explaining social deficits and heightened risk of revictimization observed among individuals with PTSD related to physical or sexual assault. The purpose of the present study was to foster more comprehensive theoretical models of PTSD by testing the hypothesis that assault-related PTSD is associated with behavioral impairments in a social trust and reciprocity task and corresponding alterations in the neural encoding of social learning mechanisms. Adult women with assault-related PTSD (n = 25) and control women (n = 15) completed a multi-trial trust game outside of the MRI scanner. A subset of these participants (15 with PTSD and 14 controls) also completed a social and non-social reinforcement learning task during 3T fMRI. Brain regions that encoded the computationally modeled parameters of value expectation, prediction error, and volatility (i.e., uncertainty) were defined and compared between groups. The PTSD group demonstrated slower learning rates during the trust game and social prediction errors had a lesser impact on subsequent investment decisions. PTSD was also associated with greater encoding of negative expected social outcomes in perigenual anterior cingulate cortex and bilateral middle frontal gyri, and greater encoding of social prediction errors in the left temporoparietal junction. These data suggest mechanisms of PTSD-related deficits in social functioning and heightened risk for re-victimization in assault victims; however, comorbidity in the PTSD group and the lack of a trauma-exposed control group temper conclusions about PTSD specifically. Copyright © 2015 Elsevier Ltd. All rights reserved.
Humanoid Cognitive Robots That Learn by Imitating: Implications for Consciousness Studies

Directory of Open Access Journals (Sweden)

James A. Reggia

2018-01-01

Full Text Available While the concept of a conscious machine is intriguing, producing such a machine remains controversial and challenging. Here, we describe how our work on creating a humanoid cognitive robot that learns to perform tasks via imitation learning relates to this issue. Our discussion is divided into three parts. First, we summarize our previous framework for advancing the understanding of the nature of phenomenal consciousness. This framework is based on identifying computational correlates of consciousness. Second, we describe a cognitive robotic system that we recently developed that learns to perform tasks by imitating human-provided demonstrations. This humanoid robot uses cause–effect reasoning to infer a demonstrator’s intentions in performing a task, rather than just imitating the observed actions verbatim. In particular, its cognitive components center on top-down control of a working memory that retains the explanatory interpretations that the robot constructs during learning. Finally, we describe our ongoing work that is focused on converting our robot’s imitation learning cognitive system into purely neurocomputational form, including both its low-level cognitive neuromotor components, its use of working memory, and its causal reasoning mechanisms. Based on our initial results, we argue that the top-down cognitive control of working memory, and in particular its gating mechanisms, is an important potential computational correlate of consciousness in humanoid robots. We conclude that developing high-level neurocognitive control systems for cognitive robots and using them to search for computational correlates of consciousness provides an important approach to advancing our understanding of consciousness, and that it provides a credible and achievable route to ultimately developing a phenomenally conscious machine.

Introduction of subsidisation in nascent climate-friendly learning technologies and evaluation of its effectiveness

International Nuclear Information System (INIS)

Rout, Ullash K.; Akimoto, Keigo; Sano, Fuminori; Tomoda, Toshimasa

2010-01-01

Given its importance as a practical phenomenon underlying the progress of learning technologies, attention should be paid to the role of subsidisation in learning theory, particularly in the case of nascent climate-related sociable learning technologies, in order to examine its benefits. Thus, this study focuses on subsidy procurement of energy technologies in several economies in the context of the component learning track in endogenous global clusters in order to suggest improvements to the adoption mechanism and examine the climate stabilization constraint. At the same time, the study attempts to determine the global progress ratio of the lithium-ion battery in order to analyse various endogenous learning scenarios for hybrid technologies. An integrated energy system model with highly disaggregated global regions (DNE21+) is used to execute this research in a medium time frame. Subsidisation of the learning track of battery technology encourages greater development of plug-in hybrid vehicles, promotes early diffusion of hybrid technologies, and relieves heavy dependency on crude oil and biofuels. The subsidies in the common learning domains in few economies benefit the nearby economies because of the technology spillover that occurs through numerous cross-feedback learning mechanisms. Endogenous learning with subsidies augments diffusion potentials, abates emissions, and shifts sectoral emissions.
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

2017-06-01

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 various situations that appear to be counterintuitive and contradict classical notions of particles and waves. For example, if we send single electrons through the slits, they may behave as a "wave" in part of the experiment and as a "particle" in another part of the same experiment. Here we discuss the development and evaluation of a research-validated Quantum Interactive Learning Tutorial (QuILT) which makes use of an interactive simulation to improve student understanding of the double-slit experiment and strives to help students develop a good grasp of foundational issues in quantum mechanics. We discuss common student difficulties identified during the development and evaluation of the QuILT and analyze the data from the pretest and post test administered to the upper-level undergraduate and first-year physics graduate students before and after they worked on the QuILT to assess its effectiveness. These data suggest that on average, the QuILT was effective in helping students develop a more robust understanding of foundational concepts in quantum mechanics that defy classical intuition using the context of the double-slit experiment. Moreover, upper-level undergraduates outperformed physics graduate students on the post test. One possible reason for this difference in performance may be the level of student engagement with the QuILT due to the grade incentive. In the undergraduate course, the post test was graded for correctness while in the graduate course, it was only graded for completeness.
Quantum interactive learning tutorial on the double-slit experiment to improve student understanding of quantum mechanics

Directory of Open Access Journals (Sweden)

Ryan Sayer

2017-05-01

Full Text Available 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 various situations that appear to be counterintuitive and contradict classical notions of particles and waves. For example, if we send single electrons through the slits, they may behave as a “wave” in part of the experiment and as a “particle” in another part of the same experiment. Here we discuss the development and evaluation of a research-validated Quantum Interactive Learning Tutorial (QuILT which makes use of an interactive simulation to improve student understanding of the double-slit experiment and strives to help students develop a good grasp of foundational issues in quantum mechanics. We discuss common student difficulties identified during the development and evaluation of the QuILT and analyze the data from the pretest and post test administered to the upper-level undergraduate and first-year physics graduate students before and after they worked on the QuILT to assess its effectiveness. These data suggest that on average, the QuILT was effective in helping students develop a more robust understanding of foundational concepts in quantum mechanics that defy classical intuition using the context of the double-slit experiment. Moreover, upper-level undergraduates outperformed physics graduate students on the post test. One possible reason for this difference in performance may be the level of student engagement with the QuILT due to the grade incentive. In the undergraduate course, the post test was graded for correctness while in the graduate course, it was only graded for completeness.
Control component retainer

International Nuclear Information System (INIS)

Walton, L.A.; King, R.A.

1983-01-01

An apparatus is described for retaining an undriven control component assembly disposed in a fuel assembly in a nuclear reactor of the type having a core grid plate. The first part of the mechanism involves a housing for the control component and the second part is a brace with a number of arms that reach under the grid plate. The brace and the housing are coupled together to firmly hold the control components in place even under strong flows of th coolant
Reliability calculation of cracked components using probabilistic fracture mechanics and a Markovian approach

International Nuclear Information System (INIS)

Schmidt, T.

1988-01-01

The numerical reliability calculation of cracked construction components under cyclical fatigue stress can be done with the help of models of probabilistic fracture mechanics. An alternative to the Monte Carlo simulation method is examined; the alternative method is based on the description of failure processes with the help of a Markov process. The Markov method is traced back directly to the stochastic parameters of a two-dimensional fracture mechanics model, the effects of inspections and repairs also being considered. The probability of failure and expected failure frequency can be determined as time functions with the transition and conditional probabilities of the original or derived Markov process. For concrete calculation, an approximative Markov chain is designed which, under certain conditions, is capable of giving a sufficient approximation of the original Markov process and the reliability characteristics determined by it. The application of the MARKOV program code developed into an algorithm reveals sufficient conformity with the Monte Carlo reference results. The starting point of the investigation was the 'Deutsche Risikostudie B (DWR)' ('German Risk Study B (DWR)'), specifically, the reliability of the main coolant line. (orig./HP) [de
Life-time management for mechanical components; Lebensdauermanagement mechanischer Komponenten

Energy Technology Data Exchange (ETDEWEB)

Roos, E. [Stuttgart Univ. (DE). Materialpruefungsanstalt (MPA)

2006-07-01

The safety and economic efficiency of industrial systems depend on the quality of components and systems. In the field of power generation, power plants should be safe and have high availability and minimum specific generation cost. Life management is essential for this. Depending on the safety relevance of systems, structures and components (SSC), this includes proofs of integrity, time-oriented or condition-oriented preventive maintenance, or just failure-oriented maintenance. (orig.)
Students’ learning processes during school-based learning and workplace learning in vocational education : a review

NARCIS (Netherlands)

Schaap, H.; Baartman, L.K.J.; Bruijn, de E.

2012-01-01

Learning in vocational schools and workplaces are the two main components of vocational education. Students have to develop professional competences by building meaningful relations between knowledge, skills and attitudes. There are, however, some major concerns about the combination of learning in
Learning by Starch Potato Growers: Learning in Small Businesses with No Employees

Science.gov (United States)

Faber, Niels R.; Maruster, Laura; Jorna, Rene J.; van Haren, Rob J. F.

2012-01-01

In small businesses with no employees, learning environments have a low learning readiness. Consequently, learners need to rely on their own agency to shape their learning experiences. Results from a study of agricultural entrepreneurs indicated that the components of motivation and self-regulated learning strategies shape learner's agency and…
Professional Learning through Everyday Work: How Finance Professionals Self-Regulate Their Learning

Science.gov (United States)

Littlejohn, Allison; Milligan, Colin; Fontana, Rosa Pia; Margaryan, Anoush

2016-01-01

Professional learning is a critical component of ongoing improvement and innovation and the adoption of new practices in the workplace. Professional learning is often achieved through learning embedded in everyday work tasks. However, little is known about how professionals self-regulate their learning through regular work activities. This paper…
Learning induces the translin/trax RNase complex to express activin receptors for persistent memory.

Science.gov (United States)

Park, Alan Jung; Havekes, Robbert; Fu, Xiuping; Hansen, Rolf; Tudor, Jennifer C; Peixoto, Lucia; Li, Zhi; Wu, Yen-Ching; Poplawski, Shane G; Baraban, Jay M; Abel, Ted

2017-09-20

Long-lasting forms of synaptic plasticity and memory require de novo protein synthesis. Yet, how learning triggers this process to form memory is unclear. Translin/trax is a candidate to drive this learning-induced memory mechanism by suppressing microRNA-mediated translational silencing at activated synapses. We find that mice lacking translin/trax display defects in synaptic tagging, which requires protein synthesis at activated synapses, and long-term memory. Hippocampal samples harvested from these mice following learning show increases in several disease-related microRNAs targeting the activin A receptor type 1C (ACVR1C), a component of the transforming growth factor-β receptor superfamily. Furthermore, the absence of translin/trax abolishes synaptic upregulation of ACVR1C protein after learning. Finally, synaptic tagging and long-term memory deficits in mice lacking translin/trax are mimicked by ACVR1C inhibition. Thus, we define a new memory mechanism by which learning reverses microRNA-mediated silencing of the novel plasticity protein ACVR1C via translin/trax.
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.
Does temperament affect learning in calves?

DEFF Research Database (Denmark)

Webb, Laura E.; van Reenen, Cornelis G.; Jensen, Margit Bak

2015-01-01

challenge tests, may affect learning an operant conditioning task in calves. Understanding how temperament affects learning in calves can help with the training of calves on novel automated feeding apparatuses or on novel feed components, and can thus help improve calf health and welfare.......The aim of the study was to investigate how temperament affects learning ability in calves. Nine two-month-old Holstein-Friesian bull calves were subjected to four challenge tests: novel object (NOT), novel environment (NET), social isolation (SIT), and social isolation with a novel environmental...... cue (SI/E). During these tests, hypothesised temperament variables were recorded. Hypothesised learning variables were recorded during training on an operant task. Principal component analysis (PCA) was conducted on temperament variables and learning variables separately. Principal components (PCs...
Shape distortion and thermo-mechanical properties of SOFC components from green tape to sintering body

DEFF Research Database (Denmark)

Teocoli, Francesca; Ni, De Wei; Tadesse Molla, Tesfaye

due to binder burn out, differential shrinkage behavior and to a potential interfacial reaction between the two materials. To analyze the phenomena, shrinkage of SOFC components single layers and bilayered samples were measured insitu by optical dilatometer. The densification mismatch stress, due...... to the strain rate difference between materials, was calculated using Cai’s model. Camber (curvature) development for in situ co-firing of a bi-layer ceramic green tape has been investigated. Analysis of shape evolution from green to sintered body can be carried out by the thermo-mechanical analysis techniques....
Innovative Approaches to Large Component Packaging

International Nuclear Information System (INIS)

Freitag, A.; Hooper, M.; Posivak, E.; Sullivan, J.

2006-01-01

Radioactive waste disposal often times requires creative approaches in packaging design, especially for large components. Innovative design techniques are required to meet the needs for handling, transporting, and disposing of these large packages. Large components (i.e., Reactor Pressure Vessel (RPV) heads and even RPVs themselves) require special packaging for shielding and contamination control, as well as for transport and disposal. WMG Inc designed and used standard packaging for RPV heads without control rod drive mechanisms (CRDMs) attached for five RPV heads and has also more recently met an even bigger challenge and developed the innovative Intact Vessel Head Transport System (IVHTS) for RPV heads with CRDMs intact. This packaging system has been given a manufacturer's exemption by the United States Department of Transportation (USDOT) for packaging RPV heads. The IVHTS packaging has now been successfully used at two commercial nuclear power plants. Another example of innovative packaging is the large component packaging that WMG designed, fabricated, and utilized at the West Valley Demonstration Project (WVDP). In 2002, West Valley's high-level waste vitrification process was shut down in preparation for D and D of the West Valley Vitrification Facility. Three of the major components of concern within the Vitrification Facility were the Melter, the Concentrate Feed Makeup Tank (CFMT), and the Melter Feed Holdup Tank (MFHT). The removal, packaging, and disposition of these three components presented significant radiological and handling challenges for the project. WMG designed, fabricated, and installed special packaging for the transport and disposal of each of these three components, which eliminated an otherwise time intensive and costly segmentation process that WVDP was considering. Finally, WMG has also designed and fabricated special packaging for both the Connecticut Yankee (CY) and San Onofre Nuclear Generating Station (SONGS) RPVs. This paper
Infant Statistical Learning

Science.gov (United States)

Saffran, Jenny R.; Kirkham, Natasha Z.

2017-01-01

Perception involves making sense of a dynamic, multimodal environment. In the absence of mechanisms capable of exploiting the statistical patterns in the natural world, infants would face an insurmountable computational problem. Infant statistical learning mechanisms facilitate the detection of structure. These abilities allow the infant to compute across elements in their environmental input, extracting patterns for further processing and subsequent learning. In this selective review, we summarize findings that show that statistical learning is both a broad and flexible mechanism (supporting learning from different modalities across many different content areas) and input specific (shifting computations depending on the type of input and goal of learning). We suggest that statistical learning not only provides a framework for studying language development and object knowledge in constrained laboratory settings, but also allows researchers to tackle real-world problems, such as multilingualism, the role of ever-changing learning environments, and differential developmental trajectories. PMID:28793812
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...
Mechanical development for reliable reactor components

International Nuclear Information System (INIS)

Ross-Ross, P.A.; Metcalfe, R.

1983-09-01

The CANDU reactor has achieved worldwide distinction because of its reliable performance. To achieve this, special attention was given to the reliability and maintainability of components in the heavy water circuits. Development programs were initiated early in the history of the CANDU reactor to improve the effectiveness of pump seals, valves, and static seals because of unacceptable performance of the commercial equipment then available. As a result, pump seals with a five year life now appear achievable, and valves and static seals are no longer a significant concern in CANDU reactors. Increasing effort is being given remotely operated tools and fabrication systems for radioactive environments
Component reliability for electronic systems

CERN Document Server

Bajenescu, Titu-Marius I

2010-01-01

The main reason for the premature breakdown of today's electronic products (computers, cars, tools, appliances, etc.) is the failure of the components used to build these products. Today professionals are looking for effective ways to minimize the degradation of electronic components to help ensure longer-lasting, more technically sound products and systems. This practical book offers engineers specific guidance on how to design more reliable components and build more reliable electronic systems. Professionals learn how to optimize a virtual component prototype, accurately monitor product reliability during the entire production process, and add the burn-in and selection procedures that are the most appropriate for the intended applications. Moreover, the book helps system designers ensure that all components are correctly applied, margins are adequate, wear-out failure modes are prevented during the expected duration of life, and system interfaces cannot lead to failure.
The mechanical design and dynamic testing of the IBEX-H1 electrostatic analyzer spacecraft instrument

Energy Technology Data Exchange (ETDEWEB)

Bernardin, John D [Los Alamos National Laboratory; Baca, Allen G [SNL

2009-01-01

This paper presents the mechanical design, fabrication and dynamic testing of an electrostatic analyzer spacecraft instrument. The functional and environmental requirements combined with limited spacecraft accommodations, resulted in complex component geometries, unique material selections, and difficult fabrication processes. The challenging aspects of the mechanical design and several of the more difficult production processes are discussed. In addition, the successes, failures, and lessons learned from acoustic and random vibration testing of a full-scale prototype instrument are presented.
The Purdue Mechanics Freeform Classroom: A New Approach to Engineering Mechanics Education

OpenAIRE

Rhoads, Jeffrey F.; Nauman, Eric; Holloway, Beth M; Krousgrill, Charles Morton

2014-01-01

The [REMOVED] Mechanics Freeform Classroom: A New Approach to Engineering Mechanics EducationMotivated by the need to address the broad spectrum of learning styles embraced by today’sengineering students, a desire to encourage active, peer-to-peer, and self-learning, and a goal ofinteracting with every student despite ever-expanding enrollments, the mechanics faculty at[REMOVED] University have developed the [REMOVED] Mechanics Freeform Classroom(PMFC) -- a new approach to engineering mechani...

Development of standard components for remote handling

International Nuclear Information System (INIS)

Taguchi, Kou; Kakudate, Satoshi; Nakahira, Masataka; Ito, Akira

1998-01-01

The core of Fusion Experimental Reactor consists of various components such as superconducting magnets and forced-cooled in-vessel components, which are remotely maintained due to intense of gamma radiation. Mechanical connectors such as cooling pipe connections, insulation joints and electrical connectors are commonly used for maintenance of these components and have to be standardized in terms of remote handling. This paper describes these mechanical connectors developed as the standard component compatible with remote handling and tolerable for radiation. (author)
Development of standard components for remote handling

Energy Technology Data Exchange (ETDEWEB)

Taguchi, Kou; Kakudate, Satoshi; Nakahira, Masataka; Ito, Akira [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment

1998-04-01

The core of Fusion Experimental Reactor consists of various components such as superconducting magnets and forced-cooled in-vessel components, which are remotely maintained due to intense of gamma radiation. Mechanical connectors such as cooling pipe connections, insulation joints and electrical connectors are commonly used for maintenance of these components and have to be standardized in terms of remote handling. This paper describes these mechanical connectors developed as the standard component compatible with remote handling and tolerable for radiation. (author)
Interactive simulations as teaching tools for engineering mechanics courses

Science.gov (United States)

Carbonell, Victoria; Romero, Carlos; Martínez, Elvira; Flórez, Mercedes

2013-07-01

This study aimed to gauge the effect of interactive simulations in class as an active teaching strategy for a mechanics course. Engineering analysis and design often use the properties of planar sections in calculations. In the stress analysis of a beam under bending and torsional loads, cross-sectional properties are used to determine stress and displacement distributions in the beam cross section. The centroid, moments and products of inertia of an area made up of several common shapes (rectangles usually) may thus be obtained by adding the moments of inertia of the component areas (U-shape, L-shape, C-shape, etc). This procedure is used to calculate the second moments of structural shapes in engineering practice because the determination of their moments of inertia is necessary for the design of structural components. This paper presents examples of interactive simulations developed for teaching the ‘Mechanics and mechanisms’ course at the Universidad Politecnica de Madrid, Spain. The simulations focus on fundamental topics such as centroids, the properties of the moment of inertia, second moments of inertia with respect to two axes, principal moments of inertia and Mohr's Circle for plane stress, and were composed using Geogebra software. These learning tools feature animations, graphics and interactivity and were designed to encourage student participation and engagement in active learning activities, to effectively explain and illustrate course topics, and to build student problem-solving skills.
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.
The mechanical behavior and reliability prediction of the HTR graphite component at various temperature and neutron dose ranges

International Nuclear Information System (INIS)

Fang, Xiang; Yu, Suyuan; Wang, Haitao; Li, Chenfeng

2014-01-01

Highlights: • The mechanical behavior of graphite component in HTRs under high temperature and neutron irradiation conditions is simulated. • The computational process of mechanical analysis is introduced. • Deformation, stresses and failure probability of the graphite component are obtained and discussed. • Various temperature and neutron dose ranges are selected in order to investigate the effect of in-core conditions on the results. - Abstract: In a pebble-bed high temperature gas-cooled reactor (HTR), nuclear graphite serves as the main structural material of the side reflectors. The reactor core is made up of a large number of graphite bricks. In the normal operation case of the reactor, the maximum temperature of the helium coolant commonly reaches about 750 °C. After around 30 years’ full power operation, the peak value of in-core fast neutron cumulative dose reaches to 1 × 10 22 n cm −2 (EDN). Such high temperature and neutron irradiation strongly impact the behavior of graphite component, causing obvious deformation. The temperature and neutron dose are unevenly distributed inside a graphite brick, resulting in stress concentrations. The deformation and stress concentration can both greatly affect safety and reliability of the graphite component. In addition, most of the graphite properties (such as Young's modulus and coefficient of thermal expansion) change remarkably under high temperature and neutron irradiations. The irradiation-induced creep also plays a very important role during the whole process, and provides a significant impact on the stress accumulation. In order to simulate the behavior of graphite component under various in-core conditions, all of the above factors must be considered carefully. In this paper, the deformation, stress distribution and failure probability of a side graphite component are studied at various temperature points and neutron dose levels. 400 °C, 500 °C, 600 °C and 750 °C are selected as the
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,…
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.
Forecast of reliability for mechanical components subjected to wearing; Pronostico de la fiabilidad de componentes mecanicos sometidos a desgaste

Energy Technology Data Exchange (ETDEWEB)

Angulo-Zevallos, J.; Castellote-Varona, C.; Alanbari, M.

2010-07-01

Generally, improving quality and price of products, obtaining a complete customer satisfaction and achieving excellence in all the processes are some of the challenges currently set up by every company. To do this, knowing frequently the reliability of some component is necessary. To achieve this goal, a research, that contributes with clear ideas and offers a methodology for the assessment of the parameters involved in the reliability calculation, becomes necessary. A parameter closely related to this concept is the probability of product failure depending on the operating time. It is known that mechanical components fail by: creep, fatigue, wear, corrosion, etc. This article proposes a methodology for finding the reliability of a component subject to wear, such as brake pads, grinding wheels, brake linings of clutch discs, etc. (Author)
Mechanical and barrier properties of starch-based films plasticized with two- or three component deep eutectic solvents.

Science.gov (United States)

Zdanowicz, Magdalena; Johansson, Caisa

2016-10-20

The aim of this work was to prepare two- and three-components deep eutectic solvents (DES) and investigate their potential as starch plasticizers. Starch/DES films were prepared via casting method. Mechanical properties, water vapor- and oxygen transmission rates were measured; additionally contact angle and moisture sorption were determined and FTIR analysis was applied on the films. Native potato starch and hydroxypropylated and oxidized starch (HOPS) with common plasticizers (e.g. polyols, urea) and DES were studied. Moreover, influence of three methods of DES introduction and concentration of plasticizer on the films properties were compared. HOPS films were prepared by two methods: as non-cured and cured samples. Some of DESs containing citrate anion exhibited crosslinking ability of polysaccharide matrix. Non-cured HOPS/DES films exhibited more favourable mechanical and barrier properties than cured analogue films. Samples prepared with unmodified potato starch had higher mechanical and barrier properties than films made with HOPS. Starch-based films plasticized with novel DESs with parallel crosslinking activity exhibited satisfactory mechanical and barrier properties. Copyright © 2016 Elsevier Ltd. All rights reserved.
Metal binding by food components

DEFF Research Database (Denmark)

Tang, Ning

for zinc binding by the investigated amino acids, peptides and proteins. The thiol group or imidazole group containing amino acids, peptides and proteins which exhibited strong zinc binding ability were further selected for interacting with zinc salts in relation to zinc absorption. The interactions...... between the above selected food components and zinc citrate or zinc phytate will lead to the enhanced solubility of zinc citrate or zinc phytate. The main driving force for this observed solubility enhancement is the complex formation between zinc and investigated food components as revealed by isothermal...... titration calorimetry and quantum mechanical calculations. This is due to the zinc binding affinity of the relatively softer ligands (investigated food components) will become much stronger than citrate or phytate when they present together in aqueous solution. This mechanism indicates these food components...
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...
Intelligent Web-Based Learning System with Personalized Learning Path Guidance

Science.gov (United States)

Chen, C. M.

2008-01-01

Personalized curriculum sequencing is an important research issue for web-based learning systems because no fixed learning paths will be appropriate for all learners. Therefore, many researchers focused on developing e-learning systems with personalized learning mechanisms to assist on-line web-based learning and adaptively provide learning paths…
Theoretical physics 6 quantum mechanics : basics

CERN Document Server

Nolting, Wolfgang

2017-01-01

This textbook offers a clear and comprehensive introduction to the basics of quantum mechanics, one of the core components of undergraduate physics courses. It follows on naturally from the previous volumes in this series, thus developing the physical understanding further on to quantized states. The first part of the book introduces wave equations while exploring the Schrödinger equation and the hydrogen atom. More complex themes are covered in the second part of the book, which describes the Dirac formulism of quantum mechanics. Ideally suited to undergraduate students with some grounding in classical mechanics and electrodynamics, the book is enhanced throughout with learning features such as boxed inserts and chapter summaries, with key mathematical derivations highlighted to aid understanding. The text is supported by numerous worked examples and end of chapter problem sets. About the Theoretical Physics series Translated from the renowned and highly successful German editions, the eight volumes of this...
CRITICAL COMPONENTS OF ONLINE LEARNING READINESS AND THEIR RELATIONSHIPS WITH LEARNER ACHIEVEMENT

Directory of Open Access Journals (Sweden)

Harun CIGDEM

2016-04-01

Full Text Available This study aimed to examine the relationship between certain factors of online learning readiness and learners’ end-of-course achievements. The study was conducted at a two-year post-secondary Turkish military school within the scope of the course titled Computer Literacy, which was designed and implemented in a blended way. The data were collected from 155 post-secondary military students through an online questionnaire. Three sub-scales of Hung et al.’s Online Learning Readiness Scale were used to collect the data during the first two weeks of the course. Descriptive and inferential statistics, such as Pearson correlation coefficients and linear regression analyses were performed to analyze the data. The descriptive results of the study indicated that students’ motivation for online learning was higher than both their computer/Internet self-efficacy and their orientations to self-directed learning. The inferential results revealed that the students’ end-of-course grades had significantly positive relationships with their computer/Internet self-efficacy and self-directed learning orientations. Finally, the students’ self-direction towards online learning appeared to be the strongest predictor of their achievements within the course; whereas computer/Internet self-efficacy and motivation for learning did not predict the learner achievement significantly.
Component design for LMFBR's

International Nuclear Information System (INIS)

Fillnow, R.H.; France, L.L.; Zerinvary, M.C.; Fox, R.O.

1975-01-01

Just as FFTF has prototype components to confirm their design, FFTF is serving as a prototype for the design of the commercial LMFBR's. Design and manufacture of critical components for the FFTF system have been accomplished primarily using vendors with little or no previous experience in supplying components for high temperature sodium systems. The exposure of these suppliers, and through them a multitude of subcontractors, to the requirements of this program has been a necessary and significant step in preparing American industry for the task of supplying the large mechanical components required for commercial LMFBR's
Placebo Mechanisms of Manual Therapy: A Sheep in Wolf's Clothing?

Science.gov (United States)

Bialosky, Joel E; Bishop, Mark D; Penza, Charles W

2017-05-01

When a physical therapist provides a manual therapy (MT) intervention for a patient presenting with pain and the patient experiences a positive clinical outcome, we cannot answer as to why this occurs. Would we continue to devote valuable time and financial resources to learning and improving our skills in providing MT interventions if the related clinical outcomes were placebo responses? In this Viewpoint, the authors conceptualize placebo as an active and important mechanism of MT and argue that placebo mechanisms deserve consideration as an important component of the treatment effect. J Orthop Sports Phys Ther 2017;47(5):301-304. doi:10.2519/jospt.2017.0604.
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.
Study on the Safety Classification Criteria of Mechanical Systems and Components for Open Pool-Type Research Reactors

International Nuclear Information System (INIS)

Belal, Al Momani; Jo, Jong Chull

2013-01-01

This paper describes a new compromised safety classification approach based on the comparative study of the different practices in safety classification of mechanical systems and components of open pool-type RRs, which have been adopted by several developed countries in the nuclear power area. It is hoped that the proposed safety classification criteria will be used to develop a harmonized consensus international standard. Different safety classification criteria for systems, structures, and components (SSCs) of nuclear reactors are used among the countries that export or import nuclear reactor technology, which may make the nuclear technology trade and exchange difficult. Thus, such various different approaches of safety classification need to be compromised to establish a global standard. This article proposes practicable optimized criteria for safety classification of SSCs for open pool-type research reactors (RRs)
Study on the Safety Classification Criteria of Mechanical Systems and Components for Open Pool-Type Research Reactors

Energy Technology Data Exchange (ETDEWEB)

Belal, Al Momani [Korea Advanced Institute of Science and Technology, Daejeon (Korea, Republic of); Jo, Jong Chull [Korea Institute of Nuclear Safety, Daejeon (Korea, Republic of)

2013-10-15

This paper describes a new compromised safety classification approach based on the comparative study of the different practices in safety classification of mechanical systems and components of open pool-type RRs, which have been adopted by several developed countries in the nuclear power area. It is hoped that the proposed safety classification criteria will be used to develop a harmonized consensus international standard. Different safety classification criteria for systems, structures, and components (SSCs) of nuclear reactors are used among the countries that export or import nuclear reactor technology, which may make the nuclear technology trade and exchange difficult. Thus, such various different approaches of safety classification need to be compromised to establish a global standard. This article proposes practicable optimized criteria for safety classification of SSCs for open pool-type research reactors (RRs)
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...

Movement Sonification: Audiovisual benefits on motor learning

Directory of Open Access Journals (Sweden)

Weber Andreas

2011-12-01

Full Text Available Processes of motor control and learning in sports as well as in motor rehabilitation are based on perceptual functions and emergent motor representations. Here a new method of movement sonification is described which is designed to tune in more comprehensively the auditory system into motor perception to enhance motor learning. Usually silent features of the cyclic movement pattern "indoor rowing" are sonified in real time to make them additionally available to the auditory system when executing the movement. Via real time sonification movement perception can be enhanced in terms of temporal precision and multi-channel integration. But beside the contribution of a single perceptual channel to motor perception and motor representation also mechanisms of multisensory integration can be addressed, if movement sonification is configured adequately: Multimodal motor representations consisting of at least visual, auditory and proprioceptive components - can be shaped subtly resulting in more precise motor control and enhanced motor learning.
Multidimensionality of Teachers' Graded Responses for Preschoolers' Stylistic Learning Behavior: The Learning-to-Learn Scales

Science.gov (United States)

McDermott, Paul A.; Fantuzzo, John W.; Warley, Heather P.; Waterman, Clare; Angelo, Lauren E.; Gadsden, Vivian L.; Sekino, Yumiko

2011-01-01

Assessment of preschool learning behavior has become very popular as a mechanism to inform cognitive development and promote successful interventions. The most widely used measures offer sound predictions but distinguish only a few types of stylistic learning and lack sensitive growth detection. The Learning-to-Learn Scales was designed to…
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…
A real-time standard parts inspection based on deep learning

Science.gov (United States)

Xu, Kuan; Li, XuDong; Jiang, Hongzhi; Zhao, Huijie

2017-10-01

Since standard parts are necessary components in mechanical structure like bogie and connector. These mechanical structures will be shattered or loosen if standard parts are lost. So real-time standard parts inspection systems are essential to guarantee their safety. Researchers would like to take inspection systems based on deep learning because it works well in image with complex backgrounds which is common in standard parts inspection situation. A typical inspection detection system contains two basic components: feature extractors and object classifiers. For the object classifier, Region Proposal Network (RPN) is one of the most essential architectures in most state-of-art object detection systems. However, in the basic RPN architecture, the proposals of Region of Interest (ROI) have fixed sizes (9 anchors for each pixel), they are effective but they waste much computing resources and time. In standard parts detection situations, standard parts have given size, thus we can manually choose sizes of anchors based on the ground-truths through machine learning. The experiments prove that we could use 2 anchors to achieve almost the same accuracy and recall rate. Basically, our standard parts detection system could reach 15fps on NVIDIA GTX1080 (GPU), while achieving detection accuracy 90.01% mAP.
Peer-Assisted Learning Programme: Supporting Students in High-Risk Subjects at the Mechanical Engineering Department at Walter Sisulu University

Directory of Open Access Journals (Sweden)

Makala Qonda

2017-12-01

Full Text Available The majority of the students who enroll at the Walter Sisulu University (WSU in South Africa are not equipped with the necessary academic/learning skills to cope with the university environment, especially in Mechanical Engineering. The Department of Higher Education and Training (2013, p. 17, further states that “students’ support is crucial to ensure that students adapt to the demands of college life and that they can meet the demands of college programmes”. Particularly in South Africa, the school environment might also contribute to poor student performance as a result of insufficient student support, and a lack of facilities and resources. In order to address this gap, a Peer-Assisted Learning (PAL programme was implemented to provide support targeting high-risk subjects for at-risk students in Mechanical Engineering at WSU. The programme therefore is pro-active and student-driven in that senior students assist junior students with their academic work and learning processes. The programme is designed to encourage collaborative and cooperative learning approaches during group sessions and active student engagement to support student learning (Laal & Laal, 2012. The programme requires substantial resources and time commitments. It is important from an operational, learning, and student perspective to understand in what ways the PAL programme assists students (if at all. Eliciting the experiences of students also helps the department to design interventions from a student-centred perspective using the lens of learning theories. This qualitative case study explores the student experience of the Peer-Assisted Learning (PAL programme. Open-ended questionnaires/survey from 20 first-year students elicited their perceptions and experiences of the PAL programme. Responses were analysed thematically. Findings indicated that the students had useful insights that may contribute to revising the programme. Aspects mentioned were improved study
Component Architectures and Web-Based Learning Environments

Science.gov (United States)

Ferdig, Richard E.; Mishra, Punya; Zhao, Yong

2004-01-01

The Web has caught the attention of many educators as an efficient communication medium and content delivery system. But we feel there is another aspect of the Web that has not been given the attention it deserves. We call this aspect of the Web its "component architecture." Briefly it means that on the Web one can develop very complex…
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.
Bioactive components and mechanisms of Chinese poplar propolis alleviates oxidized low-density lipoprotein-induced endothelial cells injury.

Science.gov (United States)

Chang, Huasong; Yuan, Wenwen; Wu, Haizhu; Yin, Xusheng; Xuan, Hongzhuan

2018-05-03

Propolis, a polyphenol-rich natural product, has been used as a functional food in anti-inflammation. However, its bioactive components and mechanisms have not been fully elucidated. To discover the bioactive components and anti-inflammatory mechanism, we prepared and separated 8 subfractions from ethyl acetate extract of Chinese propolis (EACP) and investigated the mechanism in oxidized low density lipoprotein (ox-LDL) induced human umbilical vein endothelial cells (HUVECs) damage. Eight subfractions were prepared and separated from ethyl acetate extract of Chinese propolis (EACP) with different concentrations of methanol-water solution, and analysed its chemical constituents by HPLC-DAD/Q-TOF-MS. Then 80% confluent HUVECs were stimulated with 40 μg/mL ox-LDL. Cell viability and apoptosis were evaluated by Sulforhodamine B (SRB) assay and Hoechst 33,258 staining, respectively. Levels of caspase 3, PARP, LC3B, p62, p-mTOR, p-p70S6K, p-PI3K, p-Akt, LOX-1 and p-p38 MAPK were assessed by western blotting and immunofluorescence assay, respectively. Reactive oxygen species (ROS) and mitochondrial membrane potential (MMP) were measured with fluorescent probes. Each subfraction exhibited similar protective effect although the contents of chemical constituents were different. EACP attenuated ox-LDL induced HUVECs apoptosis, depressed the ratio of LC3-II/LC3-I and enhanced the p62 level. In addition, treatment with EACP also activated the phosphorylation of PI3K/Akt/mTOR, and deactivated the level of LOX-1 and phosphorylation of p38 MAPK. The overproduction of ROS and the damage of MMP were also ameliorated after ECAP treatment. These findings indicated that the bioactive component of propolis on anti-inflammatory activity was not determined by a single constituent, but a complex interaction including flavonoids, esters and phenolic acids. EACP attenuated ox-LDL induced HUVECs injury by inhibiting LOX-1 level and depressed ROS production against oxidative stress in ox
Quality Control Activities Related to Mechanical Maintenance of Safety Related Components at Krsko NPP

International Nuclear Information System (INIS)

Djakovic, D.

2016-01-01

For successful, safe and reliable operation of nuclear power plant, maintenance processes have to be systematically controlled and procedures for quality control of maintenance activities shall be established. This is requested by the quality assurance program, which shall provide control over activities affecting the quality of structures, systems, and components, considering their importance to safety. As a part of Quality and Nuclear Oversight Division (QNOD; SKV), the Quality Control Department (QC) provides quality control activities, which are deeply involved in maintenance processes at Krsko NPP, both on safety related and non-safety related (non-nuclear safety) components. QC activities on safety related components have to fulfil all requirements, which will enable the components to perform their intended safety functions. This paper describes quality control activities related to mechanical maintenance of safety related components at Krsko NPP and significant role of the Krsko plant QC Department in three particular maintenance cases connected with safety related components. In these three specific cases, the QC has confirmed its importance in compliance with quality assurance program and presented its significant added value in providing safe and reliable operation of the plant. The first maintenance activity was installation of nozzle check valves in the scope of a modification for improving regulation of spent fuel pit pumps. The QC Department performed receipt inspection of the valves. Using non-destructive examination methods and X-ray spectrometry, it was found out that the valve diffuser was made of improper material, which could cause progressive corrosion of the valve diffuser in borated water and consequently a loss of safety function of the valves followed by long-term consequences. The second one was the receipt inspection of containment ventilation fan coolers. The coolers were claimed and sent back to the supplier because the QC Department
High concentration of vitamin E decreases thermosensation and thermotaxis learning and the underlying mechanisms in the nematode Caenorhabditis elegans.

Science.gov (United States)

Li, Yiping; Li, Yinxia; Wu, Qiuli; Ye, Huayue; Sun, Lingmei; Ye, Boping; Wang, Dayong

2013-01-01

α-tocopherol is a powerful liposoluble antioxidant and the most abundant isoform of vitamin E in the body. Under normal physiological conditions, adverse effects of relatively high concentration of vitamin E on organisms and the underlying mechanisms are still largely unclear. In the present study, we used the nematode Caenorhabditis elegans as an in vivo assay system to investigate the possible adverse effects of high concentration of vitamin E on thermosensation and thermotaxis learning and the underlying mechanisms. Our data show that treatment with 100-200 µg/mL of vitamin E did not noticeably influence both thermosensation and thermotaxis learning; however, treatment with 400 µg/mL of vitamin E altered both thermosensation and thermotaxis learning. The observed decrease in thermotaxis learning in 400 µg/mL of vitamin E treated nematodes might be partially due to the moderate but significant deficits in thermosensation, but not due to deficits in locomotion behavior or perception to food and starvation. Treatment with 400 µg/mL of vitamin E did not noticeably influence the morphology of GABAergic neurons, but significantly decreased fluorescent intensities of the cell bodies in AFD sensory neurons and AIY interneurons, required for thermosensation and thermotaxis learning control. Treatment with 400 µg/mL of vitamin E affected presynaptic function of neurons, but had no remarkable effects on postsynaptic function. Moreover, promotion of synaptic transmission by activating PKC-1 effectively retrieved deficits in both thermosensation and thermotaxis learning induced by 400 µg/mL of vitamin E. Therefore, relatively high concentrations of vitamin E administration may cause adverse effects on thermosensation and thermotaxis learning by inducing damage on the development of specific neurons and presynaptic function under normal physiological conditions in C. elegans.
Learning Groups in MOOCs: Lessons for Online Learning in Higher Education

Directory of Open Access Journals (Sweden)

Godfrey Mayende

2017-06-01

Full Text Available when there is interaction within online learning groups, meaningful learning is achieved. Motivating and sustaining effective student interactions requires planning, coordination and implementation of curriculum, pedagogy and technology. For our aim to understand online learning group processes to identify effective online learning group mechanisms, comparative analysis was used on a massive open online course (MOOC run in 2015 and 2016. Qualitative (interaction on the platform and quantitative (survey methods were used. The findings revealed several possible ways to improve online learning group processes. This paper concludes that course organization helped in increasing individual participation in the groups. Motivation by peers helped to increase sustainability of interaction in the learning groups. Applying these mechanisms in higher education can make online learning groups more effective.
Enrichment of the metallic components from waste printed circuit boards by a mechanical separation process using a stamp mill

International Nuclear Information System (INIS)

Yoo, Jae-Min; Jeong, Jinki; Yoo, Kyoungkeun; Lee, Jae-chun; Kim, Wonbaek

2009-01-01

Printed circuit boards incorporated in most electrical and electronic equipment contain valuable metals such as Cu, Ni, Au, Ag, Pd, Fe, Sn, and Pb. In order to employ a hydrometallurgical route for the recycling of valuable metals from printed circuit boards, a mechanical pre-treatment step is needed. In this study, the metallic components from waste printed circuit boards have been enriched using a mechanical separation process. Waste printed circuit boards shredded to 5.0 mm. The fractions of milled printed circuit boards of size 5.0 mm fraction and the heavy fraction were subjected to two-step magnetic separation. Through the first magnetic separation at 700 Gauss, 83% of the nickel and iron, based on the whole printed circuit boards, was recovered in the magnetic fraction, and 92% of the copper was recovered in the non-magnetic fraction. The cumulative recovery of nickel-iron concentrate was increased by a second magnetic separation at 3000 Gauss, but the grade of the concentrate decreased remarkably from 76% to 56%. The cumulative recovery of copper concentrate decreased, but the grade increased slightly from 71.6% to 75.4%. This study has demonstrated the feasibility of the mechanical separation process consisting of milling/size classification/gravity separation/two-step magnetic separation for enriching metallic components such as Cu, Ni, Al, and Fe from waste printed circuit boards
Deciphering the Cognitive and Neural Mechanisms Underlying ...

International Development Research Centre (IDRC) Digital Library (Canada)

Deciphering the Cognitive and Neural Mechanisms Underlying Auditory Learning. This project seeks to understand the brain mechanisms necessary for people to learn to perceive sounds. Neural circuits and learning. The research team will test people with and without musical training to evaluate their capacity to learn ...
ONE PROBABLE MECHANISM OF THE LEARNING-MEMORY DAMAGE BY LEAD: THE CHANGES OF NOS IN HIPPOCAMPUS

Institute of Scientific and Technical Information of China (English)

王静; 赵义; 杨章民; 张进; 李积胜; 司履生; 王一理

2003-01-01

Objective To study the effects of lead on the activity and expression of nitric oxide synthase (NOS) and relationship between the effects of lead on learning-memory and changes of NOS in subfields of hippocampus. Methods Y-maze test was used to study the effects of lead on ability of learning-memory; NADPH-d histochemistry and immunohistochemistry methods were used to investigate the changes of NOS in subfields of hippocampus. Results Compared with the control group, the ability of learning- memory in lead-exposed rats was significantly decreased (P＜0.05); the number of NOS positive neurons in CA1 region and dentate gyrus of lead-exposed rats was significantly decreased(P＜0.05), but no marked changes in CA3 region; the number of nNOS positive neurons in CA1 of lead-exposed rats was also significantly decreased(P＜0.05), but no obvious changes in CA3. Conclusion Lead could damage the ability of learning-memory in rats. Lead could decrease the activity and expression of NOS in hippocampus and had different effects on NOS in different subfields of hippocampus. The changes of NOS in hippocampus induced by lead may be the mechanism of the learning-memory damage by lead.
Language Learning Enhanced by Massive Multiple Online Role-Playing Games (MMORPGs) and the Underlying Behavioral and Neural Mechanisms

Science.gov (United States)

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 application of the MMORPGs based on relevant macroscopic and microscopic studies, showing that gamers’ overall language proficiency or some specific language skills can be enhanced by real-time online interaction with peers and game narratives or instructions embedded in the MMORPGs. Mechanisms underlying the educational assistant role of MMORPGs in second language learning are discussed from both behavioral and neural perspectives. We suggest that attentional bias makes gamers/learners allocate more cognitive resources toward task-related stimuli in a controlled or an automatic way. Moreover, with a moderating role played by activation of reward circuit, playing the MMORPGs may strengthen or increase functional connectivity from seed regions such as left anterior insular/frontal operculum (AI/FO) and visual word form area to other language-related brain areas. PMID:28303097
Language Learning Enhanced by Massive Multiple Online Role-Playing Games (MMORPGs) and the Underlying Behavioral and Neural Mechanisms.

Science.gov (United States)

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 application of the MMORPGs based on relevant macroscopic and microscopic studies, showing that gamers' overall language proficiency or some specific language skills can be enhanced by real-time online interaction with peers and game narratives or instructions embedded in the MMORPGs. Mechanisms underlying the educational assistant role of MMORPGs in second language learning are discussed from both behavioral and neural perspectives. We suggest that attentional bias makes gamers/learners allocate more cognitive resources toward task-related stimuli in a controlled or an automatic way. Moreover, with a moderating role played by activation of reward circuit, playing the MMORPGs may strengthen or increase functional connectivity from seed regions such as left anterior insular/frontal operculum (AI/FO) and visual word form area to other language-related brain areas.
Global view of the mechanisms of improved learning and memory capability in mice with music-exposure by microarray.

Science.gov (United States)

Meng, Bo; Zhu, Shujia; Li, Shijia; Zeng, Qingwen; Mei, Bing

2009-08-28

Music has been proved beneficial to improve learning and memory in many species including human in previous research work. Although some genes have been identified to contribute to the mechanisms, it is believed that the effect of music is manifold, behind which must concern a complex regulation network. To further understand the mechanisms, we exposed the mice to classical music for one month. The subsequent behavioral experiments showed improvement of spatial learning capability and elevation of fear-motivated memory in the mice with music-exposure as compared to the naïve mice. Meanwhile, we applied the microarray to compare the gene expression profiles of the hippocampus and cortex between the mice with music-exposure and the naïve mice. The results showed approximately 454 genes in cortex (200 genes up-regulated and 254 genes down-regulated) and 437 genes in hippocampus (256 genes up-regulated and 181 genes down-regulated) were significantly affected in music-exposing mice, which mainly involved in ion channel activity and/or synaptic transmission, cytoskeleton, development, transcription, hormone activity. Our work may provide some hints for better understanding the effects of music on learning and memory.
Fracture-mechanical investigations on the propagation of heat-tension-cracks, in boittle multi-component media

International Nuclear Information System (INIS)

Grebner, H.

1983-01-01

The quasistatic dissipation of thermically induced cracks in brittle multi-components material with plane boundary areas is studied. The distribution of Eigentension, which is causing the dissipation of cracks, is produced by cooling the composite material from the production temperature to room temperature. Tension distributions, respectively of the fracture-mechanical coefficients were determined by solving of the boundary value problems of the theory of plane thermoelasticity, a based on existence of a plane distortion state, respectively of a plane state of tension. Because of the complicated shape of the free surface one adopted a numerical solution, the finite-element method, to solve the corresponding mixed boundary value problems. (orig.) [de
Web Log Pre-processing and Analysis for Generation of Learning Profiles in Adaptive E-learning

Directory of Open Access Journals (Sweden)

Radhika M. Pai

2016-03-01

Full Text Available Adaptive E-learning Systems (AESs enhance the efficiency of online courses in education by providing personalized contents and user interfaces that changes according to learner’s requirements and usage patterns. This paper presents the approach to generate learning profile of each learner which helps to identify the learning styles and provide Adaptive User Interface which includes adaptive learning components and learning material. The proposed method analyzes the captured web usage data to identify the learning profile of the learners. The learning profiles are identified by an algorithmic approach that is based on the frequency of accessing the materials and the time spent on the various learning components on the portal. The captured log data is pre-processed and converted into standard XML format to generate learners sequence data corresponding to the different sessions and time spent. The learning style model adopted in this approach is Felder-Silverman Learning Style Model (FSLSM. This paper also presents the analysis of learner’s activities, preprocessed XML files and generated sequences.
Web Log Pre-processing and Analysis for Generation of Learning Profiles in Adaptive E-learning

Directory of Open Access Journals (Sweden)

Radhika M. Pai

2016-04-01

Full Text Available Adaptive E-learning Systems (AESs enhance the efficiency of online courses in education by providing personalized contents and user interfaces that changes according to learner’s requirements and usage patterns. This paper presents the approach to generate learning profile of each learner which helps to identify the learning styles and provide Adaptive User Interface which includes adaptive learning components and learning material. The proposed method analyzes the captured web usage data to identify the learning profile of the learners. The learning profiles are identified by an algorithmic approach that is based on the frequency of accessing the materials and the time spent on the various learning components on the portal. The captured log data is pre-processed and converted into standard XML format to generate learners sequence data corresponding to the different sessions and time spent. The learning style model adopted in this approach is Felder-Silverman Learning Style Model (FSLSM. This paper also presents the analysis of learner’s activities, preprocessed XML files and generated sequences.

Engaging Environments Enhance Motor Skill Learning in a Computer Gaming Task.

Science.gov (United States)

Lohse, Keith R; Boyd, Lara A; Hodges, Nicola J

2016-01-01

Engagement during practice can motivate a learner to practice more, hence having indirect effects on learning through increased practice. However, it is not known whether engagement can also have a direct effect on learning when the amount of practice is held constant. To address this question, 40 participants played a video game that contained an embedded repeated sequence component, under either highly engaging conditions (the game group) or mechanically identical but less engaging conditions (the sterile group). The game environment facilitated retention over a 1-week interval. Specifically, the game group improved in both speed and accuracy for random and repeated trials, suggesting a general motor-related improvement, rather than a specific influence of engagement on implicit sequence learning. These data provide initial evidence that increased engagement during practice has a direct effect on generalized learning, improving retention and transfer of a complex motor skill.
Spatio temporal media components for neurofeedback

DEFF Research Database (Denmark)

Jensen, Camilla Birgitte Falk; Petersen, Michael Kai; Larsen, Jakob Eg

2013-01-01

A class of Brain Computer Interfaces (BCI) involves interfaces for neurofeedback training, where a user can learn to self-regulate brain activity based on real-time feedback. These particular interfaces are constructed from audio-visual components and temporal settings, which appear to have...... a strong influence on the ability to control brain activity. Therefore, identifying the different interface components and exploring their individual effects might be key for constructing new interfaces that support more efficient neurofeedback training. We discuss experiments involving two different...
Interactive simulations as teaching tools for engineering mechanics courses

International Nuclear Information System (INIS)

Carbonell, Victoria; Martínez, Elvira; Flórez, Mercedes; Romero, Carlos

2013-01-01

This study aimed to gauge the effect of interactive simulations in class as an active teaching strategy for a mechanics course. Engineering analysis and design often use the properties of planar sections in calculations. In the stress analysis of a beam under bending and torsional loads, cross-sectional properties are used to determine stress and displacement distributions in the beam cross section. The centroid, moments and products of inertia of an area made up of several common shapes (rectangles usually) may thus be obtained by adding the moments of inertia of the component areas (U-shape, L-shape, C-shape, etc). This procedure is used to calculate the second moments of structural shapes in engineering practice because the determination of their moments of inertia is necessary for the design of structural components. This paper presents examples of interactive simulations developed for teaching the ‘Mechanics and mechanisms’ course at the Universidad Politecnica de Madrid, Spain. The simulations focus on fundamental topics such as centroids, the properties of the moment of inertia, second moments of inertia with respect to two axes, principal moments of inertia and Mohr's Circle for plane stress, and were composed using Geogebra software. These learning tools feature animations, graphics and interactivity and were designed to encourage student participation and engagement in active learning activities, to effectively explain and illustrate course topics, and to build student problem-solving skills. (paper)
Contribution to improving reliability assessments of mechanical structural components requiring a high degree of safety using weighted Monte Carlo simulation

Energy Technology Data Exchange (ETDEWEB)

Kutter, R

1981-12-04

Physical theories to inquire lifetime and reliability of mechanical structures or components under multiscale random stress do not exist. Today those dates were examinated e.g. in development of aircrafts and motorcars by fatigue-testing of original components and sections during long terms. Knowing the distributions of stress and material-parameters the same testing is to be realized simulationary on highspeed computers. This study gives methods to reduce the necessary computation time to attending ones even to proof reliability up to R=1-10/sup -9/. These methods were of Monte-Carlo-Simulation with weighted parameters and respect to life-history.
Are All Program Elements Created Equal? Relations Between Specific Social and Emotional Learning Components and Teacher-Student Classroom Interaction Quality.

Science.gov (United States)

Abry, Tashia; Rimm-Kaufman, Sara E; Curby, Timothy W

2017-02-01

School-based social and emotional learning (SEL) programs are presented to educators with little understanding of the program components that have the greatest leverage for improving targeted outcomes. Conducted in the context of a randomized controlled trial, the present study used variation in treatment teachers' (N = 143) implementation of four core components of the Responsive Classroom approach to examine relations between each component and the quality of teachers' emotional, organizational, and instructional interactions in third, fourth, and fifth grade classrooms (controlling for pre-intervention interaction quality and other covariates). We also examined the extent to which these relations varied as a function of teachers' baseline levels of interaction quality. Indices of teachers' implementation of Morning Meeting, Rule Creation, Interactive Modeling, and Academic Choice were derived from a combination of teacher-reported surveys and classroom observations. Ratings of teacher-student classroom interactions were aggregated across five observations conducted throughout the school year. Structural path models indicated that teachers' use of Morning Meeting and Academic Choice related to higher levels of emotionally supportive interactions; Academic Choice also related to higher levels of instructional interactions. In addition, teachers' baseline interaction quality moderated several associations such that the strongest relations between RC component use and interaction quality emerged for teachers with the lowest baseline interaction quality. Results highlight the value of examining individual program components toward the identification of program active ingredients that can inform intervention optimization and teacher professional development.
The effect of melliferous bee (Apis mellifera carnica poll and mechanical means on seed yield, yield components and quality of alfalfa seed (Medicago sativa L

Directory of Open Access Journals (Sweden)

Jevtić Goran

2005-01-01

Full Text Available Number of alfalfa pollinators in free pollination was investigated as well as effect of measures that promote pollination alfalfa (using sugar syrup and mechanical means. In first year of investigations, with higher precipitation, higher number of others pollinators (80,8 then honeybees (45,6 on alfalfa field was determined. In second year, there were much more honeybees (139,5 then all others alfalfa pollinators (12,37. Pollination improvement with sugar syrup had positive effect on seed yield and seed yield components since by this way more seeds were obtained compare to free pollination and by using mechanical means. Highest seed yield was obtained with sugar syrup (44,90 gm-2, with mechanical improvement of pollination 40,74 gm-2 and in free pollination 30,41 gm-2. As for yield components pollination improvement gave better results compare to free pollination. Pod setting and number of seeds per pod were especially significant compare to control. There were no statistically significant differences between free pollination and improved pollination for seed quality components (mass of 1000 seeds, energy of germination and germination ability.
The Academic Library and the Culture for Learning

Science.gov (United States)

Hufford, Jon R.

2016-01-01

Several components of a campus culture affect learning, yet assessments regularly neglect some of them. Academic librarians should evaluate how they impact courses and student learning through their support of these neglected components. Assessment goals to address some of the components include measuring the level of support for courses with…
LEARNING TECHNOLOGIES FOR STUDENTS IN THE CLOUD ORIENTED LEARNING ENVIRONMENT OF COMPREHENSIVE EDUCATIONAL INSTITUTIONS

Directory of Open Access Journals (Sweden)

Svitlana G. Lytvynova

2015-06-01

Full Text Available The paper analyzes the «flipped» learning and «Web Quest» technologies. The features of the «flipped» learning technology are generalized, as well as compared with traditional learning, clarified the benefits of the technology for teachers and students, described the features of the technology used by teacher and students, developed a teacher’s and student’s flow chart for preparation to the lesson, generalized control and motivation components for activating learning activities of students, found out that a component of cloud oriented learning environment (COLE – Lync (Skype Pro can be used to develop video clips and support «flipped» learning technology. The author defines the concept of «Web Quest» technology, generalizes the «Web Quest» structure components. In the article the functions, features of this technology, the types of problems that can be solved with the help of this technology, as well as «Web Quest» classification are presented. It has been found out that the cloud oriented learning environment gives all the possibilities for «Web Quest» technology implementation in teaching of different subjects of all branches of science. With the help of «flipped» technology training and «Web Quest» a number of important problems of education can be solved – providing the continuous communication intensive training beyond general educational establishment and activation of learning activities of students.
Nanomechanical characterization of adaptive optics components in microprojectors

International Nuclear Information System (INIS)

Palacio, Manuel; Bhushan, Bharat

2010-01-01

Compact microprojectors are being developed for information display in mobile electronic devices. A key component of the microprojector is the green laser package, which consists of an adaptive optics component with a drive mechanism. A crucial concern is the mechanical wear of key drive mechanism components, such as the carbon fiber reinforced polymer (CFRP) driving rod, the Zn alloy body and the stainless steel friction plate, after prolonged operation. Since friction and wear are dependent on the mechanical properties, nanoindentation experiments were conducted on these drive mechanism components using a depth-sensing nanoindenter at room and elevated temperatures up to 100 °C. The hardness and elastic modulus of all the materials studied decrease at increasing test temperatures. From plasticity index analysis, a correlation between the tendency for plastic deformation and the mechanical properties was obtained. Nanoscratch studies were also conducted in order to simulate wear, as well as examine the scratch resistance and deformation modes of these materials, where it was found that the CFRP rod exhibited the highest scratch resistance. The CFRP rod undergoes mostly brittle deformation, while the Zn alloy body and friction plate undergo plastic deformation.
Deep Learning in Open Source Learning Streams

DEFF Research Database (Denmark)

Kjærgaard, Thomas

2016-01-01

This chapter presents research on deep learning in a digital learning environment and raises the question if digital instructional designs can catalyze deeper learning than traditional classroom teaching. As a theoretical point of departure the notion of ‘situated learning’ is utilized...... and contrasted to the notion of functionalistic learning in a digital context. The mechanism that enables deep learning in this context is ‘The Open Source Learning Stream’. ‘The Open Source Learning Stream’ is the notion of sharing ‘learning instances’ in a digital space (discussion board, Facebook group......, unistructural, multistructural or relational learning. The research concludes that ‘The Open Source Learning Stream’ can catalyze deep learning and that there are four types of ‘Open Source Learning streams’; individual/ asynchronous, individual/synchronous, shared/asynchronous and shared...
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).
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).
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…
Latent semantics as cognitive components

DEFF Research Database (Denmark)

Petersen, Michael Kai; Mørup, Morten; Hansen, Lars Kai

2010-01-01

Cognitive component analysis, defined as an unsupervised learning of features resembling human comprehension, suggests that the sensory structures we perceive might often be modeled by reducing dimensionality and treating objects in space and time as linear mixtures incorporating sparsity...... emotional responses can be encoded in words, we propose a simplified cognitive approach to model how we perceive media. Representing song lyrics in a vector space of reduced dimensionality using LSA, we combine bottom-up defined term distances with affective adjectives, that top-down constrain the latent......, which we suggest might function as cognitive components for perceiving the underlying structure in lyrics....
Genetic component in learning ability in bees.

Science.gov (United States)

Kerr, W E; Moura Duarte, F A; Oliveira, R S

1975-10-01

Twenty-five bees, five from each of five hives, were trained to collect food at a table. When the bee reached the table, time was recorded for 12 visits. Then a blue and yellow pan was substituted for the original metal pan, and time and correct responses were recorded for 30 trips (discrimination phase). Finally, food was taken from the pan and extinction was recorded as incorrect responses for 20 visits. Variance analysis was carried out, and genetic variance was undetected for discrimination, but was detected for extinction. It is concluded that learning is very important for bees, so that any impairment in such ability affects colony survival.
Component Commonality and Its Cost Implications - Increasing the Commonality of the Right Components

DEFF Research Database (Denmark)

Lyly-Yrjänäinen, Jouni; Suomala, Petri; Israelsen, Poul

Component commonality (Labro 2004, Zhou & Gruppström 2004) can be defined as the use of the same version of a component across multiple products. It is usually seen as a means to manage costs without sacrificing product variety. However, when managing costs with component commonality, the managers...... constructions was identified as the most important bottleneck for the delivery process causing many indirect costs, especially with respect to project-management-related activities. Interestingly, by eliminating the need for mechanical engineering, the context starts to approach assembly-to-order context, also...... should be able to identify rather rapidly which group of components would enable the most significant cost reductions. Unfortunately, the existing literature lacks profound discussion of how to identify the right components for increased component commonality. The objective of the paper is to discuss how...
Autonomous development and learning in artificial intelligence and robotics: Scaling up deep learning to human-like learning.

Science.gov (United States)

Oudeyer, Pierre-Yves

2017-01-01

Autonomous lifelong development and learning are fundamental capabilities of humans, differentiating them from current deep learning systems. However, other branches of artificial intelligence have designed crucial ingredients towards autonomous learning: curiosity and intrinsic motivation, social learning and natural interaction with peers, and embodiment. These mechanisms guide exploration and autonomous choice of goals, and integrating them with deep learning opens stimulating perspectives.
Mechanics of brazed joints and compliant layers in high heat flux components

International Nuclear Information System (INIS)

Lovato, G.; Moret, F.; Chaumat, G.

1994-01-01

Soft layers are of great interest for the joining of dissimilar materials like beryllium, tungsten or carbon base refractory tiles for plasma interface and cooled structures made of copper or molybdenum. Soft layers reduce the residual and in-service stress/strain level without reducing the thermal capability. Thin soft layers interfaces are produced during the brazing or HIP bonding cycles. However, the numerical modelling of the mechanical effect of such soft layers remains largely inaccurate. The camber of [CFC tiles (A05, N11, N112)/Ag-Cu-Ti filler metal/OFHC or TZM substrate] assemblies is recorded during the whole brazing thermal cycle and subsequent thermal fatigue cycles using a special vertical dilatometer. An inverse method based on Finite Element modelling of the samples is used to determine the joint constitutive law. Then, by comparing experiments and FEM calculations, the effects of distributed damage of the CFC and of the strain hardening and thermal softening of OFHC on the in-service stress/strain state of the component are observed. (authors). 5 refs., 7 figs
Quantum-mechanical predictions of electron-induced ionization cross sections of DNA components

International Nuclear Information System (INIS)

Champion, Christophe

2013-01-01

Ionization of biomolecules remains still today rarely investigated on both the experimental and the theoretical sides. In this context, the present work appears as one of the first quantum mechanical approaches providing a multi-differential description of the electron-induced ionization process of the main DNA components for impact energies ranging from the target ionization threshold up to about 10 keV. The cross section calculations are here performed within the 1st Born approximation framework in which the ejected electron is described by a Coulomb wave whereas the incident and the scattered electrons are both described by a plane wave. The biological targets of interest, namely, the DNA nucleobases and the sugar-phosphate backbone, are here described by means of the GAUSSIAN 09 system using the restricted Hartree-Fock method with geometry optimization. The theoretical predictions also obtained have shown a reasonable agreement with the experimental total ionization cross sections while huge discrepancies have been pointed out with existing theoretical models, mainly developed within a semi-classical framework.
Mechanics of brazed joints and compliant layers in high heat flux components

International Nuclear Information System (INIS)

Lovato, G.; Moret, F.; Chaumat, G.; Cailletaud, G.; Pilvin, P.

1995-01-01

Soft layers are of great interest for the joining of dissimilar materials like beryllium, tungsten or carbone base refractory tiles for plasma interface and cooled structures made of copper or molybdenum. Soft layers reduce the residual and in-service stress/strain level without reducing the thermal capability. Thin soft layers interfaces are produced during the brazing or HIP bonding cycles. However, the numerical modelling of the mechanical effect of such soft layers remains largely inaccurate. The camber of [CFC tiles (A05, N11, N112)/Ag-Cu-Ti filler metal/OFHC or TZM substrate] assemblies is recorded during the whole brazing thermal cycle and subsequent thermal fatigue cycles using a special vertical dilatometer. An inverse method based on Finite Element modelling of the samples is used to determine the joint constitutive law. Then, by comparing experiments and FEM calculations, the effects of distributed damage of the CFC and of the strain hardening and thermal softening of OFHC on the in-service stress/strain state of the component are observed. (orig.)

The Pellini test as a brittle fracture criterion for components and for the determination of the application limits of fracture mechanics

International Nuclear Information System (INIS)

Schulze, H.D.

1976-01-01

Linear-elastic fracture mechanics have made it possible to make the brittle behaviour of cracks in components accessible for a description. The concepts envisaging an extension to yield point mechanics as well, which would allow the behaviour of cracks with large plastic deformations at the tip of the crack to be described, are at present not perfected enough yet to be applied in practice. The Pellini concept with its semi-quantitative statements closes at present this gap. (orig./RW) [de
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…
Curcumin, a component of golden spice: from bedside to bench and back.

Science.gov (United States)

Prasad, Sahdeo; Gupta, Subash C; Tyagi, Amit K; Aggarwal, Bharat B

2014-11-01

Although the history of the golden spice turmeric (Curcuma longa) goes back thousands of years, it is only within the past century that we learned about the chemistry of its active component, curcumin. More than 6000 articles published within the past two decades have discussed the molecular basis for the antioxidant, anti-inflammatory, antibacterial, antiviral, antifungal, and anticancer activities assigned to this nutraceutical. Over sixty five clinical trials conducted on this molecules, have shed light on the role of curcumin in various chronic conditions, including autoimmune, cardiovascular, neurological, and psychological diseases, as well as diabetes and cancer. The current review provides an overview of the history, chemistry, analogs, and mechanism of action of curcumin. Published by Elsevier Inc.
Learning Analytics to Understand Cultural Impacts on Technology Enhanced Learning

Science.gov (United States)

Mittelmeier, Jenna; Tempelaar, Dirk; Rienties, Bart; Nguyen, Quan

2016-01-01

In this empirical study, we investigate the role of national cultural dimensions as distal antecedents of the use intensity of e-tutorials, which constitute the digital component within a blended learning course. Profiting from the context of a dispositional learning analytics application, we investigate cognitive processing strategies and…
Statistical Mechanics of On-line Learning When a Moving Teacher Goes around an Unlearnable True Teacher

Science.gov (United States)

Urakami, Masahiro; Miyoshi, Seiji; Okada, Masato

2007-04-01

In the framework of on-line learning, a learning machine might move around a teacher due to the differences in structures or output functions between the teacher and the learning machine. In this paper we analyze the generalization performance of a new student supervised by a moving machine. A model composed of a fixed true teacher, a moving teacher, and a student is treated theoretically using statistical mechanics, where the true teacher is a nonmonotonic perceptron and the others are simple perceptrons. Calculating the generalization errors numerically, we show that the generalization errors of a student can temporarily become smaller than that of a moving teacher and can reach the lowest value, even if the student only uses examples from the moving teacher. However, the generalization error of the student eventually becomes the same value with that of the moving teacher. This behavior is qualitatively different from that of a linear model.
Turing mechanism for homeostatic control of synaptic density during C. elegans growth

Science.gov (United States)

Brooks, Heather A.; Bressloff, Paul C.

2017-07-01

We propose a mechanism for the homeostatic control of synapses along the ventral cord of Caenorhabditis elegans during development, based on a form of Turing pattern formation on a growing domain. C. elegans is an important animal model for understanding cellular mechanisms underlying learning and memory. Our mathematical model consists of two interacting chemical species, where one is passively diffusing and the other is actively trafficked by molecular motors, which switch between forward and backward moving states (bidirectional transport). This differs significantly from the standard mechanism for Turing pattern formation based on the interaction between fast and slow diffusing species. We derive evolution equations for the chemical concentrations on a slowly growing one-dimensional domain, and use numerical simulations to demonstrate the insertion of new concentration peaks as the length increases. Taking the passive component to be the protein kinase CaMKII and the active component to be the glutamate receptor GLR-1, we interpret the concentration peaks as sites of new synapses along the length of C. elegans, and thus show how the density of synaptic sites can be maintained.
Student Autonomy and its Effects on Student Enjoyment in a Traditional Mechanics Course for First-Year Engineering Students

Science.gov (United States)

Perera, Janaki I.; Quinlivan, Brendan T.; Simonovich, Jennifer A.; Towers, Emily; Zadik, Oren H.; Zastavker, Yevgeniya V.

2012-02-01

In light of recent literature in educational psychology, this study investigates instructional support and students' autonomy at a small technical undergraduate school. Grounded theory is used to analyze twelve semi-structured open-ended interviews about engineering students' experiences in Introductory Mechanics that includes Lecture, Recitation, and Laboratory components. Using data triangulation with each course component as a unit of analysis, this study examines students' course enjoyment as a function of instructional support and autonomy. The Lecture utilizes traditional instructor-centered pedagogy with predominantly passive learning and no student autonomy. The Recitation creates an active learning environment through small group work with a moderate degree of autonomy. The Laboratory is designed around self-guided project-based activities with significant autonomy. Despite these differences, all three course components provide similar levels of instructional support. The data reveal that students enjoy the low autonomy provided by Lecture and Recitations while finding the Laboratory frustrating. Analyses indicate that the differences in autonomy contribute to students' misinterpretation of the three course components' value within the context of the entire course.
Geophysical Factor Resolving of Rainfall Mechanism for Super Typhoons by Using Multiple Spatiotemporal Components Analysis

Science.gov (United States)

Huang, Chien-Lin; Hsu, Nien-Sheng

2016-04-01

This study develops a novel methodology to resolve the geophysical cause of typhoon-induced rainfall considering diverse dynamic co-evolution at multiple spatiotemporal components. The multi-order hidden patterns of complex hydrological process in chaos are detected to understand the fundamental laws of rainfall mechanism. The discovered spatiotemporal features are utilized to develop a state-of-the-art descriptive statistical model for mechanism validation, modeling and further prediction during typhoons. The time series of hourly typhoon precipitation from different types of moving track, atmospheric field and landforms are respectively precede the signal analytical process to qualify each type of rainfall cause and to quantify the corresponding affected degree based on the measured geophysical atmospheric-hydrological variables. This study applies the developed methodology in Taiwan Island which is constituted by complex diverse landform formation. The identified driving-causes include: (1) cloud height to ground surface; (2) co-movement effect induced by typhoon wind field with monsoon; (3) stem capacity; (4) interaction between typhoon rain band and terrain; (5) structural intensity variance of typhoon; and (6) integrated cloudy density of rain band. Results show that: (1) for the central maximum wind speed exceeding 51 m/sec, Causes (1) and (3) are the primary ones to generate rainfall; (2) for the typhoon moving toward the direction of 155° to 175°, Cause (2) is the primary one; (3) for the direction of 90° to 155°, Cause (4) is the primary one; (4) for the typhoon passing through mountain chain which above 3500 m, Cause (5) is the primary one; and (5) for the moving speed lower than 18 km/hr, Cause (6) is the primary one. Besides, the multiple geophysical component-based precipitation modeling can achieve 81% of average accuracy and 0.732 of average correlation coefficient (CC) within average 46 hours of duration, that improve their predictability.
Applications of probabilistic fracture mechanics to FBR components

International Nuclear Information System (INIS)

Yagawa, Genki; Yoshimura, Shinobu; Takenaka, Makoto; Hojo, Kiminobu; Kaguchi, Hitoshi.

1991-01-01

A probabilistic fracture mechanics code PCCF which could analyze half-elliptical crack behavior in a plate under creep-fatigue condition using nonlinear fracture mechanics parameters was developed. The effects of bending stress level on failure probability was studied using the PCCF as test analyses. As the results, failure mode was leakage not break in all cases analyzed in this study. It is shown that leak probability is sensitive to stress level and increase rapidly around yield stress of materials. (J.P.N.)
Autophosphorylation of [alpha]CaMKII is Differentially Involved in New Learning and Unlearning Mechanisms of Memory Extinction

Science.gov (United States)

Kimura, Ryoichi; Silva, Alcino J.; Ohno, Masuo

2008-01-01

Accumulating evidence indicates the key role of [alpha]-calcium/calmodulin-dependent protein kinase II ([alpha]CaMKII) in synaptic plasticity and learning, but it remains unclear how this kinase participates in the processing of memory extinction. Here, we investigated the mechanism by which [alpha]CaMKII may mediate extinction by using…
Ab initio Algorithmic Causal Deconvolution of Intertwined Programs and Networks by Generative Mechanism

KAUST Repository

Zenil, Hector

2018-02-18

To extract and learn representations leading to generative mechanisms from data, especially without making arbitrary decisions and biased assumptions, is a central challenge in most areas of scientific research particularly in connection to current major limitations of influential topics and methods of machine and deep learning as they have often lost sight of the model component. Complex data is usually produced by interacting sources with different mechanisms. Here we introduce a parameter-free model-based approach, based upon the seminal concept of Algorithmic Probability, that decomposes an observation and signal into its most likely algorithmic generative mechanisms. Our methods use a causal calculus to infer model representations. We demonstrate the method ability to distinguish interacting mechanisms and deconvolve them, regardless of whether the objects produce strings, space-time evolution diagrams, images or networks. We numerically test and evaluate our method and find that it can disentangle observations from discrete dynamic systems, random and complex networks. We think that these causal inference techniques can contribute as key pieces of information for estimations of probability distributions complementing other more statistical-oriented techniques that otherwise lack model inference capabilities.
Faster native vowel discrimination learning in musicians is mediated by an optimization of mnemonic functions.

Science.gov (United States)

Elmer, Stefan; Greber, Marielle; Pushparaj, Arethy; Kühnis, Jürg; Jäncke, Lutz

2017-09-01

The ability to discriminate phonemes varying in spectral and temporal attributes constitutes one of the most basic intrinsic elements underlying language learning mechanisms. Since previous work has consistently shown that professional musicians are characterized by perceptual and cognitive advantages in a variety of language-related tasks, and since vowels can be considered musical sounds within the domain of speech, here we investigated the behavioral and electrophysiological correlates of native vowel discrimination learning in a sample of professional musicians and non-musicians. We evaluated the contribution of both the neurophysiological underpinnings of perceptual (i.e., N1/P2 complex) and mnemonic functions (i.e., N400 and P600 responses) while the participants were instructed to judge whether pairs of native consonant-vowel (CV) syllables manipulated in the first formant transition of the vowel (i.e., from /tu/ to /to/) were identical or not. Results clearly demonstrated faster learning in musicians, compared to non-musicians, as reflected by shorter reaction times and higher accuracy. Most notably, in terms of morphology, time course, and voltage strength, this steeper learning curve was accompanied by distinctive N400 and P600 manifestations between the two groups. In contrast, we did not reveal any group differences during the early stages of auditory processing (i.e., N1/P2 complex), suggesting that faster learning was mediated by an optimization of mnemonic but not perceptual functions. Based on a clear taxonomy of the mnemonic functions involved in the task, results are interpreted as pointing to a relationship between faster learning mechanisms in musicians and an optimization of echoic (i.e., N400 component) and working memory (i.e., P600 component) functions. Copyright © 2017 Elsevier Ltd. All rights reserved.
PSYCHOLOGICAL STRATEGY OF COOPERATION, MOTIVATIONAL, INFORMATION AND TECHNOLOGICAL COMPONENTS OF FUTURE HUMANITARIAN TEACHER READINESS FOR PROFESSIONAL ACTIVITY IN POLYSUBJECTIVE LEARNING ENVIRONMENT

Directory of Open Access Journals (Sweden)

Y. Spivakovska

2014-04-01

Full Text Available Redefining of modern information and communication technologies (ICT from teaching aids to teaching process subjects, continuous growth of their subjectivity necessary demands appropriate knowledge, skills, appropriate attitude to didactic capabilities of ICT, ability to cooperate with them and to build pupils learning activity aimed at formation and development of self organization, self development skills, promoting their subjective position in getting education that will be readiness of modern teacher to organize effective professional activities in polysubjective learning environment (PLE. The new tasks of humanitarian teacher related to self selection and design of educational content as well as the modeling of the learning process in conditions of PLE virtualized alternatives choice, impose special requirements to professionally important teacher’s personality qualities, rather to his readiness to implement effective professional work in such conditions. In this article the essence of future humanitarian teacher readiness concept to professional activity in polysubjective educational environment is proved. The structure of the readiness is analyzed. Psychological strategy of cooperation, reflective, motivational and informational partials are substantiated and characterized as components of the future humanitarian teacher readiness to professional activities in polysubjective educational environment.
Learning Object Metadata in a Web-Based Learning Environment

NARCIS (Netherlands)

Avgeriou, Paris; Koutoumanos, Anastasios; Retalis, Symeon; Papaspyrou, Nikolaos

2000-01-01

The plethora and variance of learning resources embedded in modern web-based learning environments require a mechanism to enable their structured administration. This goal can be achieved by defining metadata on them and constructing a system that manages the metadata in the context of the learning
Children's Learning

Science.gov (United States)

Siegler, Robert S.

2005-01-01

A new field of children's learning is emerging. This new field differs from the old in recognizing that children's learning includes active as well as passive mechanisms and qualitative as well as quantitative changes. Children's learning involves substantial variability of representations and strategies within individual children as well as…
Machine learning-enabled discovery and design of membrane-active peptides.

Science.gov (United States)

Lee, Ernest Y; Wong, Gerard C L; Ferguson, Andrew L

2017-07-08

Antimicrobial peptides are a class of membrane-active peptides that form a critical component of innate host immunity and possess a diversity of sequence and structure. Machine learning approaches have been profitably employed to efficiently screen sequence space and guide experiment towards promising candidates with high putative activity. In this mini-review, we provide an introduction to antimicrobial peptides and summarize recent advances in machine learning-enabled antimicrobial peptide discovery and design with a focus on a recent work Lee et al. Proc. Natl. Acad. Sci. USA 2016;113(48):13588-13593. This study reports the development of a support vector machine classifier to aid in the design of membrane active peptides. We use this model to discover membrane activity as a multiplexed function in diverse peptide families and provide interpretable understanding of the physicochemical properties and mechanisms governing membrane activity. Experimental validation of the classifier reveals it to have learned membrane activity as a unifying signature of antimicrobial peptides with diverse modes of action. Some of the discriminating rules by which it performs classification are in line with existing "human learned" understanding, but it also unveils new previously unknown determinants and multidimensional couplings governing membrane activity. Integrating machine learning with targeted experimentation can guide both antimicrobial peptide discovery and design and new understanding of the properties and mechanisms underpinning their modes of action. Copyright © 2017 Elsevier Ltd. All rights reserved.
Is LabTutor a helpful component of the blended learning approach to biosciences?

Science.gov (United States)

Swift, Amelia; Efstathiou, Nikolaos; Lameu, Paula

2016-09-01

To evaluate the use of LabTutor (a physiological data capture and e-learning package) in bioscience education for student nurses. Knowledge of biosciences is important for nurses the world over, who have to monitor and assess their patient's clinical condition, and interpret that information to determine the most appropriate course of action. Nursing students have long been known to find acquiring useable bioscience knowledge challenging. Blended learning strategies are common in bioscience teaching to address the difficulties students have. Student nurses have a preference for hands-on learning, small group sessions and are helped by close juxtaposition of theory and practice. An evaluation of a new teaching method using in-classroom voluntary questionnaire. A structured survey instrument including statements and visual analogue response format and open questions was given to students who participated in Labtutor sessions. The students provided feedback in about the equipment, the learning and the session itself. First year (n = 93) and third year (n = 36) students completed the evaluation forms. The majority of students were confident about the equipment and using it to learn although a few felt anxious about computer-based learning. They all found the equipment helpful as part of their bioscience education and they all enjoyed the sessions. This equipment provides a helpful way to encourage guided independent learning through practice and discovery and because each session is case study based and the relationship of the data to the patient is made clear. Our students helped to evaluate our initial use of LabTutor and found the sessions enjoyable and helpful. LabTutor provides an effective learning tool as part of a blended learning strategy for biosciences teaching. Improving bioscience knowledge will lead to a greater understanding of pathophysiology, treatments and interventions and monitoring. © 2016 John Wiley & Sons Ltd.
Teacher Collaboration and Student Learning in a Professional Learning Community

Science.gov (United States)

Vaughan, Mary Elaine

2013-01-01

Researchers have endorsed teacher collaboration within a professional learning community (PLC) that is focused on student learning. Despite these research-based endorsements, several Algebra 1 teachers in a southeastern high school implemented components of a PLC with little or no results in student achievement. The purpose of this study was to…
Representation for dialect recognition using topographic independent component analysis

Science.gov (United States)

Wei, Qu

2004-10-01

In dialect speech recognition, the feature of tone in one dialect is subject to changes in pitch frequency as well as the length of tone. It is beneficial for the recognition if a representation can be derived to account for the frequency and length changes of tone in an effective and meaningful way. In this paper, we propose a method for learning such a representation from a set of unlabeled speech sentences containing the features of the dialect changed from various pitch frequencies and time length. Topographic independent component analysis (TICA) is applied for the unsupervised learning to produce an emergent result that is a topographic matrix made up of basis components. The dialect speech is topographic in the following sense: the basis components as the units of the speech are ordered in the feature matrix such that components of one dialect are grouped in one axis and changes in time windows are accounted for in the other axis. This provides a meaningful set of basis vectors that may be used to construct dialect subspaces for dialect speech recognition.
Simultaneous multi-component seismic denoising and reconstruction via K-SVD

Science.gov (United States)

Hou, Sian; Zhang, Feng; Li, Xiangyang; Zhao, Qiang; Dai, Hengchang

2018-06-01

Data denoising and reconstruction play an increasingly significant role in seismic prospecting for their value in enhancing effective signals, dealing with surface obstacles and reducing acquisition costs. In this paper, we propose a novel method to denoise and reconstruct multicomponent seismic data simultaneously. This method lies within the framework of machine learning and the key points are defining a suitable weight function and a modified inner product operator. The purpose of these two processes are to perform missing data machine learning when the random noise deviation is unknown, and building a mathematical relationship for each component to incorporate all the information of multi-component data. Two examples, using synthetic and real multicomponent data, demonstrate that the new method is a feasible alternative for multi-component seismic data processing.

Active Learning with Irrelevant Examples

Science.gov (United States)

Wagstaff, Kiri; Mazzoni, Dominic

2009-01-01

An improved active learning method has been devised for training data classifiers. One example of a data classifier is the algorithm used by the United States Postal Service since the 1960s to recognize scans of handwritten digits for processing zip codes. Active learning algorithms enable rapid training with minimal investment of time on the part of human experts to provide training examples consisting of correctly classified (labeled) input data. They function by identifying which examples would be most profitable for a human expert to label. The goal is to maximize classifier accuracy while minimizing the number of examples the expert must label. Although there are several well-established methods for active learning, they may not operate well when irrelevant examples are present in the data set. That is, they may select an item for labeling that the expert simply cannot assign to any of the valid classes. In the context of classifying handwritten digits, the irrelevant items may include stray marks, smudges, and mis-scans. Querying the expert about these items results in wasted time or erroneous labels, if the expert is forced to assign the item to one of the valid classes. In contrast, the new algorithm provides a specific mechanism for avoiding querying the irrelevant items. This algorithm has two components: an active learner (which could be a conventional active learning algorithm) and a relevance classifier. The combination of these components yields a method, denoted Relevance Bias, that enables the active learner to avoid querying irrelevant data so as to increase its learning rate and efficiency when irrelevant items are present. The algorithm collects irrelevant data in a set of rejected examples, then trains the relevance classifier to distinguish between labeled (relevant) training examples and the rejected ones. The active learner combines its ranking of the items with the probability that they are relevant to yield a final decision about which item
COGNITIVE FATIGUE FACILITATES PROCEDURAL SEQUENCE LEARNING

Directory of Open Access Journals (Sweden)

Guillermo eBorragán

2016-03-01

Full Text Available Enhanced procedural learning has been evidenced in conditions where cognitive control is diminished, including hypnosis, disruption of prefrontal activity and non-optimal time of the day. Another condition depleting the availability of controlled resources is cognitive fatigue. We tested the hypothesis that cognitive fatigue, eventually leading to diminished cognitive control, facilitates procedural sequence learning. In a two-day experiment, twenty-three young healthy adults were administered a serial reaction time task (SRTT following the induction of high or low levels of cognitive fatigue, in a counterbalanced order. Cognitive fatigue was induced using the Time load Dual-back (TloadDback paradigm, a dual working memory task that allows tailoring cognitive load levels to the individual's optimal performance capacity. In line with our hypothesis, reaction times in the SRTT were faster in the high- than in the low-level fatigue condition, and performance improvement showed more of a benefit from the sequential components than from motor. Altogether, our results suggest a paradoxical, facilitating impact of cognitive fatigue on procedural motor sequence learning. We propose that facilitated learning in the high-level fatigue condition stems from a reduction in the cognitive resources devoted to cognitive control processes that normally oppose automatic procedural acquisition mechanisms.
Supportive Learning: Linear Learning and Collaborative Learning

Science.gov (United States)

Lee, Bih Ni; Abdullah, Sopiah; Kiu, Su Na

2016-01-01

This is a conceptual paper which is trying to look at the educational technology is not limited to high technology. However, electronic educational technology, also known as e-learning, has become an important part of today's society, which consists of a wide variety of approaches to digitization, components and methods of delivery. In the…
Linkages between motivation, self-efficacy, self-regulated learning and preferences for traditional learning environments or those with an online component

Directory of Open Access Journals (Sweden)

Daniel Auld

2010-10-01

Full Text Available This study assessed 96 law school students’ preferences for online, hybrid, or traditional learning environments, and their reasons for these preferences, learning strategies, and motivational orientations. A discriminant analysis revealed that non-traditional learning environment familiarity, self-efficacy, and employment status were the strongest predictors of preferences for non-traditional learning environments. Preferences for traditional environments were attributed to students’ familiarity and ability to engage in and foster personal interaction. Preferences for hybrid and online environments were attributed to opportunities for enhanced learning given the convenience and flexible manner in which students with time and familial constraints could access these environments.
Evaluation of different fracture-mechanical J-integral initiation values with regard to their usability in the safety assessment of components

International Nuclear Information System (INIS)

Eisele, U.; Roos, E.

1991-01-01

Determining fracture-mechanical material characteristic values on the basis of the J-integral is described and stipulated in a variety of standards and guidelines. The individual specifications differ in terms of procedure when determining the characteristic values and, therefore, also in terms of the meaningfulness of the results. This paper presents the different procedures, suggested in the course of the development of test methods in the field of elastic-plastic fracture mechanics, used to characterize crack initiation behaviour with regard to their features as material characteristic values and their usability in the safety assessment of components. (orig.)
Explosion bonding of dissimilar materials for fabricating APS front end components: Analysis of metallurgical and mechanical properties and UHV applications

International Nuclear Information System (INIS)

Li, Yuheng; Shu, Deming; Kuzay, T.M.

1994-01-01

The front end beamline section contains photon shutters and fixed masks. These components are made of OFHC copper and GlidCOP AL-15. Stainless steels (304 or 316) are also used for connecting photon shutters and fixed masks to other components that operate in the ultrahigh vacuum system. All these dissimilar materials need to be joined together. However, bonding these dissimilar materials is very difficult because of their different mechanical and thermal properties and incompatible metallurgical properties. Explosion bonding is a bonding method in which the controlled energy of a detonating explosive is used to create a metallurgical bond between two or more similar or dissimilar materials. No intermediate filler metal, for example, a brazing compound or soldering alloy, is needed to promote bonding, and no external heat need be applied. A study of the metallurgical and mechanical properties and YGV applications of GlidCop AL-15, OFHC copper, and 304 stainless steel explosion-bonded joints has been done. This report contains five parts: an ultrasonic examination of explosion-bonded joints and a standard setup; mechanical-property and thermal-cycle tests of GlidCop AL-15/304 stainless steel explosion-bonded joints; leak tests of a GlidCop AL-15/304 stainless steel explosion-bonded interfaces for UHV application; metallurgical examination of explosion-bonded interfaces and failure analysis, and discussion and conclusion
GCS component development cycle

Science.gov (United States)

Rodríguez, Jose A.; Macias, Rosa; Molgo, Jordi; Guerra, Dailos; Pi, Marti

2012-09-01

The GTC1 is an optical-infrared 10-meter segmented mirror telescope at the ORM observatory in Canary Islands (Spain). First light was at 13/07/2007 and since them it is in the operation phase. The GTC control system (GCS) is a distributed object & component oriented system based on RT-CORBA8 and it is responsible for the management and operation of the telescope, including its instrumentation. GCS has used the Rational Unified process (RUP9) in its development. RUP is an iterative software development process framework. After analysing (use cases) and designing (UML10) any of GCS subsystems, an initial component description of its interface is obtained and from that information a component specification is written. In order to improve the code productivity, GCS has adopted the code generation to transform this component specification into the skeleton of component classes based on a software framework, called Device Component Framework. Using the GCS development tools, based on javadoc and gcc, in only one step, the component is generated, compiled and deployed to be tested for the first time through our GUI inspector. The main advantages of this approach are the following: It reduces the learning curve of new developers and the development error rate, allows a systematic use of design patterns in the development and software reuse, speeds up the deliverables of the software product and massively increase the timescale, design consistency and design quality, and eliminates the future refactoring process required for the code.
Learning-based identification and iterative learning control of direct-drive robots

NARCIS (Netherlands)

Bukkems, B.H.M.; Kostic, D.; Jager, de A.G.; Steinbuch, M.

2005-01-01

A combination of model-based and Iterative Learning Control is proposed as a method to achieve high-quality motion control of direct-drive robots in repetitive motion tasks. We include both model-based and learning components in the total control law, as their individual properties influence the
Procedures for the design of the main mechanical components of a wind system; Dimensionamento dos componentes mecanicos principais de aerogeradores

Energy Technology Data Exchange (ETDEWEB)

Hirata, M.H.; Marco Filho, F. de [Universidade Federal, Rio de Janeiro, RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia

1990-12-31

Procedures for the design of the main mechanical components of a wind system were developed. One of the main concerns was related to the possibility of its use in small micro-computers. This goal was reached and an APPLE II computer was used. The resulting algorithm permits a friendly interaction between man and machine. 5 refs., 12 figs
Deep Reinforcement Learning: An Overview

OpenAIRE

Li, Yuxi

2017-01-01

We give an overview of recent exciting achievements of deep reinforcement learning (RL). We discuss six core elements, six important mechanisms, and twelve applications. We start with background of machine learning, deep learning and reinforcement learning. Next we discuss core RL elements, including value function, in particular, Deep Q-Network (DQN), policy, reward, model, planning, and exploration. After that, we discuss important mechanisms for RL, including attention and memory, unsuperv...
Analysis of Maths Learning Activities Developed By Pre-service Teachers in Terms of the Components of Content, Purpose, Application Methods

Directory of Open Access Journals (Sweden)

Çağla Toprak

2014-04-01

Full Text Available Today- when the influence of the alteration movement done in order to keep up with the age of the educational system is still continuing- the importance of teachers in students’ learning and achieving what is expected from the education system has been stated by the studies conducted (Hazır & Bıkmaz, 2006. Teachers own a critical role in the stage of both preparing teaching materials and using them (Stein & Smith, 1998b; Swan, 2007. When the existing curriculums –in particular, maths and geometry cirriculums- are analyzed, it can be observed that activities are the most significant teaching materials (Bozkurt, 2012. In fact, it is possible to characterize the existing curriculums as activity-based ones (Report of Workshop Examining Content of Primary School Curriculums According to Branches, 2010; Epö, 2005. Therefore, what sort of learning activities there are, what qualities they need to have, how to design and apply them are topics that must be elaborated (Uğurel et al., 2010. At this point, our study to increase the skills of pre-service teachers during the process of developing activities was conducted with 27 pre-service teachers -19 girls 8 boys- studying in the 4th year in Mathematics Education Department at a state university in the Aegean Region. The activity designs the pre-service teachers developed considering the patterns given after a series of practice were analyzed in documents in terms of the aim of design and the form of practice. As a result of the studies, it is observed that pre-service teachers deal with the topics from the maths curriculum and these topics are of different grade levels. The result of the examination named as target component suggests that activities developed aim firstly at providing learning and this is followed by reinforcing the concepts already learned. It is stated that pre-service teachers prefer mostly small group (cooperative studies in the activities they develop.Key Words: �
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.
Social learning and human mate preferences: a potential mechanism for generating and maintaining between-population diversity in attraction

Science.gov (United States)

Little, Anthony C.; Jones, Benedict C.; DeBruine, Lisa M.; Caldwell, Christine A.

2011-01-01

Inspired by studies demonstrating mate-choice copying effects in non-human species, recent studies of attractiveness judgements suggest that social learning also influences human preferences. In the first part of our article, we review evidence for social learning effects on preferences in humans and other animals. In the second part, we present new empirical evidence that social learning not only influences the attractiveness of specific individuals, but can also generalize to judgements of previously unseen individuals possessing similar physical traits. The different conditions represent different populations and, once a preference arises in a population, social learning can lead to the spread of preferences within that population. In the final part of our article, we discuss the theoretical basis for, and possible impact of, biases in social learning whereby individuals may preferentially copy the choices of those with high status or better access to critical information about potential mates. Such biases could mean that the choices of a select few individuals carry the greatest weight, rapidly generating agreement in preferences within a population. Collectively, these issues suggest that social learning mechanisms encourage the spread of preferences for certain traits once they arise within a population and so may explain certain cross-cultural differences. PMID:21199841
A probabilistic model for component-based shape synthesis

KAUST Repository

Kalogerakis, Evangelos; Chaudhuri, Siddhartha; Koller, Daphne; Koltun, Vladlen

2012-01-01

represents probabilistic relationships between properties of shape components, and relates them to learned underlying causes of structural variability within the domain. These causes are treated as latent variables, leading to a compact representation
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
Implementation of 3D virtual learning environment to improve students’ cognitive achievement

Science.gov (United States)

Rasim; Langi, A. Z. R.; Rosmansyah, Y.; Munir

2018-05-01

Virtual Learning Environment (VLE) has been widely used in assisting learning. This study aims to implement VLE-based learning in software engineering course. VLE provides many facilities for learning. In this research, VLE components used were presenter and quiz chair components. Evaluation results showed a significant difference from classical learning.
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.
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.
Learning from input and memory evolution: points of vulnerability on a pathway to mastery in word learning.

Science.gov (United States)

Storkel, Holly L

2015-02-01

Word learning consists of at least two neurocognitive processes: learning from input during training and memory evolution during gaps between training sessions. Fine-grained analysis of word learning by normal adults provides evidence that learning from input is swift and stable, whereas memory evolution is a point of potential vulnerability on the pathway to mastery. Moreover, success during learning from input is linked to positive outcomes from memory evolution. These two neurocognitive processes can be overlaid on to components of clinical treatment with within-session variables (i.e. dose form and dose) potentially linked to learning from input and between-session variables (i.e. dose frequency) linked to memory evolution. Collecting data at the beginning and end of a treatment session can be used to identify the point of vulnerability in word learning for a given client and the appropriate treatment component can then be adjusted to improve the client's word learning. Two clinical cases are provided to illustrate this approach.
Nuclear power plant Generic Aging Lessons Learned (GALL). Appendix B

International Nuclear Information System (INIS)

Kasza, K.E.; Diercks, D.R.; Holland, J.W.; Choi, S.U.

1996-12-01

The purpose of this generic aging lessons learned (GALL) review is to provide a systematic review of plant aging information in order to assess materials and component aging issues related to continued operation and license renewal of operating reactors. Literature on mechanical, structural, and thermal-hydraulic components and systems reviewed consisted of 97 Nuclear Plant Aging Research (NPAR) reports, 23 NRC Generic Letters, 154 Information Notices, 29 Licensee Event Reports (LERs), 4 Bulletins, and 9 Nuclear Management and Resources Council Industry Reports (NUMARC IRs) and literature on electrical components and systems reviewed consisted of 66 NPAR reports, 8 NRC Generic Letters, 111 Information Notices, 53 LERs, 1 Bulletin, and 1 NUMARC IR. More than 550 documents were reviewed. The results of these reviews were systematized using a standardized GALL tabular format and standardized definitions of aging-related degradation mechanisms and effects. The tables are included in volumes 1 and 2 of this report. A computerized data base has also been developed for all review tables and can be used to expedite the search for desired information on structures, components, and relevant aging effects. A survey of the GALL tables reveals that all ongoing significant component aging issues are currently being addressed by the regulatory process. However, the aging of what are termed passive components has been highlighted for continued scrutiny. This report consists of Volume 2, which consists of the GALL literature review tables for the NUMARC Industry Reports reviewed for the report

Oxidative stress protection and stomatal patterning as components of salinity tolerance mechanism in quinoa (Chenopodium quinoa).

Science.gov (United States)

Shabala, Lana; Mackay, Alex; Tian, Yu; Jacobsen, Sven-Erik; Zhou, Daowei; Shabala, Sergey

2012-09-01

Two components of salinity stress are a reduction in water availability to plants and the formation of reactive oxygen species. In this work, we have used quinoa (Chenopodium quinoa), a dicotyledonous C3 halophyte species displaying optimal growth at approximately 150 mM NaCl, to study mechanisms by which halophytes cope with the afore-mentioned components of salt stress. The relative contribution of organic and inorganic osmolytes in leaves of different physiological ages (e.g. positions on the stem) was quantified and linked with the osmoprotective function of organic osmolytes. We show that the extent of the oxidative stress (UV-B irradiation) damage to photosynthetic machinery in young leaves is much less when compared with old leaves, and attribute this difference to the difference in the size of the organic osmolyte pool (1.5-fold difference under control conditions; sixfold difference in plants grown at 400 mM NaCl). Consistent with this, salt-grown plants showed higher Fv/Fm values compared with control plants after UV-B exposure. Exogenous application of physiologically relevant concentrations of glycine betaine substantially mitigated oxidative stress damage to PSII, in a dose-dependent manner. We also show that salt-grown plants showed a significant (approximately 30%) reduction in stomatal density observed in all leaves. It is concluded that accumulation of organic osmolytes plays a dual role providing, in addition to osmotic adjustment, protection of photosynthetic machinery against oxidative stress in developing leaves. It is also suggested that salinity-induced reduction in stomatal density represents a fundamental mechanism by which plants optimize water use efficiency under saline conditions. Copyright © Physiologia Plantarum 2012.
Self-regulated learning: A key learning effect of feedback in a ...

African Journals Online (AJOL)

Background. Problem-based learning (PBL) has been adopted across many health professions training institutions. Small-group student tutorials are a major component of PBL. Facilitator feedback during a tutorial is a key activity to promote self-regulated learning. Objective. To explore ways in which students use feedback ...
A Hybrid Teaching and Learning Model

Science.gov (United States)

Juhary, Jowati Binti

This paper aims at analysing the needs for a specific teaching and learning model for the National Defence University of Malaysia (NDUM). The main argument is that whether there are differences between teaching and learning for academic component versus military component at the university. It is further argued that in order to achieve excellence, there should be one teaching and learning culture. Data were collected through interviews with military cadets. It is found that there are variations of teaching and learning strategies for academic courses, in comparison to a dominant teaching and learning style for military courses. Thus, in the interest of delivering quality education and training for students at the university, the paper argues that possibly a hybrid model for teaching and learning is fundamental in order to generate a one culture of academic and military excellence for the NDUM.
Learning Approaches - Final Report Sub-Project 4

DEFF Research Database (Denmark)

Dirckinck-Holmfeld, Lone; Rodríguez Illera, José Luis; Escofet, Anna

2007-01-01

The overall aim of Subproject 4 is to apply learning approaches that are appropriate and applicable using ICT. The task is made up of two components 4.1 dealing with learning approaches (see deliverable 4.1), and component 4.2 application of ICT (see deliverable 4.2, deliverable 4.3 & deliverable...
On Phonemes As Cognitive Components of Speech

DEFF Research Database (Denmark)

Feng, Ling; Hansen, Lars Kai

2008-01-01

. The basic features are 25-dimensional short time (20ms) melfrequency weighted cepstral coefficients. Features are integrated by means of stacking to obtain features at longer time scales. Energy based sparsification is carried out to achieve sparse representations. Our hypothesis is ecological: we assume...... that features that essentially independent in a context defined ensemble can be efficiently coded using a sparse independent component representation. This means that supervised and unsupervised learning should result in similar representations. We indeed find that supervised and unsupervised learning seem...
Early adversity and learning: implications for typical and atypical behavioral development.

Science.gov (United States)

Hanson, Jamie L; van den Bos, Wouter; Roeber, Barbara J; Rudolph, Karen D; Davidson, Richard J; Pollak, Seth D

2017-07-01

Children who experience early adversity often develop emotion regulatory problems, but little is known about the mechanisms that mediate this relation. We tested whether general associative learning processes contribute to associations between adversity, in the form of child maltreatment, and negative behavioral outcomes. Eighty-one participants between 12 and 17 years of age were recruited for this study and completed a probabilistic learning Task. Forty-one of these participants had been exposed to physical abuse, a form of early adversity. Forty additional participants without any known history of maltreatment served as a comparison group. All participants (and their parents) also completed portions of the Youth Life Stress Interview to understand adolescent's behavior. We calculated measures of associative learning, and also constructed mathematical models of learning. We found that adolescents exposed to high levels of adversity early in their lives had lower levels of associative learning than comparison adolescents. In addition, we found that impaired associative learning partially explained the higher levels of behavioral problems among youth who suffered early adversity. Using mathematical models, we also found that two components of learning were specifically affected in children exposed to adversity: choice variability and biases in their beliefs about the likelihood of rewards in the environment. Participants who had been exposed to early adversity were less able than their peers to correctly learn which stimuli were likely to result in reward, even after repeated feedback. These individuals also used information about known rewards in their environments less often. In addition, individuals exposed to adversity made decisions early in the learning process as if rewards were less consistent and occurred more at random. These data suggest one mechanism through which early life experience shapes behavioral development. © 2017 Association for Child and
Learning curves for solid oxide fuel cells

International Nuclear Information System (INIS)

Rivera-Tinoco, Rodrigo; Schoots, Koen; Zwaan, Bob van der

2012-01-01

Highlights: ► We present learning curves for fuel cells based on empirical data. ► We disentangle different cost reduction mechanisms for SOFCs. ► We distinguish between learning-by-doing, R and D, economies-of-scale and automation. - Abstract: In this article we present learning curves for solid oxide fuel cells (SOFCs). With data from fuel cell manufacturers we derive a detailed breakdown of their production costs. We develop a bottom-up model that allows for determining overall SOFC manufacturing costs with their respective cost components, among which material, energy, labor and capital charges. The results obtained from our model prove to deviate by at most 13% from total cost figures quoted in the literature. For the R and D stage of development and diffusion, we find local learning rates between 13% and 17% and we demonstrate that the corresponding cost reductions result essentially from learning-by-searching effects. When considering periods in time that focus on the pilot and early commercial production stages, we find regional learning rates of 27% and 1%, respectively, which we assume derive mainly from genuine learning phenomena. These figures turnout significantly higher, approximately 44% and 12% respectively, if also effects of economies-of-scale and automation are included. When combining all production stages we obtain lr = 35%, which represents a mix of cost reduction phenomena. This high learning rate value and the potential to scale up production suggest that continued efforts in the development of SOFC manufacturing processes, as well as deployment and use of SOFCs, may lead to substantial further cost reductions.
Identifying the Components of Effective Learning Environments Based on Health Students\\' Perception

Directory of Open Access Journals (Sweden)

Yousefi Afrashteh M

2015-08-01

Full Text Available Aims: Effective learning environment can lead to establish and strengthen the appropriate conditions of learning in higher education. This study aimed to identify and define the factors associated with effective learning environment in the field of health education. Participants & Methods: This qualitative study with content analysis approach was conducted in 2013. Participants were 9 graduate and 7 undergraduate students of health majors that were selected using purposive sampling method. Data were recorded by interview and were analyzed using qualitative content analysis. Findings: Analysis of the data revealed 4 themes and 13 classes active and interactive teaching (participating viewpoints of students in educational planning, engaging students in class discussions, providing practical examples to understand the content, relaxing about expressed thoughts, the possibility of constructive criticism master plan of activities and according to the conditions and individual differences between students, Joyful atmosphere (academic motivation, the joy of learning and attendance, a sense of acceptance and respect from teachers and classroom dynamics and vitality and fatigue, relation of courses with professional needs (knowledge of the needs of the job in training course content and related training to the needs of job opportunities and professors’ scientific and power and expert (expertise and scientific capabilities in the field of teaching. Conclusion: 4 major themes and their characteristics can help to organize the learning environment in medical education.
ITER plasma facing components

International Nuclear Information System (INIS)

Kuroda, T.; Vieider, G.; Akiba, M.

1991-01-01

This document summarizes results of the Conceptual Design Activities (1988-1990) for the International Thermonuclear Experimental Reactor (ITER) project, namely those that pertain to the plasma facing components of the reactor vessel, of which the main components are the first wall and the divertor plates. After an introduction and an executive summary, the principal functions of the plasma-facing components are delineated, i.e., (i) define the low-impurity region within which the plasma is produced, (ii) absorb the electromagnetic radiation and charged-particle flux from the plasma, and (iii) protect the blanket/shield components from the plasma. A list of critical design issues for the divertor plates and the first wall is given, followed by discussions of the divertor plate design (including the issues of material selection, erosion lifetime, design concepts, thermal and mechanical analysis, operating limits and overall lifetime, tritium inventory, baking and conditioning, safety analysis, manufacture and testing, and advanced divertor concepts) and the first wall design (armor material and design, erosion lifetime, overall design concepts, thermal and mechanical analysis, lifetime and operating limits, tritium inventory, baking and conditioning, safety analysis, manufacture and testing, an alternative first wall design, and the limiters used instead of the divertor plates during start-up). Refs, figs and tabs
Adaptive online monitoring for ICU patients by combining just-in-time learning and principal component analysis.

Science.gov (United States)

Li, Xuejian; Wang, Youqing

2016-12-01

Offline general-type models are widely used for patients' monitoring in intensive care units (ICUs), which are developed by using past collected datasets consisting of thousands of patients. However, these models may fail to adapt to the changing states of ICU patients. Thus, to be more robust and effective, the monitoring models should be adaptable to individual patients. A novel combination of just-in-time learning (JITL) and principal component analysis (PCA), referred to learning-type PCA (L-PCA), was proposed for adaptive online monitoring of patients in ICUs. JITL was used to gather the most relevant data samples for adaptive modeling of complex physiological processes. PCA was used to build an online individual-type model and calculate monitoring statistics, and then to judge whether the patient's status is normal or not. The adaptability of L-PCA lies in the usage of individual data and the continuous updating of the training dataset. Twelve subjects were selected from the Physiobank's Multi-parameter Intelligent Monitoring for Intensive Care II (MIMIC II) database, and five vital signs of each subject were chosen. The proposed method was compared with the traditional PCA and fast moving-window PCA (Fast MWPCA). The experimental results demonstrated that the fault detection rates respectively increased by 20 % and 47 % compared with PCA and Fast MWPCA. L-PCA is first introduced into ICU patients monitoring and achieves the best monitoring performance in terms of adaptability to changes in patient status and sensitivity for abnormality detection.
Component aging evaluation with expert systems

International Nuclear Information System (INIS)

Wiesemann, J.S.; Maguire, H.T. Jr.

1988-01-01

The age degradation of components involves a complex relationship between a variety of variables. These relationships are typically modeled using probabilistic and deterministic analyses. These methods depend upon a formal understanding of the underlying degradation mechanisms and a database of experience which allows statistical analyses to extract numerical trends. At present, not all age degradation mechanisms are adequately modeled and available data for age degradation is in most cases insufficient. In addition, these methods tend to focus upon answers to isolated questions (e.g., What is the component failure rate?) rather than the more pertinent questions concerning operations and maintenance (e.g., should the component be replaced at the next outage). Fortunately, knowledge in the form of personal experience does exist which allows plant personnel to make decisions concerning operations and maintenance. This knowledge can be modeled using expert systems. This paper discusses CAGES (Component Aging Expert System). It combines expert rules (heuristics), probabilistic models, and deterministic models to make evaluations of component aging; predict the implications for component life extension, operational readiness, maintenance effectiveness, and safety, and make recommendations for maintenance and operation
Blended Learning: How Teachers Balance the Blend of Online and Classroom Components

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Jeffrey, Lynn M.; Milne, John; Suddaby, Gordon

2014-01-01

Despite teacher resistance to the use of technology in education, blended learning has increased rapidly, driven by evidence of its advantages over either online or classroom teaching alone. However, blended learning courses still fail to maximize the benefits this format offers. Much research has been conducted on various aspects of this problem,…
Lifelong Learning for the Hand Surgeon.

Science.gov (United States)

Adkinson, Joshua M; Chung, Kevin C

2015-09-01

Hand surgeons are faced with the impossible task of mastering a rapidly expanding pool of knowledge and surgical techniques. Dedication to lifelong learning is, therefore, an essential component of delivering the best, most up-to-date care for patients. Board certification, participation in continuing medical education and maintenance of certification activities, and attendance at national meetings are essential mechanisms by which hand surgeons may foster the acquisition of essential knowledge and clinical skills, This article highlights the history, current status, and emerging needs in continuing medical education for the hand surgeon. Copyright © 2015 American Society for Surgery of the Hand. Published by Elsevier Inc. All rights reserved.
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…
Experiential Learning: Lessons Learned from the UND Business and Government Symposium

Science.gov (United States)

Harsell, Dana Michael; O'Neill, Patrick B.

2010-01-01

The authors describe lessons learned from a limited-duration experiential learning component of a Master's level course. The course is open to Master's in Business and Master's in Public Administration students and explores the relationships between government and business. A complete discussion of the Master's in Business and Master's in Public…
Teach Them How They Learn: Learning Styles and Information Systems Education

Science.gov (United States)

Cegielski, Casey G.; Hazen, Benjamin T.; Rainer, R. Kelly

2011-01-01

The rich, interdisciplinary tradition of learning styles is markedly absent in information systems-related research. The current study applies the framework of learning styles to a common educational component of many of today's information systems curricula--object-oriented systems development--in an effort to answer the question as to whether…
Prediction of retained residual stresses in laboratory fracture mechanics specimens extracted from welded components

International Nuclear Information System (INIS)

Hurlston, R.G.; Sherry, A.H.; James, P.; Sharples, J.K.

2015-01-01

The measurement of weld material fracture toughness properties is important for the structural integrity assessment of engineering components. However, welds can contain high levels of residual stress and these can be retained in fracture mechanics specimens, particularly when machined from non-stress relieved welds. Retained residual stresses can make the measurement of valid fracture toughness properties difficult. This paper describes the results of analytical work undertaken to investigate factors that can influence the magnitude and distribution of residual stresses retained in fracture mechanics specimen blanks extracted from as-welded ferritic and austenitic stainless steel plates. The results indicate that significant levels of residual stress can be retained in specimen blanks prior to notching, and that the magnitude and distribution of stress is dependent upon material properties, specimen geometry and size, and extraction location through the thickness of the weld. Finite element modelling is shown to provide a useful approach for estimating the level and distributions of retained residual stresses. A new stress partitioning approach has been developed to estimate retained stress levels and results compare favourably with FE analysis and available experimental data. The approach can help guide the selection of specimen geometry and machining strategies to minimise the level of residual stresses retained in fracture mechanics specimen blanks extracted from non stress-relieved welds and thus improve the measurement of weld fracture toughness properties. - Highlights: • A simplified method for generating realistic weld residual stresses has been developed. • It has been shown that significant levels of residual stress can be retained within laboratory fracture mechanics specimens. • The level and distribution is dependant upon material, specimen type, specimen size and extraction location. • A method has been developed to allow estimates of the
Critical thinking as a self-regulatory process component in teaching and learning.

Science.gov (United States)

Phan, Huy P

2010-05-01

This article presents a theoretically grounded model of critical thinking and self-regulation in the context of teaching and learning. Critical thinking, deriving from an educational psychology perspective is a complex process of reflection that helps individuals become more analytical in their thinking and professional development. My conceptualisation in this discussion paper argues that both theoretical orientations (critical thinking and self-regulation) operate in a dynamic interactive system of teaching and learning. My argument, based on existing research evidence, suggests two important points: (i) critical thinking acts as another cognitive strategy of self-regulation that learners use in their learning, and (ii) critical thinking may be a product of various antecedents such as different self-regulatory strategies.
Framework for robot skill learning using reinforcement learning

Science.gov (United States)

Wei, Yingzi; Zhao, Mingyang

2003-09-01

Robot acquiring skill is a process similar to human skill learning. Reinforcement learning (RL) is an on-line actor critic method for a robot to develop its skill. The reinforcement function has become the critical component for its effect of evaluating the action and guiding the learning process. We present an augmented reward function that provides a new way for RL controller to incorporate prior knowledge and experience into the RL controller. Also, the difference form of augmented reward function is considered carefully. The additional reward beyond conventional reward will provide more heuristic information for RL. In this paper, we present a strategy for the task of complex skill learning. Automatic robot shaping policy is to dissolve the complex skill into a hierarchical learning process. The new form of value function is introduced to attain smooth motion switching swiftly. We present a formal, but practical, framework for robot skill learning and also illustrate with an example the utility of method for learning skilled robot control on line.
Learning under uncertainty in smart home environments.

Science.gov (United States)

Zhang, Shuai; McClean, Sally; Scotney, Bryan; Nugent, Chris

2008-01-01

Technologies and services for the home environment can provide levels of independence for elderly people to support 'ageing in place'. Learning inhabitants' patterns of carrying out daily activities is a crucial component of these technological solutions with sensor technologies being at the core of such smart environments. Nevertheless, identifying high-level activities from low-level sensor events can be a challenge, as information may be unreliable resulting in incomplete data. Our work addresses the issues of learning in the presence of incomplete data along with the identification and the prediction of inhabitants and their activities under such uncertainty. We show via the evaluation results that our approach also offers the ability to assess the impact of various sensors in the activity recognition process. The benefit of this work is that future predictions can be utilised in a proposed intervention mechanism in a real smart home environment.

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