High-frequency TRNS reduces BOLD activity during visuomotor learning.

Directory of Open Access Journals (Sweden)

Catarina Saiote

Full Text Available Transcranial direct current stimulation (tDCS and transcranial random noise stimulation (tRNS consist in the application of electrical current of small intensity through the scalp, able to modulate perceptual and motor learning, probably by changing brain excitability. We investigated the effects of these transcranial electrical stimulation techniques in the early and later stages of visuomotor learning, as well as associated brain activity changes using functional magnetic resonance imaging (fMRI. We applied anodal and cathodal tDCS, low-frequency and high-frequency tRNS (lf-tRNS, 0.1-100 Hz; hf-tRNS 101-640 Hz, respectively and sham stimulation over the primary motor cortex (M1 during the first 10 minutes of a visuomotor learning paradigm and measured performance changes for 20 minutes after stimulation ceased. Functional imaging scans were acquired throughout the whole experiment. Cathodal tDCS and hf-tRNS showed a tendency to improve and lf-tRNS to hinder early learning during stimulation, an effect that remained for 20 minutes after cessation of stimulation in the late learning phase. Motor learning-related activity decreased in several regions as reported previously, however, there was no significant modulation of brain activity by tDCS. In opposition to this, hf-tRNS was associated with reduced motor task-related-activity bilaterally in the frontal cortex and precuneous, probably due to interaction with ongoing neuronal oscillations. This result highlights the potential of lf-tRNS and hf-tRNS to differentially modulate visuomotor learning and advances our knowledge on neuroplasticity induction approaches combined with functional imaging methods.

Team-Based Learning Reduces Attrition in a First-Semester General Chemistry Course

Science.gov (United States)

Comeford, Lorrie

2016-01-01

Team-based learning (TBL) is an instructional method that has been shown to reduce attrition and increase student learning in a number of disciplines. TBL was implemented in a first-semester general chemistry course, and its effect on attrition was assessed. Attrition from sections before implementing TBL (fall 2008 to fall 2009) was compared with…

Theories of superconductivity (a few remarks)

International Nuclear Information System (INIS)

Ginzburg, V.L.

1992-01-01

The early history in the development of superconductivity. Idea of pairing, Schafroth and BCS types of theories. Some remarks on present state of the microscopical theory of high-temperature superconductors (HTSC). Mean field macroscopic theory of superconductivity and its specific features in HTSC. About generalized macroscopic theory applicable in critical region. Concluding remarks. (orig.)

Perceptual learning eases crowding by reducing recognition errors but not position errors.

Science.gov (United States)

Xiong, Ying-Zi; Yu, Cong; Zhang, Jun-Yun

2015-08-01

When an observer reports a letter flanked by additional letters in the visual periphery, the response errors (the crowding effect) may result from failure to recognize the target letter (recognition errors), from mislocating a correctly recognized target letter at a flanker location (target misplacement errors), or from reporting a flanker as the target letter (flanker substitution errors). Crowding can be reduced through perceptual learning. However, it is not known how perceptual learning operates to reduce crowding. In this study we trained observers with a partial-report task (Experiment 1), in which they reported the central target letter of a three-letter string presented in the visual periphery, or a whole-report task (Experiment 2), in which they reported all three letters in order. We then assessed the impact of training on recognition of both unflanked and flanked targets, with particular attention to how perceptual learning affected the types of errors. Our results show that training improved target recognition but not single-letter recognition, indicating that training indeed affected crowding. However, training did not reduce target misplacement errors or flanker substitution errors. This dissociation between target recognition and flanker substitution errors supports the view that flanker substitution may be more likely a by-product (due to response bias), rather than a cause, of crowding. Moreover, the dissociation is not consistent with hypothesized mechanisms of crowding that would predict reduced positional errors.

Remarks on stellar clusters

International Nuclear Information System (INIS)

Teller, E.

1985-01-01

In the following, a few simple remarks on the evolution and properties of stellar clusters will be collected. In particular, globular clusters will be considered. Though details of such clusters are often not known, a few questions can be clarified with the help of primitive arguments. These are:- why are spherical clusters spherical, why do they have high densities, why do they consist of approximately a million stars, how may a black hole of great mass form within them, may they be the origin of gamma-ray bursts, may their invisible remnants account for the missing mass of our galaxy. The available data do not warrant a detailed evaluation. However, it is remarkable that exceedingly simple models can shed some light on the questions enumerated above. (author)

Remarkable convergent evolution in specialized parasitic Thecostraca (Crustacea)

DEFF Research Database (Denmark)

Pérez-Losada, Marcos; Høeg, Jens Thorvald; Crandall, Keith A

2009-01-01

the metamorphosis found in the Facetotecta and Rhizocephala suggests a common evolutionary origin, but until now no comprehensive study has looked at the basic evolution of these thecostracan groups. Results To this end, we collected DNA sequences from three nuclear genes [18S rRNA (2,305), 28S rRNA (2...... analyses indicate a convergent evolution of the very similar and highly reduced slug-shaped stages found during metamorphosis of both the Rhizocephala and the Facetotecta. This provides a remarkable case of convergent evolution and implies that the advanced endoparasitic mode of life known from...

Reducing statistics anxiety and enhancing statistics learning achievement: effectiveness of a one-minute strategy.

Science.gov (United States)

Chiou, Chei-Chang; Wang, Yu-Min; Lee, Li-Tze

2014-08-01

Statistical knowledge is widely used in academia; however, statistics teachers struggle with the issue of how to reduce students' statistics anxiety and enhance students' statistics learning. This study assesses the effectiveness of a "one-minute paper strategy" in reducing students' statistics-related anxiety and in improving students' statistics-related achievement. Participants were 77 undergraduates from two classes enrolled in applied statistics courses. An experiment was implemented according to a pretest/posttest comparison group design. The quasi-experimental design showed that the one-minute paper strategy significantly reduced students' statistics anxiety and improved students' statistics learning achievement. The strategy was a better instructional tool than the textbook exercise for reducing students' statistics anxiety and improving students' statistics achievement.

Seven remarkable days

CERN Document Server

This has been a truly remarkable seven days for CERN. Things have moved so fast that it has sometimes been hard to separate fact from fiction – all the more so since facts have often seemed too good to be true. It’s been a week of many firsts. Monday was the first time we’ve had two captured beams in the LHC. It’s the first time the LHC has functioned as a particle accelerator, boosting particles to the highest beam energy so far achieved at CERN. And it’s been a week in which we’ve seen the highest energy proton-proton collisions ever produced at CERN: our last hadron collider, the SPS was a proton-antiproton collider, a technically simpler machine than the LHC. This week’s successes are all the more remarkable precisely because of the complexity of the LHC. Unlike the SPS collider, it is two accelerators not one, making the job of commissioning nearly twice as difficult. I’d like to express my heartfelt thanks and congra...

Welcome remarks

International Nuclear Information System (INIS)

Zhao Hong

1993-01-01

In his opening remarks Mr. Zhao Hong stressed the importance of nuclear power for further economic development. He noticed that one of the main factors to obstruct the progress of nuclear energy is nuclear dread in public psychology and that enhancement of the public acceptance of nuclear power is an important task to promote the development of nuclear power. Than he described activities in China in public relation work in the field of nuclear energy. Importance of international cooperation on peaceful use of nuclear energy and supporting non-proliferation regime was stressed

NRC closing remarks

International Nuclear Information System (INIS)

Coffman, F.

1994-01-01

This section contains the edited transcript of the NRC closing remarks made by Mr. Franklin Coffman (Chief, Human Factors Branch, Office of Nuclear Regulatory Research) and Dr. Cecil Thomas (Deputy Director, Division of Reactor Controls and Human Factors, Office of Nuclear Reactor Regulation). This editing consisted of minimal editing to correct grammar and remove extraneous references to microphone volume, etc

Remarkable reduction of thermal conductivity in phosphorene phononic crystal

International Nuclear Information System (INIS)

Xu, Wen; Zhang, Gang

2016-01-01

Phosphorene has received much attention due to its interesting physical and chemical properties, and its potential applications such as thermoelectricity. In thermoelectric applications, low thermal conductivity is essential for achieving a high figure of merit. In this work, we propose to reduce the thermal conductivity of phosphorene by adopting the phononic crystal structure, phosphorene nanomesh. With equilibrium molecular dynamics simulations, we find that the thermal conductivity is remarkably reduced in the phononic crystal. Our analysis shows that the reduction is due to the depressed phonon group velocities induced by Brillouin zone folding, and the reduced phonon lifetimes in the phononic crystal. Interestingly, it is found that the anisotropy ratio of thermal conductivity could be tuned by the ‘non-square’ pores in the phononic crystal, as the phonon group velocities in the direction with larger projection of pores is more severely suppressed, leading to greater reduction of thermal conductivity in this direction. Our work provides deep insight into thermal transport in phononic crystals and proposes a new strategy to reduce the thermal conductivity of monolayer phosphorene. (paper)

Learning Organic Chemistry Through Natural Products

Indian Academy of Sciences (India)

Higher Learning. ... The Series on "learning Organic Chemistry Through Natural Products". Nature is a remarkable ... skeletal structure to the interior electronic configu- ration ... Among the advantages of this approach are the fact that unlike the.

Learning oncogenetic networks by reducing to mixed integer linear programming.

Science.gov (United States)

Shahrabi Farahani, Hossein; Lagergren, Jens

2013-01-01

Cancer can be a result of accumulation of different types of genetic mutations such as copy number aberrations. The data from tumors are cross-sectional and do not contain the temporal order of the genetic events. Finding the order in which the genetic events have occurred and progression pathways are of vital importance in understanding the disease. In order to model cancer progression, we propose Progression Networks, a special case of Bayesian networks, that are tailored to model disease progression. Progression networks have similarities with Conjunctive Bayesian Networks (CBNs) [1],a variation of Bayesian networks also proposed for modeling disease progression. We also describe a learning algorithm for learning Bayesian networks in general and progression networks in particular. We reduce the hard problem of learning the Bayesian and progression networks to Mixed Integer Linear Programming (MILP). MILP is a Non-deterministic Polynomial-time complete (NP-complete) problem for which very good heuristics exists. We tested our algorithm on synthetic and real cytogenetic data from renal cell carcinoma. We also compared our learned progression networks with the networks proposed in earlier publications. The software is available on the website https://bitbucket.org/farahani/diprog.

Opening remarks

International Nuclear Information System (INIS)

Southwood, Richard

1987-01-01

General opening remarks to a conference on the effects of low-level radiation on man, exploring particularly areas where disagreements have most frequently been voiced. The author comments on two approaches: a) the study, stepwise of putative cause and effect chains, using models which are tested by comparing calculated and observed effects. b) the epidemiological approach by extensive correlative study of cause, correlations and effect. Attention is drawn to the confidence to be accorded to any quantitative theory supported by both approaches, and the need for further analysis if the approaches give different indications. (U.K.)

Remarks of Joseph Marrone

International Nuclear Information System (INIS)

Marrone, J.

1985-01-01

The author's remarks are directed primarily at proposals that have been made that would substantially tort law with respect to radiation claims in order to ease the ability of claimants to recovery damages from defendants. The change would be based upon what had been assumed to be a ''scientific'' means of measuring the ''probability'' that exposure to ionizing radiation was the case of a cancer in a particular claimant. The remarks are divided into three parts: a summary description of the nuclear insurance pools, including the tort radiation claims filed against the pools; and a brief description of claims against the Federal Government and its contractors; an examination of the elementary principles of tort law, and an outline of the threat that has developed that would transform it into a hybrid social benefits program; and comment on the danger to the integrity of science when it is injected into the legislative process

Agent-Based Approach for E-Learning

Directory of Open Access Journals (Sweden)

Samir Bourekkache

2009-12-01

Full Text Available The current life knows a remarkable development which changes all aspects of our life such as: our working environment, educational system, traveling patterns, sport activities…etc. The busy lifestyle faced by individuals today and the fast pattern of life may lead to their inability to be involved in a process of education. There is also a considerable technological development, especially the development of computing and communication technology. All these factors led to the idea of the need to reduce the time and to benefit from this technology, particularly in the field of education. The way of the classical education is very slow, and the student is obliged to be present at specific times which may be inappropriate for the majority of learners. Moreover, the substantial funds allocated for the success of classical learning process. Thus, it emerged the so-called E-learning via the Internet; the aims of this new mode of learning across the network (web are to reduce the time of a process of learning –education- as well as to erase the drawbacks of the classical way of education. Therefore, in E-learning, the learner is not forced to be present at specific times, but he is free to choose the time of learning, which is appropriate with his schedule. Another point that is the adaptation of the content (courses with the intellectual and social characteristics of the learner and with his background (previous knowledge, which is the main task for each educational system. The technology of Multiagent system is relevant in this area.

Stochastic Learning and the Intuitive Criterion in Simple Signaling Games

DEFF Research Database (Denmark)

Sloth, Birgitte; Whitta-Jacobsen, Hans Jørgen

A stochastic learning process for signaling games with two types, two signals, and two responses gives rise to equilibrium selection which is in remarkable accordance with the selection obtained by the intuitive criterion......A stochastic learning process for signaling games with two types, two signals, and two responses gives rise to equilibrium selection which is in remarkable accordance with the selection obtained by the intuitive criterion...

Language Learning in Wittgenstein and Davidson

Science.gov (United States)

Kotzee, Ben

2014-01-01

In this paper, I discuss language learning in Wittgenstein and Davidson. Starting from a remark by Bakhurst, I hold that both Wittgenstein and Davidson's philosophies of language contain responses to the problem of language learning, albeit of a different form. Following Williams, I hold that the concept of language learning can explain…

A remarkable representation of the SO(3,2) Kac-Moody algebra

International Nuclear Information System (INIS)

Dobrev, V.K.; Sezgin, E.

1990-01-01

We construct a minimal representation of the SO(3,2) Kac-Moody algebra algebra which is based on the spin-zero singleton (the Rac) representation of SO(3,2). The representation is minimal in the sense that the central charge k of the SO(3,2) Kac-Moody algebra is chosen to take the special value of 5/2 which allows the imposition of maximum number of reducibility conditions. For the Rac, this is the unique choice for the remarkable property of maximum reducibility which is consistent with unitarity. To ensure unitarity, we furthermore impose invariance condition under the maximal compact subalgebra SO(3) x SO(2). (author). 19 refs, 1 fig

Influences of reduced masticatory sensory input from soft-diet feeding upon spatial memory/learning ability in mice.

Science.gov (United States)

Tsutsui, Keisuke; Kaku, Masato; Motokawa, Masahide; Tohma, Yuiko; Kawata, Toshitsugu; Fujita, Tadashi; Kohno, Shinya; Ohtani, Junji; Tenjoh, Kaoru; Nakano, Mao; Kamada, Hiroko; Tanne, Kazuo

2007-02-01

It has been reported that reduction of masticatory afferent stimulation might influence learning and memory function. In order to clarify the influences of reduced masticatory sensory input on spatial memory/learning ability and neuropathological changes, we conducted the Morris water maze experiment and investigated the number of hippocampal neurons in association with the differences in masticatory afferent stimuli from hard- and soft-diet feeding in mice. The water maze experiment showed no significant difference in learning ability between 180-day-old solid- and powderdiet groups. Meanwhile, the ability was significantly reduced in the 360-day-old powder-diet group as compared with the age-matched solid-diet group. The total number of pyramidal cells in the hippocampal CA1 and CA3 regions was significantly smaller in 360-day-old powder-diet group than in the remaining groups. These results demonstrate that reduction of masticatory afferent stimuli due to long-term soft-diet feeding may induce neuron loss in the hippocampus and reduced memory/learning ability.

Concluding remarks

International Nuclear Information System (INIS)

Vogt, E.

1989-05-01

The workshop has covered in a very interesting and complete way the basic physics issues to be addressed by the complementary facilities, in Canada and Japan, intended to explore the intensity-frontier of strong-interaction physics. Japan has its new KEK facilities and its future Japanese Hadron Project (JHP): Canada has its present TRIUMF laboratory and its future KAON Factory. Both JHP and KAON appear very near to final construction approval. The possibilities are very great for new joint programs between the two countries which can lead the world in the new strong interaction physics. These concluding remarks describe the general science basis and particularly the models for the internationalization of science needed to make these new collaborations thrive

MRI in assessing children with learning disability, focal findings, and reduced automaticity.

Science.gov (United States)

Urion, David K; Huff, Hanalise V; Carullo, Maria Paulina

2015-08-18

In children with clinically diagnosed learning disabilities with focal findings on neurologic or neuropsychological evaluations, there is a hypothesized association between disorders in automaticity and focal structural abnormalities observed in brain MRIs. We undertook a retrospective analysis of cases referred to a tertiary-hospital-based learning disabilities program. Individuals were coded as having a focal deficit if either neurologic or neuropsychological evaluation demonstrated focal dysfunction. Those with abnormal MRI findings were categorized based on findings. Children with abnormalities from each of these categories were compared in terms of deficits in automaticity, as measured by the tasks of Rapid Automatized Naming, Rapid Alternating Stimulus Naming, or the timed motor performance battery from the Physical and Neurological Examination for Soft Signs. Data were compared in children with and without disorders of automaticity regarding type of brain structure abnormality. Of the 1,587 children evaluated, 127 had a focal deficit. Eighty-seven had a brain MRI (52 on 1.5-tesla machines and 35 on 3.0-tesla machines). Forty of these images were found to be abnormal. These children were compared with a clinic sample of 150 patients with learning disabilities and no focal findings on examination, who also had undergone MRI. Only 5 of the latter group had abnormalities on MRI. Reduced verbal automaticity was associated with cerebellar abnormalities, whereas reduced automaticity on motor or motor and verbal tasks was associated with white matter abnormalities. Reduced automaticity of retrieval and slow timed motor performance appear to be highly associated with MRI findings. © 2015 American Academy of Neurology.

Learning classification models with soft-label information.

Science.gov (United States)

Nguyen, Quang; Valizadegan, Hamed; Hauskrecht, Milos

2014-01-01

Learning of classification models in medicine often relies on data labeled by a human expert. Since labeling of clinical data may be time-consuming, finding ways of alleviating the labeling costs is critical for our ability to automatically learn such models. In this paper we propose a new machine learning approach that is able to learn improved binary classification models more efficiently by refining the binary class information in the training phase with soft labels that reflect how strongly the human expert feels about the original class labels. Two types of methods that can learn improved binary classification models from soft labels are proposed. The first relies on probabilistic/numeric labels, the other on ordinal categorical labels. We study and demonstrate the benefits of these methods for learning an alerting model for heparin induced thrombocytopenia. The experiments are conducted on the data of 377 patient instances labeled by three different human experts. The methods are compared using the area under the receiver operating characteristic curve (AUC) score. Our AUC results show that the new approach is capable of learning classification models more efficiently compared to traditional learning methods. The improvement in AUC is most remarkable when the number of examples we learn from is small. A new classification learning framework that lets us learn from auxiliary soft-label information provided by a human expert is a promising new direction for learning classification models from expert labels, reducing the time and cost needed to label data.

The Effect of Learning Cycle Model on Students’ Reducing Ecological Footprints

Directory of Open Access Journals (Sweden)

Özgül Keleş

2011-12-01

Full Text Available The objective of this study is to investigate effect of ecological footprint education, in which 5E learning cycle model is used, in reducing primary school students’ ecological footprints. The working group of the study is composed of 124 primary school students studying in 4th, 5th, 6th, 7th, 8th classes. In this study, 5E learning model is used in teaching a course in order to increase the participating students’ knowledge about ecological footprints and to calculate ecological footprints. Experimental method is used in this study. In data analysis, the paired samples t-test is used in for relevant samplings. The findings gathered indicate that ecological footprints of the participating students to the study decreased at the end of the study. It is determined that the mean of primary students’ ecological footprints differ from meaningfully according to level of the class and sex. Prospective solution offers are developed by handling the prospective effects of conclusions of the study on sustainable life and environmental education and conclusions’ importance in terms of learning and developing learning programmes with a critical point of view

Deep learning enables reduced gadolinium dose for contrast-enhanced brain MRI.

Science.gov (United States)

Gong, Enhao; Pauly, John M; Wintermark, Max; Zaharchuk, Greg

2018-02-13

There are concerns over gadolinium deposition from gadolinium-based contrast agents (GBCA) administration. To reduce gadolinium dose in contrast-enhanced brain MRI using a deep learning method. Retrospective, crossover. Sixty patients receiving clinically indicated contrast-enhanced brain MRI. 3D T 1 -weighted inversion-recovery prepped fast-spoiled-gradient-echo (IR-FSPGR) imaging was acquired at both 1.5T and 3T. In 60 brain MRI exams, the IR-FSPGR sequence was obtained under three conditions: precontrast, postcontrast images with 10% low-dose (0.01mmol/kg) and 100% full-dose (0.1 mmol/kg) of gadobenate dimeglumine. We trained a deep learning model using the first 10 cases (with mixed indications) to approximate full-dose images from the precontrast and low-dose images. Synthesized full-dose images were created using the trained model in two test sets: 20 patients with mixed indications and 30 patients with glioma. For both test sets, low-dose, true full-dose, and the synthesized full-dose postcontrast image sets were compared quantitatively using peak-signal-to-noise-ratios (PSNR) and structural-similarity-index (SSIM). For the test set comprised of 20 patients with mixed indications, two neuroradiologists scored blindly and independently for the three postcontrast image sets, evaluating image quality, motion-artifact suppression, and contrast enhancement compared with precontrast images. Results were assessed using paired t-tests and noninferiority tests. The proposed deep learning method yielded significant (n = 50, P 5 dB PSNR gains and >11.0% SSIM). Ratings on image quality (n = 20, P = 0.003) and contrast enhancement (n = 20, P deep learning method, gadolinium dose can be reduced 10-fold while preserving contrast information and avoiding significant image quality degradation. 3 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2018. © 2018 International Society for Magnetic Resonance in Medicine.

Incoherent dictionary learning for reducing crosstalk noise in least-squares reverse time migration

Science.gov (United States)

Wu, Juan; Bai, Min

2018-05-01

We propose to apply a novel incoherent dictionary learning (IDL) algorithm for regularizing the least-squares inversion in seismic imaging. The IDL is proposed to overcome the drawback of traditional dictionary learning algorithm in losing partial texture information. Firstly, the noisy image is divided into overlapped image patches, and some random patches are extracted for dictionary learning. Then, we apply the IDL technology to minimize the coherency between atoms during dictionary learning. Finally, the sparse representation problem is solved by a sparse coding algorithm, and image is restored by those sparse coefficients. By reducing the correlation among atoms, it is possible to preserve most of the small-scale features in the image while removing much of the long-wavelength noise. The application of the IDL method to regularization of seismic images from least-squares reverse time migration shows successful performance.

Deep Learning Microscopy

KAUST Repository

Rivenson, Yair; Gorocs, Zoltan; Gunaydin, Harun; Zhang, Yibo; Wang, Hongda; Ozcan, Aydogan

2017-01-01

regular optical microscope, without any changes to its design. We blindly tested this deep learning approach using various tissue samples that are imaged with low-resolution and wide-field systems, where the network rapidly outputs an image with remarkably

Effects of novelty-reducing preparation on exploratory behavior and cognitive learning in a science museum setting

Science.gov (United States)

Kubota, Carole A.; Olstad, Roger G.

The purpose of this study was to examine the relationships between (a) novelty and exploratory behavior, (b) novelty and cognitive learning, and (c) exploratory behavior and cognitive learning in science museums. Sixty-four sixth-grade public school students participated in a posttest-only control group design. The control group received a treatment designed to decrease the novelty of a field trip setting through a vicarious exposure while the placebo group received an informative but not novelty-reducing treatment. Both groups then visited the field site where they were videotaped. Statistical analyses were conducted on both dependent variables with socioeconomic status and academic achievement as covariates, novelty-reducing preparation as the independent variable, and gender as moderator variable. Exploratory behavior was shown to be positively correlated with cognitive learning. Significant differences were detected for exploratory behavior. For both dependent variables, gender by treatment group interaction was significant with novelty-reducing preparation shown to be highly effective on boys but having no effect on girls.

"Experience and Learning"

DEFF Research Database (Denmark)

Olesen, Henning Salling

2007-01-01

to the understanding of knowledge, based on examples from the author's research into professional learning (general practitioners). The pivotal role of language use and language socialisation is explained in brief, developing a psychodynamic complement to a language game concept of language use.......Taking it's point of departure in some critical remarks to some of the most important recent theorizing of learning in the workplace, this chapter presents an alternative framework for theorizing learning as a subjective process in a social and societal context, based in life history research. Key...

Aging increases the susceptibility to motor memory interference and reduces off-line gains in motor skill learning

DEFF Research Database (Denmark)

Roig, Marc; Ritterband-Rosenbaum, Anina; Jensen, Jesper Lundbye

2014-01-01

Declines in the ability to learn motor skills in older adults are commonly attributed to deficits in the encoding of sensorimotor information during motor practice. We investigated whether aging also impairs motor memory consolidation by assessing the susceptibility to memory interference and off...... greater susceptibility to memory interference and no off-line gains in motor skill learning. Performing B produced memory interference and reduced off-line gains only in the older group. However, older adults also showed deficits in memory consolidation independent of the interfering effects of B. Age......-related declines in motor skill learning are not produced exclusively by deficits in the encoding of sensorimotor information during practice. Aging also increases the susceptibility to memory interference and reduces off-line gains in motor skill learning after practice....

Why copy others? Insights from the social learning strategies tournament.

Science.gov (United States)

Rendell, L; Boyd, R; Cownden, D; Enquist, M; Eriksson, K; Feldman, M W; Fogarty, L; Ghirlanda, S; Lillicrap, T; Laland, K N

2010-04-09

Social learning (learning through observation or interaction with other individuals) is widespread in nature and is central to the remarkable success of humanity, yet it remains unclear why copying is profitable and how to copy most effectively. To address these questions, we organized a computer tournament in which entrants submitted strategies specifying how to use social learning and its asocial alternative (for example, trial-and-error learning) to acquire adaptive behavior in a complex environment. Most current theory predicts the emergence of mixed strategies that rely on some combination of the two types of learning. In the tournament, however, strategies that relied heavily on social learning were found to be remarkably successful, even when asocial information was no more costly than social information. Social learning proved advantageous because individuals frequently demonstrated the highest-payoff behavior in their repertoire, inadvertently filtering information for copiers. The winning strategy (discountmachine) relied nearly exclusively on social learning and weighted information according to the time since acquisition.

Optimizing learning path selection through memetic algorithms

NARCIS (Netherlands)

Acampora, G.; Gaeta, M.; Loia, V.; Ritrovato, P.; Salerno, S.

2008-01-01

e-Learning is a critical support mechanism for industrial and academic organizations to enhance the skills of employees and students and, consequently, the overall competitiveness in the new economy. The remarkable velocity and volatility of modern knowledge require novel learning methods offering

Adaptive and perceptual learning technologies in medical education and training.

Science.gov (United States)

Kellman, Philip J

2013-10-01

Recent advances in the learning sciences offer remarkable potential to improve medical education and maximize the benefits of emerging medical technologies. This article describes 2 major innovation areas in the learning sciences that apply to simulation and other aspects of medical learning: Perceptual learning (PL) and adaptive learning technologies. PL technology offers, for the first time, systematic, computer-based methods for teaching pattern recognition, structural intuition, transfer, and fluency. Synergistic with PL are new adaptive learning technologies that optimize learning for each individual, embed objective assessment, and implement mastery criteria. The author describes the Adaptive Response-Time-based Sequencing (ARTS) system, which uses each learner's accuracy and speed in interactive learning to guide spacing, sequencing, and mastery. In recent efforts, these new technologies have been applied in medical learning contexts, including adaptive learning modules for initial medical diagnosis and perceptual/adaptive learning modules (PALMs) in dermatology, histology, and radiology. Results of all these efforts indicate the remarkable potential of perceptual and adaptive learning technologies, individually and in combination, to improve learning in a variety of medical domains. Reprint & Copyright © 2013 Association of Military Surgeons of the U.S.

Psychosocial modulators of motor learning in Parkinson’s disease

Directory of Open Access Journals (Sweden)

Petra eZemankova

2016-02-01

Full Text Available Using the remarkable overlap between brain circuits affected in Parkinson’s disease (PD and those underlying motor sequence learning, we may improve the effectiveness of motor rehabilitation interventions by identifying motor learning facilitators in PD. For instance, additional sensory stimulation and task cueing enhanced motor learning in people with PD, whereas exercising using musical rhythms or console computer games improved gait and balance, and reduced some motor symptoms, in addition to increasing task enjoyment. Yet, despite these advances, important knowledge gaps remain. Most studies investigating motor learning in PD used laboratory-specific tasks and equipment, with little resemblance to real life situations. Thus, it is unknown whether similar results could be achieved in more ecological setups and whether individual’s task engagement could further improve motor learning capacity. Moreover, the role of social interaction in motor skill learning process has not yet been investigated in PD and the role of mind-set and self-regulatory mechanisms have been sporadically examined. Here we review evidence suggesting that these psychosocial factors may be important modulators of motor learning in PD. We propose their incorporation in future research, given that it could lead to development of improved non-pharmacological interventions aimed to preserve or restore motor function in PD.

Exploring e-learning knowledge through ontological memetic agents

NARCIS (Netherlands)

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

2010-01-01

E-Learning systems have proven to be fundamental in several areas of tertiary education and in business companies. There are many significant advantages for people who learn online such as convenience, portability, flexibility and costs. However, the remarkable velocity and volatility of modern

Concluding Remarks | Ewing | Rwanda Journal

African Journals Online (AJOL)

Rwanda Journal. Journal Home · ABOUT THIS JOURNAL · Advanced Search · Current Issue · Archives · Journal Home > Vol 2, No 2 (2015) >. Log in or Register to get access to full text downloads. Username, Password, Remember me, or Register. Concluding Remarks. Helen Ewing. Abstract. No Abstract. Full Text:.

Optimized mixed oils remarkably reduce the amount of surfactants in microemulsions without affecting oral bioavailability of ibuprofen by simultaneously enlarging microemulsion areas and enhancing drug solubility.

Science.gov (United States)

Chen, Yizhen; Tuo, Jue; Huang, Huizhi; Liu, Dan; You, Xiuhua; Mai, Jialuo; Song, Jiaqi; Xie, Yanqi; Wu, Chuanbin; Hu, Haiyan

2015-06-20

The toxicity and irritation associated with high amounts of surfactants restrict the extensive utilization of microemulsions. To address these shortcomings, employing mixed oils to enlarge microemulsion areas therefore reducing surfactant contents is a promising strategy. However, what kinds of mixed oils are more efficient in enlarging microemulsion areas still remains unclear. In this research, we found that the chain length and degree of unsaturation of oils play a key role in enlarging microemulsion areas. The combination of moderate chain saturated oil caprylic/capric triglyceride (GTCC) with long chain unsaturated oil glycerol trioleate significantly increased the microemulsion areas. Solubility of ibuprofen in the mixed oils was unexpectedly and remarkably increased (almost 300mg/mL) compared with that (around 100mg/mL) of the single oil (GTCC), which also resulted in greatly increased solubility of ibuprofen in mixed oils-containing microemulsions. By optimizing the mixed oil formulation, the absolute amount of surfactant in drug-loaded microemulsions was reduced but increased drug oral bioavailability in rats was maintained. It could be concluded that the combined use of moderate chain oils and long chain unsaturated oils could not only acquire enlarged microemulsion areas but also enhanced drug solubility, therefore doubly reducing surfactant amount, which is extremely beneficial for developing safe microemulsions. Copyright © 2015. Published by Elsevier B.V.

Perceptual learning to reduce sensory eye dominance beyond the focus of top-down visual attention.

Science.gov (United States)

Xu, Jingping P; He, Zijiang J; Ooi, Teng Leng

2012-05-15

Perceptual learning is an important means for the brain to maintain its agility in a dynamic environment. Top-down focal attention, which selects task-relevant stimuli against competing ones in the background, is known to control and select what is learned in adults. Still unknown, is whether the adult brain is able to learn highly visible information beyond the focus of top-down attention. If it is, we should be able to reveal a purely stimulus-driven perceptual learning occurring in functions that are largely determined by the early cortical level, where top-down attention modulation is weak. Such an automatic, stimulus-driven learning mechanism is commonly assumed to operate only in the juvenile brain. We performed perceptual training to reduce sensory eye dominance (SED), a function that taps on the eye-of-origin information represented in the early visual cortex. Two retinal locations were simultaneously stimulated with suprathreshold, dichoptic orthogonal gratings. At each location, monocular cueing triggered perception of the grating images of the weak eye and suppression of the strong eye. Observers attended only to one location and performed orientation discrimination of the gratings seen by the weak eye, while ignoring the highly visible gratings at the second, unattended, location. We found SED was not only reduced at the attended location, but also at the unattended location. Furthermore, other untrained visual functions mediated by higher cortical levels improved. An automatic, stimulus-driven learning mechanism causes synaptic alterations in the early cortical level, with a far-reaching impact on the later cortical levels. Copyright © 2011 Elsevier Ltd. All rights reserved.

The challenge of education and learning in the developing world.

Science.gov (United States)

Kremer, Michael; Brannen, Conner; Glennerster, Rachel

2013-04-19

Across many different contexts, randomized evaluations find that school participation is sensitive to costs: Reducing out-of-pocket costs, merit scholarships, and conditional cash transfers all increase schooling. Addressing child health and providing information on how earnings rise with education can increase schooling even more cost-effectively. However, among those in school, test scores are remarkably low and unresponsive to more-of-the-same inputs, such as hiring additional teachers, buying more textbooks, or providing flexible grants. In contrast, pedagogical reforms that match teaching to students' learning levels are highly cost effective at increasing learning, as are reforms that improve accountability and incentives, such as local hiring of teachers on short-term contracts. Technology could potentially improve pedagogy and accountability. Improving pre- and postprimary education are major future challenges.

d-Cycloserine reduces context specificity of sexual extinction learning.

Science.gov (United States)

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

2015-11-01

d-Cycloserine (DCS) enhances extinction processes in animals. Although classical conditioning is hypothesized to play a pivotal role in the aetiology of appetitive motivation problems, no research has been conducted on the effect of DCS on the reduction of context specificity of extinction in human appetitive learning, while facilitation hereof is relevant in the context of treatment of problematic reward-seeking behaviors. Female participants were presented with two conditioned stimuli (CSs) that either predicted (CS+) or did not predict (CS-) a potential sexual reward (unconditioned stimulus (US); genital vibrostimulation). Conditioning took place in context A and extinction in context B. Subjects received DCS (125mg) or placebo directly after the experiment on day 1 in a randomized, double-blind, between-subject fashion (Placebo n=31; DCS n=31). Subsequent testing for CS-evoked conditioned responses (CRs) in both the conditioning (A) and the extinction context (B) took place 24h later on day 2. Drug effects on consolidation were then assessed by comparing the recall of sexual extinction memories between the DCS and the placebo groups. Post learning administration of DCS facilitates sexual extinction memory consolidation and affects extinction's fundamental context specificity, evidenced by reduced conditioned genital and subjective sexual responses, relative to placebo, for presentations of the reward predicting cue 24h later outside the extinction context. DCS makes appetitive extinction memories context-independent and prevents the return of conditioned response. NMDA receptor glycine site agonists may be potential pharmacotherapies for the prevention of relapse of appetitive motivation disorders with a learned component. Copyright © 2015 Elsevier Inc. All rights reserved.

Displays mounted on cutting blocks reduce the learning curve in navigated total knee arthroplasty.

Science.gov (United States)

Schnurr, Christoph; Eysel, Peer; König, Dietmar Pierre

2011-01-01

The use of computer navigation in total knee arthroplasty (TKA) improves the implant alignment but increases the operation time. Studies have shown that the operation time is further prolonged due to the surgeon's learning curve, and longer operation times have been associated with higher morbidity risks. It has been our hypothesis that an improvement in the human-machine interface might reduce the time required during the learning curve. Accordingly, we asked whether the use of navigation devices with a display fixed on the surgical instruments would reduce the operation time in navigated TKAs performed by navigation beginners. Thirty medical students were randomized and used two navigation devices in rotation: these were the Kolibri® device with an external display and the Dash® device with a display that was fixed on the cutting blocks. The time for adjustment of the tibial and femoral cutting blocks on knee models while using these devices was measured. A significant time reduction was demonstration when the Dash® device was used: The time reduction was 21% for the tibial block (p = 0.007), 40% for the femoral block (p learning curve may be diminished.

Statistical learning methods: Basics, control and performance

Energy Technology Data Exchange (ETDEWEB)

Zimmermann, J. [Max-Planck-Institut fuer Physik, Foehringer Ring 6, 80805 Munich (Germany)]. E-mail: zimmerm@mppmu.mpg.de

2006-04-01

The basics of statistical learning are reviewed with a special emphasis on general principles and problems for all different types of learning methods. Different aspects of controlling these methods in a physically adequate way will be discussed. All principles and guidelines will be exercised on examples for statistical learning methods in high energy and astrophysics. These examples prove in addition that statistical learning methods very often lead to a remarkable performance gain compared to the competing classical algorithms.

Statistical learning methods: Basics, control and performance

International Nuclear Information System (INIS)

Zimmermann, J.

2006-01-01

The basics of statistical learning are reviewed with a special emphasis on general principles and problems for all different types of learning methods. Different aspects of controlling these methods in a physically adequate way will be discussed. All principles and guidelines will be exercised on examples for statistical learning methods in high energy and astrophysics. These examples prove in addition that statistical learning methods very often lead to a remarkable performance gain compared to the competing classical algorithms

Understanding and reducing student withdrawal in e-learning

Directory of Open Access Journals (Sweden)

Marko Radovan

2012-03-01

Full Text Available In this paper we address the problem of student dropout from e-learning programmes. The proponents of e-learning highlight several advantages of this type of education as compared to the traditional, such as greater openness and diversity of training materials, the ability to adjust the mode and speed of learning, and similar. Despite these advantages, an increasing number of programmes and acceptance of e-learning as a national strategy all around the world, e-learning providers also face the problem of drop-outs. Research shows that student dropout in educational programmes implemented in the form of e-learning is higher than in traditional programmes. The reasons that affect the dropout rate should be considered when designing and implementing e-learning programmes

Improving ability mathematic literacy, self-efficacy and reducing mathematical anxiety with learning Treffinger model at senior high school students

Directory of Open Access Journals (Sweden)

Hafizh Nizham

2017-12-01

Full Text Available This study is a Quasi Experimental study with the design of The Pretest-Post-Test Non-Equivalent Group Design. Population in this research is all student of class X SHS in South Jakarta. Sampling is done by purposive sampling, to obtain an experimental class and control class. In the experimental class, students learn with Treffinger learning model and control, class learning with conventional learning. This study is also to examine the differences of self-efficacy improvement and students literacy skills, and decreased students' mathematical anxiety. Also, this study also examines the relevance of early mathematical abilities (high, medium, low with improving students' math literacy skills. The instrument used in this research is literacy skill test, self-efficacy scale, mathematical anxiety scale, observation sheet, and student interview. Data were analyzed by t-test, one-way ANOVA, and two lines. From the results of the data, it is found that: (1 The improvement of literacy ability of students who are learned with Treffinger model learning is not significantly higher than students who learn with conventional. (2 The self-efficacy of students who learning with the Treffinger model learning  is better than the student that is learning by conventional. (3 The mathematical anxiety of students learning with Treffinger model learning reduces better than students learning with conventional. (4 There is a difference in the improvement of students' mathematical literacy skills learning by learning the Treffinger model and students learning with conventional learning based on early mathematical abilities. (5 Student response to Treffinger model learning is better than students learning with conventional learning. Therefore, learning model Treffinger can be an alternative model of learning to improve students' mathematical literacy skills, and self-efficacy students, and able to reduce mathematical anxiety.

Reinforcement Learning for Ramp Control: An Analysis of Learning Parameters

Directory of Open Access Journals (Sweden)

Chao Lu

2016-08-01

Full Text Available Reinforcement Learning (RL has been proposed to deal with ramp control problems under dynamic traffic conditions; however, there is a lack of sufficient research on the behaviour and impacts of different learning parameters. This paper describes a ramp control agent based on the RL mechanism and thoroughly analyzed the influence of three learning parameters; namely, learning rate, discount rate and action selection parameter on the algorithm performance. Two indices for the learning speed and convergence stability were used to measure the algorithm performance, based on which a series of simulation-based experiments were designed and conducted by using a macroscopic traffic flow model. Simulation results showed that, compared with the discount rate, the learning rate and action selection parameter made more remarkable impacts on the algorithm performance. Based on the analysis, some suggestionsabout how to select suitable parameter values that can achieve a superior performance were provided.

Characterizing the Learning Effect in Response to Biofeedback Aimed at Reducing Tibial Acceleration during Running

Directory of Open Access Journals (Sweden)

Linda M. A. van Gelder

2018-02-01

Full Text Available Increased tibial acceleration has been found to be an important risk factor for tibial stress fractures. Interventions aimed at reducing this variable which found a beneficial effect include the use of biofeedback in gait retraining. However, no studies have focused on the time participants take to modify tibial acceleration, therefore we aimed to find the start of a learning plateau in this study. Six participants ran on a treadmill while multisensory feedback was given. A single-subject analysis was used to characterise the learning effects. All participants changed peak tibial acceleration within the first step of running in the feedback condition. Two participants further reduced tibial acceleration to reach a plateau within 120 steps. In four of the six participants a strong effect of the feedback was still present after a week. Further research is needed to optimise the use of biofeedback in reducing the prevalence of tibial stress fractures.

Understanding and reducing student withdrawal in e-learning

OpenAIRE

Marko Radovan

2012-01-01

In this paper we address the problem of student dropout from e-learning programmes. The proponents of e-learning highlight several advantages of this type of education as compared to the traditional, such as greater openness and diversity of training materials, the ability to adjust the mode and speed of learning, and similar. Despite these advantages, an increasing number of programmes and acceptance of e-learning as a national strategy all around the world, e-learning providers also face th...

Does Hearing Several Speakers Reduce Foreign Word Learning?

Science.gov (United States)

Ludington, Jason Darryl

2016-01-01

Learning spoken word forms is a vital part of second language learning, and CALL lends itself well to this training. Not enough is known, however, about how auditory variation across speech tokens may affect receptive word learning. To find out, 144 Thai university students with no knowledge of the Patani Malay language learned 24 foreign words in…

Remarks on superconductive networks

International Nuclear Information System (INIS)

Dominguez, D.; Lopez, A.R.N.; Simonin, J.M.

1989-01-01

Some remarks on the determination of the normal-superconductor phase boundary in random superconductive networks are made. A recently reported work by Soukoulis, Grest and Li which introduces weak links between nodes as these are removed in the site percolation problem is discussed. By the analysis of two simple geometries, it is shown that this procedure introduces spurious effects which mask the physical properties of the system. These affect in particular the field slope critical index and the sharpness of the normal-superconductor boundary. (Author)

Training, Simulation, the Learning Curve, and How to Reduce Complications in Urology.

Science.gov (United States)

Brunckhorst, Oliver; Volpe, Alessandro; van der Poel, Henk; Mottrie, Alexander; Ahmed, Kamran

2016-04-01

Urology is at the forefront of minimally invasive surgery to a great extent. These procedures produce additional learning challenges and possess a steep initial learning curve. Training and assessment methods in surgical specialties such as urology are known to lack clear structure and often rely on differing operative flow experienced by individuals and institutions. This article aims to assess current urology training modalities, to identify the role of simulation within urology, to define and identify the learning curves for various urologic procedures, and to discuss ways to decrease complications in the context of training. A narrative review of the literature was conducted through December 2015 using the PubMed/Medline, Embase, and Cochrane Library databases. Evidence of the validity of training methods in urology includes observation of a procedure, mentorship and fellowship, e-learning, and simulation-based training. Learning curves for various urologic procedures have been recommended based on the available literature. The importance of structured training pathways is highlighted, with integration of modular training to ensure patient safety. Valid training pathways are available in urology. The aim in urology training should be to combine all of the available evidence to produce procedure-specific curricula that utilise the vast array of training methods available to ensure that we continue to improve patient outcomes and reduce complications. The current evidence for different training methods available in urology, including simulation-based training, was reviewed, and the learning curves for various urologic procedures were critically analysed. Based on the evidence, future pathways for urology curricula have been suggested to ensure that patient safety is improved. Copyright © 2016 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Discriminative Nonlinear Analysis Operator Learning: When Cosparse Model Meets Image Classification.

Science.gov (United States)

Wen, Zaidao; Hou, Biao; Jiao, Licheng

2017-05-03

Linear synthesis model based dictionary learning framework has achieved remarkable performances in image classification in the last decade. Behaved as a generative feature model, it however suffers from some intrinsic deficiencies. In this paper, we propose a novel parametric nonlinear analysis cosparse model (NACM) with which a unique feature vector will be much more efficiently extracted. Additionally, we derive a deep insight to demonstrate that NACM is capable of simultaneously learning the task adapted feature transformation and regularization to encode our preferences, domain prior knowledge and task oriented supervised information into the features. The proposed NACM is devoted to the classification task as a discriminative feature model and yield a novel discriminative nonlinear analysis operator learning framework (DNAOL). The theoretical analysis and experimental performances clearly demonstrate that DNAOL will not only achieve the better or at least competitive classification accuracies than the state-of-the-art algorithms but it can also dramatically reduce the time complexities in both training and testing phases.

Keeping Pace with K-12 Online Learning, 2016

Science.gov (United States)

Gemin, Butch; Pape, Larry

2017-01-01

"Keeping Pace with K-12 Online Learning 2016" marks the thirteenth consecutive year Evergreen has published its annual research of the K-12 education online learning market. The thirteen years of researching, writing and publishing this report represents a time of remarkable change. There has been a constant presence that has become the…

Concluding Remarks: Experiment from a materials perspective

International Nuclear Information System (INIS)

Fisk, Z

2011-01-01

The author provides some remarks regarding the current status of experiments in strongly correlated electron systems. By construction, they are biased by the author's perspectives at the time of writing.

Hidden Dangers of Computer Modelling: Remarks on Sokolik and Smith's Connectionist Learning Model of French Gender.

Science.gov (United States)

Carroll, Susanne E.

1995-01-01

Criticizes the computer modelling experiments conducted by Sokolik and Smith (1992), which involved the learning of French gender attribution using connectionist architecture. The article argues that the experiments greatly oversimplified the complexity of gender learning, in that they were designed in such a way that knowledge that must be…

2011 Asia Pacific Few-Body Conference Summary Remarks

International Nuclear Information System (INIS)

Gibson, B. F.

2013-01-01

These remarks represent the author’s personal perspective regarding ideas presented at this fifth Asia Pacific Conference on Few-Body Problems in Physics. They are not intended as a comprehensive summary of what we witnessed during this week of stimulating presentations and intense discussions. However, these remarks do characterize some of the physics we heard and some of the key questions raised. The ideas presented will hopefully outlive the rapporteurs who brought their work and that of others to our attention here in the International Hall of the Sungkyunkwan University in Seoul, Republic of Korea. (author)

A Role for Chunk Formation in Statistical Learning of Second Language Syntax

Science.gov (United States)

Hamrick, Phillip

2014-01-01

Humans are remarkably sensitive to the statistical structure of language. However, different mechanisms have been proposed to account for such statistical sensitivities. The present study compared adult learning of syntax and the ability of two models of statistical learning to simulate human performance: Simple Recurrent Networks, which learn by…

Remarks on the clump theory

International Nuclear Information System (INIS)

Krommes, J.A.

1986-07-01

Further details are provided of a soon-to-be published dialog [Phys. Fluids 29 (July, 1986)] which discussed the role of the small scales in fluid clump theory. It is argued that the approximation of the clump lifetime which is compatible with exponentially rapid separation of adjacent orbits is inappropriate for the description of the dynamically important large scales. Various other remarks are made relating to the analytic treatment of strong drift-wave-like turbulence

Remarks on the clump theory

International Nuclear Information System (INIS)

Krommes, J.A.

1986-01-01

Further details are provided of a recently published dialog [Phys. Fluids 29 (July, 1986)] which discussed the role of the small scales in fluid clump theory. It is argued that the approximation of the clump lifetime which is compatible with exponentially rapid separation of adjacent orbits is inappropriate for the description of the dynamically important large scales. Various other remarks are made relating to the analytic treatment of strong drift-wave-like turbulence. (author)

Remarks on High Energy Evolution

OpenAIRE

Kovner, Alex; Lublinsky, Michael

2005-01-01

We make several remarks on the B-JIMWLK hierarchy. First, we present a simple and instructive derivation of this equation by considering an arbitrary projectile wave function with small number of valence gluons. We also generalize the equation by including corrections which incorporate effects of high density in the projectile wave function. Second, we systematically derive the dipole model approximation to the hierarchy. We show that in the dipole approximation the hierarchy has a simplifyin...

Agent-specific learning signals for self-other distinction during mentalising.

Directory of Open Access Journals (Sweden)

Sam Ereira

2018-04-01

Full Text Available Humans have a remarkable ability to simulate the minds of others. How the brain distinguishes between mental states attributed to self and mental states attributed to someone else is unknown. Here, we investigated how fundamental neural learning signals are selectively attributed to different agents. Specifically, we asked whether learning signals are encoded in agent-specific neural patterns or whether a self-other distinction depends on encoding agent identity separately from this learning signal. To examine this, we tasked subjects to learn continuously 2 models of the same environment, such that one was selectively attributed to self and the other was selectively attributed to another agent. Combining computational modelling with magnetoencephalography (MEG enabled us to track neural representations of prediction errors (PEs and beliefs attributed to self, and of simulated PEs and beliefs attributed to another agent. We found that the representational pattern of a PE reliably predicts the identity of the agent to whom the signal is attributed, consistent with a neural self-other distinction implemented via agent-specific learning signals. Strikingly, subjects exhibiting a weaker neural self-other distinction also had a reduced behavioural capacity for self-other distinction and displayed more marked subclinical psychopathological traits. The neural self-other distinction was also modulated by social context, evidenced in a significantly reduced decoding of agent identity in a nonsocial control task. Thus, we show that self-other distinction is realised through an encoding of agent identity intrinsic to fundamental learning signals. The observation that the fidelity of this encoding predicts psychopathological traits is of interest as a potential neurocomputational psychiatric biomarker.

Machine Learning Topological Invariants with Neural Networks

Science.gov (United States)

Zhang, Pengfei; Shen, Huitao; Zhai, Hui

2018-02-01

In this Letter we supervisedly train neural networks to distinguish different topological phases in the context of topological band insulators. After training with Hamiltonians of one-dimensional insulators with chiral symmetry, the neural network can predict their topological winding numbers with nearly 100% accuracy, even for Hamiltonians with larger winding numbers that are not included in the training data. These results show a remarkable success that the neural network can capture the global and nonlinear topological features of quantum phases from local inputs. By opening up the neural network, we confirm that the network does learn the discrete version of the winding number formula. We also make a couple of remarks regarding the role of the symmetry and the opposite effect of regularization techniques when applying machine learning to physical systems.

Some remarks on the Bonnor-Swaminarayan solution

International Nuclear Information System (INIS)

Berezdivin, R.; Herrera, L.

1976-01-01

The letter re-examines the Bonnor-Swaminarayan solution with the aim to try a clarification of its physical interpretation. The radiative nature of the solution as suggested by Bicak is questioned and some remarks on this topic are given

The Effectiveness of Process-Oriented Guided Inquiry Learning to Reduce Alternative Conceptions in Secondary Chemistry

Science.gov (United States)

Barthlow, Michelle J.; Watson, Scott B.

2014-01-01

A nonequivalent, control group design was used to investigate student achievement in secondary chemistry. This study investigated the effect of process-oriented guided inquiry learning (POGIL) in high school chemistry to reduce alternate conceptions related to the particulate nature of matter versus traditional lecture pedagogy. Data were…

Children’s social learning : Variety is the spice of life

NARCIS (Netherlands)

Cox, R.F.A

2015-01-01

Two of the “challenges” with respect to children’s social learning identified in the overview of this workshop are: “learning the structure of others’ behavior” and “coupling one’s perceptual and motor actions to those of the social partner”. Remarkably, the most understudied aspect related to both

Deep Learning in Radiology.

Science.gov (United States)

McBee, Morgan P; Awan, Omer A; Colucci, Andrew T; Ghobadi, Comeron W; Kadom, Nadja; Kansagra, Akash P; Tridandapani, Srini; Auffermann, William F

2018-03-29

As radiology is inherently a data-driven specialty, it is especially conducive to utilizing data processing techniques. One such technique, deep learning (DL), has become a remarkably powerful tool for image processing in recent years. In this work, the Association of University Radiologists Radiology Research Alliance Task Force on Deep Learning provides an overview of DL for the radiologist. This article aims to present an overview of DL in a manner that is understandable to radiologists; to examine past, present, and future applications; as well as to evaluate how radiologists may benefit from this remarkable new tool. We describe several areas within radiology in which DL techniques are having the most significant impact: lesion or disease detection, classification, quantification, and segmentation. The legal and ethical hurdles to implementation are also discussed. By taking advantage of this powerful tool, radiologists can become increasingly more accurate in their interpretations with fewer errors and spend more time to focus on patient care. Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

"I'll stop procrastinating now!" Fostering specific processes of self-regulated learning to reduce academic procrastination.

Science.gov (United States)

Grunschel, Carola; Patrzek, Justine; Klingsieck, Katrin B; Fries, Stefan

2018-01-01

Academic procrastination is considered to be a result of self-regulation failure having detrimental effects on students' well-being and academic performance. In the present study, we developed and evaluated a group training that aimed to reduce academic procrastination. We based the training on a cyclical process model of self-regulated learning, thus, focusing on improving deficient processes of self-regulated learning among academic procrastinators (e.g., time management, dealing with distractions). The training comprised five sessions and took place once a week for 90 min in groups of no more than 10 students. Overall, 106 students completed the training. We evaluated the training using a comprehensive control group design with repeated measures (three points of measurement); the control group was trained after the intervention group's training. The results showed that our training was successful. The trained intervention group significantly reduced academic procrastination and improved specific processes of self-regulated learning (e.g., time management, concentration), whereas the untrained control group showed no change regarding these variables. After the control group had also been trained, the control group also showed the expected favorable changes. The students rated the training overall as good and found it recommendable for procrastinating friends. Hence, fostering self-regulatory processes in our intervention was a successful attempt to support students in reducing academic procrastination. The evaluation of the training encourages us to adapt the training for different groups of procrastinators.

Remarks about the hypothesis of limiting fragmentation

International Nuclear Information System (INIS)

Chou, T.T.; Yang, C.N.

1987-01-01

Remarks are made about the hypothesis of limiting fragmentation. In particular, the concept of favored and disfavored fragment distribution is introduced. Also, a sum rule is proved leading to a useful quantity called energy-fragmentation fraction. (author). 11 refs, 1 fig., 2 tabs

A Swarm-Based Learning Method Inspired by Social Insects

Science.gov (United States)

He, Xiaoxian; Zhu, Yunlong; Hu, Kunyuan; Niu, Ben

Inspired by cooperative transport behaviors of ants, on the basis of Q-learning, a new learning method, Neighbor-Information-Reference (NIR) learning method, is present in the paper. This is a swarm-based learning method, in which principles of swarm intelligence are strictly complied with. In NIR learning, the i-interval neighbor's information, namely its discounted reward, is referenced when an individual selects the next state, so that it can make the best decision in a computable local neighborhood. In application, different policies of NIR learning are recommended by controlling the parameters according to time-relativity of concrete tasks. NIR learning can remarkably improve individual efficiency, and make swarm more "intelligent".

The Role of School Libraries in Reducing Learning Disadvantages in Migrant Children

Directory of Open Access Journals (Sweden)

Ellen Kleijnen

2015-04-01

Full Text Available The educational achievement of children from non-Western migrant families in the Netherlands and other Western countries lags behind that of natives, especially when it comes to language proficiency and reading ability. This literature review pinpoints what is known and what is as yet unknown about reducing learning disadvantages through school libraries to point to directions for future research. A considerable body of research has shown that school libraries are positively related to learning outcomes in children, as well as to their reading behavior and attitude toward reading, factors that correlate positively with reading and language skills. However, on the basis of existing research, it is hard to draw firm conclusions about the effect of school libraries on students from migrant families in particular. This article indicates that future research should explicitly focus on the impact of school libraries’ reading promotion efforts on the reading behavior, attitude toward reading, and reading and language skills of migrant students, leading to more effective educational policies.

Polypyridyl iron(II) complexes showing remarkable photocytotoxicity ...

Indian Academy of Sciences (India)

aditya

Polypyridyl iron(II) complexes showing remarkable photocytotoxicity in visible light. ADITYA GARAI a. , UTTARA BASU a. , ILA PANT b. , PATURU KONDAIAH*. ,b. AND. AKHIL R. CHAKRAVARTY*. ,a a. Department of Inorganic and Physical Chemistry, Indian Institute of Science, Bangalore. 560012, India. E-mail: ...

Post-learning arousal enhances veridical memory and reduces false memory in the Deese-Roediger-McDermott paradigm.

Science.gov (United States)

Nielson, Kristy A; Correro, Anthony N

2017-10-01

The Deese-Roediger-McDermott (DRM) paradigm examines false memory by introducing words associated with a non-presented 'critical lure' as memoranda, which typically causes the lures to be remembered as frequently as studied words. Our prior work has shown enhanced veridical memory and reduced misinformation effects when arousal is induced after learning (i.e., during memory consolidation). These effects have not been examined in the DRM task, or with signal detection analysis, which can elucidate the mechanisms underlying memory alterations. Thus, 130 subjects studied and then immediately recalled six DRM lists, one after another, and then watched a 3-min arousing (n=61) or neutral (n=69) video. Recognition tested 70min later showed that arousal induced after learning led to better delayed discrimination of studied words from (a) critical lures, and (b) other non-presented 'weak associates.' Furthermore, arousal reduced liberal response bias (i.e., the tendency toward accepting dubious information) for studied words relative to all foils, including critical lures and 'weak associates.' Thus, arousal induced after learning effectively increased the distinction between signal and noise by enhancing access to verbatim information and reducing endorsement of dubious information. These findings provide important insights into the cognitive mechanisms by which arousal modulates early memory consolidation processes. Copyright © 2017 Elsevier Inc. All rights reserved.

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

NARCIS (Netherlands)

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

2011-01-01

Learning is a critical support mechanism for industrial and academic organizations to enhance the skills of employees and students and, consequently, the overall competitiveness in the new economy. The remarkable velocity and volatility of modern knowledge require novel learning methods offering

Closing remarks

International Nuclear Information System (INIS)

Reig, J.

2007-01-01

Good afternoon. Before providing the closing remarks on behalf of the NEA, I would like to take this opportunity and make some personal reflections, if you allow me Mr. Chairman. I have had the opportunity to take part in the three workshops on public communication organised by the NEA. In the first one in Paris in 2000, representing my country, Spain, and in the two last ones in Ottawa in 2004 and Tokyo today, on behalf of the NEA. The topics for the three workshops follow a logical order, first the focus was on investing in trust in a time when public communication was becoming a big challenge for the regulators. Second, maintaining and measuring public confidence to assess how credible regulators are in front of the public; and finally here in Tokyo, transparency, which is a basic element to achieve trust and credibility. In my view, a regulatory decision has three main components, it has to be technically sound. legally correct and well communicated. The emphasis in the early years was in the technical matters, till legal issues became a key element to achieve the political acceptance from governments and local authorities. Finally the public communication aspects resulted into a major effort and challenge to achieve social acceptance. (author)

Concluding theoretical remarks

International Nuclear Information System (INIS)

Ellis, J.

1986-01-01

My task in this talk is to review the happenings of this workshop from a theoretical perspective, and to emphasize lines for possible future research. My remarks are organized into a theoretical overview of the what, why, (mainly the hierarchy problem) how, (supersymmetry must be broken: softly or spontaneously, and if the latter, by means of a new U tilde(1) gauge group or through the chiral superfields) when (how heavy are supersymmetric partner particles in different types of theories) and where (can one find evidence for) supersymmetry. In the last part are discussed various ongoing and future searches for photinos γ tilde, gravitinos G tilde, the U vector boson, shiggses H tilde, squarks q tilde and sleptons l tilde, gluinos g tilde, winos W tilde and other gauginos, as well as hunts for indirect effects of supersymmetry, such as for example in baryon decay. Finally there is a little message of encouragement to our experimental colleagues, based on historical precedent. (orig.)

Methods for reducing interference in the Complementary Learning Systems model: oscillating inhibition and autonomous memory rehearsal.

Science.gov (United States)

Norman, Kenneth A; Newman, Ehren L; Perotte, Adler J

2005-11-01

The stability-plasticity problem (i.e. how the brain incorporates new information into its model of the world, while at the same time preserving existing knowledge) has been at the forefront of computational memory research for several decades. In this paper, we critically evaluate how well the Complementary Learning Systems theory of hippocampo-cortical interactions addresses the stability-plasticity problem. We identify two major challenges for the model: Finding a learning algorithm for cortex and hippocampus that enacts selective strengthening of weak memories, and selective punishment of competing memories; and preventing catastrophic forgetting in the case of non-stationary environments (i.e. when items are temporarily removed from the training set). We then discuss potential solutions to these problems: First, we describe a recently developed learning algorithm that leverages neural oscillations to find weak parts of memories (so they can be strengthened) and strong competitors (so they can be punished), and we show how this algorithm outperforms other learning algorithms (CPCA Hebbian learning and Leabra at memorizing overlapping patterns. Second, we describe how autonomous re-activation of memories (separately in cortex and hippocampus) during REM sleep, coupled with the oscillating learning algorithm, can reduce the rate of forgetting of input patterns that are no longer present in the environment. We then present a simple demonstration of how this process can prevent catastrophic interference in an AB-AC learning paradigm.

Patient safety: lessons learned

International Nuclear Information System (INIS)

Bagian, James P.

2006-01-01

The traditional approach to patient safety in health care has ranged from reticence to outward denial of serious flaws. This undermines the otherwise remarkable advances in technology and information that have characterized the specialty of medical practice. In addition, lessons learned in industries outside health care, such as in aviation, provide opportunities for improvements that successfully reduce mishaps and errors while maintaining a standard of excellence. This is precisely the call in medicine prompted by the 1999 Institute of Medicine report ''To Err Is Human: Building a Safer Health System.'' However, to effect these changes, key components of a successful safety system must include: (1) communication, (2) a shift from a posture of reliance on human infallibility (hence ''shame and blame'') to checklists that recognize the contribution of the system and account for human limitations, and (3) a cultivation of non-punitive open and/or de-identified/anonymous reporting of safety concerns, including close calls, in addition to adverse events. (orig.)

Evaluating theories of bird song learning: implications for future directions.

Science.gov (United States)

Margoliash, D

2002-12-01

Studies of birdsong learning have stimulated extensive hypotheses at all levels of behavioral and physiological organization. This hypothesis building is valuable for the field and is consistent with the remarkable range of issues that can be rigorously addressed in this system. The traditional instructional (template) theory of song learning has been challenged on multiple fronts, especially at a behavioral level by evidence consistent with selectional hypotheses. In this review I highlight the caveats associated with these theories to better define the limits of our knowledge and identify important experiments for the future. The sites and representational forms of the various conceptual entities posited by the template theory are unknown. The distinction between instruction and selection in vocal learning is not well established at a mechanistic level. There is as yet insufficient neurophysiological data to choose between competing mechanisms of error-driven learning and reinforcement learning. Both may obtain for vocal learning. The possible role of sleep in acoustic or procedural memory consolidation, while supported by some physiological observations, does not yet have support in the behavioral literature. The remarkable expansion of knowledge in the past 20 years and the recent development of new technologies for physiological and behavioral experiments should permit direct tests of these theories in the coming decade.

Negative affect reduces performance in implicit sequence learning.

Directory of Open Access Journals (Sweden)

Junchen Shang

Full Text Available BACKGROUND: It is well documented that positive rather than negative moods encourage integrative processing of conscious information. However, the extent to which implicit or unconscious learning can be influenced by affective states remains unclear. METHODOLOGY/PRINCIPAL FINDINGS: A Serial Reaction Time (SRT task with sequence structures requiring integration over past trials was adopted to examine the effect of affective states on implicit learning. Music was used to induce and maintain positive and negative affective states. The present study showed that participants in negative rather than positive states learned less of the regularity. Moreover, the knowledge was shown by a Bayesian analysis to be largely unconscious as participants were poor at recognizing the regularity. CONCLUSIONS/SIGNIFICANCE: The results demonstrated that negative rather than positive affect inhibited implicit learning of complex structures. Our findings help to understand the effects of affective states on unconscious or implicit processing.

Remarks on the elaboration of an English–Spanish ...

African Journals Online (AJOL)

Spanish word-combination dictionary examined here, some concluding remarks are made with regard to the educational implications of this kind of dictionary primarily aimed at intermediate- to advanced-level Spanish-speaking EFL learners.

Self-study program on HTML browser--application to Clinical Nursing General Remarks Course.

Science.gov (United States)

Ochiai, N; Sota, Y; Ezumi, H

1997-01-01

We created a self-study program using HTML browser on the Clinical Nursing General Remarks Course, Eighty-three students each selected a published book on a personal history (written personal reflections from individuals who had undergone medical treatment and hospitalization), read it and submitted reports of their impressions of the histories. Their reports were arranged from a nursing perspective and entered on the home page of our college using HTML browser. We intended that the students would become more interested in reading of the personal histories, and that they would acquire new self-study skills and increase their interest in Internet through use of our program. In addition, we hoped that this program would encourage positive communication and mutual sharing of information. The students were able to easily refer to a personal history according to their interest from a nursing perspective. Therefore this program realized the mutual learning among students and other users.

A Deep Learning based Approach to Reduced Order Modeling of Fluids using LSTM Neural Networks

Science.gov (United States)

Mohan, Arvind; Gaitonde, Datta

2017-11-01

Reduced Order Modeling (ROM) can be used as surrogates to prohibitively expensive simulations to model flow behavior for long time periods. ROM is predicated on extracting dominant spatio-temporal features of the flow from CFD or experimental datasets. We explore ROM development with a deep learning approach, which comprises of learning functional relationships between different variables in large datasets for predictive modeling. Although deep learning and related artificial intelligence based predictive modeling techniques have shown varied success in other fields, such approaches are in their initial stages of application to fluid dynamics. Here, we explore the application of the Long Short Term Memory (LSTM) neural network to sequential data, specifically to predict the time coefficients of Proper Orthogonal Decomposition (POD) modes of the flow for future timesteps, by training it on data at previous timesteps. The approach is demonstrated by constructing ROMs of several canonical flows. Additionally, we show that statistical estimates of stationarity in the training data can indicate a priori how amenable a given flow-field is to this approach. Finally, the potential and limitations of deep learning based ROM approaches will be elucidated and further developments discussed.

Alberta High School, College Elevate Learning with Rare Joint Venture

Science.gov (United States)

Pearson, George

2012-01-01

The refusal by a group of parents in Olds, Alberta, in 2003 to accept a provincial grant to renovate their high school set in motion a remarkable collaboration that spawned an innovative learning campus for an entire community and beyond. The new Olds High School, which opened in 2010, is part of a new Community Learning Campus (CLC), a joint…

Using Audiovisual TV Interviews to Create Visible Authors that Reduce the Learning Gap between Native and Non-Native Language Speakers

Science.gov (United States)

Inglese, Terry; Mayer, Richard E.; Rigotti, Francesca

2007-01-01

Can archives of audiovisual TV interviews be used to make authors more visible to students, and thereby reduce the learning gap between native and non-native language speakers in college classes? We examined students in a college course who learned about one scholar's ideas through watching an audiovisual TV interview (i.e., visible author format)…

Learning to REDUCE: A Reduced Electricity Consumption Prediction Ensemble

Energy Technology Data Exchange (ETDEWEB)

Aman, Saima; Chelmis, Charalampos; Prasanna, Viktor

2016-02-12

Utilities use Demand Response (DR) to balance supply and demand in the electric grid by involving customers in efforts to reduce electricity consumption during peak periods. To implement and adapt DR under dynamically changing conditions of the grid, reliable prediction of reduced consumption is critical. However, despite the wealth of research on electricity consumption prediction and DR being long in practice, the problem of reduced consumption prediction remains largely un-addressed. In this paper, we identify unique computational challenges associated with the prediction of reduced consumption and contrast this to that of normal consumption and DR baseline prediction.We propose a novel ensemble model that leverages different sequences of daily electricity consumption on DR event days as well as contextual attributes for reduced consumption prediction. We demonstrate the success of our model on a large, real-world, high resolution dataset from a university microgrid comprising of over 950 DR events across a diverse set of 32 buildings. Our model achieves an average error of 13.5%, an 8.8% improvement over the baseline. Our work is particularly relevant for buildings where electricity consumption is not tied to strict schedules. Our results and insights should prove useful to the researchers and practitioners working in the sustainable energy domain.

How to Improve Learning when Going Online Using POPBL

DEFF Research Database (Denmark)

Borch, Ole; Helbo, Jan; Madsen, Per Printz

2007-01-01

, Pedagogical and Technological (DPT) methods must be selected and used properly to ensure progress in the learning process. Although it has never been proven that PBL increases learning, there are many observations indicating improved learning, e.g. the students are able to learn more beyond required...... objectives within the defined time slot. The remote online education Master of Industrial Information Technology (MII) at Aalborg University (AAU), Denmark, is using collaborative Project Organized PBL (POPBL) and is using new DPT resulting in very high motivation and in remarkable learning results......It is accepted worldwide; that Problem Based Learning (PBL) is a very fine method to improve learning motivation and to satisfy the students being more innovative and creative. Progress in learning is supported by teaching, individual and team reflections and collaborative project work. On...

Remarks concerning two sympatric seedeaters Poliospiza spp. in ...

African Journals Online (AJOL)

Turner, D.A., Finch, B.F, & Hunter, N.D. Remarks concerning the all-black coastal boubous. (Laniarius ... Currently, however, there is little evidence to support such a theory, and it is .... twigs with its beak in order to increase the size of the hole.

Theorizing Learning in Life History - a psycho-societal approach

DEFF Research Database (Denmark)

Olesen, Henning Salling

2007-01-01

to the understanding of knowledge, based on examples from the author's research into professional learning (general practitioners). The pivotal role of language use and language socialisation is explained in brief, developing a psychodynamic complement to a language game concept of language use.......  Taking it's point of departure in some critical remarks to some of the most important recent theorizing of learning, this article presents an alternative framework for theorizing learning as a subjective process in a social and societal context, based in life history research. Key concepts...

Chemical physics of electroactive materials: concluding remarks.

Science.gov (United States)

Rutland, Mark W

2017-07-01

It is an honour to be charged with providing the concluding remarks for a Faraday Discussion. As many have remarked before, it is nonetheless a prodigious task, and what follows is necessarily a personal, and probably perverse, view of a watershed event in the Chemical Physics of Electroactive materials. The spirit of the conference was captured in a single sentence during the meeting itself."It is the nexus between rheology, electrochemistry, colloid science and energy storage". The current scientific climate is increasingly dominated by a limited number of global challenges, and there is thus a tendency for research to resemble a football match played by 6 year olds, where everyone on the field chases the (funding) ball instead of playing to their "discipline". It is thus reassuring to see how the application of rigorous chemical physics is leading to ingenious new solutions for both energy storage and harvesting, via, for example, nanoactuation, electrowetting, ionic materials and nanoplasmonics. In fact, the same language of chemical physics allows seamless transition between applications as diverse as mechano-electric energy generation, active moisture transport and plasmonic shutters - even the origins of life were addressed in the context of electro-autocatalysis!

Remarkable long-range-systematic in the binding energies of α-nuclei. II

International Nuclear Information System (INIS)

Gross, D.H.E.

2003-01-01

In this Letter I present further data that show the remarkable evidence for the existence of an α-cluster structure in the ground states of even-even N=Z nuclei. Such a remarkable systematic was observed 20 years ago Gross and Nemes [Phys. Lett. B 130 (1983) 131] for these nuclei at A≤72 and is extended here up to A=100

Development of REI meetings (concluding remarks)

International Nuclear Information System (INIS)

Roessler, K.

1988-01-01

It is an honour and a pleasure to deliver the concluding remarks of this Fourth International Conference on Radiation Effects in Insulators. After commenting upon the present meeting, the genesis of REI conferences, their aims and position relative to related meetings in radiation and ion implantation research will be treated, particularly in order to inform new-comers. The development of the last four REI meetings will be discussed on the base of a statistical analysis. Some recommendations and an outlook of future trends will be given. (orig.)

The European Public Prosecutor's Office (EPPO): Introductory Remarks

NARCIS (Netherlands)

Vervaele, J.A.E.

2018-01-01

These introductory remarks deal with the reasons why the EPPO is perceived by some as a controversial body. These reasons are mirrored with the problem identification and the causes thereof. The size of EU fraud and related corruption and money laundering, both at the income and expenditure side, is

Remarkable resilience of teeth.

Science.gov (United States)

Chai, Herzl; Lee, James J-W; Constantino, Paul J; Lucas, Peter W; Lawn, Brian R

2009-05-05

Tooth enamel is inherently weak, with fracture toughness comparable with glass, yet it is remarkably resilient, surviving millions of functional contacts over a lifetime. We propose a microstructural mechanism of damage resistance, based on observations from ex situ loading of human and sea otter molars (teeth with strikingly similar structural features). Section views of the enamel implicate tufts, hypomineralized crack-like defects at the enamel-dentin junction, as primary fracture sources. We report a stabilization in the evolution of these defects, by "stress shielding" from neighbors, by inhibition of ensuing crack extension from prism interweaving (decussation), and by self-healing. These factors, coupled with the capacity of the tooth configuration to limit the generation of tensile stresses in largely compressive biting, explain how teeth may absorb considerable damage over time without catastrophic failure, an outcome with strong implications concerning the adaptation of animal species to diet.

Group learning versus local learning: Which is prefer for public cooperation?

Science.gov (United States)

Yang, Shi-Han; Song, Qi-Qing

2018-01-01

We study the evolution of cooperation in public goods games on various graphs, focusing on the effects that are brought by different kinds of strategy donors. This highlights a basic feature of a public good game, for which there exists a remarkable difference between the interactive players and the players who are imitated. A player can learn from all the groups where the player is a member or from the typically local nearest neighbors, and the results show that the group learning rules have better performance in promoting cooperation on many networks than the local learning rules. The heterogeneity of networks' degree may be an effective mechanism for harvesting the cooperation expectation in many cases, however, we find that heterogeneity does not definitely mean the high frequency of cooperators in a population under group learning rules. It was shown that cooperators always hardly evolve whenever the interaction and the replacement do not coincide for evolutionary pairwise dilemmas on graphs, while for PG games we find that breaking the symmetry is conducive to the survival of cooperators.

Remarkable recoveries: research and practice from a patient's perspective.

Science.gov (United States)

Barasch, Marc Ian

2008-08-01

Mind-body therapies are often portrayed in the literature as self-palliative, adjunctive, and complementary, but rarely as contributive to cure. Many physicians continue to view them as acceptable indulgences so long as they are harmless and the patient remains fully compliant with a standard treatment regimen. The possibility that such modalities might help drive the healing process itself is infrequently acknowledged. This article addresses the topic of such therapies, examining remarkable recoveries in cancer, and suggesting the need for a "Remarkable Recovery Registry" to expand the literature on these cases. The author discusses the importance of complementary alternative medicine, and emotional and pyschologic support in the treatment regimen, and the need for health care providers and patients to work together to provide the best emotional environment for the healing process.

Motor cortex is required for learning but not executing a motor skill

Science.gov (United States)

Kawai, Risa; Markman, Timothy; Poddar, Rajesh; Ko, Raymond; Fantana, Antoniu; Dhawale, Ashesh; Kampff, Adam R.; Ölveczky, Bence P.

2018-01-01

Motor cortex is widely believed to underlie the acquisition and execution of motor skills, yet its contributions to these processes are not fully understood. One reason is that studies on motor skills often conflate motor cortex’s established role in dexterous control with roles in learning and producing task-specific motor sequences. To dissociate these aspects, we developed a motor task for rats that trains spatiotemporally precise movement patterns without requirements for dexterity. Remarkably, motor cortex lesions had no discernible effect on the acquired skills, which were expressed in their distinct pre-lesion forms on the very first day of post-lesion training. Motor cortex lesions prior to training, however, rendered rats unable to acquire the stereotyped motor sequences required for the task. These results suggest a remarkable capacity of subcortical motor circuits to execute learned skills and a previously unappreciated role for motor cortex in ‘tutoring’ these circuits during learning. PMID:25892304

Direct oxide reducing method

International Nuclear Information System (INIS)

Tokiwai, Moriyasu.

1995-01-01

Calcium oxides and magnetic oxides as wastes generated upon direct reduction are subjected to molten salt electrolysis, and reduced metallic calcium and magnesium are separated and recovered. Then calcium and magnesium are used recyclically as the reducing agent upon conducting direct oxide reduction. Even calcium oxides and magnesium oxides, which have high melting points and difficult to be melted usually, can be melted in molten salts of mixed fluorides or chlorides by molten-salt electrolysis. Oxides are decomposed by electrolysis, and oxygen is removed in the form of carbon monoxide, while the reduced metallic calcium and magnesium rise above the molten salts on the side of a cathode, and then separated. Since only carbon monoxide is generated as radioactive wastes upon molten salt electrolysis, the amount of radioactive wastes can be greatly reduced, and the amount of the reducing agent used can also be decreased remarkably. (N.H.)

A Remarkable Recent Transition in the Solar Dynamo

NARCIS (Netherlands)

de Jager, C.; Akasofu, S.-I.; Duhau, S.; Livingston, W.C.; Nieuwenhuijzen, H.; Potgieter, M.S.

2016-01-01

We summarize the major aspects of the remarkable, fairly long lasting period(∼ 2005 to ∼ 2010) of low solar activity, that we will call the Transition. It is the transitionalstage between the Grand Maximum of the 20th century and a forthcoming (most probablyRegular) episode of solar activity. The

The effects of reduced dopamine transporter function and chronic lithium on motivation, probabilistic learning, and neurochemistry in mice: Modeling bipolar mania.

Science.gov (United States)

Milienne-Petiot, Morgane; Kesby, James P; Graves, Mary; van Enkhuizen, Jordy; Semenova, Svetlana; Minassian, Arpi; Markou, Athina; Geyer, Mark A; Young, Jared W

2017-02-01

Bipolar disorder (BD) mania patients exhibit poor cognition and reward-seeking/hypermotivation, negatively impacting a patient's quality of life. Current treatments (e.g., lithium), do not treat such deficits. Treatment development has been limited due to a poor understanding of the neural mechanisms underlying these behaviors. Here, we investigated putative mechanisms underlying cognition and reward-seeking/motivational changes relevant to BD mania patients using two validated mouse models and neurochemical analyses. The effects of reducing dopamine transporter (DAT) functioning via genetic (knockdown vs. wild-type littermates), or pharmacological (GBR12909- vs. vehicle-treated C57BL/6J mice) means were assessed in the probabilistic reversal learning task (PRLT), and progressive ratio breakpoint (PRB) test, during either water or chronic lithium treatment. These tasks quantify reward learning and effortful motivation, respectively. Neurochemistry was performed on brain samples of DAT mutants ± chronic lithium using high performance liquid chromatography. Reduced DAT functioning increased reversals in the PRLT, an effect partially attenuated by chronic lithium. Chronic lithium alone slowed PRLT acquisition. Reduced DAT functioning increased motivation (PRB), an effect attenuated by lithium in GBR12909-treated mice. Neurochemical analyses revealed that DAT knockdown mice exhibited elevated homovanillic acid levels, but that lithium had no effect on these elevated levels. Reducing DAT functioning recreates many aspects of BD mania including hypermotivation and improved reversal learning (switching), as well as elevated homovanillic acid levels. Chronic lithium only exerted main effects, impairing learning and elevating norepinephrine and serotonin levels of mice, not specifically treating the underlying mechanisms identified in these models. Copyright © 2016 Elsevier Ltd. All rights reserved.

Cultural Challenges in Developing E-Learning Content

Directory of Open Access Journals (Sweden)

Marianne Amir Azer

2011-03-01

Full Text Available Education is an important component of any nation’s development process. Society has been credited with creating technology, but technology is simultaneously creating society. One of the key benefits of such technology creation includes learning and curriculum development, which is otherwise referred to as e-leaning, and more appropriately referred to as global e-learning. Global e-learning raises some implications, which include communication, culture, and technology, that must be addressed before successful implementation and outcome can occur. In this paper, we discuss cultural related issues such as culture influence on e-learning and the dimensions of cultural variability. In addition, we present the main challenges to provide e-learning opportunities. Finally, a case study for facing the cultural challenges is presented; this will be followed by concluding remarks at the end of this paper.

Extreme learning machine for reduced order modeling of turbulent geophysical flows

Science.gov (United States)

San, Omer; Maulik, Romit

2018-04-01

We investigate the application of artificial neural networks to stabilize proper orthogonal decomposition-based reduced order models for quasistationary geophysical turbulent flows. An extreme learning machine concept is introduced for computing an eddy-viscosity closure dynamically to incorporate the effects of the truncated modes. We consider a four-gyre wind-driven ocean circulation problem as our prototype setting to assess the performance of the proposed data-driven approach. Our framework provides a significant reduction in computational time and effectively retains the dynamics of the full-order model during the forward simulation period beyond the training data set. Furthermore, we show that the method is robust for larger choices of time steps and can be used as an efficient and reliable tool for long time integration of general circulation models.

Learning reduced kinetic Monte Carlo models of complex chemistry from molecular dynamics.

Science.gov (United States)

Yang, Qian; Sing-Long, Carlos A; Reed, Evan J

2017-08-01

We propose a novel statistical learning framework for automatically and efficiently building reduced kinetic Monte Carlo (KMC) models of large-scale elementary reaction networks from data generated by a single or few molecular dynamics simulations (MD). Existing approaches for identifying species and reactions from molecular dynamics typically use bond length and duration criteria, where bond duration is a fixed parameter motivated by an understanding of bond vibrational frequencies. In contrast, we show that for highly reactive systems, bond duration should be a model parameter that is chosen to maximize the predictive power of the resulting statistical model. We demonstrate our method on a high temperature, high pressure system of reacting liquid methane, and show that the learned KMC model is able to extrapolate more than an order of magnitude in time for key molecules. Additionally, our KMC model of elementary reactions enables us to isolate the most important set of reactions governing the behavior of key molecules found in the MD simulation. We develop a new data-driven algorithm to reduce the chemical reaction network which can be solved either as an integer program or efficiently using L1 regularization, and compare our results with simple count-based reduction. For our liquid methane system, we discover that rare reactions do not play a significant role in the system, and find that less than 7% of the approximately 2000 reactions observed from molecular dynamics are necessary to reproduce the molecular concentration over time of methane. The framework described in this work paves the way towards a genomic approach to studying complex chemical systems, where expensive MD simulation data can be reused to contribute to an increasingly large and accurate genome of elementary reactions and rates.

Exploiting ICT and E-Learning in Teacher's Professional Development in Algeria: The Case of English Secondary School Teachers

Science.gov (United States)

Guemide, Boutkhil; Benachaiba, Chellali

2012-01-01

The real potential of ICT is the way it changes learners to become autonomous in their learning process. E-learning also plays a crucial role in today's life and in modern education. Its importance lies in the fact that people are finding that e-learning can make a remarkable change in teaching/ or learning: to how quickly they master a skill; how…

Meeting the challenge of continuing education with eLearning.

Science.gov (United States)

Levesque, David R; Kelly, Gina

2002-01-01

remarkable. eLearning facilitates learning at anytime and anywhere. It reduces the obstacles of time and distance, providing greater equality of opportunity.

Steering the dynamics within reduced space through quantum learning control

International Nuclear Information System (INIS)

Kim, Young Sik

2003-01-01

In quantum dynamics of many-body systems, to identify the Hamiltonian becomes more difficult very rapidly as the number of degrees of freedom increases. In order to simplify the dynamics and to deduce dynamically relevant Hamiltonian information, it is desirable to control the dynamics to lie within a reduced space. With a judicious choice for the cost functional, the closed loop optimal control experiments can be manipulated efficiently to steer the dynamics to lie within a subspace of the system eigenstates without requiring any prior detailed knowledge about the system Hamiltonian. The procedure is simulated for optimally controlled population transfer experiments in the system of two degrees of freedom. To show the feasibility of steering the dynamics to lie in a specified subspace, the learning algorithms guiding the dynamics are presented along with frequency filtering. The results demonstrate that the optimal control fields derive the system to the desired target state through the desired subspace

Sucrose Responsiveness, Learning Success, and Task Specialization in Ants

Science.gov (United States)

Perez, Margot; Rolland, Uther; Giurfa,, Martin; d'Ettorre, Patrizia

2013-01-01

Social insects possess remarkable learning capabilities, which are crucial for their ecological success. They also exhibit interindividual differences in responsiveness to environmental stimuli, which underlie task specialization and division of labor. Here we investigated for the first time the relationships between sucrose responsiveness,…

Reducing test anxiety and improving academic self-esteem in high school and college students with learning disabilities.

Science.gov (United States)

Wachelka, D; Katz, R C

1999-09-01

Test anxiety seems like a benign problem to some people, but it can be potentially serious when it leads to high levels of distress and academic failure in otherwise capable students. Because test anxiety is common in older students with learning disabilities (LD), it is surprising that little research has been done on ways to reduce the distress these students experience in test situations. In this study, we used a randomized pretest-posttest control group design to examine the effectiveness of a cognitive-behavioral treatment for reducing test anxiety and improving academic self-esteem in a cohort (N = 27) of high school and college students with learning disabilities (LD). All of the students participated voluntarily. They were enrolled in classes for students with learning problems. Before the study began, they complained of test anxiety and showed an elevated score on the Test Anxiety Inventory (TAI). Eleven students (85%) completed the 8-week long treatment, which consisted of progressive muscle relaxation, guided imagery, self-instruction training, as well as training in study and test-taking skills. Results showed significant improvement in the treated group which was not evident in an untreated control group (N = 16). Compared to the control group, the treated group showed significant reductions in test anxiety on the TAI, as well as improvement in study skills and academic self-esteem as measured by the Survey of Study Habits and Attitudes, and the school scale of the Coopersmith Self-Esteem Inventory. These results extend the generality of similar studies on reducing test anxiety and improving academic self-esteem in younger students. They also suggest that relief from test anxiety can be expected fairly quickly when cognitive-behavioral methods are used. Additional implications and methodological limitations of the study are discussed.

Using Self-Regulated Learning Strategies in Enhancing Language Proficiency with a Focus on Reading Comprehension

Science.gov (United States)

Abbasian, Gholam-Reza; Hartoonian, Anahid

2014-01-01

Self-regulated learning strategies have recently received a remarkable attention by researchers. The aim of this study was to explore the relationship between self-regulated learning strategies and students' language proficiency as well as their reading comprehension. To do so, 115 Iranian EFL university students were selected. First, a TOEFL test…

Motor cortex is required for learning but not for executing a motor skill.

Science.gov (United States)

Kawai, Risa; Markman, Timothy; Poddar, Rajesh; Ko, Raymond; Fantana, Antoniu L; Dhawale, Ashesh K; Kampff, Adam R; Ölveczky, Bence P

2015-05-06

Motor cortex is widely believed to underlie the acquisition and execution of motor skills, but its contributions to these processes are not fully understood. One reason is that studies on motor skills often conflate motor cortex's established role in dexterous control with roles in learning and producing task-specific motor sequences. To dissociate these aspects, we developed a motor task for rats that trains spatiotemporally precise movement patterns without requirements for dexterity. Remarkably, motor cortex lesions had no discernible effect on the acquired skills, which were expressed in their distinct pre-lesion forms on the very first day of post-lesion training. Motor cortex lesions prior to training, however, rendered rats unable to acquire the stereotyped motor sequences required for the task. These results suggest a remarkable capacity of subcortical motor circuits to execute learned skills and a previously unappreciated role for motor cortex in "tutoring" these circuits during learning. Copyright © 2015 Elsevier Inc. All rights reserved.

Reducing Test Anxiety while Increasing Learning: The Cheat Sheet

Science.gov (United States)

Erbe, Brigitte

2007-01-01

Student learning is greatly enhanced by studying prior to an exam. Allowing students to prepare a cheat sheet for the exam helps structure this study time and deepens learning. The crib sheet is well defined: one double-sided page of notes. An award for the best and most creative cheat sheet allows the instructor to appreciate the students'…

Some Remarks on Stability of Generalized Equations

Czech Academy of Sciences Publication Activity Database

Outrata, Jiří; Henrion, R.; Kruger, A.Y.

2013-01-01

Roč. 159, č. 3 (2013), s. 681-697 ISSN 0022-3239 R&D Projects: GA AV ČR IAA100750802; GA ČR(CZ) GAP201/12/0671 Institutional support: RVO:67985556 Keywords : Parameterized generalized equation * Regular and limiting coderivative * Constant rank CQ * Mathematical program with equilibrium constraints Subject RIV: BA - General Mathematics Impact factor: 1.406, year: 2013 http://library.utia.cas.cz/separaty/2013/MTR/outrata-some remarks on stability of generalized equations.pdf

Reducing errors benefits the field-based learning of a fundamental movement skill in children.

Science.gov (United States)

Capio, C M; Poolton, J M; Sit, C H P; Holmstrom, M; Masters, R S W

2013-03-01

Proficient fundamental movement skills (FMS) are believed to form the basis of more complex movement patterns in sports. This study examined the development of the FMS of overhand throwing in children through either an error-reduced (ER) or error-strewn (ES) training program. Students (n = 216), aged 8-12 years (M = 9.16, SD = 0.96), practiced overhand throwing in either a program that reduced errors during practice (ER) or one that was ES. ER program reduced errors by incrementally raising the task difficulty, while the ES program had an incremental lowering of task difficulty. Process-oriented assessment of throwing movement form (Test of Gross Motor Development-2) and product-oriented assessment of throwing accuracy (absolute error) were performed. Changes in performance were examined among children in the upper and lower quartiles of the pretest throwing accuracy scores. ER training participants showed greater gains in movement form and accuracy, and performed throwing more effectively with a concurrent secondary cognitive task. Movement form improved among girls, while throwing accuracy improved among children with low ability. Reduced performance errors in FMS training resulted in greater learning than a program that did not restrict errors. Reduced cognitive processing costs (effective dual-task performance) associated with such approach suggest its potential benefits for children with developmental conditions. © 2011 John Wiley & Sons A/S.

Collisionless shocks and upstream waves and particles: Introductory remarks

International Nuclear Information System (INIS)

Kennel, C.F.

1981-01-01

We discuss more aspects of collisionless shock theory that might be pertinent to the problem of upstream waves and particles. It is hoped that our qualititive remarks may be a useful guide for the general reader as he goes through the detailed papers to come

Some remarks on electron scattering in a laser field

International Nuclear Information System (INIS)

Ehlotzky, F.

1988-01-01

Potential scattering of electrons in a quantized radiation field is reconsidered. Some remarks are made on the validity of the Kroll-Watson scattering formula and on the close connection of this formula with the classical transition rate of scattering in a radiation field. (17 refs.)

Some concluding remarks about cold moderator development

International Nuclear Information System (INIS)

Carpenter, J.M.

1990-01-01

This paper is the transcription of remarks made at the conclusion of the Workshop on Cold Neutron Sources held at the Los Angeles National Laboratory, Los Alamos, New Mexico, March 5--7, 1990. Areas of interest include the following: scattering functions; cold moderator materials; radiation mixing of chemical composition; comparison of some pulsed moderator spectra; hydrogen mixtures; premoderators and shields; composite reflectors; exotic moderator materials; deuterated methanes; mixed moderator materials; and test facility availabilities. 2 refs., 4 figs., 1 tab

Students’ Preferred Characteristics of Learning Environments in Vocational Secondary Education

Directory of Open Access Journals (Sweden)

Ingeborg Placklé

2014-12-01

Full Text Available If teachers and teacher educators are willing to support the learning of students, it is important for them to learn what motivates students to engage in learning. Students have their own preferences on design characteristics of powerful learning environments in vocational education. We developed an instrument - the Inventory Powerful Learning Environments in Vocational Education - to measure students’ preferences on characteristics of powerful learning environments in vocational education. We investigated whether student preferences on the design of their learning environments are in line with what is described in the literature as beneficial for learning. Data of 544 students show that the preferences of students support most characteristics of PLEs in vocational education. Looking through the eyes of students, teachers have to challenge their students and encourage them to take their learning in their own hands. Adaptive learning support is needed. Remarkable, students do not prefer having reflective dialogues with teachers or peers.

Hospital transformation and organisational learning.

Science.gov (United States)

Ho, W

1999-12-01

Kwong Wah Hospital was founded by the charity organisation Tung Wah Group of Hospitals some 88 years ago, with management transfer to the Hong Kong Hospital Authority in 1991. Capitalizing both from the traditional caring culture of its founder, as well as opportunities in the new management environment, the hospital has scored remarkable successes in service quality, community partnership, organisational effectiveness, and staff development. Underpinning these transformations were Structure, Process, People, and Culture strategies. The learning imperative is heavily mandated or the success of each of these strands of development. Indeed, the embodiment of a learning organisation culture provides the impetus in sustaining the change momentum, towards achieving the Vision of becoming a 'Most Preferred Hospital' in Hong Kong.

Some remarks on a scenario of supersymmetry in quantum mechanics

International Nuclear Information System (INIS)

Jannussis, A.; Tsohantzis, I; Vavougios, D.

1990-01-01

Some remarks are given on a recent paper of Lahiri, Kumar Roy and Bagchi who have constructed a scenario of supersymmetry in quantum mechanics by imposing a structure on the raising and lowering operators

Bidirectional extreme learning machine for regression problem and its learning effectiveness.

Science.gov (United States)

Yang, Yimin; Wang, Yaonan; Yuan, Xiaofang

2012-09-01

It is clear that the learning effectiveness and learning speed of neural networks are in general far slower than required, which has been a major bottleneck for many applications. Recently, a simple and efficient learning method, referred to as extreme learning machine (ELM), was proposed by Huang , which has shown that, compared to some conventional methods, the training time of neural networks can be reduced by a thousand times. However, one of the open problems in ELM research is whether the number of hidden nodes can be further reduced without affecting learning effectiveness. This brief proposes a new learning algorithm, called bidirectional extreme learning machine (B-ELM), in which some hidden nodes are not randomly selected. In theory, this algorithm tends to reduce network output error to 0 at an extremely early learning stage. Furthermore, we find a relationship between the network output error and the network output weights in the proposed B-ELM. Simulation results demonstrate that the proposed method can be tens to hundreds of times faster than other incremental ELM algorithms.

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

Science.gov (United States)

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

2007-01-01

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

Motion Learning Based on Bayesian Program Learning

Directory of Open Access Journals (Sweden)

Cheng Meng-Zhen

2017-01-01

Full Text Available The concept of virtual human has been highly anticipated since the 1980s. By using computer technology, Human motion simulation could generate authentic visual effect, which could cheat human eyes visually. Bayesian Program Learning train one or few motion data, generate new motion data by decomposing and combining. And the generated motion will be more realistic and natural than the traditional one.In this paper, Motion learning based on Bayesian program learning allows us to quickly generate new motion data, reduce workload, improve work efficiency, reduce the cost of motion capture, and improve the reusability of data.

Brief, pre-learning stress reduces false memory production and enhances true memory selectively in females.

Science.gov (United States)

Zoladz, Phillip R; Peters, David M; Kalchik, Andrea E; Hoffman, Mackenzie M; Aufdenkampe, Rachael L; Woelke, Sarah A; Wolters, Nicholas E; Talbot, Jeffery N

2014-04-10

Some of the previous research on stress-memory interactions has suggested that stress increases the production of false memories. However, as accumulating work has shown that the effects of stress on learning and memory depend critically on the timing of the stressor, we hypothesized that brief stress administered immediately before learning would reduce, rather than increase, false memory production. In the present study, participants submerged their dominant hand in a bath of ice cold water (stress) or sat quietly (no stress) for 3 min. Then, participants completed a short-term memory task, the Deese-Roediger-McDermott paradigm, in which they were presented with 10 different lists of semantically related words (e.g., candy, sour, sugar) and, after each list, were tested for their memory of presented words (e.g., candy), non-presented unrelated "distractor" words (e.g., hat), and non-presented semantically related "critical lure" words (e.g., sweet). Stress, overall, significantly reduced the number of critical lures recalled (i.e., false memory) by participants. In addition, stress enhanced memory for the presented words (i.e., true memory) in female, but not male, participants. These findings reveal that stress does not unequivocally enhance false memory production and that the timing of the stressor is an important variable that could mediate such effects. Such results could have important implications for understanding the dependability of eyewitness accounts of events that are observed following stress. Copyright © 2014 Elsevier Inc. All rights reserved.

Muscle cocontraction following dynamics learning.

Science.gov (United States)

Darainy, Mohammad; Ostry, David J

2008-09-01

Coactivation of antagonist muscles is readily observed early in motor learning, in interactions with unstable mechanical environments and in motor system pathologies. Here we present evidence that the nervous system uses coactivation control far more extensively and that patterns of cocontraction during movement are closely tied to the specific requirements of the task. We have examined the changes in cocontraction that follow dynamics learning in tasks that are thought to involve finely sculpted feedforward adjustments to motor commands. We find that, even following substantial training, cocontraction varies in a systematic way that depends on both movement direction and the strength of the external load. The proportion of total activity that is due to cocontraction nevertheless remains remarkably constant. Moreover, long after indices of motor learning and electromyographic measures have reached asymptotic levels, cocontraction still accounts for a significant proportion of total muscle activity in all phases of movement and in all load conditions. These results show that even following dynamics learning in predictable and stable environments, cocontraction forms a central part of the means by which the nervous system regulates movement.

Remarks on the low value obtained for the Hubble constant

International Nuclear Information System (INIS)

Jaakkola, Toivo

1975-01-01

Some remarks are made on the basis of the data given by Sandage and Tamman, suggesting that these authors have over-estimated the distances to the most luminous galaxies and obtained a value too low for the Hubble constant [fr

Personalized summarization using user preference for m-learning

Science.gov (United States)

Lee, Sihyoung; Yang, Seungji; Ro, Yong Man; Kim, Hyoung Joong

2008-02-01

As the Internet and multimedia technology is becoming advanced, the number of digital multimedia contents is also becoming abundant in learning area. In order to facilitate the access of digital knowledge and to meet the need of a lifelong learning, e-learning could be the helpful alternative way to the conventional learning paradigms. E-learning is known as a unifying term to express online, web-based and technology-delivered learning. Mobile-learning (m-learning) is defined as e-learning through mobile devices using wireless transmission. In a survey, more than half of the people remarked that the re-consumption was one of the convenient features in e-learning. However, it is not easy to find user's preferred segmentation from a full version of lengthy e-learning content. Especially in m-learning, a content-summarization method is strongly required because mobile devices are limited to low processing power and battery capacity. In this paper, we propose a new user preference model for re-consumption to construct personalized summarization for re-consumption. The user preference for re-consumption is modeled based on user actions with statistical model. Based on the user preference model for re-consumption with personalized user actions, our method discriminates preferred parts over the entire content. Experimental results demonstrated successful personalized summarization.

Learning in Life History - psycho-societal interpretation of biographies

DEFF Research Database (Denmark)

Olesen, Henning Salling

2008-01-01

Taking its point of departure from some critical remarks about some of the most important recent theorizing of learning, this article presents an alternative framework for theorizing learning as a subjective process in a social and societal context, based on life history research. The key concepts...... of subjectivity and experience, derived from European critical theory, are briefly introduced with respect to their intellectual background. Based on examples from the author’s research into the professional learning, the article outlines the implications of these concepts in relation to an understanding...... of emotional aspects of learning in everyday life and to an understanding of knowledge. The pivotal role of language use and language socialisation is explained in brief, and a psychodynamic complement to a language game concept of language use is developed....

Hierarchical Traces for Reduced NSM Memory Requirements

Science.gov (United States)

Dahl, Torbjørn S.

This paper presents work on using hierarchical long term memory to reduce the memory requirements of nearest sequence memory (NSM) learning, a previously published, instance-based reinforcement learning algorithm. A hierarchical memory representation reduces the memory requirements by allowing traces to share common sub-sequences. We present moderated mechanisms for estimating discounted future rewards and for dealing with hidden state using hierarchical memory. We also present an experimental analysis of how the sub-sequence length affects the memory compression achieved and show that the reduced memory requirements do not effect the speed of learning. Finally, we analyse and discuss the persistence of the sub-sequences independent of specific trace instances.

Can Social-Emotional Learning Reduce School Dropout in Developing Countries?

Science.gov (United States)

Wang, Huan; Chu, James; Loyalka, Prashant; Xin, Tao; Shi, Yaojiang; Qu, Qinghe; Yang, Chu

2016-01-01

An alarming number of students drop out of junior high school in developing countries. In this study, we examine the impacts of providing a social-emotional learning (SEL) program on the dropout behavior and learning anxiety of students in the first two years of junior high. We do so by analyzing data from a randomized controlled trial involving…

Some remarks on word formation in Danish

DEFF Research Database (Denmark)

Götzsche, Hans

Abstract for the 25th Scandinavian Conference of Linguistics Some remarks on wordformation in Danish Some Danish word formation phenomena pose a problem for the linguist, being a predicament for analysis. In Danish a train leaves the station when it afgår ‘leaves’, while a minister may gå af......, there are some patterns for these Danish compounds concerning their internal semantics, in that the same lexical items may be used for different purposes depending on whether they are formed as a straightforward linear sequence (a word formation) or a reversed sequence (a phrase). The problem is (i) how the two...

A strategy for quantum algorithm design assisted by machine learning

International Nuclear Information System (INIS)

Bang, Jeongho; Lee, Jinhyoung; Ryu, Junghee; Yoo, Seokwon; Pawłowski, Marcin

2014-01-01

We propose a method for quantum algorithm design assisted by machine learning. The method uses a quantum–classical hybrid simulator, where a ‘quantum student’ is being taught by a ‘classical teacher’. In other words, in our method, the learning system is supposed to evolve into a quantum algorithm for a given problem, assisted by a classical main-feedback system. Our method is applicable for designing quantum oracle-based algorithms. We chose, as a case study, an oracle decision problem, called a Deutsch–Jozsa problem. We showed by using Monte Carlo simulations that our simulator can faithfully learn a quantum algorithm for solving the problem for a given oracle. Remarkably, the learning time is proportional to the square root of the total number of parameters, rather than showing the exponential dependence found in the classical machine learning-based method. (paper)

A strategy for quantum algorithm design assisted by machine learning

Science.gov (United States)

Bang, Jeongho; Ryu, Junghee; Yoo, Seokwon; Pawłowski, Marcin; Lee, Jinhyoung

2014-07-01

We propose a method for quantum algorithm design assisted by machine learning. The method uses a quantum-classical hybrid simulator, where a ‘quantum student’ is being taught by a ‘classical teacher’. In other words, in our method, the learning system is supposed to evolve into a quantum algorithm for a given problem, assisted by a classical main-feedback system. Our method is applicable for designing quantum oracle-based algorithms. We chose, as a case study, an oracle decision problem, called a Deutsch-Jozsa problem. We showed by using Monte Carlo simulations that our simulator can faithfully learn a quantum algorithm for solving the problem for a given oracle. Remarkably, the learning time is proportional to the square root of the total number of parameters, rather than showing the exponential dependence found in the classical machine learning-based method.

Adult neurogenesis is reduced in the dorsal hippocampus of rats displaying learned helplessness behavior.

Science.gov (United States)

Ho, Y C; Wang, S

2010-11-24

Clinical and preclinical studies suggest that the hippocampus has a role in the pathophysiology of major depression. In the learned helplessness (LH) animal model of depression after inescapable shocks (ISs) animals that display LH behavior have reduced cell proliferation in the hippocampus; this effect can be reversed by antidepressant treatment. Using this model, we compared rats that displayed LH behavior and rats that did not show LH behavior (NoLH) after ISs to determine whether reduced hippocampal cell proliferation is associated with the manifestation of LH behavior or is a general response to stress. Specifically, we examined cell proliferation, neurogenesis, and synaptic function in dorsal and ventral hippocampus of LH and NoLH animals and control rats that were not shocked. The LH rats had showed reduced cell proliferation, neurogenesis, and synaptic transmission in the dorsal hippocampus, whereas no changes were seen in the ventral hippocampus. These changes were not observed in the NoLH animals. In a group of NoLH rats that received the same amount of electrical shock as the LH rats to control for the unequal shocks received in these two groups, we observed changes in Ki-67(+) cells associated with acute stress. We conclude that reduced hippocampal cell proliferation and neurogenesis are associated with the manifestation of LH behavior and that the dorsal hippocampus is the most affected area. Copyright © 2010 IBRO. Published by Elsevier Ltd. All rights reserved.

Memristive learning and memory functions in polyvinyl alcohol polymer memristors

Directory of Open Access Journals (Sweden)

Yan Lei

2014-07-01

Full Text Available Polymer based memristive devices can offer simplicity in fabrication and at the same time promise functionalities for artificial neural applications. In this work, inherent learning and memory functions have been achieved in polymer memristive devices employing Polyvinyl Alcohol. The change in conduction in such polymer devices strongly depends on the pulse amplitude, duration and time interval. Through repetitive stimuli training, temporary short-term memory can transfer into consolidated long-term memory. These behaviors bear remarkable similarities to certain learning and memory functions of biological systems.

Impact of Interactive Engagement on Reducing the Gender Gap in Quantum Physics Learning Outcomes among Senior Secondary School Students

Science.gov (United States)

Adegoke, Benson Adesina

2012-01-01

In this study, the author examines the extent to which an interactive engagement approach can reduce the gender gap in senior secondary school (SSS) (age 16-18 years) students' learning outcomes in quantum physics. One hundred and twenty one (male = 65; female = 56) SSS 3 students participated in this study. They were randomly selected from two…

Reducing Peripheral Inflammation with Infliximab Reduces Neuroinflammation and Improves Cognition in Rats with Hepatic Encephalopathy

Science.gov (United States)

Dadsetan, Sherry; Balzano, Tiziano; Forteza, Jerónimo; Cabrera-Pastor, Andrea; Taoro-Gonzalez, Lucas; Hernandez-Rabaza, Vicente; Gil-Perotín, Sara; Cubas-Núñez, Laura; García-Verdugo, José-Manuel; Agusti, Ana; Llansola, Marta; Felipo, Vicente

2016-01-01

Inflammation contributes to cognitive impairment in patients with hepatic encephalopathy (HE). However, the process by which peripheral inflammation results in cognitive impairment remains unclear. In animal models, neuroinflammation and altered neurotransmission mediate cognitive impairment. Taking into account these data, we hypothesized that in rats with HE: (1) peripheral inflammation is a main contributor to neuroinflammation; (2) neuroinflammation in hippocampus impairs spatial learning by altering AMPA and/or NMDA receptors membrane expression; (3) reducing peripheral inflammation with infliximab (anti-TNF-a) would improve spatial learning; (4) this would be associated with reduced neuroinflammation and normalization of the membrane expression of glutamate receptors. The aims of this work were to assess these hypotheses. We analyzed in rats with portacaval shunt (PCS) and control rats, treated or not with infliximab: (a) peripheral inflammation by measuring prostaglandin E2, IL10, IL-17, and IL-6; (b) neuroinflammation in hippocampus by analyzing microglial activation and the content of TNF-a and IL-1b; (c) AMPA and NMDA receptors membrane expression in hippocampus; and (d) spatial learning in the Radial and Morris water mazes. We assessed the effects of treatment with infliximab on peripheral inflammation, on neuroinflammation and AMPA and NMDA receptors membrane expression in hippocampus and on spatial learning and memory. PCS rats show increased serum prostaglandin E2, IL-17, and IL-6 and reduced IL-10 levels, indicating increased peripheral inflammation. PCS rats also show microglial activation and increased nuclear NF-kB and expression of TNF-a and IL-1b in hippocampus. This was associated with altered AMPA and NMDA receptors membrane expression in hippocampus and impaired spatial learning and memory in the radial and Morris water maze. Treatment with infliximab reduces peripheral inflammation in PCS rats, normalizing prostaglandin E2, IL-17, IL-6, and

Terahertz radiation generation by lasers with remarkable efficiency in electron–positron plasma

International Nuclear Information System (INIS)

Malik, Hitendra K.

2015-01-01

Photo-mixing of spatial-super-Gaussian lasers and electron–positron plasma are proposed for realizing a large amplitude nonlinear current in order to generate an efficient terahertz radiation. An external magnetic field together with a proper index of the lasers helps achieving controllable current and hence, the focused radiation of tunable frequency and power along with a remarkable efficiency of the scheme as ∼6%. - Highlights: • First proposal of photo-mixing of spatial-super-Gaussian (SSG) lasers in electron–positron (e–p) plasma. • Large amplitude nonlinear current due to the contribution of both the plasma species. • Magnetic field as an additional parameter for tunable THz radiation with a remarkable efficiency of ∼6%.

Remarks on Hamiltonian structures in G2-geometry

International Nuclear Information System (INIS)

Cho, Hyunjoo; Salur, Sema; Todd, A. J.

2013-01-01

In this article, we treat G 2 -geometry as a special case of multisymplectic geometry and make a number of remarks regarding Hamiltonian multivector fields and Hamiltonian differential forms on manifolds with an integrable G 2 -structure; in particular, we discuss existence and make a number of identifications of the spaces of Hamiltonian structures associated to the two multisymplectic structures associated to an integrable G 2 -structure. Along the way, we prove some results in multisymplectic geometry that are generalizations of results from symplectic geometry

Instructional Utility and Learning Efficacy of Common Active Learning Strategies

Science.gov (United States)

McConell, David A.; Chapman, LeeAnna; Czaijka, C. Douglas; Jones, Jason P.; Ryker, Katherine D.; Wiggen, Jennifer

2017-01-01

The adoption of active learning instructional practices in college science, technology, engineering, and mathematics (STEM) courses has been shown to result in improvements in student learning, contribute to increased retention rates, and reduce the achievement gap among different student populations. Descriptions of active learning strategies…

Scalable, incremental learning with MapReduce parallelization for cell detection in high-resolution 3D microscopy data

KAUST Repository

Sung, Chul

2013-08-01

Accurate estimation of neuronal count and distribution is central to the understanding of the organization and layout of cortical maps in the brain, and changes in the cell population induced by brain disorders. High-throughput 3D microscopy techniques such as Knife-Edge Scanning Microscopy (KESM) are enabling whole-brain survey of neuronal distributions. Data from such techniques pose serious challenges to quantitative analysis due to the massive, growing, and sparsely labeled nature of the data. In this paper, we present a scalable, incremental learning algorithm for cell body detection that can address these issues. Our algorithm is computationally efficient (linear mapping, non-iterative) and does not require retraining (unlike gradient-based approaches) or retention of old raw data (unlike instance-based learning). We tested our algorithm on our rat brain Nissl data set, showing superior performance compared to an artificial neural network-based benchmark, and also demonstrated robust performance in a scenario where the data set is rapidly growing in size. Our algorithm is also highly parallelizable due to its incremental nature, and we demonstrated this empirically using a MapReduce-based implementation of the algorithm. We expect our scalable, incremental learning approach to be widely applicable to medical imaging domains where there is a constant flux of new data. © 2013 IEEE.

Perceptual learning and human expertise.

Science.gov (United States)

Kellman, Philip J; Garrigan, Patrick

2009-06-01

We consider perceptual learning: experience-induced changes in the way perceivers extract information. Often neglected in scientific accounts of learning and in instruction, perceptual learning is a fundamental contributor to human expertise and is crucial in domains where humans show remarkable levels of attainment, such as language, chess, music, and mathematics. In Section 2, we give a brief history and discuss the relation of perceptual learning to other forms of learning. We consider in Section 3 several specific phenomena, illustrating the scope and characteristics of perceptual learning, including both discovery and fluency effects. We describe abstract perceptual learning, in which structural relationships are discovered and recognized in novel instances that do not share constituent elements or basic features. In Section 4, we consider primary concepts that have been used to explain and model perceptual learning, including receptive field change, selection, and relational recoding. In Section 5, we consider the scope of perceptual learning, contrasting recent research, focused on simple sensory discriminations, with earlier work that emphasized extraction of invariance from varied instances in more complex tasks. Contrary to some recent views, we argue that perceptual learning should not be confined to changes in early sensory analyzers. Phenomena at various levels, we suggest, can be unified by models that emphasize discovery and selection of relevant information. In a final section, we consider the potential role of perceptual learning in educational settings. Most instruction emphasizes facts and procedures that can be verbalized, whereas expertise depends heavily on implicit pattern recognition and selective extraction skills acquired through perceptual learning. We consider reasons why perceptual learning has not been systematically addressed in traditional instruction, and we describe recent successful efforts to create a technology of perceptual

Perceptual learning and human expertise

Science.gov (United States)

Kellman, Philip J.; Garrigan, Patrick

2009-06-01

We consider perceptual learning: experience-induced changes in the way perceivers extract information. Often neglected in scientific accounts of learning and in instruction, perceptual learning is a fundamental contributor to human expertise and is crucial in domains where humans show remarkable levels of attainment, such as language, chess, music, and mathematics. In Section 2, we give a brief history and discuss the relation of perceptual learning to other forms of learning. We consider in Section 3 several specific phenomena, illustrating the scope and characteristics of perceptual learning, including both discovery and fluency effects. We describe abstract perceptual learning, in which structural relationships are discovered and recognized in novel instances that do not share constituent elements or basic features. In Section 4, we consider primary concepts that have been used to explain and model perceptual learning, including receptive field change, selection, and relational recoding. In Section 5, we consider the scope of perceptual learning, contrasting recent research, focused on simple sensory discriminations, with earlier work that emphasized extraction of invariance from varied instances in more complex tasks. Contrary to some recent views, we argue that perceptual learning should not be confined to changes in early sensory analyzers. Phenomena at various levels, we suggest, can be unified by models that emphasize discovery and selection of relevant information. In a final section, we consider the potential role of perceptual learning in educational settings. Most instruction emphasizes facts and procedures that can be verbalized, whereas expertise depends heavily on implicit pattern recognition and selective extraction skills acquired through perceptual learning. We consider reasons why perceptual learning has not been systematically addressed in traditional instruction, and we describe recent successful efforts to create a technology of perceptual

Nationwide Genomic Study in Denmark Reveals Remarkable Population Homogeneity.

Science.gov (United States)

Athanasiadis, Georgios; Cheng, Jade Y; Vilhjálmsson, Bjarni J; Jørgensen, Frank G; Als, Thomas D; Le Hellard, Stephanie; Espeseth, Thomas; Sullivan, Patrick F; Hultman, Christina M; Kjærgaard, Peter C; Schierup, Mikkel H; Mailund, Thomas

2016-10-01

Denmark has played a substantial role in the history of Northern Europe. Through a nationwide scientific outreach initiative, we collected genetic and anthropometrical data from ∼800 high school students and used them to elucidate the genetic makeup of the Danish population, as well as to assess polygenic predictions of phenotypic traits in adolescents. We observed remarkable homogeneity across different geographic regions, although we could still detect weak signals of genetic structure reflecting the history of the country. Denmark presented genomic affinity with primarily neighboring countries with overall resemblance of decreasing weight from Britain, Sweden, Norway, Germany, and France. A Polish admixture signal was detected in Zealand and Funen, and our date estimates coincided with historical evidence of Wend settlements in the south of Denmark. We also observed considerably diverse demographic histories among Scandinavian countries, with Denmark having the smallest current effective population size compared to Norway and Sweden. Finally, we found that polygenic prediction of self-reported adolescent height in the population was remarkably accurate (R 2 = 0.639 ± 0.015). The high homogeneity of the Danish population could render population structure a lesser concern for the upcoming large-scale gene-mapping studies in the country. Copyright © 2016 by the Genetics Society of America.

Remarks on the thermopreferendum of palearctic bats in their natural habitats

NARCIS (Netherlands)

Gaisler, Jiří

1970-01-01

This contribution comprises two remarks of ecological rather than physiological character. Contrary to Herter (1952), Herreid (1967), and Harmata (1969), I did not examine the temperature preference, or thermopreferendum, of bats under experimental conditions but concluded on it only on grounds of

Remarkable Women in a Remarkable Age. On the Genesis of the English Public Sphere, 1642-1752

Directory of Open Access Journals (Sweden)

Eleonora Cappuccilli

2015-06-01

Full Text Available During the era of the English Revolutions and shortly after that, some spaces, albeit limited, of female visibility open up. Thanks to the window of opportunity caused by the collapse of censorship, the participation in the radical sects and in the Civil war, some remarkable women succeed in introducing themselves in the public sphere, shaping it since its very genesis. Moreover, analysing law institutions as jointure and feoffment, the attempt is to reconstruct some fragments of juridical female autonomy, which belie the total pervasiveness of coverture in the XVII century. As in private law, in public law women, in the role of queens, gain centrality: the principle of female authority, while safeguards the holding of the monarchical regime, destabilizes its patriarchal structure. Going through the works of Katherine Chidley, Margaret Cavendish, Damaris Masham and Mary Astell, the essay aims at reconstructing women's public voice, a voice which upsets the consolidated frames and subverts the established positions, questioning the same social hierarchies.

Autonomy in learning: a relationship between failure and success of Distance Education students

Directory of Open Access Journals (Sweden)

Adejalmo Moreira Abadi

2016-05-01

Full Text Available This paper presents the results of a research conducted with undergraduate students of distance education at face-to-face support learning centers of Roraima. The research aimed to analyze the relationship between autonomy in distance learning and students’ outcomes. The issue was to investigate which causes related to autonomy contributed to the low performance rate. The theoretical framework deals with Distance Education and autonomy in distance learning. It was a quali-quantitative research, delineated as a case study. The data analysis was structured in order to define the profile of the student, the factors that influence dropout and completion of the courses. The final remarks present evidence of interfering causes in the results and in the relationship with learning autonomy, involving students as learning structure, and the institution as teaching structure.

Reduced magnetohydrodynamics and the Hasegawa-Mima equation

International Nuclear Information System (INIS)

Hazeltine, R.D.

1983-04-01

Reduced magnetohydrodynamics consists of a set of simplified fluid equations which has become a principal tool in the interpretation of plasma fluid motions in tokamak experiments. The Hasegawa-Mima equation is applied to the study of electrostatic fluctuations in turbulent plasmas. The relation between thee two nonlinear models is elucidated. It is shown tht both models can be obtained from appropriate limits of a third, inclusive, nonlinear system. The inclusive system is remarkably simple

Exploring the Role of Conventionality in Children's Interpretation of Ironic Remarks

Science.gov (United States)

Burnett, Debra L.

2015-01-01

Irony comprehension in seven- and eight-year-old children with typically developing language skills was explored under the framework of the graded salience hypothesis. Target ironic remarks, either conventional or novel/situation-specific, were presented following brief story contexts. Children's responses to comprehension questions were used to…

Reduced Interference from Memory Testing: A Postretrieval Monitoring Account

Science.gov (United States)

Pierce, Benton H.; Gallo, David A.; McCain, Jason L.

2017-01-01

Initial learning can interfere with subsequent learning (proactive interference [PI]), but recent work indicates initial testing can reduce PI. Here, we tested 2 alternative hypotheses of this effect: Does testing reduce PI by constraining retrieval to the target list, or by facilitating a postretrieval monitoring process? Participants first…

Remarks of the SFRP working group about ICRP recommendations

International Nuclear Information System (INIS)

Schieber, C.; Cordoliani, Y.S.

2005-01-01

Remarks of the SFRP working group about ICRP recommendations. The International Commission on Radiological Protection has proposed last summer on its Web site the draft text of the 2005 ICRP recommendations for consultation. As it was done for the previous drafts, the French Society for Radiation Protection, has sent his comments to the ICRP, through a specific working group. The text sent to the ICRP is presented here to the readers of the SFRP's Journal. (author)

A brief history of the most remarkable numbers e, i and γ in mathematical sciences with applications

Science.gov (United States)

Debnath, Lokenath

2015-08-01

This paper deals with a brief history of the most remarkable Euler numbers e, i and γ in mathematical sciences. Included are many properties of the constants e, i and γ and their applications in algebra, geometry, physics, chemistry, ecology, business and industry. Special attention is given to the growth and decay phenomena in many real-world problems including stability and instability of their solutions. Some specific and modern applications of logarithms, complex numbers and complex exponential functions to electrical circuits and mechanical systems are presented with examples. Included are the use of complex numbers and complex functions in the description and analysis of chaos and fractals with the aid of modern computer technology. In addition, the phasor method is described with examples of applications in engineering science. The major focus of this paper is to provide basic information through historical approach to mathematics teaching and learning of the fundamental knowledge and skills required for students and teachers at all levels so that they can understand the concepts of mathematics, and mathematics education in science and technology.

Functional electrical stimulation mediated by iterative learning control and 3D robotics reduces motor impairment in chronic stroke

Directory of Open Access Journals (Sweden)

Meadmore Katie L

2012-06-01

Full Text Available Abstract Background Novel stroke rehabilitation techniques that employ electrical stimulation (ES and robotic technologies are effective in reducing upper limb impairments. ES is most effective when it is applied to support the patients’ voluntary effort; however, current systems fail to fully exploit this connection. This study builds on previous work using advanced ES controllers, and aims to investigate the feasibility of Stimulation Assistance through Iterative Learning (SAIL, a novel upper limb stroke rehabilitation system which utilises robotic support, ES, and voluntary effort. Methods Five hemiparetic, chronic stroke participants with impaired upper limb function attended 18, 1 hour intervention sessions. Participants completed virtual reality tracking tasks whereby they moved their impaired arm to follow a slowly moving sphere along a specified trajectory. To do this, the participants’ arm was supported by a robot. ES, mediated by advanced iterative learning control (ILC algorithms, was applied to the triceps and anterior deltoid muscles. Each movement was repeated 6 times and ILC adjusted the amount of stimulation applied on each trial to improve accuracy and maximise voluntary effort. Participants completed clinical assessments (Fugl-Meyer, Action Research Arm Test at baseline and post-intervention, as well as unassisted tracking tasks at the beginning and end of each intervention session. Data were analysed using t-tests and linear regression. Results From baseline to post-intervention, Fugl-Meyer scores improved, assisted and unassisted tracking performance improved, and the amount of ES required to assist tracking reduced. Conclusions The concept of minimising support from ES using ILC algorithms was demonstrated. The positive results are promising with respect to reducing upper limb impairments following stroke, however, a larger study is required to confirm this.

Escaping the flybottle: solipsism and method in Wittgenstein's Philosophical Remarks

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Jônadas Techio

2012-12-01

Full Text Available The paper supports a dialectical interpretation of Wittgenstein's method focusing on the analysis of the conditions of experience presented in his Philosophical Remarks. By means of a close reading of some key passages dealing with solipsism I will try to lay bare their self-subverting character: the fact that they amount to miniature dialectical exercises offering specific directions to pass from particular pieces of disguised nonsense to corresponding pieces of patent nonsense. Yet, in order to follow those directions one needs to allow oneself to become simultaneously tempted by and suspicious of their all-too-evident "metaphysical tone" - a tone which, as we shall see, is particularly manifest in those claims purporting to state what can or cannot be the case, and, still more particularly, those purporting to state what can or cannot be done in language or thought, thus leading to the view that there are some (determinate things which are ineffable or unthinkable. I conclude by suggesting that in writing those remarks Wittgenstein was still moved by an ethical project, which gets conspicuously displayed in these reiterations of his attempts to cure the readers (and himself from some of the temptations expressed by solipsism.

Grids in topographic maps reduce distortions in the recall of learned object locations.

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Edler, Dennis; Bestgen, Anne-Kathrin; Kuchinke, Lars; Dickmann, Frank

2014-01-01

To date, it has been shown that cognitive map representations based on cartographic visualisations are systematically distorted. The grid is a traditional element of map graphics that has rarely been considered in research on perception-based spatial distortions. Grids do not only support the map reader in finding coordinates or locations of objects, they also provide a systematic structure for clustering visual map information ("spatial chunks"). The aim of this study was to examine whether different cartographic kinds of grids reduce spatial distortions and improve recall memory for object locations. Recall performance was measured as both the percentage of correctly recalled objects (hit rate) and the mean distance errors of correctly recalled objects (spatial accuracy). Different kinds of grids (continuous lines, dashed lines, crosses) were applied to topographic maps. These maps were also varied in their type of characteristic areas (LANDSCAPE) and different information layer compositions (DENSITY) to examine the effects of map complexity. The study involving 144 participants shows that all experimental cartographic factors (GRID, LANDSCAPE, DENSITY) improve recall performance and spatial accuracy of learned object locations. Overlaying a topographic map with a grid significantly reduces the mean distance errors of correctly recalled map objects. The paper includes a discussion of a square grid's usefulness concerning object location memory, independent of whether the grid is clearly visible (continuous or dashed lines) or only indicated by crosses.

Learning Based Approach for Optimal Clustering of Distributed Program's Call Flow Graph

Science.gov (United States)

Abofathi, Yousef; Zarei, Bager; Parsa, Saeed

Optimal clustering of call flow graph for reaching maximum concurrency in execution of distributable components is one of the NP-Complete problems. Learning automatas (LAs) are search tools which are used for solving many NP-Complete problems. In this paper a learning based algorithm is proposed to optimal clustering of call flow graph and appropriate distributing of programs in network level. The algorithm uses learning feature of LAs to search in state space. It has been shown that the speed of reaching to solution increases remarkably using LA in search process, and it also prevents algorithm from being trapped in local minimums. Experimental results show the superiority of proposed algorithm over others.

Using Learning Strategies to Inhibit the Nocebo Effect.

Science.gov (United States)

Quinn, Veronica F; Colagiuri, Ben

2018-01-01

Learning is a key mechanism underpinning the development of the nocebo effect. The learning literature has cataloged and explored numerous ways in which the environment can be manipulated to prevent, reduce, or eradicate learning. Knowledge of these processes could be used to both inhibit the development of nocebo effects and reduce already established nocebo learning. This review describes the available evidence on how such learning strategies have, or could be, applied to reduce the nocebo effect in both healthy participants and patients to date. These learning strategies include overshadowing, latent inhibition, extinction, and contingency degradation. These strategies represent important new avenues for investigation and should be used by researchers to design and test interventions to reduce nocebo effects. © 2018 Elsevier Inc. All rights reserved.

Reduced tonic inhibition in the dentate gyrus contributes to chronic stress-induced impairments in learning and memory.

Science.gov (United States)

Lee, Vallent; MacKenzie, Georgina; Hooper, Andrew; Maguire, Jamie

2016-10-01

It is well established that stress impacts the underlying processes of learning and memory. The effects of stress on memory are thought to involve, at least in part, effects on the hippocampus, which is particularly vulnerable to stress. Chronic stress induces hippocampal alterations, including but not limited to dendritic atrophy and decreased neurogenesis, which are thought to contribute to chronic stress-induced hippocampal dysfunction and deficits in learning and memory. Changes in synaptic transmission, including changes in GABAergic inhibition, have been documented following chronic stress. Recently, our laboratory demonstrated shifts in EGABA in CA1 pyramidal neurons following chronic stress, compromising GABAergic transmission and increasing excitability of these neurons. Interestingly, here we demonstrate that these alterations are unique to CA1 pyramidal neurons, since we do not observe shifts in EGABA following chronic stress in dentate gyrus granule cells. Following chronic stress, there is a decrease in the expression of the GABAA receptor (GABAA R) δ subunit and tonic GABAergic inhibition in dentate gyrus granule cells, whereas there is an increase in the phasic component of GABAergic inhibition, evident by an increase in the peak amplitude of spontaneous inhibitory postsynaptic currents (sIPSCs). Given the numerous changes observed in the hippocampus following stress, it is difficult to pinpoint the pertinent contributing pathophysiological factors. Here we directly assess the impact of a reduction in tonic GABAergic inhibition of dentate gyrus granule cells on learning and memory using a mouse model with a decrease in GABAA R δ subunit expression specifically in dentate gyrus granule cells (Gabrd/Pomc mice). Reduced GABAA R δ subunit expression and function in dentate gyrus granule cells is sufficient to induce deficits in learning and memory. Collectively, these findings suggest that the reduction in GABAA R δ subunit-mediated tonic inhibition

Reduced tonic inhibition in the dentate gyrus contributes to chronic stress-induced impairments in learning and memory

Science.gov (United States)

Hooper, Andrew; Maguire, Jamie

2016-01-01

It is well established that stress impacts the underlying processes of learning and memory. The effects of stress on memory are thought to involve, at least in part, effects on the hippocampus, which is particularly vulnerable to stress. Chronic stress induces hippocampal alterations, including but not limited to dendritic atrophy and decreased neurogenesis, which are thought to contribute to chronic stress-induced hippocampal dysfunction and deficits in learning and memory. Changes in synaptic transmission, including changes in GABAergic inhibition, have been documented following chronic stress. Recently, our laboratory demonstrated shifts in EGABA in CA1 pyramidal neurons following chronic stress, compromising GABAergic transmission and increasing excitability of these neurons. Interestingly, here we demonstrate that these alterations are unique to CA1 pyramidal neurons, since we do not observe shifts in EGABA following chronic stress in dentate gyrus granule cells. Following chronic stress, there is a decrease in the expression of the GABAA receptor (GABAAR) δ subunit and tonic GABAergic inhibition in dentate gyrus granule cells; whereas, there is an increase in the phasic component of GABAergic inhibition, evident by an increase in the peak amplitude of spontaneous inhibitory postsynaptic currents (sIPSCs). Given the numerous changes observed in the hippocampus following stress, it is difficult to pinpoint the pertinent contributing pathophysiological factors. Here we directly assess the impact of a reduction in tonic GABAergic inhibition of dentate gyrus granule cells on learning and memory using a mouse model with a decrease in GABAAR δ subunit expression specifically in dentate gyrus granule cells (Gabrd/Pomc mice). Reduced GABAAR δ subunit expression and function in dentate gyrus granule cells is sufficient to induce deficits in learning and memory. Collectively, these findings suggest that the reduction in GABAAR δ subunit-mediated tonic inhibition in

Remarks about the displaced spectra techniques

International Nuclear Information System (INIS)

Behringer, K.; Pineyro, J.

1989-01-01

In a recent paper a new method, called displaced spectra techniques, was presented for distinguishing between sinusoidal components and narrowband random noise contributions in otherwise random noise data. It is based on Fourier transform techniques, and uses the power spectral density (PSD) and a newly-introduced second-order displaced power spectra density (SDPSD) function. In order to distinguish between the two peak types, a validation criterion has been established. In this note, three topics are covered: a) improved numerical data for the validation criterion are given by using the refined estimation procedure of the PSD and SDPSD functions by the Welch method; b) the validation criterion requires the subtraction of the background below the peaks. A semiautomatic procedure is described; c) it was observed that peaks in the real part of the SDPSD function can be accompanied by fine structure phenomena which are unresolved in the PSD function. A few remarks are made about this problem. (author)

Remark on the gravitational field produced by an infinite straight string

International Nuclear Information System (INIS)

Francisco, G.; Matsas, G.E.A.

1989-01-01

The results predicted by Newtonian gravity and general relativity are compared regarding the field produced by an infinite gauge string with constant density λ. A simple gedankenexperiment is suggested to stress the remarkable differences between these two theories. The existence of the usual Newtonian limit is discussed in this case

Teachers' Remarks about Their Salaries in 1800 in the Helvetic Republic

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Brühwiler, Ingrid

2015-01-01

For centuries, teachers have complained about their salaries. In the Stapfer inquiry of 1799, some teachers made remarks about financial issues, particularly their low incomes. This inquiry is the main source for the arguments presented here regarding teachers' low salary during this period of the Helvetic Republic. The disparity between the…

Older adults learn less, but still reduce metabolic cost, during motor adaptation

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Huang, Helen J.

2013-01-01

The ability to learn new movements and dynamics is important for maintaining independence with advancing age. Age-related sensorimotor changes and increased muscle coactivation likely alter the trial-and-error-based process of adapting to new movement demands (motor adaptation). Here, we asked, to what extent is motor adaptation to novel dynamics maintained in older adults (≥65 yr)? We hypothesized that older adults would adapt to the novel dynamics less well than young adults. Because older adults often use muscle coactivation, we expected older adults to use greater muscle coactivation during motor adaptation than young adults. Nevertheless, we predicted that older adults would reduce muscle activity and metabolic cost with motor adaptation, similar to young adults. Seated older (n = 11, 73.8 ± 5.6 yr) and young (n = 15, 23.8 ± 4.7 yr) adults made targeted reaching movements while grasping a robotic arm. We measured their metabolic rate continuously via expired gas analysis. A force field was used to add novel dynamics. Older adults had greater movement deviations and compensated for just 65% of the novel dynamics compared with 84% in young adults. As expected, older adults used greater muscle coactivation than young adults. Last, older adults reduced muscle activity with motor adaptation and had consistent reductions in metabolic cost later during motor adaptation, similar to young adults. These results suggest that despite increased muscle coactivation, older adults can adapt to the novel dynamics, albeit less accurately. These results also suggest that reductions in metabolic cost may be a fundamental feature of motor adaptation. PMID:24133222

Cuprous oxide nanoparticles dispersed on reduced graphene oxide as an efficient electrocatalyst for oxygen reduction reaction.

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Yan, Xiao-Yan; Tong, Xi-Li; Zhang, Yue-Fei; Han, Xiao-Dong; Wang, Ying-Yong; Jin, Guo-Qiang; Qin, Yong; Guo, Xiang-Yun

2012-02-11

Cuprous oxide (Cu(2)O) nanoparticles dispersed on reduced graphene oxide (RGO) were prepared by reducing copper acetate supported on graphite oxide using diethylene glycol as both solvent and reducing agent. The Cu(2)O/RGO composite exhibits excellent catalytic activity and remarkable tolerance to methanol and CO in the oxygen reduction reaction. This journal is © The Royal Society of Chemistry 2012

Learning invariance from natural images inspired by observations in the primary visual cortex.

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Teichmann, Michael; Wiltschut, Jan; Hamker, Fred

2012-05-01

The human visual system has the remarkable ability to largely recognize objects invariant of their position, rotation, and scale. A good interpretation of neurobiological findings involves a computational model that simulates signal processing of the visual cortex. In part, this is likely achieved step by step from early to late areas of visual perception. While several algorithms have been proposed for learning feature detectors, only few studies at hand cover the issue of biologically plausible learning of such invariance. In this study, a set of Hebbian learning rules based on calcium dynamics and homeostatic regulations of single neurons is proposed. Their performance is verified within a simple model of the primary visual cortex to learn so-called complex cells, based on a sequence of static images. As a result, the learned complex-cell responses are largely invariant to phase and position.

Reduced spatial learning in mice infected with the nematode, Heligmosomoides polygyrus.

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Kavaliers, M; Colwell, D D

1995-06-01

Parasite modification of host behaviour influences a number of critical responses, but little is known about the effects on host spatial abilities. This study examined the effects of infection with the intestinal trichostrongylid nematode, Heligmosomoides polygyrus, on spatial water maze learning by male laboratory mice, Mus musculus. In this task individual mice had to learn the spatial location of a submerged hidden platform using extramaze visual cues. Determinations of spatial performance were made on day 19 post-infection with mice that had been administered either 50 or 200 infective larvae of H. polygyrus. The infected mice displayed over 1 day of testing (6 blocks of 4 trials) significantly poorer acquisition and retention of the water maze task than either sham-infected or control mice, with mice that had received 200 infective larvae displaying significantly poorer spatial performance than individuals receiving 50 larvae. The decrease in spatial learning occurred in the absence of either any symptoms of illness and malaise, or any evident motor, visual and motivational impairments. It is suggested that in this single host system the parasitic infection-induced decrease in spatial learning arises as a side-effect of the host's immunological and neuromodulatory responses and represents a fitness cost of response to infection.

Reduced autobiographical memory specificity is associated with impaired discrimination learning in anxiety disorder patients

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Lenaert, Bert; Boddez, Yannick; Vervliet, Bram; Schruers, Koen; Hermans, Dirk

2015-01-01

Associative learning plays an important role in the development of anxiety disorders, but a thorough understanding of the variables that impact such learning is still lacking. We investigated whether individual differences in autobiographical memory specificity are related to discrimination learning and generalization. In an associative learning task, participants learned the association between two pictures of female faces and a non-aversive outcome. Subsequently, six morphed pictures functioning as generalization stimuli (GSs) were introduced. In a sample of healthy participants (Study 1), we did not find evidence for differences in discrimination learning as a function of memory specificity. In a sample of anxiety disorder patients (Study 2), individuals who were characterized by low memory specificity showed deficient discrimination learning relative to high specific individuals. In contrast to previous findings, results revealed no effect of memory specificity on generalization. These results indicate that impaired discrimination learning, previously shown in patients suffering from an anxiety disorder, may be—in part—due to limited memory specificity. Together, these studies emphasize the importance of incorporating cognitive variables in associative learning theories and their implications for the development of anxiety disorders. In addition, re-analyses of the data (Study 3) showed that patients suffering from panic disorder showed higher outcome expectancies in the presence of the stimulus that was never followed by an outcome during discrimination training, relative to patients suffering from other anxiety disorders and healthy participants. Because we used a neutral, non-aversive outcome (i.e., drawing of a lightning bolt), these data suggest that learning abnormalities in panic disorder may not be restricted to fear learning, but rather reflect a more general associative learning deficit that also manifests in fear irrelevant contexts. PMID

Phenotypic transformation affects associative learning in the desert locust.

Science.gov (United States)

Simões, Patrício M V; Niven, Jeremy E; Ott, Swidbert R

2013-12-02

In desert locusts, increased population densities drive phenotypic transformation from the solitarious to the gregarious phase within a generation [1-4]. Here we show that when presented with odor-food associations, the two extreme phases differ in aversive but not appetitive associative learning, with solitarious locusts showing a conditioned aversion more quickly than gregarious locusts. The acquisition of new learned aversions was blocked entirely in acutely crowded solitarious (transiens) locusts, whereas appetitive learning and prior learned associations were unaffected. These differences in aversive learning support phase-specific feeding strategies. Associative training with hyoscyamine, a plant alkaloid found in the locusts' habitat [5, 6], elicits a phase-dependent odor preference: solitarious locusts avoid an odor associated with hyoscyamine, whereas gregarious locusts do not. Remarkably, when solitarious locusts are crowded and then reconditioned with the odor-hyoscyamine pairing as transiens, the specific blockade of aversive acquisition enables them to override their prior aversive memory with an appetitive one. Under fierce food competition, as occurs during crowding in the field, this provides a neuroecological mechanism enabling locusts to reassign an appetitive value to an odor that they learned previously to avoid. Copyright © 2013 Elsevier Ltd. All rights reserved.

The effect of negative performance stereotypes on learning.

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Rydell, Robert J; Rydell, Michael T; Boucher, Kathryn L

2010-12-01

Stereotype threat (ST) research has focused exclusively on how negative group stereotypes reduce performance. The present work examines if pejorative stereotypes about women in math inhibit their ability to learn the mathematical rules and operations necessary to solve math problems. In Experiment 1, women experiencing ST had difficulty encoding math-related information into memory and, therefore, learned fewer mathematical rules and showed poorer math performance than did controls. In Experiment 2, women experiencing ST while learning modular arithmetic (MA) performed more poorly than did controls on easy MA problems; this effect was due to reduced learning of the mathematical operations underlying MA. In Experiment 3, ST reduced women's, but not men's, ability to learn abstract mathematical rules and to transfer these rules to a second, isomorphic task. This work provides the first evidence that negative stereotypes about women in math reduce their level of mathematical learning and demonstrates that reduced learning due to stereotype threat can lead to poorer performance in negatively stereotyped domains. PsycINFO Database Record (c) 2010 APA, all rights reserved.

Unbound color, prefaced by remarks on baryon spectroscopy

International Nuclear Information System (INIS)

Greenberg, O.W.

Theoretical and experimental issues related to the possibility that color is unbound are surveyed. This implies that quarks, gluons and other particles carrying color can exist as isolated objects. It is surprisingly difficult to distinguish models with unbound color from those in which color is permanently confined. None-the-less, the present situation seems discouraging for unbound color because there is no unambiguous support for it and because the crucial prediction of formation of a colored gluon in e + e - collisions has been ruled out wherever sufficient data exists. The above survey is prefaced by remarks on the symmetric quark model for baryon spectroscopy

Remarks on the 'Grenelle Environnement' portfolio of measures

International Nuclear Information System (INIS)

2009-01-01

The Boston Consulting Group has presented its remarks on the economic impact of the portfolio of measures issued from the 'Grenelle de l'Environnement' workshop that was held in France and involved people with a variety of backgrounds (government representatives, politicians, companies, professional syndicates, NGOs, scientists and university professors, etc.). These measures (covering sectors such as agriculture, biodiversity, wastes, renewable energies, transport, buildings, risk prevention, etc.) are said to potentially generate 450 billions Euros of economic activities and 600,000 jobs during 12 years. Their direct impacts on the environment would be a 14 percent reduction in greenhouse gases between 2010 and 2020. Concerning renewable energies, investment focusing is suggested

Remarkable rates of lightning strike mortality in Malawi.

Science.gov (United States)

Mulder, Monique Borgerhoff; Msalu, Lameck; Caro, Tim; Salerno, Jonathan

2012-01-01

Livingstone's second mission site on the shore of Lake Malawi suffers very high rates of consequential lightning strikes. Comprehensive interviewing of victims and their relatives in seven Traditional Authorities in Nkhata Bay District, Malawi revealed that the annual rate of consequential strikes was 419/million, more than six times higher than that in other developing countries; the rate of deaths from lightning was 84/million/year, 5.4 times greater than the highest ever recorded. These remarkable figures reveal that lightning constitutes a significant stochastic source of mortality with potential life history consequences, but it should not deflect attention away from the more prominent causes of mortality in this rural area.

Remarks on search methods for stable, massive, elementary particles

International Nuclear Information System (INIS)

Perl, Martin L.

2001-01-01

This paper was presented at the 69th birthday celebration of Professor Eugene Commins, honoring his research achievements. These remarks are about the experimental techniques used in the search for new stable, massive particles, particles at least as massive as the electron. A variety of experimental methods such as accelerator experiments, cosmic ray studies, searches for halo particles in the galaxy and searches for exotic particles in bulk matter are described. A summary is presented of the measured limits on the existence of new stable, massive particle

Adiabatic analysis of collisions. III. Remarks on the spin model

International Nuclear Information System (INIS)

Fano, U.

1979-01-01

Analysis of a spin-rotation model illustrates how transitions between adiabatic channel states stem from the second, rather than from the first, rate of change of these states, provided that appropriate identification of channels and scaling of the independent variable are used. These remarks, like the earlier development of a post-adiabatic approach, aim at elucidating the surprising success of approximate separation of variables in the treatment of complex mechanical systems

Remarkable Computing - the Challenge of Designing for the Home

DEFF Research Database (Denmark)

Petersen, Marianne Graves

2004-01-01

The vision of ubiquitous computing is floating into the domain of the household, despite arguments that lessons from design of workplace artefacts cannot be blindly transferred into the domain of the household. This paper discusses why the ideal of unremarkable or ubiquitous computing is too narrow...... with respect to the household. It points out how understanding technology use, is a matter of looking into the process of use and on how the specific context of the home, in several ways, call for technology to be remarkable rather than unremarkable....

LIFELONG LEARNING THROUGH SECOND LIFE: CURRENT TRENDS, POTENTIALS AND LIMITATIONS

Directory of Open Access Journals (Sweden)

Nil GOKSEL-CANBEK

2011-08-01

Full Text Available Lifelong Learning (LLL has been a remarkable response to people-centered educational demand of 21st century. In order to provide effective formal, non-formal, and informal learning, immersive educational activities undertaken throughout life should be aimed to create a learning society in which people can experience individual and collective learning with no constrains of time or location. The concept of lifelong learning within the context of distance immersive education encompasses diverse 3D activities. The three dimensional, Web-based structured activities supported by distance learning technologies can be viewed as interactive tools which foster LLL. In this perspective, Second Life (SL can be regarded as one of the learning simulation milieus that allow learners to participate in various educational LLL activities in individual or group forms. The following paper examines how SL, taking advantage of its simulative nature and the possibility for creative interaction among participants, which are also common in games, allows the learners to participate in immersive constructivist learning activities. The article will also touch on the current uses of SL as a tool for LLL, as well as its potentials for further development according to the current trends in adult education. Further, the authors will discuss its limitations and will make suggestions towards a more complete pedagogical use.

Event-Driven Random Back-Propagation: Enabling Neuromorphic Deep Learning Machines.

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Neftci, Emre O; Augustine, Charles; Paul, Somnath; Detorakis, Georgios

2017-01-01

An ongoing challenge in neuromorphic computing is to devise general and computationally efficient models of inference and learning which are compatible with the spatial and temporal constraints of the brain. One increasingly popular and successful approach is to take inspiration from inference and learning algorithms used in deep neural networks. However, the workhorse of deep learning, the gradient descent Gradient Back Propagation (BP) rule, often relies on the immediate availability of network-wide information stored with high-precision memory during learning, and precise operations that are difficult to realize in neuromorphic hardware. Remarkably, recent work showed that exact backpropagated gradients are not essential for learning deep representations. Building on these results, we demonstrate an event-driven random BP (eRBP) rule that uses an error-modulated synaptic plasticity for learning deep representations. Using a two-compartment Leaky Integrate & Fire (I&F) neuron, the rule requires only one addition and two comparisons for each synaptic weight, making it very suitable for implementation in digital or mixed-signal neuromorphic hardware. Our results show that using eRBP, deep representations are rapidly learned, achieving classification accuracies on permutation invariant datasets comparable to those obtained in artificial neural network simulations on GPUs, while being robust to neural and synaptic state quantizations during learning.

Event-Driven Random Back-Propagation: Enabling Neuromorphic Deep Learning Machines

Directory of Open Access Journals (Sweden)

Emre O. Neftci

2017-06-01

Full Text Available An ongoing challenge in neuromorphic computing is to devise general and computationally efficient models of inference and learning which are compatible with the spatial and temporal constraints of the brain. One increasingly popular and successful approach is to take inspiration from inference and learning algorithms used in deep neural networks. However, the workhorse of deep learning, the gradient descent Gradient Back Propagation (BP rule, often relies on the immediate availability of network-wide information stored with high-precision memory during learning, and precise operations that are difficult to realize in neuromorphic hardware. Remarkably, recent work showed that exact backpropagated gradients are not essential for learning deep representations. Building on these results, we demonstrate an event-driven random BP (eRBP rule that uses an error-modulated synaptic plasticity for learning deep representations. Using a two-compartment Leaky Integrate & Fire (I&F neuron, the rule requires only one addition and two comparisons for each synaptic weight, making it very suitable for implementation in digital or mixed-signal neuromorphic hardware. Our results show that using eRBP, deep representations are rapidly learned, achieving classification accuracies on permutation invariant datasets comparable to those obtained in artificial neural network simulations on GPUs, while being robust to neural and synaptic state quantizations during learning.

How can machine-learning methods assist in virtual screening for hyperuricemia? A healthcare machine-learning approach.

Science.gov (United States)

Ichikawa, Daisuke; Saito, Toki; Ujita, Waka; Oyama, Hiroshi

2016-12-01

Our purpose was to develop a new machine-learning approach (a virtual health check-up) toward identification of those at high risk of hyperuricemia. Applying the system to general health check-ups is expected to reduce medical costs compared with administering an additional test. Data were collected during annual health check-ups performed in Japan between 2011 and 2013 (inclusive). We prepared training and test datasets from the health check-up data to build prediction models; these were composed of 43,524 and 17,789 persons, respectively. Gradient-boosting decision tree (GBDT), random forest (RF), and logistic regression (LR) approaches were trained using the training dataset and were then used to predict hyperuricemia in the test dataset. Undersampling was applied to build the prediction models to deal with the imbalanced class dataset. The results showed that the RF and GBDT approaches afforded the best performances in terms of sensitivity and specificity, respectively. The area under the curve (AUC) values of the models, which reflected the total discriminative ability of the classification, were 0.796 [95% confidence interval (CI): 0.766-0.825] for the GBDT, 0.784 [95% CI: 0.752-0.815] for the RF, and 0.785 [95% CI: 0.752-0.819] for the LR approaches. No significant differences were observed between pairs of each approach. Small changes occurred in the AUCs after applying undersampling to build the models. We developed a virtual health check-up that predicted the development of hyperuricemia using machine-learning methods. The GBDT, RF, and LR methods had similar predictive capability. Undersampling did not remarkably improve predictive power. Copyright © 2016 Elsevier Inc. All rights reserved.

Mosaic model for sensorimotor learning and control.

Science.gov (United States)

Haruno, M; Wolpert, D M; Kawato, M

2001-10-01

Humans demonstrate a remarkable ability to generate accurate and appropriate motor behavior under many different and often uncertain environmental conditions. We previously proposed a new modular architecture, the modular selection and identification for control (MOSAIC) model, for motor learning and control based on multiple pairs of forward (predictor) and inverse (controller) models. The architecture simultaneously learns the multiple inverse models necessary for control as well as how to select the set of inverse models appropriate for a given environment. It combines both feedforward and feedback sensorimotor information so that the controllers can be selected both prior to movement and subsequently during movement. This article extends and evaluates the MOSAIC architecture in the following respects. The learning in the architecture was implemented by both the original gradient-descent method and the expectation-maximization (EM) algorithm. Unlike gradient descent, the newly derived EM algorithm is robust to the initial starting conditions and learning parameters. Second, simulations of an object manipulation task prove that the architecture can learn to manipulate multiple objects and switch between them appropriately. Moreover, after learning, the model shows generalization to novel objects whose dynamics lie within the polyhedra of already learned dynamics. Finally, when each of the dynamics is associated with a particular object shape, the model is able to select the appropriate controller before movement execution. When presented with a novel shape-dynamic pairing, inappropriate activation of modules is observed followed by on-line correction.

Parental Attitudes and Motivational Factors in Enrollment of Children in Early Foreign Language Learning in the Notranjska Region

Directory of Open Access Journals (Sweden)

Darja Premrl

2012-12-01

Full Text Available In this article we present the parents‘ opinions about the contemporary sources in the field of early foreign language teaching and learning and their influence on the decisions parents make about including/excluding their child into the program of early foreign language learning. We found out, on the one hand, that parents are poorly informed about the current state of early foreign language learning both in Slovenia and abroad. On the other hand, parents reported positive attitudes about early foreign language teaching, a remarkable sense of right approach in early foreign language learning and, above all, their desire to know more about the subject.

The effect of learning on the function of monkey extrastriate visual cortex.

Directory of Open Access Journals (Sweden)

Gregor Rainer

2004-02-01

Full Text Available One of the most remarkable capabilities of the adult brain is its ability to learn and continuously adapt to an ever-changing environment. While many studies have documented how learning improves the perception and identification of visual stimuli, relatively little is known about how it modifies the underlying neural mechanisms. We trained monkeys to identify natural images that were degraded by interpolation with visual noise. We found that learning led to an improvement in monkeys' ability to identify these indeterminate visual stimuli. We link this behavioral improvement to a learning-dependent increase in the amount of information communicated by V4 neurons. This increase was mediated by a specific enhancement in neural activity. Our results reveal a mechanism by which learning increases the amount of information that V4 neurons are able to extract from the visual environment. This suggests that V4 plays a key role in resolving indeterminate visual inputs by coordinated interaction between bottom-up and top-down processing streams.

The end of a remarkable era

CERN Multimedia

2011-01-01

An important era in particle physics is coming to an end: the US Department of Energy announced on Monday that it will not fund an extension to Tevatron running beyond 2011. It is a poignant moment for particle physics as we prepare to bid farewell to a machine that has changed our view of the Universe, and played a significant role in paving the way for the new era that is opening up with the LHC.   The Tevatron has been at the high-energy frontier of particle physics for over a quarter of a century. That’s a remarkable achievement by any account, and the physics results are there to prove it. As well as bringing us the discovery of the top quark in 1995, the Tevatron’s experiments have provided vitally important precision measurements covering the full spectrum of Standard Model physics, not to mention hints of what may lie beyond. With several months of running still to come, it would be a foolish gambler who bet against further new physics emerging before the Teva...

Using Perturbed Physics Ensembles and Machine Learning to Select Parameters for Reducing Regional Biases in a Global Climate Model

Science.gov (United States)

Li, S.; Rupp, D. E.; Hawkins, L.; Mote, P.; McNeall, D. J.; Sarah, S.; Wallom, D.; Betts, R. A.

2017-12-01

This study investigates the potential to reduce known summer hot/dry biases over Pacific Northwest in the UK Met Office's atmospheric model (HadAM3P) by simultaneously varying multiple model parameters. The bias-reduction process is done through a series of steps: 1) Generation of perturbed physics ensemble (PPE) through the volunteer computing network weather@home; 2) Using machine learning to train "cheap" and fast statistical emulators of climate model, to rule out regions of parameter spaces that lead to model variants that do not satisfy observational constraints, where the observational constraints (e.g., top-of-atmosphere energy flux, magnitude of annual temperature cycle, summer/winter temperature and precipitation) are introduced sequentially; 3) Designing a new PPE by "pre-filtering" using the emulator results. Steps 1) through 3) are repeated until results are considered to be satisfactory (3 times in our case). The process includes a sensitivity analysis to find dominant parameters for various model output metrics, which reduces the number of parameters to be perturbed with each new PPE. Relative to observational uncertainty, we achieve regional improvements without introducing large biases in other parts of the globe. Our results illustrate the potential of using machine learning to train cheap and fast statistical emulators of climate model, in combination with PPEs in systematic model improvement.

Concluding remarks of international symposium on highly excited states in nuclear reactions

Energy Technology Data Exchange (ETDEWEB)

Bernstein, A. M.; Ikegami, H.; Muraoka, M. [eds.

1980-01-01

This is the concluding remarks in the international symposium on highly excited states in nuclear reactions. The remarks concentrate on the giant quadrupole states. In the framework of the distorted wave Born approximation (DWB), the differential cross section can be deduced. The relevant transition matrix elements are defined, and the quantities which are measured in inelastic hadron (h, h') reactions are shown. These are used to obtain both neutron and proton transition multipole matrix elements. This is equivalent to make the isospin decomposition of the electromagnetic transition matrix elements. The ratios of the transition matrix elements of neutrons and protons of the lowest 2/sup +/ states in even-even single closed shell nuclei are evaluated and compared with experimental results. For each nucleus, the consistency between various measurements is generally good. The effect of the virtual excitation of giant 2/sup +/ states into the ground and first excited states of even-even nuclei is discussed. The accuracy of (h, h') results can be tested.

Machine Learning-based discovery of closures for reduced models of dynamical systems

Science.gov (United States)

Pan, Shaowu; Duraisamy, Karthik

2017-11-01

Despite the successful application of machine learning (ML) in fields such as image processing and speech recognition, only a few attempts has been made toward employing ML to represent the dynamics of complex physical systems. Previous attempts mostly focus on parameter calibration or data-driven augmentation of existing models. In this work we present a ML framework to discover closure terms in reduced models of dynamical systems and provide insights into potential problems associated with data-driven modeling. Based on exact closure models for linear system, we propose a general linear closure framework from viewpoint of optimization. The framework is based on trapezoidal approximation of convolution term. Hyperparameters that need to be determined include temporal length of memory effect, number of sampling points, and dimensions of hidden states. To circumvent the explicit specification of memory effect, a general framework inspired from neural networks is also proposed. We conduct both a priori and posteriori evaluations of the resulting model on a number of non-linear dynamical systems. This work was supported in part by AFOSR under the project ``LES Modeling of Non-local effects using Statistical Coarse-graining'' with Dr. Jean-Luc Cambier as the technical monitor.

A global first integral for certain dynamical systems and related remarks

International Nuclear Information System (INIS)

Gonzalez-Gascon, F.

1977-01-01

A global first integral for certain dynamical systems and the related remarks are presented. In particular, it is shown that for these dynamical systems by introducing the (intrinsic) definition of the divergence of a vector field defined on an orientable differentiable manifold, the first integral, i.e. the (intrinsic) divergence of a vector field is now, automatically, a global first integral. (author)

Self-assembled thin film of imidazolium ionic liquid on a silicon surface: Low friction and remarkable wear-resistivity

International Nuclear Information System (INIS)

Gusain, Rashi; Kokufu, Sho; Bakshi, Paramjeet S.; Utsunomiya, Toru; Ichii, Takashi; Sugimura, Hiroyuki; Khatri, Om P.

2016-01-01

Graphical abstract: - Highlights: • Ionic liquid thin film is deposited on a silicon surface via covalent interaction. • Chemical and morphological features of ionic liquid thin film are probed by XPS and AFM. • Ionic liquid thin film exhibited low and steady friction along with remarkable wear-resistivity. - Abstract: Imidazolium-hexafluorophosphate (ImPF_6) ionic liquid thin film is prepared on a silicon surface using 3-chloropropyltrimethoxysilane as a bifunctional chemical linker. XPS result revealed the covalent grafting of ImPF_6 thin film on a silicon surface. The atomic force microscopic images demonstrated that the ImPF_6 thin film is composed of nanoscopic pads/clusters with height of 3–7 nm. Microtribological properties in terms of coefficient of friction and wear-resistivity are probed at the mean Hertzian contact pressure of 0.35–0.6 GPa under the rotational sliding contact. The ImPF_6 thin film exhibited low and steady coefficient of friction (μ = 0.11) along with remarkable wear-resistivity to protect the underlying silicon substrate. The low shear strength of ImPF_6 thin film, the covalent interaction between ImPF_6 ionic liquid thin film and underlying silicon substrate, and its regular grafting collectively reduced the friction and improved the anti-wear property. The covalently grafted ionic liquid thin film further shows immense potential to expand the durability and lifetime of M/NEMS based devices with significant reduction of the friction.

Self-assembled thin film of imidazolium ionic liquid on a silicon surface: Low friction and remarkable wear-resistivity

Energy Technology Data Exchange (ETDEWEB)

Gusain, Rashi [CSIR-Indian Institute of Petroleum, Mohkampur, Dehardun 248005 (India); Academy of Scientific and Innovative Research, New Delhi 110025 (India); Kokufu, Sho [Department of Materials Science and Engineering, Kyoto University, Kyoto 606-8501 (Japan); Bakshi, Paramjeet S. [CSIR-Indian Institute of Petroleum, Mohkampur, Dehardun 248005 (India); Utsunomiya, Toru; Ichii, Takashi; Sugimura, Hiroyuki [Department of Materials Science and Engineering, Kyoto University, Kyoto 606-8501 (Japan); Khatri, Om P., E-mail: opkhatri@iip.res.in [CSIR-Indian Institute of Petroleum, Mohkampur, Dehardun 248005 (India); Academy of Scientific and Innovative Research, New Delhi 110025 (India)

2016-02-28

Graphical abstract: - Highlights: • Ionic liquid thin film is deposited on a silicon surface via covalent interaction. • Chemical and morphological features of ionic liquid thin film are probed by XPS and AFM. • Ionic liquid thin film exhibited low and steady friction along with remarkable wear-resistivity. - Abstract: Imidazolium-hexafluorophosphate (ImPF{sub 6}) ionic liquid thin film is prepared on a silicon surface using 3-chloropropyltrimethoxysilane as a bifunctional chemical linker. XPS result revealed the covalent grafting of ImPF{sub 6} thin film on a silicon surface. The atomic force microscopic images demonstrated that the ImPF{sub 6} thin film is composed of nanoscopic pads/clusters with height of 3–7 nm. Microtribological properties in terms of coefficient of friction and wear-resistivity are probed at the mean Hertzian contact pressure of 0.35–0.6 GPa under the rotational sliding contact. The ImPF{sub 6} thin film exhibited low and steady coefficient of friction (μ = 0.11) along with remarkable wear-resistivity to protect the underlying silicon substrate. The low shear strength of ImPF{sub 6} thin film, the covalent interaction between ImPF{sub 6} ionic liquid thin film and underlying silicon substrate, and its regular grafting collectively reduced the friction and improved the anti-wear property. The covalently grafted ionic liquid thin film further shows immense potential to expand the durability and lifetime of M/NEMS based devices with significant reduction of the friction.

A remark on the energy conditions for Hawking's area theorem

Science.gov (United States)

Lesourd, Martin

2018-06-01

Hawking's area theorem is a fundamental result in black hole theory that is universally associated with the null energy condition. That this condition can be weakened is illustrated by the formulation of a strengthened version of the theorem based on an energy condition that allows for violations of the null energy condition. With the semi-classical context in mind, some brief remarks pertaining to the suitability of the area theorem and its energy condition are made.

Aversion learning can reduce meal size without taste avoidance in rats.

Science.gov (United States)

Tracy, Andrea L; Schurdak, Jennifer D; Chambers, James B; Benoit, Stephen C

2016-03-01

Nausea and aversive food responses are commonly reported following bariatric surgery, along with post-surgical reduction in meal size. This study investigates whether a meal size limit can be conditioned by associating large meals with aversive outcomes. In rats, the intake of meals exceeding a pre-defined size threshold was paired with lithium chloride-induced gastric illness, and the effects on self-determined food intakes and body weight were measured. Rats given LiCl contingent on the intake of a large meal learned to reliably reduce intake below this meal size threshold, while post-meal saline or LiCl before meals did not change meal size. It was further demonstrated that this is not a conditioned taste aversion and that this effect transferred to foods not explicitly trained. Finally, when rats received LiCl following all large meals, the number of small meals increased, but total food intake and body weight decreased. While further work is needed, this is the first demonstration that meal size may be conditioned, using an aversion procedure, to remain under a target threshold and that this effect is distinct from taste avoidance. Corresponding reduction in food intake and body weight suggests that this phenomenon may have implications for developing weight loss strategies and understanding the efficacy of bariatric surgery. © 2016 The Obesity Society.

Moral Learning: Conceptual foundations and normative relevance.

Science.gov (United States)

Railton, Peter

2017-10-01

What is distinctive about a bringing a learning perspective to moral psychology? Part of the answer lies in the remarkable transformations that have taken place in learning theory over the past two decades, which have revealed how powerful experience-based learning can be in the acquisition of abstract causal and evaluative representations, including generative models capable of attuning perception, cognition, affect, and action to the physical and social environment. When conjoined with developments in neuroscience, these advances in learning theory permit a rethinking of fundamental questions about the acquisition of moral understanding and its role in the guidance of behavior. For example, recent research indicates that spatial learning and navigation involve the formation of non-perspectival as well as ego-centric models of the physical environment, and that spatial representations are combined with learned information about risk and reward to guide choice and potentiate further learning. Research on infants provides evidence that they form non-perspectival expected-value representations of agents and actions as well, which help them to navigate the human environment. Such representations can be formed by highly-general mental processes such as causal and empathic simulation, and thus afford a foundation for spontaneous moral learning and action that requires no innate moral faculty and can exhibit substantial autonomy with respect to community norms. If moral learning is indeed integral with the acquisition and updating of casual and evaluative models, this affords a new way of understanding well-known but seemingly puzzling patterns in intuitive moral judgment-including the notorious "trolley problems." Copyright © 2016 The Author. Published by Elsevier B.V. All rights reserved.

Reduced Mental Load in Learning a Motor Visual Task with Virtual 3D Method

Science.gov (United States)

Dan, A.; Reiner, M.

2018-01-01

Distance learning is expanding rapidly, fueled by the novel technologies for shared recorded teaching sessions on the Web. Here, we ask whether 3D stereoscopic (3DS) virtual learning environment teaching sessions are more compelling than typical two-dimensional (2D) video sessions and whether this type of teaching results in superior learning. The…

Reducing the drop-out rate of a technical oriented course by introducing Problem Based Learning – a first concept

Directory of Open Access Journals (Sweden)

Christian Kaufmann

2011-04-01

Full Text Available At the University of Applied Sciences (UAS Technikum Wien one of the most difficult courses in the Bachelor degree program of Computer Science is “Database Systems and Database Design”. Together with “Advanced Computer Programming”, this course accounts for the high drop-out rate in the degree program. For this reason, this course was chosen for a redesign, in line with the research project QUADRO (Measures to increase quality of teaching and to reduce drop-out rates promoted by the City of Vienna – MA 27 (EU strategy and promote economic development. As the authors have already gained experience in Problem Based Learning (PBL, they saw an opportunity to improve students’ database knowledge by changing the teaching method to Problem Based Learning (PBL. The proposed paper first explains the current situation, identifies its drawbacks and difficulties. In a second step, it describes the new method, shows the students’ feedback after the first semester and the resulting changes in the concept.

Associative visual learning by tethered bees in a controlled visual environment.

Science.gov (United States)

Buatois, Alexis; Pichot, Cécile; Schultheiss, Patrick; Sandoz, Jean-Christophe; Lazzari, Claudio R; Chittka, Lars; Avarguès-Weber, Aurore; Giurfa, Martin

2017-10-10

Free-flying honeybees exhibit remarkable cognitive capacities but the neural underpinnings of these capacities cannot be studied in flying insects. Conversely, immobilized bees are accessible to neurobiological investigation but display poor visual learning. To overcome this limitation, we aimed at establishing a controlled visual environment in which tethered bees walking on a spherical treadmill learn to discriminate visual stimuli video projected in front of them. Freely flying bees trained to walk into a miniature Y-maze displaying these stimuli in a dark environment learned the visual discrimination efficiently when one of them (CS+) was paired with sucrose and the other with quinine solution (CS-). Adapting this discrimination to the treadmill paradigm with a tethered, walking bee was successful as bees exhibited robust discrimination and preferred the CS+ to the CS- after training. As learning was better in the maze, movement freedom, active vision and behavioral context might be important for visual learning. The nature of the punishment associated with the CS- also affects learning as quinine and distilled water enhanced the proportion of learners. Thus, visual learning is amenable to a controlled environment in which tethered bees learn visual stimuli, a result that is important for future neurobiological studies in virtual reality.

Some remarks on theological thought of María Zambrano

Directory of Open Access Journals (Sweden)

Juana Sánchez-Gey Venegas

2018-01-01

Full Text Available Maria Zambrano reflects upon some of the problems she has been always interested in: Christianity and Mysticism with especial emphasis on the divine processions, the Incarnation of Christ, the Virgin Mary, the liturgy among other personal experiences. In these letters the pursuit for the Holy Spirit as the foundation of knowledge is remarkably noticeable, so that it could be argued that this experience contributes and gives rise to the rejection both of rationalism and of materialism of the philosophy.

Some Remarks on Stochastic Versions of the Ramsey Growth Model

Czech Academy of Sciences Publication Activity Database

Sladký, Karel

2012-01-01

Roč. 19, č. 29 (2012), s. 139-152 ISSN 1212-074X R&D Projects: GA ČR GAP402/10/1610; GA ČR GAP402/10/0956; GA ČR GAP402/11/0150 Institutional support: RVO:67985556 Keywords : Economic dynamics * Ramsey growth model with disturbance * stochastic dynamic programming * multistage stochastic programs Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/separaty/2013/E/sladky-some remarks on stochastic versions of the ramsey growth model.pdf

Learning to Play in a Day: Faster Deep Reinforcement Learning by Optimality Tightening

OpenAIRE

He, Frank S.; Liu, Yang; Schwing, Alexander G.; Peng, Jian

2016-01-01

We propose a novel training algorithm for reinforcement learning which combines the strength of deep Q-learning with a constrained optimization approach to tighten optimality and encourage faster reward propagation. Our novel technique makes deep reinforcement learning more practical by drastically reducing the training time. We evaluate the performance of our approach on the 49 games of the challenging Arcade Learning Environment, and report significant improvements in both training time and...

Stochastic Synapses Enable Efficient Brain-Inspired Learning Machines

Science.gov (United States)

Neftci, Emre O.; Pedroni, Bruno U.; Joshi, Siddharth; Al-Shedivat, Maruan; Cauwenberghs, Gert

2016-01-01

Recent studies have shown that synaptic unreliability is a robust and sufficient mechanism for inducing the stochasticity observed in cortex. Here, we introduce Synaptic Sampling Machines (S2Ms), a class of neural network models that uses synaptic stochasticity as a means to Monte Carlo sampling and unsupervised learning. Similar to the original formulation of Boltzmann machines, these models can be viewed as a stochastic counterpart of Hopfield networks, but where stochasticity is induced by a random mask over the connections. Synaptic stochasticity plays the dual role of an efficient mechanism for sampling, and a regularizer during learning akin to DropConnect. A local synaptic plasticity rule implementing an event-driven form of contrastive divergence enables the learning of generative models in an on-line fashion. S2Ms perform equally well using discrete-timed artificial units (as in Hopfield networks) or continuous-timed leaky integrate and fire neurons. The learned representations are remarkably sparse and robust to reductions in bit precision and synapse pruning: removal of more than 75% of the weakest connections followed by cursory re-learning causes a negligible performance loss on benchmark classification tasks. The spiking neuron-based S2Ms outperform existing spike-based unsupervised learners, while potentially offering substantial advantages in terms of power and complexity, and are thus promising models for on-line learning in brain-inspired hardware. PMID:27445650

HyDR-MI : A hybrid algorithm to reduce dimensionality in multiple instance learning

NARCIS (Netherlands)

Zafra, A.; Pechenizkiy, M.; Ventura, S.

2013-01-01

Feature selection techniques have been successfully applied in many applications for making supervised learning more effective and efficient. These techniques have been widely used and studied in traditional supervised learning settings, where each instance is expected to have a label. In multiple

Parts of the Whole: Learn More, Learn Better

Directory of Open Access Journals (Sweden)

Dorothy Wallace

2012-01-01

Full Text Available Building on previous columns in Numeracy, this column analyzes various teaching techniques in terms of their ability to build cognitive schema, extend existing schema, reinforce learning, move mean understanding of a group of students, and reduce variance in understanding of a group. We offer a pedagogical cycle as an example of how to address multiple learning goals using common teaching methods.

Learning More than Expected: The Influence of Teachers' Attitudes on Children's Learning Outcomes

Science.gov (United States)

Youn, Minjong

2016-01-01

This study employed the concept of teachers' sense of responsibility for students' learning to examine the extent to which the gap in math learning growth is reduced and whether such attitudes can improve children's learning outcomes to a degree that is above and beyond their expected achievement relative to their initial academic skills. Analysis…

Short-term and long-term memory deficits in handedness learning in mice with absent corpus callosum and reduced hippocampal commissure.

Science.gov (United States)

Ribeiro, Andre S; Eales, Brenda A; Biddle, Fred G

2013-05-15

The corpus callosum (CC) and hippocampal commissure (HC) are major interhemispheric connections whose role in brain function and behaviors is fascinating and contentious. Paw preference of laboratory mice is a genetically regulated, adaptive behavior, continuously shaped by training and learning. We studied variation with training in paw-preference in mice of the 9XCA/WahBid ('9XCA') recombinant inbred strain, selected for complete absence of the CC and severely reduced HC. We measured sequences of paw choices in 9XCA mice in two training sessions in unbiased test chambers, separated by one-week. We compared them with sequences of paw choices in model non-learner mice that have random unbiased paw choices and with those of C57BL/6JBid ('C57BL/6J') mice that have normal interhemispheric connections and learn a paw preference. Positive autocorrelation between successive paw choices during each session and change in paw-preference bias between sessions indicate that 9XCA mice have weak, but not null, learning skills. We tested the effect of the forebrain commissural defect on paw-preference learning with the independent BTBR T+ tf/J ('BTBR') mouse strain that has a genetically identical, non-complementing commissural trait. BTBR has weak short-term and long-term memory skills, identical to 9XCA. The results provide strong evidence that CC and HC contribute in memory function and formation of paw-preference biases. Copyright © 2013 Elsevier B.V. All rights reserved.

E-learning in medical education: the potential environmental impact.

Science.gov (United States)

Walsh, Kieran

2018-03-01

Introduction There is a growing interest in the use of e-learning in medical education. However until recently there has been little interest in the potential environmental benefits of e-learning. This paper models various environmental outcomes that might emerge from the use of an e-learning resource (BMJ Learning) in CPD. Methods We modeled the use of e-learning as a component of CPD and evaluated the potential impact of this use on the learner's carbon footprint. We looked at a number of models - all from the perspective of a General Practitioner (GP). We assumed that all GPs completed 50 h or credits of CPD per year. Results High users of e-learning can reduce their carbon footprint - mainly by reducing their travel to face-to-face events (reducing printing also has a small beneficial effect). A high user of e-learning can reduce the carbon footprint that relates to their CPD by 18.5 kg. Discussion As global warming continues to pose a risk to human and environmental health, we feel that doctors have a duty to consider learning activities (such as e-learning) that are associated with a lower carbon footprint.

Neuropsychology of learning and memory in teleost fish.

Science.gov (United States)

Salas, Cosme; Broglio, Cristina; Durán, Emilio; Gómez, Antonia; Ocaña, Francisco M; Jiménez-Moya, Fernando; Rodríguez, Fernando

2006-01-01

Traditionally, brain and behavior evolution was viewed as an anagenetic process that occurred in successive stages of increasing complexity and advancement. Fishes, considered the most primitive vertebrates, were supposed to have a scarcely differentiated telencephalon, and limited learning capabilities. However, recent developmental, neuroanatomical, and functional data indicate that the evolution of brain and behavior may have been more conservative than previously thought. Experimental data suggest that the properties and neural basis of learning and memory are notably similar among teleost fish and land vertebrates. For example, lesion studies show that the teleost cerebellum is essential in classical conditioning of discrete motor responses. The lateral telencephalic pallium of the teleost fish, proposed as homologous to the hippocampus, is selectively involved in spatial learning and memory, and in trace classical conditioning. In contrast, the medial pallium, considered homologous to the amygdala, is involved in emotional conditioning in teleost fish. The data reviewed here show a remarkable parallelism between mammals and teleost fish concerning the role of different brain centers in learning and memory and cognitive processes. These evidences suggest that these separate memory systems could have appeared early during the evolution of vertebrates, having been conserved through phylogenesis.

Scale in technology and learning-by-doing in the windmill industry

DEFF Research Database (Denmark)

Madsen, Erik Strøjer; Jensen, Camilla; Hansen, Jørgen Drud

2003-01-01

that learning-by-doing in the Danish windmill industry has contributed significantly to improve the cost efficiency of the producers. The technological development has been stimulated both by process and product innovations as the capacity of the individual mills has increased. The learning effect created......This paper examines the remarkable development of technology and the fast learning-by-doing in the windmill industry since it emerged in the beginning of the 1980s. Based on time series of prices of windmills, a dynamic cost function for producing windmills is tested. The estimations verified...... by early subsidies from the government has consolidated the competitive advantages of the windmill cluster in Denmark and preserved the first mover advantages at the world market. The article concludes that the industry probably will enter into a matured phase in the future with more modest technological...

Scale in Technology and Learning-by-Doing in the Windmill Industry

DEFF Research Database (Denmark)

Madsen, Erik Strøjer; Jensen, Camilla; Hansen, Jørgen Drud

that learning-by-doing in the Danish windmill industry has contributed significantly to improve the cost efficiency of the producers. The technological development has been stimulated both by process and product innovations as the capacity of the individual mills has increased. The learning effect created......This paper examines the remarkable development of technology and the fast learning-by-doing in the windmill industry since it emerged in the beginning of the 1980s. Based on time series of prices of windmills a dynamic cost function for producing windmills is tested. The estimations verified...... by early subsidies from the government has consolidated the competitive advantages of the windmill cluster in Denmark and preserved the first mover advantages at the world market. The article concludes that the industry probably will enter into a matured phase in the future with more modest technological...

Scale in technology and learning-by-doing in the windmill industry

DEFF Research Database (Denmark)

Madsen, Erik Strøjer; Jensen, Camilla; Hansen, Jørgen Drud

2003-01-01

This paper examines the remarkable development of technology and the fast learning-by-doing in the windmill industry since it emerged in the beginning of the 1980s. Based on time series of prices of windmills, a dynamic cost function for producing windmills is tested. The estimations verified...... that learning-by-doing in the Danish windmill industry has contributed significantly to improve the cost efficiency of the producers. The technological development has been stimulated both by process and product innovations as the capacity of the individual mills has increased. The learning effect created...... by early subsidies from the government has consolidated the competitive advantages of the windmill cluster in Denmark and preserved the first mover advantages at the world market. The article concludes that the industry probably will enter into a matured phase in the future with more modest technological...

The effectiveness of process oriented guided inquiry learning to reduce alternate conceptions in secondary chemistry

Science.gov (United States)

Barthlow, Michelle J.

2011-12-01

A nonequivalent, control group, pretest-posttest design was used to investigate student achievement in secondary chemistry. This study investigated the effect of process oriented guided inquiry learning (POGIL) in high school chemistry to reduce alternate conceptions related to the particulate nature of matter versus traditional lecture pedagogy. Data were collected from chemistry students in four large high schools and analyzed using ANCOVA. The results show that POGIL pedagogy, as opposed to traditional lecture pedagogy, resulted in fewer alternate conceptions related to the particulate nature of matter. Male and female students in the POGIL group posted better posttest scores than their traditional group peers. African-American and Hispanic students in the POGIL group exhibited achievement gains consistent with Caucasian and Asian students. Further studies are needed to determine the value of POGIL to address achievement gap concerns in chemistry.

Remarks on theoretical hot-atom chemistry

International Nuclear Information System (INIS)

Inokuti, Mitio

1993-01-01

The publication of the 'Handbook of Hot Atom Chemistry', following the earlier volume 'Recent Trend and Application', was a major milestone in physical chemistry. Theoretical treatments of hot atom chemistry must address two classes of problems. The first class concerns the individual collisions of hot atoms with other atoms or molecules. The second class concerns the description of the consequences of the many collisions of hot atoms and their chemical environment. Most of the remarks pertain to the problems of the first class. The central issue is the adiabaticity of nuclear motions versus electronic motions. To be precise, any atomic core motion should be mentioned rather than pure nuclear motion, because tightly bound core electrons are largely irrelevant to the chemistry. When nuclear motions are sufficiently slow, or for other reasons that can be regarded as adiabatic, the collision problem is basically straightforward, therefore, interatomic and intermolecular forces can be assumed, and their consequences for nuclear motions are calculable in principle. In the case of non-adiabaticity being important, much more difficult problems arise, and it is briefly discussed, and the work by Phelps is cited. (K.I.)

Aging and depression vulnerability interaction results in decreased serotonin innervation associated with reduced BDNF levels in hippocampus of rats bred for learned helplessness.

Science.gov (United States)

Aznar, Susana; Klein, Anders B; Santini, Martin A; Knudsen, Gitte M; Henn, Fritz; Gass, Peter; Vollmayr, Barbara

2010-07-01

Epidemiological studies have revealed a strong genetic contribution to the risk for depression. Both reduced hippocampal serotonin neurotransmission and brain-derived neurotrophic factor (BDNF) levels have been associated with increased depression vulnerability and are also regulated during aging. Brains from young (5 months old) and old (13 months old) congenital Learned Helplessness rats (cLH), and congenital Non Learned Helplessness rats (cNLH) were immunohistochemically stained for the serotonin transporter and subsequently stereologically quantified for estimating hippocampal serotonin fiber density. Hippocampal BDNF protein levels were measured by ELISA. An exacerbated age-related loss of serotonin fiber density specific for the CA1 area was observed in the cLH animals, whereas reduced hippocampal BDNF levels were seen in young and old cLH when compared with age-matched cNLH controls. These observations indicate that aging should be taken into account when studying the neurobiological factors behind the vulnerability for depression and that understanding the effect of aging on genetically predisposed individuals may contribute to a better understanding of the pathophysiology behind depression, particularly in the elderly.

Faculty Integration of Technology into Instruction and Students' Perceptions of Computer Technology to Improve Student Learning

Science.gov (United States)

Keengwe, Jared

2007-01-01

There has been a remarkable improvement in access and rate of adoption of technology in higher education. Even so, reports indicate that faculty members are not integrating technology into instruction in ways that make a difference in student learning (Cuban, 2001; McCannon & Crews, 2000). To help faculty make informed decisions on student…

Evaluation of a potential nuclear fuel repository criticality: Lessons learned

Energy Technology Data Exchange (ETDEWEB)

Wilson, J.R.; Evans, D.

1995-10-01

This paper presents lessons learned from a Probabilistic Risk Assessment (PRA) of the potential for a criticality in a repository containing spent nuclear fuel with high enriched uranium. The insights gained consisted of remarkably detailed conclusions about design issues, failure mechanisms, frequencies and source terms for events up to 10,000 years in the future. Also discussed are the approaches taken by the analysts in presenting this very technical report to a nontechnical and possibly antagonistic audience.

Evaluation of a potential nuclear fuel repository criticality: Lessons learned

International Nuclear Information System (INIS)

Wilson, J.R.; Evans, D.

1995-01-01

This paper presents lessons learned from a Probabilistic Risk Assessment (PRA) of the potential for a criticality in a repository containing spent nuclear fuel with high enriched uranium. The insights gained consisted of remarkably detailed conclusions about design issues, failure mechanisms, frequencies and source terms for events up to 10,000 years in the future. Also discussed are the approaches taken by the analysts in presenting this very technical report to a nontechnical and possibly antagonistic audience

The more total cognitive load is reduced by cues, the better retention and transfer of multimedia learning: A meta-analysis and two meta-regression analyses.

Science.gov (United States)

Xie, Heping; Wang, Fuxing; Hao, Yanbin; Chen, Jiaxue; An, Jing; Wang, Yuxin; Liu, Huashan

2017-01-01

Cueing facilitates retention and transfer of multimedia learning. From the perspective of cognitive load theory (CLT), cueing has a positive effect on learning outcomes because of the reduction in total cognitive load and avoidance of cognitive overload. However, this has not been systematically evaluated. Moreover, what remains ambiguous is the direct relationship between the cue-related cognitive load and learning outcomes. A meta-analysis and two subsequent meta-regression analyses were conducted to explore these issues. Subjective total cognitive load (SCL) and scores on a retention test and transfer test were selected as dependent variables. Through a systematic literature search, 32 eligible articles encompassing 3,597 participants were included in the SCL-related meta-analysis. Among them, 25 articles containing 2,910 participants were included in the retention-related meta-analysis and the following retention-related meta-regression, while there were 29 articles containing 3,204 participants included in the transfer-related meta-analysis and the transfer-related meta-regression. The meta-analysis revealed a statistically significant cueing effect on subjective ratings of cognitive load (d = -0.11, 95% CI = [-0.19, -0.02], p < 0.05), retention performance (d = 0.27, 95% CI = [0.08, 0.46], p < 0.01), and transfer performance (d = 0.34, 95% CI = [0.12, 0.56], p < 0.01). The subsequent meta-regression analyses showed that dSCL for cueing significantly predicted dretention for cueing (β = -0.70, 95% CI = [-1.02, -0.38], p < 0.001), as well as dtransfer for cueing (β = -0.60, 95% CI = [-0.92, -0.28], p < 0.001). Thus in line with CLT, adding cues in multimedia materials can indeed reduce SCL and promote learning outcomes, and the more SCL is reduced by cues, the better retention and transfer of multimedia learning.

Increased water intake to reduce headache: learning from a critical appraisal.

Science.gov (United States)

Price, Amy; Burls, Amanda

2015-12-01

). 47% in the intervention (water) group self-reported improvement (6 > on a 10-point scale) against 25% in controls. Drinking water did not reduce headache days. The transparency from the author of this critically appraised paper enables others to use this study as a teaching tool and to learn from the shortcomings in the trial. The study was underpowered and contains methodological shortcomings. Participants were partially un-blinded during the trial increasing the risk for bias. Only the subjective measures are statistically significant and attrition was significant. The intervention is low risk and of negligible cost. A methodologically sound RCT is recommended to evaluate if the intervention has beneficial effects. © 2015 John Wiley & Sons, Ltd.

Out of School Learning Environments in Social Studies Education: A Phenomenological Research with Teacher Candidates

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Topçu, Ersin

2017-01-01

In this study, it was aimed to determine the remarks of teacher candidates on the place and importance of out of school learning environments in Social Studies education. Phenomenological method, which is one of the qualitative research designs, was used in this study. The work group of the study consists of 73 teacher candidates who conduct out…

Attention Cueing and Activity Equally Reduce False Alarm Rate in Visual-Auditory Associative Learning through Improving Memory.

Science.gov (United States)

Nikouei Mahani, Mohammad-Ali; Haghgoo, Hojjat Allah; Azizi, Solmaz; Nili Ahmadabadi, Majid

2016-01-01

In our daily life, we continually exploit already learned multisensory associations and form new ones when facing novel situations. Improving our associative learning results in higher cognitive capabilities. We experimentally and computationally studied the learning performance of healthy subjects in a visual-auditory sensory associative learning task across active learning, attention cueing learning, and passive learning modes. According to our results, the learning mode had no significant effect on learning association of congruent pairs. In addition, subjects' performance in learning congruent samples was not correlated with their vigilance score. Nevertheless, vigilance score was significantly correlated with the learning performance of the non-congruent pairs. Moreover, in the last block of the passive learning mode, subjects significantly made more mistakes in taking non-congruent pairs as associated and consciously reported lower confidence. These results indicate that attention and activity equally enhanced visual-auditory associative learning for non-congruent pairs, while false alarm rate in the passive learning mode did not decrease after the second block. We investigated the cause of higher false alarm rate in the passive learning mode by using a computational model, composed of a reinforcement learning module and a memory-decay module. The results suggest that the higher rate of memory decay is the source of making more mistakes and reporting lower confidence in non-congruent pairs in the passive learning mode.

Reducing Math Anxiety: Findings from Incorporating Service Learning into a Quantitative Reasoning Course at Seattle University

Directory of Open Access Journals (Sweden)

Allison Henrich

2011-07-01

Full Text Available How might one teach mathematics to math-anxious students and at the same time reduce their math anxiety? This paper describes what we found when we incorporated a service learning component into a quantitative reasoning course at Seattle University in Fall 2010 (20 students and Spring 2011 (28 students. The course is taken primarily by humanities majors, many of whom would not take a course in math if they didn’t need to satisfy the university’s core requirement. For the service learning component, each student met with and tutored children at local schools for 1-2 hours per week (total about 15 service hours, kept a weekly journal reflecting on the experience, and wrote a five-page final paper on the importance and reasonable expectations of mathematics literacy. The autobiographies, self-description at the beginning of the class, focus group interviews at the end of the term, journal entries, final essays, and student evaluations indicated that the students gained confidence in their mathematical abilities, a greater interest in mathematics, and a broader sense of the importance of math literacy in modern society. One notable finding was that students discovered that the act of manufacturing enthusiasm about math as a tool for tutoring the children made them more enthusiastic about math in their own courses.

The remarkable convergence of skull shape in crocodilians and toothed whales.

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McCurry, Matthew R; Evans, Alistair R; Fitzgerald, Erich M G; Adams, Justin W; Clausen, Philip D; McHenry, Colin R

2017-03-15

The striking resemblance of long-snouted aquatic mammals and reptiles has long been considered an example of morphological convergence, yet the true cause of this similarity remains untested. We addressed this deficit through three-dimensional morphometric analysis of the full diversity of crocodilian and toothed whale (Odontoceti) skull shapes. Our focus on biomechanically important aspects of shape allowed us to overcome difficulties involved in comparing mammals and reptiles, which have fundamental differences in the number and position of skull bones. We examined whether diet, habitat and prey size correlated with skull shape using phylogenetically informed statistical procedures. Crocodilians and toothed whales have a similar range of skull shapes, varying from extremely short and broad to extremely elongate. This spectrum of shapes represented more of the total variation in our dataset than between phylogenetic groups. The most elongate species (river dolphins and gharials) are extremely convergent in skull shape, clustering outside of the range of the other taxa. Our results suggest the remarkable convergence between long-snouted river dolphins and gharials is driven by diet rather than physical factors intrinsic to riverine environments. Despite diverging approximately 288 million years ago, crocodilians and odontocetes have evolved a remarkably similar morphological solution to feeding on similar prey. © 2017 The Author(s).

How to facilitate freshmen learning and support their transition to a university study environment

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Kangas, Jari; Rantanen, Elisa; Kettunen, Lauri

2017-11-01

Most freshmen enter universities with high expectations and with good motivation, but too many are driven into performing instead of true learning. The issues are not only related to the challenge of comprehending the substance, social and other factors have an impact as well. All these multifaceted needs should be accounted for to facilitate student learning. Learning is an individual process and remarkable improvement in the learning practices is possible, if proper actions are addressed early enough. We motivate and describe a study of the experience obtained from a set of tailor-made courses that were given alongside standard curriculum. The courses aimed to provide a 'safe community' to address the multifaceted needs. Such support was integrated into regular coursework where active learning techniques, e.g. interactive small groups were incorporated. To assess impact of the courses we employ the feedback obtained during the courses and longitudinal statistical data about students' success.

Perceptual learning modifies untrained pursuit eye movements.

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Szpiro, Sarit F A; Spering, Miriam; Carrasco, Marisa

2014-07-07

Perceptual learning improves detection and discrimination of relevant visual information in mature humans, revealing sensory plasticity. Whether visual perceptual learning affects motor responses is unknown. Here we implemented a protocol that enabled us to address this question. We tested a perceptual response (motion direction estimation, in which observers overestimate motion direction away from a reference) and a motor response (voluntary smooth pursuit eye movements). Perceptual training led to greater overestimation and, remarkably, it modified untrained smooth pursuit. In contrast, pursuit training did not affect overestimation in either pursuit or perception, even though observers in both training groups were exposed to the same stimuli for the same time period. A second experiment revealed that estimation training also improved discrimination, indicating that overestimation may optimize perceptual sensitivity. Hence, active perceptual training is necessary to alter perceptual responses, and an acquired change in perception suffices to modify pursuit, a motor response. © 2014 ARVO.

Learning difficulties or learning English difficulties? Additional language acquisition: an update for paediatricians.

Science.gov (United States)

Clifford, Vanessa; Rhodes, Anthea; Paxton, Georgia

2014-03-01

Australia is a diverse society: 26% of the population were born overseas, a further 20% have at least one parent born overseas and 19% speak a language other than English at home. Paediatricians are frequently involved in the assessment and management of non-English-speaking-background children with developmental delay, disability or learning issues. Despite the diversity of our patient population, information on how children learn additional or later languages is remarkably absent in paediatric training. An understanding of second language acquisition is essential to provide appropriate advice to this patient group. It takes a long time (5 years or more) for any student to develop academic competency in a second language, even a student who has received adequate prior schooling in their first language. Refugee students are doubly disadvantaged as they frequently have limited or interrupted prior schooling, and many are unable to read and write in their first language. We review the evidence on second language acquisition during childhood, describe support for English language learners within the Australian education system, consider refugee-background students as a special risk group and address common misconceptions about how children learn English as an additional language. © 2013 The Authors. Journal of Paediatrics and Child Health © 2013 Paediatrics and Child Health Division (Royal Australasian College of Physicians).

Closing remarks at the symposium in honour of Daniel Bellus. Pharmacenter, University of Basel, February 6, 2009.

Science.gov (United States)

Ganter, Camille

2010-01-01

In the Closing Remarks at the Symposium on 'Frontiers in Bioorganic Chemistry' (Friday, February 6, 2009, Pharmacenter, University of Basel) in honour of Daniel Bellus, his arrival in Zürich in fall 1967 and especially his postdoctoral work at the Laboratorium für Organische Chemie at the Eidgenössische Technische Hochschule (ETH) in Zürich throughout the year 1967/68 were mentioned. In his most remarkable paper (published in 1969 in Helv. Chim. Acta), the photochemistry of the alpha,beta-unsaturated cyclohexenones O-acetyl-testosterone and 10-methy-delta1,9-octalon-(2) is described in detail. Change of solvent leads to lowering or increasing of the n,pi*- and (pi,pi*)-triplet energies, resulting in a crossing of the two energy levels. Personal remarks on Daniel Bellus and warmest thanks to him, to Profs. Beat Ernst and Bernd Giese (the organizers of the symposium) and to all the speakers concluded this most special event.

Using spreadsheets to develop applied skills in a business math course: Student feedback and perceived learning

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Thomas Mays

2015-10-01

Full Text Available This paper describes the redesign of a business math course and its delivery in both face-to-face and online formats. Central to the redesigned course was the addition of applied spreadsheet exercises that served as both learning and summative assessment tools. Several other learning activities and assignments were integrated in the course to address diverse student learning styles and levels of math anxiety. Students were invited to complete a survey that asked them to rank course activities and assignments based on how well they helped the student learn course material. Open-ended items were also included in the survey. In the online course sections, students reported higher perceived learning from the use the spreadsheet-based application assignments, while face-to-face students preferred demonstrations. Qualitative remarks from the online students included numerous comments about the positive learning impact of the business application spreadsheet-based assignments, as well as the link between these assignments and what students considered the “real world.”

Case-based learning in an electronic learning environment

OpenAIRE

John Graham

2014-01-01

The benefits of e-learning have been widely established. These benefits include reduced costs, time savings, flexibility, accessible learning, and convenience. Due to such benefits, it has attracted business, industry, the professions, and of course educational institutes to begin using this platform either to supplement traditional teaching strategies or offer it as a complete substitute for them. The benefits of teaching with case studies are also well-recognized. Working with real world si...

Characterization of remarkable floods in France, a transdisciplinary approach applied on generalized floods of January 1910

Science.gov (United States)

Boudou, Martin; Lang, Michel; Vinet, Freddy; Coeur, Denis

2014-05-01

The 2007 Flood Directive promotes the integration and valorization of historical and significant floods in flood risk management (Flood Directive Text, chapter II, and article 4). Taking into account extreme past floods analysis seems necessary in the mitigation process of vulnerability face to flooding risk. In France, this aspect of the Directive was carried out through the elaboration of Preliminary Flood Risk Assessment (PFRA) and the establishment of a 2000 floods list. From this first list, a sample of 176 floods, considered as remarkable has been selected. These floods were compiled in discussion with local authorities in charge of flood management (Lang et al., 2012) and have to be integrated in priority in local risk management policies. However, a consideration emerges about this classification: how a remarkable flood can be defined? According which criteria can it be considered as remarkable? To answer these questions, a methodology has been established by building an evaluation grid of remarkable floods in France. The primary objective of this grid is to analyze the remarkable flood's characteristics (hydrological and meteorological characteristics, sociological- political and economic impacts), and secondly to propose a classification of significant floods selected in the 2011 PFRA. To elaborate this evaluation grid, several issues had to be taken into account. First, the objective is to allow the comparison of events from various periods. These temporal disparities include the integration of various kinds of data and point out the importance of historical hydrology. It is possible to evaluate accurately the characteristics of recent floods by interpreting quantitative data (for example hydrological records. However, for floods that occurred before the 1960's it is necessary resorting to qualitative information such as written sources is necessary (Coeur, Lang, 2008). In a second part the evaluation grid requires equitable criteria in order not to

A Robust Cooperated Control Method with Reinforcement Learning and Adaptive H∞ Control

Science.gov (United States)

Obayashi, Masanao; Uchiyama, Shogo; Kuremoto, Takashi; Kobayashi, Kunikazu

This study proposes a robust cooperated control method combining reinforcement learning with robust control to control the system. A remarkable characteristic of the reinforcement learning is that it doesn't require model formula, however, it doesn't guarantee the stability of the system. On the other hand, robust control system guarantees stability and robustness, however, it requires model formula. We employ both the actor-critic method which is a kind of reinforcement learning with minimal amount of computation to control continuous valued actions and the traditional robust control, that is, H∞ control. The proposed system was compared method with the conventional control method, that is, the actor-critic only used, through the computer simulation of controlling the angle and the position of a crane system, and the simulation result showed the effectiveness of the proposed method.

Writing and querying MapReduce views in CouchDB

CERN Document Server

Holt, Bradley

2011-01-01

If you want to use CouchDB to support real-world applications, you'll need to create MapReduce views that let you query this document-oriented database for meaningful data. With this short and concise ebook, you'll learn how to create a variety of MapReduce views to help you query and aggregate data in CouchDB's large, distributed datasets. You'll get step-by-step instructions and lots of sample code to create and explore several MapReduce views through the course of the book, using an example database you construct. To work with these different views, you'll learn how to use the Futon web a

Remarks on Prof. Michał Kokowski’s comment about the studies into the life of Prof. Jan Czochralski (in Polish

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Paweł E. TOMASZEWSKI

2015-12-01

Full Text Available Remarks on the critical comments regarding the contents of the paper published after the presentation delivered by the biographer of Prof. Jan Czochralski. Unfortunately, Prof. Kokowski used an incorrect historical approach to such a short paper. The remarks are presented in four main points.

A Perfect Ecosystem for Learning? Modern Thoughts for Organizing Higher Education

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Pasi Juvonen

2018-01-01

Full Text Available The background of the article lies in South Eastern Finland, in Lappeenranta, where an active University campus has attracted a group of ICT startups as well as SME’s in the field to collaboration. The novel education approach also has another remarkable role as a developer and source of innovation. An experimental development ecosystem (EDE, where learning of knowledge, skills and character are combined, is presented in the article. Also future paths of the EDE are discussed. Companies in the ICT field worldwide are in constant need of competent experts who are ready to adopt the new tools and, at the same time, have an entrepreneurial mindset. We argue that inspiring students to learn through appropriate learning methods and providing them with a modern learning environment comes first. ICT tools, applications and systems to support learning objectives come second. The model presented in the article has been studied for some years as action research. The learning methods that have been found beneficial in IT and marketing bachelor education have been spread to other bachelor and master study programs as well. Results from the data show that students who study as team entrepreneurs have learned content knowledge, meta-skills and reflection skills via the learner-centric methods used in EDE. They have also been inspired to employ new ICT tools and applications to support their learning and project work.

Biomimetic approach to tacit learning based on compound control.

Science.gov (United States)

Shimoda, Shingo; Kimura, Hidenori

2010-02-01

The remarkable capability of living organisms to adapt to unknown environments is due to learning mechanisms that are totally different from the current artificial machine-learning paradigm. Computational media composed of identical elements that have simple activity rules play a major role in biological control, such as the activities of neurons in brains and the molecular interactions in intracellular control. As a result of integrations of the individual activities of the computational media, new behavioral patterns emerge to adapt to changing environments. We previously implemented this feature of biological controls in a form of machine learning and succeeded to realize bipedal walking without the robot model or trajectory planning. Despite the success of bipedal walking, it was a puzzle as to why the individual activities of the computational media could achieve the global behavior. In this paper, we answer this question by taking a statistical approach that connects the individual activities of computational media to global network behaviors. We show that the individual activities can generate optimized behaviors from a particular global viewpoint, i.e., autonomous rhythm generation and learning of balanced postures, without using global performance indices.

Experience in a Climate Microworld: Influence of Surface and Structure Learning, Problem Difficulty, and Decision Aids in Reducing Stock-Flow Misconceptions

OpenAIRE

Medha Kumar; Varun Dutt; Varun Dutt

2018-01-01

Research shows that people’s wait-and-see preferences for actions against climate change are a result of several factors, including cognitive misconceptions. The use of simulation tools could help reduce these misconceptions concerning Earth’s climate. However, it is still unclear whether the learning in these tools is of the problem’s surface features (dimensions of emissions and absorptions and cover-story used) or of the problem’s structural features (how emissions and absorptions cause a ...

Programming MapReduce with Scalding

CERN Document Server

Chalkiopoulos, Antonios

2014-01-01

This book is an easy-to-understand, practical guide to designing, testing, and implementing complex MapReduce applications in Scala using the Scalding framework. It is packed with examples featuring log-processing, ad-targeting, and machine learning. This book is for developers who are willing to discover how to effectively develop MapReduce applications. Prior knowledge of Hadoop or Scala is not required; however, investing some time on those topics would certainly be beneficial.

Experience in a Climate Microworld: Influence of Surface and Structure Learning, Problem Difficulty, and Decision Aids in Reducing Stock-Flow Misconceptions

Directory of Open Access Journals (Sweden)

Medha Kumar

2018-03-01

Full Text Available Research shows that people’s wait-and-see preferences for actions against climate change are a result of several factors, including cognitive misconceptions. The use of simulation tools could help reduce these misconceptions concerning Earth’s climate. However, it is still unclear whether the learning in these tools is of the problem’s surface features (dimensions of emissions and absorptions and cover-story used or of the problem’s structural features (how emissions and absorptions cause a change in CO2 concentration under different CO2 concentration scenarios. Also, little is known on how problem’s difficulty in these tools (the shape of CO2 concentration trajectory, as well as the use of these tools as a decision aid influences performance. The primary objective of this paper was to investigate how learning about Earth’s climate via simulation tools is influenced by problem’s surface and structural features, problem’s difficulty, and decision aids. In experiment 1, we tested the influence of problem’s surface and structural features in a simulation called Dynamic Climate Change Simulator (DCCS on subsequent performance in a paper-and-pencil Climate Stabilization (CS task (N = 100 across four between-subject conditions. In experiment 2, we tested the effects of problem’s difficulty in DCCS on subsequent performance in the CS task (N = 90 across three between-subject conditions. In experiment 3, we tested the influence of DCCS as a decision aid on subsequent performance in the CS task (N = 60 across two between-subject conditions. Results revealed a significant reduction in people’s misconceptions in the CS task after performing in DCCS compared to when performing in CS task in the absence of DCCS. The decrease in misconceptions in the CS task was similar for both problems’ surface and structural features, showing both structure and surface learning in DCCS. However, the proportion of misconceptions was similar across

Deep learning aided decision support for pulmonary nodules diagnosing: a review.

Science.gov (United States)

Yang, Yixin; Feng, Xiaoyi; Chi, Wenhao; Li, Zhengyang; Duan, Wenzhe; Liu, Haiping; Liang, Wenhua; Wang, Wei; Chen, Ping; He, Jianxing; Liu, Bo

2018-04-01

Deep learning techniques have recently emerged as promising decision supporting approaches to automatically analyze medical images for different clinical diagnosing purposes. Diagnosing of pulmonary nodules by using computer-assisted diagnosing has received considerable theoretical, computational, and empirical research work, and considerable methods have been developed for detection and classification of pulmonary nodules on different formats of images including chest radiographs, computed tomography (CT), and positron emission tomography in the past five decades. The recent remarkable and significant progress in deep learning for pulmonary nodules achieved in both academia and the industry has demonstrated that deep learning techniques seem to be promising alternative decision support schemes to effectively tackle the central issues in pulmonary nodules diagnosing, including feature extraction, nodule detection, false-positive reduction, and benign-malignant classification for the huge volume of chest scan data. The main goal of this investigation is to provide a comprehensive state-of-the-art review of the deep learning aided decision support for pulmonary nodules diagnosing. As far as the authors know, this is the first time that a review is devoted exclusively to deep learning techniques for pulmonary nodules diagnosing.

Broiler chickens can benefit from machine learning: support vector machine analysis of observational epidemiological data.

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Hepworth, Philip J; Nefedov, Alexey V; Muchnik, Ilya B; Morgan, Kenton L

2012-08-07

Machine-learning algorithms pervade our daily lives. In epidemiology, supervised machine learning has the potential for classification, diagnosis and risk factor identification. Here, we report the use of support vector machine learning to identify the features associated with hock burn on commercial broiler farms, using routinely collected farm management data. These data lend themselves to analysis using machine-learning techniques. Hock burn, dermatitis of the skin over the hock, is an important indicator of broiler health and welfare. Remarkably, this classifier can predict the occurrence of high hock burn prevalence with accuracy of 0.78 on unseen data, as measured by the area under the receiver operating characteristic curve. We also compare the results with those obtained by standard multi-variable logistic regression and suggest that this technique provides new insights into the data. This novel application of a machine-learning algorithm, embedded in poultry management systems could offer significant improvements in broiler health and welfare worldwide.

The Social Interplay of Disciplinarity and Interdisciplinarity. Some Introductory Remarks

Directory of Open Access Journals (Sweden)

Reinhold Hedtke

2006-12-01

Full Text Available Social Science Education as a subject field in schools is an intrinsic pluridisciplinary feature, whatever disciplines are included, however it may be organised and wherever it may be institutionalised. Civic education, economic education, social education and historical education each comprise several academic disciplines even if they are thought to be completely independent subjects. From the start on, disciplinarity and interdisciplinarity are on the agenda for any subject related to social science education and are one of its main problems. For these introductory remarks interdisciplinarity can be simply defined as relating two or more academic disciplines or school subjects to each other if this is done in a purposeful, systematic, explicit and reflective way. The overarching goal is to improve education that is to enhance students' understandings of the worlds and their abilities to act within and towards them. A relationship between disciplines or subjects which misses one or more of the four characteristics can be called pluridisciplinary or multidisciplinary (cf. Audigier 2006. In the following I first want to discuss some aspects of disciplinarity and interdisciplinarity at schools and at universities and the weakness of interdisciplinarity. I sketch some social science based ideas on the interrelationship between the subject structure of the academic world and the world of schools (3. and of some tendency to commonalities or even unification of social sciences and related competencies (4.. I conclude with some remarks on different kinds of knowledge (5.. Last but not least, I'll give an overview on the papers in this issue of the Journal of Social Science Education (6..

Trends in extreme learning machines: a review.

Science.gov (United States)

Huang, Gao; Huang, Guang-Bin; Song, Shiji; You, Keyou

2015-01-01

Extreme learning machine (ELM) has gained increasing interest from various research fields recently. In this review, we aim to report the current state of the theoretical research and practical advances on this subject. We first give an overview of ELM from the theoretical perspective, including the interpolation theory, universal approximation capability, and generalization ability. Then we focus on the various improvements made to ELM which further improve its stability, sparsity and accuracy under general or specific conditions. Apart from classification and regression, ELM has recently been extended for clustering, feature selection, representational learning and many other learning tasks. These newly emerging algorithms greatly expand the applications of ELM. From implementation aspect, hardware implementation and parallel computation techniques have substantially sped up the training of ELM, making it feasible for big data processing and real-time reasoning. Due to its remarkable efficiency, simplicity, and impressive generalization performance, ELM have been applied in a variety of domains, such as biomedical engineering, computer vision, system identification, and control and robotics. In this review, we try to provide a comprehensive view of these advances in ELM together with its future perspectives.

Are baboons learning "orthographic" representations? Probably not.

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Maja Linke

Full Text Available The ability of Baboons (papio papio to distinguish between English words and nonwords has been modeled using a deep learning convolutional network model that simulates a ventral pathway in which lexical representations of different granularity develop. However, given that pigeons (columba livia, whose brain morphology is drastically different, can also be trained to distinguish between English words and nonwords, it appears that a less species-specific learning algorithm may be required to explain this behavior. Accordingly, we examined whether the learning model of Rescorla and Wagner, which has proved to be amazingly fruitful in understanding animal and human learning could account for these data. We show that a discrimination learning network using gradient orientation features as input units and word and nonword units as outputs succeeds in predicting baboon lexical decision behavior-including key lexical similarity effects and the ups and downs in accuracy as learning unfolds-with surprising precision. The models performance, in which words are not explicitly represented, is remarkable because it is usually assumed that lexicality decisions, including the decisions made by baboons and pigeons, are mediated by explicit lexical representations. By contrast, our results suggest that in learning to perform lexical decision tasks, baboons and pigeons do not construct a hierarchy of lexical units. Rather, they make optimal use of low-level information obtained through the massively parallel processing of gradient orientation features. Accordingly, we suggest that reading in humans first involves initially learning a high-level system building on letter representations acquired from explicit instruction in literacy, which is then integrated into a conventionalized oral communication system, and that like the latter, fluent reading involves the massively parallel processing of the low-level features encoding semantic contrasts.

Human-level control through deep reinforcement learning

Science.gov (United States)

Mnih, Volodymyr; Kavukcuoglu, Koray; Silver, David; Rusu, Andrei A.; Veness, Joel; Bellemare, Marc G.; Graves, Alex; Riedmiller, Martin; Fidjeland, Andreas K.; Ostrovski, Georg; Petersen, Stig; Beattie, Charles; Sadik, Amir; Antonoglou, Ioannis; King, Helen; Kumaran, Dharshan; Wierstra, Daan; Legg, Shane; Hassabis, Demis

2015-02-01

The theory of reinforcement learning provides a normative account, deeply rooted in psychological and neuroscientific perspectives on animal behaviour, of how agents may optimize their control of an environment. To use reinforcement learning successfully in situations approaching real-world complexity, however, agents are confronted with a difficult task: they must derive efficient representations of the environment from high-dimensional sensory inputs, and use these to generalize past experience to new situations. Remarkably, humans and other animals seem to solve this problem through a harmonious combination of reinforcement learning and hierarchical sensory processing systems, the former evidenced by a wealth of neural data revealing notable parallels between the phasic signals emitted by dopaminergic neurons and temporal difference reinforcement learning algorithms. While reinforcement learning agents have achieved some successes in a variety of domains, their applicability has previously been limited to domains in which useful features can be handcrafted, or to domains with fully observed, low-dimensional state spaces. Here we use recent advances in training deep neural networks to develop a novel artificial agent, termed a deep Q-network, that can learn successful policies directly from high-dimensional sensory inputs using end-to-end reinforcement learning. We tested this agent on the challenging domain of classic Atari 2600 games. We demonstrate that the deep Q-network agent, receiving only the pixels and the game score as inputs, was able to surpass the performance of all previous algorithms and achieve a level comparable to that of a professional human games tester across a set of 49 games, using the same algorithm, network architecture and hyperparameters. This work bridges the divide between high-dimensional sensory inputs and actions, resulting in the first artificial agent that is capable of learning to excel at a diverse array of challenging tasks.

Human-level control through deep reinforcement learning.

Science.gov (United States)

Mnih, Volodymyr; Kavukcuoglu, Koray; Silver, David; Rusu, Andrei A; Veness, Joel; Bellemare, Marc G; Graves, Alex; Riedmiller, Martin; Fidjeland, Andreas K; Ostrovski, Georg; Petersen, Stig; Beattie, Charles; Sadik, Amir; Antonoglou, Ioannis; King, Helen; Kumaran, Dharshan; Wierstra, Daan; Legg, Shane; Hassabis, Demis

2015-02-26

The theory of reinforcement learning provides a normative account, deeply rooted in psychological and neuroscientific perspectives on animal behaviour, of how agents may optimize their control of an environment. To use reinforcement learning successfully in situations approaching real-world complexity, however, agents are confronted with a difficult task: they must derive efficient representations of the environment from high-dimensional sensory inputs, and use these to generalize past experience to new situations. Remarkably, humans and other animals seem to solve this problem through a harmonious combination of reinforcement learning and hierarchical sensory processing systems, the former evidenced by a wealth of neural data revealing notable parallels between the phasic signals emitted by dopaminergic neurons and temporal difference reinforcement learning algorithms. While reinforcement learning agents have achieved some successes in a variety of domains, their applicability has previously been limited to domains in which useful features can be handcrafted, or to domains with fully observed, low-dimensional state spaces. Here we use recent advances in training deep neural networks to develop a novel artificial agent, termed a deep Q-network, that can learn successful policies directly from high-dimensional sensory inputs using end-to-end reinforcement learning. We tested this agent on the challenging domain of classic Atari 2600 games. We demonstrate that the deep Q-network agent, receiving only the pixels and the game score as inputs, was able to surpass the performance of all previous algorithms and achieve a level comparable to that of a professional human games tester across a set of 49 games, using the same algorithm, network architecture and hyperparameters. This work bridges the divide between high-dimensional sensory inputs and actions, resulting in the first artificial agent that is capable of learning to excel at a diverse array of challenging tasks.

A REMARKABLE CLADONIACEAE FLORA AT SUBANDEAN REGION IN CHÁMEZA (CASANARE, COLOMBIA

Directory of Open Access Journals (Sweden)

LADY JOHANNA HERRERA VARGAS

2014-12-01

Full Text Available A remarkable Cladoniaceae flora was discovered in the subandean region of Chámeza, ( Casanare, Colombia at 1200 meters above sea level. Four species of the genus Cladonia (Cladoniaceae, Lichenized Fungi are new records for Colombia : Cladonia macilentoides, C. scabriuscula, C. sipmanii and C. subdelicatula. This shows the importance of increasing diversity studies at mid elevations where suitable habitats for species of Cladonia occur.

Electroweak interactions at the SSC: introductory remarks multi W and Z production

International Nuclear Information System (INIS)

Gaillard, M.K.

1984-03-01

This report is a partial summary of the work of the electroweak interaction study group at the Workshop on p anti p Options for the Super Collider, University of Chicago, February 13-17, 1984. Included are general remarks concerning the topics studied and a discussion of multi intermediate vector boson production as a probe of the gauge and scalar sectors of the electroweak theory

Applying Collaborative Learning and Quality Improvement to Public Health: Lessons from the Collaborative Improvement and Innovation Network (CoIIN) to Reduce Infant Mortality.

Science.gov (United States)

Ghandour, Reem M; Flaherty, Katherine; Hirai, Ashley; Lee, Vanessa; Walker, Deborah Klein; Lu, Michael C

2017-06-01

Infant mortality remains a significant public health problem in the U.S. The Collaborative Improvement & Innovation Network (CoIIN) model is an innovative approach, using the science of quality improvement and collaborative learning, which was applied across 13 Southern states in Public Health Regions IV and VI to reduce infant mortality and improve birth outcomes. We provide an in-depth discussion of the history, development, implementation, and adaptation of the model based on the experience of the original CoIIN organizers and participants. In addition to the political genesis and functional components of the initiative, 8 key lessons related to staffing, planning, and implementing future CoIINs are described in detail. This paper reports the findings from a process evaluation of the model. Data on the states' progress toward reducing infant mortality and improving birth outcomes were collected through a survey in the final months of a 24-month implementation period, as well as through ongoing team communications. The peer-to-peer exchange and platform for collaborative learning, as well as the sharing of data across the states, were major strengths and form the foundation for future CoIIN efforts. A lasting legacy of the initiative is the unique application and sharing of provisional "real time" data to inform "real time" decision-making. The CoIIN model of collaborative learning, QI, and innovation offers a promising approach to strengthening partnerships within and across states, bolstering data systems to inform and track progress more rapidly, and ultimately accelerating improvement toward healthier communities, States, and the Nation as a whole.

Concluding remarks: Faraday Discussion on chemistry in the urban atmosphere.

Science.gov (United States)

Jimenez, Jose L

2016-07-18

This article summarises the Concluding remarks from the Faraday Discussion on Chemistry in the Urban Atmosphere. The following themes are addressed: (a) new results that inform our understanding of the evolving sources and composition of the urban atmosphere ("News"); (b) results that identify gaps in our understanding that necessitate further work ("Gaps"); (c) the emerging instrumentation revolution and some of the challenges that it brings; (d) the structural issues of insufficient support for the analysis of field campaigns; and (e) some important areas that were missing from this Faraday Discussion and that should receive an increasing focus in the future.

Effectiveness of counteraggression strategies in reducing interactive aggression by males.

Science.gov (United States)

Kimble, C E; Fitz, D; Onorad, J R

1977-04-01

Studies on techniques of reducing aggression have typically examined passive, matching, and punitive strategies of counteraggression and have been remarkably inconsistent in their findings. This research was designed to resolve the contradictory results by reconceptuallzing the strategies in terms of counteraggression/aggression (cA/A) ratios. We predicted that the norm of reciprocity and the tendency to exploit weakness would make a cA/A ratio of less than but close to 1.0 (matching) most effective in reducing aggression. Ten cA/A ratios were used. One hundred male subjects set punishment level set by their opponent (a confederate) on 25 trials, and, on 13 losing trials, received punishment. The most effective cA/A ratios for reducing aggression were the lowest ones. Lower cA/A ratios reduced aggression and ratios greater than 1.0 increased aggresion. Contrary to the results of previous studies, the matching strategy was ineffective in reducing aggresion.

Developments in Interpreting Learning Curves and Applications to Energy Technology Policy

International Nuclear Information System (INIS)

Van der Zwaan, B.C.C.; Wene, C.O.

2011-01-01

The book 'Learning Curves: Theory, Models, and Applications' first draws a learning map that shows where learning is involved within organizations, then examines how it can be sustained, perfected, and accelerated. The book reviews empirical findings in the literature in terms of different sources for learning and partial assessments of the steps that make up the actual learning process inside the learning curve. Chapter 23 on 'Developments in Interpreting Learning Curves and Applications to Energy Technology Policy' is written by Bob van der Zwaan and Clas-Otto Wene. In this chapter they provide some interpretations of experience and learning curves starting from three different theoretical platforms. These interpretations are aimed at explaining learning rates for different energy technologies. The ultimate purpose is to find the role that experience and learning curves can legitimately play in designing efficient government deployment programs and in analyzing the implications of different energy scenarios. The 'Component Learning' section summarizes recent work by the authors that focuses on the disaggregation of technologies in their respective components and argues that traditional learning for overall technology should perhaps be replaced by a phenomenology that recognizes learning for individual components. The 'Learning and Time' section presents an approach that departs more strongly from the conventional learning curve methodology, by suggesting that exponential growth and progress may be the deeper underlying processes behind observed learning-by-doing. Contrary to this view, the cybernetic approach presented in the 'Cybernetic Approach' section sees learning curves as expressing a fundamental property of organizations in competitive markets and applies the findings from second order cybernetics to calculate the learning rates for operationally closed systems. All three interpretations find empirical support. The 'Conclusions' section summarizes the

Developments in Interpreting Learning Curves and Applications to Energy Technology Policy

Energy Technology Data Exchange (ETDEWEB)

Van der Zwaan, B.C.C. [Energy research Centre of the Netherlands, ECN Policy Studies, Petten (Netherlands); Wene, C.O. [Wenergy, Lund (Sweden)

2011-06-15

The book 'Learning Curves: Theory, Models, and Applications' first draws a learning map that shows where learning is involved within organizations, then examines how it can be sustained, perfected, and accelerated. The book reviews empirical findings in the literature in terms of different sources for learning and partial assessments of the steps that make up the actual learning process inside the learning curve. Chapter 23 on 'Developments in Interpreting Learning Curves and Applications to Energy Technology Policy' is written by Bob van der Zwaan and Clas-Otto Wene. In this chapter they provide some interpretations of experience and learning curves starting from three different theoretical platforms. These interpretations are aimed at explaining learning rates for different energy technologies. The ultimate purpose is to find the role that experience and learning curves can legitimately play in designing efficient government deployment programs and in analyzing the implications of different energy scenarios. The 'Component Learning' section summarizes recent work by the authors that focuses on the disaggregation of technologies in their respective components and argues that traditional learning for overall technology should perhaps be replaced by a phenomenology that recognizes learning for individual components. The 'Learning and Time' section presents an approach that departs more strongly from the conventional learning curve methodology, by suggesting that exponential growth and progress may be the deeper underlying processes behind observed learning-by-doing. Contrary to this view, the cybernetic approach presented in the 'Cybernetic Approach' section sees learning curves as expressing a fundamental property of organizations in competitive markets and applies the findings from second order cybernetics to calculate the learning rates for operationally closed systems. All three interpretations find empirical

In quest of a relativistic constituent quark model - some constructive remarks

International Nuclear Information System (INIS)

Hofsaess, T.; Schierholz, G.

1978-01-01

The set-up of a relativistic constituent quark model in four dimensions is one of the outstanding problems in particle physics. For the time being this involves a great deal of model building which, very probably, will not change in the near future. In this paper we shall offer some general remarks which might help putting such models into shape. Most of the earlier attempts are found controversial. In particular, a conventional quark constituent interpretation could not be recovered. (orig.) [de

Using Expectancy Value Theory as a Framework to Reduce Student Resistance to Active Learning: A Proof of Concept.

Science.gov (United States)

Cooper, Katelyn M; Ashley, Michael; Brownell, Sara E

2017-01-01

There has been a national movement to transition college science courses from passive lectures to active learning environments. Active learning has been shown to be a more effective way for students to learn, yet there is concern that some students are resistant to active learning approaches. Although there is much discussion about student resistance to active learning, few studies have explored this topic. Furthermore, a limited number of studies have applied theoretical frameworks to student engagement in active learning. We propose using a theoretical lens of expectancy value theory to understand student resistance to active learning. In this study, we examined student perceptions of active learning after participating in 40 hours of active learning. We used the principal components of expectancy value theory to probe student experience in active learning: student perceived self-efficacy in active learning, value of active learning, and potential cost of participating in active learning. We found that students showed positive changes in the components of expectancy value theory and reported high levels of engagement in active learning, which provide proof of concept that expectancy value theory can be used to boost student perceptions of active learning and their engagement in active learning classrooms. From these findings, we have built a theoretical framework of expectancy value theory applied to active learning.

How attention can create synaptic tags for the learning of working memories in sequential tasks.

Directory of Open Access Journals (Sweden)

Jaldert O Rombouts

2015-03-01

Full Text Available Intelligence is our ability to learn appropriate responses to new stimuli and situations. Neurons in association cortex are thought to be essential for this ability. During learning these neurons become tuned to relevant features and start to represent them with persistent activity during memory delays. This learning process is not well understood. Here we develop a biologically plausible learning scheme that explains how trial-and-error learning induces neuronal selectivity and working memory representations for task-relevant information. We propose that the response selection stage sends attentional feedback signals to earlier processing levels, forming synaptic tags at those connections responsible for the stimulus-response mapping. Globally released neuromodulators then interact with tagged synapses to determine their plasticity. The resulting learning rule endows neural networks with the capacity to create new working memory representations of task relevant information as persistent activity. It is remarkably generic: it explains how association neurons learn to store task-relevant information for linear as well as non-linear stimulus-response mappings, how they become tuned to category boundaries or analog variables, depending on the task demands, and how they learn to integrate probabilistic evidence for perceptual decisions.

A Learning Architecture: How School Leaders Can Design for Learning Social Justice

Science.gov (United States)

Scanlan, Martin

2013-01-01

Purpose: The field of socially just educational leadership focuses on reducing inequities within schools. The purpose of this article is to illustrate how one strand of social learning theory, communities of practice, can serve as a powerful tool for analyzing learning within a school ostensibly pursuing social justice. The author employs a core…

A Direct-Learning Approach to Acquiring a Bimanual Tapping Skill.

Science.gov (United States)

Michaels, Claire F; Gomes, Thábata V B; Benda, Rodolfo N

2017-01-01

The theory of direct learning (D. M. Jacobs & C. F. Michaels, 2007 ) has proven useful in understanding improvement in perception and exploratory action. Here the authors assess its usefulness for understanding the learning of a motor skill, bimanual tapping at a difficult phase relation. Twenty participants attempted to learn to tap with 2 index fingers at 2 Hz with a phase lag of 90° (i.e., with a right-right period of 500 ms and a right-left period of 125 ms). There were 30 trials, each with 50 tapping cycles. Computer-screen feedback informed of errors in both period and phase for each pair of taps. Participants differed dramatically in their success. Learning was assessed by identifying the succession of attractors capturing tapping over the experiment. A few participants' attractors migrated from antiphase to 90° with an appropriate period; others became attracted to a fixed right-left interval, rather than phase, with or without attraction to period. Changes in attractor loci were explained with mixed success by direct learning, inviting elaboration of the theory. The transition to interval attractors was understood as a change in intention, and was remarkable for its indifference to typical bimanual interactions.

Leveraging knowledge engineering and machine learning for microbial bio-manufacturing.

Science.gov (United States)

Oyetunde, Tolutola; Bao, Forrest Sheng; Chen, Jiung-Wen; Martin, Hector Garcia; Tang, Yinjie J

2018-05-03

Genome scale modeling (GSM) predicts the performance of microbial workhorses and helps identify beneficial gene targets. GSM integrated with intracellular flux dynamics, omics, and thermodynamics have shown remarkable progress in both elucidating complex cellular phenomena and computational strain design (CSD). Nonetheless, these models still show high uncertainty due to a poor understanding of innate pathway regulations, metabolic burdens, and other factors (such as stress tolerance and metabolite channeling). Besides, the engineered hosts may have genetic mutations or non-genetic variations in bioreactor conditions and thus CSD rarely foresees fermentation rate and titer. Metabolic models play important role in design-build-test-learn cycles for strain improvement, and machine learning (ML) may provide a viable complementary approach for driving strain design and deciphering cellular processes. In order to develop quality ML models, knowledge engineering leverages and standardizes the wealth of information in literature (e.g., genomic/phenomic data, synthetic biology strategies, and bioprocess variables). Data driven frameworks can offer new constraints for mechanistic models to describe cellular regulations, to design pathways, to search gene targets, and to estimate fermentation titer/rate/yield under specified growth conditions (e.g., mixing, nutrients, and O 2 ). This review highlights the scope of information collections, database constructions, and machine learning techniques (such as deep learning and transfer learning), which may facilitate "Learn and Design" for strain development. Copyright © 2018. Published by Elsevier Inc.

Interference in Ballistic Motor Learning: Specificity and Role of Sensory Error Signals

Science.gov (United States)

Lundbye-Jensen, Jesper; Petersen, Tue Hvass; Rothwell, John C.; Nielsen, Jens Bo

2011-01-01

Humans are capable of learning numerous motor skills, but newly acquired skills may be abolished by subsequent learning. Here we ask what factors determine whether interference occurs in motor learning. We speculated that interference requires competing processes of synaptic plasticity in overlapping circuits and predicted specificity. To test this, subjects learned a ballistic motor task. Interference was observed following subsequent learning of an accuracy-tracking task, but only if the competing task involved the same muscles and movement direction. Interference was not observed from a non-learning task suggesting that interference requires competing learning. Subsequent learning of the competing task 4 h after initial learning did not cause interference suggesting disruption of early motor memory consolidation as one possible mechanism underlying interference. Repeated transcranial magnetic stimulation (rTMS) of corticospinal motor output at intensities below movement threshold did not cause interference, whereas suprathreshold rTMS evoking motor responses and (re)afferent activation did. Finally, the experiments revealed that suprathreshold repetitive electrical stimulation of the agonist (but not antagonist) peripheral nerve caused interference. The present study is, to our knowledge, the first to demonstrate that peripheral nerve stimulation may cause interference. The finding underscores the importance of sensory feedback as error signals in motor learning. We conclude that interference requires competing plasticity in overlapping circuits. Interference is remarkably specific for circuits involved in a specific movement and it may relate to sensory error signals. PMID:21408054

Global checklist of species of Grania (Clitellata: Enchytraeidae with remarks on their geographic distribution

Directory of Open Access Journals (Sweden)

Alessandro Prantoni

2017-12-01

Full Text Available A checklist of all currently accepted species of Grania Southern, 1913 (Annelida, Clitellata, Enchytraeidae is presented. The genus is widespread over the world and comprises 81 species described to date. Remarks on their geographical distribution, habitat, synonymies and museum catalogue numbers are provided.

Complex population response of dorsal putamen neurons predicts the ability to learn.

Science.gov (United States)

Laquitaine, Steeve; Piron, Camille; Abellanas, David; Loewenstein, Yonatan; Boraud, Thomas

2013-01-01

Day-to-day variability in performance is a common experience. We investigated its neural correlate by studying learning behavior of monkeys in a two-alternative forced choice task, the two-armed bandit task. We found substantial session-to-session variability in the monkeys' learning behavior. Recording the activity of single dorsal putamen neurons we uncovered a dual function of this structure. It has been previously shown that a population of neurons in the DLP exhibits firing activity sensitive to the reward value of chosen actions. Here, we identify putative medium spiny neurons in the dorsal putamen that are cue-selective and whose activity builds up with learning. Remarkably we show that session-to-session changes in the size of this population and in the intensity with which this population encodes cue-selectivity is correlated with session-to-session changes in the ability to learn the task. Moreover, at the population level, dorsal putamen activity in the very beginning of the session is correlated with the performance at the end of the session, thus predicting whether the monkey will have a "good" or "bad" learning day. These results provide important insights on the neural basis of inter-temporal performance variability.

Pileup Mitigation with Machine Learning (PUMML)

Science.gov (United States)

Komiske, Patrick T.; Metodiev, Eric M.; Nachman, Benjamin; Schwartz, Matthew D.

2017-12-01

Pileup involves the contamination of the energy distribution arising from the primary collision of interest (leading vertex) by radiation from soft collisions (pileup). We develop a new technique for removing this contamination using machine learning and convolutional neural networks. The network takes as input the energy distribution of charged leading vertex particles, charged pileup particles, and all neutral particles and outputs the energy distribution of particles coming from leading vertex alone. The PUMML algorithm performs remarkably well at eliminating pileup distortion on a wide range of simple and complex jet observables. We test the robustness of the algorithm in a number of ways and discuss how the network can be trained directly on data.

Reducing Retroactive Interference through the Use of Different Encoding Techniques: An Exploration of Pre-Test/Post-Test Analyses

Science.gov (United States)

Cumming, John M.; De Miranda, Michael A.

2012-01-01

Retroactive interference (RI) in list learning occurs when the learning of a second list of words interferes with the recall of the first learned list. Having the lists be thematically different can reduce retroactive interference within list learning; however, this study demonstrates how RI can be reduced when the lists contain similar words.…

Closing remarks at 4th NuFact '02 workshop, London, England, 6 July 2002

International Nuclear Information System (INIS)

Sessler, Andrew M.

2003-01-01

A brief survey is given of actual R and D activities around the world. Following that, various conceptual developments significant to factories are reviewed. Then we turn to the costs of a factory. We discuss the present budgetary woes throughout the world and end with some closing remarks

Remarks on the high-energy behavior of string scattering amplitudes in warped spacetimes. II

International Nuclear Information System (INIS)

Andreev, Oleg

2005-01-01

We study the Regge limit of string amplitudes within the model of Polchinski-Strassler for string scattering in warped spacetimes. We also present some numerical estimations of the Regge slopes and intercepts. It is quite remarkable that the real values of those are inside a range of ours

Central and peripheral administration of antisense oligonucleotide targeting amyloid-β protein precursor improves learning and memory and reduces neuroinflammatory cytokines in Tg2576 (AβPPswe) mice.

Science.gov (United States)

Farr, Susan A; Erickson, Michelle A; Niehoff, Michael L; Banks, William A; Morley, John E

2014-01-01

Alzheimer's disease (AD) is a progressive neurodegenerative disease. Currently, there are no therapies to stop or reverse the symptoms of AD. We have developed an antisense oligonucleotide (OL-1) against the amyloid-β protein precursor (AβPP) that can decrease AβPP expression and amyloid-β protein (Aβ) production. This antisense rapidly crosses the blood-brain barrier, reverses learning and memory impairments, reduces oxidative stress, and restores brain-to-blood efflux of Aβ in SAMP8 mice. Here, we examined the effects of this AβPP antisense in the Tg2576 mouse model of AD. We administered the OL-1 antisense into the lateral ventricle 3 times at 2week intervals. Seventy-two hours after the third injection, we tested learning and memory in T-maze foot shock avoidance. In the second study, we injected the mice with OL-1 antisense 3 times at 2-week intervals via the tail vein. Seventy-two hours later, we tested learning and memory T-maze, novel object recognition, and elevated plus maze. At the end of behavioral testing, brain tissue was collected. OL-1 antisense administered centrally improved acquisition and retention of T-maze foot shock avoidance. OL-1 antisense administered via tail vein improved learning and memory in both T-maze foot shock avoidance and novel object-place recognition. In the elevated plus maze, the mice which received OL-1 antisense spent less time in the open arms and had fewer entries into the open arms indicating reduced disinhibitation. Biochemical analyses reveal significant reduction of AβPP signal and a reduction of measures of neuroinflammation. The current findings support the therapeutic potential of OL-1 AβPP antisense.

Concluding remarks. International Conference on Nuclear Physics, Berkeley, California, August 1980

International Nuclear Information System (INIS)

Feshbach, H.

1980-10-01

Not a conference summary, these concluding remarks consider five major themes that were illuminated during the conference and the problems within them that need to be resolved in the future. The five topics considered and the following: new degrees of freedom (single-particle motion, giant resonances, nuclear molecular resonances, nuclear matter, kaon-produced hypernuclei, implications of the bag model and quantum chromodynamics), new forms of matter, new reaction mechanisms (direct vs compound-nucleus reactions, heavy-ion reactions), new aspects of the weak interactions in nuclei (weak neutral currents, P invariance), and new symmetries. 4 figures

BWR stability using a reduced dynamical model

International Nuclear Information System (INIS)

Ballestrin Bolea, J.M.; Blazquez, J.B.

1990-01-01

BWR stability can be treated with reduced order dynamical models. When the parameters of the model came from experimental data, the predictions are accurate. In this work an alternative derivation for the void fraction equation is made, but remarking the physical struct-ure of the parameters. As the poles of power/reactivity transfer function are related with the parameters, the measurement of the poles by other techniques such as noise analysis will lead to the parameters, but the system of equations in non-linear. Simple parametric calculat-ion of decay ratio are performed, showing why BWRs become unstable when they are operated at low flow and high power. (Author). 7 refs

Remarkable reduction in the threshold voltage of pentacene-based thin film transistors with pentacene/CuPc sandwich configuration

Directory of Open Access Journals (Sweden)

Yi Li

2014-06-01

Full Text Available This study investigates the remarkable reduction in the threshold voltage (VT of pentacene-based thin film transistors with pentacene/copper phthalocyanine (CuPc sandwich configuration. This reduction is accompanied by increased mobility and lowered sub-threshold slope (S. Sandwich devices coated with a 5 nm layer of CuPc layer are compared with conventional top-contact devices, and results indicate that VT decreased significantly from −20.4 V to −0.2 V, that mobility increased from 0.18 cm2/Vs to 0.51 cm2/Vs, and that S was reduced from 4.1 V/dec to 2.9 V/dec. However, the on/off current ratio remains at 105. This enhanced performance could be attributed to the reduction in charge trap density by the incorporated CuPc layer. Results suggest that this method is simple and effectively generates pentacene-based organic thin film transistors with high mobility and low VT.

Remarks on Batchelor's theorem

International Nuclear Information System (INIS)

Blattner, R.J.; Rawnsley, J.H.

1984-01-01

The authors show that the structure sheaf of a graded manifold is the sheaf of sections of the exterior algebra bundle of a vector bundle by reducing the problem to one in the theory of extensions of sheaves of commutative algebras to which standard cohomological techniques can be applied. (Auth.)

Linking Individual Learning Styles to Approach-Avoidance Motivational Traits and Computational Aspects of Reinforcement Learning.

Directory of Open Access Journals (Sweden)

Kristoffer Carl Aberg

Full Text Available Learning how to gain rewards (approach learning and avoid punishments (avoidance learning is fundamental for everyday life. While individual differences in approach and avoidance learning styles have been related to genetics and aging, the contribution of personality factors, such as traits, remains undetermined. Moreover, little is known about the computational mechanisms mediating differences in learning styles. Here, we used a probabilistic selection task with positive and negative feedbacks, in combination with computational modelling, to show that individuals displaying better approach (vs. avoidance learning scored higher on measures of approach (vs. avoidance trait motivation, but, paradoxically, also displayed reduced learning speed following positive (vs. negative outcomes. These data suggest that learning different types of information depend on associated reward values and internal motivational drives, possibly determined by personality traits.

Linking Individual Learning Styles to Approach-Avoidance Motivational Traits and Computational Aspects of Reinforcement Learning

Science.gov (United States)

Carl Aberg, Kristoffer; Doell, Kimberly C.; Schwartz, Sophie

2016-01-01

Learning how to gain rewards (approach learning) and avoid punishments (avoidance learning) is fundamental for everyday life. While individual differences in approach and avoidance learning styles have been related to genetics and aging, the contribution of personality factors, such as traits, remains undetermined. Moreover, little is known about the computational mechanisms mediating differences in learning styles. Here, we used a probabilistic selection task with positive and negative feedbacks, in combination with computational modelling, to show that individuals displaying better approach (vs. avoidance) learning scored higher on measures of approach (vs. avoidance) trait motivation, but, paradoxically, also displayed reduced learning speed following positive (vs. negative) outcomes. These data suggest that learning different types of information depend on associated reward values and internal motivational drives, possibly determined by personality traits. PMID:27851807

The control of tonic pain by active relief learning

Science.gov (United States)

Mano, Hiroaki; Lee, Michael; Yoshida, Wako; Kawato, Mitsuo; Robbins, Trevor W

2018-01-01

Tonic pain after injury characterises a behavioural state that prioritises recovery. Although generally suppressing cognition and attention, tonic pain needs to allow effective relief learning to reduce the cause of the pain. Here, we describe a central learning circuit that supports learning of relief and concurrently suppresses the level of ongoing pain. We used computational modelling of behavioural, physiological and neuroimaging data in two experiments in which subjects learned to terminate tonic pain in static and dynamic escape-learning paradigms. In both studies, we show that active relief-seeking involves a reinforcement learning process manifest by error signals observed in the dorsal putamen. Critically, this system uses an uncertainty (‘associability’) signal detected in pregenual anterior cingulate cortex that both controls the relief learning rate, and endogenously and parametrically modulates the level of tonic pain. The results define a self-organising learning circuit that reduces ongoing pain when learning about potential relief. PMID:29482716

The control of tonic pain by active relief learning.

Science.gov (United States)

Zhang, Suyi; Mano, Hiroaki; Lee, Michael; Yoshida, Wako; Kawato, Mitsuo; Robbins, Trevor W; Seymour, Ben

2018-02-27

Tonic pain after injury characterises a behavioural state that prioritises recovery. Although generally suppressing cognition and attention, tonic pain needs to allow effective relief learning to reduce the cause of the pain. Here, we describe a central learning circuit that supports learning of relief and concurrently suppresses the level of ongoing pain. We used computational modelling of behavioural, physiological and neuroimaging data in two experiments in which subjects learned to terminate tonic pain in static and dynamic escape-learning paradigms. In both studies, we show that active relief-seeking involves a reinforcement learning process manifest by error signals observed in the dorsal putamen. Critically, this system uses an uncertainty ('associability') signal detected in pregenual anterior cingulate cortex that both controls the relief learning rate, and endogenously and parametrically modulates the level of tonic pain. The results define a self-organising learning circuit that reduces ongoing pain when learning about potential relief. © 2018, Zhang et al.

Dictionary Learning Based on Nonnegative Matrix Factorization Using Parallel Coordinate Descent

Directory of Open Access Journals (Sweden)

Zunyi Tang

2013-01-01

Full Text Available Sparse representation of signals via an overcomplete dictionary has recently received much attention as it has produced promising results in various applications. Since the nonnegativities of the signals and the dictionary are required in some applications, for example, multispectral data analysis, the conventional dictionary learning methods imposed simply with nonnegativity may become inapplicable. In this paper, we propose a novel method for learning a nonnegative, overcomplete dictionary for such a case. This is accomplished by posing the sparse representation of nonnegative signals as a problem of nonnegative matrix factorization (NMF with a sparsity constraint. By employing the coordinate descent strategy for optimization and extending it to multivariable case for processing in parallel, we develop a so-called parallel coordinate descent dictionary learning (PCDDL algorithm, which is structured by iteratively solving the two optimal problems, the learning process of the dictionary and the estimating process of the coefficients for constructing the signals. Numerical experiments demonstrate that the proposed algorithm performs better than the conventional nonnegative K-SVD (NN-KSVD algorithm and several other algorithms for comparison. What is more, its computational consumption is remarkably lower than that of the compared algorithms.

Cyclodextrin-Scaffolded Alamethicin with Remarkably Efficient Membrane Permeabilizing Properties and Membrane Current Conductance

DEFF Research Database (Denmark)

Hjørringgaard, Claudia Ulrich; Vad, Brian Stougaard; Matchkov, Vladimir

2012-01-01

Bacterial resistance to classical antibiotics is a serious medical problem, which continues to grow. Small antimicrobial peptides represent a potential solution and are increasingly being developed as novel therapeutic agents. Many of these peptides owe their antibacterial activity to the formati......-channel current measurements, the α-helices of the templated multimers were demonstrated to insert into lipid bilayers forming highly efficient and remarkably stable ion-channels...

Plasma membrane ordering agent pluronic F-68 (PF-68) reduces neurotransmitter uptake and release and produces learning and memory deficits in rats

Science.gov (United States)

Clarke, M. S.; Prendergast, M. A.; Terry, A. V. Jr

1999-01-01

A substantial body of evidence indicates that aged-related changes in the fluidity and lipid composition of the plasma membrane contribute to cellular dysfunction in humans and other mammalian species. In the CNS, reductions in neuronal plasma membrane order (PMO) (i.e., increased plasma membrane fluidity) have been attributed to age as well as the presence of the beta-amyloid peptide-25-35, known to play an important role in the neuropathology of Alzheimer's disease (AD). These PMO increases may influence neurotransmitter synthesis, receptor binding, and second messenger systems as well as signal transduction pathways. The effects of neuronal PMO on learning and memory processes have not been adequately investigated, however. Based on the hypothesis that an increase in PMO may alter a number of aspects of synaptic transmission, we investigated several neurochemical and behavioral effects of the membrane ordering agent, PF-68. In cell culture, PF-68 (nmoles/mg SDS extractable protein) reduced [3H]norepinephrine (NE) uptake into differentiated PC-12 cells as well as reduced nicotine stimulated [3H]NE release. The compound (800-2400 microg/kg, i.p., resulting in nmoles/mg SDS extractable protein in the brain) decreased step-through latencies and increased the frequencies of crossing into the unsafe side of the chamber in inhibitory avoidance training. In the Morris water maze, PF-68 increased the latencies and swim distances required to locate a hidden platform and reduced the time spent and distance swam in the previous target quadrant during transfer (probe) trials. PF-68 did not impair performance of a well-learned working memory task, the rat delayed stimulus discrimination task (DSDT), however. Studies with 14C-labeled PF-68 indicated that significant (pmoles/mg wet tissue) levels of the compound entered the brain from peripheral (i.p.) injection. No PF-68 related changes were observed in swim speeds or in visual acuity tests in water maze experiments, rotorod

Entropy Learning in Neural Network

Directory of Open Access Journals (Sweden)

Geok See Ng

2017-12-01

Full Text Available In this paper, entropy term is used in the learning phase of a neural network.  As learning progresses, more hidden nodes get into saturation.  The early creation of such hidden nodes may impair generalisation.  Hence entropy approach is proposed to dampen the early creation of such nodes.  The entropy learning also helps to increase the importance of relevant nodes while dampening the less important nodes.  At the end of learning, the less important nodes can then be eliminated to reduce the memory requirements of the neural network.

The effectiveness of E- learning in learning: A review of the literature

Directory of Open Access Journals (Sweden)

Mousazadeh Somayeh

2016-02-01

Full Text Available Entry to the information age and effective life in information-oriented society requires an understanding of its characteristics. One of the social institutions that will undergo extensive changes at this age is general and higher education and training institutions. The aim of this review study is to evaluate the effectiveness of e learning in learning. This paper is a review study carried out using Medline and CINAHL databases and Google search engine. The studies used include review articles and English meta-analysis of language.Of the retrieved results,38 documents including articles, books and web sites were investigated and classified. At first, the background of e learning was studied history and in the next section its effectiveness in learning was briefly examined. The overall benefits of e-learning include the promotion of learning, independence and individual satisfaction, learning at anytime, anywhere and with any background, learning without the same prerequisites, speed and process of learning due to individual needs, individual learning along with cooperative learning, saving time and costs significantly, the possibility of teaching and learning for all people, mutual teaching and learning, getting quick results in learning, learning more by using multimedia and maintaining resources and reducing environmental and audio pollution. The results of studies suggest positive effects of e-learning on learning thus it is suggested that this approach be used more in education, which requires building the required grounds.

Remarks before the Beijing meeting of the pacific basin conference

International Nuclear Information System (INIS)

Rusche, B.C.

1987-01-01

A substantial amount of new generating capacity must be added in the United States before the turn of the century. Noting that the Light Water Reactor (LWR) has enjoyed a remarkably good safety record, the United States Department of Energy (DOE) is working actively to restore public and investor confidence in nuclear power. DOE is working with U.S. industry to encourage licensing reform, simplification and standardization of large plant designs, and resolution of the waste managment issues. We also are pursuing new, more tolerant, lower cost designs and are prepared to share our technology advances with other nations under mutually acceptable conditions and are determined to be a reliable supplier of equipment and enrichment services. (author)

Some remarks on the design of HIF current multiplication rings

International Nuclear Information System (INIS)

Reich, K.H.

1983-12-01

The conceptual design of heavy ion fusion drivers has now reached a state, where the overall approach has become fairly clear. One design features an RF linac plus current and beam multiplication rings. The present remarks concern the assignment of multiturn injection, beam storage and bunching to an optimized number of rings and transport lines, as well as some criteria for their designs. The main parameter constraints are discussed, showing how they can be met, although there is little flexibility at the present stage of understanding and technology. A shortened version of this report is scheduled for presentation at the ''INS International Symposium on Heavy Ion Accelerators and Their Application to Inertial Fusion'' Tokyo, January 23-27 1984. (author)

Nursing students' views of sociocultural factors in clinical learning: a qualitative content analysis.

Science.gov (United States)

Dadgaran, Ideh; Parvizy, Soroor; Peyrovi, Hamid

2013-06-01

The aim of this study is description of nursing students' views of sociocultural factors in clinical learning. A qualitative content analysis was conducted to describe nursing students' views of sociocultural factors in clinical learning. The participants consisted of 21 nursing students. Semi-structured and interactive interviews were used to collect data. All the interviews were recorded and transcribed, and then, they were analyzed using Qualitative Content Analysis and Max Qualitative Data Analysis 2010. From the transcripts, a remarkable number of primary themes, main themes, and sub-themes emerged. The main themes consisted of elements related to "society and culture", "family", "staff", and "classmates". The themes encompassed a spectrum of facilitators of and impediments to clinical learning. The findings showed that the administrators of nursing education should coordinate with faculty and staff by adopting interactive and participatory solutions, including the establishment of clinical learning teams and the transformation of hospitals into suitable sociocultural environments for education. © 2012 The Authors. Japan Journal of Nursing Science © 2012 Japan Academy of Nursing Science.

Learning rational temporal eye movement strategies.

Science.gov (United States)

Hoppe, David; Rothkopf, Constantin A

2016-07-19

During active behavior humans redirect their gaze several times every second within the visual environment. Where we look within static images is highly efficient, as quantified by computational models of human gaze shifts in visual search and face recognition tasks. However, when we shift gaze is mostly unknown despite its fundamental importance for survival in a dynamic world. It has been suggested that during naturalistic visuomotor behavior gaze deployment is coordinated with task-relevant events, often predictive of future events, and studies in sportsmen suggest that timing of eye movements is learned. Here we establish that humans efficiently learn to adjust the timing of eye movements in response to environmental regularities when monitoring locations in the visual scene to detect probabilistically occurring events. To detect the events humans adopt strategies that can be understood through a computational model that includes perceptual and acting uncertainties, a minimal processing time, and, crucially, the intrinsic costs of gaze behavior. Thus, subjects traded off event detection rate with behavioral costs of carrying out eye movements. Remarkably, based on this rational bounded actor model the time course of learning the gaze strategies is fully explained by an optimal Bayesian learner with humans' characteristic uncertainty in time estimation, the well-known scalar law of biological timing. Taken together, these findings establish that the human visual system is highly efficient in learning temporal regularities in the environment and that it can use these regularities to control the timing of eye movements to detect behaviorally relevant events.

Remarks on an equation common to Weyl's gauge field, Yang-Mills field and Toda lattice

International Nuclear Information System (INIS)

Nishioka, M.

1984-01-01

In this letter a remark is presented on an equation of a gauge-invariant Weyl's gauge field and it is shown that the equation is common to Yang's approach to the self-duality condition for SU 2 gauge field and the simplest Toda lattice

Active Learning of Classification Models with Likert-Scale Feedback.

Science.gov (United States)

Xue, Yanbing; Hauskrecht, Milos

2017-01-01

Annotation of classification data by humans can be a time-consuming and tedious process. Finding ways of reducing the annotation effort is critical for building the classification models in practice and for applying them to a variety of classification tasks. In this paper, we develop a new active learning framework that combines two strategies to reduce the annotation effort. First, it relies on label uncertainty information obtained from the human in terms of the Likert-scale feedback. Second, it uses active learning to annotate examples with the greatest expected change. We propose a Bayesian approach to calculate the expectation and an incremental SVM solver to reduce the time complexity of the solvers. We show the combination of our active learning strategy and the Likert-scale feedback can learn classification models more rapidly and with a smaller number of labeled instances than methods that rely on either Likert-scale labels or active learning alone.

Machine learning of molecular properties: Locality and active learning

Science.gov (United States)

Gubaev, Konstantin; Podryabinkin, Evgeny V.; Shapeev, Alexander V.

2018-06-01

In recent years, the machine learning techniques have shown great potent1ial in various problems from a multitude of disciplines, including materials design and drug discovery. The high computational speed on the one hand and the accuracy comparable to that of density functional theory on another hand make machine learning algorithms efficient for high-throughput screening through chemical and configurational space. However, the machine learning algorithms available in the literature require large training datasets to reach the chemical accuracy and also show large errors for the so-called outliers—the out-of-sample molecules, not well-represented in the training set. In the present paper, we propose a new machine learning algorithm for predicting molecular properties that addresses these two issues: it is based on a local model of interatomic interactions providing high accuracy when trained on relatively small training sets and an active learning algorithm of optimally choosing the training set that significantly reduces the errors for the outliers. We compare our model to the other state-of-the-art algorithms from the literature on the widely used benchmark tests.

Learning shapes spontaneous activity itinerating over memorized states.

Directory of Open Access Journals (Sweden)

Tomoki Kurikawa

Full Text Available Learning is a process that helps create neural dynamical systems so that an appropriate output pattern is generated for a given input. Often, such a memory is considered to be included in one of the attractors in neural dynamical systems, depending on the initial neural state specified by an input. Neither neural activities observed in the absence of inputs nor changes caused in the neural activity when an input is provided were studied extensively in the past. However, recent experimental studies have reported existence of structured spontaneous neural activity and its changes when an input is provided. With this background, we propose that memory recall occurs when the spontaneous neural activity changes to an appropriate output activity upon the application of an input, and this phenomenon is known as bifurcation in the dynamical systems theory. We introduce a reinforcement-learning-based layered neural network model with two synaptic time scales; in this network, I/O relations are successively memorized when the difference between the time scales is appropriate. After the learning process is complete, the neural dynamics are shaped so that it changes appropriately with each input. As the number of memorized patterns is increased, the generated spontaneous neural activity after learning shows itineration over the previously learned output patterns. This theoretical finding also shows remarkable agreement with recent experimental reports, where spontaneous neural activity in the visual cortex without stimuli itinerate over evoked patterns by previously applied signals. Our results suggest that itinerant spontaneous activity can be a natural outcome of successive learning of several patterns, and it facilitates bifurcation of the network when an input is provided.

Global learning for local solutions: Reducing vulnerability of marine-dependent coastal communities

Science.gov (United States)

Salim, S. S.; Paytan, A.

2016-12-01

The project `Global learning for local solutions: Reducing vulnerability of marine-dependent coastal communities' (GULLS) falls within the Belmont Forum and G8 Research Councils Initiative on Multilateral Research Funding. Participants include teams from nine countries: Australia, Brazil, India, Madagascar, Mozambique, New Zealand, South Africa, the United Kingdom and the United States of America. The project focuses on five regional `hotspots' of climate and social change, defined as fast-warming marine areas and areas experiencing social tensions as a result of change: south-east Australia, Brazil, India, South Africa, and the Mozambique Channel and adjacent countries of Mozambique and Madagascar. These areas require most urgent attention and serve as valuable case studies for wider applications. The project aims to assist coastal communities and other stakeholders dependent on marine resources to adapt to climate change and variability through an integrated and trans-disciplinary approach. Combining best available global knowledge with local knowledge and conditions, it is exploring adaptation options and approaches to strengthen resilience at local and community levels, with a focus on options for reconciling the needs for food security with long-term sustainability and conservation. The project will also contribute to capacity development and empowering fishing communities and other fisheries-dependent stakeholders.A standardized vulnerability assessment framework is being developed that will be used to integrate results from natural, social and economic studies in order to identify needs and options for strengthening management and existing policies. Structured comparisons between the hot-spots will assist global efforts for adaptation and strengthening resilience in marine and coastal social-ecological systems.

BWR stability using a reducing dynamical model

International Nuclear Information System (INIS)

Ballestrin Bolea, J. M.; Blazquez Martinez, J. B.

1990-01-01

BWR stability can be treated with reduced order dynamical models. When the parameters of the model came from dynamical models. When the parameters of the model came from experimental data, the predictions are accurate. In this work an alternative derivation for the void fraction equation is made, but remarking the physical structure of the parameters. As the poles of power/reactivity transfer function are related with the parameters, the measurement of the poles by other techniques such as noise analysis will lead to the parameters, but the system of equations is non-linear. Simple parametric calculation of decay ratio are performed, showing why BWRs become unstable when they are operated at low flow and high power. (Author)

Blended learning versus traditional teaching-learning-setting: Evaluation of cognitive and affective learning outcomes for the inter-professional field of occupational medicine and prevention / Blended Learning versus traditionelles Lehr-Lernsetting: Evaluierung von kognitiven und affektiven Lernergebnissen für das interprofessionelle Arbeitsfeld Arbeitsmedizin und Prävention

OpenAIRE

Eckler Ursula; Greisberger Andrea; Höhne Franziska; Putz Peter

2017-01-01

Blended learning is characterised as a combination of face-to-face teaching and e-learning in terms of knowledge transfer, students’ learning activities and reduced presence at the teaching facility. The present cohort study investigated long-term effects of blended learning regarding cognitive outcomes as well as self-indicated estimates of immediate learning effects on the affective domain in the inter-professional field of occupational medicine. Physiotherapy students (bachelor degree) at ...

Summary of remarks and recommendations concerning the 2nd draft revision of the IAEA transport regulations

International Nuclear Information System (INIS)

The report contains a summary of all the remarks and recommendations that had been received by the International Atomic Energy Agency from Member States and International Organizations on the second draft revision of the IAEA transport regulations

Liraglutide Improves Water Maze Learning and Memory Performance While Reduces Hyperphosphorylation of Tau and Neurofilaments in APP/PS1/Tau Triple Transgenic Mice.

Science.gov (United States)

Chen, Shuyi; Sun, Jie; Zhao, Gang; Guo, Ai; Chen, Yanlin; Fu, Rongxia; Deng, Yanqiu

2017-08-01

The purpose of this study was to explore how liraglutide affects AD-like pathology and cognitive function in APP/PS1/Tau triple transgenic (3 × Tg) Alzheimer disease (AD) model mice. Male 3 × Tg mice and C57BL/6 J mice were treated for 8 weeks with liraglutide (300 μg/kg/day, subcutaneous injection) or saline. Levels of phosphorylated tau, neurofilaments (NFs), extracellular signal-regulated kinase (ERK), and c-Jun N-terminal kinase (JNK) in brain tissues were assessed with western blots. Fluoro-Jade-B labeling were applied to detect pathological changes. The Morris water maze (MWM) was used to assess the spatial learning and memory. Liraglutide decreased levels of hyperphosphorylated tau and NFs in 3 × Tg liraglutide-treated (Tg + LIR) mice, increased ERK phosphorylation, and decreased JNK phosphorylation. Liraglutide also decreased the number of degenerative neurons in the hippocampus and cortex of Tg + LIR mice, and shortened their escape latencies and increased their hidden platform crossings in the MWM task. Liraglutide did not significantly affect the animals' body weight (BW) or fasting blood glucose. Liraglutide can reduce hyperphosphorylation of tau and NFs and reduce neuronal degeneration, apparently through alterations in JNK and ERK signaling, which may be related to its positive effects on AD-like learning and memory impairment.

Using Expectancy Value Theory as a Framework to Reduce Student Resistance to Active Learning: A Proof of Concept

OpenAIRE

Cooper, Katelyn M.; Ashley, Michael; Brownell, Sara E.

2017-01-01

There has been a national movement to transition college science courses from passive lectures to active learning environments. Active learning has been shown to be a more effective way for students to learn, yet there is concern that some students are resistant to active learning approaches. Although there is much discussion about student resistance to active learning, few studies have explored this topic. Furthermore, a limited number of studies have applied theoretical frameworks to studen...

The Lie of Online Learning.

Science.gov (United States)

Zielinski, Dave

2000-01-01

Managers look at online training as an activity that should be done "off time" whereas employees still think of it as something to be done during working hours. No valid study has shown that online delivery reduces learning time. A better understanding of learning needs must be considered before requiring online training. (JOW)

Invariant spatial context is learned but not retrieved in gaze-contingent tunnel-view search.

Science.gov (United States)

Zang, Xuelian; Jia, Lina; Müller, Hermann J; Shi, Zhuanghua

2015-05-01

Our visual brain is remarkable in extracting invariant properties from the noisy environment, guiding selection of where to look and what to identify. However, how the brain achieves this is still poorly understood. Here we explore interactions of local context and global structure in the long-term learning and retrieval of invariant display properties. Participants searched for a target among distractors, without knowing that some "old" configurations were presented repeatedly (randomly inserted among "new" configurations). We simulated tunnel vision, limiting the visible region around fixation. Robust facilitation of performance for old versus new contexts was observed when the visible region was large but not when it was small. However, once the display was made fully visible during the subsequent transfer phase, facilitation did become manifest. Furthermore, when participants were given a brief preview of the total display layout prior to tunnel view search with 2 items visible, facilitation was already obtained during the learning phase. The eye movement results revealed contextual facilitation to be coupled with changes of saccadic planning, characterized by slightly extended gaze durations but a reduced number of fixations and shortened scan paths for old displays. Taken together, our findings show that invariant spatial display properties can be acquired based on scarce, para-/foveal information, while their effective retrieval for search guidance requires the availability (even if brief) of a certain extent of peripheral information. (c) 2015 APA, all rights reserved).

Active Learning Using Hint Information.

Science.gov (United States)

Li, Chun-Liang; Ferng, Chun-Sung; Lin, Hsuan-Tien

2015-08-01

The abundance of real-world data and limited labeling budget calls for active learning, an important learning paradigm for reducing human labeling efforts. Many recently developed active learning algorithms consider both uncertainty and representativeness when making querying decisions. However, exploiting representativeness with uncertainty concurrently usually requires tackling sophisticated and challenging learning tasks, such as clustering. In this letter, we propose a new active learning framework, called hinted sampling, which takes both uncertainty and representativeness into account in a simpler way. We design a novel active learning algorithm within the hinted sampling framework with an extended support vector machine. Experimental results validate that the novel active learning algorithm can result in a better and more stable performance than that achieved by state-of-the-art algorithms. We also show that the hinted sampling framework allows improving another active learning algorithm designed from the transductive support vector machine.

Fast learning method for convolutional neural networks using extreme learning machine and its application to lane detection.

Science.gov (United States)

Kim, Jihun; Kim, Jonghong; Jang, Gil-Jin; Lee, Minho

2017-03-01

Deep learning has received significant attention recently as a promising solution to many problems in the area of artificial intelligence. Among several deep learning architectures, convolutional neural networks (CNNs) demonstrate superior performance when compared to other machine learning methods in the applications of object detection and recognition. We use a CNN for image enhancement and the detection of driving lanes on motorways. In general, the process of lane detection consists of edge extraction and line detection. A CNN can be used to enhance the input images before lane detection by excluding noise and obstacles that are irrelevant to the edge detection result. However, training conventional CNNs requires considerable computation and a big dataset. Therefore, we suggest a new learning algorithm for CNNs using an extreme learning machine (ELM). The ELM is a fast learning method used to calculate network weights between output and hidden layers in a single iteration and thus, can dramatically reduce learning time while producing accurate results with minimal training data. A conventional ELM can be applied to networks with a single hidden layer; as such, we propose a stacked ELM architecture in the CNN framework. Further, we modify the backpropagation algorithm to find the targets of hidden layers and effectively learn network weights while maintaining performance. Experimental results confirm that the proposed method is effective in reducing learning time and improving performance. Copyright © 2016 Elsevier Ltd. All rights reserved.

Active learning: a step towards automating medical concept extraction.

Science.gov (United States)

Kholghi, Mahnoosh; Sitbon, Laurianne; Zuccon, Guido; Nguyen, Anthony

2016-03-01

This paper presents an automatic, active learning-based system for the extraction of medical concepts from clinical free-text reports. Specifically, (1) the contribution of active learning in reducing the annotation effort and (2) the robustness of incremental active learning framework across different selection criteria and data sets are determined. The comparative performance of an active learning framework and a fully supervised approach were investigated to study how active learning reduces the annotation effort while achieving the same effectiveness as a supervised approach. Conditional random fields as the supervised method, and least confidence and information density as 2 selection criteria for active learning framework were used. The effect of incremental learning vs standard learning on the robustness of the models within the active learning framework with different selection criteria was also investigated. The following 2 clinical data sets were used for evaluation: the Informatics for Integrating Biology and the Bedside/Veteran Affairs (i2b2/VA) 2010 natural language processing challenge and the Shared Annotated Resources/Conference and Labs of the Evaluation Forum (ShARe/CLEF) 2013 eHealth Evaluation Lab. The annotation effort saved by active learning to achieve the same effectiveness as supervised learning is up to 77%, 57%, and 46% of the total number of sequences, tokens, and concepts, respectively. Compared with the random sampling baseline, the saving is at least doubled. Incremental active learning is a promising approach for building effective and robust medical concept extraction models while significantly reducing the burden of manual annotation. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Remarkable identities related to the (quantum) elliptic Calogero-Sutherland model

International Nuclear Information System (INIS)

Langmann, Edwin

2006-01-01

We present remarkable functional identities related to the elliptic Calogero-Sutherland (eCS) system. We derive them from a second quantization of the eCS model within a quantum field theory model of anyons on a circle and at finite temperature. The identities involve two eCS Hamiltonians with arbitrary and, in general, different particle numbers N and M, and a particular function of N+M variables arising as anyon correlation function of N particles and M antiparticles. In addition to identities obtained from anyons with the same statistics parameter λ, we also obtain 'dual' relations involving 'mixed' correlation functions of anyons with two different statistics parameters λ and 1/λ. We also give alternative, elementary proofs of these identities by direct computations

Allotropes of Phosphorus with Remarkable Stability and Intrinsic Piezoelectricity

Science.gov (United States)

Li, Zhenqing; He, Chaoyu; Ouyang, Tao; Zhang, Chunxiao; Tang, Chao; Römer, Rudolf A.; Zhong, Jianxin

2018-04-01

We construct a class of two-dimensional (2D) phosphorus allotropes by assembling a previously proposed ultrathin metastable phosphorus nanotube into planar structures in different stacking orientations. Based on first-principles methods, the structures, stabilities, and fundamental electronic properties of these allotropes are systematically investigated. Our results show that these 2D van der Waals phosphorene allotropes possess remarkable stabilities due to the strong intertube van der Waals interactions, which cause an energy release of about 30 - 70 meV /atom , depending on their stacking details. Most of them are confirmed to be energetically more favorable than the experimentally viable α -P and β -P . Three of them, showing a relatively higher probability of being synthesized in the future, are further confirmed to be dynamically stable semiconductors with strain-tunable band gaps and intrinsic piezoelectricity, which may have potential applications in nanosized sensors, piezotronics, and energy harvesting in portable electronic nanodevices.

A remarkable legacy

Science.gov (United States)

Parkinson, Stuart

2008-02-01

Joseph Rotblat, who died in 2005 at the age of 96, was a rare combination of distinguished scientist and leading peace advocate. During the Second World War he was involved with the Manhattan Project - which created the world's first atomic bombs - but then decided to resign on ethical grounds. This life-changing decision set the scene for the dual role that he would play for the rest of his life. On the one hand, Rotblat was a key figure in setting up and leading the Pugwash Conferences on Science and World Affairs, which bring together scientists and public figures concerned with reducing the danger of armed conflict and seeking co-operative solutions for global problems. On the other, he was an accomplished nuclear and medical physicist, eventually becoming president of the British Institute of Radiology.

Transitioning to Blended Learning: Understanding Student and Faculty Perceptions

Science.gov (United States)

Napier, Nannette P.; Dekhane, Sonal; Smith, Stella

2011-01-01

This paper describes the conversion of an introductory computing course to the blended learning model at a small, public liberal arts college. Blended learning significantly reduces face-to-face instruction by incorporating rich, online learning experiences. To assess the impact of blended learning on students, survey data was collected at the…

Active learning in practice: Implementation of the principles of active learning in an engineering course

DEFF Research Database (Denmark)

Rützou, C.

2017-01-01

The most common form of teaching is still the form where a teacher presents the subject of the lecture to a listening audience. During teaching history this has proved to be an effective way of teaching, however the probability of students being inactive is high and the learning outcome may...... through the same curriculum as usual during a term? • Will Active Learning reduce failure rate? • Will Active Learning give a higher learning outcome than traditional teaching? This paper deals with the results of this experiment, answers the mentioned questions and presents a way to implement Active...

Remarkable biomimetic chemoselective aerobic oxidation of flavano-ellagitannins found in oak-aged wine.

Science.gov (United States)

Petit, Emilie; Lefeuvre, Dorothée; Jacquet, Rémi; Pouységu, Laurent; Deffieux, Denis; Quideau, Stéphane

2013-10-25

Under the auspices of Bacchus! Acutissimins, natural flavano-ellagitannins, occur in oak-aged wine as a result of a diastereoselective condensation reaction of the flavan-3-ol catechin, a component of grapes, with the C-glucosidic ellagitannin vescalagin, found in oak. The acutissimins are further converted into natural mongolicains and analogues of camelliatannin G in a remarkably chemoselective fashion by simple aerobic oxidation. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Learning a locomotor task: with or without errors?

Science.gov (United States)

Marchal-Crespo, Laura; Schneider, Jasmin; Jaeger, Lukas; Riener, Robert

2014-03-04

Robotic haptic guidance is the most commonly used robotic training strategy to reduce performance errors while training. However, research on motor learning has emphasized that errors are a fundamental neural signal that drive motor adaptation. Thus, researchers have proposed robotic therapy algorithms that amplify movement errors rather than decrease them. However, to date, no study has analyzed with precision which training strategy is the most appropriate to learn an especially simple task. In this study, the impact of robotic training strategies that amplify or reduce errors on muscle activation and motor learning of a simple locomotor task was investigated in twenty two healthy subjects. The experiment was conducted with the MAgnetic Resonance COmpatible Stepper (MARCOS) a special robotic device developed for investigations in the MR scanner. The robot moved the dominant leg passively and the subject was requested to actively synchronize the non-dominant leg to achieve an alternating stepping-like movement. Learning with four different training strategies that reduce or amplify errors was evaluated: (i) Haptic guidance: errors were eliminated by passively moving the limbs, (ii) No guidance: no robot disturbances were presented, (iii) Error amplification: existing errors were amplified with repulsive forces, (iv) Noise disturbance: errors were evoked intentionally with a randomly-varying force disturbance on top of the no guidance strategy. Additionally, the activation of four lower limb muscles was measured by the means of surface electromyography (EMG). Strategies that reduce or do not amplify errors limit muscle activation during training and result in poor learning gains. Adding random disturbing forces during training seems to increase attention, and therefore improve motor learning. Error amplification seems to be the most suitable strategy for initially less skilled subjects, perhaps because subjects could better detect their errors and correct them

Statistical learning in high energy and astrophysics

International Nuclear Information System (INIS)

Zimmermann, J.

2005-01-01

This thesis studies the performance of statistical learning methods in high energy and astrophysics where they have become a standard tool in physics analysis. They are used to perform complex classification or regression by intelligent pattern recognition. This kind of artificial intelligence is achieved by the principle ''learning from examples'': The examples describe the relationship between detector events and their classification. The application of statistical learning methods is either motivated by the lack of knowledge about this relationship or by tight time restrictions. In the first case learning from examples is the only possibility since no theory is available which would allow to build an algorithm in the classical way. In the second case a classical algorithm exists but is too slow to cope with the time restrictions. It is therefore replaced by a pattern recognition machine which implements a fast statistical learning method. But even in applications where some kind of classical algorithm had done a good job, statistical learning methods convinced by their remarkable performance. This thesis gives an introduction to statistical learning methods and how they are applied correctly in physics analysis. Their flexibility and high performance will be discussed by showing intriguing results from high energy and astrophysics. These include the development of highly efficient triggers, powerful purification of event samples and exact reconstruction of hidden event parameters. The presented studies also show typical problems in the application of statistical learning methods. They should be only second choice in all cases where an algorithm based on prior knowledge exists. Some examples in physics analyses are found where these methods are not used in the right way leading either to wrong predictions or bad performance. Physicists also often hesitate to profit from these methods because they fear that statistical learning methods cannot be controlled in a

Statistical learning in high energy and astrophysics

Energy Technology Data Exchange (ETDEWEB)

Zimmermann, J.

2005-06-16

This thesis studies the performance of statistical learning methods in high energy and astrophysics where they have become a standard tool in physics analysis. They are used to perform complex classification or regression by intelligent pattern recognition. This kind of artificial intelligence is achieved by the principle ''learning from examples'': The examples describe the relationship between detector events and their classification. The application of statistical learning methods is either motivated by the lack of knowledge about this relationship or by tight time restrictions. In the first case learning from examples is the only possibility since no theory is available which would allow to build an algorithm in the classical way. In the second case a classical algorithm exists but is too slow to cope with the time restrictions. It is therefore replaced by a pattern recognition machine which implements a fast statistical learning method. But even in applications where some kind of classical algorithm had done a good job, statistical learning methods convinced by their remarkable performance. This thesis gives an introduction to statistical learning methods and how they are applied correctly in physics analysis. Their flexibility and high performance will be discussed by showing intriguing results from high energy and astrophysics. These include the development of highly efficient triggers, powerful purification of event samples and exact reconstruction of hidden event parameters. The presented studies also show typical problems in the application of statistical learning methods. They should be only second choice in all cases where an algorithm based on prior knowledge exists. Some examples in physics analyses are found where these methods are not used in the right way leading either to wrong predictions or bad performance. Physicists also often hesitate to profit from these methods because they fear that statistical learning methods cannot

Rotational bands in the nuclear sup(168)Er and some remarks on their interpretation

International Nuclear Information System (INIS)

Davidson, W.F.; Dixon, W.R.; Storey, R.S.

1984-01-01

Further analysis of previously published data on sup(168)Er, together with results of new measurements of selected portions of the neutron capture γ-ray spectrum, has resulted in the construction of an improved level spectrum for this nucleus. Altogether 127 excited levels have now been established and grouped into 36 rotational bands. Some remarks on their interpretation are advanced

Technology Assisted Language Learning is a silver bullet for enhancing Language competence and performance: A Case Study

Directory of Open Access Journals (Sweden)

Jameel Ahmad

2016-11-01

Full Text Available Technology Assisted Language Learning (TALL is an infallible means to develop profound knowledge and wide range of language skills. It instills in EFL learners an illimitable passion for task-based and skills oriented learning rather than rote memorization. New technological gadgets have commoditized a broad-based learning and teaching avenues and brought the whole learning process to life. A vast variety of authentic online- learning resources, motivational visual prompts, exciting videos, web-based interactivity and customizable language software, email, discussion forums, Skype, Twitter, apps, Internet mobiles, Facebook and YouTube have become obtrusive tools to enhance competence and performance in EFL teaching and learning realms. Technology can also provide various types of scaffolding for students learning to read. Nevertheless, instructors can also enhance their pedagogical effectiveness. However, the main focus of interest in this study is to ascertain to what extent the modern technological devices augment learners’ competence and performance specifically in vocabulary learning, grammatical accuracy and listening/ speaking skills. The remarkable scores of empirical surveys conducted in the present study reveal that TALL does assist learners to improve listening / speaking skills, pronunciation, extensive vocabulary and grammatical accuracy. The findings also manifest that the hybridity, instantaneity and super-diversity of digital learning lay far-reaching impact on learners' motivation for learning and incredibly maneuver learners to immerse in the whole learning process.

Advanced Machine learning Algorithm Application for Rotating Machine Health Monitoring

Energy Technology Data Exchange (ETDEWEB)

Kanemoto, Shigeru; Watanabe, Masaya [The University of Aizu, Aizuwakamatsu (Japan); Yusa, Noritaka [Tohoku University, Sendai (Japan)

2014-08-15

The present paper tries to evaluate the applicability of conventional sound analysis techniques and modern machine learning algorithms to rotating machine health monitoring. These techniques include support vector machine, deep leaning neural network, etc. The inner ring defect and misalignment anomaly sound data measured by a rotating machine mockup test facility are used to verify the above various kinds of algorithms. Although we cannot find remarkable difference of anomaly discrimination performance, some methods give us the very interesting eigen patterns corresponding to normal and abnormal states. These results will be useful for future more sensitive and robust anomaly monitoring technology.

Advanced Machine learning Algorithm Application for Rotating Machine Health Monitoring

International Nuclear Information System (INIS)

Kanemoto, Shigeru; Watanabe, Masaya; Yusa, Noritaka

2014-01-01

The present paper tries to evaluate the applicability of conventional sound analysis techniques and modern machine learning algorithms to rotating machine health monitoring. These techniques include support vector machine, deep leaning neural network, etc. The inner ring defect and misalignment anomaly sound data measured by a rotating machine mockup test facility are used to verify the above various kinds of algorithms. Although we cannot find remarkable difference of anomaly discrimination performance, some methods give us the very interesting eigen patterns corresponding to normal and abnormal states. These results will be useful for future more sensitive and robust anomaly monitoring technology

Negative viscosity can enhance learning of inertial dynamics.

Science.gov (United States)

Huang, Felix C; Patton, James L; Mussa-Ivaldi, Ferdinando A

2009-06-01

We investigated how learning of inertial load manipulation is influenced by movement amplification with negative viscosity. Using a force-feedback device, subjects trained on anisotropic loads (5 orientations) with free movements in one of three conditions (inertia only, negative viscosity only, or combined), prior to common evaluation conditions (prescribed circular pattern with inertia only). Training with Combined-Load resulted in lower error (6.89±3.25%) compared to Inertia-Only (8.40±4.32%) and Viscosity-Only (8.17±4.13%) according to radial deviation analysis (% of trial mean radius). Combined-Load and Inertia-Only groups exhibited similar unexpected no-load trials (8.38±4.31% versus 8.91±4.70% of trial mean radius), which suggests comparable low-impedance strategies. These findings are remarkable since negative viscosity, only available during training, evidently enhanced learning when combined with inertia. Modeling analysis suggests that a feedforward after-effect of negative viscosity cannot predict such performance gains. Instead, results from Combined-Load training are consistent with greater feedforward inertia compensation along with a small increase in impedance control. The capability of the nervous system to generalize learning from negative viscosity suggests an intriguing new method for enhancing sensorimotor adaptation.

The Public University in South Africa: Philosophical Remarks on the Notion of "Elitist Knowledge" Production

Science.gov (United States)

Waghid, Yusef

2009-01-01

In my remarks about elitist knowledge production, I firstly try to adjust the perspective from which the university could be analysed; I specifically explore the functions of the university in relation to Habermas's categorisation of knowledge. Secondly, with reference to Derrida's reflections on the university, I reformulate a conception of the…

Impaired implicit learning and feedback processing after stroke.

Science.gov (United States)

Lam, J M; Globas, C; Hosp, J A; Karnath, H-O; Wächter, T; Luft, A R

2016-02-09

The ability to learn is assumed to support successful recovery and rehabilitation therapy after stroke. Hence, learning impairments may reduce the recovery potential. Here, the hypothesis is tested that stroke survivors have deficits in feedback-driven implicit learning. Stroke survivors (n=30) and healthy age-matched control subjects (n=21) learned a probabilistic classification task with brain activation measured using functional magnetic resonance imaging in a subset of these individuals (17 stroke and 10 controls). Stroke subjects learned slower than controls to classify cues. After being rewarded with a smiley face, they were less likely to give the same response when the cue was repeated. Stroke subjects showed reduced brain activation in putamen, pallidum, thalamus, frontal and prefrontal cortices and cerebellum when compared with controls. Lesion analysis identified those stroke survivors as learning-impaired who had lesions in frontal areas, putamen, thalamus, caudate and insula. Lesion laterality had no effect on learning efficacy or brain activation. These findings suggest that stroke survivors have deficits in reinforcement learning that may be related to dysfunctional processing of feedback-based decision-making, reward signals and working memory. Copyright © 2015 IBRO. Published by Elsevier Ltd. All rights reserved.

Using REDUCE in high energy physics

International Nuclear Information System (INIS)

Grozin, A.G.

1997-01-01

This book describes the use of the symbolic manipulation language REDUCE in particle physics. There are several general purpose mathematics packages available to physicists, including Mathematica, Maple, and REDUCE. Each has advantages and disadvantages, but REDUCE has been found to be both powerful and convenient in solving a wide range of problems. This book introduces the reader to REDUCE and demonstrates its utility as a mathematical tool in physics. The first chapter of the book describes the REDUCE system, including some library packages. The following chapters show the use of REDUCE in examples from classical mechanics, hydrodynamics, general relativity, and quantum mechanics. The rest of the book systematically presents the Standard Model of particle physics (QED, weak interactions, QCD). A large number of scattering and decay processes are calculated with REDUCE. All example programs from the book can be downloaded via Internet. The emphasis throughout is on learning through worked examples. This will be an essential introduction and reference for high energy and theoretical physicists. (author)

Webcasts promote in-class active participation and learning in an engineering elective course

Science.gov (United States)

Freguia, Stefano

2017-09-01

This paper describes the design and outcomes of an educational intervention undertaken to improve the quality of delivery of a fourth-year engineering elective course - Industrial Wastewater and Solid Waste Management at the University of Queensland. The objective was to increase the level of active participation of students in planned active-learning classroom activities, including whole-class discussions and small group project-type work. According to a flipped classroom model, new online material in the form of webcasts was proposed to students before class. Students reacted very positively to the webcasts: the percentage of students viewing the webcast before planned workshop sessions ranged between 80% and 92% over the five weeks of the intervention. Enhanced engagement led also to increased attendance (85-92% at workshop sessions), and remarkable active participation in class (half of observed teams were ∼80% active). Remarkably, team performance as quantified by their report marks linearly correlated with the level of active participation in class.

Public meeting on radiation safety for industrial radiographerss: remarks, questions and answers at five NRC regional meetings

International Nuclear Information System (INIS)

1978-11-01

Over the past several years thenumber of radiation overexposures experienced in the radiography industry has been higher than for any other single group of NRC licensees. To inform radiography licensees of NRC's concern fo these recurring overexposure incidents, NRC staff representatives met with licensees in a series of five regional meetings. At these meetings the staff presented prepared remarks and answered questions on NRC regulations and operations. The main purposes of the meetings were to express NRC's concern for the high incidence of overexposures, and to open a line of communication between the NRC and radiography licensees in an effort to achieve the common goal of improved radiation safety. The remarks presented by the staff and subjects discussed at these meetings included: the purpose, scope, findings and goals of the NRC inspection program; ways and means of incorporating safety into radiography operations; and case histories of overexposure incidents, with highlights of the causes and possible preventions. At each of the regional meetings the staff received a request for a copy of the prepared remarks and a consolidation of the questions and answers that were discussed. This document includes that information, and a copy is being provided to each organizaion or firm attending the regional meetings. Requests for other copies should be made in accordance with the directions printed inside the front cover of this document

Extinction produces context inhibition and multiple-context extinction reduces response recovery in human predictive learning.

Science.gov (United States)

Glautier, Steven; Elgueta, Tito; Nelson, James Byron

2013-12-01

Two experiments with human participants were used to investigate recovery of an extinguished learned response after a context change using ABC designs. In an ABC design, the context changes over the three successive stages of acquisition (context A), extinction (context B), and test (context C). In both experiments, we found reduced recovery in groups that had extinction in multiple contexts, and that the extinction contexts acquired inhibitory strength. These results confirm those of previous investigations, that multiple-context extinction can produce less response recovery than single-context extinction, and they also provide new evidence for the involvement of contextual inhibitory processes in extinction in humans. The foregoing results are broadly in line with a protection-from-extinction account of response recovery. Yet, despite the fact that we detected contextual inhibition, predictions based on protection-from-extinction were not fully reliable for the single- and multiple-context group differences that we observed in (1) rates of extinction and (2) the strength of context inhibition. Thus, although evidence was obtained for a protection-from-extinction account of response recovery, this account can not explain all of the data.

A Brief History of the Most Remarkable Numbers "e," "i" and "?" in Mathematical Sciences with Applications

Science.gov (United States)

Debnath, Lokenath

2015-01-01

This paper deals with a brief history of the most remarkable Euler numbers "e,"?"i"?and?"?" in mathematical sciences. Included are many properties of the constants "e,"?"i"?and?"?" and their applications in algebra, geometry, physics, chemistry, ecology, business and industry. Special…

Rats with congenital learned helplessness respond less to sucrose but show no deficits in activity or learning.

Science.gov (United States)

Vollmayr, Barbara; Bachteler, Daniel; Vengeliene, Valentina; Gass, Peter; Spanagel, Rainer; Henn, Fritz

2004-04-02

Inbred rat strains for congenital learned helplessness (cLH) and for congenital resistance to learned helplessness (cNLH) were investigated as a model to study genetic predisposition to major depression. Congenitally helpless rats respond less to sucrose under a progressive ratio schedule. This is not confounded by locomotor hypoactivity: in contrast, cLH rats show a slight hyperactivity during the first 5 min of an open field test. cLH rats acquire operant responding to sucrose as readily as cNLH rats and exhibit normal memory acquisition and retrieval in the Morris water maze, thus ruling out general learning deficits as the cause of the decreased response to sucrose. Reduced total responses and reduced breaking points for sucrose in the cLH strain argue for anhedonia, which is an analogue to loss of pleasure essential for the diagnosis of major depressive episodes, and thus confirm the validity of congenitally learned helpless rats as a model of major depression.

Fastest learning in small-world neural networks

International Nuclear Information System (INIS)

Simard, D.; Nadeau, L.; Kroeger, H.

2005-01-01

We investigate supervised learning in neural networks. We consider a multi-layered feed-forward network with back propagation. We find that the network of small-world connectivity reduces the learning error and learning time when compared to the networks of regular or random connectivity. Our study has potential applications in the domain of data-mining, image processing, speech recognition, and pattern recognition

Learning of grammar-like visual sequences by adults with and without language-learning disabilities.

Science.gov (United States)

Aguilar, Jessica M; Plante, Elena

2014-08-01

Two studies examined learning of grammar-like visual sequences to determine whether a general deficit in statistical learning characterizes this population. Furthermore, we tested the hypothesis that difficulty in sustaining attention during the learning task might account for differences in statistical learning. In Study 1, adults with normal language (NL) or language-learning disability (LLD) were familiarized with the visual artificial grammar and then tested using items that conformed or deviated from the grammar. In Study 2, a 2nd sample of adults with NL and LLD were presented auditory word pairs with weak semantic associations (e.g., groom + clean) along with the visual learning task. Participants were instructed to attend to visual sequences and to ignore the auditory stimuli. Incidental encoding of these words would indicate reduced attention to the primary task. In Studies 1 and 2, both groups demonstrated learning and generalization of the artificial grammar. In Study 2, neither the NL nor the LLD group appeared to encode the words presented during the learning phase. The results argue against a general deficit in statistical learning for individuals with LLD and demonstrate that both NL and LLD learners can ignore extraneous auditory stimuli during visual learning.

Teletandem between French and Brazilian students: Some preliminary remarks

Directory of Open Access Journals (Sweden)

Liliane SANTOS

2015-12-01

Full Text Available ABSTRACT In its French-Brazilian version, the Teletandem Brazil project enables students from the University of Lille 3 (France and from the State University of São Paulo (Unesp, Brazil, to take part in online exchanges, based on the principles of autonomy and reciprocity. In this work, we will present some preliminary remarks on the construction of cultural identity representations by the students who took part in the project, from 2006 to 2012, the specificity of the exchanges we analyze being that most of the French students involved in them are third generation Portuguese. We will examine the consequences of the introduction of a third culture within exchanges which, linguistically speaking, are bilateral. The French students are often experiencing conflicting feelings toward Brazil and, similarly, the Brazilian students may have conflicting feelings towards Portugal and France. Our preliminary results show that the most successful linguistic exchanges occur when students face their own cultural identity with no feeling of superiority or inferiority.

Remark on state vector construction when flavor mixing exists

International Nuclear Information System (INIS)

Fujii, K.; Shimomura, T.

2006-01-01

In the framework of quantum field theory, we consider the way to construct the one-particle state (with definite 3-momentum) when particle mixing exists, such as in the case of flavor-neutrino mixing. In the preceding report (Prog. Theor. Phys. 112, 901 (2004)), we have examined the structure of expectation values of the flavor neutrino charges (at time t) with respect to a neutrino-source state prepared at time t' (earlier than t). When there is no mixing, each of various contributions to the expectation value is equal, in its dominant part, to the transition probability corresponding to the respective neutrino-production process. On the basis of the assumption that such an equality holds also in the mixing case, we can find an appropriate form of one-flavor-neutrino state with 3-momentum and helicity. Along the same way, we examine the boson case when flavor mixing exists. We give remarks on the relation and difference between the ordinary and the present approaches to flavor oscillation

Syntactic learning by mere exposure--an ERP study in adult learners.

Science.gov (United States)

Mueller, Jutta L; Oberecker, Regine; Friederici, Angela D

2009-07-29

Artificial language studies have revealed the remarkable ability of humans to extract syntactic structures from a continuous sound stream by mere exposure. However, it remains unclear whether the processes acquired in such tasks are comparable to those applied during normal language processing. The present study compares the ERPs to auditory processing of simple Italian sentences in native and non-native speakers after brief exposure to Italian sentences of a similar structure. The sentences contained a non-adjacent dependency between an auxiliary and the morphologically marked suffix of the verb. Participants were presented four alternating learning and testing phases. During learning phases only correct sentences were presented while during testing phases 50 percent of the sentences contained a grammatical violation. The non-native speakers successfully learned the dependency and displayed an N400-like negativity and a subsequent anteriorily distributed positivity in response to rule violations. The native Italian group showed an N400 followed by a P600 effect. The presence of the P600 suggests that native speakers applied a grammatical rule. In contrast, non-native speakers appeared to use a lexical form-based processing strategy. Thus, the processing mechanisms acquired in the language learning task were only partly comparable to those applied by competent native speakers.

Syntactic learning by mere exposure - An ERP study in adult learners

Science.gov (United States)

Mueller, Jutta L; Oberecker, Regine; Friederici, Angela D

2009-01-01

Background Artificial language studies have revealed the remarkable ability of humans to extract syntactic structures from a continuous sound stream by mere exposure. However, it remains unclear whether the processes acquired in such tasks are comparable to those applied during normal language processing. The present study compares the ERPs to auditory processing of simple Italian sentences in native and non-native speakers after brief exposure to Italian sentences of a similar structure. The sentences contained a non-adjacent dependency between an auxiliary and the morphologically marked suffix of the verb. Participants were presented four alternating learning and testing phases. During learning phases only correct sentences were presented while during testing phases 50 percent of the sentences contained a grammatical violation. Results The non-native speakers successfully learned the dependency and displayed an N400-like negativity and a subsequent anteriorily distributed positivity in response to rule violations. The native Italian group showed an N400 followed by a P600 effect. Conclusion The presence of the P600 suggests that native speakers applied a grammatical rule. In contrast, non-native speakers appeared to use a lexical form-based processing strategy. Thus, the processing mechanisms acquired in the language learning task were only partly comparable to those applied by competent native speakers. PMID:19640301

Management of the learning curve

DEFF Research Database (Denmark)

Pedersen, Peter-Christian; Slepniov, Dmitrij

2016-01-01

Purpose – This paper focuses on the management of the learning curve in overseas capacity expansions. The purpose of this paper is to unravel the direct as well as indirect influences on the learning curve and to advance the understanding of how these affect its management. Design...... the dimensions of the learning process involved in a capacity expansion project and identified the direct and indirect labour influences on the production learning curve. On this basis, the study proposes solutions to managing learning curves in overseas capacity expansions. Furthermore, the paper concludes...... with measures that have the potential to significantly reduce the non-value-added time when establishing new capacities overseas. Originality/value – The paper uses a longitudinal in-depth case study of a Danish wind turbine manufacturer and goes beyond a simplistic treatment of the lead time and learning...

Anti-ceramidase LCL385 acutely reduces BCL-2 expression in the hippocampus but is not associated with an increase of learned helplessness in rats.

Science.gov (United States)

Nahas, Ziad; Jiang, Yan; Zeidan, Youssef H; Bielawska, Alicja; Szulc, Zdzislaw; Devane, Lindsay; Kalivas, Peter; Hannun, Yusuf A

2009-01-30

Evidence from in situ studies supports the role of anti-apoptotic factors in the antidepressant responses of certain psychotropics. The availability of anti-ceramidase pro-apoptocic compound (LCL385) provides an opportunity to test in vivo the relation between hippocampal apopotosis and learned helplessness. 40 Sprague-Dawley male rodents underwent an FST after a treatment with LCL385, desipramine (DMI), or placebo (SAL) over 3 days. Behavioral responses, including immobility, swimming and climbing were counted during the 6min test. Western blot labeling was used to detect anti-apoptosis in hippocampus. DMI alone was associated with reduced immobility and increased climbing whereas LCL385 alone showed a decrease in Bcl-2/beta-actin ratio. Direct modulation of Bcl-2 expression in the hippocampus is not associated with learned helplessness in stressed rats. Three-day administration of DMI and LCL385 show divergent effects on behavioral and anti-apoptotic measures.

Approximate kernel competitive learning.

Science.gov (United States)

Wu, Jian-Sheng; Zheng, Wei-Shi; Lai, Jian-Huang

2015-03-01

Kernel competitive learning has been successfully used to achieve robust clustering. However, kernel competitive learning (KCL) is not scalable for large scale data processing, because (1) it has to calculate and store the full kernel matrix that is too large to be calculated and kept in the memory and (2) it cannot be computed in parallel. In this paper we develop a framework of approximate kernel competitive learning for processing large scale dataset. The proposed framework consists of two parts. First, it derives an approximate kernel competitive learning (AKCL), which learns kernel competitive learning in a subspace via sampling. We provide solid theoretical analysis on why the proposed approximation modelling would work for kernel competitive learning, and furthermore, we show that the computational complexity of AKCL is largely reduced. Second, we propose a pseudo-parallelled approximate kernel competitive learning (PAKCL) based on a set-based kernel competitive learning strategy, which overcomes the obstacle of using parallel programming in kernel competitive learning and significantly accelerates the approximate kernel competitive learning for large scale clustering. The empirical evaluation on publicly available datasets shows that the proposed AKCL and PAKCL can perform comparably as KCL, with a large reduction on computational cost. Also, the proposed methods achieve more effective clustering performance in terms of clustering precision against related approximate clustering approaches. Copyright © 2014 Elsevier Ltd. All rights reserved.

Neuropsychology of reward learning and negative symptoms in schizophrenia.

Science.gov (United States)

Nestor, Paul G; Choate, Victoria; Niznikiewicz, Margaret; Levitt, James J; Shenton, Martha E; McCarley, Robert W

2014-11-01

We used the Iowa Gambling Test (IGT) to examine the relationship of reward learning to both neuropsychological functioning and symptom formation in 65 individuals with schizophrenia. Results indicated that compared to controls, participants with schizophrenia showed significantly reduced reward learning, which in turn correlated with reduced intelligence, memory and executive function, and negative symptoms. The current findings suggested that a disease-related disturbance in reward learning may underlie both cognitive and motivation deficits, as expressed by neuropsychological impairment and negative symptoms in schizophrenia. Copyright © 2014 Elsevier B.V. All rights reserved.

The remarkably high excitation planetary nebula GC 6537.

Science.gov (United States)

Aller, L H; Hung, S; Feibelman, W A

1999-05-11

NGC 6537 is an unusually high excitation point symmetric planetary nebula with a rich spectrum. Its kinematical structures are of special interest. We are here primarily concerned with the high resolution spectrum as revealed by the Hamilton echelle Spectrograph at Lick Observatory (resolution approximately 0.2 A) and supplemented by UV and near-UV data. These extensive data permit a determination of interstellar extinction, plasma diagnostics, and ionic concentrations. The photoionization models that have been used successfully for many planetary nebulae are not entirely satisfactory here. The plasma electron temperature of a photoionization model cannot much exceed 20,000 K, but plasma diagnostics show that regions emitting radiation of highly ionized atoms such as [NeIV] and [NeV] are much hotter, showing that shock excitation must be important, as suggested by the remarkable kinematics of this object. Hence, instead of employing a strict photoionization model, we are guided by the nebular diagnostics, which reveal how electron temperature varies with ionization potential and accommodates density effects. The predictions of the photoionization model may be useful in estimating ionization correction factor. In effect, we have estimated the chemical composition by using both photoionization and shock considerations.

Column-Oriented Storage Techniques for MapReduce

OpenAIRE

Floratou, Avrilia; Patel, Jignesh; Shekita, Eugene; Tata, Sandeep

2011-01-01

Users of MapReduce often run into performance problems when they scale up their workloads. Many of the problems they encounter can be overcome by applying techniques learned from over three decades of research on parallel DBMSs. However, translating these techniques to a MapReduce implementation such as Hadoop presents unique challenges that can lead to new design choices. This paper describes how column-oriented storage techniques can be incorporated in Hadoop in a way that preserves its pop...

Learning to classify wakes from local sensory information

Science.gov (United States)

Alsalman, Mohamad; Colvert, Brendan; Kanso, Eva; Kanso Team

2017-11-01

Aquatic organisms exhibit remarkable abilities to sense local flow signals contained in their fluid environment and to surmise the origins of these flows. For example, fish can discern the information contained in various flow structures and utilize this information for obstacle avoidance and prey tracking. Flow structures created by flapping and swimming bodies are well characterized in the fluid dynamics literature; however, such characterization relies on classical methods that use an external observer to reconstruct global flow fields. The reconstructed flows, or wakes, are then classified according to the unsteady vortex patterns. Here, we propose a new approach for wake identification: we classify the wakes resulting from a flapping airfoil by applying machine learning algorithms to local flow information. In particular, we simulate the wakes of an oscillating airfoil in an incoming flow, extract the downstream vorticity information, and train a classifier to learn the different flow structures and classify new ones. This data-driven approach provides a promising framework for underwater navigation and detection in application to autonomous bio-inspired vehicles.

Sodium Valproate Withdrawal Correlates with Reduced Aggression

Science.gov (United States)

Pritchard, Duncan; Hoerger, Marguerite; Dyer, Tim; Graham, Nicola; Penney, Heather; Mace, F. Charles

2014-01-01

People with learning disabilities are sometimes prescribed psychotropic medication to help manage their challenging behaviour. This case study describes how a multicomponent behavioural intervention in conjunction with the systematic withdrawal of sodium valproate was strongly correlated with reduced aggression. No symptoms of bipolar disorder or…

Gaussian Processes for Data-Efficient Learning in Robotics and Control.

Science.gov (United States)

Deisenroth, Marc Peter; Fox, Dieter; Rasmussen, Carl Edward

2015-02-01

Autonomous learning has been a promising direction in control and robotics for more than a decade since data-driven learning allows to reduce the amount of engineering knowledge, which is otherwise required. However, autonomous reinforcement learning (RL) approaches typically require many interactions with the system to learn controllers, which is a practical limitation in real systems, such as robots, where many interactions can be impractical and time consuming. To address this problem, current learning approaches typically require task-specific knowledge in form of expert demonstrations, realistic simulators, pre-shaped policies, or specific knowledge about the underlying dynamics. In this paper, we follow a different approach and speed up learning by extracting more information from data. In particular, we learn a probabilistic, non-parametric Gaussian process transition model of the system. By explicitly incorporating model uncertainty into long-term planning and controller learning our approach reduces the effects of model errors, a key problem in model-based learning. Compared to state-of-the art RL our model-based policy search method achieves an unprecedented speed of learning. We demonstrate its applicability to autonomous learning in real robot and control tasks.

Reducing the Risk of Methadone Overdose

Centers for Disease Control (CDC) Podcasts

2012-07-03

This podcast is based on the July 2012 CDC Vital Signs report. Approximately 14 people die every day of overdoses related to methadone. Listen to learn how to reduce your risk of an overdose.  Created: 7/3/2012 by Centers for Disease Control and Prevention (CDC).   Date Released: 7/3/2012.

Concluding remarks and outlook: Europhysics conference on flavor-mixing in weak interactions

International Nuclear Information System (INIS)

Chau, L.L.

1984-01-01

Some comments are offered on the present knowledge of the mixing matrix of Kobayashi and Maskawa and of the dynamics of nonleptonic decay. Also, remarks are made concerning CP violation. Plans for research from 1984 to 1989 are listed briefly. The history of studies on weak interactions is briefly reviewed, and several unanswered questions are stated, such as where are the truth particles, how may they be discovered, what is the mass-generating mechanism for the gauge bosons, how many Z 0 's and W's are there, do neutrinos have mass, and how long do protons live

A Remarkable Collection of Rare Scriptures in a Small University Library Setting

Directory of Open Access Journals (Sweden)

Teresa Cardin Ellis

2013-04-01

Full Text Available Hardin-Simmons University was given two remarkable collections of rare Bibles and a Sefer Torah with the expressed desire of the donors for the collections to be shared with students, faculty and other constituencies of the university's Richardson Library. The library has tried to fulfill this request while attempting to preserve these treasures for future generations. As small university, without a trained archivist or preservationist, we have utilized resources outside our library and contiue to pursue sources to assist us in the maintenance of these special collections while still engaging them in the educational process.

Applying lessons learned to enhance human performance and reduce human error for ISS operations

Energy Technology Data Exchange (ETDEWEB)

Nelson, W.R.

1998-09-01

A major component of reliability, safety, and mission success for space missions is ensuring that the humans involved (flight crew, ground crew, mission control, etc.) perform their tasks and functions as required. This includes compliance with training and procedures during normal conditions, and successful compensation when malfunctions or unexpected conditions occur. A very significant issue that affects human performance in space flight is human error. Human errors can invalidate carefully designed equipment and procedures. If certain errors combine with equipment failures or design flaws, mission failure or loss of life can occur. The control of human error during operation of the International Space Station (ISS) will be critical to the overall success of the program. As experience from Mir operations has shown, human performance plays a vital role in the success or failure of long duration space missions. The Department of Energy`s Idaho National Engineering and Environmental Laboratory (INEEL) is developed a systematic approach to enhance human performance and reduce human errors for ISS operations. This approach is based on the systematic identification and evaluation of lessons learned from past space missions such as Mir to enhance the design and operation of ISS. This paper describes previous INEEL research on human error sponsored by NASA and how it can be applied to enhance human reliability for ISS.

Cognitive emotion regulation enhances aversive prediction error activity while reducing emotional responses.

Science.gov (United States)

Mulej Bratec, Satja; Xie, Xiyao; Schmid, Gabriele; Doll, Anselm; Schilbach, Leonhard; Zimmer, Claus; Wohlschläger, Afra; Riedl, Valentin; Sorg, Christian

2015-12-01

Cognitive emotion regulation is a powerful way of modulating emotional responses. However, despite the vital role of emotions in learning, it is unknown whether the effect of cognitive emotion regulation also extends to the modulation of learning. Computational models indicate prediction error activity, typically observed in the striatum and ventral tegmental area, as a critical neural mechanism involved in associative learning. We used model-based fMRI during aversive conditioning with and without cognitive emotion regulation to test the hypothesis that emotion regulation would affect prediction error-related neural activity in the striatum and ventral tegmental area, reflecting an emotion regulation-related modulation of learning. Our results show that cognitive emotion regulation reduced emotion-related brain activity, but increased prediction error-related activity in a network involving ventral tegmental area, hippocampus, insula and ventral striatum. While the reduction of response activity was related to behavioral measures of emotion regulation success, the enhancement of prediction error-related neural activity was related to learning performance. Furthermore, functional connectivity between the ventral tegmental area and ventrolateral prefrontal cortex, an area involved in regulation, was specifically increased during emotion regulation and likewise related to learning performance. Our data, therefore, provide first-time evidence that beyond reducing emotional responses, cognitive emotion regulation affects learning by enhancing prediction error-related activity, potentially via tegmental dopaminergic pathways. Copyright © 2015 Elsevier Inc. All rights reserved.

Implementation of a smartphone as a wireless gyroscope platform for quantifying reduced arm swing in hemiplegie gait with machine learning classification by multilayer perceptron neural network.

Science.gov (United States)

LeMoyne, Robert; Mastroianni, Timothy

2016-08-01

Natural gait consists of synchronous and rhythmic patterns for both the lower and upper limb. People with hemiplegia can experience reduced arm swing, which can negatively impact the quality of gait. Wearable and wireless sensors, such as through a smartphone, have demonstrated the ability to quantify various features of gait. With a software application the smartphone (iPhone) can function as a wireless gyroscope platform capable of conveying a gyroscope signal recording as an email attachment by wireless connectivity to the Internet. The gyroscope signal recordings of the affected hemiplegic arm with reduced arm swing arm and the unaffected arm are post-processed into a feature set for machine learning. Using a multilayer perceptron neural network a considerable degree of classification accuracy is attained to distinguish between the affected hemiplegic arm with reduced arm swing arm and the unaffected arm.

Improving Neuromuscular Monitoring and Reducing Residual Neuromuscular Blockade With E-Learning

DEFF Research Database (Denmark)

Thomsen, Jakob Louis Demant; Mathiesen, Ole; Hägi-Pedersen, Daniel

2017-01-01

BACKGROUND: Muscle relaxants facilitate endotracheal intubation under general anesthesia and improve surgical conditions. Residual neuromuscular blockade occurs when the patient is still partially paralyzed when awakened after surgery. The condition is associated with subjective discomfort and an......-learning module can increase anesthetists' use of neuromuscular monitoring. TRIAL REGISTRATION: Clinicaltrials.gov NCT02925143; https://clinicaltrials.gov/ct2/show/NCT02925143 (Archived by WebCite® at http://www.webcitation.org/6s50iTV2x)....

Opening Remarks of the Acquisition Path Analysis Methodology Session

International Nuclear Information System (INIS)

Renis, T.

2015-01-01

An overview of the recent development work that has been done on acquisition path analysis, implementation of the methodologies within the Department of Safeguards, lessons learned and future areas for development will be provided. (author)

Access to oral health care services among adults with learning disabilities: a scoping review.

Science.gov (United States)

Naseem, Mustafa; Shah, Altaf H; Khiyani, Muhammad Faheem; Khurshid, Zohaib; Zafar, Muhammad Sohail; Gulzar, Shabnam; AlJameel, AlBandary H; Khalil, Hesham S

2016-01-01

The prevalence of oral diseases including dental caries and periodontal conditions is remarkably higher in people with disabilities. The provision of accessible oral health services for people with learning disabilities may be challenging. The objectives of the review were to identify barriers in accessing oral health care that persists within society, enabling or disabling people with learning disabilities. Using the Arksey O'Malley framework, a scoping review was conducted on PubMed/Medline, OVIDSP, and EMBASE. Studies were evaluated and short-listed based on the inclusion criteria, which consisted of: (1) study participants or population with learning disabilities, (2) aged 16 years or over, (3) reporting on access to oral health services, (4) published in the English language. Those that justified the inclusion criteria were carefully chosen after a blind peer-reviewed process when relevance and quality were debated. Nine studies were eventually included from searches. Tabulation of data was done under the heading of study type, outcomes, the year of publication and patient selection. The majority of studies provided a biomedical overview of access for adults with learning disabilities. The concept of access for people with disability is still ill-defined and obscure. Access to oral health care and needs of people with learning disabilities are complex and multi-facet.

Neuropsychology of Reward Learning and Negative Symptoms in Schizophrenia

OpenAIRE

Nestor, Paul G.; Choate, Victoria; Niznikiewicz, Margaret; Levitt, James J.; Shenton, Martha E; McCarley, Robert W.

2014-01-01

We used the Iowa Gambling Test (IGT) to examine the relationship of reward learning to both neuropsychological functioning and symptom formation in 65 individuals with schizophrenia. Results indicated that compared to controls, participants with schizophrenia showed significantly reduced reward learning, which in turn correlated with reduced intelligence, memory and executive function, and increased negative symptoms. The current findings suggested that a disease-related disturbance in reward...

Syntactic learning by mere exposure – An ERP study in adult learners

Directory of Open Access Journals (Sweden)

Friederici Angela D

2009-07-01

Full Text Available Abstract Background Artificial language studies have revealed the remarkable ability of humans to extract syntactic structures from a continuous sound stream by mere exposure. However, it remains unclear whether the processes acquired in such tasks are comparable to those applied during normal language processing. The present study compares the ERPs to auditory processing of simple Italian sentences in native and non-native speakers after brief exposure to Italian sentences of a similar structure. The sentences contained a non-adjacent dependency between an auxiliary and the morphologically marked suffix of the verb. Participants were presented four alternating learning and testing phases. During learning phases only correct sentences were presented while during testing phases 50 percent of the sentences contained a grammatical violation. Results The non-native speakers successfully learned the dependency and displayed an N400-like negativity and a subsequent anteriorily distributed positivity in response to rule violations. The native Italian group showed an N400 followed by a P600 effect. Conclusion The presence of the P600 suggests that native speakers applied a grammatical rule. In contrast, non-native speakers appeared to use a lexical form-based processing strategy. Thus, the processing mechanisms acquired in the language learning task were only partly comparable to those applied by competent native speakers.

Machine Learning and Data Mining Methods in Diabetes Research.

Science.gov (United States)

Kavakiotis, Ioannis; Tsave, Olga; Salifoglou, Athanasios; Maglaveras, Nicos; Vlahavas, Ioannis; Chouvarda, Ioanna

2017-01-01

The remarkable advances in biotechnology and health sciences have led to a significant production of data, such as high throughput genetic data and clinical information, generated from large Electronic Health Records (EHRs). To this end, application of machine learning and data mining methods in biosciences is presently, more than ever before, vital and indispensable in efforts to transform intelligently all available information into valuable knowledge. Diabetes mellitus (DM) is defined as a group of metabolic disorders exerting significant pressure on human health worldwide. Extensive research in all aspects of diabetes (diagnosis, etiopathophysiology, therapy, etc.) has led to the generation of huge amounts of data. The aim of the present study is to conduct a systematic review of the applications of machine learning, data mining techniques and tools in the field of diabetes research with respect to a) Prediction and Diagnosis, b) Diabetic Complications, c) Genetic Background and Environment, and e) Health Care and Management with the first category appearing to be the most popular. A wide range of machine learning algorithms were employed. In general, 85% of those used were characterized by supervised learning approaches and 15% by unsupervised ones, and more specifically, association rules. Support vector machines (SVM) arise as the most successful and widely used algorithm. Concerning the type of data, clinical datasets were mainly used. The title applications in the selected articles project the usefulness of extracting valuable knowledge leading to new hypotheses targeting deeper understanding and further investigation in DM.

Engaging Students' Learning Through a Blended Environment

Directory of Open Access Journals (Sweden)

Andrew Stuart

2013-05-01

Full Text Available Within the furniture manufacturing industry a high proportion of occupational accidents are as a result of non-compliance to machining regulations and incorrect work practices. Safety training plays an important role in reducing accidents and promoting a safety culture within this sector. This article details an action research study undertaken during the first year of a new Degree in Timber Product Technology, which set out to evaluate the impact a blended learning environment and reusable learning objects (RLOs could have on promoting safe work practices and a safety culture amongst students. A constructivist approach was taken and the module design was underpinned by Kolb’s model of experiential learning, placing more responsibility on the learners for their own learning and encouraging them to reflect upon their experiences. The findings of this study suggest that students with prior industry machining experience required a change in their attitude to machining which was achieved within the practical labs, while students with no machining experiences were intimidated by the learning environment in the practical labs but whose learning experience was enhanced through the use of RLOs and other eLearning resources. In order to reduce occupational accidents in the furniture manufacturing industry the promotion of continuing professional development (CPD training courses is required in order to change workers’ behaviour to machine safety and encourage lifelong learning so as to promote a safety culture within the furniture manufacturing industry.

The influence of serotonin on fear learning.

Directory of Open Access Journals (Sweden)

Catherine Hindi Attar

Full Text Available Learning of associations between aversive stimuli and predictive cues is the basis of Pavlovian fear conditioning and is driven by a mismatch between expectation and outcome. To investigate whether serotonin modulates the formation of such aversive cue-outcome associations, we used functional magnetic resonance imaging (fMRI and dietary tryptophan depletion to reduce brain serotonin (5-HT levels in healthy human subjects. In a Pavlovian fear conditioning paradigm, 5-HT depleted subjects compared to a non-depleted control group exhibited attenuated autonomic responses to cues indicating the upcoming of an aversive event. These results were closely paralleled by reduced aversive learning signals in the amygdala and the orbitofrontal cortex, two prominent structures of the neural fear circuit. In agreement with current theories of serotonin as a motivational opponent system to dopamine in fear learning, our data provide first empirical evidence for a role of serotonin in representing formally derived learning signals for aversive events.

Eliciting explanations: Constraints on when self-explanation aids learning.

Science.gov (United States)

Rittle-Johnson, Bethany; Loehr, Abbey M

2017-10-01

Generating explanations for oneself in an attempt to make sense of new information (i.e., self-explanation) is often a powerful learning technique. Despite its general effectiveness, in a growing number of studies, prompting for self-explanation improved some aspects of learning, but reduced learning of other aspects. Drawing on this recent research, as well as on research comparing self-explanation under different conditions, we propose four constraints on the effectiveness of self-explanation. First, self-explanation promotes attention to particular types of information, so it is better suited to promote particular learning outcomes in particular types of domains, such as transfer in domains guided by general principles or heuristics. Second, self-explaining a variety of types of information can improve learning, but explaining one's own solution methods or choices may reduce learning under certain conditions. Third, explanation prompts focus effort on particular aspects of the to-be-learned material, potentially drawing effort away from other important information. Explanation prompts must be carefully designed to align with target learning outcomes. Fourth, prompted self-explanation often promotes learning better than unguided studying, but alternative instructional techniques may be more effective under some conditions. Attention to these constraints should optimize the effectiveness of self-explanation as an instructional technique in future research and practice.

Reactive behavior, learning, and anticipation

Science.gov (United States)

Whitehead, Steven D.; Ballard, Dana H.

1989-01-01

Reactive systems always act, thinking only long enough to 'look up' the action to execute. Traditional planning systems think a lot, and act only after generating fairly precise plans. Each represents an endpoint on a spectrum. It is argued that primitive forms of reasoning, like anticipation, play an important role in reducing the cost of learning and that the decision to act or think should be based on the uncertainty associated with the utility of executing an action in a particular situation. An architecture for an adaptable reactive system is presented and it is shown how it can be augmented with a simple anticipation mechanism that can substantially reduce the cost and time of learning.

Concluding Remarks: The Current Status and Future Prospects for GRB Astronomy

Science.gov (United States)

Gehrels, Neil

2009-01-01

We are in a remarkable period of discovery in GRB astronomy. The current satellites including Swift, Fermi. AGILE and INTEGRAL are detecting and observing bursts of all varieties. Increasing capabilities for follow-up observations on the ground and in space are leading to rapid and deep coverage across the electromagnetic spectrum, The future will see continued operation of the current experiments and with future missions like SVOM plus possible rni_Ssions like JANUS and EXIST. An exciting expansion of capabilities is occurring in areas of gravitational waves and neutrinos that could open new windows on the GRB phenomenon. Increased IR capabilities on the ground and with missions like JWST will enable further exploration of high redshift bursts. The future is bright.

On the remarkable spectrum of a non-Hermitian random matrix model

International Nuclear Information System (INIS)

Holz, D E; Orland, H; Zee, A

2003-01-01

A non-Hermitian random matrix model proposed a few years ago has a remarkably intricate spectrum. Various attempts have been made to understand the spectrum, but even its dimension is not known. Using the Dyson-Schmidt equation, we show that the spectrum consists of a non-denumerable set of lines in the complex plane. Each line is the support of the spectrum of a periodic Hamiltonian, obtained by the infinite repetition of any finite sequence of the disorder variables. Our approach is based on the 'theory of words'. We make a complete study of all four-letter words. The spectrum is complicated because our matrix contains everything that will ever be written in the history of the universe, including this particular paper

Deep Learning Microscopy

KAUST Repository

Rivenson, Yair

2017-05-12

We demonstrate that a deep neural network can significantly improve optical microscopy, enhancing its spatial resolution over a large field-of-view and depth-of-field. After its training, the only input to this network is an image acquired using a regular optical microscope, without any changes to its design. We blindly tested this deep learning approach using various tissue samples that are imaged with low-resolution and wide-field systems, where the network rapidly outputs an image with remarkably better resolution, matching the performance of higher numerical aperture lenses, also significantly surpassing their limited field-of-view and depth-of-field. These results are transformative for various fields that use microscopy tools, including e.g., life sciences, where optical microscopy is considered as one of the most widely used and deployed techniques. Beyond such applications, our presented approach is broadly applicable to other imaging modalities, also spanning different parts of the electromagnetic spectrum, and can be used to design computational imagers that get better and better as they continue to image specimen and establish new transformations among different modes of imaging.

Student-oriented learning outlines: a valuable supplement to traditional instruction.

Science.gov (United States)

VanArsdale, S K; Hammons, J O

1998-01-01

In a time of changing health care and funding restraints in institutions, continuing education and staff development departments are being challenged to produce better prepared nurses at reduced costs per employee. Improvements in how nurses are prepared are needed to ensure higher levels of competence without increasing the cost. This article describes the development and use of a practical strategy for mastery learning known as Student-Oriented Learning Outlines or SOLOs. This approach has been found to be effective in producing improvements in learning and ultimately patient care while reducing cost to the institution.

Not Utilized Learning Potentials

DEFF Research Database (Denmark)

Kragelund, Linda

2007-01-01

  When the Danish Nursing Education in 2002 became a Bachelor Degree the clinical part of the education was reduced. Therefore, it was necessary to optimize learning in practice.       I made a qualitative investigation to describe student nurses' learning processes in non-routine situations where...... they interact with psychiatric patients. The theoretical framework includes primarily P. Jarvis' concept disjuncture and A. Heller's theory about everyday life. The empirical part of the study is primarily based on qualitative semi-structured interviews with, observations of and obser-views with a volunteer......-conscious disjuncture, in development of the concept pseudo-everyday life activities and in a categorizing mo­del for and a theory about student nurses' learning processes. The theory includes relations between 4 types of  disjuncture, 3 types of content in the learning processes, and factors that provoke...

Nicotine facilitates memory consolidation in perceptual learning.

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Beer, Anton L; Vartak, Devavrat; Greenlee, Mark W

2013-01-01

Perceptual learning is a special type of non-declarative learning that involves experience-dependent plasticity in sensory cortices. The cholinergic system is known to modulate declarative learning. In particular, reduced levels or efficacy of the neurotransmitter acetylcholine were found to facilitate declarative memory consolidation. However, little is known about the role of the cholinergic system in memory consolidation of non-declarative learning. Here we compared two groups of non-smoking men who learned a visual texture discrimination task (TDT). One group received chewing tobacco containing nicotine for 1 h directly following the TDT training. The other group received a similar tasting control substance without nicotine. Electroencephalographic recordings during substance consumption showed reduced alpha activity and P300 latencies in the nicotine group compared to the control group. When re-tested on the TDT the following day, both groups responded more accurately and more rapidly than during training. These improvements were specific to the retinal location and orientation of the texture elements of the TDT suggesting that learning involved early visual cortex. A group comparison showed that learning effects were more pronounced in the nicotine group than in the control group. These findings suggest that oral consumption of nicotine enhances the efficacy of nicotinic acetylcholine receptors. Our findings further suggest that enhanced efficacy of the cholinergic system facilitates memory consolidation in perceptual learning (and possibly other types of non-declarative learning). In that regard acetylcholine seems to affect consolidation processes in perceptual learning in a different manner than in declarative learning. Alternatively, our findings might reflect dose-dependent cholinergic modulation of memory consolidation. This article is part of a Special Issue entitled 'Cognitive Enhancers'. Copyright © 2012 Elsevier Ltd. All rights reserved.

Perceptual learning in Williams syndrome: looking beyond averages.

Directory of Open Access Journals (Sweden)

Patricia Gervan

Full Text Available Williams Syndrome is a genetically determined neurodevelopmental disorder characterized by an uneven cognitive profile and surprisingly large neurobehavioral differences among individuals. Previous studies have already shown different forms of memory deficiencies and learning difficulties in WS. Here we studied the capacity of WS subjects to improve their performance in a basic visual task. We employed a contour integration paradigm that addresses occipital visual function, and analyzed the initial (i.e. baseline and after-learning performance of WS individuals. Instead of pooling the very inhomogeneous results of WS subjects together, we evaluated individual performance by expressing it in terms of the deviation from the average performance of the group of typically developing subjects of similar age. This approach helped us to reveal information about the possible origins of poor performance of WS subjects in contour integration. Although the majority of WS individuals showed both reduced baseline and reduced learning performance, individual analysis also revealed a dissociation between baseline and learning capacity in several WS subjects. In spite of impaired initial contour integration performance, some WS individuals presented learning capacity comparable to learning in the typically developing population, and vice versa, poor learning was also observed in subjects with high initial performance levels. These data indicate a dissociation between factors determining initial performance and perceptual learning.

Active learning of Pareto fronts.

Science.gov (United States)

Campigotto, Paolo; Passerini, Andrea; Battiti, Roberto

2014-03-01

This paper introduces the active learning of Pareto fronts (ALP) algorithm, a novel approach to recover the Pareto front of a multiobjective optimization problem. ALP casts the identification of the Pareto front into a supervised machine learning task. This approach enables an analytical model of the Pareto front to be built. The computational effort in generating the supervised information is reduced by an active learning strategy. In particular, the model is learned from a set of informative training objective vectors. The training objective vectors are approximated Pareto-optimal vectors obtained by solving different scalarized problem instances. The experimental results show that ALP achieves an accurate Pareto front approximation with a lower computational effort than state-of-the-art estimation of distribution algorithms and widely known genetic techniques.

E-Learning Tutoring System for Sijil Pelajaran Malaysia (SPM English

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Mohd Yusof Munirah

2018-01-01

Full Text Available An E-Learning tutoring system for English (SPM is an e-learning platform for Sijil Pelajaran Malaysia English subject. E-learning is a web based application that supports the delivery of learning, skills and knowledge related to the English subject in SPM. E-learning use the technology to enable people to learn anytime and anywhere. Besides, it is developed with the purpose to evaluate student’s performance through an online quiz. Nowadays, tuition center have a lot of students, hence insufficient time to analyze the individual performance in learning English. In addition, e-learning is able to reduce the printing cost and administrative cost at the same time reducing usage of paper and printed materials associate in learning. The system developed by using Javascript and PHP language based on system prototyping methodology. The result will produce student’s performance in monthly quiz and teacher are able to monitor the performance of each students. Although the development or this e-learning is based on requirement gathered via tuition center, however it can be proposed to be by any learning center or to self-study. It is hoped that this e-learning will be able to improve student knowledge in English language and subsequently help student to obtain the best result in SPM by providing more guided references and practices.

The use of a mobile assistant learning system for health education based on project-based learning.

Science.gov (United States)

Wu, Ting-Ting

2014-10-01

With the development of mobile devices and wireless technology, mobile technology has gradually infiltrated nursing practice courses to facilitate instruction. Mobile devices save manpower and reduce errors while enhancing nursing students' professional knowledge and skills. To achieve teaching objectives and address the drawbacks of traditional education, this study presents a mobile assistant learning system to help nursing students prepare health education materials. The proposed system is based on a project-based learning strategy to assist nursing students with internalizing professional knowledge and developing critical thinking skills. Experimental results show that the proposed mobile system and project-based learning strategy can promote learning effectiveness and efficiency. Most nursing students and nursing educators showed positive attitudes toward this mobile learning system and looked forward to using it again in related courses in the future.

The Diamond Light Source and the challenges ahead for structural biology: some informal remarks.

Science.gov (United States)

Ramakrishnan, V

2015-03-06

The remarkable advances in structural biology in the past three decades have led to the determination of increasingly complex structures that lie at the heart of many important biological processes. Many of these advances have been made possible by the use of X-ray crystallography using synchrotron radiation. In this short article, some of the challenges and prospects that lie ahead will be summarized. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Opportunities for Socioemotional Learning in Music Classrooms

Science.gov (United States)

Jacobi, Bonnie S.

2012-01-01

The elementary music class is an ideal setting for building socioemotional skills in children. These skills can assist children in their early music learning through brain development, and they become increasingly important as students reach higher levels of musicianship. Socioemotional learning programs are currently being used to reduce at-risk…

Probabilistic Motor Sequence Yields Greater Offline and Less Online Learning than Fixed Sequence.

Science.gov (United States)

Du, Yue; Prashad, Shikha; Schoenbrun, Ilana; Clark, Jane E

2016-01-01

It is well acknowledged that motor sequences can be learned quickly through online learning. Subsequently, the initial acquisition of a motor sequence is boosted or consolidated by offline learning. However, little is known whether offline learning can drive the fast learning of motor sequences (i.e., initial sequence learning in the first training session). To examine offline learning in the fast learning stage, we asked four groups of young adults to perform the serial reaction time (SRT) task with either a fixed or probabilistic sequence and with or without preliminary knowledge (PK) of the presence of a sequence. The sequence and PK were manipulated to emphasize either procedural (probabilistic sequence; no preliminary knowledge (NPK)) or declarative (fixed sequence; with PK) memory that were found to either facilitate or inhibit offline learning. In the SRT task, there were six learning blocks with a 2 min break between each consecutive block. Throughout the session, stimuli followed the same fixed or probabilistic pattern except in Block 5, in which stimuli appeared in a random order. We found that PK facilitated the learning of a fixed sequence, but not a probabilistic sequence. In addition to overall learning measured by the mean reaction time (RT), we examined the progressive changes in RT within and between blocks (i.e., online and offline learning, respectively). It was found that the two groups who performed the fixed sequence, regardless of PK, showed greater online learning than the other two groups who performed the probabilistic sequence. The groups who performed the probabilistic sequence, regardless of PK, did not display online learning, as indicated by a decline in performance within the learning blocks. However, they did demonstrate remarkably greater offline improvement in RT, which suggests that they are learning the probabilistic sequence offline. These results suggest that in the SRT task, the fast acquisition of a motor sequence is driven

Punishment Insensitivity and Impaired Reinforcement Learning in Preschoolers

Science.gov (United States)

Briggs-Gowan, Margaret J.; Nichols, Sara R.; Voss, Joel; Zobel, Elvira; Carter, Alice S.; McCarthy, Kimberly J.; Pine, Daniel S.; Blair, James; Wakschlag, Lauren S.

2014-01-01

Background: Youth and adults with psychopathic traits display disrupted reinforcement learning. Advances in measurement now enable examination of this association in preschoolers. The current study examines relations between reinforcement learning in preschoolers and parent ratings of reduced responsiveness to socialization, conceptualized as a…

Seizure Classification From EEG Signals Using Transfer Learning, Semi-Supervised Learning and TSK Fuzzy System.

Science.gov (United States)

Jiang, Yizhang; Wu, Dongrui; Deng, Zhaohong; Qian, Pengjiang; Wang, Jun; Wang, Guanjin; Chung, Fu-Lai; Choi, Kup-Sze; Wang, Shitong

2017-12-01

Recognition of epileptic seizures from offline EEG signals is very important in clinical diagnosis of epilepsy. Compared with manual labeling of EEG signals by doctors, machine learning approaches can be faster and more consistent. However, the classification accuracy is usually not satisfactory for two main reasons: the distributions of the data used for training and testing may be different, and the amount of training data may not be enough. In addition, most machine learning approaches generate black-box models that are difficult to interpret. In this paper, we integrate transductive transfer learning, semi-supervised learning and TSK fuzzy system to tackle these three problems. More specifically, we use transfer learning to reduce the discrepancy in data distribution between the training and testing data, employ semi-supervised learning to use the unlabeled testing data to remedy the shortage of training data, and adopt TSK fuzzy system to increase model interpretability. Two learning algorithms are proposed to train the system. Our experimental results show that the proposed approaches can achieve better performance than many state-of-the-art seizure classification algorithms.

QUEST: Eliminating Online Supervised Learning for Efficient Classification Algorithms.

Science.gov (United States)

Zwartjes, Ardjan; Havinga, Paul J M; Smit, Gerard J M; Hurink, Johann L

2016-10-01

In this work, we introduce QUEST (QUantile Estimation after Supervised Training), an adaptive classification algorithm for Wireless Sensor Networks (WSNs) that eliminates the necessity for online supervised learning. Online processing is important for many sensor network applications. Transmitting raw sensor data puts high demands on the battery, reducing network life time. By merely transmitting partial results or classifications based on the sampled data, the amount of traffic on the network can be significantly reduced. Such classifications can be made by learning based algorithms using sampled data. An important issue, however, is the training phase of these learning based algorithms. Training a deployed sensor network requires a lot of communication and an impractical amount of human involvement. QUEST is a hybrid algorithm that combines supervised learning in a controlled environment with unsupervised learning on the location of deployment. Using the SITEX02 dataset, we demonstrate that the presented solution works with a performance penalty of less than 10% in 90% of the tests. Under some circumstances, it even outperforms a network of classifiers completely trained with supervised learning. As a result, the need for on-site supervised learning and communication for training is completely eliminated by our solution.

Strength of Temporal White Matter Pathways Predicts Semantic Learning.

Science.gov (United States)

Ripollés, Pablo; Biel, Davina; Peñaloza, Claudia; Kaufmann, Jörn; Marco-Pallarés, Josep; Noesselt, Toemme; Rodríguez-Fornells, Antoni

2017-11-15

Learning the associations between words and meanings is a fundamental human ability. Although the language network is cortically well defined, the role of the white matter pathways supporting novel word-to-meaning mappings remains unclear. Here, by using contextual and cross-situational word learning, we tested whether learning the meaning of a new word is related to the integrity of the language-related white matter pathways in 40 adults (18 women). The arcuate, uncinate, inferior-fronto-occipital and inferior-longitudinal fasciculi were virtually dissected using manual and automatic deterministic fiber tracking. Critically, the automatic method allowed assessing the white matter microstructure along the tract. Results demonstrate that the microstructural properties of the left inferior-longitudinal fasciculus predict contextual learning, whereas the left uncinate was associated with cross-situational learning. In addition, we identified regions of special importance within these pathways: the posterior middle temporal gyrus, thought to serve as a lexical interface and specifically related to contextual learning; the anterior temporal lobe, known to be an amodal hub for semantic processing and related to cross-situational learning; and the white matter near the hippocampus, a structure fundamental for the initial stages of new-word learning and, remarkably, related to both types of word learning. No significant associations were found for the inferior-fronto-occipital fasciculus or the arcuate. While previous results suggest that learning new phonological word forms is mediated by the arcuate fasciculus, these findings show that the temporal pathways are the crucial neural substrate supporting one of the most striking human abilities: our capacity to identify correct associations between words and meanings under referential indeterminacy. SIGNIFICANCE STATEMENT The language-processing network is cortically (i.e., gray matter) well defined. However, the role of the

Instructed fear learning, extinction, and recall: additive effects of cognitive information on emotional learning of fear.

Science.gov (United States)

Javanbakht, Arash; Duval, Elizabeth R; Cisneros, Maria E; Taylor, Stephan F; Kessler, Daniel; Liberzon, Israel

2017-08-01

The effects of instruction on learning of fear and safety are rarely studied. We aimed to examine the effects of cognitive information and experience on fear learning. Fourty healthy participants, randomly assigned to three groups, went through fear conditioning, extinction learning, and extinction recall with two conditioned stimuli (CS+). Information was presented about the presence or absence of conditioned stimulus-unconditioned stimulus (CS-US) contingency at different stages of the experiment. Information about the CS-US contingency prior to fear conditioning enhanced fear response and reduced extinction recall. Information about the absence of CS-US contingency promoted extinction learning and recall, while omission of this information prior to recall resulted in fear renewal. These findings indicate that contingency information can facilitate fear expression during fear learning, and can facilitate extinction learning and recall. Information seems to function as an element of the larger context in which conditioning occurs.

Optimal learning on climate change: why climate skeptics should reduce emissions

NARCIS (Netherlands)

van Wijnbergen, S.; Willems, T.

2015-01-01

Climate skeptics typically argue that the possibility that global warming is exogenous, implies that we should not take additional action towards reducing emissions until we know what drives warming. This paper however shows that even climate skeptics have an incentive to reduce emissions: such a

Chandra Sees Remarkable Eclipse of Black Hole

Science.gov (United States)

2007-04-01

A remarkable eclipse of a supermassive black hole and the hot gas disk around it has been observed with NASA's Chandra X-ray Observatory. This eclipse has allowed two key predictions about the effects of supermassive black holes to be tested. Just as eclipses of the Sun and moon give astronomers rare opportunities to learn about those objects, an alignment in a nearby galaxy has provided a rare opportunity to investigate a supermassive black hole. Illustrations of Black Hole Eclipse Illustrations of Black Hole Eclipse The supermassive black hole is located in NGC 1365, a galaxy 60 million light years from Earth. It contains a so called active galactic nucleus, or AGN. Scientists believe that the black hole at the center of the AGN is fed by a steady stream of material, presumably in the form of a disk. Material just about to fall into a black hole should be heated to millions of degrees before passing over the event horizon, or point of no return. The disk of gas around the central black hole in NGC 1365 produces copious X-rays but is much too small to resolve directly with a telescope. However, the disk was eclipsed by an intervening cloud, so observation of the time taken for the disk to go in and out of eclipse allowed scientists to estimate the size of the disk. Black Hole Animation Black Hole Animation "For years we've been struggling to confirm the size of this X-ray structure," said Guido Risaliti of the Harvard-Smithsonian Center for Astrophysics (CfA) in Cambridge, Mass, and the Italian Institute of Astronomy (INAF). "This serendipitous eclipse enabled us to make this breakthrough." The Chandra team directly measured the size of the X-ray source as about seven times the distance between the Sun and the Earth. That means the source of X-rays is about 2 billion times smaller than the host galaxy and only about 10 times larger than the estimated size of the black hole's event horizon, consistent with theoretical predictions. Chandra X-ray Image of NGC 1365

Optimal learning on climate change: why climate skeptics should reduce emissions

NARCIS (Netherlands)

van Wijnbergen, S.; Willems, T.

2012-01-01

Climate skeptics argue that the possibility that global warming is exogenous implies that we should not take additional action towards reducing greenhouse gas emissions until we know more. However this paper shows that even climate skeptics have an incentive to reduce emissions: such a change of

Comprehension of direct and indirect sarcastic remarks in children and adolescents with Tourette's syndrome.

Science.gov (United States)

Drury, Helena; Shah, Shivani; Stern, Jeremy S; Crawford, Sarah; Channon, Shelley

2018-05-01

Previous research has reported that aspects of social cognition such as nonliteral language comprehension are impaired in adults with Tourette's syndrome (TS), but little is known about social cognition in children and adolescents with TS. The present study aims to evaluate a measure of sarcasm comprehension suitable for use with children and adolescents (Experiment 1), and to examine sarcasm comprehension in children and adolescents with TS-alone or TS and attention deficit hyperactivity disorder (ADHD; Experiment 2). In Experiment 1, the measure of sarcasm comprehension was found to be sensitive to differences in nonliteral language comprehension for typically-developing children aged 10 to 11 years old compared to children aged 8 to 9 years old; the older group performed significantly better on the comprehension of scenarios ending with either direct or indirect sarcastic remarks, whereas the two age groups did not differ on the comprehension of scenarios ending with sincere remarks. In Experiment 2, both the TS-alone and TS+ADHD groups performed below the level of the control participants on the comprehension of indirect sarcasm items but not on the comprehension of direct sarcasm items and sincere items. Those with TS+ADHD also performed below the level of the control participants on measures of interference control and fluency. The findings are discussed with reference to the possible contribution of executive functioning and mentalizing to the patterns of performance.

Vicarious Neural Processing of Outcomes during Observational Learning

NARCIS (Netherlands)

Monfardini, Elisabetta; Gazzola, Valeria; Boussaoud, Driss; Brovelli, Andrea; Keysers, Christian; Wicker, Bruno

2013-01-01

Learning what behaviour is appropriate in a specific context by observing the actions of others and their outcomes is a key constituent of human cognition, because it saves time and energy and reduces exposure to potentially dangerous situations. Observational learning of associative rules relies on

On the Motivation and Foundation of Natural Time Analysis: Useful Remarks

Science.gov (United States)

Varotsos, Panayiotis A.; Sarlis, Nicholas V.; Skordas, Efthimios S.

2016-08-01

Since its introduction in 2001, natural time analysis has been applied to diverse fields with remarkable results. Its validity has not been doubted by any publication to date. Here, we indicate that frequently asked questions on the motivation and the foundation of natural time analysis are directly answered if one takes into account the following two key points that we have considered as widely accepted when natural time analysis was proposed: first, the aspects on the energy of a system forwarded by Max Planck in his Treatise on Thermodynamics; second, the theorem on the characteristic functions of probability distributions which Gauss called Ein Schönes Theorem der Wahrscheinlichkeitsrechnung (beautiful theorem of probability calculus). The case of the time series of earthquakes and of the precursory Seismic Electric Signals are discussed as typical examples.

Reduced brain-derived neurotrophic factor expression in cortex and hippocampus involved in the learning and memory deficit in molarless SAMP8 mice

Institute of Scientific and Technical Information of China (English)

JIANG Qing-song; LIANG Zi-liang; WU Min-Jie; FENG Lin; LIU Li-li; ZHANG Jian-jun

2011-01-01

Background The molarless condition has been reported to compromise learning and memory functions. However, it remains unclear how the molarless condition directly affects the central nervous system, and the functional consequences on the brain cortex and hippocampus have not been described in detail. The aim of this study was to find the molecular mechanism related with learning and memory deficit after a bilateral molarless condition having been surgically induced in senescence-accelerated mice/prone8 (SAMP8) mice, which may ultimately provide an experimental basis for clinical prevention of senile dementia.Methods Mice were either sham-operated or subjected to complete molar removal. The animals' body weights were monitored every day. Learning ability and memory were measured in a water maze test at the end of the 1 st, 2nd, and 3rd months after surgery. As soon as significantly prolonged escape latency in the molarless group was detected, the locomotor activity was examined in an open field test. Subsequently, the animals were decapitated and the cortex and hippocampus were dissected for Western blotting to measure the expression levels of brain-derived neurotrophic factor (BDNF) and the tropomyosin related kinase B (TrkB), the high affinity receptor of BDNF.Results Slightly lower weights were consistently observed in the molarless group, but there was no significant difference in weights between the two groups (P＞0.05). Compared with the sham group, the molarless group exhibited lengthened escape latency in the water maze test three months after surgery, whereas no difference in locomotor activity was observed. Meanwhile, in the cortex and hippocampus, BDNF levels were significantly decreased in the molarless group (P＜0.05); but the expression of its receptor, TrkB, was not significantly affected.Conclusion These results suggested that the molarless condition impaired learning and memory abilities in SAMP8mice three months after teeth extraction, and this

A Field Research on Organizational Learning, Crisis Management Capability and Firm Performance

Directory of Open Access Journals (Sweden)

Cemal Zehir

2016-01-01

Full Text Available Turkey has experienced a series of crises in 1994, 1999 and 2001, which induced remarkable damage in Turkish economy. Thus crisis management has been the main topic in Turkish agenda so many years. Besides crisis management, organizational learning also has been focused as an affective crisis management mean. Crisis preparedness process which is a part of crisis management is vital for any organization’s existence because the emergence of crises is inevitable. Therefore the crisis preparedness has been a topic of increasing importance for organizations seeking an effective way to fight against potential crises. In this context, this research aim to investigate the relationship among the crisis preparedness capability, organizational learning capability and organizational performance.  This survey is conducted on 400 managers of 114 firms operating in the Marmara region.  SPSS 15.0 statistics package program was used to analyze the data obtained from 400 questionnaires. Factor analysis, and reliability analysis have been executed to reveal the reliability of scale, and correlation and regression analyses have been executed to reveal the relationship among the crisis preparedness capability, organizational learning capability, and organizational performance.

A Field Research on Organizational Learning, Crisis Management Capability and Firm Performance

Directory of Open Access Journals (Sweden)

Cemal Zehir

2014-07-01

Full Text Available Turkey has experienced a series of crises in 1994, 1999 and 2001, which induced remarkable damage in Turkish economy. Thus crisis management has been the main topic in Turkish agenda so many years. Besides crisis management, organizational learning also has been focused as an affective crisis management mean. Crisis preparedness process which is a part of crisis management is vital for any organization’s existence because the emergence of crises is inevitable. Therefore the crisis preparedness has been a topic of increasing importance for organizations seeking an effective way to fight against potential crises. In this context, this research aim to investigate the relationship among the crisis preparedness capability, organizational learning capability and organizational performance. This survey is conducted on 400 managers of 114 firms operating in the Marmara region.  SPSS 15.0 statistics package program was used to analyze the data obtained from 400 questionnaires. Factor analysis, and reliability analysis have been executed to reveal the reliability of scale, and correlation and regression analyses have been executed to reveal the relationship among the crisis preparedness capability, organizational learning capability, and organizational performance.

Drinking songs: alcohol effects on learned song of zebra finches.

Directory of Open Access Journals (Sweden)

Christopher R Olson

Full Text Available Speech impairment is one of the most intriguing and least understood effects of alcohol on cognitive function, largely due to the lack of data on alcohol effects on vocalizations in the context of an appropriate experimental model organism. Zebra finches, a representative songbird and a premier model for understanding the neurobiology of vocal production and learning, learn song in a manner analogous to how humans learn speech. Here we show that when allowed access, finches readily drink alcohol, increase their blood ethanol concentrations (BEC significantly, and sing a song with altered acoustic structure. The most pronounced effects were decreased amplitude and increased entropy, the latter likely reflecting a disruption in the birds' ability to maintain the spectral structure of song under alcohol. Furthermore, specific syllables, which have distinct acoustic structures, were differentially influenced by alcohol, likely reflecting a diversity in the neural mechanisms required for their production. Remarkably, these effects on vocalizations occurred without overt effects on general behavioral measures, and importantly, they occurred within a range of BEC that can be considered risky for humans. Our results suggest that the variable effects of alcohol on finch song reflect differential alcohol sensitivity of the brain circuitry elements that control different aspects of song production. They also point to finches as an informative model for understanding how alcohol affects the neuronal circuits that control the production of learned motor behaviors.

Hypothermia and near-drowning associated with life-threatening injuries: A remarkable recovery: A case report

Directory of Open Access Journals (Sweden)

Tariq Cachalia

2016-08-01

Full Text Available A young male suffered multiple severe injuries after a fall and near-drowning. On presentation to the emergency department (ED, he was in a critical and unstable condition and his chances of survival were deemed very low. This case illustrates the management of the hypothermic multi-trauma patient and the remarkable recovery made possible by a high standard of care. Keywords: Polytrauma, Shock, Hypothermia, Coagulopathy, Trauma care

Remarks on the Colonized Libido: Trying to Think beyond Patriarchy

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Hilan Bensusan

2004-01-01

Full Text Available In these remarks I attempt to think through some of the consequences of the way we conceive and live our desires. I try to contrast those desires with both our idea of freedom and the way we usually understand nature. This takes me quickly to issues such as pornography, male identity and then to how we gain and preserve our self-esteem. This, in turn, takes me to issues that are somehow linked to the institutional and emotional structures of patriarchy under a regime of heterosexuality as a norm. I try to consider these issues from the point of view of someone who was trained within the practices and thoughts of masculinity and is bothered by the consequences of such training. I endeavour to find a way to rethink the colonization of our desires so that we can find paths to an exercise of our capacities of desire that could be somehow freer.

Social Skills Training to Reduce Depression in Adolescents.

Science.gov (United States)

Reed, Michael K.

1994-01-01

Evaluated efficacy of Structured Learning Therapy (SLT), which focuses on developing social competencies, self-evaluation skills, and appropriate affective expression, in treating adolescent depression. Findings from 18 adolescents randomly assigned to either SLT treatment or control group suggest that SLT reliably reduced depression in males and…

E-Learning platform system for the department of library and ...

African Journals Online (AJOL)

The application of e-learning is accentuated amongst higher institutions of learning globally. Due to the increase in enrolment and the daunting task of teaching large classes, there arises the need to adopt e-learning platform to reduce the burden between the teacher and student collaborations. This paper seeks the ...

Some remarks about decontamination

International Nuclear Information System (INIS)

Bertini, A.

1990-01-01

Decontamination in itself is not the elimination of a problem, but corresponds to move that problem from one place to another. It is beneficial only if the contamination is less of a nuisance when moved to the ''other place''. Therefore any prospective decontamination process is to be considered essentially in terms of cost-benefit, and in particular in terms of reducing the burden on the waste management systems. The paper is not intended to deal with and to review critically the technical aspects of the various decontamination processes which are currently available. Its aim is to call the attention of those who may be faced with the problem of large-scale decontamination, so that this operation is carried out after all practical aspects have been examined. (author)

Some remarks on the derivability of linear nonconservative systems from a Lagrangian

International Nuclear Information System (INIS)

Bahar, L.Y.; Kwatny, H.G.

1980-01-01

In this paper the linearization of the equations governing the behavior of large-scale interconnected electric power systems is carried out. It is shown that the perturbed equations of motion represent a linear, nonconservative dynamical system with arbitrary parameter matrices. Simplified conditions for the derivability of such systems from a Lagrangian are given. First integrals are derived when a certain commutativity relation is satisfied. It is shown that previously obtained results can be recovered as special cases of the present development. An example in which independent energy-like integrals are obtained by utilizing the results of this paper is given. Finally, a remark contained in a previous paper by the authors is clarified

A case of parotid tumor showing remarkable regression following hyperthermo-chemo-radiotherapy

International Nuclear Information System (INIS)

Fujimura, Takashi; Yonemura, Yutaka; Kamata, Toru

1987-01-01

A 72-year-old woman developed adenocarcinoma of the left parotid gland. Because of the excessive size of her tumor and the fact that she suffered from severe liver dysfunction, she was treated by hyperthermo-chemo-radiotherapy (HCR therapy). After ten sessions of radiofrequency hyperthermia with HEH 500 (13.56 MHz radiofrequency wave), 50-Gy irradiation from a linac and administration of 33.0 g of tegafur in suppository form, the tumor mass showed remarkable regression decreasing in size by as much as 84 % on computed tomography. Histologically, the tumor which was resected under local anesthesia, showed almost total necrosis. The multidisciplinary HCR therapy was well tolerated and effective as a therapy for cancer in this case. (author)

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

Science.gov (United States)

Tamiya, Satoshi

2014-01-01

Multilingualism poses unique psychiatric problems, especially in the field of child psychiatry. The author discusses several linguistic and transcultural issues in relation to Language Disorder, Specific Learning Disorder and Selective Mutism. Linguistic characteristics of multiple language development, including so-called profile effects and code-switching, need to be understood for differential diagnosis. It is also emphasized that Language Disorder in a bilingual person is not different or worse than that in a monolingual person. Second language proficiency, cultural background and transfer from the first language all need to be considered in an evaluation for Specific Learning Disorder. Selective Mutism has to be differentiated from the silent period observed in the normal successive bilingual development. The author concludes the review by remarking on some caveats around methods of language evaluation in a multilingual person.

A remarkable new genus of Protosmylinae (Neuroptera: Osmylidae) from late Eocene Florissant, Colorado.

Science.gov (United States)

Makarkin, Vladimir N

2017-05-18

Pseudosmylidia relicta gen. et sp. nov. (Neuroptera: Osmylidae) is described from the late Eocene of Florissant (U.S.A., Colorado). It is assigned to the subfamily Protosmylinae based on the presence of two venational features characteristic of the subfamily: most crossveins in the radial to intramedial spaces of the forewing are arranged in four gradate series, and CuP is short and simple or forked only once in the hind wing. This genus is remarkable by CuP in the forewing bearing few pectinate branches. This is the only genus of extant and Cenozoic fossil Osmylidae in which this plesiomorphic condition is retained.

Embedding responses in spontaneous neural activity shaped through sequential learning.

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Tomoki Kurikawa

Full Text Available Recent experimental measurements have demonstrated that spontaneous neural activity in the absence of explicit external stimuli has remarkable spatiotemporal structure. This spontaneous activity has also been shown to play a key role in the response to external stimuli. To better understand this role, we proposed a viewpoint, "memories-as-bifurcations," that differs from the traditional "memories-as-attractors" viewpoint. Memory recall from the memories-as-bifurcations viewpoint occurs when the spontaneous neural activity is changed to an appropriate output activity upon application of an input, known as a bifurcation in dynamical systems theory, wherein the input modifies the flow structure of the neural dynamics. Learning, then, is a process that helps create neural dynamical systems such that a target output pattern is generated as an attractor upon a given input. Based on this novel viewpoint, we introduce in this paper an associative memory model with a sequential learning process. Using a simple hebbian-type learning, the model is able to memorize a large number of input/output mappings. The neural dynamics shaped through the learning exhibit different bifurcations to make the requested targets stable upon an increase in the input, and the neural activity in the absence of input shows chaotic dynamics with occasional approaches to the memorized target patterns. These results suggest that these dynamics facilitate the bifurcations to each target attractor upon application of the corresponding input, which thus increases the capacity for learning. This theoretical finding about the behavior of the spontaneous neural activity is consistent with recent experimental observations in which the neural activity without stimuli wanders among patterns evoked by previously applied signals. In addition, the neural networks shaped by learning properly reflect the correlations of input and target-output patterns in a similar manner to those designed in

Striking multiple synergies created by combining reduced graphene oxides and carbon nanotubes for polymer nanocomposites

International Nuclear Information System (INIS)

Song Ping’an; Liu Lina; Fu Shenyuan; Yu Youming; Jin Chunde; Wu Qiang; Zhang Yan; Li Qian

2013-01-01

The extraordinary properties of carbon nanotubes (CNTs) and graphene stimulate the development of advanced composites. Recently, several studies have reported significant synergies in the mechanical, electrical and thermal conductivity properties of polymer nanocomposites by incorporating their nanohybrids. In this work, we created polypropylene nanocomposites with homogeneous dispersion of CNTs and reduced graphene oxides via a facile polymer-latex-coating plus melt-mixing strategy, and investigated their synergistic effects in their viscoelastic, gas barrier, and flammability properties. Interestingly, the results show remarkable synergies, enhancing their melt modulus and viscosity, O 2 barrier, and flame retardancy properties and respectively exhibiting a synergy percentage of 15.9%, 45.3%, and 20.3%. As previously reported, we also observed remarkable synergistic effects in their tensile strength (14.3%) and Young’s modulus (27.1%), electrical conductivity (32.3%) and thermal conductivity (34.6%). These impressive results clearly point towards a new strategy to create advanced materials by adding binary combinations of different types of nanofillers. (paper)

Failure of operant control of vocal learning in budgerigars

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Yoshimasa Seki

2018-02-01

Full Text Available Budgerigars were trained by operant conditioning to produce contact calls immediately after hearing a stimulus contact call. In Experiments 1 and 2, playback stimuli were chosen from two different contact call classes from the bird’s repertoire. Once this task was learned, the birds were then tested with other probe stimulus calls from its repertoire, which differed from the original calls drawn from the two classes. Birds failed to mimic the probe stimuli but instead produced one of the two call classes as in the training sessions, showing that birds learned that each stimulus call served as a discriminative stimulus but not as a vocal template for imitation. In Experiment 3, birds were then trained with stimulus calls falling along a 24-step acoustic gradient which varied between the two sounds representing the two contact call categories. As before, birds obtained a reward when the bird’s vocalization matched that of the stimulus above a criterion level. Since the first step and the last step in the gradient were the birds’ original contact calls,　these two patterns were easily matched. Intermediate contact calls in the gradient were much harder for the birds to match. After extensive training, one bird learned to produce contact calls that had only a modest similarity to the intermediate contact calls along the gradient. In spite of remarkable vocal plasticity under natural conditions, operant conditioning methods with budgerigars, even after extensive training and rigorous control of vocal discriminative stimuli, failed to show vocal learning.

Why Earthquake Effects are to be Reduced Conventional seismic ...

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education; Volume 10; Issue 11. Learning Earthquake Design and Construction – 24. How to Reduce Earthquake Effects on Buildings? C V R Murty. Classroom Volume 10 Issue 11 November 2005 pp 89-92 ...

Online learning in dentistry: the changes in undergraduate perceptions and attitudes over a four year period.

Science.gov (United States)

Reynolds, P A; Rice, S; Uddin, M

2007-10-13

To assess the changing perceptions and attitudes of undergraduate dental students towards e-learning between 2001-2004. DESIGN, SAMPLE AND SETTING: This was a retrospective analysis of online questionnaire data, collected from four successive cohorts of final year students undertaking an online therapeutics course in a large teaching hospital. Students were required to complete a structured and open questionnaire relating to their perceived ICT skills, the course itself, and their perceptions of e-learning. Simple numeric qualitative and qualitative analyses were applied. Questionnaires were returned by 328 students (98% response rate). Students' perceptions of having advanced ICT skills increased from 5.5% to 14.5%, with home internet access rising from 62.3% to 89.1 % (2001-2004). There was an increase in: ease of access (25.3% to 47.3%), perception of time saving (17.9% to 37.4%), appreciation of combining traditional and e-learning methods (43.8% to 57.4%) and online tutor access (21.9% to 40.7%). Free comments supporting good e-learning experiences rose from 7.2% to 32.7% with poor remarks decreasing (3.1% to 1.9%). Students' perceptions of their ICT skills has increased, matched by better equipment and greater appreciation of e-learning. A shift towards preference of a blended approach of traditional and e-learning is evident.

Opening remarks; special session 4. Burning issues and smoke screens: heat and light in southern forests

Science.gov (United States)

Peter J. Roussopoulos

1998-01-01

In Roussopoulos’ opening remarks he included nine assertions about southern forests: 1) that their characteristics are unique; 2) that they recovered from abusive agricultural practices and exploitive forest extraction in the 19th and early 20th centuries; 3) that they are brand new; 4) that social forces driving change will intensify at all scales; 5) that the...

Learning from instructional explanations: effects of prompts based on the active-constructive-interactive framework.

Science.gov (United States)

Roelle, Julian; Müller, Claudia; Roelle, Detlev; Berthold, Kirsten

2015-01-01

Although instructional explanations are commonly provided when learners are introduced to new content, they often fail because they are not integrated into effective learning activities. The recently introduced active-constructive-interactive framework posits an effectiveness hierarchy in which interactive learning activities are at the top; these are then followed by constructive and active learning activities, respectively. Against this background, we combined instructional explanations with different types of prompts that were designed to elicit these learning activities and tested the central predictions of the active-constructive-interactive framework. In Experiment 1, N = 83 students were randomly assigned to one of four combinations of instructional explanations and prompts. To test the active learning hypothesis, the learners received either (1) complete explanations and engaging prompts designed to elicit active activities or (2) explanations that were reduced by inferences and inference prompts designed to engage learners in constructing the withheld information. Furthermore, in order to explore how interactive learning activities can be elicited, we gave the learners who had difficulties in constructing the prompted inferences adapted remedial explanations with either (3) unspecific engaging prompts or (4) revision prompts. In support of the active learning hypothesis, we found that the learners who received reduced explanations and inference prompts outperformed the learners who received complete explanations and engaging prompts. Moreover, revision prompts were more effective in eliciting interactive learning activities than engaging prompts. In Experiment 2, N = 40 students were randomly assigned to either (1) a reduced explanations and inference prompts or (2) a reduced explanations and inference prompts plus adapted remedial explanations and revision prompts condition. In support of the constructive learning hypothesis, the learners who received

Scaling up machine learning: parallel and distributed approaches

National Research Council Canada - National Science Library

Bekkerman, Ron; Bilenko, Mikhail; Langford, John

2012-01-01

... presented in the book cover a range of parallelization platforms from FPGAs and GPUs to multi-core systems and commodity clusters; concurrent programming frameworks that include CUDA, MPI, MapReduce, and DryadLINQ; and various learning settings: supervised, unsupervised, semi-supervised, and online learning. Extensive coverage of parallelizat...

QUEST: Eliminating Online Supervised Learning for Efficient Classification Algorithms

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Ardjan Zwartjes

2016-10-01

Full Text Available In this work, we introduce QUEST (QUantile Estimation after Supervised Training, an adaptive classification algorithm for Wireless Sensor Networks (WSNs that eliminates the necessity for online supervised learning. Online processing is important for many sensor network applications. Transmitting raw sensor data puts high demands on the battery, reducing network life time. By merely transmitting partial results or classifications based on the sampled data, the amount of traffic on the network can be significantly reduced. Such classifications can be made by learning based algorithms using sampled data. An important issue, however, is the training phase of these learning based algorithms. Training a deployed sensor network requires a lot of communication and an impractical amount of human involvement. QUEST is a hybrid algorithm that combines supervised learning in a controlled environment with unsupervised learning on the location of deployment. Using the SITEX02 dataset, we demonstrate that the presented solution works with a performance penalty of less than 10% in 90% of the tests. Under some circumstances, it even outperforms a network of classifiers completely trained with supervised learning. As a result, the need for on-site supervised learning and communication for training is completely eliminated by our solution.

Aging Educational Program to Reduce Ageism: Intergenerational Approach

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Shima Sum

2016-06-01

Full Text Available Introduction: Ageing brings different experiences for individuals. Any individual learn about ageing from childhood whatever formal or informal. No matter they learn, what and how they learn is important. This study aimed to assess impact of an educational program on ageism in those people lower 20 years of age. Methods: This interventional study was conducted among school and university students of Babol city, Mazandaran province, Iran. Study was carried out in two stages. First 373 participants (187 school students and 186 university undergraduate students under age of 20 who recruited form Babol department of education and Babol University of Medical Sciences went under study of assessing attitudes toward ageing. In the second stage, courses on lifespan human development were delivered in 10 workshops for 151 people. Sampling method was stratified randomly from different age groups.  Workshops consisted of lecturing, discussion, watching movie, reading pamphlets and having conversations with experienced older adults. Data was gathered by a questionnaire consisting of demographic characteristics and The Fraboni Scale of Ageism. Results: The mean of ageism score among school and university students were 49.93 ± 9.25 and 46.96 ± 7.64 respectively. There was statistically significant difference between two groups in ageism scores (p = 0.001 so that ageism was higher among school students However after implementation of education program, ageism score reduced for all 151 students from 46.92 ± 7.82 to 45.85 ± 7.79 which was statistically significant (p = 0.001. Conclusion: Educational program to reduce ageism is beneficial and could reduce the level of ageism. Suggestions for educators to combat ageism are provided.

Human-like brain hemispheric dominance in birdsong learning.

Science.gov (United States)

Moorman, Sanne; Gobes, Sharon M H; Kuijpers, Maaike; Kerkhofs, Amber; Zandbergen, Matthijs A; Bolhuis, Johan J

2012-07-31

Unlike nonhuman primates, songbirds learn to vocalize very much like human infants acquire spoken language. In humans, Broca's area in the frontal lobe and Wernicke's area in the temporal lobe are crucially involved in speech production and perception, respectively. Songbirds have analogous brain regions that show a similar neural dissociation between vocal production and auditory perception and memory. In both humans and songbirds, there is evidence for lateralization of neural responsiveness in these brain regions. Human infants already show left-sided dominance in their brain activation when exposed to speech. Moreover, a memory-specific left-sided dominance in Wernicke's area for speech perception has been demonstrated in 2.5-mo-old babies. It is possible that auditory-vocal learning is associated with hemispheric dominance and that this association arose in songbirds and humans through convergent evolution. Therefore, we investigated whether there is similar song memory-related lateralization in the songbird brain. We exposed male zebra finches to tutor or unfamiliar song. We found left-sided dominance of neuronal activation in a Broca-like brain region (HVC, a letter-based name) of juvenile and adult zebra finch males, independent of the song stimulus presented. In addition, juvenile males showed left-sided dominance for tutor song but not for unfamiliar song in a Wernicke-like brain region (the caudomedial nidopallium). Thus, left-sided dominance in the caudomedial nidopallium was specific for the song-learning phase and was memory-related. These findings demonstrate a remarkable neural parallel between birdsong and human spoken language, and they have important consequences for our understanding of the evolution of auditory-vocal learning and its neural mechanisms.

The possible benefits of reduced errors in the motor skills acquisition of children

Directory of Open Access Journals (Sweden)

Capio Catherine M

2012-01-01

Full Text Available Abstract An implicit approach to motor learning suggests that relatively complex movement skills may be better acquired in environments that constrain errors during the initial stages of practice. This current concept paper proposes that reducing the number of errors committed during motor learning leads to stable performance when attention demands are increased by concurrent cognitive tasks. While it appears that this approach to practice may be beneficial for motor learning, further studies are needed to both confirm this advantage and better understand the underlying mechanisms. An approach involving error minimization during early learning may have important applications in paediatric rehabilitation.

Evaluating a learning management system for blended learning in Greek higher education.

Science.gov (United States)

Kabassi, Katerina; Dragonas, Ioannis; Ntouzevits, Alexandra; Pomonis, Tzanetos; Papastathopoulos, Giorgos; Vozaitis, Yiannis

2016-01-01

This paper focuses on the usage of a learning management system in an educational institution for higher education in Greece. More specifically, the paper examines the literature on the use of different learning management systems for blended learning in higher education in Greek Universities and Technological Educational Institutions and reviews the advantages and disadvantages. Moreover, the paper describes the usage of the Open eClass platform in a Technological Educational Institution, TEI of Ionian Islands, and the effort to improve the educational material by organizing it and adding video-lectures. The platform has been evaluated by the students of the TEI of Ionian Islands based on six dimensions: namely student, teacher, course, technology, system design, and environmental dimension. The results of this evaluation revealed that Open eClass has been successfully used for blended learning in the TEI of Ionian Islands. Despite the instructors' initial worries about students' lack of participation in their courses if their educational material was made available online and especially in video lectures; blended learning did not reduce physical presence of the students in the classroom. Instead it was only used as a supplementary tool that helps students to study further, watch missed lectures, etc.

Decision Making in Reinforcement Learning Using a Modified Learning Space Based on the Importance of Sensors

Directory of Open Access Journals (Sweden)

Yasutaka Kishima

2013-01-01

Full Text Available Many studies have been conducted on the application of reinforcement learning (RL to robots. A robot which is made for general purpose has redundant sensors or actuators because it is difficult to assume an environment that the robot will face and a task that the robot must execute. In this case, -space on RL contains redundancy so that the robot must take much time to learn a given task. In this study, we focus on the importance of sensors with regard to a robot’s performance of a particular task. The sensors that are applicable to a task differ according to the task. By using the importance of the sensors, we try to adjust the state number of the sensors and to reduce the size of -space. In this paper, we define the measure of importance of a sensor for a task with the correlation between the value of each sensor and reward. A robot calculates the importance of the sensors and makes the size of -space smaller. We propose the method which reduces learning space and construct the learning system by putting it in RL. In this paper, we confirm the effectiveness of our proposed system with an experimental robot.

Identifying Students' Difficulties When Learning Technical Skills via a Wireless Sensor Network

Science.gov (United States)

Wang, Jingying; Wen, Ming-Lee; Jou, Min

2016-01-01

Practical training and actual application of acquired knowledge and techniques are crucial for the learning of technical skills. We established a wireless sensor network system (WSNS) based on the 5E learning cycle in a practical learning environment to improve students' reflective abilities and to reduce difficulties for the learning of technical…

β-asarone improves learning and memory and reduces Acetyl Cholinesterase and Beta-amyloid 42 levels in APP/PS1 transgenic mice by regulating Beclin-1-dependent autophagy.

Science.gov (United States)

Deng, Minzhen; Huang, Liping; Ning, Baile; Wang, Nanbu; Zhang, Qinxin; Zhu, Caixia; Fang, Yongqi

2016-12-01

Alzheimer's disease (AD) is the most common neurodegenerative disorder in the elderly, and studies have suggested that β-asarone has pharmacological effects on beta-amyloid (Aβ) injected in the rat hippocampus. However, the effect of β-asarone on autophagy in the APP/PS1 transgenic mouse is unreported. APP/PS1 transgenic mice were randomly divided into six groups (n=10/group): an untreated group, an Aricept-treated group, a 3-MA-treated group, a rapamycin-treated group, an LY294002-treated group, a β-asarone-treated group. The control group consisted of wild-type C57BL/6 mice. All treatments were administered to the mice for 30 days. Spatial learning and memory were assessed by water maze, passive avoidance, and step-down tests. AChE and Aβ 42 levels in the hippocampus were determined by ELISA. p-Akt, p-mTOR, and LC3B expression were detected by flow cytometry. The expression of p-Akt, p-mTOR, Beclin-1, and p62 proteins was assessed by western blot. Changes in autophagy were viewed using a transmission electron microscope. APP and Beclin-1 mRNA levels were measured by Real-Time PCR. The learning and memory of APP/PS1 transgenic mice were improved significantly after β-asarone treatment compared with the untreated group. In addition, β-asarone treatment reduced AChE and Aβ 42 levels, increased p-mTOR and p62 expression, decreased p-Akt, Beclin-1, and LC3B expression, decreased the number of autophagosomes and reduced APP mRNA and Beclin-1 mRNA levels compared with the untreated group. That is, β-asarone treatment can improve the learning and memory abilities of APP/PS1 transgenic mouse by inhibiting Beclin-1-dependent autophagy via the PI3K/Akt/mTOR pathway. Copyright © 2016 Elsevier B.V. All rights reserved.

Creating e-learning games with Unity

CERN Document Server

Horachek, David

2014-01-01

Unity is a fully integrated development engine providing the required functionality to create games and interactive 3D content, while reducing the time, effort, and cost of developing the content. Nowadays, many people have started to use Unity in an eLearning setting as it allows them to create real-world scenarios, or models, for training purposes. With Unity, one can develop video games that are not only fun, but are also effective teaching and learning tools. When properly designed, an engaging game is an ideal platform for the presentation, testing, and application of learning objectives.

Understanding reduced rotavirus vaccine efficacy in low socio-economic settings.

Directory of Open Access Journals (Sweden)

Benjamin A Lopman

Full Text Available Rotavirus vaccine efficacy ranges from >90% in high socio-economic settings (SES to 50% in low SES. With the imminent introduction of rotavirus vaccine in low SES countries, understanding reasons for reduced efficacy in these settings could identify strategies to improve vaccine performance.We developed a mathematical model to predict rotavirus vaccine efficacy in high, middle and low SES based on data specific for each setting on incidence, protection conferred by natural infection and immune response to vaccination. We then examined factors affecting efficacy.Vaccination was predicted to prevent 93%, 86% and 51% of severe rotavirus gastroenteritis in high, middle and low SES, respectively. Also predicted was that vaccines are most effective against severe disease and efficacy declines with age in low but not high SES. Reduced immunogenicity of vaccination and reduced protection conferred by natural infection are the main factors that compromise efficacy in low SES.The continued risk of severe disease in non-primary natural infections in low SES is a key factor underpinning reduced efficacy of rotavirus vaccines. Predicted efficacy was remarkably consistent with observed clinical trial results from different SES, validating the model. The phenomenon of reduced vaccine efficacy can be predicted by intrinsic immunological and epidemiological factors of low SES populations. Modifying aspects of the vaccine (e.g. improving immunogenicity in low SES and vaccination program (e.g. additional doses may bring improvements.

Understanding reduced rotavirus vaccine efficacy in low socio-economic settings.

Science.gov (United States)

Lopman, Benjamin A; Pitzer, Virginia E; Sarkar, Rajiv; Gladstone, Beryl; Patel, Manish; Glasser, John; Gambhir, Manoj; Atchison, Christina; Grenfell, Bryan T; Edmunds, W John; Kang, Gagandeep; Parashar, Umesh D

2012-01-01

Rotavirus vaccine efficacy ranges from >90% in high socio-economic settings (SES) to 50% in low SES. With the imminent introduction of rotavirus vaccine in low SES countries, understanding reasons for reduced efficacy in these settings could identify strategies to improve vaccine performance. We developed a mathematical model to predict rotavirus vaccine efficacy in high, middle and low SES based on data specific for each setting on incidence, protection conferred by natural infection and immune response to vaccination. We then examined factors affecting efficacy. Vaccination was predicted to prevent 93%, 86% and 51% of severe rotavirus gastroenteritis in high, middle and low SES, respectively. Also predicted was that vaccines are most effective against severe disease and efficacy declines with age in low but not high SES. Reduced immunogenicity of vaccination and reduced protection conferred by natural infection are the main factors that compromise efficacy in low SES. The continued risk of severe disease in non-primary natural infections in low SES is a key factor underpinning reduced efficacy of rotavirus vaccines. Predicted efficacy was remarkably consistent with observed clinical trial results from different SES, validating the model. The phenomenon of reduced vaccine efficacy can be predicted by intrinsic immunological and epidemiological factors of low SES populations. Modifying aspects of the vaccine (e.g. improving immunogenicity in low SES) and vaccination program (e.g. additional doses) may bring improvements.

Forebrain-Specific Loss of BMPRII in Mice Reduces Anxiety and Increases Object Exploration.

Science.gov (United States)

McBrayer, Zofeyah L; Dimova, Jiva; Pisansky, Marc T; Sun, Mu; Beppu, Hideyuki; Gewirtz, Jonathan C; O'Connor, Michael B

2015-01-01

To investigate the role of Bone Morphogenic Protein Receptor Type II (BMPRII) in learning, memory, and exploratory behavior in mice, a tissue-specific knockout of BMPRII in the post-natal hippocampus and forebrain was generated. We found that BMPRII mutant mice had normal spatial learning and memory in the Morris water maze, but showed significantly reduced swimming speeds with increased floating behavior. Further analysis using the Porsolt Swim Test to investigate behavioral despair did not reveal any differences in immobility between mutants and controls. In the Elevated Plus Maze, BMPRII mutants and Smad4 mutants showed reduced anxiety, while in exploratory tests, BMPRII mutants showed more interest in object exploration. These results suggest that loss of BMPRII in the mouse hippocampus and forebrain does not disrupt spatial learning and memory encoding, but instead impacts exploratory and anxiety-related behaviors.

Forebrain-Specific Loss of BMPRII in Mice Reduces Anxiety and Increases Object Exploration.

Directory of Open Access Journals (Sweden)

Zofeyah L McBrayer

Full Text Available To investigate the role of Bone Morphogenic Protein Receptor Type II (BMPRII in learning, memory, and exploratory behavior in mice, a tissue-specific knockout of BMPRII in the post-natal hippocampus and forebrain was generated. We found that BMPRII mutant mice had normal spatial learning and memory in the Morris water maze, but showed significantly reduced swimming speeds with increased floating behavior. Further analysis using the Porsolt Swim Test to investigate behavioral despair did not reveal any differences in immobility between mutants and controls. In the Elevated Plus Maze, BMPRII mutants and Smad4 mutants showed reduced anxiety, while in exploratory tests, BMPRII mutants showed more interest in object exploration. These results suggest that loss of BMPRII in the mouse hippocampus and forebrain does not disrupt spatial learning and memory encoding, but instead impacts exploratory and anxiety-related behaviors.

A machine learning model with human cognitive biases capable of learning from small and biased datasets.

Science.gov (United States)

Taniguchi, Hidetaka; Sato, Hiroshi; Shirakawa, Tomohiro

2018-05-09

Human learners can generalize a new concept from a small number of samples. In contrast, conventional machine learning methods require large amounts of data to address the same types of problems. Humans have cognitive biases that promote fast learning. Here, we developed a method to reduce the gap between human beings and machines in this type of inference by utilizing cognitive biases. We implemented a human cognitive model into machine learning algorithms and compared their performance with the currently most popular methods, naïve Bayes, support vector machine, neural networks, logistic regression and random forests. We focused on the task of spam classification, which has been studied for a long time in the field of machine learning and often requires a large amount of data to obtain high accuracy. Our models achieved superior performance with small and biased samples in comparison with other representative machine learning methods.

Learning to interact with a computer by gaze

DEFF Research Database (Denmark)

Aoki, Hirotaka; Hansen, John Paulin; Itoh, Kenji

2008-01-01

that inefficient eye movements was dramatically reduced after only 15 to 25 sentences of typing, equal to approximately 3-4 hours of practice. The performance data fits a general learning model based on the power law of practice. The learning model can be used to estimate further improvements in gaze typing...

The windmill of learning processes

DEFF Research Database (Denmark)

Kragelund, Linda

2011-01-01

that part of the nursing education has been reduced in some countries as e.g. Denmark.  The approach is presented through a model termed the 'Windmill of Learning Processes', which draws on empirical data from a qualitative investigation with an explorative and descriptive design, and on the theoretical......This article presents a new approach to student nurses' learning from their interaction with psychiatric patients. Using the approach can enable students and mentors to exploit students' learning opportunities, and help students to get the most out of their clinical placement in a time, where...... concepts of 'disjuncture', and 'everyday life activities'. 'Disjuncture' is defined as a situation in which there is disharmony between a person's experiences and the current situation. In such a situation there is potential for learning. My analysis of the empirical data led to the identification of a new...

Enhancing students' learning in problem based learning: validation of a self-assessment scale for active learning and critical thinking.

Science.gov (United States)

Khoiriyah, Umatul; Roberts, Chris; Jorm, Christine; Van der Vleuten, C P M

2015-08-26

Problem based learning (PBL) is a powerful learning activity but fidelity to intended models may slip and student engagement wane, negatively impacting learning processes, and outcomes. One potential solution to solve this degradation is by encouraging self-assessment in the PBL tutorial. Self-assessment is a central component of the self-regulation of student learning behaviours. There are few measures to investigate self-assessment relevant to PBL processes. We developed a Self-assessment Scale on Active Learning and Critical Thinking (SSACT) to address this gap. We wished to demonstrated evidence of its validity in the context of PBL by exploring its internal structure. We used a mixed methods approach to scale development. We developed scale items from a qualitative investigation, literature review, and consideration of previous existing tools used for study of the PBL process. Expert review panels evaluated its content; a process of validation subsequently reduced the pool of items. We used structural equation modelling to undertake a confirmatory factor analysis (CFA) of the SSACT and coefficient alpha. The 14 item SSACT consisted of two domains "active learning" and "critical thinking." The factorial validity of SSACT was evidenced by all items loading significantly on their expected factors, a good model fit for the data, and good stability across two independent samples. Each subscale had good internal reliability (>0.8) and strongly correlated with each other. The SSACT has sufficient evidence of its validity to support its use in the PBL process to encourage students to self-assess. The implementation of the SSACT may assist students to improve the quality of their learning in achieving PBL goals such as critical thinking and self-directed learning.

Attentional Bias in Human Category Learning: The Case of Deep Learning.

Science.gov (United States)

Hanson, Catherine; Caglar, Leyla Roskan; Hanson, Stephen José

2018-01-01

. Third, we show that even BP can exhibit human like learning differences between integral and separable category structures when high dimensional stimuli (face exemplars) are used. We conclude, after visualizing the hidden unit representations, that DL appears to extend initial learning due to feature development thereby reducing destructive feature competition by incrementally refining feature detectors throughout later layers until a tipping point (in terms of error) is reached resulting in rapid asymptotic learning.

Attentional Bias in Human Category Learning: The Case of Deep Learning

Directory of Open Access Journals (Sweden)

Catherine Hanson

2018-04-01

structures. Third, we show that even BP can exhibit human like learning differences between integral and separable category structures when high dimensional stimuli (face exemplars are used. We conclude, after visualizing the hidden unit representations, that DL appears to extend initial learning due to feature development thereby reducing destructive feature competition by incrementally refining feature detectors throughout later layers until a tipping point (in terms of error is reached resulting in rapid asymptotic learning.

Characteristics and Activities of Teachers on Distance Learning Programs that Affect Their Ratings

Directory of Open Access Journals (Sweden)

Svetlana M. Stanišić Stojić

2014-09-01

Full Text Available This paper presents an analysis of teachers’ ratings on distance learning undergraduate study programs: 7,156 students enrolled in traditional and 528 students enrolled in distance learning studies took part in the evaluation questionnaire, assessing 71 teachers. The data were collected from the Moodle platform and from the Singidunum University information system, and then analysed with SPSS statistical software. The parameters considered as potentially affecting teacher ratings are: number of teachers engaged in a particular course, total number of courses in which the teacher is engaged, teacher’s gender and age, total number of the available resources, and so forth. The results imply that scores assigned to individual teachers are consistent in both traditional and distance learning programs. The average rate was perceived to be lower when there were several teachers in a single course; such an effect was enhanced in cases where there was a significant age discrepancy among them. The other factors considered did not show a significant association with teacher ratings. Students’ main remarks about the work of the teachers have been summarised at the end of this paper. Possible explanations and implications of the results are discussed and recommendations are given.

Reducing weight precision of convolutional neural networks towards large-scale on-chip image recognition

Science.gov (United States)

Ji, Zhengping; Ovsiannikov, Ilia; Wang, Yibing; Shi, Lilong; Zhang, Qiang

2015-05-01

In this paper, we develop a server-client quantization scheme to reduce bit resolution of deep learning architecture, i.e., Convolutional Neural Networks, for image recognition tasks. Low bit resolution is an important factor in bringing the deep learning neural network into hardware implementation, which directly determines the cost and power consumption. We aim to reduce the bit resolution of the network without sacrificing its performance. To this end, we design a new quantization algorithm called supervised iterative quantization to reduce the bit resolution of learned network weights. In the training stage, the supervised iterative quantization is conducted via two steps on server - apply k-means based adaptive quantization on learned network weights and retrain the network based on quantized weights. These two steps are alternated until the convergence criterion is met. In this testing stage, the network configuration and low-bit weights are loaded to the client hardware device to recognize coming input in real time, where optimized but expensive quantization becomes infeasible. Considering this, we adopt a uniform quantization for the inputs and internal network responses (called feature maps) to maintain low on-chip expenses. The Convolutional Neural Network with reduced weight and input/response precision is demonstrated in recognizing two types of images: one is hand-written digit images and the other is real-life images in office scenarios. Both results show that the new network is able to achieve the performance of the neural network with full bit resolution, even though in the new network the bit resolution of both weight and input are significantly reduced, e.g., from 64 bits to 4-5 bits.

The development of automaticity in short-term memory search: Item-response learning and category learning.

Science.gov (United States)

Cao, Rui; Nosofsky, Robert M; Shiffrin, Richard M

2017-05-01

In short-term-memory (STM)-search tasks, observers judge whether a test probe was present in a short list of study items. Here we investigated the long-term learning mechanisms that lead to the highly efficient STM-search performance observed under conditions of consistent-mapping (CM) training, in which targets and foils never switch roles across trials. In item-response learning, subjects learn long-term mappings between individual items and target versus foil responses. In category learning, subjects learn high-level codes corresponding to separate sets of items and learn to attach old versus new responses to these category codes. To distinguish between these 2 forms of learning, we tested subjects in categorized varied mapping (CV) conditions: There were 2 distinct categories of items, but the assignment of categories to target versus foil responses varied across trials. In cases involving arbitrary categories, CV performance closely resembled standard varied-mapping performance without categories and departed dramatically from CM performance, supporting the item-response-learning hypothesis. In cases involving prelearned categories, CV performance resembled CM performance, as long as there was sufficient practice or steps taken to reduce trial-to-trial category-switching costs. This pattern of results supports the category-coding hypothesis for sufficiently well-learned categories. Thus, item-response learning occurs rapidly and is used early in CM training; category learning is much slower but is eventually adopted and is used to increase the efficiency of search beyond that available from item-response learning. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Reduced order modelling techniques for mesh movement strategies as applied to fluid structure interactions

CSIR Research Space (South Africa)

Bogaers, Alfred EJ

2010-01-01

Full Text Available of Laplacian or Bi-harmonic equations [7], radial basis function (RBF) interpolation [3, 15] or through mesh optimization [1, 6]. Despite the successes of these algorithms in reducing the frequency and necessity for re- meshing, they still account for a... simulations of a real system. What makes POD remarkable is that the selected modes are not only appropriate but make up the optimal linear basis for describing any given system. POD has been applied in a wide range of disciplines including image processing...

Sleep reduces false memory in healthy older adults.

Science.gov (United States)

Lo, June C; Sim, Sam K Y; Chee, Michael W L

2014-04-01

To investigate the effects of post-learning sleep and sleep architecture on false memory in healthy older adults. Balanced, crossover design. False memory was induced using the Deese-Roediger-McDermott (DRM) paradigm and assessed following nocturnal sleep and following a period of daytime wakefulness. Post-learning sleep structure was evaluated using polysomnography (PSG). Sleep research laboratory. Fourteen healthy older adults from the Singapore-Longitudinal Aging Brain Study (mean age ± standard deviation = 66.6 ± 4.1 y; 7 males). At encoding, participants studied lists of words that were semantically related to non-presented critical lures. At retrieval, they made "remember"/"know" and "new" judgments. Compared to wakefulness, post-learning sleep was associated with reduced "remember" responses, but not "know" responses to critical lures. In contrast, there were no significant differences in the veridical recognition of studied words, false recognition of unrelated distractors, discriminability, or response bias between the sleep and the wake conditions. More post-learning slow wave sleep was associated with greater reduction in false memory. In healthy older adults, sleep facilitates the reduction in false memory without affecting veridical memory. This benefit correlates with the amount of slow wave sleep in the post-learning sleep episode.

Multisensory perceptual learning of temporal order: audiovisual learning transfers to vision but not audition.

Directory of Open Access Journals (Sweden)

David Alais

2010-06-01

Full Text Available An outstanding question in sensory neuroscience is whether the perceived timing of events is mediated by a central supra-modal timing mechanism, or multiple modality-specific systems. We use a perceptual learning paradigm to address this question.Three groups were trained daily for 10 sessions on an auditory, a visual or a combined audiovisual temporal order judgment (TOJ. Groups were pre-tested on a range TOJ tasks within and between their group modality prior to learning so that transfer of any learning from the trained task could be measured by post-testing other tasks. Robust TOJ learning (reduced temporal order discrimination thresholds occurred for all groups, although auditory learning (dichotic 500/2000 Hz tones was slightly weaker than visual learning (lateralised grating patches. Crossmodal TOJs also displayed robust learning. Post-testing revealed that improvements in temporal resolution acquired during visual learning transferred within modality to other retinotopic locations and orientations, but not to auditory or crossmodal tasks. Auditory learning did not transfer to visual or crossmodal tasks, and neither did it transfer within audition to another frequency pair. In an interesting asymmetry, crossmodal learning transferred to all visual tasks but not to auditory tasks. Finally, in all conditions, learning to make TOJs for stimulus onsets did not transfer at all to discriminating temporal offsets. These data present a complex picture of timing processes.The lack of transfer between unimodal groups indicates no central supramodal timing process for this task; however, the audiovisual-to-visual transfer cannot be explained without some form of sensory interaction. We propose that auditory learning occurred in frequency-tuned processes in the periphery, precluding interactions with more central visual and audiovisual timing processes. Functionally the patterns of featural transfer suggest that perceptual learning of temporal order

Multisensory perceptual learning of temporal order: audiovisual learning transfers to vision but not audition.

Science.gov (United States)

Alais, David; Cass, John

2010-06-23

An outstanding question in sensory neuroscience is whether the perceived timing of events is mediated by a central supra-modal timing mechanism, or multiple modality-specific systems. We use a perceptual learning paradigm to address this question. Three groups were trained daily for 10 sessions on an auditory, a visual or a combined audiovisual temporal order judgment (TOJ). Groups were pre-tested on a range TOJ tasks within and between their group modality prior to learning so that transfer of any learning from the trained task could be measured by post-testing other tasks. Robust TOJ learning (reduced temporal order discrimination thresholds) occurred for all groups, although auditory learning (dichotic 500/2000 Hz tones) was slightly weaker than visual learning (lateralised grating patches). Crossmodal TOJs also displayed robust learning. Post-testing revealed that improvements in temporal resolution acquired during visual learning transferred within modality to other retinotopic locations and orientations, but not to auditory or crossmodal tasks. Auditory learning did not transfer to visual or crossmodal tasks, and neither did it transfer within audition to another frequency pair. In an interesting asymmetry, crossmodal learning transferred to all visual tasks but not to auditory tasks. Finally, in all conditions, learning to make TOJs for stimulus onsets did not transfer at all to discriminating temporal offsets. These data present a complex picture of timing processes. The lack of transfer between unimodal groups indicates no central supramodal timing process for this task; however, the audiovisual-to-visual transfer cannot be explained without some form of sensory interaction. We propose that auditory learning occurred in frequency-tuned processes in the periphery, precluding interactions with more central visual and audiovisual timing processes. Functionally the patterns of featural transfer suggest that perceptual learning of temporal order may be

Reducing Supply Chain GHG Emissions from LCD Panel Manufacturing Webinar

Science.gov (United States)

Fluorinated greenhouse gases (F-GHGs) are among the most potent and persistent greenhouse gases contributing to global climate change. Learn about the manufacturing processes which release F-GHGs, and how LCD suppliers are working to reduce emissions.

Revitalizing pathology laboratories in a gastrointestinal pathophysiology course using multimedia and team-based learning techniques.

Science.gov (United States)

Carbo, Alexander R; Blanco, Paola G; Graeme-Cooke, Fiona; Misdraji, Joseph; Kappler, Steven; Shaffer, Kitt; Goldsmith, Jeffrey D; Berzin, Tyler; Leffler, Daniel; Najarian, Robert; Sepe, Paul; Kaplan, Jennifer; Pitman, Martha; Goldman, Harvey; Pelletier, Stephen; Hayward, Jane N; Shields, Helen M

2012-05-15

In 2008, we changed the gastrointestinal pathology laboratories in a gastrointestinal pathophysiology course to a more interactive format using modified team-based learning techniques and multimedia presentations. The results were remarkably positive and can be used as a model for pathology laboratory improvement in any organ system. Over a two-year period, engaging and interactive pathology laboratories were designed. The initial restructuring of the laboratories included new case material, Digital Atlas of Video Education Project videos, animations and overlays. Subsequent changes included USMLE board-style quizzes at the beginning of each laboratory, with individual readiness assessment testing and group readiness assessment testing, incorporation of a clinician as a co-teacher and role playing for the student groups. Student responses for pathology laboratory contribution to learning improved significantly compared to baseline. Increased voluntary attendance at pathology laboratories was observed. Spontaneous student comments noted the positive impact of the laboratories on their learning. Pathology laboratory innovations, including modified team-based learning techniques with individual and group self-assessment quizzes, multimedia presentations, and paired teaching by a pathologist and clinical gastroenterologist led to improvement in student perceptions of pathology laboratory contributions to their learning and better pathology faculty evaluations. These changes can be universally applied to other pathology laboratories to improve student satisfaction. Copyright © 2012 Elsevier GmbH. All rights reserved.

Electric circuits and signals

CERN Document Server

Sabah, Nassir H

2007-01-01

Circuit Variables and Elements Overview Learning Objectives Electric Current Voltage Electric Power and Energy Assigned Positive Directions Active and Passive Circuit Elements Voltage and Current Sources The Resistor The Capacitor The Inductor Concluding Remarks Summary of Main Concepts and Results Learning Outcomes Supplementary Topics on CD Problems and Exercises Basic Circuit Connections and Laws Overview Learning Objectives Circuit Terminology Kirchhoff's Laws Voltage Division and Series Connection of Resistors Current Division and Parallel Connection of Resistors D-Y Transformation Source Equivalence and Transformation Reduced-Voltage Supply Summary of Main Concepts and Results Learning Outcomes Supplementary Topics and Examples on CD Problems and Exercises Basic Analysis of Resistive Circuits Overview Learning Objectives Number of Independent Circuit Equations Node-Voltage Analysis Special Considerations in Node-Voltage Analysis Mesh-Current Analysis Special Conside...

Characteristics of effective schools in facing and reducing bullying

NARCIS (Netherlands)

Kyriakides, Leonidas; Creemers, Bert Peter Maria

This article examines whether variation in school effectiveness in terms of reducing bullying can be attributed to differences in their classroom and school learning environment. All 6th grade students (n = 1504) of 35 primary schools in Cyprus participated in this study. The revised Olweus

Intelligent e-Learning Systems: An Educational Paradigm Shift

Directory of Open Access Journals (Sweden)

Suman Bhattacharya

2016-12-01

Full Text Available Learning is the long process of transforming information as well as experience into knowledge, skills, attitude and behaviors. To make up the wide gap between the demand of increasing higher education and comparatively limited resources, more and more educational institutes are looking into instructional technology. Use of online resources not only reduces the cost of education but also meet the needs of society. Intelligent e-learning has become one of the important channels to reach out to students exceeding geographic boundaries. Besides this, the characteristics of e-learning have complicated the process of education, and have brought challenges to both instructors and students. This paper will focus on the discussion of different discipline of intelligent e-learning like scaffolding based e-learning, personalized e-learning, confidence based e-learning, intelligent tutoring system, etc. to illuminate the educational paradigm shift in intelligent e-learning system.

Remarkable optical red shift and extremely high optical absorption coefficient of V-Ga co-doped TiO2

Science.gov (United States)

Deng, Quanrong; Han, Xiaoping; Gao, Yun; Shao, Guosheng

2012-07-01

A first attempt has been made to study the effect of codoping of transition metal and sp metal on the electronic structure and associated optical properties of TiO2, through V-Ga codoped thin films. V-Ga codoped rutile TiO2 films were fabricated on fused quartz substrates using pulsed laser ablation, followed by heat treatment at high temperatures. Gigantic redshift in the optical absorption edge was observed in V-Ga co-doped TiO2 materials, from UV to infrared region with high absorption coefficient. Through combined structural characterization and theoretical modeling, this is attributed to the p-d hybridization between the two metals. This leads to additional energy bands to overlap with the minimum of the conduction band, leading to remarkably narrowed band gap free of mid-gap states. The direct-gap of the co-doped phase is key to the remarkably high optical absorption coefficient of the coped titania.

Boosting solar investment with limited subsidies: Rent management and policy learning in India

International Nuclear Information System (INIS)

Altenburg, Tilman; Engelmeier, Tobias

2013-01-01

In order to avoid irreversible damage to global ecosystems, new ‘green’ technologies are needed, some of which are nowhere near commercial maturity. In these cases, governments may create temporary rents to make investments ‘artificially’ attractive, but the creation of such rents involves risks of faulty allocation and political capture. This article first highlights the importance of managing rents effectively in promoting ‘green’ technologies; it then shows how India's National Solar Mission has been remarkably effective in triggering solar investments and managing the necessary subsidies, e.g. through a process of competitive reverse bidding for tariffs. Policy design and implementation also reflect considerable experimentation and learning. Some risks remain, especially regarding the enforceability of renewable energy quotas at the level of Indian states. - Highlights: • India's National Solar Mission effectively triggered solar investments. • Reverse bidding substantially decreased policy costs. • Sequenced implementation allowed for policy learning. • India's solar policy is a good example of green rent management

Wavelet-enhanced convolutional neural network: a new idea in a deep learning paradigm.

Science.gov (United States)

Savareh, Behrouz Alizadeh; Emami, Hassan; Hajiabadi, Mohamadreza; Azimi, Seyed Majid; Ghafoori, Mahyar

2018-05-29

Manual brain tumor segmentation is a challenging task that requires the use of machine learning techniques. One of the machine learning techniques that has been given much attention is the convolutional neural network (CNN). The performance of the CNN can be enhanced by combining other data analysis tools such as wavelet transform. In this study, one of the famous implementations of CNN, a fully convolutional network (FCN), was used in brain tumor segmentation and its architecture was enhanced by wavelet transform. In this combination, a wavelet transform was used as a complementary and enhancing tool for CNN in brain tumor segmentation. Comparing the performance of basic FCN architecture against the wavelet-enhanced form revealed a remarkable superiority of enhanced architecture in brain tumor segmentation tasks. Using mathematical functions and enhancing tools such as wavelet transform and other mathematical functions can improve the performance of CNN in any image processing task such as segmentation and classification.

Single molecule microscopy and spectroscopy: concluding remarks.

Science.gov (United States)

van Hulst, Niek F

2015-01-01

Chemistry is all about molecules: control, synthesis, interaction and reaction of molecules. All too easily on a blackboard, one draws molecules, their structures and dynamics, to create an insightful picture. The dream is to see these molecules in reality. This is exactly what "Single Molecule Detection" provides: a look at molecules in action at ambient conditions; a breakthrough technology in chemistry, physics and biology. Within the realms of the Royal Society of Chemistry, the Faraday Discussion on "Single Molecule Microscopy and Spectroscopy" was a very appropriate topic for presentation, deliberation and debate. Undoubtedly, the Faraday Discussions have a splendid reputation in stimulating scientific debates along the traditions set by Michael Faraday. Interestingly, back in the 1830's, Faraday himself pursued an experiment that led to the idea that atoms in a compound were joined by an electrical component. He placed two opposite electrodes in a solution of water containing a dissolved compound, and observed that one of the elements of the compound accumulated on one electrode, while the other was deposited on the opposite electrode. Although Faraday was deeply opposed to atomism, he had to recognize that electrical forces were responsible for the joining of atoms. Probably a direct view on the atoms or molecules in his experiment would have convinced him. As such, Michael Faraday might have liked the gathering at Burlington House in September 2015 (). Surely, with the questioning eyes of his bust on the 1st floor corridor, the non-believer Michael Faraday has incited each passer-by to enter into discussion and search for deeper answers at the level of single molecules. In these concluding remarks, highlights of the presented papers and discussions are summarized, complemented by a conclusion on future perspectives.

Improving the Impact and Return of Investment of Game-Based Learning

Science.gov (United States)

Loh, Christian Sebastian

2013-01-01

Today's economic situation demands that learning organizations become more diligent in their business dealings to reduce cost and increase bottom line for survival. While there are many champions and proponents claiming that game-based learning (GBL) is sure to improve learning, researchers have, thus far, been unable to (re)produce concrete,…

Learned helplessness is independent of levels of brain-derived neurotrophic factor in the hippocampus.

Science.gov (United States)

Greenwood, B N; Strong, P V; Foley, T E; Thompson, R S; Fleshner, M

2007-02-23

Reduced levels of brain-derived neurotrophic factor (BDNF) in the hippocampus have been implicated in human affective disorders and behavioral stress responses. The current studies examined the role of BDNF in the behavioral consequences of inescapable stress, or learned helplessness. Inescapable stress decreased BDNF mRNA and protein in the hippocampus of sedentary rats. Rats allowed voluntary access to running wheels for either 3 or 6 weeks prior to exposure to stress were protected against stress-induced reductions of hippocampal BDNF protein. The observed prevention of stress-induced deceases in BDNF, however, occurred in a time course inconsistent with the prevention of learned helplessness by wheel running, which is evident following 6 weeks, but not 3 weeks, of wheel running. BDNF suppression in physically active rats was produced by administering a single injection of the selective serotonin reuptake inhibitor fluoxetine (10 mg/kg) just prior to stress. Despite reduced levels of hippocampal BDNF mRNA following stress, physically active rats given the combination of fluoxetine and stress remained resistant against learned helplessness. Sedentary rats given both fluoxetine and stress still demonstrated typical learned helplessness behaviors. Fluoxetine by itself reduced BDNF mRNA in sedentary rats only, but did not affect freezing or escape learning 24 h later. Finally, bilateral injections of BDNF (1 mug) into the dentate gyrus prior to stress prevented stress-induced reductions of hippocampal BDNF but did not prevent learned helplessness in sedentary rats. These data indicate that learned helplessness behaviors are independent of the presence or absence of hippocampal BDNF because blocking inescapable stress-induced BDNF suppression does not always prevent learned helplessness, and learned helplessness does not always occur in the presence of reduced BDNF. Results also suggest that the prevention of stress-induced hippocampal BDNF suppression is not

Group-Based Active Learning of Classification Models.

Science.gov (United States)

Luo, Zhipeng; Hauskrecht, Milos

2017-05-01

Learning of classification models from real-world data often requires additional human expert effort to annotate the data. However, this process can be rather costly and finding ways of reducing the human annotation effort is critical for this task. The objective of this paper is to develop and study new ways of providing human feedback for efficient learning of classification models by labeling groups of examples. Briefly, unlike traditional active learning methods that seek feedback on individual examples, we develop a new group-based active learning framework that solicits label information on groups of multiple examples. In order to describe groups in a user-friendly way, conjunctive patterns are used to compactly represent groups. Our empirical study on 12 UCI data sets demonstrates the advantages and superiority of our approach over both classic instance-based active learning work, as well as existing group-based active-learning methods.

An investigation about learning burnout in medical college students and its influencing factors

Directory of Open Access Journals (Sweden)

Li Ling

2014-03-01

Conclusion: Learning burnout in students is of a moderate level. We should help and guide students according to their profession, grade, learning characteristics, and whether they have existing attributional style problems; these interventions should help to reduce learning burnout.

Early onset marijuana use is associated with learning inefficiencies.

Science.gov (United States)

Schuster, Randi Melissa; Hoeppner, Susanne S; Evins, A Eden; Gilman, Jodi M

2016-05-01

Verbal memory difficulties are the most widely reported and persistent cognitive deficit associated with early onset marijuana use. Yet, it is not known what memory stages are most impaired in those with early marijuana use. Forty-eight young adults, aged 18-25, who used marijuana at least once per week and 48 matched nonusing controls (CON) completed the California Verbal Learning Test, Second Edition (CVLT-II). Marijuana users were stratified by age of initial use: early onset users (EMJ), who started using marijuana at or before age 16 (n = 27), and late onset marijuana user group (LMJ), who started using marijuana after age 16 (n = 21). Outcome variables included trial immediate recall, total learning, clustering strategies (semantic clustering, serial clustering, ratio of semantic to serial clustering, and total number of strategies used), delayed recall, and percent retention. Learning improved with repetition, with no group effect on the learning slope. EMJ learned fewer words overall than LMJ or CON. There was no difference between LMJ and CON in total number of words learned. Reduced overall learning mediated the effect on reduced delayed recall among EMJ, but not CON or LMJ. Learning improved with greater use of semantic versus serial encoding, but this did not vary between groups. EMJ was not related to delayed recall after adjusting for encoding. Young adults reporting early onset marijuana use had learning weaknesses, which accounted for the association between early onset marijuana use and delayed recall. No amnestic effect of marijuana use was observed. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Research and application of a novel hybrid decomposition-ensemble learning paradigm with error correction for daily PM10 forecasting

Science.gov (United States)

Luo, Hongyuan; Wang, Deyun; Yue, Chenqiang; Liu, Yanling; Guo, Haixiang

2018-03-01

In this paper, a hybrid decomposition-ensemble learning paradigm combining error correction is proposed for improving the forecast accuracy of daily PM10 concentration. The proposed learning paradigm is consisted of the following two sub-models: (1) PM10 concentration forecasting model; (2) error correction model. In the proposed model, fast ensemble empirical mode decomposition (FEEMD) and variational mode decomposition (VMD) are applied to disassemble original PM10 concentration series and error sequence, respectively. The extreme learning machine (ELM) model optimized by cuckoo search (CS) algorithm is utilized to forecast the components generated by FEEMD and VMD. In order to prove the effectiveness and accuracy of the proposed model, two real-world PM10 concentration series respectively collected from Beijing and Harbin located in China are adopted to conduct the empirical study. The results show that the proposed model performs remarkably better than all other considered models without error correction, which indicates the superior performance of the proposed model.

Remarkable weakness against cleavage stress for YBCO-coated conductors and its effect on the YBCO coil performance

International Nuclear Information System (INIS)

Yanagisawa, Y.; Nakagome, H.; Takematsu, T.; Takao, T.; Sato, N.; Takahashi, M.; Maeda, H.

2011-01-01

Cleavage strength for YBCO-coated conductor is extremely low, typically 0.5 MPa. The remarkable weakness is due to cracks on the slit edge of the conductor. The cleavage stress appears on YBCO double pancake coils impregnated with epoxy. The cleavage stress should be avoided in the coil winding. Cleavage strength for an YBCO-coated conductor at 77 K was investigated with a model experiment. The nominal cleavage strength for an YBCO-coated conductor is extremely low, typically 0.5 MPa. This low nominal cleavage strength is due to stress concentration on a small part of the YBCO-coated conductor in cleavage fracture. Debonding by the cleavage stress occurs at the interface between the buffer layer and the Hastelloy substrate. The nominal cleavage strength for a slit edge of the conductor is 2.5-times lower than that for the original edge of the conductor; cracks and micro-peel existing over the slit edge reduce the cleavage strength for the slit edge. Cleavage stress and peel stress should be avoided in coil winding, as they easily delaminate the YBCO-coated conductor, resulting in substantial degradation of coil performance. These problems are especially important for epoxy impregnated YBCO-coated conductor coils. It appears that effect of cleavage stress and peel stress are mostly negligible for paraffin impregnated YBCO-coated conductor coils or dry wound YBCO-coated conductor coils.

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

Differential learning and memory performance in OEF/OIF veterans for verbal and visual material.

Science.gov (United States)

Sozda, Christopher N; Muir, James J; Springer, Utaka S; Partovi, Diana; Cole, Michael A

2014-05-01

Memory complaints are particularly salient among veterans who experience combat-related mild traumatic brain injuries and/or trauma exposure, and represent a primary barrier to successful societal reintegration and everyday functioning. Anecdotally within clinical practice, verbal learning and memory performance frequently appears differentially reduced versus visual learning and memory scores. We sought to empirically investigate the robustness of a verbal versus visual learning and memory discrepancy and to explore potential mechanisms for a verbal/visual performance split. Participants consisted of 103 veterans with reported history of mild traumatic brain injuries returning home from U.S. military Operations Enduring Freedom and Iraqi Freedom referred for outpatient neuropsychological evaluation. Findings indicate that visual learning and memory abilities were largely intact while verbal learning and memory performance was significantly reduced in comparison, residing at approximately 1.1 SD below the mean for verbal learning and approximately 1.4 SD below the mean for verbal memory. This difference was not observed in verbal versus visual fluency performance, nor was it associated with estimated premorbid verbal abilities or traumatic brain injury history. In our sample, symptoms of depression, but not posttraumatic stress disorder, were significantly associated with reduced composite verbal learning and memory performance. Verbal learning and memory performance may benefit from targeted treatment of depressive symptomatology. Also, because visual learning and memory functions may remain intact, these might be emphasized when applying neurocognitive rehabilitation interventions to compensate for observed verbal learning and memory difficulties.

IS E-LEARNING NECESSARY FOR UNIVERSITY STUDENTS? A Case From Iran

OpenAIRE

Faranak OMIDIAN; Fatemeh KEYVANIFARD

2012-01-01

Today many claim that e-learning can result in considerable time and cost-savings , such as traveling , work time and etc . This study was conducted to investigate these questions: should e-learning be used to reduce travel related stress? should e-learning be offered fully online to reach students living in remote areas? should e-learning be adopted to allow working students to study from home ? Pressure to use e-learning was developed as a factor to answer above questions. Data was colle...

Hebbian Learning is about contingency, not contiguity, and explains the emergence of predictive mirror neurons

NARCIS (Netherlands)

Keysers, C.; Perrett, David I; Gazzola, Valeria

Hebbian Learning should not be reduced to contiguity, as it detects contingency and causality. Hebbian Learning accounts of mirror neurons make predictions that differ from associative learning: Through Hebbian Learning, mirror neurons become dynamic networks that calculate predictions and

Teacher Learning by Script

Science.gov (United States)

Reeves, Jenelle

2010-01-01

Scripted instruction (SI) programs, which direct teachers to teach, even to talk, from a standardized written script, are roundly criticized for inhibiting teacher creativity and teacher learning. In fact, such programs utilize scripting for exactly that reason: to reduce teacher interference with (and presumed weakening of) the prescribed…

Introduction to Metagenomics at DOE JGI (Opening Remarks for the Metagenomics Informatics Challenges Workshop: 10K Genomes at a Time)

Energy Technology Data Exchange (ETDEWEB)

Kyrpides, Nikos [DOE JGI

2011-10-12

After a quick introduction by DOE JGI Director Eddy Rubin, DOE JGI's Nikos Kyrpides delivers the opening remarks at the Metagenomics Informatics Challenges Workshop held at the DOE JGI on October 12-13, 2011

Ego Depletion Impairs Implicit Learning

Science.gov (United States)

Thompson, Kelsey R.; Sanchez, Daniel J.; Wesley, Abigail H.; Reber, Paul J.

2014-01-01

Implicit skill learning occurs incidentally and without conscious awareness of what is learned. However, the rate and effectiveness of learning may still be affected by decreased availability of central processing resources. Dual-task experiments have generally found impairments in implicit learning, however, these studies have also shown that certain characteristics of the secondary task (e.g., timing) can complicate the interpretation of these results. To avoid this problem, the current experiments used a novel method to impose resource constraints prior to engaging in skill learning. Ego depletion theory states that humans possess a limited store of cognitive resources that, when depleted, results in deficits in self-regulation and cognitive control. In a first experiment, we used a standard ego depletion manipulation prior to performance of the Serial Interception Sequence Learning (SISL) task. Depleted participants exhibited poorer test performance than did non-depleted controls, indicating that reducing available executive resources may adversely affect implicit sequence learning, expression of sequence knowledge, or both. In a second experiment, depletion was administered either prior to or after training. Participants who reported higher levels of depletion before or after training again showed less sequence-specific knowledge on the post-training assessment. However, the results did not allow for clear separation of ego depletion effects on learning versus subsequent sequence-specific performance. These results indicate that performance on an implicitly learned sequence can be impaired by a reduction in executive resources, in spite of learning taking place outside of awareness and without conscious intent. PMID:25275517

Ego depletion impairs implicit learning.

Directory of Open Access Journals (Sweden)

Kelsey R Thompson

Full Text Available Implicit skill learning occurs incidentally and without conscious awareness of what is learned. However, the rate and effectiveness of learning may still be affected by decreased availability of central processing resources. Dual-task experiments have generally found impairments in implicit learning, however, these studies have also shown that certain characteristics of the secondary task (e.g., timing can complicate the interpretation of these results. To avoid this problem, the current experiments used a novel method to impose resource constraints prior to engaging in skill learning. Ego depletion theory states that humans possess a limited store of cognitive resources that, when depleted, results in deficits in self-regulation and cognitive control. In a first experiment, we used a standard ego depletion manipulation prior to performance of the Serial Interception Sequence Learning (SISL task. Depleted participants exhibited poorer test performance than did non-depleted controls, indicating that reducing available executive resources may adversely affect implicit sequence learning, expression of sequence knowledge, or both. In a second experiment, depletion was administered either prior to or after training. Participants who reported higher levels of depletion before or after training again showed less sequence-specific knowledge on the post-training assessment. However, the results did not allow for clear separation of ego depletion effects on learning versus subsequent sequence-specific performance. These results indicate that performance on an implicitly learned sequence can be impaired by a reduction in executive resources, in spite of learning taking place outside of awareness and without conscious intent.

Ego depletion impairs implicit learning.

Science.gov (United States)

Thompson, Kelsey R; Sanchez, Daniel J; Wesley, Abigail H; Reber, Paul J

2014-01-01

Implicit skill learning occurs incidentally and without conscious awareness of what is learned. However, the rate and effectiveness of learning may still be affected by decreased availability of central processing resources. Dual-task experiments have generally found impairments in implicit learning, however, these studies have also shown that certain characteristics of the secondary task (e.g., timing) can complicate the interpretation of these results. To avoid this problem, the current experiments used a novel method to impose resource constraints prior to engaging in skill learning. Ego depletion theory states that humans possess a limited store of cognitive resources that, when depleted, results in deficits in self-regulation and cognitive control. In a first experiment, we used a standard ego depletion manipulation prior to performance of the Serial Interception Sequence Learning (SISL) task. Depleted participants exhibited poorer test performance than did non-depleted controls, indicating that reducing available executive resources may adversely affect implicit sequence learning, expression of sequence knowledge, or both. In a second experiment, depletion was administered either prior to or after training. Participants who reported higher levels of depletion before or after training again showed less sequence-specific knowledge on the post-training assessment. However, the results did not allow for clear separation of ego depletion effects on learning versus subsequent sequence-specific performance. These results indicate that performance on an implicitly learned sequence can be impaired by a reduction in executive resources, in spite of learning taking place outside of awareness and without conscious intent.

Learning Pedagogy in Physics

Science.gov (United States)

Harlow, Danielle B.; Swanson, Lauren H.; Dwyer, Hilary A.; Bianchini, Julie A.

2010-10-01

We report on an adapted version of the Physics and Everyday Thinking (PET) curriculum. A unique aspect of PET is its inclusion of special activities that focus on Learning about Learning (LAL) in which undergraduates analyze videos of children talking about science and explicitly consider the nature of science. To create a course that intentionally linked science content, children's ideas, and strategies for science instruction, we augmented the existing LAL activities with discussions about teaching, and added activities focused on LAL from companion curricula such as Physical Science and Everyday Thinking (PSET) and Learning Physical Science (LEPS). To compensate for the additional time on LAL, we reduced the content activities to only those that directly supported LAL activities. We found that students made significant gains on the CLASS and expressed beliefs about teaching consistent with the PET pedagogy.

Mlifdect: Android Malware Detection Based on Parallel Machine Learning and Information Fusion

Directory of Open Access Journals (Sweden)

Xin Wang

2017-01-01

Full Text Available In recent years, Android malware has continued to grow at an alarming rate. More recent malicious apps’ employing highly sophisticated detection avoidance techniques makes the traditional machine learning based malware detection methods far less effective. More specifically, they cannot cope with various types of Android malware and have limitation in detection by utilizing a single classification algorithm. To address this limitation, we propose a novel approach in this paper that leverages parallel machine learning and information fusion techniques for better Android malware detection, which is named Mlifdect. To implement this approach, we first extract eight types of features from static analysis on Android apps and build two kinds of feature sets after feature selection. Then, a parallel machine learning detection model is developed for speeding up the process of classification. Finally, we investigate the probability analysis based and Dempster-Shafer theory based information fusion approaches which can effectively obtain the detection results. To validate our method, other state-of-the-art detection works are selected for comparison with real-world Android apps. The experimental results demonstrate that Mlifdect is capable of achieving higher detection accuracy as well as a remarkable run-time efficiency compared to the existing malware detection solutions.

Spectroscopic and asteroseismic analysis of the remarkable main-sequence A star KIC 11145123

Science.gov (United States)

Takada-Hidai, Masahide; Kurtz, Donald W.; Shibahashi, Hiromoto; Murphy, Simon J.; Takata, Masao; Saio, Hideyuki; Sekii, Takashi

2017-10-01

A spectroscopic analysis was carried out to clarify the properties of KIC 11145123 - the first main-sequence star with a directly measured core-to-surface rotation profile - based on spectra observed with the High Dispersion Spectrograph (HDS) of the Subaru telescope. The atmospheric parameters (Teff = 7600 K, log g = 4.2, ξ = 3.1 km s-1 and [Fe/H] = -0.71 dex), the radial and rotation velocities, and elemental abundances were obtained by analysing line strengths and fitting line profiles, which were calculated with a 1D LTE model atmosphere. The main properties of KIC 11145123 are: (1) a low [Fe/H] = -0.71 ± 0.11 dex and a high radial velocity of -135.4 ± 0.2 km s-1. These are remarkable among late-A stars. Our best asteroseismic models with this low [Fe/H] have slightly high helium abundance and low masses of 1.4 M⊙. All of these results strongly suggest that KIC 11145123 is a Population II blue straggler; (2) the projected rotation velocity confirms the asteroseismically predicted slow rotation of the star; (3) comparisons of abundance patterns between KIC 11145123 and Am, Ap, and blue stragglers show that KIC 11145123 is neither an Am star nor an Ap star, but has abundances consistent with a blue straggler. We conclude that the remarkably long 100-d rotation period of this star is a consequence of it being a blue straggler, but both pathways for the formation of blue stragglers - merger and mass loss in a binary system - pose difficulties for our understanding of the exceedingly slow rotation. In particular, we show that there is no evidence of any secondary companion star, and we put stringent limits on the possible mass of any such purported companion through the phase modulation technique.

Collaborative learning of clinical skills in health professions education

DEFF Research Database (Denmark)

Tolsgaard, Martin G.; Kulasegaram, Kulamakan M.; Ringsted, Charlotte V

2016-01-01

Objectives: This study is designed to provide an overview of why, how, when and for whom collaborative learning of clinical skills may work in health professions education. Why: Collaborative learning of clinical skills may influence learning positively according to the non-medical literature...... suggests that learning is dependent on cognitive co-construction, shared knowledge and reduced cognitive load. When and for whom: The literature on the collaborative learning of clinical skills in health science education is reviewed to support or contradict the hypotheses provided by the theories outlined...... above. Collaborative learning of clinical skills leads to improvements in self-efficacy, confidence and performance when task processing is observable or communicable. However, the effects of collaborative learning of clinical skills may decrease over time as benefits in terms of shared cognition...

Reducing the Risk of Methadone Overdose PSA (:60)

Centers for Disease Control (CDC) Podcasts

2012-07-03

This 60 second PSA is based on the July 2012 CDC Vital Signs report. Approximately 14 people die every day of overdoses related to methadone. Listen to learn how to reduce your risk of an overdose.  Created: 7/3/2012 by Centers for Disease Control and Prevention (CDC).   Date Released: 7/3/2012.

Ensemble Network Architecture for Deep Reinforcement Learning

Directory of Open Access Journals (Sweden)

Xi-liang Chen

2018-01-01

Full Text Available The popular deep Q learning algorithm is known to be instability because of the Q-value’s shake and overestimation action values under certain conditions. These issues tend to adversely affect their performance. In this paper, we develop the ensemble network architecture for deep reinforcement learning which is based on value function approximation. The temporal ensemble stabilizes the training process by reducing the variance of target approximation error and the ensemble of target values reduces the overestimate and makes better performance by estimating more accurate Q-value. Our results show that this architecture leads to statistically significant better value evaluation and more stable and better performance on several classical control tasks at OpenAI Gym environment.

Use what you can: Storage, abstraction processes and perceptual adjustments help listeners recognize reduced forms

Directory of Open Access Journals (Sweden)

Katja ePoellmann

2014-05-01

Full Text Available Three eye-tracking experiments tested whether native listeners recognized reduced Dutch words better after having heard the same reduced words, or different reduced words of the same reduction type and whether familiarization with one reduction type helps listeners to deal with another reduction type. In the exposure phase, a segmental reduction group was exposed to /b/-reductions (e.g., minderij instead of binderij, 'book binder' and a syllabic reduction group was exposed to full-vowel deletions (e.g., p'raat instead of paraat, 'ready', while a control group did not hear any reductions. In the test phase, all three groups heard the same speaker producing reduced-/b/ and deleted-vowel words that were either repeated (Experiments 1 & 2 or new (Experiment 3, but that now appeared as targets in semantically neutral sentences. Word-specific learning effects were found for vowel-deletions but not for /b/-reductions. Generalization of learning to new words of the same reduction type occurred only if the exposure words showed a phonologically consistent reduction pattern (/b/-reductions. In contrast, generalization of learning to words of another reduction type occurred only if the exposure words showed a phonologically inconsistent reduction pattern (the vowel deletions; learning about them generalized to recognition of the /b/-reductions. In order to deal with reductions, listeners thus use various means. They store reduced variants (e.g., for the inconsistent vowel-deleted words and they abstract over incoming information to build up and apply mapping rules (e.g., for the consistent /b/-reductions. Experience with inconsistent pronunciations leads to greater perceptual flexibility in dealing with other forms of reduction uttered by the same speaker than experience with consistent pronunciations.

Integrity assessment of pipelines - additional remarks; Avaliacao da integridade de dutos - observacoes adicionais

Energy Technology Data Exchange (ETDEWEB)

Alves, Luis F.C. [PETROBRAS S.A., Salvador, BA (Brazil). Unidade de Negocios. Exploracao e Producao

2005-07-01

Integrity assessment of pipelines is part of a process that aims to enhance the operating safety of pipelines. During this task, questions related to the interpretation of inspection reports and the way of regarding the impact of several parameters on the pipeline integrity normally come up. In order to satisfactorily answer such questions, the integrity assessment team must be able to suitably approach different subjects such as corrosion control and monitoring, assessment of metal loss and geometric anomalies, and third party activities. This paper presents additional remarks on some of these questions based on the integrity assessment of almost fifty pipelines that has been done at PETROBRAS/E and P Bahia over the past eight years. (author)

Learn, how to learn

Science.gov (United States)

Narayanan, M.

2002-12-01

Ernest L. Boyer, in his 1990 book, "Scholarship Reconsidered: Priorities of the Professorate" cites some ground breaking studies and offers a new paradigm that identifies the need to recognize the growing conversation about teaching, scholarship and research in the Universities. The use of `ACORN' model suggested by Hawkins and Winter to conquer and mastering change, may offer some helpful hints for the novice professor, whose primary objective might be to teach students to `learn how to learn'. Action : It is possible to effectively change things only when a teaching professor actually tries out a new idea. Communication : Changes are successful only when the new ideas effectively communicated and implemented. Ownership : Support for change is extremely important and is critical. Only strong commitment for accepting changes demonstrates genuine leadership. Reflection : Feedback helps towards thoughtful evaluation of the changes implemented. Only reflection can provide a tool for continuous improvement. Nurture : Implemented changes deliver results only when nurtured and promoted with necessary support systems, documentation and infrastructures. Inspired by the ACORN model, the author experimented on implementing certain principles of `Total Quality Management' in the classroom. The author believes that observing the following twenty principles would indeed help the student learners how to learn, on their own towards achieving the goal of `Lifelong Learning'. The author uses an acronym : QUOTES : Quality Underscored On Teaching Excellence Strategy, to describe his methods for improving classroom teacher-learner participation. 1. Break down all barriers. 2. Create consistency of purpose with a plan. 3. Adopt the new philosophy of quality. 4. Establish high Standards. 5. Establish Targets / Goals. 6. Reduce dependence on Lectures. 7. Employ Modern Methods. 8. Control the Process. 9. Organize to reach goals. 10. Prevention vs. Correction. 11. Periodic Improvements. 12

Student Teachers' Proactive Strategies and Experienced Learning Environment for Reducing Study-Related Burnout