WorldWideScience

Sample records for response training network

  1. Training Recurrent Networks

    Pedersen, Morten With

    1997-01-01

    Training recurrent networks is generally believed to be a difficult task. Excessive training times and lack of convergence to an acceptable solution are frequently reported. In this paper we seek to explain the reason for this from a numerical point of view and show how to avoid problems when...... training. In particular we investigate ill-conditioning, the need for and effect of regularization and illustrate the superiority of second-order methods for training...

  2. Controllability of Train Service Network

    Xuelei Meng

    2015-01-01

    Full Text Available Train service network is a network form of train service plan. The controllability of the train service plan determines the recovery possibility of the train service plan in emergencies. We first build the small-world model for train service network and analyze the scale-free character of it. Then based on the linear network controllability theory, we discuss the LB model adaptability in train service network controllability analysis. The LB model is improved and we construct the train service network and define the connotation of the driver nodes based on the immune propagation and cascading failure in the train service network. An algorithm to search for the driver nodes, turning the train service network into a bipartite graph, is proposed and applied in the train service network. We analyze the controllability of the train service network of China with the method and the results of the computing case prove the feasibility of it.

  3. Local Dynamics in Trained Recurrent Neural Networks.

    Rivkind, Alexander; Barak, Omri

    2017-06-23

    Learning a task induces connectivity changes in neural circuits, thereby changing their dynamics. To elucidate task-related neural dynamics, we study trained recurrent neural networks. We develop a mean field theory for reservoir computing networks trained to have multiple fixed point attractors. Our main result is that the dynamics of the network's output in the vicinity of attractors is governed by a low-order linear ordinary differential equation. The stability of the resulting equation can be assessed, predicting training success or failure. As a consequence, networks of rectified linear units and of sigmoidal nonlinearities are shown to have diametrically different properties when it comes to learning attractors. Furthermore, a characteristic time constant, which remains finite at the edge of chaos, offers an explanation of the network's output robustness in the presence of variability of the internal neural dynamics. Finally, the proposed theory predicts state-dependent frequency selectivity in the network response.

  4. Local Dynamics in Trained Recurrent Neural Networks

    Rivkind, Alexander; Barak, Omri

    2017-06-01

    Learning a task induces connectivity changes in neural circuits, thereby changing their dynamics. To elucidate task-related neural dynamics, we study trained recurrent neural networks. We develop a mean field theory for reservoir computing networks trained to have multiple fixed point attractors. Our main result is that the dynamics of the network's output in the vicinity of attractors is governed by a low-order linear ordinary differential equation. The stability of the resulting equation can be assessed, predicting training success or failure. As a consequence, networks of rectified linear units and of sigmoidal nonlinearities are shown to have diametrically different properties when it comes to learning attractors. Furthermore, a characteristic time constant, which remains finite at the edge of chaos, offers an explanation of the network's output robustness in the presence of variability of the internal neural dynamics. Finally, the proposed theory predicts state-dependent frequency selectivity in the network response.

  5. Lateralized odor preference training in rat pups reveals an enhanced network response in anterior piriform cortex to olfactory input that parallels extended memory.

    Fontaine, Christine J; Harley, Carolyn W; Yuan, Qi

    2013-09-18

    The present study examines synaptic plasticity in the anterior piriform cortex (aPC) using ex vivo slices from rat pups given lateralized odor preference training. In the early odor preference learning model, a brief 10 min training session yields 24 h memory, while four daily sessions yield 48 h memory. Odor preference memory can be lateralized through naris occlusion as the anterior commissure is not yet functional. AMPA receptor-mediated postsynaptic responses in the aPC to lateral olfactory tract input, shown to be enhanced at 24 h, are no longer enhanced 48 h after a single training session. Following four spaced lateralized trials, the AMPA receptor-mediated fEPSP is enhanced in the trained aPC at 48 h. Calcium imaging of aPC pyramidal cells within 48 h revealed decreased firing thresholds in the pyramidal cell network. Thus multiday odor preference training induced increased odor input responsiveness in previously weakly activated aPC cells. These results support the hypothesis that increased synaptic strength in olfactory input networks mediates odor preference memory. The increase in aPC network activation parallels behavioral memory.

  6. Supervised learning in spiking neural networks with FORCE training.

    Nicola, Wilten; Clopath, Claudia

    2017-12-20

    Populations of neurons display an extraordinary diversity in the behaviors they affect and display. Machine learning techniques have recently emerged that allow us to create networks of model neurons that display behaviors of similar complexity. Here we demonstrate the direct applicability of one such technique, the FORCE method, to spiking neural networks. We train these networks to mimic dynamical systems, classify inputs, and store discrete sequences that correspond to the notes of a song. Finally, we use FORCE training to create two biologically motivated model circuits. One is inspired by the zebra finch and successfully reproduces songbird singing. The second network is motivated by the hippocampus and is trained to store and replay a movie scene. FORCE trained networks reproduce behaviors comparable in complexity to their inspired circuits and yield information not easily obtainable with other techniques, such as behavioral responses to pharmacological manipulations and spike timing statistics.

  7. Training trajectories by continuous recurrent multilayer networks.

    Leistritz, L; Galicki, M; Witte, H; Kochs, E

    2002-01-01

    This paper addresses the problem of training trajectories by means of continuous recurrent neural networks whose feedforward parts are multilayer perceptrons. Such networks can approximate a general nonlinear dynamic system with arbitrary accuracy. The learning process is transformed into an optimal control framework where the weights are the controls to be determined. A training algorithm based upon a variational formulation of Pontryagin's maximum principle is proposed for such networks. Computer examples demonstrating the efficiency of the given approach are also presented.

  8. Training Results and Information Network

    US Agency for International Development — TraiNet is USAID's official training data management system that is accessed from a web browser and the entry point for data about training programs and participants...

  9. Method Accelerates Training Of Some Neural Networks

    Shelton, Robert O.

    1992-01-01

    Three-layer networks trained faster provided two conditions are satisfied: numbers of neurons in layers are such that majority of work done in synaptic connections between input and hidden layers, and number of neurons in input layer at least as great as number of training pairs of input and output vectors. Based on modified version of back-propagation method.

  10. Nuclear safety education and training network

    Bastos, J.; Ulfkjaer, L.

    2004-01-01

    In March 2001, the Secretariat convened an Advisory Group on Education and Training in nuclear safety. The Advisory Group considered structure, scope and means related to the implementation of an IAEA Programme on Education and Training . A strategic plan was agreed and the following outputs were envisaged: 1. A Training Support Programme in nuclear safety, including a standardized and harmonized approach for training developed by the IAEA and in use by Member States. 2. National and regional training centres, established to support sustainable national nuclear safety infrastructures. 3. Training material for use by lecturers and students developed by the IAEA in English and translated to other languages. The implementation of the plan was initiated in 2002 emphasizing the preparation of training materials. In 2003 a pilot project for a network on Education and Training in Asia was initiated

  11. Dynamic training algorithm for dynamic neural networks

    Tan, Y.; Van Cauwenberghe, A.; Liu, Z.

    1996-01-01

    The widely used backpropagation algorithm for training neural networks based on the gradient descent has a significant drawback of slow convergence. A Gauss-Newton method based recursive least squares (RLS) type algorithm with dynamic error backpropagation is presented to speed-up the learning procedure of neural networks with local recurrent terms. Finally, simulation examples concerning the applications of the RLS type algorithm to identification of nonlinear processes using a local recurrent neural network are also included in this paper

  12. NATO Education and Training Network

    2012-02-01

    Federated Battle Laboratories Network (CFBLNet) .............................................. 15  5.1  History ...CFBLNet countries, NATO nations and Partners perspective (January 2009) 5.1 History In April 1999, the US made a proposal to the NATO C3 Board to...permanent subscription provides standard access to the: • CFBLNet Blackbone ( IPv4 (IPv6) transport network) • CFBLNet CUE (Unclassified Enclave all

  13. Training Deep Spiking Neural Networks Using Backpropagation.

    Lee, Jun Haeng; Delbruck, Tobi; Pfeiffer, Michael

    2016-01-01

    Deep spiking neural networks (SNNs) hold the potential for improving the latency and energy efficiency of deep neural networks through data-driven event-based computation. However, training such networks is difficult due to the non-differentiable nature of spike events. In this paper, we introduce a novel technique, which treats the membrane potentials of spiking neurons as differentiable signals, where discontinuities at spike times are considered as noise. This enables an error backpropagation mechanism for deep SNNs that follows the same principles as in conventional deep networks, but works directly on spike signals and membrane potentials. Compared with previous methods relying on indirect training and conversion, our technique has the potential to capture the statistics of spikes more precisely. We evaluate the proposed framework on artificially generated events from the original MNIST handwritten digit benchmark, and also on the N-MNIST benchmark recorded with an event-based dynamic vision sensor, in which the proposed method reduces the error rate by a factor of more than three compared to the best previous SNN, and also achieves a higher accuracy than a conventional convolutional neural network (CNN) trained and tested on the same data. We demonstrate in the context of the MNIST task that thanks to their event-driven operation, deep SNNs (both fully connected and convolutional) trained with our method achieve accuracy equivalent with conventional neural networks. In the N-MNIST example, equivalent accuracy is achieved with about five times fewer computational operations.

  14. Solar Training Network and Solar Ready Vets

    Dalstrom, Tenley Ann

    2016-09-14

    In 2016, the White House announced the Solar Ready Vets program, funded under DOE's SunShot initiative would be administered by The Solar Foundation to connect transitioning military personnel to solar training and employment as they separate from service. This presentation is geared to informing and recruiting employer partners for the Solar Ready Vets program, and the Solar Training Network. It describes the programs, and the benefits to employers that choose to connect to the programs.

  15. THE EXPERIENCE OF NETWORKING POSTGRADUATE TRAINING PROGRAMMES

    E. A. Teplyashina

    2017-01-01

    Full Text Available Introduction. Present scientific and innovative education programmes focus on the development of applied research in priority areas of industry, cross-industry and regional development. Implementation of such programs is most effective along with the network organization of the process of training. In accordance with the Federal Law on Education in the Russian Federation, this model of networking as «educational institution – educational organization» is a very convenient form of academic mobility realisation.The aim of the present paper is to analyse the model of interaction of the networking postgraduate training programmes at Krasnoyarsk State Medical University named after Prof. V. F. Voino-Yasenetsky and Medical School of Niigata University (Japan.Methodology and research methods involve theoretical analysis of the scientific outcomes of implementing a networking postgraduate training programme, comparative-teaching method, generalization, and pedagogical modeling.Results. The mechanisms of developing the partnership between universities of different countries are detailed. The experience of network international education in a postgraduate study is presented. The presented experience allowed the authors to develop an integrated strategy of cooperation with foreign colleagues in this direction. The advantages and problems of use of a network form of training of academic and teaching staff in a postgraduate school are revealed. The proposals and recommendations on optimization and harmonization of the purposes, tasks and programs of network interaction of the educational organizations are formulated.Practical significance. The proposed materials of the publication can form the base for creation and designing of an effective system of postgraduate education and competitiveness growth of the Russian universities. 

  16. Applications of neural networks in training science.

    Pfeiffer, Mark; Hohmann, Andreas

    2012-04-01

    Training science views itself as an integrated and applied science, developing practical measures founded on scientific method. Therefore, it demands consideration of a wide spectrum of approaches and methods. Especially in the field of competitive sports, research questions are usually located in complex environments, so that mainly field studies are drawn upon to obtain broad external validity. Here, the interrelations between different variables or variable sets are mostly of a nonlinear character. In these cases, methods like neural networks, e.g., the pattern recognizing methods of Self-Organizing Kohonen Feature Maps or similar instruments to identify interactions might be successfully applied to analyze data. Following on from a classification of data analysis methods in training-science research, the aim of the contribution is to give examples of varied sports in which network approaches can be effectually used in training science. First, two examples are given in which neural networks are employed for pattern recognition. While one investigation deals with the detection of sporting talent in swimming, the other is located in game sports research, identifying tactical patterns in team handball. The third and last example shows how an artificial neural network can be used to predict competitive performance in swimming. Copyright © 2011 Elsevier B.V. All rights reserved.

  17. Adaptive training of feedforward neural networks by Kalman filtering

    Ciftcioglu, Oe.

    1995-02-01

    Adaptive training of feedforward neural networks by Kalman filtering is described. Adaptive training is particularly important in estimation by neural network in real-time environmental where the trained network is used for system estimation while the network is further trained by means of the information provided by the experienced/exercised ongoing operation. As result of this, neural network adapts itself to a changing environment to perform its mission without recourse to re-training. The performance of the training method is demonstrated by means of actual process signals from a nuclear power plant. (orig.)

  18. Character Recognition Using Genetically Trained Neural Networks

    Diniz, C.; Stantz, K.M.; Trahan, M.W.; Wagner, J.S.

    1998-10-01

    Computationally intelligent recognition of characters and symbols addresses a wide range of applications including foreign language translation and chemical formula identification. The combination of intelligent learning and optimization algorithms with layered neural structures offers powerful techniques for character recognition. These techniques were originally developed by Sandia National Laboratories for pattern and spectral analysis; however, their ability to optimize vast amounts of data make them ideal for character recognition. An adaptation of the Neural Network Designer soflsvare allows the user to create a neural network (NN_) trained by a genetic algorithm (GA) that correctly identifies multiple distinct characters. The initial successfid recognition of standard capital letters can be expanded to include chemical and mathematical symbols and alphabets of foreign languages, especially Arabic and Chinese. The FIN model constructed for this project uses a three layer feed-forward architecture. To facilitate the input of characters and symbols, a graphic user interface (GUI) has been developed to convert the traditional representation of each character or symbol to a bitmap. The 8 x 8 bitmap representations used for these tests are mapped onto the input nodes of the feed-forward neural network (FFNN) in a one-to-one correspondence. The input nodes feed forward into a hidden layer, and the hidden layer feeds into five output nodes correlated to possible character outcomes. During the training period the GA optimizes the weights of the NN until it can successfully recognize distinct characters. Systematic deviations from the base design test the network's range of applicability. Increasing capacity, the number of letters to be recognized, requires a nonlinear increase in the number of hidden layer neurodes. Optimal character recognition performance necessitates a minimum threshold for the number of cases when genetically training the net. And, the

  19. EHV network operation, maintenance, organization and training

    Gravier, J P [Electricite de France (EDF), 75 - Paris (France)

    1994-12-31

    The service interruptions of electricity have an ever increasing social and industrial impact, it is thus fundamental to operate the network to its best level of performances. To face these changing conditions, Electricite de France has consequently adapted its strategy to improve its organization for maintenance and operation, clarify the operation procedures and give further training to the staff. This work presents the above mentioned issues. (author) 2 figs.

  20. Consistently Trained Artificial Neural Network for Automatic Ship Berthing Control

    Y.A. Ahmed

    2015-09-01

    Full Text Available In this paper, consistently trained Artificial Neural Network controller for automatic ship berthing is discussed. Minimum time course changing manoeuvre is utilised to ensure such consistency and a new concept named ‘virtual window’ is introduced. Such consistent teaching data are then used to train two separate multi-layered feed forward neural networks for command rudder and propeller revolution output. After proper training, several known and unknown conditions are tested to judge the effectiveness of the proposed controller using Monte Carlo simulations. After getting acceptable percentages of success, the trained networks are implemented for the free running experiment system to judge the network’s real time response for Esso Osaka 3-m model ship. The network’s behaviour during such experiments is also investigated for possible effect of initial conditions as well as wind disturbances. Moreover, since the final goal point of the proposed controller is set at some distance from the actual pier to ensure safety, therefore a study on automatic tug assistance is also discussed for the final alignment of the ship with actual pier.

  1. An Improved Walk Model for Train Movement on Railway Network

    Li Keping; Mao Bohua; Gao Ziyou

    2009-01-01

    In this paper, we propose an improved walk model for simulating the train movement on railway network. In the proposed method, walkers represent trains. The improved walk model is a kind of the network-based simulation analysis model. Using some management rules for walker movement, walker can dynamically determine its departure and arrival times at stations. In order to test the proposed method, we simulate the train movement on a part of railway network. The numerical simulation and analytical results demonstrate that the improved model is an effective tool for simulating the train movement on railway network. Moreover, it can well capture the characteristic behaviors of train scheduling in railway traffic. (general)

  2. Artificial Neural Networks for Nonlinear Dynamic Response Simulation in Mechanical Systems

    Christiansen, Niels Hørbye; Høgsberg, Jan Becker; Winther, Ole

    2011-01-01

    It is shown how artificial neural networks can be trained to predict dynamic response of a simple nonlinear structure. Data generated using a nonlinear finite element model of a simplified wind turbine is used to train a one layer artificial neural network. When trained properly the network is ab...... to perform accurate response prediction much faster than the corresponding finite element model. Initial result indicate a reduction in cpu time by two orders of magnitude....

  3. PHMC post-NPH emergency response training

    Conrads, T.J.

    1997-01-01

    This document describes post-Natural Phenomena Hazard (NPH) emergency response training that was provided to two teams of Project Hanford Management Contractors (PHMC) staff that will be used to assess potential structural damage that may occur as a result of a significant natural phenomena event. This training supports recent plans and procedures to use trained staff to inspect structures following an NPH event on the Hanford Site

  4. PHMC post-NPH emergency response training

    Conrads, T.J.

    1997-04-08

    This document describes post-Natural Phenomena Hazard (NPH) emergency response training that was provided to two teams of Project Hanford Management Contractors (PHMC) staff that will be used to assess potential structural damage that may occur as a result of a significant natural phenomena event. This training supports recent plans and procedures to use trained staff to inspect structures following an NPH event on the Hanford Site.

  5. Parallelization of Neural Network Training for NLP with Hogwild!

    Deyringer Valentin

    2017-10-01

    Full Text Available Neural Networks are prevalent in todays NLP research. Despite their success for different tasks, training time is relatively long. We use Hogwild! to counteract this phenomenon and show that it is a suitable method to speed up training Neural Networks of different architectures and complexity. For POS tagging and translation we report considerable speedups of training, especially for the latter. We show that Hogwild! can be an important tool for training complex NLP architectures.

  6. Introduction to the EC's Marie Curie Initial Training Network (MC-ITN) project: Particle Training Network for European Radiotherapy (PARTNER).

    Dosanjh, Manjit; Magrin, Giulio

    2013-07-01

    PARTNER (Particle Training Network for European Radiotherapy) is a project funded by the European Commission's Marie Curie-ITN funding scheme through the ENLIGHT Platform for 5.6 million Euro. PARTNER has brought together academic institutes, research centres and leading European companies, focusing in particular on a specialized radiotherapy (RT) called hadron therapy (HT), interchangeably referred to as particle therapy (PT). The ultimate goal of HT is to deliver more effective treatment to cancer patients leading to major improvement in the health of citizens. In Europe, several hundred million Euro have been invested, since the beginning of this century, in PT. In this decade, the use of HT is rapidly growing across Europe, and there is an urgent need for qualified researchers from a range of disciplines to work on its translational research. In response to this need, the European community of HT, and in particular 10 leading academic institutes, research centres, companies and small and medium-sized enterprises, joined together to form the PARTNER consortium. All partners have international reputations in the diverse but complementary fields associated with PT: clinical, radiobiological and technological. Thus the network incorporates a unique set of competencies, expertise, infrastructures and training possibilities. This paper describes the status and needs of PT research in Europe, the importance of and challenges associated with the creation of a training network, the objectives, the initial results, and the expected long-term benefits of the PARTNER initiative.

  7. Introduction to the EC's marie curie initial training network (MC-ITN) project. Particle training network for European radiotherapy (PARTNER)

    Dosanjh, Manjit; Magrin, Giulio

    2013-01-01

    PARTNER (Particle Training Network for European Radiotherapy) is a project funded by the European Commission's Marie Curie-ITN funding scheme through the ENLIGHT Platform for 5.6 million Euro. PARTNER has brought together academic institutes, research centres and leading European companies, focusing in particular on a specialized radiotherapy (RT) called hadron therapy (HT), interchangeably referred to as particle therapy (PT). The ultimate goal of HT is to deliver more effective treatment to cancer patients leading to major improvement in the health of citizens. In Europe, several hundred million Euro have been invested, since the beginning of this century, in PT. In this decade, the use of HT is rapidly growing across Europe, and there is an urgent need for qualified researchers from a range of disciplines to work on its translational research. In response to this need, the European community of HT, and in particular 10 leading academic institutes, research centres, companies and small and medium-sized enterprises, joined together to form the PARTNER consortium. All partners have international reputations in the diverse but complementary fields associated with PT: clinical, radiobiological and technological. Thus the network incorporates a unique set of competencies, expertise, infrastructures and training possibilities. This paper describes the status and needs of PT research in Europe, the importance of and challenges associated with the creation of a training network, the objectives, the initial results, and the expected long-term benefits of the PARTNER initiative. (author)

  8. STIR: Assessing and Training Response Inhibition Abilities

    2014-07-30

    Learning to stop responding to alcohol cues reduces alcohol intake via reduced affective associations rather than increased response inhibition. Addiction ...requires an abstract application of the core learning principle1,2, and viable examples are often hard to find and/or assess. If exposure to non...inhibition training that expands upon previous successful “near transfer” response inhibition training efforts—such as treating alcohol addictions by

  9. Towards dropout training for convolutional neural networks.

    Wu, Haibing; Gu, Xiaodong

    2015-11-01

    Recently, dropout has seen increasing use in deep learning. For deep convolutional neural networks, dropout is known to work well in fully-connected layers. However, its effect in convolutional and pooling layers is still not clear. This paper demonstrates that max-pooling dropout is equivalent to randomly picking activation based on a multinomial distribution at training time. In light of this insight, we advocate employing our proposed probabilistic weighted pooling, instead of commonly used max-pooling, to act as model averaging at test time. Empirical evidence validates the superiority of probabilistic weighted pooling. We also empirically show that the effect of convolutional dropout is not trivial, despite the dramatically reduced possibility of over-fitting due to the convolutional architecture. Elaborately designing dropout training simultaneously in max-pooling and fully-connected layers, we achieve state-of-the-art performance on MNIST, and very competitive results on CIFAR-10 and CIFAR-100, relative to other approaches without data augmentation. Finally, we compare max-pooling dropout and stochastic pooling, both of which introduce stochasticity based on multinomial distributions at pooling stage. Copyright © 2015 Elsevier Ltd. All rights reserved.

  10. An Efficient Supervised Training Algorithm for Multilayer Spiking Neural Networks.

    Xie, Xiurui; Qu, Hong; Liu, Guisong; Zhang, Malu; Kurths, Jürgen

    2016-01-01

    The spiking neural networks (SNNs) are the third generation of neural networks and perform remarkably well in cognitive tasks such as pattern recognition. The spike emitting and information processing mechanisms found in biological cognitive systems motivate the application of the hierarchical structure and temporal encoding mechanism in spiking neural networks, which have exhibited strong computational capability. However, the hierarchical structure and temporal encoding approach require neurons to process information serially in space and time respectively, which reduce the training efficiency significantly. For training the hierarchical SNNs, most existing methods are based on the traditional back-propagation algorithm, inheriting its drawbacks of the gradient diffusion and the sensitivity on parameters. To keep the powerful computation capability of the hierarchical structure and temporal encoding mechanism, but to overcome the low efficiency of the existing algorithms, a new training algorithm, the Normalized Spiking Error Back Propagation (NSEBP) is proposed in this paper. In the feedforward calculation, the output spike times are calculated by solving the quadratic function in the spike response model instead of detecting postsynaptic voltage states at all time points in traditional algorithms. Besides, in the feedback weight modification, the computational error is propagated to previous layers by the presynaptic spike jitter instead of the gradient decent rule, which realizes the layer-wised training. Furthermore, our algorithm investigates the mathematical relation between the weight variation and voltage error change, which makes the normalization in the weight modification applicable. Adopting these strategies, our algorithm outperforms the traditional SNN multi-layer algorithms in terms of learning efficiency and parameter sensitivity, that are also demonstrated by the comprehensive experimental results in this paper.

  11. Response to Commentaries on Bystander Training as Leadership Training.

    Katz, Jackson

    2018-03-01

    In this article, the author responds to three commentaries about his article "Bystander Training as Leadership Training: Notes on the Origins, Philosophy, and Pedagogy of the Mentors in Violence Prevention Model," published in this volume. Topics covered in the commentaries and response include questions about evaluation and evidence for program effectiveness; the necessity for gender violence prevention education to be gender transformative and part of a comprehensive, multilevel prevention approach, especially for adolescents; and the degree to which Mentors in Violence Prevention (MVP), as a "social justice"-oriented program, incorporates intersectional and anti-oppression frameworks and perspectives.

  12. Short radiological emergency response training program

    Williams, R.D.; Greenhouse, N.A.

    1977-01-01

    This paper presents an outline of a radiological emergency response training program conducted at Brookhaven National Laboratory by the health physics and safety training staff. This course is given to groups from local, county, state, and federal agencies and industrial organizations. It is normally three days in length, although the structure is flexible to accommodate individual needs and prior training. An important feature of the course is an emergency exercise utilizing a short lived radionuclide to better simulate real accident conditions. Groups are encouraged to use their own instruments to gain better familiarity with their operating characteristics under field conditions. Immediately following the exercise, a critical review of the students' performance is conducted

  13. Train-Network Interactions and Stability Evaluation in High-Speed Railways--Part I: Phenomena and Modeling

    Hu, Haitao; Tao, Haidong; Blaabjerg, Frede

    2018-01-01

    of the electric trains and traction network are equally modeled. In which, an impedance-based input behavior of the train is fully investigated with considering available controllers and their parameters in DQ-domain. While, the entire traction network, including traction transformer, catenary, supply lines......, is represented in a frequency-domain nodal matrix. Furthermore, the impedance-frequency responses of both electric train and traction network are measured and validated through frequency scan method. Finally, a generalized train-network simulation and experimental systems are proposed for verifying...

  14. Neural network training by Kalman filtering in process system monitoring

    Ciftcioglu, Oe.

    1996-03-01

    Kalman filtering approach for neural network training is described. Its extended form is used as an adaptive filter in a nonlinear environment of the form a feedforward neural network. Kalman filtering approach generally provides fast training as well as avoiding excessive learning which results in enhanced generalization capability. The network is used in a process monitoring application where the inputs are measurement signals. Since the measurement errors are also modelled in Kalman filter the approach yields accurate training with the implication of accurate neural network model representing the input and output relationships in the application. As the process of concern is a dynamic system, the input source of information to neural network is time dependent so that the training algorithm presents an adaptive form for real-time operation for the monitoring task. (orig.)

  15. Behaviour in O of the Neural Networks Training Cost

    Goutte, Cyril

    1998-01-01

    We study the behaviour in zero of the derivatives of the cost function used when training non-linear neural networks. It is shown that a fair number offirst, second and higher order derivatives vanish in zero, validating the belief that 0 is a peculiar and potentially harmful location. These calc......We study the behaviour in zero of the derivatives of the cost function used when training non-linear neural networks. It is shown that a fair number offirst, second and higher order derivatives vanish in zero, validating the belief that 0 is a peculiar and potentially harmful location....... These calculations arerelated to practical and theoretical aspects of neural networks training....

  16. Contemporary social network sites: Relevance in anesthesiology teaching, training, and research.

    Haldar, Rudrashish; Kaushal, Ashutosh; Samanta, Sukhen; Ambesh, Paurush; Srivastava, Shashi; Singh, Prabhat K

    2016-01-01

    The phenomenal popularity of social networking sites has been used globally by medical professionals to boost professional associations and scientific developments. They have tremendous potential to forge professional liaisons, generate employment,upgrading skills and publicizing scientific achievements. We highlight the role of social networking mediums in influencing teaching, training and research in anaesthesiology. The growth of social networking sites have been prompted by the limitations of previous facilities in terms of ease of data and interface sharing and the amalgamation of audio visual aids on common platforms in the newer facilities. Contemporary social networking sites like Facebook, Twitter, Tumblr,Linkedn etc and their respective features based on anaesthesiology training or practice have been discussed. A host of advantages which these sites confer are also discussed. Likewise the potential pitfalls and drawbacks of these facilities have also been addressed. Social networking sites have immense potential for development of training and research in Anaesthesiology. However responsible and cautious utilization is advocated.

  17. Radar Training Facility Local Area Network -

    Department of Transportation — The RTF LAN system provides a progressive training environment for initial and refresher radar training qualification for new and re-hired FAA employees. Its purpose...

  18. Training strategy for convolutional neural networks in pedestrian gender classification

    Ng, Choon-Boon; Tay, Yong-Haur; Goi, Bok-Min

    2017-06-01

    In this work, we studied a strategy for training a convolutional neural network in pedestrian gender classification with limited amount of labeled training data. Unsupervised learning by k-means clustering on pedestrian images was used to learn the filters to initialize the first layer of the network. As a form of pre-training, supervised learning for the related task of pedestrian classification was performed. Finally, the network was fine-tuned for gender classification. We found that this strategy improved the network's generalization ability in gender classification, achieving better test results when compared to random weights initialization and slightly more beneficial than merely initializing the first layer filters by unsupervised learning. This shows that unsupervised learning followed by pre-training with pedestrian images is an effective strategy to learn useful features for pedestrian gender classification.

  19. Digital intelligent booster for DCC miniature train networks

    Ursu, M. P.; Condruz, D. A.

    2017-08-01

    Modern miniature trains are now driven by means of the DCC (Digital Command and Control) system, which allows the human operator or a personal computer to launch commands to each individual train or even to control different features of the same train. The digital command station encodes these commands and sends them to the trains by means of electrical pulses via the rails of the railway network. Due to the development of the miniature railway network, it may happen that the power requirement of the increasing number of digital locomotives, carriages and accessories exceeds the nominal output power of the digital command station. This digital intelligent booster relieves the digital command station from powering the entire railway network all by itself, and it automatically handles the multiple powered sections of the network. This electronic device is also able to detect and process short-circuits and overload conditions, without the intervention of the digital command station.

  20. Training of reverse propagation neural networks applied to neutron dosimetry

    Hernandez P, C. F.; Martinez B, M. R.; Leon P, A. A.; Espinoza G, J. G.; Castaneda M, V. H.; Solis S, L. O.; Castaneda M, R.; Ortiz R, M.; Vega C, H. R.; Mendez V, R.; Gallego, E.; De Sousa L, M. A.

    2016-10-01

    Neutron dosimetry is of great importance in radiation protection as aims to provide dosimetric quantities to assess the magnitude of detrimental health effects due to exposure of neutron radiation. To quantify detriment to health is necessary to evaluate the dose received by the occupationally exposed personnel using different detection systems called dosimeters, which have very dependent responses to the energy distribution of neutrons. The neutron detection is a much more complex problem than the detection of charged particles, since it does not carry an electric charge, does not cause direct ionization and has a greater penetration power giving the possibility of interacting with matter in a different way. Because of this, various neutron detection systems have been developed, among which the Bonner spheres spectrometric system stands out due to the advantages that possesses, such as a wide range of energy, high sensitivity and easy operation. However, once obtained the counting rates, the problem lies in the neutron spectrum deconvolution, necessary for the calculation of the doses, using different mathematical methods such as Monte Carlo, maximum entropy, iterative methods among others, which present various difficulties that have motivated the development of new technologies. Nowadays, methods based on artificial intelligence technologies are being used to perform neutron dosimetry, mainly using the theory of artificial neural networks. In these new methods the need for spectrum reconstruction can be eliminated for the calculation of the doses. In this work an artificial neural network or reverse propagation was trained for the calculation of 15 equivalent doses from the counting rates of the Bonner spheres spectrometric system using a set of 7 spheres, one of 2 spheres and two of a single sphere of different sizes, testing different error values until finding the most appropriate. The optimum network topology was obtained through the robust design

  1. EXPERIENCE NETWORKING UNIVERSITY OF EDUCATION TRAINING MASTERS SAFETY OF LIFE

    Elvira Mikhailovna Rebko

    2016-01-01

    The article discloses experience networking of universities (Herzen State Pedagogical University and Sakhalin State University) in the development and implementation of joint training programs for master’s education in the field of life safety «Social security in the urban environment». The novelty of the work is to create a schematic design of basic educational training program for master’s education in the mode of networking, and to identify effective instructional techniques and conditions...

  2. International Nuclear Security Education Network (INSEN) and the Nuclear Security Training and Support Centre (NSSC) Network

    Nikonov, Dmitriy

    2013-01-01

    International Nuclear Security Education Network established in 2010: A partnership between the IAEA and universities, research institutions and other stakeholders - •Promotion of nuclear security education; • Development of educational materials; • Professional development for faculty members; • Collaborative research and resource sharing. Currently over 90 members from 38 member states. Mission: to enhance global nuclear security by developing, sharing and promoting excellence in nuclear security education. Nuclear Security Support Centre: Primary objectives are: • Develop human resources through the implementation of a tailored training programme; • Develop a network of experts; • Provide technical support for lifecycle equipment management and scientific support for the detection of and the response to nuclear security events

  3. Cold weather oil spill response training

    Solsberg, L.B.; Owens, E.H.

    2001-01-01

    In April 2000, a three-day oil spill response training program was conducted on Alaska's North Slope. The unique hands-on program was specifically developed for Chevron Corporation's world-wide response team. It featured a combination of classroom and outdoor sessions that helped participants to learn and apply emergency measures in a series of field exercises performed in very cold weather conditions. Temperatures remained below minus 20 degrees C and sometimes reached minus 40 degrees C throughout the training. The classroom instructions introduced participants to the Emergency Prevention Preparedness and Response (EPPR) Working Group's Field Guide for Spill Response in Arctic Waters. This guide provides response strategies specific to the Arctic, including open water, ice and snow conditions. The sessions also reviewed the Alaska Clean Seas Tactics Manual which addresses spill containment and recovery, storage, tracking, burning and disposal. The issues that were emphasized throughout the training program were cold weather safety and survival. During the training sessions, participants were required to set up weather ports and drive snowmobiles and all terrain vehicles. Their mission was to detect oil with infra-red and hand-held devices. They were required to contain the oil by piling snow into snow banks, and by augering, trenching and slotting ice. Oil was removed by trimming operations on solid ice, snow melting, snow blowing, skimming and pumping. In-situ burning was also performed. Other sessions were also conducted develop skills in site characterization and treating oiled shorelines. The successfully conducted field sessions spanned all phases of a cleanup operation in cold weather. 5 refs., 7 figs

  4. Transfer of Training: Adding Insight through Social Network Analysis

    Van den Bossche, Piet; Segers, Mien

    2013-01-01

    This article reviews studies which apply a social network perspective to examine transfer of training. The theory behind social networks focuses on the interpersonal mechanisms and social structures that exist among interacting units such as people within an organization. A premise of this perspective is that individual's behaviors and outcomes…

  5. African Network Operators Group (AfNOG) Training Workshops and ...

    The African Network Operators Group (AfNOG) is a forum for technical cooperation and coordination between African network operators and engineers from the region's universities, research institutions and industry. This year, AfNOG's training workshops and meetings will be held in Rabat, Morocco, between 24 May and 6 ...

  6. Improving the Robustness of Deep Neural Networks via Stability Training

    Zheng, Stephan; Song, Yang; Leung, Thomas; Goodfellow, Ian

    2016-01-01

    In this paper we address the issue of output instability of deep neural networks: small perturbations in the visual input can significantly distort the feature embeddings and output of a neural network. Such instability affects many deep architectures with state-of-the-art performance on a wide range of computer vision tasks. We present a general stability training method to stabilize deep networks against small input distortions that result from various types of common image processing, such...

  7. Introduction to the EC's Marie Curie Initial Training Network (MC-ITN) project: Particle Training Network for European Radiotherapy (PARTNER)

    Dosanjh, Manjit

    2013-01-01

    PARTNER (Particle Training Network for European Radiotherapy) is a project funded by the European Commission’s Marie Curie-ITN funding scheme through the ENLIGHT Platform for 5.6 million Euro. PARTNER has brought together academic institutes, research centres and leading European companies, focusing in particular on a specialized radiotherapy (RT) called hadron therapy (HT), interchangeably referred to as particle therapy (PT). The ultimate goal of HT is to deliver more effective treatment to cancer patients leading to major improvement in the health of citizens. In Europe, several hundred million Euro have been invested, since the beginning of this century, in PT. In this decade, the use of HT is rapidly growing across Europe, and there is an urgent need for qualified researchers from a range of disciplines to work on its translational research. In response to this need, the European community of HT, and in particular 10 leading academic institutes, research centres, companies and small and medium-sized en...

  8. Network Culture, Performance & Corporate Responsibility

    Silvio M. Brondoni

    2003-01-01

    The growth and sustainability of free market economies highlights the need to define rules more suited to the current condition of market globalisation and also encourages firms to adopt more transparent and accountable corporate responsibility (and corporate social responsibility, namely the relationship between the company, environment and social setting). From a managerial perspective, corporate responsibility is linked to ensure the lasting pursuit of the company mission, seeking increasi...

  9. Accelerating deep neural network training with inconsistent stochastic gradient descent.

    Wang, Linnan; Yang, Yi; Min, Renqiang; Chakradhar, Srimat

    2017-09-01

    Stochastic Gradient Descent (SGD) updates Convolutional Neural Network (CNN) with a noisy gradient computed from a random batch, and each batch evenly updates the network once in an epoch. This model applies the same training effort to each batch, but it overlooks the fact that the gradient variance, induced by Sampling Bias and Intrinsic Image Difference, renders different training dynamics on batches. In this paper, we develop a new training strategy for SGD, referred to as Inconsistent Stochastic Gradient Descent (ISGD) to address this problem. The core concept of ISGD is the inconsistent training, which dynamically adjusts the training effort w.r.t the loss. ISGD models the training as a stochastic process that gradually reduces down the mean of batch's loss, and it utilizes a dynamic upper control limit to identify a large loss batch on the fly. ISGD stays on the identified batch to accelerate the training with additional gradient updates, and it also has a constraint to penalize drastic parameter changes. ISGD is straightforward, computationally efficient and without requiring auxiliary memories. A series of empirical evaluations on real world datasets and networks demonstrate the promising performance of inconsistent training. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. EXPERIENCE NETWORKING UNIVERSITY OF EDUCATION TRAINING MASTERS SAFETY OF LIFE

    Elvira Mikhailovna Rebko

    2016-02-01

    Full Text Available The article discloses experience networking of universities (Herzen State Pedagogical University and Sakhalin State University in the development and implementation of joint training programs for master’s education in the field of life safety «Social security in the urban environment». The novelty of the work is to create a schematic design of basic educational training program for master’s education in the mode of networking, and to identify effective instructional techniques and conditions of networking.Purpose – present the results of the joint development of a network of the basic educational program (BEP, to identify the stages of networking, to design a generalized scheme of development and implementation of a network of educational training program for master’s education in the field of life safety.Results generalized model of networking partner institutions to develop and implement the basic educational program master.Practical implications: the education process for Master of Education in the field of health and safety in Herzen State Pedagogical University and Sakhalin State University.

  11. Role of physical and mental training in brain network configuration.

    Foster, Philip P

    2015-01-01

    It is hypothesized that the topology of brain networks is constructed by connecting nodes which may be continuously remodeled by appropriate training. Efficiency of physical and/or mental training on the brain relies on the flexibility of networks' architecture molded by local remodeling of proteins and synapses of excitatory neurons producing transformations in network topology. Continuous remodeling of proteins of excitatory neurons is fine-tuning the scaling and strength of excitatory synapses up or down via regulation of intra-cellular metabolic and regulatory networks of the genome-transcriptome-proteome interface. Alzheimer's disease is a model of "energy cost-driven small-world network disorder" with dysfunction of high-energy cost wiring as the network global efficiency is impaired by the deposition of an informed agent, the amyloid-β, selectively targeting high-degree nodes. In schizophrenia, the interconnectivity and density of rich-club networks are significantly reduced. Training-induced homeostatic synaptogenesis-enhancement, presumably via reconfiguration of brain networks into greater small-worldness, appears essential in learning, memory, and executive functions. A macroscopic cartography of creation-removal of synaptic connections in a macro-network, and at the intra-cellular scale, micro-networks regulate the physiological mechanisms for the preferential attachment of synapses. The strongest molecular relationship of exercise and functional connectivity was identified for brain-derived neurotrophic factor (BDNF). The allele variant, rs7294919, also shows a powerful relationship with the hippocampal volume. How the brain achieves this unique quest of reconfiguration remains a puzzle. What are the underlying mechanisms of synaptogenesis promoting communications brain ↔ muscle and brain ↔ brain in such trainings? What is the respective role of independent mental, physical, or combined-mental-physical trainings? Physical practice seems to be

  12. Establishing Network Interaction between Resource Training Centers for People with Disabilities and Partner Universities

    Panyukova S.V.,

    2018-05-01

    Full Text Available The paper focuses on the problem of accessibility and quality of higher education for students with disabilities. We describe our experience in organising network interaction between the MSUPE Resource and Training Center for Disabled People established in 2016-2017 and partner universities in ‘fixed territories’. The need for cooperation and network interaction arises from the high demand for the cooperation of efforts of leading experts, researchers, methodologists and instructors necessary for improving the quality and accessibility of higher education for persons with disabilities. The Resource and Training Center offers counseling for the partner universities, arranges advanced training for those responsible for teaching of the disabled, and offers specialized equipment for temporary use. In this article, we emphasize the importance of organizing network interactions with universities and social partners in order to ensure accessibility of higher education for students with disabilities.

  13. Modelling electric trains energy consumption using Neural Networks

    Martinez Fernandez, P.; Garcia Roman, C.; Insa Franco, R.

    2016-07-01

    Nowadays there is an evident concern regarding the efficiency and sustainability of the transport sector due to both the threat of climate change and the current financial crisis. This concern explains the growth of railways over the last years as they present an inherent efficiency compared to other transport means. However, in order to further expand their role, it is necessary to optimise their energy consumption so as to increase their competitiveness. Improving railways energy efficiency requires both reliable data and modelling tools that will allow the study of different variables and alternatives. With this need in mind, this paper presents the development of consumption models based on neural networks that calculate the energy consumption of electric trains. These networks have been trained based on an extensive set of consumption data measured in line 1 of the Valencia Metro Network. Once trained, the neural networks provide a reliable estimation of the vehicles consumption along a specific route when fed with input data such as train speed, acceleration or track longitudinal slope. These networks represent a useful modelling tool that may allow a deeper study of railway lines in terms of energy expenditure with the objective of reducing the costs and environmental impact associated to railways. (Author)

  14. Role of physical and mental training in brain network configuration

    Philip P. Foster

    2015-06-01

    Full Text Available Continuous remodeling of proteins of excitatory neurons is fine-tuning the scaling and strength of excitatory synapses up or down via regulation of intra-cellular metabolic and regulatory networks of the genome-transcriptome-proteome interface. Alzheimer's disease is a model of energy cost-driven small-world network disorder as the network global efficiency is impaired by the deposition of an informed agent, the amyloid-β, selectively targeting high-degree nodes. In schizophrenia, the interconnectivity and density of rich-club networks are significantly reduced. Training-induced homeostatic synaptogenesis-enhancement produces a reconfiguration of brain networks into greater small-worldness. Creation of synaptic connections in a macro-network, and, at the intra-cellular scale, micro-networks regulate the physiological mechanisms for the preferential attachment of synapses. The strongest molecular relationship of exercise and functional connectivity was identified for brain-derived neurotrophic factor (BDNF. The allele variant, rs7294919, also shows a powerful relationship with the hippocampal volume. How the brain achieves this unique quest of reconfiguration remains a puzzle. What are the underlying mechanisms of synaptogenesis promoting communications brain ↔ muscle and brain ↔ brain in such trainings? What is the respective role of independent mental, physical or combined-mental-physical trainings? Physical practice seems to be playing an instrumental role in the cognitive enhancement (brain ↔ muscle com.. However, mental training, meditation or virtual reality (films, games require only minimal motor activity and cardio-respiratory stimulation. Therefore, other potential paths (brain ↔ brain com. molding brain networks are nonetheless essential. Patients with motor neuron disease/injury (e.g. amyotrophic lateral sclerosis, traumatism also achieve successful cognitive enhancement albeit they may only elicit mental practice

  15. An accelerated training method for back propagation networks

    Shelton, Robert O. (Inventor)

    1993-01-01

    The principal objective is to provide a training procedure for a feed forward, back propagation neural network which greatly accelerates the training process. A set of orthogonal singular vectors are determined from the input matrix such that the standard deviations of the projections of the input vectors along these singular vectors, as a set, are substantially maximized, thus providing an optimal means of presenting the input data. Novelty exists in the method of extracting from the set of input data, a set of features which can serve to represent the input data in a simplified manner, thus greatly reducing the time/expense to training the system.

  16. Revisiting Social Network Utilization by Physicians-in-Training.

    Black, Erik W; Thompson, Lindsay A; Duff, W Patrick; Dawson, Kara; Saliba, Heidi; Black, Nicole M Paradise

    2010-06-01

    To measure and compare the frequency and content of online social networking among 2 cohorts of medical students and residents (2007 and 2009). Using the online social networking application Facebook, we evaluated social networking profiles for 2 cohorts of medical students (n  =  528) and residents (n  =  712) at the University of Florida in Gainesville. Objective measures included existence of a profile, whether it was made private, and whether any personally identifiable information was included. Subjective outcomes included photographic content, affiliated social groups, and personal information not generally disclosed in a doctor-patient encounter. We compared our results to our previously published and reported data from 2007. Social networking continues to be common amongst physicians-in-training, with 39.8% of residents and 69.5% of medical students maintaining Facebook accounts. Residents' participation significantly increased (P privacy settings (P privacy and the expansive and impersonal networks of online "friends" who may view profiles.

  17. Bayesian model ensembling using meta-trained recurrent neural networks

    Ambrogioni, L.; Berezutskaya, Y.; Gü ç lü , U.; Borne, E.W.P. van den; Gü ç lü tü rk, Y.; Gerven, M.A.J. van; Maris, E.G.G.

    2017-01-01

    In this paper we demonstrate that a recurrent neural network meta-trained on an ensemble of arbitrary classification tasks can be used as an approximation of the Bayes optimal classifier. This result is obtained by relying on the framework of e-free approximate Bayesian inference, where the Bayesian

  18. Bioinformatics Training Network (BTN): a community resource for bioinformatics trainers

    Schneider, Maria V.; Walter, Peter; Blatter, Marie-Claude

    2012-01-01

    and clearly tagged in relation to target audiences, learning objectives, etc. Ideally, they would also be peer reviewed, and easily and efficiently accessible for downloading. Here, we present the Bioinformatics Training Network (BTN), a new enterprise that has been initiated to address these needs and review...

  19. The Analysis of User Behaviour of a Network Management Training Tool using a Neural Network

    Helen Donelan

    2005-10-01

    Full Text Available A novel method for the analysis and interpretation of data that describes the interaction between trainee network managers and a network management training tool is presented. A simulation based approach is currently being used to train network managers, through the use of a simulated network. The motivation is to provide a tool for exposing trainees to a life like situation without disrupting a live network. The data logged by this system describes the detailed interaction between trainee network manager and simulated network. The work presented here provides an analysis of this interaction data that enables an assessment of the capabilities of the trainee network manager as well as an understanding of how the network management tasks are being approached. A neural network architecture is implemented in order to perform an exploratory data analysis of the interaction data. The neural network employs a novel form of continuous self-organisation to discover key features in the data and thus provide new insights into the learning and teaching strategies employed.

  20. Parallel Evolutionary Optimization for Neuromorphic Network Training

    Schuman, Catherine D [ORNL; Disney, Adam [University of Tennessee (UT); Singh, Susheela [North Carolina State University (NCSU), Raleigh; Bruer, Grant [University of Tennessee (UT); Mitchell, John Parker [University of Tennessee (UT); Klibisz, Aleksander [University of Tennessee (UT); Plank, James [University of Tennessee (UT)

    2016-01-01

    One of the key impediments to the success of current neuromorphic computing architectures is the issue of how best to program them. Evolutionary optimization (EO) is one promising programming technique; in particular, its wide applicability makes it especially attractive for neuromorphic architectures, which can have many different characteristics. In this paper, we explore different facets of EO on a spiking neuromorphic computing model called DANNA. We focus on the performance of EO in the design of our DANNA simulator, and on how to structure EO on both multicore and massively parallel computing systems. We evaluate how our parallel methods impact the performance of EO on Titan, the U.S.'s largest open science supercomputer, and BOB, a Beowulf-style cluster of Raspberry Pi's. We also focus on how to improve the EO by evaluating commonality in higher performing neural networks, and present the result of a study that evaluates the EO performed by Titan.

  1. European training network on full-parallax imaging (Conference Presentation)

    Martínez-Corral, Manuel; Saavedra, Genaro

    2017-05-01

    Current displays are far from truly recreating visual reality. This requires a full-parallax display that can reproduce radiance field emanated from the real scenes. The develop-ment of such technology will require a new generation of researchers trained both in the physics, and in the biology of human vision. The European Training Network on Full-Parallax Imaging (ETN-FPI) aims at developing this new generation. Under H2020 funding ETN-FPI brings together 8 beneficiaries and 8 partner organizations from five EU countries with the aim of training 15 talented pre-doctoral students to become future research leaders in this area. In this contribution we will explain the main objectives of the network, and specifically the advances obtained at the University of Valencia.

  2. Mechanical response of biopolymer double networks

    Carroll, Joshua; Das, Moumita

    We investigate a double network model of articular cartilage (AC) and characterize its equilibrium mechanical response. AC has very few cells and the extracellular matrix mainly determines its mechanical response. This matrix can be thought of as a double polymer network made of collagen and aggrecan. The collagen fibers are stiff and resist tension and compression forces, while aggrecans are flexible and control swelling and hydration. We construct a microscopic model made of two interconnected disordered polymer networks, with fiber elasticity chosen to qualitatively mimic the experimental system. We study the collective mechanical response of this double network as a function of the concentration and stiffness of the individual components as well as the strength of the connection between them using rigidity percolation theory. Our results may provide a better understanding of mechanisms underlying the mechanical resilience of AC, and more broadly may also lead to new perspectives on the mechanical response of multicomponent soft materials. This work was partially supported by a Cottrell College Science Award.

  3. GIONET (GMES Initial Operations Network for Earth Observation Research Training)

    Nicolas, V.; Balzter, H.

    2013-12-01

    GMES Initial Operations - Network for Earth Observation Research Training (GIONET) is a Marie Curie funded project that aims to establish the first of a kind European Centre of Excellence for Earth Observation Research Training. Copernicus (previously known as GMES (Global Monitoring for Environment and Security) is a joint undertaking of the European Space Agency and the European Commission. It develops fully operational Earth Observation monitoring services for a community of end users from the public and private sector. The first services that are considered fully operational are the land monitoring and emergency monitoring core services. In GIONET, 14 early stage researchers are being trained at PhD level in understanding the complex physical processes that determine how electromagnetic radiation interacts with the atmosphere and the land surface ultimately form the signal received by a satellite. In order to achieve this, the researchers are based in industry and universities across Europe, as well as receiving the best technical training and scientific education. The training programme through supervised research focuses on 14 research topics. Each topic is carried out by an Early Stage Researcher based in one of the partner organisations and is expected to lead to a PhD degree. The 14 topics are grouped in 5 research themes: Forest monitoring Land cover and change Coastal zone and freshwater monitoring Geohazards and emergency response Climate adaptation and emergency response The methods developed and used in GIONET are as diverse as its research topics. GIONET has already held two summer schools; one at Friedrich Schiller University in Jena (Germany), on 'New operational radar satellite applications: Introduction to SAR, Interferometry and Polarimetry for Land Surface Mapping'. The 2nd summer school took place last September at the University of Leicester (UK )on 'Remote sensing of land cover and forest in GMES'. The next Summer School in September 2013

  4. GMES Initial Operations - Network for Earth Observation Research Training (GIONET)

    Nicolas-Perea, V.; Balzter, H.

    2012-12-01

    GMES Initial Operations - Network for Earth Observation Research Training (GIONET) is a Marie Curie funded project that aims to establish the first of a kind European Centre of Excellence for Earth Observation Research Training. GIONET is a partnership of leading Universities, research institutes and private companies from across Europe aiming to cultivate a community of early stage researchers in the areas of optical and radar remote sensing skilled for the emerging GMES land monitoring services during the GMES Initial Operations period (2011-2013) and beyond. GIONET is expected to satisfy the demand for highly skilled researchers and provide personnel for operational phase of the GMES and monitoring and emergency services. It will achieve this by: -Providing postgraduate training in Earth Observation Science that exposes students to different research disciplines and complementary skills, providing work experiences in the private and academic sectors, and leading to a recognized qualification (Doctorate). -Enabling access to first class training in both fundamental and applied research skills to early-stage researchers at world-class academic centers and market leaders in the private sector. -Building on the experience from previous GMES research and development projects in the land monitoring and emergency information services. The training program through supervised research focuses on 14 research topics (each carried out by an Early Stage Researchers based in one of the partner organization) divided in 5 main areas: Forest monitoring: Global biomass information systems Forest Monitoring of the Congo Basin using Synthetic Aperture radar (SAR) Multi-concept Earth Observation Capabilities for Biomass Mapping and Change Detection: Synergy of Multi-temporal and Multi-frequency Interferometric Radar and Optical Satellite Data Land cover and change: Multi-scale Remote Sensing Synergy for Land Process Studies: from field Spectrometry to Airborne Hyperspectral and

  5. MO-DE-BRA-04: The CREATE Medical Physics Research Training Network: Training of New Generation Innovators

    Seuntjens, J; Collins, L; Devic, S; El Naqa, I; Nadeau, J; Reader, A [McGill University, Montreal, QC (Canada); Beaulieu, L; Despres, P [Centre Hospitalier Univ de Quebec, Quebec, QC (Canada); Pike, B [University of Calgary, Calgary, Alberta (Canada)

    2015-06-15

    Purpose: Over the past century, physicists have played a major role in transforming scientific discovery into everyday clinical applications. However, with the increasingly stringent requirements to regulate medical physics as a health profession, the role of physicists as scientists and innovators has become at serious risk of erosion. These challenges trigger the need for a new, revolutionized training program at the graduate level that respects scientific rigor, attention for medical physics-relevant developments in basic sciences, innovation and entrepreneurship. Methods: A grant proposal was funded by the Collaborative REsearch and Training Experience program (CREATE) of the Natural Sciences and Engineering Research Council (NSERC) of Canada. This enabled the creation of the Medical Physics Research Training Network (MPRTN) around two CAMPEP-accredited medical physics programs. Members of the network consist of medical device companies, government (research and regulatory) and academia. The MPRTN/CREATE program proposes a curriculum with three main themes: (1) radiation physics, (2) imaging & image processing and (3) radiation response, outcomes and modeling. Results: The MPRTN was created mid 2013 (mprtn.com) and features (1) four new basic Ph.D. courses; (2) industry participation in research projects; (3) formal job-readiness training with involvement of guest faculty from academia, government and industry. MPRTN activities since 2013 include 22 conferences; 7 workshops and 4 exchange travels. Three patents were filed or issued, nine awards/best papers were won. Fifteen journal publications were accepted/published, 102 conference abstracts. There are now 13 industry partners. Conclusion: A medical physics research training network has been set up with the goal to harness graduate student’s job-readiness for industry, government and academia in addition to the conventional clinical role. Two years after inception, significant successes have been booked

  6. MO-DE-BRA-04: The CREATE Medical Physics Research Training Network: Training of New Generation Innovators

    Seuntjens, J; Collins, L; Devic, S; El Naqa, I; Nadeau, J; Reader, A; Beaulieu, L; Despres, P; Pike, B

    2015-01-01

    Purpose: Over the past century, physicists have played a major role in transforming scientific discovery into everyday clinical applications. However, with the increasingly stringent requirements to regulate medical physics as a health profession, the role of physicists as scientists and innovators has become at serious risk of erosion. These challenges trigger the need for a new, revolutionized training program at the graduate level that respects scientific rigor, attention for medical physics-relevant developments in basic sciences, innovation and entrepreneurship. Methods: A grant proposal was funded by the Collaborative REsearch and Training Experience program (CREATE) of the Natural Sciences and Engineering Research Council (NSERC) of Canada. This enabled the creation of the Medical Physics Research Training Network (MPRTN) around two CAMPEP-accredited medical physics programs. Members of the network consist of medical device companies, government (research and regulatory) and academia. The MPRTN/CREATE program proposes a curriculum with three main themes: (1) radiation physics, (2) imaging & image processing and (3) radiation response, outcomes and modeling. Results: The MPRTN was created mid 2013 (mprtn.com) and features (1) four new basic Ph.D. courses; (2) industry participation in research projects; (3) formal job-readiness training with involvement of guest faculty from academia, government and industry. MPRTN activities since 2013 include 22 conferences; 7 workshops and 4 exchange travels. Three patents were filed or issued, nine awards/best papers were won. Fifteen journal publications were accepted/published, 102 conference abstracts. There are now 13 industry partners. Conclusion: A medical physics research training network has been set up with the goal to harness graduate student’s job-readiness for industry, government and academia in addition to the conventional clinical role. Two years after inception, significant successes have been booked

  7. Simulation of Stimuli-Responsive Polymer Networks

    Thomas Gruhn

    2013-11-01

    Full Text Available The structure and material properties of polymer networks can depend sensitively on changes in the environment. There is a great deal of progress in the development of stimuli-responsive hydrogels for applications like sensors, self-repairing materials or actuators. Biocompatible, smart hydrogels can be used for applications, such as controlled drug delivery and release, or for artificial muscles. Numerical studies have been performed on different length scales and levels of details. Macroscopic theories that describe the network systems with the help of continuous fields are suited to study effects like the stimuli-induced deformation of hydrogels on large scales. In this article, we discuss various macroscopic approaches and describe, in more detail, our phase field model, which allows the calculation of the hydrogel dynamics with the help of a free energy that considers physical and chemical impacts. On a mesoscopic level, polymer systems can be modeled with the help of the self-consistent field theory, which includes the interactions, connectivity, and the entropy of the polymer chains, and does not depend on constitutive equations. We present our recent extension of the method that allows the study of the formation of nano domains in reversibly crosslinked block copolymer networks. Molecular simulations of polymer networks allow the investigation of the behavior of specific systems on a microscopic scale. As an example for microscopic modeling of stimuli sensitive polymer networks, we present our Monte Carlo simulations of a filament network system with crosslinkers.

  8. Training Feedforward Neural Networks Using Symbiotic Organisms Search Algorithm

    Haizhou Wu

    2016-01-01

    Full Text Available Symbiotic organisms search (SOS is a new robust and powerful metaheuristic algorithm, which stimulates the symbiotic interaction strategies adopted by organisms to survive and propagate in the ecosystem. In the supervised learning area, it is a challenging task to present a satisfactory and efficient training algorithm for feedforward neural networks (FNNs. In this paper, SOS is employed as a new method for training FNNs. To investigate the performance of the aforementioned method, eight different datasets selected from the UCI machine learning repository are employed for experiment and the results are compared among seven metaheuristic algorithms. The results show that SOS performs better than other algorithms for training FNNs in terms of converging speed. It is also proven that an FNN trained by the method of SOS has better accuracy than most algorithms compared.

  9. Electronic collaboration in dermatology resident training through social networking.

    Meeks, Natalie M; McGuire, April L; Carroll, Bryan T

    2017-04-01

    The use of online educational resources and professional social networking sites is increasing. The field of dermatology is currently under-utilizing online social networking as a means of professional collaboration and sharing of training materials. In this study, we sought to assess the current structure of and satisfaction with dermatology resident education and gauge interest for a professional social networking site for educational collaboration. Two surveys-one for residents and one for faculty-were electronically distributed via the American Society for Dermatologic Surgery and Association of Professors of Dermatology (APD) listserves. The surveys confirmed that there is interest among dermatology residents and faculty in a dermatology professional networking site with the goal to enhance educational collaboration.

  10. Novel maximum-margin training algorithms for supervised neural networks.

    Ludwig, Oswaldo; Nunes, Urbano

    2010-06-01

    This paper proposes three novel training methods, two of them based on the backpropagation approach and a third one based on information theory for multilayer perceptron (MLP) binary classifiers. Both backpropagation methods are based on the maximal-margin (MM) principle. The first one, based on the gradient descent with adaptive learning rate algorithm (GDX) and named maximum-margin GDX (MMGDX), directly increases the margin of the MLP output-layer hyperplane. The proposed method jointly optimizes both MLP layers in a single process, backpropagating the gradient of an MM-based objective function, through the output and hidden layers, in order to create a hidden-layer space that enables a higher margin for the output-layer hyperplane, avoiding the testing of many arbitrary kernels, as occurs in case of support vector machine (SVM) training. The proposed MM-based objective function aims to stretch out the margin to its limit. An objective function based on Lp-norm is also proposed in order to take into account the idea of support vectors, however, overcoming the complexity involved in solving a constrained optimization problem, usually in SVM training. In fact, all the training methods proposed in this paper have time and space complexities O(N) while usual SVM training methods have time complexity O(N (3)) and space complexity O(N (2)) , where N is the training-data-set size. The second approach, named minimization of interclass interference (MICI), has an objective function inspired on the Fisher discriminant analysis. Such algorithm aims to create an MLP hidden output where the patterns have a desirable statistical distribution. In both training methods, the maximum area under ROC curve (AUC) is applied as stop criterion. The third approach offers a robust training framework able to take the best of each proposed training method. The main idea is to compose a neural model by using neurons extracted from three other neural networks, each one previously trained by

  11. Deep Convolutional Neural Networks: Structure, Feature Extraction and Training

    Namatēvs Ivars

    2017-12-01

    Full Text Available Deep convolutional neural networks (CNNs are aimed at processing data that have a known network like topology. They are widely used to recognise objects in images and diagnose patterns in time series data as well as in sensor data classification. The aim of the paper is to present theoretical and practical aspects of deep CNNs in terms of convolution operation, typical layers and basic methods to be used for training and learning. Some practical applications are included for signal and image classification. Finally, the present paper describes the proposed block structure of CNN for classifying crucial features from 3D sensor data.

  12. Jointly Optimize Data Augmentation and Network Training: Adversarial Data Augmentation in Human Pose Estimation

    Peng, Xi; Tang, Zhiqiang; Yang, Fei; Feris, Rogerio; Metaxas, Dimitris

    2018-01-01

    Random data augmentation is a critical technique to avoid overfitting in training deep neural network models. However, data augmentation and network training are usually treated as two isolated processes, limiting the effectiveness of network training. Why not jointly optimize the two? We propose adversarial data augmentation to address this limitation. The main idea is to design an augmentation network (generator) that competes against a target network (discriminator) by generating `hard' au...

  13. Shakeout: A New Approach to Regularized Deep Neural Network Training.

    Kang, Guoliang; Li, Jun; Tao, Dacheng

    2018-05-01

    Recent years have witnessed the success of deep neural networks in dealing with a plenty of practical problems. Dropout has played an essential role in many successful deep neural networks, by inducing regularization in the model training. In this paper, we present a new regularized training approach: Shakeout. Instead of randomly discarding units as Dropout does at the training stage, Shakeout randomly chooses to enhance or reverse each unit's contribution to the next layer. This minor modification of Dropout has the statistical trait: the regularizer induced by Shakeout adaptively combines , and regularization terms. Our classification experiments with representative deep architectures on image datasets MNIST, CIFAR-10 and ImageNet show that Shakeout deals with over-fitting effectively and outperforms Dropout. We empirically demonstrate that Shakeout leads to sparser weights under both unsupervised and supervised settings. Shakeout also leads to the grouping effect of the input units in a layer. Considering the weights in reflecting the importance of connections, Shakeout is superior to Dropout, which is valuable for the deep model compression. Moreover, we demonstrate that Shakeout can effectively reduce the instability of the training process of the deep architecture.

  14. Artificial Neural Network with Hardware Training and Hardware Refresh

    Duong, Tuan A. (Inventor)

    2003-01-01

    A neural network circuit is provided having a plurality of circuits capable of charge storage. Also provided is a plurality of circuits each coupled to at least one of the plurality of charge storage circuits and constructed to generate an output in accordance with a neuron transfer function. Each of a plurality of circuits is coupled to one of the plurality of neuron transfer function circuits and constructed to generate a derivative of the output. A weight update circuit updates the charge storage circuits based upon output from the plurality of transfer function circuits and output from the plurality of derivative circuits. In preferred embodiments, separate training and validation networks share the same set of charge storage circuits and may operate concurrently. The validation network has a separate transfer function circuits each being coupled to the charge storage circuits so as to replicate the training network s coupling of the plurality of charge storage to the plurality of transfer function circuits. The plurality of transfer function circuits may be constructed each having a transconductance amplifier providing differential currents combined to provide an output in accordance with a transfer function. The derivative circuits may have a circuit constructed to generate a biased differential currents combined so as to provide the derivative of the transfer function.

  15. Training Excitatory-Inhibitory Recurrent Neural Networks for Cognitive Tasks: A Simple and Flexible Framework.

    H Francis Song

    2016-02-01

    Full Text Available The ability to simultaneously record from large numbers of neurons in behaving animals has ushered in a new era for the study of the neural circuit mechanisms underlying cognitive functions. One promising approach to uncovering the dynamical and computational principles governing population responses is to analyze model recurrent neural networks (RNNs that have been optimized to perform the same tasks as behaving animals. Because the optimization of network parameters specifies the desired output but not the manner in which to achieve this output, "trained" networks serve as a source of mechanistic hypotheses and a testing ground for data analyses that link neural computation to behavior. Complete access to the activity and connectivity of the circuit, and the ability to manipulate them arbitrarily, make trained networks a convenient proxy for biological circuits and a valuable platform for theoretical investigation. However, existing RNNs lack basic biological features such as the distinction between excitatory and inhibitory units (Dale's principle, which are essential if RNNs are to provide insights into the operation of biological circuits. Moreover, trained networks can achieve the same behavioral performance but differ substantially in their structure and dynamics, highlighting the need for a simple and flexible framework for the exploratory training of RNNs. Here, we describe a framework for gradient descent-based training of excitatory-inhibitory RNNs that can incorporate a variety of biological knowledge. We provide an implementation based on the machine learning library Theano, whose automatic differentiation capabilities facilitate modifications and extensions. We validate this framework by applying it to well-known experimental paradigms such as perceptual decision-making, context-dependent integration, multisensory integration, parametric working memory, and motor sequence generation. Our results demonstrate the wide range of neural

  16. Enhancing the benefits of written emotional disclosure through response training.

    Konig, Andrea; Eonta, Alison; Dyal, Stephanie R; Vrana, Scott R

    2014-05-01

    Writing about a personal stressful event has been found to have psychological and physical health benefits, especially when physiological response increases during writing. Response training was developed to amplify appropriate physiological reactivity in imagery exposure. The present study examined whether response training enhances the benefits of written emotional disclosure. Participants were assigned to either a written emotional disclosure condition (n=113) or a neutral writing condition (n=133). Participants in each condition wrote for 20 minutes on 3 occasions and received response training (n=79), stimulus training (n=84) or no training (n=83). Heart rate and skin conductance were recorded throughout a 10-minute baseline, 20-minute writing, and a 10-minute recovery period. Self-reported emotion was assessed in each session. One month after completing the sessions, participants completed follow-up assessments of psychological and physical health outcomes. Emotional disclosure elicited greater physiological reactivity and self-reported emotion than neutral writing. Response training amplified physiological reactivity to emotional disclosure. Greater heart rate during emotional disclosure was associated with the greatest reductions in event-related distress, depression, and physical illness symptoms at follow-up, especially among response trained participants. Results support an exposure explanation of emotional disclosure effects and are the first to demonstrate that response training facilitates emotional processing and may be a beneficial adjunct to written emotional disclosure. Copyright © 2014. Published by Elsevier Ltd.

  17. Enhancing the Benefits of Written Emotional Disclosure through Response Training

    Konig, Andrea; Eonta, Alison; Dyal, Stephanie R.; Vrana, Scott R.

    2014-01-01

    Writing about a personal stressful event has been found to have psychological and physical health benefits, especially when physiological response increases during writing. Response training was developed to amplify appropriate physiological reactivity in imagery exposure. The present study examined whether response training enhances the benefits of written emotional disclosure. Participants were assigned to either a written emotional disclosure condition (n = 113) or a neutral writing condition (n = 133). Participants in each condition wrote for 20 minutes on three occasions and received response training (n = 79), stimulus training (n = 84) or no training (n = 83). Heart rate and skin conductance were recorded throughout a 10-minute baseline, 20-minute writing, and a 10-minute recovery period. Self-reported emotion was assessed in each session. One month after completing the sessions, participants completed follow-up assessments of psychological and physical health outcomes. Emotional disclosure elicited greater physiological reactivity and self-reported emotion than neutral writing. Response training amplified physiological reactivity to emotional disclosure. Greater heart rate during emotional disclosure was associated with the greatest reductions in event-related distress, depression, and physical illness symptoms at follow-up, especially among response trained participants. Results support an exposure explanation of emotional disclosure effects and are the first to demonstrate that response training facilitates emotional processing and may be a beneficial adjunct to written emotional disclosure. PMID:24680230

  18. Phase-response curves and synchronized neural networks.

    Smeal, Roy M; Ermentrout, G Bard; White, John A

    2010-08-12

    We review the principal assumptions underlying the application of phase-response curves (PRCs) to synchronization in neuronal networks. The PRC measures how much a given synaptic input perturbs spike timing in a neural oscillator. Among other applications, PRCs make explicit predictions about whether a given network of interconnected neurons will synchronize, as is often observed in cortical structures. Regarding the assumptions of the PRC theory, we conclude: (i) The assumption of noise-tolerant cellular oscillations at or near the network frequency holds in some but not all cases. (ii) Reduced models for PRC-based analysis can be formally related to more realistic models. (iii) Spike-rate adaptation limits PRC-based analysis but does not invalidate it. (iv) The dependence of PRCs on synaptic location emphasizes the importance of improving methods of synaptic stimulation. (v) New methods can distinguish between oscillations that derive from mutual connections and those arising from common drive. (vi) It is helpful to assume linear summation of effects of synaptic inputs; experiments with trains of inputs call this assumption into question. (vii) Relatively subtle changes in network structure can invalidate PRC-based predictions. (viii) Heterogeneity in the preferred frequencies of component neurons does not invalidate PRC analysis, but can annihilate synchronous activity.

  19. Effect of training algorithms on neural networks aided pavement ...

    Especially, the use of Finite Element (FE) based pavement modeling results for training the NN aided inverse analysis is considered to be accurate in realistically characterizing the non-linear stress-sensitive response of underlying pavement layers in real-time. Efficient NN learning algorithms have been developed and ...

  20. Time response of temperature sensors using neural networks

    Santos, Roberto Carlos dos

    2010-01-01

    In a PWR nuclear power plant, the primary coolant temperature and feedwater temperature are measured using RTDs (Resistance Temperature Detectors). These RTDs typically feed the plant's control and safety systems and must, therefore, be very accurate and have good dynamic performance. The response time of RTDs is characterized by a single parameter called the Plunge Time Constant defined as the time it takes the sensor output to achieve 63.2 percent of its final value after a step change in temperature. Nuclear reactor service conditions are difficult to reproduce in the laboratory, and an in-situ test method called LCSR (Loop Current Step Response) test was developed to measure remotely the response time of RTDs. >From this test, the time constant of the sensor is identified by means of the LCSR transformation that involves the dynamic response modal time constants determination using a nodal heat-transfer model. This calculation is not simple and requires specialized personnel. For this reason an Artificial Neural Network has been developed to predict the time constant of RTD from LCSR test transient. It eliminates the transformations involved in the LCSR application. A series of LCSR tests on RTDs generates the response transients of the sensors, the input data of the networks. Plunge tests are used to determine the time constants of the RTDs, the desired output of the ANN, trained using these sets of input/output data. This methodology was firstly applied to theoretical data simulating 10 RTDs with different time constant values, resulting in an average error of about 0.74 %. Experimental data from three different RTDs was used to predict time constant resulting in a maximum error of 3,34 %. The time constants values predicted from ANN were compared with those obtained from traditional way resulting in an average error of about 18 % and that shows the network is able to predict accurately the sensor time constant. (author)

  1. Training feed-forward neural networks with gain constraints

    Hartman

    2000-04-01

    Inaccurate input-output gains (partial derivatives of outputs with respect to inputs) are common in neural network models when input variables are correlated or when data are incomplete or inaccurate. Accurate gains are essential for optimization, control, and other purposes. We develop and explore a method for training feedforward neural networks subject to inequality or equality-bound constraints on the gains of the learned mapping. Gain constraints are implemented as penalty terms added to the objective function, and training is done using gradient descent. Adaptive and robust procedures are devised for balancing the relative strengths of the various terms in the objective function, which is essential when the constraints are inconsistent with the data. The approach has the virtue that the model domain of validity can be extended via extrapolation training, which can dramatically improve generalization. The algorithm is demonstrated here on artificial and real-world problems with very good results and has been advantageously applied to dozens of models currently in commercial use.

  2. Bistable responses in bacterial genetic networks: Designs and dynamical consequences

    Tiwari, Abhinav; Ray, J. Christian J.; Narula, Jatin; Igoshin, Oleg A.

    2011-01-01

    A key property of living cells is their ability to react to stimuli with specific biochemical responses. These responses can be understood through the dynamics of underlying biochemical and genetic networks. Evolutionary design principles have been well studied in networks that display graded responses, with a continuous relationship between input signal and system output. Alternatively, biochemical networks can exhibit bistable responses so that over a range of signals the network possesses two stable steady states. In this review, we discuss several conceptual examples illustrating network designs that can result in a bistable response of the biochemical network. Next, we examine manifestations of these designs in bacterial master-regulatory genetic circuits. In particular, we discuss mechanisms and dynamic consequences of bistability in three circuits: two-component systems, sigma-factor networks, and a multistep phosphorelay. Analyzing these examples allows us to expand our knowledge of evolutionary design principles for networks with bistable responses. PMID:21385588

  3. Asia-Pacific Research and Training Network on Trade (ARTNET ...

    During the first phase of support (102568), the Network produced a number of high quality trade policy studies, disseminated the results to policymakers and increased the capacity of research institutions - notably those in the least developed countries - to conduct trade policy ... Agent(e) responsable du CRDI. Due, Evan ...

  4. Enhancing the Benefits of Written Emotional Disclosure through Response Training

    Konig, Andrea; Eonta, Alison; Dyal, Stephanie R.; Vrana, Scott R.

    2013-01-01

    Writing about a personal stressful event has been found to have psychological and physical health benefits, especially when physiological response increases during writing. Response training was developed to amplify appropriate physiological reactivity in imagery exposure. The present study examined whether response training enhances the benefits of written emotional disclosure. Participants were assigned to either a written emotional disclosure condition (n = 113) or a neutral writing condit...

  5. Superimposed Training-Based Channel Estimation for MIMO Relay Networks

    Xiaoyan Xu

    2012-01-01

    Full Text Available We introduce the superimposed training strategy into the multiple-input multiple-output (MIMO amplify-and-forward (AF one-way relay network (OWRN to perform the individual channel estimation at the destination. Through the superposition of a group of additional training vectors at the relay subject to power allocation, the separated estimates of the source-relay and relay-destination channels can be obtained directly at the destination, and the accordance with the two-hop AF strategy can be guaranteed at the same time. The closed-form Bayesian Cramér-Rao lower bound (CRLB is derived for the estimation of two sets of flat-fading MIMO channel under random channel parameters and further exploited to design the optimal training vectors. A specific suboptimal channel estimation algorithm is applied in the MIMO AF OWRN using the optimal training sequences, and the normalized mean square error performance for the estimation is provided to verify the Bayesian CRLB results.

  6. Radiological response training for law enforcement personnel

    Maixner, R.D.

    1983-01-01

    A specialized training course for Nevada's law enforcement personnel has been conducted by Reynolds Electrical and Engineering Co., Inc. for the US Department of Energy since February 1981. This course is designed for those persons who are first to arrive at a transportation accident scene. The course provides a basic understanding of radiation protection, the prevention of contamination spread from the accident site, use of radiation detection equipment, and decontamination procedures. The Department of Energy's Nevada Operations Office provides the training at no cost to Nevada agencies. Each agency selects its attendees. Details of the course are given

  7. Training and validation of the ATLAS pixel clustering neural networks

    The ATLAS collaboration

    2018-01-01

    The high centre-of-mass energy of the LHC gives rise to dense environments, such as the core of high-pT jets, in which the charge clusters left by ionising particles in the silicon sensors of the pixel detector can merge, compromising the tracking and vertexing efficiency. To recover optimal performance, a neural network-based approach is used to separate clusters originating from single and multiple particles and to estimate all hit positions within clusters. This note presents the training strategy employed and a set of benchmark performance measurements on a Monte Carlo sample of high-pT dijet events.

  8. Emergency response training with the BNL plant analyzer

    Cheng, H.S.; Guppy, J.G.; Mallen, A.N.; Wulff, W.

    1987-01-01

    Presented is the experience in the use of the BNL Plant Analyzer for NRC emergency response training to simulated accidents in a BWR. The unique features of the BNL Plant Analyzer that are important for the emergency response training are summarized. A closed-loop simulation of all the key systems of a power plant in question was found essential to the realism of the emergency drills conducted at NRC. The faster than real-time simulation speeds afforded by the BNL Plant Analyzer have demonstrated its usefulness for the timely conduct of the emergency response training

  9. Training Excitatory-Inhibitory Recurrent Neural Networks for Cognitive Tasks: A Simple and Flexible Framework

    Wang, Xiao-Jing

    2016-01-01

    The ability to simultaneously record from large numbers of neurons in behaving animals has ushered in a new era for the study of the neural circuit mechanisms underlying cognitive functions. One promising approach to uncovering the dynamical and computational principles governing population responses is to analyze model recurrent neural networks (RNNs) that have been optimized to perform the same tasks as behaving animals. Because the optimization of network parameters specifies the desired output but not the manner in which to achieve this output, “trained” networks serve as a source of mechanistic hypotheses and a testing ground for data analyses that link neural computation to behavior. Complete access to the activity and connectivity of the circuit, and the ability to manipulate them arbitrarily, make trained networks a convenient proxy for biological circuits and a valuable platform for theoretical investigation. However, existing RNNs lack basic biological features such as the distinction between excitatory and inhibitory units (Dale’s principle), which are essential if RNNs are to provide insights into the operation of biological circuits. Moreover, trained networks can achieve the same behavioral performance but differ substantially in their structure and dynamics, highlighting the need for a simple and flexible framework for the exploratory training of RNNs. Here, we describe a framework for gradient descent-based training of excitatory-inhibitory RNNs that can incorporate a variety of biological knowledge. We provide an implementation based on the machine learning library Theano, whose automatic differentiation capabilities facilitate modifications and extensions. We validate this framework by applying it to well-known experimental paradigms such as perceptual decision-making, context-dependent integration, multisensory integration, parametric working memory, and motor sequence generation. Our results demonstrate the wide range of neural activity

  10. [Training of institutional research networks as a strategy of improvement].

    Galván-Plata, María Eugenia; Almeida-Gutiérrez, Eduardo; Salamanca-Gómez, Fabio Abdel

    2017-01-01

    The Instituto Mexicano del Seguro Social (IMSS) through the Coordinación de Investigación en Salud (Health Research Council) has promoted a strong link between the generation of scientific knowledge and the clinical care through the program Redes Institucionales de Investigación (Institutional Research Network Program), whose main aim is to promote and generate collaborative research between clinical, basic, epidemiologic, educational, economic and health services researchers, seeking direct benefits for patients, as well as to generate a positive impact on institutional processes. All of these research lines have focused on high-priority health issues in Mexico. The IMSS internal structure, as well as the sufficient health services coverage, allows the integration of researchers at the three levels of health care into these networks. A few years after their creation, these networks have already generated significant results, and these are currently applied in the institutional regulations in diseases that represent a high burden to health care. Two examples are the National Health Care Program for Patients with Acute Myocardial Infarction "Código Infarto", and the Early Detection Program on Chronic Kidney Disease; another result is the generation of multiple scientific publications, and the promotion of training of human resources in research from the same members of our Research Networks. There is no doubt that the Coordinación de Investigación en Salud advances steadily implementing the translational research, which will keep being fruitful to the benefit of our patients, and of our own institution.

  11. Network Training for a Boy with Learning Disabilities and Behaviours That Challenge

    Cooper, Kate; McElwee, Jennifer

    2016-01-01

    Background: Network Training is an intervention that draws upon systemic ideas and behavioural principles to promote positive change in networks of support for people defined as having a learning disability. To date, there are no published case studies looking at the outcomes of Network Training. Materials and Methods: This study aimed to…

  12. Self-consistent determination of the spike-train power spectrum in a neural network with sparse connectivity

    Benjamin eDummer

    2014-09-01

    Full Text Available A major source of random variability in cortical networks is the quasi-random arrival of presynaptic action potentials from many other cells. In network studies as well as in the study of the response properties of single cells embedded in a network, synaptic background input is often approximated by Poissonian spike trains. However, the output statistics of the cells is in most cases far from being Poisson. This is inconsistent with the assumption of similar spike-train statistics for pre- and postsynaptic cells in a recurrent network. Here we tackle this problem for the popular class of integrate-and-fire neurons and study a self-consistent statistics of input and output spectra of neural spike trains. Instead of actually using a large network, we use an iterative scheme, in which we simulate a single neuron over several generations. In each of these generations, the neuron is stimulated with surrogate stochastic input that has a similar statistics as the output of the previous generation. For the surrogate input, we employ two distinct approximations: (i a superposition of renewal spike trains with the same interspike interval density as observed in the previous generation and (ii a Gaussian current with a power spectrum proportional to that observed in the previous generation. For input parameters that correspond to balanced input in the network, both the renewal and the Gaussian iteration procedure converge quickly and yield comparable results for the self-consistent spike-train power spectrum. We compare our results to large-scale simulations of a random sparsely connected network of leaky integrate-and-fire neurons (Brunel, J. Comp. Neurosci. 2000 and show that in the asynchronous regime close to a state of balanced synaptic input from the network, our iterative schemes provide excellent approximations to the autocorrelation of spike trains in the recurrent network.

  13. Illusory Motion Reproduced by Deep Neural Networks Trained for Prediction.

    Watanabe, Eiji; Kitaoka, Akiyoshi; Sakamoto, Kiwako; Yasugi, Masaki; Tanaka, Kenta

    2018-01-01

    The cerebral cortex predicts visual motion to adapt human behavior to surrounding objects moving in real time. Although the underlying mechanisms are still unknown, predictive coding is one of the leading theories. Predictive coding assumes that the brain's internal models (which are acquired through learning) predict the visual world at all times and that errors between the prediction and the actual sensory input further refine the internal models. In the past year, deep neural networks based on predictive coding were reported for a video prediction machine called PredNet. If the theory substantially reproduces the visual information processing of the cerebral cortex, then PredNet can be expected to represent the human visual perception of motion. In this study, PredNet was trained with natural scene videos of the self-motion of the viewer, and the motion prediction ability of the obtained computer model was verified using unlearned videos. We found that the computer model accurately predicted the magnitude and direction of motion of a rotating propeller in unlearned videos. Surprisingly, it also represented the rotational motion for illusion images that were not moving physically, much like human visual perception. While the trained network accurately reproduced the direction of illusory rotation, it did not detect motion components in negative control pictures wherein people do not perceive illusory motion. This research supports the exciting idea that the mechanism assumed by the predictive coding theory is one of basis of motion illusion generation. Using sensory illusions as indicators of human perception, deep neural networks are expected to contribute significantly to the development of brain research.

  14. Illusory Motion Reproduced by Deep Neural Networks Trained for Prediction

    Eiji Watanabe

    2018-03-01

    Full Text Available The cerebral cortex predicts visual motion to adapt human behavior to surrounding objects moving in real time. Although the underlying mechanisms are still unknown, predictive coding is one of the leading theories. Predictive coding assumes that the brain's internal models (which are acquired through learning predict the visual world at all times and that errors between the prediction and the actual sensory input further refine the internal models. In the past year, deep neural networks based on predictive coding were reported for a video prediction machine called PredNet. If the theory substantially reproduces the visual information processing of the cerebral cortex, then PredNet can be expected to represent the human visual perception of motion. In this study, PredNet was trained with natural scene videos of the self-motion of the viewer, and the motion prediction ability of the obtained computer model was verified using unlearned videos. We found that the computer model accurately predicted the magnitude and direction of motion of a rotating propeller in unlearned videos. Surprisingly, it also represented the rotational motion for illusion images that were not moving physically, much like human visual perception. While the trained network accurately reproduced the direction of illusory rotation, it did not detect motion components in negative control pictures wherein people do not perceive illusory motion. This research supports the exciting idea that the mechanism assumed by the predictive coding theory is one of basis of motion illusion generation. Using sensory illusions as indicators of human perception, deep neural networks are expected to contribute significantly to the development of brain research.

  15. Tuning of spinal networks to frequency components of spike trains in individual afferents.

    Koerber, H R; Seymour, A W; Mendell, L M

    1991-10-01

    Cord dorsum potentials (CDPs) evoked by primary afferent fiber stimulation reflect the response of postsynaptic dorsal horn neurons. The properties of these CDPs have been shown to vary in accordance with the type of primary afferent fiber stimulated. The purpose of the present study was to determine the relationships between frequency modulation of the afferent input trains, the amplitude modulation of the evoked CDPs, and the type of primary afferent stimulated. The somata of individual primary afferent fibers were impaled in the L7 dorsal root ganglion of alpha-chloralose-anesthetized cats. Action potentials (APs) were evoked in single identified afferents via the intracellular microelectrode while simultaneously recording the response of dorsal horn neurons as CDPs, or activity of individual target interneurons recorded extracellularly or intracellularly. APs were evoked in afferents using temporal patterns identical to the responses of selected afferents to natural stimulation of their receptive fields. Two such physiologically realistic trains, one recorded from a hair follicle and the other from a slowly adapting type 1 receptor, were chosen as standard test trains. Modulation of CDP amplitude in response to this frequency-modulated afferent activity varied according to the type of peripheral mechanoreceptor innervated. Dorsal horn networks driven by A beta afferents innervating hair follicles, rapidly adapting pad (Krause end bulb), and field receptors seemed "tuned" to amplify the onset of activity in single afferents. Networks driven by afferents innervating down hair follicles and pacinian corpuscles required more high-frequency activity to elicit their peak response. Dorsal horn networks driven by afferents innervating slowly adapting receptors including high-threshold mechanoreceptors exhibited some sensitivity to the instantaneous frequency, but in general they reproduced the activity in the afferent fiber much more faithfully. Responses of

  16. Cognitive responses to hypobaric hypoxia: implications for aviation training

    Neuhaus C

    2014-11-01

    Full Text Available Christopher Neuhaus,1,2 Jochen Hinkelbein2,31Department of Anesthesiology, Heidelberg University Hospital, Ruprecht Karls University of Heidelberg, Heidelberg, 2Emergency Medicine and Air Rescue Working Group, German Society of Aviation and Space Medicine (DGLRM, Munich, 3Department of Anesthesiology and Intensive Care Medicine, University Hospital of Cologne, Cologne, GermanyAbstract: The aim of this narrative review is to provide an overview on cognitive responses to hypobaric hypoxia and to show relevant implications for aviation training. A principal element of hypoxia-awareness training is the intentional evocation of hypoxia symptoms during specific training sessions within a safe and controlled environment. Repetitive training should enable pilots to learn and recognize their personal hypoxia symptoms. A time span of 3–6 years is generally considered suitable to refresh knowledge of the more subtle and early symptoms especially. Currently, there are two different technical approaches available to induce hypoxia during training: hypobaric chamber training and reduced-oxygen breathing devices. Hypoxia training for aircrew is extremely important and effective, and the hypoxia symptoms should be emphasized clearly to aircrews. The use of tight-fitting masks, leak checks, and equipment checks should be taught to all aircrew and reinforced regularly. It is noteworthy that there are major differences in the required quality and quantity of hypoxia training for both military and civilian pilots.Keywords: cognitive response, aviation training, pilot, hypoxia, oxygen, loss of consciousness

  17. Guest editorial - Networked collaboration, sharing and response

    Olav Skundberg

    2008-11-01

    Full Text Available  This issue of Seminar.net contains three articles that were written in connection with a Norwegian e-learning conference titled “Networked collaboration, sharing and response”. The conference was held in Mars 2008 in Trondheim, and the presentations from the conference is available (in norwegian language at http://www.nvu.no. Networked collaboration was chosen as a theme because collaboration is important to achieve learning, according to the social-constructivistic pedagogy that has a strong standing in Norway, but how should this occur on the net? Sharing of content, as in digital learning resources, is a phenomenon with increasing popularity as described in the OECD-report “Giving Knowledge for Free”. But to achieve reuse of content, not only publishing it, it is important with a networked community where the plethora of information can be sorted with relevance to specific topics. Response is about guiding, coaching and tutoring. In what ways may resources and tools be used to move in the direction of solving Bloom’s two sigma problem/challenge? The first article, by Morten Flate Paulsen, shows how cooperative learning can be implemented successfully so that students have optimal individual freedom within online learning communities. The second article, by Carl F. Dons, shows how student teachers can be prepared to deal with pupils who have a wide range of experiences of the digital world. The third and last article, by Kristin Dale, is sharing experiences with multiple choice-tests to give midterm responses to students. In addition, this issue has a commentary article by Rune Krumsvik discussing the need to develop new practices for teachers and students on the background of the digital developments. The conference and articles covers three big themes. It may be difficult to find more important issues, apart from finding money and time to support its development. Olav Skundberg, guest editorAssociate professor

  18. Training and Transfer Effects of Response Inhibition Training in Children and Adults

    Zhao, Xin; Chen, Ling; Maes, Joseph H. R.

    2018-01-01

    Response inhibition is crucial for mental and physical health but studies assessing the trainability of this type of inhibition are rare. Thirty-nine children aged 10-12 years and 46 adults aged 18-24 years were assigned to an adaptive go/no-go inhibition training condition or an active control condition. Transfer of training effects to…

  19. New Learning Methods for Marine Oil Spill Response Training

    Justiina Halonen

    2017-06-01

    Full Text Available In Finland the Regional Fire and Rescue Services (RFRS are responsible for near shore oil spill response and shoreline cleanup operations. In addition, they assist in other types of maritime incidents, such as search and rescue operations and fire-fighting on board. These statutory assignments require the RFRS to have capability to act both on land and at sea. As maritime incidents occur infrequently, little routine has been established. In order to improve their performance in maritime operations, the RFRS are participating in a new oil spill training programme to be launched by South-Eastern Finland University of Applied Sciences. This training programme aims to utilize new educational methods; e-learning and simulator based training. In addition to fully exploiting the existing navigational bridge simulator, radio communication simulator and crisis management simulator, an entirely new simulator is developed. This simulator is designed to model the oil recovery process; recovery method, rate and volume in various conditions with different oil types. New simulator enables creation of a comprehensive training programme covering training tasks from a distress call to the completion of an oil spill response operation. Structure of the training programme, as well as the training objectives, are based on the findings from competence and education surveys conducted in spring 2016. In these results, a need for vessel maneuvering and navigation exercises together with actual response measures training were emphasized. Also additional training for maritime radio communication, GMDSS-emergency protocols and collaboration with maritime authorities were seemed important. This paper describes new approach to the maritime operations training designed for rescue authorities, a way of learning by doing, without mobilising the vessels at sea.

  20. Gradual DropIn of Layers to Train Very Deep Neural Networks

    Smith, Leslie N.; Hand, Emily M.; Doster, Timothy

    2015-01-01

    We introduce the concept of dynamically growing a neural network during training. In particular, an untrainable deep network starts as a trainable shallow network and newly added layers are slowly, organically added during training, thereby increasing the network's depth. This is accomplished by a new layer, which we call DropIn. The DropIn layer starts by passing the output from a previous layer (effectively skipping over the newly added layers), then increasingly including units from the ne...

  1. Anomalous Anticipatory Responses in Networked Random Data

    Nelson, Roger D.; Bancel, Peter A.

    2006-01-01

    We examine an 8-year archive of synchronized, parallel time series of random data from a world spanning network of physical random event generators (REGs). The archive is a publicly accessible matrix of normally distributed 200-bit sums recorded at 1 Hz which extends from August 1998 to the present. The primary question is whether these data show non-random structure associated with major events such as natural or man-made disasters, terrible accidents, or grand celebrations. Secondarily, we examine the time course of apparently correlated responses. Statistical analyses of the data reveal consistent evidence that events which strongly affect people engender small but significant effects. These include suggestions of anticipatory responses in some cases, leading to a series of specialized analyses to assess possible non-random structure preceding precisely timed events. A focused examination of data collected around the time of earthquakes with Richter magnitude 6 and greater reveals non-random structure with a number of intriguing, potentially important features. Anomalous effects in the REG data are seen only when the corresponding earthquakes occur in populated areas. No structure is found if they occur in the oceans. We infer that an important contributor to the effect is the relevance of the earthquake to humans. Epoch averaging reveals evidence for changes in the data some hours prior to the main temblor, suggestive of reverse causation

  2. REPRODUCTIVE HORMONES AND CORTISOL RESPONSES TO PLYOMETRIC TRAINING IN MALES

    Serife Vatansever Ozen

    2012-07-01

    Full Text Available Plyometric training activities are commonly used by a wide range of athletes to increase jump performance and improve explosive power and muscular activation patterns. The purpose of the study was to evaluate the effects of plyometric training on male reproductive hormones. Nineteen recreationally active males volunteered to participate in this study and were randomly assigned to plyometrically trained (n=10, 21.2 ±2.3 years and control groups (n=9, 21.4± 2.1. The plyometric training group performed in a six-week plyometric training programme and the control group did not perform any plyometric training techniques. Resting serum levels of testosterone, prolactin, follicle stimulating hormone (FSH, luteinising hormone (LH, and cortisol were measured in each subject at t0 (before the training, t1 (end of third week and t2 (end of training. Two-way ANOVA revealed significant (P<0.05 interaction effects for testosterone, prolactin, FSH and cortisol. Six-week plyometric training decreased serum levels of testosterone, cortisol and FSH and increased serum levels of prolactin. These results suggest the presence of alterations in anabolic and catabolic hormonal responses to resistance exercise in men.

  3. Analyzing Track Responses to Train Braking

    Bose, Tulika; Levenberg, Eyal; Zania, Varvara

    2018-01-01

    The objective of this study was to suggest a response analysis framework for railway tracks that are subjected to braking. An analytical formulation was developed, in which the rail–track system was modeled as an infinite beam supported by an orthogonal Winkler foundation consisting of linear...... a response analysis framework for railway tracks that are subjected to braking. An analytical formulation was developed, in which the rail–track system was modeled as an infinite beam supported by an orthogonal Winkler foundation consisting of linear springs in perpendicular directions. The spring constants...... springs in perpendicular directions. The spring constants were varied over a wide range in order to represent different track types. Braking loads were simulated as representative sets of vertical and longitudinal forces, either concentrated or distributed. Considering a realistic set of model parameters...

  4. Networked simulation for team training of Space Station astronauts, ground controllers, and scientists - A training and development environment

    Hajare, Ankur R.; Wick, Daniel T.; Bovenzi, James J.

    1991-01-01

    The purpose of this paper is to describe plans for the Space Station Training Facility (SSTF) which has been designed to meet the envisioned training needs for Space Station Freedom. To meet these needs, the SSTF will integrate networked simulators with real-world systems in five training modes: Stand-Alone, Combined, Joint-Combined, Integrated, and Joint-Integrated. This paper describes the five training modes within the context of three training scenaries. In addition, this paper describes an authoring system which will support the rapid integration of new real-world system changes in the Space Station Freedom Program.

  5. Effects of salience-network-node neurofeedback training on affective biases in major depressive disorder.

    Hamilton, J Paul; Glover, Gary H; Bagarinao, Epifanio; Chang, Catie; Mackey, Sean; Sacchet, Matthew D; Gotlib, Ian H

    2016-03-30

    Neural models of major depressive disorder (MDD) posit that over-response of components of the brain's salience network (SN) to negative stimuli plays a crucial role in the pathophysiology of MDD. In the present proof-of-concept study, we tested this formulation directly by examining the affective consequences of training depressed persons to down-regulate response of SN nodes to negative material. Ten participants in the real neurofeedback group saw, and attempted to learn to down-regulate, activity from an empirically identified node of the SN. Ten other participants engaged in an equivalent procedure with the exception that they saw SN-node neurofeedback indices from participants in the real neurofeedback group. Before and after scanning, all participants completed tasks assessing emotional responses to negative scenes and to negative and positive self-descriptive adjectives. Compared to participants in the sham-neurofeedback group, from pre- to post-training, participants in the real-neurofeedback group showed a greater decrease in SN-node response to negative stimuli, a greater decrease in self-reported emotional response to negative scenes, and a greater decrease in self-reported emotional response to negative self-descriptive adjectives. Our findings provide support for a neural formulation in which the SN plays a primary role in contributing to negative cognitive biases in MDD. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  6. Early Wheel Train Damage Detection Using Wireless Sensor Network Antenna

    Fazilah, A. F. M.; Azemi, S. N.; Azremi, A. A. H.; Soh, P. J.; Kamarudin, L. M.

    2018-03-01

    Antenna for a wireless sensor network for early wheel trains damage detection has successfully developed and fabricated with the aim to minimize the risk and increase the safety guaranty for train. Current antenna design is suffered in gain and big in size. For the sensor, current existing sensor only detect when the wheel malfunction. Thus, a compact microstrip patch antenna with operating frequency at 2.45GHz is design with high gain of 4.95dB will attach to the wireless sensor device. Simulation result shows that the antenna is working at frequency 2.45GHz and the return loss at -34.46dB are in a good agreement. The result also shows the good radiation pattern and almost ideal VSWR which is 1.04. The Arduino Nano, LM35DZ and ESP8266-07 Wi-Fi module is applied to the core system with capability to sense the temperature and send the data wirelessly to the cloud. An android application has been created to monitor the temperature reading based on the real time basis. The mainly focuses for the future improvement is by minimize the size of the antenna in order to make in more compact. In addition, upgrade an android application that can collect the raw data from cloud and make an alarm system to alert the loco pilot.

  7. Application and evaluation of training for response to emergency situations

    Kidwell, M.D.

    1979-01-01

    At Washington Gas Light Co., a magnetic situation-simulation board has become an effective tool for training field personnel in emergency procedures and decisionmaking. Class participants use magnetic disks - symbolizing physical features and components of the distribution system and service equipment - to visually describe the step-by-step procedures applied to specific emergency scenarios. A manually operated clock keeps a running account of the time estimated for each step, emphasizing the need for quick response. Situation-board programs of typical problems, complete with script and drawings, are available to all training foremen to ensure uniform training throughout the department.

  8. Hazardous Materials Management and Emergency Response training Center needs assessment

    McGinnis, K.A.; Bolton, P.A.; Robinson, R.K.

    1993-09-01

    For the Hanford Site to provide high-quality training using simulated job-site situations to prepare the 4,000 Site workers and 500 emergency responders for known and unknown hazards a Hazardous Materials Management and Emergency Response Training Center is needed. The center will focus on providing classroom lecture as well as hands-on, realistic training. The establishment of the center will create a partnership among the US Department of Energy; its contractors; labor; local, state, and tribal governments; and Xavier and Tulane Universities of Louisiana. This report presents the background, history, need, benefits, and associated costs of the proposed center

  9. Impedance-Based Harmonic Instability Assessment in Multiple Electric Trains and Traction Network Interaction System

    Tao, Haidong; Hu, Haitao; Wang, Xiongfei

    2018-01-01

    This paper presents an impedance-based method to systematically investigate the interaction between multi-train and traction networks, focusing on evaluating the harmonic instability problems. Firstly, the interaction mechanism of multi-train and the traction network is represented as a feedback ...

  10. Social Networking in School Psychology Training Programs: A Survey of Faculty and Graduate Students

    Pham, Andy V.; Goforth, Anisa N.; Segool, Natasha; Burt, Isaac

    2014-01-01

    The increasing use of social networking sites has become an emerging focus in school psychology training, policy, and research. The purpose of the current study is to present data from a survey on social networking among faculty and graduate students in school psychology training programs. A total of 110 faculty and 112 graduate students in school…

  11. The lateralization of intrinsic networks in the aging brain implicates the effects of cognitive training

    Cheng eLuo

    2016-03-01

    Full Text Available Lateralization of function is an important organization of human brain. The distribution of intrinsic networks in the resting brain is strongly related to the cognitive function, gender and age. In this study, the longitudinal design with one year duration was used to evaluate the cognitive training effects on the lateralization of intrinsic networks among healthy older adults. The subjects were divided into two groups randomly: one with multi-domain cognitive training in three month, the other as a wait-list control group. Resting state fMRI data were acquired before training and one year after training. We analyzed the functional lateralization in ten common resting state fMRI networks. We observed statically significant training effects on the lateralization of two important RSNs related to high-level cognition: right- and left- frontoparietal networks. Especially, the lateralization of left-frontoparietal network were retained well in training group, but decreased in control group. The increased lateralization with aging was observed on the cerebellum network, in which the lateralization was significantly increased in control group although the same change tendency was observed in training group. These findings indicate that the lateralization of the high-level cognitive intrinsic networks is sensitive to the multi-domain cognitive training. This study provides a neuroimaging evidence to support that the cognitive training should have advantages to the cognitive decline in healthy older adults.

  12. Method of Parallel-Hierarchical Network Self-Training and its Application for Pattern Classification and Recognition

    TIMCHENKO, L.

    2012-11-01

    Full Text Available Propositions necessary for development of parallel-hierarchical (PH network training methods are discussed in this article. Unlike already known structures of the artificial neural network, where non-normalized (absolute similarity criteria are used for comparison, the suggested structure uses a normalized criterion. Based on the analysis of training rules, a conclusion is made that application of two training methods with a teacher is optimal for PH network training: error correction-based training and memory-based training. Mathematical models of training and a combined method of PH network training for recognition of static and dynamic patterns are developed.

  13. Endurance exercise training increases peripheral vascular response in human fingers.

    Katayama, K; Shimoda, M; Maeda, J; Takemiya, T

    1998-10-01

    The purpose of this study was to clarify whether peripheral vascular response to alteration of transmural pressure is changed by endurance exercise training. The healthy male subjects (training group; n = 6) performed endurance exercise training that consisted of cycle ergometer exercise 5 d.week-1 and 30 min.d-1 for a period of 8 weeks. Changes in the peripheral vascular response to alteration of transmural pressure in the human finger were measured by a differential digital photoplethysmogram (DeltaDPG) and blood pressure during passive movement of the arm to different vertical hand positions relative to heart level. Following 8 weeks of endurance training, percent changes in DeltaDPG from heart level in the training group increased significantly (mean +/- SD, -48.1 +/- 7. 3 to -58.7 +/- 9.3% at the lowered position, 46.1 +/- 13.4 to 84.6 +/- 8.8% at the elevated position, ppressure, also significantly changed in the training group over the 8 weeks (5.6 +/- 1.3 to 2.7 +/- 1.6 mV. V-1.s-1.mmHg-1 at the lowered position, 30.0 +/- 12.4 to 54.4 +/- 18. 9 mV.V-1.s-1.mmHg-1 at the elevated position ). Maximal oxygen uptake (V.O2 max) was significantly increased in the training group. On the other hand, the control group (n = 6) showed no significant changes in all parameters for 8 weeks. Therefore these results suggest that endurance exercise training induces an increase in peripheral vascular response to alteration of transmural pressure in the human finger.

  14. Conference report: Undergraduate family medicine and primary care training in Sub-Saharan Africa: Reflections of the PRIMAFAMED network

    Innocent Besigye

    2017-01-01

    Full Text Available Internationally, there is a move towards strengthening primary healthcare systems and encouraging community-based and socially responsible education. The development of doctors with an interest in primary healthcare and family medicine in the African region should begin during undergraduate training. Over the last few years, attention has been given to the development of postgraduate training in family medicine in the African region, but little attention has been given to undergraduate training. This article reports on the 8th PRIMAFAMED (Primary Care and Family Medicine Education network meeting held in Nairobi from 21 to 24 May 2016. At this meeting the delegates spent time presenting and discussing the current state of undergraduate training at 18 universities in the region and shared lessons on how to successfully implement undergraduate training. This article reports on the rationale for, information presented, process followed and conclusions reached at the conference.

  15. C-RNN-GAN: Continuous recurrent neural networks with adversarial training

    Mogren, Olof

    2016-01-01

    Generative adversarial networks have been proposed as a way of efficiently training deep generative neural networks. We propose a generative adversarial model that works on continuous sequential data, and apply it by training it on a collection of classical music. We conclude that it generates music that sounds better and better as the model is trained, report statistics on generated music, and let the reader judge the quality by downloading the generated songs.

  16. Non-Linear State Estimation Using Pre-Trained Neural Networks

    Bayramoglu, Enis; Andersen, Nils Axel; Ravn, Ole

    2010-01-01

    effecting the transformation. This function is approximated by a neural network using offline training. The training is based on monte carlo sampling. A way to obtain parametric distributions of flexible shape to be used easily with these networks is also presented. The method can also be used to improve...... other parametric methods around regions with strong non-linearities by including them inside the network....

  17. Skeletal Muscle Response to Endurance Training in IL-6-/- Mice.

    Wojewoda, M; Kmiecik, K; Majerczak, J; Ventura-Clapier, R; Fortin, D; Onopiuk, M; Rog, J; Kaminski, K; Chlopicki, S; Zoladz, J A

    2015-12-01

    We examined effects of moderate-intensity endurance training on muscle COX/CS activities and V'O2max in control WT and IL-6(-/-) mice. Animals were exercised for 10 weeks on treadmill for 1 h, 5 days a week at velocity of 6 m·min(-1) which was increased by 0.5 m·min(-1) every 2 weeks up to 8 m·min(-1) . Training triggered an increase of enzyme activities in soleus muscle of WT mice (COX: 480.3±8.9 U·g(-1) in sedentary group vs. 773.3±62.6 U·g(-1) in trained group, P<0.05 and CS: 374.0±6.0 U·g(-1) in sedentary group vs. 534.2±20.5 U·g(-1) in trained group, P<0.01, respectively) whereas no changes were observed in soleus of IL6(-/-) mice. Moreover, in mixed gastrocnemius muscle of trained IL-6(-/-) mice enzyme activities tended to be lower (COX: 410.7±48.4 U·g(-1) for sedentary vs. 277.0±36.5 U·g(-1) for trained group and CS: 343.8±24.6 U·g(-1) for sedentary vs. 251.7±27.1 U·g(-1) for trained group). No changes in V'O2max were observed in WT and IL-6(-/-) mice after training. Concluding, moderate-velocity endurance training-induced increase in COX and CS activities in muscles of WT mice only which suggests that IL-6 regulates training-induced skeletal muscle responses to exercise. © Georg Thieme Verlag KG Stuttgart · New York.

  18. Dose-response relationship of autonomic nervous system responses to individualized training impulse in marathon runners.

    Manzi, Vincenzo; Castagna, Carlo; Padua, Elvira; Lombardo, Mauro; D'Ottavio, Stefano; Massaro, Michele; Volterrani, Maurizio; Iellamo, Ferdinando

    2009-06-01

    In athletes, exercise training induces autonomic nervous system (ANS) adaptations that could be used to monitor training status. However, the relationship between training and ANS in athletes has been investigated without regard for individual training loads. We tested the hypothesis that in long-distance athletes, changes in ANS parameters are dose-response related to individual volume/intensity training load and could predict athletic performance. A spectral analysis of heart rate (HR), systolic arterial pressure variability, and baroreflex sensitivity by the sequences technique was investigated in eight recreational athletes during a 6-mo training period culminating with a marathon. Individualized training load responses were monitored by a modified training impulse (TRIMP(i)) method, which was determined in each athlete using the individual HR and lactate profiling determined during a treadmill test. Monthly TRIMP(i) steadily increased during the training period. All the ANS parameters were significantly and very highly correlated to the dose of exercise with a second-order regression model (r(2) ranged from 0.90 to 0.99; P marathon. These results suggest that in recreational athletes, ANS adaptations to exercise training are dose related on an individual basis, showing a progressive shift toward a sympathetic predominance, and that LF oscillations in HRV at peak training load could predict athletic achievement in this athlete population.

  19. Experience report: a training center for health response

    Maurmo, Alexandre M.; Leite, Teresa C.S.B.

    2009-01-01

    The Professor Nelson Valverde Training Center was created within FEAM (The ELETRONUCLEAR Medical Assistance Foundation) with the objective of capacitating Radio Nuclear Accident Responders for the Health Area in the Almirante Alvaro Alberto Nuclear Central (Angra dos Reis - RJ - Brazil). The first step was structuring the contents for this training using IAEA's Manuals as base (EPR Medical - 2005, EPR First Responders - 2006 and TMT - Handbook - 2009) and data from REAC/TS. The second step was to capacitate instructors. The third step was the integration with the Company's Radiological Protection Division, giving radiological assessment. Finally, the development of training applications, ending with Drills, Tests and Assessment, gathering data and suggestions, objectifying the constant improvement. Training Programs with pre and post evaluations have been started. Since 2004 training internal courses were ministered for 125 professionals with annual re-training and were ministered to 130 professionals from several external institutions. During the same period training courses were ministered to 140 trainees from the Radiological Protection Division of The Nuclear Power Plant of Angra dos Reis, as First Lay Responders, objectifying the improvement of the quality of the emergency response. (author)

  20. Internal measuring models in trained neural networks for parameter estimation from images

    Feng, Tian-Jin; Feng, T.J.; Houkes, Z.; Korsten, Maarten J.; Spreeuwers, Lieuwe Jan

    1992-01-01

    The internal representations of 'learned' knowledge in neural networks are still poorly understood, even for backpropagation networks. The paper discusses a possible interpretation of learned knowledge of a network trained for parameter estimation from images. The outputs of the hidden layer are the

  1. Internal-state analysis in layered artificial neural network trained to categorize lung sounds

    Oud, M

    2002-01-01

    In regular use of artificial neural networks, only input and output states of the network are known to the user. Weight and bias values can be extracted but are difficult to interpret. We analyzed internal states of networks trained to map asthmatic lung sound spectra onto lung function parameters.

  2. Home Network Technologies and Automating Demand Response

    McParland, Charles

    2009-12-01

    Over the past several years, interest in large-scale control of peak energy demand and total consumption has increased. While motivated by a number of factors, this interest has primarily been spurred on the demand side by the increasing cost of energy and, on the supply side by the limited ability of utilities to build sufficient electricity generation capacity to meet unrestrained future demand. To address peak electricity use Demand Response (DR) systems are being proposed to motivate reductions in electricity use through the use of price incentives. DR systems are also be design to shift or curtail energy demand at critical times when the generation, transmission, and distribution systems (i.e. the 'grid') are threatened with instabilities. To be effectively deployed on a large-scale, these proposed DR systems need to be automated. Automation will require robust and efficient data communications infrastructures across geographically dispersed markets. The present availability of widespread Internet connectivity and inexpensive, reliable computing hardware combined with the growing confidence in the capabilities of distributed, application-level communications protocols suggests that now is the time for designing and deploying practical systems. Centralized computer systems that are capable of providing continuous signals to automate customers reduction of power demand, are known as Demand Response Automation Servers (DRAS). The deployment of prototype DRAS systems has already begun - with most initial deployments targeting large commercial and industrial (C & I) customers. An examination of the current overall energy consumption by economic sector shows that the C & I market is responsible for roughly half of all energy consumption in the US. On a per customer basis, large C & I customers clearly have the most to offer - and to gain - by participating in DR programs to reduce peak demand. And, by concentrating on a small number of relatively

  3. 30 CFR 254.41 - Training your response personnel.

    2010-07-01

    ... procedures; (3) Oil-spill trajectory analysis and predicting spill movement; and (4) Any other... 30 Mineral Resources 2 2010-07-01 2010-07-01 false Training your response personnel. 254.41 Section 254.41 Mineral Resources MINERALS MANAGEMENT SERVICE, DEPARTMENT OF THE INTERIOR OFFSHORE OIL...

  4. Examining the Efficacy of Personal Response Devices in Army Training

    Hill, Angelina; Babbitt, Bea

    2013-01-01

    Benefits of personal response devices (PRDs) have been demonstrated in a variety of settings and disciplines in higher education. This study looked outside of higher education to investigate the efficacy of PRDs in an Army training course in terms of trainee performance, engagement, and satisfaction. Instructors were also surveyed to determine…

  5. Mechanisms of the training response in patients with peripheral ...

    by Gardner et al.18 of 21 studies on exercise training in patients with PAD, PFWD increased 179% and the .... causes an inequality in the supply of and demand for oxygen. Aerobic generation of ATP becomes .... Pohl U, Holtz J, Busse R, Bassenge E. Crucial role of endothelium in the vasodilator response to increased flow ...

  6. Child Welfare Research and Training: A Response to David Stoesz

    Smith, Brenda D.; Vandiver, Vikki L.

    2016-01-01

    In this response to David Stoesz' critique, "The Child Welfare Cartel," the authors agree that child welfare research and training must be improved. The authors disagree, however, with Stoesz' critique of social work education, his assessment of the most-needed forms of child welfare research, and his depiction of the goals and…

  7. A Telescopic Binary Learning Machine for Training Neural Networks.

    Brunato, Mauro; Battiti, Roberto

    2017-03-01

    This paper proposes a new algorithm based on multiscale stochastic local search with binary representation for training neural networks [binary learning machine (BLM)]. We study the effects of neighborhood evaluation strategies, the effect of the number of bits per weight and that of the maximum weight range used for mapping binary strings to real values. Following this preliminary investigation, we propose a telescopic multiscale version of local search, where the number of bits is increased in an adaptive manner, leading to a faster search and to local minima of better quality. An analysis related to adapting the number of bits in a dynamic way is presented. The control on the number of bits, which happens in a natural manner in the proposed method, is effective to increase the generalization performance. The learning dynamics are discussed and validated on a highly nonlinear artificial problem and on real-world tasks in many application domains; BLM is finally applied to a problem requiring either feedforward or recurrent architectures for feedback control.

  8. Metadynamics for training neural network model chemistries: A competitive assessment

    Herr, John E.; Yao, Kun; McIntyre, Ryker; Toth, David W.; Parkhill, John

    2018-06-01

    Neural network model chemistries (NNMCs) promise to facilitate the accurate exploration of chemical space and simulation of large reactive systems. One important path to improving these models is to add layers of physical detail, especially long-range forces. At short range, however, these models are data driven and data limited. Little is systematically known about how data should be sampled, and "test data" chosen randomly from some sampling techniques can provide poor information about generality. If the sampling method is narrow, "test error" can appear encouragingly tiny while the model fails catastrophically elsewhere. In this manuscript, we competitively evaluate two common sampling methods: molecular dynamics (MD), normal-mode sampling, and one uncommon alternative, Metadynamics (MetaMD), for preparing training geometries. We show that MD is an inefficient sampling method in the sense that additional samples do not improve generality. We also show that MetaMD is easily implemented in any NNMC software package with cost that scales linearly with the number of atoms in a sample molecule. MetaMD is a black-box way to ensure samples always reach out to new regions of chemical space, while remaining relevant to chemistry near kbT. It is a cheap tool to address the issue of generalization.

  9. Distributed computing methodology for training neural networks in an image-guided diagnostic application.

    Plagianakos, V P; Magoulas, G D; Vrahatis, M N

    2006-03-01

    Distributed computing is a process through which a set of computers connected by a network is used collectively to solve a single problem. In this paper, we propose a distributed computing methodology for training neural networks for the detection of lesions in colonoscopy. Our approach is based on partitioning the training set across multiple processors using a parallel virtual machine. In this way, interconnected computers of varied architectures can be used for the distributed evaluation of the error function and gradient values, and, thus, training neural networks utilizing various learning methods. The proposed methodology has large granularity and low synchronization, and has been implemented and tested. Our results indicate that the parallel virtual machine implementation of the training algorithms developed leads to considerable speedup, especially when large network architectures and training sets are used.

  10. Measuring dynamic process of working memory training with functional brain networks

    Hong Wang

    2015-12-01

    Full Text Available In this paper, we proposed the functional brain networks and graphic theory method to measure the effect of working memory training on the neural activities. 12 subjects were recruited in this study, and they did the same working memory task before they had been trained and after training. We architected functional brain networks based on EEG coherence and calculated properties of brain networks to measure the neural co-activities and the working memory level of subjects. As the result, the internal connections in frontal region decreased after working memory training, but the connection between frontal region and top region increased. And the more small-world feature was observed after training. The features observed above were in alpha (8-13 Hz and beta (13-30 Hz bands. The functional brain networks based on EEG coherence proposed in this paper can be used as the indicator of working memory level.

  11. On Training Bi-directional Neural Network Language Model with Noise Contrastive Estimation

    He, Tianxing; Zhang, Yu; Droppo, Jasha; Yu, Kai

    2016-01-01

    We propose to train bi-directional neural network language model(NNLM) with noise contrastive estimation(NCE). Experiments are conducted on a rescore task on the PTB data set. It is shown that NCE-trained bi-directional NNLM outperformed the one trained by conventional maximum likelihood training. But still(regretfully), it did not out-perform the baseline uni-directional NNLM.

  12. Training programs for emergency response personnel at Hanford

    Oscarson, E.E.

    1979-01-01

    The Three Mile Island reactor accident has focused attention on emergency planning and preparedness including selection and training of personnel. At Hanford, Pacific Northwest Laboratory (PNL) is in the unique position of providing emergency response personnel, planning, training and equipment not only for its own organization and facilities but also for the Hanford Site in general, as well as the Interagency Radiological Assistance Plan (IRAP) Region 8 Team. Team members are chosen for one or more of the emergency teams based upon professional education and/or experience as well as interest, aptitude and specialized knowledge. Consequently, the initial training orientation of each new team member is not directed toward general professional ability, but rather toward specialized knowledge required to carry out their assigned emergency tasks. Continual training and practice is necessary to maintain the interest and skills for effectively coping with major emergencies. The types of training which are conducted include: tests of emergency systems and/or procedures; drills involving plant employees and/or emergency team members (e.g., activation of emergency notification systems); short training sessions on special topics; and realistic emergency exercises involving the simulation of major accidents wherein the emergency team must solve specific problems on a real time basis

  13. Stimulation of demand response through evaluation and training

    Encinas, N.; Alfonso, D.; Alvarez, C.; Mendez, C.; Rodriguez, J.; Perez-Navarro, A.; Gabaldon, A.

    2004-01-01

    The objective of Demand Response is to enhance customer choice opportunities by means of price-responsive mechanisms in contrast to direct load control practices and associated revenues based on fixed incentives. In this way, the new approach complements the traditional concept of Demand Side Management by including the voluntary nature to customer participation. This voluntary feature implies a change in customers' traditional behaviour and therefore stimulation and training is needed to achieve an optimal participation. This paper presents a methodology developed to stimulate and train customers for Demand Response practices as well as to identify the suitable products for different customers. Finally, the paper includes an example of the methodology considering a university as a customer. (au)

  14. The effects of working memory training on functional brain network efficiency.

    Langer, Nicolas; von Bastian, Claudia C; Wirz, Helen; Oberauer, Klaus; Jäncke, Lutz

    2013-10-01

    The human brain is a highly interconnected network. Recent studies have shown that the functional and anatomical features of this network are organized in an efficient small-world manner that confers high efficiency of information processing at relatively low connection cost. However, it has been unclear how the architecture of functional brain networks is related to performance in working memory (WM) tasks and if these networks can be modified by WM training. Therefore, we conducted a double-blind training study enrolling 66 young adults. Half of the subjects practiced three WM tasks and were compared to an active control group practicing three tasks with low WM demand. High-density resting-state electroencephalography (EEG) was recorded before and after training to analyze graph-theoretical functional network characteristics at an intracortical level. WM performance was uniquely correlated with power in the theta frequency, and theta power was increased by WM training. Moreover, the better a person's WM performance, the more their network exhibited small-world topology. WM training shifted network characteristics in the direction of high performers, showing increased small-worldness within a distributed fronto-parietal network. Taken together, this is the first longitudinal study that provides evidence for the plasticity of the functional brain network underlying WM. Copyright © 2013 Elsevier Ltd. All rights reserved.

  15. Analysis of Network Topologies Underlying Ethylene Growth Response Kinetics.

    Prescott, Aaron M; McCollough, Forest W; Eldreth, Bryan L; Binder, Brad M; Abel, Steven M

    2016-01-01

    Most models for ethylene signaling involve a linear pathway. However, measurements of seedling growth kinetics when ethylene is applied and removed have resulted in more complex network models that include coherent feedforward, negative feedback, and positive feedback motifs. The dynamical responses of the proposed networks have not been explored in a quantitative manner. Here, we explore (i) whether any of the proposed models are capable of producing growth-response behaviors consistent with experimental observations and (ii) what mechanistic roles various parts of the network topologies play in ethylene signaling. To address this, we used computational methods to explore two general network topologies: The first contains a coherent feedforward loop that inhibits growth and a negative feedback from growth onto itself (CFF/NFB). In the second, ethylene promotes the cleavage of EIN2, with the product of the cleavage inhibiting growth and promoting the production of EIN2 through a positive feedback loop (PFB). Since few network parameters for ethylene signaling are known in detail, we used an evolutionary algorithm to explore sets of parameters that produce behaviors similar to experimental growth response kinetics of both wildtype and mutant seedlings. We generated a library of parameter sets by independently running the evolutionary algorithm many times. Both network topologies produce behavior consistent with experimental observations, and analysis of the parameter sets allows us to identify important network interactions and parameter constraints. We additionally screened these parameter sets for growth recovery in the presence of sub-saturating ethylene doses, which is an experimentally-observed property that emerges in some of the evolved parameter sets. Finally, we probed simplified networks maintaining key features of the CFF/NFB and PFB topologies. From this, we verified observations drawn from the larger networks about mechanisms underlying ethylene

  16. Analysis of Network Topologies Underlying Ethylene Growth Response Kinetics

    Aaron M. Prescott

    2016-08-01

    Full Text Available Most models for ethylene signaling involve a linear pathway. However, measurements of seedling growth kinetics when ethylene is applied and removed have resulted in more complex network models that include coherent feedforward, negative feedback, and positive feedback motifs. However, the dynamical responses of the proposed networks have not been explored in a quantitative manner. Here, we explore (i whether any of the proposed models are capable of producing growth-response behaviors consistent with experimental observations and (ii what mechanistic roles various parts of the network topologies play in ethylene signaling. To address this, we used computational methods to explore two general network topologies: The first contains a coherent feedforward loop that inhibits growth and a negative feedback from growth onto itself (CFF/NFB. In the second, ethylene promotes the cleavage of EIN2, with the product of the cleavage inhibiting growth and promoting the production of EIN2 through a positive feedback loop (PFB. Since few network parameters for ethylene signaling are known in detail, we used an evolutionary algorithm to explore sets of parameters that produce behaviors similar to experimental growth response kinetics of both wildtype and mutant seedlings. We generated a library of parameter sets by independently running the evolutionary algorithm many times. Both network topologies produce behavior consistent with experimental observations and analysis of the parameter sets allows us to identify important network interactions and parameter constraints. We additionally screened these parameter sets for growth recovery in the presence of sub-saturating ethylene doses, which is an experimentally-observed property that emerges in some of the evolved parameter sets. Finally, we probed simplified networks maintaining key features of the CFF/NFB and PFB topologies. From this, we verified observations drawn from the larger networks about mechanisms

  17. Korean efforts for education and training network in nuclear technology

    Han, Kyong-Won; Lee, Eui-Jin

    2007-01-01

    education programs along with a career in the nuclear fields at home and abroad should raise young generation's interests. Global network will serve as a vehicle that drives nuclear education and training forward. NTC of KAERI has developed the ANENT temporary web site (www.anent-temp.org) for the IAEA Consultancy Meting on Establishment of ANENT held in June 2003 at KAERI. According to the results from the discussion of the meeting, KAERI has requested to continue to work toward establishment of a web site for all activities related to ANENT. The followings are KAERI's efforts made for the ANENT: Installation of a portable cyber education system (Edu-V producer) and cyber studio for the effective production of VOD materials; Production of VOD type learning materials: 3 IAEA courses containing 52 lectures. For the progress of the establishment of ANENT, it is believed that exchange of informational and materials on education and training should be considered in advance among the member states. The followings are our suggestions for the exchange of information and materials to be discussed among member states: Formulation of a working group; Identification of the scope of activities; Establishment of cooperative mechanism; Design of ANENT web, and loading of existing information and materials on the web; Production and loading of new materials including cyber education and training materials; Sustainable operation of ANENT web site

  18. SuperNeurons: Dynamic GPU Memory Management for Training Deep Neural Networks

    Wang, Linnan; Ye, Jinmian; Zhao, Yiyang; Wu, Wei; Li, Ang; Song, Shuaiwen Leon; Xu, Zenglin; Kraska, Tim

    2018-01-01

    Going deeper and wider in neural architectures improves the accuracy, while the limited GPU DRAM places an undesired restriction on the network design domain. Deep Learning (DL) practitioners either need change to less desired network architectures, or nontrivially dissect a network across multiGPUs. These distract DL practitioners from concentrating on their original machine learning tasks. We present SuperNeurons: a dynamic GPU memory scheduling runtime to enable the network training far be...

  19. Metabolic Response to Four Weeks of Muscular Endurance Resistance Training

    John W. Farrell III

    2017-10-01

    Full Text Available Background: Previous investigations have shown that muscular endurance resistance training (MERT is conducive in improving the onset of blood lactate accumulation (OBLA. However, the metabolic response and time course for adaption is still unclear. Objective: The aims of the current study were to evaluate and track the metabolic response to an individual session of MERT as well as to assess performance adaptations of supplementing an aerobic exercise training program with four weeks of MERT. Methods: Seventeen aerobically active men were randomly assigned to either the experimental (EX or control group (CON, 9 EX and 8 CON. Baseline measures included a graded exercise test (GXT and 1-repetition maximum (1RM testing for leg press (LP, leg curl (LC, and leg extension (LE. CON continued their regular aerobic activity while the EX supplemented their regular aerobic exercise with 4 weeks of MERT. Results: No significant group differences were observed for all pre-training variables. Following four weeks of training no significant differences in cardiorespiratory or metabolic variables were observed for either group. However, significant improvements in LC and LE 1-RM were observed in EX compared to CON. Substantial accumulations in blood lactate were observed following each MERT session. Conclusion: Four weeks of MERT did not improve cardiorespiratory or metabolic variables, but did significantly improve LC and LE. MERT was also observed to induce a blood lactate response similar to that of HIIT. These findings suggest greater than four weeks is need to see metabolic adaptations conducive for improved aerobic performance using MERT.

  20. Reward-based training of recurrent neural networks for cognitive and value-based tasks.

    Song, H Francis; Yang, Guangyu R; Wang, Xiao-Jing

    2017-01-13

    Trained neural network models, which exhibit features of neural activity recorded from behaving animals, may provide insights into the circuit mechanisms of cognitive functions through systematic analysis of network activity and connectivity. However, in contrast to the graded error signals commonly used to train networks through supervised learning, animals learn from reward feedback on definite actions through reinforcement learning. Reward maximization is particularly relevant when optimal behavior depends on an animal's internal judgment of confidence or subjective preferences. Here, we implement reward-based training of recurrent neural networks in which a value network guides learning by using the activity of the decision network to predict future reward. We show that such models capture behavioral and electrophysiological findings from well-known experimental paradigms. Our work provides a unified framework for investigating diverse cognitive and value-based computations, and predicts a role for value representation that is essential for learning, but not executing, a task.

  1. Feedback Models for Collaboration and Trust in Crisis Response Networks

    Hudgens, Bryan J; Bordetsky, Alex

    2008-01-01

    .... Coordination within disaster response networks is difficult for several reasons, including the chaotic nature of the crisis, a need for the various organizations to balance shared goals (crisis amelioration...

  2. Response variability in balanced cortical networks

    Lerchner, Alexander; Ursta, C.; Hertz, J.

    2006-01-01

    We study the spike statistics of neurons in a network with dynamically balanced excitation and inhibition. Our model, intended to represent a generic cortical column, comprises randomly connected excitatory and inhibitory leaky integrate-and-fire neurons, driven by excitatory input from an external...

  3. Comparisons of complex network based models and real train flow model to analyze Chinese railway vulnerability

    Ouyang, Min; Zhao, Lijing; Hong, Liu; Pan, Zhezhe

    2014-01-01

    Recently numerous studies have applied complex network based models to study the performance and vulnerability of infrastructure systems under various types of attacks and hazards. But how effective are these models to capture their real performance response is still a question worthy of research. Taking the Chinese railway system as an example, this paper selects three typical complex network based models, including purely topological model (PTM), purely shortest path model (PSPM), and weight (link length) based shortest path model (WBSPM), to analyze railway accessibility and flow-based vulnerability and compare their results with those from the real train flow model (RTFM). The results show that the WBSPM can produce the train routines with 83% stations and 77% railway links identical to the real routines and can approach the RTFM the best for railway vulnerability under both single and multiple component failures. The correlation coefficient for accessibility vulnerability from WBSPM and RTFM under single station failures is 0.96 while it is 0.92 for flow-based vulnerability; under multiple station failures, where each station has the same failure probability fp, the WBSPM can produce almost identical vulnerability results with those from the RTFM under almost all failures scenarios when fp is larger than 0.62 for accessibility vulnerability and 0.86 for flow-based vulnerability

  4. Natural semantic networks in the Social Representations of Responsibility

    Humberto Emilio Aguilera Arévalo

    2010-07-01

    Full Text Available The study of social representations of responsibility is a fundamental construct of the present democratic societies. Different empirical techniques such as natural semantic networks can significantly improve the approach to the object of study than the traditional associationist techniques. The present study examines natural semantic networks of six stimulus words with respect to responsibility and irresponsibility at the individual, in group and out group level in a sample of Guatemalan students.

  5. A neural network driving curve generation method for the heavy-haul train

    Youneng Huang

    2016-05-01

    Full Text Available The heavy-haul train has a series of characteristics, such as the locomotive traction properties, the longer length of train, and the nonlinear train pipe pressure during train braking. When the train is running on a continuous long and steep downgrade railway line, the safety of the train is ensured by cycle braking, which puts high demands on the driving skills of the driver. In this article, a driving curve generation method for the heavy-haul train based on a neural network is proposed. First, in order to describe the nonlinear characteristics of train braking, the neural network model is constructed and trained by practical driving data. In the neural network model, various nonlinear neurons are interconnected to work for information processing and transmission. The target value of train braking pressure reduction and release time is achieved by modeling the braking process. The equation of train motion is computed to obtain the driving curve. Finally, in four typical operation scenarios, comparing the curve data generated by the method with corresponding practical data of the Shuohuang heavy-haul railway line, the results show that the method is effective.

  6. Exploring the effects of transducer models when training convolutional neural networks to eliminate reflection artifacts in experimental photoacoustic images

    Allman, Derek; Reiter, Austin; Bell, Muyinatu

    2018-02-01

    We previously proposed a method of removing reflection artifacts in photoacoustic images that uses deep learning. Our approach generally relies on using simulated photoacoustic channel data to train a convolutional neural network (CNN) that is capable of distinguishing sources from artifacts based on unique differences in their spatial impulse responses (manifested as depth-based differences in wavefront shapes). In this paper, we directly compare a CNN trained with our previous continuous transducer model to a CNN trained with an updated discrete acoustic receiver model that more closely matches an experimental ultrasound transducer. These two CNNs were trained with simulated data and tested on experimental data. The CNN trained using the continuous receiver model correctly classified 100% of sources and 70.3% of artifacts in the experimental data. In contrast, the CNN trained using the discrete receiver model correctly classified 100% of sources and 89.7% of artifacts in the experimental images. The 19.4% increase in artifact classification accuracy indicates that an acoustic receiver model that closely mimics the experimental transducer plays an important role in improving the classification of artifacts in experimental photoacoustic data. Results are promising for developing a method to display CNN-based images that remove artifacts in addition to only displaying network-identified sources as previously proposed.

  7. Ventilatory responses to exercise training in obese adolescents.

    Mendelson, Monique; Michallet, Anne-Sophie; Estève, François; Perrin, Claudine; Levy, Patrick; Wuyam, Bernard; Flore, Patrice

    2012-10-15

    The aim of this study was to examine ventilatory responses to training in obese adolescents. We assessed body composition, pulmonary function and ventilatory responses (among which expiratory flow limitation and operational lung volumes) during progressive cycling exercise in 16 obese adolescents (OB) before and after 12 weeks of exercise training and in 16 normal-weight volunteers. As expected, obese adolescents' resting expiratory reserve volume was lower and inversely correlated with thoraco-abdominal fat mass (r = -0.74, p<0.0001). OB presented lower end expiratory (EELV) and end inspiratory lung volumes (EILV) at rest and during submaximal exercise, and modest expiratory flow limitation. After training, OB increased maximal aerobic performance (+19%) and maximal inspiratory pressure (93.7±31.4 vs. 81.9±28.2 cm H2O, +14%) despite lack of decrease in trunk fat and body weight. Furthermore, EELV and EILV were greater during submaximal exercise (+11% and +9% in EELV and EILV, respectively), expiratory flow limitation delayed but was not accompanied by increased V(T). However, submaximal exertional symptoms (dyspnea and leg discomfort) were significantly decreased (-71.3% and -70.7%, respectively). Our results suggest that exercise training can improve pulmonary function at rest (static inspiratory muscle strength) and exercise (greater operating lung volumes and delayed expiratory flow limitation) but these modifications did not entirely account for improved dyspnea and exercise performance in obese adolescents. Copyright © 2012 Elsevier B.V. All rights reserved.

  8. Topologically determined optimal stochastic resonance responses of spatially embedded networks

    Gosak, Marko; Marhl, Marko; Korosak, Dean

    2011-01-01

    We have analyzed the stochastic resonance phenomenon on spatial networks of bistable and excitable oscillators, which are connected according to their location and the amplitude of external forcing. By smoothly altering the network topology from a scale-free (SF) network with dominating long-range connections to a network where principally only adjacent oscillators are connected, we reveal that besides an optimal noise intensity, there is also a most favorable interaction topology at which the best correlation between the response of the network and the imposed weak external forcing is achieved. For various distributions of the amplitudes of external forcing, the optimal topology is always found in the intermediate regime between the highly heterogeneous SF network and the strong geometric regime. Our findings thus indicate that a suitable number of hubs and with that an optimal ratio between short- and long-range connections is necessary in order to obtain the best global response of a spatial network. Furthermore, we link the existence of the optimal interaction topology to a critical point indicating the transition from a long-range interactions-dominated network to a more lattice-like network structure.

  9. IAEA Response and Assistance Network. Date Effective: 1 January 2011

    2010-01-01

    This publication is a tool for (1) supporting the provision of international assistance in the event of a nuclear or radiological incident or emergency, (2) cooperation between States, their competent authorities and the IAEA, and (3) harmonization of response capabilities of States offering assistance under the Response and Assistance Network (RANET). The publication may also assist competent authorities and other response organizations in their efforts to establish and/or maintain their own response capabilities.

  10. Statistical and optimization methods to expedite neural network training for transient identification

    Reifman, J.; Vitela, E.J.; Lee, J.C.

    1993-01-01

    Two complementary methods, statistical feature selection and nonlinear optimization through conjugate gradients, are used to expedite feedforward neural network training. Statistical feature selection techniques in the form of linear correlation coefficients and information-theoretic entropy are used to eliminate redundant and non-informative plant parameters to reduce the size of the network. The method of conjugate gradients is used to accelerate the network training convergence and to systematically calculate the Teaming and momentum constants at each iteration. The proposed techniques are compared with the backpropagation algorithm using the entire set of plant parameters in the training of neural networks to identify transients simulated with the Midland Nuclear Power Plant Unit 2 simulator. By using 25% of the plant parameters and the conjugate gradients, a 30-fold reduction in CPU time was obtained without degrading the diagnostic ability of the network

  11. Robust network topologies for generating switch-like cellular responses.

    Najaf A Shah

    2011-06-01

    Full Text Available Signaling networks that convert graded stimuli into binary, all-or-none cellular responses are critical in processes ranging from cell-cycle control to lineage commitment. To exhaustively enumerate topologies that exhibit this switch-like behavior, we simulated all possible two- and three-component networks on random parameter sets, and assessed the resulting response profiles for both steepness (ultrasensitivity and extent of memory (bistability. Simulations were used to study purely enzymatic networks, purely transcriptional networks, and hybrid enzymatic/transcriptional networks, and the topologies in each class were rank ordered by parametric robustness (i.e., the percentage of applied parameter sets exhibiting ultrasensitivity or bistability. Results reveal that the distribution of network robustness is highly skewed, with the most robust topologies clustering into a small number of motifs. Hybrid networks are the most robust in generating ultrasensitivity (up to 28% and bistability (up to 18%; strikingly, a purely transcriptional framework is the most fragile in generating either ultrasensitive (up to 3% or bistable (up to 1% responses. The disparity in robustness among the network classes is due in part to zero-order ultrasensitivity, an enzyme-specific phenomenon, which repeatedly emerges as a particularly robust mechanism for generating nonlinearity and can act as a building block for switch-like responses. We also highlight experimentally studied examples of topologies enabling switching behavior, in both native and synthetic systems, that rank highly in our simulations. This unbiased approach for identifying topologies capable of a given response may be useful in discovering new natural motifs and in designing robust synthetic gene networks.

  12. Functional neural networks underlying response inhibition in adolescents and adults.

    Stevens, Michael C; Kiehl, Kent A; Pearlson, Godfrey D; Calhoun, Vince D

    2007-07-19

    This study provides the first description of neural network dynamics associated with response inhibition in healthy adolescents and adults. Functional and effective connectivity analyses of whole brain hemodynamic activity elicited during performance of a Go/No-Go task were used to identify functionally integrated neural networks and characterize their causal interactions. Three response inhibition circuits formed a hierarchical, inter-dependent system wherein thalamic modulation of input to premotor cortex by fronto-striatal regions led to response suppression. Adolescents differed from adults in the degree of network engagement, regional fronto-striatal-thalamic connectivity, and network dynamics. We identify and characterize several age-related differences in the function of neural circuits that are associated with behavioral performance changes across adolescent development.

  13. Working memory training mostly engages general-purpose large-scale networks for learning.

    Salmi, Juha; Nyberg, Lars; Laine, Matti

    2018-03-21

    The present meta-analytic study examined brain activation changes following working memory (WM) training, a form of cognitive training that has attracted considerable interest. Comparisons with perceptual-motor (PM) learning revealed that WM training engages domain-general large-scale networks for learning encompassing the dorsal attention and salience networks, sensory areas, and striatum. Also the dynamics of the training-induced brain activation changes within these networks showed a high overlap between WM and PM training. The distinguishing feature for WM training was the consistent modulation of the dorso- and ventrolateral prefrontal cortex (DLPFC/VLPFC) activity. The strongest candidate for mediating transfer to similar untrained WM tasks was the frontostriatal system, showing higher striatal and VLPFC activations, and lower DLPFC activations after training. Modulation of transfer-related areas occurred mostly with longer training periods. Overall, our findings place WM training effects into a general perception-action cycle, where some modulations may depend on the specific cognitive demands of a training task. Copyright © 2018 Elsevier Ltd. All rights reserved.

  14. Structured chaos shapes spike-response noise entropy in balanced neural networks

    Guillaume eLajoie

    2014-10-01

    Full Text Available Large networks of sparsely coupled, excitatory and inhibitory cells occur throughout the brain. For many models of these networks, a striking feature is that their dynamics are chaotic and thus, are sensitive to small perturbations. How does this chaos manifest in the neural code? Specifically, how variable are the spike patterns that such a network produces in response to an input signal? To answer this, we derive a bound for a general measure of variability -- spike-train entropy. This leads to important insights on the variability of multi-cell spike pattern distributions in large recurrent networks of spiking neurons responding to fluctuating inputs. The analysis is based on results from random dynamical systems theory and is complemented by detailed numerical simulations. We find that the spike pattern entropy is an order of magnitude lower than what would be extrapolated from single cells. This holds despite the fact that network coupling becomes vanishingly sparse as network size grows -- a phenomenon that depends on ``extensive chaos, as previously discovered for balanced networks without stimulus drive. Moreover, we show how spike pattern entropy is controlled by temporal features of the inputs. Our findings provide insight into how neural networks may encode stimuli in the presence of inherently chaotic dynamics.

  15. Corporate Social Responsibility in Online Social Networks

    Horn, Christian; Brem, Alexander; Wölfl, S.

    2014-01-01

    Considering growing public awareness of social, ethical and ecological responsibility, companies have constantly been increasing their efforts in CSR communications. Social Media as tools of brand communication receive increasing attention and it is expected that the marketing sector...

  16. Optimizing Intermodal Train Schedules with a Design Balanced Network Design Model

    Pedersen, Michael Berliner; Crainic, Teodor Gabriel

    We present a modeling approach for optimizing intermodal trains schedules based on an infrastructure divided into time-dependent train paths. The formulation can be generalized to a capacitated multi commodity network design model with additional design balance constraints. We present a Tabu Search...

  17. Interpersonal competencies: Responsiveness, technique, and training in psychotherapy.

    Hatcher, Robert L

    2015-11-01

    Professional practice in psychology is anchored in interpersonal or relational skills. These skills are essential to successful interactions with clients and their families, students, and colleagues. Expertise in these skills is desired and expected for the practicing psychologist. An important but little-studied aspect of interpersonal skills is what Stiles and colleagues (Stiles, Honos-Webb, & Surko, 1998; Stiles, 2009, 2013) have called appropriate responsiveness. In treatment relationships, appropriate responsiveness is the therapist's ability to achieve optimal benefit for the client by adjusting responses to the current state of the client and the interaction. This article was designed to clarify this aspect of responsiveness, showing its links to empathy, illustrating how responsiveness has been detected in controlled clinical trials, discussing how educators and supervisors have worked to enhance students' responsiveness, and considering how appropriate responsiveness has been assessed. The article also discusses the development of skills underlying appropriate responsiveness and the role of stable differences in talent in training of professional psychologists. Notwithstanding other pessimistic reports on psychologists' expertise, demonstrable expertise may exist in the effective, responsive use of these skills in treatment settings. Appropriate responsiveness may be a variety of executive functioning, organizing and guiding the use of many specific competencies. As such it may be a metacompetency, with implications for the design of competency schemes. Key to all of these considerations is the distinction between therapeutic techniques and their responsive use, which involves astute judgment as to when and how to utilize these responses to best effect in the treatment situation. (c) 2015 APA, all rights reserved).

  18. Adaptive training of neural networks for control of autonomous mobile robots

    Steur, E.; Vromen, T.; Nijmeijer, H.; Fossen, T.I.; Nijmeijer, H.; Pettersen, K.Y.

    2017-01-01

    We present an adaptive training procedure for a spiking neural network, which is used for control of a mobile robot. Because of manufacturing tolerances, any hardware implementation of a spiking neural network has non-identical nodes, which limit the performance of the controller. The adaptive

  19. Navigating Social Networking and Social Media in School Psychology: Ethical and Professional Considerations in Training Programs

    Pham, Andy V.

    2014-01-01

    Social networking and social media have undoubtedly proliferated within the past decade, allowing widespread communication and dissemination of user-generated content and information. Some psychology graduate programs, including school psychology, have started to embrace social networking and media for instructional and training purposes; however,…

  20. Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning?

    Tajbakhsh, Nima; Shin, Jae Y.; Gurudu, Suryakanth R.; Hurst, R. Todd; Kendall, Christopher B.; Gotway, Michael B.; Liang, Jianming

    2017-01-01

    Training a deep convolutional neural network (CNN) from scratch is difficult because it requires a large amount of labeled training data and a great deal of expertise to ensure proper convergence. A promising alternative is to fine-tune a CNN that has been pre-trained using, for instance, a large set of labeled natural images. However, the substantial differences between natural and medical images may advise against such knowledge transfer. In this paper, we seek to answer the following centr...

  1. Mapping, Awareness, and Virtualization Network Administrator Training Tool (MAVNATT) Architecture and Framework

    2015-06-01

    unit may setup and teardown the entire tactical infrastructure multiple times per day. This tactical network administrator training is a critical...language and runs on Linux and Unix based systems. All provisioning is based around the Nagios Core application, a powerful backend solution for network...start up a large number of virtual machines quickly. CORE supports the simulation of fixed and mobile networks. CORE is open-source, written in Python

  2. Contemporary social network sites: Relevance in anesthesiology teaching, training, and research

    Rudrashish Haldar; Ashutosh Kaushal; Sukhen Samanta; Paurush Ambesh; Shashi Srivastava; Prabhat K Singh

    2016-01-01

    Objective: The phenomenal popularity of social networking sites has been used globally by medical professionals to boost professional associations and scientific developments. They have tremendous potential to forge professional liaisons, generate employment,upgrading skills and publicizing scientific achievements. We highlight the role of social networking mediums in influencing teaching, training and research in anaesthesiology. Background: The growth of social networking sites have been pr...

  3. Training signaling pathway maps to biochemical data with constrained fuzzy logic: quantitative analysis of liver cell responses to inflammatory stimuli.

    Melody K Morris

    2011-03-01

    Full Text Available Predictive understanding of cell signaling network operation based on general prior knowledge but consistent with empirical data in a specific environmental context is a current challenge in computational biology. Recent work has demonstrated that Boolean logic can be used to create context-specific network models by training proteomic pathway maps to dedicated biochemical data; however, the Boolean formalism is restricted to characterizing protein species as either fully active or inactive. To advance beyond this limitation, we propose a novel form of fuzzy logic sufficiently flexible to model quantitative data but also sufficiently simple to efficiently construct models by training pathway maps on dedicated experimental measurements. Our new approach, termed constrained fuzzy logic (cFL, converts a prior knowledge network (obtained from literature or interactome databases into a computable model that describes graded values of protein activation across multiple pathways. We train a cFL-converted network to experimental data describing hepatocytic protein activation by inflammatory cytokines and demonstrate the application of the resultant trained models for three important purposes: (a generating experimentally testable biological hypotheses concerning pathway crosstalk, (b establishing capability for quantitative prediction of protein activity, and (c prediction and understanding of the cytokine release phenotypic response. Our methodology systematically and quantitatively trains a protein pathway map summarizing curated literature to context-specific biochemical data. This process generates a computable model yielding successful prediction of new test data and offering biological insight into complex datasets that are difficult to fully analyze by intuition alone.

  4. Education and Training, and Knowledge Networks for Capacity-Building in Nuclear Security

    Mrabit, Khammar

    2014-01-01

    Conclusions: • Capacity Building (CB) is critical for States to establish and maintain effective and sustainable nuclear security regime. • IAEA is a worldwide platform promoting international cooperation for CB in nuclear security involving more than 160 countries and over 20 Organizations and Initiatives. • IAEA Division of Nuclear Security is ready to continue supporting States in developing their CB through: – Comprehensive Training Programme: more than 80 training events annually – International Nuclear Security Training and Support Centre Network (NSSC) – Comprehensive Education Programme – International Nuclear Security Network (INSEN)

  5. Network-Based Coordination of Civil-Service Training: Lessons from the Case of Estonia

    Metsma Merilin

    2017-06-01

    Full Text Available The focus of this article is on the coordination of civil-service training in a decentralized civil-service system. The Estonian case is studied. The article investigates network-based coordination, analyzes the power sources of the central coordinator and discusses the opportunities and limitations of creating coherence through network-type cooperation. The article concludes that the key power sources for the central coordinator are financial, human and technical resources paired with knowledge, leadership and commitment. The case study shows that, in a decentralized civil service system, a common understanding on training and development can be fostered by intense collaboration through networks.

  6. IMPLICATIONS OF SOCIAL RESPONSIBILITY DISCLOSURE ON GLOBAL PRODUCTION NETWORK

    Le Bo; Dan Shen; Jin Jun Bo

    2014-01-01

    This paper aims to discuss effectiveness of social responsibility disclosure in promoting global production network. Through a critical review on the theoretical development from supply chain to global production network, the global supply chain management of Apple Inc., as a case, is investigated, with focus on corporate and NGOs’ social disclosure on the environmental and labor rights' issues of its suppliers in China. The paper concludes that effectiveness of corporate social disclosure on...

  7. Repetition Performance And Blood Lactate Responses Adopting Different Recovery Periods Between Training Sessions In Trained Men.

    Miranda, Humberto; de Freitas Maia, Marianna; Paz, Gabriel Andrade; de Souza, João A A A; Simão, Roberto; de Araújo Farias, Déborah; Willardson, Jeffrey M

    2017-02-08

    The purpose of this study was to examine the effect of different recovery periods (24h, 48h, and 72h) between repeated resistance training (RT) sessions for the upper body muscles on repetition performance and blood lactate responses in trained men. Sixteen recreationally trained men (age: 26.1 ± 3.1 years; height: 179 ± 4.5 cm; body mass: 82.6 ± 4.0 kg, 4.5 ± 2.2 years of RT experience) participated in this study. Eight-repetition maximum (8-RM) loads were determined for the bench press (BP), 30° incline bench press (BP30), and 45° incline bench press (BP45) exercises. To assess the effects of different recovery periods between repeated training sessions, three protocols were performed in randomized order, including: 24 hours (P24); 48 hours (P48); and 72 hours (P72). Each RT session consisted of performing four repetition maximum sets of BP, BP30, and BP45 with 8-RM loads and 2-minute rest intervals between sets. Blood lactate levels were measured pre-session (PRE), immediately post-session (POST), 3 minutes post-session (P3), and 5 minutes post-session (P5). For the P24 protocol, significant decreases in repetition performance were found between sessions for the BP, BP30, and BP45 exercises, respectively. When considering session 2 only, the total work (repetition x sets) was significantly higher in P48 and P72 versus P24 for the BP30 and BP45 exercises. Blood lactate levels (i.e. POST, P3, and P5) significantly increased for session 2 under the P24 compared to the P48 and P72 protocols, respectively. Therefore, coaches and practitioners who need to accomplish a higher training volume for the upper body muscles should adopt recovery periods longer than 24 hours between sessions that train the same or similar muscle groups.

  8. Training the next generation of psychotraumatologists: COllaborative Network for Training and EXcellence in psychoTraumatology (CONTEXT)

    Vallières, Frédérique; Hyland, Philip; Murphy, Jamie; Hansen, Maj; Shevlin, Mark; Elklit, Ask; Ceannt, Ruth; Armour, Cherie; Wiedemann, Nana; Munk, Mette; Dinesen, Cecilie; O’Hare, Geraldine; Cunningham, Twylla; Askerod, Ditte; Spitz, Pernille; Blackwell, Noeline; McCarthy, Angela; O’Dowd, Leonie; Scott, Shirley; Reid, Tracey; Mokake, Andreas; Halpin, Rory; Perera, Camila; Gleeson, Christina; Frost, Rachel; Flanagan, Natalie; Aldamman, Kinan; Tamrakar, Trina; Louison Vang, Maria; Sherwood, Larissa; Travers, Áine; Haahr-Pedersen, Ida; Walshe, Catherine; McDonagh, Tracey; Bramsen, Rikke Holm

    2018-01-01

    ABSTRACT In this paper we present a description of the Horizon2020, Marie Skłodowska-Curie Action funded, research and training programme CONTEXT: COllaborative Network for Training and EXcellence in psychoTraumatology. The three objectives of the programme are put forward, each of which refers to a key component of the CONTEXT programme. First, we summarize the 12 individual research projects that will take place across three priority populations: (i) refugees and asylum seekers, (ii) first responders, and (iii) perpetrators and survivors of childhood and gender-based violence. Second, we detail the mentoring and training programme central to CONTEXT. Finally, we describe how the research, together with the training, will contribute towards better policy, guidelines, and practice within the field of psychotraumatology. PMID:29372015

  9. Training the next generation of psychotraumatologists: COllaborative Network for Training and EXcellence in psychoTraumatology (CONTEXT).

    Vallières, Frédérique; Hyland, Philip; Murphy, Jamie; Hansen, Maj; Shevlin, Mark; Elklit, Ask; Ceannt, Ruth; Armour, Cherie; Wiedemann, Nana; Munk, Mette; Dinesen, Cecilie; O'Hare, Geraldine; Cunningham, Twylla; Askerod, Ditte; Spitz, Pernille; Blackwell, Noeline; McCarthy, Angela; O'Dowd, Leonie; Scott, Shirley; Reid, Tracey; Mokake, Andreas; Halpin, Rory; Perera, Camila; Gleeson, Christina; Frost, Rachel; Flanagan, Natalie; Aldamman, Kinan; Tamrakar, Trina; Louison Vang, Maria; Sherwood, Larissa; Travers, Áine; Haahr-Pedersen, Ida; Walshe, Catherine; McDonagh, Tracey; Bramsen, Rikke Holm

    2018-01-01

    In this paper we present a description of the Horizon2020, Marie Skłodowska-Curie Action funded, research and training programme CONTEXT: COllaborative Network for Training and EXcellence in psychoTraumatology. The three objectives of the programme are put forward, each of which refers to a key component of the CONTEXT programme. First, we summarize the 12 individual research projects that will take place across three priority populations: (i) refugees and asylum seekers, (ii) first responders, and (iii) perpetrators and survivors of childhood and gender-based violence. Second, we detail the mentoring and training programme central to CONTEXT. Finally, we describe how the research, together with the training, will contribute towards better policy, guidelines, and practice within the field of psychotraumatology.

  10. A Dynamic Linear Hashing Method for Redundancy Management in Train Ethernet Consist Network

    Xiaobo Nie

    2016-01-01

    Full Text Available Massive transportation systems like trains are considered critical systems because they use the communication network to control essential subsystems on board. Critical system requires zero recovery time when a failure occurs in a communication network. The newly published IEC62439-3 defines the high-availability seamless redundancy protocol, which fulfills this requirement and ensures no frame loss in the presence of an error. This paper adopts these for train Ethernet consist network. The challenge is management of the circulating frames, capable of dealing with real-time processing requirements, fast switching times, high throughout, and deterministic behavior. The main contribution of this paper is the in-depth analysis it makes of network parameters imposed by the application of the protocols to train control and monitoring system (TCMS and the redundant circulating frames discarding method based on a dynamic linear hashing, using the fastest method in order to resolve all the issues that are dealt with.

  11. Aging and Network Properties: Stability Over Time and Links with Learning during Working Memory Training

    Alexandru D. Iordan

    2018-01-01

    Full Text Available Growing evidence suggests that healthy aging affects the configuration of large-scale functional brain networks. This includes reducing network modularity and local efficiency. However, the stability of these effects over time and their potential role in learning remain poorly understood. The goal of the present study was to further clarify previously reported age effects on “resting-state” networks, to test their reliability over time, and to assess their relation to subsequent learning during training. Resting-state fMRI data from 23 young (YA and 20 older adults (OA were acquired in 2 sessions 2 weeks apart. Graph-theoretic analyses identified both consistencies in network structure and differences in module composition between YA and OA, suggesting topological changes and less stability of functional network configuration with aging. Brain-wide, OA showed lower modularity and local efficiency compared to YA, consistent with the idea of age-related functional dedifferentiation, and these effects were replicable over time. At the level of individual networks, OA consistently showed greater participation and lower local efficiency and within-network connectivity in the cingulo-opercular network, as well as lower intra-network connectivity in the default-mode network and greater participation of the somato-sensorimotor network, suggesting age-related differential effects at the level of specialized brain modules. Finally, brain-wide network properties showed associations, albeit limited, with learning rates, as assessed with 10 days of computerized working memory training administered after the resting-state sessions, suggesting that baseline network configuration may influence subsequent learning outcomes. Identification of neural mechanisms associated with learning-induced plasticity is important for further clarifying whether and how such changes predict the magnitude and maintenance of training gains, as well as the extent and limits of

  12. 33 CFR Appendix C to Part 155 - Training Elements for Oil Spill Response Plans

    2010-07-01

    .... 155, App. C Appendix C to Part 155—Training Elements for Oil Spill Response Plans 1. General 1.1The portion of the plan dealing with training is one of the key elements of a response plan. This concept is... included training as one of the sections required in a vessel or facility response plan. In reviewing...

  13. 5-HTTLPR differentially predicts brain network responses to emotional faces

    Fisher, Patrick M; Grady, Cheryl L; Madsen, Martin K

    2015-01-01

    The effects of the 5-HTTLPR polymorphism on neural responses to emotionally salient faces have been studied extensively, focusing on amygdala reactivity and amygdala-prefrontal interactions. Despite compelling evidence that emotional face paradigms engage a distributed network of brain regions...... to fearful faces was significantly greater in S' carriers compared to LA LA individuals. These findings provide novel evidence for emotion-specific 5-HTTLPR effects on the response of a distributed set of brain regions including areas responsive to emotionally salient stimuli and critical components...... involved in emotion, cognitive and visual processing, less is known about 5-HTTLPR effects on broader network responses. To address this, we evaluated 5-HTTLPR differences in the whole-brain response to an emotional faces paradigm including neutral, angry and fearful faces using functional magnetic...

  14. Regional training course on medical response on radiological emergencies. Annex

    2000-01-01

    This short information is an annex of the documentation distributed to the participants to the International Atomic Energy Agency (IAEA) Regional Training Course on Medical Response on Radiological Emergencies, organised by the IAEA in co-operation with the Government of Argentina thought the Nuclear Regulatory Authority, held in Buenos Aires, Argentina, 16-20 October 2000. The course was intended to people from IAEA Member State in the Latin American and Caribbean region, and to professionals and workers on medicine related with the radiation protection. This annex present information about: Radioactive materials transport; Internal and external contamination; Radiation accidents; Physical dosimetry

  15. Enhancing response coordination through the assessment of response network structural dynamics.

    Alireza Abbasi

    Full Text Available Preparing for intensifying threats of emergencies in unexpected, dangerous, and serious natural or man-made events, and consequent management of the situation, is highly demanding in terms of coordinating the personnel and resources to support human lives and the environment. This necessitates prompt action to manage the uncertainties and risks imposed by such extreme events, which requires collaborative operation among different stakeholders (i.e., the personnel from both the state and local communities. This research aims to find a way to enhance the coordination of multi-organizational response operations. To do so, this manuscript investigates the role of participants in the formed coordination response network and also the emergence and temporal dynamics of the network. By analyzing an inter-personal response coordination operation to an extreme bushfire event, the networks' and participants' structural change is evaluated during the evolution of the operation network over four time durations. The results reveal that the coordination response network becomes more decentralized over time due to the high volume of communication required to exchange information. New emerging communication structures often do not fit the developed plans, which stress the need for coordination by feedback in addition to by plan. In addition, we find that the participant's brokering role in the response operation network identifies a formal and informal coordination role. This is useful for comparison of network structures to examine whether what really happens during response operations complies with the initial policy.

  16. Weighted complex network analysis of the Beijing subway system: Train and passenger flows

    Feng, Jia; Li, Xiamiao; Mao, Baohua; Xu, Qi; Bai, Yun

    2017-05-01

    In recent years, complex network theory has become an important approach to the study of the structure and dynamics of traffic networks. However, because traffic data is difficult to collect, previous studies have usually focused on the physical topology of subway systems, whereas few studies have considered the characteristics of traffic flows through the network. Therefore, in this paper, we present a multi-layer model to analyze traffic flow patterns in subway networks, based on trip data and an operation timetable obtained from the Beijing Subway System. We characterize the patterns in terms of the spatiotemporal flow size distributions of both the train flow network and the passenger flow network. In addition, we describe the essential interactions between these two networks based on statistical analyses. The results of this study suggest that layered models of transportation systems can elucidate fundamental differences between the coexisting traffic flows and can also clarify the mechanism that causes these differences.

  17. Response efficiency during functional communication training: effects of effort on response allocation.

    Richman, D M; Wacker, D P; Winborn, L

    2001-01-01

    An analogue functional analysis revealed that the problem behavior of a young child with developmental delays was maintained by positive reinforcement. A concurrent-schedule procedure was then used to vary the amount of effort required to emit mands. Results suggested that response effort can be an important variable when developing effective functional communication training programs.

  18. Efficient probabilistic inference in generic neural networks trained with non-probabilistic feedback.

    Orhan, A Emin; Ma, Wei Ji

    2017-07-26

    Animals perform near-optimal probabilistic inference in a wide range of psychophysical tasks. Probabilistic inference requires trial-to-trial representation of the uncertainties associated with task variables and subsequent use of this representation. Previous work has implemented such computations using neural networks with hand-crafted and task-dependent operations. We show that generic neural networks trained with a simple error-based learning rule perform near-optimal probabilistic inference in nine common psychophysical tasks. In a probabilistic categorization task, error-based learning in a generic network simultaneously explains a monkey's learning curve and the evolution of qualitative aspects of its choice behavior. In all tasks, the number of neurons required for a given level of performance grows sublinearly with the input population size, a substantial improvement on previous implementations of probabilistic inference. The trained networks develop a novel sparsity-based probabilistic population code. Our results suggest that probabilistic inference emerges naturally in generic neural networks trained with error-based learning rules.Behavioural tasks often require probability distributions to be inferred about task specific variables. Here, the authors demonstrate that generic neural networks can be trained using a simple error-based learning rule to perform such probabilistic computations efficiently without any need for task specific operations.

  19. ENETRAP: European network on education and training in radiological protection

    Michele Coeck; Cecile Etard; Siegurd Moebius; Annemarie Schmitt-Hannig; Andrea Luciani; Jan van der Steen; Marisa Marco; Joanne Stewart; Jacques Balosso; Rosemary Thompson

    2006-01-01

    Recent studies have shown that there is a wide variety of approaches to education and training of the Qualified Expert across the EU. As they stand, such differences are a barrier to the mutual recognition of the Qualified Expert status and, in part, are contributing to a perceived shortage in expertise in radiation protection and safety. The overall aim of ENETRAP is to determine mechanisms that in the longer term will facilitate better integration of education and training activities (with a view to mutual recognition across the EU) and to ensure the ongoing provision of the necessary competence and expertise at the level of the Qualified Expert. (authors)

  20. SU-F-E-09: Respiratory Signal Prediction Based On Multi-Layer Perceptron Neural Network Using Adjustable Training Samples

    Sun, W; Jiang, M; Yin, F [Duke University Medical Center, Durham, NC (United States)

    2016-06-15

    Purpose: Dynamic tracking of moving organs, such as lung and liver tumors, under radiation therapy requires prediction of organ motions prior to delivery. The shift of moving organ may change a lot due to huge transform of respiration at different periods. This study aims to reduce the influence of that changes using adjustable training signals and multi-layer perceptron neural network (ASMLP). Methods: Respiratory signals obtained using a Real-time Position Management(RPM) device were used for this study. The ASMLP uses two multi-layer perceptron neural networks(MLPs) to infer respiration position alternately and the training sample will be updated with time. Firstly, a Savitzky-Golay finite impulse response smoothing filter was established to smooth the respiratory signal. Secondly, two same MLPs were developed to estimate respiratory position from its previous positions separately. Weights and thresholds were updated to minimize network errors according to Leverberg-Marquart optimization algorithm through backward propagation method. Finally, MLP 1 was used to predict 120∼150s respiration position using 0∼120s training signals. At the same time, MLP 2 was trained using 30∼150s training signals. Then MLP is used to predict 150∼180s training signals according to 30∼150s training signals. The respiration position is predicted as this way until it was finished. Results: In this experiment, the two methods were used to predict 2.5 minute respiratory signals. For predicting 1s ahead of response time, correlation coefficient was improved from 0.8250(MLP method) to 0.8856(ASMLP method). Besides, a 30% improvement of mean absolute error between MLP(0.1798 on average) and ASMLP(0.1267 on average) was achieved. For predicting 2s ahead of response time, correlation coefficient was improved from 0.61415 to 0.7098.Mean absolute error of MLP method(0.3111 on average) was reduced by 35% using ASMLP method(0.2020 on average). Conclusion: The preliminary results

  1. Effects of training strategies implemented in a complex videogame on functional connectivity of attentional networks.

    Voss, Michelle W; Prakash, Ruchika Shaurya; Erickson, Kirk I; Boot, Walter R; Basak, Chandramallika; Neider, Mark B; Simons, Daniel J; Fabiani, Monica; Gratton, Gabriele; Kramer, Arthur F

    2012-01-02

    We used the Space Fortress videogame, originally developed by cognitive psychologists to study skill acquisition, as a platform to examine learning-induced plasticity of interacting brain networks. Novice videogame players learned Space Fortress using one of two training strategies: (a) focus on all aspects of the game during learning (fixed priority), or (b) focus on improving separate game components in the context of the whole game (variable priority). Participants were scanned during game play using functional magnetic resonance imaging (fMRI), both before and after 20 h of training. As expected, variable priority training enhanced learning, particularly for individuals who initially performed poorly. Functional connectivity analysis revealed changes in brain network interaction reflective of more flexible skill learning and retrieval with variable priority training, compared to procedural learning and skill implementation with fixed priority training. These results provide the first evidence for differences in the interaction of large-scale brain networks when learning with different training strategies. Our approach and findings also provide a foundation for exploring the brain plasticity involved in transfer of trained abilities to novel real-world tasks such as driving, sport, or neurorehabilitation. Copyright © 2011 Elsevier Inc. All rights reserved.

  2. Contemplative/emotion training reduces negative emotional behavior and promotes prosocial responses.

    Kemeny, Margaret E; Foltz, Carol; Cavanagh, James F; Cullen, Margaret; Giese-Davis, Janine; Jennings, Patricia; Rosenberg, Erika L; Gillath, Omri; Shaver, Phillip R; Wallace, B Alan; Ekman, Paul

    2012-04-01

    Contemplative practices are believed to alleviate psychological problems, cultivate prosocial behavior and promote self-awareness. In addition, psychological science has developed tools and models for understanding the mind and promoting well-being. Additional effort is needed to combine frameworks and techniques from these traditions to improve emotional experience and socioemotional behavior. An 8-week intensive (42 hr) meditation/emotion regulation training intervention was designed by experts in contemplative traditions and emotion science to reduce "destructive enactment of emotions" and enhance prosocial responses. Participants were 82 healthy female schoolteachers who were randomly assigned to a training group or a wait-list control group, and assessed preassessment, postassessment, and 5 months after training completion. Assessments included self-reports and experimental tasks to capture changes in emotional behavior. The training group reported reduced trait negative affect, rumination, depression, and anxiety, and increased trait positive affect and mindfulness compared to the control group. On a series of behavioral tasks, the training increased recognition of emotions in others (Micro-Expression Training Tool), protected trainees from some of the psychophysiological effects of an experimental threat to self (Trier Social Stress Test; TSST), appeared to activate cognitive networks associated with compassion (lexical decision procedure), and affected hostile behavior in the Marital Interaction Task. Most effects at postassessment that were examined at follow-up were maintained (excluding positive affect, TSST rumination, and respiratory sinus arrhythmia recovery). Findings suggest that increased awareness of mental processes can influence emotional behavior, and they support the benefit of integrating contemplative theories/practices with psychological models and methods of emotion regulation. (PsycINFO Database Record (c) 2012 APA, all rights reserved).

  3. Characterizing root response phenotypes by neural network analysis

    Hatzig, Sarah V.; Schiessl, Sarah; Stahl, Andreas; Snowdon, Rod J.

    2015-01-01

    Roots play an immediate role as the interface for water acquisition. To improve sustainability in low-water environments, breeders of major crops must therefore pay closer attention to advantageous root phenotypes; however, the complexity of root architecture in response to stress can be difficult to quantify. Here, the Sholl method, an established technique from neurobiology used for the characterization of neural network anatomy, was adapted to more adequately describe root responses to osm...

  4. Local and global responses in complex gene regulation networks

    Tsuchiya, Masa; Selvarajoo, Kumar; Piras, Vincent; Tomita, Masaru; Giuliani, Alessandro

    2009-04-01

    An exacerbated sensitivity to apparently minor stimuli and a general resilience of the entire system stay together side-by-side in biological systems. This apparent paradox can be explained by the consideration of biological systems as very strongly interconnected network systems. Some nodes of these networks, thanks to their peculiar location in the network architecture, are responsible for the sensitivity aspects, while the large degree of interconnection is at the basis of the resilience properties of the system. One relevant feature of the high degree of connectivity of gene regulation networks is the emergence of collective ordered phenomena influencing the entire genome and not only a specific portion of transcripts. The great majority of existing gene regulation models give the impression of purely local ‘hard-wired’ mechanisms disregarding the emergence of global ordered behavior encompassing thousands of genes while the general, genome wide, aspects are less known. Here we address, on a data analysis perspective, the discrimination between local and global scale regulations, this goal was achieved by means of the examination of two biological systems: innate immune response in macrophages and oscillating growth dynamics in yeast. Our aim was to reconcile the ‘hard-wired’ local view of gene regulation with a global continuous and scalable one borrowed from statistical physics. This reconciliation is based on the network paradigm in which the local ‘hard-wired’ activities correspond to the activation of specific crucial nodes in the regulation network, while the scalable continuous responses can be equated to the collective oscillations of the network after a perturbation.

  5. Asia-Pacific Research and Training Network on Trade (ARTNET ...

    During Phase II, ARTNET will continue its training and capacity building efforts, focusing on trade facilitation, preferential trade agreements (PTAs) and other trade agreements. Given the complexity of the trade and investment environment in the region, ARTNET will explore the interaction between trade, investment, ...

  6. Transient response of nonlinear polymer networks: A kinetic theory

    Vernerey, Franck J.

    2018-06-01

    Dynamic networks are found in a majority of natural materials, but also in engineering materials, such as entangled polymers and physically cross-linked gels. Owing to their transient bond dynamics, these networks display a rich class of behaviors, from elasticity, rheology, self-healing, or growth. Although classical theories in rheology and mechanics have enabled us to characterize these materials, there is still a gap in our understanding on how individuals (i.e., the mechanics of each building blocks and its connection with others) affect the emerging response of the network. In this work, we introduce an alternative way to think about these networks from a statistical point of view. More specifically, a network is seen as a collection of individual polymer chains connected by weak bonds that can associate and dissociate over time. From the knowledge of these individual chains (elasticity, transient attachment, and detachment events), we construct a statistical description of the population and derive an evolution equation of their distribution based on applied deformation and their local interactions. We specifically concentrate on nonlinear elastic response that follows from the strain stiffening response of individual chains of finite size. Upon appropriate averaging operations and using a mean field approximation, we show that the distribution can be replaced by a so-called chain distribution tensor that is used to determine important macroscopic measures such as stress, energy storage and dissipation in the network. Prediction of the kinetic theory are then explored against known experimental measurement of polymer responses under uniaxial loading. It is found that even under the simplest assumptions of force-independent chain kinetics, the model is able to reproduce complex time-dependent behaviors of rubber and self-healing supramolecular polymers.

  7. Pilot program: NRC severe reactor accident incident response training manual: US Nuclear Regulatory Commission response

    Sakenas, C.A.; McKenna, T.J.; Perkins, K.; Miller, C.W.; Hively, L.M.; Sharpe, R.W.; Giitter, J.G.; Watkins, R.M.

    1987-02-01

    This pilot training manual has been written to fill the need for a general text on NRC response to reactor accidents. The manual is intended to be the foundation for a course for all NRC response personnel. US Nuclear Regulatory Commission Response is the fifth in a series of volumes that collectively summarize the US Nuclear Regulatory Commission (NRC) emergency response during severe power reactor accidents and provide necessary background information. This volume describes NRC response modes, organizations, and official positions; roles of other federal agencies are also described briefly. Each volume serves, respectively, as the text for a course of instruction in a series of courses for NRC response personnel. These materials do not provide guidance or license requirements for NRC licensees. Each volume is accompanied by an appendix of slides that can be used to present this material. The slides are called out in the text

  8. Effects of Cognitive Training on Resting-State Functional Connectivity of Default Mode, Salience, and Central Executive Networks.

    Cao, Weifang; Cao, Xinyi; Hou, Changyue; Li, Ting; Cheng, Yan; Jiang, Lijuan; Luo, Cheng; Li, Chunbo; Yao, Dezhong

    2016-01-01

    Neuroimaging studies have documented that aging can disrupt certain higher cognitive systems such as the default mode network (DMN), the salience network and the central executive network (CEN). The effect of cognitive training on higher cognitive systems remains unclear. This study used a 1-year longitudinal design to explore the cognitive training effect on three higher cognitive networks in healthy older adults. The community-living healthy older adults were divided into two groups: the multi-domain cognitive training group (24 sessions of cognitive training over a 3-months period) and the wait-list control group. All subjects underwent cognitive measurements and resting-state functional magnetic resonance imaging scanning at baseline and at 1 year after the training ended. We examined training-related changes in functional connectivity (FC) within and between three networks. Compared with the baseline, we observed maintained or increased FC within all three networks after training. The scans after training also showed maintained anti-correlation of FC between the DMN and CEN compared to the baseline. These findings demonstrated that cognitive training maintained or improved the functional integration within networks and the coupling between the DMN and CEN in older adults. Our findings suggested that multi-domain cognitive training can mitigate the aging-related dysfunction of higher cognitive networks.

  9. Training Convolutional Neural Networks for Translational Invariance on SAR ATR

    Malmgren-Hansen, David; Engholm, Rasmus; Østergaard Pedersen, Morten

    2016-01-01

    In this paper we present a comparison of the robustness of Convolutional Neural Networks (CNN) to other classifiers in the presence of uncertainty of the objects localization in SAR image. We present a framework for simulating simple SAR images, translating the object of interest systematically...

  10. A simulator-based nuclear reactor emergency response training exercise.

    Waller, Edward; Bereznai, George; Shaw, John; Chaput, Joseph; Lafortune, Jean-Francois

    Training offsite emergency response personnel basic awareness of onsite control room operations during nuclear power plant emergency conditions was the primary objective of a week-long workshop conducted on a CANDU® virtual nuclear reactor simulator available at the University of Ontario Institute of Technology, Oshawa, Canada. The workshop was designed to examine both normal and abnormal reactor operating conditions, and to observe the conditions in the control room that may have impact on the subsequent offsite emergency response. The workshop was attended by participants from a number of countries encompassing diverse job functions related to nuclear emergency response. Objectives of the workshop were to provide opportunities for participants to act in the roles of control room personnel under different reactor operating scenarios, providing a unique experience for participants to interact with the simulator in real-time, and providing increased awareness of control room operations during accident conditions. The ability to "pause" the simulator during exercises allowed the instructors to evaluate and critique the performance of participants, and to provide context with respect to potential offsite emergency actions. Feedback from the participants highlighted (i) advantages of observing and participating "hands-on" with operational exercises, (ii) their general unfamiliarity with control room operational procedures and arrangements prior to the workshop, (iii) awareness of the vast quantity of detailed control room procedures for both normal and transient conditions, and (iv) appreciation of the increased workload for the operators in the control room during a transient from normal operations. Based upon participant feedback, it was determined that the objectives of the training had been met, and that future workshops should be conducted.

  11. Can you hear me now? Musical training shapes functional brain networks for selective auditory attention and hearing speech in noise

    Dana L Strait

    2011-06-01

    Full Text Available Even in the quietest of rooms, our senses are perpetually inundated by a barrage of sounds, requiring the auditory system to adapt to a variety of listening conditions in order to extract signals of interest (e.g., one speaker’s voice amidst others. Brain networks that promote selective attention are thought to sharpen the neural encoding of a target signal, suppressing competing sounds and enhancing perceptual performance. Here, we ask: does musical training benefit cortical mechanisms that underlie selective attention to speech? To answer this question, we assessed the impact of selective auditory attention on cortical auditory-evoked response variability in musicians and nonmusicians. Outcomes indicate strengthened brain networks for selective auditory attention in musicians in that musicians but not nonmusicians demonstrate decreased prefrontal response variability with auditory attention. Results are interpreted in the context of previous work from our laboratory documenting perceptual and subcortical advantages in musicians for the hearing and neural encoding of speech in background noise. Musicians’ neural proficiency for selectively engaging and sustaining auditory attention to language indicates a potential benefit of music for auditory training. Given the importance of auditory attention for the development of language-related skills, musical training may aid in the prevention, habilitation and remediation of children with a wide range of attention-based language and learning impairments.

  12. Implementation and Outcomes of a Collaborative Multi-Center Network Aimed at Web-Based Cognitive Training - COGWEB Network.

    Tedim Cruz, Vítor; Pais, Joana; Ruano, Luis; Mateus, Cátia; Colunas, Márcio; Alves, Ivânia; Barreto, Rui; Conde, Eduardo; Sousa, Andreia; Araújo, Isabel; Bento, Virgílio; Coutinho, Paula; Rocha, Nelson

    2014-01-01

    Cognitive care for the most prevalent neurologic and psychiatric conditions will only improve through the implementation of new sustainable approaches. Innovative cognitive training methodologies and collaborative professional networks are necessary evolutions in the mental health sector. The objective of the study was to describe the implementation process and early outcomes of a nationwide multi-organizational network supported on a Web-based cognitive training system (COGWEB). The setting for network implementation was the Portuguese mental health system and the hospital-, academic-, community-based institutions and professionals providing cognitive training. The network started in August 2012, with 16 centers, and was monitored until September 2013 (inclusions were open). After onsite training, all were allowed to use COGWEB in their clinical or research activities. For supervision and maintenance were implemented newsletters, questionnaires, visits and webinars. The following outcomes were prospectively measured: (1) number, (2) type, (3) time to start, and (4) activity state of centers; age, gender, level of education, and medical diagnosis of patients enrolled. The network included 68 professionals from 41 centers, (33/41) 80% clinical, (8/41) 19% nonclinical. A total of 298 patients received cognitive training; 45.3% (n=135) female, mean age 54.4 years (SD 18.7), mean educational level 9.8 years (SD 4.8). The number enrolled each month increased significantly (r=0.6; P=.031). At 12 months, 205 remained on treatment. The major causes of cognitive impairment were: (1) neurodegenerative (115/298, 38.6%), (2) structural brain lesions (63/298, 21.1%), (3) autoimmune (40/298, 13.4%), (4) schizophrenia (30/298, 10.1%), and (5) others (50/298, 16.8%). The comparison of the patient profiles, promoter versus all other clinical centers, showed significant increases in the diversity of causes and spectrums of ages and education. Over its first year, there was a major

  13. Brain network involved in visual processing of movement stimuli used in upper limb robotic training: an fMRI study.

    Nocchi, Federico; Gazzellini, Simone; Grisolia, Carmela; Petrarca, Maurizio; Cannatà, Vittorio; Cappa, Paolo; D'Alessio, Tommaso; Castelli, Enrico

    2012-07-24

    The potential of robot-mediated therapy and virtual reality in neurorehabilitation is becoming of increasing importance. However, there is limited information, using neuroimaging, on the neural networks involved in training with these technologies. This study was intended to detect the brain network involved in the visual processing of movement during robotic training. The main aim was to investigate the existence of a common cerebral network able to assimilate biological (human upper limb) and non-biological (abstract object) movements, hence testing the suitability of the visual non-biological feedback provided by the InMotion2 Robot. A visual functional Magnetic Resonance Imaging (fMRI) task was administered to 22 healthy subjects. The task required observation and retrieval of motor gestures and of the visual feedback used in robotic training. Functional activations of both biological and non-biological movements were examined to identify areas activated in both conditions, along with differential activity in upper limb vs. abstract object trials. Control of response was also tested by administering trials with congruent and incongruent reaching movements. The observation of upper limb and abstract object movements elicited similar patterns of activations according to a caudo-rostral pathway for the visual processing of movements (including specific areas of the occipital, temporal, parietal, and frontal lobes). Similarly, overlapping activations were found for the subsequent retrieval of the observed movement. Furthermore, activations of frontal cortical areas were associated with congruent trials more than with the incongruent ones. This study identified the neural pathway associated with visual processing of movement stimuli used in upper limb robot-mediated training and investigated the brain's ability to assimilate abstract object movements with human motor gestures. In both conditions, activations were elicited in cerebral areas involved in visual

  14. Brain network involved in visual processing of movement stimuli used in upper limb robotic training: an fMRI study

    Nocchi Federico

    2012-07-01

    Full Text Available Abstract Background The potential of robot-mediated therapy and virtual reality in neurorehabilitation is becoming of increasing importance. However, there is limited information, using neuroimaging, on the neural networks involved in training with these technologies. This study was intended to detect the brain network involved in the visual processing of movement during robotic training. The main aim was to investigate the existence of a common cerebral network able to assimilate biological (human upper limb and non-biological (abstract object movements, hence testing the suitability of the visual non-biological feedback provided by the InMotion2 Robot. Methods A visual functional Magnetic Resonance Imaging (fMRI task was administered to 22 healthy subjects. The task required observation and retrieval of motor gestures and of the visual feedback used in robotic training. Functional activations of both biological and non-biological movements were examined to identify areas activated in both conditions, along with differential activity in upper limb vs. abstract object trials. Control of response was also tested by administering trials with congruent and incongruent reaching movements. Results The observation of upper limb and abstract object movements elicited similar patterns of activations according to a caudo-rostral pathway for the visual processing of movements (including specific areas of the occipital, temporal, parietal, and frontal lobes. Similarly, overlapping activations were found for the subsequent retrieval of the observed movement. Furthermore, activations of frontal cortical areas were associated with congruent trials more than with the incongruent ones. Conclusions This study identified the neural pathway associated with visual processing of movement stimuli used in upper limb robot-mediated training and investigated the brain’s ability to assimilate abstract object movements with human motor gestures. In both conditions

  15. Gaming industry employees' responses to responsible gambling training: a public health imperative.

    LaPlante, Debi A; Gray, Heather M; LaBrie, Richard A; Kleschinsky, John H; Shaffer, Howard J

    2012-06-01

    Gaming industry employees work in settings that create personal health risks. They also have direct contact with customers who might engage in multiple risky activities (e.g., drinking, smoking, and gambling) and might need to facilitate help-seeking by patrons or co-workers who experience problems. Consequently, the empirical examination of the processes and procedures designed to prepare employees for such complex situations is a public health imperative. In the current study we describe an evaluation of the Casino, Inc. Play Responsibly responsible gaming program. We surveyed 217 employees prior to and 1 month after (n = 116) they completed a multimedia driven responsible gambling training program. We observed that employees improved their knowledge of responsible gambling concepts from baseline to follow-up. The Play Responsibly program was more successful in providing new knowledge than it was in correcting mistaken beliefs that existed prior to training. We conclude, generally, that Play Responsibly is associated with increases in employees' responsible gambling knowledge.

  16. Pap-smear Classification Using Efficient Second Order Neural Network Training Algorithms

    Ampazis, Nikolaos; Dounias, George; Jantzen, Jan

    2004-01-01

    In this paper we make use of two highly efficient second order neural network training algorithms, namely the LMAM (Levenberg-Marquardt with Adaptive Momentum) and OLMAM (Optimized Levenberg-Marquardt with Adaptive Momentum), for the construction of an efficient pap-smear test classifier. The alg......In this paper we make use of two highly efficient second order neural network training algorithms, namely the LMAM (Levenberg-Marquardt with Adaptive Momentum) and OLMAM (Optimized Levenberg-Marquardt with Adaptive Momentum), for the construction of an efficient pap-smear test classifier...

  17. 33 CFR Appendix D to Part 154 - Training Elements for Oil Spill Response Plans

    2010-07-01

    ... Appendix D to Part 154—Training Elements for Oil Spill Response Plans 1. General 1.1The portion of the plan dealing with training is one of the key elements of a response plan. This concept is clearly expressed by... that the plans often do not provide sufficient information in the training section of the plan for...

  18. Optimal Path Choice in Railway Passenger Travel Network Based on Residual Train Capacity

    Fei Dou

    2014-01-01

    Full Text Available Passenger’s optimal path choice is one of the prominent research topics in the field of railway passenger transport organization. More and more different train types are available, increasing path choices from departure to destination for travelers are unstoppable. However, travelers cannot avoid being confused when they hope to choose a perfect travel plan based on various travel time and cost constraints before departure. In this study, railway passenger travel network is constructed based on train timetable. Both the generalized cost function we developed and the residual train capacity are considered to be the foundation of path searching procedure. The railway passenger travel network topology is analyzed based on residual train capacity. Considering the total travel time, the total travel cost, and the total number of passengers, we propose an optimal path searching algorithm based on residual train capacity in railway passenger travel network. Finally, the rationale of the railway passenger travel network and the optimal path generation algorithm are verified positively by case study.

  19. The Effects of Long-term Abacus Training on Topological Properties of Brain Functional Networks.

    Weng, Jian; Xie, Ye; Wang, Chunjie; Chen, Feiyan

    2017-08-18

    Previous studies in the field of abacus-based mental calculation (AMC) training have shown that this training has the potential to enhance a wide variety of cognitive abilities. It can also generate specific changes in brain structure and function. However, there is lack of studies investigating the impact of AMC training on the characteristics of brain networks. In this study, utilizing graph-based network analysis, we compared topological properties of brain functional networks between an AMC group and a matched control group. Relative to the control group, the AMC group exhibited higher nodal degrees in bilateral calcarine sulcus and increased local efficiency in bilateral superior occipital gyrus and right cuneus. The AMC group also showed higher nodal local efficiency in right fusiform gyrus, which was associated with better math ability. However, no relationship was significant in the control group. These findings provide evidence that long-term AMC training may improve information processing efficiency in visual-spatial related regions, which extend our understanding of training plasticity at the brain network level.

  20. Online Sequence Training of Recurrent Neural Networks with Connectionist Temporal Classification

    Hwang, Kyuyeon; Sung, Wonyong

    2015-01-01

    Connectionist temporal classification (CTC) based supervised sequence training of recurrent neural networks (RNNs) has shown great success in many machine learning areas including end-to-end speech and handwritten character recognition. For the CTC training, however, it is required to unroll (or unfold) the RNN by the length of an input sequence. This unrolling requires a lot of memory and hinders a small footprint implementation of online learning or adaptation. Furthermore, the length of tr...

  1. Engine cylinder pressure reconstruction using crank kinematics and recurrently-trained neural networks

    Bennett, C.; Dunne, J. F.; Trimby, S.; Richardson, D.

    2017-02-01

    A recurrent non-linear autoregressive with exogenous input (NARX) neural network is proposed, and a suitable fully-recurrent training methodology is adapted and tuned, for reconstructing cylinder pressure in multi-cylinder IC engines using measured crank kinematics. This type of indirect sensing is important for cost effective closed-loop combustion control and for On-Board Diagnostics. The challenge addressed is to accurately predict cylinder pressure traces within the cycle under generalisation conditions: i.e. using data not previously seen by the network during training. This involves direct construction and calibration of a suitable inverse crank dynamic model, which owing to singular behaviour at top-dead-centre (TDC), has proved difficult via physical model construction, calibration, and inversion. The NARX architecture is specialised and adapted to cylinder pressure reconstruction, using a fully-recurrent training methodology which is needed because the alternatives are too slow and unreliable for practical network training on production engines. The fully-recurrent Robust Adaptive Gradient Descent (RAGD) algorithm, is tuned initially using synthesised crank kinematics, and then tested on real engine data to assess the reconstruction capability. Real data is obtained from a 1.125 l, 3-cylinder, in-line, direct injection spark ignition (DISI) engine involving synchronised measurements of crank kinematics and cylinder pressure across a range of steady-state speed and load conditions. The paper shows that a RAGD-trained NARX network using both crank velocity and crank acceleration as input information, provides fast and robust training. By using the optimum epoch identified during RAGD training, acceptably accurate cylinder pressures, and especially accurate location-of-peak-pressure, can be reconstructed robustly under generalisation conditions, making it the most practical NARX configuration and recurrent training methodology for use on production engines.

  2. Neural network connectivity and response latency modelled by stochastic processes

    Tamborrino, Massimiliano

    is connected to thousands of other neurons. The rst question is: how to model neural networks through stochastic processes? A multivariate Ornstein-Uhlenbeck process, obtained as a diffusion approximation of a jump process, is the proposed answer. Obviously, dependencies between neurons imply dependencies......Stochastic processes and their rst passage times have been widely used to describe the membrane potential dynamics of single neurons and to reproduce neuronal spikes, respectively.However, cerebral cortex in human brains is estimated to contain 10-20 billions of neurons and each of them...... between their spike times. Therefore, the second question is: how to detect neural network connectivity from simultaneously recorded spike trains? Answering this question corresponds to investigate the joint distribution of sequences of rst passage times. A non-parametric method based on copulas...

  3. Artificial neural network classification using a minimal training set - Comparison to conventional supervised classification

    Hepner, George F.; Logan, Thomas; Ritter, Niles; Bryant, Nevin

    1990-01-01

    Recent research has shown an artificial neural network (ANN) to be capable of pattern recognition and the classification of image data. This paper examines the potential for the application of neural network computing to satellite image processing. A second objective is to provide a preliminary comparison and ANN classification. An artificial neural network can be trained to do land-cover classification of satellite imagery using selected sites representative of each class in a manner similar to conventional supervised classification. One of the major problems associated with recognition and classifications of pattern from remotely sensed data is the time and cost of developing a set of training sites. This reseach compares the use of an ANN back propagation classification procedure with a conventional supervised maximum likelihood classification procedure using a minimal training set. When using a minimal training set, the neural network is able to provide a land-cover classification superior to the classification derived from the conventional classification procedure. This research is the foundation for developing application parameters for further prototyping of software and hardware implementations for artificial neural networks in satellite image and geographic information processing.

  4. Identification of Abnormal System Noise Temperature Patterns in Deep Space Network Antennas Using Neural Network Trained Fuzzy Logic

    Lu, Thomas; Pham, Timothy; Liao, Jason

    2011-01-01

    This paper presents the development of a fuzzy logic function trained by an artificial neural network to classify the system noise temperature (SNT) of antennas in the NASA Deep Space Network (DSN). The SNT data were classified into normal, marginal, and abnormal classes. The irregular SNT pattern was further correlated with link margin and weather data. A reasonably good correlation is detected among high SNT, low link margin and the effect of bad weather; however we also saw some unexpected non-correlations which merit further study in the future.

  5. Transfer Learning for Video Recognition with Scarce Training Data for Deep Convolutional Neural Network

    Su, Yu-Chuan; Chiu, Tzu-Hsuan; Yeh, Chun-Yen; Huang, Hsin-Fu; Hsu, Winston H.

    2014-01-01

    Unconstrained video recognition and Deep Convolution Network (DCN) are two active topics in computer vision recently. In this work, we apply DCNs as frame-based recognizers for video recognition. Our preliminary studies, however, show that video corpora with complete ground truth are usually not large and diverse enough to learn a robust model. The networks trained directly on the video data set suffer from significant overfitting and have poor recognition rate on the test set. The same lack-...

  6. Training the Recurrent neural network by the Fuzzy Min-Max algorithm for fault prediction

    Zemouri, Ryad; Racoceanu, Daniel; Zerhouni, Noureddine; Minca, Eugenia; Filip, Florin

    2009-01-01

    In this paper, we present a training technique of a Recurrent Radial Basis Function neural network for fault prediction. We use the Fuzzy Min-Max technique to initialize the k-center of the RRBF neural network. The k-means algorithm is then applied to calculate the centers that minimize the mean square error of the prediction task. The performances of the k-means algorithm are then boosted by the Fuzzy Min-Max technique.

  7. A Control Simulation Method of High-Speed Trains on Railway Network with Irregular Influence

    Yang Lixing; Li Xiang; Li Keping

    2011-01-01

    Based on the discrete time method, an effective movement control model is designed for a group of highspeed trains on a rail network. The purpose of the model is to investigate the specific traffic characteristics of high-speed trains under the interruption of stochastic irregular events. In the model, the high-speed rail traffic system is supposed to be equipped with the moving-block signalling system to guarantee maximum traversing capacity of the railway. To keep the safety of trains' movements, some operational strategies are proposed to control the movements of trains in the model, including traction operation, braking operation, and entering-station operation. The numerical simulations show that the designed model can well describe the movements of high-speed trains on the rail network. The research results can provide the useful information not only for investigating the propagation features of relevant delays under the irregular disturbance but also for rerouting and rescheduling trains on the rail network. (general)

  8. The corticospinal responses of metronome-paced, but not self-paced strength training are similar to motor skill training.

    Leung, Michael; Rantalainen, Timo; Teo, Wei-Peng; Kidgell, Dawson

    2017-12-01

    The corticospinal responses to skill training may be different to strength training, depending on how the strength training is performed. It was hypothesised that the corticospinal responses would not be different following skill training and metronome-paced strength training (MPST), but would differ when compared with self-paced strength training (SPST). Corticospinal excitability, short-interval intra-cortical inhibition (SICI) and strength and tracking error were measured at baseline and 2 and 4 weeks. Participants (n = 44) were randomly allocated to visuomotor tracking, MPST, SPST or a control group. MPST increased strength by 7 and 18%, whilst SPST increased strength by 12 and 26% following 2 and 4 weeks of strength training. There were no changes in strength following skill training. Skill training reduced tracking error by 47 and 58% at 2 and 4 weeks. There were no changes in tracking error following SPST; however, tracking error reduced by 24% following 4 weeks of MPST. Corticospinal excitability increased by 40% following MPST and by 29% following skill training. There was no change in corticospinal excitability following 4 weeks of SPST. Importantly, the magnitude of change between skill training and MPST was not different. SICI decreased by 41 and 61% following 2 and 4 weeks of MPST, whilst SICI decreased by 41 and 33% following 2 and 4 weeks of skill training. Again, SPST had no effect on SICI at 2 and 4 weeks. There was no difference in the magnitude of SICI reduction between skill training and MPST. This study adds new knowledge regarding the corticospinal responses to skill and MPST, showing they are similar but different when compared with SPST.

  9. Interaction of multiple networks modulated by the working memory training based on real-time fMRI

    Shen, Jiahui; Zhang, Gaoyan; Zhu, Chaozhe; Yao, Li; Zhao, Xiaojie

    2015-03-01

    Neuroimaging studies of working memory training have identified the alteration of brain activity as well as the regional interactions within the functional networks such as central executive network (CEN) and default mode network (DMN). However, how the interaction within and between these multiple networks is modulated by the training remains unclear. In this paper, we examined the interaction of three training-induced brain networks during working memory training based on real-time functional magnetic resonance imaging (rtfMRI). Thirty subjects assigned to the experimental and control group respectively participated in two times training separated by seven days. Three networks including silence network (SN), CEN and DMN were identified by the training data with the calculated function connections within each network. Structural equation modeling (SEM) approach was used to construct the directional connectivity patterns. The results showed that the causal influences from the percent signal changes of target ROI to the SN were positively changed in both two groups, as well as the causal influence from the SN to CEN was positively changed in experimental group but negatively changed in control group from the SN to DMN. Further correlation analysis of the changes in each network with the behavioral improvements showed that the changes in SN were stronger positively correlated with the behavioral improvement of letter memory task. These findings indicated that the SN was not only a switch between the target ROI and the other networks in the feedback training but also an essential factor to the behavioral improvement.

  10. On the use of harmony search algorithm in the training of wavelet neural networks

    Lai, Kee Huong; Zainuddin, Zarita; Ong, Pauline

    2015-10-01

    Wavelet neural networks (WNNs) are a class of feedforward neural networks that have been used in a wide range of industrial and engineering applications to model the complex relationships between the given inputs and outputs. The training of WNNs involves the configuration of the weight values between neurons. The backpropagation training algorithm, which is a gradient-descent method, can be used for this training purpose. Nonetheless, the solutions found by this algorithm often get trapped at local minima. In this paper, a harmony search-based algorithm is proposed for the training of WNNs. The training of WNNs, thus can be formulated as a continuous optimization problem, where the objective is to maximize the overall classification accuracy. Each candidate solution proposed by the harmony search algorithm represents a specific WNN architecture. In order to speed up the training process, the solution space is divided into disjoint partitions during the random initialization step of harmony search algorithm. The proposed training algorithm is tested onthree benchmark problems from the UCI machine learning repository, as well as one real life application, namely, the classification of electroencephalography signals in the task of epileptic seizure detection. The results obtained show that the proposed algorithm outperforms the traditional harmony search algorithm in terms of overall classification accuracy.

  11. Convolutional neural networks based on augmented training samples for synthetic aperture radar target recognition

    Yan, Yue

    2018-03-01

    A synthetic aperture radar (SAR) automatic target recognition (ATR) method based on the convolutional neural networks (CNN) trained by augmented training samples is proposed. To enhance the robustness of CNN to various extended operating conditions (EOCs), the original training images are used to generate the noisy samples at different signal-to-noise ratios (SNRs), multiresolution representations, and partially occluded images. Then, the generated images together with the original ones are used to train a designed CNN for target recognition. The augmented training samples can contrapuntally improve the robustness of the trained CNN to the covered EOCs, i.e., the noise corruption, resolution variance, and partial occlusion. Moreover, the significantly larger training set effectively enhances the representation capability for other conditions, e.g., the standard operating condition (SOC), as well as the stability of the network. Therefore, better performance can be achieved by the proposed method for SAR ATR. For experimental evaluation, extensive experiments are conducted on the Moving and Stationary Target Acquisition and Recognition dataset under SOC and several typical EOCs.

  12. A Fast C++ Implementation of Neural Network Backpropagation Training Algorithm: Application to Bayesian Optimal Image Demosaicing

    Yi-Qing Wang

    2015-09-01

    Full Text Available Recent years have seen a surge of interest in multilayer neural networks fueled by their successful applications in numerous image processing and computer vision tasks. In this article, we describe a C++ implementation of the stochastic gradient descent to train a multilayer neural network, where a fast and accurate acceleration of tanh(· is achieved with linear interpolation. As an example of application, we present a neural network able to deliver state-of-the-art performance in image demosaicing.

  13. Establishment of Oversea HRD Network and Operation of International Nuclear Education/Training Program

    Lee, E. J.; Min, B. J.; Han, K. W.

    2008-02-01

    The project deals with establishment of international network for human resources and the development of international nuclear education and training programs. The primary result is the establishment of KAERI International Nuclear R and D Academy as a new activity on cooperation for human resource development and building network. For this purpose, KAERI concluded the MOU with Vietnamese Universities and selected 3 students to provide Master and Ph. D. Courses in 2008. KAERI also held the 3rd World Nuclear University Summer Institute, in which some 150 international nuclear professionals attended for 6 weeks. Also, as part of regional networking, the Asian Network for Education in Nuclear Technology (ANENT) was promoted through development of a cyber platform and accomplishment the first IAEA e-training course. There were 3 kind of development activities for the international cooperation of human resources development. Firstly, the project provided training courses on nuclear energy development for the Egyptian Nuclear personnel under the bilateral cooperation. Secondly, the project published the English textbook and its lecture materials on introduction to nuclear engineering and fundamentals on OPR 1000 system technology. Lastly, the project developed a new KOICA training course on research reactor and radioisotope application technology to expand the KOICA sponsorship from 2008. The international nuclear education/training program had offered 15 courses to 314 people from 52 countries. In parallel, the project developed 11 kinds of lecturer materials and also developed 29 kinds of cyber lecturer materials. The operation of the International Nuclear Training and Education Center (INTEC) has contributed remarkably not only to the effective implementation of education/training activities of this project, but also to the promotion of other domestic and international activities of KAERI and other organizations

  14. Establishment of Oversea HRD Network and Operation of International Nuclear Education/Training Program

    Lee, E. J.; Min, B. J.; Han, K. W. (and others)

    2008-02-15

    The project deals with establishment of international network for human resources and the development of international nuclear education and training programs. The primary result is the establishment of KAERI International Nuclear R and D Academy as a new activity on cooperation for human resource development and building network. For this purpose, KAERI concluded the MOU with Vietnamese Universities and selected 3 students to provide Master and Ph. D. Courses in 2008. KAERI also held the 3rd World Nuclear University Summer Institute, in which some 150 international nuclear professionals attended for 6 weeks. Also, as part of regional networking, the Asian Network for Education in Nuclear Technology (ANENT) was promoted through development of a cyber platform and accomplishment the first IAEA e-training course. There were 3 kind of development activities for the international cooperation of human resources development. Firstly, the project provided training courses on nuclear energy development for the Egyptian Nuclear personnel under the bilateral cooperation. Secondly, the project published the English textbook and its lecture materials on introduction to nuclear engineering and fundamentals on OPR 1000 system technology. Lastly, the project developed a new KOICA training course on research reactor and radioisotope application technology to expand the KOICA sponsorship from 2008. The international nuclear education/training program had offered 15 courses to 314 people from 52 countries. In parallel, the project developed 11 kinds of lecturer materials and also developed 29 kinds of cyber lecturer materials. The operation of the International Nuclear Training and Education Center (INTEC) has contributed remarkably not only to the effective implementation of education/training activities of this project, but also to the promotion of other domestic and international activities of KAERI and other organizations.

  15. The Evaluation on Data Mining Methods of Horizontal Bar Training Based on BP Neural Network

    Zhang Yanhui

    2015-01-01

    Full Text Available With the rapid development of science and technology, data analysis has become an indispensable part of people’s work and life. Horizontal bar training has multiple categories. It is an emphasis for the re-search of related workers that categories of the training and match should be reduced. The application of data mining methods is discussed based on the problem of reducing categories of horizontal bar training. The BP neural network is applied to the cluster analysis and the principal component analysis, which are used to evaluate horizontal bar training. Two kinds of data mining methods are analyzed from two aspects, namely the operational convenience of data mining and the rationality of results. It turns out that the principal component analysis is more suitable for data processing of horizontal bar training.

  16. EDA-EMERGE : An FP7 initial training network to equip the next generation of young scientists with the skills to address the complexity of environmental contamination with emerging pollutants

    Brack, Werner; Govender, Selvan; Schulze, Tobias; Krauss, Martin; Hu, Meng; Muz, Melis; Hollender, Juliane; Schirmer, Kristin; Schollee, Jennifer; Hidasi, Anita; Slobodnik, Jaroslav; Rabova, Zuzana; Ait-Aissa, Selim; Sonavane, Manoj; Carere, Mario; Lamoree, Marja; Leonards, Pim; Tufi, Sara; Ouyang, Xiyu; Schriks, Merijn; Thomas, Kevin; De Almeida, Ana Catarina; Froment, Jean; Hammers-Wirtz, Monika; Ahel, Marijan; Koprivica, Sanja; Hollert, Henner; Seiler, Thomas Benjamin; Di Paolo, Carolina; Tindall, Andrew; Spirhanzlova, Petra

    2013-01-01

    The initial training network consortium novel tools in effect-directed analysis to support the identification and monitoring of emerging toxicants on a European scale (EDA-EMERGE) was formed in response to the seventh EU framework program call to train a new generation of young scientists (13 PhD

  17. Southern State Radiological Transportation Emergency Response Training Course Summary

    1990-09-01

    The Southern States Energy Board (SSEB) is an interstate compact organization that serves 16 states and the commonwealth of Puerto Rico with information and analysis in energy and environmental matters. Nuclear waste management is a topic that has garnered considerable attention in the SSEB region in the last several years. Since 1985, SSEB has received support from the US Department of Energy for the regional analysis of high-level radioactive waste transportation issues. In the performance of its work in this area, SSEB formed the Advisory Committee on High-Level Radioactive Materials Transportation, which comprises representatives from impacted states and tribes. SSEB meets with the committee semi-annually to provide issue updates to members and to solicit their views on activities impacting their respective states. Among the waste transportation issues considered by SSEB and the committee are shipment routing, the impacts of monitored retrievable storage, state liability in the event of an accident and emergency preparedness and response. This document addresses the latter by describing the radiological emergency response training courses and programs of the southern states, as well as federal courses available outside the southern region

  18. Dynamical Response of Networks Under External Perturbations: Exact Results

    Chinellato, David D.; Epstein, Irving R.; Braha, Dan; Bar-Yam, Yaneer; de Aguiar, Marcus A. M.

    2015-04-01

    We give exact statistical distributions for the dynamic response of influence networks subjected to external perturbations. We consider networks whose nodes have two internal states labeled 0 and 1. We let nodes be frozen in state 0, in state 1, and the remaining nodes change by adopting the state of a connected node with a fixed probability per time step. The frozen nodes can be interpreted as external perturbations to the subnetwork of free nodes. Analytically extending and to be smaller than 1 enables modeling the case of weak coupling. We solve the dynamical equations exactly for fully connected networks, obtaining the equilibrium distribution, transition probabilities between any two states and the characteristic time to equilibration. Our exact results are excellent approximations for other topologies, including random, regular lattice, scale-free and small world networks, when the numbers of fixed nodes are adjusted to take account of the effect of topology on coupling to the environment. This model can describe a variety of complex systems, from magnetic spins to social networks to population genetics, and was recently applied as a framework for early warning signals for real-world self-organized economic market crises.

  19. Innovation in European Vocational Education and Training: Network Learning in England, Finland and Germany

    Heikkila, Eila

    2013-01-01

    This article presents a comparative study of innovation in vocational education and training (VET) in three innovative European countries: England, Finland and Germany. The focus is on innovation emerging from VET practitioners' (directors, teachers, project coordinators, etc.) participation in inter-organisational networks with local, regional,…

  20. Can surgical simulation be used to train detection and classification of neural networks?

    Zisimopoulos, Odysseas; Flouty, Evangello; Stacey, Mark; Muscroft, Sam; Giataganas, Petros; Nehme, Jean; Chow, Andre; Stoyanov, Danail

    2017-10-01

    Computer-assisted interventions (CAI) aim to increase the effectiveness, precision and repeatability of procedures to improve surgical outcomes. The presence and motion of surgical tools is a key information input for CAI surgical phase recognition algorithms. Vision-based tool detection and recognition approaches are an attractive solution and can be designed to take advantage of the powerful deep learning paradigm that is rapidly advancing image recognition and classification. The challenge for such algorithms is the availability and quality of labelled data used for training. In this Letter, surgical simulation is used to train tool detection and segmentation based on deep convolutional neural networks and generative adversarial networks. The authors experiment with two network architectures for image segmentation in tool classes commonly encountered during cataract surgery. A commercially-available simulator is used to create a simulated cataract dataset for training models prior to performing transfer learning on real surgical data. To the best of authors' knowledge, this is the first attempt to train deep learning models for surgical instrument detection on simulated data while demonstrating promising results to generalise on real data. Results indicate that simulated data does have some potential for training advanced classification methods for CAI systems.

  1. Training and development through the IAEA's global research network

    Benson, T.

    1988-01-01

    The Agency's research contract programme stimulates and co-ordinates the undertaking of research, in selected nuclear fields of interest, by scientists in IAEA Member States. Benefits of the research contract programme can be direct or indirect. Direct benefits include increased scientific knowledge in a specific field and case-by-case application of this knowledge. Indirect benefits include the training effects - what participants in the programme learn via work carried out under the contract or at regularly held RCMs. The educational effect of CRPs is substantial as many institutes, guided by Agency scientific staff, learn how to conduct research without assistance. Unanticipated spin-off benefits can also result from a CRP through information exchanges at RCMs that stimulate ideas for other research programmes or methods of research

  2. Pap-smear Classification Using Efficient Second Order Neural Network Training Algorithms

    Ampazis, Nikolaos; Dounias, George; Jantzen, Jan

    2004-01-01

    In this paper we make use of two highly efficient second order neural network training algorithms, namely the LMAM (Levenberg-Marquardt with Adaptive Momentum) and OLMAM (Optimized Levenberg-Marquardt with Adaptive Momentum), for the construction of an efficient pap-smear test classifier. The alg......In this paper we make use of two highly efficient second order neural network training algorithms, namely the LMAM (Levenberg-Marquardt with Adaptive Momentum) and OLMAM (Optimized Levenberg-Marquardt with Adaptive Momentum), for the construction of an efficient pap-smear test classifier....... The algorithms are methodologically similar, and are based on iterations of the form employed in the Levenberg-Marquardt (LM) method for non-linear least squares problems with the inclusion of an additional adaptive momentum term arising from the formulation of the training task as a constrained optimization...

  3. Nonlinear Robust Observer-Based Fault Detection for Networked Suspension Control System of Maglev Train

    Yun Li

    2013-01-01

    Full Text Available A fault detection approach based on nonlinear robust observer is designed for the networked suspension control system of Maglev train with random induced time delay. First, considering random bounded time-delay and external disturbance, the nonlinear model of the networked suspension control system is established. Then, a nonlinear robust observer is designed using the input of the suspension gap. And the estimate error is proved to be bounded with arbitrary precision by adopting an appropriate parameter. When sensor faults happen, the residual between the real states and the observer outputs indicates which kind of sensor failures occurs. Finally, simulation results using the actual parameters of CMS-04 maglev train indicate that the proposed method is effective for maglev train.

  4. ENETRAP II: European network of education and training in radiation protection, data base training

    Marco Arboli, M.; Llorente, C.; Coeck, M.

    2012-01-01

    Development and implementation of a European standard for high quality initial training and professional development continued in the R adiation Protection Expert-RPE and Radiation Protection Officer-RPO, also of a methodology for the mutual recognition of these professionals by making use of the available instruments of the European Union (GE).

  5. The responsiveness of training participation to tax deductability

    Leuven, E.; Oosterbeek, H.

    2006-01-01

    To stimulate investment in training by individuals, the Dutch tax system allows a deduction of direct training expenditures from taxable income. This paper investigates to what extent the resulting cost reduction encourages training investments. Two different identification strategies are used. The

  6. Relationships between music training, speech processing, and word learning: a network perspective.

    Elmer, Stefan; Jäncke, Lutz

    2018-03-15

    Numerous studies have documented the behavioral advantages conferred on professional musicians and children undergoing music training in processing speech sounds varying in the spectral and temporal dimensions. These beneficial effects have previously often been associated with local functional and structural changes in the auditory cortex (AC). However, this perspective is oversimplified, in that it does not take into account the intrinsic organization of the human brain, namely, neural networks and oscillatory dynamics. Therefore, we propose a new framework for extending these previous findings to a network perspective by integrating multimodal imaging, electrophysiology, and neural oscillations. In particular, we provide concrete examples of how functional and structural connectivity can be used to model simple neural circuits exerting a modulatory influence on AC activity. In addition, we describe how such a network approach can be used for better comprehending the beneficial effects of music training on more complex speech functions, such as word learning. © 2018 New York Academy of Sciences.

  7. Diagnostics of Nuclear Reactor Accidents Based on Particle Swarm Optimization Trained Neural Networks

    Abdel-Aal, M.M.Z.

    2004-01-01

    Automation in large, complex systems such as chemical plants, electrical power generation, aerospace and nuclear plants has been steadily increasing in the recent past. automated diagnosis and control forms a necessary part of these systems,this contains thousands of alarms processing in every component, subsystem and system. so the accurate and speed of diagnosis of faults is an important factors in operation and maintaining their health and continued operation and in reducing of repair and recovery time. using of artificial intelligence facilitates the alarm classifications and faults diagnosis to control any abnormal events during the operation cycle of the plant. thesis work uses the artificial neural network as a powerful classification tool. the work basically is has two components, the first is to effectively train the neural network using particle swarm optimization, which non-derivative based technique. to achieve proper training of the neural network to fault classification problem and comparing this technique to already existing techniques

  8. Mindfulness Meditation Training and Executive Control Network Resting State Functional Connectivity: A Randomized Controlled Trial.

    Taren, Adrienne A; Gianaros, Peter J; Greco, Carol M; Lindsay, Emily K; Fairgrieve, April; Brown, Kirk Warren; Rosen, Rhonda K; Ferris, Jennifer L; Julson, Erica; Marsland, Anna L; Creswell, J David

    Mindfulness meditation training has been previously shown to enhance behavioral measures of executive control (e.g., attention, working memory, cognitive control), but the neural mechanisms underlying these improvements are largely unknown. Here, we test whether mindfulness training interventions foster executive control by strengthening functional connections between dorsolateral prefrontal cortex (dlPFC)-a hub of the executive control network-and frontoparietal regions that coordinate executive function. Thirty-five adults with elevated levels of psychological distress participated in a 3-day randomized controlled trial of intensive mindfulness meditation or relaxation training. Participants completed a resting state functional magnetic resonance imaging scan before and after the intervention. We tested whether mindfulness meditation training increased resting state functional connectivity (rsFC) between dlPFC and frontoparietal control network regions. Left dlPFC showed increased connectivity to the right inferior frontal gyrus (T = 3.74), right middle frontal gyrus (MFG) (T = 3.98), right supplementary eye field (T = 4.29), right parietal cortex (T = 4.44), and left middle temporal gyrus (T = 3.97, all p < .05) after mindfulness training relative to the relaxation control. Right dlPFC showed increased connectivity to right MFG (T = 4.97, p < .05). We report that mindfulness training increases rsFC between dlPFC and dorsal network (superior parietal lobule, supplementary eye field, MFG) and ventral network (right IFG, middle temporal/angular gyrus) regions. These findings extend previous work showing increased functional connectivity among brain regions associated with executive function during active meditation by identifying specific neural circuits in which rsFC is enhanced by a mindfulness intervention in individuals with high levels of psychological distress. Clinicaltrials.gov,NCT01628809.

  9. High responders and low responders: factors associated with individual variation in response to standardized training.

    Mann, Theresa N; Lamberts, Robert P; Lambert, Michael I

    2014-08-01

    The response to an exercise intervention is often described in general terms, with the assumption that the group average represents a typical response for most individuals. In reality, however, it is more common for individuals to show a wide range of responses to an intervention rather than a similar response. This phenomenon of 'high responders' and 'low responders' following a standardized training intervention may provide helpful insights into mechanisms of training adaptation and methods of training prescription. Therefore, the aim of this review was to discuss factors associated with inter-individual variation in response to standardized, endurance-type training. It is well-known that genetic influences make an important contribution to individual variation in certain training responses. The association between genotype and training response has often been supported using heritability estimates; however, recent studies have been able to link variation in some training responses to specific single nucleotide polymorphisms. It would appear that hereditary influences are often expressed through hereditary influences on the pre-training phenotype, with some parameters showing a hereditary influence in the pre-training phenotype but not in the subsequent training response. In most cases, the pre-training phenotype appears to predict only a small amount of variation in the subsequent training response of that phenotype. However, the relationship between pre-training autonomic activity and subsequent maximal oxygen uptake response appears to show relatively stronger predictive potential. Individual variation in response to standardized training that cannot be explained by genetic influences may be related to the characteristics of the training program or lifestyle factors. Although standardized programs usually involve training prescribed by relative intensity and duration, some methods of relative exercise intensity prescription may be more successful in creating

  10. Virtual reality adaptive stimulation of limbic networks in the mental readiness training.

    Cosić, Kresimir; Popović, Sinisa; Kostović, Ivica; Judas, Milos

    2010-01-01

    A significant proportion of severe psychological problems in recent large-scale peacekeeping operations underscores the importance of effective methods for strengthening the stress resilience. Virtual reality (VR) adaptive stimulation, based on the estimation of the participant's emotional state from physiological signals, may enhance the mental readiness training (MRT). Understanding neurobiological mechanisms by which the MRT based on VR adaptive stimulation can affect the resilience to stress is important for practical application in the stress resilience management. After the delivery of a traumatic audio-visual stimulus in the VR, the cascade of events occurs in the brain, which evokes various physiological manifestations. In addition to the "limbic" emotional and visceral brain circuitry, other large-scale sensory, cognitive, and memory brain networks participate with less known impact in this physiological response. The MRT based on VR adaptive stimulation may strengthen the stress resilience through targeted brain-body interactions. Integrated interdisciplinary efforts, which would integrate the brain imaging and the proposed approach, may contribute to clarifying the neurobiological foundation of the resilience to stress.

  11. Signalling network construction for modelling plant defence response.

    Dragana Miljkovic

    Full Text Available Plant defence signalling response against various pathogens, including viruses, is a complex phenomenon. In resistant interaction a plant cell perceives the pathogen signal, transduces it within the cell and performs a reprogramming of the cell metabolism leading to the pathogen replication arrest. This work focuses on signalling pathways crucial for the plant defence response, i.e., the salicylic acid, jasmonic acid and ethylene signal transduction pathways, in the Arabidopsis thaliana model plant. The initial signalling network topology was constructed manually by defining the representation formalism, encoding the information from public databases and literature, and composing a pathway diagram. The manually constructed network structure consists of 175 components and 387 reactions. In order to complement the network topology with possibly missing relations, a new approach to automated information extraction from biological literature was developed. This approach, named Bio3graph, allows for automated extraction of biological relations from the literature, resulting in a set of (component1, reaction, component2 triplets and composing a graph structure which can be visualised, compared to the manually constructed topology and examined by the experts. Using a plant defence response vocabulary of components and reaction types, Bio3graph was applied to a set of 9,586 relevant full text articles, resulting in 137 newly detected reactions between the components. Finally, the manually constructed topology and the new reactions were merged to form a network structure consisting of 175 components and 524 reactions. The resulting pathway diagram of plant defence signalling represents a valuable source for further computational modelling and interpretation of omics data. The developed Bio3graph approach, implemented as an executable language processing and graph visualisation workflow, is publically available at http://ropot.ijs.si/bio3graph/and can be

  12. Cooperative VET in Training Networks: Analysing the Free-Rider Problem in a Sociology-of-Conventions Perspective

    Leemann, Regula Julia; Imdorf, Christian

    2015-01-01

    In training networks, particularly small and medium-sized enterprises pool their resources to train apprentices within the framework of the dual VET system, while an intermediary organisation is tasked with managing operations. Over the course of their apprenticeship, the apprentices switch from one training company to another on a (half-) yearly…

  13. ON OPERATION OF 740 M LONG FREIGHT TRAINS ON CZECH TEN-T RAILWAY NETWORK

    Michal Drábek

    2016-09-01

    Full Text Available Regulation (EU No 1315/2013 defines actual scope of core and comprehensive TEN-T network, including both networks for railway freight transport. For the core network, possibility to operate 740 m long freight trains is required. The aim of this paper is to analyse availability of appropriate overtaking tracks for 740 m long freight trains. Due to ETCS braking curves and odometry, such trains, after ETCS implementation, will require 780-800 m long overtaking tracks. For practical reasons (e.g. bypass lines, whole Czech railway TEN-T network is analysed. The overtaking track, whose occupation means influence on scheduled traffic or threat to boarding passengers, are excluded. The data was collected from station schemes from Collection of Official Requisites for 2015/16 Timetable, issued by SŽDC, Czech state Infrastructure Manager. Most of appropriate tracks are over 800 m long, but their density in the network and in particular directions varies considerably. For freight traffic, gradient of the line is important, so in the resulting figure, there are marked significant peaks for particular lines as well. Czech TEN-T lines are further segmented on the basis of number of tracks and their traffic character. Then, specific issues on overtaking or crossing of 740 m long freight trains are discussed. As a conclusion, for long-term development of Czech TEN-T lines, targeted investment is recommended not only for passenger railway, but also for freight railway. An attractive capacity offer for railway undertakings, which can stimulate freight traffic on European Rail freight corridors, can be represented by network-bound periodic freight train paths with suitable long overtaking tracks outside bottlenecks. After the overtaking by passenger trains, a freight train should run without stop through large node station or a bottleneck area. Before the sections with high gradients, coupling of additional locomotives should be connected with the overtaking

  14. Conceptual design report, Hazardous Materials Management and Emergency Response (HAMMER) Training Center

    Kelly, K.E. [Westinghouse Hanford Co., Richland, WA (United States)

    1994-11-09

    For the next 30 years, the main activities at the US Department of Energy (DOE) Hanford Site will involve the management, handling, and cleanup of toxic substances. If the DOE is to meet its high standards of safety, the thousands of workers involved in these activities will need systematic training appropriate to their tasks and the risks associated with these tasks. Furthermore, emergency response for DOE shipments is the primary responsibility of state, tribal, and local governments. A collaborative training initiative with the DOE will strengthen emergency response at the Hanford Site and within the regional communities. Local and international labor has joined the Hazardous Materials Management and Emergency Response (HAMMER) partnership, and will share in the HAMMER Training Center core programs and facilities using their own specialized trainers and training programs. The HAMMER Training Center will provide a centralized regional site dedicated to the training of hazardous material, emergency response, and fire fighting personnel.

  15. Conceptual design report, Hazardous Materials Management and Emergency Response (HAMMER) Training Center

    Kelly, K.E.

    1994-01-01

    For the next 30 years, the main activities at the US Department of Energy (DOE) Hanford Site will involve the management, handling, and cleanup of toxic substances. If the DOE is to meet its high standards of safety, the thousands of workers involved in these activities will need systematic training appropriate to their tasks and the risks associated with these tasks. Furthermore, emergency response for DOE shipments is the primary responsibility of state, tribal, and local governments. A collaborative training initiative with the DOE will strengthen emergency response at the Hanford Site and within the regional communities. Local and international labor has joined the Hazardous Materials Management and Emergency Response (HAMMER) partnership, and will share in the HAMMER Training Center core programs and facilities using their own specialized trainers and training programs. The HAMMER Training Center will provide a centralized regional site dedicated to the training of hazardous material, emergency response, and fire fighting personnel

  16. IAEA Response and Assistance Network. Date Effective: 1 September 2013

    2013-01-01

    The Parties to the Convention on Assistance in the Case of a Nuclear Accident or Radiological Emergency (the 'Assistance Convention') have undertaken to cooperate between themselves and with the IAEA to facilitate the timely provision of assistance in the case of a nuclear accident or radiological emergency, in order to mitigate its consequences. In September 2000, the General Conference of the IAEA, in resolution GC(44)/RES/16, encouraged Member States ''to implement instruments for improving their response, in particular their contribution to international response, to nuclear and radiological emergencies'' as well as ''to participate actively in the process of strengthening international, national and regional capabilities for responding to nuclear and radiological emergencies and to make those capabilities more consistent and coherent''. As part of the IAEA's strategy for supporting the practical implementation of the Assistance Convention, in 2000 the IAEA Secretariat established a global Emergency Response Network (ERNET) of teams suitably qualified to respond to nuclear or radiological emergencies rapidly and, in principle, on a regional basis. The IAEA Secretariat published IAEA Emergency Response Network - ERNET (EPR-ERNET) in 2000, which set out the criteria and requirements to be met by members of the network. An updated edition was published in 2002. The Second Meeting of the Representatives of Competent Authorities Identified under the Convention on Early Notification of a Nuclear Accident and the Convention on Assistance in the Case of a Nuclear Accident or Radiological Emergency, held in Vienna in June 2003, recommended that the IAEA Secretariat convene a Technical Meeting to formulate recommendations aimed at improving participation in the network. Participants in a Technical Meeting held in March 2004 developed a new concept for the network and a completely new draft of the publication. In July 2005, the Third Meeting of Competent Authorities

  17. Reorganization of functional brain networks mediates the improvement of cognitive performance following real-time neurofeedback training of working memory.

    Zhang, Gaoyan; Yao, Li; Shen, Jiahui; Yang, Yihong; Zhao, Xiaojie

    2015-05-01

    Working memory (WM) is essential for individuals' cognitive functions. Neuroimaging studies indicated that WM fundamentally relied on a frontoparietal working memory network (WMN) and a cinguloparietal default mode network (DMN). Behavioral training studies demonstrated that the two networks can be modulated by WM training. Different from the behavioral training, our recent study used a real-time functional MRI (rtfMRI)-based neurofeedback method to conduct WM training, demonstrating that WM performance can be significantly improved after successfully upregulating the activity of the target region of interest (ROI) in the left dorsolateral prefrontal cortex (Zhang et al., [2013]: PloS One 8:e73735); however, the neural substrate of rtfMRI-based WM training remains unclear. In this work, we assessed the intranetwork and internetwork connectivity changes of WMN and DMN during the training, and their correlations with the change of brain activity in the target ROI as well as with the improvement of post-training behavior. Our analysis revealed an "ROI-network-behavior" correlation relationship underlying the rtfMRI training. Further mediation analysis indicated that the reorganization of functional brain networks mediated the effect of self-regulation of the target brain activity on the improvement of cognitive performance following the neurofeedback training. The results of this study enhance our understanding of the neural basis of real-time neurofeedback and suggest a new direction to improve WM performance by regulating the functional connectivity in the WM related networks. © 2014 Wiley Periodicals, Inc.

  18. Disaster response team FAST skills training with a portable ultrasound simulator compared to traditional training: pilot study.

    Paddock, Michael T; Bailitz, John; Horowitz, Russ; Khishfe, Basem; Cosby, Karen; Sergel, Michelle J

    2015-03-01

    Pre-hospital focused assessment with sonography in trauma (FAST) has been effectively used to improve patient care in multiple mass casualty events throughout the world. Although requisite FAST knowledge may now be learned remotely by disaster response team members, traditional live instructor and model hands-on FAST skills training remains logistically challenging. The objective of this pilot study was to compare the effectiveness of a novel portable ultrasound (US) simulator with traditional FAST skills training for a deployed mixed provider disaster response team. We randomized participants into one of three training groups stratified by provider role: Group A. Traditional Skills Training, Group B. US Simulator Skills Training, and Group C. Traditional Skills Training Plus US Simulator Skills Training. After skills training, we measured participants' FAST image acquisition and interpretation skills using a standardized direct observation tool (SDOT) with healthy models and review of FAST patient images. Pre- and post-course US and FAST knowledge were also assessed using a previously validated multiple-choice evaluation. We used the ANOVA procedure to determine the statistical significance of differences between the means of each group's skills scores. Paired sample t-tests were used to determine the statistical significance of pre- and post-course mean knowledge scores within groups. We enrolled 36 participants, 12 randomized to each training group. Randomization resulted in similar distribution of participants between training groups with respect to provider role, age, sex, and prior US training. For the FAST SDOT image acquisition and interpretation mean skills scores, there was no statistically significant difference between training groups. For US and FAST mean knowledge scores, there was a statistically significant improvement between pre- and post-course scores within each group, but again there was not a statistically significant difference between

  19. Dose-response relationship of the cardiovascular adaptation to endurance training in healthy adults: how much training for what benefit?

    Iwasaki, Ken-Ichi; Zhang, Rong; Zuckerman, Julie H; Levine, Benjamin D

    2003-10-01

    Occupational or recreational exercise reduces mortality from cardiovascular disease. The potential mechanisms for this reduction may include changes in blood pressure (BP) and autonomic control of the circulation. Therefore, we conducted the present long-term longitudinal study to quantify the dose-response relationship between the volume and intensity of exercise training, and regulation of heart rate (HR) and BP. We measured steady-state hemodynamics and analyzed dynamic cardiovascular regulation by spectral and transfer function analysis of cardiovascular variability in 11 initially sedentary subjects during 1 yr of progressive endurance training sufficient to allow them to complete a marathon. From this, we found that 1) moderate exercise training for 3 mo decreased BP, HR, and total peripheral resistance, and increased cardiovascular variability and arterial baroreflex sensitivity; 2) more prolonged and intense training did not augment these changes further; and 3) most of these changes returned to control values at 12 mo despite markedly increased training duration and intensity equivalent to that routinely observed in competitive athletes. In conclusion, increases in R-wave-R-wave interval and cardiovascular variability indexes are consistent with an augmentation of vagal modulation of HR after exercise training. It appears that moderate doses of training for 3 mo are sufficient to achieve this response as well as a modest hypotensive effect from decreasing vascular resistance. However, more prolonged and intense training does not necessarily lead to greater enhancement of circulatory control and, therefore, may not provide an added protective benefit via autonomic mechanisms against death by cardiovascular disease.

  20. Simulating Quantitative Cellular Responses Using Asynchronous Threshold Boolean Network Ensembles

    Shah Imran

    2011-07-01

    Full Text Available Abstract Background With increasing knowledge about the potential mechanisms underlying cellular functions, it is becoming feasible to predict the response of biological systems to genetic and environmental perturbations. Due to the lack of homogeneity in living tissues it is difficult to estimate the physiological effect of chemicals, including potential toxicity. Here we investigate a biologically motivated model for estimating tissue level responses by aggregating the behavior of a cell population. We assume that the molecular state of individual cells is independently governed by discrete non-deterministic signaling mechanisms. This results in noisy but highly reproducible aggregate level responses that are consistent with experimental data. Results We developed an asynchronous threshold Boolean network simulation algorithm to model signal transduction in a single cell, and then used an ensemble of these models to estimate the aggregate response across a cell population. Using published data, we derived a putative crosstalk network involving growth factors and cytokines - i.e., Epidermal Growth Factor, Insulin, Insulin like Growth Factor Type 1, and Tumor Necrosis Factor α - to describe early signaling events in cell proliferation signal transduction. Reproducibility of the modeling technique across ensembles of Boolean networks representing cell populations is investigated. Furthermore, we compare our simulation results to experimental observations of hepatocytes reported in the literature. Conclusion A systematic analysis of the results following differential stimulation of this model by growth factors and cytokines suggests that: (a using Boolean network ensembles with asynchronous updating provides biologically plausible noisy individual cellular responses with reproducible mean behavior for large cell populations, and (b with sufficient data our model can estimate the response to different concentrations of extracellular ligands. Our

  1. The individual response to training and competition at altitude.

    Chapman, Robert F

    2013-12-01

    Performance in athletic activities that include a significant aerobic component at mild or moderate altitudes shows a large individual variation. Physiologically, a large portion of the negative effect of altitude on exercise performance can be traced to limitations of oxygen diffusion, either at the level of the alveoli or the muscle microvasculature. In the lung, the ability to maintain arterial oxyhaemoglobin saturation (SaO₂) appears to be a primary factor, ultimately influencing oxygen delivery to the periphery. SaO₂ in hypoxia can be defended by increasing ventilatory drive; however, during heavy exercise, many athletes demonstrate limitations to expiratory flow and are unable to increase ventilation in hypoxia. Additionally, increasing ventilatory work in hypoxia may actually be negative for performance, if dyspnoea increases or muscle blood flow is reduced secondary to an increased sympathetic outflow (eg, the muscle metaboreflex response). Taken together, some athletes are clearly more negatively affected during exercise in hypoxia than other athletes. With careful screening, it may be possible to develop a protocol for determining which athletes may be the most negatively affected during competition and/or training at altitude.

  2. Training, Drills Pivotal in Mounting Response to Orlando Shooting.

    Albert, Eric; Bullard, Timothy

    2016-08-01

    Emergency providers at Orlando Regional Medical Center in Orlando. FL, faced multiple challenges in responding to the worst mass shooting in U.S. history. As the scene of the shooting was only three blocks away from the hospital, there was little time to prepare when notified that victims would begin arriving shortly after 2 a.m. on June 12. Also, fears of a gunman near the hospital briefly put the ED on lock down. However, using the incident command system, the hospital was able to mobilize quickly, receiving 44 patients, nine of whom died shortly after arrival. Administrators note that recent training exercises geared toward a mass shooting event facilitated the response and probably saved lives. Patients arrived at the hospital in two waves, with the initial surge occurring right after the hooting took place around 2 a.m., and the second surge occurring about three hours later. At one point, more than 90 patients were in the ED, more than half for reasons unrelated to the shooting. Clinicians contended with a much higher than usual noise level while treating patients, making it hard to hear reports from EMS personnel. Also, treatment had to commence prior to identification for some patients who arrived unconscious or unable to speak. While surgeons and other key specialists were called into the hospital to address identified needs, administrators actually called hospital personnel to tell them not to come in unless they were notified. This prevented added management hurdles.

  3. Functional design criteria for the Hazardous Materials Management and Emergency Response (HAMMER) Training Center. Revision 1

    Sato, P.K.

    1995-01-01

    Within the United States, there are few hands-on training centers capable of providing integrated technical training within a practical application environment. Currently, there are no training facilities that offer both radioactive and chemical hazardous response training. There are no hands-on training centers that provide training for both hazardous material operations and emergency response that also operate as a partnership between organized labor, state agencies, tribes, and local emergency responders within the US Department of Energy (DOE) complex. Available facilities appear grossly inadequate for training the thousands of people at Hanford, and throughout the Pacific Northwest, who are required to qualify under nationally-mandated requirements. It is estimated that 4,000 workers at the Hanford Site alone need hands-on training. Throughout the Pacific Northwest, the potential target audience would be over 30,000 public sector emergency response personnel, as well as another 10,000 clean-up workers represented by organized labor. The HAMMER Training Center will be an interagency-sponsored training center. It will be designed, built, and operated to ensure that clean-up workers, fire fighters, and public sector management and emergency response personnel are trained to handle accidental spills of hazardous materials. Training will cover wastes at clean-up sites, and in jurisdictions along the transportation corridors, to effectively protect human life, property, and the environment

  4. End-to-End Delay Model for Train Messaging over Public Land Mobile Networks

    Franco Mazzenga

    2017-11-01

    Full Text Available Modern train control systems rely on a dedicated radio network for train to ground communications. A number of possible alternatives have been analysed to adopt the European Rail Traffic Management System/European Train Control System (ERTMS/ETCS control system on local/regional lines to improve transport capacity. Among them, a communication system based on public networks (cellular&satellite provides an interesting, effective and alternative solution to proprietary and expensive radio networks. To analyse performance of this solution, it is necessary to model the end-to-end delay and message loss to fully characterize the message transfer process from train to ground and vice versa. Starting from the results of a railway test campaign over a 300 km railway line for a cumulative 12,000 traveled km in 21 days, in this paper, we derive a statistical model for the end-to-end delay required for delivering messages. In particular, we propose a two states model allowing for reproducing the main behavioral characteristics of the end-to-end delay as observed experimentally. Model formulation has been derived after deep analysis of the recorded experimental data. When it is applied to model a realistic scenario, it allows for explicitly accounting for radio coverage characteristics, the received power level, the handover points along the line and for the serving radio technology. As an example, the proposed model is used to generate the end-to-end delay profile in a realistic scenario.

  5. Outcomes from the GLEON fellowship program. Training graduate students in data driven network science.

    Dugan, H.; Hanson, P. C.; Weathers, K. C.

    2016-12-01

    In the water sciences there is a massive need for graduate students who possess the analytical and technical skills to deal with large datasets and function in the new paradigm of open, collaborative -science. The Global Lake Ecological Observatory Network (GLEON) graduate fellowship program (GFP) was developed as an interdisciplinary training program to supplement the intensive disciplinary training of traditional graduate education. The primary goal of the GFP was to train a diverse cohort of graduate students in network science, open-web technologies, collaboration, and data analytics, and importantly to provide the opportunity to use these skills to conduct collaborative research resulting in publishable scientific products. The GFP is run as a series of three week-long workshops over two years that brings together a cohort of twelve students. In addition, fellows are expected to attend and contribute to at least one international GLEON all-hands' meeting. Here, we provide examples of training modules in the GFP (model building, data QA/QC, information management, bayesian modeling, open coding/version control, national data programs), as well as scientific outputs (manuscripts, software products, and new global datasets) produced by the fellows, as well as the process by which this team science was catalyzed. Data driven education that lets students apply learned skills to real research projects reinforces concepts, provides motivation, and can benefit their publication record. This program design is extendable to other institutions and networks.

  6. SAGRAD: A Program for Neural Network Training with Simulated Annealing and the Conjugate Gradient Method.

    Bernal, Javier; Torres-Jimenez, Jose

    2015-01-01

    SAGRAD (Simulated Annealing GRADient), a Fortran 77 program for computing neural networks for classification using batch learning, is discussed. Neural network training in SAGRAD is based on a combination of simulated annealing and Møller's scaled conjugate gradient algorithm, the latter a variation of the traditional conjugate gradient method, better suited for the nonquadratic nature of neural networks. Different aspects of the implementation of the training process in SAGRAD are discussed, such as the efficient computation of gradients and multiplication of vectors by Hessian matrices that are required by Møller's algorithm; the (re)initialization of weights with simulated annealing required to (re)start Møller's algorithm the first time and each time thereafter that it shows insufficient progress in reaching a possibly local minimum; and the use of simulated annealing when Møller's algorithm, after possibly making considerable progress, becomes stuck at a local minimum or flat area of weight space. Outlines of the scaled conjugate gradient algorithm, the simulated annealing procedure and the training process used in SAGRAD are presented together with results from running SAGRAD on two examples of training data.

  7. Training algorithms evaluation for artificial neural network to temporal prediction of photovoltaic generation

    Arantes Monteiro, Raul Vitor; Caixeta Guimarães, Geraldo; Rocio Castillo, Madeleine; Matheus Moura, Fabrício Augusto; Tamashiro, Márcio Augusto

    2016-01-01

    Current energy policies are encouraging the connection of power generation based on low-polluting technologies, mainly those using renewable sources, to distribution networks. Hence, it becomes increasingly important to understand technical challenges, facing high penetration of PV systems at the grid, especially considering the effects of intermittence of this source on the power quality, reliability and stability of the electric distribution system. This fact can affect the distribution networks on which they are attached causing overvoltage, undervoltage and frequency oscillations. In order to predict these disturbs, artificial neural networks are used. This article aims to analyze 3 training algorithms used in artificial neural networks for temporal prediction of the generated active power thru photovoltaic panels. As a result it was concluded that the algorithm with the best performance among the 3 analyzed was the Levenberg-Marquadrt.

  8. Psychophysiological Responses to Group Exercise Training Sessions: Does Exercise Intensity Matter?

    Matteo Vandoni

    Full Text Available Group exercise training programs were introduced as a strategy for improving health and fitness and potentially reducing dropout rates. This study examined the psychophysiological responses to group exercise training sessions. Twenty-seven adults completed two group exercise training sessions of moderate and vigorous exercise intensities in a random and counterbalanced order. The %HRR and the exertional and arousal responses to vigorous session were higher than those during the moderate session (p<0.05. Consequently, the affective responses to vigorous session were less pleasant than those during moderate session (p<0.05. These results suggest that the psychophysiological responses to group exercise training sessions are intensity-dependent. From an adherence perspective, interventionists are encouraged to emphasize group exercise training sessions at a moderate intensity to maximize affective responses and to minimize exertional responses, which in turn may positively affect future exercise behavior.

  9. REPRODUCTIVE HORMONES AND CORTISOL RESPONSES TO PLYOMETRIC TRAINING IN MALES

    Serife Vatansever Ozen

    2012-01-01

    Plyometric training activities are commonly used by a wide range of athletes to increase jump performance and improve explosive power and muscular activation patterns. The purpose of the study was to evaluate the effects of plyometric training on male reproductive hormones. Nineteen recreationally active males volunteered to participate in this study and were randomly assigned to plyometrically trained (n=10, 21.2 ±2.3 years) and control groups (n=9, 21.4± 2.1). The plyometric training group ...

  10. Discriminating response groups in metabolic and regulatory pathway networks.

    Van Hemert, John L; Dickerson, Julie A

    2012-04-01

    Analysis of omics experiments generates lists of entities (genes, metabolites, etc.) selected based on specific behavior, such as changes in response to stress or other signals. Functional interpretation of these lists often uses category enrichment tests using functional annotations like Gene Ontology terms and pathway membership. This approach does not consider the connected structure of biochemical pathways or the causal directionality of events. The Omics Response Group (ORG) method, described in this work, interprets omics lists in the context of metabolic pathway and regulatory networks using a statistical model for flow within the networks. Statistical results for all response groups are visualized in a novel Pathway Flow plot. The statistical tests are based on the Erlang distribution model under the assumption of independent and identically Exponential-distributed random walk flows through pathways. As a proof of concept, we applied our method to an Escherichia coli transcriptomics dataset where we confirmed common knowledge of the E.coli transcriptional response to Lipid A deprivation. The main response is related to osmotic stress, and we were also able to detect novel responses that are supported by the literature. We also applied our method to an Arabidopsis thaliana expression dataset from an abscisic acid study. In both cases, conventional pathway enrichment tests detected nothing, while our approach discovered biological processes beyond the original studies. We created a prototype for an interactive ORG web tool at http://ecoserver.vrac.iastate.edu/pathwayflow (source code is available from https://subversion.vrac.iastate.edu/Subversion/jlv/public/jlv/pathwayflow). The prototype is described along with additional figures and tables in Supplementary Material. julied@iastate.edu Supplementary data are available at Bioinformatics online.

  11. Reconstruction of sparse connectivity in neural networks from spike train covariances

    Pernice, Volker; Rotter, Stefan

    2013-01-01

    The inference of causation from correlation is in general highly problematic. Correspondingly, it is difficult to infer the existence of physical synaptic connections between neurons from correlations in their activity. Covariances in neural spike trains and their relation to network structure have been the subject of intense research, both experimentally and theoretically. The influence of recurrent connections on covariances can be characterized directly in linear models, where connectivity in the network is described by a matrix of linear coupling kernels. However, as indirect connections also give rise to covariances, the inverse problem of inferring network structure from covariances can generally not be solved unambiguously. Here we study to what degree this ambiguity can be resolved if the sparseness of neural networks is taken into account. To reconstruct a sparse network, we determine the minimal set of linear couplings consistent with the measured covariances by minimizing the L 1 norm of the coupling matrix under appropriate constraints. Contrary to intuition, after stochastic optimization of the coupling matrix, the resulting estimate of the underlying network is directed, despite the fact that a symmetric matrix of count covariances is used for inference. The performance of the new method is best if connections are neither exceedingly sparse, nor too dense, and it is easily applicable for networks of a few hundred nodes. Full coupling kernels can be obtained from the matrix of full covariance functions. We apply our method to networks of leaky integrate-and-fire neurons in an asynchronous–irregular state, where spike train covariances are well described by a linear model. (paper)

  12. Training-Image Based Geostatistical Inversion Using a Spatial Generative Adversarial Neural Network

    Laloy, Eric; Hérault, Romain; Jacques, Diederik; Linde, Niklas

    2018-01-01

    Probabilistic inversion within a multiple-point statistics framework is often computationally prohibitive for high-dimensional problems. To partly address this, we introduce and evaluate a new training-image based inversion approach for complex geologic media. Our approach relies on a deep neural network of the generative adversarial network (GAN) type. After training using a training image (TI), our proposed spatial GAN (SGAN) can quickly generate 2-D and 3-D unconditional realizations. A key characteristic of our SGAN is that it defines a (very) low-dimensional parameterization, thereby allowing for efficient probabilistic inversion using state-of-the-art Markov chain Monte Carlo (MCMC) methods. In addition, available direct conditioning data can be incorporated within the inversion. Several 2-D and 3-D categorical TIs are first used to analyze the performance of our SGAN for unconditional geostatistical simulation. Training our deep network can take several hours. After training, realizations containing a few millions of pixels/voxels can be produced in a matter of seconds. This makes it especially useful for simulating many thousands of realizations (e.g., for MCMC inversion) as the relative cost of the training per realization diminishes with the considered number of realizations. Synthetic inversion case studies involving 2-D steady state flow and 3-D transient hydraulic tomography with and without direct conditioning data are used to illustrate the effectiveness of our proposed SGAN-based inversion. For the 2-D case, the inversion rapidly explores the posterior model distribution. For the 3-D case, the inversion recovers model realizations that fit the data close to the target level and visually resemble the true model well.

  13. NeuroRecovery Network provides standardization of locomotor training for persons with incomplete spinal cord injury.

    Morrison, Sarah A; Forrest, Gail F; VanHiel, Leslie R; Davé, Michele; D'Urso, Denise

    2012-09-01

    To illustrate the continuity of care afforded by a standardized locomotor training program across a multisite network setting within the Christopher and Dana Reeve Foundation NeuroRecovery Network (NRN). Single patient case study. Two geographically different hospital-based outpatient facilities. This case highlights a 25-year-old man diagnosed with C4 motor incomplete spinal cord injury with American Spinal Injury Association Impairment Scale grade D. Standardized locomotor training program 5 sessions per week for 1.5 hours per session, for a total of 100 treatment sessions, with 40 sessions at 1 center and 60 at another. Ten-meter walk test and 6-minute walk test were assessed at admission and discharge across both facilities. For each of the 100 treatment sessions percent body weight support, average, and maximum treadmill speed were evaluated. Locomotor endurance, as measured by the 6-minute walk test, and overground gait speed showed consistent improvement from admission to discharge. Throughout training, the patient decreased the need for body weight support and was able to tolerate faster treadmill speeds. Data indicate that the patient continued to improve on both treatment parameters and walking function. Standardization across the NRN centers provided a mechanism for delivering consistent and reproducible locomotor training programs across 2 facilities without disrupting training or recovery progression. Copyright © 2012 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

  14. Brain network response underlying decisions about abstract reinforcers.

    Mills-Finnerty, Colleen; Hanson, Catherine; Hanson, Stephen Jose

    2014-12-01

    Decision making studies typically use tasks that involve concrete action-outcome contingencies, in which subjects do something and get something. No studies have addressed decision making involving abstract reinforcers, where there are no action-outcome contingencies and choices are entirely hypothetical. The present study examines these kinds of choices, as well as whether the same biases that exist for concrete reinforcer decisions, specifically framing effects, also apply during abstract reinforcer decisions. We use both General Linear Model as well as Bayes network connectivity analysis using the Independent Multi-sample Greedy Equivalence Search (IMaGES) algorithm to examine network response underlying choices for abstract reinforcers under positive and negative framing. We find for the first time that abstract reinforcer decisions activate the same network of brain regions as concrete reinforcer decisions, including the striatum, insula, anterior cingulate, and VMPFC, results that are further supported via comparison to a meta-analysis of decision making studies. Positive and negative framing activated different parts of this network, with stronger activation in VMPFC during negative framing and in DLPFC during positive, suggesting different decision making pathways depending on frame. These results were further clarified using connectivity analysis, which revealed stronger connections between anterior cingulate, insula, and accumbens during negative framing compared to positive. Taken together, these results suggest that not only do abstract reinforcer decisions rely on the same brain substrates as concrete reinforcers, but that the response underlying framing effects on abstract reinforcers also resemble those for concrete reinforcers, specifically increased limbic system connectivity during negative frames. Copyright © 2014 Elsevier Inc. All rights reserved.

  15. Responses to a questionnaire on networking between OIE Reference Laboratories and OIE Collaborating Centres.

    Brückner, G K; Linnane, S; Diaz, F; Vallat, B

    2007-01-01

    Two separate questionnaires were distributed to 20 OIE Collaborating Centres and 160 OIE Reference Laboratories to assess the current status of networking and collaboration among OIE Reference Laboratories and between OIE Reference Laboratories and OIE Collaborating Centres. The questionnaire for the OIE Reference Laboratories contained 7 sections with questions on networking between laboratories, reporting of information, biosecurity quality control, and financing. Emphasis was placed in obtaining information on inter-laboratory relationships and exchange of expertise, training needs and sharing of data and information. The questionnaire for the OIE Collaborating Centres contained six sections with the emphasis on aspects related to awareness of services that can be provided, expertise that could be made available, sharing of information and the relationship with the national veterinary services of the countries concerned. The responses to the questionnaires were collated, categorised and statistically evaluated to allow for tentative inferences on the data provided. Valuable information emanated from the data identifying the current status of networking and indicating possible shortcomings that could be addressed to improve networking.

  16. Metastable Features of Economic Networks and Responses to Exogenous Shocks.

    Ali Hosseiny

    Full Text Available It is well known that a network structure plays an important role in addressing a collective behavior. In this paper we study a network of firms and corporations for addressing metastable features in an Ising based model. In our model we observe that if in a recession the government imposes a demand shock to stimulate the network, metastable features shape its response. Actually we find that there exists a minimum bound where any demand shock with a size below it is unable to trigger the market out of recession. We then investigate the impact of network characteristics on this minimum bound. We surprisingly observe that in a Watts-Strogatz network, although the minimum bound depends on the average of the degrees, when translated into the language of economics, such a bound is independent of the average degrees. This bound is about 0.44ΔGDP, where ΔGDP is the gap of GDP between recession and expansion. We examine our suggestions for the cases of the United States and the European Union in the recent recession, and compare them with the imposed stimulations. While the stimulation in the US has been above our threshold, in the EU it has been far below our threshold. Beside providing a minimum bound for a successful stimulation, our study on the metastable features suggests that in the time of crisis there is a "golden time passage" in which the minimum bound for successful stimulation can be much lower. Hence, our study strongly suggests stimulations to arise within this time passage.

  17. An Improved Neural Network Training Algorithm for Wi-Fi Fingerprinting Positioning

    Esmond Mok

    2013-09-01

    Full Text Available Ubiquitous positioning provides continuous positional information in both indoor and outdoor environments for a wide spectrum of location based service (LBS applications. With the rapid development of the low-cost and high speed data communication, Wi-Fi networks in many metropolitan cities, strength of signals propagated from the Wi-Fi access points (APs namely received signal strength (RSS have been cleverly adopted for indoor positioning. In this paper, a Wi-Fi positioning algorithm based on neural network modeling of Wi-Fi signal patterns is proposed. This algorithm is based on the correlation between the initial parameter setting for neural network training and output of the mean square error to obtain better modeling of the nonlinear highly complex Wi-Fi signal power propagation surface. The test results show that this neural network based data processing algorithm can significantly improve the neural network training surface to achieve the highest possible accuracy of the Wi-Fi fingerprinting positioning method.

  18. Influence of cueing on the preparation and execution of untrained and trained complex motor responses

    S.R. Alouche

    2012-05-01

    Full Text Available This study investigated the influence of cueing on the performance of untrained and trained complex motor responses. Healthy adults responded to a visual target by performing four sequential movements (complex response or a single movement (simple response of their middle finger. A visual cue preceded the target by an interval of 300, 1000, or 2000 ms. In Experiment 1, the complex and simple responses were not previously trained. During the testing session, the complex response pattern varied on a trial-by-trial basis following the indication provided by the visual cue. In Experiment 2, the complex response and the simple response were extensively trained beforehand. During the testing session, the trained complex response pattern was performed in all trials. The latency of the untrained and trained complex responses decreased from the short to the medium and long cue-target intervals. The latency of the complex response was longer than that of the simple response, except in the case of the trained responses and the long cue-target interval. These results suggest that the preparation of untrained complex responses cannot be completed in advance, this being possible, however, for trained complex responses when enough time is available. The duration of the 1st submovement, 1st pause and 2nd submovement of the untrained and the trained complex responses increased from the short to the long cue-target interval, suggesting that there is an increase of online programming of the response possibly related to the degree of certainty about the moment of target appearance.

  19. Mercury Deposition Network Site Operator Training for the System Blank and Blind Audit Programs

    Wetherbee, Gregory A.; Lehmann, Christopher M.B.

    2008-01-01

    The U.S. Geological Survey operates the external quality assurance project for the National Atmospheric Deposition Program/Mercury Deposition Network. The project includes the system blank and blind audit programs for assessment of total mercury concentration data quality for wet-deposition samples. This presentation was prepared to train new site operators and to refresh experienced site operators to successfully process and submit system blank and blind audit samples for chemical analysis. Analytical results are used to estimate chemical stability and contamination levels of National Atmospheric Deposition Program/Mercury Deposition Network samples and to evaluate laboratory variability and bias.

  20. Applying Culturally Responsive Pedagogy to the Vocational Training of Immigrants

    Wu, Ya-Ling

    2016-01-01

    Training and learning are the personal process in which individuals interact with social and cultural contexts. Immigrant trainees bring their early educational and life experiences into training classrooms, and their learning is strongly affected by their prior socialization and socio-cultural experiences. Therefore, it is necessary to provide…

  1. Modeling the Responses to Resistance Training in an Animal Experiment Study

    Antony G. Philippe

    2015-01-01

    Full Text Available The aim of the present study was to test whether systems models of training effects on performance in athletes can be used to explore the responses to resistance training in rats. 11 Wistar Han rats (277 ± 15 g underwent 4 weeks of resistance training consisting in climbing a ladder with progressive loads. Training amount and performance were computed from total work and mean power during each training session. Three systems models relating performance to cumulated training bouts have been tested: (i with a single component for adaptation to training, (ii with two components to distinguish the adaptation and fatigue produced by exercise bouts, and (iii with an additional component to account for training-related changes in exercise-induced fatigue. Model parameters were fitted using a mixed-effects modeling approach. The model with two components was found to be the most suitable to analyze the training responses (R2=0.53; P<0.001. In conclusion, the accuracy in quantifying training loads and performance in a rodent experiment makes it possible to model the responses to resistance training. This modeling in rodents could be used in future studies in combination with biological tools for enhancing our understanding of the adaptive processes that occur during physical training.

  2. Using a site-specific technical error to establish training responsiveness: a preliminary explorative study.

    Weatherwax, Ryan M; Harris, Nigel K; Kilding, Andrew E; Dalleck, Lance C

    2018-01-01

    Even though cardiorespiratory fitness (CRF) training elicits numerous health benefits, not all individuals have positive training responses following a structured CRF intervention. It has been suggested that the technical error (TE), a combination of biological variability and measurement error, should be used to establish specific training responsiveness criteria to gain further insight on the effectiveness of the training program. To date, most training interventions use an absolute change or a TE from previous findings, which do not take into consideration the training site and equipment used to establish training outcomes or the specific cohort being evaluated. The purpose of this investigation was to retrospectively analyze training responsiveness of two CRF training interventions using two common criteria and a site-specific TE. Sixteen men and women completed two maximal graded exercise tests and verification bouts to identify maximal oxygen consumption (VO 2 max) and establish a site-specific TE. The TE was then used to retrospectively analyze training responsiveness in comparison to commonly used criteria: percent change of >0% and >+5.6% in VO 2 max. The TE was found to be 7.7% for relative VO 2 max. χ 2 testing showed significant differences in all training criteria for each intervention and pooled data from both interventions, except between %Δ >0 and %Δ >+7.7% in one of the investigations. Training nonresponsiveness ranged from 11.5% to 34.6%. Findings from the present study support the utility of site-specific TE criterion to quantify training responsiveness. A similar methodology of establishing a site-specific and even cohort specific TE should be considered to establish when true cardiorespiratory training adaptations occur.

  3. The Bilevel Design Problem for Communication Networks on Trains: Model, Algorithm, and Verification

    Yin Tian

    2014-01-01

    Full Text Available This paper proposes a novel method to solve the problem of train communication network design. Firstly, we put forward a general description of such problem. Then, taking advantage of the bilevel programming theory, we created the cost-reliability-delay model (CRD model that consisted of two parts: the physical topology part aimed at obtaining the networks with the maximum reliability under constrained cost, while the logical topology part focused on the communication paths yielding minimum delay based on the physical topology delivered from upper level. We also suggested a method to solve the CRD model, which combined the genetic algorithm and the Floyd-Warshall algorithm. Finally, we used a practical example to verify the accuracy and the effectiveness of the CRD model and further applied the novel method on a train with six carriages.

  4. LAI inversion from optical reflectance using a neural network trained with a multiple scattering model

    Smith, James A.

    1992-01-01

    The inversion of the leaf area index (LAI) canopy parameter from optical spectral reflectance measurements is obtained using a backpropagation artificial neural network trained using input-output pairs generated by a multiple scattering reflectance model. The problem of LAI estimation over sparse canopies (LAI 1000 percent for low LAI. Minimization methods applied to merit functions constructed from differences between measured reflectances and predicted reflectances using multiple-scattering models are unacceptably sensitive to a good initial guess for the desired parameter. In contrast, the neural network reported generally yields absolute percentage errors of <30 percent when weighting coefficients trained on one soil type were applied to predicted canopy reflectance at a different soil background.

  5. An approach to unfold the response of a multi-element system using an artificial neural network

    Cordes, E.; Fehrenbacher, G.; Schuetz, R.; Sprunck, M.; Hahn, K.; Hofmann, R.; Wahl, W.

    1998-01-01

    An unfolding procedure is proposed which aims at obtaining spectral information of a neutron radiation field by the analysis of the response of a multi-element system consisting of converter type semiconductors. For the unfolding procedure an artificial neural network (feed forward network), trained by the back-propagation method, was used. The response functions of the single elements to neutron radiation were calculated by application of a computational model for an energy range from 10 -2 eV to 10 MeV. The training of the artificial neural network was based on the computation of responses of a six-element system for a set of 300 neutron spectra and the application of the back-propagation method. The validation was performed by the unfolding of 100 computed responses. Two unfolding examples were pointed out for the determination of the neutron spectra. The spectra resulting from the unfolding procedure agree well with the original spectra used for the response computation

  6. Planning Training Loads for the 400 M Hurdles in Three-Month Mesocycles using Artificial Neural Networks.

    Przednowek, Krzysztof; Iskra, Janusz; Wiktorowicz, Krzysztof; Krzeszowski, Tomasz; Maszczyk, Adam

    2017-12-01

    This paper presents a novel approach to planning training loads in hurdling using artificial neural networks. The neural models performed the task of generating loads for athletes' training for the 400 meters hurdles. All the models were calculated based on the training data of 21 Polish National Team hurdlers, aged 22.25 ± 1.96, competing between 1989 and 2012. The analysis included 144 training plans that represented different stages in the annual training cycle. The main contribution of this paper is to develop neural models for planning training loads for the entire career of a typical hurdler. In the models, 29 variables were used, where four characterized the runner and 25 described the training process. Two artificial neural networks were used: a multi-layer perceptron and a network with radial basis functions. To assess the quality of the models, the leave-one-out cross-validation method was used in which the Normalized Root Mean Squared Error was calculated. The analysis shows that the method generating the smallest error was the radial basis function network with nine neurons in the hidden layer. Most of the calculated training loads demonstrated a non-linear relationship across the entire competitive period. The resulting model can be used as a tool to assist a coach in planning training loads during a selected training period.

  7. Planning Training Loads for The 400 M Hurdles in Three-Month Mesocycles Using Artificial Neural Networks

    Przednowek Krzysztof

    2017-12-01

    Full Text Available This paper presents a novel approach to planning training loads in hurdling using artificial neural networks. The neural models performed the task of generating loads for athletes’ training for the 400 meters hurdles. All the models were calculated based on the training data of 21 Polish National Team hurdlers, aged 22.25 ± 1.96, competing between 1989 and 2012. The analysis included 144 training plans that represented different stages in the annual training cycle. The main contribution of this paper is to develop neural models for planning training loads for the entire career of a typical hurdler. In the models, 29 variables were used, where four characterized the runner and 25 described the training process. Two artificial neural networks were used: a multi-layer perceptron and a network with radial basis functions. To assess the quality of the models, the leave-one-out cross-validation method was used in which the Normalized Root Mean Squared Error was calculated. The analysis shows that the method generating the smallest error was the radial basis function network with nine neurons in the hidden layer. Most of the calculated training loads demonstrated a non-linear relationship across the entire competitive period. The resulting model can be used as a tool to assist a coach in planning training loads during a selected training period.

  8. Consumer Perceptions About Pilot Training: An Emotional Response

    Rosser, Timothy G.

    Civilian pilot training has followed a traditional path for several decades. With a potential pilot shortage approaching, ICAO proposed a new paradigm in pilot training methodology called the Multi-Crew Pilot License. This new methodology puts a pilot in the cockpit of an airliner with significantly less flight time experience than the traditional methodology. The purpose of this study was to determine to what extent gender, country of origin and pilot training methodology effect an aviation consumer's willingness to fly. Additionally, this study attempted to determine what emotions mediate a consumer's decision. This study surveyed participants from India and the United States to measure their willingness to fly using the Willingness to Fly Scale shown to be valid and reliable by Rice et al. (2015). The scale uses a five point Likert-type scale. In order to determine the mediating emotions, Ekman and Friesen's (1979) universal emotions, which are happiness, surprise, fear, disgust, anger, and sadness were used. Data were analyzed using SPSS. Descriptive statistics are provided for respondent's age and willingness to fly values. An ANOVA was conducted to test the first four hypotheses and Hayes (2004, 2008) bootstrapping process was used for the mediation analysis. Results indicated a significant main effect for training, F(1,972) = 227.76, p . .001, etap 2 = 0.190, country of origin, F(1, 972) = 28.86, p relationship between training and country of origin, and training. The findings of this study are important to designers of MPL training programs and airline marketers.

  9. Optimal Parameter for the Training of Multilayer Perceptron Neural Networks by Using Hierarchical Genetic Algorithm

    Orozco-Monteagudo, Maykel; Taboada-Crispi, Alberto; Gutierrez-Hernandez, Liliana

    2008-01-01

    This paper deals with the controversial topic of the selection of the parameters of a genetic algorithm, in this case hierarchical, used for training of multilayer perceptron neural networks for the binary classification. The parameters to select are the crossover and mutation probabilities of the control and parametric genes and the permanency percent. The results can be considered as a guide for using this kind of algorithm.

  10. Individual Channel Estimation in a Diamond Relay Network Using Relay-Assisted Training

    Xianwen He

    2017-01-01

    Full Text Available We consider the training design and channel estimation in the amplify-and-forward (AF diamond relay network. Our strategy is to transmit the source training in time-multiplexing (TM mode while each relay node superimposes its own relay training over the amplified received data signal without bandwidth expansion. The principal challenge is to obtain accurate channel state information (CSI of second-hop link due to the multiaccess interference (MAI and cooperative data interference (CDI. To maintain the orthogonality between data and training, a modified relay-assisted training scheme is proposed to migrate the CDI, where some of the cooperative data at the relay are discarded to accommodate relay training. Meanwhile, a couple of optimal zero-correlation zone (ZCZ relay-assisted sequences are designed to avoid MAI. At the destination node, the received signals from the two relay nodes are combined to achieve spatial diversity and enhanced data reliability. The simulation results are presented to validate the performance of the proposed schemes.

  11. Project plan, Hazardous Materials Management and Emergency Response Training Center: Project 95L-EWT-100

    Borgeson, M.E.

    1994-01-01

    The Hazardous Materials Management and Emergency Response (HAMMER) Training Center will provide for classroom lectures and hands-on practical training in realistic situations for workers and emergency responders who are tasked with handling and cleanup of toxic substances. The primary objective of the HAMMER project is to provide hands-on training and classroom facilities for hazardous material workers and emergency responders. This project will also contribute towards complying with the planning and training provisions of recent legislation. In March 1989 Title 29 Code of Federal Regulations Occupational Safety and Health Administration 1910 Rules and National Fire Protection Association Standard 472 defined professional requirements for responders to hazardous materials incidents. Two general types of training are addressed for hazardous materials: training for hazardous waste site workers and managers, and training for emergency response organizations

  12. A simulation training evaluation method for distribution network fault based on radar chart

    Yuhang Xu

    2018-01-01

    Full Text Available In order to solve the problem of automatic evaluation of dispatcher fault simulation training in distribution network, a simulation training evaluation method based on radar chart for distribution network fault is proposed. The fault handling information matrix is established to record the dispatcher fault handling operation sequence and operation information. The four situations of the dispatcher fault isolation operation are analyzed. The fault handling anti-misoperation rule set is established to describe the rules prohibiting dispatcher operation. Based on the idea of artificial intelligence reasoning, the feasibility of dispatcher fault handling is described by the feasibility index. The relevant factors and evaluation methods are discussed from the three aspects of the fault handling result feasibility, the anti-misoperation correctness and the operation process conciseness. The detailed calculation formula is given. Combining the independence and correlation between the three evaluation angles, a comprehensive evaluation method of distribution network fault simulation training based on radar chart is proposed. The method can comprehensively reflect the fault handling process of dispatchers, and comprehensively evaluate the fault handling process from various angles, which has good practical value.

  13. Locomotor Training and Strength and Balance Exercises for Walking Recovery After Stroke: Response to Number of Training Sessions.

    Rose, Dorian K; Nadeau, Stephen E; Wu, Samuel S; Tilson, Julie K; Dobkin, Bruce H; Pei, Qinglin; Duncan, Pamela W

    2017-11-01

    Evidence-based guidelines are needed to inform rehabilitation practice, including the effect of number of exercise training sessions on recovery of walking ability after stroke. The objective of this study was to determine the response to increasing number of training sessions of 2 interventions-locomotor training and strength and balance exercises-on poststroke walking recovery. This is a secondary analysis of the Locomotor Experience Applied Post-Stroke (LEAPS) randomized controlled trial. Six rehabilitation sites in California and Florida and participants' homes were used. Participants were adults who dwelled in the community (N=347), had had a stroke, were able to walk at least 3 m (10 ft) with assistance, and had completed the required number of intervention sessions. Participants received 36 sessions (3 times per week for 12 weeks), 90 minutes in duration, of locomotor training (gait training on a treadmill with body-weight support and overground training) or strength and balance training. Talking speed, as measured by the 10-Meter Walk Test, and 6-minute walking distance were assessed before training and following 12, 24, and 36 intervention sessions. Participants at 2 and 6 months after stroke gained in gait speed and walking endurance after up to 36 sessions of treatment, but the rate of gain diminished steadily and, on average, was very low during the 25- to 36-session epoch, regardless of treatment type or severity of impairment. Results may not generalize to people who are unable to initiate a step at 2 months after stroke or people with severe cardiac disease. In general, people who dwelled in the community showed improvements in gait speed and walking distance with up to 36 sessions of locomotor training or strength and balance exercises at both 2 and 6 months after stroke. However, gains beyond 24 sessions tended to be very modest. The tracking of individual response trajectories is imperative in planning treatment. Published by Oxford University

  14. Modeling of an ionic polymer metal composite actuator based on an extended Kalman filter trained neural network

    Truong, Dinh Quang; Ahn, Kyoung Kwan

    2014-01-01

    An ion polymer metal composite (IPMC) is an electroactive polymer that bends in response to a small applied electric field as a result of mobility of cations in the polymer network and vice versa. This paper presents an innovative and accurate nonlinear black-box model (NBBM) for estimating the bending behavior of IPMC actuators. The model is constructed via a general multilayer perceptron neural network (GMLPNN) integrated with a smart learning mechanism (SLM) that is based on an extended Kalman filter with self-decoupling ability (SDEKF). Here the GMLPNN is built with an ability to autoadjust its structure based on its characteristic vector. Furthermore, by using the SLM based on the SDEKF, the GMLPNN parameters are optimized with small computational effort, and the modeling accuracy is improved. An apparatus employing an IPMC actuator is first set up to investigate the IPMC characteristics and to generate the data for training and validating the model. The advanced NBBM model for the IPMC system is then created with the proper inputs to estimate IPMC tip displacement. Next, the model is optimized using the SLM mechanism with the training data. Finally, the optimized NBBM model is verified with the validating data. A comparison between this model and the previously developed model is also carried out to prove the effectiveness of the proposed modeling technique. (paper)

  15. Dynamic response of a monorail steel bridge under a moving train

    Lee, C. H.; Kawatani, M.; Kim, C. W.; Nishimura, N.; Kobayashi, Y.

    2006-06-01

    This study proposes a dynamic response analysis procedure for traffic-induced vibration of a monorail bridge and train. Each car in the monorail train is idealized as a dynamic system of 15-degrees-of-freedom. The governing equations of motion for a three-dimensional monorail bridge-train interaction system are derived using Lagrange's formulation for monorail trains, and a finite-element method for modal analysis of monorail bridges. Analytical results on dynamic response of the monorail train and bridge are compared with field-test data in order to verify the validity of the proposed analysis procedure, and a positive correlation is found. An interesting feature of the monorail bridge response is that sway motion is caused by torsional behavior resulting from eccentricity between the shear center of the bridge section and the train load.

  16. Response of moose to a high‐density road network

    Wattles, David W.; Zeller, Katherine A.; DeStefano, Stephen

    2018-01-01

    Road networks and the disturbance associated with vehicle traffic alter animal behavior, movements, and habitat selection. The response of moose (Alces americanus) to roads has been documented in relatively rural areas, but less is known about moose response to roads in more highly roaded landscapes. We examined road‐crossing frequencies and habitat use of global positioning system (GPS)‐collared moose in Massachusetts, USA, where moose home ranges have road densities approximately twice that of previous studies. We compared seasonal road‐crossing frequencies of moose with a null movement model. We estimated moose travel speeds during road‐crossing events and compared them with speeds during other home range movements. To estimate the extent of the road effect zone and determine how roads influenced moose habitat use, we fit a third‐order resource selection function. With the exception of the lowest use road class (roads less than expected based on the null movement model and frequency decreased with increasing road size and traffic. Moose crossed roads faster than they traveled during other times. This effect increased with increasing road use intensity. Overall, roads were a major factor determining what portions of Massachusetts moose used and how they moved among habitat patches. Our results suggest that moose in Massachusetts can adapt to a high‐density road network, but the road effect is still strongly negative and, in some cases, is more pronounced than in study areas with lower road densities. Future road construction and the expansion of road networks may have a large effect on moose and other wildlife.

  17. Impact of real-time fMRI working memory feedback training on the interactions between three core brain networks.

    Zhang, Qiushi; Zhang, Gaoyan; Yao, Li; Zhao, Xiaojie

    2015-01-01

    Working memory (WM) refers to the temporary holding and manipulation of information during the performance of a range of cognitive tasks, and WM training is a promising method for improving an individual's cognitive functions. Our previous work demonstrated that WM performance can be improved through self-regulation of dorsal lateral prefrontal cortex (PFC) activation using real-time functional magnetic resonance imaging (rtfMRI), which enables individuals to control local brain activities volitionally according to the neurofeedback. Furthermore, research concerning large-scale brain networks has demonstrated that WM training requires the engagement of several networks, including the central executive network (CEN), the default mode network (DMN) and the salience network (SN), and functional connectivity within the CEN and DMN can be changed by WM training. Although a switching role of the SN between the CEN and DMN has been demonstrated, it remains unclear whether WM training can affect the interactions between the three networks and whether a similar mechanism also exists during the training process. In this study, we investigated the dynamic functional connectivity between the three networks during the rtfMRI feedback training using independent component analysis (ICA) and correlation analysis. The results indicated that functional connectivity within and between the three networks were significantly enhanced by feedback training, and most of the changes were associated with the insula and correlated with behavioral improvements. These findings suggest that the insula plays a critical role in the reorganization of functional connectivity among the three networks induced by rtfMRI training and in WM performance, thus providing new insights into the mechanisms of high-level functions and the clinical treatment of related functional impairments.

  18. Wind power forecast using wavelet neural network trained by improved Clonal selection algorithm

    Chitsaz, Hamed; Amjady, Nima; Zareipour, Hamidreza

    2015-01-01

    Highlights: • Presenting a Morlet wavelet neural network for wind power forecasting. • Proposing improved Clonal selection algorithm for training the model. • Applying Maximum Correntropy Criterion to evaluate the training performance. • Extensive testing of the proposed wind power forecast method on real-world data. - Abstract: With the integration of wind farms into electric power grids, an accurate wind power prediction is becoming increasingly important for the operation of these power plants. In this paper, a new forecasting engine for wind power prediction is proposed. The proposed engine has the structure of Wavelet Neural Network (WNN) with the activation functions of the hidden neurons constructed based on multi-dimensional Morlet wavelets. This forecast engine is trained by a new improved Clonal selection algorithm, which optimizes the free parameters of the WNN for wind power prediction. Furthermore, Maximum Correntropy Criterion (MCC) has been utilized instead of Mean Squared Error as the error measure in training phase of the forecasting model. The proposed wind power forecaster is tested with real-world hourly data of system level wind power generation in Alberta, Canada. In order to demonstrate the efficiency of the proposed method, it is compared with several other wind power forecast techniques. The obtained results confirm the validity of the developed approach

  19. A pre-trained convolutional neural network based method for thyroid nodule diagnosis.

    Ma, Jinlian; Wu, Fa; Zhu, Jiang; Xu, Dong; Kong, Dexing

    2017-01-01

    In ultrasound images, most thyroid nodules are in heterogeneous appearances with various internal components and also have vague boundaries, so it is difficult for physicians to discriminate malignant thyroid nodules from benign ones. In this study, we propose a hybrid method for thyroid nodule diagnosis, which is a fusion of two pre-trained convolutional neural networks (CNNs) with different convolutional layers and fully-connected layers. Firstly, the two networks pre-trained with ImageNet database are separately trained. Secondly, we fuse feature maps learned by trained convolutional filters, pooling and normalization operations of the two CNNs. Finally, with the fused feature maps, a softmax classifier is used to diagnose thyroid nodules. The proposed method is validated on 15,000 ultrasound images collected from two local hospitals. Experiment results show that the proposed CNN based methods can accurately and effectively diagnose thyroid nodules. In addition, the fusion of the two CNN based models lead to significant performance improvement, with an accuracy of 83.02%±0.72%. These demonstrate the potential clinical applications of this method. Copyright © 2016 Elsevier B.V. All rights reserved.

  20. Training Small Networks for Scene Classification of Remote Sensing Images via Knowledge Distillation

    Guanzhou Chen

    2018-05-01

    Full Text Available Scene classification, aiming to identify the land-cover categories of remotely sensed image patches, is now a fundamental task in the remote sensing image analysis field. Deep-learning-model-based algorithms are widely applied in scene classification and achieve remarkable performance, but these high-level methods are computationally expensive and time-consuming. Consequently in this paper, we introduce a knowledge distillation framework, currently a mainstream model compression method, into remote sensing scene classification to improve the performance of smaller and shallower network models. Our knowledge distillation training method makes the high-temperature softmax output of a small and shallow student model match the large and deep teacher model. In our experiments, we evaluate knowledge distillation training method for remote sensing scene classification on four public datasets: AID dataset, UCMerced dataset, NWPU-RESISC dataset, and EuroSAT dataset. Results show that our proposed training method was effective and increased overall accuracy (3% in AID experiments, 5% in UCMerced experiments, 1% in NWPU-RESISC and EuroSAT experiments for small and shallow models. We further explored the performance of the student model on small and unbalanced datasets. Our findings indicate that knowledge distillation can improve the performance of small network models on datasets with lower spatial resolution images, numerous categories, as well as fewer training samples.

  1. PARTICLE SWARM OPTIMIZATION (PSO FOR TRAINING OPTIMIZATION ON CONVOLUTIONAL NEURAL NETWORK (CNN

    Arie Rachmad Syulistyo

    2016-02-01

    Full Text Available Neural network attracts plenty of researchers lately. Substantial number of renowned universities have developed neural network for various both academically and industrially applications. Neural network shows considerable performance on various purposes. Nevertheless, for complex applications, neural network’s accuracy significantly deteriorates. To tackle the aforementioned drawback, lot of researches had been undertaken on the improvement of the standard neural network. One of the most promising modifications on standard neural network for complex applications is deep learning method. In this paper, we proposed the utilization of Particle Swarm Optimization (PSO in Convolutional Neural Networks (CNNs, which is one of the basic methods in deep learning. The use of PSO on the training process aims to optimize the results of the solution vectors on CNN in order to improve the recognition accuracy. The data used in this research is handwritten digit from MNIST. The experiments exhibited that the accuracy can be attained in 4 epoch is 95.08%. This result was better than the conventional CNN and DBN.  The execution time was also almost similar to the conventional CNN. Therefore, the proposed method was a promising method.

  2. A knowledge based system for training radiation emergency response personnel

    Kuriakose, K.K.; Peter, T.U.; Natarajan, A.

    1992-01-01

    One of the important aspects of radiation emergency preparedness is to impart training to emergency handling staff. Mock exercises are generally used for this purpose. But practical considerations limit the frequency of such exercises. A suitably designed computer software can be effectively used to impart training. With the advent of low cost personal computers, the frequency with which the training programme can be conducted is unlimited. A computer software with monotonic behaviour is inadequate for such training. It is necessary to provide human like tutoring capabilities. With the advances in knowledge based computer systems, it is possible to develop such a system. These systems have the capability of providing individualized training. This paper describes the development of such a system for training and evaluation of agencies associated with the management of radiation emergency. It also discusses the utility of the software as a general purpose tutor. The details required for the preparation of data files and knowledge base files are included. It uses a student model based on performance measures. The software is developed in C under MS-DOS. It uses a rule based expert system shell developed in C. The features of this shell are briefly described. (author). 5 refs

  3. Self-Consistent Scheme for Spike-Train Power Spectra in Heterogeneous Sparse Networks.

    Pena, Rodrigo F O; Vellmer, Sebastian; Bernardi, Davide; Roque, Antonio C; Lindner, Benjamin

    2018-01-01

    Recurrent networks of spiking neurons can be in an asynchronous state characterized by low or absent cross-correlations and spike statistics which resemble those of cortical neurons. Although spatial correlations are negligible in this state, neurons can show pronounced temporal correlations in their spike trains that can be quantified by the autocorrelation function or the spike-train power spectrum. Depending on cellular and network parameters, correlations display diverse patterns (ranging from simple refractory-period effects and stochastic oscillations to slow fluctuations) and it is generally not well-understood how these dependencies come about. Previous work has explored how the single-cell correlations in a homogeneous network (excitatory and inhibitory integrate-and-fire neurons with nearly balanced mean recurrent input) can be determined numerically from an iterative single-neuron simulation. Such a scheme is based on the fact that every neuron is driven by the network noise (i.e., the input currents from all its presynaptic partners) but also contributes to the network noise, leading to a self-consistency condition for the input and output spectra. Here we first extend this scheme to homogeneous networks with strong recurrent inhibition and a synaptic filter, in which instabilities of the previous scheme are avoided by an averaging procedure. We then extend the scheme to heterogeneous networks in which (i) different neural subpopulations (e.g., excitatory and inhibitory neurons) have different cellular or connectivity parameters; (ii) the number and strength of the input connections are random (Erdős-Rényi topology) and thus different among neurons. In all heterogeneous cases, neurons are lumped in different classes each of which is represented by a single neuron in the iterative scheme; in addition, we make a Gaussian approximation of the input current to the neuron. These approximations seem to be justified over a broad range of parameters as

  4. Self-Consistent Scheme for Spike-Train Power Spectra in Heterogeneous Sparse Networks

    Rodrigo F. O. Pena

    2018-03-01

    Full Text Available Recurrent networks of spiking neurons can be in an asynchronous state characterized by low or absent cross-correlations and spike statistics which resemble those of cortical neurons. Although spatial correlations are negligible in this state, neurons can show pronounced temporal correlations in their spike trains that can be quantified by the autocorrelation function or the spike-train power spectrum. Depending on cellular and network parameters, correlations display diverse patterns (ranging from simple refractory-period effects and stochastic oscillations to slow fluctuations and it is generally not well-understood how these dependencies come about. Previous work has explored how the single-cell correlations in a homogeneous network (excitatory and inhibitory integrate-and-fire neurons with nearly balanced mean recurrent input can be determined numerically from an iterative single-neuron simulation. Such a scheme is based on the fact that every neuron is driven by the network noise (i.e., the input currents from all its presynaptic partners but also contributes to the network noise, leading to a self-consistency condition for the input and output spectra. Here we first extend this scheme to homogeneous networks with strong recurrent inhibition and a synaptic filter, in which instabilities of the previous scheme are avoided by an averaging procedure. We then extend the scheme to heterogeneous networks in which (i different neural subpopulations (e.g., excitatory and inhibitory neurons have different cellular or connectivity parameters; (ii the number and strength of the input connections are random (Erdős-Rényi topology and thus different among neurons. In all heterogeneous cases, neurons are lumped in different classes each of which is represented by a single neuron in the iterative scheme; in addition, we make a Gaussian approximation of the input current to the neuron. These approximations seem to be justified over a broad range of

  5. THE INTERIM RESULTS AND THE WAYS TO IMPLEMENT THE PROGRAMS TEACHER TRAINING IN NETWORK FORM

    A. A. Tolsteneva

    2016-01-01

    Full Text Available The paper presents the results of approbation of new modules primary educational undergraduate specialties Group expanded education and pedagogy (training areas-economics, involving academic mobility of students of universities in terms of networking of Novosibirsk and Nizhny Novgorod pedagogical universities. The article describes the structure of established affiliate networks, conducted pedagogical and methodical analysis modules have passed testing, recommendations for improvement and suggested ways for the development of a modular approach to building educational programs in teacher education system. The implementation of educational modules require their integration into the curricula of the Nizhny Novgorod State Pedagogical University, with no loss of content, giving the existing curriculum structure saturation. Thus, it was achieved 100% consistency of curriculum, opening further opportunities for the implementation of educational programs in terms of networking.

  6. Project management plan, Hazardous Materials Management and Emergency Response Training Center

    Borgeson, M.E.

    1994-01-01

    For the next 30 years, the main activities at the Hanford Site will involve the handling and cleanup of toxic substances. Thousands of workers involved in these new activities will need systematic training appropriate to their tasks and associated risks. This project is an important part of the Hanford Site mission and will enable the US Department of Energy (DOE) to meet high standards for safety. The Hazardous Materials Management and Emergency Response Training Center (HAMMER) project will construct a centralized regional training center dedicated to training hazardous materials workers and emergency responders in classrooms and with hands-on, realistic training aids representing actual field conditions. The HAMMER Training Center will provide a cost-effective, high-quality way to meet the Hanford Site training needs. The training center creates a partnership among DOE; government contractors; labor; local, state, and tribal governments; and selected institutions of higher education

  7. Aggression prevention training for student nurses: differential responses to training and the interaction between theory and practice.

    Beech, Bernard

    2008-03-01

    Workplace violence is of great concern to all health care professionals. Nurses are major targets for incidents of violence, with student nurses being clearly recognised as a high-risk sub-group. Training is widely advocated as the appropriate organisational response but the effects and effectiveness of training are inadequately studied. A recently completed Ph.D study used a longitudinal research design to evaluate the effects of a three-day 'aggression prevention and management training programme' on various learning domains of three cohorts of UK student nurses destined for adult, child, mental health and learning disability specialities [N=243] in their first year of nurse training. A purpose-designed questionnaire was used to collect data on knowledge, attitudes, confidence, and self-assessed competence at four time points, two before and two following the educational input. This paper focuses on the differences detected in student nurses' responses to different sections of the questionnaire, at various time points, in relation to recorded demographic variables, namely, their age, gender, destined speciality, and previous relevant training experience. It also considers the 'interaction' between theoretical preparation and clinical practice. These finding may also have wider relevance to skills training and understanding of the reality of student nurse experience in clinical settings.

  8. A Simple Network Architecture Accounts for Diverse Reward Time Responses in Primary Visual Cortex.

    Huertas, Marco A; Hussain Shuler, Marshall G; Shouval, Harel Z

    2015-09-16

    Many actions performed by animals and humans depend on an ability to learn, estimate, and produce temporal intervals of behavioral relevance. Exemplifying such learning of cued expectancies is the observation of reward-timing activity in the primary visual cortex (V1) of rodents, wherein neural responses to visual cues come to predict the time of future reward as behaviorally experienced in the past. These reward-timing responses exhibit significant heterogeneity in at least three qualitatively distinct classes: sustained increase or sustained decrease in firing rate until the time of expected reward, and a class of cells that reach a peak in firing at the expected delay. We elaborate upon our existing model by including inhibitory and excitatory units while imposing simple connectivity rules to demonstrate what role these inhibitory elements and the simple architectures play in sculpting the response dynamics of the network. We find that simply adding inhibition is not sufficient for obtaining the different distinct response classes, and that a broad distribution of inhibitory projections is necessary for obtaining peak-type responses. Furthermore, although changes in connection strength that modulate the effects of inhibition onto excitatory units have a strong impact on the firing rate profile of these peaked responses, the network exhibits robustness in its overall ability to predict the expected time of reward. Finally, we demonstrate how the magnitude of expected reward can be encoded at the expected delay in the network and how peaked responses express this reward expectancy. Heterogeneity in single-neuron responses is a common feature of neuronal systems, although sometimes, in theoretical approaches, it is treated as a nuisance and seldom considered as conveying a different aspect of a signal. In this study, we focus on the heterogeneous responses in the primary visual cortex of rodents trained with a predictable delayed reward time. We describe under what

  9. Country-overlapping radiation protection education and training by the CHERNE network; Laenderuebergreifende Strahlenschutzausbildung im Rahmen des CHERNE-Netzwerks

    Hoyler, Frieder [Fachhochschule Aachen, Juelich (Germany). Strahlenschutzkursstaette

    2013-09-01

    The CHERNE network is promoting the cooperation between colleges and research facilities at the training of students. The article describes particular study courses in the field of radiation protection. (orig.)

  10. Co-trained convolutional neural networks for automated detection of prostate cancer in multi-parametric MRI.

    Yang, Xin; Liu, Chaoyue; Wang, Zhiwei; Yang, Jun; Min, Hung Le; Wang, Liang; Cheng, Kwang-Ting Tim

    2017-12-01

    Multi-parameter magnetic resonance imaging (mp-MRI) is increasingly popular for prostate cancer (PCa) detection and diagnosis. However, interpreting mp-MRI data which typically contains multiple unregistered 3D sequences, e.g. apparent diffusion coefficient (ADC) and T2-weighted (T2w) images, is time-consuming and demands special expertise, limiting its usage for large-scale PCa screening. Therefore, solutions to computer-aided detection of PCa in mp-MRI images are highly desirable. Most recent advances in automated methods for PCa detection employ a handcrafted feature based two-stage classification flow, i.e. voxel-level classification followed by a region-level classification. This work presents an automated PCa detection system which can concurrently identify the presence of PCa in an image and localize lesions based on deep convolutional neural network (CNN) features and a single-stage SVM classifier. Specifically, the developed co-trained CNNs consist of two parallel convolutional networks for ADC and T2w images respectively. Each network is trained using images of a single modality in a weakly-supervised manner by providing a set of prostate images with image-level labels indicating only the presence of PCa without priors of lesions' locations. Discriminative visual patterns of lesions can be learned effectively from clutters of prostate and surrounding tissues. A cancer response map with each pixel indicating the likelihood to be cancerous is explicitly generated at the last convolutional layer of the network for each modality. A new back-propagated error E is defined to enforce both optimized classification results and consistent cancer response maps for different modalities, which help capture highly representative PCa-relevant features during the CNN feature learning process. The CNN features of each modality are concatenated and fed into a SVM classifier. For images which are classified to contain cancers, non-maximum suppression and adaptive

  11. Circulating adiponectin concentration and body composition are altered in response to high-intensity interval training.

    Shing, Cecilia M; Webb, Jessica J; Driller, Matthew W; Williams, Andrew D; Fell, James W

    2013-08-01

    Adiponectin influences metabolic adaptations that would prove beneficial to endurance athletes, and yet to date there is little known about the response of adiponectin concentrations to exercise, and, in particular, the response of this hormone to training in an athlete population. This study aimed to determine the response of plasma adiponectin concentrations to acute exercise after 2 different training programs and to determine the influence of the training on body composition. Seven state-level representative rowers (age: 19 ± 1.2 years [mean ± SD], height: 1.77 ± 0.10 m, body mass: 74.0 ± 10.7 kg, VO2peak 62.1 ± 7.0 ml·kg·min) participated in the double-blind, randomized crossover investigation. Rowers performed an incremental graded exercise test before and after completing 4 weeks of high-intensity interval ergometer training and 4 weeks of traditional ergometer rowing training. Rowers' body composition was assessed at baseline and after each training program. Significant increases in plasma adiponectin concentration occurred in response to maximal exercise after completion of the high-intensity interval training (p = 0.016) but not after traditional ergometer rowing training (p = 0.69). The high-intensity interval training also resulted in significant increases in mean 4-minute power output (p = 0.002) and VO2peak (p = 0.05), and a decrease in body fat percentage (p = 0.022). Mean 4-minute power output, VO2peak, and body fat percentage were not significantly different after 4 weeks of traditional ergometer rowing training (p > 0.05). Four weeks of high-intensity interval training is associated with an increase in adiponectin concentration in response to maximal exercise and a reduction in body fat percentage. The potential for changes in adiponectin concentration to reflect positive training adaptations and athlete performance level should be further explored.

  12. Individual responses to combined endurance and strength training in older adults.

    Karavirta, Laura; Häkkinen, Keijo; Kauhanen, Antti; Arija-Blázquez, Alfredo; Sillanpää, Elina; Rinkinen, Niina; Häkkinen, Arja

    2011-03-01

    A combination of endurance and strength training is generally used to seek further health benefits or enhanced physical performance in older adults compared with either of the training modes alone. The mean change within a training group, however, may conceal a wide range of individual differences in the responses. The purpose, therefore, was to examine the individual trainability of aerobic capacity and maximal strength, when endurance and strength training are performed separately or concurrently. For this study, 175 previously untrained volunteers, 89 men and 86 women between the ages of 40 and 67 yr, completed a 21-wk period of either strength training (S) twice a week, endurance training (E) twice a week, combined training (ES) four times per week, or served as controls. Training adaptations were quantified as peak oxygen uptake (VO2peak) in a bicycle ergometer test to exhaustion and maximal isometric bilateral leg extension force (MVC) in a dynamometer. A large range in training responses, similar to endurance or strength training alone, was also observed with combined endurance and strength training in both ΔVO2peak (from -8% to 42%) and ΔMVC (from -12% to 87%). There were no significant correlations between the training responses in VO2peak and MVC in the E, S, or especially in the ES group, suggesting that the same subjects did not systematically increase both aerobic capacity and maximal strength. The goal of combined endurance and strength training--increasing both aerobic capacity and maximal strength simultaneously--was only achieved by some of the older subjects. New means are needed to personalize endurance, strength, and especially combined endurance and strength training programs for optimal individual adaptations.

  13. Temporal evolution of brain reorganization under cross-modal training: insights into the functional architecture of encoding and retrieval networks

    Likova, Lora T.

    2015-03-01

    This study is based on the recent discovery of massive and well-structured cross-modal memory activation generated in the primary visual cortex (V1) of totally blind people as a result of novel training in drawing without any vision (Likova, 2012). This unexpected functional reorganization of primary visual cortex was obtained after undergoing only a week of training by the novel Cognitive-Kinesthetic Method, and was consistent across pilot groups of different categories of visual deprivation: congenitally blind, late-onset blind and blindfolded (Likova, 2014). These findings led us to implicate V1 as the implementation of the theoretical visuo-spatial 'sketchpad' for working memory in the human brain. Since neither the source nor the subsequent 'recipient' of this non-visual memory information in V1 is known, these results raise a number of important questions about the underlying functional organization of the respective encoding and retrieval networks in the brain. To address these questions, an individual totally blind from birth was given a week of Cognitive-Kinesthetic training, accompanied by functional magnetic resonance imaging (fMRI) both before and just after training, and again after a two-month consolidation period. The results revealed a remarkable temporal sequence of training-based response reorganization in both the hippocampal complex and the temporal-lobe object processing hierarchy over the prolonged consolidation period. In particular, a pattern of profound learning-based transformations in the hippocampus was strongly reflected in V1, with the retrieval function showing massive growth as result of the Cognitive-Kinesthetic memory training and consolidation, while the initially strong hippocampal response during tactile exploration and encoding became non-existent. Furthermore, after training, an alternating patch structure in the form of a cascade of discrete ventral regions underwent radical transformations to reach complete functional

  14. Combined Ozone Retrieval From METOP Sensors Using META-Training Of Deep Neural Networks

    Felder, Martin; Sehnke, Frank; Kaifel, Anton

    2013-12-01

    The newest installment of our well-proven Neural Net- work Ozone Retrieval System (NNORSY) combines the METOP sensors GOME-2 and IASI with cloud information from AVHRR. Through the use of advanced meta- learning techniques like automatic feature selection and automatic architecture search applied to a set of deep neural networks, having at least two or three hidden layers, we have been able to avoid many technical issues normally encountered during the construction of such a joint retrieval system. This has been made possible by harnessing the processing power of modern consumer graphics cards with high performance graphic processors (GPU), which decreases training times by about two orders of magnitude. The system was trained on data from 2009 and 2010, including target ozone profiles from ozone sondes, ACE- FTS and MLS-AURA. To make maximum use of tropospheric information in the spectra, the data were partitioned into several sets of different cloud fraction ranges with the GOME-2 FOV, on which specialized retrieval networks are being trained. For the final ozone retrieval processing the different specialized networks are combined. The resulting retrieval system is very stable and does not show any systematic dependence on solar zenith angle, scan angle or sensor degradation. We present several sensitivity studies with regard to cloud fraction and target sensor type, as well as the performance in several latitude bands and with respect to independent validation stations. A visual cross-comparison against high-resolution ozone profiles from the KNMI EUMETSAT Ozone SAF product has also been performed and shows some distinctive features which we will briefly discuss. Overall, we demonstrate that a complex retrieval system can now be constructed with a minimum of ma- chine learning knowledge, using automated algorithms for many design decisions previously requiring expert knowledge. Provided sufficient training data and computation power of GPUs is available, the

  15. MONITORING TRAINING LOADS, STRESS, IMMUNE-ENDOCRINE RESPONSES AND PERFORMANCE IN TENNIS PLAYERS

    Rodrigo Vitasovic Gomes

    2013-06-01

    Full Text Available The study aim was to investigate the effect of a periodised pre-season training plan on internal training load and subsequent stress tolerance, immune-endocrine responses and physical performance in tennis players. Well-trained young tennis players (n = 10 were monitored across the pre-season period, which was divided into 4 weeks of progressive overloading training and a 1-week tapering period. Weekly measures of internal training load, training monotony and stress tolerance (sources and symptoms of stress were taken, along with salivary testosterone, cortisol and immunoglobulin A. One repetition maximum strength, running endurance, jump height and agility were assessed before and after training. The periodised training plan led to significant weekly changes in training loads (i.e. increasing in weeks 3 and 4, decreasing in week 5 and post-training improvements in strength, endurance and agility (P < 0.05. Cortisol concentration and the symptoms of stress also increased in weeks 3 and/or 4, before returning to baseline in week 5 (P < 0.05. Conversely, the testosterone to cortisol ratio decreased in weeks 3 and 4, before returning to baseline in week 5 (P < 0.05. In conclusion, the training plan evoked adaptive changes in stress tolerance and hormonal responses, which may have mediated the improvements in physical performance.

  16. Evaluation of tactical training in team handball by means of artificial neural networks.

    Hassan, Amr; Schrapf, Norbert; Ramadan, Wael; Tilp, Markus

    2017-04-01

    While tactical performance in competition has been analysed extensively, the assessment of training processes of tactical behaviour has rather been neglected in the literature. Therefore, the purpose of this study is to provide a methodology to assess the acquisition and implementation of offensive tactical behaviour in team handball. The use of game analysis software combined with an artificial neural network (ANN) software enabled identifying tactical target patterns from high level junior players based on their positions during offensive actions. These patterns were then trained by an amateur junior handball team (n = 14, 17 (0.5) years)). Following 6 weeks of tactical training an exhibition game was performed where the players were advised to use the target patterns as often as possible. Subsequently, the position data of the game was analysed with an ANN. The test revealed that 58% of the played patterns could be related to the trained target patterns. The similarity between executed patterns and target patterns was assessed by calculating the mean distance between key positions of the players in the game and the target pattern which was 0.49 (0.20) m. In summary, the presented method appears to be a valid instrument to assess tactical training.

  17. QoS-Aware Resource Allocation for Network Virtualization in an Integrated Train Ground Communication System

    Li Zhu

    2018-01-01

    Full Text Available Urban rail transit plays an increasingly important role in urbanization processes. Communications-Based Train Control (CBTC Systems, Passenger Information Systems (PIS, and Closed Circuit Television (CCTV are key applications of urban rail transit to ensure its normal operation. In existing urban rail transit systems, different applications are deployed with independent train ground communication systems. When the train ground communication systems are built repeatedly, limited wireless spectrum will be wasted, and the maintenance work will also become complicated. In this paper, we design a network virtualization based integrated train ground communication system, in which all the applications in urban rail transit can share the same physical infrastructure. In order to better satisfy the Quality of Service (QoS requirement of each application, this paper proposes a virtual resource allocation algorithm based on QoS guarantee, base station load balance, and application station fairness. Moreover, with the latest achievement of distributed convex optimization, we exploit a novel distributed optimization method based on alternating direction method of multipliers (ADMM to solve the virtual resource allocation problem. Extensive simulation results indicate that the QoS of the designed integrated train ground communication system can be improved significantly using the proposed algorithm.

  18. Training Working Memory in Childhood Enhances Coupling between Frontoparietal Control Network and Task-Related Regions.

    Barnes, Jessica J; Nobre, Anna Christina; Woolrich, Mark W; Baker, Kate; Astle, Duncan E

    2016-08-24

    Working memory is a capacity upon which many everyday tasks depend and which constrains a child's educational progress. We show that a child's working memory can be significantly enhanced by intensive computer-based training, relative to a placebo control intervention, in terms of both standardized assessments of working memory and performance on a working memory task performed in a magnetoencephalography scanner. Neurophysiologically, we identified significantly increased cross-frequency phase amplitude coupling in children who completed training. Following training, the coupling between the upper alpha rhythm (at 16 Hz), recorded in superior frontal and parietal cortex, became significantly coupled with high gamma activity (at ∼90 Hz) in inferior temporal cortex. This altered neural network activity associated with cognitive skill enhancement is consistent with a framework in which slower cortical rhythms enable the dynamic regulation of higher-frequency oscillatory activity related to task-related cognitive processes. Whether we can enhance cognitive abilities through intensive training is one of the most controversial topics of cognitive psychology in recent years. This is particularly controversial in childhood, where aspects of cognition, such as working memory, are closely related to school success and are implicated in numerous developmental disorders. We provide the first neurophysiological account of how working memory training may enhance ability in childhood, using a brain recording technique called magnetoencephalography. We borrowed an analysis approach previously used with intracranial recordings in adults, or more typically in other animal models, called "phase amplitude coupling." Copyright © 2016 Barnes et al.

  19. Modeling the dynamics of the lead bismuth eutectic experimental accelerator driven system by an infinite impulse response locally recurrent neural network

    Zio, Enrico; Pedroni, Nicola; Broggi, Matteo; Golea, Lucia Roxana

    2009-01-01

    In this paper, an infinite impulse response locally recurrent neural network (IIR-LRNN) is employed for modelling the dynamics of the Lead Bismuth Eutectic eXperimental Accelerator Driven System (LBE-XADS). The network is trained by recursive back-propagation (RBP) and its ability in estimating transients is tested under various conditions. The results demonstrate the robustness of the locally recurrent scheme in the reconstruction of complex nonlinear dynamic relationships

  20. Atomoxetine restores the response inhibition network in Parkinson's disease.

    Rae, Charlotte L; Nombela, Cristina; Rodríguez, Patricia Vázquez; Ye, Zheng; Hughes, Laura E; Jones, P Simon; Ham, Timothy; Rittman, Timothy; Coyle-Gilchrist, Ian; Regenthal, Ralf; Sahakian, Barbara J; Barker, Roger A; Robbins, Trevor W; Rowe, James B

    2016-08-01

    Parkinson's disease impairs the inhibition of responses, and whilst impulsivity is mild for some patients, severe impulse control disorders affect ∼10% of cases. Based on preclinical models we proposed that noradrenergic denervation contributes to the impairment of response inhibition, via changes in the prefrontal cortex and its subcortical connections. Previous work in Parkinson's disease found that the selective noradrenaline reuptake inhibitor atomoxetine could improve response inhibition, gambling decisions and reflection impulsivity. Here we tested the hypotheses that atomoxetine can restore functional brain networks for response inhibition in Parkinson's disease, and that both structural and functional connectivity determine the behavioural effect. In a randomized, double-blind placebo-controlled crossover study, 19 patients with mild-to-moderate idiopathic Parkinson's disease underwent functional magnetic resonance imaging during a stop-signal task, while on their usual dopaminergic therapy. Patients received 40 mg atomoxetine or placebo, orally. This regimen anticipates that noradrenergic therapies for behavioural symptoms would be adjunctive to, not a replacement for, dopaminergic therapy. Twenty matched control participants provided normative data. Arterial spin labelling identified no significant changes in regional perfusion. We assessed functional interactions between key frontal and subcortical brain areas for response inhibition, by comparing 20 dynamic causal models of the response inhibition network, inverted to the functional magnetic resonance imaging data and compared using random effects model selection. We found that the normal interaction between pre-supplementary motor cortex and the inferior frontal gyrus was absent in Parkinson's disease patients on placebo (despite dopaminergic therapy), but this connection was restored by atomoxetine. The behavioural change in response inhibition (improvement indicated by reduced stop-signal reaction

  1. Dose response relationship in anti-stress gene regulatory networks.

    Zhang, Qiang; Andersen, Melvin E

    2007-03-02

    To maintain a stable intracellular environment, cells utilize complex and specialized defense systems against a variety of external perturbations, such as electrophilic stress, heat shock, and hypoxia, etc. Irrespective of the type of stress, many adaptive mechanisms contributing to cellular homeostasis appear to operate through gene regulatory networks that are organized into negative feedback loops. In general, the degree of deviation of the controlled variables, such as electrophiles, misfolded proteins, and O2, is first detected by specialized sensor molecules, then the signal is transduced to specific transcription factors. Transcription factors can regulate the expression of a suite of anti-stress genes, many of which encode enzymes functioning to counteract the perturbed variables. The objective of this study was to explore, using control theory and computational approaches, the theoretical basis that underlies the steady-state dose response relationship between cellular stressors and intracellular biochemical species (controlled variables, transcription factors, and gene products) in these gene regulatory networks. Our work indicated that the shape of dose response curves (linear, superlinear, or sublinear) depends on changes in the specific values of local response coefficients (gains) distributed in the feedback loop. Multimerization of anti-stress enzymes and transcription factors into homodimers, homotrimers, or even higher-order multimers, play a significant role in maintaining robust homeostasis. Moreover, our simulation noted that dose response curves for the controlled variables can transition sequentially through four distinct phases as stressor level increases: initial superlinear with lesser control, superlinear more highly controlled, linear uncontrolled, and sublinear catastrophic. Each phase relies on specific gain-changing events that come into play as stressor level increases. The low-dose region is intrinsically nonlinear, and depending on

  2. Dose response relationship in anti-stress gene regulatory networks.

    Qiang Zhang

    2007-03-01

    Full Text Available To maintain a stable intracellular environment, cells utilize complex and specialized defense systems against a variety of external perturbations, such as electrophilic stress, heat shock, and hypoxia, etc. Irrespective of the type of stress, many adaptive mechanisms contributing to cellular homeostasis appear to operate through gene regulatory networks that are organized into negative feedback loops. In general, the degree of deviation of the controlled variables, such as electrophiles, misfolded proteins, and O2, is first detected by specialized sensor molecules, then the signal is transduced to specific transcription factors. Transcription factors can regulate the expression of a suite of anti-stress genes, many of which encode enzymes functioning to counteract the perturbed variables. The objective of this study was to explore, using control theory and computational approaches, the theoretical basis that underlies the steady-state dose response relationship between cellular stressors and intracellular biochemical species (controlled variables, transcription factors, and gene products in these gene regulatory networks. Our work indicated that the shape of dose response curves (linear, superlinear, or sublinear depends on changes in the specific values of local response coefficients (gains distributed in the feedback loop. Multimerization of anti-stress enzymes and transcription factors into homodimers, homotrimers, or even higher-order multimers, play a significant role in maintaining robust homeostasis. Moreover, our simulation noted that dose response curves for the controlled variables can transition sequentially through four distinct phases as stressor level increases: initial superlinear with lesser control, superlinear more highly controlled, linear uncontrolled, and sublinear catastrophic. Each phase relies on specific gain-changing events that come into play as stressor level increases. The low-dose region is intrinsically nonlinear

  3. Description of load progression and pain response during progressive resistance training early after total hip arthroplasty

    Mikkelsen, Lone R; Petersen, Annemette K; Mechlenburg, Inger

    2016-01-01

    events during the initial four weeks of training. RESULTS: The majority of patients experienced only moderate hip pain during exercise (range in median across exercises and sessions: 5-35 mm Visual Analog Scale) and mild pain at rest (median: 1-18 mm Visual Analog Scale), both of which decreased over...... time ( p training load (67%-166 % across exercises, p training sessions, short term pain response (an increase >20 mm Visual Analog Scale) occurred in 13 patients in 24 training sessions. CONCLUSION: Progressive resistance......OBJECTIVE: To describe a progressive resistance training intervention implemented shortly after total hip arthroplasty, including a detailed description of load progression, pain response and adverse events to the training. DESIGN: Secondary analyses of data from the intervention group...

  4. A characterization of scale invariant responses in enzymatic networks.

    Maja Skataric

    Full Text Available An ubiquitous property of biological sensory systems is adaptation: a step increase in stimulus triggers an initial change in a biochemical or physiological response, followed by a more gradual relaxation toward a basal, pre-stimulus level. Adaptation helps maintain essential variables within acceptable bounds and allows organisms to readjust themselves to an optimum and non-saturating sensitivity range when faced with a prolonged change in their environment. Recently, it was shown theoretically and experimentally that many adapting systems, both at the organism and single-cell level, enjoy a remarkable additional feature: scale invariance, meaning that the initial, transient behavior remains (approximately the same even when the background signal level is scaled. In this work, we set out to investigate under what conditions a broadly used model of biochemical enzymatic networks will exhibit scale-invariant behavior. An exhaustive computational study led us to discover a new property of surprising simplicity and generality, uniform linearizations with fast output (ULFO, whose validity we show is both necessary and sufficient for scale invariance of three-node enzymatic networks (and sufficient for any number of nodes. Based on this study, we go on to develop a mathematical explanation of how ULFO results in scale invariance. Our work provides a surprisingly consistent, simple, and general framework for understanding this phenomenon, and results in concrete experimental predictions.

  5. New Roles, New Responsibilities: Examining Training Needs of Repository Staff

    Natasha Simons

    2012-05-01

    Full Text Available INTRODUCTION Institutional repositories play a critical role in the research lifecycle. Funding agencies are increasingly seeking an improved return on their investment in research. Repositories facilitate this process by providing storage of, and access to, institutional research outputs and, more recently, research data. While repositories are generally managed within the academic library, repository staff require different skills and knowledge compared with traditional library roles. This study reports on a survey of Australasian institutional repository staff to identify skills and knowledge sets. METHODS Institutional repository staff working at universities in Australia and New Zealand were invited to participate in an online survey which incorporated both open and closed-ended question types. RESULTS The survey found significant gaps in the current provision of formal training and coursework related to institutional repositories, which echoed findings in the United Kingdom, Italy, and the United States. DISCUSSION There is clearly a need for more and varied training opportunities for repository professionals. Repository work requires a specific set of skills that can be difficult to find and institutions will benefit from investing in training and ongoing development opportunities for repository staff. CONCLUSION The data from this study could be used to facilitate staff recruitment, development, training, and retention strategies.

  6. Awareness Training Program on Responsible Gambling for Casino Employees

    Giroux, Isabelle; Boutin, Claude; Ladouceur, Robert; Lachance, Stella; Dufour, Magali

    2008-01-01

    Over the last years, several comprehensive training programs for problem gambling have been developed and implemented in various casinos around the world. However, the efficacy of these programs has rarely been assessed and evaluated scientifically. A workshop called "Des gens qui font la difference" (People Making a Difference) was…

  7. Diminished hormonal responses to exercise in trained rats

    Galbo, H; Richter, Erik; Holst, J J

    1977-01-01

    Male rats (120 g) either were subjected to a 12-wk physical training program (T rats) or were sedentary controls (C rats). Subsequently the rats were killed at rest or after a 45- or 90-min forced swim. At rest, T rats had higher liver and muscle glycogen concentrations but lower plasma insulin...

  8. Back muscle response to sudden trunk loading can be modified by training among healthcare workers

    Pedersen, Mogens Theisen; Essendrop, Morten; Skotte, Jørgen H.

    2007-01-01

    Study Design. Experimental study of the effect of physical training on the reaction to sudden back loading. Objective. To investigate the effect and sustainability of "on the job training" on the reaction to sudden back loading among employees at a geriatric ward. Summary of Background Data...... of the trunk (stopping time). Data on the possibilities of a training-induced improvement in the reflex response among workers exposed to sudden trunk loading on the job are, however, nonexistent, and there is no evidence of long-term benefits, i.e., the sustainability of a positive training effect. Methods....... Available data suggest that a delayed muscle reflex response to sudden trunk loading may increase the risk of low back injuries. We have previously shown that training may alter the response to sudden trunk loading in healthy subjects and decrease the time elapsed until stopping of the forward movement...

  9. The effects of verbal information and approach-avoidance training on children's fear-related responses.

    Lester, Kathryn J; Lisk, Stephen C; Mikita, Nina; Mitchell, Sophie; Huijding, Jorg; Rinck, Mike; Field, Andy P

    2015-09-01

    This study examined the effects of verbal information and approach-avoidance training on fear-related cognitive and behavioural responses about novel animals. One hundred and sixty children (7-11 years) were randomly allocated to receive: a) positive verbal information about one novel animal and threat information about a second novel animal (verbal information condition); b) approach-avoidance training in which they repeatedly pushed away (avoid) or pulled closer (approach) pictures of the animals (approach-avoidance training), c) a combined condition in which verbal information was given prior to approach-avoidance training (verbal information + approach-avoidance training) and d) a combined condition in which approach-avoidance training was given prior to verbal information (approach-avoidance training + verbal information). Threat and positive information significantly increased and decreased fear beliefs and avoidance behaviour respectively. Approach-avoidance training was successful in training the desired behavioural responses but had limited effects on fear-related responses. Verbal information and both combined conditions resulted in significantly larger effects than approach-avoidance training. We found no evidence for an additive effect of these pathways. This study used a non-clinical sample and focused on novel animals rather than animals about which children already had experience or established fears. The study also compared positive information/approach with threat information/avoid training, limiting specific conclusions regarding the independent effects of these conditions. The present study finds little evidence in support of a possible causal role for behavioural response training in the aetiology of childhood fear. However, the provision of verbal information appears to be an important pathway involved in the aetiology of childhood fear. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

  10. Real-Time Surveillance in Emergencies Using the Early Warning Alert and Response Network.

    Cordes, Kristina M; Cookson, Susan T; Boyd, Andrew T; Hardy, Colleen; Malik, Mamunur Rahman; Mala, Peter; El Tahir, Khalid; Everard, Marthe; Jasiem, Mohamad; Husain, Farah

    2017-11-01

    Humanitarian emergencies often result in population displacement and increase the risk for transmission of communicable diseases. To address the increased risk for outbreaks during humanitarian emergencies, the World Health Organization developed the Early Warning Alert and Response Network (EWARN) for early detection of epidemic-prone diseases. The US Centers for Disease Control and Prevention has worked with the World Health Organization, ministries of health, and other partners to support EWARN through the implementation and evaluation of these systems and the development of standardized guidance. Although protocols have been developed for the implementation and evaluation of EWARN, a need persists for standardized training and additional guidance on supporting these systems remotely when access to affected areas is restricted. Continued collaboration between partners and the Centers for Disease Control and Prevention for surveillance during emergencies is necessary to strengthen capacity and support global health security.

  11. Working memory training in congenitally blind individuals results in an integration of occipital cortex in functional networks.

    Gudi-Mindermann, Helene; Rimmele, Johanna M; Nolte, Guido; Bruns, Patrick; Engel, Andreas K; Röder, Brigitte

    2018-08-01

    The functional relevance of crossmodal activation (e.g. auditory activation of occipital brain regions) in congenitally blind individuals is still not fully understood. The present study tested whether the occipital cortex of blind individuals is integrated into a challenged functional network. A working memory (WM) training over four sessions was implemented. Congenitally blind and matched sighted participants were adaptively trained with an n-back task employing either voices (auditory training) or tactile stimuli (tactile training). In addition, a minimally demanding 1-back task served as an active control condition. Power and functional connectivity of EEG activity evolving during the maintenance period of an auditory 2-back task were analyzed, run prior to and after the WM training. Modality-specific (following auditory training) and modality-independent WM training effects (following both auditory and tactile training) were assessed. Improvements in auditory WM were observed in all groups, and blind and sighted individuals did not differ in training gains. Auditory and tactile training of sighted participants led, relative to the active control group, to an increase in fronto-parietal theta-band power, suggesting a training-induced strengthening of the existing modality-independent WM network. No power effects were observed in the blind. Rather, after auditory training the blind showed a decrease in theta-band connectivity between central, parietal, and occipital electrodes compared to the blind tactile training and active control groups. Furthermore, in the blind auditory training increased beta-band connectivity between fronto-parietal, central and occipital electrodes. In the congenitally blind, these findings suggest a stronger integration of occipital areas into the auditory WM network. Copyright © 2018 Elsevier B.V. All rights reserved.

  12. Electricity price forecast using Combinatorial Neural Network trained by a new stochastic search method

    Abedinia, O.; Amjady, N.; Shafie-khah, M.; Catalão, J.P.S.

    2015-01-01

    Highlights: • Presenting a Combinatorial Neural Network. • Suggesting a new stochastic search method. • Adapting the suggested method as a training mechanism. • Proposing a new forecast strategy. • Testing the proposed strategy on real-world electricity markets. - Abstract: Electricity price forecast is key information for successful operation of electricity market participants. However, the time series of electricity price has nonlinear, non-stationary and volatile behaviour and so its forecast method should have high learning capability to extract the complex input/output mapping function of electricity price. In this paper, a Combinatorial Neural Network (CNN) based forecasting engine is proposed to predict the future values of price data. The CNN-based forecasting engine is equipped with a new training mechanism for optimizing the weights of the CNN. This training mechanism is based on an efficient stochastic search method, which is a modified version of chemical reaction optimization algorithm, giving high learning ability to the CNN. The proposed price forecast strategy is tested on the real-world electricity markets of Pennsylvania–New Jersey–Maryland (PJM) and mainland Spain and its obtained results are extensively compared with the results obtained from several other forecast methods. These comparisons illustrate effectiveness of the proposed strategy.

  13. Pre-trained convolutional neural networks as feature extractors for tuberculosis detection.

    Lopes, U K; Valiati, J F

    2017-10-01

    It is estimated that in 2015, approximately 1.8 million people infected by tuberculosis died, most of them in developing countries. Many of those deaths could have been prevented if the disease had been detected at an earlier stage, but the most advanced diagnosis methods are still cost prohibitive for mass adoption. One of the most popular tuberculosis diagnosis methods is the analysis of frontal thoracic radiographs; however, the impact of this method is diminished by the need for individual analysis of each radiography by properly trained radiologists. Significant research can be found on automating diagnosis by applying computational techniques to medical images, thereby eliminating the need for individual image analysis and greatly diminishing overall costs. In addition, recent improvements on deep learning accomplished excellent results classifying images on diverse domains, but its application for tuberculosis diagnosis remains limited. Thus, the focus of this work is to produce an investigation that will advance the research in the area, presenting three proposals to the application of pre-trained convolutional neural networks as feature extractors to detect the disease. The proposals presented in this work are implemented and compared to the current literature. The obtained results are competitive with published works demonstrating the potential of pre-trained convolutional networks as medical image feature extractors. Copyright © 2017 Elsevier Ltd. All rights reserved.

  14. Deep learning quick reference useful hacks for training and optimizing deep neural networks with TensorFlow and Keras

    Bernico, Michael

    2018-01-01

    This book is a practical guide to applying deep neural networks including MLPs, CNNs, LSTMs, and more in Keras and TensorFlow. Packed with useful hacks to solve real-world challenges along with the supported math and theory around each topic, this book will be a quick reference for training and optimize your deep neural networks.

  15. Manifold absolute pressure estimation using neural network with hybrid training algorithm.

    Mohd Taufiq Muslim

    Full Text Available In a modern small gasoline engine fuel injection system, the load of the engine is estimated based on the measurement of the manifold absolute pressure (MAP sensor, which took place in the intake manifold. This paper present a more economical approach on estimating the MAP by using only the measurements of the throttle position and engine speed, resulting in lower implementation cost. The estimation was done via two-stage multilayer feed-forward neural network by combining Levenberg-Marquardt (LM algorithm, Bayesian Regularization (BR algorithm and Particle Swarm Optimization (PSO algorithm. Based on the results found in 20 runs, the second variant of the hybrid algorithm yields a better network performance than the first variant of hybrid algorithm, LM, LM with BR and PSO by estimating the MAP closely to the simulated MAP values. By using a valid experimental training data, the estimator network that trained with the second variant of the hybrid algorithm showed the best performance among other algorithms when used in an actual retrofit fuel injection system (RFIS. The performance of the estimator was also validated in steady-state and transient condition by showing a closer MAP estimation to the actual value.

  16. Training Deep Convolutional Neural Networks with Resistive Cross-Point Devices.

    Gokmen, Tayfun; Onen, Murat; Haensch, Wilfried

    2017-01-01

    In a previous work we have detailed the requirements for obtaining maximal deep learning performance benefit by implementing fully connected deep neural networks (DNN) in the form of arrays of resistive devices. Here we extend the concept of Resistive Processing Unit (RPU) devices to convolutional neural networks (CNNs). We show how to map the convolutional layers to fully connected RPU arrays such that the parallelism of the hardware can be fully utilized in all three cycles of the backpropagation algorithm. We find that the noise and bound limitations imposed by the analog nature of the computations performed on the arrays significantly affect the training accuracy of the CNNs. Noise and bound management techniques are presented that mitigate these problems without introducing any additional complexity in the analog circuits and that can be addressed by the digital circuits. In addition, we discuss digitally programmable update management and device variability reduction techniques that can be used selectively for some of the layers in a CNN. We show that a combination of all those techniques enables a successful application of the RPU concept for training CNNs. The techniques discussed here are more general and can be applied beyond CNN architectures and therefore enables applicability of the RPU approach to a large class of neural network architectures.

  17. Training Deep Convolutional Neural Networks with Resistive Cross-Point Devices

    Tayfun Gokmen

    2017-10-01

    Full Text Available In a previous work we have detailed the requirements for obtaining maximal deep learning performance benefit by implementing fully connected deep neural networks (DNN in the form of arrays of resistive devices. Here we extend the concept of Resistive Processing Unit (RPU devices to convolutional neural networks (CNNs. We show how to map the convolutional layers to fully connected RPU arrays such that the parallelism of the hardware can be fully utilized in all three cycles of the backpropagation algorithm. We find that the noise and bound limitations imposed by the analog nature of the computations performed on the arrays significantly affect the training accuracy of the CNNs. Noise and bound management techniques are presented that mitigate these problems without introducing any additional complexity in the analog circuits and that can be addressed by the digital circuits. In addition, we discuss digitally programmable update management and device variability reduction techniques that can be used selectively for some of the layers in a CNN. We show that a combination of all those techniques enables a successful application of the RPU concept for training CNNs. The techniques discussed here are more general and can be applied beyond CNN architectures and therefore enables applicability of the RPU approach to a large class of neural network architectures.

  18. EEG signal classification using PSO trained RBF neural network for epilepsy identification

    Sandeep Kumar Satapathy

    Full Text Available The electroencephalogram (EEG is a low amplitude signal generated in the brain, as a result of information flow during the communication of several neurons. Hence, careful analysis of these signals could be useful in understanding many human brain disorder diseases. One such disease topic is epileptic seizure identification, which can be identified via a classification process of the EEG signal after preprocessing with the discrete wavelet transform (DWT. To classify the EEG signal, we used a radial basis function neural network (RBFNN. As shown herein, the network can be trained to optimize the mean square error (MSE by using a modified particle swarm optimization (PSO algorithm. The key idea behind the modification of PSO is to introduce a method to overcome the problem of slow searching in and around the global optimum solution. The effectiveness of this procedure was verified by an experimental analysis on a benchmark dataset which is publicly available. The result of our experimental analysis revealed that the improvement in the algorithm is significant with respect to RBF trained by gradient descent and canonical PSO. Here, two classes of EEG signals were considered: the first being an epileptic and the other being non-epileptic. The proposed method produced a maximum accuracy of 99% as compared to the other techniques. Keywords: Electroencephalography, Radial basis function neural network, Particle swarm optimization, Discrete wavelet transform, Machine learning

  19. Training Deep Convolutional Neural Networks with Resistive Cross-Point Devices

    Gokmen, Tayfun; Onen, Murat; Haensch, Wilfried

    2017-01-01

    In a previous work we have detailed the requirements for obtaining maximal deep learning performance benefit by implementing fully connected deep neural networks (DNN) in the form of arrays of resistive devices. Here we extend the concept of Resistive Processing Unit (RPU) devices to convolutional neural networks (CNNs). We show how to map the convolutional layers to fully connected RPU arrays such that the parallelism of the hardware can be fully utilized in all three cycles of the backpropagation algorithm. We find that the noise and bound limitations imposed by the analog nature of the computations performed on the arrays significantly affect the training accuracy of the CNNs. Noise and bound management techniques are presented that mitigate these problems without introducing any additional complexity in the analog circuits and that can be addressed by the digital circuits. In addition, we discuss digitally programmable update management and device variability reduction techniques that can be used selectively for some of the layers in a CNN. We show that a combination of all those techniques enables a successful application of the RPU concept for training CNNs. The techniques discussed here are more general and can be applied beyond CNN architectures and therefore enables applicability of the RPU approach to a large class of neural network architectures. PMID:29066942

  20. Manifold absolute pressure estimation using neural network with hybrid training algorithm.

    Muslim, Mohd Taufiq; Selamat, Hazlina; Alimin, Ahmad Jais; Haniff, Mohamad Fadzli

    2017-01-01

    In a modern small gasoline engine fuel injection system, the load of the engine is estimated based on the measurement of the manifold absolute pressure (MAP) sensor, which took place in the intake manifold. This paper present a more economical approach on estimating the MAP by using only the measurements of the throttle position and engine speed, resulting in lower implementation cost. The estimation was done via two-stage multilayer feed-forward neural network by combining Levenberg-Marquardt (LM) algorithm, Bayesian Regularization (BR) algorithm and Particle Swarm Optimization (PSO) algorithm. Based on the results found in 20 runs, the second variant of the hybrid algorithm yields a better network performance than the first variant of hybrid algorithm, LM, LM with BR and PSO by estimating the MAP closely to the simulated MAP values. By using a valid experimental training data, the estimator network that trained with the second variant of the hybrid algorithm showed the best performance among other algorithms when used in an actual retrofit fuel injection system (RFIS). The performance of the estimator was also validated in steady-state and transient condition by showing a closer MAP estimation to the actual value.

  1. Two Methods of Interpersonal Skills Training; Conceptual- versus Response-Oriented Approaches.

    Bohart, Arthur C.; And Others

    1979-01-01

    Training people in warmth, empathy, and genuineness might fulfill a specific helping role and increase their general social comfort for others. By using conceptual and response-oriented approaches, authors show that training individuals to be effective counselors also helped them be more interpersonally effective. (Author/BEF)

  2. Cardiac hypertrophy and IGF-1 response to testosterone propionate treatment in trained male rats

    Żebrowska Aleksandra

    2017-04-01

    Full Text Available Several studies have suggested that testosterone exerts a growth-promoting effect in the heart. Limited data are available regarding interactions between possible endocrine/paracrine effects in response to exercise training. Therefore, we examined supraphysiological testosterone-induced heart hypertrophy and cardiac insulin-like growth factor (IGF-1 content in sedentary and exercise-trained rats.

  3. The effect of training on cardiovascular responses to arm exercise in individuals with tetraplegia

    Hopman, M T; Dallmeijer, A J; Snoek, G; van der Woude, L H

    1996-01-01

    The aim of this study was to investigate the physiological responses to maximal and submaximal arm-cranking exercise in 21 individuals with tetraplegia (TP) and to evaluate the effect of a 3 and 6-month training period (mean frequency of 1.5 h.week-1, mean intensity at 35% of the training time above

  4. Disaster Response Preparedness and Training: A Capabilities Assessment of the Asia Pacific Military Health Exchange

    2018-02-01

    responses revealed major themes of need for additional training in leadership /communication, austere/realistic training environment, interoperability...casualties. Since the military is best equipped to manage global operations, medical military members of the Indo-Asia Pacific nations initiated efforts...three previously separate medical, nursing, and leadership information exchanges into a single event. APHME was developed to foster information and

  5. 20 CFR 670.510 - Are Job Corps center operators responsible for providing all vocational training?

    2010-04-01

    ... 20 Employees' Benefits 3 2010-04-01 2010-04-01 false Are Job Corps center operators responsible for providing all vocational training? 670.510 Section 670.510 Employees' Benefits EMPLOYMENT AND TRAINING ADMINISTRATION, DEPARTMENT OF LABOR THE JOB CORPS UNDER TITLE I OF THE WORKFORCE INVESTMENT ACT...

  6. Acute LSD effects on response inhibition neural networks.

    Schmidt, A; Müller, F; Lenz, C; Dolder, P C; Schmid, Y; Zanchi, D; Lang, U E; Liechti, M E; Borgwardt, S

    2017-10-02

    Recent evidence shows that the serotonin 2A receptor (5-hydroxytryptamine2A receptor, 5-HT2AR) is critically involved in the formation of visual hallucinations and cognitive impairments in lysergic acid diethylamide (LSD)-induced states and neuropsychiatric diseases. However, the interaction between 5-HT2AR activation, cognitive impairments and visual hallucinations is still poorly understood. This study explored the effect of 5-HT2AR activation on response inhibition neural networks in healthy subjects by using LSD and further tested whether brain activation during response inhibition under LSD exposure was related to LSD-induced visual hallucinations. In a double-blind, randomized, placebo-controlled, cross-over study, LSD (100 µg) and placebo were administered to 18 healthy subjects. Response inhibition was assessed using a functional magnetic resonance imaging Go/No-Go task. LSD-induced visual hallucinations were measured using the 5 Dimensions of Altered States of Consciousness (5D-ASC) questionnaire. Relative to placebo, LSD administration impaired inhibitory performance and reduced brain activation in the right middle temporal gyrus, superior/middle/inferior frontal gyrus and anterior cingulate cortex and in the left superior frontal and postcentral gyrus and cerebellum. Parahippocampal activation during response inhibition was differently related to inhibitory performance after placebo and LSD administration. Finally, activation in the left superior frontal gyrus under LSD exposure was negatively related to LSD-induced cognitive impairments and visual imagery. Our findings show that 5-HT2AR activation by LSD leads to a hippocampal-prefrontal cortex-mediated breakdown of inhibitory processing, which might subsequently promote the formation of LSD-induced visual imageries. These findings help to better understand the neuropsychopharmacological mechanisms of visual hallucinations in LSD-induced states and neuropsychiatric disorders.

  7. "Living high - training low" vs. "living high - training high": erythropoietic responses and performance of adolescent cross-country skiers.

    Christoulas, K; Karamouzis, M; Mandroukas, K

    2011-03-01

    To determine and compare the erythropoietic response and exercise performance of adolescent cross-country skiers, as a result of "living high-training high" (HH) and "living high-training low" (HL). Nine female and six male adolescent cross-country skiers volunteered to participate in separate trials. In the first trial (HH), the skiers lived and trained for 21 days at 1550-2050 m, while in the second trial (HL) they trained near sea level (450-500 m) but resided at 1550 m. All participants underwent maximal cycle ergometer tests for the determination of VO2max and cardiorespiratory parameters via an open circuit system at sea level before ascent to altitude, and 1-2 days after descent from altitude. Blood samples were drawn prior to and immediately after maximal cycle exercise testing, at sea level prior to ascent, on days 1 (D1) and 21 (D21) at altitude (1740 m), and 1-2 days post-altitude, for the determination of serum erythropoietin (EPO) concentration, haemoglobin (Hb), hematocrit (Ht), and red blood cell (RBC) volume. The results showed that both boys and girls cross-country skiers, significantly improved their sea level VO2max after 21 days of living at moderate altitude and training near sea level. The present study demonstrates that living at moderate altitude, 1550-2050 m and training low, near sea level (450-500 m) significantly increases VO2max and RBC mass for both boys and girls. Results indicate that applying the training concept "living high - training low" in adolescent athletes may improve their endurance performance.

  8. Psychophysiological Responses to Group Exercise Training Sessions: Does Exercise Intensity Matter?

    Vandoni, Matteo; Codrons, Erwan; Marin, Luca; Correale, Luca; Bigliassi, Marcelo; Buzzachera, Cosme Franklim

    2016-01-01

    Group exercise training programs were introduced as a strategy for improving health and fitness and potentially reducing dropout rates. This study examined the psychophysiological responses to group exercise training sessions. Twenty-seven adults completed two group exercise training sessions of moderate and vigorous exercise intensities in a random and counterbalanced order. The %HRR and the exertional and arousal responses to vigorous session were higher than those during the moderate session (psession were less pleasant than those during moderate session (ptraining sessions are intensity-dependent. From an adherence perspective, interventionists are encouraged to emphasize group exercise training sessions at a moderate intensity to maximize affective responses and to minimize exertional responses, which in turn may positively affect future exercise behavior.

  9. Training motor responses to food: A novel treatment for obesity targeting implicit processes

    Stice, E.; Lawrence, N.S.; Kemps, E.; Veling, H.P.

    2016-01-01

    The present review first summarizes results from prospective brain imaging studies focused on identifying neural vulnerability factors that predict excessive weight gain. Next, findings from cognitive psychology experiments evaluating various interventions involving food response inhibition training

  10. Train-Network Interactions and Stability Evaluation in High-Speed Railways--Part II: Influential Factors and Verifications

    Hu, Haitao; Tao, Haidong; Wang, Xiongfei

    2018-01-01

    Low-frequency oscillation (LFO), harmonic resonance and resonance instability phenomena happened in high speed railways (HSRs) are resulted from the interactions between multiple electric trains and traction network. A train-network interaction system and a unified impedance-based model......, catenary lines and autotransformers (ATs); 3) different numbers and positions of trains and railway lines will also be considered and discussed. In order to validate the theoretical results, the time-domain simulation and experiment system have been conducted. Finally, the differences and the relations...

  11. 'Nordic' Hamstrings Exercise - Engagement Characteristics and Training Responses

    Iga, J; Fruer, C S; Deighan, Martine A; De Ste Croix, Mark B; James, David V

    2012-01-01

    The present study examined the neuromuscular activation characteristics of the hamstrings during the 'Nordic' hamstrings exercise (NHE) and changes in the eccentric strength of the knee flexors with NHE training. Initially, the normalised root mean square electromyographic (EMG) activity of the hamstrings of both limbs during various phases (90-61 degrees, 60-31 degrees and 30-0 degrees of knee extension) of the NHE were determined in 18 soccer players. Subsequently participants were randomly...

  12. Acceleration of Deep Neural Network Training with Resistive Cross-Point Devices: Design Considerations

    Tayfun Gokmen

    2016-07-01

    Full Text Available In recent years, deep neural networks (DNN have demonstrated significant business impact in large scale analysis and classification tasks such as speech recognition, visual object detection, pattern extraction, etc. Training of large DNNs, however, is universally considered as time consuming and computationally intensive task that demands datacenter-scale computational resources recruited for many days. Here we propose a concept of resistive processing unit (RPU devices that can potentially accelerate DNN training by orders of magnitude while using much less power. The proposed RPU device can store and update the weight values locally thus minimizing data movement during training and allowing to fully exploit the locality and the parallelism of the training algorithm. We evaluate the effect of various RPU device features/non-idealities and system parameters on performance in order to derive the device and system level specifications for implementation of an accelerator chip for DNN training in a realistic CMOS-compatible technology. For large DNNs with about 1 billion weights this massively parallel RPU architecture can achieve acceleration factors of 30,000X compared to state-of-the-art microprocessors while providing power efficiency of 84,000 GigaOps/s/W. Problems that currently require days of training on a datacenter-size cluster with thousands of machines can be addressed within hours on a single RPU accelerator. A system consisting of a cluster of RPU accelerators will be able to tackle Big Data problems with trillions of parameters that is impossible to address today like, for example, natural speech recognition and translation between all world languages, real-time analytics on large streams of business and scientific data, integration and analysis of multimodal sensory data flows from a massive number of IoT (Internet of Things sensors.

  13. Acceleration of Deep Neural Network Training with Resistive Cross-Point Devices: Design Considerations.

    Gokmen, Tayfun; Vlasov, Yurii

    2016-01-01

    In recent years, deep neural networks (DNN) have demonstrated significant business impact in large scale analysis and classification tasks such as speech recognition, visual object detection, pattern extraction, etc. Training of large DNNs, however, is universally considered as time consuming and computationally intensive task that demands datacenter-scale computational resources recruited for many days. Here we propose a concept of resistive processing unit (RPU) devices that can potentially accelerate DNN training by orders of magnitude while using much less power. The proposed RPU device can store and update the weight values locally thus minimizing data movement during training and allowing to fully exploit the locality and the parallelism of the training algorithm. We evaluate the effect of various RPU device features/non-idealities and system parameters on performance in order to derive the device and system level specifications for implementation of an accelerator chip for DNN training in a realistic CMOS-compatible technology. For large DNNs with about 1 billion weights this massively parallel RPU architecture can achieve acceleration factors of 30, 000 × compared to state-of-the-art microprocessors while providing power efficiency of 84, 000 GigaOps∕s∕W. Problems that currently require days of training on a datacenter-size cluster with thousands of machines can be addressed within hours on a single RPU accelerator. A system consisting of a cluster of RPU accelerators will be able to tackle Big Data problems with trillions of parameters that is impossible to address today like, for example, natural speech recognition and translation between all world languages, real-time analytics on large streams of business and scientific data, integration, and analysis of multimodal sensory data flows from a massive number of IoT (Internet of Things) sensors.

  14. Training reduces catabolic and inflammatory response to a single practice in female volleyball players.

    Eliakim, Alon; Portal, Shawn; Zadik, Zvi; Meckel, Yoav; Nemet, Dan

    2013-11-01

    We examined the effect of training on hormonal and inflammatory response to a single volleyball practice in elite adolescent players. Thirteen female, national team level, Israeli volleyball players (age 16.0 ± 1.4 years, Tanner stage 4-5) participated in the study. Blood samples were collected before and immediately after a typical 60 minutes of volleyball practice, before and after 7 weeks of training during the initial phase of the season. Training involved tactic and technical drills (20% of time), power and speed drills (25% of time), interval sessions (25% of time), endurance-type training (15% of time), and resistance training (15% of time). To achieve greater training responses, the study was performed during the early phase (first 7 weeks) of the volleyball season. Hormonal measurements included the anabolic hormones growth hormone (GH), insulin-like growth factor-I (IGF-I) and IGF-binding protein-3, the catabolic hormone cortisol, the proinflammatory marker interleukin-6 (IL-6), and the anti-inflammatory marker IL-1 receptor antagonist. Training led to a significant improvement of vertical jump, anaerobic properties (peak and mean power by the Wingate Anaerobic Test), and predicted VO2max (by the 20-m shuttle run). Volleyball practice, both before and after the training intervention, was associated with a significant increase of serum lactate, GH, and IL-6. Training resulted in a significantly reduced cortisol response ([INCREMENT]cortisol: 4.2 ± 13.7 vs. -4.4 ± 12.3 ng · ml, before and after training, respectively; p volleyball practice. The results suggest that along with the improvement of power and anaerobic and aerobic characteristics, training reduces the catabolic and inflammatory response to exercise.

  15. Using guitar learning to probe the Action Observation Network's response to visuomotor familiarity.

    Gardner, Tom; Aglinskas, Aidas; Cross, Emily S

    2017-08-01

    Watching other people move elicits engagement of a collection of sensorimotor brain regions collectively termed the Action Observation Network (AON). An extensive literature documents more robust AON responses when observing or executing familiar compared to unfamiliar actions, as well as a positive correlation between amplitude of AON response and an observer's familiarity with an observed or executed movement. On the other hand, emerging evidence shows patterns of AON activity counter to these findings, whereby in some circumstances, unfamiliar actions lead to greater AON engagement than familiar actions. In an attempt to reconcile these conflicting findings, some have proposed that the relationship between AON response amplitude and action familiarity is nonlinear in nature. In the present study, we used an elaborate guitar training intervention to probe the relationship between movement familiarity and AON engagement during action execution and action observation tasks. Participants underwent fMRI scanning while executing one set of guitar sequences with a scanner-compatible bass guitar and observing a second set of sequences. Participants then acquired further physical practice or observational experience with half of these stimuli outside the scanner across 3 days. Participants then returned for an identical scanning session, wherein they executed and observed equal numbers of familiar (trained) and unfamiliar (untrained) guitar sequences. Via region of interest analyses, we extracted activity within AON regions engaged during both scanning sessions, and then fit linear, quadratic and cubic regression models to these data. The data best support the cubic regression models, suggesting that the response profile within key sensorimotor brain regions associated with the AON respond to action familiarity in a nonlinear manner. Moreover, by probing the subjective nature of the prediction error signal, we show results consistent with a predictive coding account of

  16. Assessment of neural networks training strategies for histomorphometric analysis of synchrotron radiation medical images

    Alvarenga de Moura Meneses, Anderson, E-mail: ameneses@lmp.ufrj.b [Federal University of Rio de Janeiro, COPPE, Nuclear Engineering Program, CP 68509, CEP 21.941-972, Rio de Janeiro, RJ (Brazil); IDSIA (Dalle Molle Institute for Artificial Intelligence), University of Lugano (Switzerland); Gomes Pinheiro, Christiano Jorge [State University of Rio de Janeiro, RJ (Brazil); Rancoita, Paola [IDSIA (Dalle Molle Institute for Artificial Intelligence), University of Lugano (Switzerland); Mathematics Department, Universita degli Studi di Milano (Italy); Schaul, Tom; Gambardella, Luca Maria [IDSIA (Dalle Molle Institute for Artificial Intelligence), University of Lugano (Switzerland); Schirru, Roberto [Federal University of Rio de Janeiro, COPPE, Nuclear Engineering Program, CP 68509, CEP 21.941-972, Rio de Janeiro, RJ (Brazil); Barroso, Regina Cely; Oliveira, Luis Fernando de [State University of Rio de Janeiro, RJ (Brazil)

    2010-09-21

    Micro-computed tomography ({mu}CT) obtained by synchrotron radiation (SR) enables magnified images with a high space resolution that might be used as a non-invasive and non-destructive technique for the quantitative analysis of medical images, in particular the histomorphometry (HMM) of bony mass. In the preprocessing of such images, conventional operations such as binarization and morphological filtering are used before calculating the stereological parameters related, for example, to the trabecular bone microarchitecture. However, there is no standardization of methods for HMM based on {mu}CT images, especially the ones obtained with SR X-ray. Notwithstanding the several uses of artificial neural networks (ANNs) in medical imaging, their application to the HMM of SR-{mu}CT medical images is still incipient, despite the potential of both techniques. The contribution of this paper is the assessment and comparison of well-known training algorithms as well as the proposal of training strategies (combinations of training algorithms, sub-image kernel and symmetry information) for feed-forward ANNs in the task of bone pixels recognition in SR-{mu}CT medical images. For a quantitative comparison, the results of a cross validation and a statistical analysis of the results for 36 training strategies are presented. The ANNs demonstrated both very low mean square errors in the validation, and good quality segmentation of the image of interest for application to HMM in SR-{mu}CT medical images.

  17. Assessment of neural networks training strategies for histomorphometric analysis of synchrotron radiation medical images

    Alvarenga de Moura Meneses, Anderson; Gomes Pinheiro, Christiano Jorge; Rancoita, Paola; Schaul, Tom; Gambardella, Luca Maria; Schirru, Roberto; Barroso, Regina Cely; Oliveira, Luis Fernando de

    2010-01-01

    Micro-computed tomography (μCT) obtained by synchrotron radiation (SR) enables magnified images with a high space resolution that might be used as a non-invasive and non-destructive technique for the quantitative analysis of medical images, in particular the histomorphometry (HMM) of bony mass. In the preprocessing of such images, conventional operations such as binarization and morphological filtering are used before calculating the stereological parameters related, for example, to the trabecular bone microarchitecture. However, there is no standardization of methods for HMM based on μCT images, especially the ones obtained with SR X-ray. Notwithstanding the several uses of artificial neural networks (ANNs) in medical imaging, their application to the HMM of SR-μCT medical images is still incipient, despite the potential of both techniques. The contribution of this paper is the assessment and comparison of well-known training algorithms as well as the proposal of training strategies (combinations of training algorithms, sub-image kernel and symmetry information) for feed-forward ANNs in the task of bone pixels recognition in SR-μCT medical images. For a quantitative comparison, the results of a cross validation and a statistical analysis of the results for 36 training strategies are presented. The ANNs demonstrated both very low mean square errors in the validation, and good quality segmentation of the image of interest for application to HMM in SR-μCT medical images.

  18. A comparative study of breast cancer diagnosis based on neural network ensemble via improved training algorithms.

    Azami, Hamed; Escudero, Javier

    2015-08-01

    Breast cancer is one of the most common types of cancer in women all over the world. Early diagnosis of this kind of cancer can significantly increase the chances of long-term survival. Since diagnosis of breast cancer is a complex problem, neural network (NN) approaches have been used as a promising solution. Considering the low speed of the back-propagation (BP) algorithm to train a feed-forward NN, we consider a number of improved NN trainings for the Wisconsin breast cancer dataset: BP with momentum, BP with adaptive learning rate, BP with adaptive learning rate and momentum, Polak-Ribikre conjugate gradient algorithm (CGA), Fletcher-Reeves CGA, Powell-Beale CGA, scaled CGA, resilient BP (RBP), one-step secant and quasi-Newton methods. An NN ensemble, which is a learning paradigm to combine a number of NN outputs, is used to improve the accuracy of the classification task. Results demonstrate that NN ensemble-based classification methods have better performance than NN-based algorithms. The highest overall average accuracy is 97.68% obtained by NN ensemble trained by RBP for 50%-50% training-test evaluation method.

  19. Computer Simulation as a Tool for Assessing Decision-Making in Pandemic Influenza Response Training

    James M Leaming

    2013-05-01

    Full Text Available Introduction: We sought to develop and test a computer-based, interactive simulation of a hypothetical pandemic influenza outbreak. Fidelity was enhanced with integrated video and branching decision trees, built upon the 2007 federal planning assumptions. We conducted a before-and-after study of the simulation effectiveness to assess the simulations’ ability to assess participants’ beliefs regarding their own hospitals’ mass casualty incident preparedness.Methods: Development: Using a Delphi process, we finalized a simulation that serves up a minimum of over 50 key decisions to 6 role-players on networked laptops in a conference area. The simulation played out an 8-week scenario, beginning with pre-incident decisions. Testing: Role-players and trainees (N=155 were facilitated to make decisions during the pandemic. Because decision responses vary, the simulation plays out differently, and a casualty counter quantifies hypothetical losses. The facilitator reviews and critiques key factors for casualty control, including effective communications, working with external organizations, development of internal policies and procedures, maintaining supplies and services, technical infrastructure support, public relations and training. Pre- and post-survey data were compared on trainees.Results: Post-simulation trainees indicated a greater likelihood of needing to improve their organization in terms of communications, mass casualty incident planning, public information and training. Participants also recognized which key factors required immediate attention at their own home facilities.Conclusion: The use of a computer-simulation was effective in providing a facilitated environment for determining the perception of preparedness, evaluating general preparedness concepts and introduced participants to critical decisions involved in handling a regional pandemic influenza surge. [West J Emerg Med. 2013;14(3:236–242.

  20. The National Response System: The Need to Leverage Networks and Knowledge

    Compagnoni, Barry A

    2006-01-01

    .... When viewing our national response from the perspective of network theory and knowledge management, specific gaps are identified in doctrine, organizational composition and technological capability...

  1. Pre-Trained Neural Networks used for Non-Linear State Estimation

    Bayramoglu, Enis; Andersen, Nils Axel; Ravn, Ole

    2011-01-01

    of the paramters in the distribution. This transformation is approximated by a neural network using offline training, which is based on monte carlo sampling. In the paper, there will also be presented a method to construct a flexible distributions well suited for covering the effect of the non-linearities......The paper focuses on nonlinear state estimation assuming non-Gaussian distributions of the states and the disturbances. The posterior distribution and the aposteriori distribution is described by a chosen family of paramtric distributions. The state transformation then results in a transformation...

  2. GLANAM (Glaciated North Atlantic Margins): A Marie Curie Initial Training Network between Norway, the UK & Denmark

    Petter Sejrup, Hans; Oline Hjelstuen, Berit

    2015-04-01

    GLANAM (Glaciated North Atlantic Margins) is an Initial Training Network (ITN) funded under the EU Marie Curie Programme. It comprises 10 research partners from Norway, UK and Denmark, including 7 University research teams, 1 industrial full partner and 2 industrial associate partners. The GLANAM network will employ and train 15 early career researchers (Fellows). The aim of GLANAM is to improve the career prospects and development of young researchers in both the public and private sector within the field of earth science, focusing on North Atlantic glaciated margins. The young scientists will perform multi-disciplinary research and receive training in geophysics, remote sensing, GIS, sedimentology, geomorphology, stratigraphy, geochemistry and numerical modeling through three interconnected work packages that collectively address knowledge gaps related to the large, glacial age, sedimentary depocentres on the North Atlantic margin. The 15 Fellows will work on projects that geographically extend from Ireland in the south to the High Arctic. Filling these gaps will not only result in major new insights regarding glacial age processes on continental margins in general, but will also provide paleoclimate information essential for understanding the role of marine-based ice sheets in the climate system and for the testing of climate models. GLANAM brings together leading European research groups working on glaciated margins in a coordinated and collaborative research and training project. Focusing on the North Atlantic margins, this coordinated approach will lead to a major advance in the understanding of glaciated margins more widely and will fundamentally strengthen European research and build capacity in this field.

  3. Roles and Responsibilities, and Education and Training Requirements for Clinically Qualified Medical Physicists (Russian Edition)

    2014-01-01

    This publication addresses the shortfall of well trained and clinically qualified medical physicists working in radiation medicine. The roles, responsibilities and clinical training requirements of medical physicists have not always been well defined or well understood by health care professionals, health authorities and regulatory agencies. To fill this gap, this publication provides recommendations for the academic education and clinical training of clinically qualified medical physicists, including recommendations for their accreditation certification and registration, along with continuous professional development. The goal is to establish criteria that support the harmonization of education and clinical training worldwide

  4. Exercise training modulates functional sympatholysis and alpha-adrenergic vasoconstrictor responsiveness in hypertensive and normotensive individuals

    Mortensen, Stefan Peter; Nyberg, Michael Permin; Gliemann Hybholt, Lasse

    2014-01-01

    were measured before and after 8 weeks of aerobic training (3-4 times/week) in 8 hypertensive (47 ± 2 years) and 8 normotensive untrained individuals (46 ± 1 years) during arterial tyramine infusion, arterial ATP infusion and/or one-legged knee extensions. Before training, exercise hypaeremia and leg......Essential hypertension is linked to an increased sympathetic vasoconstrictor activity and reduced tissue perfusion. We investigated the role of exercise training on functional sympatholysis and postjunctional α-adrenergic responsiveness in individuals with essential hypertension. Leg haemodynamics...... vascular conductance (LVC) were lower in the hypertensive individuals (P Training lowered blood pressure in the hypertensive individuals (P

  5. The Stress and Coping Responses of Certified Graduate Athletic Training Students

    Reed, Sarah

    2004-01-01

    Objective: To assess the sources of stress and coping responses of certified graduate athletic training students. Design and Setting: We interviewed certified graduate athletic training students 3 times over a 9-month period. We transcribed the interviews verbatim and used grounded theory analytic procedures to inductively analyze the participants' sources of stress and coping responses. Subjects: Three male and 3 female certified graduate athletic training students from a postcertification graduate athletic training program volunteered to participate in this investigation. The participants were full-time graduate students, with a mean age of 23 years, who had worked an average of 1.5 years as certified athletic trainers at the time of the first interview. Measurements: We used grounded theory analytic procedures to inductively analyze the participants' sources of stress and coping responses. Results: A total of 6 general sources of stress and 11 coping dimensions were revealed. The stress dimensions were labeled athletic training duties, comparing job duties, responsibilities as student, time management, social evaluation, and future concerns. The coping responses were planning, instrumental social support, adjusting to job responsibilities, positive evaluations, emotional social support, humor, wishful thinking, religion, mental or behavioral disengagement, activities outside the profession, and other outcomes. Conclusions: Certified graduate athletic training students should be encouraged to use problem-focused (eg, seeking advice, planning) and emotion-focused (eg, positive evaluations, humor) forms of coping with stress. PMID:15173872

  6. Promoting Response Variability and Stimulus Generalization in Martial Arts Training

    Harding, Jay W.; Wacker, David P.; Berg, Wendy K.; Rick, Gary; Lee, John F.

    2004-01-01

    The effects of reinforcement and extinction on response variability and stimulus generalization in the punching and kicking techniques of 2 martial arts students were evaluated across drill and sparring conditions. During both conditions, the students were asked to demonstrate different techniques in response to an instructor's punching attack.…

  7. SOME ASPECTS OF TRAINING SOCIALLY RESPONSIBLE ENGINEERS ABROAD

    N. Sayenko

    2016-06-01

    Full Text Available The article gives an overview of various concepts of social responsibility abroad. It is underlined that Ukrainian technical universities should borrow the best practices of ethical education from foreign countries. Analysis of social responsibility content and structural components as well as some ways of its development abroad is given.

  8. Spreading of Excellence in SARNET Network on Severe Accidents: The Education and Training Programme

    Sandro Paci

    2012-01-01

    Full Text Available The SARNET2 (severe accidents Research NETwork of Excellence project started in April 2009 for 4 years in the 7th Framework Programme (FP7 of the European Commission (EC, following a similar first project in FP6. Forty-seven organisations from 24 countries network their capacities of research in the severe accident (SA field inside SARNET to resolve the most important remaining uncertainties and safety issues on SA in water-cooled nuclear power plants (NPPs. The network includes a large majority of the European actors involved in SA research plus a few non-European relevant ones. The “Education and Training” programme in SARNET is a series of actions foreseen in this network for the “spreading of excellence.” It is focused on raising the competence level of Master and Ph.D. students and young researchers engaged in SA research and on organizing information/training courses for NPP staff or regulatory authorities (but also for researchers interested in SA management procedures.

  9. Comparative Analysis of Neural Network Training Methods in Real-time Radiotherapy

    Nouri S.

    2017-03-01

    Full Text Available Background: The motions of body and tumor in some regions such as chest during radiotherapy treatments are one of the major concerns protecting normal tissues against high doses. By using real-time radiotherapy technique, it is possible to increase the accuracy of delivered dose to the tumor region by means of tracing markers on the body of patients. Objective: This study evaluates the accuracy of some artificial intelligence methods including neural network and those of combination with genetic algorithm as well as particle swarm optimization (PSO estimating tumor positions in real-time radiotherapy. Method: One hundred recorded signals of three external markers were used as input data. The signals from 3 markers thorough 10 breathing cycles of a patient treated via a cyber-knife for a lung tumor were used as data input. Then, neural network method and its combination with genetic or PSO algorithms were applied determining the tumor locations using MATLAB© software program. Results: The accuracies were obtained 0.8%, 12% and 14% in neural network, genetic and particle swarm optimization algorithms, respectively. Conclusion: The internal target volume (ITV should be determined based on the applied neural network algorithm on training steps.

  10. Long-term intensive gymnastic training induced changes in intra- and inter-network functional connectivity: an independent component analysis.

    Huang, Huiyuan; Wang, Junjing; Seger, Carol; Lu, Min; Deng, Feng; Wu, Xiaoyan; He, Yuan; Niu, Chen; Wang, Jun; Huang, Ruiwang

    2018-01-01

    Long-term intensive gymnastic training can induce brain structural and functional reorganization. Previous studies have identified structural and functional network differences between world class gymnasts (WCGs) and non-athletes at the whole-brain level. However, it is still unclear how interactions within and between functional networks are affected by long-term intensive gymnastic training. We examined both intra- and inter-network functional connectivity of gymnasts relative to non-athletes using resting-state fMRI (R-fMRI). R-fMRI data were acquired from 13 WCGs and 14 non-athlete controls. Group-independent component analysis (ICA) was adopted to decompose the R-fMRI data into spatial independent components and associated time courses. An automatic component identification method was used to identify components of interest associated with resting-state networks (RSNs). We identified nine RSNs, the basal ganglia network (BG), sensorimotor network (SMN), cerebellum (CB), anterior and posterior default mode networks (aDMN/pDMN), left and right fronto-parietal networks (lFPN/rFPN), primary visual network (PVN), and extrastriate visual network (EVN). Statistical analyses revealed that the intra-network functional connectivity was significantly decreased within the BG, aDMN, lFPN, and rFPN, but increased within the EVN in the WCGs compared to the controls. In addition, the WCGs showed uniformly decreased inter-network functional connectivity between SMN and BG, CB, and PVN, BG and PVN, and pDMN and rFPN compared to the controls. We interpret this generally weaker intra- and inter-network functional connectivity in WCGs during the resting state as a result of greater efficiency in the WCGs' brain associated with long-term motor skill training.

  11. Endurance- and Resistance-Trained Men Exhibit Lower Cardiovascular Responses to Psychosocial Stress Than Untrained Men.

    Gröpel, Peter; Urner, Maren; Pruessner, Jens C; Quirin, Markus

    2018-01-01

    Evidence shows that regular physical exercise reduces physiological reactivity to psychosocial stress. However, previous research mainly focused on the effect of endurance exercise, with only a few studies looking at the effect of resistance exercise. The current study tested whether individuals who regularly participate in either endurance or resistance training differ from untrained individuals in adrenal and cardiovascular reactivity to psychosocial stress. Twelve endurance-trained men, 10 resistance-trained men, and 12 healthy but untrained men were exposed to a standardized psychosocial stressor, the Trier Social Stress Test. Measurements of heart rate, free salivary cortisol levels, and mood were obtained throughout the test and compared among the three groups. Overall, both endurance- and resistance-trained men had lower heart rate levels than untrained men, indicating higher cardiac performance of the trained groups. Trained men also exhibited lower heart rate responses to psychosocial stress compared with untrained men. There were no significant group differences in either cortisol responses or mood responses to the stressor. The heart rate results are consistent with previous studies indicating reduced cardiovascular reactivity to psychosocial stress in trained individuals. These findings suggest that long-term endurance and resistance trainings may be related to the same cardiovascular benefits, without exhibiting strong effects on the cortisol reactivity to stress.

  12. Dynamic response analysis of single-span guideway caused by high speed maglev train

    Jin Shi

    Full Text Available High speed maglev is one of the most important reformations in the ground transportation systems because of its no physical contact nature. This paper intends to study the dynamic response of the single-span guideway induced by moving maglev train. The dynamic model of the maglev train-guideway system is established. In this model, a maglev train consists of three vehicles and each vehicle is regarded as a multibody system with 34 degrees-of-freedom. The guideway is modeled as a simply supported beam. Considering the motion-dependent nature of electromagnetic forces in the maglev system, an iterative approach is presented to compute the dynamic response of a maglev train-guideway system. The histories of the train traversing the guideways are simulated and the dynamic responses of the guideway and the train vehicles are calculated. A field experiment is carried out to verify the results of the analysis. The resonant conditions of single-span guideway are analyzed. The results show that all the dynamic indexes of train-guideway system are far less than permissive values of railway and maglev system, the vertical resonant of guideways caused by periodical excitations of the train will not happen.

  13. Role and responsibilities of management in NPP personnel training and competence. Working material

    1994-01-01

    The main aim and result of this seminar was imparting knowledge to various levels of Paks NPP management on their special tasks and responsibilities to achieve personnel competence, which include: meeting relevant regulatory and other requirements; defining the qualifications for NPP personnel jobs; training using systematic approach to training to attain the required level of qualification and competence of all NPP personnel, which includes management, operations, maintenance and technical support personnel and others; recruiting and retaining qualified personnel, including career development; supporting the training of all personnel on their responsibilities for introducing, maintaining and improving safety. Refs, figs and tabs

  14. Memory self-efficacy predicts responsiveness to inductive reasoning training in older adults.

    Payne, Brennan R; Jackson, Joshua J; Hill, Patrick L; Gao, Xuefei; Roberts, Brent W; Stine-Morrow, Elizabeth A L

    2012-01-01

    In the current study, we assessed the relationship between memory self-efficacy at pretest and responsiveness to inductive reasoning training in a sample of older adults. Participants completed a measure of self-efficacy assessing beliefs about memory capacity. Participants were then randomly assigned to a waitlist control group or an inductive reasoning training intervention. Latent change score models were used to examine the moderators of change in inductive reasoning. Inductive reasoning showed clear improvements in the training group compared with the control. Within the training group, initial memory capacity beliefs significantly predicted change in inductive reasoning such that those with higher levels of capacity beliefs showed greater responsiveness to the intervention. Further analyses revealed that self-efficacy had effects on how trainees allocated time to the training materials over the course of the intervention. Results indicate that self-referential beliefs about cognitive potential may be an important factor contributing to plasticity in adulthood.

  15. Advanced simulation and management software for nuclear emergency training and response

    Rose, K.W.

    2011-01-01

    The importance of training of safety personnel to deal with real world scenarios is prevalent amongst nuclear emergency preparedness and response organizations. For the development of training tools we have committed to ensure that field procedures, data collection software and decision making tools be identical during training sessions as they would be during a real emergency. By identifying the importance of a fully integrated tool, we have developed a safety support system capable of both functioning in training mode and real mode, enabling emergency response organizations to train more efficiently and effectively. This new fully integrated emergency management tool is called S3-FAST also known as Safety Support Systems - Field Assessment Survey Tool. (orig.)

  16. Active Component Responsibility in Reserve Component Pre- and Postmobilization Training

    2015-01-01

    XI as part of the Army Posture Statement, including a comparison of the promotion rates of officers assigned as AC advisers with those of all other...reflect true equipping posture , a tendency to upgrade rat- ings as reports move up the chain of command, and an inability to link funding to changes in...with our aviation force. … [W] hen we say we need to train the tank crews on simulators, we have got to make sure those things are there. (U.S. House of

  17. Train Stop Scheduling in a High-Speed Rail Network by Utilizing a Two-Stage Approach

    Huiling Fu

    2012-01-01

    Full Text Available Among the most commonly used methods of scheduling train stops are practical experience and various “one-step” optimal models. These methods face problems of direct transferability and computational complexity when considering a large-scale high-speed rail (HSR network such as the one in China. This paper introduces a two-stage approach for train stop scheduling with a goal of efficiently organizing passenger traffic into a rational train stop pattern combination while retaining features of regularity, connectivity, and rapidity (RCR. Based on a three-level station classification definition, a mixed integer programming model and a train operating tactics descriptive model along with the computing algorithm are developed and presented for the two stages. A real-world numerical example is presented using the Chinese HSR network as the setting. The performance of the train stop schedule and the applicability of the proposed approach are evaluated from the perspective of maintaining RCR.

  18. Elucidation of time-dependent systems biology cell response patterns with time course network enrichment

    Wiwie, Christian; Rauch, Alexander; Haakonsson, Anders

    2018-01-01

    , no methods exist to integrate time series data with networks, thus preventing the identification of time-dependent systems biology responses. We close this gap with Time Course Network Enrichment (TiCoNE). It combines a new kind of human-augmented clustering with a novel approach to network enrichment...

  19. Cooperative approach to training for radiological emergency preparedness and response in Southeast Asia

    Bus, John; Popp, Andrew; Holland, Brian; Murray, Allan

    2011-01-01

    The paper describes the collaborative and systematic approach to training for nuclear and radiological emergency preparedness and response and the outcomes of this work with ANSTO's Southeast Asian counterparts, particularly in the Philippines. The standards and criteria being applied are discussed, along with the methods, design and conduct of workshops, table-top and field exercises. The following elements of this training will be presented: (a) identifying the priority areas for training through needs analysis;(b) strengthening individual profesional expertise through a structured approach to training; and (c) enhancing individual Agency and National nuclear and radiological emergency preparedness and response arrangements and capabilities. Whilst the work is motivated by nuclear security concerns, the implications for effective and sustainable emergency response to any nuclear or radiological incidents are noted. (author)

  20. Training requirements and responsibilities for the Buried Waste Integrated Demonstration at the Radioactive Waste Management Complex

    Vega, H.G.; French, S.B.; Rick, D.L.

    1992-09-01

    The Buried Waste Integrated Demonstration (BWID) is scheduled to conduct intrusive (hydropunch screening tests, bore hole installation, soil sampling, etc.) and nonintrusive (geophysical surveys) studies at the Radioactive Waste Management Complex (RWMC). These studies and activities will be limited to specific locations at the RWMC. The duration of these activities will vary, but most tasks are not expected to exceed 90 days. The BWID personnel requested that the Waste Management Operational Support Group establish the training requirements and training responsibilities for BWID personnel and BWID subcontractor personnel. This document specifies these training requirements and responsibilities. While the responsibilities of BWID and the RWMC are, in general, defined in the interface agreement, the training elements are based on regulatory requirements, DOE orders, DOE-ID guidance, state law, and the nature of the work to be performed

  1. Requirement of trained first responders and national level preparedness for prevention and response to radiological terrorism

    Sharma, R.; Pradeepkumar, K.S.

    2010-01-01

    In this paper we have identified the educational needs for response to radiological emergency in India with major thrust on training. The paper has also enumerated the available educational and training infrastructure, the human resources, as well as the important stake holders for development of sustainable education and training programme. The training of emergency response personnel will help in quick decision making, planning and effective response during such emergencies. Medical Emergency management requires planning by hospitals which includes up-gradation of earmarked hospitals, development of mobile hospitals and mobile medical teams supported by communication backups and adequate medical logistics for radiological emergency. Department of Atomic Energy (DAE) is a nodal agency for advising authorities for any nuclear/radiological emergency in public domain. DAE through the various ERCs have already developed technical expertise, systems, software and methodology for quick impact assessment which may be required for the implementation of countermeasures if required following any nuclear disaster/radiological emergency

  2. EMG and Kinematic Responses to Unexpected Slips After Slip Training in Virtual Reality

    Parijat, Prakriti; Lockhart, Thurmon E.

    2015-01-01

    The objective of the study was to design a virtual reality (VR) training to induce perturbation in older adults similar to a slip and examine the effect of the training on kinematic and muscular responses in older adults. Twenty-four older adults were involved in a laboratory study and randomly assigned to two groups (virtual reality training and control). Both groups went through three sessions including baseline slip, training, and transfer of training on slippery surface. The training group experienced twelve simulated slips using a visual perturbation induced by tilting a virtual reality scene while walking on the treadmill and the control group completed normal walking during the training session. Kinematic, kinetic, and EMG data were collected during all the sessions. Results demonstrated the proactive adjustments such as increased trunk flexion at heel contact after training. Reactive adjustments included reduced time to peak activations of knee flexors, reduced knee coactivation, reduced time to trunk flexion, and reduced trunk angular velocity after training. In conclusion, the study findings indicate that the VR training was able to generate a perturbation in older adults that evoked recovery reactions and such motor skill can be transferred to the actual slip trials. PMID:25296401

  3. Integrated Optimization of Service-Oriented Train Plan and Schedule on Intercity Rail Network with Varying Demand

    Wenliang Zhou

    2015-01-01

    Full Text Available For a better service level of a train operating plan, we propose an integrated optimization method of train planning and train scheduling, which generally are optimized, respectively. Based on the cost analysis of both passengers travelling and enterprises operation, and the constraint analysis of trains operation, we construct a multiobjective function and build an integrated optimization model with the aim of reducing both passenger travel costs and enterprise operating costs. Then, a solving algorithm is established based on the simulated annealing algorithm. Finally, using as an example the Changzhutan intercity rail network, as an example we analyze the optimized results and the influence of the model parameters on the results.

  4. A multi-radio, multi-hop ad-hoc radio communication network for Communications-Based Train Control (CBTC)

    Farooq, Jahanzeb; Bro, Lars; Karstensen, Rasmus Thystrup

    2018-01-01

    Communications-Based Train Control (CBTC) is a modern signalling system that uses radio communication to transfer train control information between train and wayside. The trackside networks in these systems are mostly based on conventional infrastructure Wi-Fi (IEEE 802.11). It means a train has...... to continuously associate (i.e. perform handshake) with the trackside Wi-Fi Access Points (AP) as it moves, which incurs communication delays. Additionally, these APs are connected to the wayside infrastructure via optical fiber cables that incurs huge costs. This paper presents a novel design in which trackside...

  5. Long-term meditation training induced changes in the operational synchrony of default mode network modules during a resting state.

    Fingelkurts, Andrew A; Fingelkurts, Alexander A; Kallio-Tamminen, Tarja

    2016-02-01

    Using theoretical analysis of self-consciousness concept and experimental evidence on the brain default mode network (DMN) that constitutes the neural signature of self-referential processes, we hypothesized that the anterior and posterior subnets comprising the DMN should show differences in their integrity as a function of meditation training. Functional connectivity within DMN and its subnets (measured by operational synchrony) has been measured in ten novice meditators using an electroencephalogram (EEG) recording in a pre-/post-meditation intervention design. We have found that while the whole DMN was clearly suppressed, different subnets of DMN responded differently after 4 months of meditation training: The strength of EEG operational synchrony in the right and left posterior modules of the DMN decreased in resting post-meditation condition compared to a pre-meditation condition, whereas the frontal DMN module on the contrary exhibited an increase in the strength of EEG operational synchrony. These findings combined with published data on functional-anatomic heterogeneity within the DMN and on trait subjective experiences commonly found following meditation allow us to propose that the first-person perspective and the sense of agency (the witnessing observer) are presented by the frontal DMN module, while the posterior modules of the DMN are generally responsible for the experience of the continuity of 'I' as embodied and localized within bodily space. Significance of these findings is discussed.

  6. Path selection rules for droplet trains in single-lane microfluidic networks

    Amon, A.; Schmit, A.; Salkin, L.; Courbin, L.; Panizza, P.

    2013-07-01

    We investigate the transport of periodic trains of droplets through microfluidic networks having one inlet, one outlet, and nodes consisting of T junctions. Variations of the dilution of the trains, i.e., the distance between drops, reveal the existence of various hydrodynamic regimes characterized by the number of preferential paths taken by the drops. As the dilution increases, this number continuously decreases until only one path remains explored. Building on a continuous approach used to treat droplet traffic through a single asymmetric loop, we determine selection rules for the paths taken by the drops and we predict the variations of the fraction of droplets taking these paths with the parameters at play including the dilution. Our results show that as dilution decreases, the paths are selected according to the ascending order of their hydrodynamic resistance in the absence of droplets. The dynamics of these systems controlled by time-delayed feedback is complex: We observe a succession of periodic regimes separated by a wealth of bifurcations as the dilution is varied. In contrast to droplet traffic in single asymmetric loops, the dynamical behavior in networks of loops is sensitive to initial conditions because of extra degrees of freedom.

  7. A modified backpropagation algorithm for training neural networks on data with error bars

    Gernoth, K.A.; Clark, J.W.

    1994-08-01

    A method is proposed for training multilayer feedforward neural networks on data contaminated with noise. Specifically, we consider the case that the artificial neural system is required to learn a physical mapping when the available values of the target variable are subject to experimental uncertainties, but are characterized by error bars. The proposed method, based on maximum likelihood criterion for parameter estimation, involves simple modifications of the on-line backpropagation learning algorithm. These include incorporation of the error-bar assignments in a pattern-specific learning rate, together with epochal updating of a new measure of model accuracy that replaces the usual mean-square error. The extended backpropagation algorithm is successfully tested on two problems relevant to the modelling of atomic-mass systematics by neural networks. Provided the underlying mapping is reasonably smooth, neural nets trained with the new procedure are able to learn the true function to a good approximation even in the presence of high levels of Gaussian noise. (author). 26 refs, 2 figs, 5 tabs

  8. Predicting Response to Neoadjuvant Chemotherapy with PET Imaging Using Convolutional Neural Networks.

    Petros-Pavlos Ypsilantis

    Full Text Available Imaging of cancer with 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET has become a standard component of diagnosis and staging in oncology, and is becoming more important as a quantitative monitor of individual response to therapy. In this article we investigate the challenging problem of predicting a patient's response to neoadjuvant chemotherapy from a single 18F-FDG PET scan taken prior to treatment. We take a "radiomics" approach whereby a large amount of quantitative features is automatically extracted from pretherapy PET images in order to build a comprehensive quantification of the tumor phenotype. While the dominant methodology relies on hand-crafted texture features, we explore the potential of automatically learning low- to high-level features directly from PET scans. We report on a study that compares the performance of two competing radiomics strategies: an approach based on state-of-the-art statistical classifiers using over 100 quantitative imaging descriptors, including texture features as well as standardized uptake values, and a convolutional neural network, 3S-CNN, trained directly from PET scans by taking sets of adjacent intra-tumor slices. Our experimental results, based on a sample of 107 patients with esophageal cancer, provide initial evidence that convolutional neural networks have the potential to extract PET imaging representations that are highly predictive of response to therapy. On this dataset, 3S-CNN achieves an average 80.7% sensitivity and 81.6% specificity in predicting non-responders, and outperforms other competing predictive models.

  9. Development and Comparative Study of Effects of Training Algorithms on Performance of Artificial Neural Network Based Analog and Digital Automatic Modulation Recognition

    Jide Julius Popoola

    2015-11-01

    Full Text Available This paper proposes two new classifiers that automatically recognise twelve combined analog and digital modulated signals without any a priori knowledge of the modulation schemes and the modulation parameters. The classifiers are developed using pattern recognition approach. Feature keys extracted from the instantaneous amplitude, instantaneous phase and the spectrum symmetry of the simulated signals are used as inputs to the artificial neural network employed in developing the classifiers. The two developed classifiers are trained using scaled conjugate gradient (SCG and conjugate gradient (CONJGRAD training algorithms. Sample results of the two classifiers show good success recognition performance with an average overall recognition rate above 99.50% at signal-to-noise ratio (SNR value from 0 dB and above with the two training algorithms employed and an average overall recognition rate slightly above 99.00% and 96.40% respectively at - 5 dB SNR value for SCG and CONJGRAD training algorithms. The comparative performance evaluation of the two developed classifiers using the two training algorithms shows that the two training algorithms have different effects on both the response rate and efficiency of the two developed artificial neural networks classifiers. In addition, the result of the performance evaluation carried out on the overall success recognition rates between the two developed classifiers in this study using pattern recognition approach with the two training algorithms and one reported classifier in surveyed literature using decision-theoretic approach shows that the classifiers developed in this study perform favourably with regard to accuracy and performance probability as compared to classifier presented in previous study.

  10. Case Study: Does training of private networks of Family Planning clinicians in urban Pakistan affect service utilization?

    2010-01-01

    Background To determine whether training of providers participating in franchise clinic networks is associated with increased Family Planning service use among low-income urban families in Pakistan. Methods The study uses 2001 survey data consisting of interviews with 1113 clinical and non-clinical providers working in public and private hospitals/clinics. Data analysis excludes non-clinical providers reducing sample size to 822. Variables for the analysis are divided into client volume, and training in family planning. Regression models are used to compute the association between training and service use in franchise versus private non-franchise clinics. Results In franchise clinic networks, staff are 6.5 times more likely to receive family planning training (P = 0.00) relative to private non-franchises. Service use was significantly associated with training (P = 0.00), franchise affiliation (P = 0.01), providers' years of family planning experience (P = 0.02) and the number of trained staff working at government owned clinics (P = 0.00). In this setting, nurses are significantly less likely to receive training compared to doctors (P = 0.00). Conclusions These findings suggest that franchises recruit and train various cadres of health workers and training maybe associated with increased service use through improvement in quality of services. PMID:21062460

  11. Case Study: Does training of private networks of Family Planning clinicians in urban Pakistan affect service utilization?

    Qureshi Asma M

    2010-11-01

    Full Text Available Abstract Background To determine whether training of providers participating in franchise clinic networks is associated with increased Family Planning service use among low-income urban families in Pakistan. Methods The study uses 2001 survey data consisting of interviews with 1113 clinical and non-clinical providers working in public and private hospitals/clinics. Data analysis excludes non-clinical providers reducing sample size to 822. Variables for the analysis are divided into client volume, and training in family planning. Regression models are used to compute the association between training and service use in franchise versus private non-franchise clinics. Results In franchise clinic networks, staff are 6.5 times more likely to receive family planning training (P = 0.00 relative to private non-franchises. Service use was significantly associated with training (P = 0.00, franchise affiliation (P = 0.01, providers' years of family planning experience (P = 0.02 and the number of trained staff working at government owned clinics (P = 0.00. In this setting, nurses are significantly less likely to receive training compared to doctors (P = 0.00. Conclusions These findings suggest that franchises recruit and train various cadres of health workers and training maybe associated with increased service use through improvement in quality of services.

  12. Case Study: Does training of private networks of Family Planning clinicians in urban Pakistan affect service utilization?

    Qureshi, Asma M

    2010-11-09

    To determine whether training of providers participating in franchise clinic networks is associated with increased Family Planning service use among low-income urban families in Pakistan. The study uses 2001 survey data consisting of interviews with 1113 clinical and non-clinical providers working in public and private hospitals/clinics. Data analysis excludes non-clinical providers reducing sample size to 822. Variables for the analysis are divided into client volume, and training in family planning. Regression models are used to compute the association between training and service use in franchise versus private non-franchise clinics. In franchise clinic networks, staff are 6.5 times more likely to receive family planning training (P = 0.00) relative to private non-franchises. Service use was significantly associated with training (P = 0.00), franchise affiliation (P = 0.01), providers' years of family planning experience (P = 0.02) and the number of trained staff working at government owned clinics (P = 0.00). In this setting, nurses are significantly less likely to receive training compared to doctors (P = 0.00). These findings suggest that franchises recruit and train various cadres of health workers and training maybe associated with increased service use through improvement in quality of services.

  13. Integration of metabolic and gene regulatory networks modulates the C. elegans dietary response.

    Watson, Emma; MacNeil, Lesley T; Arda, H Efsun; Zhu, Lihua Julie; Walhout, Albertha J M

    2013-03-28

    Expression profiles are tailored according to dietary input. However, the networks that control dietary responses remain largely uncharacterized. Here, we combine forward and reverse genetic screens to delineate a network of 184 genes that affect the C. elegans dietary response to Comamonas DA1877 bacteria. We find that perturbation of a mitochondrial network composed of enzymes involved in amino acid metabolism and the TCA cycle affects the dietary response. In humans, mutations in the corresponding genes cause inborn diseases of amino acid metabolism, most of which are treated by dietary intervention. We identify several transcription factors (TFs) that mediate the changes in gene expression upon metabolic network perturbations. Altogether, our findings unveil a transcriptional response system that is poised to sense dietary cues and metabolic imbalances, illustrating extensive communication between metabolic networks in the mitochondria and gene regulatory networks in the nucleus. Copyright © 2013 Elsevier Inc. All rights reserved.

  14. Differential effects of massed and spaced training on place and response learning: A memory systems perspective.

    Wingard, Jeffrey C; Goodman, Jarid; Leong, Kah-Chung; Packard, Mark G

    2015-09-01

    Studies employing brain lesion or intracerebral drug infusions in rats have demonstrated a double dissociation between the roles of the hippocampus and dorsolateral striatum in place and response learning. The hippocampus mediates a rapid cognitive learning process underlying place learning, whereas the dorsolateral striatum mediates a relatively slower learning process in which stimulus-response habits underlying response learning are acquired in an incremental fashion. One potential implication of these findings is that hippocampus-dependent learning may benefit from a relative massing of training trials, whereas dorsal striatum-dependent learning may benefit from a relative distribution of training trials. In order to examine this hypothesis, the present study compared the effects of massed (30s inter-trial interval; ITI) or spaced (30min ITI) training on acquisition of a hippocampus-dependent place learning task, and a dorsolateral striatum-dependent response task in a plus-maze. In the place task rats swam from varying start points (N or S) to a hidden escape platform located in a consistent spatial location (W). In the response task rats swam from varying start points (N or S) to a hidden escape platform located in the maze arm consistent with a body-turn response (left). In the place task, rats trained with the massed trial schedule acquired the task quicker than rats trained with the spaced trial schedule. In the response task, rats trained with the spaced trial schedule acquired the task quicker than rats trained with the massed trial schedule. The double dissociation observed suggests that the reinforcement parameters most conducive to effective learning in hippocampus-dependent and dorsolateral striatum-dependent learning may have differential temporal characteristics. Copyright © 2015 Elsevier B.V. All rights reserved.

  15. The Effects of Martial Arts Training on Attentional Networks in Typical Adults.

    Johnstone, Ashleigh; Marí-Beffa, Paloma

    2018-01-01

    There is substantial evidence that training in Martial Arts is associated with improvements in cognitive function in children; but little has been studied in healthy adults. Here, we studied the impact of extensive training in Martial Arts on cognitive control in adults. To do so, we used the Attention Network Test (ANT) to test two different groups of participants: with at least 2 years of Martial Arts experience, and with no experience with the sport. Participants were screened from a wider sample of over 500 participants who volunteered to participate. 48 participants were selected: 21 in the Martial Arts group (mean age = 19.68) and 27 in the Non-Martial Arts group (mean age = 19.63). The two groups were matched on a number of demographic variables that included Age and BMI, following the results of a previous pilot study where these factors were found to significantly impact the ANT measures. An effect of Martial Arts experience was found on the Alert network, but not the Orienting or Executive ones. More specifically, Martial Artists showed improved performance when alert had to be sustained endogenously, performing more like the control group when an exogenous cue was provided. This result was further confirmed by a negative correlation between number of years of Martial Arts experience and the costs due to the lack of an exogenous cue suggesting that the longer a person takes part in the sport, the better their endogenous alert is. Results are interpreted in the context of the impact of training a particular attentional state in specific neurocognitive pathways.

  16. The Effects of Martial Arts Training on Attentional Networks in Typical Adults

    Ashleigh Johnstone

    2018-02-01

    Full Text Available There is substantial evidence that training in Martial Arts is associated with improvements in cognitive function in children; but little has been studied in healthy adults. Here, we studied the impact of extensive training in Martial Arts on cognitive control in adults. To do so, we used the Attention Network Test (ANT to test two different groups of participants: with at least 2 years of Martial Arts experience, and with no experience with the sport. Participants were screened from a wider sample of over 500 participants who volunteered to participate. 48 participants were selected: 21 in the Martial Arts group (mean age = 19.68 and 27 in the Non-Martial Arts group (mean age = 19.63. The two groups were matched on a number of demographic variables that included Age and BMI, following the results of a previous pilot study where these factors were found to significantly impact the ANT measures. An effect of Martial Arts experience was found on the Alert network, but not the Orienting or Executive ones. More specifically, Martial Artists showed improved performance when alert had to be sustained endogenously, performing more like the control group when an exogenous cue was provided. This result was further confirmed by a negative correlation between number of years of Martial Arts experience and the costs due to the lack of an exogenous cue suggesting that the longer a person takes part in the sport, the better their endogenous alert is. Results are interpreted in the context of the impact of training a particular attentional state in specific neurocognitive pathways.

  17. The role and responsibilities of management for the training and qualification of nuclear power plant personnel

    Mautner Markhof, F.

    1998-01-01

    The aim of this paper is to provide management-level personnel with an overview and understanding of their main role and responsibilities related to training, competence and qualification of NPP personnel. It addresses the responsibilities of various levels of management personnel, emphasizing performance excellence and effective management through successful dealing with key issues and problems

  18. Exposing College Students to Exercise: The Training Interventions and Genetics of Exercise Response (TIGER) Study

    Sailors, Mary H.; Jackson, Andrew S.; McFarlin, Brian K.; Turpin, Ian; Ellis, Kenneth J.; Foreyt, John P.; Hoelscher, Deanna M.; Bray, Molly S.

    2010-01-01

    Objective: The Training Interventions and Genetics of Exercise Response (TIGER) study is an exercise program designed to introduce sedentary college students to regular physical activity and to identify genetic factors that influence response to exercise. Participants: A multiracial/ethnic cohort (N = 1,567; 39% male), age 18 to 35 years,…

  19. Research on Linear Wireless Sensor Networks Used for Online Monitoring of Rolling Bearing in Freight Train

    Wang Nan; Meng Qingfeng; Zheng Bin; Li Tong; Ma Qinghai

    2011-01-01

    This paper presents a Wireless Sensor Networks (WSNs) technique for the purpose of on-line monitoring of rolling bearing in freight train. A new technical scheme including the arrangements of sensors, the design of sensor nodes and base station, routing protocols, signal acquirement, processing and transmission is described, and an on-line monitoring system is established. Considering the approximately linear arrangements of cars and the running state of freight train, a linear topology structure of WSNs is adopted and five linear routing protocols are discussed in detail as to obtain the desired minimum energy consumption of WSNs. By analysing the simulation results, an optimal multi-hop routing protocol named sub-section routing protocol according to equal distance is adopted, in which all sensor nodes are divided into different groups according to the equal transmission distance, the optimal transmission distance and number of hops of routing protocol are also studied. We know that the communication consumes significant power in WSNs, so, in order to save the limit power supply of WSNs, the data compression and coding scheme based on lifting integer wavelet and embedded zerotree wavelet (EZW) algorithms is studied to reduce the amounts of data transmitted. The experimental results of rolling bearing have been given at last to verify the effectiveness of data compression algorithm. The on-line monitoring system of rolling bearing in freight train will be applied to actual application in the near future.

  20. Using Wireless Sensor Networks and Trains as Data Mules to Monitor Slab Track Infrastructures.

    Cañete, Eduardo; Chen, Jaime; Díaz, Manuel; Llopis, Luis; Reyna, Ana; Rubio, Bartolomé

    2015-06-26

    Recently, slab track systems have arisen as a safer and more sustainable option for high speed railway infrastructures, compared to traditional ballasted tracks. Integrating Wireless Sensor Networks within these infrastructures can provide structural health related data that can be used to evaluate their degradation and to not only detect failures but also to predict them. The design of such systems has to deal with a scenario of large areas with inaccessible zones, where neither Internet coverage nor electricity supply is guaranteed. In this paper we propose a monitoring system for slab track systems that measures vibrations and displacements in the track. Collected data is transmitted to passing trains, which are used as data mules to upload the information to a remote control center. On arrival at the station, the data is stored in a database, which is queried by an application in order to detect and predict failures. In this paper, different communication architectures are designed and tested to select the most suitable system meeting such requirements as efficiency, low cost and data accuracy. In addition, to ensure communication between the sensing devices and the train, the communication system must take into account parameters such as train speed, antenna coverage, band and frequency.

  1. Using Wireless Sensor Networks and Trains as Data Mules to Monitor Slab Track Infrastructures

    Eduardo Cañete

    2015-06-01

    Full Text Available Recently, slab track systems have arisen as a safer and more sustainable option for high speed railway infrastructures, compared to traditional ballasted tracks. Integrating Wireless Sensor Networks within these infrastructures can provide structural health related data that can be used to evaluate their degradation and to not only detect failures but also to predict them. The design of such systems has to deal with a scenario of large areas with inaccessible zones, where neither Internet coverage nor electricity supply is guaranteed. In this paper we propose a monitoring system for slab track systems that measures vibrations and displacements in the track. Collected data is transmitted to passing trains, which are used as data mules to upload the information to a remote control center. On arrival at the station, the data is stored in a database, which is queried by an application in order to detect and predict failures. In this paper, different communication architectures are designed and tested to select the most suitable system meeting such requirements as efficiency, low cost and data accuracy. In addition, to ensure communication between the sensing devices and the train, the communication system must take into account parameters such as train speed, antenna coverage, band and frequency.

  2. Research on Linear Wireless Sensor Networks Used for Online Monitoring of Rolling Bearing in Freight Train

    Wang Nan; Meng Qingfeng; Zheng Bin [Theory of Lubrication and Bearing Institute, Xi' an Jiaotong University Xi' an, 710049 (China); Li Tong; Ma Qinghai, E-mail: heroyoyu.2009@stu.xjtu.edu.cn [Xi' an Rail Bureau, Xi' an, 710054 (China)

    2011-07-19

    This paper presents a Wireless Sensor Networks (WSNs) technique for the purpose of on-line monitoring of rolling bearing in freight train. A new technical scheme including the arrangements of sensors, the design of sensor nodes and base station, routing protocols, signal acquirement, processing and transmission is described, and an on-line monitoring system is established. Considering the approximately linear arrangements of cars and the running state of freight train, a linear topology structure of WSNs is adopted and five linear routing protocols are discussed in detail as to obtain the desired minimum energy consumption of WSNs. By analysing the simulation results, an optimal multi-hop routing protocol named sub-section routing protocol according to equal distance is adopted, in which all sensor nodes are divided into different groups according to the equal transmission distance, the optimal transmission distance and number of hops of routing protocol are also studied. We know that the communication consumes significant power in WSNs, so, in order to save the limit power supply of WSNs, the data compression and coding scheme based on lifting integer wavelet and embedded zerotree wavelet (EZW) algorithms is studied to reduce the amounts of data transmitted. The experimental results of rolling bearing have been given at last to verify the effectiveness of data compression algorithm. The on-line monitoring system of rolling bearing in freight train will be applied to actual application in the near future.

  3. Physiological and behavioral responses of horses during police training

    Munsters, C.C.B.M.; Visser, E.K.; Broek, van den J.; Sloet van Oldruitenborgh-Oosterbaan, M.M.

    2013-01-01

    Mounted police horses have to cope with challenging, unpredictable situations when on duty and it is essential to gain insight into how these horses handle stress to warrant their welfare. The aim of the study was to evaluate physiological and behavioral responses of 12 (six experienced and six

  4. Exercise training alters effect of high-fat feeding on the ACTH stress response in pigs.

    Jankord, Ryan; Ganjam, Venkataseshu K; Turk, James R; Hamilton, Marc T; Laughlin, M Harold

    2008-06-01

    Eating and physical activity behaviors influence neuroendocrine output. The purpose of this study was to test, in an animal model of diet-induced cardiovascular disease, the effects of high-fat feeding and exercise training on hypothalamo-pituitary-adrenocortical (HPA) axis activity. We hypothesized that a high-fat diet would increase circulating free fatty acids (FFAs) and decrease the adrenocorticotropic hormone (ACTH) and cortisol response to an acute stressor. We also hypothesized that exercise training would reverse the high-fat diet-induced changes in FFAs and thereby restore the ACTH and cortisol response. Pigs were placed in 1 of 4 groups (normal diet, sedentary; normal diet, exercise training; high-fat diet, sedentary; high-fat diet, exercise training; n = 8/group). Animals were placed on their respective dietary and activity treatments for 16-20 weeks. After completion of the treatments animals were anesthetized and underwent surgical intubation. Blood samples were collected after surgery and the ACTH and cortisol response to surgery was determined and the circulating concentrations of FFAs, glucose, cholesterol, insulin, and IGF-1 were measured. Consistent with our hypothesis, high-fat feeding increased FFAs by 200% and decreased the ACTH stress response by 40%. In exercise-trained animals, the high-fat diet also increased FFA; however, the increase in FFA in exercise-trained pigs was accompanied by a 60% increase in the ACTH response. The divergent effect of high-fat feeding on ACTH response was not expected, as exercise training alone had no effect on the ACTH response. Results demonstrate a significant interaction between diet and exercise and their effect on the ACTH response. The divergent effects of high-fat diet could not be explained by changes in weight gain, blood glucose, insulin, or IGF-1, as these were altered by high-fat feeding, but unaffected by exercise training. Thus, the increase in FFA with high-fat feeding may explain the blunted

  5. Inferring a Drive-Response Network from Time Series of Topological Measures in Complex Networks with Transfer Entropy

    Xinbo Ai

    2014-11-01

    Full Text Available Topological measures are crucial to describe, classify and understand complex networks. Lots of measures are proposed to characterize specific features of specific networks, but the relationships among these measures remain unclear. Taking into account that pulling networks from different domains together for statistical analysis might provide incorrect conclusions, we conduct our investigation with data observed from the same network in the form of simultaneously measured time series. We synthesize a transfer entropy-based framework to quantify the relationships among topological measures, and then to provide a holistic scenario of these measures by inferring a drive-response network. Techniques from Symbolic Transfer Entropy, Effective Transfer Entropy, and Partial Transfer Entropy are synthesized to deal with challenges such as time series being non-stationary, finite sample effects and indirect effects. We resort to kernel density estimation to assess significance of the results based on surrogate data. The framework is applied to study 20 measures across 2779 records in the Technology Exchange Network, and the results are consistent with some existing knowledge. With the drive-response network, we evaluate the influence of each measure by calculating its strength, and cluster them into three classes, i.e., driving measures, responding measures and standalone measures, according to the network communities.

  6. Training and exercises of the Emergency Response Team at the Los Alamos Plutonium Facility

    Yearwood, D.D.

    1988-01-01

    The Los Alamos National Laboratory Plutonium Facility has an active Emergency Response Team. The Emergency Response Team is composed of members of the operating and support groups within the Plutonium Facility. In addition to their initial indoctrination, the members are trained and certified in first-aid, CPR, fire and rescue, and the use of self-contained-breathing-apparatus. Training exercises, drills, are conducted once a month. The drills consist of scenarios which require the Emergency Response Team to apply CPR and/or first aid. The drills are performed in the Plutonium Facility, they are video taped, then reviewed and critiqued by site personnel. Through training and effective drills and the Emergency Response Team can efficiently respond to any credible accident which may occur at the Plutonium Facility. 3 tabs

  7. The neuronal response to electrical constant-amplitude pulse train stimulation: additive Gaussian noise.

    Matsuoka, A J; Abbas, P J; Rubinstein, J T; Miller, C A

    2000-11-01

    Experimental results from humans and animals show that electrically evoked compound action potential (EAP) responses to constant-amplitude pulse train stimulation can demonstrate an alternating pattern, due to the combined effects of highly synchronized responses to electrical stimulation and refractory effects (Wilson et al., 1994). One way to improve signal representation is to reduce the level of across-fiber synchrony and hence, the level of the amplitude alternation. To accomplish this goal, we have examined EAP responses in the presence of Gaussian noise added to the pulse train stimulus. Addition of Gaussian noise at a level approximately -30 dB relative to EAP threshold to the pulse trains decreased the amount of alternation, indicating that stochastic resonance may be induced in the auditory nerve. The use of some type of conditioning stimulus such as Gaussian noise may provide a more 'normal' neural response pattern.

  8. A Partnership Training Program in Breast Cancer Diagnosis: Concept Development of the Next Generation Diagnostic Breast Imaging Using Digital Image Library and Networking Techniques

    Chouikha, Mohamed F

    2004-01-01

    ...); and Georgetown University (Image Science and Information Systems, ISIS). In this partnership training program, we will train faculty and students in breast cancer imaging, digital image database library techniques and network communication strategy...

  9. Quantization and training of object detection networks with low-precision weights and activations

    Yang, Bo; Liu, Jian; Zhou, Li; Wang, Yun; Chen, Jie

    2018-01-01

    As convolutional neural networks have demonstrated state-of-the-art performance in object recognition and detection, there is a growing need for deploying these systems on resource-constrained mobile platforms. However, the computational burden and energy consumption of inference for these networks are significantly higher than what most low-power devices can afford. To address these limitations, this paper proposes a method to train object detection networks with low-precision weights and activations. The probability density functions of weights and activations of each layer are first directly estimated using piecewise Gaussian models. Then, the optimal quantization intervals and step sizes for each convolution layer are adaptively determined according to the distribution of weights and activations. As the most computationally expensive convolutions can be replaced by effective fixed point operations, the proposed method can drastically reduce computation complexity and memory footprint. Performing on the tiny you only look once (YOLO) and YOLO architectures, the proposed method achieves comparable accuracy to their 32-bit counterparts. As an illustration, the proposed 4-bit and 8-bit quantized versions of the YOLO model achieve a mean average precision of 62.6% and 63.9%, respectively, on the Pascal visual object classes 2012 test dataset. The mAP of the 32-bit full-precision baseline model is 64.0%.

  10. BIOCHEMICAL CHANGES AND ENDOCRINE RESPONSES IN PRE-COMPETITION TRAINING IN ELITE SWIMMERS

    Yue Li

    2012-01-01

    Full Text Available The aim of this study was to describe biochemical changes and endocrine responses to low-volume pre-competition swimming training for elite swimmers. Twelve sprint swimmers (6 males and 6 females participated in 3-week pre-competition training. Measures of velocity anaerobic threshold (VAT, creatine kinase (CK, blood urea (BU, haemoglobin (Hb and testosterone/cortisol ratio (TC were obtained before and after the 1st, 2nd and 3rd week of training. The training load decreased from 27.3 to 13.7 km per week within 3 weeks. The VAT tested the load with an increased training protocol of 200 m×4 freestyle swimming and initial loads were 85, 90, 95, and 100 percent of the individual load. There were changes in the values of VAT, CK, BU, Hb and TC ratio during the training, and the changes corresponded to the changes of the training stimuli in time. There were also differences between the male and female swimmers. The most significant finding in this study was that such training stimulated the enginery of the swimmers and helped the swimmers recover enginery and indicated improved velocity in the competition with the following adjusting exercise after pre-competition training.

  11. Predictors and moderators of biopsychological social stress responses following brief self-compassion meditation training.

    Arch, Joanna J; Landy, Lauren N; Brown, Kirk Warren

    2016-07-01

    Arch et al. (2014) demonstrated that brief self-compassion meditation training (SCT) dampened sympathetic (salivary alpha-amylase) and subjective anxiety responses to the Trier Social Stress Test (TSST), relative to attention and no-instruction control conditions. The present study examined baseline predictors and moderators of these SCT intervention effects. Baseline characteristics included two stress vulnerability traits (social anxiety and rumination) and two potential resiliency traits (non-attachment and self-compassion). We investigated how these traits moderated the effects of SCT on response to the TSST, relative to the control conditions. We also tested how these individual differences predicted TSST responses across conditions in order to uncover characteristics that confer increased vulnerability and resiliency to social stressors. Trait non-attachment, rumination (for sympathetic TSST response only), and social anxiety (for subjective TSST response only) interacted with training condition to moderate TSST responses such that following SCT, lower attachment and lower social anxiety predicted lower TSST stress responses, relative to those scoring higher on these traits. In contrast, trait self-compassion neither moderated nor predicted responses to the TSST. Thus, although SCT had robust effects on buffering stress across individuals with varying levels of trait self-compassion, other psychological traits enhanced or dampened the effect of SCT on TSST responses. These findings support the importance of examining the role of relevant baseline psychological traits to predict sympathetic and subjective responses to social evaluative threat, particularly in the context of resiliency training. Copyright © 2016 Elsevier Ltd. All rights reserved.

  12. Stimulus- and response-reinforcer contingencies in autoshaping, operant, classical, and omission training procedures in rats.

    Atnip, G W

    1977-07-01

    Separate groups of rats received 500 trials of lever-press training under autoshaping (food delivery followed 10-second lever presentations, or occurred immediately following a response); operant conditioning (responding was necessary for food delivery); and classical conditioning (food followed lever presentations regardless of responding). Each group then received 500 trials on an omission procedure in which food was omitted on trials with a response. Another group received 1000 trials on the omission procedure, and a fifth group, random control, received 1000 uncorrelated presentations of lever and food. The autoshaping, operant, and classical groups reached high response levels by the end of initial training. Acquisition was fastest in the autoshaping group. Responding remained consistently low in the control group. The omission group responded at a level between the control group and the other three groups. During omission training, responding in these three groups declined to the omission-group level. During omission training, the rats continued contacting the lever frequently after lever pressing had declined. Response maintenance under omission training seems not to require topographic similarity between the response and reinforcer-elicited consummatory behaviors.

  13. Training motor responses to food: A novel treatment for obesity targeting implicit processes.

    Stice, Eric; Lawrence, Natalia S; Kemps, Eva; Veling, Harm

    2016-11-01

    The present review first summarizes results from prospective brain imaging studies focused on identifying neural vulnerability factors that predict excessive weight gain. Next, findings from cognitive psychology experiments evaluating various interventions involving food response inhibition training or food response facilitation training are reviewed that appear to target these neural vulnerability factors and that have produced encouraging weight loss effects. Findings from both of these reviewed research fields suggest that interventions that reduce reward and attention region responses to high calorie food cues and increase inhibitory region responses to high calorie food cues could prove useful in the treatment of obesity. Based on this review, a new conceptual model is presented to describe how different cognitive training procedures may contribute to modifying eating behavior and important directions for future research are offered. It is concluded that there is a need for evaluating the effectiveness of more intensive food response training interventions and testing whether adding such training to extant weight loss interventions increases their efficacy. Copyright © 2016 Elsevier Ltd. All rights reserved.

  14. Salivary Hormones Response to Preparation and Pre-competitive Training of World-class Level Athletes

    Guilhem, Gaël; Hanon, Christine; Gendreau, Nicolas; Bonneau, Dominique; Guével, Arnaud; Chennaoui, Mounir

    2015-01-01

    This study aimed to compare the response of salivary hormones of track and field athletes induced by preparation and pre-competitive training periods in an attempt to comment on the physiological effects consistent with the responses of each of the proteins measured. Salivary testosterone, cortisol, alpha-amylase, immunoglobulin A (IgA), chromogranin A, blood creatine kinase activity, and profile of mood state were assessed at rest in 24 world-class level athletes during preparation (3 times in 3 months) and pre-competitive (5 times in 5 weeks) training periods. Total mood disturbance and fatigue perception were reduced, while IgA (+61%) and creatine kinase activity (+43%) increased, and chromogranin A decreased (−27%) during pre-competitive compared to preparation period. A significant increase in salivary testosterone (+9 to +15%) and a decrease in testosterone/cortisol ratio were associated with a progressive reduction in training load during pre-competitive period (P athletics training. PMID:26635619

  15. Glucosamine but not ibuprofen alters cartilage turnover in osteoarthritis patients in response to physical training

    Petersen, Susanne Germann; Saxne, T; Heinegard, D

    2010-01-01

    OBJECTIVE: To investigate changes in levels of serum cartilage oligomeric matrix protein (COMP) and urine c-telopeptide of type-2 collagen (CTX-II) as markers for cartilage turnover in patients with osteoarthritis (OA) of the knee, in response to muscle strength training in combination with treat......OBJECTIVE: To investigate changes in levels of serum cartilage oligomeric matrix protein (COMP) and urine c-telopeptide of type-2 collagen (CTX-II) as markers for cartilage turnover in patients with osteoarthritis (OA) of the knee, in response to muscle strength training in combination......). RESULTS: All three groups increased their muscle strength following 12 weeks of strength training (Preduced in the glucosamine-treated group after the training period (P=0.012), whereas they did not change in the two other groups. Glucosamine reduced COMP statistically...

  16. Development of a virtual reality training system. An application to emergency response in radioactive materials transport

    Watabe, Naohito

    2003-01-01

    A virtual reality (VR) training system was developed for the purpose of confirming the applicability of virtual reality on training systems for emergency response of radioactive materials transport. This system has following features; 1) Accident scenarios were derived from an event tree analysis. 2) Instructors can edit the training scenario. 3) Three VR scenes were prepared: vehicle and equipment checks, vehicle travel on an expressway, and emergency response in a tunnel fire accident. 4) every action by users is recorded automatically. 5) Instructors and users hold briefing session after the training, and they can review and confirm the results with VR animation. 6) A support database is provided for the convenience of users. The applicability of the system was validated through some trial applications and demonstrations. (author)

  17. Myogenic response of human skeletal muscle to 12 weeks of resistance training at light loading intensity

    Mackey, Abigail; Holm, L; Reitelseder, S

    2011-01-01

    There is strong evidence for enhanced numbers of satellite cells with heavy resistance training. The satellite cell response to very light muscle loading is, however, unknown. We, therefore, designed a 12-week training protocol where volunteers trained one leg with a high load (H) and the other leg...... with a light load (L). Twelve young healthy men [mean age 25 ± 3 standard deviation (SD) years] volunteered for the study. Muscle biopsies were collected from the m. vastus lateralis of both legs before and after the training period and satellite cells were visualized by CD56 immunohistochemistry....... A significant main effect of time was observed (P12 ± 0.03 to 0.15 ± 0.05, mean ± SD). The finding that 12 weeks of training skeletal muscle even with very light loads can induce an increase in the number of satellite...

  18. Development and Operation of International Nuclear Education/Training Program and HRD Cooperation Network

    Lee, E. J.; Min, B. J.; Han, K. W.

    2006-12-01

    The primary result of the project is the establishment of a concept of International Nuclear R and D Academy that integrates the on-going long term activity for international nuclear education/training and a new activity to establish an international cooperation network for nuclear human resources development. For this, the 2007 WNU Summer Institute was hosted with the establishment of an MOU and subsequent preparations. Also, ANENT was promoted through development of a cyber platform for the ANENT web-portal, hosting the third ANENT Coordination Committee meeting, etc. Then a cooperation with universities in Vietnam was launched resulting in preparation of an MOU for the cooperation. Finally, a relevant system framework was established and required procedures were drafted especially for providing students from developing countries with long term education/training programs (e.g. MS and Ph D. courses). The international nuclear education/training programs have offered 13 courses to 182 people from 43 countries. The overall performance of the courses was evaluated to be outstanding. In parallel, the establishment of an MOU for the cooperation of KOICA-IAEA-KAERI courses to ensure their stable and systematic operation. Also, an effort was made to participate in FNCA. Atopia Hall of the International Nuclear Training and Education Center (INTEC) hosted 477 events (corresponding to 18,521 participants) and Nuri Hall (guesthouse) accommodated 4,616 people in 2006. This shows a steady increase of the use rate since the opening of the center, along with a continuous improvement of the equipment

  19. Development and Operation of International Nuclear Education/Training Program and HRD Cooperation Network

    Lee, E J; Min, B J; Han, K W [and others

    2006-12-15

    The primary result of the project is the establishment of a concept of International Nuclear R and D Academy that integrates the on-going long term activity for international nuclear education/training and a new activity to establish an international cooperation network for nuclear human resources development. For this, the 2007 WNU Summer Institute was hosted with the establishment of an MOU and subsequent preparations. Also, ANENT was promoted through development of a cyber platform for the ANENT web-portal, hosting the third ANENT Coordination Committee meeting, etc. Then a cooperation with universities in Vietnam was launched resulting in preparation of an MOU for the cooperation. Finally, a relevant system framework was established and required procedures were drafted especially for providing students from developing countries with long term education/training programs (e.g. MS and Ph D. courses). The international nuclear education/training programs have offered 13 courses to 182 people from 43 countries. The overall performance of the courses was evaluated to be outstanding. In parallel, the establishment of an MOU for the cooperation of KOICA-IAEA-KAERI courses to ensure their stable and systematic operation. Also, an effort was made to participate in FNCA. Atopia Hall of the International Nuclear Training and Education Center (INTEC) hosted 477 events (corresponding to 18,521 participants) and Nuri Hall (guesthouse) accommodated 4,616 people in 2006. This shows a steady increase of the use rate since the opening of the center, along with a continuous improvement of the equipment.

  20. Environmental Learning in Online Social Networks: Adopting Environmentally Responsible Behaviors

    Robelia, Beth A.; Greenhow, Christine; Burton, Lisa

    2011-01-01

    Online social networks are increasingly important information and communication tools for young people and for the environmental movement. Networks may provide the motivation for young adults to increase environmental behaviors by increasing their knowledge of environmental issues and of the specific actions they can take to reduce greenhouse gas…

  1. Influence of the Training Set Value on the Quality of the Neural Network to Identify Selected Moulding Sand Properties

    Jakubski J.

    2013-06-01

    Full Text Available Artificial neural networks are one of the modern methods of the production optimisation. An attempt to apply neural networks for controlling the quality of bentonite moulding sands is presented in this paper. This is the assessment method of sands suitability by means of detecting correlations between their individual parameters. This paper presents the next part of the study on usefulness of artificial neural networks to support rebonding of green moulding sand, using chosen properties of moulding sands, which can be determined fast. The effect of changes in the training set quantity on the quality of the network is presented in this article. It has been shown that a small change in the data set would change the quality of the network, and may also make it necessary to change the type of network in order to obtain good results.

  2. Extinction Training Regulates Neuroadaptive Responses to Withdrawal from Chronic Cocaine Self-Administration

    Self, David W.; Choi, Kwang-Ho; Simmons, Diana; Walker, John R.; Smagula, Cynthia S.

    2004-01-01

    Cocaine produces multiple neuroadaptations with chronic repeated use. Many of these neuroadaptations can be reversed or normalized by extinction training during withdrawal from chronic cocaine self-administration in rats. This article reviews our past and present studies on extinction-induced modulation of the neuroadaptive response to chronic cocaine in the mesolimbic dopamine system, and the role of this modulation in addictive behavior in rats. Extinction training normalizes tyrosine hydro...

  3. Transferring Pre-Trained Deep CNNs for Remote Scene Classification with General Features Learned from Linear PCA Network

    Jie Wang

    2017-03-01

    Full Text Available Deep convolutional neural networks (CNNs have been widely used to obtain high-level representation in various computer vision tasks. However, in the field of remote sensing, there are not sufficient images to train a useful deep CNN. Instead, we tend to transfer successful pre-trained deep CNNs to remote sensing tasks. In the transferring process, generalization power of features in pre-trained deep CNNs plays the key role. In this paper, we propose two promising architectures to extract general features from pre-trained deep CNNs for remote scene classification. These two architectures suggest two directions for improvement. First, before the pre-trained deep CNNs, we design a linear PCA network (LPCANet to synthesize spatial information of remote sensing images in each spectral channel. This design shortens the spatial “distance” of target and source datasets for pre-trained deep CNNs. Second, we introduce quaternion algebra to LPCANet, which further shortens the spectral “distance” between remote sensing images and images used to pre-train deep CNNs. With five well-known pre-trained deep CNNs, experimental results on three independent remote sensing datasets demonstrate that our proposed framework obtains state-of-the-art results without fine-tuning and feature fusing. This paper also provides baseline for transferring fresh pretrained deep CNNs to other remote sensing tasks.

  4. Cognitive radio-aided wireless sensor networks for emergency response

    Arkoulis, Stamatios; Spanos, Dimitrios-Emmanuel; Barbounakis, Socrates; Zafeiropoulos, Anastasios; Mitrou, Nikolas

    2010-01-01

    A lot of research effort has been put into wireless sensor networks (WSNs) and several methods have been proposed to minimize the energy consumption and maximize the network's lifetime. However, little work has been carried out regarding WSNs deployed for emergency situations. We argue that such WSNs should function under a flexible channel allocation scheme when needed and be able to operate and adapt in dynamic, ever-changing environments coexisting with other interfering networks (IEEE 802.11b/g, 802.15.4, 802.15.1). In this paper, a simple and efficient method for the detection of a single operational frequency channel that guarantees satisfactory communication among all network nodes is proposed. Experimental measurements carried out in a real environment reveal the coexistence problem among networks in close proximity that operate in the same frequency band and prove the validity and efficiency of our approach

  5. Early and late rate of force development: differential adaptive responses to resistance training?

    Andersen, L L; Andersen, Jesper Løvind; Zebis, M K

    2010-01-01

    The objective of this study is to investigate the potentially opposing influence of qualitative and quantitative muscular adaptations in response to high-intensity resistance training on contractile rate of force development (RFD) in the early (200 ms) of rising muscle force. Fifteen healthy young......-intensity resistance training due to differential influences of qualitative and quantitative muscular adaptations on early and later phases of rising muscle force....... males participated in a 14-week resistance training intervention for the lower body and 10 matched subjects participated as controls. Maximal muscle strength (MVC) and RFD were measured during maximal voluntary isometric contraction of the quadriceps femoris muscle. Muscle biopsies were obtained from...

  6. A 12-week resistance training program elicits positive changes in hemodynamic responses in the elderly

    Cinthya Campos Salazar

    2009-03-01

    Full Text Available The aim of the study was to determine the effect of a resistance training program in hemodynamic responses and adaptations in 60 yr. old elderly. Volunteers were 60 healthy-elderly who underwent a training program 3 times/wk. for 12 wk. Participants were randomly assigned to either a control group, an exercise group who trained at 30% intensity of 5 maximal repetitions (5RM (30% of 5RM or an exercise group at an intensity of 70% (70% of 5RM. Hemodynamic variables measured were mean arterial pressure (MAP, calculated before and immediately after the training session, and rate pressure product (RPP, estimated once a month and before and after finishing the program. Results indicated that resistance exercise training at 30% and 70% of 5RM, with a total exercise work of 872.7 and 890.9 kg did not elicited cardiovascular risks for the elderly. A 12-wk resistance exercise training reduced the cardiovascular strain as shown by the RPP (~16% and the MAP (~9%, with no adverse effects throughout the program. Unfortunately, all the hemodynamic benefits were reverted 6 days following completion of the program. In conclusion, a healthy elderly population must perform resistance training exercises to significantly reduce the cardiovascular stress. We suggest to conduct further research that looks into different exercise intensities in longer program duration and to determine the mechanisms responsible for the deleterious effects of the detraining by using physiological, biochemical and biomechanical variables.

  7. Hazardous materials emergency response training program at Texas A ampersand M University

    Stirling, A.G.

    1989-01-01

    The Texas Engineering Extension Service (TEEX) as the engineering vocational training arm of the Texas A ampersand M University system has conducted oil-spill, hazardous-material, and related safety training for industry since 1976 and fire suppression training since 1931. In 1987 TEEX conducted training for some 66,000 persons, of which some 6000 were in hazardous-materials safety training and 22,000 in fire suppression or related fields. Various laws and regulations exist relative to employee training at an industrial facility, such as the Hazard Communication Act, the Resource Conservation and Recovery Act (RCRA), the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA or more commonly Superfund), the Community Right to Know Law, and the Superfund Amendments and Reauthorization Act (SARA), Titles I and III. The TEEX programs developed on the foundation emphasize the hands-on approach (60% field exercises) to provide a comprehensive training curriculum resulting in regulatory compliance, an effective emergency response capability, a prepared community, and a safe work environment

  8. Bladder cancer treatment response assessment in CT urography using two-channel deep-learning network

    Cha, Kenny H.; Hadjiiski, Lubomir M.; Chan, Heang-Ping; Samala, Ravi K.; Cohan, Richard H.; Caoili, Elaine M.; Weizer, Alon Z.; Alva, Ajjai

    2018-02-01

    We are developing a CAD system for bladder cancer treatment response assessment in CT. We trained a 2- Channel Deep-learning Convolution Neural Network (2Ch-DCNN) to identify responders (T0 disease) and nonresponders to chemotherapy. The 87 lesions from 82 cases generated 18,600 training paired ROIs that were extracted from segmented bladder lesions in the pre- and post-treatment CT scans and partitioned for 2-fold cross validation. The paired ROIs were input to two parallel channels of the 2Ch-DCNN. We compared the 2Ch-DCNN with our hybrid prepost- treatment ROI DCNN method and the assessments by 2 experienced abdominal radiologists. The radiologist estimated the likelihood of stage T0 after viewing each pre-post-treatment CT pair. Receiver operating characteristic analysis was performed and the area under the curve (AUC) and the partial AUC at sensitivity AUC0.9) were compared. The test AUCs were 0.76+/-0.07 and 0.75+/-0.07 for the 2 partitions, respectively, for the 2Ch-DCNN, and were 0.75+/-0.08 and 0.75+/-0.07 for the hybrid ROI method. The AUCs for Radiologist 1 were 0.67+/-0.09 and 0.75+/-0.07 for the 2 partitions, respectively, and were 0.79+/-0.07 and 0.70+/-0.09 for Radiologist 2. For the 2Ch-DCNN, the AUC0.9s were 0.43 and 0.39 for the 2 partitions, respectively, and were 0.19 and 0.28 for the hybrid ROI method. For Radiologist 1, the AUC0.9s were 0.14 and 0.34 for partition 1 and 2, respectively, and were 0.33 and 0.23 for Radiologist 2. Our study demonstrated the feasibility of using a 2Ch-DCNN for the estimation of bladder cancer treatment response in CT.

  9. The Role of Eif6 in Skeletal Muscle Homeostasis Revealed by Endurance Training Co-expression Networks

    Kim Clarke

    2017-11-01

    Full Text Available Regular endurance training improves muscle oxidative capacity and reduces the risk of age-related disorders. Understanding the molecular networks underlying this phenomenon is crucial. Here, by exploiting the power of computational modeling, we show that endurance training induces profound changes in gene regulatory networks linking signaling and selective control of translation to energy metabolism and tissue remodeling. We discovered that knockdown of the mTOR-independent factor Eif6, which we predicted to be a key regulator of this process, affects mitochondrial respiration efficiency, ROS production, and exercise performance. Our work demonstrates the validity of a data-driven approach to understanding muscle homeostasis.

  10. Asian network for education in nuclear technology: An initiative to promote education and training in nuclear technology

    Kosilov, A.

    2006-01-01

    It has become increasingly clear that there is a need to consolidate the efforts of academia and industry in education and training. Partnerships of operating organizations with educational institutions and universities that provide qualified professionals for the nuclear industry should be assessed based upon medium and long term needs and strengthened where needed. In this regard the IAEA is taking the necessary action to initiate this kind of partnership through continuous networking. The paper describes the IAEA approach to promoting education and training through the Asian Network for Education in Nuclear Technology (ANENT). (author)

  11. Adaptation of perceptual responses to low-load blood flow restriction training

    Martín-Hernández, Juan; Ruiz-Aguado, Jorge; Herrero, Azael Juan

    2017-01-01

    The purpose of this study was to determine the adaptive response of ratings of perceived exertion (RPE) and pain over six consecutive training sessions. Thirty subjects were assigned to either a blood flow restricted training group (BFRT) or a high intensity group (HIT). BFRT group performed four...... sets (30+15+15+15, respectively) of unilateral leg extension at an intensity of 20% one repetition maximum (1RM) while a restrictive cuff was applied to the most proximal part of the leg. HIT group performed 3 sets of eight repetitions with 85%1RM. RPE and pain were assessed following every exercise.......01). No between-group differences were found at any time point. In summary, BFRT induces a high perceptual response to training. However, this perceptual response is rapidly attenuated, leading to values similar to those experienced during HIT. Low load BFRT should not be limited to highly motivated individuals...

  12. Changes in fat oxidation in response to various regimes of high intensity interval training (HIIT).

    Astorino, Todd Anthony; Schubert, Matthew M

    2018-01-01

    Increased whole-body fat oxidation (FOx) has been consistently demonstrated in response to moderate intensity continuous exercise training. Completion of high intensity interval training (HIIT) and its more intense form, sprint interval training (SIT), has also been reported to increase FOx in different populations. An explanation for this increase in FOx is primarily peripheral adaptations via improvements in mitochondrial content and function. However, studies examining changes in FOx are less common in response to HIIT or SIT than those determining increases in maximal oxygen uptake which is concerning, considering that FOx has been identified as a predictor of weight gain and glycemic control. In this review, we explored physiological and methodological issues underpinning existing literature concerning changes in FOx in response to HIIT and SIT. Our results show that completion of interval training increases FOx in approximately 50% of studies, with the frequency of increased FOx higher in response to studies using HIIT compared to SIT. Significant increases in β-HAD, citrate synthase, fatty acid binding protein, or FAT/CD36 are likely responsible for the greater FOx seen in these studies. We encourage scientists to adopt strict methodological procedures to attenuate day-to-day variability in FOx, which is dramatic, and develop standardized procedures for assessing FOx, which may improve detection of changes in FOx in response to HIIT.

  13. IAEA emergency response network ERNET. Emergency preparedness and response. Date effective: 1 December 2002

    2003-04-01

    The Parties to the Convention on Assistance in the Case of a Nuclear Accident or Radiological Emergency have undertaken to co-operate among themselves and with the IAEA in facilitating the prompt provision of assistance in the event of a nuclear accident or radiological emergency, and in minimizing the consequences and in protecting life, property and the environment from the effects of any radioactive releases. As part of the IAEA strategy for supporting such co-operation, the Secretariat of the IAEA is establishing a global Emergency Response Network (ERNET) of teams suitably qualified to respond rapidly, on a regional basis, to nuclear accidents or radiological emergencies. This manual sets out the criteria and requirements to be met by ERNET teams. It is intended for use by institutions in Member States in developing, applying and maintaining their emergency response capabilities and in implementing quality assurance programmes within the context of ERNET. The manual is worded on the assumption that a State Competent Authority designated as the body responsible for reacting to nuclear accidents or radiological emergencies which occur outside the jurisdiction of that State will be the State Contact Point for receiving requests for assistance from the IAEA under the Convention on Assistance in the Case of a Nuclear Accident or Radiological Emergency

  14. IAEA emergency response network ERNET. Emergency preparedness and response. Date effective: 1 December 2000

    2000-12-01

    The Parties to the Convention on Assistance in the Case of a Nuclear Accident or Radiological Emergency have undertaken to co-operate among themselves and with the IAEA in facilitating the prompt provision of assistance in the event of a nuclear accident or radiological emergency, and in minimizing the consequences and in protecting life, property and the environment from the effects of any radioactive releases. As part of the IAEA strategy for supporting such co-operation, the Secretariat of the IAEA is establishing a global Emergency Response Network (ERNET) of teams suitably qualified to respond rapidly, on a regional basis, to nuclear accidents or radiological emergencies. This manual sets out the criteria and requirements to be met by ERNET teams. It is intended for use by institutions in Member States in developing, applying and maintaining their emergency response capabilities and in implementing quality assurance programmes within the context of ERNET. The manual is worded on the assumption that a State Competent Authority designated as the body responsible for reacting to nuclear accidents or radiological emergencies which occur outside the jurisdiction of that State will be the State Contact Point for receiving requests for assistance from the IAEA under the Convention on Assistance in the Case of a Nuclear Accident or Radiological Emergency

  15. Functional MRI neurofeedback training on connectivity between two regions induces long-lasting changes in intrinsic functional network

    Fukuda eMegumi

    2015-03-01

    Full Text Available Motor or perceptual learning is known to influence functional connectivity between brain regions and induce short-term changes in the intrinsic functional networks revealed as correlations in slow blood-oxygen-level dependent (BOLD signal fluctuations. However, no cause-and-effect relationship has been elucidated between a specific change in connectivity and a long-term change in global networks. Here, we examine the hypothesis that functional connectivity (i.e. temporal correlation between two regions is increased and preserved for a long time when two regions are simultaneously activated or deactivated. Using the connectivity-neurofeedback training paradigm, subjects successfully learned to increase the correlation of activity between the lateral parietal and primary motor areas, regions that belong to different intrinsic networks and negatively correlated before training under the resting conditions. Furthermore, whole-brain hypothesis-free analysis as well as functional network analyses demonstrated that the correlation in the resting state between these areas as well as the correlation between the intrinsic networks that include the areas increased for at least two months. These findings indicate that the connectivity-neurofeedback training can cause long-term changes in intrinsic connectivity and that intrinsic networks can be shaped by experience-driven modulation of regional correlation.

  16. A parallel neural network training algorithm for control of discrete dynamical systems.

    Gordillo, J. L.; Hanebutte, U. R.; Vitela, J. E.

    1998-01-20

    In this work we present a parallel neural network controller training code, that uses MPI, a portable message passing environment. A comprehensive performance analysis is reported which compares results of a performance model with actual measurements. The analysis is made for three different load assignment schemes: block distribution, strip mining and a sliding average bin packing (best-fit) algorithm. Such analysis is crucial since optimal load balance can not be achieved because the work load information is not available a priori. The speedup results obtained with the above schemes are compared with those corresponding to the bin packing load balance scheme with perfect load prediction based on a priori knowledge of the computing effort. Two multiprocessor platforms: a SGI/Cray Origin 2000 and a IBM SP have been utilized for this study. It is shown that for the best load balance scheme a parallel efficiency of over 50% for the entire computation is achieved by 17 processors of either parallel computers.

  17. Unscented Kalman Filter-Trained Neural Networks for Slip Model Prediction

    Li, Zhencai; Wang, Yang; Liu, Zhen

    2016-01-01

    The purpose of this work is to investigate the accurate trajectory tracking control of a wheeled mobile robot (WMR) based on the slip model prediction. Generally, a nonholonomic WMR may increase the slippage risk, when traveling on outdoor unstructured terrain (such as longitudinal and lateral slippage of wheels). In order to control a WMR stably and accurately under the effect of slippage, an unscented Kalman filter and neural networks (NNs) are applied to estimate the slip model in real time. This method exploits the model approximating capabilities of nonlinear state–space NN, and the unscented Kalman filter is used to train NN’s weights online. The slip parameters can be estimated and used to predict the time series of deviation velocity, which can be used to compensate control inputs of a WMR. The results of numerical simulation show that the desired trajectory tracking control can be performed by predicting the nonlinear slip model. PMID:27467703

  18. Artificial neural network and response surface methodology modeling in mass transfer parameters predictions during osmotic dehydration of Carica papaya L.

    J. Prakash Maran

    2013-09-01

    Full Text Available In this study, a comparative approach was made between artificial neural network (ANN and response surface methodology (RSM to predict the mass transfer parameters of osmotic dehydration of papaya. The effects of process variables such as temperature, osmotic solution concentration and agitation speed on water loss, weight reduction, and solid gain during osmotic dehydration were investigated using a three-level three-factor Box-Behnken experimental design. Same design was utilized to train a feed-forward multilayered perceptron (MLP ANN with back-propagation algorithm. The predictive capabilities of the two methodologies were compared in terms of root mean square error (RMSE, mean absolute error (MAE, standard error of prediction (SEP, model predictive error (MPE, chi square statistic (χ2, and coefficient of determination (R2 based on the validation data set. The results showed that properly trained ANN model is found to be more accurate in prediction as compared to RSM model.

  19. Training modifies innate immune responses in blood monocytes and in pulmonary alveolar macrophages.

    Frellstedt, Linda; Waldschmidt, Ingrid; Gosset, Philippe; Desmet, Christophe; Pirottin, Dimitri; Bureau, Fabrice; Farnir, Frédéric; Franck, Thierry; Dupuis-Tricaud, Marie-Capucine; Lekeux, Pierre; Art, Tatiana

    2014-07-01

    In humans, strenuous exercise causes increased susceptibility to respiratory infections associated with down-regulated expression of Toll-like receptors (TLRs) and costimulatory and antigen-presenting molecules. Lower airway diseases are also a common problem in sport and racing horses. Because innate immunity plays an essential role in lung defense mechanisms, we assessed the effect of acute exercise and training on innate immune responses in two different compartments. Blood monocytes and pulmonary alveolar macrophages (PAMs) were collected from horses in untrained, moderately trained, intensively trained, and deconditioned states before and after a strenuous exercise test. The cells were analyzed for TLR messenger ribonucleic acid (mRNA) expression by real-time PCR in vitro, and cytokine production after in vitro stimulation with TLR ligands was measured by ELISA. Our results showed that training, but not acute exercise, modified the innate immune responses in both compartments. The mRNA expression of TLR3 was down-regulated by training in both cell types, whereas the expression of TLR4 was up-regulated in monocytes. Monocytes treated with LPS and a synthetic diacylated lipoprotein showed increased cytokine secretion in trained and deconditioned subjects, indicating the activation of cells at the systemic level. The production of TNF-α and IFN-β in nonstimulated and stimulated PAMs was decreased in trained and deconditioned horses and might therefore explain the increased susceptibility to respiratory infections. Our study reports a dissociation between the systemic and the lung response to training that is probably implicated in the systemic inflammation and in the pulmonary susceptibility to infection.

  20. Affective and enjoyment responses in high intensity interval training and continuous training: A systematic review and meta-analysis.

    Bruno Ribeiro Ramalho Oliveira

    Full Text Available Previous studies investigating the effects of high intensity interval training (HIIT and moderate intensity continuous training (MICT showed controversial results. The aim of the present study was to systematically review the literature on the effects of HIIT and MICT on affective and enjoyment responses. The PRISMA Statement and the Cochrane recommendation were used to perform this systematic review and the database search was performed using PubMed, Scopus, ISI Web of Knowledge, PsycINFO, and SPORTDiscus. Eight studies investigating the acute affective and enjoyment responses on HIIT and MICT were included in the present systematic review. The standardized mean difference (SMD was calculated for Feeling Scale (FS, Physical Activity Enjoyment Scale (PACES and Exercise Enjoyment Scale (EES. The MICT was used as the reference condition. The overall results showed similar beneficial effects of HIIT on PACES and EES responses compared to MICT with SMDs classified as small (PACES-SMD = 0.49, I2 = 69.3%, p = 0.001; EES-SMD = 0.48, I2 = 24.1%, p = 0.245 while for FS, the overall result showed a trivial effect (FS-SMD = 0.19, I2 = 78.9%, p<0.001. Most of the comparisons performed presented positive effects for HIIT. For the FS, six of 12 comparisons showed beneficial effects for HIIT involving normal weight and overweight-to-obese populations. For PACES, six of 10 comparisons showed beneficial effects for HIIT involving normal weight and overweight-to-obese populations. For EES, six of seven comparisons showed beneficial effects for HIIT also involving normal weight and overweight-to-obese populations. Based on the results of the present study, it is possible to conclude that HIIT exercise may be a viable strategy for obtaining positive psychological responses. Although HIIT exercise may be recommended for obtaining positive psychological responses, chronic studies should clarify the applicability of HIIT for exercise adherence.

  1. Affective and enjoyment responses in high intensity interval training and continuous training: A systematic review and meta-analysis.

    Oliveira, Bruno Ribeiro Ramalho; Santos, Tony Meireles; Kilpatrick, Marcus; Pires, Flávio Oliveira; Deslandes, Andréa Camaz

    2018-01-01

    Previous studies investigating the effects of high intensity interval training (HIIT) and moderate intensity continuous training (MICT) showed controversial results. The aim of the present study was to systematically review the literature on the effects of HIIT and MICT on affective and enjoyment responses. The PRISMA Statement and the Cochrane recommendation were used to perform this systematic review and the database search was performed using PubMed, Scopus, ISI Web of Knowledge, PsycINFO, and SPORTDiscus. Eight studies investigating the acute affective and enjoyment responses on HIIT and MICT were included in the present systematic review. The standardized mean difference (SMD) was calculated for Feeling Scale (FS), Physical Activity Enjoyment Scale (PACES) and Exercise Enjoyment Scale (EES). The MICT was used as the reference condition. The overall results showed similar beneficial effects of HIIT on PACES and EES responses compared to MICT with SMDs classified as small (PACES-SMD = 0.49, I2 = 69.3%, p = 0.001; EES-SMD = 0.48, I2 = 24.1%, p = 0.245) while for FS, the overall result showed a trivial effect (FS-SMD = 0.19, I2 = 78.9%, pHIIT. For the FS, six of 12 comparisons showed beneficial effects for HIIT involving normal weight and overweight-to-obese populations. For PACES, six of 10 comparisons showed beneficial effects for HIIT involving normal weight and overweight-to-obese populations. For EES, six of seven comparisons showed beneficial effects for HIIT also involving normal weight and overweight-to-obese populations. Based on the results of the present study, it is possible to conclude that HIIT exercise may be a viable strategy for obtaining positive psychological responses. Although HIIT exercise may be recommended for obtaining positive psychological responses, chronic studies should clarify the applicability of HIIT for exercise adherence.

  2. Using paradox theory to understand responses to tensions between service and training in general surgery.

    Cleland, Jennifer; Roberts, Ruby; Kitto, Simon; Strand, Pia; Johnston, Peter

    2018-03-01

    The tension between service and training in pressured health care environments can have a detrimental impact on training quality and job satisfaction. Yet the management literature proposes that competing demands are inherent in organisational settings: it is not the demands as such that lead to negative outcomes but how people and organisations react to opposing tensions. We explored how key stakeholders responded to competing service-training demands in a surgical setting that had recently gone through a highly-publicised organisational crisis. This was an explanatory case study of a general surgery unit. Public documents informed the research questions and the data were triangulated with semi-structured interviews (n = 14) with key stakeholders. Data coding and analysis were initially inductive but, after the themes emerged, we used a paradox lens to group themes into four contextual dimensions: performing, organising, belonging and learning. Tensions were apparent in the data, with managers, surgeons and trainees or residents in conflict with each other because of different goals or priorities and divergent perspectives on the same issue of balancing service and training (performing). This adversely impacted on relationships across and within groups (belonging, learning) and led to individuals prioritising their own goals rather than working for the 'greater good' (performing, belonging). Yet although relationships and communication improved, the approach to getting a better balance maintained the 'compartmentalisation' of training (organising) rather than acknowledging that training and service cannot be separated. Stakeholder responses to the tensions provided temporary relief but were unlikely to lead to real change if the tension between service and training was considered to be an interdependent and persistent paradox. Reframing the service-training paradox in this way may encourage adjusting responses to create effective working partnerships. Our findings

  3. Dynamic response of the train-track-bridge system subjected to derailment impacts

    Ling, Liang; Dhanasekar, Manicka; Thambiratnam, David P.

    2018-04-01

    Derailments on bridges, although not frequent, when occurs due to a complex dynamic interaction of the train-track-bridge structural system, are very severe. Furthermore, the forced vibration induced by the post-derailment impacts can toss out the derailed wagons from the bridge deck with severe consequences to the traffic underneath and the safety of the occupants of the wagons. This paper presents a study of the train-track-bridge interaction during a heavy freight train crossing a concrete box girder bridge from a normal operation to a derailed state. A numerical model that considers the bridge vibration, train-track interaction and the train post-derailment behaviour is formulated based on a coupled finite-element - multi-body dynamics (FE-MBD) theory. The model is applied to predict the post-derailment behaviour of a freight train composed of one locomotive and several wagons, as well as the dynamic response of a straight single-span simply supported bridge containing ballast track subjected to derailment impacts. For this purpose, a typical derailment scenario of a heavy freight train passing over a severe track geometry defect is introduced. The dynamic derailment behaviour of the heavy freight train and the dynamic responses of the rail bridge are illustrated through numerical examples. The results exhibit the potential for tossing out of the derailed trains from the unstable increase in the yaw angle signature and a lower rate of increase of the bridge deck bending moment compared to the increase in the static axle load of the derailed wheelset.

  4. Effective Response to Attacks On Department of Defense Computer Networks

    Shaha, Patrick

    2001-01-01

    .... For the Commanders-in-Chief (CINCs), computer networking has proven especially useful in maintaining contact and sharing data with elements forward deployed as well as with host nation governments and agencies...

  5. A national assessment of the roles and responsibilities of training officers.

    Bentley, Melissa A; Eggerichs-Purcell, Jennifer J; Brown, William E; Wagoner, Robert; Gibson, Gregory C; Sahni, Ritu

    2013-01-01

    Since the inception of emergency medical services (EMS), individuals have assumed the role of "training officer" without a clear and concise description of the responsibilities inherent in this position. Furthermore, EMS system leaders rely heavily on these individuals to implement changes within an EMS system and to ensure the competency of practicing out-of-hospital professionals. The limited understanding of and research in training officer roles highlight the need for study in this area. Specific objectives of our study were to describe demographic and work-life characteristics of training officers, estimate the number of hours spent on specific training officer tasks in a typical week, and determine methods of training officer appointment and education received after appointment. This was a questionnaire-based cross-sectional census analysis of all training officers in the National Registry of Emergency Medical Technicians (NREMT) database. This questionnaire contained items related to demographics, work-life characteristics, and specific roles and responsibilities of training officers. Descriptive statistics, chi-square, and Mann-Whitney U tests were utilized to assess specific differences among training officers. Over 2,500 individuals responded to this questionnaire (2,528/4,956). The majority of the respondents were male (79.0%), held a full-time salaried position (64.9%), and were of nonminority status (93.4%). Individuals reported an overall median number of years worked in EMS of 19.0 (standard deviation [SD] = 8.7, range = 0-45) and a median of 4.0 years of serving as a training officer (SD = 5.1, range = 0-33), and planned to serve as a training officer for a median of 10.0 years (SD = 7.6, range = 0-50). The highest median numbers of hours spent on specific training officer tasks in a typical week were for providing patient care (median = 8.0, SD = 18.1); developing, delivering, and accounting for continuing education (median = 5.0, SD = 9

  6. Training Knowledge Bots for Physics-Based Simulations Using Artificial Neural Networks

    Samareh, Jamshid A.; Wong, Jay Ming

    2014-01-01

    Millions of complex physics-based simulations are required for design of an aerospace vehicle. These simulations are usually performed by highly trained and skilled analysts, who execute, monitor, and steer each simulation. Analysts rely heavily on their broad experience that may have taken 20-30 years to accumulate. In addition, the simulation software is complex in nature, requiring significant computational resources. Simulations of system of systems become even more complex and are beyond human capacity to effectively learn their behavior. IBM has developed machines that can learn and compete successfully with a chess grandmaster and most successful jeopardy contestants. These machines are capable of learning some complex problems much faster than humans can learn. In this paper, we propose using artificial neural network to train knowledge bots to identify the idiosyncrasies of simulation software and recognize patterns that can lead to successful simulations. We examine the use of knowledge bots for applications of computational fluid dynamics (CFD), trajectory analysis, commercial finite-element analysis software, and slosh propellant dynamics. We will show that machine learning algorithms can be used to learn the idiosyncrasies of computational simulations and identify regions of instability without including any additional information about their mathematical form or applied discretization approaches.

  7. An Issue of Boundary Value for Velocity and Training Overhead Using Cooperative MIMO Technique in Wireless Sensor Network

    M. R. Islam

    2011-06-01

    Full Text Available A boundary value of velocity of data gathering node (DGN and a critical value for training overhead beyond which the cooperative communication in wireless sensor network will not be feasible is proposed in this paper. Multiple Input Multiple Outputs (MIMO cooperative communication is taken as an application. The performance in terms of energy efficiency and delay for a combination of two transmitting and two receiving antennas is analyzed. The results show that a set of critical value of velocity and training overhead pair is present for the long haul communication from the sensors to the data gathering node. Later a graphical relation between boundary value of training overhead and velocity is simulated. A mathematical relation between velocity and training overhead is also developed. The effects of several parameters on training overhead and velocity are analyzed.

  8. Brief mindfulness meditation training alters psychological and neuroendocrine responses to social evaluative stress.

    Creswell, J David; Pacilio, Laura E; Lindsay, Emily K; Brown, Kirk Warren

    2014-06-01

    To test whether a brief mindfulness meditation training intervention buffers self-reported psychological and neuroendocrine responses to the Trier Social Stress Test (TSST) in young adult volunteers. A second objective evaluates whether pre-existing levels of dispositional mindfulness moderate the effects of brief mindfulness meditation training on stress reactivity. Sixty-six (N=66) participants were randomly assigned to either a brief 3-day (25-min per day) mindfulness meditation training or an analytic cognitive training control program. All participants completed a standardized laboratory social-evaluative stress challenge task (the TSST) following the third mindfulness meditation or cognitive training session. Measures of psychological (stress perceptions) and biological (salivary cortisol, blood pressure) stress reactivity were collected during the social evaluative stress-challenge session. Brief mindfulness meditation training reduced self-reported psychological stress reactivity but increased salivary cortisol reactivity to the TSST, relative to the cognitive training comparison program. Participants who were low in pre-existing levels of dispositional mindfulness and then received mindfulness meditation training had the greatest cortisol reactivity to the TSST. No significant main or interactive effects were observed for systolic or diastolic blood pressure reactivity to the TSST. The present study provides an initial indication that brief mindfulness meditation training buffers self-reported psychological stress reactivity, but also increases cortisol reactivity to social evaluative stress. This pattern may indicate that initially brief mindfulness meditation training fosters greater active coping efforts, resulting in reduced psychological stress appraisals and greater cortisol reactivity during social evaluative stressors. Copyright © 2014 Elsevier Ltd. All rights reserved.

  9. Reverse engineering biological networks :applications in immune responses to bio-toxins.

    Martino, Anthony A.; Sinclair, Michael B.; Davidson, George S.; Haaland, David Michael; Timlin, Jerilyn Ann; Thomas, Edward Victor; Slepoy, Alexander; Zhang, Zhaoduo; May, Elebeoba Eni; Martin, Shawn Bryan; Faulon, Jean-Loup Michel

    2005-12-01

    Our aim is to determine the network of events, or the regulatory network, that defines an immune response to a bio-toxin. As a model system, we are studying T cell regulatory network triggered through tyrosine kinase receptor activation using a combination of pathway stimulation and time-series microarray experiments. Our approach is composed of five steps (1) microarray experiments and data error analysis, (2) data clustering, (3) data smoothing and discretization, (4) network reverse engineering, and (5) network dynamics analysis and fingerprint identification. The technological outcome of this study is a suite of experimental protocols and computational tools that reverse engineer regulatory networks provided gene expression data. The practical biological outcome of this work is an immune response fingerprint in terms of gene expression levels. Inferring regulatory networks from microarray data is a new field of investigation that is no more than five years old. To the best of our knowledge, this work is the first attempt that integrates experiments, error analyses, data clustering, inference, and network analysis to solve a practical problem. Our systematic approach of counting, enumeration, and sampling networks matching experimental data is new to the field of network reverse engineering. The resulting mathematical analyses and computational tools lead to new results on their own and should be useful to others who analyze and infer networks.

  10. Characterization of the rapid transcriptional response to long-term sensitization training in Aplysia californica.

    Herdegen, Samantha; Holmes, Geraldine; Cyriac, Ashly; Calin-Jageman, Irina E; Calin-Jageman, Robert J

    2014-12-01

    We used a custom-designed microarray and quantitative PCR to characterize the rapid transcriptional response to long-term sensitization training in the marine mollusk Aplysia californica. Aplysia were exposed to repeated noxious shocks to one side of the body, a procedure known to induce a long-lasting, transcription-dependent increase in reflex responsiveness that is restricted to the side of training. One hour after training, pleural ganglia from the trained and untrained sides of the body were harvested; these ganglia contain the sensory nociceptors which help mediate the expression of long-term sensitization memory. Microarray analysis from 8 biological replicates suggests that long-term sensitization training rapidly regulates at least 81 transcripts. We used qPCR to test a subset of these transcripts and found that 83% were confirmed in the same samples, and 86% of these were again confirmed in an independent sample. Thus, our new microarray design shows strong convergent and predictive validity for analyzing the transcriptional correlates of memory in Aplysia. Fully validated transcripts include some previously identified as regulated in this paradigm (ApC/EBP and ApEgr) but also include novel findings. Specifically, we show that long-term sensitization training rapidly up-regulates the expression of transcripts which may encode Aplysia homologs of a C/EBPγ transcription factor, a glycine transporter (GlyT2), and a vacuolar-protein-sorting-associated protein (VPS36). Copyright © 2014 Elsevier Inc. All rights reserved.

  11. Influence of HMB supplementation and resistance training on cytokine responses to resistance exercise.

    Kraemer, William J; Hatfield, Disa L; Comstock, Brett A; Fragala, Maren S; Davitt, Patrick M; Cortis, Cristina; Wilson, Jacob M; Lee, Elaine C; Newton, Robert U; Dunn-Lewis, Courtenay; Häkkinen, Keijo; Szivak, Tunde K; Hooper, David R; Flanagan, Shawn D; Looney, David P; White, Mark T; Volek, Jeff S; Maresh, Carl M

    2014-01-01

    The purpose of this study was to determine the effects of a multinutritional supplement including amino acids, β-hydroxy-β-methylbutyrate (HMB), and carbohydrates on cytokine responses to resistance exercise and training. Seventeen healthy, college-aged men were randomly assigned to a Muscle Armor™ (MA; Abbott Nutrition, Columbus, OH) or placebo supplement group and 12 weeks of resistance training. An acute resistance exercise protocol was administered at 0, 6, and 12 weeks of training. Venous blood samples at pre-, immediately post-, and 30-minutes postexercise were analyzed via bead multiplex immunoassay for 17 cytokines. After 12 weeks of training, the MA group exhibited decreased interferon-gamma (IFN-γ) and interleukin (IL)-10. IL-1β differed by group at various times. Granulocyte colony-stimulating factor (G-CSF), granulocyte-macrophage colony-stimulating factor (GM-CSF), IL-6, IL-7, IL-8, IL-12p70, IL-13, IL-17, monocyte chemoattractant protein-1 (MCP-1), and macrophage inflammatory protein-1 beta (MIP-1β) changed over the 12-week training period but did not differ by group. Twelve weeks of resistance training alters the cytokine response to acute resistance exercise, and supplementation with HMB and amino acids appears to further augment this result.

  12. Human-simulated intelligent control of train braking response of bridge with MRB

    Li, Rui; Zhou, Hongli; Wu, Yueyuan; Wang, Xiaojie

    2016-04-01

    The urgent train braking could bring structural response menace to the bridge under passive control. Based on the analysis of breaking dynamics of a train-bridge vibration system, a magnetorheological elastomeric bearing (MRB) whose mechanical parameters are adjustable is designed, tested and modeled. A finite element method (FEM) is carried out to model and optimize a full scale vibration isolation system for railway bridge based on MRB. According to the model above, we also consider the effect of different braking stop positions on the vibration isolation system and classify the bridge longitudinal vibration characteristics into several cases. Because the train-bridge vibration isolation system has multiple vibration states and strongly coupling with nonlinear characteristics, a human-simulated intelligent control (HSIC) algorithm for isolating the bridge vibration under the impact of train braking is proposed, in which the peak shear force of pier top, the displacement of beam and the acceleration of beam are chosen as control goals. The simulation of longitudinal vibration control system under the condition of train braking is achieved by MATLAB. The results indicate that different braking stop positions significantly affect the vibration isolation system and the structural response is the most drastic when the train stops at the third cross-span. With the proposed HSIC smart isolation system, the displacement of bridge beam and peak shear force of pier top is reduced by 53.8% and 34.4%, respectively. Moreover, the acceleration of bridge beam is effectively controlled within limited range.

  13. Dissociation of rapid response learning and facilitation in perceptual and conceptual networks of person recognition.

    Valt, Christian; Klein, Christoph; Boehm, Stephan G

    2015-08-01

    Repetition priming is a prominent example of non-declarative memory, and it increases the accuracy and speed of responses to repeatedly processed stimuli. Major long-hold memory theories posit that repetition priming results from facilitation within perceptual and conceptual networks for stimulus recognition and categorization. Stimuli can also be bound to particular responses, and it has recently been suggested that this rapid response learning, not network facilitation, provides a sound theory of priming of object recognition. Here, we addressed the relevance of network facilitation and rapid response learning for priming of person recognition with a view to advance general theories of priming. In four experiments, participants performed conceptual decisions like occupation or nationality judgments for famous faces. The magnitude of rapid response learning varied across experiments, and rapid response learning co-occurred and interacted with facilitation in perceptual and conceptual networks. These findings indicate that rapid response learning and facilitation in perceptual and conceptual networks are complementary rather than competing theories of priming. Thus, future memory theories need to incorporate both rapid response learning and network facilitation as individual facets of priming. © 2014 The British Psychological Society.

  14. ACTN3 R577X POLYMORPHISM AND NEUROMUSCULAR RESPONSE TO RESISTANCE TRAINING

    Paulo Gentil

    2011-06-01

    Full Text Available The R577X polymorphism at the ACTN3 gene has been associated with muscle strength, hypertrophy and athletic status. The X allele, which is associated with the absence of ACTN3 protein is supposed to impair performance of high force/velocity muscle contractions. The purpose of the present study was to investigate the association of the R577X polymorphism with the muscle response to resistance training in young men. One hundred forty one men performed two resistance training sessions per week for 11 weeks. Participants were tested for 1RM bench press, knee extensors peak torque, and knee extensors muscle thickness at baseline and after the training period. Genotyping was conducted using de DdeI restriction enzyme. Genotype distribution was 34.4% for RR, 47% for RX and 18.6% for the XX genotype. According to the results, the R577X polymorphism at the ACTN3 gene is not associated with baseline muscle strength or with the muscle strength response to resistance training. However, only carriers of the R allele showed increases in muscle thickness in response to training

  15. Just-in-time training of dental responders in a simulated pandemic immunization response exercise.

    Colvard, Michael D; Hirst, Jeremy L; Vesper, Benjamin J; DeTella, George E; Tsagalis, Mila P; Roberg, Mary J; Peters, David E; Wallace, Jimmy D; James, James J

    2014-06-01

    The reauthorization of the Pandemic and All-Hazards Preparedness Act in 2013 incorporated the dental profession and dental professionals into the federal legislation governing public health response to pandemics and all-hazard situations. Work is now necessary to expand the processes needed to incorporate and train oral health care professionals into pandemic and all-hazard response events. A just-in-time (JIT) training exercise and immunization drill using an ex vivo porcine model system was conducted to demonstrate the rapidity to which dental professionals can respond to a pandemic influenza scenario. Medical history documentation, vaccination procedures, and patient throughput and error rates of 15 dental responders were evaluated by trained nursing staff and emergency response personnel. The average throughput (22.33/hr) and medical error rates (7 of 335; 2.08%) of the dental responders were similar to those found in analogous influenza mass vaccination clinics previously conducted using certified public health nurses. The dental responder immunization drill validated the capacity and capability of dental professionals to function as a valuable immunization resource. The ex vivo porcine model system used for JIT training can serve as a simple and inexpensive training tool to update pandemic responders' immunization techniques and procedures supporting inoculation protocols.

  16. Strength Training Prior to Endurance Exercise: Impact on the Neuromuscular System, Endurance Performance and Cardiorespiratory Responses

    Conceição Matheus

    2014-12-01

    Full Text Available This study aimed to investigate the acute effects of two strength-training protocols on the neuromuscular and cardiorespiratory responses during endurance exercise. Thirteen young males (23.2 ± 1.6 years old participated in this study. The hypertrophic strength-training protocol was composed of 6 sets of 8 squats at 75% of maximal dynamic strength. The plyometric strength-training protocol was composed of 6 sets of 8 jumps performed with the body weight as the workload. Endurance exercise was performed on a cycle ergometer at a power corresponding to the second ventilatory threshold until exhaustion. Before and after each protocol, a maximal voluntary contraction was performed, and the rate of force development and electromyographic parameters were assessed. After the hypertrophic strengthtraining and plyometric strength-training protocol, significant decreases were observed in the maximal voluntary contraction and rate of force development, whereas no changes were observed in the electromyographic parameters. Oxygen uptake and a heart rate during endurance exercise were not significantly different among the protocols. However, the time-to-exhaustion was significantly higher during endurance exercise alone than when performed after hypertrophic strength-training or plyometric strength-training (p <0.05. These results suggest that endurance performance may be impaired when preceded by strength-training, with no oxygen uptake or heart rate changes during the exercise.

  17. RESPUESTAS CARDIOVASCULARES AL ENTRENAMIENTO DE FUERZA BAJO OCLUSIÓN VASCULAR [Cardiovascular responses to strength training under occlusive training

    Sergio Benito Hernández

    2013-11-01

    Full Text Available El entrenamiento de la fuerza bajo oclusión vascular se muestra como una alternativa al entrenamiento de alta intensidad. El presente estudio muestra las respuestas cardiovasculares a este tipo de entrenamiento. 10 sujetos fueron sometidos a dos protocolos de entrenamiento oclusivo diferenciados por el peso levantado, (30% del peso máximo, post30, y 70% del peso máximo, post70. Se registraron los valores de tensión arterial sistólica (TAS, diastólica (TAD y frecuencia cardiaca (FC. Los resultados evidencian disminución significativa en TAS y TAD en el grupo post30 en 7 y 13 mm Hg respectivamente en referencia a los valores basales (p<0.05, resultando un descenso muy significativo en el grupo post70, 14 y 20 mm Hg respectivamente (p<0.005. Los valores de la FC no se vieron alterados por ninguno de los protocolos experimentales (p>0.05. Los efectos de tamaño para todos los grupos resultaron triviales (d<0.25. En conclusión los resultados del presente estudios presentan una tendencia a la reducción de la tensión arterial significativa en TAS y TAD en los protocolos de entrenamiento oclusivo, resultando más notable cuando se aplica la mayor intensidad de entrenamiento. Resultan necesarios más estudios que examinen el comportamiento de los parámetros cardiovasculares tras el entrenamiento de fuerza bajo oclusión vascular.AbstractOcclusive strength training is shown like an alternative to intensive training. Present study shown cardiovascular responses to this training. 10 subjects were subjected to two occlusion training protocols, differentiated by the weight lifted (30 % of maximum weight lifted, post30, and 70 % of maximum weight lifted, post70. The values of arterial systolic tension (TAS, diastolic (TAD and heart rate (FC were recorded. The results showing a significant decline in TAS and TAD after post30 of 7 and 13 mm Hg respectively from basis values (p<0.05, resulting a very significant decline in post70 group, 14 and 20 mm Hg

  18. Temporal specificity of training: intra-day effects on biochemical responses and Olympic-Weightlifting performances.

    Ammar, Achraf; Chtourou, Hamdi; Trabelsi, Khaled; Padulo, Johnny; Turki, Mouna; El Abed, Kais; Hoekelmann, Anitta; Hakim, Ahmed

    2015-01-01

    The aim of this study was to investigate the performance of an Olympic-Weightlifting session training at three times of the day on the performance related to biochemical responses. Nine weightlifters (21 ± 0.5 years) performed, in randomised order, on three Olympic-Weightlifting training (snatch, clean and jerk) sessions (08:00 a.m., 02:00 p. m., 06:00 p. m.). Blood samples were collected: before, 3 min and 48 h after each training session. Haematological parameters and markers of muscle injury were assessed. Resting oral temperature and rating of perceived exertion (RPE) were also assessed during each session. ANOVA showed that the performance was better (P weightlifters. Therefore, coaches and weightlifters should be advised to schedule their training session in the afternoon hour.

  19. Understanding the Construction of Personal Learning Networks to Support Non-Formal Workplace Learning of Training Professionals

    Manning, Christin

    2013-01-01

    Workers in the 21st century workplace are faced with rapid and constant developments that place a heavy demand on them to continually learn beyond what the Human Resources and Training groups can meet. As a consequence, professionals must rely on non-formal learning approaches through the development of a personal learning network to keep…

  20. Hybrid Polymer-Network Hydrogels with Tunable Mechanical Response

    Sebastian Czarnecki

    2016-03-01

    Full Text Available Hybrid polymer-network gels built by both physical and covalent polymer crosslinking combine the advantages of both these crosslinking types: they exhibit high mechanical strength along with excellent fracture toughness and extensibility. If these materials are extensively deformed, their physical crosslinks can break such that strain energy is dissipated and irreversible fracturing is restricted to high strain only. This mechanism of energy dissipation is determined by the kinetics and thermodynamics of the physical crosslinking contribution. In this paper, we present a poly(ethylene glycol (PEG based material toolkit to control these contributions in a rational and custom fashion. We form well-defined covalent polymer-network gels with regularly distributed additional supramolecular mechanical fuse links, whose strength of connectivity can be tuned without affecting the primary polymer-network composition. This is possible because the supramolecular fuse links are based on terpyridine–metal complexation, such that the mere choice of the fuse-linking metal ion adjusts their kinetics and thermodynamics of complexation–decomplexation, which directly affects the mechanical properties of the hybrid gels. We use oscillatory shear rheology to demonstrate this rational control and enhancement of the mechanical properties of the hybrid gels. In addition, static light scattering reveals their highly regular and well-defined polymer-network structures. As a result of both, the present approach provides an easy and reliable concept for preparing hybrid polymer-network gels with rationally designed properties.

  1. A multi-radio, multi-hop ad-hoc radio communication network for Communications-Based Train Control (CBTC): Introducing frequency separation for train-to-trackside communication

    Farooq, Jahanzeb; Bro, Lars; Karstensen, Rasmus Thystrup

    2018-01-01

    Communications-Based Train Control (CBTC) is a modern signalling system that uses radio communication to transfer train control information between train and wayside. The trackside networks in these systems are mostly based on conventionalinfrastructureWi-Fi(IEEE802.11).Itmeansatrain has to conti...

  2. Responses of catecholestrogen metabolism to acute graded exercise in normal menstruating women before and after training.

    De Crée, C; Ball, P; Seidlitz, B; Van Kranenburg, G; Geurten, P; Keizer, H A

    1997-10-01

    It has been hypothesized that exercise-related hypo-estrogenemia occurs as a consequence of increased competition of catecholestrogens (CE) for catechol-O-methyltransferase (COMT). This may result in higher norepinephrine (NE) concentrations, which could interfere with normal gonadotropin pulsatility. The present study investigates the effects of training on CE responses to acute exercise stress. Nine untrained eumenorrheic women (mean percentage of body fat +/-SD: 24.8 +/- 3.1%) volunteered for an intensive 5-day training program. Resting, submaximal, and maximal (tmax) exercise plasma CE, estrogen, and catecholamine responses were determined pre- and post training in both the follicular (FPh) and luteal phase (LPh). Acute exercise stress increased total primary estrogens (E) but had little effect on total 2-hydroxyestrogens (2-OHE) and 2-hydroxyestrogen-monomethylethers (2-MeOE) (= O-methylated CE after competition for catechol-O-methyltransferase). This pattern was not significantly changed by training. However, posttraining LPh mean (+/-SE) plasma E, 2-OHE, and 2-MeOE concentrations were significantly lower (P Training produced opposite effects on 2-OHE:E ratios (an estimation of CE formation) during acute exercise in the FPh (reduction) and LPh (increase). The 2-MeOE:2-OHE ratio (an estimation of CE activity) showed significantly higher values at tmax in both menstrual phases after training (FPh: +11%; LPh: +23%; P training, NE values were significantly higher (P training lowers absolute concentrations of plasma estrogens and CE; the acute exercise challenge altered plasma estrogens but had little effect on CE; estimation of the formation and activity of CE suggests that formation and O-methylation of CE proportionately increases. These findings may be of importance for NE-mediated effects on gonadotropin release.

  3. European Nuclear Education Network Association - Support for nuclear education, training and knowledge management

    Ghitescu, Petre

    2009-01-01

    Developed in 2002-2003 the FP5 EURATOM project 'European Nuclear Engineering Network - ENEN' aimed to establish the basis for conserving nuclear knowledge and expertise, to create an European Higher Education Area for nuclear disciplines and to facilitate the implementation of the Bologna declaration in the nuclear disciplines. In order to ensure the continuity of the achievements and results of the ENEN project, on 22 September 2003, the European Nuclear Higher Education Area was formalized by creating the European Nuclear Education Network Association. ENEN Association goals are oriented towards universities by developing a more harmonized approach for education in the nuclear sciences and engineering in Europe, integrating European education and training in nuclear safety and radiation protection and achieving a better cooperation and sharing of resources and capabilities at the national and international level. At the same time it is oriented towards the end-users (industries, regulatory bodies, research centers, universities) by creating a secure basis of knowledge and skills of value to the EU. It maintains an adequate supply of qualified human resources for design, construction, operation and maintenance of nuclear infrastructures and plants. Also it maintains the necessary competence and expertise for the continued safe use of nuclear energy and applications of radiation in industry and medicine. In 2004-2005, 35 partners continued and expanded the started in FP 5 ENEN Association activities with the FP6 project 'NEPTUNO- Nuclear Education Platform for Training and Universities Organizations'. Thus ENEN established and implemented the European Master of Science in Nuclear Engineering, expanded its activities from education to training, organized and coordinated training sessions and pilot courses and included in its activities the Knowledge Management. At present, the ENEN Association gathers 45 universities, 7 research centers and one multinational company

  4. Accreditation and training on internal dosimetry in a laboratory network in Brazil: an increasing demand.

    Dantas, B M; Dantas, A L A; Acar, M E D; Cardoso, J C S; Julião, L M Q C; Lima, M F; Taddei, M H T; Arine, D R; Alonso, T; Ramos, M A P; Fajgelj, A

    2011-03-01

    In recent years, Brazilian Nuclear Programme has been reviewed and updated by government authorities in face of the demand for energy supply and its associated environmental constraints. The immediate impact of new national programmes and projects in nuclear field is the increase in the number of exposed personnel and the consequent need for reliable dosimetry services in the country. Several Technical Documents related to internal dosimetry have been released by the International Atomic Energy Agency and International Commission on Radiological Protection. However, standard bioassay procedures and methodologies for bioassay data interpretation are still under discussion and, in some cases, both in routine and emergency internal monitoring, procedures can vary from one laboratory to another and responses may differ markedly among Dosimetry Laboratories. Thus, it may be difficult to interpret and use bioassay data generated from different laboratories of a network. The main goal of this work is to implement a National Network of Laboratories aimed to provide reliable internal monitoring services in Brazil. The establishment of harmonised in vivo and in vitro radioanalytical techniques, dose assessment methods and the implementation of the ISO/IEC 17025 requirements will result in the recognition of technical competence of the network.

  5. Genetic dissection of acute ethanol responsive gene networks in prefrontal cortex: functional and mechanistic implications.

    Aaron R Wolen

    Full Text Available Individual differences in initial sensitivity to ethanol are strongly related to the heritable risk of alcoholism in humans. To elucidate key molecular networks that modulate ethanol sensitivity we performed the first systems genetics analysis of ethanol-responsive gene expression in brain regions of the mesocorticolimbic reward circuit (prefrontal cortex, nucleus accumbens, and ventral midbrain across a highly diverse family of 27 isogenic mouse strains (BXD panel before and after treatment with ethanol.Acute ethanol altered the expression of ~2,750 genes in one or more regions and 400 transcripts were jointly modulated in all three. Ethanol-responsive gene networks were extracted with a powerful graph theoretical method that efficiently summarized ethanol's effects. These networks correlated with acute behavioral responses to ethanol and other drugs of abuse. As predicted, networks were heavily populated by genes controlling synaptic transmission and neuroplasticity. Several of the most densely interconnected network hubs, including Kcnma1 and Gsk3β, are known to influence behavioral or physiological responses to ethanol, validating our overall approach. Other major hub genes like Grm3, Pten and Nrg3 represent novel targets of ethanol effects. Networks were under strong genetic control by variants that we mapped to a small number of chromosomal loci. Using a novel combination of genetic, bioinformatic and network-based approaches, we identified high priority cis-regulatory candidate genes, including Scn1b, Gria1, Sncb and Nell2.The ethanol-responsive gene networks identified here represent a previously uncharacterized intermediate phenotype between DNA variation and ethanol sensitivity in mice. Networks involved in synaptic transmission were strongly regulated by ethanol and could contribute to behavioral plasticity seen with chronic ethanol. Our novel finding that hub genes and a small number of loci exert major influence over the ethanol

  6. How is VR used to support training in industry? The INTUITION network of excellence working group on education and training

    Cobb, S.C.; Richir, S.; D'Cruz, M.; Klinger, E.; Day, A.; David, P.; Gardeux, F.; van den Broek, Egon; van der Voort, Mascha C.; Meijer, F.; Izkara, J.L.; Mavrikios, D.

    2008-01-01

    INTUITION is the European Network of Excellence on virtual reality and virtual environments applications for future workspaces. The purpose of the network is to gather expertise from partner members and determine the future research agenda for the development and use of virtual reality (VR)

  7. Visual Attention to Suffering After Compassion Training Is Associated With Decreased Amygdala Responses

    Helen Y. Weng

    2018-05-01

    Full Text Available Compassion meditation training is hypothesized to increase the motivational salience of cues of suffering, while also enhancing equanimous attention and decreasing emotional reactivity to suffering. However, it is currently unknown how compassion meditation impacts visual attention to suffering, and how this impacts neural activation in regions associated with motivational salience as well as aversive responses, such as the amygdala. Healthy adults were randomized to 2 weeks of compassion or reappraisal training. We measured BOLD fMRI responses before and after training while participants actively engaged in their assigned training to images depicting human suffering or non-suffering. Eye-tracking data were recorded concurrently, and we computed looking time for socially and emotionally evocative areas of the images, and calculated visual preference for suffering vs. non-suffering. Increases in visual preference for suffering due to compassion training were associated with decreases in the amygdala, a brain region involved in negative valence, arousal, and physiological responses typical of fear and anxiety states. This pattern was specifically in the compassion group, and was not found in the reappraisal group. In addition, compassion training-related increases in visual preference for suffering were also associated with decreases in regions sensitive to valence and empathic distress, spanning the anterior insula and orbitofrontal cortex (while the reappraisal group showed the opposite effect. Examining visual attention alone demonstrated that engaging in compassion in general (across both time points resulted in visual attention preference for suffering compared to engaging in reappraisal. Collectively, these findings suggest that compassion meditation may cultivate visual preference for suffering while attenuating neural responses in regions typically associated with aversive processing of negative stimuli, which may cultivate a more

  8. The Development of Teachers' Responses to Challenging Situations during Interaction Training

    Talvio, Markus; Lonka, Kirsti; Komulainen, Erkki; Kuusela, Marjo; Lintunen, Taru

    2015-01-01

    The qualitative changes in teachers' responses in challenging situations were analysed during a four-day Teacher Effectiveness Training (TET) course, which aimed at improving teachers' interpersonal dynamics with pupils, parents and colleagues. The participants were 21 teachers from one elementary and 23 teachers from one secondary school…

  9. Preschool children's response to behavioural parent training and parental predictors of outcome in routine clinical care

    van der Veen-Mulders, Lianne; Hoekstra, Pieter J; Nauta, Maaike H; van den Hoofdakker, Barbara J

    OBJECTIVE: To investigate the effectiveness of behavioral parent training (BPT) for preschool children with disruptive behaviours and to explore parental predictors of response. METHODS: Parents of 68 preschool children, aged between 2.7 and 5.9 years, participated in BPT. We evaluated the changes

  10. The Impact of Training and Conflict Avoidance on Responses to Sexual Harassment

    Goldberg, Caren B.

    2007-01-01

    This study used a pretest/posttest design and included a control group to examine the impact of harassment training on intended responses to harassment. The sample consisted of 282 full-time professionals. At time 2, trainees expressed lower intentions to confront the perpetrator than did control-group participants. The simple and moderating…

  11. The miRNA Plasma Signature in Response to Acute Aerobic Exercise and Endurance Training

    Nielsen, Søren; Åkerström, Thorbjörn; Rinnov, Anders

    2014-01-01

    MiRNAs are potent intracellular posttranscriptional regulators and are also selectively secreted into the circulation in a cell-specific fashion. Global changes in miRNA expression in skeletal muscle in response to endurance exercise training have been reported. Therefore, our aim was to establis...

  12. T-S Fuzzy Model Based Control Strategy for the Networked Suspension Control System of Maglev Train

    Guang He

    2015-01-01

    Full Text Available The control problem for the networked suspension control system of maglev train with random induced time delay and packet dropouts is investigated. First, Takagi-Sugeno (T-S fuzzy models are utilized to represent the discrete-time nonlinear networked suspension control system, and the parameters uncertainties of the nonlinear model have also been taken into account. The controllers take the form of parallel distributed compensation. Then, a sufficient condition for the stability of the networked suspension control system is derived. Based on the criteria, the state feedback fuzzy controllers are obtained, and the controller gains can be computed by using MATLAB LMI Toolbox directly. Finally, both the numerical simulations and physical experiments on the full-scale single bogie of CMS-04 maglev train have been accomplished to demonstrate the effectiveness of this proposed method.

  13. The national response plan and radioactive incident monitoring network (RIMNET)

    Jones, M.W.

    1989-01-01

    The Department of the Environment is responsible through Her Majesty's Inspectorate of Pollution for co-ordination of the Government's response to overseas nuclear incidents. This paper describes the contingency arrangements that have been set up for this purpose. (author)

  14. Development of an Educational Network to Strengthen Education, Training and Outreach in Latin America: LANENT-Latin American Network for Education in Nuclear Technology

    Da Silva, A.

    2016-01-01

    Full text: In the current century, networks have played an important role in the dissemination of experiences, information exchange and training of human resources for different area of expertise. The IAEA has encouraged in regions, through its member states, the creation of educational networks to meet rapidly and efficiently the dissemination and exchange of knowledge between professionals and students in the nuclear area. With this vision, the Latin American Network for Education in Nuclear Technology (LANENT) was established to contribute to preserving, promoting and sharing nuclear knowledge as well as fostering nuclear knowledge transfer in the Latin American region. LANENT seeks to increase technical and scientific cooperation among its members in so far as to promote the benefits of nuclear technology and foster the progress and development of nuclear technology in areas such as education, health, the industry, the government, the environment, the mining industry, among others. By means of LANENT, the participating institutions of this network, devoted to education and training of professionals and technicians in the Latin American region, may have access to major information on nuclear technology so as to make their human resources broaden their nuclear knowledge. Moreover, this network seeks to communicate the benefits of nuclear technology to the public with the aim of arousing interest in nuclear technology of the younger generations. This paper will present and analyze results and initiatives developed by LANENT in Latin America. (author

  15. Response of pressurized water reactor (PWR) to network power generation demands

    Schreiner, L.A.

    1991-01-01

    The flexibility of the PWR type reactor in terms of response to the variations of the network power demands, is demonstrated. The factors that affect the transitory flexibility and some design prospects that allow the reactor fits the requirements of the network power demands, are also discussed. (M.J.A.)

  16. Relaxation Response and Resiliency Training and Its Effect on Healthcare Resource Utilization.

    James E Stahl

    Full Text Available Poor psychological and physical resilience in response to stress drives a great deal of health care utilization. Mind-body interventions can reduce stress and build resiliency. The rationale for this study is therefore to estimate the effect of mind-body interventions on healthcare utilization.Estimate the effect of mind body training, specifically, the Relaxation Response Resiliency Program (3RP on healthcare utilization.Retrospective controlled cohort observational study.Major US Academic Health Network.All patients receiving 3RP at the MGH Benson-Henry Institute from 1/12/2006 to 7/1/2014 (n = 4452, controls (n = 13149 followed for a median of 4.2 years (.85-8.4 yrs.Utilization as measured by billable encounters/year (be/yr stratified by encounter type: clinical, imaging, laboratory and procedural, by class of chief complaint: e.g., Cardiovascular, and by site of care delivery, e.g., Emergency Department. Subgroup analysis by propensity score matched pre-intervention utilization rate.At one year, total utilization for the intervention group decreased by 43% [53.5 to 30.5 be/yr] (p <0.0001. Clinical encounters decreased by 41.9% [40 to 23.2 be/yr], imaging by 50.3% [11.5 to 5.7 be/yr], lab encounters by 43.5% [9.8 to 5.6], and procedures by 21.4% [2.2 to 1.7 be/yr], all p < 0.01. The intervention group's Emergency department (ED visits decreased from 3.6 to 1.7/year (p<0.0001 and Hospital and Urgent care visits converged with the controls. Subgroup analysis (identically matched initial utilization rates-Intervention group: high utilizing controls showed the intervention group significantly reduced utilization relative to the control group by: 18.3% across all functional categories, 24.7% across all site categories and 25.3% across all clinical categories.Mind body interventions such as 3RP have the potential to substantially reduce healthcare utilization at relatively low cost and thus can serve as key components in any population health and

  17. Identifying the relevant dependencies of the neural network response on characteristics of the input space

    CERN. Geneva

    2018-01-01

    This talk presents an approach to identify those characteristics of the neural network inputs that are most relevant for the response and therefore provides essential information to determine the systematic uncertainties.

  18. The construction of corporate social responsibility in network societies: A communication view

    Schultz, F.; Castello, I.; Morsing, M.

    2013-01-01

    The paper introduces the communication view on Corporate Social Responsibility (CSR), which regards CSR as communicatively constructed in dynamic interaction processes in today's networked societies. Building on the idea that communication constitutes organizations we discuss the potentially

  19. State and Training Effects of Mindfulness Meditation on Brain Networks Reflect Neuronal Mechanisms of Its Antidepressant Effect

    Chuan-Chih Yang

    2016-01-01

    Full Text Available The topic of investigating how mindfulness meditation training can have antidepressant effects via plastic changes in both resting state and meditation state brain activity is important in the rapidly emerging field of neuroplasticity. In the present study, we used a longitudinal design investigating resting state fMRI both before and after 40 days of meditation training in 13 novices. After training, we compared differences in network connectivity between rest and meditation using common resting state functional connectivity methods. Interregional methods were paired with local measures such as Regional Homogeneity. As expected, significant differences in functional connectivity both between states (rest versus meditation and between time points (before versus after training were observed. During meditation, the internal consistency in the precuneus and the temporoparietal junction increased, while the internal consistency of frontal brain regions decreased. A follow-up analysis of regional connectivity of the dorsal anterior cingulate cortex further revealed reduced connectivity with anterior insula during meditation. After meditation training, reduced resting state functional connectivity between the pregenual anterior cingulate and dorsal medical prefrontal cortex was observed. Most importantly, significantly reduced depression/anxiety scores were observed after training. Hence, these findings suggest that mindfulness meditation might be of therapeutic use by inducing plasticity related network changes altering the neuronal basis of affective disorders such as depression.

  20. Fast demand response in support of the active distribution network

    MacDougall, P.; Heskes, P.; Crolla, P.; Burt, G.; Warmer, C.

    2013-01-01

    Demand side management has traditionally been investigated for "normal" operation services such as balancing and congestion management. However they potentially could be utilized for Distributed Network Operator (DNO) services. This paper investigates and validates the use of a supply and demand

  1. Response surface and neural network based predictive models of cutting temperature in hard turning

    Mozammel Mia

    2016-11-01

    Full Text Available The present study aimed to develop the predictive models of average tool-workpiece interface temperature in hard turning of AISI 1060 steels by coated carbide insert. The Response Surface Methodology (RSM and Artificial Neural Network (ANN were employed to predict the temperature in respect of cutting speed, feed rate and material hardness. The number and orientation of the experimental trials, conducted in both dry and high pressure coolant (HPC environments, were planned using full factorial design. The temperature was measured by using the tool-work thermocouple. In RSM model, two quadratic equations of temperature were derived from experimental data. The analysis of variance (ANOVA and mean absolute percentage error (MAPE were performed to suffice the adequacy of the models. In ANN model, 80% data were used to train and 20% data were employed for testing. Like RSM, herein, the error analysis was also conducted. The accuracy of the RSM and ANN model was found to be ⩾99%. The ANN models exhibit an error of ∼5% MAE for testing data. The regression coefficient was found to be greater than 99.9% for both dry and HPC. Both these models are acceptable, although the ANN model demonstrated a higher accuracy. These models, if employed, are expected to provide a better control of cutting temperature in turning of hardened steel.

  2. Complex Projective Synchronization in Drive-Response Stochastic Complex Networks by Impulsive Pinning Control

    Xuefei Wu

    2014-01-01

    Full Text Available The complex projective synchronization in drive-response stochastic coupled networks with complex-variable systems is considered. The impulsive pinning control scheme is adopted to achieve complex projective synchronization and several simple and practical sufficient conditions are obtained in a general drive-response network. In addition, the adaptive feedback algorithms are proposed to adjust the control strength. Several numerical simulations are provided to show the effectiveness and feasibility of the proposed methods.

  3. Requirement of trained first responders and national level preparedness for prevention and response to radiological terrorism

    Sharma, R.; Pradeepkumar, K.S.

    2011-01-01

    The increase in the usage of radioactive sources in various fields and the present scenario of adopting various means of terrorism indicates a possible environment for malicious usage of radioactive sources. Many nations, India inclusive, have to strengthen further it's capability to deal with Nuclear/Radiological Emergencies. The probable radiological emergency scenario in public domain involves inadvertent melting of radioactive material, transport accident involving radioactive material/sources and presence of orphan sources as reported elsewhere. Explosion of Radiological Dispersal Device (RDDs) or Improvised Nuclear Devices (IND) leading to spread of radioactive contamination in public places have been identified by IAEA as probable radiological threats. The IAEA documents put lot of emphasis, at national level, on training and educational issues related with Radiological Emergencies. The agencies and institutions dealing with radioactive sources have few personnel trained in radiation protection. Experience so far indicates that public awareness is also not adequate in the field of radiological safety which may create difficulties during emergency response in public domain. The major challenges are associated with mitigation, monitoring methodology, contaminated and overexposed casualties, decontamination and media briefing. In this paper, we have identified the educational needs for response to radiological emergency in India with major thrust on training. The paper has also enumerated the available educational and training infrastructure, the human resources, as well as the important stake holders for development of sustainable education and training programme. (author)

  4. Effects of the network structure and coupling strength on the noise-induced response delay of a neuronal network

    Ozer, Mahmut; Uzuntarla, Muhammet

    2008-01-01

    The Hodgkin-Huxley (H-H) neuron model driven by stimuli just above threshold shows a noise-induced response delay with respect to time to the first spike for a certain range of noise strengths, an effect called 'noise delayed decay' (NDD). We study the response time of a network of coupled H-H neurons, and investigate how the NDD can be affected by the connection topology of the network and the coupling strength. We show that the NDD effect exists for weak and intermediate coupling strengths, whereas it disappears for strong coupling strength regardless of the connection topology. We also show that although the network structure has very little effect on the NDD for a weak coupling strength, the network structure plays a key role for an intermediate coupling strength by decreasing the NDD effect with the increasing number of random shortcuts, and thus provides an additional operating regime, that is absent in the regular network, in which the neurons may also exploit a spike time code

  5. Dose-response of altitude training: how much altitude is enough?

    Levine, Benjamin D; Stray-Gundersen, James

    2006-01-01

    Altitude training continues to be a key adjunctive aid for the training of competitive athletes throughout the world. Over the past decade, evidence has accumulated from many groups of investigators that the "living high--training low" approach to altitude training provides the most robust and reliable performance enhancements. The success of this strategy depends on two key features: 1) living high enough, for enough hours per day, for a long enough period of time, to initiate and sustain an erythropoietic effect of high altitude; and 2) training low enough to allow maximal quality of high intensity workouts, requiring high rates of sustained oxidative flux. Because of the relatively limited access to environments where such a strategy can be practically applied, numerous devices have been developed to "bring the mountain to the athlete," which has raised the key issue of the appropriate "dose" of altitude required to stimulate an acclimatization response and performance enhancement. These include devices using molecular sieve technology to provide a normobaric hypoxic living or sleeping environment, approaches using very high altitudes (5,500m) for shorter periods of time during the day, and "intermittent hypoxic training" involving breathing very hypoxic gas mixtures for alternating 5 minutes periods over the course of 60-90 minutes. Unfortunately, objective testing of the strategies employing short term (less than 4 hours) normobaric or hypobaric hypoxia has failed to demonstrate an advantage of these techniques. Moreover individual variability of the response to even the best of living high--training low strategies has been great, and the mechanisms behind this variability remain obscure. Future research efforts will need to focus on defining the optimal dosing strategy for these devices, and determining the underlying mechanisms of the individual variability so as to enable the individualized "prescription" of altitude exposure to optimize the performance of

  6. The dose-response relationship of balance training in physically active older adults.

    Maughan, Kristen K; Lowry, Kristin A; Franke, Warren D; Smiley-Oyen, Ann L

    2012-10-01

    A 6-wk group balance-training program was conducted with physically active older adults (based on American College of Sports Medicine requirements) to investigate the effect of dose-related static and dynamic balance-specific training. All participants, age 60-87 yr, continued their regular exercise program while adding balance training in 1 of 3 doses: three 20-min sessions/wk (n = 20), one 20-min session/wk (n = 21), or no balance training (n = 19). Static balance (single-leg-stance, tandem), dynamic balance (alternate stepping, limits of stability), and balance confidence (ABC) were assessed pre- and posttraining. Significant interactions were observed for time in single-leg stance, excursion in limits of stability, and balance confidence, with the greatest increase observed in the group that completed 3 training sessions/wk. The results demonstrate a dose-response relationship indicating that those who are already physically active can improve balance performance with the addition of balance-specific training.

  7. Investigating the Cellular and Metabolic Responses of World-Class Canoeists Training: A Sportomics Approach

    Wagner Santos Coelho

    2016-11-01

    Full Text Available (1 Background: We have been using the Sportomics approach to evaluate biochemical and hematological changes in response to exercise. The aim of this study was to evaluate the metabolic and hematologic responses of world-class canoeists during a training session; (2 Methods: Blood samples were taken at different points and analyzed for their hematological properties, activities of selected enzymes, hormones, and metabolites; (3 Results: Muscle stress biomarkers were elevated in response to exercise which correlated with modifications in the profile of white blood cells, where a leukocyte rise was observed after the canoe session. These results were accompanied by an increase in other exercise intensity parameters such as lactatemia and ammonemia. Adrenocorticotropic hormone and cortisol increased during the exercise sessions. The acute rise in both erythrocytes and white blood profile were probably due to muscle cell damage, rather than hepatocyte integrity impairment; (4 Conclusion: The cellular and metabolic responses found here, together with effective nutrition support, are crucial to understanding the effects of exercise in order to assist in the creation of new training and recovery planning. Also we show that Sportomics is a primal tool for training management and performance improvement, as well as to the understanding of metabolic response to exercise.

  8. Enhancing Self-Awareness: A Practical Strategy to Train Culturally Responsive Social Work Students

    Nalini J. Negi

    2010-10-01

    Full Text Available A primary goal of social justice educators is to engage students in a process of self-discovery, with the goal of helping them recognize their own biases, develop empathy, and become better prepared for culturally responsive practice. While social work educators are mandated with the important task of training future social workers in culturally responsive practice with diverse populations, practical strategies on how to do so are scant. This article introduces a teaching exercise, the Ethnic Roots Assignment, which has been shown qualitatively to aid students in developing self-awareness, a key component of culturally competent social work practice. Practical suggestions for classroom utilization, common challenges, and past student responses to participating in the exercise are provided. The dissemination of such a teaching exercise can increase the field’s resources for addressing the important goal of cultural competence training.

  9. The effect of internal audit effectiveness, auditor responsibility and training in fraud detection

    George Drogalas

    2017-12-01

    Full Text Available The purpose of this study is to explore the relationship between internal audit effectiveness, internal auditor’s responsibility, training and fraud detection. During the last decade internal auditing has become an integral part of modern businesses since it is capable of detecting errors or offences which lead to fraud. In order to investigate the above relationship, we conducted a survey of companies listed in the Athens Stock Exchange. We used factor analysis to validate the survey instrument and to construct our variables measuring fraud detection, internal audit effectiveness, auditor responsibility and training. We used regression analysis to test for significance between the constructed variables. Our analysis shows that audit effectiveness, auditor responsibility and auditor training affect positively and significantly the detection of fraud. Our results highlight the importance of internal audit in detecting accounting fraud and the need of companies to invest on internal audit processes and training in order to achieve enhanced corporate performance. Finally, our research stresses the importance of internal audit and fraud detection for companies which operate in countries which are in a period of economic crisis.

  10. Corporate Environmental Responsibility in Demand Networks (summary section only)

    Kovács, Gyöngyi

    2006-01-01

    Research on corporate responsibility has traditionally focused on the responsibilities of companies within their corporate boundaries only. Yet this view is challenged today as more and more companies face the situation in which the environmental and social performance of their suppliers, distributors, industry or other associated partners impacts on their sales performance and brand equity. Simultaneously, policy-makers have taken up the discussion on corporate responsibility from the perspe...

  11. Use of the Remote Access Virtual Environment Network (RAVEN) for coordinated IVA-EVA astronaut training and evaluation.

    Cater, J P; Huffman, S D

    1995-01-01

    This paper presents a unique virtual reality training and assessment tool developed under a NASA grant, "Research in Human Factors Aspects of Enhanced Virtual Environments for Extravehicular Activity (EVA) Training and Simulation." The Remote Access Virtual Environment Network (RAVEN) was created to train and evaluate the verbal, mental and physical coordination required between the intravehicular (IVA) astronaut operating the Remote Manipulator System (RMS) arm and the EVA astronaut standing in foot restraints on the end of the RMS. The RAVEN system currently allows the EVA astronaut to approach the Hubble Space Telescope (HST) under control of the IVA astronaut and grasp, remove, and replace the Wide Field Planetary Camera drawer from its location in the HST. Two viewpoints, one stereoscopic and one monoscopic, were created all linked by Ethernet, that provided the two trainees with the appropriate training environments.

  12. Autogenic Feedback Training Exercise: Controlling Physiological Responses to Mitigate Motion Sickness

    Walton, Nia; Spencer, Telissa; Cowings, Patricia; Toscano, William B.

    2018-01-01

    During space travel approximately 50 of the crew experience symptoms of motion sickness that can range from mild forms of nausea or dizziness to severe malaise and vomiting1. Developing an effective treatment for these symptoms has become a priority of the National Aeronautics and Space Administration (NASA). Autogenic-Feedback Training Exercise (AFTE) is a nonpharmacological countermeasure for mitigating motion sickness. It involves training subjects to control physiological responses in high stress environments2. The primary goal of this experiment is to evaluate the effectiveness of AFTE for increasing tolerance to motion sickness in high stress environments.

  13. The cardiovascular and endocrine responses to voluntary and forced diving in trained and untrained rats

    DiNovo, Karyn. M.; Connolly, Tiffanny M.

    2010-01-01

    The mammalian diving response, consisting of apnea, bradycardia, and increased total peripheral resistance, can be modified by conscious awareness, fear, and anticipation. We wondered whether swim and dive training in rats would 1) affect the magnitude of the cardiovascular responses during voluntary and forced diving, and 2) whether this training would reduce or eliminate any stress due to diving. Results indicate Sprague-Dawley rats have a substantial diving response. Immediately upon submersion, heart rate (HR) decreased by 78%, from 453 ± 12 to 101 ± 8 beats per minute (bpm), and mean arterial pressure (MAP) decreased 25%, from 143 ± 1 to 107 ± 5 mmHg. Approximately 4.5 s after submergence, MAP had increased to a maximum 174 ± 3 mmHg. Blood corticosterone levels indicate trained rats find diving no more stressful than being held by a human, while untrained rats find swimming and diving very stressful. Forced diving is stressful to both trained and untrained rats. The magnitude of bradycardia was similar during both voluntary and forced diving, while the increase in MAP was greater during forced diving. The diving response of laboratory rats, therefore, appears to be dissimilar from that of other animals, as most birds and mammals show intensification of diving bradycardia during forced diving compared with voluntary diving. Rats may exhibit an accentuated antagonism between the parasympathetic and sympathetic branches of the autonomic nervous system, such that in the autonomic control of HR, parasympathetic activity overpowers sympathetic activity. Additionally, laboratory rats may lack the ability to modify the degree of parasympathetic outflow to the heart during an intense cardiorespiratory response (i.e., the diving response). PMID:19923359

  14. Training for the medical response in radiological emergency experiences and results

    Cardenas Herrera, J.; Lopez Forteza, Y.

    2003-01-01

    The use of the nuclear techniques int he social practice confers a special imporatnce to the relative aspects to the safety of the practices and radiationsources, for what the implementation of efficient programs of radiation protection constitutes a priority. However in spite of the will before expressed, regrettably radiological situations happen accidental assocaited to multiple causes taht suggest the creation of response capacities to intervention before these fortuitous facts. The experiences accumulated in the last decades related with accidental exposures have evidenced the convenience of having properly qualified human resources for the Medical Response in Radiological Emergencies. The training in the medical aspects of the radiological emergencies acquires a singular character. In such a sense when valuing the national situation put onof manifest deficiences as for the training in medical aspects of the radiological emergencies that advised the development of training programs in such aspects for the different response groups linked to the topic. After identified the training necessities and the scope of the same ones, the contents of the training program were elaborated. The program has as general purpose the invigoration of the capacity of the medical response in front of accidental radiological situations, by means of actions that they bear to prepare groups of medical response in the handling of people accident victims and to the identification of potentials,accidental scenarios, as well as of the necessary resources to confront them. The program content approaches theoretical and paractical aspects to the medical aspect to radiological emergencies. The program include the different topics about fundamental of physical biological to radiation protection, radiation protection during exposure of radiological accidents, medical care for overexposed or contaminated persons, drill, exercises and concludes with designation of a strategy as preparation and

  15. Thinking in networks: artistic–architectural responses to ubiquitous information

    Yvonne Spielmann

    2011-12-01

    Full Text Available The article discusses creative practices that in aesthetical-technical ways intervene into the computer networked communication systems.I am interested in artist practices that use networks in different ways to make us aware about the possibilities to rethink media-cultural environments. I use the example of the Japanese art-architectural group Double Negative Architecture to give an example of creatively thinking in networks.Yvonne Spielmann (Ph.D., Dr. habil. is presently Research Professor and Chair of New Media at The University of the West of Scotland. Her work focuses on inter-relationships between media and culture, technology, art, science and communication, and in particular on Western/European and non-Western/South-East Asian interaction. Milestones of publish research output are four authored monographs and about 90 single authored articles. Her book, “Video, the Reflexive Medium” (published by MIT Press 2008, Japanese edition by Sangen-sha Press 2011 was rewarded the 2009 Lewis Mumford Award for Outstanding Scholarship in the Ecology of Technics. Her most recent book “Hybrid Cultures” was published in German by Suhrkamp Press in 2010, English edition from MIT Press in 2012. Spielmann's work has been published in German and English and has been translated into French, Polish, Croatian, Swedish, Japanese, and Korean. She holds the 2011 Swedish Prize for Swedish–German scientific co-operation.

  16. Concept typicality responses in the semantic memory network.

    Santi, Andrea; Raposo, Ana; Frade, Sofia; Marques, J Frederico

    2016-12-01

    For decades concept typicality has been recognized as critical to structuring conceptual knowledge, but only recently has typicality been applied in better understanding the processes engaged by the neurological network underlying semantic memory. This previous work has focused on one region within the network - the Anterior Temporal Lobe (ATL). The ATL responds negatively to concept typicality (i.e., the more atypical the item, the greater the activation in the ATL). To better understand the role of typicality in the entire network, we ran an fMRI study using a category verification task in which concept typicality was manipulated parametrically. We argue that typicality is relevant to both amodal feature integration centers as well as category-specific regions. Both the Inferior Frontal Gyrus (IFG) and ATL demonstrated a negative correlation with typicality, whereas inferior parietal regions showed positive effects. We interpret this in light of functional theories of these regions. Interactions between category and typicality were not observed in regions classically recognized as category-specific, thus, providing an argument against category specific regions, at least with fMRI. Copyright © 2016 Elsevier Ltd. All rights reserved.

  17. Networking of TSOs in Emergency Preparedness and Response

    Weiss, F.P.; Maqua, M.; Kerner, A.; Scott-de-Martinville, E.

    2012-01-01

    On its 2011 General Conference, the IAEA announced the foundation of a forum of technical safety organizations (TSO), the TSO forum, to promote the international cooperation and networking among the TSOs worldwide and to complement the existing network of the regulators. In the light of the Fukushima accident it appears that in case of a large accident, every national crisis organization of the country immediately impacted needs the full access to its technical and human resources to face the situation and obviously the communication and collaboration with other crisis centers will suffer from such challenging conditions. Such a limiting issue can only be resolved by making the international collaboration of the technical crisis centers an official part of their work. Therefore, a new framework has to be settled to establish a worldwide network of technical emergency centers. This, certainly will require state negotiations at top level. The feedback experience from the collaboration between the technical emergency centers during the Fukushima accident could be very fruitful for the new framework. (A.C.)

  18. Cooperative VET in Training Networks: Analysing the Free-Rider Problem in a Sociology-of-Conventions Perspective

    Regula Julia Leemann

    2015-12-01

    Full Text Available In training networks, particularly small and medium-sized enterprises pool their resources to train apprentices within the framework of the dual VET system, while an intermediary organisation is tasked with managing operations. Over the course of their apprenticeship, the apprentices switch from one training company to another on a (half- yearly basis. Drawing on a case study of four training networks in Switzerland and the theoretical framework of the sociology of conventions, this paper aims to understand the reasons for the slow dissemination and reluctant adoption of this promising form of organising VET in Switzerland. The results of the study show that the system of moving from one company to another creages a variety of free-rider constellations in the distribution of the collectively generated corporative benefits. This explains why companies are reluctant to participate in this model. For the network to be sustainable, the intermediary organisation has to address discontent arising from free-rider problems while taking into account that the solutions found are always tentative and will often result in new free-rider problems.

  19. Predicting Student Academic Performance: A Comparison of Two Meta-Heuristic Algorithms Inspired by Cuckoo Birds for Training Neural Networks

    Jeng-Fung Chen

    2014-10-01

    Full Text Available Predicting student academic performance with a high accuracy facilitates admission decisions and enhances educational services at educational institutions. This raises the need to propose a model that predicts student performance, based on the results of standardized exams, including university entrance exams, high school graduation exams, and other influential factors. In this study, an approach to the problem based on the artificial neural network (ANN with the two meta-heuristic algorithms inspired by cuckoo birds and their lifestyle, namely, Cuckoo Search (CS and Cuckoo Optimization Algorithm (COA is proposed. In particular, we used previous exam results and other factors, such as the location of the student’s high school and the student’s gender as input variables, and predicted the student academic performance. The standard CS and standard COA were separately utilized to train the feed-forward network for prediction. The algorithms optimized the weights between layers and biases of the neuron network. The simulation results were then discussed and analyzed to investigate the prediction ability of the neural network trained by these two algorithms. The findings demonstrated that both CS and COA have potential in training ANN and ANN-COA obtained slightly better results for predicting student academic performance in this case. It is expected that this work may be used to support student admission procedures and strengthen the service system in educational institutions.

  20. Response Time Test for The Application of the Data Communication Network to Nuclear Power Plant

    Shin, Y.C.; Lee, J.Y.; Park, H.Y.; Seong, S.H.; Chung, H.Y.

    2002-01-01

    This paper discusses the response time test for the application of the Data Communication Network (DCN) to Nuclear Power Plant (NPP). Conventional Instrumentation and Control (I and C) Systems using the analog technology in NPP have raised many problems regarding the lack of spare parts, maintenance burden, inaccuracy, etc.. In order to solve the problems, the Korean Next Generation Reactor (KNGR) I and C system has adopted the digital technology and new design features of using the data communication networks. It is essential to prove the response time requirements that arise from the introduction of digital I and C technology and data communication networks to nuclear power plant design. For the response time test, a high reliable data communication network structure has been developed to meet the requirements of redundancy, diversity, and segmentation. This paper presents the results of network load analysis and response time test for the KNGR DCN prototype. The test has been focused on the response time from the field components to the gateway because the response times from the gateway to the specific systems are similar to those of the existing design. It is verified that the response time requirements are met through the prototype test for KNGR I and C systems. (authors)

  1. Evaluation of the Physiological Challenges in Extreme Environments: Implications for Enhanced Training, Operational Performance and Sex-Specific Responses

    2017-10-01

    Operational Performance and Sex -Specific Responses PRINCIPAL INVESTIGATOR: Brent C. Ruby CONTRACTING ORGANIZATION: The University of Montana Missoula...Implications for Enhanced Training, Operational Performance and Sex -Specific Responses 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT...Evaluation of the physiological challenges in extreme environments: Implications for enhanced training, operational performance and sex -specific

  2. Enhanced Corticospinal Excitability and Volitional Drive in Response to Shortening and Lengthening Strength Training and Changes Following Detraining

    Tallent, Jamie; Goodall, Stuart; Gibbon, Karl C.; Hortobagyi, Tibor; Howatson, Glyn

    2017-01-01

    There is a limited understanding of the neurological adaptations responsible for changes in strength following shortening and lengthening resistance training and subsequent detraining. The aim of the study was to investigate differences in corticospinal and spinal responses to resistance training of

  3. Enhancing adaptive capacity for restoring fire-dependent ecosystems: the Fire Learning Network's Prescribed Fire Training Exchanges

    Andrew G. Spencer

    2015-09-01

    Full Text Available Prescribed fire is a critical tool for promoting restoration and increasing resilience in fire-adapted ecosystems, but there are barriers to its use, including a shortage of personnel with adequate ecological knowledge and operational expertise to implement prescribed fire across multijurisdictional landscapes. In the United States, recognized needs for both professional development and increased use of fire are not being met, often because of institutional limitations. The Fire Learning Network has been characterized as a multiscalar, collaborative network that works to enhance the adaptive capacity of fire management institutions, and this network developed the Prescribed Fire Training Exchanges (TREXs to address persistent challenges in increasing the capacity for prescribed fire implementation. Our research was designed to investigate where fire professionals face professional barriers, how the TREX addresses these, and in what ways the TREX may be contributing to the adaptive capacity of fire management institutions. We evaluated the training model using surveys, interviews, focus groups, and participant observation. We found that, although the training events cannot overcome all institutional barriers, they incorporate the key components of professional development in fire; foster collaboration, learning, and network building; and provide flexible opportunities with an emphasis on local context to train a variety of professionals with disparate needs. The strategy also offers an avenue for overcoming barriers faced by contingent and nonfederal fire professionals in attaining training and operational experience, thereby increasing the variety of actors and resources involved in fire management. Although it is an incremental step, the TREX is contributing to the adaptive capacity of institutions in social-ecological systems in which fire is a critical ecological process.

  4. Influence of the Training Methods in the Diagnosis of Multiple Sclerosis Using Radial Basis Functions Artificial Neural Networks

    Ángel Gutiérrez

    2015-04-01

    Full Text Available The data available in the average clinical study of a disease is very often small. This is one of the main obstacles in the application of neural networks to the classification of biological signals used for diagnosing diseases. A rule of thumb states that the number of parameters (weights that can be used for training a neural network should be around 15% of the available data, to avoid overlearning. This condition puts a limit on the dimension of the input space. Different authors have used different approaches to solve this problem, like eliminating redundancy in the data, preprocessing the data to find centers for the radial basis functions, or extracting a small number of features that were used as inputs. It is clear that the classification would be better the more features we could feed into the network. The approach utilized in this paper is incrementing the number of training elements with randomly expanding training sets. This way the number of original signals does not constraint the dimension of the input set in the radial basis network. Then we train the network using the method that minimizes the error function using the gradient descent algorithm and the method that uses the particle swarm optimization technique. A comparison between the two methods showed that for the same number of iterations on both methods, the particle swarm optimization was faster, it was learning to recognize only the sick people. On the other hand, the gradient method was not as good in general better at identifying those people.

  5. Development of visible-light responsive and mechanically enhanced "smart" UCST interpenetrating network hydrogels.

    Xu, Yifei; Ghag, Onkar; Reimann, Morgan; Sitterle, Philip; Chatterjee, Prithwish; Nofen, Elizabeth; Yu, Hongyu; Jiang, Hanqing; Dai, Lenore L

    2017-12-20

    An interpenetrating polymer network (IPN), chlorophyllin-incorporated environmentally responsive hydrogel was synthesized and exhibited the following features: enhanced mechanical properties, upper critical solution temperature (UCST) swelling behavior, and promising visible-light responsiveness. Poor mechanical properties are known challenges for hydrogel-based materials. By forming an interpenetrating network between polyacrylamide (PAAm) and poly(acrylic acid) (PAAc) polymer networks, the mechanical properties of the synthesized IPN hydrogels were significantly improved compared to hydrogels made of a single network of each polymer. The formation of the interpenetrating network was confirmed by Fourier Transform Infrared Spectroscopy (FTIR), the analysis of glass transition temperature, and a unique UCST responsive swelling behavior, which is in contrast to the more prevalent lower critical solution temperature (LCST) behaviour of environmentally responsive hydrogels. The visible-light responsiveness of the synthesized hydrogel also demonstrated a positive swelling behavior, and the effect of incorporating chlorophyllin as the chromophore unit was observed to reduce the average pore size and further enhance the mechanical properties of the hydrogel. This interpenetrating network system shows potential to serve as a new route in developing "smart" hydrogels using visible-light as a simple, inexpensive, and remotely controllable stimulus.

  6. The Strategic Impact of Corporate Responsibility and Criminal Networks on Value Co-Creation

    Peter Zettinig

    2011-02-01

    Full Text Available This article is motivated by the increasing concern about the ever-declining security of pharmaceutical products due to the abundance of counterfeit network actors. We argue that if networks are effective mechanisms for criminal organizations to infiltrate into any value chain, then networks should also work for responsible businesses in their quests to counter this phenomenon of value destruction, which is ultimately detrimental to the value co-creation process. Thus, this article demonstrates a nuanced understanding of the strategic impact of corporate responsibility of actors in networks on value co-creation. The current discourse on value co-creation in business networks is structured in such a way that it precludes its inherent corporate responsibility component even though they are not mutually exclusive. Moreover, research on value co-creation aimed at the proactive and responsible defence of a network substance via value co-protection has been mostly scant. We propose a model of value-optimization through value co-protection and ethical responsibility. This way of theorizing has several implications for both policy making and managerial decision making in the pharmaceutical industry and beyond.

  7. Development and evaluation of a leadership training program for public health emergency response: results from a Chinese study

    Xu Yihua

    2008-10-01

    Full Text Available Abstract Background Since the 9/11 attack and severe acute respiratory syndrome (SARS, the development of qualified and able public health leaders has become a new urgency in building the infrastructure needed to address public health emergencies. Although previous studies have reported that the training of individual leaders is an important approach, the systemic and scientific training model need further improvement and development. The purpose of this study was to develop, deliver, and evaluate a participatory leadership training program for emergency response. Methods Forty-one public health leaders (N = 41 from five provinces completed the entire emergency preparedness training program in China. The program was evaluated by anonymous questionnaires and semi-structured interviews held prior to training, immediately post-training and 12-month after training (Follow-up. Results The emergency preparedness training resulted in positive shifts in knowledge, self-assessment of skills for public health leaders. More than ninety-five percent of participants reported that the training model was scientific and feasible. Moreover, the response of participants in the program to the avian influenza outbreak, as well as the planned evaluations for this leadership training program, further demonstrated both the successful approaches and methods and the positive impact of this integrated leadership training initiative. Conclusion The emergency preparedness training program met its aims and objectives satisfactorily, and improved the emergency capability of public health leaders. This suggests that the leadership training model was effective and feasible in improving the emergency preparedness capability.

  8. Networks of trainees: examining the effects of attending an interdisciplinary research training camp on the careers of new obesity scholars

    Godley J

    2014-10-01

    Full Text Available Jenny Godley,1 Nicole M Glenn,2 Arya M Sharma,3 John C Spence4 1Department of Sociology, University of Calgary, Calgary, AB, Canada; 2School of Public Health, Université de Montréal, Montreal, QC, Canada; 3Department of Medicine, 4Sedentary Living Laboratory, Faculty of Physical Education and Recreation, University of Alberta, Edmonton, AB, Canada Abstract: Students training in obesity research, prevention, and management face the challenge of developing expertise in their chosen academic field while at the same time recognizing that obesity is a complex issue that requires a multidisciplinary and multisectoral approach. In appreciation of this challenge, the Canadian Obesity Network (CON has run an interdisciplinary summer training camp for graduate students, new career researchers, and clinicians for the past 8 years. This paper evaluates the effects of attending this training camp on trainees' early careers. We use social network analysis to examine the professional connections developed among trainee Canadian obesity researchers who attended this camp over its first 5 years of operation (2006–2010. We examine four relationships (knowing, contacting, and meeting each other, and working together among previous trainees. We assess the presence and diversity of these relationships among trainees across different years and disciplines and find that interdisciplinary contact and working relationships established at the training camp have been maintained over time. In addition, we evaluate the qualitative data on trainees' career trajectories and their assessments of the impact that the camp had on their careers. Many trainees report that camp attendance had a positive impact on their career development, particularly in terms of establishing contacts and professional relationships. Both the quantitative and the qualitative results demonstrate the importance of interdisciplinary training and relationships for career development in the health

  9. The European Nuclear Education Network: Towards Harmonisation of Education, Training, and Transfer of Knowledge

    Tuomisto, F.; Cizelj, L.; Dieguez Porras, P.

    2016-01-01

    Full text: The European Nuclear Education Network (ENEN) Association strives to develop a more harmonized approach for education in the nuclear sciences and nuclear engineering in Europe and to integrate European education and training in nuclear safety and radiation protection. Improved co-operation and sharing of academic resources and capabilities at the national and international level is an important long-term objective. With respect to stakeholders, such as nuclear industries, research centers, regulatory bodies and other nuclear infrastructures, the primary objectives of ENEN are to create a secure basis of skills and knowledge of value to the EU, and to maintain a high-quality supply of qualified human resources for design, construction, operation and maintenance of nuclear infrastructures, industries and power plants. ENEN supports activities aimed at maintaining the necessary competence and expertise for the continued safe use of nuclear energy and applications of radiation and nuclear techniques in agriculture, industry and medicine. In this technical brief we describe selected activities pursued to reach these goals. (author

  10. Training echo state networks for rotation-invariant bone marrow cell classification.

    Kainz, Philipp; Burgsteiner, Harald; Asslaber, Martin; Ahammer, Helmut

    2017-01-01

    The main principle of diagnostic pathology is the reliable interpretation of individual cells in context of the tissue architecture. Especially a confident examination of bone marrow specimen is dependent on a valid classification of myeloid cells. In this work, we propose a novel rotation-invariant learning scheme for multi-class echo state networks (ESNs), which achieves very high performance in automated bone marrow cell classification. Based on representing static images as temporal sequence of rotations, we show how ESNs robustly recognize cells of arbitrary rotations by taking advantage of their short-term memory capacity. The performance of our approach is compared to a classification random forest that learns rotation-invariance in a conventional way by exhaustively training on multiple rotations of individual samples. The methods were evaluated on a human bone marrow image database consisting of granulopoietic and erythropoietic cells in different maturation stages. Our ESN approach to cell classification does not rely on segmentation of cells or manual feature extraction and can therefore directly be applied to image data.

  11. German MedicalTeachingNetwork (MDN) implementing national standards for teacher training.

    Lammerding-Koeppel, M; Ebert, T; Goerlitz, A; Karsten, G; Nounla, C; Schmidt, S; Stosch, C; Dieter, P

    2016-01-01

    An increasing demand for proof of professionalism in higher education strives for quality assurance (QA) and improvement in medical education. A wide range of teacher trainings is available to medical staff in Germany. Cross-institutional approval of individual certificates is usually a difficult and time consuming task for institutions. In case of non-acceptance it may hinder medical teachers in their professional mobility. The faculties of medicine aimed to develop a comprehensive national framework, to promote standards for formal faculty development programmes across institutions and to foster professionalization of medical teaching. Addressing the above challenges in a joint approach, the faculties set up the national MedicalTeacherNetwork (MDN). Great importance is attributed to work out nationally concerted standards for faculty development and an agreed-upon quality control process across Germany. Medical teachers benefit from these advantages due to portability of faculty development credentials from one faculty of medicine to another within the MDN system. The report outlines the process of setting up the MDN and the national faculty development programme in Germany. Success factors, strengths and limitations are discussed from an institutional, individual and general perspective. Faculties engaged in similar developments might be encouraged to transfer the MDN concept to their countries.

  12. Improving quantitative structure-activity relationship models using Artificial Neural Networks trained with dropout.

    Mendenhall, Jeffrey; Meiler, Jens

    2016-02-01

    Dropout is an Artificial Neural Network (ANN) training technique that has been shown to improve ANN performance across canonical machine learning (ML) datasets. Quantitative Structure Activity Relationship (QSAR) datasets used to relate chemical structure to biological activity in Ligand-Based Computer-Aided Drug Discovery pose unique challenges for ML techniques, such as heavily biased dataset composition, and relatively large number of descriptors relative to the number of actives. To test the hypothesis that dropout also improves QSAR ANNs, we conduct a benchmark on nine large QSAR datasets. Use of dropout improved both enrichment false positive rate and log-scaled area under the receiver-operating characteristic curve (logAUC) by 22-46 % over conventional ANN implementations. Optimal dropout rates are found to be a function of the signal-to-noise ratio of the descriptor set, and relatively independent of the dataset. Dropout ANNs with 2D and 3D autocorrelation descriptors outperform conventional ANNs as well as optimized fingerprint similarity search methods.

  13. Fluid distribution network and steam generators and method for nuclear power plant training simulator

    Alliston, W.H.; Johnson, S.J.; Mutafelija, B.A.

    1975-01-01

    A description is given of a training simulator for the real-time dynamic operation of a nuclear power plant which utilizes apparatus that includes control consoles having manual and automatic devices corresponding to simulated plant components and indicating devices for monitoring physical values in the simulated plant. A digital computer configuration is connected to the control consoles to calculate the dynamic real-time simulated operation of the plant in accordance with the simulated plant components to provide output data including data for operating the control console indicating devices. In the method and system for simulating a fluid distribution network of the power plant, such as that which includes, for example, a main steam system which distributes steam from steam generators to high pressure turbine steam reheaters, steam dump valves, and feedwater heaters, the simultaneous solution of linearized non-linear algebraic equations is used to calculate all the flows throughout the simulated system. A plurality of parallel connected steam generators that supply steam to the system are simulated individually, and include the simulation of shrink-swell characteristics

  14. Identification, Response, and Referral of Suicidal Youth Following Applied Suicide Intervention Skills Training.

    Ewell Foster, Cynthia J; Burnside, Amanda N; Smith, Patricia K; Kramer, Anne C; Wills, Allie; A King, Cheryl

    2017-06-01

    Gatekeeper training is a public health approach to suicide prevention that encourages community members to identify those at risk for suicide, respond appropriately, and refer for clinical services. Despite widespread use, few studies have examined whether training results in behavior change in participants. This study employed a naturalistic pre-post design to follow 434 participants in Applied Suicide Intervention Skills Training, finding small but significant increases in self-reported identification of at-risk youth, some helpful responses to youth, and numbers of youth referred to treatment from pre-test to 6- to 9-month follow-up. Changes in active listening and helping behaviors meant to support treatment referrals (such as convincing a youth to seek treatment) were not observed over time. Additional analyses explored predictors of self-reported skill utilization including identification as a "natural helper" and attitudes about suicide prevention. © 2016 The American Association of Suicidology.

  15. An investigation of response and stimulus modality transfer effects after dual-task training in younger and older.

    Lussier, Maxime; Gagnon, Christine; Bherer, Louis

    2012-01-01

    It has been shown that dual-task training leads to significant improvement in dual-task performance in younger and older adults. However, the extent to which training benefits to untrained tasks requires further investigation. The present study assessed (a) whether dual-task training leads to cross-modality transfer in untrained tasks using new stimuli and/or motor responses modalities, (b) whether transfer effects are related to improved ability to prepare and maintain multiple task-set and/or enhanced response coordination, (c) whether there are age-related differences in transfer effects. Twenty-three younger and 23 older adults were randomly assigned to dual-task training or control conditions. All participants were assessed before and after training on three dual-task transfer conditions; (1) stimulus modality transfer (2) response modality transfer (3) stimulus and response modalities transfer task. Training group showed larger improvement than the control group in the three transfer dual-task conditions, which suggests that training leads to more than specific learning of stimuli/response associations. Attentional costs analyses showed that training led to improved dual-task cost, only in conditions that involved new stimuli or response modalities, but not both. Moreover, training did not lead to a reduced task-set cost in the transfer conditions, which suggests some limitations in transfer effects that can be expected. Overall, the present study supports the notion that cognitive plasticity for attentional control is preserved in late adulthood.

  16. An investigation of far response and stimulus modality transfer effects after dual-task training in younger and older adults

    Maxime eLussier

    2012-05-01

    Full Text Available It has been shown that dual-task training leads to significant improvement in dual-task performances in younger and older adults. However, the extent to which training benefits to untrained tasks requires further investigation. The present study assessed (a whether dual-task training leads to cross-modality transfer in untrained tasks using new stimuli and/or motor responses modalities, (b whether transfer effects are related to improvement in working memory and/or enhanced response coordination, (c whether there are age-related differences in transfer effects. Twenty-three younger and 23 older adults were randomly assigned to dual-task training or control conditions. All participants were assessed before and after training on three dual-task transfer conditions; (1 stimulus modality transfer (2 response modality transfer (3 stimulus and response modalities transfer task. Training group showed larger improvement than the control group in the three transfer dual-task conditions, which suggests that training leads to more than specific learning of stimuli/response associations. Attentional cost analyses showed that training led to improved dual-task cost, only in conditions that involved new stimuli or response modalities, but not both. Moreover, training did not lead to a reduced task-set cost in the transfer conditions, which suggests some limitations in transfer effects that can be expected. Overall, the present study supports the notion that cognitive plasticity for attentional control is preserved in late adulthood.

  17. Extensive training and hippocampus or striatum lesions: effect on place and response strategies.

    Jacobson, Tara K; Gruenbaum, Benjamin F; Markus, Etan J

    2012-02-01

    The hippocampus has been linked to spatial navigation and the striatum to response learning. The current study focuses on how these brain regions continue to interact when an animal is very familiar with the task and the environment and must continuously switch between navigation strategies. Rats were trained to solve a plus maze using a place or a response strategy on different trials within a testing session. A room cue (illumination) was used to indicate which strategy should be used on a given trial. After extensive training, animals underwent dorsal hippocampus, dorsal lateral striatum or sham lesions. As expected hippocampal lesions predominantly caused impairment on place but not response trials. Striatal lesions increased errors on both place and response trials. Competition between systems was assessed by determining error type. Pre-lesion and sham animals primarily made errors to arms associated with the wrong (alternative) strategy, this was not found after lesions. The data suggest a qualitative change in the relationship between hippocampal and striatal systems as a task is well learned. During acquisition the two systems work in parallel, competing with each other. After task acquisition, the two systems become more integrated and interdependent. The fact that with extensive training (as something becomes a "habit"), behaviors become dependent upon the dorsal lateral striatum has been previously shown. The current findings indicate that dorsal lateral striatum involvement occurs even when the behavior is spatial and continues to require hippocampal processing. Published by Elsevier Inc.

  18. High-intensity interval training induces a modest systemic inflammatory response in active, young men

    Zwetsloot, Kevin A; John, Casey S; Lawrence, Marcus M; Battista, Rebecca A; Shanely, R Andrew

    2014-01-01

    The purpose of this study was to determine: 1) the extent to which an acute session of high-intensity interval training (HIIT) increases systemic inflammatory cytokines and chemokines, and 2) whether 2 weeks of HIIT training alters the inflammatory response. Eight recreationally active males (aged 22±2 years) performed 2 weeks of HIIT on a cycle ergometer (six HIIT sessions at 8–12 intervals; 60-second intervals, 75-second active rest) at a power output equivalent to 100% of their predetermined peak oxygen uptake (VO2max). Serum samples were collected during the first and sixth HIIT sessions at rest and immediately, 15, 30, and 45 minutes post-exercise. An acute session of HIIT induced significant increases in interleukin (IL)-6, IL-8, IL-10, tumor necrosis factor-α, and monocyte chemotactic protein-1 compared with rest. The concentrations of interferon-γ, granulocyte macrophage-colony-stimulating factor, and IL-1β were unaltered with an acute session of HIIT Two weeks of training did not alter the inflammatory response to an acute bout of HIIT exercise. Maximal power achieved during a VO2max test significantly increased 4.6%, despite no improvements in VO2max after 2 weeks of HIIT. These data suggest that HIIT exercise induces a small inflammatory response in young, recreationally active men; however, 2 weeks of HIIT does not alter this response. PMID:24520199

  19. Principles for Developing Benchmark Criteria for Staff Training in Responsible Gambling.

    Oehler, Stefan; Banzer, Raphaela; Gruenerbl, Agnes; Malischnig, Doris; Griffiths, Mark D; Haring, Christian

    2017-03-01

    One approach to minimizing the negative consequences of excessive gambling is staff training to reduce the rate of the development of new cases of harm or disorder within their customers. The primary goal of the present study was to assess suitable benchmark criteria for the training of gambling employees at casinos and lottery retailers. The study utilised the Delphi Method, a survey with one qualitative and two quantitative phases. A total of 21 invited international experts in the responsible gambling field participated in all three phases. A total of 75 performance indicators were outlined and assigned to six categories: (1) criteria of content, (2) modelling, (3) qualification of trainer, (4) framework conditions, (5) sustainability and (6) statistical indicators. Nine of the 75 indicators were rated as very important by 90 % or more of the experts. Unanimous support for importance was given to indicators such as (1) comprehensibility and (2) concrete action-guidance for handling with problem gamblers, Additionally, the study examined the implementation of benchmarking, when it should be conducted, and who should be responsible. Results indicated that benchmarking should be conducted every 1-2 years regularly and that one institution should be clearly defined and primarily responsible for benchmarking. The results of the present study provide the basis for developing a benchmarking for staff training in responsible gambling.

  20. Familial aggregation of VO(2max) response to exercise training: results from the HERITAGE Family Study.

    Bouchard, C; An, P; Rice, T; Skinner, J S; Wilmore, J H; Gagnon, J; Pérusse, L; Leon, A S; Rao, D C

    1999-09-01

    The aim of this study was to test the hypothesis that individual differences in the response of maximal O(2) uptake (VO(2max)) to a standardized training program are characterized by familial aggregation. A total of 481 sedentary adult Caucasians from 98 two-generation families was exercise trained for 20 wk and was tested for VO(2max) on a cycle ergometer twice before and twice after the training program. The mean increase in VO(2max) reached approximately 400 ml/min, but there was considerable heterogeneity in responsiveness, with some individuals experiencing little or no gain, whereas others gained >1.0 l/min. An ANOVA revealed that there was 2.5 times more variance between families than within families in the VO(2max) response variance. With the use of a model-fitting procedure, the most parsimonious models yielded a maximal heritability estimate of 47% for the VO(2max) response, which was adjusted for age and sex with a maternal transmission of 28% in one of the models. We conclude that the trainability of VO(2max) is highly familial and includes a significant genetic component.