WorldWideScience

Sample records for sustained neural processing

  1. Sustainable processing

    DEFF Research Database (Denmark)

    Kristensen, Niels Heine

    2004-01-01

    Kristensen_NH and_Beck A: Sustainable processing. In Otto Schmid, Alexander Beck and Ursula Kretzschmar (Editors) (2004): Underlying Principles in Organic and "Low-Input Food" Processing - Literature Survey. Research Institute of Organic Agriculture FiBL, CH-5070 Frick, Switzerland. ISBN 3-906081-58-3...

  2. Sustainability of abrasive processes

    DEFF Research Database (Denmark)

    Aurich, J.C.; Linke, B.; Hauschild, Michael Zwicky

    2013-01-01

    , the content of technical presentations in STC G, and the results of a comprehensive literature study. The approach to sustainability includes environmental, social, and economic sustainability in accordance with the definition proposed in the Brundtland Report of the United Nations [156]. The main focus......This paper presents an overview of research on sustainability of abrasive processes. It incorporates results from a round robin study on ‘‘energy-efficiency of abrasive processes’’ which has been carried out within the scientific technical committee ‘‘abrasive processes’’ (STC G) of CIRP...... is on environmental and social sustainability. Economic sustainability will be considered as manufacturing productivity. © 2013 CIRP....

  3. Neural networks in signal processing

    International Nuclear Information System (INIS)

    Govil, R.

    2000-01-01

    Nuclear Engineering has matured during the last decade. In research and design, control, supervision, maintenance and production, mathematical models and theories are used extensively. In all such applications signal processing is embedded in the process. Artificial Neural Networks (ANN), because of their nonlinear, adaptive nature are well suited to such applications where the classical assumptions of linearity and second order Gaussian noise statistics cannot be made. ANN's can be treated as nonparametric techniques, which can model an underlying process from example data. They can also adopt their model parameters to statistical change with time. Algorithms in the framework of Neural Networks in Signal processing have found new applications potentials in the field of Nuclear Engineering. This paper reviews the fundamentals of Neural Networks in signal processing and their applications in tasks such as recognition/identification and control. The topics covered include dynamic modeling, model based ANN's, statistical learning, eigen structure based processing and generalization structures. (orig.)

  4. Principles of neural information processing

    CERN Document Server

    Seelen, Werner v

    2016-01-01

    In this fundamental book the authors devise a framework that describes the working of the brain as a whole. It presents a comprehensive introduction to the principles of Neural Information Processing as well as recent and authoritative research. The books´ guiding principles are the main purpose of neural activity, namely, to organize behavior to ensure survival, as well as the understanding of the evolutionary genesis of the brain. Among the developed principles and strategies belong self-organization of neural systems, flexibility, the active interpretation of the world by means of construction and prediction as well as their embedding into the world, all of which form the framework of the presented description. Since, in brains, their partial self-organization, the lifelong adaptation and their use of various methods of processing incoming information are all interconnected, the authors have chosen not only neurobiology and evolution theory as a basis for the elaboration of such a framework, but also syst...

  5. Sustainable Process Synthesis-Intensification

    DEFF Research Database (Denmark)

    Babi, Deenesh Kavi; Holtbruegge, Johannes; Lutze, Philip

    2014-01-01

    Sustainable process design can be achieved by performing process synthesis and process intensification together. This approach first defines a design target through a sustainability analysis and then finds design alternatives that match the target through process intensification. A systematic......, multi-stage framework for process synthesis- intensification that identifies more sustainable process designs has been developed. At stages 1-2, the working scale is at the level of unit operations, where a base case design is identified and analyzed with respect to sustainability metrics. At stages 3......, a phenomena-based process synthesis method is applied, where the phenomena involved in each tasks are identified, manipulated and recombined to generate new and/or existing unit operations configured into flowsheets that are more sustainable from those found in the previous levels. An overview of the key...

  6. SUSTAINABLE AND DESIGN BUILDING PROCESSES

    Directory of Open Access Journals (Sweden)

    Silvio F. R. MOTTA

    2009-05-01

    Full Text Available The article presents a historical revision of the sustainable development and the sustainable in the constructed environment. It describes the main concepts and practices for implantation of the sustainable in the civil construction. These concepts and practices are reviewed from the perspective of the dialectic method, the general theory of systems and the theories of creative processes. These concepts are also analyzed from the perspective of quality management. The article proposes a model based on the dialectic, in which sustainability is considered an open system and a search inventive. The implantation of the sustainable in projects, companies and design processes are considered as main strategy. A vertical insertion of the sustainable in the process is proposal. In this vertical insertion, the sustainable is presents in all the phases and activities of the process. The model is organized to promote the external creative solutions to the process, through the promotion of research centers. Tools of selection of possibilities and practical are suggested, considering the characteristic dialectics proposals. The article concludes that sustainable is a cultural change in the processes, practical and management current.

  7. Handbook on neural information processing

    CERN Document Server

    Maggini, Marco; Jain, Lakhmi

    2013-01-01

    This handbook presents some of the most recent topics in neural information processing, covering both theoretical concepts and practical applications. The contributions include:                         Deep architectures                         Recurrent, recursive, and graph neural networks                         Cellular neural networks                         Bayesian networks                         Approximation capabilities of neural networks                         Semi-supervised learning                         Statistical relational learning                         Kernel methods for structured data                         Multiple classifier systems                         Self organisation and modal learning                         Applications to ...

  8. Sustainable process synthesis–intensification

    DEFF Research Database (Denmark)

    Babi, Deenesh Kavi; Holtbruegge, Johannes; Lutze, Philip

    2015-01-01

    Chemical industry is facing global challenges such as the need to find sustainable production processes.Process intensification as part of process synthesis has the potential to find truly innovative and moresustainable solutions. In this paper, a computer-aided, multi-level, multi-scale framework...... for synthesis,design and intensification of processes, for identifying more sustainable alternatives is presented. Withinthe framework, a three stage work-flow has been implemented where, in the first “synthesis” stage anoptimal processing route is synthesized through a network superstructure optimization...

  9. Neural overlap in processing music and speech.

    Science.gov (United States)

    Peretz, Isabelle; Vuvan, Dominique; Lagrois, Marie-Élaine; Armony, Jorge L

    2015-03-19

    Neural overlap in processing music and speech, as measured by the co-activation of brain regions in neuroimaging studies, may suggest that parts of the neural circuitries established for language may have been recycled during evolution for musicality, or vice versa that musicality served as a springboard for language emergence. Such a perspective has important implications for several topics of general interest besides evolutionary origins. For instance, neural overlap is an important premise for the possibility of music training to influence language acquisition and literacy. However, neural overlap in processing music and speech does not entail sharing neural circuitries. Neural separability between music and speech may occur in overlapping brain regions. In this paper, we review the evidence and outline the issues faced in interpreting such neural data, and argue that converging evidence from several methodologies is needed before neural overlap is taken as evidence of sharing. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

  10. Neural overlap in processing music and speech

    Science.gov (United States)

    Peretz, Isabelle; Vuvan, Dominique; Lagrois, Marie-Élaine; Armony, Jorge L.

    2015-01-01

    Neural overlap in processing music and speech, as measured by the co-activation of brain regions in neuroimaging studies, may suggest that parts of the neural circuitries established for language may have been recycled during evolution for musicality, or vice versa that musicality served as a springboard for language emergence. Such a perspective has important implications for several topics of general interest besides evolutionary origins. For instance, neural overlap is an important premise for the possibility of music training to influence language acquisition and literacy. However, neural overlap in processing music and speech does not entail sharing neural circuitries. Neural separability between music and speech may occur in overlapping brain regions. In this paper, we review the evidence and outline the issues faced in interpreting such neural data, and argue that converging evidence from several methodologies is needed before neural overlap is taken as evidence of sharing. PMID:25646513

  11. Conceptual Chemical Process Design for Sustainability.

    Science.gov (United States)

    This chapter examines the sustainable design of chemical processes, with a focus on conceptual design, hierarchical and short-cut methods, and analyses of process sustainability for alternatives. The chapter describes a methodology for incorporating process sustainability analyse...

  12. Recent theoretical, neural, and clinical advances in sustained attention research.

    Science.gov (United States)

    Fortenbaugh, Francesca C; DeGutis, Joseph; Esterman, Michael

    2017-05-01

    Models of attention often distinguish among attention subtypes, with classic models separating orienting, switching, and sustaining functions. Compared with other forms of attention, the neurophysiological basis of sustaining attention has received far less notice, yet it is known that momentary failures of sustained attention can have far-ranging negative effects in healthy individuals, and lasting sustained attention deficits are pervasive in clinical populations. In recent years, however, there has been increased interest in characterizing moment-to-moment fluctuations in sustained attention, in addition to the overall vigilance decrement, and understanding how these neurocognitive systems change over the life span and across various clinical populations. The use of novel neuroimaging paradigms and statistical approaches has allowed for better characterization of the neural networks supporting sustained attention and has highlighted dynamic interactions within and across multiple distributed networks that predict behavioral performance. These advances have also provided potential biomarkers to identify individuals with sustained attention deficits. These findings have led to new theoretical models explaining why sustaining focused attention is a challenge for individuals and form the basis for the next generation of sustained attention research, which seeks to accurately diagnose and develop theoretically driven treatments for sustained attention deficits that affect a variety of clinical populations. © 2017 New York Academy of Sciences.

  13. Recent theoretical, neural, and clinical advances in sustained attention research

    Science.gov (United States)

    Fortenbaugh, Francesca C.; DeGutis, Joseph; Esterman, Michael

    2017-01-01

    Models of attention often distinguish between attention subtypes, with classic models separating orienting, switching, and sustaining functions. Compared to other forms of attention, the neurophysiological basis of sustaining attention has received far less attention yet it is known that momentary failures of sustained attention can have far ranging negative impacts in healthy individuals and lasting sustained attention deficits are pervasive in clinical populations. In recent years, however, there has been increased interest in characterizing moment-to-moment fluctuations in sustained attention in addition to the overall vigilance decrement and understanding how these neurocognitive systems change over the lifespan and across various clinical populations. The use of novel neuroimaging paradigms and statistical approaches has allowed for better characterization of the neural networks supporting sustained attention, and highlighted dynamic interactions within and across multiple distributed networks that predict behavioral performance. These advances have also provided potential biomarkers to identify individuals with sustained attention deficits. These findings have led to new theoretical models of why sustaining focused attention is a challenge for individuals and form the basis for the next generation of sustained attention research, which seeks to accurately diagnose and develop theoretically-driven treatments for sustained attention deficits that affect a variety of clinical populations. PMID:28260249

  14. Textiles and clothing sustainability sustainable textile chemical processes

    CERN Document Server

    2017-01-01

    This book highlights the challenges in sustainable wet processing of textiles, natural dyes, enzymatic textiles and sustainable textile finishes. Textile industry is known for its chemical processing issues and many NGO’s are behind the textile sector to streamline its chemical processing, which is the black face of clothing and fashion sector. Sustainable textile chemical processes are crucial for attaining sustainability in the clothing sector. Seven comprehensive chapters are aimed to highlight these issues in the book.

  15. Signal Processing and Neural Network Simulator

    Science.gov (United States)

    Tebbe, Dennis L.; Billhartz, Thomas J.; Doner, John R.; Kraft, Timothy T.

    1995-04-01

    The signal processing and neural network simulator (SPANNS) is a digital signal processing simulator with the capability to invoke neural networks into signal processing chains. This is a generic tool which will greatly facilitate the design and simulation of systems with embedded neural networks. The SPANNS is based on the Signal Processing WorkSystemTM (SPWTM), a commercial-off-the-shelf signal processing simulator. SPW provides a block diagram approach to constructing signal processing simulations. Neural network paradigms implemented in the SPANNS include Backpropagation, Kohonen Feature Map, Outstar, Fully Recurrent, Adaptive Resonance Theory 1, 2, & 3, and Brain State in a Box. The SPANNS was developed by integrating SAIC's Industrial Strength Neural Networks (ISNN) Software into SPW.

  16. Sustainable Process Synthesis-Intensification

    DEFF Research Database (Denmark)

    Babi, Deenesh Kavi

    The chemical and biochemical industry needs major reductions in energy consumption, waste generation, number of equipment used in the construction of plants and capital/operational cost. These required reductions can be addressed through process intensification that is the efficient use of raw....... Therefore sustainable process design can be achieved by performing process syn-thesis and process intensification together. The main contribution of this work is the development of a systematic computer-aided multi-scale, multi-level framework for performing process synthesis-intensification that aims...... designs that otherwise could not be found from the higher scales. The framework is applied to three case studies related to the chemical and bioprocess industry in order to test the applicability of the framework for covering a wide range of applications, showing that process intensification provides...

  17. Sustained Activity in Hierarchical Modular Neural Networks: Self-Organized Criticality and Oscillations

    Science.gov (United States)

    Wang, Sheng-Jun; Hilgetag, Claus C.; Zhou, Changsong

    2010-01-01

    Cerebral cortical brain networks possess a number of conspicuous features of structure and dynamics. First, these networks have an intricate, non-random organization. In particular, they are structured in a hierarchical modular fashion, from large-scale regions of the whole brain, via cortical areas and area subcompartments organized as structural and functional maps to cortical columns, and finally circuits made up of individual neurons. Second, the networks display self-organized sustained activity, which is persistent in the absence of external stimuli. At the systems level, such activity is characterized by complex rhythmical oscillations over a broadband background, while at the cellular level, neuronal discharges have been observed to display avalanches, indicating that cortical networks are at the state of self-organized criticality (SOC). We explored the relationship between hierarchical neural network organization and sustained dynamics using large-scale network modeling. Previously, it was shown that sparse random networks with balanced excitation and inhibition can sustain neural activity without external stimulation. We found that a hierarchical modular architecture can generate sustained activity better than random networks. Moreover, the system can simultaneously support rhythmical oscillations and SOC, which are not present in the respective random networks. The mechanism underlying the sustained activity is that each dense module cannot sustain activity on its own, but displays SOC in the presence of weak perturbations. Therefore, the hierarchical modular networks provide the coupling among subsystems with SOC. These results imply that the hierarchical modular architecture of cortical networks plays an important role in shaping the ongoing spontaneous activity of the brain, potentially allowing the system to take advantage of both the sensitivity of critical states and the predictability and timing of oscillations for efficient information

  18. Garri Processing And Fish Smoking Enterprises: Sustainable ...

    African Journals Online (AJOL)

    The study examines the status of garri processing and fish smoking projects as viable and sustainable projects in the Ogba/Egbema/Ndoni local government area of Rivers State. This is because the projects provided employment to the unemployed and the unemployable thereby sustaining them and improving the lot of the ...

  19. Neural substrates of sublexical processing for spelling.

    Science.gov (United States)

    DeMarco, Andrew T; Wilson, Stephen M; Rising, Kindle; Rapcsak, Steven Z; Beeson, Pélagie M

    2017-01-01

    We used fMRI to examine the neural substrates of sublexical phoneme-grapheme conversion during spelling in a group of healthy young adults. Participants performed a writing-to-dictation task involving irregular words (e.g., choir), plausible nonwords (e.g., kroid), and a control task of drawing familiar geometric shapes (e.g., squares). Written production of both irregular words and nonwords engaged a left-hemisphere perisylvian network associated with reading/spelling and phonological processing skills. Effects of lexicality, manifested by increased activation during nonword relative to irregular word spelling, were noted in anterior perisylvian regions (posterior inferior frontal gyrus/operculum/precentral gyrus/insula), and in left ventral occipito-temporal cortex. In addition to enhanced neural responses within domain-specific components of the language network, the increased cognitive demands associated with spelling nonwords engaged domain-general frontoparietal cortical networks involved in selective attention and executive control. These results elucidate the neural substrates of sublexical processing during written language production and complement lesion-deficit correlation studies of phonological agraphia. Copyright © 2016 Elsevier Inc. All rights reserved.

  20. Sustained activity in hierarchical modular neural networks: self-organized criticality and oscillations

    Directory of Open Access Journals (Sweden)

    Sheng-Jun Wang

    2011-06-01

    Full Text Available Cerebral cortical brain networks possess a number of conspicuous features of structure and dynamics. First, these networks have an intricate, non-random organization. They are structured in a hierarchical modular fashion, from large-scale regions of the whole brain, via cortical areas and area subcompartments organized as structural and functional maps to cortical columns, and finally circuits made up of individual neurons. Second, the networks display self-organized sustained activity, which is persistent in the absence of external stimuli. At the systems level, such activity is characterized by complex rhythmical oscillations over a broadband background, while at the cellular level, neuronal discharges have been observed to display avalanches, indicating that cortical networks are at the state of self-organized criticality. We explored the relationship between hierarchical neural network organization and sustained dynamics using large-scale network modeling. It was shown that sparse random networks with balanced excitation and inhibition can sustain neural activity without external stimulation. We find that a hierarchical modular architecture can generate sustained activity better than random networks. Moreover, the system can simultaneously support rhythmical oscillations and self-organized criticality, which are not present in the respective random networks. The underlying mechanism is that each dense module cannot sustain activity on its own, but displays self-organized criticality in the presence of weak perturbations. The hierarchical modular networks provide the coupling among subsystems with self-organized criticality. These results imply that the hierarchical modular architecture of cortical networks plays an important role in shaping the ongoing spontaneous activity of the brain, potentially allowing the system to take advantage of both the sensitivityof critical state and predictability and timing of oscillations for efficient

  1. Modeling and Advanced Control for Sustainable Process ...

    Science.gov (United States)

    This book chapter introduces a novel process systems engineering framework that integrates process control with sustainability assessment tools for the simultaneous evaluation and optimization of process operations. The implemented control strategy consists of a biologically-inspired, multi-agent-based method. The sustainability and performance assessment of process operating points is carried out using the U.S. E.P.A.’s GREENSCOPE assessment tool that provides scores for the selected economic, material management, environmental and energy indicators. The indicator results supply information on whether the implementation of the controller is moving the process towards a more sustainable operation. The effectiveness of the proposed framework is illustrated through a case study of a continuous bioethanol fermentation process whose dynamics are characterized by steady-state multiplicity and oscillatory behavior. This book chapter contribution demonstrates the application of novel process control strategies for sustainability by increasing material management, energy efficiency, and pollution prevention, as needed for SHC Sustainable Uses of Wastes and Materials Management.

  2. Active voltammetric microsensors with neural signal processing.

    Energy Technology Data Exchange (ETDEWEB)

    Vogt, M. C.

    1998-12-11

    Many industrial and environmental processes, including bioremediation, would benefit from the feedback and control information provided by a local multi-analyte chemical sensor. For most processes, such a sensor would need to be rugged enough to be placed in situ for long-term remote monitoring, and inexpensive enough to be fielded in useful numbers. The multi-analyte capability is difficult to obtain from common passive sensors, but can be provided by an active device that produces a spectrum-type response. Such new active gas microsensor technology has been developed at Argonne National Laboratory. The technology couples an electrocatalytic ceramic-metallic (cermet) microsensor with a voltammetric measurement technique and advanced neural signal processing. It has been demonstrated to be flexible, rugged, and very economical to produce and deploy. Both narrow interest detectors and wide spectrum instruments have been developed around this technology. Much of this technology's strength lies in the active measurement technique employed. The technique involves applying voltammetry to a miniature electrocatalytic cell to produce unique chemical ''signatures'' from the analytes. These signatures are processed with neural pattern recognition algorithms to identify and quantify the components in the analyte. The neural signal processing allows for innovative sampling and analysis strategies to be employed with the microsensor. In most situations, the whole response signature from the voltammogram can be used to identify, classify, and quantify an analyte, without dissecting it into component parts. This allows an instrument to be calibrated once for a specific gas or mixture of gases by simple exposure to a multi-component standard rather than by a series of individual gases. The sampled unknown analytes can vary in composition or in concentration, the calibration, sensing, and processing methods of these active voltammetric microsensors can

  3. Active voltammetric microsensors with neural signal processing

    Science.gov (United States)

    Vogt, Michael C.; Skubal, Laura R.

    1999-02-01

    Many industrial and environmental processes, including bioremediation, would benefit from the feedback and control information provided by a local multi-analyte chemical sensor. For most processes, such a sensor would need to be rugged enough to be placed in situ for long-term remote monitoring, and inexpensive enough to be fielded in useful numbers. The multi-analyte capability is difficult to obtain from common passive sensors, but can be provided by an active device that produces a spectrum-type response. Such new active gas microsensor technology has been developed at Argonne National Laboratory. The technology couples an electrocatalytic ceramic-metallic (cermet) microsensor with a voltammetric measurement technique and advanced neural signal processing. It has been demonstrated to be flexible, rugged, and very economical to produce and deploy. Both narrow interest detectors and wide spectrum instruments have been developed around this technology. Much of this technology's strength lies in the active measurement technique employed. The technique involves applying voltammetry to a miniature electrocatalytic cell to produce unique chemical 'signatures' from the analytes. These signatures are processed with neural pattern recognition algorithms to identify and quantify the components in the analyte. The neural signal processing allows for innovative sampling and analysis strategies to be employed with the microsensor. In most situations, the whole response signature from the voltammogram can be used to identify, classify, and quantify an analyte, without dissecting it into component parts. This allows an instrument to be calibrated once for a specific gas or mixture of gases by simple exposure to a multi-component standard rather than by a series of individual gases. The sampled unknown analytes can vary in composition or in concentration; the calibration, sensing, and processing methods of these active voltammetric microsensors can detect, recognize, and

  4. Sustainability evaluation of nanotechnology processing and production

    OpenAIRE

    Teresa M. Mata; Nídia de Sá Caetano; António A. Martins

    2015-01-01

    This article discusses the current situation and challenges posed by nanotechnology from a sustainability point of view. It presents an objective methodology to evaluate the sustainability of nanotechnology products, based on a life cycle thinking approach, a framework particularly suited to assess all current and future relevant economic, societal and environmental impacts products and processes. It is grounded on a hierarchical definition of indicators, starting from 3D indicators that take...

  5. The gamma model : a new neural network for temporal processing

    NARCIS (Netherlands)

    Vries, de B.

    1992-01-01

    In this paper we develop the gamma neural model, a new neural net architecture for processing of temporal patterns. Time varying patterns are normally segmented into a sequence of static patterns that are successively presented to a neural net. In the approach presented here segmentation is avoided.

  6. Neural Adaptation Effects in Conceptual Processing

    Directory of Open Access Journals (Sweden)

    Barbara F. M. Marino

    2015-07-01

    Full Text Available We investigated the conceptual processing of nouns referring to objects characterized by a highly typical color and orientation. We used a go/no-go task in which we asked participants to categorize each noun as referring or not to natural entities (e.g., animals after a selective adaptation of color-edge neurons in the posterior LV4 region of the visual cortex was induced by means of a McCollough effect procedure. This manipulation affected categorization: the green-vertical adaptation led to slower responses than the green-horizontal adaptation, regardless of the specific color and orientation of the to-be-categorized noun. This result suggests that the conceptual processing of natural entities may entail the activation of modality-specific neural channels with weights proportional to the reliability of the signals produced by these channels during actual perception. This finding is discussed with reference to the debate about the grounded cognition view.

  7. Neural processing of reward in adolescent rodents

    Directory of Open Access Journals (Sweden)

    Nicholas W. Simon

    2015-02-01

    Full Text Available Immaturities in adolescent reward processing are thought to contribute to poor decision making and increased susceptibility to develop addictive and psychiatric disorders. Very little is known; however, about how the adolescent brain processes reward. The current mechanistic theories of reward processing are derived from adult models. Here we review recent research focused on understanding of how the adolescent brain responds to rewards and reward-associated events. A critical aspect of this work is that age-related differences are evident in neuronal processing of reward-related events across multiple brain regions even when adolescent rats demonstrate behavior similar to adults. These include differences in reward processing between adolescent and adult rats in orbitofrontal cortex and dorsal striatum. Surprisingly, minimal age related differences are observed in ventral striatum, which has been a focal point of developmental studies. We go on to discuss the implications of these differences for behavioral traits affected in adolescence, such as impulsivity, risk-taking, and behavioral flexibility. Collectively, this work suggests that reward-evoked neural activity differs as a function of age and that regions such as the dorsal striatum that are not traditionally associated with affective processing in adults may be critical for reward processing and psychiatric vulnerability in adolescents.

  8. Theory of Neural Information Processing Systems

    International Nuclear Information System (INIS)

    Galla, Tobias

    2006-01-01

    It is difficult not to be amazed by the ability of the human brain to process, to structure and to memorize information. Even by the toughest standards the behaviour of this network of about 10 11 neurons qualifies as complex, and both the scientific community and the public take great interest in the growing field of neuroscience. The scientific endeavour to learn more about the function of the brain as an information processing system is here a truly interdisciplinary one, with important contributions from biology, computer science, physics, engineering and mathematics as the authors quite rightly point out in the introduction of their book. The role of the theoretical disciplines here is to provide mathematical models of information processing systems and the tools to study them. These models and tools are at the centre of the material covered in the book by Coolen, Kuehn and Sollich. The book is divided into five parts, providing basic introductory material on neural network models as well as the details of advanced techniques to study them. A mathematical appendix complements the main text. The range of topics is extremely broad, still the presentation is concise and the book well arranged. To stress the breadth of the book let me just mention a few keywords here: the material ranges from the basics of perceptrons and recurrent network architectures to more advanced aspects such as Bayesian learning and support vector machines; Shannon's theory of information and the definition of entropy are discussed, and a chapter on Amari's information geometry is not missing either. Finally the statistical mechanics chapters cover Gardner theory and the replica analysis of the Hopfield model, not without being preceded by a brief introduction of the basic concepts of equilibrium statistical physics. The book also contains a part on effective theories of the macroscopic dynamics of neural networks. Many dynamical aspects of neural networks are usually hard to find in the

  9. Autonomous dynamics in neural networks: the dHAN concept and associative thought processes

    Science.gov (United States)

    Gros, Claudius

    2007-02-01

    The neural activity of the human brain is dominated by self-sustained activities. External sensory stimuli influence this autonomous activity but they do not drive the brain directly. Most standard artificial neural network models are however input driven and do not show spontaneous activities. It constitutes a challenge to develop organizational principles for controlled, self-sustained activity in artificial neural networks. Here we propose and examine the dHAN concept for autonomous associative thought processes in dense and homogeneous associative networks. An associative thought-process is characterized, within this approach, by a time-series of transient attractors. Each transient state corresponds to a stored information, a memory. The subsequent transient states are characterized by large associative overlaps, which are identical to acquired patterns. Memory states, the acquired patterns, have such a dual functionality. In this approach the self-sustained neural activity has a central functional role. The network acquires a discrimination capability, as external stimuli need to compete with the autonomous activity. Noise in the input is readily filtered-out. Hebbian learning of external patterns occurs coinstantaneous with the ongoing associative thought process. The autonomous dynamics needs a long-term working-point optimization which acquires within the dHAN concept a dual functionality: It stabilizes the time development of the associative thought process and limits runaway synaptic growth, which generically occurs otherwise in neural networks with self-induced activities and Hebbian-type learning rules.

  10. Effects of social sustainability signals on neural valuation signals and taste-experience of food products

    Directory of Open Access Journals (Sweden)

    Laura eEnax

    2015-09-01

    Full Text Available Value-based decision making occurs when individuals choose between different alternatives and place a value on each alternative and its attributes. Marketing actions frequently manipulate product attributes, by adding e.g., health claims on the packaging. A previous imaging study found that an emblem for organic products increased willingness to pay (WTP and activity in the ventral striatum (VS. The current study investigated neural and behavioral processes underlying the influence of Fair Trade (FT labeling on food valuation and choice. Sustainability is an important product attribute for many consumers, with FT signals being one way to highlight ethically sustainable production. Forty participants valuated products in combination with an FT emblem or no emblem and stated their WTP in a bidding task while in an MRI scanner. After that, participants tasted – objectively identical – chocolates, presented either as FT or as conventionally produced. In the fMRI task, WTP was significantly higher for FT products. FT labeling increased activity in regions important for reward-processing and salience, that is, in the VS, anterior and posterior cingulate, as well as superior frontal gyrus. Subjective value, that is, WTP was correlated with activity in the ventromedial prefrontal cortex (vmPFC. We find that the anterior cingulate, VS and superior frontal gyrus exhibit task-related increases in functional connectivity to the vmPFC when an FT product was evaluated, suggesting a network which alters valuation processes. We also found a significant taste-placebo effect, with higher experienced taste pleasantness and intensity for FT labeled chocolates. Our results reveal a possible neural mechanism underlying valuation processes of certified food products. The results are important in light of understanding current marketing trends as well as designing future interventions that aim at positively influencing food choice.

  11. Garri Processing And Fish Smoking Enterprises: Sustainable ...

    African Journals Online (AJOL)

    Garri Processing And Fish Smoking Enterprises: Sustainable Development Projects In Ogba/Egbema/Ndoni Local Government Of Rivers State, Nigeria. ... Alternatively, you can download the PDF file directly to your computer, from where it can be opened using a PDF reader. To download the PDF, click the Download link ...

  12. Life cycle sustainability assessment of chemical processes

    DEFF Research Database (Denmark)

    Xu, Di; Lv, Liping; Ren, Jingzheng

    2017-01-01

    In this study, an integrated vector-based three-dimensional (3D) methodology for the life cycle sustainability assessment (LCSA) of chemical process alternatives is proposed. In the methodology, a 3D criteria assessment system is first established by using the life cycle assessment, the life cycl...

  13. Sustainable Food Processing Inspired by Nature.

    Science.gov (United States)

    Sybesma, Wilbert; Blank, Imre; Lee, Yuan-Kun

    2017-04-01

    Here, we elaborate on the natural origin and use of enzymes and cultures in sustainable food processing. We also illustrate how enzymatically treated or fermented food can contribute to solving challenges involving nutrition and health, such as aging, malnutrition, obesity, and allergy. Copyright © 2017. Published by Elsevier Ltd.

  14. Neural Parallel Engine: A toolbox for massively parallel neural signal processing.

    Science.gov (United States)

    Tam, Wing-Kin; Yang, Zhi

    2018-05-01

    Large-scale neural recordings provide detailed information on neuronal activities and can help elicit the underlying neural mechanisms of the brain. However, the computational burden is also formidable when we try to process the huge data stream generated by such recordings. In this study, we report the development of Neural Parallel Engine (NPE), a toolbox for massively parallel neural signal processing on graphical processing units (GPUs). It offers a selection of the most commonly used routines in neural signal processing such as spike detection and spike sorting, including advanced algorithms such as exponential-component-power-component (EC-PC) spike detection and binary pursuit spike sorting. We also propose a new method for detecting peaks in parallel through a parallel compact operation. Our toolbox is able to offer a 5× to 110× speedup compared with its CPU counterparts depending on the algorithms. A user-friendly MATLAB interface is provided to allow easy integration of the toolbox into existing workflows. Previous efforts on GPU neural signal processing only focus on a few rudimentary algorithms, are not well-optimized and often do not provide a user-friendly programming interface to fit into existing workflows. There is a strong need for a comprehensive toolbox for massively parallel neural signal processing. A new toolbox for massively parallel neural signal processing has been created. It can offer significant speedup in processing signals from large-scale recordings up to thousands of channels. Copyright © 2018 Elsevier B.V. All rights reserved.

  15. Introduction to spiking neural networks: Information processing, learning and applications.

    Science.gov (United States)

    Ponulak, Filip; Kasinski, Andrzej

    2011-01-01

    The concept that neural information is encoded in the firing rate of neurons has been the dominant paradigm in neurobiology for many years. This paradigm has also been adopted by the theory of artificial neural networks. Recent physiological experiments demonstrate, however, that in many parts of the nervous system, neural code is founded on the timing of individual action potentials. This finding has given rise to the emergence of a new class of neural models, called spiking neural networks. In this paper we summarize basic properties of spiking neurons and spiking networks. Our focus is, specifically, on models of spike-based information coding, synaptic plasticity and learning. We also survey real-life applications of spiking models. The paper is meant to be an introduction to spiking neural networks for scientists from various disciplines interested in spike-based neural processing.

  16. Optimal Hierarchical Modular Topologies for Producing Limited Sustained Activation of Neural Networks

    OpenAIRE

    Kaiser, Marcus; Hilgetag, Claus C.

    2010-01-01

    An essential requirement for the representation of functional patterns in complex neural networks, such as the mammalian cerebral cortex, is the existence of stable regimes of network activation, typically arising from a limited parameter range. In this range of limited sustained activity (LSA), the activity of neural populations in the network persists between the extremes of either quickly dying out or activating the whole network. Hierarchical modular networks were previously found to show...

  17. Linking neural and symbolic representation and processing of conceptual structures

    NARCIS (Netherlands)

    van der Velde, Frank; Forth, Jamie; Nazareth, Deniece S.; Wiggins, Geraint A.

    2017-01-01

    We compare and discuss representations in two cognitive architectures aimed at representing and processing complex conceptual (sentence-like) structures. First is the Neural Blackboard Architecture (NBA), which aims to account for representation and processing of complex and combinatorial conceptual

  18. Diagnostic Classifiers: Revealing how Neural Networks Process Hierarchical Structure

    NARCIS (Netherlands)

    Veldhoen, S.; Hupkes, D.; Zuidema, W.

    2016-01-01

    We investigate how neural networks can be used for hierarchical, compositional semantics. To this end, we define the simple but nontrivial artificial task of processing nested arithmetic expressions and study whether different types of neural networks can learn to add and subtract. We find that

  19. Sustainable Process Design of Lignocellulose based Biofuel

    DEFF Research Database (Denmark)

    Mangnimit, Saranya; Malakul, Pomthong; Gani, Rafiqul

    the production and use of alternative and sustainable energy sources as rapidly as possible. Biofuel is a type of alternative energy that can be produced from many sources including sugar substances (such as sugarcane juice and molasses), starchy materials (such as corn and cassava), and lignocellulosic...... materials such as agricultural residual, straw and wood chips, the residual from wood industry. However, those sugar and starchy materials can be used not only to make biofuels but they are also food sources. Thus, lignocellulosic materials are interesting feed-stocls as they are inexpensive, abundantly...... available, and are also non-food crops. In this respect, Cassava rhizome has several characteristics that make it a potential feedstock for fuel ethanol production. It has high content of cellulose and hemicelluloses . The objective of this paper is to present a study focused on the sustainable process...

  20. Neurotrophin gene therapy for sustained neural preservation after deafness.

    Science.gov (United States)

    Atkinson, Patrick J; Wise, Andrew K; Flynn, Brianna O; Nayagam, Bryony A; Hume, Clifford R; O'Leary, Stephen J; Shepherd, Robert K; Richardson, Rachael T

    2012-01-01

    The cochlear implant provides auditory cues to profoundly deaf patients by electrically stimulating the residual spiral ganglion neurons. These neurons, however, undergo progressive degeneration after hearing loss, marked initially by peripheral fibre retraction and ultimately culminating in cell death. This research aims to use gene therapy techniques to both hold and reverse this degeneration by providing a sustained and localised source of neurotrophins to the deafened cochlea. Adenoviral vectors containing green fluorescent protein, with or without neurotrophin-3 and brain derived neurotrophic factor, were injected into the lower basal turn of scala media of guinea pigs ototoxically deafened one week prior to intervention. This single injection resulted in localised and sustained gene expression, principally in the supporting cells within the organ of Corti. Guinea pigs treated with adenoviral neurotrophin-gene therapy had greater neuronal survival compared to contralateral non-treated cochleae when examined at 7 and 11 weeks post injection. Moreover; there was evidence of directed peripheral fibre regrowth towards cells expressing neurotrophin genes after both treatment periods. These data suggest that neurotrophin-gene therapy can provide sustained protection of spiral ganglion neurons and peripheral fibres after hearing loss.

  1. USAF Logistics Process Optimization Study for the Aircraft Asset Sustainment Process. Volume 3. Future to be Asset Sustainment Process Model

    National Research Council Canada - National Science Library

    Adamson, Anthony

    1998-01-01

    .... It is published as three separate volumes. Volume I, USAF Logistics Process Optimization Study for the Aircraft Asset Sustainment Process -- Phase II Report, discusses the result and cost/benefit analysis of testing three initiatives...

  2. Doubly stochastic Poisson processes in artificial neural learning.

    Science.gov (United States)

    Card, H C

    1998-01-01

    This paper investigates neuron activation statistics in artificial neural networks employing stochastic arithmetic. It is shown that a doubly stochastic Poisson process is an appropriate model for the signals in these circuits.

  3. The Impact of Corporate Sustainability on Organizational Processes and Performance

    OpenAIRE

    Eccles, Robert G; Ioannou, Ioannis; Serafeim, Georgios

    2014-01-01

    We investigate the effect of corporate sustainability on organizational processes and performance. Using a matched sample of 180 US companies, we find that corporations that voluntarily adopted sustainability policies by 1993 - termed as High Sustainability companies - exhibit by 2009 distinct organizational processes compared to a matched sample of companies that adopted almost none of these policies - termed as Low Sustainability companies. The boards of directors of High Sustainability com...

  4. Hybrid digital signal processing and neural networks applications in PWRs

    International Nuclear Information System (INIS)

    Eryurek, E.; Upadhyaya, B.R.; Kavaklioglu, K.

    1991-01-01

    Signal validation and plant subsystem tracking in power and process industries require the prediction of one or more state variables. Both heteroassociative and auotassociative neural networks were applied for characterizing relationships among sets of signals. A multi-layer neural network paradigm was applied for sensor and process monitoring in a Pressurized Water Reactor (PWR). This nonlinear interpolation technique was found to be very effective for these applications

  5. Precision Scaling of Neural Networks for Efficient Audio Processing

    OpenAIRE

    Ko, Jong Hwan; Fromm, Josh; Philipose, Matthai; Tashev, Ivan; Zarar, Shuayb

    2017-01-01

    While deep neural networks have shown powerful performance in many audio applications, their large computation and memory demand has been a challenge for real-time processing. In this paper, we study the impact of scaling the precision of neural networks on the performance of two common audio processing tasks, namely, voice-activity detection and single-channel speech enhancement. We determine the optimal pair of weight/neuron bit precision by exploring its impact on both the performance and ...

  6. Designing neural networks that process mean values of random variables

    International Nuclear Information System (INIS)

    Barber, Michael J.; Clark, John W.

    2014-01-01

    We develop a class of neural networks derived from probabilistic models posed in the form of Bayesian networks. Making biologically and technically plausible assumptions about the nature of the probabilistic models to be represented in the networks, we derive neural networks exhibiting standard dynamics that require no training to determine the synaptic weights, that perform accurate calculation of the mean values of the relevant random variables, that can pool multiple sources of evidence, and that deal appropriately with ambivalent, inconsistent, or contradictory evidence. - Highlights: • High-level neural computations are specified by Bayesian belief networks of random variables. • Probability densities of random variables are encoded in activities of populations of neurons. • Top-down algorithm generates specific neural network implementation of given computation. • Resulting “neural belief networks” process mean values of random variables. • Such networks pool multiple sources of evidence and deal properly with inconsistent evidence

  7. Designing neural networks that process mean values of random variables

    Energy Technology Data Exchange (ETDEWEB)

    Barber, Michael J. [AIT Austrian Institute of Technology, Innovation Systems Department, 1220 Vienna (Austria); Clark, John W. [Department of Physics and McDonnell Center for the Space Sciences, Washington University, St. Louis, MO 63130 (United States); Centro de Ciências Matemáticas, Universidade de Madeira, 9000-390 Funchal (Portugal)

    2014-06-13

    We develop a class of neural networks derived from probabilistic models posed in the form of Bayesian networks. Making biologically and technically plausible assumptions about the nature of the probabilistic models to be represented in the networks, we derive neural networks exhibiting standard dynamics that require no training to determine the synaptic weights, that perform accurate calculation of the mean values of the relevant random variables, that can pool multiple sources of evidence, and that deal appropriately with ambivalent, inconsistent, or contradictory evidence. - Highlights: • High-level neural computations are specified by Bayesian belief networks of random variables. • Probability densities of random variables are encoded in activities of populations of neurons. • Top-down algorithm generates specific neural network implementation of given computation. • Resulting “neural belief networks” process mean values of random variables. • Such networks pool multiple sources of evidence and deal properly with inconsistent evidence.

  8. Sustainable process design & analysis of hybrid separations

    DEFF Research Database (Denmark)

    Kumar Tula, Anjan; Befort, Bridgette; Garg, Nipun

    2016-01-01

    Distillation is an energy intensive operation in chemical process industries. There are around 40,000 distillation columns in operation in the US, requiring approximately 40% of the total energy consumption in US chemical process industries. However, analysis of separations by distillation has...... shown that more than 50% of energy is spent in purifying the last 5-10% of the distillate product. Membrane modules on the other hand can achieve high purity separations at lower energy costs, but if the flux is high, it requires large membrane area. A hybrid scheme where distillation and membrane...... modules are combined such that each operates at its highest efficiency, has the potential for significant energy reduction without significant increase of capital costs. This paper presents a method for sustainable design of hybrid distillation-membrane schemes with guaranteed reduction of energy...

  9. Neural Language Processing in Adolescent First-Language Learners: Longitudinal Case Studies in American Sign Language.

    Science.gov (United States)

    Ferjan Ramirez, Naja; Leonard, Matthew K; Davenport, Tristan S; Torres, Christina; Halgren, Eric; Mayberry, Rachel I

    2016-03-01

    One key question in neurolinguistics is the extent to which the neural processing system for language requires linguistic experience during early life to develop fully. We conducted a longitudinal anatomically constrained magnetoencephalography (aMEG) analysis of lexico-semantic processing in 2 deaf adolescents who had no sustained language input until 14 years of age, when they became fully immersed in American Sign Language. After 2 to 3 years of language, the adolescents' neural responses to signed words were highly atypical, localizing mainly to right dorsal frontoparietal regions and often responding more strongly to semantically primed words (Ferjan Ramirez N, Leonard MK, Torres C, Hatrak M, Halgren E, Mayberry RI. 2014. Neural language processing in adolescent first-language learners. Cereb Cortex. 24 (10): 2772-2783). Here, we show that after an additional 15 months of language experience, the adolescents' neural responses remained atypical in terms of polarity. While their responses to less familiar signed words still showed atypical localization patterns, the localization of responses to highly familiar signed words became more concentrated in the left perisylvian language network. Our findings suggest that the timing of language experience affects the organization of neural language processing; however, even in adolescence, language representation in the human brain continues to evolve with experience. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  10. Neural Correlates of Processing Negative and Sexually Arousing Pictures

    Science.gov (United States)

    Bailey, Kira; West, Robert; Mullaney, Kellie M.

    2012-01-01

    Recent work has questioned whether the negativity bias is a distinct component of affective picture processing. The current study was designed to determine whether there are different neural correlates of processing positive and negative pictures using event-related brain potentials. The early posterior negativity and late positive potential were greatest in amplitude for erotic pictures. Partial Least Squares analysis revealed one latent variable that distinguished erotic pictures from neutral and positive pictures and another that differentiated negative pictures from neutral and positive pictures. The effects of orienting task on the neural correlates of processing negative and erotic pictures indicate that affective picture processing is sensitive to both stimulus-driven, and attentional or decision processes. The current data, together with other recent findings from our laboratory, lead to the suggestion that there are distinct neural correlates of processing negative and positive stimuli during affective picture processing. PMID:23029071

  11. Optimization of blanking process using neural network simulation

    International Nuclear Information System (INIS)

    Hambli, R.

    2005-01-01

    The present work describes a methodology using the finite element method and neural network simulation in order to predict the optimum punch-die clearance during sheet metal blanking processes. A damage model is used in order to describe crack initiation and propagation into the sheet. The proposed approach combines predictive finite element and neural network modeling of the leading blanking parameters. Numerical results obtained by finite element computation including damage and fracture modeling were utilized to train the developed simulation environment based on back propagation neural network modeling. The comparative study between the numerical results and the experimental ones shows the good agreement. (author)

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

    International Nuclear Information System (INIS)

    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.)

  13. The Sustainable Development Assessment of Reservoir Resettlement Based on a BP Neural Network.

    Science.gov (United States)

    Huang, Li; Huang, Jian; Wang, Wei

    2018-01-18

    Resettlement affects not only the resettlers' production activities and life but also, directly or indirectly, the normal operation of power stations, the sustainable development of the resettlers, and regional social stability. Therefore, a scientific evaluation index system for the sustainable development of reservoir resettlement must be established that fits Chinese national conditions and not only promotes reservoir resettlement research but also improves resettlement practice. This essay builds an evaluation index system for resettlers' sustainable development based on a back-propagation (BP) neural network, which can be adopted in China, taking the resettlement necessitated by step hydropower stations along the Wujiang River cascade as an example. The assessment results show that the resettlement caused by step power stations along the Wujiang River is sustainable, and this evaluation supports the conclusion that national policies and regulations, which are undergoing constant improvement, and resettlement has increasingly improved. The results provide a reference for hydropower reservoir resettlement in developing countries.

  14. The Sustainable Development Assessment of Reservoir Resettlement Based on a BP Neural Network

    Science.gov (United States)

    Huang, Li; Huang, Jian

    2018-01-01

    Resettlement affects not only the resettlers’ production activities and life but also, directly or indirectly, the normal operation of power stations, the sustainable development of the resettlers, and regional social stability. Therefore, a scientific evaluation index system for the sustainable development of reservoir resettlement must be established that fits Chinese national conditions and not only promotes reservoir resettlement research but also improves resettlement practice. This essay builds an evaluation index system for resettlers’ sustainable development based on a back-propagation (BP) neural network, which can be adopted in China, taking the resettlement necessitated by step hydropower stations along the Wujiang River cascade as an example. The assessment results show that the resettlement caused by step power stations along the Wujiang River is sustainable, and this evaluation supports the conclusion that national policies and regulations, which are undergoing constant improvement, and resettlement has increasingly improved. The results provide a reference for hydropower reservoir resettlement in developing countries. PMID:29346305

  15. The Sustainable Development Assessment of Reservoir Resettlement Based on a BP Neural Network

    Directory of Open Access Journals (Sweden)

    Li Huang

    2018-01-01

    Full Text Available Resettlement affects not only the resettlers’ production activities and life but also, directly or indirectly, the normal operation of power stations, the sustainable development of the resettlers, and regional social stability. Therefore, a scientific evaluation index system for the sustainable development of reservoir resettlement must be established that fits Chinese national conditions and not only promotes reservoir resettlement research but also improves resettlement practice. This essay builds an evaluation index system for resettlers’ sustainable development based on a back-propagation (BP neural network, which can be adopted in China, taking the resettlement necessitated by step hydropower stations along the Wujiang River cascade as an example. The assessment results show that the resettlement caused by step power stations along the Wujiang River is sustainable, and this evaluation supports the conclusion that national policies and regulations, which are undergoing constant improvement, and resettlement has increasingly improved. The results provide a reference for hydropower reservoir resettlement in developing countries.

  16. Explicit versus implicit neural processing of musical emotions

    OpenAIRE

    Bogert, Brigitte; Numminen-Kontti, Taru; Gold, Benjamin; Sams, Mikko; Numminen, Jussi; Burunat, Iballa; Lampinen, Jouko; Brattico, Elvira

    2016-01-01

    Music is often used to regulate emotions and mood. Typically, music conveys and induces emotions even when one does not attend to them. Studies on the neural substrates of musical emotions have, however, only examined brain activity when subjects have focused on the emotional content of the music. Here we address with functional magnetic resonance imaging (fMRI) the neural processing of happy, sad, and fearful music with a paradigm in which 56 subjects were instructed to either classify the e...

  17. Nonlinear signal processing using neural networks: Prediction and system modelling

    Energy Technology Data Exchange (ETDEWEB)

    Lapedes, A.; Farber, R.

    1987-06-01

    The backpropagation learning algorithm for neural networks is developed into a formalism for nonlinear signal processing. We illustrate the method by selecting two common topics in signal processing, prediction and system modelling, and show that nonlinear applications can be handled extremely well by using neural networks. The formalism is a natural, nonlinear extension of the linear Least Mean Squares algorithm commonly used in adaptive signal processing. Simulations are presented that document the additional performance achieved by using nonlinear neural networks. First, we demonstrate that the formalism may be used to predict points in a highly chaotic time series with orders of magnitude increase in accuracy over conventional methods including the Linear Predictive Method and the Gabor-Volterra-Weiner Polynomial Method. Deterministic chaos is thought to be involved in many physical situations including the onset of turbulence in fluids, chemical reactions and plasma physics. Secondly, we demonstrate the use of the formalism in nonlinear system modelling by providing a graphic example in which it is clear that the neural network has accurately modelled the nonlinear transfer function. It is interesting to note that the formalism provides explicit, analytic, global, approximations to the nonlinear maps underlying the various time series. Furthermore, the neural net seems to be extremely parsimonious in its requirements for data points from the time series. We show that the neural net is able to perform well because it globally approximates the relevant maps by performing a kind of generalized mode decomposition of the maps. 24 refs., 13 figs.

  18. Using GREENSCOPE for Sustainable Process Design: An Educational Opportunity

    Science.gov (United States)

    Increasing sustainability can be approached through the education of those who design, construct, and operate facilities. As chemical engineers learn elements of process systems engineering, they can be introduced to sustainability concepts. The EPA’s GREENSCOPE methodology and...

  19. Innovation process and needs of sustainability driven small firms

    NARCIS (Netherlands)

    Molenaar, N.; Keskin, D.; Diehl, J.C.; Lauche, K.

    2010-01-01

    Traditional approaches to sustainable consumption and production emphasized addressing issues related to the natural environment and sustainability through optimizing existing products, processes and businesses. Even though the conventional wisdom suggests that young and new firms have greater

  20. Purposes, People and Processes in Leadership for Sustainability

    OpenAIRE

    KLÖFVER, ANNA

    2015-01-01

    Leadership is recognized as a crucial element for successfully introducing, implementing andinstitutionalizing change for sustainability. However, it is unclear which purposes, people and processes, regarded as core components of leadership, drive sustainability and how they do it.The objective of this thesis is to investigate how organizational leadership for sustainability can be conceptualized in terms of purposes, people and processes driving sustainability. Addressed research questions a...

  1. Linking Neural and Symbolic Representation and Processing of Conceptual Structures

    Directory of Open Access Journals (Sweden)

    Frank van der Velde

    2017-08-01

    Full Text Available We compare and discuss representations in two cognitive architectures aimed at representing and processing complex conceptual (sentence-like structures. First is the Neural Blackboard Architecture (NBA, which aims to account for representation and processing of complex and combinatorial conceptual structures in the brain. Second is IDyOT (Information Dynamics of Thinking, which derives sentence-like structures by learning statistical sequential regularities over a suitable corpus. Although IDyOT is designed at a level more abstract than the neural, so it is a model of cognitive function, rather than neural processing, there are strong similarities between the composite structures developed in IDyOT and the NBA. We hypothesize that these similarities form the basis of a combined architecture in which the individual strengths of each architecture are integrated. We outline and discuss the characteristics of this combined architecture, emphasizing the representation and processing of conceptual structures.

  2. High level cognitive information processing in neural networks

    Science.gov (United States)

    Barnden, John A.; Fields, Christopher A.

    1992-01-01

    Two related research efforts were addressed: (1) high-level connectionist cognitive modeling; and (2) local neural circuit modeling. The goals of the first effort were to develop connectionist models of high-level cognitive processes such as problem solving or natural language understanding, and to understand the computational requirements of such models. The goals of the second effort were to develop biologically-realistic model of local neural circuits, and to understand the computational behavior of such models. In keeping with the nature of NASA's Innovative Research Program, all the work conducted under the grant was highly innovative. For instance, the following ideas, all summarized, are contributions to the study of connectionist/neural networks: (1) the temporal-winner-take-all, relative-position encoding, and pattern-similarity association techniques; (2) the importation of logical combinators into connection; (3) the use of analogy-based reasoning as a bridge across the gap between the traditional symbolic paradigm and the connectionist paradigm; and (4) the application of connectionism to the domain of belief representation/reasoning. The work on local neural circuit modeling also departs significantly from the work of related researchers. In particular, its concentration on low-level neural phenomena that could support high-level cognitive processing is unusual within the area of biological local circuit modeling, and also serves to expand the horizons of the artificial neural net field.

  3. Analysis of the Growth Process of Neural Cells in Culture Environment Using Image Processing Techniques

    Science.gov (United States)

    Mirsafianf, Atefeh S.; Isfahani, Shirin N.; Kasaei, Shohreh; Mobasheri, Hamid

    Here we present an approach for processing neural cells images to analyze their growth process in culture environment. We have applied several image processing techniques for: 1- Environmental noise reduction, 2- Neural cells segmentation, 3- Neural cells classification based on their dendrites' growth conditions, and 4- neurons' features Extraction and measurement (e.g., like cell body area, number of dendrites, axon's length, and so on). Due to the large amount of noise in the images, we have used feed forward artificial neural networks to detect edges more precisely.

  4. Sustainability Reporting Process Model using Business Intelligence

    OpenAIRE

    Alxneit, Thorsten Julius

    2015-01-01

    Sustainability including the reporting requirements is one of the most relevant topics for companies. In recent years, many software providers have launched new software tools targeting companies committed to implementing sustainability reporting. But it’s not only companies willing to use their Business Intelligence (BI) solution, there are also basic principles such as the single source of truth and tendencies to combine sustainability reporting with the financial reporting (...

  5. Neural correlates of successful semantic processing during propofol sedation

    NARCIS (Netherlands)

    Adapa, Ram M.; Davis, Matthew H.; Stamatakis, Emmanuel A.; Absalom, Anthony R.; Menon, David K.

    Sedation has a graded effect on brain responses to auditory stimuli: perceptual processing persists at sedation levels that attenuate more complex processing. We used fMRI in healthy volunteers sedated with propofol to assess changes in neural responses to spoken stimuli. Volunteers were scanned

  6. A fuzzy art neural network based color image processing and ...

    African Journals Online (AJOL)

    To improve the learning process from the input data, a new learning rule was suggested. In this paper, a new method is proposed to deal with the RGB color image pixels, which enables a Fuzzy ART neural network to process the RGB color images. The application of the algorithm was implemented and tested on a set of ...

  7. Integrating Sustainability into the Real Estate Valuation Process: A ...

    African Journals Online (AJOL)

    This paper sought the perception of Nigerian real estate valuers on sustainable development and how sustainability can be integrated into the real estate valuation process in Nigeria. One hundred and sixty Estate Surveyors and Valuers were asked, among others, to rate the significance of a range of sustainability features ...

  8. Sustainability Analysis and Market Demand Estimation in the Retail Industry through a Convolutional Neural Network

    Directory of Open Access Journals (Sweden)

    Luyao Wang

    2018-05-01

    Full Text Available The Chinese retail industry is expected to grow dramatically over the next few years, owing to the rapid increase in purchasing power of Chinese consumers. Retail managers should analyze the market demands and avoid dull sales to promote the sustainable development of the retail industry. Economic sustainability in the retail industry, which refers to a suitable return of investment, requires the implementation of precise product allocation strategies in different regions. This study proposed a hybrid model to evaluate economic sustainability in the preparation of goods of retail shops on the basis of market demand evaluation. Through a grid-based convolutional neural network, a regression model was first established to model the relationship between consumer distribution and the potential market demand. Then, another model was proposed to evaluate the sustainability among regions based on their supply-demand analysis. An experiment was conducted based on the actual sales data of retail shops in Guiyang, China. Results showed an immense diversity of sustainability in the entire city and three classes of regions were distinguished, namely, high, moderate, and limited. Our model was proven to be effective in the sustainability evaluation of supply and demand in the retail industry after validation showed that its accuracy reached 92.8%.

  9. Forests, environment, sustainable development and peace process

    International Nuclear Information System (INIS)

    Orozco Munoz, Jose Miguel

    1998-01-01

    The paper tries about the perspectives of the peace and the environment in the negotiation calendar with the armed groups and their thought about if the sustainable development is a common objective between the government and these groups

  10. Combinatorial structures and processing in neural blackboard architectures

    NARCIS (Netherlands)

    van der Velde, Frank; van der Velde, Frank; de Kamps, Marc; Besold, Tarek R.; d'Avila Garcez, Artur; Marcus, Gary F.; Miikkulainen, Risto

    2015-01-01

    We discuss and illustrate Neural Blackboard Architectures (NBAs) as the basis for variable binding and combinatorial processing the brain. We focus on the NBA for sentence structure. NBAs are based on the notion that conceptual representations are in situ, hence cannot be copied or transported.

  11. Recurrent Artificial Neural Networks and Finite State Natural Language Processing.

    Science.gov (United States)

    Moisl, Hermann

    It is argued that pessimistic assessments of the adequacy of artificial neural networks (ANNs) for natural language processing (NLP) on the grounds that they have a finite state architecture are unjustified, and that their adequacy in this regard is an empirical issue. First, arguments that counter standard objections to finite state NLP on the…

  12. Music Signal Processing Using Vector Product Neural Networks

    Science.gov (United States)

    Fan, Z. C.; Chan, T. S.; Yang, Y. H.; Jang, J. S. R.

    2017-05-01

    We propose a novel neural network model for music signal processing using vector product neurons and dimensionality transformations. Here, the inputs are first mapped from real values into three-dimensional vectors then fed into a three-dimensional vector product neural network where the inputs, outputs, and weights are all three-dimensional values. Next, the final outputs are mapped back to the reals. Two methods for dimensionality transformation are proposed, one via context windows and the other via spectral coloring. Experimental results on the iKala dataset for blind singing voice separation confirm the efficacy of our model.

  13. A new neural framework for visuospatial processing.

    Science.gov (United States)

    Kravitz, Dwight J; Saleem, Kadharbatcha S; Baker, Chris I; Mishkin, Mortimer

    2011-04-01

    The division of cortical visual processing into distinct dorsal and ventral streams is a key framework that has guided visual neuroscience. The characterization of the ventral stream as a 'What' pathway is relatively uncontroversial, but the nature of dorsal stream processing is less clear. Originally proposed as mediating spatial perception ('Where'), more recent accounts suggest it primarily serves non-conscious visually guided action ('How'). Here, we identify three pathways emerging from the dorsal stream that consist of projections to the prefrontal and premotor cortices, and a major projection to the medial temporal lobe that courses both directly and indirectly through the posterior cingulate and retrosplenial cortices. These three pathways support both conscious and non-conscious visuospatial processing, including spatial working memory, visually guided action and navigation, respectively.

  14. Is Sustainable Remediation Now a Self-Sustaining Process? an International Progress Report

    Science.gov (United States)

    Smith, J. W. N.

    2014-12-01

    Sustainable remediation - the consideration of environmental, social and economic factors associated with soil and groundwater risk-management options, to help select the best overall solution - has been a rapidly evolving topic in recent years. The first published reference[1] to 'sustainable remediation' was in the title of a 1999 conference paper by Kearney et al., (1999), but activity really accelerated in the middle-late 2000's, with establishment of a number of collaborative sustainable remediation groups and fora, and increased publication rates in the peer reviewed literature (Fig 1). Figure 1. Journal paper publications with search term 'sustainable remediation' (SCOPUS survey, 17 July 2014) This presentation will review the international progress of sustainable remediation concept development and application in regulatory and corporate decision-making processes. It will look back at what has already been achieved, provide an update on the latest initiatives and developments, and look forward to what the future of sustainable remediation might look like. Specifically it will describe: Sustainable remediation frameworks: synergies and international collaboration; Latest guidance and tools developed by the various sustainable remediation organisations (SuRFs), including the SuRF-UK Best Management Practices and Tier 1 Briefcase; Best practice standard development by ASTM and ISO; Regulatory acceptance of sustainable remediation, including incorporation into legislation, and the NICOLE - Common Forum Joint statement on 'risk-informed and sustainable remediation' in Europe; Examples of corporate adoption of sustainable remediation principles. The presentation will conclude with a look forward to a vision of sustainable remediation in 2020.

  15. Neural correlates of processing "self-conscious" vs. "basic" emotions.

    Science.gov (United States)

    Gilead, Michael; Katzir, Maayan; Eyal, Tal; Liberman, Nira

    2016-01-29

    Self-conscious emotions are prevalent in our daily lives and play an important role in both normal and pathological behavior. Despite their immense significance, the neural substrates that are involved in the processing of such emotions are surprisingly under-studied. In light of this, we conducted an fMRI study in which participants thought of various personal events which elicited feelings of negative and positive self-conscious (i.e., guilt, pride) or basic (i.e., anger, joy) emotions. We performed a conjunction analysis to investigate the neural correlates associated with processing events that are related to self-conscious vs. basic emotions, irrespective of valence. The results show that processing self-conscious emotions resulted in activation within frontal areas associated with self-processing and self-control, namely, the mPFC extending to the dACC, and within the lateral-dorsal prefrontal cortex. Processing basic emotions resulted in activation throughout relatively phylogenetically-ancient regions of the cortex, namely in visual and tactile processing areas and in the insular cortex. Furthermore, self-conscious emotions differentially activated the mPFC such that the negative self-conscious emotion (guilt) was associated with a more dorsal activation, and the positive self-conscious emotion (pride) was associated with a more ventral activation. We discuss how these results shed light on the nature of mental representations and neural systems involved in self-reflective and affective processing. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

    DEFF Research Database (Denmark)

    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...

  17. Adaptive Moving Object Tracking Integrating Neural Networks And Intelligent Processing

    Science.gov (United States)

    Lee, James S. J.; Nguyen, Dziem D.; Lin, C.

    1989-03-01

    A real-time adaptive scheme is introduced to detect and track moving objects under noisy, dynamic conditions including moving sensors. This approach integrates the adaptiveness and incremental learning characteristics of neural networks with intelligent reasoning and process control. Spatiotemporal filtering is used to detect and analyze motion, exploiting the speed and accuracy of multiresolution processing. A neural network algorithm constitutes the basic computational structure for classification. A recognition and learning controller guides the on-line training of the network, and invokes pattern recognition to determine processing parameters dynamically and to verify detection results. A tracking controller acts as the central control unit, so that tracking goals direct the over-all system. Performance is benchmarked against the Widrow-Hoff algorithm, for target detection scenarios presented in diverse FLIR image sequences. Efficient algorithm design ensures that this recognition and control scheme, implemented in software and commercially available image processing hardware, meets the real-time requirements of tracking applications.

  18. Psychological Processing in Chronic Pain: A Neural Systems Approach

    OpenAIRE

    Simons, Laura; Elman, Igor; Borsook, David

    2013-01-01

    Our understanding of chronic pain involves complex brain circuits that include sensory, emotional, cognitive and interoceptive processing. The feed-forward interactions between physical (e.g., trauma) and emotional pain and the consequences of altered psychological status on the expression of pain have made the evaluation and treatment of chronic pain a challenge in the clinic. By understanding the neural circuits involved in psychological processes, a mechanistic approach to the implementati...

  19. Neural Correlates of Automatic and Controlled Auditory Processing in Schizophrenia

    Science.gov (United States)

    Morey, Rajendra A.; Mitchell, Teresa V.; Inan, Seniha; Lieberman, Jeffrey A.; Belger, Aysenil

    2009-01-01

    Individuals with schizophrenia demonstrate impairments in selective attention and sensory processing. The authors assessed differences in brain function between 26 participants with schizophrenia and 17 comparison subjects engaged in automatic (unattended) and controlled (attended) auditory information processing using event-related functional MRI. Lower regional neural activation during automatic auditory processing in the schizophrenia group was not confined to just the temporal lobe, but also extended to prefrontal regions. Controlled auditory processing was associated with a distributed frontotemporal and subcortical dysfunction. Differences in activation between these two modes of auditory information processing were more pronounced in the comparison group than in the patient group. PMID:19196926

  20. Development of Chemical Process Design and Control for Sustainability

    Science.gov (United States)

    This contribution describes a novel process systems engineering framework that couples advanced control with sustainability evaluation and decision making for the optimization of process operations to minimize environmental impacts associated with products, materials, and energy....

  1. Modeling of an industrial drying process by artificial neural networks

    Directory of Open Access Journals (Sweden)

    E. Assidjo

    2008-09-01

    Full Text Available A suitable method is needed to solve the nonquality problem in the grated coconut industry due to the poor control of product humidity during the process. In this study the possibility of using an artificial neural network (ANN, precisely a Multilayer Perceptron, for modeling the drying step of the production of grated coconut process is highlighted. Drying must confer to the product a final moisture of 3%. Unfortunately, under industrial conditions, this moisture varies from 1.9 to 4.8 %. In order to control this parameter and consequently reduce the proportion of the product that does not meet the humidity specification, a 9-4-1 neural network architecture was established using data gathered from an industrial plant. This Multilayer Perceptron can satisfactorily model the process with less bias, ranging from -0.35 to 0.34%, and can reduce the rate of rejected products from 92% to 3% during the first cycle of drying.

  2. Neural mechanisms of order information processing in working memory

    Directory of Open Access Journals (Sweden)

    Barbara Dolenc

    2013-11-01

    Full Text Available The ability to encode and maintain the exact order of short sequences of stimuli or events is often crucial to our ability for effective high-order planning. However, it is not yet clear which neural mechanisms underpin this process. Several studies suggest that in comparison with item recognition temporal order coding activates prefrontal and parietal brain regions. Results of various studies tend to favour the hypothesis that the order of the stimuli is represented and encoded on several stages, from primacy and recency estimates to the exact position of the item in a sequence. Different brain regions play a different role in this process. Dorsolateral prefrontal cortex has a more general role in attention, while the premotor cortex is more involved in the process of information grouping. Parietal lobe and hippocampus also play a significant role in order processing as they enable the representation of distance. Moreover, order maintenance is associated with the existence of neural oscillators that operate at different frequencies. Electrophysiological studies revealed that theta and alpha oscillations play an important role in the maintenance of temporal order information. Those EEG oscillations are differentially associated with processes that support the maintenance of order information and item recognition. Various studies suggest a link between prefrontal areas and memory for temporal order, implying that EEG neural oscillations in the prefrontal cortex may play a role in the maintenance of information on temporal order.

  3. Internal mechanisms underlying anticipatory language processing: Evidence from event-related-potentials and neural oscillations.

    Science.gov (United States)

    Li, Xiaoqing; Zhang, Yuping; Xia, Jinyan; Swaab, Tamara Y

    2017-07-28

    Although numerous studies have demonstrated that the language processing system can predict upcoming content during comprehension, there is still no clear picture of the anticipatory stage of predictive processing. This electroencephalograph study examined the cognitive and neural oscillatory mechanisms underlying anticipatory processing during language comprehension, and the consequences of this prediction for bottom-up processing of predicted/unpredicted content. Participants read Mandarin Chinese sentences that were either strongly or weakly constraining and that contained critical nouns that were congruent or incongruent with the sentence contexts. We examined the effects of semantic predictability on anticipatory processing prior to the onset of the critical nouns and on integration of the critical nouns. The results revealed that, at the integration stage, the strong-constraint condition (compared to the weak-constraint condition) elicited a reduced N400 and reduced theta activity (4-7Hz) for the congruent nouns, but induced beta (13-18Hz) and theta (4-7Hz) power decreases for the incongruent nouns, indicating benefits of confirmed predictions and potential costs of disconfirmed predictions. More importantly, at the anticipatory stage, the strongly constraining context elicited an enhanced sustained anterior negativity and beta power decrease (19-25Hz), which indicates that strong prediction places a higher processing load on the anticipatory stage of processing. The differences (in the ease of processing and the underlying neural oscillatory activities) between anticipatory and integration stages of lexical processing were discussed with regard to predictive processing models. Copyright © 2017 Elsevier Ltd. All rights reserved.

  4. The Sustainable Process Index. A new dimension in ecological evaluation

    International Nuclear Information System (INIS)

    Krotscheck, Christian; Narodoslawsky, Michael

    1996-01-01

    The Sustainable Process Index (SPI) is a measure developed to evaluate the viability of processes under sustainable economic conditions. Its advantages are its universal applicability, its scientific basis, the possibility of adoption in process analyses and syntheses, the high sensitivity for sustainable qualities, and the capability of aggregation to one measure. It has proved to be useful in industrial strategic planning. The concept of the SPI is based on the assumption that in a truly sustainable society the basis of economy is the sustainable flow of solar exergy. The conversion of the solar exergy to services needs area. Thus, area becomes the limiting factor of a sustainable economy. The SPI evaluates the areas needed to provide the raw materials and energy demands and to accommodate by-product flows from a process in a sustainable way. It relates these areas to the area available to a citizen in a given geographical (from regional to global) context. The data necessary to calculate the SPI are usually known at an early stage in process development. The result of the computation is the ratio between the area needed to supply a citizen with a given service and the area needed to supply a citizen with all possible services. Thus, it is a measure of the expense of this service in an economy oriented towards sustainability

  5. Neural processes underlying cultural differences in cognitive persistence.

    Science.gov (United States)

    Telzer, Eva H; Qu, Yang; Lin, Lynda C

    2017-08-01

    Self-improvement motivation, which occurs when individuals seek to improve upon their competence by gaining new knowledge and improving upon their skills, is critical for cognitive, social, and educational adjustment. While many studies have delineated the neural mechanisms supporting extrinsic motivation induced by monetary rewards, less work has examined the neural processes that support intrinsically motivated behaviors, such as self-improvement motivation. Because cultural groups traditionally vary in terms of their self-improvement motivation, we examined cultural differences in the behavioral and neural processes underlying motivated behaviors during cognitive persistence in the absence of extrinsic rewards. In Study 1, 71 American (47 females, M=19.68 years) and 68 Chinese (38 females, M=19.37 years) students completed a behavioral cognitive control task that required cognitive persistence across time. In Study 2, 14 American and 15 Chinese students completed the same cognitive persistence task during an fMRI scan. Across both studies, American students showed significant declines in cognitive performance across time, whereas Chinese participants demonstrated effective cognitive persistence. These behavioral effects were explained by cultural differences in self-improvement motivation and paralleled by increasing activation and functional coupling between the inferior frontal gyrus (IFG) and ventral striatum (VS) across the task among Chinese participants, neural activation and coupling that remained low in American participants. These findings suggest a potential neural mechanism by which the VS and IFG work in concert to promote cognitive persistence in the absence of extrinsic rewards. Thus, frontostriatal circuitry may be a neurobiological signal representing intrinsic motivation for self-improvement that serves an adaptive function, increasing Chinese students' motivation to engage in cognitive persistence. Copyright © 2017 Elsevier Inc. All rights

  6. Development of Chemical Process Design and Control for Sustainability

    Directory of Open Access Journals (Sweden)

    Shuyun Li

    2016-07-01

    Full Text Available This contribution describes a novel process systems engineering framework that couples advanced control with sustainability evaluation for the optimization of process operations to minimize environmental impacts associated with products, materials and energy. The implemented control strategy combines a biologically-inspired method with optimal control concepts for finding more sustainable operating trajectories. The sustainability assessment of process operating points is carried out by using the U.S. EPA’s Gauging Reaction Effectiveness for the ENvironmental Sustainability of Chemistries with a multi-Objective Process Evaluator (GREENSCOPE tool that provides scores for the selected indicators in the economic, material efficiency, environmental and energy areas. The indicator scores describe process performance on a sustainability measurement scale, effectively determining which operating point is more sustainable if there are more than several steady states for one specific product manufacturing. Through comparisons between a representative benchmark and the optimal steady states obtained through the implementation of the proposed controller, a systematic decision can be made in terms of whether the implementation of the controller is moving the process towards a more sustainable operation. The effectiveness of the proposed framework is illustrated through a case study of a continuous fermentation process for fuel production, whose material and energy time variation models are characterized by multiple steady states and oscillatory conditions.

  7. Sustainability assessment of shielded metal arc welding (SMAW) process

    Science.gov (United States)

    Alkahla, Ibrahim; Pervaiz, Salman

    2017-09-01

    Shielded metal arc welding (SMAW) process is one of the most commonly employed material joining processes utilized in the various industrial sectors such as marine, ship-building, automotive, aerospace, construction and petrochemicals etc. The increasing pressure on manufacturing sector wants the welding process to be sustainable in nature. The SMAW process incorporates several types of inputs and output streams. The sustainability concerns associated with SMAW process are linked with the various input and output streams such as electrical energy requirement, input material consumptions, slag formation, fumes emission and hazardous working conditions associated with the human health and occupational safety. To enhance the environmental performance of the SMAW welding process, there is a need to characterize the sustainability for the SMAW process under the broad framework of sustainability. Most of the available literature focuses on the technical and economic aspects of the welding process, however the environmental and social aspects are rarely addressed. The study reviews SMAW process with respect to the triple bottom line (economic, environmental and social) sustainability approach. Finally, the study concluded recommendations towards achieving economical and sustainable SMAW welding process.

  8. Reactor and process design in sustainable energy technology

    CERN Document Server

    Shi, Fan

    2014-01-01

    Reactor Process Design in Sustainable Energy Technology compiles and explains current developments in reactor and process design in sustainable energy technologies, including optimization and scale-up methodologies and numerical methods. Sustainable energy technologies that require more efficient means of converting and utilizing energy can help provide for burgeoning global energy demand while reducing anthropogenic carbon dioxide emissions associated with energy production. The book, contributed by an international team of academic and industry experts in the field, brings numerous reactor design cases to readers based on their valuable experience from lab R&D scale to industry levels. It is the first to emphasize reactor engineering in sustainable energy technology discussing design. It provides comprehensive tools and information to help engineers and energy professionals learn, design, and specify chemical reactors and processes confidently. Emphasis on reactor engineering in sustainable energy techn...

  9. Neural PID Control Strategy for Networked Process Control

    Directory of Open Access Journals (Sweden)

    Jianhua Zhang

    2013-01-01

    Full Text Available A new method with a two-layer hierarchy is presented based on a neural proportional-integral-derivative (PID iterative learning method over the communication network for the closed-loop automatic tuning of a PID controller. It can enhance the performance of the well-known simple PID feedback control loop in the local field when real networked process control applied to systems with uncertain factors, such as external disturbance or randomly delayed measurements. The proposed PID iterative learning method is implemented by backpropagation neural networks whose weights are updated via minimizing tracking error entropy of closed-loop systems. The convergence in the mean square sense is analysed for closed-loop networked control systems. To demonstrate the potential applications of the proposed strategies, a pressure-tank experiment is provided to show the usefulness and effectiveness of the proposed design method in network process control systems.

  10. Methods and tools for sustainable chemical process design

    DEFF Research Database (Denmark)

    Loureiro da Costa Lira Gargalo, Carina; Chairakwongsa, Siwanat; Quaglia, Alberto

    2015-01-01

    As the pressure on chemical and biochemical processes to achieve a more sustainable performance increases, the need to define a systematic and holistic way to accomplish this is becoming more urgent. In this chapter, a multilevel computer-aided framework for systematic design of more sustainable...

  11. Process for forming synapses in neural networks and resistor therefor

    Science.gov (United States)

    Fu, Chi Y.

    1996-01-01

    Customizable neural network in which one or more resistors form each synapse. All the resistors in the synaptic array are identical, thus simplifying the processing issues. Highly doped, amorphous silicon is used as the resistor material, to create extremely high resistances occupying very small spaces. Connected in series with each resistor in the array is at least one severable conductor whose uppermost layer has a lower reflectivity of laser energy than typical metal conductors at a desired laser wavelength.

  12. Sustainable and Intensified Design of a Biodiesel Production Process

    DEFF Research Database (Denmark)

    Mansouri, Seyed Soheil; Ismail, Muhammad I.; Babi, Deenesh Kavi

    impact and maximum profitability is needed. In this work a computer-aided framework for process synthesis and process intensification is applied for sustainable production of biodiesel from pure/waste palm oil as the feedstock. This approach examines several biodiesel processing routes that were...... collected through available data and current technologies reported in the literature. Using this information, a generic superstructure of processing routes was created that described a network of configurations representing multiple designs for the production of biodiesel. Therefore, based on the currently...... of economic and environmental sustainability was identified. For the case of biodiesel production, the intensified process alternative turned out to be the most economical and more sustainable than other alternatives. The computer-aided methods and tools used in this work are: SustainPro (method and tool...

  13. Process framework for identifying sustainability aspects in university curricula and integrating education for sustainable development

    DEFF Research Database (Denmark)

    Holm, Tove; Sammalisto, Kaisu; Grindsted, Thomas Skou

    2015-01-01

    Sustainability aspects in higher education must be enhanced with more concrete actions. Universities are globally required to have quality assurance to secure and improve teaching and learning, and they use management systems to this aim. Integrating education for sustainable development...... and management systems are alike in that they are based on continuous improvement and systematic thinking; for both processes all stakeholders need to be involved. Although quality assurance is compulsory for higher education, education for sustainable development has barely been examined or integrated...... in this context. This article examines how voluntary integration of education for sustainable development into management systems at universities could facilitate a scheme to overcome the challenges to integrating education for sustainable development that were identified in previous research. For this, a process...

  14. Sustainable development of gree solvent separation process

    OpenAIRE

    Lisickov, Kiril; Fidancevska, Emilija; Grujic, Radoslav; Srebrenkoska, Vineta; Kuvendziev, Stefan

    2011-01-01

    Solvents defi ne a major part of the environmental performance of processes in the chemical industry and impact on cost, safety and health issues. The idea of green solvents expresses the goal to minimize the environmental impact resulting from the use of solvents in chemical production. In spite of conventional separation methods, precise process green technologies are based on the application of modern processes and process equipment as well as control and management...

  15. Engaged listeners: shared neural processing of powerful political speeches.

    Science.gov (United States)

    Schmälzle, Ralf; Häcker, Frank E K; Honey, Christopher J; Hasson, Uri

    2015-08-01

    Powerful speeches can captivate audiences, whereas weaker speeches fail to engage their listeners. What is happening in the brains of a captivated audience? Here, we assess audience-wide functional brain dynamics during listening to speeches of varying rhetorical quality. The speeches were given by German politicians and evaluated as rhetorically powerful or weak. Listening to each of the speeches induced similar neural response time courses, as measured by inter-subject correlation analysis, in widespread brain regions involved in spoken language processing. Crucially, alignment of the time course across listeners was stronger for rhetorically powerful speeches, especially for bilateral regions of the superior temporal gyri and medial prefrontal cortex. Thus, during powerful speeches, listeners as a group are more coupled to each other, suggesting that powerful speeches are more potent in taking control of the listeners' brain responses. Weaker speeches were processed more heterogeneously, although they still prompted substantially correlated responses. These patterns of coupled neural responses bear resemblance to metaphors of resonance, which are often invoked in discussions of speech impact, and contribute to the literature on auditory attention under natural circumstances. Overall, this approach opens up possibilities for research on the neural mechanisms mediating the reception of entertaining or persuasive messages. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  16. Nonlinear identification of process dynamics using neural networks

    International Nuclear Information System (INIS)

    Parlos, A.G.; Atiya, A.F.; Chong, K.T.

    1992-01-01

    In this paper the nonlinear identification of process dynamics encountered in nuclear power plant components is addressed, in an input-output sense, using artificial neural systems. A hybrid feedforward/feedback neural network, namely, a recurrent multilayer perceptron, is used as the model structure to be identified. The feedforward portion of the network architecture provides its well-known interpolation property, while through recurrency and cross-talk, the local information feedback enables representation of temporal variations in the system nonlinearities. The standard backpropagation learning algorithm is modified, and it is used for the supervised training of the proposed hybrid network. The performance of recurrent multilayer perceptron networks in identifying process dynamics is investigated via the case study of a U-tube steam generator. The response of representative steam generator is predicted using a neural network, and it is compared to the response obtained from a sophisticated computer model based on first principles. The transient responses compare well, although further research is warranted to determine the predictive capabilities of these networks during more severe operational transients and accident scenarios

  17. Adaptive model predictive process control using neural networks

    Science.gov (United States)

    Buescher, K.L.; Baum, C.C.; Jones, R.D.

    1997-08-19

    A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may include difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data. 46 figs.

  18. Vicarious neural processing of outcomes during observational learning.

    Directory of Open Access Journals (Sweden)

    Elisabetta Monfardini

    Full Text Available Learning what behaviour is appropriate in a specific context by observing the actions of others and their outcomes is a key constituent of human cognition, because it saves time and energy and reduces exposure to potentially dangerous situations. Observational learning of associative rules relies on the ability to map the actions of others onto our own, process outcomes, and combine these sources of information. Here, we combined newly developed experimental tasks and functional magnetic resonance imaging (fMRI to investigate the neural mechanisms that govern such observational learning. Results show that the neural systems involved in individual trial-and-error learning and in action observation and execution both participate in observational learning. In addition, we identified brain areas that specifically activate for others' incorrect outcomes during learning in the posterior medial frontal cortex (pMFC, the anterior insula and the posterior superior temporal sulcus (pSTS.

  19. Vicarious neural processing of outcomes during observational learning.

    Science.gov (United States)

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

    2013-01-01

    Learning what behaviour is appropriate in a specific context by observing the actions of others and their outcomes is a key constituent of human cognition, because it saves time and energy and reduces exposure to potentially dangerous situations. Observational learning of associative rules relies on the ability to map the actions of others onto our own, process outcomes, and combine these sources of information. Here, we combined newly developed experimental tasks and functional magnetic resonance imaging (fMRI) to investigate the neural mechanisms that govern such observational learning. Results show that the neural systems involved in individual trial-and-error learning and in action observation and execution both participate in observational learning. In addition, we identified brain areas that specifically activate for others' incorrect outcomes during learning in the posterior medial frontal cortex (pMFC), the anterior insula and the posterior superior temporal sulcus (pSTS).

  20. Acute Stress Influences Neural Circuits of Reward Processing

    Directory of Open Access Journals (Sweden)

    Anthony John Porcelli

    2012-11-01

    Full Text Available People often make decisions under aversive conditions such as acute stress. Yet, less is known about the process in which acute stress can influence decision-making. A growing body of research has established that reward-related information associated with the outcomes of decisions exerts a powerful influence over the choices people make and that an extensive network of brain regions, prominently featuring the striatum, is involved in the processing of this reward-related information. Thus, an important step in research on the nature of acute stress’ influence over decision-making is to examine how it may modulate responses to rewards and punishments within reward-processing neural circuitry. In the current experiment, we employed a simple reward processing paradigm – where participants received monetary rewards and punishments – known to evoke robust striatal responses. Immediately prior to performing each of two task runs, participants were exposed to acute stress (i.e., cold pressor or a no stress control procedure in a between-subjects fashion. No stress group participants exhibited a pattern of activity within the dorsal striatum and orbitofrontal cortex consistent with past research on outcome processing – specifically, differential responses for monetary rewards over punishments. In contrast, acute stress group participants’ dorsal striatum and orbitofrontal cortex demonstrated decreased sensitivity to monetary outcomes and a lack of differential activity. These findings provide insight into how neural circuits may process rewards and punishments associated with simple decisions under acutely stressful conditions.

  1. Using Dual Process Models to Examine Impulsivity Throughout Neural Maturation.

    Science.gov (United States)

    Leshem, Rotem

    2016-01-01

    The multivariate construct of impulsivity is examined through neural systems and connections that comprise the executive functioning system. It is proposed that cognitive and behavioral components of impulsivity can be divided into two distinct groups, mediated by (1) the cognitive control system: deficits in top-down cognitive control processes referred to as action/cognitive impulsivity and (2) the socioemotional system: related to bottom-up affective/motivational processes referred to as affective impulsivity. Examination of impulsivity from a developmental viewpoint can guide future research, potentially enabling the selection of more effective interventions for impulsive individuals, based on the cognitive components requiring improvement.

  2. Water retention in mushroom during sustainable processing

    NARCIS (Netherlands)

    Paudel, E.

    2015-01-01

    This thesis deals with the understanding of the water holding capacity of mushroom, in the context of a redesign of their industrial processing. For designing food process the retention of food quality is of the utmost importance. Water holding capacity is an important quality aspect of

  3. Sustainable processes synthesis for renewable resources

    International Nuclear Information System (INIS)

    Halasz, L.; Povoden, G.; Narodoslawsky, M.

    2005-01-01

    Renewable resources pose special challenges to process synthesis. Due to decentral raw material generation, usually low transport densities and the perishable character of most renewable raw materials in combination with their time dependent availability, logistical questions as well as adaptation to regional agricultural structures are necessary. This calls for synthesis of structures not only of single processes but of the whole value chain attached to the utilisation of a certain resource. As most of the innovative technologies proposed to build on a renewable raw material base face stiff economic competition from fossil based processes, economic optimality of the value chain is crucial to their implementation. On top of this widening of the process definition for synthesis, many processes on the base of renewable resources apply technologies (like membrane separations, chromatographic purification steps, etc.) for which the heuristic knowledge is still slim. This reduces the choice of methods for process synthesis, mainly to methods based on combinatorial principles. The paper investigates applicability as well as impact on technology development of process synthesis for renewable raw material utilisation. It takes logistic considerations into account and applies process synthesis to the case study of the green biorefinery concept. The results show the great potential of process synthesis for technology development of renewable resource utilisation. Applied early in the development phase, it can point towards the most promising utilisation pathways, thus guiding the engineering work. On top of that, and even more important, it can help avoid costly development flops as it also clearly indicates 'blind alleys' that have to be avoided

  4. Sustainable Process Design of Biofuels: Bioethanol Production from Cassava rhizome

    DEFF Research Database (Denmark)

    Mangnimit, S.; Malakul, P.; Gani, Rafiqul

    2013-01-01

    This study is focused on the sustainable process design of bioethanol production from cassava rhizome. The study includes: process simulation, sustainability analysis, economic evaluation and life cycle assessment (LCA). A steady state process simulation if performed to generate a base case design........ Also, simultaneously with sustainability analysis, the life cycle impact on environment associated with bioethanol production is performed. Finally, candidate alternative designs are generated and compared with the base case design in terms of LCA, economics, waste, energy usage and enviromental impact...... in order to identify the most sustainable design for the production of ethanol. The capacity for ethanol production from cassava rhizome is set to 150,000 liters/day, which is about 1.3 % of the total demand of ethanol in Thailand. LCA on the base case design pointed to large amounts of CO2 and CO...

  5. Sustainable Intensified Process Retrofit for the Production of MDI

    DEFF Research Database (Denmark)

    Babi, Deenesh Kavi; Woodley, John; Gani, Rafiqul

    Process intensification (PI) is a means by which processes can be made more efficient and sustainable at different levels, the unit operations, functional and phenomena levels. Therefore PI can be used for making process improvements at the functional level for the production of an important poly...... polyurethane, methylene diphenyldi-isocyanate (MDI)....

  6. Sustaining Operational Resiliency: A Process Improvement Approach to Security Management

    National Research Council Canada - National Science Library

    Caralli, Richard A

    2006-01-01

    .... Coordinating these efforts to sustain operational resiliency requires a process-oriented approach that can be defined, measured, and actively managed. This report describes the fundamental elements and benefits of a process approach to security and operational resiliency and provides a notional view of a framework for process improvement.

  7. Processing of chromatic information in a deep convolutional neural network.

    Science.gov (United States)

    Flachot, Alban; Gegenfurtner, Karl R

    2018-04-01

    Deep convolutional neural networks are a class of machine-learning algorithms capable of solving non-trivial tasks, such as object recognition, with human-like performance. Little is known about the exact computations that deep neural networks learn, and to what extent these computations are similar to the ones performed by the primate brain. Here, we investigate how color information is processed in the different layers of the AlexNet deep neural network, originally trained on object classification of over 1.2M images of objects in their natural contexts. We found that the color-responsive units in the first layer of AlexNet learned linear features and were broadly tuned to two directions in color space, analogously to what is known of color responsive cells in the primate thalamus. Moreover, these directions are decorrelated and lead to statistically efficient representations, similar to the cardinal directions of the second-stage color mechanisms in primates. We also found, in analogy to the early stages of the primate visual system, that chromatic and achromatic information were segregated in the early layers of the network. Units in the higher layers of AlexNet exhibit on average a lower responsivity for color than units at earlier stages.

  8. Neural Mechanisms and Information Processing in Recognition Systems

    Directory of Open Access Journals (Sweden)

    Mamiko Ozaki

    2014-10-01

    Full Text Available Nestmate recognition is a hallmark of social insects. It is based on the match/mismatch of an identity signal carried by members of the society with that of the perceiving individual. While the behavioral response, amicable or aggressive, is very clear, the neural systems underlying recognition are not fully understood. Here we contrast two alternative hypotheses for the neural mechanisms that are responsible for the perception and information processing in recognition. We focus on recognition via chemical signals, as the common modality in social insects. The first, classical, hypothesis states that upon perception of recognition cues by the sensory system the information is passed as is to the antennal lobes and to higher brain centers where the information is deciphered and compared to a neural template. Match or mismatch information is then transferred to some behavior-generating centers where the appropriate response is elicited. An alternative hypothesis, that of “pre-filter mechanism”, posits that the decision as to whether to pass on the information to the central nervous system takes place in the peripheral sensory system. We suggest that, through sensory adaptation, only alien signals are passed on to the brain, specifically to an “aggressive-behavior-switching center”, where the response is generated if the signal is above a certain threshold.

  9. An application of neural networks to process and materials control

    International Nuclear Information System (INIS)

    Howell, J.A.; Whiteson, R.

    1991-01-01

    Process control consists of two basic elements: a model of the process and knowledge of the desired control algorithm. In some cases the level of the control algorithm is merely supervisory, as in an alarm-reporting or anomaly-detection system. If the model of the process is known, then a set of equations may often be solved explicitly to provide the control algorithm. Otherwise, the model has to be discovered through empirical studies. Neural networks have properties that make them useful in this application. They can learn (make internal models from experience or observations). The problem of anomaly detection in materials control systems fits well into this general control framework. To successfully model a process with a neutral network, a good set of observables must be chosen. These observables must in some sense adequately span the space of representable events, so that a signature metric can be built for normal operation. In this way, a non-normal event, one that does not fit within the signature, can be detected. In this paper, we discuss the issues involved in applying a neural network model to anomaly detection in materials control systems. These issues include data selection and representation, network architecture, prediction of events, the use of simulated data, and software tools. 10 refs., 4 figs., 1 tab

  10. Neural processing of emotional-intensity predicts emotion regulation choice.

    Science.gov (United States)

    Shafir, Roni; Thiruchselvam, Ravi; Suri, Gaurav; Gross, James J; Sheppes, Gal

    2016-12-01

    Emotional-intensity is a core characteristic of affective events that strongly determines how individuals choose to regulate their emotions. Our conceptual framework suggests that in high emotional-intensity situations, individuals prefer to disengage attention using distraction, which can more effectively block highly potent emotional information, as compared with engagement reappraisal, which is preferred in low emotional-intensity. However, existing supporting evidence remains indirect because prior intensity categorization of emotional stimuli was based on subjective measures that are potentially biased and only represent the endpoint of emotional-intensity processing. Accordingly, this study provides the first direct evidence for the role of online emotional-intensity processing in predicting behavioral regulatory-choices. Utilizing the high temporal resolution of event-related potentials, we evaluated online neural processing of stimuli's emotional-intensity (late positive potential, LPP) prior to regulatory-choices between distraction and reappraisal. Results showed that enhanced neural processing of intensity (enhanced LPP amplitudes) uniquely predicted (above subjective measures of intensity) increased tendency to subsequently choose distraction over reappraisal. Additionally, regulatory-choices led to adaptive consequences, demonstrated in finding that actual implementation of distraction relative to reappraisal-choice resulted in stronger attenuation of LPPs and self-reported arousal. © The Author (2016). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  11. Forecasting financial asset processes: stochastic dynamics via learning neural networks.

    Science.gov (United States)

    Giebel, S; Rainer, M

    2010-01-01

    Models for financial asset dynamics usually take into account their inherent unpredictable nature by including a suitable stochastic component into their process. Unknown (forward) values of financial assets (at a given time in the future) are usually estimated as expectations of the stochastic asset under a suitable risk-neutral measure. This estimation requires the stochastic model to be calibrated to some history of sufficient length in the past. Apart from inherent limitations, due to the stochastic nature of the process, the predictive power is also limited by the simplifying assumptions of the common calibration methods, such as maximum likelihood estimation and regression methods, performed often without weights on the historic time series, or with static weights only. Here we propose a novel method of "intelligent" calibration, using learning neural networks in order to dynamically adapt the parameters of the stochastic model. Hence we have a stochastic process with time dependent parameters, the dynamics of the parameters being themselves learned continuously by a neural network. The back propagation in training the previous weights is limited to a certain memory length (in the examples we consider 10 previous business days), which is similar to the maximal time lag of autoregressive processes. We demonstrate the learning efficiency of the new algorithm by tracking the next-day forecasts for the EURTRY and EUR-HUF exchange rates each.

  12. Integration of life cycle assessment software with tools for economic and sustainability analyses and process simulation for sustainable process design

    DEFF Research Database (Denmark)

    Kalakul, Sawitree; Malakul, Pomthong; Siemanond, Kitipat

    2014-01-01

    The sustainable future of the world challenges engineers to develop chemical process designs that are not only technically and economically feasible but also environmental friendly. Life cycle assessment (LCA) is a tool for identifying and quantifying environmental impacts of the chemical product...... with other process design tools such as sustainable design (SustainPro), economic analysis (ECON) and process simulation. The software framework contains four main tools: Tool-I is for life cycle inventory (LCI) knowledge management that enables easy maintenance and future expansion of the LCI database; Tool...... and/or the process that makes it. It can be used in conjunction with process simulation and economic analysis tools to evaluate the design of any existing and/or new chemical-biochemical process and to propose improvement options in order to arrive at the best design among various alternatives...

  13. Neural markers of opposite-sex bias in face processing

    Directory of Open Access Journals (Sweden)

    Alice Mado eProverbio

    2010-10-01

    Full Text Available Some behavioral and neuroimaging studies suggest that adults prefer to view attractive faces of the opposite sex more than attractive faces of the same sex. However, unlike the other-race face effect (ORE; Caldara et al., 2004, little is known regarding the existence of an opposite-/same-sex bias in face processing. In this study, the faces of 130 attractive male and female adults were foveally presented to 40 heterosexual university students (20 men and 20 women who were engaged in a secondary perceptual task (landscape detection. The automatic processing of face gender was investigated by recording ERPs from 128 scalp sites. Neural markers of opposite- vs. same-sex bias in face processing included larger and earlier centro-parietal N400s in response to faces of the opposite sex and a larger late positivity (LP to same-sex faces. Analysis of intra-cortical neural generators (swLORETA showed that facial processing-related (FG, BA37, BA20/21 and emotion-related brain areas (the right parahippocampal gyrus, BA35; uncus, BA36/38; and the cingulate gyrus, BA24 had higher activations in response to opposite- than same-sex faces. The results of this analysis, along with data obtained from ERP recordings, support the hypothesis that both genders process opposite-sex faces differently than same-sex faces. The data also suggest a hemispheric asymmetry in the processing of opposite-/same-sex faces, with the right hemisphere involved in processing same-sex faces and the left hemisphere involved in processing faces of the opposite sex. The data support previous literature suggesting a right lateralization for the representation of self-image and body awareness.

  14. Neural markers of opposite-sex bias in face processing.

    Science.gov (United States)

    Proverbio, Alice Mado; Riva, Federica; Martin, Eleonora; Zani, Alberto

    2010-01-01

    Some behavioral and neuroimaging studies suggest that adults prefer to view attractive faces of the opposite sex more than attractive faces of the same sex. However, unlike the other-race face effect (Caldara et al., 2004), little is known regarding the existence of an opposite-/same-sex bias in face processing. In this study, the faces of 130 attractive male and female adults were foveally presented to 40 heterosexual university students (20 men and 20 women) who were engaged in a secondary perceptual task (landscape detection). The automatic processing of face gender was investigated by recording ERPs from 128 scalp sites. Neural markers of opposite- vs. same-sex bias in face processing included larger and earlier centro-parietal N400s in response to faces of the opposite sex and a larger late positivity (LP) to same-sex faces. Analysis of intra-cortical neural generators (swLORETA) showed that facial processing-related (FG, BA37, BA20/21) and emotion-related brain areas (the right parahippocampal gyrus, BA35; uncus, BA36/38; and the cingulate gyrus, BA24) had higher activations in response to opposite- than same-sex faces. The results of this analysis, along with data obtained from ERP recordings, support the hypothesis that both genders process opposite-sex faces differently than same-sex faces. The data also suggest a hemispheric asymmetry in the processing of opposite-/same-sex faces, with the right hemisphere involved in processing same-sex faces and the left hemisphere involved in processing faces of the opposite sex. The data support previous literature suggesting a right lateralization for the representation of self-image and body awareness.

  15. Neural pulse frequency modulation of an exponentially correlated Gaussian process

    Science.gov (United States)

    Hutchinson, C. E.; Chon, Y.-T.

    1976-01-01

    The effect of NPFM (Neural Pulse Frequency Modulation) on a stationary Gaussian input, namely an exponentially correlated Gaussian input, is investigated with special emphasis on the determination of the average number of pulses in unit time, known also as the average frequency of pulse occurrence. For some classes of stationary input processes where the formulation of the appropriate multidimensional Markov diffusion model of the input-plus-NPFM system is possible, the average impulse frequency may be obtained by a generalization of the approach adopted. The results are approximate and numerical, but are in close agreement with Monte Carlo computer simulation results.

  16. Design and optimization of sustainable process technologies

    DEFF Research Database (Denmark)

    Mussatto, Solange I.; Qin, Fen; Yamakawa, Celina Kiyomi

    has been then considered a keypoint to achieve such purposes, being also able to result in potential environmental, economic, and social benefits. In this sense, the Biomass Conversion and Bioprocess TechnologyGroup (BCBT) has been working on the development of newstrategies for the use of biomass......, minimizing the costs and maximizing the efficiencyand productivity.Once the optimal conditions are identified, the process scale-up can be then evaluated. This could be translated in a faster time to market for newprocess technologies....

  17. Can Intrinsic Fluctuations Increase Efficiency in Neural Information Processing?

    Science.gov (United States)

    Liljenström, Hans

    2003-05-01

    All natural processes are accompanied by fluctuations, characterized as noise or chaos. Biological systems, which have evolved during billions of years, are likely to have adapted, not only to cope with such fluctuations, but also to make use of them. We investigate how the complex dynamics of the brain, including oscillations, chaos and noise, can affect the efficiency of neural information processing. In particular, we consider the amplification and functional role of internal fluctuations. Using computer simulations of a neural network model of the olfactory cortex and hippocampus, we demonstrate how microscopic fluctuations can result in global effects at the network level. We show that the rate of information processing in associative memory tasks can be maximized for optimal noise levels, analogous to stochastic resonance phenomena. Noise can also induce transitions between different dynamical states, which could be of significance for learning and memory. A chaotic-like behavior, induced by noise or by an increase in neuronal excitability, can enhance system performance if it is transient and converges to a limit cycle memory state. We speculate whether this dynamical behavior perhaps could be related to (creative) thinking.

  18. Multiscale neural connectivity during human sensory processing in the brain

    Science.gov (United States)

    Maksimenko, Vladimir A.; Runnova, Anastasia E.; Frolov, Nikita S.; Makarov, Vladimir V.; Nedaivozov, Vladimir; Koronovskii, Alexey A.; Pisarchik, Alexander; Hramov, Alexander E.

    2018-05-01

    Stimulus-related brain activity is considered using wavelet-based analysis of neural interactions between occipital and parietal brain areas in alpha (8-12 Hz) and beta (15-30 Hz) frequency bands. We show that human sensory processing related to the visual stimuli perception induces brain response resulted in different ways of parieto-occipital interactions in these bands. In the alpha frequency band the parieto-occipital neuronal network is characterized by homogeneous increase of the interaction between all interconnected areas both within occipital and parietal lobes and between them. In the beta frequency band the occipital lobe starts to play a leading role in the dynamics of the occipital-parietal network: The perception of visual stimuli excites the visual center in the occipital area and then, due to the increase of parieto-occipital interactions, such excitation is transferred to the parietal area, where the attentional center takes place. In the case when stimuli are characterized by a high degree of ambiguity, we find greater increase of the interaction between interconnected areas in the parietal lobe due to the increase of human attention. Based on revealed mechanisms, we describe the complex response of the parieto-occipital brain neuronal network during the perception and primary processing of the visual stimuli. The results can serve as an essential complement to the existing theory of neural aspects of visual stimuli processing.

  19. Statistical process control using optimized neural networks: a case study.

    Science.gov (United States)

    Addeh, Jalil; Ebrahimzadeh, Ata; Azarbad, Milad; Ranaee, Vahid

    2014-09-01

    The most common statistical process control (SPC) tools employed for monitoring process changes are control charts. A control chart demonstrates that the process has altered by generating an out-of-control signal. This study investigates the design of an accurate system for the control chart patterns (CCPs) recognition in two aspects. First, an efficient system is introduced that includes two main modules: feature extraction module and classifier module. In the feature extraction module, a proper set of shape features and statistical feature are proposed as the efficient characteristics of the patterns. In the classifier module, several neural networks, such as multilayer perceptron, probabilistic neural network and radial basis function are investigated. Based on an experimental study, the best classifier is chosen in order to recognize the CCPs. Second, a hybrid heuristic recognition system is introduced based on cuckoo optimization algorithm (COA) algorithm to improve the generalization performance of the classifier. The simulation results show that the proposed algorithm has high recognition accuracy. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

  20. Framework for Sustainability Performance Assessment for Manufacturing Processes- A Review

    Science.gov (United States)

    Singh, K.; Sultan, I.

    2017-07-01

    Manufacturing industries are facing tough competition due to increasing raw material cost and depleting natural resources. There is great pressure on the industry to produce environmental friendly products using environmental friendly processes. To address these issues modern manufacturing industries are focusing on sustainable manufacturing. To develop more sustainable societies, industries need to better understand how to respond to environmental, economic and social challenges. This paper proposed some framework and tools that accelerate the transition towards a sustainable system. The developed framework will be beneficial for sustainability assessment comparing different plans alongside material properties, ultimately helping the manufacturing industries to reduce the carbon emissions and material waste, besides improving energy efficiency. It is expected that this would be highly beneficial for determination of environmental impact of a process at early design stages. Therefore, it would greatly help the manufacturing industries for selection of process plan based on sustainable indices. Overall objective of this paper would have good impact on reducing air emissions and protecting environment. We expect this work to contribute to the development of a standard reference methodology to help further sustainability in the manufacturing sector.

  1. Sustainable Process Networks for CO2 Conversion

    DEFF Research Database (Denmark)

    Frauzem, Rebecca; Kongpanna, P.; Pavarajam, V.

    According to various organizations, especially the Intergovernmental Panel on Climate Change, global warming is an ever-increasing threat to the environment and poses a problem if not addressed. As a result, efforts are being made across academic and industrial fields to find methods of reducing...... drawbacks to this geologic storage system: the CO2 is not eliminated, the implementation is limited due to natural phenomena, and the capturing methods are often expensive. Thus, it is desirable to develop an alternative strategy for reducing the CO2 emissions [2]. An additional process that reduces...... that are thermodynamically feasible, including the co-reactants, catalysts, operating conditions and reactions. Research has revealed that there are a variety of reactions that fulfill the aforementioned criteria. The products that are formed fall into categories: fuels, bulk chemicals and specialty chemicals. While fuels...

  2. Nicotine Withdrawal Induces Neural Deficits in Reward Processing.

    Science.gov (United States)

    Oliver, Jason A; Evans, David E; Addicott, Merideth A; Potts, Geoffrey F; Brandon, Thomas H; Drobes, David J

    2017-06-01

    Nicotine withdrawal reduces neurobiological responses to nonsmoking rewards. Insight into these reward deficits could inform the development of targeted interventions. This study examined the effect of withdrawal on neural and behavioral responses during a reward prediction task. Smokers (N = 48) attended two laboratory sessions following overnight abstinence. Withdrawal was manipulated by having participants smoke three regular nicotine (0.6 mg yield; satiation) or very low nicotine (0.05 mg yield; withdrawal) cigarettes. Electrophysiological recordings of neural activity were obtained while participants completed a reward prediction task that involved viewing four combinations of predictive and reward-determining stimuli: (1) Unexpected Reward; (2) Predicted Reward; (3) Predicted Punishment; (4) Unexpected Punishment. The task evokes a medial frontal negativity that mimics the phasic pattern of dopaminergic firing in ventral tegmental regions associated with reward prediction errors. Nicotine withdrawal decreased the amplitude of the medial frontal negativity equally across all trial types (p nicotine dependence (p Nicotine withdrawal had equivocal impact across trial types, suggesting reward processing deficits are unlikely to stem from changes in phasic dopaminergic activity during prediction errors. Effects on tonic activity may be more pronounced. Pharmacological interventions directly targeting the dopamine system and behavioral interventions designed to increase reward motivation and responsiveness (eg, behavioral activation) may aid in mitigating withdrawal symptoms and potentially improving smoking cessation outcomes. Findings from this study indicate nicotine withdrawal impacts reward processing signals that are observable in smokers' neural activity. This may play a role in the subjective aversive experience of nicotine withdrawal and potentially contribute to smoking relapse. Interventions that address abnormal responding to both pleasant and

  3. Sustainable Chemical Process Development through an Integrated Framework

    DEFF Research Database (Denmark)

    Papadakis, Emmanouil; Kumar Tula, Anjan; Anantpinijwatna, Amata

    2016-01-01

    This paper describes the development and the application of a general integrated framework based on systematic model-based methods and computer-aided tools with the objective to achieve more sustainable process designs and to improve the process understanding. The developed framework can be appli...... studies involve multiphase reaction systems for the synthesis of active pharmaceutical ingredients....

  4. Towards a neural basis of processing musical semantics

    Science.gov (United States)

    Koelsch, Stefan

    2011-06-01

    Processing of meaning is critical for language perception, and therefore the majority of research on meaning processing has focused on the semantic, lexical, conceptual, and propositional processing of language. However, music is another a means of communication, and meaning also emerges from the interpretation of musical information. This article provides a framework for the investigation of the processing of musical meaning, and reviews neuroscience studies investigating this issue. These studies reveal two neural correlates of meaning processing, the N400 and the N5 (which are both components of the event-related electric brain potential). Here I argue that the N400 can be elicited by musical stimuli due to the processing of extra-musical meaning, whereas the N5 can be elicited due to the processing of intra-musical meaning. Notably, whereas the N400 can be elicited by both linguistic and musical stimuli, the N5 has so far only been observed for the processing of meaning in music. Thus, knowledge about both the N400 and the N5 can advance our understanding of how the human brain processes meaning information.

  5. Neural networks in front-end processing and control

    International Nuclear Information System (INIS)

    Lister, J.B.; Schnurrenberger, H.; Staeheli, N.; Stockhammer, N.; Duperrex, P.A.; Moret, J.M.

    1992-01-01

    Research into neural networks has gained a large following in recent years. In spite of the long term timescale of this Artificial Intelligence research, the tools which the community is developing can already find useful applications to real practical problems in experimental research. One of the main advantages of the parallel algorithms being developed in AI is the structural simplicity of the required hardware implementation, and the simple nature of the calculations involved. This makes these techniques ideal for problems in which both speed and data volume reduction are important, the case for most front-end processing tasks. In this paper the authors illustrate the use of a particular neural network known as the Multi-Layer Perceptron as a method for solving several different tasks, all drawn from the field of Tokamak research. The authors also briefly discuss the use of the Multi-Layer Perceptron as a non-linear controller in a feedback loop. The authors outline the type of problem which can be usefully addressed by these techniques, even before the large-scale parallel processing hardware currently under development becomes cheaply available. The authors also present some of the difficulties encountered in applying these networks

  6. Neural networks in front-end processing and control

    International Nuclear Information System (INIS)

    Lister, J.B.; Schnurrenberger, H.; Staeheli, N.; Stockhammer, N.; Duperrex, P.A.; Moret, J.M.

    1991-07-01

    Research into neural networks has gained a large following in recent years. In spite of the long term timescale of this Artificial Intelligence research, the tools which the community is developing can already find useful applications to real practical problems in experimental research. One of the main advantages of the parallel algorithms being developed in AI is the structural simplicity of the required hardware implementation, and the simple nature of the calculations involved. This makes these techniques ideal for problems in which both speed and data volume reduction are important, the case for most front-end processing tasks. In this paper we illustrate the use of a particular neural network known as the Multi-Layer Perceptron as a method for solving several different tasks, all drawn from the field of Tokamak research. We also briefly discuss the use of the Multi-Layer Perceptron as a non-linear controller in a feedback loop. We outline the type of problem which can be usefully addressed by these techniques, even before the large-scale parallel processing hardware currently under development becomes cheaply available. We also present some of the difficulties encountered in applying these networks. (author) 13 figs., 9 refs

  7. USC orthogonal multiprocessor for image processing with neural networks

    Science.gov (United States)

    Hwang, Kai; Panda, Dhabaleswar K.; Haddadi, Navid

    1990-07-01

    This paper presents the architectural features and imaging applications of the Orthogonal MultiProcessor (OMP) system, which is under construction at the University of Southern California with research funding from NSF and assistance from several industrial partners. The prototype OMP is being built with 16 Intel i860 RISC microprocessors and 256 parallel memory modules using custom-designed spanning buses, which are 2-D interleaved and orthogonally accessed without conflicts. The 16-processor OMP prototype is targeted to achieve 430 MIPS and 600 Mflops, which have been verified by simulation experiments based on the design parameters used. The prototype OMP machine will be initially applied for image processing, computer vision, and neural network simulation applications. We summarize important vision and imaging algorithms that can be restructured with neural network models. These algorithms can efficiently run on the OMP hardware with linear speedup. The ultimate goal is to develop a high-performance Visual Computer (Viscom) for integrated low- and high-level image processing and vision tasks.

  8. Neural dynamics of motion processing and speed discrimination.

    Science.gov (United States)

    Chey, J; Grossberg, S; Mingolla, E

    1998-09-01

    A neural network model of visual motion perception and speed discrimination is presented. The model shows how a distributed population code of speed tuning, that realizes a size-speed correlation, can be derived from the simplest mechanisms whereby activations of multiple spatially short-range filters of different size are transformed into speed-turned cell responses. These mechanisms use transient cell responses to moving stimuli, output thresholds that covary with filter size, and competition. These mechanisms are proposed to occur in the V1-->MT cortical processing stream. The model reproduces empirically derived speed discrimination curves and simulates data showing how visual speed perception and discrimination can be affected by stimulus contrast, duration, dot density and spatial frequency. Model motion mechanisms are analogous to mechanisms that have been used to model 3-D form and figure-ground perception. The model forms the front end of a larger motion processing system that has been used to simulate how global motion capture occurs, and how spatial attention is drawn to moving forms. It provides a computational foundation for an emerging neural theory of 3-D form and motion perception.

  9. Sustainable process design with process intensification - Development and implementation of a framework for sustainable carbon dioxide capture and utilization processes

    DEFF Research Database (Denmark)

    Frauzem, Rebecca

    . The developed framework adopts a 3-stage approach for sustainable design, which is comprised of: (1) synthesis, (2) design, and (3) innovation. In the first stage, the optimal processing route is obtained from a network via a superstructure-based approach. This stage incorporates a structured database...... and are designed and simulated in detail: 1. Dimethyl ether from methanol via combined reforming 2. Dimethyl ether from methanol via direct hydrogenation 3. Dimethyl carbonate via ethylene carbonate and methanol from combined reforming 4. Dimethyl carbonate via ethylene carbonate and methanol from direct...... hydrogenation. Through the analysis of the processes, it can be seen that the methanol distillation and the dimethyl carbonate downstream separation contribute to largeamounts of the utility consumption and therefore costs. Therefore, the reductionof the utility consumption of the methanol distillation...

  10. Fluid Intelligence and Automatic Neural Processes in Facial Expression Perception

    DEFF Research Database (Denmark)

    Liu, Tongran; Xiao, Tong; Li, Xiaoyan

    2015-01-01

    The relationship between human fluid intelligence and social-emotional abilities has been a topic of considerable interest. The current study investigated whether adolescents with different intellectual levels had different automatic neural processing of facial expressions. Two groups of adolescent...... males were enrolled: a high IQ group and an average IQ group. Age and parental socioeconomic status were matched between the two groups. Participants counted the numbers of the central cross changes while paired facial expressions were presented bilaterally in an oddball paradigm. There were two.......2). Participants were required to concentrate on the primary task of counting the central cross changes and to ignore the expressions to ensure that facial expression processing was automatic. Event-related potentials (ERPs) were obtained during the tasks. The visual mismatch negativity (vMMN) components were...

  11. Genetic Algorithms vs. Artificial Neural Networks in Economic Forecasting Process

    Directory of Open Access Journals (Sweden)

    Nicolae Morariu

    2008-01-01

    Full Text Available This paper aims to describe the implementa-tion of a neural network and a genetic algorithm system in order to forecast certain economic indicators of a free market economy. In a free market economy forecasting process precedes the economic planning (a management function, providing important information for the result of the last process. Forecasting represents a starting point in setting of target for a firm, an organization or even a branch of the economy. Thus, the forecasting method used can influence in a significant mode the evolution of an entity. In the following we will describe the forecasting of an economic indicator using two intelligent systems. The difference between the results obtained by this two systems are described in chapter IV.

  12. The principles of artificial neural network information processing

    International Nuclear Information System (INIS)

    Dai, Ru-Wei

    1993-01-01

    In this article, the basic structure of an artificial neuron is first introduced. In addition, principles of artificial neural network as well as several important artificial neural models such as perception, back propagation model, Hopfield net, and ART model are briefly discussed and analyzed. Finally the application of artificial neural network for Chinese character recognition is also given. (author)

  13. The principles of artificial neural network information processing

    International Nuclear Information System (INIS)

    Dai, Ru-Wei

    1993-01-01

    In this article, the basic structure of an artificial neuron is first introduced. In addition, principles of artificial neural network as well as several important artificial neural models such as Perceptron, Back propagation model, Hopfield net, and ART model are briefly discussed and analyzed. Finally, the application of artificial neural network for Chinese Character Recognition is also given. (author)

  14. Emotional sounds modulate early neural processing of emotional pictures

    Directory of Open Access Journals (Sweden)

    Antje B M Gerdes

    2013-10-01

    Full Text Available In our natural environment, emotional information is conveyed by converging visual and auditory information; multimodal integration is of utmost importance. In the laboratory, however, emotion researchers have mostly focused on the examination of unimodal stimuli. Few existing studies on multimodal emotion processing have focused on human communication such as the integration of facial and vocal expressions. Extending the concept of multimodality, the current study examines how the neural processing of emotional pictures is influenced by simultaneously presented sounds. Twenty pleasant, unpleasant, and neutral pictures of complex scenes were presented to 22 healthy participants. On the critical trials these pictures were paired with pleasant, unpleasant and neutral sounds. Sound presentation started 500 ms before picture onset and each stimulus presentation lasted for 2s. EEG was recorded from 64 channels and ERP analyses focused on the picture onset. In addition, valence, and arousal ratings were obtained. Previous findings for the neural processing of emotional pictures were replicated. Specifically, unpleasant compared to neutral pictures were associated with an increased parietal P200 and a more pronounced centroparietal late positive potential (LPP, independent of the accompanying sound valence. For audiovisual stimulation, increased parietal P100 and P200 were found in response to all pictures which were accompanied by unpleasant or pleasant sounds compared to pictures with neutral sounds. Most importantly, incongruent audiovisual pairs of unpleasant pictures and pleasant sounds enhanced parietal P100 and P200 compared to pairings with congruent sounds. Taken together, the present findings indicate that emotional sounds modulate early stages of visual processing and, therefore, provide an avenue by which multimodal experience may enhance perception.

  15. BOOK REVIEW: Theory of Neural Information Processing Systems

    Science.gov (United States)

    Galla, Tobias

    2006-04-01

    It is difficult not to be amazed by the ability of the human brain to process, to structure and to memorize information. Even by the toughest standards the behaviour of this network of about 1011 neurons qualifies as complex, and both the scientific community and the public take great interest in the growing field of neuroscience. The scientific endeavour to learn more about the function of the brain as an information processing system is here a truly interdisciplinary one, with important contributions from biology, computer science, physics, engineering and mathematics as the authors quite rightly point out in the introduction of their book. The role of the theoretical disciplines here is to provide mathematical models of information processing systems and the tools to study them. These models and tools are at the centre of the material covered in the book by Coolen, Kühn and Sollich. The book is divided into five parts, providing basic introductory material on neural network models as well as the details of advanced techniques to study them. A mathematical appendix complements the main text. The range of topics is extremely broad, still the presentation is concise and the book well arranged. To stress the breadth of the book let me just mention a few keywords here: the material ranges from the basics of perceptrons and recurrent network architectures to more advanced aspects such as Bayesian learning and support vector machines; Shannon's theory of information and the definition of entropy are discussed, and a chapter on Amari's information geometry is not missing either. Finally the statistical mechanics chapters cover Gardner theory and the replica analysis of the Hopfield model, not without being preceded by a brief introduction of the basic concepts of equilibrium statistical physics. The book also contains a part on effective theories of the macroscopic dynamics of neural networks. Many dynamical aspects of neural networks are usually hard to find in the

  16. Direct process estimation from tomographic data using artificial neural systems

    Science.gov (United States)

    Mohamad-Saleh, Junita; Hoyle, Brian S.; Podd, Frank J.; Spink, D. M.

    2001-07-01

    The paper deals with the goal of component fraction estimation in multicomponent flows, a critical measurement in many processes. Electrical capacitance tomography (ECT) is a well-researched sensing technique for this task, due to its low-cost, non-intrusion, and fast response. However, typical systems, which include practicable real-time reconstruction algorithms, give inaccurate results, and existing approaches to direct component fraction measurement are flow-regime dependent. In the investigation described, an artificial neural network approach is used to directly estimate the component fractions in gas-oil, gas-water, and gas-oil-water flows from ECT measurements. A 2D finite- element electric field model of a 12-electrode ECT sensor is used to simulate ECT measurements of various flow conditions. The raw measurements are reduced to a mutually independent set using principal components analysis and used with their corresponding component fractions to train multilayer feed-forward neural networks (MLFFNNs). The trained MLFFNNs are tested with patterns consisting of unlearned ECT simulated and plant measurements. Results included in the paper have a mean absolute error of less than 1% for the estimation of various multicomponent fractions of the permittivity distribution. They are also shown to give improved component fraction estimation compared to a well known direct ECT method.

  17. Computer-Aided Sustainable Process Synthesis-Design and Analysis

    DEFF Research Database (Denmark)

    Kumar Tula, Anjan

    -groups is that, the performance of the entire process can be evaluated from the contributions of the individual process-groups towards the selected flowsheet property (for example, energy consumed). The developed flowsheet property models include energy consumption, carbon footprint, product recovery, product......Process synthesis involves the investigation of chemical reactions needed to produce the desired product, selection of the separation techniques needed for downstream processing, as well as taking decisions on sequencing the involved separation operations. For an effective, efficient and flexible...... focuses on the development and application of a computer-aided framework for sustainable synthesis-design and analysis of process flowsheets by generating feasible alternatives covering the entire search space and includes analysis tools for sustainability, LCA and economics. The synthesis method is based...

  18. Dynamic Neural Processing of Linguistic Cues Related to Death

    Science.gov (United States)

    Ma, Yina; Qin, Jungang; Han, Shihui

    2013-01-01

    Behavioral studies suggest that humans evolve the capacity to cope with anxiety induced by the awareness of death’s inevitability. However, the neurocognitive processes that underlie online death-related thoughts remain unclear. Our recent functional MRI study found that the processing of linguistic cues related to death was characterized by decreased neural activity in human insular cortex. The current study further investigated the time course of neural processing of death-related linguistic cues. We recorded event-related potentials (ERP) to death-related, life-related, negative-valence, and neutral-valence words in a modified Stroop task that required color naming of words. We found that the amplitude of an early frontal/central negativity at 84–120 ms (N1) decreased to death-related words but increased to life-related words relative to neutral-valence words. The N1 effect associated with death-related and life-related words was correlated respectively with individuals’ pessimistic and optimistic attitudes toward life. Death-related words also increased the amplitude of a frontal/central positivity at 124–300 ms (P2) and of a frontal/central positivity at 300–500 ms (P3). However, the P2 and P3 modulations were observed for both death-related and negative-valence words but not for life-related words. The ERP results suggest an early inverse coding of linguistic cues related to life and death, which is followed by negative emotional responses to death-related information. PMID:23840787

  19. Neural Signaling of Food Healthiness Associated with Emotion Processing.

    Science.gov (United States)

    Herwig, Uwe; Dhum, Matthias; Hittmeyer, Anna; Opialla, Sarah; Scherpiet, Sigrid; Keller, Carmen; Brühl, Annette B; Siegrist, Michael

    2016-01-01

    The ability to differentiate healthy from unhealthy foods is important in order to promote good health. Food, however, may have an emotional connotation, which could be inversely related to healthiness. The neurobiological background of differentiating healthy and unhealthy food and its relations to emotion processing are not yet well understood. We addressed the neural activations, particularly considering the single subject level, when one evaluates a food item to be of a higher, compared to a lower grade of healthiness with a particular view on emotion processing brain regions. Thirty-seven healthy subjects underwent functional magnetic resonance imaging while evaluating the healthiness of food presented as photographs with a subsequent rating on a visual analog scale. We compared individual evaluations of high and low healthiness of food items and also considered gender differences. We found increased activation when food was evaluated to be healthy in the left dorsolateral prefrontal cortex and precuneus in whole brain analyses. In ROI analyses, perceived and rated higher healthiness was associated with lower amygdala activity and higher ventral striatal and orbitofrontal cortex activity. Females exerted a higher activation in midbrain areas when rating food items as being healthy. Our results underline the close relationship between food and emotion processing, which makes sense considering evolutionary aspects. Actively evaluating and deciding whether food is healthy is accompanied by neural signaling associated with reward and self-relevance, which could promote salutary nutrition behavior. The involved brain regions may be amenable to mechanisms of emotion regulation in the context of psychotherapeutic regulation of food intake.

  20. USAF Logistics Process Optimization Study for the Aircraft Asset Sustainment Process. Volume 2

    National Research Council Canada - National Science Library

    Adamson, Anthony

    1998-01-01

    .... It is published as three separate volumes. Volume I, USAF Logistics Process Optimization Study for the Aircraft Asset Sustainment Process -- Phase II Report, discusses the result and cost/benefit analysis of testing three initiatives...

  1. USAF Logistics Process Optimization Study for the Aircraft Asset Sustainment Process. Volume 1

    National Research Council Canada - National Science Library

    Adamson, Anthony

    1998-01-01

    .... It is published as three separate volumes. Volume I, USAF Logistics Process Optimization Study for the Aircraft Asset Sustainment Process -- Phase II Report, discusses the result and cost/benefit analysis of testing three initiatives...

  2. Toward Sustainable Anticipatory Governance: Analyzing and Assessing Nanotechnology Innovation Processes

    Science.gov (United States)

    Foley, Rider Williams

    Cities around the globe struggle with socio-economic disparities, resource inefficiency, environmental contamination, and quality-of-life challenges. Technological innovation, as one prominent approach to problem solving, promises to address these challenges; yet, introducing new technologies, such as nanotechnology, into society and cities has often resulted in negative consequences. Recent research has conceptually linked anticipatory governance and sustainability science: to understand the role of technology in complex problems our societies face; to anticipate negative consequences of technological innovation; and to promote long-term oriented and responsible governance of technologies. This dissertation advances this link conceptually and empirically, focusing on nanotechnology and urban sustainability challenges. The guiding question for this dissertation research is: How can nanotechnology be innovated and governed in responsible ways and with sustainable outcomes? The dissertation: analyzes the nanotechnology innovation process from an actor- and activities-oriented perspective (Chapter 2); assesses this innovation process from a comprehensive perspective on sustainable governance (Chapter 3); constructs a small set of future scenarios to consider future implications of different nanotechnology governance models (Chapter 4); and appraises the amenability of sustainability problems to nanotechnological interventions (Chapter 5). The four studies are based on data collected through literature review, document analysis, participant observation, interviews, workshops, and walking audits, as part of process analysis, scenario construction, and technology assessment. Research was conducted in collaboration with representatives from industry, government agencies, and civic organizations. The empirical parts of the four studies focus on Metropolitan Phoenix. Findings suggest that: predefined mandates and economic goals dominate the nanotechnology innovation process

  3. Neural processing of auditory signals and modular neural control for sound tropism of walking machines

    DEFF Research Database (Denmark)

    Manoonpong, Poramate; Pasemann, Frank; Fischer, Joern

    2005-01-01

    and a neural preprocessing system together with a modular neural controller are used to generate a sound tropism of a four-legged walking machine. The neural preprocessing network is acting as a low-pass filter and it is followed by a network which discerns between signals coming from the left or the right....... The parameters of these networks are optimized by an evolutionary algorithm. In addition, a simple modular neural controller then generates the desired different walking patterns such that the machine walks straight, then turns towards a switched-on sound source, and then stops near to it....

  4. Sustainable flexible process innovation. Towards a new building design approach

    NARCIS (Netherlands)

    Brand, G.J.W. van den; Quanjel, E.; Zeiler, W.

    2001-01-01

    Developers and investors ofresidential and office buildings are facing large risks. A yearly loss ofcapital of approximately 50 billion EURO can be reduced by improvement of the design process. The need for more sustainable and end user oriented buildings on a background ofthe dynamics ofever

  5. A sustainable process for gram-scale synthesis of stereoselective ...

    Indian Academy of Sciences (India)

    We have developed a new, simple and sustainable process for stereoselective synthesis of aryl substituted (E)-2-thiocyanatoacrylic acids by nucleophilic substitution and Knoevenagel condensation involving chloroacetic acid, ammonium thiocyanate and aromatic aldehydes at room temperature. The selectivity was ...

  6. Neural tissue engineering scaffold with sustained RAPA release relieves neuropathic pain in rats.

    Science.gov (United States)

    Ding, Tan; Zhu, Chao; Kou, Zhen-Zhen; Yin, Jun-Bin; Zhang, Ting; Lu, Ya-Cheng; Wang, Li-Ying; Luo, Zhuo-Jing; Li, Yun-Qing

    2014-09-01

    To investigate the effect of locally slow-released rapamycin (RAPA) from bionic peripheral nerve stent to reduce the incidence of neuropathic pain or mitigate the degree of pain after nerve injury. We constructed a neural tissue engineering scaffold with sustained release of RAPA to repair 20mm defects in rat sciatic nerves. Four presurgical and postsurgical time windows were selected to monitor the changes in the expression of pain-related dorsal root ganglion (DRG) voltage-gated sodium channels 1.3 (Nav1.3), 1.7 (Nav1.7), and 1.8 (Nav1.8) through immunohistochemistry (IHC) and Western Blot, along with the observation of postsurgical pathological pain in rats by pain-related behavior approaches. Relatively small upregulation of DRG sodium channels was observed in the experimental group (RAPA+poly(lactic-co-glycolic acid) (PLGA)+stent) after surgery, along with low degrees of neuropathic pain and anxiety, which were similar to those in the Autologous nerve graft group. Autoimmune inflammatory response plays a leading role in the occurrence of post-traumatic neuropathic pain, and that RAPA significantly inhibits the abnormal upregulation of sodium channels to reduce pain by alleviating inflammatory response. Copyright © 2014 Elsevier Inc. All rights reserved.

  7. Image processing and analysis using neural networks for optometry area

    Science.gov (United States)

    Netto, Antonio V.; Ferreira de Oliveira, Maria C.

    2002-11-01

    In this work we describe the framework of a functional system for processing and analyzing images of the human eye acquired by the Hartmann-Shack technique (HS), in order to extract information to formulate a diagnosis of eye refractive errors (astigmatism, hypermetropia and myopia). The analysis is to be carried out using an Artificial Intelligence system based on Neural Nets, Fuzzy Logic and Classifier Combination. The major goal is to establish the basis of a new technology to effectively measure ocular refractive errors that is based on methods alternative those adopted in current patented systems. Moreover, analysis of images acquired with the Hartmann-Shack technique may enable the extraction of additional information on the health of an eye under exam from the same image used to detect refraction errors.

  8. Reconstruction of an engine combustion process with a neural network

    Energy Technology Data Exchange (ETDEWEB)

    Jacob, P J; Gu, F; Ball, A D [School of Engineering, University of Manchester, Manchester (United Kingdom)

    1998-12-31

    The cylinder pressure waveform in an internal combustion engine is one of the most important parameters in describing the engine combustion process. It is used for a range of diagnostic tasks such as identification of ignition faults or mechanical wear in the cylinders. However, it is very difficult to measure this parameter directly. Never-the-less, the cylinder pressure may be inferred from other more readily obtainable parameters. In this presentation it is shown how a Radial Basis Function network, which may be regarded as a form of neural network, may be used to model the cylinder pressure as a function of the instantaneous crankshaft velocity, recorded with a simple magnetic sensor. The application of the model is demonstrated on a four cylinder DI diesel engine with data from a wide range of speed and load settings. The prediction capabilities of the model once trained are validated against measured data. (orig.) 4 refs.

  9. Reconstruction of an engine combustion process with a neural network

    Energy Technology Data Exchange (ETDEWEB)

    Jacob, P.J.; Gu, F.; Ball, A.D. [School of Engineering, University of Manchester, Manchester (United Kingdom)

    1997-12-31

    The cylinder pressure waveform in an internal combustion engine is one of the most important parameters in describing the engine combustion process. It is used for a range of diagnostic tasks such as identification of ignition faults or mechanical wear in the cylinders. However, it is very difficult to measure this parameter directly. Never-the-less, the cylinder pressure may be inferred from other more readily obtainable parameters. In this presentation it is shown how a Radial Basis Function network, which may be regarded as a form of neural network, may be used to model the cylinder pressure as a function of the instantaneous crankshaft velocity, recorded with a simple magnetic sensor. The application of the model is demonstrated on a four cylinder DI diesel engine with data from a wide range of speed and load settings. The prediction capabilities of the model once trained are validated against measured data. (orig.) 4 refs.

  10. Unsupervised Neural Network Quantifies the Cost of Visual Information Processing.

    Science.gov (United States)

    Orbán, Levente L; Chartier, Sylvain

    2015-01-01

    Untrained, "flower-naïve" bumblebees display behavioural preferences when presented with visual properties such as colour, symmetry, spatial frequency and others. Two unsupervised neural networks were implemented to understand the extent to which these models capture elements of bumblebees' unlearned visual preferences towards flower-like visual properties. The computational models, which are variants of Independent Component Analysis and Feature-Extracting Bidirectional Associative Memory, use images of test-patterns that are identical to ones used in behavioural studies. Each model works by decomposing images of floral patterns into meaningful underlying factors. We reconstruct the original floral image using the components and compare the quality of the reconstructed image to the original image. Independent Component Analysis matches behavioural results substantially better across several visual properties. These results are interpreted to support a hypothesis that the temporal and energetic costs of information processing by pollinators served as a selective pressure on floral displays: flowers adapted to pollinators' cognitive constraints.

  11. Neural correlates of sublexical processing in phonological working memory.

    Science.gov (United States)

    McGettigan, Carolyn; Warren, Jane E; Eisner, Frank; Marshall, Chloe R; Shanmugalingam, Pradheep; Scott, Sophie K

    2011-04-01

    This study investigated links between working memory and speech processing systems. We used delayed pseudoword repetition in fMRI to investigate the neural correlates of sublexical structure in phonological working memory (pWM). We orthogonally varied the number of syllables and consonant clusters in auditory pseudowords and measured the neural responses to these manipulations under conditions of covert rehearsal (Experiment 1). A left-dominant network of temporal and motor cortex showed increased activity for longer items, with motor cortex only showing greater activity concomitant with adding consonant clusters. An individual-differences analysis revealed a significant positive relationship between activity in the angular gyrus and the hippocampus, and accuracy on pseudoword repetition. As models of pWM stipulate that its neural correlates should be activated during both perception and production/rehearsal [Buchsbaum, B. R., & D'Esposito, M. The search for the phonological store: From loop to convolution. Journal of Cognitive Neuroscience, 20, 762-778, 2008; Jacquemot, C., & Scott, S. K. What is the relationship between phonological short-term memory and speech processing? Trends in Cognitive Sciences, 10, 480-486, 2006; Baddeley, A. D., & Hitch, G. Working memory. In G. H. Bower (Ed.), The psychology of learning and motivation: Advances in research and theory (Vol. 8, pp. 47-89). New York: Academic Press, 1974], we further assessed the effects of the two factors in a separate passive listening experiment (Experiment 2). In this experiment, the effect of the number of syllables was concentrated in posterior-medial regions of the supratemporal plane bilaterally, although there was no evidence of a significant response to added clusters. Taken together, the results identify the planum temporale as a key region in pWM; within this region, representations are likely to take the form of auditory or audiomotor "templates" or "chunks" at the level of the syllable

  12. Bioprocesses: Modelling needs for process evaluation and sustainability assessment

    DEFF Research Database (Denmark)

    Jiménez-Gonzaléz, Concepcion; Woodley, John

    2010-01-01

    development such that they can also be used to evaluate processes against sustainability metrics, as well as economics as an integral part of assessments. Finally, property models will also be required based on compounds not currently present in existing databases. It is clear that many new opportunities......The next generation of process engineers will face a new set of challenges, with the need to devise new bioprocesses, with high selectivity for pharmaceutical manufacture, and for lower value chemicals manufacture based on renewable feedstocks. In this paper the current and predicted future roles...... of process system engineering and life cycle inventory and assessment in the design, development and improvement of sustainable bioprocesses are explored. The existing process systems engineering software tools will prove essential to assist this work. However, the existing tools will also require further...

  13. Neural Processing of Emotional Musical and Nonmusical Stimuli in Depression.

    Directory of Open Access Journals (Sweden)

    Rebecca J Lepping

    Full Text Available Anterior cingulate cortex (ACC and striatum are part of the emotional neural circuitry implicated in major depressive disorder (MDD. Music is often used for emotion regulation, and pleasurable music listening activates the dopaminergic system in the brain, including the ACC. The present study uses functional MRI (fMRI and an emotional nonmusical and musical stimuli paradigm to examine how neural processing of emotionally provocative auditory stimuli is altered within the ACC and striatum in depression.Nineteen MDD and 20 never-depressed (ND control participants listened to standardized positive and negative emotional musical and nonmusical stimuli during fMRI scanning and gave subjective ratings of valence and arousal following scanning.ND participants exhibited greater activation to positive versus negative stimuli in ventral ACC. When compared with ND participants, MDD participants showed a different pattern of activation in ACC. In the rostral part of the ACC, ND participants showed greater activation for positive information, while MDD participants showed greater activation to negative information. In dorsal ACC, the pattern of activation distinguished between the types of stimuli, with ND participants showing greater activation to music compared to nonmusical stimuli, while MDD participants showed greater activation to nonmusical stimuli, with the greatest response to negative nonmusical stimuli. No group differences were found in striatum.These results suggest that people with depression may process emotional auditory stimuli differently based on both the type of stimulation and the emotional content of that stimulation. This raises the possibility that music may be useful in retraining ACC function, potentially leading to more effective and targeted treatments.

  14. Acoustic richness modulates the neural networks supporting intelligible speech processing.

    Science.gov (United States)

    Lee, Yune-Sang; Min, Nam Eun; Wingfield, Arthur; Grossman, Murray; Peelle, Jonathan E

    2016-03-01

    The information contained in a sensory signal plays a critical role in determining what neural processes are engaged. Here we used interleaved silent steady-state (ISSS) functional magnetic resonance imaging (fMRI) to explore how human listeners cope with different degrees of acoustic richness during auditory sentence comprehension. Twenty-six healthy young adults underwent scanning while hearing sentences that varied in acoustic richness (high vs. low spectral detail) and syntactic complexity (subject-relative vs. object-relative center-embedded clause structures). We manipulated acoustic richness by presenting the stimuli as unprocessed full-spectrum speech, or noise-vocoded with 24 channels. Importantly, although the vocoded sentences were spectrally impoverished, all sentences were highly intelligible. These manipulations allowed us to test how intelligible speech processing was affected by orthogonal linguistic and acoustic demands. Acoustically rich speech showed stronger activation than acoustically less-detailed speech in a bilateral temporoparietal network with more pronounced activity in the right hemisphere. By contrast, listening to sentences with greater syntactic complexity resulted in increased activation of a left-lateralized network including left posterior lateral temporal cortex, left inferior frontal gyrus, and left dorsolateral prefrontal cortex. Significant interactions between acoustic richness and syntactic complexity occurred in left supramarginal gyrus, right superior temporal gyrus, and right inferior frontal gyrus, indicating that the regions recruited for syntactic challenge differed as a function of acoustic properties of the speech. Our findings suggest that the neural systems involved in speech perception are finely tuned to the type of information available, and that reducing the richness of the acoustic signal dramatically alters the brain's response to spoken language, even when intelligibility is high. Copyright © 2015 Elsevier

  15. Guiding Principles for Sustainable Existing Buildings: Radiochemical Processing Laboratory

    Energy Technology Data Exchange (ETDEWEB)

    Pope, Jason E. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2013-11-11

    In 2006, the United States (U.S.) Department of Energy (DOE) signed the Federal Leadership in High Performance and Sustainable Buildings Memorandum of Understanding (MOU), along with 21 other agencies. Pacific Northwest National Laboratory (PNNL) is exceeding this requirement and, currently, about 25 percent of its buildings are High Performance and Sustainable Buildings. The pages that follow document the Guiding Principles conformance effort for the Radiochemical Processing Laboratory (RPL) at PNNL. The RPL effort is part of continued progress toward a building inventory that is 100 percent compliant with the Guiding Principles.

  16. Neural correlates of gesture processing across human development.

    Science.gov (United States)

    Wakefield, Elizabeth M; James, Thomas W; James, Karin H

    2013-01-01

    Co-speech gesture facilitates learning to a greater degree in children than in adults, suggesting that the mechanisms underlying the processing of co-speech gesture differ as a function of development. We suggest that this may be partially due to children's lack of experience producing gesture, leading to differences in the recruitment of sensorimotor networks when comparing adults to children. Here, we investigated the neural substrates of gesture processing in a cross-sectional sample of 5-, 7.5-, and 10-year-old children and adults and focused on relative recruitment of a sensorimotor system that included the precentral gyrus (PCG) and the posterior middle temporal gyrus (pMTG). Children and adults were presented with videos in which communication occurred through different combinations of speech and gesture during a functional magnetic resonance imaging (fMRI) session. Results demonstrated that the PCG and pMTG were recruited to different extents in the two populations. We interpret these novel findings as supporting the idea that gesture perception (pMTG) is affected by a history of gesture production (PCG), revealing the importance of considering gesture processing as a sensorimotor process.

  17. Male veterans with PTSD exhibit aberrant neural dynamics during working memory processing: an MEG study.

    Science.gov (United States)

    McDermott, Timothy J; Badura-Brack, Amy S; Becker, Katherine M; Ryan, Tara J; Khanna, Maya M; Heinrichs-Graham, Elizabeth; Wilson, Tony W

    2016-06-01

    Posttraumatic stress disorder (PTSD) is associated with executive functioning deficits, including disruptions in working memory. In this study, we examined the neural dynamics of working memory processing in veterans with PTSD and a matched healthy control sample using magnetoencephalography (MEG). Our sample of recent combat veterans with PTSD and demographically matched participants without PTSD completed a working memory task during a 306-sensor MEG recording. The MEG data were preprocessed and transformed into the time-frequency domain. Significant oscillatory brain responses were imaged using a beamforming approach to identify spatiotemporal dynamics. Fifty-one men were included in our analyses: 27 combat veterans with PTSD and 24 controls. Across all participants, a dynamic wave of neural activity spread from posterior visual cortices to left frontotemporal regions during encoding, consistent with a verbal working memory task, and was sustained throughout maintenance. Differences related to PTSD emerged during early encoding, with patients exhibiting stronger α oscillatory responses than controls in the right inferior frontal gyrus (IFG). Differences spread to the right supramarginal and temporal cortices during later encoding where, along with the right IFG, they persisted throughout the maintenance period. This study focused on men with combat-related PTSD using a verbal working memory task. Future studies should evaluate women and the impact of various traumatic experiences using diverse tasks. Posttraumatic stress disorder is associated with neurophysiological abnormalities during working memory encoding and maintenance. Veterans with PTSD engaged a bilateral network, including the inferior prefrontal cortices and supramarginal gyri. Right hemispheric neural activity likely reflects compensatory processing, as veterans with PTSD work to maintain accurate performance despite known cognitive deficits associated with the disorder.

  18. Sustainable cost reduction by lean management in metallurgical processes

    Directory of Open Access Journals (Sweden)

    A. V. Todorut

    2016-10-01

    Full Text Available This paper focuses on the need for sustainable cost reduction in the metallurgical industry by applying Lean Management (LM tools and concepts in metallurgical production processes leading to increased competitiveness of corporations in a global market. The paper highlights that Lean Management is a novel way of thinking, adapting to change, reducing waste and continuous improvement, leading to sustainable development of companies in the metallurgical industry. The authors outline the main Lean Management instruments based on recent scientific research and include a comparative analysis of other tools, such as Sort, Straighten, Shine, Standardize, Sustain (5S, Visual Management (VM, Kaizen, Total Productive Maintenance (TPM, Single-Minute Exchange of Dies (SMED, leading to a critical appraisal of their application in the metallurgical industry.

  19. RELEVANCE OF ECONOMIC INSTRUMENTS USED IN SUSTAINABLE DEVELOPMENT PROCESS

    Directory of Open Access Journals (Sweden)

    SORINA-GEANINA MĂRGĂRIT (STĂNESCU

    2011-01-01

    Full Text Available The interaction between environmental, economic and social factors influences the ecological balance and generates the change of living conditions and those of socio-economic development. One of the essential conditions for building a sustainable economic development is the identification and implementation of active or voluntary instruments to influence economic and social activity towards ensuring their sustainability. In this paper, we intend to introduce the tools used in the process of sustainable development, which have a key role in adopting an environmentally responsible behavior. The results of this study are represented by the drafting of the advantages and disadvantages of using these economic and financial instruments. The purpose of this paper is to present the evolution of costs for environmental protection and the relevance of instruments used at the national level in environmental protection.

  20. Sustainability.

    Science.gov (United States)

    Chang, Chein-Chi; DiGiovanni, Kimberly; Mei, Ying; Wei, Li

    2016-10-01

    This review on Sustainability covers selected 2015 publications on the focus of Sustainability. It is divided into the following sections : • Sustainable water and wastewater utilities • Sustainable water resources management • Stormwater and green infrastructure • Sustainability in wastewater treatment • Life cycle assessment (LCA) applications • Sustainability and energy in wastewater industry, • Sustainability and asset management.

  1. Sustainability of compressive residual stress by stress improvement processes

    International Nuclear Information System (INIS)

    Nishikawa, Satoru; Okita, Shigeru; Yamaguchi, Atsunori

    2013-01-01

    Stress improvement processes are countermeasures against stress corrosion cracking in nuclear power plant components. It is necessary to confirm whether compressive residual stress induced by stress improvement processes can be sustained under operation environment. In order to evaluate stability of the compressive residual stress in 60-year operating conditions, the 0.07% cyclic strains of 200 times at 593 K were applied to the welded specimens, then a thermal aging treatment for 1.66x10 6 s at 673 K was carried out. As the result, it was confirmed that the compressive residual stresses were sustained on both surfaces of the dissimilar welds of austenitic stainless steel (SUS316L) and nickel base alloy (NCF600 and alloy 182) processed by laser peening (LP), water jet peening (WJP), ultrasonic shot peening (USP), shot peening (SP) and polishing under 60-year operating conditions. (author)

  2. The application of neural networks with artificial intelligence technique in the modeling of industrial processes

    International Nuclear Information System (INIS)

    Saini, K. K.; Saini, Sanju

    2008-01-01

    Neural networks are a relatively new artificial intelligence technique that emulates the behavior of biological neural systems in digital software or hardware. These networks can 'learn', automatically, complex relationships among data. This feature makes the technique very useful in modeling processes for which mathematical modeling is difficult or impossible. The work described here outlines some examples of the application of neural networks with artificial intelligence technique in the modeling of industrial processes.

  3. Attention Modulates the Neural Processes Underlying Multisensory Integration of Emotion

    Directory of Open Access Journals (Sweden)

    Hao Tam Ho

    2011-10-01

    Full Text Available Integrating emotional information from multiple sensory modalities is generally assumed to be a pre-attentive process (de Gelder et al., 1999. This assumption, however, presupposes that the integrative process occurs independent of attention. Using event-potentials (ERP the present study investigated whether the neural processes underlying the integration of dynamic facial expression and emotional prosody is indeed unaffected by attentional manipulations. To this end, participants were presented with congruent and incongruent face-voice combinations (eg, an angry face combined with a neutral voice and performed different two-choice tasks in four consecutive blocks. Three of the tasks directed the participants' attention to emotion expressions in the face, the voice or both. The fourth task required participants to attend to the synchronicity between voice and lip movements. The results show divergent modulations of early ERP components by the different attentional manipulations. For example, when attention was directed to the face (or the voice, incongruent stimuli elicited a reduced N1 as compared to congruent stimuli. This effect was absent, when attention was diverted away from the emotionality in both face and voice suggesting that the detection of emotional incongruence already requires attention. Based on these findings, we question whether multisensory integration of emotion occurs indeed pre-attentively.

  4. Use of neural networks in process engineering. Thermodynamics, diffusion, and process control and simulation applications

    International Nuclear Information System (INIS)

    Otero, F

    1998-01-01

    This article presents the current status of the use of Artificial Neural Networks (ANNs) in process engineering applications where common mathematical methods do not completely represent the behavior shown by experimental observations, results, and plant operating data. Three examples of the use of ANNs in typical process engineering applications such as prediction of activity in solvent-polymer binary systems, prediction of a surfactant self-diffusion coefficient of micellar systems, and process control and simulation are shown. These examples are important for polymerization applications, enhanced-oil recovery, and automatic process control

  5. Improving sustainability of maize to ethanol processing by plant breeding and process optimization

    NARCIS (Netherlands)

    Slegers, P.M.; Torres Salvador, A.F.; Boxtel, van A.J.B.; Trindade, L.M.

    2017-01-01

    Efficient management of plant resources is essential for a sustainable biobased economy. The biomass conversion efficiency and sustainability performance depend greatly on the choice of feedstock and the applied processing technology. The aim of this research was to enhance the biomass use of maize

  6. Membrane-based processes for sustainable power generation using water

    KAUST Repository

    Logan, Bruce E.; Elimelech, Menachem

    2012-01-01

    Water has always been crucial to combustion and hydroelectric processes, but it could become the source of power in membrane-based systems that capture energy from natural and waste waters. Two processes are emerging as sustainable methods for capturing energy from sea water: pressure-retarded osmosis and reverse electrodialysis. These processes can also capture energy from waste heat by generating artificial salinity gradients using synthetic solutions, such as thermolytic salts. A further source of energy comes from organic matter in waste waters, which can be harnessed using microbial fuel-cell technology, allowing both wastewater treatment and power production. © 2012 Macmillan Publishers Limited. All rights reserved.

  7. Membrane-based processes for sustainable power generation using water

    KAUST Repository

    Logan, Bruce E.

    2012-08-15

    Water has always been crucial to combustion and hydroelectric processes, but it could become the source of power in membrane-based systems that capture energy from natural and waste waters. Two processes are emerging as sustainable methods for capturing energy from sea water: pressure-retarded osmosis and reverse electrodialysis. These processes can also capture energy from waste heat by generating artificial salinity gradients using synthetic solutions, such as thermolytic salts. A further source of energy comes from organic matter in waste waters, which can be harnessed using microbial fuel-cell technology, allowing both wastewater treatment and power production. © 2012 Macmillan Publishers Limited. All rights reserved.

  8. Bistability Analysis of Excitatory-Inhibitory Neural Networks in Limited-Sustained-Activity Regime

    International Nuclear Information System (INIS)

    Ni Yun; Wu Liang; Wu Dan; Zhu Shiqun

    2011-01-01

    Bistable behavior of neuronal complex networks is investigated in the limited-sustained-activity regime when the network is composed of excitatory and inhibitory neurons. The standard stability analysis is performed on the two metastable states separately. Both theoretical analysis and numerical simulations show consistently that the difference between time scales of excitatory and inhibitory populations can influence the dynamical behaviors of the neuronal networks dramatically, leading to the transition from bistable behaviors with memory effects to the collapse of bistable behaviors. These results may suggest one possible neuronal information processing by only tuning time scales. (interdisciplinary physics and related areas of science and technology)

  9. Risky decisions and their consequences: neural processing by boys with Antisocial Substance Disorder.

    Directory of Open Access Journals (Sweden)

    Thomas J Crowley

    2010-09-01

    Full Text Available Adolescents with conduct and substance problems ("Antisocial Substance Disorder" (ASD repeatedly engage in risky antisocial and drug-using behaviors. We hypothesized that, during processing of risky decisions and resulting rewards and punishments, brain activation would differ between abstinent ASD boys and comparison boys.We compared 20 abstinent adolescent male patients in treatment for ASD with 20 community controls, examining rapid event-related blood-oxygen-level-dependent (BOLD responses during functional magnetic resonance imaging. In 90 decision trials participants chose to make either a cautious response that earned one cent, or a risky response that would either gain 5 cents or lose 10 cents; odds of losing increased as the game progressed. We also examined those times when subjects experienced wins, or separately losses, from their risky choices. We contrasted decision trials against very similar comparison trials requiring no decisions, using whole-brain BOLD-response analyses of group differences, corrected for multiple comparisons. During decision-making ASD boys showed hypoactivation in numerous brain regions robustly activated by controls, including orbitofrontal and dorsolateral prefrontal cortices, anterior cingulate, basal ganglia, insula, amygdala, hippocampus, and cerebellum. While experiencing wins, ASD boys had significantly less activity than controls in anterior cingulate, temporal regions, and cerebellum, with more activity nowhere. During losses ASD boys had significantly more activity than controls in orbitofrontal cortex, dorsolateral prefrontal cortex, brain stem, and cerebellum, with less activity nowhere.Adolescent boys with ASD had extensive neural hypoactivity during risky decision-making, coupled with decreased activity during reward and increased activity during loss. These neural patterns may underlie the dangerous, excessive, sustained risk-taking of such boys. The findings suggest that the dysphoria, reward

  10. Aberrant Neural Connectivity during Emotional Processing Associated with Posttraumatic Stress.

    Science.gov (United States)

    Sadeh, Naomi; Spielberg, Jeffrey M; Warren, Stacie L; Miller, Gregory A; Heller, Wendy

    2014-11-01

    Given the complexity of the brain, characterizing relations among distributed brain regions is likely essential to describing the neural instantiation of posttraumatic stress symptoms. This study examined patterns of functional connectivity among key brain regions implicated in the pathophysiology of posttraumatic stress disorder (PTSD) in 35 trauma-exposed adults using an emotion-word Stroop task. PTSD symptom severity (particularly hyperarousal symptoms) moderated amygdala-mPFC coupling during the processing of unpleasant words, and this moderation correlated positively with reported real-world impairment and amygdala reactivity. Reexperiencing severity moderated hippocampus-insula coupling during pleasant and unpleasant words. Results provide evidence that PTSD symptoms differentially moderate functional coupling during emotional interference and underscore the importance of examining network connectivity in research on PTSD. They suggest that hyperarousal is associated with negative mPFC-amygdala coupling and that reexperiencing is associated with altered insula-hippocampus function, patterns of connectivity that may represent separable indicators of dysfunctional inhibitory control during affective processing.

  11. Forward and Reverse Process Models for the Squeeze Casting Process Using Neural Network Based Approaches

    Directory of Open Access Journals (Sweden)

    Manjunath Patel Gowdru Chandrashekarappa

    2014-01-01

    Full Text Available The present research work is focussed to develop an intelligent system to establish the input-output relationship utilizing forward and reverse mappings of artificial neural networks. Forward mapping aims at predicting the density and secondary dendrite arm spacing (SDAS from the known set of squeeze cast process parameters such as time delay, pressure duration, squeezes pressure, pouring temperature, and die temperature. An attempt is also made to meet the industrial requirements of developing the reverse model to predict the recommended squeeze cast parameters for the desired density and SDAS. Two different neural network based approaches have been proposed to carry out the said task, namely, back propagation neural network (BPNN and genetic algorithm neural network (GA-NN. The batch mode of training is employed for both supervised learning networks and requires huge training data. The requirement of huge training data is generated artificially at random using regression equation derived through real experiments carried out earlier by the same authors. The performances of BPNN and GA-NN models are compared among themselves with those of regression for ten test cases. The results show that both models are capable of making better predictions and the models can be effectively used in shop floor in selection of most influential parameters for the desired outputs.

  12. High school music classes enhance the neural processing of speech.

    Science.gov (United States)

    Tierney, Adam; Krizman, Jennifer; Skoe, Erika; Johnston, Kathleen; Kraus, Nina

    2013-01-01

    Should music be a priority in public education? One argument for teaching music in school is that private music instruction relates to enhanced language abilities and neural function. However, the directionality of this relationship is unclear and it is unknown whether school-based music training can produce these enhancements. Here we show that 2 years of group music classes in high school enhance the neural encoding of speech. To tease apart the relationships between music and neural function, we tested high school students participating in either music or fitness-based training. These groups were matched at the onset of training on neural timing, reading ability, and IQ. Auditory brainstem responses were collected to a synthesized speech sound presented in background noise. After 2 years of training, the neural responses of the music training group were earlier than at pre-training, while the neural timing of students in the fitness training group was unchanged. These results represent the strongest evidence to date that in-school music education can cause enhanced speech encoding. The neural benefits of musical training are, therefore, not limited to expensive private instruction early in childhood but can be elicited by cost-effective group instruction during adolescence.

  13. Dissociable neural processes underlying risky decisions for self versus other

    Directory of Open Access Journals (Sweden)

    Daehyun eJung

    2013-03-01

    Full Text Available Previous neuroimaging studies on decision making have mainly focused on decisions on behalf of oneself. Considering that people often make decisions on behalf of others, it is intriguing that there is little neurobiological evidence on how decisions for others differ from those for self. Thus, the present study focused on the direct comparison between risky decisions for self and those for other using functional magnetic resonance imaging (fMRI. Participants (N = 23 were asked to perform a gambling task for themselves (decision-for-self condition or for another person (decision-for-other condition while in the scanner. Their task was to choose between a low-risk option (i.e., win or lose 10 points and a high-risk option (i.e., win or lose 90 points. The winning probabilities of each option varied from 17% to 83%. Compared to choices for others, choices for self were more risk-averse at lower winning probability and more risk-seeking at higher winning probability, perhaps due to stronger affective process during risky decision for self compared to other. The brain activation pattern changed according to the target of the decision, such that reward-related regions were more active in the decision-for-self condition than in the decision-for-other condition, whereas brain regions related to the theory of mind (ToM showed greater activation in the decision-for-other condition than in the decision-for-self condition. A parametric modulation analysis reflecting each individual’s decision model revealed that activation of the amygdala and the dorsomedial prefrontal cortex (DMPFC were associated with value computation for self and for other, respectively, during a risky financial decision. The present study suggests that decisions for self and other may recruit fundamentally distinctive neural processes, which can be mainly characterized by dominant affective/impulsive and cognitive/regulatory processes, respectively.

  14. Dissociable Neural Processes Underlying Risky Decisions for Self Versus Other

    Science.gov (United States)

    Jung, Daehyun; Sul, Sunhae; Kim, Hackjin

    2013-01-01

    Previous neuroimaging studies on decision making have mainly focused on decisions on behalf of oneself. Considering that people often make decisions on behalf of others, it is intriguing that there is little neurobiological evidence on how decisions for others differ from those for oneself. The present study directly compared risky decisions for self with those for another person using functional magnetic resonance imaging (fMRI). Participants were asked to perform a gambling task on behalf of themselves (decision-for-self condition) or another person (decision-for-other condition) while in the scanner. Their task was to choose between a low-risk option (i.e., win or lose 10 points) and a high-risk option (i.e., win or lose 90 points) with variable levels of winning probability. Compared with choices regarding others, those regarding oneself were more risk-averse at lower winning probabilities and more risk-seeking at higher winning probabilities, perhaps due to stronger affective process during risky decisions for oneself compared with those for other. The brain-activation pattern changed according to the target, such that reward-related regions were more active in the decision-for-self condition than in the decision-for-other condition, whereas brain regions related to the theory of mind (ToM) showed greater activation in the decision-for-other condition than in the decision-for-self condition. Parametric modulation analysis using individual decision models revealed that activation of the amygdala and the dorsomedial prefrontal cortex (DMPFC) were associated with value computations for oneself and for another, respectively, during risky financial decisions. The results of the present study suggest that decisions for oneself and for other may recruit fundamentally distinct neural processes, which can be mainly characterized as dominant affective/impulsive and cognitive/regulatory processes, respectively. PMID:23519016

  15. Models of neural dynamics in brain information processing - the developments of 'the decade'

    International Nuclear Information System (INIS)

    Borisyuk, G N; Borisyuk, R M; Kazanovich, Yakov B; Ivanitskii, Genrikh R

    2002-01-01

    Neural network models are discussed that have been developed during the last decade with the purpose of reproducing spatio-temporal patterns of neural activity in different brain structures. The main goal of the modeling was to test hypotheses of synchronization, temporal and phase relations in brain information processing. The models being considered are those of temporal structure of spike sequences, of neural activity dynamics, and oscillatory models of attention and feature integration. (reviews of topical problems)

  16. A novel neural-wavelet approach for process diagnostics and complex system modeling

    Science.gov (United States)

    Gao, Rong

    Neural networks have been effective in several engineering applications because of their learning abilities and robustness. However certain shortcomings, such as slow convergence and local minima, are always associated with neural networks, especially neural networks applied to highly nonlinear and non-stationary problems. These problems can be effectively alleviated by integrating a new powerful tool, wavelets, into conventional neural networks. The multi-resolution analysis and feature localization capabilities of the wavelet transform offer neural networks new possibilities for learning. A neural wavelet network approach developed in this thesis enjoys fast convergence rate with little possibility to be caught at a local minimum. It combines the localization properties of wavelets with the learning abilities of neural networks. Two different testbeds are used for testing the efficiency of the new approach. The first is magnetic flowmeter-based process diagnostics: here we extend previous work, which has demonstrated that wavelet groups contain process information, to more general process diagnostics. A loop at Applied Intelligent Systems Lab (AISL) is used for collecting and analyzing data through the neural-wavelet approach. The research is important for thermal-hydraulic processes in nuclear and other engineering fields. The neural-wavelet approach developed is also tested with data from the electric power grid. More specifically, the neural-wavelet approach is used for performing short-term and mid-term prediction of power load demand. In addition, the feasibility of determining the type of load using the proposed neural wavelet approach is also examined. The notion of cross scale product has been developed as an expedient yet reliable discriminator of loads. Theoretical issues involved in the integration of wavelets and neural networks are discussed and future work outlined.

  17. ALADDIN: a neural model for event classification in dynamic processes

    International Nuclear Information System (INIS)

    Roverso, Davide

    1998-02-01

    ALADDIN is a prototype system which combines fuzzy clustering techniques and artificial neural network (ANN) models in a novel approach to the problem of classifying events in dynamic processes. The main motivation for the development of such a system derived originally from the problem of finding new principled methods to perform alarm structuring/suppression in a nuclear power plant (NPP) alarm system. One such method consists in basing the alarm structuring/suppression on a fast recognition of the event generating the alarms, so that a subset of alarms sufficient to efficiently handle the current fault can be selected to be presented to the operator, minimizing in this way the operator's workload in a potentially stressful situation. The scope of application of a system like ALADDIN goes however beyond alarm handling, to include diagnostic tasks in general. The eventual application of the system to domains other than NPPs was also taken into special consideration during the design phase. In this document we report on the first phase of the ALADDIN project which consisted mainly in a comparative study of a series of ANN-based approaches to event classification, and on the proposal of a first system prototype which is to undergo further tests and, eventually, be integrated in existing alarm, diagnosis, and accident management systems such as CASH, IDS, and CAMS. (author)

  18. Unsupervised Neural Network Quantifies the Cost of Visual Information Processing.

    Directory of Open Access Journals (Sweden)

    Levente L Orbán

    Full Text Available Untrained, "flower-naïve" bumblebees display behavioural preferences when presented with visual properties such as colour, symmetry, spatial frequency and others. Two unsupervised neural networks were implemented to understand the extent to which these models capture elements of bumblebees' unlearned visual preferences towards flower-like visual properties. The computational models, which are variants of Independent Component Analysis and Feature-Extracting Bidirectional Associative Memory, use images of test-patterns that are identical to ones used in behavioural studies. Each model works by decomposing images of floral patterns into meaningful underlying factors. We reconstruct the original floral image using the components and compare the quality of the reconstructed image to the original image. Independent Component Analysis matches behavioural results substantially better across several visual properties. These results are interpreted to support a hypothesis that the temporal and energetic costs of information processing by pollinators served as a selective pressure on floral displays: flowers adapted to pollinators' cognitive constraints.

  19. Sustainability of Welding Process through Bobbin Friction Stir Welding

    Science.gov (United States)

    Sued, M. K.; Samsuri, S. S. M.; Kassim, M. K. A. M.; Nasir, S. N. N. M.

    2018-03-01

    Welding process is in high demand, which required a competitive technology to be adopted. This is important for sustaining the needs of the joining industries without ignoring the impact of the process to the environment. Friction stir welding (FSW) is stated to be benefitting the environment through low energy consumption, which cannot be achieved through traditional arc welding. However, this is not well documented, especially for bobbin friction stir welding (BFSW). Therefore, an investigation is conducted by measuring current consumption of the machine during the BFSW process. From the measurement, different phases of BFSW welding process and its electrical demand are presented. It is found that in general total energy in BFSW is about 130kW inclusive of all identified process phases. The phase that utilise for joint formation is in weld phase that used the highest total energy of 120kWs. The recorded total energy is still far below the traditional welding technology and the conventional friction stir welding (CFSW) energy demand. This indicates that BFSW technology with its vast benefit able to sustain the joining technology in near future.

  20. Neural Networks as a Tool for Georadar Data Processing

    Directory of Open Access Journals (Sweden)

    Szymczyk Piotr

    2015-12-01

    Full Text Available In this article a new neural network based method for automatic classification of ground penetrating radar (GPR traces is proposed. The presented approach is based on a new representation of GPR signals by polynomials approximation. The coefficients of the polynomial (the feature vector are neural network inputs for automatic classification of a special kind of geologic structure—a sinkhole. The analysis and results show that the classifier can effectively distinguish sinkholes from other geologic structures.

  1. Neural network post-processing of grayscale optical correlator

    Science.gov (United States)

    Lu, Thomas T; Hughlett, Casey L.; Zhoua, Hanying; Chao, Tien-Hsin; Hanan, Jay C.

    2005-01-01

    In this paper we present the use of a radial basis function neural network (RBFNN) as a post-processor to assist the optical correlator to identify the objects and to reject false alarms. Image plane features near the correlation peaks are extracted and fed to the neural network for analysis. The approach is capable of handling large number of object variations and filter sets. Preliminary experimental results are presented and the performance is analyzed.

  2. High school music classes enhance the neural processing of speech

    OpenAIRE

    Tierney, Adam; Krizman, Jennifer; Skoe, Erika; Johnston, Kathleen; Kraus, Nina

    2013-01-01

    Should music be a priority in public education? One argument for teaching music in school is that private music instruction relates to enhanced language abilities and neural function. However, the directionality of this relationship is unclear and it is unknown whether school-based music training can produce these enhancements. Here we show that two years of group music classes in high school enhance the subcortical encoding of speech. To tease apart the relationships between music and neural...

  3. Possible promotion of neuronal differentiation in fetal rat brain neural progenitor cells after sustained exposure to static magnetism.

    Science.gov (United States)

    Nakamichi, Noritaka; Ishioka, Yukichi; Hirai, Takao; Ozawa, Shusuke; Tachibana, Masaki; Nakamura, Nobuhiro; Takarada, Takeshi; Yoneda, Yukio

    2009-08-15

    We have previously shown significant potentiation of Ca(2+) influx mediated by N-methyl-D-aspartate receptors, along with decreased microtubules-associated protein-2 (MAP2) expression, in hippocampal neurons cultured under static magnetism without cell death. In this study, we investigated the effects of static magnetism on the functionality of neural progenitor cells endowed to proliferate for self-replication and differentiate into neuronal, astroglial, and oligodendroglial lineages. Neural progenitor cells were isolated from embryonic rat neocortex and hippocampus, followed by culture under static magnetism at 100 mT and subsequent determination of the number of cells immunoreactive for a marker protein of particular progeny lineages. Static magnetism not only significantly decreased proliferation of neural progenitor cells without affecting cell viability, but also promoted differentiation into cells immunoreactive for MAP2 with a concomitant decrease in that for an astroglial marker, irrespective of the presence of differentiation inducers. In neural progenitors cultured under static magnetism, a significant increase was seen in mRNA expression of several activator-type proneural genes, such as Mash1, Math1, and Math3, together with decreased mRNA expression of the repressor type Hes5. These results suggest that sustained static magnetism could suppress proliferation for self-renewal and facilitate differentiation into neurons through promoted expression of activator-type proneural genes by progenitor cells in fetal rat brain.

  4. Neural activity and emotional processing following military deployment: Effects of mild traumatic brain injury and posttraumatic stress disorder.

    Science.gov (United States)

    Zuj, Daniel V; Felmingham, Kim L; Palmer, Matthew A; Lawrence-Wood, Ellie; Van Hooff, Miranda; Lawrence, Andrew J; Bryant, Richard A; McFarlane, Alexander C

    2017-11-01

    Posttraumatic Stress Disorder (PTSD) and mild traumatic brain injury (mTBI) are common comorbidities during military deployment that affect emotional brain processing, yet few studies have examined the independent effects of mTBI and PTSD. The purpose of this study was to examine distinct differences in neural responses to emotional faces in mTBI and PTSD. Twenty-one soldiers reporting high PTSD symptoms were compared to 21 soldiers with low symptoms, and 16 soldiers who reported mTBI-consistent injury and symptoms were compared with 16 soldiers who did not sustain an mTBI. Participants viewed emotional face expressions while their neural activity was recorded (via event-related potentials) prior to and following deployment. The high-PTSD group displayed increased P1 and P2 amplitudes to threatening faces at post-deployment compared to the low-PTSD group. In contrast, the mTBI group displayed reduced face-specific processing (N170 amplitude) to all facial expressions compared to the no-mTBI group. Here, we identified distinctive neural patterns of emotional face processing, with attentional biases towards threatening faces in PTSD, and reduced emotional face processing in mTBI. Copyright © 2017 Elsevier Inc. All rights reserved.

  5. Promoting environmental sustainability via an expert elicitation process

    International Nuclear Information System (INIS)

    Swor, Tom; Canter, Larry

    2011-01-01

    Environmental sustainability (ES) planning was applied to the 981-mile, commercially navigable Ohio River. Navigation improvement needs were identified within the broad study along with actions to restore aquatic and riparian ecological resources to a higher state of sustainability. The actions were identified via an Expert Elicitation Process (EEP) involving aquatic and riparian/terrestrial experts knowledgeable of Ohio River resources. The received information was synthesized into goals for the selected resources (Valued Ecosystem Components - or VECs), actions or measures to attain the goals, and monitoring to evaluate conditions. Finally, 26 types of ES actions were identified and classified into three ES alternatives. These alternatives were then evaluated relative to key decision criteria, and such evaluations, based on pertinent decision criteria, were also conducted for four navigation improvement alternatives. Finally, the best combination of ES and navigation alternatives was identified. The key lessons derived from this use of EEP were that: (1) EEP can support the preliminary identification of ES measures; however, more detailed study of specific designs and cost evaluations will be necessary; (2) the method promotes collaboration between key scientists and policymakers from governmental agencies and private sectors, and such collaboration will ultimately provide the foundation for implementation of sustainability actions; and (3) an effective EEP does not occur by accident, it requires careful planning, implementation, and documentation. - Research Highlights: → Use of an Expert Elicitation Process (EEP) is demonstrated in this study. → EEP was used to identify Environmental Sustainability (ES) needs for the Ohio River. → EEP helped develop consensus among resource experts on ES needs. → EEP promotes collaboration to identify and contribute to common resource goals. → EEP may be used in assessing cumulative effects and formulating restoration

  6. Improving the environmental sustainability of a waste processing plant

    Energy Technology Data Exchange (ETDEWEB)

    Turner, Tom [AREVA RMC, Abingdon, Oxfordshire (United Kingdom); Watson, Stuart [RSRL, Harwell, Oxfordshire (United Kingdom)

    2013-07-01

    This paper describes how the level of environmental sustainability at the Solid Waste Processing plant at Research Sites Restoration Ltd (RSRL) Harwell was measured and improved. It provides reasons to improve environmental performance in an organisation, states best practice on how improvement should be conducted, and gives first-hand experience on how changes were implemented. In this paper sustainability is defined as 'meeting the needs of the present without compromising the ability of future generations to meet their own needs'. A baseline for environmental sustainability was created, by looking at multiple attributes. From this, a matrix was created to show how the baseline environmental performance compared to best practice, and a gap analysis was performed. Results from this analysis showed areas for potential systematic improvement, and actions were created. Nearly all actions were implemented within one year, and environmental sustainability improved significantly. Most improvements cost no money to implement, and the few that did had to pass criteria in a business case. Results from a company-wide survey showed that the vast majority of employees felt that environmental issues were important, and that they were willing to help improve performance. Environmental awareness training was given to everyone in the department, and individuals were given measurable improvement targets. A focus group was set up and met regularly to agree improvements and monitor results. Environmental performance was publicised regularly to highlight successes and seek further engagement and improvement. Improvement ideas were encouraged and managed in a transparent way which showed clear prioritisation and accountability. The culture of environmental improvement changed visibly and results at the end of the first year showed that electricity consumption had reduced by 12.5%, and gas consumption had reduced by 7.3%. In less than two years over UK Pound 60,000 was saved

  7. Improving the environmental sustainability of a waste processing plant

    International Nuclear Information System (INIS)

    Turner, Tom; Watson, Stuart

    2013-01-01

    This paper describes how the level of environmental sustainability at the Solid Waste Processing plant at Research Sites Restoration Ltd (RSRL) Harwell was measured and improved. It provides reasons to improve environmental performance in an organisation, states best practice on how improvement should be conducted, and gives first-hand experience on how changes were implemented. In this paper sustainability is defined as 'meeting the needs of the present without compromising the ability of future generations to meet their own needs'. A baseline for environmental sustainability was created, by looking at multiple attributes. From this, a matrix was created to show how the baseline environmental performance compared to best practice, and a gap analysis was performed. Results from this analysis showed areas for potential systematic improvement, and actions were created. Nearly all actions were implemented within one year, and environmental sustainability improved significantly. Most improvements cost no money to implement, and the few that did had to pass criteria in a business case. Results from a company-wide survey showed that the vast majority of employees felt that environmental issues were important, and that they were willing to help improve performance. Environmental awareness training was given to everyone in the department, and individuals were given measurable improvement targets. A focus group was set up and met regularly to agree improvements and monitor results. Environmental performance was publicised regularly to highlight successes and seek further engagement and improvement. Improvement ideas were encouraged and managed in a transparent way which showed clear prioritisation and accountability. The culture of environmental improvement changed visibly and results at the end of the first year showed that electricity consumption had reduced by 12.5%, and gas consumption had reduced by 7.3%. In less than two years over UK Pound 60,000 was saved

  8. On the Sustainability and Progress of Energy Neutral Mineral Processing

    Directory of Open Access Journals (Sweden)

    Frederik Reitsma

    2018-01-01

    Full Text Available A number of primary ores such as phosphate rock, gold-, copper- and rare earth ores contain considerable amounts of accompanying uranium and other critical materials. Energy neutral mineral processing is the extraction of unconventional uranium during primary ore processing to use it, after enrichment and fuel production, to generate greenhouse gas lean energy in a nuclear reactor. Energy neutrality is reached if the energy produced from the extracted uranium is equal to or larger than the energy required for primary ore processing, uranium extraction, -conversion, -enrichment and -fuel production. This work discusses the sustainability of energy neutral mineral processing and provides an overview of the current progress of a multinational research project on that topic conducted under the umbrella of the International Atomic Energy Agency.

  9. A computer-aided approach for achieving sustainable process design by process intensification

    DEFF Research Database (Denmark)

    Anantasarn, Nateetorn; Suriyapraphadilok, Uthaiporn; Babi, Deenesh Kavi

    2017-01-01

    to generate flowsheet alternatives that satisfy the design targets thereby, minimizing and/or eliminating the process hot-spots. The application of the framework is highlighted through the production of para-xylene via toluene methylation where more sustainable flowsheet alternatives that consist of hybrid......Process intensification can be applied to achieve sustainable process design. In this paper, a systematic, 3-stage synthesis-intensification framework is applied to achieve more sustainable design. In stage 1, the synthesis stage, an objective function and design constraints are defined and a base...... case is synthesized. In stage 2, the design and analysis stage, the base case is analyzed using economic and environmental analyses to identify process hot-spots that are translated into design targets. In stage 3, the innovation design stage, phenomena-based process intensification is performed...

  10. Process identification through modular neural networks and rule extraction (extended abstract)

    NARCIS (Netherlands)

    van der Zwaag, B.J.; Slump, Cornelis H.; Spaanenburg, L.; Blockeel, Hendrik; Denecker, Marc

    2002-01-01

    Monolithic neural networks may be trained from measured data to establish knowledge about the process. Unfortunately, this knowledge is not guaranteed to be found and – if at all – hard to extract. Modular neural networks are better suited for this purpose. Domain-ordered by topology, rule

  11. The impact of high trait social anxiety on neural processing of facial emotion expressions in females.

    Science.gov (United States)

    Felmingham, Kim L; Stewart, Laura F; Kemp, Andrew H; Carr, Andrea R

    2016-05-01

    A cognitive model of social anxiety predicts that an early attentional bias leads to greater cognitive processing of social threat signals, whereas the vigilance-avoidance model predicts there will be subsequent reduction in cognitive processing. This study tests these models by examining neural responses to social threat stimuli using Event-related potentials (ERP). 19 women with high trait social anxiety and 19 women with low trait social anxiety viewed emotional expressions (angry, disgusted, happy and neutral) in a passive viewing task whilst ERP responses were recorded. The HSA group revealed greater automatic attention, or hypervigilance, to all facial expressions, as indexed by greater N1 amplitude compared to the LSA group. They also showed greater sustained attention and elaborative processing of all facial expressions, indexed by significantly increased P2 and P3 amplitudes compared to the LSA group. These results support cognitive models of social anxiety, but are not consistent with predictions of the vigilance-avoidance model. Copyright © 2016. Published by Elsevier B.V.

  12. Neural Temporal Dynamics of Facial Emotion Processing: Age Effects and Relationship to Cognitive Function

    Directory of Open Access Journals (Sweden)

    Xiaoyan Liao

    2017-06-01

    Full Text Available This study used event-related potentials (ERPs to investigate the effects of age on neural temporal dynamics of processing task-relevant facial expressions and their relationship to cognitive functions. Negative (sad, afraid, angry, and disgusted, positive (happy, and neutral faces were presented to 30 older and 31 young participants who performed a facial emotion categorization task. Behavioral and ERP indices of facial emotion processing were analyzed. An enhanced N170 for negative faces, in addition to intact right-hemispheric N170 for positive faces, was observed in older adults relative to their younger counterparts. Moreover, older adults demonstrated an attenuated within-group N170 laterality effect for neutral faces, while younger adults showed the opposite pattern. Furthermore, older adults exhibited sustained temporo-occipital negativity deflection over the time range of 200–500 ms post-stimulus, while young adults showed posterior positivity and subsequent emotion-specific frontal negativity deflections. In older adults, decreased accuracy for labeling negative faces was positively correlated with Montreal Cognitive Assessment Scores, and accuracy for labeling neutral faces was negatively correlated with age. These findings suggest that older people may exert more effort in structural encoding for negative faces and there are different response patterns for the categorization of different facial emotions. Cognitive functioning may be related to facial emotion categorization deficits observed in older adults. This may not be attributable to positivity effects: it may represent a selective deficit for the processing of negative facial expressions in older adults.

  13. Learning-induced neural plasticity of speech processing before birth.

    Science.gov (United States)

    Partanen, Eino; Kujala, Teija; Näätänen, Risto; Liitola, Auli; Sambeth, Anke; Huotilainen, Minna

    2013-09-10

    Learning, the foundation of adaptive and intelligent behavior, is based on plastic changes in neural assemblies, reflected by the modulation of electric brain responses. In infancy, auditory learning implicates the formation and strengthening of neural long-term memory traces, improving discrimination skills, in particular those forming the prerequisites for speech perception and understanding. Although previous behavioral observations show that newborns react differentially to unfamiliar sounds vs. familiar sound material that they were exposed to as fetuses, the neural basis of fetal learning has not thus far been investigated. Here we demonstrate direct neural correlates of human fetal learning of speech-like auditory stimuli. We presented variants of words to fetuses; unlike infants with no exposure to these stimuli, the exposed fetuses showed enhanced brain activity (mismatch responses) in response to pitch changes for the trained variants after birth. Furthermore, a significant correlation existed between the amount of prenatal exposure and brain activity, with greater activity being associated with a higher amount of prenatal speech exposure. Moreover, the learning effect was generalized to other types of similar speech sounds not included in the training material. Consequently, our results indicate neural commitment specifically tuned to the speech features heard before birth and their memory representations.

  14. Neural Generalized Predictive Control of a non-linear Process

    DEFF Research Database (Denmark)

    Sørensen, Paul Haase; Nørgård, Peter Magnus; Ravn, Ole

    1998-01-01

    The use of neural network in non-linear control is made difficult by the fact the stability and robustness is not guaranteed and that the implementation in real time is non-trivial. In this paper we introduce a predictive controller based on a neural network model which has promising stability qu...... detail and discuss the implementation difficulties. The neural generalized predictive controller is tested on a pneumatic servo sys-tem.......The use of neural network in non-linear control is made difficult by the fact the stability and robustness is not guaranteed and that the implementation in real time is non-trivial. In this paper we introduce a predictive controller based on a neural network model which has promising stability...... qualities. The controller is a non-linear version of the well-known generalized predictive controller developed in linear control theory. It involves minimization of a cost function which in the present case has to be done numerically. Therefore, we develop the numerical algorithms necessary in substantial...

  15. High school music classes enhance the neural processing of speech

    Directory of Open Access Journals (Sweden)

    Adam eTierney

    2013-12-01

    Full Text Available Should music be a priority in public education? One argument for teaching music in school is that private music instruction relates to enhanced language abilities and neural function. However, the directionality of this relationship is unclear and it is unknown whether school-based music training can produce these enhancements. Here we show that two years of group music classes in high school enhance the subcortical encoding of speech. To tease apart the relationships between music and neural function, we tested high school students participating in either music or fitness-based training. These groups were matched at the onset of training on neural timing, reading ability, and IQ. Auditory brainstem responses were collected to a synthesized speech sound presented in background noise. After 2 years of training, the subcortical responses of the music training group were earlier than at pretraining, while the neural timing of students in the fitness training group was unchanged. These results represent the strongest evidence to date that in-school music education can cause enhanced speech encoding. The neural benefits of musical training are, therefore, not limited to expensive private instruction early in childhood but can be elicited by cost-effective group instruction during adolescence.

  16. Neural signal processing and closed-loop control algorithm design for an implanted neural recording and stimulation system.

    Science.gov (United States)

    Hamilton, Lei; McConley, Marc; Angermueller, Kai; Goldberg, David; Corba, Massimiliano; Kim, Louis; Moran, James; Parks, Philip D; Sang Chin; Widge, Alik S; Dougherty, Darin D; Eskandar, Emad N

    2015-08-01

    A fully autonomous intracranial device is built to continually record neural activities in different parts of the brain, process these sampled signals, decode features that correlate to behaviors and neuropsychiatric states, and use these features to deliver brain stimulation in a closed-loop fashion. In this paper, we describe the sampling and stimulation aspects of such a device. We first describe the signal processing algorithms of two unsupervised spike sorting methods. Next, we describe the LFP time-frequency analysis and feature derivation from the two spike sorting methods. Spike sorting includes a novel approach to constructing a dictionary learning algorithm in a Compressed Sensing (CS) framework. We present a joint prediction scheme to determine the class of neural spikes in the dictionary learning framework; and, the second approach is a modified OSort algorithm which is implemented in a distributed system optimized for power efficiency. Furthermore, sorted spikes and time-frequency analysis of LFP signals can be used to generate derived features (including cross-frequency coupling, spike-field coupling). We then show how these derived features can be used in the design and development of novel decode and closed-loop control algorithms that are optimized to apply deep brain stimulation based on a patient's neuropsychiatric state. For the control algorithm, we define the state vector as representative of a patient's impulsivity, avoidance, inhibition, etc. Controller parameters are optimized to apply stimulation based on the state vector's current state as well as its historical values. The overall algorithm and software design for our implantable neural recording and stimulation system uses an innovative, adaptable, and reprogrammable architecture that enables advancement of the state-of-the-art in closed-loop neural control while also meeting the challenges of system power constraints and concurrent development with ongoing scientific research designed

  17. Neural manufacturing: a novel concept for processing modeling, monitoring, and control

    Science.gov (United States)

    Fu, Chi Y.; Petrich, Loren; Law, Benjamin

    1995-09-01

    Semiconductor fabrication lines have become extremely costly, and achieving a good return from such a high capital investment requires efficient utilization of these expensive facilities. It is highly desirable to shorten processing development time, increase fabrication yield, enhance flexibility, improve quality, and minimize downtime. We propose that these ends can be achieved by applying recent advances in the areas of artificial neural networks, fuzzy logic, machine learning, and genetic algorithms. We use the term neural manufacturing to describe such applications. This paper describes our use of artificial neural networks to improve the monitoring and control of semiconductor process.

  18. Sustainability reporting in public sector organisations: Exploring the relation between the reporting process and organisational change management for sustainability.

    Science.gov (United States)

    Domingues, Ana Rita; Lozano, Rodrigo; Ceulemans, Kim; Ramos, Tomás B

    2017-05-01

    Sustainability Reporting has become a key element in different organisations. Although there have been a number of academic publications discussing the adoption of sustainability reports in the public sector, their numbers have been quite low when compared to those focussing on corporate reports. Additionally, there has been little research on the link between sustainability reporting in Public Sector Organisations (PSOs) and Organisational Change Management for Sustainability (OCMS). This paper focuses on the contribution of sustainability reporting to OCMS. A survey was sent to all PSOs that have published at least one sustainability report based on the GRI guidelines. The study provides a critical analysis of the relation between sustainability reporting and OCMS in PSOs, including the drivers for reporting, the impacts on organisation change management, and the role of stakeholders in the process. Despite still lagging in sustainability reporting journey, PSOs are starting to use sustainability reporting as a communication tool, and this could drive organisational changes for sustainability. Copyright © 2017 Elsevier Ltd. All rights reserved.

  19. Empirical Study on Sustainable Opportunities Recognition. A Polyvinyl Chloride (PVC Joinery Industry Analysis Using Augmented Sustainable Development Process Model

    Directory of Open Access Journals (Sweden)

    Eduard-Gabriel Ceptureanu

    2017-09-01

    Full Text Available This paper analyzes factors influencing recognition of sustainable opportunities by using an augmented sustainability process model. The conceptual model used two main factors, Knowledge and Motivation, and one moderating variable, Social embeddedness. We investigated entrepreneurs from PVC joinery industry and concluded that while market orientation and sustainable entrepreneurial orientation definitely and positively influence sustainable opportunity recognition, others variables like knowledge of the natural/communal environment, awareness of sustainable development or focus on success have less support. Among all variables analyzed, perception of the threat of the natural/communal environment and altruism toward others have the poorest impact on opportunity recognition. Finally, we concluded that social embeddedness has a moderating effect on sustainable opportunity recognition, even though the results were mixed.

  20. Application of neural networks to multiple alarm processing and diagnosis in nuclear power plants

    International Nuclear Information System (INIS)

    Cheon, Se Woo; Chang Soon Heung; Chung, Hak Yeong

    1992-01-01

    This paper presents feasibility studies of multiple alarm processing and diagnosis using neural networks. The back-propagation neural network model is applied to the training of multiple alarm patterns for the identification of failure in a reactor coolant pump (RCP) system. The general mapping capability of the neural network enables to identify a fault easily. The case studies are performed with emphasis on the applicability of the neural network to pattern recognition problems. It is revealed that the neural network model can identify the cause of multiple alarms properly, even when untrained or sensor-failed alarm symptoms are given. It is also shown that multiple failures are easily identified using the symptoms of multiple alarms

  1. Artificial neural network modelling approach for a biomass gasification process in fixed bed gasifiers

    International Nuclear Information System (INIS)

    Mikulandrić, Robert; Lončar, Dražen; Böhning, Dorith; Böhme, Rene; Beckmann, Michael

    2014-01-01

    Highlights: • 2 Different equilibrium models are developed and their performance is analysed. • Neural network prediction models for 2 different fixed bed gasifier types are developed. • The influence of different input parameters on neural network model performance is analysed. • Methodology for neural network model development for different gasifier types is described. • Neural network models are verified for various operating conditions based on measured data. - Abstract: The number of the small and middle-scale biomass gasification combined heat and power plants as well as syngas production plants has been significantly increased in the last decade mostly due to extensive incentives. However, existing issues regarding syngas quality, process efficiency, emissions and environmental standards are preventing biomass gasification technology to become more economically viable. To encounter these issues, special attention is given to the development of mathematical models which can be used for a process analysis or plant control purposes. The presented paper analyses possibilities of neural networks to predict process parameters with high speed and accuracy. After a related literature review and measurement data analysis, different modelling approaches for the process parameter prediction that can be used for an on-line process control were developed and their performance were analysed. Neural network models showed good capability to predict biomass gasification process parameters with reasonable accuracy and speed. Measurement data for the model development, verification and performance analysis were derived from biomass gasification plant operated by Technical University Dresden

  2. Sustainable Acquisition Process Improvement for Naval Facilities Engineering Command

    National Research Council Canada - National Science Library

    Sanders, Erin

    2003-01-01

    .... To meet the new requirements, laws must be implemented through effective policy. For over 6 years, the Navy has been acquiring sustainably designed facilities and has recently set sustainable development policy guidelines...

  3. Environmental assessment for sustainable development: process, actors and practice

    International Nuclear Information System (INIS)

    Andre, P.; Delisle, C.E.; Reveret, J.-P.

    2003-01-01

    Multiple environmental problems afflict our contemporary world and have been the subject of discussions during many international meetings. All declarations resulting from these meetings insist on including environmental problems and on environmental assessment (EA) as an important tool to achieve this. This book aims to reach three objectives. First, it introduces EA to people from different disciplines, and therefore it opens up the perspective of new disciplinary horizons. Second, the authors discuss EA as a socio-political process rather than emphasizing methodologies. Third, this book draws mainly on the experience in Francophone countries which is still poorly disseminated. This book focusses on process and actors. Thus, the subject matter is divided into five major parts: the history and major issues of EA from a sustainable development perspective (Chapters 1 to 3); the actors, i.e. the Project Proponent and consulting firms, the public, the decision maker and international actors (Chapters 4 to 7); methods and tools including public participation (Chapters 8 and 9); processes in practice through step by step processes in practice and case studies (Chapters 10 and 11); and, finally, recent and upcoming developments in EA, including elements of strategic environmental assessment (Chapters 12 and 13). An index facilitates searching for information. The reader is also invited to consult the book's website

  4. SYNAPTIC DEPRESSION IN DEEP NEURAL NETWORKS FOR SPEECH PROCESSING.

    Science.gov (United States)

    Zhang, Wenhao; Li, Hanyu; Yang, Minda; Mesgarani, Nima

    2016-03-01

    A characteristic property of biological neurons is their ability to dynamically change the synaptic efficacy in response to variable input conditions. This mechanism, known as synaptic depression, significantly contributes to the formation of normalized representation of speech features. Synaptic depression also contributes to the robust performance of biological systems. In this paper, we describe how synaptic depression can be modeled and incorporated into deep neural network architectures to improve their generalization ability. We observed that when synaptic depression is added to the hidden layers of a neural network, it reduces the effect of changing background activity in the node activations. In addition, we show that when synaptic depression is included in a deep neural network trained for phoneme classification, the performance of the network improves under noisy conditions not included in the training phase. Our results suggest that more complete neuron models may further reduce the gap between the biological performance and artificial computing, resulting in networks that better generalize to novel signal conditions.

  5. USGCRP's Sustained Assessment Process: Progress to date and future plans

    Science.gov (United States)

    DeAngelo, B. J.; Reidmiller, D.; Lipschultz, F.; Cloyd, E. T.

    2016-12-01

    One of the four main objectives of the U.S. Global Change Research Program's (USGCRP's) Strategic Plan is to "Conduct Sustained Assessments", which seeks to build a process that synthesizes and advances the state of scientific knowledge on global change, develops future scenarios and potential impacts, and evaluates how effectively science is being and can be used to inform and support the Nation's response to climate change. To do so, USGCRP strives to establish a standing capacity to conduct national climate assessments with sectoral and regional information to evaluate climate risks and opportunities, and to inform decision-making, especially with regard to resiliency planning and adaptation measures. Building on the success of the 3rd National Climate Assessment (NCA) (2014), we discuss the range of USGCRP activities that embody the sustained assessment concept. Special reports, such as the recent Climate and Human Health Assessment and upcoming Climate Science Special Report, fill gaps in our understanding and provide crucial building blocks for next NCA report (NCA4). To facilitate the use of consistent assumptions across NCA4, new scenario products for climate, population, and land use will be made available through initiatives such as NOAA's Climate Resilience Toolkit. NCA4 will be informed by user engagement to advance the customization of knowledge. The report will strive to advance our ability to quantify various risks, monetize certain impacts, and communicate the benefits (i.e., avoided impacts) of various mitigation pathways. NCAnet (a national network of climate-interested stakeholders) continues to grow and foster collaborations across levels of governance and within civil society. Finally, USGCRP continues to actively engage with other assessment processes, at international, state, city, and tribal levels, to exchange ideas and to facilitate the potential for "linked" assessments across spatial scales.

  6. Sustainability assessment of novel chemical processes at early stage: application to biobased processes

    NARCIS (Netherlands)

    Patel, A.D.; Meesters, K.; Uil, H. den; Jong, E. de; Blok, K.; Patel, M.K.

    2012-01-01

    Chemical conversions have been a cornerstone of industrial revolution and societal progress. Continuing this progress in a resource constrained world poses a critical challenge which demands the development of innovative chemical processes to meet our energy and material needs in a sustainable way.

  7. Sustainability and the anthropogenic alteration of evolutionary processes

    Directory of Open Access Journals (Sweden)

    John Cairns, Jr.

    2004-08-01

    Full Text Available Persuasive evidence indicates that Earth is now experiencing a major biotic crisis. Even if humankind ceases severe stress on natural systems, the crisis will probably disrupt the basic evolutionary processes that characterized the period preceding the agricultural and industrial revolutions.Proliferation of drug and pesticide resistant species and opportunistic species that thrive in human-dominated ecosystems will become increasingly common. The effect on humankind of altering basic evolutionary processes is uncertain because the understanding of these processes is not robust. The probable result will not be an environment as favorable to humans as the one that has existed for most of human history. Humans probably have altered the environment since Homo sapiens first appeared. However, only in the last two centuries has the degree and rate of change reached levels now considered by many people to be ‘normal’, even though the record shows they are not.Greatly improved technology has facilitated increased exploitation of natural resources to unsustainablelevels. This exploitation, in turn, has led to exponential human population growth, which has depleted natural capital (living systems and the services they provide. Economic globalization has ensured that ecosystems far distant from consumers can be and are profitably exploited. Economicgrowth has become a universal mantra that is coupled with a conviction that such growth can continue indefinitely on a finite planet. A major paradigm shift is essential if sustainable use of the planet is to become a reality.

  8. Parametric models to relate spike train and LFP dynamics with neural information processing.

    Science.gov (United States)

    Banerjee, Arpan; Dean, Heather L; Pesaran, Bijan

    2012-01-01

    Spike trains and local field potentials (LFPs) resulting from extracellular current flows provide a substrate for neural information processing. Understanding the neural code from simultaneous spike-field recordings and subsequent decoding of information processing events will have widespread applications. One way to demonstrate an understanding of the neural code, with particular advantages for the development of applications, is to formulate a parametric statistical model of neural activity and its covariates. Here, we propose a set of parametric spike-field models (unified models) that can be used with existing decoding algorithms to reveal the timing of task or stimulus specific processing. Our proposed unified modeling framework captures the effects of two important features of information processing: time-varying stimulus-driven inputs and ongoing background activity that occurs even in the absence of environmental inputs. We have applied this framework for decoding neural latencies in simulated and experimentally recorded spike-field sessions obtained from the lateral intraparietal area (LIP) of awake, behaving monkeys performing cued look-and-reach movements to spatial targets. Using both simulated and experimental data, we find that estimates of trial-by-trial parameters are not significantly affected by the presence of ongoing background activity. However, including background activity in the unified model improves goodness of fit for predicting individual spiking events. Uncovering the relationship between the model parameters and the timing of movements offers new ways to test hypotheses about the relationship between neural activity and behavior. We obtained significant spike-field onset time correlations from single trials using a previously published data set where significantly strong correlation was only obtained through trial averaging. We also found that unified models extracted a stronger relationship between neural response latency and trial

  9. Changing Professional Demands in Sustainable Regional Development: A Curriculum Design Process to meet Transboundary Competence

    NARCIS (Netherlands)

    Lansu, Angelique; Boon, Jo; Sloep, Peter; van Dam-Mieras, Rietje

    2012-01-01

    Lansu, A., Boon, J., Sloep, P. B., & Van Dam-Mieras, R. (Accepted). Changing Professional Demands in Sustainable Regional Development: A Curriculum Design Process to meet Transboundary Competence. Journal of Cleaner Production. [Special Issue: Learning for Sustainable Development in Regional

  10. Neural Activations of Guided Imagery and Music in Negative Emotional Processing: A Functional MRI Study.

    Science.gov (United States)

    Lee, Sang Eun; Han, Yeji; Park, HyunWook

    2016-01-01

    The Bonny Method of Guided Imagery and Music uses music and imagery to access and explore personal emotions associated with episodic memories. Understanding the neural mechanism of guided imagery and music (GIM) as combined stimuli for emotional processing informs clinical application. We performed functional magnetic resonance imaging (fMRI) to demonstrate neural mechanisms of GIM for negative emotional processing when personal episodic memory is recalled and re-experienced through GIM processes. Twenty-four healthy volunteers participated in the study, which used classical music and verbal instruction stimuli to evoke negative emotions. To analyze the neural mechanism, activated regions associated with negative emotional and episodic memory processing were extracted by conducting volume analyses for the contrast between GIM and guided imagery (GI) or music (M). The GIM stimuli showed increased activation over the M-only stimuli in five neural regions associated with negative emotional and episodic memory processing, including the left amygdala, left anterior cingulate gyrus, left insula, bilateral culmen, and left angular gyrus (AG). Compared with GI alone, GIM showed increased activation in three regions associated with episodic memory processing in the emotional context, including the right posterior cingulate gyrus, bilateral parahippocampal gyrus, and AG. No neural regions related to negative emotional and episodic memory processing showed more activation for M and GI than for GIM. As a combined multimodal stimulus, GIM may increase neural activations related to negative emotions and episodic memory processing. Findings suggest a neural basis for GIM with personal episodic memories affecting cortical and subcortical structures and functions. © the American Music Therapy Association 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  11. From Imitation to Prediction, Data Compression vs Recurrent Neural Networks for Natural Language Processing

    Directory of Open Access Journals (Sweden)

    Juan Andres Laura

    2018-03-01

    Full Text Available In recent studies Recurrent Neural Networks were used for generative processes and their surprising performance can be explained by their ability to create good predictions. In addition, Data Compression is also based on prediction. What the problem comes down to is whether a data compressor could be used to perform as well as recurrent neural networks in the natural language processing tasks of sentiment analysis and automatic text generation. If this is possible, then the problem comes down to determining if a compression algorithm is even more intelligent than a neural network in such tasks. In our journey, a fundamental difference between a Data Compression Algorithm and Recurrent Neural Networks has been discovered.

  12. Neural activity, neural connectivity, and the processing of emotionally valenced information in older adults: links with life satisfaction.

    Science.gov (United States)

    Waldinger, Robert J; Kensinger, Elizabeth A; Schulz, Marc S

    2011-09-01

    This study examines whether differences in late-life well-being are linked to how older adults encode emotionally valenced information. Using fMRI with 39 older adults varying in life satisfaction, we examined how viewing positive and negative images would affect activation and connectivity of an emotion-processing network. Participants engaged most regions within this network more robustly for positive than for negative images, but within the PFC this effect was moderated by life satisfaction, with individuals higher in satisfaction showing lower levels of activity during the processing of positive images. Participants high in satisfaction showed stronger correlations among network regions-particularly between the amygdala and other emotion processing regions-when viewing positive, as compared with negative, images. Participants low in satisfaction showed no valence effect. Findings suggest that late-life satisfaction is linked with how emotion-processing regions are engaged and connected during processing of valenced information. This first demonstration of a link between neural recruitment and late-life well-being suggests that differences in neural network activation and connectivity may account for the preferential encoding of positive information seen in some older adults.

  13. Filtering and spectral processing of 1-D signals using cellular neural networks

    NARCIS (Netherlands)

    Moreira-Tamayo, O.; Pineda de Gyvez, J.

    1996-01-01

    This paper presents cellular neural networks (CNN) for one-dimensional discrete signal processing. Although CNN has been extensively used in image processing applications, little has been done for 1-dimensional signal processing. We propose a novel CNN architecture to carry out these tasks. This

  14. Breakout Prediction Based on BP Neural Network in Continuous Casting Process

    Directory of Open Access Journals (Sweden)

    Zhang Ben-guo

    2016-01-01

    Full Text Available An improved BP neural network model was presented by modifying the learning algorithm of the traditional BP neural network, based on the Levenberg-Marquardt algorithm, and was applied to the breakout prediction system in the continuous casting process. The results showed that the accuracy rate of the model for the temperature pattern of sticking breakout was 96.43%, and the quote rate was 100%, that verified the feasibility of the model.

  15. Study on algorithm of process neural network for soft sensing in sewage disposal system

    Science.gov (United States)

    Liu, Zaiwen; Xue, Hong; Wang, Xiaoyi; Yang, Bin; Lu, Siying

    2006-11-01

    A new method of soft sensing based on process neural network (PNN) for sewage disposal system is represented in the paper. PNN is an extension of traditional neural network, in which the inputs and outputs are time-variation. An aggregation operator is introduced to process neuron, and it makes the neuron network has the ability to deal with the information of space-time two dimensions at the same time, so the data processing enginery of biological neuron is imitated better than traditional neuron. Process neural network with the structure of three layers in which hidden layer is process neuron and input and output are common neurons for soft sensing is discussed. The intelligent soft sensing based on PNN may be used to fulfill measurement of the effluent BOD (Biochemical Oxygen Demand) from sewage disposal system, and a good training result of soft sensing was obtained by the method.

  16. D-FNN Based Modeling and BP Neural Network Decoupling Control of PVC Stripping Process

    Directory of Open Access Journals (Sweden)

    Shu-zhi Gao

    2014-01-01

    Full Text Available PVC stripping process is a kind of complicated industrial process with characteristics of highly nonlinear and time varying. Aiming at the problem of establishing the accurate mathematics model due to the multivariable coupling and big time delay, the dynamic fuzzy neural network (D-FNN is adopted to establish the PVC stripping process model based on the actual process operation datum. Then, the PVC stripping process is decoupled by the distributed neural network decoupling module to obtain two single-input-single-output (SISO subsystems (slurry flow to top tower temperature and steam flow to bottom tower temperature. Finally, the PID controller based on BP neural networks is used to control the decoupled PVC stripper system. Simulation results show the effectiveness of the proposed integrated intelligent control method.

  17. EDUCATION PROCESS VISUALIZATION IN METACOGNITION DEVELOPMENT AND SUSTAINABILITY

    Directory of Open Access Journals (Sweden)

    Elena Aleksandrovna Makarova

    2017-12-01

    Full Text Available The article reflects on the role of visualization in education. Modern society is characterized by rapid growth of information that people have to process in order to maintain progress and sustainability in science and development of education. The amount of information is growing so quickly that a person is no longer able to perceive actual data about the outside world and process it using traditional methods. The basis of the “image of the world” contains not only concepts, but the semantic images created with the help of visual thinking. In our study we assume that students are quite limited in their knowledge about cognitive phenomena or in their meta-cognition and do relatively little monitoring of their own memory, comprehension, and other cognitive enterprises. But we also assume that every student is potentially capable of meta-cognition, which is thinking of how better to perform cognitive actions and to be aware of how to learn. Developing meta-cognitive awareness is important because it helps learners become more efficacious and more autonomous. For many of them it can be identified as the most effective way of acquiring knowledge. Visualizing the very process of learning can help see how well it is going. Schema theory offers different ways of using schemas, especially in education. So far, there have been researches on schema as a tool for particular skills such as better comprehension, memorizing and retrieval of the knowledge received. It means students can use schemas to better understand the process of learning and skills acquired.

  18. Neural processing of amplitude and formant rise time in dyslexia.

    Science.gov (United States)

    Peter, Varghese; Kalashnikova, Marina; Burnham, Denis

    2016-06-01

    This study aimed to investigate how children with dyslexia weight amplitude rise time (ART) and formant rise time (FRT) cues in phonetic discrimination. Passive mismatch responses (MMR) were recorded for a/ba/-/wa/contrast in a multiple deviant odd-ball paradigm to identify the neural response to cue weighting in 17 children with dyslexia and 17 age-matched control children. The deviant stimuli had either partial or full ART or FRT cues. The results showed that ART did not generate an MMR in either group, whereas both partial and full FRT cues generated MMR in control children while only full FRT cues generated MMR in children with dyslexia. These findings suggest that children, both controls and those with dyslexia, discriminate speech based on FRT cues and not ART cues. However, control children have greater sensitivity to FRT cues in speech compared to children with dyslexia. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  19. Two multichannel integrated circuits for neural recording and signal processing.

    Science.gov (United States)

    Obeid, Iyad; Morizio, James C; Moxon, Karen A; Nicolelis, Miguel A L; Wolf, Patrick D

    2003-02-01

    We have developed, manufactured, and tested two analog CMOS integrated circuit "neurochips" for recording from arrays of densely packed neural electrodes. Device A is a 16-channel buffer consisting of parallel noninverting amplifiers with a gain of 2 V/V. Device B is a 16-channel two-stage analog signal processor with differential amplification and high-pass filtering. It features selectable gains of 250 and 500 V/V as well as reference channel selection. The resulting amplifiers on Device A had a mean gain of 1.99 V/V with an equivalent input noise of 10 microV(rms). Those on Device B had mean gains of 53.4 and 47.4 dB with a high-pass filter pole at 211 Hz and an equivalent input noise of 4.4 microV(rms). Both devices were tested in vivo with electrode arrays implanted in the somatosensory cortex.

  20. Defining Sustainable Universities Following Public Opinion Formation Process

    Science.gov (United States)

    Zaptcioglu Celikdemir, Deniz; Gunay, Gonca; Katrinli, Alev; Penbek Alpbaz, Sebnem

    2017-01-01

    Purpose: The purpose of this paper is to define the sustainable university in Turkey, by considering perspectives of various stakeholders such as experts, intellectual, public, political parties and media using public opinion formation analysis. The paper aims to re-define the "sustainable university" with all dimensions including…

  1. Neural Indices of Semantic Processing in Early Childhood Distinguish Eventual Stuttering Persistence and Recovery

    Science.gov (United States)

    Kreidler, Kathryn; Wray, Amanda Hampton; Usler, Evan; Weber, Christine

    2017-01-01

    Purpose: Maturation of neural processes for language may lag in some children who stutter (CWS), and event-related potentials (ERPs) distinguish CWS who have recovered from those who have persisted. The current study explores whether ERPs indexing semantic processing may distinguish children who will eventually persist in stuttering…

  2. Sustainable building assessment tool: integrating sustainability into current design and building processes

    CSIR Research Space (South Africa)

    Gibberd, Jeremy T

    2008-09-01

    Full Text Available the carrying capacity of supporting ecosystems. ( International Union for Conservation of Nature 1991) These definitions focus on what Wackernagel and Yount call the “socio-economic” and “ecological imperatives” of sustainability (Wackernagel et al, 2000.... Figure 1 Human development and ecological footprints 2003 (from the Living Planet Report) The figure is interesting in that it suggest that only one country (in Latin America and the Caribbean) meets the minimum criteria for sustainability...

  3. Internationally Standardized Reporting (Checklist) on the Sustainable Development Performance of Uranium Mining and Processing Sites

    International Nuclear Information System (INIS)

    Harris, Frank

    2014-01-01

    The Internationally Standardized Reporting Checklist on the Sustainable Development Performance of Uranium Mining and Processing Sites: • A mutual and beneficial work between a core group of uranium miners and nuclear utilities; • An approach based on an long term experience, international policies and sustainable development principles; • A process to optimize the reporting mechanism, tools and efforts; • 11 sections focused on the main sustainable development subject matters known at an operational and headquarter level. The WNA will make available the sustainable development checklist for member utilities and uranium suppliers. Utilities and suppliers are encouraged to use the checklist for sustainable development verification.

  4. Synaptic energy drives the information processing mechanisms in spiking neural networks.

    Science.gov (United States)

    El Laithy, Karim; Bogdan, Martin

    2014-04-01

    Flow of energy and free energy minimization underpins almost every aspect of naturally occurring physical mechanisms. Inspired by this fact this work establishes an energy-based framework that spans the multi-scale range of biological neural systems and integrates synaptic dynamic, synchronous spiking activity and neural states into one consistent working paradigm. Following a bottom-up approach, a hypothetical energy function is proposed for dynamic synaptic models based on the theoretical thermodynamic principles and the Hopfield networks. We show that a synapse exposes stable operating points in terms of its excitatory postsynaptic potential as a function of its synaptic strength. We postulate that synapses in a network operating at these stable points can drive this network to an internal state of synchronous firing. The presented analysis is related to the widely investigated temporal coherent activities (cell assemblies) over a certain range of time scales (binding-by-synchrony). This introduces a novel explanation of the observed (poly)synchronous activities within networks regarding the synaptic (coupling) functionality. On a network level the transitions from one firing scheme to the other express discrete sets of neural states. The neural states exist as long as the network sustains the internal synaptic energy.

  5. Achieving More Sustainable Designs through a Process Synthesis-Intensification Framework

    DEFF Research Database (Denmark)

    Babi, Deenesh Kavi; Woodley, John; Gani, Rafiqul

    2014-01-01

    More sustainable process designs refer to design alternatives that correspond to lowervalues of a set of targeted performance criteria. In this paper, a multi-level frameworkfor process synthesis-intensification that leads to more sustainable process designs ispresented. At the highest level of a...

  6. SustainPro - A tool for systematic process analysis, generation and evaluation of sustainable design alternatives

    DEFF Research Database (Denmark)

    Carvalho, Ana; Matos, Henrique A.; Gani, Rafiqul

    2013-01-01

    the user through the necessary steps according to work-flow of the implemented methodology. At the end the design alternatives, are evaluated using environmental impact assessment tools and safety indices. The extended features of the methodology incorporate Life Cycle Assessment analysis and economic....... The software tool is based on the implementation of an extended systematic methodology for sustainable process design (Carvalho et al. 2008 and Carvalho et al. 2009). Using process information/data such as the process flowsheet, the associated mass / energy balance data and the cost data, SustainPro guides...... analysis. The application and the main features of SustainPro are illustrated through a case study of ß-Galactosidase production....

  7. Sustaining the Exponential Growth of Embedded Digital Signal Processing Capability

    National Research Council Canada - National Science Library

    Shaw, Gary A; Richards, Mark A

    2004-01-01

    .... We conjecture that as IC shrinkage and attendant performance improvements begin to slow, the exponential rate of improvement we have become accustomed to for embedded applications will be sustainable...

  8. Neural information processing in cognition: we start to understand the orchestra, but where is the conductor?

    Directory of Open Access Journals (Sweden)

    Guenther ePalm

    2016-01-01

    Full Text Available Research in neural information processing has been successful in the past, providing useful approaches both to practical problems in computer science and to computational models in neuroscience. Recent developments in the area of cognitive neuroscience present new challenges for a computational or theoretical understanding asking for neural information processing models that fulfill criteria or constraints from cognitive psychology, neuroscience and computational efficiency. The most important of these criteria for the evaluation of present and future contributions to this new emerging field are listed at the end of this article.

  9. Neural Information Processing in Cognition: We Start to Understand the Orchestra, but Where is the Conductor?

    Science.gov (United States)

    Palm, Günther

    2016-01-01

    Research in neural information processing has been successful in the past, providing useful approaches both to practical problems in computer science and to computational models in neuroscience. Recent developments in the area of cognitive neuroscience present new challenges for a computational or theoretical understanding asking for neural information processing models that fulfill criteria or constraints from cognitive psychology, neuroscience and computational efficiency. The most important of these criteria for the evaluation of present and future contributions to this new emerging field are listed at the end of this article. PMID:26858632

  10. A Mathematical Programming Approach to the Optimal Sustainable Product Mix for the Process Industry

    Directory of Open Access Journals (Sweden)

    Noha M. Galal

    2015-09-01

    Full Text Available The increasing concerns about the environment and the depletion of natural resources are the main drivers for the growing interest in sustainability. Manufacturing operations are frequently considered to have an adverse effect on the environment. Hence, the sustainable operation of manufacturing facilities is a vital practice to ensure sustainability. The aim of this paper is to find the optimum product mix of a manufacturing facility to maximize its sustainability. A mixed integer non-linear programming model is developed to specify the product mix in order to maximize a proposed sustainability index (SI of a manufacturing facility. The sustainability index comprises the economic, environmental and social pillars of sustainability in a weighted form using the analytic hierarchy process (AHP. The model results allow the identification of the prospective improvements of manufacturing sustainability.

  11. Modeling of an industrial process of pleuromutilin fermentation using feed-forward neural networks

    Directory of Open Access Journals (Sweden)

    L. Khaouane

    2013-03-01

    Full Text Available This work investigates the use of artificial neural networks in modeling an industrial fermentation process of Pleuromutilin produced by Pleurotus mutilus in a fed-batch mode. Three feed-forward neural network models characterized by a similar structure (five neurons in the input layer, one hidden layer and one neuron in the output layer are constructed and optimized with the aim to predict the evolution of three main bioprocess variables: biomass, substrate and product. Results show a good fit between the predicted and experimental values for each model (the root mean squared errors were 0.4624% - 0.1234 g/L and 0.0016 mg/g respectively. Furthermore, the comparison between the optimized models and the unstructured kinetic models in terms of simulation results shows that neural network models gave more significant results. These results encourage further studies to integrate the mathematical formulae extracted from these models into an industrial control loop of the process.

  12. Erythropoietin reduces neural and cognitive processing of fear in human models of antidepressant drug action

    DEFF Research Database (Denmark)

    Miskowiak, Kamilla; O'Sullivan, Ursula; Harmer, Catherine J

    2007-01-01

    with reduced attention to fear. Erythropoietin additionally reduced recognition of fearful facial expressions without affecting recognition of other emotional expressions. These actions occurred in the absence of changes in hematological parameters. CONCLUSIONS: The present study demonstrates that Epo directly......) versus saline on the neural processing of happy and fearful faces in 23 healthy volunteers. Facial expression recognition was assessed outside the scanner. RESULTS: One week after administration, Epo reduced neural response to fearful versus neutral faces in the occipito-parietal cortex consistent...... study aimed to explore the effects of Epo on neural and behavioral measures of emotional processing relevant for depression and the effects of conventional antidepressant medication. METHODS: In the present study, we used functional magnetic resonance imaging to explore the effects of Epo (40,000 IU...

  13. Neural correlates of olfactory processing in congenital blindness

    DEFF Research Database (Denmark)

    Kupers, R; Beaulieu-Lefebvre, M; Schneider, F C

    2011-01-01

    Adaptive neuroplastic changes have been well documented in congenitally blind individuals for the processing of tactile and auditory information. By contrast, very few studies have investigated olfactory processing in the absence of vision. There is ample evidence that the olfactory system...... magnetic resonance imaging to measure changes in the blood-oxygenation level-dependent signal in congenitally blind and blindfolded sighted control subjects during a simple odor detection task. We found several group differences in task-related activations. Compared to sighted controls, congenitally blind......, linking it also to olfactory processing in addition to tactile and auditory processing....

  14. Prediction of ferric iron precipitation in bioleaching process using partial least squares and artificial neural network

    Directory of Open Access Journals (Sweden)

    Golmohammadi Hassan

    2013-01-01

    Full Text Available A quantitative structure-property relationship (QSPR study based on partial least squares (PLS and artificial neural network (ANN was developed for the prediction of ferric iron precipitation in bioleaching process. The leaching temperature, initial pH, oxidation/reduction potential (ORP, ferrous concentration and particle size of ore were used as inputs to the network. The output of the model was ferric iron precipitation. The optimal condition of the neural network was obtained by adjusting various parameters by trial-and-error. After optimization and training of the network according to back-propagation algorithm, a 5-5-1 neural network was generated for prediction of ferric iron precipitation. The root mean square error for the neural network calculated ferric iron precipitation for training, prediction and validation set are 32.860, 40.739 and 35.890, respectively, which are smaller than those obtained by PLS model (180.972, 165.047 and 149.950, respectively. Results obtained reveal the reliability and good predictivity of neural network model for the prediction of ferric iron precipitation in bioleaching process.

  15. Predictive business process monitoring with LSTM neural networks

    NARCIS (Netherlands)

    Tax, N.; Verenich, I.; La Rosa, M.; Dumas, M.; Pohl, Klaus; Dubois, Eric

    2017-01-01

    Predictive business process monitoring methods exploit logs of completed cases of a process in order to make predictions about running cases thereof. Existing methods in this space are tailor-made for specific prediction tasks. Moreover, their relative accuracy is highly sensitive to the dataset at

  16. Smokers exhibit biased neural processing of smoking and affective images.

    Science.gov (United States)

    Oliver, Jason A; Jentink, Kade G; Drobes, David J; Evans, David E

    2016-08-01

    There has been growing interest in the role that implicit processing of drug cues can play in motivating drug use behavior. However, the extent to which drug cue processing biases relate to the processing biases exhibited to other types of evocative stimuli is largely unknown. The goal of the present study was to determine how the implicit cognitive processing of smoking cues relates to the processing of affective cues using a novel paradigm. Smokers (n = 50) and nonsmokers (n = 38) completed a picture-viewing task, in which participants were presented with a series of smoking, pleasant, unpleasant, and neutral images while engaging in a distractor task designed to direct controlled resources away from conscious processing of image content. Electroencephalogram recordings were obtained throughout the task for extraction of event-related potentials (ERPs). Smokers exhibited differential processing of smoking cues across 3 different ERP indices compared with nonsmokers. Comparable effects were found for pleasant cues on 2 of these indices. Late cognitive processing of smoking and pleasant cues was associated with nicotine dependence and cigarette use. Results suggest that cognitive biases may extend across classes of stimuli among smokers. This raises important questions about the fundamental meaning of cognitive biases, and suggests the need to consider generalized cognitive biases in theories of drug use behavior and interventions based on cognitive bias modification. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  17. Effects of alexithymia and empathy on the neural processing of social and monetary rewards.

    Science.gov (United States)

    Goerlich, Katharina Sophia; Votinov, Mikhail; Lammertz, Sarah E; Winkler, Lina; Spreckelmeyer, Katja N; Habel, Ute; Gründer, Gerhard; Gossen, Anna

    2017-07-01

    Empathy has been found to affect the neural processing of social and monetary rewards. Alexithymia, a subclinical condition showing a close inverse relationship with empathy is linked to dysfunctions of socio-emotional processing in the brain. Whether alexithymia alters the neural processing of rewards, which is currently unknown. Here, we investigated the influence of both alexithymia and empathy on reward processing using a social incentive delay (SID) task and a monetary incentive delay (MID) task in 45 healthy men undergoing functional magnetic resonance imaging. Controlling for temperament-character dimensions and rejection sensitivity, the relationship of alexithymia and empathy with neural activity in several a priori regions of interest (ROIs) was examined by means of partial correlations, while participants anticipated and received social and monetary rewards. Results were considered significant if they survived Holm-Bonferroni correction for multiple comparisons. Alexithymia modulated neural activity in several ROIs of the emotion and reward network, both during the anticipation of social and monetary rewards and in response to the receipt of monetary rewards. In contrast, empathy did not affect reward anticipation and modulated ROI activity only in response to the receipt of social rewards. These results indicate a significant influence of alexithymia on the processing of social and monetary rewards in the healthy brain.

  18. A preferential design approach for energy-efficient and robust implantable neural signal processing hardware.

    Science.gov (United States)

    Narasimhan, Seetharam; Chiel, Hillel J; Bhunia, Swarup

    2009-01-01

    For implantable neural interface applications, it is important to compress data and analyze spike patterns across multiple channels in real time. Such a computational task for online neural data processing requires an innovative circuit-architecture level design approach for low-power, robust and area-efficient hardware implementation. Conventional microprocessor or Digital Signal Processing (DSP) chips would dissipate too much power and are too large in size for an implantable system. In this paper, we propose a novel hardware design approach, referred to as "Preferential Design" that exploits the nature of the neural signal processing algorithm to achieve a low-voltage, robust and area-efficient implementation using nanoscale process technology. The basic idea is to isolate the critical components with respect to system performance and design them more conservatively compared to the noncritical ones. This allows aggressive voltage scaling for low power operation while ensuring robustness and area efficiency. We have applied the proposed approach to a neural signal processing algorithm using the Discrete Wavelet Transform (DWT) and observed significant improvement in power and robustness over conventional design.

  19. Focused process improvement events: sustainability of impact on process and performance in an academic radiology department.

    Science.gov (United States)

    Rosenkrantz, Andrew B; Lawson, Kirk; Ally, Rosina; Chen, David; Donno, Frank; Rittberg, Steven; Rodriguez, Joan; Recht, Michael P

    2015-01-01

    To evaluate sustainability of impact of rapid, focused process improvement (PI) events on process and performance within an academic radiology department. Our department conducted PI during 2011 and 2012 in CT, MRI, ultrasound, breast imaging, and research billing. PI entailed participation by all stakeholders, facilitation by the department chair, collection of baseline data, meetings during several weeks, definition of performance metrics, creation of an improvement plan, and prompt implementation. We explore common themes among PI events regarding initial impact and durability of changes. We also assess performance in each area pre-PI, immediately post-PI, and at the time of the current study. All PI events achieved an immediate improvement in performance metrics, often entailing both examination volumes and on-time performance. IT-based solutions, process standardization, and redefinition of staff responsibilities were often central in these changes, and participants consistently expressed improved internal leadership and problem-solving ability. Major environmental changes commonly occurred after PI, including a natural disaster with equipment loss, a change in location or services offered, and new enterprise-wide electronic medical record system incorporating new billing and radiology informatics systems, requiring flexibility in the PI implementation plan. Only one PI team conducted regular post-PI follow-up meetings. Sustained improvement was frequently, but not universally, observed: in the long-term following initial PI, measures of examination volume showed continued progressive improvements, whereas measures of operational efficiency remained stable or occasionally declined. Focused PI is generally effective in achieving performance improvement, although a changing environment influences the sustainability of impact. Thus, continued process evaluation and ongoing workflow modifications are warranted. Copyright © 2015 American College of Radiology

  20. A novel joint-processing adaptive nonlinear equalizer using a modular recurrent neural network for chaotic communication systems.

    Science.gov (United States)

    Zhao, Haiquan; Zeng, Xiangping; Zhang, Jiashu; Liu, Yangguang; Wang, Xiaomin; Li, Tianrui

    2011-01-01

    To eliminate nonlinear channel distortion in chaotic communication systems, a novel joint-processing adaptive nonlinear equalizer based on a pipelined recurrent neural network (JPRNN) is proposed, using a modified real-time recurrent learning (RTRL) algorithm. Furthermore, an adaptive amplitude RTRL algorithm is adopted to overcome the deteriorating effect introduced by the nesting process. Computer simulations illustrate that the proposed equalizer outperforms the pipelined recurrent neural network (PRNN) and recurrent neural network (RNN) equalizers. Copyright © 2010 Elsevier Ltd. All rights reserved.

  1. Neural basis of uncertain cue processing in trait anxiety.

    Science.gov (United States)

    Zhang, Meng; Ma, Chao; Luo, Yanyan; Li, Ji; Li, Qingwei; Liu, Yijun; Ding, Cody; Qiu, Jiang

    2016-02-19

    Individuals with high trait anxiety form a non-clinical group with a predisposition for an anxiety-related bias in emotional and cognitive processing that is considered by some to be a prerequisite for psychiatric disorders. Anxious individuals tend to experience more worry under uncertainty, and processing uncertain information is an important, but often overlooked factor in anxiety. So, we decided to explore the brain correlates of processing uncertain information in individuals with high trait anxiety using the learn-test paradigm. Behaviorally, the percentages on memory test and the likelihood ratios of identifying novel stimuli under uncertainty were similar to the certain fear condition, but different from the certain neutral condition. The brain results showed that the visual cortex, bilateral fusiform gyrus, and right parahippocampal gyrus were active during the processing of uncertain cues. Moreover, we found that trait anxiety was positively correlated with the BOLD signal of the right parahippocampal gyrus during the processing of uncertain cues. No significant results were found in the amygdala during uncertain cue processing. These results suggest that memory retrieval is associated with uncertain cue processing, which is underpinned by over-activation of the right parahippocampal gyrus, in individuals with high trait anxiety.

  2. Ethanol production from steam exploded rapeseed straw and the process simulation using artificial neural networks

    DEFF Research Database (Denmark)

    Talebnia, Farid; Mighani, Moein; Rahimnejad, Mostafa

    2015-01-01

    and 67% of maximum theoretical value. Next, data of the experimental runs were exploited for modeling the processes by artificial neural networks (ANNs) and performance of the developed models was evaluated. The ANN-based models showed a great potential for time-course prediction of the studied processes....... Efficiency of the joint network for simulating the whole process was also determined and promising results were obtained....

  3. Understanding human visual processing with Deep Neural Networks

    OpenAIRE

    Thorat, Sushrut

    2016-01-01

    This presentation has 2 parts:1. An introduction to the vision processing - neuroscience, and machine vision.2. Discussion of one of the first papers relating Deep Networks to the visual ventral stream. (Khaligh-Razavi, 2014)

  4. Cellular Neural Network for Real Time Image Processing

    International Nuclear Information System (INIS)

    Vagliasindi, G.; Arena, P.; Fortuna, L.; Mazzitelli, G.; Murari, A.

    2008-01-01

    Since their introduction in 1988, Cellular Nonlinear Networks (CNNs) have found a key role as image processing instruments. Thanks to their structure they are able of processing individual pixels in a parallel way providing fast image processing capabilities that has been applied to a wide range of field among which nuclear fusion. In the last years, indeed, visible and infrared video cameras have become more and more important in tokamak fusion experiments for the twofold aim of understanding the physics and monitoring the safety of the operation. Examining the output of these cameras in real-time can provide significant information for plasma control and safety of the machines. The potentiality of CNNs can be exploited to this aim. To demonstrate the feasibility of the approach, CNN image processing has been applied to several tasks both at the Frascati Tokamak Upgrade (FTU) and the Joint European Torus (JET)

  5. The neural bases of spatial frequency processing during scene perception

    Science.gov (United States)

    Kauffmann, Louise; Ramanoël, Stephen; Peyrin, Carole

    2014-01-01

    Theories on visual perception agree that scenes are processed in terms of spatial frequencies. Low spatial frequencies (LSF) carry coarse information whereas high spatial frequencies (HSF) carry fine details of the scene. However, how and where spatial frequencies are processed within the brain remain unresolved questions. The present review addresses these issues and aims to identify the cerebral regions differentially involved in low and high spatial frequency processing, and to clarify their attributes during scene perception. Results from a number of behavioral and neuroimaging studies suggest that spatial frequency processing is lateralized in both hemispheres, with the right and left hemispheres predominantly involved in the categorization of LSF and HSF scenes, respectively. There is also evidence that spatial frequency processing is retinotopically mapped in the visual cortex. HSF scenes (as opposed to LSF) activate occipital areas in relation to foveal representations, while categorization of LSF scenes (as opposed to HSF) activates occipital areas in relation to more peripheral representations. Concomitantly, a number of studies have demonstrated that LSF information may reach high-order areas rapidly, allowing an initial coarse parsing of the visual scene, which could then be sent back through feedback into the occipito-temporal cortex to guide finer HSF-based analysis. Finally, the review addresses spatial frequency processing within scene-selective regions areas of the occipito-temporal cortex. PMID:24847226

  6. Prediction of deformations of steel plate by artificial neural network in forming process with induction heating

    International Nuclear Information System (INIS)

    Nguyen, Truong Thinh; Yang, Young Soo; Bae, Kang Yul; Choi, Sung Nam

    2009-01-01

    To control a heat source easily in the forming process of steel plate with heating, the electro-magnetic induction process has been used as a substitute of the flame heating process. However, only few studies have analyzed the deformation of a workpiece in the induction heating process by using a mathematical model. This is mainly due to the difficulty of modeling the heat flux from the inductor traveling on the conductive plate during the induction process. In this study, the heat flux distribution over a steel plate during the induction process is first analyzed by a numerical method with the assumption that the process is in a quasi-stationary state around the inductor and also that the heat flux itself greatly depends on the temperature of the workpiece. With the heat flux, heat flow and thermo-mechanical analyses on the plate to obtain deformations during the heating process are then performed with a commercial FEM program for 34 combinations of heating parameters. An artificial neural network is proposed to build a simplified relationship between deformations and heating parameters that can be easily utilized to predict deformations of steel plate with a wide range of heating parameters in the heating process. After its architecture is optimized, the artificial neural network is trained with the deformations obtained from the FEM analyses as outputs and the related heating parameters as inputs. The predicted outputs from the neural network are compared with those of the experiments and the numerical results. They are in good agreement

  7. Level of Processing Modulates the Neural Correlates of Emotional Memory Formation

    Science.gov (United States)

    Ritchey, Maureen; LaBar, Kevin S.; Cabeza, Roberto

    2011-01-01

    Emotion is known to influence multiple aspects of memory formation, including the initial encoding of the memory trace and its consolidation over time. However, the neural mechanisms whereby emotion impacts memory encoding remain largely unexplored. The present study used a levels-of-processing manipulation to characterize the impact of emotion on…

  8. Specific and Nonspecific Neural Activity during Selective Processing of Visual Representations in Working Memory

    Science.gov (United States)

    Oh, Hwamee; Leung, Hoi-Chung

    2010-01-01

    In this fMRI study, we investigated prefrontal cortex (PFC) and visual association regions during selective information processing. We recorded behavioral responses and neural activity during a delayed recognition task with a cue presented during the delay period. A specific cue ("Face" or "Scene") was used to indicate which one of the two…

  9. Is There Neural Evidence for an Evidence Accumulation Process in Memory Decisions?

    NARCIS (Netherlands)

    van Vugt, Marieke K; Beulen, Marijke A; Taatgen, Niels A

    2016-01-01

    Models of evidence accumulation have been very successful at describing human decision making behavior. Recent years have also seen the first reports of neural correlates of this accumulation process. However, these studies have mostly focused on perceptual decision making tasks, ignoring the role

  10. Neural reward processing is modulated by approach- and avoidance-related personality traits

    NARCIS (Netherlands)

    Simon, J.J.; Walther, S.; Fiebach, C.J.; Friederich, H.C.; Stippich, C.; Weisbrod, M.; Kaiser, S.

    2009-01-01

    The neural processing of reward can be differentiated into two sub-components with different functions, "wanting" (i.e., the expectation of a reward which includes appetitive and motivational components) and "liking" (i.e., the hedonic impact experienced during the receipt of a reward), involving

  11. Neural Substrates for Processing Task-Irrelevant Sad Images in Adolescents

    Science.gov (United States)

    Wang, Lihong; Huettel, Scott; De Bellis, Michael D.

    2008-01-01

    Neural systems related to cognitive and emotional processing were examined in adolescents using event-related functional magnetic resonance imaging (fMRI). Ten healthy adolescents performed an emotional oddball task. Subjects detected infrequent circles (targets) within a continual stream of phase-scrambled images (standards). Sad and neutral…

  12. Sadness is unique: Neural processing of emotions in speech prosody in musicians and non-musicians

    Directory of Open Access Journals (Sweden)

    Mona ePark

    2015-01-01

    Full Text Available Musical training has been shown to have positive effects on several aspects of speech processing, however, the effects of musical training on the neural processing of speech prosody conveying distinct emotions are yet to be better understood. We used functional magnetic resonance imaging (fMRI to investigate whether the neural responses to speech prosody conveying happiness, sadness, and fear differ between musicians and non-musicians. Differences in processing of emotional speech prosody between the two groups were only observed when sadness was expressed. Musicians showed increased activation in the middle frontal gyrus, the anterior medial prefrontal cortex, the posterior cingulate cortex and the retrosplenial cortex. Our results suggest an increased sensitivity of emotional processing in musicians with respect to sadness expressed in speech, possibly reflecting empathic processes.

  13. Application of fuzzy neural network technologies in management of transport and logistics processes in Arctic

    Science.gov (United States)

    Levchenko, N. G.; Glushkov, S. V.; Sobolevskaya, E. Yu; Orlov, A. P.

    2018-05-01

    The method of modeling the transport and logistics process using fuzzy neural network technologies has been considered. The analysis of the implemented fuzzy neural network model of the information management system of transnational multimodal transportation of the process showed the expediency of applying this method to the management of transport and logistics processes in the Arctic and Subarctic conditions. The modular architecture of this model can be expanded by incorporating additional modules, since the working conditions in the Arctic and the subarctic themselves will present more and more realistic tasks. The architecture allows increasing the information management system, without affecting the system or the method itself. The model has a wide range of application possibilities, including: analysis of the situation and behavior of interacting elements; dynamic monitoring and diagnostics of management processes; simulation of real events and processes; prediction and prevention of critical situations.

  14. Influence of neural adaptation on dynamics and equilibrium state of neural activities in a ring neural network

    Science.gov (United States)

    Takiyama, Ken

    2017-12-01

    How neural adaptation affects neural information processing (i.e. the dynamics and equilibrium state of neural activities) is a central question in computational neuroscience. In my previous works, I analytically clarified the dynamics and equilibrium state of neural activities in a ring-type neural network model that is widely used to model the visual cortex, motor cortex, and several other brain regions. The neural dynamics and the equilibrium state in the neural network model corresponded to a Bayesian computation and statistically optimal multiple information integration, respectively, under a biologically inspired condition. These results were revealed in an analytically tractable manner; however, adaptation effects were not considered. Here, I analytically reveal how the dynamics and equilibrium state of neural activities in a ring neural network are influenced by spike-frequency adaptation (SFA). SFA is an adaptation that causes gradual inhibition of neural activity when a sustained stimulus is applied, and the strength of this inhibition depends on neural activities. I reveal that SFA plays three roles: (1) SFA amplifies the influence of external input in neural dynamics; (2) SFA allows the history of the external input to affect neural dynamics; and (3) the equilibrium state corresponds to the statistically optimal multiple information integration independent of the existence of SFA. In addition, the equilibrium state in a ring neural network model corresponds to the statistically optimal integration of multiple information sources under biologically inspired conditions, independent of the existence of SFA.

  15. Neural signal processing for identifying failed fuel rods in nuclear reactors

    International Nuclear Information System (INIS)

    Seixas, Jose M. de; Soares Filho, William; Pereira, Wagner C.A.; Teles, Claudio C.B.

    2002-01-01

    Ultrasonic pulses were used for automatic detection of failed nuclear fuel rods. For experimental tests of the proposed method, an assembly prototype of 16 x 16 rods was built by using genuine rods but without fuel inside (just air). Some rods were partially filled with water to simulate cracked rods. Using neural signal processing on the received echoes of the emitted ultrasonic pulses, a detection efficiency of 97% was obtained. Neural detection is shown to outperform other classical discriminating methods and can also reveal important features of the signal structure of the received echoes. (author)

  16. Sustainable Production of Asphalt using Biomass as Primary Process Fuel

    DEFF Research Database (Denmark)

    Bühler, Fabian; Nguyen, Tuong-Van; Elmegaard, Brian

    2016-01-01

    is the heating and drying of aggregate,where natural gas, fuel oil or LPG is burned in a direct-fired rotary dryer. Replacing this energy source with amore sustainable one presents several technical and economic challenges, as high temperatures, short startuptimes and seasonal production variations are required...

  17. Neural analysis of bovine ovaries ultrasound images in the identification process of the corpus luteum

    Science.gov (United States)

    Górna, K.; Jaśkowski, B. M.; Okoń, P.; Czechlowski, M.; Koszela, K.; Zaborowicz, M.; Idziaszek, P.

    2017-07-01

    The aim of the paper is to shown the neural image analysis as a method useful for identifying the development stage of the domestic bovine corpus luteum on digital USG (UltraSonoGraphy) images. Corpus luteum (CL) is a transient endocrine gland that develops after ovulation from the follicle secretory cells. The aim of CL is the production of progesterone, which regulates many reproductive functions. In the presented studies, identification of the corpus luteum was carried out on the basis of information contained in ultrasound digital images. Development stage of the corpus luteum was considered in two aspects: just before and middle of domination phase and luteolysis and degradation phase. Prior to the classification, the ultrasound images have been processed using a GLCM (Gray Level Co-occurence Matrix). To generate a classification model, a Neural Networks module implemented in the STATISTICA was used. Five representative parameters describing the ultrasound image were used as learner variables. On the output of the artificial neural network was generated information about the development stage of the corpus luteum. Results of this study indicate that neural image analysis combined with GLCM texture analysis may be a useful tool for identifying the bovine corpus luteum in the context of its development phase. Best-generated artificial neural network model was the structure of MLP (Multi Layer Perceptron) 5:5-17-1:1.

  18. Hybrid digital signal processing and neural networks for automated diagnostics using NDE methods

    International Nuclear Information System (INIS)

    Upadhyaya, B.R.; Yan, W.

    1993-11-01

    The primary purpose of the current research was to develop an integrated approach by combining information compression methods and artificial neural networks for the monitoring of plant components using nondestructive examination data. Specifically, data from eddy current inspection of heat exchanger tubing were utilized to evaluate this technology. The focus of the research was to develop and test various data compression methods (for eddy current data) and the performance of different neural network paradigms for defect classification and defect parameter estimation. Feedforward, fully-connected neural networks, that use the back-propagation algorithm for network training, were implemented for defect classification and defect parameter estimation using a modular network architecture. A large eddy current tube inspection database was acquired from the Metals and Ceramics Division of ORNL. These data were used to study the performance of artificial neural networks for defect type classification and for estimating defect parameters. A PC-based data preprocessing and display program was also developed as part of an expert system for data management and decision making. The results of the analysis showed that for effective (low-error) defect classification and estimation of parameters, it is necessary to identify proper feature vectors using different data representation methods. The integration of data compression and artificial neural networks for information processing was established as an effective technique for automation of diagnostics using nondestructive examination methods

  19. Neural correlates of the processing of self-referent emotional information in bulimia nervosa.

    Science.gov (United States)

    Pringle, A; Ashworth, F; Harmer, C J; Norbury, R; Cooper, M J

    2011-10-01

    There is increasing interest in understanding the roles of distorted beliefs about the self, ostensibly unrelated to eating, weight and shape, in eating disorders (EDs), but little is known about their neural correlates. We therefore used functional magnetic resonance imaging to investigate the neural correlates of self-referent emotional processing in EDs. During the scan, unmedicated patients with bulimia nervosa (n=11) and healthy controls (n=16) responded to personality words previously found to be related to negative self beliefs in EDs and depression. Rating of the negative personality descriptors resulted in reduced activation in patients compared to controls in parietal, occipital and limbic areas including the amygdala. There was no evidence that reduced activity in patients was secondary to increased cognitive control. Different patterns of neural activation between patients and controls may be the result of either habituation to personally relevant negative self beliefs or of emotional blunting in patients. Copyright © 2011 Elsevier Ltd. All rights reserved.

  20. Fault detection and diagnosis for complex multivariable processes using neural networks

    International Nuclear Information System (INIS)

    Weerasinghe, M.

    1998-06-01

    Development of a reliable fault diagnosis method for large-scale industrial plants is laborious and often difficult to achieve due to the complexity of the targeted systems. The main objective of this thesis is to investigate the application of neural networks to the diagnosis of non-catastrophic faults in an industrial nuclear fuel processing plant. The proposed methods were initially developed by application to a simulated chemical process prior to further validation on real industrial data. The diagnosis of faults at a single operating point is first investigated. Statistical data conditioning methods of data scaling and principal component analysis are investigated to facilitate fault classification and reduce the complexity of neural networks. Successful fault diagnosis was achieved with significantly smaller networks than using all process variables as network inputs. Industrial processes often manufacture at various operating points, but demonstrated applications of neural networks for fault diagnosis usually only consider a single (primary) operating point. Developing a standard neural network scheme for fault diagnosis at all operating points would be usually impractical due to the unavailability of suitable training data for less frequently used (secondary) operating points. To overcome this problem, the application of a single neural network for the diagnosis of faults operating at different points is investigated. The data conditioning followed the same techniques as used for the fault diagnosis of a single operating point. The results showed that a single neural network could be successfully used to diagnose faults at operating points other than that it is trained for, and the data conditioning significantly improved the classification. Artificial neural networks have been shown to be an effective tool for process fault diagnosis. However, a main criticism is that details of the procedures taken to reach the fault diagnosis decisions are embedded in

  1. A systems engineering approach to manage the complexity in sustainable chemical product-process design

    DEFF Research Database (Denmark)

    Gani, Rafiqul

    This paper provides a perspective on model-data based solution approaches for chemical product-process design, which consists of finding the identity of the candidate chemical product, designing the process that can sustainably manufacture it and verifying the performance of the product during...... framework can manage the complexity associated with product-process problems very efficiently. Three specific computer-aided tools (ICAS, Sustain-Pro and VPPDLab) have been presented and their applications to product-process design, highlighted....

  2. Analytic network process model for sustainable lean and green manufacturing performance indicator

    Science.gov (United States)

    Aminuddin, Adam Shariff Adli; Nawawi, Mohd Kamal Mohd; Mohamed, Nik Mohd Zuki Nik

    2014-09-01

    Sustainable manufacturing is regarded as the most complex manufacturing paradigm to date as it holds the widest scope of requirements. In addition, its three major pillars of economic, environment and society though distinct, have some overlapping among each of its elements. Even though the concept of sustainability is not new, the development of the performance indicator still needs a lot of improvement due to its multifaceted nature, which requires integrated approach to solve the problem. This paper proposed the best combination of criteria en route a robust sustainable manufacturing performance indicator formation via Analytic Network Process (ANP). The integrated lean, green and sustainable ANP model can be used to comprehend the complex decision system of the sustainability assessment. The finding shows that green manufacturing is more sustainable than lean manufacturing. It also illustrates that procurement practice is the most important criteria in the sustainable manufacturing performance indicator.

  3. Neural processing associated with cognitive and affective Theory of Mind in adolescents and adults.

    Science.gov (United States)

    Sebastian, Catherine L; Fontaine, Nathalie M G; Bird, Geoffrey; Blakemore, Sarah-Jayne; Brito, Stephane A De; McCrory, Eamon J P; Viding, Essi

    2012-01-01

    Theory of Mind (ToM) is the ability to attribute thoughts, intentions and beliefs to others. This involves component processes, including cognitive perspective taking (cognitive ToM) and understanding emotions (affective ToM). This study assessed the distinction and overlap of neural processes involved in these respective components, and also investigated their development between adolescence and adulthood. While data suggest that ToM develops between adolescence and adulthood, these populations have not been compared on cognitive and affective ToM domains. Using fMRI with 15 adolescent (aged 11-16 years) and 15 adult (aged 24-40 years) males, we assessed neural responses during cartoon vignettes requiring cognitive ToM, affective ToM or physical causality comprehension (control). An additional aim was to explore relationships between fMRI data and self-reported empathy. Both cognitive and affective ToM conditions were associated with neural responses in the classic ToM network across both groups, although only affective ToM recruited medial/ventromedial PFC (mPFC/vmPFC). Adolescents additionally activated vmPFC more than did adults during affective ToM. The specificity of the mPFC/vmPFC response during affective ToM supports evidence from lesion studies suggesting that vmPFC may integrate affective information during ToM. Furthermore, the differential neural response in vmPFC between adult and adolescent groups indicates developmental changes in affective ToM processing.

  4. Long-Term Alterations in Neural and Endocrine Processes Induced by Motherhood

    Science.gov (United States)

    Bridges, Robert S.

    2015-01-01

    The reproductive experience of pregnancy, lactation and motherhood can significantly remodel the female’s biological state, affecting endocrine, neuroendocrine, neural, and immunological processes. The brain, pituitary gland, liver, thymus, and mammary tissue are among the structures that are modified by reproductive experience. The present review that focuses on rodent research, but also includes pertinent studies in sheep and other species, identifies specific changes in these processes brought about by the biological states of pregnancy, parturition, and lactation and how the components of reproductive experience contribute to the remodeling of the maternal brain and organ systems. Findings indicate that prior parity alters key circulating hormone levels and neural receptor gene expression. Moreover, reproductive experience results in modifications in neural processes and glial support. The possible role of pregnancy-induced neurogenesis is considered in the context of neuroplasticity and behavior, and the effects of reproductive experience on maternal memory, i.e. the retention of maternal behavior, together with anxiety and learning are presented. Together, these sets of findings support the concept that the neural and biological state of the adult female is significantly and dramatically altered on a long-term basis by the experiences of parity and motherhood. Remodeling of the maternal brain and other biological systems is posited to help facilitate adaptations to environmental/ecological challenges as the female raises young and ages. PMID:26388065

  5. Effect of short-term escitalopram treatment on neural activation during emotional processing.

    Science.gov (United States)

    Maron, Eduard; Wall, Matt; Norbury, Ray; Godlewska, Beata; Terbeck, Sylvia; Cowen, Philip; Matthews, Paul; Nutt, David J

    2016-01-01

    Recent functional magnetic resonance (fMRI) imaging studies have revealed that subchronic medication with escitalopram leads to significant reduction in both amygdala and medial frontal gyrus reactivity during processing of emotional faces, suggesting that escitalopram may have a distinguishable modulatory effect on neural activation as compared with other serotonin-selective antidepressants. In this fMRI study we aimed to explore whether short-term medication with escitalopram in healthy volunteers is associated with reduced neural response to emotional processing, and whether this effect is predicted by drug plasma concentration. The neural response to fearful and happy faces was measured before and on day 7 of treatment with escitalopram (10mg) in 15 healthy volunteers and compared with those in a control unmedicated group (n=14). Significantly reduced activation to fearful, but not to happy facial expressions was observed in the bilateral amygdala, cingulate and right medial frontal gyrus following escitalopram medication. This effect was not correlated with plasma drug concentration. In accordance with previous data, we showed that escitalopram exerts its rapid direct effect on emotional processing via attenuation of neural activation in pathways involving medial frontal gyrus and amygdala, an effect that seems to be distinguishable from that of other SSRIs. © The Author(s) 2015.

  6. The role of automaticity and attention in neural processes underlying empathy for happiness, sadness, and anxiety

    Directory of Open Access Journals (Sweden)

    Sylvia A. Morelli

    2013-05-01

    Full Text Available Although many studies have examined the neural basis of experiencing empathy, relatively little is known about how empathic processes are affected by different attentional conditions. Thus, we examined whether instructions to empathize might amplify responses in empathy-related regions and whether cognitive load would diminish the involvement of these regions. 32 participants completed a functional magnetic resonance imaging session assessing empathic responses to individuals experiencing happy, sad, and anxious events. Stimuli were presented under three conditions: watching naturally, while instructed to empathize, and under cognitive load. Across analyses, we found evidence for a core set of neural regions that support empathic processes (dorsomedial prefrontal cortex, DMPFC; medial prefrontal cortex, MPFC; temporoparietal junction, TPJ; amygdala; ventral anterior insula, AI; septal area, SA. Two key regions – the ventral AI and SA – were consistently active across all attentional conditions, suggesting that they are automatically engaged during empathy. In addition, watching versus empathizing with targets was not markedly different and instead led to similar subjective and neural responses to others’ emotional experiences. In contrast, cognitive load reduced the subjective experience of empathy and diminished neural responses in several regions related to empathy (DMPFC, MPFC, TPJ, amygdala and social cognition. The current results reveal how attention impacts empathic processes and provides insight into how empathy may unfold in everyday interactions.

  7. Neural Correlates of Feedback Processing in Decision Making under Risk

    Directory of Open Access Journals (Sweden)

    Beate eSchuermann

    2012-07-01

    Full Text Available Introduction. Event-related brain potentials (ERP provide important information about the sensitivity of the brain to process varying risks. The aim of the present study was to determine how different risk levels are reflected in decision-related ERPs, namely the feedback-related negativity (FRN and the P300. Material and Methods. 20 participants conducted a probabilistic two-choice gambling task while an electroencephalogram was recorded. Choices were provided between a low-risk option yielding low rewards and low losses and a high-risk option yielding high rewards and high losses. While options differed in expected risks, they were equal in expected values and in feedback probabilities. Results. At the behavioral level, participants were generally risk-averse but modulated their risk-taking behavior according to reward history. An early positivity (P200 was enhanced on negative feedbacks in high-risk compared to low-risk options. With regard to the FRN, there were significant amplitude differences between positive and negative feedbacks in high-risk options, but not in low-risk options. While the FRN on negative feedbacks did not vary with decision riskiness, reduced amplitudes were found for positive feedbacks in high-risk relative to low-risk choices. P300 amplitudes were larger in high-risk decisions, and in an additive way, after negative compared to positive feedback. Discussion. The present study revealed significant influences of risk and valence processing on ERPs. FRN findings suggest that the reward prediction error signal is increased after high-risk decisions. The increased P200 on negative feedback in risky decisions suggests that large negative prediction errors are processed as early as in the P200 time range. The later P300 amplitude is sensitive to feedback valence as well as to the risk of a decision. Thus, the P300 carries additional information for reward processing, mainly the enhanced motivational significance of risky

  8. Neural correlates of audiovisual speech processing in a second language.

    Science.gov (United States)

    Barrós-Loscertales, Alfonso; Ventura-Campos, Noelia; Visser, Maya; Alsius, Agnès; Pallier, Christophe; Avila Rivera, César; Soto-Faraco, Salvador

    2013-09-01

    Neuroimaging studies of audiovisual speech processing have exclusively addressed listeners' native language (L1). Yet, several behavioural studies now show that AV processing plays an important role in non-native (L2) speech perception. The current fMRI study measured brain activity during auditory, visual, audiovisual congruent and audiovisual incongruent utterances in L1 and L2. BOLD responses to congruent AV speech in the pSTS were stronger than in either unimodal condition in both L1 and L2. Yet no differences in AV processing were expressed according to the language background in this area. Instead, the regions in the bilateral occipital lobe had a stronger congruency effect on the BOLD response (congruent higher than incongruent) in L2 as compared to L1. According to these results, language background differences are predominantly expressed in these unimodal regions, whereas the pSTS is similarly involved in AV integration regardless of language dominance. Copyright © 2013 Elsevier Inc. All rights reserved.

  9. Artificial neural networks in variable process control: application in particleboard manufacture

    Energy Technology Data Exchange (ETDEWEB)

    Esteban, L. G.; Garcia Fernandez, F.; Palacios, P. de; Conde, M.

    2009-07-01

    Artificial neural networks are an efficient tool for modelling production control processes using data from the actual production as well as simulated or design of experiments data. In this study two artificial neural networks were combined with the control process charts and it was checked whether the data obtained by the networks were valid for variable process control in particleboard manufacture. The networks made it possible to obtain the mean and standard deviation of the internal bond strength of the particleboard within acceptable margins using known data of thickness, density, moisture content, swelling and absorption. The networks obtained met the acceptance criteria for test values from non-standard test methods, as well as the criteria for using these values in statistical process control. (Author) 47 refs.

  10. Sustained NMDA receptor hypofunction induces compromised neural systems integration and schizophrenia-like alterations in functional brain networks.

    Science.gov (United States)

    Dawson, Neil; Xiao, Xiaolin; McDonald, Martin; Higham, Desmond J; Morris, Brian J; Pratt, Judith A

    2014-02-01

    Compromised functional integration between cerebral subsystems and dysfunctional brain network organization may underlie the neurocognitive deficits seen in psychiatric disorders. Applying topological measures from network science to brain imaging data allows the quantification of complex brain network connectivity. While this approach has recently been used to further elucidate the nature of brain dysfunction in schizophrenia, the value of applying this approach in preclinical models of psychiatric disease has not been recognized. For the first time, we apply both established and recently derived algorithms from network science (graph theory) to functional brain imaging data from rats treated subchronically with the N-methyl-D-aspartic acid (NMDA) receptor antagonist phencyclidine (PCP). We show that subchronic PCP treatment induces alterations in the global properties of functional brain networks akin to those reported in schizophrenia. Furthermore, we show that subchronic PCP treatment induces compromised functional integration between distributed neural systems, including between the prefrontal cortex and hippocampus, that have established roles in cognition through, in part, the promotion of thalamic dysconnectivity. We also show that subchronic PCP treatment promotes the functional disintegration of discrete cerebral subsystems and also alters the connectivity of neurotransmitter systems strongly implicated in schizophrenia. Therefore, we propose that sustained NMDA receptor hypofunction contributes to the pathophysiology of dysfunctional brain network organization in schizophrenia.

  11. Neural processing of musical meter in musicians and non-musicians.

    Science.gov (United States)

    Zhao, T Christina; Lam, H T Gloria; Sohi, Harkirat; Kuhl, Patricia K

    2017-11-01

    Musical sounds, along with speech, are the most prominent sounds in our daily lives. They are highly dynamic, yet well structured in the temporal domain in a hierarchical manner. The temporal structures enhance the predictability of musical sounds. Western music provides an excellent example: while time intervals between musical notes are highly variable, underlying beats can be realized. The beat-level temporal structure provides a sense of regular pulses. Beats can be further organized into units, giving the percept of alternating strong and weak beats (i.e. metrical structure or meter). Examining neural processing at the meter level offers a unique opportunity to understand how the human brain extracts temporal patterns, predicts future stimuli and optimizes neural resources for processing. The present study addresses two important questions regarding meter processing, using the mismatch negativity (MMN) obtained with electroencephalography (EEG): 1) how tempo (fast vs. slow) and type of metrical structure (duple: two beats per unit vs. triple: three beats per unit) affect the neural processing of metrical structure in non-musically trained individuals, and 2) how early music training modulates the neural processing of metrical structure. Metrical structures were established by patterns of consecutive strong and weak tones (Standard) with occasional violations that disrupted and reset the structure (Deviant). Twenty non-musicians listened passively to these tones while their neural activities were recorded. MMN indexed the neural sensitivity to the meter violations. Results suggested that MMNs were larger for fast tempo and for triple meter conditions. Further, 20 musically trained individuals were tested using the same methods and the results were compared to the non-musicians. While tempo and meter type similarly influenced MMNs in both groups, musicians overall exhibited significantly reduced MMNs, compared to their non-musician counterparts. Further analyses

  12. Event-driven processing for hardware-efficient neural spike sorting

    Science.gov (United States)

    Liu, Yan; Pereira, João L.; Constandinou, Timothy G.

    2018-02-01

    Objective. The prospect of real-time and on-node spike sorting provides a genuine opportunity to push the envelope of large-scale integrated neural recording systems. In such systems the hardware resources, power requirements and data bandwidth increase linearly with channel count. Event-based (or data-driven) processing can provide here a new efficient means for hardware implementation that is completely activity dependant. In this work, we investigate using continuous-time level-crossing sampling for efficient data representation and subsequent spike processing. Approach. (1) We first compare signals (synthetic neural datasets) encoded with this technique against conventional sampling. (2) We then show how such a representation can be directly exploited by extracting simple time domain features from the bitstream to perform neural spike sorting. (3) The proposed method is implemented in a low power FPGA platform to demonstrate its hardware viability. Main results. It is observed that considerably lower data rates are achievable when using 7 bits or less to represent the signals, whilst maintaining the signal fidelity. Results obtained using both MATLAB and reconfigurable logic hardware (FPGA) indicate that feature extraction and spike sorting accuracies can be achieved with comparable or better accuracy than reference methods whilst also requiring relatively low hardware resources. Significance. By effectively exploiting continuous-time data representation, neural signal processing can be achieved in a completely event-driven manner, reducing both the required resources (memory, complexity) and computations (operations). This will see future large-scale neural systems integrating on-node processing in real-time hardware.

  13. PROCESSING THE INFORMATION CONTENT ON THE BASIS OF FUZZY NEURAL MODEL OF DECISION MAKING

    Directory of Open Access Journals (Sweden)

    Nina V. Komleva

    2013-01-01

    Full Text Available The article is devoted to the issues of mathematical modeling of the decision-making process of information content processing based on the fuzzy neural network TSK. Integral rating assessment of the content, which is necessary for taking a decision about its further usage, is made depended on varying characteristics. Mechanism for building individual trajectory and forming individual competence is provided to make the intellectual content search.

  14. Emotionally anesthetized: media violence induces neural changes during emotional face processing

    OpenAIRE

    Stockdale, Laura A.; Morrison, Robert G.; Kmiecik, Matthew J.; Garbarino, James; Silton, Rebecca L.

    2015-01-01

    Media violence exposure causes increased aggression and decreased prosocial behavior, suggesting that media violence desensitizes people to the emotional experience of others. Alterations in emotional face processing following exposure to media violence may result in desensitization to others’ emotional states. This study used scalp electroencephalography methods to examine the link between exposure to violence and neural changes associated with emotional face processing. Twenty-five particip...

  15. Level of processing modulates the neural correlates of emotional memory formation

    OpenAIRE

    Ritchey, Maureen; LaBar, Kevin S.; Cabeza, Roberto

    2010-01-01

    Emotion is known to influence multiple aspects of memory formation, including the initial encoding of the memory trace and its consolidation over time. However, the neural mechanisms whereby emotion impacts memory encoding remain largely unexplored. The present study employed a levels-of-processing manipulation to characterize the impact of emotion on encoding with and without the influence of elaborative processes. Participants viewed emotionally negative, neutral, and positive scenes under ...

  16. Control System Design for Cylindrical Tank Process Using Neural Model Predictive Control Technique

    Directory of Open Access Journals (Sweden)

    M. Sridevi

    2010-10-01

    Full Text Available Chemical manufacturing and process industry requires innovative technologies for process identification. This paper deals with model identification and control of cylindrical process. Model identification of the process was done using ARMAX technique. A neural model predictive controller was designed for the identified model. The performance of the controllers was evaluated using MATLAB software. The performance of NMPC controller was compared with Smith Predictor controller and IMC controller based on rise time, settling time, overshoot and ISE and it was found that the NMPC controller is better suited for this process.

  17. Who has a stake? How stakeholder processes influence partnership sustainability

    Directory of Open Access Journals (Sweden)

    Mary-Ellen Boyle

    2011-11-01

    Full Text Available As universities attempt to expand their relevance by engaging with local and regional societal challenges, various kinds of partnerships are emerging. A broad range of stakeholders, from both the university and the community, are typically engaged in and influence the development, implementation and perpetuation of these partnerships. This paper juxtaposes analysis of three community-university partnerships in Worcester, Massachusetts, USA, paying particular attention to the partnerships’ stakeholders, and to their relative importance. This research builds upon current understandings of critical factors in partnership sustainability, as these three partnerships have different goals, involve different university and community stakeholders, and are at different points in their organisational history. The fact that they share the same context – the same city – offers a unique opportunity for comparative case study analysis. The theory of stakeholder salience is used to explain findings about partnership sustainability and to make suggestions for strengthening existing partnerships. Specifically, we argue that stakeholder power and legitimacy, along with stakeholder urgency, are key factors in sustaining community-university partnerships. Keywords Community-university partnerships; economic development; community development; stakeholder salience

  18. Disrupted neural processing of emotional faces in psychopathy.

    Science.gov (United States)

    Contreras-Rodríguez, Oren; Pujol, Jesus; Batalla, Iolanda; Harrison, Ben J; Bosque, Javier; Ibern-Regàs, Immaculada; Hernández-Ribas, Rosa; Soriano-Mas, Carles; Deus, Joan; López-Solà, Marina; Pifarré, Josep; Menchón, José M; Cardoner, Narcís

    2014-04-01

    Psychopaths show a reduced ability to recognize emotion facial expressions, which may disturb the interpersonal relationship development and successful social adaptation. Behavioral hypotheses point toward an association between emotion recognition deficits in psychopathy and amygdala dysfunction. Our prediction was that amygdala dysfunction would combine deficient activation with disturbances in functional connectivity with cortical regions of the face-processing network. Twenty-two psychopaths and 22 control subjects were assessed and functional magnetic resonance maps were generated to identify both brain activation and task-induced functional connectivity using psychophysiological interaction analysis during an emotional face-matching task. Results showed significant amygdala activation in control subjects only, but differences between study groups did not reach statistical significance. In contrast, psychopaths showed significantly increased activation in visual and prefrontal areas, with this latest activation being associated with psychopaths' affective-interpersonal disturbances. Psychophysiological interaction analyses revealed a reciprocal reduction in functional connectivity between the left amygdala and visual and prefrontal cortices. Our results suggest that emotional stimulation may evoke a relevant cortical response in psychopaths, but a disruption in the processing of emotional faces exists involving the reciprocal functional interaction between the amygdala and neocortex, consistent with the notion of a failure to integrate emotion into cognition in psychopathic individuals.

  19. Neural substrate of the late positive potential in emotional processing

    Science.gov (United States)

    Liu, Yuelu; Huang, Haiqing; McGinnis, Menton; Keil, Andreas; Ding, Mingzhou

    2012-01-01

    The late positive potential (LPP) is a reliable electrophysiological index of emotional perception in humans. Despite years of research the brain structures that contribute to the generation and modulation of LPP are not well understood. Recording EEG and fMRI simultaneously, and applying a recently proposed single-trial ERP analysis method, we addressed the problem by correlating the single-trial LPP amplitude evoked by affective pictures with the blood-oxygen-level-dependent (BOLD) activity. Three results were found. First, relative to neutral pictures, pleasant and unpleasant pictures elicited enhanced LPP, as well as heightened BOLD activity in both visual cortices and emotion-processing structures such as amygdala and prefrontal cortex, consistent with previous findings. Second, the LPP amplitude across three picture categories was significantly correlated with BOLD activity in visual cortices, temporal cortices, amygdala, orbitofrontal cortex, and insula. Third, within each picture category, LPP-BOLD coupling revealed category-specific differences. For pleasant pictures, the LPP amplitude was coupled with BOLD in occipitotemporal junction, medial prefrontal cortex, amygdala, and precuneus, whereas for unpleasant pictures, significant LPP-BOLD correlation was observed in ventrolateral prefrontal cortex, insula, and posterior cingulate cortex. These results suggest that LPP is generated and modulated by an extensive brain network comprised of both cortical and subcortical structures associated with visual and emotional processing and the degree of contribution by each of these structures to the LPP modulation is valence-specific. PMID:23077042

  20. Young Adults with Autism Spectrum Disorder Show Early Atypical Neural Activity during Emotional Face Processing

    Directory of Open Access Journals (Sweden)

    Rachel C. Leung

    2018-02-01

    Full Text Available Social cognition is impaired in autism spectrum disorder (ASD. The ability to perceive and interpret affect is integral to successful social functioning and has an extended developmental course. However, the neural mechanisms underlying emotional face processing in ASD are unclear. Using magnetoencephalography (MEG, the present study explored neural activation during implicit emotional face processing in young adults with and without ASD. Twenty-six young adults with ASD and 26 healthy controls were recruited. Participants indicated the location of a scrambled pattern (target that was presented alongside a happy or angry face. Emotion-related activation sources for each emotion were estimated using the Empirical Bayes Beamformer (pcorr ≤ 0.001 in Statistical Parametric Mapping 12 (SPM12. Emotional faces elicited elevated fusiform, amygdala and anterior insula and reduced anterior cingulate cortex (ACC activity in adults with ASD relative to controls. Within group comparisons revealed that angry vs. happy faces elicited distinct neural activity in typically developing adults; there was no distinction in young adults with ASD. Our data suggest difficulties in affect processing in ASD reflect atypical recruitment of traditional emotional processing areas. These early differences may contribute to difficulties in deriving social reward from faces, ascribing salience to faces, and an immature threat processing system, which collectively could result in deficits in emotional face processing.

  1. Modulated neural processing of Western harmony in folk musicians.

    Science.gov (United States)

    Brattico, Elvira; Tupala, Tiina; Glerean, Enrico; Tervaniemi, Mari

    2013-07-01

    A chord deviating from the conventions of Western tonal music elicits an early right anterior negativity (ERAN) in inferofrontal brain regions. Here, we tested whether the ERAN is modulated by expertise in more than one music culture, as typical of folk musicians. Finnish folk musicians and nonmusicians participated in electroencephalography recordings. The cadences consisted of seven chords. In incongruous cadences, the third, fifth, or seventh chord was a Neapolitan. The ERAN to the Neapolitans was enhanced in folk musicians compared to nonmusicians. Folk musicians showed an enhanced P3a for the ending Neapolitan. The Neapolitan at the fifth position was perceived differently and elicited a late enhanced ERAN in folk musicians. Hence, expertise in more than one music culture seems to modify chord processing by enhancing the ERAN to ambivalent chords and the P3a to incongruous chords, and by altering their perceptual attributes. Copyright © 2013 Society for Psychophysiological Research.

  2. Neural correlates of affect processing and aggression in methamphetamine dependence.

    Science.gov (United States)

    Payer, Doris E; Lieberman, Matthew D; London, Edythe D

    2011-03-01

    Methamphetamine abuse is associated with high rates of aggression but few studies have addressed the contributing neurobiological factors. To quantify aggression, investigate function in the amygdala and prefrontal cortex, and assess relationships between brain function and behavior in methamphetamine-dependent individuals. In a case-control study, aggression and brain activation were compared between methamphetamine-dependent and control participants. Participants were recruited from the general community to an academic research center. Thirty-nine methamphetamine-dependent volunteers (16 women) who were abstinent for 7 to 10 days and 37 drug-free control volunteers (18 women) participated in the study; subsets completed self-report and behavioral measures. Functional magnetic resonance imaging (fMRI) was performed on 25 methamphetamine-dependent and 23 control participants. We measured self-reported and perpetrated aggression and self-reported alexithymia. Brain activation was assessed using fMRI during visual processing of facial affect (affect matching) and symbolic processing (affect labeling), the latter representing an incidental form of emotion regulation. Methamphetamine-dependent participants self-reported more aggression and alexithymia than control participants and escalated perpetrated aggression more following provocation. Alexithymia scores correlated with measures of aggression. During affect matching, fMRI showed no differences between groups in amygdala activation but found lower activation in methamphetamine-dependent than control participants in the bilateral ventral inferior frontal gyrus. During affect labeling, participants recruited the dorsal inferior frontal gyrus and exhibited decreased amygdala activity, consistent with successful emotion regulation; there was no group difference in this effect. The magnitude of decrease in amygdala activity during affect labeling correlated inversely with self-reported aggression in control participants

  3. Models of neural dynamics in brain information processing - the developments of 'the decade'

    Energy Technology Data Exchange (ETDEWEB)

    Borisyuk, G N; Borisyuk, R M; Kazanovich, Yakov B [Institute of Mathematical Problems of Biology, Russian Academy of Sciences, Pushchino, Moscow region (Russian Federation); Ivanitskii, Genrikh R [Institute for Theoretical and Experimental Biophysics, Russian Academy of Sciences, Pushchino, Moscow region (Russian Federation)

    2002-10-31

    Neural network models are discussed that have been developed during the last decade with the purpose of reproducing spatio-temporal patterns of neural activity in different brain structures. The main goal of the modeling was to test hypotheses of synchronization, temporal and phase relations in brain information processing. The models being considered are those of temporal structure of spike sequences, of neural activity dynamics, and oscillatory models of attention and feature integration. (reviews of topical problems)

  4. What Can Psychiatric Disorders Tell Us about Neural Processing of the Self?

    Science.gov (United States)

    Zhao, Weihua; Luo, Lizhu; Li, Qin; Kendrick, Keith M

    2013-01-01

    Many psychiatric disorders are associated with abnormal self-processing. While these disorders also have a wide-range of complex, and often heterogeneous sets of symptoms involving different cognitive, emotional, and motor domains, an impaired sense of self can contribute to many of these. Research investigating self-processing in healthy subjects has facilitated identification of changes in specific neural circuits which may cause altered self-processing in psychiatric disorders. While there is evidence for altered self-processing in many psychiatric disorders, here we will focus on four of the most studied ones, schizophrenia, autism spectrum disorder (ASD), major depression, and borderline personality disorder (BPD). We review evidence for dysfunction in two different neural systems implicated in self-processing, namely the cortical midline system (CMS) and the mirror neuron system (MNS), as well as contributions from altered inter-hemispheric connectivity (IHC). We conclude that while abnormalities in frontal-parietal activity and/or connectivity in the CMS are common to all four disorders there is more disruption of integration between frontal and parietal regions resulting in a shift toward parietal control in schizophrenia and ASD which may contribute to the greater severity and delusional aspects of their symptoms. Abnormalities in the MNS and in IHC are also particularly evident in schizophrenia and ASD and may lead to disturbances in sense of agency and the physical self in these two disorders. A better future understanding of how changes in the neural systems sub-serving self-processing contribute to different aspects of symptom abnormality in psychiatric disorders will require that more studies carry out detailed individual assessments of altered self-processing in conjunction with measurements of neural functioning.

  5. Neural processing of speech in children is influenced by bilingual experience

    Science.gov (United States)

    Krizman, Jennifer; Slater, Jessica; Skoe, Erika; Marian, Viorica; Kraus, Nina

    2014-01-01

    Language experience fine-tunes how the auditory system processes sound. For example, bilinguals, relative to monolinguals, have more robust evoked responses to speech that manifest as stronger neural encoding of the fundamental frequency (F0) and greater across-trial consistency. However, it is unknown whether such enhancements increase with increasing second language experience. We predict that F0 amplitude and neural consistency scale with dual-language experience during childhood, such that more years of bilingual experience leads to more robust F0 encoding and greater neural consistency. To test this hypothesis, we recorded auditory brainstem responses to the synthesized syllables ‘ba’ and ‘ga’ in two groups of bilingual children who were matched for age at test (8.4+/−0.67 years) but differed in their age of second language acquisition. One group learned English and Spanish simultaneously from birth (n=13), while the second group learned the two languages sequentially (n=15), spending on average their first four years as monolingual Spanish speakers. We find that simultaneous bilinguals have a larger F0 response to ‘ba’ and ‘ga’ and a more consistent response to ‘ba’ compared to sequential bilinguals. We also demonstrate that these neural enhancements positively relate with years of bilingual experience. These findings support the notion that bilingualism enhances subcortical auditory processing. PMID:25445377

  6. Using the artificial neural network to control the steam turbine heating process

    International Nuclear Information System (INIS)

    Nowak, Grzegorz; Rusin, Andrzej

    2016-01-01

    Highlights: • Inverse Artificial Neural Network has a potential to control the start-up process of a steam turbine. • Two serial neural networks made it possible to model the rotor stress based of steam parameters. • An ANN with feedback enables transient stress modelling with good accuracy. - Abstract: Due to the significant share of renewable energy sources (RES) – wind farms in particular – in the power sector of many countries, power generation systems become sensitive to variable weather conditions. Under unfavourable changes in weather, ensuring required energy supplies involves hasty start-ups of conventional steam power units whose operation should be characterized by higher and higher flexibility. Controlling the process of power engineering machinery operation requires fast predictive models that will make it possible to analyse many parallel scenarios and select the most favourable one. This approach is employed by the algorithm for the inverse neural network control presented in this paper. Based on the current thermal state of the turbine casing, the algorithm controls the steam temperature at the turbine inlet to keep both the start-up rate and the safety of the machine at the allowable level. The method used herein is based on two artificial neural networks (ANN) working in series.

  7. Diminished Neural Processing of Aversive and Rewarding Stimuli During Selective Serotonin Reuptake Inhibitor Treatment

    Science.gov (United States)

    McCabe, Ciara; Mishor, Zevic; Cowen, Philip J.; Harmer, Catherine J.

    2010-01-01

    Background Selective serotonin reuptake inhibitors (SSRIs) are popular medications for anxiety and depression, but their effectiveness, particularly in patients with prominent symptoms of loss of motivation and pleasure, has been questioned. There are few studies of the effect of SSRIs on neural reward mechanisms in humans. Methods We studied 45 healthy participants who were randomly allocated to receive the SSRI citalopram, the noradrenaline reuptake inhibitor reboxetine, or placebo for 7 days in a double-blind, parallel group design. We used functional magnetic resonance imaging to measure the neural response to rewarding (sight and/or flavor of chocolate) and aversive stimuli (sight of moldy strawberries and/or an unpleasant strawberry taste) on the final day of drug treatment. Results Citalopram reduced activation to the chocolate stimuli in the ventral striatum and the ventral medial/orbitofrontal cortex. In contrast, reboxetine did not suppress ventral striatal activity and in fact increased neural responses within medial orbitofrontal cortex to reward. Citalopram also decreased neural responses to the aversive stimuli conditions in key “punishment” areas such as the lateral orbitofrontal cortex. Reboxetine produced a similar, although weaker effect. Conclusions Our findings are the first to show that treatment with SSRIs can diminish the neural processing of both rewarding and aversive stimuli. The ability of SSRIs to decrease neural responses to reward might underlie the questioned efficacy of SSRIs in depressive conditions characterized by decreased motivation and anhedonia and could also account for the experience of emotional blunting described by some patients during SSRI treatment. PMID:20034615

  8. Modeling fMRI signals can provide insights into neural processing in the cerebral cortex.

    Science.gov (United States)

    Vanni, Simo; Sharifian, Fariba; Heikkinen, Hanna; Vigário, Ricardo

    2015-08-01

    Every stimulus or task activates multiple areas in the mammalian cortex. These distributed activations can be measured with functional magnetic resonance imaging (fMRI), which has the best spatial resolution among the noninvasive brain imaging methods. Unfortunately, the relationship between the fMRI activations and distributed cortical processing has remained unclear, both because the coupling between neural and fMRI activations has remained poorly understood and because fMRI voxels are too large to directly sense the local neural events. To get an idea of the local processing given the macroscopic data, we need models to simulate the neural activity and to provide output that can be compared with fMRI data. Such models can describe neural mechanisms as mathematical functions between input and output in a specific system, with little correspondence to physiological mechanisms. Alternatively, models can be biomimetic, including biological details with straightforward correspondence to experimental data. After careful balancing between complexity, computational efficiency, and realism, a biomimetic simulation should be able to provide insight into how biological structures or functions contribute to actual data processing as well as to promote theory-driven neuroscience experiments. This review analyzes the requirements for validating system-level computational models with fMRI. In particular, we study mesoscopic biomimetic models, which include a limited set of details from real-life networks and enable system-level simulations of neural mass action. In addition, we discuss how recent developments in neurophysiology and biophysics may significantly advance the modelling of fMRI signals. Copyright © 2015 the American Physiological Society.

  9. Suprathreshold stochastic resonance in neural processing tuned by correlation.

    Science.gov (United States)

    Durrant, Simon; Kang, Yanmei; Stocks, Nigel; Feng, Jianfeng

    2011-07-01

    Suprathreshold stochastic resonance (SSR) is examined in the context of integrate-and-fire neurons, with an emphasis on the role of correlation in the neuronal firing. We employed a model based on a network of spiking neurons which received synaptic inputs modeled by Poisson processes stimulated by a stepped input signal. The smoothed ensemble firing rate provided an output signal, and the mutual information between this signal and the input was calculated for networks with different noise levels and different numbers of neurons. It was found that an SSR effect was present in this context. We then examined a more biophysically plausible scenario where the noise was not controlled directly, but instead was tuned by the correlation between the inputs. The SSR effect remained present in this scenario with nonzero noise providing improved information transmission, and it was found that negative correlation between the inputs was optimal. Finally, an examination of SSR in the context of this model revealed its connection with more traditional stochastic resonance and showed a trade-off between supratheshold and subthreshold components. We discuss these results in the context of existing empirical evidence concerning correlations in neuronal firing.

  10. Beyond the evoked/intrinsic neural process dichotomy

    Directory of Open Access Journals (Sweden)

    Taylor Bolt

    2018-03-01

    Full Text Available Contemporary functional neuroimaging research has increasingly focused on characterization of intrinsic or “spontaneous” brain activity. Analysis of intrinsic activity is often contrasted with analysis of task-evoked activity that has traditionally been the focus of cognitive neuroscience. But does this evoked/intrinsic dichotomy adequately characterize human brain function? Based on empirical data demonstrating a close functional interdependence between intrinsic and task-evoked activity, we argue that the dichotomy between intrinsic and task-evoked activity as unobserved contributions to brain activity is artificial. We present an alternative picture of brain function in which the brain’s spatiotemporal dynamics do not consist of separable intrinsic and task-evoked components, but reflect the enaction of a system of mutual constraints to move the brain into and out of task-appropriate functional configurations. According to this alternative picture, cognitive neuroscientists are tasked with describing both the temporal trajectory of brain activity patterns across time, and the modulation of this trajectory by task states, without separating this process into intrinsic and task-evoked components. We argue that this alternative picture of brain function is best captured in a novel explanatory framework called enabling constraint. Overall, these insights call for a reconceptualization of functional brain activity, and should drive future methodological and empirical efforts.

  11. A quantum theoretical approach to information processing in neural networks

    Science.gov (United States)

    Barahona da Fonseca, José; Barahona da Fonseca, Isabel; Suarez Araujo, Carmen Paz; Simões da Fonseca, José

    2000-05-01

    A reinterpretation of experimental data on learning was used to formulate a law on data acquisition similar to the Hamiltonian of a mechanical system. A matrix of costs in decision making specifies values attributable to a barrier that opposed to hypothesis formation about decision making. The interpretation of the encoding costs as frequencies of oscillatory phenomena leads to a quantum paradigm based in the models of photoelectric effect as well as of a particle against a potential barrier. Cognitive processes are envisaged as complex phenomena represented by structures linked by valence bounds. This metaphor is used to find some prerequisites to certain types of conscious experience as well as to find an explanation for some pathological distortions of cognitive operations as they are represented in the context of the isolobal model. Those quantum phenomena are understood as representing an analogue programming for specific special purpose computations. The formation of complex chemical structures within the context of isolobal theory is understood as an analog quantum paradigm for complex cognitive computations.

  12. Inactivity-induced phrenic and hypoglossal motor facilitation are differentially expressed following intermittent vs. sustained neural apnea

    Science.gov (United States)

    Baertsch, N. A.

    2013-01-01

    Reduced respiratory neural activity elicits a rebound increase in phrenic and hypoglossal motor output known as inactivity-induced phrenic and hypoglossal motor facilitation (iPMF and iHMF, respectively). We hypothesized that, similar to other forms of respiratory plasticity, iPMF and iHMF are pattern sensitive. Central respiratory neural activity was reversibly reduced in ventilated rats by hyperventilating below the CO2 apneic threshold to create brief intermittent neural apneas (5, ∼1.5 min each, separated by 5 min), a single brief massed neural apnea (7.5 min), or a single prolonged neural apnea (30 min). Upon restoration of respiratory neural activity, long-lasting (>60 min) iPMF was apparent following brief intermittent and prolonged, but not brief massed, neural apnea. Further, brief intermittent and prolonged neural apnea elicited an increase in the maximum phrenic response to high CO2, suggesting that iPMF is associated with an increase in phrenic dynamic range. By contrast, only prolonged neural apnea elicited iHMF, which was transient in duration (<15 min). Intermittent, massed, and prolonged neural apnea all elicited a modest transient facilitation of respiratory frequency. These results indicate that iPMF, but not iHMF, is pattern sensitive, and that the response to respiratory neural inactivity is motor pool specific. PMID:23493368

  13. Sustainability indicator system and policy processes in Malaysia: a framework for utilisation and learning.

    Science.gov (United States)

    Hezri, A A

    2004-12-01

    Formulation of effective sustainability indicators for national assessment demands a comprehensive understanding of the utilisation, diffusion and dissemination of information in policy processes. To illustrate the dynamic of sustainability assessment within the context of policy processes, this paper uses a case study of national sustainability indicators development in Malaysia. Subsequently, this paper ascribes the limited achievement of national sustainability assessment in Malaysia to four types of constraints: meta-policy issues; technical capacities; communication concerns; and the inherent knowledge gaps within the indicator developer community vis-a-vis their theoretical limitations. It is proposed that such constraints will be encountered in many countries. Drawing from the literature on public policy, this paper outlines a framework for investigating indicator behaviour within policy processes based on well-established concepts such as knowledge utilisation and policy learning. I conclude this paper by elaborating on the corresponding future challenges that must be addressed before effective integration of sustainability indicators within policy systems can occur.

  14. Eigenanalysis of a neural network for optic flow processing

    International Nuclear Information System (INIS)

    Weber, F; Eichner, H; Borst, A; Cuntz, H

    2008-01-01

    Flies gain information about self-motion during free flight by processing images of the environment moving across their retina. The visual course control center in the brain of the blowfly contains, among others, a population of ten neurons, the so-called vertical system (VS) cells that are mainly sensitive to downward motion. VS cells are assumed to encode information about rotational optic flow induced by self-motion (Krapp and Hengstenberg 1996 Nature 384 463-6). Recent evidence supports a connectivity scheme between the VS cells where neurons with neighboring receptive fields are connected to each other by electrical synapses at the axonal terminals, whereas the boundary neurons in the network are reciprocally coupled via inhibitory synapses (Haag and Borst 2004 Nat. Neurosci. 7 628-34; Farrow et al 2005 J. Neurosci. 25 3985-93; Cuntz et al 2007 Proc. Natl Acad. Sci. USA). Here, we investigate the functional properties of the VS network and its connectivity scheme by reducing a biophysically realistic network to a simplified model, where each cell is represented by a dendritic and axonal compartment only. Eigenanalysis of this model reveals that the whole population of VS cells projects the synaptic input provided from local motion detectors on to its behaviorally relevant components. The two major eigenvectors consist of a horizontal and a slanted line representing the distribution of vertical motion components across the fly's azimuth. They are, thus, ideally suited for reliably encoding translational and rotational whole-field optic flow induced by respective flight maneuvers. The dimensionality reduction compensates for the contrast and texture dependence of the local motion detectors of the correlation-type, which becomes particularly pronounced when confronted with natural images and their highly inhomogeneous contrast distribution

  15. Tenant Recruitment and Support Processes in Sustainability-Profiled Business Incubators

    Science.gov (United States)

    Bank, Natasha; Kanda, Wisdom

    2016-01-01

    Recruitment and support processes in sustainability-profiled incubators have received little research attention. The article addresses this knowledge gap in an empirical investigation of three sustainability-oriented incubators in Sweden, Finland and Germany. The data are based on interviews with managers, stakeholders and tenants in Green Tech…

  16. Sustainability Attitudes and Behavioral Motivations of College Students: Testing the Extended Parallel Process Model

    Science.gov (United States)

    Perrault, Evan K.; Clark, Scott K.

    2018-01-01

    Purpose: A planet that can no longer sustain life is a frightening thought--and one that is often present in mass media messages. Therefore, this study aims to test the components of a classic fear appeal theory, the extended parallel process model (EPPM) and to determine how well its constructs predict sustainability behavioral intentions. This…

  17. Sustainable Chemical Processes and Products. New Design Methodology and Design Tools

    NARCIS (Netherlands)

    Korevaar, G.

    2004-01-01

    The current chemical industry is not sustainable, which leads to the fact that innovation of chemical processes and products is too often hazardous for society in general and the environment in particular. It really is a challenge to implement sustainability considerations in the design activities

  18. An approach to quantitative sustainability assessment in the early stages of process design.

    Science.gov (United States)

    Tugnoli, Alessandro; Santarelli, Francesco; Cozzani, Valerio

    2008-06-15

    A procedure was developed for the quantitative assessment of key performance indicators suitable for the sustainability analysis of alternative processes, mainly addressing the early stages of process design. The methodology was based on the calculation of a set of normalized impact indices allowing a direct comparison of the additional burden of each process alternative on a selected reference area. Innovative reference criteria were developed to compare and aggregate the impact indicators on the basis of the site-specific impact burden and sustainability policy. An aggregation procedure also allows the calculation of overall sustainability performance indicators and of an "impact fingerprint" of each process alternative. The final aim of the method is to support the decision making process during process development, providing a straightforward assessment of the expected sustainability performances. The application of the methodology to case studies concerning alternative waste disposal processes allowed a preliminary screening of the expected critical sustainability impacts of each process. The methodology was shown to provide useful results to address sustainability issues in the early stages of process design.

  19. Optical Calibration Process Developed for Neural-Network-Based Optical Nondestructive Evaluation Method

    Science.gov (United States)

    Decker, Arthur J.

    2004-01-01

    A completely optical calibration process has been developed at Glenn for calibrating a neural-network-based nondestructive evaluation (NDE) method. The NDE method itself detects very small changes in the characteristic patterns or vibration mode shapes of vibrating structures as discussed in many references. The mode shapes or characteristic patterns are recorded using television or electronic holography and change when a structure experiences, for example, cracking, debonds, or variations in fastener properties. An artificial neural network can be trained to be very sensitive to changes in the mode shapes, but quantifying or calibrating that sensitivity in a consistent, meaningful, and deliverable manner has been challenging. The standard calibration approach has been difficult to implement, where the response to damage of the trained neural network is compared with the responses of vibration-measurement sensors. In particular, the vibration-measurement sensors are intrusive, insufficiently sensitive, and not numerous enough. In response to these difficulties, a completely optical alternative to the standard calibration approach was proposed and tested successfully. Specifically, the vibration mode to be monitored for structural damage was intentionally contaminated with known amounts of another mode, and the response of the trained neural network was measured as a function of the peak-to-peak amplitude of the contaminating mode. The neural network calibration technique essentially uses the vibration mode shapes of the undamaged structure as standards against which the changed mode shapes are compared. The published response of the network can be made nearly independent of the contaminating mode, if enough vibration modes are used to train the net. The sensitivity of the neural network can be adjusted for the environment in which the test is to be conducted. The response of a neural network trained with measured vibration patterns for use on a vibration isolation

  20. Energy-efficient neural information processing in individual neurons and neuronal networks.

    Science.gov (United States)

    Yu, Lianchun; Yu, Yuguo

    2017-11-01

    Brains are composed of networks of an enormous number of neurons interconnected with synapses. Neural information is carried by the electrical signals within neurons and the chemical signals among neurons. Generating these electrical and chemical signals is metabolically expensive. The fundamental issue raised here is whether brains have evolved efficient ways of developing an energy-efficient neural code from the molecular level to the circuit level. Here, we summarize the factors and biophysical mechanisms that could contribute to the energy-efficient neural code for processing input signals. The factors range from ion channel kinetics, body temperature, axonal propagation of action potentials, low-probability release of synaptic neurotransmitters, optimal input and noise, the size of neurons and neuronal clusters, excitation/inhibition balance, coding strategy, cortical wiring, and the organization of functional connectivity. Both experimental and computational evidence suggests that neural systems may use these factors to maximize the efficiency of energy consumption in processing neural signals. Studies indicate that efficient energy utilization may be universal in neuronal systems as an evolutionary consequence of the pressure of limited energy. As a result, neuronal connections may be wired in a highly economical manner to lower energy costs and space. Individual neurons within a network may encode independent stimulus components to allow a minimal number of neurons to represent whole stimulus characteristics efficiently. This basic principle may fundamentally change our view of how billions of neurons organize themselves into complex circuits to operate and generate the most powerful intelligent cognition in nature. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  1. Automated processing of measuring information and control processes of eutrophication in water for household purpose, based on artificial neural networks

    Directory of Open Access Journals (Sweden)

    О.М. Безвесільна

    2006-04-01

    Full Text Available  The possibilities of application  informational-computer technologies for automated handling of a measuring information about development of seaweed (evtrofication in household reservoirs are considered. The input data’s for a research of processes evtrofication are videoimages of tests of water, which are used for the definition of geometric characteristics, number and biomass of seaweed. For handling a measuring information the methods of digital handling videoimages and mathematical means of artificial neural networks are offered.

  2. Altered neural reward and loss processing and prediction error signalling in depression

    Science.gov (United States)

    Ubl, Bettina; Kuehner, Christine; Kirsch, Peter; Ruttorf, Michaela

    2015-01-01

    Dysfunctional processing of reward and punishment may play an important role in depression. However, functional magnetic resonance imaging (fMRI) studies have shown heterogeneous results for reward processing in fronto-striatal regions. We examined neural responsivity associated with the processing of reward and loss during anticipation and receipt of incentives and related prediction error (PE) signalling in depressed individuals. Thirty medication-free depressed persons and 28 healthy controls performed an fMRI reward paradigm. Regions of interest analyses focused on neural responses during anticipation and receipt of gains and losses and related PE-signals. Additionally, we assessed the relationship between neural responsivity during gain/loss processing and hedonic capacity. When compared with healthy controls, depressed individuals showed reduced fronto-striatal activity during anticipation of gains and losses. The groups did not significantly differ in response to reward and loss outcomes. In depressed individuals, activity increases in the orbitofrontal cortex and nucleus accumbens during reward anticipation were associated with hedonic capacity. Depressed individuals showed an absence of reward-related PEs but encoded loss-related PEs in the ventral striatum. Depression seems to be linked to blunted responsivity in fronto-striatal regions associated with limited motivational responses for rewards and losses. Alterations in PE encoding might mirror blunted reward- and enhanced loss-related associative learning in depression. PMID:25567763

  3. Hidden sources of joy, fear, and sadness: Explicit versus implicit neural processing of musical emotions.

    Science.gov (United States)

    Bogert, Brigitte; Numminen-Kontti, Taru; Gold, Benjamin; Sams, Mikko; Numminen, Jussi; Burunat, Iballa; Lampinen, Jouko; Brattico, Elvira

    2016-08-01

    Music is often used to regulate emotions and mood. Typically, music conveys and induces emotions even when one does not attend to them. Studies on the neural substrates of musical emotions have, however, only examined brain activity when subjects have focused on the emotional content of the music. Here we address with functional magnetic resonance imaging (fMRI) the neural processing of happy, sad, and fearful music with a paradigm in which 56 subjects were instructed to either classify the emotions (explicit condition) or pay attention to the number of instruments playing (implicit condition) in 4-s music clips. In the implicit vs. explicit condition, stimuli activated bilaterally the inferior parietal lobule, premotor cortex, caudate, and ventromedial frontal areas. The cortical dorsomedial prefrontal and occipital areas activated during explicit processing were those previously shown to be associated with the cognitive processing of music and emotion recognition and regulation. Moreover, happiness in music was associated with activity in the bilateral auditory cortex, left parahippocampal gyrus, and supplementary motor area, whereas the negative emotions of sadness and fear corresponded with activation of the left anterior cingulate and middle frontal gyrus and down-regulation of the orbitofrontal cortex. Our study demonstrates for the first time in healthy subjects the neural underpinnings of the implicit processing of brief musical emotions, particularly in frontoparietal, dorsolateral prefrontal, and striatal areas of the brain. Copyright © 2016 Elsevier Ltd. All rights reserved.

  4. Sustainable Acquisition Process Improvement for Naval Facilities Engineering Command

    National Research Council Canada - National Science Library

    Sanders, Erin

    2003-01-01

    .... While this guidance is intended to create an open and competitive process to achieve lowest cost or best value, conflicts among traditional acquisition processes and new law requirements are emerging...

  5. Models of neural networks temporal aspects of coding and information processing in biological systems

    CERN Document Server

    Hemmen, J; Schulten, Klaus

    1994-01-01

    Since the appearance of Vol. 1 of Models of Neural Networks in 1991, the theory of neural nets has focused on two paradigms: information coding through coherent firing of the neurons and functional feedback. Information coding through coherent neuronal firing exploits time as a cardinal degree of freedom. This capacity of a neural network rests on the fact that the neuronal action potential is a short, say 1 ms, spike, localized in space and time. Spatial as well as temporal correlations of activity may represent different states of a network. In particular, temporal correlations of activity may express that neurons process the same "object" of, for example, a visual scene by spiking at the very same time. The traditional description of a neural network through a firing rate, the famous S-shaped curve, presupposes a wide time window of, say, at least 100 ms. It thus fails to exploit the capacity to "bind" sets of coherently firing neurons for the purpose of both scene segmentation and figure-ground segregatio...

  6. Predicting tool life in turning operations using neural networks and image processing

    Science.gov (United States)

    Mikołajczyk, T.; Nowicki, K.; Bustillo, A.; Yu Pimenov, D.

    2018-05-01

    A two-step method is presented for the automatic prediction of tool life in turning operations. First, experimental data are collected for three cutting edges under the same constant processing conditions. In these experiments, the parameter of tool wear, VB, is measured with conventional methods and the same parameter is estimated using Neural Wear, a customized software package that combines flank wear image recognition and Artificial Neural Networks (ANNs). Second, an ANN model of tool life is trained with the data collected from the first two cutting edges and the subsequent model is evaluated on two different subsets for the third cutting edge: the first subset is obtained from the direct measurement of tool wear and the second is obtained from the Neural Wear software that estimates tool wear using edge images. Although the complete-automated solution, Neural Wear software for tool wear recognition plus the ANN model of tool life prediction, presented a slightly higher error than the direct measurements, it was within the same range and can meet all industrial requirements. These results confirm that the combination of image recognition software and ANN modelling could potentially be developed into a useful industrial tool for low-cost estimation of tool life in turning operations.

  7. Opponent appetitive-aversive neural processes underlie predictive learning of pain relief.

    Science.gov (United States)

    Seymour, Ben; O'Doherty, John P; Koltzenburg, Martin; Wiech, Katja; Frackowiak, Richard; Friston, Karl; Dolan, Raymond

    2005-09-01

    Termination of a painful or unpleasant event can be rewarding. However, whether the brain treats relief in a similar way as it treats natural reward is unclear, and the neural processes that underlie its representation as a motivational goal remain poorly understood. We used fMRI (functional magnetic resonance imaging) to investigate how humans learn to generate expectations of pain relief. Using a pavlovian conditioning procedure, we show that subjects experiencing prolonged experimentally induced pain can be conditioned to predict pain relief. This proceeds in a manner consistent with contemporary reward-learning theory (average reward/loss reinforcement learning), reflected by neural activity in the amygdala and midbrain. Furthermore, these reward-like learning signals are mirrored by opposite aversion-like signals in lateral orbitofrontal cortex and anterior cingulate cortex. This dual coding has parallels to 'opponent process' theories in psychology and promotes a formal account of prediction and expectation during pain.

  8. Social anhedonia is associated with neural abnormalities during face emotion processing.

    Science.gov (United States)

    Germine, Laura T; Garrido, Lucia; Bruce, Lori; Hooker, Christine

    2011-10-01

    Human beings are social organisms with an intrinsic desire to seek and participate in social interactions. Social anhedonia is a personality trait characterized by a reduced desire for social affiliation and reduced pleasure derived from interpersonal interactions. Abnormally high levels of social anhedonia prospectively predict the development of schizophrenia and contribute to poorer outcomes for schizophrenia patients. Despite the strong association between social anhedonia and schizophrenia, the neural mechanisms that underlie individual differences in social anhedonia have not been studied and are thus poorly understood. Deficits in face emotion recognition are related to poorer social outcomes in schizophrenia, and it has been suggested that face emotion recognition deficits may be a behavioral marker for schizophrenia liability. In the current study, we used functional magnetic resonance imaging (fMRI) to see whether there are differences in the brain networks underlying basic face emotion processing in a community sample of individuals low vs. high in social anhedonia. We isolated the neural mechanisms related to face emotion processing by comparing face emotion discrimination with four other baseline conditions (identity discrimination of emotional faces, identity discrimination of neutral faces, object discrimination, and pattern discrimination). Results showed a group (high/low social anhedonia) × condition (emotion discrimination/control condition) interaction in the anterior portion of the rostral medial prefrontal cortex, right superior temporal gyrus, and left somatosensory cortex. As predicted, high (relative to low) social anhedonia participants showed less neural activity in face emotion processing regions during emotion discrimination as compared to each control condition. The findings suggest that social anhedonia is associated with abnormalities in networks responsible for basic processes associated with social cognition, and provide a

  9. Sustained visual-spatial attention produces costs and benefits in response time and evoked neural activity.

    Science.gov (United States)

    Mangun, G R; Buck, L A

    1998-03-01

    This study investigated the simple reaction time (RT) and event-related potential (ERP) correlates of biasing attention towards a location in the visual field. RTs and ERPs were recorded to stimuli flashed randomly and with equal probability to the left and right visual hemifields in the three blocked, covert attention conditions: (i) attention divided equally to left and right hemifield locations; (ii) attention biased towards the left location; or (iii) attention biased towards the right location. Attention was biased towards left or right by instructions to the subjects, and responses were required to all stimuli. Relative to the divided attention condition, RTs were significantly faster for targets occurring where more attention was allocated (benefits), and slower to targets where less attention was allocated (costs). The early P1 (100-140 msec) component over the lateral occipital scalp regions showed attentional benefits. There were no amplitude modulations of the occipital N1 (125-180 msec) component with attention. Between 200 and 500 msec latency, a late positive deflection (LPD) showed both attentional costs and benefits. The behavioral findings show that when sufficiently induced to bias attention, human observers demonstrate RT benefits as well as costs. The corresponding P1 benefits suggest that the RT benefits of spatial attention may arise as the result of modulations of visual information processing in the extrastriate visual cortex.

  10. Using GREENSCOPE Indicators for Sustainable Computer-Aided Process Evaluation and Design

    Science.gov (United States)

    Manufacturing sustainability can be increased by educating those who design, construct, and operate facilities, and by using appropriate tools for process evaluation and design. The U.S. Environmental Protection Agency's GREENSCOPE methodology and tool, for evaluation and design ...

  11. Using Green Chemistry and Engineering Principles to Design, Assess, and Retrofit Chemical Processes for Sustainability

    Science.gov (United States)

    The concepts of green chemistry and engineering (GC&E) have been promoted as an effective qualitative framework for developing more sustainable chemical syntheses, processes, and material management techniques. This has been demonstrated by many theoretical and practical cases. I...

  12. Phenomena Based Process Intensification of Toluene Methylation for Sustainable Para-xylene Production

    DEFF Research Database (Denmark)

    Anantasarn, Nateetorn; Babi, Deenesh Kavi; Suriyapraphadilok, Uthaiporn

    2016-01-01

    The objective of this work is to generate more sustainable intensified process designs for the production of important chemicals in the petrochemical sector. A 3-stage approach is applied. In stage 1, the base case design is generated or selected from literature. In stage 2, the base case design...... is analysed in terms of economics, sustainability and LCA factors in order to identify process hot-spots that are translated into design targets. In stage 3, intensified flowsheet alternatives are generated that match the targets and thereby eliminate and/or minimize the process hot-spots using a phenomena...... operations to generate more sustainable designs. An overview of the key concepts and framework are presented together with the results from a case study highlighting the application of the framework to the sustainable design of a production process for para-xylene, which is an important chemical utilized...

  13. Specific neural basis of Chinese idioms processing: an event-related functional MRI study

    International Nuclear Information System (INIS)

    Chen Shaoqi; Zhang Yanzhen; Xiao Zhuangwei; Zhang Xuexin

    2007-01-01

    Objective: To address the neural basis of Chinese idioms processing with different kinds of stimuli using an event-related fMRI design. Methods: Sixteen native Chinese speakers were asked to perform a semantic decision task during fMRI scanning. Three kinds of stimuli were used: Real idioms (Real-idiom condition); Literally plausible phrases (Pseudo-idiom condition, the last character of a real idiom was replaced by a character with similar meaning); Literally implausible strings (Non-idiom condition, the last character of a real idiom was replaced by a character with unrelated meaning). Reaction time and correct rate were recorded at the same time. Results: The error rate was 2.6%, 5.2% and 0.9% (F=3.51, P 0.05) for real idioms, pseudo-idioms and wrong idioms, respectively. Similar neural network was activated in all of the three conditions. However, the right hippocampus was only activated in the real idiom condition, and significant activations were found in anterior portion of left inferior frontal gyms (BA47) in real-and pseudo-idiom conditions, but not in non-idiom condition. Conclusion: The right hippocampus plays a specific role in the particular wording of the Chinese idioms. And the left anterior inferior frontal gyms (BA47) may be engaged in the semantic processing of Chinese idioms. The results support the notion that there were specific neural bases for Chinese idioms processing. (authors)

  14. Innovation, Management and Sustainability - change processes in the food service sector

    DEFF Research Database (Denmark)

    Kristensen, Niels Heine; Dahl, Astrid; Mikkelsen, Bent Egberg

    2005-01-01

    Kristensen NH, Thorsen AV, Dahl A, Engelund EH, Mikkelsen BE (2005): Innovation, Management and Sustainability - change processes in the food service sector. Chapter in "Culinary Arts and Sciences V - Global and National Perspectives". Bournemouth University. ISBN 1-85899-179-X......Kristensen NH, Thorsen AV, Dahl A, Engelund EH, Mikkelsen BE (2005): Innovation, Management and Sustainability - change processes in the food service sector. Chapter in "Culinary Arts and Sciences V - Global and National Perspectives". Bournemouth University. ISBN 1-85899-179-X...

  15. Sustainable Chemical Processes and Products. New Design Methodology and Design Tools

    OpenAIRE

    Korevaar, G.

    2004-01-01

    The current chemical industry is not sustainable, which leads to the fact that innovation of chemical processes and products is too often hazardous for society in general and the environment in particular. It really is a challenge to implement sustainability considerations in the design activities of chemical engineers. Therefore, the main question of this thesis is: how can a trained chemical engineer develop a conceptual design of a chemical process or a chemical product in such a way that ...

  16. Neural and Behavioral Evidence for an Online Resetting Process in Visual Working Memory.

    Science.gov (United States)

    Balaban, Halely; Luria, Roy

    2017-02-01

    Visual working memory (VWM) guides behavior by holding a set of active representations and modifying them according to changes in the environment. This updating process relies on a unique mapping between each VWM representation and an actual object in the environment. Here, we destroyed this mapping by either presenting a coherent object but then breaking it into independent parts or presenting an object but then abruptly replacing it with a different object. This allowed us to introduce the neural marker and behavioral consequence of an online resetting process in humans' VWM. Across seven experiments, we demonstrate that this resetting process involves abandoning the old VWM contents because they no longer correspond to the objects in the environment. Then, VWM encodes the novel information and reestablishes the correspondence between the new representations and the objects. The resetting process was marked by a unique neural signature: a sharp drop in the amplitude of the electrophysiological index of VWM contents (the contralateral delay activity), presumably indicating the loss of the existent object-to-representation mappings. This marker was missing when an updating process occurred. Moreover, when tracking moving items, VWM failed to detect salient changes in the object's shape when these changes occurred during the resetting process. This happened despite the object being fully visible, presumably because the mapping between the object and a VWM representation was lost. Importantly, we show that resetting, its neural marker, and the behavioral cost it entails, are specific to situations that involve a destruction of the objects-to-representations correspondence. Visual working memory (VWM) maintains task-relevant information in an online state. Previous studies showed that VWM representations are accessed and modified after changes in the environment. Here, we show that this updating process critically depends on an ongoing mapping between the

  17. Noun and verb processing in aphasia: Behavioural profiles and neural correlates

    Directory of Open Access Journals (Sweden)

    Reem S.W. Alyahya

    Full Text Available The behavioural and neural processes underpinning different word classes, particularly nouns and verbs, have been a long-standing area of interest in psycholinguistic, neuropsychology and aphasiology research. This topic has theoretical implications concerning the organisation of the language system, as well as clinical consequences related to the management of patients with language deficits. Research findings, however, have diverged widely, which might, in part, reflect methodological differences, particularly related to controlling the psycholinguistic variations between nouns and verbs. The first aim of this study, therefore, was to develop a set of neuropsychological tests that assessed single-word production and comprehension with a matched set of nouns and verbs. Secondly, the behavioural profiles and neural correlates of noun and verb processing were explored, based on these novel tests, in a relatively large cohort of 48 patients with chronic post-stroke aphasia. A data-driven approach, principal component analysis (PCA, was also used to determine how noun and verb production and comprehension were related to the patients' underlying fundamental language domains. The results revealed no performance differences between noun and verb production and comprehension once matched on multiple psycholinguistic features including, most critically, imageability. Interestingly, the noun-verb differences found in previous studies were replicated in this study once un-matched materials were used. Lesion-symptom mapping revealed overlapping neural correlates of noun and verb processing along left temporal and parietal regions. These findings support the view that the neural representation of noun and verb processing at single-word level are jointly-supported by distributed cortical regions. The PCA generated five fundamental language and cognitive components of aphasia: phonological production, phonological recognition, semantics, fluency, and

  18. Systematic methods for synthesis and design of sustainable chemical and biochemical processes

    DEFF Research Database (Denmark)

    Gani, Rafiqul

    Chemical and biochemical process design consists of designing the process that can sustainably manufacture an identified chemical product through a chemical or biochemical route. The chemical product tree is potentially very large; starting from a set of basic raw materials (such as petroleum...... for process intensification, sustainable process design, identification of optimal biorefinery models as well as integrated process-control design, and chemical product design. The lecture will present the main concepts, the decomposition based solution approach, the developed methods and tools together...

  19. DESIGNING SUSTAINABLE PROCESSES WITH SIMULATION: THE WASTE REDUCTION (WAR) ALGORITHM

    Science.gov (United States)

    The WAR Algorithm, a methodology for determining the potential environmental impact (PEI) of a chemical process, is presented with modifications that account for the PEI of the energy consumed within that process. From this theory, four PEI indexes are used to evaluate the envir...

  20. Sustaining Innovation: Developing an Instructional Technology Assessment Process

    Science.gov (United States)

    Carmo, Monica Cristina

    2013-01-01

    This case study developed an instructional technology assessment process for the Gevirtz Graduate School of Education (GGSE). The theoretical framework of Adelman and Taylor (2001) guided the development of this instructional technology assessment process and the tools to aid in its facilitation. GGSE faculty, staff, and graduate students…

  1. Evaluating the Sustainability of Manufacturing: Process and Life Cycle Assessments

    Science.gov (United States)

    The Circular Economy is a popular term in environmental studies, but methods are needed to quickly and accurately evaluate recycling opportunities rather than assuming that recycling is appropriate. Through the study of recycling processes (i.e., processes that turn wastes into ...

  2. Abnormal neural hierarchy in processing of verbal information in patients with schizophrenia.

    Science.gov (United States)

    Lerner, Yulia; Bleich-Cohen, Maya; Solnik-Knirsh, Shimrit; Yogev-Seligmann, Galit; Eisenstein, Tamir; Madah, Waheed; Shamir, Alon; Hendler, Talma; Kremer, Ilana

    2018-01-01

    Previous research indicates abnormal comprehension of verbal information in patients with schizophrenia. Yet the neural mechanism underlying the breakdown of verbal information processing in schizophrenia is poorly understood. Imaging studies in healthy populations have shown a network of brain areas involved in hierarchical processing of verbal information over time. Here, we identified critical aspects of this hierarchy, examining patients with schizophrenia. Using functional magnetic resonance imaging, we examined various levels of information comprehension elicited by naturally presented verbal stimuli; from a set of randomly shuffled words to an intact story. Specifically, patients with first episode schizophrenia ( N  = 15), their non-manifesting siblings ( N  = 14) and healthy controls ( N  = 15) listened to a narrated story and randomly scrambled versions of it. To quantify the degree of dissimilarity between the groups, we adopted an inter-subject correlation (inter-SC) approach, which estimates differences in synchronization of neural responses within and between groups. The temporal topography found in healthy and siblings groups were consistent with our previous findings - high synchronization in responses from early sensory toward high order perceptual and cognitive areas. In patients with schizophrenia, stimuli with short and intermediate temporal scales evoked a typical pattern of reliable responses, whereas story condition (long temporal scale) revealed robust and widespread disruption of the inter-SCs. In addition, the more similar the neural activity of patients with schizophrenia was to the average response in the healthy group, the less severe the positive symptoms of the patients. Our findings suggest that system-level neural indication of abnormal verbal information processing in schizophrenia reflects disease manifestations.

  3. Neural Correlates of Hostile Jokes: Cognitive and Motivational Processes in Humor Appreciation

    Directory of Open Access Journals (Sweden)

    Yu-Chen Chan

    2016-10-01

    Full Text Available Hostile jokes provide aggressive catharsis and a feeling of superiority. Behavioral research has found that hostile jokes are perceived as funnier than non-hostile jokes. The purpose of the present study was to identify the neural correlates of the interaction between type and humor by comparing hostile jokes (HJs, non-hostile jokes (NJs, and their corresponding hostile sentences (HSs and non-hostile sentences (NSs. Hostile jokes primarily showed activation in the dorsomedial prefrontal cortex (dmPFC and midbrain compared with the corresponding hostile baseline. Conversely, non-hostile jokes primarily revealed activation in the ventromedial PFC (vmPFC, amygdala, midbrain, ventral anterior cingulate cortex, and nucleus accumbens (NAcc compared with the corresponding non-hostile baseline. These results support the critical role of the medial prefrontal cortex (mPFC for the neural correlates of social cognition and socio-emotional processing in response to different types of jokes. Moreover, the processing of hostile jokes showed increased activation in the dmPFC, which suggested cognitive operations of social motivation, whereas the processing of non-hostile jokes displayed increased activation in the vmPFC, which suggested social-affective engagement. Hostile jokes versus non-hostile jokes primarily showed increased activation in the dmPFC and midbrain, whereas non-hostile jokes versus hostile jokes primarily displayed greater activation in the amygdala and midbrain. The psychophysiological interaction (PPI analysis demonstrated functional coupling of the dmPFC-dlPFC and midbrain-dmPFC for hostile jokes and functional coupling of the vmPFC-midbrain and amygdala-midbrain-NAcc for non-hostile jokes. Surprisingly, the neural correlates of hostile jokes were not perceived as funnier than non-hostile jokes. Future studies could further investigate the neural correlates of potentially important traits of high-hostility tendencies in humor appreciation

  4. Abnormal neural hierarchy in processing of verbal information in patients with schizophrenia

    Directory of Open Access Journals (Sweden)

    Yulia Lerner

    2018-01-01

    Full Text Available Previous research indicates abnormal comprehension of verbal information in patients with schizophrenia. Yet the neural mechanism underlying the breakdown of verbal information processing in schizophrenia is poorly understood. Imaging studies in healthy populations have shown a network of brain areas involved in hierarchical processing of verbal information over time. Here, we identified critical aspects of this hierarchy, examining patients with schizophrenia. Using functional magnetic resonance imaging, we examined various levels of information comprehension elicited by naturally presented verbal stimuli; from a set of randomly shuffled words to an intact story. Specifically, patients with first episode schizophrenia (N = 15, their non-manifesting siblings (N = 14 and healthy controls (N = 15 listened to a narrated story and randomly scrambled versions of it. To quantify the degree of dissimilarity between the groups, we adopted an inter-subject correlation (inter-SC approach, which estimates differences in synchronization of neural responses within and between groups. The temporal topography found in healthy and siblings groups were consistent with our previous findings – high synchronization in responses from early sensory toward high order perceptual and cognitive areas. In patients with schizophrenia, stimuli with short and intermediate temporal scales evoked a typical pattern of reliable responses, whereas story condition (long temporal scale revealed robust and widespread disruption of the inter-SCs. In addition, the more similar the neural activity of patients with schizophrenia was to the average response in the healthy group, the less severe the positive symptoms of the patients. Our findings suggest that system-level neural indication of abnormal verbal information processing in schizophrenia reflects disease manifestations.

  5. Musical intervention enhances infants' neural processing of temporal structure in music and speech.

    Science.gov (United States)

    Zhao, T Christina; Kuhl, Patricia K

    2016-05-10

    Individuals with music training in early childhood show enhanced processing of musical sounds, an effect that generalizes to speech processing. However, the conclusions drawn from previous studies are limited due to the possible confounds of predisposition and other factors affecting musicians and nonmusicians. We used a randomized design to test the effects of a laboratory-controlled music intervention on young infants' neural processing of music and speech. Nine-month-old infants were randomly assigned to music (intervention) or play (control) activities for 12 sessions. The intervention targeted temporal structure learning using triple meter in music (e.g., waltz), which is difficult for infants, and it incorporated key characteristics of typical infant music classes to maximize learning (e.g., multimodal, social, and repetitive experiences). Controls had similar multimodal, social, repetitive play, but without music. Upon completion, infants' neural processing of temporal structure was tested in both music (tones in triple meter) and speech (foreign syllable structure). Infants' neural processing was quantified by the mismatch response (MMR) measured with a traditional oddball paradigm using magnetoencephalography (MEG). The intervention group exhibited significantly larger MMRs in response to music temporal structure violations in both auditory and prefrontal cortical regions. Identical results were obtained for temporal structure changes in speech. The intervention thus enhanced temporal structure processing not only in music, but also in speech, at 9 mo of age. We argue that the intervention enhanced infants' ability to extract temporal structure information and to predict future events in time, a skill affecting both music and speech processing.

  6. A review on sustainable yeast biotechnological processes and applications

    DEFF Research Database (Denmark)

    Nandy, Subir Kumar; Srivastava, R. K.

    2018-01-01

    Yeast is very well known eukaryotic organism for its remarkable biodiversity and extensive industrial applications. Saccharomyces cerevisiae is one of the most widely used microorganisms in biotechnology with successful applications in the biochemical production. Biological conversion with the fo......Yeast is very well known eukaryotic organism for its remarkable biodiversity and extensive industrial applications. Saccharomyces cerevisiae is one of the most widely used microorganisms in biotechnology with successful applications in the biochemical production. Biological conversion...... with the focus on the different utilization of renewable feedstocks into fuels and chemicals has been intensively investigated due to increasing concerns on sustainability issues worldwide. Compared with its counterparts, Saccharomyces cerevisiae, the baker's yeast, is more industrially relevant due to known...... genetic and physiological background, the availability of a large collection of genetic tools, the compatibility of high-density and large-scale fermentation, and optimize the pathway for variety of products. Therefore, S. cerevisiae is one of the most popular cell factories and has been successfully used...

  7. Deep recurrent neural network reveals a hierarchy of process memory during dynamic natural vision.

    Science.gov (United States)

    Shi, Junxing; Wen, Haiguang; Zhang, Yizhen; Han, Kuan; Liu, Zhongming

    2018-05-01

    The human visual cortex extracts both spatial and temporal visual features to support perception and guide behavior. Deep convolutional neural networks (CNNs) provide a computational framework to model cortical representation and organization for spatial visual processing, but unable to explain how the brain processes temporal information. To overcome this limitation, we extended a CNN by adding recurrent connections to different layers of the CNN to allow spatial representations to be remembered and accumulated over time. The extended model, or the recurrent neural network (RNN), embodied a hierarchical and distributed model of process memory as an integral part of visual processing. Unlike the CNN, the RNN learned spatiotemporal features from videos to enable action recognition. The RNN better predicted cortical responses to natural movie stimuli than the CNN, at all visual areas, especially those along the dorsal stream. As a fully observable model of visual processing, the RNN also revealed a cortical hierarchy of temporal receptive window, dynamics of process memory, and spatiotemporal representations. These results support the hypothesis of process memory, and demonstrate the potential of using the RNN for in-depth computational understanding of dynamic natural vision. © 2018 Wiley Periodicals, Inc.

  8. The neural basis of sublexical speech and corresponding nonspeech processing: a combined EEG-MEG study.

    Science.gov (United States)

    Kuuluvainen, Soila; Nevalainen, Päivi; Sorokin, Alexander; Mittag, Maria; Partanen, Eino; Putkinen, Vesa; Seppänen, Miia; Kähkönen, Seppo; Kujala, Teija

    2014-03-01

    We addressed the neural organization of speech versus nonspeech sound processing by investigating preattentive cortical auditory processing of changes in five features of a consonant-vowel syllable (consonant, vowel, sound duration, frequency, and intensity) and their acoustically matched nonspeech counterparts in a simultaneous EEG-MEG recording of mismatch negativity (MMN/MMNm). Overall, speech-sound processing was enhanced compared to nonspeech sound processing. This effect was strongest for changes which affect word meaning (consonant, vowel, and vowel duration) in the left and for the vowel identity change in the right hemisphere also. Furthermore, in the right hemisphere, speech-sound frequency and intensity changes were processed faster than their nonspeech counterparts, and there was a trend for speech-enhancement in frequency processing. In summary, the results support the proposed existence of long-term memory traces for speech sounds in the auditory cortices, and indicate at least partly distinct neural substrates for speech and nonspeech sound processing. Copyright © 2014 Elsevier Inc. All rights reserved.

  9. [Sustainable process improvement with application of 'lean philosophy'].

    Science.gov (United States)

    Rouppe van der Voort, Marc B V; van Merode, G G Frits; Veraart, Henricus G N

    2013-01-01

    Process improvement is increasingly being implemented, particularly with the aid of 'lean philosophy'. This management philosophy aims to improve quality by reducing 'wastage'. Local improvements can produce negative effects elsewhere due to interdependence of processes. An 'integrated system approach' is required to prevent this. Some hospitals claim that this has been successful. Research into process improvement with the application of lean philosophy has reported many positive effects, defined as improved safety, quality and efficiency. Due to methodological shortcomings and lack of rigorous evaluations it is, however, not yet possible to determine the impact of this approach. It is, however, obvious that the investigated applications are fragmentary, with a dominant focus on the instrumental aspect of the philosophy and a lack of integration in a total system, and with insufficient attention to human aspects. Process improvement is required to achieve better and more goal-oriented healthcare. To achieve this, hospitals must develop integrated system approaches that combine methods for process design with continuous improvement of processes and with personnel management. It is crucial that doctors take the initiative to guide and improve processes in an integral manner.

  10. A Framework for Supporting Organizational Transition Processes Towards Sustainable Energy Systems

    Science.gov (United States)

    Buch, Rajesh

    Economic development over the last century has driven a tripling of the world's population, a twenty-fold increase in fossil fuel consumption, and a tripling of traditional biomass consumption. The associated broad income and wealth inequities are retaining over 2 billion people in poverty. Adding to this, fossil fuel combustion is impacting the environment across spatial and temporal scales and the cost of energy is outpacing all other variable costs for most industries. With 60% of world energy delivered in 2008 consumed by the commercial and industrial sector, the fragmented and disparate energy-related decision making within organizations are largely responsible for the inefficient and impacting use of energy resources. The global transition towards sustainable development will require the collective efforts of national, regional, and local governments, institutions, the private sector, and a well-informed public. The leadership role in this transition could be provided by private and public sector organizations, by way of sustainability-oriented organizations, cultures, and infrastructure. The diversity in literature exemplifies the developing nature of sustainability science, with most sustainability assessment approaches and frameworks lacking transformational characteristics, tending to focus on analytical methods. In general, some shortfalls in sustainability assessment processes include lack of: · thorough stakeholder participation in systems and stakeholder mapping, · participatory envisioning of future sustainable states, · normative aggregation of results to provide an overall measure of sustainability, and · influence within strategic decision-making processes. Specific to energy sustainability assessments, while some authors aggregate results to provide overall sustainability scores, assessments have focused solely on energy supply scenarios, while including the deficits discussed above. This paper presents a framework for supporting

  11. The neural processing of foreign-accented speech and its relationship to listener bias

    Directory of Open Access Journals (Sweden)

    Han-Gyol eYi

    2014-10-01

    Full Text Available Foreign-accented speech often presents a challenging listening condition. In addition to deviations from the target speech norms related to the inexperience of the nonnative speaker, listener characteristics may play a role in determining intelligibility levels. We have previously shown that an implicit visual bias for associating East Asian faces and foreignness predicts the listeners’ perceptual ability to process Korean-accented English audiovisual speech (Yi et al., 2013. Here, we examine the neural mechanism underlying the influence of listener bias to foreign faces on speech perception. In a functional magnetic resonance imaging (fMRI study, native English speakers listened to native- and Korean-accented English sentences, with or without faces. The participants’ Asian-foreign association was measured using an implicit association test (IAT, conducted outside the scanner. We found that foreign-accented speech evoked greater activity in the bilateral primary auditory cortices and the inferior frontal gyri, potentially reflecting greater computational demand. Higher IAT scores, indicating greater bias, were associated with increased BOLD response to foreign-accented speech with faces in the primary auditory cortex, the early node for spectrotemporal analysis. We conclude the following: (1 foreign-accented speech perception places greater demand on the neural systems underlying speech perception; (2 face of the talker can exaggerate the perceived foreignness of foreign-accented speech; (3 implicit Asian-foreign association is associated with decreased neural efficiency in early spectrotemporal processing.

  12. Product-service system method to measure sustainability level of traditional smoked fish processing industries

    Directory of Open Access Journals (Sweden)

    Purwaningsih Ratna

    2018-01-01

    Full Text Available Small Medium Enterprise’s (SME of traditional fish processing at Semarang, Central Java, Indonesia still focus their business on gain more profits. Sustainability aspect has not received enough attention yet. This study aims to review the sustainability level of SME smoked fish Semarang using product service system (PSS method. PSS consists of three dimensions (1 Environment, (2 Socio-cultural and (3 Economic. Each dimension consists of 6 criteria's. PSS not only assess the level of sustainability but also formulated the recommendation to increase the industries sustainability level. Sustainability assessment and recommendations formulation is guided by a check-list form. Then, the portfolio diagram used to select these recommendations according to its feasibility to be implemented and its importance for the industries. The result of sustainability assessment for traditional fish processing is 0.44, categorized as medium level. The recommendations for the environmental dimension are (1 use of liquid smoke on fish processing and (2 use of wastewater treatment with anaerobic ponds Recommendation for the socio-cultural dimension is use personal protective tool to reduce worker risk on safety and health. Recommendation for the economic dimension is used social media for product marketing and increasing the economic value of fish lung wastes. Recommendations are then illustrated in a diagram in the form of radar sustainability.

  13. Aligning Strategy with Sustainable Development Goals (SDGs: Process Scoping Diagram for Entrepreneurial Higher Education Institutions (HEIs

    Directory of Open Access Journals (Sweden)

    Elena Fleacă

    2018-03-01

    Full Text Available Seeing that the prosperity of people and society is possible with the aid of sustained and inclusive economic growth of all countries and regions, the sustainable development of our world has gained the particular attention of a wide range of decisional factors; civil society, the business sector, and the scientific community. Education has a decisive impact on changes in the way that societies are coping with national, regional, and global challenges and opportunities brought by sustainable development. The paper addressed the lack of capacity of higher education institutions (HEIs to integrate the principles and practices of sustainable development into all aspects of education and learning, which hampers the capability to act as an entrepreneurial university. Embarking on the path of sustainable development goals (SDGs requires HEI to design, launch, implement, and customize specific processes architecture to govern the advance of the sustainability approach. The authors applied the process scoping diagram to capture and conceptualize the educational model needed to guide the HEI through the process of change in its daily operations. The SIPOC method (Supplier, Input, Process, Output, Customer was applied and with the aid of Visio software tool, the processes relationships were articulated and embedded in the educational model of HEI. Finally, the authors shared their views on the scalability of the model, which may be customized and harmonized in accordance with different HEI’s circumstances and priorities.

  14. Neural and Computational Mechanisms of Action Processing: Interaction between Visual and Motor Representations.

    Science.gov (United States)

    Giese, Martin A; Rizzolatti, Giacomo

    2015-10-07

    Action recognition has received enormous interest in the field of neuroscience over the last two decades. In spite of this interest, the knowledge in terms of fundamental neural mechanisms that provide constraints for underlying computations remains rather limited. This fact stands in contrast with a wide variety of speculative theories about how action recognition might work. This review focuses on new fundamental electrophysiological results in monkeys, which provide constraints for the detailed underlying computations. In addition, we review models for action recognition and processing that have concrete mathematical implementations, as opposed to conceptual models. We think that only such implemented models can be meaningfully linked quantitatively to physiological data and have a potential to narrow down the many possible computational explanations for action recognition. In addition, only concrete implementations allow judging whether postulated computational concepts have a feasible implementation in terms of realistic neural circuits. Copyright © 2015 Elsevier Inc. All rights reserved.

  15. Programmable neural processing on a smartdust for brain-computer interfaces.

    Science.gov (United States)

    Yuwen Sun; Shimeng Huang; Oresko, Joseph J; Cheng, Allen C

    2010-10-01

    Brain-computer interfaces (BCIs) offer tremendous promise for improving the quality of life for disabled individuals. BCIs use spike sorting to identify the source of each neural firing. To date, spike sorting has been performed by either using off-chip analysis, which requires a wired connection penetrating the skull to a bulky external power/processing unit, or via custom application-specific integrated circuits that lack the programmability to perform different algorithms and upgrades. In this research, we propose and test the feasibility of performing on-chip, real-time spike sorting on a programmable smartdust, including feature extraction, classification, compression, and wireless transmission. A detailed power/performance tradeoff analysis using DVFS is presented. Our experimental results show that the execution time and power density meet the requirements to perform real-time spike sorting and wireless transmission on a single neural channel.

  16. Neural Correlates of Contrast and Humor: Processing Common Features of Verbal Irony

    Science.gov (United States)

    Obert, Alexandre; Gierski, Fabien; Calmus, Arnaud; Flucher, Aurélie; Portefaix, Christophe; Pierot, Laurent; Kaladjian, Arthur; Caillies, Stéphanie

    2016-01-01

    Irony is a kind of figurative language used by a speaker to say something that contrasts with the context and, to some extent, lends humor to a situation. However, little is known about the brain regions that specifically support the processing of these two common features of irony. The present study had two main aims: (i) investigate the neural basis of irony processing, by delivering short ironic spoken sentences (and their literal counterparts) to participants undergoing fMRI; and (ii) assess the neural effect of two irony parameters, obtained from normative studies: degree of contrast and humor appreciation. Results revealed activation of the bilateral inferior frontal gyrus (IFG), posterior part of the left superior temporal gyrus, medial frontal cortex, and left caudate during irony processing, suggesting the involvement of both semantic and theory-of-mind networks. Parametric models showed that contrast was specifically associated with the activation of bilateral frontal and subcortical areas, and that these regions were also sensitive to humor, as shown by a conjunction analysis. Activation of the bilateral IFG is consistent with the literature on humor processing, and reflects incongruity detection/resolution processes. Moreover, the activation of subcortical structures can be related to the reward processing of social events. PMID:27851821

  17. Artificial neural network approach to modeling of alcoholic fermentation of thick juice from sugar beet processing

    Directory of Open Access Journals (Sweden)

    Jokić Aleksandar I.

    2012-01-01

    Full Text Available In this paper the bioethanol production in batch culture by free Saccharomyces cerevisiae cells from thick juice as intermediate product of sugar beet processing was examined. The obtained results suggest that it is possible to decrease fermentation time for the cultivation medium based on thick juice with starting sugar content of 5-15 g kg-1. For the fermentation of cultivation medium based on thick juice with starting sugar content of 20 and 25 g kg-1 significant increase in ethanol content was attained during the whole fermentation process, resulting in 12.51 and 10.95 dm3 m-3 ethanol contents after 48 h, respectively. Other goals of this work were to investigate the possibilities for experimental results prediction using artificial neural networks (ANNs and to find its optimal topology. A feed-forward back-propagation artificial neural network was used to test the hypothesis. As input variables fermentation time and starting sugar content were used. Neural networks had one output value, ethanol content, yeast cell number or sugar content. There was one hidden layer and the optimal number of neurons was found to be nine for all selected network outputs. In this study transfer function was tansig and the selected learning rule was Levenberg-Marquardt. Results suggest that artificial neural networks are good prediction tool for selected network outputs. It was found that experimental results are in very good agreement with computed ones. The coefficient of determination (the R-squared was found to be 0.9997, 0.9997 and 0.9999 for ethanol content, yeast cell number and sugar content, respectively.

  18. Neural correlates of treatment response in depressed bipolar adolescents during emotion processing.

    Science.gov (United States)

    Diler, Rasim Somer; Ladouceur, Cecile D; Segreti, Annamaria; Almeida, Jorge R C; Birmaher, Boris; Axelson, David A; Phillips, Mary L; Pan, Lisa A

    2013-06-01

    Depressive mood in adolescents with bipolar disorder (BDd) is associated with significant morbidity and mortality, but we have limited information about neural correlates of depression and treatment response in BDd. Ten adolescents with BDd (8 females, mean age = 15.6 ± 0.9) completed two (fearful and happy) face gender labeling fMRI experiments at baseline and after 6-weeks of open treatment. Whole-brain analysis was used at baseline to compare their neural activity with those of 10 age and sex-matched healthy controls (HC). For comparisons of the neural activity at baseline and after treatment of youth with BDd, region of interest analysis for dorsal/ventral prefrontal, anterior cingulate, and amygdala activity, and significant regions identified by wholebrain analysis between BDd and HC were analyzed. There was significant improvement in depression scores (mean percentage change on the Child Depression Rating Scale-Revised 57 % ± 28). Neural activity after treatment was decreased in left occipital cortex in the intense fearful experiment, but increased in left insula, left cerebellum, and right ventrolateral prefrontal cortex in the intense happy experiment. Greater improvement in depression was associated with baseline higher activity in ventral ACC to mild happy faces. Study sample size was relatively small for subgroup analysis and consisted of mainly female adolescents that were predominantly on psychotropic medications during scanning. Our results of reduced negative emotion processing versus increased positive emotion processing after treatment of depression (improvement of cognitive bias to negative and away from positive) are consistent with the improvement of depression according to Beck's cognitive theory.

  19. Image processing using pulse-coupled neural networks applications in Python

    CERN Document Server

    Lindblad, Thomas

    2013-01-01

    Image processing algorithms based on the mammalian visual cortex are powerful tools for extraction information and manipulating images. This book reviews the neural theory and translates them into digital models. Applications are given in areas of image recognition, foveation, image fusion and information extraction. The third edition reflects renewed international interest in pulse image processing with updated sections presenting several newly developed applications. This edition also introduces a suite of Python scripts that assist readers in replicating results presented in the text and to further develop their own applications.

  20. Sustained posterior contralateral activity indicates re-entrant target processing in visual change detection: An EEG study

    Directory of Open Access Journals (Sweden)

    Daniel eSchneider

    2014-05-01

    Full Text Available The present study investigated the neural mechanisms that contribute to the detection of visual feature changes between stimulus displays by means of event-related lateralizations of the electroencephalogram (EEG. Participants were instructed to respond to a luminance change in either of two lateralized stimuli that could randomly occur alone or together with an irrelevant orientation change of the same or contralateral stimulus. Task performance based on response times and accuracy was decreased compared to the remaining stimulus conditions when relevant and irrelevant feature changes were presented contralateral to each other (lateral distractor condition. The sensory response to the feature changes was reflected in a posterior contralateral positivity at around 100ms after change presentation and a posterior contralateral negativity in the N1 time window (N1pc. N2pc reflected a subsequent attentional bias in favor of the relevant luminance change. The continuation of the sustained posterior contralateral negativity (SPCN following N2pc covaried with response times within feature change conditions and revealed a posterior topography comparable to the earlier components associated with sensory and attentional mechanisms. Therefore, this component might reflect the re-processing of information based on sustained short-term memory representations in the visual system until a stable target percept is created that can serve as the perceptual basis for response selection and the initiation of goal-directed behavior.

  1. Erythropoietin modulates neural and cognitive processing of emotional information in biomarker models of antidepressant drug action in depressed patients

    DEFF Research Database (Denmark)

    Miskowiak, Kamilla W; Favaron, Elisa; Hafizi, Sepehr

    2010-01-01

    Erythropoietin (Epo) has neuroprotective and neurotrophic effects, and may be a novel therapeutic agent in the treatment of psychiatric disorders. We have demonstrated antidepressant-like effects of Epo on the neural and cognitive processing of facial expressions in healthy volunteers. The curren...... study investigates the effects of Epo on the neural and cognitive response to emotional facial expressions in depressed patients.......Erythropoietin (Epo) has neuroprotective and neurotrophic effects, and may be a novel therapeutic agent in the treatment of psychiatric disorders. We have demonstrated antidepressant-like effects of Epo on the neural and cognitive processing of facial expressions in healthy volunteers. The current...

  2. Endogenous testosterone levels are associated with neural activity in men with schizophrenia during facial emotion processing.

    Science.gov (United States)

    Ji, Ellen; Weickert, Cynthia Shannon; Lenroot, Rhoshel; Catts, Stanley V; Vercammen, Ans; White, Christopher; Gur, Raquel E; Weickert, Thomas W

    2015-06-01

    Growing evidence suggests that testosterone may play a role in the pathophysiology of schizophrenia given that testosterone has been linked to cognition and negative symptoms in schizophrenia. Here, we determine the extent to which serum testosterone levels are related to neural activity in affective processing circuitry in men with schizophrenia. Functional magnetic resonance imaging was used to measure blood-oxygen-level-dependent signal changes as 32 healthy controls and 26 people with schizophrenia performed a facial emotion identification task. Whole brain analyses were performed to determine regions of differential activity between groups during processing of angry versus non-threatening faces. A follow-up ROI analysis using a regression model in a subset of 16 healthy men and 16 men with schizophrenia was used to determine the extent to which serum testosterone levels were related to neural activity. Healthy controls displayed significantly greater activation than people with schizophrenia in the left inferior frontal gyrus (IFG). There was no significant difference in circulating testosterone levels between healthy men and men with schizophrenia. Regression analyses between activation in the IFG and circulating testosterone levels revealed a significant positive correlation in men with schizophrenia (r=.63, p=.01) and no significant relationship in healthy men. This study provides the first evidence that circulating serum testosterone levels are related to IFG activation during emotion face processing in men with schizophrenia but not in healthy men, which suggests that testosterone levels modulate neural processes relevant to facial emotion processing that may interfere with social functioning in men with schizophrenia. Crown Copyright © 2015. Published by Elsevier B.V. All rights reserved.

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

    Science.gov (United States)

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

    2011-04-26

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

  4. A sustainable process for gram-scale synthesis of stereoselective ...

    Indian Academy of Sciences (India)

    RAJAN ABRAHAM

    2018-02-07

    Feb 7, 2018 ... for the additional structure modification.17–20. Acrylic acid derivatives ... mild conditions, and application in synthesizing bio- logically ... cal process for the gram-scale synthesis of streoselective ... ate yield of desired product 2 (58%, Table 1, entry. 2). .... Cross-Coupling and Atom-Economic Addition Reac-.

  5. Sustained qualification process for full scope nuclear power plant simulators

    International Nuclear Information System (INIS)

    Pirson, J.; Stubbe, E.; Vanhoenacker, L.

    1994-01-01

    In the past decade, simulator training for all nuclear power plant operators has evolved into a vital requirement. To assure a correct training, the simulator qualification process is an important issue not only for the initial validation but also following major simulator updates, which are necessary during the lifetime of the simulator. In order to avoid degradation of the simulator validated software, the modifications have to be introduced according to a rigorous methodology and a practical requalification process has to be applied. Such methodology has to be enforced at every phase of the simulator construction or updating process from plant data package constitution, over simulator software development to simulator response qualification. The initial qualification and requalification process is based on the 3 levels identified by the ANSI/ANS 3-5 standard for steady-state, operational transients and accident conditions. For the initial certification of the full scope simulators in Belgium, a practical qualification methodology has been applied, which has been adapted into a set of non regression tests for the requalification after major simulator updates. (orig.) (4 refs., 3 figs.)

  6. Preparation of porcelain tile granulates by more environmentally sustainable processes

    Energy Technology Data Exchange (ETDEWEB)

    Gil, C.; Silvestre, D.; Piquer, J.; Garcia-Ten, J.; Quereda, E.; Vicente, M. J.

    2012-07-01

    This study examines the feasibility of manufacturing glazed porcelain tiles with a more environmentally friendly manufacturing process, by reducing water and thermal energy consumption. The process studied in this paper is dry milling in a pendulum mill, with subsequent granulation (in order to obtain a press powder with similar flow ability to that of spray dried powders). The different morphology of the new granulate with respect to the standard spray-dried granulate modifies the microstructure of the green compacts and thus, their behaviour and fired tile properties. In order to obtain porcelain tiles with the required properties (water absorption, mechanical strength,) changes have been made in the raw materials mixture and in the processing variables. Finally, porcelain tiles measuring 50x50 cm have been manufactured at industrial scale with the new granulate using a conventional firing cycle, obtaining quality levels identical to those provided by the spray-dried granulate. These results open the possibility of preparing porcelain tile body compositions through a manufacturing process alternative to the standard one, more environmentally friendly and with lower costs. (Author)

  7. Developing a Benchmark Tool for Sustainable Consumption: An Iterative Process

    Science.gov (United States)

    Heiskanen, E.; Timonen, P.; Nissinen, A.; Gronroos, J.; Honkanen, A.; Katajajuuri, J. -M.; Kettunen, J.; Kurppa, S.; Makinen, T.; Seppala, J.; Silvenius, F.; Virtanen, Y.; Voutilainen, P.

    2007-01-01

    This article presents the development process of a consumer-oriented, illustrative benchmarking tool enabling consumers to use the results of environmental life cycle assessment (LCA) to make informed decisions. LCA provides a wealth of information on the environmental impacts of products, but its results are very difficult to present concisely…

  8. Teaching Sustainable Process Design Using 12 Systematic Computer-Aided Tasks

    DEFF Research Database (Denmark)

    Babi, Deenesh K.

    2015-01-01

    (tasks 4-7) and then sizing, costing and economic analysis of the designed process (tasks 8-9). This produces a base case design. In tasks 10-12, the student explores opportunities for heat and/or mass integration, followed by a sustainability analysis, in order to evaluate the base case design and set......In this paper a task-based approach for teaching (sustainable) process design to students pursuing a degree in chemical and biochemical engineering is presented. In tasks 1-3 the student makes design decisions for product and process selection followed by simple and rigorous model simulations...... targets for further improvement. Finally, a process optimization problem is formulated and solved to obtain the more sustainable process design. The 12 tasks are explained in terms of input and output of each task and examples of application of this approach in an MSclevel course are reported....

  9. Sustainable Ammonia Synthesis – Exploring the scientific challenges associated with discovering alternative, sustainable processes for ammonia production

    Energy Technology Data Exchange (ETDEWEB)

    Nørskov, Jens [Stanford Univ., CA (United States); ; SLAC National Accelerator Lab., Menlo Park, CA (United States); Chen, Jingguang [Columbia Univ., New York, NY (United States); Brookhaven National Lab. (BNL), Upton, NY (United States); Miranda, Raul [Dept. of Energy (DOE), Washington DC (United States). Office of Science; Fitzsimmons, Tim [Dept. of Energy (DOE), Washington DC (United States). Office of Science; Stack, Robert [Dept. of Energy (DOE), Washington DC (United States). Office of Science

    2016-02-18

    Ammonia (NH3) is essential to all life on our planet. Until about 100 years ago, NH3 produced by reduction of dinitrogen (N2) in air came almost exclusively from bacteria containing the enzyme nitrogenase.. DOE convened a roundtable of experts on February 18, 2016. Participants in the Roundtable discussions concluded that the scientific basis for sustainable processes for ammonia synthesis is currently lacking, and it needs to be enhanced substantially before it can form the foundation for alternative processes. The Roundtable Panel identified an overarching grand challenge and several additional scientific grand challenges and research opportunities: -Discovery of active, selective, scalable, long-lived catalysts for sustainable ammonia synthesis. -Development of relatively low pressure (<10 atm) and relatively low temperature (<200 C) thermal processes. -Integration of knowledge from nature (enzyme catalysis), molecular/homogeneous and heterogeneous catalysis. -Development of electrochemical and photochemical routes for N2 reduction based on proton and electron transfer -Development of biochemical routes to N2 reduction -Development of chemical looping (solar thermochemical) approaches -Identification of descriptors of catalytic activity using a combination of theory and experiments -Characterization of surface adsorbates and catalyst structures (chemical, physical and electronic) under conditions relevant to ammonia synthesis.

  10. Neural Systems Underlying Emotional and Non-emotional Interference Processing: An ALE Meta-Analysis of Functional Neuroimaging Studies

    OpenAIRE

    Xu, Min; Xu, Guiping; Yang, Yang

    2016-01-01

    Understanding how the nature of interference might influence the recruitments of the neural systems is considered as the key to understanding cognitive control. Although, interference processing in the emotional domain has recently attracted great interest, the question of whether there are separable neural patterns for emotional and non-emotional interference processing remains open. Here, we performed an activation likelihood estimation meta-analysis of 78 neuroimaging experiments, and exam...

  11. Soil mapping and processes modelling for sustainable land management: a review

    Science.gov (United States)

    Pereira, Paulo; Brevik, Eric; Muñoz-Rojas, Miriam; Miller, Bradley; Smetanova, Anna; Depellegrin, Daniel; Misiune, Ieva; Novara, Agata; Cerda, Artemi

    2017-04-01

    Soil maps and models are fundamental for a correct and sustainable land management (Pereira et al., 2017). They are an important in the assessment of the territory and implementation of sustainable measures in urban areas, agriculture, forests, ecosystem services, among others. Soil maps represent an important basis for the evaluation and restoration of degraded areas, an important issue for our society, as consequence of climate change and the increasing pressure of humans on the ecosystems (Brevik et al. 2016; Depellegrin et al., 2016). The understanding of soil spatial variability and the phenomena that influence this dynamic is crucial to the implementation of sustainable practices that prevent degradation, and decrease the economic costs of soil restoration. In this context, soil maps and models are important to identify areas affected by degradation and optimize the resources available to restore them. Overall, soil data alone or integrated with data from other sciences, is an important part of sustainable land management. This information is extremely important land managers and decision maker's implements sustainable land management policies. The objective of this work is to present a review about the advantages of soil mapping and process modeling for sustainable land management. References Brevik, E., Calzolari, C., Miller, B., Pereira, P., Kabala, C., Baumgarten, A., Jordán, A. (2016) Historical perspectives and future needs in soil mapping, classification and pedological modelling, Geoderma, 264, Part B, 256-274. Depellegrin, D.A., Pereira, P., Misiune, I., Egarter-Vigl, L. (2016) Mapping Ecosystem Services in Lithuania. International Journal of Sustainable Development and World Ecology, 23, 441-455. Pereira, P., Brevik, E., Munoz-Rojas, M., Miller, B., Smetanova, A., Depellegrin, D., Misiune, I., Novara, A., Cerda, A. (2017) Soil mapping and process modelling for sustainable land management. In: Pereira, P., Brevik, E., Munoz-Rojas, M., Miller, B

  12. Unconscious neural processing differs with method used to render stimuli invisible

    Directory of Open Access Journals (Sweden)

    Sergey Victor Fogelson

    2014-06-01

    Full Text Available Visual stimuli can be kept from awareness using various methods. The extent of processing that a given stimulus receives in the absence of awareness is typically used to make claims about the role of consciousness more generally. The neural processing elicited by a stimulus, however, may also depend on the method used to keep it from awareness, and not only on whether the stimulus reaches awareness. Here we report that the method used to render an image invisible has a dramatic effect on how category information about the unseen stimulus is encoded across the human brain. We collected fMRI data while subjects viewed images of faces and tools, that were rendered invisible using either continuous flash suppression (CFS or chromatic flicker fusion (CFF. In a third condition, we presented the same images under normal fully visible viewing conditions. We found that category information about visible images could be extracted from patterns of fMRI responses throughout areas of neocortex known to be involved in face or tool processing. However, category information about stimuli kept from awareness using CFS could be recovered exclusively within occipital cortex, whereas information about stimuli kept from awareness using CFF was also decodable within temporal and frontal regions. We conclude that unconsciously presented objects are processed differently depending on how they are rendered subjectively invisible. Caution should therefore be used in making generalizations on the basis of any one method about the neural basis of consciousness or the extent of information processing without consciousness.

  13. Unconscious neural processing differs with method used to render stimuli invisible.

    Science.gov (United States)

    Fogelson, Sergey V; Kohler, Peter J; Miller, Kevin J; Granger, Richard; Tse, Peter U

    2014-01-01

    Visual stimuli can be kept from awareness using various methods. The extent of processing that a given stimulus receives in the absence of awareness is typically used to make claims about the role of consciousness more generally. The neural processing elicited by a stimulus, however, may also depend on the method used to keep it from awareness, and not only on whether the stimulus reaches awareness. Here we report that the method used to render an image invisible has a dramatic effect on how category information about the unseen stimulus is encoded across the human brain. We collected fMRI data while subjects viewed images of faces and tools, that were rendered invisible using either continuous flash suppression (CFS) or chromatic flicker fusion (CFF). In a third condition, we presented the same images under normal fully visible viewing conditions. We found that category information about visible images could be extracted from patterns of fMRI responses throughout areas of neocortex known to be involved in face or tool processing. However, category information about stimuli kept from awareness using CFS could be recovered exclusively within occipital cortex, whereas information about stimuli kept from awareness using CFF was also decodable within temporal and frontal regions. We conclude that unconsciously presented objects are processed differently depending on how they are rendered subjectively invisible. Caution should therefore be used in making generalizations on the basis of any one method about the neural basis of consciousness or the extent of information processing without consciousness.

  14. A Sparse Auto Encoder Deep Process Neural Network Model and its Application

    Directory of Open Access Journals (Sweden)

    Xu Shaohua

    2017-01-01

    Full Text Available Aiming at the problem of time-varying signal pattern classification, a sparse auto-encoder deep process neural network (SAE-DPNN is proposed. The input of SAE-DPNN is time-varying process signal and the output is pattern category. It combines the time-varying signal classification method of process neural network (PNN and the data feature extraction and hierarchical sparse representation mechanism of sparse automatic encoder (SAE. Based on the feedforward PNN model, SAE-DPNN is constructed by stacking the process neurons, SAE network and softmax classifier. It can maintain the time-sequence and structure of the input signal, express and synthesize the process distribution characteristics of multidimensional time-varying signals and their combinations. SAE-DPNN improves the identification of complex features and distinguishes between different types of signals, realizes the direct classification of time-varying signals. In this paper, the feature extraction and representation mechanism of time-varying signal in SAE-DPNN are analyzed, and a specific learning algorithm is given. The experimental results verify the effectiveness of the model and algorithm.

  15. Neural correlates of attentional and mnemonic processing in event-based prospective memory

    Directory of Open Access Journals (Sweden)

    Justin B Knight

    2010-02-01

    Full Text Available Prospective memory, or memory for realizing delayed intentions, was examined with an event-based paradigm while simultaneously measuring neural activity with high-density EEG recordings. Specifically, the neural substrates of monitoring for an event-based cue were examined, as well as those perhaps associated with the cognitive processes supporting detection of cues and fulfillment of intentions. Participants engaged in a baseline lexical decision task (LDT, followed by a LDT with an embedded prospective memory (PM component. Event-based cues were constituted by color and lexicality (red words. Behavioral data provided evidence that monitoring, or preparatory attentional processes, were used to detect cues. Analysis of the event-related potentials (ERP revealed visual attentional modulations at 140 and 220 ms post-stimulus associated with preparatory attentional processes. In addition, ERP components at 220, 350, and 400 ms post-stimulus were enhanced for intention-related items. Our results suggest preparatory attention may operate by selectively modulating processing of features related to a previously formed event-based intention, as well as provide further evidence for the proposal that dissociable component processes support the fulfillment of delayed intentions.

  16. Identifying temporal and causal contributions of neural processes underlying the Implicit Association Test (IAT

    Directory of Open Access Journals (Sweden)

    Chad Edward Forbes

    2012-11-01

    Full Text Available The Implicit Association Test (IAT is a popular behavioral measure that assesses the associative strength between outgroup members and stereotypical and counterstereotypical traits. Less is known, however, about the degree to which the IAT reflects automatic processing. Two studies examined automatic processing contributions to a gender-IAT using a data driven, social neuroscience approach. Performance on congruent (e.g., categorizing male names with synonyms of strength and incongruent (e.g., categorizing female names with synonyms of strength IAT blocks were separately analyzed using EEG (event-related potentials, or ERPs, and coherence; Study 1 and lesion (Study 2 methodologies. Compared to incongruent blocks, performance on congruent IAT blocks was associated with more positive ERPs that manifested in frontal and occipital regions at automatic processing speeds, occipital regions at more controlled processing speeds and was compromised by volume loss in the anterior temporal lobe, insula and medial PFC. Performance on incongruent blocks was associated with volume loss in supplementary motor areas, cingulate gyrus and a region in medial PFC similar to that found for congruent blocks. Greater coherence was found between frontal and occipital regions to the extent individuals exhibited more bias. This suggests there are separable neural contributions to congruent and incongruent blocks of the IAT but there is also a surprising amount of overlap. Given the temporal and regional neural distinctions, these results provide converging evidence that stereotypic associative strength assessed by the IAT indexes automatic processing to a degree.

  17. Dissociated neural processing for decisions in managers and non-managers.

    Directory of Open Access Journals (Sweden)

    Svenja Caspers

    Full Text Available Functional neuroimaging studies of decision-making so far mainly focused on decisions under uncertainty or negotiation with other persons. Dual process theory assumes that, in such situations, decision making relies on either a rapid intuitive, automated or a slower rational processing system. However, it still remains elusive how personality factors or professional requirements might modulate the decision process and the underlying neural mechanisms. Since decision making is a key task of managers, we hypothesized that managers, facing higher pressure for frequent and rapid decisions than non-managers, prefer the heuristic, automated decision strategy in contrast to non-managers. Such different strategies may, in turn, rely on different neural systems. We tested managers and non-managers in a functional magnetic resonance imaging study using a forced-choice paradigm on word-pairs. Managers showed subcortical activation in the head of the caudate nucleus, and reduced hemodynamic response within the cortex. In contrast, non-managers revealed the opposite pattern. With the head of the caudate nucleus being an initiating component for process automation, these results supported the initial hypothesis, hinting at automation during decisions in managers. More generally, the findings reveal how different professional requirements might modulate cognitive decision processing.

  18. Neural correlates of attentional and mnemonic processing in event-based prospective memory.

    Science.gov (United States)

    Knight, Justin B; Ethridge, Lauren E; Marsh, Richard L; Clementz, Brett A

    2010-01-01

    Prospective memory (PM), or memory for realizing delayed intentions, was examined with an event-based paradigm while simultaneously measuring neural activity with high-density EEG recordings. Specifically, the neural substrates of monitoring for an event-based cue were examined, as well as those perhaps associated with the cognitive processes supporting detection of cues and fulfillment of intentions. Participants engaged in a baseline lexical decision task (LDT), followed by a LDT with an embedded PM component. Event-based cues were constituted by color and lexicality (red words). Behavioral data provided evidence that monitoring, or preparatory attentional processes, were used to detect cues. Analysis of the event-related potentials (ERP) revealed visual attentional modulations at 140 and 220 ms post-stimulus associated with preparatory attentional processes. In addition, ERP components at 220, 350, and 400 ms post-stimulus were enhanced for intention-related items. Our results suggest preparatory attention may operate by selectively modulating processing of features related to a previously formed event-based intention, as well as provide further evidence for the proposal that dissociable component processes support the fulfillment of delayed intentions.

  19. Handedness is related to neural mechanisms underlying hemispheric lateralization of face processing

    Science.gov (United States)

    Frässle, Stefan; Krach, Sören; Paulus, Frieder Michel; Jansen, Andreas

    2016-06-01

    While the right-hemispheric lateralization of the face perception network is well established, recent evidence suggests that handedness affects the cerebral lateralization of face processing at the hierarchical level of the fusiform face area (FFA). However, the neural mechanisms underlying differential hemispheric lateralization of face perception in right- and left-handers are largely unknown. Using dynamic causal modeling (DCM) for fMRI, we aimed to unravel the putative processes that mediate handedness-related differences by investigating the effective connectivity in the bilateral core face perception network. Our results reveal an enhanced recruitment of the left FFA in left-handers compared to right-handers, as evidenced by more pronounced face-specific modulatory influences on both intra- and interhemispheric connections. As structural and physiological correlates of handedness-related differences in face processing, right- and left-handers varied with regard to their gray matter volume in the left fusiform gyrus and their pupil responses to face stimuli. Overall, these results describe how handedness is related to the lateralization of the core face perception network, and point to different neural mechanisms underlying face processing in right- and left-handers. In a wider context, this demonstrates the entanglement of structurally and functionally remote brain networks, suggesting a broader underlying process regulating brain lateralization.

  20. Dissociated neural processing for decisions in managers and non-managers.

    Science.gov (United States)

    Caspers, Svenja; Heim, Stefan; Lucas, Marc G; Stephan, Egon; Fischer, Lorenz; Amunts, Katrin; Zilles, Karl

    2012-01-01

    Functional neuroimaging studies of decision-making so far mainly focused on decisions under uncertainty or negotiation with other persons. Dual process theory assumes that, in such situations, decision making relies on either a rapid intuitive, automated or a slower rational processing system. However, it still remains elusive how personality factors or professional requirements might modulate the decision process and the underlying neural mechanisms. Since decision making is a key task of managers, we hypothesized that managers, facing higher pressure for frequent and rapid decisions than non-managers, prefer the heuristic, automated decision strategy in contrast to non-managers. Such different strategies may, in turn, rely on different neural systems. We tested managers and non-managers in a functional magnetic resonance imaging study using a forced-choice paradigm on word-pairs. Managers showed subcortical activation in the head of the caudate nucleus, and reduced hemodynamic response within the cortex. In contrast, non-managers revealed the opposite pattern. With the head of the caudate nucleus being an initiating component for process automation, these results supported the initial hypothesis, hinting at automation during decisions in managers. More generally, the findings reveal how different professional requirements might modulate cognitive decision processing.

  1. Forward and reverse mapping for milling process using artificial neural networks

    Directory of Open Access Journals (Sweden)

    Rashmi L. Malghan

    2018-02-01

    Full Text Available The data set presented is related to the milling process of AA6061-4.5%Cu-5%SiCp composite. The data primarily concentrates on predicting values of some machining responses, such as cutting force, surface finish and power utilization utilizing using forward back propagation neural network based approach, i.e. ANN based on three process parameters, such as spindle speed, feed rate and depth of cut.The comparing reverse model is likewise created to prescribe the ideal settings of processing parameters for accomplishing the desired responses as indicated by the necessities of the end clients. These modelling approaches are very proficient to foresee the benefits of machining responses and also process parameter settings in light of the experimental technique. Keywords: ANN, Forward mapping, Reverse mapping, Milling process

  2. Residual Neural Processing of Musical Sound Features in Adult Cochlear Implant Users

    Science.gov (United States)

    Timm, Lydia; Vuust, Peter; Brattico, Elvira; Agrawal, Deepashri; Debener, Stefan; Büchner, Andreas; Dengler, Reinhard; Wittfoth, Matthias

    2014-01-01

    Auditory processing in general and music perception in particular are hampered in adult cochlear implant (CI) users. To examine the residual music perception skills and their underlying neural correlates in CI users implanted in adolescence or adulthood, we conducted an electrophysiological and behavioral study comparing adult CI users with normal-hearing age-matched controls (NH controls). We used a newly developed musical multi-feature paradigm, which makes it possible to test automatic auditory discrimination of six different types of sound feature changes inserted within a musical enriched setting lasting only 20 min. The presentation of stimuli did not require the participants’ attention, allowing the study of the early automatic stage of feature processing in the auditory cortex. For the CI users, we obtained mismatch negativity (MMN) brain responses to five feature changes but not to changes of rhythm, whereas we obtained MMNs for all the feature changes in the NH controls. Furthermore, the MMNs to deviants of pitch of CI users were reduced in amplitude and later than those of NH controls for changes of pitch and guitar timber. No other group differences in MMN parameters were found to changes in intensity and saxophone timber. Furthermore, the MMNs in CI users reflected the behavioral scores from a respective discrimination task and were correlated with patients’ age and speech intelligibility. Our results suggest that even though CI users are not performing at the same level as NH controls in neural discrimination of pitch-based features, they do possess potential neural abilities for music processing. However, CI users showed a disrupted ability to automatically discriminate rhythmic changes compared with controls. The current behavioral and MMN findings highlight the residual neural skills for music processing even in CI users who have been implanted in adolescence or adulthood. Highlights: -Automatic brain responses to musical feature changes

  3. Concepts in context: Processing mental state concepts with internal or external focus involves different neural systems

    Science.gov (United States)

    Oosterwijk, Suzanne; Mackey, Scott; Wilson-Mendenhall, Christine; Winkielman, Piotr; Paulus, Martin P.

    2015-01-01

    According to embodied cognition theories concepts are contextually-situated and grounded in neural systems that produce experiential states. This view predicts that processing mental state concepts recruits neural regions associated with different aspects of experience depending on the context in which people understand a concept. This neuroimaging study tested this prediction using a set of sentences that described emotional (e.g., fear, joy) and non-emotional (e.g., thinking, hunger) mental states with internal focus (i.e. focusing on bodily sensations and introspection) or external focus (i.e. focusing on expression and action). Consistent with our predictions, data suggested that the inferior frontal gyrus, a region associated with action representation, was engaged more by external than internal sentences. By contrast, the ventromedial prefrontal cortex, a region associated with the generation of internal states, was engaged more by internal emotion sentences than external sentence categories. Similar patterns emerged when we examined the relationship between neural activity and independent ratings of sentence focus. Furthermore, ratings of emotion were associated with activation in the medial prefrontal cortex, whereas ratings of activity were associated with activation in the inferior frontal gyrus. These results suggest that mental state concepts are represented in a dynamic way, using context-relevant interoceptive and sensorimotor resources. PMID:25748274

  4. Banknote recognition: investigating processing and cognition framework using competitive neural network.

    Science.gov (United States)

    Oyedotun, Oyebade K; Khashman, Adnan

    2017-02-01

    Humans are apt at recognizing patterns and discovering even abstract features which are sometimes embedded therein. Our ability to use the banknotes in circulation for business transactions lies in the effortlessness with which we can recognize the different banknote denominations after seeing them over a period of time. More significant is that we can usually recognize these banknote denominations irrespective of what parts of the banknotes are exposed to us visually. Furthermore, our recognition ability is largely unaffected even when these banknotes are partially occluded. In a similar analogy, the robustness of intelligent systems to perform the task of banknote recognition should not collapse under some minimum level of partial occlusion. Artificial neural networks are intelligent systems which from inception have taken many important cues related to structure and learning rules from the human nervous/cognition processing system. Likewise, it has been shown that advances in artificial neural network simulations can help us understand the human nervous/cognition system even furthermore. In this paper, we investigate three cognition hypothetical frameworks to vision-based recognition of banknote denominations using competitive neural networks. In order to make the task more challenging and stress-test the investigated hypotheses, we also consider the recognition of occluded banknotes. The implemented hypothetical systems are tasked to perform fast recognition of banknotes with up to 75 % occlusion. The investigated hypothetical systems are trained on Nigeria's Naira banknotes and several experiments are performed to demonstrate the findings presented within this work.

  5. Power to punish norm violations affects the neural processes of fairness-related decision making

    Directory of Open Access Journals (Sweden)

    Xuemei eCheng

    2015-12-01

    Full Text Available Punishing norm violations is considered an important motive during rejection of unfair offers in the Ultimatum Game (UG. The present study investigates the impact of the power to punish norm violations on people’s responses to unfairness and associated neural correlates. In the UG condition participants had the power to punish norm violations, while an alternate condition, the Impunity Game (IG, was presented where participants had no power to punish norm violations since rejection only reduced the responder’s income to zero. Results showed that unfair offers were rejected more often in UG compared to IG. At the neural level, anterior insula and dorsal anterior cingulate cortex were more active when participants received and rejected unfair offers in both UG and IG. Moreover, greater dorsolateral prefrontal cortex activity was observed when participants rejected than accepted unfair offers in UG but not in IG. Ventromedial prefrontal cortex activation was higher in UG than IG when unfair offers were accepted as well as when rejecting unfair offers in IG as opposed to UG. Taken together, our results demonstrate that the power to punish norm violations affects not only people’s behavioral responses to unfairness but also the neural correlates of the fairness-related social decision-making process.

  6. Sequential neural processes in abacus mental addition: an EEG and FMRI case study.

    Science.gov (United States)

    Ku, Yixuan; Hong, Bo; Zhou, Wenjing; Bodner, Mark; Zhou, Yong-Di

    2012-01-01

    Abacus experts are able to mentally calculate multi-digit numbers rapidly. Some behavioral and neuroimaging studies have suggested a visuospatial and visuomotor strategy during abacus mental calculation. However, no study up to now has attempted to dissociate temporally the visuospatial neural process from the visuomotor neural process during abacus mental calculation. In the present study, an abacus expert performed the mental addition tasks (8-digit and 4-digit addends presented in visual or auditory modes) swiftly and accurately. The 100% correct rates in this expert's task performance were significantly higher than those of ordinary subjects performing 1-digit and 2-digit addition tasks. ERPs, EEG source localizations, and fMRI results taken together suggested visuospatial and visuomotor processes were sequentially arranged during the abacus mental addition with visual addends and could be dissociated from each other temporally. The visuospatial transformation of the numbers, in which the superior parietal lobule was most likely involved, might occur first (around 380 ms) after the onset of the stimuli. The visuomotor processing, in which the superior/middle frontal gyri were most likely involved, might occur later (around 440 ms). Meanwhile, fMRI results suggested that neural networks involved in the abacus mental addition with auditory stimuli were similar to those in the visual abacus mental addition. The most prominently activated brain areas in both conditions included the bilateral superior parietal lobules (BA 7) and bilateral middle frontal gyri (BA 6). These results suggest a supra-modal brain network in abacus mental addition, which may develop from normal mental calculation networks.

  7. Product-service system method to measure sustainability level of traditional smoked fish processing industries

    OpenAIRE

    Purwaningsih Ratna; Cahyantari Anggaina Elfandora; Ariyani Zulfaida; Susanty Aries; Arvianto Ary; Santoso Haryo

    2018-01-01

    Small Medium Enterprise’s (SME) of traditional fish processing at Semarang, Central Java, Indonesia still focus their business on gain more profits. Sustainability aspect has not received enough attention yet. This study aims to review the sustainability level of SME smoked fish Semarang using product service system (PSS) method. PSS consists of three dimensions (1) Environment, (2) Socio-cultural and (3) Economic. Each dimension consists of 6 criteria's. PSS not only assess the level of sust...

  8. Sustainability certification systems as guidelines for early-phase urban design processes

    OpenAIRE

    Jensen, Lotte Bjerregaard; Bjerre, Lærke; Mansfelt, Lise

    2016-01-01

    The German Sustainable Building Council (Deutsche Gesellschaft für Nachhaltiges Bauen or DGNB) has one of the most comprehensive sustainability certification systems for urban districts (UD). Their explicit aim is that the system should impact the very earliest design decisions. The Technical University of Denmark has tested the DGNB-UD system in two experimental design projects for similar locations to find out how it can be used in the early-phase design process. This paper describes these ...

  9. Differences in neural activity when processing emotional arousal and valence in autism spectrum disorders.

    Science.gov (United States)

    Tseng, Angela; Wang, Zhishun; Huo, Yuankai; Goh, Suzanne; Russell, James A; Peterson, Bradley S

    2016-02-01

    Individuals with autism spectrum disorders (ASD) often have difficulty recognizing and interpreting facial expressions of emotion, which may impair their ability to navigate and communicate successfully in their social, interpersonal environments. Characterizing specific differences between individuals with ASD and their typically developing (TD) counterparts in the neural activity subserving their experience of emotional faces may provide distinct targets for ASD interventions. Thus we used functional magnetic resonance imaging (fMRI) and a parametric experimental design to identify brain regions in which neural activity correlated with ratings of arousal and valence for a broad range of emotional faces. Participants (51 ASD, 84 TD) were group-matched by age, sex, IQ, race, and socioeconomic status. Using task-related change in blood-oxygen-level-dependent (BOLD) fMRI signal as a measure, and covarying for age, sex, FSIQ, and ADOS scores, we detected significant differences across diagnostic groups in the neural activity subserving the dimension of arousal but not valence. BOLD-signal in TD participants correlated inversely with ratings of arousal in regions associated primarily with attentional functions, whereas BOLD-signal in ASD participants correlated positively with arousal ratings in regions commonly associated with impulse control and default-mode activity. Only minor differences were detected between groups in the BOLD signal correlates of valence ratings. Our findings provide unique insight into the emotional experiences of individuals with ASD. Although behavioral responses to face-stimuli were comparable across diagnostic groups, the corresponding neural activity for our ASD and TD groups differed dramatically. The near absence of group differences for valence correlates and the presence of strong group differences for arousal correlates suggest that individuals with ASD are not atypical in all aspects of emotion-processing. Studying these similarities

  10. Spillover processes in the development of a sustainable consumption pattern

    DEFF Research Database (Denmark)

    Thøgersen, John

    1998-01-01

    Hypotheses about possible mechanisms for spillover processes between pro-environmental behaviours are developed and tested by means of structural equation modelling. Data were collected by means of telephone interviews with a representative sample Danish adults. Personal norms concerning recycling...... and packaging waste prevention are found to be rooted in the same more general, internalised values. Further, a predicted positive spillover effect from recycling to packaging waste prevention is confirmed. However, whereas a positive spillover effect from re-cycling to personal norms concerning packaging waste...

  11. Spillover processes in the development of a sustainable consumption pattern

    DEFF Research Database (Denmark)

    Thøgersen, John

    1999-01-01

    recycling and packaging waste prevention are found to be rooted in the same more general, internalised values. Further, a predicted positive spillover effect from recycling to packaging waste prevention is confirmed. However, whereas a positive spillover effect from re-cycling to personal norms concerning......Hypotheses about possible mechanisms for spillover processes between pro-environmental behaviours are developed and tested by means of structural equation modelling. Data were collected by means of telephone interviews with a representative sample of Danish adults. Personal norms concerning...

  12. Development of sustainable paper coatings using nanoscale industrial surface processing

    DEFF Research Database (Denmark)

    Markert, Frank; Breedveld, Leo; Lahti, Johanna

    in the PlasmaNice project, as environmental and social aspects are addressed using methods like life cycle check (LCC), life cycle assessment (LCA), and industrial risk assessment (RA) within the boundary of an economical production for different market segments. The results are intended to be used partly...... products, and the process and material developers providing new coatings with specific properties. The combination of RA and LCA/LCC within the early stages of product development provide a more holistic approach, It is commonly believed to be also economical beneficial as changes are easier to implement...

  13. An integrated biotechnology platform for developing sustainable chemical processes.

    Science.gov (United States)

    Barton, Nelson R; Burgard, Anthony P; Burk, Mark J; Crater, Jason S; Osterhout, Robin E; Pharkya, Priti; Steer, Brian A; Sun, Jun; Trawick, John D; Van Dien, Stephen J; Yang, Tae Hoon; Yim, Harry

    2015-03-01

    Genomatica has established an integrated computational/experimental metabolic engineering platform to design, create, and optimize novel high performance organisms and bioprocesses. Here we present our platform and its use to develop E. coli strains for production of the industrial chemical 1,4-butanediol (BDO) from sugars. A series of examples are given to demonstrate how a rational approach to strain engineering, including carefully designed diagnostic experiments, provided critical insights about pathway bottlenecks, byproducts, expression balancing, and commercial robustness, leading to a superior BDO production strain and process.

  14. Business Process Reengineering of Sustainable Teak Forest at Agroforestry Industry

    Directory of Open Access Journals (Sweden)

    Muhammad Alkaff

    2016-12-01

    Full Text Available Forest destruction both in the form of deforestation and degradation continues. Forest management on the basis of partnership with the community is also one of forest management methods to tackle deforestation. Agroforestry company has a commitment to support legal teak supplies and support teak forest afforestation. Plant breeding efforts were being undertaken all national agroforestry company and implemented in cooperation with BPPT as a partner to obtain superior teak plants. A problem in producing a superior teak seedling is the high cost of seed production. Because of this, teak seedlings produced. Materials used for the study were obtained from questionnaires carried out by employees. The data were analyzed using descriptive analysis, structured equation model and value stream analysis tools. The results reveal that the main factors affecting the production process of teak seedlings are transportation, process, human, material and machine. The improvement of production system teak seedlings will be applied in the following order of priority: transportation with 60.8% influential level, motion with 49.5% effective level, defect with 3.8% influential level, and inventory with 2.5% influential level.

  15. A computer-aided software-tool for sustainable process synthesis-intensification

    DEFF Research Database (Denmark)

    Kumar Tula, Anjan; Babi, Deenesh K.; Bottlaender, Jack

    2017-01-01

    and determine within the design space, the more sustainable processes. In this paper, an integrated computer-aided software-tool that searches the design space for hybrid/intensified more sustainable process options is presented. Embedded within the software architecture are process synthesis...... operations as well as reported hybrid/intensified unit operations is large and can be difficult to manually navigate in order to determine the best process flowsheet for the production of a desired chemical product. Therefore, it is beneficial to utilize computer-aided methods and tools to enumerate, analyze...... constraints while also matching the design targets, they are therefore more sustainable than the base case. The application of the software-tool to the production of biodiesel is presented, highlighting the main features of the computer-aided, multi-stage, multi-scale methods that are able to determine more...

  16. Preparation of porcelain tile granulates by more environmentally sustainable processes

    Directory of Open Access Journals (Sweden)

    García-Ten, J.

    2012-04-01

    Full Text Available This study examines the feasibility of manufacturing glazed porcelain tiles with a more environmentally friendly manufacturing process, by reducing water and thermal energy consumption. The process studied in this paper is dry milling in a pendulum mill, with subsequent granulation (in order to obtain a press powder with similar flowability to that of spraydried powders. The different morphology of the new granulate with respect to the standard spray-dried granulate modifies the microstructure of the green compacts and thus, their behaviour and fired tile properties. In order to obtain porcelain tiles with the required properties (water absorption, mechanical strength,… changes have been made in the raw materials mixture and in the processing variables. Finally, porcelain tiles measuring 50x50 cm have been manufactured at industrial scale with the new granulate using a conventional firing cycle, obtaining quality levels identical to those provided by the spray-dried granulate. These results open the possibility of preparing porcelain tile body compositions through a manufacturing process alternative to the standard one, more environmentally friendly and with lower costs.

    En el presente trabajo se ha estudiado la viabilidad de fabricar gres porcelánico esmaltado utilizando un sistema de preparación de la composición del soporte más respetuoso con el medio ambiente, lo que implica una reducción importante de los consumos de agua y de energía térmica. El proceso que se estudia en el presente trabajo es el consistente en la molienda vía seca en molino pendular y en la posterior granulación (para obtener un polvo de prensas con fluidez similar a la de los polvos atomizados. La distinta morfología de los nuevos gránulos obtenidos respecto al polvo atomizado actual, modifica la microestuctura en crudo de las piezas y, con ello, el comportamiento y propiedades finales de las baldosas obtenidas. Por ello, ha sido necesario

  17. [GSH fermentation process modeling using entropy-criterion based RBF neural network model].

    Science.gov (United States)

    Tan, Zuoping; Wang, Shitong; Deng, Zhaohong; Du, Guocheng

    2008-05-01

    The prediction accuracy and generalization of GSH fermentation process modeling are often deteriorated by noise existing in the corresponding experimental data. In order to avoid this problem, we present a novel RBF neural network modeling approach based on entropy criterion. It considers the whole distribution structure of the training data set in the parameter learning process compared with the traditional MSE-criterion based parameter learning, and thus effectively avoids the weak generalization and over-learning. Then the proposed approach is applied to the GSH fermentation process modeling. Our results demonstrate that this proposed method has better prediction accuracy, generalization and robustness such that it offers a potential application merit for the GSH fermentation process modeling.

  18. Research of processes of eutrophication of Teteriv river reservoir based on neural networks mass

    Directory of Open Access Journals (Sweden)

    Yelnikova T.A.

    2016-12-01

    Full Text Available Methods of process control of eutrophication in water are based on water sampling, handling them in the laboratory and calculation of indexes of pond ecosystem. However, these methods have some significant drawbacks associated with using manual labor. The method of determining of the geometric parameters of phytoplankton through the use of neural networks for processing water samples is developed. Due to this method eutrophic processes of reservoirs of river Teteriv are investigated. A comparative analysis of eutrophic processes of reservoirs "Denyshi" and “Vidsichne” intake during 2014-2015 years are given. The differences between qualitative and quantitative composition of phytoplankton algae in two reservoirs of the river Teteriv used for water supply of Zhitomir city area are found out. The influence of exogenous and endogenous factors on the expansion of phytoplankton is researched. Research results can be used for monitoring and forecasting of ecological state of water for household purposes, used for water supply of cities.

  19. A discussion on the sustainable development of 60Co irradiation processing in Jiangsu province

    International Nuclear Information System (INIS)

    Liu Chunquan; Zhu Jiating; Zhao Yongfu; Xie Zongchuan

    2005-01-01

    This article focuses on the situation of irradiation processing in Jiangsu Province after China's entered into WTO. Irradiation processing has been developed very rapidly in recent years. The potential problems were analyzed, and some proposals related with sustainable development were raised up. (authors)

  20. Promotion of sustainable employability : Occupational health in the meat processing industry

    NARCIS (Netherlands)

    van Holland, Breunis Johannes

    2016-01-01

    Due to rising retirement age, sustainable employability is gaining interest among employers. Such is the case in the meat processing industry. A strategy to address these challenges is health promotion at work. Therefore, the largest Dutch meat processing company has implemented a Workers’ Health

  1. Developing and commercializing sustainable new wood products : a process for identifying viable products.

    Science.gov (United States)

    Gordon A. Enk; Stuart L. Hart

    2003-01-01

    A process was designed to evaluate the sustainability and potential marketability of USDA Forest Service patented technologies. The process was designed and tested jointly by the University of North Carolina, the University of Michigan, Partners for Strategic Change, and the USDA Forest Service. Two technologies were evaluated: a fiber-based product and a wood fiber/...

  2. On Stakeholders and the Decision Making Process Concerning Sustainable Renovation and Refurbishment in Sweden, Denmark and Cyprus

    DEFF Research Database (Denmark)

    Gohardani, Navid; Björk, Folke; Jensen, Per Anker

    2013-01-01

    This article examines the decision making process related to sustainable renovation and refurbishment in buildings. The utilized methodology identifies three distinct phases in order to instigate an engagement in sustainable renovation, by means of questionnaires and semi-structured interviews...

  3. Neural Correlates of Hostile Jokes: Cognitive and Motivational Processes in Humor Appreciation.

    Science.gov (United States)

    Chan, Yu-Chen; Liao, Yi-Jun; Tu, Cheng-Hao; Chen, Hsueh-Chih

    2016-01-01

    Hostile jokes (HJs) provide aggressive catharsis and a feeling of superiority. Behavioral research has found that HJs are perceived as funnier than non-hostile jokes (NJs). The purpose of the present study was to identify the neural correlates of the interaction between type and humor by comparing HJs, NJs, and their corresponding hostile sentences (HSs) and non-hostile sentences (NSs). HJs primarily showed activation in the dorsomedial prefrontal cortex (dmPFC) and midbrain compared with the corresponding hostile baseline. Conversely, NJs primarily revealed activation in the ventromedial PFC (vmPFC), amygdala, midbrain, ventral anterior cingulate cortex, and nucleus accumbens (NAcc) compared with the corresponding non-hostile baseline. These results support the critical role of the medial PFC (mPFC) for the neural correlates of social cognition and socio-emotional processing in response to different types of jokes. Moreover, the processing of HJs showed increased activation in the dmPFC, which suggested cognitive operations of social motivation, whereas the processing of NJs displayed increased activation in the vmPFC, which suggested social-affective engagement. HJs versus NJs primarily showed increased activation in the dmPFC and midbrain, whereas NJs versus HJs primarily displayed greater activation in the amygdala and midbrain. The psychophysiological interaction (PPI) analysis demonstrated functional coupling of the dmPFC-dlPFC and midbrain-dmPFC for HJs and functional coupling of the vmPFC-midbrain and amygdala-midbrain-NAcc for NJs. Surprisingly, HJs were not perceived as funnier than NJs. Future studies could further investigate the neural correlates of potentially important traits of high-hostility tendencies in humor appreciation based on the psychoanalytic and superiority theories of humor.

  4. Neural Reward Processing Mediates the Relationship between Insomnia Symptoms and Depression in Adolescence.

    Science.gov (United States)

    Casement, Melynda D; Keenan, Kate E; Hipwell, Alison E; Guyer, Amanda E; Forbes, Erika E

    2016-02-01

    Emerging evidence suggests that insomnia may disrupt reward-related brain function-a potentially important factor in the development of depressive disorder. Adolescence may be a period during which such disruption is especially problematic given the rise in the incidence of insomnia and ongoing development of neural systems that support reward processing. The present study uses longitudinal data to test the hypothesis that disruption of neural reward processing is a mechanism by which insomnia symptoms-including nocturnal insomnia symptoms (NIS) and nonrestorative sleep (NRS)-contribute to depressive symptoms in adolescent girls. Participants were 123 adolescent girls and their caregivers from an ongoing longitudinal study of precursors to depression across adolescent development. NIS and NRS were assessed annually from ages 9 to 13 years. Girls completed a monetary reward task during a functional MRI scan at age 16 years. Depressive symptoms were assessed at ages 16 and 17 years. Multivariable regression tested the prospective associations between NIS and NRS, neural response during reward anticipation, and the mean number of depressive symptoms (omitting sleep problems). NRS, but not NIS, during early adolescence was positively associated with late adolescent dorsal medial prefrontal cortex (dmPFC) response to reward anticipation and depressive symptoms. DMPFC response mediated the relationship between early adolescent NRS and late adolescent depressive symptoms. These results suggest that NRS may contribute to depression by disrupting reward processing via altered activity in a region of prefrontal cortex involved in affective control. The results also support the mechanistic differentiation of NIS and NRS. © 2016 Associated Professional Sleep Societies, LLC.

  5. Attenuated Neural Processing of Risk in Young Adults at Risk for Stimulant Dependence.

    Directory of Open Access Journals (Sweden)

    Martina Reske

    Full Text Available Approximately 10% of young adults report non-medical use of stimulants (cocaine, amphetamine, methylphenidate, which puts them at risk for the development of dependence. This fMRI study investigates whether subjects at early stages of stimulant use show altered decision making processing.158 occasional stimulants users (OSU and 50 comparison subjects (CS performed a "risky gains" decision making task during which they could select safe options (cash in 20 cents or gamble them for double or nothing in two consecutive gambles (win or lose 40 or 80 cents, "risky decisions". The primary analysis focused on risky versus safe decisions. Three secondary analyses were conducted: First, a robust regression examined the effect of lifetime exposure to stimulants and marijuana; second, subgroups of OSU with >1000 (n = 42, or <50 lifetime marijuana uses (n = 32, were compared to CS with <50 lifetime uses (n = 46 to examine potential marijuana effects; third, brain activation associated with behavioral adjustment following monetary losses was probed.There were no behavioral differences between groups. OSU showed attenuated activation across risky and safe decisions in prefrontal cortex, insula, and dorsal striatum, exhibited lower anterior cingulate cortex (ACC and dorsal striatum activation for risky decisions and greater inferior frontal gyrus activation for safe decisions. Those OSU with relatively more stimulant use showed greater dorsal ACC and posterior insula attenuation. In comparison, greater lifetime marijuana use was associated with less neural differentiation between risky and safe decisions. OSU who chose more safe responses after losses exhibited similarities with CS relative to those preferring risky options.Individuals at risk for the development of stimulant use disorders presented less differentiated neural processing of risky and safe options. Specifically, OSU show attenuated brain response in regions critical for performance monitoring

  6. Neural Correlates of Hostile Jokes: Cognitive and Motivational Processes in Humor Appreciation

    Science.gov (United States)

    Chan, Yu-Chen; Liao, Yi-Jun; Tu, Cheng-Hao

    2016-01-01

    Hostile jokes (HJs) provide aggressive catharsis and a feeling of superiority. Behavioral research has found that HJs are perceived as funnier than non-hostile jokes (NJs). The purpose of the present study was to identify the neural correlates of the interaction between type and humor by comparing HJs, NJs, and their corresponding hostile sentences (HSs) and non-hostile sentences (NSs). HJs primarily showed activation in the dorsomedial prefrontal cortex (dmPFC) and midbrain compared with the corresponding hostile baseline. Conversely, NJs primarily revealed activation in the ventromedial PFC (vmPFC), amygdala, midbrain, ventral anterior cingulate cortex, and nucleus accumbens (NAcc) compared with the corresponding non-hostile baseline. These results support the critical role of the medial PFC (mPFC) for the neural correlates of social cognition and socio-emotional processing in response to different types of jokes. Moreover, the processing of HJs showed increased activation in the dmPFC, which suggested cognitive operations of social motivation, whereas the processing of NJs displayed increased activation in the vmPFC, which suggested social-affective engagement. HJs versus NJs primarily showed increased activation in the dmPFC and midbrain, whereas NJs versus HJs primarily displayed greater activation in the amygdala and midbrain. The psychophysiological interaction (PPI) analysis demonstrated functional coupling of the dmPFC–dlPFC and midbrain–dmPFC for HJs and functional coupling of the vmPFC–midbrain and amygdala–midbrain–NAcc for NJs. Surprisingly, HJs were not perceived as funnier than NJs. Future studies could further investigate the neural correlates of potentially important traits of high-hostility tendencies in humor appreciation based on the psychoanalytic and superiority theories of humor. PMID:27840604

  7. MANAGING SUSTAINABLE DEVELOPMENT OF MEAT PROCESSING PLANTS AS PART OF THE MECHANISM OF STRATEGIC PLANNING

    Directory of Open Access Journals (Sweden)

    I. S. Gusev

    2015-01-01

    Full Text Available Studies have proven that, at present one of the priority research areas as part of the Development Strategy of the Food Processing Industry of the Russian Federation until 2020 is to develop effective mechanisms for sustainable socio-economic development of industrial enterprises. This article investigated the logic of strategic planning within the framework of sustainable economic growth, analyzed the structure of strategic planning, study the subject of strategic planning in the management of sustainable development of enterprises, justified the basic principles of strategic planning for the effective management of sustainable development of industrial enterprises, as well as the complex of organizational tactical activities of operational management strategy for sustainable development of the enterprise. The observation revealed that currently there was a high need for the framework of the branch, departmental and state programs implemented in industrial management of scientific and methodological approaches of strategic planning. Studies have shown that these approaches in its conceptual entity should be based on the growth potential of the sustainable development of meat processing plants in space and time in order to achieve high competitive advantages. Conducted a systematic analysis of industry conditions proved that the problem of sustainable operation and development of meat processing enterprises as a problem of management and control is relatively new, unexplored and highly relevant. On the contrary, it is the basis of modern management strategy and management is a concept and methodology of the so-called adaptive enterprise development under the action of various external and internal factors, risks that may threaten its economic stability and sustainability.

  8. Neural networks underlying language and social cognition during self-other processing in Autism spectrum disorders.

    Science.gov (United States)

    Kana, Rajesh K; Sartin, Emma B; Stevens, Carl; Deshpande, Hrishikesh D; Klein, Christopher; Klinger, Mark R; Klinger, Laura Grofer

    2017-07-28

    The social communication impairments defining autism spectrum disorders (ASD) may be built upon core deficits in perspective-taking, language processing, and self-other representation. Self-referential processing entails the ability to incorporate self-awareness, self-judgment, and self-memory in information processing. Very few studies have examined the neural bases of integrating self-other representation and semantic processing in individuals with ASD. The main objective of this functional MRI study is to examine the role of language and social brain networks in self-other processing in young adults with ASD. Nineteen high-functioning male adults with ASD and 19 age-sex-and-IQ-matched typically developing (TD) control participants made "yes" or "no" judgments of whether an adjective, presented visually, described them (self) or their favorite teacher (other). Both ASD and TD participants showed significantly increased activity in the medial prefrontal cortex (MPFC) during self and other processing relative to letter search. Analyses of group differences revealed significantly reduced activity in left inferior frontal gyrus (LIFG), and left inferior parietal lobule (LIPL) in ASD participants, relative to TD controls. ASD participants also showed significantly weaker functional connectivity of the anterior cingulate cortex (ACC) with several brain areas while processing self-related words. The LIFG and IPL are important regions functionally at the intersection of language and social roles; reduced recruitment of these regions in ASD participants may suggest poor level of semantic and social processing. In addition, poor connectivity of the ACC may suggest the difficulty in meeting the linguistic and social demands of this task in ASD. Overall, this study provides new evidence of the altered recruitment of the neural networks underlying language and social cognition in ASD. Published by Elsevier Ltd.

  9. Central vasopressin V1a receptors modulate neural processing in mothers facing intruder threat to pups

    OpenAIRE

    Caffrey, Martha K.; Nephew, Benjamin C.; Febo, Marcelo

    2009-01-01

    Vasopressin V1a receptors in the rat brain have been studied for their role in modulating aggression and anxiety. In the current study blood-oxygen-level-dependent (BOLD) functional MRI was used to test whether V1a receptors modulate neural processing in the maternal brain when dams are exposed to a male intruder. Primiparous females were given an intracerebroventricular (ICV) injection of vehicle or V1a receptor antagonist ([deamino-Pen1, O-Me-Try, Arg8]-Vasopressin, 125 ng/10 μL) 90-120 min...

  10. Preference Construction Processes for Renewable Energies: Assessing the Influence of Sustainability Information and Decision Support Methods

    Directory of Open Access Journals (Sweden)

    Kiyotada Hayashi

    2016-11-01

    Full Text Available Sustainability information and decision support can be two important driving forces for making sustainable transitions in society. However, not enough knowledge is available on the effectiveness of these two factors. Here, we conducted an experimental study to support the hypotheses that acquisition of sustainability information and use of decision support methods consistently construct preferences for renewable power generation technologies that use solar power, wind power, small-scale hydroelectric power, geothermal power, wood biomass, or biogas as energy sources. The sustainability information was prepared using a renewable energy-focused input-output model of Japan and contained life cycle greenhouse gas emissions, electricity generation costs, and job creation. We measured rank-ordered preferences in the following four steps in experimental workshops conducted for municipal officials: provision of (1 energy-source names; (2 sustainability information; (3 additional explanation of public value; and (4 knowledge and techniques about multi-attribute value functions. The degree of changes in preference orders was evaluated using Spearman’s rank correlation coefficient. The consistency of rank-ordered preferences among participants was determined by using the maximum eigenvalue for the coefficient matrix. The results show: (1 the individual preferences evolved drastically in response to the sustainability information and the decision support method; and (2 the rank-ordered preferences were more consistent during the preference construction processes. These results indicate that provision of sustainability information, coupled with decision support methods, is effective for decision making regarding renewable energies.

  11. Neural networks

    International Nuclear Information System (INIS)

    Denby, Bruce; Lindsey, Clark; Lyons, Louis

    1992-01-01

    The 1980s saw a tremendous renewal of interest in 'neural' information processing systems, or 'artificial neural networks', among computer scientists and computational biologists studying cognition. Since then, the growth of interest in neural networks in high energy physics, fueled by the need for new information processing technologies for the next generation of high energy proton colliders, can only be described as explosive

  12. A customizable stochastic state point process filter (SSPPF) for neural spiking activity.

    Science.gov (United States)

    Xin, Yao; Li, Will X Y; Min, Biao; Han, Yan; Cheung, Ray C C

    2013-01-01

    Stochastic State Point Process Filter (SSPPF) is effective for adaptive signal processing. In particular, it has been successfully applied to neural signal coding/decoding in recent years. Recent work has proven its efficiency in non-parametric coefficients tracking in modeling of mammal nervous system. However, existing SSPPF has only been realized in commercial software platforms which limit their computational capability. In this paper, the first hardware architecture of SSPPF has been designed and successfully implemented on field-programmable gate array (FPGA), proving a more efficient means for coefficient tracking in a well-established generalized Laguerre-Volterra model for mammalian hippocampal spiking activity research. By exploring the intrinsic parallelism of the FPGA, the proposed architecture is able to process matrices or vectors with random size, and is efficiently scalable. Experimental result shows its superior performance comparing to the software implementation, while maintaining the numerical precision. This architecture can also be potentially utilized in the future hippocampal cognitive neural prosthesis design.

  13. Neural correlates of anticipation and processing of performance feedback in social anxiety.

    Science.gov (United States)

    Heitmann, Carina Y; Peterburs, Jutta; Mothes-Lasch, Martin; Hallfarth, Marlit C; Böhme, Stephanie; Miltner, Wolfgang H R; Straube, Thomas

    2014-12-01

    Fear of negative evaluation, such as negative social performance feedback, is the core symptom of social anxiety. The present study investigated the neural correlates of anticipation and perception of social performance feedback in social anxiety. High (HSA) and low (LSA) socially anxious individuals were asked to give a speech on a personally relevant topic and received standardized but appropriate expert performance feedback in a succeeding experimental session in which neural activity was measured during anticipation and presentation of negative and positive performance feedback concerning the speech performance, or a neutral feedback-unrelated control condition. HSA compared to LSA subjects reported greater anxiety during anticipation of negative feedback. Functional magnetic resonance imaging results showed deactivation of medial prefrontal brain areas during anticipation of negative feedback relative to the control and the positive condition, and medial prefrontal and insular hyperactivation during presentation of negative as well as positive feedback in HSA compared to LSA subjects. The results indicate distinct processes underlying feedback processing during anticipation and presentation of feedback in HSA as compared to LSA individuals. In line with the role of the medial prefrontal cortex in self-referential information processing and the insula in interoception, social anxiety seems to be associated with lower self-monitoring during feedback anticipation, and an increased self-focus and interoception during feedback presentation, regardless of feedback valence. © 2014 Wiley Periodicals, Inc.

  14. Neural pathways in processing of sexual arousal: a dynamic causal modeling study.

    Science.gov (United States)

    Seok, J-W; Park, M-S; Sohn, J-H

    2016-09-01

    Three decades of research have investigated brain processing of visual sexual stimuli with neuroimaging methods. These researchers have found that sexual arousal stimuli elicit activity in a broad neural network of cortical and subcortical brain areas that are known to be associated with cognitive, emotional, motivational and physiological components. However, it is not completely understood how these neural systems integrate and modulated incoming information. Therefore, we identify cerebral areas whose activations were correlated with sexual arousal using event-related functional magnetic resonance imaging and used the dynamic causal modeling method for searching the effective connectivity about the sexual arousal processing network. Thirteen heterosexual males were scanned while they passively viewed alternating short trials of erotic and neutral pictures on a monitor. We created a subset of seven models based on our results and previous studies and selected a dominant connectivity model. Consequently, we suggest a dynamic causal model of the brain processes mediating the cognitive, emotional, motivational and physiological factors of human male sexual arousal. These findings are significant implications for the neuropsychology of male sexuality.

  15. COMT val108/158 met genotype affects neural but not cognitive processing in healthy individuals.

    Science.gov (United States)

    Dennis, Nancy A; Need, Anna C; LaBar, Kevin S; Waters-Metenier, Sheena; Cirulli, Elizabeth T; Kragel, James; Goldstein, David B; Cabeza, Roberto

    2010-03-01

    The relationship between cognition and a functional polymorphism in the catechol-O-methlytransferase (COMT) gene, val108/158met, is one of debate in the literature. Furthermore, based on the dopaminergic differences associated with the COMT val108/158met genotype, neural differences during cognition may be present, regardless of genotypic differences in cognitive performance. To investigate these issues the current study aimed to 1) examine the effects of COMT genotype using a large sample of healthy individuals (n = 496-1218) and multiple cognitive measures, and using a subset of the sample (n = 22), 2) examine whether COMT genotype effects medial temporal lobe (MTL) and frontal activity during successful relational memory processing, and 3) investigate group differences in functional connectivity associated with successful relational memory processing. Results revealed no significant group difference in cognitive performance between COMT genotypes in any of the 19 cognitive measures. However, in the subset sample, COMT val homozygotes exhibited significantly decreased MTL and increased prefrontal activity during both successful relational encoding and retrieval, and reduced connectivity between these regions compared with met homozygotes. Taken together, the results suggest that although the COMT val108/158met genotype has no effect on cognitive behavioral measures in healthy individuals, it is associated with differences in neural process underlying cognitive output.

  16. Effects of task demands on the early neural processing of fearful and happy facial expressions.

    Science.gov (United States)

    Itier, Roxane J; Neath-Tavares, Karly N

    2017-05-15

    Task demands shape how we process environmental stimuli but their impact on the early neural processing of facial expressions remains unclear. In a within-subject design, ERPs were recorded to the same fearful, happy and neutral facial expressions presented during a gender discrimination, an explicit emotion discrimination and an oddball detection tasks, the most studied tasks in the field. Using an eye tracker, fixation on the face nose was enforced using a gaze-contingent presentation. Task demands modulated amplitudes from 200 to 350ms at occipito-temporal sites spanning the EPN component. Amplitudes were more negative for fearful than neutral expressions starting on N170 from 150 to 350ms, with a temporo-occipital distribution, whereas no clear effect of happy expressions was seen. Task and emotion effects never interacted in any time window or for the ERP components analyzed (P1, N170, EPN). Thus, whether emotion is explicitly discriminated or irrelevant for the task at hand, neural correlates of fearful and happy facial expressions seem immune to these task demands during the first 350ms of visual processing. Copyright © 2017 Elsevier B.V. All rights reserved.

  17. Reaction time, processing speed and sustained attention in schizophrenia: impact on social functioning.

    Science.gov (United States)

    Lahera, Guillermo; Ruiz, Alicia; Brañas, Antía; Vicens, María; Orozco, Arantxa

    Previous studies have linked processing speed with social cognition and functioning of patients with schizophrenia. A discriminant analysis is needed to determine the different components of this neuropsychological construct. This paper analyzes the impact of processing speed, reaction time and sustained attention on social functioning. 98 outpatients between 18 and 65 with DSM-5 diagnosis of schizophrenia, with a period of 3 months of clinical stability, were recruited. Sociodemographic and clinical data were collected, and the following variables were measured: processing speed (Trail Making Test [TMT], symbol coding [BACS], verbal fluency), simple and elective reaction time, sustained attention, recognition of facial emotions and global functioning. Processing speed (measured only through the BACS), sustained attention (CPT) and elective reaction time (but not simple) were associated with functioning. Recognizing facial emotions (FEIT) correlated significantly with scores on measures of processing speed (BACS, Animals, TMT), sustained attention (CPT) and reaction time. The linear regression model showed a significant relationship between functioning, emotion recognition (P=.015) and processing speed (P=.029). A deficit in processing speed and facial emotion recognition are associated with worse global functioning in patients with schizophrenia. Copyright © 2017 SEP y SEPB. Publicado por Elsevier España, S.L.U. All rights reserved.

  18. Functional Roles of Neural Preparatory Processes in a Cued Stroop Task Revealed by Linking Electrophysiology with Behavioral Performance.

    Science.gov (United States)

    Wang, Chao; Ding, Mingzhou; Kluger, Benzi M

    2015-01-01

    It is well established that cuing facilitates behavioral performance and that different aspects of instructional cues evoke specific neural preparatory processes in cued task-switching paradigms. To deduce the functional role of these neural preparatory processes the majority of studies vary aspects of the experimental paradigm and describe how these variations alter markers of neural preparatory processes. Although these studies provide important insights, they also have notable limitations, particularly in terms of understanding the causal or functional relationship of neural markers to cognitive and behavioral processes. In this study, we sought to address these limitations and uncover the functional roles of neural processes by examining how variability in the amplitude of neural preparatory processes predicts behavioral performance to subsequent stimuli. To achieve this objective 16 young adults were recruited to perform a cued Stroop task while their brain activity was measured using high-density electroencephalography. Four temporally overlapping but functionally and topographically distinct cue-triggered event related potentials (ERPs) were identified: 1) A left-frontotemporal negativity (250-700 ms) that was positively associated with word-reading performance; 2) a midline-frontal negativity (450-800 ms) that was positively associated with color-naming and incongruent performance; 3) a left-frontal negativity (450-800 ms) that was positively associated with switch trial performance; and 4) a centroparietal positivity (450-800 ms) that was positively associated with performance for almost all trial types. These results suggest that at least four dissociable cognitive processes are evoked by instructional cues in the present task, including: 1) domain-specific task facilitation; 2) switch-specific task-set reconfiguration; 3) preparation for response conflict; and 4) proactive attentional control. Examining the relationship between ERPs and behavioral

  19. Functional Roles of Neural Preparatory Processes in a Cued Stroop Task Revealed by Linking Electrophysiology with Behavioral Performance.

    Directory of Open Access Journals (Sweden)

    Chao Wang

    Full Text Available It is well established that cuing facilitates behavioral performance and that different aspects of instructional cues evoke specific neural preparatory processes in cued task-switching paradigms. To deduce the functional role of these neural preparatory processes the majority of studies vary aspects of the experimental paradigm and describe how these variations alter markers of neural preparatory processes. Although these studies provide important insights, they also have notable limitations, particularly in terms of understanding the causal or functional relationship of neural markers to cognitive and behavioral processes. In this study, we sought to address these limitations and uncover the functional roles of neural processes by examining how variability in the amplitude of neural preparatory processes predicts behavioral performance to subsequent stimuli. To achieve this objective 16 young adults were recruited to perform a cued Stroop task while their brain activity was measured using high-density electroencephalography. Four temporally overlapping but functionally and topographically distinct cue-triggered event related potentials (ERPs were identified: 1 A left-frontotemporal negativity (250-700 ms that was positively associated with word-reading performance; 2 a midline-frontal negativity (450-800 ms that was positively associated with color-naming and incongruent performance; 3 a left-frontal negativity (450-800 ms that was positively associated with switch trial performance; and 4 a centroparietal positivity (450-800 ms that was positively associated with performance for almost all trial types. These results suggest that at least four dissociable cognitive processes are evoked by instructional cues in the present task, including: 1 domain-specific task facilitation; 2 switch-specific task-set reconfiguration; 3 preparation for response conflict; and 4 proactive attentional control. Examining the relationship between ERPs and behavioral

  20. SUSTAINABILITY COST ACCOUNTING - PART 1: A MONETARY PROCEDURE TO EVALUATE THE SUSTAINABILITY OF TECHNOLOGIES IN THE SOUTH AFRICAN PROCESS INDUSTRY

    Directory of Open Access Journals (Sweden)

    A. C. Brent

    2012-01-01

    Full Text Available

    ENGLISH ABSTRACT: The development and management of new technologies is fundamental to the manufacturing sector as a core operational initiative. Managers of a new technology are increasingly pressurised to consider the economic, environmental, and social impacts associated with the life cycle of the technology (and product during decision-making – i.e. the overall sustainability of the technology. At present, there is no consensus on a methodology to incorporate externalities – for example, environmental and social impacts at macro-level, for which a company is (typically not held financially liable – into management practices. This paper introduces the Sustainability Cost Accounting (SCA procedure, whereby externalities (burdens and benefits are translated into financial terms to assess the overall sustainability performance of a developed technology in the process industry.

    AFRIKAANSE OPSOMMING: ‘n Sentrale operasionele initiatief van die vervaardigings-industrie is die ontwikkeling en bestuur van nuwe tegnologieë. Bestuurders van nuwe tegnologieë word toenemend onder druk geplaas om die ekonomiese-, omgewings-, en sosiale impakte, wat verwant is aan die lewenssiklus van ‘n tegnologie (of produk, in ag te neem tydens besluitneming ten opsigte van die globale volhoudbaarheid van die tegnologie. Op hierdie stadium is daar geen konsensus oor die metodologie wat gevolg moet word om eksterne faktore – bv. omgewings- en sosiale impakte op makrovlak, waarvoor ‘n maatskappy tipies nie aanspreeklik gehou word nie – te inkorporeer in die bestuurpraktyk. Hierdie artikel stel die Volhoudbaarheid Kosterekeningkunde (VKR prosedure voor, waarvolgens die oorgrote volhoudbare prestasie, in terme van eksterne voor- en nadele van ‘n ontwikkelde tegnologie, in die prosesindustrie ge-assesseer kan word in finansiële terme.

  1. How does sustainability certification affect the design process? Mapping final design projects at an architectural office

    DEFF Research Database (Denmark)

    Landgren, Mathilde; Jensen, Lotte Bjerregaard

    2017-01-01

    process and informing the industry of them. This has led to optimised design processes such as Integrated Energy Design, in which many decisions related to energy consumption and indoor climate are made in the early design stages. The current tendency is to use an expanded notion of sustainability......, derived from the sustainability certification system itself, and to apply it even in the early design process. This perspective emphasises all phases of the life cycle of a building. The goal of the present study was to map how a Danish architectural office approached sustainability in the projects......The context of the study is the very strict regulation of energy consumption for operating buildings in Denmark. It is difficult to meet the requirements by system optimisation in the final design phase, so recent research has focused on ways of meeting the target by adapting the whole design...

  2. Energy-efficient biomass processing with pulsed electric fields for bioeconomy and sustainable development.

    Science.gov (United States)

    Golberg, Alexander; Sack, Martin; Teissie, Justin; Pataro, Gianpiero; Pliquett, Uwe; Saulis, Gintautas; Stefan, Töpfl; Miklavcic, Damijan; Vorobiev, Eugene; Frey, Wolfgang

    2016-01-01

    Fossil resources-free sustainable development can be achieved through a transition to bioeconomy, an economy based on sustainable biomass-derived food, feed, chemicals, materials, and fuels. However, the transition to bioeconomy requires development of new energy-efficient technologies and processes to manipulate biomass feed stocks and their conversion into useful products, a collective term for which is biorefinery. One of the technological platforms that will enable various pathways of biomass conversion is based on pulsed electric fields applications (PEF). Energy efficiency of PEF treatment is achieved by specific increase of cell membrane permeability, a phenomenon known as membrane electroporation. Here, we review the opportunities that PEF and electroporation provide for the development of sustainable biorefineries. We describe the use of PEF treatment in biomass engineering, drying, deconstruction, extraction of phytochemicals, improvement of fermentations, and biogas production. These applications show the potential of PEF and consequent membrane electroporation to enable the bioeconomy and sustainable development.

  3. Gamification as a Means to User Involvement in Decision-making Processes for Sustainable Buildings

    DEFF Research Database (Denmark)

    Hansen, Hanne Tine Ring; Knudstrup, Mary-Ann; Skøtt, Stine

    2017-01-01

    of life. Design thinking was used as method to develop a tool that focuses on how to make sustainable strategy development accessible to non-specialists during those critical stages of building design processes when goals and prioritisations are set. The tool is based on an open and editable platform...... and it will be available to the public in the early Summer of 2017. The paper presents how design thinking is used as an engaging research and development methodology, as well as, an introduction to the dialogue and prioritisation tool’s content and format.......User ownership, actors’ and stakeholders’ lack of knowledge is often identified as critical success parameters and barriers when evaluating how well sustainable buildings perform. Recognising that it is impossible to drive sustainable development without the people who pay for sustainable buildings...

  4. Neural dynamics of morphological processing in spoken word comprehension: Laterality and automaticity

    Directory of Open Access Journals (Sweden)

    Caroline M. Whiting

    2013-11-01

    Full Text Available Rapid and automatic processing of grammatical complexity is argued to take place during speech comprehension, engaging a left-lateralised fronto-temporal language network. Here we address how neural activity in these regions is modulated by the grammatical properties of spoken words. We used combined magneto- and electroencephalography (MEG, EEG to delineate the spatiotemporal patterns of activity that support the recognition of morphologically complex words in English with inflectional (-s and derivational (-er affixes (e.g. bakes, baker. The mismatch negativity (MMN, an index of linguistic memory traces elicited in a passive listening paradigm, was used to examine the neural dynamics elicited by morphologically complex words. Results revealed an initial peak 130-180 ms after the deviation point with a major source in left superior temporal cortex. The localisation of this early activation showed a sensitivity to two grammatical properties of the stimuli: 1 the presence of morphological complexity, with affixed words showing increased left-laterality compared to non-affixed words; and 2 the grammatical category, with affixed verbs showing greater left-lateralisation in inferior frontal gyrus compared to affixed nouns (bakes vs. beaks. This automatic brain response was additionally sensitive to semantic coherence (the meaning of the stem vs. the meaning of the whole form in fronto-temporal regions. These results demonstrate that the spatiotemporal pattern of neural activity in spoken word processing is modulated by the presence of morphological structure, predominantly engaging the left-hemisphere’s fronto-temporal language network, and does not require focused attention on the linguistic input.

  5. Multidimensional analysis of the abnormal neural oscillations associated with lexical processing in schizophrenia.

    Science.gov (United States)

    Xu, Tingting; Stephane, Massoud; Parhi, Keshab K

    2013-04-01

    The neural mechanisms of language abnormalities, the core symptoms in schizophrenia, remain unclear. In this study, a new experimental paradigm, combining magnetoencephalography (MEG) techniques and machine intelligence methodologies, was designed to gain knowledge about the frequency, brain location, and time of occurrence of the neural oscillations that are associated with lexical processing in schizophrenia. The 248-channel MEG recordings were obtained from 12 patients with schizophrenia and 10 healthy controls, during a lexical processing task, where the patients discriminated correct from incorrect lexical stimuli that were visually presented. Event-related desynchronization/synchronization (ERD/ERS) was computed along the frequency, time, and space dimensions combined, that resulted in a large spectral-spatial-temporal ERD/ERS feature set. Machine intelligence techniques were then applied to select a small subset of oscillation patterns that are abnormal in patients with schizophrenia, according to their discriminating power in patient and control classification. Patients with schizophrenia showed abnormal ERD/ERS patterns during both lexical encoding and post-encoding periods. The top-ranked features were located at the occipital and left frontal-temporal areas, and covered a wide frequency range, including δ (1-4 Hz), α (8-12 Hz), β (12-32 Hz), and γ (32-48 Hz) bands. These top features could discriminate the patient group from the control group with 90.91% high accuracy, which demonstrates significant brain oscillation abnormalities in patients with schizophrenia at the specific frequency, time, and brain location indicated by these top features. As neural oscillation abnormality may be due to the mechanisms of the disease, the spectral, spatial, and temporal content of the discriminating features can offer useful information for helping understand the physiological basis of the language disorder in schizophrenia, as well as the pathology of the

  6. A potential neural substrate for processing functional classes of complex acoustic signals.

    Directory of Open Access Journals (Sweden)

    Isabelle George

    Full Text Available Categorization is essential to all cognitive processes, but identifying the neural substrates underlying categorization processes is a real challenge. Among animals that have been shown to be able of categorization, songbirds are particularly interesting because they provide researchers with clear examples of categories of acoustic signals allowing different levels of recognition, and they possess a system of specialized brain structures found only in birds that learn to sing: the song system. Moreover, an avian brain nucleus that is analogous to the mammalian secondary auditory cortex (the caudo-medial nidopallium, or NCM has recently emerged as a plausible site for sensory representation of birdsong, and appears as a well positioned brain region for categorization of songs. Hence, we tested responses in this non-primary, associative area to clear and distinct classes of songs with different functions and social values, and for a possible correspondence between these responses and the functional aspects of songs, in a highly social songbird species: the European starling. Our results clearly show differential neuronal responses to the ethologically defined classes of songs, both in the number of neurons responding, and in the response magnitude of these neurons. Most importantly, these differential responses corresponded to the functional classes of songs, with increasing activation from non-specific to species-specific and from species-specific to individual-specific sounds. These data therefore suggest a potential neural substrate for sorting natural communication signals into categories, and for individual vocal recognition of same-species members. Given the many parallels that exist between birdsong and speech, these results may contribute to a better understanding of the neural bases of speech.

  7. A pilot study investigating changes in neural processing after mindfulness training in elite athletes.

    Science.gov (United States)

    Haase, Lori; May, April C; Falahpour, Maryam; Isakovic, Sara; Simmons, Alan N; Hickman, Steven D; Liu, Thomas T; Paulus, Martin P

    2015-01-01

    The ability to pay close attention to the present moment can be a crucial factor for performing well in a competitive situation. Training mindfulness is one approach to potentially improve elite athletes' ability to focus their attention on the present moment. However, virtually nothing is known about whether these types of interventions alter neural systems that are important for optimal performance. This pilot study examined whether an intervention aimed at improving mindfulness [Mindful Performance Enhancement, Awareness and Knowledge (mPEAK)] changes neural activation patterns during an interoceptive challenge. Participants completed a task involving anticipation and experience of loaded breathing during functional magnetic resonance imaging recording. There were five main results following mPEAK training: (1) elite athletes self-reported higher levels of interoceptive awareness and mindfulness and lower levels of alexithymia; (2) greater insula and anterior cingulate cortex (ACC) activation during anticipation and post-breathing load conditions; (3) increased ACC activation during the anticipation condition was associated with increased scores on the describing subscale of the Five Facet Mindfulness Questionnaire; (4) increased insula activation during the post-load condition was associated with decreases in the Toronto Alexithymia Scale identifying feelings subscale; (5) decreased resting state functional connectivity between the PCC and the right medial frontal cortex and the ACC. Taken together, this pilot study suggests that mPEAK training may lead to increased attention to bodily signals and greater neural processing during the anticipation and recovery from interoceptive perturbations. This association between attention to and processing of interoceptive afferents may result in greater adaptation during stressful situations in elite athletes.

  8. Neural changes associated with semantic processing in healthy aging despite intact behavioral performance.

    Science.gov (United States)

    Lacombe, Jacinthe; Jolicoeur, Pierre; Grimault, Stephan; Pineault, Jessica; Joubert, Sven

    2015-10-01

    Semantic memory recruits an extensive neural network including the left inferior prefrontal cortex (IPC) and the left temporoparietal region, which are involved in semantic control processes, as well as the anterior temporal lobe region (ATL) which is considered to be involved in processing semantic information at a central level. However, little is known about the underlying neuronal integrity of the semantic network in normal aging. Young and older healthy adults carried out a semantic judgment task while their cortical activity was recorded using magnetoencephalography (MEG). Despite equivalent behavioral performance, young adults activated the left IPC to a greater extent than older adults, while the latter group recruited the temporoparietal region bilaterally and the left ATL to a greater extent than younger adults. Results indicate that significant neuronal changes occur in normal aging, mainly in regions underlying semantic control processes, despite an apparent stability in performance at the behavioral level. Copyright © 2015 Elsevier Inc. All rights reserved.

  9. Methodology for automatic process of the fired ceramic tile's internal defect using IR images and artificial neural network

    OpenAIRE

    Andrade, Roberto Márcio de; Eduardo, Alexandre Carlos

    2011-01-01

    In the ceramic industry, rarely testing systems were employed to on-line detect the presence of defects in ceramic tiles. This paper is concerned with the problem of automatic inspection of ceramic tiles using Infrared Images and Artificial Neural Network (ANN). The performance of the technique has been evaluated theoretically and experimentally from laboratory and on line tile samples. It has been performed system for IR image processing and, utilizing an Artificial Neural Network (ANN), det...

  10. Neural Correlates of Sex/Gender Differences in Humor Processing for Different Joke Types.

    Science.gov (United States)

    Chan, Yu-Chen

    2016-01-01

    Humor operates through a variety of techniques, which first generate surprise and then amusement and laughter once the unexpected incongruity is resolved. As different types of jokes use different techniques, the corresponding humor processes also differ. The present study builds on the framework of the 'tri-component theory of humor,' which details the mechanisms involved in cognition (comprehension), affect (appreciation), and laughter (expression). This study seeks to identify differences among joke types and between sexes/genders in the neural mechanisms underlying humor processing. Three types of verbal jokes, bridging-inference jokes (BJs), exaggeration jokes (EJs), and ambiguity jokes (AJs), were used as stimuli. The findings revealed differences in brain activity for an interaction between sex/gender and joke type. For BJs, women displayed greater activation in the temporoparietal-mesocortical-motor network than men, demonstrating the importance of the temporoparietal junction (TPJ) presumably for 'theory of mind' processing, the orbitofrontal cortex for motivational functions and reward coding, and the supplementary motor area for laughter. Women also showed greater activation than men in the frontal-mesolimbic network associated with EJs, including the anterior (frontopolar) prefrontal cortex (aPFC, BA 10) for executive control processes, and the amygdala and midbrain for reward anticipation and salience processes. Conversely, AJs elicited greater activation in men than women in the frontal-paralimbic network, including the dorsal prefrontal cortex (dPFC) and parahippocampal gyrus. All joke types elicited greater activation in the aPFC of women than of men, whereas men showed greater activation than women in the dPFC. To confirm the findings related to sex/gender differences, random group analysis and within group variance analysis were also performed. These findings help further establish the mechanisms underlying the processing of different joke types

  11. Neural Correlates of Sex/Gender Differences in Humor Processing for Different Joke Types

    Directory of Open Access Journals (Sweden)

    Yu-Chen eChan

    2016-04-01

    Full Text Available Humor operates through a variety of techniques, which first generate surprise and then amusement and laughter once the unexpected incongruity is resolved. As different types of jokes use different techniques, the corresponding humor processes also differ. The present study builds on the framework of the ‘tri-component theory of humor’, which details the mechanisms involved in cognition (comprehension, affect (appreciation, and laughter (expression. This study seeks to identify differences among joke types and between sexes/genders in the neural mechanisms underlying humor processing. Three types of verbal jokes, bridging-inference jokes (BJs, exaggeration jokes (EJs, and ambiguity jokes (AJs, were used as stimuli. The findings revealed differences in brain activity for an interaction between sex/gender and joke type. For BJs, women displayed greater activation in the temporoparietal-mesocortical-motor network than men, demonstrating the importance of the temporoparietal junction (TPJ presumably for ‘theory of mind’ processing, the orbitofrontal cortex for motivational functions and reward coding, and the supplementary motor area for laughter. Women also showed greater activation than men in the frontal-mesolimbic network associated with EJs, including the anterior (frontopolar prefrontal cortex (aPFC, BA 10 for executive control processes, and the amygdala and midbrain for reward anticipation and salience processes. Conversely, AJs elicited greater activation in men than women in the frontal-paralimbic network, including the dorsal prefrontal cortex (dPFC and parahippocampal gyrus. All joke types elicited greater activation in the aPFC of women than of men, whereas men showed greater activation than women in the dPFC. To confirm the findings related to sex/gender differences, random group analysis and within group variance analysis were also performed. These findings help further establish the mechanisms underlying the processing of

  12. Adaptive neural network controller for the molten steel level control of strip casting processes

    International Nuclear Information System (INIS)

    Chen, Hung Yi; Huang, Shiuh Jer

    2010-01-01

    The twin-roll strip casting process is a steel-strip production method which combines continuous casting and hot rolling processes. The production line from molten liquid steel to the final steel-strip is shortened and the production cost is reduced significantly as compared to conventional continuous casting. The quality of strip casting process depends on many process parameters, such as molten steel level in the pool, solidification position, and roll gap. Their relationships are complex and the strip casting process has the properties of nonlinear uncertainty and time-varying characteristics. It is difficult to establish an accurate process model for designing a model-based controller to monitor the strip quality. In this paper, a model-free adaptive neural network controller is developed to overcome this problem. The proposed control strategy is based on a neural network structure combined with a sliding-mode control scheme. An adaptive rule is employed to on-line adjust the weights of radial basis functions by using the reaching condition of a specified sliding surface. This surface has the on-line learning ability to respond to the system's nonlinear and time-varying behaviors. Since this model-free controller has a simple control structure and small number of control parameters, it is easy to implement. Simulation results, based on a semi experimental system dynamic model and parameters, are executed to show the control performance of the proposed intelligent controller. In addition, the control performance is compared with that of a traditional Pid controller

  13. Systematic methods and tools for design of sustainable chemical processes for CO2 utilization

    DEFF Research Database (Denmark)

    Kongpanna, Pichayapan; Babi, Deenesh K.; Pavarajarn, Varong

    2016-01-01

    A systematic computer-aided framework for sustainable process design is presented together with its application to the synthesis and generation of processing networks for dimethyl carbonate (DMC) production with CO2 utilization. The framework integrated with various methods, tools, algorithms......-stage involves selection and analysis of the identified networks as a base case design in terms of operational feasibility, economics, life cycle assessment factors and sustainability measures, which are employed to establish targets for improvement in the next-stage. The innovation-stage involves generation...

  14. A process synthesis-intensification framework for the development of sustainable membrane-based operations

    DEFF Research Database (Denmark)

    Babi, Deenesh Kavi; Lutze, Philip; Woodley, John

    2014-01-01

    In this paper a multi-level, multi-scale framework for process synthesis-intensification that aims to make the process more sustainable than a base-case, which may represent a new process or an existing process, is presented. At the first level (operation-scale) a conceptual base case design...... of extension of the combined intensification-synthesis method and its application to generate membrane-based operations. Also, application of the framework is illustrated through a case study involving the production of methyl acetate where membrane-based intensified operations play a major role in determining...... is synthesized through the sequencing of unit operations and subsequently analyzed for identifying process hot-spots using economic, life cycle and sustainability metrics. These hot-spots are limitations/bottlenecks associated with tasks that may be targeted for overall process improvement. At the second level...

  15. Characteristics of nursing professionals and the practice of ecologically sustainable actions in the medication processes

    Directory of Open Access Journals (Sweden)

    Patricia de Oliveira Furukawa

    Full Text Available ABSTRACT Objectives: to verify the correlation between the characteristics of professionals and the practice of sustainable actions in the medication processes in an ICU, and to determine if interventions such as training and awareness can promote sustainable practices performed by nursing staff in the hospital. Methods: before-and-after design study using Lean Six Sigma methodology, applied in an intensive care unit. Nursing staff were observed regarding the practice of ecologically sustainable actions during medication processes (n = 324 cases for each group (pre and post-intervention through a data collection instrument. The processes analyzed involved 99 professionals in the pre-intervention phase and 97 in the post-intervention phase. Data were analyzed quantitatively and the association of variables was accomplished by means of statistical inference, according to the nature of the related variables. Results: the education level was the only characteristic that showed to be relevant to an increase in sustainable practices, with a statistically significant difference (p = 0.002. When comparing before and after the intervention, there was an increase in environmentally friendly actions with statistically significant differences (p = 0.001. Conclusions: the results suggest that institutions should encourage and invest in formal education, as well as training of health professionals to promote sustainable practices in the hospital.

  16. Attention training improves aberrant neural dynamics during working memory processing in veterans with PTSD.

    Science.gov (United States)

    McDermott, Timothy J; Badura-Brack, Amy S; Becker, Katherine M; Ryan, Tara J; Bar-Haim, Yair; Pine, Daniel S; Khanna, Maya M; Heinrichs-Graham, Elizabeth; Wilson, Tony W

    2016-12-01

    Posttraumatic stress disorder (PTSD) is associated with executive functioning deficits, including disruptions in working memory (WM). Recent studies suggest that attention training reduces PTSD symptomatology, but the underlying neural mechanisms are unknown. We used high-density magnetoencephalography (MEG) to evaluate whether attention training modulates brain regions serving WM processing in PTSD. Fourteen veterans with PTSD completed a WM task during a 306-sensor MEG recording before and after 8 sessions of attention training treatment. A matched comparison sample of 12 combat-exposed veterans without PTSD completed the same WM task during a single MEG session. To identify the spatiotemporal dynamics, each group's data were transformed into the time-frequency domain, and significant oscillatory brain responses were imaged using a beamforming approach. All participants exhibited activity in left hemispheric language areas consistent with a verbal WM task. Additionally, veterans with PTSD and combat-exposed healthy controls each exhibited oscillatory responses in right hemispheric homologue regions (e.g., right Broca's area); however, these responses were in opposite directions. Group differences in oscillatory activity emerged in the theta band (4-8 Hz) during encoding and in the alpha band (9-12 Hz) during maintenance and were significant in right prefrontal and right supramarginal and inferior parietal regions. Importantly, following attention training, these significant group differences were reduced or eliminated. This study provides initial evidence that attention training improves aberrant neural activity in brain networks serving WM processing.

  17. Individual differences in speech-in-noise perception parallel neural speech processing and attention in preschoolers

    Science.gov (United States)

    Thompson, Elaine C.; Carr, Kali Woodruff; White-Schwoch, Travis; Otto-Meyer, Sebastian; Kraus, Nina

    2016-01-01

    From bustling classrooms to unruly lunchrooms, school settings are noisy. To learn effectively in the unwelcome company of numerous distractions, children must clearly perceive speech in noise. In older children and adults, speech-in-noise perception is supported by sensory and cognitive processes, but the correlates underlying this critical listening skill in young children (3–5 year olds) remain undetermined. Employing a longitudinal design (two evaluations separated by ~12 months), we followed a cohort of 59 preschoolers, ages 3.0–4.9, assessing word-in-noise perception, cognitive abilities (intelligence, short-term memory, attention), and neural responses to speech. Results reveal changes in word-in-noise perception parallel changes in processing of the fundamental frequency (F0), an acoustic cue known for playing a role central to speaker identification and auditory scene analysis. Four unique developmental trajectories (speech-in-noise perception groups) confirm this relationship, in that improvements and declines in word-in-noise perception couple with enhancements and diminishments of F0 encoding, respectively. Improvements in word-in-noise perception also pair with gains in attention. Word-in-noise perception does not relate to strength of neural harmonic representation or short-term memory. These findings reinforce previously-reported roles of F0 and attention in hearing speech in noise in older children and adults, and extend this relationship to preschool children. PMID:27864051

  18. A New Processing Method Combined with BP Neural Network for Francis Turbine Synthetic Characteristic Curve Research

    Directory of Open Access Journals (Sweden)

    Junyi Li

    2017-01-01

    Full Text Available A BP (backpropagation neural network method is employed to solve the problems existing in the synthetic characteristic curve processing of hydroturbine at present that most studies are only concerned with data in the high efficiency and large guide vane opening area, which can hardly meet the research requirements of transition process especially in large fluctuation situation. The principle of the proposed method is to convert the nonlinear characteristics of turbine to torque and flow characteristics, which can be used for real-time simulation directly based on neural network. Results show that obtained sample data can be extended successfully to cover working areas wider under different operation conditions. Another major contribution of this paper is the resampling technique proposed in the paper to overcome the limitation to sample period simulation. In addition, a detailed analysis for improvements of iteration convergence of the pressure loop is proposed, leading to a better iterative convergence during the head pressure calculation. Actual applications verify that methods proposed in this paper have better simulation results which are closer to the field and provide a new perspective for hydroturbine synthetic characteristic curve fitting and modeling.

  19. Effects of modality on the neural correlates of encoding processes supporting recollection and familiarity

    Science.gov (United States)

    Gottlieb, Lauren J.; Rugg, Michael D.

    2011-01-01

    Prior research has demonstrated that the neural correlates of successful encoding (“subsequent memory effects”) partially overlap with neural regions selectively engaged by the on-line demands of the study task. The primary goal of the present experiment was to determine whether this overlap is associated solely with encoding processes supporting later recollection, or whether overlapping subsequent memory and study condition effects are also evident when later memory is familiarity-based. Subjects (N = 17) underwent fMRI scanning while studying a series of visually and auditorily presented words. Memory for the words was subsequently tested with a modified Remember/Know procedure. Auditorily selective subsequent familiarity effects were evident in bilateral temporal regions that also responded preferentially to auditory items. Although other interpretations are possible, these findings suggest that overlap between study condition-selective subsequent memory effects and regions selectively sensitive to study demands is not uniquely associated with later recollection. In addition, modality-independent subsequent memory effects were identified in several cortical regions. In every case, the effects were greatest for later recollected items, and smaller for items later recognized on the basis of familiarity. The implications of this quantitative dissociation for dual-process models of recognition memory are discussed. PMID:21852431

  20. "Thinking about not-thinking": neural correlates of conceptual processing during Zen meditation.

    Directory of Open Access Journals (Sweden)

    Giuseppe Pagnoni

    2008-09-01

    Full Text Available Recent neuroimaging studies have identified a set of brain regions that are metabolically active during wakeful rest and consistently deactivate in a variety the performance of demanding tasks. This "default network" has been functionally linked to the stream of thoughts occurring automatically in the absence of goal-directed activity and which constitutes an aspect of mental behavior specifically addressed by many meditative practices. Zen meditation, in particular, is traditionally associated with a mental state of full awareness but reduced conceptual content, to be attained via a disciplined regulation of attention and bodily posture. Using fMRI and a simplified meditative condition interspersed with a lexical decision task, we investigated the neural correlates of conceptual processing during meditation in regular Zen practitioners and matched control subjects. While behavioral performance did not differ between groups, Zen practitioners displayed a reduced duration of the neural response linked to conceptual processing in regions of the default network, suggesting that meditative training may foster the ability to control the automatic cascade of semantic associations triggered by a stimulus and, by extension, to voluntarily regulate the flow of spontaneous mentation.

  1. Neural processing of food and emotional stimuli in adolescent and adult anorexia nervosa patients

    Science.gov (United States)

    Forster, Clemens; Dörfler, Arnd; Lindsiepe, Silja; Heinrich, Hartmut; Graap, Holmer; Moll, Gunther H.; Kratz, Oliver

    2018-01-01

    Background A constant preoccupation with food and restrictive eating are main symptoms of anorexia nervosa (AN). Imaging studies revealed aberrant neural activation patterns in brain regions processing hedonic and reward reactions as well as–potentially aversive–emotions. An imbalance between so called “bottom-up” and “top-down” control areas is discussed. The present study is focusing on neural processing of disease-specific food stimuli and emotional stimuli and its developmental course in adolescent and adult AN patients and could offer new insight into differential mechanisms underlying shorter or more chronic disease. Methods 33 adolescents aged 12–18 years (15 AN patients, 18 control participants) and 32 adult women (16 AN patients, 16 control participants) underwent functional magnetic resonance imaging (fMRI, 3T high-field scanner) while watching pictures of high and low-calorie food and affective stimuli. Afterwards, they rated subjective valence of each picture. FMRI data analysis was performed using a region of interest based approach. Results Pictures of high-calorie food items were rated more negatively by AN patients. Differences in activation between patients and controls were found in “bottom up” and “top down” control areas for food stimuli and in several emotion processing regions for affective stimuli which were more pronounced in adolescents than in adults. Conclusion A differential pattern was seen for food stimuli compared to generally emotion eliciting stimuli. Adolescents with AN show reduced processing of affective stimuli and enhanced activation of regions involved in “bottom up” reward processing and “top down” control as well as the insula with regard to food stimuli with a focus on brain regions which underlie changes during adolescent development. In adults less clear and less specific activation differences were present, pointing towards a high impact that regions undergoing maturation might have on AN

  2. Neural processing of food and emotional stimuli in adolescent and adult anorexia nervosa patients.

    Science.gov (United States)

    Horndasch, Stefanie; Roesch, Julie; Forster, Clemens; Dörfler, Arnd; Lindsiepe, Silja; Heinrich, Hartmut; Graap, Holmer; Moll, Gunther H; Kratz, Oliver

    2018-01-01

    A constant preoccupation with food and restrictive eating are main symptoms of anorexia nervosa (AN). Imaging studies revealed aberrant neural activation patterns in brain regions processing hedonic and reward reactions as well as-potentially aversive-emotions. An imbalance between so called "bottom-up" and "top-down" control areas is discussed. The present study is focusing on neural processing of disease-specific food stimuli and emotional stimuli and its developmental course in adolescent and adult AN patients and could offer new insight into differential mechanisms underlying shorter or more chronic disease. 33 adolescents aged 12-18 years (15 AN patients, 18 control participants) and 32 adult women (16 AN patients, 16 control participants) underwent functional magnetic resonance imaging (fMRI, 3T high-field scanner) while watching pictures of high and low-calorie food and affective stimuli. Afterwards, they rated subjective valence of each picture. FMRI data analysis was performed using a region of interest based approach. Pictures of high-calorie food items were rated more negatively by AN patients. Differences in activation between patients and controls were found in "bottom up" and "top down" control areas for food stimuli and in several emotion processing regions for affective stimuli which were more pronounced in adolescents than in adults. A differential pattern was seen for food stimuli compared to generally emotion eliciting stimuli. Adolescents with AN show reduced processing of affective stimuli and enhanced activation of regions involved in "bottom up" reward processing and "top down" control as well as the insula with regard to food stimuli with a focus on brain regions which underlie changes during adolescent development. In adults less clear and less specific activation differences were present, pointing towards a high impact that regions undergoing maturation might have on AN symptoms.

  3. Deep architecture neural network-based real-time image processing for image-guided radiotherapy.

    Science.gov (United States)

    Mori, Shinichiro

    2017-08-01

    To develop real-time image processing for image-guided radiotherapy, we evaluated several neural network models for use with different imaging modalities, including X-ray fluoroscopic image denoising. Setup images of prostate cancer patients were acquired with two oblique X-ray fluoroscopic units. Two types of residual network were designed: a convolutional autoencoder (rCAE) and a convolutional neural network (rCNN). We changed the convolutional kernel size and number of convolutional layers for both networks, and the number of pooling and upsampling layers for rCAE. The ground-truth image was applied to the contrast-limited adaptive histogram equalization (CLAHE) method of image processing. Network models were trained to keep the quality of the output image close to that of the ground-truth image from the input image without image processing. For image denoising evaluation, noisy input images were used for the training. More than 6 convolutional layers with convolutional kernels >5×5 improved image quality. However, this did not allow real-time imaging. After applying a pair of pooling and upsampling layers to both networks, rCAEs with >3 convolutions each and rCNNs with >12 convolutions with a pair of pooling and upsampling layers achieved real-time processing at 30 frames per second (fps) with acceptable image quality. Use of our suggested network achieved real-time image processing for contrast enhancement and image denoising by the use of a conventional modern personal computer. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

  4. Dissociable neural processes during risky decision-making in individuals with Internet-gaming disorder

    Directory of Open Access Journals (Sweden)

    Lu Liu

    2017-01-01

    Full Text Available Risk-taking is purported to be central to addictive behaviors. However, for Internet gaming disorder (IGD, a condition conceptualized as a behavioral addiction, the neural processes underlying impaired decision-making (risk evaluation and outcome processing related to gains and losses have not been systematically investigated. Forty-one males with IGD and 27 healthy comparison (HC male participants were recruited, and the cups task was used to identify neural processes associated with gain- and loss-related risk- and outcome-processing in IGD. During risk evaluation, the IGD group, compared to the HC participants, showed weaker modulation for experienced risk within the bilateral dorsolateral prefrontal cortex (DLPFC (t = −4.07; t = −3.94; PFWE < 0.05 and inferior parietal lobule (IPL (t = −4.08; t = −4.08; PFWE < 0.05 for potential losses. The modulation of the left DLPFC and bilateral IPL activation were negatively related to addiction severity within the IGD group (r = −0.55; r = −0.61; r = −0.51; PFWE < 0.05. During outcome processing, the IGD group presented greater responses for the experienced reward within the ventral striatum, ventromedial prefrontal cortex, and orbitofrontal cortex (OFC (t = 5.04, PFWE < 0.05 for potential gains, as compared to HC participants. Within the IGD group, the increased reward-related activity in the right OFC was positively associated with severity of IGD (r = 0.51, PFWE < 0.05. These results provide a neurobiological foundation for decision-making deficits in individuals with IGD and suggest an imbalance between hypersensitivity for reward and weaker risk experience and self-control for loss. The findings suggest a biological mechanism for why individuals with IGD may persist in game-seeking behavior despite negative consequences, and treatment development strategies may focus on targeting these neural pathways in this population.

  5. Sustainability of cement kiln co-processing of wastes in India: a pilot study.

    Science.gov (United States)

    Baidya, Rahul; Ghosh, Sadhan Kumar; Parlikar, Ulhas V

    2017-07-01

    Co-processing in cement kiln achieves effective utilization of the material and energy value present in the wastes, thereby conserving the natural resources by reducing the use of virgin material. In India, a number of multifolded initiatives have been taken that take into account the potential and volume of waste generation. This paper studies the factors which might influence the sustainability of co-processing of waste in cement kilns as a business model, considering the issues and challenges in the supply chain framework in India in view of the four canonical pillars of sustainability. A pilot study on co-processing was carried out in one of the cement plant in India to evaluate the environmental performance, economical performance, operational performance and social performance. The findings will help India and other developing countries to introduce effective supply chain management for co-processing while addressing the issues and challenges during co-processing of different waste streams in the cement kilns.

  6. The influence of motherhood on neural systems for reward processing in low income, minority, young women.

    Science.gov (United States)

    Moses-Kolko, Eydie L; Forbes, Erika E; Stepp, Stephanie; Fraser, David; Keenan, Kate E; Guyer, Amanda E; Chase, Henry W; Phillips, Mary L; Zevallos, Carlos R; Guo, Chaohui; Hipwell, Alison E

    2016-04-01

    Given the association between maternal caregiving behavior and heightened neural reward activity in experimental animal studies, the present study examined whether motherhood in humans positively modulates reward-processing neural circuits, even among mothers exposed to various life stressors and depression. Subjects were 77 first-time mothers and 126 nulliparous young women from the Pittsburgh Girls Study, a longitudinal study beginning in childhood. Subjects underwent a monetary reward task during functional magnetic resonance imaging in addition to assessment of current depressive symptoms. Life stress was measured by averaging data collected between ages 8-15 years. Using a region-of-interest approach, we conducted hierarchical regression to examine the relationship of psychosocial factors (life stress and current depression) and motherhood with extracted ventral striatal (VST) response to reward anticipation. Whole-brain regression analyses were performed post-hoc to explore non-striatal regions associated with reward anticipation in mothers vs nulliparous women. Anticipation of monetary reward was associated with increased neural activity in expected regions including caudate, orbitofrontal, occipital, superior and middle frontal cortices. There was no main effect of motherhood nor motherhood-by-psychosocial factor interaction effect on VST response during reward anticipation. Depressive symptoms were associated with increased VST activity across the entire sample. In exploratory whole brain analysis, motherhood was associated with increased somatosensory cortex activity to reward (FWE cluster forming threshold preward anticipation-related VST activity nor does motherhood modulate the impact of depression or life stress on VST activity. Future studies are needed to evaluate whether earlier postpartum assessment of reward function, inclusion of mothers with more severe depressive symptoms, and use of reward tasks specific for social reward might reveal an

  7. Decision Making under Uncertainty: A Neural Model based on Partially Observable Markov Decision Processes

    Directory of Open Access Journals (Sweden)

    Rajesh P N Rao

    2010-11-01

    Full Text Available A fundamental problem faced by animals is learning to select actions based on noisy sensory information and incomplete knowledge of the world. It has been suggested that the brain engages in Bayesian inference during perception but how such probabilistic representations are used to select actions has remained unclear. Here we propose a neural model of action selection and decision making based on the theory of partially observable Markov decision processes (POMDPs. Actions are selected based not on a single optimal estimate of state but on the posterior distribution over states (the belief state. We show how such a model provides a unified framework for explaining experimental results in decision making that involve both information gathering and overt actions. The model utilizes temporal difference (TD learning for maximizing expected reward. The resulting neural architecture posits an active role for the neocortex in belief computation while ascribing a role to the basal ganglia in belief representation, value computation, and action selection. When applied to the random dots motion discrimination task, model neurons representing belief exhibit responses similar to those of LIP neurons in primate neocortex. The appropriate threshold for switching from information gathering to overt actions emerges naturally during reward maximization. Additionally, the time course of reward prediction error in the model shares similarities with dopaminergic responses in the basal ganglia during the random dots task. For tasks with a deadline, the model learns a decision making strategy that changes with elapsed time, predicting a collapsing decision threshold consistent with some experimental studies. The model provides a new framework for understanding neural decision making and suggests an important role for interactions between the neocortex and the basal ganglia in learning the mapping between probabilistic sensory representations and actions that maximize

  8. Transnational Comparison of Sustainability Assessment Programs for Viticulture and a Case-Study on Programs’ Engagement Processes

    OpenAIRE

    Irina Santiago-Brown; Andrew Metcalfe; Cate Jerram; Cassandra Collins

    2014-01-01

    This article documents and compares the most prominent sustainability assessment programs for individual organisations in viticulture worldwide. Certification and engagement processes for membership uptake; benefits; motives; inhibiting factors; and desirable reporting system features of viticultural sustainability programs, are all considered. Case-study results are derived from nine sustainability programs; 14 focus groups with 83 CEOs, Chief Viticulturists or Winemakers from wine grape pro...

  9. Cognitive processes and neural basis of language switching: proposal of a new model.

    Science.gov (United States)

    Moritz-Gasser, Sylvie; Duffau, Hugues

    2009-12-09

    Although studies on bilingualism are abundant, cognitive processes and neural foundations of language switching received less attention. The aim of our study is to provide new insights to this still open question: do dedicated region(s) for language switching exist or is this function underlain by a distributed circuit of interconnected brain areas, part of a more general cognitive system? On the basis of recent behavioral, neuroimaging, and brain stimulation studies, we propose an original 'hodological' model of language switching. This process might be subserved by a large-scale cortico-subcortical network, with an executive system (prefrontal cortex, anterior cingulum, caudate nucleus) controlling a more dedicated language subcircuit, which involves postero-temporal areas, supramarginal and angular gyri, Broca's area, and the superior longitudinal fasciculus.

  10. Stochastic modeling for neural spiking events based on fractional superstatistical Poisson process

    Directory of Open Access Journals (Sweden)

    Hidetoshi Konno

    2018-01-01

    Full Text Available In neural spike counting experiments, it is known that there are two main features: (i the counting number has a fractional power-law growth with time and (ii the waiting time (i.e., the inter-spike-interval distribution has a heavy tail. The method of superstatistical Poisson processes (SSPPs is examined whether these main features are properly modeled. Although various mixed/compound Poisson processes are generated with selecting a suitable distribution of the birth-rate of spiking neurons, only the second feature (ii can be modeled by the method of SSPPs. Namely, the first one (i associated with the effect of long-memory cannot be modeled properly. Then, it is shown that the two main features can be modeled successfully by a class of fractional SSPP (FSSPP.

  11. Neural sensitivity to social deviance predicts attentive processing of peer-group judgment.

    Science.gov (United States)

    Schnuerch, Robert; Trautmann-Lengsfeld, Sina Alexa; Bertram, Mario; Gibbons, Henning

    2014-01-01

    The detection of one's deviance from social norms is an essential mechanism of individual adjustment to group behavior and, thus, for the perpetuation of norms within groups. It has been suggested that error signals in mediofrontal cortex provide the neural basis of such deviance detection, which contributes to later adjustment to the norm. In the present study, we used event-related potentials (ERPs) to demonstrate that, across participants, the strength of mediofrontal brain correlates of the detection of deviance from a peer group's norms was negatively related to attentive processing of the same group's judgments in a later task. We propose that an individual's perception of social deviance might bias basic cognitive processing during further interaction with the group. Strongly perceiving disagreement with a group could cause an individual to avoid or inhibit this group's judgments.

  12. A probablistic neural network classification system for signal and image processing

    Energy Technology Data Exchange (ETDEWEB)

    Bowman, B. [Lawrence Livermore National Lab., CA (United States)

    1994-11-15

    The Acoustical Heart Valve Analysis Package is a system for signal and image processing and classification. It is being developed in both Matlab and C, to provide an interactive, interpreted environment, and has been optimized for large scale matrix operations. It has been used successfully to classify acoustic signals from implanted prosthetic heart valves in human patients, and will be integrated into a commercial Heart Valve Screening Center. The system uses several standard signal processing algorithms, as well as supervised learning techniques using the probabilistic neural network (PNN). Although currently used for the acoustic heart valve application, the algorithms and modular design allow it to be used for other applications, as well. We will describe the signal classification system, and show results from a set of test valves.

  13. Stochastic modeling for neural spiking events based on fractional superstatistical Poisson process

    Science.gov (United States)

    Konno, Hidetoshi; Tamura, Yoshiyasu

    2018-01-01

    In neural spike counting experiments, it is known that there are two main features: (i) the counting number has a fractional power-law growth with time and (ii) the waiting time (i.e., the inter-spike-interval) distribution has a heavy tail. The method of superstatistical Poisson processes (SSPPs) is examined whether these main features are properly modeled. Although various mixed/compound Poisson processes are generated with selecting a suitable distribution of the birth-rate of spiking neurons, only the second feature (ii) can be modeled by the method of SSPPs. Namely, the first one (i) associated with the effect of long-memory cannot be modeled properly. Then, it is shown that the two main features can be modeled successfully by a class of fractional SSPP (FSSPP).

  14. Neural responses to ambiguity involve domain-general and domain-specific emotion processing systems.

    Science.gov (United States)

    Neta, Maital; Kelley, William M; Whalen, Paul J

    2013-04-01

    Extant research has examined the process of decision making under uncertainty, specifically in situations of ambiguity. However, much of this work has been conducted in the context of semantic and low-level visual processing. An open question is whether ambiguity in social signals (e.g., emotional facial expressions) is processed similarly or whether a unique set of processors come on-line to resolve ambiguity in a social context. Our work has examined ambiguity using surprised facial expressions, as they have predicted both positive and negative outcomes in the past. Specifically, whereas some people tended to interpret surprise as negatively valenced, others tended toward a more positive interpretation. Here, we examined neural responses to social ambiguity using faces (surprise) and nonface emotional scenes (International Affective Picture System). Moreover, we examined whether these effects are specific to ambiguity resolution (i.e., judgments about the ambiguity) or whether similar effects would be demonstrated for incidental judgments (e.g., nonvalence judgments about ambiguously valenced stimuli). We found that a distinct task control (i.e., cingulo-opercular) network was more active when resolving ambiguity. We also found that activity in the ventral amygdala was greater to faces and scenes that were rated explicitly along the dimension of valence, consistent with findings that the ventral amygdala tracks valence. Taken together, there is a complex neural architecture that supports decision making in the presence of ambiguity: (a) a core set of cortical structures engaged for explicit ambiguity processing across stimulus boundaries and (b) other dedicated circuits for biologically relevant learning situations involving faces.

  15. Impact of load-related neural processes on feature binding in visuospatial working memory.

    Directory of Open Access Journals (Sweden)

    Nicole A Kochan

    Full Text Available BACKGROUND: The capacity of visual working memory (WM is substantially limited and only a fraction of what we see is maintained as a temporary trace. The process of binding visual features has been proposed as an adaptive means of minimising information demands on WM. However the neural mechanisms underlying this process, and its modulation by task and load effects, are not well understood. OBJECTIVE: To investigate the neural correlates of feature binding and its modulation by WM load during the sequential phases of encoding, maintenance and retrieval. METHODS AND FINDINGS: 18 young healthy participants performed a visuospatial WM task with independent factors of load and feature conjunction (object identity and position in an event-related functional MRI study. During stimulus encoding, load-invariant conjunction-related activity was observed in left prefrontal cortex and left hippocampus. During maintenance, greater activity for task demands of feature conjunction versus single features, and for increased load was observed in left-sided regions of the superior occipital cortex, precuneus and superior frontal cortex. Where these effects were expressed in overlapping cortical regions, their combined effect was additive. During retrieval, however, an interaction of load and feature conjunction was observed. This modulation of feature conjunction activity under increased load was expressed through greater deactivation in medial structures identified as part of the default mode network. CONCLUSIONS AND SIGNIFICANCE: The relationship between memory load and feature binding qualitatively differed through each phase of the WM task. Of particular interest was the interaction of these factors observed within regions of the default mode network during retrieval which we interpret as suggesting that at low loads, binding processes may be 'automatic' but at higher loads it becomes a resource-intensive process leading to disengagement of activity in this

  16. Neural cascade of conflict processing: not just time-on-task

    Science.gov (United States)

    McKay, Cameron C.; van den Berg, Berry; Woldorff, Marty G.

    2017-01-01

    In visual conflict tasks (e.g., Stroop or flanker), response times (RTs) are generally longer on incongruent trials relative to congruent ones. Two event-related-potential (ERP) components classically associated with the processing of stimulus conflict are the fronto-central, incongruency-related negativity (Ninc) and the posterior late-positive complex (LPC), which are derived from the ERP difference waves for incongruent minus congruent trials. It has been questioned, however, whether these effects, or other neural measures of incongruency (e.g., fMRI responses in the anterior cingulate), reflect true conflict processing, or whether such effects derive mainly from differential time-on-task. To address this question, we leveraged high-temporal-resolution ERP measures of brain activity during two behavioral tasks. The first task, a modified Erikson flanker paradigm (with congruent and incongruent trials), was used to evoke the classic RT and ERP effects associated with conflict. In the second, a non-conflict comparison condition, participants visually discriminated a single stimulus (with easy and hard discrimination conditions). Behaviorally, the parameters were titrated to yield similar RT effects of conflict and difficulty (27 ms). Neurally, both within-task contrasts showed an initial fronto-central negative-polarity wave (N2-latency effect), but they then diverged. In the difficulty difference wave, the initial negativity led directly into the posterior LPC, whereas in the incongruency contrast the initial negativity was followed a by a second fronto-central negative peak (Ninc), which was then followed by a considerably longer-latency LPC. These results provide clear evidence that the longer processing for incongruent stimulus inputs do not just reflect time-on-task or difficulty, but include a true conflict-processing component. PMID:28017818

  17. Trait Rumination Influences Neural Correlates of the Anticipation but Not the Consumption Phase of Reward Processing

    Directory of Open Access Journals (Sweden)

    Natália Kocsel

    2017-05-01

    Full Text Available Cumulative evidence suggests that trait rumination can be defined as an abstract information processing mode, which leads people to constantly anticipate the likely impact of present events on future events and experiences. A previous study with remitted depressed patients suggested that enhanced rumination tendencies distort brain mechanisms of anticipatory processes associated with reward and loss cues. In the present study, we explored the impact of trait rumination on neural activity during reward and loss anticipation among never-depressed people. We analyzed the data of 37 healthy controls, who performed the monetary incentive delay (MID task which was designed for the simultaneous measurement of the anticipation (motivational and consumption (hedonic phase of reward processing, during functional magnetic resonance imaging (fMRI. Our results show that rumination—after controlling for age, gender, and current mood—significantly influenced neural responses to reward (win cues compared to loss cues. Blood-oxygenation-level-dependent (BOLD activity in the left inferior frontal gyrus (IFG triangularis, left anterior insula, and left rolandic operculum was positively related to Ruminative Response Scale (RRS scores. We did not detect any significant rumination-related activations associated with win-neutral or loss-neutral cues and with reward or loss consumption. Our results highlight the influence of trait rumination on reward anticipation in a non-depressed sample. They also suggest that for never-depressed ruminators rewarding cues are more salient than loss cues. BOLD response during reward consumption did not relate to rumination, suggesting that rumination mainly relates to processing of the motivational (wanting aspect of reward rather than the hedonic (liking aspect, at least in the absence of pathological mood.

  18. Prediction of Emergency Department Hospital Admission Based on Natural Language Processing and Neural Networks.

    Science.gov (United States)

    Zhang, Xingyu; Kim, Joyce; Patzer, Rachel E; Pitts, Stephen R; Patzer, Aaron; Schrager, Justin D

    2017-10-26

    To describe and compare logistic regression and neural network modeling strategies to predict hospital admission or transfer following initial presentation to Emergency Department (ED) triage with and without the addition of natural language processing elements. Using data from the National Hospital Ambulatory Medical Care Survey (NHAMCS), a cross-sectional probability sample of United States EDs from 2012 and 2013 survey years, we developed several predictive models with the outcome being admission to the hospital or transfer vs. discharge home. We included patient characteristics immediately available after the patient has presented to the ED and undergone a triage process. We used this information to construct logistic regression (LR) and multilayer neural network models (MLNN) which included natural language processing (NLP) and principal component analysis from the patient's reason for visit. Ten-fold cross validation was used to test the predictive capacity of each model and receiver operating curves (AUC) were then calculated for each model. Of the 47,200 ED visits from 642 hospitals, 6,335 (13.42%) resulted in hospital admission (or transfer). A total of 48 principal components were extracted by NLP from the reason for visit fields, which explained 75% of the overall variance for hospitalization. In the model including only structured variables, the AUC was 0.824 (95% CI 0.818-0.830) for logistic regression and 0.823 (95% CI 0.817-0.829) for MLNN. Models including only free-text information generated AUC of 0.742 (95% CI 0.731- 0.753) for logistic regression and 0.753 (95% CI 0.742-0.764) for MLNN. When both structured variables and free text variables were included, the AUC reached 0.846 (95% CI 0.839-0.853) for logistic regression and 0.844 (95% CI 0.836-0.852) for MLNN. The predictive accuracy of hospital admission or transfer for patients who presented to ED triage overall was good, and was improved with the inclusion of free text data from a patient

  19. Applicability of Montreal Process Criterion 1 - conservation of biological diversity - to rangeland sustainability

    Science.gov (United States)

    Curtis H. Flather; Carolyn Hull Sieg

    2000-01-01

    Nine indicators of biodiversity conservation have been defined by the nations participating in the Montreal Process for assessing sustainability of temperate and boreal forests. Five of these indicators address compositional and spatial diversity of ecosystems; two address species diversity; and two are indirect measures of genetic diversity. Our objective was to...

  20. Ethical issues in engineering design processes ; regulative frameworks for safety and sustainability

    NARCIS (Netherlands)

    Gorp, A. van

    2007-01-01

    The ways designers deal with ethical issues that arise in their consideration of safety and sustainability in engineering design processes are described. In the case studies, upon which this article is based, a difference can be seen between normal and radical design. Designers refer to regulative

  1. Creating Sustainable Education Projects in Roatán, Honduras through Continuous Process Improvement

    Science.gov (United States)

    Raven, Arjan; Randolph, Adriane B.; Heil, Shelli

    2010-01-01

    The investigators worked together with permanent residents of Roatán, Honduras on sustainable initiatives to help improve the island's troubled educational programs. Our initiatives focused on increasing the number of students eligible and likely to attend a university. Using a methodology based in continuous process improvement, we developed…

  2. Teaching Methods Influencing the Sustainability of the Teaching Process in Technology Education in General Education Schools

    Science.gov (United States)

    Soobik, Mart

    2014-01-01

    The sustainability of technology education is related to a traditional understanding of craft and the methods used to teach it; however, the methods used in the teaching process have been influenced by the innovative changes accompanying the development of technology. In respect to social and economic development, it is important to prepare young…

  3. Does compliance to patient safety tasks improve and sustain when radiotherapy treatment processes are standardized?

    Science.gov (United States)

    Simons, Pascale A M; Houben, Ruud; Benders, Jos; Pijls-Johannesma, Madelon; Vandijck, Dominique; Marneffe, Wim; Backes, Huub; Groothuis, Siebren

    2014-10-01

    To realize safe radiotherapy treatment, processes must be stabilized. Standard operating procedures (SOP's) were expected to stabilize the treatment process and perceived task importance would increase sustainability in compliance. This paper presents the effects on compliance to safety related tasks of a process redesign based on lean principles. Compliance to patient safety tasks was measured by video recording of actual radiation treatment, before (T0), directly after (T1) and 1.5 years after (T2) a process redesign. Additionally, technologists were surveyed on perceived task importance and reported incidents were collected for three half-year periods between 2007 and 2009. Compliance to four out of eleven tasks increased at T1, of which improvements on three sustained (T2). Perceived importance of tasks strongly correlated (0.82) to compliance rates at T2. The two tasks, perceived as least important, presented low base-line compliance, improved (T1), but relapsed at T2. The reported near misses (patient-level not reached) on accelerators increased (P improvements sustained after 1.5 years, indicating increased stability. Perceived importance of tasks correlated positively to compliance and sustainability. Raising the perception of task importance is thus crucial to increase compliance. The redesign resulted in increased willingness to report incidents, creating opportunities for patient safety improvement in radiotherapy treatment. Copyright © 2014 Elsevier Ltd. All rights reserved.

  4. A Review of the Literature Related to the Change Process Schools Undergo to Sustain PLCs

    Science.gov (United States)

    Jones, Christopher M.; Thessin, Rebecca A.

    2015-01-01

    This literature review examines the existing literature on the role of the principal in the change process to create a context for change to both develop professional learning communities (PLCs) and sustain a context of continuous improvement over time. The Brown and Anfara (2003) framework was used as a theoretical lens to analyze the literature…

  5. Transition management as a model for managing processes of co-evolution towards sustainable development

    NARCIS (Netherlands)

    R. Kemp (René); D.A. Loorbach (Derk); J. Rotmans (Jan)

    2007-01-01

    textabstractSustainable development requires changes in socio-technical systems and wider societal change - in beliefs, values and governance that co-evolve with technology changes. In this article we present a practical model for managing processes of co-evolution: transition management. Transition

  6. Lateral Information Processing by Spiking Neurons: A Theoretical Model of the Neural Correlate of Consciousness

    Directory of Open Access Journals (Sweden)

    Marc Ebner

    2011-01-01

    Full Text Available Cognitive brain functions, for example, sensory perception, motor control and learning, are understood as computation by axonal-dendritic chemical synapses in networks of integrate-and-fire neurons. Cognitive brain functions may occur either consciously or nonconsciously (on “autopilot”. Conscious cognition is marked by gamma synchrony EEG, mediated largely by dendritic-dendritic gap junctions, sideways connections in input/integration layers. Gap-junction-connected neurons define a sub-network within a larger neural network. A theoretical model (the “conscious pilot” suggests that as gap junctions open and close, a gamma-synchronized subnetwork, or zone moves through the brain as an executive agent, converting nonconscious “auto-pilot” cognition to consciousness, and enhancing computation by coherent processing and collective integration. In this study we implemented sideways “gap junctions” in a single-layer artificial neural network to perform figure/ground separation. The set of neurons connected through gap junctions form a reconfigurable resistive grid or sub-network zone. In the model, outgoing spikes are temporally integrated and spatially averaged using the fixed resistive grid set up by neurons of similar function which are connected through gap-junctions. This spatial average, essentially a feedback signal from the neuron's output, determines whether particular gap junctions between neurons will open or close. Neurons connected through open gap junctions synchronize their output spikes. We have tested our gap-junction-defined sub-network in a one-layer neural network on artificial retinal inputs using real-world images. Our system is able to perform figure/ground separation where the laterally connected sub-network of neurons represents a perceived object. Even though we only show results for visual stimuli, our approach should generalize to other modalities. The system demonstrates a moving sub-network zone of

  7. A longitudinal study investigating neural processing of speech envelope modulation rates in children with (a family risk for) dyslexia.

    Science.gov (United States)

    De Vos, Astrid; Vanvooren, Sophie; Vanderauwera, Jolijn; Ghesquière, Pol; Wouters, Jan

    2017-08-01

    Recent evidence suggests that a fundamental deficit in the synchronization of neural oscillations to temporal information in speech may underlie phonological processing problems in dyslexia. Since previous studies were performed cross-sectionally in school-aged children or adults, developmental aspects of neural auditory processing in relation to reading acquisition and dyslexia remain to be investigated. The present longitudinal study followed 68 children during development from pre-reader (5 years old) to beginning reader (7 years old) and more advanced reader (9 years old). Thirty-six children had a family risk for dyslexia and 14 children eventually developed dyslexia. EEG recordings of auditory steady-state responses to 4 and 20 Hz modulations, corresponding to syllable and phoneme rates, were collected at each point in time. Our results demonstrate an increase in neural synchronization to phoneme-rate modulations around the onset of reading acquisition. This effect was negatively correlated with later reading and phonological skills, indicating that children who exhibit the largest increase in neural synchronization to phoneme rates, develop the poorest reading and phonological skills. Accordingly, neural synchronization to phoneme-rate modulations was found to be significantly higher in beginning and more advanced readers with dyslexia. We found no developmental effects regarding neural synchronization to syllable rates, nor any effects of a family risk for dyslexia. Altogether, our findings suggest that the onset of reading instruction coincides with an increase in neural responsiveness to phoneme-rate modulations, and that the extent of this increase is related to (the outcome of) reading development. Hereby, dyslexic children persistently demonstrate atypically high neural synchronization to phoneme rates from the beginning of reading acquisition onwards. Copyright © 2017 Elsevier Ltd. All rights reserved.

  8. The lean approach for improvement of the sustainability of a remanufacturing process

    Directory of Open Access Journals (Sweden)

    Paulina Golińska

    2014-09-01

    Full Text Available Background: The lean production is a well-established managerial concept, which helps companies to provide the customer value and to reduce cost. Recently it gains a lot of attention among the remanufacturers. In this paper the assumption is made that remanufacturing process is more sustainable, if there will be efficient utilization of the resources. The resource utilization is efficient when there is no waste of resources. The implementation of lean principles and tools into a remanufacturing process can benefit to improved sustainability but also it suffers some constrains, which are identified in this paper. Methods: The research methodology consists of a literature review, where research papers from the Scopus, Science Direct and Business Source Premier databases were used. The search criterion was the phrase "lean remanufacturing". On the basis of literature review the lean remanufacturing problems are identified. The framework for lean remanufacturing analysis was established. Author presents also case studies on assessment of the leanness of remanufacturing process and discusses the potential for waste elimination in order to improve sustainability of remanufacturing process. Results: Problem identification and analysis framework of lean remanufacturing process is discussed. The case studies results are analysed in the context of the finding of the literature review. The advantages and constrains of lean remanufacturing are discussed. Conclusions: A remanufacturing process is more complex than the respective production process. The implementation of lean production principles and tools into remanufacturing process is at a very early stage comparing to the traditional manufacturing. There are evidences from the industrial studies and the academic research on lean remanufacturing benefits. There is a need to distinguish between lean remanufacturing on an operational and a strategic level. From the perspective of sustainability of

  9. Analysis of Artificial Neural Network Backpropagation Using Conjugate Gradient Fletcher Reeves In The Predicting Process

    Science.gov (United States)

    Wanto, Anjar; Zarlis, Muhammad; Sawaluddin; Hartama, Dedy

    2017-12-01

    Backpropagation is a good artificial neural network algorithm used to predict, one of which is to predict the rate of Consumer Price Index (CPI) based on the foodstuff sector. While conjugate gradient fletcher reeves is a suitable optimization method when juxtaposed with backpropagation method, because this method can shorten iteration without reducing the quality of training and testing result. Consumer Price Index (CPI) data that will be predicted to come from the Central Statistics Agency (BPS) Pematangsiantar. The results of this study will be expected to contribute to the government in making policies to improve economic growth. In this study, the data obtained will be processed by conducting training and testing with artificial neural network backpropagation by using parameter learning rate 0,01 and target error minimum that is 0.001-0,09. The training network is built with binary and bipolar sigmoid activation functions. After the results with backpropagation are obtained, it will then be optimized using the conjugate gradient fletcher reeves method by conducting the same training and testing based on 5 predefined network architectures. The result, the method used can increase the speed and accuracy result.

  10. A neural model of motion processing and visual navigation by cortical area MST.

    Science.gov (United States)

    Grossberg, S; Mingolla, E; Pack, C

    1999-12-01

    Cells in the dorsal medial superior temporal cortex (MSTd) process optic flow generated by self-motion during visually guided navigation. A neural model shows how interactions between well-known neural mechanisms (log polar cortical magnification, Gaussian motion-sensitive receptive fields, spatial pooling of motion-sensitive signals and subtractive extraretinal eye movement signals) lead to emergent properties that quantitatively simulate neurophysiological data about MSTd cell properties and psychophysical data about human navigation. Model cells match MSTd neuron responses to optic flow stimuli placed in different parts of the visual field, including position invariance, tuning curves, preferred spiral directions, direction reversals, average response curves and preferred locations for stimulus motion centers. The model shows how the preferred motion direction of the most active MSTd cells can explain human judgments of self-motion direction (heading), without using complex heading templates. The model explains when extraretinal eye movement signals are needed for accurate heading perception, and when retinal input is sufficient, and how heading judgments depend on scene layouts and rotation rates.

  11. Higher-order neural processing tunes motion neurons to visual ecology in three species of hawkmoths.

    Science.gov (United States)

    Stöckl, A L; O'Carroll, D; Warrant, E J

    2017-06-28

    To sample information optimally, sensory systems must adapt to the ecological demands of each animal species. These adaptations can occur peripherally, in the anatomical structures of sensory organs and their receptors; and centrally, as higher-order neural processing in the brain. While a rich body of investigations has focused on peripheral adaptations, our understanding is sparse when it comes to central mechanisms. We quantified how peripheral adaptations in the eyes, and central adaptations in the wide-field motion vision system, set the trade-off between resolution and sensitivity in three species of hawkmoths active at very different light levels: nocturnal Deilephila elpenor, crepuscular Manduca sexta , and diurnal Macroglossum stellatarum. Using optical measurements and physiological recordings from the photoreceptors and wide-field motion neurons in the lobula complex, we demonstrate that all three species use spatial and temporal summation to improve visual performance in dim light. The diurnal Macroglossum relies least on summation, but can only see at brighter intensities. Manduca, with large sensitive eyes, relies less on neural summation than the smaller eyed Deilephila , but both species attain similar visual performance at nocturnal light levels. Our results reveal how the visual systems of these three hawkmoth species are intimately matched to their visual ecologies. © 2017 The Author(s).

  12. Age associations with neural processing of reward anticipation in adolescents with bipolar disorders

    Science.gov (United States)

    Urošević, Snežana; Luciana, Monica; Jensen, Jonathan B.; Youngstrom, Eric A.; Thomas, Kathleen M.

    2016-01-01

    Reward/behavioral approach system hypersensitivity is implicated in bipolar disorders (BD) and in normative development during adolescence. Pediatric onset of BD is associated with a more severe illness course. However, little is known about neural processing of rewards in adolescents with BD or developmental (i.e., age) associations with activation of these neural systems. The present study aims to address this knowledge gap. The present sample included 21 adolescents with BD and 26 healthy adolescents, ages 13 to 19. Participants completed a functional magnetic resonance imaging (fMRI) protocol using the Monetary Incentive Delay (MID) task. Behavioral performance was similar between groups. Group differences in BOLD activation during target anticipation and feedback anticipation periods of the task were examined using whole-brain analyses, as were group differences in age effects. During both target anticipation and feedback anticipation, adolescents with BD, compared to adolescents without psychopathology, exhibited decreased engagement of frontal regions involved in cognitive control (i.e., dorsolateral prefrontal cortex). Healthy adolescents exhibited age-related decreases, while adolescents with BD exhibited age-related increases, in activity of other cognitive control frontal areas (i.e., right inferior frontal gyrus), suggesting altered development in the BD group. Longitudinal research is needed to examine potentially abnormal development of cognitive control during reward pursuit in adolescent BD and whether early therapeutic interventions can prevent these potential deviations from normative development. PMID:27114896

  13. A neural model for transient identification in dynamic processes with 'don't know' response

    International Nuclear Information System (INIS)

    Mol, Antonio C. de A.; Martinez, Aquilino S.; Schirru, Roberto

    2003-01-01

    This work presents an approach for neural network based transient identification which allows either dynamic identification or a 'don't know' response. The approach uses two 'jump' multilayer neural networks (NN) trained with the backpropagation algorithm. The 'jump' network is used because it is useful to dealing with very complex patterns, which is the case of the space of the state variables during some abnormal events. The first one is responsible for the dynamic identification. This NN uses, as input, a short set (in a moving time window) of recent measurements of each variable avoiding the necessity of using starting events. The other one is used to validate the instantaneous identification (from the first net) through the validation of each variable. This net is responsible for allowing the system to provide a 'don't know' response. In order to validate the method, a Nuclear Power Plant (NPP) transient identification problem comprising 15 postulated accidents, simulated for a pressurized water reactor (PWR), was proposed in the validation process it has been considered noisy data in order to evaluate the method robustness. Obtained results reveal the ability of the method in dealing with both dynamic identification of transients and correct 'don't know' response. Another important point studied in this work is that the system has shown to be independent of a trigger signal which indicates the beginning of the transient, thus making it robust in relation to this limitation

  14. Adaptive neural reward processing during anticipation and receipt of monetary rewards in mindfulness meditators.

    Science.gov (United States)

    Kirk, Ulrich; Brown, Kirk Warren; Downar, Jonathan

    2015-05-01

    Reward seeking is ubiquitous and adaptive in humans. But excessive reward seeking behavior, such as chasing monetary rewards, may lead to diminished subjective well-being. This study examined whether individuals trained in mindfulness meditation show neural evidence of lower susceptibility to monetary rewards. Seventy-eight participants (34 meditators, 44 matched controls) completed the monetary incentive delay task while undergoing functional magnetic resonance imaging. The groups performed equally on the task, but meditators showed lower neural activations in the caudate nucleus during reward anticipation, and elevated bilateral posterior insula activation during reward anticipation. Meditators also evidenced reduced activations in the ventromedial prefrontal cortex during reward receipt compared with controls. Connectivity parameters between the right caudate and bilateral anterior insula were attenuated in meditators during incentive anticipation. In summary, brain regions involved in reward processing-both during reward anticipation and receipt of reward-responded differently in mindfulness meditators than in nonmeditators, indicating that the former are less susceptible to monetary incentives. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  15. Age associations with neural processing of reward anticipation in adolescents with bipolar disorders

    Directory of Open Access Journals (Sweden)

    Snežana Urošević

    2016-01-01

    Full Text Available Reward/behavioral approach system hypersensitivity is implicated in bipolar disorders (BD and in normative development during adolescence. Pediatric onset of BD is associated with a more severe illness course. However, little is known about neural processing of rewards in adolescents with BD or developmental (i.e., age associations with activation of these neural systems. The present study aims to address this knowledge gap. The present sample included 21 adolescents with BD and 26 healthy adolescents, ages 13 to 19. Participants completed a functional magnetic resonance imaging (fMRI protocol using the Monetary Incentive Delay (MID task. Behavioral performance was similar between groups. Group differences in BOLD activation during target anticipation and feedback anticipation periods of the task were examined using whole-brain analyses, as were group differences in age effects. During both target anticipation and feedback anticipation, adolescents with BD, compared to adolescents without psychopathology, exhibited decreased engagement of frontal regions involved in cognitive control (i.e., dorsolateral prefrontal cortex. Healthy adolescents exhibited age-related decreases, while adolescents with BD exhibited age-related increases, in activity of other cognitive control frontal areas (i.e., right inferior frontal gyrus, suggesting altered development in the BD group. Longitudinal research is needed to examine potentially abnormal development of cognitive control during reward pursuit in adolescent BD and whether early therapeutic interventions can prevent these potential deviations from normative development.

  16. Co-speech gestures influence neural activity in brain regions associated with processing semantic information.

    Science.gov (United States)

    Dick, Anthony Steven; Goldin-Meadow, Susan; Hasson, Uri; Skipper, Jeremy I; Small, Steven L

    2009-11-01

    Everyday communication is accompanied by visual information from several sources, including co-speech gestures, which provide semantic information listeners use to help disambiguate the speaker's message. Using fMRI, we examined how gestures influence neural activity in brain regions associated with processing semantic information. The BOLD response was recorded while participants listened to stories under three audiovisual conditions and one auditory-only (speech alone) condition. In the first audiovisual condition, the storyteller produced gestures that naturally accompany speech. In the second, the storyteller made semantically unrelated hand movements. In the third, the storyteller kept her hands still. In addition to inferior parietal and posterior superior and middle temporal regions, bilateral posterior superior temporal sulcus and left anterior inferior frontal gyrus responded more strongly to speech when it was further accompanied by gesture, regardless of the semantic relation to speech. However, the right inferior frontal gyrus was sensitive to the semantic import of the hand movements, demonstrating more activity when hand movements were semantically unrelated to the accompanying speech. These findings show that perceiving hand movements during speech modulates the distributed pattern of neural activation involved in both biological motion perception and discourse comprehension, suggesting listeners attempt to find meaning, not only in the words speakers produce, but also in the hand movements that accompany speech.

  17. Experimental study and artificial neural network modeling of tartrazine removal by photocatalytic process under solar light.

    Science.gov (United States)

    Sebti, Aicha; Souahi, Fatiha; Mohellebi, Faroudja; Igoud, Sadek

    2017-07-01

    This research focuses on the application of an artificial neural network (ANN) to predict the removal efficiency of tartrazine from simulated wastewater using a photocatalytic process under solar illumination. A program is developed in Matlab software to optimize the neural network architecture and select the suitable combination of training algorithm, activation function and hidden neurons number. The experimental results of a batch reactor operated under different conditions of pH, TiO 2 concentration, initial organic pollutant concentration and solar radiation intensity are used to train, validate and test the networks. While negligible mineralization is demonstrated, the experimental results show that under sunlight irradiation, 85% of tartrazine is removed after 300 min using only 0.3 g/L of TiO 2 powder. Therefore, irradiation time is prolonged and almost 66% of total organic carbon is reduced after 15 hours. ANN 5-8-1 with Bayesian regulation back-propagation algorithm and hyperbolic tangent sigmoid transfer function is found to be able to predict the response with high accuracy. In addition, the connection weights approach is used to assess the importance contribution of each input variable on the ANN model response. Among the five experimental parameters, the irradiation time has the greatest effect on the removal efficiency of tartrazine.

  18. A Pontine Region is a Neural Correlate of the Human Affective Processing Network

    Directory of Open Access Journals (Sweden)

    Tatia M.C. Lee

    2015-11-01

    Full Text Available The in vivo neural activity of the pons during the perception of affective stimuli has not been studied despite the strong implications of its role in affective processing. To examine the activity of the pons during the viewing of affective stimuli, and to verify its functional and structural connectivity with other affective neural correlates, a multimodal magnetic resonance imaging methodology was employed in this study. We observed the in vivo activity of the pons when viewing affective stimuli. Furthermore, small-world connectivity indicated that the functional connectivity (FC between the pons and the cortico-limbic affective regions was meaningful, with the coefficient λ being positively associated with self-reported emotional reactivity. The FC between the pons and the cortico-limbic-striatal areas was related to self-reported negative affect. Corroborating this finding was the observation that the tract passing through the pons and the left hippocampus was negatively related to self-reported positive affect and positively correlated with emotional reactivity. Our findings support the framework that the pons works conjunctively with the distributed cortico-limbic-striatal systems in shaping individuals' affective states and reactivity. Our work paves the path for future research on the contribution of the pons to the precipitation and maintenance of affective disorders.

  19. Modeling of yield and environmental impact categories in tea processing units based on artificial neural networks.

    Science.gov (United States)

    Khanali, Majid; Mobli, Hossein; Hosseinzadeh-Bandbafha, Homa

    2017-12-01

    In this study, an artificial neural network (ANN) model was developed for predicting the yield and life cycle environmental impacts based on energy inputs required in processing of black tea, green tea, and oolong tea in Guilan province of Iran. A life cycle assessment (LCA) approach was used to investigate the environmental impact categories of processed tea based on the cradle to gate approach, i.e., from production of input materials using raw materials to the gate of tea processing units, i.e., packaged tea. Thus, all the tea processing operations such as withering, rolling, fermentation, drying, and packaging were considered in the analysis. The initial data were obtained from tea processing units while the required data about the background system was extracted from the EcoInvent 2.2 database. LCA results indicated that diesel fuel and corrugated paper box used in drying and packaging operations, respectively, were the main hotspots. Black tea processing unit caused the highest pollution among the three processing units. Three feed-forward back-propagation ANN models based on Levenberg-Marquardt training algorithm with two hidden layers accompanied by sigmoid activation functions and a linear transfer function in output layer, were applied for three types of processed tea. The neural networks were developed based on energy equivalents of eight different input parameters (energy equivalents of fresh tea leaves, human labor, diesel fuel, electricity, adhesive, carton, corrugated paper box, and transportation) and 11 output parameters (yield, global warming, abiotic depletion, acidification, eutrophication, ozone layer depletion, human toxicity, freshwater aquatic ecotoxicity, marine aquatic ecotoxicity, terrestrial ecotoxicity, and photochemical oxidation). The results showed that the developed ANN models with R 2 values in the range of 0.878 to 0.990 had excellent performance in predicting all the output variables based on inputs. Energy consumption for

  20. Neural regions supporting lexical processing of objects and actions: A case series analysis

    Directory of Open Access Journals (Sweden)

    Bonnie L Breining

    2014-04-01

    Full Text Available Introduction. Linking semantic representations to lexical items is an important cognitive process for both producing and comprehending language. Past research has suggested that the bilateral anterior temporal lobes are critical for this process (e.g. Patterson, Nestor, & Rogers, 2007. However, the majority of studies focused on object concepts alone, ignoring actions. The few that considered actions suggest that the temporal poles are not critical for their processing (e.g. Kemmerer et al., 2010. In this case series, we investigated the neural substrates of linking object and action concepts to lexical labels by correlating the volume of defined regions of interest with behavioral performance on picture-word verification and picture naming tasks of individuals with primary progressive aphasia (PPA. PPA is a neurodegenerative condition with heterogeneous neuropathological causes, characterized by increasing language deficits for at least two years in the face of relatively intact cognitive function in other domains (Gorno-Tempini et al., 2011. This population displays appropriate heterogeneity of performance and focal atrophy for investigating the neural substrates involved in lexical semantic processing of objects and actions. Method. Twenty-one individuals with PPA participated in behavioral assessment within six months of high resolution anatomical MRI scans. Behavioral assessments consisted of four tasks: picture-word verification and picture naming of objects and actions. Performance on these assessments was correlated with brain volume measured using atlas-based analysis in twenty regions of interest that are commonly atrophied in PPA and implicated in language processing. Results. Impaired performance for all four tasks significantly correlated with atrophy in the right superior temporal pole, left anterior middle temporal gyrus, and left fusiform gyrus. No regions were identified in which volume correlated with performance for both

  1. The Effect of Early Visual Deprivation on the Neural Bases of Auditory Processing.

    Science.gov (United States)

    Guerreiro, Maria J S; Putzar, Lisa; Röder, Brigitte

    2016-02-03

    Transient congenital visual deprivation affects visual and multisensory processing. In contrast, the extent to which it affects auditory processing has not been investigated systematically. Research in permanently blind individuals has revealed brain reorganization during auditory processing, involving both intramodal and crossmodal plasticity. The present study investigated the effect of transient congenital visual deprivation on the neural bases of auditory processing in humans. Cataract-reversal individuals and normally sighted controls performed a speech-in-noise task while undergoing functional magnetic resonance imaging. Although there were no behavioral group differences, groups differed in auditory cortical responses: in the normally sighted group, auditory cortex activation increased with increasing noise level, whereas in the cataract-reversal group, no activation difference was observed across noise levels. An auditory activation of visual cortex was not observed at the group level in cataract-reversal individuals. The present data suggest prevailing auditory processing advantages after transient congenital visual deprivation, even many years after sight restoration. The present study demonstrates that people whose sight was restored after a transient period of congenital blindness show more efficient cortical processing of auditory stimuli (here speech), similarly to what has been observed in congenitally permanently blind individuals. These results underscore the importance of early sensory experience in permanently shaping brain function. Copyright © 2016 the authors 0270-6474/16/361620-11$15.00/0.

  2. Understanding sustainable diets: a descriptive analysis of the determinants and processes that influence diets and their impact on health, food security, and environmental sustainability.

    Science.gov (United States)

    Johnston, Jessica L; Fanzo, Jessica C; Cogill, Bruce

    2014-07-01

    The confluence of population, economic development, and environmental pressures resulting from increased globalization and industrialization reveal an increasingly resource-constrained world in which predictions point to the need to do more with less and in a "better" way. The concept of sustainable diets presents an opportunity to successfully advance commitments to sustainable development and the elimination of poverty, food and nutrition insecurity, and poor health outcomes. This study examines the determinants of sustainable diets, offers a descriptive analysis of these areas, and presents a causal model and framework from which to build. The major determinants of sustainable diets fall into 5 categories: 1) agriculture, 2) health, 3) sociocultural, 4) environmental, and 5) socioeconomic. When factors or processes are changed in 1 determinant category, such changes affect other determinant categories and, in turn, the level of "sustainability" of a diet. The complex web of determinants of sustainable diets makes it challenging for policymakers to understand the benefits and considerations for promoting, processing, and consuming such diets. To advance this work, better measurements and indicators must be developed to assess the impact of the various determinants on the sustainability of a diet and the tradeoffs associated with any recommendations aimed at increasing the sustainability of our food system. © 2014 American Society for Nutrition.

  3. Grassland Sustainability

    Science.gov (United States)

    Deborah U. Potter; Paulette L. Ford

    2004-01-01

    In this chapter we discuss grassland sustainability in the Southwest, grassland management for sustainability, national and local criteria and indicators of sustainable grassland ecosystems, and monitoring for sustainability at various scales. Ecological sustainability is defined as: [T]he maintenance or restoration of the composition, structure, and processes of...

  4. Sensitivity analysis of technological, economic and sustainability evaluation of power plants using the analytic hierarchy process

    International Nuclear Information System (INIS)

    Chatzimouratidis, Athanasios I.; Pilavachi, Petros A.

    2009-01-01

    Technological, economic and sustainability evaluation of power plants by use of the analytic hierarchy process and nine end node criteria for a reference scenario based on subjective criteria weighting has been presented in a previous paper by authors. However, criteria weight variations may substantially modify overall evaluations and rankings of power plants. The current paper presents a sensitivity analysis with four alternative scenarios (sets of criteria weights) compared with the reference scenario. The results show that priority to 'technology and sustainability' favors renewable energy power plants, while priority to 'economic' criteria favors mainly nuclear power plants and less the four types of fossil fuel power plant

  5. A Method for Sustainable Carbon Dioxide Utilization Process Synthesis and Design

    DEFF Research Database (Denmark)

    Frauzem, Rebecca; Fjellerup, Kasper; Roh, Kosan

    As a result of increasing regulations and concern about the impact of greenhouse gases on the environment, carbon dioxide (CO2) emissions are a primary focus for reducing emissions and improving global sustainability. One method to achieve reduced emissions, is the conversion of CO2 to useful...... compounds via chemical reactions. However, conversion is still in its infancy and requires work for implementation at an industrial level. One aspect of this is the development of a methodology for the formulation and optimization of sustainable conversion processes. This methodology follows three stages...

  6. Interaction matters: A perceived social partner alters the neural processing of human speech.

    Science.gov (United States)

    Rice, Katherine; Redcay, Elizabeth

    2016-04-01

    Mounting evidence suggests that social interaction changes how communicative behaviors (e.g., spoken language, gaze) are processed, but the precise neural bases by which social-interactive context may alter communication remain unknown. Various perspectives suggest that live interactions are more rewarding, more attention-grabbing, or require increased mentalizing-thinking about the thoughts of others. Dissociating between these possibilities is difficult because most extant neuroimaging paradigms examining social interaction have not directly compared live paradigms to conventional "offline" (or recorded) paradigms. We developed a novel fMRI paradigm to assess whether and how an interactive context changes the processing of speech matched in content and vocal characteristics. Participants listened to short vignettes--which contained no reference to people or mental states--believing that some vignettes were prerecorded and that others were presented over a real-time audio-feed by a live social partner. In actuality, all speech was prerecorded. Simply believing that speech was live increased activation in each participant's own mentalizing regions, defined using a functional localizer. Contrasting live to recorded speech did not reveal significant differences in attention or reward regions. Further, higher levels of autistic-like traits were associated with altered neural specialization for live interaction. These results suggest that humans engage in ongoing mentalizing about social partners, even when such mentalizing is not explicitly required, illustrating how social context shapes social cognition. Understanding communication in social context has important implications for typical and atypical social processing, especially for disorders like autism where social difficulties are more acute in live interaction. Copyright © 2015 Elsevier Inc. All rights reserved.

  7. Altered neural processing of reward and punishment in adolescents with Major Depressive Disorder.

    Science.gov (United States)

    Landes, I; Bakos, S; Kohls, G; Bartling, J; Schulte-Körne, G; Greimel, E

    2018-05-01

    Altered reward and punishment function has been suggested as an important vulnerability factor for the development of Major Depressive Disorder (MDD). Prior ERP studies found evidence for neurophysiological dysfunctions in reinforcement processes in adults with MDD. To date, only few ERP studies have examined the neural underpinnings of reinforcement processing in adolescents diagnosed with MDD. The present event-related potential (ERP) study aimed to investigate neurophysiological mechanisms of anticipation and consumption of reward and punishment in adolescents with MDD in one comprehensive paradigm. During ERP recording, 25 adolescents with MDD and 29 healthy controls (12-17 years) completed a Monetary Incentive Delay Task comprising both a monetary reward and a monetary punishment condition. During anticipation, the cue-P3 signaling attentional allocation was recorded. During consumption, the feedback-P3 and Reward Positivity (RewP) were recorded to capture attentional allocation and outcome evaluation, respectively. Compared to controls, adolescents with MDD showed prolonged cue-P3 latencies to reward cues. Furthermore, unlike controls, adolescents with MDD displayed shorter feedback-P3 latencies in the reward versus punishment condition. RewPs did not differ between groups. It remains unanswered whether the observed alterations in adolescent MDD represent a state or trait. Delayed neural processing of reward cues corresponds to the clinical presentation of adolescent MDD with reduced motivational tendencies to obtain rewards. Relatively shorter feedback-P3 latencies in the reward versus punishment condition could indicate a high salience of performance-contingent reward. Frequent exposure of negatively biased adolescents with MDD to performance-contingent rewards might constitute a promising intervention approach. Copyright © 2018 Elsevier B.V. All rights reserved.

  8. FGF8 signaling sustains progenitor status and multipotency of cranial neural crest-derived mesenchymal cells in vivo and in vitro

    Science.gov (United States)

    Shao, Meiying; Liu, Chao; Song, Yingnan; Ye, Wenduo; He, Wei; Yuan, Guohua; Gu, Shuping; Lin, Congxin; Ma, Liang; Zhang, Yanding; Tian, Weidong; Hu, Tao; Chen, YiPing

    2015-01-01

    The cranial neural crest (CNC) cells play a vital role in craniofacial development and regeneration. They are multi-potent progenitors, being able to differentiate into various types of tissues. Both pre-migratory and post-migratory CNC cells are plastic, taking on diverse fates by responding to different inductive signals. However, what sustains the multipotency of CNC cells and derivatives remains largely unknown. In this study, we present evidence that FGF8 signaling is able to sustain progenitor status and multipotency of CNC-derived mesenchymal cells both in vivo and in vitro. We show that augmented FGF8 signaling in pre-migratory CNC cells prevents cell differentiation and organogenesis in the craniofacial region by maintaining their progenitor status. CNC-derived mesenchymal cells with Fgf8 overexpression or control cells in the presence of exogenous FGF8 exhibit prolonged survival, proliferation, and multi-potent differentiation capability in cell cultures. Remarkably, exogenous FGF8 also sustains the capability of CNC-derived mesenchymal cells to participate in organogenesis such as odontogenesis. Furthermore, FGF8-mediated signaling strongly promotes adipogenesis but inhibits osteogenesis of CNC-derived mesenchymal cells in vitro. Our results reveal a specific role for FGF8 in the maintenance of progenitor status and in fate determination of CNC cells, implicating a potential application in expansion and fate manipulation of CNC-derived cells in stem cell-based craniofacial regeneration. PMID:26243590

  9. Adolescent transformations of behavioral and neural processes as potential targets for prevention.

    Science.gov (United States)

    Eldreth, Dana; Hardin, Michael G; Pavletic, Nevia; Ernst, Monique

    2013-06-01

    Adolescence is a transitional period in development that is marked by a distinct, typical behavioral profile of high rates of exploration, novelty-seeking, and emotional lability. While these behaviors generally assist the adolescent transition to independence, they can also confer vulnerability for excessive risk-taking and psychopathology, particularly in the context of specific environmental or genetic influences. As prevention research depends on the identification of targets of vulnerability, the following review will discuss the interplay among motivational systems including reward-related, avoidance-related, and regulatory processes in typical and atypical adolescent development. Each set of processes will be discussed in relation to their underlying neural correlates and distinct developmental trajectories. Evidence suggests that typical adolescent behavior and the risk for atypical development are mediated by heightened adolescent responsiveness of reward-related and avoidance-related systems under specific conditions, concurrent with poor modulation by immature regulatory processes. Finally, we will propose strategies to exploit heightened reward processing to reinforce inhibitory control, which is an essential component of regulatory processes in prevention interventions.

  10. Neural correlates of British sign language comprehension: spatial processing demands of topographic language.

    Science.gov (United States)

    MacSweeney, Mairéad; Woll, Bencie; Campbell, Ruth; Calvert, Gemma A; McGuire, Philip K; David, Anthony S; Simmons, Andrew; Brammer, Michael J

    2002-10-01

    In all signed languages used by deaf people, signs are executed in "sign space" in front of the body. Some signed sentences use this space to map detailed "real-world" spatial relationships directly. Such sentences can be considered to exploit sign space "topographically." Using functional magnetic resonance imaging, we explored the extent to which increasing the topographic processing demands of signed sentences was reflected in the differential recruitment of brain regions in deaf and hearing native signers of the British Sign Language. When BSL signers performed a sentence anomaly judgement task, the occipito-temporal junction was activated bilaterally to a greater extent for topographic than nontopographic processing. The differential role of movement in the processing of the two sentence types may account for this finding. In addition, enhanced activation was observed in the left inferior and superior parietal lobules during processing of topographic BSL sentences. We argue that the left parietal lobe is specifically involved in processing the precise configuration and location of hands in space to represent objects, agents, and actions. Importantly, no differences in these regions were observed when hearing people heard and saw English translations of these sentences. Despite the high degree of similarity in the neural systems underlying signed and spoken languages, exploring the linguistic features which are unique to each of these broadens our understanding of the systems involved in language comprehension.

  11. Neural Correlates of Attentional Processing of Threat in Youth with and without Anxiety Disorders.

    Science.gov (United States)

    Bechor, Michele; Ramos, Michelle L; Crowley, Michael J; Silverman, Wendy K; Pettit, Jeremy W; Reeb-Sutherland, Bethany C

    2018-04-02

    Late-stage attentional processing of threatening stimuli, quantified through event-related potentials (ERPs), differentiates youth with and without anxiety disorders. It is unknown whether early-stage attentional processing of threatening stimuli differentiates these groups. Examining both early and late stage attentional processes in youth may advance knowledge and enhance efforts to identify biomarkers for translational prevention and treatment research. Twenty-one youth with primary DSM-IV-TR anxiety disorders (10 males, ages 8-15 years) and 21 typically developing Controls (15 males, ages 8-16 years) completed a dot probe task while electroencephalography (EEG) was recorded, and ERPs were examined. Youth with anxiety disorders showed significantly larger (more positive) P1 amplitudes for threatening stimuli than for neutral stimuli, and Controls showed the opposite pattern. Youth with anxiety showed larger (more negative) N170 amplitudes compared with Controls. Controls showed significantly larger (more positive) P2 and P3 amplitudes, regardless of stimuli valence, compared with youth with anxiety disorders. ERPs observed during the dot probe task indicate youth with anxiety disorders display distinct neural processing during early stage attentional orienting and processing of faces; this was not the case for Controls. Such results suggest these ERP components may have potential as biomarkers of anxiety disorders in youth.

  12. How right is left? Handedness modulates neural responses during morphosyntactic processing.

    Science.gov (United States)

    Grey, Sarah; Tanner, Darren; van Hell, Janet G

    2017-08-15

    Most neurocognitive models of language processing generally assume population-wide homogeneity in the neural mechanisms used during language comprehension, yet individual differences are known to influence these neural mechanisms. In this study, we focus on handedness as an individual difference hypothesized to affect language comprehension. Left-handers and right-handers with a left-handed blood relative, or familial sinistrals, are hypothesized to process language differently than right-handers with no left-handed relatives (Hancock and Bever, 2013; Ullman, 2004). Yet, left-handers are often excluded from neurocognitive language research, and familial sinistrality in right-handers is often not taken into account. In the current study we used event-related potentials to test morphosyntactic processing in three groups that differed in their handedness profiles: left-handers (LH), right-handers with a left-handed blood relative (RH FS+), and right-handers with no reported left-handed blood relative (RH FS-; both right-handed groups were previously tested by Tanner and Van Hell, 2014). Results indicated that the RH FS- group showed only P600 responses during morphosyntactic processing whereas the LH and RH FS+ groups showed biphasic N400-P600 patterns. N400s in LH and RH FS+ groups are consistent with theories that associate left-handedness (self or familial) with increased reliance on lexical/semantic mechanisms during language processing. Inspection of individual-level results illustrated that variability in RH FS- individuals' morphosyntactic processing was remarkably low: most individuals were P600-dominant. In contrast, LH and RH FS+ individuals showed marked variability in brain responses, which was similar for both groups: half of individuals were N400-dominant and half were P600-dominant. Our findings have implications for neurocognitive models of language that have been largely formulated around data from only right-handers without accounting for familial

  13. A Systematic Approach for Conceptual and Sustainable Process Design: Production of Methylamines From Methanol and Ammonia

    DEFF Research Database (Denmark)

    Mansouri, Seyed Soheil; Ismail, Muhammad Imran Bin; Almoor, Karim

    2012-01-01

    and environmentally acceptable plant for producing mono-methylamines, di-methylamines and tri-methylamines from methanol and ammonia. The systematic method divides the process design work into 12 sequential tasks that covers all stages of conceptual design, starting from the consideration of qualitative aspects...... of the process flow sheet and preliminary calculations to the detailed process simulations, equipment sizing, costing, an economic evaluation, and sustainability of the designed process. At the end of task-9, the base case design is obtained, which is then further refined and improved with respect to heat...

  14. THE ACTIVE INTEGRATED CIRCULAR PROCESS – EXPRESSION OF MAXIMUM SYNTHESIS OF SUSTAINABLE DEVELOPMENT

    Directory of Open Access Journals (Sweden)

    Done Ioan

    2015-06-01

    Full Text Available "The accelerated pace of economic growth, prompted by the need to ensure reducing disparities between the various countries, has imposed in the last two decades the adoption of sustainable development principles, particularly as a result of the Rio Declaration on Environment and Development (1992 and the UNESCO Declaration in the fall of 1997. In specific literature, in essence, sustainable development is considered "an economic and social process that is characterized by a simultaneous and concerted action at global, regional and local level. Its objective is to provide living conditions both for the present and forth future. Sustainable development “encompasses the economic, ecological, social and political aspects, linked through cultural and spiritual relationships."(Coşea, 2007In Romania, achieving sustainable development is a major, difficult objective, because it must be done in terms of convergence to the demands of the economic, social, cultural and political context of the EU, and in terms of the completion of the transition to a functioning and competitive market economy. In this context, it is imposed the economic competitiveness through reindustrialization and not least, by harnessing the active integrated circular process. Gross value added and profit chain in the structures of active integrated circular process must reflect the interests of the forces involved(employers, employees and the statethereby forming the basis of respect for the correlation between sustainable development, economic growth and increasing national wealth. The elimination or marginalization of certain links in the value chain and profit causes major disruptions or bankruptcy, with direct implications for recognizing and rewarding performance. Essentially, the building of active integrated circular process will determine the maximization of the profit – the foundation of satisfying all economic interests.

  15. Expanding the occupational health methodology: A concatenated artificial neural network approach to model the burnout process in Chinese nurses.

    Science.gov (United States)

    Ladstätter, Felix; Garrosa, Eva; Moreno-Jiménez, Bernardo; Ponsoda, Vicente; Reales Aviles, José Manuel; Dai, Junming

    2016-01-01

    Artificial neural networks are sophisticated modelling and prediction tools capable of extracting complex, non-linear relationships between predictor (input) and predicted (output) variables. This study explores this capacity by modelling non-linearities in the hardiness-modulated burnout process with a neural network. Specifically, two multi-layer feed-forward artificial neural networks are concatenated in an attempt to model the composite non-linear burnout process. Sensitivity analysis, a Monte Carlo-based global simulation technique, is then utilised to examine the first-order effects of the predictor variables on the burnout sub-dimensions and consequences. Results show that (1) this concatenated artificial neural network approach is feasible to model the burnout process, (2) sensitivity analysis is a prolific method to study the relative importance of predictor variables and (3) the relationships among variables involved in the development of burnout and its consequences are to different degrees non-linear. Many relationships among variables (e.g., stressors and strains) are not linear, yet researchers use linear methods such as Pearson correlation or linear regression to analyse these relationships. Artificial neural network analysis is an innovative method to analyse non-linear relationships and in combination with sensitivity analysis superior to linear methods.

  16. Development of an ultrasonic weld inspection system based on image processing and neural networks

    Science.gov (United States)

    Roca Barceló, Fernando; Jaén del Hierro, Pedro; Ribes Llario, Fran; Real Herráiz, Julia

    2018-04-01

    Several types of discontinuities and defects may be present on a weld, thus leading to a considerable reduction of its resistance. Therefore, ensuring a high welding quality and reliability has become a matter of key importance for many construction and industrial activities. Among the non-destructive weld testing and inspection techniques, the time-of-flight diffraction (TOFD) arises as a very safe (no ionising radiation), precise, reliable and versatile practice. However, this technique presents a relevant drawback, associated to the appearance of speckle noise that should be addressed. In this regard, this paper presents a new, intelligent and automatic method for weld inspection and analysis, based on TOFD, image processing and neural networks. The developed system is capable of detecting weld defects and imperfections with accuracy, and classify them into different categories.

  17. Artificial neural network (ANN) approach for modeling Zn(II) adsorption in batch process

    Energy Technology Data Exchange (ETDEWEB)

    Yildiz, Sayiter [Engineering Faculty, Cumhuriyet University, Sivas (Turkmenistan)

    2017-09-15

    Artificial neural networks (ANN) were applied to predict adsorption efficiency of peanut shells for the removal of Zn(II) ions from aqueous solutions. Effects of initial pH, Zn(II) concentrations, temperature, contact duration and adsorbent dosage were determined in batch experiments. The sorption capacities of the sorbents were predicted with the aid of equilibrium and kinetic models. The Zn(II) ions adsorption onto peanut shell was better defined by the pseudo-second-order kinetic model, for both initial pH, and temperature. The highest R{sup 2} value in isotherm studies was obtained from Freundlich isotherm for the inlet concentration and from Temkin isotherm for the sorbent amount. The high R{sup 2} values prove that modeling the adsorption process with ANN is a satisfactory approach. The experimental results and the predicted results by the model with the ANN were found to be highly compatible with each other.

  18. Gender effects and sexual-orientation impact on androstadienone-evoked behavior and neural processing

    Directory of Open Access Journals (Sweden)

    Jacqueline eKrajnik

    2014-07-01

    Full Text Available In humans, the most established and investigated substance acting as a chemosignal, i.e., a substance that is excreted from the body, is 4,16-androstadien-3-one (AND. AND, which is found in sweat and saliva, is known to be responsible for influencing several variables, such as psychophysiological status, behavior, as well as cortical processing. The aim of the present review is to give insight into the variety of AND effects, with special regard to specific cross-sexual characteristics of this putative human chemosignal, emphasizing the neural activation patterns and factors such as contextual conditions. This review highlights the importance of including those contributing factors into the analysis of behavioral as well as brain-related studies.

  19. Modeling the Process of Color Image Recognition Using ART2 Neural Network

    Directory of Open Access Journals (Sweden)

    Todor Petkov

    2015-09-01

    Full Text Available This paper thoroughly describes the use of unsupervised adaptive resonance theory ART2 neural network for the purposes of image color recognition of x-ray images and images taken by nuclear magnetic resonance. In order to train the network, the pixel values of RGB colors are regarded as learning vectors with three values, one for red, one for green and one for blue were used. At the end the trained network was tested by the values of pictures and determines the design, or how to visualize the converted picture. As a result we had the same pictures with colors according to the network. Here we use the generalized net to prepare a model that describes the process of the color image recognition.

  20. Detection of outliers by neural network on the gas centrifuge experimental data of isotopic separation process

    International Nuclear Information System (INIS)

    Andrade, Monica de Carvalho Vasconcelos

    2004-01-01

    This work presents and discusses the neural network technique aiming at the detection of outliers on a set of gas centrifuge isotope separation experimental data. In order to evaluate the application of this new technique, the result obtained of the detection is compared to the result of the statistical analysis combined with the cluster analysis. This method for the detection of outliers presents a considerable potential in the field of data analysis and it is at the same time easier and faster to use and requests very less knowledge of the physics involved in the process. This work established a procedure for detecting experiments which are suspect to contain gross errors inside a data set where the usual techniques for identification of these errors cannot be applied or its use/demands an excessively long work. (author)

  1. Artificial neural network (ANN) approach for modeling Zn(II) adsorption in batch process

    International Nuclear Information System (INIS)

    Yildiz, Sayiter

    2017-01-01

    Artificial neural networks (ANN) were applied to predict adsorption efficiency of peanut shells for the removal of Zn(II) ions from aqueous solutions. Effects of initial pH, Zn(II) concentrations, temperature, contact duration and adsorbent dosage were determined in batch experiments. The sorption capacities of the sorbents were predicted with the aid of equilibrium and kinetic models. The Zn(II) ions adsorption onto peanut shell was better defined by the pseudo-second-order kinetic model, for both initial pH, and temperature. The highest R"2 value in isotherm studies was obtained from Freundlich isotherm for the inlet concentration and from Temkin isotherm for the sorbent amount. The high R"2 values prove that modeling the adsorption process with ANN is a satisfactory approach. The experimental results and the predicted results by the model with the ANN were found to be highly compatible with each other.

  2. Using an Artificial Neural Network Approach for Supplier Evaluation Process and a Sectoral Application

    Directory of Open Access Journals (Sweden)

    A. Yeşim Yayla

    2011-02-01

    Full Text Available In this study, a-three layered feed-forward backpropagation Artificial Neural Network (ANN model is developed for the supplier firms in ceramic sector on the bases of user effectiveness for using concurrent engineering method. The developed model is also questioned for its usability in the supplier evaluation process. The network's independent variables of the developed model are considered as input variables of the network and dependent variables are used as output variables. The values of these variables are determined with factor analysis. For obtaining the date set to be used in the analysis, a questionnaire form with 34 questions explaining the network's input and output variables are prepared and sent out to 52 firms active in related sector. For obtaining more accurate results from the network, the questions having factor load below 0,6 are eliminated from the analysis. With the elimination of the questions from the analysis, the answers given for 22 questions explaining 8 input variables are used for the evaluation the network's inputs, the answers given for 3 questions explaining output variables are used for the evaluation the network's outputs. The data set of the network's are divided into four equal groups with k-fold method in order to get four different alternative network structures. As a conclusion, the forecasted firm scores giving the minimum error from the network test simulation and real firm scores are found to be very close to each other, thus, it is concluded that the developed artificial neural network model can be used effectively in the supplier evaluation process.

  3. Synchronizing the tracking eye movements with the motion of a visual target: Basic neural processes.

    Science.gov (United States)

    Goffart, Laurent; Bourrelly, Clara; Quinet, Julie

    2017-01-01

    In primates, the appearance of an object moving in the peripheral visual field elicits an interceptive saccade that brings the target image onto the foveae. This foveation is then maintained more or less efficiently by slow pursuit eye movements and subsequent catch-up saccades. Sometimes, the tracking is such that the gaze direction looks spatiotemporally locked onto the moving object. Such a spatial synchronism is quite spectacular when one considers that the target-related signals are transmitted to the motor neurons through multiple parallel channels connecting separate neural populations with different conduction speeds and delays. Because of the delays between the changes of retinal activity and the changes of extraocular muscle tension, the maintenance of the target image onto the fovea cannot be driven by the current retinal signals as they correspond to past positions of the target. Yet, the spatiotemporal coincidence observed during pursuit suggests that the oculomotor system is driven by a command estimating continuously the current location of the target, i.e., where it is here and now. This inference is also supported by experimental perturbation studies: when the trajectory of an interceptive saccade is experimentally perturbed, a correction saccade is produced in flight or after a short delay, and brings the gaze next to the location where unperturbed saccades would have landed at about the same time, in the absence of visual feedback. In this chapter, we explain how such correction can be supported by previous visual signals without assuming "predictive" signals encoding future target locations. We also describe the basic neural processes which gradually yield the synchronization of eye movements with the target motion. When the process fails, the gaze is driven by signals related to past locations of the target, not by estimates to its upcoming locations, and a catch-up is made to reinitiate the synchronization. © 2017 Elsevier B.V. All rights

  4. Estimation of Apple Volume and Its Shape Indentation Using Image Processing Technique and Neural Network

    Directory of Open Access Journals (Sweden)

    M Jafarlou

    2014-04-01

    Full Text Available Physical properties of agricultural products such as volume are the most important parameters influencing grading and packaging systems. They should be measured accurately as they are considered for any good system design. Image processing and neural network techniques are both non-destructive and useful methods which are recently used for such purpose. In this study, the images of apples were captured from a constant distance and then were processed in MATLAB software and the edges of apple images were extracted. The interior area of apple image was divided into some thin trapezoidal elements perpendicular to longitudinal axis. Total volume of apple was estimated by the summation of incremental volumes of these elements revolved around the apple’s longitudinal axis. The picture of half cut apple was also captured in order to obtain the apple shape’s indentation volume, which was subtracted from the previously estimated total volume of apple. The real volume of apples was measured using water displacement method and the relation between the real volume and estimated volume was obtained. The t-test and Bland-Altman indicated that the difference between the real volume and the estimated volume was not significantly different (p>0.05 i.e. the mean difference was 1.52 cm3 and the accuracy of measurement was 92%. Utilizing neural network with input variables of dimension and mass has increased the accuracy up to 97% and the difference between the mean of volumes decreased to 0.7 cm3.

  5. Assessment of modularity architecture for recovery process of electric vehicle in supporting sustainable design

    Science.gov (United States)

    Baroroh, D. K.; Alfiah, D.

    2018-05-01

    The electric vehicle is one of the innovations to reduce the pollution of the vehicle. Nevertheless, it still has a problem, especially for disposal stage. In supporting product design and development strategy, which is the idea of sustainable design or problem solving of disposal stage, assessment of modularity architecture from electric vehicle in recovery process needs to be done. This research used Design Structure Matrix (DSM) approach to deciding interaction of components and assessment of modularity architecture using the calculation of value from 3 variables, namely Module Independence (MI), Module Similarity (MS), and Modularity for End of Life Stage (MEOL). The result of this research shows that existing design of electric vehicles has the architectural design which has a high value of modularity for recovery process on disposal stage. Accordingly, so it can be reused and recycled in component level or module without disassembly process to support the product that is environmentally friendly (sustainable design) and able reduce disassembly cost.

  6. Sustainable chemical processing and energy-carbon dioxide management: review of challenges and opportunities

    DEFF Research Database (Denmark)

    Frauzem, Rebecca; Vooradi, Ramsagar; Bertran, Maria-Ona

    2018-01-01

    This paper presents a brief review of the available energy sources for consumption, their effects in terms of CO2-emission and its management, and sustainable chemical processing where energy-consumption, CO2-emission, as well as economics and environmental impacts are considered. Not all available...... energy sources are being utilized efficiently, while, the energy source causing the largest emission of CO2 is being used in the largest amount. The CO2 management is therefore looking at "curing" the problem rather than "preventing" it. Examples highlighting the synthesis, design and analysis...... of sustainable chemical processing in the utilization of biomass-based energy-chemicals production, carbon-capture and utilization with zero or negative CO2-emission to produce value added chemicals as well as retrofit design of energy intensive chemical processes with significant reduction of energy consumption...

  7. Segregation of solid waste from a fish-processing industry: a sustainable action

    Directory of Open Access Journals (Sweden)

    Yeda dos Santos Silva

    2018-05-01

    Full Text Available Segregation techniques represent a sustainable alternative to minimize wastes of raw material in processing industries. This study considered the premise; its purpose was to use segregation techniques to determine the theoretical removal rate of solid compounds present in processing effluents, in order to support the sustainable development of the fish industry. The removal rates obtained for different treatments were evaluated for the parameters: total solids, organic matter and oils and greases, and the efficiency of the segregation of the effluent streams in the different stages of fish processing was evaluated through descriptive statistical analysis. The segregation recovered from 31% to 70% of total solids; from 15% to 97.50% of organic matter, and from 10% to 63% of oils and greases. These results indicates that the raw material can be used in new products, leading to reduced final-effluent concentration.

  8. Neural bases of different cognitive strategies for facial affect processing in schizophrenia.

    Science.gov (United States)

    Fakra, Eric; Salgado-Pineda, Pilar; Delaveau, Pauline; Hariri, Ahmad R; Blin, Olivier

    2008-03-01

    To examine the neural basis and dynamics of facial affect processing in schizophrenic patients as compared to healthy controls. Fourteen schizophrenic patients and fourteen matched controls performed a facial affect identification task during fMRI acquisition. The emotional task included an intuitive emotional condition (matching emotional faces) and a more cognitively demanding condition (labeling emotional faces). Individual analysis for each emotional condition, and second-level t-tests examining both within-, and between-group differences, were carried out using a random effects approach. Psychophysiological interactions (PPI) were tested for variations in functional connectivity between amygdala and other brain regions as a function of changes in experimental conditions (labeling versus matching). During the labeling condition, both groups engaged similar networks. During the matching condition, schizophrenics failed to activate regions of the limbic system implicated in the automatic processing of emotions. PPI revealed an inverse functional connectivity between prefrontal regions and the left amygdala in healthy volunteers but there was no such change in patients. Furthermore, during the matching condition, and compared to controls, patients showed decreased activation of regions involved in holistic face processing (fusiform gyrus) and increased activation of regions associated with feature analysis (inferior parietal cortex, left middle temporal lobe, right precuneus). Our findings suggest that schizophrenic patients invariably adopt a cognitive approach when identifying facial affect. The distributed neocortical network observed during the intuitive condition indicates that patients may resort to feature-based, rather than configuration-based, processing and may constitute a compensatory strategy for limbic dysfunction.

  9. Mapping Common Aphasia Assessments to Underlying Cognitive Processes and Their Neural Substrates.

    Science.gov (United States)

    Lacey, Elizabeth H; Skipper-Kallal, Laura M; Xing, Shihui; Fama, Mackenzie E; Turkeltaub, Peter E

    2017-05-01

    Understanding the relationships between clinical tests, the processes they measure, and the brain networks underlying them, is critical in order for clinicians to move beyond aphasia syndrome classification toward specification of individual language process impairments. To understand the cognitive, language, and neuroanatomical factors underlying scores of commonly used aphasia tests. Twenty-five behavioral tests were administered to a group of 38 chronic left hemisphere stroke survivors and a high-resolution magnetic resonance image was obtained. Test scores were entered into a principal components analysis to extract the latent variables (factors) measured by the tests. Multivariate lesion-symptom mapping was used to localize lesions associated with the factor scores. The principal components analysis yielded 4 dissociable factors, which we labeled Word Finding/Fluency, Comprehension, Phonology/Working Memory Capacity, and Executive Function. While many tests loaded onto the factors in predictable ways, some relied heavily on factors not commonly associated with the tests. Lesion symptom mapping demonstrated discrete brain structures associated with each factor, including frontal, temporal, and parietal areas extending beyond the classical language network. Specific functions mapped onto brain anatomy largely in correspondence with modern neural models of language processing. An extensive clinical aphasia assessment identifies 4 independent language functions, relying on discrete parts of the left middle cerebral artery territory. A better understanding of the processes underlying cognitive tests and the link between lesion and behavior may lead to improved aphasia diagnosis, and may yield treatments better targeted to an individual's specific pattern of deficits and preserved abilities.

  10. The neural basis of temporal order processing in past and future thought.

    Science.gov (United States)

    D'Argembeau, Arnaud; Jeunehomme, Olivier; Majerus, Steve; Bastin, Christine; Salmon, Eric

    2015-01-01

    Although growing evidence has shown that remembering the past and imagining the future recruit a common core network of frontal-parietal-temporal regions, the extent to which these regions contribute to the temporal dimension of autobiographical thought remains unclear. In this fMRI study, we focused on the event-sequencing aspect of time and examined whether ordering past and future events involve common neural substrates. Participants had to determine which of two past (or future) events occurred (or would occur) before the other, and these order judgments were compared with a task requiring to think about the content of the same past or future events. For both past and future events, we found that the left posterior hippocampus was more activated when establishing the order of events, whereas the anterior hippocampus was more activated when representing their content. Aside from the hippocampus, most of the brain regions that were activated when thinking about temporal order (notably the intraparietal sulcus, dorsolateral pFC, dorsal anterior cingulate, and visual cortex) lied outside the core network and may reflect the involvement of controlled processes and visuospatial imagery to locate events in time. Collectively, these findings suggest (a) that the same processing operations are engaged for ordering past events and planned future events in time, (b) that anterior and posterior portions of the hippocampus are involved in processing different aspects of autobiographical thought, and (c) that temporal order is not necessarily an intrinsic property of memory or future thought but instead requires additional, controlled processes.

  11. Neural mechanisms of context-dependent processing of CO2 avoidance behavior in fruit flies.

    Science.gov (United States)

    Siju, K P; Bräcker, Lasse B; Grunwald Kadow, I C

    2014-01-01

    The fruit fly, Drosophila melanogaster, innately avoids even low levels of CO2. CO2 is part of the so-called Drosophila stress odor produced by stressed flies, but also a byproduct of fermenting fruit, a main food source, making the strong avoidance behavior somewhat surprising. Therefore, we addressed whether feeding states might influence the fly's behavior and processing of CO2. In a recent report, we showed that this innate behavior is differentially processed and modified according to the feeding state of the fly. Interestingly, we found that hungry flies require the function of the mushroom body, a higher brain center required for olfactory learning and memory, but thought to be dispensable for innate olfactory behaviors. In addition, we anatomically and functionally characterized a novel bilateral projection neuron connecting the CO2 sensory input to the mushroom body. This neuron was essential for processing of CO2 in the starved fly but not in the fed fly. In this Extra View article, we provide evidence for the potential involvement of the neuromodulator dopamine in state-dependent CO2 avoidance behavior. Taken together, our work demonstrates that CO2 avoidance behavior is mediated by alternative neural pathways in a context-dependent manner. Furthermore, it shows that the mushroom body is not only involved in processing of learned olfactory behavior, as previously suggested, but also in context-dependent innate olfaction.

  12. The effect of early visual deprivation on the neural bases of multisensory processing.

    Science.gov (United States)

    Guerreiro, Maria J S; Putzar, Lisa; Röder, Brigitte

    2015-06-01

    Developmental vision is deemed to be necessary for the maturation of multisensory cortical circuits. Thus far, this has only been investigated in animal studies, which have shown that congenital visual deprivation markedly reduces the capability of neurons to integrate cross-modal inputs. The present study investigated the effect of transient congenital visual deprivation on the neural mechanisms of multisensory processing in humans. We used functional magnetic resonance imaging to compare responses of visual and auditory cortical areas to visual, auditory and audio-visual stimulation in cataract-reversal patients and normally sighted controls. The results showed that cataract-reversal patients, unlike normally sighted controls, did not exhibit multisensory integration in auditory areas. Furthermore, cataract-reversal patients, but not normally sighted controls, exhibited lower visual cortical processing within visual cortex during audio-visual stimulation than during visual stimulation. These results indicate that congenital visual deprivation affects the capability of cortical areas to integrate cross-modal inputs in humans, possibly because visual processing is suppressed during cross-modal stimulation. Arguably, the lack of vision in the first months after birth may result in a reorganization of visual cortex, including the suppression of noisy visual input from the deprived retina in order to reduce interference during auditory processing. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  13. Emotionally anesthetized: media violence induces neural changes during emotional face processing.

    Science.gov (United States)

    Stockdale, Laura A; Morrison, Robert G; Kmiecik, Matthew J; Garbarino, James; Silton, Rebecca L

    2015-10-01

    Media violence exposure causes increased aggression and decreased prosocial behavior, suggesting that media violence desensitizes people to the emotional experience of others. Alterations in emotional face processing following exposure to media violence may result in desensitization to others' emotional states. This study used scalp electroencephalography methods to examine the link between exposure to violence and neural changes associated with emotional face processing. Twenty-five participants were shown a violent or nonviolent film clip and then completed a gender discrimination stop-signal task using emotional faces. Media violence did not affect the early visual P100 component; however, decreased amplitude was observed in the N170 and P200 event-related potentials following the violent film, indicating that exposure to film violence leads to suppression of holistic face processing and implicit emotional processing. Participants who had just seen a violent film showed increased frontal N200/P300 amplitude. These results suggest that media violence exposure may desensitize people to emotional stimuli and thereby require fewer cognitive resources to inhibit behavior. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  14. Understanding Sustainable Diets: A Descriptive Analysis of the Determinants and Processes That Influence Diets and Their Impact on Health, Food Security, and Environmental Sustainability123

    Science.gov (United States)

    Johnston, Jessica L.; Fanzo, Jessica C.; Cogill, Bruce

    2014-01-01

    The confluence of population, economic development, and environmental pressures resulting from increased globalization and industrialization reveal an increasingly resource-constrained world in which predictions point to the need to do more with less and in a “better” way. The concept of sustainable diets presents an opportunity to successfully advance commitments to sustainable development and the elimination of poverty, food and nutrition insecurity, and poor health outcomes. This study examines the determinants of sustainable diets, offers a descriptive analysis of these areas, and presents a causal model and framework from which to build. The major determinants of sustainable diets fall into 5 categories: 1) agriculture, 2) health, 3) sociocultural, 4) environmental, and 5) socioeconomic. When factors or processes are changed in 1 determinant category, such changes affect other determinant categories and, in turn, the level of “sustainability” of a diet. The complex web of determinants of sustainable diets makes it challenging for policymakers to understand the benefits and considerations for promoting, processing, and consuming such diets. To advance this work, better measurements and indicators must be developed to assess the impact of the various determinants on the sustainability of a diet and the tradeoffs associated with any recommendations aimed at increasing the sustainability of our food system. PMID:25022991

  15. A systems engineering approach to manage the complexity in sustainable chemical product-process design

    DEFF Research Database (Denmark)

    Gani, Rafiqul

    This paper provides a perspective on model-data based solution approaches for chemical product-process design, which consists of finding the identity of the candidate chemical product, designing the process that can sustainably manufacture it and verifying the performance of the product during...... application. The chemical product tree is potentially very large and a wide range of options exist for selecting the product to make, the raw material to use as well as the processing route to employ. It is shown that systematic computer-aided methods and tools integrated within a model-data based design...

  16. Application of a systematic methodology for sustainable carbon dioxide utilization process design

    DEFF Research Database (Denmark)

    Plaza, Cristina Calvera; Frauzem, Rebecca; Gani, Rafiqul

    than carbon capture and storage. To achieve this a methodology is developed to design sustainable carbon dioxide utilization processes. First, the information on the possible utilization alternatives is collected, including the economic potential of the process and the carbon dioxide emissions...... emission are desired in order to reduce the carbon dioxide emissions. Using this estimated preliminary evaluation, the top processes, with the most negative carbon dioxide emission are investigated by rigorous detailed simulation to evaluate the net carbon dioxide emissions. Once the base case design...

  17. Recognition of malignant processes with neural nets from ESR spectra of serum albumin

    Energy Technology Data Exchange (ETDEWEB)

    Seidel, P. [Inst. of Medical Physics and Biophysics, Univ. Leipzig (Germany); Gurachevsky, A.; Muravsky, V.; Schnurr, K.; Seibt, G. [Medinnovation GmbH, Wildau (Germany); Matthes, G. [Inst. of Transfusion Medicine, Univ. Hospital Leipzig (Germany)

    2005-07-01

    Cancer diseases are the focus of intense research due to their frequent occurrence. It is known from the literature that serum proteins are changed in the case of malignant processes. Changes of albumin conformation, transport efficiency, and binding characteristics can be determined by electron spin resonance spectroscopy (ESR). The present study analysed the binding/dissociation function of albumin with an ESR method using 16-doxyl stearate spin probe as reporter molecule and ethanol as modifier of hydrophobic interactions. Native and frozen plasma of healthy donors (608 samples), patients with malignant diseases (423 samples), and patients with benign conditions (221 samples) were analysed. The global specificity was 91% and the sensitivity 96%. In look-back samples of 27 donors, a malignant process could be detected up to 30 months before clinical diagnosis. To recognise different entities of malignant diseases from the ESR spectra, Artificial neural networks were implemented. For 48 female donors with breast cancer, the recognition specificity was 85%. Other carcinoma entities (22 colon, 18 prostate, 12 stomach) were recognised with specificities between 75% and 84%. Should these specificity values be reproduced in larger studies, the described method could be used as a new specific tumour marker for the early detection of malignant processes. Since transmission of cancer via blood transfusion cannot be excluded as yet, the described ESR method could also be used as a quality test for plasma products. (orig.)

  18. When speaker identity is unavoidable: Neural processing of speaker identity cues in natural speech.

    Science.gov (United States)

    Tuninetti, Alba; Chládková, Kateřina; Peter, Varghese; Schiller, Niels O; Escudero, Paola

    2017-11-01

    Speech sound acoustic properties vary largely across speakers and accents. When perceiving speech, adult listeners normally disregard non-linguistic variation caused by speaker or accent differences, in order to comprehend the linguistic message, e.g. to correctly identify a speech sound or a word. Here we tested whether the process of normalizing speaker and accent differences, facilitating the recognition of linguistic information, is found at the level of neural processing, and whether it is modulated by the listeners' native language. In a multi-deviant oddball paradigm, native and nonnative speakers of Dutch were exposed to naturally-produced Dutch vowels varying in speaker, sex, accent, and phoneme identity. Unexpectedly, the analysis of mismatch negativity (MMN) amplitudes elicited by each type of change shows a large degree of early perceptual sensitivity to non-linguistic cues. This finding on perception of naturally-produced stimuli contrasts with previous studies examining the perception of synthetic stimuli wherein adult listeners automatically disregard acoustic cues to speaker identity. The present finding bears relevance to speech normalization theories, suggesting that at an unattended level of processing, listeners are indeed sensitive to changes in fundamental frequency in natural speech tokens. Copyright © 2017 Elsevier Inc. All rights reserved.

  19. Interactions between Depression and Facilitation within Neural Networks: Updating the Dual-Process Theory of Plasticity

    Science.gov (United States)

    Prescott, Steven A.

    1998-01-01

    Repetitive stimulation often results in habituation of the elicited response. However, if the stimulus is sufficiently strong, habituation may be preceded by transient sensitization or even replaced by enduring sensitization. In 1970, Groves and Thompson formulated the dual-process theory of plasticity to explain these characteristic behavioral changes on the basis of competition between decremental plasticity (depression) and incremental plasticity (facilitation) occurring within the neural network. Data from both vertebrate and invertebrate systems are reviewed and indicate that the effects of depression and facilitation are not exclusively additive but, rather, that those processes interact in a complex manner. Serial ordering of induction of learning, in which a depressing locus precedes the modulatory system responsible for inducing facilitation, causes the facilitation to wane. The parallel and/or serial expression of depression and waning facilitation within the stimulus–response pathway culminates in the behavioral changes that characterize dual-process learning. A mathematical model is presented to formally express and extend understanding of the interactions between depression and facilitation. PMID:10489261

  20. Statistical learning problem of artificial neural network to control roofing process

    Directory of Open Access Journals (Sweden)

    Lapidus Azariy

    2017-01-01

    Full Text Available Now software developed on the basis of artificial neural networks (ANN has been actively implemented in construction companies to support decision-making in organization and management of construction processes. ANN learning is the main stage of its development. A ke