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Sample records for neural constraints influencing

  1. Neural constraints and flexibility in language processing.

    Science.gov (United States)

    Huyck, Christian R

    2016-01-01

    Humans process language with their neurons. Memory in neurons is supported by neural firing and by short- and long-term synaptic weight change; the emergent behaviour of neurons, synchronous firing, and cell assembly dynamics is also a form of memory. As the language signal moves to later stages, it is processed with different mechanisms that are slower but more persistent.

  2. Resolving time and space constraints during neural crest formation and delamination.

    Science.gov (United States)

    Duband, Jean-Loup; Dady, Alwyn; Fleury, Vincent

    2015-01-01

    A striking feature of neural crest development in vertebrates is that all the specification, delamination, migration, and differentiation steps occur consecutively in distinct areas of the embryo and at different timings of development. The significance and consequences of this partition into clearly separated events are not fully understood yet, but it ought to be related to the necessity of controlling precisely and independently each step, given the wide array of cell types and tissues derived from the neural crest and the long duration of their development spanning almost the entire embryonic life. In this chapter, using the examples of early neural crest induction and delamination, we discuss how time and space constraints influence their development and describe the molecular and cellular responses that are employed by cells to adapt. In the first example, we analyze how cell sorting and cell movements cooperate to allow nascent neural crest cells, which are initially mingled with other neurectodermal progenitors after induction, to segregate from the neural tube and ectoderm populations and settle at the apex of the neural tube prior to migration. In the second example, we examine how cadherins drive the entire process of neural crest segregation from the rest of the neurectoderm by their dual role in mediating first cell sorting and cohesion during specification and later in promoting their delamination. In the third example, we describe how the expression and activity of the transcription factors known to drive epithelium-to-mesenchyme transition (EMT) are regulated timely and spatially by the cellular machinery so that they can alternatively and successively regulate neural crest specification and delamination. In the last example, we briefly tackle the problem of how factors triggering EMT may elicit different cell responses in neural tube and neural crest progenitors. © 2015 Elsevier Inc. All rights reserved.

  3. Commentary. Integrative Modeling and the Role of Neural Constraints

    Czech Academy of Sciences Publication Activity Database

    Bantegnie, Brice

    2017-01-01

    Roč. 8, SEP 5 (2017), s. 1-2, č. článku 1531. ISSN 1664-1078 Institutional support: RVO:67985955 Keywords : mechanistic explanation * functional analysis * mechanistic integration * reverse inference * neural plasticity * neural networks Subject RIV: AA - Philosophy ; Religion Impact factor: 2.323, year: 2016

  4. Trade-off between Multiple Constraints Enables Simultaneous Formation of Modules and Hubs in Neural Systems

    Science.gov (United States)

    Chen, Yuhan; Wang, Shengjun; Hilgetag, Claus C.; Zhou, Changsong

    2013-01-01

    The formation of the complex network architecture of neural systems is subject to multiple structural and functional constraints. Two obvious but apparently contradictory constraints are low wiring cost and high processing efficiency, characterized by short overall wiring length and a small average number of processing steps, respectively. Growing evidence shows that neural networks are results from a trade-off between physical cost and functional value of the topology. However, the relationship between these competing constraints and complex topology is not well understood quantitatively. We explored this relationship systematically by reconstructing two known neural networks, Macaque cortical connectivity and C. elegans neuronal connections, from combinatory optimization of wiring cost and processing efficiency constraints, using a control parameter , and comparing the reconstructed networks to the real networks. We found that in both neural systems, the reconstructed networks derived from the two constraints can reveal some important relations between the spatial layout of nodes and the topological connectivity, and match several properties of the real networks. The reconstructed and real networks had a similar modular organization in a broad range of , resulting from spatial clustering of network nodes. Hubs emerged due to the competition of the two constraints, and their positions were close to, and partly coincided, with the real hubs in a range of values. The degree of nodes was correlated with the density of nodes in their spatial neighborhood in both reconstructed and real networks. Generally, the rebuilt network matched a significant portion of real links, especially short-distant ones. These findings provide clear evidence to support the hypothesis of trade-off between multiple constraints on brain networks. The two constraints of wiring cost and processing efficiency, however, cannot explain all salient features in the real networks. The discrepancy

  5. Trade-off between multiple constraints enables simultaneous formation of modules and hubs in neural systems.

    Directory of Open Access Journals (Sweden)

    Yuhan Chen

    Full Text Available The formation of the complex network architecture of neural systems is subject to multiple structural and functional constraints. Two obvious but apparently contradictory constraints are low wiring cost and high processing efficiency, characterized by short overall wiring length and a small average number of processing steps, respectively. Growing evidence shows that neural networks are results from a trade-off between physical cost and functional value of the topology. However, the relationship between these competing constraints and complex topology is not well understood quantitatively. We explored this relationship systematically by reconstructing two known neural networks, Macaque cortical connectivity and C. elegans neuronal connections, from combinatory optimization of wiring cost and processing efficiency constraints, using a control parameter α, and comparing the reconstructed networks to the real networks. We found that in both neural systems, the reconstructed networks derived from the two constraints can reveal some important relations between the spatial layout of nodes and the topological connectivity, and match several properties of the real networks. The reconstructed and real networks had a similar modular organization in a broad range of α, resulting from spatial clustering of network nodes. Hubs emerged due to the competition of the two constraints, and their positions were close to, and partly coincided, with the real hubs in a range of α values. The degree of nodes was correlated with the density of nodes in their spatial neighborhood in both reconstructed and real networks. Generally, the rebuilt network matched a significant portion of real links, especially short-distant ones. These findings provide clear evidence to support the hypothesis of trade-off between multiple constraints on brain networks. The two constraints of wiring cost and processing efficiency, however, cannot explain all salient features in the real

  6. Constraints of Biological Neural Networks and Their Consideration in AI Applications

    Directory of Open Access Journals (Sweden)

    Richard Stafford

    2010-01-01

    Full Text Available Biological organisms do not evolve to perfection, but to out compete others in their ecological niche, and therefore survive and reproduce. This paper reviews the constraints imposed on imperfect organisms, particularly on their neural systems and ability to capture and process information accurately. By understanding biological constraints of the physical properties of neurons, simpler and more efficient artificial neural networks can be made (e.g., spiking networks will transmit less information than graded potential networks, spikes only occur in nature due to limitations of carrying electrical charges over large distances. Furthermore, understanding the behavioural and ecological constraints on animals allows an understanding of the limitations of bio-inspired solutions, but also an understanding of why bio-inspired solutions may fail and how to correct these failures.

  7. Neural mechanisms of social influence in adolescence.

    Science.gov (United States)

    Welborn, B Locke; Lieberman, Matthew D; Goldenberg, Diane; Fuligni, Andrew J; Galván, Adriana; Telzer, Eva H

    2016-01-01

    During the transformative period of adolescence, social influence plays a prominent role in shaping young people's emerging social identities, and can impact their propensity to engage in prosocial or risky behaviors. In this study, we examine the neural correlates of social influence from both parents and peers, two important sources of influence. Nineteen adolescents (age 16-18 years) completed a social influence task during a functional magnetic resonance imaging (fMRI) scan. Social influence from both sources evoked activity in brain regions implicated in mentalizing (medial prefrontal cortex, left temporoparietal junction, right temporoparietal junction), reward (ventromedial prefrontal cortex), and self-control (right ventrolateral prefrontal cortex). These results suggest that mental state reasoning, social reward and self-control processes may help adolescents to evaluate others' perspectives and overcome the prepotent force of their own antecedent attitudes to shift their attitudes toward those of others. Findings suggest common neural networks involved in social influence from both parents and peers. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  8. A one-layer projection neural network for nonsmooth optimization subject to linear equalities and bound constraints.

    Science.gov (United States)

    Liu, Qingshan; Wang, Jun

    2013-05-01

    This paper presents a one-layer projection neural network for solving nonsmooth optimization problems with generalized convex objective functions and subject to linear equalities and bound constraints. The proposed neural network is designed based on two projection operators: linear equality constraints, and bound constraints. The objective function in the optimization problem can be any nonsmooth function which is not restricted to be convex but is required to be convex (pseudoconvex) on a set defined by the constraints. Compared with existing recurrent neural networks for nonsmooth optimization, the proposed model does not have any design parameter, which is more convenient for design and implementation. It is proved that the output variables of the proposed neural network are globally convergent to the optimal solutions provided that the objective function is at least pseudoconvex. Simulation results of numerical examples are discussed to demonstrate the effectiveness and characteristics of the proposed neural network.

  9. Search strategies in practice: Influence of information and task constraints.

    Science.gov (United States)

    Pacheco, Matheus M; Newell, Karl M

    2017-11-07

    The practice of a motor task has been conceptualized as a process of search through a perceptual-motor workspace. The present study investigated the influence of information and task constraints on the search strategy as reflected in the sequential relations of the outcome in a discrete movement virtual projectile task. The results showed that the relation between the changes of trial-to-trial movement outcome to performance level was dependent on the landscape of the task dynamics and the influence of inherent variability. Furthermore, the search was in a constrained parameter region of the perceptual-motor workspace that depended on the task constraints. These findings show that there is not a single function of trial-to-trial change over practice but rather that local search strategies (proportional, discontinuous, constant) adapt to the level of performance and the confluence of constraints to action. Copyright © 2017 Elsevier B.V. All rights reserved.

  10. A One-Layer Recurrent Neural Network for Pseudoconvex Optimization Problems With Equality and Inequality Constraints.

    Science.gov (United States)

    Qin, Sitian; Yang, Xiudong; Xue, Xiaoping; Song, Jiahui

    2017-10-01

    Pseudoconvex optimization problem, as an important nonconvex optimization problem, plays an important role in scientific and engineering applications. In this paper, a recurrent one-layer neural network is proposed for solving the pseudoconvex optimization problem with equality and inequality constraints. It is proved that from any initial state, the state of the proposed neural network reaches the feasible region in finite time and stays there thereafter. It is also proved that the state of the proposed neural network is convergent to an optimal solution of the related problem. Compared with the related existing recurrent neural networks for the pseudoconvex optimization problems, the proposed neural network in this paper does not need the penalty parameters and has a better convergence. Meanwhile, the proposed neural network is used to solve three nonsmooth optimization problems, and we make some detailed comparisons with the known related conclusions. In the end, some numerical examples are provided to illustrate the effectiveness of the performance of the proposed neural network.

  11. Hybrid neural modelling of an anaerobic digester with respect to biological constraints.

    Science.gov (United States)

    Karama, A; Bernard, O; Gouzé, J L; Benhammou, A; Dochain, D

    2001-01-01

    A hybrid model for an anaerobic digestion process is proposed. The fermentation is assumed to be performed in two steps, acidogenesis and methanogenesis, by two bacterial populations. The model is based on mass balance equations, and the bacterial growth rates are represented by neural networks. In order to guarantee the biological meaning of the hybrid model (positivity of the concentrations, boundedness, saturation or inhibition of the growth rates) outside the training data set, a method that imposes constraints in the neural network is proposed. The method is applied to experimental data from a fixed bed reactor.

  12. Constraints influencing sports wheelchair propulsion performance and injury risk

    Science.gov (United States)

    2013-01-01

    The Paralympic Games are the pinnacle of sport for many athletes with a disability. A potential issue for many wheelchair athletes is how to train hard to maximise performance while also reducing the risk of injuries, particularly to the shoulder due to the accumulation of stress placed on this joint during activities of daily living, training and competition. The overall purpose of this narrative review was to use the constraints-led approach of dynamical systems theory to examine how various constraints acting upon the wheelchair-user interface may alter hand rim wheelchair performance during sporting activities, and to a lesser extent, their injury risk. As we found no studies involving Paralympic athletes that have directly utilised the dynamical systems approach to interpret their data, we have used this approach to select some potential constraints and discussed how they may alter wheelchair performance and/or injury risk. Organism constraints examined included player classifications, wheelchair setup, training and intrinsic injury risk factors. Task constraints examined the influence of velocity and types of locomotion (court sports vs racing) in wheelchair propulsion, while environmental constraints focused on forces that tend to oppose motion such as friction and surface inclination. Finally, the ecological validity of the research studies assessing wheelchair propulsion was critiqued prior to recommendations for practice and future research being given. PMID:23557065

  13. 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.

  14. Neural Based Tabu Search method for solving unit commitment problem with cooling-banking constraints

    Directory of Open Access Journals (Sweden)

    Rajan Asir Christober Gnanakkan Charles

    2009-01-01

    Full Text Available This paper presents a new approach to solve short-term unit commitment problem (UCP using Neural Based Tabu Search (NBTS with cooling and banking constraints. The objective of this paper is to find the generation scheduling such that the total operating cost can be minimized, when subjected to a variety of constraints. This also means that it is desirable to find the optimal generating unit commitment in the power system for next H hours. A 7-unit utility power system in India demonstrates the effectiveness of the proposed approach; extensive studies have also been performed for different IEEE test systems consist of 10, 26 and 34 units. Numerical results are shown to compare the superiority of the cost solutions obtained using the Tabu Search (TS method, Dynamic Programming (DP and Lagrangian Relaxation (LR methods in reaching proper unit commitment.

  15. Asymmetric continuous-time neural networks without local traps for solving constraint satisfaction problems.

    Directory of Open Access Journals (Sweden)

    Botond Molnár

    Full Text Available There has been a long history of using neural networks for combinatorial optimization and constraint satisfaction problems. Symmetric Hopfield networks and similar approaches use steepest descent dynamics, and they always converge to the closest local minimum of the energy landscape. For finding global minima additional parameter-sensitive techniques are used, such as classical simulated annealing or the so-called chaotic simulated annealing, which induces chaotic dynamics by addition of extra terms to the energy landscape. Here we show that asymmetric continuous-time neural networks can solve constraint satisfaction problems without getting trapped in non-solution attractors. We concentrate on a model solving Boolean satisfiability (k-SAT, which is a quintessential NP-complete problem. There is a one-to-one correspondence between the stable fixed points of the neural network and the k-SAT solutions and we present numerical evidence that limit cycles may also be avoided by appropriately choosing the parameters of the model. This optimal parameter region is fairly independent of the size and hardness of instances, this way parameters can be chosen independently of the properties of problems and no tuning is required during the dynamical process. The model is similar to cellular neural networks already used in CNN computers. On an analog device solving a SAT problem would take a single operation: the connection weights are determined by the k-SAT instance and starting from any initial condition the system searches until finding a solution. In this new approach transient chaotic behavior appears as a natural consequence of optimization hardness and not as an externally induced effect.

  16. Using Stochastic Spiking Neural Networks on SpiNNaker to Solve Constraint Satisfaction Problems

    Science.gov (United States)

    Fonseca Guerra, Gabriel A.; Furber, Steve B.

    2017-01-01

    Constraint satisfaction problems (CSP) are at the core of numerous scientific and technological applications. However, CSPs belong to the NP-complete complexity class, for which the existence (or not) of efficient algorithms remains a major unsolved question in computational complexity theory. In the face of this fundamental difficulty heuristics and approximation methods are used to approach instances of NP (e.g., decision and hard optimization problems). The human brain efficiently handles CSPs both in perception and behavior using spiking neural networks (SNNs), and recent studies have demonstrated that the noise embedded within an SNN can be used as a computational resource to solve CSPs. Here, we provide a software framework for the implementation of such noisy neural solvers on the SpiNNaker massively parallel neuromorphic hardware, further demonstrating their potential to implement a stochastic search that solves instances of P and NP problems expressed as CSPs. This facilitates the exploration of new optimization strategies and the understanding of the computational abilities of SNNs. We demonstrate the basic principles of the framework by solving difficult instances of the Sudoku puzzle and of the map color problem, and explore its application to spin glasses. The solver works as a stochastic dynamical system, which is attracted by the configuration that solves the CSP. The noise allows an optimal exploration of the space of configurations, looking for the satisfiability of all the constraints; if applied discontinuously, it can also force the system to leap to a new random configuration effectively causing a restart.

  17. Using Stochastic Spiking Neural Networks on SpiNNaker to Solve Constraint Satisfaction Problems

    Directory of Open Access Journals (Sweden)

    Gabriel A. Fonseca Guerra

    2017-12-01

    Full Text Available Constraint satisfaction problems (CSP are at the core of numerous scientific and technological applications. However, CSPs belong to the NP-complete complexity class, for which the existence (or not of efficient algorithms remains a major unsolved question in computational complexity theory. In the face of this fundamental difficulty heuristics and approximation methods are used to approach instances of NP (e.g., decision and hard optimization problems. The human brain efficiently handles CSPs both in perception and behavior using spiking neural networks (SNNs, and recent studies have demonstrated that the noise embedded within an SNN can be used as a computational resource to solve CSPs. Here, we provide a software framework for the implementation of such noisy neural solvers on the SpiNNaker massively parallel neuromorphic hardware, further demonstrating their potential to implement a stochastic search that solves instances of P and NP problems expressed as CSPs. This facilitates the exploration of new optimization strategies and the understanding of the computational abilities of SNNs. We demonstrate the basic principles of the framework by solving difficult instances of the Sudoku puzzle and of the map color problem, and explore its application to spin glasses. The solver works as a stochastic dynamical system, which is attracted by the configuration that solves the CSP. The noise allows an optimal exploration of the space of configurations, looking for the satisfiability of all the constraints; if applied discontinuously, it can also force the system to leap to a new random configuration effectively causing a restart.

  18. Neural mechanisms of resistance to peer influence in early adolescence.

    Science.gov (United States)

    Grosbras, Marie-Helène; Jansen, Marije; Leonard, Gabriel; McIntosh, Anthony; Osswald, Katja; Poulsen, Catherine; Steinberg, Laurence; Toro, Roberto; Paus, Tomas

    2007-07-25

    During the shift from a parent-dependent child to a fully autonomous adult, peers take on a significant role in shaping the adolescent's behavior. Peer-derived influences are not always positive, however. Here, we explore neural correlates of interindividual differences in the probability of resisting peer influence in early adolescence. Using functional magnetic resonance imaging, we found striking differences between 10-year-old children with high and low resistance to peer influence in their brain activity during observation of angry hand movements and angry facial expressions: compared with subjects with low resistance to peer influence, individuals with high resistance showed a highly coordinated brain activity in neural systems underlying perception of action and decision making. These findings suggest that the probability of resisting peer influence depends on neural interactions during observation of emotion-laden actions.

  19. Neural responses to exclusion predict susceptibility to social influence.

    Science.gov (United States)

    Falk, Emily B; Cascio, Christopher N; O'Donnell, Matthew Brook; Carp, Joshua; Tinney, Francis J; Bingham, C Raymond; Shope, Jean T; Ouimet, Marie Claude; Pradhan, Anuj K; Simons-Morton, Bruce G

    2014-05-01

    Social influence is prominent across the lifespan, but sensitivity to influence is especially high during adolescence and is often associated with increased risk taking. Such risk taking can have dire consequences. For example, in American adolescents, traffic-related crashes are leading causes of nonfatal injury and death. Neural measures may be especially useful in understanding the basic mechanisms of adolescents' vulnerability to peer influence. We examined neural responses to social exclusion as potential predictors of risk taking in the presence of peers in recently licensed adolescent drivers. Risk taking was assessed in a driving simulator session occurring approximately 1 week after the neuroimaging session. Increased activity in neural systems associated with the distress of social exclusion and mentalizing during an exclusion episode predicted increased risk taking in the presence of a peer (controlling for solo risk behavior) during a driving simulator session outside the neuroimaging laboratory 1 week later. These neural measures predicted risky driving behavior above and beyond self-reports of susceptibility to peer pressure and distress during exclusion. These results address the neural bases of social influence and risk taking; contribute to our understanding of social and emotional function in the adolescent brain; and link neural activity in specific, hypothesized, regions to risk-relevant outcomes beyond the neuroimaging laboratory. Results of this investigation are discussed in terms of the mechanisms underlying risk taking in adolescents and the public health implications for adolescent driving. Copyright © 2014 Society for Adolescent Health and Medicine. All rights reserved.

  20. Neural constraints on eye motion in human eye-head saccades.

    Science.gov (United States)

    Misslisch, H; Tweed, D; Vilis, T

    1998-02-01

    We examined two ways in which the neural control system for eye-head saccades constrains the motion of the eye in the head. The first constraint involves Listing's law, which holds ocular torsion at zero during head-fixed saccades. During eye-head saccades, does this law govern the eye's motion in space or in the head? Our subjects, instructed to saccade between space-fixed targets with the head held still in different positions, systematically violated Listing's law of the eye in space in a way that approximately, but not perfectly, preserved Listing's law of the eye in head. This finding implies that the brain does not compute desired eye position based on the desired gaze direction alone but also considers head position. The second constraint we studied was saturation, the process where desired-eye-position commands in the brain are "clipped" to keep them within an effective oculomotor range (EOMR), which is smaller than the mechanical range of eye motion. We studied the adaptability of the EOMR by asking subjects to make head-only saccades. As predicted by current eye-head models, subjects failed to hold their eyes still in their orbits. Unexpectedly, though, the range of eye-in-head motion in the horizontal-vertical plane was on average 31% smaller in area than during normal eye-head saccades, suggesting that the EOMR had been reduced by effort of will. Larger reductions were possible with altered visual input: when subjects donned pinhole glasses, the EOMR immediately shrank by 80%. But even with its reduced EOMR, the eye still moved into the "blind" region beyond the pinhole aperture during eye-head saccades. Then, as the head movement brought the saccade target toward the pinhole, the eyes reversed their motion, anticipating or roughly matching the target's motion even though it was still outside the pinhole and therefore invisible. This finding shows that the backward rotation of the eye is timed by internal computations, not by vision. When subjects wore

  1. Neural mechanisms of social influence in adolescence

    National Research Council Canada - National Science Library

    Welborn, B Locke; Lieberman, Matthew D; Goldenberg, Diane; Fuligni, Andrew J; Galván, Adriana; Telzer, Eva H

    2016-01-01

    During the transformative period of adolescence, social influence plays a prominent role in shaping young people's emerging social identities, and can impact their propensity to engage in prosocial or risky behaviors...

  2. The Neural Basis of Social Influence in a Dictator Decision

    Directory of Open Access Journals (Sweden)

    Zhenyu Wei

    2017-12-01

    Full Text Available Humans tend to reduce inequitable distributions. Previous neuroimaging studies have shown that inequitable decisions are related to brain regions that associated with negative emotion and signaling conflict. In the highly complex human social environment, our opinions and behaviors can be affected by social information. In current study, we used a modified dictator game to investigate the effect of social influence on making an equitable decision. We found that the choices of participants in present task was influenced by the choices of peers. However, participants’ decisions were influenced by equitable rather than inequitable group choices. fMRI results showed that brain regions that related to norm violation and social conflict were related to the inequitable social influence. The neural responses in the dorsomedial prefrontal cortex, rostral cingulate zone, and insula predicted subsequent conforming behavior in individuals. Additionally, psychophysiological interaction analysis revealed that the interconnectivity between the dorsal striatum and insula was elevated in advantageous inequity influence versus no-social influence conditions. We found decreased functional connectivity between the medial prefrontal cortex and insula, supplementary motor area, posterior cingulate gyrus and dorsal anterior cingulate cortex in the disadvantageous inequity influence versus no-social influence conditions. This suggests that a disadvantageous inequity influence may decrease the functional connectivity among brain regions that are related to reward processes. Thus, the neural mechanisms underlying social influence in an equitable decision may be similar to those implicated in social norms and reward processing.

  3. The Neural Basis of Social Influence in a Dictator Decision.

    Science.gov (United States)

    Wei, Zhenyu; Zhao, Zhiying; Zheng, Yong

    2017-01-01

    Humans tend to reduce inequitable distributions. Previous neuroimaging studies have shown that inequitable decisions are related to brain regions that associated with negative emotion and signaling conflict. In the highly complex human social environment, our opinions and behaviors can be affected by social information. In current study, we used a modified dictator game to investigate the effect of social influence on making an equitable decision. We found that the choices of participants in present task was influenced by the choices of peers. However, participants' decisions were influenced by equitable rather than inequitable group choices. fMRI results showed that brain regions that related to norm violation and social conflict were related to the inequitable social influence. The neural responses in the dorsomedial prefrontal cortex, rostral cingulate zone, and insula predicted subsequent conforming behavior in individuals. Additionally, psychophysiological interaction analysis revealed that the interconnectivity between the dorsal striatum and insula was elevated in advantageous inequity influence versus no-social influence conditions. We found decreased functional connectivity between the medial prefrontal cortex and insula, supplementary motor area, posterior cingulate gyrus and dorsal anterior cingulate cortex in the disadvantageous inequity influence versus no-social influence conditions. This suggests that a disadvantageous inequity influence may decrease the functional connectivity among brain regions that are related to reward processes. Thus, the neural mechanisms underlying social influence in an equitable decision may be similar to those implicated in social norms and reward processing.

  4. Complexities and constraints influencing learner performance in physical science

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    Mavhungu Abel Mafukata

    2016-01-01

    Full Text Available This paper explores complexities and constraints affecting performance and output of physical science learners in Vhembe District, Limpopo Province, South Africa. The study was motivated by the desire of the researcher to establish, profile and characterise the complexities and constraints reminiscence of poor performance of learners in physical science as measured through end-of-year Grade 12 (final year of high school education examination results. Twenty six schools (n=26 were purposively selected from three circuits of education (n=3. From these schools, two learners were randomly selected (n=52 for interviews. In addition, two circuit managers (n=2 were conveniently selected as part of Key Informant Interviews (KII. For the Focus Group Discussions (FGDs, twelve (n=12 parents were randomly selected to form two groups of six members each. Multi-factor complexities and constraints impeding performance of learners were discovered. Intensive teacher in-service programme is recommended. Community engagement should be encouraged to educate parents on the value of involvement in the education of their children. Free access learner support structures such as Homework and Extra-lessons Assistance Centre (H&EACs should be established.

  5. Neural mechanisms of contextual influences during social perceptual decisions

    OpenAIRE

    El Zein, Marwa

    2015-01-01

    Everyday social decisions require the combination of multiple sources of information and therefore build upon abundant contextual elements such as the social cues of emitters (e.g., gaze direction, emotion, gesture), the attentional focus of observers, their mood and their past experience. The work conducted during this Ph.D. (including three main studies in healthy human subjects) aimed at characterizing the cognitive and neural mechanisms of contextual influences in social settings. The fir...

  6. Neural-Dynamic-Method-Based Dual-Arm CMG Scheme With Time-Varying Constraints Applied to Humanoid Robots.

    Science.gov (United States)

    Zhang, Zhijun; Li, Zhijun; Zhang, Yunong; Luo, Yamei; Li, Yuanqing

    2015-12-01

    We propose a dual-arm cyclic-motion-generation (DACMG) scheme by a neural-dynamic method, which can remedy the joint-angle-drift phenomenon of a humanoid robot. In particular, according to a neural-dynamic design method, first, a cyclic-motion performance index is exploited and applied. This cyclic-motion performance index is then integrated into a quadratic programming (QP)-type scheme with time-varying constraints, called the time-varying-constrained DACMG (TVC-DACMG) scheme. The scheme includes the kinematic motion equations of two arms and the time-varying joint limits. The scheme can not only generate the cyclic motion of two arms for a humanoid robot but also control the arms to move to the desired position. In addition, the scheme considers the physical limit avoidance. To solve the QP problem, a recurrent neural network is presented and used to obtain the optimal solutions. Computer simulations and physical experiments demonstrate the effectiveness and the accuracy of such a TVC-DACMG scheme and the neural network solver.

  7. Neural Correlates of Social Influence Among Cannabis Users.

    Science.gov (United States)

    Gilman, Jodi M

    2017-06-01

    Although peer influence is an important factor in the initiation and maintenance of cannabis use, few studies have investigated the neural correlates of peer influence among cannabis users. The current review summarizes research on the neuroscience of social influence in cannabis users, with the goal of highlighting gaps in the literature and the need for future research. Brain regions underlying peer influence may function differently in cannabis users. Compared to non-using controls, regions of the brain underlying reward, such as the striatum, show greater connectivity with frontal regions, and also show hyperactivity when participants are presented with peer information. Other subcortical regions, such as the insula, show hypoactivation during social exclusion in cannabis users, indicating that neural responses to peer interactions may be altered in cannabis users. Although neuroscience is increasingly being used to study social behavior, few studies have specifically focused on cannabis use, and therefore it is difficult to draw conclusions about social mechanisms that may differentiate cannabis users and controls. This area of research may be a promising avenue in which to explore a critical factor underlying cannabis use and addiction.

  8. Social influence modulates the neural computation of value.

    Science.gov (United States)

    Zaki, Jamil; Schirmer, Jessica; Mitchell, Jason P

    2011-07-01

    Social influence--individuals' tendency to conform to the beliefs and attitudes of others--has interested psychologists for decades. However, it has traditionally been difficult to distinguish true modification of attitudes from mere public compliance with social norms; this study addressed this challenge using functional neuroimaging. Participants rated the attractiveness of faces and subsequently learned how their peers ostensibly rated each face. Participants were then scanned using functional MRI while they rated each face a second time. The second ratings were influenced by social norms: Participants changed their ratings to conform to those of their peers. This social influence was accompanied by modulated engagement of two brain regions associated with coding subjective value--the nucleus accumbens and orbitofrontal cortex--a finding suggesting that exposure to social norms affected participants' neural representations of value assigned to stimuli. These findings document the utility of neuroimaging to demonstrate the private acceptance of social norms.

  9. The neural basis of social influence and attitude change.

    Science.gov (United States)

    Izuma, Keise

    2013-06-01

    Human attitudes and preferences are susceptible to social influence. Recent social neuroscience studies, using theories and experimental paradigms from social psychology, have begun to elucidate the neural mechanisms underlying how others influence our attitudes through processes such as social conformity, cognitive inconsistency and persuasion. The currently available evidence highlights the role of the posterior medial frontal cortex (pMFC) in social conformity and cognitive inconsistency, which represents the discrepancy between one's own and another person's opinion, or, more broadly, between currently inconsistent and ideally consistent states. Research on persuasion has revealed that people's susceptibility to persuasive messages is related to activation in a nearby but more anterior part of the medial frontal cortex. Future progress in this field will depend upon the ability of researchers to dissociate underlying motivations for attitude change in different paradigms, and to utilize neuroimaging methods to advance social psychological theories of social influence. Copyright © 2013 Elsevier Ltd. All rights reserved.

  10. 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.

  11. Protein distance constraints predicted by neural networks and probability density functions

    DEFF Research Database (Denmark)

    Lund, Ole; Frimand, Kenneth; Gorodkin, Jan

    1997-01-01

    We predict interatomic C-α distances by two independent data driven methods. The first method uses statistically derived probability distributions of the pairwise distance between two amino acids, whilst the latter method consists of a neural network prediction approach equipped with windows taking....... The predictions are based on a data set derived using a new threshold similarity. We show that distances in proteins are predicted more accurately by neural networks than by probability density functions. We show that the accuracy of the predictions can be further increased by using sequence profiles. A threading...

  12. Solving the Weighted Constraint Satisfaction Problems Via the Neural Network Approach

    Directory of Open Access Journals (Sweden)

    Khalid Haddouch

    2016-09-01

    Full Text Available A wide variety of real world optimization problems can be modelled as Weighted Constraint Satisfaction Problems (WCSPs. In this paper, we model this problem in terms of in original 0-1 quadratic programming subject to leaner constraints. View it performance, we use the continuous Hopfield network to solve the obtained model basing on original energy function. To validate our model, we solve several instance of benchmarking WCSP. In this regard, our approach recognizes the optimal solution of the said instances.

  13. Influence of subcontracting constraints on the performance of manufacturing industries in Nigeria

    Directory of Open Access Journals (Sweden)

    Victor Chukwunweike Nwokocha

    2015-01-01

    Full Text Available In this work, an attempt has been made to show the influence of subcontracting constraints on firm performance in Nigeria. The study in line with the literature identified a number of constraints hindering an effective subcontracting arrangement in the study area. While the constraints were found not to have affected the use of subcontracting in the country, low capital intensity, disclosure of commercial secrets, poor services and interest conflict were found to have restricted subcontracting arrangements in the study area to sharing of equipment and short-term contracts. These constraints however were found not have affected the performance of manufacturing industries in the study area. This paper keeping in mind the findings of this study suggested that manufacturing industries in Nigeria should invest more in machineries and tools so as to increase subcontracting co-operations among industries.

  14. Texture synthesis using convolutional neural networks with long-range consistency and spectral constraints

    NARCIS (Netherlands)

    Schreiber, Shaun; Geldenhuys, Jaco; Villiers, De Hendrik

    2017-01-01

    Procedural texture generation enables the creation of more rich and detailed virtual environments without the help of an artist. However, finding a flexible generative model of real world textures remains an open problem. We present a novel Convolutional Neural Network based texture model

  15. Sliding Mode Control for NSVs with Input Constraint Using Neural Network and Disturbance Observer

    Directory of Open Access Journals (Sweden)

    Yan-long Zhou

    2013-01-01

    Full Text Available The sliding mode control (SMC scheme is proposed for near space vehicles (NSVs with strong nonlinearity, high coupling, parameter uncertainty, and unknown time-varying disturbance based on radial basis function neural networks (RBFNNs and the nonlinear disturbance observer (NDO. Considering saturation characteristic of rudders, RBFNNs are constructed as a compensator to overcome the saturation nonlinearity. The stability of the closed-loop system is proved, and the tracking error as well as the disturbance observer error can converge to the origin through the Lyapunov analysis. Simulation results are presented to demonstrate the effectiveness of the proposed flight control scheme.

  16. Fairness influences early signatures of reward-related neural processing.

    Science.gov (United States)

    Massi, Bart; Luhmann, Christian C

    2015-12-01

    Many humans exhibit a strong preference for fairness during decision-making. Although there is evidence that social factors influence reward-related and affective neural processing, it is unclear if this effect is mediated by compulsory outcome evaluation processes or results from slower deliberate cognition. Here we show that the feedback-related negativity (FRN) and late positive potential (LPP), two signatures of early hedonic processing, are modulated by the fairness of rewards during a passive rating task. We find that unfair payouts elicit larger FRNs than fair payouts, whereas fair payouts elicit larger LPPs than unfair payouts. This is true both in the time-domain, where the FRN and LPP are related, and in the time-frequency domain, where the two signals are largely independent. Ultimately, this work demonstrates that fairness affects the early stages of reward and affective processing, suggesting a common biological mechanism for social and personal reward evaluation.

  17. Long-term Practice with Domain-Specific Task Constraints Influences Perceptual Skills

    Directory of Open Access Journals (Sweden)

    Luca Oppici

    2017-08-01

    Full Text Available The long-term impact of practice with different task constraints on perceptual skill is relatively un-explored. This study examined the influence of extensive practice, i.e., more than a 1000 h of structured practice, with domain-specific task constraints on perceptual skill associated with the passing action. Despite performing the same passing skill, it is not known whether long-term exposure to specific soccer or futsal task constraints influences the players’ attunement to environmental information. This study examined this issue by assessing the attention orientation of soccer (n = 24 and futsal players (n = 24 during modified games (6 vs. 6. Futsal players had higher scanning behavior during ball reception and control (40% more ball-player attention alternations while soccer players mainly scanned the environment when not in ball possession (25% more attention alternations. We suggest that the behavioral differences found are elicited by the extensive domain-specific practice. That is, the higher number of players in soccer, and by a more intense game and easier to control ball in futsal. This study provides new insights into the long-term effects of practicing with specific task constraints.

  18. Long-term Practice with Domain-Specific Task Constraints Influences Perceptual Skills.

    Science.gov (United States)

    Oppici, Luca; Panchuk, Derek; Serpiello, Fabio R; Farrow, Damian

    2017-01-01

    The long-term impact of practice with different task constraints on perceptual skill is relatively un-explored. This study examined the influence of extensive practice, i.e., more than a 1000 h of structured practice, with domain-specific task constraints on perceptual skill associated with the passing action. Despite performing the same passing skill, it is not known whether long-term exposure to specific soccer or futsal task constraints influences the players' attunement to environmental information. This study examined this issue by assessing the attention orientation of soccer (n = 24) and futsal players (n = 24) during modified games (6 vs. 6). Futsal players had higher scanning behavior during ball reception and control (40% more ball-player attention alternations) while soccer players mainly scanned the environment when not in ball possession (25% more attention alternations). We suggest that the behavioral differences found are elicited by the extensive domain-specific practice. That is, the higher number of players in soccer, and by a more intense game and easier to control ball in futsal. This study provides new insights into the long-term effects of practicing with specific task constraints.

  19. The influence of referees' expertise, gender, motivation, and time constraints on decisional bias against women.

    Science.gov (United States)

    Souchon, Nicolas; Livingstone, Andrew G; Maio, Gregory R

    2013-12-01

    The influence of player gender on referees' decision making was experimentally investigated. In Experiment 1, including 145 male handball referees, we investigated (a) the influence of referees' level of expertise on their decisional biases against women and (b) the referees' gender stereotypes. Results revealed that biases against women were powerful regardless of the referees' level of expertise and that male referees' stereotype toward female players tends to be negative. In Experiment 2, including 115 sport science students, we examined the influence of the participants' gender, motivation to control bias, and time constraints on gender bias. Results indicated that participants' gender had no impact on gender bias and that participants were able to reduce this bias in conditions in which they were motivated to control the bias.

  20. Integrated systems optimization model for biofuel development: The influence of environmental constraints

    Science.gov (United States)

    Housh, M.; Ng, T.; Cai, X.

    2012-12-01

    The environmental impact is one of the major concerns of biofuel development. While many other studies have examined the impact of biofuel expansion on stream flow and water quality, this study examines the problem from the other side - will and how a biofuel production target be affected by given environmental constraints. For this purpose, an integrated model comprises of different sub-systems of biofuel refineries, transportation, agriculture, water resources and crops/ethanol market has been developed. The sub-systems are integrated into one large-scale model to guide the optimal development plan considering the interdependency between the subsystems. The optimal development plan includes biofuel refineries location and capacity, refinery operation, land allocation between biofuel and food crops, and the corresponding stream flow and nitrate load in the watershed. The watershed is modeled as a network flow, in which the nodes represent sub-watersheds and the arcs are defined as the linkage between the sub-watersheds. The runoff contribution of each sub-watershed is determined based on the land cover and the water uses in that sub-watershed. Thus, decisions of other sub-systems such as the land allocation in the land use sub-system and the water use in the refinery sub-system define the sources and the sinks of the network. Environmental policies will be addressed in the integrated model by imposing stream flow and nitrate load constraints. These constraints can be specified by location and time in the watershed to reflect the spatial and temporal variation of the regulations. Preliminary results show that imposing monthly water flow constraints and yearly nitrate load constraints will change the biofuel development plan dramatically. Sensitivity analysis is performed to examine how the environmental constraints and their spatial and the temporal distribution influence the overall biofuel development plan and the performance of each of the sub

  1. The roles of constraint-based and dedication-based influences on user's continued online shopping behavior.

    Science.gov (United States)

    Chang, Su-Chao; Chou, Chi-Min

    2012-11-01

    The objective of this study was to determine empirically the role of constraint-based and dedication-based influences as drivers of the intention to continue using online shopping websites. Constraint-based influences consist of two variables: trust and perceived switching costs. Dedication-based influences consist of three variables: satisfaction, perceived usefulness, and trust. The current results indicate that both constraint-based and dedication-based influences are important drivers of the intention to continue using online shopping websites. The data also shows that trust has the strongest total effect on online shoppers' intention to continue using online shopping websites. In addition, the results indicate that the antecedents of constraint-based influences, technical bonds (e.g., perceived operational competence and perceived website interactivity) and social bonds (e.g., perceived relationship investment, community building, and intimacy) have indirect positive effects on the intention to continue using online shopping websites. Based on these findings, this research suggests that online shopping websites should build constraint-based and dedication-based influences to enhance user's continued online shopping behaviors simultaneously.

  2. Numerical exploration of the influence of neural noise on the ...

    Indian Academy of Sciences (India)

    The relationship between stimulus intensity and the probability of detecting the presence of the stimulus is described by the psychometrical function. The probabilistic nature of this relationship is based on the stochastic behaviour of sensory neural channels and sensory networks involved in perceptual processing (Kiang ...

  3. Influence of Ambient Stressors and Time Constraints on Diagnostic Accuracy of Borderline Pigmented Skin Lesions.

    Science.gov (United States)

    Feci, Luca; Cevenini, Gabriele; Nami, Niccolò; Fagiolini, Alberto; Perotti, Roberto; Miracco, Clelia; Fimiani, Michele; Rubegni, Pietro

    2015-01-01

    Health professionals are required to make complex decisions in dynamic contexts involving many variables and factors. Decisions are more difficult in the presence of uncertainty, urgency and high risk. To evaluate the effect of ambient stressors and time constraints on decision making by expert dermatologists faced with borderline pigmented skin lesions (PSL) (early melanoma vs. atypical nevi). We performed a retrospective chart review of PSL from the image databases of our department. A total of 321 PSL (219 nevi and 102 melanomas) were randomly assigned to three groups: control group, ambient stress group and time stress group. The diagnostic accuracy of each group was evaluated as sensitivity and specificity. Mean sensitivity and specificity of diagnosis were 69.2 and 90.5% in the control group, 62 and 81.2% in the ambient stress group and 59.6 and 82.5% in the time stress group, respectively. Time constraints and stressors negatively influenced the performance of dermatologists in the diagnosis of atypical PSL. © 2015 S. Karger AG, Basel.

  4. Neural correlates of prosocial peer influence on public goods game donations during adolescence

    OpenAIRE

    Van Hoorn, Jorien; van Dijk, Eric; Güroğlu, Berna; Crone, Eveline A.

    2016-01-01

    A unique feature of adolescent social re-orientation is heightened sensitivity to peer influence when taking risks. However, positive peer influence effects are not yet well understood. The present fMRI study tested a novel hypothesis, by examining neural correlates of prosocial peer influence on donation decisions in adolescence. Participants (age 12–16 years; N = 61) made decisions in anonymous groups about the allocation of tokens between themselves and the group in a public goods game. Tw...

  5. The influence of toxicity constraints in models of chemotherapeutic protocol escalation

    KAUST Repository

    Boston, E. A. J.

    2011-04-06

    The prospect of exploiting mathematical and computational models to gain insight into the influence of scheduling on cancer chemotherapeutic effectiveness is increasingly being considered. However, the question of whether such models are robust to the inclusion of additional tumour biology is relatively unexplored. In this paper, we consider a common strategy for improving protocol scheduling that has foundations in mathematical modelling, namely the concept of dose densification, whereby rest phases between drug administrations are reduced. To maintain a manageable scope in our studies, we focus on a single cell cycle phase-specific agent with uncomplicated pharmacokinetics, as motivated by 5-Fluorouracil-based adjuvant treatments of liver micrometastases. In particular, we explore predictions of the effectiveness of dose densification and other escalations of the protocol scheduling when the influence of toxicity constraints, cell cycle phase specificity and the evolution of drug resistance are all represented within the modelling. For our specific focus, we observe that the cell cycle and toxicity should not simply be neglected in modelling studies. Our explorations also reveal the prediction that dose densification is often, but not universally, effective. Furthermore, adjustments in the duration of drug administrations are predicted to be important, especially when dose densification in isolation does not yield improvements in protocol outcomes. © The author 2011. Published by Oxford University Press on behalf of the Institute of Mathematics and its Applications. All rights reserved.

  6. Neural plasticity and the development of attention: Intrinsic and extrinsic influences.

    Science.gov (United States)

    Swingler, Margaret M; Perry, Nicole B; Calkins, Susan D

    2015-05-01

    The development of attention has been strongly linked to the regulation of emotion and behavior and has therefore been of particular interest to researchers aiming to better understand precursors to behavioral maladjustment. In the current paper, we utilize a developmental psychopathology and neural plasticity framework to highlight the importance of both intrinsic (i.e., infant neural functioning) and extrinsic (i.e., caregiver behavior) factors for the development of attentional control across the first year. We begin by highlighting the importance of attention for children's emotion regulation abilities and mental health. We then review the development of attention behavior and underscore the importance of neural development and caregiver behavior for shaping attentional control. Finally, we posit that neural activation associated with the development of the executive attention network may be one mechanism through which maternal caregiving behavior influences the development of infants' attentional control and subsequent emotion regulation abilities known to be influential to childhood psychopathology.

  7. Constraints to Strategy Implementation and their Influence on Business Performance: the Case of a Waste Management Logistics Company

    Directory of Open Access Journals (Sweden)

    Chengedzai Mafini

    2016-08-01

    Full Text Available Waste management companies in developing countries often have to contend with a plethora of factors that inhibit their business performance. The primary objective of this study was to investigate the influence of constraints to strategy implementation on the business performance of a waste management logistics company in South Africa. The study was triggered by the lack of previous research focusing on constraints to strategy implementation in the waste management sector. The study employed a quantitative approach using the cross sectional survey design in which data were collected from 309 employees of a waste management logistics company based in Gauteng Province. Seven constraints to strategy implementation; namely, management practices, human resource capabilities, customer service, external orientation, internal communication, innovation and employee motivation were identified through Exploratory Factor Analysis. Pearson correlations showed that business performance is negatively affected as and when each constraint becomes more prevalent. Regression analysis showed that all constraints were statistically significant. To academics, the study provides current insights on factors impacting on business performance in waste management organisations. Management practitioners may improve the levels of business performance through structural adjustments of the seven constraints identified in this study. The study may be used as a reference point in the diagnosis of business performance related challenges in companies operating within the waste management sector.

  8. Reproductive constraints influence habitat accessibility, segregation, and preference of sympatric albatross species.

    Science.gov (United States)

    Kappes, Michelle A; Shaffer, Scott A; Tremblay, Yann; Foley, David G; Palacios, Daniel M; Bograd, Steven J; Costa, Daniel P

    2015-01-01

    The spatiotemporal distribution of animals is dependent on a suite of factors, including the distribution of resources, interactions within and between species, physiological limitations, and requirements for reproduction, dispersal, or migration. During breeding, reproductive constraints play a major role in the distribution and behavior of central place foragers, such as pelagic seabirds. We examined the foraging behavior and marine habitat selection of Laysan (Phoebastria immutabilis) and black-footed (P. nigripes) albatrosses throughout their eight month breeding cycle at Tern Island, Northwest Hawaiian Islands to evaluate how variable constraints of breeding influenced habitat availability and foraging decisions. We used satellite tracking and light-based geolocation to determine foraging locations of individuals, and applied a biologically realistic null usage model to generate control locations and model habitat preference under a case-control design. Remotely sensed oceanographic data were used to characterize albatross habitats in the North Pacific. Individuals of both species ranged significantly farther and for longer durations during incubation and chick-rearing compared to the brooding period. Interspecific segregation of core foraging areas was observed during incubation and chick-rearing, but not during brooding. At-sea activity patterns were most similar between species during brooding; neither species altered foraging effort to compensate for presumed low prey availability and high energy demands during this stage. Habitat selection during long-ranging movements was most strongly associated with sea surface temperature for both species, with a preference for cooler ocean temperatures compared to overall availability. During brooding, lower explanatory power of habitat models was likely related to the narrow range of ocean temperatures available for selection. Laysan and black-footed albatrosses differ from other albatross species in that they breed

  9. Influence of the neural microenvironment on prostate cancer.

    Science.gov (United States)

    Coarfa, Christian; Florentin, Diego; Putluri, NagiReddy; Ding, Yi; Au, Jason; He, Dandan; Ragheb, Ahmed; Frolov, Anna; Michailidis, George; Lee, MinJae; Kadmon, Dov; Miles, Brian; Smith, Christopher; Ittmann, Michael; Rowley, David; Sreekumar, Arun; Creighton, Chad J; Ayala, Gustavo

    2018-02-01

    Nerves are key factors in prostate cancer (PCa), but the functional role of innervation in prostate cancer is poorly understood. PCa induced neurogenesis and perineural invasion (PNI), are associated with aggressive disease. We denervated rodent prostates chemically and physically, before orthotopically implanting cancer cells. We also performed a human neoadjuvant clinical trial using botulinum toxin type A (Botox) and saline in the same patient, before prostatectomy. Bilateral denervation resulted in reduced tumor incidence and size in mice. Botox treatment in humans resulted in increased apoptosis of cancer cells in the Botox treated side. A similar denervation gene array profile was identified in tumors arising in denervated rodent prostates, in spinal cord injury patients and in the Botox treated side of patients. Denervation induced exhibited a signature gene profile, indicating translation and bioenergetic shutdown. Nerves also regulate basic cellular functions of non-neoplastic epithelial cells. Nerves play a role in the homeostasis of normal epithelial tissues and are involved in prostate cancer tumor survival. This study confirms that interactions between human cancer and nerves are essential to disease progression. This work may make a major impact in general cancer treatment strategies, as nerve/cancer interactions are likely important in other cancers as well. Targeting the neural microenvironment may represent a therapeutic approach for the treatment of human prostate cancer. © 2017 The Authors. The Prostate Published by Wiley Periodicals, Inc.

  10. Cue validity probability influences neural processing of targets.

    Science.gov (United States)

    Arjona, Antonio; Escudero, Miguel; Gómez, Carlos M

    2016-09-01

    The neural bases of the so-called Spatial Cueing Effect in a visuo-auditory version of the Central Cue Posneŕs Paradigm (CCPP) are analyzed by means of behavioral patterns (Reaction Times and Errors) and Event-Related Potentials (ERPs), namely the Contingent Negative Variation (CNV), N1, P2a, P2p, P3a, P3b and Negative Slow Wave (NSW). The present version consisted of three types of trial blocks with different validity/invalidity proportions: 50% valid - 50% invalid trials, 68% valid - 32% invalid trials and 86% valid - 14% invalid trials. Thus, ERPs can be analyzed as the proportion of valid trials per block increases. Behavioral (Reaction Times and Incorrect responses) and ERP (lateralized component of CNV, P2a, P3b and NSW) results showed a spatial cueing effect as the proportion of valid trials per block increased. Results suggest a brain activity modulation related to sensory-motor attention and working memory updating, in order to adapt to external unpredictable contingencies. Copyright © 2016 Elsevier B.V. All rights reserved.

  11. Conditions that influence the elimination of postural constraints after office employees working with VDU have received ergonomics training.

    Science.gov (United States)

    Montreuil, Sylvie; Laflamme, Lucie; Brisson, Chantal; Teiger, Catherine

    2006-01-01

    The goal of this article is to better understand how preventive measures are undertaken after training. It examines how certain variables, such as musculoskeletal pain, participant age and workstation and work content characteristics influence the reduction of postural constraints after office employees working with a computer have received ergonomics training. A pre-test/post-test design was used. The 207 female office workers were given 6 hours of ergonomics training. The variables were determined using a self-administered questionnaire and an observation grid filled out 2 weeks before and 6 months after the training session. The FAC and HAC were used in the data processing. The presence or absence of musculoskeletal pain had no statistically significant influence on whether or not postural constraints were eliminated. The age of the participants and the possibility of adjusting the workstation characteristics and work content produced differentiated results with regard to postural constraint reduction. We concluded that trained people succeed in taking relevant and effective measures to reduce the postural constraints found in VDUs. However other measures than work station adjustments lead to this prevention and such training must be strongly supported by the various hierarchical levels of an enterprise or an institution.

  12. Neural Mechanisms of the Influence of Popularity on Adolescent Ratings of Music

    OpenAIRE

    Berns, Gregory S.; Capra, C. Monica; Moore, Sara; Noussair, Charles

    2009-01-01

    It is well-known that social influences affect consumption decisions. We used functional magnetic resonance imaging (fMRI) to elucidate the neural mechanisms associated with social influence with regard to a common consumer good: music. Our study population was adolescents, age 12–17. Music is a common purchase in this age group, and it is widely believed that adolescent behavior is influenced by perceptions of popularity in their reference group. Using 15-second clips of songs from MySpace.c...

  13. Neural Basis of Two Kinds of Social Influence: Obedience and Conformity

    OpenAIRE

    Ying eXie; Mingliang eChen; Hongxia eLai; Wuke eZhang; Zhen eZhao; Ch. Mahmood eAnwar

    2016-01-01

    Event-related potentials (ERPs) were used in this study to explore the neural mechanism of obedience and conformity on the model of online book purchasing. Participants were asked to decide as quickly as possible whether to buy a book based on limited information including its title, keywords and number of positive and negative reviews. Obedience was induced by forcing participants to buy books which received mostly negative reviews. In contrast, conformity was aroused by majority influence (...

  14. Temperament and Parenting Styles in Early Childhood Differentially Influence Neural Response to Peer Evaluation in Adolescence

    OpenAIRE

    Guyer, Amanda E.; Jarcho, Johanna M.; Pérez-Edgar, Koraly; Degnan, Kathryn A.; Pine, Daniel S.; Fox, Nathan A.; Nelson, Eric E.

    2015-01-01

    Behavioral inhibition (BI) is a temperament characterized by social reticence and withdrawal from unfamiliar or novel contexts and conveys risk for social anxiety disorder. Developmental outcomes associated with this temperament can be influenced by children’s caregiving context. The convergence of a child’s temperamental disposition and rearing environment is ultimately expressed at both the behavioral and neural levels in emotional and cognitive response patterns to social challenges. The p...

  15. Bases neurales des influences contextuelles lors des décisions perceptives sociales

    OpenAIRE

    El Zein, Marwa

    2015-01-01

    Everyday social decisions require the combination of multiple sources of information and therefore build upon abundant contextual elements such as the social cues of emitters (e.g., gaze direction, emotion, gesture), the attentional focus of observers, their mood and their past experience. The work conducted during this Ph.D. (including three main studies in healthy human subjects) aimed at characterizing the cognitive and neural mechanisms of contextual influences in social settings. The fir...

  16. The influence of reducing intermediate target constraints on grasp posture planning during a three-segment object manipulation task.

    Science.gov (United States)

    Seegelke, Christian; Hughes, Charmayne M L; Knoblauch, Andreas; Schack, Thomas

    2015-02-01

    The present experiment examined the influence of final target position on grasp posture planning during a three-segment object manipulation task in which the required object orientation at the first target position was unconstrained. Participants grasped a cylindrical object from a home position, placed it at an intermediate position in a freely chosen orientation, and subsequently placed it at one of four final target positions. Considerable inter-individual differences in initial grasp selection were observed which also led to differences in final grasp postures. Whereas some participants strongly adjusted their initial grasp postures to the final target orientation, and thus showed a preference for end-state comfort, other participants showed virtually no adjustment in initial grasp postures, hence satisfying initial-state comfort. Interestingly, as intermediate grasp postures were similar regardless of initial grasp adjustment, intermediate-state comfort was prioritized by all participants. These results provide further evidence for the interaction of multiple action selection constraints in grasp posture planning during multi-segment object manipulation tasks. Whereas some constraints may take strict precedence in a given task, other constraints may be more flexible and weighted differently among participants. This differentiated weighting leads to task- and subject-specific constraint hierarchies and is reflected in inter-individual differences in grasp selection.

  17. Research ethics and Institutional Review Boards. The influence of moral constraints on emotion research.

    Science.gov (United States)

    Sontag, Michael

    2012-01-01

    Researchers in the twenty-first century face a set of challenges unknown to researchers a half century ago--the need to justify the moral acceptability of their research methods through formal review processes. However, the role that moral constraints play in the development and demise of scientific theories has largely gone unappreciated. The rise of Institutional Review Boards (IRB) in the 1960s compounded the impact of moral constraints on scientific research and on the theories that develop out of such highly monitored research. To demonstrate the effects of moral constraints on scientific theory and research, this paper offers a history and analysis of the interaction between evolving moral standards and twentieth century emotion theory. Recommendations regarding IRB reform are also reviewed. The paper concludes by arguing that, while appropriate IRB reform is important, it cannot eliminate the need for careful reflection on the broader forces that shape scientific practice and understanding.

  18. Influence of increasing construct constraint in the presence of posterolateral deficiency at knee replacement: A biomechanical study.

    Science.gov (United States)

    Ghosh, Kanishka M; Manning, William A; Blain, Alasdair P; Rushton, Steve P; Longstaff, Lee M; Amis, Andrew A; Deehan, David J

    2016-03-01

    When faced with posterolateral corner (PLC) deficiency, surgeons must choose a total knee replacement (TKR) construct that provides the appropriate level of constraint. This should match the internal constraint of the device to the soft tissue host laxity pattern. Little guidance is available peroperatively, with factors influencing final component choice remaining ill defined. This study aimed to quantify the effect of PLC insufficiency on the "envelope of laxity" (EoL) after TKR and the effect of increasingly component constraint upon knee behavior through a functional arc of flexion. Using computer navigation, mixed effect modeling and loaded cadaveric legs--laxity was quantified under separate states: the native knee, after implantation of a posterior stabilized (PS)-TKR, after sectioning the lateral (fibular) collateral ligament and popliteus tendon (PS-TKR-PLC), and after re-implantation with a semi-constrained "total stabilized" knee replacement (TS-TKR). Laxity was quantified from 0 to 110° of flexion for anterior draw, varus-valgus, and internal-external rotation. Implantation of the PS-TKR was consistently associated with increased constraint when compared to the native knee. PLC sectioning led to significantly increased laxity during varus stress from mid to deep flexion. Revision to a TS-TKR construct restored constraint mimicking that of the primary state but only for the arc of motion 0-90°. In a posterolateral deficient state, a fixed bearing semi-constrained TS-TKR restored the knee to near normal kinematics but this was only achieved from an arc of motion 0-90° of flexion. At higher flexion angles, there remained an unfavorable laxity pattern with varus stress opening. © 2015 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.

  19. Neural Correlates of Social Influence on Risk Taking and Substance Use in Adolescents.

    Science.gov (United States)

    Telzer, Eva H; Rogers, Christina R; Van Hoorn, Jorien

    2017-09-01

    Adolescents often engage in elevated levels of risk taking that gives rise to substance use. Family and peers constitute the primary contextual risk factors for adolescent substance use. This report reviews how families and peers influence adolescent neurocognitive development to inform their risk taking and subsequent substance use. Developmental neuroscience using functional magnetic resonance imaging (fMRI) has identified regions of the brain involved in social cognition, cognitive control, and reward processing that are integrally linked to social influence on adolescent risk taking. These neural mechanisms play a role in how peer and family influence (e.g., physical presence, relationship quality, rejection) translates into adolescent substance use. Peers and families can independently, and in tandem, contribute to adolescent substance use, for better or for worse. We propose that future work utilize fMRI to investigate the neural mechanisms involved in different aspects of peer and family influence, and how these contexts uniquely and interactively influence adolescent substance use initiation and escalation across development.

  20. The Unification Space implemented as a localist neural net: predictions and error-tolerance in a constraint-based parser.

    Science.gov (United States)

    Vosse, Theo; Kempen, Gerard

    2009-12-01

    We introduce a novel computer implementation of the Unification-Space parser (Vosse and Kempen in Cognition 75:105-143, 2000) in the form of a localist neural network whose dynamics is based on interactive activation and inhibition. The wiring of the network is determined by Performance Grammar (Kempen and Harbusch in Verb constructions in German and Dutch. Benjamins, Amsterdam, 2003), a lexicalist formalism with feature unification as binding operation. While the network is processing input word strings incrementally, the evolving shape of parse trees is represented in the form of changing patterns of activation in nodes that code for syntactic properties of words and phrases, and for the grammatical functions they fulfill. The system is capable, at least qualitatively and rudimentarily, of simulating several important dynamic aspects of human syntactic parsing, including garden-path phenomena and reanalysis, effects of complexity (various types of clause embeddings), fault-tolerance in case of unification failures and unknown words, and predictive parsing (expectation-based analysis, surprisal effects). English is the target language of the parser described.

  1. Restoring natural geomorphic process to river environments influenced by practical design constraints

    Science.gov (United States)

    Moir, H. J.

    2015-12-01

    The process restoration philosophy promotes the reinstatement of natural process (particularly the continuum of sediment transport processes) at the catchment scale. Associated with this approach is the concept that river biological communities, having evolved under natural/ un-impacted conditions, will respond positively to the reinstatement of natural physical function. The application of this 'let-the-river-do-the-work' approach is regarded as providing a sustainable alternative to traditional more 'hard engineering' approaches. However, often the reality is that full restoration of the controlling physical processes at the catchment scale is not feasible due to a variety of constraints (e.g. altered geomorphic regime, agriculture, infrastructure/ services, urban development, costs, etc.) and less ambitious objectives have to be set. Thus, under these typical constrained circumstances, can process restoration still be applied and, given the fundamental assumption of biophysical linkage, can ecology still be expected to respond positively? To elucidate these issues, we present four case studies from Scotland which represent the spectrum of process restoration application relating to almost no design constraints to very significant limitations (culvert daylighting within a housing development). We highlight that, despite significant constraints, physical river processes can (and should) always be considered in restoration design. The case studies demonstrate that natural physical processes (evidenced through indicators of sediment transport) quickly reinstate following construction; this was despite significant local constraints but reliant on physical/ geomorphic process being explicitly incorporated into to the design approach. Furthermore, evidence of associated improvements to the ecological/ habitat/ biotic condition of the restored sections of river were observed.

  2. Influence of optimization constraints in uneven parallel bar dismount swing simulations.

    Science.gov (United States)

    Sheets, Alison L; Hubbard, Mont

    2009-08-07

    Forward dynamics simulations of a dismount preparation swing on the uneven parallel bars were optimized to investigate the sensitivity of dismount revolution potential to the maximum bar force before slipping, and to low-bar avoidance. All optimization constraints were classified as 1-anatomical/physiological; limiting maximum hand force on the high bar before slipping, joint ranges of motion and maximum torques, muscle activation/deactivation timing and 2-geometric; avoiding low-bar contact, and requiring minimum landing distance. The gymnast model included torso/head, arm and two leg segments connected by a planar rotating, compliant shoulder and frictionless ball-and-socket hip joints. Maximum shoulder and hip torques were measured as functions of joint angle and angular velocity. Motions were driven by scaling maximum torques by a joint torque activation function of time which approximated the average activation of all muscles crossing the joint causing extension/flexion, or adduction/abduction. Ten joint torque activation values, and bar release times were optimized to maximize dismount revolutions using the downhill simplex method. Low-bar avoidance and maximum bar-force constraints are necessary because they reduce dismount revolution potential. Compared with the no low-bar performance, optimally avoiding the low bar by piking and straddling (abducting) the hips reduces dismount revolutions by 1.8%. Using previously reported experimentally measured peak uneven bar-force values of 3.6 and 4.0 body weight (BW) as optimization constraints, 1.40 and 1.55 revolutions with the body extended and arms overhead were possible, respectively. The bar-force constraint is not active if larger than 6.9 BW, and instead performances are limited only by maximum shoulder and hip torques. Bar forces accelerate the mass center (CM) when performing muscular work to flex/extend the joints, and increase gymnast mechanical energy. Therefore, the bar-force constraint inherently

  3. Analysis of feature selection with Probabilistic Neural Network (PNN) to classify sources influencing indoor air quality

    Science.gov (United States)

    Saad, S. M.; Shakaff, A. Y. M.; Saad, A. R. M.; Yusof, A. M.; Andrew, A. M.; Zakaria, A.; Adom, A. H.

    2017-03-01

    There are various sources influencing indoor air quality (IAQ) which could emit dangerous gases such as carbon monoxide (CO), carbon dioxide (CO2), ozone (O3) and particulate matter. These gases are usually safe for us to breathe in if they are emitted in safe quantity but if the amount of these gases exceeded the safe level, they might be hazardous to human being especially children and people with asthmatic problem. Therefore, a smart indoor air quality monitoring system (IAQMS) is needed that able to tell the occupants about which sources that trigger the indoor air pollution. In this project, an IAQMS that able to classify sources influencing IAQ has been developed. This IAQMS applies a classification method based on Probabilistic Neural Network (PNN). It is used to classify the sources of indoor air pollution based on five conditions: ambient air, human activity, presence of chemical products, presence of food and beverage, and presence of fragrance. In order to get good and best classification accuracy, an analysis of several feature selection based on data pre-processing method is done to discriminate among the sources. The output from each data pre-processing method has been used as the input for the neural network. The result shows that PNN analysis with the data pre-processing method give good classification accuracy of 99.89% and able to classify the sources influencing IAQ high classification rate.

  4. Performance environment and nested task constraints influence long jump approach run: a preliminary study.

    Science.gov (United States)

    Panteli, Flora; Smirniotou, Athanasia; Theodorou, Apostolos

    2016-01-01

    The purpose of the study was to investigate possible changes at step pattern and technical performance of the long jump approach run in seven young long jumpers by modifying the performance environment (long jump runway versus track lane) and the nested actions (run-through with take-off versus complete long jump). Our findings suggest that the step pattern and technical aspects of the approach run are affected by environmental context and nested task constraints. In terms of environmental context, it appears that practising the training routine of run-through followed by take-off on the long jump runway allows athletes to simulate competition conditions in terms of step regulation and technical efficacy. The task of run-through followed by take-off on the track lane failed to initiate visual perception, step regulation and technical efficiency at the steps preceding the instant of take-off. In terms of nested task constraints, when run-ups were followed by jump for distance instead of only a take-off, a higher level of consistency was achieved and step regulation was based on perception-action coupling. Practising long jump run-up accuracy at a setting not containing the informational elements of the performance environment fails to develop the key elements of the skill.

  5. Strategies and determinants for selection of alternate foot placement during human locomotion: influence of spatial and temporal constraints.

    Science.gov (United States)

    Moraes, Renato; Lewis, M Anthony; Patla, Aftab E

    2004-11-01

    During locomotion in a cluttered terrain, certain terrain surfaces such as an icy one are not appropriate for foot placement; an alternate choice is required. In a previous study we showed that the selection of foot placement is not random but systematic; the dominant choices made are not uniquely defined by the available or predicted sensory inputs. We argued that selection is guided by specific rules and involves minimal displacement of the foot from its normal landing spot. The experimental protocol involved implicit spatial constraint by requiring individuals to step on the force plate that could trigger a lighted area to be avoided, thereby requiring individuals to respond within one step-cycle. Alternate foot placement was visually identified, but not measured. The purpose of this study was to directly measure foot placement, validate and/or refine the rules used to guide selection, and identify whether the alternate foot placement choices are influenced by spatial and temporal constraints on response selection. The area to be avoided was visible from the start and therefore individuals could plan and implement appropriate avoidance strategies without any temporal constraint. Spatial constraint introduced in this experiment included requirement both to step on a specific location and to avoid stepping on a specific location on the next step. The results provide support for the rules previously identified in guiding foot placement to an alternate location. Minimal displacement of the foot from its normal landing spot was validated as an important factor for selecting alternate foot placement. When several choices satisfied this factor, additional factors guide alternate foot placement. Modifications in the plane of progression are preferred while stepping wide is avoided. When no temporal constraints are imposed on the response selection, enhancing forward progression of the body becomes the dominant determinant followed by stability and lastly by energy costs

  6. Model of brain activation predicts the neural collective influence map of the brain.

    Science.gov (United States)

    Morone, Flaviano; Roth, Kevin; Min, Byungjoon; Stanley, H Eugene; Makse, Hernán A

    2017-04-11

    Efficient complex systems have a modular structure, but modularity does not guarantee robustness, because efficiency also requires an ingenious interplay of the interacting modular components. The human brain is the elemental paradigm of an efficient robust modular system interconnected as a network of networks (NoN). Understanding the emergence of robustness in such modular architectures from the interconnections of its parts is a longstanding challenge that has concerned many scientists. Current models of dependencies in NoN inspired by the power grid express interactions among modules with fragile couplings that amplify even small shocks, thus preventing functionality. Therefore, we introduce a model of NoN to shape the pattern of brain activations to form a modular environment that is robust. The model predicts the map of neural collective influencers (NCIs) in the brain, through the optimization of the influence of the minimal set of essential nodes responsible for broadcasting information to the whole-brain NoN. Our results suggest intervention protocols to control brain activity by targeting influential neural nodes predicted by network theory.

  7. Constraints specific influences of vision, touch and surface compliance in postural dynamics.

    Science.gov (United States)

    Lee, I-Chieh; Pacheco, Matheus M; Newell, Karl M

    2018-01-01

    Studies that have manipulated vision and touch in posture usually emphasize the prescriptive closed-loop function of the information to reduce the amount of postural motion. In contrast, we examine here the hypothesis that the standard sensory manipulations to maintain quiet stance also change in specific ways the constraints on the task goal and the emergent movement organization. Twelve participants were instructed to maintain quiet postural stance under three sensory factors: surface compliance (foam/no foam), visual information (open/closed eyes) and tactile information (finger touch/no finger touch). The standard deviation of center of pressure (COP) motion decreased with the presence of vision, touch and rigid surface. The correlation dimension showed that the manipulation of touch and vision produced different attractor dynamics that also interacted with surface compliance. Vision decreased the correlation dimension in the foam surface while the touch manipulation increased dimension in the rigid surface. The sensory information manipulations changed the qualitative properties of the attractor dynamics as well as the quantitative properties of the amount of postural motion providing evidence for the specific nature of the postural organization across information conditions. Copyright © 2017 Elsevier B.V. All rights reserved.

  8. Energetic constraints, not predation, influence the evolution of sleep patterning in mammals.

    Science.gov (United States)

    Capellini, I; Nunn, C L; McNamara, P; Preston, B T; Barton, R A

    2008-10-01

    Mammalian sleep is composed of two distinct states - rapid-eye-movement (REM) and non-REM (NREM) sleep - that alternate in cycles over a sleep bout. The duration of these cycles varies extensively across mammalian species. Because the end of a sleep cycle is often followed by brief arousals to waking, a shorter sleep cycle has been proposed to function as an anti-predator strategy. Similarly, higher predation risk could explain why many species exhibit a polyphasic sleep pattern (division of sleep into several bouts per day), as having multiple sleep bouts avoids long periods of unconsciousness, potentially reducing vulnerability.Using phylogenetic comparative methods, we tested these predictions in mammals, and also investigated the relationships among sleep phasing, sleep-cycle length, sleep durations and body mass.Neither sleep-cycle length nor phasing of sleep was significantly associated with three different measures of predation risk, undermining the idea that they represent anti-predator adaptations.Polyphasic sleep was associated with small body size, shorter sleep cycles and longer sleep durations. The correlation with size may reflect energetic constraints: small animals need to feed more frequently, preventing them from consolidating sleep into a single bout. The reduced daily sleep quotas in monophasic species suggests that the consolidation of sleep into one bout per day may deliver the benefits of sleep more efficiently and, since early mammals were small-bodied and polyphasic, a more efficient monophasic sleep pattern could be a hitherto unrecognized advantage of larger size.

  9. Organizational Influences and Constraints on Community College Web-Based Media Relations

    Science.gov (United States)

    McAllister, Sheila M.; Taylor, Maureen

    2012-01-01

    Various organizational, departmental, and interdepartmental factors influence how an educational institution practices public relations. These factors may enable or hinder the ways in which communication practitioners build and maintain relationships with the media. Higher education institutions are especially in need of public relations efforts.…

  10. Comparative study on influence of fetal bovine serum and serum of adult rat on cultivation of newborn rat neural cells

    Directory of Open Access Journals (Sweden)

    Sukach A. N.

    2014-09-01

    Full Text Available Aim. To study the influence of fetal bovine serum and serum of adult rats on behavior of newborn rat isolated neural cells during their cultivation in vitro. Methods. The isolation of neural cells from neonatal rat brain. The determination of the dynamics of cellular monolayer formation. Immunocytochemical staining of cells for β-tubulin III, nestin and vimentin. Results. It has been determined that the addition of serum of adult rats to the cultivation medium creates more favorable conditions for survival, attachment and spread of differentiated, and proliferation of the stem/progenitor neural cells of newborn rats during cultivation in vitro compared with the fetal bovine serum. Conclusions. Using the serum of adult rats is preferable for the cultivation of isolated neural cells of newborn rats compared with the fetal bovine serum.

  11. 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.

  12. Temperament and Parenting Styles in Early Childhood Differentially Influence Neural Response to Peer Evaluation in Adolescence.

    Science.gov (United States)

    Guyer, Amanda E; Jarcho, Johanna M; Pérez-Edgar, Koraly; Degnan, Kathryn A; Pine, Daniel S; Fox, Nathan A; Nelson, Eric E

    2015-07-01

    Behavioral inhibition (BI) is a temperament characterized by social reticence and withdrawal from unfamiliar or novel contexts and conveys risk for social anxiety disorder. Developmental outcomes associated with this temperament can be influenced by children's caregiving context. The convergence of a child's temperamental disposition and rearing environment is ultimately expressed at both the behavioral and neural levels in emotional and cognitive response patterns to social challenges. The present study used functional neuroimaging to assess the moderating effects of different parenting styles on neural response to peer rejection in two groups of adolescents characterized by their early childhood temperament (M(age) = 17.89 years, N = 39, 17 males, 22 females; 18 with BI; 21 without BI). The moderating effects of authoritarian and authoritative parenting styles were examined in three brain regions linked with social anxiety: ventrolateral prefrontal cortex (vlPFC), striatum, and amygdala. In youth characterized with BI in childhood, but not in those without BI, diminished responses to peer rejection in vlPFC were associated with higher levels of authoritarian parenting. In contrast, all youth showed decreased caudate response to peer rejection at higher levels of authoritative parenting. These findings indicate that BI in early life relates to greater neurobiological sensitivity to variance in parenting styles, particularly harsh parenting, in late adolescence. These results are discussed in relation to biopsychosocial models of development.

  13. Influence of neural stem cell transplantation on angiogenesis in rats with spinal cord injury.

    Science.gov (United States)

    Li, Z; Guo, G-H; Wang, G-S; Guan, C-X; Yue, L

    2014-08-07

    We examined the influence of neural stem cell transplantation on angiogenesis in rats with spinal cord injury. Sixty rats with spinal cord injury were divided into an experimental group and a control group and given neural stem cells or an equivalent amount of phosphate-buffered saline by intravenous transplantation, respectively. Basso, Beattie, and Bresnahan (BBB) motor function assessment was performed in rats at different times after transplantation, and von Willebrand factor (vWF) immunofluorescence and Western blot analysis of vascular endothelial growth factor (VEGF) protein were also performed. The BBB scores of rats in the 2 groups were both zero before transplantation. The BBB score gradually increased over time. The BBB score of the experimental group showed no significant difference compared with that of the control group (P > 0.05) 7 days after transplantation. The BBB score of the experimental group was significantly improved compared with that of the control group 14 days after transplantation (P cells and VEGF protein expression in the experimental group were significantly increased compared with those in the control group 7 and 14 days after transplantation, respectively (P stem cell transplantation may promote angiogenesis by inducing VEGF expression as well as improve functional recovery of limb movements.

  14. The influence of the diffusion module to determination of two substrate concentrations by articial neural network

    Directory of Open Access Journals (Sweden)

    Linas Litvinas

    2015-09-01

    Full Text Available The essential part of amperometric biosensor is an enzyme. It should be selective, i.e., react only with certain substrate. The selectivity of enzyme reduces the set of possible to use enzymes. This paper demonstrates that non selective enzymes (reacting with two substrates can be used to determine concentrations of two substrates. For this purpose the steady-state current of two double biosensors was measured. The currents were used as input for an artificial neural network to determine concentrations of the substrates. The proposed approach was approved as the relative error of determined concentrations was relatively small. Paper analyses the influence of biosensor parameters to error values. The recommendations to error values minimisation were obtained.DOI: 10.15181/csat.v3i2.1109 

  15. 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.

  16. Classifying Sources Influencing Indoor Air Quality (IAQ Using Artificial Neural Network (ANN

    Directory of Open Access Journals (Sweden)

    Shaharil Mad Saad

    2015-05-01

    Full Text Available Monitoring indoor air quality (IAQ is deemed important nowadays. A sophisticated IAQ monitoring system which could classify the source influencing the IAQ is definitely going to be very helpful to the users. Therefore, in this paper, an IAQ monitoring system has been proposed with a newly added feature which enables the system to identify the sources influencing the level of IAQ. In order to achieve this, the data collected has been trained with artificial neural network or ANN—a proven method for pattern recognition. Basically, the proposed system consists of sensor module cloud (SMC, base station and service-oriented client. The SMC contain collections of sensor modules that measure the air quality data and transmit the captured data to base station through wireless network. The IAQ monitoring system is also equipped with IAQ Index and thermal comfort index which could tell the users about the room’s conditions. The results showed that the system is able to measure the level of air quality and successfully classify the sources influencing IAQ in various environments like ambient air, chemical presence, fragrance presence, foods and beverages and human activity.

  17. Neural correlates of prosocial peer influence on public goods game donations during adolescence.

    Science.gov (United States)

    Van Hoorn, Jorien; Van Dijk, Eric; Güroğlu, Berna; Crone, Eveline A

    2016-06-01

    A unique feature of adolescent social re-orientation is heightened sensitivity to peer influence when taking risks. However, positive peer influence effects are not yet well understood. The present fMRI study tested a novel hypothesis, by examining neural correlates of prosocial peer influence on donation decisions in adolescence. Participants (age 12-16 years; N = 61) made decisions in anonymous groups about the allocation of tokens between themselves and the group in a public goods game. Two spectator groups of same-age peers-in fact youth actors-were allegedly online during some of the decisions. The task had a within-subjects design with three conditions: (1) EVALUATION: spectators evaluated decisions with likes for large donations to the group, (2) Spectator: spectators were present but no evaluative feedback was displayed and (3) Alone: no spectators nor feedback. Results showed that prosocial behavior increased in the presence of peers, and even more when participants received evaluative feedback from peers. Peer presence resulted in enhanced activity in several social brain regions including medial prefrontal cortex, temporal parietal junction (TPJ), precuneus and superior temporal sulcus. TPJ activity correlated with donations, which suggests similar networks for prosocial behavior and sensitivity to peers. These findings highlight the importance of peers in fostering prosocial development throughout adolescence. © The Author (2016). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  18. Influences of microhabitat constraints and rock-climbing disturbance on cliff-face vegetation communities.

    Science.gov (United States)

    Kuntz, Kathryn Lynne; Larson, Douglas W

    2006-06-01

    Many researchers report that rock climbing has significant negative effects on cliff biota. Most work on climbing disturbance, however has not controlled for variation in microsite characteristics when comparing areas with and without climbing presence. Additionally, some researchers do not identify the style or difficulty level of climbing routes sampled or select climbing routes that do not represent current trends in the sport. We solved these problems by sampling climbing areas used by advanced "sport" climbers and quantifying differences in microtopography between climbed and control cliffs. We determined whether differences in vegetation existed between pristine and sport-climbed cliff faces when microsite factors were not controlled. We then determined the relative influence of the presence of climbing, cliff-face microtopography, local physical factors, and regional geography on the richness, abundance, and community composition of cliff-face vascular plants, bryophytes, and lichens. When we did not control for microsite differences among cliffs, our results were consistent with the majority of prior work on impacts of climbing (i.e., sport-climbed cliff faces supported a lower mean richness of vascular plants and bryophytes and significantly different frequencies of individual species when compared with pristine cliff faces). When we investigated the relative influences of microtopography and climbing disturbance, however the differences in vegetation were not related to climbing disturbance but rather to the selection by sport climbers of cliff faces with microsite characteristics that support less vegetation. Climbed sites had not diverged toward a separate vegetation community; instead, they supported a subset of the species found on pristine cliff faces. Prior management recommendations to restrict development of new climbing routes should be reevaluated based on our results.

  19. Influence of topology in the evolution of coordination in complex networks under information diffusion constraints

    Science.gov (United States)

    Kasthurirathna, Dharshana; Piraveenan, Mahendra; Harré, Michael

    2014-01-01

    In this paper, we study the influence of the topological structure of social systems on the evolution of coordination in them. We simulate a coordination game ("Stag-hunt") on four well-known classes of complex networks commonly used to model social systems, namely scale-free, small-world, random and hierarchical-modular, as well as on the well-mixed model. Our particular focus is on understanding the impact of information diffusion on coordination, and how this impact varies according to the topology of the social system. We demonstrate that while time-lags and noise in the information about relative payoffs affect the emergence of coordination in all social systems, some topologies are markedly more resilient than others to these effects. We also show that, while non-coordination may be a better strategy in a society where people do not have information about the payoffs of others, coordination will quickly emerge as the better strategy when people get this information about others, even with noise and time lags. Societies with the so-called small-world structure are most conducive to the emergence of coordination, despite limitations in information propagation, while societies with scale-free topologies are most sensitive to noise and time-lags in information diffusion. Surprisingly, in all topologies, it is not the highest connected people (hubs), but the slightly less connected people (provincial hubs) who first adopt coordination. Our findings confirm that the evolution of coordination in social systems depends heavily on the underlying social network structure.

  20. The influences and neural correlates of past and present during gambling in humans.

    Science.gov (United States)

    Sacré, Pierre; Subramanian, Sandya; Kerr, Matthew S D; Kahn, Kevin; Johnson, Matthew A; Bulacio, Juan; González-Martínez, Jorge A; Sarma, Sridevi V; Gale, John T

    2017-12-07

    During financial decision-making tasks, humans often make "rational" decisions, where they maximize expected reward. However, this rationality may compete with a bias that reflects past outcomes. That is, if one just lost money or won money, this may impact future decisions. It is unclear how past outcomes influence future decisions in humans, and how neural circuits encode present and past information. In this study, six human subjects performed a financial decision-making task while we recorded local field potentials from multiple brain structures. We constructed a model for each subject characterizing bets on each trial as a function of present and past information. The models suggest that some patients are more influenced by previous trial outcomes (i.e., previous return and risk) than others who stick to more fixed decision strategies. In addition, past return and present risk modulated with the activity in the cuneus; while present return and past risk modulated with the activity in the superior temporal gyrus and the angular gyrus, respectively. Our findings suggest that these structures play a role in decision-making beyond their classical functions by incorporating predictions and risks in humans' decision strategy, and provide new insight into how humans link their internal biases to decisions.

  1. Neural responses to smoking stimuli are influenced by smokers' attitudes towards their own smoking behaviour.

    Directory of Open Access Journals (Sweden)

    Bastian Stippekohl

    Full Text Available An important feature of addiction is the high drug craving that may promote the continuation of consumption. Environmental stimuli classically conditioned to drug-intake have a strong motivational power for addicts and can elicit craving. However, addicts differ in the attitudes towards their own consumption behavior: some are content with drug taking (consonant users whereas others are discontent (dissonant users. Such differences may be important for clinical practice because the experience of dissonance might enhance the likelihood to consider treatment. This fMRI study investigated in smokers whether these different attitudes influence subjective and neural responses to smoking stimuli. Based on self-characterization, smokers were divided into consonant and dissonant smokers. These two groups were presented smoking stimuli and neutral stimuli. Former studies have suggested differences in the impact of smoking stimuli depending on the temporal stage of the smoking ritual they are associated with. Therefore, we used stimuli associated with the beginning (BEGIN-smoking-stimuli and stimuli associated with the terminal stage (END-smoking-stimuli of the smoking ritual as distinct stimulus categories. Stimulus ratings did not differ between both groups. Brain data showed that BEGIN-smoking-stimuli led to enhanced mesolimbic responses (amygdala, hippocampus, insula in dissonant compared to consonant smokers. In response to END-smoking-stimuli, dissonant smokers showed reduced mesocortical responses (orbitofrontal cortex, subcallosal cortex compared to consonant smokers. These results suggest that smoking stimuli with a high incentive value (BEGIN-smoking-stimuli are more appetitive for dissonant than consonant smokers at least on the neural level. To the contrary, smoking stimuli with low incentive value (END-smoking-stimuli seem to be less appetitive for dissonant smokers than consonant smokers. These differences might be one reason why dissonant

  2. Influence of aerobic exercise training on the neural correlates of motor learning in Parkinson's disease individuals.

    Science.gov (United States)

    Duchesne, C; Gheysen, F; Bore, A; Albouy, G; Nadeau, A; Robillard, M E; Bobeuf, F; Lafontaine, A L; Lungu, O; Bherer, L; Doyon, J

    Aerobic exercise training (AET) has been shown to provide general health benefits, and to improve motor behaviours in particular, in individuals with Parkinson's disease (PD). However, the influence of AET on their motor learning capacities, as well as the change in neural substrates mediating this effect remains to be explored. In the current study, we employed functional Magnetic Resonance Imaging (fMRI) to assess the effect of a 3-month AET program on the neural correlates of implicit motor sequence learning (MSL). 20 healthy controls (HC) and 19 early PD individuals participated in a supervised, high-intensity, stationary recumbent bike training program (3 times/week for 12 weeks). Exercise prescription started at 20 min (+ 5 min/week up to 40 min) based on participant's maximal aerobic power. Before and after the AET program, participants' brain was scanned while performing an implicit version of the serial reaction time task. Brain data revealed pre-post MSL-related increases in functional activity in the hippocampus, striatum and cerebellum in PD patients, as well as in the striatum in HC individuals. Importantly, the functional brain changes in PD individuals correlated with changes in aerobic fitness: a positive relationship was found with increased activity in the hippocampus and striatum, while a negative relationship was observed with the cerebellar activity. Our results reveal, for the first time, that exercise training produces functional changes in known motor learning related brain structures that are consistent with improved behavioural performance observed in PD patients. As such, AET can be a valuable non-pharmacological intervention to promote, not only physical fitness in early PD, but also better motor learning capacity useful in day-to-day activities through increased plasticity in motor related structures.

  3. Neural mechanisms of the influence of popularity on adolescent ratings of music.

    Science.gov (United States)

    Berns, Gregory S; Capra, C Monica; Moore, Sara; Noussair, Charles

    2010-02-01

    It is well-known that social influences affect consumption decisions. We used functional magnetic resonance imaging (fMRI) to elucidate the neural mechanisms associated with social influence with regard to a common consumer good: music. Our study population was adolescents, age 12-17. Music is a common purchase in this age group, and it is widely believed that adolescent behavior is influenced by perceptions of popularity in their reference group. Using 15-s clips of songs from MySpace.com, we obtained behavioral measures of preferences and neurobiological responses to the songs. The data were gathered with, and without, the overall popularity of the song revealed. Song popularity had a significant effect on the participants' likability ratings of the songs. fMRI results showed a strong correlation between the participants' rating and activity in the caudate nucleus, a region previously implicated in reward-driven actions. The tendency to change one's evaluation of a song was positively correlated with activation in the anterior insula and anterior cingulate, two regions that are associated with physiological arousal and negative affective states. Sensitivity to popularity was linked to lower activation levels in the middle temporal gyrus, suggesting a lower depth of musical semantic processing. Our results suggest that a principal mechanism whereby popularity ratings affect consumer choice is through the anxiety generated by the mismatch between one's own preferences and others'. This mismatch anxiety motivates people to switch their choices in the direction of the consensus. Our data suggest that this is a major force behind the conformity observed in music tastes in some teenagers. Copyright (c) 2009 Elsevier Inc. All rights reserved.

  4. Androgenic influences on neural asymmetry: Handedness and language lateralization in individuals with congenital adrenal hyperplasia.

    Science.gov (United States)

    Mathews, Greta A; Fane, Briony A; Pasterski, Vickie L; Conway, Gerard S; Brook, Charles; Hines, Melissa

    2004-07-01

    This study tested the hypothesis that prenatal androgen levels influence hand preferences and language lateralization, two manifestations of neural asymmetry. Participants were individuals with congenital adrenal hyperplasia (CAH, a genetic disorder that results in excess adrenal androgen production beginning prenatally) (40 females; 29 males) and their unaffected relatives (29 females; 30 males) who ranged in age from 12-45 years. The Edinburgh-Crovitz Inventory and the performance of five simple tasks (the Handedness Activities Test) were the measures of hand preferences, and a dichotic listening task composed of consonant-vowel nonsense syllables was the measure of language lateralization. No sex differences were observed among relative controls in hand preferences or language lateralization. Male participants with CAH were less consistently right-handed for writing than unaffected male relatives, when those who had been forced to switch writing hands from left to right were considered with left-handers as being not consistently right-handed. There were no other significant differences between individuals with CAH and unaffected relatives. These results do not support the hypothesis that prenatal androgens influence language lateralization, nor do they support the Geschwind-Behan-Galaburda model that posits a key role for testosterone in the development of cognitive problems in males, secondary to changes in hemispheric development and cognitive lateralization. Hormonal influences on handedness, although not always consistent, may be more likely. However, given that sex differences in both language lateralization and handedness are small, it is possible that limited sample size precludes the detection of consistent group differences.

  5. Constraint Differentiation

    DEFF Research Database (Denmark)

    Mödersheim, Sebastian Alexander; Basin, David; Viganò, Luca

    2010-01-01

    We introduce constraint differentiation, a powerful technique for reducing search when model-checking security protocols using constraint-based methods. Constraint differentiation works by eliminating certain kinds of redundancies that arise in the search space when using constraints to represent...

  6. Determining the Neural Substrate for Encoding a Memory of Human Pain and the Influence of Anxiety.

    Science.gov (United States)

    Tseng, Ming-Tsung; Kong, Yazhuo; Eippert, Falk; Tracey, Irene

    2017-12-06

    To convert a painful stimulus into a briefly maintainable construct when the painful stimulus is no longer accessible is essential to guide human behavior and avoid dangerous situations. Because of the aversive nature of pain, this encoding process might be influenced by emotional aspects and could thus vary across individuals, but we have yet to understand both the basic underlying neural mechanisms as well as potential interindividual differences. Using fMRI in combination with a delayed-discrimination task in healthy volunteers of both sexes, we discovered that brain regions involved in this working memory encoding process were dissociable according to whether the to-be-remembered stimulus was painful or not, with the medial thalamus and the rostral anterior cingulate cortex encoding painful and the primary somatosensory cortex encoding nonpainful stimuli. Encoding of painful stimuli furthermore significantly enhanced functional connectivity between the thalamus and medial prefrontal cortex (mPFC). With regards to emotional aspects influencing encoding processes, we observed that more anxious participants showed significant performance advantages when encoding painful stimuli. Importantly, only during the encoding of pain, the interindividual differences in anxiety were associated with the strength of coupling between medial thalamus and mPFC, which was furthermore related to activity in the amygdala. These results indicate not only that there is a distinct signature for the encoding of a painful experience in humans, but also that this encoding process involves a strong affective component. SIGNIFICANCE STATEMENT To convert the sensation of pain into a briefly maintainable construct is essential to guide human behavior and avoid dangerous situations. Although this working memory encoding process is implicitly contained in the majority of studies, the underlying neural mechanisms remain unclear. Using fMRI in a delayed-discrimination task, we found that the

  7. The neural correlates of biomechanical constraints in hand laterality judgment task performed from other person's perspective: A near-infrared spectroscopy study.

    Science.gov (United States)

    Meng, Shuang; Oi, Misato; Saito, Godai; Saito, Hirofumi

    2017-01-01

    Previous studies, mainly using a first-person perspective (1PP), have shown that the judgments of the hand laterality judgment (HLJ) task are dependent on biomechanical constraints (BC). Specifically, differing reaction times (RT) for hand pictures rotated medially or laterally around the mid sagittal plane are attributed to the BC effect on motor imagery. In contrast, we investigated whether the HLJ task is also subject to BC when performed from a third-person perspective (3PP) as well as 1PP using near-infrared spectroscopy (NIRS) to measure the brain activity of prefrontal cortex (PFC) in right-handed participants assigned to 1PP or 3PP groups. The 1PP group judged whether a presented hand was their own left or right hand, and the 3PP group whether it was the other's left or right hand. Using their HLJ task error rates, the 1PP and 3PP groups were subdivided into an Error Group (EG) and No Error Group (NEG). For the 1PP group, both EG and NEG showed a significant Hand Laterality × Orientation interaction for RT, indicating the BC effect on motor imagery. For the 3PP group, however, neither EG nor NEG showed the interaction, even though EG showed a significantly longer RT than NEG. These results suggest that the 3PP EG appropriately followed the 3PP task instruction, while the NEG might have taken 1PP. However, the 3PP EG NIRS profile of left PFC showed a significant Hand Laterality × Orientation interaction, while the 1PP EG did not. More noteworthy is that the left PFC activation of EG showed an interaction between the 1PP and 3PP groups when the left hand was presented. Furthermore, in the NEG, the PFC activation was not influenced by the BC in either the 1PP or 3PP condition. These results indicate that BC interferes with the HLJ task performed from the 1PP and 3PP.

  8. A neural networks application for the study of the influence of transport conditions on the working performance

    Science.gov (United States)

    Anghel, D.-C.; Ene, A.; Ştirbu, C.; Sicoe, G.

    2017-10-01

    This paper presents a study about the factors that influence the working performances of workers in the automotive industry. These factors regard mainly the transportations conditions, taking into account the fact that a large number of workers live in places that are far away of the enterprise. The quantitative data obtained from this study will be generalized by using a neural network, software simulated. The neural network is able to estimate the performance of workers even for the combinations of input factors that had been not recorded by the study. The experimental data obtained from the study will be divided in two classes. The first class that contains approximately 80% of data will be used by the Java software for the training of the neural network. The weights resulted from the training process will be saved in a text file. The other class that contains the rest of the 20% of experimental data will be used to validate the neural network. The training and the validation of the networks are performed in a Java software (TrainAndValidate java class). We designed another java class, Test.java that will be used with new input data, for new situations. The experimental data collected from the study. The software that simulated the neural network. The software that estimates the working performance, when new situations are met. This application is useful for human resources department of an enterprise. The output results are not quantitative. They are qualitative (from low performance to high performance, divided in five classes).

  9. Numerical Analysis of the Influence of In-Plane Constraints on the Crack Tip Opening Displacement for SEN(B Specimens Under Predominantly Plane Strain Conditions

    Directory of Open Access Journals (Sweden)

    Graba M.

    2016-12-01

    Full Text Available This paper presents a numerical analysis of the relationship between in-plane constraints and the crack tip opening displacement (CTOD for single-edge notched bend (SEN(B specimens under predominantly plane strain conditions. It provides details of the numerical model and discusses the influence of external load and in-plane constraints on the CTOD. The work also reviews methods for determining the CTOD. The new formula proposed in this paper can be used to estimate the value of the coefficient dn as a function of the relative crack length, the strain hardening exponent and the yield strength - dn(n, σ0/E, a/W, with these parameters affecting the level of in-plane constraints. Some of the numerical results were approximated using simple mathematical formulae.

  10. Neural Basis of Two Kinds of Social Influence: Obedience and Conformity

    Directory of Open Access Journals (Sweden)

    Ying eXie

    2016-02-01

    Full Text Available Event-related potentials (ERPs were used in this study to explore the neural mechanism of obedience and conformity on the model of online book purchasing. Participants were asked to decide as quickly as possible whether to buy a book based on limited information including its title, keywords and number of positive and negative reviews. Obedience was induced by forcing participants to buy books which received mostly negative reviews. In contrast, conformity was aroused by majority influence (caused by positive and negative comments. P3 and N2, two kinds of ERP components related to social cognitive process, were measured and recorded with electroencephalogram (EEG test. The results show that compared with conformity decisions, obedience decisions induced greater cognitive conflicts. In ERP measurements, greater amplitudes of N2 component were observed in the context of obedience. However, consistency level did not make a difference on P3 peak latency for both conformity and obedience. This shows that classification process is implicit in both conformity and obedience decision-making. In addition, for both conformity and obedience decisions, augmented P3 was observed when the reviews consistency (either negative or positive was higher.

  11. Neural Basis of Two Kinds of Social Influence: Obedience and Conformity.

    Science.gov (United States)

    Xie, Ying; Chen, Mingliang; Lai, Hongxia; Zhang, Wuke; Zhao, Zhen; Anwar, Ch Mahmood

    2016-01-01

    Event-related potentials (ERPs) were used in this study to explore the neural mechanism of obedience and conformity on the model of online book purchasing. Participants were asked to decide as quickly as possible whether to buy a book based on limited information including its title, keywords and number of positive and negative reviews. Obedience was induced by forcing participants to buy books which received mostly negative reviews. In contrast, conformity was aroused by majority influence (caused by positive and negative comments). P3 and N2, two kinds of ERP components related to social cognitive process, were measured and recorded with electroencephalogram (EEG) test. The results show that compared with conformity decisions, obedience decisions induced greater cognitive conflicts. In ERP measurements, greater amplitudes of N2 component were observed in the context of obedience. However, consistency level did not make a difference on P3 peak latency for both conformity and obedience. This shows that classification process is implicit in both conformity and obedience decision-making. In addition, for both conformity and obedience decisions, augmented P3 was observed when the reviews consistency (either negative or positive) was higher.

  12. Biphasic influence of Miz1 on neural crest development by regulating cell survival and apical adhesion complex formation in the developing neural tube

    Science.gov (United States)

    Kerosuo, Laura; Bronner, Marianne E.

    2014-01-01

    Myc interacting zinc finger protein-1 (Miz1) is a transcription factor known to regulate cell cycle– and cell adhesion–related genes in cancer. Here we show that Miz1 also plays a critical role in neural crest development. In the chick, Miz1 is expressed throughout the neural plate and closing neural tube. Its morpholino-mediated knockdown affects neural crest precursor survival, leading to reduction of neural plate border and neural crest specifier genes Msx-1, Pax7, FoxD3, and Sox10. Of interest, Miz1 loss also causes marked reduction of adhesion molecules (N-cadherin, cadherin6B, and α1-catenin) with a concomitant increase of E-cadherin in the neural folds, likely leading to delayed and decreased neural crest emigration. Conversely, Miz1 overexpression results in up-regulation of cadherin6B and FoxD3 expression in the neural folds/neural tube, leading to premature neural crest emigration and increased number of migratory crest cells. Although Miz1 loss effects cell survival and proliferation throughout the neural plate, the neural progenitor marker Sox2 was unaffected, suggesting a neural crest–selective effect. The results suggest that Miz1 is important not only for survival of neural crest precursors, but also for maintenance of integrity of the neural folds and tube, via correct formation of the apical adhesion complex therein. PMID:24307680

  13. Influence of the complex-shape light signal on the neural network

    Science.gov (United States)

    Melnikov, Leonid A.; Novosselova, Anna V.; Blinova, Nadejda V.

    1999-03-01

    The effect of external signals of different shapes (constant, serrated and others) on the ring neural network modeling the visual perception is investigated numerically. New specific features in the dynamics of the neural network, such as the excitation, the swapping and the depression, were observed. The cooperative amplication of the external signal and the memory effect have been observed.

  14. Factors influencing the differentiation of dopaminergic traits in transplanted neural stem cells.

    Science.gov (United States)

    Yang, Ming; Donaldson, Angela E; Jiang, Yubao; Iacovitti, Lorraine

    2003-10-01

    1. Our previous studies demonstrated that when neural stem cells (NSCs) of the C17.2 clonal line are transplanted into the intact or 6-hydroxydopamine (6-OHDA) lesioned rat striatum, in most, but not all grafts, cells spontaneously express the dopamine (DA) biosynthetic enzymes, tyrosine hydroxylase (TH), and aromatic L-amino acid decarboxylase (Yang, M., Stull, N. D., Snyder. E. Y., Berk, M. A., and Iacovitti, L. (2002). Exp. Neurol.). 2. These results suggested that there were certain conditions which were more conducive to the development of DA traits in NSCs and possibly other neurotransmitter phenotypes. 3. In the present study, we modified a number of variables in vitro (i.e. passage number, confluence) and/or in vivo (degree, type, and site of injury) before assessing the survival, migration. and differentiation of engrafted NSCs. 4. We found that low confluence cultures were comprised exclusively of flattened polygonal cells, which when transplanted, migrated widely in the brain but did not express TH. 5. In contrast, high confluence cultures contained both polygonal cells and an overlying bed of fusiform cells. 6. When these NSCs were maintained for 12-20 passages and then transplanted, virtually all engrafted cells in 65% of the grafts expressed TH but not markers of other neurotransmitter systems. 7. Importantly, all TH+ grafts were accompanied by significant physical damage to the brain while TH- grafts were not, suggesting that local injury-related factors were also important. 8. Of no apparent influence on TH expression, regardless of how cells were grown prior to implantation, was the site of transplantation (cortex or striatum) or the degree of chemical lesion (intact, partial or full). 9. We conclude that transplanted NSCs can express traits specifically associated with DA neurons but only when cells are grown under certain conditions in vitro and then transplanted in proximity to injury-induced factors present in vivo.

  15. Caldesmon regulates actin dynamics to influence cranial neural crest migration in Xenopus

    OpenAIRE

    Nie, Shuyi; Kee, Yun; Bronner-Fraser, Marianne

    2011-01-01

    Caldesmon (CaD) is an important actin modulator that associates with actin filaments to regulate cell morphology and motility. Although extensively studied in cultured cells, there is little functional information regarding the role of CaD in migrating cells in vivo. Here we show that nonmuscle CaD is highly expressed in both premigratory and migrating cranial neural crest cells of Xenopus embryos. Depletion of CaD with antisense morpholino oligonucleotides causes cranial neural crest cells t...

  16. Beauty is in the belief of the beholder: cognitive influences on the neural response to facial attractiveness.

    Science.gov (United States)

    Thiruchselvam, Ravi; Harper, Jessica; Homer, Abigail L

    2016-12-01

    Judgments of facial attractiveness are central to decision-making in various domains, but little is known about the extent to which they are malleable. In this study, we used EEG/ERP methods to examine two novel influences on neural and subjective responses to facial attractiveness: an observer's expectation and repetition. In each trial of our task, participants viewed either an ordinary or attractive face. To alter expectations, the faces were preceded by a peer-rating that ostensibly reflected the overall attractiveness value assigned to that face by other individuals. To examine the impact of repetition, trials were presented twice throughout the experimental session. Results showed that participants' expectations about a person's attractiveness level powerfully altered both the neural response (i.e. the late positive potential; LPP) and self-reported attractiveness ratings. Intriguingly, repetition enhanced both the LPP and self-reported attractiveness as well. Exploratory analyses further suggested that both observer expectation and repetition modulated early neural responses (i.e. the early posterior negativity; EPN) elicited by facial attractiveness. Collectively, these results highlight novel influences on a core social judgment that underlies individuals' affective lives. © The Author (2016). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  17. The Influence of EDM Parameters in Finishing Stage on Surface Quality of Hot Work Steel Using Artificial Neural Network

    Science.gov (United States)

    Amini, S.; Atefi, R.; Solhjoei, N.

    2011-01-01

    In this paper, the influence of different EDM parameters (pulse current, pulse voltage, pulse on-time , pulse off-time) in finishing stage on the surface quality (Ra) as a result of application copper electrode to a work piece( hot work steel DIN1.2344) has been investigated. Design of the experiment was chosen full factorial. Statistical analysis has been done and artificial neural network has been used to choose proper machining parameters and to reach certain surface roughness. Finally a hybrid model has been designed to reduce the artificial neural network errors. The experiment results indicated a good performance of proposed method in optimization of such a complex and non-linear problems.

  18. The Power of the Like in Adolescence: Effects of Peer Influence on Neural and Behavioral Responses to Social Media.

    Science.gov (United States)

    Sherman, Lauren E; Payton, Ashley A; Hernandez, Leanna M; Greenfield, Patricia M; Dapretto, Mirella

    2016-07-01

    We investigated a unique way in which adolescent peer influence occurs on social media. We developed a novel functional MRI (fMRI) paradigm to simulate Instagram, a popular social photo-sharing tool, and measured adolescents' behavioral and neural responses to likes, a quantifiable form of social endorsement and potential source of peer influence. Adolescents underwent fMRI while viewing photos ostensibly submitted to Instagram. They were more likely to like photos depicted with many likes than photos with few likes; this finding showed the influence of virtual peer endorsement and held for both neutral photos and photos of risky behaviors (e.g., drinking, smoking). Viewing photos with many (compared with few) likes was associated with greater activity in neural regions implicated in reward processing, social cognition, imitation, and attention. Furthermore, when adolescents viewed risky photos (as opposed to neutral photos), activation in the cognitive-control network decreased. These findings highlight possible mechanisms underlying peer influence during adolescence. © The Author(s) 2016.

  19. Strategies influence neural activity for feedback learning across child and adolescent development.

    Science.gov (United States)

    Peters, Sabine; Koolschijn, P Cédric M P; Crone, Eveline A; Van Duijvenvoorde, Anna C K; Raijmakers, Maartje E J

    2014-09-01

    Learning from feedback is an important aspect of executive functioning that shows profound improvements during childhood and adolescence. This is accompanied by neural changes in the feedback-learning network, which includes pre-supplementary motor area (pre- SMA)/anterior cingulate cortex (ACC), dorsolateral prefrontal cortex (DLPFC), superior parietal cortex (SPC), and the basal ganglia. However, there can be considerable differences within age ranges in performance that are ascribed to differences in strategy use. This is problematic for traditional approaches of analyzing developmental data, in which age groups are assumed to be homogenous in strategy use. In this study, we used latent variable models to investigate if underlying strategy groups could be detected for a feedback-learning task and whether there were differences in neural activation patterns between strategies. In a sample of 268 participants between ages 8 to 25 years, we observed four underlying strategy groups, which were cut across age groups and varied in the optimality of executive functioning. These strategy groups also differed in neural activity during learning; especially the most optimal performing group showed more activity in DLPFC, SPC and pre-SMA/ACC compared to the other groups. However, age differences remained an important contributor to neural activation, even when correcting for strategy. These findings contribute to the debate of age versus performance predictors of neural development, and highlight the importance of studying individual differences in strategy use when studying development. Copyright © 2014 Elsevier Ltd. All rights reserved.

  20. The influence of mental fatigue and motivation on neural network dynamics; an EEG coherence study

    NARCIS (Netherlands)

    Lorist, Monicque M.; Bezdan, Eniko; Caat, Michael ten; Span, Mark M.; Roerdink, Jos B.T.M.; Maurits, Natasha M.

    2009-01-01

    The purpose of the present study is to examine the effects of mental fatigue and motivation on neural network dynamics activated during task switching. Mental fatigue was induced by 2 h of continuous performance; after which subjects were motivated by using social comparison and monetary reward as

  1. Folic acid supplementation influences the distribution of neural tube defect subtypes : A registry-based study

    NARCIS (Netherlands)

    Bergman, J. E. H.; Otten, E.; Verheij, J. B. G. M.; de Walle, H. E. K.

    Periconceptional folic acid (FA) reduces neural tube defect (NTD) risk, but seems to have a varying effect per NTD subtype. We aimed to study the effect of FA supplementation on NTD subtype distribution using data from EUROCAT Northern Netherlands. We included all birth types with non-syndromal NTDs

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

    Science.gov (United States)

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

    2015-01-12

    Language experience fine-tunes how the auditory system processes sound. 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 and we demonstrate that these neural enhancements track with years of bilingual experience. These findings support the notion that bilingualism enhances subcortical auditory processing. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  3. 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

  4. Caldesmon regulates actin dynamics to influence cranial neural crest migration in Xenopus.

    Science.gov (United States)

    Nie, Shuyi; Kee, Yun; Bronner-Fraser, Marianne

    2011-09-01

    Caldesmon (CaD) is an important actin modulator that associates with actin filaments to regulate cell morphology and motility. Although extensively studied in cultured cells, there is little functional information regarding the role of CaD in migrating cells in vivo. Here we show that nonmuscle CaD is highly expressed in both premigratory and migrating cranial neural crest cells of Xenopus embryos. Depletion of CaD with antisense morpholino oligonucleotides causes cranial neural crest cells to migrate a significantly shorter distance, prevents their segregation into distinct migratory streams, and later results in severe defects in cartilage formation. Demonstrating specificity, these effects are rescued by adding back exogenous CaD. Interestingly, CaD proteins with mutations in the Ca(2+)-calmodulin-binding sites or ErK/Cdk1 phosphorylation sites fail to rescue the knockdown phenotypes, whereas mutation of the PAK phosphorylation site is able to rescue them. Analysis of neural crest explants reveals that CaD is required for the dynamic arrangements of actin and, thus, for cell shape changes and process formation. Taken together, these results suggest that the actin-modulating activity of CaD may underlie its critical function and is regulated by distinct signaling pathways during normal neural crest migration.

  5. The influence of personality on neural mechanisms of observational fear and reward learning.

    Science.gov (United States)

    Hooker, Christine I; Verosky, Sara C; Miyakawa, Asako; Knight, Robert T; D'Esposito, Mark

    2008-09-01

    Fear and reward learning can occur through direct experience or observation. Both channels can enhance survival or create maladaptive behavior. We used fMRI to isolate neural mechanisms of observational fear and reward learning and investigate whether neural response varied according to individual differences in neuroticism and extraversion. Participants learned object-emotion associations by observing a woman respond with fearful (or neutral) and happy (or neutral) facial expressions to novel objects. The amygdala-hippocampal complex was active when learning the object-fear association, and the hippocampus was active when learning the object-happy association. After learning, objects were presented alone; amygdala activity was greater for the fear (vs. neutral) and happy (vs. neutral) associated object. Importantly, greater amygdala-hippocampal activity during fear (vs. neutral) learning predicted better recognition of learned objects on a subsequent memory test. Furthermore, personality modulated neural mechanisms of learning. Neuroticism positively correlated with neural activity in the amygdala and hippocampus during fear (vs. neutral) learning. Low extraversion/high introversion was related to faster behavioral predictions of the fearful and neutral expressions during fear learning. In addition, low extraversion/high introversion was related to greater amygdala activity during happy (vs. neutral) learning, happy (vs. neutral) object recognition, and faster reaction times for predicting happy and neutral expressions during reward learning. These findings suggest that neuroticism is associated with an increased sensitivity in the neural mechanism for fear learning which leads to enhanced encoding of fear associations, and that low extraversion/high introversion is related to enhanced conditionability for both fear and reward learning.

  6. Do semantic sentence constraint and L2 proficiency influence language selectivity of lexical access in native language listening?

    Science.gov (United States)

    Lagrou, Evelyne; Hartsuiker, Robert J; Duyck, Wouter

    2015-12-01

    We investigated whether language nonselective lexical access in bilingual auditory word recognition when listening in the native language (L1) is modulated by (a) the semantic constraint of the sentence and (b) the second language (L2) proficiency level. We report 2 experiments in which Dutch-English bilinguals with different proficiency levels completed an L1 auditory lexical-decision task on the last word of low- and high-constraining sentences. The critical stimuli were interlingual homophones (e.g., lief [sweet] - leaf /li:f/). Participants recognized homophones significantly slower than matched control words. Importantly, neither the semantic constraint of the sentence, nor the proficiency level of the bilinguals interacted with this interlingual homophone effect. However, when we compared the slow and fast reaction times (RTs), we observed a reduction in the homophone interference effect when listening to high-constraining sentences in L1 for the slow RTs, but not for the fast RTs. Taken together, this provides strong evidence for a language-nonselective account of lexical access when listening in L1, and suggests that even when low-proficient bilinguals are listening to high-constraint sentences in L1, both languages of a bilingual are still activated. (c) 2015 APA, all rights reserved).

  7. The influence of a depressed scapular alignment on upper limb neural tissue mechanosensitivity and local pressure pain sensitivity.

    Science.gov (United States)

    Martínez-Merinero, Patricia; Lluch, Enriqe; Gallezo-Izquierdo, Tomas; Pecos-Martín, Daniel; Plaza-Manzano, Gustavo; Nuñez-Nagy, Susana; Falla, Deborah

    2017-06-01

    A depressed scapular alignment could lead to prolonged and repetitive stress or compression of the brachial plexus, resulting in sensitization of neural tissue. However, no study has investigated the influence of alignment of the scapulae on sensitization of upper limb neural tissue in otherwise asymptomatic people. In this case-control study, we investigate the influence of a depressed scapular alignment on mechanosensitivity of the upper limb peripheral nervous system as well as pressure pain thresholds (PPT). Asymptomatic individuals with neutral vertical scapular alignment (n = 25) or depressed scapular alignment (n = 25) participated. We measured the upper limb neurodynamic test (ULNT1), including assessment of symptom response and elbow range of motion (ROM), and PPT measured over upper limb peripheral nerve trunks, the upper trapezius muscle and overlying cervical zygapophyseal joints. Subjects with a depressed scapular reported significantly greater pain intensity (t = 5.7, p < 0.0001) and reduced elbow extension ROM (t = -2.7, p < 0.01) during the ULNT1 compared to those with a normal scapular orientation. Regardless of the location tested, the group presenting with a depressed scapular had significantly lower PPT compared to those with a normal scapular orientation (PPT averaged across all sites: normal orientation: 3.3 ± 0.6 kg/cm(2), depressed scapular: 2.1 ± 0.5 kg/cm(2), p < 0.00001). Despite being asymptomatic, people with a depressed scapular have greater neck and upper limb neural tissue mechanosensitivity when compared to people with a normal scapular orientation. This study offers insight into the potential development of neck-arm pain due to a depressed scapular position. Copyright © 2017 Elsevier Ltd. All rights reserved.

  8. Neural outcome processing of peer-influenced risk-taking behavior in late adolescence: Preliminary evidence for gene × environment interactions.

    Science.gov (United States)

    Webber, Troy A; Soder, Heather E; Potts, Geoffrey F; Park, Jong Y; Bornovalova, Marina A

    2017-02-01

    Adolescent brains are particularly susceptible to the rewarding properties of risky decisions in social contexts. Individual differences in genetic influences on dopamine transmission moderate neural outcome processing of risky decisions and may exert pronounced effects on adolescent risk-taking behavior (RTB) and corresponding neural outcome processing in peer contexts, a process called gene-environment interaction (G × E). Eighty-five undergraduate students completed a behavioral risk task alone and in the presence of a confederate peer providing "risky" feedback. We tested for G × E effects using a polygenic risk index that included 3 candidate genetic variations associated with high dopamine transmission efficiency, as well as the moderating role of family history of behavioral disinhibition. Difference waves for the P300 and FRN (i.e., feedback-related negativity) were examined as indices of neural outcome processing. A G × E effect was observed for RTB and the P300, but not the FRN. Family history of behavioral disinhibition also interacted with peer influence to predict P300 amplitude. These data provide preliminary evidence for G × E for peer-influenced RTB and neural outcome processing during late adolescence. Genetic influences on dopaminergic function may be particularly relevant for attentional and motivational neural systems, as indexed by the P300, which exert downstream effects on peer-influenced RTB. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  9. The influence of cochlear traveling wave and neural adaptation on auditory brainstem responses

    DEFF Research Database (Denmark)

    Junius, D.; Dau, Torsten

    2005-01-01

    ), disparities occurred between the responses, reflecting a nonlinearity in the processing when neural activity is integrated across frequency. In the third experiment, the effect of within-train rate on wave-V response was investigated. The response to the chirp presented at a within-train rate of 95 Hz...... processing in the human auditory system. The findings might also be useful for the development of effective stimulation paradigms in clinical applications....

  10. Factors Influencing the Differentiation of Dopaminergic Traits in Transplanted Neural Stem Cells

    OpenAIRE

    Yang, Ming; Donaldson, Angela E.; Jiang, Yubao; Iacovitti, Lorraine

    2003-01-01

    Our previous studies demonstrated that when neural stem cells (NSCs) of the C17.2 clonal line are transplanted into the intact or 6-hydroxydopamine (6-OHDA) lesioned rat striatum, in most, but not all grafts, cells spontaneously express the dopamine (DA) biosynthetic enzymes, tyrosine hydroxylase (TH), and aromatic l-amino acid decarboxylase (Yang, M., Stull, N. D., Snyder, E. Y., Berk, M. A., and Iacovitti, L. (2002). Exp. Neurol.).These results suggested that there were certain conditions w...

  11. The influence of immunosuppressive drugs on neural stem/progenitor cell fate in vitro

    Energy Technology Data Exchange (ETDEWEB)

    Skardelly, Marco, E-mail: Marco.Skardelly@med.uni-tuebingen.de [Department of Neurosurgery, University Hospital, Leipzig (Germany); Translational Centre for Regenerative Medicine, University of Leipzig, Leipzig (Germany); Glien, Anja; Groba, Claudia; Schlichting, Nadine [Department of Neurosurgery, University Hospital, Leipzig (Germany); Kamprad, Manja [Institute of Clinical Immunology, Medical Faculty, University of Leipzig, Leipzig (Germany); Meixensberger, Juergen [Department of Neurosurgery, University Hospital, Leipzig (Germany); Milosevic, Javorina [Translational Centre for Regenerative Medicine, University of Leipzig, Leipzig (Germany)

    2013-12-10

    In allogenic and xenogenic transplantation, adequate immunosuppression plays a major role in graft survival, especially over the long term. The effect of immunosuppressive drugs on neural stem/progenitor cell fate has not been sufficiently explored. The focus of this study is to systematically investigate the effects of the following four different immunotherapeutic strategies on human neural progenitor cell survival/death, proliferation, metabolic activity, differentiation and migration in vitro: (1) cyclosporine A (CsA), a calcineurin inhibitor; (2) everolimus (RAD001), an mTOR-inhibitor; (3) mycophenolic acid (MPA, mycophenolate), an inhibitor of inosine monophosphate dehydrogenase and (4) prednisolone, a steroid. At the minimum effective concentration (MEC), we found a prominent decrease in hNPCs' proliferative capacity (BrdU incorporation), especially for CsA and MPA, and an alteration of the NAD(P)H-dependent metabolic activity. Cell death rate, neurogenesis, gliogenesis and cell migration remained mostly unaffected under these conditions for all four immunosuppressants, except for apoptotic cell death, which was significantly increased by MPA treatment. - Highlights: • Four immunosuppresants (ISs) were tested in human neural progenitor cells in vitro. • Cyclosporine A and mycophenolic acid showed a prominent anti-proliferative activity • Mycophenolic acid exhibited a significant pro-apoptotic effect. • NAD(P)H-dependent metabolic activity was occasionally induced by ISs. • Neuronal differentiation and migration potential remained unaffected by ISs treatment.

  12. Biological Constraints on Literacy Acquisition.

    Science.gov (United States)

    Cossu, Giuseppe

    1999-01-01

    Investigates some of the biological constraints that shape the process of literacy acquisition. Explores the possibility of isolating processing components of reading which correspond to computational units of equivalent size in the neural architecture. Suggests that the process of literacy acquisition is largely constrained by a specific…

  13. A Concept for Extending the Applicability of Constraint-Induced Movement Therapy through Motor Cortex Activity Feedback Using a Neural Prosthesis

    Directory of Open Access Journals (Sweden)

    Tomas E. Ward

    2007-01-01

    Full Text Available This paper describes a concept for the extension of constraint-induced movement therapy (CIMT through the use of feedback of primary motor cortex activity. CIMT requires residual movement to act as a source of feedback to the patient, thus preventing its application to those with no perceptible movement. It is proposed in this paper that it is possible to provide feedback of the motor cortex effort to the patient by measurement with near infrared spectroscopy (NIRS. Significant changes in such effort may be used to drive rehabilitative robotic actuators, for example. This may provide a possible avenue for extending CIMT to patients hitherto excluded as a result of severity of condition. In support of such a paradigm, this paper details the current status of CIMT and related attempts to extend rehabilitation therapy through the application of technology. An introduction to the relevant haemodynamics is given including a description of the basic technology behind a suitable NIRS system. An illustration of the proposed therapy is described using a simple NIRS system driving a robotic arm during simple upper-limb unilateral isometric contraction exercises with healthy subjects.

  14. Don't worry, be happy - Neural correlates of the influence of musically induced mood on self-evaluation.

    Science.gov (United States)

    Oetken, Sarah; Pauly, Katharina D; Gur, Ruben C; Schneider, Frank; Habel, Ute; Pohl, Anna

    2017-06-01

    Self-evaluation affects one's own mental state, social interactions and everyday life. Mood, in turn, has an impact on self-evaluation. However, the influence of mood on self-evaluation at the neural level has barely been examined. In this fMRI study, the interaction of mood and self-perception was investigated in 20 healthy participants. Happy, sad and neutral music was presented while participants were instructed to immerse themselves in the mood of the music and to rate how well presented traits characterized themselves. In a lexical control condition, subjects had to count a specific letter in the word. Behavioral data reflected successful mood induction. While self-ascription of positive traits was unaffected by mood, self-ascription of negative characteristics was decreased by negative affect. A positive correlation was found between self-worth scores and the difference in the amount of self-ascribed positive versus negative traits during negative mood induction. At the neural level, amygdalo-hippocampal, superior and middle temporal structures were differently involved in self-evaluation (vs. lexical processing) depending on the mood. While activation of the amygdalo-hippocampal complex was found during sad in comparison to both happy and neutral mood, superior/middle temporal gyrus (STG/MTG) activation was only found when contrasting sad vs. neutral mood. Further, a correlation analysis with self-worth ratings revealed a positive relation to STG activation during self-ascription of trait adjectives in sad compared to neutral mood. Our results underscore the importance of the current emotional state for self-evaluation and identify some neural correlates of this effect. Our findings in healthy research participants suggest a compensatory mechanism during sad mood induction to maintain a positive self-image, which is supported by activation of limbic and fronto-temporal cortex. Studies in clinically depressed populations could reveal whether this compensatory

  15. Neural correlates of informational cascades: brain mechanisms of social influence on belief updating.

    Science.gov (United States)

    Huber, Rafael E; Klucharev, Vasily; Rieskamp, Jörg

    2015-04-01

    Informational cascades can occur when rationally acting individuals decide independently of their private information and follow the decisions of preceding decision-makers. In the process of updating beliefs, differences in the weighting of private and publicly available social information may modulate the probability that a cascade starts in a decisive way. By using functional magnetic resonance imaging, we examined neural activity while participants updated their beliefs based on the decisions of two fictitious stock market traders and their own private information, which led to a final decision of buying one of two stocks. Computational modeling of the behavioral data showed that a majority of participants overweighted private information. Overweighting was negatively correlated with the probability of starting an informational cascade in trials especially prone to conformity. Belief updating by private information was related to activity in the inferior frontal gyrus/anterior insula, the dorsolateral prefrontal cortex and the parietal cortex; the more a participant overweighted private information, the higher the activity in the inferior frontal gyrus/anterior insula and the lower in the parietal-temporal cortex. This study explores the neural correlates of overweighting of private information, which underlies the tendency to start an informational cascade. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  16. Influence of perspective on the neural correlates of motor resonance during natural action observation.

    Science.gov (United States)

    Vingerhoets, Guy; Stevens, Lenny; Meesdom, Morgan; Honoré, Pieterjan; Vandemaele, Pieter; Achten, Eric

    2012-01-01

    We investigated the neural correlates of motor resonance during the observation of natural transitive actions and determined how the observer's perspective modulates the neural activation. Seventeen right-handed participants observed right and left hand tool grasping actions from a first-person or third-person perspective while undergoing fMRI. A two-factorial analysis of variance over the parietal region revealed no main effects of hand identity or perspective, but unveiled a hand by perspective interaction effect. The first-person perspective elicited parietal activation in the hemisphere contralateral to the performing hand as if the modelled action was mimicked with the same anatomical hand. In the third-person perspective, parietal activation ipsilateral to the modelled hand was found, indicating a specular strategy, rather than an anatomical imitation. Motor resonance was maximal in three foci in the superior parietal lobule and intraparietal sulcus that have been associated with prehensile actions. Our results suggest that therapeutic strategies aimed to elicit motor resonance, such as motor imagery and observational modelling, can adjust their spatial frame of reference according to the hemisphere they intend to stimulate.

  17. Neural Plastic Effects of Working Memory Training Influenced by Self-perceived Stress in Stroke: A Case Illustration.

    Science.gov (United States)

    Leung, Ada W S; Barrett, Lauren M; Butterworth, Darcy; Werther, Karin; Dawson, Deirdre R; Brintnell, E Sharon

    2016-01-01

    This case study examined the effects of auditory working memory (WM) training on neuroplastic changes in stroke survivors and how such effects might be influenced by self-perceived stress. Two participants with a history of stroke participated in the study. One of them had a higher level of self-perceived stress. Both participants underwent a course of auditory WM training and completed baseline and post-training assessments such as self-perceived stress, performance satisfaction questionnaires, behavioral task performance, and functional magnetic resonance imaging. They were trained on a computerized auditory WM task (n-back) 5 days a week for 6 weeks, for a total of 20 h. Participant 1 had high levels of perceived stress, both pre- and post-training, and showed improvement on the satisfaction aspect of functional engagement only. Participant 2 had lower levels of perceived stress and demonstrated improvements on all performance tasks. Neuroimaging results showed evidence of improved neural efficiency on the trained task for participant 2. The results shed light on the need to evaluate psychological influences, e.g., stress, when studying the neuroplastic changes in people with stroke. However, the case design approach and other factors that might have positively influenced outcomes mean that these results must be interpreted with a great deal of caution. Future studies using a larger sample are recommended to verify the findings.

  18. Neural plastic effects of working memory training influenced by self-perceived stress in stroke: A case illustration

    Directory of Open Access Journals (Sweden)

    Ada W.S. Leung

    2016-08-01

    Full Text Available This case study examined the effects of auditory working memory (WM training on neuroplastic changes in stroke survivors and how such effects might be influenced by self-perceived stress. Two participants with a history of stroke participated in the study. One of them had a higher level of self-perceived stress. Both participants underwent a course of auditory WM training and completed baseline and post-training assessments such as self-perceived stress, performance satisfaction questionnaires, behavioral task performance, and functional magnetic resonance imaging. They were trained on a computerized auditory WM task (n-back five days a week for six weeks, for a total of 20 hours. Participant 1 had high levels of perceived stress, both pre- and post-training, and showed improvement on the satisfaction aspect of functional engagement only. Participant 2 had lower levels of perceived stress and demonstrated improvements on all performance tasks. Neuroimaging results showed evidence of improved neural efficiency on the trained task for participant 2. The results shed light on the need to evaluate psychological influences, e.g., stress, when studying the neuroplastic changes in people with stroke. However, the case design approach and other factors that might have positively influenced outcomes mean that these results must be interpreted with a great deal of caution. Future studies using a larger sample are recommended to verify the findings.

  19. Neural computations underpinning the strategic management of influence in advice giving.

    Science.gov (United States)

    Hertz, Uri; Palminteri, Stefano; Brunetti, Silvia; Olesen, Cecilie; Frith, Chris D; Bahrami, Bahador

    2017-12-19

    Research on social influence has focused mainly on the target of influence (e.g., consumer and voter); thus, the cognitive and neurobiological underpinnings of the source of the influence (e.g., politicians and salesmen) remain unknown. Here, in a three-sided advice-giving game, two advisers competed to influence a client by modulating their own confidence in their advice about which lottery the client should choose. We report that advisers' strategy depends on their level of influence on the client and their merit relative to one another. Moreover, blood-oxygenation-level-dependent (BOLD) signal in the temporo-parietal junction is modulated by adviser's current level of influence on the client, and relative merit prediction error affects activity in medial-prefrontal cortex. Both types of social information modulate ventral striatum response. By demonstrating what happens in our mind and brain when we try to influence others, these results begin to explain the biological mechanisms that shape inter-individual differences in social conduct.

  20. Neural correlates of prosocial peer influence on public goods game donations during adolescence

    National Research Council Canada - National Science Library

    Van Hoorn, Jorien; Van Dijk, Eric; Güroğlu, Berna; Crone, Eveline A

    2016-01-01

    ... peer influence on donation decisions in adolescence. Participants (age 12-16 years; N = 61) made decisions in anonymous groups about the allocation of tokens between themselves and the group in a public goods game...

  1. The influence of the dwell time deviation constraint (DTDC) parameter on dosimetry with IPSA optimisation for HDR prostate brachytherapy.

    Science.gov (United States)

    Smith, Ryan L; Panettieri, Vanessa; Lancaster, Craig; Mason, Natasha; Franich, Rick D; Millar, Jeremy L

    2015-03-01

    To investigate how the dwell time deviation constraint (DTDC) parameter, applied to inverse planning by simulated annealing (IPSA) optimisation limits large dwell times from occurring in each catheter and to characterise the effect on the resulting dosimetry for prostate high dose rate (HDR) brachytherapy treatment plans. An unconstrained IPSA optimised treatment plan, using the Oncentra Brachytherapy treatment planning system (version 4.3, Nucletron an Elekta company, Elekta AB, Stockholm, Sweden), was generated for 20 consecutive HDR prostate brachytherapy patients, with the DTDC set to zero. Successive constrained optimisation plans were also created for each patient by increasing the DTDC parameter by 0.2, up to a maximum value of 1.0. We defined a "plan modulation index", to characterise the change of dwell time modulation as the DTDC parameter was increased. We calculated the dose volume histogram indices for the PTV (D90, V100, V150, V200%) and urethra (D10%) to characterise the effect on the resulting dosimetry. The average PTV D90% decreases as the DTDC is applied, on average by only 1.5 %, for a DTDC = 0.4. The measures of high dose regions in the PTV, V150 and V200%, increase on average by less than 5 and 2 % respectively. The net effect of DTDC on the modulation of dwell times has been characterised by the introduction of the plan modulation index. DTDC applied during IPSA optimisation of HDR prostate brachytherapy plans reduce the occurrence of large isolated dwell times within individual catheters. The mechanism by which DTDC works has been described and its effect on the modulation of dwell times has been characterised. The authors recommend using a DTDC parameter no greater than 0.4 to obtain a plan with dwell time modulation comparable to a geometric optimised plan. This yielded on average a 1.5 % decrease in PTV coverage and an acceptable increase in V150%, without compromising the urethral dose.

  2. The integration of social influence and reward: Computational approaches and neural evidence.

    Science.gov (United States)

    Tomlin, Damon; Nedic, Andrea; Prentice, Deborah A; Holmes, Philip; Cohen, Jonathan D

    2017-05-24

    Decades of research have established that decision-making is dramatically impacted by both the rewards an individual receives and the behavior of others. How do these distinct influences exert their influence on an individual's actions, and can the resulting behavior be effectively captured in a computational model? To address this question, we employed a novel spatial foraging game in which groups of three participants sought to find the most rewarding location in an unfamiliar two-dimensional space. As the game transitioned from one block to the next, the availability of information regarding other group members was varied systematically, revealing the relative impacts of feedback from the environment and information from other group members on individual decision-making. Both reward-based and socially-based sources of information exerted a significant influence on behavior, and a computational model incorporating these effects was able to recapitulate several key trends in the behavioral data. In addition, our findings suggest how these sources were processed and combined during decision-making. Analysis of reaction time, location of gaze, and functional magnetic resonance imaging (fMRI) data indicated that these distinct sources of information were integrated simultaneously for each decision, rather than exerting their influence in a separate, all-or-none fashion across separate subsets of trials. These findings add to our understanding of how the separate influences of reward from the environment and information derived from other social agents are combined to produce decisions.

  3. Attribution of intentional causation influences the perception of observed movements: Behavioural evidence and neural correlates

    Directory of Open Access Journals (Sweden)

    James W Moore

    2013-01-01

    Full Text Available Recent research on human agency suggests that intentional causation is associated with a subjective compression in the temporal interval between actions and their effects. That is, intentional movements and their causal effects are perceived as closer together in time than equivalent unintentional movements and their causal effects. This so-called intentional binding effect is consistently found for one’s own self-generated actions. It has also been suggested that intentional binding occurs when observing intentional movements of others. However, this evidence is undermined by limitations of the paradigm used. In the current study we aimed to overcome these limitations using a more rigorous design in combination with functional Magnetic Resonance Imaging (fMRI to explore the neural underpinnings of intentional binding of observed movements. In particular, we aimed to identify brain areas sensitive to the interaction between intentionality and causality attributed to the observed action. Our behavioural results confirmed the occurrence of intentional binding for observed movements using this more rigorous paradigm. Our fMRI results highlighted a collection of brain regions whose activity was sensitive to the interaction between intentionality and causation. Intriguingly, these brain regions have previously been implicated in the sense of agency over one’s own movements. We discuss the implications of these results for intentional binding specifically, and the sense of agency more generally.

  4. Risk-taking and social exclusion in adolescence: neural mechanisms underlying peer influences on decision-making.

    Science.gov (United States)

    Peake, Shannon J; Dishion, Thomas J; Stormshak, Elizabeth A; Moore, William E; Pfeifer, Jennifer H

    2013-11-15

    Social exclusion and risk-taking are both common experiences of concern in adolescence, yet little is known about how the two may be related at behavioral or neural levels. In this fMRI study, adolescents (N=27, 14 male, 14-17years-old) completed a series of tasks in the scanner assessing risky decision-making before and after an episode of social exclusion. In this particular context, exclusion was associated with greater behavioral risk-taking among adolescents with low self-reported resistance to peer influence (RPI). When making risky decisions after social exclusion, adolescents who had lower RPI exhibited higher levels of activity in the right temporoparietal junction (rTPJ), and this response in rTPJ was a significant mediator of the relationship between RPI and greater risk-taking after social exclusion. Lower RPI was also associated with lower levels of activity in lPFC during crashes following social exclusion, but unlike rTPJ this response in lPFC was not a significant mediator of the relationship between RPI and greater risk-taking after social exclusion. The results suggest that mentalizing and/or attentional mechanisms have a unique direct effect on adolescents' vulnerability to peer influence on risk-taking. Copyright © 2013 Elsevier Inc. All rights reserved.

  5. Developmental influences on the neural bases of responses to social rejection: implications of social neuroscience for education.

    Science.gov (United States)

    Sebastian, Catherine L; Tan, Geoffrey C Y; Roiser, Jonathan P; Viding, Essi; Dumontheil, Iroise; Blakemore, Sarah-Jayne

    2011-08-01

    Relational aggression such as social rejection is common within school peer groups. Converging evidence suggests that adolescent females are particularly sensitive to social rejection. We used a novel fMRI adaptation of the Cyberball social rejection paradigm to investigate the neural response to social rejection in 19 mid-adolescent (aged 14-16) and 16 adult female participants. Across all participants, social exclusion (relative to inclusion) elicited a response in bilateral medial prefrontal cortex (mPFC) extending into ventral and subgenual anterior cingulate cortex and medial orbitofrontal cortex; and the left ventrolateral PFC (vlPFC); regions that have been associated in previous studies with social evaluation, negative affective processing, and affect regulation respectively. However, the exclusion-related response in right vlPFC, a region associated in previous studies with the regulation of rejection-related distress, was attenuated in adolescents. Within mPFC, greater activation during exclusion vs. inclusion was associated with greater self-reported susceptibility to peer influence in adolescents but not in adults. This suggests that the brain's response to experimentally-induced social rejection relates to adolescent behaviour in real-world social interactions. We speculate about the potential implications of these findings for educational settings. In particular, functional development of affective circuitry during adolescence may influence social interaction within the school peer group. Copyright © 2010 Elsevier Inc. All rights reserved.

  6. How arousal influences neural competition: What dual competition does not explain.

    Science.gov (United States)

    Greening, Steven G; Mather, Mara

    2015-01-01

    We argue that although the "dual competition" model is useful when considering interactions between emotional and neutral stimuli, it fails to account for the influence of emotional arousal on perceptual or goal-directed behavior involving neutral stimuli. We present the "arousal-biased competition" framework as an alternative that accounts for both scenarios.

  7. Early influence of the rs4675690 on the neural substrates of sadness.

    Science.gov (United States)

    Fortier, Emilie; Noreau, Anne; Lepore, Franco; Boivin, Michel; Pérusse, Daniel; Rouleau, Guy A; Beauregard, Mario

    2011-12-01

    CREB1 has previously been implicated in mood disorders, suicide, and antidepressant response. There is some evidence that the T allele in rs4675690, a single-nucleotide polymorphism near the CREB1 gene, is involved in the modulation of neural responses to negative stimuli. It is not known whether differential brain activity during negative mood state appears early in life in T allele carriers. Functional magnetic resonance imaging (fMRI) was used to measure brain activity, during a transient state of sadness, in children homozygous for the T allele or the C allele. This primary emotion was selected given that it is the prevailing mood in major depressive disorder (MDD). Blood-oxygen-level dependent (BOLD) signal changes were measured while subjects viewed blocks of neutral film excerpts and blocks of sad film excerpts. There was significantly greater BOLD activation in the TT group, compared to the CC group, in the right dorsal anterior cingulate cortex (Brodmann area [BA 24]), right putamen, right caudate nucleus and left anterior temporal pole (BA 21), when the brain activity associated with the viewing of the emotionally neutral film excerpts was subtracted from that associated with the viewing of the sad film excerpts. A replication study using larger samples may be required for more definitive conclusions. The different pattern of regional brain activation found here during transient sadness - in children carrying the T allele, compared to those carrying the C allele - might increase later in life susceptibility to emotional dysregulation and depressive symptoms. Copyright © 2011 Elsevier B.V. All rights reserved.

  8. Variety identification of wheat using mass spectrometry with neural networks and the influence of mass spectra processing prior to neural network analysis

    DEFF Research Database (Denmark)

    Sørensen, Helle Aagaard; Sperotto, Maria Maddalena; Petersen, M.

    2002-01-01

    The performance of matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry with neural networks in wheat variety classification is further evaluated.(1) Two principal issues were studied: (a) the number of varieties that could be classified correctly; and (b) various means...

  9. Imaging Posture Veils Neural Signals

    Directory of Open Access Journals (Sweden)

    Robert T Thibault

    2016-10-01

    Full Text Available Whereas modern brain imaging often demands holding body positions incongruent with everyday life, posture governs both neural activity and cognitive performance. Humans commonly perform while upright; yet, many neuroimaging methodologies require participants to remain motionless and adhere to non-ecological comportments within a confined space. This inconsistency between ecological postures and imaging constraints undermines the transferability and generalizability of many a neuroimaging assay.Here we highlight the influence of posture on brain function and behavior. Specifically, we challenge the tacit assumption that brain processes and cognitive performance are comparable across a spectrum of positions. We provide an integrative synthesis regarding the increasingly prominent influence of imaging postures on autonomic function, mental capacity, sensory thresholds, and neural activity. Arguing that neuroimagers and cognitive scientists could benefit from considering the influence posture wields on both general functioning and brain activity, we examine existing imaging technologies and the potential of portable and versatile imaging devices (e.g., functional near infrared spectroscopy. Finally, we discuss ways that accounting for posture may help unveil the complex brain processes of everyday cognition.

  10. Observational Constraints on Terpene Oxidation with and without Anthropogenic Influence in the Amazon using Speciated Measurements from SV-TAG

    Science.gov (United States)

    Yee, L.; Isaacman, G. A.; Kreisberg, N. M.; Liu, Y.; McKinney, K. A.; de Sá, S. S.; Martin, S. T.; Alexander, M. L.; Palm, B. B.; Hu, W.; Campuzano Jost, P.; Day, D. A.; Jimenez, J. L.; Viegas, J.; Springston, S. R.; Wurm, F.; Ferreira De Brito, J.; Artaxo, P.; Manzi, A. O.; Machado, L.; Longo, K.; Oliveira, M. B.; Souza, R. A. F. D.; Hering, S. V.; Goldstein, A. H.

    2014-12-01

    Biogenic volatile organic compounds (BVOCs) from the Amazon forest represent the largest regional source of organic carbon emissions to the atmosphere. These BVOC emissions dominantly consist of volatile and semi-volatile terpenoid compounds that undergo chemical transformations in the atmosphere to form oxygenated condensable gases and secondary organic aerosol (SOA). However, the oxidation pathways of these compounds are still not well understood, and are expected to differ significantly between "pristine" conditions, as is common in Amazonia, and polluted conditions caused by emissions from growing cities. Our focus is to elucidate how anthropogenic emissions influence BVOC chemistry and BSOA formation through speciated measurements of their oxidation products. We have deployed the Semi-Volatile Thermal desorption Aerosol Gas Chromatograph (SV-TAG) at the rural T3 site located west of the urban center of Manaus, Brazil as part of the Green Ocean Amazon (GoAmazon) 2014 field campaign to measure hourly concentrations of semi-volatile BVOCs and their oxidation products during the wet and dry seasons. Primary BVOC concentrations measured by the SV-TAG include sesquiterpenes and diterpenes, which have rarely been speciated with high time-resolution. We observe sesquiterpenes to be anti-correlated with ozone, indicative of sesquiterpene oxidation playing a major role in the regional oxidant budget. The role of sesquiterpenes in atmospheric SOA formation are of interest due to their high aerosol yields and high reactivity with ozone, relative to more commonly measured BVOCs (e.g. monoterpenes). We explore relative concentrations of sesquiterpenes and monoterpenes and their roles as precursors to SOA formation by combining SV-TAG measurements with those from an additional suite of VOC and particle measurements deployed in the Amazon. We also report the first ever hourly observations of the gas-particle partitioning of speciated terpene oxidation products in the Amazon

  11. Influences of social reward experience on behavioral responses to drugs of abuse: Review of shared and divergent neural plasticity mechanisms for sexual reward and drugs of abuse.

    Science.gov (United States)

    Beloate, Lauren N; Coolen, Lique M

    2017-12-01

    Different factors influence the development of drug addiction in humans, including social reward experiences. In animals, experience with social rewards, such as sexual behavior, pair bonding, social and environmental enrichment, can be protective. However, loss or lack of social rewards can lead to a vulnerability to drug-seeking behavior. The effects of social reward experience on drug-seeking behavior are associated with changes in the neural pathways that control drug-related behavior. This review will provide an introduction and overview of the mesolimbic pathway and the influence of social reward experience on drug-seeking behavior in rodents. Moreover, the research from our laboratory on effects of sexual experience and loss of sex reward on psychostimulant and opiate reward will be reviewed. Finally, we will review current knowledge of the neural mechanisms that underlie these interactions. Investigations of the neural underpinnings by which social and drug rewards interact contribute to improved understanding of the neural basis of vulnerability for drug addiction and reward-related behaviors in general. Copyright © 2017 Elsevier Ltd. All rights reserved.

  12. Peak Torque and Rate of Torque Development Influence on Repeated Maximal Exercise Performance: Contractile and Neural Contributions

    Science.gov (United States)

    Morel, Baptiste; Rouffet, David M.; Saboul, Damien; Rota, Samuel; Clémençon, Michel; Hautier, Christophe A.

    2015-01-01

    Rapid force production is critical to improve performance and prevent injuries. However, changes in rate of force/torque development caused by the repetition of maximal contractions have received little attention. The aim of this study was to determine the relative influence of rate of torque development (RTD) and peak torque (Tpeak) on the overall performance (i.e. mean torque, Tmean) decrease during repeated maximal contractions and to investigate the contribution of contractile and neural mechanisms to the alteration of the various mechanical variables. Eleven well-trained men performed 20 sets of 6-s isokinetic maximal knee extensions at 240°·s-1, beginning every 30 seconds. RTD, Tpeak and Tmean as well as the Rate of EMG Rise (RER), peak EMG (EMGpeak) and mean EMG (EMGmean) of the vastus lateralis were monitored for each contraction. A wavelet transform was also performed on raw EMG signal for instant mean frequency (ifmean) calculation. A neuromuscular testing procedure was carried out before and immediately after the fatiguing protocol including evoked RTD (eRTD) and maximal evoked torque (eTpeak) induced by high frequency doublet (100 Hz). Tmean decrease was correlated to RTD and Tpeak decrease (R²=0.62; pmuscle in the first milliseconds of the contraction. PMID:25901576

  13. Influence of alcohol use and family history of alcoholism on neural response to alcohol cues in college drinkers.

    Science.gov (United States)

    Dager, Alecia D; Anderson, Beth M; Stevens, Michael C; Pulido, Carmen; Rosen, Rivkah; Jiantonio-Kelly, Rachel E; Sisante, Jason-Flor; Raskin, Sarah A; Tennen, Howard; Austad, Carol S; Wood, Rebecca M; Fallahi, Carolyn R; Pearlson, Godfrey D

    2013-01-01

    Heavy drinkers show altered functional magnetic resonance imaging (fMRI) response to alcohol cues. Little is known about alcohol cue reactivity among college age drinkers, who show the greatest rates of alcohol use disorders. Family history of alcoholism (family history positive [FHP]) is a risk factor for problematic drinking, but the impact on alcohol cue reactivity is unclear. We investigated the influence of heavy drinking and family history of alcoholism on alcohol cue-related fMRI response among college students. Participants were 19 family history negative (FHN) light drinkers, 11 FHP light drinkers, 25 FHN heavy drinkers, and 10 FHP heavy drinkers, aged 18 to 21. During fMRI scanning, participants viewed alcohol images, nonalcohol beverage images, and degraded control images, with each beverage image presented twice. We characterized blood oxygen level-dependent (BOLD) contrast for alcohol versus nonalcohol images and examined BOLD response to repeated alcohol images to understand exposure effects. Heavy drinkers exhibited greater BOLD response than light drinkers in posterior visual association regions, anterior cingulate, medial frontal cortex, hippocampus, amygdala, and dorsal striatum, and hyperactivation to repeated alcohol images in temporo-parietal, frontal, and insular regions (clusters > 8,127 μl, p alcohol images in temporo-parietal regions, fusiform, and hippocampus. There were no interactions between family history and drinking group. Our results parallel findings of hyperactivation to alcohol cues among heavy drinkers in regions subserving visual attention, memory, motivation, and habit. Heavy drinkers demonstrated heightened activation to repeated alcohol images, which could influence continued drinking. Family history of alcoholism was associated with greater response to repeated alcohol images in regions underlying visual attention, recognition, and encoding, which could suggest aspects of alcohol cue reactivity that are independent of

  14. Creativity from Constraints in Engineering Design

    DEFF Research Database (Denmark)

    Onarheim, Balder

    2012-01-01

    This paper investigates the role of constraints in limiting and enhancing creativity in engineering design. Based on a review of literature relating constraints to creativity, the paper presents a longitudinal participatory study from Coloplast A/S, a major international producer of disposable...... medical equipment. At Coloplast, constraints played a fundamental role and the observations show the important, dual role of constraints in terms of being a limitation and a prerequisite for creativity. Too few or too many constraints had a negative impact on creativity, whereas the formulation, rationale...... and ownership of formal constraints played a crucial role in defining their influence on creativity – along with the tacit constraints held by the designers. The designers were found to be highly constraint focused, and four main creative strategies for constraint manipulation were observed: blackboxing...

  15. A multimedia constraint system

    NARCIS (Netherlands)

    J.E.A. van Hintum; G.J. Reynolds

    1995-01-01

    textabstractThe MADE constraint system provides excellent opportunities to introduce constraints in a multimedia application. Multimedia applications are not only a good place to experiment with constraint systems; constraints in a multimedia environment are almost indispensable. Due to the

  16. Differences in task demands influence the hemispheric lateralization and neural correlates of metaphor.

    Science.gov (United States)

    Yang, Fanpei Gloria; Edens, Jennifer; Simpson, Claire; Krawczyk, Daniel C

    2009-11-01

    This study investigated metaphor comprehension in the broader context of task-difference effects and manipulation of processing difficulty. We predicted that right hemisphere recruitment would show greater specificity to processing difficulty rather than metaphor comprehension. Previous metaphor processing studies have established that the left inferior frontal gyrus strongly correlates with metaphor comprehension but there has been controversy about whether right hemisphere (RH) involvement is specific for metaphor comprehension. Functional MRI data were recorded from healthy subjects who read novel metaphors, conventional metaphors, definition-like sentences, or literal sentences. We investigated metaphor processing in contexts where semantic judgment or imagery modulates linguistic judgment. Our findings support the position that the type of task rather than figurative language processing per se modulates the left inferior gyrus (LIFG). RH involvement was more influenced by processing difficulty and less by the novelty or figurativity of linguistic expressions. Our results suggest that figurative language processing depends upon the effects of task-type and processing difficulty on imaging results.

  17. Body Position Influences Which Neural Structures Are Recruited by Lumbar Transcutaneous Spinal Cord Stimulation.

    Directory of Open Access Journals (Sweden)

    Simon M Danner

    Full Text Available Transcutaneous stimulation of the human lumbosacral spinal cord is used to evoke spinal reflexes and to neuromodulate altered sensorimotor function following spinal cord injury. Both applications require the reliable stimulation of afferent posterior root fibers. Yet under certain circumstances, efferent anterior root fibers can be co-activated. We hypothesized that body position influences the preferential stimulation of sensory or motor fibers. Stimulus-triggered responses to transcutaneous spinal cord stimulation were recorded using surface-electromyography from quadriceps, hamstrings, tibialis anterior, and triceps surae muscles in 10 individuals with intact nervous systems in the supine, standing and prone positions. Single and paired (30-ms inter-stimulus intervals biphasic stimulation pulses were applied through surface electrodes placed on the skin between the T11 and T12 inter-spinous processes referenced to electrodes on the abdomen. The paired stimulation was applied to evaluate the origin of the evoked electromyographic response; trans-synaptic responses would be suppressed whereas direct efferent responses would almost retain their amplitude. We found that responses to the second stimulus were decreased to 14%±5% of the amplitude of the response to the initial pulse in the supine position across muscles, to 30%±5% in the standing, and to only 80%±5% in the prone position. Response thresholds were lowest during standing and highest in the prone position and response amplitudes were largest in the supine and smallest in the prone position. The responses obtained in the supine and standing positions likely resulted from selective stimulation of sensory fibers while concomitant motor-fiber stimulation occurred in the prone position. We assume that changes of root-fiber paths within the generated electric field when in the prone position increase the stimulation thresholds of posterior above those of anterior root fibers. Thus, we

  18. Body Position Influences Which Neural Structures Are Recruited by Lumbar Transcutaneous Spinal Cord Stimulation.

    Science.gov (United States)

    Danner, Simon M; Krenn, Matthias; Hofstoetter, Ursula S; Toth, Andrea; Mayr, Winfried; Minassian, Karen

    2016-01-01

    Transcutaneous stimulation of the human lumbosacral spinal cord is used to evoke spinal reflexes and to neuromodulate altered sensorimotor function following spinal cord injury. Both applications require the reliable stimulation of afferent posterior root fibers. Yet under certain circumstances, efferent anterior root fibers can be co-activated. We hypothesized that body position influences the preferential stimulation of sensory or motor fibers. Stimulus-triggered responses to transcutaneous spinal cord stimulation were recorded using surface-electromyography from quadriceps, hamstrings, tibialis anterior, and triceps surae muscles in 10 individuals with intact nervous systems in the supine, standing and prone positions. Single and paired (30-ms inter-stimulus intervals) biphasic stimulation pulses were applied through surface electrodes placed on the skin between the T11 and T12 inter-spinous processes referenced to electrodes on the abdomen. The paired stimulation was applied to evaluate the origin of the evoked electromyographic response; trans-synaptic responses would be suppressed whereas direct efferent responses would almost retain their amplitude. We found that responses to the second stimulus were decreased to 14%±5% of the amplitude of the response to the initial pulse in the supine position across muscles, to 30%±5% in the standing, and to only 80%±5% in the prone position. Response thresholds were lowest during standing and highest in the prone position and response amplitudes were largest in the supine and smallest in the prone position. The responses obtained in the supine and standing positions likely resulted from selective stimulation of sensory fibers while concomitant motor-fiber stimulation occurred in the prone position. We assume that changes of root-fiber paths within the generated electric field when in the prone position increase the stimulation thresholds of posterior above those of anterior root fibers. Thus, we recommend conducting

  19. The influence of semantic and syntactic context constraints on lexical selection and integration in spoken-word comprehension as revealed by ERPs.

    Science.gov (United States)

    van den Brink, Daniëlle; Hagoort, Peter

    2004-01-01

    An event-related brain potential experiment was carried out to investigate the influence of semantic and syntactic context constraints on lexical selection and integration in spoken-word comprehension. Subjects were presented with constraining spoken sentences that contained a critical word that was either (a) congruent, (b) semantically and syntactically incongruent, but beginning with the same initial phonemes as the congruent critical word, or (c) semantically and syntactically incongruent, beginning with phonemes that differed from the congruent critical word. Relative to the congruent condition, an N200 effect reflecting difficulty in the lexical selection process was obtained in the semantically and syntactically incongruent condition where word onset differed from that of the congruent critical word. Both incongruent conditions elicited a large N400 followed by a left anterior negativity (LAN) time-locked to the moment of word category violation and a P600 effect. These results would best fit within a cascaded model of spoken-word processing, proclaiming an optimal use of contextual information during spoken-word identification by allowing for semantic and syntactic processing to take place in parallel after bottom-up activation of a set of candidates, and lexical integration to proceed with a limited number of candidates that still match the acoustic input.

  20. The Influence of Genre Constraints on Author Representation in Medical Research Articles. The French Indefinite Pronoun On in IMRAD Research Articles

    Directory of Open Access Journals (Sweden)

    Anje Müller Gjesdal

    2013-07-01

    Full Text Available Scientific discourse is characterized by highly normative and strict genre constraints on language use, both on the macro (text and micro (word level. The purpose of this article is to study the distribution of the French indefinite pronoun on and its interpretative values across the sections of French-language medical articles (KIAP corpus in the IMRAD format (Introduction, Methods, Results and Discussion. The main hypothesis is that the IMRAD structure entails a specific distribution of macro level textual structures (author roles, argumentation, rhetorical functions, and that this is reflected in the distribution of micro level linguistic markers, such as the pronoun on. Previous studies based on a more limited material (Gjesdal, 2008 indicate that the variation in the interpretative values of on seems to be influenced by the IMRAD format, and, furthermore, that the different values seem to correspond to different author roles. Particular emphasis will be put on the influence of the linear sequencing of text imposed by the IMRAD format and the distribution of author roles and speech acts across the text.Le discours scientifique se caractérise par des contraintes rigoureuses sur la production linguistique au niveau micro-linguistique (mot aussi bien qu’au niveau macro-linguistique (texte. Cet article a pour objectif d’étudier la distribution du pronom on et ses valeurs interprétatives à travers les sections d’articles médicaux sous le format IMRAD (Introduction, Methods, Results and Discussion dans un corpus d’articles médicaux (le corpus KIAP. L’hypothèse principale est que la structure IMRAD impose une distribution spécifique de structures textuelles (rôles d’auteur, argumentation, fonctions rhétoriques qui sera à son tour reflétée dans la distribution des marqueurs micro-linguistiques comme le pronom on.

  1. On Constraints in Assembly Planning

    Energy Technology Data Exchange (ETDEWEB)

    Calton, T.L.; Jones, R.E.; Wilson, R.H.

    1998-12-17

    Constraints on assembly plans vary depending on product, assembly facility, assembly volume, and many other factors. Assembly costs and other measures to optimize vary just as widely. To be effective, computer-aided assembly planning systems must allow users to express the plan selection criteria that appIy to their products and production environments. We begin this article by surveying the types of user criteria, both constraints and quality measures, that have been accepted by assembly planning systems to date. The survey is organized along several dimensions, including strategic vs. tactical criteria; manufacturing requirements VS. requirements of the automated planning process itself and the information needed to assess compliance with each criterion. The latter strongly influences the efficiency of planning. We then focus on constraints. We describe a framework to support a wide variety of user constraints for intuitive and efficient assembly planning. Our framework expresses all constraints on a sequencing level, specifying orders and conditions on part mating operations in a number of ways. Constraints are implemented as simple procedures that either accept or reject assembly operations proposed by the planner. For efficiency, some constraints are supplemented with special-purpose modifications to the planner's algorithms. Fast replanning enables an interactive plan-view-constrain-replan cycle that aids in constraint discovery and documentation. We describe an implementation of the framework in a computer-aided assembly planning system and experiments applying the system to a number of complex assemblies, including one with 472 parts.

  2. Influence of the Training Set Value on the Quality of the Neural Network to Identify Selected Moulding Sand Properties

    National Research Council Canada - National Science Library

    J. Jakubski; St. M. Dobosz; K. Major-Gabryś

    2013-01-01

    .... This paper presents the next part of the study on usefulness of artificial neural networks to support rebonding of green moulding sand, using chosen properties of moulding sands, which can be determined fast...

  3. Influences of hand dominance on the maintenance of benefits after home-based modified constraint-induced movement therapy in individuals with stroke

    Directory of Open Access Journals (Sweden)

    Renata C. M. Lima

    2014-10-01

    Full Text Available Objective: To investigate the influence of hand dominance on the maintenance of gains after home-based modified constraint-induced movement therapy (mCIMT. Method: Aprevious randomized controlled trial was conducted to examine the addition of trunk restraint to the mCIMT. Twenty-two chronic stroke survivors with mild to moderate motor impairments received individual home-based mCIMT with or without trunk restraints, five times per week, three hours daily over two weeks. In this study, the participants were separated into dominant group, which had their paretic upper limb as dominant before the stroke (n=8, and non-dominant group (n=14 for analyses. The ability to perform unimanual tasks was measured by the Wolf Motor Function Test (WMFT and the Motor Activity Log (MAL, whereas the capacity to perform bimanual tasks was measured using the Bilateral Activity Assessment Scale (BAAS. Results: Analysis revealed significant positive effects on the MAL amount of use and quality of the movement scales, as well as on the BAAS scores after intervention, with no differences between groups. Both groups maintained the bimanual improvements during follow-ups (BAAS-seconds 0.1, 95% CI -10.0 to 10.0, however only the dominant group maintained the unilateral improvements (MAL-amount of use: 1.5, 95% CI 0.7 to 2.3; MAL-quality: 1.3, 95% CI 0.5 to 2.1. Conclusions: Upper limb dominance did not interfere with the acquisition of upper limb skills after mCIMT. However, the participants whose paretic upper limb was dominant demonstrated better abilities to maintain the unilateral gains. The bilateral improvements were maintained, regardless of upper limb dominance.

  4. What Is Neural Plasticity?

    Science.gov (United States)

    von Bernhardi, Rommy; Bernhardi, Laura Eugenín-von; Eugenín, Jaime

    2017-01-01

    "Neural plasticity" refers to the capacity of the nervous system to modify itself, functionally and structurally, in response to experience and injury. As the various chapters in this volume show, plasticity is a key component of neural development and normal functioning of the nervous system, as well as a response to the changing environment, aging, or pathological insult. This chapter discusses how plasticity is necessary not only for neural networks to acquire new functional properties, but also for them to remain robust and stable. The article also reviews the seminal proposals developed over the years that have driven experiments and strongly influenced concepts of neural plasticity.

  5. The power of the “like” in adolescence: Effects of peer influence on neural and behavioral responses to social media

    Science.gov (United States)

    Sherman, Lauren E.; Payton, Ashley A.; Hernandez, Leanna M.; Greenfield, Patricia M.; Dapretto, Mirella

    2016-01-01

    We investigated a unique way in which adolescent peer influence occurs on social media. We developed a novel fMRI paradigm to simulate the popular social photo-sharing tool Instagram, and measured adolescents’ behavioral and neural responses to “Likes,” a quantifiable form of social endorsement and potential source of peer influence. Adolescents underwent fMRI while viewing photographs ostensibly submitted to Instagram. Adolescents were more likely to Like photos depicted with many Likes and refrain from Liking photos with few Likes – indicating the influence of virtual peer endorsement, a finding that held for both neutral photos and photos of risky behaviors (e.g., drinking, smoking). Viewing photographs with many (vs. few) Likes was associated with greater activity in neural regions implicated in reward processing, social cognition, imitation, and attention. Furthermore, when adolescents viewed risky (vs. non-risky) photographs, activation in the cognitive control network decreased. These findings highlight possible mechanisms underlying peer influence during adolescence. PMID:27247125

  6. Soft Concurrent Constraint Programming

    OpenAIRE

    Bistarelli, S.; Montanari, U.; Rossi, F.

    2002-01-01

    Soft constraints extend classical constraints to represent multiple consistency levels, and thus provide a way to express preferences, fuzziness, and uncertainty. While there are many soft constraint solving formalisms, even distributed ones, by now there seems to be no concurrent programming framework where soft constraints can be handled. In this paper we show how the classical concurrent constraint (cc) programming framework can work with soft constraints, and we also propose an extension ...

  7. A neurodynamic approach to convex optimization problems with general constraint.

    Science.gov (United States)

    Qin, Sitian; Liu, Yadong; Xue, Xiaoping; Wang, Fuqiang

    2016-12-01

    This paper presents a neurodynamic approach with a recurrent neural network for solving convex optimization problems with general constraint. It is proved that for any initial point, the state of the proposed neural network reaches the constraint set in finite time, and converges to an optimal solution of the convex optimization problem finally. In contrast to the existing related neural networks, the convergence rate of the state of the proposed neural network can be calculated quantitatively via the Łojasiewicz exponent under some mild assumptions. As applications, we estimate explicitly some Łojasiewicz exponents to show the convergence rate of the state of the proposed neural network for solving convex quadratic optimization problems. And some numerical examples are given to demonstrate the effectiveness of the proposed neural network. Copyright © 2016 Elsevier Ltd. All rights reserved.

  8. Stochastic Constraint Programming

    OpenAIRE

    Walsh, Toby

    2009-01-01

    To model combinatorial decision problems involving uncertainty and probability, we introduce stochastic constraint programming. Stochastic constraint programs contain both decision variables (which we can set) and stochastic variables (which follow a probability distribution). They combine together the best features of traditional constraint satisfaction, stochastic integer programming, and stochastic satisfiability. We give a semantics for stochastic constraint programs, and propose a number...

  9. Influence of Acoustic Feedback on the Learning Strategies of Neural Network-Based Sound Classifiers in Digital Hearing Aids

    Directory of Open Access Journals (Sweden)

    Lorena Álvarez

    2009-01-01

    Full Text Available Sound classifiers embedded in digital hearing aids are usually designed by using sound databases that do not include the distortions associated to the feedback that often occurs when these devices have to work at high gain and low gain margin to oscillation. The consequence is that the classifier learns inappropriate sound patterns. In this paper we explore the feasibility of using different sound databases (generated according to 18 configurations of real patients, and a variety of learning strategies for neural networks in the effort of reducing the probability of erroneous classification. The experimental work basically points out that the proposed methods assist the neural network-based classifier in reducing its error probability in more than 18%. This helps enhance the elderly user's comfort: the hearing aid automatically selects, with higher success probability, the program that is best adapted to the changing acoustic environment the user is facing.

  10. Buffering social influence: neural correlates of response inhibition predict driving safety in the presence of a peer.

    Science.gov (United States)

    Cascio, Christopher N; Carp, Joshua; O'Donnell, Matthew Brook; Tinney, Francis J; Bingham, C Raymond; Shope, Jean T; Ouimet, Marie Claude; Pradhan, Anuj K; Simons-Morton, Bruce G; Falk, Emily B

    2015-01-01

    Adolescence is a period characterized by increased sensitivity to social cues, as well as increased risk-taking in the presence of peers. For example, automobile crashes are the leading cause of death for adolescents, and driving with peers increases the risk of a fatal crash. Growing evidence points to an interaction between neural systems implicated in cognitive control and social and emotional context in predicting adolescent risk. We tested such a relationship in recently licensed teen drivers. Participants completed an fMRI session in which neural activity was measured during a response inhibition task, followed by a separate driving simulator session 1 week later. Participants drove alone and with a peer who was randomly assigned to express risk-promoting or risk-averse social norms. The experimentally manipulated social context during the simulated drive moderated the relationship between individual differences in neural activity in the hypothesized cognitive control network (right inferior frontal gyrus, BG) and risk-taking in the driving context a week later. Increased activity in the response inhibition network was not associated with risk-taking in the presence of a risky peer but was significantly predictive of safer driving in the presence of a cautious peer, above and beyond self-reported susceptibility to peer pressure. Individual differences in recruitment of the response inhibition network may allow those with stronger inhibitory control to override risky tendencies when in the presence of cautious peers. This relationship between social context and individual differences in brain function expands our understanding of neural systems involved in top-down cognitive control during adolescent development.

  11. Plasticity in central neural drive with short-term disuse and recovery - effects on muscle strength and influence of aging.

    Science.gov (United States)

    Hvid, L G; Aagaard, P; Ørtenblad, N; Kjaer, M; Suetta, C

    2018-02-21

    While short-term disuse negatively affects mechanical muscle function (e.g. isometric muscle strength) little is known of the relative contribution of adaptions in central neural drive and peripheral muscle contractility. The present study investigated the relative contribution of adaptations in central neural drive and peripheral muscle contractility on changes in isometric muscle strength following short-term unilateral disuse (4 days, knee brace) and subsequent active recovery (7 days, one session of resistance training) in young (n = 11, 24 yrs) and old healthy men (n = 11, 67 yrs). Maximal isometric knee extensor strength (MVC) (isokinetic dynamometer), voluntary muscle activation (superimposed twitch technique), and electrically evoked muscle twitch force (single and doublet twitch stimulation) were assessed prior to and after disuse, and after recovery. Following disuse, relative decreases in MVC did not differ statistically between old (16.4 ± 3.7%, p plasticity in voluntary muscle activation (~central neural drive) is a dominant mechanism affecting short-term disuse- and recovery-induced changes in muscle strength in older adults. Copyright © 2017. Published by Elsevier Inc.

  12. Pressures and constraints on general management.

    Science.gov (United States)

    Stewart, R

    1989-03-01

    A discussion of pressures and constraints on general management is not straightforward. Pressures and constraints can be seen both as external influences and as individually determined. This dual origin is important so that general managers can help themselves, and be helped, to be more in control of their jobs and their environment. Drawing on the findings from the Templeton tracer study of DGMs and from the Templeton DGMs' group, the paper considers a range of possible pressures and constraints on DGMs. It argues that an effective general manager will know which pressures and constraints are external and which are self-imposed and will know which can and should be changed.

  13. Influence of the antifolate drug Methotrexate on the development of murine neural tube defects and genomic instability.

    Science.gov (United States)

    Zhao, Jie; Guan, Tao; Wang, Jianhua; Xiang, Qian; Wang, Mingsheng; Wang, Xiuwei; Guan, Zhen; Xie, Qiu; Niu, Bo; Zhang, Ting

    2013-09-01

    Impaired folate metabolism is considered a risk factor for neural tube defects (NTDs). However, the relationship between folate deficiency and the risk of NTDs remains unclear, because experimentally induced dietary folate deficiency is insufficient to cause NTDs in non-mutant mice. Methotrexate (MTX) is a specific folate antagonist that competitively inhibits dihydrofolate reductase (DHFR) activity. The objective of this study was to develop a folate dysmetabolism murine model, and study the development of NTDs and its mechanism. Pregnant mice were injected with different doses of MTX [0, 0.5, 1.0, 3.0, 4.5 and 6.0 mg kg(-1) body weight (b/w) intraperitoneally (i.p.)] on gestational day 7.5 and sacrificed on gestational day 11.5. DHFR activity in embryonic tissues was detected, and folate concentrations were analyzed using LC/MS/MS. Copy number variations (CNVs) in neural tube tissues were detected using array comparative genomic hybridization (aCGH). A dose of MTX 4.5 mg kg(-1) b/w, resulted in the highest incidence of NTDs (31.4%) compared with the other groups, and DHFR activities, 5-MeTHF and 5-FoTHF concentrations in embryonic tissues decreased significantly after MTX injection. Furthermore, we found three high-confidence CNVs on chromosome X using aCGH, which was confirmed by RT-PCR and MassARRAY. These results indicate that MTX could cause a folate-associated dysmetabolism, which is similar to that of dietary folate deficiency in mice. The presence of CNVs in neural tube tissues was associated with the development of NTDs. Copyright © 2012 John Wiley & Sons, Ltd.

  14. Holonomic constraints: an analytical result

    Energy Technology Data Exchange (ETDEWEB)

    Mazars, Martial [Laboratoire de Physique Theorique (UMR 8627), Universite de Paris Sud XI, Batiment 210, 91405 Orsay Cedex (France)

    2007-02-23

    Systems subjected to holonomic constraints follow quite complicated dynamics that could not be described easily with Hamiltonian or Lagrangian dynamics. The influence of holonomic constraints in equations of motions is taken into account by using Lagrange multipliers. Finding the value of the Lagrange multipliers allows us to compute the forces induced by the constraints and therefore, to integrate the equations of motions of the system. Computing analytically the Lagrange multipliers for a constrained system may be a difficult task that depends on the complexity of systems. For complex systems it is, most of the time, impossible to achieve. In computer simulations, some algorithms using iterative procedures estimate numerically Lagrange multipliers or constraint forces by correcting the unconstrained trajectory. In this work, we provide an analytical computation of the Lagrange multipliers for a set of linear holonomic constraints with an arbitrary number of bonds of constant length. In the appendix explicit formulae are shown for Lagrange multipliers for systems having 1, 2, 3, 4 and 5 bonds of constant length, linearly connected.

  15. Neural correlates of emotion regulation deficits in remitted depression: the influence of regulation strategy, habitual regulation use, and emotional valence.

    Science.gov (United States)

    Kanske, Philipp; Heissler, Janine; Schönfelder, Sandra; Wessa, Michèle

    2012-07-02

    Regulating emotions through reappraisal has been shown to elicit abnormal neural activation patterns in currently depressed patients. It is, however, unclear if this deficit generalizes to other emotion regulation strategies, if it persists when patients recover, and if it is related to habitual use of reappraisal strategies. Therefore, we measured the neural responses to emotional images with functional magnetic resonance imaging in remitted patients with previous episodes of major depression and healthy controls. While viewing the images participants regulated the elicited emotions using either a reappraisal or a distraction strategy. Habitual reappraisal use was measured with the Cognitive Emotion Regulation Questionnaire. Depressed patients showed a selective deficit in down-regulating amygdala responses to negative emotional stimuli using reappraisal. This down-regulation of amygdala activity was strongest in participants high in habitual reappraisal use. Activity in the regulating control-network including anterior cingulate and lateral orbitofrontal cortex was increased during both emotion regulation strategies. The findings in remitted patients with previous episodes of major depression suggest that altered emotion regulation is a trait-marker for depression. This interpretation is supported by the relation of habitual reappraisal use to amygdala down-regulation success. Copyright © 2012 Elsevier Inc. All rights reserved.

  16. A SOLUTION TO THE DOUBLE DUMMY CONTRACT BRIDGE PROBLEM INFLUENCED BY SUPERVISED LEARNING MODULE ADAPTED BY ARTIFICIAL NEURAL NETWORK

    Directory of Open Access Journals (Sweden)

    M. Dharmalingam

    2014-10-01

    Full Text Available Contract Bridge is an intellectual game which motivates multiple skills and application of prior experience and knowledge, as no player knows accurately what moves other players are capable of making. The Bridge is a game played in the presence of imperfect information, yet its strategies must be well formulated, since the outcome at any intermediate stage is solely based on the choices made during the immediately preceding phase. In this paper, we train an Artificial Neural Network architecture using sample deals and use it to estimate the number of tricks to be taken by one pair of bridge players, which is the main challenge in the Double Dummy Bridge Problem. We focus on Back Propagation Neural Network Architecture with Back Propagation Algorithm with Sigmoidal transfer functions. We used two approaches namely, High – Card Point Count System and Distribution Point Method during the bidding phase of Contract Bridge. We experimented with two sigmoidal transfer functions namely, Log Sigmoid transfer function and the Hyperbolic Tangent Sigmoid function. Results reveal that the later performs better giving lower mean squared error on the output.

  17. The Soft Cumulative Constraint

    OpenAIRE

    Petit, Thierry; Poder, Emmanuel

    2009-01-01

    This research report presents an extension of Cumulative of Choco constraint solver, which is useful to encode over-constrained cumulative problems. This new global constraint uses sweep and task interval violation-based algorithms.

  18. Composing constraint solvers

    NARCIS (Netherlands)

    P. Zoeteweij (Peter)

    2005-01-01

    htmlabstractComposing constraint solvers based on tree search and constraint propagation through generic iteration leads to efficient and flexible constraint solvers. This was demonstrated using OpenSolver, an abstract branch-and-propagate tree search engine that supports a wide range of relevant

  19. Simultaneous influence of gas mixture composition and process temperature on Fe2O3->FeO reduction kinetics: neural network modeling

    Directory of Open Access Journals (Sweden)

    K. Piotrowski

    2005-09-01

    Full Text Available The kinetics of Fe2O3->FeO reaction was investigated. The thermogravimetric (TGA data covered the reduction of hematite both by pure species (nitrogen diluted CO or H2 and by their mixture. The conventional analysis has indicated that initially the reduction of hematite is a complex, surface controlled process, however once a thin layer of lower oxidation state iron oxides (magnetite, wüstite is formed on the surface, it changes to diffusion control. Artificial Neural Network (ANN has proved to be a convenient tool for modeling of this complex, heterogeneous reaction runs within the both (kinetic and diffusion regions, correctly considering influence of temperature and gas composition effects and their complex interactions. ANN's model shows the capability to mimic some extreme (minimum of the reaction rate within the determined temperature window, while the Arrhenius dependency is of limited use.

  20. Evidence on the Adaptive Recruitment of Chinese Cork Oak (Quercus variabilis Bl.: Influence on Repeated Germination and Constraint Germination by Food-Hoarding Animals

    Directory of Open Access Journals (Sweden)

    Yifeng Zhang

    2016-02-01

    Full Text Available In drought temperate forest, seedling recruitment is highly dependent on seed burial by native animal dispersers. To prolong seed storage, animals often take measures to impede seed germination. Aiming to understand the strategic balance between the natural seed germination and the role played by animals in the constraint germination procedures, we investigated the stages on the germinated acorns of Chinese cork oak (Quercus variabilis Bl. and the rodents’ behavior on the consequential delay in developmental processes of acorns in Mt. Taihangshan area of Jiyuan, Henan, China. The results showed that (1 Apodemus peninsulae Thomas excise radicles from germinated acorns before hoarding; (2 radicle-excised acorns re-germinate successfully if the excised radicle was un-lignified, but reverse if excised radicle was lignified; and (3 seedlings derived from radicle-excised acorns produce more lateral roots than that of sound acorns. We conclude that rodents take the radicle-excision behavior as a deliberate mechanism to slow the rapid germination of acorns; nevertheless, the acorns adaptively respond to this negative treatment and counteract the constraint from rodents by regermination to preserve the viability of the seeds. Consequently, this plays a significant role in forest recruitment. This study proves the new survival model of Chinese cork oak against animal predation, and will broaden theories of animal-forest interaction, forest succession and can be used as a meaningful venture to temperate forest restoration efforts.

  1. Exploiting elasticity: Modeling the influence of neural control on mechanics and energetics of ankle muscle-tendons during human hopping.

    Science.gov (United States)

    Robertson, Benjamin D; Sawicki, Gregory S

    2014-07-21

    We present a simplified Hill-type model of the human triceps surae-Achilles tendon complex working on a gravitational-inertial load during cyclic contractions (i.e. vertical hopping). Our goal was to determine the role that neural control plays in governing muscle, or contractile element (CE), and tendon, or series elastic element (SEE), mechanics and energetics within a compliant muscle-tendon unit (MTU). We constructed a 2D parameter space consisting of many combinations of stimulation frequency and magnitude (i.e. neural control strategies). We compared the performance of each control strategy by evaluating peak force and average positive mechanical power output for the system (MTU) and its respective components (CE, SEE), force-length (F-L) and -velocity (F-V) operating point of the CE during active force production, average metabolic rate for the CE, and both MTU and CE apparent efficiency. Our results suggest that frequency of stimulation plays a primary role in governing whole-MTU mechanics. These include the phasing of both activation and peak force relative to minimum MTU length, average positive power, and apparent efficiency. Stimulation amplitude was primarily responsible for governing average metabolic rate and within MTU mechanics, including peak force generation and elastic energy storage and return in the SEE. Frequency and amplitude of stimulation both played integral roles in determining CE F-L operating point, with both higher frequency and amplitude generally corresponding to lower CE strains, reduced injury risk, and elimination of the need for passive force generation in the CE parallel elastic element (PEE). Copyright © 2014 Elsevier Ltd. All rights reserved.

  2. Constraints and Creativity in NPD - Testing the Impact of 'Late Constraints'

    DEFF Research Database (Denmark)

    Onarheim, Balder; Valgeirsdóttir, Dagný

    The aim of the presented work is to investigate how the timing of project constraints can influence the creativity of the output in New Product Development (NPD) projects. When seeking to produce a creative output, is it beneficial to know all constraints when initiating a project, or will constr......, in the presented setup no negative impact of adding radically new constraints during a project was found, highlighting for managers that it is not crucial to a project’s creative output to have all constraints from the beginning.......The aim of the presented work is to investigate how the timing of project constraints can influence the creativity of the output in New Product Development (NPD) projects. When seeking to produce a creative output, is it beneficial to know all constraints when initiating a project......, or will constraints introduced throughout a project potentially lead to a more creative output? While the relationship between constraints and creativity is fairly well studied, the question of how introducing constraints late in a project can influence creativity is still unanswered. A single factor, two level...

  3. What motivates adolescents? Neural responses to rewards and their influence on adolescents' risk taking, learning, and cognitive control.

    Science.gov (United States)

    van Duijvenvoorde, Anna C K; Peters, Sabine; Braams, Barbara R; Crone, Eveline A

    2016-11-01

    Adolescence is characterized by pronounced changes in motivated behavior, during which emphasis on potential rewards may result in an increased tendency to approach things that are novel and bring potential for positive reinforcement. While this may result in risky and health-endangering behavior, it may also lead to positive consequences, such as behavioral flexibility and greater learning. In this review we will discuss both the maladaptive and adaptive properties of heightened reward-sensitivity in adolescents by reviewing recent cognitive neuroscience findings in relation to behavioral outcomes. First, we identify brain regions involved in processing rewards in adults and adolescents. Second, we discuss how functional changes in reward-related brain activity during adolescence are related to two behavioral domains: risk taking and cognitive control. Finally, we conclude that progress lies in new levels of explanation by further integration of neural results with behavioral theories and computational models. In addition, we highlight that longitudinal measures, and a better conceptualization of adolescence and environmental determinants, are of crucial importance for understanding positive and negative developmental trajectories. Copyright © 2016 Elsevier Ltd. All rights reserved.

  4. Influence of neural mobilization of lower limbs on the functional performance and dynamic balance in asymptomatic individuals: a cross-over randomized controlled trial

    Directory of Open Access Journals (Sweden)

    Nunes Guilherme S.

    2017-12-01

    Full Text Available Purpose. To verify the influence of neural mobilization (NM applied to the lower limbs on functional performance and dynamic balance in asymptomatic individuals. Methods. The total of 30 asymptomatic participants (15 women and 15 men; age, 30.1 ± 6.7 years; height, 1.70 ± 0.1 m; body mass, 73.1 ± 13.4 kg were enrolled in this cross-over randomized controlled trial. The participants received NM of the femoral, sciatic, and tibial nerves, as well as static stretching (SS of the following muscles: hamstring, lumbar, piriformis, hip adductors, hip flexors, quadriceps, and triceps surae. The order of applying NM and SS was randomly decided and the interventions were performed at least 48 hours apart. Functional performance was measured by performance in vertical jump (VJ and dynamic balance was measured with the Star Excursion Balance Test (SEBT. Results. There were no differences between NM and SS for height (cm in VJ (p = 0.16 or in the distance reached (% in the SEBT, normalized by lower limb length (dominant limb: anterior, p = 0.35; posterolateral, p = 0.69; posteromedial, p = 0.50 / non-dominant limb: anterior, p = 0.68; posterolateral, p = 1.00; posteromedial, p = 0.77. Conclusions. NM did not exert any influence on functional performance or dynamic balance. Thereby, having no positive or negative impact on performance, NM can be used at any time of treatment.

  5. Individual variation in the neural processes of motor decisions in the stop signal task: the influence of novelty seeking and harm avoidance personality traits.

    Science.gov (United States)

    Hu, Jianping; Lee, Dianne; Hu, Sien; Zhang, Sheng; Chao, Herta; Li, Chiang-Shan R

    2016-06-01

    Personality traits contribute to variation in human behavior, including the propensity to take risk. Extant work targeted risk-taking processes with an explicit manipulation of reward, but it remains unclear whether personality traits influence simple decisions such as speeded versus delayed responses during cognitive control. We explored this issue in an fMRI study of the stop signal task, in which participants varied in response time trial by trial, speeding up and risking a stop error or slowing down to avoid errors. Regional brain activations to speeded versus delayed motor responses (risk-taking) were correlated to novelty seeking (NS), harm avoidance (HA) and reward dependence (RD), with age and gender as covariates, in a whole brain regression. At a corrected threshold, the results showed a positive correlation between NS and risk-taking responses in the dorsomedial prefrontal, bilateral orbitofrontal, and frontopolar cortex, and between HA and risk-taking responses in the parahippocampal gyrus and putamen. No regional activations varied with RD. These findings demonstrate that personality traits influence the neural processes of executive control beyond behavioral tasks that involve explicit monetary reward. The results also speak broadly to the importance of characterizing inter-subject variation in studies of cognition and brain functions.

  6. Lamin b1 polymorphism influences morphology of the nuclear envelope, cell cycle progression, and risk of neural tube defects in mice.

    Directory of Open Access Journals (Sweden)

    Sandra C P De Castro

    Full Text Available Neural tube defects (NTDs, including spina bifida and anencephaly, are common birth defects whose complex multigenic causation has hampered efforts to delineate their molecular basis. The effect of putative modifier genes in determining NTD susceptibility may be investigated in mouse models, particularly those that display partial penetrance such as curly tail, a strain in which NTDs result from a hypomorphic allele of the grainyhead-like-3 gene. Through proteomic analysis, we found that the curly tail genetic background harbours a polymorphic variant of lamin B1, lacking one of a series of nine glutamic acid residues. Lamins are intermediate filament proteins of the nuclear lamina with multiple functions that influence nuclear structure, cell cycle properties, and transcriptional regulation. Fluorescence loss in photobleaching showed that the variant lamin B1 exhibited reduced stability in the nuclear lamina. Genetic analysis demonstrated that the variant also affects neural tube closure: the frequency of spina bifida and anencephaly was reduced three-fold when wild-type lamin B1 was bred into the curly tail strain background. Cultured fibroblasts expressing variant lamin B1 show significantly increased nuclear dysmorphology and diminished proliferative capacity, as well as premature senescence, associated with reduced expression of cyclins and Smc2, and increased expression of p16. The cellular basis of spinal NTDs in curly tail embryos involves a proliferation defect localised to the hindgut epithelium, and S-phase progression was diminished in the hindgut of embryos expressing variant lamin B1. These observations indicate a mechanistic link between altered lamin B1 function, exacerbation of the Grhl3-mediated cell proliferation defect, and enhanced susceptibility to NTDs. We conclude that lamin B1 is a modifier gene of major effect for NTDs resulting from loss of Grhl3 function, a role that is likely mediated via the key function of lamin B1

  7. [Artificial neural networks in Neurosciences].

    Science.gov (United States)

    Porras Chavarino, Carmen; Salinas Martínez de Lecea, José María

    2011-11-01

    This article shows that artificial neural networks are used for confirming the relationships between physiological and cognitive changes. Specifically, we explore the influence of a decrease of neurotransmitters on the behaviour of old people in recognition tasks. This artificial neural network recognizes learned patterns. When we change the threshold of activation in some units, the artificial neural network simulates the experimental results of old people in recognition tasks. However, the main contributions of this paper are the design of an artificial neural network and its operation inspired by the nervous system and the way the inputs are coded and the process of orthogonalization of patterns.

  8. Interactive actions of Bdnf methylation and cell metabolism for building neural resilience under the influence of diet.

    Science.gov (United States)

    Tyagi, Ethika; Zhuang, Yumei; Agrawal, Rahul; Ying, Zhe; Gomez-Pinilla, Fernando

    2015-01-01

    Quality nutrition during the period of brain formation is a predictor of brain functional capacity and plasticity during adulthood; however it is not clear how this conferred plasticity imparts long-term neural resilience. Here we report that early exposure to dietary omega-3 fatty acids orchestrates key interactions between metabolic signals and Bdnf methylation creating a reservoir of neuroplasticity that can protect the brain against the deleterious effects of switching to a Western diet (WD). We observed that the switch to a WD increased Bdnf methylation specific to exon IV, in proportion to anxiety-like behavior, in Sprague Dawley rats reared in low omega-3 fatty acid diet, and these effects were abolished by the DNA methyltransferase inhibitor 5-aza-2'-deoxycytidine. Blocking methylation also counteracted the reducing action of WD on the transcription regulator CTCF binding to Bdnf promoter IV. In vitro studies confirmed that CTCF binding to Bdnf promoter IV is essential for the action of DHA on BDNF regulation. Diet is also intrinsically associated to cell metabolism, and here we show that the switch to WD downregulated cell metabolism (NAD/NADH ratio and SIRT1). The fact that DNA methyltransferase inhibitor did not alter these parameters suggests they occur upstream to methylation. In turn, the methylation inhibitor counteracted the action of WD on PGC-1α, a mitochondrial transcription co-activator and BDNF regulator, suggesting that PGC-1α is an effector of Bdnf methylation. Results support a model in which diet can build an "epigenetic memory" during brain formation that confers resilience to metabolic perturbations occurring in adulthood. Copyright © 2015 Elsevier Inc. All rights reserved.

  9. Application of artificial neural network model for groundwater level forecasting in a river island with artificial influencing factors

    Science.gov (United States)

    Lee, Sanghoon; Yoon, Heesung; Park, Byeong-Hak; Lee, Kang-Kun

    2017-04-01

    Groundwater use has been increased for various purposes like agriculture, industry or drinking water in recent years, the issue related to sustainability on the groundwater use also has been raised. Accordingly, forecasting the groundwater level is of great importance for planning sustainable use of groundwater. In a small island surrounded by the Han River, South Korea, seasonal fluctuation of the groundwater level is characterized by multiple factors such as recharge/discharge event of the Paldang dam, Water Curtain Cultivation (WCC) during the winter season, operation of Groundwater Heat Pump System (GWHP). For a period when the dam operation is only occurred in the study area, a prediction of the groundwater level can be easily achieved by a simple cross-correlation model. However, for a period when the WCC and the GWHP systems are working together, the groundwater level prediction is challenging due to its unpredictable operation of the two systems. This study performed Artificial Neural Network (ANN) model to forecast the groundwater level in the river area reflecting the various predictable/unpredictable factors. For constructing the ANN models, two monitoring wells, YSN1 and YSO8, which are located near the injection and abstraction wells for the GWHP system were selected, respectively. By training with the groundwater level data measured in January 2015 to August 2015, response of groundwater level by each of the surface water level, the WCC and the GWHP system were evaluated. Consequentially, groundwater levels in December 2015 to March 2016 were predicted by ANN models, providing optimal fits in comparison to the observed water levels. This study suggests that the ANN model is a useful tool to forecast the groundwater level in terms of the management of groundwater. Acknowledgement : Financial support was provided by the "R&D Project on Environmental Management of Geologic CO2 Storage" from the KEITI (Project Number: 2014001810003) This research was

  10. Influences of granular constraints and surface effects on the heterogeneity of elastic, superelastic, and plastic responses of polycrystalline shape memory alloys

    Science.gov (United States)

    Paranjape, Harshad M.; Paul, Partha P.; Sharma, Hemant; Kenesei, Peter; Park, Jun-Sang; Duerig, T. W.; Brinson, L. Catherine; Stebner, Aaron P.

    2017-05-01

    Deformation heterogeneities at the microstructural length-scale developed in polycrystalline shape memory alloys (SMAs) during superelastic loading are studied using both experiments and simulations. In situ X-ray diffraction, specifically the far-field high energy diffraction microscopy (ff-HEDM) technique, was used to non-destructively measure the grain-averaged statistics of position, crystal orientation, elastic strain tensor, and volume for hundreds of austenite grains in a superelastically loaded nickel-titanium (NiTi) SMA. These experimental data were also used to create a synthetic microstructure within a finite element model. The development of intragranular stresses were then simulated during tensile loading of the model using anisotropic elasticity. Driving forces for phase transformation and slip were calculated from these stresses. The grain-average responses of individual austenite crystals examined before and after multiple stress-induced transformation events showed that grains in the specimen interior carry more axial stress than the surface grains as the superelastic response ;shakes down;. Examination of the heterogeneity within individual grains showed that regions near grain boundaries exhibit larger stress variation compared to the grain interiors. This intragranular heterogeneity is more strongly driven by the constraints of neighboring grains than the initial stress state and orientation of the individual grains.

  11. Neural mechanisms influencing interlimb coordination during locomotion in humans: presynaptic modulation of forearm H-reflexes during leg cycling.

    Directory of Open Access Journals (Sweden)

    Tsuyoshi Nakajima

    conservation of neural control mechanisms between the arms and legs during locomotor behaviors in humans.

  12. A large-scale neural network model of the influence of neuromodulatory levels on working memory and behavior.

    Science.gov (United States)

    Avery, Michael C; Dutt, Nikil; Krichmar, Jeffrey L

    2013-01-01

    The dorsolateral prefrontal cortex (dlPFC), which is regarded as the primary site for visuospatial working memory in the brain, is significantly modulated by dopamine (DA) and norepinephrine (NE). DA and NE originate in the ventral tegmental area (VTA) and locus coeruleus (LC), respectively, and have been shown to have an "inverted-U" dose-response profile in dlPFC, where the level of arousal and decision-making performance is a function of DA and NE concentrations. Moreover, there appears to be a sweet spot, in terms of the level of DA and NE activation, which allows for optimal working memory and behavioral performance. When either DA or NE is too high, input to the PFC is essentially blocked. When either DA or NE is too low, PFC network dynamics become noisy and activity levels diminish. Mechanisms for how this is occurring have been suggested, however, they have not been tested in a large-scale model with neurobiologically plausible network dynamics. Also, DA and NE levels have not been simultaneously manipulated experimentally, which is not realistic in vivo due to strong bi-directional connections between the VTA and LC. To address these issues, we built a spiking neural network model that includes D1, α2A, and α1 receptors. The model was able to match the inverted-U profiles that have been shown experimentally for differing levels of DA and NE. Furthermore, we were able to make predictions about what working memory and behavioral deficits may occur during simultaneous manipulation of DA and NE outside of their optimal levels. Specifically, when DA levels were low and NE levels were high, cues could not be held in working memory due to increased noise. On the other hand, when DA levels were high and NE levels were low, incorrect decisions were made due to weak overall network activity. We also show that lateral inhibition in working memory may play a more important role in increasing signal-to-noise ratio than increasing recurrent excitatory input.

  13. Symbolic Constraints in Constructive Geometric Constraint Solving

    OpenAIRE

    Hoffmann, Christoph M.; Joan-Arinyo, Robert

    1997-01-01

    In design and manufacturing applications, users of computer aided design systems want to define relationships between dimension variables, since such relationships express design intent very flexibly. This work reports on a technique developed to enhance a class of constructive geometric constraint solvers with the capability of managing functional relationships between dimension variables. The method is shown to be correct.

  14. A new perspective on behavioral inconsistency and neural noise in aging: Compensatory speeding of neural communication

    Directory of Open Access Journals (Sweden)

    S. Lee Hong

    2012-09-01

    Full Text Available This paper seeks to present a new perspective on the aging brain. Here, we make connections between two key phenomena of brain aging: 1 increased neural noise or random background activity; and 2 slowing of brain activity. Our perspective proposes the possibility that the slowing of neural processing due to decreasing nerve conduction velocities leads to a compensatory speeding of neuron firing rates. These increased firing rates lead to a broader distribution of power in the frequency spectrum of neural oscillations, which we propose, can just as easily be interpreted as neural noise. Compensatory speeding of neural activity, as we present, is constrained by the: A availability of metabolic energy sources; and B competition for frequency bandwidth needed for neural communication. We propose that these constraints lead to the eventual inability to compensate for age-related declines in neural function that are manifested clinically as deficits in cognition, affect, and motor behavior.

  15. Temporal Concurrent Constraint Programming

    DEFF Research Database (Denmark)

    Nielsen, Mogens; Palamidessi, Catuscia; Valencia, Frank Dan

    2002-01-01

    The ntcc calculus is a model of non-deterministic temporal concurrent constraint programming. In this paper we study behavioral notions for this calculus. In the underlying computational model, concurrent constraint processes are executed in discrete time intervals. The behavioral notions studied...

  16. Credit Constraints in Education

    Science.gov (United States)

    Lochner, Lance; Monge-Naranjo, Alexander

    2012-01-01

    We review studies of the impact of credit constraints on the accumulation of human capital. Evidence suggests that credit constraints have recently become important for schooling and other aspects of households' behavior. We highlight the importance of early childhood investments, as their response largely determines the impact of credit…

  17. The Antigone Constraint.

    Science.gov (United States)

    Tuggy, David

    This paper presents a class of sentences that certain syntactic rules of English would be expected to produce, but that are not grammatical. The sentences all involve the raising of a sentential Noun Phrase (NP) and the subsequent application of some syntactic rule to that senential NP. A constraint, referred to as the Antigone Constraint, is…

  18. Theory of Constraints (TOC)

    DEFF Research Database (Denmark)

    Michelsen, Aage U.

    2004-01-01

    Tankegangen bag Theory of Constraints samt planlægningsprincippet Drum-Buffer-Rope. Endvidere skitse af The Thinking Process.......Tankegangen bag Theory of Constraints samt planlægningsprincippet Drum-Buffer-Rope. Endvidere skitse af The Thinking Process....

  19. Evaluating Distributed Timing Constraints

    DEFF Research Database (Denmark)

    Kristensen, C.H.; Drejer, N.

    1994-01-01

    In this paper we describe a solution to the problem of implementing time-optimal evaluation of timing constraints in distributed real-time systems.......In this paper we describe a solution to the problem of implementing time-optimal evaluation of timing constraints in distributed real-time systems....

  20. Mapping of neural pathways that influence diaphragm activity and project to the lumbar spinal cord in cats.

    Science.gov (United States)

    Rice, C D; Weber, S A; Waggoner, A L; Jessell, M E; Yates, B J

    2010-05-01

    During breathing, the diaphragm and abdominal muscles contract out of phase. However, during other behaviors (including vomiting, postural adjustments, and locomotion) simultaneous contractions are required of the diaphragm and other muscle groups including abdominal muscles. Recent studies in cats using transneuronal tracing techniques showed that in addition to neurons in the respiratory groups, cells in the inferior and lateral vestibular nuclei (VN) and medial pontomedullary reticular formation (MRF) influence diaphragm activity. The goal of the present study was to determine whether neurons in these regions have collateralized projections to both diaphragm motoneurons and the lumbar spinal cord. For this purpose, the transneuronal tracer rabies virus was injected into the diaphragm, and the monosynaptic retrograde tracer Fluoro-Gold (FG) was injected into the Th13-L1 spinal segments. A large fraction of MRF and VN neurons (median of 72 and 91%, respectively) that were infected by rabies virus were dual-labeled by FG. These data show that many MRF and VN neurons that influence diaphragm activity also have a projection to the lumbar spinal cord and thus likely are involved in coordinating behaviors that require synchronized contractions of the diaphragm and other muscle groups.

  1. Constraint-based reachability

    Directory of Open Access Journals (Sweden)

    Arnaud Gotlieb

    2013-02-01

    Full Text Available Iterative imperative programs can be considered as infinite-state systems computing over possibly unbounded domains. Studying reachability in these systems is challenging as it requires to deal with an infinite number of states with standard backward or forward exploration strategies. An approach that we call Constraint-based reachability, is proposed to address reachability problems by exploring program states using a constraint model of the whole program. The keypoint of the approach is to interpret imperative constructions such as conditionals, loops, array and memory manipulations with the fundamental notion of constraint over a computational domain. By combining constraint filtering and abstraction techniques, Constraint-based reachability is able to solve reachability problems which are usually outside the scope of backward or forward exploration strategies. This paper proposes an interpretation of classical filtering consistencies used in Constraint Programming as abstract domain computations, and shows how this approach can be used to produce a constraint solver that efficiently generates solutions for reachability problems that are unsolvable by other approaches.

  2. Managing Constraint Generators in Retail Design Processes

    DEFF Research Database (Denmark)

    Münster, Mia Borch; Haug, Anders

    case studies of fashion store design projects, the present paper addresses this gap. The and six case studies of fashion store design projects, the present paper sheds light on the types of constraints generated by the relevant constraint generators. The paper shows that in the cases studied...... and landlords need to be considered as well as the interest of the client and brand owner. Furthermore the users need to be taken into account in order to develop an interesting and functional shopping and working environments. Finally, suppliers and competitors may influence the design with regard...... pro-actively with constraints, the resources for alteration can be limited, but in order to do this a solid understanding of the types of constraints is required. Although literature has dealt with the topic it does not provide detailed answers to these questions. Based on a literature study and six...

  3. The Ambiguous Role of Constraints in Creativity

    DEFF Research Database (Denmark)

    Biskjær, Michael Mose; Onarheim, Balder; Wiltschnig, Stefan

    2011-01-01

    The relationship between creativity and constraints is often described in the literature either in rather imprecise, general concepts or in relation to very specific domains. Cross-domain and cross-disciplinary takes on how the handling of constraints influences creative activities are rare....... In this paper, we explore these particular issues in two creative domains: art and engineering design. These domains vary so greatly in terms of number and types of constraints in play that we argue for considering them as opposite extremes of a continuum of levels of creative freedom. By comparing two case...... studies of Danish cutting-edge proponents of creative expertise thus exemplifying each domain, this preliminary exploration mainly focuses on similarities in how such successful professionals work with constraints to frame their creative process and ensure its progression toward the final outcome. Our...

  4. The influence of mechanical constraints introduced by β annealed microstructures on the yield strength and ductility of Ti-6Al-4V

    Energy Technology Data Exchange (ETDEWEB)

    Kasemer, Matthew; Quey, Romain; Dawson, Paul

    2017-06-01

    Discussed is a computational study of the influence of the microstructure’s geometric morphology on the yield strength and ductility of Ti-6Al-4V. Uniaxial tension tests were conducted on physical specimens to determine the macroscopic yield strength and ductility of two microstructural variations (mill annealed and β annealed) to establish comparisons of macroscopic properties. A multi-experimental approach was utilized to gather two dimensional and three dimensional data, which were used to inform the construction of representative β annealed polycrystals. A highly parallelized crystal plasticity finite element framework was employed to model the deformation response of the generated polycrystals subjected to uniaxial tension. To gauge the macroscopic response’s sensitivity to the morphology of the geometry, the key geometrical features - namely the number of high temperature β phase grains, α phase colonies, and size of remnant secondary β phase lamellae - were altered systematically in a suite of simulations. Both single phase and dual phase aggregates were studied. Presented are the calculated yield strengths and ductilities, and the resulting trends as functions of geometric parameters are examined in light of the heterogeneity in deformation at the crystal scale.

  5. 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

  6. Neurometaplasticity: Glucoallostasis control of plasticity of the neural networks of error commission, detection, and correction modulates neuroplasticity to influence task precision

    Science.gov (United States)

    Welcome, Menizibeya O.; Dane, Şenol; Mastorakis, Nikos E.; Pereverzev, Vladimir A.

    2017-12-01

    The term "metaplasticity" is a recent one, which means plasticity of synaptic plasticity. Correspondingly, neurometaplasticity simply means plasticity of neuroplasticity, indicating that a previous plastic event determines the current plasticity of neurons. Emerging studies suggest that neurometaplasticity underlie many neural activities and neurobehavioral disorders. In our previous work, we indicated that glucoallostasis is essential for the control of plasticity of the neural network that control error commission, detection and correction. Here we review recent works, which suggest that task precision depends on the modulatory effects of neuroplasticity on the neural networks of error commission, detection, and correction. Furthermore, we discuss neurometaplasticity and its role in error commission, detection, and correction.

  7. Do You Believe It? Verbal Suggestions Influence the Clinical and Neural Effects of Escitalopram in Social Anxiety Disorder: A Randomized Trial.

    Science.gov (United States)

    Faria, Vanda; Gingnell, Malin; Hoppe, Johanna M; Hjorth, Olof; Alaie, Iman; Frick, Andreas; Hultberg, Sara; Wahlstedt, Kurt; Engman, Jonas; Månsson, Kristoffer N T; Carlbring, Per; Andersson, Gerhard; Reis, Margareta; Larsson, Elna-Marie; Fredrikson, Mats; Furmark, Tomas

    2017-10-01

    administration yielded significantly better outcome on the LSAS-SR (adjusted difference 21.17, 95% CI 10.69-31.65, p<0.0001) with more than three times higher response rate (50% vs. 14%; χ 2 (1)=6.91, p=0.009) and twice the effect size (d=2.24 vs. d=1.13) from pre-to posttreatment. There was no significant between-group difference on anticipatory speech anxiety (STAI-S), both groups improving with treatment. No serious adverse reactions were recorded. On fMRI outcomes, there was suggestive evidence for a differential neural response to treatment between groups in the posterior cingulate, superior temporal and inferior frontal gyri (all z thresholds exceeding 3.68, p≤0.001). Reduced social anxiety with treatment correlated significantly with enhanced posterior cingulate (z threshold 3.24, p=0.0006) and attenuated amygdala (z threshold 2.70, p=0.003) activity. The clinical and neural effects of escitalopram were markedly influenced by verbal suggestions. This points to a pronounced placebo component in SSRI-treatment of SAD and favors a biopsychosocial over a biomedical explanatory model for SSRI efficacy. The Swedish Research Council for Working Life and Social Research (grant 2011-1368), the Swedish Research Council (grant 421-2013-1366), Riksbankens Jubileumsfond - the Swedish Foundation for Humanities and Social Sciences (grant P13-1270:1). Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

  8. Evolvable synthetic neural system

    Science.gov (United States)

    Curtis, Steven A. (Inventor)

    2009-01-01

    An evolvable synthetic neural system includes an evolvable neural interface operably coupled to at least one neural basis function. Each neural basis function includes an evolvable neural interface operably coupled to a heuristic neural system to perform high-level functions and an autonomic neural system to perform low-level functions. In some embodiments, the evolvable synthetic neural system is operably coupled to one or more evolvable synthetic neural systems in a hierarchy.

  9. Neurally and mathematically motivated architecture for language and thought.

    Science.gov (United States)

    Perlovsky, L I; Ilin, R

    2010-01-01

    Neural structures of interaction between thinking and language are unknown. This paper suggests a possible architecture motivated by neural and mathematical considerations. A mathematical requirement of computability imposes significant constraints on possible architectures consistent with brain neural structure and with a wealth of psychological knowledge. How language interacts with cognition. Do we think with words, or is thinking independent from language with words being just labels for decisions? Why is language learned by the age of 5 or 7, but acquisition of knowledge represented by learning to use this language knowledge takes a lifetime? This paper discusses hierarchical aspects of language and thought and argues that high level abstract thinking is impossible without language. We discuss a mathematical technique that can model the joint language-thought architecture, while overcoming previously encountered difficulties of computability. This architecture explains a contradiction between human ability for rational thoughtful decisions and irrationality of human thinking revealed by Tversky and Kahneman; a crucial role in this contradiction might be played by language. The proposed model resolves long-standing issues: how the brain learns correct words-object associations; why animals do not talk and think like people. We propose the role played by language emotionality in its interaction with thought. We relate the mathematical model to Humboldt's "firmness" of languages; and discuss possible influence of language grammar on its emotionality. Psychological and brain imaging experiments related to the proposed model are discussed. Future theoretical and experimental research is outlined.

  10. Constraints in Genetic Programming

    Science.gov (United States)

    Janikow, Cezary Z.

    1996-01-01

    Genetic programming refers to a class of genetic algorithms utilizing generic representation in the form of program trees. For a particular application, one needs to provide the set of functions, whose compositions determine the space of program structures being evolved, and the set of terminals, which determine the space of specific instances of those programs. The algorithm searches the space for the best program for a given problem, applying evolutionary mechanisms borrowed from nature. Genetic algorithms have shown great capabilities in approximately solving optimization problems which could not be approximated or solved with other methods. Genetic programming extends their capabilities to deal with a broader variety of problems. However, it also extends the size of the search space, which often becomes too large to be effectively searched even by evolutionary methods. Therefore, our objective is to utilize problem constraints, if such can be identified, to restrict this space. In this publication, we propose a generic constraint specification language, powerful enough for a broad class of problem constraints. This language has two elements -- one reduces only the number of program instances, the other reduces both the space of program structures as well as their instances. With this language, we define the minimal set of complete constraints, and a set of operators guaranteeing offspring validity from valid parents. We also show that these operators are not less efficient than the standard genetic programming operators if one preprocesses the constraints - the necessary mechanisms are identified.

  11. Perceived constraints to art museum attendance

    Science.gov (United States)

    Jinhee Jun; Gerard Kyle; Joseph T. O' Leary

    2007-01-01

    We explored selected socio-demographic factors that influence the perception of constraints to art museum attendance among a sample of interested individuals who were currently not enjoying art museum visitation. Data from the Survey of Public Participation in the Arts (SPPA), a nationwide survey were used for this study. Using multivariate analysis of variance, we...

  12. University Course Timetabling using Constraint Programming

    Directory of Open Access Journals (Sweden)

    Hadi Shahmoradi

    2017-03-01

    Full Text Available University course timetabling problem is a challenging and time-consuming task on the overall structure of timetable in every academic environment. The problem deals with many factors such as the number of lessons, classes, teachers, students and working time, and these are influenced by some hard and soft constraints. The aim of solving this problem is to assign courses and classes to teachers and students, so that the restrictions are held. In this paper, a constraint programming method is proposed to satisfy maximum constraints and expectation, in order to address university timetabling problem. For minimizing the penalty of soft constraints, a cost function is introduced and AHP method is used for calculating its coefficients. The proposed model is tested on department of management, University of Isfahan dataset using OPL on the IBM ILOG CPLEX Optimization Studio platform. A statistical analysis has been conducted and shows the performance of the proposed approach in satisfying all hard constraints and also the satisfying degree of the soft constraints is on maximum desirable level. The running time of the model is less than 20 minutes that is significantly better than the non-automated ones.

  13. Psychological constraints on egalitarianism

    DEFF Research Database (Denmark)

    Kasperbauer, Tyler Joshua

    2015-01-01

    Debates over egalitarianism for the most part are not concerned with constraints on achieving an egalitarian society, beyond discussions of the deficiencies of egalitarian theory itself. This paper looks beyond objections to egalitarianism as such and investigates the relevant psychological...... philosophy, which aim to construct moral goals with current social and political constraints in mind, to argue that human psychology must be part of a non-ideal theory of egalitarianism. The descriptive thesis holds that the most fundamental psychological challenge to egalitarian ideals comes from what...... processes motivating people to resist various aspects of egalitarianism. I argue for two theses, one normative and one descriptive. The normative thesis holds that egalitarians must take psychological constraints into account when constructing egalitarian ideals. I draw from non-ideal theories in political...

  14. The influence of a constraint and bimanual training program using a variety of modalities on endurance and on the cardiac autonomic regulation system of children with unilateral cerebral palsy: A self-control clinical trial.

    Science.gov (United States)

    Cohen-Holzer, Marilyn; Sorek, Gilad; Schweizer, Maayan; Katz-Leurer, Michal

    2017-01-01

    An intensive hybrid program, combining constraint with bimanual training, improves upper extremity function as well as walking endurance of children with unilateral cerebral palsy (UCP). Endurance improvement may be associated with the cardiac autonomic regulation system (CARS) adaptation, known to be impaired among these children. To examine the influence of an intensive hybrid program on CARS, walking endurance and the correlation with upper extremity function of children with UCP. Twenty-four children aged 6-10 years with UCP participated in a hybrid program, 10 days, 6 hours per day. Data were collected pre-, post- and 3-months post-intervention. Main outcome measures included the Polar RS800CX for heart rate (HR) and heart rate variability (HRV) data, the 6-Minute Walk Test (6MWT) for endurance, and the Assisting Hand Assessment (AHA) and Jebsen-Taylor Test of Hand Function (JTTHF) for bimanual and unimanual function. A significant reduction in HR and an increase in HRV at post- and 3-month post-intervention was noted (χ22= 8.3, p = 0.016) along with a significant increase in 6MWT with a median increase of 81 meters (χ22= 11.0, p = 0.004) at the same interval. A significant improvement was noted in unimanual and bimanual performance following the intervention. An intensive hybrid program effectively improved CARS function as well as walking endurance and upper extremity function in children with UCP (213).

  15. Random Constraint Satisfaction Problems

    Directory of Open Access Journals (Sweden)

    Amin Coja-Oghlan

    2009-11-01

    Full Text Available Random instances of constraint satisfaction problems such as k-SAT provide challenging benchmarks. If there are m constraints over n variables there is typically a large range of densities r=m/n where solutions are known to exist with probability close to one due to non-constructive arguments. However, no algorithms are known to find solutions efficiently with a non-vanishing probability at even much lower densities. This fact appears to be related to a phase transition in the set of all solutions. The goal of this extended abstract is to provide a perspective on this phenomenon, and on the computational challenge that it poses.

  16. Exploring the Spatial-Temporal Disparities of Urban Land Use Economic Efficiency in China and Its Influencing Factors under Environmental Constraints Based on a Sequential Slacks-Based Model

    Directory of Open Access Journals (Sweden)

    Hualin Xie

    2015-07-01

    Full Text Available Using a sequential slack-based measure (SSBM model, this paper analyzes the spatiotemporal disparities of urban land use economic efficiency (ULUEE under environmental constraints, and its influencing factors in 270 cities across China from 2003–2012. The main results are as follows: (1 The average ULUEE for Chinese cities is only 0.411, and out of the 270 cities, only six cities are always efficient in urban land use in the study period. Most cities have a lot of room to improve the economic output of secondary and tertiary industries, as well as environmental protection work; (2 The eastern region of China enjoys the highest ULUEE, followed by the western and central regions. Super-scale cities show the best performance of all four city scales, followed by large-scale, small-scale and medium-scale cities. Cities with relatively developed economies and less pollutant discharge always have better ULUEE; (3 The results of slack variables analysis show that most cities have problems such as the labor surplus, over-development, excessive pollutant discharge, economic output shortage, and unreasonable use of funds is the most serious one; (4 The regression results of the influencing factors show that improvements of the per capita GDP and land use intensity are helpful to raise ULUEE. The urbanization rate and the proportion of foreign enterprises’ output account for the total output in the secondary and tertiary industries only have the same effect in some regions and city scales. The land management policy and land leasing policy have negative impact on the ULUEE in all the three regions and four city scales; (5 Some targeted policy goals are proposed, including the reduction of surplus labor, and pay more attention to environmental protection. Most importantly, effective implementation of land management policies from the central government, and stopping blind leasing of land to make up the local government’s financial deficit would be very

  17. Constraint-based scheduling applying constraint programming to scheduling problems

    CERN Document Server

    Baptiste, Philippe; Nuijten, Wim

    2001-01-01

    Constraint Programming is a problem-solving paradigm that establishes a clear distinction between two pivotal aspects of a problem: (1) a precise definition of the constraints that define the problem to be solved and (2) the algorithms and heuristics enabling the selection of decisions to solve the problem. It is because of these capabilities that Constraint Programming is increasingly being employed as a problem-solving tool to solve scheduling problems. Hence the development of Constraint-Based Scheduling as a field of study. The aim of this book is to provide an overview of the most widely used Constraint-Based Scheduling techniques. Following the principles of Constraint Programming, the book consists of three distinct parts: The first chapter introduces the basic principles of Constraint Programming and provides a model of the constraints that are the most often encountered in scheduling problems. Chapters 2, 3, 4, and 5 are focused on the propagation of resource constraints, which usually are responsibl...

  18. The effects of perceived leisure constraints among Korean university students

    Science.gov (United States)

    Sae-Sook Oh; Sei-Yi Oh; Linda L. Caldwell

    2002-01-01

    This study is based on Crawford, Jackson, and Godbey's model of leisure constraints (1991), and examines the relationships between the influences of perceived constraints, frequency of participation, and health status in the context of leisure-time outdoor activities. The study was based on a sample of 234 Korean university students. This study provides further...

  19. Neural crest contributions to the lamprey head

    Science.gov (United States)

    McCauley, David W.; Bronner-Fraser, Marianne

    2003-01-01

    The neural crest is a vertebrate-specific cell population that contributes to the facial skeleton and other derivatives. We have performed focal DiI injection into the cranial neural tube of the developing lamprey in order to follow the migratory pathways of discrete groups of cells from origin to destination and to compare neural crest migratory pathways in a basal vertebrate to those of gnathostomes. The results show that the general pathways of cranial neural crest migration are conserved throughout the vertebrates, with cells migrating in streams analogous to the mandibular and hyoid streams. Caudal branchial neural crest cells migrate ventrally as a sheet of cells from the hindbrain and super-pharyngeal region of the neural tube and form a cylinder surrounding a core of mesoderm in each pharyngeal arch, similar to that seen in zebrafish and axolotl. In addition to these similarities, we also uncovered important differences. Migration into the presumptive caudal branchial arches of the lamprey involves both rostral and caudal movements of neural crest cells that have not been described in gnathostomes, suggesting that barriers that constrain rostrocaudal movement of cranial neural crest cells may have arisen after the agnathan/gnathostome split. Accordingly, neural crest cells from a single axial level contributed to multiple arches and there was extensive mixing between populations. There was no apparent filling of neural crest derivatives in a ventral-to-dorsal order, as has been observed in higher vertebrates, nor did we find evidence of a neural crest contribution to cranial sensory ganglia. These results suggest that migratory constraints and additional neural crest derivatives arose later in gnathostome evolution.

  20. Temporal Concurrent Constraint Programming

    DEFF Research Database (Denmark)

    Valencia, Frank Dan

    Concurrent constraint programming (ccp) is a formalism for concurrency in which agents interact with one another by telling (adding) and asking (reading) information in a shared medium. Temporal ccp extends ccp by allowing agents to be constrained by time conditions. This dissertation studies...

  1. Partially clairvoyant scheduling for aggregate constraints

    Directory of Open Access Journals (Sweden)

    K. Subramani

    2005-01-01

    constraints. In this paper, we extend the class of constraints for which partially clairvoyant schedules can be determined efficiently, to include aggregate constraints. Aggregate constraints form a strict superset of standard constraints and can be used to model performance metrics.

  2. Developmental constraint of insect audition.

    Science.gov (United States)

    Lakes-Harlan, Reinhard; Strauss, Johannes

    2006-12-12

    Insect ears contain very different numbers of sensory cells, from only one sensory cell in some moths to thousands of sensory cells, e.g. in cicadas. These differences still await functional explanation and especially the large numbers in cicadas remain puzzling. Insects of the different orders have distinct developmental sequences for the generation of auditory organs. These sensory cells might have different functions depending on the developmental stages. Here we propose that constraints arising during development are also important for the design of insect ears and might influence cell numbers of the adults. We propose that the functional requirements of the subadult stages determine the adult complement of sensory units in the auditory system of cicadas. The hypothetical larval sensory organ should function as a vibration receiver, representing a functional caenogenesis. Experiments at different levels have to be designed to test the hypothesis. Firstly, the neuroanatomy of the larval sense organ should be analyzed to detail. Secondly, the function should be unraveled neurophysiologically and behaviorally. Thirdly, the persistence of the sensory cells and the rebuilding of the sensory organ to the adult should be investigated. Usually, the evolution of insect ears is viewed with respect to physiological and neuronal mechanisms of sound perception. This view should be extended to the development of sense organs. Functional requirements during postembryonic development may act as constraints for the evolution of adult organs, as exemplified with the auditory system of cicadas.

  3. Developmental constraint of insect audition

    Directory of Open Access Journals (Sweden)

    Strauß Johannes

    2006-12-01

    Full Text Available Abstract Background Insect ears contain very different numbers of sensory cells, from only one sensory cell in some moths to thousands of sensory cells, e.g. in cicadas. These differences still await functional explanation and especially the large numbers in cicadas remain puzzling. Insects of the different orders have distinct developmental sequences for the generation of auditory organs. These sensory cells might have different functions depending on the developmental stages. Here we propose that constraints arising during development are also important for the design of insect ears and might influence cell numbers of the adults. Presentation of the hypothesis We propose that the functional requirements of the subadult stages determine the adult complement of sensory units in the auditory system of cicadas. The hypothetical larval sensory organ should function as a vibration receiver, representing a functional caenogenesis. Testing the hypothesis Experiments at different levels have to be designed to test the hypothesis. Firstly, the neuroanatomy of the larval sense organ should be analyzed to detail. Secondly, the function should be unraveled neurophysiologically and behaviorally. Thirdly, the persistence of the sensory cells and the rebuilding of the sensory organ to the adult should be investigated. Implications of the hypothesis Usually, the evolution of insect ears is viewed with respect to physiological and neuronal mechanisms of sound perception. This view should be extended to the development of sense organs. Functional requirements during postembryonic development may act as constraints for the evolution of adult organs, as exemplified with the auditory system of cicadas.

  4. The influence of emotional priming on the neural substrates of memory: a prospective fMRI study using portrait art stimuli.

    Science.gov (United States)

    Baeken, Chris; De Raedt, Rudi; Van Schuerbeek, Peter; De Mey, Johan; Bossuyt, Axel; Luypaert, Robert

    2012-07-16

    Events coupled with an emotional context seem to be better retained than non-emotional events. The aim of our study was to investigate whether an emotional context could influence the neural substrates of memory associations with novel portrait art stimuli. In the current prospective fMRI study, we have investigated for one specific visual art form (modern artistic portraits with a high degree of abstraction) whether memory is influenced by priming with emotional facial pictures. In total forty healthy female volunteers in the same age range were recruited for the study. Twenty of these women participated in a prospective brain imaging memory paradigm and were asked to memorize a series of similar looking, but different portraits. After randomization, for twelve participants (Group 1), a third of the portraits was emotionally primed with approach-related pictures (smiling baby faces), a third with withdrawal-related pictures (baby faces with severe dermatological conditions), and another third with neutral images. Group 2 consisted of eight participants and they were not primed. Then, during an fMRI session 2h later, these portraits were viewed in random order intermixed with a set of new (previously unseen) ones, and the participants had to decide for each portrait whether or not they had already been seen. In a separate experiment, a different sample of twenty healthy females (Group 3) rated their mood after being exposed to the same art stimuli, without priming. The portraits did not evoke significant mood changes by themselves, supporting their initial neutral emotional character (Group 3). The correct decision on whether the portraits were Familiar of Unfamiliar led to similar neuronal activations in brain areas implicated in visual and attention processing for both groups (Groups 1 and 2). In contrast, whereas primed participants showed significant higher neuronal activities in the left midline superior frontal cortex (Brodmann area (BA) 6), unprimed

  5. Stereo, Shading, and Surfaces: Curvature Constraints Couple Neural Computations

    Science.gov (United States)

    2014-04-23

    reinforce weak or missing responses. How might con- straints ci;j be designed for such a task? Do they resemble third-order edge statistics? We apply...image into cortical coordinates [Fig. 6(b) and (d)] reveals a rich connection to Gestalt principles [121]. Good continuation [125] for curvesVthat slow... gestalt laws for the perceptual organization of contours,’’ J. Vis., vol. 2, no. 4, 2002, DOI: 10.1167/2.4.5. [28] J. H. Elder and R. M. Goldberg

  6. Leukemia inhibitory factor (LIF) enhances MAP2 + and HUC/D + neurons and influences neurite extension during differentiation of neural progenitors derived from human embryonic stem cells.

    Science.gov (United States)

    Leukemia Inhibitory Factor (L1F), a member of the Interleukin 6 cytokine family, has a role in differentiation of Human Neural Progenitor (hNP) cells in vitro. hNP cells, derived from Human Embryonic Stem (hES) cells, have an unlimited capacity for self-renewal in monolayer cultu...

  7. The DNA glycosylases OGG1 and NEIL3 influence differentiation potential, proliferation, and senescence-associated signs in neural stem cells

    Energy Technology Data Exchange (ETDEWEB)

    Reis, Amilcar [Linnaeus Center in Developmental Biology for Regenerative Medicine (DBRM), Department of Neuroscience, Karolinska Institutet, SE 17177 Stockholm (Sweden); Hermanson, Ola, E-mail: ola.hermanson@ki.se [Linnaeus Center in Developmental Biology for Regenerative Medicine (DBRM), Department of Neuroscience, Karolinska Institutet, SE 17177 Stockholm (Sweden)

    2012-07-13

    Highlights: Black-Right-Pointing-Pointer DNA glycosylases OGG1 and NEIL3 are required for neural stem cell state. Black-Right-Pointing-Pointer No effect on cell viability by OGG1 or NEIL3 knockdown in neural stem cells. Black-Right-Pointing-Pointer OGG1 or NEIL3 RNA knockdown result in decreased proliferation and differentiation. Black-Right-Pointing-Pointer Increased HP1{gamma} immunoreactivity after NEIL3 knockdown suggests premature senescence. -- Abstract: Embryonic neural stem cells (NSCs) exhibit self-renewal and multipotency as intrinsic characteristics that are key parameters for proper brain development. When cells are challenged by oxidative stress agents the resulting DNA lesions are repaired by DNA glycosylases through the base excision repair (BER) pathway as a means to maintain the fidelity of the genome, and thus, proper cellular characteristics. The functional roles for DNA glycosylases in NSCs have however remained largely unexplored. Here we demonstrate that RNA knockdown of the DNA glycosylases OGG1 and NEIL3 decreased NSC differentiation ability and resulted in decreased expression of both neuronal and astrocytic genes after mitogen withdrawal, as well as the stem cell marker Musashi-1. Furthermore, while cell survival remained unaffected, NEIL3 deficient cells displayed decreased cell proliferation rates along with an increase in HP1{gamma} immunoreactivity, a sign of premature senescence. Our results suggest that DNA glycosylases play multiple roles in governing essential neural stem cell characteristics.

  8. Robustness of the ATLAS pixel clustering neural network algorithm

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00407780; The ATLAS collaboration

    2016-01-01

    Proton-proton collisions at the energy frontier puts strong constraints on track reconstruction algorithms. In the ATLAS track reconstruction algorithm, an artificial neural network is utilised to identify and split clusters of neighbouring read-out elements in the ATLAS pixel detector created by multiple charged particles. The robustness of the neural network algorithm is presented, probing its sensitivity to uncertainties in the detector conditions. The robustness is studied by evaluating the stability of the algorithm's performance under a range of variations in the inputs to the neural networks. Within reasonable variation magnitudes, the neural networks prove to be robust to most variation types.

  9. The NCL natural constraint language

    CERN Document Server

    Zhou, Jianyang

    2012-01-01

    This book presents the Natural Constraint Language (NCL) language, a description language in conventional mathematical logic for modeling and solving constraint satisfaction problems. It uses illustrations and tutorials to detail NCL and its applications.

  10. Neural Networks

    Directory of Open Access Journals (Sweden)

    Schwindling Jerome

    2010-04-01

    Full Text Available This course presents an overview of the concepts of the neural networks and their aplication in the framework of High energy physics analyses. After a brief introduction on the concept of neural networks, the concept is explained in the frame of neuro-biology, introducing the concept of multi-layer perceptron, learning and their use as data classifer. The concept is then presented in a second part using in more details the mathematical approach focussing on typical use cases faced in particle physics. Finally, the last part presents the best way to use such statistical tools in view of event classifers, putting the emphasis on the setup of the multi-layer perceptron. The full article (15 p. corresponding to this lecture is written in french and is provided in the proceedings of the book SOS 2008.

  11. Optimal neural computations require analog processors

    Energy Technology Data Exchange (ETDEWEB)

    Beiu, V.

    1998-12-31

    This paper discusses some of the limitations of hardware implementations of neural networks. The authors start by presenting neural structures and their biological inspirations, while mentioning the simplifications leading to artificial neural networks. Further, the focus will be on hardware imposed constraints. They will present recent results for three different alternatives of parallel implementations of neural networks: digital circuits, threshold gate circuits, and analog circuits. The area and the delay will be related to the neurons` fan-in and to the precision of their synaptic weights. The main conclusion is that hardware-efficient solutions require analog computations, and suggests the following two alternatives: (i) cope with the limitations imposed by silicon, by speeding up the computation of the elementary silicon neurons; (2) investigate solutions which would allow the use of the third dimension (e.g. using optical interconnections).

  12. The neural crest and neural crest cells: discovery and significance ...

    Indian Academy of Sciences (India)

    PRAKASH KUMAR

    such as sea urchins, flies, fish and humans. (ii) Embryos (and so larvae and adults) form by differentiation from these germ layers. (iii) Homologous structures in different animals arise from the same germ layers. The germ-layer theory exerted a profound influence on those claiming a neural crest — that is, an ectodermal.

  13. Perceived Constraints on Recreational Sport Participation: Investigating Their Relationship with Intrinsic Motivation, Extrinsic Motivation and Amotivation.

    Science.gov (United States)

    Alexandris, Konstantinos; Tsorbatzoudis, Charalambos; Grouios, George

    2002-01-01

    Investigated the influence of constraint dimensions on intrinsic motivation, extrinsic motivation, and amotivation among Greek adults who reported participation in some type of sport and physical activity. Data from the Sport Motivation Scale and leisure constraints questionnaire revealed that intrapersonal constraints acted as de-motivating…

  14. [Establishment of an artificial neural network model for analysis of the influence of climate factors on the density of Aedes albopictus].

    Science.gov (United States)

    Yu, De-xian; Lin, Li-feng; Luo, Lei; Zhou, Wen; Gao, Lu-lu; Chen, Qing; Yu, Shou-yi

    2010-07-01

    To establish a model for predicting the density of Aedes albopictus based on the climate factors. The data of Aedes albopictus density and climate changes from 1995 to 2001 in Guangzhou were collected and analyzed. The predicting model for Aedes albopictus density was established using the Artificial Neural Network Toolbox of Matlab 7.0 software package. The climate factors used to establish the model included the average monthly pressure, evaporation capacity, relative humidity, sunshine hour, temperature, wind speed, and precipitation, and the established model was tested and verified. The BP network model was established according to data of mosquito density and climate factors. After training the neural network for 25 times, the error of performance decreased from 0.305 539 to 2.937 51x10(-14). Verification of the model with the data of mosquito density showed a concordance rate of prediction of 80%. The neural network model based on the climate factors is effective for predicting Aedes albopictus density.

  15. Minimal investment risk of a portfolio optimization problem with budget and investment concentration constraints

    Science.gov (United States)

    Shinzato, Takashi

    2017-02-01

    In the present paper, the minimal investment risk for a portfolio optimization problem with imposed budget and investment concentration constraints is considered using replica analysis. Since the minimal investment risk is influenced by the investment concentration constraint (as well as the budget constraint), it is intuitive that the minimal investment risk for the problem with an investment concentration constraint can be larger than that without the constraint (that is, with only the budget constraint). Moreover, a numerical experiment shows the effectiveness of our proposed analysis. In contrast, the standard operations research approach failed to identify accurately the minimal investment risk of the portfolio optimization problem.

  16. Design with Nonlinear Constraints

    KAUST Repository

    Tang, Chengcheng

    2015-12-10

    Most modern industrial and architectural designs need to satisfy the requirements of their targeted performance and respect the limitations of available fabrication technologies. At the same time, they should reflect the artistic considerations and personal taste of the designers, which cannot be simply formulated as optimization goals with single best solutions. This thesis aims at a general, flexible yet e cient computational framework for interactive creation, exploration and discovery of serviceable, constructible, and stylish designs. By formulating nonlinear engineering considerations as linear or quadratic expressions by introducing auxiliary variables, the constrained space could be e ciently accessed by the proposed algorithm Guided Projection, with the guidance of aesthetic formulations. The approach is introduced through applications in different scenarios, its effectiveness is demonstrated by examples that were difficult or even impossible to be computationally designed before. The first application is the design of meshes under both geometric and static constraints, including self-supporting polyhedral meshes that are not height fields. Then, with a formulation bridging mesh based and spline based representations, the application is extended to developable surfaces including origami with curved creases. Finally, general approaches to extend hard constraints and soft energies are discussed, followed by a concluding remark outlooking possible future studies.

  17. Neural Tube Defects

    Science.gov (United States)

    ... vitamin, before and during pregnancy prevents most neural tube defects. Neural tube defects are usually diagnosed before the infant is ... or imaging tests. There is no cure for neural tube defects. The nerve damage and loss of function ...

  18. Overlapping constraint for variational surface reconstruction

    DEFF Research Database (Denmark)

    Aanæs, Henrik; Solem, J.E.

    2005-01-01

    In this paper a counter example, illustrating a shortcoming in most variational formulations for 3D surface estimation, is presented. The nature of this shortcoming is a lack of an overlapping constraint. A remedy for this shortcoming is presented in the form of a penalty function with an analysi...... of the effects of this function on surface motion. For practical purposes, this will only have minor influence on current methods. However, the insight provided in the analysis is likely to influence future developments in the field of variational surface reconstruction....

  19. Constraints and Ambiguity

    DEFF Research Database (Denmark)

    Dove, Graham; Biskjær, Michael Mose; Lundqvist, Caroline Emilie

    2017-01-01

    Developing creative abilities is an important part of 21st century skills, and yet remains challenging. In this paper we describe a study investigating small-scale creative strategies that groups of Scandinavian high school students use when collaboratively building LEGO models. We recorded thirty...... groups of students building three models each. We studied groups building with traditional plastic bricks and also using a digital environment. The building tasks students undertake, and our subsequent analysis, are informed by the role constraints and ambiguity play in creative processes. Based...... on the insights we gained, we present three strategies for designing tools and environments that support students as they develop creative skills. These strategies relate to: tools and materials, mutual learning, and reflection...

  20. Relative constraints and evolution

    Science.gov (United States)

    Ochoa, Juan G. Diaz

    2014-03-01

    Several mathematical models of evolving systems assume that changes in the micro-states are constrained to the search of an optimal value in a local or global objective function. However, the concept of evolution requires a continuous change in the environment and species, making difficult the definition of absolute optimal values in objective functions. In this paper, we define constraints that are not absolute but relative to local micro-states, introducing a rupture in the invariance of the phase space of the system. This conceptual basis is useful to define alternative mathematical models for biological (or in general complex) evolving systems. We illustrate this concept with a modified Ising model, which can be useful to understand and model problems like the somatic evolution of cancer.

  1. Complex movement patterns: modifiability and constraints.

    Science.gov (United States)

    Bout, R G

    1998-01-01

    Most behaviours involve complex morphological systems and vice versa morphological systems are used by the organism in many different ways. During evolution and ontogeny changes in kinematics and function of skeletal and muscular systems must be coordinated with changes in their neural control. Neuromotor patterns are sometimes believed to be conserved in evolution, leading to diversification at the level of musculoskeletal design. Vertebrate motor patterns used in feeding are reviewed to examine this hypothesis. Stereotyped behaviour is not necessarily the result of phylogenetic constraints but may also result from the functional demands imposed by the mechanics of the jaw apparatus and the nature of the task performed. Sensory feedback and descending control not only contribute to 'online' control of movement but also shape the development of motor patterns and learning behaviour and indicate a potentially large flexibility. The neural and sensory apparatus that produces this flexibility will be subject to evolutionary modification. In the absence of a demand for flexibility motor patterns may become stereotyped in some species, while they are very flexible in others. To the extent that morphological systems perform independent movements during different behaviours, separate basic motor patterns may be required, which may be coordinated in different ways.

  2. An Introduction to 'Creativity Constraints'

    DEFF Research Database (Denmark)

    Onarheim, Balder; Biskjaer, Michael Mose

    Constraints play a vital role as both restrainers and enablers in innovation processes by governing what the creative agent/s can and cannot do, and what the output can and cannot be. Notions of constraints are common in creativity research, but current contributions are highly dispersed due to n...... and sub-concepts, including ‘late’, ‘self-imposed’, and ‘continua of creativity constraints’, to inform future cross-disciplinary work on creativity constraints....

  3. Solving Sudoku with Constraint Programming

    Science.gov (United States)

    Crawford, Broderick; Castro, Carlos; Monfroy, Eric

    Constraint Programming (CP) is a powerful paradigm for modeling and solving Complex Combinatorial Problems (generally issued from Decision Making). In this work, we model the known Sudoku puzzle as a Constraint Satisfaction Problems and solve it with CP comparing the performance of different Variable and Value Selection Heuristics in its Enumeration phase. We encourage this kind of benchmark problem because it may suggest new techniques in constraint modeling and solving of complex systems, or aid the understanding of its main advantages and limits.

  4. Constraint-Based Categorial Grammar

    CERN Document Server

    Bouma, G; Bouma, Gosse; Noord, Gertjan van

    1994-01-01

    We propose a generalization of Categorial Grammar in which lexical categories are defined by means of recursive constraints. In particular, the introduction of relational constraints allows one to capture the effects of (recursive) lexical rules in a computationally attractive manner. We illustrate the linguistic merits of the new approach by showing how it accounts for the syntax of Dutch cross-serial dependencies and the position and scope of adjuncts in such constructions. Delayed evaluation is used to process grammars containing recursive constraints.

  5. [Neural repair].

    Science.gov (United States)

    Kitada, Masaaki; Dezawa, Mari

    2008-05-01

    Recent progress of stem cell biology gives us the hope for neural repair. We have established methods to specifically induce functional Schwann cells and neurons from bone marrow stromal cells (MSCs). The effectiveness of these induced cells was evaluated by grafting them either into peripheral nerve injury, spinal cord injury, or Parkinson' s disease animal models. MSCs-derived Schwann cells supported axonal regeneration and re-constructed myelin to facilitate the functional recovery in peripheral and spinal cord injury. MSCs-derived dopaminergic neurons integrated into host striatum and contributed to behavioral repair. In this review, we introduce the differentiation potential of MSCs and finally discuss about their benefits and drawbacks of these induction systems for cell-based therapy in neuro-traumatic and neuro-degenerative diseases.

  6. Minimal Flavor Constraints for Technicolor

    DEFF Research Database (Denmark)

    Sakuma, Hidenori; Sannino, Francesco

    2010-01-01

    We analyze the constraints on the the vacuum polarization of the standard model gauge bosons from a minimal set of flavor observables valid for a general class of models of dynamical electroweak symmetry breaking. We will show that the constraints have a strong impact on the self-coupling and mas......We analyze the constraints on the the vacuum polarization of the standard model gauge bosons from a minimal set of flavor observables valid for a general class of models of dynamical electroweak symmetry breaking. We will show that the constraints have a strong impact on the self...

  7. Deepening Contractions and Collateral Constraints

    DEFF Research Database (Denmark)

    Jensen, Henrik; Ravn, Søren Hove; Santoro, Emiliano

    and occasionally non-binding credit constraints. Easier credit access increases the likelihood that constraints become slack in the face of expansionary shocks, while contractionary shocks are further amplified due to tighter constraints. As a result, busts gradually become deeper than booms. Based...... on the differential impact that occasionally non-binding constraints exert on the shape of expansions and contractions, we are also able to reconcile a more negatively skewed business cycle with a moderation in its volatility. Finally, our model can account for an intrinsic feature of economic downturns preceded...

  8. Activation of Group II Metabotropic Glutamate Receptors Increases Proliferation but does not Influence Neuronal Differentiation of a Human Neural Stem Cell Line

    DEFF Research Database (Denmark)

    Dindler, Anne; Blaabjerg, Morten; Kamand, Morad

    2018-01-01

    The multiple functions of glutamate include regulation of neural development and stem cells. While the importance of the ionotropic glutamate receptors is well established, less is known about the role of metabotropic glutamate receptors (mGluRs). In this study, we examined the effects of pharmac......The multiple functions of glutamate include regulation of neural development and stem cells. While the importance of the ionotropic glutamate receptors is well established, less is known about the role of metabotropic glutamate receptors (mGluRs). In this study, we examined the effects...... number was not related to cell viability. Subsequent differentiation of the cells resulted in a slight decrease in beta-tubulin III-positive neurons (5.2% to 3.2% of total cells) for DCG-IV pre-treated cultures. Treatment with DCG-IV and LY342495 during cell differentiation alone had no such effect....../3 during cell proliferation. This article is protected by copyright. All rights reserved....

  9. Implicit Motives and Men’s Perceived Constraint in Fatherhood

    Directory of Open Access Journals (Sweden)

    Jessica Ruppen

    2016-11-01

    Full Text Available Research shows that implicit motives influence social relationships. However, little is known about their role in fatherhood and, particularly, how men experience their paternal role. Therefore, this study examined the association of implicit motives and fathers’ perceived constraint due to fatherhood. Furthermore, we explored their relation to fathers’ life satisfaction. Participants were fathers with biological children (N = 276. They were asked to write picture stories, which were then coded for implicit affiliation and power motives. Perceived constraint and life satisfaction were assessed on a visual analog scale. A higher implicit need for affiliation was significantly associated with lower perceived constraint, whereas the implicit need for power had the opposite effect. Perceived constraint had a negative influence on life satisfaction. Structural equation modeling revealed significant indirect effects of implicit affiliation and power motives on life satisfaction mediated by perceived constraint. Our findings indicate that men with a higher implicit need for affiliation experience less constraint due to fatherhood, resulting in higher life satisfaction. The implicit need for power, however, results in more perceived constraint and is related to decreased life satisfaction.

  10. Modifier constraint in alkali borophosphate glasses using topological constraint theory

    Energy Technology Data Exchange (ETDEWEB)

    Li, Xiang [Key Laboratory for Ultrafine Materials of Ministry of Education, School of Materials Science and Engineering, East China University of Science and Technology, Shanghai 200237 (China); Zeng, Huidan, E-mail: hdzeng@ecust.edu.cn [Key Laboratory for Ultrafine Materials of Ministry of Education, School of Materials Science and Engineering, East China University of Science and Technology, Shanghai 200237 (China); Jiang, Qi [Key Laboratory for Ultrafine Materials of Ministry of Education, School of Materials Science and Engineering, East China University of Science and Technology, Shanghai 200237 (China); Zhao, Donghui [Unifrax Corporation, Niagara Falls, NY 14305 (United States); Chen, Guorong [Key Laboratory for Ultrafine Materials of Ministry of Education, School of Materials Science and Engineering, East China University of Science and Technology, Shanghai 200237 (China); Wang, Zhaofeng; Sun, Luyi [Department of Chemical & Biomolecular Engineering and Polymer Program, Institute of Materials Science, University of Connecticut, Storrs, CT 06269 (United States); Chen, Jianding [Key Laboratory for Ultrafine Materials of Ministry of Education, School of Materials Science and Engineering, East China University of Science and Technology, Shanghai 200237 (China)

    2016-12-01

    In recent years, composition-dependent properties of glasses have been successfully predicted using the topological constraint theory. The constraints of the glass network are derived from two main parts: network formers and network modifiers. The constraints of the network formers can be calculated on the basis of the topological structure of the glass. However, the latter cannot be accurately calculated in this way, because of the existing of ionic bonds. In this paper, the constraints of the modifier ions in phosphate glasses were thoroughly investigated using the topological constraint theory. The results show that the constraints of the modifier ions are gradually increased with the addition of alkali oxides. Furthermore, an improved topological constraint theory for borophosphate glasses is proposed by taking the composition-dependent constraints of the network modifiers into consideration. The proposed theory is subsequently evaluated by analyzing the composition dependence of the glass transition temperature in alkali borophosphate glasses. This method is supposed to be extended to other similar glass systems containing alkali ions.

  11. The Neural Crest in Cardiac Congenital Anomalies

    Science.gov (United States)

    Keyte, Anna; Hutson, Mary Redmond

    2012-01-01

    This review discusses the function of neural crest as they relate to cardiovascular defects. The cardiac neural crest cells are a subpopulation of cranial neural crest discovered nearly 30 years ago by ablation of premigratory neural crest. The cardiac neural crest cells are necessary for normal cardiovascular development. We begin with a description of the crest cells in normal development, including their function in remodeling the pharyngeal arch arteries, outflow tract septation, valvulogenesis, and development of the cardiac conduction system. The cells are also responsible for modulating signaling in the caudal pharynx, including the second heart field. Many of the molecular pathways that are known to influence specification, migration, patterning and final targeting of the cardiac neural crest cells are reviewed. The cardiac neural crest cells play a critical role in the pathogenesis of various human cardiocraniofacial syndromes such as DiGeorge, Velocardiofacial, CHARGE, Fetal Alcohol, Alagille, LEOPARD, and Noonan syndromes, as well as Retinoic Acid Embryopathy. The loss of neural crest cells or their dysfunction may not always directly cause abnormal cardiovascular development, but are involved secondarily because crest cells represent a major component in the complex tissue interactions in the head, pharynx and outflow tract. Thus many of the human syndromes linking defects in the heart, face and brain can be better understood when considered within the context of a single cardiocraniofacial developmental module with the neural crest being a key cell type that interconnects the regions. PMID:22595346

  12. Bureaucratic Dilemmas: Civil Servants between Political Responsiveness and Normative Constraints

    DEFF Research Database (Denmark)

    Opstrup, Niels; Christensen, Jørgen Grønnegård

    2017-01-01

    by norms that define the correct behavior when the civil service provides ministers with political advice and assistance. Organizational factors strongly influence civil servants’ behavior when they have to balance responsiveness against constraints on their role as political advisers. Moreover, civil...... servants working closely with ministers pay more attention to legal constraints than their peers among agency officials and specialists. Agency officials and specialists are much more prone to prioritize professional standards. We argue that this pattern can be generalized West European systems....

  13. Subgradient-based neural networks for nonsmooth nonconvex optimization problems.

    Science.gov (United States)

    Bian, Wei; Xue, Xiaoping

    2009-06-01

    This paper presents a subgradient-based neural network to solve a nonsmooth nonconvex optimization problem with a nonsmooth nonconvex objective function, a class of affine equality constraints, and a class of nonsmooth convex inequality constraints. The proposed neural network is modeled with a differential inclusion. Under a suitable assumption on the constraint set and a proper assumption on the objective function, it is proved that for a sufficiently large penalty parameter, there exists a unique global solution to the neural network and the trajectory of the network can reach the feasible region in finite time and stay there thereafter. It is proved that the trajectory of the neural network converges to the set which consists of the equilibrium points of the neural network, and coincides with the set which consists of the critical points of the objective function in the feasible region. A condition is given to ensure the convergence to the equilibrium point set in finite time. Moreover, under suitable assumptions, the coincidence between the solution to the differential inclusion and the "slow solution" of it is also proved. Furthermore, three typical examples are given to present the effectiveness of the theoretic results obtained in this paper and the good performance of the proposed neural network.

  14. Recent advances in neural recording microsystems.

    Science.gov (United States)

    Gosselin, Benoit

    2011-01-01

    The accelerating pace of research in neuroscience has created a considerable demand for neural interfacing microsystems capable of monitoring the activity of large groups of neurons. These emerging tools have revealed a tremendous potential for the advancement of knowledge in brain research and for the development of useful clinical applications. They can extract the relevant control signals directly from the brain enabling individuals with severe disabilities to communicate their intentions to other devices, like computers or various prostheses. Such microsystems are self-contained devices composed of a neural probe attached with an integrated circuit for extracting neural signals from multiple channels, and transferring the data outside the body. The greatest challenge facing development of such emerging devices into viable clinical systems involves addressing their small form factor and low-power consumption constraints, while providing superior resolution. In this paper, we survey the recent progress in the design and the implementation of multi-channel neural recording Microsystems, with particular emphasis on the design of recording and telemetry electronics. An overview of the numerous neural signal modalities is given and the existing microsystem topologies are covered. We present energy-efficient sensory circuits to retrieve weak signals from neural probes and we compare them. We cover data management and smart power scheduling approaches, and we review advances in low-power telemetry. Finally, we conclude by summarizing the remaining challenges and by highlighting the emerging trends in the field.

  15. Recent Advances in Neural Recording Microsystems

    Directory of Open Access Journals (Sweden)

    Benoit Gosselin

    2011-04-01

    Full Text Available The accelerating pace of research in neuroscience has created a considerable demand for neural interfacing microsystems capable of monitoring the activity of large groups of neurons. These emerging tools have revealed a tremendous potential for the advancement of knowledge in brain research and for the development of useful clinical applications. They can extract the relevant control signals directly from the brain enabling individuals with severe disabilities to communicate their intentions to other devices, like computers or various prostheses. Such microsystems are self-contained devices composed of a neural probe attached with an integrated circuit for extracting neural signals from multiple channels, and transferring the data outside the body. The greatest challenge facing development of such emerging devices into viable clinical systems involves addressing their small form factor and low-power consumption constraints, while providing superior resolution. In this paper, we survey the recent progress in the design and the implementation of multi-channel neural recording Microsystems, with particular emphasis on the design of recording and telemetry electronics. An overview of the numerous neural signal modalities is given and the existing microsystem topologies are covered. We present energy-efficient sensory circuits to retrieve weak signals from neural probes and we compare them. We cover data management and smart power scheduling approaches, and we review advances in low-power telemetry. Finally, we conclude by summarizing the remaining challenges and by highlighting the emerging trends in the field.

  16. Evaluation of crack tip constraint using photoelasticity

    Energy Technology Data Exchange (ETDEWEB)

    Ayatollahi, M.R.; Safari, H

    2003-09-01

    The method of photoelasticity has been used extensively in the past for investigating elastic stresses in cracked specimens. However, previous studies concentrate predominantly on different methods for determining the stress intensity factors. Some of these methods make use of the higher order stress terms including the T-stress to achieve more accurate experimental results for stress intensity factors. Nevertheless, the effect of T-stress on the stress fields near the crack tip has received little attention in previous photoelastic studies. In this paper, a two-parameter formulation is used to study how the T-stress influences the isochromatic fringe patterns around the tip of a mode I crack. Theoretical and experimental results obtained in this research show that the isochromatic fringes near the crack tip rotate forward and backward for negative and positive values of T-stress, respectively. Therefore, the experimental technique of photoelasticity can be used to distinguish low constraint cracked components from high constraint ones.

  17. A new one-layer neural network for linear and quadratic programming.

    Science.gov (United States)

    Gao, Xingbao; Liao, Li-Zhi

    2010-06-01

    In this paper, we present a new neural network for solving linear and quadratic programming problems in real time by introducing some new vectors. The proposed neural network is stable in the sense of Lyapunov and can converge to an exact optimal solution of the original problem when the objective function is convex on the set defined by equality constraints. Compared with existing one-layer neural networks for quadratic programming problems, the proposed neural network has the least neurons and requires weak stability conditions. The validity and transient behavior of the proposed neural network are demonstrated by some simulation results.

  18. Neural Approaches to Machine Consciousness

    Science.gov (United States)

    Aleksander, Igor; Eng., F. R.

    2008-10-01

    `Machine Consciousness', which some years ago might have been suppressed as an inappropriate pursuit, has come out of the closet and is now a legitimate area of research concern. This paper briefly surveys the last few years of worldwide research in this area which divides into rule-based and neural approaches and then reviews the work of the author's laboratory during the last ten years. The paper develops a fresh perspective on this work: it is argued that neural approaches, in this case, digital neural systems, can address phenomenological consciousness. Important clarifications of phenomenology and virtuality which enter this modelling are explained in the early parts of the paper. In neural models, phenomenology is a form of depictive inner representation that has five specific axiomatic features: a sense of self-presence in an external world; a sense of imagination of past experience and fiction; a sense of attention; a capacity for planning; a sense of emotion-based volition that influences planning. It is shown that these five features have separate but integrated support in dynamic neural systems.

  19. Constraint Programming for Context Comprehension

    DEFF Research Database (Denmark)

    Christiansen, Henning

    2014-01-01

    A close similarity is demonstrated between context comprehension, such as discourse analysis, and constraint programming. The constraint store takes the role of a growing knowledge base learned throughout the discourse, and a suitable con- straint solver does the job of incorporating new pieces...

  20. Constraints in vector meson photoproduction

    Energy Technology Data Exchange (ETDEWEB)

    Kloet, W. M.; Tabakin, F

    2000-01-31

    Constraints are discussed for spin observables extracted from photoproduction of vector mesons. These constraints originate from positivity of the spin density matrix and should be part of any future analysis of experimental data. Spin observables need to be defined in the photon-nucleon c.m. frame.

  1. Constraints in Vector Meson Photoproduction

    Science.gov (United States)

    Kloet, W. M.; Tabakin, F.

    2000-01-01

    Constraints are discussed for spin observables extracted from photoproduction of vector mesons. These constraints originate from positivity of the spin density matrix and should be part of any future analysis of experimental data. Spin observables need to be defined in the photon-nucleon c.m. frame.

  2. Thermodynamic Constraints Improve Metabolic Networks.

    Science.gov (United States)

    Krumholz, Elias W; Libourel, Igor G L

    2017-08-08

    In pursuit of establishing a realistic metabolic phenotypic space, the reversibility of reactions is thermodynamically constrained in modern metabolic networks. The reversibility constraints follow from heuristic thermodynamic poise approximations that take anticipated cellular metabolite concentration ranges into account. Because constraints reduce the feasible space, draft metabolic network reconstructions may need more extensive reconciliation, and a larger number of genes may become essential. Notwithstanding ubiquitous application, the effect of reversibility constraints on the predictive capabilities of metabolic networks has not been investigated in detail. Instead, work has focused on the implementation and validation of the thermodynamic poise calculation itself. With the advance of fast linear programming-based network reconciliation, the effects of reversibility constraints on network reconciliation and gene essentiality predictions have become feasible and are the subject of this study. Networks with thermodynamically informed reversibility constraints outperformed gene essentiality predictions compared to networks that were constrained with randomly shuffled constraints. Unconstrained networks predicted gene essentiality as accurately as thermodynamically constrained networks, but predicted substantially fewer essential genes. Networks that were reconciled with sequence similarity data and strongly enforced reversibility constraints outperformed all other networks. We conclude that metabolic network analysis confirmed the validity of the thermodynamic constraints, and that thermodynamic poise information is actionable during network reconciliation. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  3. Fixed Costs and Hours Constraints

    Science.gov (United States)

    Johnson, William R.

    2011-01-01

    Hours constraints are typically identified by worker responses to questions asking whether they would prefer a job with more hours and more pay or fewer hours and less pay. Because jobs with different hours but the same rate of pay may be infeasible when there are fixed costs of employment or mandatory overtime premia, the constraint in those…

  4. Weighted Constraints in Fuzzy Optimization

    NARCIS (Netherlands)

    U. Kaymak (Uzay); J.M. Sousa

    2001-01-01

    textabstractMany practical optimization problems are characterized by some flexibility in the problem constraints, where this flexibility can be exploited for additional trade-off between improving the objective function and satisfying the constraints. Especially in decision making, this type of

  5. Market segmentation using perceived constraints

    Science.gov (United States)

    Jinhee Jun; Gerard Kyle; Andrew Mowen

    2008-01-01

    We examined the practical utility of segmenting potential visitors to Cleveland Metroparks using their constraint profiles. Our analysis identified three segments based on their scores on the dimensions of constraints: Other priorities--visitors who scored the highest on 'other priorities' dimension; Highly Constrained--visitors who scored relatively high on...

  6. Integrity Constraints in Trust Management

    NARCIS (Netherlands)

    Etalle, Sandro; Winsborough, William H.

    We introduce the use, monitoring, and enforcement of integrity constraints in trust managementstyle authorization systems. We consider what portions of the policy state must be monitored to detect violations of integrity constraints. Then we address the fact that not all participants in a trust

  7. Genetic, epigenetic, and environmental contributions to neural tube closure.

    Science.gov (United States)

    Wilde, Jonathan J; Petersen, Juliette R; Niswander, Lee

    2014-01-01

    The formation of the embryonic brain and spinal cord begins as the neural plate bends to form the neural folds, which meet and adhere to close the neural tube. The neural ectoderm and surrounding tissues also coordinate proliferation, differentiation, and patterning. This highly orchestrated process is susceptible to disruption, leading to neural tube defects (NTDs), a common birth defect. Here, we highlight genetic and epigenetic contributions to neural tube closure. We describe an online database we created as a resource for researchers, geneticists, and clinicians. Neural tube closure is sensitive to environmental influences, and we discuss disruptive causes, preventative measures, and possible mechanisms. New technologies will move beyond candidate genes in small cohort studies toward unbiased discoveries in sporadic NTD cases. This will uncover the genetic complexity of NTDs and critical gene-gene interactions. Animal models can reveal the causative nature of genetic variants, the genetic interrelationships, and the mechanisms underlying environmental influences.

  8. Conservation constraints on random matrices

    CERN Document Server

    Ma Wen Jong; Hsieh, J

    2003-01-01

    We study the random matrices constrained by the summation rules that are present in the Hessian of the potential energy surface in the instantaneous normal mode calculations, as a result of momentum conservation. In this paper, we analyse the properties related to such conservation constraints in two classes of real symmetric matrices: one with purely row-wise summation rules and the other with the constraints on the blocks of each matrix, which underscores partially the spatial dimension. We show explicitly that the constraints are removable by separating the degrees of freedom of the zero-eigenvalue modes. The non-spectral degrees of freedom under the constraints can be realized in terms of the ordinary constraint-free orthogonal symmetry but with the rank deducted by the block dimension. We propose that the ensemble of real symmetric matrices with full randomness, constrained by the summation rules, is equivalent to the Gaussian orthogonal ensemble (GOE) with lowered rank. Independent of the joint probabil...

  9. Efficient Searching with Linear Constraints

    DEFF Research Database (Denmark)

    Agarwal, Pankaj K.; Arge, Lars Allan; Erickson, Jeff

    2000-01-01

    We show how to preprocess a set S of points in d into an external memory data structure that efficiently supports linear-constraint queries. Each query is in the form of a linear constraint xd a0+∑d−1i=1 aixi; the data structure must report all the points of S that satisfy the constraint...... space and answers linear-constraint queries using an optimal number of I/Os in the worst case. For d=3, we present a near-linear-size data structure that answers queries using an optimal number of I/Os on the average. We present linear-size data structures that can answer d-dimensional linear-constraint...

  10. The influence of information status on pronoun resolution in Mandarin Chinese: Evidence from ERPs

    Directory of Open Access Journals (Sweden)

    Xiaodong eXu

    2015-07-01

    Full Text Available The purpose of this study is to shed light on the neural mechanisms underlying the modulation of pronoun resolution processes by the information status of the antecedent. Information status was manipulated by using a structurally-based constraint (e.g., order of mention as well as a pragmatically-based constraint (i.e., topichood. We found that the pronouns referring to topic entities (the initial NP in SOV structure in Experiment 1 and OSV structure in Experiment 2 elicited attenuated P600 responses compared to the pronouns referring to non-topic entities (the initial NP in SVO structure or the second NP in OSV structure in both experiments when potential interference from structural constraints was controlled. The linear structural constraint, namely the order of mention, had no clear influence on the P600 effect when the syntactic structural constraint was held constant (i.e., when both entities were syntactic subjects, regardless of whether one (Experiment 1 or two (Experiment 2 animate antecedents were present. These findings suggest that pragmatically encoded features such as topichood and givenness can be processed separately from structural constraints such as order of mention to promote the salient status of a referent and thereby facilitate pronoun interpretation.

  11. An Evolutionary Optimization Framework for Neural Networks and Neuromorphic Architectures

    Energy Technology Data Exchange (ETDEWEB)

    Schuman, Catherine D [ORNL; Plank, James [University of Tennessee (UT); Disney, Adam [University of Tennessee (UT); Reynolds, John [University of Tennessee (UT)

    2016-01-01

    As new neural network and neuromorphic architectures are being developed, new training methods that operate within the constraints of the new architectures are required. Evolutionary optimization (EO) is a convenient training method for new architectures. In this work, we review a spiking neural network architecture and a neuromorphic architecture, and we describe an EO training framework for these architectures. We present the results of this training framework on four classification data sets and compare those results to other neural network and neuromorphic implementations. We also discuss how this EO framework may be extended to other architectures.

  12. LSF restoration by means of a neural network

    CERN Document Server

    Burstein, P

    1999-01-01

    The LSF restoration problem is written as a Maximum Entropy one, where the constraint on the restoration energy is dictated by the 'Discrepancy Principle'. The ME solution is found by means of a continuous-Hopfield neural network which reduces the energy of the output misfit, and maximizes the restoration entropy at the same time. A positive learning parameter controls the constraint compliance. Prior knowledge insertion into the net's algorithm, such as prior LSF models, upper bounds, etc. is presented. Simulations, both with computer generated and experimental data are carried out. The results are compared to those of the Least Squares method. Sensitivity of constraint fulfillment is analyzed.

  13. Vocabulary Constraint on Texts

    Directory of Open Access Journals (Sweden)

    C. Sutarsyah

    2008-01-01

    Full Text Available This case study was carried out in the English Education Department of State University of Malang. The aim of the study was to identify and describe the vocabulary in the reading text and to seek if the text is useful for reading skill development. A descriptive qualitative design was applied to obtain the data. For this purpose, some available computer programs were used to find the description of vocabulary in the texts. It was found that the 20 texts containing 7,945 words are dominated by low frequency words which account for 16.97% of the words in the texts. The high frequency words occurring in the texts were dominated by function words. In the case of word levels, it was found that the texts have very limited number of words from GSL (General Service List of English Words (West, 1953. The proportion of the first 1,000 words of GSL only accounts for 44.6%. The data also show that the texts contain too large proportion of words which are not in the three levels (the first 2,000 and UWL. These words account for 26.44% of the running words in the texts.  It is believed that the constraints are due to the selection of the texts which are made of a series of short-unrelated texts. This kind of text is subject to the accumulation of low frequency words especially those of content words and limited of words from GSL. It could also defeat the development of students' reading skills and vocabulary enrichment.

  14. A Novel Neural Network for Generally Constrained Variational Inequalities.

    Science.gov (United States)

    Gao, Xingbao; Liao, Li-Zhi

    2017-09-01

    This paper presents a novel neural network for solving generally constrained variational inequality problems by constructing a system of double projection equations. By defining proper convex energy functions, the proposed neural network is proved to be stable in the sense of Lyapunov and converges to an exact solution of the original problem for any starting point under the weaker cocoercivity condition or the monotonicity condition of the gradient mapping on the linear equation set. Furthermore, two sufficient conditions are provided to ensure the stability of the proposed neural network for a special case. The proposed model overcomes some shortcomings of existing continuous-time neural networks for constrained variational inequality, and its stability only requires some monotonicity conditions of the underlying mapping and the concavity of nonlinear inequality constraints on the equation set. The validity and transient behavior of the proposed neural network are demonstrated by some simulation results.

  15. CONSTRAINT PROGRAMMING AND UNIVERSITY TIMETABLING

    Directory of Open Access Journals (Sweden)

    G.W. Groves

    2012-01-01

    Full Text Available

    ENGLISH ABSTRACT: The technology of Constraint Programming is rapidly becoming a popular alternative for solving large-scale industry problems. This paper provides an introduction to Constraint Programming and to Constraint Logic Programming (CLP, an enabler of constraint programming. The use of Constraint Logic Programming is demonstrated by describing a system developed for scheduling university timetables. Timetabling problems have a high degree of algorithmic complexity (they are usually NP-Complete, and share features with scheduling problems encountered in industry. The system allows the declaration of both hard requirements, which must always be satisfied, and soft constraints which need not be satisfied, though this would be an advantage.

    AFRIKAANSE OPSOMMING: Hierdie artikel beskryf ’n familie van probleem-oplossingstegnieke bekend as “Constraint Programming”, wat al hoe meer gebruik word om groot-skaalse industriële probleme op te los. Die nut van hierdie tegnieke word gedemonstreer deur die beskrywing van ’n skeduleringsisteem om die roosters vir ’n universiteit te genereer. Roosterskeduleringsprobleme is in praktiese gevalle NP-volledig en deel baie eienskappe met industriële skeduleringsprobleme. Die sisteem wat hier beskryf word maak gebruik van beide harde beperkings (wat altyd bevredig moet word en sagte beperkings (bevrediging hiervan is wel voordelig maar dit is opsioneel.

  16. Analysis of optical flow constraints.

    Science.gov (United States)

    Del Bimbo, A; Nesi, P; Sanz, J C

    1995-01-01

    Different constraint equations have been proposed in the literature for the derivation of optical flow. Despite of the large number of papers dealing with computational techniques to estimate optical flow, only a few authors have investigated conditions under which these constraints exactly model the velocity field, that is, the perspective projection on the image plane of the true 3-D velocity. These conditions are analyzed under different hypotheses, and the departures of the constraint equations in modeling the velocity field are derived for different motion conditions. Experiments are also presented giving measures of these departures and of the induced errors in the estimation of the velocity field.

  17. Testing for a cultural influence on reading for meaning in the developing brain: the neural basis of semantic processing in Chinese children

    Directory of Open Access Journals (Sweden)

    Tai-Li Chou

    2009-11-01

    Full Text Available Functional magnetic resonance imaging (fMRI was used to explore the neural correlates of semantic judgments in a group of 8- to 15-year-old Chinese children. Participants were asked to indicate if pairs of Chinese characters presented visually were related in meaning. The related pairs were arranged in a continuous variable according to association strength. Pairs of characters with weaker semantic association elicited greater activation in the mid ventral region (BA 45 of left inferior frontal gyrus, suggesting increased demands on the process of selecting appropriate semantic features. By contrast, characters with stronger semantic association elicited greater activation in left inferior parietal lobule (BA 39, suggesting stronger integration of highly related features. In addition, there was a developmental increase, similar to previously reported findings in English, in left posterior middle temporal gyrus (BA 21, suggesting that older children have more elaborated semantic representations. There were additional age-related increases in the posterior region of left inferior parietal lobule and in the ventral regions of left inferior frontal gyrus, suggesting that reading acquisition relies more on the mapping from orthography to semantics in Chinese children as compared to previously reported findings in English.

  18. RBF neural network based H∞ H∞ H∞ synchronization for ...

    Indian Academy of Sciences (India)

    Based on this neural network and linear matrix inequality (LMI) formulation, the RBFNNHS controller and the learning laws are presented to reduce the effect of disturbance to an H ∞ norm constraint. It is shown that finding the RBFNNHS controller and the learning laws can be transformed into the LMI problem and solved ...

  19. Topology Optimization with Stress Constraints

    NARCIS (Netherlands)

    Verbart, A.

    2015-01-01

    This thesis contains contributions to the development of topology optimization techniques capable of handling stress constraints. The research that led to these contributions was motivated by the need for topology optimization techniques more suitable for industrial applications. Currently, topology

  20. Decentralized systems with design constraints

    CERN Document Server

    Mahmoud, Magdi S

    2014-01-01

    This volume provides a rigorous examination of the analysis, stability and control of large-scale systems, and addresses the difficulties that arise because of dimensionality, information structure constraints, parametric uncertainty and time-delays.

  1. An Introduction to 'Creativity Constraints'

    DEFF Research Database (Denmark)

    Onarheim, Balder; Biskjær, Michael Mose

    2013-01-01

    Constraints play a vital role as both restrainers and enablers in innovation processes by governing what the creative agent/s can and cannot do, and what the output can and cannot be. Notions of constraints are common in creativity research, but current contributions are highly dispersed due...... to no overall conceptual framing or shared terminology. This lack of unity hinders overt opportunities for cross-disciplinary interchange. We argue that an improved understanding of constraints in creativity holds a promising potential for advancements in creativity research across domains and disciplines. Here......, we give an overview of the growing, but incohesive body of research into creativity and constraints, which leads us to introduce ‘creativity constraints’ as a unifying concept to help bridge these disjoint contributions to facilitate crossdisciplinary interchange. Finally, we suggest key topics...

  2. Can Leverage Constraints Help Investors?

    OpenAIRE

    Heimer, Rawley

    2014-01-01

    This paper provides causal evidence that leverage constraints can reduce the underperformance of individual investors. In accordance with Dodd-Frank, the CFTC was given regulatory authority over the retail market for foreign exchange and capped the maximum permissible leverage available to U.S. traders. By comparing U.S. traders on the same brokerages with their unregulated European counterparts, I show that the leverage constraint reduces average per-trade losses even after adjusting for ris...

  3. Risk Sharing under Incentive Constraints.

    OpenAIRE

    Wagner, W.B.

    2002-01-01

    In addressing the matter, this thesis covers issues such as the welfare gains from international risk sharing, the impact of international risk sharing on national economic policies and production efficiency, the welfare effects of international risk sharing in the presence of tax competition, and risk sharing among entrepreneurs that face financing constraints. The thesis outlines the implications of incentive constraints for the efficiency of the actual extent and pattern of risk sharing am...

  4. Introduction to neural networks

    CERN Document Server

    James, Frederick E

    1994-02-02

    1. Introduction and overview of Artificial Neural Networks. 2,3. The Feed-forward Network as an inverse Problem, and results on the computational complexity of network training. 4.Physics applications of neural networks.

  5. Morphological neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Ritter, G.X.; Sussner, P. [Univ. of Florida, Gainesville, FL (United States)

    1996-12-31

    The theory of artificial neural networks has been successfully applied to a wide variety of pattern recognition problems. In this theory, the first step in computing the next state of a neuron or in performing the next layer neural network computation involves the linear operation of multiplying neural values by their synaptic strengths and adding the results. Thresholding usually follows the linear operation in order to provide for nonlinearity of the network. In this paper we introduce a novel class of neural networks, called morphological neural networks, in which the operations of multiplication and addition are replaced by addition and maximum (or minimum), respectively. By taking the maximum (or minimum) of sums instead of the sum of products, morphological network computation is nonlinear before thresholding. As a consequence, the properties of morphological neural networks are drastically different than those of traditional neural network models. In this paper we consider some of these differences and provide some particular examples of morphological neural network.

  6. Social and Contextual Constraints on Embodied Perception.

    Science.gov (United States)

    Schnall, Simone

    2017-03-01

    A number of papers have challenged research on physiological and psychological influences on perception by claiming to show that such findings can be explained by nonperceptual factors such as demand characteristics. Relatedly, calls for separating perception from judgment have been issued. However, such efforts fail to consider key processes known to shape judgment processes: people's inability to report accurately on their judgments, conversational dynamics of experimental research contexts, and misattribution and discounting processes. Indeed, the fact that initially observed effects of embodied influences disappear is predicted by an extensive amount of literature on judgments studied within social psychology. Thus, findings from such studies suggest that the initially presumed underlying processes are at work-namely, functional considerations that are informative in the context of preparing the body for action. In this article, I provide suggestions on how to conduct research on perception within the social constraints of experimental contexts.

  7. Artificial Neural Network Based Model for Forecasting of Inflation in India

    Directory of Open Access Journals (Sweden)

    Gour Sundar Mitra Thakur

    2016-03-01

    Full Text Available Inflation can be attributed to both microeconomic and macroeconomic factors which influence the stability of the economy of any nation. With the raising of recession at the end of the year 2008, world communities started paying much contemplation on inflation and put enormous hard work to predict it accurately. Prediction of inflation is not a simple task. Moreover, the behavior of inflation is so complex and uncertain that both economists and statisticians have been striving to model and forecast inflation in an accurate way. As a result, many researchers have proposed inflation forecasting models based on different methods; however the accuracy is always being a major constraint. In this paper, we have analyzed the historical monthly economic data of India between January 2000 and December 2012 and constructed an inflation forecasting model based on feed forward back propagation neural network. Initially some critical factors that can considerably influence the inflation of India have been identified, then an efficient artificial neural network (ANN model has been proposed to forecast the inflation. Accuracy of the model is proved to be satisfactory when compared with the forecasting of some well-known agencies.

  8. The theory of reasoned action as parallel constraint satisfaction: towards a dynamic computational model of health behavior.

    Science.gov (United States)

    Orr, Mark G; Thrush, Roxanne; Plaut, David C

    2013-01-01

    The reasoned action approach, although ubiquitous in health behavior theory (e.g., Theory of Reasoned Action/Planned Behavior), does not adequately address two key dynamical aspects of health behavior: learning and the effect of immediate social context (i.e., social influence). To remedy this, we put forth a computational implementation of the Theory of Reasoned Action (TRA) using artificial-neural networks. Our model re-conceptualized behavioral intention as arising from a dynamic constraint satisfaction mechanism among a set of beliefs. In two simulations, we show that constraint satisfaction can simultaneously incorporate the effects of past experience (via learning) with the effects of immediate social context to yield behavioral intention, i.e., intention is dynamically constructed from both an individual's pre-existing belief structure and the beliefs of others in the individual's social context. In a third simulation, we illustrate the predictive ability of the model with respect to empirically derived behavioral intention. As the first known computational model of health behavior, it represents a significant advance in theory towards understanding the dynamics of health behavior. Furthermore, our approach may inform the development of population-level agent-based models of health behavior that aim to incorporate psychological theory into models of population dynamics.

  9. The theory of reasoned action as parallel constraint satisfaction: towards a dynamic computational model of health behavior.

    Directory of Open Access Journals (Sweden)

    Mark G Orr

    Full Text Available The reasoned action approach, although ubiquitous in health behavior theory (e.g., Theory of Reasoned Action/Planned Behavior, does not adequately address two key dynamical aspects of health behavior: learning and the effect of immediate social context (i.e., social influence. To remedy this, we put forth a computational implementation of the Theory of Reasoned Action (TRA using artificial-neural networks. Our model re-conceptualized behavioral intention as arising from a dynamic constraint satisfaction mechanism among a set of beliefs. In two simulations, we show that constraint satisfaction can simultaneously incorporate the effects of past experience (via learning with the effects of immediate social context to yield behavioral intention, i.e., intention is dynamically constructed from both an individual's pre-existing belief structure and the beliefs of others in the individual's social context. In a third simulation, we illustrate the predictive ability of the model with respect to empirically derived behavioral intention. As the first known computational model of health behavior, it represents a significant advance in theory towards understanding the dynamics of health behavior. Furthermore, our approach may inform the development of population-level agent-based models of health behavior that aim to incorporate psychological theory into models of population dynamics.

  10. Multisensory constraints on awareness

    Science.gov (United States)

    Deroy, Ophelia; Chen, Yi-Chuan; Spence, Charles

    2014-01-01

    Given that multiple senses are often stimulated at the same time, perceptual awareness is most likely to take place in multisensory situations. However, theories of awareness are based on studies and models established for a single sense (mostly vision). Here, we consider the methodological and theoretical challenges raised by taking a multisensory perspective on perceptual awareness. First, we consider how well tasks designed to study unisensory awareness perform when used in multisensory settings, stressing that studies using binocular rivalry, bistable figure perception, continuous flash suppression, the attentional blink, repetition blindness and backward masking can demonstrate multisensory influences on unisensory awareness, but fall short of tackling multisensory awareness directly. Studies interested in the latter phenomenon rely on a method of subjective contrast and can, at best, delineate conditions under which individuals report experiencing a multisensory object or two unisensory objects. As there is not a perfect match between these conditions and those in which multisensory integration and binding occur, the link between awareness and binding advocated for visual information processing needs to be revised for multisensory cases. These challenges point at the need to question the very idea of multisensory awareness. PMID:24639579

  11. A novel neural dynamical approach to convex quadratic program and its efficient applications.

    Science.gov (United States)

    Xia, Youshen; Sun, Changyin

    2009-12-01

    This paper proposes a novel neural dynamical approach to a class of convex quadratic programming problems where the number of variables is larger than the number of equality constraints. The proposed continuous-time and proposed discrete-time neural dynamical approach are guaranteed to be globally convergent to an optimal solution. Moreover, the number of its neurons is equal to the number of equality constraints. In contrast, the number of neurons in existing neural dynamical methods is at least the number of the variables. Therefore, the proposed neural dynamical approach has a low computational complexity. Compared with conventional numerical optimization methods, the proposed discrete-time neural dynamical approach reduces multiplication operation per iteration and has a large computational step length. Computational examples and two efficient applications to signal processing and robot control further confirm the good performance of the proposed approach.

  12. Returns, productivity and constraints analyses of cassava/maize ...

    African Journals Online (AJOL)

    The study was conducted in Isi-Uzo LGA of Enugu State, and evaluated the productivity and profitability of cassava/maize/melon mixed cropping with the aim to determine the degree and direction of influence of the production factors and identification of constraints militating against the enterprise. Multistage and purposive ...

  13. Female Involvement in Physical Recreation. Gender Role as a Constraint.

    Science.gov (United States)

    Kane, Mary Jo

    1990-01-01

    Female socialization, through the influence of gender as a social institution, acts as a powerful constraint on women's involvement in physical recreation. The contribution made to this socialization by young children's play behavior and the link between gender-role conformity and dual career women's lack of leisure are discussed. (IAH)

  14. Effect Of Credit Constraint On Production Efficiency Of Farm ...

    African Journals Online (AJOL)

    Credit constraint in agriculture affects not only the purchasing power of producers to procure farm inputs and to cover operating costs in the short run, but also their capacity to make farm-related investments as well as risk behavior in technology choice and adoption. These, in turn, influence technical efficiencies of the ...

  15. Constraint programming and decision making

    CERN Document Server

    Kreinovich, Vladik

    2014-01-01

    In many application areas, it is necessary to make effective decisions under constraints. Several area-specific techniques are known for such decision problems; however, because these techniques are area-specific, it is not easy to apply each technique to other applications areas. Cross-fertilization between different application areas is one of the main objectives of the annual International Workshops on Constraint Programming and Decision Making. Those workshops, held in the US (El Paso, Texas), in Europe (Lyon, France), and in Asia (Novosibirsk, Russia), from 2008 to 2012, have attracted researchers and practitioners from all over the world. This volume presents extended versions of selected papers from those workshops. These papers deal with all stages of decision making under constraints: (1) formulating the problem of multi-criteria decision making in precise terms, (2) determining when the corresponding decision problem is algorithmically solvable; (3) finding the corresponding algorithms, and making...

  16. Non-invasive neural stimulation

    Science.gov (United States)

    Tyler, William J.; Sanguinetti, Joseph L.; Fini, Maria; Hool, Nicholas

    2017-05-01

    Neurotechnologies for non-invasively interfacing with neural circuits have been evolving from those capable of sensing neural activity to those capable of restoring and enhancing human brain function. Generally referred to as non-invasive neural stimulation (NINS) methods, these neuromodulation approaches rely on electrical, magnetic, photonic, and acoustic or ultrasonic energy to influence nervous system activity, brain function, and behavior. Evidence that has been surmounting for decades shows that advanced neural engineering of NINS technologies will indeed transform the way humans treat diseases, interact with information, communicate, and learn. The physics underlying the ability of various NINS methods to modulate nervous system activity can be quite different from one another depending on the energy modality used as we briefly discuss. For members of commercial and defense industry sectors that have not traditionally engaged in neuroscience research and development, the science, engineering and technology required to advance NINS methods beyond the state-of-the-art presents tremendous opportunities. Within the past few years alone there have been large increases in global investments made by federal agencies, foundations, private investors and multinational corporations to develop advanced applications of NINS technologies. Driven by these efforts NINS methods and devices have recently been introduced to mass markets via the consumer electronics industry. Further, NINS continues to be explored in a growing number of defense applications focused on enhancing human dimensions. The present paper provides a brief introduction to the field of non-invasive neural stimulation by highlighting some of the more common methods in use or under current development today.

  17. Magnetotail dynamics under isobaric constraints

    Science.gov (United States)

    Birn, Joachim; Schindler, Karl; Janicke, Lutz; Hesse, Michael

    1994-01-01

    Using linear theory and nonlinear MHD simulations, we investigate the resistive and ideal MHD stability of two-dimensional plasma configurations under the isobaric constraint dP/dt = 0, which in ideal MHD is equivalent to conserving the pressure function P = P(A), where A denotes the magnetic flux. This constraint is satisfied for incompressible modes, such as Alfven waves, and for systems undergoing energy losses. The linear stability analysis leads to a Schroedinger equation, which can be investigated by standard quantum mechanics procedures. We present an application to a typical stretched magnetotail configuration. For a one-dimensional sheet equilibrium characteristic properties of tearing instability are rediscovered. However, the maximum growth rate scales with the 1/7 power of the resistivity, which implies much faster growth than for the standard tearing mode (assuming that the resistivity is small). The same basic eigen-mode is found also for weakly two-dimensional equilibria, even in the ideal MHD limit. In this case the growth rate scales with the 1/4 power of the normal magnetic field. The results of the linear stability analysis are confirmed qualitatively by nonlinear dynamic MHD simulations. These results suggest the interesting possibility that substorm onset, or the thinning in the late growth phase, is caused by the release of a thermodynamic constraint without the (immediate) necessity of releasing the ideal MHD constraint. In the nonlinear regime the resistive and ideal developments differ in that the ideal mode does not lead to neutral line formation without the further release of the ideal MHD constraint; instead a thin current sheet forms. The isobaric constraint is critically discussed. Under perhaps more realistic adiabatic conditions the ideal mode appears to be stable but could be driven by external perturbations and thus generate the thin current sheet in the late growth phase, before a nonideal instability sets in.

  18. Effect of Auditory Constraints on Motor Learning Depends on Stage of Recovery Post Stroke

    Directory of Open Access Journals (Sweden)

    Viswanath eAluru

    2014-06-01

    Full Text Available In order to develop evidence-based rehabilitation protocols post stroke, one must first reconcile the vast heterogeneity in the post-stroke population and develop protocols to facilitate motor learning in the various subgroups. The main purpose of this study is to show that auditory constraints interact with the stage of recovery post stroke to influence motor learning. We characterized the stages of upper limb recovery using task-based kinematic measures in twenty subjects with chronic hemiparesis, and used a bimanual wrist extension task using a custom-made wrist trainer to facilitate learning of wrist extension in the paretic hand under four auditory conditions: 1 without auditory cueing; 2 to non-musical happy sounds; 3 to self-selected music; and 4 to a metronome beat set at a comfortable tempo. Two bimanual trials (15 s each were followed by one unimanual trial with the paretic hand over six cycles under each condition. Clinical metrics, wrist and arm kinematics and electromyographic activity were recorded. Hierarchical cluster analysis with the Mahalanobis metric based on baseline speed and extent of wrist movement stratified subjects into three distinct groups which reflected their stage of recovery: spastic paresis, spastic co-contraction, and minimal paresis. In spastic paresis, the metronome beat increased wrist extension, but also increased muscle co-activation across the wrist. In contrast, in spastic co-contraction, no auditory stimulation increased wrist extension and reduced co-activation. In minimal paresis, wrist extension did not improve under any condition. The results suggest that auditory task constraints interact with stage of recovery during motor learning after stroke, perhaps due to recruitment of distinct neural substrates over the course of recovery. The findings advance our understanding of the mechanisms of progression of motor recovery and lay the foundation for personalized treatment algorithms post stroke.

  19. Health care input constraints and cost effectiveness analysis decision rules.

    Science.gov (United States)

    van Baal, Pieter; Morton, Alec; Severens, Johan L

    2018-01-27

    Results of cost effectiveness analyses (CEA) studies are most useful for decision makers if they face only one constraint: the health care budget. However, in practice, decision makers wishing to use the results of CEA studies may face multiple resource constraints relating to, for instance, constraints in health care inputs such as a shortage of skilled labour. The presence of multiple resource constraints influences the decision rules of CEA and limits the usefulness of traditional CEA studies for decision makers. The goal of this paper is to illustrate how results of CEA can be interpreted and used in case a decision maker faces a health care input constraint. We set up a theoretical model describing the optimal allocation of the health care budget in the presence of a health care input constraint. Insights derived from that model were used to analyse a stylized example based on a decision about a surgical robot as well as a published cost effectiveness study on eye care services in Zambia. Our theoretical model shows that applying default decision rules in the presence of a health care input constraint leads to suboptimal decisions but that there are ways of preserving the traditional decision rules of CEA by reweighing different cost categories. The examples illustrate how such adjustments can be made, and makes clear that optimal decisions depend crucially on such adjustments. We conclude that it is possible to use the results of cost effectiveness studies in the presence of health care input constraints if results are properly adjusted. Copyright © 2018 The Author(s). Published by Elsevier Ltd.. All rights reserved.

  20. New Constraints on Quantum Theories

    Directory of Open Access Journals (Sweden)

    Comay E.

    2013-04-01

    Full Text Available Hierarchical relationships between physical theories are discussed. It is explained how a lower rank theory imposes constraints on an acceptable structure of its higher rank theory. This principle is applied to the case of quantum mechanics and quantum field theory of massive particles. It is proved that the Dirac equation is consistent with these constraints whereas the Klein-Gordon equation, as well as all other second order quan- tum equations are inconsistent with the Schrödinger equation. This series of arguments undermines the theoretical structure of the Standard Model.

  1. Recurrent neural network for non-smooth convex optimization problems with application to the identification of genetic regulatory networks.

    Science.gov (United States)

    Cheng, Long; Hou, Zeng-Guang; Lin, Yingzi; Tan, Min; Zhang, Wenjun Chris; Wu, Fang-Xiang

    2011-05-01

    A recurrent neural network is proposed for solving the non-smooth convex optimization problem with the convex inequality and linear equality constraints. Since the objective function and inequality constraints may not be smooth, the Clarke's generalized gradients of the objective function and inequality constraints are employed to describe the dynamics of the proposed neural network. It is proved that the equilibrium point set of the proposed neural network is equivalent to the optimal solution of the original optimization problem by using the Lagrangian saddle-point theorem. Under weak conditions, the proposed neural network is proved to be stable, and the state of the neural network is convergent to one of its equilibrium points. Compared with the existing neural network models for non-smooth optimization problems, the proposed neural network can deal with a larger class of constraints and is not based on the penalty method. Finally, the proposed neural network is used to solve the identification problem of genetic regulatory networks, which can be transformed into a non-smooth convex optimization problem. The simulation results show the satisfactory identification accuracy, which demonstrates the effectiveness and efficiency of the proposed approach.

  2. Effects of Social Constraints on Career Maturity: The Mediating Effect of the Time Perspective

    Science.gov (United States)

    Kim, Kyung-Nyun; Oh, Se-Hee

    2013-01-01

    Previous studies have provided mixed results for the effects of social constraints on career maturity. However, there has been growing interest in these effects from the time perspective. Few studies have examined the effects of social constraints on the time perspective which in turn influences career maturity. This study examines the mediating…

  3. Evolvable Neural Software System

    Science.gov (United States)

    Curtis, Steven A.

    2009-01-01

    The Evolvable Neural Software System (ENSS) is composed of sets of Neural Basis Functions (NBFs), which can be totally autonomously created and removed according to the changing needs and requirements of the software system. The resulting structure is both hierarchical and self-similar in that a given set of NBFs may have a ruler NBF, which in turn communicates with other sets of NBFs. These sets of NBFs may function as nodes to a ruler node, which are also NBF constructs. In this manner, the synthetic neural system can exhibit the complexity, three-dimensional connectivity, and adaptability of biological neural systems. An added advantage of ENSS over a natural neural system is its ability to modify its core genetic code in response to environmental changes as reflected in needs and requirements. The neural system is fully adaptive and evolvable and is trainable before release. It continues to rewire itself while on the job. The NBF is a unique, bilevel intelligence neural system composed of a higher-level heuristic neural system (HNS) and a lower-level, autonomic neural system (ANS). Taken together, the HNS and the ANS give each NBF the complete capabilities of a biological neural system to match sensory inputs to actions. Another feature of the NBF is the Evolvable Neural Interface (ENI), which links the HNS and ANS. The ENI solves the interface problem between these two systems by actively adapting and evolving from a primitive initial state (a Neural Thread) to a complicated, operational ENI and successfully adapting to a training sequence of sensory input. This simulates the adaptation of a biological neural system in a developmental phase. Within the greater multi-NBF and multi-node ENSS, self-similar ENI s provide the basis for inter-NBF and inter-node connectivity.

  4. Constraint Programming versus Mathematical Programming

    DEFF Research Database (Denmark)

    Hansen, Jesper

    2003-01-01

    Constraint Logic Programming (CLP) is a relatively new technique from the 80's with origins in Computer Science and Artificial Intelligence. Lately, much research have been focused on ways of using CLP within the paradigm of Operations Research (OR) and vice versa. The purpose of this paper...

  5. Intertemporal consumption and credit constraints

    DEFF Research Database (Denmark)

    Leth-Petersen, Søren

    2010-01-01

    There is continuing controversy over the importance of credit constraints. This paper investigates whether total household expenditure and debt is affected by an exogenous increase in access to credit provided by a credit market reform that enabled Danish house owners to use housing equity...

  6. Conjoined Constraints and Phonological Acquisition

    Directory of Open Access Journals (Sweden)

    Giovana Bonilha

    2003-12-01

    Full Text Available Since the start of Optimality Theory (Prince & Smolensky, 1993, research on phonological acquisition has explored the explanatory potential of constraint theories. This study, also based on Optimality Theory, attempts to analyze the acquisition of CVVC syllable structure by Brazilian Portuguese children and addresses the issue of Local Conjunction (Smolensky, 1995, 1997 in research that deals with problems of phonological acquisition.

  7. Continuous Optimization on Constraint Manifolds

    Science.gov (United States)

    Dean, Edwin B.

    1988-01-01

    This paper demonstrates continuous optimization on the differentiable manifold formed by continuous constraint functions. The first order tensor geodesic differential equation is solved on the manifold in both numerical and closed analytic form for simple nonlinear programs. Advantages and disadvantages with respect to conventional optimization techniques are discussed.

  8. Sterile neutrino constraints from cosmology

    DEFF Research Database (Denmark)

    Hamann, Jan; Hannestad, Steen; Raffelt, Georg G.

    2012-01-01

    The presence of light particles beyond the standard model's three neutrino species can profoundly impact the physics of decoupling and primordial nucleosynthesis. I review the observational signatures of extra light species, present constraints from recent data, and discuss the implications of po...... of possible sterile neutrinos with O(eV)-masses for cosmology....

  9. Constraint-Based Scheduling System

    Science.gov (United States)

    Zweben, Monte; Eskey, Megan; Stock, Todd; Taylor, Will; Kanefsky, Bob; Drascher, Ellen; Deale, Michael; Daun, Brian; Davis, Gene

    1995-01-01

    Report describes continuing development of software for constraint-based scheduling system implemented eventually on massively parallel computer. Based on machine learning as means of improving scheduling. Designed to learn when to change search strategy by analyzing search progress and learning general conditions under which resource bottleneck occurs.

  10. Adaptive Neurotechnology for Making Neural Circuits Functional .

    Science.gov (United States)

    Jung, Ranu

    2008-03-01

    Two of the most important trends in recent technological developments are that technology is increasingly integrated with biological systems and that it is increasingly adaptive in its capabilities. Neuroprosthetic systems that provide lost sensorimotor function after a neural disability offer a platform to investigate this interplay between biological and engineered systems. Adaptive neurotechnology (hardware and software) could be designed to be biomimetic, guided by the physical and programmatic constraints observed in biological systems, and allow for real-time learning, stability, and error correction. An example will present biomimetic neural-network hardware that can be interfaced with the isolated spinal cord of a lower vertebrate to allow phase-locked real-time neural control. Another will present adaptive neural network control algorithms for functional electrical stimulation of the peripheral nervous system to provide desired movements of paralyzed limbs in rodents or people. Ultimately, the frontier lies in being able to utilize the adaptive neurotechnology to promote neuroplasticity in the living system on a long-time scale under co-adaptive conditions.

  11. Aeroelastic Tailoring of Transport Wings Including Transonic Flutter Constraints

    Science.gov (United States)

    Stanford, Bret K.; Wieseman, Carol D.; Jutte, Christine V.

    2015-01-01

    Several minimum-mass optimization problems are solved to evaluate the effectiveness of a variety of novel tailoring schemes for subsonic transport wings. Aeroelastic stress and panel buckling constraints are imposed across several trimmed static maneuver loads, in addition to a transonic flutter margin constraint, captured with aerodynamic influence coefficient-based tools. Tailoring with metallic thickness variations, functionally graded materials, balanced or unbalanced composite laminates, curvilinear tow steering, and distributed trailing edge control effectors are all found to provide reductions in structural wing mass with varying degrees of success. The question as to whether this wing mass reduction will offset the increased manufacturing cost is left unresolved for each case.

  12. Consciousness and neural plasticity

    DEFF Research Database (Denmark)

    In contemporary consciousness studies the phenomenon of neural plasticity has received little attention despite the fact that neural plasticity is of still increased interest in neuroscience. We will, however, argue that neural plasticity could be of great importance to consciousness studies....... If consciousness is related to neural processes it seems, at least prima facie, that the ability of the neural structures to change should be reflected in a theory of this relationship "Neural plasticity" refers to the fact that the brain can change due to its own activity. The brain is not static but rather...... a dynamic entity, which physical structure changes according to its use and environment. This change may take the form of growth of new neurons, the creation of new networks and structures, and change within network structures, that is, changes in synaptic strengths. Plasticity raises questions about...

  13. Fuzzy and neural control

    Science.gov (United States)

    Berenji, Hamid R.

    1992-01-01

    Fuzzy logic and neural networks provide new methods for designing control systems. Fuzzy logic controllers do not require a complete analytical model of a dynamic system and can provide knowledge-based heuristic controllers for ill-defined and complex systems. Neural networks can be used for learning control. In this chapter, we discuss hybrid methods using fuzzy logic and neural networks which can start with an approximate control knowledge base and refine it through reinforcement learning.

  14. Neural Systems Laboratory

    Data.gov (United States)

    Federal Laboratory Consortium — As part of the Electrical and Computer Engineering Department and The Institute for System Research, the Neural Systems Laboratory studies the functionality of the...

  15. A neural flow estimator

    DEFF Research Database (Denmark)

    Jørgensen, Ivan Harald Holger; Bogason, Gudmundur; Bruun, Erik

    1995-01-01

    is implemented using switched-current technique and is capable of estimating flow in the μl/s range. The neural estimator is built around a multiplierless neural network, containing 96 synaptic weights which are updated using the LMS1-algorithm. An experimental chip has been designed that operates at 5 V......This paper proposes a new way to estimate the flow in a micromechanical flow channel. A neural network is used to estimate the delay of random temperature fluctuations induced in a fluid. The design and implementation of a hardware efficient neural flow estimator is described. The system...

  16. Evolutionary Algorithms For Neural Networks Binary And Real Data Classification

    Directory of Open Access Journals (Sweden)

    Dr. Hanan A.R. Akkar

    2015-08-01

    Full Text Available Artificial neural networks are complex networks emulating the way human rational neurons process data. They have been widely used generally in prediction clustering classification and association. The training algorithms that used to determine the network weights are almost the most important factor that influence the neural networks performance. Recently many meta-heuristic and Evolutionary algorithms are employed to optimize neural networks weights to achieve better neural performance. This paper aims to use recently proposed algorithms for optimizing neural networks weights comparing these algorithms performance with other classical meta-heuristic algorithms used for the same purpose. However to evaluate the performance of such algorithms for training neural networks we examine such algorithms to classify four opposite binary XOR clusters and classification of continuous real data sets such as Iris and Ecoli.

  17. Project Scheduling Under Resource Constraints: Application of the Cumulative Global Constraint

    OpenAIRE

    Trojet, Mariem; H'Mida, Fehmi; Lopez, Pierre

    2009-01-01

    International audience; This paper concerns project scheduling under resource constraints. The objective is to find a solution that minimizes the project makespan, while respecting the precedence constraints and the resource constraints. The problem under consideration is modelled as a Constraint Satisfaction Problem (CSP). It is implemented under the constraint programming language CHIP V5. For modelling the resource constraints, we are particularly interested in the application of the cumul...

  18. Constraints on the wing morphology of pterosaurs.

    Science.gov (United States)

    Palmer, Colin; Dyke, Gareth

    2012-03-22

    Animals that fly must be able to do so over a huge range of aerodynamic conditions, determined by weather, wind speed and the nature of their environment. No single parameter can be used to determine-let alone measure-optimum flight performance as it relates to wing shape. Reconstructing the wings of the extinct pterosaurs has therefore proved especially problematic: these Mesozoic flying reptiles had a soft-tissue membranous flight surface that is rarely preserved in the fossil record. Here, we review basic mechanical and aerodynamic constraints that influenced the wing shape of pterosaurs, and, building on this, present a series of theoretical modelling results. These results allow us to predict the most likely wing shapes that could have been employed by these ancient reptiles, and further show that a combination of anterior sweep and a reflexed proximal wing section provides an aerodynamically balanced and efficient theoretical pterosaur wing shape, with clear benefits for their flight stability.

  19. Brain and language: evidence for neural multifunctionality.

    Science.gov (United States)

    Cahana-Amitay, Dalia; Albert, Martin L

    2014-01-01

    This review paper presents converging evidence from studies of brain damage and longitudinal studies of language in aging which supports the following thesis: the neural basis of language can best be understood by the concept of neural multifunctionality. In this paper the term "neural multifunctionality" refers to incorporation of nonlinguistic functions into language models of the intact brain, reflecting a multifunctional perspective whereby a constant and dynamic interaction exists among neural networks subserving cognitive, affective, and praxic functions with neural networks specialized for lexical retrieval, sentence comprehension, and discourse processing, giving rise to language as we know it. By way of example, we consider effects of executive system functions on aspects of semantic processing among persons with and without aphasia, as well as the interaction of executive and language functions among older adults. We conclude by indicating how this multifunctional view of brain-language relations extends to the realm of language recovery from aphasia, where evidence of the influence of nonlinguistic factors on the reshaping of neural circuitry for aphasia rehabilitation is clearly emerging.

  20. Central neural pathways for thermoregulation

    Science.gov (United States)

    Morrison, Shaun F.; Nakamura, Kazuhiro

    2010-01-01

    Central neural circuits orchestrate a homeostatic repertoire to maintain body temperature during environmental temperature challenges and to alter body temperature during the inflammatory response. This review summarizes the functional organization of the neural pathways through which cutaneous thermal receptors alter thermoregulatory effectors: the cutaneous circulation for heat loss, the brown adipose tissue, skeletal muscle and heart for thermogenesis and species-dependent mechanisms (sweating, panting and saliva spreading) for evaporative heat loss. These effectors are regulated by parallel but distinct, effector-specific neural pathways that share a common peripheral thermal sensory input. The thermal afferent circuits include cutaneous thermal receptors, spinal dorsal horn neurons and lateral parabrachial nucleus neurons projecting to the preoptic area to influence warm-sensitive, inhibitory output neurons which control thermogenesis-promoting neurons in the dorsomedial hypothalamus that project to premotor neurons in the rostral ventromedial medulla, including the raphe pallidus, that descend to provide the excitation necessary to drive thermogenic thermal effectors. A distinct population of warm-sensitive preoptic neurons controls heat loss through an inhibitory input to raphe pallidus neurons controlling cutaneous vasoconstriction. PMID:21196160

  1. Computational neural learning formalisms for manipulator inverse kinematics

    Science.gov (United States)

    Gulati, Sandeep; Barhen, Jacob; Iyengar, S. Sitharama

    1989-01-01

    An efficient, adaptive neural learning paradigm for addressing the inverse kinematics of redundant manipulators is presented. The proposed methodology exploits the infinite local stability of terminal attractors - a new class of mathematical constructs which provide unique information processing capabilities to artificial neural systems. For robotic applications, synaptic elements of such networks can rapidly acquire the kinematic invariances embedded within the presented samples. Subsequently, joint-space configurations, required to follow arbitrary end-effector trajectories, can readily be computed. In a significant departure from prior neuromorphic learning algorithms, this methodology provides mechanisms for incorporating an in-training skew to handle kinematics and environmental constraints.

  2. Quasi-Lagrangian neural network for convex quadratic optimization.

    Science.gov (United States)

    Costantini, Giovanni; Perfetti, Renzo; Todisco, Massimiliano

    2008-10-01

    A new neural network for convex quadratic optimization is presented in this brief. The proposed network can handle both equality and inequality constraints, as well as bound constraints on the optimization variables. It is based on the Lagrangian approach, but exploits a partial dual method in order to keep the number of variables at minimum. The dynamic evolution is globally convergent and the steady-state solutions satisfy the necessary and sufficient conditions of optimality. The circuit implementation is simpler with respect to existing solutions for the same class of problems. The validity of the proposed approach is verified through some simulation examples.

  3. Neural Networks: Implementations and Applications

    NARCIS (Netherlands)

    Vonk, E.; Veelenturf, L.P.J.; Jain, L.C.

    1996-01-01

    Artificial neural networks, also called neural networks, have been used successfully in many fields including engineering, science and business. This paper presents the implementation of several neural network simulators and their applications in character recognition and other engineering areas

  4. Self-Imposed Creativity Constraints

    DEFF Research Database (Denmark)

    Biskjaer, Michael Mose

    2013-01-01

    Abstract This dissertation epitomizes three years of research guided by the research question: how can we conceptualize creative self-binding as a resource in art and design processes? Concretely, the dissertation seeks to offer insight into the puzzling observation that highly skilled creative...... practitioners sometimes freely and intentionally impose rigid rules, peculiar principles, and other kinds of creative obstructions on themselves as a means to spur momentum in the process and reach a distinctly original outcome. To investigate this the dissertation is composed of four papers (Part II) framed...... of analysis. Informed by the insight that constraints both enable and restrain creative agency, the dissertation’s main contention is that creative self- binding may profitably be conceptualized as the exercise of self-imposed creativity constraints. Thus, the dissertation marks an analytical move from vague...

  5. Aggregating energy flexibilities under constraints

    DEFF Research Database (Denmark)

    Valsomatzis, Emmanouil; Pedersen, Torben Bach; Abello, Alberto

    2016-01-01

    The flexibility of individual energy prosumers (producers and/or consumers) has drawn a lot of attention in recent years. Aggregation of such flexibilities provides prosumers with the opportunity to directly participate in the energy market and at the same time reduces the complexity of scheduling...... the energy units. However, aggregated flexibility should support normal grid operation. In this paper, we build on the flex-offer (FO) concept to model the inherent flexibility of a prosumer (e.g., a single flexible consumption device such as a clothes washer). An FO captures flexibility in both time...... and amount dimensions. We define the problem of aggregating FOs taking into account grid power constraints. We also propose two constraint-based aggregation techniques that efficiently aggregate FOs while retaining flexibility. We show through a comprehensive evaluation that our techniques, in contrast...

  6. A compendium of chameleon constraints

    Science.gov (United States)

    Burrage, Clare; Sakstein, Jeremy

    2016-11-01

    The chameleon model is a scalar field theory with a screening mechanism that explains how a cosmologically relevant light scalar can avoid the constraints of intra-solar-system searches for fifth-forces. The chameleon is a popular dark energy candidate and also arises in f(R) theories of gravity. Whilst the chameleon is designed to avoid historical searches for fifth-forces it is not unobservable and much effort has gone into identifying the best observables and experiments to detect it. These results are not always presented for the same models or in the same language, a particular problem when comparing astrophysical and laboratory searches making it difficult to understand what regions of parameter space remain. Here we present combined constraints on the chameleon model from astrophysical and laboratory searches for the first time and identify the remaining windows of parameter space. We discuss the implications for cosmological chameleon searches and future small-scale probes.

  7. Managing Restaurant Tables using Constraints

    Science.gov (United States)

    Vidotto, Alfio; Brown, Kenneth N.; Beck, J. Christopher

    Restaurant table management can have significant impact on both profitability and the customer experience. The core of the issue is a complex dynamic combinatorial problem. We show how to model the problem as constraint satisfaction, with extensions which generate flexible seating plans and which maintain stability when changes occur. We describe an implemented system which provides advice to users in real time. The system is currently being evaluated in a restaurant environment.

  8. Public investment under fiscal constraints

    OpenAIRE

    Alessandro Missale; emanuele bacchiocchi; elisa borghi

    2009-01-01

    EU New Member States must comply with the Stability and Growth Pact (SGP) and the investment requirements implied by the Lisbon Agenda. However, the SGP rules may result in underinvestment or distortions in the allocation of public expenditure. This paper provides new evidence on the effects of debt sustainability and SGP fiscal constraints on government expenditure in fixed capital, education and health in OECD countries by estimating government expenditure reaction functions to public debt ...

  9. Constraint-based feature validation

    OpenAIRE

    Dohmen, M.H.P.J.

    1998-01-01

    The feature modeling paradigm combines geometric and functional product information in one model. In an ideal product development environment, multiple views of a product in terms of features coexist. Feature validation concerns the validity of the feature information in all these views, focusing on validity specification and maintenance. This thesis presents a feature validation scheme based on constraints. It enables flexible and expressive feature validity maintenance. The scheme ensures t...

  10. Memory Constraint Online Multitask Classification

    OpenAIRE

    Cavallanti, Giovanni; Cesa-Bianchi, Nicolò

    2012-01-01

    We investigate online kernel algorithms which simultaneously process multiple classification tasks while a fixed constraint is imposed on the size of their active sets. We focus in particular on the design of algorithms that can efficiently deal with problems where the number of tasks is extremely high and the task data are large scale. Two new projection-based algorithms are introduced to efficiently tackle those issues while presenting different trade offs on how the available memory is man...

  11. Feature extraction using convolutional neural network for classifying breast density in mammographic images

    Science.gov (United States)

    Thomaz, Ricardo L.; Carneiro, Pedro C.; Patrocinio, Ana C.

    2017-03-01

    Breast cancer is the leading cause of death for women in most countries. The high levels of mortality relate mostly to late diagnosis and to the direct proportionally relationship between breast density and breast cancer development. Therefore, the correct assessment of breast density is important to provide better screening for higher risk patients. However, in modern digital mammography the discrimination among breast densities is highly complex due to increased contrast and visual information for all densities. Thus, a computational system for classifying breast density might be a useful tool for aiding medical staff. Several machine-learning algorithms are already capable of classifying small number of classes with good accuracy. However, machinelearning algorithms main constraint relates to the set of features extracted and used for classification. Although well-known feature extraction techniques might provide a good set of features, it is a complex task to select an initial set during design of a classifier. Thus, we propose feature extraction using a Convolutional Neural Network (CNN) for classifying breast density by a usual machine-learning classifier. We used 307 mammographic images downsampled to 260x200 pixels to train a CNN and extract features from a deep layer. After training, the activation of 8 neurons from a deep fully connected layer are extracted and used as features. Then, these features are feedforward to a single hidden layer neural network that is cross-validated using 10-folds to classify among four classes of breast density. The global accuracy of this method is 98.4%, presenting only 1.6% of misclassification. However, the small set of samples and memory constraints required the reuse of data in both CNN and MLP-NN, therefore overfitting might have influenced the results even though we cross-validated the network. Thus, although we presented a promising method for extracting features and classifying breast density, a greater database is

  12. Physicians' responses to resource constraints.

    Science.gov (United States)

    Hurst, Samia A; Hull, Sara Chandros; DuVal, Gordon; Danis, Marion

    2005-03-28

    A common dilemma that confronts physicians in clinical practice is the allocation of scarce resources. Yet the strategies used by physicians in actual situations of resource constraint have not been studied. This study explores the strategies and rationales reported by physicians in situations of resource constraints encountered in practice. A national survey of US internists, oncologists, and intensive care specialists was performed by computer-assisted telephone interviews. As part of this survey, we asked physicians to tell us about a recent ethical dilemma encountered in practice. A subset of respondents reported difficulties regarding resource allocation. Transcripts of open-ended responses were coded for content based on consensus. Of the 600 physicians originally identified, 537 were eligible and 344 participated (response rate, 64%). Internists do not make allocation decisions alone but rather engage in negotiation in their resolution. Furthermore, these decisions are not made as dichotomous choices. Rather they often involve alternative solutions in the face of complexities of both the health care system and situations where limited resources must be allocated. Justice is not commonly the justification for rationing. Physicians' experiences in situations of resource constraints appear to be more complex than the normative literature on health care rationing assumes. In addition, reasoning about justice in health care seems to play only a small part in clinical decision making. Bridging this gap could be an important step in fostering fair allocation of resources in difficult cases.

  13. Analysis of Space Tourism Constraints

    Science.gov (United States)

    Bonnal, Christophe

    2002-01-01

    Space tourism appears today as a new Eldorado in a relatively near future. Private operators are already proposing services for leisure trips in Low Earth Orbit, and some happy few even tested them. But are these exceptional events really marking the dawn of a new space age ? The constraints associated to the space tourism are severe : - the economical balance of space tourism is tricky; development costs of large manned - the technical definition of such large vehicles is challenging, mainly when considering - the physiological aptitude of passengers will have a major impact on the mission - the orbital environment will also lead to mission constraints on aspects such as radiation, However, these constraints never appear as show-stoppers and have to be dealt with pragmatically: - what are the recommendations one can make for future research in the field of space - which typical roadmap shall one consider to develop realistically this new market ? - what are the synergies with the conventional missions and with the existing infrastructure, - how can a phased development start soon ? The paper proposes hints aiming at improving the credibility of Space Tourism and describes the orientations to follow in order to solve the major hurdles found in such an exciting development.

  14. Updating neutrino magnetic moment constraints

    Directory of Open Access Journals (Sweden)

    B.C. Cañas

    2016-02-01

    Full Text Available In this paper we provide an updated analysis of the neutrino magnetic moments (NMMs, discussing both the constraints on the magnitudes of the three transition moments Λi and the role of the CP violating phases present both in the mixing matrix and in the NMM matrix. The scattering of solar neutrinos off electrons in Borexino provides the most stringent restrictions, due to its robust statistics and the low energies observed, below 1 MeV. Our new limit on the effective neutrino magnetic moment which follows from the most recent Borexino data is 3.1×10−11μB at 90% C.L. This corresponds to the individual transition magnetic moment constraints: |Λ1|≤5.6×10−11μB, |Λ2|≤4.0×10−11μB, and |Λ3|≤3.1×10−11μB (90% C.L., irrespective of any complex phase. Indeed, the incoherent admixture of neutrino mass eigenstates present in the solar flux makes Borexino insensitive to the Majorana phases present in the NMM matrix. For this reason we also provide a global analysis including the case of reactor and accelerator neutrino sources, presenting the resulting constraints for different values of the relevant CP phases. Improved reactor and accelerator neutrino experiments will be needed in order to underpin the full profile of the neutrino electromagnetic properties.

  15. Infrared Constraint on Ultraviolet Theories

    Energy Technology Data Exchange (ETDEWEB)

    Tsai, Yuhsin [Cornell Univ., Ithaca, NY (United States)

    2012-08-01

    While our current paradigm of particle physics, the Standard Model (SM), has been extremely successful at explaining experiments, it is theoretically incomplete and must be embedded into a larger framework. In this thesis, we review the main motivations for theories beyond the SM (BSM) and the ways such theories can be constrained using low energy physics. The hierarchy problem, neutrino mass and the existence of dark matter (DM) are the main reasons why the SM is incomplete . Two of the most plausible theories that may solve the hierarchy problem are the Randall-Sundrum (RS) models and supersymmetry (SUSY). RS models usually suffer from strong flavor constraints, while SUSY models produce extra degrees of freedom that need to be hidden from current experiments. To show the importance of infrared (IR) physics constraints, we discuss the flavor bounds on the anarchic RS model in both the lepton and quark sectors. For SUSY models, we discuss the difficulties in obtaining a phenomenologically allowed gaugino mass, its relation to R-symmetry breaking, and how to build a model that avoids this problem. For the neutrino mass problem, we discuss the idea of generating small neutrino masses using compositeness. By requiring successful leptogenesis and the existence of warm dark matter (WDM), we can set various constraints on the hidden composite sector. Finally, to give an example of model independent bounds from collider experiments, we show how to constrain the DM–SM particle interactions using collider results with an effective coupling description.

  16. Computational modeling of neural plasticity for self-organization of neural networks.

    Science.gov (United States)

    Chrol-Cannon, Joseph; Jin, Yaochu

    2014-11-01

    Self-organization in biological nervous systems during the lifetime is known to largely occur through a process of plasticity that is dependent upon the spike-timing activity in connected neurons. In the field of computational neuroscience, much effort has been dedicated to building up computational models of neural plasticity to replicate experimental data. Most recently, increasing attention has been paid to understanding the role of neural plasticity in functional and structural neural self-organization, as well as its influence on the learning performance of neural networks for accomplishing machine learning tasks such as classification and regression. Although many ideas and hypothesis have been suggested, the relationship between the structure, dynamics and learning performance of neural networks remains elusive. The purpose of this article is to review the most important computational models for neural plasticity and discuss various ideas about neural plasticity's role. Finally, we suggest a few promising research directions, in particular those along the line that combines findings in computational neuroscience and systems biology, and their synergetic roles in understanding learning, memory and cognition, thereby bridging the gap between computational neuroscience, systems biology and computational intelligence. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  17. Critical Branching Neural Networks

    Science.gov (United States)

    Kello, Christopher T.

    2013-01-01

    It is now well-established that intrinsic variations in human neural and behavioral activity tend to exhibit scaling laws in their fluctuations and distributions. The meaning of these scaling laws is an ongoing matter of debate between isolable causes versus pervasive causes. A spiking neural network model is presented that self-tunes to critical…

  18. Kunstige neurale net

    DEFF Research Database (Denmark)

    Hørning, Annette

    1994-01-01

    Artiklen beskæftiger sig med muligheden for at anvende kunstige neurale net i forbindelse med datamatisk procession af naturligt sprog, specielt automatisk talegenkendelse.......Artiklen beskæftiger sig med muligheden for at anvende kunstige neurale net i forbindelse med datamatisk procession af naturligt sprog, specielt automatisk talegenkendelse....

  19. Ant colony optimization and constraint programming

    CERN Document Server

    Solnon, Christine

    2013-01-01

    Ant colony optimization is a metaheuristic which has been successfully applied to a wide range of combinatorial optimization problems. The author describes this metaheuristic and studies its efficiency for solving some hard combinatorial problems, with a specific focus on constraint programming. The text is organized into three parts. The first part introduces constraint programming, which provides high level features to declaratively model problems by means of constraints. It describes the main existing approaches for solving constraint satisfaction problems, including complete tree search

  20. Relationship between protein structure and geometrical constraints

    DEFF Research Database (Denmark)

    Lund, Ole; Hansen, Jan; Brunak, Søren

    1996-01-01

    We evaluate to what extent the structure of proteins can be deduced from incomplete knowledge of disulfide bridges, surface assignments, secondary structure assignments, and additional distance constraints. A cost function taking such constraints into account was used to obtain protein structures...... using a simple minimization algorithm. For small proteins, the approximate structure could be obtained using one additional distance constraint for each amino acid in the protein. We also studied the effect of using predicted secondary structure and surface assignments. The constraints used...

  1. Influence of the Different Primary Cancers and Different Types of Bone Metastasis on the Lesion-based Artificial Neural Network Value Calculated by a Computer-aided Diagnostic System,BONENAVI, on Bone Scintigraphy Images

    Directory of Open Access Journals (Sweden)

    TAKURO ISODA

    2017-01-01

    Full Text Available Objective(s: BONENAVI, a computer-aided diagnostic system, is used in bone scintigraphy. This system provides the artificial neural network (ANN and bone scan index (BSI values. ANN is associated with the possibility of bone metastasis, while BSI is related to the amount of bone metastasis. The degree of uptake on bone scintigraphy can be affected by the type of bone metastasis. Therefore, the ANN value provided by BONENAVI may be influenced by the characteristics of bone metastasis. In this study, we aimed to assess the relationship between ANN value and characteristics of bone metastasis. Methods: We analyzed 50 patients (36 males, 14 females; age range: 42–87 yrs, median age: 72.5 yrs with prostate, breast, or lung cancer who had undergone bone scintigraphy and were diagnosed with bone metastasis (32 cases of prostate cancer, nine cases of breast cancer, and nine cases of lung cancer. Those who had received systematic therapy over the past years were excluded. Bone metastases were diagnosed clinically, and the type of bone metastasis (osteoblastic, mildly osteoblastic,osteolytic, and mixed components was decided visually by the agreement of two radiologists. We compared the ANN values (case-based and lesion-based among the three primary cancers and four types of bone metastasis.Results: There was no significant difference in case-based ANN values among prostate, breast, and lung cancers. However, the lesion-based ANN values were the highest in cases with prostate cancer and the lowest in cases of lung cancer (median values: prostate cancer, 0.980; breast cancer, 0.909; and lung cancer, 0.864. Mildly osteoblastic lesions showed significantly lower ANN values than the other three types of bone metastasis (median values: osteoblastic, 0.939; mildly osteoblastic, 0.788; mixed type, 0.991; and osteolytic, 0.969. The possibility of a lesion-based ANN value below 0.5 was 10.9% for bone metastasis in prostate cancer, 12.9% for breast cancer, and 37

  2. Influence of the Different Primary Cancers and Different Types of Bone Metastasis on the Lesion-based Artificial Neural Network Value Calculated by a Computer-aided Diagnostic System, BONENAVI, on Bone Scintigraphy Images.

    Science.gov (United States)

    Isoda, Takuro; BaBa, Shingo; Maruoka, Yasuhiro; Kitamura, Yoshiyuki; Tahara, Keiichiro; Sasaki, Masayuki; Hatakenaka, Masamitsu; Honda, Hiroshi

    2017-01-01

    BONENAVI, a computer-aided diagnostic system, is used in bone scintigraphy. This system provides the artificial neural network (ANN) and bone scan index (BSI) values. ANN is associated with the possibility of bone metastasis, while BSI is related to the amount of bone metastasis. The degree of uptake on bone scintigraphy can be affected by the type of bone metastasis. Therefore, the ANN value provided by BONENAVI may be influenced by the characteristics of bone metastasis. In this study, we aimed to assess the relationship between ANN value and characteristics of bone metastasis. We analyzed 50 patients (36 males,14 females; age range: 87-42 yrs median age:72.5 yrs) with prostate, breast, or lung cancer who had undergone bone scintigraphy and were diagnosed with bone metastasis (32 cases of prostate cancer, nine cases of breast cancer, and nine cases of lung cancer). Those who had received systematic therapy over the past years were excluded. Bone metastases were diagnosed clinically, and the type of bone metastasis (osteoblastic, mildly osteoblastic, osteolytic, and mixed components) was decided visually by the agreement of two radiologists. We compared the ANN values (case-based and lesion-based) among the three primary cancers and four types of bone metastasis. There was no significant difference in case-based ANN values among prostate, breast, and lung cancers. However, the lesion-based ANN values were the highest in cases with prostate cancer and the lowest in cases of lung cancer (median values: prostate cancer, 0.980; breast cancer 0.909; and lung cancer, 0.864). Mildly osteoblastic lesions showed significantly lower ANN values than the other three types of bone metastasis (median values: osteoblastic,; 0.939 mildly osteoblastic; 0.788, mixed type; 0.991, and osteolytic. 0.969) The possibility of a lesion-based ANN value below 0.5 was %10.9 for bone metastasis in prostate cancer, %12.9 for breast cancer, and %37.2 for lung cancer. The corresponding

  3. Organizational Constraints on Corporate Public Relations Practitioners.

    Science.gov (United States)

    Ryan, Michael

    1987-01-01

    Catalogs various internal constraints under which many public relations practitioners work, including constraints on (1) access to management; (2) information collection; (3) dissemination of timely, accurate information; and (4) the public relations mission. Reports that most practitioners see organizational constraints as more of a problem for…

  4. Reliance on constraints means detection of information

    NARCIS (Netherlands)

    Jacobs, D.M.; Runeson, S.; Andersson, I.E.K.

    2001-01-01

    We argue four points. First, perception always relies on environmental constraints, not only in special cases. Second, constraints are taken advantage of by detecting information granted by the constraints rather than by internalizing them. Third, apparent motion phenomena reveal reliance on

  5. A general treatment of dynamic integrity constraints

    NARCIS (Netherlands)

    de Brock, EO

    This paper introduces a general, set-theoretic model for expressing dynamic integrity constraints, i.e., integrity constraints on the state changes that are allowed in a given state space. In a managerial context, such dynamic integrity constraints can be seen as representations of "real world"

  6. Stimulation and recording electrodes for neural prostheses

    CERN Document Server

    Pour Aryan, Naser; Rothermel, Albrecht

    2015-01-01

    This book provides readers with basic principles of the electrochemistry of the electrodes used in modern, implantable neural prostheses. The authors discuss the boundaries and conditions in which the electrodes continue to function properly for long time spans, which are required when designing neural stimulator devices for long-term in vivo applications. Two kinds of electrode materials, titanium nitride and iridium are discussed extensively, both qualitatively and quantitatively. The influence of the counter electrode on the safety margins and electrode lifetime in a two electrode system is explained. Electrode modeling is handled in a final chapter.

  7. A two-layer recurrent neural network for nonsmooth convex optimization problems.

    Science.gov (United States)

    Qin, Sitian; Xue, Xiaoping

    2015-06-01

    In this paper, a two-layer recurrent neural network is proposed to solve the nonsmooth convex optimization problem subject to convex inequality and linear equality constraints. Compared with existing neural network models, the proposed neural network has a low model complexity and avoids penalty parameters. It is proved that from any initial point, the state of the proposed neural network reaches the equality feasible region in finite time and stays there thereafter. Moreover, the state is unique if the initial point lies in the equality feasible region. The equilibrium point set of the proposed neural network is proved to be equivalent to the Karush-Kuhn-Tucker optimality set of the original optimization problem. It is further proved that the equilibrium point of the proposed neural network is stable in the sense of Lyapunov. Moreover, from any initial point, the state is proved to be convergent to an equilibrium point of the proposed neural network. Finally, as applications, the proposed neural network is used to solve nonlinear convex programming with linear constraints and L1 -norm minimization problems.

  8. A nonfeasible gradient projection recurrent neural network for equality-constrained optimization problems.

    Science.gov (United States)

    Barbarosou, Maria P; Maratos, Nicholas G

    2008-10-01

    In this paper, a recurrent neural network for both convex and nonconvex equality-constrained optimization problems is proposed, which makes use of a cost gradient projection onto the tangent space of the constraints. The proposed neural network constructs a generically nonfeasible trajectory, satisfying the constraints only as t --> infinity. Local convergence results are given that do not assume convexity of the optimization problem to be solved. Global convergence results are established for convex optimization problems. An exponential convergence rate is shown to hold both for the convex case and the nonconvex case. Numerical results indicate that the proposed method is efficient and accurate.

  9. Comparison of Simulation Algorithms for the Hopfield Neural Network: An Application of Economic Dispatch

    OpenAIRE

    Altun, Tankut Yalçınöz and Halis

    2014-01-01

    This paper is mainly concerned with an investigation of the suitability of Hopfield neural network structures in solving the power economic dispatch problem. For Hopfield neural network applications to this problem three important questions have been answered: what the size of the power system is; how efficient the computational method; and how to handle constraints. A new mapping process is formulated and a computational method for obtaining the weights and biases is described. A few simulat...

  10. CMOS-based Stochastically Spiking Neural Network for Optimization under Uncertainties

    Science.gov (United States)

    2017-03-01

    uncertainties. We discuss a ‘scenario generation’ circuit to non- parametrically estimate/emulate statistics of uncertain cost/constraints...are explored: (1) We discuss a ‘scenario generation’ circuit to non- parametrically estimate and emulate statistics of uncertain cost/constraints...uncertainties. The discussed mixed-signal, CMOS-based architecture of stochastically spiking neural network minimizes area/power of each cell and

  11. Improved probabilistic neural networks with self-adaptive strategies for transformer fault diagnosis problem

    Directory of Open Access Journals (Sweden)

    Jiao-Hong Yi

    2016-01-01

    Full Text Available Probabilistic neural network has successfully solved all kinds of engineering problems in various fields since it is proposed. In probabilistic neural network, Spread has great influence on its performance, and probabilistic neural network will generate bad prediction results if it is improperly selected. It is difficult to select the optimal manually. In this article, a variant of probabilistic neural network with self-adaptive strategy, called self-adaptive probabilistic neural network, is proposed. In self-adaptive probabilistic neural network, Spread can be self-adaptively adjusted and selected and then the best selected Spread is used to guide the self-adaptive probabilistic neural network train and test. In addition, two simplified strategies are incorporated into the proposed self-adaptive probabilistic neural network with the aim of further improving its performance and then two versions of simplified self-adaptive probabilistic neural network (simplified self-adaptive probabilistic neural networks 1 and 2 are proposed. The variants of self-adaptive probabilistic neural networks are further applied to solve the transformer fault diagnosis problem. By comparing them with basic probabilistic neural network, and the traditional back propagation, extreme learning machine, general regression neural network, and self-adaptive extreme learning machine, the results have experimentally proven that self-adaptive probabilistic neural networks have a more accurate prediction and better generalization performance when addressing the transformer fault diagnosis problem.

  12. Dynamics of neural cryptography.

    Science.gov (United States)

    Ruttor, Andreas; Kinzel, Wolfgang; Kanter, Ido

    2007-05-01

    Synchronization of neural networks has been used for public channel protocols in cryptography. In the case of tree parity machines the dynamics of both bidirectional synchronization and unidirectional learning is driven by attractive and repulsive stochastic forces. Thus it can be described well by a random walk model for the overlap between participating neural networks. For that purpose transition probabilities and scaling laws for the step sizes are derived analytically. Both these calculations as well as numerical simulations show that bidirectional interaction leads to full synchronization on average. In contrast, successful learning is only possible by means of fluctuations. Consequently, synchronization is much faster than learning, which is essential for the security of the neural key-exchange protocol. However, this qualitative difference between bidirectional and unidirectional interaction vanishes if tree parity machines with more than three hidden units are used, so that those neural networks are not suitable for neural cryptography. In addition, the effective number of keys which can be generated by the neural key-exchange protocol is calculated using the entropy of the weight distribution. As this quantity increases exponentially with the system size, brute-force attacks on neural cryptography can easily be made unfeasible.

  13. QPO Constraints on Neutron Stars

    Science.gov (United States)

    Miller, M. Coleman

    2005-01-01

    The kilohertz frequencies of QPOs from accreting neutron star systems imply that they are generated in regions of strong gravity, close to the star. This suggests that observations of the QPOs can be used to constrain the properties of neutron stars themselves, and in particular to inform us about the properties of cold matter beyond nuclear densities. Here we discuss some relatively model-insensitive constraints that emerge from the kilohertz QPOs, as well as recent developments that may hint at phenomena related to unstable circular orbits outside neutron stars.

  14. Varieties of the generality constraint

    Directory of Open Access Journals (Sweden)

    Lenny Clapp

    2011-12-01

    Full Text Available Since its introduction by Evans (1982, the generality constraint (GC has been invoked by various philosophers for different purposes. Our purpose here is, first, to clarify what precisely the GC states by way of an interpretive framework, the GC Schema, and second, to demonstrate in terms of this framework some problems that arise if one invokes the GC (or systematicity without clearly specifying an appropriate interpretation. By utilizing the GC Schema these sorts of problems can be avoided, and we thus propose it as a tool to facilitate argumentation that appeals to the GC.

  15. ANT Advanced Neural Tool

    Energy Technology Data Exchange (ETDEWEB)

    Labrador, I.; Carrasco, R.; Martinez, L.

    1996-07-01

    This paper describes a practical introduction to the use of Artificial Neural Networks. Artificial Neural Nets are often used as an alternative to the traditional symbolic manipulation and first order logic used in Artificial Intelligence, due the high degree of difficulty to solve problems that can not be handled by programmers using algorithmic strategies. As a particular case of Neural Net a Multilayer Perception developed by programming in C language on OS9 real time operating system is presented. A detailed description about the program structure and practical use are included. Finally, several application examples that have been treated with the tool are presented, and some suggestions about hardware implementations. (Author) 15 refs.

  16. Neural Learning Control of Flexible Joint Manipulator with Predefined Tracking Performance and Application to Baxter Robot

    Directory of Open Access Journals (Sweden)

    Min Wang

    2017-01-01

    Full Text Available This paper focuses on neural learning from adaptive neural control (ANC for a class of flexible joint manipulator under the output tracking constraint. To facilitate the design, a new transformed function is introduced to convert the constrained tracking error into unconstrained error variable. Then, a novel adaptive neural dynamic surface control scheme is proposed by combining the neural universal approximation. The proposed control scheme not only decreases the dimension of neural inputs but also reduces the number of neural approximators. Moreover, it can be verified that all the closed-loop signals are uniformly ultimately bounded and the constrained tracking error converges to a small neighborhood around zero in a finite time. Particularly, the reduction of the number of neural input variables simplifies the verification of persistent excitation (PE condition for neural networks (NNs. Subsequently, the proposed ANC scheme is verified recursively to be capable of acquiring and storing knowledge of unknown system dynamics in constant neural weights. By reusing the stored knowledge, a neural learning controller is developed for better control performance. Simulation results on a single-link flexible joint manipulator and experiment results on Baxter robot are given to illustrate the effectiveness of the proposed scheme.

  17. Neural coordination can be enhanced by occasional interruption of normal firing patterns: a self-optimizing spiking neural network model.

    Science.gov (United States)

    Woodward, Alexander; Froese, Tom; Ikegami, Takashi

    2015-02-01

    The state space of a conventional Hopfield network typically exhibits many different attractors of which only a small subset satisfies constraints between neurons in a globally optimal fashion. It has recently been demonstrated that combining Hebbian learning with occasional alterations of normal neural states avoids this problem by means of self-organized enlargement of the best basins of attraction. However, so far it is not clear to what extent this process of self-optimization is also operative in real brains. Here we demonstrate that it can be transferred to more biologically plausible neural networks by implementing a self-optimizing spiking neural network model. In addition, by using this spiking neural network to emulate a Hopfield network with Hebbian learning, we attempt to make a connection between rate-based and temporal coding based neural systems. Although further work is required to make this model more realistic, it already suggests that the efficacy of the self-optimizing process is independent from the simplifying assumptions of a conventional Hopfield network. We also discuss natural and cultural processes that could be responsible for occasional alteration of neural firing patterns in actual brains. Copyright © 2014 Elsevier Ltd. All rights reserved.

  18. Hidden neural networks

    DEFF Research Database (Denmark)

    Krogh, Anders Stærmose; Riis, Søren Kamaric

    1999-01-01

    A general framework for hybrids of hidden Markov models (HMMs) and neural networks (NNs) called hidden neural networks (HNNs) is described. The article begins by reviewing standard HMMs and estimation by conditional maximum likelihood, which is used by the HNN. In the HNN, the usual HMM probability...... parameters are replaced by the outputs of state-specific neural networks. As opposed to many other hybrids, the HNN is normalized globally and therefore has a valid probabilistic interpretation. All parameters in the HNN are estimated simultaneously according to the discriminative conditional maximum...... likelihood criterion. The HNN can be viewed as an undirected probabilistic independence network (a graphical model), where the neural networks provide a compact representation of the clique functions. An evaluation of the HNN on the task of recognizing broad phoneme classes in the TIMIT database shows clear...

  19. [Neural codes for perception].

    Science.gov (United States)

    Romo, R; Salinas, E; Hernández, A; Zainos, A; Lemus, L; de Lafuente, V; Luna, R

    This article describes experiments designed to show the neural codes associated with the perception and processing of tactile information. The results of these experiments have shown the neural activity correlated with tactile perception. The neurones of the primary somatosensory cortex (S1) represent the physical attributes of tactile perception. We found that these representations correlated with tactile perception. By means of intracortical microstimulation we demonstrated the causal relationship between S1 activity and tactile perception. In the motor areas of the frontal lobe is to be found the connection between sensorial and motor representation whilst decisions are being taken. S1 generates neural representations of the somatosensory stimuli which seen to be sufficient for tactile perception. These neural representations are subsequently processed by central areas to S1 and seem useful in perception, memory and decision making.

  20. Neural Oscillators Programming Simplified

    Directory of Open Access Journals (Sweden)

    Patrick McDowell

    2012-01-01

    Full Text Available The neurological mechanism used for generating rhythmic patterns for functions such as swallowing, walking, and chewing has been modeled computationally by the neural oscillator. It has been widely studied by biologists to model various aspects of organisms and by computer scientists and robotics engineers as a method for controlling and coordinating the gaits of walking robots. Although there has been significant study in this area, it is difficult to find basic guidelines for programming neural oscillators. In this paper, the authors approach neural oscillators from a programmer’s point of view, providing background and examples for developing neural oscillators to generate rhythmic patterns that can be used in biological modeling and robotics applications.

  1. Neural cryptography with feedback.

    Science.gov (United States)

    Ruttor, Andreas; Kinzel, Wolfgang; Shacham, Lanir; Kanter, Ido

    2004-04-01

    Neural cryptography is based on a competition between attractive and repulsive stochastic forces. A feedback mechanism is added to neural cryptography which increases the repulsive forces. Using numerical simulations and an analytic approach, the probability of a successful attack is calculated for different model parameters. Scaling laws are derived which show that feedback improves the security of the system. In addition, a network with feedback generates a pseudorandom bit sequence which can be used to encrypt and decrypt a secret message.

  2. Neural cryptography with feedback

    Science.gov (United States)

    Ruttor, Andreas; Kinzel, Wolfgang; Shacham, Lanir; Kanter, Ido

    2004-04-01

    Neural cryptography is based on a competition between attractive and repulsive stochastic forces. A feedback mechanism is added to neural cryptography which increases the repulsive forces. Using numerical simulations and an analytic approach, the probability of a successful attack is calculated for different model parameters. Scaling laws are derived which show that feedback improves the security of the system. In addition, a network with feedback generates a pseudorandom bit sequence which can be used to encrypt and decrypt a secret message.

  3. Neural network applications

    Science.gov (United States)

    Padgett, Mary L.; Desai, Utpal; Roppel, T.A.; White, Charles R.

    1993-01-01

    A design procedure is suggested for neural networks which accommodates the inclusion of such knowledge-based systems techniques as fuzzy logic and pairwise comparisons. The use of these procedures in the design of applications combines qualitative and quantitative factors with empirical data to yield a model with justifiable design and parameter selection procedures. The procedure is especially relevant to areas of back-propagation neural network design which are highly responsive to the use of precisely recorded expert knowledge.

  4. Building Neural Net Software

    OpenAIRE

    Neto, João Pedro; Costa, José Félix

    1999-01-01

    In a recent paper [Neto et al. 97] we showed that programming languages can be translated on recurrent (analog, rational weighted) neural nets. The goal was not efficiency but simplicity. Indeed we used a number-theoretic approach to machine programming, where (integer) numbers were coded in a unary fashion, introducing a exponential slow down in the computations, with respect to a two-symbol tape Turing machine. Implementation of programming languages in neural nets turns to be not only theo...

  5. NEMEFO: NEural MEteorological FOrecast

    Energy Technology Data Exchange (ETDEWEB)

    Pasero, E.; Moniaci, W.; Meindl, T.; Montuori, A. [Polytechnic of Turin (Italy). Dept. of Electronics

    2004-07-01

    Artificial Neural Systems are a well-known technique used to classify and recognize objects. Introducing the time dimension they can be used to forecast numerical series. NEMEFO is a ''nowcasting'' tool, which uses both statistical and neural systems to forecast meteorological data in a restricted area close to a meteorological weather station in a short time range (3 hours). Ice, fog, rain are typical events which can be anticipated by NEMEFO. (orig.)

  6. Neural and Neural Gray-Box Modeling for Entry Temperature Prediction in a Hot Strip Mill

    Science.gov (United States)

    Barrios, José Angel; Torres-Alvarado, Miguel; Cavazos, Alberto; Leduc, Luis

    2011-10-01

    In hot strip mills, initial controller set points have to be calculated before the steel bar enters the mill. Calculations rely on the good knowledge of rolling variables. Measurements are available only after the bar has entered the mill, and therefore they have to be estimated. Estimation of process variables, particularly that of temperature, is of crucial importance for the bar front section to fulfill quality requirements, and the same must be performed in the shortest possible time to preserve heat. Currently, temperature estimation is performed by physical modeling; however, it is highly affected by measurement uncertainties, variations in the incoming bar conditions, and final product changes. In order to overcome these problems, artificial intelligence techniques such as artificial neural networks and fuzzy logic have been proposed. In this article, neural network-based systems, including neural-based Gray-Box models, are applied to estimate scale breaker entry temperature, given its importance, and their performance is compared to that of the physical model used in plant. Several neural systems and several neural-based Gray-Box models are designed and tested with real data. Taking advantage of the flexibility of neural networks for input incorporation, several factors which are believed to have influence on the process are also tested. The systems proposed in this study were proven to have better performance indexes and hence better prediction capabilities than the physical models currently used in plant.

  7. Neural crest specification: tissues, signals, and transcription factors.

    Science.gov (United States)

    Rogers, C D; Jayasena, C S; Nie, S; Bronner, M E

    2012-01-01

    The neural crest is a transient population of multipotent and migratory cells unique to vertebrate embryos. Initially derived from the borders of the neural plate, these cells undergo an epithelial to mesenchymal transition to leave the central nervous system, migrate extensively in the periphery, and differentiate into numerous diverse derivatives. These include but are not limited to craniofacial cartilage, pigment cells, and peripheral neurons and glia. Attractive for their similarities to stem cells and metastatic cancer cells, neural crest cells are a popular model system for studying cell/tissue interactions and signaling factors that influence cell fate decisions and lineage transitions. In this review, we discuss the mechanisms required for neural crest formation in various vertebrate species, focusing on the importance of signaling factors from adjacent tissues and conserved gene regulatory interactions, which are required for induction and specification of the ectodermal tissue that will become neural crest. Copyright © 2011 Wiley Periodicals, Inc.

  8. A PERFORMANCE CONSTRAINT ON THE EVOLUTION OF TRILLED VOCALIZATIONS IN A SONGBIRD FAMILY (PASSERIFORMES: EMBERIZIDAE).

    Science.gov (United States)

    Podos, Jeffrey

    1997-04-01

    Behavioral evolution can be influenced by constraints, for example, of phylogeny and performance. In this paper I describe a pattern in the evolution of birdsongs that may reflect a constraint on vocal performance. Trilled vocalizations from 34 species of songbirds (Passeriformes: Emberizidae) were analyzed. Two acoustic variables, trill rate and frequency bandwidth, were measured for different trill types. In most species, maximal values of frequency bandwidth were found to decrease with increasing trill rates. Further, trills with low trill rates exhibited wide variance in frequency bandwidth, and trills with high trill rates exhibited only narrow frequency bandwidths. The bounded nature of this pattern suggests that performance constraints have limited the evolutionary diversification of trills. In particular, I explore the role of constraints associated with vocal tract modulations during song production and evolution. Identification of this constraint may enhance our ability to explain particular patterns of trill evolution. © 1997 The Society for the Study of Evolution.

  9. Thermodynamic constraints on fluctuation phenomena

    Science.gov (United States)

    Maroney, O. J. E.

    2009-12-01

    The relationships among reversible Carnot cycles, the absence of perpetual motion machines, and the existence of a nondecreasing globally unique entropy function form the starting point of many textbook presentations of the foundations of thermodynamics. However, the thermal fluctuation phenomena associated with statistical mechanics has been argued to restrict the domain of validity of this basis of the second law of thermodynamics. Here we demonstrate that fluctuation phenomena can be incorporated into the traditional presentation, extending rather than restricting the domain of validity of the phenomenologically motivated second law. Consistency conditions lead to constraints upon the possible spectrum of thermal fluctuations. In a special case this uniquely selects the Gibbs canonical distribution and more generally incorporates the Tsallis distributions. No particular model of microscopic dynamics need be assumed.

  10. Atom mapping with constraint programming.

    Science.gov (United States)

    Mann, Martin; Nahar, Feras; Schnorr, Norah; Backofen, Rolf; Stadler, Peter F; Flamm, Christoph

    2014-01-01

    Chemical reactions are rearrangements of chemical bonds. Each atom in an educt molecule thus appears again in a specific position of one of the reaction products. This bijection between educt and product atoms is not reported by chemical reaction databases, however, so that the "Atom Mapping Problem" of finding this bijection is left as an important computational task for many practical applications in computational chemistry and systems biology. Elementary chemical reactions feature a cyclic imaginary transition state (ITS) that imposes additional restrictions on the bijection between educt and product atoms that are not taken into account by previous approaches. We demonstrate that Constraint Programming is well-suited to solving the Atom Mapping Problem in this setting. The performance of our approach is evaluated for a manually curated subset of chemical reactions from the KEGG database featuring various ITS cycle layouts and reaction mechanisms.

  11. Constraint Ornstein-Uhlenbeck bridges

    Science.gov (United States)

    Mazzolo, Alain

    2017-09-01

    In this paper, we study the Ornstein-Uhlenbeck bridge process (i.e., the Ornstein-Uhlenbeck process conditioned to start and end at fixed points) constraints to have a fixed area under its path. We present both anticipative (in this case, we need the knowledge of the future of the path) and non-anticipative versions of the stochastic process. We obtain the anticipative description thanks to the theory of generalized Gaussian bridges while the non-anticipative representation comes from the theory of stochastic control. For this last representation, a stochastic differential equation is derived which leads to an effective Langevin equation. Finally, we extend our theoretical findings to linear bridge processes.

  12. Optical flow computation using extended constraints.

    Science.gov (United States)

    Del Bimbo, A; Nesi, P; Sanz, J C

    1996-01-01

    Several approaches for optical flow estimation use partial differential equations to model changes in image brightness throughout time. A commonly used equation is the so-called optical flow constraint (OFC), which assumes that the image brightness is stationary with respect to time. More recently, a different constraint referred to as the extended optical flow constraint (EOFC) has been introduced, which also contains the divergence of the flow field of image brightness. There is no agreement in the literature about which of these constraints provides the best estimation of the velocity field. Two new solutions for optical flow computation are proposed, which are based on an approximation of the constraint equations. The two techniques have been used with both EOFC and OFC constraint equations. Results achieved by using these solutions have been compared with several well-known computational methods for optical flow estimation in different motion conditions. Estimation errors have also been measured and compared for different types of motion.

  13. Causality Constraints in Conformal Field Theory

    CERN Multimedia

    CERN. Geneva

    2015-01-01

    Causality places nontrivial constraints on QFT in Lorentzian signature, for example fixing the signs of certain terms in the low energy Lagrangian. In d-dimensional conformal field theory, we show how such constraints are encoded in crossing symmetry of Euclidean correlators, and derive analogous constraints directly from the conformal bootstrap (analytically). The bootstrap setup is a Lorentzian four-point function corresponding to propagation through a shockwave. Crossing symmetry fixes the signs of certain log terms that appear in the conformal block expansion, which constrains the interactions of low-lying operators. As an application, we use the bootstrap to rederive the well known sign constraint on the (∂φ)4 coupling in effective field theory, from a dual CFT. We also find constraints on theories with higher spin conserved currents. Our analysis is restricted to scalar correlators, but we argue that similar methods should also impose nontrivial constraints on the interactions of spinni...

  14. Relationship between protein structure and geometrical constraints.

    OpenAIRE

    Lund, O.; Hansen, J.; Brunak, S.; Bohr, J.

    1996-01-01

    We evaluate to what extent the structure of proteins can be deduced from incomplete knowledge of disulfide bridges, surface assignments, secondary structure assignments, and additional distance constraints. A cost function taking such constraints into account was used to obtain protein structures using a simple minimization algorithm. For small proteins, the approximate structure could be obtained using one additional distance constraint for each amino acid in the protein. We also studied the...

  15. Review of Minimal Flavor Constraints for Technicolor

    DEFF Research Database (Denmark)

    S. Fukano, Hidenori; Sannino, Francesco

    2010-01-01

    We analyze the constraints on the the vacuum polarization of the standard model gauge bosons from a minimal set of flavor observables valid for a general class of models of dynamical electroweak symmetry breaking. We will show that the constraints have a strong impact on the self-coupling and mas......We analyze the constraints on the the vacuum polarization of the standard model gauge bosons from a minimal set of flavor observables valid for a general class of models of dynamical electroweak symmetry breaking. We will show that the constraints have a strong impact on the self...

  16. Toward an automaton Constraint for Local Search

    Directory of Open Access Journals (Sweden)

    Jun He

    2009-10-01

    Full Text Available We explore the idea of using finite automata to implement new constraints for local search (this is already a successful technique in constraint-based global search. We show how it is possible to maintain incrementally the violations of a constraint and its decision variables from an automaton that describes a ground checker for that constraint. We establish the practicality of our approach idea on real-life personnel rostering problems, and show that it is competitive with the approach of [Pralong, 2007].

  17. Extending models for two-dimensional constraints

    DEFF Research Database (Denmark)

    Forchhammer, Søren

    2009-01-01

    for models of two-dimensional constraints and as examples we apply it to the hard-square constraint and the no isolated bits (n.i.b) constraint. The iterative scaling can ensure that the entropy of the extension is optimized and that the entropy is increased compared to the initial model defined on 2 times 2...... elements. Application to a simple stationary model with hidden states is also outlined. For the n.i.b constraint, the initial model is based on elements defined by blocks of (1 times 2) binary symbols....

  18. Notes on Timed Concurrent Constraint Programming

    DEFF Research Database (Denmark)

    Nielsen, Mogens; Valencia, Frank D.

    2004-01-01

    and program reactive systems. This note provides a comprehensive introduction to the background for and central notions from the theory of tccp. Furthermore, it surveys recent results on a particular tccp calculus, ntcc, and it provides a classification of the expressive power of various tccp languages.......A constraint is a piece of (partial) information on the values of the variables of a system. Concurrent constraint programming (ccp) is a model of concurrency in which agents (also called processes) interact by telling and asking information (constraints) to and from a shared store (a constraint...

  19. Neural network modeling of emotion

    Science.gov (United States)

    Levine, Daniel S.

    2007-03-01

    This article reviews the history and development of computational neural network modeling of cognitive and behavioral processes that involve emotion. The exposition starts with models of classical conditioning dating from the early 1970s. Then it proceeds toward models of interactions between emotion and attention. Then models of emotional influences on decision making are reviewed, including some speculative (not and not yet simulated) models of the evolution of decision rules. Through the late 1980s, the neural networks developed to model emotional processes were mainly embodiments of significant functional principles motivated by psychological data. In the last two decades, network models of these processes have become much more detailed in their incorporation of known physiological properties of specific brain regions, while preserving many of the psychological principles from the earlier models. Most network models of emotional processes so far have dealt with positive and negative emotion in general, rather than specific emotions such as fear, joy, sadness, and anger. But a later section of this article reviews a few models relevant to specific emotions: one family of models of auditory fear conditioning in rats, and one model of induced pleasure enhancing creativity in humans. Then models of emotional disorders are reviewed. The article concludes with philosophical statements about the essential contributions of emotion to intelligent behavior and the importance of quantitative theories and models to the interdisciplinary enterprise of understanding the interactions of emotion, cognition, and behavior.

  20. The Criticality Hypothesis in Neural Systems

    Science.gov (United States)

    Karimipanah, Yahya

    There is mounting evidence that neural networks of the cerebral cortex exhibit scale invariant dynamics. At the larger scale, fMRI recordings have shown evidence for spatiotemporal long range correlations. On the other hand, at the smaller scales this scale invariance is marked by the power law distribution of the size and duration of spontaneous bursts of activity, which are referred as neuronal avalanches. The existence of such avalanches has been confirmed by several studies in vitro and in vivo, among different species and across multiple scales, from spatial scale of MEG and EEG down to single cell resolution. This prevalent scale free nature of cortical activity suggests the hypothesis that the cortex resides at a critical state between two phases of order (short-lasting activity) and disorder (long-lasting activity). In addition, it has been shown, both theoretically and experimentally, that being at criticality brings about certain functional advantages for information processing. However, despite the plenty of evidence and plausibility of the neural criticality hypothesis, still very little is known on how the brain may leverage such criticality to facilitate neural coding. Moreover, the emergent functions that may arise from critical dynamics is poorly understood. In the first part of this thesis, we review several pieces of evidence for the neural criticality hypothesis at different scales, as well as some of the most popular theories of self-organized criticality (SOC). Thereafter, we will focus on the most prominent evidence from small scales, namely neuronal avalanches. We will explore the effect of adaptation and how it can maintain scale free dynamics even at the presence of external stimuli. Using calcium imaging we also experimentally demonstrate the existence of scale free activity at the cellular resolution in vivo. Moreover, by exploring the subsampling issue in neural data, we will find some fundamental constraints of the conventional methods

  1. Discretionary time of Chinese college students: Activities and impact of SARS-induced constraints on choices

    Science.gov (United States)

    He Yang; Susan Hutchinson; Harry Zinn; Alan Watson

    2011-01-01

    How people make choices about activity engagement during discretionary time is a topic of increasing interest to those studying quality of life issues. Assuming choices are made to maximize individual welfare, several factors are believed to influence these choices. Constraints theory from the leisure research literature suggests these choices are heavily influenced by...

  2. A Bayesian framework for simultaneously modeling neural and behavioral data.

    Science.gov (United States)

    Turner, Brandon M; Forstmann, Birte U; Wagenmakers, Eric-Jan; Brown, Scott D; Sederberg, Per B; Steyvers, Mark

    2013-05-15

    Scientists who study cognition infer underlying processes either by observing behavior (e.g., response times, percentage correct) or by observing neural activity (e.g., the BOLD response). These two types of observations have traditionally supported two separate lines of study. The first is led by cognitive modelers, who rely on behavior alone to support their computational theories. The second is led by cognitive neuroimagers, who rely on statistical models to link patterns of neural activity to experimental manipulations, often without any attempt to make a direct connection to an explicit computational theory. Here we present a flexible Bayesian framework for combining neural and cognitive models. Joining neuroimaging and computational modeling in a single hierarchical framework allows the neural data to influence the parameters of the cognitive model and allows behavioral data, even in the absence of neural data, to constrain the neural model. Critically, our Bayesian approach can reveal interactions between behavioral and neural parameters, and hence between neural activity and cognitive mechanisms. We demonstrate the utility of our approach with applications to simulated fMRI data with a recognition model and to diffusion-weighted imaging data with a response time model of perceptual choice. Copyright © 2013 Elsevier Inc. All rights reserved.

  3. A Bayesian framework for simultaneously modeling neural and behavioral data✩

    Science.gov (United States)

    Turner, Brandon M.; Forstmann, Birte U.; Wagenmakers, Eric-Jan; Brown, Scott D.; Sederberg, Per B.; Steyvers, Mark

    2013-01-01

    Scientists who study cognition infer underlying processes either by observing behavior (e.g., response times, percentage correct) or by observing neural activity (e.g., the BOLD response). These two types of observations have traditionally supported two separate lines of study. The first is led by cognitive modelers, who rely on behavior alone to support their computational theories. The second is led by cognitive neuroimagers, who rely on statistical models to link patterns of neural activity to experimental manipulations, often without any attempt to make a direct connection to an explicit computational theory. Here we present a flexible Bayesian framework for combining neural and cognitive models. Joining neuroimaging and computational modeling in a single hierarchical framework allows the neural data to influence the parameters of the cognitive model and allows behavioral data, even in the absence of neural data, to constrain the neural model. Critically, our Bayesian approach can reveal interactions between behavioral and neural parameters, and hence between neural activity and cognitive mechanisms. We demonstrate the utility of our approach with applications to simulated fMRI data with a recognition model and to diffusion-weighted imaging data with a response time model of perceptual choice. PMID:23370060

  4. Adult Mammalian Neural Stem Cells and Neurogenesis: Five Decades Later

    Science.gov (United States)

    Bond, Allison M.; Ming, Guo-li; Song, Hongjun

    2015-01-01

    Summary Adult somatic stem cells in various organs maintain homeostatic tissue regeneration and enhance plasticity. Since its initial discovery five decades ago, investigations of adult neurogenesis and neural stem cells have led to an established and expanding field that has significantly influenced many facets of neuroscience, developmental biology and regenerative medicine. Here we review recent progress and focus on questions related to adult mammalian neural stem cells that also apply to other somatic stem cells. We further discuss emerging topics that are guiding the field toward better understanding adult neural stem cells and ultimately applying these principles to improve human health. PMID:26431181

  5. On The Parameters of Geometric Constraints for Cracked Plates under Tension - Three-Dimensional Problems

    Science.gov (United States)

    Graba, M.

    2017-12-01

    This paper provides a comparative analysis of selected parameters of the geometric constraints for cracked plates subjected to tension. The results of three-dimensional numerical calculations were used to assess the distribution of these parameters around the crack front and their changes along the crack front. The study also involved considering the influence of the external load on the averaged values of the parameters of the geometric constraints as well as the relationship between the material constants and the level of the geometric constraints contributing to the actual fracture toughness for certain geometries.

  6. Lesbians and Gay Men's Vacation Motivations, Perceptions, and Constraints: A Study of Cruise Vacation Choice.

    Science.gov (United States)

    Weeden, Clare; Lester, Jo-Anne; Jarvis, Nigel

    2016-08-01

    This study explores the push-pull vacation motivations of gay male and lesbian consumers and examines how these underpin their perceptions and purchase constraints of a mainstream and LGBT(1) cruise. Findings highlight a complex vacation market. Although lesbians and gay men share many of the same travel motivations as their heterosexual counterparts, the study reveals sexuality is a significant variable in their perception of cruise vacations, which further influences purchase constraints and destination choice. Gay men have more favorable perceptions than lesbians of both mainstream and LGBT cruises. The article recommends further inquiry into the multifaceted nature of motivations, perception, and constraints within the LGBT market in relation to cruise vacations.

  7. Hindcasting cyclonic waves using neural networks

    Digital Repository Service at National Institute of Oceanography (India)

    Mandal, S.; Rao, S.; Chakravarty, N.V.

    the backpropagation networks with updated algorithms are used in this paper. A brief description about the working of a back propagation neural network and three updated algorithms is given below. Backpropagation learning: Backpropagation is the most widely used... algorithm for supervised learning with multi layer feed forward networks. The idea of the backpropagation learning algorithm is the repeated application of the chain rule to compute the influence of each weight in the network with respect to an arbitrary...

  8. Neural Plasticity in the Gustatory System

    OpenAIRE

    Hill, David L.

    2004-01-01

    Sensory systems adapt to changing environmental influences by coordinated alterations in structure and function. These alterations are referred to as plastic changes. The gustatory system displays numerous plastic changes even in receptor cells. This review focuses on the plasticity of gustatory structures through the first synaptic relay in the brain. Unlike other sensory systems, there is a remarkable amount of environmentally induced changes in these peripheral-most neural structures. The ...

  9. Foetal ECG recovery using dynamic neural networks.

    Science.gov (United States)

    Camps-Valls, Gustavo; Martínez-Sober, Marcelino; Soria-Olivas, Emilio; Magdalena-Benedito, Rafael; Calpe-Maravilla, Javier; Guerrero-Martínez, Juan

    2004-07-01

    Non-invasive electrocardiography has proven to be a very interesting method for obtaining information about the foetus state and thus to assure its well-being during pregnancy. One of the main applications in this field is foetal electrocardiogram (ECG) recovery by means of automatic methods. Evident problems found in the literature are the limited number of available registers, the lack of performance indicators, and the limited use of non-linear adaptive methods. In order to circumvent these problems, we first introduce the generation of synthetic registers and discuss the influence of different kinds of noise to the modelling. Second, a method which is based on numerical (correlation coefficient) and statistical (analysis of variance, ANOVA) measures allows us to select the best recovery model. Finally, finite impulse response (FIR) and gamma neural networks are included in the adaptive noise cancellation (ANC) scheme in order to provide highly non-linear, dynamic capabilities to the recovery model. Neural networks are benchmarked with classical adaptive methods such as the least mean squares (LMS) and the normalized LMS (NLMS) algorithms in simulated and real registers and some conclusions are drawn. For synthetic registers, the most determinant factor in the identification of the models is the foetal-maternal signal-to-noise ratio (SNR). In addition, as the electromyogram contribution becomes more relevant, neural networks clearly outperform the LMS-based algorithm. From the ANOVA test, we found statistical differences between LMS-based models and neural models when complex situations (high foetal-maternal and foetal-noise SNRs) were present. These conclusions were confirmed after doing robustness tests on synthetic registers, visual inspection of the recovered signals and calculation of the recognition rates of foetal R-peaks for real situations. Finally, the best compromise between model complexity and outcomes was provided by the FIR neural network. Both

  10. Physical activity participation and constraints among athletic training students.

    Science.gov (United States)

    Stanek, Justin; Rogers, Katherine; Anderson, Jordan

    2015-02-01

    Researchers have examined the physical activity (PA) habits of certified athletic trainers; however, none have looked specifically at athletic training students. To assess PA participation and constraints to participation among athletic training students. Cross-sectional study. Entry-level athletic training education programs (undergraduate and graduate) across the United States. Participants were 1125 entry-level athletic training students. Self-reported PA participation, including a calculated PA index based on a typical week. Leisure constraints and demographic data were also collected. Only 22.8% (252/1105) of athletic training students were meeting the American College of Sports Medicine recommendations for PA through moderate-intensity cardiorespiratory exercise. Although 52.3% (580/1105) were meeting the recommendations through vigorous-intensity cardiorespiratory exercise, 60.5% (681/1125) were meeting the recommendations based on the combined total of moderate or vigorous cardiorespiratory exercise. In addition, 57.2% (643/1125) of respondents met the recommendations for resistance exercise. Exercise habits of athletic training students appear to be better than the national average and similar to those of practicing athletic trainers. Students reported structural constraints such as lack of time due to work or studies as the most significant barrier to exercise participation. Athletic training students experienced similar constraints to PA participation as practicing athletic trainers, and these constraints appeared to influence their exercise participation during their entry-level education. Athletic training students may benefit from a greater emphasis on work-life balance during their entry-level education to promote better health and fitness habits.

  11. Conducting Polymers for Neural Prosthetic and Neural Interface Applications

    Science.gov (United States)

    2015-01-01

    Neural interfacing devices are an artificial mechanism for restoring or supplementing the function of the nervous system lost as a result of injury or disease. Conducting polymers (CPs) are gaining significant attention due to their capacity to meet the performance criteria of a number of neuronal therapies including recording and stimulating neural activity, the regeneration of neural tissue and the delivery of bioactive molecules for mediating device-tissue interactions. CPs form a flexible platform technology that enables the development of tailored materials for a range of neuronal diagnostic and treatment therapies. In this review the application of CPs for neural prostheses and other neural interfacing devices are discussed, with a specific focus on neural recording, neural stimulation, neural regeneration, and therapeutic drug delivery. PMID:26414302

  12. Learning to teach data journalism: Innovation, influence and constraints

    OpenAIRE

    Hewett, J.

    2016-01-01

    Journalism education has tended to respond slowly to developments in digital journalism, such as data journalism, despite or because of close links with the industry. This paper examines the obstacles to innovation in journalism education with particular reference to data journalism, drawing on the literature, a review of stakeholders and course documents, and the author’s reflections on developing a data journalism module as part of a new MA programme. It highlights the complexities linked t...

  13. Determining discourses: Constraints and resources influencing early career science teachers

    Science.gov (United States)

    Grindstaff, Kelly E.

    This study explores the thinking and practices of five early-career teachers of grades eight to ten science, in relation to their histories, schools, students, and larger cultural and political forces. All the teachers are young women, two in their fourth year of teaching, who teach together in an affluent suburb, along with one first-year teacher. The other two are first-year teachers who teach in an urban setting. All of these teachers most closely associated good science teaching with forming relationships with students. They filtered science content through a lens of relevance (mostly to everyday life) and interest for students. Thus they filtered science content through a commitment to serving students, which makes sense since I argue that the primary motivations for teaching had more to do with working with students and helping people than the disciplines of science. Thus, within the discourse of the supremacy of curriculum and the prevalence of testing, these teachers enact hybrid practices which focus on covering content -- to help ensure the success of students -- and on relevance and interest, which has more to do with teaching styles and personality than disciplines of science. Ideas of good teaching are not very focused on science, which contradicts the type of support they seek and utilize around science content. This presents a challenge to pre- and in-service education and support to question what student success means, what concern for students entails and how to connect caring and concern for students with science.

  14. Hyperbolic Hopfield neural networks.

    Science.gov (United States)

    Kobayashi, M

    2013-02-01

    In recent years, several neural networks using Clifford algebra have been studied. Clifford algebra is also called geometric algebra. Complex-valued Hopfield neural networks (CHNNs) are the most popular neural networks using Clifford algebra. The aim of this brief is to construct hyperbolic HNNs (HHNNs) as an analog of CHNNs. Hyperbolic algebra is a Clifford algebra based on Lorentzian geometry. In this brief, a hyperbolic neuron is defined in a manner analogous to a phasor neuron, which is a typical complex-valued neuron model. HHNNs share common concepts with CHNNs, such as the angle and energy. However, HHNNs and CHNNs are different in several aspects. The states of hyperbolic neurons do not form a circle, and, therefore, the start and end states are not identical. In the quantized version, unlike complex-valued neurons, hyperbolic neurons have an infinite number of states.

  15. Neural Semantic Encoders.

    Science.gov (United States)

    Munkhdalai, Tsendsuren; Yu, Hong

    2017-04-01

    We present a memory augmented neural network for natural language understanding: Neural Semantic Encoders. NSE is equipped with a novel memory update rule and has a variable sized encoding memory that evolves over time and maintains the understanding of input sequences through read, compose and write operations. NSE can also access multiple and shared memories. In this paper, we demonstrated the effectiveness and the flexibility of NSE on five different natural language tasks: natural language inference, question answering, sentence classification, document sentiment analysis and machine translation where NSE achieved state-of-the-art performance when evaluated on publically available benchmarks. For example, our shared-memory model showed an encouraging result on neural machine translation, improving an attention-based baseline by approximately 1.0 BLEU.

  16. Global neural dynamic surface tracking control of strict-feedback systems with application to hypersonic flight vehicle.

    Science.gov (United States)

    Xu, Bin; Yang, Chenguang; Pan, Yongping

    2015-10-01

    This paper studies both indirect and direct global neural control of strict-feedback systems in the presence of unknown dynamics, using the dynamic surface control (DSC) technique in a novel manner. A new switching mechanism is designed to combine an adaptive neural controller in the neural approximation domain, together with the robust controller that pulls the transient states back into the neural approximation domain from the outside. In comparison with the conventional control techniques, which could only achieve semiglobally uniformly ultimately bounded stability, the proposed control scheme guarantees all the signals in the closed-loop system are globally uniformly ultimately bounded, such that the conventional constraints on initial conditions of the neural control system can be relaxed. The simulation studies of hypersonic flight vehicle (HFV) are performed to demonstrate the effectiveness of the proposed global neural DSC design.

  17. 2D neural hardware versus 3D biological ones

    Energy Technology Data Exchange (ETDEWEB)

    Beiu, V.

    1998-12-31

    This paper will present important limitations of hardware neural nets as opposed to biological neural nets (i.e. the real ones). The author starts by discussing neural structures and their biological inspirations, while mentioning the simplifications leading to artificial neural nets. Going further, the focus will be on hardware constraints. The author will present recent results for three different alternatives of implementing neural networks: digital, threshold gate, and analog, while the area and the delay will be related to neurons' fan-in and weights' precision. Based on all of these, it will be shown why hardware implementations cannot cope with their biological inspiration with respect to their power of computation: the mapping onto silicon lacking the third dimension of biological nets. This translates into reduced fan-in, and leads to reduced precision. The main conclusion is that one is faced with the following alternatives: (1) try to cope with the limitations imposed by silicon, by speeding up the computation of the elementary silicon neurons; (2) investigate solutions which would allow one to use the third dimension, e.g. using optical interconnections.

  18. Filtering Algorithms for Global Chance Constraints

    NARCIS (Netherlands)

    Hnich, B.; Rossi, R.; Tarim, S.A.; Prestwich, S.

    2012-01-01

    Stochastic Constraint Satisfaction Problems (SCSPs) are a powerful modeling framework for problems under uncertainty. To solve them is a PSPACE task. The only complete solution approach to date — scenario-based stochastic constraint programming — compiles SCSPs down into classical CSPs. This allows

  19. Integrity Constraints in Trust Management (Extended Abstract)

    NARCIS (Netherlands)

    Etalle, Sandro; Winsborough, William H.; Ahn, G-J.

    We introduce the use, monitoring, and enforcement of integrity constraints in trust managementstyle authorization systems. We consider what portions of the policy state must be monitored to detect violations of integrity constraints. Then we address the fact that not all participants in a trust

  20. Cosmological Constraints from Gravitational Lens Time Delays

    Science.gov (United States)

    Coe, Dan; Moustakas, Leonidas A.

    2009-11-01

    Future large ensembles of time delay (TD) lenses have the potential to provide interesting cosmological constraints complementary to those of other methods. In a flat universe with constant w including a Planck prior, The Large Synoptic Survey Telescope TD measurements for ~4000 lenses should constrain the local Hubble constant h to ~0.007 (~1%), Ω de to ~0.005, and w to ~0.026 (all 1σ precisions). Similar constraints could be obtained by a dedicated gravitational lens observatory (OMEGA) which would obtain precise TD and mass model measurements for ~100 well-studied lenses. We compare these constraints (as well as those for a more general cosmology) to the "optimistic Stage IV" constraints expected from weak lensing, supernovae, baryon acoustic oscillations, and cluster counts, as calculated by the Dark Energy Task Force. TDs yield a modest constraint on a time-varying w(z), with the best constraint on w(z) at the "pivot redshift" of z ≈ 0.31. Our Fisher matrix calculation is provided to allow TD constraints to be easily compared to and combined with constraints from other experiments. We also show how cosmological constraining power varies as a function of numbers of lenses, lens model uncertainty, TD precision, redshift precision, and the ratio of four-image to two-image lenses.

  1. Efficient sizing of structures under stress constraints

    NARCIS (Netherlands)

    Hong, Z.; Abdalla, M.M.

    2016-01-01

    Optimisation algorithms used to automatically size structural members commonly involve stress constraints to avoid material failure. Therefore the cost of optimisation grows rapidly as the number of structural members is increased due to the corresponding increase in the number of constraints. In

  2. A model for strategy in constraint solving

    NARCIS (Netherlands)

    J.J. van Wijk (Jack)

    1997-01-01

    textabstractThe use of constraints for the definition of graphical user interfaces has been recognized as a great concept. However, often many valuations of the variables will satisfy the constraints, and which particular valuation matches best with the expectation of the user cannot be decided

  3. Supernova constraints on neutrino mass and mixing

    Indian Academy of Sciences (India)

    In this article I review the constraints on neutrino mass and mixing coming from type-II supernovae. The bounds obtained on these parameters from shock reheating, -process nucleosynthesis and from SN1987A are discussed. Given the current constraints on neutrino mass and mixing the effect of oscillations of neutrinos ...

  4. Missed opportunities and caretaker constraints to childhood ...

    African Journals Online (AJOL)

    Background: Despite concerted support to vaccination programmes, coverage remains low. While health service reasons for this are known, there is little information on caretaker constraints to vaccination in Africa. Objective: To establish the prevalence of missed vaccination opportunities and caretaker constraints to ...

  5. Climate Change Adaptation Constraints among Smallholder ...

    African Journals Online (AJOL)

    The mean ranks of the constraints significantly differ from one another with the three topmost constraints being unreliable water source, lack of information on climate change and limited income. But for crop diversification, poor extension services and lack of credit are factors that cut across all the identified adaptation ...

  6. Constraints on three flavor neutrino mixing

    Indian Academy of Sciences (India)

    Home; Journals; Pramana – Journal of Physics; Volume 54; Issue 1. Constraints on three flavor neutrino ... We summarize the constraints on three flavor neutrino mixing coming from data. We first map out the allowed region in ... Mohan Narayan1. Department of Physics, Indian Institute of Technology, Mumbai 400 076, India ...

  7. Domain General Constraints on Statistical Learning

    Science.gov (United States)

    Thiessen, Erik D.

    2011-01-01

    All theories of language development suggest that learning is constrained. However, theories differ on whether these constraints arise from language-specific processes or have domain-general origins such as the characteristics of human perception and information processing. The current experiments explored constraints on statistical learning of…

  8. Network Design with Node Degree Balance Constraints

    DEFF Research Database (Denmark)

    Pedersen, Michael Berliner; Crainic, Teodor Gabriel

    This presentation discusses an extension to the network design model where there in addition to the flow conservation constraints also are constraints that require design conservation. This means that the number of arcs entering and leaving a node must be the same. As will be shown the model has...

  9. A Temporal Concurrent Constraint Programming Calculus

    DEFF Research Database (Denmark)

    Palamidessi, Catuscia; Valencia Posso, Frank Darwin

    2001-01-01

    The tcc model is a formalism for reactive concurrent constraint programming. In this paper we propose a model of temporal concurrent constraint programming which adds to tcc the capability of modeling asynchronous and non-deterministic timed behavior. We call this tcc extension the ntcc calculus...

  10. On Noisy Extensions of Nonholonomic Constraints

    Science.gov (United States)

    Gay-Balmaz, François; Putkaradze, Vakhtang

    2016-12-01

    We propose several stochastic extensions of nonholonomic constraints for mechanical systems and study the effects on the dynamics and on the conservation laws. Our approach relies on a stochastic extension of the Lagrange-d'Alembert framework. The mechanical system we focus on is the example of a Routh sphere, i.e., a rolling unbalanced ball on the plane. We interpret the noise in the constraint as either a stochastic motion of the plane, random slip or roughness of the surface. Without the noise, this system possesses three integrals of motion: energy, Jellet and Routh. Depending on the nature of noise in the constraint, we show that either energy, or Jellet, or both integrals can be conserved, with probability 1. We also present some exact solutions for particular types of motion in terms of stochastic integrals. Next, for an arbitrary nonholonomic system, we consider two different ways of including stochasticity in the constraints. We show that when the noise preserves the linearity of the constraints, then energy is preserved. For other types of noise in the constraint, e.g., in the case of an affine noise, the energy is not conserved. We study in detail a class of Lagrangian mechanical systems on semidirect products of Lie groups, with "rolling ball type" constraints. We conclude with numerical simulations illustrating our theories, and some pedagogical examples of noise in constraints for other nonholonomic systems popular in the literature, such as the nonholonomic particle, the rolling disk and the Chaplygin sleigh.

  11. The neural crest and neural crest cells: discovery and significance ...

    Indian Academy of Sciences (India)

    In this paper I provide a brief overview of the major phases of investigation into the neural crest and the major players involved, discuss how the origin of the neural crest relates to the origin of the nervous system in vertebrate embryos, discuss the impact on the germ-layer theory of the discovery of the neural crest and of ...

  12. VOCABULARY CONSTRAINT ON READING MATERIALS

    Directory of Open Access Journals (Sweden)

    Cucu Sutarsyah

    2016-02-01

    Full Text Available The aim of the study is to identify and describe the vocabulary in reading materials and to seek if the texts are useful for reading skill development. A descriptive qualitative design was applied to obtain the data. Some available computer programs were used to find the description of vocabulary in the texts. It was found that the texts are dominated by low frequency words which compose 16.97% of the words in the texts. In terms of high frequency words occurring in the texts, function words dominate the texts. In the case of word levels, it was found that the texts being used have very limited number of words from GSL (West, 1953. The proportion of the first 1,000 words of GSL only comprises 44.6%. The data also show that the texts contain too large proportion of words which are not in the three levels (the first 2,000 and UWL. These words constitute account for 26.44% of the running words in the texts.  It is believed that the constraints are due to the selection of the texts which are made of a series of short-unrelated texts. This kind of text is subject to the accumulation of low frequency words especially those of content words and limited of words from GSL. It could also impede the development of students' reading skills and vocabulary enrichment.

  13. Enhancing Hohlraum Design with Artificial Neural Networks

    Science.gov (United States)

    Peterson, J. L.; Berzak Hopkins, L. F.; Humbird, K. D.; Brandon, S. T.; Field, J. E.; Langer, S. H.; Nora, R. C.; Spears, B. K.

    2017-10-01

    A primary goal of hohlraum design is to efficiently convert available laser power and energy to capsule drive, compression and ultimately fusion neutron yield. However, a major challenge of this multi-dimensional optimization problem is the relative computational expense of hohlraum simulations. In this work, we explore overcoming this obstacle with the use of artificial neural networks built off ensembles of hohlraum simulations. These machine learning systems emulate the behavior of full simulations in a fraction of the time, thereby enabling the rapid exploration of design parameters. We will demonstrate this technology with a search for modifications to existing high-yield designs that can maximize neutron production within NIF's current laser power and energy constraints. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. LLNL-ABS-734401.

  14. Optimum beamforming subject to multiple linear constraints

    Science.gov (United States)

    Steele, A. K.

    1980-09-01

    Optimum beamformers with a single look direction constraint can suffer from signal suppression problems when the optimum weights are calculated from the inverse of the signal-plus-noise cross-spectral matrix. Signal suppression occurs when the beam steer direction does not exactly correspond to the signal direction and this can occur if the number of fixed beams is small. The use of multiple linear constraints upon the optimum weights reduces this signal suppression. Multiple directional constraints can lead to ill-conditioned equations. However, it is shown that the limiting solutions of multiple directional constraints are multiple derivative contraints and these do not lead to ill-conditioned equations. The ability of various derivative constraints to prevent signal suppression is analyzed quantitatively.

  15. Obstacle avoidance for kinematically redundant manipulators using a dual neural network.

    Science.gov (United States)

    Zhang, Yunong; Wang, Jun

    2004-02-01

    One important issue in the motion planning and control of kinematically redundant manipulators is the obstacle avoidance. In this paper, a recurrent neural network is developed and applied for kinematic control of redundant manipulators with obstacle avoidance capability. An improved problem formulation is proposed in the sense that the collision-avoidance requirement is represented by dynamically-updated inequality constraints. In addition, physical constraints such as joint physical limits are also incorporated directly into the formulation. Based on the improved problem formulation, a dual neural network is developed for the online solution to collision-free inverse kinematics problem. The neural network is simulated for motion control of the PA10 robot arm in the presence of point and window-shaped obstacle.

  16. Introduction to Artificial Neural Networks

    DEFF Research Database (Denmark)

    Larsen, Jan

    1999-01-01

    The note addresses introduction to signal analysis and classification based on artificial feed-forward neural networks.......The note addresses introduction to signal analysis and classification based on artificial feed-forward neural networks....

  17. Deconvolution using a neural network

    Energy Technology Data Exchange (ETDEWEB)

    Lehman, S.K.

    1990-11-15

    Viewing one dimensional deconvolution as a matrix inversion problem, we compare a neural network backpropagation matrix inverse with LMS, and pseudo-inverse. This is a largely an exercise in understanding how our neural network code works. 1 ref.

  18. The Flattened Aggregate Constraint Homotopy Method for Nonlinear Programming Problems with Many Nonlinear Constraints

    Directory of Open Access Journals (Sweden)

    Zhengyong Zhou

    2014-01-01

    Full Text Available The aggregate constraint homotopy method uses a single smoothing constraint instead of m-constraints to reduce the dimension of its homotopy map, and hence it is expected to be more efficient than the combined homotopy interior point method when the number of constraints is very large. However, the gradient and Hessian of the aggregate constraint function are complicated combinations of gradients and Hessians of all constraint functions, and hence they are expensive to calculate when the number of constraint functions is very large. In order to improve the performance of the aggregate constraint homotopy method for solving nonlinear programming problems, with few variables and many nonlinear constraints, a flattened aggregate constraint homotopy method, that can save much computation of gradients and Hessians of constraint functions, is presented. Under some similar conditions for other homotopy methods, existence and convergence of a smooth homotopy path are proven. A numerical procedure is given to implement the proposed homotopy method, preliminary computational results show its performance, and it is also competitive with the state-of-the-art solver KNITRO for solving large-scale nonlinear optimization.

  19. Natural Constraints to Species Diversification.

    Directory of Open Access Journals (Sweden)

    Eric Lewitus

    2016-08-01

    Full Text Available Identifying modes of species diversification is fundamental to our understanding of how biodiversity changes over evolutionary time. Diversification modes are captured in species phylogenies, but characterizing the landscape of diversification has been limited by the analytical tools available for directly comparing phylogenetic trees of groups of organisms. Here, we use a novel, non-parametric approach and 214 family-level phylogenies of vertebrates representing over 500 million years of evolution to identify major diversification modes, to characterize phylogenetic space, and to evaluate the bounds and central tendencies of species diversification. We identify five principal patterns of diversification to which all vertebrate families hold. These patterns, mapped onto multidimensional space, constitute a phylogenetic space with distinct properties. Firstly, phylogenetic space occupies only a portion of all possible tree space, showing family-level phylogenies to be constrained to a limited range of diversification patterns. Secondly, the geometry of phylogenetic space is delimited by quantifiable trade-offs in tree size and the heterogeneity and stem-to-tip distribution of branching events. These trade-offs are indicative of the instability of certain diversification patterns and effectively bound speciation rates (for successful clades within upper and lower limits. Finally, both the constrained range and geometry of phylogenetic space are established by the differential effects of macroevolutionary processes on patterns of diversification. Given these properties, we show that the average path through phylogenetic space over evolutionary time traverses several diversification stages, each of which is defined by a different principal pattern of diversification and directed by a different macroevolutionary process. The identification of universal patterns and natural constraints to diversification provides a foundation for understanding the

  20. Different-Level Simultaneous Minimization Scheme for Fault Tolerance of Redundant Manipulator Aided with Discrete-Time Recurrent Neural Network

    Directory of Open Access Journals (Sweden)

    Long Jin

    2017-09-01

    Full Text Available By incorporating the physical constraints in joint space, a different-level simultaneous minimization scheme, which takes both the robot kinematics and robot dynamics into account, is presented and investigated for fault-tolerant motion planning of redundant manipulator in this paper. The scheme is reformulated as a quadratic program (QP with equality and bound constraints, which is then solved by a discrete-time recurrent neural network. Simulative verifications based on a six-link planar redundant robot manipulator substantiate the efficacy and accuracy of the presented acceleration fault-tolerant scheme, the resultant QP and the corresponding discrete-time recurrent neural network.

  1. Different-Level Simultaneous Minimization Scheme for Fault Tolerance of Redundant Manipulator Aided with Discrete-Time Recurrent Neural Network.

    Science.gov (United States)

    Jin, Long; Liao, Bolin; Liu, Mei; Xiao, Lin; Guo, Dongsheng; Yan, Xiaogang

    2017-01-01

    By incorporating the physical constraints in joint space, a different-level simultaneous minimization scheme, which takes both the robot kinematics and robot dynamics into account, is presented and investigated for fault-tolerant motion planning of redundant manipulator in this paper. The scheme is reformulated as a quadratic program (QP) with equality and bound constraints, which is then solved by a discrete-time recurrent neural network. Simulative verifications based on a six-link planar redundant robot manipulator substantiate the efficacy and accuracy of the presented acceleration fault-tolerant scheme, the resultant QP and the corresponding discrete-time recurrent neural network.

  2. Neural Network Ensembles

    DEFF Research Database (Denmark)

    Hansen, Lars Kai; Salamon, Peter

    1990-01-01

    We propose several means for improving the performance an training of neural networks for classification. We use crossvalidation as a tool for optimizing network parameters and architecture. We show further that the remaining generalization error can be reduced by invoking ensembles of similar...... networks....

  3. Neural systems for control

    National Research Council Canada - National Science Library

    Omidvar, Omid; Elliott, David L

    1997-01-01

    ... is reprinted with permission from A. Barto, "Reinforcement Learning," Handbook of Brain Theory and Neural Networks, M.A. Arbib, ed.. The MIT Press, Cambridge, MA, pp. 804-809, 1995. Chapter 4, Figures 4-5 and 7-9 and Tables 2-5, are reprinted with permission, from S. Cho, "Map Formation in Proprioceptive Cortex," International Jour...

  4. Neural Tube Defects

    Science.gov (United States)

    ... pregnancies each year in the United States. A baby’s neural tube normally develops into the brain and spinal cord. ... fluid in the brain. This is called hydrocephalus. Babies with this condition are treated with surgery to insert a tube (called a shunt) into the brain. The shunt ...

  5. UAV Trajectory Modeling Using Neural Networks

    Science.gov (United States)

    Xue, Min

    2017-01-01

    Large amount of small Unmanned Aerial Vehicles (sUAVs) are projected to operate in the near future. Potential sUAV applications include, but not limited to, search and rescue, inspection and surveillance, aerial photography and video, precision agriculture, and parcel delivery. sUAVs are expected to operate in the uncontrolled Class G airspace, which is at or below 500 feet above ground level (AGL), where many static and dynamic constraints exist, such as ground properties and terrains, restricted areas, various winds, manned helicopters, and conflict avoidance among sUAVs. How to enable safe, efficient, and massive sUAV operations at the low altitude airspace remains a great challenge. NASA's Unmanned aircraft system Traffic Management (UTM) research initiative works on establishing infrastructure and developing policies, requirement, and rules to enable safe and efficient sUAVs' operations. To achieve this goal, it is important to gain insights of future UTM traffic operations through simulations, where the accurate trajectory model plays an extremely important role. On the other hand, like what happens in current aviation development, trajectory modeling should also serve as the foundation for any advanced concepts and tools in UTM. Accurate models of sUAV dynamics and control systems are very important considering the requirement of the meter level precision in UTM operations. The vehicle dynamics are relatively easy to derive and model, however, vehicle control systems remain unknown as they are usually kept by manufactures as a part of intellectual properties. That brings challenges to trajectory modeling for sUAVs. How to model the vehicle's trajectories with unknown control system? This work proposes to use a neural network to model a vehicle's trajectory. The neural network is first trained to learn the vehicle's responses at numerous conditions. Once being fully trained, given current vehicle states, winds, and desired future trajectory, the neural

  6. A-Lamp: Adaptive Layout-Aware Multi-Patch Deep Convolutional Neural Network for Photo Aesthetic Assessment

    OpenAIRE

    Ma, Shuang; Liu, Jing; Chen, Chang Wen

    2017-01-01

    Deep convolutional neural networks (CNN) have recently been shown to generate promising results for aesthetics assessment. However, the performance of these deep CNN methods is often compromised by the constraint that the neural network only takes the fixed-size input. To accommodate this requirement, input images need to be transformed via cropping, warping, or padding, which often alter image composition, reduce image resolution, or cause image distortion. Thus the aesthetics of the origina...

  7. Tracking error constrained robust adaptive neural prescribed performance control for flexible hypersonic flight vehicle

    Directory of Open Access Journals (Sweden)

    Zhonghua Wu

    2017-02-01

    Full Text Available A robust adaptive neural control scheme based on a back-stepping technique is developed for the longitudinal dynamics of a flexible hypersonic flight vehicle, which is able to ensure the state tracking error being confined in the prescribed bounds, in spite of the existing model uncertainties and actuator constraints. Minimal learning parameter technique–based neural networks are used to estimate the model uncertainties; thus, the amount of online updated parameters is largely lessened, and the prior information of the aerodynamic parameters is dispensable. With the utilization of an assistant compensation system, the problem of actuator constraint is overcome. By combining the prescribed performance function and sliding mode differentiator into the neural back-stepping control design procedure, a composite state tracking error constrained adaptive neural control approach is presented, and a new type of adaptive law is constructed. As compared with other adaptive neural control designs for hypersonic flight vehicle, the proposed composite control scheme exhibits not only low-computation property but also strong robustness. Finally, two comparative simulations are performed to demonstrate the robustness of this neural prescribed performance controller.

  8. Understanding the Implications of Neural Population Activity on Behavior

    Science.gov (United States)

    Briguglio, John

    Learning how neural activity in the brain leads to the behavior we exhibit is one of the fundamental questions in Neuroscience. In this dissertation, several lines of work are presented to that use principles of neural coding to understand behavior. In one line of work, we formulate the efficient coding hypothesis in a non-traditional manner in order to test human perceptual sensitivity to complex visual textures. We find a striking agreement between how variable a particular texture signal is and how sensitive humans are to its presence. This reveals that the efficient coding hypothesis is still a guiding principle for neural organization beyond the sensory periphery, and that the nature of cortical constraints differs from the peripheral counterpart. In another line of work, we relate frequency discrimination acuity to neural responses from auditory cortex in mice. It has been previously observed that optogenetic manipulation of auditory cortex, in addition to changing neural responses, evokes changes in behavioral frequency discrimination. We are able to account for changes in frequency discrimination acuity on an individual basis by examining the Fisher information from the neural population with and without optogenetic manipulation. In the third line of work, we address the question of what a neural population should encode given that its inputs are responses from another group of neurons. Drawing inspiration from techniques in machine learning, we train Deep Belief Networks on fake retinal data and show the emergence of Garbor-like filters, reminiscent of responses in primary visual cortex. In the last line of work, we model the state of a cortical excitatory-inhibitory network during complex adaptive stimuli. Using a rate model with Wilson-Cowan dynamics, we demonstrate that simple non-linearities in the signal transferred from inhibitory to excitatory neurons can account for real neural recordings taken from auditory cortex. This work establishes and tests

  9. Constraint satisfaction problems CSP formalisms and techniques

    CERN Document Server

    Ghedira, Khaled

    2013-01-01

    A Constraint Satisfaction Problem (CSP) consists of a set of variables, a domain of values for each variable and a set of constraints. The objective is to assign a value for each variable such that all constraints are satisfied. CSPs continue to receive increased attention because of both their high complexity and their omnipresence in academic, industrial and even real-life problems. This is why they are the subject of intense research in both artificial intelligence and operations research. This book introduces the classic CSP and details several extensions/improvements of both formalisms a

  10. QCD unitarity constraints on Reggeon Field Theory

    Energy Technology Data Exchange (ETDEWEB)

    Kovner, Alex [Physics Department, University of Connecticut,2152 Hillside Road, Storrs, CT 06269 (United States); Levin, Eugene [Departemento de Física, Universidad Técnica Federico Santa María,and Centro Científico-Tecnológico de Valparaíso,Avda. Espana 1680, Casilla 110-V, Valparaíso (Chile); Department of Particle Physics, Tel Aviv University,Tel Aviv 69978 (Israel); Lublinsky, Michael [Physics Department, Ben-Gurion University of the Negev,Beer Sheva 84105 (Israel); Physics Department, University of Connecticut,2152 Hillside Road, Storrs, CT 06269 (United States)

    2016-08-04

    We point out that the s-channel unitarity of QCD imposes meaningful constraints on a possible form of the QCD Reggeon Field Theory. We show that neither the BFKL nor JIMWLK nor Braun’s Hamiltonian satisfy the said constraints. In a toy, zero transverse dimensional case we construct a model that satisfies the analogous constraint and show that at infinite energy it indeed tends to a “black disk limit' as opposed to the model with triple Pomeron vertex only, routinely used as a toy model in the literature.

  11. CONSTRAINT EFFECT IN FRACTURE WHAT IS IT

    Energy Technology Data Exchange (ETDEWEB)

    Lam, P; Prof. Yuh J. Chao, P

    2008-10-29

    The meaning of the phrase 'constraint effect in fracture' has changed in the past two decades from 'contained plasticity' to a broader description of 'dependence of fracture toughness value on geometry of test specimen or structure'. This paper will first elucidate the fundamental mechanics reasons for the apparent 'constraint effects in fracture', followed by outlining a straightforward approach to overcoming this problem in both brittle (elastic) and ductile (elastic-plastic) fracture. It is concluded by discussing the major difference in constraint effect on fracture event in elastic and elastic-plastic materials.

  12. COHERENT constraints on nonstandard neutrino interactions

    Science.gov (United States)

    Liao, Jiajun; Marfatia, Danny

    2017-12-01

    Coherent elastic neutrino-nucleus scattering consistent with the standard model has been observed by the COHERENT experiment. We study nonstandard neutrino interactions using the detected spectrum. For the case in which the nonstandard interactions (NSI) are induced by a vector mediator lighter than 50 MeV, we obtain constraints on the coupling of the mediator. For a heavier mediator, we find that degeneracies between the NSI parameters severely weaken the constraints. However, these degeneracies do not affect COHERENT constraints on the effective NSI parameters for matter propagation in the Earth.

  13. Relaxations of semiring constraint satisfaction problems

    CSIR Research Space (South Africa)

    Leenen, L

    2007-03-01

    Full Text Available 5 ted by Abstract The Semiring Constraint Satisfaction Problem (SCSP) framework is a popular approach for the representation of partial con- straint satisfaction problems. In this framework preferences can be associated with tuples of values... of the domains of con- straints. The operator × is used to combine constraints in order to find a solution (i.e., a single constraint) to a SCSP, and the operator + is used to define the c-value of the projection of a tuple of values over a set of vari...

  14. Forecasting volatility with neural regression: a contribution to model adequacy.

    Science.gov (United States)

    Refenes, A N; Holt, W T

    2001-01-01

    Neural nets' usefulness for forecasting is limited by problems of overfitting and the lack of rigorous procedures for model identification, selection and adequacy testing. This paper describes a methodology for neural model misspecification testing. We introduce a generalization of the Durbin-Watson statistic for neural regression and discuss the general issues of misspecification testing using residual analysis. We derive a generalized influence matrix for neural estimators which enables us to evaluate the distribution of the statistic. We deploy Monte Carlo simulation to compare the power of the test for neural and linear regressors. While residual testing is not a sufficient condition for model adequacy, it is nevertheless a necessary condition to demonstrate that the model is a good approximation to the data generating process, particularly as neural-network estimation procedures are susceptible to partial convergence. The work is also an important step toward developing rigorous procedures for neural model identification, selection and adequacy testing which have started to appear in the literature. We demonstrate its applicability in the nontrivial problem of forecasting implied volatility innovations using high-frequency stock index options. Each step of the model building process is validated using statistical tests to verify variable significance and model adequacy with the results confirming the presence of nonlinear relationships in implied volatility innovations.

  15. Advances in neurocognitive rehabilitation research from 1992 to 2017: The ascension of neural plasticity.

    Science.gov (United States)

    Crosson, Bruce; Hampstead, Benjamin M; Krishnamurthy, Lisa C; Krishnamurthy, Venkatagiri; McGregor, Keith M; Nocera, Joe R; Roberts, Simone; Rodriguez, Amy D; Tran, Stella M

    2017-11-01

    The last 25 years have seen profound changes in neurocognitive rehabilitation that continue to motivate its evolution. Although the concept of nervous system plasticity was discussed by William James (1890), the foundation for experience-based plasticity had not reached the critical empirical mass to seriously impact rehabilitation research until after 1992. The objective of this review is to describe how the emergence of neural plasticity has changed neurocognitive rehabilitation research. The important developments included (a) introduction of a widely available tool that could measure brain plasticity (i.e., functional MRI); (b) development of new structural imaging techniques that could define limits of and opportunities for neural plasticity; (c) deployment of noninvasive brain stimulation to leverage neural plasticity for rehabilitation; (d) growth of a literature indicating that exercise has positively impacts neural plasticity, especially for older persons; and (e) enhancement of neural plasticity by creating interventions that generalize beyond the boundaries of treatment activities. Given the massive literature, each of these areas is developed by example. The expanding influence of neural plasticity has provided new models and tools for neurocognitive rehabilitation in neural injuries and disorders, as well as methods for measuring neural plasticity and predicting its limits and opportunities. Early clinical trials have provided very encouraging results. Now that neural plasticity has gained a firm foothold, it will continue to influence the evolution of neurocognitive rehabilitation research for the next 25 years and advance rehabilitation for neural injuries and disease. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  16. A word-order constraint on phonological activation.

    Science.gov (United States)

    Janssen, Niels; Alario, F-Xavier; Caramazza, Alfonso

    2008-03-01

    Word-order rules impose major constraints on linguistic behavior. For example, adjectives appear before nouns in English, and after nouns in French. This means that constraints on word order must be language-specific properties upheld on-line by the language system. Despite the importance of these rules, little is known about how they operate. We report an influence of word order on the activation of phonological representations. Participants were presented with colored objects and asked to name either the colors or the objects; the phonological similarity between the object and color names was manipulated. French speakers showed a phonological congruency effect in color naming, but not in object naming. English participants yielded the opposite pattern: a phonological effect in object naming, but not in color naming. Differences in the typical order of nouns and adjectives in French and English provide a plausible account for this cross-linguistic contrast. More generally, these results provide direct evidence for the operation of word-order constraints during language production.

  17. Conflicting Constraints in Resource-Adaptive Language Comprehension

    Science.gov (United States)

    Weber, Andrea; Crocker, Matthew W.; Knoeferle, Pia

    The primary goal of psycholinguistic research is to understand the architectures and mechanisms that underlie human language comprehension and production. This entails an understanding of how linguistic knowledge is represented and organized in the brain and a theory of how that knowledge is accessed when we use language. Research has traditionally emphasized purely linguistic aspects of on-line comprehension, such as the influence of lexical, syntactic, semantic and discourse constraints, and their tim -course. It has become increasingly clear, however, that nonlinguistic information, such as the visual environment, are also actively exploited by situated language comprehenders.

  18. Bioprinting for Neural Tissue Engineering.

    Science.gov (United States)

    Knowlton, Stephanie; Anand, Shivesh; Shah, Twisha; Tasoglu, Savas

    2018-01-01

    Bioprinting is a method by which a cell-encapsulating bioink is patterned to create complex tissue architectures. Given the potential impact of this technology on neural research, we review the current state-of-the-art approaches for bioprinting neural tissues. While 2D neural cultures are ubiquitous for studying neural cells, 3D cultures can more accurately replicate the microenvironment of neural tissues. By bioprinting neuronal constructs, one can precisely control the microenvironment by specifically formulating the bioink for neural tissues, and by spatially patterning cell types and scaffold properties in three dimensions. We review a range of bioprinted neural tissue models and discuss how they can be used to observe how neurons behave, understand disease processes, develop new therapies and, ultimately, design replacement tissues. Copyright © 2017 Elsevier Ltd. All rights reserved.

  19. Shaping the learning curve: epigenetic dynamics in neural plasticity.

    Science.gov (United States)

    Bronfman, Zohar Z; Ginsburg, Simona; Jablonka, Eva

    2014-01-01

    A key characteristic of learning and neural plasticity is state-dependent acquisition dynamics reflected by the non-linear learning curve that links increase in learning with practice. Here we propose that the manner by which epigenetic states of individual cells change during learning contributes to the shape of the neural and behavioral learning curve. We base our suggestion on recent studies showing that epigenetic mechanisms such as DNA methylation, histone acetylation, and RNA-mediated gene regulation are intimately involved in the establishment and maintenance of long-term neural plasticity, reflecting specific learning-histories and influencing future learning. Our model, which is the first to suggest a dynamic molecular account of the shape of the learning curve, leads to several testable predictions regarding the link between epigenetic dynamics at the promoter, gene-network, and neural-network levels. This perspective opens up new avenues for therapeutic interventions in neurological pathologies.

  20. The Ambiguous Role of Constraints in Creativity: A Cross-Domain Exploration

    DEFF Research Database (Denmark)

    Biskjaer, Michael Mose; Onarheim, Balder; Wiltschnig, Stefan

    2011-01-01

    The relationship between creativity and constraints is often described in the literature either in rather imprecise, general concepts or in relation to very specific domains. Cross-domain and cross-disciplinary takes on how the handling of constraints influences creative activities are rare....... In this paper, we explore these particular issues in two creative domains: art and engineering design. These domains vary so greatly in terms of number and types of constraints in play that we argue for considering them as opposite extremes of a continuum of levels of creative freedom. By comparing two case...... studies of Danish cutting-edge proponents of creative expertise thus exemplifying each domain, this preliminary exploration mainly focuses on similarities in how such successful professionals work with constraints to frame their creative process and ensure its progression toward the final outcome. Our...

  1. Choco: an Open Source Java Constraint Programming Library

    OpenAIRE

    Jussien, Narendra; Rochart, Guillaume; Lorca, Xavier

    2008-01-01

    International audience; Choco is a java library for constraint satisfaction problems (CSP), constraint programming (CP) and explanation-based constraint solving (e-CP). It is built on a event-based propagation mechanism with backtrackable structures.

  2. Application-Specific Constraints for Multimedia Presentation Generation

    NARCIS (Netherlands)

    J.P.T.M. Geurts (Joost); J.R. van Ossenbruggen (Jacco); L. Hardman (Lynda)

    2001-01-01

    textabstractThe paper describes the advantages of the use of constraint logic programming to articulate transformation rules for multimedia presentation in combination with efficient constraint solving techniques. It demonstrates the need for two different types of constraints. Quantitative

  3. Comparing Evolutionary Algorithms on Binary Constraint Satisfaction Problems

    NARCIS (Netherlands)

    Craenen, B.G.W.; Eiben, A.E.; van Hemert, J.I.

    2003-01-01

    Constraint handling is not straightforward in evolutionary algorithms (EAs) since the usual search operators, mutation and recombination, are 'blind' to constraints. Nevertheless, the issue is highly relevant, for many challenging problems involve constraints. Over the last decade, numerous EAs for

  4. Constraints To Farmers Effective Participation In Agricultural ...

    African Journals Online (AJOL)

    eastern Nigeria is the provision of agricultural extension services to farmers. This study, therefore, examined the constraints to farmers' effective participation in the agricultural extension programmes of four non-profit NGOs in three states of ...

  5. Constraint theory multidimensional mathematical model management

    CERN Document Server

    Friedman, George J

    2017-01-01

    Packed with new material and research, this second edition of George Friedman’s bestselling Constraint Theory remains an invaluable reference for all engineers, mathematicians, and managers concerned with modeling. As in the first edition, this text analyzes the way Constraint Theory employs bipartite graphs and presents the process of locating the “kernel of constraint” trillions of times faster than brute-force approaches, determining model consistency and computational allowability. Unique in its abundance of topological pictures of the material, this book balances left- and right-brain perceptions to provide a thorough explanation of multidimensional mathematical models. Much of the extended material in this new edition also comes from Phan Phan’s PhD dissertation in 2011, titled “Expanding Constraint Theory to Determine Well-Posedness of Large Mathematical Models.” Praise for the first edition: "Dr. George Friedman is indisputably the father of the very powerful methods of constraint theory...

  6. Biological constraints do not entail cognitive closure.

    Science.gov (United States)

    Vlerick, Michael

    2014-12-01

    From the premise that our biology imposes cognitive constraints on our epistemic activities, a series of prominent authors--most notably Fodor, Chomsky and McGinn--have argued that we are cognitively closed to certain aspects and properties of the world. Cognitive constraints, they argue, entail cognitive closure. I argue that this is not the case. More precisely, I detect two unwarranted conflations at the core of arguments deriving closure from constraints. The first is a conflation of what I will refer to as 'representation' and 'object of representation'. The second confuses the cognitive scope of the assisted mind for that of the unassisted mind. Cognitive closure, I conclude, cannot be established from pointing out the (uncontroversial) existence of cognitive constraints. Copyright © 2014 Elsevier Ltd. All rights reserved.

  7. Short-sale Constraints and Credit Runs

    DEFF Research Database (Denmark)

    Venter, Gyuri

    This paper studies how short-sale constraints affect the informational efficiency of market prices and the link between prices and economic activity. I show that under short-sale constraints security prices contain less information. However, short-sale constraints increase the informativeness...... of prices to some agents who learn about the quality of an investment opportunity from market prices and have additional private information. Then I apply this observation when modeling a run on an investment bank by its short-term creditors, who are endowed with dispersed information and also learn from......), creditors with high private signals are more lenient to roll over debt, and a bank with lower asset quality remains solvent. This leads to higher allocative efficiency in the real economy. My result thus implies that the decrease in average informativeness due to short-sale constraints can be more than...

  8. Constraint Specialisation in Horn Clause Verification

    DEFF Research Database (Denmark)

    Kafle, Bishoksan; Gallagher, John Patrick

    2015-01-01

    We present a method for specialising the constraints in constrained Horn clauses with respect to a goal. We use abstract interpretation to compute a model of a query-answer transformation of a given set of clauses and a goal. The effect is to propagate the constraints from the goal top-down and p......We present a method for specialising the constraints in constrained Horn clauses with respect to a goal. We use abstract interpretation to compute a model of a query-answer transformation of a given set of clauses and a goal. The effect is to propagate the constraints from the goal top...... results on verification problems show that this is an effective transformation, both in our own verification tools (convex polyhedra analyser) and as a pre-processor to other Horn clause verification tools....

  9. Constraint specialisation in Horn clause verification

    DEFF Research Database (Denmark)

    Kafle, Bishoksan; Gallagher, John Patrick

    2017-01-01

    We present a method for specialising the constraints in constrained Horn clauses with respect to a goal. We use abstract interpretation to compute a model of a query–answer transformed version of a given set of clauses and a goal. The constraints from the model are then used to compute a speciali......We present a method for specialising the constraints in constrained Horn clauses with respect to a goal. We use abstract interpretation to compute a model of a query–answer transformed version of a given set of clauses and a goal. The constraints from the model are then used to compute...... underlying the clauses. Experimental results on verification problems show that this is an effective transformation, both in our own verification tools (based on a convex polyhedra analyser) and as a pre-processor to other Horn clause verification tools....

  10. Integrity Constraint Checking in Federated Databases

    NARCIS (Netherlands)

    Grefen, P.W.P.J.; Widom, Jennifer

    A federated database is comprised of multiple interconnected databases that cooperate in an autonomous fashion. Global integrity constraints are very useful in federated databases, but the lack of global queries, global transaction mechanisms, and global concurrency control renders traditional

  11. Ligand-based virtual screening under partial shape constraints

    Science.gov (United States)

    von Behren, Mathias M.; Rarey, Matthias

    2017-04-01

    Ligand-based virtual screening has proven to be a viable technology during the search for new lead structures in drug discovery. Despite the rapidly increasing number of published methods, meaningful shape matching as well as ligand and target flexibility still remain open challenges. In this work, we analyze the influence of knowledge-based sterical constraints on the performance of the recently published ligand-based virtual screening method mRAISE. We introduce the concept of partial shape matching enabling a more differentiated view on chemical structure. The new method is integrated into the LBVS tool mRAISE providing multiple options for such constraints. The applied constraints can either be derived automatically from a protein-ligand complex structure or by manual selection of ligand atoms. In this way, the descriptor directly encodes the fit of a ligand into the binding site. Furthermore, the conservation of close contacts between the binding site surface and the query ligand can be enforced. We validated our new method on the DUD and DUD-E datasets. Although the statistical performance remains on the same level, detailed analysis reveal that for certain and especially very flexible targets a significant improvement can be achieved. This is further highlighted looking at the quality of calculated molecular alignments using the recently introduced mRAISE dataset. The new partial shape constraints improved the overall quality of molecular alignments especially for difficult targets with highly flexible or different sized molecules. The software tool mRAISE is freely available on Linux operating systems for evaluation purposes and academic use (see http://www.zbh.uni-hamburg.de/raise).

  12. Ligand-based virtual screening under partial shape constraints.

    Science.gov (United States)

    von Behren, Mathias M; Rarey, Matthias

    2017-04-01

    Ligand-based virtual screening has proven to be a viable technology during the search for new lead structures in drug discovery. Despite the rapidly increasing number of published methods, meaningful shape matching as well as ligand and target flexibility still remain open challenges. In this work, we analyze the influence of knowledge-based sterical constraints on the performance of the recently published ligand-based virtual screening method mRAISE. We introduce the concept of partial shape matching enabling a more differentiated view on chemical structure. The new method is integrated into the LBVS tool mRAISE providing multiple options for such constraints. The applied constraints can either be derived automatically from a protein-ligand complex structure or by manual selection of ligand atoms. In this way, the descriptor directly encodes the fit of a ligand into the binding site. Furthermore, the conservation of close contacts between the binding site surface and the query ligand can be enforced. We validated our new method on the DUD and DUD-E datasets. Although the statistical performance remains on the same level, detailed analysis reveal that for certain and especially very flexible targets a significant improvement can be achieved. This is further highlighted looking at the quality of calculated molecular alignments using the recently introduced mRAISE dataset. The new partial shape constraints improved the overall quality of molecular alignments especially for difficult targets with highly flexible or different sized molecules. The software tool mRAISE is freely available on Linux operating systems for evaluation purposes and academic use (see http://www.zbh.uni-hamburg.de/raise ).

  13. Synchronized sweep algorithms for scalable scheduling constraints

    OpenAIRE

    Letort, Arnaud; Carlsson, Mats; Beldiceanu, Nicolas

    2013-01-01

    This report introduces a family of synchronized sweep based filtering algorithms for handling scheduling problems involving resource and precedence constraints. The key idea is to filter all constraints of a scheduling problem in a synchronized way in order to scale better. In addition to normal filtering mode, the algorithms can run in greedy mode, in which case they perform a greedy assignment of start and end times. The filtering mode achieves a significant speed-up over ...

  14. Creating buzz: the neural correlates of effective message propagation.

    Science.gov (United States)

    Falk, Emily B; Morelli, Sylvia A; Welborn, B Locke; Dambacher, Karl; Lieberman, Matthew D

    2013-07-01

    Social interaction promotes the spread of values, attitudes, and behaviors. Here, we report on neural responses to ideas that are destined to spread. We scanned message communicators using functional MRI during their initial exposure to the to-be-communicated ideas. These message communicators then had the opportunity to spread the messages and their corresponding subjective evaluations to message recipients outside the scanner. Successful ideas were associated with neural responses in the communicators' mentalizing systems and reward systems when they first heard the messages, prior to spreading them. Similarly, individuals more able to spread their own views to others produced greater mentalizing-system activity during initial encoding. Unlike prior social-influence studies that focused on the individuals being influenced, this investigation focused on the brains of influencers. Successful social influence is reliably associated with an influencer-to-be's state of mind when first encoding ideas.

  15. Neural network technologies

    Science.gov (United States)

    Villarreal, James A.

    1991-01-01

    A whole new arena of computer technologies is now beginning to form. Still in its infancy, neural network technology is a biologically inspired methodology which draws on nature's own cognitive processes. The Software Technology Branch has provided a software tool, Neural Execution and Training System (NETS), to industry, government, and academia to facilitate and expedite the use of this technology. NETS is written in the C programming language and can be executed on a variety of machines. Once a network has been debugged, NETS can produce a C source code which implements the network. This code can then be incorporated into other software systems. Described here are various software projects currently under development with NETS and the anticipated future enhancements to NETS and the technology.

  16. Analysis of neural data

    CERN Document Server

    Kass, Robert E; Brown, Emery N

    2014-01-01

    Continual improvements in data collection and processing have had a huge impact on brain research, producing data sets that are often large and complicated. By emphasizing a few fundamental principles, and a handful of ubiquitous techniques, Analysis of Neural Data provides a unified treatment of analytical methods that have become essential for contemporary researchers. Throughout the book ideas are illustrated with more than 100 examples drawn from the literature, ranging from electrophysiology, to neuroimaging, to behavior. By demonstrating the commonality among various statistical approaches the authors provide the crucial tools for gaining knowledge from diverse types of data. Aimed at experimentalists with only high-school level mathematics, as well as computationally-oriented neuroscientists who have limited familiarity with statistics, Analysis of Neural Data serves as both a self-contained introduction and a reference work.

  17. Neural tube defects

    Directory of Open Access Journals (Sweden)

    M.E. Marshall

    1981-09-01

    Full Text Available Neural tube defects refer to any defect in the morphogenesis of the neural tube, the most common types being spina bifida and anencephaly. Spina bifida has been recognised in skeletons found in north-eastern Morocco and estimated to have an age of almost 12 000 years. It was also known to the ancient Greek and Arabian physicians who thought that the bony defect was due to the tumour. The term spina bifida was first used by Professor Nicolai Tulp of Amsterdam in 1652. Many other terms have been used to describe this defect, but spina bifida remains the most useful general term, as it describes the separation of the vertebral elements in the midline.

  18. Safety-Guaranteed Trajectory Tracking Control for the Underactuated Hovercraft with State and Input Constraints

    Directory of Open Access Journals (Sweden)

    Mingyu Fu

    2017-01-01

    Full Text Available This paper develops a safety-guaranteed trajectory tracking controller for hovercraft by using a safety-guaranteed auxiliary dynamic system, an integral sliding mode control, and an adaptive neural network method. The safety-guaranteed auxiliary dynamic system is designed to implement system state and input constraints. By considering the relationship of velocity and resistance hump, the velocity of hovercraft is constrained to eliminate the effect of resistance hump and obtain better stability. And the safety limit of drift angle is well performed to guarantee the light safe maneuvers of hovercraft tracking with high velocities. In view of the natural capabilities of actuators, the control input is constrained. High nonlinearity and model uncertainties of hovercraft are approximated by employing adaptive radical basis function neural networks. The proposed controller guarantees the boundedness of all the closed-loop signals. Specifically, the tracking errors are uniformly ultimately bounded. Numerical simulations are implemented to demonstrate the efficacy of the designed controller.

  19. Proliferating resident microglia express the stem cell antigen CD34 in response to acute neural injury

    DEFF Research Database (Denmark)

    Ladeby, Rune; Wirenfeldt, Martin; Dalmau, Ishar

    2005-01-01

    Reactive microgliosis is a highly characteristic response to neural injury and disease, which may influence neurodegenerative processes and neural plasticity. We have investigated the origin and characteristics of reactive microglia in the acute phase of their activation in the dentate gyrus...

  20. Forecasting macroeconomic variables using neural network models and three automated model selection techniques

    DEFF Research Database (Denmark)

    Kock, Anders Bredahl; Teräsvirta, Timo

    2016-01-01

    When forecasting with neural network models one faces several problems, all of which influence the accuracy of the forecasts. First, neural networks are often hard to estimate due to their highly nonlinear structure. To alleviate the problem, White (2006) presented a solution (QuickNet...

  1. On the neural mechanisms subserving consciousness and attention

    Directory of Open Access Journals (Sweden)

    Catherine eTallon-Baudry

    2012-01-01

    Full Text Available Consciousness, as described in the experimental literature, is a multi-faceted phenomenon, that impinges on other well-studied concepts such as attention and control. Do consciousness and attention refer to different aspects of the same core phenomenon, or do they correspond to distinct functions? One possibility to address this question is to examine the neural mechanisms underlying consciousness and attention. If consciousness and attention pertain to the same concept, they should rely on shared neural mechanisms. Conversely, if their underlying mechanisms are distinct, then consciousness and attention should be considered as distinct entities. This paper therefore reviews neurophysiological facts arguing in favor or against a tight relationship between consciousness and attention. Three neural mechanisms that have been associated with both attention and consciousness are examined (neural amplification, involvement of the fronto-parietal network, and oscillatory synchrony, to conclude that the commonalities between attention and consciousness at the neural level may have been overestimated. Last but not least, experiments in which both attention and consciousness were probed at the neural level point toward a dissociation between the two concepts. It therefore appears from this review that consciousness and attention rely on distinct neural properties, although they can interact at the behavioral level. It is proposed that a "cumulative influence model", in which attention and consciousness correspond to distinct neural mechanisms feeding a single decisional process leading to behavior, fits best with available neural and behavioral data. In this view, consciousness should not be considered as a top-level executive function but should rather be defined by its experiential properties.

  2. Neural networks for triggering

    Energy Technology Data Exchange (ETDEWEB)

    Denby, B. (Fermi National Accelerator Lab., Batavia, IL (USA)); Campbell, M. (Michigan Univ., Ann Arbor, MI (USA)); Bedeschi, F. (Istituto Nazionale di Fisica Nucleare, Pisa (Italy)); Chriss, N.; Bowers, C. (Chicago Univ., IL (USA)); Nesti, F. (Scuola Normale Superiore, Pisa (Italy))

    1990-01-01

    Two types of neural network beauty trigger architectures, based on identification of electrons in jets and recognition of secondary vertices, have been simulated in the environment of the Fermilab CDF experiment. The efficiencies for B's and rejection of background obtained are encouraging. If hardware tests are successful, the electron identification architecture will be tested in the 1991 run of CDF. 10 refs., 5 figs., 1 tab.

  3. Artificial neural network modelling

    CERN Document Server

    Samarasinghe, Sandhya

    2016-01-01

    This book covers theoretical aspects as well as recent innovative applications of Artificial Neural networks (ANNs) in natural, environmental, biological, social, industrial and automated systems. It presents recent results of ANNs in modelling small, large and complex systems under three categories, namely, 1) Networks, Structure Optimisation, Robustness and Stochasticity 2) Advances in Modelling Biological and Environmental Systems and 3) Advances in Modelling Social and Economic Systems. The book aims at serving undergraduates, postgraduates and researchers in ANN computational modelling. .

  4. Neurally-mediated sincope.

    Science.gov (United States)

    Can, I; Cytron, J; Jhanjee, R; Nguyen, J; Benditt, D G

    2009-08-01

    Syncope is a syndrome characterized by a relatively sudden, temporary and self-terminating loss of consciousness; the causes may vary, but they have in common a temporary inadequacy of cerebral nutrient flow, usually due to a fall in systemic arterial pressure. However, while syncope is a common problem, it is only one explanation for episodic transient loss of consciousness (TLOC). Consequently, diagnostic evaluation should start with a broad consideration of real or seemingly real TLOC. Among those patients in whom TLOC is deemed to be due to ''true syncope'', the focus may then reasonably turn to assessing the various possible causes; in this regard, the neurally-mediated syncope syndromes are among the most frequently encountered. There are three common variations: vasovagal syncope (often termed the ''common'' faint), carotid sinus syndrome, and the so-called ''situational faints''. Defining whether the cause is due to a neurally-mediated reflex relies heavily on careful history taking and selected testing (e.g., tilt-test, carotid massage). These steps are important. Despite the fact that neurally-mediated faints are usually relatively benign from a mortality perspective, they are nevertheless only infrequently an isolated event; neurally-mediated syncope tends to recur, and physical injury resulting from falls or accidents, diminished quality-of-life, and possible restriction from employment or avocation are real concerns. Consequently, defining the specific form and developing an effective treatment strategy are crucial. In every case the goal should be to determine the cause of syncope with sufficient confidence to provide patients and family members with a reliable assessment of prognosis, recurrence risk, and treatment options.

  5. The Neural Noisy Channel

    OpenAIRE

    Yu, Lei; Blunsom, Phil; Dyer, Chris; Grefenstette, Edward; Kocisky, Tomas

    2016-01-01

    We formulate sequence to sequence transduction as a noisy channel decoding problem and use recurrent neural networks to parameterise the source and channel models. Unlike direct models which can suffer from explaining-away effects during training, noisy channel models must produce outputs that explain their inputs, and their component models can be trained with not only paired training samples but also unpaired samples from the marginal output distribution. Using a latent variable to control ...

  6. Efeitos do potencial de ação neural sobre a percepção de fala em usuários de implante coclear Influence of evoked compound action potential on speech perception in cochlear implant users

    Directory of Open Access Journals (Sweden)

    Mariana Cardoso Guedes

    2007-08-01

    Full Text Available O Potencial de Ação Composto Evocado Eletricamente reflete a atividade do nervo auditivo, podendo ser registrado através dos eletrodos do implante coclear. A determinação dos elementos neurais estimuláveis pode contribuir para explicar a variabilidade de desempenho entre indivíduos implantados. OBJETIVO: Comparar o desempenho nos testes de percepção da fala entre pacientes que apresentaram e que não apresentaram potencial de ação composto evocado eletricamente no momento intra-operatório. MATERIAL E MÉTODO: Estudo prospectivo no qual 100 indivíduos usuários do implante coclear Nucleus 24 foram divididos em dois grupos de acordo com a presença ou ausência do potencial de ação intra-operatório. Após 6 meses de uso do dispositivo, os resultados dos testes de percepção de fala foram comparados entre os grupos. RESULTADOS: O potencial foi observado em 72% dos pacientes. A percepção no teste de frases em formato aberto foi melhor nos indivíduos com presença de potencial (média 82,8% contra 41,0%, p = 0,005. Houve associação entre ausência do potencial e etiologia da surdez por meningite. CONCLUSÃO: Ausência de potencial neural intraoperatório esteve associada ao pior desempenho na percepção da fala e à etiologia da surdez por meningite. Por outro lado, a presença do potencial de ação intraoperatório sugere ótimo prognóstico.Electrically Evoked Compound Action Potential is a measure of synchronous cochlear nerve fibers activity elicited by electrical stimulation of the cochlear implant. The electrophysiological nerve responses may contribute to explain the variability in individual performance of cochlear implant recipients. AIM: To compare speech perception tests’ performances of cochlear implant users according to the presence or absence of intraoperative neural telemetry responses. MATERIAL AND METHOD: Prospective study design with 100 "Nucleus 24" cochlear implant users divided in two groups according

  7. Natural language acquisition in large scale neural semantic networks

    Science.gov (United States)

    Ealey, Douglas

    This thesis puts forward the view that a purely signal- based approach to natural language processing is both plausible and desirable. By questioning the veracity of symbolic representations of meaning, it argues for a unified, non-symbolic model of knowledge representation that is both biologically plausible and, potentially, highly efficient. Processes to generate a grounded, neural form of this model-dubbed the semantic filter-are discussed. The combined effects of local neural organisation, coincident with perceptual maturation, are used to hypothesise its nature. This theoretical model is then validated in light of a number of fundamental neurological constraints and milestones. The mechanisms of semantic and episodic development that the model predicts are then used to explain linguistic properties, such as propositions and verbs, syntax and scripting. To mimic the growth of locally densely connected structures upon an unbounded neural substrate, a system is developed that can grow arbitrarily large, data- dependant structures composed of individual self- organising neural networks. The maturational nature of the data used results in a structure in which the perception of concepts is refined by the networks, but demarcated by subsequent structure. As a consequence, the overall structure shows significant memory and computational benefits, as predicted by the cognitive and neural models. Furthermore, the localised nature of the neural architecture also avoids the increasing error sensitivity and redundancy of traditional systems as the training domain grows. The semantic and episodic filters have been demonstrated to perform as well, or better, than more specialist networks, whilst using significantly larger vocabularies, more complex sentence forms and more natural corpora.

  8. Constraint-Muse: A Soft-Constraint Based System for Music Therapy

    Science.gov (United States)

    Hölzl, Matthias; Denker, Grit; Meier, Max; Wirsing, Martin

    Monoidal soft constraints are a versatile formalism for specifying and solving multi-criteria optimization problems with dynamically changing user preferences. We have developed a prototype tool for interactive music creation, called Constraint Muse, that uses monoidal soft constraints to ensure that a dynamically generated melody harmonizes with input from other sources. Constraint Muse provides an easy to use interface based on Nintendo Wii controllers and is intended to be used in music therapy for people with Parkinson’s disease and for children with high-functioning autism or Asperger’s syndrome.

  9. Imposing Constraints from the Source Tree on ITG Constraints for SMT

    Science.gov (United States)

    Yamamoto, Hirofumi; Okuma, Hideo; Sumita, Eiichiro

    In the current statistical machine translation (SMT), erroneous word reordering is one of the most serious problems. To resolve this problem, many word-reordering constraint techniques have been proposed. Inversion transduction grammar (ITG) is one of these constraints. In ITG constraints, target-side word order is obtained by rotating nodes of the source-side binary tree. In these node rotations, the source binary tree instance is not considered. Therefore, stronger constraints for word reordering can be obtained by imposing further constraints derived from the source tree on the ITG constraints. For example, for the source word sequence { a b c d }, ITG constraints allow a total of twenty-two target word orderings. However, when the source binary tree instance ((a b) (c d)) is given, our proposed “imposing source tree on ITG” (IST-ITG) constraints allow only eight word orderings. The reduction in the number of word-order permutations by our proposed stronger constraints efficiently suppresses erroneous word orderings. In our experiments with IST-ITG using the NIST MT08 English-to-Chinese translation track's data, the proposed method resulted in a 1.8-points improvement in character BLEU-4 (35.2 to 37.0) and a 6.2% lower CER (74.1 to 67.9%) compared with our baseline condition.

  10. Sequentially acting Sox transcription factors in neural lineage development.

    Science.gov (United States)

    Bergsland, Maria; Ramsköld, Daniel; Zaouter, Cécile; Klum, Susanne; Sandberg, Rickard; Muhr, Jonas

    2011-12-01

    Pluripotent embryonic stem (ES) cells can generate all cell types, but how cell lineages are initially specified and maintained during development remains largely unknown. Different classes of Sox transcription factors are expressed during neurogenesis and have been assigned important roles from early lineage specification to neuronal differentiation. Here we characterize the genome-wide binding for Sox2, Sox3, and Sox11, which have vital functions in ES cells, neural precursor cells (NPCs), and maturing neurons, respectively. The data demonstrate that Sox factor binding depends on developmental stage-specific constraints and reveal a remarkable sequential binding of Sox proteins to a common set of neural genes. Interestingly, in ES cells, Sox2 preselects for neural lineage-specific genes destined to be bound and activated by Sox3 in NPCs. In NPCs, Sox3 binds genes that are later bound and activated by Sox11 in differentiating neurons. Genes prebound by Sox proteins are associated with a bivalent chromatin signature, which is resolved into a permissive monovalent state upon binding of activating Sox factors. These data indicate that a single key transcription factor family acts sequentially to coordinate neural gene expression from the early lineage specification in pluripotent cells to later stages of neuronal development.

  11. Projection learning algorithm for threshold - controlled neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Reznik, A.M.

    1995-03-01

    The projection learning algorithm proposed in [1, 2] and further developed in [3] substantially improves the efficiency of memorizing information and accelerates the learning process in neural networks. This algorithm is compatible with the completely connected neural network architecture (the Hopfield network [4]), but its application to other networks involves a number of difficulties. The main difficulties include constraints on interconnection structure and the need to eliminate the state uncertainty of latent neurons if such are present in the network. Despite the encouraging preliminary results of [3], further extension of the applications of the projection algorithm therefore remains problematic. In this paper, which is a continuation of the work begun in [3], we consider threshold-controlled neural networks. Networks of this type are quite common. They represent the receptor neuron layers in some neurocomputer designs. A similar structure is observed in the lower divisions of biological sensory systems [5]. In multilayer projection neural networks with lateral interconnections, the neuron layers or parts of these layers may also have the structure of a threshold-controlled completely connected network. Here the thresholds are the potentials delivered through the projection connections from other parts of the network. The extension of the projection algorithm to the class of threshold-controlled networks may accordingly prove to be useful both for extending its technical applications and for better understanding of the operation of the nervous system in living organisms.

  12. Neural Based Orthogonal Data Fitting The EXIN Neural Networks

    CERN Document Server

    Cirrincione, Giansalvo

    2008-01-01

    Written by three leaders in the field of neural based algorithms, Neural Based Orthogonal Data Fitting proposes several neural networks, all endowed with a complete theory which not only explains their behavior, but also compares them with the existing neural and traditional algorithms. The algorithms are studied from different points of view, including: as a differential geometry problem, as a dynamic problem, as a stochastic problem, and as a numerical problem. All algorithms have also been analyzed on real time problems (large dimensional data matrices) and have shown accurate solutions. Wh

  13. U.S. States’ fiscal constraints and effects on budget policies

    Directory of Open Access Journals (Sweden)

    Iannella Mario

    2016-05-01

    Full Text Available The article looks at fiscal constraints adopted by the U.S. States. It questions the ability of those rules to determine sound budgetary policies. To assess this point it analyses, in the general part, the major kind of constraints so far adopted. Of each major category the focus is upon institutional weaknesses that create the room for the adoption of circumventing practices. The following section focuses instead on three case studies, to show examples of the way in which the constraints influenced policy-making without mining the ability of government to adopt unbalanced budgetary policies. The weaknesses are combined with the adoption of a deferential approach by the Courts that generally legitimized the accounting devices adopted by the States. The outcome is a system in which budget policies are influenced by several factors that go beyond the institutional framework. On the other side, legal boundaries create distortions and unwanted effects in policies implemented by the States.

  14. Tailoring broadband acoustic energy suppression characteristics of double porosity metamaterials with compression constraints and mass inclusions.

    Science.gov (United States)

    Cui, Shichao; Harne, Ryan L

    2017-06-01

    A metamaterial that capitalizes on a double porosity architecture is introduced for controlling broadband acoustic energy suppression properties. When the metamaterial is subjected to static compressive stress, a global rotation of the internal metamaterial architecture is induced that softens the effective stiffness and results in a considerable means to tailor wave transmission and absorption properties. The influences of mass inclusions and compression constraints are examined by computational and experimental efforts. The results indicate that the mass inclusions and applied constraints can significantly impact the absorption and transmission properties of double porosity metamaterials, while the appropriate utilization of the underlying poroelastic media can further magnify these parametric influences. Based on the widespread implementation of compressed poroelastic media in applications, the results of this research uncover how internal metamaterial architecture and constraints may be exploited to enhance engineering noise control properties while using less poroelastic material mass.

  15. Neural remodeling in retinal degeneration.

    Science.gov (United States)

    Marc, Robert E; Jones, Bryan W; Watt, Carl B; Strettoi, Enrica

    2003-09-01

    Mammalian retinal degenerations initiated by gene defects in rods, cones or the retinal pigmented epithelium (RPE) often trigger loss of the sensory retina, effectively leaving the neural retina deafferented. The neural retina responds to this challenge by remodeling, first by subtle changes in neuronal structure and later by large-scale reorganization. Retinal degenerations in the mammalian retina generally progress through three phases. Phase 1 initiates with expression of a primary insult, followed by phase 2 photoreceptor death that ablates the sensory retina via initial photoreceptor stress, phenotype deconstruction, irreversible stress and cell death, including bystander effects or loss of trophic support. The loss of cones heralds phase 3: a protracted period of global remodeling of the remnant neural retina. Remodeling resembles the responses of many CNS assemblies to deafferentation or trauma, and includes neuronal cell death, neuronal and glial migration, elaboration of new neurites and synapses, rewiring of retinal circuits, glial hypertrophy and the evolution of a fibrotic glial seal that isolates the remnant neural retina from the surviving RPE and choroid. In early phase 2, stressed photoreceptors sprout anomalous neurites that often reach the inner plexiform and ganglion cell layers. As death of rods and cones progresses, bipolar and horizontal cells are deafferented and retract most of their dendrites. Horizontal cells develop anomalous axonal processes and dendritic stalks that enter the inner plexiform layer. Dendrite truncation in rod bipolar cells is accompanied by revision of their macromolecular phenotype, including the loss of functioning mGluR6 transduction. After ablation of the sensory retina, Müller cells increase intermediate filament synthesis, forming a dense fibrotic layer in the remnant subretinal space. This layer invests the remnant retina and seals it from access via the choroidal route. Evidence of bipolar cell death begins in

  16. Neural Correlates of Stimulus Reportability

    OpenAIRE

    Hulme, Oliver J.; Friston, Karl F.; Zeki, Semir

    2009-01-01

    Most experiments on the “neural correlates of consciousness” employ stimulus reportability as an operational definition of what is consciously perceived. The interpretation of such experiments therefore depends critically on understanding the neural basis of stimulus reportability. Using a high volume of fMRI data, we investigated the neural correlates of stimulus reportability using a partial report object detection paradigm. Subjects were presented with a random array of circularly arranged...

  17. Symbolic processing in neural networks

    OpenAIRE

    Neto, João Pedro; Hava T Siegelmann; Costa,J.Félix

    2003-01-01

    In this paper we show that programming languages can be translated into recurrent (analog, rational weighted) neural nets. Implementation of programming languages in neural nets turns to be not only theoretical exciting, but has also some practical implications in the recent efforts to merge symbolic and sub symbolic computation. To be of some use, it should be carried in a context of bounded resources. Herein, we show how to use resource bounds to speed up computations over neural nets, thro...

  18. EDITORIAL: Special issue on applied neurodynamics: from neural dynamics to neural engineering Special issue on applied neurodynamics: from neural dynamics to neural engineering

    Science.gov (United States)

    Chiel, Hillel J.; Thomas, Peter J.

    2011-12-01

    , the sun, earth and moon) proved to be far more difficult. In the late nineteenth century, Poincaré made significant progress on this problem, introducing a geometric method of reasoning about solutions to differential equations (Diacu and Holmes 1996). This work had a powerful impact on mathematicians and physicists, and also began to influence biology. In his 1925 book, based on his work starting in 1907, and that of others, Lotka used nonlinear differential equations and concepts from dynamical systems theory to analyze a wide variety of biological problems, including oscillations in the numbers of predators and prey (Lotka 1925). Although little was known in detail about the function of the nervous system, Lotka concluded his book with speculations about consciousness and the implications this might have for creating a mathematical formulation of biological systems. Much experimental work in the 1930s and 1940s focused on the biophysical mechanisms of excitability in neural tissue, and Rashevsky and others continued to apply tools and concepts from nonlinear dynamical systems theory as a means of providing a more general framework for understanding these results (Rashevsky 1960, Landahl and Podolsky 1949). The publication of Hodgkin and Huxley's classic quantitative model of the action potential in 1952 created a new impetus for these studies (Hodgkin and Huxley 1952). In 1955, FitzHugh published an important paper that summarized much of the earlier literature, and used concepts from phase plane analysis such as asymptotic stability, saddle points, separatrices and the role of noise to provide a deeper theoretical and conceptual understanding of threshold phenomena (Fitzhugh 1955, Izhikevich and FitzHugh 2006). The Fitzhugh-Nagumo equations constituted an important two-dimensional simplification of the four-dimensional Hodgkin and Huxley equations, and gave rise to an extensive literature of analysis. Many of the papers in this special issue build on tools

  19. Neural Correlates of Face Detection

    National Research Council Canada - National Science Library

    Xu, Xiaokun; Biederman, Irving

    2014-01-01

    Although face detection likely played an essential adaptive role in our evolutionary past and in contemporary social interactions, there have been few rigorous studies investigating its neural correlates...

  20. Diffusion Processes Satisfying a Conservation Law Constraint

    Directory of Open Access Journals (Sweden)

    J. Bakosi

    2014-01-01

    Full Text Available We investigate coupled stochastic differential equations governing N nonnegative continuous random variables that satisfy a conservation principle. In various fields a conservation law requires a set of fluctuating variables to be nonnegative and (if appropriately normalized sum to one. As a result, any stochastic differential equation model to be realizable must not produce events outside of the allowed sample space. We develop a set of constraints on the drift and diffusion terms of such stochastic models to ensure that both the nonnegativity and the unit-sum conservation law constraints are satisfied as the variables evolve in time. We investigate the consequences of the developed constraints on the Fokker-Planck equation, the associated system of stochastic differential equations, and the evolution equations of the first four moments of the probability density function. We show that random variables, satisfying a conservation law constraint, represented by stochastic diffusion processes, must have diffusion terms that are coupled and nonlinear. The set of constraints developed enables the development of statistical representations of fluctuating variables satisfying a conservation law. We exemplify the results with the bivariate beta process and the multivariate Wright-Fisher, Dirichlet, and Lochner’s generalized Dirichlet processes.

  1. Pair Production Constraints on Superluminal Neutrinos Revisited

    Energy Technology Data Exchange (ETDEWEB)

    Brodsky, Stanley J.; /SLAC; Gardner, Susan; /Kentucky U.

    2012-02-16

    We revisit the pair creation constraint on superluminal neutrinos considered by Cohen and Glashow in order to clarify which types of superluminal models are constrained. We show that a model in which the superluminal neutrino is effectively light-like can evade the Cohen-Glashow constraint. In summary, any model for which the CG pair production process operates is excluded because such timelike neutrinos would not be detected by OPERA or other experiments. However, a superluminal neutrino which is effectively lightlike with fixed p{sup 2} can evade the Cohen-Glashow constraint because of energy-momentum conservation. The coincidence involved in explaining the SN1987A constraint certainly makes such a picture improbable - but it is still intrinsically possible. The lightlike model is appealing in that it does not violate Lorentz symmetry in particle interactions, although one would expect Hughes-Drever tests to turn up a violation eventually. Other evasions of the CG constraints are also possible; perhaps, e.g., the neutrino takes a 'short cut' through extra dimensions or suffers anomalous acceleration in matter. Irrespective of the OPERA result, Lorentz-violating interactions remain possible, and ongoing experimental investigation of such possibilities should continue.

  2. Two new constraints for the cumulant matrix

    Energy Technology Data Exchange (ETDEWEB)

    Ramos-Cordoba, Eloy; Salvador, Pedro; Matito, Eduard [Institut de Química Computacional i Catàlisi (IQCC) and Department de Química, Universitat de Girona, Campus de Montilivi, 17071 Girona, Catalonia (Spain); Piris, Mario [Kimika Fakultatea, Euskal Herriko Unibertsitatea UPV/EHU, and Donostia International Physics Center (DIPC). P.K. 1072, 20080 Donostia, Euskadi (Spain)

    2014-12-21

    We suggest new strict constraints that the two-particle cumulant matrix should fulfill. The constraints are obtained from the decomposition of 〈S-^{sup 2}〉, previously developed in our laboratory, and the vanishing number of electrons shared by two non-interacting fragments. The conditions impose stringent constraints into the cumulant structure without any need to perform an orbital optimization procedure thus carrying very small or no computational effort. These constraints are tested on the series of Piris natural orbital functionals (PNOF), which are among the most accurate ones available in the literature. Interestingly, even though all PNOF cumulants ensure correct overall 〈S{sup ^2}〉 values, none of them is consistent with the local spin structure of systems that dissociate more than one pair of electrons. A careful analysis of the local spin components reveals the most important missing contributions in the cumulant expression thus suggesting a means to improve PNOF5. The constraints provide an inexpensive tool for the construction and testing of cumulant structures that complement previously known conditions such as the N-representability or the square of the total spin angular momentum, 〈S{sup ^2}〉.

  3. Forces Associated with Nonlinear Nonholonomic Constraint Equations

    Science.gov (United States)

    Roithmayr, Carlos M.; Hodges, Dewey H.

    2010-01-01

    A concise method has been formulated for identifying a set of forces needed to constrain the behavior of a mechanical system, modeled as a set of particles and rigid bodies, when it is subject to motion constraints described by nonholonomic equations that are inherently nonlinear in velocity. An expression in vector form is obtained for each force; a direction is determined, together with the point of application. This result is a consequence of expressing constraint equations in terms of dot products of vectors rather than in the usual way, which is entirely in terms of scalars and matrices. The constraint forces in vector form are used together with two new analytical approaches for deriving equations governing motion of a system subject to such constraints. If constraint forces are of interest they can be brought into evidence in explicit dynamical equations by employing the well-known nonholonomic partial velocities associated with Kane's method; if they are not of interest, equations can be formed instead with the aid of vectors introduced here as nonholonomic partial accelerations. When the analyst requires only the latter, smaller set of equations, they can be formed directly; it is not necessary to expend the labor to form the former, larger set first and subsequently perform matrix multiplications.

  4. Fault diagnosis in satellite attitude control systems using artificial neural networkk

    Science.gov (United States)

    Ayodele I., Olanipekun

    The nonlinear behavior exhibited by altitude control system processes and also the presence of external constraints on the operating conditions causes hitch in the dynamics of system processes. This research work proposes a fault detection/tolerant prediction in an altitude control system. This is done through the artificial neural network fault detection by deploying the neural network approach. A fault detection and isolation module is developed in the actuator system of the Altitude Control System, thereby achieving the goal of this thesis. This can be done by two basic classification stages: Neural Residual Generator (Neural Observer)- This stage is responsible for generating residual errors that can reflect the real behavior of the entire process as against its normal conditions. Adaptive Neural Classifier - This stage is responsible for managing the isolation task of the fault detected by evaluating the generated residual errors from the neural estimator which gives detailed information about faults detected e.g., fault location and time. These two stages can be implemented by executing the tasks listed below: 1. Study and develop a generic three axis stabilized altitude control model based on the reaction wheels. This is established with three separate PD controllers designed for each reaction wheel of the satellite axis using the Matlab - SIMULINK. 2. Develop a dynamic neural network residual generator based on Dynamic Multilayer Perceptron Network (DMLP) which is then applied to the reaction wheel model designed commonly called the actuator in the altitude control system of a satellite 3. Develop a neural network adaptive classifier based on the Learning Vector Quantization (LVQ) model which is used for the isolation concept. The advantages of the proposed dynamic neural network and neural adaptive classifier approach are showcased.

  5. Sensory-related neural activity regulates the structure of vascular networks in the cerebral cortex

    Science.gov (United States)

    Lacoste, Baptiste; Comin, Cesar H.; Ben-Zvi, Ayal; Kaeser, Pascal S.; Xu, Xiaoyin; Costa, Luciano da F.; Gu, Chenghua

    2014-01-01

    SUMMARY Neurovascular interactions are essential for proper brain function. While the effect of neural activity on cerebral blood flow has been extensively studied, whether neural activity influences vascular patterning remains elusive. Here, we demonstrate that neural activity promotes the formation of vascular networks in the early postnatal mouse barrel cortex. Using a combination of genetics, imaging, and computational tools to allow simultaneous analysis of neuronal and vascular components, we found that vascular density and branching were decreased in the barrel cortex when sensory input was reduced by either a complete deafferentation, a genetic impairment of neurotransmitter release at thalamocortical synapses, or a selective reduction of sensory-related neural activity by whisker plucking. In contrast, enhancement of neural activity by whisker stimulation led to an increase in vascular density and branching. The finding that neural activity is necessary and sufficient to trigger alterations of vascular networks reveals a novel feature of neurovascular interactions. PMID:25155955

  6. Sensory-related neural activity regulates the structure of vascular networks in the cerebral cortex.

    Science.gov (United States)

    Lacoste, Baptiste; Comin, Cesar H; Ben-Zvi, Ayal; Kaeser, Pascal S; Xu, Xiaoyin; Costa, Luciano da F; Gu, Chenghua

    2014-09-03

    Neurovascular interactions are essential for proper brain function. While the effect of neural activity on cerebral blood flow has been extensively studied, whether or not neural activity influences vascular patterning remains elusive. Here, we demonstrate that neural activity promotes the formation of vascular networks in the early postnatal mouse barrel cortex. Using a combination of genetics, imaging, and computational tools to allow simultaneous analysis of neuronal and vascular components, we found that vascular density and branching were decreased in the barrel cortex when sensory input was reduced by either a complete deafferentation, a genetic impairment of neurotransmitter release at thalamocortical synapses, or a selective reduction of sensory-related neural activity by whisker plucking. In contrast, enhancement of neural activity by whisker stimulation led to an increase in vascular density and branching. The finding that neural activity is necessary and sufficient to trigger alterations of vascular networks reveals an important feature of neurovascular interactions. Copyright © 2014 Elsevier Inc. All rights reserved.

  7. Software implementation of artificial neural networks in automated intelligent systems

    Directory of Open Access Journals (Sweden)

    В.П. Харченко

    2009-02-01

    Full Text Available  Application of neural networks technologies effectively decides the task of synthesis of origin of accident risk and gives out the vector of managing signals of network on incomplete and distorted information about the phenomena, events and processes which influence on safety flights.

  8. Data Driven Broiler Weight Forecasting using Dynamic Neural Network Models

    DEFF Research Database (Denmark)

    Johansen, Simon Vestergaard; Bendtsen, Jan Dimon; Riisgaard-Jensen, Martin

    2017-01-01

    In this article, the dynamic influence of environmental broiler house conditions and broiler growth is investigated. Dynamic neural network forecasting models have been trained on farm-scale broiler batch production data from 12 batches from the same house. The model forecasts future broiler weight...

  9. Discretionary Time of Chinese College Students: Activities and Impact of SARS-Induced Constraints on Choices

    Science.gov (United States)

    Yang, He; Hutchinson, Susan; Zinn, Harry; Watson, Alan

    2011-01-01

    How people make choices about activity engagement during discretionary time is a topic of increasing interest to those studying quality of life issues. Assuming choices are made to maximize individual welfare, several factors are believed to influence these choices. Constraints theory from the leisure research literature suggests these choices are…

  10. Total enzyme activity constraint and homeostatic constraint impact on the optimization potential of a kinetic model.

    Science.gov (United States)

    Komasilovs, Vitalijs; Pentjuss, Agris; Elsts, Atis; Stalidzans, Egils

    2017-09-28

    The application of biologically and biochemically relevant constraints during the optimization of kinetic models reduces the impact of suggested changes in processes not included in the scope of the model. This increases the probability that the design suggested by model optimization can be carried out by an organism after implementation of design in vivo. A case study was carried out to determine the impact of total enzyme activity and homeostatic constraints on the objective function values and the following ranking of adjustable parameter combinations. The application of constraints on the model of sugar cane metabolism revealed that a homeostatic constraint caused heavier limitations of the objective function than a total enzyme activity constraint. Both constraints changed the ranking of adjustable parameter combinations: no "universal" constraint-independent top-ranked combinations were found. Therefore, when searching for the best subset of adjustable parameters, a full scan of their combinations is suggested for a small number of adjustable parameters, and evolutionary search strategies are suggested for a large number. Simultaneous application of both constraints is suggested. Copyright © 2017 Elsevier B.V. All rights reserved.

  11. Solving constraint satisfaction problems with networks of spiking neurons

    Directory of Open Access Journals (Sweden)

    Zeno eJonke

    2016-03-01

    Full Text Available Network of neurons in the brain apply – unlike processors in our current generation ofcomputer hardware – an event-based processing strategy, where short pulses (spikes areemitted sparsely by neurons to signal the occurrence of an event at a particular point intime. Such spike-based computations promise to be substantially more power-efficient thantraditional clocked processing schemes. However it turned out to be surprisingly difficult todesign networks of spiking neurons that can solve difficult computational problems on the levelof single spikes (rather than rates of spikes. We present here a new method for designingnetworks of spiking neurons via an energy function. Furthermore we show how the energyfunction of a network of stochastically firing neurons can be shaped in a quite transparentmanner by composing the networks of simple stereotypical network motifs. We show that thisdesign approach enables networks of spiking neurons to produce approximate solutions todifficult (NP-hard constraint satisfaction problems from the domains of planning/optimizationand verification/logical inference. The resulting networks employ noise as a computationalresource. Nevertheless the timing of spikes (rather than just spike rates plays an essential rolein their computations. Furthermore, networks of spiking neurons carry out for the Traveling Salesman Problem a more efficient stochastic search for good solutions compared with stochastic artificial neural networks (Boltzmann machines and Gibbs sampling.

  12. Temperature Sensitivity of Neural Tube Defects in Zoep Mutants.

    Science.gov (United States)

    Ma, Phyo; Swartz, Morgan R; Kindt, Lexy M; Kangas, Ashley M; Liang, Jennifer Ostrom

    2015-12-01

    Neural tube defects (NTD) occur when the flat neural plate epithelium fails to fold into the neural tube, the precursor to the brain and spinal cord. Squint (Sqt/Ndr1), a Nodal ligand, and One-eyed pinhead (Oep), a component of the Nodal receptor, are required for anterior neural tube closure in zebrafish. The NTD in sqt and Zoep mutants are incompletely penetrant. The penetrance of several defects in sqt mutants increases upon heat or cold shock. In this project, undergraduate students tested whether temperature influences the Zoep open neural tube phenotype. Single pairs of adults were spawned at 28.5°C, the normal temperature for zebrafish, and one half of the resulting embryos were moved to 34°C at different developmental time points. Analysis of variance indicated temperature and clutch/genetic background significantly contributed to the penetrance of the open neural tube phenotype. Heat shock affected the embryos only at or before the midblastula stage. Many factors, including temperature changes in the mother, nutrition, and genetic background, contribute to NTD in humans. Thus, sqt and Zoep mutants may serve as valuable models for studying the interactions between genetics and the environment during neurulation.

  13. Optimization of multilayer neural network parameters for speaker recognition

    Science.gov (United States)

    Tovarek, Jaromir; Partila, Pavol; Rozhon, Jan; Voznak, Miroslav; Skapa, Jan; Uhrin, Dominik; Chmelikova, Zdenka

    2016-05-01

    This article discusses the impact of multilayer neural network parameters for speaker identification. The main task of speaker identification is to find a specific person in the known set of speakers. It means that the voice of an unknown speaker (wanted person) belongs to a group of reference speakers from the voice database. One of the requests was to develop the text-independent system, which means to classify wanted person regardless of content and language. Multilayer neural network has been used for speaker identification in this research. Artificial neural network (ANN) needs to set parameters like activation function of neurons, steepness of activation functions, learning rate, the maximum number of iterations and a number of neurons in the hidden and output layers. ANN accuracy and validation time are directly influenced by the parameter settings. Different roles require different settings. Identification accuracy and ANN validation time were evaluated with the same input data but different parameter settings. The goal was to find parameters for the neural network with the highest precision and shortest validation time. Input data of neural networks are a Mel-frequency cepstral coefficients (MFCC). These parameters describe the properties of the vocal tract. Audio samples were recorded for all speakers in a laboratory environment. Training, testing and validation data set were split into 70, 15 and 15 %. The result of the research described in this article is different parameter setting for the multilayer neural network for four speakers.

  14. Flood estimation: a neural network approach

    Energy Technology Data Exchange (ETDEWEB)

    Swain, P.C.; Seshachalam, C.; Umamahesh, N.V. [Regional Engineering Coll., Warangal (India). Water and Environment Div.

    2000-07-01

    The artificial neural network (ANN) approach described in this study aims at predicting the flood flow into a reservoir. This differs from the traditional methods of flow prediction in the sense that it belongs to a class of data driven approaches, where as the traditional methods are model driven. Physical processes influencing the occurrences of streamflow in a river are highly complex, and are very difficult to be modelled by available statistical or deterministic models. ANNs provide model free solutions and hence can be expected to be appropriate in these conditions. Non-linearity, adaptivity, evidential response and fault tolerance are additional properties and capabilities of the neural networks. This paper highlights the applicability of neural networks for predicting daily flood flow taking the Hirakud reservoir on river Mahanadi in Orissa, India as the case study. The correlation between the observed and predicted flows and the relative error are considered to measure the performance of the model. The correlation between the observed and the modelled flows are computed to be 0.9467 in testing phase of the model. (orig.)

  15. Contextual Constraint and Preview Time Modulate the Semantic Preview Effect: Evidence from Chinese Sentence Reading.

    Science.gov (United States)

    Li, Nan; Wang, Suiping; Mo, Luxi; Kliegl, Reinhold

    2017-03-23

    Word recognition in sentence reading is influenced by information from both preview and context. Recently, semantic preview effect (SPE) was observed being modulated by the constraint of context, indicating that context might accelerate the processing of semantically related preview words. Besides, SPE was found to depend on preview time, which suggests SPE may change with different processing stages of preview words. Therefore it raises the question of whether preview-time-dependent SPE would be modulated by contextual constraint. In the current study, we investigated the impact of contextual constraint on SPE in Chinese reading, but also examined its dependency on preview time. The preview word and the target word were identical, semantically related, or unrelated to the target word. The results showed a significant three-way interaction: The SPE depended on contextual constraint and preview time. In separate analyses for low and high contextual constraint of target words, the SPE significantly decreased with an increase in preview duration when the target word was of low constraint in the sentence. The effect was numerically in the same direction, but weaker and statistically non-significant when the target word was highly constrained in the sentence. The results indicate that word processing in sentences is a dynamic process of integrating information from both preview (bottom up) and context (top down).

  16. Relative Packing Groups in Template-Based Structure Prediction: Cooperative Effects of True Positive Constraints

    Science.gov (United States)

    Day, Ryan; Qu, Xiaotao; Swanson, Rosemarie; Bohannan, Zach; Bliss, Robert

    2011-01-01

    Abstract Most current template-based structure prediction methods concentrate on finding the correct backbone conformation and then packing sidechains within that backbone. Our packing-based method derives distance constraints from conserved relative packing groups (RPGs). In our refinement approach, the RPGs provide a level of resolution that restrains global topology while allowing conformational sampling. In this study, we test our template-based structure prediction method using 51 prediction units from CASP7 experiments. RPG-based constraints are able to substantially improve approximately two-thirds of starting templates. Upon deeper investigation, we find that true positive spatial constraints, especially those non-local in sequence, derived from the RPGs were important to building nearer native models. Surprisingly, the fraction of incorrect or false positive constraints does not strongly influence the quality of the final candidate. This result indicates that our RPG-based true positive constraints sample the self-consistent, cooperative interactions of the native structure. The lack of such reinforcing cooperativity explains the weaker effect of false positive constraints. Generally, these findings are encouraging indications that RPGs will improve template-based structure prediction. PMID:21210729

  17. LINCS : A linear constraint solver for molecular simulations

    NARCIS (Netherlands)

    Hess, B; Bekker, H.; Berendsen, H.J.C.; Fraaije, J.G E M

    In this article, we present a new LINear Constraint Solver (LINCS) for molecular simulations with bond constraints. The algorithm is inherently stable, as the constraints themselves are reset instead of derivatives of the constraints, thereby eliminating drift. Although the derivation of the

  18. 12 CFR 1805.502 - Severe constraints waiver.

    Science.gov (United States)

    2010-01-01

    ... 12 Banks and Banking 7 2010-01-01 2010-01-01 false Severe constraints waiver. 1805.502 Section... constraints waiver. (a) In the case of an Applicant with severe constraints on available sources of matching... request a “severe constraints waiver” as part of its application for assistance. An Applicant shall...

  19. Optics in neural computation

    Science.gov (United States)

    Levene, Michael John

    In all attempts to emulate the considerable powers of the brain, one is struck by both its immense size, parallelism, and complexity. While the fields of neural networks, artificial intelligence, and neuromorphic engineering have all attempted oversimplifications on the considerable complexity, all three can benefit from the inherent scalability and parallelism of optics. This thesis looks at specific aspects of three modes in which optics, and particularly volume holography, can play a part in neural computation. First, holography serves as the basis of highly-parallel correlators, which are the foundation of optical neural networks. The huge input capability of optical neural networks make them most useful for image processing and image recognition and tracking. These tasks benefit from the shift invariance of optical correlators. In this thesis, I analyze the capacity of correlators, and then present several techniques for controlling the amount of shift invariance. Of particular interest is the Fresnel correlator, in which the hologram is displaced from the Fourier plane. In this case, the amount of shift invariance is limited not just by the thickness of the hologram, but by the distance of the hologram from the Fourier plane. Second, volume holography can provide the huge storage capacity and high speed, parallel read-out necessary to support large artificial intelligence systems. However, previous methods for storing data in volume holograms have relied on awkward beam-steering or on as-yet non- existent cheap, wide-bandwidth, tunable laser sources. This thesis presents a new technique, shift multiplexing, which is capable of very high densities, but which has the advantage of a very simple implementation. In shift multiplexing, the reference wave consists of a focused spot a few millimeters in front of the hologram. Multiplexing is achieved by simply translating the hologram a few tens of microns or less. This thesis describes the theory for how shift

  20. Robust Quasi-LPV Control Based on Neural State Space Models

    DEFF Research Database (Denmark)

    Bendtsen, Jan Dimon; Trangbæk, Klaus

    2002-01-01

    In this paper we derive a synthesis result for robust LPV output feedback controllers for nonlinear systems modelled by neural state space models. This result is achieved by writing the neural state space model on a linear fractional transformation form in a non-conservative way, separating...... that there is some uncertainty on the identified nonlinearities. The control law is therefore made robust to noise perturbations. After formulating the controller synthesis as a set of LMIs with added constraints, some implementation issues are addressed and a simulation example is presented....

  1. A recurrent neural network for solving a class of generalized convex optimization problems.

    Science.gov (United States)

    Hosseini, Alireza; Wang, Jun; Hosseini, S Mohammad

    2013-08-01

    In this paper, we propose a penalty-based recurrent neural network for solving a class of constrained optimization problems with generalized convex objective functions. The model has a simple structure described by using a differential inclusion. It is also applicable for any nonsmooth optimization problem with affine equality and convex inequality constraints, provided that the objective function is regular and pseudoconvex on feasible region of the problem. It is proven herein that the state vector of the proposed neural network globally converges to and stays thereafter in the feasible region in finite time, and converges to the optimal solution set of the problem. Copyright © 2013 Elsevier Ltd. All rights reserved.

  2. Constraints and spandrels of interareal connectomes

    Science.gov (United States)

    Rubinov, Mikail

    2016-12-01

    Interareal connectomes are whole-brain wiring diagrams of white-matter pathways. Recent studies have identified modules, hubs, module hierarchies and rich clubs as structural hallmarks of these wiring diagrams. An influential current theory postulates that connectome modules are adequately explained by evolutionary pressures for wiring economy, but that the other hallmarks are not explained by such pressures and are therefore less trivial. Here, we use constraint network models to test these postulates in current gold-standard vertebrate and invertebrate interareal-connectome reconstructions. We show that empirical wiring-cost constraints inadequately explain connectome module organization, and that simultaneous module and hub constraints induce the structural byproducts of hierarchies and rich clubs. These byproducts, known as spandrels in evolutionary biology, include the structural substrate of the default-mode network. Our results imply that currently standard connectome characterizations are based on circular analyses or double dipping, and we emphasize an integrative approach to future connectome analyses for avoiding such pitfalls.

  3. Restricting query relaxation through user constraints

    Energy Technology Data Exchange (ETDEWEB)

    Gaasterland, T.

    1993-07-01

    This paper describes techniques to restrict and to heuristically control relaxation of deductive database queries. The process of query relaxation provides a user with a means to automatically identify new queries that are related to the user`s original query. However, for large databases, many relaxations may be possible. The methods to control and restrict the relaxation process introduced in this paper focus the relaxation process and make it more efficient. User restrictions over the data base domain may be expressed as user constraints. This paper describes how user constraints can restrict relaxed queries. Also, a set of heuristics based on cooperative answering techniques are presented for controlling the relaxation process. Finally, the interaction of the methods for relaxing queries, processing user constraints, and applying the heuristic rules is described.

  4. Lorentz violation. Motivation and new constraints

    Energy Technology Data Exchange (ETDEWEB)

    Liberati, S. [Scuola Internazionale Superiore di Studi Avanzati SISSA, Trieste (Italy); Istituto Nazionale di Fisica Nucleare INFN, Sezione di Trieste (Italy); Maccione, L. [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany)

    2009-09-15

    We review the main theoretical motivations and observational constraints on Planck scale sup-pressed violations of Lorentz invariance. After introducing the problems related to the phenomenological study of quantum gravitational effects, we discuss the main theoretical frameworks within which possible departures from Lorentz invariance can be described. In particular, we focus on the framework of Effective Field Theory, describing several possible ways of including Lorentz violation therein and discussing their theoretical viability. We review the main low energy effects that are expected in this framework. We discuss the current observational constraints on such a framework, focusing on those achievable through high-energy astrophysics observations. In this context we present a summary of the most recent and strongest constraints on QED with Lorentz violating non-renormalizable operators. Finally, we discuss the present status of the field and its future perspectives. (orig.)

  5. Parasympathetic neural activity accounts for the lowering of exercise heart rate at high altitude

    DEFF Research Database (Denmark)

    Boushel, Robert Christopher; Calbet, J A; Rådegran, G

    2001-01-01

    In chronic hypoxia, both heart rate (HR) and cardiac output (Q) are reduced during exercise. The role of parasympathetic neural activity in lowering HR is unresolved, and its influence on Q and oxygen transport at high altitude has never been studied.......In chronic hypoxia, both heart rate (HR) and cardiac output (Q) are reduced during exercise. The role of parasympathetic neural activity in lowering HR is unresolved, and its influence on Q and oxygen transport at high altitude has never been studied....

  6. Evaluation of a Neural-Network-Based adaptive Beamforming Scheme with Magnitude-Only Constraints

    NARCIS (Netherlands)

    Castaldi, G.; Galdi, V.; Gerini, G.

    2009-01-01

    In this paper, we present an adaptive beamforming scheme for smart antenna arrays in the presence of several desired and interfering signals, and additive white Gaussian noise. As compared with standard schemes, the proposed algorithm minimizes the noise and interference contributions, but enforces

  7. From random to regular: Neural constraints on the emergence of isochronous rhythm during cultural transmission

    DEFF Research Database (Denmark)

    Lumaca, Massimo; Haumann, Niels Trusbak; Brattico, Elvira

    2017-01-01

    A core design feature of human communication systems and expressive behaviours is their temporal organization. The cultural evolutionary origins of this feature remain unclear. Here, we test the hypothesis that regularities in the temporal organization of signalling sequences arise in the course...

  8. Coverage-based constraints for IMRT optimization.

    Science.gov (United States)

    Mescher, H; Ulrich, S; Bangert, M

    2017-09-05

    Radiation therapy treatment planning requires an incorporation of uncertainties in order to guarantee an adequate irradiation of the tumor volumes. In current clinical practice, uncertainties are accounted for implicitly with an expansion of the target volume according to generic margin recipes. Alternatively, it is possible to account for uncertainties by explicit minimization of objectives that describe worst-case treatment scenarios, the expectation value of the treatment or the coverage probability of the target volumes during treatment planning. In this note we show that approaches relying on objectives to induce a specific coverage of the clinical target volumes are inevitably sensitive to variation of the relative weighting of the objectives. To address this issue, we introduce coverage-based constraints for intensity-modulated radiation therapy (IMRT) treatment planning. Our implementation follows the concept of coverage-optimized planning that considers explicit error scenarios to calculate and optimize patient-specific probabilities [Formula: see text] of covering a specific target volume fraction [Formula: see text] with a certain dose [Formula: see text]. Using a constraint-based reformulation of coverage-based objectives we eliminate the trade-off between coverage and competing objectives during treatment planning. In-depth convergence tests including 324 treatment plan optimizations demonstrate the reliability of coverage-based constraints for varying levels of probability, dose and volume. General clinical applicability of coverage-based constraints is demonstrated for two cases. A sensitivity analysis regarding penalty variations within this planing study based on IMRT treatment planning using (1) coverage-based constraints, (2) coverage-based objectives, (3) probabilistic optimization, (4) robust optimization and (5) conventional margins illustrates the potential benefit of coverage-based constraints that do not require tedious adjustment of target

  9. Effect of Local Constraint on Driving Torque of Driving Mechanism for Half-rotating Wing

    Directory of Open Access Journals (Sweden)

    Wang Huixing

    2016-01-01

    Full Text Available Half-rotating wing (HRW is a new kind of flapping wing system with rotating-type flapping instead of oscillating-type flapping. For the complex mechanical transmission and high weight which is not suitable for flight of traditional half-rotating mechanism (HRM.The simplified HRM with local constraint was proposed as the driving mechanism of HRW in this paper. The performing process and characteristics of local constraint was further given. According to contact state between moving components, the performing process of local constraint was divided into two stages. To analyze the influence of local constraint on the driving torque exerted in the crank of driving mechanism, the model of driving torque under different stages were respectively established. Based on the model, the change curve of driving torque was obtained through simulation by MATLAB, which showed that local constraint had little influence on driving torque. The results could provide guidance for the choice of motor of HRW and optimization of dynamics.

  10. Updated galactic radio constraints on Dark Matter

    Science.gov (United States)

    Cirelli, Marco; Taoso, Marco

    2016-07-01

    We perform a detailed analysis of the synchrotron signals produced by dark matter annihilations and decays. We consider different set-ups for the propagation of electrons and positrons, the galactic magnetic field and dark matter properties. We then confront these signals with radio and microwave maps, including Planck measurements, from a frequency of 22 MHz up to 70 GHz. We derive two sets of constraints: conservative and progressive, the latter based on a modeling of the astrophysical emission. Radio and microwave constraints are complementary to those obtained with other indirect detection methods, especially for dark matter annihilating into leptonic channels.

  11. Modifier constraints in alkali ultraphosphate glasses

    DEFF Research Database (Denmark)

    Rodrigues, B.P.; Mauro, J.C.; Yue, Yuanzheng

    2014-01-01

    In applying the recently introduced concept of cationic constraint strength [J. Chem. Phys. 140, 214501 (2014)] to bond constraint theory (BCT) of binary phosphate glasses in the ultraphosphate region of xR2O-(1-x)P2O5 (with x ≤ 0.5 and R = {Li, Na, Cs}), we demonstrate that a fundamental...... of the modifier sites and then use this to calculate the glass transition temperature as a function of chemical composition. A statistical distribution of sites achieves a remarkable agreement with experimental data for all tested glasses and greatly improves upon previously published work....

  12. Universal constraints on axions from inflation

    DEFF Research Database (Denmark)

    Ferreira, R. Z.; Sloth, M. S.

    2014-01-01

    through this mechanism, larger than the vacuum ones, without violating the observational constraints unless we combine this mechanism with a curvaton or if the sigma field becomes heavy and decays during inflation. Even in this last case there are non-trivial constraints coming from the slow......-roll evolution of the curvature perturbation on super horizon scales which should be taken into account. We also comment on implications for inflationary models where axions play an important role as, for example, models of natural inflation where more than one axion are included and models where the curvaton...

  13. Optimal Portfolio Choice with Wash Sale Constraints

    DEFF Research Database (Denmark)

    Astrup Jensen, Bjarne; Marekwica, Marcel

    2011-01-01

    is to a large extent driven by the desire to realize those losses, either immediately by sharply decreasing the holding of assets carrying unrealized losses, or indirectly by increasing such holdings in order to prepare for a decrease in a future period to earn the tax rebate payment. Our findings are robust......We analytically solve the portfolio choice problem in the presence of wash sale constraints in a two-period model with one risky asset. Our results show that wash sale constraints can heavily affect portfolio choice of investors with unrealized losses. The trading behavior of such investors...

  14. Constraints on hadronically decaying dark matter

    Energy Technology Data Exchange (ETDEWEB)

    Garny, Mathias [Technische Univ. Muenchen, Garching (Germany). Physik-Department; Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany); Ibarra, Alejandro [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany); Tran, David [Technische Univ. Muenchen, Garching (Germany). Physik-Department; Minnesota Univ., Minneapolis, MN (United States). School of Physics and Astronomy

    2012-05-15

    We present general constraints on dark matter stability in hadronic decay channels derived from measurements of cosmic-ray antiprotons.We analyze various hadronic decay modes in a model-independent manner by examining the lowest-order decays allowed by gauge and Lorentz invariance for scalar and fermionic dark matter particles and present the corresponding lower bounds on the partial decay lifetimes in those channels. We also investigate the complementarity between hadronic and gamma-ray constraints derived from searches for monochromatic lines in the sky, which can be produced at the quantum level if the dark matter decays into quark-antiquark pairs at leading order.

  15. Constraint algebra for interacting quantum systems

    Science.gov (United States)

    Fubini, S.; Roncadelli, M.

    1988-04-01

    We consider relativistic constrained systems interacting with external fields. We provide physical arguments to support the idea that the quantum constraint algebra should be the same as in the free quantum case. For systems with ordering ambiguities this principle is essential to obtain a unique quantization. This is shown explicitly in the case of a relativistic spinning particle, where our assumption about the constraint algebra plus invariance under general coordinate transformations leads to a unique S-matrix. On leave from Dipartimento di Fisica Nucleare e Teorica, Università di Pavia and INFN, I-27100 Pavia, Italy.

  16. On the evolutionary constraint surface of hydra

    Science.gov (United States)

    Slobodkin, L. B.; Dunn, K.

    1983-01-01

    Food consumption, body size, and budding rate were measured simultaneously in isolated individual hydra of six strains. For each individual hydra the three measurements define a point in the three dimensional space with axes: food consumption, budding rate, and body size. These points lie on a single surface, regardless of species. Floating rate and incidence of sexuality map onto this surface. It is suggested that this surface is an example of a general class of evolutionary constraint surfaces derived from the conjunction of evolutinary theory and the theory of ecological resource budgets. These constraint surfaces correspond to microevolutionary domains.

  17. Simplification of integrity constraints for data integration

    DEFF Research Database (Denmark)

    Christiansen, Henning; Martinenghi, Davide

    2004-01-01

    When two or more databases are combined into a global one, integrity may be violated even when each database is consistent with its own local integrity constraints. Efficient methods for checking global integrity in data integration systems are called for: answers to queries can then be trusted...... together with given a priori constraints on the combination, so that only a minimal number of tuples needs to be considered. Combination from scratch, integration of a new source, and absorption of local updates are dealt with for both the local-as-view and global-as-view approaches to data integration....

  18. Constraints on vector meson photoproduction spin observables

    Science.gov (United States)

    Kloet, W. M.; Tabakin, Frank

    2000-01-01

    Extraction of spin observables from vector meson photoproduction on a nucleon target is described. Starting from density matrix elements in the vector meson's rest frame, we transform to spin observables in the photon-nucleon c.m. frame. Several constraints on the transformed density matrix and on the spin observables follow from requiring that the angular distribution and the density matrix be positive definite. A set of constraints that are required in order to extract meaningful spin observables from forthcoming data are enunciated.

  19. Updated galactic radio constraints on Dark Matter

    Energy Technology Data Exchange (ETDEWEB)

    Cirelli, Marco [Laboratoire de Physique Théorique et Hautes Energies (LPTHE),UMR 7589 CNRS & UPMC, 4 Place Jussieu, Paris, F-75252 (France); Taoso, Marco [Instituto de Física Teórica (IFT) UAM/CSIC,calle Nicolás Cabrera 13-15, Cantoblanco, Madrid, 28049 (Spain)

    2016-07-25

    We perform a detailed analysis of the synchrotron signals produced by dark matter annihilations and decays. We consider different set-ups for the propagation of electrons and positrons, the galactic magnetic field and dark matter properties. We then confront these signals with radio and microwave maps, including PLANCK measurements, from a frequency of 22 MHz up to 70 GHz. We derive two sets of constraints: conservative and progressive, the latter based on a modeling of the astrophysical emission. Radio and microwave constraints are complementary to those obtained with other indirect detection methods, especially for dark matter annihilating into leptonic channels.

  20. Light dark matter versus astrophysical constraints

    OpenAIRE

    Cline, James M.; Frey, Andrew R.

    2011-01-01

    Hints of direct dark matter detection coming from the DAMA, CoGeNT experiments point toward light dark matter with isospin-violating and possibly inelastic couplings. However an array of astrophysical constraints are rapidly closing the window on light dark matter. We point out that if the relic density is determined by annihilation into invisible states, these constraints can be evaded. As an example we present a model of quasi-Dirac dark matter, interacting via two U(1) gauge bosons, one of...