WorldWideScience

Sample records for network activity rate

  1. Rate-Based Active Queue Management for TCP Flows over Wired and Wireless Networks

    OpenAIRE

    Jun Wang; Min Song

    2007-01-01

    Current active queue management (AQM) and TCP protocol are designed and tuned to work well on wired networks where packet loss is mainly due to network congestion. In wireless networks, however, communication links suffer from significant transmission bit errors and handoff failures. As a result, the performance of TCP flows is significantly degraded. To mitigate this problem, we analyze existing AQM schemes and propose a rate-based exponential AQM (REAQM) scheme. The proposed REAQM scheme u...

  2. Active random noise control using adaptive learning rate neural networks with an immune feedback law

    Science.gov (United States)

    Sasaki, Minoru; Kuribayashi, Takumi; Ito, Satoshi

    2005-12-01

    In this paper an active random noise control using adaptive learning rate neural networks with an immune feedback law is presented. The adaptive learning rate strategy increases the learning rate by a small constant if the current partial derivative of the objective function with respect to the weight and the exponential average of the previous derivatives have the same sign, otherwise the learning rate is decreased by a proportion of its value. The use of an adaptive learning rate attempts to keep the learning step size as large as possible without leading to oscillation. In the proposed method, because of the immune feedback law change a learning rate of the neural networks individually and adaptively, it is expected that a cost function minimize rapidly and training time is decreased. Numerical simulations and experiments of active random noise control with the transfer function of the error path will be performed, to validate the convergence properties of the adaptive learning rate Neural Networks with the immune feedback law. Control results show that adaptive learning rate Neural Networks control structure can outperform linear controllers and conventional neural network controller for the active random noise control.

  3. Cortical Network Models of Firing Rates in the Resting and Active States Predict BOLD Responses.

    Directory of Open Access Journals (Sweden)

    Maxwell R Bennett

    Full Text Available Measurements of blood oxygenation level dependent (BOLD signals have produced some surprising observations. One is that their amplitude is proportional to the entire activity in a region of interest and not just the fluctuations in this activity. Another is that during sleep and anesthesia the average BOLD correlations between regions of interest decline as the activity declines. Mechanistic explanations of these phenomena are described here using a cortical network model consisting of modules with excitatory and inhibitory neurons, taken as regions of cortical interest, each receiving excitatory inputs from outside the network, taken as subcortical driving inputs in addition to extrinsic (intermodular connections, such as provided by associational fibers. The model shows that the standard deviation of the firing rate is proportional to the mean frequency of the firing when the extrinsic connections are decreased, so that the mean BOLD signal is proportional to both as is observed experimentally. The model also shows that if these extrinsic connections are decreased or the frequency of firing reaching the network from the subcortical driving inputs is decreased, or both decline, there is a decrease in the mean firing rate in the modules accompanied by decreases in the mean BOLD correlations between the modules, consistent with the observed changes during NREM sleep and under anesthesia. Finally, the model explains why a transient increase in the BOLD signal in a cortical area, due to a transient subcortical input, gives rises to responses throughout the cortex as observed, with these responses mediated by the extrinsic (intermodular connections.

  4. The effects of dynamical synapses on firing rate activity: a spiking neural network model.

    Science.gov (United States)

    Khalil, Radwa; Moftah, Marie Z; Moustafa, Ahmed A

    2017-11-01

    Accumulating evidence relates the fine-tuning of synaptic maturation and regulation of neural network activity to several key factors, including GABA A signaling and a lateral spread length between neighboring neurons (i.e., local connectivity). Furthermore, a number of studies consider short-term synaptic plasticity (STP) as an essential element in the instant modification of synaptic efficacy in the neuronal network and in modulating responses to sustained ranges of external Poisson input frequency (IF). Nevertheless, evaluating the firing activity in response to the dynamical interaction between STP (triggered by ranges of IF) and these key parameters in vitro remains elusive. Therefore, we designed a spiking neural network (SNN) model in which we incorporated the following parameters: local density of arbor essences and a lateral spread length between neighboring neurons. We also created several network scenarios based on these key parameters. Then, we implemented two classes of STP: (1) short-term synaptic depression (STD) and (2) short-term synaptic facilitation (STF). Each class has two differential forms based on the parametric value of its synaptic time constant (either for depressing or facilitating synapses). Lastly, we compared the neural firing responses before and after the treatment with STP. We found that dynamical synapses (STP) have a critical differential role on evaluating and modulating the firing rate activity in each network scenario. Moreover, we investigated the impact of changing the balance between excitation (E) and inhibition (I) on stabilizing this firing activity. © 2017 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

  5. Shapley ratings in brain networks

    Directory of Open Access Journals (Sweden)

    Rolf Kötter

    2007-11-01

    Full Text Available Recent applications of network theory to brain networks as well as the expanding empirical databases of brain architecture spawn an interest in novel techniques for analyzing connectivity patterns in the brain. Treating individual brain structures as nodes in a directed graph model permits the application of graph theoretical concepts to the analysis of these structures within their large-scale connectivity networks. In this paper, we explore the application of concepts from graph and game theory toward this end. Specifically, we utilize the Shapley value principle, which assigns a rank to players in a coalition based upon their individual contributions to the collective profit of that coalition, to assess the contributions of individual brain structures to the graph derived from the global connectivity network. We report Shapley values for variations of a prefrontal network, as well as for a visual cortical network, which had both been extensively investigated previously. This analysis highlights particular nodes as strong or weak contributors to global connectivity. To understand the nature of their contribution, we compare the Shapley values obtained from these networks and appropriate controls to other previously described nodal measures of structural connectivity. We find a strong correlation between Shapley values and both betweenness centrality and connection density. Moreover, a stepwise multiple linear regression analysis indicates that approximately 79% of the variance in Shapley values obtained from random networks can be explained by betweenness centrality alone. Finally, we investigate the effects of local lesions on the Shapley ratings, showing that the present networks have an immense structural resistance to degradation. We discuss our results highlighting the use of such measures for characterizing the organization and functional role of brain networks.

  6. Fire danger rating network density

    Science.gov (United States)

    Rudy M. King; R. William Furman

    1976-01-01

    Conventional statistical techniques are used to answer the question, "What is the necessary station density for a fire danger network?" The Burning Index of the National Fire-Danger Rating System is used as an indicator of fire danger. Results are presented as station spacing in tabular form for each of six regions in the western United States.

  7. Feed-Forward Propagation of Temporal and Rate Information between Cortical Populations during Coherent Activation in Engineered In Vitro Networks.

    Science.gov (United States)

    DeMarse, Thomas B; Pan, Liangbin; Alagapan, Sankaraleengam; Brewer, Gregory J; Wheeler, Bruce C

    2016-01-01

    Transient propagation of information across neuronal assembles is thought to underlie many cognitive processes. However, the nature of the neural code that is embedded within these transmissions remains uncertain. Much of our understanding of how information is transmitted among these assemblies has been derived from computational models. While these models have been instrumental in understanding these processes they often make simplifying assumptions about the biophysical properties of neurons that may influence the nature and properties expressed. To address this issue we created an in vitro analog of a feed-forward network composed of two small populations (also referred to as assemblies or layers) of living dissociated rat cortical neurons. The populations were separated by, and communicated through, a microelectromechanical systems (MEMS) device containing a strip of microscale tunnels. Delayed culturing of one population in the first layer followed by the second a few days later induced the unidirectional growth of axons through the microtunnels resulting in a primarily feed-forward communication between these two small neural populations. In this study we systematically manipulated the number of tunnels that connected each layer and hence, the number of axons providing communication between those populations. We then assess the effect of reducing the number of tunnels has upon the properties of between-layer communication capacity and fidelity of neural transmission among spike trains transmitted across and within layers. We show evidence based on Victor-Purpura's and van Rossum's spike train similarity metrics supporting the presence of both rate and temporal information embedded within these transmissions whose fidelity increased during communication both between and within layers when the number of tunnels are increased. We also provide evidence reinforcing the role of synchronized activity upon transmission fidelity during the spontaneous synchronized

  8. Feed-Forward Propagation of Temporal and Rate Information between Cortical Populations during Coherent Activation in Engineered In Vitro Networks

    Science.gov (United States)

    DeMarse, Thomas B.; Pan, Liangbin; Alagapan, Sankaraleengam; Brewer, Gregory J.; Wheeler, Bruce C.

    2016-01-01

    Transient propagation of information across neuronal assembles is thought to underlie many cognitive processes. However, the nature of the neural code that is embedded within these transmissions remains uncertain. Much of our understanding of how information is transmitted among these assemblies has been derived from computational models. While these models have been instrumental in understanding these processes they often make simplifying assumptions about the biophysical properties of neurons that may influence the nature and properties expressed. To address this issue we created an in vitro analog of a feed-forward network composed of two small populations (also referred to as assemblies or layers) of living dissociated rat cortical neurons. The populations were separated by, and communicated through, a microelectromechanical systems (MEMS) device containing a strip of microscale tunnels. Delayed culturing of one population in the first layer followed by the second a few days later induced the unidirectional growth of axons through the microtunnels resulting in a primarily feed-forward communication between these two small neural populations. In this study we systematically manipulated the number of tunnels that connected each layer and hence, the number of axons providing communication between those populations. We then assess the effect of reducing the number of tunnels has upon the properties of between-layer communication capacity and fidelity of neural transmission among spike trains transmitted across and within layers. We show evidence based on Victor-Purpura’s and van Rossum’s spike train similarity metrics supporting the presence of both rate and temporal information embedded within these transmissions whose fidelity increased during communication both between and within layers when the number of tunnels are increased. We also provide evidence reinforcing the role of synchronized activity upon transmission fidelity during the spontaneous

  9. Peer Ratings in Massive Online Social Networks

    OpenAIRE

    Zinoviev, Dmitry

    2014-01-01

    Instant quality feedback in the form of online peer ratings is a prominent feature of modern massive online social networks (MOSNs). It allows network members to indicate their appreciation of a post, comment, photograph, etc. Some MOSNs support both positive and negative (signed) ratings. In this study, we rated 11 thousand MOSN member profiles and collected user responses to the ratings. MOSN users are very sensitive to peer ratings: 33% of the subjects visited the researcher's profile in r...

  10. Dimensions of network activity

    NARCIS (Netherlands)

    Torenvlied, R.; Akkerman, A.; Meier, K.; O'Toole, L.

    2013-01-01

    Studies in public management show that agencies draw different types of support from different actors and organizations in their environment. If this is true, we would expect that managers differentiate their networking activity toward different types of external actors and organizations. However,

  11. Active Versus Passive Academic Networking

    DEFF Research Database (Denmark)

    Goel, Rajeev K.; Grimpe, Christoph

    2013-01-01

    This paper examines determinants of networking by academics. Using information from a unique large survey of German researchers, the key contribution focuses on the active versus passive networking distinction. Is active networking by researchers a substitute or a complement to passive networking...... that some types of passive academic networking are complementary to active networking, while others are substitute. Further, we find differences in factors promoting participation in European conferences versus conferences in rest of the world. Finally, publishing bottlenecks as a group generally do...... not appear to be a hindrance to active networking. Implications for academic policy are discussed...

  12. Distributed Rate Allocation for Wireless Networks

    CERN Document Server

    Jose, Jubin

    2010-01-01

    This paper describes a distributed algorithm for rate allocation in wireless networks. As the main result, the paper establishes that this algorithm is throughput-optimal for very general class of throughput regions. In contrast to distributed on-off scheduling algorithms, this algorithm enables optimal utilization of physical layer schemes by scheduling multiple rate levels. The algorithm is based on a Markov process on these discrete set of rates with certain transition rates. For dealing with multiple rate levels, the paper introduces an important structure for the transition rates, which enable the design of appropriate update rule for these transition rates. The update uses local queue length information alone, and thus does not require global exchange of queue length information. In addition, the algorithm requires that each link can determine the feasibility of increasing its data-rate from the current value without reducing the data-rates of other links. Determining rate feasibility does not introduce...

  13. Stochastic cycle selection in active flow networks

    Science.gov (United States)

    Woodhouse, Francis; Forrow, Aden; Fawcett, Joanna; Dunkel, Jorn

    2016-11-01

    Active biological flow networks pervade nature and span a wide range of scales, from arterial blood vessels and bronchial mucus transport in humans to bacterial flow through porous media or plasmodial shuttle streaming in slime molds. Despite their ubiquity, little is known about the self-organization principles that govern flow statistics in such non-equilibrium networks. By connecting concepts from lattice field theory, graph theory and transition rate theory, we show how topology controls dynamics in a generic model for actively driven flow on a network. Through theoretical and numerical analysis we identify symmetry-based rules to classify and predict the selection statistics of complex flow cycles from the network topology. Our conceptual framework is applicable to a broad class of biological and non-biological far-from-equilibrium networks, including actively controlled information flows, and establishes a new correspondence between active flow networks and generalized ice-type models.

  14. A Network Centrality Method for the Rating Problem

    Science.gov (United States)

    2015-01-01

    We propose a new method for aggregating the information of multiple users rating multiple items. Our approach is based on the network relations induced between items by the rating activity of the users. Our method correlates better than the simple average with respect to the original rankings of the users, and besides, it is computationally more efficient than other methods proposed in the literature. Moreover, our method is able to discount the information that would be obtained adding to the system additional users with a systematically biased rating activity. PMID:25830502

  15. Neural Networks Modelling of Municipal Real Estate Market Rent Rates

    Directory of Open Access Journals (Sweden)

    Muczyński Andrzej

    2016-12-01

    Full Text Available This paper presents the results of research on the application of neural networks modelling of municipal real estate market rent rates. The test procedure was based on selected networks trained on the local real estate market data and transformation of the detected dependencies – through established models – to estimate the potential market rent rates of municipal premises. On this basis, the assessment of the adequacy of the actual market rent rates of municipal properties was made. Empirical research was conducted on the local real estate market of the city of Olsztyn in Poland. In order to describe the phenomenon of market rent rates formation an unidirectional three-layer network and a network of radial base was selected. Analyses showed a relatively low degree of convergence of the actual municipal rent rents with potential market rent rates. This degree was strongly varied depending on the type of business ran on the property and its’ social and economic impact. The applied research methodology and the obtained results can be used in order to rationalize municipal property management, including the activation of rental policy.

  16. Modeling network technology deployment rates with different network models

    OpenAIRE

    Chung, Yoo

    2011-01-01

    To understand the factors that encourage the deployment of a new networking technology, we must be able to model how such technology gets deployed. We investigate how network structure influences deployment with a simple deployment model and different network models through computer simulations. The results indicate that a realistic model of networking technology deployment should take network structure into account.

  17. How adaptation shapes spike rate oscillations in recurrent neuronal networks

    Directory of Open Access Journals (Sweden)

    Moritz eAugustin

    2013-02-01

    Full Text Available Neural mass signals from in-vivo recordings often show oscillations with frequencies ranging from <1 Hz to 100 Hz. Fast rhythmic activity in the beta and gamma range can be generated by network based mechanisms such as recurrent synaptic excitation-inhibition loops. Slower oscillations might instead depend on neuronal adaptation currents whose timescales range from tens of milliseconds to seconds. Here we investigate how the dynamics of such adaptation currents contribute to spike rate oscillations and resonance properties in recurrent networks of excitatory and inhibitory neurons. Based on a network of sparsely coupled spiking model neurons with two types of adaptation current and conductance based synapses with heterogeneous strengths and delays we use a mean-field approach to analyze oscillatory network activity. For constant external input, we find that spike-triggered adaptation currents provide a mechanism to generate slow oscillations over a wide range of adaptation timescales as long as recurrent synaptic excitation is sufficiently strong. Faster rhythms occur when recurrent inhibition is slower than excitation and oscillation frequency increases with the strength of inhibition. Adaptation facilitates such network based oscillations for fast synaptic inhibition and leads to decreased frequencies. For oscillatory external input, adaptation currents amplify a narrow band of frequencies and cause phase advances for low frequencies in addition to phase delays at higher frequencies. Our results therefore identify the different key roles of neuronal adaptation dynamics for rhythmogenesis and selective signal propagation in recurrent networks.

  18. Rate Aware Instantly Decodable Network Codes

    KAUST Repository

    Douik, Ahmed

    2016-02-26

    This paper addresses the problem of reducing the delivery time of data messages to cellular users using instantly decodable network coding (IDNC) with physical-layer rate awareness. While most of the existing literature on IDNC does not consider any physical layer complications, this paper proposes a cross-layer scheme that incorporates the different channel rates of the various users in the decision process of both the transmitted message combinations and the rates with which they are transmitted. The completion time minimization problem in such scenario is first shown to be intractable. The problem is, thus, approximated by reducing, at each transmission, the increase of an anticipated version of the completion time. The paper solves the problem by formulating it as a maximum weight clique problem over a newly designed rate aware IDNC (RA-IDNC) graph. Further, the paper provides a multi-layer solution to improve the completion time approximation. Simulation results suggest that the cross-layer design largely outperforms the uncoded transmissions strategies and the classical IDNC scheme. © 2015 IEEE.

  19. Artificial Neural Network for Monthly Rainfall Rate Prediction

    Science.gov (United States)

    Purnomo, H. D.; Hartomo, K. D.; Prasetyo, S. Y. J.

    2017-03-01

    Rainfall rate forecasting plays an important role in various human activities. Rainfall forecasting is a challenging task due to the uncertainty of natural phenomena. In this paper, two neural network models are proposed for monthly rainfall rate forecasting. The performance of the proposed model is assesses based on monthly rainfall rate in Ampel, Boyolali, from 2001-2013. The experiment results show that the accuracy of the first model is much better than the accuracy of the second model. Its average accuracy is just above 98%, while the accuracy of the second model is approximately 75%. In additional, both models tend to perform better when the fluctuation of rainfall is low.

  20. Networking Technologies and the Rate of Technological Change

    Directory of Open Access Journals (Sweden)

    Charles Mitchell

    2005-12-01

    Full Text Available Network technology is changing rapidly and those adept at ICT analysis need resolve rate of change issues. Developments in networking now are in the direction of heuristic intelligence. Since about 1980, networking techniques have encouraged combining bits of information with imagination cognitively to improve ideas about reality. ICT enterprise projects utilize networking to sustain requisite imagination. Assumptions and misassuptions of project builders are rationally comprehended as networking sustains creative processes. The monopolization of valuable network techniques influences in the direction of esoteric networking. Data presents that substantial knowledge and networking is now occurring globally. As a netaphor, networking

  1. Theorizing Network-Centric Activity in Education

    Science.gov (United States)

    HaLevi, Andrew

    2011-01-01

    Networks and network-centric activity are increasingly prevalent in schools and school districts. In addition to ubiquitous social network tools like Facebook and Twitter, educational leaders deal with a wide variety of network organizational forms that include professional development, advocacy, informational networks and network-centric reforms.…

  2. Networking activism: implications for Greece

    Directory of Open Access Journals (Sweden)

    Pantelis Vatikiotis

    2011-12-01

    Full Text Available The outbreak of December 2008 against police brutality through a wave of demonstrations and street protests in Athens, which was strongly advocated by protest activities and practices across the world, addresses several issues in relation to the transformative potentials of mediated collective action. The paper critically evaluates different accounts of December events, probing then into thevery networking of that movement. From this perspective, it points out another aspect of the local-global interplay in protest culture along new mediating practices (beyond the creation of transnational publics, that of the implications of transnational networking for local social activism and identification, addressing relevant questions in the Greek context.

  3. Neural network analysis of varying trends in real exchange rates

    NARCIS (Netherlands)

    J.F. Kaashoek (Johan); H.K. van Dijk (Herman)

    1999-01-01

    textabstractIn this paper neural networks are fitted to the real exchange rates of seven industrialized countries. The size and topology of the used networks is found by reducing the size of the network through the use of multiple correlation coefficients, principal component analysis of residuals

  4. How Sleep Activates Epileptic Networks?

    Directory of Open Access Journals (Sweden)

    Peter Halász

    2013-01-01

    Full Text Available Background. The relationship between sleep and epilepsy has been long ago studied, and several excellent reviews are available. However, recent development in sleep research, the network concept in epilepsy, and the recognition of high frequency oscillations in epilepsy and more new results may put this matter in a new light. Aim. The review address the multifold interrelationships between sleep and epilepsy networks and with networks of cognitive functions. Material and Methods. The work is a conceptual update of the available clinical data and relevant studies. Results and Conclusions. Studies exploring dynamic microstructure of sleep have found important gating mechanisms for epileptic activation. As a general rule interictal epileptic manifestations seem to be linked to the slow oscillations of sleep and especially to the reactive delta bouts characterized by A1 subtype in the CAP system. Important link between epilepsy and sleep is the interference of epileptiform discharges with the plastic functions in NREM sleep. This is the main reason of cognitive impairment in different forms of early epileptic encephalopathies affecting the brain in a special developmental window. The impairment of cognitive functions via sleep is present especially in epileptic networks involving the thalamocortical system and the hippocampocortical memory encoding system.

  5. Importance sampling in rate-sharing networks

    NARCIS (Netherlands)

    Lieshout, P.; Mandjes, M.

    2008-01-01

    We consider a network supporting elastic traffic, where the service capacity is shared among the various classes according to an alpha-fair sharing policy. Assuming Poisson arrivals and exponentially distributed service requirements for each class, the dynamics of the user population may be

  6. A network centrality method for the rating problem

    CERN Document Server

    Li, Yongli; Wu, Chong

    2014-01-01

    We propose a new method for aggregating the information of multiple reviewers rating multiple products. Our approach is based on the network relations induced between products by the rating activity of the reviewers. We show that our method is algorithmically implementable even for large numbers of both products and consumers, as is the case for many online sites. Moreover, comparing it with the simple average, which is mostly used in practice, and with other methods previously proposed in the literature, it performs very well under various dimension, proving itself to be an optimal trade--off between computational efficiency, accordance with the reviewers original orderings, and robustness with respect to the inclusion of systematically biased reports.

  7. Coordinated Voltage Control of Active Distribution Network

    Directory of Open Access Journals (Sweden)

    Xie Jiang

    2016-01-01

    Full Text Available This paper presents a centralized coordinated voltage control method for active distribution network to solve off-limit problem of voltage after incorporation of distributed generation (DG. The proposed method consists of two parts, it coordinated primal-dual interior point method-based voltage regulation schemes of DG reactive powers and capacitors with centralized on-load tap changer (OLTC controlling method which utilizes system’s maximum and minimum voltages, to improve the qualified rate of voltage and reduce the operation numbers of OLTC. The proposed coordination has considered the cost of capacitors. The method is tested using a radial edited IEEE-33 nodes distribution network which is modelled using MATLAB.

  8. Information mining in weighted complex networks with nonlinear rating projection

    Science.gov (United States)

    Liao, Hao; Zeng, An; Zhou, Mingyang; Mao, Rui; Wang, Bing-Hong

    2017-10-01

    Weighted rating networks are commonly used by e-commerce providers nowadays. In order to generate an objective ranking of online items' quality according to users' ratings, many sophisticated algorithms have been proposed in the complex networks domain. In this paper, instead of proposing new algorithms we focus on a more fundamental problem: the nonlinear rating projection. The basic idea is that even though the rating values given by users are linearly separated, the real preference of users to items between the different given values is nonlinear. We thus design an approach to project the original ratings of users to more representative values. This approach can be regarded as a data pretreatment method. Simulation in both artificial and real networks shows that the performance of the ranking algorithms can be improved when the projected ratings are used.

  9. Algorithm for queueing networks with multi-rate traffic

    DEFF Research Database (Denmark)

    Iversen, Villy Bæk; King-Tim, Ko

    2011-01-01

    In this paper we present a new algorithm for evaluating queueing networks with multi-rate traffic. The detailed state space of a node is evaluated by explicit formulæ. We consider reversible nodes with multi-rate traffic and find the state probabilities by taking advantage of local balance. Theory...... is reversibility which implies that the arrival process and departure process are identical processes, for example state-dependent Poisson processes. This property is equivalent to reversibility. Due to product form, an open network with multi-rate traffic is easy to evaluate by convolution algorithms because...

  10. A reconsideration of negative ratings for network-based recommendation

    Science.gov (United States)

    Hu, Liang; Ren, Liang; Lin, Wenbin

    2018-01-01

    Recommendation algorithms based on bipartite networks have become increasingly popular, thanks to their accuracy and flexibility. Currently, many of these methods ignore users' negative ratings. In this work, we propose a method to exploit negative ratings for the network-based inference algorithm. We find that negative ratings play a positive role regardless of sparsity of data sets. Furthermore, we improve the efficiency of our method and compare it with the state-of-the-art algorithms. Experimental results show that the present method outperforms the existing algorithms.

  11. Algorithm for queueing networks with multi-rate traffic

    DEFF Research Database (Denmark)

    Iversen, Villy Bæk; Ko, King-Tim

    2011-01-01

    In this paper we present a new algorithm for evaluating queueing networks with multi-rate traffic. The detailed state space of a node is evaluated by explicit formulæ. We consider reversible nodes with multi-rate traffic and find the state probabilities by taking advantage of local balance. Theory...... is reversibility which implies that the arrival process and departure process are identical processes, for example state-dependent Poisson processes. This property is equivalent to reversibility. Due to product form, an open network with multi-rate traffic is easy to evaluate by convolution algorithms because...... the nodes behave as independent nodes. For closed queueing networks with multiple servers in every node and multi-rate services we may apply multidimensional convolution algorithm to aggregate the nodes so that we end up with two nodes, the aggregated node and a single node, for which we can calculate...

  12. Modeling the Relationship Between Social Network Activity, Inactivity, and Growth

    CERN Document Server

    Ribeiro, Bruno

    2013-01-01

    Online Social Networks (OSNs) are multi-billion dollar enterprises. Surprisingly, little is known about the mechanisms that drive them to growth, stability, or death. This study sheds light on these mechanisms. We are particularly interested in OSNs where current subscribers can invite new users to join the network (e.g., Facebook, LinkedIn). Measuring the relationship between subscriber activity and network growth of a large OSN over five years, we formulate three hypotheses that together describe the observed OSN subscriber behavior. We then provide a model (and extensions) that simultaneously satisfies all three hypotheses. Our model provides deep insights into the dynamics of subscriber activity, inactivity, and network growth rates, even predicting four types of OSNs with respect to subscriber activity evolution. Finally, we present activity data of nearly thirty OSN websites, measured over five years, and show that the observed activity is well described by one of the four activity time series predicted...

  13. Shaping Neuronal Network Activity by Presynaptic Mechanisms.

    Directory of Open Access Journals (Sweden)

    Ayal Lavi

    2015-09-01

    Full Text Available Neuronal microcircuits generate oscillatory activity, which has been linked to basic functions such as sleep, learning and sensorimotor gating. Although synaptic release processes are well known for their ability to shape the interaction between neurons in microcircuits, most computational models do not simulate the synaptic transmission process directly and hence cannot explain how changes in synaptic parameters alter neuronal network activity. In this paper, we present a novel neuronal network model that incorporates presynaptic release mechanisms, such as vesicle pool dynamics and calcium-dependent release probability, to model the spontaneous activity of neuronal networks. The model, which is based on modified leaky integrate-and-fire neurons, generates spontaneous network activity patterns, which are similar to experimental data and robust under changes in the model's primary gain parameters such as excitatory postsynaptic potential and connectivity ratio. Furthermore, it reliably recreates experimental findings and provides mechanistic explanations for data obtained from microelectrode array recordings, such as network burst termination and the effects of pharmacological and genetic manipulations. The model demonstrates how elevated asynchronous release, but not spontaneous release, synchronizes neuronal network activity and reveals that asynchronous release enhances utilization of the recycling vesicle pool to induce the network effect. The model further predicts a positive correlation between vesicle priming at the single-neuron level and burst frequency at the network level; this prediction is supported by experimental findings. Thus, the model is utilized to reveal how synaptic release processes at the neuronal level govern activity patterns and synchronization at the network level.

  14. Shaping Neuronal Network Activity by Presynaptic Mechanisms

    Science.gov (United States)

    Ashery, Uri

    2015-01-01

    Neuronal microcircuits generate oscillatory activity, which has been linked to basic functions such as sleep, learning and sensorimotor gating. Although synaptic release processes are well known for their ability to shape the interaction between neurons in microcircuits, most computational models do not simulate the synaptic transmission process directly and hence cannot explain how changes in synaptic parameters alter neuronal network activity. In this paper, we present a novel neuronal network model that incorporates presynaptic release mechanisms, such as vesicle pool dynamics and calcium-dependent release probability, to model the spontaneous activity of neuronal networks. The model, which is based on modified leaky integrate-and-fire neurons, generates spontaneous network activity patterns, which are similar to experimental data and robust under changes in the model's primary gain parameters such as excitatory postsynaptic potential and connectivity ratio. Furthermore, it reliably recreates experimental findings and provides mechanistic explanations for data obtained from microelectrode array recordings, such as network burst termination and the effects of pharmacological and genetic manipulations. The model demonstrates how elevated asynchronous release, but not spontaneous release, synchronizes neuronal network activity and reveals that asynchronous release enhances utilization of the recycling vesicle pool to induce the network effect. The model further predicts a positive correlation between vesicle priming at the single-neuron level and burst frequency at the network level; this prediction is supported by experimental findings. Thus, the model is utilized to reveal how synaptic release processes at the neuronal level govern activity patterns and synchronization at the network level. PMID:26372048

  15. Network management systems for active distribution networks. A feasibility study

    Energy Technology Data Exchange (ETDEWEB)

    Roberts, D.A.

    2004-07-01

    A technical feasibility study on network management systems for active distribution networks is reported. The study investigated the potential for modifying a Distribution Network Operator (DNO) Supervisory Control and Data Acquisition System (SCADA) to give some degree of active management. Government incentives have encouraged more and more embedded generation being connected to the UK distribution networks and further acceleration of the process should support the 2010 target for a reduction in emissions of carbon dioxide. The report lists the objectives of the study and summarises what has been achieved; it also discusses limitations, reliability and resilience of existing SCADA. Safety and operational communications are discussed under staff safety and operational safety. Recommendations that could facilitate active management through SCADA are listed, together with suggestions for further study. The work was carried out as part of the DTI New and Renewable Energy Programme managed by Future Energy Solutions.

  16. Estimation of blood flow rates in large microvascular networks.

    Science.gov (United States)

    Fry, Brendan C; Lee, Jack; Smith, Nicolas P; Secomb, Timothy W

    2012-08-01

    Recent methods for imaging microvascular structures provide geometrical data on networks containing thousands of segments. Prediction of functional properties, such as solute transport, requires information on blood flow rates also, but experimental measurement of many individual flows is difficult. Here, a method is presented for estimating flow rates in a microvascular network based on incomplete information on the flows in the boundary segments that feed and drain the network. With incomplete boundary data, the equations governing blood flow form an underdetermined linear system. An algorithm was developed that uses independent information about the distribution of wall shear stresses and pressures in microvessels to resolve this indeterminacy, by minimizing the deviation of pressures and wall shear stresses from target values. The algorithm was tested using previously obtained experimental flow data from four microvascular networks in the rat mesentery. With two or three prescribed boundary conditions, predicted flows showed relatively small errors in most segments and fewer than 10% incorrect flow directions on average. The proposed method can be used to estimate flow rates in microvascular networks, based on incomplete boundary data, and provides a basis for deducing functional properties of microvessel networks. © 2012 John Wiley & Sons Ltd.

  17. Firing rate dynamics in recurrent spiking neural networks with intrinsic and network heterogeneity.

    Science.gov (United States)

    Ly, Cheng

    2015-12-01

    Heterogeneity of neural attributes has recently gained a lot of attention and is increasing recognized as a crucial feature in neural processing. Despite its importance, this physiological feature has traditionally been neglected in theoretical studies of cortical neural networks. Thus, there is still a lot unknown about the consequences of cellular and circuit heterogeneity in spiking neural networks. In particular, combining network or synaptic heterogeneity and intrinsic heterogeneity has yet to be considered systematically despite the fact that both are known to exist and likely have significant roles in neural network dynamics. In a canonical recurrent spiking neural network model, we study how these two forms of heterogeneity lead to different distributions of excitatory firing rates. To analytically characterize how these types of heterogeneities affect the network, we employ a dimension reduction method that relies on a combination of Monte Carlo simulations and probability density function equations. We find that the relationship between intrinsic and network heterogeneity has a strong effect on the overall level of heterogeneity of the firing rates. Specifically, this relationship can lead to amplification or attenuation of firing rate heterogeneity, and these effects depend on whether the recurrent network is firing asynchronously or rhythmically firing. These observations are captured with the aforementioned reduction method, and furthermore simpler analytic descriptions based on this dimension reduction method are developed. The final analytic descriptions provide compact and descriptive formulas for how the relationship between intrinsic and network heterogeneity determines the firing rate heterogeneity dynamics in various settings.

  18. Mode Selection in Compressible Active Flow Networks

    Science.gov (United States)

    Forrow, Aden; Woodhouse, Francis G.; Dunkel, Jörn

    2017-07-01

    Coherent, large-scale dynamics in many nonequilibrium physical, biological, or information transport networks are driven by small-scale local energy input. Here, we introduce and explore an analytically tractable nonlinear model for compressible active flow networks. In contrast to thermally driven systems, we find that active friction selects discrete states with a limited number of oscillation modes activated at distinct fixed amplitudes. Using perturbation theory, we systematically predict the stationary states of noisy networks and find good agreement with a Bayesian state estimation based on a hidden Markov model applied to simulated time series data. Our results suggest that the macroscopic response of active network structures, from actomyosin force networks to cytoplasmic flows, can be dominated by a significantly reduced number of modes, in contrast to energy equipartition in thermal equilibrium. The model is also well suited to study topological sound modes and spectral band gaps in active matter.

  19. When do correlations increase with firing rates in recurrent networks?

    Directory of Open Access Journals (Sweden)

    Andrea K Barreiro

    2017-04-01

    Full Text Available A central question in neuroscience is to understand how noisy firing patterns are used to transmit information. Because neural spiking is noisy, spiking patterns are often quantified via pairwise correlations, or the probability that two cells will spike coincidentally, above and beyond their baseline firing rate. One observation frequently made in experiments, is that correlations can increase systematically with firing rate. Theoretical studies have determined that stimulus-dependent correlations that increase with firing rate can have beneficial effects on information coding; however, we still have an incomplete understanding of what circuit mechanisms do, or do not, produce this correlation-firing rate relationship. Here, we studied the relationship between pairwise correlations and firing rates in recurrently coupled excitatory-inhibitory spiking networks with conductance-based synapses. We found that with stronger excitatory coupling, a positive relationship emerged between pairwise correlations and firing rates. To explain these findings, we used linear response theory to predict the full correlation matrix and to decompose correlations in terms of graph motifs. We then used this decomposition to explain why covariation of correlations with firing rate-a relationship previously explained in feedforward networks driven by correlated input-emerges in some recurrent networks but not in others. Furthermore, when correlations covary with firing rate, this relationship is reflected in low-rank structure in the correlation matrix.

  20. Altered default network activity in obesity.

    Science.gov (United States)

    Tregellas, Jason R; Wylie, Korey P; Rojas, Donald C; Tanabe, Jody; Martin, Jesse; Kronberg, Eugene; Cordes, Dietmar; Cornier, Marc-Andre

    2011-12-01

    The regulation of energy intake is a complex process involving the integration of homeostatic signals and both internal and external sensory inputs. To better understand the neurobiology of this process and how it may be dysfunctional in obesity, this study examined activity of the brain's "default network" in reduced-obese (RO) as compared to lean individuals. The default network is a group of functionally connected brain regions thought to play an important role in internally directed cognitive activity and the interplay between external and internal sensory processing. Functional magnetic resonance imaging was performed in 24 lean and 18 RO individuals in the fasted state after 2 days of eucaloric energy intake and after 2 days of 30% overfeeding in a counterbalanced design. Scanning was performed while subjects passively viewed images of food and nonfood objects. Independent component analysis was used to identify the default network component. In the eucaloric state, greater default network activity was observed in RO compared to lean individuals in the lateral inferior parietal and posterior cingulate cortices. Activity was positively correlated with appetite. Overfeeding resulted in increased default network activity in lean but not RO individuals. These findings suggest that the function of the default network, a major contributor to intrinsic neuronal activity, is altered in obesity and/or obese-prone individuals. Future studies of the network's function and its relationship to other brain networks may improve our understanding of the mechanisms and treatment of obesity.

  1. The interchangeability of learning rate and gain in backpropagation neural networks

    NARCIS (Netherlands)

    Thimm, G.; Moerland, P.; Fiesler, E.

    1996-01-01

    The backpropagation algorithm is widely used for training multilayer neural networks. In this publication the gain of its activation function(s) is investigated. In specific, it is proven that changing the gain of the activation function is equivalent to changing the learning rate and the weights.

  2. Opinion dynamics in activity-driven networks

    Science.gov (United States)

    Li, Dandan; Han, Dun; Ma, Jing; Sun, Mei; Tian, Lixin; Khouw, Timothy; Stanley, H. Eugene

    2017-10-01

    Social interaction between individuals constantly affects the development of their personal opinions. Previous models such as the Deffuant model and the Hegselmann-Krause (HK) model have assumed that individuals only update their opinions after interacting with neighbors whose opinions are similar to their own. However, people are capable of communicating widely with all of their neighbors to gather their ideas and opinions, even if they encounter a number of opposing attitudes. We propose a model in which agents listen to the opinions of all their neighbors. Continuous opinion dynamics are investigated in activity-driven networks with a tolerance threshold. We study how the initial opinion distribution, tolerance threshold, opinion-updating speed, and activity rate affect the evolution of opinion. We find that when the initial fraction of positive opinion is small, all opinions become negative by the end of the simulation. As the initial fraction of positive opinions rises above a certain value —about 0.45— the final fraction of positive opinions sharply increases and eventually equals 1. Increased tolerance threshold δ is found to lead to a more varied final opinion distribution. We also find that if the negative opinion has an initial advantage, the final fraction of negative opinion increases and reaches its peak as the updating speed λ approaches 0.5. Finally we show that the lower the activity rate of individuals, the greater the fluctuation range of their opinions.

  3. Botulinum Toxin Suppression of CNS Network Activity In Vitro

    Directory of Open Access Journals (Sweden)

    Joseph J. Pancrazio

    2014-01-01

    Full Text Available The botulinum toxins are potent agents which disrupt synaptic transmission. While the standard method for BoNT detection and quantification is based on the mouse lethality assay, we have examined whether alterations in cultured neuronal network activity can be used to detect the functional effects of BoNT. Murine spinal cord and frontal cortex networks cultured on substrate integrated microelectrode arrays allowed monitoring of spontaneous spike and burst activity with exposure to BoNT serotype A (BoNT-A. Exposure to BoNT-A inhibited spike activity in cultured neuronal networks where, after a delay due to toxin internalization, the rate of activity loss depended on toxin concentration. Over a 30 hr exposure to BoNT-A, the minimum concentration detected was 2 ng/mL, a level consistent with mouse lethality studies. A small proportion of spinal cord networks, but not frontal cortex networks, showed a transient increase in spike and burst activity with exposure to BoNT-A, an effect likely due to preferential inhibition of inhibitory synapses expressed in this tissue. Lastly, prior exposure to human-derived antisera containing neutralizing antibodies prevented BoNT-A induced inhibition of network spike activity. These observations suggest that the extracellular recording from cultured neuronal networks can be used to detect and quantify functional BoNT effects.

  4. Competing activation mechanisms in epidemics on networks

    Science.gov (United States)

    Castellano, Claudio; Pastor-Satorras, Romualdo

    2012-04-01

    In contrast to previous common wisdom that epidemic activity in heterogeneous networks is dominated by the hubs with the largest number of connections, recent research has pointed out the role that the innermost, dense core of the network plays in sustaining epidemic processes. Here we show that the mechanism responsible of spreading depends on the nature of the process. Epidemics with a transient state are boosted by the innermost core. Contrarily, epidemics allowing a steady state present a dual scenario, where either the hub independently sustains activity and propagates it to the rest of the system, or, alternatively, the innermost network core collectively turns into the active state, maintaining it globally. In uncorrelated networks the former mechanism dominates if the degree distribution decays with an exponent larger than 5/2, and the latter otherwise. Topological correlations, rife in real networks, may perturb this picture, mixing the role of both mechanisms.

  5. Network Events on Multiple Space and Time Scales in Cultured Neural Networks and in a Stochastic Rate Model.

    Directory of Open Access Journals (Sweden)

    Guido Gigante

    2015-11-01

    Full Text Available Cortical networks, in-vitro as well as in-vivo, can spontaneously generate a variety of collective dynamical events such as network spikes, UP and DOWN states, global oscillations, and avalanches. Though each of them has been variously recognized in previous works as expression of the excitability of the cortical tissue and the associated nonlinear dynamics, a unified picture of the determinant factors (dynamical and architectural is desirable and not yet available. Progress has also been partially hindered by the use of a variety of statistical measures to define the network events of interest. We propose here a common probabilistic definition of network events that, applied to the firing activity of cultured neural networks, highlights the co-occurrence of network spikes, power-law distributed avalanches, and exponentially distributed 'quasi-orbits', which offer a third type of collective behavior. A rate model, including synaptic excitation and inhibition with no imposed topology, synaptic short-term depression, and finite-size noise, accounts for all these different, coexisting phenomena. We find that their emergence is largely regulated by the proximity to an oscillatory instability of the dynamics, where the non-linear excitable behavior leads to a self-amplification of activity fluctuations over a wide range of scales in space and time. In this sense, the cultured network dynamics is compatible with an excitation-inhibition balance corresponding to a slightly sub-critical regime. Finally, we propose and test a method to infer the characteristic time of the fatigue process, from the observed time course of the network's firing rate. Unlike the model, possessing a single fatigue mechanism, the cultured network appears to show multiple time scales, signalling the possible coexistence of different fatigue mechanisms.

  6. Neural networks with discontinuous/impact activations

    CERN Document Server

    Akhmet, Marat

    2014-01-01

    This book presents as its main subject new models in mathematical neuroscience. A wide range of neural networks models with discontinuities are discussed, including impulsive differential equations, differential equations with piecewise constant arguments, and models of mixed type. These models involve discontinuities, which are natural because huge velocities and short distances are usually observed in devices modeling the networks. A discussion of the models, appropriate for the proposed applications, is also provided. This book also: Explores questions related to the biological underpinning for models of neural networks\\ Considers neural networks modeling using differential equations with impulsive and piecewise constant argument discontinuities Provides all necessary mathematical basics for application to the theory of neural networks Neural Networks with Discontinuous/Impact Activations is an ideal book for researchers and professionals in the field of engineering mathematics that have an interest in app...

  7. Complex Network for Solar Active Regions

    Science.gov (United States)

    Daei, Farhad; Safari, Hossein; Dadashi, Neda

    2017-08-01

    In this paper we developed a complex network of solar active regions (ARs) to study various local and global properties of the network. The values of the Hurst exponent (0.8-0.9) were evaluated by both the detrended fluctuation analysis and the rescaled range analysis applied on the time series of the AR numbers. The findings suggest that ARs can be considered as a system of self-organized criticality (SOC). We constructed a growing network based on locations, occurrence times, and the lifetimes of 4227 ARs recorded from 1999 January 1 to 2017 April 14. The behavior of the clustering coefficient shows that the AR network is not a random network. The logarithmic behavior of the length scale has the characteristics of a so-called small-world network. It is found that the probability distribution of the node degrees for undirected networks follows the power law with exponents of about 3.7-4.2. This indicates the scale-free nature of the AR network. The scale-free and small-world properties of the AR network confirm that the system of ARs forms a system of SOC. Our results show that the occurrence probability of flares (classified by GOES class C> 5, M, and X flares) in the position of the AR network hubs takes values greater than that obtained for other nodes.

  8. Decorrelation of Neural-Network Activity by Inhibitory Feedback

    Science.gov (United States)

    Einevoll, Gaute T.; Diesmann, Markus

    2012-01-01

    Correlations in spike-train ensembles can seriously impair the encoding of information by their spatio-temporal structure. An inevitable source of correlation in finite neural networks is common presynaptic input to pairs of neurons. Recent studies demonstrate that spike correlations in recurrent neural networks are considerably smaller than expected based on the amount of shared presynaptic input. Here, we explain this observation by means of a linear network model and simulations of networks of leaky integrate-and-fire neurons. We show that inhibitory feedback efficiently suppresses pairwise correlations and, hence, population-rate fluctuations, thereby assigning inhibitory neurons the new role of active decorrelation. We quantify this decorrelation by comparing the responses of the intact recurrent network (feedback system) and systems where the statistics of the feedback channel is perturbed (feedforward system). Manipulations of the feedback statistics can lead to a significant increase in the power and coherence of the population response. In particular, neglecting correlations within the ensemble of feedback channels or between the external stimulus and the feedback amplifies population-rate fluctuations by orders of magnitude. The fluctuation suppression in homogeneous inhibitory networks is explained by a negative feedback loop in the one-dimensional dynamics of the compound activity. Similarly, a change of coordinates exposes an effective negative feedback loop in the compound dynamics of stable excitatory-inhibitory networks. The suppression of input correlations in finite networks is explained by the population averaged correlations in the linear network model: In purely inhibitory networks, shared-input correlations are canceled by negative spike-train correlations. In excitatory-inhibitory networks, spike-train correlations are typically positive. Here, the suppression of input correlations is not a result of the mere existence of correlations between

  9. Selection on Network Dynamics Drives Differential Rates of Protein Domain Evolution.

    Directory of Open Access Journals (Sweden)

    Brian K Mannakee

    2016-07-01

    Full Text Available The long-held principle that functionally important proteins evolve slowly has recently been challenged by studies in mice and yeast showing that the severity of a protein knockout only weakly predicts that protein's rate of evolution. However, the relevance of these studies to evolutionary changes within proteins is unknown, because amino acid substitutions, unlike knockouts, often only slightly perturb protein activity. To quantify the phenotypic effect of small biochemical perturbations, we developed an approach to use computational systems biology models to measure the influence of individual reaction rate constants on network dynamics. We show that this dynamical influence is predictive of protein domain evolutionary rate within networks in vertebrates and yeast, even after controlling for expression level and breadth, network topology, and knockout effect. Thus, our results not only demonstrate the importance of protein domain function in determining evolutionary rate, but also the power of systems biology modeling to uncover unanticipated evolutionary forces.

  10. Estimating Ads’ Click through Rate with Recurrent Neural Network

    Directory of Open Access Journals (Sweden)

    Chen Qiao-Hong

    2016-01-01

    Full Text Available With the development of the Internet, online advertising spreads across every corner of the world, the ads' click through rate (CTR estimation is an important method to improve the online advertising revenue. Compared with the linear model, the nonlinear models can study much more complex relationships between a large number of nonlinear characteristics, so as to improve the accuracy of the estimation of the ads’ CTR. The recurrent neural network (RNN based on Long-Short Term Memory (LSTM is an improved model of the feedback neural network with ring structure. The model overcomes the problem of the gradient of the general RNN. Experiments show that the RNN based on LSTM exceeds the linear models, and it can effectively improve the estimation effect of the ads’ click through rate.

  11. Coupled interference based rate adaptation in ad hoc networks

    CSIR Research Space (South Africa)

    Awuor, F

    2011-09-01

    Full Text Available since the channel condition is time variant [5], [6]. Hence CIN considers link adaptation based on SINR performance to derive transmit power that minimizes coupled interference in the network. In [5], an algorithm is proposed where an average value... channel condition variance for proper choice of PHY mode. In [7], rate adaptation scheme is proposed wherein nodes select the power-rate pair to maximize their utility based on the previous measured SINRs. The values of SINR employed by [5],[6] and [7...

  12. NETWORK ACTIVATION DURING BIMANUAL MOVEMENTS IN HUMANS

    Science.gov (United States)

    Walsh, RR; Small, SL; Chen, EE; Solodkin, A.

    2008-01-01

    The coordination of movement between the upper limbs is a function highly distributed across the animal kingdom. How the central nervous system generates such bilateral, synchronous movements, and how this differs from the generation of unilateral movements, remains uncertain. Electrophysiologic and functional imaging studies support that the activity of many brain regions during bimanual and unimanual movement are quite similar. Thus, the same brain regions (and indeed the same neurons) respond similarly during unimanual and bimanual movements as measured by electrophysiological responses. How then are different motor behaviors generated? To address this question, we studied unimanual and bimanual movements using fMRI and constructed networks of activation using Structural Equation Modeling (SEM). Our results suggest that (1) the dominant hemisphere appears to initiate activity responsible for bimanual movement; (2) activation during bimanual movement does not reflect the sum of right and left unimanual activation; (3) production of unimanual movement involves a network that is distinct from, and not a mirror of, the network for contralateral unimanual movement; and (4) using SEM, it is possible to obtain robust group networks representative of a population and to identify individual networks which can be used to detect subtle differences both between subjects as well as within a single subject over time. In summary, these results highlight a differential role for the dominant and non-dominant hemispheres during bimanual movements, further elaborating the concept of handedness and dominance. This knowledge increases our understanding of cortical motor physiology in health and after neurological damage. PMID:18718872

  13. PROJECT ACTIVITY ANALYSIS WITHOUT THE NETWORK MODEL

    Directory of Open Access Journals (Sweden)

    S. Munapo

    2012-01-01

    Full Text Available

    ENGLISH ABSTRACT: This paper presents a new procedure for analysing and managing activity sequences in projects. The new procedure determines critical activities, critical path, start times, free floats, crash limits, and other useful information without the use of the network model. Even though network models have been successfully used in project management so far, there are weaknesses associated with the use. A network is not easy to generate, and dummies that are usually associated with it make the network diagram complex – and dummy activities have no meaning in the original project management problem. The network model for projects can be avoided while still obtaining all the useful information that is required for project management. What are required are the activities, their accurate durations, and their predecessors.

    AFRIKAANSE OPSOMMING: Die navorsing beskryf ’n nuwerwetse metode vir die ontleding en bestuur van die sekwensiële aktiwiteite van projekte. Die voorgestelde metode bepaal kritiese aktiwiteite, die kritieke pad, aanvangstye, speling, verhasing, en ander groothede sonder die gebruik van ’n netwerkmodel. Die metode funksioneer bevredigend in die praktyk, en omseil die administratiewe rompslomp van die tradisionele netwerkmodelle.

  14. Backtracking and Mixing Rate of Diffusion on Uncorrelated Temporal Networks

    Directory of Open Access Journals (Sweden)

    Martin Gueuning

    2017-10-01

    Full Text Available We consider the problem of diffusion on temporal networks, where the dynamics of each edge is modelled by an independent renewal process. Despite the apparent simplicity of the model, the trajectories of a random walker exhibit non-trivial properties. Here, we quantify the walker’s tendency to backtrack at each step (return where he/she comes from, as well as the resulting effect on the mixing rate of the process. As we show through empirical data, non-Poisson dynamics may significantly slow down diffusion due to backtracking, by a mechanism intrinsically different from the standard bus paradox and related temporal mechanisms. We conclude by discussing the implications of our work for the interpretation of results generated by null models of temporal networks.

  15. Reconstructing Causal Biological Networks through Active Learning.

    Directory of Open Access Journals (Sweden)

    Hyunghoon Cho

    Full Text Available Reverse-engineering of biological networks is a central problem in systems biology. The use of intervention data, such as gene knockouts or knockdowns, is typically used for teasing apart causal relationships among genes. Under time or resource constraints, one needs to carefully choose which intervention experiments to carry out. Previous approaches for selecting most informative interventions have largely been focused on discrete Bayesian networks. However, continuous Bayesian networks are of great practical interest, especially in the study of complex biological systems and their quantitative properties. In this work, we present an efficient, information-theoretic active learning algorithm for Gaussian Bayesian networks (GBNs, which serve as important models for gene regulatory networks. In addition to providing linear-algebraic insights unique to GBNs, leading to significant runtime improvements, we demonstrate the effectiveness of our method on data simulated with GBNs and the DREAM4 network inference challenge data sets. Our method generally leads to faster recovery of underlying network structure and faster convergence to final distribution of confidence scores over candidate graph structures using the full data, in comparison to random selection of intervention experiments.

  16. [Legal aspects of networking of medical activities].

    Science.gov (United States)

    Preissler, Reinhold

    2005-04-01

    Medical networks lack a legal definition. From the viewpoint of social law, this term means a form of organization of joint-service providers in a non-specified composition for the undertaking of medical care activities; from the point of view of occupational law, this consists of a loose form of joint practice. Such medical network can conclude treatment contracts with the patients and exchange patients' medical records. A practice network can take over services as contract partner of hospitals or other institutions, in the interest of improved competition chances within the integrated care system. The joining of a third partner is basically left open by the MBO, however according to SGB V this is possible only after approval by all contract partners. In advance of a planned medical care center, is it recommended to found a physician network as starting model. Before single practices fuse into a single enterprise, management-, tax-, legal-, as well as psychological aspects must be considered.

  17. Spontaneous Plasticity of Multineuronal Activity Patterns in Activated Hippocampal Networks

    Directory of Open Access Journals (Sweden)

    Atsushi Usami

    2008-01-01

    Full Text Available Using functional multineuron imaging with single-cell resolution, we examined how hippocampal networks by themselves change the spatiotemporal patterns of spontaneous activity during the course of emitting spontaneous activity. When extracellular ionic concentrations were changed to those that mimicked in vivo conditions, spontaneous activity was increased in active cell number and activity frequency. When ionic compositions were restored to the control conditions, the activity level returned to baseline, but the weighted spatial dispersion of active cells, as assessed by entropy-based metrics, did not. Thus, the networks can modify themselves by altering the internal structure of their correlated activity, even though they as a whole maintained the same level of activity in space and time.

  18. Neural Network Analysis and Evaluation of the Fetal Heart Rate

    Directory of Open Access Journals (Sweden)

    Yasuaki Noguchi

    2009-01-01

    Full Text Available The aim of the present study is to obtain a highly objective automatic fetal heart rate (FHR diagnosis. The neural network software was composed of three layers with the back propagation, to which 8 FHR data, including sinusoidal FHR, were input and the system was educated by the data of 20 cases with a known outcome. The output was the probability of a normal, intermediate, or pathologic outcome. The neural index studied prolonged monitoring. The neonatal states and the FHR score strongly correlated with the outcome probability. The neural index diagnosis was correct. The completed software was transferred to other computers, where the system function was correct.

  19. Simulation of heart rate variability model in a network

    Science.gov (United States)

    Cascaval, Radu C.; D'Apice, Ciro; D'Arienzo, Maria Pia

    2017-07-01

    We consider a 1-D model for the simulation of the blood flow in the cardiovascular system. As inflow condition we consider a model for the aortic valve. The opening and closing of the valve is dynamically determined by the pressure difference between the left ventricular and aortic pressures. At the outflow we impose a peripheral resistance model. To approximate the solution we use a numerical scheme based on the discontinuous Galerkin method. We also considering a variation in heart rate and terminal reflection coefficient due to monitoring of the pressure in the network.

  20. Structure formation in active networks

    CERN Document Server

    Köhler, Simone; Bausch, Andreas R

    2011-01-01

    Structure formation and constant reorganization of the actin cytoskeleton are key requirements for the function of living cells. Here we show that a minimal reconstituted system consisting of actin filaments, crosslinking molecules and molecular-motor filaments exhibits a generic mechanism of structure formation, characterized by a broad distribution of cluster sizes. We demonstrate that the growth of the structures depends on the intricate balance between crosslinker-induced stabilization and simultaneous destabilization by molecular motors, a mechanism analogous to nucleation and growth in passive systems. We also show that the intricate interplay between force generation, coarsening and connectivity is responsible for the highly dynamic process of structure formation in this heterogeneous active gel, and that these competing mechanisms result in anomalous transport, reminiscent of intracellular dynamics.

  1. Modulation of neuronal network activity with ghrelin

    NARCIS (Netherlands)

    Stoyanova, Irina; Rutten, Wim; le Feber, Jakob

    2012-01-01

    Ghrelin is a neuropeptide regulating multiple physiological processes, including high brain functions such as learning and memory formation. However, the effect of ghrelin on network activity patterns and developments has not been studied yet. Therefore, we used dissociated cortical neurons plated

  2. Discrete rate and variable power adaptation for underlay cognitive networks

    KAUST Repository

    Abdallah, Mohamed M.

    2010-01-01

    We consider the problem of maximizing the average spectral efficiency of a secondary link in underlay cognitive networks. In particular, we consider the network setting whereby the secondary transmitter employs discrete rate and variable power adaptation under the constraints of maximum average transmit power and maximum average interference power allowed at the primary receiver due to the existence of an interference link between the secondary transmitter and the primary receiver. We first find the optimal discrete rates assuming a predetermined partitioning of the signal-to-noise ratio (SNR) of both the secondary and interference links. We then present an iterative algorithm for finding a suboptimal partitioning of the SNR of the interference link assuming a fixed partitioning of the SNR of secondary link selected for the case where no interference link exists. Our numerical results show that the average spectral efficiency attained by using the iterative algorithm is close to that achieved by the computationally extensive exhaustive search method for the case of Rayleigh fading channels. In addition, our simulations show that selecting the optimal partitioning of the SNR of the secondary link assuming no interference link exists still achieves the maximum average spectral efficiency for the case where the average interference constraint is considered. © 2010 IEEE.

  3. Activity Recognition Using Complex Network Analysis.

    Science.gov (United States)

    Jalloul, Nahed; Poree, Fabienne; Viardot, Geoffrey; L'Hostis, Phillipe; Carrault, Guy

    2017-10-12

    In this paper, we perform complex network analysis on a connectivity dataset retrieved from a monitoring system in order to classify simple daily activities. The monitoring system is composed of a set of wearable sensing modules positioned on the subject's body and the connectivity data consists of the correlation between each pair of modules. A number of network measures are then computed followed by the application of statistical significance and feature selection methods. These methods were implemented for the purpose of reducing the total number of modules in the monitoring system required to provide accurate activity classification. The obtained results show that an overall accuracy of 84.6% for activity classification is achieved, using a Random Forest (RF) classifier, and when considering a monitoring system composed of only two modules positioned at the Neck and Thigh of the subject's body.

  4. Collective dynamics of active cytoskeletal networks

    CERN Document Server

    Köhler, Simone; Bausch, Andreas R

    2011-01-01

    Self organization mechanisms are essential for the cytoskeleton to adapt to the requirements of living cells. They rely on the intricate interplay of cytoskeletal filaments, crosslinking proteins and molecular motors. Here we present an in vitro minimal model system consisting of actin filaments, fascin and myosin-II filaments exhibiting pulsative collective long range dynamics. The reorganizations in the highly dynamic steady state of the active gel are characterized by alternating periods of runs and stalls resulting in a superdiffusive dynamics of the network's constituents. They are dominated by the complex competition of crosslinking molecules and motor filaments in the network: Collective dynamics are only observed if the relative strength of the binding of myosin-II filaments to the actin network allows exerting high enough forces to unbind actin/fascin crosslinks. The feedback between structure formation and dynamics can be resolved by combining these experiments with phenomenological simulations base...

  5. Networking activities in technology-based entrepreneurial teams

    DEFF Research Database (Denmark)

    Neergaard, Helle

    2005-01-01

    Based on social network theoy, this article investigates the distribution of networking roles and responsibilities in entrepreneurial founding teams. Its focus is on the team as a collection of individuals, thus allowing the research to address differences in networking patterns. It identifies six...... central networking activities and shows that not all founding team members are equally active 'networkers'. The analyses show that team members prioritize different networking activities and that one member in particular has extensive networking activities whereas other memebrs of the team are more...

  6. Intruder Activity Analysis under Unreliable Sensor Networks

    Energy Technology Data Exchange (ETDEWEB)

    Tae-Sic Yoo; Humberto E. Garcia

    2007-09-01

    This paper addresses the problem of counting intruder activities within a monitored domain by a sensor network. The deployed sensors are unreliable. We characterize imperfect sensors with misdetection and false-alarm probabilities. We model intruder activities with Markov Chains. A set of Hidden Markov Models (HMM) models the imperfect sensors and intruder activities to be monitored. A novel sequential change detection/isolation algorithm is developed to detect and isolate a change from an HMM representing no intruder activity to another HMM representing some intruder activities. Procedures for estimating the entry time and the trace of intruder activities are developed. A domain monitoring example is given to illustrate the presented concepts and computational procedures.

  7. Practical Rate-Based Congestion Control for Wireless Mesh Networks

    Science.gov (United States)

    Elrakabawy, Sherif M.; Lindemann, Christoph

    We introduce an adaptive pacing scheme to overcome the drawbacks of TCP in wireless mesh networks with Internet connectivity. The pacing scheme is implemented at the wireless TCP sender as well as at the mesh gateway, and reacts according to the direction of TCP flows running across the wireless network and the Internet. TCP packets are transmitted rate-based within the TCP congestion window according to the current out-of-interference delay and the coefficient of variation of recently measured round-trip times. Opposed to the majority of previous work which builds on simulations, we implement a Linux prototype of our approach and evaluate its feasibility in a real 20-node mesh testbed. In an experimental performance study, we compare the goodput and fairness of our approach against the widely deployed TCP NewReno. Experiments show that our approach, which we denote as Mesh Adaptive Pacing (MAP), can achieve up to 150% more goodput than TCP NewReno and significantly improves fairness between competing flows. MAP is incrementally deployable since it is TCP-compatible, does not require cross-layer information from intermediate nodes along the path, and requires no modifications in the wired domain.

  8. Transmission rate allocation in multisensor target tracking over a shared network.

    Science.gov (United States)

    Ranasingha, M Chamara; Murthi, Manohar N; Premaratne, Kamal; Fan, Xingzhe

    2009-04-01

    In a multisensor target tracking application running on a shared network, at what bit rates should the sensors send their measurements to the tracking fusion center? Clearly, the sensors cannot use arbitrary rates in a shared network, and a standard network rate control algorithm may not provide rates amenable to effective target tracking. For Kalman filter-based multisensor target tracking, we derive a utility function that captures the tracking quality of service as a function of the sensor bit rates. We incorporate this utility function into a network rate resource allocation framework, deriving a distributed rate control algorithm for a shared network that is suitable for current best effort packet networks, such as the Internet. In simulation studies, the new rate control algorithm engenders significantly better tracking performance than a standard rate control method, while the ordinary data transfer flows continue to effectively operate while using their standard rate control methods.

  9. Topological dimension tunes activity patterns in hierarchical modular networks

    Science.gov (United States)

    Safari, Ali; Moretti, Paolo; Muñoz, Miguel A.

    2017-11-01

    Connectivity patterns of relevance in neuroscience and systems biology can be encoded in hierarchical modular networks (HMNs). Recent studies highlight the role of hierarchical modular organization in shaping brain activity patterns, providing an excellent substrate to promote both segregation and integration of neural information. Here, we propose an extensive analysis of the critical spreading rate (or ‘epidemic’ threshold)—separating a phase with endemic persistent activity from one in which activity ceases—on diverse HMNs. By employing analytical and computational techniques we determine the nature of such a threshold and scrutinize how it depends on general structural features of the underlying HMN. We critically discuss the extent to which current graph-spectral methods can be applied to predict the onset of spreading in HMNs and, most importantly, we elucidate the role played by the network topological dimension as a relevant and unifying structural parameter, controlling the epidemic threshold.

  10. Hopfield neural network and optical fiber sensor as intelligent heart rate monitor

    Science.gov (United States)

    Mutter, Kussay Nugamesh

    2018-01-01

    This paper presents a design and fabrication of an intelligent fiber-optic sensor used for examining and monitoring heart rate activity. It is found in the literature that the use of fiber sensors as heart rate sensor is widely studied. However, the use of smart sensors based on Hopfield neural networks is very low. In this work, the sensor is a three fibers without cladding of about 1 cm, fed by laser light of 1550 nm of wavelength. The sensing portions are mounted with a micro sensitive diaphragm to transfer the pulse pressure on the left radial wrist. The influenced light intensity will be detected by a three photodetectors as inputs into the Hopfield neural network algorithm. The latter is a singlelayer auto-associative memory structure with a same input and output layers. The prior training weights are stored in the net memory for the standard recorded normal heart rate signals. The sensors' heads work on the reflection intensity basis. The novelty here is that the sensor uses a pulse pressure and Hopfield neural network in an integrity approach. The results showed a significant output measurements of heart rate and counting with a plausible error rate.

  11. Activating and inhibiting connections in biological network dynamics

    Directory of Open Access Journals (Sweden)

    Knight Rob

    2008-12-01

    Full Text Available Abstract Background Many studies of biochemical networks have analyzed network topology. Such work has suggested that specific types of network wiring may increase network robustness and therefore confer a selective advantage. However, knowledge of network topology does not allow one to predict network dynamical behavior – for example, whether deleting a protein from a signaling network would maintain the network's dynamical behavior, or induce oscillations or chaos. Results Here we report that the balance between activating and inhibiting connections is important in determining whether network dynamics reach steady state or oscillate. We use a simple dynamical model of a network of interacting genes or proteins. Using the model, we study random networks, networks selected for robust dynamics, and examples of biological network topologies. The fraction of activating connections influences whether the network dynamics reach steady state or oscillate. Conclusion The activating fraction may predispose a network to oscillate or reach steady state, and neutral evolution or selection of this parameter may affect the behavior of biological networks. This principle may unify the dynamics of a wide range of cellular networks. Reviewers Reviewed by Sergei Maslov, Eugene Koonin, and Yu (Brandon Xia (nominated by Mark Gerstein. For the full reviews, please go to the Reviewers' comments section.

  12. A Distributed Flow Rate Control Algorithm for Networked Agent System with Multiple Coding Rates to Optimize Multimedia Data Transmission

    Directory of Open Access Journals (Sweden)

    Shuai Zeng

    2013-01-01

    Full Text Available With the development of wireless technologies, mobile communication applies more and more extensively in the various walks of life. The social network of both fixed and mobile users can be seen as networked agent system. At present, kinds of devices and access network technology are widely used. Different users in this networked agent system may need different coding rates multimedia data due to their heterogeneous demand. This paper proposes a distributed flow rate control algorithm to optimize multimedia data transmission of the networked agent system with the coexisting various coding rates. In this proposed algorithm, transmission path and upload bandwidth of different coding rate data between source node, fixed and mobile nodes are appropriately arranged and controlled. On the one hand, this algorithm can provide user nodes with differentiated coding rate data and corresponding flow rate. On the other hand, it makes the different coding rate data and user nodes networked, which realizes the sharing of upload bandwidth of user nodes which require different coding rate data. The study conducts mathematical modeling on the proposed algorithm and compares the system that adopts the proposed algorithm with the existing system based on the simulation experiment and mathematical analysis. The results show that the system that adopts the proposed algorithm achieves higher upload bandwidth utilization of user nodes and lower upload bandwidth consumption of source node.

  13. Partner network communities – a resource of universities’ activities

    Directory of Open Access Journals (Sweden)

    Romm Mark V.

    2016-01-01

    Full Text Available The network activity is not only part and parcel of the modern university, but it also demonstrates the level of its success. There appeared an urgent need for understanding the nature of universities’ network interactions and finding the most effective models of their network cooperation. The article analyzes partnership network communities with higher educational establishments (universities’ participation, which are being actively created nowadays. The conditions for successful network activities of a university in scientific, academic and professional network communities are presented.

  14. Improvement of the Measure of the Network Survival Rate and its Application to a Japanese Business Relations Network

    Science.gov (United States)

    Kawamoto, Hirokazu; Takayasu, Hideki; Takayasu, Misako

    We analyze the typical characteristics of the percolation transition of a large-scale complex network, a Japanese business relation network consisting of approximately 600,000 nodes and 4,000,000 links. By utilizing percolation characteristics, we revise the definition of network survival rate that we previously proposed. The new network survival rate has a strong correlation with the old one. The calculation cost is also much smaller and the number of trials decreases from 100,000 to 1,000. Finally, we discuss the identification of robust and fragile regions using this index.

  15. Bringing metabolic networks to life: convenience rate law and thermodynamic constraints

    Directory of Open Access Journals (Sweden)

    Klipp Edda

    2006-12-01

    Full Text Available Abstract Background Translating a known metabolic network into a dynamic model requires rate laws for all chemical reactions. The mathematical expressions depend on the underlying enzymatic mechanism; they can become quite involved and may contain a large number of parameters. Rate laws and enzyme parameters are still unknown for most enzymes. Results We introduce a simple and general rate law called "convenience kinetics". It can be derived from a simple random-order enzyme mechanism. Thermodynamic laws can impose dependencies on the kinetic parameters. Hence, to facilitate model fitting and parameter optimisation for large networks, we introduce thermodynamically independent system parameters: their values can be varied independently, without violating thermodynamical constraints. We achieve this by expressing the equilibrium constants either by Gibbs free energies of formation or by a set of independent equilibrium constants. The remaining system parameters are mean turnover rates, generalised Michaelis-Menten constants, and constants for inhibition and activation. All parameters correspond to molecular energies, for instance, binding energies between reactants and enzyme. Conclusion Convenience kinetics can be used to translate a biochemical network – manually or automatically - into a dynamical model with plausible biological properties. It implements enzyme saturation and regulation by activators and inhibitors, covers all possible reaction stoichiometries, and can be specified by a small number of parameters. Its mathematical form makes it especially suitable for parameter estimation and optimisation. Parameter estimates can be easily computed from a least-squares fit to Michaelis-Menten values, turnover rates, equilibrium constants, and other quantities that are routinely measured in enzyme assays and stored in kinetic databases.

  16. Supervised learning in a recurrent network of rate-model neurons exhibiting frequency adaptation.

    Science.gov (United States)

    Fortier, Pierre A; Guigon, Emmanuel; Burnod, Yves

    2005-09-01

    For gradient descent learning to yield connectivity consistent with real biological networks, the simulated neurons would have to include more realistic intrinsic properties such as frequency adaptation. However, gradient descent learning cannot be used straightforwardly with adapting rate-model neurons because the derivative of the activation function depends on the activation history. The objectives of this study were to (1) develop a simple computational approach to reproduce mathematical gradient descent and (2) use this computational approach to provide supervised learning in a network formed of rate-model neurons that exhibit frequency adaptation. The results of mathematical gradient descent were used as a reference in evaluating the performance of the computational approach. For this comparison, standard (nonadapting) rate-model neurons were used for both approaches. The only difference was the gradient calculation: the mathematical approach used the derivative at a point in weight space, while the computational approach used the slope for a step change in weight space. Theoretically, the results of the computational approach should match those of the mathematical approach, as the step size is reduced but floating-point accuracy formed a lower limit to usable step sizes. A systematic search for an optimal step size yielded a computational approach that faithfully reproduced the results of mathematical gradient descent. The computational approach was then used for supervised learning of both connection weights and intrinsic properties of rate-model neurons to convert a tonic input into a phasic-tonic output pattern. Learning produced biologically realistic connectivity that essentially used a monosynaptic connection from the tonic input neuron to an output neuron with strong frequency adaptation as compared to a complex network when using nonadapting neurons. Thus, more biologically realistic connectivity was achieved by implementing rate-model neurons with

  17. Application of Neural Networks to House Pricing and Bond Rating

    NARCIS (Netherlands)

    Daniëls, H.A.M.; Kamp, B.; Verkooijen, W.J.H.

    1997-01-01

    Feed forward neural networks receive a growing attention as a data modelling tool in economic classification problems. It is well-known that controlling the design of a neural network can be cumbersome. Inaccuracies may lead to a manifold of problems in the application such as higher errors due to

  18. Circumpolar Active Layer Monitoring (CALM) Program Network, Version 1

    Data.gov (United States)

    National Aeronautics and Space Administration — The CALM network includes 168 active sites in both hemispheres with 15 participating countries. This network represents the only coordinated and standardized program...

  19. Social networks: Networking of social actors in the sphere of economic activities

    OpenAIRE

    Babović Marija

    2005-01-01

    The article reviews one of the important fields of study in contemporary economic sociology - social networks in the sphere of economic activities. Besides basic theoretical and methodological conceptions in studying social networks that originate from general sociology and special sociological disciplines most important fields of study of social networks in economic sociology are presented. Some influential studies of social networks are analyzed; some key weaknesses of social network approa...

  20. Using Active Networking to Detect and Troubleshoot Issues in Tactical Data Networks

    Science.gov (United States)

    2014-06-01

    team SDN software defined networking SIPRnet Secret Internet Protocol Router Network SSH secure shell xiv SVG Scalable Vector Graphics SNMP Simple...networking ( SDN ) paradigm, which has gained popularity in recent years, has its roots in the idea of programmable networks [6]. By extending the...addressed by SDN [6]. While there are simi- larities between SDN and active networking, SDN is primarily concerned with the idea of separating the control

  1. Measurement of switching latency in high data rate Ethernet networks

    OpenAIRE

    Hegr, Tomáš; Vozňák, Miroslav; Kozák, Miloš; Boháč, Leoš

    2015-01-01

    The paper deals with a methodology of switching latency measurement in switched Ethernet networks. The switching latency is parameter necessary for simulation and design of low-latency networks that are often intended for realtime control inherent to many industrial applications. The proposed measurement methodology provides a simple way of switching the latency determination and vendor quoted latency values verification directly at the physical layer. Numerous experimental measurements...

  2. Decreasing-Rate Pruning Optimizes the Construction of Efficient and Robust Distributed Networks.

    Directory of Open Access Journals (Sweden)

    Saket Navlakha

    2015-07-01

    Full Text Available Robust, efficient, and low-cost networks are advantageous in both biological and engineered systems. During neural network development in the brain, synapses are massively over-produced and then pruned-back over time. This strategy is not commonly used when designing engineered networks, since adding connections that will soon be removed is considered wasteful. Here, we show that for large distributed routing networks, network function is markedly enhanced by hyper-connectivity followed by aggressive pruning and that the global rate of pruning, a developmental parameter not previously studied by experimentalists, plays a critical role in optimizing network structure. We first used high-throughput image analysis techniques to quantify the rate of pruning in the mammalian neocortex across a broad developmental time window and found that the rate is decreasing over time. Based on these results, we analyzed a model of computational routing networks and show using both theoretical analysis and simulations that decreasing rates lead to more robust and efficient networks compared to other rates. We also present an application of this strategy to improve the distributed design of airline networks. Thus, inspiration from neural network formation suggests effective ways to design distributed networks across several domains.

  3. Optimal downlink rate allocation in multicell CDMA networks

    NARCIS (Netherlands)

    Endrayanto, A.I.; Gabor, A.F.; Boucherie, Richardus J.

    2007-01-01

    We study downlink rate allocation for a three cells CDMA system. Based on the discretized cell model, the rate optimization problem that maximizes the total downlink rate allocation is formulated. We propose an approximation procedure for obtaining a rate allocation in three cells case. Via

  4. Application of time-hopping UWB range-bit rate performance in the UWB sensor networks

    NARCIS (Netherlands)

    Nascimento, J.R.V. do; Nikookar, H.

    2008-01-01

    In this paper, the achievable range-bit rate performance is evaluated for Time-Hopping (TH) UWB networks complying with the FCC outdoor emission limits in the presence of Multiple Access Interference (MAI). Application of TH-UWB range-bit rate performance is presented for UWB sensor networks.

  5. Linking Environmental Orientation to Start-ups’ Networking Activities

    DEFF Research Database (Denmark)

    Dickel, Petra; Ritter, Thomas

    generation as their primary focus. Addressing this research gap, we develop hypotheses on the different networking activities of environmentally oriented start-ups arguing that their societal focus has a positive impact on the frequency of their networking and the size of their network. For empirically...... investigating such networking differences, we use data from 179 technology-based start-ups and show that start-ups with a strong external environmental orientation have significantly higher networking frequency and build larger networks. On the contrary, strong internal environmental orientation is linked...

  6. False Positive STEMI Activations in a Regional Network: Comprehensive Analysis and Clinical Impact. Results From the Catalonian Codi Infart Network.

    Science.gov (United States)

    Regueiro, Ander; Fernández-Rodríguez, Diego; Freixa, Xavier; Bosch, Xavier; Martín-Yuste, Victoria; Brugaletta, Salvatore; Roqué, Mercè; Sabaté, Manel; Masotti, Mónica

    2017-07-12

    ST-segment elevation myocardial infarction (STEMI) network activation by a noncardiologist reduces delay times but may increase the rate of false-positive STEMI diagnoses. We aimed to determine the prevalence, predictors, and clinical impact of false-positive activations within the Catalonian STEMI network (Codi Infart). From January 2010 through December 2011, all consecutive patients treated within the Codi Infart network were included. Code activations were classified as appropriate if they satisfied both electrocardiogram and clinical STEMI criteria. Appropriate activations were classified as false positives using 2 nonexclusive definitions: a) "angiographic" if a culprit coronary artery was not identified, and b) "clinical" if the discharge diagnosis was other than STEMI. In total, 5701 activations were included. Appropriate activation was performed in 87.8% of the episodes. The rate of angiographic false positives was 14.6%, while the rate of clinical false positives was 11.6%. Irrespective of the definition, female sex, left bundle branch block, and previous myocardial infarction were independent predictors of false-positive STEMI diagnoses. Using the clinical definition, hospitals without percutaneous coronary intervention and patients with complications during the first medical contact also had a false-positive STEMI diagnoses rate higher than the mean. In-hospital and 30-day mortality rates were similar for false-positive and true-positive STEMI patients after adjustment for possible confounders. False-positive STEMI diagnoses were frequent. Outcomes were similar for patients with a true-positive or false-positive STEMI diagnosis treated within a STEMI network. The presence of any modifiable predictors of a false-positive STEMI diagnosis warrants careful assessment to optimize the use of STEMI networks. Copyright © 2017 Sociedad Española de Cardiología. Published by Elsevier España, S.L.U. All rights reserved.

  7. Network Patch Cables Demystified: A Super Activity for Computer Networking Technology

    Science.gov (United States)

    Brown, Douglas L.

    2004-01-01

    This article de-mystifies network patch cable secrets so that people can connect their computers and transfer those pesky files--without screaming at the cables. It describes a network cabling activity that can offer students a great hands-on opportunity for working with the tools, techniques, and media used in computer networking. Since the…

  8. Resource Discovery in Activity-Based Sensor Networks

    DEFF Research Database (Denmark)

    Bucur, Doina; Bardram, Jakob

    This paper proposes a service discovery protocol for sensor networks that is specifically tailored for use in humancentered pervasive environments. It uses the high-level concept of computational activities (as logical bundles of data and resources) to give sensors in Activity-Based Sensor Networks...... (ABSNs) knowledge about their usage even at the network layer. ABSN redesigns classical network-level service discovery protocols to include and use this logical structuring of the network for a more practically applicable service discovery scheme. Noting that in practical settings activity-based sensor...... patches are localized, ABSN designs a completely distributed, hybrid discovery protocol which is proactive in a neighbourhood zone and reactive outside, tailored so that any query among the sensors of one activity is routed through the network with minimum overhead, guided by the bounds of that activity...

  9. Random walks on activity-driven networks with attractiveness

    Science.gov (United States)

    Alessandretti, Laura; Sun, Kaiyuan; Baronchelli, Andrea; Perra, Nicola

    2017-05-01

    Virtually all real-world networks are dynamical entities. In social networks, the propensity of nodes to engage in social interactions (activity) and their chances to be selected by active nodes (attractiveness) are heterogeneously distributed. Here, we present a time-varying network model where each node and the dynamical formation of ties are characterized by these two features. We study how these properties affect random-walk processes unfolding on the network when the time scales describing the process and the network evolution are comparable. We derive analytical solutions for the stationary state and the mean first-passage time of the process, and we study cases informed by empirical observations of social networks. Our work shows that previously disregarded properties of real social systems, such as heterogeneous distributions of activity and attractiveness as well as the correlations between them, substantially affect the dynamical process unfolding on the network.

  10. Recovery Act: Energy Efficiency of Data Networks through Rate Adaptation (EEDNRA) - Final Technical Report

    Energy Technology Data Exchange (ETDEWEB)

    Matthew Andrews; Spyridon Antonakopoulos; Steve Fortune; Andrea Francini; Lisa Zhang

    2011-07-12

    This Concept Definition Study focused on developing a scientific understanding of methods to reduce energy consumption in data networks using rate adaptation. Rate adaptation is a collection of techniques that reduce energy consumption when traffic is light, and only require full energy when traffic is at full provisioned capacity. Rate adaptation is a very promising technique for saving energy: modern data networks are typically operated at average rates well below capacity, but network equipment has not yet been designed to incorporate rate adaptation. The Study concerns packet-switching equipment, routers and switches; such equipment forms the backbone of the modern Internet. The focus of the study is on algorithms and protocols that can be implemented in software or firmware to exploit hardware power-control mechanisms. Hardware power-control mechanisms are widely used in the computer industry, and are beginning to be available for networking equipment as well. Network equipment has different performance requirements than computer equipment because of the very fast rate of packet arrival; hence novel power-control algorithms are required for networking. This study resulted in five published papers, one internal report, and two patent applications, documented below. The specific technical accomplishments are the following: • A model for the power consumption of switching equipment used in service-provider telecommunication networks as a function of operating state, and measured power-consumption values for typical current equipment. • An algorithm for use in a router that adapts packet processing rate and hence power consumption to traffic load while maintaining performance guarantees on delay and throughput. • An algorithm that performs network-wide traffic routing with the objective of minimizing energy consumption, assuming that routers have less-than-ideal rate adaptivity. • An estimate of the potential energy savings in service-provider networks

  11. Evaluating Maximum Wind Energy Exploitation in Active Distribution Networks

    DEFF Research Database (Denmark)

    Siano, Pierluigi; Chen, Peiyuan; Chen, Zhe

    2010-01-01

    The increased spreading of distributed and renewable generation requires moving towards active management of distribution networks. In this paper, in order to evaluate maximum wind energy exploitation in active distribution networks, a method based on a multi-period optimal power flow (OPF...

  12. Topological evolution of virtual social networks by modeling social activities

    Science.gov (United States)

    Sun, Xin; Dong, Junyu; Tang, Ruichun; Xu, Mantao; Qi, Lin; Cai, Yang

    2015-09-01

    With the development of Internet and wireless communication, virtual social networks are becoming increasingly important in the formation of nowadays' social communities. Topological evolution model is foundational and critical for social network related researches. Up to present most of the related research experiments are carried out on artificial networks, however, a study of incorporating the actual social activities into the network topology model is ignored. This paper first formalizes two mathematical abstract concepts of hobbies search and friend recommendation to model the social actions people exhibit. Then a social activities based topology evolution simulation model is developed to satisfy some well-known properties that have been discovered in real-world social networks. Empirical results show that the proposed topology evolution model has embraced several key network topological properties of concern, which can be envisioned as signatures of real social networks.

  13. Sensitivity of the active fracture model parameter to fracture network orientation and injection scenarios

    Science.gov (United States)

    Başağaoğlu, Hakan; Succi, Sauro; Manepally, Chandrika; Fedors, Randall; Wyrick, Danielle Y.

    2009-09-01

    Active fractures refer to the portions of unsaturated, connected fractures that actively conduct water. The active fracture model parameter accounts for the reduction in the number of fractures carrying water and in the fracture-matrix interface area in field-scale simulations of flow and transport in unsaturated fractured rocks. One example includes the numerical analyses of the fault test results at the Yucca Mountain site, Nevada (USA). In such applications, the active fracture model parameter is commonly used as a calibration parameter without relating it to fracture network orientations and infiltration rates. A two-dimensional, multiphase lattice-Boltzmann model was used in this study to investigate the sensitivity of the active fracture model parameter to fracture network orientation and injection scenarios for an unsaturated, variable dipping, and geometrically simple fracture network. The active fracture model parameter differed by as much as 0.11-0.44 when the effects of fracture network orientation, injection rate, and injection mode were included in the simulations. Hence, the numerical results suggest that the sensitivity of the active fracture model parameter to fracture network orientation, injection rates, and injection modes should be explored at the field-scale to strengthen the technical basis and range of applicability of the active fracture model.

  14. Brain network activity in monolingual and bilingual older adults.

    Science.gov (United States)

    Grady, Cheryl L; Luk, Gigi; Craik, Fergus I M; Bialystok, Ellen

    2015-01-01

    Bilingual older adults typically have better performance on tasks of executive control (EC) than do their monolingual peers, but differences in brain activity due to language experience are not well understood. Based on studies showing a relation between the dynamic range of brain network activity and performance on EC tasks, we hypothesized that life-long bilingual older adults would show increased functional connectivity relative to monolinguals in networks related to EC. We assessed intrinsic functional connectivity and modulation of activity in task vs. fixation periods in two brain networks that are active when EC is engaged, the frontoparietal control network (FPC) and the salience network (SLN). We also examined the default mode network (DMN), which influences behavior through reduced activity during tasks. We found stronger intrinsic functional connectivity in the FPC and DMN in bilinguals than in monolinguals. Although there were no group differences in the modulation of activity across tasks and fixation, bilinguals showed stronger correlations than monolinguals between intrinsic connectivity in the FPC and task-related increases of activity in prefrontal and parietal regions. This bilingual difference in network connectivity suggests that language experience begun in childhood and continued throughout adulthood influences brain networks in ways that may provide benefits in later life. Copyright © 2014 Elsevier Ltd. All rights reserved.

  15. Rate adaptation in ad hoc networks based on pricing

    CSIR Research Space (South Africa)

    Awuor, F

    2011-09-01

    Full Text Available that incorporates penalty (pricing) obtruded to users’ choices of transmission parameters to curb the self-interest behaviour. Therefore users determine their data rates and transmit power based on the perceived coupled interference at the intended receiver...

  16. The salience network causally influences default mode network activity during moral reasoning

    Science.gov (United States)

    Wilson, Stephen M.; D’Esposito, Mark; Kayser, Andrew S.; Grossman, Scott N.; Poorzand, Pardis; Seeley, William W.; Miller, Bruce L.; Rankin, Katherine P.

    2013-01-01

    Large-scale brain networks are integral to the coordination of human behaviour, and their anatomy provides insights into the clinical presentation and progression of neurodegenerative illnesses such as Alzheimer’s disease, which targets the default mode network, and behavioural variant frontotemporal dementia, which targets a more anterior salience network. Although the default mode network is recruited when healthy subjects deliberate about ‘personal’ moral dilemmas, patients with Alzheimer’s disease give normal responses to these dilemmas whereas patients with behavioural variant frontotemporal dementia give abnormal responses to these dilemmas. We hypothesized that this apparent discrepancy between activation- and patient-based studies of moral reasoning might reflect a modulatory role for the salience network in regulating default mode network activation. Using functional magnetic resonance imaging to characterize network activity of patients with behavioural variant frontotemporal dementia and healthy control subjects, we present four converging lines of evidence supporting a causal influence from the salience network to the default mode network during moral reasoning. First, as previously reported, the default mode network is recruited when healthy subjects deliberate about ‘personal’ moral dilemmas, but patients with behavioural variant frontotemporal dementia producing atrophy in the salience network give abnormally utilitarian responses to these dilemmas. Second, patients with behavioural variant frontotemporal dementia have reduced recruitment of the default mode network compared with healthy control subjects when deliberating about these dilemmas. Third, a Granger causality analysis of functional neuroimaging data from healthy control subjects demonstrates directed functional connectivity from nodes of the salience network to nodes of the default mode network during moral reasoning. Fourth, this Granger causal influence is diminished in

  17. Topic-oriented community detection of rating-based social networks

    Directory of Open Access Journals (Sweden)

    Ali Reihanian

    2016-07-01

    Full Text Available Nowadays, real world social networks contain a vast range of information including shared objects, comments, following information, etc. Finding meaningful communities in this kind of networks is an interesting research area and has attracted the attention of many researchers. The community structure of complex networks reveals both their organization and hidden relations among their constituents. Most of the researches in the field of community detection mainly focus on the topological structure of the network without performing any content analysis. In recent years, a number of researches have proposed approaches which consider both the contents that are interchanged in networks, and the topological structures of the networks in order to find more meaningful communities. In this research, the effect of topic analysis in finding more meaningful communities in social networking sites in which the users express their feelings toward different objects (like movies by means of rating is demonstrated by performing extensive experiments.

  18. A user oriented active network simulator

    Science.gov (United States)

    Rao, K. S.; Swamy, M. N. S.

    1980-07-01

    A digital computer simulator for the frequency response and tolerance analysis of an electrical network comprising RLCM elements, ideal operational amplifiers and controlled sources is presented in this tutorial paper. The simulator is based on 'tableau approach'. Reordering of the sparse tableau matrix is done using Markowitz Criterion and the diagonal pivots are chosen for simplicity. The simulator also employs dynamic allocation for maximum utilization of memory and faster turn around time. Three networks are simulated and their results are presented in this paper. A network in which the operational amplifiers are assumed to have single pole behaviour is also analyzed.

  19. Mesoscale Architecture Shapes Initiation and Richness of Spontaneous Network Activity.

    Science.gov (United States)

    Okujeni, Samora; Kandler, Steffen; Egert, Ulrich

    2017-04-05

    Spontaneous activity in the absence of external input, including propagating waves of activity, is a robust feature of neuronal networks in vivo and in vitro The neurophysiological and anatomical requirements for initiation and persistence of such activity, however, are poorly understood, as is their role in the function of neuronal networks. Computational network studies indicate that clustered connectivity may foster the generation, maintenance, and richness of spontaneous activity. Since this mesoscale architecture cannot be systematically modified in intact tissue, testing these predictions is impracticable in vivo Here, we investigate how the mesoscale structure shapes spontaneous activity in generic networks of rat cortical neurons in vitro In these networks, neurons spontaneously arrange into local clusters with high neurite density and form fasciculating long-range axons. We modified this structure by modulation of protein kinase C, an enzyme regulating neurite growth and cell migration. Inhibition of protein kinase C reduced neuronal aggregation and fasciculation of axons, i.e., promoted uniform architecture. Conversely, activation of protein kinase C promoted aggregation of neurons into clusters, local connectivity, and bundling of long-range axons. Supporting predictions from theory, clustered networks were more spontaneously active and generated diverse activity patterns. Neurons within clusters received stronger synaptic inputs and displayed increased membrane potential fluctuations. Intensified clustering promoted the initiation of synchronous bursting events but entailed incomplete network recruitment. Moderately clustered networks appear optimal for initiation and propagation of diverse patterns of activity. Our findings support a crucial role of the mesoscale architectures in the regulation of spontaneous activity dynamics. SIGNIFICANCE STATEMENT Computational studies predict richer and persisting spatiotemporal patterns of spontaneous activity in

  20. Assessing state-level active living promotion using network analysis.

    Science.gov (United States)

    Buchthal, Opal Vanessa; Taniguchi, Nicole; Iskandar, Livia; Maddock, Jay

    2013-01-01

    Physical inactivity is a growing problem in the United States, one that is being addressed through the development of active living communities. However, active living promotion requires collaboration among organizations that may not have previously shared goals. A network analysis was conducted to assess Hawaii's active living promotion network. Twenty-six organizations playing a significant role in promoting active living in Hawaii were identified and surveyed about their frequency of contact, level of collaboration, and funding flow with other agencies. A communication network was identified linking all agencies. This network had many long pathways, impeding information flow. The Department of Health (DOH) and the State Nutrition and Physical Activity Coalition (NPAC) were central nodes, but DOH connected state agencies while NPAC linked county and voluntary organizations. Within the network, information sharing was common, but collaboration and formal partnership were low. Linkages between county and state agencies, between counties, and between state agencies with different core agendas were particularly low. Results suggest that in the early stages of development, active living networks may be divided by geography and core missions, requiring work to bridge these divides. Network mapping appears helpful in identifying areas for network development.

  1. Dynamic Control of Synchronous Activity in Networks of Spiking Neurons.

    Directory of Open Access Journals (Sweden)

    Axel Hutt

    Full Text Available Oscillatory brain activity is believed to play a central role in neural coding. Accumulating evidence shows that features of these oscillations are highly dynamic: power, frequency and phase fluctuate alongside changes in behavior and task demands. The role and mechanism supporting this variability is however poorly understood. We here analyze a network of recurrently connected spiking neurons with time delay displaying stable synchronous dynamics. Using mean-field and stability analyses, we investigate the influence of dynamic inputs on the frequency of firing rate oscillations. We show that afferent noise, mimicking inputs to the neurons, causes smoothing of the system's response function, displacing equilibria and altering the stability of oscillatory states. Our analysis further shows that these noise-induced changes cause a shift of the peak frequency of synchronous oscillations that scales with input intensity, leading the network towards critical states. We lastly discuss the extension of these principles to periodic stimulation, in which externally applied driving signals can trigger analogous phenomena. Our results reveal one possible mechanism involved in shaping oscillatory activity in the brain and associated control principles.

  2. Near cost-optimal inventory control policies for divergent networks under fill rate constraints

    NARCIS (Netherlands)

    van der Heijden, Matthijs C.

    2000-01-01

    We deal with the optimisation of stock levels in general divergent networks under a periodic review, order-up-to (R, S) policy. The goal is to attain target fill rates, while the total holding costs in the entire network are minimised. To this end, we first present a method for the fast calculation

  3. The association between social networks and self-rated risk of HIV ...

    African Journals Online (AJOL)

    Elizabeth J. Lyimo

    2014-03-18

    Mar 18, 2014 ... Participation in bridging networks was greater among females (25%) than males (12%, p , .005). Of ... association between bonding and bridging social networks on self-rated risk of HIV among study participants. However, sexually .... the social ecological model (SEM) described by Bronfenbrenner (1994).

  4. Creative elements: network-based predictions of active centres in proteins, cellular and social networks

    CERN Document Server

    Csermely, Peter

    2008-01-01

    Active centres and hot spots of proteins have a paramount importance in enzyme action, protein complex formation and drug design. Recently a number of publications successfully applied the analysis of residue networks to predict active centres in proteins. Most real-world networks show a number of properties, such as small-worldness or scale-free degree distribution, which are rather general features of networks from molecules to the society. Based on extensive analogies I propose that the existing findings and methodology enable us to detect active centres in cells, social networks and ecosystems. Members of these active centres are creative elements of the respective networks, which may help them to survive unprecedented, novel challenges, and play a key role in the development, survival and evolvability of complex systems.

  5. Social network analysis of childhood and youth physical activity: a systematic review.

    Science.gov (United States)

    Macdonald-Wallis, Kyle; Jago, Russell; Sterne, Jonathan A C

    2012-12-01

    Social network analysis has been used to better understand the influence of friends and peer groups in a wide range of health behaviors. This systematic review synthesizes findings from various social network analyses of child and adolescent physical activity, to determine the extent to which social network structure is associated with physical activity behaviors. Medical and social science databases were searched and screened between September and November 2011. Eligible studies collected a measure of physical activity and a measure of an individual's social network, either through friendship nominations or social ratings, and reported analyses investigating the association between physical activity and the social network measure. A total of 1767 articles yielded nine publications from seven eligible studies, which were synthesized and analyzed in December 2011. Three research themes were identified: (1) friendship similarities in physical activity; (2) peer group influences on physical activity; and (3) social preference (i.e., popularity) and physical activity. Synthesis of findings across studies found strong evidence for similarities in physical activity levels between an individual and their friends and within peer groups. There was mixed evidence for an association between social preference and physical activity levels. Friendship plays an important role in shaping physical activity behaviors. Physical activity interventions targeted at peer groups and that account for the influence of friendship groups might have utility as a means of increasing youth physical activity. Copyright © 2012 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.

  6. Simulating activation propagation in social networks using the graph theory

    Directory of Open Access Journals (Sweden)

    František Dařena

    2010-01-01

    Full Text Available The social-network formation and analysis is nowadays one of objects that are in a focus of intensive research. The objective of the paper is to suggest the perspective of representing social networks as graphs, with the application of the graph theory to problems connected with studying the network-like structures and to study spreading activation algorithm for reasons of analyzing these structures. The paper presents the process of modeling multidimensional networks by means of directed graphs with several characteristics. The paper also demonstrates using Spreading Activation algorithm as a good method for analyzing multidimensional network with the main focus on recommender systems. The experiments showed that the choice of parameters of the algorithm is crucial, that some kind of constraint should be included and that the algorithm is able to provide a stable environment for simulations with networks.

  7. The Association Between Social Networks and Self-rated risk of HIV Infection among Secondary School Students in Moshi Municipality, Tanzania.

    OpenAIRE

    Lyimo, EJ; Todd, J.; Richey, LA; B. Njau

    2014-01-01

    Abstract This study describes the social networks of secondary school students in Moshi Municipality, and their association with self-rated risk of human immunodeficiency virus (HIV) infection. A cross-sectional analytical study was conducted among 300 students aged 15-24 years in 5 secondary schools in Moshi, Tanzania. Bonding networks were defined as social groupings of students participating in activities within the school, while bridging networks were groups that included students partici...

  8. The Contagion Effects of Repeated Activation in Social Networks

    OpenAIRE

    Piedrahita, Pablo; Borge-Holthoefer, Javier; Moreno, Yamir; González-Bailón, Sandra

    2017-01-01

    Demonstrations, protests, riots, and shifts in public opinion respond to the coordinating potential of communication networks. Digital technologies have turned interpersonal networks into massive, pervasive structures that constantly pulsate with information. Here, we propose a model that aims to analyze the contagion dynamics that emerge in networks when repeated activation is allowed, that is, when actors can engage recurrently in a collective effort. We analyze how the structure of communi...

  9. Time-delay polynomial networks and rates of approximation

    Directory of Open Access Journals (Sweden)

    Irwin W. Sandberg

    1998-01-01

    Full Text Available We consider a large family of finite memory causal time-invariant maps G from an input set S to a set of ℝ-valued functions, with the members of both sets of functions defined on the nonnegative integers, and we give an upper bound on the error in approximating a G using a two-stage structure consisting of a tapped delay line and a static polynomial network N . This upper bound depends on the degree of the multivariable polynomial that characterizes N. Also given is a lower bound on the worst-case error in approximating a G using polynomials of a fixed maximum degree. These upper and lower bounds differ only by a multiplicative constant. We also give a corresponding result for the approximation of not-necessarily-causal input–output maps with inputs and outputs that may depend on more than one variable. This result is of interest, for example, in connection with image processing.

  10. Recognizing Multi-user Activities using Body Sensor Networks

    DEFF Research Database (Denmark)

    Gu, Tao; Wang, Liang; Chen, Hanhua

    2011-01-01

    activity classes of data—for building activity models and design a scalable, noise-resistant, Emerging Pattern based Multi-user Activity Recognizer (epMAR) to recognize both single- and multi-user activities. We develop a multi-modal, wireless body sensor network for collecting real-world traces in a smart...

  11. Detecting eavesdropping activity in fiber optic networks

    Science.gov (United States)

    MacDonald, Gregory G.

    The secure transmission of data is critical to governments, military organizations, financial institutions, health care providers and other enterprises. The primary method of securing in-transit data is though data encryption. A number of encryption methods exist but the fundamental approach is to assume an eavesdropper has access to the encrypted message but does not have the computing capability to decrypt the message in a timely fashion. Essentially, the strength of security depends on the complexity of the encryption method and the resources available to the eavesdropper. The development of future technologies, most notably quantum computers and quantum computing, is often cited as a direct threat to traditional encryption schemes. It seems reasonable that additional effort should be placed on prohibiting the eavesdropper from coming into possession of the encrypted message in the first place. One strategy for denying possession of the encrypted message is to secure the physical layer of the communications path. Because the majority of transmitted information is over fiber-optic networks, it seems appropriate to consider ways of enhancing the integrity and security of the fiber-based physical layer. The purpose of this research is to investigate the properties of light, as they are manifested in single mode fiber, as a means of insuring the integrity and security of the physical layer of a fiber-optic based communication link. Specifically, the approach focuses on the behavior of polarization in single mode fiber, as it is shown to be especially sensitive to fiber geometry. Fiber geometry is necessarily modified during the placement of optical taps. The problem of detecting activity associated with the placement of an optical tap is herein approached as a supervised machine learning anomaly identification task. The inputs include raw polarization measurements along with additional features derived from various visualizations of the raw data (the inputs are

  12. Analysis of Blocking Rate and Bandwidth Usage of Mobile IPTV Services in Wireless Cellular Networks

    Directory of Open Access Journals (Sweden)

    Mingfu Li

    2014-01-01

    Full Text Available Mobile IPTV services over wireless cellular networks become more and more popular, owing to the significant growth in access bandwidth of wireless cellular networks such as 3G/4G and WiMAX. However, the spectrum resources of wireless cellular networks is rare. How to enhance the spectral efficiency of mobile networks becomes an important issue. Unicast, broadcast, and multicast are the most important transport schemes for offering mobile IPTV services over wireless cellular networks. Therefore, bandwidth usages and blocking rates of unicast, broadcast, and multicast IPTV services were analyzed and compared in this paper. Simulations were also conducted to validate the analytical results. Numerical results demonstrate that the presented analysis is correct, and multicast scheme achieves the best bandwidth usage and blocking rate performance, relative to the other two schemes.

  13. Analysis of blocking rate and bandwidth usage of mobile IPTV services in wireless cellular networks.

    Science.gov (United States)

    Li, Mingfu

    2014-01-01

    Mobile IPTV services over wireless cellular networks become more and more popular, owing to the significant growth in access bandwidth of wireless cellular networks such as 3G/4G and WiMAX. However, the spectrum resources of wireless cellular networks is rare. How to enhance the spectral efficiency of mobile networks becomes an important issue. Unicast, broadcast, and multicast are the most important transport schemes for offering mobile IPTV services over wireless cellular networks. Therefore, bandwidth usages and blocking rates of unicast, broadcast, and multicast IPTV services were analyzed and compared in this paper. Simulations were also conducted to validate the analytical results. Numerical results demonstrate that the presented analysis is correct, and multicast scheme achieves the best bandwidth usage and blocking rate performance, relative to the other two schemes.

  14. Maximum entropy modeling of metabolic networks by constraining growth-rate moments predicts coexistence of phenotypes

    Science.gov (United States)

    De Martino, Daniele

    2017-12-01

    In this work maximum entropy distributions in the space of steady states of metabolic networks are considered upon constraining the first and second moments of the growth rate. Coexistence of fast and slow phenotypes, with bimodal flux distributions, emerges upon considering control on the average growth (optimization) and its fluctuations (heterogeneity). This is applied to the carbon catabolic core of Escherichia coli where it quantifies the metabolic activity of slow growing phenotypes and it provides a quantitative map with metabolic fluxes, opening the possibility to detect coexistence from flux data. A preliminary analysis on data for E. coli cultures in standard conditions shows degeneracy for the inferred parameters that extend in the coexistence region.

  15. Tourist activated networks: Implications for dynamic packaging systems in tourism

    DEFF Research Database (Denmark)

    Zach, Florian; Gretzel, Ulrike; Fesenmaier, Daniel R.

    2008-01-01

    This paper discusses tourist activated networks as a concept to inform technological applications supporting dynamic bundling and en-route recommendations. Empirical data was collected from travellers who visited a regional destination in the US and then analyzed with respect to its network struc...... marketing....

  16. Modeling multiple time scale firing rate adaptation in a neural network of local field potentials.

    Science.gov (United States)

    Lundstrom, Brian Nils

    2015-02-01

    In response to stimulus changes, the firing rates of many neurons adapt, such that stimulus change is emphasized. Previous work has emphasized that rate adaptation can span a wide range of time scales and produce time scale invariant power law adaptation. However, neuronal rate adaptation is typically modeled using single time scale dynamics, and constructing a conductance-based model with arbitrary adaptation dynamics is nontrivial. Here, a modeling approach is developed in which firing rate adaptation, or spike frequency adaptation, can be understood as a filtering of slow stimulus statistics. Adaptation dynamics are modeled by a stimulus filter, and quantified by measuring the phase leads of the firing rate in response to varying input frequencies. Arbitrary adaptation dynamics are approximated by a set of weighted exponentials with parameters obtained by fitting to a desired filter. With this approach it is straightforward to assess the effect of multiple time scale adaptation dynamics on neural networks. To demonstrate this, single time scale and power law adaptation were added to a network model of local field potentials. Rate adaptation enhanced the slow oscillations of the network and flattened the output power spectrum, dampening intrinsic network frequencies. Thus, rate adaptation may play an important role in network dynamics.

  17. Methodology for earthquake rupture rate estimates of fault networks: example for the western Corinth rift, Greece

    Science.gov (United States)

    Chartier, Thomas; Scotti, Oona; Lyon-Caen, Hélène; Boiselet, Aurélien

    2017-10-01

    Modeling the seismic potential of active faults is a fundamental step of probabilistic seismic hazard assessment (PSHA). An accurate estimation of the rate of earthquakes on the faults is necessary in order to obtain the probability of exceedance of a given ground motion. Most PSHA studies consider faults as independent structures and neglect the possibility of multiple faults or fault segments rupturing simultaneously (fault-to-fault, FtF, ruptures). The Uniform California Earthquake Rupture Forecast version 3 (UCERF-3) model takes into account this possibility by considering a system-level approach rather than an individual-fault-level approach using the geological, seismological and geodetical information to invert the earthquake rates. In many places of the world seismological and geodetical information along fault networks is often not well constrained. There is therefore a need to propose a methodology relying on geological information alone to compute earthquake rates of the faults in the network. In the proposed methodology, a simple distance criteria is used to define FtF ruptures and consider single faults or FtF ruptures as an aleatory uncertainty, similarly to UCERF-3. Rates of earthquakes on faults are then computed following two constraints: the magnitude frequency distribution (MFD) of earthquakes in the fault system as a whole must follow an a priori chosen shape and the rate of earthquakes on each fault is determined by the specific slip rate of each segment depending on the possible FtF ruptures. The modeled earthquake rates are then compared to the available independent data (geodetical, seismological and paleoseismological data) in order to weight different hypothesis explored in a logic tree.The methodology is tested on the western Corinth rift (WCR), Greece, where recent advancements have been made in the understanding of the geological slip rates of the complex network of normal faults which are accommodating the ˜ 15 mm yr-1 north

  18. Decentralized control of transmission rates in energy-critical wireless networks

    KAUST Repository

    Xia, Li

    2013-06-01

    In this paper, we discuss the decentralized optimization of delay and energy consumption in a multi-hop wireless network. The goal is to minimize the energy consumption of energy-critical nodes and the overall packet transmission delay of the network. The transmission rates of energy-critical nodes are adjustable according to the local information of nodes, i.e., the length of packets queued. The multi-hop network is modeled as a queueing network.We prove that the system performance is monotone w.r.t. (with respect to) the transmission rate, thus the “bang-bang” control is an optimal control. We also prove that there exists a threshold type control policy which is optimal. We propose a decentralized algorithm to control transmission rates of these energy-critical nodes. Some simulation experiments are conducted to demonstrate the effectiveness of our approach.

  19. Simulation of Missile Autopilot with Two-Rate Hybrid Neural Network System

    Directory of Open Access Journals (Sweden)

    ASTROV, I.

    2007-04-01

    Full Text Available This paper proposes a two-rate hybrid neural network system, which consists of two artificial neural network subsystems. These neural network subsystems are used as the dynamic subsystems controllers.1 This is because such neuromorphic controllers are especially suitable to control complex systems. An illustrative example - two-rate neural network hybrid control of decomposed stochastic model of a rigid guided missile over different operating conditions - was carried out using the proposed two-rate state-space decomposition technique. This example demonstrates that this research technique results in simplified low-order autonomous control subsystems with various speeds of actuation, and shows the quality of the proposed technique. The obtained results show that the control tasks for the autonomous subsystems can be solved more qualitatively than for the original system. The simulation and animation results with use of software package Simulink demonstrate that this research technique would work for real-time stochastic systems.

  20. Effect of physician collaboration network on hospitalization cost and readmission rate.

    Science.gov (United States)

    Uddin, Shahadat; Hossain, Liaquat; Kelaher, Margaret

    2012-10-01

    Previous studies have documented the effect of collaboration among physicians on the effectiveness in delivering health services and in producing better patient outcomes. However, there is no systematic empirical study suggesting the underlying relationship between the collaboration network of physicians and its effect on hospitalization cost and readmission rate. In this study, we explore the effect of different attributes (i.e. degree centrality, betweenness centrality, network density and network distance) of physician collaboration network (PCN) on hospitalization cost and readmission rate. We analyse health insurance claim data set of total hip replacement (THR) patients to construct PCN and to test the effect of its network attributes on hospitalization cost and readmission rate. We consider patient age as moderating factor, which could affect the relation of the PCN attributes with hospitalization cost and readmission rate. We find that degree centrality (i.e. level of involvement) and network density (i.e. level of connectedness) of PCN are negatively correlated with hospitalization cost and readmission rate. In contrast, betweenness centrality (i.e. capacity to control the flow of information) is found positively correlated with hospitalization cost and readmission rate. Distance (i.e. embeddedness of actors in a network) is found positively correlated with hospitalization cost but negatively correlated with readmission rate. We do not notice any significant impact of patient age on the relation of PCN attributes with hospitalization cost and readmission rate. The results show that the structure of PCNs is related to indicators of hospital costs and quality (readmission). In their respective hospitals, health-care managers or administrators may follow our research findings to reduce cost and improve quality.

  1. Facility Activity Inference Using Radiation Networks

    Energy Technology Data Exchange (ETDEWEB)

    Rao, Nageswara S. [ORNL; Ramirez Aviles, Camila A. [ORNL

    2017-11-01

    We consider the problem of inferring the operational status of a reactor facility using measurements from a radiation sensor network deployed around the facility’s ventilation off-gas stack. The intensity of stack emissions decays with distance, and the sensor counts or measurements are inherently random with parameters determined by the intensity at the sensor’s location. We utilize the measurements to estimate the intensity at the stack, and use it in a one-sided Sequential Probability Ratio Test (SPRT) to infer on/off status of the reactor. We demonstrate the superior performance of this method over conventional majority fusers and individual sensors using (i) test measurements from a network of 21 NaI detectors, and (ii) effluence measurements collected at the stack of a reactor facility. We also analytically establish the superior detection performance of the network over individual sensors with fixed and adaptive thresholds by utilizing the Poisson distribution of the counts. We quantify the performance improvements of the network detection over individual sensors using the packing number of the intensity space.

  2. Computational Modeling of Complex Protein Activity Networks

    NARCIS (Netherlands)

    Schivo, Stefano; Leijten, Jeroen; Karperien, Marcel; Post, Janine N.; Prignet, Claude

    2017-01-01

    Because of the numerous entities interacting, the complexity of the networks that regulate cell fate makes it impossible to analyze and understand them using the human brain alone. Computational modeling is a powerful method to unravel complex systems. We recently described the development of a

  3. Consumer Activities and Reactions to Social Network Marketing

    Directory of Open Access Journals (Sweden)

    Bistra Vassileva

    2017-06-01

    Full Text Available The purpose of this paper is to understand consumer behavioural models with respect to their reactions to social network marketing. Theoretical background is focused on online and social network usage, motivations and behaviour. The research goal is to explore consumer reactions to the exposure of social network marketing based on the following criteria: level of brand engagement, word-of-mouth (WOM referral behaviour, and purchase intentions. Consumers are investigated based on their attitudes toward social network marketing and basic socio-demographic covariates using data from a sample size of 700 Bulgarian respondents (age group 21–54 years, Internet users, urban inhabitants. Factor and cluster analyses are applied. It is found that consumers are willing to receive information about brands and companies through social networks. They like to talk in social networks about these brands and companies and to share information as well (factor 2, brand engagement. Internet users are willing to share information received through social network advertising (factor 1, wom referral behaviour but they would not buy a certain brand as a result of brand communication activities in social networks (factor 3, purchase intention. Several practical implications regarding marketing activities through social networks are drawn.

  4. Cross-Layer Active Predictive Congestion Control Protocol for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Yinfeng Wu

    2009-10-01

    Full Text Available In wireless sensor networks (WSNs, there are numerous factors that may cause network congestion problems, such as the many-to-one communication modes, mutual interference of wireless links, dynamic changes of network topology and the memory-restrained characteristics of nodes. All these factors result in a network being more vulnerable to congestion. In this paper, a cross-layer active predictive congestion control scheme (CL-APCC for improving the performance of networks is proposed. Queuing theory is applied in the CL-APCC to analyze data flows of a single-node according to its memory status, combined with the analysis of the average occupied memory size of local networks. It also analyzes the current data change trends of local networks to forecast and actively adjust the sending rate of the node in the next period. In order to ensure the fairness and timeliness of the network, the IEEE 802.11 protocol is revised based on waiting time, the number of the node‟s neighbors and the original priority of data packets, which dynamically adjusts the sending priority of the node. The performance of CL-APCC, which is evaluated by extensive simulation experiments. is more efficient in solving the congestion in WSNs. Furthermore, it is clear that the proposed scheme has an outstanding advantage in terms of improving the fairness and lifetime of networks.

  5. Contagion processes on the static and activity driven coupling networks

    CERN Document Server

    Lei, Yanjun; Guo, Quantong; Ma, Yifang; Li, Meng; Zheng, Zhiming

    2015-01-01

    The evolution of network structure and the spreading of epidemic are common coexistent dynamical processes. In most cases, network structure is treated either static or time-varying, supposing the whole network is observed in a same time window. In this paper, we consider the epidemic spreading on a network consisting of both static and time-varying structures. At meanwhile, the time-varying part and the epidemic spreading are supposed to be of the same time scale. We introduce a static and activity driven coupling (SADC) network model to characterize the coupling between static (strong) structure and dynamic (weak) structure. Epidemic thresholds of SIS and SIR model are studied on SADC both analytically and numerically with various coupling strategies, where the strong structure is of homogeneous or heterogeneous degree distribution. Theoretical thresholds obtained from SADC model can both recover and generalize the classical results in static and time-varying networks. It is demonstrated that weak structure...

  6. Network interventions on physical activity in an afterschool program: an agent-based social network study.

    Science.gov (United States)

    Zhang, Jun; Shoham, David A; Tesdahl, Eric; Gesell, Sabina B

    2015-04-01

    We studied simulated interventions that leveraged social networks to increase physical activity in children. We studied a real-world social network of 81 children (average age = 7.96 years) who lived in low socioeconomic status neighborhoods, and attended public schools and 1 of 2 structured afterschool programs. The sample was ethnically diverse, and 44% were overweight or obese. We used social network analysis and agent-based modeling simulations to test whether implementing a network intervention would increase children's physical activity. We tested 3 intervention strategies. The intervention that targeted opinion leaders was effective in increasing the average level of physical activity across the entire network. However, the intervention that targeted the most sedentary children was the best at increasing their physical activity levels. Which network intervention to implement depends on whether the goal is to shift the entire distribution of physical activity or to influence those most adversely affected by low physical activity. Agent-based modeling could be an important complement to traditional project planning tools, analogous to sample size and power analyses, to help researchers design more effective interventions for increasing children's physical activity.

  7. Maximum Data Collection Rate Routing Protocol Based on Topology Control for Rechargeable Wireless Sensor Networks.

    Science.gov (United States)

    Lin, Haifeng; Bai, Di; Gao, Demin; Liu, Yunfei

    2016-07-30

    In Rechargeable Wireless Sensor Networks (R-WSNs), in order to achieve the maximum data collection rate it is critical that sensors operate in very low duty cycles because of the sporadic availability of energy. A sensor has to stay in a dormant state in most of the time in order to recharge the battery and use the energy prudently. In addition, a sensor cannot always conserve energy if a network is able to harvest excessive energy from the environment due to its limited storage capacity. Therefore, energy exploitation and energy saving have to be traded off depending on distinct application scenarios. Since higher data collection rate or maximum data collection rate is the ultimate objective for sensor deployment, surplus energy of a node can be utilized for strengthening packet delivery efficiency and improving the data generating rate in R-WSNs. In this work, we propose an algorithm based on data aggregation to compute an upper data generation rate by maximizing it as an optimization problem for a network, which is formulated as a linear programming problem. Subsequently, a dual problem by introducing Lagrange multipliers is constructed, and subgradient algorithms are used to solve it in a distributed manner. At the same time, a topology controlling scheme is adopted for improving the network's performance. Through extensive simulation and experiments, we demonstrate that our algorithm is efficient at maximizing the data collection rate in rechargeable wireless sensor networks.

  8. An investigation of the relationship between activation of a social cognitive neural network and social functioning.

    Science.gov (United States)

    Pinkham, Amy E; Hopfinger, Joseph B; Ruparel, Kosha; Penn, David L

    2008-07-01

    Previous work examining the neurobiological substrates of social cognition in healthy individuals has reported modulation of a social cognitive network such that increased activation of the amygdala, fusiform gyrus, and superior temporal sulcus are evident when individuals judge a face to be untrustworthy as compared with trustworthy. We examined whether this pattern would be present in individuals with schizophrenia who are known to show reduced activation within these same neural regions when processing faces. Additionally, we sought to determine how modulation of this social cognitive network may relate to social functioning. Neural activation was measured using functional magnetic resonance imaging with blood oxygenation level dependent contrast in 3 groups of individuals--nonparanoid individuals with schizophrenia, paranoid individuals with schizophrenia, and healthy controls--while they rated faces as either trustworthy or untrustworthy. Analyses of mean percent signal change extracted from a priori regions of interest demonstrated that both controls and nonparanoid individuals with schizophrenia showed greater activation of this social cognitive network when they rated a face as untrustworthy relative to trustworthy. In contrast, paranoid individuals did not show a significant difference in levels of activation based on how they rated faces. Further, greater activation of this social cognitive network to untrustworthy faces was significantly and positively correlated with social functioning. These findings indicate that impaired modulation of neural activity while processing social stimuli may underlie deficits in social cognition and social dysfunction in schizophrenia.

  9. Entertainment Capture through Heart Rate Activity in Physical Interactive Playgrounds

    DEFF Research Database (Denmark)

    Yannakakis, Georgios; Hallam, John; Lund, Henrik Hautop

    2008-01-01

    An approach for capturing and modeling individual entertainment (“fun”) preferences is applied to users of the innovative Playware playground, an interactive physical playground inspired by computer games, in this study. The goal is to construct, using representative statistics computed from...... that predict reported entertainment preferences given HR features. These models are expressed as artificial neural networks and are demonstrated and evaluated on two Playware games and two control tasks requiring physical activity. The best network is able to correctly match expressed preferences in 64...

  10. Reduction Method for Active Distribution Networks

    DEFF Research Database (Denmark)

    Raboni, Pietro; Chen, Zhe

    2013-01-01

    On-line security assessment is traditionally performed by Transmission System Operators at the transmission level, ignoring the effective response of distributed generators and small loads. On the other hand the required computation time and amount of real time data for including Distribution Net...... by comparing the results obtained in PSCAD® with the detailed network model and with the reduced one. Moreover the control schemes of a wind turbine and a photovoltaic plant included in the detailed network model are described.......On-line security assessment is traditionally performed by Transmission System Operators at the transmission level, ignoring the effective response of distributed generators and small loads. On the other hand the required computation time and amount of real time data for including Distribution...

  11. Critical Transitions in Social Network Activity

    DEFF Research Database (Denmark)

    Kuehn, Christian; Martens, Erik Andreas; Romero, Daniel M

    2014-01-01

    for a priori unknown events in society are present in social networks is an exciting open problem, to which at present only highly speculative answers can be given. Here, we instead provide a first step towards tackling a simpler question by focusing on a priori known events and analyse a social media data set...... with a focus on classical variance and autocorrelation warning signs. Our results thus pertain to one absolutely fundamental question: Can the stochastic warning signs known from other areas also be detected in large-scale social media data? We answer this question affirmatively as we find that several...... a priori known events are preceded by variance and autocorrelation growth. Our findings thus clearly establish the necessary starting point to further investigate the relationship between abstract mathematical theory and various classes of critical transitions in social networks....

  12. Unveiling causal activity of complex networks

    Science.gov (United States)

    Williams-García, Rashid V.; Beggs, John M.; Ortiz, Gerardo

    2017-07-01

    We introduce a novel tool for analyzing complex network dynamics, allowing for cascades of causally-related events, which we call causal webs (c-webs), to be separated from other non-causally-related events. This tool shows that traditionally-conceived avalanches may contain mixtures of spatially-distinct but temporally-overlapping cascades of events, and dynamical disorder or noise. In contrast, c-webs separate these components, unveiling previously hidden features of the network and dynamics. We apply our method to mouse cortical data with resulting statistics which demonstrate for the first time that neuronal avalanches are not merely composed of causally-related events. The original version of this article was uploaded to the arXiv on March 17th, 2016 [1].

  13. Active system area networks for data intensive computations. Final report

    Energy Technology Data Exchange (ETDEWEB)

    None

    2002-04-01

    The goal of the Active System Area Networks (ASAN) project is to develop hardware and software technologies for the implementation of active system area networks (ASANs). The use of the term ''active'' refers to the ability of the network interfaces to perform application-specific as well as system level computations in addition to their traditional role of data transfer. This project adopts the view that the network infrastructure should be an active computational entity capable of supporting certain classes of computations that would otherwise be performed on the host CPUs. The result is a unique network-wide programming model where computations are dynamically placed within the host CPUs or the NIs depending upon the quality of service demands and network/CPU resource availability. The projects seeks to demonstrate that such an approach is a better match for data intensive network-based applications and that the advent of low-cost powerful embedded processors and configurable hardware makes such an approach economically viable and desirable.

  14. Resource management for multimedia services in high data rate wireless networks

    CERN Document Server

    Zhang, Ruonan; Pan, Jianping

    2017-01-01

    This brief offers a valuable resource on principles of quality-of-service (QoS) provisioning and the related link-layer resource management techniques for high data-rate wireless networks. The primary emphasis is on protocol modeling and analysis. It introduces media access control (MAC) protocols, standards of wireless local area networks (WLANs), wireless personal area networks (WPANs), and wireless body area networks (WBANs), discussing their key technologies, applications, and deployment scenarios. The main analytical approaches and models for performance analysis of the fundamental resource scheduling mechanisms, including the contention-based, reservation-based, and hybrid MAC, are presented. To help readers understand and evaluate system performance, the brief contains a range of simulation results. In addition, a thorough bibliography provides an additional tool. This brief is an essential resource for engineers, researchers, students, and users of wireless networks.

  15. Neuronal response impedance mechanism implementing cooperative networks with low firing rates and μs precision.

    Science.gov (United States)

    Vardi, Roni; Goldental, Amir; Marmari, Hagar; Brama, Haya; Stern, Edward A; Sardi, Shira; Sabo, Pinhas; Kanter, Ido

    2015-01-01

    Realizations of low firing rates in neural networks usually require globally balanced distributions among excitatory and inhibitory links, while feasibility of temporal coding is limited by neuronal millisecond precision. We show that cooperation, governing global network features, emerges through nodal properties, as opposed to link distributions. Using in vitro and in vivo experiments we demonstrate microsecond precision of neuronal response timings under low stimulation frequencies, whereas moderate frequencies result in a chaotic neuronal phase characterized by degraded precision. Above a critical stimulation frequency, which varies among neurons, response failures were found to emerge stochastically such that the neuron functions as a low pass filter, saturating the average inter-spike-interval. This intrinsic neuronal response impedance mechanism leads to cooperation on a network level, such that firing rates are suppressed toward the lowest neuronal critical frequency simultaneously with neuronal microsecond precision. Our findings open up opportunities of controlling global features of network dynamics through few nodes with extreme properties.

  16. Inferring Transition Rates of Networks from Populations in Continuous-Time Markov Processes.

    Science.gov (United States)

    Dixit, Purushottam D; Jain, Abhinav; Stock, Gerhard; Dill, Ken A

    2015-11-10

    We are interested inferring rate processes on networks. In particular, given a network's topology, the stationary populations on its nodes, and a few global dynamical observables, can we infer all the transition rates between nodes? We draw inferences using the principle of maximum caliber (maximum path entropy). We have previously derived results for discrete-time Markov processes. Here, we treat continuous-time processes, such as dynamics among metastable states of proteins. The present work leads to a particularly important analytical result: namely, that when the network is constrained only by a mean jump rate, the rate matrix is given by a square-root dependence of the rate, kab ∝ (πb/πa)(1/2), on πa and πb, the stationary-state populations at nodes a and b. This leads to a fast way to estimate all of the microscopic rates in the system. As an illustration, we show that the method accurately predicts the nonequilibrium transition rates in an in silico gene expression network and transition probabilities among the metastable states of a small peptide at equilibrium. We note also that the method makes sensible predictions for so-called extra-thermodynamic relationships, such as those of Bronsted, Hammond, and others.

  17. Exchange rate prediction with multilayer perceptron neural network using gold price as external factor

    Directory of Open Access Journals (Sweden)

    Mohammad Fathian

    2012-04-01

    Full Text Available In this paper, the problem of predicting the exchange rate time series in the foreign exchange rate market is going to be solved using a time-delayed multilayer perceptron neural network with gold price as external factor. The input for the learning phase of the artificial neural network are the exchange rate data of the last five days plus the gold price in two different currencies of the exchange rate as the external factor for helping the artificial neural network improving its forecast accuracy. The five-day delay has been chosen because of the weekly cyclic behavior of the exchange rate time series with the consideration of two holidays in a week. The result of forecasts are then compared with using the multilayer peceptron neural network without gold price external factor by two most important evaluation techniques in the literature of exchange rate prediction. For the experimental analysis phase, the data of three important exchange rates of EUR/USD, GBP/USD, and USD/JPY are used.

  18. The association between social networks and self-rated risk of HIV infection among secondary school students in Moshi Municipality, Tanzania.

    Science.gov (United States)

    Lyimo, Elizabeth J; Todd, Jim; Richey, Lisa Ann; Njau, Bernard

    2013-01-01

    This study describes the social networks of secondary school students in Moshi Municipality, and their association with self-rated risk of human immunodeficiency virus (HIV) infection. A cross-sectional analytical study was conducted among 300 students aged 15-24 years in 5 secondary schools in Moshi, Tanzania. Bonding networks were defined as social groupings of students participating in activities within the school, while bridging networks were groups that included students participating in social groupings from outside of the school environs. A structured questionnaire was used to ask about participation in bonding and bridging social networks and self-rated HIV risk behavior. More participants participated in bonding networks (72%) than in bridging networks (29%). Participation in bridging networks was greater among females (25%) than males (12%, psexually experienced, and of these 62 (70%) considered themselves to be at low risk of HIV infection. Factors associated with self-rated risk of HIV included: type of school (psexually experienced (psex in the past three months (psexual partner (psexual intercourse (passociation between bonding and bridging social networks on self-rated risk of HIV among study participants. However, sexually experienced participants rated themselves at low risk of HIV infection despite practicing unsafe sex. Efforts to raise adolescents' self-awareness of risk of HIV infection through life skills education and HIV/acquired immunodeficiency syndrome risk reduction strategies may be beneficial to students in this at-risk group.

  19. ICA model order selection of task co-activation networks.

    Science.gov (United States)

    Ray, Kimberly L; McKay, D Reese; Fox, Peter M; Riedel, Michael C; Uecker, Angela M; Beckmann, Christian F; Smith, Stephen M; Fox, Peter T; Laird, Angela R

    2013-01-01

    Independent component analysis (ICA) has become a widely used method for extracting functional networks in the brain during rest and task. Historically, preferred ICA dimensionality has widely varied within the neuroimaging community, but typically varies between 20 and 100 components. This can be problematic when comparing results across multiple studies because of the impact ICA dimensionality has on the topology of its resultant components. Recent studies have demonstrated that ICA can be applied to peak activation coordinates archived in a large neuroimaging database (i.e., BrainMap Database) to yield whole-brain task-based co-activation networks. A strength of applying ICA to BrainMap data is that the vast amount of metadata in BrainMap can be used to quantitatively assess tasks and cognitive processes contributing to each component. In this study, we investigated the effect of model order on the distribution of functional properties across networks as a method for identifying the most informative decompositions of BrainMap-based ICA components. Our findings suggest dimensionality of 20 for low model order ICA to examine large-scale brain networks, and dimensionality of 70 to provide insight into how large-scale networks fractionate into sub-networks. We also provide a functional and organizational assessment of visual, motor, emotion, and interoceptive task co-activation networks as they fractionate from low to high model-orders.

  20. Systematic network assessment of the carcinogenic activities of cadmium.

    Science.gov (United States)

    Chen, Peizhan; Duan, Xiaohua; Li, Mian; Huang, Chao; Li, Jingquan; Chu, Ruiai; Ying, Hao; Song, Haiyun; Jia, Xudong; Ba, Qian; Wang, Hui

    2016-11-01

    Cadmium has been defined as type I carcinogen for humans, but the underlying mechanisms of its carcinogenic activity and its influence on protein-protein interactions in cells are not fully elucidated. The aim of the current study was to evaluate, systematically, the carcinogenic activity of cadmium with systems biology approaches. From a literature search of 209 studies that performed with cellular models, 208 proteins influenced by cadmium exposure were identified. All of these were assessed by Western blotting and were recognized as key nodes in network analyses. The protein-protein functional interaction networks were constructed with NetBox software and visualized with Cytoscape software. These cadmium-rewired genes were used to construct a scale-free, highly connected biological protein interaction network with 850 nodes and 8770 edges. Of the network, nine key modules were identified and 60 key signaling pathways, including the estrogen, RAS, PI3K-Akt, NF-κB, HIF-1α, Jak-STAT, and TGF-β signaling pathways, were significantly enriched. With breast cancer, colorectal and prostate cancer cellular models, we validated the key node genes in the network that had been previously reported or inferred form the network by Western blotting methods, including STAT3, JNK, p38, SMAD2/3, P65, AKT1, and HIF-1α. These results suggested the established network was robust and provided a systematic view of the carcinogenic activities of cadmium in human. Copyright © 2016 Elsevier Inc. All rights reserved.

  1. Cultured Neural Networks: Optimization of Patterned Network Adhesiveness and Characterization of their Neural Activity

    Directory of Open Access Journals (Sweden)

    W. L. C. Rutten

    2006-01-01

    Full Text Available One type of future, improved neural interface is the “cultured probe”. It is a hybrid type of neural information transducer or prosthesis, for stimulation and/or recording of neural activity. It would consist of a microelectrode array (MEA on a planar substrate, each electrode being covered and surrounded by a local circularly confined network (“island” of cultured neurons. The main purpose of the local networks is that they act as biofriendly intermediates for collateral sprouts from the in vivo system, thus allowing for an effective and selective neuron–electrode interface. As a secondary purpose, one may envisage future information processing applications of these intermediary networks. In this paper, first, progress is shown on how substrates can be chemically modified to confine developing networks, cultured from dissociated rat cortex cells, to “islands” surrounding an electrode site. Additional coating of neurophobic, polyimide-coated substrate by triblock-copolymer coating enhances neurophilic-neurophobic adhesion contrast. Secondly, results are given on neuronal activity in patterned, unconnected and connected, circular “island” networks. For connected islands, the larger the island diameter (50, 100 or 150 μm, the more spontaneous activity is seen. Also, activity may show a very high degree of synchronization between two islands. For unconnected islands, activity may start at 22 days in vitro (DIV, which is two weeks later than in unpatterned networks.

  2. Linking structure and activity in nonlinear spiking networks.

    Directory of Open Access Journals (Sweden)

    Gabriel Koch Ocker

    2017-06-01

    Full Text Available Recent experimental advances are producing an avalanche of data on both neural connectivity and neural activity. To take full advantage of these two emerging datasets we need a framework that links them, revealing how collective neural activity arises from the structure of neural connectivity and intrinsic neural dynamics. This problem of structure-driven activity has drawn major interest in computational neuroscience. Existing methods for relating activity and architecture in spiking networks rely on linearizing activity around a central operating point and thus fail to capture the nonlinear responses of individual neurons that are the hallmark of neural information processing. Here, we overcome this limitation and present a new relationship between connectivity and activity in networks of nonlinear spiking neurons by developing a diagrammatic fluctuation expansion based on statistical field theory. We explicitly show how recurrent network structure produces pairwise and higher-order correlated activity, and how nonlinearities impact the networks' spiking activity. Our findings open new avenues to investigating how single-neuron nonlinearities-including those of different cell types-combine with connectivity to shape population activity and function.

  3. Impact of window decrement rate on TCP performance in an adhoc network

    Science.gov (United States)

    Suherman; Hutasuhut, Arief T. W.; Badra, Khaldun; Al-Akaidi, Marwan

    2017-09-01

    Transmission control protocol (TCP) is a reliable transport protocol handling end to end connection in TCP/IP stack. It works well in copper or optical fibre link, but experiences increasing delay in wireless network. Further, TCP experiences multiple retransmissions due to higher collision probability within wireless network. The situation may get worsen in an ad hoc network. This paper examines the impact half window or window reduction rate to the overall TCP performances. The evaluation using NS-2 simulator shows that the smaller the window decrement rate results the smaller end to end delay. Delay is reduced to 17.05% in average when window decrement rate decreases. Average jitter also decreases 4.15%, while packet loss is not affected.

  4. The efficacy of centralized flow rate control in 802.11-based wireless mesh networks

    KAUST Repository

    Jamshaid, K.

    2013-06-13

    Commodity WiFi-based wireless mesh networks (WMNs) can be used to provide last mile Internet access. These networks exhibit extreme unfairness with backlogged traffic sources. Current solutions propose distributed source-rate control algorithms requiring link-layer or transport-layer changes on all mesh nodes. This is often infeasible in large practical deployments. In wireline networks, router-assisted rate control techniques have been proposed for use alongside end-to-end mechanisms. We wish to evaluate the feasibility of establishing similar centralized control via gateways in WMNs. In this paper, we focus on the efficacy of this control rather than the specifics of the controller design mechanism. We answer the question: Given sources that react predictably to congestion notification, can we enforce a desired rate allocation through a single centralized controller? The answer is not obvious because flows experience varying contention levels, and transmissions are scheduled by a node using imperfect local knowledge. We find that common router-assisted flow control schemes used in wired networks fail in WMNs because they assume that (1) links are independent, and (2) router queue buildups are sufficient for detecting congestion. We show that non-work-conserving, rate-based centralized scheduling can effectively enforce rate allocation. It can achieve results comparable to source rate limiting, without requiring any modifications to mesh routers or client devices. 2013 Jamshaid et al.; licensee Springer.

  5. A prediction method for the wax deposition rate based on a radial basis function neural network

    Directory of Open Access Journals (Sweden)

    Ying Xie

    2017-06-01

    Full Text Available The radial basis function neural network is a popular supervised learning tool based on machinery learning technology. Its high precision having been proven, the radial basis function neural network has been applied in many areas. The accumulation of deposited materials in the pipeline may lead to the need for increased pumping power, a decreased flow rate or even to the total blockage of the line, with losses of production and capital investment, so research on predicting the wax deposition rate is significant for the safe and economical operation of an oil pipeline. This paper adopts the radial basis function neural network to predict the wax deposition rate by considering four main influencing factors, the pipe wall temperature gradient, pipe wall wax crystal solubility coefficient, pipe wall shear stress and crude oil viscosity, by the gray correlational analysis method. MATLAB software is employed to establish the RBF neural network. Compared with the previous literature, favorable consistency exists between the predicted outcomes and the experimental results, with a relative error of 1.5%. It can be concluded that the prediction method of wax deposition rate based on the RBF neural network is feasible.

  6. Clusters of reaction rates and concentrations in protein networks such as the phosphotransferase system.

    Science.gov (United States)

    Härdin, Hanna M; Zagaris, Antonios; Willms, Allan R; Westerhoff, Hans V

    2014-01-01

    To understand the functioning of living cells, it is often helpful or even necessary to exploit inherent timescale disparities and focus on long-term dynamic behaviour. In the present study, we explore this type of behaviour for the biochemical network of the phosphotransferase system. We show that, during the slow phase that follows a fast initial transient, the network reaction rates are partitioned into clusters corresponding to connected parts of the reaction network. Rates within any of these clusters assume essentially the same value: differences within each cluster are vastly smaller than that from one cluster to another. This rate clustering induces an analogous clustering of the reactive compounds: only the molecular concentrations on the interface between these clusters are produced and consumed at substantially different rates and hence change considerably during the slow phase. The remaining concentrations essentially assume their steady-state values already by the end of the transient phase. Further, we find that this clustering phenomenon occurs for a large number of parameter values and also for models with different topologies; to each of these models, there corresponds a particular network partitioning. Our results show that, in spite of its complexity, the phosphotransferase system tends to behave in a rather simple (yet versatile) way. The persistence of clustering for the perturbed models we examined suggests that it is likely to be encountered in various environmental conditions, as well as in other signal transduction pathways with network structures similar to that of the phosphotransferase system. © 2013 FEBS.

  7. Ethanol affects network activity in cultured rat hippocampus: mediation by potassium channels.

    Directory of Open Access Journals (Sweden)

    Eduard Korkotian

    Full Text Available The effects of ethanol on neuronal network activity were studied in dissociated cultures of rat hippocampus. Exposure to low (0.25-0.5% ethanol concentrations caused an increase in synchronized network spikes, and a decrease in the duration of individual spikes. Ethanol also caused an increase in rate of miniature spontaneous excitatory postsynaptic currents. Higher concentrations of ethanol eliminated network spikes. These effects were reversible upon wash. The effects of the high, but not the low ethanol were blocked by the GABA antagonist bicuculline. The enhancing action of low ethanol was blocked by apamin, an SK potassium channel antagonist, and mimicked by 1-EBIO, an SK channel opener. It is proposed that in cultured hippocampal networks low concentration of ethanol is associated with SK channel activity, rather than the GABAergic receptor.

  8. Flexibility and Balancing in Active Distribution Networks

    DEFF Research Database (Denmark)

    Kordheili, Reza Ahmadi

    , and causes higher fluctuations in the demand. In countries such as Denmark, different incentives have been proposed and applied to encourage customers for investing on solar photovoltaic (PV) panels. These policies have increased the number of household PV panels. However, presence of such small energy...... in these batteries. A detailed modeling of Li-ion battery is presented in chapter 2 as well. PV panels are modelled as a function of solar irradiation and ambient temperature. In the next step, the impact of PV panels and electric vehicles on LV network was quantified separately. For PV panels, different placement......Environmental concerns, together with the fast-pacing changes in the renewable energy technologies, have led to significant growth of renewable energy sources (RESs) in energy systems. Among different sources of renewable energy, wind and solar energy are the most progressed sources so far. However...

  9. Regulation of burstiness by network-driven activation

    CERN Document Server

    García-Pérez, Guillermo; Serrano, M Ángeles

    2014-01-01

    We prove that complex networks of interactions have the capacity to regulate and buffer unpredictable fluctuations in production events. We show that non-bursty network-driven activation dynamics can effectively regulate the level of burstiness in the production of nodes, which can be enhanced or reduced. Burstiness can be induced even when the endogenous inter-event time distribution of nodes' production is non-bursty. We found that hubs tend to be less controllable than low degree nodes, which are more susceptible to the networked regulatory effects. Our results have important implications for the analysis and engineering of bursty activity in a range of systems, from telecommunication networks to transcription and translation of genes into proteins in cells.

  10. Explicit Rate Adjustment (ERA: Responsiveness, Network Utilization Efficiency and Fairness for Layered Multicast

    Directory of Open Access Journals (Sweden)

    Somnuk PUANGPRONPITAG

    2005-08-01

    Full Text Available To provide layered multicast with responsiveness, efficiency in network utilization, scalability and fairness (including inter-protocol fairness, intra-protocol fairness, intra-session fairness and TCP-friendliness for layered multicast, we propose in this paper a new multicast congestion control, called Explicit Rate Adjustment (ERA. Our protocol uses an algorithm relying on TCP throughput equation and Packet-bunch Probe techniques to detect optimal bandwidth utilization; then adjusts the reception rate accordingly. We have built ERA into a network simulator (ns2 and demonstrate via simulations that the goals are reached.

  11. Study of active crossover network | Tyona | Nigerian Journal of Physics

    African Journals Online (AJOL)

    An active crossover network system has been realized using an active component LF356 with a JFET input. The net work has two drives, the low frequency drive (Bass) and the high frequency drive (Treble). It employs high level crossover technique. The circuit performance was adequately verified and the frequency ...

  12. Active Learning for Node Classification in Assortative and Disassortative Networks

    CERN Document Server

    Moore, Cristopher; Zhu, Yaojia; Rouquier, Jean-Baptiste; Lane, Terran

    2011-01-01

    In many real-world networks, nodes have class labels, attributes, or variables that affect the network's topology. If the topology of the network is known but the labels of the nodes are hidden, we would like to select a small subset of nodes such that, if we knew their labels, we could accurately predict the labels of all the other nodes. We develop an active learning algorithm for this problem which uses information-theoretic techniques to choose which nodes to explore. We test our algorithm on networks from three different domains: a social network, a network of English words that appear adjacently in a novel, and a marine food web. Our algorithm makes no initial assumptions about how the groups connect, and performs well even when faced with quite general types of network structure. In particular, we do not assume that nodes of the same class are more likely to be connected to each other---only that they connect to the rest of the network in similar ways.

  13. Impact of visual repetition rate on intrinsic properties of low frequency fluctuations in the visual network.

    Directory of Open Access Journals (Sweden)

    Yi-Chia Li

    Full Text Available BACKGROUND: Visual processing network is one of the functional networks which have been reliably identified to consistently exist in human resting brains. In our work, we focused on this network and investigated the intrinsic properties of low frequency (0.01-0.08 Hz fluctuations (LFFs during changes of visual stimuli. There were two main questions to be discussed in this study: intrinsic properties of LFFs regarding (1 interactions between visual stimuli and resting-state; (2 impact of repetition rate of visual stimuli. METHODOLOGY/PRINCIPAL FINDINGS: We analyzed scanning sessions that contained rest and visual stimuli in various repetition rates with a novel method. The method included three numerical approaches involving ICA (Independent Component Analyses, fALFF (fractional Amplitude of Low Frequency Fluctuation, and Coherence, to respectively investigate the modulations of visual network pattern, low frequency fluctuation power, and interregional functional connectivity during changes of visual stimuli. We discovered when resting-state was replaced by visual stimuli, more areas were involved in visual processing, and both stronger low frequency fluctuations and higher interregional functional connectivity occurred in visual network. With changes of visual repetition rate, the number of areas which were involved in visual processing, low frequency fluctuation power, and interregional functional connectivity in this network were also modulated. CONCLUSIONS/SIGNIFICANCE: To combine the results of prior literatures and our discoveries, intrinsic properties of LFFs in visual network are altered not only by modulations of endogenous factors (eye-open or eye-closed condition; alcohol administration and disordered behaviors (early blind, but also exogenous sensory stimuli (visual stimuli with various repetition rates. It demonstrates that the intrinsic properties of LFFs are valuable to represent physiological states of human brains.

  14. Active Engine Mounting Control Algorithm Using Neural Network

    Directory of Open Access Journals (Sweden)

    Fadly Jashi Darsivan

    2009-01-01

    Full Text Available This paper proposes the application of neural network as a controller to isolate engine vibration in an active engine mounting system. It has been shown that the NARMA-L2 neurocontroller has the ability to reject disturbances from a plant. The disturbance is assumed to be both impulse and sinusoidal disturbances that are induced by the engine. The performance of the neural network controller is compared with conventional PD and PID controllers tuned using Ziegler-Nichols. From the result simulated the neural network controller has shown better ability to isolate the engine vibration than the conventional controllers.

  15. Patterns recognition of electric brain activity using artificial neural networks

    Science.gov (United States)

    Musatov, V. Yu.; Pchelintseva, S. V.; Runnova, A. E.; Hramov, A. E.

    2017-04-01

    An approach for the recognition of various cognitive processes in the brain activity in the perception of ambiguous images. On the basis of developed theoretical background and the experimental data, we propose a new classification of oscillating patterns in the human EEG by using an artificial neural network approach. After learning of the artificial neural network reliably identified cube recognition processes, for example, left-handed or right-oriented Necker cube with different intensity of their edges, construct an artificial neural network based on Perceptron architecture and demonstrate its effectiveness in the pattern recognition of the EEG in the experimental.

  16. AMETH laboratories network activities; Activites du reseau de Laboratoires AMETH

    Energy Technology Data Exchange (ETDEWEB)

    Marimbordes, T.; Ould El Moctar, A.; Peerhossaini, H. [Nantes Univ., Ecole Polytechnique, UMR CNRS 6607, Lab. de Thermocinetique, 44 (France)] [and others

    2000-07-01

    The AMETH laboratories are a network for the improvement of thermal exchanges for one or two phases. This meeting of the 15 november 2000, dealt with the activities of this network of laboratories in the following topics: thermal-hydrodynamic instabilities and control of the limit layer; transfers with change in the liquid-vapor phase; transfers with change in the solid-liquid phase. Ten papers were presented. (A.L.B.)

  17. High Accuracy Human Activity Monitoring using Neural network

    OpenAIRE

    Sharma, Annapurna; Lee, Young-Dong; Chung, Wan-Young

    2011-01-01

    This paper presents the designing of a neural network for the classification of Human activity. A Triaxial accelerometer sensor, housed in a chest worn sensor unit, has been used for capturing the acceleration of the movements associated. All the three axis acceleration data were collected at a base station PC via a CC2420 2.4GHz ISM band radio (zigbee wireless compliant), processed and classified using MATLAB. A neural network approach for classification was used with an eye on theoretical a...

  18. Modafinil enhances alerting-related brain activity in attention networks.

    Science.gov (United States)

    Ikeda, Yumiko; Funayama, Takuya; Tateno, Amane; Fukayama, Haruhisa; Okubo, Yoshiro; Suzuki, Hidenori

    2017-07-01

    Modafinil is a wake-promoting agent and has been reported to be effective in improving attention in patients with attentional disturbance. However, neural substrates underlying the modafinil effects on attention are not fully understood. We employed a functional magnetic resonance imaging (fMRI) study with the attention network test (ANT) task in healthy adults and examined which networks of attention are mainly affected by modafinil and which neural substrates are responsible for the drug effects. We used a randomized placebo-controlled within-subjects cross-over design. Twenty-three healthy adults participated in two series of an fMRI study, taking either a placebo or modafinil. The participants performed the ANT task, which is designed to measure three distinct attentional networks, alerting, orienting, and executive control, during the fMRI scanning. The effects of modafinil on behavioral performance and regional brain activity were analyzed. We found that modafinil enhanced alerting performance and showed greater alerting network activity in the left middle and inferior occipital gyri as compared with the placebo. The brain activations in the occipital regions were positively correlated with alerting performance. Modafinil enhanced alerting performance and increased activation in the occipital lobe in the alerting network possibly relevant to noradrenergic activity during the ANT task. The present study may provide a rationale for the treatment of patients with distinct symptoms of impaired attention.

  19. Poly(Capro-Lactone) Networks as Actively Moving Polymers

    Science.gov (United States)

    Meng, Yuan

    Shape-memory polymers (SMPs), as a subset of actively moving polymers, form an exciting class of materials that can store and recover elastic deformation energy upon application of an external stimulus. Although engineering of SMPs nowadays has lead to robust materials that can memorize multiple temporary shapes, and can be triggered by various stimuli such as heat, light, moisture, or applied magnetic fields, further commercialization of SMPs is still constrained by the material's incapability to store large elastic energy, as well as its inherent one-way shape-change nature. This thesis develops a series of model semi-crystalline shape-memory networks that exhibit ultra-high energy storage capacity, with accurately tunable triggering temperature; by introducing a second competing network, or reconfiguring the existing network under strained state, configurational chain bias can be effectively locked-in, and give rise to two-way shape-actuators that, in the absence of an external load, elongates upon cooling and reversibly contracts upon heating. We found that well-defined network architecture plays essential role on strain-induced crystallization and on the performance of cold-drawn shape-memory polymers. Model networks with uniform molecular weight between crosslinks, and specified functionality of each net-point, results in tougher, more elastic materials with a high degree of crystallinity and outstanding shape-memory properties. The thermal behavior of the model networks can be finely modified by introducing non-crystalline small molecule linkers that effectively frustrates the crystallization of the network strands. This resulted in shape-memory networks that are ultra-sensitive to heat, as deformed materials can be efficiently triggered to revert to its permanent state upon only exposure to body temperature. We also coupled the same reaction adopted to create the model network with conventional free-radical polymerization to prepare a dual-cure "double

  20. Dynamic neural networking as a basis for plasticity in the control of heart rate.

    Science.gov (United States)

    Kember, G; Armour, J A; Zamir, M

    2013-01-21

    A model is proposed in which the relationship between individual neurons within a neural network is dynamically changing to the effect of providing a measure of "plasticity" in the control of heart rate. The neural network on which the model is based consists of three populations of neurons residing in the central nervous system, the intrathoracic extracardiac nervous system, and the intrinsic cardiac nervous system. This hierarchy of neural centers is used to challenge the classical view that the control of heart rate, a key clinical index, resides entirely in central neuronal command (spinal cord, medulla oblongata, and higher centers). Our results indicate that dynamic networking allows for the possibility of an interplay among the three populations of neurons to the effect of altering the order of control of heart rate among them. This interplay among the three levels of control allows for different neural pathways for the control of heart rate to emerge under different blood flow demands or disease conditions and, as such, it has significant clinical implications because current understanding and treatment of heart rate anomalies are based largely on a single level of control and on neurons acting in unison as a single entity rather than individually within a (plastically) interconnected network. Copyright © 2012 Elsevier Ltd. All rights reserved.

  1. Pattern Formation on Networks: from Localised Activity to Turing Patterns

    Science.gov (United States)

    McCullen, Nick; Wagenknecht, Thomas

    2016-06-01

    Networks of interactions between competing species are used to model many complex systems, such as in genetics, evolutionary biology or sociology and knowledge of the patterns of activity they can exhibit is important for understanding their behaviour. The emergence of patterns on complex networks with reaction-diffusion dynamics is studied here, where node dynamics interact via diffusion via the network edges. Through the application of a generalisation of dynamical systems analysis this work reveals a fundamental connection between small-scale modes of activity on networks and localised pattern formation seen throughout science, such as solitons, breathers and localised buckling. The connection between solutions with a single and small numbers of activated nodes and the fully developed system-scale patterns are investigated computationally using numerical continuation methods. These techniques are also used to help reveal a much larger portion of of the full number of solutions that exist in the system at different parameter values. The importance of network structure is also highlighted, with a key role being played by nodes with a certain so-called optimal degree, on which the interaction between the reaction kinetics and the network structure organise the behaviour of the system.

  2. Open-source hardware and software and web application for gamma dose rate network operation.

    Science.gov (United States)

    Luff, R; Zähringer, M; Harms, W; Bleher, M; Prommer, B; Stöhlker, U

    2014-08-01

    The German Federal Office for Radiation Protection operates a network of about 1800 gamma dose rate stations as a part of the national emergency preparedness plan. Each of the six network centres is capable of operating the network alone. Most of the used hardware and software have been developed in-house under open-source license. Short development cycles and close cooperation between developers and users ensure robustness, transparency and fast maintenance procedures, thus avoiding unnecessary complex solutions. This also reduces the overall costs of the network operation. An easy-to-expand web interface has been developed to make the complete system available to other interested network operators in order to increase cooperation between different countries. The interface is also regularly in use for education during scholarships of trainees supported, e.g. by the 'International Atomic Energy Agency' to operate a local area dose rate monitoring test network. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  3. Stock Price Change Rate Prediction by Utilizing Social Network Activities

    National Research Council Canada - National Science Library

    Deng, Shangkun; Mitsubuchi, Takashi; Sakurai, Akito

    2014-01-01

    .... The hypothesis is tested by accuracy of predictions as well as performance of simulated trading because success or failure of prediction is better measured by profits or losses the investors gain or suffer...

  4. Noise in attractor networks in the brain produced by graded firing rate representations.

    Directory of Open Access Journals (Sweden)

    Tristan J Webb

    Full Text Available Representations in the cortex are often distributed with graded firing rates in the neuronal populations. The firing rate probability distribution of each neuron to a set of stimuli is often exponential or gamma. In processes in the brain, such as decision-making, that are influenced by the noise produced by the close to random spike timings of each neuron for a given mean rate, the noise with this graded type of representation may be larger than with the binary firing rate distribution that is usually investigated. In integrate-and-fire simulations of an attractor decision-making network, we show that the noise is indeed greater for a given sparseness of the representation for graded, exponential, than for binary firing rate distributions. The greater noise was measured by faster escaping times from the spontaneous firing rate state when the decision cues are applied, and this corresponds to faster decision or reaction times. The greater noise was also evident as less stability of the spontaneous firing state before the decision cues are applied. The implication is that spiking-related noise will continue to be a factor that influences processes such as decision-making, signal detection, short-term memory, and memory recall even with the quite large networks found in the cerebral cortex. In these networks there are several thousand recurrent collateral synapses onto each neuron. The greater noise with graded firing rate distributions has the advantage that it can increase the speed of operation of cortical circuitry.

  5. Angular Rate Sensing with GyroWheel Using Genetic Algorithm Optimized Neural Networks.

    Science.gov (United States)

    Zhao, Yuyu; Zhao, Hui; Huo, Xin; Yao, Yu

    2017-07-22

    GyroWheel is an integrated device that can provide three-axis control torques and two-axis angular rate sensing for small spacecrafts. Large tilt angle of its rotor and de-tuned spin rate lead to a complex and non-linear dynamics as well as difficulties in measuring angular rates. In this paper, the problem of angular rate sensing with the GyroWheel is investigated. Firstly, a simplified rate sensing equation is introduced, and the error characteristics of the method are analyzed. According to the analysis results, a rate sensing principle based on torque balance theory is developed, and a practical way to estimate the angular rates within the whole operating range of GyroWheel is provided by using explicit genetic algorithm optimized neural networks. The angular rates can be determined by the measurable values of the GyroWheel (including tilt angles, spin rate and torque coil currents), the weights and the biases of the neural networks. Finally, the simulation results are presented to illustrate the effectiveness of the proposed angular rate sensing method with GyroWheel.

  6. A General Rate K/N Convolutional Decoder Based on Neural Networks with Stopping Criterion

    Directory of Open Access Journals (Sweden)

    Johnny W. H. Kao

    2009-01-01

    Full Text Available A novel algorithm for decoding a general rate K/N convolutional code based on recurrent neural network (RNN is described and analysed. The algorithm is introduced by outlining the mathematical models of the encoder and decoder. A number of strategies for optimising the iterative decoding process are proposed, and a simulator was also designed in order to compare the Bit Error Rate (BER performance of the RNN decoder with the conventional decoder that is based on Viterbi Algorithm (VA. The simulation results show that this novel algorithm can achieve the same bit error rate and has a lower decoding complexity. Most importantly this algorithm allows parallel signal processing, which increases the decoding speed and accommodates higher data rate transmission. These characteristics are inherited from a neural network structure of the decoder and the iterative nature of the algorithm, that outperform the conventional VA algorithm.

  7. Structural and functional social network attributes moderate the association of self-rated health with mental health in midlife and older adults.

    Science.gov (United States)

    Windsor, Tim D; Rioseco, Pilar; Fiori, Katherine L; Curtis, Rachel G; Booth, Heather

    2016-01-01

    Social relationships are multifaceted, and different social network components can operate via different processes to influence well-being. This study examined associations of social network structure and relationship quality (positive and negative social exchanges) with mental health in midlife and older adults. The focus was on both direct associations of network structure and relationship quality with mental health, and whether these social network attributes moderated the association of self-rated health (SRH) with mental health. Analyses were based on survey data provided by 2001 (Mean age = 65, SD = 8.07) midlife and older adults. We used Latent Class Analysis (LCA) to classify participants into network types based on network structure (partner status, network size, contact frequency, and activity engagement), and used continuous measures of positive and negative social exchanges to operationalize relationship quality. Regression analysis was used to test moderation. LCA revealed network types generally consistent with those reported in previous studies. Participants in more diverse networks reported better mental health than those categorized into a restricted network type after adjustment for age, sex, education, and employment status. Analysis of moderation indicated that those with poorer SRH were less likely to report poorer mental health if they were classified into more diverse networks. A similar moderation effect was also evident for positive exchanges. The findings suggest that both quantity and quality of social relationships can play a role in buffering against the negative implications of physical health decline for mental health.

  8. Modeling and Model Predictive Power and Rate Control of Wireless Communication Networks

    Directory of Open Access Journals (Sweden)

    Cunwu Han

    2014-01-01

    Full Text Available A novel power and rate control system model for wireless communication networks is presented, which includes uncertainties, input constraints, and time-varying delays in both state and control input. A robust delay-dependent model predictive power and rate control method is proposed, and the state feedback control law is obtained by solving an optimization problem that is derived by using linear matrix inequality (LMI techniques. Simulation results are given to illustrate the effectiveness of the proposed method.

  9. Packetized Predictive Control for Rate-Limited Networks via Sparse Representation

    DEFF Research Database (Denmark)

    Nagahara, Masaaki; Quevedo, Daniel; Østergaard, Jan

    2012-01-01

    controller and the plant input. To achieve robustness with respect to dropouts, the controller transmits data packets containing plant input predictions, which minimize a finite horizon cost function. In our formulation, we design sparse packets for rate-limited networks, by adopting an an ℓ0 optimization...

  10. Training a multilayer neural network for the Euro-dollar (EUR/ USD) exchange rate

    National Research Council Canada - National Science Library

    Jaime Alberto Villamil Torres; Jesús Alberto Delgado Rivera

    2010-01-01

    ... (as first approximation) a random walk. This paper reports the results of using ANNs for Euro/USD exchange rate trading and the usefulness of the algorithm for chemotaxis leading to training networks thereby maximising an objective function re predicting a trader’s profits. JEL: F310, C450.

  11. The association between social networks and self-rated risk of HIV ...

    African Journals Online (AJOL)

    This study describes the social networks of secondary school students in Moshi Municipality, and their association with self-rated risk of human immunodeficiency virus (HIV) infection. A cross-sectional analytical study was conducted among 300 students aged 15–24 years in 5 secondary schools in Moshi, Tanzania.

  12. Choosing optimum noise figure and data rate in wireless sensor network radio transceivers

    NARCIS (Netherlands)

    Dutta, R.; van der Zee, Ronan A.R.; Bentum, Marinus Jan; Kokkeler, Andre B.J.

    2011-01-01

    To reduce the energy consumption in wireless sensor network transceivers, we propose an approach which combines two tradeoffs. The first tradeoff is between the receiver sensitivity and transmitter output power. The second one is the duty cycle and data rate of the transceiver. The combined approach

  13. Estimation of mutation rates from paternity cases using a Bayesian network

    DEFF Research Database (Denmark)

    Vicard, P.; Dawid, A.P.; Mortera, J.

    and paternal mutation rates, while allowing a wide variety of mutation models. A Bayesian network is constructed to facilitate computation of the likelihood function for the mutation parameters. It can process both full and summary genotypic information, from both complete putative father-mother-child triplets...

  14. Depression and unemployment incidence rate evolution in Portugal, 1995-2013: General Practitioner Sentinel Network data.

    Science.gov (United States)

    Rodrigues, Ana Paula; Sousa-Uva, Mafalda; Fonseca, Rita; Marques, Sara; Pina, Nuno; Matias-Dias, Carlos

    2017-11-17

    Quantify, for both genders, the correlation between the depression incidence rate and the unemployment rate in Portugal between 1995 and 2013. An ecological study was developed to correlate the evolution of the depression incidence rates estimated by the General Practitioner Sentinel Network and the annual unemployment rates provided by the National Statistical Institute in official publications. There was a positive correlation between the depression incidence rate and the unemployment rate in Portugal, which was significant only for males (R2 = 0.83, p = 0.04). For this gender, an increase of 37 new cases of depression per 100,000 inhabitants was estimated for each 1% increase in the unemployment rate between 1995 and 2013. Although the study design does not allow the establishment of a causal association between unemployment and depression, the results suggest that the evolution of unemployment in Portugal may have had a significant impact on the level of mental health of the Portuguese, especially among men.

  15. Impact of dynamic rate coding aspects of mobile phone networks on forensic voice comparison.

    Science.gov (United States)

    Alzqhoul, Esam A S; Nair, Balamurali B T; Guillemin, Bernard J

    2015-09-01

    Previous studies have shown that landline and mobile phone networks are different in their ways of handling the speech signal, and therefore in their impact on it. But the same is also true of the different networks within the mobile phone arena. There are two major mobile phone technologies currently in use today, namely the global system for mobile communications (GSM) and code division multiple access (CDMA) and these are fundamentally different in their design. For example, the quality of the coded speech in the GSM network is a function of channel quality, whereas in the CDMA network it is determined by channel capacity (i.e., the number of users sharing a cell site). This paper examines the impact on the speech signal of a key feature of these networks, namely dynamic rate coding, and its subsequent impact on the task of likelihood-ratio-based forensic voice comparison (FVC). Surprisingly, both FVC accuracy and precision are found to be better for both GSM- and CDMA-coded speech than for uncoded. Intuitively one expects FVC accuracy to increase with increasing coded speech quality. This trend is shown to occur for the CDMA network, but, surprisingly, not for the GSM network. Further, in respect to comparisons between these two networks, FVC accuracy for CDMA-coded speech is shown to be slightly better than for GSM-coded speech, particularly when the coded-speech quality is high, but in terms of FVC precision the two networks are shown to be very similar. Copyright © 2015 The Chartered Society of Forensic Sciences. Published by Elsevier Ireland Ltd. All rights reserved.

  16. CRRT: Congestion-Aware and Rate-Controlled Reliable Transport in Wireless Sensor Networks

    Science.gov (United States)

    Alam, Muhammad Mahbub; Hong, Choong Seon

    For successful data collection in wireless sensor networks, it is important to ensure that the required delivery ratio is maintained while keeping a fair rate for every sensor. Furthermore, emerging high-rate applications might require complete reliability and the transfer of large volume of data, where persistent congestion might occur. These requirements demand a complete but efficient solution for data transport in sensor networks which reliably transports data from many sources to one or more sinks, avoids congestion and maintains fairness. In this paper, we propose congestion-aware and rate-controlled reliable transport (CRRT), an efficient and low-overhead data transport mechanism for sensor networks. CRRT uses efficient MAC retransmission to increase one-hop reliability and end-to-end retransmission for loss recovery. It also controls the total rate of the sources centrally, avoids the congestion in the bottleneck based on congestion notifications from intermediate nodes and centrally assigns the rate to the sources based on rate assignment policy of the applications. Performance of CRRT is evaluated in NS-2 and simulation results demonstrate the effectiveness of CRRT.

  17. Fine-Grained Rate Shaping for Video Streaming over Wireless Networks

    Directory of Open Access Journals (Sweden)

    Chen Tsuhan

    2004-01-01

    Full Text Available Video streaming over wireless networks faces challenges of time-varying packet loss rate and fluctuating bandwidth. In this paper, we focus on streaming precoded video that is both source and channel coded. Dynamic rate shaping has been proposed to “shape” the precompressed video to adapt to the fluctuating bandwidth. In our earlier work, rate shaping was extended to shape the channel coded precompressed video, and to take into account the time-varying packet loss rate as well as the fluctuating bandwidth of the wireless networks. However, prior work on rate shaping can only adjust the rate oarsely. In this paper, we propose “fine-grained rate shaping (FGRS” to allow for bandwidth adaptation over a wide range of bandwidth and packet loss rate in fine granularities. The video is precoded with fine granularity scalability (FGS followed by channel coding. Utilizing the fine granularity property of FGS and channel coding, FGRS selectively drops part of the precoded video and still yields decodable bit-stream at the decoder. Moreover, FGRS optimizes video streaming rather than achieves heuristic objectives as conventional methods. A two-stage rate-distortion (RD optimization algorithm is proposed for FGRS. Promising results of FGRS are shown.

  18. Managing CSCL Activity through networking models

    Directory of Open Access Journals (Sweden)

    Luis Casillas

    2014-04-01

    Full Text Available This study aims at managing activity carried out in Computer-Supported Collaborative Learning (CSCL environments. We apply an approach that gathers and manages the knowledge underlying huge data structures, resulting from collaborative interaction among participants and stored as activity logs. Our method comprises a variety of important issues and aspects, such as: deep understanding of collaboration among participants in workgroups, definition of an ontology for providing meaning to isolated data manifestations, discovering of knowledge structures built in huge amounts of data stored in log files, and development of high-semantic indicators to describe diverse primitive collaborative acts, and binding these indicators to formal descriptions defined in the collaboration ontology; besides our method includes gathering collaboration indicators from web forums using natural language processing (NLP techniques.

  19. Collaborative Event-Driven Coverage and Rate Allocation for Event Miss-Ratio Assurances in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Ozgur Sanli H

    2010-01-01

    Full Text Available Wireless sensor networks are often required to provide event miss-ratio assurance for a given event type. To meet such assurances along with minimum energy consumption, this paper shows how a node's activation and rate assignment is dependent on its distance to event sources, and proposes a practical coverage and rate allocation (CORA protocol to exploit this dependency in realistic environments. Both uniform event distribution and nonuniform event distribution are considered and the notion of ideal correlation distance around a clusterhead is introduced for on-duty node selection. In correlation distance guided CORA, rate assignment assists coverage scheduling by determining which nodes should be activated for minimizing data redundancy in transmission. Coverage scheduling assists rate assignment by controlling the amount of overlap among sensing regions of neighboring nodes, thereby providing sufficient data correlation for rate assignment. Extensive simulation results show that CORA meets the required event miss-ratios in realistic environments. CORA's joint coverage scheduling and rate allocation reduce the total energy expenditure by 85%, average battery energy consumption by 25%, and the overhead of source coding up to 90% as compared to existing rate allocation techniques.

  20. Intelligent Soft Computing on Forex: Exchange Rates Forecasting with Hybrid Radial Basis Neural Network

    Directory of Open Access Journals (Sweden)

    Lukas Falat

    2016-01-01

    Full Text Available This paper deals with application of quantitative soft computing prediction models into financial area as reliable and accurate prediction models can be very helpful in management decision-making process. The authors suggest a new hybrid neural network which is a combination of the standard RBF neural network, a genetic algorithm, and a moving average. The moving average is supposed to enhance the outputs of the network using the error part of the original neural network. Authors test the suggested model on high-frequency time series data of USD/CAD and examine the ability to forecast exchange rate values for the horizon of one day. To determine the forecasting efficiency, they perform a comparative statistical out-of-sample analysis of the tested model with autoregressive models and the standard neural network. They also incorporate genetic algorithm as an optimizing technique for adapting parameters of ANN which is then compared with standard backpropagation and backpropagation combined with K-means clustering algorithm. Finally, the authors find out that their suggested hybrid neural network is able to produce more accurate forecasts than the standard models and can be helpful in eliminating the risk of making the bad decision in decision-making process.

  1. Intelligent Soft Computing on Forex: Exchange Rates Forecasting with Hybrid Radial Basis Neural Network.

    Science.gov (United States)

    Falat, Lukas; Marcek, Dusan; Durisova, Maria

    2016-01-01

    This paper deals with application of quantitative soft computing prediction models into financial area as reliable and accurate prediction models can be very helpful in management decision-making process. The authors suggest a new hybrid neural network which is a combination of the standard RBF neural network, a genetic algorithm, and a moving average. The moving average is supposed to enhance the outputs of the network using the error part of the original neural network. Authors test the suggested model on high-frequency time series data of USD/CAD and examine the ability to forecast exchange rate values for the horizon of one day. To determine the forecasting efficiency, they perform a comparative statistical out-of-sample analysis of the tested model with autoregressive models and the standard neural network. They also incorporate genetic algorithm as an optimizing technique for adapting parameters of ANN which is then compared with standard backpropagation and backpropagation combined with K-means clustering algorithm. Finally, the authors find out that their suggested hybrid neural network is able to produce more accurate forecasts than the standard models and can be helpful in eliminating the risk of making the bad decision in decision-making process.

  2. Max-Min Optimality of Service Rate Control in Closed Queueing Networks

    KAUST Repository

    Xia, Li

    2013-04-01

    In this technical note, we discuss the optimality properties of service rate control in closed Jackson networks. We prove that when the cost function is linear to a particular service rate, the system performance is monotonic w.r.t. (with respect to) that service rate and the optimal value of that service rate can be either maximum or minimum (we call it Max-Min optimality); When the second-order derivative of the cost function w.r.t. a particular service rate is always positive (negative), which makes the cost function strictly convex (concave), the optimal value of such service rate for the performance maximization (minimization) problem can be either maximum or minimum. To the best of our knowledge, this is the most general result for the optimality of service rates in closed Jackson networks and all the previous works only involve the first conclusion. Moreover, our result is also valid for both the state-dependent and load-dependent service rates, under both the time-average and customer-average performance criteria.

  3. Persistent activity in neural networks with dynamic synapses.

    Directory of Open Access Journals (Sweden)

    Omri Barak

    2007-02-01

    Full Text Available Persistent activity states (attractors, observed in several neocortical areas after the removal of a sensory stimulus, are believed to be the neuronal basis of working memory. One of the possible mechanisms that can underlie persistent activity is recurrent excitation mediated by intracortical synaptic connections. A recent experimental study revealed that connections between pyramidal cells in prefrontal cortex exhibit various degrees of synaptic depression and facilitation. Here we analyze the effect of synaptic dynamics on the emergence and persistence of attractor states in interconnected neural networks. We show that different combinations of synaptic depression and facilitation result in qualitatively different network dynamics with respect to the emergence of the attractor states. This analysis raises the possibility that the framework of attractor neural networks can be extended to represent time-dependent stimuli.

  4. Topological quantum computing with a very noisy network and local error rates approaching one percent.

    Science.gov (United States)

    Nickerson, Naomi H; Li, Ying; Benjamin, Simon C

    2013-01-01

    A scalable quantum computer could be built by networking together many simple processor cells, thus avoiding the need to create a single complex structure. The difficulty is that realistic quantum links are very error prone. A solution is for cells to repeatedly communicate with each other and so purify any imperfections; however prior studies suggest that the cells themselves must then have prohibitively low internal error rates. Here we describe a method by which even error-prone cells can perform purification: groups of cells generate shared resource states, which then enable stabilization of topologically encoded data. Given a realistically noisy network (≥10% error rate) we find that our protocol can succeed provided that intra-cell error rates for initialisation, state manipulation and measurement are below 0.82%. This level of fidelity is already achievable in several laboratory systems.

  5. Nash Equilibrium of an Energy Saving Strategy with Dual Rate Transmission in Wireless Regional Area Network

    Directory of Open Access Journals (Sweden)

    Zhanqiang Huo

    2017-01-01

    Full Text Available Wireless regional area network (WRAN adopts centralized network architecture and is currently one of the most typical cognitive radio networks. In order to reduce the energy consumption of the communication networks with the constraint of spectrum resource utilization, a working sleep mechanism is introduced into the base station (BS, and a novel energy saving strategy with dual rate transmission is proposed. Combining the multiple-vacation queue and priority queue, using the quasi-birth-death process and the matrix-geometric solution method, we assess the average latency and the forced termination probability of secondary user packets, as well as the energy saving ratio and the channel utilization of system. Based on the revenue-expenditure structure, a profit function is built, and then the Nash equilibrium behavior and the socially optimal behavior are investigated. With the help of the particle swarm optimization, an intelligent optimization algorithm to search the socially optimal arrival rate of secondary user packets is presented. In order to unify the arrival rates of secondary user packets with Nash equilibrium and social optimization, a reasonable pricing policy is formulated. In addition, system experiments are carried out to verify the effectiveness of the energy saving strategy and the rationality of the pricing policy.

  6. Cognitive Multiple-Antenna Network with Outage and Rate Margins at the Primary System

    DEFF Research Database (Denmark)

    Maham, Behrouz; Popovski, Petar

    2015-01-01

    for the primary base station (BS): space-time coding, antenna selection, and beamforming, each of them with different channel information requirements. We first consider the case in which the primary BS uses a fixed rate and we analyze the outage probability. In high-SNR scenario, we derive closed-form asymptotic...... BS and introduce a suitable rate margin and a consistent requirement for primary throughput, for which we determine the outage probability. To be able to accommodate the secondary network, a rate margin is assumed at the primary link. We calculate the exact outage probabilities and average throughput...

  7. Power consumption analysis of constant bit rate video transmission over 3G networks

    DEFF Research Database (Denmark)

    Ukhanova, Ann; Belyaev, Evgeny; Wang, Le

    2012-01-01

    This paper presents an analysis of the power consumption of video data transmission with constant bit rate over 3G mobile wireless networks. The work includes the description of the radio resource control transition state machine in 3G networks, followed by a detailed power consumption analysis...... for the 3GPP transition state machine that allows to decrease power consumption on a mobile device taking signaling traffic, buffer size and latency restrictions into account. Furthermore, we discuss the gain in power consumption vs. PSNR for transmitted video and show the possibility of performing power...... consumption management based on the requirements for the video quality....

  8. Power consumption analysis of constant bit rate data transmission over 3G mobile wireless networks

    DEFF Research Database (Denmark)

    Wang, Le; Ukhanova, Ann; Belyaev, Evgeny

    2011-01-01

    This paper presents the analysis of the power consumption of data transmission with constant bit rate over 3G mobile wireless networks. Our work includes the description of the transition state machine in 3G networks, followed by the detailed energy consumption analysis and measurement results...... of the radio link power consumption. Based on these description and analysis, we propose power consumption model. The power model was evaluated on the smartphone Nokia N900, which follows a 3GPP Release 5 and 6 supporting HSDPA/HSPA data bearers. Further we propose method of parameters selection for 3GPP...... transition state machine that allows to decrease power consumption on the mobile device....

  9. Residue Geometry Networks: A Rigidity-Based Approach to the Amino Acid Network and Evolutionary Rate Analysis

    Science.gov (United States)

    Fokas, Alexander S.; Cole, Daniel J.; Ahnert, Sebastian E.; Chin, Alex W.

    2016-09-01

    Amino acid networks (AANs) abstract the protein structure by recording the amino acid contacts and can provide insight into protein function. Herein, we describe a novel AAN construction technique that employs the rigidity analysis tool, FIRST, to build the AAN, which we refer to as the residue geometry network (RGN). We show that this new construction can be combined with network theory methods to include the effects of allowed conformal motions and local chemical environments. Importantly, this is done without costly molecular dynamics simulations required by other AAN-related methods, which allows us to analyse large proteins and/or data sets. We have calculated the centrality of the residues belonging to 795 proteins. The results display a strong, negative correlation between residue centrality and the evolutionary rate. Furthermore, among residues with high closeness, those with low degree were particularly strongly conserved. Random walk simulations using the RGN were also successful in identifying allosteric residues in proteins involved in GPCR signalling. The dynamic function of these residues largely remain hidden in the traditional distance-cutoff construction technique. Despite being constructed from only the crystal structure, the results in this paper suggests that the RGN can identify residues that fulfil a dynamical function.

  10. Connecting African Activism with Global Networks: ICTs and South ...

    African Journals Online (AJOL)

    Connecting African Activism with Global Networks: ICTs and South African Social Movements. Herman Wasserman. Abstract. No Abstract Available Africa Development Vol. XXX (1&2) 2005: 163-182. Article Metrics. Metrics Loading ... Metrics powered by PLOS ALM · http://dx.doi.org/10.4314/ad.v30i1.22218 · AJOL African ...

  11. Designing a dynamic network based approach for asset management activities

    NARCIS (Netherlands)

    Volker, L.; Scharpff, J.; De Weerdt, M.M.; Herder, P.M.

    2012-01-01

    Transportation networks are important public infrastructures because they enable economic and social activity. Trends in contracting the maintenance of such assets have caused a shift in governance from a public body to market-like arrangements and changed the roles and responsibilities among asset

  12. Microgrids in Active Network Management-Part I

    DEFF Research Database (Denmark)

    Palizban, Omid; Kauhaniemia, Kimmo; Guerrero, Josep M.

    2014-01-01

    The microgrid concept has been closely investigated and implemented by numerous experts worldwide. The first part of this paper describes the principles of microgrid design, considering the operational concepts and requirements arising from participation in active network management. Over the last...

  13. Active ageing roadmap - a collaborative networks contribution to demographic sustainability

    NARCIS (Netherlands)

    Camarinha-Matos, L.M.; Afsarmanesh, H.

    2010-01-01

    The application of the collaborative networks paradigm, and a new generation of collaboration-support platforms and tools, is a promising approach to supporting active ageing, and facilitating better use of the talents and potential of retired or retiring senior professionals. As such, collaborative

  14. Restructuring the crystalline cellulose hydrogen bond network enhances its depolymerization rate

    Science.gov (United States)

    Shishir P.S. Chundawat; Giovanni Bellesia; Nirmal Uppugundla; Leonardo da Costa Sousa; Dahai Gao; Albert M. Cheh; Umesh P. Agarwal; Christopher M. Bianchetti; George N. Phillips; Paul Langan; Venkatesh Balan; S. Gnanakaran; Bruce E. Dale

    2011-01-01

    Conversion of lignocellulose to biofuels is partly inefficient due to the deleterious impact of cellulose crystallinity on enzymatic saccharification. We demonstrate how the synergistic activity of cellulases was enhanced by altering the hydrogen bond network within crystalline cellulose fibrils. We provide a molecular-scale explanation of these phenomena through...

  15. Predicting changes in volcanic activity through modelling magma ascent rate.

    Science.gov (United States)

    Thomas, Mark; Neuberg, Jurgen

    2013-04-01

    It is a simple fact that changes in volcanic activity happen and in retrospect they are easy to spot, the dissimilar eruption dynamics between an effusive and explosive event are not hard to miss. However to be able to predict such changes is a much more complicated process. To cause altering styles of activity we know that some part or combination of parts within the system must vary with time, as if there is no physical change within the system, why would the change in eruptive activity occur? What is unknown is which parts or how big a change is needed. We present the results of a suite of conduit flow models that aim to answer these questions by assessing the influence of individual model parameters such as the dissolved water content or magma temperature. By altering these variables in a systematic manner we measure the effect of the changes by observing the modelled ascent rate. We use the ascent rate as we believe it is a very important indicator that can control the style of eruptive activity. In particular, we found that the sensitivity of the ascent rate to small changes in model parameters surprising. Linking these changes to observable monitoring data in a way that these data could be used as a predictive tool is the ultimate goal of this work. We will show that changes in ascent rate can be estimated by a particular type of seismicity. Low frequency seismicity, thought to be caused by the brittle failure of melt is often linked with the movement of magma within a conduit. We show that acceleration in the rate of low frequency seismicity can correspond to an increase in the rate of magma movement and be used as an indicator for potential changes in eruptive activity.

  16. Network 13 partnership to improve the influenza, pneumococcal pneumonia, and hepatitis B vaccination rates among dialysis patients.

    Science.gov (United States)

    Duval, Linda; George, Cheryl; Hedrick, Nellie; Woodruff, Sandra; Kleinpeter, Myra A

    2011-01-01

    Vaccinations are available for primary prevention of many infections in adults. Morbidity and mortality from invasive diseases such as influenza and Streptococcus pneumoniae (pneumococcus) remain high and may be largely preventable by vaccination of high-risk adults, including dialysis patients. The current 23-valent vaccine-efficacious, with a low adverse event profile-is widely available. Revaccination is also recommended in patients with immunocompromising conditions, including chronic kidney disease. Despite having many opportunities to be vaccinated, adult hemodialysis and peritoneal dialysis patients are often missed During the recent H1N1 influenza outbreak, we conducted a performance improvement project to increase the vaccination rates for pneumococcal pneumonia, hepatitis B, and influenza, with a special focus on prevention. The project included an education phase, baseline assessment of vaccination rates, intervention, and a follow-up assessment of vaccination rates. The geographic jurisdiction of ESRD Network 13 encompasses the states of Arkansas, Louisiana, and Oklahoma. At the beginning of the network-wide project, the documented state-specific rates for influenza immunization were below the average influenza immunization rates for adults reported by Centers for Disease Control and Prevention and far below its target for adults. Our improvement project incorporated educational interventions to improve patient acceptance of vaccinations, educational interventions to improve staff participation in quality improvement activities, and improved techniques of quality improvement data collection and analysis by participants. During this project, the immunization rates for hepatitis B and pneumococcal pneumonia were also reviewed. At project's conclusion, improvement was demonstrated in all three focus areas, with statistically significant improvements noted in both influenza and pneumococcus vaccination rates. The use of educational interventions to improve

  17. A Geometric Method for Model Reduction of Biochemical Networks with Polynomial Rate Functions.

    Science.gov (United States)

    Samal, Satya Swarup; Grigoriev, Dima; Fröhlich, Holger; Weber, Andreas; Radulescu, Ovidiu

    2015-12-01

    Model reduction of biochemical networks relies on the knowledge of slow and fast variables. We provide a geometric method, based on the Newton polytope, to identify slow variables of a biochemical network with polynomial rate functions. The gist of the method is the notion of tropical equilibration that provides approximate descriptions of slow invariant manifolds. Compared to extant numerical algorithms such as the intrinsic low-dimensional manifold method, our approach is symbolic and utilizes orders of magnitude instead of precise values of the model parameters. Application of this method to a large collection of biochemical network models supports the idea that the number of dynamical variables in minimal models of cell physiology can be small, in spite of the large number of molecular regulatory actors.

  18. Predicting forest insect flight activity: A Bayesian network approach.

    Science.gov (United States)

    Pawson, Stephen M; Marcot, Bruce G; Woodberry, Owen G

    2017-01-01

    Daily flight activity patterns of forest insects are influenced by temporal and meteorological conditions. Temperature and time of day are frequently cited as key drivers of activity; however, complex interactions between multiple contributing factors have also been proposed. Here, we report individual Bayesian network models to assess the probability of flight activity of three exotic insects, Hylurgus ligniperda, Hylastes ater, and Arhopalus ferus in a managed plantation forest context. Models were built from 7,144 individual hours of insect sampling, temperature, wind speed, relative humidity, photon flux density, and temporal data. Discretized meteorological and temporal variables were used to build naïve Bayes tree augmented networks. Calibration results suggested that the H. ater and A. ferus Bayesian network models had the best fit for low Type I and overall errors, and H. ligniperda had the best fit for low Type II errors. Maximum hourly temperature and time since sunrise had the largest influence on H. ligniperda flight activity predictions, whereas time of day and year had the greatest influence on H. ater and A. ferus activity. Type II model errors for the prediction of no flight activity is improved by increasing the model's predictive threshold. Improvements in model performance can be made by further sampling, increasing the sensitivity of the flight intercept traps, and replicating sampling in other regions. Predicting insect flight informs an assessment of the potential phytosanitary risks of wood exports. Quantifying this risk allows mitigation treatments to be targeted to prevent the spread of invasive species via international trade pathways.

  19. Low Duty-Cycling MAC Protocol for Low Data-Rate Medical Wireless Body Area Networks

    Directory of Open Access Journals (Sweden)

    Chongqing Zhang

    2017-05-01

    Full Text Available Wireless body area networks (WBANs are severely energy constrained, and how to improve the energy efficiency so as to prolong the network lifetime as long as possible is one of the most important goals of WBAN research. Low data-rate WBANs are promising to cut down the energy consumption and extend the network lifetime. Considering the characteristics and demands of low data-rate WBANs, a low duty-cycling medium access control (MAC protocol is specially designed for this kind of WBAN in this paper. Longer superframes are exploited to cut down the energy consumed on the transmissions and receptions of redundant beacon frames. Insertion time slots are embedded into the inactive part of a superframe to deliver the frames and satisfy the quality of service (QoS requirements. The number of the data subsections in an insertion time slot can be adaptively adjusted so as to accommodate low data-rate WBANs with different traffic. Simulation results show that the proposed MAC protocol performs well under the condition of low data-rate monitoring traffic.

  20. Localized adenosine signaling provides fine-tuned negative feedback over a wide dynamic range of neocortical network activities

    Science.gov (United States)

    Richardson, Magnus J. E.

    2014-01-01

    Although the patterns of activity produced by neocortical networks are now better understood, how these states are activated, sustained, and terminated still remains unclear. Negative feedback by the endogenous neuromodulator adenosine may potentially play an important role, as it can be released by activity and there is dense A1 receptor expression in the neocortex. Using electrophysiology, biosensors, and modeling, we have investigated the properties of adenosine signaling during physiological and pathological network activity in rat neocortical slices. Both low- and high-rate network activities were reduced by A1 receptor activation and enhanced by block of A1 receptors, consistent with activity-dependent adenosine release. Since the A1 receptors were neither saturated nor completely unoccupied during either low- or high-rate activity, adenosine signaling provides a negative-feedback mechanism with a wide dynamic range. Modeling and biosensor experiments show that during high-rate activity increases in extracellular adenosine concentration are highly localized and are uncorrelated over short distances that are certainly adenosine release during low-rate activity, although it is present, is probably a consequence of small localized increases in adenosine concentration that are rapidly diminished by diffusion and active removal mechanisms. Saturation of such removal mechanisms when higher concentrations of adenosine are released results in the accumulation of inosine, explaining the strong purine signal during high-rate activity. PMID:25392170

  1. Multichannel activity propagation across an engineered axon network

    Science.gov (United States)

    Chen, H. Isaac; Wolf, John A.; Smith, Douglas H.

    2017-04-01

    Objective. Although substantial progress has been made in mapping the connections of the brain, less is known about how this organization translates into brain function. In particular, the massive interconnectivity of the brain has made it difficult to specifically examine data transmission between two nodes of the connectome, a central component of the ‘neural code.’ Here, we investigated the propagation of multiple streams of asynchronous neuronal activity across an isolated in vitro ‘connectome unit.’ Approach. We used the novel technique of axon stretch growth to create a model of a long-range cortico-cortical network, a modular system consisting of paired nodes of cortical neurons connected by axon tracts. Using optical stimulation and multi-electrode array recording techniques, we explored how input patterns are represented by cortical networks, how these representations shift as they are transmitted between cortical nodes and perturbed by external conditions, and how well the downstream node distinguishes different patterns. Main results. Stimulus representations included direct, synaptic, and multiplexed responses that grew in complexity as the distance between the stimulation source and recorded neuron increased. These representations collapsed into patterns with lower information content at higher stimulation frequencies. With internodal activity propagation, a hierarchy of network pathways, including latent circuits, was revealed using glutamatergic blockade. As stimulus channels were added, divergent, non-linear effects were observed in local versus distant network layers. Pairwise difference analysis of neuronal responses suggested that neuronal ensembles generally outperformed individual cells in discriminating input patterns. Significance. Our data illuminate the complexity of spiking activity propagation in cortical networks in vitro, which is characterized by the transformation of an input into myriad outputs over several network layers

  2. Monitoring of fetal heart rate and uterine activity

    NARCIS (Netherlands)

    Graatsma, E.M.

    2010-01-01

    In this thesis a renewed monitoring technique for fetal heart rate (FHR) and uterine activity has been investigated. Through non-invasive measurements of electrical signals as recorded from the maternal abdomen, both the fetal-electrocardiogram (fECG) and uterine electrohysterogram (EHG) can be

  3. Effect of water activity on rates of serpentinization of olivine

    Science.gov (United States)

    Lamadrid, Hector M.; Rimstidt, J. Donald; Schwarzenbach, Esther M.; Klein, Frieder; Ulrich, Sarah; Dolocan, Andrei; Bodnar, Robert J.

    2017-07-01

    The hydrothermal alteration of mantle rocks (referred to as serpentinization) occurs in submarine environments extending from mid-ocean ridges to subduction zones. Serpentinization affects the physical and chemical properties of oceanic lithosphere, represents one of the major mechanisms driving mass exchange between the mantle and the Earth's surface, and is central to current origin of life hypotheses as well as the search for microbial life on the icy moons of Jupiter and Saturn. In spite of increasing interest in the serpentinization process by researchers in diverse fields, the rates of serpentinization and the controlling factors are poorly understood. Here we use a novel in situ experimental method involving olivine micro-reactors and show that the rate of serpentinization is strongly controlled by the salinity (water activity) of the reacting fluid and demonstrate that the rate of serpentinization of olivine slows down as salinity increases and H2O activity decreases.

  4. Time-Efficient High-Rate Data Flooding in One-Dimensional Acoustic Underwater Sensor Networks

    Directory of Open Access Journals (Sweden)

    Jae Kyun Kwon

    2015-10-01

    Full Text Available Because underwater communication environments have poor characteristics, such as severe attenuation, large propagation delays and narrow bandwidths, data is normally transmitted at low rates through acoustic waves. On the other hand, as high traffic has recently been required in diverse areas, high rate transmission has become necessary. In this paper, transmission/reception timing schemes that maximize the time axis use efficiency to improve the resource efficiency for high rate transmission are proposed. The excellence of the proposed scheme is identified by examining the power distributions by node, rate bounds, power levels depending on the rates and number of nodes, and network split gains through mathematical analysis and numerical results. In addition, the simulation results show that the proposed scheme outperforms the existing packet train method.

  5. Microgrids in Active Network Management-Part II

    DEFF Research Database (Denmark)

    Palizban, Omid; Kauhaniemi, Kimmo; Guerrero, Josep M.

    2014-01-01

    The development of distribution networks for participation in active network management (ANM) and smart grids is introduced using the microgrid concept. In recent years, this issue has been researched and implemented by many experts. The second part of this paper describes those developed......, following planned or unplanned transitions to island mode, microgrids may develop instability. For this reason, the paper addresses the principles behind island-detection methods, black-start operation, fault management, and protection systems, along with a comprehensive review of power quality. Finally...

  6. Dialysis Facility and Network Factors Associated With Low Kidney Transplantation Rates Among United States Dialysis Facilities

    Science.gov (United States)

    Patzer, R. E.; Plantinga, L.; Krisher, J.; Pastan, S. O.

    2014-01-01

    Variability in transplant rates between different dialysis units has been noted, yet little is known about facility-level factors associated with low standardized transplant ratios (STRs) across the United States End-stage Renal Disease (ESRD) Network regions. We analyzed Centers for Medicare & Medicaid Services Dialysis Facility Report data from 2007 to 2010 to examine facility-level factors associated with low STRs using multivariable mixed models. Among 4098 dialysis facilities treating 305 698 patients, there was wide variability in facility-level STRs across the 18 ESRD Networks. Four-year average STRs ranged from 0.69 (95% confidence interval [CI]: 0.64–0.73) in Network 6 (Southeastern Kidney Council) to 1.61 (95% CI: 1.47–1.76) in Network 1 (New England). Factors significantly associated with a lower STR (p dialysis were associated with higher STRs. The lowest performing dialysis facilities were in the Southeastern United States. Understanding the modifiable facility-level factors associated with low transplant rates may inform interventions to improve access to transplantation. PMID:24891272

  7. Data Aggregation Based on Overlapping Rate of Sensing Area in Wireless Sensor Networks.

    Science.gov (United States)

    Tang, Xiaolan; Xie, Hua; Chen, Wenlong; Niu, Jianwei; Wang, Shuhang

    2017-06-29

    Wireless sensor networks are required in smart applications to provide accurate control, where the high density of sensors brings in a large quantity of redundant data. In order to reduce the waste of limited network resources, data aggregation is utilized to avoid redundancy forwarding. However, most of aggregation schemes reduce information accuracy and prolong end-to-end delay when eliminating transmission overhead. In this paper, we propose a data aggregation scheme based on overlapping rate of sensing area, namely AggOR, aiming for energy-efficient data collection in wireless sensor networks with high information accuracy. According to aggregation rules, gathering nodes are selected from candidate parent nodes and appropriate neighbor nodes considering a preset threshold of overlapping rate of sensing area. Therefore, the collected data in a gathering area are highly correlated, and a large amount of redundant data could be cleaned. Meanwhile, AggOR keeps the original entropy by only deleting the duplicated data. Experiment results show that compared with others, AggOR has a high data accuracy and a short end-to-end delay with a similar network lifetime.

  8. Using dynamic line rating to minimize curtailment of wind power connected to rural power networks

    Energy Technology Data Exchange (ETDEWEB)

    Schell, Peter [Ampacimon SA, Angleur (Belgium); Lambin, Jean-Jacques [Elia, Brussels (Belgium); Godard, Bertrand; Nguyen, Huu-Minh; Lilien, J.L. [Liege Univ. (Belgium). ULG Montefiore Inst.

    2011-07-01

    Elia, the Belgian TSO, is aiming to minimize curtailment of wind power plants connected to its 70kV rural network to the absolute minimum by using Dynamic Line Rating in combination with advanced flow simulation. This combination allows Elia to use its network assets to their real time maximum, without increasing risk and decreasing the security of supply. In situations like the one described below, where it's possible to control the flow in near real-time via curtailment it becomes possible to use all of the extra capacity available via Dynamic Line Rating. On average more then 30% extra capacity is available but this figure can easily increase to 100% extra capacity as soon as there is more than 4 m/s wind perpendicular to the line. (orig.)

  9. Recursive Estimation for Dynamical Systems with Different Delay Rates Sensor Network and Autocorrelated Process Noises

    Directory of Open Access Journals (Sweden)

    Jianxin Feng

    2014-01-01

    Full Text Available The recursive estimation problem is studied for a class of uncertain dynamical systems with different delay rates sensor network and autocorrelated process noises. The process noises are assumed to be autocorrelated across time and the autocorrelation property is described by the covariances between different time instants. The system model under consideration is subject to multiplicative noises or stochastic uncertainties. The sensor delay phenomenon occurs in a random way and each sensor in the sensor network has an individual delay rate which is characterized by a binary switching sequence obeying a conditional probability distribution. By using the orthogonal projection theorem and an innovation analysis approach, the desired recursive robust estimators including recursive robust filter, predictor, and smoother are obtained. Simulation results are provided to demonstrate the effectiveness of the proposed approaches.

  10. Training a multilayer neural network for the Euro-dollar (EUR/ USD exchange rate

    Directory of Open Access Journals (Sweden)

    Jaime Alberto Villamil Torres

    2010-04-01

    Full Text Available A mathematical tool or model for predicting how an economic variable like the exchange rate (relative price between two currencies will respond is a very important need for investors and policy-makers. Most current techniques are based on statistics, particularly linear time series theory. Artificial neural networks (ANNs are mathematical models which try to emulate biological neural networks’ parallelism and nonlinearity; these models have been successfully applied in Economics and Engineering since the 1980s. ANNs appear to be an alternative for modelling the behaviour of financial variables which resemble (as first approximation a random walk. This paper reports the results of using ANNs for Euro/USD exchange rate trading and the usefulness of the algorithm for chemotaxis leading to training networks thereby maximising an objective function re predicting a trader’s profits. JEL: F310, C450.

  11. High solar activity predictions through an artificial neural network

    Science.gov (United States)

    Orozco-Del-Castillo, M. G.; Ortiz-Alemán, J. C.; Couder-Castañeda, C.; Hernández-Gómez, J. J.; Solís-Santomé, A.

    The effects of high-energy particles coming from the Sun on human health as well as in the integrity of outer space electronics make the prediction of periods of high solar activity (HSA) a task of significant importance. Since periodicities in solar indexes have been identified, long-term predictions can be achieved. In this paper, we present a method based on an artificial neural network to find a pattern in some harmonics which represent such periodicities. We used data from 1973 to 2010 to train the neural network, and different historical data for its validation. We also used the neural network along with a statistical analysis of its performance with known data to predict periods of HSA with different confidence intervals according to the three-sigma rule associated with solar cycles 24-26, which we found to occur before 2040.

  12. Activity-Driven Influence Maximization in Social Networks

    DEFF Research Database (Denmark)

    Saleem, Muhammad Aamir; Kumar, Rohit; Calders, Toon

    2017-01-01

    in to locations. Previous work on finding influential nodes in such networks mainly concentrate on the static structure imposed by the interactions or are based on fixed models for which parameters are learned using the interactions. In two recent works, however, we proposed an alternative activity data......-driven approach based on the identification of influence propagation patterns. In the first work, we identify so-called information-channels to model potential pathways for information spread, while the second work exploits how users in a location-based social network check in to locations in order to identify...... influential locations. To make our algorithms scalable, approximate versions based on sketching techniques from the data streams domain have been developed. Experiments show that in this way it is possible to efficiently find good seed sets for influence propagation in social networks....

  13. SBMLsqueezer: A CellDesigner plug-in to generate kinetic rate equations for biochemical networks

    Directory of Open Access Journals (Sweden)

    Schröder Adrian

    2008-04-01

    Full Text Available Abstract Background The development of complex biochemical models has been facilitated through the standardization of machine-readable representations like SBML (Systems Biology Markup Language. This effort is accompanied by the ongoing development of the human-readable diagrammatic representation SBGN (Systems Biology Graphical Notation. The graphical SBML editor CellDesigner allows direct translation of SBGN into SBML, and vice versa. For the assignment of kinetic rate laws, however, this process is not straightforward, as it often requires manual assembly and specific knowledge of kinetic equations. Results SBMLsqueezer facilitates exactly this modeling step via automated equation generation, overcoming the highly error-prone and cumbersome process of manually assigning kinetic equations. For each reaction the kinetic equation is derived from the stoichiometry, the participating species (e.g., proteins, mRNA or simple molecules as well as the regulatory relations (activation, inhibition or other modulations of the SBGN diagram. Such information allows distinctions between, for example, translation, phosphorylation or state transitions. The types of kinetics considered are numerous, for instance generalized mass-action, Hill, convenience and several Michaelis-Menten-based kinetics, each including activation and inhibition. These kinetics allow SBMLsqueezer to cover metabolic, gene regulatory, signal transduction and mixed networks. Whenever multiple kinetics are applicable to one reaction, parameter settings allow for user-defined specifications. After invoking SBMLsqueezer, the kinetic formulas are generated and assigned to the model, which can then be simulated in CellDesigner or with external ODE solvers. Furthermore, the equations can be exported to SBML, LaTeX or plain text format. Conclusion SBMLsqueezer considers the annotation of all participating reactants, products and regulators when generating rate laws for reactions. Thus, for

  14. Meditation leads to reduced default mode network activity beyond an active task.

    Science.gov (United States)

    Garrison, Kathleen A; Zeffiro, Thomas A; Scheinost, Dustin; Constable, R Todd; Brewer, Judson A

    2015-09-01

    Meditation has been associated with relatively reduced activity in the default mode network, a brain network implicated in self-related thinking and mind wandering. However, previous imaging studies have typically compared meditation to rest, despite other studies having reported differences in brain activation patterns between meditators and controls at rest. Moreover, rest is associated with a range of brain activation patterns across individuals that has only recently begun to be better characterized. Therefore, in this study we compared meditation to another active cognitive task, both to replicate the findings that meditation is associated with relatively reduced default mode network activity and to extend these findings by testing whether default mode activity was reduced during meditation, beyond the typical reductions observed during effortful tasks. In addition, prior studies had used small groups, whereas in the present study we tested these hypotheses in a larger group. The results indicated that meditation is associated with reduced activations in the default mode network, relative to an active task, for meditators as compared to controls. Regions of the default mode network showing a Group × Task interaction included the posterior cingulate/precuneus and anterior cingulate cortex. These findings replicate and extend prior work indicating that the suppression of default mode processing may represent a central neural process in long-term meditation, and they suggest that meditation leads to relatively reduced default mode processing beyond that observed during another active cognitive task.

  15. Automatic optimisation of gamma dose rate sensor networks: The DETECT Optimisation Tool

    DEFF Research Database (Denmark)

    Helle, K.B.; Müller, T.O.; Astrup, Poul

    2014-01-01

    Fast delivery of comprehensive information on the radiological situation is essential for decision-making in nuclear emergencies. Most national radiological agencies in Europe employ gamma dose rate sensor networks to monitor radioactive pollution of the atmosphere. Sensor locations were often ch....... The DOT runs on a server and can be accessed via common web browsers; it can also be installed locally. © 2014 Elsevier Ltd. All rights reserved...

  16. Impairment of GABA transporter GAT-1 terminates cortical recurrent network activity via enhanced phasic inhibition

    Directory of Open Access Journals (Sweden)

    Daniel Simon Razik

    2013-09-01

    Full Text Available In the central nervous system, GABA transporters (GATs very efficiently clear synaptically released GABA from the extracellular space, and thus exert a tight control on GABAergic inhibition. In neocortex, GABAergic inhibition is heavily recruited during recurrent phases of spontaneous action potential activity which alternate with neuronally quiet periods. Therefore, such activity should be quite sensitive to minute alterations of GAT function. Here, we explored the effects of a gradual impairment of GAT-1 and GAT-2/3 on spontaneous recurrent network activity – termed network bursts and silent periods – in organotypic slice cultures of rat neocortex. The GAT-1 specific antagonist NO-711 depressed activity already at nanomolar concentrations (IC50 for depression of spontaneous multiunit firing rate of 42 nM, reaching a level of 80% at 500-1000 nM. By contrast, the GAT-2/3 preferring antagonist SNAP-5114 had weaker and less consistent effects. Several lines of evidence pointed towards an enhancement of phasic GABAergic inhibition as the dominant activity-depressing mechanism: network bursts were drastically shortened, phasic GABAergic currents decayed slower, and neuronal excitability during ongoing activity was diminished. In silent periods, NO-711 had little effect on neuronal excitability or membrane resistance, quite in contrast to the effects of muscimol, a GABA mimetic which activates GABAA receptors tonically. Our results suggest that an enhancement of phasic GABAergic inhibition efficiently curtails cortical recurrent activity and may mediate antiepileptic effects of therapeutically relevant concentrations of GAT-1 antagonists.

  17. Network ethnopharmacological evaluation of the immunomodulatory activity of Withania somnifera.

    Science.gov (United States)

    Chandran, Uma; Patwardhan, Bhushan

    2017-02-02

    Withania somnifera (L.) Dunal (Ashwagandha, WS) is one of the extensively explored Ayurvedic botanicals. Several properties including immunomodulation, anti-cancer and neuro-protection of the botanical have been reported. Even though, in indigenous medicine, WS is well known for its immunomodulatory activity, the molecular mechanism of immunomodulation has not been elucidated. This study aimed the evaluation of the immunomodulatory effect of WS using network ethnopharmacology technique to elucidate the in silico molecular mechanism. Databases- DPED, UNPD, PubChem, Binding DB, ChEMBL, KEGG and STRING were used to gather information to develop the networks. The networks were constructed using Cytoscape 3.2.1. Data analysis was performed with the help of Excel pivot table and Cytoscape network analyzer tool. Investigation for WS immune modulation mechanism identified five bioactives that are capable of regulating 15 immune system pathways through 16 target proteins by bioactive-target and protein-protein interactions. The study also unveils the potential of withanolide-phytosterol combination to achieve effective immunomodulation and seven novel bioactive-immune target combinations. The study elucidated an in silico molecular mechanism of immunomodulation of WS. It unveils the potential of withanolide-phytosterol combination to achieve a better immunomodulation. Experimental validation of the network findings would aid in understanding the rationale behind WS immunomodulation as well as aid in bioactive formulation based drug discovery. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  18. 3D Filament Network Segmentation with Multiple Active Contours

    Science.gov (United States)

    Xu, Ting; Vavylonis, Dimitrios; Huang, Xiaolei

    2014-03-01

    Fluorescence microscopy is frequently used to study two and three dimensional network structures formed by cytoskeletal polymer fibers such as actin filaments and microtubules. While these cytoskeletal structures are often dilute enough to allow imaging of individual filaments or bundles of them, quantitative analysis of these images is challenging. To facilitate quantitative, reproducible and objective analysis of the image data, we developed a semi-automated method to extract actin networks and retrieve their topology in 3D. Our method uses multiple Stretching Open Active Contours (SOACs) that are automatically initialized at image intensity ridges and then evolve along the centerlines of filaments in the network. SOACs can merge, stop at junctions, and reconfigure with others to allow smooth crossing at junctions of filaments. The proposed approach is generally applicable to images of curvilinear networks with low SNR. We demonstrate its potential by extracting the centerlines of synthetic meshwork images, actin networks in 2D TIRF Microscopy images, and 3D actin cable meshworks of live fission yeast cells imaged by spinning disk confocal microscopy.

  19. A Double Rate Localization Algorithm with One Anchor for Multi-Hop Underwater Acoustic Networks.

    Science.gov (United States)

    Gao, Jingjie; Shen, Xiaohong; Zhao, Ruiqin; Mei, Haodi; Wang, Haiyan

    2017-04-28

    Localization is a basic issue for underwater acoustic networks (UANs). Currently, most localization algorithms only perform well in one-hop networks or need more anchors which are not suitable for the underwater environment. In this paper, we proposed a double rate localization algorithm with one anchor for multi-hop underwater acoustic networks (DRL). The algorithm firstly presents a double rate scheme which separates the localization procedure into two modes to increase the ranging accuracy in multi-hop UANs while maintaining the transmission rate. Then an optimal selection scheme of reference nodes was proposed to reduce the influence of references' topology on localization performance. The proposed DRL algorithm can be used in the multi-hop UANs to increase the localization accuracy and reduce the usage of anchor nodes. The simulation and experimental results demonstrated that the proposed DRL algorithm has a better localization performance than the previous algorithms in many aspects such as accuracy and communication cost, and is more suitable to the underwater environment.

  20. Labor Mobility, Social Network Effects, and Innovative Activity

    DEFF Research Database (Denmark)

    Kongsted, Hans Christian; Rønde, Thomas; Kaiser, Ulrich

    . This relationship is stronger if workers join from innovative firms. We also find evidence for positive feedback from workers who leave for an innovative firm, presumably because the worker who left stays in contact with their former colleagues. This implies that the positive feedback (“social network effects......We study the mapping between labor mobility and industrial innovative activity for the population of R&D active Danish firms observed between 1999 and 2004. Our study documents a positive relationship between the number of workers who join a firm and the firm’s innovative activity...

  1. A method to estimate emission rates from industrial stacks based on neural networks.

    Science.gov (United States)

    Olcese, Luis E; Toselli, Beatriz M

    2004-11-01

    This paper presents a technique based on artificial neural networks (ANN) to estimate pollutant rates of emission from industrial stacks, on the basis of pollutant concentrations measured on the ground. The ANN is trained on data generated by the ISCST3 model, widely accepted for evaluation of dispersion of primary pollutants as a part of an environmental impact study. Simulations using theoretical values and comparison with field data are done, obtaining good results in both cases at predicting emission rates. The application of this technique would allow the local environment authority to control emissions from industrial plants without need of performing direct measurements inside the plant. copyright 2004 Elsevier Ltd.

  2. The Brain on Art: Intense Aesthetic Experience Activates the Default Mode Network

    Directory of Open Access Journals (Sweden)

    Edward A Vessel

    2012-04-01

    Full Text Available Aesthetic responses to visual art comprise multiple types of experiences, from sensation and perception to emotion and self-reflection. Moreover, aesthetic experience is highly individual, with observers varying significantly in their responses to the same artwork. Combining fMRI and behavioral analysis of individual differences in aesthetic response, we identify two distinct patterns of neural activity exhibited by different subnetworks. Activity increased linearly with observers’ ratings (4-level scale in sensory (occipito-temporal regions. Activity in the striatum also varied linearly with ratings, with below-baseline activations for low-rated artworks. In contrast, a network of frontal regions showed a step-like increase only for the most moving artworks (4 ratings and non-differential activity for all others. This included several regions belonging to the default mode network previously associated with self-referential mentation. Our results suggest that aesthetic experience involves the integration of sensory and emotional reactions in a manner linked with their personal relevance.

  3. Water Absorption Rate Prediction of PMMA and Its Composites Using BP Neural Network

    Directory of Open Access Journals (Sweden)

    Chen Kui

    2016-01-01

    Full Text Available Referring to water absorption rate of poly (methyl methacrylate (PMMA and its composites is hard to obtain under some working conditions, BP neural network prediction model was constructed. Regarding water absorption rate predictions of exfoliated PMMA/MMT nanocomposites in 0.1 mol/L H2SO4 solution, 0.1 mol/L NaOH solution and deionized water respectively as examples, the applicability of model established in water absorption rate prediction of PMMA and its composites was researched. The results show that the relative errors between prediction value obtained from model established and actual value of water absorption rate of composites soaking 63min in three kinds of mediums are 1.50%, 0.47% and 1.04% respectively, prediction accuracy is higher than that (relative errors are 3.89%, 3.40% and 4.43% respectively obtained from GM (1, 1 model obviously. BP neural network can be used to predict water absorption rate of PMMA and its composites.

  4. Passive and Active Monitoring on a High Performance Research Network.

    Energy Technology Data Exchange (ETDEWEB)

    Matthews, Warren

    2001-05-01

    The bold network challenges described in ''Internet End-to-end Performance Monitoring for the High Energy and Nuclear Physics Community'' presented at PAM 2000 have been tackled by the intrepid administrators and engineers providing the network services. After less than a year, the BaBar collaboration has collected almost 100 million particle collision events in a database approaching 165TB (Tera=10{sup 12}). Around 20TB has been exported via the Internet to the BaBar regional center at IN2P3 in Lyon, France, for processing and around 40 TB of simulated events have been imported to SLAC from Lawrence Livermore National Laboratory (LLNL). An unforseen challenge has arisen due to recent events and highlighted security concerns at DoE funded labs. New rules and regulations suggest it is only a matter of time before many active performance measurements may not be possible between many sites. Yet, at the same time, the importance of understanding every aspect of the network and eradicating packet loss for high throughput data transfers has become apparent. Work at SLAC to employ passive monitoring using netflow and OC3MON is underway and techniques to supplement and possibly replace the active measurements are being considered. This paper will detail the special needs and traffic characterization of a remarkable research project, and how the networking hurdles have been resolved (or not!) to achieve the required high data throughput. Results from active and passive measurements will be compared, and methods for achieving high throughput and the effect on the network will be assessed along with tools that directly measure throughput and applications used to actually transfer data.

  5. A Energy-Saving Path-Shared Protection Based on Diversity Network Coding for Multi-rate Multicast in WDM Mesh Networks

    Science.gov (United States)

    Zheng, Danling; Lv, Lei; Liu, Huanlin

    2017-08-01

    For improving the survivability and energy saving of multi-rate multicast, a novel energy-saving path-shared protection based on diversity network coding (EPP-DNC) for multi-rate multicast in wavelength division multiplexing (WDM) mesh networks is proposed in the paper. In the EPP-DNC algorithm, diversity network coding on the source node for multi-rate multicast is adopted to reduce the coding energy consumption by avoiding network coding on the network's intermediate nodes. To decrease the transmission energy, shortest path shared based on heuristic is proposed to transmit the protection information for the request. To provision request's working paths efficiency, the working paths are routed on the preselected P-cycles with minimum required links and minimum energy consumption. Simulation results show that the proposed EPP-DNC can save energy consumption and improve bandwidth utilization.

  6. Spontaneous sigh rates during sedentary activity: watching television vs reading.

    Science.gov (United States)

    Hark, William T; Thompson, William M; McLaughlin, Timothy E; Wheatley, Lisa M; Platts-Mills, Thomas A E

    2005-02-01

    Spontaneous sighs are thought to play an important role in preventing atelectasis and in regulating airway tone. Recent studies have provided a mechanism by which expansion of the lungs could cause relaxation of smooth muscle. To investigate breathing patterns during 2 forms of sedentary behavior: reading and watching television. Breathing patterns were monitored for 1 to 2 hours to document respiratory rates and sigh rates. Each participant was monitored while reading and while watching a movie on videotape. During the first experiment (17 controls), metabolic rates were also measured. In the second experiment (18 controls and 9 patients with mild-to-moderate asthma), only breathing patterns were monitored. There were no significant differences in respiratory or metabolic rates between the 2 activities. In contrast, in the first experiment, 13 of 17 controls had lower sigh rates while watching a videotape than while reading (P watching a videotape (mean, 13.7 sighs per hour; range, 1.8-26.0 sighs per hour) than while reading (mean, 19.3 sighs per hour; range, 7.7-30.0 sighs per hour) (P watch television for 5 or more hours per day, breathing patterns during this time may be relevant to lung function. Our results demonstrate that prolonged periods of watching a videotape are associated with lower sigh rates than while reading. Further research is needed to determine whether these changes are relevant to increased bronchial reactivity.

  7. Position dependent rate dampening in any active hand controller

    Science.gov (United States)

    Gregory, William W. (Inventor); Kauffman, James W. (Inventor)

    1994-01-01

    A control system for an active hand controller, for example, uses a control stick connected to and controlled by a motor. Electronics are provided to control the motor to eliminate oscillations due to motor torque and high gain due to breakout at the control stick when the control stick is at about its null position. Both hardware as well as software implementations can provide position dependent dampening to the control sticks such that when the control stick is located about a null position, a higher rate of dampening is provided than when the control stick is located outside the null position, when a lower rate of dampening is provided. The system provides a stable active hand controller control stick without degraded force and feel characteristics of the system.

  8. The development trends of credit rating agencies activity in Russia

    Directory of Open Access Journals (Sweden)

    L. E. Galyaeva

    2016-01-01

    Full Text Available The process and the prospects of development of the rating industry in the country are examined in the article. The author analyzes the influence of sovereign Russian credit rating decrease by the world’s leading rating agencies at the beginning of 2015 on financial sector of the country. Politically motivated international credit rating agencies ratings hinder the development of the Russian financial system. That’s why particular attention is paid to the rejection of dependence on the international credit rating agencies ratings and the appearance of a new strong and powerful national credit agency on the Russian market. The problems concerned with speculative estimates of the Russian investment potential. The author points some possible ways to recover from the crisis by involving inner agencies instead of international ones. Special attention is devoted to the existent legislative modifications. Never the less, speaking about the prospects and the future of the leading agencies, it is significant that their work will be relevant in long term due to the increasing uncertainty of the external environment. Moreover the necessity of investing funds in different objects intensifies which leads to the investors and depositors needs of investing. The presented information may be interesting for further profound exploration of the issues, identify the range of problems to be solved by international ratings of the issuers and their securities. In addition, the information proposed in the article can be also served as a basis for further comparison of the activity of international and national agencies in terms of the services offered.

  9. Estrogen concentration affects its biodegradation rate in activated sludge.

    Science.gov (United States)

    Xu, Nan; Johnson, Andrew C; Jürgens, Monika D; Llewellyn, Neville R; Hankins, Nick P; Darton, Richard C

    2009-11-01

    The effect of concentration on the biodegradation rate of the steroid estrogens, estrone (E1) and 17-alpha-ethinylestradiol (EE2), was studied in batch and continuous-flow reactor systems using fresh activated sludge from two sewage treatment plants. Between the concentrations of 0.03 to 10 μg/L in the batch system no consistent difference was found in the biodegradation rates for either estrogen. The biodegradation half-life was 0.3 to 0.7 h for E1, and 1.5 to 4.4 h for EE2 at 15 to 20°C. However, at 100 μg/L, biodegradation rates for both estrogens decreased, with the half-life prolonged to around 2.5 h for E1 and 12 to 18 h for EE2. In continuous-flow experiments, over a 2 h residence time, 95% of E1 and 48% of EE2 were removed on average at 0.1 μg/L, whilst 52% of E1 and 20% of EE2 were removed at 100 μg/L. In general, spiking concentration of estrogens did not appear to affect biodegradation rates between the ng/L to low μg/L levels in activated sludge; however, the rates greatly slowed down when the concentration increased up to 100 μg/L. The results suggest activated sludge biodegradation studies with estrogens in the high μg/L levels could give misleading results and should be avoided.

  10. Nutrients interaction investigation to improve Monascus purpureus FTC5391 growth rate using Response Surface Methodology and Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Mohamad, R.

    2013-01-01

    Full Text Available Aims: Two vital factors, certain environmental conditions and nutrients as a source of energy are entailed for successful growth and reproduction of microorganisms. Manipulation of nutritional requirement is the simplest and most effectual strategy to stimulate and enhance the activity of microorganisms. Methodology and Results: In this study, response surface methodology (RSM and artificial neural network (ANN were employed to optimize the carbon and nitrogen sources in order to improve growth rate of Monascus purpureus FTC5391,a new local isolate. The best models for optimization of growth rate were a multilayer full feed-forward incremental back propagation network, and a modified response surface model using backward elimination. The optimum condition for cell mass production was: sucrose 2.5%, yeast extract 0.045%, casamino acid 0.275%, sodium nitrate 0.48%, potato starch 0.045%, dextrose 1%, potassium nitrate 0.57%. The experimental cell mass production using this optimal condition was 21 mg/plate/12days, which was 2.2-fold higher than the standard condition (sucrose 5%, yeast extract 0.15%, casamino acid 0.25%, sodium nitrate 0.3%, potato starch 0.2%, dextrose 1%, potassium nitrate 0.3%. Conclusion, significance and impact of study: The results of RSM and ANN showed that all carbon and nitrogen sources tested had significant effect on growth rate (P-value < 0.05. In addition the use of RSM and ANN alongside each other provided a proper growth prediction model.

  11. Modeling and Visualization of Human Activities for Multicamera Networks

    Directory of Open Access Journals (Sweden)

    Aswin C. Sankaranarayanan

    2009-01-01

    Full Text Available Multicamera networks are becoming complex involving larger sensing areas in order to capture activities and behavior that evolve over long spatial and temporal windows. This necessitates novel methods to process the information sensed by the network and visualize it for an end user. In this paper, we describe a system for modeling and on-demand visualization of activities of groups of humans. Using the prior knowledge of the 3D structure of the scene as well as camera calibration, the system localizes humans as they navigate the scene. Activities of interest are detected by matching models of these activities learnt a priori against the multiview observations. The trajectories and the activity index for each individual summarize the dynamic content of the scene. These are used to render the scene with virtual 3D human models that mimic the observed activities of real humans. In particular, the rendering framework is designed to handle large displays with a cluster of GPUs as well as reduce the cognitive dissonance by rendering realistic weather effects and illumination. We envision use of this system for immersive visualization as well as summarization of videos that capture group behavior.

  12. Ultrananocrystalline diamond thin films functionalized with therapeutically active collagen networks.

    Energy Technology Data Exchange (ETDEWEB)

    Huang, H.; Chen, M.; Bruno, P.; Lam, R.; Robinson, E.; Gruen, D.; Ho, D.; Materials Science Division; Northwestern Univ.

    2009-01-01

    The fabrication of biologically amenable interfaces in medicine bridges translational technologies with their surrounding biological environment. Functionalized nanomaterials catalyze this coalescence through the creation of biomimetic and active substrates upon which a spectrum of therapeutic elements can be delivered to adherent cells to address biomolecular processes in cancer, inflammation, etc. Here, we demonstrate the robust functionalization of ultrananocrystalline diamond (UNCD) with type I collagen and dexamethasone (Dex), an anti-inflammatory drug, to fabricate a hybrid therapeutically active substrate for localized drug delivery. UNCD oxidation coupled with a pH-mediated collagen adsorption process generated a comprehensive interface between the two materials, and subsequent Dex integration, activity, and elution were confirmed through inflammatory gene expression assays. These studies confer a translational relevance to the biofunctionalized UNCD in its role as an active therapeutic network for potent regulation of cellular activity toward applications in nanomedicine.

  13. Quantum delocalization of protons in the hydrogen bond network of an enzyme active site

    CERN Document Server

    Wang, Lu; Boxer, Steven G; Markland, Thomas E

    2015-01-01

    Enzymes utilize protein architectures to create highly specialized structural motifs that can greatly enhance the rates of complex chemical transformations. Here we use experiments, combined with ab initio simulations that exactly include nuclear quantum effects, to show that a triad of strongly hydrogen bonded tyrosine residues within the active site of the enzyme ketosteroid isomerase (KSI) facilitates quantum proton delocalization. This delocalization dramatically stabilizes the deprotonation of an active site tyrosine residue, resulting in a very large isotope effect on its acidity. When an intermediate analog is docked, it is incorporated into the hydrogen bond network, giving rise to extended quantum proton delocalization in the active site. These results shed light on the role of nuclear quantum effects in the hydrogen bond network that stabilizes the reactive intermediate of KSI, and the behavior of protons in biological systems containing strong hydrogen bonds.

  14. Reduced salience and default mode network activity in women with anorexia nervosa.

    Science.gov (United States)

    McFadden, Kristina L; Tregellas, Jason R; Shott, Megan E; Frank, Guido K W

    2014-05-01

    The neurobiology of anorexia nervosa is poorly understood. Neuronal networks contributing to action selection, self-regulation and interoception could contribute to pathologic eating and body perception in people with anorexia nervosa. We tested the hypothesis that the salience network (SN) and default mode network (DMN) would show decreased intrinsic activity in women with anorexia nervosa and those who had recovered from the disease compared to controls. The basal ganglia (BGN) and sensorimotor networks (SMN) were also investigated. Between January 2008 and January 2012, women with restricting-type anorexia nervosa, women who recovered from the disease and healthy control women completed functional magnetic resonance imaging during a conditioned stimulus task. Network activity was studied using independent component analysis. We studied 20 women with anorexia nervosa, 24 recovered women and 24 controls. Salience network activity in the anterior cingulate cortex was reduced in women with anorexia nervosa (p = 0.030; all results false-discovery rate- corrected) and recovered women (p = 0.039) compared to controls. Default mode network activity in the precuneus was reduced in women with anorexia compared to controls (p = 0.023). Sensorimotor network activity in the supplementary motor area (SMA; p = 0.008), and the left (p = 0.028) and right (p = 0.002) postcentral gyrus was reduced in women with anorexia compared to controls; SMN activity in the SMA (p = 0.019) and the right postcentral gyrus (p = 0.008) was reduced in women with anorexia compared to recovered women. There were no group differences in the BGN. Differences between patient and control populations (e.g., depression, anxiety, medication) are potential confounds, but were included as covariates. Reduced SN activity in women with anorexia nervosa and recovered women could be a trait-related biomarker or illness remnant, altering the drive to approach food. The alterations in the DMN and SMN observed only

  15. Neural network based semi-active control strategy for structural vibration mitigation with magnetorheological damper

    DEFF Research Database (Denmark)

    Bhowmik, Subrata

    2011-01-01

    This paper presents a neural network based semi-active control method for a rotary type magnetorheological (MR) damper. The characteristics of the MR damper are described by the classic Bouc-Wen model, and the performance of the proposed control method is evaluated in terms of a base exited shear...... frame structure. As demonstrated in the literature effective damping of flexible structures is obtained by a suitable combination of pure friction and negative damper stiffness. This damper model is rate-independent and fully described by the desired shape of the hysteresis loops or force...... mode of the structure. The neural network control is then developed to reproduce the desired force based on damper displacement and velocity as network input, and it is therefore referred to as an amplitude dependent model reference control method. An inverse model of the MR damper is needed...

  16. Triboelectric Nanogenerator Enabled Body Sensor Network for Self-Powered Human Heart-Rate Monitoring.

    Science.gov (United States)

    Lin, Zhiming; Chen, Jun; Li, Xiaoshi; Zhou, Zhihao; Meng, Keyu; Wei, Wei; Yang, Jin; Wang, Zhong Lin

    2017-09-26

    Heart-rate monitoring plays a critical role in personal healthcare management. A low-cost, noninvasive, and user-friendly heart-rate monitoring system is highly desirable. Here, a self-powered wireless body sensor network (BSN) system is developed for heart-rate monitoring via integration of a downy-structure-based triboelectric nanogenerator (D-TENG), a power management circuit, a heart-rate sensor, a signal processing unit, and Bluetooth module for wireless data transmission. By converting the inertia energy of human walking into electric power, a maximum power of 2.28 mW with total conversion efficiency of 57.9% was delivered at low operation frequency, which is capable of immediately and sustainably driving the highly integrated BSN system. The acquired heart-rate signal by the sensor would be processed in the signal process circuit, sent to an external device via the Bluetooth module, and displayed on a personal cell phone in a real-time manner. Moreover, by combining a TENG-based generator and a TENG-based sensor, an all-TENG-based wireless BSN system was developed, realizing continuous and self-powered heart-rate monitoring. This work presents a potential method for personal heart-rate monitoring, featured as being self-powered, cost-effective, noninvasive, and user-friendly.

  17. Depression and unemployment incidence rate evolution in Portugal, 1995–2013: General Practitioner Sentinel Network data

    Science.gov (United States)

    Rodrigues, Ana Paula; Sousa-Uva, Mafalda; Fonseca, Rita; Marques, Sara; Pina, Nuno; Matias-Dias, Carlos

    2017-01-01

    ABSTRACT OBJECTIVE Quantify, for both genders, the correlation between the depression incidence rate and the unemployment rate in Portugal between 1995 and 2013. METHODS An ecological study was developed to correlate the evolution of the depression incidence rates estimated by the General Practitioner Sentinel Network and the annual unemployment rates provided by the National Statistical Institute in official publications. RESULTS There was a positive correlation between the depression incidence rate and the unemployment rate in Portugal, which was significant only for males (R2 = 0.83, p = 0.04). For this gender, an increase of 37 new cases of depression per 100,000 inhabitants was estimated for each 1% increase in the unemployment rate between 1995 and 2013. CONCLUSIONS Although the study design does not allow the establishment of a causal association between unemployment and depression, the results suggest that the evolution of unemployment in Portugal may have had a significant impact on the level of mental health of the Portuguese, especially among men. PMID:29166442

  18. Congestion-Aware Routing and Fuzzy-based Rate Controller for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    M. Hatamian

    2016-04-01

    Full Text Available In this paper, congestion-aware routing and fuzzy-based rate controller for wireless sensor networks (WSNs is proposed. The proposed method tries to make a distinction between locally generated data and transit data by using a priority-based mechanism which provides a novel queueing model. Furthermore, a novel congestion-aware routing using greedy approach is proposed. The proposed congestion-aware routing tries to find more affordable routes. Moreover, a fuzzy rate controller is utilized for rate controlling which uses two criteria as its inputs, including congestion score and buffer occupancy. These two parameters are based on total packet input rate, packet forwarding rate at MAC layer, number of packets in the queue buffer, and total buffer size at each node. As soon as the congestion is detected, the notification signal is sent to offspring nodes. As a result, they are able to adjust their data transmission rate. Simulation results clearly show that the implementation of the proposed method using a greedy approach and fuzzy logic has done significant reduction in terms of packet loss rate, end-to-end delay and average energy consumption.

  19. Active defense scheme against DDoS based on mobile agent and network control in network confrontation

    Science.gov (United States)

    Luo, Rong; Li, Junshan; Ye, Xia; Wang, Rui

    2013-03-01

    In order to effective defend DDoS attacks in network confrontation, an active defense scheme against DDoS is built based on Mobile Agent and network control. A distributed collaborative active defense model is constructed by using mobile agent technology and encapsulating a variety of DDoS defense techniques. Meanwhile the network control theory is applied to establish a network confrontation's control model for DDoS to control the active defense process. It provides a new idea to solve the DDoS problem.

  20. Effect and Analysis of Sustainable Cell Rate using MPEG video Traffic in ATM Networks

    Directory of Open Access Journals (Sweden)

    Sakshi Kaushal

    2006-04-01

    Full Text Available The broadband networks inhibit the capability to carry multiple types of traffic – voice, video and data, but these services need to be controlled according to the traffic contract negotiated at the time of the connection to maintain desired Quality of service. Such control techniques use traffic descriptors to evaluate its performance and effectiveness. In case of Variable Bit Rate (VBR services, Peak Cell Rate (PCR and its Cell Delay Variation Tolerance (CDVTPCR are mandatory descriptors. In addition to these, ATM Forum proposed Sustainable Cell Rate (SCR and its Cell delay variation tolerance (CDVTSCR. In this paper, we evaluated the impact of specific SCR and CDVTSCR values on the Usage Parameter Control (UPC performance in case of measured MPEG traffic for improving the efficiency

  1. Taurine activates GABAergic networks in the neocortex of immature mice

    Directory of Open Access Journals (Sweden)

    Bogdan Aurel Sava

    2014-02-01

    Full Text Available Although it has been suggested that taurine is the main endogenous neurotransmitter acting on glycine receptors, the implications of glycine receptor-mediated taurine actions on immature neocortical networks have not been addressed yet. To investigate the influence of taurine on the excitability of neuronal networks in the immature neocortex, we performed whole-cell patch-clamp recordings from visually identified pyramidal neurons and interneurons in coronal slices from C57Bl/6 and GAD67-GFP transgenic mice (postnatal days 2-4. In 46 % of the pyramidal neurons bath-application of taurine at concentrations ≥ 300 mM significantly enhanced the frequency of postsynaptic currents (PSCs by 744.3 ± 93.8 % (n = 120 cells. This taurine-induced increase of PSC frequency was abolished by 0.2 mM tetrodotoxine, 1 mM strychnine or 3 mM gabazine, but was unaffected by the glutamatergic antagonists 6-cyano-7-nitroquinoxaline-2,3-dione (CNQX and (± R(--3-(2-carboxypiperazine-4-yl-propyl-1-phosphonic acid (CPP, suggesting that taurine specifically activates GABAergic network activity projecting to pyramidal neurons. Cell-attached recordings revealed that taurine enhanced the frequency of action potentials in pyramidal neurons, indicating an excitatory action of the GABAergic PSCs. In order to identify the presynaptic targets of taurine we demonstrate that bath application of taurine induced in GAD67-GFP labeled interneurons an inward current that is mainly mediated by glycine receptors and can generate action potentials in these cells. We conclude from these results that taurine can enhance network excitability in the immature neocortex by selectively activating GABAergic interneurons via interactions with glycine receptors.

  2. Innovation diffusion on time-varying activity driven networks

    Science.gov (United States)

    Rizzo, Alessandro; Porfiri, Maurizio

    2016-01-01

    Since its introduction in the 1960s, the theory of innovation diffusion has contributed to the advancement of several research fields, such as marketing management and consumer behavior. The 1969 seminal paper by Bass [F.M. Bass, Manag. Sci. 15, 215 (1969)] introduced a model of product growth for consumer durables, which has been extensively used to predict innovation diffusion across a range of applications. Here, we propose a novel approach to study innovation diffusion, where interactions among individuals are mediated by the dynamics of a time-varying network. Our approach is based on the Bass' model, and overcomes key limitations of previous studies, which assumed timescale separation between the individual dynamics and the evolution of the connectivity patterns. Thus, we do not hypothesize homogeneous mixing among individuals or the existence of a fixed interaction network. We formulate our approach in the framework of activity driven networks to enable the analysis of the concurrent evolution of the interaction and individual dynamics. Numerical simulations offer a systematic analysis of the model behavior and highlight the role of individual activity on market penetration when targeted advertisement campaigns are designed, or a competition between two different products takes place.

  3. Sensory Conflict Disrupts Activity of the Drosophila Circadian Network

    Directory of Open Access Journals (Sweden)

    Ross E.F. Harper

    2016-11-01

    Full Text Available Periodic changes in light and temperature synchronize the Drosophila circadian clock, but the question of how the fly brain integrates these two input pathways to set circadian time remains unanswered. We explore multisensory cue combination by testing the resilience of the circadian network to conflicting environmental inputs. We show that misaligned light and temperature cycles can lead to dramatic changes in the daily locomotor activities of wild-type flies during and after exposure to sensory conflict. This altered behavior is associated with a drastic reduction in the amplitude of PERIOD (PER oscillations in brain clock neurons and desynchronization between light- and temperature-sensitive neuronal subgroups. The behavioral disruption depends heavily on the phase relationship between light and temperature signals. Our results represent a systematic quantification of multisensory integration in the Drosophila circadian system and lend further support to the view of the clock as a network of coupled oscillatory subunits.

  4. Platelet serotonin transporter function predicts default-mode network activity.

    Directory of Open Access Journals (Sweden)

    Christian Scharinger

    Full Text Available The serotonin transporter (5-HTT is abundantly expressed in humans by the serotonin transporter gene SLC6A4 and removes serotonin (5-HT from extracellular space. A blood-brain relationship between platelet and synaptosomal 5-HT reuptake has been suggested, but it is unknown today, if platelet 5-HT uptake can predict neural activation of human brain networks that are known to be under serotonergic influence.A functional magnetic resonance study was performed in 48 healthy subjects and maximal 5-HT uptake velocity (Vmax was assessed in blood platelets. We used a mixed-effects multilevel analysis technique (MEMA to test for linear relationships between whole-brain, blood-oxygen-level dependent (BOLD activity and platelet Vmax.The present study demonstrates that increases in platelet Vmax significantly predict default-mode network (DMN suppression in healthy subjects independent of genetic variation within SLC6A4. Furthermore, functional connectivity analyses indicate that platelet Vmax is related to global DMN activation and not intrinsic DMN connectivity.This study provides evidence that platelet Vmax predicts global DMN activation changes in healthy subjects. Given previous reports on platelet-synaptosomal Vmax coupling, results further suggest an important role of neuronal 5-HT reuptake in DMN regulation.

  5. Epidemic spreading on activity-driven networks with attractiveness

    Science.gov (United States)

    Pozzana, Iacopo; Sun, Kaiyuan; Perra, Nicola

    2017-10-01

    We study SIS epidemic spreading processes unfolding on a recent generalization of the activity-driven modeling framework. In this model of time-varying networks, each node is described by two variables: activity and attractiveness. The first describes the propensity to form connections, while the second defines the propensity to attract them. We derive analytically the epidemic threshold considering the time scale driving the evolution of contacts and the contagion as comparable. The solutions are general and hold for any joint distribution of activity and attractiveness. The theoretical picture is confirmed via large-scale numerical simulations performed considering heterogeneous distributions and different correlations between the two variables. We find that heterogeneous distributions of attractiveness alter the contagion process. In particular, in the case of uncorrelated and positive correlations between the two variables, heterogeneous attractiveness facilitates the spreading. On the contrary, negative correlations between activity and attractiveness hamper the spreading. The results presented contribute to the understanding of the dynamical properties of time-varying networks and their effects on contagion phenomena unfolding on their fabric.

  6. Default-mode-like network activation in awake rodents.

    Directory of Open Access Journals (Sweden)

    Jaymin Upadhyay

    Full Text Available During wakefulness and in absence of performing tasks or sensory processing, the default-mode network (DMN, an intrinsic central nervous system (CNS network, is in an active state. Non-human primate and human CNS imaging studies have identified the DMN in these two species. Clinical imaging studies have shown that the pattern of activity within the DMN is often modulated in various disease states (e.g., Alzheimer's, schizophrenia or chronic pain. However, whether the DMN exists in awake rodents has not been characterized. The current data provides evidence that awake rodents also possess 'DMN-like' functional connectivity, but only subsequent to habituation to what is initially a novel magnetic resonance imaging (MRI environment as well as physical restraint. Specifically, the habituation process spanned across four separate scanning sessions (Day 2, 4, 6 and 8. At Day 8, significant (p<0.05 functional connectivity was observed amongst structures such as the anterior cingulate (seed region, retrosplenial, parietal, and hippocampal cortices. Prior to habituation (Day 2, functional connectivity was only detected (p<0.05 amongst CNS structures known to mediate anxiety (i.e., anterior cingulate (seed region, posterior hypothalamic area, amygdala and parabracial nucleus. In relating functional connectivity between cingulate-default-mode and cingulate-anxiety structures across Days 2-8, a significant inverse relationship (r = -0.65, p = 0.0004 was observed between these two functional interactions such that increased cingulate-DMN connectivity corresponded to decreased cingulate anxiety network connectivity. This investigation demonstrates that the cingulate is an important component of both the rodent DMN-like and anxiety networks.

  7. Overexpression of cypin alters dendrite morphology, single neuron activity, and network properties via distinct mechanisms

    Science.gov (United States)

    Rodríguez, Ana R.; O’Neill, Kate M.; Swiatkowski, Przemyslaw; Patel, Mihir V.; Firestein, Bonnie L.

    2018-02-01

    Objective. This study investigates the effect that overexpression of cytosolic PSD-95 interactor (cypin), a regulator of synaptic PSD-95 protein localization and a core regulator of dendrite branching, exerts on the electrical activity of rat hippocampal neurons and networks. Approach. We cultured rat hippocampal neurons and used lipid-mediated transfection and lentiviral gene transfer to achieve high levels of cypin or cypin mutant (cypinΔPDZ PSD-95 non-binding) expression cellularly and network-wide, respectively. Main results. Our analysis revealed that although overexpression of cypin and cypinΔPDZ increase dendrite numbers and decrease spine density, cypin and cypinΔPDZ distinctly regulate neuronal activity. At the single cell level, cypin promotes decreases in bursting activity while cypinΔPDZ reduces sEPSC frequency and further decreases bursting compared to cypin. At the network level, by using the Fano factor as a measure of spike count variability, cypin overexpression results in an increase in variability of spike count, and this effect is abolished when cypin cannot bind PSD-95. This variability is also dependent on baseline activity levels and on mean spike rate over time. Finally, our spike sorting data show that overexpression of cypin results in a more complex distribution of spike waveforms and that binding to PSD-95 is essential for this complexity. Significance. Our data suggest that dendrite morphology does not play a major role in cypin action on electrical activity.

  8. Using convolutional neural networks for human activity classification on micro-Doppler radar spectrograms

    Science.gov (United States)

    Jordan, Tyler S.

    2016-05-01

    This paper presents the findings of using convolutional neural networks (CNNs) to classify human activity from micro-Doppler features. An emphasis on activities involving potential security threats such as holding a gun are explored. An automotive 24 GHz radar on chip was used to collect the data and a CNN (normally applied to image classification) was trained on the resulting spectrograms. The CNN achieves an error rate of 1.65 % on classifying running vs. walking, 17.3 % error on armed walking vs. unarmed walking, and 22 % on classifying six different actions.

  9. A Comparative Study of Neural Networks and ANFIS for Forecasting Attendance Rate of Soccer Games

    Directory of Open Access Journals (Sweden)

    Mehmet Şahin

    2017-11-01

    Full Text Available The main purpose of this study was to develop and apply a neural network (NN approach and an adaptive neuro-fuzzy inference system (ANFIS model for forecasting the attendance rates at soccer games. The models were designed based on the characteristics of the problem. Past real data was used. Training data was used for training the models, and the testing data was used for evaluating the performance of the forecasting models. The obtained forecasting results were compared to the actual data and to each other. To evaluate the performance of the models, two statistical indicators, Mean Absolute Deviation (MAD and mean absolute percent error (MAPE, were used. Based on the results, the proposed neural network approach and the ANFIS model were shown to be effective in forecasting attendance at soccer games. The neural network approach performed better than the ANFIS model. The main contribution of this study is to introduce two effective techniques for estimating attendance at sports games. This is the first attempt to use an ANFIS model for that purpose.

  10. The pairwise phase consistency in cortical network and its relationship with neuronal activation

    Directory of Open Access Journals (Sweden)

    Wang Daming

    2017-01-01

    Full Text Available Gamma-band neuronal oscillation and synchronization with the range of 30-90 Hz are ubiquitous phenomenon across numerous brain areas and various species, and correlated with plenty of cognitive functions. The phase of the oscillation, as one aspect of CTC (Communication through Coherence hypothesis, underlies various functions for feature coding, memory processing and behaviour performing. The PPC (Pairwise Phase Consistency, an improved coherence measure, statistically quantifies the strength of phase synchronization. In order to evaluate the PPC and its relationships with input stimulus, neuronal activation and firing rate, a simplified spiking neuronal network is constructed to simulate orientation columns in primary visual cortex. If the input orientation stimulus is preferred for a certain orientation column, neurons within this corresponding column will obtain higher firing rate and stronger neuronal activation, which consequently engender higher PPC values, with higher PPC corresponding to higher firing rate. In addition, we investigate the PPC in time resolved analysis with a sliding window.

  11. Joint sensor placement and power rating selection in energy harvesting wireless sensor networks

    KAUST Repository

    Bushnaq, Osama M.

    2017-11-02

    In this paper, the focus is on optimal sensor placement and power rating selection for parameter estimation in wireless sensor networks (WSNs). We take into account the amount of energy harvested by the sensing nodes, communication link quality, and the observation accuracy at the sensor level. In particular, the aim is to reconstruct the estimation parameter with minimum error at a fusion center under a system budget constraint. To achieve this goal, a subset of sensing locations is selected from a large pool of candidate sensing locations. Furthermore, the type of sensor to be placed at those locations is selected from a given set of sensor types (e.g., sensors with different power ratings). We further investigate whether it is better to install a large number of cheap sensors, a few expensive sensors or a combination of different sensor types at the optimal locations.

  12. Informatics technology mimics ecology: dense, mutualistic collaboration networks are associated with higher publication rates.

    Directory of Open Access Journals (Sweden)

    Marco D Sorani

    Full Text Available Information technology (IT adoption enables biomedical research. Publications are an accepted measure of research output, and network models can describe the collaborative nature of publication. In particular, ecological networks can serve as analogies for publication and technology adoption. We constructed network models of adoption of bioinformatics programming languages and health IT (HIT from the literature.We selected seven programming languages and four types of HIT. We performed PubMed searches to identify publications since 2001. We calculated summary statistics and analyzed spatiotemporal relationships. Then, we assessed ecological models of specialization, cooperativity, competition, evolution, biodiversity, and stability associated with publications.Adoption of HIT has been variable, while scripting languages have experienced rapid adoption. Hospital systems had the largest HIT research corpus, while Perl had the largest language corpus. Scripting languages represented the largest connected network components. The relationship between edges and nodes was linear, though Bioconductor had more edges than expected and Perl had fewer. Spatiotemporal relationships were weak. Most languages shared a bioinformatics specialization and appeared mutualistic or competitive. HIT specializations varied. Specialization was highest for Bioconductor and radiology systems. Specialization and cooperativity were positively correlated among languages but negatively correlated among HIT. Rates of language evolution were similar. Biodiversity among languages grew in the first half of the decade and stabilized, while diversity among HIT was variable but flat. Compared with publications in 2001, correlation with publications one year later was positive while correlation after ten years was weak and negative.Adoption of new technologies can be unpredictable. Spatiotemporal relationships facilitate adoption but are not sufficient. As with ecosystems, dense

  13. Extraction of elementary rate constants from global network analysis of E. coli central metabolism

    Directory of Open Access Journals (Sweden)

    Broderick Gordon

    2008-05-01

    Full Text Available Abstract Background As computational performance steadily increases, so does interest in extending one-particle-per-molecule models to larger physiological problems. Such models however require elementary rate constants to calculate time-dependent rate coefficients under physiological conditions. Unfortunately, even when in vivo kinetic data is available, it is often in the form of aggregated rate laws (ARL that do not specify the required elementary rate constants corresponding to mass-action rate laws (MRL. There is therefore a need to develop a method which is capable of automatically transforming ARL kinetic information into more detailed MRL rate constants. Results By incorporating proteomic data related to enzyme abundance into an MRL modelling framework, here we present an efficient method operating at a global network level for extracting elementary rate constants from experiment-based aggregated rate law (ARL models. The method combines two techniques that can be used to overcome the difficult properties in parameterization. The first, a hybrid MRL/ARL modelling technique, is used to divide the parameter estimation problem into sub-problems, so that the parameters of the mass action rate laws for each enzyme are estimated in separate steps. This reduces the number of parameters that have to be optimized simultaneously. The second, a hybrid algebraic-numerical simulation and optimization approach, is used to render some rate constants identifiable, as well as to greatly narrow the bounds of the other rate constants that remain unidentifiable. This is done by incorporating equality constraints derived from the King-Altman and Cleland method into the simulated annealing algorithm. We apply these two techniques to estimate the rate constants of a model of E. coli glycolytic pathways. The simulation and statistical results show that our innovative method performs well in dealing with the issues of high computation cost, stiffness, local

  14. Research on Mixed Data Rate and Format Transmission in WDM Networks

    Directory of Open Access Journals (Sweden)

    LI Hong-an

    2013-03-01

    Full Text Available To meet the growing data traffic demands in the telecommunication applications, the number of wavelengths is to be increased in a fiber-optic backbone of the telecommunication network. The exponential growth of internet services, transmission capacity is a tremendous challenge to networks.   Nowadays, 10 Gb/s transmission systems are being used for commercial applications.  At the same time, the non-linear effects such as FWM, SRS, XPM, SPM, and Dispersion are also increased, when the number of wavelengths passing through the single fiber is increased. The analysis of efficient modulation formats for   DWDM system and    long-haul transmission system, we go for various modulations for DWDM system. The maimum data rate for NRZ-OOK modulation format is 10 Gb/s. For RZ-OOK the maximum rate is 50 Gb/s.  Since RZ-OOK modulation uses twice the band width when compared to NRZ-OOK modulation. The modulation format is partially upgraded from OOK to PSK, the influence of OOK signals on the updated PSK signals must be considered when using multi-channel wavelength conversion. The PSK modulation is also analyzed.

  15. Neural Network for Determining Risk Rate of Post-Heart Stroke Patients

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    Oldřich Trenz

    2014-01-01

    Full Text Available The ischemic heart disease presents an important health problem that affects a great part of the population and is the cause of one third of all deaths in the Czech Republic. The availability of data describing the patients’ prognosis enables their further analysis, with the aim of lowering the patients’ risk, by proposing optimum treatment. The main reason for creating the neural network model is not only to automate the process of establishing the risk rate of patients suffering from ischemic heart disease, but also to adapt it for practical use in clinical conditions. Our aim is to identify especially the specific group of risk-rate patients whose well-timed preventive care can improve the quality and prolong the length of their lives.The aim of the paper is to propose a patient-parameter structure, using which we could create a suitable model based on a self-taught neural network. The emphasis is placed on identifying key descriptive parameters (in the form of a reduction of the available descriptive parameters that are crucial for identifying the required patients, and simultaneously to achieve a portability of the model among individual clinical workplaces (availability of parameters.

  16. Prediction of road traffic death rate using neural networks optimised by genetic algorithm.

    Science.gov (United States)

    Jafari, Seyed Ali; Jahandideh, Sepideh; Jahandideh, Mina; Asadabadi, Ebrahim Barzegari

    2015-01-01

    Road traffic injuries (RTIs) are realised as a main cause of public health problems at global, regional and national levels. Therefore, prediction of road traffic death rate will be helpful in its management. Based on this fact, we used an artificial neural network model optimised through Genetic algorithm to predict mortality. In this study, a five-fold cross-validation procedure on a data set containing total of 178 countries was used to verify the performance of models. The best-fit model was selected according to the root mean square errors (RMSE). Genetic algorithm, as a powerful model which has not been introduced in prediction of mortality to this extent in previous studies, showed high performance. The lowest RMSE obtained was 0.0808. Such satisfactory results could be attributed to the use of Genetic algorithm as a powerful optimiser which selects the best input feature set to be fed into the neural networks. Seven factors have been known as the most effective factors on the road traffic mortality rate by high accuracy. The gained results displayed that our model is very promising and may play a useful role in developing a better method for assessing the influence of road traffic mortality risk factors.

  17. Friendship Network Characteristics Are Associated with Physical Activity and Sedentary Behavior in Early Adolescence.

    Directory of Open Access Journals (Sweden)

    Jennifer Marks

    Full Text Available There is limited understanding of the association between peer social networks and physical activity (PA, sedentary and screen-related behaviors. This study reports on associations between personal network characteristics and these important health behaviors for early adolescents.Participants were 310 students, aged 11-13 years, from fifteen randomly selected Victorian primary schools (43% response rate. PA and sedentary behaviors were collected via accelerometer and self-report questionnaire, and anthropometric measures via trained researchers. Participants nominated up to fifteen friends, and described the frequency of interaction and perceived activity intensity of these friends. Personal network predictors were examined using regression modelling for PA and sedentary/screen behavior.Perceived activity levels of friends, and friendships with very frequent interaction were associated with outside-of-school PA and/or sedentary/screen time. Differences according to sex were also observed in the association between network characteristics and PA and sedentary time. A higher number of friends and greater proportion of same sex friends were associated with boys engaging in more moderate-to-vigorous PA outside of school hours. PA intensity during school-day breaks was positively associated with having a greater proportion of friends who played sports for girls, and a greater proportion of male friends for boys.Friendship network characteristics are associated with PA and sedentary/screen time in late childhood/early adolescence, and these associations differ by sex. The positive influence of very active peers may be a promising avenue to strengthen traditional interventions for the promotion of PA and reduction in screen time.

  18. Friendship Network Characteristics Are Associated with Physical Activity and Sedentary Behavior in Early Adolescence.

    Science.gov (United States)

    Marks, Jennifer; de la Haye, Kayla; Barnett, Lisa M; Allender, Steven

    2015-01-01

    There is limited understanding of the association between peer social networks and physical activity (PA), sedentary and screen-related behaviors. This study reports on associations between personal network characteristics and these important health behaviors for early adolescents. Participants were 310 students, aged 11-13 years, from fifteen randomly selected Victorian primary schools (43% response rate). PA and sedentary behaviors were collected via accelerometer and self-report questionnaire, and anthropometric measures via trained researchers. Participants nominated up to fifteen friends, and described the frequency of interaction and perceived activity intensity of these friends. Personal network predictors were examined using regression modelling for PA and sedentary/screen behavior. Perceived activity levels of friends, and friendships with very frequent interaction were associated with outside-of-school PA and/or sedentary/screen time. Differences according to sex were also observed in the association between network characteristics and PA and sedentary time. A higher number of friends and greater proportion of same sex friends were associated with boys engaging in more moderate-to-vigorous PA outside of school hours. PA intensity during school-day breaks was positively associated with having a greater proportion of friends who played sports for girls, and a greater proportion of male friends for boys. Friendship network characteristics are associated with PA and sedentary/screen time in late childhood/early adolescence, and these associations differ by sex. The positive influence of very active peers may be a promising avenue to strengthen traditional interventions for the promotion of PA and reduction in screen time.

  19. Friendship Network Characteristics Are Associated with Physical Activity and Sedentary Behavior in Early Adolescence

    Science.gov (United States)

    Marks, Jennifer; de la Haye, Kayla; Barnett, Lisa M; Allender, Steven

    2015-01-01

    Introduction There is limited understanding of the association between peer social networks and physical activity (PA), sedentary and screen-related behaviors. This study reports on associations between personal network characteristics and these important health behaviors for early adolescents. Methods Participants were 310 students, aged 11–13 years, from fifteen randomly selected Victorian primary schools (43% response rate). PA and sedentary behaviors were collected via accelerometer and self-report questionnaire, and anthropometric measures via trained researchers. Participants nominated up to fifteen friends, and described the frequency of interaction and perceived activity intensity of these friends. Personal network predictors were examined using regression modelling for PA and sedentary/screen behavior. Results Perceived activity levels of friends, and friendships with very frequent interaction were associated with outside-of-school PA and/or sedentary/screen time. Differences according to sex were also observed in the association between network characteristics and PA and sedentary time. A higher number of friends and greater proportion of same sex friends were associated with boys engaging in more moderate-to-vigorous PA outside of school hours. PA intensity during school-day breaks was positively associated with having a greater proportion of friends who played sports for girls, and a greater proportion of male friends for boys. Conclusion Friendship network characteristics are associated with PA and sedentary/screen time in late childhood/early adolescence, and these associations differ by sex. The positive influence of very active peers may be a promising avenue to strengthen traditional interventions for the promotion of PA and reduction in screen time. PMID:26709924

  20. Mapping epileptic activity: sources or networks for the clinicians?

    Directory of Open Access Journals (Sweden)

    Francesca ePittau

    2014-11-01

    Full Text Available Epileptic seizures of focal origin are classically considered to arise from a focal epileptogenic zone and then spread to other brain regions. This is a key concept for semiological electro-clinical correlations, localisation of relevant structural lesions and selection of patients for epilepsy surgery. Recent progresses in neuro-imaging and electro-physiology and combinations thereof have been validated as contributory tools for focus localization. In parallel, these techniques have revealed that widespread networks of brain regions, rather than a single epileptogenic region, are implicated in focal epileptic activity. Sophisticated multimodal imaging and analysis strategies of brain connectivity patterns have been developed to characterize the spatio-temporal relationships within these networks by combining the strength of both techniques to optimize spatial and temporal resolution with whole-brain coverage and directional connectivity. In this paper, we review the potential clinical contribution of these functional mapping techniques as well as invasive electrophysiology in humans and animal models for characterizing network connectivity.

  1. Connectivity, excitability and activity patterns in neuronal networks

    NARCIS (Netherlands)

    le Feber, Jakob; Stoyanova, Irina; Chiappalone, Michela

    2014-01-01

    Extremely synchronized firing patterns such as those observed in brain diseases like epilepsy may result from excessive network excitability. Although network excitability is closely related to (excitatory) connectivity, a direct measure for network excitability remains unavailable. Several methods

  2. Beyond blow-up in excitatory integrate and fire neuronal networks: Refractory period and spontaneous activity.

    Science.gov (United States)

    Cáceres, María J; Perthame, Benoît

    2014-06-07

    The Network Noisy Leaky Integrate and Fire equation is among the simplest model allowing for a self-consistent description of neural networks and gives a rule to determine the probability to find a neuron at the potential v. However, its mathematical structure is still poorly understood and, concerning its solutions, very few results are available. In the midst of them, a recent result shows blow-up in finite time for fully excitatory networks. The intuitive explanation is that each firing neuron induces a discharge of the others; thus increases the activity and consequently the discharge rate of the full network. In order to better understand the details of the phenomena and show that the equation is more complex and fruitful than expected, we analyze further the model. We extend the finite time blow-up result to the case when neurons, after firing, enter a refractory state for a given period of time. We also show that spontaneous activity may occur when, additionally, randomness is included on the firing potential VF in regimes where blow-up occurs for a fixed value of VF. Copyright © 2014 Elsevier Ltd. All rights reserved.

  3. Implications of synaptic biophysics for recurrent network dynamics and active memory.

    Science.gov (United States)

    Durstewitz, Daniel

    2009-10-01

    In cortical networks, synaptic excitation is mediated by AMPA- and NMDA-type receptors. NMDA differ from AMPA synaptic potentials with regard to peak current, time course, and a strong voltage-dependent nonlinearity. Here we illustrate based on empirical and computational findings that these specific biophysical properties may have profound implications for the dynamics of cortical networks, and via dynamics on cognitive functions like active memory. The discussion will be led along a minimal set of neural equations introduced to capture the essential dynamics of the various phenomena described. NMDA currents could establish cortical bistability and may provide the relatively constant synaptic drive needed to robustly maintain enhanced levels of activity during working memory epochs, freeing fast AMPA currents for other computational purposes. Perhaps more importantly, variations in NMDA synaptic input-due to their biophysical particularities-control the dynamical regime within which single neurons and networks reside. By provoking bursting, chaotic irregularity, and coherent oscillations their major effect may be on the temporal pattern of spiking activity, rather than on average firing rate. During active memory, neurons may thus be pushed into a spiking regime that harbors complex temporal structure, potentially optimal for the encoding and processing of temporal sequence information. These observations provide a qualitatively different view on the role of synaptic excitation in neocortical dynamics than entailed by many more abstract models. In this sense, this article is a plead for taking the specific biophysics of real neurons and synapses seriously when trying to account for the neurobiology of cognition.

  4. Death and rebirth of neural activity in sparse inhibitory networks

    Science.gov (United States)

    Angulo-Garcia, David; Luccioli, Stefano; Olmi, Simona; Torcini, Alessandro

    2017-05-01

    Inhibition is a key aspect of neural dynamics playing a fundamental role for the emergence of neural rhythms and the implementation of various information coding strategies. Inhibitory populations are present in several brain structures, and the comprehension of their dynamics is strategical for the understanding of neural processing. In this paper, we clarify the mechanisms underlying a general phenomenon present in pulse-coupled heterogeneous inhibitory networks: inhibition can induce not only suppression of neural activity, as expected, but can also promote neural re-activation. In particular, for globally coupled systems, the number of firing neurons monotonically reduces upon increasing the strength of inhibition (neuronal death). However, the random pruning of connections is able to reverse the action of inhibition, i.e. in a random sparse network a sufficiently strong synaptic strength can surprisingly promote, rather than depress, the activity of neurons (neuronal rebirth). Thus, the number of firing neurons reaches a minimum value at some intermediate synaptic strength. We show that this minimum signals a transition from a regime dominated by neurons with a higher firing activity to a phase where all neurons are effectively sub-threshold and their irregular firing is driven by current fluctuations. We explain the origin of the transition by deriving a mean field formulation of the problem able to provide the fraction of active neurons as well as the first two moments of their firing statistics. The introduction of a synaptic time scale does not modify the main aspects of the reported phenomenon. However, for sufficiently slow synapses the transition becomes dramatic, and the system passes from a perfectly regular evolution to irregular bursting dynamics. In this latter regime the model provides predictions consistent with experimental findings for a specific class of neurons, namely the medium spiny neurons in the striatum.

  5. Labor Mobility, Social Network Effects, and Innovative Activity

    DEFF Research Database (Denmark)

    Kaiser, Ulrich; Kongsted, H.C.; Rønde, Thomas

    We study the mapping between labor mobility and industrial innovative activity for the population of R&D active Danish firms observed between 1999 and 2004. Our study documents a positive relationship between the number of workers who join a firm and the firm’s innovative activity. This relations......We study the mapping between labor mobility and industrial innovative activity for the population of R&D active Danish firms observed between 1999 and 2004. Our study documents a positive relationship between the number of workers who join a firm and the firm’s innovative activity....... This relationship is stronger if workers join from innovative firms. We also find evidence for positive feedback from workers who leave for an innovative firm, presumably because the worker who left stays in contact with their former colleagues. This implies that the positive feedback (“social network effects......”) that has been found by other studies not only exists but even outweighs the disruption and loss of knowledge occurring to the previous employer from the worker leaving. Summing up the effects of joining and leaving workers, we find ample evidence for mobility to be associated with an increase in total...

  6. Neural Network Hydrological Modelling: Linear Output Activation Functions?

    Science.gov (United States)

    Abrahart, R. J.; Dawson, C. W.

    2005-12-01

    The power to represent non-linear hydrological processes is of paramount importance in neural network hydrological modelling operations. The accepted wisdom requires non-polynomial activation functions to be incorporated in the hidden units such that a single tier of hidden units can thereafter be used to provide a 'universal approximation' to whatever particular hydrological mechanism or function is of interest to the modeller. The user can select from a set of default activation functions, or in certain software packages, is able to define their own function - the most popular options being logistic, sigmoid and hyperbolic tangent. If a unit does not transform its inputs it is said to possess a 'linear activation function' and a combination of linear activation functions will produce a linear solution; whereas the use of non-linear activation functions will produce non-linear solutions in which the principle of superposition does not hold. For hidden units, speed of learning and network complexities are important issues. For the output units, it is desirable to select an activation function that is suited to the distribution of the target values: e.g. binary targets (logistic); categorical targets (softmax); continuous-valued targets with a bounded range (logistic / tanh); positive target values with no known upper bound (exponential; but beware of overflow); continuous-valued targets with no known bounds (linear). It is also standard practice in most hydrological applications to use the default software settings and to insert a set of identical non-linear activation functions in the hidden layer and output layer processing units. Mixed combinations have nevertheless been reported in several hydrological modelling papers and the full ramifications of such activities requires further investigation and assessment i.e. non-linear activation functions in the hidden units connected to linear or clipped-linear activation functions in the output unit. There are two

  7. Flexible-rate optical packet generation/detection and label swapping for optical label switching networks

    Science.gov (United States)

    Wu, Zhongying; Li, Juhao; Tian, Yu; Ge, Dawei; Zhu, Paikun; Chen, Yuanxiang; Chen, Zhangyuan; He, Yongqi

    2017-03-01

    In recent years, optical label switching (OLS) gains lots of attentions due to its intrinsic advantages to implement protocol, bit-rate, granularity and data format transparency packet switching. In this paper, we propose a novel scheme to realize flexible-rate optical packet switching for OLS networks. At the transmitter node, flexible-rate packet is generated by parallel modulating different combinations of optical carriers generated from the optical multi-carrier generator (OMCG), among which the low-speed optical label occupies one carrier. At the switching node, label is extracted and re-generated in label processing unit (LPU). The payloads are switched based on routing information and new label is added after switching. At the receiver node, another OMCG serves as local oscillators (LOs) for optical payloads coherent detection. The proposed scheme offers good flexibility for dynamic optical packet switching by adjusting the payload bandwidth and could also effectively reduce the number of lasers, modulators and receivers for packet generation/detection. We present proof-of-concept demonstrations of flexible-rate packet generation/detection and label swapping in 12.5 GHz grid. The influence of crosstalk for cascaded label swapping is also investigated.

  8. Implementation of a wireless sensor network for heart rate monitoring in a senior center.

    Science.gov (United States)

    Huang, Jyh-How; Su, Tzu-Yao; Raknim, Paweeya; Lan, Kun-Chan

    2015-06-01

    Wearable sensor systems are widely used to monitor vital sign in hospitals and in recent years have also been used at home. In this article we present a system that includes a ring probe, sensor, radio, and receiver, designed for use as a long-term heart rate monitoring system in a senior center. The primary contribution of this article is successfully implementing a cheap, large-scale wireless heart rate monitoring system that is stable and comfortable to use 24 h a day. We developed new finger ring sensors for comfortable continuous wearing experience and used dynamic power adjustment on the ring so the sensor can detect pulses at different strength levels. Our system has been deployed in a senior center since May 2012, and 63 seniors have used this system in this period. During the 54-h system observation period, 10 alarms were set off. Eight of them were due to abnormal heart rate, and two of them were due to loose probes. The monitoring system runs stably with the senior center's existing WiFi network, and achieves 99.48% system availability. The managers and caregivers use our system as a reliable warning system for clinical deterioration. The results of the year-long deployment show that the wireless group heart rate monitoring system developed in this work is viable for use within a designated area.

  9. Region-specific network plasticity in simulated and living cortical networks: comparison of the center of activity trajectory (CAT) with other statistics

    Science.gov (United States)

    Chao, Zenas C.; Bakkum, Douglas J.; Potter, Steve M.

    2007-09-01

    Electrically interfaced cortical networks cultured in vitro can be used as a model for studying the network mechanisms of learning and memory. Lasting changes in functional connectivity have been difficult to detect with extracellular multi-electrode arrays using standard firing rate statistics. We used both simulated and living networks to compare the ability of various statistics to quantify functional plasticity at the network level. Using a simulated integrate-and-fire neural network, we compared five established statistical methods to one of our own design, called center of activity trajectory (CAT). CAT, which depicts dynamics of the location-weighted average of spatiotemporal patterns of action potentials across the physical space of the neuronal circuitry, was the most sensitive statistic for detecting tetanus-induced plasticity in both simulated and living networks. By reducing the dimensionality of multi-unit data while still including spatial information, CAT allows efficient real-time computation of spatiotemporal activity patterns. Thus, CAT will be useful for studies in vivo or in vitro in which the locations of recording sites on multi-electrode probes are important.

  10. Estimation of Leak Flow Rate during Post-LOCA Using Cascaded Fuzzy Neural Networks

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Dong Yeong [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of); Na, Man Gyun [Chosun University, Gwangju (Korea, Republic of)

    2016-10-15

    In this study, important parameters such as the break position, size, and leak flow rate of loss of coolant accidents (LOCAs), provide operators with essential information for recovering the cooling capability of the nuclear reactor core, for preventing the reactor core from melting down, and for managing severe accidents effectively. Leak flow rate should consist of break size, differential pressure, temperature, and so on (where differential pressure means difference between internal and external reactor vessel pressure). The leak flow rate is strongly dependent on the break size and the differential pressure, but the break size is not measured and the integrity of pressure sensors is not assured in severe circumstances. In this paper, a cascaded fuzzy neural network (CFNN) model is appropriately proposed to estimate the leak flow rate out of break, which has a direct impact on the important times (time approaching the core exit temperature that exceeds 1200 .deg. F, core uncover time, reactor vessel failure time, etc.). The CFNN is a data-based model, it requires data to develop and verify itself. Because few actual severe accident data exist, it is essential to obtain the data required in the proposed model using numerical simulations. In this study, a CFNN model was developed to predict the leak flow rate before proceeding to severe LOCAs. The simulations showed that the developed CFNN model accurately predicted the leak flow rate with less error than 0.5%. The CFNN model is much better than FNN model under the same conditions, such as the same fuzzy rules. At the result of comparison, the RMS errors of the CFNN model were reduced by approximately 82 ~ 97% of those of the FNN model.

  11. A reanalysis of “Two types of asynchronous activity in networks of excitatory and inhibitory spiking neurons” [version 1; referees: 2 approved

    Directory of Open Access Journals (Sweden)

    Rainer Engelken

    2016-08-01

    Full Text Available Neuronal activity in the central nervous system varies strongly in time and across neuronal populations. It is a longstanding proposal that such fluctuations generically arise from chaotic network dynamics. Various theoretical studies predict that the rich dynamics of rate models operating in the chaotic regime can subserve circuit computation and learning. Neurons in the brain, however, communicate via spikes and it is a theoretical challenge to obtain similar rate fluctuations in networks of spiking neuron models. A recent study investigated spiking balanced networks of leaky integrate and fire (LIF neurons and compared their dynamics to a matched rate network with identical topology, where single unit input-output functions were chosen from isolated LIF neurons receiving Gaussian white noise input. A mathematical analogy between the chaotic instability in networks of rate units and the spiking network dynamics was proposed. Here we revisit the behavior of the spiking LIF networks and these matched rate networks. We find expected hallmarks of a chaotic instability in the rate network: For supercritical coupling strength near the transition point, the autocorrelation time diverges. For subcritical coupling strengths, we observe critical slowing down in response to small external perturbations. In the spiking network, we found in contrast that the timescale of the autocorrelations is insensitive to the coupling strength and that rate deviations resulting from small input perturbations rapidly decay. The decay speed even accelerates for increasing coupling strength. In conclusion, our reanalysis demonstrates fundamental differences between the behavior of pulse-coupled spiking LIF networks and rate networks with matched topology and input-output function. In particular there is no indication of a corresponding chaotic instability in the spiking network.

  12. Optimal Bidding Strategy for Renewable Microgrid with Active Network Management

    Directory of Open Access Journals (Sweden)

    Seung Wan Kim

    2016-01-01

    Full Text Available Active Network Management (ANM enables a microgrid to optimally dispatch the active/reactive power of its Renewable Distributed Generation (RDG and Battery Energy Storage System (BESS units in real time. Thus, a microgrid with high penetration of RDGs can handle their uncertainties and variabilities to achieve the stable operation using ANM. However, the actual power flow in the line connecting the main grid and microgrid may deviate significantly from the day-ahead bids if the bids are determined without consideration of the real-time adjustment through ANM, which will lead to a substantial imbalance cost. Therefore, this study proposes a formulation for obtaining an optimal bidding which reflects the change of power flow in the connecting line by real-time adjustment using ANM. The proposed formulation maximizes the expected profit of the microgrid considering various network and physical constraints. The effectiveness of the proposed bidding strategy is verified through the simulations with a 33-bus test microgrid. The simulation results show that the proposed bidding strategy improves the expected operating profit by reducing the imbalance cost to a greater degree compared to the basic bidding strategy without consideration of ANM.

  13. Active multistage coarsening of actin networks driven by myosin motors

    Science.gov (United States)

    Silva, Marina Soares e; Depken, Martin; Stuhrmann, Björn; Korsten, Marijn; MacKintosh, Fred C.; Koenderink, Gijsje H.

    2011-01-01

    In cells, many vital processes involve myosin-driven motility that actively remodels the actin cytoskeleton and changes cell shape. Here we study how the collective action of myosin motors organizes actin filaments into contractile structures in a simplified model system devoid of biochemical regulation. We show that this self-organization occurs through an active multistage coarsening process. First, motors form dense foci by moving along the actin network structure followed by coalescence. Then the foci accumulate actin filaments in a shell around them. These actomyosin condensates eventually cluster due to motor-driven coalescence. We propose that the physical origin of this multistage aggregation is the highly asymmetric load response of actin filaments: they can support large tensions but buckle easily under piconewton compressive loads. Because the motor-generated forces well exceed this threshold, buckling is induced on the connected actin network that resists motor-driven filament sliding. We show how this buckling can give rise to the accumulation of actin shells around myosin foci and subsequent coalescence of foci into superaggregates. This new physical mechanism provides an explanation for the formation and contractile dynamics of disordered condensed actomyosin states observed in vivo. PMID:21593409

  14. Situation awareness of active distribution network: roadmap, technologies, and bottlenecks

    DEFF Research Database (Denmark)

    Lin, Jin; Wan, Can; Song, Yonghua

    2016-01-01

    With the rapid development of local generation and demand response, the active distribution network (ADN), which aggregates and manages miscellaneous distributed resources, has moved from theory to practice. Secure and optimal operations now require an advanced situation awareness (SA) system so...... in the project of developing an SA system as the basic component of a practical active distribution management system (ADMS) deployed in Beijing, China, is presented. This paper reviews the ADN’s development roadmap by illustrating the changes that are made in elements, topology, structure, and control scheme....... Taking into consideration these hardware changes, a systematic framework is proposed for the main components and the functional hierarchy of an SA system for the ADN. The SA system’s implementation bottlenecks are also presented, including, but not limited to issues in big data platform, distribution...

  15. Pre-stimulus BOLD-network activation modulates EEG spectral activity during working memory retention

    Directory of Open Access Journals (Sweden)

    Mara eKottlow

    2015-05-01

    Full Text Available Working memory (WM processes depend on our momentary mental state and therefore exhibit considerable fluctuations. Here, we investigate the interplay of task-preparatory and task-related brain activity as represented by pre-stimulus BOLD-fluctuations and spectral EEG from the retention periods of a visual WM task. Visual WM is used to maintain sensory information in the brain enabling the performance of cognitive operations and is associated with mental health.We tested 22 subjects simultaneously with EEG and fMRI while performing a visuo-verbal Sternberg task with two different loads, allowing for the temporal separation of preparation, encoding, retention and retrieval periods.Four temporally coherent networks - the default mode network (DMN, the dorsal attention, the right and the left WM network - were extracted from the continuous BOLD data by means of a group ICA. Subsequently, the modulatory effect of these networks’ pre-stimulus activation upon retention-related EEG activity in the theta, alpha and beta frequencies was analyzed. The obtained results are informative in the context of state-dependent information processing.We were able to replicate two well-known load-dependent effects: the frontal-midline theta increase during the task and the decrease of pre-stimulus DMN activity. As our main finding, these two measures seem to depend on each other as the significant negative correlations at frontal-midline channels suggested. Thus, suppressed pre-stimulus DMN levels facilitated later task related frontal midline theta increases. In general, based on previous findings that neuronal coupling in different frequency bands may underlie distinct functions in WM retention, our results suggest that processes reflected by spectral oscillations during retention seem not only to be online synchronized with activity in different attention-related networks but are also modulated by activity in these networks during preparation intervals.

  16. Mouthguard utilization rates during sport activities in Ankara, Turkey.

    Science.gov (United States)

    Cetinbaş, Tuğba; Sönmez, Hayriye

    2006-06-01

    The objective of this study was to determine the attitudes towards mouthguard use in Ankara, Turkey. In the first part of this study, an eight-item questionnaire was distributed to 22 coaches from 15 secondary schools randomly selected from five municipalities of Ankara, Turkey. The questionnaire sought information on how much coaches know regarding mouthguards and how often children and adolescents of the ages 11-18 use mouthguards. The second part of the study was based on the data obtained from direct interviews answered by 121 university athletes of three different sport modalities (football, ice hockey and martial arts). The purpose of this part of the study was to determine the rate of mouthguard use and the frequency and type of oral trauma in these athletes. The result of the coaches' questionnaires revealed that; none of the 11-18 years old children and adolescents used mouthguards while participating in sports. Of the coaches, 77.2% had seen orofacial trauma in this age group during sport activities and 95.5% of the coaches believed that mouthguards prevented oral injuries. Of the coaches, 72.7% reported that children and adolescents should use mouthguards in sport activities. The second part of the study showed that although all of the athletes owned mouth-formed type of mouthguards, the utilization rate was 74.4%. Of all players, 13.2% had suffered from one or more form of oral injury while not wearing mouthguards. The results show that in Turkey, the use of mouthguards has not become widespread in sports. It can be concluded that regular mouthguard use in sports should be encouraged in Turkey.

  17. Influence Activation Model: A New Perspective in Social Influence Analysis and Social Network Evolution

    CERN Document Server

    Yang, Yang; Lichtenwalter, Ryan N; Dong, Yuxiao

    2016-01-01

    What drives the propensity for the social network dynamics? Social influence is believed to drive both off-line and on-line human behavior, however it has not been considered as a driver of social network evolution. Our analysis suggest that, while the network structure affects the spread of influence in social networks, the network is in turn shaped by social influence activity (i.e., the process of social influence wherein one person's attitudes and behaviors affect another's). To that end, we develop a novel model of network evolution where the dynamics of network follow the mechanism of influence propagation, which are not captured by the existing network evolution models. Our experiments confirm the predictions of our model and demonstrate the important role that social influence can play in the process of network evolution. As well exploring the reason of social network evolution, different genres of social influence have been spotted having different effects on the network dynamics. These findings and ...

  18. Detection of silent cells, synchronization and modulatory activity in developing cellular networks.

    Science.gov (United States)

    Hjorth, Johannes J J; Dawitz, Julia; Kroon, Tim; Pires, Johny; Dassen, Valerie J; Berkhout, Janna A; Emperador Melero, Javier; Nadadhur, Aish G; Alevra, Mihai; Toonen, Ruud F; Heine, Vivi M; Mansvelder, Huibert D; Meredith, Rhiannon M

    2016-04-01

    Developing networks in the immature nervous system and in cellular cultures are characterized by waves of synchronous activity in restricted clusters of cells. Synchronized activity in immature networks is proposed to regulate many different developmental processes, from neuron growth and cell migration, to the refinement of synapses, topographic maps, and the mature composition of ion channels. These emergent activity patterns are not present in all cells simultaneously within the network and more immature "silent" cells, potentially correlated with the presence of silent synapses, are prominent in different networks during early developmental periods. Many current network analyses for detection of synchronous cellular activity utilize activity-based pixel correlations to identify cellular-based regions of interest (ROIs) and coincident cell activity. However, using activity-based correlations, these methods first underestimate or ignore the inactive silent cells within the developing network and second, are difficult to apply within cell-dense regions commonly found in developing brain networks. In addition, previous methods may ignore ROIs within a network that shows transient activity patterns comprising both inactive and active periods. We developed analysis software to semi-automatically detect cells within developing neuronal networks that were imaged using calcium-sensitive reporter dyes. Using an iterative threshold, modulation of activity was tracked within individual cells across the network. The distribution pattern of both inactive and active, including synchronous cells, could be determined based on distance measures to neighboring cells and according to different anatomical layers. © 2015 Wiley Periodicals, Inc.

  19. Blocking probabilities in mobile communications networks with time-varying rates ad redialing subscribers

    NARCIS (Netherlands)

    Abdalla, Nadra; Boucherie, Richardus J.

    Call-blocking probabilities are among the key performance measures in mobile communications networks. For their analysis, mobile networks can be modelled as networks of Erlang loss queues with common capacity restrictions dictated by the allocation of frequencies to the cells of the network.

  20. Resource allocation via sum-rate maximization in the uplink of multi-cell OFDMA networks

    KAUST Repository

    Tabassum, Hina

    2012-10-03

    In this paper, we consider maximizing the sum rate in the uplink of a multi-cell orthogonal frequency-division multiple access network. The problem has a non-convex combinatorial structure and is known to be NP-hard. Because of the inherent complexity of implementing the optimal solution, firstly, we derive an upper bound (UB) and a lower bound (LB) to the optimal average network throughput. Moreover, we investigate the performance of a near-optimal single cell resource allocation scheme in the presence of inter-cell interference, which leads to another easily computable LB. We then develop a centralized sub-optimal scheme that is composed of a geometric programming-based power control phase in conjunction with an iterative subcarrier allocation phase. Although the scheme is computationally complex, it provides an effective benchmark for low complexity schemes even without the power control phase. Finally, we propose less complex centralized and distributed schemes that are well suited for practical scenarios. The computational complexity of all schemes is analyzed, and the performance is compared through simulations. Simulation results demonstrate that the proposed low complexity schemes can achieve comparable performance with that of the centralized sub-optimal scheme in various scenarios. Moreover, comparisons with the UB and LB provide insight on the performance gap between the proposed schemes and the optimal solution. Copyright © 2011 John Wiley & Sons, Ltd.

  1. An Efficient Biometric-Based Algorithm Using Heart Rate Variability for Securing Body Sensor Networks

    Directory of Open Access Journals (Sweden)

    Sandeep Pirbhulal

    2015-06-01

    Full Text Available Body Sensor Network (BSN is a network of several associated sensor nodes on, inside or around the human body to monitor vital signals, such as, Electroencephalogram (EEG, Photoplethysmography (PPG, Electrocardiogram (ECG, etc. Each sensor node in BSN delivers major information; therefore, it is very significant to provide data confidentiality and security. All existing approaches to secure BSN are based on complex cryptographic key generation procedures, which not only demands high resource utilization and computation time, but also consumes large amount of energy, power and memory during data transmission. However, it is indispensable to put forward energy efficient and computationally less complex authentication technique for BSN. In this paper, a novel biometric-based algorithm is proposed, which utilizes Heart Rate Variability (HRV for simple key generation process to secure BSN. Our proposed algorithm is compared with three data authentication techniques, namely Physiological Signal based Key Agreement (PSKA, Data Encryption Standard (DES and Rivest Shamir Adleman (RSA. Simulation is performed in Matlab and results suggest that proposed algorithm is quite efficient in terms of transmission time utilization, average remaining energy and total power consumption.

  2. Optimal coordinated voltage control in active distribution networks using backtracking search algorithm.

    Science.gov (United States)

    Tengku Hashim, Tengku Juhana; Mohamed, Azah

    2017-01-01

    The growing interest in distributed generation (DG) in recent years has led to a number of generators connected to a distribution system. The integration of DGs in a distribution system has resulted in a network known as active distribution network due to the existence of bidirectional power flow in the system. Voltage rise issue is one of the predominantly important technical issues to be addressed when DGs exist in an active distribution network. This paper presents the application of the backtracking search algorithm (BSA), which is relatively new optimisation technique to determine the optimal settings of coordinated voltage control in a distribution system. The coordinated voltage control considers power factor, on-load tap-changer and generation curtailment control to manage voltage rise issue. A multi-objective function is formulated to minimise total losses and voltage deviation in a distribution system. The proposed BSA is compared with that of particle swarm optimisation (PSO) so as to evaluate its effectiveness in determining the optimal settings of power factor, tap-changer and percentage active power generation to be curtailed. The load flow algorithm from MATPOWER is integrated in the MATLAB environment to solve the multi-objective optimisation problem. Both the BSA and PSO optimisation techniques have been tested on a radial 13-bus distribution system and the results show that the BSA performs better than PSO by providing better fitness value and convergence rate.

  3. Inventive Activity of Researchers: Cross-Country Rating Assessments

    Directory of Open Access Journals (Sweden)

    Tatyana Ivanovna Volkova

    2017-03-01

    Full Text Available In recent years, the study of the research capacity of the country and regions has become more active not only from the point of view of their leading components (personnel, financial, information, organizational, material-and-technical ones but also from the perspective of the assessment of productivity and effectiveness of researchers’ work. In the cross-country analysis, the certain highly aggregative parameters, which values, as a rule, are not in favour of Russia, are used. At the same time, at profound studying of this topic, these estimates cannot represent correctly the real trends of inventive activity in the scientific and technological sphere of the country and its regions. Moreover, the measurement of the researchers’ creative potential realization is carried out mainly through the assessment systems of their printing activity. Little attention is paid to the problem of the rating assessments of the researchers’ inventive and patent activity and its products from a cross-country perspective (especially to the detailed ones as well as to its institutional determinants. Therefore, the authors have chosen this subject-matter of the research. Its empirical basis is the statistical materials of both the national database and those which are recognized by the world scientific community. This research has both theoretical and methodological orientations. The purpose is the development of methodological and methodical tools of the research and assessment of researchers’ inventive activity including methodological support of cross-country comparative assessments. The authors have based the hypothesis on their previous research: in the conditions of the decreasing level of financial security, continuous reduction of a number of researchers, institutional restrictions and contradictions, the inventive activity of national researchers is still exist, and in a number of its leading parameters is implemented at the level of the advanced

  4. Combined D-optimal design and generalized regression neural network for modeling of plasma etching rate

    Directory of Open Access Journals (Sweden)

    You Hailong

    2014-01-01

    Full Text Available Plasma etching process plays a critical role in semiconductor manufacturing. Because physical and chemical mechanisms involved in plasma etching are extremely complicated, models supporting process control are difficult to construct. This paper uses a 35-run D-optimal design to efficiently collect data under well planned conditions for important controllable variables such as power, pressure, electrode gap and gas flows of Cl2 and He and the response, etching rate, for building an empirical underlying model. Since the relationship between the control and response variables could be highly nonlinear, a generalized regression neural network is used to select important model variables and their combination effects and to fit the model. Compared with the response surface methodology, the proposed method has better prediction performance in training and testing samples. A success application of the model to control the plasma etching process demonstrates the effectiveness of the methods.

  5. Cooperative Spatial Reuse with Transmit Beamforming in Multi-rate Wireless Networks

    DEFF Research Database (Denmark)

    Lu, Chenguang; Fitzek, Frank; Eggers, Patrick Claus F.

    2009-01-01

    We present a cooperative spatial reuse (CSR) scheme as a cooperative extension of the current TDMA-based MAC to enable spatial reuse in multi-rate wireless networks. We model spatial reuse as a cooperation problem on utilizing the time slots obtained from the TDMA-based MAC. In CSR, there are two...... will leave spatial reuse mode and switch back to TDMA. In this work, we focus on the transmit beamforming techniques to enable CSR by interference cancellation on MISO (Multiple Input Single Output) links. We compare the CSR scheme using zero-forcing (ZF) transmit beamforming, namely ZF-CSR, to the TDMA......-based MAC using maximum ratio combining (MRC) transmit beamforming, namely MRC-TDMA. The numerical results of a simulated two 2 × 1 MISO links scenario show the great potential of CSR to substantially increase the capacity and energy efficiency. Udgivelsesdato: Feb. 2009...

  6. Spatial interpolation and radiological mapping of ambient gamma dose rate by using artificial neural networks and fuzzy logic methods.

    Science.gov (United States)

    Yeşilkanat, Cafer Mert; Kobya, Yaşar; Taşkın, Halim; Çevik, Uğur

    2017-09-01

    The aim of this study was to determine spatial risk dispersion of ambient gamma dose rate (AGDR) by using both artificial neural network (ANN) and fuzzy logic (FL) methods, compare the performances of methods, make dose estimations for intermediate stations with no previous measurements and create dose rate risk maps of the study area. In order to determine the dose distribution by using artificial neural networks, two main networks and five different network structures were used; feed forward ANN; Multi-layer perceptron (MLP), Radial basis functional neural network (RBFNN), Quantile regression neural network (QRNN) and recurrent ANN; Jordan networks (JN), Elman networks (EN). In the evaluation of estimation performance obtained for the test data, all models appear to give similar results. According to the cross-validation results obtained for explaining AGDR distribution, Pearson's r coefficients were calculated as 0.94, 0.91, 0.89, 0.91, 0.91 and 0.92 and RMSE values were calculated as 34.78, 43.28, 63.92, 44.86, 46.77 and 37.92 for MLP, RBFNN, QRNN, JN, EN and FL, respectively. In addition, spatial risk maps showing distributions of AGDR of the study area were created by all models and results were compared with geological, topological and soil structure. Copyright © 2017 Elsevier Ltd. All rights reserved.

  7. Self-organization of synchronous activity propagation in neuronal networks driven by local excitation.

    Science.gov (United States)

    Bayati, Mehdi; Valizadeh, Alireza; Abbassian, Abdolhossein; Cheng, Sen

    2015-01-01

    Many experimental and theoretical studies have suggested that the reliable propagation of synchronous neural activity is crucial for neural information processing. The propagation of synchronous firing activity in so-called synfire chains has been studied extensively in feed-forward networks of spiking neurons. However, it remains unclear how such neural activity could emerge in recurrent neuronal networks through synaptic plasticity. In this study, we investigate whether local excitation, i.e., neurons that fire at a higher frequency than the other, spontaneously active neurons in the network, can shape a network to allow for synchronous activity propagation. We use two-dimensional, locally connected and heterogeneous neuronal networks with spike-timing dependent plasticity (STDP). We find that, in our model, local excitation drives profound network changes within seconds. In the emergent network, neural activity propagates synchronously through the network. This activity originates from the site of the local excitation and propagates through the network. The synchronous activity propagation persists, even when the local excitation is removed, since it derives from the synaptic weight matrix. Importantly, once this connectivity is established it remains stable even in the presence of spontaneous activity. Our results suggest that synfire-chain-like activity can emerge in a relatively simple way in realistic neural networks by locally exciting the desired origin of the neuronal sequence.

  8. Consistent dust and gas models for protoplanetary disks. II. Chemical networks and rates

    Science.gov (United States)

    Kamp, I.; Thi, W.-F.; Woitke, P.; Rab, C.; Bouma, S.; Ménard, F.

    2017-11-01

    Aims: We aim to define a small and large chemical network which can be used for the quantitative simultaneous analysis of molecular emission from the near-IR to the submm. We also aim to revise reactions of excited molecular hydrogen, which are not included in UMIST, to provide a homogeneous database for future applications. Methods: We have used the thermo-chemical disk modeling code ProDiMo and a standard T Tauri disk model to evaluate the impact of various chemical networks, reaction rate databases and sets of adsorption energies on a large sample of chemical species and emerging line fluxes from the near-IR to the submm wavelength range. Results: We find large differences in the masses and radial distribution of ice reservoirs when considering freeze-out on bare or polar ice coated grains. Most strongly the ammonia ice mass and the location of the snow line (water) change. As a consequence molecules associated to the ice lines such as N2H+ change their emitting region; none of the line fluxes in the sample considered here changes by more than 25% except CO isotopologues, CN and N2H+ lines. The three-body reaction N+H2+M plays a key role in the formation of water in the outer disk. Besides that, differences between the UMIST 2006 and 2012 database change line fluxes in the sample considered here by less than a factor of two (a subset of low excitation CO and fine structure lines stays even within 25%); exceptions are OH, CN, HCN, HCO+ and N2H+ lines. However, different networks such as OSU and KIDA 2011 lead to pronounced differences in the chemistry inside 100 au and thus affect emission lines from high excitation CO, OH and CN lines. H2 is easily excited at the disk surface and state-to-state reactions enhance the abundance of CH+ and to a lesser extent HCO+. For sub-mm lines of HCN, N2H+ and HCO+, a more complex larger network is recommended. Conclusions: More work is required to consolidate data on key reactions leading to the formation of water, molecular

  9. From baseline to epileptiform activity: A path to synchronized rhythmicity in large-scale neural networks

    Science.gov (United States)

    Shusterman, Vladimir; Troy, William C.

    2008-06-01

    In large-scale neural networks in the brain the emergence of global behavioral patterns, manifested by electroencephalographic activity, is driven by the self-organization of local neuronal groups into synchronously functioning ensembles. However, the laws governing such macrobehavior and its disturbances, in particular epileptic seizures, are poorly understood. Here we use a mean-field population network model to describe a state of baseline physiological activity and the transition from the baseline state to rhythmic epileptiform activity. We describe principles which explain how this rhythmic activity arises in the form of spatially uniform self-sustained synchronous oscillations. In addition, we show how the rate of migration of the leading edge of the synchronous oscillations can be theoretically predicted, and compare the accuracy of this prediction with that measured experimentally using multichannel electrocorticographic recordings obtained from a human subject experiencing epileptic seizures. The comparison shows that the experimentally measured rate of migration of the leading edge of synchronous oscillations is within the theoretically predicted range of values. Computer simulations have been performed to investigate the interactions between different regions of the brain and to show how organization in one spatial region can promote or inhibit organization in another. Our theoretical predictions are also consistent with the results of functional magnetic resonance imaging (fMRI), in particular with observations that lower-frequency electroencephalographic (EEG) rhythms entrain larger areas of the brain than higher-frequency rhythms. These findings advance the understanding of functional behavior of interconnected populations and might have implications for the analysis of diverse classes of networks.

  10. Natural lecithin promotes neural network complexity and activity.

    Science.gov (United States)

    Latifi, Shahrzad; Tamayol, Ali; Habibey, Rouhollah; Sabzevari, Reza; Kahn, Cyril; Geny, David; Eftekharpour, Eftekhar; Annabi, Nasim; Blau, Axel; Linder, Michel; Arab-Tehrany, Elmira

    2016-05-27

    Phospholipids in the brain cell membranes contain different polyunsaturated fatty acids (PUFAs), which are critical to nervous system function and structure. In particular, brain function critically depends on the uptake of the so-called "essential" fatty acids such as omega-3 (n-3) and omega-6 (n-6) PUFAs that cannot be readily synthesized by the human body. We extracted natural lecithin rich in various PUFAs from a marine source and transformed it into nanoliposomes. These nanoliposomes increased neurite outgrowth, network complexity and neural activity of cortical rat neurons in vitro. We also observed an upregulation of synapsin I (SYN1), which supports the positive role of lecithin in synaptogenesis, synaptic development and maturation. These findings suggest that lecithin nanoliposomes enhance neuronal development, which may have an impact on devising new lecithin delivery strategies for therapeutic applications.

  11. Optimal Recognition Method of Human Activities Using Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Oniga Stefan

    2015-12-01

    Full Text Available The aim of this research is an exhaustive analysis of the various factors that may influence the recognition rate of the human activity using wearable sensors data. We made a total of 1674 simulations on a publically released human activity database by a group of researcher from the University of California at Berkeley. In a previous research, we analyzed the influence of the number of sensors and their placement. In the present research we have examined the influence of the number of sensor nodes, the type of sensor node, preprocessing algorithms, type of classifier and its parameters. The final purpose is to find the optimal setup for best recognition rates with lowest hardware and software costs.

  12. Abnormal activity of default mode network in GERD patients

    National Research Council Canada - National Science Library

    Sun, Huihui; Chen, Ying; Zhao, Xiaohu; Wang, Xiangbin; Jiang, Yuanxi; Wu, Ping; Tang, Yinhan; Meng, Qingwei; Xu, Shuchang

    2013-01-01

    ...). However, most studies were focused on the possible functions of perceptual processing related network during task status, little attention has been paid to default mode network, which has been...

  13. Allosteric networks in thrombin distinguish procoagulant vs. anticoagulant activities.

    Science.gov (United States)

    Gasper, Paul M; Fuglestad, Brian; Komives, Elizabeth A; Markwick, Phineus R L; McCammon, J Andrew

    2012-12-26

    The serine protease α-thrombin is a dual-action protein that mediates the blood-clotting cascade. Thrombin alone is a procoagulant, cleaving fibrinogen to make the fibrin clot, but the thrombin-thrombomodulin (TM) complex initiates the anticoagulant pathway by cleaving protein C. A TM fragment consisting of only the fifth and sixth EGF-like domains (TM56) is sufficient to bind thrombin, but the presence of the fourth EGF-like domain (TM456) is critical to induce the anticoagulant activity of thrombin. Crystallography of the thrombin-TM456 complex revealed no significant structural changes in thrombin, suggesting that TM4 may only provide a scaffold for optimal alignment of protein C for its cleavage by thrombin. However, a variety of experimental data have suggested that the presence of TM4 may affect the dynamic properties of the active site loops. In the present work, we have used both conventional and accelerated molecular dynamics simulation to study the structural dynamic properties of thrombin, thrombin:TM56, and thrombin:TM456 across a broad range of time scales. Two distinct yet interrelated allosteric pathways are identified that mediate both the pro- and anticoagulant activities of thrombin. One allosteric pathway, which is present in both thrombin:TM56 and thrombin:TM456, directly links the TM5 domain to the thrombin active site. The other allosteric pathway, which is only present on slow time scales in the presence of the TM4 domain, involves an extended network of correlated motions linking the TM4 and TM5 domains and the active site loops of thrombin.

  14. Size-dependent regulation of synchronized activity in living neuronal networks.

    Science.gov (United States)

    Yamamoto, Hideaki; Kubota, Shigeru; Chida, Yudai; Morita, Mayu; Moriya, Satoshi; Akima, Hisanao; Sato, Shigeo; Hirano-Iwata, Ayumi; Tanii, Takashi; Niwano, Michio

    2016-07-01

    We study the effect of network size on synchronized activity in living neuronal networks. Dissociated cortical neurons form synaptic connections in culture and generate synchronized spontaneous activity within 10 days in vitro. Using micropatterned surfaces to extrinsically control the size of neuronal networks, we show that synchronized activity can emerge in a network as small as 12 cells. Furthermore, a detailed comparison of small (∼20 cells), medium (∼100 cells), and large (∼400 cells) networks reveal that synchronized activity becomes destabilized in the small networks. A computational modeling of neural activity is then employed to explore the underlying mechanism responsible for the size effect. We find that the generation and maintenance of the synchronized activity can be minimally described by: (1) the stochastic firing of each neuron in the network, (2) enhancement in the network activity in a positive feedback loop of excitatory synapses, and (3) Ca-dependent suppression of bursting activity. The model further shows that the decrease in total synaptic input to a neuron that drives the positive feedback amplification of correlated activity is a key factor underlying the destabilization of synchrony in smaller networks. Spontaneous neural activity plays a critical role in cortical information processing, and our work constructively clarifies an aspect of the structural basis behind this.

  15. Effects of Increasing Neuromuscular Electrical Stimulation Current Intensity on Cortical Sensorimotor Network Activation: A Time Domain fNIRS Study.

    Directory of Open Access Journals (Sweden)

    Makii Muthalib

    Full Text Available Neuroimaging studies have shown neuromuscular electrical stimulation (NMES-evoked movements activate regions of the cortical sensorimotor network, including the primary sensorimotor cortex (SMC, premotor cortex (PMC, supplementary motor area (SMA, and secondary somatosensory area (S2, as well as regions of the prefrontal cortex (PFC known to be involved in pain processing. The aim of this study, on nine healthy subjects, was to compare the cortical network activation profile and pain ratings during NMES of the right forearm wrist extensor muscles at increasing current intensities up to and slightly over the individual maximal tolerated intensity (MTI, and with reference to voluntary (VOL wrist extension movements. By exploiting the capability of the multi-channel time domain functional near-infrared spectroscopy technique to relate depth information to the photon time-of-flight, the cortical and superficial oxygenated (O2Hb and deoxygenated (HHb hemoglobin concentrations were estimated. The O2Hb and HHb maps obtained using the General Linear Model (NIRS-SPM analysis method, showed that the VOL and NMES-evoked movements significantly increased activation (i.e., increase in O2Hb and corresponding decrease in HHb in the cortical layer of the contralateral sensorimotor network (SMC, PMC/SMA, and S2. However, the level and area of contralateral sensorimotor network (including PFC activation was significantly greater for NMES than VOL. Furthermore, there was greater bilateral sensorimotor network activation with the high NMES current intensities which corresponded with increased pain ratings. In conclusion, our findings suggest that greater bilateral sensorimotor network activation profile with high NMES current intensities could be in part attributable to increased attentional/pain processing and to increased bilateral sensorimotor integration in these cortical regions.

  16. Low-complexity full-rate transmission scheme with full diversity for two-path relay networks

    KAUST Repository

    Fareed, Muhammad Mehboob

    2015-04-01

    Existing full-rate transmission schemes for two-path relay networks typically cannot achieve full diversity while demanding high decoding complexity. In this paper, we present a novel low-complexity full-rate transmission scheme for two-path relay networks to harvest maximum achievable diversity. The proposed scheme adopts block transmission with small block size of four symbols, which greatly reduces the decoding complexity at the receiver. Through the performance analysis of the resulting two-path relay network in terms of the symbol error rate (SER) and diversity order, we show the proposed scheme can achieve full diversity order of four and mimic a 2 \\\\times 2 multiple-input multiple-output system. Simulations results are provided to validate the mathematical formulation. © 1967-2012 IEEE.

  17. Who Can You Turn to? Tie Activation within Core Business Discussion Networks

    Science.gov (United States)

    Renzulli, Linda A.; Aldrich, Howard

    2005-01-01

    We examine the connection between personal network characteristics and the activation of ties for access to resources during routine times. We focus on factors affecting business owners' use of their core network ties to obtain legal, loan, financial and expert advice. Owners rely more on core business ties when their core networks contain a high…

  18. Estimation of Active Stream Network Length in a Hilly Headwater Catchment Using Recession Flow Analysis

    National Research Council Canada - National Science Library

    Wei Li; Ke Zhang; Yuqiao Long; Li Feng

    2017-01-01

    .... Regarding the correlation between active stream networks and stream recession flow characteristics, we developed a new method to estimate the ASNL, under different wetness conditions, of a catchment...

  19. Neocortical Network Activity In Vivo Is Generated through a Dynamic Balance of Excitation and Inhibition

    National Research Council Canada - National Science Library

    Haider, Bilal; Duque, Alvaro; Hasenstaub, Andrea R; McCormick, David A

    2006-01-01

    .... Models of cortical function often assume that recurrent excitation and inhibition are balanced, and we recently demonstrated that spontaneous network activity in vitro contains a precise balance...

  20. Both novelty and expertise increase action observation network activity

    Directory of Open Access Journals (Sweden)

    Sook-Lei eLiew

    2013-09-01

    Full Text Available Our experiences with others affect how we perceive their actions. In particular, activity in bilateral premotor and parietal cortices during action observation, collectively known as the action observation network (AON, is modulated by one’s expertise with the observed actions or individuals. However, conflicting reports suggest that AON activity is greatest both for familiar and unfamiliar actions. The current study examines the effects of different types and amounts of experience (e.g., visual, interpersonal, personal on AON activation. fMRI was used to scan 16 healthy participants without prior experience with individuals with amputations (novices, 11 experienced occupational therapists (OTs who had varying amounts of experience with individuals with amputations, and one individual born with below-elbow residual limbs (participant CJ, as they viewed video clips of goal-matched actions performed by an individual with residual limbs and by an individual with hands. Participants were given increased visual exposure to actions performed by both effectors midway through the scanning procedure. Novices demonstrated a large AON response to the initial viewing of an individual with residual limbs compared to one with hands, but this signal was attenuated after they received visual exposure to both effectors. In contrast, OTs, who had moderate familiarity with residual limbs, demonstrated a lower AON response upon initial viewing—similar to novices after they received visual exposure. At the other extreme, CJ, who has extreme familiarity with residual limbs both visually and motorically, shows a largely increased left-lateralized AON response, exceeding that of novices and experienced OTs, when viewing the residual limb compared to hand actions. These results suggest that a nuanced model of AON engagement is needed to explain how cases of both extreme experience (CJ and extreme novelty (novices can result in the greatest AON activity.

  1. Subjective loudness and reality of auditory verbal hallucinations and activation of the inner speech processing network.

    Science.gov (United States)

    Vercammen, Ans; Knegtering, Henderikus; Bruggeman, Richard; Aleman, André

    2011-09-01

    One of the most influential cognitive models of auditory verbal hallucinations (AVH) suggests that a failure to adequately monitor the production of one's own inner speech leads to verbal thought being misidentified as an alien voice. However, it is unclear whether this theory can explain the phenomenological complexity of AVH. We aimed to assess whether subjective perceptual and experiential characteristics may be linked to neural activation in the inner speech processing network. Twenty-two patients with schizophrenia and AVH underwent a 3-T functional magnetic resonance imaging scan, while performing a metrical stress evaluation task, which has been shown to activate both inner speech production and perception regions. Regions of interest (ROIs) comprising the putative inner speech network were defined using the Anatomical Automatic Labeling system. Correlations were calculated between scores on the "loudness" and "reality" subscales of the Auditory Hallucination Rating Scale (AHRS) and activation in these ROIs. Second, the AHRS subscales, and general AVH severity, indexed by the Positive and Negative Syndrome Scale, were correlated with a language lateralization index. Louder AVH were associated with reduced task-related activity in bilateral angular gyrus, anterior cingulate gyrus, left inferior frontal gyrus, left insula, and left temporal cortex. This could potentially be due to a competition for shared neural resources. Reality on the other hand was found to be associated with reduced language lateralization. Strong activation of the inner speech processing network may contribute to the subjective loudness of AVH. However, a relatively increased contribution from right hemisphere language areas may be responsible for the more complex experiential characteristics, such as the nonself source or how real AVH are.

  2. Drosophila non-muscle myosin II motor activity determines the rate of tissue folding

    Science.gov (United States)

    Vasquez, Claudia G; Heissler, Sarah M; Billington, Neil; Sellers, James R; Martin, Adam C

    2016-01-01

    Non-muscle cell contractility is critical for tissues to adopt shape changes. Although, the non-muscle myosin II holoenzyme (myosin) is a molecular motor that powers contraction of actin cytoskeleton networks, recent studies have questioned the importance of myosin motor activity cell and tissue shape changes. Here, combining the biochemical analysis of enzymatic and motile properties for purified myosin mutants with in vivo measurements of apical constriction for the same mutants, we show that in vivo constriction rate scales with myosin motor activity. We show that so-called phosphomimetic mutants of the Drosophila regulatory light chain (RLC) do not mimic the phosphorylated RLC state in vitro. The defect in the myosin motor activity in these mutants is evident in developing Drosophila embryos where tissue recoil following laser ablation is decreased compared to wild-type tissue. Overall, our data highlights that myosin activity is required for rapid cell contraction and tissue folding in developing Drosophila embryos. DOI: http://dx.doi.org/10.7554/eLife.20828.001 PMID:28035903

  3. Elastic network normal mode dynamics reveal the GPCR activation mechanism.

    Science.gov (United States)

    Kolan, Dikla; Fonar, Gennadiy; Samson, Abraham O

    2014-04-01

    G-protein-coupled receptors (GPCR) are a family of membrane-embedded metabotropic receptors which translate extracellular ligand binding into an intracellular response. Here, we calculate the motion of several GPCR family members such as the M2 and M3 muscarinic acetylcholine receptors, the A2A adenosine receptor, the β2 -adrenergic receptor, and the CXCR4 chemokine receptor using elastic network normal modes. The normal modes reveal a dilation and a contraction of the GPCR vestibule associated with ligand passage, and activation, respectively. Contraction of the vestibule on the extracellular side is correlated with cavity formation of the G-protein binding pocket on the intracellular side, which initiates intracellular signaling. Interestingly, the normal modes of rhodopsin do not correlate well with the motion of other GPCR family members. Electrostatic potential calculation of the GPCRs reveal a negatively charged field around the ligand binding site acting as a siphon to draw-in positively charged ligands on the membrane surface. Altogether, these results expose the GPCR activation mechanism and show how conformational changes on the cell surface side of the receptor are allosterically translated into structural changes on the inside. Copyright © 2013 Wiley Periodicals, Inc.

  4. Active Low Intrusion Hybrid Monitor for Wireless Sensor Networks.

    Science.gov (United States)

    Navia, Marlon; Campelo, Jose C; Bonastre, Alberto; Ors, Rafael; Capella, Juan V; Serrano, Juan J

    2015-09-18

    Several systems have been proposed to monitor wireless sensor networks (WSN). These systems may be active (causing a high degree of intrusion) or passive (low observability inside the nodes). This paper presents the implementation of an active hybrid (hardware and software) monitor with low intrusion. It is based on the addition to the sensor node of a monitor node (hardware part) which, through a standard interface, is able to receive the monitoring information sent by a piece of software executed in the sensor node. The intrusion on time, code, and energy caused in the sensor nodes by the monitor is evaluated as a function of data size and the interface used. Then different interfaces, commonly available in sensor nodes, are evaluated: serial transmission (USART), serial peripheral interface (SPI), and parallel. The proposed hybrid monitor provides highly detailed information, barely disturbed by the measurement tool (interference), about the behavior of the WSN that may be used to evaluate many properties such as performance, dependability, security, etc. Monitor nodes are self-powered and may be removed after the monitoring campaign to be reused in other campaigns and/or WSNs. No other hardware-independent monitoring platforms with such low interference have been found in the literature.

  5. A reanalysis of “Two types of asynchronous activity in networks of excitatory and inhibitory spiking neurons” [version 1; referees: 2 approved

    OpenAIRE

    Rainer Engelken; Farzad Farkhooi; David Hansel; Carl van Vreeswijk; Fred Wolf

    2016-01-01

    Neuronal activity in the central nervous system varies strongly in time and across neuronal populations. It is a longstanding proposal that such fluctuations generically arise from chaotic network dynamics. Various theoretical studies predict that the rich dynamics of rate models operating in the chaotic regime can subserve circuit computation and learning. Neurons in the brain, however, communicate via spikes and it is a theoretical challenge to obtain similar rate fluctuations in networks o...

  6. Model Integrating Fuzzy Argument with Neural Network Enhancing the Performance of Active Queue Management

    Directory of Open Access Journals (Sweden)

    Nguyen Kim Quoc

    2015-08-01

    Full Text Available The bottleneck control by active queue management mechanisms at network nodes is essential. In recent years, some researchers have used fuzzy argument to improve the active queue management mechanisms to enhance the network performance. However, the projects using the fuzzy controller depend heavily on professionals and their parameters cannot be updated according to changes in the network, so the effectiveness of this mechanism is not high. Therefore, we propose a model combining the fuzzy controller with neural network (FNN to overcome the limitations above. Results of the training of the neural networks will find the optimal parameters for the adaptive fuzzy controller well to changes of the network. This improves the operational efficiency of the active queue management mechanisms at network nodes.

  7. 77 FR 47918 - Information Collection Activities (Released Rates)

    Science.gov (United States)

    2012-08-10

    ... Common Carriers of Household Goods, Docket No. RR 999 (Amendment No. 5) (served Jan. 21, 2011 (2011... rates that interstate movers of household goods charge for the services they offer). More specifically... without an OMB control number. Respondents: Household goods movers that desire to offer a rate limiting...

  8. Muscle networks: Connectivity analysis of EMG activity during postural control

    Science.gov (United States)

    Boonstra, Tjeerd W.; Danna-Dos-Santos, Alessander; Xie, Hong-Bo; Roerdink, Melvyn; Stins, John F.; Breakspear, Michael

    2015-12-01

    Understanding the mechanisms that reduce the many degrees of freedom in the musculoskeletal system remains an outstanding challenge. Muscle synergies reduce the dimensionality and hence simplify the control problem. How this is achieved is not yet known. Here we use network theory to assess the coordination between multiple muscles and to elucidate the neural implementation of muscle synergies. We performed connectivity analysis of surface EMG from ten leg muscles to extract the muscle networks while human participants were standing upright in four different conditions. We observed widespread connectivity between muscles at multiple distinct frequency bands. The network topology differed significantly between frequencies and between conditions. These findings demonstrate how muscle networks can be used to investigate the neural circuitry of motor coordination. The presence of disparate muscle networks across frequencies suggests that the neuromuscular system is organized into a multiplex network allowing for parallel and hierarchical control structures.

  9. Networking in Sport Management: Ideas and Activities to Enhance Student Engagement and Career Development

    Directory of Open Access Journals (Sweden)

    Alan S. Kornspan

    2013-01-01

    Full Text Available The primary purpose of this paper is to present information regarding the development of networking skills to enhance the career development of sport management students. Specifically, literature is reviewed which supports the importance of networking in the attainment of employment and career advancement in the sport industry. This is followed by an overview of emerging networking activities that allow opportunities for sport management students to expand their network. Sport industry career fairs and career conferences that students can attend are discussed. Additionally, sport industry professional associations that students can become involved with are presented. This is then followed with information related to the development of sport management clubs and various events that can be promoted to enhance the networking process. Specifically, activities provided by university faculty to enhance the educational experience of sport management students are detailed. Finally, a sample schedule of semester activities focused on student engagement and networking activities is provided.

  10. Collecting social network data to study social activity-travel behavior: an egocentric approach

    OpenAIRE

    Juan Antonio Carrasco; Bernie Hogan; Barry Wellman; Miller, Eric J.

    2008-01-01

    This paper presents a data collection effort designed to incorporate the social dimension in social activity-travel behavior by explicitly studying the link between individuals’ social activities and their social networks. The main hypothesis of the data collection effort is that individuals’ travel behavior is conditional upon their social networks; that is, a key cause of travel behavior is the social dimension represented by social networks. With this hypothesis in mind, and using survey a...

  11. Metabolic and protein interaction sub-networks controlling the proliferation rate of cancer cells and their impact on patient survival.

    Science.gov (United States)

    Feizi, Amir; Bordel, Sergio

    2013-10-24

    Cancer cells can have a broad scope of proliferation rates. Here we aim to identify the molecular mechanisms that allow some cancer cell lines to grow up to 4 times faster than other cell lines. The correlation of gene expression profiles with the growth rate in 60 different cell lines has been analyzed using several genome-scale biological networks and new algorithms. New possible regulatory feedback loops have been suggested and the known roles of several cell cycle related transcription factors have been confirmed. Over 100 growth-correlated metabolic sub-networks have been identified, suggesting a key role of simultaneous lipid synthesis and degradation in the energy supply of the cancer cells growth. Many metabolic sub-networks involved in cell line proliferation appeared also to correlate negatively with the survival expectancy of colon cancer patients.

  12. Adaptive predictions of the euro/złoty currency exchange rate using state space wavelet networks and forecast combinations

    Directory of Open Access Journals (Sweden)

    Brdyś Mietek A.

    2016-03-01

    Full Text Available The paper considers the forecasting of the euro/Polish złoty (EUR/PLN spot exchange rate by applying state space wavelet network and econometric forecast combination models. Both prediction methods are applied to produce one-trading-day-ahead forecasts of the EUR/PLN exchange rate. The paper presents the general state space wavelet network and forecast combination models as well as their underlying principles. The state space wavelet network model is, in contrast to econometric forecast combinations, a non-parametric prediction technique which does not make any distributional assumptions regarding the underlying input variables. Both methods can be used as forecasting tools in portfolio investment management, asset valuation, IT security and integrated business risk intelligence in volatile market conditions.

  13. Potential relocation of climatic environments suggests high rates of climate displacement within the North American protection network

    Science.gov (United States)

    Enric Batllori; Marc-Andre Parisien; Sean A. Parks; Max A. Moritz; Carol Miller

    2017-01-01

    Ongoing climate change may undermine the effectiveness of protected area networks in preserving the set of biotic components and ecological processes they harbor, thereby jeopardizing their conservation capacity into the future. Metrics of climate change, particularly rates and spatial patterns of climatic alteration, can help assess potential threats. Here, we perform...

  14. A Hierarchical Approach to Real-time Activity Recognition in Body Sensor Networks

    DEFF Research Database (Denmark)

    Wang, Liang; Gu, Tao; Tao, Xianping

    2012-01-01

    Real-time activity recognition in body sensor networks is an important and challenging task. In this paper, we propose a real-time, hierarchical model to recognize both simple gestures and complex activities using a wireless body sensor network. In this model, we rst use a fast and lightweight al...

  15. Real-time Human Activity Recognition using a Body Sensor Network

    DEFF Research Database (Denmark)

    Wang, Liang; Gu, Tao; Chen, Hanhua

    2010-01-01

    Real-time activity recognition using body sensor networks is an important and challenging task and it has many potential applications. In this paper, we propose a realtime, hierarchical model to recognize both simple gestures and complex activities using a wireless body sensor network...

  16. A Krebs Cycle Component Limits Caspase Activation Rate through Mitochondrial Surface Restriction of CRL Activation.

    Science.gov (United States)

    Aram, Lior; Braun, Tslil; Braverman, Carmel; Kaplan, Yosef; Ravid, Liat; Levin-Zaidman, Smadar; Arama, Eli

    2016-04-04

    How cells avoid excessive caspase activity and unwanted cell death during apoptotic caspase-mediated removal of large cellular structures is poorly understood. We investigate caspase-mediated extrusion of spermatid cytoplasmic contents in Drosophila during spermatid individualization. We show that a Krebs cycle component, the ATP-specific form of the succinyl-CoA synthetase β subunit (A-Sβ), binds to and activates the Cullin-3-based ubiquitin ligase (CRL3) complex required for caspase activation in spermatids. In vitro and in vivo evidence suggests that this interaction occurs on the mitochondrial surface, thereby limiting the source of CRL3 complex activation to the vicinity of this organelle and reducing the potential rate of caspase activation by at least 60%. Domain swapping between A-Sβ and the GTP-specific SCSβ (G-Sβ), which functions redundantly in the Krebs cycle, show that the metabolic and structural roles of A-Sβ in spermatids can be uncoupled, highlighting a moonlighting function of this Krebs cycle component in CRL activation. Copyright © 2016 Elsevier Inc. All rights reserved.

  17. Environmental activism in urban China: the role of personal networks

    NARCIS (Netherlands)

    Xie Lei,

    2007-01-01

    The study examines the characteristics of the Chinese environmental movement by looking into the roles played by leaders, activists and their individual networks in environmental NGOs. Looking into individual networks is a vital starting point to examine the dynamics of the Chinese environmental

  18. E-bra with nanosensors, smart electronics and smart phone communication network for heart rate monitoring

    Science.gov (United States)

    Varadan, Vijay K.; Kumar, Prashanth S.; Oh, Sechang; Mathur, Gyanesh N.; Rai, Pratyush; Kegley, Lauren

    2011-04-01

    Heart related ailments have been a major cause for deaths in both men and women in United States. Since 1985, more women than men have died due to cardiac or cardiovascular ailments for reasons that are not well understood as yet. Lack of a deterministic understanding of this phenomenon makes continuous real time monitoring of cardiovascular health the best approach for both early detection of pathophysiological changes and events indicative of chronic cardiovascular diseases in women. This approach requires sensor systems to be seamlessly mounted on day to day clothing for women. With this application in focus, this paper describes a e-bra platform for sensors towards heart rate monitoring. The sensors, nanomaterial or textile based dry electrodes, capture the heart activity signals in form Electrocardiograph (ECG) and relay it to a compact textile mountable amplifier-wireless transmitter module for relay to a smart phone. The ECG signal, acquired on the smart phone, can be transmitted to the cyber space for post processing. As an example, the paper discusses the heart rate estimation and heart rate variability. The data flow from sensor to smart phone to server (cyber infrastructure) has been discussed. The cyber infrastructure based signal post processing offers an opportunity for automated emergency response that can be initiated from the server or the smartphone itself. Detailed protocols for both the scenarios have been presented and their relevance to the present emergency healthcare response system has been discussed.

  19. Engineering online and in-person social networks to sustain physical activity: application of a conceptual model.

    Science.gov (United States)

    Rovniak, Liza S; Sallis, James F; Kraschnewski, Jennifer L; Sciamanna, Christopher N; Kiser, Elizabeth J; Ray, Chester A; Chinchilli, Vernon M; Ding, Ding; Matthews, Stephen A; Bopp, Melissa; George, Daniel R; Hovell, Melbourne F

    2013-08-14

    High rates of physical inactivity compromise the health status of populations globally. Social networks have been shown to influence physical activity (PA), but little is known about how best to engineer social networks to sustain PA. To improve procedures for building networks that shape PA as a normative behavior, there is a need for more specific hypotheses about how social variables influence PA. There is also a need to integrate concepts from network science with ecological concepts that often guide the design of in-person and electronically-mediated interventions. Therefore, this paper: (1) proposes a conceptual model that integrates principles from network science and ecology across in-person and electronically-mediated intervention modes; and (2) illustrates the application of this model to the design and evaluation of a social network intervention for PA. A conceptual model for engineering social networks was developed based on a scoping literature review of modifiable social influences on PA. The model guided the design of a cluster randomized controlled trial in which 308 sedentary adults were randomly assigned to three groups: WalkLink+: prompted and provided feedback on participants' online and in-person social-network interactions to expand networks for PA, plus provided evidence-based online walking program and weekly walking tips; WalkLink: evidence-based online walking program and weekly tips only; Minimal Treatment Control: weekly tips only. The effects of these treatment conditions were assessed at baseline, post-program, and 6-month follow-up. The primary outcome was accelerometer-measured PA. Secondary outcomes included objectively-measured aerobic fitness, body mass index, waist circumference, blood pressure, and neighborhood walkability; and self-reported measures of the physical environment, social network environment, and social network interactions. The differential effects of the three treatment conditions on primary and secondary

  20. Social networks of experientially similar others: formation, activation, and consequences of network ties on the health care experience.

    Science.gov (United States)

    Gage, Elizabeth A

    2013-10-01

    Research documents that interactions among experientially similar others (individuals facing a common stressor) shape health care behavior and ultimately health outcomes. However, we have little understanding of how ties among experientially similar others are formed, what resources and information flows through these networks, and how network embeddedness shapes health care behavior. This paper uses in-depth interviews with 76 parents of pediatric cancer patients to examine network ties among experientially similar others after a serious medical diagnosis. Interviews were conducted between August 2009 and May 2011. Findings demonstrate that many parents formed ties with other families experiencing pediatric cancer, and that information and resources were exchanged during the everyday activities associated with their child's care. Network flows contained emotional support, caregiving strategies, information about second opinions, health-related knowledge, and strategies for navigating the health care system. Diffusion of information, resources, and support occurred through explicit processes (direct information and support exchanges) and implicit processes (parents learning through observing other families). Network flows among parents shaped parents' perceptions of the health care experience and their role in their child's care. These findings contribute to the social networks and social support literatures by elucidating the mechanisms through which network ties among experientially similar others influence health care behavior and experiences. Copyright © 2012 Elsevier Ltd. All rights reserved.

  1. An evolutionary vaccination game in the modified activity driven network by considering the closeness

    Science.gov (United States)

    Han, Dun; Sun, Mei

    2016-02-01

    In this paper, we explore an evolutionary vaccination game in the modified activity driven network by considering the closeness. We set a closeness parameter p which is used to describe the way of connection between two individuals. The simulation results show that the closeness p may have an active role in weakening both the spreading of epidemic and the vaccination. Besides, when vaccination is not allowed, the final recovered density increases with the value of the ratio of the infection rate to the recovery rate λ / μ. However, when vaccination is allowed the final density of recovered individual first increases and then decreases with the value of λ / μ. Two variables are designed to identify the relation between the individuals' activities and their states. The results draw that both recovered and vaccinated frequency increase with the increase of the individuals' activities. Meanwhile, the immune fee has less impact on the individuals' vaccination than the closeness. While the λ / μ is in a certain range, with the increase of the value of λ / μ, the recovered frequency of the whole crowds reduces. Our results, therefore, reveal the fact that the best of intentions may lead to backfire.

  2. The self-pleasantness judgment modulates the encoding performance and the Default Mode Network activity

    Directory of Open Access Journals (Sweden)

    Perrone-Bertolotti eMarcela

    2016-03-01

    Full Text Available In this functional magnetic resonance imaging (fMRI study, we evaluated the effect of self-relevance on cerebral activity and behavioral performance during an incidental encoding task. Recent findings suggest that pleasantness judgments reliably induce self-oriented (internal thoughts and increase default mode network (DMN activity. We hypothesized that this increase in DMN activity would relate to increased memory recognition for pleasantly-judged stimuli (which depend on internally-oriented attention but decreased recognition for unpleasantly-judged items (which depend on externally-oriented attention. To test this hypothesis, brain activity was recorded from 21 healthy participants while they performed a pleasantness judgment requiring them to rate visual stimuli as pleasant or unpleasant. One hour later, participants performed a surprise memory recognition test outside of the scanner. Thus, we were able to evaluate the effects of pleasant and unpleasant judgments on cerebral activity and incidental encoding. The behavioral results showed that memory recognition was better for items rated as pleasant than items rated as unpleasant. The whole brain analysis indicated that successful encoding activates the inferior frontal and lateral temporal cortices, whereas unsuccessful encoding recruits two key medial posterior DMN regions, the posterior cingulate cortex and precuneus. A region of interest analysis including classic DMN areas, revealed significantly greater involvement of the medial Prefrontal Cortex in pleasant compared to unpleasant judgments, suggesting this region’s involvement in self-referential (i.e., internal processing. This area may be responsible for the greater recognition performance seen for pleasant stimuli. Furthermore, a significant interaction between the encoding performance (successful vs. unsuccessful and pleasantness was observed for the posterior cingulate cortex, precuneus and inferior frontal gyrus. Overall, our

  3. Selected aspects of modelling of foreign exchange rates with neural networks

    Directory of Open Access Journals (Sweden)

    Václav Mastný

    2005-01-01

    Full Text Available This paper deals with forecasting of the high-frequency foreign exchange market with neural networks. The objective is to investigate some aspects of modelling with neural networks (impact of topology, size of training set and time horizon of the forecast on the performance of the network. The data used for the purpose of this paper contain 15-minute time series of US dollar against other major currencies, Japanese Yen, British Pound and Euro. The results show, that performance of the network in terms of correct directorial change is negatively influenced by increasing number of hidden neurons and decreasing size of training set. The performance of the network is influenced by sampling frequency.

  4. Blogs and Social Network Sites as Activity Systems: Exploring Adult Informal Learning Process through Activity Theory Framework

    Science.gov (United States)

    Heo, Gyeong Mi; Lee, Romee

    2013-01-01

    This paper uses an Activity Theory framework to explore adult user activities and informal learning processes as reflected in their blogs and social network sites (SNS). Using the assumption that a web-based space is an activity system in which learning occurs, typical features of the components were investigated and each activity system then…

  5. Active Supervision and Its Impact upon Parolee Recidivism Rates

    Science.gov (United States)

    Ostermann, Michael

    2013-01-01

    Studies that compare recidivism rates between parolees and unconditionally released inmates typically attach these statuses upon release, and then follow these groups until they either fail or meet the censor date. However, this method of identifying former inmates as parolees does not comport with how parolees are conceptualized by the agencies…

  6. Comparison of GPU- and CPU-implementations of mean-firing rate neural networks on parallel hardware.

    Science.gov (United States)

    Dinkelbach, Helge Ülo; Vitay, Julien; Beuth, Frederik; Hamker, Fred H

    2012-01-01

    Modern parallel hardware such as multi-core processors (CPUs) and graphics processing units (GPUs) have a high computational power which can be greatly beneficial to the simulation of large-scale neural networks. Over the past years, a number of efforts have focused on developing parallel algorithms and simulators best suited for the simulation of spiking neural models. In this article, we aim at investigating the advantages and drawbacks of the CPU and GPU parallelization of mean-firing rate neurons, widely used in systems-level computational neuroscience. By comparing OpenMP, CUDA and OpenCL implementations towards a serial CPU implementation, we show that GPUs are better suited than CPUs for the simulation of very large networks, but that smaller networks would benefit more from an OpenMP implementation. As this performance strongly depends on data organization, we analyze the impact of various factors such as data structure, memory alignment and floating precision. We then discuss the suitability of the different hardware depending on the networks' size and connectivity, as random or sparse connectivities in mean-firing rate networks tend to break parallel performance on GPUs due to the violation of coalescence.

  7. Numerical Modeling of Variable Fluid Injection-Rate Modes on Fracturing Network Evolution in Naturally Fractured Formations

    Directory of Open Access Journals (Sweden)

    Yu Wang

    2016-05-01

    Full Text Available In this study, variable injection-rate technology was numerically investigated in a pre-existing discrete fracture network (DFN formation, the Tarim Basin in China. A flow-stress-damage (FSD coupling model has been used in an initial attempt towards how reservoir response to variable injection-rates at different hydraulic fracturing stages. The established numerical model simultaneously considered the macroscopic and microscopic heterogeneity characteristics. Eight numerical cases were studied. Four cases were used to study the variable injection-rate technology, and the other four cases were applied for a constant injection-rate in order to compare with the variable injection-rate technology. The simulation results show that the variable injection-rate technology is a potentially good method to a form complex fracturing networks. The hydraulic fracturing effectiveness when increasing the injection-rate at each stage is the best, also, the total injected fluid is at a minimum. At the initial stage, many under-fracturing points appear around the wellbore with a relatively low injection-rate; the sudden increase of injection rate drives the dynamic propagation of hydraulic fractures along many branching fracturing points. However, the case with decreasing injection rate is the worst. By comparing with constant injection-rate cases, the hydraulic fracturing effectiveness with variable flow rate technology is generally better than those with constant injection-rate technology. This work strongly links the production technology and hydraulic fracturing effectiveness evaluation and aids in the understanding and optimization of hydraulic fracturing simulations in naturally fractured reservoirs.

  8. Evaluation of Techniques to Detect Significant Network Performance Problems using End-to-End Active Network Measurements

    Energy Technology Data Exchange (ETDEWEB)

    Cottrell, R.Les; Logg, Connie; Chhaparia, Mahesh; /SLAC; Grigoriev, Maxim; /Fermilab; Haro, Felipe; /Chile U., Catolica; Nazir, Fawad; /NUST, Rawalpindi; Sandford, Mark

    2006-01-25

    End-to-End fault and performance problems detection in wide area production networks is becoming increasingly hard as the complexity of the paths, the diversity of the performance, and dependency on the network increase. Several monitoring infrastructures are built to monitor different network metrics and collect monitoring information from thousands of hosts around the globe. Typically there are hundreds to thousands of time-series plots of network metrics which need to be looked at to identify network performance problems or anomalous variations in the traffic. Furthermore, most commercial products rely on a comparison with user configured static thresholds and often require access to SNMP-MIB information, to which a typical end-user does not usually have access. In our paper we propose new techniques to detect network performance problems proactively in close to realtime and we do not rely on static thresholds and SNMP-MIB information. We describe and compare the use of several different algorithms that we have implemented to detect persistent network problems using anomalous variations analysis in real end-to-end Internet performance measurements. We also provide methods and/or guidance for how to set the user settable parameters. The measurements are based on active probes running on 40 production network paths with bottlenecks varying from 0.5Mbits/s to 1000Mbit/s. For well behaved data (no missed measurements and no very large outliers) with small seasonal changes most algorithms identify similar events. We compare the algorithms' robustness with respect to false positives and missed events especially when there are large seasonal effects in the data. Our proposed techniques cover a wide variety of network paths and traffic patterns. We also discuss the applicability of the algorithms in terms of their intuitiveness, their speed of execution as implemented, and areas of applicability. Our encouraging results compare and evaluate the accuracy of our

  9. Resonance of about-weekly human heart rate rhythm with solar activity change.

    Science.gov (United States)

    Cornelissen, G; Halberg, F; Wendt, H W; Bingham, C; Sothern, R B; Haus, E; Kleitman, E; Kleitman, N; Revilla, M A; Revilla, M; Breus, T K; Pimenov, K; Grigoriev, A E; Mitish, M D; Yatsyk, G V; Syutkina, E V

    1996-12-01

    In several human adults, certain solar activity rhythms may influence an about 7-day rhythm in heart rate. When no about-weekly feature was found in the rate of change in sunspot area, a measure of solar activity, the double amplitude of a circadian heart rate rhythm, approximated by the fit of a 7-day cosine curve, was lower, as was heart rate corresponds to about-weekly features in solar activity and/or relates to a sunspot cycle.

  10. Precise calculation of a bond percolation transition and survival rates of nodes in a complex network.

    Science.gov (United States)

    Kawamoto, Hirokazu; Takayasu, Hideki; Jensen, Henrik Jeldtoft; Takayasu, Misako

    2015-01-01

    Through precise numerical analysis, we reveal a new type of universal loopless percolation transition in randomly removed complex networks. As an example of a real-world network, we apply our analysis to a business relation network consisting of approximately 3,000,000 links among 300,000 firms and observe the transition with critical exponents close to the mean-field values taking into account the finite size effect. We focus on the largest cluster at the critical point, and introduce survival probability as a new measure characterizing the robustness of each node. We also discuss the relation between survival probability and k-shell decomposition.

  11. Lognormal firing rate distribution reveals prominent fluctuation-driven regime in spinal motor networks

    DEFF Research Database (Denmark)

    Petersen, Peter C.; Berg, Rune W.

    2016-01-01

    When spinal circuits generate rhythmic movements it is important that the neuronal activity remains within stable bounds to avoid saturation and to preserve responsiveness. Here, we simultaneously record from hundreds of neurons in lumbar spinal circuits of turtles and establish the neuronal...... fraction that operates within either a ‘mean-driven’ or a ‘fluctuation–driven’ regime. Fluctuation-driven neurons have a ‘supralinear’ input-output curve, which enhances sensitivity, whereas the mean-driven regime reduces sensitivity. We find a rich diversity of firing rates across the neuronal population...... as reflected in a lognormal distribution and demonstrate that half of the neurons spend at least 50 %% of the time in the ‘fluctuation–driven’ regime regardless of behavior. Because of the disparity in input–output properties for these two regimes, this fraction may reflect a fine trade–off between stability...

  12. Screening of TB Actives for Activity against Nontuberculous Mycobacteria Delivers High Hit Rates

    Directory of Open Access Journals (Sweden)

    Jian Liang Low

    2017-08-01

    Full Text Available The prevalence of lung disease due to infections with nontuberculous mycobacteria (NTM has been increasing and surpassed tuberculosis (TB in some countries. Treatment outcomes are often unsatisfactory, highlighting an urgent need for new anti-NTM medications. Although NTM in general do not respond well to TB specific drugs, the similarities between NTM and Mycobacterium tuberculosis at the molecular and cell structural level suggest that compound libraries active against TB could be leveraged for NTM drug discovery. Here we tested this hypothesis. The Pathogen Box from the Medicines for Malaria Venture (MMV is a collection of 400 diverse drug-like compounds, among which 129 are known to be active against M. tuberculosis. By screening this compound collection against two NTM species, Mycobacterium abscessus and Mycobacterium avium, we showed that indeed the hit rates for NTM among TB active compounds is significantly higher compared to compounds that are not active against TB. MIC/dose response confirmation identified 10 top hits. Bactericidal activity determination demonstrated attractive potency for a subset of the confirmed hits. In vivo pharmacokinetic profiling showed that some of the compounds present reasonable starting points for medicinal chemistry programs. Three of the top hits were oxazolidinones, suggesting the potential for repositioning this class of protein synthesis inhibitors to replace linezolid which suffers from low potency. Two hits were inhibitors of the trehalose monomycolate transporter MmpL3, suggesting that this transmembrane protein may be an attractive target for NTM. Other hits are predicted to target a range of functions, including cell division (FtsZ, DNA gyrase (GyrB, dihydrofolate reductase, RNA polymerase and ABC transporters. In conclusion, our study showed that screening TB active compounds for activity against NTM resulted in high hit rates, suggesting that this may be an attractive approach to kick start NTM

  13. Beneficial effect of physical activity on linear growth rate of ...

    African Journals Online (AJOL)

    It is not known if nutritional and/or other interventions could improve linear growth in adolescents. The purpose of this study was to assess the role of physical activity in promoting linear growth velocity of black adolescents in a low-income shanty town in South Africa. Two schools in a disadvantaged shanty town participated ...

  14. Social Network resources and self-rated health in a deprived Danish neighborhood

    DEFF Research Database (Denmark)

    Tanggaard Andersen, Pernille; Holst Algren, Maria; Fromsejer Heiberg, Regina

    2017-01-01

    by social network resources. This is the main aim of this article. Cross-sectional data from one deprived neighborhood located in Denmark were collected in 2008 and 2013 using a postal health survey. The target group was defined as adults older than 16 years. In 2008, 408 residents participated......Research has demonstrated that living in a deprived neighborhood contributes to the occurrence and development of poor health. Furthermore evidence shows that social networks are fundamental resources in preventing poor mental health. Neighborhood relationships and networks are vital for sustaining...... in the survey, and 405 residents participated in 2013. Our main explanatory variables were indicators of socioeconomic positions and social network resources. The analyses were conducted using univariate and bivariate analyses and multiple logistic regressions. The results showed that there was a significant...

  15. Network of photonic sensors for CO2 exchange rate measurement in forests

    Science.gov (United States)

    Sobotka, Piotr; Bieda, Marcin S.; Lesiak, Piotr; Woliński, Tomasz R.

    2017-08-01

    A network of photonic CO2 sensors based on distributed sensing elements that are spread around the tested ecosystem area is proposed. Each of the sensing elements is connected to a wireless network with adjacent sensing elements and a base station that collects, archives, and analyzes results of measurements. The sensing element includes a CO2 sensor module for data transmission as well as power supply module that analyzes speed and direction of flow of the air mass within the specified measurement point.

  16. Experimental Demonstration of Mixed Formats and Bit Rates Signal Allocation for Spectrum-flexible Optical Networking

    DEFF Research Database (Denmark)

    Borkowski, Robert; Karinou, Fotini; Angelou, Marianna

    2012-01-01

    We report on an extensive experimental study for adaptive allocation of 16-QAM and QPSK signals inside spectrum flexible heterogeneous superchannel. Physical-layer performance parameters are extracted for use in resource allocation mechanisms of future flexible networks.......We report on an extensive experimental study for adaptive allocation of 16-QAM and QPSK signals inside spectrum flexible heterogeneous superchannel. Physical-layer performance parameters are extracted for use in resource allocation mechanisms of future flexible networks....

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

    Directory of Open Access Journals (Sweden)

    Sheng-Jun Wang

    2011-06-01

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

  18. Young adolescents' perceived activity space risk, peer networks, and substance use.

    Science.gov (United States)

    Mason, Michael; Mennis, Jeremy; Way, Thomas; Light, John; Rusby, Julie; Westling, Erika; Crewe, Stephanie; Flay, Brian; Campbell, Leah; Zaharakis, Nikola; McHenry, Chantal

    2015-07-01

    Adolescent substance use is a developmentally contingent social practice that is constituted within the routine social-environment of adolescents' lives. Few studies have examined peer networks, perceived activity space risk (risk of substance use at routine locations), and substance use. We examined the moderating influence of peer network characteristics on the relationship between perceived activity space risk and substance use among a sample of 250 urban adolescents. Significant interactions were found between peer networks and perceived activity space risk on tobacco and marijuana use, such that protective peer networks reduced the effect of activity place risk on substance use. A significant 3-way interaction was found on marijuana use indicating that gender moderated peer network's effect on activity space risk. Conditional effect analysis found that boys' peer networks moderated the effect of perceived activity space risk on marijuana use, whereas for girls, the effect of perceived activity space risk on marijuana use was not moderated by their peer networks. These findings could advance theoretical models to inform social-environmental research among adolescents. Copyright © 2015 Elsevier Ltd. All rights reserved.

  19. The association between network social capital and self-rated health: pouring old wine in new bottles?

    Science.gov (United States)

    Verhaeghe, Pieter-Paul; Pattyn, Elise; Bracke, Piet; Verhaeghe, Mieke; Van De Putte, Bart

    2012-03-01

    This study examines whether there is an association between network social capital and self-rated health after controlling for social support. Moreover, we distinguish between network social capital that emerges from strong ties and weak ties. We used a cross-sectional representative sample of 815 adults from the Belgian population. Social capital is measured with the position generator and perceived social support with the MOS Social Support-scale. Results suggest that network social capital is associated with self-rated health after adjustment for social support. Because different social classes have access to different sets of resources, resources of friends and family from the intermediate and higher service classes are beneficial for self-rated health, whereas resources of friends and family from the working class appear to be rather detrimental for self-rated health. From a health-promoting perspective, these findings indicate that policy makers should deal with the root causes of socioeconomic disadvantages in society. Copyright © 2011 Elsevier Ltd. All rights reserved.

  20. Active patterning and asymmetric transport in a model actomyosin network

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Shenshen [Department of Chemical Engineering and Department of Physics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 (United States); Wolynes, Peter G. [Department of Chemistry and Center for Theoretical Biological Physics, Rice University, Houston, Texas 77005 (United States)

    2013-12-21

    Cytoskeletal networks, which are essentially motor-filament assemblies, play a major role in many developmental processes involving structural remodeling and shape changes. These are achieved by nonequilibrium self-organization processes that generate functional patterns and drive intracellular transport. We construct a minimal physical model that incorporates the coupling between nonlinear elastic responses of individual filaments and force-dependent motor action. By performing stochastic simulations we show that the interplay of motor processes, described as driving anti-correlated motion of the network vertices, and the network connectivity, which determines the percolation character of the structure, can indeed capture the dynamical and structural cooperativity which gives rise to diverse patterns observed experimentally. The buckling instability of individual filaments is found to play a key role in localizing collapse events due to local force imbalance. Motor-driven buckling-induced node aggregation provides a dynamic mechanism that stabilizes the two-dimensional patterns below the apparent static percolation limit. Coordinated motor action is also shown to suppress random thermal noise on large time scales, the two-dimensional configuration that the system starts with thus remaining planar during the structural development. By carrying out similar simulations on a three-dimensional anchored network, we find that the myosin-driven isotropic contraction of a well-connected actin network, when combined with mechanical anchoring that confers directionality to the collective motion, may represent a novel mechanism of intracellular transport, as revealed by chromosome translocation in the starfish oocyte.

  1. Phencyclidine Discoordinates Hippocampal Network Activity But Not Place Fields.

    Science.gov (United States)

    Kao, Hsin-Yi; Dvořák, Dino; Park, EunHye; Kenney, Jana; Kelemen, Eduard; Fenton, André A

    2017-12-06

    We used the psychotomimetic phencyclidine (PCP) to investigate the relationships among cognitive behavior, coordinated neural network function, and information processing within the hippocampus place cell system. We report in rats that PCP (5 mg/kg, i.p.) impairs a well learned, hippocampus-dependent place avoidance behavior in rats that requires cognitive control even when PCP is injected directly into dorsal hippocampus. PCP increases 60-100 Hz medium-freguency gamma oscillations in hippocampus CA1 and these increases correlate with the cognitive impairment caused by systemic PCP administration. PCP discoordinates theta-modulated medium-frequency and slow gamma oscillations in CA1 LFPs such that medium-frequency gamma oscillations become more theta-organized than slow gamma oscillations. CA1 place cell firing fields are preserved under PCP, but the drug discoordinates the subsecond temporal organization of discharge among place cells. This discoordination causes place cell ensemble representations of a familiar space to cease resembling pre-PCP representations despite preserved place fields. These findings point to the cognitive impairments caused by PCP arising from neural discoordination. PCP disrupts the timing of discharge with respect to the subsecond timescales of theta and gamma oscillations in the LFP. Because these oscillations arise from local inhibitory synaptic activity, these findings point to excitation-inhibition discoordination as the root of PCP-induced cognitive impairment.SIGNIFICANCE STATEMENT Hippocampal neural discharge is temporally coordinated on timescales of theta and gamma oscillations in the LFP and the discharge of a subset of pyramidal neurons called "place cells" is spatially organized such that discharge is restricted to locations called a cell's "place field." Because this temporal coordination and spatial discharge organization is thought to represent spatial knowledge, we used the psychotomimetic phencyclidine (PCP) to disrupt

  2. Effects of active links on epidemic transmission over social networks

    Science.gov (United States)

    Zhu, Guanghu; Chen, Guanrong; Fu, Xinchu

    2017-02-01

    A new epidemic model with two infection periods is developed to account for the human behavior in social network, where newly infected individuals gradually restrict most of future contacts or are quarantined, causing infectivity change from a degree-dependent form to a constant. The corresponding dynamics are formulated by a set of ordinary differential equations (ODEs) via mean-field approximation. The effects of diverse infectivity on the epidemic dynamics ​are examined, with a behavioral interpretation of the basic reproduction number. Results show that such simple adaptive reactions largely determine the impact of network structure on epidemics. Particularly, a theorem proposed by Lajmanovich and Yorke in 1976 is generalized, so that it can be applied for the analysis of the epidemic models with multi-compartments especially network-coupled ODE systems.

  3. Simultaneous water activation and glucose metabolic rate imaging with PET.

    Science.gov (United States)

    Verhaeghe, Jeroen; Reader, Andrew J

    2013-02-07

    A novel imaging and signal separation strategy is proposed to be able to separate [(18)F]FDG and multiple [(15)O]H(2)O signals from a simultaneously acquired dynamic PET acquisition of the two tracers. The technique is based on the fact that the dynamics of the two tracers are very distinct. By adopting an appropriate bolus injection strategy and by defining tailored sets of basis functions that model either the FDG or water component, it is possible to separate the FDG and water signal. The basis functions are inspired from the spectral analysis description of dynamic PET studies and are defined as the convolution of estimated generating functions (GFs) with a set of decaying exponential functions. The GFs are estimated from the overall measured head curve, while the decaying exponential functions are pre-determined. In this work, the time activity curves (TACs) are modelled post-reconstruction but the model can be incorporated in a global 4D reconstruction strategy. Extensive PET simulation studies are performed considering single [(18)F]FDG and 6 [(15)O]H(2)O bolus injections for a total acquisition time of 75 min. The proposed method is evaluated at multiple noise levels and different parameters were estimated such as [(18)F]FDG uptake and blood flow estimated from the [(15)O]H(2)O component, requiring a full dynamic analysis of the two components, static images of [(18)F]FDG and the water components as well as [(15)O]H(2)O activation. It is shown that the resulting images and parametric values in ROIs are comparable to images obtained from separate imaging, illustrating the feasibility of simultaneous imaging of [(18)F]FDG and [(15)O]H(2)O components.

  4. Method and Apparatus for Predicting Unsteady Pressure and Flow Rate Distribution in a Fluid Network

    Science.gov (United States)

    Majumdar, Alok K. (Inventor)

    2009-01-01

    A method and apparatus for analyzing steady state and transient flow in a complex fluid network, modeling phase changes, compressibility, mixture thermodynamics, external body forces such as gravity and centrifugal force and conjugate heat transfer. In some embodiments, a graphical user interface provides for the interactive development of a fluid network simulation having nodes and branches. In some embodiments, mass, energy, and specific conservation equations are solved at the nodes, and momentum conservation equations are solved in the branches. In some embodiments, contained herein are data objects for computing thermodynamic and thermophysical properties for fluids. In some embodiments, the systems of equations describing the fluid network are solved by a hybrid numerical method that is a combination of the Newton-Raphson and successive substitution methods.

  5. Tourist activated networks: Implications for dynamic bundling and en-route recommendations

    DEFF Research Database (Denmark)

    Zach, Florian; Gretzel, Ulrike

    2011-01-01

    This article discusses tourist-activated networks as a concept to inform technological applications supporting dynamic bundling and en route recommendations. Empirical data were collected from travelers who visited a regional destination in the US and then analyzed with respect to its network str...... marketing....

  6. High catalytic activity of palladium nanoparticle clusters supported on a spherical polymer network.

    Science.gov (United States)

    Sultanova, Elza D; Salnikov, Vadim V; Mukhitova, Rezeda K; Zuev, Yuriy F; Osin, Yuriy N; Zakharova, Lucia Ya; Ziganshina, Albina Y; Konovalov, Alexander I

    2015-09-04

    In this communication we report the synthesis of Pd nanoparticle clusters achieved via the assembly of Pd nanoparticles on the surface of a spherical polymer network. The network exhibits flexibility and adapts to the cluster formation. The nanoclusters display high catalytic activity toward p-nitrophenol reduction and the Suzuki-Miyaura coupling reaction.

  7. DELTAMETHRIN AND ESFENVALERATE INHIBIT SPONTANEOUS NETWORK ACTIVITY IN RAT CORTICAL NEURONS IN VITRO.

    Science.gov (United States)

    Understanding pyrethroid actions on neuronal networks will help to establish a mode of action for these compounds, which is needed for cumulative risk decisions under the Food Quality Protection Act of 1996. However, pyrethroid effects on spontaneous activity in networks of inter...

  8. AST: Activity-Security-Trust driven modeling of time varying networks.

    Science.gov (United States)

    Wang, Jian; Xu, Jiake; Liu, Yanheng; Deng, Weiwen

    2016-02-18

    Network modeling is a flexible mathematical structure that enables to identify statistical regularities and structural principles hidden in complex systems. The majority of recent driving forces in modeling complex networks are originated from activity, in which an activity potential of a time invariant function is introduced to identify agents' interactions and to construct an activity-driven model. However, the new-emerging network evolutions are already deeply coupled with not only the explicit factors (e.g. activity) but also the implicit considerations (e.g. security and trust), so more intrinsic driving forces behind should be integrated into the modeling of time varying networks. The agents undoubtedly seek to build a time-dependent trade-off among activity, security, and trust in generating a new connection to another. Thus, we reasonably propose the Activity-Security-Trust (AST) driven model through synthetically considering the explicit and implicit driving forces (e.g. activity, security, and trust) underlying the decision process. AST-driven model facilitates to more accurately capture highly dynamical network behaviors and figure out the complex evolution process, allowing a profound understanding of the effects of security and trust in driving network evolution, and improving the biases induced by only involving activity representations in analyzing the dynamical processes.

  9. Advances in the GRADE approach to rate the certainty in estimates from a network meta-analysis.

    Science.gov (United States)

    Brignardello-Petersen, Romina; Bonner, Ashley; Alexander, Paul E; Siemieniuk, Reed A; Furukawa, Toshi A; Rochwerg, Bram; Hazlewood, Glen S; Alhazzani, Waleed; Mustafa, Reem A; Murad, M Hassan; Puhan, Milo A; Schünemann, Holger J; Guyatt, Gordon H

    2018-01-01

    This article describes conceptual advances of the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) working group guidance to evaluate the certainty of evidence (confidence in evidence, quality of evidence) from network meta-analysis (NMA). Application of the original GRADE guidance, published in 2014, in a number of NMAs has resulted in advances that strengthen its conceptual basis and make the process more efficient. This guidance will be useful for systematic review authors who aim to assess the certainty of all pairwise comparisons from an NMA and who are familiar with the basic concepts of NMA and the traditional GRADE approach for pairwise meta-analysis. Two principles of the original GRADE NMA guidance are that we need to rate the certainty of the evidence for each pairwise comparison within a network separately and that in doing so we need to consider both the direct and indirect evidence. We present, discuss, and illustrate four conceptual advances: (1) consideration of imprecision is not necessary when rating the direct and indirect estimates to inform the rating of NMA estimates, (2) there is no need to rate the indirect evidence when the certainty of the direct evidence is high and the contribution of the direct evidence to the network estimate is at least as great as that of the indirect evidence, (3) we should not trust a statistical test of global incoherence of the network to assess incoherence at the pairwise comparison level, and (4) in the presence of incoherence between direct and indirect evidence, the certainty of the evidence of each estimate can help decide which estimate to believe. Copyright © 2017 Elsevier Inc. All rights reserved.

  10. Perceived influence and college students' diet and physical activity behaviors: an examination of ego-centric social networks.

    Science.gov (United States)

    Harmon, Brook E; Forthofer, Melinda; Bantum, Erin O; Nigg, Claudio R

    2016-06-06

    Obesity is partially a social phenomenon, with college students particularly vulnerable to changes in social networks and obesity-related behaviors. Currently, little is known about the structure of social networks among college students and their potential influence on diet and physical activity behaviors. The purpose of the study was to examine social influences impacting college students' diet and physical activity behaviors, including sources of influence, comparisons between sources' and students' behaviors, and associations with meeting diet and physical activity recommendations. Data was collected from 40 students attending college in Hawaii. Participants completed diet and physical activity questionnaires and a name generator. Participants rated nominees' influence on their diet and physical activity behaviors as well as compared nominees' behaviors to their own. Descriptive statistics were used to look at perceptions of influence across network groups. Logistic regression models were used to examine associations between network variables and odds of meeting recommendations. A total of 325 nominations were made and included: family (n = 116), college friends (n = 104), high school friends (n = 87), and significant others (n = 18). Nearly half of participants were not from Hawaii. Significant others of non-Hawaii students were perceived to be the most influential (M(SD) = 9(1.07)) and high school friends the least influential (M(SD) = 1.31(.42)) network. Overall, perceived influence was highest for diet compared to physical activity, but varied based on comparisons with nominees' behaviors. Significant others were most often perceived has having similar (44 %) or worse (39 %) eating behaviors than participants, and those with similar eating behaviors were perceived as most influential (M(SD) = 9.25(1.04)). Few associations were seen between network variables and odds of meeting recommendations. Among the groups nominated, high

  11. Structural plasticity of GABAergic axons is regulated by network activity and GABAA receptor activation

    Directory of Open Access Journals (Sweden)

    Anne eSchuemann

    2013-06-01

    Full Text Available Coordinated changes at excitatory and inhibitory synapses are essential for normal brain development and function. It is well established that excitatory neurons undergo structural changes, but our knowledge about inhibitory structural plasticity is rather scarce. Here we present a quantitative analysis of the dynamics of GABAergic boutons in the dendritic region of the hippocampal CA1 area using time-lapse two-photon imaging in organotypic hippocampal cultures from GAD65-GFP mice. We show that ~20% of inhibitory boutons are not stable. They are appearing, disappearing and reappearing at specific locations along the inhibitory axon and reflect immature or incomplete synapses. Furthermore, we observed that persistent boutons show large volume fluctuations over several hours, suggesting that presynaptic content of inhibitory synapses is not constant. Our data show that inhibitory boutons are highly dynamic structures and suggest that inhibitory axons are continuously probing potential locations for inhibitory synapse formation by redistributing presynaptic material along the axon.In addition, we found that neuronal activity affects the exploratory dynamics of inhibitory axons. Blocking network activity rapidly reduces the number of transient boutons, whereas enhancing activity reduces the number of persistent inhibitory boutons, possibly reflecting enhanced competition between boutons along the axon. The latter effect requires signaling through GABAA receptors. We propose that activity-dependent regulation of bouton dynamics contributes to inhibitory synaptic plasticity.

  12. Fundamental Active Current Adaptive Linear Neural Networks for Photovoltaic Shunt Active Power Filters

    Directory of Open Access Journals (Sweden)

    Muhammad Ammirrul Atiqi Mohd Zainuri

    2016-05-01

    Full Text Available This paper presents improvement of a harmonics extraction algorithm, known as the fundamental active current (FAC adaptive linear element (ADALINE neural network with the integration of photovoltaic (PV to shunt active power filters (SAPFs as active current source. Active PV injection in SAPFs should reduce dependency on grid supply current to supply the system. In addition, with a better and faster harmonics extraction algorithm, the SAPF should perform well, especially under dynamic PV and load conditions. The role of the actual injection current from SAPF after connecting PVs will be evaluated, and the better effect of using FAC ADALINE will be confirmed. The proposed SAPF was simulated and evaluated in MATLAB/Simulink first. Then, an experimental laboratory prototype was also developed to be tested with a PV simulator (CHROMA 62100H-600S, and the algorithm was implemented using a TMS320F28335 Digital Signal Processor (DSP. From simulation and experimental results, significant improvements in terms of total harmonic distortion (THD, time response and reduction of source power from grid have successfully been verified and achieved.

  13. Growth dynamics explain the development of spatiotemporal burst activity of young cultured neuronal networks in detail.

    Science.gov (United States)

    Gritsun, Taras A; le Feber, Joost; Rutten, Wim L C

    2012-01-01

    A typical property of isolated cultured neuronal networks of dissociated rat cortical cells is synchronized spiking, called bursting, starting about one week after plating, when the dissociated cells have sufficiently sent out their neurites and formed enough synaptic connections. This paper is the third in a series of three on simulation models of cultured networks. Our two previous studies [26], [27] have shown that random recurrent network activity models generate intra- and inter-bursting patterns similar to experimental data. The networks were noise or pacemaker-driven and had Izhikevich-neuronal elements with only short-term plastic (STP) synapses (so, no long-term potentiation, LTP, or depression, LTD, was included). However, elevated pre-phases (burst leaders) and after-phases of burst main shapes, that usually arise during the development of the network, were not yet simulated in sufficient detail. This lack of detail may be due to the fact that the random models completely missed network topology .and a growth model. Therefore, the present paper adds, for the first time, a growth model to the activity model, to give the network a time dependent topology and to explain burst shapes in more detail. Again, without LTP or LTD mechanisms. The integrated growth-activity model yielded realistic bursting patterns. The automatic adjustment of various mutually interdependent network parameters is one of the major advantages of our current approach. Spatio-temporal bursting activity was validated against experiment. Depending on network size, wave reverberation mechanisms were seen along the network boundaries, which may explain the generation of phases of elevated firing before and after the main phase of the burst shape.In summary, the results show that adding topology and growth explain burst shapes in great detail and suggest that young networks still lack/do not need LTP or LTD mechanisms.

  14. Growth Dynamics Explain the Development of Spatiotemporal Burst Activity of Young Cultured Neuronal Networks in Detail

    Science.gov (United States)

    Gritsun, Taras A.; le Feber, Joost; Rutten, Wim L. C.

    2012-01-01

    A typical property of isolated cultured neuronal networks of dissociated rat cortical cells is synchronized spiking, called bursting, starting about one week after plating, when the dissociated cells have sufficiently sent out their neurites and formed enough synaptic connections. This paper is the third in a series of three on simulation models of cultured networks. Our two previous studies [26], [27] have shown that random recurrent network activity models generate intra- and inter-bursting patterns similar to experimental data. The networks were noise or pacemaker-driven and had Izhikevich-neuronal elements with only short-term plastic (STP) synapses (so, no long-term potentiation, LTP, or depression, LTD, was included). However, elevated pre-phases (burst leaders) and after-phases of burst main shapes, that usually arise during the development of the network, were not yet simulated in sufficient detail. This lack of detail may be due to the fact that the random models completely missed network topology .and a growth model. Therefore, the present paper adds, for the first time, a growth model to the activity model, to give the network a time dependent topology and to explain burst shapes in more detail. Again, without LTP or LTD mechanisms. The integrated growth-activity model yielded realistic bursting patterns. The automatic adjustment of various mutually interdependent network parameters is one of the major advantages of our current approach. Spatio-temporal bursting activity was validated against experiment. Depending on network size, wave reverberation mechanisms were seen along the network boundaries, which may explain the generation of phases of elevated firing before and after the main phase of the burst shape.In summary, the results show that adding topology and growth explain burst shapes in great detail and suggest that young networks still lack/do not need LTP or LTD mechanisms. PMID:23028450

  15. Growth dynamics explain the development of spatiotemporal burst activity of young cultured neuronal networks in detail.

    Directory of Open Access Journals (Sweden)

    Taras A Gritsun

    Full Text Available A typical property of isolated cultured neuronal networks of dissociated rat cortical cells is synchronized spiking, called bursting, starting about one week after plating, when the dissociated cells have sufficiently sent out their neurites and formed enough synaptic connections. This paper is the third in a series of three on simulation models of cultured networks. Our two previous studies [26], [27] have shown that random recurrent network activity models generate intra- and inter-bursting patterns similar to experimental data. The networks were noise or pacemaker-driven and had Izhikevich-neuronal elements with only short-term plastic (STP synapses (so, no long-term potentiation, LTP, or depression, LTD, was included. However, elevated pre-phases (burst leaders and after-phases of burst main shapes, that usually arise during the development of the network, were not yet simulated in sufficient detail. This lack of detail may be due to the fact that the random models completely missed network topology .and a growth model. Therefore, the present paper adds, for the first time, a growth model to the activity model, to give the network a time dependent topology and to explain burst shapes in more detail. Again, without LTP or LTD mechanisms. The integrated growth-activity model yielded realistic bursting patterns. The automatic adjustment of various mutually interdependent network parameters is one of the major advantages of our current approach. Spatio-temporal bursting activity was validated against experiment. Depending on network size, wave reverberation mechanisms were seen along the network boundaries, which may explain the generation of phases of elevated firing before and after the main phase of the burst shape.In summary, the results show that adding topology and growth explain burst shapes in great detail and suggest that young networks still lack/do not need LTP or LTD mechanisms.

  16. Effects of correlated Gaussian noise on the mean firing rate and correlations of an electrically coupled neuronal network.

    Science.gov (United States)

    Sun, Xiaojuan; Perc, Matjaz; Lu, Qishao; Kurths, Jürgen

    2010-09-01

    In this paper, we examine the effects of correlated Gaussian noise on a two-dimensional neuronal network that is locally modeled by the Rulkov map. More precisely, we study the effects of the noise correlation on the variations of the mean firing rate and the correlations among neurons versus the noise intensity. Via numerical simulations, we show that the mean firing rate can always be optimized at an intermediate noise intensity, irrespective of the noise correlation. On the other hand, variations of the population coherence with respect to the noise intensity are strongly influenced by the ratio between local and global Gaussian noisy inputs. Biological implications of our findings are also discussed.

  17. Recommending Learning Activities in Social Network Using Data Mining Algorithms

    Science.gov (United States)

    Mahnane, Lamia

    In this paper, we show how data mining algorithms (e.g. Apriori Algorithm (AP) and Collaborative Filtering (CF)) is useful in New Social Network (NSN-AP-CF). "NSN-AP-CF" processes the clusters based on different learning styles. Next, it analyzes the habits and the interests of the users through mining the frequent episodes by the…

  18. Recommending Learning Activities in Social Network Using Data Mining Algorithms

    Science.gov (United States)

    Mahnane, Lamia

    2017-01-01

    In this paper, we show how data mining algorithms (e.g. Apriori Algorithm (AP) and Collaborative Filtering (CF)) is useful in New Social Network (NSN-AP-CF). "NSN-AP-CF" processes the clusters based on different learning styles. Next, it analyzes the habits and the interests of the users through mining the frequent episodes by the…

  19. Fast demand response in support of the active distribution network

    NARCIS (Netherlands)

    MacDougall, P.; Heskes, P.; Crolla, P.; Burt, G.; Warmer, C.

    2013-01-01

    Demand side management has traditionally been investigated for "normal" operation services such as balancing and congestion management. However they potentially could be utilized for Distributed Network Operator (DNO) services. This paper investigates and validates the use of a supply and demand

  20. Voltage Estimation in Active Distribution Grids Using Neural Networks

    DEFF Research Database (Denmark)

    Pertl, Michael; Heussen, Kai; Gehrke, Oliver

    2016-01-01

    the observability of distribution systems has to be improved. To increase the situational awareness of the power system operator data driven methods can be employed. These methods benefit from newly available data sources such as smart meters. This paper presents a voltage estimation method based on neural networks...

  1. Emulation of the Active Immune Response in a Computer Network

    Science.gov (United States)

    2009-01-15

    there exist a number of methods connected to processes of optimization intended to solve several problems including immunotherapy and immuno ...researchers and security analysts to respond faster in order to keep up with these attacks. New approaches for network security analysis, reactive and

  2. Engineering Online and In-person Social Networks for Physical Activity: A Randomized Trial

    Science.gov (United States)

    Rovniak, Liza S.; Kong, Lan; Hovell, Melbourne F.; Ding, Ding; Sallis, James F.; Ray, Chester A.; Kraschnewski, Jennifer L.; Matthews, Stephen A.; Kiser, Elizabeth; Chinchilli, Vernon M.; George, Daniel R.; Sciamanna, Christopher N.

    2016-01-01

    Background Social networks can influence physical activity, but little is known about how best to engineer online and in-person social networks to increase activity. Purpose To conduct a randomized trial based on the Social Networks for Activity Promotion model to assess the incremental contributions of different procedures for building social networks on objectively-measured outcomes. Methods Physically inactive adults (n = 308, age, 50.3 (SD = 8.3) years, 38.3% male, 83.4% overweight/obese) were randomized to 1 of 3 groups. The Promotion group evaluated the effects of weekly emailed tips emphasizing social network interactions for walking (e.g., encouragement, informational support); the Activity group evaluated the incremental effect of adding an evidence-based online fitness walking intervention to the weekly tips; and the Social Networks group evaluated the additional incremental effect of providing access to an online networking site for walking, and prompting walking/activity across diverse settings. The primary outcome was mean change in accelerometer-measured moderate-to-vigorous physical activity (MVPA), assessed at 3 and 9 months from baseline. Results Participants increased their MVPA by 21.0 mins/week, 95% CI [5.9, 36.1], p = .005, at 3 months, and this change was sustained at 9 months, with no between-group differences. Conclusions Although the structure of procedures for targeting social networks varied across intervention groups, the functional effect of these procedures on physical activity was similar. Future research should evaluate if more powerful reinforcers improve the effects of social network interventions. Trial Registration Number NCT01142804 PMID:27405724

  3. Engineering Online and In-Person Social Networks for Physical Activity: A Randomized Trial.

    Science.gov (United States)

    Rovniak, Liza S; Kong, Lan; Hovell, Melbourne F; Ding, Ding; Sallis, James F; Ray, Chester A; Kraschnewski, Jennifer L; Matthews, Stephen A; Kiser, Elizabeth; Chinchilli, Vernon M; George, Daniel R; Sciamanna, Christopher N

    2016-12-01

    Social networks can influence physical activity, but little is known about how best to engineer online and in-person social networks to increase activity. The purpose of this study was to conduct a randomized trial based on the Social Networks for Activity Promotion model to assess the incremental contributions of different procedures for building social networks on objectively measured outcomes. Physically inactive adults (n = 308, age, 50.3 (SD = 8.3) years, 38.3 % male, 83.4 % overweight/obese) were randomized to one of three groups. The Promotion group evaluated the effects of weekly emailed tips emphasizing social network interactions for walking (e.g., encouragement, informational support); the Activity group evaluated the incremental effect of adding an evidence-based online fitness walking intervention to the weekly tips; and the Social Networks group evaluated the additional incremental effect of providing access to an online networking site for walking as well as prompting walking/activity across diverse settings. The primary outcome was mean change in accelerometer-measured moderate-to-vigorous physical activity (MVPA), assessed at 3 and 9 months from baseline. Participants increased their MVPA by 21.0 min/week, 95 % CI [5.9, 36.1], p = .005, at 3 months, and this change was sustained at 9 months, with no between-group differences. Although the structure of procedures for targeting social networks varied across intervention groups, the functional effect of these procedures on physical activity was similar. Future research should evaluate if more powerful reinforcers improve the effects of social network interventions. The trial was registered with the ClinicalTrials.gov (NCT01142804).

  4. The high-resolution structure of activated opsin reveals a conserved solvent network in the transmembrane region essential for activation

    Science.gov (United States)

    Blankenship, Elise; Vahedi-Faridi, Ardeschir; Lodowski, David T.

    2015-01-01

    Rhodopsin, a light-activated G protein coupled receptor (GPCR), has been the subject of numerous biochemical and structural investigations, serving as a model receptor for GPCRs and their activation. Herein we present the 2.3 Å resolution structure of native-source rhodopsin stabilized in a conformation competent for G protein binding. An extensive water-mediated hydrogen bond network linking the chromophore binding site to the site of G protein binding is observed, providing connections to conserved motifs essential for GPCR activation. Comparison of this extensive solvent mediated hydrogen-bonding network to the positions of ordered solvent in earlier crystallographic structures of rhodopsin photointermediates reveals both static structural and dynamic functional water-protein interactions present during the activation process. When taken with observations that solvent occupies similar positions in the structures of other GPCRs, these analyses strongly support an integral role for this dynamic ordered water network in both rhodopsin and GPCR activation. PMID:26526852

  5. Synaptic depression and slow oscillatory activity in a biophysical network model of the cerebral cortex

    Directory of Open Access Journals (Sweden)

    José Manuel eBenita

    2012-08-01

    Full Text Available Short-term synaptic depression (STD is a form of synaptic plasticity that has a large impact on network computations. Experimental results suggest that STD is modulated by cortical activity, decreasing with activity in the network andincreasing during silent states. Here we explored different activity-modulation protocols in a biophysical network model for which the model displayed less STD when the network was active than when it was silent, in agreement with experimental results. Furthermore, trains of synaptic potentials had lesser decay during periods of activity (UP states than during silent periods (DOWN states, providing new experimental predictions. We next tackled the inverse question of what is the impact of modifying STD parameters on the emergent activity of the network, a question difficult to answer experimentally. We found that synaptic depression of cortical connections had a critical role to determine the regime of rhythmic cortical activity. While low STD resulted in an emergent rhythmic activity with short UP states and long DOWN states, increasing STD resulted in longer and more frequent UP states interleaved with short silent periods. A still higher synaptic depression set the network into a non-oscillatory firing regime where DOWN states no longer occurred. The speed of propagation of UP states along the network was not found to be modulated by STD during the oscillatory regime; it remained relatively stable over a range of values of STD. Overall, we found that the mutual interactions between synaptic depression and ongoing network activity are critical to determine the mechanisms that modulate cortical emergent patterns.

  6. Human embryonic stem cell-derived neuronal cells form spontaneously active neuronal networks in vitro.

    Science.gov (United States)

    Heikkilä, Teemu J; Ylä-Outinen, Laura; Tanskanen, Jarno M A; Lappalainen, Riikka S; Skottman, Heli; Suuronen, Riitta; Mikkonen, Jarno E; Hyttinen, Jari A K; Narkilahti, Susanna

    2009-07-01

    The production of functional human embryonic stem cell (hESC)-derived neuronal cells is critical for the application of hESCs in treating neurodegenerative disorders. To study the potential functionality of hESC-derived neurons, we cultured and monitored the development of hESC-derived neuronal networks on microelectrode arrays. Immunocytochemical studies revealed that these networks were positive for the neuronal marker proteins beta-tubulin(III) and microtubule-associated protein 2 (MAP-2). The hESC-derived neuronal networks were spontaneously active and exhibited a multitude of electrical impulse firing patterns. Synchronous bursts of electrical activity similar to those reported for hippocampal neurons and rodent embryonic stem cell-derived neuronal networks were recorded from the differentiated cultures until up to 4 months. The dependence of the observed neuronal network activity on sodium ion channels was examined using tetrodotoxin (TTX). Antagonists for the glutamate receptors NMDA [D(-)-2-amino-5-phosphonopentanoic acid] and AMPA/kainate [6-cyano-7-nitroquinoxaline-2,3-dione], and for GABAA receptors [(-)-bicuculline methiodide] modulated the spontaneous electrical activity, indicating that pharmacologically susceptible neuronal networks with functional synapses had been generated. The findings indicate that hESC-derived neuronal cells can generate spontaneously active networks with synchronous communication in vitro, and are therefore suitable for use in developmental and drug screening studies, as well as for regenerative medicine.

  7. Personalized Social Network Activity Feeds for Increased Interaction and Content Contribution

    Directory of Open Access Journals (Sweden)

    Shlomo eBerkovsky

    2015-10-01

    Full Text Available Online social networks were originally conceived as means of sharing information and activities with friends, and their success has been one of the primary contributors of the tremendous growth of the Web. Social network activity feeds were devised as a means to aggregate recent actions of friends into a convenient list. But the volume of actions and content generated by social network users is overwhelming, such that keeping users up-to-date with friend activities is an ongoing challenge for social network providers. Personalization has been proposed as a solution to combat social network information overload and help users to identify the nuggets of relevant information in the incoming flood of network activities. In this paper, we propose and thoroughly evaluate a personalized model for predicting the relevance of the activity feed items, which informs the ranking of the feeds and facilitates personalization. Results of a live study show that the proposed feed personalization approach successfully identifies and promotes relevant feed items and boosts the uptake of the feeds. In addition, it increases the contribution of user-generated content to the social network and spurs interaction between users.

  8. Real-time automatic interpolation of ambient gamma dose rates from the Dutch radioactivity monitoring network

    NARCIS (Netherlands)

    Hiemstra, P.H.; Pebesma, E.J.; Twenhöfel, C.J.W.; Heuvelink, G.B.M.

    2009-01-01

    Detection of radiological accidents and monitoring the spread of the contamination is of great importance. Following the Chernobyl accident many European countries have installed monitoring networks to perform this task. Real-time availability of automatically interpolated maps showing the spread of

  9. A relative rate utility based distributed power allocation algorithm for Cognitive Radio Networks

    DEFF Research Database (Denmark)

    Mahmood, Nurul Huda; Øien, G.E.; Lundheim, L.

    2012-01-01

    In an underlay Cognitive Radio Network, multiple secondary users coexist geographically and spectrally with multiple primary users under a constraint on the maximum received interference power at the primary receivers. Given such a setting, one may ask "how to achieve maximum utility benefit...

  10. Clusters of reaction rates and concentrations in protein networks such as phosphotransferase system

    NARCIS (Netherlands)

    Hardin, H.M.; Zagaris, A.; Willms, A.R.; Westerhoff, H.V.

    2014-01-01

    To understand the functioning of living cells, it is often helpful or even necessary to exploit inherent timescale disparities and focus on long-term dynamic behaviour. In the present study, we explore this type of behaviour for the biochemical network of the phosphotransferase system. We show that,

  11. Clusters of reaction rates and concentrations in protein networks such as the phosphotransferase system

    NARCIS (Netherlands)

    Härdin, Hanna M.; Zagaris, Antonios; Willms, Allan R.; Westerhoff, Hans V.

    To understand the functioning of living cells, it is often helpful or even necessary to exploit inherent timescale disparities and focus on long-term dynamic behaviour. In the present study, we explore this type of behaviour for the biochemical network of the phosphotransferase system. We show that,

  12. Hierarchy of individual calibration levels for heart rate and accelerometry to measure physical activity

    DEFF Research Database (Denmark)

    Brage, Søren; Ekelund, Ulf; Brage, Niels

    2007-01-01

    Combining accelerometry with heart rate (HR) monitoring may improve precision of physical activity measurement. Considerable variation exists in the relationships between physical activity intensity (PAI) and HR and accelerometry, which may be reduced by individual calibration. However, individual...

  13. Temporal Sequence of Hemispheric Network Activation during Semantic Processing: A Functional Network Connectivity Analysis

    Science.gov (United States)

    Assaf, Michal; Jagannathan, Kanchana; Calhoun, Vince; Kraut, Michael; Hart, John, Jr.; Pearlson, Godfrey

    2009-01-01

    To explore the temporal sequence of, and the relationship between, the left and right hemispheres (LH and RH) during semantic memory (SM) processing we identified the neural networks involved in the performance of functional MRI semantic object retrieval task (SORT) using group independent component analysis (ICA) in 47 healthy individuals. SORT…

  14. ePAL roadmap for active ageing: a collaborative networks approach to extending professional life

    NARCIS (Netherlands)

    Camarinha-Matos, L.M.; Afsarmanesh, H.; del Cura, A.; Playfoot, J.

    2010-01-01

    Active ageing, through a balanced combination of leisure and social interaction with continued work involvement, is central to meeting older citizens expectations, and maintaining their mental and physical health. Application of the collaborative networks paradigm, and the new generation of

  15. Active Power Distribution Network Security Monitoring System Based on PDMiner Platform

    National Research Council Canada - National Science Library

    CHANG Cheng

    2017-01-01

    ...,using the data mining technology and distributed parallel computing method,establishing an active distribution network security monitoring system model based on PDMiner large data mining platform...

  16. Assembling the puzzle for promoting physical activity in Brazil: a social network analysis.

    Science.gov (United States)

    Brownson, Ross C; Parra, Diana C; Dauti, Marsela; Harris, Jenine K; Hallal, Pedro C; Hoehner, Christine; Malta, Deborah Carvalho; Reis, Rodrigo S; Ramos, Luiz Roberto; Ribeiro, Isabela C; Soares, Jesus; Pratt, Michael

    2010-07-01

    Physical inactivity is a significant public health problem in Brazil that may be addressed by partnerships and networks. In conjunction with Project GUIA (Guide for Useful Interventions for Physical Activity in Brazil and Latin America), the aim of this study was to conduct a social network analysis of physical activity in Brazil. An online survey was completed by 28 of 35 organizations contacted from December 2008 through March 2009. Network analytic methods examined measures of collaboration, importance, leadership, and attributes of the respondent and organization. Leadership nominations for organizations studied ranged from 0 to 23. Positive predictors of collaboration included: south region, GUIA membership, years working in physical activity, and research, education, and promotion/practice areas of physical activity. The most frequently reported barrier to collaboration was bureaucracy. Social network analysis identified factors that are likely to improve collaboration among organizations in Brazil.

  17. Prefrontal cortical network activity: Opposite effects of psychedelic hallucinogens and D1/D5 dopamine receptor activation.

    Science.gov (United States)

    Lambe, E K; Aghajanian, G K

    2007-03-30

    The fine-tuning of network activity provides a modulating influence on how information is processed and interpreted in the brain. Here, we use brain slices of rat prefrontal cortex to study how recurrent network activity is affected by neuromodulators known to alter normal cortical function. We previously determined that glutamate spillover and stimulation of extrasynaptic N-methyl-d-aspartic acid (NMDA) receptors are required to support hallucinogen-induced cortical network activity. Since microdialysis studies suggest that psychedelic hallucinogens and dopamine D1/D5 receptor agonists have opposite effects on extracellular glutamate in prefrontal cortex, we hypothesized that these two families of psychoactive drugs would have opposite effects on cortical network activity. We found that network activity can be enhanced by 2,5-dimethoxy-4-iodoamphetamine (DOI) (a psychedelic hallucinogen that is a partial agonist of 5-HT(2A/2C) receptors) and suppressed by the selective D1/D5 agonist SKF 38393. This suppression could be mimicked by direct activation of adenylyl cyclase with forskolin or by addition of a cAMP analog. These findings are consistent with previous work showing that activation of adenylyl cyclase can upregulate neuronal glutamate transporters, thereby decreasing synaptic spillover of glutamate. Consistent with this hypothesis, a low concentration of the glutamate transporter inhibitor threo-beta-benzoylaspartic acid (TBOA) restored electrically-evoked recurrent activity in the presence of a selective D1/D5 agonist, whereas recurrent activity in the presence of a low level of the GABA(A) antagonist bicuculline was not resistant to suppression by the D1/D5 agonist. The tempering of network UP states by D1/D5 receptor activation may have implications for the proposed use of D1/D5 agonists in the treatment of schizophrenia.

  18. The effect of hyperbaric air on the electric activity of neuronal in vitro networks.

    Science.gov (United States)

    Stubbe, Marco; Nissen, Matthias; Schroeder, Jessica; Gimsa, Jan

    2015-11-15

    Breathing hyperbaric air or gas mixtures, for example during diving or when working underwater is known to alter the electrophysiological behavior of neuronal cells, which may lead to restricted cognition. During the last few decades, only very few studies into hyperbaric effects have been published, especially for the most relevant pressure range of up to 10 bar. We designed a pressurized measuring chamber to record pressure effects on the electrical activity of neuronal networks formed by primary cells of the frontal cortex of NMRI mice. Electrical activity was recorded with multi-electrode arrays (MEAs) of glass neuro chips while subjected to a step-by-step pressure increase from atmospheric pressure (1 bar) to 2 and 4 bar, followed by a decompression to 1 bar, in order to record recovery effects. The effects of pressure on the total spike rates (TSRs), which were averaged from at least 45 chips, were detected in two cell culture media with different compositions. In a DMEM medium with 6% horse serum, the TSR was increased by 19% after a pressure increase to 2 bar and remained stable at 4 bar. In NMEM medium with 2% B27, the TSR was not altered by a pressure increase to 2 bar but increased by 9% at 4 bar. After decompression to 1 bar, the activities decreased to 76% and 101% of their respective control levels in the two media. MEA recordings from neuronal networks in miniaturized hyperbaric measuring chambers provide new access for exploring the neuronal effects of hyperbaric breathing gases. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

  19. A Wireless Seismoacoustic Sensor Network for Monitoring Activity at Volcano Reventador, Ecuador

    Science.gov (United States)

    Welsh, M.; Werner-Allen, G.; Lorincz, K.; Marcillo, O.; Ruiz, M.; Johnson, J.; Lees, J. M.

    2005-12-01

    We developed a wireless sensor network for monitoring seismoacoustic activity at Volcano Reventador, Ecuador. Wireless sensor networks are a new technology and our group is among the first to apply them to monitoring volcanoes. The small size, low power, and wireless communication capabilities can greatly simplify deployments of large sensor arrays. The network consisted of 16 wireless sensor nodes, each outfitted with an 8 MHz CPU (TI MSP430) and a 2.4 GHz IEEE 802.15.4 radio (Chipcon CC2420) with data rates up to 80 Kbps. Each node acquired acoustic and seismic data at 24-bit resolution, with a microphone and either a single-axis geophone or triaxial short-period seismometer. Each node is powered by two D-cell batteries with a lifetime of about 1 week, and measures 18 x 10 x 8 cm. Nodes were distributed radially from the vent over a 3 km aperture. Control and data messages are relayed via radio to a base station node, with inter-node distances of up to 420 m. The base station transmits data using a FreeWave radio modem, via a repeater, to a laptop located 4 km from the deployment site. Each node samples continuous sensor data and a simple event-detection algorithm is used to trigger data collection. When a sensor detects an event, it relays a short message to the base station via radio. If several nodes report an event within a short time interval, the last 60 seconds of data is downloaded from each node in turn. One of the sensor nodes is programmed to transmit continuous data; due to limited radio bandwidth, it is not possible to collect continuous data from all nodes in the array. A GPS receiver and time synchronization protocol is used to establish a global timebase across all sensor nodes.

  20. Traffic accident reconstruction and an approach for prediction of fault rates using artificial neural networks: A case study in Turkey.

    Science.gov (United States)

    Can Yilmaz, Ali; Aci, Cigdem; Aydin, Kadir

    2016-08-17

    Currently, in Turkey, fault rates in traffic accidents are determined according to the initiative of accident experts (no speed analyses of vehicles just considering accident type) and there are no specific quantitative instructions on fault rates related to procession of accidents which just represents the type of collision (side impact, head to head, rear end, etc.) in No. 2918 Turkish Highway Traffic Act (THTA 1983). The aim of this study is to introduce a scientific and systematic approach for determination of fault rates in most frequent property damage-only (PDO) traffic accidents in Turkey. In this study, data (police reports, skid marks, deformation, crush depth, etc.) collected from the most frequent and controversial accident types (4 sample vehicle-vehicle scenarios) that consist of PDO were inserted into a reconstruction software called vCrash. Sample real-world scenarios were simulated on the software to generate different vehicle deformations that also correspond to energy-equivalent speed data just before the crash. These values were used to train a multilayer feedforward artificial neural network (MFANN), function fitting neural network (FITNET, a specialized version of MFANN), and generalized regression neural network (GRNN) models within 10-fold cross-validation to predict fault rates without using software. The performance of the artificial neural network (ANN) prediction models was evaluated using mean square error (MSE) and multiple correlation coefficient (R). It was shown that the MFANN model performed better for predicting fault rates (i.e., lower MSE and higher R) than FITNET and GRNN models for accident scenarios 1, 2, and 3, whereas FITNET performed the best for scenario 4. The FITNET model showed the second best results for prediction for the first 3 scenarios. Because there is no training phase in GRNN, the GRNN model produced results much faster than MFANN and FITNET models. However, the GRNN model had the worst prediction results. The

  1. Spontaneous Neuronal Activity in Developing Neocortical Networks: From Single Cells to Large-Scale Interactions.

    Science.gov (United States)

    Luhmann, Heiko J; Sinning, Anne; Yang, Jenq-Wei; Reyes-Puerta, Vicente; Stüttgen, Maik C; Kirischuk, Sergei; Kilb, Werner

    2016-01-01

    Neuronal activity has been shown to be essential for the proper formation of neuronal circuits, affecting developmental processes like neurogenesis, migration, programmed cell death, cellular differentiation, formation of local and long-range axonal connections, synaptic plasticity or myelination. Accordingly, neocortical areas reveal distinct spontaneous and sensory-driven neuronal activity patterns already at early phases of development. At embryonic stages, when immature neurons start to develop voltage-dependent channels, spontaneous activity is highly synchronized within small neuronal networks and governed by electrical synaptic transmission. Subsequently, spontaneous activity patterns become more complex, involve larger networks and propagate over several neocortical areas. The developmental shift from local to large-scale network activity is accompanied by a gradual shift from electrical to chemical synaptic transmission with an initial excitatory action of chloride-gated channels activated by GABA, glycine and taurine. Transient neuronal populations in the subplate (SP) support temporary circuits that play an important role in tuning early neocortical activity and the formation of mature neuronal networks. Thus, early spontaneous activity patterns control the formation of developing networks in sensory cortices, and disturbances of these activity patterns may lead to long-lasting neuronal deficits.

  2. Differential activation of the default mode network in jet lagged individuals

    OpenAIRE

    Coutinho,Joana; Óscar F. Gonçalves; Maia, Liliana Filipa Costa; Vasconcelos, Cristiana Fernandes; Perrone-McGovern, Kristin; Simon-Dack, Stephanie; Hernandez, Kristina; Silva, Patrícia Oliveira; Mesquita, Ana Raquel; Sampaio, Adriana

    2015-01-01

    Long-term exposure to transmeridian flights has been shown to impact cognitive functioning. Nevertheless, the immediate effects of jet lag in the activation of specific brain networks have not been investigated. We analyzed the impact of short-term jet lag on the activation of the default mode network (DMN). A group of individuals who were on a transmeridian flight and a control group went through a functional magnetic resonance imaging acquisition. Statistical analysis was performed to test ...

  3. Multi-level Control Framework for Enhanced Flexibility of Active Distribution Network

    DEFF Research Database (Denmark)

    Nainar, Karthikeyan; Pokhrel, Basanta Raj; Pillai, Jayakrishnan Radhakrishna

    2017-01-01

    In this paper, the control objectives of future active distribution networks with high penetration of renewables and flexible loads are analyzed and reviewed. From a state of the art review, the important control objectives seen from the perspective of a distribution system operator are identified...... to be hosting capacity improvement, high reliable operation and cost effective network management. Based on this review and a state of the art review concerning future distribution network control methods, a multi-level control architecture is constructed for an active distribution network, which satisfies...... the selected control objectives and provides enhanced flexibility. The control architecture is supported by generation/load forecasting and distribution state estimation techniques to improve the controllability of the network. The multi-level control architecture consists of three levels of hierarchical...

  4. Investigating solvability and complexity of linear active networks by means of matroids

    DEFF Research Database (Denmark)

    Petersen, Bjørn

    1979-01-01

    The solvability and complexity problems of finear active network are approached from a purely combinatorial point of view, using the concepts of matroid theory. Since the method is purely combinatorial, we take into account the network topology alone. Under this assumption necessary and sufficient...... conditions are given for the unique solvablity of linear active networks. The complexity and the number of dc-eigenfrequencies are also given. The method enables.you to decide if degeneracies are due to the topology alone, or if they are caused by special relations among network parameter values....... If the network parameter values are taken into account, the complexity and number of dc-eigenfrequencies given by the method, are only upper and lower bounds, respectively. The above conditions are fairly easily checked, and the complexity and number of dc-elgenfrequencies are found, using polynomially bounded...

  5. Inferring tectonic activity using drainage network and RT model: an example from the western Himalayas, India

    Science.gov (United States)

    Sahoo, Ramendra; Jain, Vikrant

    2017-04-01

    Morphology of the landscape and derived features are regarded to be an important tool for inferring about tectonic activity in an area, since surface exposures of these subsurface processes may not be available or may get eroded away over time. This has led to an extensive research in application of the non-planar morphological attributes like river long profile and hypsometry for tectonic studies, whereas drainage network as a proxy for tectonic activity has not been explored greatly. Though, significant work has been done on drainage network pattern which started in a qualitative manner and over the years, has evolved to incorporate more quantitative aspects, like studying the evolution of a network under the influence of external and internal controls. Random Topology (RT) model is one of these concepts, which elucidates the connection between evolution of a drainage network pattern and the entropy of the drainage system and it states that in absence of any geological controls, a natural population of channel networks will be topologically random. We have used the entropy maximization principle to provide a theoretical structure for the RT model. Furthermore, analysis was carried out on the drainage network structures around Jwalamukhi thrust in the Kangra reentrant in western Himalayas, India, to investigate the tectonic activity in the region. Around one thousand networks were extracted from the foot-wall (fw) and hanging-wall (hw) region of the thrust sheet and later categorized based on their magnitudes. We have adopted the goodness of fit test for comparing the network patterns in fw and hw drainage with those derived using the RT model. The null hypothesis for the test was, the drainage networks in the fw are statistically more similar than those on the hw, to the network patterns derived using the RT model for any given magnitude. The test results are favorable to our null hypothesis for networks with smaller magnitudes (< 9), whereas for larger

  6. Analyzing heterogeneity in the effects of physical activity in children on social network structure and peer selection dynamics.

    Science.gov (United States)

    Henry, Teague; Gesell, Sabina B; Ip, Edward H

    2016-09-01

    Social networks influence children and adolescents' physical activity. The focus of this paper is to examine the differences in the effects of physical activity on friendship selection, with eye to the implications on physical activity interventions for young children. Network interventions to increase physical activity are warranted but have not been conducted. Prior to implementing a network intervention in the field, it is important to understand potential heterogeneities in the effects that activity level have on network structure. In this study, the associations between activity level and cross sectional network structure, and activity level and change in network structure are assessed. We studied a real-world friendship network among 81 children (average age 7.96 years) who lived in low SES neighborhoods, attended public schools, and attended one of two structured aftercare programs, of which one has existed and the other was new. We used the exponential random graph model (ERGMs) and its longitudinal extension to evaluate the association between activity level and various demographic factors in having, forming, and dissolving friendship. Due to heterogeneity between the friendship networks within the aftercare programs, separate analyses were conducted for each network. There was heterogeneity in the effect of physical activity on both cross sectional network structure and the formation and dissolution processes, both across time and between networks. Network analysis could be used to assess the unique structure and dynamics of a social network before an intervention is implemented, so as to optimize the effects of the network intervention for increasing childhood physical activity. Additionally, if peer selection processes are changing within a network, a static network intervention strategy for childhood physical activity could become inefficient as the network evolves.

  7. Friendship networks and physical activity and sedentary behavior among youth: a systematized review

    Science.gov (United States)

    2013-01-01

    Background Low levels of physical activity and increased participation in sedentary leisure-time activities are two important obesity-risk behaviors that impact the health of today’s youth. Friend’s health behaviors have been shown to influence individual health behaviors; however, current evidence on the specific role of friendship networks in relation to levels of physical activity and sedentary behavior is limited. The purpose of this review was to summarize evidence on friendship networks and both physical activity and sedentary behavior among children and adolescents. Method After a search of seven scientific databases and reference scans, a total of thirteen articles were eligible for inclusion. All assessed the association between friendship networks and physical activity, while three also assessed sedentary behavior. Results Overall, higher levels of physical activity among friends are associated with higher levels of physical activity of the individual. Longitudinal studies reveal that an individual’s level of physical activity changes to reflect his/her friends’ higher level of physical activity. Boys tend to be influenced by their friendship network to a greater extent than girls. There is mixed evidence surrounding a friend’s sedentary behavior and individual sedentary behavior. Conclusion Friends’ physical activity level appears to have a significant influence on individual’s physical activity level. Evidence surrounding sedentary behavior is limited and mixed. Results from this review could inform effective public health interventions that harness the influence of friends to increase physical activity levels among children and adolescents. PMID:24289113

  8. Friendship networks and physical activity and sedentary behavior among youth: a systematized review.

    Science.gov (United States)

    Sawka, Keri Jo; McCormack, Gavin R; Nettel-Aguirre, Alberto; Hawe, Penelope; Doyle-Baker, Patricia K

    2013-12-01

    Low levels of physical activity and increased participation in sedentary leisure-time activities are two important obesity-risk behaviors that impact the health of today's youth. Friend's health behaviors have been shown to influence individual health behaviors; however, current evidence on the specific role of friendship networks in relation to levels of physical activity and sedentary behavior is limited. The purpose of this review was to summarize evidence on friendship networks and both physical activity and sedentary behavior among children and adolescents. After a search of seven scientific databases and reference scans, a total of thirteen articles were eligible for inclusion. All assessed the association between friendship networks and physical activity, while three also assessed sedentary behavior. Overall, higher levels of physical activity among friends are associated with higher levels of physical activity of the individual. Longitudinal studies reveal that an individual's level of physical activity changes to reflect his/her friends' higher level of physical activity. Boys tend to be influenced by their friendship network to a greater extent than girls. There is mixed evidence surrounding a friend's sedentary behavior and individual sedentary behavior. Friends' physical activity level appears to have a significant influence on individual's physical activity level. Evidence surrounding sedentary behavior is limited and mixed. Results from this review could inform effective public health interventions that harness the influence of friends to increase physical activity levels among children and adolescents.

  9. Morphological Transformation and Force Generation of Active Cytoskeletal Networks.

    Directory of Open Access Journals (Sweden)

    Tamara Carla Bidone

    2017-01-01

    Full Text Available Cells assemble numerous types of actomyosin bundles that generate contractile forces for biological processes, such as cytokinesis and cell migration. One example of contractile bundles is a transverse arc that forms via actomyosin-driven condensation of actin filaments in the lamellipodia of migrating cells and exerts significant forces on the surrounding environments. Structural reorganization of a network into a bundle facilitated by actomyosin contractility is a physiologically relevant and biophysically interesting process. Nevertheless, it remains elusive how actin filaments are reoriented, buckled, and bundled as well as undergo tension buildup during the structural reorganization. In this study, using an agent-based computational model, we demonstrated how the interplay between the density of myosin motors and cross-linking proteins and the rigidity, initial orientation, and turnover of actin filaments regulates the morphological transformation of a cross-linked actomyosin network into a bundle and the buildup of tension occurring during the transformation.

  10. Impact of Demand Side Management in Active Distribution Networks

    DEFF Research Database (Denmark)

    Ponnaganti, Pavani; Bak-Jensen, Birgitte; Pillai, Jayakrishnan Radhakrishna

    2017-01-01

    Demand Side Management (DSM) is an efficient flexible program which helps distribution network operators to meet the future critical peak demand. It is executed in cases of not only technical issues like voltage sag or swell, transformer burdening, cable congestions, but also to increase the degree...... vehicle, electric heating etc. are present. Simulations are carried out in Danish low voltage grid for summer and winter cases....

  11. Mathematical analysis techniques for modeling the space network activities

    Science.gov (United States)

    Foster, Lisa M.

    1992-01-01

    The objective of the present work was to explore and identify mathematical analysis techniques, and in particular, the use of linear programming. This topic was then applied to the Tracking and Data Relay Satellite System (TDRSS) in order to understand the space network better. Finally, a small scale version of the system was modeled, variables were identified, data was gathered, and comparisons were made between actual and theoretical data.

  12. Wrestling model of the repertoire of activity propagation modes in quadruple neural networks.

    Science.gov (United States)

    Shteingart, Hanan; Raichman, Nadav; Baruchi, Itay; Ben-Jacob, Eshel

    2010-01-01

    The spontaneous activity of engineered quadruple cultured neural networks (of four-coupled sub-networks) exhibits a repertoire of different types of mutual synchronization events. Each event corresponds to a specific activity propagation mode (APM) defined by the order of activity propagation between the sub-networks. We statistically characterized the frequency of spontaneous appearance of the different types of APMs. The relative frequencies of the APMs were then examined for their power-law properties. We found that the frequencies of appearance of the leading (most frequent) APMs have close to constant algebraic ratio reminiscent of Zipf's scaling of words. We show that the observations are consistent with a simplified "wrestling" model. This model represents an extension of the "boxing arena" model which was previously proposed to describe the ratio between the two activity modes in two coupled sub-networks. The additional new element in the "wrestling" model presented here is that the firing within each network is modeled by a time interval generator with similar intra-network Lévy distribution. We modeled the different burst-initiation zones' interaction by competition between the stochastic generators with Gaussian inter-network variability. Estimation of the model parameters revealed similarity across different cultures while the inter-burst-interval of the cultures was similar across different APMs as numerical simulation of the model predicts.

  13. Hierarchical brain networks active in approach and avoidance goal pursuit

    Directory of Open Access Journals (Sweden)

    Jeffrey Martin Spielberg

    2013-06-01

    Full Text Available Effective approach/avoidance goal pursuit is critical for attaining long-term health and well-being. Research on the neural correlates of key goal pursuit processes (e.g., motivation has long been of interest, with lateralization in prefrontal cortex being a particularly fruitful target of investigation. However, this literature has often been limited by a lack of spatial specificity and has not delineated the precise aspects of approach/avoidance motivation involved. Additionally, the relationships among brain regions (i.e., network connectivity vital to goal pursuit remain largely unexplored. Specificity in location, process, and network relationship is vital for moving beyond gross characterizations of function and identifying the precise cortical mechanisms involved in motivation. The present paper integrates research using more spatially specific methodologies (e.g., functional magnetic resonance imaging with the rich psychological literature on approach/avoidance to propose an integrative network model that takes advantage of the strengths of each of these literatures.

  14. The relationship between body temperature, heart rate, breathing rate, and rate of oxygen consumption, in the tegu lizard (Tupinambis merianae) at various levels of activity.

    Science.gov (United States)

    Piercy, Joanna; Rogers, Kip; Reichert, Michelle; Andrade, Denis V; Abe, Augusto S; Tattersall, Glenn J; Milsom, William K

    2015-12-01

    The present study determined whether EEG and/or EMG recordings could be used to reliably define activity states in the Brazilian black and white tegu lizard (Tupinambis merianae) and then examined the interactive effects of temperature and activity states on strategies for matching O2 supply and demand. In a first series of experiments, the rate of oxygen consumption (VO2), breathing frequency (fR), heart rate (fH), and EEG and EMG (neck muscle) activity were measured in different sleep/wake states (sleeping, awake but quiet, alert, or moving). In general, metabolic and cardio-respiratory changes were better indictors of the transition from sleep to wake than were changes in the EEG and EMG. In a second series of experiments, the interactive effects of temperature (17, 27 and 37 °C) and activity states on fR, tidal volume (VT), the fraction of oxygen extracted from the lung per breath (FIO2-FEO2), fH, and the cardiac O2 pulse were quantified to determine the relative roles of each of these variables in accommodating changes in VO2. The increases in oxygen supply to meet temperature- and activity-induced increases in oxygen demand were produced almost exclusively by increases in fH and fR. Regression analysis showed that the effects of temperature and activity state on the relationships between fH, fR and VO2 was to extend a common relationship along a single curve, rather than separate relationships for each metabolic state. For these lizards, the predictive powers of fR and fH were maximized when the effects of changes in temperature, digestive state and activity were pooled. However, the best r(2) values obtained were 0.63 and 0.74 using fR and fH as predictors of metabolic rate, respectively.

  15. Diversity of reproduction rate supports cooperation in the prisoner's dilemma game on complex networks

    CERN Document Server

    Szolnoki, A; Szabó, G

    2008-01-01

    In human societies the probability of strategy adoption from a given person may be affected by the personal features. Now we investigate how an artificially imposed restricted ability to reproduce, overruling ones fitness, affects an evolutionary process. For this purpose we employ the evolutionary prisoner's dilemma game on different complex graphs. Reproduction restrictions can have a facilitative effect on the evolution of cooperation that sets in irrespective of particularities of the interaction network. Indeed, an appropriate fraction of less fertile individuals may lead to full supremacy of cooperators where otherwise defection would be widespread. By studying cooperation levels within the group of individuals having full reproduction capabilities, we reveal that the recent mechanism for the promotion of cooperation is conceptually similar to the one reported previously for scale-free networks. Our results suggest that the diversity in the reproduction capability, related to inherently different attitu...

  16. ANALISIS TRANSFER RATE PENAMBAHAN NODE PADA INFRASTRUKTUR MOBILE ADHOC NETWORK (MANET UNTUK FILE SERVER

    Directory of Open Access Journals (Sweden)

    Rudi Kurniawan

    2017-05-01

    Full Text Available Teknologi Wireless Network sudah lama ditemukan dan seiring waktu juga mengalami perkembangan, Namun sifat teknologi ini menggantungkan diri pada infrastruktur jaringan yang ada. Hal ini bias menjadi kelemahan tersendiri saat kondisi infrastruktur jaringan sedang mengalami gangguan, karena setiap komunikasi yang melewati infrastruktur jaringan tersebut tidak akan sampai pada tujuan. Teknologi jaringan Mobile Ad-hoc Network (MANET diciptakan sebagai antisipasi jika infrastruktur jaringan sedang mengalami gangguan. Dengan jaringan MANET sistem komunikasi yang dilakukan tidak membutuhkan infrastruktur jaringan karena tiap node pada jaringan tersebut bersifat mobile. Untuk menguji kemampuan MANET, pada penelitian ini akan menerapkan File Transfer Protocol (FTP sebagai media untuk melakukan komunikasi data file transfer yang diimplementasi pada jaringan MANET. Dari pengujian yang telah dilakukan diperoleh hasil bahwa File Transfer dapat berfungsi dengan baik saat diterapkan pada jaringan MANET.

  17. Father Absence, Social Networks, and Maternal Ratings of Child Health: Evidence from the 2013 Social Networks and Health Information Survey in Mexico.

    Science.gov (United States)

    Edelblute, Heather B; Altman, Claire E

    2018-01-19

    Objectives To bridge the literature on the effect of father absence, international migration, and social networks on child health, we assess the association between father absence and maternal ratings of child poor health (MCPH). Next we test whether social networks of immediate and extended kin mediate the relationship between fathers' absence and MCPH. Methods Nested logistic regression models predicting MCPH are estimated using the 2013 Social Networks and Health Information Survey, collected in a migrant-sending community in Guanajuato, Mexico. These unique data distinguish among father absence due to migration versus other reasons and between immediate and extended kin ties. Results Descriptive results indicate that 25% of children with migrant fathers are assessed as having poor health, more often than children with present (15.5%) or otherwise absent fathers (17.5%). In the multivariate models, fathers' absence is not predictive of MCPH. However, the presence of extended kin ties for the mother was associated with approximately a 50% reduction in the odds of MCPH. Additionally, mother's poor self-assessed health was associated with increased odds of MCPH while the presence of a co-resident adult lowered the odds of MCPH. In sensitivity analysis among children with migrant fathers, the receipt of paternal remittances lowered the odds of MCPH. Conclusions for Practice Social networks have a direct and positive association with MCPH rather than mediating the father absence-MCPH relationship. The presence of extended kin ties in the local community is salient for more favorable child health and should be considered in public health interventions aimed at improving child health.

  18. Engagement, compliance and retention with a gamified online social networking physical activity intervention.

    Science.gov (United States)

    Ryan, Jillian; Edney, Sarah; Maher, Carol

    2017-12-01

    Health behaviour interventions delivered via online social networks are an increasingly popular approach to addressing lifestyle-related health problems. However, research to date consistently reports poor user engagement and retention. The current study examined user engagement, compliance and retention with Active Team-a gamified physical activity intervention delivered by via an online Facebook application. Associations between engagement and participant (n = 51) demographic and team characteristics (sex, age, education and team size) were examined, as well as temporal trends in engagement during the 50-day intervention. Analyses revealed significant associations between both engagement (p = gamification (p = 0.04) with education, with participants in the middle education category appearing to have the highest rates of engagement and use of gamification features. Gender was also related to engagement, with males demonstrating the highest use of the intervention's gamification features (p = 0.004). Although compliance was consistently high for the duration, engagement declined steadily throughout the intervention. Engagement peaked on Wednesdays, coinciding with the delivery of a customised email reminder. Findings reveal individual differences in engagement with Active Team, highlighting a need to tailor interventions to the target audience. Gamification features may enhance engagement amongst males, who are traditionally recognised as a difficult demographic group to engage. Finally, the use of customised, periodic push reminders delivered by email may enhance user engagement by drawing them back to the intervention and helping to sustain intervention behaviours.

  19. Sum rate maximization in the uplink of multi-cell OFDMA networks

    KAUST Repository

    Tabassum, Hina

    2012-10-03

    Resource allocation in orthogonal frequency division multiple access (OFDMA) networks plays an imperative role to guarantee the system performance. However, most of the known resource allocation schemes are focused on maximizing the local throughput of each cell, while ignoring the significant effect of inter-cell interference. This paper investigates the problem of resource allocation (i.e., subcarriers and powers) in the uplink of a multi-cell OFDMA network. The problem has a non-convex combinatorial structure and is known to be NP hard. Firstly, we investigate the upper and lower bounds to the average network throughput due to the inherent complexity of implementing the optimal solution. Later, a centralized sub-optimal resource allocation scheme is developed. We further develop less complex centralized and distributed schemes that are well-suited for practical scenarios. The computational complexity of all schemes has been analyzed and the performance is compared through numerical simulations. Simulation results demonstrate that the distributed scheme achieves comparable performance to the centralized resource allocation scheme in various scenarios. © 2011 IEEE.

  20. Calculating the Number of Cluster Heads Based on the Rate-Distortion Function in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Mingxin Yang

    2014-01-01

    Full Text Available Due to limited resources in wireless sensor nodes, energy efficiency is considered as one of the primary constraints in the design of the topology of wireless sensor networks (WSNs. Since data that are collected by wireless sensor nodes exhibit the characteristics of temporal association, data fusion has also become a very important means of reducing network traffic as well as eliminating data redundancy as far as data transmission is concerned. Another reason for data fusion is that, in many applications, only some of the data that are collected can meet the requirements of the sink node. In this paper, we propose a method to calculate the number of cluster heads or data aggregators during data fusion based on the rate-distortion function. In our discussion, we will first establish an energy consumption model and then describe a method for calculating the number of cluster heads from the point of view of reducing energy consumption. We will also show through theoretical analysis and experimentation that the network topology design based on the rate-distortion function is indeed more energy-efficient.

  1. Middle School Student's Heart Rates during Different Curricular Activities in Physical Education

    Science.gov (United States)

    Gao, Zan; Hannon, James C.; Carson, Russell L.

    2009-01-01

    The purpose of this study was to determine if students' heart rate outcomes in physical education varied as a function of activity and grade. A total of 146 sixth to eighth graders participated in different activities (i.e., walking/jogging, line dancing, soccer, and catch ball). Their average heart rate (AHR) and percentage of time in and above…

  2. A web-based, social networking physical activity intervention for insufficiently active adults delivered via Facebook app : randomized controlled trial

    OpenAIRE

    Maher, Carol; Ferguson, Monika; Vandelanotte, Corneel; Plotnikoff, Ron; de Bourdeaudhuij, Ilse; Thomas, Samantha; Nelson-Field, Karen; Olds, Tim

    2015-01-01

    Background Online social networks offer considerable potential for delivery of socially influential health behavior change interventions. Objective To determine the efficacy, engagement, and feasibility of an online social networking physical activity intervention with pedometers delivered via Facebook app. Methods A total of 110 adults with a mean age of 35.6 years (SD 12.4) were recruited online in teams of 3 to 8 friends. Teams were randomly allocated to receive access to a 50-day online s...

  3. The added value of a European Union tuberculosis reference laboratory network--analysis of the national reference laboratory activities.

    Science.gov (United States)

    Drobniewski, F A; Nikolayevskyy, V; Hoffner, S; Pogoryelova, O; Manissero, D; Ozin, A J

    2008-03-18

    National reference laboratories (NRL) and other laboratories are the cornerstones of well-functioning tuberculosis programmes and surveillance activities. However, the scope and activity of NRL services for mycobacterial identification and drug susceptibility testing (DST) has not been examined in detail across the European Union (EU), nor has the added value of cooperation and networking at the European level been explored with regard to strengthening laboratory services. Therefore, the European Centre for Disease Prevention and Control (ECDC) has commissioned a survey to explore these issues and to identify areas of work that could bring added value by supporting networking activities of tuberculosis (TB) reference laboratories in the EU. Structured questionnaires were sent to TB reference laboratory experts in the EU and European Economic Area (EEA) countries, and in three additional countries selected on the basis of their networking activities with EU projects and other initiatives (Switzerland, Croatia and Israel). The compiled results describe the activities and structure of 32 NRLs (29 countries replied, a response rate of 91%). The analysis of the survey led to the following recommendations for strengthening TB laboratory services: (1) implementing of the published European standards for TB laboratory services with respect to infrastructure, national reference functions, biosafety, human resources, quality assurance, operational research (including evaluation of new medical diagnostics), accuracy and speed, appropriately trained staff; (2) ensuring that laboratories only perform activities for which they have demonstrated proficiency; (3) implement validated and standardised second-line drug susceptibility testing (DST), including drugs used to define extensively drug-resistant tuberculosis (XDR TB); (4) aiming to identify Mycobacterium tuberculosis complex (MTBC) and rifampicin (RIF) resistance in over 90% of cultures and cases from smear-positive sputum

  4. The association between physical activity, cardiorespiratory fitness and self-rated health

    DEFF Research Database (Denmark)

    Eriksen, Louise; Curtis, Tine; Grønbæk, Morten

    2013-01-01

    OBJECTIVE: To investigate the joint association between self-reported physical activity as well as cardiorespiratory fitness and self-rated health among healthy women and men. METHOD: Data from 10,416 participants in The Danish Health Examination Survey 2007-2008 which took part in 13 Danish...... municipalities were analyzed. Leisure time physical activity level and self-rated health were based on self-reported questionnaire data. Optimal self-rated health was defined as "very good" or "good" self-rated health. Cardiorespiratory fitness (mL O2·min(-1)·kg(-1)) was estimated from maximal power output...... in a maximal cycle exercise test. RESULTS: A strong dose-response relation between cardiorespiratory fitness and self-rated health as well as between physical activity level and self-rated health among both women and men was found. Within categories of physical activity, odds ratios for optimal self...

  5. 77 FR 38397 - Agency Information Collection (Interest Rate Reduction Refinancing Loan Worksheet) Activities...

    Science.gov (United States)

    2012-06-27

    ... AFFAIRS Agency Information Collection (Interest Rate Reduction Refinancing Loan Worksheet) Activities....'' SUPPLEMENTARY INFORMATION: Title: Interest Rate Reduction Refinancing Loan Worksheet, VA Form 26-8923. OMB... are required to submit VA Form 26-8923, to request a guaranty on all interest rate reduction...

  6. Heart Rates of High School Physical Education Students during Team Sports, Individual Sports, and Fitness Activities

    Science.gov (United States)

    Laurson, Kelly R.; Brown, Dale D.; Cullen, Robert W.; Dennis, Karen K.

    2008-01-01

    This study examined how activity type influenced heart rates and time spent in target heart rate zones of high school students participating in physical education classes. Significantly higher average heart rates existed for fitness (142 plus or minus 24 beats per minute [bpm]) compared to team (118 plus or minus 24 bpm) or individual (114 plus or…

  7. Active Power Distribution Network Security Monitoring System Based on PDMiner Platform

    Directory of Open Access Journals (Sweden)

    CHANG Cheng

    2017-04-01

    Full Text Available Active distribution network system has the characteristics of complex structure,high DG permeability,large load fluctuation,strict control requirements. The data information of operation has the characteristics of high volume,high speed,diversity and value. For active distribution network data processing, according to the theory of cloud calculation,using the data mining technology and distributed parallel computing method,establishing an active distribution network security monitoring system model based on PDMiner large data mining platform. The processing of historical data and real time fault data are studied respectively. Research results show that the system by processing of historical data for risk zoning,development planning,operation state evaluation,by processing of fault data for fault analysis and processing,providing the basis for the distribution network security. The result of the system is verified by the simulation example.

  8. An energy-efficient rate adaptive media access protocol (RA-MAC) for long-lived sensor networks.

    Science.gov (United States)

    Hu, Wen; Chen, Quanjun; Corke, Peter; O'Rourke, Damien

    2010-01-01

    We introduce an energy-efficient Rate Adaptive Media Access Control (RA-MAC) algorithm for long-lived Wireless Sensor Networks (WSNs). Previous research shows that the dynamic and lossy nature of wireless communications is one of the major challenges to reliable data delivery in WSNs. RA-MAC achieves high link reliability in such situations by dynamically trading off data rate for channel gain. The extra gain that can be achieved reduces the packet loss rate which contributes to reduced energy expenditure through a reduced numbers of retransmissions. We achieve this at the expense of raw bit rate which generally far exceeds the application's link requirement. To minimize communication energy consumption, RA-MAC selects the optimal data rate based on the estimated link quality at each data rate and an analytical model of the energy consumption. Our model shows how the selected data rate depends on different channel conditions in order to minimize energy consumption. We have implemented RA-MAC in TinyOS for an off-the-shelf sensor platform (the TinyNode) on top of a state-of-the-art WSN Media Access Control Protocol, SCP-MAC, and evaluated its performance by comparing our implementation with the original SCP-MAC using both simulation and experiment.

  9. Increased default mode network activity in socially anxious individuals during reward processing.

    Science.gov (United States)

    Maresh, Erin L; Allen, Joseph P; Coan, James A

    2014-01-01

    Social anxiety has been associated with potentiated negative affect and, more recently, with diminished positive affect. It is unclear how these alterations in negative and positive affect are represented neurally in socially anxious individuals and, further, whether they generalize to non-social stimuli. To explore this, we used a monetary incentive paradigm to explore the association between social anxiety and both the anticipation and consumption of non-social incentives. Eighty-four individuals from a longitudinal community sample underwent functional magnetic resonance imaging (fMRI) while participating in a monetary incentive delay (MID) task. The MID task consisted of alternating cues indicating the potential to win or prevent losing varying amounts of money based on the speed of the participant's response. We examined whether self-reported levels of social anxiety, averaged across approximately 7 years of data, moderated brain activity when contrasting gain or loss cues with neutral cues during the anticipation and outcome phases of incentive processing. Whole brain analyses and analyses restricted to the ventral striatum for the anticipation phase and the medial prefrontal cortex for the outcome phase were conducted. Social anxiety did not associate with differences in hit rates or reaction times when responding to cues. Further, socially anxious individuals did not exhibit decreased ventral striatum activity during anticipation of gains or decreased MPFC activity during the outcome of gain trials, contrary to expectations based on literature indicating blunted positive affect in social anxiety. Instead, social anxiety showed positive associations with extensive regions implicated in default mode network activity (for example, precuneus, posterior cingulate cortex, and parietal lobe) during anticipation and receipt of monetary gain. Social anxiety was further linked with decreased activity in the ventral striatum during anticipation of monetary loss

  10. Transferring knowledge of activity recognition across sensor networks

    NARCIS (Netherlands)

    van Kasteren, T.L.M.; Englebienne, G.; Kröse, B.J.A.

    2010-01-01

    A problem in performing activity recognition on a large scale (i.e. in many homes) is that a labelled data set needs to be recorded for each house activity recognition is performed in. This is because most models for activity recognition require labelled data to learn their parameters. In this paper

  11. Special Feature: Liquids and Structural Glasses Special Feature: An active biopolymer network controlled by molecular motors

    Science.gov (United States)

    Koenderink, Gijsje H.; Dogic, Zvonimir; Nakamura, Fumihiko; Bendix, Poul M.; MacKintosh, Frederick C.; Hartwig, John H.; Stossel, Thomas P.; Weitz, David A.

    2009-09-01

    We describe an active polymer network in which processive molecular motors control network elasticity. This system consists of actin filaments cross-linked by filamin A (FLNa) and contracted by bipolar filaments of muscle myosin II. The myosin motors stiffen the network by more than two orders of magnitude by pulling on actin filaments anchored in the network by FLNa cross-links, thereby generating internal stress. The stiffening response closely mimics the effects of external stress applied by mechanical shear. Both internal and external stresses can drive the network into a highly nonlinear, stiffened regime. The active stress reaches values that are equivalent to an external stress of 14 Pa, consistent with a 1-pN force per myosin head. This active network mimics many mechanical properties of cells and suggests that adherent cells exert mechanical control by operating in a nonlinear regime where cell stiffness is sensitive to changes in motor activity. This design principle may be applicable to engineering novel biologically inspired, active materials that adjust their own stiffness by internal catalytic control.

  12. Bi-directional astrocytic regulation of neuronal activity within a network

    Science.gov (United States)

    Gordleeva, S. Yu; Stasenko, S. V.; Semyanov, A. V.; Dityatev, A. E.; Kazantsev, V. B.

    2012-01-01

    The concept of a tripartite synapse holds that astrocytes can affect both the pre- and post-synaptic compartments through the Ca2+-dependent release of gliotransmitters. Because astrocytic Ca2+ transients usually last for a few seconds, we assumed that astrocytic regulation of synaptic transmission may also occur on the scale of seconds. Here, we considered the basic physiological functions of tripartite synapses and investigated astrocytic regulation at the level of neural network activity. The firing dynamics of individual neurons in a spontaneous firing network was described by the Hodgkin–Huxley model. The neurons received excitatory synaptic input driven by the Poisson spike train with variable frequency. The mean field concentration of the released neurotransmitter was used to describe the presynaptic dynamics. The amplitudes of the excitatory postsynaptic currents (PSCs) obeyed the gamma distribution law. In our model, astrocytes depressed the presynaptic release and enhanced the PSCs. As a result, low frequency synaptic input was suppressed while high frequency input was amplified. The analysis of the neuron spiking frequency as an indicator of network activity revealed that tripartite synaptic transmission dramatically changed the local network operation compared to bipartite synapses. Specifically, the astrocytes supported homeostatic regulation of the network activity by increasing or decreasing firing of the neurons. Thus, the astrocyte activation may modulate a transition of neural network into bistable regime of activity with two stable firing levels and spontaneous transitions between them. PMID:23129997

  13. Analysing human mobility patterns of hiking activities through complex network theory.

    Science.gov (United States)

    Lera, Isaac; Pérez, Toni; Guerrero, Carlos; Eguíluz, Víctor M; Juiz, Carlos

    2017-01-01

    The exploitation of high volume of geolocalized data from social sport tracking applications of outdoor activities can be useful for natural resource planning and to understand the human mobility patterns during leisure activities. This geolocalized data represents the selection of hike activities according to subjective and objective factors such as personal goals, personal abilities, trail conditions or weather conditions. In our approach, human mobility patterns are analysed from trajectories which are generated by hikers. We propose the generation of the trail network identifying special points in the overlap of trajectories. Trail crossings and trailheads define our network and shape topological features. We analyse the trail network of Balearic Islands, as a case of study, using complex weighted network theory. The analysis is divided into the four seasons of the year to observe the impact of weather conditions on the network topology. The number of visited places does not decrease despite the large difference in the number of samples of the two seasons with larger and lower activity. It is in summer season where it is produced the most significant variation in the frequency and localization of activities from inland regions to coastal areas. Finally, we compare our model with other related studies where the network possesses a different purpose. One finding of our approach is the detection of regions with relevant importance where landscape interventions can be applied in function of the communities.

  14. Ratings of Sovereign Risk and the Macroeconomics Fundamentals of the countries: a Study Using Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Osvaldo Cândido da Silva Filho

    2009-05-01

    Full Text Available To minimize the consequences of asymmetric information, the sovereign risk ratings are instruments that constitute a key piece in the determination of credit market conditions, essential to the growth of developing countries like Brazil. In the present work we studied based on macroeconomics foundations, a classification to sovereign risk ratings realized by the ratings agencies finding the classification using Artificial Neural Networks. We observed homogeneity degree between the attributions of agencies and macroeconomics foundations in the countries of sample which four of foundations seem to be more directly connected with these attributions. After, in a comparative static exercise, we use the model to make simulations of scenarios of the credit external conditions for the Brazilian economy, changing the macroeconomics foundations which we noted that agencies expected for more per capita income increasing and decrease of public debt. (Full article in Portuguese only

  15. The distribution of physical activity in an after-school friendship network.

    Science.gov (United States)

    Gesell, Sabina B; Tesdahl, Eric; Ruchman, Eileen

    2012-06-01

    To examine whether a child's friendship network in an afterschool program influences his/her physical activity. Three waves of data were collected from school-aged children participating in aftercare (n = 81; mean [SD] age, 7.96 [1.74] years; 40% African American, 39% white, and 19% Latino) a name generator survey was used to map each child's social network, and accelerometers were used to measure physical activity. We applied stochastic actor-based modeling for social networks and behavior. Children did not form or dissolve friendships based on physical activity levels, but existing friendships heavily influenced children's level of physical activity. The strongest influence on the amount of time children spent in moderate-to-vigorous activity in the afterschool hours was the activity level of their immediate friends. Children consistently made adjustments to their activity levels of 10% or more to emulate the activity levels of their peers (odds ratio [OR] = 6.89, P < .01). Age (OR = 0.92, P < .10) and obesity status (OR = 0.66, P < .10) had marginally significant and relatively small direct effects on the activity. Gender had no direct effect on activity. These results suggest that friendship ties play a critical role in setting physical activity patterns in children as young as 5 to 12 years. Children's activity levels can be increased, decreased, or stabilized depending on the activity level of their immediate social network during a 12-week afterschool program. Network-based interventions hold the potential to produce clinically significant changes to children's physical activity.

  16. Throughput Maximization for Cognitive Radio Networks Using Active Cooperation and Superposition Coding

    KAUST Repository

    Hamza, Doha R.

    2015-02-13

    We propose a three-message superposition coding scheme in a cognitive radio relay network exploiting active cooperation between primary and secondary users. The primary user is motivated to cooperate by substantial benefits it can reap from this access scenario. Specifically, the time resource is split into three transmission phases: The first two phases are dedicated to primary communication, while the third phase is for the secondary’s transmission. We formulate two throughput maximization problems for the secondary network subject to primary user rate constraints and per-node power constraints with respect to the time durations of primary transmission and the transmit power of the primary and the secondary users. The first throughput maximization problem assumes a partial power constraint such that the secondary power dedicated to primary cooperation, i.e. for the first two communication phases, is fixed apriori. In the second throughput maximization problem, a total power constraint is assumed over the three phases of communication. The two problems are difficult to solve analytically when the relaying channel gains are strictly greater than each other and strictly greater than the direct link channel gain. However, mathematically tractable lowerbound and upperbound solutions can be attained for the two problems. For both problems, by only using the lowerbound solution, we demonstrate significant throughput gains for both the primary and the secondary users through this active cooperation scheme. We find that most of the throughput gains come from minimizing the second phase transmission time since the secondary nodes assist the primary communication during this phase. Finally, we demonstrate the superiority of our proposed scheme compared to a number of reference schemes that include best relay selection, dual-hop routing, and an interference channel model.

  17. The association between physical activity, cardiorespiratory fitness and self-rated health.

    Science.gov (United States)

    Eriksen, Louise; Curtis, Tine; Grønbæk, Morten; Helge, Jørn W; Tolstrup, Janne S

    2013-12-01

    To investigate the joint association between self-reported physical activity as well as cardiorespiratory fitness and self-rated health among healthy women and men. Data from 10,416 participants in The Danish Health Examination Survey 2007-2008 which took part in 13 Danish municipalities were analyzed. Leisure time physical activity level and self-rated health were based on self-reported questionnaire data. Optimal self-rated health was defined as "very good" or "good" self-rated health. Cardiorespiratory fitness (mL O2·min(-1)·kg(-1)) was estimated from maximal power output in a maximal cycle exercise test. A strong dose-response relation between cardiorespiratory fitness and self-rated health as well as between physical activity level and self-rated health among both women and men was found. Within categories of physical activity, odds ratios for optimal self-rated health increased with increasing categories of cardiorespiratory fitness, and vice versa. Hence, participants who were moderately/vigorously physically active and had a high cardiorespiratory fitness had the highest odds ratio for optimal self-rated health compared with sedentary participants with low cardiorespiratory fitness (odds ratio=12.2, 95% confidence interval: 9.3-16.1). Although reluctant to conclude on causality, this study suggests that an active lifestyle as well as good cardiorespiratory fitness probably increase self-rated health. © 2013.

  18. Fault Diagnosis Based on Chemical Sensor Data with an Active Deep Neural Network.

    Science.gov (United States)

    Jiang, Peng; Hu, Zhixin; Liu, Jun; Yu, Shanen; Wu, Feng

    2016-10-13

    Big sensor data provide significant potential for chemical fault diagnosis, which involves the baseline values of security, stability and reliability in chemical processes. A deep neural network (DNN) with novel active learning for inducing chemical fault diagnosis is presented in this study. It is a method using large amount of chemical sensor data, which is a combination of deep learning and active learning criterion to target the difficulty of consecutive fault diagnosis. DNN with deep architectures, instead of shallow ones, could be developed through deep learning to learn a suitable feature representation from raw sensor data in an unsupervised manner using stacked denoising auto-encoder (SDAE) and work through a layer-by-layer successive learning process. The features are added to the top Softmax regression layer to construct the discriminative fault characteristics for diagnosis in a supervised manner. Considering the expensive and time consuming labeling of sensor data in chemical applications, in contrast to the available methods, we employ a novel active learning criterion for the particularity of chemical processes, which is a combination of Best vs. Second Best criterion (BvSB) and a Lowest False Positive criterion (LFP), for further fine-tuning of diagnosis model in an active manner rather than passive manner. That is, we allow models to rank the most informative sensor data to be labeled for updating the DNN parameters during the interaction phase. The effectiveness of the proposed method is validated in two well-known industrial datasets. Results indicate that the proposed method can obtain superior diagnosis accuracy and provide significant performance improvement in accuracy and false positive rate with less labeled chemical sensor data by further active learning compared with existing methods.

  19. Fault Diagnosis Based on Chemical Sensor Data with an Active Deep Neural Network

    Science.gov (United States)

    Jiang, Peng; Hu, Zhixin; Liu, Jun; Yu, Shanen; Wu, Feng

    2016-01-01

    Big sensor data provide significant potential for chemical fault diagnosis, which involves the baseline values of security, stability and reliability in chemical processes. A deep neural network (DNN) with novel active learning for inducing chemical fault diagnosis is presented in this study. It is a method using large amount of chemical sensor data, which is a combination of deep learning and active learning criterion to target the difficulty of consecutive fault diagnosis. DNN with deep architectures, instead of shallow ones, could be developed through deep learning to learn a suitable feature representation from raw sensor data in an unsupervised manner using stacked denoising auto-encoder (SDAE) and work through a layer-by-layer successive learning process. The features are added to the top Softmax regression layer to construct the discriminative fault characteristics for diagnosis in a supervised manner. Considering the expensive and time consuming labeling of sensor data in chemical applications, in contrast to the available methods, we employ a novel active learning criterion for the particularity of chemical processes, which is a combination of Best vs. Second Best criterion (BvSB) and a Lowest False Positive criterion (LFP), for further fine-tuning of diagnosis model in an active manner rather than passive manner. That is, we allow models to rank the most informative sensor data to be labeled for updating the DNN parameters during the interaction phase. The effectiveness of the proposed method is validated in two well-known industrial datasets. Results indicate that the proposed method can obtain superior diagnosis accuracy and provide significant performance improvement in accuracy and false positive rate with less labeled chemical sensor data by further active learning compared with existing methods. PMID:27754386

  20. Social network activation: the role of health discussion partners in recovery from mental illness.

    Science.gov (United States)

    Perry, Brea L; Pescosolido, Bernice A

    2015-01-01

    In response to health problems, individuals may strategically activate their social network ties to help manage crisis and uncertainty. While it is well-established that social relationships provide a crucial safety net, little is known about who is chosen to help during an episode of illness. Guided by the Network Episode Model, two aspects of consulting others in the face of mental illness are considered. First, we ask who activates ties, and what kinds of ties and networks they attempt to leverage for discussing health matters. Second, we ask about the utility of activating health-focused network ties. Specifically, we examine the consequences of network activation at time of entry into treatment for individuals' quality of life, social satisfaction, ability to perform social roles, and mental health functioning nearly one year later. Using interview data from the longitudinal Indianapolis Network Mental Health Study (INMHS, N = 171), we focus on a sample of new patients with serious mental illness and a group with less severe disorders who are experiencing their first contact with the mental health treatment system. Three findings stand out. First, our results reveal the nature of agency in illness response. Whether under a rational choice or habitus logic, individuals appear to evaluate support needs, identifying the best possible matches among a larger group of potential health discussants. These include members of the core network and those with prior mental health experiences. Second, selective activation processes have implications for recovery. Those who secure adequate network resources report better outcomes than those who injudiciously activate network ties. Individuals who activate weaker relationships and those who are unsupportive of medical care experience poorer functioning, limited success in fulfilling social roles, and lower social satisfaction and quality of life later on. Third, the evidence suggests that social networks matter above and

  1. The ATLAS Women's Network: one year of activities

    CERN Multimedia

    Paula Eerola

    The idea for an ATLAS Women's Network was born during the ATLAS overview week in October 2005, when a few of us discussed our experiences and were pondering about what we could do. We felt that it was important to increase the visibility of women working in ATLAS in order to make a better and more effective use of the ATLAS human resources, that is, make sure that women are duly included at all levels. Furthermore, it is our belief that making ATLAS a better working environment for female collaborators and other female co-workers will benefit both us and the collaboration as a whole. On the individual level, all of us thought that we could benefit from peer support and experience sharing, and an ATLAS Women's Network could facilitate this by developing contacts between the ATLAS Women in ATLAS Institutes worldwide. Finally, we thought that it was important to increase the number of women studying physics and working in the field of physics research by identifying gender barriers in the career paths of women i...

  2. Nuclear power plant maintenance optimisation SENUF network activity

    Energy Technology Data Exchange (ETDEWEB)

    Ahlstrand, R.; Bieth, M.; Pla, P.; Rieg, C.; Trampus, P. [Inst. for Energy, EC DG Joint Research Centre, Petten (Netherlands)

    2004-07-01

    During providing scientific and technical support to TACIS and PHARE nuclear safety programs a large amount of knowledge related to Russian design reactor systems has accumulated and led to creation of a new Network concerning Nuclear Safety in Central and Eastern Europe called ''Safety of Eastern European type Nuclear Facilities'' (SENUF). SENUF contributes to bring together all stakeholders of TACIS and PHARE: beneficiaries, end users, Eastern und Western nuclear industries, and thus, to favour fruitful technical exchanges and feedback of experience. At present the main focus of SENUF is the nuclear power plant maintenance as substantial element of plant operational safety as well as life management. A Working Group has been established on plant maintenance. One of its major tasks in 2004 is to prepare a status report on advanced strategies to optimise maintenance. Optimisation projects have an interface with the plant's overall life management program. Today, almost all plants involved in SENUF network have an explicit policy to extend their service life, thus, component ageing management, modernization and refurbishment actions became much more important. A database is also under development, which intends to help sharing the available knowledge and specific equipment and tools. (orig.)

  3. Determining Methane Leak Locations and Rates with a Wireless Network Composed of Low-Cost, Printed Sensors

    Science.gov (United States)

    Smith, C. J.; Kim, B.; Zhang, Y.; Ng, T. N.; Beck, V.; Ganguli, A.; Saha, B.; Daniel, G.; Lee, J.; Whiting, G.; Meyyappan, M.; Schwartz, D. E.

    2015-12-01

    We will present our progress on the development of a wireless sensor network that will determine the source and rate of detected methane leaks. The targeted leak detection threshold is 2 g/min with a rate estimation error of 20% and localization error of 1 m within an outdoor area of 100 m2. The network itself is composed of low-cost, high-performance sensor nodes based on printed nanomaterials with expected sensitivity below 1 ppmv methane. High sensitivity to methane is achieved by modifying high surface-area-to-volume-ratio single-walled carbon nanotubes (SWNTs) with materials that adsorb methane molecules. Because the modified SWNTs are not perfectly selective to methane, the sensor nodes contain arrays of variously-modified SWNTs to build diversity of response towards gases with adsorption affinity. Methane selectivity is achieved through advanced pattern-matching algorithms of the array's ensemble response. The system is low power and designed to operate for a year on a single small battery. The SWNT sensing elements consume only microwatts. The largest power consumer is the wireless communication, which provides robust, real-time measurement data. Methane leak localization and rate estimation will be performed by machine-learning algorithms built with the aid of computational fluid dynamics simulations of gas plume formation. This sensor system can be broadly applied at gas wells, distribution systems, refineries, and other downstream facilities. It also can be utilized for industrial and residential safety applications, and adapted to other gases and gas combinations.

  4. Functional Activity and Connectivity Differences of Five Resting-State Networks in Patients with Alzheimer's Disease or Mild Cognitive Impairment.

    Science.gov (United States)

    Chen, Yu; Yan, Hao; Han, Zaizhu; Bi, Yanchao; Chen, Hongyan; Liu, Jia; Wu, Meiru; Wang, Yongjun; Zhang, Yumei

    2016-01-01

    We aimed to investigate the activity within and the connectivity between resting state networks (RSNs) in healthy subjects and patients with Alzheimer's disease (AD) or mild cognitive impairment (MCI). Magnetic resonance imaging (MRI) and resting-state MRI were performed on patients diagnosed with AD (n=18) or MCI (n=16) and on healthy subjects (n=18) with matching demographic characteristics (age, sex, and education level). Independent component analysis and Granger causality analysis (GCA) were used during image postprocessing. We calculated 'In + Out degree' for each RSN. Then, we investigated the relationships between "In + Out degree" of each brain network and the cognitive behavioural data. RSNs were obtained using the optimal matching method. The core areas of the five RSNs were similar between the AD, MCI, and healthy control groups, but the activity within these five RSNs was significantly lower in the AD and MCI groups than in the healthy control group (P<0.01, false discovery rate corrected). The GCA results showed that the connectivity between the five RSNs, particularly the connectivity from the default mode network (DMN) to the other RSNs, was slightly lower in MCI patients and was significantly lower in AD patients than in healthy subjects. In contrast, increased connectivity was evident between the memory network and the executive control network in the AD and MCI patients. The "In + Out degree" of the DMN negatively correlated with the Montreal Cognitive Assessment score in AD patients (R=-0.43, P<0.05). In conclusion, the activity within RSNs and the connectivity between RSNs differed between AD patients, MCI patients, and normal individuals; these results provide an imaging reference for the diagnosis of AD and the measurement of disease progression and reveal insight into the pathogenesis of AD.

  5. Active Coordinated Operation of Distribution Network System for Many Connections of Distributed Generators

    Science.gov (United States)

    Hayashi, Yasuhiro; Kawasaki, Shoji; Matsuki, Junya; Wakao, Shinji; Baba, Junpei; Hojo, Masahide; Yokoyama, Akihiko; Kobayashi, Naoki; Hirai, Takao; Oishi, Kohei

    Recently, total number of distributed generators (DGS) such as photovoltaic generation system and wind turbine generation system connected to an actual distribution network increases drastically. The distribution network connected with many distributed generators must be operated keeping reliability of power supply, power quality and loss minimization. In order to accomplish active distribution network operation to take advantage of many connections of DGS, a new coordinated operation of distribution system with many connections of DGS is necessary. In this paper, the authors propose a coordinated operation of distribution network system connected with many DGS by using newly proposed sectionalizing switches control, sending voltage control and computation of available DG connection capability. In order to check validity of the proposed coordinated operation of distribution system, numerical simulations using the proposed coordinated distribution system operation are carried out in a practical distribution network model.

  6. Frequency Count Attribute Oriented Induction of Corporate Network Data for Mapping Business Activity

    Science.gov (United States)

    Tanutama, Lukas

    2014-03-01

    Companies increasingly rely on Internet for effective and efficient business communication. As Information Technology infrastructure backbone for business activities, corporate network connects the company to Internet and enables its activities globally. It carries data packets generated by the activities of the users performing their business tasks. Traditionally, infrastructure operations mainly maintain data carrying capacity and network devices performance. It would be advantageous if a company knows what activities are running in its network. The research provides a simple method of mapping the business activity reflected by the network data. To map corporate users' activities, a slightly modified Attribute Oriented Induction (AOI) approach to mine the network data was applied. The frequency of each protocol invoked were counted to show what the user intended to do. The collected data was samples taken within a certain sampling period. Samples were taken due to the enormous data packets generated. Protocols of interest are only Internet related while intranet protocols are ignored. It can be concluded that the method could provide the management a general overview of the usage of its infrastructure and lead to efficient, effective and secure ICT infrastructure.

  7. Alterations in the heart rate and activity rhythms of three orbital astronauts on a space mission

    Science.gov (United States)

    Liu, Zhizhen; Wan, Yufeng; Zhang, Lin; Tian, Yu; Lv, Ke; Li, Yinghui; Wang, Chunhui; Chen, Xiaoping; Chen, Shanguang; Guo, Jinhu

    2015-01-01

    Environmental factors in space are dramatically different from those on Earth. The spaceflight environment has been known to influence human physiology and behavior on orbital missions. In this study, we investigated alterations in the diurnal rhythms of activity and heart rate of three Chinese astronauts on a space mission. An analysis of the heart rate data showed a significant decrease in heart rate amplitudes during flight in all three subjects. The heart rate amplitudes of all the three astronauts were significantly dampened during flight, and the minimum as well as the maximum value of heart rate increased after flight. A phase shift in heart rate was observed in one of the three astronauts after flight. These results demonstrate the influence of spaceflight on heart physiology and function. In addition, a significant decrease in body trunk activity and rhythmicity occurred during flight, demonstrating that the spaceflight environment disturbs motion adaptation and diurnal activity rhythms.

  8. 40 CFR 62.15275 - How do I monitor the injection rate of activated carbon?

    Science.gov (United States)

    2010-07-01

    ... activated carbon? 62.15275 Section 62.15275 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY... August 30, 1999 Other Monitoring Requirements § 62.15275 How do I monitor the injection rate of activated carbon? If your municipal waste combustion unit uses activated carbon to control dioxins/furans or...

  9. 40 CFR 60.1330 - How do I monitor the injection rate of activated carbon?

    Science.gov (United States)

    2010-07-01

    ... activated carbon? 60.1330 Section 60.1330 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY... Requirements § 60.1330 How do I monitor the injection rate of activated carbon? If your municipal waste combustion unit uses activated carbon to control dioxins/furans or mercury emissions, you must meet three...

  10. Heart rate and physical activity patterns in persons with profound intellectual and multiple disabilities

    NARCIS (Netherlands)

    Waninge, A.; Putten, A.A.J. van der; Stewart, R.E.; Steenbergen, B.; Wijck, R. van; Schans, C.P. van der

    2013-01-01

    Because physical fitness and health are related to physical activity, it is important to gain an insight into the physical activity levels of persons with profound intellectual and multiple disabilities (PIMD). The purpose of this study was to examine heart rate patterns to measure the activity

  11. Heart rate and physical activity patterns in persons with profound intellectual and multiple disabilities.

    NARCIS (Netherlands)

    Waninge, A.; Putten, A.A. van der; Stewart, R.E.; Steenbergen, B.; Wijck, R. van; Schans, C.P. van der

    2013-01-01

    Because physical fitness and health are related to physical activity, it is important to gain an insight into the physical activity levels of persons with profound intellectual and multiple disabilities (PIMD). The purpose of this study was to examine heart rate patterns to measure the activity

  12. HEART RATE AND PHYSICAL ACTIVITY PATTERNS IN PERSONS WITH PROFOUND INTELLECTUAL AND MULTIPLE DISABILITIES

    NARCIS (Netherlands)

    Waninge, Aly; van der Putten, Annette A. J.; Stewart, Roy E.; Steenbergen, Bert; van Wijck, Ruud; van der Schans, Cees P.

    2013-01-01

    Because physical fitness and health are related to physical activity, it is important to gain an insight into the physical activity levels of persons with profound intellectual and multiple disabilities (PIMD). The purpose of this study was to examine heart rate patterns to measure the activity

  13. Optimal JPWL Forward Error Correction Rate Allocation for Robust JPEG 2000 Images and Video Streaming over Mobile Ad Hoc Networks

    Directory of Open Access Journals (Sweden)

    Benoit Macq

    2008-07-01

    Full Text Available Based on the analysis of real mobile ad hoc network (MANET traces, we derive in this paper an optimal wireless JPEG 2000 compliant forward error correction (FEC rate allocation scheme for a robust streaming of images and videos over MANET. The packet-based proposed scheme has a low complexity and is compliant to JPWL, the 11th part of the JPEG 2000 standard. The effectiveness of the proposed method is evaluated using a wireless Motion JPEG 2000 client/server application; and the ability of the optimal scheme to guarantee quality of service (QoS to wireless clients is demonstrated.

  14. The association between social networks and self-rated risk of HIV infection among secondary school students in Moshi Municipality, Tanzania

    DEFF Research Database (Denmark)

    Lyimo, Elizabeth; Todd, Jim; Richey, Lisa Ann

    2013-01-01

    participants rated themselves at low risk of HIV infection despite practicing unsafe sex. Efforts to raise adolescents' self-awareness of risk of HIV infection through life skills education and HIV/acquired immunodeficiency syndrome risk reduction strategies may be beneficial to students in this at-risk group.......This study describes the social networks of secondary school students in Moshi Municipality, and their association with self-rated risk of human immunodeficiency virus (HIV) infection. A cross-sectional analytical study was conducted among 300 students aged 15–24 years in 5 secondary schools...... participation in bonding and bridging social networks and self-rated HIV risk behavior. More participants participated in bonding networks (72%) than in bridging networks (29%). Participation in bridging networks was greater among females (25%) than males (12%, p 

  15. Adaptive beamforming and rate control in real-time wireless sensor networks for QoS optimization

    Science.gov (United States)

    Hortos, William S.

    2011-06-01

    Quality-of-service (QoS) metrics for sensor types in a wireless sensor network (WSN) can be associated with metrics for multimedia that describe the quality of fused information, e.g., throughput, delay, jitter, packet error rate, information correlation, congestion, etc. These QoS metrics are typically set by the application layer of the protocol stack. Application-layer metrics, in turn, depend on the support from lower protocol layers: session, transport, network, data link (MAC), and physical. Protocol dependencies of QoS metrics motivate a cross-layer design approach to QoS optimization for heterogeneous sensor types in a WSN. Cross-layer interactions in the protocol are represented, in previous work by the author, by a set of concatenated parameters and resource levels. The "best" cross-layer designs that optimize QoS are established by applying the general theory of martingale representations to parameterized multivariate point processes (MVPPs) for discrete random events occurring in the WSN. Adaptive control of WSN behavior through cross-layer design is realized through parametric factorization of stochastic conditional rates of the MVPPs. Cross-layer parameters that optimize QoS are determined in solutions to stochastic dynamic programming conditions derived from models of transient flows of heterogeneous data. Adaptive transmit beamforming, simplified as sectored antennas, and rate control at sensor nodes are introduced to enhance the performance metrics of successful throughput, known as "goodput", congestion, capacity, etc. Adaptive antenna and rate controls are parametrized in realtime cross-layer models of WSN dynamics. Simulations demonstrate that adaptive antenna directionality and rate allocations improve overall QoS performance of a baseline design without such adaptation.

  16. Fitting the elementary rate constants of the P-gp transporter network in the hMDR1-MDCK confluent cell monolayer using a particle swarm algorithm.

    Directory of Open Access Journals (Sweden)

    Deep Agnani

    Full Text Available P-glycoprotein, a human multidrug resistance transporter, has been extensively studied due to its importance to human health and disease. In order to understand transport kinetics via P-gp, confluent cell monolayers overexpressing P-gp are widely used. The purpose of this study is to obtain the mass action elementary rate constants for P-gp's transport and to functionally characterize members of P-gp's network, i.e., other transporters that transport P-gp substrates in hMDR1-MDCKII confluent cell monolayers and are essential to the net substrate flux. Transport of a range of concentrations of amprenavir, loperamide, quinidine and digoxin across the confluent monolayer of cells was measured in both directions, apical to basolateral and basolateral to apical. We developed a global optimization algorithm using the Particle Swarm method that can simultaneously fit all datasets to yield accurate and exhaustive fits of these elementary rate constants. The statistical sensitivity of the fitted values was determined by using 24 identical replicate fits, yielding simple averages and standard deviations for all of the kinetic parameters, including the efflux active P-gp surface density. Digoxin required additional basolateral and apical transporters, while loperamide required just a basolateral tranporter. The data were better fit by assuming bidirectional transporters, rather than active importers, suggesting that they are not MRP or active OATP transporters. The P-gp efflux rate constants for quinidine and digoxin were about 3-fold smaller than reported ATP hydrolysis rate constants from P-gp proteoliposomes. This suggests a roughly 3∶1 stoichiometry between ATP hydrolysis and P-gp transport for these two drugs. The fitted values of the elementary rate constants for these P-gp substrates support the hypotheses that the selective pressures on P-gp are to maintain a broad substrate range and to keep xenobiotics out of the cytosol, but not out of the

  17. Selective Activation of Resting-State Networks following Focal Stimulation in a Connectome-Based Network Model of the Human Brain.

    Science.gov (United States)

    Spiegler, Andreas; Hansen, Enrique C A; Bernard, Christophe; McIntosh, Anthony R; Jirsa, Viktor K

    2016-01-01

    When the brain is stimulated, for example, by sensory inputs or goal-oriented tasks, the brain initially responds with activities in specific areas. The subsequent pattern formation of functional networks is constrained by the structural connectivity (SC) of the brain. The extent to which information is processed over short- or long-range SC is unclear. Whole-brain models based on long-range axonal connections, for example, can partly describe measured functional connectivity dynamics at rest. Here, we study the effect of SC on the network response to stimulation. We use a human whole-brain network model comprising long- and short-range connections. We systematically activate each cortical or thalamic area, and investigate the network response as a function of its short- and long-range SC. We show that when the brain is operating at the edge of criticality, stimulation causes a cascade of network recruitments, collapsing onto a smaller space that is partly constrained by SC. We found both short- and long-range SC essential to reproduce experimental results. In particular, the stimulation of specific areas results in the activation of one or more resting-state networks. We suggest that the stimulus-induced brain activity, which may indicate information and cognitive processing, follows specific routes imposed by structural networks explaining the emergence of functional networks. We provide a lookup table linking stimulation targets and functional network activations, which potentially can be useful in diagnostics and treatments with brain stimulation.

  18. Active Queue Management in TCP Networks Based on Fuzzy-Pid Controller

    Directory of Open Access Journals (Sweden)

    Hossein ASHTIANI

    2012-01-01

    Full Text Available We introduce a novel and robust active queue management (AQM scheme based on a fuzzy controller, called hybrid fuzzy-PID controller. In the TCP network, AQM is important to regulate the queue length by passing or dropping the packets at the intermediate routers. RED, PI, and PID algorithms have been used for AQM. But these algorithms show weaknesses in the detection and control of congestion under dynamically changing network situations. In this paper a novel Fuzzy-based proportional-integral derivative (PID controller, which acts as an active queue manager (AQM for Internet routers, is proposed. These controllers are used to reduce packet loss and improve network utilization in TCP/IP networks. A new hybrid controller is proposed and compared with traditional RED based controller. Simulations are carried out to demonstrate the effectiveness of the proposed method and show that, the new hybrid fuzzy PID controller provides better performance than random early detection (RED and PID controllers

  19. A review of active learning approaches to experimental design for uncovering biological networks.

    Directory of Open Access Journals (Sweden)

    Yuriy Sverchkov

    2017-06-01

    Full Text Available Various types of biological knowledge describe networks of interactions among elementary entities. For example, transcriptional regulatory networks consist of interactions among proteins and genes. Current knowledge about the exact structure of such networks is highly incomplete, and laboratory experiments that manipulate the entities involved are conducted to test hypotheses about these networks. In recent years, various automated approaches to experiment selection have been proposed. Many of these approaches can be characterized as active machine learning algorithms. Active learning is an iterative process in which a model is learned from data, hypotheses are generated from the model to propose informative experiments, and the experiments yield new data that is used to update the model. This review describes the various models, experiment selection strategies, validation techniques, and successful applications described in the literature; highlights common themes and notable distinctions among methods; and identifies likely directions of future research and open problems in the area.

  20. Active Vibration Control of the Smart Plate Using Artificial Neural Network Controller

    Directory of Open Access Journals (Sweden)

    Mohit

    2015-01-01

    Full Text Available The active vibration control (AVC of a rectangular plate with single input and single output approach is investigated using artificial neural network. The cantilever plate of finite length, breadth, and thickness having piezoelectric patches as sensors/actuators fixed at the upper and lower surface of the metal plate is considered for examination. The finite element model of the cantilever plate is utilized to formulate the whole strategy. The compact RIO and MATLAB simulation software are exercised to get the appropriate results. The cantilever plate is subjected to impulse input and uniform white noise disturbance. The neural network is trained offline and tuned with LQR controller. The various training algorithms to tune the neural network are exercised. The best efficient algorithm is finally considered to tune the neural network controller designed for active vibration control of the smart plate.

  1. Active-Varying Sampling-Based Fault Detection Filter Design for Networked Control Systems

    Directory of Open Access Journals (Sweden)

    Yu-Long Wang

    2014-01-01

    Full Text Available This paper is concerned with fault detection filter design for continuous-time networked control systems considering packet dropouts and network-induced delays. The active-varying sampling period method is introduced to establish a new discretized model for the considered networked control systems. The mutually exclusive distribution characteristic of packet dropouts and network-induced delays is made full use of to derive less conservative fault detection filter design criteria. Compared with the fault detection filter design adopting a constant sampling period, the proposed active-varying sampling-based fault detection filter design can improve the sensitivity of the residual signal to faults and shorten the needed time for fault detection. The simulation results illustrate the merits and effectiveness of the proposed fault detection filter design.

  2. Multi-objective optimal power flow for active distribution network considering the stochastic characteristic of photovoltaic

    Science.gov (United States)

    Zhou, Bao-Rong; Liu, Si-Liang; Zhang, Yong-Jun; Yi, Ying-Qi; Lin, Xiao-Ming

    2017-05-01

    To mitigate the impact on the distribution networks caused by the stochastic characteristic and high penetration of photovoltaic, a multi-objective optimal power flow model is proposed in this paper. The regulation capability of capacitor, inverter of photovoltaic and energy storage system embedded in active distribution network are considered to minimize the expected value of active power the T loss and probability of voltage violation in this model. Firstly, a probabilistic power flow based on cumulant method is introduced to calculate the value of the objectives. Secondly, NSGA-II algorithm is adopted for optimization to obtain the Pareto optimal solutions. Finally, the best compromise solution can be achieved through fuzzy membership degree method. By the multi-objective optimization calculation of IEEE34-node distribution network, the results show that the model can effectively improve the voltage security and economy of the distribution network on different levels of photovoltaic penetration.

  3. The Contribution of Extracurricular Activities to Adolescent Friendships: New Insights through Social Network Analysis

    Science.gov (United States)

    Schaefer, David R.; Simpkins, Sandra D.; Vest, Andrea E.; Price, Chara D.

    2011-01-01

    Extracurricular activities are settings that are theorized to help adolescents maintain existing friendships and develop new friendships. The overarching goal of the current investigation was to examine whether coparticipating in school-based extracurricular activities supported adolescents' school-based friendships. We used social network methods…

  4. HACMAC: A reliable human activity-based medium access control for implantable body sensor networks

    NARCIS (Netherlands)

    Karuppiah Ramachandran, Vignesh Raja; Havinga, Paul J.M.; Meratnia, Nirvana

    Chronic care is an eminent application of implantable body sensor networks (IBSN). Performing physical activities such as walking, running, and sitting is unavoidable during the long-term monitoring of chronic-care patients. These physical activities cripple the radio frequency (RF) signal between

  5. Activating the adoption of innovation : lessons from a passive house network

    NARCIS (Netherlands)

    Mlecnik, E.

    2016-01-01

    Purpose – The purpose of this paper is to explore innovation adoption theory and to define a model to investigate operational activities and communication in innovation networks that can stimulate both supply and demand. It also aims to exemplify this model with the activities of an innovation

  6. A Unified Approach for Calculating Error Rates of 10 Gbps WDM Network in Presence of Higher Order Dispersion

    Science.gov (United States)

    Kaur, Karamjit; Singh, Hardeep

    2017-12-01

    The lack of regeneration in all optical networks makes the data susceptible to network malfunctions, misconfigurations and signal impairments. As most of the effects are additive in nature, the signal quality is degraded by the time it reaches at the destination end making optical monitors installation a need of the day to maintain the service-level agreements for the end users. The physical layer impairments that need to be monitored are broadly classified as linear and nonlinear impairments. As the nonlinear impairments depends on the network state, it is difficult to preestimate them, while linear impairments can be easily determined from the type of fiber, wavelength/waveband, amplifier and environmental conditions. Among the linear impairments, dispersion, amplified spontaneous emission noise and attenuation are more dominating. In the present work, an effort is given to study the impact of dispersion on system quality, quantified through bit error rate (BER) and Q-value. Eye diagrams obtained at the receiver end are used for calculating system response. The curves obtained for BER and Q-value are further processed for curve fitting and suitable fifth-order polynomial equation is calculated representing the system response. Implementation of this equation in routing applications is discussed.

  7. Creative constraints: Brain activity and network dynamics underlying semantic interference during idea production.

    Science.gov (United States)

    Beaty, Roger E; Christensen, Alexander P; Benedek, Mathias; Silvia, Paul J; Schacter, Daniel L

    2017-03-01

    Functional neuroimaging research has recently revealed brain network interactions during performance on creative thinking tasks-particularly among regions of the default and executive control networks-but the cognitive mechanisms related to these interactions remain poorly understood. Here we test the hypothesis that the executive control network can interact with the default network to inhibit salient conceptual knowledge (i.e., pre-potent responses) elicited from memory during creative idea production. Participants studied common noun-verb pairs and were given a cued-recall test with corrective feedback to strengthen the paired association in memory. They then completed a verb generation task that presented either a previously studied noun (high-constraint) or an unstudied noun (low-constraint), and were asked to "think creatively" while searching for a novel verb to relate to the presented noun. Latent Semantic Analysis of verbal responses showed decreased semantic distance values in the high-constraint (i.e., interference) condition, which corresponded to increased neural activity within regions of the default (posterior cingulate cortex and bilateral angular gyri), salience (right anterior insula), and executive control (left dorsolateral prefrontal cortex) networks. Independent component analysis of intrinsic functional connectivity networks extended this finding by revealing differential interactions among these large-scale networks across the task conditions. The results suggest that interactions between the default and executive control networks underlie response inhibition during constrained idea production, providing insight into specific neurocognitive mechanisms supporting creative cognition. Copyright © 2017 Elsevier Inc. All rights reserved.

  8. Characterisation of anisotropic etching in KOH using network etch rate function model: influence of an applied potential in terms of microscopic properties

    NARCIS (Netherlands)

    Nguyen, Q.D.; Elwenspoek, Michael Curt

    2006-01-01

    Using the network etch rate function model, the anisotropic etch rate of p-type single crystal silicon was characterised in terms of microscopic properties including step velocity, step and terrace roughening. The anisotropic etch rate data needed have been obtained using a combination of 2 wagon

  9. Nitroxide polymer networks formed by Michael addition: on site-cured electrode-active organic coating.

    Science.gov (United States)

    Ibe, Takeshi; Frings, Rainer B; Lachowicz, Artur; Kyo, Soichi; Nishide, Hiroyuki

    2010-05-28

    Highly and homogeneously crosslinked poly(beta-ketoester) networks densely bearing robust nitroxide radicals were prepared via a click-type and stepwise Michael polyaddition. A half-battery cell composed of the thermally-cured radical network coatings displayed a rapid, reversible, and almost stoichiometric redox-activity even with a thickness of ca. 10 mum, which may be applicable as the electrode of organic-based rechargeable devices.

  10. Central European MetEor NeTwork: Current status and future activities

    Science.gov (United States)

    Srba, J.; Koukal, J.; Ferus, M.; Lenža, L.; Gorková, S.; Civiš, S.; Simon, J.; Csorgei, T.; Jedlièka, M.; Korec, M.; Kaniansky, S.; Polák, J.; Spurný, M.; Brázdil, T.; Mäsiar, J.; Zima, M.; Delinèák, P.; Popek, M.; Bahýl, V.; Piffl, R.; Èechmánek, M.

    2016-06-01

    The Central European video Meteor Network (CEMeNt) established in 2010 is a platform for cross-border cooperation in the field of video meteor observations between Czech Republic and Slovakia. During five years of operation the CEMeNt network went through an extensive development. In total, 37 video systems were working on 20 permanent stations located in Czech Republic and Slovakia during 2015. In this paper we summarize CEMeNt current status and introduce some future activities.

  11. Microgrids in Active Network Management-Part II:System Operation, Power Quality and Protection

    OpenAIRE

    Palizban, Omid; Kauhaniemi, Kimmo; Josep M. Guerrero

    2014-01-01

    The development of distribution networks for participation in active network management (ANM) and smart grids is introduced using the microgrid concept. In recent years, this issue has been researched and implemented by many experts. The second part of this paper describes those developed operational concepts of microgrids that have an impact on their participation in ANM and in the requirements for achieving targets. Power quality is the most challenging task in microgrids, especially when t...

  12. Robust Functionality and Active Data Management for Cooperative Networks in the Presence of WMD Stressors

    Science.gov (United States)

    2011-09-01

    Active Data ManagemE~nt for Cooperative Networks in the Presentee of WMD Stressors Approved for public release; distribution is unlimited. September...policies were obtaiMd by solving a constrained optimization problem whose cost function employs the rigorous model developed for the service reliability of...to policies that considered nodes’ roliability but disregarded the communication costs over the network. Moreover, the algorithm developed ill this

  13. FCJ-191 Mirroring the Videos of Anonymous: Cloud Activism, Living Networks, and Political Mimesis

    Directory of Open Access Journals (Sweden)

    Adam Fish

    2015-06-01

    Full Text Available Mirrors describe the multiplication of data across a network. In this article, I examine the politics of mirroring as practiced on videos by the hacktivist network Anonymous. Mirrors are designed to retain visibility on social media platforms and motivate viewers towards activism. They emerge from a particular social structure and propagate a specific symbolic system. Furthermore, mirrors are not exact replicas nor postmodern representations. Rather, mirroring maps a contestation over visibility that entangles both cloud activists and platform firms.

  14. What Motivates Young Adults to Talk About Physical Activity on Social Network Sites?

    Science.gov (United States)

    Zhang, Ni; Campo, Shelly; Yang, Jingzhen; Eckler, Petya; Snetselaar, Linda; Janz, Kathleen; Leary, Emily

    2017-06-22

    Electronic word-of-mouth on social network sites has been used successfully in marketing. In social marketing, electronic word-of-mouth about products as health behaviors has the potential to be more effective and reach more young adults than health education through traditional mass media. However, little is known about what motivates people to actively initiate electronic word-of-mouth about health behaviors on their personal pages or profiles on social network sites, thus potentially reaching all their contacts on those sites. This study filled the gap by applying a marketing theoretical model to explore the factors associated with electronic word-of-mouth on social network sites about leisure-time physical activity. A Web survey link was sent to undergraduate students at one of the Midwestern universities and 439 of them completed the survey. The average age of the 439 participants was 19 years (SD=1 year, range: 18-24). Results suggested that emotional engagement with leisure-time physical activity (ie, affective involvement in leisure-time physical activity) predicted providing relevant opinions or information on social network sites. Social network site users who perceived stronger ties with all their contacts were more likely to provide and seek leisure-time physical activity opinions and information. People who provided leisure-time physical activity opinions and information were more likely to seek opinions and information, and people who forwarded information about leisure-time physical activity were more likely to chat about it. This study shed light on the application of the electronic word-of-mouth theoretical framework in promoting health behaviors. The findings can also guide the development of future social marketing interventions using social network sites to promote leisure-time physical activity.

  15. Activity Patterns of Cultured Neural Networks on Micro Electrode Arrays

    National Research Council Canada - National Science Library

    Rutten, Wim

    2001-01-01

    A hybrid neuro-electronic interface is a cell-cultured micro electrode array, acting as a neural information transducer for stimulation and/or recording of neural activity in the brain or the spinal cord...

  16. Online social networks that connect users to physical activity partners: a review and descriptive analysis.

    Science.gov (United States)

    Nakhasi, Atul; Shen, Album Xiaotian; Passarella, Ralph Joseph; Appel, Lawrence J; Anderson, Cheryl Am

    2014-06-16

    The US Centers for Disease Control and Prevention have identified a lack of encouragement, support, or companionship from family and friends as a major barrier to physical activity. To overcome this barrier, online social networks are now actively leveraging principles of companion social support in novel ways. The aim was to evaluate the functionality, features, and usability of existing online social networks which seek to increase physical activity and fitness among users by connecting them to physical activity partners, not just online, but also face-to-face. In September 2012, we used 3 major databases to identify the website addresses for relevant online social networks. We conducted a Google search using 8 unique keyword combinations: the common keyword "find" coupled with 1 of 4 prefix terms "health," "fitness," "workout," or "physical" coupled with 1 of 2 stem terms "activity partners" or "activity buddies." We also searched 2 prominent technology start-up news sites, TechCrunch and Y Combinator, using 2 unique keyword combinations: the common keyword "find" coupled with 1 of 2 stem terms "activity partners" and "activity buddies." Sites were defined as online social health activity networks if they had the ability to (1) actively find physical activity partners or activities for the user, (2) offer dynamic, real-time tracking or sharing of social activities, and (3) provide virtual profiles to users. We excluded from our analysis sites that were not Web-based, publicly available, in English, or free. Of the 360 initial search results, we identified 13 websites that met our complete criteria of an online social health activity network. Features such as physical activity creation (13/13, 100%) and private messaging (12/13, 92%) appeared almost universally among these websites. However, integration with Web 2.0 technologies such as Facebook and Twitter (9/13, 69%) and the option of direct event joining (8/13, 62%) were not as universally present. Largely

  17. Drug target identification using network analysis: Taking active components in Sini decoction as an example

    Science.gov (United States)

    Chen, Si; Jiang, Hailong; Cao, Yan; Wang, Yun; Hu, Ziheng; Zhu, Zhenyu; Chai, Yifeng

    2016-04-01

    Identifying the molecular targets for the beneficial effects of active small-molecule compounds simultaneously is an important and currently unmet challenge. In this study, we firstly proposed network analysis by integrating data from network pharmacology and metabolomics to identify targets of active components in sini decoction (SND) simultaneously against heart failure. To begin with, 48 potential active components in SND against heart failure were predicted by serum pharmacochemistry, text mining and similarity match. Then, we employed network pharmacology including text mining and molecular docking to identify the potential targets of these components. The key enriched processes, pathways and related diseases of these target proteins were analyzed by STRING database. At last, network analysis was conducted to identify most possible targets of components in SND. Among the 25 targets predicted by network analysis, tumor necrosis factor α (TNF-α) was firstly experimentally validated in molecular and cellular level. Results indicated that hypaconitine, mesaconitine, higenamine and quercetin in SND can directly bind to TNF-α, reduce the TNF-α-mediated cytotoxicity on L929 cells and exert anti-myocardial cell apoptosis effects. We envisage that network analysis will also be useful in target identification of a bioactive compound.

  18. Barreloid Borders and Neuronal Activity Shape Panglial Gap Junction-Coupled Networks in the Mouse Thalamus.

    Science.gov (United States)

    Claus, Lena; Philippot, Camille; Griemsmann, Stephanie; Timmermann, Aline; Jabs, Ronald; Henneberger, Christian; Kettenmann, Helmut; Steinhäuser, Christian

    2018-01-01

    The ventral posterior nucleus of the thalamus plays an important role in somatosensory information processing. It contains elongated cellular domains called barreloids, which are the structural basis for the somatotopic organization of vibrissae representation. So far, the organization of glial networks in these barreloid structures and its modulation by neuronal activity has not been studied. We have developed a method to visualize thalamic barreloid fields in acute slices. Combining electrophysiology, immunohistochemistry, and electroporation in transgenic mice with cell type-specific fluorescence labeling, we provide the first structure-function analyses of barreloidal glial gap junction networks. We observed coupled networks, which comprised both astrocytes and oligodendrocytes. The spread of tracers or a fluorescent glucose derivative through these networks was dependent on neuronal activity and limited by the barreloid borders, which were formed by uncoupled or weakly coupled oligodendrocytes. Neuronal somata were distributed homogeneously across barreloid fields with their processes running in parallel to the barreloid borders. Many astrocytes and oligodendrocytes were not part of the panglial networks. Thus, oligodendrocytes are the cellular elements limiting the communicating panglial network to a single barreloid, which might be important to ensure proper metabolic support to active neurons located within a particular vibrissae signaling pathway. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  19. Measuring Ionospheric Irregularities Globally by the Rate of TEC Index and GNSS Networks

    Science.gov (United States)

    Pi, Xiaoqing

    2012-01-01

    Outline of presentation: Why do we use the rate of TEC index (ROTI) instead of the standard s4 and sigma-phi indices? What are the differences between S4, sigma-phi and ROTI? Examples of ROTI measurements and Development status and plan.

  20. Enhancing the Data Collection Rate of Tree-Based Aggregation in Wireless Sensor Networks

    NARCIS (Netherlands)

    Durmaz, O.; Krishnamachari, B.

    2008-01-01

    What is the fastest rate at which we can collect a stream of aggregated data from a set of wireless sensors organized as a tree? We explore a hierarchy of techniques using realistic simulation models to address this question. We begin by considering TDMA scheduling on a single channel, reducing the

  1. Achievable Rates of Cognitive Radio Networks Using Multi-Layer Coding with Limited CSI

    KAUST Repository

    Sboui, Lokman

    2016-03-01

    In a Cognitive Radio (CR) framework, the channel state information (CSI) feedback to the secondary transmitter (SU Tx) can be limited or unavailable. Thus, the statistical model is adopted in order to determine the system performance using the outage concept. In this paper, we adopt a new approach using multi-layer-coding (MLC) strategy, i.e., broadcast approach, to enhance spectrum sharing over fading channels. First, we consider a scenario where the secondary transmitter has no CSI of both the link between SU Tx and the primary receiver (cross-link) and its own link. We show that using MLC improves the cognitive rate compared to the rate provided by a singlelayer- coding (SLC). In addition, we observe numerically that 2-Layer coding achieves most of the gain for Rayleigh fading. Second, we analyze a scenario where SU Tx is provided by partial CSI about its link through quantized CSI. We compute its achievable rate adopting the MLC and highlight the improvement over SLC. Finally, we study the case in which the cross-link is perfect, i.e., a cooperative primary user setting, and compare the performance with the previous cases. We present asymptotic analysis at high power regime and show that the cooperation enhances considerably the cognitive rate at high values of the secondary power budget.

  2. Combined techniques for characterising pasta structure reveals how the gluten network slows enzymic digestion rate.

    Science.gov (United States)

    Zou, Wei; Sissons, Mike; Gidley, Michael J; Gilbert, Robert G; Warren, Frederick J

    2015-12-01

    The aim of the present study is to characterise the influence of gluten structure on the kinetics of starch hydrolysis in pasta. Spaghetti and powdered pasta were prepared from three different cultivars of durum semolina, and starch was also purified from each cultivar. Digestion kinetic parameters were obtained through logarithm-of-slope analysis, allowing identification of sequential digestion steps. Purified starch and semolina were digested following a single first-order rate constant, while pasta and powdered pasta followed two sequential first-order rate constants. Rate coefficients were altered by pepsin hydrolysis. Confocal microscopy revealed that, following cooking, starch granules were completely swollen for starch, semolina and pasta powder samples. In pasta, they were completely swollen in the external regions, partially swollen in the intermediate region and almost intact in the pasta strand centre. Gluten entrapment accounts for sequential kinetic steps in starch digestion of pasta; the compact microstructure of pasta also reduces digestion rates. Copyright © 2015 Elsevier Ltd. All rights reserved.

  3. Artificial neural networks can learn to estimate extinction rates from molecular phylogenies

    NARCIS (Netherlands)

    Bokma, Folmer

    2006-01-01

    Molecular phylogenies typically consist of only extant species, yet they allow inference of past rates of extinction, because. recently originated species are less likely to be extinct than ancient species. Despite the simple structure of the assumed underlying speciation-extinction process,

  4. Gender differences in the association of perceived social support and social network with self-rated health status among older adults: a population-based study in Brazil

    National Research Council Canada - National Science Library

    Caetano, Silvana C; Silva, Cosme M F P; Vettore, Mario V

    2013-01-01

    .... Hence, the present study tests the hypothesis that gender differences exist in the relationship between perceived social support, social network, and self-rated health (SRH) among older adults...

  5. Emergence of gamma motor activity in an artificial neural network model of the corticospinal system.

    Science.gov (United States)

    Grandjean, Bernard; Maier, Marc A

    2017-02-01

    Muscle spindle discharge during active movement is a function of mechanical and neural parameters. Muscle length changes (and their derivatives) represent its primary mechanical, fusimotor drive its neural component. However, neither the action nor the function of fusimotor and in particular of γ-drive, have been clearly established, since γ-motor activity during voluntary, non-locomotor movements remains largely unknown. Here, using a computational approach, we explored whether γ-drive emerges in an artificial neural network model of the corticospinal system linked to a biomechanical antagonist wrist simulator. The wrist simulator included length-sensitive and γ-drive-dependent type Ia and type II muscle spindle activity. Network activity and connectivity were derived by a gradient descent algorithm to generate reciprocal, known target α-motor unit activity during wrist flexion-extension (F/E) movements. Two tasks were simulated: an alternating F/E task and a slow F/E tracking task. Emergence of γ-motor activity in the alternating F/E network was a function of α-motor unit drive: if muscle afferent (together with supraspinal) input was required for driving α-motor units, then γ-drive emerged in the form of α-γ coactivation, as predicted by empirical studies. In the slow F/E tracking network, γ-drive emerged in the form of α-γ dissociation and provided critical, bidirectional muscle afferent activity to the cortical network, containing known bidirectional target units. The model thus demonstrates the complementary aspects of spindle output and hence γ-drive: i) muscle spindle activity as a driving force of α-motor unit activity, and ii) afferent activity providing continuous sensory information, both of which crucially depend on γ-drive.

  6. Step-rate thresholds for moderate and vigorous-intensity activity in persons with Down syndrome.

    Science.gov (United States)

    Agiovlasitis, Stamatis; Beets, Michael W; Motl, Robert W; Fernhall, Bo

    2012-09-01

    Monitoring physical activity intensity in persons with Down syndrome (DS) may be affected by an altered relationship between metabolic equivalent units (METs) and step-rate. This study examined whether the relationship between METs and step-rate is altered in persons with DS and developed step-rate thresholds for activity intensity for these persons. Cross-sectional. Eighteen persons with DS (25±7years; 8 women) and 22 persons without DS (26±5 years; 9 women) completed six over-ground walking trials each lasting 6 min at their preferred speed and at 0.5, 0.75, 1.0, 1.25, and 1.5 ms⁻¹. METs were measured with portable spirometry and step-rate with hand-tally. Random effects models were used to predict METs from step-rate, squared step-rate, height, presence of DS, sex, and body mass index (BMI). Step-rate, squared step-rate, height, and presence of DS contributed significantly to the model (SE=0.20 METs; R²=0.63); sex and BMI did not contribute. As height increased, step-rate thresholds for moderate and vigorous-intensity activity decreased. For a given height, participants with DS had lower step-rate at the moderate-intensity threshold than participants without DS. Across participant heights, the moderate-intensity cut-off ranged between 101 and 76 steps min⁻¹ in persons with DS and between 103 and 80 steps min⁻¹ in persons without DS. For persons with DS, step-rate at the vigorous-intensity threshold ranged between 136 and 126 steps min⁻¹. Persons with DS showed altered relationship between METs and step-rate and had lower step-rate thresholds for moderate-intensity activity than persons without DS. Copyright © 2012 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

  7. Associations between Aspects of Friendship Networks, Physical Activity, and Sedentary Behaviour among Adolescents

    Directory of Open Access Journals (Sweden)

    Keri Jo Sawka

    2014-01-01

    Full Text Available Background. Adolescent friendships have been linked to physical activity levels; however, network characteristics have not been broadly examined. Method. In a cross-sectional analysis of 1061 adolescents (11–15 years, achieving 60 minutes/day of moderate-to-vigorous physical activity (MVPA and participating in over 2 hours/day of sedentary behaviour were determined based on friendship network characteristics (density; proportion of active/sedentary friends; betweenness centrality; popularity; clique membership and perceived social support. Results. Adolescents with no friendship nominations participated in less MVPA. For boys and girls, a ten percent point increase in active friends was positively associated with achievement of 60 minutes/day of MVPA (OR 1.11; 95% CI 1.02–1.21, OR 1.14; 95% CI 1.02–1.27, resp.. For boys, higher social support from friends was negatively associated with achieving 60 minutes/day of MVPA (OR 0.63; 95% CI 0.42–0.96. Compared with low density networks, boys in higher density networks were more likely to participate in over 2 hours/day of sedentary behaviour (OR 2.93; 95% CI 1.32–6.49. Social support from friends also modified associations between network characteristics and MVPA and sedentary behaviour. Conclusion. Different network characteristics appeared to have different consequences. The proportion of active close friends was associated with MVPA, while network density was associated with sedentary behaviour. This poses challenges for intervention design.

  8. Constrained Active Learning for Anchor Link Prediction Across Multiple Heterogeneous Social Networks.

    Science.gov (United States)

    Zhu, Junxing; Zhang, Jiawei; Wu, Quanyuan; Jia, Yan; Zhou, Bin; Wei, Xiaokai; Yu, Philip S

    2017-08-03

    Nowadays, people are usually involved in multiple heterogeneous social networks simultaneously. Discovering the anchor links between the accounts owned by the same users across different social networks is crucial for many important inter-network applications, e.g., cross-network link transfer and cross-network recommendation. Many different supervised models have been proposed to predict anchor links so far, but they are effective only when the labeled anchor links are abundant. However, in real scenarios, such a requirement can hardly be met and most anchor links are unlabeled, since manually labeling the inter-network anchor links is quite costly and tedious. To overcome such a problem and utilize the numerous unlabeled anchor links in model building, in this paper, we introduce the active learning based anchor link prediction problem. Different from the traditional active learning problems, due to the one-to-one constraint on anchor links, if an unlabeled anchor link a = ( u , v ) is identified as positive (i.e., existing), all the other unlabeled anchor links incident to account u or account v will be negative (i.e., non-existing) automatically. Viewed in such a perspective, asking for the labels of potential positive anchor links in the unlabeled set will be rewarding in the active anchor link prediction problem. Various novel anchor link information gain measures are defined in this paper, based on which several constraint active anchor link prediction methods are introduced. Extensive experiments have been done on real-world social network datasets to compare the performance of these methods with state-of-art anchor link prediction methods. The experimental results show that the proposed Mean-entropy-based Constrained Active Learning (MC) method can outperform other methods with significant advantages.

  9. An Efficience Scheme to Reduce Burst Loss Rate and Supporting Differentiated Services in All-Optical Networks

    Science.gov (United States)

    Garg, Amit Kumar

    2011-06-01

    Due to their one-way resource reservation mechanism, Optical Burst Switching (OBS) networks experience high bursts (thus packets) loss rate. In OBS networks, the contention is resolved either by dropping one of the contending bursts or more efficiently by dropping from one of the contending bursts only the parts that overlap with the other bursts. In both situations, only one data source will suffer the data loss in favor to the other. In this paper, an efficient scheme to reduce burst loss rate has been proposed in conjunction with an appropriate mechanism to provide differentiated service in order to support the quality of service (QoS) requirements of different applications. Simulation results show that the performance of the proposed scheme is better than existing mechanisms in terms of reducing burst (packets) loss. Numerical results show that the proposed scheme provides an accurate fit for the performance of the highest traffic class and lower bounds for the other traffic classes that are tighter than earlier known results.

  10. Task-dependent changes in cross-level coupling between single neurons and oscillatory activity in multiscale networks.

    Directory of Open Access Journals (Sweden)

    Ryan T Canolty

    Full Text Available Understanding the principles governing the dynamic coordination of functional brain networks remains an important unmet goal within neuroscience. How do distributed ensembles of neurons transiently coordinate their activity across a variety of spatial and temporal scales? While a complete mechanistic account of this process remains elusive, evidence suggests that neuronal oscillations may play a key role in this process, with different rhythms influencing both local computation and long-range communication. To investigate this question, we recorded multiple single unit and local field potential (LFP activity from microelectrode arrays implanted bilaterally in macaque motor areas. Monkeys performed a delayed center-out reach task either manually using their natural arm (Manual Control, MC or under direct neural control through a brain-machine interface (Brain Control, BC. In accord with prior work, we found that the spiking activity of individual neurons is coupled to multiple aspects of the ongoing motor beta rhythm (10-45 Hz during both MC and BC, with neurons exhibiting a diversity of coupling preferences. However, here we show that for identified single neurons, this beta-to-rate mapping can change in a reversible and task-dependent way. For example, as beta power increases, a given neuron may increase spiking during MC but decrease spiking during BC, or exhibit a reversible shift in the preferred phase of firing. The within-task stability of coupling, combined with the reversible cross-task changes in coupling, suggest that task-dependent changes in the beta-to-rate mapping play a role in the transient functional reorganization of neural ensembles. We characterize the range of task-dependent changes in the mapping from beta amplitude, phase, and inter-hemispheric phase differences to the spike rates of an ensemble of simultaneously-recorded neurons, and discuss the potential implications that dynamic remapping from oscillatory activity to

  11. Advanced Nanoindentation Testing for Studying Strain-Rate Sensitivity and Activation Volume

    Science.gov (United States)

    Maier-Kiener, Verena; Durst, Karsten

    2017-11-01

    Nanoindentation became a versatile tool for testing local mechanical properties beyond hardness and modulus. By adapting standard nanoindentation test methods, simple protocols capable of probing thermally activated deformation processes can be accomplished. Abrupt strain-rate changes within one indentation allow determining the strain-rate dependency of hardness at various indentation depths. For probing lower strain-rates and excluding thermal drift influences, long-term creep experiments can be performed by using the dynamic contact stiffness for determining the true contact area. From both procedures hardness and strain-rate, and consequently strain-rate sensitivity and activation volume can be reliably deducted within one indentation, permitting information on the locally acting thermally activated deformation mechanism. This review will first discuss various testing protocols including possible challenges and improvements. Second, it will focus on different examples showing the direct influence of crystal structure and/or microstructure on the underlying deformation behavior in pure and highly alloyed material systems.

  12. Cardiovascular and Cerebrovascular Control on Return from International Space Station (CCISS)- Heart Rate and Activity

    Science.gov (United States)

    Hughson, R. L.; Shoemaker, J. K.; Blaber, A. P.; Arbeille, Ph.; Zuj, K. A.; Greaves, D. K.

    2008-06-01

    CCISS is a project to study the cardiovascular and cerebrovascular responses of astronauts before, during and after long-duration (>60-day) stays on the International Space Station. The CCISS experiments consist of three phases that are designed to achieve an integrated examination of components responsible for return of blood to the heart, the pumping of blood from the heart and the distribution to the vascular territories including the brain. In this report the data are obtained from the 24-h monitoring of physical activity (Actiwatch on wrist and ankle) and of heart rate (Holter monitor). The data show clear patterns of change in physical activity from predominantly leg-based on Earth to relatively little activity of the ankles with maintained or increased activity of the wrists on ISS. Both on Earth and on ISS the largest changes in heart rate occur during the periods of leg activity. Average heart rate was changed little during the periods of minimal activity or of sleep in comparisons of Earth with in-flight recording both within the first two weeks of flight and the last two weeks. These data clearly show the importance of monitoring heart rate and physical activity simultaneously and show that attempts to derive indicators of autonomic activity from spectral analysis of heart rate variability should not be performed in the absence of knowledge of both variables.

  13. The Effect of Sanctions and Active Labour Market Programmes on the Exit Rate From Unemployment

    DEFF Research Database (Denmark)

    Ahmad, Nisar; Svarer, Michael

    2009-01-01

    ). Hence, modeling only one of them as treatment might over or underestimate the true effect. Therefore, by using a multivariate mixed proportional hazard model (MMPH), we model the hazard rate out of unemployment along with the sanction rate and hazard rate into active labour market programmes. We......This paper simultaneously investigates the effectiveness of benefit sanctions and active labour market programmes on the exit rate from unemployment using Danish data. In the data about one third of the individuals who are sanctioned also participate in some active labour market programmes (ALMPs...... optimally select the number of supports point for the distribution of unobserved heterogeneity. Results show that pre-specifying two support points underestimates the effect of sanctions and active labour market programmes. Failing to control for selectivity for sanctions not only underestimates...

  14. Application of an Artificial Neural Network to the Prediction of OH Radical Reaction Rate Constants for Evaluating Global Warming Potential.

    Science.gov (United States)

    Allison, Thomas C

    2016-03-03

    Rate constants for reactions of chemical compounds with hydroxyl radical are a key quantity used in evaluating the global warming potential of a substance. Experimental determination of these rate constants is essential, but it can also be difficult and time-consuming to produce. High-level quantum chemistry predictions of the rate constant can suffer from the same issues. Therefore, it is valuable to devise estimation schemes that can give reasonable results on a variety of chemical compounds. In this article, the construction and training of an artificial neural network (ANN) for the prediction of rate constants at 298 K for reactions of hydroxyl radical with a diverse set of molecules is described. Input to the ANN consists of counts of the chemical bonds and bends present in the target molecule. The ANN is trained using 792 (•)OH reaction rate constants taken from the NIST Chemical Kinetics Database. The mean unsigned percent error (MUPE) for the training set is 12%, and the MUPE of the testing set is 51%. It is shown that the present methodology yields rate constants of reasonable accuracy for a diverse set of inputs. The results are compared to high-quality literature values and to another estimation scheme. This ANN methodology is expected to be of use in a wide range of applications for which (•)OH reaction rate constants are required. The model uses only information that can be gathered from a 2D representation of the molecule, making the present approach particularly appealing, especially for screening applications.

  15. 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

  16. 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.

  17. Design and Performance Investigation for the Optical Combinational Networks at High Data Rate

    Science.gov (United States)

    Tripathi, Devendra Kr.

    2017-05-01

    This article explores performance study for optical combinational designs based on nonlinear characteristics with semiconductor optical amplifier (SOA). Two configurations for optical half-adder with non-return-to-zero modulation pattern altogether with Mach-Zehnder modulator, interferometer at 50-Gbps data rate have been successfully realized. Accordingly, SUM and CARRY outputs have been concurrently executed and verified for their output waveforms. Numerical simulations for variation of data rate and key design parameters have been effectively executed outcome with optimum performance. Investigations depict overall good performance of the design in terms of the extinction factor. It also inferred that all-optical realization based on SOA is competent scheme, as it circumvents costly optoelectronic translation. This could be well supportive to erect larger complex optical combinational circuits.

  18. 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....

  19. Exploring sets of molecules from patents and relationships to other active compounds in chemical space networks

    Science.gov (United States)

    Kunimoto, Ryo; Bajorath, Jürgen

    2017-09-01

    Patents from medicinal chemistry represent a rich source of novel compounds and activity data that appear only infrequently in the scientific literature. Moreover, patent information provides a primary focal point for drug discovery. Accordingly, text mining and image extraction approaches have become hot topics in patent analysis and repositories of patent data are being established. In this work, we have generated network representations using alternative similarity measures to systematically compare molecules from patents with other bioactive compounds, visualize similarity relationships, explore the chemical neighbourhood of patent molecules, and identify closely related compounds with different activities. The design of network representations that combine patent molecules and other bioactive compounds and view patent information in the context of current bioactive chemical space aids in the analysis of patents and further extends the use of molecular networks to explore structure-activity relationships.

  20. Opposing Effects of Intrinsic Conductance and Correlated Synaptic Input on V-Fluctuations during Network Activity

    DEFF Research Database (Denmark)

    Kolind, Jens; Hounsgaard, Jørn Dybkjær; Berg, Rune W

    2012-01-01

    Neurons often receive massive concurrent bombardment of synaptic inhibition and excitation during functional network activity. This increases membrane conductance and causes fluctuations in membrane potential (V(m)) and spike timing. The conductance increase is commonly attributed to synaptic......(m) -fluctuations and conductance observed experimentally during functional network activity leave little room for intrinsic conductance to contribute. Even without intrinsic conductances the variance in V(m) -fluctuations can only be explained by a high degree of correlated firing among presynaptic neurons....... conductance, but also includes the intrinsic conductances recruited during network activity. These two sources of conductance have contrasting dynamic properties at sub-threshold membrane potentials. Synaptic transmitter gated conductance changes abruptly and briefly with each presynaptic action potential...

  1. Adaptive locomotor network activation during randomized walking speeds using functional near-infrared spectroscopy.

    Science.gov (United States)

    Kim, Ha Yeon; Kim, Eun Joo; You, Joshua Sung H

    2017-07-20

    An improved understanding of the mechanisms underlying locomotor networks has the potential to benefit the neurorehabilitation of patients with neurological locomotor deficits. However, the specific locomotor networks that mediate adaptive locomotor performance and changes in gait speed remain unknown. The aim of the present study was to examine patterns of cortical activation associated with the walking speeds of 1.5, 2.0, 2.5, and 3.0 km/h on a treadmill. Functional near-infrared spectroscopy (fNIRS) was performed on a 30-year-old right-handed healthy female subject, and cerebral hemodynamic changes were observed in cortical locomotor network areas including the primary sensorimotor cortex (SMC), premotor cortex (PMC), supplementary motor area (SMA), prefrontal cortex (PFC), and sensory association cortex (SAC). The software package NIRS-statistical parametric mapping (NIRS-SPM) was utilized to analyze fNIRS data in the MATLAB environment. SPM t-statistic maps were computed at an uncorrected threshold of pglobalized locomotor network activation of the SMC, PMC, SMA, and PMC; additionally, the site with the highest cortical activation ratio shifted from the SMC to the SMA. Global locomotor network recruitment, in particular PFC activation indicated by OxyHb in our study, may indicate a response to increased cognitive-locomotor demand due to simultaneous postural maintenance and leg movement coordination.

  2. Daily physical activity and heart rate response in people with a unilateral traumatic transtibial amputation.

    Science.gov (United States)

    Bussmann, Johannes B; Schrauwen, Hannelore J; Stam, Henk J

    2008-03-01

    To test the hypothesis that people with a unilateral traumatic transtibial amputation are less active than people without an amputation, and to explore whether both groups have a similar heart rate response while walking. A case-comparison study. General community. Nine subjects with a unilateral traumatic transtibial amputation and 9 matched subjects without known impairments. Not applicable. Percentage of dynamic activities in 48 hours (expressing activity level). Additionally, we examined heart rate and percentage heart rate reserve during walking (expressing heart rate response) and body motility during walking (expressing walking speed). These parameters were objectively measured at participants' homes on 2 consecutive days. Subjects with an amputation showed a lower percentage of dynamic activities (6.0% vs 11.7% in a 48-h period, P=.02). No significant differences were found between the 2 groups in heart rate (91.1 bpm vs 89.5 bpm, P=.86) and percentage heart rate reserve during walking (28.2% vs 27.5%, P=1.0). Body motility during walking was lower in the amputation group (.14 g vs .18 g, Ptranstibial amputation are considerably less active than persons without known impairments. The results indicate that heart rate response during walking is similar in both groups, and is probably regulated by adapting one's walking speed.

  3. Wearable Networked Sensing for Human Mobility and Activity Analytics: A Systems Study

    OpenAIRE

    Dong, Bo; Biswas, Subir

    2012-01-01

    This paper presents implementation details, system characterization, and the performance of a wearable sensor network that was designed for human activity analysis. Specific machine learning mechanisms are implemented for recognizing a target set of activities with both out-of-body and on-body processing arrangements. Impacts of energy consumption by the on-body sensors are analyzed in terms of activity detection accuracy for out-of-body processing. Impacts of limited processing abilities in ...

  4. Increased activity of pre-motor network does not change the excitability of motoneurons during protracted scratch initiation

    DEFF Research Database (Denmark)

    Guzulaitis, Robertas; Alaburda, Aidas; Hounsgaard, Jørn Dybkjær

    2013-01-01

    Intrinsic response properties of neurons change during network activity. These changes may reinforce the initiation of particular forms of network activity. If so, the involvement of neurons in particular behaviors in multifunctional networks could be determined by up or down regulation...... of their intrinsic excitability. Here we employed an experimental paradigm of protracted scratch initiation in the integrated carapace-spinal cord preparation of adult turtles (Chrysemys scripta elegans). The protracted initiation of scratch network activity allows us to investigate the excitability of motoneurons...... and pre-motor network activity in the time interval from the start of sensory stimulation until the onset of scratch activity. Our results suggest that increased activity in the pre-motor network facilitates the onset of scratch episodes but does not change the excitability of motoneurons at the onset...

  5. A Web-Based, Social Networking Physical Activity Intervention for Insufficiently Active Adults Delivered via Facebook App: Randomized Controlled Trial.

    Science.gov (United States)

    Maher, Carol; Ferguson, Monika; Vandelanotte, Corneel; Plotnikoff, Ron; De Bourdeaudhuij, Ilse; Thomas, Samantha; Nelson-Field, Karen; Olds, Tim

    2015-07-13

    Online social networks offer considerable potential for delivery of socially influential health behavior change interventions. To determine the efficacy, engagement, and feasibility of an online social networking physical activity intervention with pedometers delivered via Facebook app. A total of 110 adults with a mean age of 35.6 years (SD 12.4) were recruited online in teams of 3 to 8 friends. Teams were randomly allocated to receive access to a 50-day online social networking physical activity intervention which included self-monitoring, social elements, and pedometers ("Active Team" Facebook app; n=51 individuals, 12 teams) or a wait-listed control condition (n=59 individuals, 13 teams). Assessments were undertaken online at baseline, 8 weeks, and 20 weeks. The primary outcome measure was self-reported weekly moderate-to-vigorous physical activity (MVPA). Secondary outcomes were weekly walking, vigorous physical activity time, moderate physical activity time, overall quality of life, and mental health quality of life. Analyses were undertaken using random-effects mixed modeling, accounting for potential clustering at the team level. Usage statistics were reported descriptively to determine engagement and feasibility. At the 8-week follow-up, the intervention participants had significantly increased their total weekly MVPA by 135 minutes relative to the control group (P=.03), due primarily to increases in walking time (155 min/week increase relative to controls, Pself-monitoring features, were observed. An online, social networking physical activity intervention with pedometers can produce sizable short-term physical activity changes. Future work is needed to determine how to maintain behavior change in the longer term, how to reach at-need populations, and how to disseminate such interventions on a mass scale. Australian New Zealand Clinical Trials Registry (ANZCTR): ACTRN12614000488606; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=366239

  6. Activity of the Recommended and Optimized Rates of Pyridate on Chickpea - Mesorhizobium mediterraneum Symbiosis

    Directory of Open Access Journals (Sweden)

    Mehdi PARSA

    2014-03-01

    Full Text Available Crop-rhizobium symbiosis can be influenced by leaching of herbicides which is unavoidable after their application. Due to an adjuvant which might help to develop the low-use-rate of herbicide, an experiment was carried out to compare the impact of the recommended rate (1200 g active ingredient ha-1 and the optimized rate (282.15 g active ingredient ha-1 of pyridate on the biological properties of eight chickpea cultivars inoculated with Mesorhizobium mediterraneum, grown in pots. Based on the required rate of herbicide to give 95% control of common lambsquarters (Chenopodium album L. value, the efficacy of pyridate improved up to 3.87-fold by adding methylated rapeseed oil to spray solution. The ‘Desi’ cultivar had significantly higher nodulation than ‘Kabuli’ cultivar. In general, toxicity of the recommended rate was higher than the optimized rate. With the exception of root dry weight, all of the measured parameters were significantly affected by the recommended rate of pyridate in varying degrees. The symbiotic properties of chickpea cultivars were affected more than 10% at the recommended dose. The reduced nodulation ranged from 29% to 73% among cultivars exposed to pyridate at the recommended dose. The ‘Desi’ cultivar was more sensitive than the ‘Kabuli’ to the recommended rate of pyridate. We may conclude that effective low-use-rate of pyridate via applying of activator adjuvants should be noted.

  7. Cultured neural networks: Optimisation of patterned network adhesiveness and characterisation of their neural activity

    NARCIS (Netherlands)

    Rutten, Wim; Ruardij, T.G.; Marani, Enrico; Roelofsen, B.H.

    2006-01-01

    One type of future, improved neural interface is the "cultured probe"?. It is a hybrid type of neural information transducer or prosthesis, for stimulation and/or recording of neural activity. It would consist of a microelectrode array (MEA) on a planar substrate, each electrode being covered and

  8. Validation of the Social Networking Activity Intensity Scale among Junior Middle School Students in China

    Science.gov (United States)

    Li, Jibin; Lau, Joseph T. F.; Mo, Phoenix K. H.; Su, Xuefen; Wu, Anise M. S.; Tang, Jie; Qin, Zuguo

    2016-01-01

    Background Online social networking use has been integrated into adolescents’ daily life and the intensity of online social networking use may have important consequences on adolescents’ well-being. However, there are few validated instruments to measure social networking use intensity. The present study aims to develop the Social Networking Activity Intensity Scale (SNAIS) and validate it among junior middle school students in China. Methods A total of 910 students who were social networking users were recruited from two junior middle schools in Guangzhou, and 114 students were retested after two weeks to examine the test-retest reliability. The psychometrics of the SNAIS were estimated using appropriate statistical methods. Results Two factors, Social Function Use Intensity (SFUI) and Entertainment Function Use Intensity (EFUI), were clearly identified by both exploratory and confirmatory factor analyses. No ceiling or floor effects were observed for the SNAIS and its two subscales. The SNAIS and its two subscales exhibited acceptable reliability (Cronbach’s alpha = 0.89, 0.90 and 0.60, and test-retest Intra-class Correlation Coefficient = 0.85, 0.87 and 0.67 for Overall scale, SFUI and EFUI subscale, respectively, pnetworking, social networking addiction, Internet addiction, and characteristics related to social networking use. Conclusions The SNAIS is an easily self-administered scale with good psychometric properties. It would facilitate more research in this field worldwide and specifically in the Chinese population. PMID:27798699

  9. Active turnover regulates pattern formation and stress transmission in disordered acto-myosin networks

    Science.gov (United States)

    McCall, Patrick; Stam, Samantha; Kovar, David; Gardel, Margaret

    The shape and mechanics of animal cells are controlled by a dynamic, thin network of semiflexible actin filaments and myosin-II motor proteins called the actomyosin cortex. Motor-generated stresses in the cortex drive changes in cell shape during cell division and morphogenesis, while dynamic turnover of actin filaments dissipates stress. The relative effects that force generation, force dissipation, and disassembly and reassembly of material have on motion in these networks are unknown. We find that cross-linked actin networks in vitro contract under myosin-generated stresses, resulting in partial filament disassembly, the formation of asters, and clustering of myosin motors. We observe a rapid restoration of uniform polymer density in the presence of the assembly factors which catalyze network turnover through elongation of severed actin filaments. When severing is accelerated further by the addition of a severing protein, network contraction and motor clustering are dramatically suppressed. We test the relative effects of material regeneration and force transmission using image analysis, and conclude that the dominant mechanism for this effect is relatively short-lived stresses that do not propagate over considerable distance or push network deformation into the nonlinear contractile regime we have previously characterized. Our results present a framework to understand cytoskeletal active matter that are influenced by a complex interplay between stress generation, network reorganization, and polymer turnover.

  10. Active influence in dynamical models of structural balance in social networks

    Science.gov (United States)

    Summers, Tyler H.; Shames, Iman

    2013-07-01

    We consider a nonlinear dynamical system on a signed graph, which can be interpreted as a mathematical model of social networks in which the links can have both positive and negative connotations. In accordance with a concept from social psychology called structural balance, the negative links play a key role in both the structure and dynamics of the network. Recent research has shown that in a nonlinear dynamical system modeling the time evolution of “friendliness levels” in the network, two opposing factions emerge from almost any initial condition. Here we study active external influence in this dynamical model and show that any agent in the network can achieve any desired structurally balanced state from any initial condition by perturbing its own local friendliness levels. Based on this result, we also introduce a new network centrality measure for signed networks. The results are illustrated in an international-relations network using United Nations voting record data from 1946 to 2008 to estimate friendliness levels amongst various countries.

  11. Validation of the Social Networking Activity Intensity Scale among Junior Middle School Students in China.

    Science.gov (United States)

    Li, Jibin; Lau, Joseph T F; Mo, Phoenix K H; Su, Xuefen; Wu, Anise M S; Tang, Jie; Qin, Zuguo

    2016-01-01

    Online social networking use has been integrated into adolescents' daily life and the intensity of online social networking use may have important consequences on adolescents' well-being. However, there are few validated instruments to measure social networking use intensity. The present study aims to develop the Social Networking Activity Intensity Scale (SNAIS) and validate it among junior middle school students in China. A total of 910 students who were social networking users were recruited from two junior middle schools in Guangzhou, and 114 students were retested after two weeks to examine the test-retest reliability. The psychometrics of the SNAIS were estimated using appropriate statistical methods. Two factors, Social Function Use Intensity (SFUI) and Entertainment Function Use Intensity (EFUI), were clearly identified by both exploratory and confirmatory factor analyses. No ceiling or floor effects were observed for the SNAIS and its two subscales. The SNAIS and its two subscales exhibited acceptable reliability (Cronbach's alpha = 0.89, 0.90 and 0.60, and test-retest Intra-class Correlation Coefficient = 0.85, 0.87 and 0.67 for Overall scale, SFUI and EFUI subscale, respectively, pnetworking, social networking addiction, Internet addiction, and characteristics related to social networking use. The SNAIS is an easily self-administered scale with good psychometric properties. It would facilitate more research in this field worldwide and specifically in the Chinese population.

  12. Update on the activities of the GGOS Bureau of Networks and Observations

    Science.gov (United States)

    Pearlman, Michael R.; Pavlis, Erricos C.; Ma, Chopo; Noll, Carey; Thaller, Daniela; Richter, Bernd; Gross, Richard; Neilan, Ruth; Mueller, Juergen; Barzaghi, Ricardo; hide

    2016-01-01

    The recently reorganized GGOS Bureau of Networks and Observations has many elements that are associated with building and sustaining the infrastructure that supports the Global Geodetic Observing System (GGOS) through the development and maintenance of the International Terrestrial and Celestial Reference Frames, improved gravity field models and their incorporation into the reference frame, the production of precision orbits for missions of interest to GGOS, and many other applications. The affiliated Service Networks (IVS, ILRS, IGS, IDS, and now the IGFS and the PSMSL) continue to grow geographically and to improve core and co-location site performance with newer technologies. Efforts are underway to expand GGOS participation and outreach. Several groups are undertaking initiatives and seeking partnerships to update existing sites and expand the networks in geographic areas void of coverage. New satellites are being launched by the Space Agencies in disciplines relevant to GGOS. Working groups now constitute an integral part of the Bureau, providing key service to GGOS. Their activities include: projecting future network capability and examining trade-off options for station deployment and technology upgrades, developing metadata collection and online availability strategies; improving coordination and information exchange with the missions for better ground-based network response and space-segment adequacy for the realization of GGOS goals; and standardizing site-tie measurement, archiving, and analysis procedures. This poster will present the progress in the Bureau's activities and its efforts to expand the networks and make them more effective in supporting GGOS.

  13. Operation Optimization Based on the Power Supply and Storage Capacity of an Active Distribution Network

    Directory of Open Access Journals (Sweden)

    Wenpeng Yu

    2013-12-01

    Full Text Available Due to the interconnection and active management of Distributed Generation (DG and Energy Storage Systems (ESSs, the traditional electrical distribution network has become an Active Distribution Network (ADN, posing challenges to the operation optimization of the network. The power supply and storage capacity indexes of a Local Autonomy Control Region (LACR, which consists of DGs, ESSs and the network, are proposed in this paper to quantify the power regulating range of a LACR. DG/ESS and the network are considered as a whole in the model of the indexes, considering both network constraints and power constraints of the DG/ESS. The index quantifies the maximum LACR power supplied to or received from ADN lines. Similarly, power supply and storage capacity indexes of the ADN line are also proposed to quantify the maximum power exchanged between ADN lines. Then a practical algorithm to calculate the indexes is presented, and an operation optimization model is proposed based on the indexes to maximum the economic benefit of DG/ESS. In the optimization model, the power supply reliability of the ADN line is also considered. Finally, the indexes of power supply and storage capacity and the optimization are demonstrated in a case study.

  14. Tissue factor activates allosteric networks in factor VIIa through structural and dynamic changes

    DEFF Research Database (Denmark)

    Madsen, Jesper Jonasson; Persson, E.; Olsen, O. H.

    2015-01-01

    Background: Tissue factor (TF) promotes colocalization of enzyme (factorVIIa) and substrate (FX or FIX), and stabilizes the active conformation of FVIIa. Details on how TF induces structural and dynamic changes in the catalytic domain of FVIIa to enhance its efficiency remain elusive. Objective......: To elucidate the activation of allosteric networks in the catalytic domain of the FVIIa protease it is when bound to TF.MethodsLong-timescale molecular dynamics simulations of FVIIa, free and in complex with TF, were executed and analyzed by dynamic network analysis. Results: Allosteric paths of correlated...

  15. Neural oscillations: beta band activity across motor networks.

    Science.gov (United States)

    Khanna, Preeya; Carmena, Jose M

    2015-06-01

    Local field potential (LFP) activity in motor cortical and basal ganglia regions exhibits prominent beta (15-40Hz) oscillations during reaching and grasping, muscular contraction, and attention tasks. While in vitro and computational work has revealed specific mechanisms that may give rise to the frequency and duration of this oscillation, there is still controversy about what behavioral processes ultimately drive it. Here, simultaneous behavioral and large-scale neural recording experiments from non-human primate and human subjects are reviewed in the context of specific hypotheses about how beta band activity is generated. Finally, a new experimental paradigm utilizing operant conditioning combined with motor tasks is proposed as a way to further investigate this oscillation. Copyright © 2014 Elsevier Ltd. All rights reserved.

  16. Recurrently connected and localized neuronal communities initiate coordinated spontaneous activity in neuronal networks.

    Science.gov (United States)

    Lonardoni, Davide; Amin, Hayder; Di Marco, Stefano; Maccione, Alessandro; Berdondini, Luca; Nieus, Thierry

    2017-07-01

    Developing neuronal systems intrinsically generate coordinated spontaneous activity that propagates by involving a large number of synchronously firing neurons. In vivo, waves of spikes transiently characterize the activity of developing brain circuits and are fundamental for activity-dependent circuit formation. In vitro, coordinated spontaneous spiking activity, or network bursts (NBs), interleaved within periods of asynchronous spikes emerge during the development of 2D and 3D neuronal cultures. Several studies have investigated this type of activity and its dynamics, but how a neuronal system generates these coordinated events remains unclear. Here, we investigate at a cellular level the generation of network bursts in spontaneously active neuronal cultures by exploiting high-resolution multielectrode array recordings and computational network modelling. Our analysis reveals that NBs are generated in specialized regions of the network (functional neuronal communities) that feature neuronal links with high cross-correlation peak values, sub-millisecond lags and that share very similar structural connectivity motifs providing recurrent interactions. We show that the particular properties of these local structures enable locally amplifying spontaneous asynchronous spikes and that this mechanism can lead to the initiation of NBs. Through the analysis of simulated and experimental data, we also show that AMPA currents drive the coordinated activity, while NMDA and GABA currents are only involved in shaping the dynamics of NBs. Overall, our results suggest that the presence of functional neuronal communities with recurrent local connections allows a neuronal system to generate spontaneous coordinated spiking activity events. As suggested by the rules used for implementing our computational model, such functional communities might naturally emerge during network development by following simple constraints on distance-based connectivity.

  17. Recurrently connected and localized neuronal communities initiate coordinated spontaneous activity in neuronal networks.

    Directory of Open Access Journals (Sweden)

    Davide Lonardoni

    2017-07-01

    Full Text Available Developing neuronal systems intrinsically generate coordinated spontaneous activity that propagates by involving a large number of synchronously firing neurons. In vivo, waves of spikes transiently characterize the activity of developing brain circuits and are fundamental for activity-dependent circuit formation. In vitro, coordinated spontaneous spiking activity, or network bursts (NBs, interleaved within periods of asynchronous spikes emerge during the development of 2D and 3D neuronal cultures. Several studies have investigated this type of activity and its dynamics, but how a neuronal system generates these coordinated events remains unclear. Here, we investigate at a cellular level the generation of network bursts in spontaneously active neuronal cultures by exploiting high-resolution multielectrode array recordings and computational network modelling. Our analysis reveals that NBs are generated in specialized regions of the network (functional neuronal communities that feature neuronal links with high cross-correlation peak values, sub-millisecond lags and that share very similar structural connectivity motifs providing recurrent interactions. We show that the particular properties of these local structures enable locally amplifying spontaneous asynchronous spikes and that this mechanism can lead to the initiation of NBs. Through the analysis of simulated and experimental data, we also show that AMPA currents drive the coordinated activity, while NMDA and GABA currents are only involved in shaping the dynamics of NBs. Overall, our results suggest that the presence of functional neuronal communities with recurrent local connections allows a neuronal system to generate spontaneous coordinated spiking activity events. As suggested by the rules used for implementing our computational model, such functional communities might naturally emerge during network development by following simple constraints on distance-based connectivity.

  18. Genetic Networks Activated by Blast Injury to the Eye

    Science.gov (United States)

    2015-08-01

    transferred to PVD membranes. The blots were blocked with 2% non-fat dry milk in phosphate buffer (pH 7.4) and probed overnight with the rabbit anti- SOX11...inorganic cation transmembrane transporter, and metal ion transmembrane transporter activity); and cellular components (cell projection part, neuron...primary antibody (Santa Cruz Biotechnology, Inc. California). We then rinsed the blots and probed them with the HRP-labeled donkey anti- rabbit

  19. Impact of Demand Side Management in Active Distribution Networks

    DEFF Research Database (Denmark)

    Ponnaganti, Pavani; Bak-Jensen, Birgitte; Pillai, Jayakrishnan Radhakrishna

    2017-01-01

    of visibility in the electricity markets. The aim of this paper is to find the optimal flexible demands that can be shifted to another time in order to operate the active distribution system within secure operating limits. A simple mechanism is proposed for finding the flexibility of the loads where electric...... vehicle, electric heating etc. are present. Simulations are carried out in Danish low voltage grid for summer and winter cases....

  20. Cybersecurity Activities Support to DoD Information Network Operations

    Science.gov (United States)

    2016-03-07

    Component training or certification requirements. DoDI 8530.01, March 7, 2016 ENCLOSURE 4 33 ENCLOSURE 4 CYBERSECURITY INTEGRATION INTO DoDIN...Department of Defense INSTRUCTION NUMBER 8530.01 March 7, 2016 DoD CIO SUBJECT: Cybersecurity Activities Support to DoD Information...organizational entities within the DoD (referred to collectively in this instruction as the “DoD Components”). DoDI 8530.01, March 7, 2016 2 b