WorldWideScience

Sample records for level active networking

  1. 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 identifie......-ordination and management of the network assets at different voltage levels and geographical locations. The paper finally shows the applicability of the multi-level control architecture to some of the key challenges in the distribution system operation by relevant scenarios....... 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...

  2. Caribbean Sea Level Network

    Science.gov (United States)

    von Hillebrandt-Andrade, C.; Crespo Jones, H.

    2012-12-01

    requirements and factors have been considered for the sustainability of the stations. The sea level stations have to potentially sustain very aggressive conditions of not only tsunamis, but on a more regular basis, hurricanes. Given the requirement that the data be available in near real time, for tsunami and other coastal hazard application, robust communication systems are also essential. For the local operator, the ability to be able to visualize the data is critical and tools like the IOC Sea level Monitoring Facility and the Tide Tool program are very useful. It has also been emphasized the need for these stations to serve multiple purposes. For climate and other research applications the data need to be archived, QC'd and analyzed. Increasing the user base for the sea level data has also been seen as an important goal to gain the local buy in; local weather and meteorological offices are considered as key stakeholders but for whom applications still need to be developed. The CARIBE EWS continues to look forward to working with other IOC partners including the Global Sea Level Observing System (GLOSS) and Sub-Commission for the Caribbean and Adjacent Regions (IOCARIBE)/GOOS, as well as with local, national and global sea level station operators and agencies for the development of a sustainable sea level network.

  3. Effects of Managers’ Work Motivation and Networking Activity on Their Reported Levels of External Red Tape

    NARCIS (Netherlands)

    Torenvlied, R.; Akkerman, A.

    2012-01-01

    This study brings together two perspectives on managers’ reported levels of red tape. The work motivation perspective explains how managers’ characteristics, such as work engagement (alienation) or commitment, affect their reported levels of red tape. The external control perspective explains how

  4. A template for constructing Bayesian networks in forensic biology cases when considering activity level propositions.

    Science.gov (United States)

    Taylor, Duncan; Biedermann, Alex; Hicks, Tacha; Champod, Christophe

    2018-03-01

    The hierarchy of propositions has been accepted amongst the forensic science community for some time. It is also accepted that the higher up the hierarchy the propositions are, against which the scientist are competent to evaluate their results, the more directly useful the testimony will be to the court. Because each case represents a unique set of circumstances and findings, it is difficult to come up with a standard structure for evaluation. One common tool that assists in this task is Bayesian networks (BNs). There is much diversity in the way that BN can be constructed. In this work, we develop a template for BN construction that allows sufficient flexibility to address most cases, but enough commonality and structure that the flow of information in the BN is readily recognised at a glance. We provide seven steps that can be used to construct BNs within this structure and demonstrate how they can be applied, using a case example. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

  5. Reflections on Active Networking

    Science.gov (United States)

    2005-01-01

    with a Software Switch for Active Networks ”. We had initially called the project “ SoftSwitch ”, but after some concerns David Farber raised that this...Reflections on Active Networking Jonathan M. Smith CIS Department, University of Pennsylvania jms@cis.upenn.edu Abstract Interactions among...telecommunications networks , computers, and other peripheral devices have been of interest since the earliest distributed computing systems. A key

  6. 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

  7. ANN multiscale model of anti-HIV drugs activity vs AIDS prevalence in the US at county level based on information indices of molecular graphs and social networks.

    Science.gov (United States)

    González-Díaz, Humberto; Herrera-Ibatá, Diana María; Duardo-Sánchez, Aliuska; Munteanu, Cristian R; Orbegozo-Medina, Ricardo Alfredo; Pazos, Alejandro

    2014-03-24

    This work is aimed at describing the workflow for a methodology that combines chemoinformatics and pharmacoepidemiology methods and at reporting the first predictive model developed with this methodology. The new model is able to predict complex networks of AIDS prevalence in the US counties, taking into consideration the social determinants and activity/structure of anti-HIV drugs in preclinical assays. We trained different Artificial Neural Networks (ANNs) using as input information indices of social networks and molecular graphs. We used a Shannon information index based on the Gini coefficient to quantify the effect of income inequality in the social network. We obtained the data on AIDS prevalence and the Gini coefficient from the AIDSVu database of Emory University. We also used the Balaban information indices to quantify changes in the chemical structure of anti-HIV drugs. We obtained the data on anti-HIV drug activity and structure (SMILE codes) from the ChEMBL database. Last, we used Box-Jenkins moving average operators to quantify information about the deviations of drugs with respect to data subsets of reference (targets, organisms, experimental parameters, protocols). The best model found was a Linear Neural Network (LNN) with values of Accuracy, Specificity, and Sensitivity above 0.76 and AUROC > 0.80 in training and external validation series. This model generates a complex network of AIDS prevalence in the US at county level with respect to the preclinical activity of anti-HIV drugs in preclinical assays. To train/validate the model and predict the complex network we needed to analyze 43,249 data points including values of AIDS prevalence in 2,310 counties in the US vs ChEMBL results for 21,582 unique drugs, 9 viral or human protein targets, 4,856 protocols, and 10 possible experimental measures.

  8. Levelling Profiles and a GPS Network to Monitor the Active Folding and Faulting Deformation in the Campo de Dalias (Betic Cordillera, Southeastern Spain)

    Science.gov (United States)

    Marín-Lechado, Carlos; Galindo-Zaldívar, Jesús; Gil, Antonio José; Borque, María Jesús; de Lacy, María Clara; Pedrera, Antonio; López-Garrido, Angel Carlos; Alfaro, Pedro; García-Tortosa, Francisco; Ramos, Maria Isabel; Rodríguez-Caderot, Gracia; Rodríguez-Fernández, José; Ruiz-Constán, Ana; de Galdeano-Equiza, Carlos Sanz

    2010-01-01

    The Campo de Dalias is an area with relevant seismicity associated to the active tectonic deformations of the southern boundary of the Betic Cordillera. A non-permanent GPS network was installed to monitor, for the first time, the fault- and fold-related activity. In addition, two high precision levelling profiles were measured twice over a one-year period across the Balanegra Fault, one of the most active faults recognized in the area. The absence of significant movement of the main fault surface suggests seismogenic behaviour. The possible recurrence interval may be between 100 and 300 y. The repetitive GPS and high precision levelling monitoring of the fault surface during a long time period may help us to determine future fault behaviour with regard to the existence (or not) of a creep component, the accumulation of elastic deformation before faulting, and implications of the fold-fault relationship. PMID:22319309

  9. Friendship network position and salivary cortisol levels.

    Science.gov (United States)

    Kornienko, Olga; Clemans, Katherine H; Out, Dorothée; Granger, Douglas A

    2013-01-01

    We employed a social network analysis approach to examine the associations between friendship network position and cortisol levels. The sample consisted of 74 first-year students (93% female, ages 22-38 years, M = 27) from a highly competitive, accelerated Nursing program. Participants completed questionnaires online, and the entire group met at one time to complete a series of sociometric nominations and donated a saliva sample. Saliva was later assayed for cortisol. Metrics derived from directed friendship nominations indexed each student's friendship network status regarding popularity, gregariousness, and degree of interconnectedness. Results revealed that (1) individuals with lower gregariousness status (i.e., lowest number of outgoing ties) had higher cortisol levels, and (2) individuals with higher popularity status (i.e., higher numbers of incoming ties) had higher cortisol levels. Popularity and gregariousness-based network status is significantly associated with hypothalamic-pituitary-adrenal axis activity. Implications for prevailing theories of the social determinants of individual differences in biological sensitivity and susceptibility to context are discussed.

  10. Forecasting Water Levels Using Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Shreenivas N. Londhe

    2011-06-01

    Full Text Available For all Ocean related activities it is necessary to predict the actual water levels as accurate as possible. The present work aims at predicting the water levels with a lead time of few hours to a day using the technique of artificial neural networks. Instead of using the previous and current values of observed water level time series directly as input and output the water level anomaly (difference between the observed water level and harmonically predicted tidal level is calculated for each hour and the ANN model is developed using this time series. The network predicted anomaly is then added to harmonic tidal level to predict the water levels. The exercise is carried out at six locations, two in The Gulf of Mexico, two in The Gulf of Maine and two in The Gulf of Alaska along the USA coastline. The ANN models performed reasonably well for all forecasting intervals at all the locations. The ANN models were also run in real time mode for a period of eight months. Considering the hurricane season in Gulf of Mexico the models were also tested particularly during hurricanes.

  11. Simulation of Changes of Activity Level of Some Carbohydrazes of Russian Sturgeon by the Influence of Environmental Osmotic Pressure by Means of Hybrid Networks

    Directory of Open Access Journals (Sweden)

    A. V. Tuktarov

    2010-01-01

    Full Text Available The article is devoted to the problem of simulation of the influence environmental osmotic pressure to the activity level of maltase and α-amilase of intestinal mucous tunic of Russian sturgeon. For the solving of this problem methods of neural networks and fuzzy logic are used. Create models are rated as the category of adaptive neural-fuzzy inference systems. Regularities of this influence were researched; created models have high approximate property and generalize well.

  12. 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......? Other contributions include examining the role of geographic factors in networking and whether research bottlenecks affect a researcher's propensity to network. Are the determinants of European conference participation by German researchers different from conferences in rest of the world? Results show...... 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...

  13. Global physical activity levels

    DEFF Research Database (Denmark)

    Hallal, Pedro C; Andersen, Lars Bo; Bull, Fiona C

    2012-01-01

    To implement effective non-communicable disease prevention programmes, policy makers need data for physical activity levels and trends. In this report, we describe physical activity levels worldwide with data for adults (15 years or older) from 122 countries and for adolescents (13-15-years......-income countries. The proportion of 13-15-year-olds doing fewer than 60 min of physical activity of moderate to vigorous intensity per day is 80·3% (80·1-80·5); boys are more active than are girls. Continued improvement in monitoring of physical activity would help to guide development of policies and programmes......-old) from 105 countries. Worldwide, 31·1% (95% CI 30·9-31·2) of adults are physically inactive, with proportions ranging from 17·0% (16·8-17·2) in southeast Asia to about 43% in the Americas and the eastern Mediterranean. Inactivity rises with age, is higher in women than in men, and is increased in high...

  14. Russian State Leveling Network (present and future)

    Science.gov (United States)

    Mazurova, Elena; Kopeikin, Sergei; Karpik, Aleksander

    2017-04-01

    In August 2016 the sixth session of the United Nations Committee of Experts of Global Geospatial Information Management (UN-GGIM) endorsed the roadmap for the development of a Global Geodetic Reference Frame (GGRF) and urged countries to join efforts for its creation. In response to the UN appeal in this article describes the current state of the high-precision Leveling Network in Russia and prospects of its development. In this paper, we consider projects related to the construction of new high-precision leveling lines by the classical methods, as well as issues of creating high-precision leveling network, associated with the development and implementation of a fundamentally new method of determining heights in geodesy - chronometric leveling based on the application of quantum metrology of time and the fundamental laws of general relativity. Keywords: leveling network, chronometric leveling, quantum metrology of time, the general theory of relativity.

  15. Constructing level-2 phylogenetic networks from triplets

    OpenAIRE

    Iersel, Leo; Keijsper, J.C.M.; Kelk, Steven; Stougie, Leen; Hagen, F.; Boekhout, T.; Vingron, M.; Wong, L.

    2009-01-01

    htmlabstractJansson and Sung showed that, given a dense set of input triplets T (representing hypotheses about the local evolutionary relationships of triplets of taxa), it is possible to determine in polynomial time whether there exists a level-1 network consistent with T, and if so to construct such a network (Inferring a Level-1 Phylogenetic Network from a Dense Set of Rooted Triplets, Theoretical Computer Science, 363, pp. 60-68 (2006)). Here we extend this work by showing that this probl...

  16. 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.

  17. Multi-Level Secure Local Area Network

    OpenAIRE

    Naval Postgraduate School (U.S.); Center for Information Systems Studies Security and Research (CISR)

    2011-01-01

    Multi-Level Secure Local Area Network is a cost effective, multi-level, easy to use office environment leveraging existing high assurance technology. The Department of Defense and U.S. Government have an identified need to securely share information classified at differing security levels. Because there exist no commercial solutions to this problem, NPS is developing a MLS LAN. The MLS LAN extends high assurance capabilities of an evaluated multi-level secure system to commercial personal com...

  18. Network Communication for Low Level RF Control

    International Nuclear Information System (INIS)

    Liu Weiqing; Yin Chengke; Zhang Tongxuan; Fu Zechuan; Liu Jianfei

    2009-01-01

    Low Level RF (LLRF) control system for storage ring of Shanghai Synchrotron Radiation Facility (SSRF) has been built by digital technology. The settings of parameters and the feedback loop status are carried out through the network communication interface, and the local oscillation and clock, which is the important component of the digital LLRF control system, are also configured through network communication. NIOS II processor was employed as a core to build the embedded system with a real-time operating system MicroC/OS-II, finally Lightweight TCP/IP (LwIP) was used to achieve the communication interface. The communication network is stable after a long-term operation. (authors)

  19. 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.

  20. 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.…

  1. Achieving Network Level Privacy in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Sungyoung Lee

    2010-02-01

    Full Text Available Full network level privacy has often been categorized into four sub-categories: Identity, Route, Location and Data privacy. Achieving full network level privacy is a critical and challenging problem due to the constraints imposed by the sensor nodes (e.g., energy, memory and computation power, sensor networks (e.g., mobility and topology and QoS issues (e.g., packet reach-ability and timeliness. In this paper, we proposed two new identity, route and location privacy algorithms and data privacy mechanism that addresses this problem. The proposed solutions provide additional trustworthiness and reliability at modest cost of memory and energy. Also, we proved that our proposed solutions provide protection against various privacy disclosure attacks, such as eavesdropping and hop-by-hop trace back attacks.

  2. 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.

  3. 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...

  4. Radon levels in a water distribution network

    International Nuclear Information System (INIS)

    Alabdula'aly, A.I.

    1997-01-01

    The capital city of Saudi Arabia, Riyadh, relies on both desalinated sea water as well as treated groundwater to meet all its water requirements. About 66% of the water demand is met by desalinated sea water, and the remaining is supplied by six groundwater treatment plants located in the vicinity of the city and supplied with water from 161 wells. The desalinated sea water is blended with only one plant product water and pumped to the distribution network, whereas the other five plants product water is pumped directly to the network. A study of 222 Rn levels in the city distribution network was carried out in which 89 samples were collected from different locations representing the city districts. All samples have shown low radon levels with an average concentration of 0.2 Bq l -1 and a range values of 0.1-1.0 Bq l -1 . The level of radon in different parts of the network was found to be influenced by the water sources to which they are supplied. The lowest radon levels were observed in districts supplied mostly by desalinated sea water. (Author)

  5. Active hippocampal networks undergo spontaneous synaptic modification.

    Directory of Open Access Journals (Sweden)

    Masako Tsukamoto-Yasui

    Full Text Available The brain is self-writable; as the brain voluntarily adapts itself to a changing environment, the neural circuitry rearranges its functional connectivity by referring to its own activity. How the internal activity modifies synaptic weights is largely unknown, however. Here we report that spontaneous activity causes complex reorganization of synaptic connectivity without any external (or artificial stimuli. Under physiologically relevant ionic conditions, CA3 pyramidal cells in hippocampal slices displayed spontaneous spikes with bistable slow oscillations of membrane potential, alternating between the so-called UP and DOWN states. The generation of slow oscillations did not require fast synaptic transmission, but their patterns were coordinated by local circuit activity. In the course of generating spontaneous activity, individual neurons acquired bidirectional long-lasting synaptic modification. The spontaneous synaptic plasticity depended on a rise in intracellular calcium concentrations of postsynaptic cells, but not on NMDA receptor activity. The direction and amount of the plasticity varied depending on slow oscillation patterns and synapse locations, and thus, they were diverse in a network. Once this global synaptic refinement occurred, the same neurons now displayed different patterns of spontaneous activity, which in turn exhibited different levels of synaptic plasticity. Thus, active networks continuously update their internal states through ongoing synaptic plasticity. With computational simulations, we suggest that with this slow oscillation-induced plasticity, a recurrent network converges on a more specific state, compared to that with spike timing-dependent plasticity alone.

  6. Letter to Editor: RESITA NETWORK - ACADEMIC ENTREPRENEURSHIP AND INNOVATION NETWORK OF SOUTH EASTERN EUROPEAN UNIVERSITIES: AN EXAMPLE OF SUCCESSFUL NETWORKING IN ENTREPRENEURSHIP AND INNOVATION AT ACADEMIC LEVEL

    Directory of Open Access Journals (Sweden)

    Peter Schulte

    2013-05-01

    Full Text Available The foundation, development, activities, and wider social impact of the AcademicEntrepreneurship and Innovation Network of South Eastern European Universities, or shortlyRESITA Network, is presented in this paper as a positive example of successful networking inentrepreneurship and innovation at academic level.

  7. Effort levels of the partners in networked manufacturing

    Science.gov (United States)

    Chai, G. R.; Cai, Z.; Su, Y. N.; Zong, S. L.; Zhai, G. Y.; Jia, J. H.

    2017-08-01

    Compared with traditional manufacturing mode, could networked manufacturing improve effort levels of the partners? What factors will affect effort level of the partners? How to encourage the partners to improve their effort levels? To answer these questions, we introduce network effect coefficient to build effort level model of the partners in networked manufacturing. The results show that (1) with the increase of the network effect in networked manufacturing, the actual effort level can go beyond the ideal level of traditional manufacturing. (2) Profit allocation based on marginal contribution rate would help improve effort levels of the partners in networked manufacturing. (3) The partners in networked manufacturing who wishes to have a larger distribution ratio must make a higher effort level, and enterprises with insufficient effort should be terminated in networked manufacturing.

  8. An fMRI study of joint action – varying levels of cooperation correlates with activity in sensorimotor control, but not mentalization, networks

    Directory of Open Access Journals (Sweden)

    Thierry eChaminade

    2012-06-01

    Full Text Available As social agents, humans continuously interact with with the people around them. Here, motor cooperation was investigated by designing a situation in which pairs of participants, one being scanned with fMRI, controlled jointly a visually presented object with joystick movements. The object oscillated dynamically along two dimensions, shades of pink and width of gratings, corresponding to the two cardinal directions of joystick movements. While the overall control of each participant on the object was kept constant, the amount of cooperation along the two dimensions varied along four levels, from no (each participant controlled exclusively one dimension to full (each participant controlled half of each dimension cooperation. Increasing cooperation correlated with BOLD signal in the left parietal operculum and anterior cingulate cortex, while decreasing cooperation correlated with activity in the right inferior frontal and superior temporal gyri, in the intraparietal sulci and inferior temporal gyrii bilaterally, and in the dorsomedial prefrontal cortex. As joint control improved with the level of cooperation, we assessed the brain responses correlating with joint performance, and found that activity in most of the areas associated with levels of cooperation also correlated with the joint performance. The only brain area found exclusively in the negative correlation with cooperation was within the posterior region of the rostral medial frontal cortex, involved in the monitoring of action outcome. We therefore propose that this region responds to the predictability of visual feedback given the motor commands, which is maximal when participants do not cooperate as they fully control one dimension. Our results therefore indicate that, in the current experimental paradigm, the level of cooperation affects sensorimotor processing, but not mentalizing. Altogether, humans do not need to have access to others’ intentional states to cooperate on a joint

  9. 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.

  10. Monitoring Malware Activity on the LAN Network

    Science.gov (United States)

    Skrzewski, Mirosław

    Many security related organizations periodically publish current network and systems security information, with the lists of top malware programs. These lists raises the question how these threats spreads out, if the worms (the only threat with own communication abilities) are low or missing on these lists. The paper discuss the research on malware network activity, aimed to deliver the answer to the question, what is the main infection channel of modern malware, done with the usage of virtual honeypot systems on dedicated, unprotected network. Systems setup, network and systems monitoring solutions, results of over three months of network traffic and malware monitoring are presented, along with the proposed answer to our research question.

  11. 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 Networ....... ABSN enhances the generic Extended Zone Routing Protocol with logical sensor grouping and greatly lowers network overhead during the process of discovery, while keeping discovery latency close to optimal.......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...

  12. How to Identify Success Among Networks That Promote Active Living.

    Science.gov (United States)

    Litt, Jill; Varda, Danielle; Reed, Hannah; Retrum, Jessica; Tabak, Rachel; Gustat, Jeanette; O'Hara Tompkins, Nancy

    2015-11-01

    We evaluated organization- and network-level factors that influence organizations' perceived success. This is important for managing interorganizational networks, which can mobilize communities to address complex health issues such as physical activity, and for achieving change. In 2011, we used structured interview and network survey data from 22 states in the United States to estimate multilevel random-intercept models to understand organization- and network-level factors that explain perceived network success. A total of 53 of 59 "whole networks" met the criteria for inclusion in the analysis (89.8%). Coordinators identified 559 organizations, with 3 to 12 organizations from each network taking the online survey (response rate = 69.7%; range = 33%-100%). Occupying a leadership position (P Organizations' perceptions of success can influence decisions about continuing involvement and investment in networks designed to promote environment and policy change for active living. Understanding these factors can help leaders manage complex networks that involve diverse memberships, varied interests, and competing community-level priorities.

  13. The Political Activity in the Network Environment

    Directory of Open Access Journals (Sweden)

    Марианна Юрьевна Павлютенкова

    2015-12-01

    Full Text Available The rapid development and deep penetration into all areas of modern society of information and communication technologies significantly increase the role of network interactions. Network structures represented primarily social networks, embedded in the public policy process and became one of the key political actors. Online communities take the form of public policy, where the formation of public opinion and political decision-making plays the main role. Networking environment opens up new opportunities for the opposition and protest movements, civic participation, and control of public policy in general. The article gives an insight on the political aspects of social networking, concludes on the trend formation and network's strengthening of the political activity in a wide distribution of e-networking and e-communications.

  14. Levels, Linkages, and Networks in Cross-Cultural Innovation.

    Science.gov (United States)

    Kennedy, Judith; Kennedy, Chris

    1998-01-01

    Individuals belong to different cultural networks, and these networks and connections between them play an important role in success or failure of educational innovation and should be included in any model of the management or evaluation of innovation. Looks at functions of the different networks to which individuals belong at three levels,…

  15. A practical algorithm for reconstructing level-1 phylogenetic networks

    NARCIS (Netherlands)

    Huber, K.T.; Iersel, van L.J.J.; Kelk, S.M.; Suchecki, R.

    2011-01-01

    Recently, much attention has been devoted to the construction of phylogenetic networks which generalize phylogenetic trees in order to accommodate complex evolutionary processes. Here, we present an efficient, practical algorithm for reconstructing level-1 phylogenetic networks-a type of network

  16. 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 ...

  17. 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...

  18. Neural electrical activity and neural network growth.

    Science.gov (United States)

    Gafarov, F M

    2018-05-01

    The development of central and peripheral neural system depends in part on the emergence of the correct functional connectivity in its input and output pathways. Now it is generally accepted that molecular factors guide neurons to establish a primary scaffold that undergoes activity-dependent refinement for building a fully functional circuit. However, a number of experimental results obtained recently shows that the neuronal electrical activity plays an important role in the establishing of initial interneuronal connections. Nevertheless, these processes are rather difficult to study experimentally, due to the absence of theoretical description and quantitative parameters for estimation of the neuronal activity influence on growth in neural networks. In this work we propose a general framework for a theoretical description of the activity-dependent neural network growth. The theoretical description incorporates a closed-loop growth model in which the neural activity can affect neurite outgrowth, which in turn can affect neural activity. We carried out the detailed quantitative analysis of spatiotemporal activity patterns and studied the relationship between individual cells and the network as a whole to explore the relationship between developing connectivity and activity patterns. The model, developed in this work will allow us to develop new experimental techniques for studying and quantifying the influence of the neuronal activity on growth processes in neural networks and may lead to a novel techniques for constructing large-scale neural networks by self-organization. Copyright © 2018 Elsevier Ltd. All rights reserved.

  19. 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.

  20. A Cluster- Based Secure Active Network Environment

    Institute of Scientific and Technical Information of China (English)

    CHEN Xiao-lin; ZHOU Jing-yang; DAI Han; LU Sang-lu; CHEN Gui-hai

    2005-01-01

    We introduce a cluster-based secure active network environment (CSANE) which separates the processing of IP packets from that of active packets in active routers. In this environment, the active code authorized or trusted by privileged users is executed in the secure execution environment (EE) of the active router, while others are executed in the secure EE of the nodes in the distributed shared memory (DSM) cluster. With the supports of a multi-process Java virtual machine and KeyNote, untrusted active packets are controlled to securely consume resource. The DSM consistency management makes that active packets can be parallelly processed in the DSM cluster as if they were processed one by one in ANTS (Active Network Transport System). We demonstrate that CSANE has good security and scalability, but imposing little changes on traditional routers.

  1. Flexibility and Balancing in Active Distribution Networks

    DEFF Research Database (Denmark)

    Kordheili, Reza Ahmadi

    . Chapter 4 presents the details of the analysis, as well as the details of the MV network. To generalize the analysis, a standard MV network has been used for the studies. The MV network is also an active network, i.e. it involves MV wind turbines and decentralized combined heat and power (DCHP). DCHP...... units play an important role in Danish power system, and they contribute to electricity production as well. Modeling of wind turbines is done considering real data of a Vestas wind turbine. For wind speed, a modified wind speed model has been used for wind turbines, considering the available wind...... measurement. Also, a detailed model of DCHP units has been used in this thesis. Details of wind turbine model, as well as details of DCHP are presented in the thesis. The third objective of the research is to include the LV and MV networks in frequency response of the power system. Considering the increasing...

  2. Management of synchronized network activity by highly active neurons

    International Nuclear Information System (INIS)

    Shein, Mark; Raichman, Nadav; Ben-Jacob, Eshel; Volman, Vladislav; Hanein, Yael

    2008-01-01

    Increasing evidence supports the idea that spontaneous brain activity may have an important functional role. Cultured neuronal networks provide a suitable model system to search for the mechanisms by which neuronal spontaneous activity is maintained and regulated. This activity is marked by synchronized bursting events (SBEs)—short time windows (hundreds of milliseconds) of rapid neuronal firing separated by long quiescent periods (seconds). However, there exists a special subset of rapidly firing neurons whose activity also persists between SBEs. It has been proposed that these highly active (HA) neurons play an important role in the management (i.e. establishment, maintenance and regulation) of the synchronized network activity. Here, we studied the dynamical properties and the functional role of HA neurons in homogeneous and engineered networks, during early network development, upon recovery from chemical inhibition and in response to electrical stimulations. We found that their sequences of inter-spike intervals (ISI) exhibit long time correlations and a unimodal distribution. During the network's development and under intense inhibition, the observed activity follows a transition period during which mostly HA neurons are active. Studying networks with engineered geometry, we found that HA neurons are precursors (the first to fire) of the spontaneous SBEs and are more responsive to electrical stimulations

  3. Aberrant Network Activity in Schizophrenia.

    Science.gov (United States)

    Hunt, Mark J; Kopell, Nancy J; Traub, Roger D; Whittington, Miles A

    2017-06-01

    Brain dynamic changes associated with schizophrenia are largely equivocal, with interpretation complicated by many factors, such as the presence of therapeutic agents and the complex nature of the syndrome itself. Evidence for a brain-wide change in individual network oscillations, shared by all patients, is largely equivocal, but stronger for lower (delta) than for higher (gamma) bands. However, region-specific changes in rhythms across multiple, interdependent, nested frequencies may correlate better with pathology. Changes in synaptic excitation and inhibition in schizophrenia disrupt delta rhythm-mediated cortico-cortical communication, while enhancing thalamocortical communication in this frequency band. The contrasting relationships between delta and higher frequencies in thalamus and cortex generate frequency mismatches in inter-regional connectivity, leading to a disruption in temporal communication between higher-order brain regions associated with mental time travel. Copyright © 2017 Elsevier Ltd. All rights reserved.

  4. 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.

  5. Critical network effect induces business oscillations in multi-level marketing systems

    OpenAIRE

    Juanico, Dranreb Earl

    2012-01-01

    The "social-networking revolution" of late (e.g., with the advent of social media, Facebook, and the like) has been propelling the crusade to elucidate the embedded networks that underlie economic activity. An unexampled synthesis of network science and economics uncovers how the web of human interactions spurred by familiarity and similarity could potentially induce the ups and downs ever so common to our economy. Zeroing in on the million-strong global industry known as multi-level marketin...

  6. Adaptive intelligent power systems: Active distribution networks

    International Nuclear Information System (INIS)

    McDonald, Jim

    2008-01-01

    Electricity networks are extensive and well established. They form a key part of the infrastructure that supports industrialised society. These networks are moving from a period of stability to a time of potentially major transition, driven by a need for old equipment to be replaced, by government policy commitments to cleaner and renewable sources of electricity generation, and by change in the power industry. This paper looks at moves towards active distribution networks. The novel transmission and distribution systems of the future will challenge today's system designs. They will cope with variable voltages and frequencies, and will offer more flexible, sustainable options. Intelligent power networks will need innovation in several key areas of information technology. Active control of flexible, large-scale electrical power systems is required. Protection and control systems will have to react to faults and unusual transient behaviour and ensure recovery after such events. Real-time network simulation and performance analysis will be needed to provide decision support for system operators, and the inputs to energy and distribution management systems. Advanced sensors and measurement will be used to achieve higher degrees of network automation and better system control, while pervasive communications will allow networks to be reconfigured by intelligent systems

  7. Determining the confidence levels of sensor outputs using neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Broten, G S; Wood, H C [Saskatchewan Univ., Saskatoon, SK (Canada). Dept. of Electrical Engineering

    1996-12-31

    This paper describes an approach for determining the confidence level of a sensor output using multi-sensor arrays, sensor fusion and artificial neural networks. The authors have shown in previous work that sensor fusion and artificial neural networks can be used to learn the relationships between the outputs of an array of simulated partially selective sensors and the individual analyte concentrations in a mixture of analyses. Other researchers have shown that an array of partially selective sensors can be used to determine the individual gas concentrations in a gaseous mixture. The research reported in this paper shows that it is possible to extract confidence level information from an array of partially selective sensors using artificial neural networks. The confidence level of a sensor output is defined as a numeric value, ranging from 0% to 100%, that indicates the confidence associated with a output of a given sensor. A three layer back-propagation neural network was trained on a subset of the sensor confidence level space, and was tested for its ability to generalize, where the confidence level space is defined as all possible deviations from the correct sensor output. A learning rate of 0.1 was used and no momentum terms were used in the neural network. This research has shown that an artificial neural network can accurately estimate the confidence level of individual sensors in an array of partially selective sensors. This research has also shown that the neural network`s ability to determine the confidence level is influenced by the complexity of the sensor`s response and that the neural network is able to estimate the confidence levels even if more than one sensor is in error. The fundamentals behind this research could be applied to other configurations besides arrays of partially selective sensors, such as an array of sensors separated spatially. An example of such a configuration could be an array of temperature sensors in a tank that is not in

  8. A Practical Algorithm for Reconstructing Level-1 Phylogenetic Networks

    NARCIS (Netherlands)

    K.T. Huber; L.J.J. van Iersel (Leo); S.M. Kelk (Steven); R. Suchecki

    2010-01-01

    htmlabstractRecently much attention has been devoted to the construction of phylogenetic networks which generalize phylogenetic trees in order to accommodate complex evolutionary processes. Here we present an efficient, practical algorithm for reconstructing level-1 phylogenetic networks - a type of

  9. 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.

  10. The level of youth activism

    OpenAIRE

    Borojević, Tatjana; Vuk, Drago; Petrović, Nataša; Slović, Dragoslav

    2017-01-01

    During the period from 2007 to 2014, and in addition to huge institutional changes, large steps were taken in the field of youth policy in the Republic of Serbia in order to create national resources which would have influence on the improvement of the youth status and life. On the other hand, the practice shows that the existence of the national framework for youth support, as a local service network intended for youths, is not a crucial prerequisite to change the current situation when it c...

  11. System-level Modeling of Wireless Integrated Sensor Networks

    DEFF Research Database (Denmark)

    Virk, Kashif M.; Hansen, Knud; Madsen, Jan

    2005-01-01

    Wireless integrated sensor networks have emerged as a promising infrastructure for a new generation of monitoring and tracking applications. In order to efficiently utilize the extremely limited resources of wireless sensor nodes, accurate modeling of the key aspects of wireless sensor networks...... is necessary so that system-level design decisions can be made about the hardware and the software (applications and real-time operating system) architecture of sensor nodes. In this paper, we present a SystemC-based abstract modeling framework that enables system-level modeling of sensor network behavior...... by modeling the applications, real-time operating system, sensors, processor, and radio transceiver at the sensor node level and environmental phenomena, including radio signal propagation, at the sensor network level. We demonstrate the potential of our modeling framework by simulating and analyzing a small...

  12. 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.

  13. 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...... Networks also would be too large. In this paper an adaptive aggregation method for subsystems with power electronic interfaced generators and voltage dependant loads is proposed. With this tool may be relatively easier including distribution networks into security assessment. The method is validated...... 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....

  14. Enhancement of the FDOT's project level and network level bridge management analysis tools

    Science.gov (United States)

    2011-02-01

    Over several years, the Florida Department of Transportation (FDOT) has been implementing the AASHTO Pontis Bridge Management System to support network-level and project-level decision making in the headquarters and district offices. Pontis is an int...

  15. The Unified Levelling Network of Sarawak and its Adjustment

    Science.gov (United States)

    Som, Z. A. M.; Yazid, A. M.; Ming, T. K.; Yazid, N. M.

    2016-09-01

    The height reference network of Sarawak has seen major improvement in over the past two decades. The most significant improvement was the establishment of extended precise leveling network of which is now able to connect all three major datum points at Pulau Lakei, Original and Bintulu. Datum by following the major accessible routes across Sarawak. This means the leveling network in Sarawak has now been inter-connected and unified. By having such a unified network leads to the possibility of having a common single least squares adjustment been performed for the first time. The least squares adjustment of this unified levelling network was attempted in order to compute the height of all Bench Marks established in the entire levelling network. The adjustment was done by using MoreFix levelling adjustment package developed at FGHT UTM. The computational procedure adopted is linear parametric adjustment by minimum constraint. Since Sarawak has three separate datums therefore three separate adjustments were implemented by utilizing datum at Pulau Lakei, Original Miri and Bintulu Datum respectively. Results of the MoreFix unified adjustment agreed very well with adjustment repeated using Starnet. Further the results were compared with solution given by Jupem and they are in good agreement as well. The difference in height analysed were within 10mm for the case of minimum constraint at Pulau Lakei datum and with much better agreement in the case of Original Miri Datum.

  16. THE UNIFIED LEVELLING NETWORK OF SARAWAK AND ITS ADJUSTMENT

    Directory of Open Access Journals (Sweden)

    Z. A. M. Som

    2016-09-01

    Full Text Available The height reference network of Sarawak has seen major improvement in over the past two decades. The most significant improvement was the establishment of extended precise leveling network of which is now able to connect all three major datum points at Pulau Lakei, Original and Bintulu. Datum by following the major accessible routes across Sarawak. This means the leveling network in Sarawak has now been inter-connected and unified. By having such a unified network leads to the possibility of having a common single least squares adjustment been performed for the first time. The least squares adjustment of this unified levelling network was attempted in order to compute the height of all Bench Marks established in the entire levelling network. The adjustment was done by using MoreFix levelling adjustment package developed at FGHT UTM. The computational procedure adopted is linear parametric adjustment by minimum constraint. Since Sarawak has three separate datums therefore three separate adjustments were implemented by utilizing datum at Pulau Lakei, Original Miri and Bintulu Datum respectively. Results of the MoreFix unified adjustment agreed very well with adjustment repeated using Starnet. Further the results were compared with solution given by Jupem and they are in good agreement as well. The difference in height analysed were within 10mm for the case of minimum constraint at Pulau Lakei datum and with much better agreement in the case of Original Miri Datum.

  17. Network feedback regulates motor output across a range of modulatory neuron activity.

    Science.gov (United States)

    Spencer, Robert M; Blitz, Dawn M

    2016-06-01

    Modulatory projection neurons alter network neuron synaptic and intrinsic properties to elicit multiple different outputs. Sensory and other inputs elicit a range of modulatory neuron activity that is further shaped by network feedback, yet little is known regarding how the impact of network feedback on modulatory neurons regulates network output across a physiological range of modulatory neuron activity. Identified network neurons, a fully described connectome, and a well-characterized, identified modulatory projection neuron enabled us to address this issue in the crab (Cancer borealis) stomatogastric nervous system. The modulatory neuron modulatory commissural neuron 1 (MCN1) activates and modulates two networks that generate rhythms via different cellular mechanisms and at distinct frequencies. MCN1 is activated at rates of 5-35 Hz in vivo and in vitro. Additionally, network feedback elicits MCN1 activity time-locked to motor activity. We asked how network activation, rhythm speed, and neuron activity levels are regulated by the presence or absence of network feedback across a physiological range of MCN1 activity rates. There were both similarities and differences in responses of the two networks to MCN1 activity. Many parameters in both networks were sensitive to network feedback effects on MCN1 activity. However, for most parameters, MCN1 activity rate did not determine the extent to which network output was altered by the addition of network feedback. These data demonstrate that the influence of network feedback on modulatory neuron activity is an important determinant of network output and feedback can be effective in shaping network output regardless of the extent of network modulation. Copyright © 2016 the American Physiological Society.

  18. Italian retail gasoline activities: inadequate distribution network

    International Nuclear Information System (INIS)

    Verde, Stefano

    2005-01-01

    It is common belief that competition in the Italian retail gasoline activities is hindered by oil companies' collusive behaviour. However, when developing a broader analysis of the sector, low efficiency and scarce competition could results as the consequences coming from an inadequate distribution network and from the recognition of international markets and focal point [it

  19. 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

  20. Alumni Activities : International Alumni Network for TUAS

    OpenAIRE

    Saarinen, Riikka-Maria

    2013-01-01

    Turku University of Applied Sciences is currently planning on creating an International Alumni Network for the former exchange students who had their exchange period at TUAS. In this thesis, alumni functions are divided into three sections, i.e. the purpose of the alumni, the activities of the alumni and the management of the communication of the alumni. The research of the alumni functions was conducted by introduction of alumni activities in general and introducing three examples of Amer...

  1. Distributed applications monitoring at system and network level

    CERN Document Server

    Aderholz, Michael; Augé, E; Bagliesi, G; Banistoni, G; Barone, L; Boschini, M; Brunengo, A; Bunn, J J; Butler, J; Campanella, M; Capiluppi, P; D'Amato, M; Darneri, M; Di Mattia, A; Dorokhov, A E; Gagliardi, F; Gaines, I; Gasparini, U; Ghiselli, A; Gordon, J; Grandi, C; Gálvez, P; Harris, F; Holtman, K; Karimäki, V; Karita, Y; Klem, J T; Legrand, I; Leltchouk, M; Linglin, D; Lubrano, P; Luminari, L; McArthur, I C; Michelotto, M; Morita, Y; Nazarenko, A; Newman, H; O'Dell, Vivian; O'Neale, S W; Osculati, B; Pepé, M; Perini, L; Pinfold, James L; Pordes, R; Prelz, F; Putzer, A; Resconi, S; Robertson, L; Rolli, S; Sasaki, T; Sato, H; Schaffer, R D; Schalk, T L; Servoli, L; Sgaravatto, M; Shiers, J; Silvestris, L; Siroli, G P; Sliwa, K; Smith, T; Somigliana, R; Stanescu, C; Stockinger, H E; Ugolotti, D; Valente, E; Vistoli, C; Wilkinson, R P; Willers, Ian Malcolm; Williams, D O

    2001-01-01

    Most distributed applications are based on architectural models that do not involve real-time knowledge of network status and of their network usage. Moreover the new "network aware" architectures are still under development and their design is not yet complete. We considered, as a use case, an application using ODBMS (Objectivity /DB) for the distributed analysis of experimental data. The dynamic usage of system and network resources at host and application levels has been measured in different client/server configurations, and on several LAN and WAN layouts. The aim was to study the application efficiency and behavior versus the network characteristics and conditions. The most interesting results of the LAN and WAN tests are described. System bottlenecks and limitations have been identified, and efficient working conditions in the different scenarios have been defined. The behavior observed when moving away from the optimal working conditions is also described.

  2. BRAIN NETWORKS. Correlated gene expression supports synchronous activity in brain networks.

    Science.gov (United States)

    Richiardi, Jonas; Altmann, Andre; Milazzo, Anna-Clare; Chang, Catie; Chakravarty, M Mallar; Banaschewski, Tobias; Barker, Gareth J; Bokde, Arun L W; Bromberg, Uli; Büchel, Christian; Conrod, Patricia; Fauth-Bühler, Mira; Flor, Herta; Frouin, Vincent; Gallinat, Jürgen; Garavan, Hugh; Gowland, Penny; Heinz, Andreas; Lemaître, Hervé; Mann, Karl F; Martinot, Jean-Luc; Nees, Frauke; Paus, Tomáš; Pausova, Zdenka; Rietschel, Marcella; Robbins, Trevor W; Smolka, Michael N; Spanagel, Rainer; Ströhle, Andreas; Schumann, Gunter; Hawrylycz, Mike; Poline, Jean-Baptiste; Greicius, Michael D

    2015-06-12

    During rest, brain activity is synchronized between different regions widely distributed throughout the brain, forming functional networks. However, the molecular mechanisms supporting functional connectivity remain undefined. We show that functional brain networks defined with resting-state functional magnetic resonance imaging can be recapitulated by using measures of correlated gene expression in a post mortem brain tissue data set. The set of 136 genes we identify is significantly enriched for ion channels. Polymorphisms in this set of genes significantly affect resting-state functional connectivity in a large sample of healthy adolescents. Expression levels of these genes are also significantly associated with axonal connectivity in the mouse. The results provide convergent, multimodal evidence that resting-state functional networks correlate with the orchestrated activity of dozens of genes linked to ion channel activity and synaptic function. Copyright © 2015, American Association for the Advancement of Science.

  3. [Establishment of regional active neonatal transport network].

    Science.gov (United States)

    Kong, Xiang-yong; Gao, Xin; Yin, Xiao-juan; Hong, Xiao-yang; Fang, Huan-sheng; Wang, Zi-zhen; Li, Ai-hua; Luo, Fen-ping; Feng, Zhi-chun

    2010-01-01

    To evaluate the clinical function and significance of establishing a regional active neonatal transport network (ANTN) in Beijing. The authors retrospectively studied intensive care and the role of ANTN system in management of critically ill neonates and compared the outcome of newborn infants transported to our NICU before and after we established standardized NICU and ANTN system (phase 1: July 2004 to June 2006 vs phase 2: July 2006 to May 2008). The number of neonatal transport significantly increased from 587 during phase 1 to 2797 during phase 2. Success rate of transport and the total cure rate in phase 2 were 97.85% and 91.99% respectively, which were significantly higher than those in phase 1 (94.36% and 88.69%, respectively, P capacity of our NICU was enlarged following the development of ANTN. There are 200 beds for level 3 infants in phase 2, but there were only 20 beds in phase 1. Significantly less patients in the phase 2 had hypothermia, acidosis and the blood glucose instability than those in phase 1 (P transported to our NICU were higher in phase 2 compared with that in phase 1, especially infants whose gestational age was below 32 weeks. The proportions of asphyxia and respiratory distress syndrome were lower in phase 2 than that in phase 1, but the total cure rates of these two diseases had no significant changes between the two phases. The most important finding was that the improvement of outcome of premature infants and those with asphyxia and aspiration syndrome was noted following the development of ANTN. Establishing regional ANTN for a tertiary hospital is very important to elevate the total level in management of critically ill newborn infants. It plays a very important role in reducing mortality and improving total outcomes of newborn infants. There are still some problems remained to solve after four years practice in order to optimize the ANTN to meet needs of the development of neonatology.

  4. A distributed lumped active all-pass network configuration.

    Science.gov (United States)

    Huelsman, L. P.; Raghunath, S.

    1972-01-01

    In this correspondence a new and interesting distributed lumped active network configuration that realizes an all-pass network function is described. A design chart for determining the values of the network elements is included.

  5. Regulatory networks, legal federalism, and multi-level regulatory systems

    OpenAIRE

    Kerber, Wolfgang; Wendel, Julia

    2016-01-01

    Transnational regulatory networks play important roles in multi-level regulatory regimes, as e.g, the European Union. In this paper we analyze the role of regulatory networks from the perspective of the economic theory of legal federalism. Often sophisticated intermediate institutional solutions between pure centralisation and pure decentralisation can help to solve complex tradeoff problems between the benefits and problems of centralised and decentralised solutions. Drawing upon the insight...

  6. Combining region- and network-level brain-behavior relationships in a structural equation model.

    Science.gov (United States)

    Bolt, Taylor; Prince, Emily B; Nomi, Jason S; Messinger, Daniel; Llabre, Maria M; Uddin, Lucina Q

    2018-01-15

    Brain-behavior associations in fMRI studies are typically restricted to a single level of analysis: either a circumscribed brain region-of-interest (ROI) or a larger network of brain regions. However, this common practice may not always account for the interdependencies among ROIs of the same network or potentially unique information at the ROI-level, respectively. To account for both sources of information, we combined measurement and structural components of structural equation modeling (SEM) approaches to empirically derive networks from ROI activity, and to assess the association of both individual ROIs and their respective whole-brain activation networks with task performance using three large task-fMRI datasets and two separate brain parcellation schemes. The results for working memory and relational tasks revealed that well-known ROI-performance associations are either non-significant or reversed when accounting for the ROI's common association with its corresponding network, and that the network as a whole is instead robustly associated with task performance. The results for the arithmetic task revealed that in certain cases, an ROI can be robustly associated with task performance, even when accounting for its associated network. The SEM framework described in this study provides researchers additional flexibility in testing brain-behavior relationships, as well as a principled way to combine ROI- and network-levels of analysis. Copyright © 2017 Elsevier Inc. All rights reserved.

  7. Interaction Networks: Generating High Level Hints Based on Network Community Clustering

    Science.gov (United States)

    Eagle, Michael; Johnson, Matthew; Barnes, Tiffany

    2012-01-01

    We introduce a novel data structure, the Interaction Network, for representing interaction-data from open problem solving environment tutors. We show how using network community detecting techniques are used to identify sub-goals in problems in a logic tutor. We then use those community structures to generate high level hints between sub-goals.…

  8. Birth Order and Activity Level in Children.

    Science.gov (United States)

    Eaton, Warren O.; And Others

    1989-01-01

    Studied 7,018 children between birth and 7 years and 81 children of 5-8 years to test the hypothesis that birth order is negatively related to motor activity level. Activity level declined linearly across birth position, so that early-borns were rated as more active than later-borns. (RJC)

  9. 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...

  10. Determining the confidence levels of sensor outputs using neural networks

    International Nuclear Information System (INIS)

    Broten, G.S.; Wood, H.C.

    1995-01-01

    This paper describes an approach for determining the confidence level of a sensor output using multi-sensor arrays, sensor fusion and artificial neural networks. The authors have shown in previous work that sensor fusion and artificial neural networks can be used to learn the relationships between the outputs of an array of simulated partially selective sensors and the individual analyte concentrations in a mixture of analyses. Other researchers have shown that an array of partially selective sensors can be used to determine the individual gas concentrations in a gaseous mixture. The research reported in this paper shows that it is possible to extract confidence level information from an array of partially selective sensors using artificial neural networks. The confidence level of a sensor output is defined as a numeric value, ranging from 0% to 100%, that indicates the confidence associated with a output of a given sensor. A three layer back-propagation neural network was trained on a subset of the sensor confidence level space, and was tested for its ability to generalize, where the confidence level space is defined as all possible deviations from the correct sensor output. A learning rate of 0.1 was used and no momentum terms were used in the neural network. This research has shown that an artificial neural network can accurately estimate the confidence level of individual sensors in an array of partially selective sensors. This research has also shown that the neural network's ability to determine the confidence level is influenced by the complexity of the sensor's response and that the neural network is able to estimate the confidence levels even if more than one sensor is in error. The fundamentals behind this research could be applied to other configurations besides arrays of partially selective sensors, such as an array of sensors separated spatially. An example of such a configuration could be an array of temperature sensors in a tank that is not in

  11. A Network Perspective on Individual-Level Ambidexterity in Organizations

    DEFF Research Database (Denmark)

    Rogan, Michelle; Mors, Marie Louise

    2014-01-01

    in the internal and external networks of 79 senior managers in a management consulting firm revealed significant differences in the density, contact heterogeneity, and informality of ties in the networks of senior managers who engaged in both exploration and exploitation compared with managers that predominately......Addressing the call for a deeper understanding of ambidexterity at the individual level, we propose that managers’ networks are an important yet understudied factor in the ability to balance the trade-off between exploring for new business and exploiting existing business. Analyses of 1,449 ties...... explored or exploited. The findings suggest that managers’ networks are important levers for their ability to behave ambidextrously and offer insights into the microfoundations of organizational ambidexterity....

  12. Activity Level Change Detection for Persistent Surveillance

    National Research Council Canada - National Science Library

    Liu, F; Bush, L. A

    2004-01-01

    .... Instead of traditional target tracking, this approach utilizes GMTI data as moving spots on the ground to estimate the level of activities and detect unusual activities such as military deployments...

  13. Achieving Network Level Privacy in Wireless Sensor Networks†

    Science.gov (United States)

    Shaikh, Riaz Ahmed; Jameel, Hassan; d’Auriol, Brian J.; Lee, Heejo; Lee, Sungyoung; Song, Young-Jae

    2010-01-01

    Full network level privacy has often been categorized into four sub-categories: Identity, Route, Location and Data privacy. Achieving full network level privacy is a critical and challenging problem due to the constraints imposed by the sensor nodes (e.g., energy, memory and computation power), sensor networks (e.g., mobility and topology) and QoS issues (e.g., packet reach-ability and timeliness). In this paper, we proposed two new identity, route and location privacy algorithms and data privacy mechanism that addresses this problem. The proposed solutions provide additional trustworthiness and reliability at modest cost of memory and energy. Also, we proved that our proposed solutions provide protection against various privacy disclosure attacks, such as eavesdropping and hop-by-hop trace back attacks. PMID:22294881

  14. Network Physics anounces first product to provide business-level management of the most complex and dynamic networks

    CERN Multimedia

    2003-01-01

    Network Physics, provider of business-level, traffic flow-based network management solutions, today announced the introduction of the Network Physics NP/BizFlow-1000. With the NP/BizFlow-1000, Fortune 1000 companies with complex and dynamic networks can analyze the flows that link business groups, critical applications, and network software and hardware (1 page).

  15. Associating at the European Level: Civil Society Networks in Brussels

    NARCIS (Netherlands)

    Brandsen, T.; Sittermann, B.; Freise, M.; Hallmann, T.

    2014-01-01

    This chapter examines the position of the third sector at the European level, where it has slowly been building a presence. Although great advances have been made, especially from the 1990s onwards, and the sector’s European networks are much stronger than before, it remains institutionally weak and

  16. The Dynamics of network and dyad level supply management

    DEFF Research Database (Denmark)

    Ellegaard, Chris

    -supplier relation and its immediate network context, are presented. In analysing the data, the dynamic interdependency between management of one level and management of the other, will be demonstrated. The analysis reveals a need for an alternating approach to supply management, which takes the dynamic complexity...

  17. State-dependent, bidirectional modulation of neural network activity by endocannabinoids.

    Science.gov (United States)

    Piet, Richard; Garenne, André; Farrugia, Fanny; Le Masson, Gwendal; Marsicano, Giovanni; Chavis, Pascale; Manzoni, Olivier J

    2011-11-16

    The endocannabinoid (eCB) system and the cannabinoid CB1 receptor (CB1R) play key roles in the modulation of brain functions. Although actions of eCBs and CB1Rs are well described at the synaptic level, little is known of their modulation of neural activity at the network level. Using microelectrode arrays, we have examined the role of CB1R activation in the modulation of the electrical activity of rat and mice cortical neural networks in vitro. We find that exogenous activation of CB1Rs expressed on glutamatergic neurons decreases the spontaneous activity of cortical neural networks. Moreover, we observe that the net effect of the CB1R antagonist AM251 inversely correlates with the initial level of activity in the network: blocking CB1Rs increases network activity when basal network activity is low, whereas it depresses spontaneous activity when its initial level is high. Our results reveal a complex role of CB1Rs in shaping spontaneous network activity, and suggest that the outcome of endogenous neuromodulation on network function might be state dependent.

  18. 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.

  19. Mean-field level analysis of epidemics in directed networks

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Jiazeng [School of Mathematical Sciences, Peking University, Beijing 100871 (China); Liu, Zengrong [Mathematics Department, Shanghai University, Shanghai 200444 (China)], E-mail: wangjiazen@yahoo.com.cn, E-mail: zrongliu@online.sh.cn

    2009-09-04

    The susceptible-infected-removed spreading model in a directed graph is studied. The mean-field level rate equations are built with the degree-degree connectivity correlation element and the (in, out)-degree distribution. And the outbreak threshold is obtained analytically-it is determined by the combination of connectivity probability and the degree distribution. Furthermore, the methods of calculating the degree-degree correlations in directed networks are presented. The numerical results of the discrete epidemic processes in networks verify our analyses.

  20. Mean-field level analysis of epidemics in directed networks

    International Nuclear Information System (INIS)

    Wang, Jiazeng; Liu, Zengrong

    2009-01-01

    The susceptible-infected-removed spreading model in a directed graph is studied. The mean-field level rate equations are built with the degree-degree connectivity correlation element and the (in, out)-degree distribution. And the outbreak threshold is obtained analytically-it is determined by the combination of connectivity probability and the degree distribution. Furthermore, the methods of calculating the degree-degree correlations in directed networks are presented. The numerical results of the discrete epidemic processes in networks verify our analyses.

  1. Spontaneous brain network activity: Analysis of its temporal complexity

    Directory of Open Access Journals (Sweden)

    Mangor Pedersen

    2017-06-01

    Full Text Available The brain operates in a complex way. The temporal complexity underlying macroscopic and spontaneous brain network activity is still to be understood. In this study, we explored the brain’s complexity by combining functional connectivity, graph theory, and entropy analyses in 25 healthy people using task-free functional magnetic resonance imaging. We calculated the pairwise instantaneous phase synchrony between 8,192 brain nodes for a total of 200 time points. This resulted in graphs for which time series of clustering coefficients (the “cliquiness” of a node and participation coefficients (the between-module connectivity of a node were estimated. For these two network metrics, sample entropy was calculated. The procedure produced a number of results: (1 Entropy is higher for the participation coefficient than for the clustering coefficient. (2 The average clustering coefficient is negatively related to its associated entropy, whereas the average participation coefficient is positively related to its associated entropy. (3 The level of entropy is network-specific to the participation coefficient, but not to the clustering coefficient. High entropy for the participation coefficient was observed in the default-mode, visual, and motor networks. These results were further validated using an independent replication dataset. Our work confirms that brain networks are temporally complex. Entropy is a good candidate metric to explore temporal network alterations in diseases with paroxysmal brain disruptions, including schizophrenia and epilepsy. In recent years, connectomics has provided significant insights into the topological complexity of brain networks. However, the temporal complexity of brain networks still remains somewhat poorly understood. In this study we used entropy analysis to demonstrate that the properties of network segregation (the clustering coefficient and integration (the participation coefficient are temporally complex

  2. 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.

  3. Controlling Voltage Levels of Distribution Network-Radial Feeder after Connecting Wind Turbines to the Network

    Directory of Open Access Journals (Sweden)

    Muhammad Al Badri

    2017-11-01

    Full Text Available Several factors in power generation and supply need to be taken into account such as shortages of energy supply, system stability, and energy quality and system disruption due to network losses, industrial development and population expansion. The addition of wind turbines to the distribution network is of great benefit in providing additional power and solving these problems, but this addition is accompanied by the problem of low voltage network. This research found optimal solutions to the problem of low voltage distribution network after connecting wind turbines. The main idea of this paper is to optimize the low-voltage problem as a result of connecting the wind turbines to the "far end" of the radial feeder for a distribution network and to obtain a voltage level within an acceptable and stable range. The problem of low voltage solved by using the load-drop compensation, capacitor-bank and “doubly-fed” induction generators. The results of this study were based on the operation of the entire design of the simulation system which would be compatible with the reality of the energy flow of all network components by using the PSCAD program. The present analysis program revealed an optimum solution for the low voltage profile of the distribution network after connecting the wind turbine.

  4. 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.

  5. 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...

  6. Teacher Candidates' Opinions Regarding Instructional and Safe Use of Social Networks and Internet Addiction Risk Levels

    Directory of Open Access Journals (Sweden)

    Enis Fasli

    2018-05-01

    Full Text Available In conjunction with the development and advancement of internet technologies, social networking sites have created a socialization environment. Instructors point out that these tools must be used as an active and different form of communication with students. Also, participation of the students through social networking sites should be encouraged. However, the risk of internet addiction has also become widespread on the increase use of social networks. The aim of this research is to “determine the opinions of teacher candidates on the use of social networking sites in education and Internet addiction risk levels”. General survey model was used in this research in order to determine the opinions regarding social networks of teacher candidates from the education faculties in the Turkish Republic of Northern Cyprus and figure out their internet addiction risk levels. “Use of Social Networks in Education Scale” developed by Ozturk and Akgun and “Internet Addiction Test” developed by Young were used in this research. According to the results of the study, it has been figured out that almost all of the teacher candidates think that sharing information through social networking sites is either partially safe or not safe. Besides, most of the teacher candidates feel anxious about keeping information as confidential. Another important result is that teacher candidates are internet users at an average level. It also shows that they might spend too much time on the internet however they use internet in a controlled manner.

  7. Network governance of active employment policy

    DEFF Research Database (Denmark)

    Damgaard, Bodil; Torfing, Jacob

    2010-01-01

    The recent reform of the Danish governance system in the field of active employment policy has been subject to fierce criticism, as many commentators fear that it is the beginning of the end of the Danish Model of active stakeholder involvement. Drawing on both quantitative and qualitative data, ......, the tight metagovernance of the LECs does not seem to straightjacket the LECs as there is a considerable scope for local policy making which makes it worthwhile for the social partners to participate in the local networks.......The recent reform of the Danish governance system in the field of active employment policy has been subject to fierce criticism, as many commentators fear that it is the beginning of the end of the Danish Model of active stakeholder involvement. Drawing on both quantitative and qualitative data......, this study aims to analyse the impact of the governance reform by assessing the initial experiences with the Local Employment Councils (LECs). The analysis shows that the LECs are relatively well-functioning and contribute to an effective and democratic governance of local employment policy. Furthermore...

  8. Gap Filling of Daily Sea Levels by Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Lyubka Pashova

    2013-06-01

    Full Text Available In the recent years, intelligent methods as artificial neural networks are successfully applied for data analysis from different fields of the geosciences. One of the encountered practical problems is the availability of gaps in the time series that prevent their comprehensive usage for the scientific and practical purposes. The article briefly describes two types of the artificial neural network (ANN architectures - Feed-Forward Backpropagation (FFBP and recurrent Echo state network (ESN. In some cases, the ANN can be used as an alternative on the traditional methods, to fill in missing values in the time series. We have been conducted several experiments to fill the missing values of daily sea levels spanning a 5-years period using both ANN architectures. A multiple linear regression for the same purpose has been also applied. The sea level data are derived from the records of the tide gauge Burgas, which is located on the western Black Sea coast. The achieved results have shown that the performance of ANN models is better than that of the classical one and they are very promising for the real-time interpolation of missing data in the time series.

  9. Multi-level deep supervised networks for retinal vessel segmentation.

    Science.gov (United States)

    Mo, Juan; Zhang, Lei

    2017-12-01

    Changes in the appearance of retinal blood vessels are an important indicator for various ophthalmologic and cardiovascular diseases, including diabetes, hypertension, arteriosclerosis, and choroidal neovascularization. Vessel segmentation from retinal images is very challenging because of low blood vessel contrast, intricate vessel topology, and the presence of pathologies such as microaneurysms and hemorrhages. To overcome these challenges, we propose a neural network-based method for vessel segmentation. A deep supervised fully convolutional network is developed by leveraging multi-level hierarchical features of the deep networks. To improve the discriminative capability of features in lower layers of the deep network and guide the gradient back propagation to overcome gradient vanishing, deep supervision with auxiliary classifiers is incorporated in some intermediate layers of the network. Moreover, the transferred knowledge learned from other domains is used to alleviate the issue of insufficient medical training data. The proposed approach does not rely on hand-crafted features and needs no problem-specific preprocessing or postprocessing, which reduces the impact of subjective factors. We evaluate the proposed method on three publicly available databases, the DRIVE, STARE, and CHASE_DB1 databases. Extensive experiments demonstrate that our approach achieves better or comparable performance to state-of-the-art methods with a much faster processing speed, making it suitable for real-world clinical applications. The results of cross-training experiments demonstrate its robustness with respect to the training set. The proposed approach segments retinal vessels accurately with a much faster processing speed and can be easily applied to other biomedical segmentation tasks.

  10. 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.

  11. Active Traffic Capture for Network Forensics

    Science.gov (United States)

    Slaviero, Marco; Granova, Anna; Olivier, Martin

    Network traffic capture is an integral part of network forensics, but current traffic capture techniques are typically passive in nature. Under heavy loads, it is possible for a sniffer to miss packets, which affects the quality of forensic evidence.

  12. Default activity patterns at the neocortical microcircuit level

    Directory of Open Access Journals (Sweden)

    Artur eLuczak

    2012-06-01

    Full Text Available Even in absence of sensory stimuli cortical networks exhibit complex, self-organized activity patterns. While the function of those spontaneous patterns of activation remains poorly understood, recent studies both in vivo and in vitro have demonstrated that neocortical neurons activate in a surprisingly similar sequential order both spontaneously and following input into cortex. For example, neurons that tend to fire earlier within spontaneous bursts of activity also fire earlier than other neurons in response to sensory stimuli. These 'default patterns' can last hundreds of milliseconds and are strongly conserved under a variety of conditions. In this paper we will review recent evidence for these default patterns at the local cortical level. We speculate that cortical architecture imposes common constraints on spontaneous and evoked activity flow, which result in the similarity of the patterns.

  13. Prediction of SO{sub 2} levels using neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Belen M. Fernandez de Castro; Jose Manuel Prada Sanchez; Wenceslao Gonzalez Manteiga [and others] [University of Santiago de Compostela, Santiago (Spain). Department of Statistics and Operations Research, Faculty of Mathematics

    2003-05-01

    The paper presents an adaptation of the air pollution control help system in the neighbourhood of a coal-fired power plant in As Pontes (A Coruna, Spain), property of Endesa Generacion S.A., to the European Council Directive 1999/30/CE. This system contains a statistical prediction made half an hour before the measurement, and it helps the staff in the power plant prevent air quality level episodes. The prediction is made using neural network models. This prediction is compared with one made by a semiparametric model. 11 refs., 6 figs., 4 tabs.

  14. Technical and economic impacts of active management on distribution network

    International Nuclear Information System (INIS)

    Zhang, Jietan; Cheng, Haozhong; Wang, Chun

    2009-01-01

    With the deregulation of energy market and the appeal for environment protection, more and more distributed generation (DG) is embedded in the distribution network. However the approach of connecting DG in most cases is based on a so-called ''fit and forget'' policy and the capacity of DG is limited rigidly by distribution network operator (DNO) to avoid the negative effects of high level penetration. Therefore active management (AM) is put forward as an effective method to network reinforcement for the connection and operation of DG. In this paper, the concept and principle of AM are introduced, and several indices are proposed to evaluate both technical and economic impacts of AM on distribution network with DG. To simplify the simulation fuzzy C-means clustering (FCM) algorithm is introduced. The test results on a sample system represent that AM will lead to decrease of power generation of DG, but it can reduce energy losses and improve voltage profile effectively. Furthermore, AM will take great economic incentives to DG developer as well as DNO with reasonable policy. (author)

  15. A new chaotic Hopfield network with piecewise linear activation function

    International Nuclear Information System (INIS)

    Peng-Sheng, Zheng; Wan-Sheng, Tang; Jian-Xiong, Zhang

    2010-01-01

    This paper presents a new chaotic Hopfield network with a piecewise linear activation function. The dynamic of the network is studied by virtue of the bifurcation diagram, Lyapunov exponents spectrum and power spectrum. Numerical simulations show that the network displays chaotic behaviours for some well selected parameters

  16. PersonA: Persuasive social network for physical Activity.

    Science.gov (United States)

    Ayubi, Soleh U; Parmanto, Bambang

    2012-01-01

    Advances in physical activity (PA) monitoring devices provide ample opportunities for innovations in the way the information produced by these devices is used to encourage people to have more active lifestyles. One such innovation is expanding the current use of the information from self-management to social support. We developed a Persuasive social network for physical Activity (PersonA) that combines automatic input of physical activity data, a smartphone, and a social networking system (SNS). This paper describes the motivation for and overarching design of the PersonA and its functional and non-functional features. PersonA is designed to intelligently and automatically receive raw PA data from the sensors in the smartphone, calculate the data into meaningful PA information, store the information on a secure server, and show the information to the users as persuasive and real-time feedbacks or publish the information to the SNS to generate social support. The implementation of self-monitoring, social support, and persuasive concepts using currently available technologies has the potential for promoting healthy lifestyle, greater community participation, and higher quality of life. We also expect that PersonA will enable health professionals to collect in situ data related to physical activity. The platform is currently being used and tested to improve PA level of three groups of users in Pittsburgh, PA, USA.

  17. Convolutional Neural Networks for Text Categorization: Shallow Word-level vs. Deep Character-level

    OpenAIRE

    Johnson, Rie; Zhang, Tong

    2016-01-01

    This paper reports the performances of shallow word-level convolutional neural networks (CNN), our earlier work (2015), on the eight datasets with relatively large training data that were used for testing the very deep character-level CNN in Conneau et al. (2016). Our findings are as follows. The shallow word-level CNNs achieve better error rates than the error rates reported in Conneau et al., though the results should be interpreted with some consideration due to the unique pre-processing o...

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

    Science.gov (United States)

    2014-06-01

    networking (SDN) paradigm, which has gained popularity in recent years, has its roots in the idea of programmable networks [6]. By extending the...278–289, Aug. 2011. 67 [13] M. Hicks, P. Kakkar, J. T. Moore, C. A. Gunter, and S. Nettles , “Plan: A programming language for active networks,” ACM

  19. Actively shielded low level gamma - spectrometric system

    International Nuclear Information System (INIS)

    Mrdja, D.; Bikit, I.; Forkapic, S.; Slivka, J.; Veskovic, M.

    2005-01-01

    The results of the adjusting and testing of the actively shielded low level gamma-spectrometry system are presented. The veto action of the shield reduces the background in the energy region of 50 keV to the 2800 keV for about 3 times. (author) [sr

  20. Physical activity level among undergraduate students in ...

    African Journals Online (AJOL)

    Physical activity level among undergraduate students in Terengganu, Malaysia using pedometer. N.A.M. Yusoff, S Ganeson, K.F. Ismail, H Juahir, M.R. Shahril, L.P. Lin, A Ahmad, S.W. Wafa, S Harith, R Rajikan ...

  1. Infraslow Electroencephalographic and Dynamic Resting State Network Activity.

    Science.gov (United States)

    Grooms, Joshua K; Thompson, Garth J; Pan, Wen-Ju; Billings, Jacob; Schumacher, Eric H; Epstein, Charles M; Keilholz, Shella D

    2017-06-01

    A number of studies have linked the blood oxygenation level dependent (BOLD) signal to electroencephalographic (EEG) signals in traditional frequency bands (δ, θ, α, β, and γ), but the relationship between BOLD and its direct frequency correlates in the infraslow band (resting state magnetic resonance imaging data were acquired simultaneously. The DC EEG signals were correlated with the BOLD signal in patterns that resembled resting state networks. Subsequent dynamic analysis showed that the correlation between DC EEG and the BOLD signal varied substantially over time, even within individual subjects. The variation in DC EEG appears to reflect the time-varying contribution of different resting state networks. Furthermore, some of the patterns of DC EEG and BOLD correlation are consistent with previous work demonstrating quasiperiodic spatiotemporal patterns of large-scale network activity in resting state. These findings demonstrate that infraslow electrical activity is linked to BOLD fluctuations in humans and that it may provide a basis for large-scale organization comparable to that observed in animal studies.

  2. Character-level neural network for biomedical named entity recognition.

    Science.gov (United States)

    Gridach, Mourad

    2017-06-01

    Biomedical named entity recognition (BNER), which extracts important named entities such as genes and proteins, is a challenging task in automated systems that mine knowledge in biomedical texts. The previous state-of-the-art systems required large amounts of task-specific knowledge in the form of feature engineering, lexicons and data pre-processing to achieve high performance. In this paper, we introduce a novel neural network architecture that benefits from both word- and character-level representations automatically, by using a combination of bidirectional long short-term memory (LSTM) and conditional random field (CRF) eliminating the need for most feature engineering tasks. We evaluate our system on two datasets: JNLPBA corpus and the BioCreAtIvE II Gene Mention (GM) corpus. We obtained state-of-the-art performance by outperforming the previous systems. To the best of our knowledge, we are the first to investigate the combination of deep neural networks, CRF, word embeddings and character-level representation in recognizing biomedical named entities. Copyright © 2017 Elsevier Inc. All rights reserved.

  3. Network Layer Protocol Activation for Packet Data Access in UMTS WCDMA Laboratory Network

    OpenAIRE

    Lakkisto, Erkka

    2011-01-01

    The purpose of this Bachelor’s Thesis was to set up the UMTS WCDMA network in the laboratory environment of Helsinki Metropolia University of Applied Sciences and to study the network layer protocol activation for packet data access. The development of 3G technology has been very rapid and it can be considered as one of the main technologies in telecommunication. Implementing the laboratory network in Metropolia enables teaching and researching of the modern network technology. Labora...

  4. Active Computer Network Defense: An Assessment

    Science.gov (United States)

    2001-04-01

    sufficient base of knowledge in information technology can be assumed to be working on some form of computer network warfare, even if only defensive in...the Defense Information Infrastructure (DII) to attack. Transmission Control Protocol/ Internet Protocol (TCP/IP) networks are inherently resistant to...aims to create this part of information superiority, and computer network defense is one of its fundamental components. Most of these efforts center

  5. Developing a network-level structural capacity index for structural evaluation of pavements.

    Science.gov (United States)

    2013-03-01

    The objective of this project was to develop a structural index for use in network-level pavement evaluation to facilitate : the inclusion of the pavements structural condition in pavement management applications. The primary goal of network-level...

  6. 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...... structure. The results indicate that the tourist activated network for the destination is rather sparse and that there are clearly differences in core and peripheral nodes. The findings illustrate the structure of a tourist activated network and provide implications for technology design and tourism...

  7. Physical activity levels early after lung transplantation.

    Science.gov (United States)

    Wickerson, Lisa; Mathur, Sunita; Singer, Lianne G; Brooks, Dina

    2015-04-01

    Little is known of the early changes in physical activity after lung transplantation. The purposes of this study were: (1) to describe physical activity levels in patients up to 6 months following lung transplantation and (2) to explore predictors of the change in physical activity in that population. This was a prospective cohort study. Physical activity (daily steps and time spent in moderate-intensity activity) was measured using an accelerometer before and after transplantation (at hospital discharge, 3 months, and 6 months). Additional functional measurements included submaximal exercise capacity (measured with the 6-Minute Walk Test), quadriceps muscle torque, and health-related quality of life (measured with the Medical Outcomes Study 36-Item Short-Form Health Survey 36 [SF-36] and the St George's Respiratory Questionnaire). Thirty-six lung transplant recipients (18 men, 18 women; mean age=49 years, SD=14) completed posttransplant measurements. Before transplant, daily steps were less than a third of the general population. By 3 months posttransplant, the largest improvement in physical activity had occurred, and level of daily steps reached 55% of the general population. The change in daily steps (pretransplant to 3 months posttransplant) was inversely correlated with pretransplant 6-minute walk distance (r=-.48, P=.007), daily steps (r=-.36, P=.05), and SF-36 physical functioning (SF-36 PF) score (r=-.59, P=.0005). The SF-36 PF was a significant predictor of the change in physical activity, accounting for 35% of the variation in change in daily steps. Only individuals who were ambulatory prior to transplant and discharged from the hospital in less than 3 months were included in the study. Physical activity levels improve following lung transplantation, particularly in individuals with low self-reported physical functioning. However, the majority of lung transplant recipients remain sedentary between 3 to 6 months following transplant. The role of exercise

  8. 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.

  9. Toward a Theory of Industrial Supply Networks: A Multi-Level Perspective via Network Analysis

    Directory of Open Access Journals (Sweden)

    Yi Zuo

    2017-07-01

    Full Text Available In most supply chains (SCs, transaction relationships between suppliers and customers are commonly considered to be an extrapolation from a linear perspective. However, this traditional linear concept of an SC is egotistic and oversimplified and does not sufficiently reflect the complex and cyclical structure of supplier-customer relationships in current economic and industrial situations. The interactional relationships and topological characteristics between suppliers and customers should be analyzed using supply networks (SNs rather than traditional linear SCs. Therefore, this paper reconceptualizes SCs as SNs in complex adaptive systems (CAS, and presents three main contributions. First, we propose an integrated framework of CAS network by synthesizing multi-level network analysis from the network-, community- and vertex-perspective. The CAS perspective enables us to understand the advances of SN properties. Second, in order to emphasize the CAS properties of SNs, we conducted a real-world SN based on the Japanese industry and describe an advanced investigation of SN theory. The CAS properties help in enriching the SN theory, which can benefit SN management, community economics and industrial resilience. Third, we propose a quantitative metric of entropy to measure the complexity and robustness of SNs. The results not only support a specific understanding of the structural outcomes relevant to SNs, but also deliver efficient and effective support to the management and design of SNs.

  10. Competing dynamic phases of active polymer networks

    Science.gov (United States)

    Freedman, Simon; Banerjee, Shiladitya; Dinner, Aaron R.

    Recent experiments on in-vitro reconstituted assemblies of F-actin, myosin-II motors, and cross-linking proteins show that tuning local network properties can changes the fundamental biomechanical behavior of the system. For example, by varying cross-linker density and actin bundle rigidity, one can switch between contractile networks useful for reshaping cells, polarity sorted networks ideal for directed molecular transport, and frustrated networks with robust structural properties. To efficiently investigate the dynamic phases of actomyosin networks, we developed a coarse grained non-equilibrium molecular dynamics simulation of model semiflexible filaments, molecular motors, and cross-linkers with phenomenologically defined interactions. The simulation's accuracy was verified by benchmarking the mechanical properties of its individual components and collective behavior against experimental results at the molecular and network scales. By adjusting the model's parameters, we can reproduce the qualitative phases observed in experiment and predict the protein characteristics where phase crossovers could occur in collective network dynamics. Our model provides a framework for understanding cells' multiple uses of actomyosin networks and their applicability in materials research. Supported by the Department of Defense (DoD) through the National Defense Science & Engineering Graduate Fellowship (NDSEG) Program.

  11. Networking Activities at the Library of Congress.

    Science.gov (United States)

    Maruyama, Lenore S.; Avram, Henriette D.

    1979-01-01

    Examines the background studies and high-priority projects which will lay the groundwork for the library bibliographic component of a National Library and Information Service Network and reviews the progress and problems of the national network as evidenced by current cooperative projects. (CWM)

  12. High level cognitive information processing in neural networks

    Science.gov (United States)

    Barnden, John A.; Fields, Christopher A.

    1992-01-01

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

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

    DEFF Research Database (Denmark)

    Dickel, Petra; Ritter, Thomas

    Besides for-profit start-ups, an increasing number of firms start their existence with the purpose to “do good” for society – mirrored in an increasing academic discussion of sustainable firms. Yet, there is little research on the networking activities of start-ups that do not have profit...... 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...

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

    Science.gov (United States)

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

    2010-01-01

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

  15. Development of Human-level Decision Making Algorithm for NPPs through Deep Neural Networks : Conceptual Approach

    International Nuclear Information System (INIS)

    Kim, Seung Geun; Seong, Poong Hyun

    2017-01-01

    Development of operation support systems and automation systems are closely related to machine learning field. However, since it is hard to achieve human-level delicacy and flexibility for complex tasks with conventional machine learning technologies, only operation support systems with simple purposes were developed and high-level automation related studies were not actively conducted. As one of the efforts for reducing human error in NPPs and technical advance toward automation, the ultimate goal of this research is to develop human-level decision making algorithm for NPPs during emergency situations. The concepts of SL, RL, policy network, value network, and MCTS, which were applied to decision making algorithm for other fields are introduced and combined with nuclear field specifications. Since the research is currently at the conceptual stage, more research is warranted.

  16. Are Preschool Children Active Enough? Objectively Measured Physical Activity Levels

    Science.gov (United States)

    Cardon, Greet M.; De Bourdeaudhuij, Ilse M. M.

    2008-01-01

    The present study aimed to describe accelerometer-based physical activity levels in 4- and 5-year-old children (N = 76) on 2 weekdays and 2 weekend days. The children were sedentary for 9.6 hr (85%) daily, while they engaged in moderate to vigorous physical activity (MVPA) for 34 min (5%). Only 7% of the children engaged in MVPA for 60 min per…

  17. Finding quasi-optimal network topologies for information transmission in active networks.

    Science.gov (United States)

    Baptista, Murilo S; de Carvalho, Josué X; Hussein, Mahir S

    2008-01-01

    This work clarifies the relation between network circuit (topology) and behaviour (information transmission and synchronization) in active networks, e.g. neural networks. As an application, we show how one can find network topologies that are able to transmit a large amount of information, possess a large number of communication channels, and are robust under large variations of the network coupling configuration. This theoretical approach is general and does not depend on the particular dynamic of the elements forming the network, since the network topology can be determined by finding a Laplacian matrix (the matrix that describes the connections and the coupling strengths among the elements) whose eigenvalues satisfy some special conditions. To illustrate our ideas and theoretical approaches, we use neural networks of electrically connected chaotic Hindmarsh-Rose neurons.

  18. Finding quasi-optimal network topologies for information transmission in active networks.

    Directory of Open Access Journals (Sweden)

    Murilo S Baptista

    Full Text Available This work clarifies the relation between network circuit (topology and behaviour (information transmission and synchronization in active networks, e.g. neural networks. As an application, we show how one can find network topologies that are able to transmit a large amount of information, possess a large number of communication channels, and are robust under large variations of the network coupling configuration. This theoretical approach is general and does not depend on the particular dynamic of the elements forming the network, since the network topology can be determined by finding a Laplacian matrix (the matrix that describes the connections and the coupling strengths among the elements whose eigenvalues satisfy some special conditions. To illustrate our ideas and theoretical approaches, we use neural networks of electrically connected chaotic Hindmarsh-Rose neurons.

  19. Academic Activities Transaction Extraction Based on Deep Belief Network

    Directory of Open Access Journals (Sweden)

    Xiangqian Wang

    2017-01-01

    Full Text Available Extracting information about academic activity transactions from unstructured documents is a key problem in the analysis of academic behaviors of researchers. The academic activities transaction includes five elements: person, activities, objects, attributes, and time phrases. The traditional method of information extraction is to extract shallow text features and then to recognize advanced features from text with supervision. Since the information processing of different levels is completed in steps, the error generated from various steps will be accumulated and affect the accuracy of final results. However, because Deep Belief Network (DBN model has the ability to automatically unsupervise learning of the advanced features from shallow text features, the model is employed to extract the academic activities transaction. In addition, we use character-based feature to describe the raw features of named entities of academic activity, so as to improve the accuracy of named entity recognition. In this paper, the accuracy of the academic activities extraction is compared by using character-based feature vector and word-based feature vector to express the text features, respectively, and with the traditional text information extraction based on Conditional Random Fields. The results show that DBN model is more effective for the extraction of academic activities transaction information.

  20. Network-dependent modulation of brain activity during sleep.

    Science.gov (United States)

    Watanabe, Takamitsu; Kan, Shigeyuki; Koike, Takahiko; Misaki, Masaya; Konishi, Seiki; Miyauchi, Satoru; Miyahsita, Yasushi; Masuda, Naoki

    2014-09-01

    Brain activity dynamically changes even during sleep. A line of neuroimaging studies has reported changes in functional connectivity and regional activity across different sleep stages such as slow-wave sleep (SWS) and rapid-eye-movement (REM) sleep. However, it remains unclear whether and how the large-scale network activity of human brains changes within a given sleep stage. Here, we investigated modulation of network activity within sleep stages by applying the pairwise maximum entropy model to brain activity obtained by functional magnetic resonance imaging from sleeping healthy subjects. We found that the brain activity of individual brain regions and functional interactions between pairs of regions significantly increased in the default-mode network during SWS and decreased during REM sleep. In contrast, the network activity of the fronto-parietal and sensory-motor networks showed the opposite pattern. Furthermore, in the three networks, the amount of the activity changes throughout REM sleep was negatively correlated with that throughout SWS. The present findings suggest that the brain activity is dynamically modulated even in a sleep stage and that the pattern of modulation depends on the type of the large-scale brain networks. Copyright © 2014 Elsevier Inc. All rights reserved.

  1. The European network of Biosafety-Level-4 laboratories: enhancing European preparedness for new health threats.

    Science.gov (United States)

    Nisii, C; Castilletti, C; Di Caro, A; Capobianchi, M R; Brown, D; Lloyd, G; Gunther, S; Lundkvist, A; Pletschette, M; Ippolito, G

    2009-08-01

    Emerging and re-emerging infections and possible bioterrorism acts will continue to challenge both the medical community and civilian populations worldwide, urging health authorities to respond rapidly and effectively. Established in 2005, the European Community (EC)-funded European Network of Biosafety-Level-4 laboratories (Euronet-P4), which brings together the laboratories in Porton Down, London, Hamburg, Marburg, Solna, Lyon and Rome, seeks to increase international collaboration in the areas of high containment laboratory biosafety and viral diagnostic capability, to strengthen Europe's capacity to respond to an infectious disease emergency, and to offer assistance to countries not equipped with such costly facilities. Network partners have agreed on a common strategy to fill the gaps identified in the field of risk group-4 agents' laboratory diagnosis, namely the lack of standardization and of reference samples. The network has received a further 3-year funding, to offer assistance to external laboratories, and to start the planning of field activities.

  2. Network-level accident-mapping: Distance based pattern matching using artificial neural network.

    Science.gov (United States)

    Deka, Lipika; Quddus, Mohammed

    2014-04-01

    The objective of an accident-mapping algorithm is to snap traffic accidents onto the correct road segments. Assigning accidents onto the correct segments facilitate to robustly carry out some key analyses in accident research including the identification of accident hot-spots, network-level risk mapping and segment-level accident risk modelling. Existing risk mapping algorithms have some severe limitations: (i) they are not easily 'transferable' as the algorithms are specific to given accident datasets; (ii) they do not perform well in all road-network environments such as in areas of dense road network; and (iii) the methods used do not perform well in addressing inaccuracies inherent in and type of road environment. The purpose of this paper is to develop a new accident mapping algorithm based on the common variables observed in most accident databases (e.g. road name and type, direction of vehicle movement before the accident and recorded accident location). The challenges here are to: (i) develop a method that takes into account uncertainties inherent to the recorded traffic accident data and the underlying digital road network data, (ii) accurately determine the type and proportion of inaccuracies, and (iii) develop a robust algorithm that can be adapted for any accident set and road network of varying complexity. In order to overcome these challenges, a distance based pattern-matching approach is used to identify the correct road segment. This is based on vectors containing feature values that are common in the accident data and the network data. Since each feature does not contribute equally towards the identification of the correct road segments, an ANN approach using the single-layer perceptron is used to assist in "learning" the relative importance of each feature in the distance calculation and hence the correct link identification. The performance of the developed algorithm was evaluated based on a reference accident dataset from the UK confirming that

  3. 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

  4. Ripples Make Waves: Binding Structured Activity and Plasticity in Hippocampal Networks

    Directory of Open Access Journals (Sweden)

    Josef H. L. P. Sadowski

    2011-01-01

    Full Text Available Establishing novel episodic memories and stable spatial representations depends on an exquisitely choreographed, multistage process involving the online encoding and offline consolidation of sensory information, a process that is largely dependent on the hippocampus. Each step is influenced by distinct neural network states that influence the pattern of activation across cellular assemblies. In recent years, the occurrence of hippocampal sharp wave ripple (SWR oscillations has emerged as a potentially vital network phenomenon mediating the steps between encoding and consolidation, both at a cellular and network level by promoting the rapid replay and reactivation of recent activity patterns. Such events facilitate memory formation by optimising the conditions for synaptic plasticity to occur between contingent neural elements. In this paper, we explore the ways in which SWRs and other network events can bridge the gap between spatiomnemonic processing at cellular/synaptic and network levels in the hippocampus.

  5. Google matrix of the world network of economic activities

    Science.gov (United States)

    Kandiah, Vivek; Escaith, Hubert; Shepelyansky, Dima L.

    2015-07-01

    Using the new data from the OECD-WTO world network of economic activities we construct the Google matrix G of this directed network and perform its detailed analysis. The network contains 58 countries and 37 activity sectors for years 1995 and 2008. The construction of G, based on Markov chain transitions, treats all countries on equal democratic grounds while the contribution of activity sectors is proportional to their exchange monetary volume. The Google matrix analysis allows to obtain reliable ranking of countries and activity sectors and to determine the sensitivity of CheiRank-PageRank commercial balance of countries in respect to price variations and labor cost in various countries. We demonstrate that the developed approach takes into account multiplicity of network links with economy interactions between countries and activity sectors thus being more efficient compared to the usual export-import analysis. The spectrum and eigenstates of G are also analyzed being related to specific activity communities of countries.

  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. A review on the impact of embedded generation to network fault level

    Science.gov (United States)

    Yahaya, M. S.; Basar, M. F.; Ibrahim, Z.; Nasir, M. N. N.; Lada, M. Y.; Bukhari, W. M.

    2015-05-01

    The line of Embedded Generation (EG) in power systems especially for renewable energy has increased markedly in recent years. The interconnection of EG has a technical impact which needs to considered. One of the technical challenges faced by the Distribution Network Operator (DNO) is the network fault level. In this paper, the different methods of interconnection with and without EG on the network is analyze by looking at the impact of network fault level. This comparative study made to determine the most effective method to reduce fault level or fault current. This paper will gives basic understanding on the fault level effect when synchronous generator connected to network by different method of interconnection. A three phase fault is introduced at one network bus bar. By employ it to simple network configuration of network configurations which is normal interconnection and splitting network connection with and without EG, the fault level has been simulated and analyzed. Developing the network model by using PSS-Viper™ software package, the fault level for both networks will be showed and the difference is defines. From the review, network splitting was found the best interconnection method and greatest potential for reducing the fault level in the network.

  8. Sensor Data Security Level Estimation Scheme for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Alex Ramos

    2015-01-01

    Full Text Available Due to their increasing dissemination, wireless sensor networks (WSNs have become the target of more and more sophisticated attacks, even capable of circumventing both attack detection and prevention mechanisms. This may cause WSN users, who totally trust these security mechanisms, to think that a sensor reading is secure, even when an adversary has corrupted it. For that reason, a scheme capable of estimating the security level (SL that these mechanisms provide to sensor data is needed, so that users can be aware of the actual security state of this data and can make better decisions on its use. However, existing security estimation schemes proposed for WSNs fully ignore detection mechanisms and analyze solely the security provided by prevention mechanisms. In this context, this work presents the sensor data security estimator (SDSE, a new comprehensive security estimation scheme for WSNs. SDSE is designed for estimating the sensor data security level based on security metrics that analyze both attack prevention and detection mechanisms. In order to validate our proposed scheme, we have carried out extensive simulations that show the high accuracy of SDSE estimates.

  9. Sensor Data Security Level Estimation Scheme for Wireless Sensor Networks

    Science.gov (United States)

    Ramos, Alex; Filho, Raimir Holanda

    2015-01-01

    Due to their increasing dissemination, wireless sensor networks (WSNs) have become the target of more and more sophisticated attacks, even capable of circumventing both attack detection and prevention mechanisms. This may cause WSN users, who totally trust these security mechanisms, to think that a sensor reading is secure, even when an adversary has corrupted it. For that reason, a scheme capable of estimating the security level (SL) that these mechanisms provide to sensor data is needed, so that users can be aware of the actual security state of this data and can make better decisions on its use. However, existing security estimation schemes proposed for WSNs fully ignore detection mechanisms and analyze solely the security provided by prevention mechanisms. In this context, this work presents the sensor data security estimator (SDSE), a new comprehensive security estimation scheme for WSNs. SDSE is designed for estimating the sensor data security level based on security metrics that analyze both attack prevention and detection mechanisms. In order to validate our proposed scheme, we have carried out extensive simulations that show the high accuracy of SDSE estimates. PMID:25608215

  10. Sensor data security level estimation scheme for wireless sensor networks.

    Science.gov (United States)

    Ramos, Alex; Filho, Raimir Holanda

    2015-01-19

    Due to their increasing dissemination, wireless sensor networks (WSNs) have become the target of more and more sophisticated attacks, even capable of circumventing both attack detection and prevention mechanisms. This may cause WSN users, who totally trust these security mechanisms, to think that a sensor reading is secure, even when an adversary has corrupted it. For that reason, a scheme capable of estimating the security level (SL) that these mechanisms provide to sensor data is needed, so that users can be aware of the actual security state of this data and can make better decisions on its use. However, existing security estimation schemes proposed for WSNs fully ignore detection mechanisms and analyze solely the security provided by prevention mechanisms. In this context, this work presents the sensor data security estimator (SDSE), a new comprehensive security estimation scheme for WSNs. SDSE is designed for estimating the sensor data security level based on security metrics that analyze both attack prevention and detection mechanisms. In order to validate our proposed scheme, we have carried out extensive simulations that show the high accuracy of SDSE estimates.

  11. Coupling Strength and System Size Induce Firing Activity of Globally Coupled Neural Network

    International Nuclear Information System (INIS)

    Wei Duqu; Luo Xiaoshu; Zou Yanli

    2008-01-01

    We investigate how firing activity of globally coupled neural network depends on the coupling strength C and system size N. Network elements are described by space-clamped FitzHugh-Nagumo (SCFHN) neurons with the values of parameters at which no firing activity occurs. It is found that for a given appropriate coupling strength, there is an intermediate range of system size where the firing activity of globally coupled SCFHN neural network is induced and enhanced. On the other hand, for a given intermediate system size level, there exists an optimal value of coupling strength such that the intensity of firing activity reaches its maximum. These phenomena imply that the coupling strength and system size play a vital role in firing activity of neural network

  12. Consumer Activities and Reactions to Social Network Marketing

    OpenAIRE

    Bistra Vassileva

    2017-01-01

    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 ...

  13. Using Hierarchical Temporal Memory for Detecting Anomalous Network Activity

    Science.gov (United States)

    2008-03-01

    warfare, computer network operations, psychological operations, military deception, and operations security, in concert with specified supporting and...you up short—you were subconsciously predicting something else and were surprised by the mismatch” [3]. Notable neurobiologist Horace Barlow of the...malicious network activity is flagged as abnormal . That is, test data should present the N-HTM network with spatial-temporal patterns that do not match 46

  14. A flow level model for wireless multihop ad hoc network throughput

    NARCIS (Netherlands)

    Coenen, Tom Johannes Maria; van den Berg, Hans Leo; Boucherie, Richardus J.

    2005-01-01

    A flow level model for multihop wireless ad hoc networks is presented in this paper. Using a flow level view, we show the main properties and modeling challenges for ad hoc networks. Considering different scenarios, a multihop WLAN and a serial network with a TCP-like flow control protocol, we

  15. The Impact of the Physical Activity Policy Research Network.

    Science.gov (United States)

    Manteiga, Alicia M; Eyler, Amy A; Valko, Cheryl; Brownson, Ross C; Evenson, Kelly R; Schmid, Thomas

    2017-03-01

    Lack of physical activity is one of the greatest challenges of the 21st century. The Physical Activity Policy Research Network (PAPRN) is a thematic network established in 2004 to identify determinants, implementation, and outcomes of policies that are effective in increasing physical activity. The purpose of this study is to describe the products of PAPRN and make recommendations for future research and best practices. A mixed methods approach was used to obtain both quantitative and qualitative data on the network. First, in 2014, PAPRN's dissemination products from 2004 to 2014 were extracted and reviewed, including 57 publications and 56 presentations. Next, semi-structured qualitative interviews were conducted with 25 key network participants from 17 locations around the U.S. The transcripts were transcribed and coded. The results of the interviews indicated that the research network addressed several components of its mission, including the identification of physical activity policies, determinants of these policies, and the process of policy implementation. However, research focusing on physical activity policy outcomes was limited. Best practices included collaboration between researchers and practitioners and involvement of practitioners in research design, data collection, and dissemination of results. PAPRN is an example of a productive research network and has contributed to both the process and content of physical activity policy research over the past decade. Future research should emphasize physical activity policy outcomes. Additionally, increased partnerships with practitioners for collaborative, cross-sectoral physical activity policy research should be developed. Copyright © 2016 American Journal of Preventive Medicine. All rights reserved.

  16. Technical and economic evaluation of voltage level in transmission network expansion planning using GA

    International Nuclear Information System (INIS)

    Jalilzadeh, S.; Kazemi, A.; Shayeghi, H.; Madavi, M.

    2008-01-01

    Transmission network expansion planning is an important part of power system planning. Its task is to determine an optimal network configuration according to load growth. It determines where, when and how many new transmission lines should be installed. Up to now, various methods have been presented to solve the static transmission network expansion planning (STNEP) problem, but in all of these methods, the STNEP problem has been solved regardless of voltage level of the lines. In this paper, due to different voltage levels in the transmission network, which cause different annual losses, STNEP has been studied considering the voltage level of the transmission lines and the network loss using the genetic algorithm (GA). Finally, the proposed idea has been examined on Garvers 6 bus network. The results show that considering the loss in a network with different voltage levels decreases the operational costs considerably, and the network satisfies the requirement of delivering electric power more safely and reliably to load centers

  17. 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.

  18. 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

  19. Intrinsically-generated fluctuating activity in excitatory-inhibitory networks

    Science.gov (United States)

    Mastrogiuseppe, Francesca; Ostojic, Srdjan

    2017-01-01

    Recurrent networks of non-linear units display a variety of dynamical regimes depending on the structure of their synaptic connectivity. A particularly remarkable phenomenon is the appearance of strongly fluctuating, chaotic activity in networks of deterministic, but randomly connected rate units. How this type of intrinsically generated fluctuations appears in more realistic networks of spiking neurons has been a long standing question. To ease the comparison between rate and spiking networks, recent works investigated the dynamical regimes of randomly-connected rate networks with segregated excitatory and inhibitory populations, and firing rates constrained to be positive. These works derived general dynamical mean field (DMF) equations describing the fluctuating dynamics, but solved these equations only in the case of purely inhibitory networks. Using a simplified excitatory-inhibitory architecture in which DMF equations are more easily tractable, here we show that the presence of excitation qualitatively modifies the fluctuating activity compared to purely inhibitory networks. In presence of excitation, intrinsically generated fluctuations induce a strong increase in mean firing rates, a phenomenon that is much weaker in purely inhibitory networks. Excitation moreover induces two different fluctuating regimes: for moderate overall coupling, recurrent inhibition is sufficient to stabilize fluctuations; for strong coupling, firing rates are stabilized solely by the upper bound imposed on activity, even if inhibition is stronger than excitation. These results extend to more general network architectures, and to rate networks receiving noisy inputs mimicking spiking activity. Finally, we show that signatures of the second dynamical regime appear in networks of integrate-and-fire neurons. PMID:28437436

  20. Synaptic model for spontaneous activity in developing networks

    DEFF Research Database (Denmark)

    Lerchner, Alexander; Rinzel, J.

    2005-01-01

    Spontaneous rhythmic activity occurs in many developing neural networks. The activity in these hyperexcitable networks is comprised of recurring "episodes" consisting of "cycles" of high activity that alternate with "silent phases" with little or no activity. We introduce a new model of synaptic...... dynamics that takes into account that only a fraction of the vesicles stored in a synaptic terminal is readily available for release. We show that our model can reproduce spontaneous rhythmic activity with the same general features as observed in experiments, including a positive correlation between...

  1. Bit Level Synchronized MAC Protocol for Multireader RFID Networks

    Directory of Open Access Journals (Sweden)

    Namboodiri Vinod

    2010-01-01

    Full Text Available The operation of multiple RFID readers in close proximity results in interference between the readers. This issue is termed the reader collision problem and cannot always be solved by assigning them to different frequency channels due to technical and regulatory limitations. The typical solution is to separate the operation of such readers across time. This sequential operation, however, results in a long delay to identify all tags. We present a bit level synchronized (BLSync MAC protocol for multi-reader RFID networks that allows multiple readers to operate simultaneously on the same frequency channel. The BLSync protocol solves the reader collision problem by allowing all readers to transmit the same query at the same time. We analyze the performance of using the BLSync protocol and demonstrate benefits of 40%–50% in terms of tag reading delay for most settings. The benefits of BLSync, first demonstrated through analysis, are then validated and quantified through simulations on realistic reader-tag layouts.

  2. 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......) analysis is proposed. Active network management schemes such as coordinated voltage control, energy curtailment and power factor control are integrated in the method in order to investigate their impacts on the maximization of wind energy exploitation. Some case studies, using real data from a Danish...... distribution system, confirmed the effectiveness of the proposed method in evaluating the optimal applications of active management schemes to increase wind energy harvesting without costly network reinforcement for the connection of wind generation....

  3. Nonreciprocal signal routing in an active quantum network

    Science.gov (United States)

    Metelmann, A.; Türeci, H. E.

    2018-04-01

    As superconductor quantum technologies are moving towards large-scale integrated circuits, a robust and flexible approach to routing photons at the quantum level becomes a critical problem. Active circuits, which contain parametrically driven elements selectively embedded in the circuit, offer a viable solution. Here, we present a general strategy for routing nonreciprocally quantum signals between two sites of a given lattice of oscillators, implementable with existing superconducting circuit components. Our approach makes use of a dual lattice of overdamped oscillators linking the nodes of the main lattice. Solutions for spatially selective driving of the lattice elements can be found, which optimally balance coherent and dissipative hopping of microwave photons to nonreciprocally route signals between two given nodes. In certain lattices these optimal solutions are obtained at the exceptional point of the dynamical matrix of the network. We also demonstrate that signal and noise transmission characteristics can be separately optimized.

  4. Network-level architecture and the evolutionary potential of underground metabolism.

    Science.gov (United States)

    Notebaart, Richard A; Szappanos, Balázs; Kintses, Bálint; Pál, Ferenc; Györkei, Ádám; Bogos, Balázs; Lázár, Viktória; Spohn, Réka; Csörgő, Bálint; Wagner, Allon; Ruppin, Eytan; Pál, Csaba; Papp, Balázs

    2014-08-12

    A central unresolved issue in evolutionary biology is how metabolic innovations emerge. Low-level enzymatic side activities are frequent and can potentially be recruited for new biochemical functions. However, the role of such underground reactions in adaptation toward novel environments has remained largely unknown and out of reach of computational predictions, not least because these issues demand analyses at the level of the entire metabolic network. Here, we provide a comprehensive computational model of the underground metabolism in Escherichia coli. Most underground reactions are not isolated and 45% of them can be fully wired into the existing network and form novel pathways that produce key precursors for cell growth. This observation allowed us to conduct an integrated genome-wide in silico and experimental survey to characterize the evolutionary potential of E. coli to adapt to hundreds of nutrient conditions. We revealed that underground reactions allow growth in new environments when their activity is increased. We estimate that at least ∼20% of the underground reactions that can be connected to the existing network confer a fitness advantage under specific environments. Moreover, our results demonstrate that the genetic basis of evolutionary adaptations via underground metabolism is computationally predictable. The approach used here has potential for various application areas from bioengineering to medical genetics.

  5. Critical Transitions in Social Network Activity

    DEFF Research Database (Denmark)

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

    2014-01-01

    A large variety of complex systems in ecology, climate science, biomedicine and engineering have been observed to exhibit tipping points, where the dynamical state of the system abruptly changes. For example, such critical transitions may result in the sudden change of ecological environments...... 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....

  6. Network robustness assessed within a dual connectivity framework: joint dynamics of the Active and Idle Networks.

    Science.gov (United States)

    Tejedor, Alejandro; Longjas, Anthony; Zaliapin, Ilya; Ambroj, Samuel; Foufoula-Georgiou, Efi

    2017-08-17

    Network robustness against attacks has been widely studied in fields as diverse as the Internet, power grids and human societies. But current definition of robustness is only accounting for half of the story: the connectivity of the nodes unaffected by the attack. Here we propose a new framework to assess network robustness, wherein the connectivity of the affected nodes is also taken into consideration, acknowledging that it plays a crucial role in properly evaluating the overall network robustness in terms of its future recovery from the attack. Specifically, we propose a dual perspective approach wherein at any instant in the network evolution under attack, two distinct networks are defined: (i) the Active Network (AN) composed of the unaffected nodes and (ii) the Idle Network (IN) composed of the affected nodes. The proposed robustness metric considers both the efficiency of destroying the AN and that of building-up the IN. We show, via analysis of well-known prototype networks and real world data, that trade-offs between the efficiency of Active and Idle Network dynamics give rise to surprising robustness crossovers and re-rankings, which can have significant implications for decision making.

  7. System-Level Design Methodologies for Networked Multiprocessor Systems-on-Chip

    DEFF Research Database (Denmark)

    Virk, Kashif Munir

    2008-01-01

    is the first such attempt in the published literature. The second part of the thesis deals with the issues related to the development of system-level design methodologies for networked multiprocessor systems-on-chip at various levels of design abstraction with special focus on the modeling and design...... at the system-level. The multiprocessor modeling framework is then extended to include models of networked multiprocessor systems-on-chip which is then employed to model wireless sensor networks both at the sensor node level as well as the wireless network level. In the third and the final part, the thesis...... to the transaction-level model. The thesis, as a whole makes contributions by describing a design methodology for networked multiprocessor embedded systems at three layers of abstraction from system-level through transaction-level to the cycle accurate level as well as demonstrating it practically by implementing...

  8. Fragmenting networks by targeting collective influencers at a mesoscopic level

    Science.gov (United States)

    Kobayashi, Teruyoshi; Masuda, Naoki

    2016-11-01

    A practical approach to protecting networks against epidemic processes such as spreading of infectious diseases, malware, and harmful viral information is to remove some influential nodes beforehand to fragment the network into small components. Because determining the optimal order to remove nodes is a computationally hard problem, various approximate algorithms have been proposed to efficiently fragment networks by sequential node removal. Morone and Makse proposed an algorithm employing the non-backtracking matrix of given networks, which outperforms various existing algorithms. In fact, many empirical networks have community structure, compromising the assumption of local tree-like structure on which the original algorithm is based. We develop an immunization algorithm by synergistically combining the Morone-Makse algorithm and coarse graining of the network in which we regard a community as a supernode. In this way, we aim to identify nodes that connect different communities at a reasonable computational cost. The proposed algorithm works more efficiently than the Morone-Makse and other algorithms on networks with community structure.

  9. Bi-directional astrocytic regulation of neuronal activity within a network

    Directory of Open Access Journals (Sweden)

    Susan Yu Gordleeva

    2012-11-01

    Full Text Available The concept of a tripartite synapse holds that astrocytes can affect both the pre- and postsynaptic 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 postsynaptic currents. 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.

  10. Topological probability and connection strength induced activity in complex neural networks

    International Nuclear Information System (INIS)

    Du-Qu, Wei; Bo, Zhang; Dong-Yuan, Qiu; Xiao-Shu, Luo

    2010-01-01

    Recent experimental evidence suggests that some brain activities can be assigned to small-world networks. In this work, we investigate how the topological probability p and connection strength C affect the activities of discrete neural networks with small-world (SW) connections. Network elements are described by two-dimensional map neurons (2DMNs) with the values of parameters at which no activity occurs. It is found that when the value of p is smaller or larger, there are no active neurons in the network, no matter what the value of connection strength is; for a given appropriate connection strength, there is an intermediate range of topological probability where the activity of 2DMN network is induced and enhanced. On the other hand, for a given intermediate topological probability level, there exists an optimal value of connection strength such that the frequency of activity reaches its maximum. The possible mechanism behind the action of topological probability and connection strength is addressed based on the bifurcation method. Furthermore, the effects of noise and transmission delay on the activity of neural network are also studied. (general)

  11. 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

  12. Systematic network assessment of the carcinogenic activities of cadmium

    International Nuclear Information System (INIS)

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

    2016-01-01

    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. - Highlights: • A cadmium-influenced network with 850 nodes and 8770 edges was established. • The cadmium-rewired gene network was scale-free and highly connected. • Nine modules were identified, and 60 key signaling pathways related to cadmium-induced carcinogenesis were found. • Key mediators in the network were validated in multiple cellular models.

  13. Systematic network assessment of the carcinogenic activities of cadmium

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Peizhan; Duan, Xiaohua; Li, Mian; Huang, Chao [Key Laboratory of Food Safety Research, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai (China); Li, Jingquan; Chu, Ruiai; Ying, Hao; Song, Haiyun [Key Laboratory of Food Safety Research, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai (China); Key Laboratory of Food Safety Risk Assessment, Ministry of Health, Beijing (China); Jia, Xudong [Key Laboratory of Food Safety Risk Assessment, Ministry of Health, Beijing (China); Ba, Qian, E-mail: qba@sibs.ac.cn [Key Laboratory of Food Safety Research, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai (China); Key Laboratory of Food Safety Risk Assessment, Ministry of Health, Beijing (China); Wang, Hui, E-mail: huiwang@sibs.ac.cn [Key Laboratory of Food Safety Research, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai (China); Key Laboratory of Food Safety Risk Assessment, Ministry of Health, Beijing (China); School of Life Science and Technology, ShanghaiTech University, Shanghai (China)

    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. - Highlights: • A cadmium-influenced network with 850 nodes and 8770 edges was established. • The cadmium-rewired gene network was scale-free and highly connected. • Nine modules were identified, and 60 key signaling pathways related to cadmium-induced carcinogenesis were found. • Key mediators in the network were validated in multiple cellular models.

  14. Trinets encode tree-child and level-2 phylogenetic networks

    NARCIS (Netherlands)

    L.J.J. van Iersel (Leo); V. Moulton

    2012-01-01

    htmlabstractPhylogenetic networks generalize evolutionary trees, and are commonly used to represent evolutionary histories of species that undergo reticulate evolutionary processes such as hybridization, recombination and lateral gene transfer. Recently, there has been great interest in trying to

  15. A distributed water level network in ephemeral river reaches to identify hydrological processes within anthropogenic catchments

    Science.gov (United States)

    Sarrazin, B.; Braud, I.; Lagouy, M.; Bailly, J. S.; Puech, C.; Ayroles, H.

    2009-04-01

    In order to study the impact of land use change on the water cycle, distributed hydrological models are more and more used, because they have the ability to take into account the land surface heterogeneity and its evolution due to anthropogenic pressure. These models provide continuous distributed simulations of streamflow, runoff, soil moisture, etc, which, ideally, should be evaluated against continuous distributed measurements, taken at various scales and located in nested sub-catchments. Distributed network of streamflow gauging stations are in general scarce and very expensive to maintain. Furthermore, they can hardly be installed in the upstream parts of the catchments where river beds are not well defined. In this paper, we present an alternative to these standard streamflow gauging stations network, based on self powered high resolution water level sensors using a capacitive water height data logger. One of their advantages is that they can be installed even in ephemeral reaches and from channel head locations to high order streams. Furthermore, these innovative and easily adaptable low cost sensors offer the possibility to develop in the near future, a wireless network application. Such a network, including 15 sensors has been set up on nested watersheds in small and intermittent streams of a 7 km² catchment, located in the mountainous "Mont du Lyonnais" area, close to the city of Lyon, France. The land use of this catchment is mostly pasture, crop and forest, but the catchment is significantly affected by human activities, through the existence of a dense roads and paths network and urbanized areas. The equipment provides water levels survey during precipitation events in the hydrological network with a very accurate time step (2 min). Water levels can be related to runoff production and catchment response as a function of scale. This response will depend, amongst other, on variable soil water storage capacity, physiographic data and characteristics of

  16. Resource Sharing Networks for Higher Education at State Level

    OpenAIRE

    Raman Nair, R.

    1990-01-01

    The project proposal on Development of an Information and Library Network (INFLIBNET) became a public document by 1990. The aim of INFLIBNET as provided in the report was modernizing college and university libraries in India and connecting them through a nation-wide high speed data network using the state-of-art technologies for the optimum utilization of information. INFLIBNET was envisaged to be a major player in promoting scholarly communication among academicians and researchers in India....

  17. Connectivity, excitability and activity patterns in neuronal networks

    International Nuclear Information System (INIS)

    Le Feber, Joost; Stoyanova, Irina I; 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 currently exist for estimating network connectivity, most of which are related to cross-correlation. An example is the conditional firing probability (CFP) analysis which calculates the pairwise probability (CFP i,j ) that electrode j records an action potential at time t = τ, given that electrode i recorded a spike at t = 0. However, electrode i often records multiple spikes within the analysis interval, and CFP values are biased by the on-going dynamic state of the network. Here we show that in a linear approximation this bias may be removed by deconvoluting CFP i,j with the autocorrelation of i (i.e. CFP i,i ), to obtain the single pulse response (SPR i,j )—the average response at electrode j to a single spike at electrode i. Thus, in a linear system SPRs would be independent of the dynamic network state. Nonlinear components of synaptic transmission, such as facilitation and short term depression, will however still affect SPRs. Therefore SPRs provide a clean measure of network excitability. We used carbachol and ghrelin to moderately activate cultured cortical networks to affect their dynamic state. Both neuromodulators transformed the bursting firing patterns of the isolated networks into more dispersed firing. We show that the influence of the dynamic state on SPRs is much smaller than the effect on CFPs, but not zero. The remaining difference reflects the alteration in network excitability. We conclude that SPRs are less contaminated by the dynamic network state and that mild excitation may decrease network excitability, possibly through short term synaptic depression. (papers)

  18. 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.

  19. 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.

  20. Linking structure and activity in nonlinear spiking networks.

    Science.gov (United States)

    Ocker, Gabriel Koch; Josić, Krešimir; Shea-Brown, Eric; Buice, Michael A

    2017-06-01

    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.

  1. PSA Level 2 activities for RBMK reactors

    International Nuclear Information System (INIS)

    Gubler, R.

    1998-01-01

    Probabilistic safety analyses (PSAs) of the boiling water graphite moderated pressure tube reactors (RBMKs) have been developed only recently and they are limited to Level 1. Activities at the IAEA were first motivated because of the difficulties to characterize core damage for RBMK reactors. Core damage probability is used in documents of the IAEA as a convenient single valued measure, for example for probabilistic safety criteria. The limited number of PSAs that have been completed for the RBMK reactors have shown that several special features of these channel type reactors necessitate revisiting of the characterization of core damage for these reactors. Furthermore, it has become increasingly evident that detailed deterministic analysis of DBAs and beyond design basis accidents reveal considerable insights into RBMK response to various accident conditions. These analyses can also help in better characterizing the outstanding phenomenological uncertainties, improved EOPs and AM strategies, including potential risk-beneficial accident negative backfits. The deterministic efforts should be focused first on elucidating accident progression processes and phenomena, and second on finding, qualifying and implementing procedures to minimize the risk of severe accident states The IAEA PSA procedures were mainly developed in New of vessel type LWRs, and would therefore require extensions to make them directly applicable. to channel type reactors. (author) (author)

  2. Goal-congruent default network activity facilitates cognitive control.

    Science.gov (United States)

    Spreng, R Nathan; DuPre, Elizabeth; Selarka, Dhawal; Garcia, Juliana; Gojkovic, Stefan; Mildner, Judith; Luh, Wen-Ming; Turner, Gary R

    2014-10-15

    Substantial neuroimaging evidence suggests that spontaneous engagement of the default network impairs performance on tasks requiring executive control. We investigated whether this impairment depends on the congruence between executive control demands and internal mentation. We hypothesized that activation of the default network might enhance performance on an executive control task if control processes engage long-term memory representations that are supported by the default network. Using fMRI, we scanned 36 healthy young adult humans on a novel two-back task requiring working memory for famous and anonymous faces. In this task, participants (1) matched anonymous faces interleaved with anonymous face, (2) matched anonymous faces interleaved with a famous face, or (3) matched a famous faces interleaved with an anonymous face. As predicted, we observed a facilitation effect when matching famous faces, compared with anonymous faces. We also observed greater activation of the default network during these famous face-matching trials. The results suggest that activation of the default network can contribute to task performance during an externally directed executive control task. Our findings provide evidence that successful activation of the default network in a contextually relevant manner facilitates goal-directed cognition. Copyright © 2014 the authors 0270-6474/14/3414108-07$15.00/0.

  3. Usage of link-level performance indicators for HSDPA network-level simulations in E-UMTS

    NARCIS (Netherlands)

    Brouwer, Frank; de Bruin, I.C.C.; Silva, João Carlos; Souto, Nuno; Cercas, Francisco; Correia, Américo

    2004-01-01

    The paper describes integration of HSDPA (high-speed downlink packet access) link-level simulation results into network-level simulations for enhanced UMTS. The link-level simulations model all physical layer features depicted in the 3GPP standards. These include: generation of transport blocks;

  4. Tansig activation function (of MLP network) for cardiac abnormality detection

    Science.gov (United States)

    Adnan, Ja'afar; Daud, Nik Ghazali Nik; Ishak, Mohd Taufiq; Rizman, Zairi Ismael; Rahman, Muhammad Izzuddin Abd

    2018-02-01

    Heart abnormality often occurs regardless of gender, age and races. This problem sometimes does not show any symptoms and it can cause a sudden death to the patient. In general, heart abnormality is the irregular electrical activity of the heart. This paper attempts to develop a program that can detect heart abnormality activity through implementation of Multilayer Perceptron (MLP) network. A certain amount of data of the heartbeat signals from the electrocardiogram (ECG) will be used in this project to train the MLP network by using several training algorithms with Tansig activation function.

  5. Application of Artificial Neural Network into the Water Level Modeling and Forecast

    Directory of Open Access Journals (Sweden)

    Marzenna Sztobryn

    2013-06-01

    Full Text Available The dangerous sea and river water level increase does not only destroy the human lives, but also generate the severe flooding in coastal areas. The rapidly changes in the direction and velocity of wind and associated with them sea level changes could be the severe threat for navigation, especially on the fairways of small fishery harbors located in the river mouth. There is the area of activity of two external forcing: storm surges and flood wave. The aim of the work was the description of an application of Artificial Neural Network (ANN methodology into the water level forecast in the case study field in Swibno harbor located is located at 938.7 km of the Wisla River and at a distance of about 3 km up the mouth (Gulf of Gdansk - Baltic Sea.

  6. 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.

  7. 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.

  8. 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.)

  9. Managing nuclear knowledge: IAEA activities and international coordination. Asian Network for Education in Nuclear Technology (ANENT)

    International Nuclear Information System (INIS)

    2007-07-01

    This CD-ROM is attached to the booklet 'Managing nuclear knowledge: IAEA activities and international coordination. Asian Network for Education in Nuclear Technology (ANENT)'. It contains the background material with regard to ANENT in full text, including policy level papers, reports, presentation material made by Member States, and meeting summaries during the period 2002-2005. Further information on the current ANENT activities and related IAEA activities is available at 'http://anent-iaea.org' and 'http://iaea.org/inisnkm'

  10. Recognizing Multi-user Activities using Body Sensor Networks

    DEFF Research Database (Denmark)

    Gu, Tao; Wang, Liang; Chen, Hanhua

    2011-01-01

    The advances of wireless networking and sensor technology open up an interesting opportunity to infer human activities in a smart home environment. Existing work in this paradigm focuses mainly on recognizing activities of a single user. In this work, we address the fundamental problem...... 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...... home environment, and conduct comprehensive empirical studies to evaluate our system. Results show that epMAR outperforms existing schemes in terms of accuracy, scalability and robustness....

  11. Managing coopetition through horizontal supply chain relations : Linking dyadic and network levels of analysis

    NARCIS (Netherlands)

    Wilhelm, Miriam M.

    2011-01-01

    A growing research stream has expanded the level of analysis beyond single buyer-supplier relations to the network, including supplier-supplier relations. These supplier-supplier relations may constitute a missing link between the traditional analysis of the dyadic and the network level of analysis

  12. Managing coopetition through horizontal supply chain relations : Linking dyadic and network levels of analysis

    NARCIS (Netherlands)

    Wilhelm, Miriam M.

    A growing research stream has expanded the level of analysis beyond single buyer-supplier relations to the network, including supplier-supplier relations. These supplier-supplier relations may constitute a missing link between the traditional analysis of the dyadic and the network level of analysis

  13. Cities, Europeanization and Multi-level Governance: Governing Climate Change through Transnational Municipal Networks

    NARCIS (Netherlands)

    Kern, K.; Bulkeley, H.

    2009-01-01

    This article focuses on a variant of multi-level governance and Europeanization, i.e. the transnational networking of local authorities. Focusing on local climate change policy, the article examines how transnational municipal networks (TMNs) govern in the context of multi-level European governance.

  14. 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.

  15. 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.

  16. On attracting sets in artificial networks: cross activation

    Directory of Open Access Journals (Sweden)

    Sadyrbaev Felix

    2018-01-01

    Full Text Available Mathematical models of artificial networks can be formulated in terms of dynamical systems describing the behaviour of a network over time. The interrelation between nodes (elements of a network is encoded in the regulatory matrix. We consider a system of ordinary differential equations that describes in particular also genomic regulatory networks (GRN and contains a sigmoidal function. The results are presented on attractors of such systems for a particular case of cross activation. The regulatory matrix is then of particular form consisting of unit entries everywhere except the main diagonal. We show that such a system can have not more than three critical points. At least n–1 eigenvalues corresponding to any of the critical points are negative. An example for a particular choice of sigmoidal function is considered.

  17. Habitual physical activity levels are positively correlated with CD4 ...

    African Journals Online (AJOL)

    Habitual physical activity levels are positively correlated with CD4 counts in an ... per month) and functional independence as assessed from the responses to the ... and between CD4 cell counts and total habitual physical activity levels (p ...

  18. Information transmission and signal permutation in active flow networks

    Science.gov (United States)

    Woodhouse, Francis G.; Fawcett, Joanna B.; Dunkel, Jörn

    2018-03-01

    Recent experiments show that both natural and artificial microswimmers in narrow channel-like geometries will self-organise to form steady, directed flows. This suggests that networks of flowing active matter could function as novel autonomous microfluidic devices. However, little is known about how information propagates through these far-from-equilibrium systems. Through a mathematical analogy with spin-ice vertex models, we investigate here the input–output characteristics of generic incompressible active flow networks (AFNs). Our analysis shows that information transport through an AFN is inherently different from conventional pressure or voltage driven networks. Active flows on hexagonal arrays preserve input information over longer distances than their passive counterparts and are highly sensitive to bulk topological defects, whose presence can be inferred from marginal input–output distributions alone. This sensitivity further allows controlled permutations on parallel inputs, revealing an unexpected link between active matter and group theory that can guide new microfluidic mixing strategies facilitated by active matter and aid the design of generic autonomous information transport networks.

  19. Systems-level mechanisms of action of Panax ginseng: a network pharmacological approach.

    Science.gov (United States)

    Park, Sa-Yoon; Park, Ji-Hun; Kim, Hyo-Su; Lee, Choong-Yeol; Lee, Hae-Jeung; Kang, Ki Sung; Kim, Chang-Eop

    2018-01-01

    Panax ginseng has been used since ancient times based on the traditional Asian medicine theory and clinical experiences, and currently, is one of the most popular herbs in the world. To date, most of the studies concerning P. ginseng have focused on specific mechanisms of action of individual constituents. However, in spite of many studies on the molecular mechanisms of P. ginseng , it still remains unclear how multiple active ingredients of P. ginseng interact with multiple targets simultaneously, giving the multidimensional effects on various conditions and diseases. In order to decipher the systems-level mechanism of multiple ingredients of P. ginseng , a novel approach is needed beyond conventional reductive analysis. We aim to review the systems-level mechanism of P. ginseng by adopting novel analytical framework-network pharmacology. Here, we constructed a compound-target network of P. ginseng using experimentally validated and machine learning-based prediction results. The targets of the network were analyzed in terms of related biological process, pathways, and diseases. The majority of targets were found to be related with primary metabolic process, signal transduction, nitrogen compound metabolic process, blood circulation, immune system process, cell-cell signaling, biosynthetic process, and neurological system process. In pathway enrichment analysis of targets, mainly the terms related with neural activity showed significant enrichment and formed a cluster. Finally, relative degrees analysis for the target-disease association of P. ginseng revealed several categories of related diseases, including respiratory, psychiatric, and cardiovascular diseases.

  20. The Meso-level Structure of F/OSS Collaboration Network

    DEFF Research Database (Denmark)

    Conald, Guido; Rullani, Francesco

    2010-01-01

    Social networks in Free/Open Source Software (F/OSS) have been usually analyzed at the level of the single project e.g., [6], or at the level of a whole ecology of projects, e.g., [33]. In this paper, we also investigate the social network generated by developers who collaborate to one or multiple...... F/OSS projects, but we focus on the less-studied meso-level structure emerging when applying to this network a community-detection technique. The network of ‘communities’ emerging from this analysis links sub-groups of densely connected developers, sub-groups that are smaller than the components...... of the network but larger than the teams working on single projects. Our results reveal the complexity of this meso-level structure, where several dense sub-groups of developers are connected by sparse collaboration among different sub-groups. We discuss the theoretical implications of our findings...

  1. Quantifying levels of animal activity using camera trap data

    NARCIS (Netherlands)

    Rowcliffe, J.M.; Kays, R.; Kranstauber, B.; Carbone, C.; Jansen, P.A.

    2014-01-01

    1.Activity level (the proportion of time that animals spend active) is a behavioural and ecological metric that can provide an indicator of energetics, foraging effort and exposure to risk. However, activity level is poorly known for free-living animals because it is difficult to quantify activity

  2. 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.

  3. Localizing potentially active post-transcriptional regulations in the Ewing's sarcoma gene regulatory network

    Directory of Open Access Journals (Sweden)

    Delyon Bernard

    2010-11-01

    Full Text Available Abstract Background A wide range of techniques is now available for analyzing regulatory networks. Nonetheless, most of these techniques fail to interpret large-scale transcriptional data at the post-translational level. Results We address the question of using large-scale transcriptomic observation of a system perturbation to analyze a regulatory network which contained several types of interactions - transcriptional and post-translational. Our method consisted of post-processing the outputs of an open-source tool named BioQuali - an automatic constraint-based analysis mimicking biologist's local reasoning on a large scale. The post-processing relied on differences in the behavior of the transcriptional and post-translational levels in the network. As a case study, we analyzed a network representation of the genes and proteins controlled by an oncogene in the context of Ewing's sarcoma. The analysis allowed us to pinpoint active interactions specific to this cancer. We also identified the parts of the network which were incomplete and should be submitted for further investigation. Conclusions The proposed approach is effective for the qualitative analysis of cancer networks. It allows the integrative use of experimental data of various types in order to identify the specific information that should be considered a priority in the initial - and possibly very large - experimental dataset. Iteratively, new dataset can be introduced into the analysis to improve the network representation and make it more specific.

  4. Kainate-induced network activity in the anterior cingulate cortex.

    Science.gov (United States)

    Shinozaki, R; Hojo, Y; Mukai, H; Hashizume, M; Murakoshi, T

    2016-06-14

    Anterior cingulate cortex (ACC) plays a pivotal role in higher order processing of cognition, attention and emotion. The network oscillation is considered an essential means for integration of these CNS functions. The oscillation power and coherence among related areas are often dis-regulated in several psychiatric and pathological conditions with a hemispheric asymmetric manner. Here we describe the network-based activity of field potentials recorded from the superficial layer of the mouse ACC in vitro using submerged type recordings. A short activation by kainic acid administration to the preparation induced populational activities ranging over several frequency bands including theta (3-8Hz), alpha (8-12Hz), beta (13-30Hz), low gamma (30-50Hz) and high gamma (50-80Hz). These responses were repeatable and totally abolished by tetrodotoxin, and greatly diminished by inhibitors of ionotropic and metabotropic glutamate receptors, GABAA receptor or gap-junctions. These observations suggest that the kainate-induced network activity can be a useful model of the network oscillation in the ACC circuit. Copyright © 2016 IBRO. Published by Elsevier Ltd. All rights reserved.

  5. Provable network activity for protecting users against false accusation

    NARCIS (Netherlands)

    Papadopoulos, Panagiotis; Athanasopoulos, Ilias; Kosta, Eleni; Siganos, George; Keromytis, Angelos D.; Markatos, Evangelos P.

    2016-01-01

    With the proliferation of the World Wide Web, data traces that correspond to users’ network activity can be collected by several Internet actors, including (i) web sites, (ii) smartphone apps, and even (iii) Internet Service Providers. Given that the collection and storage of these data are beyond

  6. Photonic network R and D activities in Japan

    Science.gov (United States)

    Kitayama, Ken-ichi; Miki, Tetsuya; Morioka, Toshio; Tsushima, Hideaki; Koga, Masafumi; Mori, Kazuyuki; Araki, Soichiro; Sato, Ken-ichi; Onaka, Hiroshi; Namiki, Shu; Aovama, Tomonori

    2005-11-01

    R and D activities on photonic networks in Japan are presented. First, milestones in current, ongoing R and D programs supported by Japanese government agencies are introduced, including long-distance and WDM fiber transmission, wavelength routing, optical burst switching, and control plane technology for IP backbone networks. Their goal was set to evolve a legacy telecommunications network to IP over WDM networks by introducing technologies for WDM and wavelength routing. We then discuss the perspectives of so-called PHASE II R and D programs for photonic networks over the next five years until 2010, by focusing on the report which has been recently issued by the Photonic Internet Forum (PIF), a consortium that has major carriers, telecom vendors, and Japanese academics as members. The PHASE II R and D programs should serve to establish a photonic platform to provide abundant bandwidth on demand, at any time on a real-time basis through the customer's initiative, to promote bandwidth-rich applications, such as grid computing, real-time digital-cinema streaming, medical and educational applications, and network storage in e-commerce.

  7. RelEx: Visualization for Actively Changing Overlay Network Specifications.

    Science.gov (United States)

    Sedlmair, M; Frank, A; Munzner, T; Butz, A

    2012-12-01

    We present a network visualization design study focused on supporting automotive engineers who need to specify and optimize traffic patterns for in-car communication networks. The task and data abstractions that we derived support actively making changes to an overlay network, where logical communication specifications must be mapped to an underlying physical network. These abstractions are very different from the dominant use case in visual network analysis, namely identifying clusters and central nodes, that stems from the domain of social network analysis. Our visualization tool RelEx was created and iteratively refined through a full user-centered design process that included a full problem characterization phase before tool design began, paper prototyping, iterative refinement in close collaboration with expert users for formative evaluation, deployment in the field with real analysts using their own data, usability testing with non-expert users, and summative evaluation at the end of the deployment. In the summative post-deployment study, which entailed domain experts using the tool over several weeks in their daily practice, we documented many examples where the use of RelEx simplified or sped up their work compared to previous practices.

  8. Imaging network level language recovery after left PCA stroke.

    Science.gov (United States)

    Sebastian, Rajani; Long, Charltien; Purcell, Jeremy J; Faria, Andreia V; Lindquist, Martin; Jarso, Samson; Race, David; Davis, Cameron; Posner, Joseph; Wright, Amy; Hillis, Argye E

    2016-05-11

    The neural mechanisms that support aphasia recovery are not yet fully understood. Our goal was to evaluate longitudinal changes in naming recovery in participants with posterior cerebral artery (PCA) stroke using a case-by-case analysis. Using task based and resting state functional magnetic resonance imaging (fMRI) and detailed language testing, we longitudinally studied the recovery of the naming network in four participants with PCA stroke with naming deficits at the acute (0 week), sub acute (3-5 weeks), and chronic time point (5-7 months) post stroke. Behavioral and imaging analyses (task related and resting state functional connectivity) were carried out to elucidate longitudinal changes in naming recovery. Behavioral and imaging analysis revealed that an improvement in naming accuracy from the acute to the chronic stage was reflected by increased connectivity within and between left and right hemisphere "language" regions. One participant who had persistent moderate naming deficit showed weak and decreasing connectivity longitudinally within and between left and right hemisphere language regions. These findings emphasize a network view of aphasia recovery, and show that the degree of inter- and intra- hemispheric balance between the language-specific regions is necessary for optimal recovery of naming, at least in participants with PCA stroke.

  9. Activity flow over resting-state networks shapes cognitive task activations.

    Science.gov (United States)

    Cole, Michael W; Ito, Takuya; Bassett, Danielle S; Schultz, Douglas H

    2016-12-01

    Resting-state functional connectivity (FC) has helped reveal the intrinsic network organization of the human brain, yet its relevance to cognitive task activations has been unclear. Uncertainty remains despite evidence that resting-state FC patterns are highly similar to cognitive task activation patterns. Identifying the distributed processes that shape localized cognitive task activations may help reveal why resting-state FC is so strongly related to cognitive task activations. We found that estimating task-evoked activity flow (the spread of activation amplitudes) over resting-state FC networks allowed prediction of cognitive task activations in a large-scale neural network model. Applying this insight to empirical functional MRI data, we found that cognitive task activations can be predicted in held-out brain regions (and held-out individuals) via estimated activity flow over resting-state FC networks. This suggests that task-evoked activity flow over intrinsic networks is a large-scale mechanism explaining the relevance of resting-state FC to cognitive task activations.

  10. Contextual Multi-Scale Region Convolutional 3D Network for Activity Detection

    KAUST Repository

    Bai, Yancheng

    2018-01-28

    Activity detection is a fundamental problem in computer vision. Detecting activities of different temporal scales is particularly challenging. In this paper, we propose the contextual multi-scale region convolutional 3D network (CMS-RC3D) for activity detection. To deal with the inherent temporal scale variability of activity instances, the temporal feature pyramid is used to represent activities of different temporal scales. On each level of the temporal feature pyramid, an activity proposal detector and an activity classifier are learned to detect activities of specific temporal scales. Temporal contextual information is fused into activity classifiers for better recognition. More importantly, the entire model at all levels can be trained end-to-end. Our CMS-RC3D detector can deal with activities at all temporal scale ranges with only a single pass through the backbone network. We test our detector on two public activity detection benchmarks, THUMOS14 and ActivityNet. Extensive experiments show that the proposed CMS-RC3D detector outperforms state-of-the-art methods on THUMOS14 by a substantial margin and achieves comparable results on ActivityNet despite using a shallow feature extractor.

  11. Contextual Multi-Scale Region Convolutional 3D Network for Activity Detection

    KAUST Repository

    Bai, Yancheng; Xu, Huijuan; Saenko, Kate; Ghanem, Bernard

    2018-01-01

    Activity detection is a fundamental problem in computer vision. Detecting activities of different temporal scales is particularly challenging. In this paper, we propose the contextual multi-scale region convolutional 3D network (CMS-RC3D) for activity detection. To deal with the inherent temporal scale variability of activity instances, the temporal feature pyramid is used to represent activities of different temporal scales. On each level of the temporal feature pyramid, an activity proposal detector and an activity classifier are learned to detect activities of specific temporal scales. Temporal contextual information is fused into activity classifiers for better recognition. More importantly, the entire model at all levels can be trained end-to-end. Our CMS-RC3D detector can deal with activities at all temporal scale ranges with only a single pass through the backbone network. We test our detector on two public activity detection benchmarks, THUMOS14 and ActivityNet. Extensive experiments show that the proposed CMS-RC3D detector outperforms state-of-the-art methods on THUMOS14 by a substantial margin and achieves comparable results on ActivityNet despite using a shallow feature extractor.

  12. Information Extraction with Character-level Neural Networks and Free Noisy Supervision

    OpenAIRE

    Meerkamp, Philipp; Zhou, Zhengyi

    2016-01-01

    We present an architecture for information extraction from text that augments an existing parser with a character-level neural network. The network is trained using a measure of consistency of extracted data with existing databases as a form of noisy supervision. Our architecture combines the ability of constraint-based information extraction systems to easily incorporate domain knowledge and constraints with the ability of deep neural networks to leverage large amounts of data to learn compl...

  13. Why and how selection patterns in classroom networks differ between students.The potential influence of networks size preferences, level of information, and group membership.

    Directory of Open Access Journals (Sweden)

    Baerveldt, Chris

    2010-12-01

    Full Text Available High school students can select class mates for new friendships using a repertoire of patterns. They can actively pursue new friendships, make use of the existing network structure, and/ or use the scarce and often erroneous information about candidates. In this theoretical paper, we argue that such selection patterns should not be studied as the result of general rules, as is usually done in social network studies. Specifically, we state that network size preferences, the level of information about individual attributes of fellow classmates, and group membership are likely to differ among high school students, and that as a result, also their selection patterns are likely to be different. In this paper we sketch the theoretical articulations between these.

  14. GABA and Gap Junctions in the Development of Synchronized Activity in Human Pluripotent Stem Cell-Derived Neural Networks

    Directory of Open Access Journals (Sweden)

    Meeri Eeva-Liisa Mäkinen

    2018-03-01

    Full Text Available The electrical activity of the brain arises from single neurons communicating with each other. However, how single neurons interact during early development to give rise to neural network activity remains poorly understood. We studied the emergence of synchronous neural activity in human pluripotent stem cell (hPSC-derived neural networks simultaneously on a single-neuron level and network level. The contribution of gamma-aminobutyric acid (GABA and gap junctions to the development of synchronous activity in hPSC-derived neural networks was studied with GABA agonist and antagonist and by blocking gap junctional communication, respectively. We characterized the dynamics of the network-wide synchrony in hPSC-derived neural networks with high spatial resolution (calcium imaging and temporal resolution microelectrode array (MEA. We found that the emergence of synchrony correlates with a decrease in very strong GABA excitation. However, the synchronous network was found to consist of a heterogeneous mixture of synchronously active cells with variable responses to GABA, GABA agonists and gap junction blockers. Furthermore, we show how single-cell distributions give rise to the network effect of GABA, GABA agonists and gap junction blockers. Finally, based on our observations, we suggest that the earliest form of synchronous neuronal activity depends on gap junctions and a decrease in GABA induced depolarization but not on GABAA mediated signaling.

  15. GABA and Gap Junctions in the Development of Synchronized Activity in Human Pluripotent Stem Cell-Derived Neural Networks

    Science.gov (United States)

    Mäkinen, Meeri Eeva-Liisa; Ylä-Outinen, Laura; Narkilahti, Susanna

    2018-01-01

    The electrical activity of the brain arises from single neurons communicating with each other. However, how single neurons interact during early development to give rise to neural network activity remains poorly understood. We studied the emergence of synchronous neural activity in human pluripotent stem cell (hPSC)-derived neural networks simultaneously on a single-neuron level and network level. The contribution of gamma-aminobutyric acid (GABA) and gap junctions to the development of synchronous activity in hPSC-derived neural networks was studied with GABA agonist and antagonist and by blocking gap junctional communication, respectively. We characterized the dynamics of the network-wide synchrony in hPSC-derived neural networks with high spatial resolution (calcium imaging) and temporal resolution microelectrode array (MEA). We found that the emergence of synchrony correlates with a decrease in very strong GABA excitation. However, the synchronous network was found to consist of a heterogeneous mixture of synchronously active cells with variable responses to GABA, GABA agonists and gap junction blockers. Furthermore, we show how single-cell distributions give rise to the network effect of GABA, GABA agonists and gap junction blockers. Finally, based on our observations, we suggest that the earliest form of synchronous neuronal activity depends on gap junctions and a decrease in GABA induced depolarization but not on GABAA mediated signaling. PMID:29559893

  16. When BOLD is thicker than water: processing social information about kin and friends at different levels of the social network.

    Science.gov (United States)

    Wlodarski, Rafael; Dunbar, Robin I M

    2016-12-01

    The aim of this study was to examine differences in the neural processing of social information about kin and friends at different levels of closeness and social network level. Twenty-five female participants engaged in a cognitive social task involving different individuals in their social network while undergoing functional magnetic resonance imaging scanning to detect BOLD (Blood Oxygen Level Dependent) signals changes. Greater levels of activation occurred in several regions of the brain previously associated with social cognition when thinking about friends than when thinking about kin, including the posterior cingulate cortex (PCC) and the ventral medial prefrontal cortex (vMPFC). Linear parametric analyses across network layers further showed that, when it came to thinking about friends, activation increased in the vMPFC, lingual gyrus, and sensorimotor cortex as individuals thought about friends at closer layers of the network. These findings suggest that maintaining friendships may be more cognitively exacting than maintaining kin relationships. © The Author (2016). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  17. The Greenlandic sea areas and activity level up to 2025

    DEFF Research Database (Denmark)

    Jakobsen, Uffe; í Dali, Birita

    2016-01-01

    , petroleum activity, tourism and research/government activity. The last chapter is devoted to summarizing findings about the current developed activity level in the High North sea and coastal regions and the estimated activity level up to 2025. Possible implications for the preparedness system in the High....... It includes an overview of types of vessels and other objects involved in different activities, and the volume of traffic connected to different types of activities, such as fisheries, petroleum, tourism, navy and research. Furthermore, this report estimates the maritime activity level in the area the next...

  18. 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.

  19. Systems-level organization of non-alcoholic fatty liver disease progression network

    Directory of Open Access Journals (Sweden)

    K. Shubham

    2017-10-01

    Full Text Available Non-Alcoholic Fatty Liver Disease (NAFLD is a hepatic metabolic disorder that is commonly associated with sedentary lifestyle and high fat diets. NAFLD is prevalent in individuals with obesity, insulin resistance and Type 2 Diabetes (T2D. The clinical spectrum of NAFLD ranges from simple steatosis to Non-Alcoholic Steatohepatitis (NASH with fibrosis, which can progress to cirrhosis and hepatocellular carcinoma.The pathogenesis of NAFLD is complex, involving crosstalk between multiple organs, cell-types, and environmental and genetic factors. Dysfunction of White Adipose Tissue (WAT plays a central role in the development of NAFLD and other metabolic disorders. WAT is an active endocrine organ that regulates whole-body energy homeostasis, lipid metabolism, insulin sensitivity and food intake by secreting biologically active molecules (lipokines, adipokines and cytokines. WAT dynamically reacts to nutrient excess or deprivation by remodelling the number (called hyperplasia and/or size (called hypertrophy of adipocytes to store fat or supply nutrients to other tissues by lipolysis, respectively. Adipose tissue remodelling is also accompanied by changes in the composition or function of stromal vascular cells and ECM. The major objective of our study was to identify and characterize the metabolic and signaling modules associated with the progression of NAFLD in the VAT. We performed Weighted Gene Co-expression Network Analysis (WGCNA to organize microarray data obtained from the VAT of patients at different stages of NAFLD into functional modules. In order to obtain insights into the metabolism and its regulation at the genome scale, a co-expression network of metabolic genes in the Human Metabolic Network (HMR2 was constructed and compared with the co-expression network constructed based on all the varying genes. We also used the prior network information on adipocyte metabolism (GEM to verify and extract reporter metabolites. Our analysis revealed

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

    OpenAIRE

    Kaiser, Marcus; Hilgetag, Claus C.

    2010-01-01

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

  1. The European ALARA network. Development, functioning and main activities

    International Nuclear Information System (INIS)

    Schmitt-Hannig, A.

    2009-01-01

    The new ICRP recommendations (ICRP 103), and in particular the detailed treatment of optimisation in the ICRP Publication 101, define optimisation of protection as a source-related process aimed at keeping the likelihood of incurred exposures, the number of people exposed and the magnitude of their individual doses as low as reasonably achievable, also below constraints, taking into account economic and societal factors. Practical implementation and further development of the ALARA principle has been achieved for many years now by the successful cooperation of experts from different European organisations; first as pioneers by establishing the European ALARA Network and then by enthusiastically supporting the activities of the network itself. This contribution presents the evolution, operation and key activities of the European ALARA Network (EAN) in the last years; the successful cooperation of experts from different professional backgrounds, advocating the ALARA principle in a range of radiation protection areas, and contributing to its further development by trading experience and networking. The interaction between the EAN and international organisations, which support the ALARA principle by including relevant activities in their work programmes, is described. (orig.)

  2. Uniqueness, intractability and exact algorithms: reflections on level-k phylogenetic networks

    NARCIS (Netherlands)

    L.J.J. van Iersel (Leo); S.M. Kelk (Steven); M. Mnich

    2009-01-01

    htmlabstractPhylogenetic networks provide a way to describe and visualize evolutionary histories that have undergone so-called reticulate evolutionary events such as recombination, hybridization or horizontal gene transfer. The level k of a network determines how non-treelike the evolution can be,

  3. Higher frequency network activity flow predicts lower frequency node activity in intrinsic low-frequency BOLD fluctuations.

    Science.gov (United States)

    Bajaj, Sahil; Adhikari, Bhim Mani; Dhamala, Mukesh

    2013-01-01

    The brain remains electrically and metabolically active during resting conditions. The low-frequency oscillations (LFO) of the blood oxygen level-dependent (BOLD) signal of functional magnetic resonance imaging (fMRI) coherent across distributed brain regions are known to exhibit features of this activity. However, these intrinsic oscillations may undergo dynamic changes in time scales of seconds to minutes during resting conditions. Here, using wavelet-transform based time-frequency analysis techniques, we investigated the dynamic nature of default-mode networks from intrinsic BOLD signals recorded from participants maintaining visual fixation during resting conditions. We focused on the default-mode network consisting of the posterior cingulate cortex (PCC), the medial prefrontal cortex (mPFC), left middle temporal cortex (LMTC) and left angular gyrus (LAG). The analysis of the spectral power and causal flow patterns revealed that the intrinsic LFO undergo significant dynamic changes over time. Dividing the frequency interval 0 to 0.25 Hz of LFO into four intervals slow-5 (0.01-0.027 Hz), slow-4 (0.027-0.073 Hz), slow-3 (0.073-0.198 Hz) and slow-2 (0.198-0.25 Hz), we further observed significant positive linear relationships of slow-4 in-out flow of network activity with slow-5 node activity, and slow-3 in-out flow of network activity with slow-4 node activity. The network activity associated with respiratory related frequency (slow-2) was found to have no relationship with the node activity in any of the frequency intervals. We found that the net causal flow towards a node in slow-3 band was correlated with the number of fibers, obtained from diffusion tensor imaging (DTI) data, from the other nodes connecting to that node. These findings imply that so-called resting state is not 'entirely' at rest, the higher frequency network activity flow can predict the lower frequency node activity, and the network activity flow can reflect underlying structural

  4. 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.

  5. Implementation of a network level protocol on a GIXINET type local network

    International Nuclear Information System (INIS)

    Loeuillet, J.L.

    1987-11-01

    The installation of a communication system for transferring results from several experiment laboratories to a computing center is described. The objectives of a useful bit rate of 24 kbs, low connection cost and simple infrastructure, extension of the network to 4 buildings situated within a radius of 300m, and connection in the most standardized fashion possible are attained by using the GIXINET local network and adopting the X25 packet protocol. Bit rates of 17.2 kbs for standard 128 octet packets, and 44 kbs for nonstandard packets (776 octets in this case) [fr

  6. Network Resilience Analysis: Review Of Concepts And A Country-Level. Case Study

    Directory of Open Access Journals (Sweden)

    Mariusz Kamola

    2014-01-01

    Full Text Available This paper presents the rationale behind performing an analysis of Internet resilience in the sense of maintaining a connection of autonomous systems in the presence of failures or attacks — on a level of a single country. Next, the graph of a network is constructed that represents interconnections between autonomous systems. The connectivity of the graph is examined for cases of link or node failure. Resilience metrics are proposed, focusing on a single autonomous system or on overall network reliability. The process of geographic location of networking infrastructure is presented, leading to an analysis of network resilience in the case of a joint failure of neighboring autonomous systems.

  7. Associations between Aspects of Friendship Networks, Physical Activity, and Sedentary Behaviour among Adolescents

    Science.gov (United States)

    McCormack, Gavin R.; Nettel-Aguirre, Alberto; Blackstaffe, Anita; Perry, Rosemary; Hawe, Penelope

    2014-01-01

    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. PMID:25328690

  8. 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.

  9. A network-level explanation for the differences in HIV prevalence in ...

    African Journals Online (AJOL)

    A network-level explanation for the differences in HIV prevalence in South Africa's ... or ethnic groups may help explain the differential spread of HIV in South Africa. ... Keywords: concurrency, epidemiology, ethnicity, HIV/AIDS, race, social ...

  10. Development of a Regional Neural Network for Coastal Water Level Predictions

    National Research Council Canada - National Science Library

    Huang, Wenrui; Murray, Catherine; Kraus, Nicholas; Rosati, Julie

    2003-01-01

    .... Fortunately, the US National Oceanographic and Atmospheric Administration (NOAA) has a national network of water level monitoring stations distributed in regional scale that has been operating for several decades...

  11. How Should the Fires Network for the Future Force BDE Level UA be Structured?

    National Research Council Canada - National Science Library

    Ulloa, Juan

    2004-01-01

    ... to all available fires in the area of operations. This monograph constitutes an exploratory study of and preliminary analysis of the effects of networking all available fires at the brigade level UA...

  12. Social networks usage implications at the level of medical services consumption in Romania

    Directory of Open Access Journals (Sweden)

    Daniel Adrian Gardan

    2017-03-01

    The research results reveal key issues from the perspective of emotional involvement within consumption for the patients and the influence of key variables such as level of education, personality and lifestyle within social networks usage context.

  13. Conceptual plan for closer integration of network- and project-level pavement management

    Science.gov (United States)

    1998-01-01

    This report presents an evaluation of current performance modeling concepts and a feasibility study of the possibility of integrating network- and project-level performance prediction. The widely differing modeling methods in use today are reviewed a...

  14. Do low levels of physical activity in female adolescents cause ...

    African Journals Online (AJOL)

    Background. The increase in obesity levels in South African adolescents is attributed to an energy imbalance such that physical inactivity is causally related to adiposity. However, in some settings obesity occurs in spite of high physical activity levels. Objectives. To examine objectively measured physical activity levels of ...

  15. Intrinsic network activity in tinnitus investigated using functional MRI

    Science.gov (United States)

    Leaver, Amber M.; Turesky, Ted K.; Seydell-Greenwald, Anna; Morgan, Susan; Kim, Hung J.; Rauschecker, Josef P.

    2016-01-01

    Tinnitus is an increasingly common disorder in which patients experience phantom auditory sensations, usually ringing or buzzing in the ear. Tinnitus pathophysiology has been repeatedly shown to involve both auditory and non-auditory brain structures, making network-level studies of tinnitus critical. In this magnetic resonance imaging (MRI) study, we used two resting-state functional connectivity (RSFC) approaches to better understand functional network disturbances in tinnitus. First, we demonstrated tinnitus-related reductions in RSFC between specific brain regions and resting-state networks (RSNs), defined by independent components analysis (ICA) and chosen for their overlap with structures known to be affected in tinnitus. Then, we restricted ICA to data from tinnitus patients, and identified one RSN not apparent in control data. This tinnitus RSN included auditory-sensory regions like inferior colliculus and medial Heschl’s gyrus, as well as classically non-auditory regions like the mediodorsal nucleus of the thalamus, striatum, lateral prefrontal and orbitofrontal cortex. Notably, patients’ reported tinnitus loudness was positively correlated with RSFC between the mediodorsal nucleus and the tinnitus RSN, indicating that this network may underlie the auditory-sensory experience of tinnitus. These data support the idea that tinnitus involves network dysfunction, and further stress the importance of communication between auditory-sensory and fronto-striatal circuits in tinnitus pathophysiology. PMID:27091485

  16. 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.

  17. An Experimental Exploration of the Impact of Network-Level Packet Loss on Network Intrusion Detection

    Science.gov (United States)

    2015-08-01

    fast recovery algorithms. Freemont (CA): Internet Engineering Task Force; 1997 Jan. RFC No.: 2001. 2. Smith SC, Hammell RJ, Parker TW, Marvel LM. A...2014. p. 1–6. 3. Sangster B, O’Connor T, Cook T, Fanelli R, Dean E , Adams WJ, Morrell C, Conti G. Toward instrumenting network warfare competitions

  18. Humanitarian Information Management Network Effectiveness: An Analysis at the Organizational and Network Levels

    Science.gov (United States)

    Ngamassi Tchouakeu, Louis-Marie

    2011-01-01

    Massive international response to humanitarian crises such as the South Asian Tsunami in 2004, the Hurricane Katrina in 2005 and the Haiti earthquake in 2010 highlights the importance of humanitarian inter-organizational collaboration networks, especially in information management and exchange. Despite more than a decade old call for more research…

  19. A High-Level Petri Net Framework for Genetic Regulatory Networks

    Directory of Open Access Journals (Sweden)

    Banks Richard

    2007-12-01

    Full Text Available To understand the function of genetic regulatory networks in the development of cellular systems, we must not only realise the individual network entities, but also the manner by which they interact. Multi-valued networks are a promising qualitative approach for modelling such genetic regulatory networks, however, at present they have limited formal analysis techniques and tools. We present a flexible formal framework for modelling and analysing multi-valued genetic regulatory networks using high-level Petri nets and logic minimization techniques. We demonstrate our approach with a detailed case study in which part of the genetic regulatory network responsible for the carbon starvation stress response in Escherichia coli is modelled and analysed. We then compare and contrast this multivalued model to a corresponding Boolean model and consider their formal relationship.

  20. Assessing sensory versus optogenetic network activation by combining (o)fMRI with optical Ca2+ recordings

    Science.gov (United States)

    Schmid, Florian; Wachsmuth, Lydia; Schwalm, Miriam; Prouvot, Pierre-Hugues; Jubal, Eduardo Rosales; Fois, Consuelo; Pramanik, Gautam; Zimmer, Claus; Stroh, Albrecht

    2015-01-01

    Encoding of sensory inputs in the cortex is characterized by sparse neuronal network activation. Optogenetic stimulation has previously been combined with fMRI (ofMRI) to probe functional networks. However, for a quantitative optogenetic probing of sensory-driven sparse network activation, the level of similarity between sensory and optogenetic network activation needs to be explored. Here, we complement ofMRI with optic fiber-based population Ca2+ recordings for a region-specific readout of neuronal spiking activity in rat brain. Comparing Ca2+ responses to the blood oxygenation level-dependent signal upon sensory stimulation with increasing frequencies showed adaptation of Ca2+ transients contrasted by an increase of blood oxygenation level-dependent responses, indicating that the optical recordings convey complementary information on neuronal network activity to the corresponding hemodynamic response. To study the similarity of optogenetic and sensory activation, we quantified the density of cells expressing channelrhodopsin-2 and modeled light propagation in the tissue. We estimated the effectively illuminated volume and numbers of optogenetically stimulated neurons, being indicative of sparse activation. At the functional level, upon either sensory or optogenetic stimulation we detected single-peak short-latency primary Ca2+ responses with similar amplitudes and found that blood oxygenation level-dependent responses showed similar time courses. These data suggest that ofMRI can serve as a representative model for functional brain mapping. PMID:26661247

  1. Assessing sensory versus optogenetic network activation by combining (o)fMRI with optical Ca2+ recordings.

    Science.gov (United States)

    Schmid, Florian; Wachsmuth, Lydia; Schwalm, Miriam; Prouvot, Pierre-Hugues; Jubal, Eduardo Rosales; Fois, Consuelo; Pramanik, Gautam; Zimmer, Claus; Faber, Cornelius; Stroh, Albrecht

    2016-11-01

    Encoding of sensory inputs in the cortex is characterized by sparse neuronal network activation. Optogenetic stimulation has previously been combined with fMRI (ofMRI) to probe functional networks. However, for a quantitative optogenetic probing of sensory-driven sparse network activation, the level of similarity between sensory and optogenetic network activation needs to be explored. Here, we complement ofMRI with optic fiber-based population Ca 2+ recordings for a region-specific readout of neuronal spiking activity in rat brain. Comparing Ca 2+ responses to the blood oxygenation level-dependent signal upon sensory stimulation with increasing frequencies showed adaptation of Ca 2+ transients contrasted by an increase of blood oxygenation level-dependent responses, indicating that the optical recordings convey complementary information on neuronal network activity to the corresponding hemodynamic response. To study the similarity of optogenetic and sensory activation, we quantified the density of cells expressing channelrhodopsin-2 and modeled light propagation in the tissue. We estimated the effectively illuminated volume and numbers of optogenetically stimulated neurons, being indicative of sparse activation. At the functional level, upon either sensory or optogenetic stimulation we detected single-peak short-latency primary Ca 2+ responses with similar amplitudes and found that blood oxygenation level-dependent responses showed similar time courses. These data suggest that ofMRI can serve as a representative model for functional brain mapping. © The Author(s) 2015.

  2. Platelets retain high levels of active plasminogen activator inhibitor 1.

    Directory of Open Access Journals (Sweden)

    Helén Brogren

    Full Text Available The vascular fibrinolytic system is crucial for spontaneous lysis of blood clots. Plasminogen activator inhibitor 1 (PAI-1, the principal inhibitor of the key fibrinolytic enzyme tissue-type plasminogen activator (tPA, is present in platelets at high concentrations. However, the majority of PAI-1 stored in platelets has been considered to be inactive. Our recent finding (Brogren H, et al. Blood 2004 that PAI-1 de novo synthesized in platelets remained active for over 24 h, suggested that PAI-1 stored in the α-granules might be active to a larger extent than previously reported. To re-evaluate this issue, we performed experiments where the fraction of active PAI-1 was estimated by analyzing the tPA-PAI-1 complex formation. In these experiments platelets were lysed with Triton X-100 in the presence of serial dilutions of tPA and subsequently the tPA-PAI-1 complex was evaluated by Western blot. Also, using a non-immunologic assay, tPA was labeled with (125I, and (125I-tPA and (125I-tPA-PAI-1 was quantified by scintigraphy. Interestingly, both methods demonstrated that the majority (>50% of platelet PAI-1 is active. Further analyses suggested that pre-analytical procedures used in previous studies (sonication or freezing/thawing may have substantially reduced the activity of platelet PAI-1, which has lead to an underestimation of the proportion of active PAI-1. Our in vitro results are more compatible with the role of PAI-1 in clot stabilization as demonstrated in physiological and pathophysiological studies.

  3. Comparative, Population-Level Analysis of Social Networks in Organizations

    Science.gov (United States)

    Jacobs, Abigail Z.

    2017-01-01

    As social behavior moves increasingly online, the study of social behavior has followed. Online traces of social systems, whether to study online behavior directly or the online traces of offline activity, have made possible previously unavailable empirical analyses of people, groups and organizations. However, practically observing any social…

  4. Network-level structure-function relationships in human neocortex

    NARCIS (Netherlands)

    Miŝic, Bratislav; Betzel, Richard F.; De Reus, Marcel A.; Van Den Heuvel, Martijn P.; Berman, Marc G.; McIntosh, Anthony R.; Sporns, Olaf

    2016-01-01

    The dynamics of spontaneous fluctuations in neural activity are shaped by underlying patterns of anatomical connectivity. While numerous studies have demonstrated edge-wise correspondence between structural and functional connections, much less is known about how large-scale coherent functional

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

    International Nuclear Information System (INIS)

    Matthews, Warren

    2001-01-01

    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 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

  6. 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.

  7. Generalized activity equations for spiking neural network dynamics

    Directory of Open Access Journals (Sweden)

    Michael A Buice

    2013-11-01

    Full Text Available Much progress has been made in uncovering the computational capabilities of spiking neural networks. However, spiking neurons will always be more expensive to simulate compared to rate neurons because of the inherent disparity in time scales - the spike duration time is much shorter than the inter-spike time, which is much shorter than any learning time scale. In numerical analysis, this is a classic stiff problem. Spiking neurons are also much more difficult to study analytically. One possible approach to making spiking networks more tractable is to augment mean field activity models with some information about spiking correlations. For example, such a generalized activity model could carry information about spiking rates and correlations between spikes self-consistently. Here, we will show how this can be accomplished by constructing a complete formal probabilistic description of the network and then expanding around a small parameter such as the inverse of the number of neurons in the network. The mean field theory of the system gives a rate-like description. The first order terms in the perturbation expansion keep track of covariances.

  8. Analysis of stationary availability factor of two-level backbone computer networks with arbitrary topology

    Science.gov (United States)

    Rahman, P. A.

    2018-05-01

    This scientific paper deals with the two-level backbone computer networks with arbitrary topology. A specialized method, offered by the author for calculation of the stationary availability factor of the two-level backbone computer networks, based on the Markov reliability models for the set of the independent repairable elements with the given failure and repair rates and the methods of the discrete mathematics, is also discussed. A specialized algorithm, offered by the author for analysis of the network connectivity, taking into account different kinds of the network equipment failures, is also observed. Finally, this paper presents an example of calculation of the stationary availability factor for the backbone computer network with the given topology.

  9. AmeriFlux Network Data Activities: updates, progress and plans

    Science.gov (United States)

    Yang, B.; Boden, T.; Krassovski, M.; Song, X.

    2013-12-01

    The Carbon Dioxide Information Analysis Center (CDIAC) at the Oak Ridge National Laboratory serves as the long-term data repository for the AmeriFlux network. Datasets currently available include hourly or half-hourly meteorological and flux observations, biological measurement records, and synthesis data products. In this presentation, we provide an update of this network database including a comprehensive review and evaluation of the biological data from about 70 sites, development of a new product for flux uncertainty estimates, and re-formatting of Level-2 standard files. In 2013, we also provided data support to two synthesis studies --- 2012 drought synthesis and FACE synthesis. Issues related to data quality and solutions in compiling datasets for these synthesis studies will be discussed. We will also present our work plans in developing and producing other high-level products, such as derivation of phenology from the available measurements at flux sites.

  10. 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 las......, energy storage systems, and market participation in both island and grid-connection operation. Finally, control techniques and the principles of energy-storage systems are summarized in a comprehensive flowchart.......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...

  11. Forecasting Flare Activity Using Deep Convolutional Neural Networks

    Science.gov (United States)

    Hernandez, T.

    2017-12-01

    Current operational flare forecasting relies on human morphological analysis of active regions and the persistence of solar flare activity through time (i.e. that the Sun will continue to do what it is doing right now: flaring or remaining calm). In this talk we present the results of applying deep Convolutional Neural Networks (CNNs) to the problem of solar flare forecasting. CNNs operate by training a set of tunable spatial filters that, in combination with neural layer interconnectivity, allow CNNs to automatically identify significant spatial structures predictive for classification and regression problems. We will start by discussing the applicability and success rate of the approach, the advantages it has over non-automated forecasts, and how mining our trained neural network provides a fresh look into the mechanisms behind magnetic energy storage and release.

  12. The effect of the neural activity on topological properties of growing neural networks.

    Science.gov (United States)

    Gafarov, F M; Gafarova, V R

    2016-09-01

    The connectivity structure in cortical networks defines how information is transmitted and processed, and it is a source of the complex spatiotemporal patterns of network's development, and the process of creation and deletion of connections is continuous in the whole life of the organism. In this paper, we study how neural activity influences the growth process in neural networks. By using a two-dimensional activity-dependent growth model we demonstrated the neural network growth process from disconnected neurons to fully connected networks. For making quantitative investigation of the network's activity influence on its topological properties we compared it with the random growth network not depending on network's activity. By using the random graphs theory methods for the analysis of the network's connections structure it is shown that the growth in neural networks results in the formation of a well-known "small-world" network.

  13. Concurrent enterprise: a conceptual framework for enterprise supply-chain network activities

    Science.gov (United States)

    Addo-Tenkorang, Richard; Helo, Petri T.; Kantola, Jussi

    2017-04-01

    Supply-chain management (SCM) in manufacturing industries has evolved significantly over the years. Recently, a lot more relevant research has picked up on the development of integrated solutions. Thus, seeking a collaborative optimisation of geographical, just-in-time (JIT), quality (customer demand/satisfaction) and return-on-investment (profits), aspects of organisational management and planning through 'best practice' business-process management - concepts and application; employing system tools such as certain applications/aspects of enterprise resource planning (ERP) - SCM systems information technology (IT) enablers to enhance enterprise integrated product development/concurrent engineering principles. This article assumed three main organisation theory applications in positioning its assumptions. Thus, proposing a feasible industry-specific framework not currently included within the SCOR model's level four (4) implementation level, as well as other existing SCM integration reference models such as in the MIT process handbook's - Process Interchange Format (PIF), the TOVE project, etc. which could also be replicated in other SCs. However, the wider focus of this paper's contribution will be concentrated on a complimentary proposed framework to the SCC's SCOR reference model. Quantitative empirical closed-ended questionnaires in addition to the main data collected from a qualitative empirical real-life industrial-based pilot case study were used: To propose a conceptual concurrent enterprise framework for SCM network activities. This research adopts a design structure matrix simulation approach analysis to propose an optimal enterprise SCM-networked value-adding, customised master data-management platform/portal for efficient SCM network information exchange and an effective supply-chain (SC) network systems-design teams' structure. Furthermore, social network theory analysis will be employed in a triangulation approach with statistical correlation analysis

  14. Prenatal androgen exposure and children's aggressive behavior and activity level.

    Science.gov (United States)

    Spencer, Debra; Pasterski, Vickie; Neufeld, Sharon; Glover, Vivette; O'Connor, Thomas G; Hindmarsh, Peter C; Hughes, Ieuan A; Acerini, Carlo L; Hines, Melissa

    2017-11-01

    Some human behaviors, including aggression and activity level, differ on average for males and females. Here we report findings from two studies investigating possible relations between prenatal androgen and children's aggression and activity level. For study 1, aggression and activity level scores for 43 girls and 38 boys, aged 4 to 11years, with congenital adrenal hyperplasia (CAH, a genetic condition causing increased adrenal androgen production beginning prenatally) were compared to those of similarly-aged, unaffected relatives (41 girls, 31 boys). Girls with CAH scored higher on aggression than unaffected girls, d=0.69, and unaffected boys scored higher on activity level than unaffected girls, d=0.50. No other group differences were significant. For study 2, the relationship of amniotic fluid testosterone to aggression and activity level was investigated in typically-developing children (48 girls, 44 boys), aged 3 to 5years. Boys scored higher than girls on aggression, d=0.41, and activity level, d=0.50. However, amniotic fluid testosterone was not a significant predictor of aggression or activity level for either sex. The results of the two studies provide some support for an influence of prenatal androgen exposure on children's aggressive behavior, but not activity level. The within-sex variation in amniotic fluid testosterone may not be sufficient to allow reliable assessment of relations to aggression or activity level. Copyright © 2017 Elsevier Inc. All rights reserved.

  15. Multi-agent system based active distribution networks

    OpenAIRE

    Nguyen, H.P.

    2010-01-01

    This thesis gives a particular vision of the future power delivery system with its main requirements. An investigation of suitable concepts and technologies which creates a road map forward the smart grid has been carried out. They should meet the requirements on sustainability, efficiency, flexibility and intelligence. The so called Active Distribution Network (ADN) is introduced as an important element of the future power delivery system. With an open architecture, the ADN is designed to in...

  16. 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.

  17. Recurrently connected and localized neuronal communities initiate coordinated spontaneous activity in neuronal networks

    Science.gov (United States)

    Amin, Hayder; Maccione, Alessandro; Nieus, Thierry

    2017-01-01

    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. PMID:28749937

  18. 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.

  19. 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.

  20. Maturation of Cerebellar Purkinje Cell Population Activity during Postnatal Refinement of Climbing Fiber Network

    Directory of Open Access Journals (Sweden)

    Jean-Marc Good

    2017-11-01

    Full Text Available Neural circuits undergo massive refinements during postnatal development. In the developing cerebellum, the climbing fiber (CF to Purkinje cell (PC network is drastically reshaped by eliminating early-formed redundant CF to PC synapses. To investigate the impact of CF network refinement on PC population activity during postnatal development, we monitored spontaneous CF responses in neighboring PCs and the activity of populations of nearby CF terminals using in vivo two-photon calcium imaging. Population activity is highly synchronized in newborn mice, and the degree of synchrony gradually declines during the first postnatal week in PCs and, to a lesser extent, in CF terminals. Knockout mice lacking P/Q-type voltage-gated calcium channel or glutamate receptor δ2, in which CF network refinement is severely impaired, exhibit an abnormally high level of synchrony in PC population activity. These results suggest that CF network refinement is a structural basis for developmental desynchronization and maturation of PC population activity.

  1. Using Conjugate Gradient Network to Classify Stress Level of Patients.

    Directory of Open Access Journals (Sweden)

    Er. S. Pawar

    2013-02-01

    Full Text Available Diagnosis of stress is important because it can cause many diseases e.g., heart disease, headache, migraine, sleep problems, irritability etc. Diagnosis of stress in patients often involves acquisition of biological signals for example heart rate, electrocardiogram (ECG, electromyography signals (EMG etc. Stress diagnosis using biomedical signals is difficult and since the biomedical signals are too complex to generate any rule an experienced person or expert is needed to determine stress levels. Also, it is not feasible to use all the features that are available or possible to extract from the signal. So, relevant features should be chosen from the extracted features that are capable to diagnose stress. Electronics devices are increasingly being seen in the field of medicine for diagnosis, therapy, checking of stress levels etc. The research and development work of medical electronics engineers leads to the manufacturing of sophisticated diagnostic medical equipment needed to ensure good health care. Biomedical engineering combines the design and problem solving skills of engineering with medical and biological sciences to improve health care diagnosis and treatment.

  2. Polarity-specific high-level information propagation in neural networks.

    Science.gov (United States)

    Lin, Yen-Nan; Chang, Po-Yen; Hsiao, Pao-Yueh; Lo, Chung-Chuan

    2014-01-01

    Analyzing the connectome of a nervous system provides valuable information about the functions of its subsystems. Although much has been learned about the architectures of neural networks in various organisms by applying analytical tools developed for general networks, two distinct and functionally important properties of neural networks are often overlooked. First, neural networks are endowed with polarity at the circuit level: Information enters a neural network at input neurons, propagates through interneurons, and leaves via output neurons. Second, many functions of nervous systems are implemented by signal propagation through high-level pathways involving multiple and often recurrent connections rather than by the shortest paths between nodes. In the present study, we analyzed two neural networks: the somatic nervous system of Caenorhabditis elegans (C. elegans) and the partial central complex network of Drosophila, in light of these properties. Specifically, we quantified high-level propagation in the vertical and horizontal directions: the former characterizes how signals propagate from specific input nodes to specific output nodes and the latter characterizes how a signal from a specific input node is shared by all output nodes. We found that the two neural networks are characterized by very efficient vertical and horizontal propagation. In comparison, classic small-world networks show a trade-off between vertical and horizontal propagation; increasing the rewiring probability improves the efficiency of horizontal propagation but worsens the efficiency of vertical propagation. Our result provides insights into how the complex functions of natural neural networks may arise from a design that allows them to efficiently transform and combine input signals.

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

    Directory of Open Access Journals (Sweden)

    Stephen M Pawson

    Full Text Available 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.

  4. Developing a decision-making framework for levels of logistics outsourcing in food supply chain networks

    NARCIS (Netherlands)

    Hsiao, L.; Vorst, van der J.G.A.J.; Kemp, R.G.M.; Omta, S.W.F.

    2010-01-01

    Purpose – The purpose of this paper is to present a decision-making framework for outsourcing levels of logistics activities. These are: execution level of basic activities (such as transportation, warehousing); value-added activities; planning and control level of activities (such as transportation

  5. Promotion of active ageing combining sensor and social network data.

    Science.gov (United States)

    Bilbao, Aritz; Almeida, Aitor; López-de-Ipiña, Diego

    2016-12-01

    The increase of life expectancy in modern society has caused an increase in elderly population. Elderly people want to live independently in their home environment for as long as possible. However, as we age, our physical skills tend to worsen and our social circle tends to become smaller, something that often leads to a considerable decrease of both our physical and social activities. In this paper, we present an AAL framework developed within the SONOPA project, whose objective is to promote active ageing by combining a social network with information inferred using in-home sensors. Copyright © 2016 Elsevier Inc. All rights reserved.

  6. Systems Biology Graphical Notation: Activity Flow language Level 1 Version 1.2.

    Science.gov (United States)

    Mi, Huaiyu; Schreiber, Falk; Moodie, Stuart; Czauderna, Tobias; Demir, Emek; Haw, Robin; Luna, Augustin; Le Novère, Nicolas; Sorokin, Anatoly; Villéger, Alice

    2015-09-04

    The Systems Biological Graphical Notation (SBGN) is an international community effort for standardized graphical representations of biological pathways and networks. The goal of SBGN is to provide unambiguous pathway and network maps for readers with different scientific backgrounds as well as to support efficient and accurate exchange of biological knowledge between different research communities, industry, and other players in systems biology. Three SBGN languages, Process Description (PD), Entity Relationship (ER) and Activity Flow (AF), allow for the representation of different aspects of biological and biochemical systems at different levels of detail. The SBGN Activity Flow language represents the influences of activities among various entities within a network. Unlike SBGN PD and ER that focus on the entities and their relationships with others, SBGN AF puts the emphasis on the functions (or activities) performed by the entities, and their effects to the functions of the same or other entities. The nodes (elements) describe the biological activities of the entities, such as protein kinase activity, binding activity or receptor activity, which can be easily mapped to Gene Ontology molecular function terms. The edges (connections) provide descriptions of relationships (or influences) between the activities, e.g., positive influence and negative influence. Among all three languages of SBGN, AF is the closest to signaling pathways in biological literature and textbooks, but its well-defined semantics offer a superior precision in expressing biological knowledge.

  7. 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.

  8. Study on application of adaptive fuzzy control and neural network in the automatic leveling system

    Science.gov (United States)

    Xu, Xiping; Zhao, Zizhao; Lan, Weiyong; Sha, Lei; Qian, Cheng

    2015-04-01

    This paper discusses the adaptive fuzzy control and neural network BP algorithm in large flat automatic leveling control system application. The purpose is to develop a measurement system with a flat quick leveling, Make the installation on the leveling system of measurement with tablet, to be able to achieve a level in precision measurement work quickly, improve the efficiency of the precision measurement. This paper focuses on the automatic leveling system analysis based on fuzzy controller, Use of the method of combining fuzzy controller and BP neural network, using BP algorithm improve the experience rules .Construct an adaptive fuzzy control system. Meanwhile the learning rate of the BP algorithm has also been run-rate adjusted to accelerate convergence. The simulation results show that the proposed control method can effectively improve the leveling precision of automatic leveling system and shorten the time of leveling.

  9. Do low levels of physical activity in female adolescents cause ...

    African Journals Online (AJOL)

    Recently Mokabane et al. asserted that black female periurban adolescents exhibited low levels of physical activity and high levels of sedentary behaviour, and that there is a causal, unidirectional, inverse relationship between physical activity and adiposity.[1] However, contrary to their conclusions, the data they presented ...

  10. Deep Recurrent Neural Networks for Human Activity Recognition

    Directory of Open Access Journals (Sweden)

    Abdulmajid Murad

    2017-11-01

    Full Text Available Adopting deep learning methods for human activity recognition has been effective in extracting discriminative features from raw input sequences acquired from body-worn sensors. Although human movements are encoded in a sequence of successive samples in time, typical machine learning methods perform recognition tasks without exploiting the temporal correlations between input data samples. Convolutional neural networks (CNNs address this issue by using convolutions across a one-dimensional temporal sequence to capture dependencies among input data. However, the size of convolutional kernels restricts the captured range of dependencies between data samples. As a result, typical models are unadaptable to a wide range of activity-recognition configurations and require fixed-length input windows. In this paper, we propose the use of deep recurrent neural networks (DRNNs for building recognition models that are capable of capturing long-range dependencies in variable-length input sequences. We present unidirectional, bidirectional, and cascaded architectures based on long short-term memory (LSTM DRNNs and evaluate their effectiveness on miscellaneous benchmark datasets. Experimental results show that our proposed models outperform methods employing conventional machine learning, such as support vector machine (SVM and k-nearest neighbors (KNN. Additionally, the proposed models yield better performance than other deep learning techniques, such as deep believe networks (DBNs and CNNs.

  11. 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.

  12. Deep Recurrent Neural Networks for Human Activity Recognition.

    Science.gov (United States)

    Murad, Abdulmajid; Pyun, Jae-Young

    2017-11-06

    Adopting deep learning methods for human activity recognition has been effective in extracting discriminative features from raw input sequences acquired from body-worn sensors. Although human movements are encoded in a sequence of successive samples in time, typical machine learning methods perform recognition tasks without exploiting the temporal correlations between input data samples. Convolutional neural networks (CNNs) address this issue by using convolutions across a one-dimensional temporal sequence to capture dependencies among input data. However, the size of convolutional kernels restricts the captured range of dependencies between data samples. As a result, typical models are unadaptable to a wide range of activity-recognition configurations and require fixed-length input windows. In this paper, we propose the use of deep recurrent neural networks (DRNNs) for building recognition models that are capable of capturing long-range dependencies in variable-length input sequences. We present unidirectional, bidirectional, and cascaded architectures based on long short-term memory (LSTM) DRNNs and evaluate their effectiveness on miscellaneous benchmark datasets. Experimental results show that our proposed models outperform methods employing conventional machine learning, such as support vector machine (SVM) and k-nearest neighbors (KNN). Additionally, the proposed models yield better performance than other deep learning techniques, such as deep believe networks (DBNs) and CNNs.

  13. Application of neural networks to seismic active control

    International Nuclear Information System (INIS)

    Tang, Yu.

    1995-01-01

    An exploratory study on seismic active control using an artificial neural network (ANN) is presented in which a singledegree-of-freedom (SDF) structural system is controlled by a trained neural network. A feed-forward neural network and the backpropagation training method are used in the study. In backpropagation training, the learning rate is determined by ensuring the decrease of the error function at each training cycle. The training patterns for the neural net are generated randomly. Then, the trained ANN is used to compute the control force according to the control algorithm. The control strategy proposed herein is to apply the control force at every time step to destroy the build-up of the system response. The ground motions considered in the simulations are the N21E and N69W components of the Lake Hughes No. 12 record that occurred in the San Fernando Valley in California on February 9, 1971. Significant reduction of the structural response by one order of magnitude is observed. Also, it is shown that the proposed control strategy has the ability to reduce the peak that occurs during the first few cycles of the time history. These promising results assert the potential of applying ANNs to active structural control under seismic loads

  14. Tunable deformation modes shape contractility in active biopolymer networks

    Science.gov (United States)

    Stam, Samantha; Banerjee, Shiladitya; Weirich, Kim; Freedman, Simon; Dinner, Aaron; Gardel, Margaret

    Biological polymer-based materials remodel under active, molecular motor-driven forces to perform diverse physiological roles, such as force transmission and spatial self-organization. Critical to understanding these biomaterials is elucidating the role of microscopic polymer deformations, such as stretching, bending, buckling, and relative sliding, on material remodeling. Here, we report that the shape of motor-driven deformations can be used to identify microscopic deformation modes and determine how they propagate to longer length scales. In cross-linked actin networks with sufficiently low densities of the motor protein myosin II, microscopic network deformations are predominantly uniaxial, or dominated by sliding. However, longer-wavelength modes are mostly biaxial, or dominated by bending and buckling, indicating that deformations with uniaxial shapes do not propagate across length scales significantly larger than that of individual polymers. As the density of myosin II is increased, biaxial modes dominate on all length scales we examine due to buildup of sufficient stress to produce smaller-wavelength buckling. In contrast, when we construct networks from unipolar, rigid actin bundles, we observe uniaxial, sliding-based contractions on 1 to 100 μm length scales. Our results demonstrate the biopolymer mechanics can be used to tune deformation modes which, in turn, control shape changes in active materials.

  15. Systems Biology Graphical Notation: Activity Flow language Level 1 Version 1.2

    Directory of Open Access Journals (Sweden)

    Mi Huaiyu

    2015-06-01

    Full Text Available The Systems Biological Graphical Notation (SBGN is an international community effort for standardized graphical representations of biological pathways and networks. The goal of SBGN is to provide unambiguous pathway and network maps for readers with different scientific backgrounds as well as to support efficient and accurate exchange of biological knowledge between different research communities, industry, and other players in systems biology. Three SBGN languages, Process Description (PD, Entity Relationship (ER and Activity Flow (AF, allow for the representation of different aspects of biological and biochemical systems at different levels of detail.

  16. Adolescents' social environment and depression: social networks, extracurricular activity, and family relationship influences.

    Science.gov (United States)

    Mason, Michael J; Schmidt, Christopher; Abraham, Anisha; Walker, Leslie; Tercyak, Kenneth

    2009-12-01

    The present study examined components of adolescents' social environment (social network, extracurricular activities, and family relationships) in association with depression. A total of 332 adolescents presenting for a routine medical check-up were self-assessed for social network risk (i.e., smoking habits of best male and female friends), extracurricular activity level (i.e., participation in organized sports teams, clubs, etc.), family relationship quality (i.e., cohesion and conflict), and symptoms of depression (i.e., minimal, mild, moderate/severe). Results of a forward linear regression modeling indicate that social environment components were associated with a significant proportion of the variance in adolescent depression (Adjusted R (2) = .177, p social network (beta = .107, p depression symptoms. Conversely, adolescents who engaged in more extracurricular activities (beta = -.118, p depressive symptoms. These findings highlight the important role that the social environment plays in adolescent depression, as well as yields new insights into socially-based intervention targets that may ameliorate adolescent depression. These intervention targets may be gender-specific, include positive social network skills training, increase adolescents' engagement in organized activities, and attend to the quality of their family relationships.

  17. Model for a flexible motor memory based on a self-active recurrent neural network.

    Science.gov (United States)

    Boström, Kim Joris; Wagner, Heiko; Prieske, Markus; de Lussanet, Marc

    2013-10-01

    Using recent recurrent network architecture based on the reservoir computing approach, we propose and numerically simulate a model that is focused on the aspects of a flexible motor memory for the storage of elementary movement patterns into the synaptic weights of a neural network, so that the patterns can be retrieved at any time by simple static commands. The resulting motor memory is flexible in that it is capable to continuously modulate the stored patterns. The modulation consists in an approximately linear inter- and extrapolation, generating a large space of possible movements that have not been learned before. A recurrent network of thousand neurons is trained in a manner that corresponds to a realistic exercising scenario, with experimentally measured muscular activations and with kinetic data representing proprioceptive feedback. The network is "self-active" in that it maintains recurrent flow of activation even in the absence of input, a feature that resembles the "resting-state activity" found in the human and animal brain. The model involves the concept of "neural outsourcing" which amounts to the permanent shifting of computational load from higher to lower-level neural structures, which might help to explain why humans are able to execute learned skills in a fluent and flexible manner without the need for attention to the details of the movement. Copyright © 2013 Elsevier B.V. All rights reserved.

  18. Energy Efficient Four Level Cooperative Opportunistic Communication for Wireless Personal Area Networks (WPAN)

    DEFF Research Database (Denmark)

    Rohokale, Vandana M.; Inamdar, Sandeep; Prasad, Neeli R.

    2013-01-01

    For wireless sensor networks (WSN),energy is a scarce resource. Due to limited battery resources, the energy consumption is the critical issue for the transmission as well as reception of the signals in the wireless communication. WSNs are infrastructure-less shared network demanding more energy...... consumption due to collaborative transmissions. This paper proposes a new cooperative opportunistic four level model for IEEE 802.15.4 Wireless Personal Area Network (WPAN).The average per node energy consumption is observed merely about 0.17mJ for the cooperative wireless communication which proves...... the proposed mechanism to be energy efficient. This paper further proposes four levels of cooperative data transmission from source to destination to improve network coverage with energy efficiency....

  19. A BHR Composite Network-Based Visualization Method for Deformation Risk Level of Underground Space.

    Directory of Open Access Journals (Sweden)

    Wei Zheng

    Full Text Available This study proposes a visualization processing method for the deformation risk level of underground space. The proposed method is based on a BP-Hopfield-RGB (BHR composite network. Complex environmental factors are integrated in the BP neural network. Dynamic monitoring data are then automatically classified in the Hopfield network. The deformation risk level is combined with the RGB color space model and is displayed visually in real time, after which experiments are conducted with the use of an ultrasonic omnidirectional sensor device for structural deformation monitoring. The proposed method is also compared with some typical methods using a benchmark dataset. Results show that the BHR composite network visualizes the deformation monitoring process in real time and can dynamically indicate dangerous zones.

  20. Integrating Micro-level Interactions with Social Network Analysis in Tie Strength Research

    DEFF Research Database (Denmark)

    Torre, Osku; Gupta, Jayesh Prakash; Kärkkäinen, Hannu

    2017-01-01

    of tie strength based on reciprocal interaction from publicly available Facebook data, and suggest that this approach could work as a basis for further tie strength studies. Our approach makes use of weak tie theory, and enables researchers to study micro-level interactions (i.e. discussions, messages......A social tie is a target for ongoing, high-level scientific debate. Measuring the tie strength in social networks has been an important topic for academic studies since Mark Granovetter's seminal papers in 1970's. However, it is still a problematic issue mainly for two reasons: 1) existing tie...... strengthening process in online social networks. Therefore, we suggest a new approach to tie strength research, which focuses on studying communication patterns (edges) more rather than actors (nodes) in a social network. In this paper we build a social network analysis-based approach to enable the evaluation...

  1. Eleven years of net network research activity - inr contributions

    International Nuclear Information System (INIS)

    Deaconu, V.; Ionita, I.; Meleg, T.; Deaconu, M.; Truta, C.; Oncioiu, G.

    2013-01-01

    The European Network on Neutron Techniques Standardization for Structural Integrity (NeT) was established in 2002, grouping institutions from industry, research and academic media. Coordinated by the European Commission.s Joint Research Centre, the main mission of this network is to develop experimental and numerical techniques and standards for the reliable characterisation of residual stresses in structural welds. Each problem is tackled by creating a dedicated Task Group which manages measurement and modelling round robin studies and undertakes a thorough analysis and interpretation of the results. Over forty institutions are active NeT partners, their specific involvement and contributions being summarised in this paper. The Institute for Nuclear Research Pitesti (INR) is one of NeT founders and its contribution is related to numerical modelling, specimen analysis, material characterisation, data analysis or SANS support. This is also emphasised throughout this paper, together with the specific NeT research topics presentation. (authors)

  2. Three-Level Z-Source Inverters Using a Single LC Impedance Network

    DEFF Research Database (Denmark)

    Loh, Poh Chiang; Lim, Sok Wei; Gao, Feng

    2007-01-01

    two LC impedance networks and two isolated dc sources, which can significantly increase the overall system cost and require a more complex modulator for balancing the network inductive voltage boosting. Offering a number of less costly alternatives, this letter presents the design and control of two...... three-level Z-source inverters, whose output voltage can be stepped down or up using only a single LC impedance network connected between the dc input source and either a neutral-point-clamped (NPC) or dc-link cascaded inverter circuitry. Through careful design of their modulation scheme, both inverters...

  3. Risk Evaluation of Railway Coal Transportation Network Based on Multi Level Grey Evaluation Model

    Science.gov (United States)

    Niu, Wei; Wang, Xifu

    2018-01-01

    The railway transport mode is currently the most important way of coal transportation, and now China’s railway coal transportation network has become increasingly perfect, but there is still insufficient capacity, some lines close to saturation and other issues. In this paper, the theory and method of risk assessment, analytic hierarchy process and multi-level gray evaluation model are applied to the risk evaluation of coal railway transportation network in China. Based on the example analysis of Shanxi railway coal transportation network, to improve the internal structure and the competitiveness of the market.

  4. Identification of Pavement Distress Types and Pavement Condition Evaluation Based on Network Level Inspection for Jazan City Road Network

    Directory of Open Access Journals (Sweden)

    M Mubaraki

    2014-06-01

    Full Text Available The first step in establishing a pavement management system (PMS is road network identification. An important feature of a PMS is the ability to determine the current condition of a road network and predict its future condition. Pavement condition evaluation may involve structure, roughness, surface distress, and safety evaluation. In this study, a pavement distress condition rating procedure was used to achieve the objectives of this study. The main objectives of this study were to identify the common types of distress that exist on the Jazan road network (JRN, either on main roads or secondary roads, and to evaluate the pavement condition based on network level inspection. The study was conducted by collecting pavement distress types from 227 sample units on main roads and 500 sample units from secondary roads. Data were examined through analysis of common types of distress identified in both main and secondary roads. Through these data, pavement condition index (PCI for each sample unit was then calculated. Through these calculations, average PCIs for the main and secondary roads were determined. Results indicated that the most common pavement distress types on main roads were patching and utility cut patching, longitudinal and transverse cracking, polished aggregate, weathering and raveling, and alligator cracking. The most common pavement distress types on secondary roads were weathering and raveling, patching and utility cut patching, longitudinal and transverse cracking, potholes, and alligator cracking. The results also indicated that 65% of Jazan's main road network has an average pavement condition rating of very good while only 30% of Jazan's secondary roads network has an average pavement condition.

  5. Analysis on the University’s Network Security Level System in the Big Data Era

    Science.gov (United States)

    Li, Tianli

    2017-12-01

    The rapid development of science and technology, the continuous expansion of the scope of computer network applications, has gradually improved the social productive forces, has had a positive impact on the increase production efficiency and industrial scale of China's different industries. Combined with the actual application of computer network in the era of large data, we can see the existence of influencing factors such as network virus, hacker and other attack modes, threatening network security and posing a potential threat to the safe use of computer network in colleges and universities. In view of this unfavorable development situation, universities need to pay attention to the analysis of the situation of large data age, combined with the requirements of network security use, to build a reliable network space security system from the equipment, systems, data and other different levels. To avoid the security risks exist in the network. Based on this, this paper will analyze the hierarchical security system of cyberspace security in the era of large data.

  6. The Use of Meta-Level Control for Coordination in a Distributed Problem Solving Network,

    Science.gov (United States)

    1983-01-01

    crucial aspect of the design organizational structuring in coordinating the local activity of achs decentralized network control policies. It is...TEMTED EXflD.MENTS WITn and ratings of the subgoals." Threshold values indicating ORGANIZATIONAL STRUCIURING IkeA usaw lani of a subal are specif’ied in...the monitoring are. This environmental vehicle, approximate position, time frame, and belief. The scenario was designed to test the networks ability

  7. 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.

  8. Towards a new paradigm: Activity level balanced sustainability reporting.

    Science.gov (United States)

    Samudhram, Ananda; Siew, Eu-Gene; Sinnakkannu, Jothee; Yeow, Paul H P

    2016-11-01

    Technoeconomic paradigms based economic growth theories suggest that waves of technological innovations drove the economic growth of advanced economies. Widespread economic degradation and pollution is an unintended consequence of such growth. Tackling environmental and social issues at firm levels would help us to overcome such issues at macro-levels. Consequently, the Triple Bottom Line (TBL) reporting approach promotes firm level economic, environmental and social performances. Incorporating Zink's (2014) 3-pillar presentation model, this paper indicates that economic, social and environmental performances tend to be reported at firm level. All three pillars are not covered evenly at the activity levels. Thus, a loophole is identified whereby excellent environmental performance at activity levels could potentially leave poor social performance undisclosed. A refinement of the TBL paradigm, whereby all three pillars are covered at the activity level, is suggested, to enhance sustainability reporting. Copyright © 2016 Elsevier Ltd. All rights reserved.

  9. The perceived constraints, motivation, and physical activity levels of ...

    African Journals Online (AJOL)

    The purpose of this research was threefold; Are Korean youth physically active to promote health during leisure time? What constraints to physical active do youth experience during leisure time? Are there relationships among constraints, motivation, and physical activity level? Of 1 280 youth randomly selected by a ...

  10. Predictive functional control for active queue management in congested TCP/IP networks.

    Science.gov (United States)

    Bigdeli, N; Haeri, M

    2009-01-01

    Predictive functional control (PFC) as a new active queue management (AQM) method in dynamic TCP networks supporting explicit congestion notification (ECN) is proposed. The ability of the controller in handling system delay along with its simplicity and low computational load makes PFC a privileged AQM method in the high speed networks. Besides, considering the disturbance term (which represents model/process mismatches, external disturbances, and existing noise) in the control formulation adds some level of robustness into the PFC-AQM controller. This is an important and desired property in the control of dynamically-varying computer networks. In this paper, the controller is designed based on a small signal linearized fluid-flow model of the TCP/AQM networks. Then, closed-loop transfer function representation of the system is derived to analyze the robustness with respect to the network and controller parameters. The analytical as well as the packet-level ns-2 simulation results show the out-performance of the developed controller for both queue regulation and resource utilization. Fast response, low queue fluctuations (and consequently low delay jitter), high link utilization, good disturbance rejection, scalability, and low packet marking probability are other features of the developed method with respect to other well-known AQM methods such as RED, PI, and REM which are also simulated for comparison.

  11. Analysis of the error of the developed method of determination the active conductivity reducing the insulation level between one phase of the network and ground, and insulation parameters in a non-symmetric network with isolated neutral with voltage above 1000 V

    Science.gov (United States)

    Utegulov, B. B.

    2018-02-01

    In the work the study of the developed method was carried out for reliability by analyzing the error in indirect determination of the insulation parameters in an asymmetric network with an isolated neutral voltage above 1000 V. The conducted studies of the random relative mean square errors show that the accuracy of indirect measurements in the developed method can be effectively regulated not only by selecting a capacitive additional conductivity, which are connected between phases of the electrical network and the ground, but also by the selection of measuring instruments according to the accuracy class. When choosing meters with accuracy class of 0.5 with the correct selection of capacitive additional conductivity that are connected between the phases of the electrical network and the ground, the errors in measuring the insulation parameters will not exceed 10%.

  12. The importance of delineating networks by activity type in bottlenose dolphins (Tursiops truncatus) in Cedar Key, Florida.

    Science.gov (United States)

    Gazda, Stefanie; Iyer, Swami; Killingback, Timothy; Connor, Richard; Brault, Solange

    2015-03-01

    Network analysis has proved to be a valuable tool for studying the behavioural patterns of complex social animals. Often such studies either do not distinguish between different behavioural states of the organisms or simply focus attention on a single behavioural state to the exclusion of all others. In either of these approaches it is impossible to ascertain how the behavioural patterns of individuals depend on the type of activity they are engaged in. Here we report on a network-based analysis of the behavioural associations in a population of bottlenose dolphins (Tursiops truncatus) in Cedar Key, Florida. We consider three distinct behavioural states-socializing, travelling and foraging-and analyse the association networks corresponding to each activity. Moreover, in constructing the different activity networks we do not simply record a spatial association between two individuals as being either present or absent, but rather quantify the degree of any association, thus allowing us to construct weighted networks describing each activity. The results of these weighted activity networks indicate that networks can reveal detailed patterns of bottlenose dolphins at the population level; dolphins socialize in large groups with preferential associations; travel in small groups with preferential associates; and spread out to forage in very small, weakly connected groups. There is some overlap in the socialize and travel networks but little overlap between the forage and other networks. This indicates that the social bonds maintained in other activities are less important as they forage on dispersed, solitary prey. The overall network, not sorted by activity, does not accurately represent any of these patterns.

  13. Sea Levels Online: Sea Level Variations of the United States Derived from National Water Level Observation Network Stations

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Water level records are a combination of the fluctuations of the ocean and the vertical land motion at the location of the station. Monthly mean sea level (MSL)...

  14. Wireless sensor networks for active vibration control in automobile structures

    International Nuclear Information System (INIS)

    Mieyeville, Fabien; Navarro, David; Du, Wan; Ichchou, Mohamed; Scorletti, Gérard

    2012-01-01

    Wireless sensor networks (WSNs) are nowadays widely used in monitoring and tracking applications. This paper presents the feasibility of using WSNs in active vibration control strategies. The method employed here involves active-structural acoustic control using piezoelectric sensors distributed on a car structure. This system aims at being merged with a WSN whose head node collects data and processes control laws so as to command piezoelectric actuators wisely placed on the structure. We will study the feasibility of implementing WSNs in active vibration control and introduce a complete design methodology to optimize hardware/software and control law synergy in mechatronic systems. A design space exploration will be conducted so as to identify the best WSN platform and the resulting impact on control. (paper)

  15. Ferromagnetic interaction model of activity level in workplace communication

    Science.gov (United States)

    Akitomi, Tomoaki; Ara, Koji; Watanabe, Jun-ichiro; Yano, Kazuo

    2013-03-01

    The nature of human-human interaction, specifically, how people synchronize with each other in multiple-participant conversations, is described by a ferromagnetic interaction model of people’s activity levels. We found two microscopic human interaction characteristics from a real-environment face-to-face conversation. The first characteristic is that people quite regularly synchronize their activity level with that of the other participants in a conversation. The second characteristic is that the degree of synchronization increases as the number of participants increases. Based on these microscopic ferromagnetic characteristics, a “conversation activity level” was modeled according to the Ising model. The results of a simulation of activity level based on this model well reproduce macroscopic experimental measurements of activity level. This model will give a new insight into how people interact with each other in a conversation.

  16. Active Crohn's disease is associated with low vitamin D levels

    DEFF Research Database (Denmark)

    Jørgensen, Søren Peter; Hvas, Christian Lodberg; Agnholt, Jørgen

    2013-01-01

    activity is associated with low vitamin D levels. METHODS: In a cross-sectional study of 182 CD patients and 62 healthy controls, we measured serum 25-OH vitamin D. Stratified analysis was used to compare 25-OH vitamin D levels with Crohn's disease activity index, C-reactive protein, smoking status, intake...... of oral vitamin D supplements and seasonal variation in CD patients and healthy controls. RESULTS: Serum 25-OH vitamin D was inversely associated with disease activity: Median 25-OH vitamin D levels of Crohn's disease in remission, mildly, and moderately active diseases evaluated by Crohn's disease...... D levels (51nmol/l) than patients who did not smoke (76nmol/l), plevels. CONCLUSIONS: Active Crohn's disease was associated with low serum 25-OH vitamin D. Patients who smoked had lower 25-OH...

  17. Randomization and resilience of brain functional networks as systems-level endophenotypes of schizophrenia.

    Science.gov (United States)

    Lo, Chun-Yi Zac; Su, Tsung-Wei; Huang, Chu-Chung; Hung, Chia-Chun; Chen, Wei-Ling; Lan, Tsuo-Hung; Lin, Ching-Po; Bullmore, Edward T

    2015-07-21

    Schizophrenia is increasingly conceived as a disorder of brain network organization or dysconnectivity syndrome. Functional MRI (fMRI) networks in schizophrenia have been characterized by abnormally random topology. We tested the hypothesis that network randomization is an endophenotype of schizophrenia and therefore evident also in nonpsychotic relatives of patients. Head movement-corrected, resting-state fMRI data were acquired from 25 patients with schizophrenia, 25 first-degree relatives of patients, and 29 healthy volunteers. Graphs were used to model functional connectivity as a set of edges between regional nodes. We estimated the topological efficiency, clustering, degree distribution, resilience, and connection distance (in millimeters) of each functional network. The schizophrenic group demonstrated significant randomization of global network metrics (reduced clustering, greater efficiency), a shift in the degree distribution to a more homogeneous form (fewer hubs), a shift in the distance distribution (proportionally more long-distance edges), and greater resilience to targeted attack on network hubs. The networks of the relatives also demonstrated abnormal randomization and resilience compared with healthy volunteers, but they were typically less topologically abnormal than the patients' networks and did not have abnormal connection distances. We conclude that schizophrenia is associated with replicable and convergent evidence for functional network randomization, and a similar topological profile was evident also in nonpsychotic relatives, suggesting that this is a systems-level endophenotype or marker of familial risk. We speculate that the greater resilience of brain networks may confer some fitness advantages on nonpsychotic relatives that could explain persistence of this endophenotype in the population.

  18. Damage Level Prediction of Reinforced Concrete Building Based on Earthquake Time History Using Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Suryanita Reni

    2017-01-01

    Full Text Available The strong motion earthquake could cause the building damage in case of the building not considered in the earthquake design of the building. The study aims to predict the damage-level of building due to earthquake using Artificial Neural Networks method. The building model is a reinforced concrete building with ten floors and height between floors is 3.6 m. The model building received a load of the earthquake based on nine earthquake time history records. Each time history scaled to 0,5g, 0,75g, and 1,0g. The Artificial Neural Networks are designed in 4 architectural models using the MATLAB program. Model 1 used the displacement, velocity, and acceleration as input and Model 2 used the displacement only as the input. Model 3 used the velocity as input, and Model 4 used the acceleration just as input. The output of the Neural Networks is the damage level of the building with the category of Safe (1, Immediate Occupancy (2, Life Safety (3 or in a condition of Collapse Prevention (4. According to the results, Neural Network models have the prediction rate of the damage level between 85%-95%. Therefore, one of the solutions for analyzing the structural responses and the damage level promptly and efficiently when the earthquake occurred is by using Artificial Neural Network

  19. Moving Target Detection and Active Tracking with a Multicamera Network

    Directory of Open Access Journals (Sweden)

    Long Zhao

    2014-01-01

    Full Text Available We propose a systematic framework for Intelligence Video Surveillance System (IVSS with a multicamera network. The proposed framework consists of low-cost static and PTZ cameras, target detection and tracking algorithms, and a low-cost PTZ camera feedback control algorithm based on target information. The target detection and tracking is realized by fixed cameras using a moving target detection and tracking algorithm; the PTZ camera is manoeuvred to actively track the target from the tracking results of the static camera. The experiments are carried out using practical surveillance system data, and the experimental results show that the systematic framework and algorithms presented in this paper are efficient.

  20. 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...... 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...

  1. Oscillatory activity in neocortical networks during tactile discrimination near the limit of spatial acuity.

    Science.gov (United States)

    Adhikari, Bhim M; Sathian, K; Epstein, Charles M; Lamichhane, Bidhan; Dhamala, Mukesh

    2014-05-01

    Oscillatory interactions within functionally specialized but distributed brain regions are believed to be central to perceptual and cognitive functions. Here, using human scalp electroencephalography (EEG) recordings combined with source reconstruction techniques, we study how oscillatory activity functionally organizes different neocortical regions during a tactile discrimination task near the limit of spatial acuity. While undergoing EEG recordings, blindfolded participants felt a linear three-dot array presented electromechanically, under computer control, and reported whether the central dot was offset to the left or right. The average brain response differed significantly for trials with correct and incorrect perceptual responses in the timeframe approximately between 130 and 175ms. During trials with correct responses, source-level peak activity appeared in the left primary somatosensory cortex (SI) at around 45ms, in the right lateral occipital complex (LOC) at 130ms, in the right posterior intraparietal sulcus (pIPS) at 160ms, and finally in the left dorsolateral prefrontal cortex (dlPFC) at 175ms. Spectral interdependency analysis of activity in these nodes showed two distinct distributed networks, a dominantly feedforward network in the beta band (12-30Hz) that included all four nodes and a recurrent network in the gamma band (30-100Hz) that linked SI, pIPS and dlPFC. Measures of network activity in both bands were correlated with the accuracy of task performance. These findings suggest that beta and gamma band oscillatory networks coordinate activity between neocortical regions mediating sensory and cognitive processing to arrive at tactile perceptual decisions. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

  2. The impact of pregnancy on physical activity level.

    Science.gov (United States)

    Fell, Deshayne B; Joseph, K S; Armson, B Anthony; Dodds, Linda

    2009-09-01

    The purpose of this study was to compare women's levels of physical activity during early pregnancy and during the year before pregnancy, and to identify characteristics associated with discontinuing sports and exercise among women previously active during the year before pregnancy. Data collected from 1,737 women enrolled in a prospective cohort study and who had no contraindications for exercise were included in this analysis. Measures of physical activity (including household and care-giving activities, active living and sports and exercise activities) during early pregnancy were compared to the year before pregnancy. Log binomial regression was used to identify factors associated with discontinuing sports and exercise during pregnancy. There was a statistically significant decrease in all summary measures of physical activity during early pregnancy. The largest decreases were observed in sports and exercise activity. Among women active before pregnancy, age pregnancy body mass index (BMI) > or = 30 kg/m(2) and lower levels of pre-pregnancy exercise were associated with discontinuing sports and exercise activities during pregnancy. Most women reduced their physical activity level during the first 20 weeks of pregnancy compared with their level of activity during the year prior to pregnancy, particularly for sports and exercise, although a small proportion of women in this study actually increased their activity in this area during early pregnancy. Participation in sports and exercise activity during pregnancy is potentially modifiable and could favorably impact perinatal health and maternal post-partum weight. The results of this study suggests that pregnancy is an event that leads to a decrease in physical activity.

  3. Altered Brain Network in Amyotrophic Lateral Sclerosis: A Resting Graph Theory-Based Network Study at Voxel-Wise Level.

    Science.gov (United States)

    Zhou, Chaoyang; Hu, Xiaofei; Hu, Jun; Liang, Minglong; Yin, Xuntao; Chen, Lin; Zhang, Jiuquan; Wang, Jian

    2016-01-01

    Amyotrophic lateral sclerosis (ALS) is a rare degenerative disorder characterized by loss of upper and lower motor neurons. Neuroimaging has provided noticeable evidence that ALS is a complex disease, and shown that anatomical and functional lesions extend beyond precentral cortices and corticospinal tracts, to include the corpus callosum; frontal, sensory, and premotor cortices; thalamus; and midbrain. The aim of this study is to investigate graph theory-based functional network abnormalities at voxel-wise level in ALS patients on a whole brain scale. Forty-three ALS patients and 44 age- and sex-matched healthy volunteers were enrolled. The voxel-wise network degree centrality (DC), a commonly employed graph-based measure of network organization, was used to characterize the alteration of whole brain functional network. Compared with the controls, the ALS patients showed significant increase of DC in the left cerebellum posterior lobes, bilateral cerebellum crus, bilateral occipital poles, right orbital frontal lobe, and bilateral prefrontal lobes; significant decrease of DC in the bilateral primary motor cortex, bilateral sensory motor region, right prefrontal lobe, left bilateral precuneus, bilateral lateral temporal lobes, left cingulate cortex, and bilateral visual processing cortex. The DC's z-scores of right inferior occipital gyrus were significant negative correlated with the ALSFRS-r scores. Our findings confirm that the regions with abnormal network DC in ALS patients were located in multiple brain regions including primary motor, somatosensory and extra-motor areas, supporting the concept that ALS is a multisystem disorder. Specifically, our study found that DC in the visual areas was altered and ALS patients with higher DC in right inferior occipital gyrus have more severity of disease. The result demonstrated that the altered DC value in this region can probably be used to assess severity of ALS.

  4. Altered brain network in Amyotrophic Lateral Sclerosis: a resting graph theory-based network study at voxel-wise level

    Directory of Open Access Journals (Sweden)

    Chaoyang eZhou

    2016-05-01

    Full Text Available Amyotrophic lateral sclerosis (ALS is a rare degenerative disorder characterized by loss of upper and lower motor neurons. Neuroimaging has provided noticeable evidence that ALS is a complex disease, and shown that anatomical and functional lesions extend beyond precentral cortices and corticospinal tracts, to include the corpus callosum; frontal, sensory, and premotor cortices; thalamus; and midbrain. The aim of this study is to investigate graph theory-based functional network abnormalities at voxel-wise level in ALS patients on a whole brain scale. Forty-three ALS patients and 44 age- and sex- matched healthy volunteers were enrolled. The voxel-wise network degree centrality (DC, a commonly employed graph-based measure of network organization, was used to characterize the alteration of whole brain functional network. Compared with the controls, the ALS patients showed significant increase of DC in the left cerebellum posterior lobes, bilateral cerebellum crus, bilateral occipital poles, right orbital frontal lobe and bilateral prefrontal lobes; significant decrease of DC in the bilateral primary motor cortex, bilateral sensory motor region, right prefrontal lobe, left bilateral precuneus, bilateral lateral temporal lobes, left cingulate cortex, and bilateral visual processing cortex. The DC’s z-scores of right inferior occipital gyrus were significant negative correlated with the ALSFRS-r scores. Our findings confirm that the regions with abnormal network DC in ALS patients were located in multiple brain regions including primary motor, somatosensory and extra-motor areas, supporting the concept that ALS is a multisystem disorder. Specifically, our study found that DC in the visual areas was altered and ALS patients with higher DC in right inferior occipital gyrus have more severity of disease. The result demonstrated that the altered DC value in this region can probably be used to assess severity of ALS.

  5. 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.

  6. Evaluating C-RAN Fronthaul Functional Splits in Terms of Network Level Energy and Cost Savings

    DEFF Research Database (Denmark)

    Checko, Aleksandra; Popovska Avramova, Andrijana; Berger, Michael Stübert

    2016-01-01

    The placement of the complete baseband processing in a centralized pool results in high data rate requirement and inflexibility of the fronthaul network, which challenges the energy and cost effectiveness of the cloud radio access network (C-RAN). Recently, redesign of the C-RAN through functional...... split in the baseband processing chain has been proposed to overcome these challenges. This paper evaluates, by mathematical and simulation methods, different splits with respect to network level energy and cost efficiency having in the mind the expected quality of service.The proposed mathematical...... model quantifies the multiplexing gains and the trade-offs between centralization and decentralization concerning the cost of the pool, fronthaul network capacity and resource utilization. The event-based simulation captures the influence of the traffic load dynamics and traffic type variation...

  7. The effect of increasing levels of embedded generation on the distribution network. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Collinson, A; Earp, G K; Howson, D; Owen, R D; Wright, A J

    1999-10-01

    This report was commissioned as part of the EA Technology Strategic Technology Programme under guidance of the Module 5 (Embedded Generation) Steering Group. This report aims to provide information related to the distribution and supply of electricity in the context of increasing levels of embedded generation. There is a brief description of the operating environment within which electricity companies in the UK must operate. Technical issues related to the connection of generation to the existing distribution infrastructure are highlighted and the design philosophy adopted by network designers in accommodating applications for the connection of embedded generation to the network is discussed. The effects embedded generation has on the network and the issues raised are presented as many of them present barriers to the connection of embedded generators. The final chapters cover the forecast of required connection to 2010 and solutions to restrictions preventing the connection of more embedded generation to the network. (author)

  8. DReAM: Demand Response Architecture for Multi-level District Heating and Cooling Networks

    Energy Technology Data Exchange (ETDEWEB)

    Bhattacharya, Saptarshi; Chandan, Vikas; Arya, Vijay; Kar, Koushik

    2017-05-19

    In this paper, we exploit the inherent hierarchy of heat exchangers in District Heating and Cooling (DHC) networks and propose DReAM, a novel Demand Response (DR) architecture for Multi-level DHC networks. DReAM serves to economize system operation while still respecting comfort requirements of individual consumers. Contrary to many present day DR schemes that work on a consumer level granularity, DReAM works at a level of hierarchy above buildings, i.e. substations that supply heat to a group of buildings. This improves the overall DR scalability and reduce the computational complexity. In the first step of the proposed approach, mathematical models of individual substations and their downstream networks are abstracted into appropriately constructed low-complexity structural forms. In the second step, this abstracted information is employed by the utility to perform DR optimization that determines the optimal heat inflow to individual substations rather than buildings, in order to achieve the targeted objectives across the network. We validate the proposed DReAM framework through experimental results under different scenarios on a test network.

  9. An Integrative Bioinformatics Framework for Genome-scale Multiple Level Network Reconstruction of Rice

    Directory of Open Access Journals (Sweden)

    Liu Lili

    2013-06-01

    Full Text Available Understanding how metabolic reactions translate the genome of an organism into its phenotype is a grand challenge in biology. Genome-wide association studies (GWAS statistically connect genotypes to phenotypes, without any recourse to known molecular interactions, whereas a molecular mechanistic description ties gene function to phenotype through gene regulatory networks (GRNs, protein-protein interactions (PPIs and molecular pathways. Integration of different regulatory information levels of an organism is expected to provide a good way for mapping genotypes to phenotypes. However, the lack of curated metabolic model of rice is blocking the exploration of genome-scale multi-level network reconstruction. Here, we have merged GRNs, PPIs and genome-scale metabolic networks (GSMNs approaches into a single framework for rice via omics’ regulatory information reconstruction and integration. Firstly, we reconstructed a genome-scale metabolic model, containing 4,462 function genes, 2,986 metabolites involved in 3,316 reactions, and compartmentalized into ten subcellular locations. Furthermore, 90,358 pairs of protein-protein interactions, 662,936 pairs of gene regulations and 1,763 microRNA-target interactions were integrated into the metabolic model. Eventually, a database was developped for systematically storing and retrieving the genome-scale multi-level network of rice. This provides a reference for understanding genotype-phenotype relationship of rice, and for analysis of its molecular regulatory network.

  10. Neural Network with Local Memory for Nuclear Reactor Power Level Control

    International Nuclear Information System (INIS)

    Uluyol, Oender; Ragheb, Magdi; Tsoukalas, Lefteri

    2001-01-01

    A methodology is introduced for a neural network with local memory called a multilayered local output gamma feedback (LOGF) neural network within the paradigm of locally-recurrent globally-feedforward neural networks. It appears to be well-suited for the identification, prediction, and control tasks in highly dynamic systems; it allows for the presentation of different timescales through incorporation of a gamma memory. A learning algorithm based on the backpropagation-through-time approach is derived. The spatial and temporal weights of the network are iteratively optimized for a given problem using the derived learning algorithm. As a demonstration of the methodology, it is applied to the task of power level control of a nuclear reactor at different fuel cycle conditions. The results demonstrate that the LOGF neural network controller outperforms the classical as well as the state feedback-assisted classical controllers for reactor power level control by showing a better tracking of the demand power, improving the fuel and exit temperature responses, and by performing robustly in different fuel cycle and power level conditions

  11. Network analysis of inter-organizational relationships and policy use among active living organizations in Alberta, Canada.

    Science.gov (United States)

    Loitz, Christina C; Stearns, Jodie A; Fraser, Shawn N; Storey, Kate; Spence, John C

    2017-08-09

    Coordinated partnerships and collaborations can optimize the efficiency and effectiveness of service and program delivery in organizational networks. However, the extent to which organizations are working together to promote physical activity, and use physical activity policies in Canada, is unknown. This project sought to provide a snapshot of the funding, coordination and partnership relationships among provincial active living organizations (ALOs) in Alberta, Canada. Additionally, the awareness, and use of the provincial policy and national strategy by the organizations was examined. Provincial ALOs (N = 27) answered questions regarding their funding, coordination and partnership connections with other ALOs in the network. Social network analysis was employed to examine network structure and position of each ALO. Discriminant function analysis determined the extent to which degree centrality was associated with the use of the Active Alberta (AA) policy and Active Canada 20/20 (AC 20/20) strategy. The funding network had a low density level (density = .20) and was centralized around Alberta Tourism Parks and Recreation (ATPR; degree centralization = 48.77%, betweenness centralization = 32.43%). The coordination network had a moderate density level (density = .31), and was low-to-moderately centralized around a few organizations (degree centralization = 45.37%, betweenness centrality = 19.92%). The partnership network had a low density level (density = .15), and was moderate-to-highly centralized around ATPR. Most organizations were aware of AA (89%) and AC 20/20 (78%), however more were using AA (67%) compared to AC 20/20 (33%). Central ALOs in the funding network were more likely to use AA and AC 20/20. Central ALOs in the coordination network were more likely to use AC 20/20, but not AA. Increasing formal and informal relationships between organizations and integrating disconnected or peripheral organizations could increase the capacity of the

  12. Network analysis of inter-organizational relationships and policy use among active living organizations in Alberta, Canada

    Directory of Open Access Journals (Sweden)

    Christina C. Loitz

    2017-08-01

    Full Text Available Abstract Background Coordinated partnerships and collaborations can optimize the efficiency and effectiveness of service and program delivery in organizational networks. However, the extent to which organizations are working together to promote physical activity, and use physical activity policies in Canada, is unknown. This project sought to provide a snapshot of the funding, coordination and partnership relationships among provincial active living organizations (ALOs in Alberta, Canada. Additionally, the awareness, and use of the provincial policy and national strategy by the organizations was examined. Methods Provincial ALOs (N = 27 answered questions regarding their funding, coordination and partnership connections with other ALOs in the network. Social network analysis was employed to examine network structure and position of each ALO. Discriminant function analysis determined the extent to which degree centrality was associated with the use of the Active Alberta (AA policy and Active Canada 20/20 (AC 20/20 strategy. Results The funding network had a low density level (density = .20 and was centralized around Alberta Tourism Parks and Recreation (ATPR; degree centralization = 48.77%, betweenness centralization = 32.43%. The coordination network had a moderate density level (density = .31, and was low-to-moderately centralized around a few organizations (degree centralization = 45.37%, betweenness centrality = 19.92%. The partnership network had a low density level (density = .15, and was moderate-to-highly centralized around ATPR. Most organizations were aware of AA (89% and AC 20/20 (78%, however more were using AA (67% compared to AC 20/20 (33%. Central ALOs in the funding network were more likely to use AA and AC 20/20. Central ALOs in the coordination network were more likely to use AC 20/20, but not AA. Conclusions Increasing formal and informal relationships between organizations and integrating disconnected or

  13. 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...

  14. Stock price change rate prediction by utilizing social network activities.

    Science.gov (United States)

    Deng, Shangkun; Mitsubuchi, Takashi; Sakurai, Akito

    2014-01-01

    Predicting stock price change rates for providing valuable information to investors is a challenging task. Individual participants may express their opinions in social network service (SNS) before or after their transactions in the market; we hypothesize that stock price change rate is better predicted by a function of social network service activities and technical indicators than by a function of just stock market activities. 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. In this paper, we propose a hybrid model that combines multiple kernel learning (MKL) and genetic algorithm (GA). MKL is adopted to optimize the stock price change rate prediction models that are expressed in a multiple kernel linear function of different types of features extracted from different sources. GA is used to optimize the trading rules used in the simulated trading by fusing the return predictions and values of three well-known overbought and oversold technical indicators. Accumulated return and Sharpe ratio were used to test the goodness of performance of the simulated trading. Experimental results show that our proposed model performed better than other models including ones using state of the art techniques.

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

    Directory of Open Access Journals (Sweden)

    Shangkun Deng

    2014-01-01

    Full Text Available Predicting stock price change rates for providing valuable information to investors is a challenging task. Individual participants may express their opinions in social network service (SNS before or after their transactions in the market; we hypothesize that stock price change rate is better predicted by a function of social network service activities and technical indicators than by a function of just stock market activities. 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. In this paper, we propose a hybrid model that combines multiple kernel learning (MKL and genetic algorithm (GA. MKL is adopted to optimize the stock price change rate prediction models that are expressed in a multiple kernel linear function of different types of features extracted from different sources. GA is used to optimize the trading rules used in the simulated trading by fusing the return predictions and values of three well-known overbought and oversold technical indicators. Accumulated return and Sharpe ratio were used to test the goodness of performance of the simulated trading. Experimental results show that our proposed model performed better than other models including ones using state of the art techniques.

  16. 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.

  17. 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.

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

    Science.gov (United States)

    Hutt, Axel; Mierau, Andreas; Lefebvre, Jérémie

    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.

  19. 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...

  20. Memory and pattern storage in neural networks with activity dependent synapses

    Science.gov (United States)

    Mejias, J. F.; Torres, J. J.

    2009-01-01

    We present recently obtained results on the influence of the interplay between several activity dependent synaptic mechanisms, such as short-term depression and facilitation, on the maximum memory storage capacity in an attractor neural network [1]. In contrast with the case of synaptic depression, which drastically reduces the capacity of the network to store and retrieve activity patterns [2], synaptic facilitation is able to enhance the memory capacity in different situations. In particular, we find that a convenient balance between depression and facilitation can enhance the memory capacity, reaching maximal values similar to those obtained with static synapses, that is, without activity-dependent processes. We also argue, employing simple arguments, that this level of balance is compatible with experimental data recorded from some cortical areas, where depression and facilitation may play an important role for both memory-oriented tasks and information processing. We conclude that depressing synapses with a certain level of facilitation allow to recover the good retrieval properties of networks with static synapses while maintaining the nonlinear properties of dynamic synapses, convenient for information processing and coding.

  1. Evaluation of the Performance of Feedforward and Recurrent Neural Networks in Active Cancellation of Sound Noise

    Directory of Open Access Journals (Sweden)

    Mehrshad Salmasi

    2012-07-01

    Full Text Available Active noise control is based on the destructive interference between the primary noise and generated noise from the secondary source. An antinoise of equal amplitude and opposite phase is generated and combined with the primary noise. In this paper, performance of the neural networks is evaluated in active cancellation of sound noise. For this reason, feedforward and recurrent neural networks are designed and trained. After training, performance of the feedforwrad and recurrent networks in noise attenuation are compared. We use Elman network as a recurrent neural network. For simulations, noise signals from a SPIB database are used. In order to compare the networks appropriately, equal number of layers and neurons are considered for the networks. Moreover, training and test samples are similar. Simulation results show that feedforward and recurrent neural networks present good performance in noise cancellation. As it is seen, the ability of recurrent neural network in noise attenuation is better than feedforward network.

  2. Managing nuclear knowledge: IAEA activities and international coordination. Asian Network for Education in Nuclear Technology (ANENT)

    International Nuclear Information System (INIS)

    2007-07-01

    This booklet summarizes the main activities being carried out by the IAEA with regard to the Asian Network for Education in Nuclear Technology (ANENT) and other related activities including those completed during the period 2002-2005. It briefly describes the background information on the events leading to the formation of the ANENT; the terms of reference formulated at the second Coordination Committee meeting held in Vietnam, October 2005; and objectives, strategy and other institutional and managerial policies reaffirmed by the members. The attached CD-ROM contains nearly all of the background material in full text, including policy level papers, reports, presentations made by Member States, and meeting summaries

  3. Photonic Network R&D Activities in Japan-Current Activities and Future Perspectives

    Science.gov (United States)

    Kitayama, Ken-Ichi; Miki, Tetsuya; Morioka, Toshio; Tsushima, Hideaki; Koga, Masafumi; Mori, Kazuyuki; Araki, Soichiro; Sato, Ken-Ichi; Onaka, Hiroshi; Namiki, Shu; Aoyama, Tomonori

    2005-10-01

    R&D activities on photonic networks in Japan are presented. First, milestones in current ongoing R&D programs supported by Japanese government agencies are introduced, including long-distance and wavelength division multiplexing (WDM) fiber transmission, wavelength routing, optical burst switching (OBS), and control-plane technology for IP backbone networks. Their goal was set to evolve a legacy telecommunications network to IP-over-WDM networks by introducing technologies for WDM and wavelength routing. We then discuss the perspectives of so-called PHASE II R&D programs for photonic networks over the next 5 years until 2010, by focusing on the report that has been recently issued by the Photonic Internet Forum (PIF), a consortium that has major carriers, telecom vendors, and Japanese academics as members. The PHASE II R&D programs should serve to establish a photonic platform to provide abundant bandwidth on demand, at any time on a real-time basis, through the customer's initiative to promote bandwidth-rich applications, such as grid computing, real-time digital-cinema streaming, medical and educational applications, and network storage in e-commerce.

  4. 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.

  5. Robust Synchronization in an E/I Network with Medium Synaptic Delay and High Level of Heterogeneity

    International Nuclear Information System (INIS)

    Han Fang; Wang Zhi-Jie; Gong Tao; Fan Hong

    2015-01-01

    It is known that both excitatory and inhibitory neuronal networks can achieve robust synchronization only under certain conditions, such as long synaptic delay or low level of heterogeneity. In this work, robust synchronization can be found in an excitatory/inhibitory (E/I) neuronal network with medium synaptic delay and high level of heterogeneity, which often occurs in real neuronal networks. Two effects of post-synaptic potentials (PSP) to network synchronization are presented, and the synaptic contribution of excitatory and inhibitory neurons to robust synchronization in this E/I network is investigated. It is found that both excitatory and inhibitory neurons may contribute to robust synchronization in E/I networks, especially the excitatory PSP has a more positive effect on synchronization in E/I networks than that in excitatory networks. This may explain the strong robustness of synchronization in E/I neuronal networks. (paper)

  6. Movement Activity Levels on Traditional and Contemporary Playground Structures.

    Science.gov (United States)

    Gabbard, Carl P.; LeBlanc, Elizabeth

    This study investigated playground activity levels of children in grades K-4 and compared levels of use of traditional and creative playground apparatus. The traditional playground area consisted of climbing bars, slides, ladders, chin bars, swings, see saws, and a merry-go-round. The creative playground contained tire hurdles, tire walk, tire…

  7. Protein C activity and antigen levels in childhood

    NARCIS (Netherlands)

    van Teunenbroek, A.; Peters, M.; Sturk, A.; Borm, J. J.; Breederveld, C.

    1990-01-01

    Hereditary protein C deficiency is an important risk factor for thrombosis. To enable its diagnosis shortly after birth, we determined reference values of protein C antigen and activity levels for the first 3 months of life. To establish an age-related range of protein C levels we also determined

  8. Active Ageing Level of Older Persons: Regional Comparison in Thailand

    Directory of Open Access Journals (Sweden)

    Md. Nuruzzaman Haque

    2016-01-01

    Full Text Available Active ageing level and its discrepancy in different regions (Bangkok, Central, North, Northeast, and South of Thailand have been examined for prioritizing the policy agenda to be implemented. Attempt has been made to test preliminary active ageing models for Thai older persons and hence active ageing index (AAI, ranges from 0 to 1 has been estimated. Using nationally representative data and confirmatory factor analysis approach, this study justified active ageing models for female and male older persons in Thailand. Results revealed that active ageing level of Thai older persons is not high (mean AAIs for female and male older persons are 0.64 and 0.61, resp., and those are significantly different (p<0.001. Mean AAI in Central region is lower than North, Northeast, and South regions but there is no significant difference in the latter three regions of Thailand. Special emphasis should be given to Central region and policy should be undertaken for increasing active ageing level. Implementation of an Integrated Active Ageing Package (IAAP, containing policies for older persons to improve their health and economic security, to promote participation in social groups and longer working lives, and to arrange learning programs, would be helpful for increasing older persons’ active ageing level in Thailand.

  9. Active Ageing Level of Older Persons: Regional Comparison in Thailand.

    Science.gov (United States)

    Haque, Md Nuruzzaman

    2016-01-01

    Active ageing level and its discrepancy in different regions (Bangkok, Central, North, Northeast, and South) of Thailand have been examined for prioritizing the policy agenda to be implemented. Attempt has been made to test preliminary active ageing models for Thai older persons and hence active ageing index (AAI, ranges from 0 to 1) has been estimated. Using nationally representative data and confirmatory factor analysis approach, this study justified active ageing models for female and male older persons in Thailand. Results revealed that active ageing level of Thai older persons is not high (mean AAIs for female and male older persons are 0.64 and 0.61, resp., and those are significantly different (p active ageing level. Implementation of an Integrated Active Ageing Package (IAAP), containing policies for older persons to improve their health and economic security, to promote participation in social groups and longer working lives, and to arrange learning programs, would be helpful for increasing older persons' active ageing level in Thailand.

  10. Seasonality in Children's Pedometer-Measured Physical Activity Levels

    Science.gov (United States)

    Beighle, Aaron; Alderman, Brandon; Morgan, Charles F.; Le Masurier, Guy

    2008-01-01

    Seasonality appears to have an impact on children's physical activity levels, but equivocal findings demand more study in this area. With the increased use of pedometers in both research and practice, collecting descriptive data in various seasons to examine the impact of seasonality on pedometer-measured physical activity among children is…

  11. High Levels of Phytophenolics and Antioxidant Activities in Oryza ...

    African Journals Online (AJOL)

    Purpose: To investigate phenolic levels, phytophenolic profiles and total antioxidant activities of Oryza sativa, unpolished Thai rice. Methods: Unpolished Thai rice strains of Leum Phua, Klam, Hawm Nil and Black Rose were measured for antioxidant activity using 1,1-diphenyl-2-picrylhydrazyl (DPPH), ...

  12. Serum paraoxonase activity and lipid hydroperoxide levels in adult ...

    African Journals Online (AJOL)

    EB

    2013-09-03

    Sep 3, 2013 ... Objectives: In this study, we aimed to investigate serum PON1 activity and lipid hydroperoxide (LOOH) levels in adult football players after three days ... oxidative stress after three days football tournament. In addition, physical activity for a ... polymorphism, gender, and exercise. Furthermore, it has been ...

  13. 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, Plife or mental health quality of life at either time point. High levels of engagement with the intervention, and particularly the self-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

  14. Validation of the Social Networking Activity Intensity Scale among Junior Middle School Students in China

    OpenAIRE

    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...

  15. Impacts of optimal energy storage deployment and network reconfiguration on renewable integration level in distribution systems

    International Nuclear Information System (INIS)

    Santos, Sérgio F.; Fitiwi, Desta Z.; Cruz, Marco R.M.; Cabrita, Carlos M.P.; Catalão, João P.S.

    2017-01-01

    Highlights: • A dynamic and multi-objective stochastic mixed integer linear programming model is developed. • A new mechanism to quantify the impacts of network flexibility and ESS deployments on RES integration is presented. • Optimal integration of ESSs dramatically increases the level and the optimal exploitation of renewable DGs. • As high as 90% of RES integration level may be possible in distribution network systems. • Joint DG and ESS installations along with optimal network reconfiguration greatly contribute to voltage stability. - Abstract: Nowadays, there is a wide consensus about integrating more renewable energy sources-RESs to solve a multitude of global concerns such as meeting an increasing demand for electricity, reducing energy security and heavy dependence on fossil fuels for energy production, and reducing the overall carbon footprint of power production. Framed in this context, the coordination of RES integration with energy storage systems (ESSs), along with the network’s switching capability and/or reinforcement, is expected to significantly improve system flexibility, thereby increasing the capability of the system in accommodating large-scale RES power. Hence, this paper presents a novel mechanism to quantify the impacts of network switching and/or reinforcement as well as deployment of ESSs on the level of renewable power integrated in the system. To carry out this analysis, a dynamic and multi-objective stochastic mixed integer linear programming (S-MILP) model is developed, which jointly takes the optimal deployment of RES-based DGs and ESSs into account in coordination with distribution network reinforcement and/or reconfiguration. The IEEE 119-bus test system is used as a case study. Numerical results clearly show the capability of ESS deployment in dramatically increasing the level of renewable DGs integrated in the system. Although case-dependent, the impact of network reconfiguration on RES power integration is not

  16. 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.

  17. Communication Networks - Analysis of jitter due to call-level fluctuations

    NARCIS (Netherlands)

    Mandjes, M.R.H.

    2007-01-01

    Abstract In communication networks used by constant bit rate applications, call-level dynamics (i.e. entering and leaving calls) lead to fluctuations in the load, and therefore also fluctuations in the delay (jitter). By intentionally delaying the packets at the destination, one can transform the

  18. A Closer Look at Deep Learning Neural Networks with Low-level Spectral Periodicity Features

    DEFF Research Database (Denmark)

    Sturm, Bob L.; Kereliuk, Corey; Pikrakis, Aggelos

    2014-01-01

    Systems built using deep learning neural networks trained on low-level spectral periodicity features (DeSPerF) reproduced the most “ground truth” of the systems submitted to the MIREX 2013 task, “Audio Latin Genre Classification.” To answer why this was the case, we take a closer look...

  19. Networking and Managers' Career Success in the Malaysian Public Sector: The Moderating Effect of Managerial Level

    Science.gov (United States)

    Rasdi, Roziah Mohd; Garavan, Thomas N.; Ismail, Maimunah

    2012-01-01

    Purpose: The purpose of this paper is to investigate how managerial level moderates the relationships between networking behaviours and career success (objective and subjective) in the context of a public sector organisation in Malaysia. Design/methodology/approach: The study utilised a cross-sectional design and investigated these relationships…

  20. Dual-Level Game-Based Energy Efficiency and Fairness for Green Cellular Networks

    Directory of Open Access Journals (Sweden)

    Sungwook Kim

    2016-01-01

    Full Text Available In the recent decades, cellular networks have revolutionized the way of next generation communication networks. However, due to the global climate change, reducing the energy consumption of cellular infrastructures is an important and urgent problem. In this study, we propose a novel two-level cooperative game framework for improving the energy efficiency and fairness in cellular networks. For the energy efficiency, base stations (BSs constantly monitor the current traffic load and cooperate with each other to maximize the energy saving. For the energy fairness, renewable energy can be shared dynamically while ensuring the fairness among BSs. To achieve an excellent cellular network performance, the concepts of the Raiffa Bargaining Solution and Jain’s fairness are extended and practically applied to our dual-level cooperative game model. Through system level simulations, the proposed scheme is evaluated and compared with other existing schemes. The simulation results show that our two-level game approach outperforms the existing schemes in providing a better fair-efficient system performance.

  1. LTAR information management: Six examples of data intensive work at site and network levels

    Science.gov (United States)

    Information systems for managing research data from the Long-term Agroecosystem Research (LTAR) program are implemented at site and network levels. Different information management tools are necessary to manage a variety of data types. There is no one-size fits all solution for managing all LTAR dat...

  2. PolNet: A Tool to Quantify Network-Level Cell Polarity and Blood Flow in Vascular Remodeling.

    Science.gov (United States)

    Bernabeu, Miguel O; Jones, Martin L; Nash, Rupert W; Pezzarossa, Anna; Coveney, Peter V; Gerhardt, Holger; Franco, Claudio A

    2018-05-08

    In this article, we present PolNet, an open-source software tool for the study of blood flow and cell-level biological activity during vessel morphogenesis. We provide an image acquisition, segmentation, and analysis protocol to quantify endothelial cell polarity in entire in vivo vascular networks. In combination, we use computational fluid dynamics to characterize the hemodynamics of the vascular networks under study. The tool enables, to our knowledge for the first time, a network-level analysis of polarity and flow for individual endothelial cells. To date, PolNet has proven invaluable for the study of endothelial cell polarization and migration during vascular patterning, as demonstrated by two recent publications. Additionally, the tool can be easily extended to correlate blood flow with other experimental observations at the cellular/molecular level. We release the source code of our tool under the Lesser General Public License. Copyright © 2018 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  3. A Neural Network Approach to Fluid Level Measurement in Dynamic Environments Using a Single Capacitive Sensor

    Directory of Open Access Journals (Sweden)

    Edin TERZIC

    2010-03-01

    Full Text Available A measurement system has been developed using a single tube capacitive sensor to accurately determine the fluid level in vehicular fuel tanks. A novel approach based on artificial neural networks based signal pre-processing and classification has been described in this article. A broad investigation on the Backpropagation neural network and some selected signal pre-processing filters, namely, Moving Mean, Moving Median, and Wavelet Filter has also been presented. An on field drive trial was conducted under normal driving conditions at various fuel volumes ranging from 5 L to 50 L to acquire training samples from the capacitive sensor. A second field trial was conducted to obtain test samples to verify the performance of the neural network. The neural network was trained and verified with 50 % of the training and test samples. The results obtained using the neural network approach having different filtration methods are compared with the results obtained using simple Moving Mean and Moving Median functions. It is demonstrated that the Backpropagation neural network with Moving Median filter produced the most accurate outcome compared with the other signal filtration methods.

  4. The contribution to distribution network fault levels from the connection of distributed generation

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2005-07-01

    This report summarises the findings of a study investigating the potential impact of distributed generation (DG) on the UK distribution network fault levels up to the year 2010, and examining ways of managing the fault levels so that they do not become a barrier to increased penetration of DG. The project focuses on the circumstances and scenarios that give rise to the fault levels. The background to the study is traced, and a technical review is presented covering the relationship between DG and fault levels, and the likely impact in the period to 2010. Options for managing increased fault levels, and fault level management and costs are outlined, and a case study is given. The measurement and calculation of fault level values are described along with constraints to DG penetration due to fault level limitations, characteristics of DG machines, and long term perspectives to 2020-2030.

  5. Dynamic Sleep Scheduling on Air Pollution Levels Monitoring with Wireless Sensor Network

    Directory of Open Access Journals (Sweden)

    Gezaq Abror

    2018-01-01

    Full Text Available Wireless Sensor Network (WSN can be applied for Air Pollution Level Monitoring System that have been determined by the Environmental Impact Management Agency which is  PM10, SO2, O3, NO2 and CO. In WSN, node system is constrained to a limited power supply, so that the node system has a lifetime. To doing lifetime maximization, power management scheme is required and sensor nodes should use energy efficiently. This paper proposes dynamic sleep scheduling using Time Category-Fuzzy Logic (Time-Fuzzy Scheduling as a reference for calculating time interval for sleep and activated node system to support power management scheme. This research contributed in power management design to be applied to the WSN system to reduce energy expenditure. From the test result in real hardware node system, it can be seen that Time-Fuzzy Scheduling is better in terms of using the battery and it is better in terms of energy consumption too because it is more efficient 51.85% when it is compared with Fuzzy Scheduling, it is more efficient 68.81% when it is compared with Standard Scheduling and it is more efficient 85.03% when compared with No Scheduling.

  6. LEA: An Algorithm to Estimate the Level of Location Exposure in Infrastructure-Based Wireless Networks

    Directory of Open Access Journals (Sweden)

    Francisco Garcia

    2017-01-01

    Full Text Available Location privacy in wireless networks is nowadays a major concern. This is due to the fact that the mere fact of transmitting may allow a network to pinpoint a mobile node. We consider that a first step to protect a mobile node in this situation is to provide it with the means to quantify how accurately a network establishes its position. To achieve this end, we introduce the location-exposure algorithm (LEA, which runs on the mobile terminal only and whose operation consists of two steps. In the first step, LEA discovers the positions of nearby network nodes and uses this information to emulate how they estimate the position of the mobile node. In the second step, it quantifies the level of exposure by computing the distance between the position estimated in the first step and its true position. We refer to these steps as a location-exposure problem. We tested our proposal with simulations and testbed experiments. These results show the ability of LEA to reproduce the location of the mobile node, as seen by the network, and to quantify the level of exposure. This knowledge can help the mobile user decide which actions should be performed before transmitting.

  7. SHORT-TERM SOLAR FLARE LEVEL PREDICTION USING A BAYESIAN NETWORK APPROACH

    International Nuclear Information System (INIS)

    Yu Daren; Huang Xin; Hu Qinghua; Zhou Rui; Wang Huaning; Cui Yanmei

    2010-01-01

    A Bayesian network approach for short-term solar flare level prediction has been proposed based on three sequences of photospheric magnetic field parameters extracted from Solar and Heliospheric Observatory/Michelson Doppler Imager longitudinal magnetograms. The magnetic measures, the maximum horizontal gradient, the length of neutral line, and the number of singular points do not have determinate relationships with solar flares, so the solar flare level prediction is considered as an uncertainty reasoning process modeled by the Bayesian network. The qualitative network structure which describes conditional independent relationships among magnetic field parameters and the quantitative conditional probability tables which determine the probabilistic values for each variable are learned from the data set. Seven sequential features-the maximum, the mean, the root mean square, the standard deviation, the shape factor, the crest factor, and the pulse factor-are extracted to reduce the dimensions of the raw sequences. Two Bayesian network models are built using raw sequential data (BN R ) and feature extracted data (BN F ), respectively. The explanations of these models are consistent with physical analyses of experts. The performances of the BN R and the BN F appear comparable with other methods. More importantly, the comprehensibility of the Bayesian network models is better than other methods.

  8. An event- and network-level analysis of college students' maximum drinking day.

    Science.gov (United States)

    Meisel, Matthew K; DiBello, Angelo M; Balestrieri, Sara G; Ott, Miles Q; DiGuiseppi, Graham T; Clark, Melissa A; Barnett, Nancy P

    2018-04-01

    Heavy episodic drinking is common among college students and remains a serious public health issue. Previous event-level research among college students has examined behaviors and individual-level characteristics that drive consumption and related consequences but often ignores the social network of people with whom these heavy drinking episodes occur. The main aim of the current study was to investigate the network of social connections between drinkers on their heaviest drinking occasions. Sociocentric network methods were used to collect information from individuals in the first-year class (N=1342) at one university. Past-month drinkers (N=972) reported on the characteristics of their heaviest drinking occasion in the past month and indicated who else among their network connections was present during this occasion. Average max drinking day indegree, or the total number of times a participant was nominated as being present on another students' heaviest drinking occasion, was 2.50 (SD=2.05). Network autocorrelation models indicated that max drinking day indegree (e.g., popularity on heaviest drinking occassions) and peers' number of drinks on their own maximum drinking occasions were significantly associated with participant maximum number of drinks, after controlling for demographic variables, pregaming, and global network indegree (e.g., popularity in the entire first-year class). Being present at other peers' heaviest drinking occasions is associated with greater drinking quantities on one's own heaviest drinking occasion. These findings suggest the potential for interventions that target peer influences within close social networks of drinkers. Copyright © 2017 Elsevier Ltd. All rights reserved.

  9. Correlation of Level of Trauma Activation With Emergency Department Intervention.

    Science.gov (United States)

    Cooper, Michael C; Srivastava, Geetanjali

    2018-06-01

    In-hospital trauma team activation criteria are formulated to identify severely injured patients requiring specialized multidisciplinary care. Efficacy of trauma activation (TA) criteria is commonly measured by emergency department (ED) disposition, injury severity score, and mortality. Necessity of critical ED interventions is another measure that has been proposed to evaluate the appropriateness of TA criteria. Two-year retrospective cohort study of 1715 patients from our trauma registry at a Level 1 pediatric trauma center. We abstracted data on acute interventions, level and criterion of TA, ED disposition, and mortality. We report odds ratio (OR) with 95% confidence intervals (CIs), positive predictive value, and frequency of acute interventions. Trauma activation was initiated for 947 (55%) of the 1715 patients. There were 426 ED interventions performed on 235 patients (14%); 67.8% were in level 1 activations; 17.6% in level 2, and 14.6% in level 3. Highest-level activations were highly associated with need for ED interventions (OR, 16.1; 95% CI, 11.5-22.4). The ORs for requiring an ED intervention were low for lower level activations (OR, 0.4; 95% CI, 0.3-0.5), trauma service consults (OR, 0.3; 95% CI, 0.2-0.4), and certain mechanism-based criteria. The ORs for ED intervention for isolated motor vehicle collision (0.2; 95% CI, 0.1-0.7), isolated all-terrain vehicle rollover (0.4; 95% CI, 0.1-1.7), and suspected spinal cord injury (0.5; 95% CI, 0.1-3.7) were significantly lower than 1. Highest-level activation criteria correlate with high utilization of ED resources and interventions. Lower level activation criteria and trauma service consult criteria are not highly correlated with need for ED interventions. Downgrading isolated motor vehicle collision and all-terrain vehicle rollovers and suspected spinal cord injury to lower level activations could decrease the overtriage rate, and adding age-specific bradycardia as a physiologic criterion could improve our

  10. Neural Networks Mediating High-Level Mentalizing in Patients With Right Cerebral Hemispheric Gliomas

    Directory of Open Access Journals (Sweden)

    Riho Nakajima

    2018-03-01

    Full Text Available Mentalizing is the ability to understand others’ mental state through external cues. It consists of two networks, namely low-level and high-level metalizing. Although it is an essential function in our daily social life, surgical resection of right cerebral hemisphere disturbs mentalizing processing with high possibility. In the past, little was known about the white matter related to high-level mentalizing, and the conservation of high-level mentalizing during surgery has not been a focus of attention. Therefore, the main purpose of this study was to examine the neural networks underlying high-level mentalizing and then, secondarily, investigate the usefulness of awake surgery in preserving the mentalizing network. A total of 20 patients with glioma localized in the right hemisphere who underwent awake surgery participated in this study. All patients were assigned to two groups: with or without intraoperative assessment of high-level mentalizing. Their high-level mentalizing abilities were assessed before surgery and 1 week and 3 months after surgery. At 3 months after surgery, only patients who received the intraoperative high-level mentalizing test showed the same score as normal healthy volunteers. The tract-based lesion symptom analysis was performed to confirm the severity of damage of associated fibers and high-level mentalizing accuracy. This analysis revealed the superior longitudinal fascicles (SLF III and fronto-striatal tract (FST to be associated with high-level mentalizing processing. Moreover, the voxel-based lesion symptom analysis demonstrated that resection of orbito-frontal cortex (OFC causes persistent mentalizing dysfunction. Our study indicates that damage of the OFC and structural connectivity of the SLF and FST causes the disorder of mentalizing after surgery, and assessing high-level mentalizing during surgery may be useful to preserve these pathways.

  11. DNCON2: improved protein contact prediction using two-level deep convolutional neural networks.

    Science.gov (United States)

    Adhikari, Badri; Hou, Jie; Cheng, Jianlin

    2018-05-01

    Significant improvements in the prediction of protein residue-residue contacts are observed in the recent years. These contacts, predicted using a variety of coevolution-based and machine learning methods, are the key contributors to the recent progress in ab initio protein structure prediction, as demonstrated in the recent CASP experiments. Continuing the development of new methods to reliably predict contact maps is essential to further improve ab initio structure prediction. In this paper we discuss DNCON2, an improved protein contact map predictor based on two-level deep convolutional neural networks. It consists of six convolutional neural networks-the first five predict contacts at 6, 7.5, 8, 8.5 and 10 Å distance thresholds, and the last one uses these five predictions as additional features to predict final contact maps. On the free-modeling datasets in CASP10, 11 and 12 experiments, DNCON2 achieves mean precisions of 35, 50 and 53.4%, respectively, higher than 30.6% by MetaPSICOV on CASP10 dataset, 34% by MetaPSICOV on CASP11 dataset and 46.3% by Raptor-X on CASP12 dataset, when top L/5 long-range contacts are evaluated. We attribute the improved performance of DNCON2 to the inclusion of short- and medium-range contacts into training, two-level approach to prediction, use of the state-of-the-art optimization and activation functions, and a novel deep learning architecture that allows each filter in a convolutional layer to access all the input features of a protein of arbitrary length. The web server of DNCON2 is at http://sysbio.rnet.missouri.edu/dncon2/ where training and testing datasets as well as the predictions for CASP10, 11 and 12 free-modeling datasets can also be downloaded. Its source code is available at https://github.com/multicom-toolbox/DNCON2/. chengji@missouri.edu. Supplementary data are available at Bioinformatics online.

  12. Prediction of BMI by impulsivity, eating behavior and activity level

    Directory of Open Access Journals (Sweden)

    Jiang Xiaxia

    2016-01-01

    Full Text Available Objective: Discuss the relationship between the impulsivity, eating behavior and activity level and the body mass index (BMI. Method: Test 147 female college students with the impulsivity questionnaire (BIS-11 and BIS/BAS, Dutch Eating Behavior Questionnaire (DBEQ, Sitting Time Scale (STS and Exercising Time Scale (ETS. Results: (1 The correlation analysis indicates that BMI and impulsivity (r = 0.43 and 0.52 have a significant positive correlation with the sitting time (r = 0.61 and a significant negative correlation with the activity level (r= −0.49. (2 The path analysis indicates that the reward sensitivity directly affects BMI and indirectly affects BMI through the activity level as well; the eating behavior has an insignificantly direct impact on BMI, because its impact is generated by the intermediary role of induced diet. Conclusion: (1 The impulsivity, eating behavior and activity level are closely related to BMI; (2 the activity level, sitting time and induced diet play an intermediary role between the impulsivity and BMI.

  13. Systemic lupus erythematosus activity and beta two microglobulin levels

    Directory of Open Access Journals (Sweden)

    Thelma Larocca Skare

    Full Text Available CONTEXT AND OBJECTIVE: Systemic lupus erythematosus (SLE is an autoimmune disease with a cyclical clinical course. Evaluation of the clinical activity of this disease is important for choosing the correct treatment. The objective of this study was to analyze the value of beta-2 microglobulin (β2M serum levels in determining SLE clinical activity.DESIGN AND SETTING: Cross-sectional analytical study conducted at the rheumatology outpatient clinic of a private university hospital.METHODS: 129 SLE patients were studied regarding disease activity using SLEDAI (SLE Disease Activity Index and cumulative damage using SLICC ACR (SLE International Collaborating Clinics/American College of Rheumatology Damage Index for SLE. At the same time, the β2M serum level, ESR (erythrocyte sedimentation rate, anti-dsDNA (anti-double-stranded DNA and C3 and C4 complement fractions were determined.RESULTS: β2M levels correlated positively with SLEDAI (P = 0.02 and ESR (P = 0.0009 and negatively with C3 (P = 0.007. Patients who were positive for anti-dsDNA had higher β2M serum levels (P = 0.009.CONCLUSION: β2M levels are elevated in SLE patients with active disease.

  14. Correlated alpha activity with the facial expression processing network in a simultaneous EEG-fMRI experiment.

    Science.gov (United States)

    Simoes, Marco; Direito, Bruno; Lima, Joao; Castelhano, Joao; Ferreira, Carlos; Couceiro, Ricardo; Carvalho, Paulo; Castelo-Branco, Miguel

    2017-07-01

    The relationship between EEG and fMRI data is poorly covered in the literature. Extensive work has been conducted in resting-state and epileptic activity, highlighting a negative correlation between the alpha power band of the EEG and the BOLD activity in the default-mode-network. The identification of an appropriate task-specific relationship between fMRI and EEG data for predefined regions-of-interest, would allow the transfer of interventional paradigms (such as BOLD-based neurofeedback sessions) from fMRI to EEG, enhancing its application range by lowering its costs and improving its flexibility. In this study, we present an analysis of the correlation between task-specific alpha band fluctuations and BOLD activity in the facial expressions processing network. We characterized the network ROIs through a stringent localizer and identified two clusters on the scalp (one frontal, one parietal-occipital) with marked alpha fluctuations, related to the task. We then check whether such power variations throughout the time correlate with the BOLD activity in the network. Our results show statistically significant negative correlations between the alpha power in both clusters and for all the ROIs of the network. The correlation levels have still not met the requirements for transferring the protocol to an EEG setup, but they pave the way towards a better understand on how frontal and parietal-occipital alpha relates to the activity of the facial expressions processing network.

  15. Analysis of Amygdalar-Cortical Network Covariance During Pre- versus Post-menopausal Estrogen Levels: Potential Relevance to Resting State Networks, Mood, and Cognition

    Science.gov (United States)

    Ottowitz, William E.; Derro, David; Dougherty, Darin D.; Lindquist, Martin A.; Fischman, Alan J.; Hall, Janet E.

    2014-01-01

    Objectives 1.) Expand the scope of neuroendocrine applications of functional neuroimaging techniques. 2.) Compare the covariance of amygdalar activity with that of the rest of the brain during pre- and post-menopausal levels of estrogen (E2). Based on the distribution of cortical E2 receptors and the neocortical regions where E2 has been shown to preferentially accumulate, we predict that E2 infusion will increase covariance of amygdalar activity with that of the temporal and frontal cortices. Design This basic physiology study employed a within-subject design. All participants were post-menopausal women (n =7). Analysis of covariance between whole brain and amygdalar regional cerebral glucose consumption (CMRglc) was conducted in a voxel-wise manner by means of the basic regression option in SPM2 and was applied to FDG-PET scans acquired at baseline and after a 24 hour graded E2 infusion. Setting an academic medical center; Massachusetts General Hospital, Boston, Massachusetts. Results E2 levels (mean ± sem) were significantly greater at 24 hours (257.9 pg/mL ± 29.7) than at 0 hours (28.1 pg/mL ± 3.4). Right amygdalar CMRglc showed a significant covariance with activity of three different regions of the temporal cortex during E2 infusion, but none at baseline. In addition, right amygdalar CMRglc covaried with that of the right medial and superior frontal gyri only during E2 infusion. Conclusions In addition to suggesting changes in amygdalar-cortical network connectivity as a result of short-term E2 exposure, these analyses provide evidence that basic neuroendocrine research may benefit from further use of FDG-PET and other functional neuroimaging modalities for network level analyses. PMID:18766152

  16. Serum Renalase Levels Correlate with Disease Activity in Lupus Nephritis.

    Directory of Open Access Journals (Sweden)

    Chaojun Qi

    Full Text Available Lupus nephritis (LN is among the most serious complications of systemic lupus erythematosus (SLE, which causes significant morbidity and mortality. Renalase is a novel, kidney-secreted cytokine-like protein that promotes cell survival. Here, we aimed to investigate the relationship of serum renalase levels with LN and its role in the disease progression of LN.For this cross-sectional study, 67 LN patients and 35 healthy controls were enrolled. Seventeen active LN patients who received standard therapies were followed up for six months. Disease activity was determined by the SLE Disease Activity-2000 (SLEDAI-2K scoring system and serum renalase amounts were determined by ELISA. Predictive value of renalase for disease activity was assessed. Furthermore, the expression of renalase in the kidneys of patients and macrophage infiltration was assessed by immunohistochemistry.Serum renalase amounts were significantly higher in LN patients than in healthy controls. Moreover, patients with proliferative LN had more elevated serum renalase levels than Class V LN patients. In proliferative LN patients, serum renalase levels were significantly higher in patients with active LN than those with inactive LN. Serum renalase levels were positively correlated with SLEDAI-2K, 24-h urine protein excretion, ds-DNA and ESR but inversely correlated with serum albumin and C3. Renalase amounts decreased significantly after six-months of standard therapy. The performance of renalase as a marker for diagnosis of active LN was 0.906 with a cutoff value of 66.67 μg/ml. We also observed that the amount of renalase was significantly higher in glomerular of proliferative LN along with the co-expression of macrophages.Serum renalase levels were correlated with disease activity in LN. Serum renalase might serve as a potential indicator for disease activity in LN. The marked increase of glomerular renalase and its association with macrophages suggest that it might play an

  17. 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

    2016-01-01

    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. PMID:27228907

  18. 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.

  19. Development of Active External Network Topology Module for Floodlight SDN Controller

    Directory of Open Access Journals (Sweden)

    A. A. Noskov

    2015-01-01

    Full Text Available Traditional network architecture is inflexible and complicated. This observation has led to a paradigm shift towards software-defined networking (SDN, where network management level is separated from data forwarding level. This change was made possible by control plane transfer from the switching equipment to software modules that run on a dedicated server, called the controller (or network operating system, or network applications, that work with this controller. Methods of representation, storage and communication interfaces with network topology elements are the most important aspects of network operating systems available to SDN user because performance of some key controller modules is heavily dependent on internal representation of the network topology. Notably, firewall and routing modules are examples of such modules. This article describes the methods used for presentation and storage of network topologies, as well as interface to the corresponding Floodlight modules. An alternative algorithm has been suggested and developed for message exchange conveying network topology alterations between the controller and network applications. Proposed algorithm makes implementation of module alerting based on subscription to the relevant events. API for interaction between controller and network applications has been developed. This algorithm and API formed the base for Topology Tracker module capable to inform network applications about the changes that had occurred in the network topology and also stores compact representation of the network to speed up the interaction process.

  20. Extraction of Children's Friendship Relation from Activity Level

    Science.gov (United States)

    Kono, Aki; Shintani, Kimio; Katsuki, Takuya; Kihara, Shin'ya; Ueda, Mari; Kaneda, Shigeo; Haga, Hirohide

    Children learn to fit into society through living in a group, and it's greatly influenced by their friend relations. Although preschool teachers need to observe them to assist in the growth of children's social progress and support the development each child's personality, only experienced teachers can watch over children while providing high-quality guidance. To resolve the problem, this paper proposes a mathematical and objective method that assists teachers with observation. It uses numerical data of activity level recorded by pedometers, and we make tree diagram called dendrogram based on hierarchical clustering with recorded activity level. Also, we calculate children's ``breadth'' and ``depth'' of friend relations by using more than one dendrogram. When we record children's activity level in a certain kindergarten for two months and evaluated the proposed method, the results usually coincide with remarks of teachers about the children.

  1. Use of modeling to assess the scalability of Ethernet networks for the ATLAS second level trigger

    CERN Document Server

    Korcyl, K; Dobinson, Robert W; Saka, F

    1999-01-01

    The second level trigger of LHC's ATLAS experiment has to perform real-time analyses on detector data at 10 GBytes/s. A switching network is required to connect more than thousand read-out buffers to about thousand processors that execute the trigger algorithm. We are investigating the use of Ethernet technology to build this large switching network. Ethernet is attractive because of the huge installed base, competitive prices, and recent introduction of the high-performance Gigabit version. Due to the network's size it has to be constructed as a layered structure of smaller units. To assess the scalability of such a structure we evaluated a single switch unit. (0 refs).

  2. Two-level modulation scheme to reduce latency for optical mobile fronthaul networks.

    Science.gov (United States)

    Sung, Jiun-Yu; Chow, Chi-Wai; Yeh, Chien-Hung; Chang, Gee-Kung

    2016-10-31

    A system using optical two-level orthogonal-frequency-division-multiplexing (OFDM) - amplitude-shift-keying (ASK) modulation is proposed and demonstrated to reduce the processing latency for the optical mobile fronthaul networks. At the proposed remote-radio-head (RRH), the high data rate OFDM signal does not need to be processed, but is directly launched into a high speed photodiode (HSPD) and subsequently emitted by an antenna. Only a low bandwidth PD is needed to recover the low data rate ASK control signal. Hence, it is simple and provides low-latency. Furthermore, transporting the proposed system over the already deployed optical-distribution-networks (ODNs) of passive-optical-networks (PONs) is also demonstrated with 256 ODN split-ratios.

  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. Lipidic profile and the level of physical activity of adolescent scholars

    Directory of Open Access Journals (Sweden)

    Renato Canevari Dutra da Silva

    2011-12-01

    Full Text Available Objective: To assess the relationship between lipid profile and physical activity level of adolescent students in Rio Verde-GO, Brazil. Methods: A descriptive and cross-sectionalstudy, conducted in 2006, with a population comprised by 1,229 adolescent students of both genders, aged 15 to 17 years (X = 15.9 years, SD + 0.81, from public and private schools. The level of physical activity was assessed through the International PhysicalActivity Questionnaire (IPAQ. Later, 48 teenagers underwent a lipidogram (lipid profile. Lipid concentrations of total cholesterol (TC, HDL-c (high density lipoprotein and LDL (low density lipoprotein and triglycerides (TGL were determined and assessed according to cutoff points proposed by the III Brazilian Guidelines on dyslipidemias and Guideline of Atherosclerosis, Department of Atherosclerosis of Brazilian Society of Cardiology. Statisticalanalysis was performed by binomial test for proportions and Pearson’s correlation test, adopting p <0.05. Results: Applying IPAQ we found a percentage of 77.7% active adolescents and 22.3% of insufficiently active adolescents, with the highest percentage of active teens inmales (p = 0.0000. Adolescents of both sexes from public network were considered more active than teens from private schools. The lipid profile of the studied adolescents was within normal range. Conclusion: There was no relationship between physical activity level and lipid profile of the adolescents assessed.

  5. Play Equipment, Physical Activity Opportunities, and Children's Activity Levels at Childcare

    Directory of Open Access Journals (Sweden)

    Jessica S. Gubbels

    2012-01-01

    Full Text Available This study investigated the association between physical activity facilities at childcare (e.g., play equipment and physical activity of 2- and 3-year olds. Observations of physical activity intensity were performed among 175 children at 9 childcare centers in The Netherlands, using the OSRAC-P. The physical activity facilities were assessed for indoors and outdoors separately, using the EPAO instrument. Regular (single-level multivariate and multilevel linear regression analyses examined the association of the facilities and child characteristics (age and sex with children's activity levels. Various physical activity facilities were available in all childcare centers (e.g., balls. Riding toys and a small playing area were associated with lower indoor physical activity levels. Outdoor physical activity levels were positively associated with the availability of portable jumping equipment and the presence of a structured track on the playground. Portable slides, fixed swinging equipment, and sandboxes were negatively associated with outdoor activity levels. In addition, the 3-year old children were more active outdoors than the 2-year olds. In conclusion, not all physical activity facilities at childcare were indeed positively associated with children's activity levels. The current findings provide concrete leads for childcare providers regarding which factors they can improve in the physical environment to facilitate children's physical activity.

  6. Effect of fluorozis on the erythrocyte antioxidant enzyme activity levels

    International Nuclear Information System (INIS)

    Akdogan, M.; YiImaz, D.; Yontem, M.; Kalei, S.; Kilic, I.

    2011-01-01

    While the flourine level of (drinking) water was higher than normal ranges in the center of Isparta region before 1995 year, this problematic situation is solved in later years. (However) the individuals who are staying in Yenice district are still expose to high levels of fluorine because of the usage of Andik spring water (3.8 mg/L flour level) as drinking water. In this study we aimed to investigate the harmful effect of floride on human erythrocytes via antioxidant defence system and lipid peroxidation. Therefore, we studied the activities of erythrocyte antioxidant enzymes such as Superoxide Dismutase (SOD), Glutathione Peroxidase (GSH-Px) and Catalase (CAT), and the level of erythrocyte Glutathione (GSH), thiobarbituric acid reactive substance (TBARS) and the level of urine floride in high floride exposed people (children, adult and elderly). The activities of SOD, GSH-Px and CAT and the level of GSH, TBARS and urine floride were higher in 3.8 mg/L floride exposed children (Group II) than 0.8 mg/L floride exposed control children (Group I) (p 0.05). The activities of SOD, GSH-Px and CAT were lower and the levels of TBARS and urine floride were higher in 3.8 mg/L floride exposed elderly people (Group VI) than 0.8 mg/L floride exposed control elderly people (Group V) (p 0.05). As a result we thought that increased SOD, GSH-Px and CAT activities in floride exposed children and adult people, decreased activities of these enzymes in floride exposed elderly people, and increased TBARS in all groups may indicate floride caused oxidative damage in erythrocytes. (author)

  7. Mental health and physical activity levels of school children

    Directory of Open Access Journals (Sweden)

    Gabrielle Cerqueira da Silva

    2017-03-01

    Full Text Available Introduction: The regular practice of physical activity is fundamental to the health of children, it has been cited as factor of protection for mental disorders in school age. Objective: To verify the relation between mental health and physical activity levels in schoolchildren of the city Jacobina, Bahia. Method: Sample composed of 55 students between the ages 08 to 10 and their parents, who participated as secondary informants in this study. The Child Behavior Checklist (CBCL was used for evaluation of mental health problems of the schoolchildren, Physical Activity Questionnaire for Older Children (PAQ-C, for evaluation of the physical activity levels of the subject, and a social-demographic questionnaire. Results: Most children were classified as sedentary (80% and only 7.3% of the sample showed positive for trace of mental disorder. No significant association was found between mental disorders and physical activity levels among the group, or between these variables and socio-demographic characteristics of children. It was observed that the girls were more sedentary than boys, with significant difference (p < 0.01. Conclusion: Despite the low prevalence of mental health problems among schoolchildren and the non-association with physical activity levels, special attention is necessary with this audience, aiming to strengthen physical activity as a protective factor for children’s mental health, with investments in actions aimed at the encouragement of regular practice of physical activity, combining family and school. Studies with a larger number of samples need to be conducted and its findings must be thoroughly analyzed.

  8. Towards a system level understanding of non-model organisms sampled from the environment: a network biology approach.

    Directory of Open Access Journals (Sweden)

    Tim D Williams

    2011-08-01

    Full Text Available The acquisition and analysis of datasets including multi-level omics and physiology from non-model species, sampled from field populations, is a formidable challenge, which so far has prevented the application of systems biology approaches. If successful, these could contribute enormously to improving our understanding of how populations of living organisms adapt to environmental stressors relating to, for example, pollution and climate. Here we describe the first application of a network inference approach integrating transcriptional, metabolic and phenotypic information representative of wild populations of the European flounder fish, sampled at seven estuarine locations in northern Europe with different degrees and profiles of chemical contaminants. We identified network modules, whose activity was predictive of environmental exposure and represented a link between molecular and morphometric indices. These sub-networks represented both known and candidate novel adverse outcome pathways representative of several aspects of human liver pathophysiology such as liver hyperplasia, fibrosis, and hepatocellular carcinoma. At the molecular level these pathways were linked to TNF alpha, TGF beta, PDGF, AGT and VEGF signalling. More generally, this pioneering study has important implications as it can be applied to model molecular mechanisms of compensatory adaptation to a wide range of scenarios in wild populations.

  9. Towards a system level understanding of non-model organisms sampled from the environment: a network biology approach.

    Science.gov (United States)

    Williams, Tim D; Turan, Nil; Diab, Amer M; Wu, Huifeng; Mackenzie, Carolynn; Bartie, Katie L; Hrydziuszko, Olga; Lyons, Brett P; Stentiford, Grant D; Herbert, John M; Abraham, Joseph K; Katsiadaki, Ioanna; Leaver, Michael J; Taggart, John B; George, Stephen G; Viant, Mark R; Chipman, Kevin J; Falciani, Francesco

    2011-08-01

    The acquisition and analysis of datasets including multi-level omics and physiology from non-model species, sampled from field populations, is a formidable challenge, which so far has prevented the application of systems biology approaches. If successful, these could contribute enormously to improving our understanding of how populations of living organisms adapt to environmental stressors relating to, for example, pollution and climate. Here we describe the first application of a network inference approach integrating transcriptional, metabolic and phenotypic information representative of wild populations of the European flounder fish, sampled at seven estuarine locations in northern Europe with different degrees and profiles of chemical contaminants. We identified network modules, whose activity was predictive of environmental exposure and represented a link between molecular and morphometric indices. These sub-networks represented both known and candidate novel adverse outcome pathways representative of several aspects of human liver pathophysiology such as liver hyperplasia, fibrosis, and hepatocellular carcinoma. At the molecular level these pathways were linked to TNF alpha, TGF beta, PDGF, AGT and VEGF signalling. More generally, this pioneering study has important implications as it can be applied to model molecular mechanisms of compensatory adaptation to a wide range of scenarios in wild populations.

  10. Click-Evoked Auditory Efferent Activity: Rate and Level Effects.

    Science.gov (United States)

    Boothalingam, Sriram; Kurke, Julianne; Dhar, Sumitrajit

    2018-05-07

    There currently are no standardized protocols to evaluate auditory efferent function in humans. Typical tests use broadband noise to activate the efferents, but only test the contralateral efferent pathway, risk activating the middle ear muscle reflex (MEMR), and are laborious for clinical use. In an attempt to develop a clinical test of bilateral auditory efferent function, we have designed a method that uses clicks to evoke efferent activity, obtain click-evoked otoacoustic emissions (CEOAEs), and monitor MEMR. This allows for near-simultaneous estimation of cochlear and efferent function. In the present study, we manipulated click level (60, 70, and 80 dB peak-equivalent sound pressure level [peSPL]) and rate (40, 50, and 62.5 Hz) to identify an optimal rate-level combination that evokes measurable efferent modulation of CEOAEs. Our findings (n = 58) demonstrate that almost all click levels and rates used caused significant inhibition of CEOAEs, with a significant interaction between level and rate effects. Predictably, bilateral activation produced greater inhibition compared to stimulating the efferents only in the ipsilateral or contralateral ear. In examining the click rate-level effects during bilateral activation in greater detail, we observed a 1-dB inhibition of CEOAE level for each 10-dB increase in click level, with rate held constant at 62.5 Hz. Similarly, a 10-Hz increase in rate produced a 0.74-dB reduction in CEOAE level, with click level held constant at 80 dB peSPL. The effect size (Cohen's d) was small for either monaural condition and medium for bilateral, faster-rate, and higher-level conditions. We were also able to reliably extract CEOAEs from efferent eliciting clicks. We conclude that clicks can indeed be profitably employed to simultaneously evaluate cochlear health using CEOAEs as well as their efferent modulation. Furthermore, using bilateral clicks allows the evaluation of both the crossed and uncrossed elements of the auditory

  11. Extrinsic and Intrinsic Brain Network Connectivity Maintains Cognition across the Lifespan Despite Accelerated Decay of Regional Brain Activation.

    Science.gov (United States)

    Tsvetanov, Kamen A; Henson, Richard N A; Tyler, Lorraine K; Razi, Adeel; Geerligs, Linda; Ham, Timothy E; Rowe, James B

    2016-03-16

    The maintenance of wellbeing across the lifespan depends on the preservation of cognitive function. We propose that successful cognitive aging is determined by interactions both within and between large-scale functional brain networks. Such connectivity can be estimated from task-free functional magnetic resonance imaging (fMRI), also known as resting-state fMRI (rs-fMRI). However, common correlational methods are confounded by age-related changes in the neurovascular signaling. To estimate network interactions at the neuronal rather than vascular level, we used generative models that specified both the neural interactions and a flexible neurovascular forward model. The networks' parameters were optimized to explain the spectral dynamics of rs-fMRI data in 602 healthy human adults from population-based cohorts who were approximately uniformly distributed between 18 and 88 years (www.cam-can.com). We assessed directed connectivity within and between three key large-scale networks: the salience network, dorsal attention network, and default mode network. We found that age influences connectivity both within and between these networks, over and above the effects on neurovascular coupling. Canonical correlation analysis revealed that the relationship between network connectivity and cognitive function was age-dependent: cognitive performance relied on neural dynamics more strongly in older adults. These effects were driven partly by reduced stability of neural activity within all networks, as expressed by an accelerated decay of neural information. Our findings suggest that the balance of excitatory connectivity between networks, and the stability of intrinsic neural representations within networks, changes with age. The cognitive function of older adults becomes increasingly dependent on these factors. Maintaining cognitive function is critical to successful aging. To study the neural basis of cognitive function across the lifespan, we studied a large population

  12. A Bi-Level Programming Model for the Railway Express Cargo Service Network Design Problem

    Directory of Open Access Journals (Sweden)

    Boliang Lin

    2018-06-01

    Full Text Available Service network design is fundamentally crucial for railway express cargo transportation. The main challenge is to strike a balance between two conflicting objectives: low network setup costs and high expected operational incomes. Different configurations of these objectives will have different impacts on the quality of freight transportation services. In this paper, a bi-level programming model for the railway express cargo service network design problem is proposed. The upper-level model forms the optimal decisions in terms of the service characteristics, and the low-level model selects the service arcs for each commodity. The rail express cargo is strictly subject to the service commitment, the capacity restriction, flow balance constraints, and logical relationship constraints among the decisions variables. Moreover, linearization techniques are used to convert the lower-level model to a linear one so that it can be directly solved by a standard optimization solver. Finally, a real-world case study based on the Beijing–Guangzhou Railway Line is carried out to demonstrate the effectiveness and efficiency of the proposed solution approach.

  13. TSUNAMI HAZARD MITIGATION AND THE NOAA NATIONAL WATER LEVEL OBSERVATION NETWORK

    Directory of Open Access Journals (Sweden)

    James R. Hubbard

    2002-01-01

    Full Text Available With the renewed interest in regional Tsunami Warning Systems and the potential tsunami threats throughout the Caribbean and West coast of the United States, the National Ocean Service (NOS, National Water Level Observation Network (NWLON consisting of 175 primary stations, is well situated to play a role in the National Hazard Mitigation effort. In addition, information regarding local mean sea level trends and GPS derived geodetic datum relationships at numerous coastal locations is readily available for tsunami hazard assessment and mapping applications.Tsunami inundation maps and modeling are just two of the more important products which may be derived from NWLON data. In addition to the seven water level gauges that are hardwired into the West Coast and Alaska Tsunami Warning Center (WClATWC, NOS has a significant number of gauges with real-time satellite telemetry capabilities located along the Pacific Northwest coastline, the Gulf of Mexico and the Caribbean. These gauges, in concert with near shore buoy systems, have the potential for increasing the effectiveness of the existing tsunami warning system.The recent expansion of the Caribbean Sea Level Gauge Network through the NOS regional partnerships with Central American and Caribbean countries have opened an opportunity for a basin-wide tsunami warning network in a region which is ill prepared for a major tsunami event.

  14. Automatic adjustment of display window (gray-level condition) for MR images using neural networks

    International Nuclear Information System (INIS)

    Ohhashi, Akinami; Nambu, Kyojiro.

    1992-01-01

    We have developed a system to automatically adjust the display window width and level (WWL) for MR images using neural networks. There were three main points in the development of our system as follows: 1) We defined an index for the clarity of a displayed image, and called 'EW'. EW is a quantitative measure of the clarity of an image displayed in a certain WWL, and can be derived from the difference between gray-level with the WWL adjusted by a human expert and with a certain WWL. 2) We extracted a group of six features from a gray-level histogram of a displayed image. We designed two neural networks which are able to learn the relationship between these features and the desired output (teaching signal), 'EQ', which is normalized to 0 to 1.0 from EW. Two neural networks were used to share the patterns to be learned; one learns a variety of patterns with less accuracy, and the other learns similar patterns with accuracy. Learning was performed using a back-propagation method. As a result, the neural networks after learning are able to provide a quantitative measure, 'Q', of the clarity of images displayed in the designated WWL. 3) Using the 'Hill climbing' method, we have been able to determine the best possible WWL for a displaying image. We have tested this technique for MR brain images. The results show that this system can adjust WWL comparable to that adjusted by a human expert for the majority of test images. The neural network is effective for the automatic adjustment of the display window for MR images. We are now studying the application of this method to MR images of another regions. (author)

  15. Diffusion Imaging of Cerebral White Matter in Persons Who Stutter: Evidence for Network-Level Anomalies

    Directory of Open Access Journals (Sweden)

    Shanqing eCai

    2014-02-01

    Full Text Available Deficits in brain white matter have been a main focus of recent neuroimaging studies on stuttering. However, no prior study has examined brain connectivity on the global level of the cerebral cortex in persons who stutter (PWS. In the current study, we analyzed the results from probabilistic tractography between regions comprising the cortical speech network. An anatomical parcellation scheme was used to define 28 speech production-related ROIs in each hemisphere. We used network-based statistic (NBS and graph theory to analyze the connectivity patterns obtained from tractography. At the network level, the probabilistic corticocortical connectivity from the PWS group were significantly weaker that from persons with fluent speech (PFS. NBS analysis revealed significant components in the bilateral speech networks with negative correlations with stuttering severity. To facilitate comparison with previous studies, we also performed tract-based spatial statistics (TBSS and regional fractional anisotropy (FA averaging. Results from tractography, TBSS and regional FA averaging jointly highlight the importance of several regions in the left peri-Rolandic sensorimotor and premotor areas, most notably the left ventral premotor cortex and middle primary motor cortex, in the neuroanatomical basis of stuttering.

  16. Between “design” and “bricolage”: Genetic networks, levels of selection, and adaptive evolution

    Science.gov (United States)

    Wilkins, Adam S.

    2007-01-01

    The extent to which “developmental constraints” in complex organisms restrict evolutionary directions remains contentious. Yet, other forms of internal constraint, which have received less attention, may also exist. It will be argued here that a set of partial constraints below the level of phenotypes, those involving genes and molecules, influences and channels the set of possible evolutionary trajectories. At the top-most organizational level there are the genetic network modules, whose operations directly underlie complex morphological traits. The properties of these network modules, however, have themselves been set by the evolutionary history of the component genes and their interactions. Characterization of the components, structures, and operational dynamics of specific genetic networks should lead to a better understanding not only of the morphological traits they underlie but of the biases that influence the directions of evolutionary change. Furthermore, such knowledge may permit assessment of the relative degrees of probability of short evolutionary trajectories, those on the microevolutionary scale. In effect, a “network perspective” may help transform evolutionary biology into a scientific enterprise with greater predictive capability than it has hitherto possessed. PMID:17494754

  17. Between "design" and "bricolage": genetic networks, levels of selection, and adaptive evolution.

    Science.gov (United States)

    Wilkins, Adam S

    2007-05-15

    The extent to which "developmental constraints" in complex organisms restrict evolutionary directions remains contentious. Yet, other forms of internal constraint, which have received less attention, may also exist. It will be argued here that a set of partial constraints below the level of phenotypes, those involving genes and molecules, influences and channels the set of possible evolutionary trajectories. At the top-most organizational level there are the genetic network modules, whose operations directly underlie complex morphological traits. The properties of these network modules, however, have themselves been set by the evolutionary history of the component genes and their interactions. Characterization of the components, structures, and operational dynamics of specific genetic networks should lead to a better understanding not only of the morphological traits they underlie but of the biases that influence the directions of evolutionary change. Furthermore, such knowledge may permit assessment of the relative degrees of probability of short evolutionary trajectories, those on the microevolutionary scale. In effect, a "network perspective" may help transform evolutionary biology into a scientific enterprise with greater predictive capability than it has hitherto possessed.

  18. 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.

  19. Recent Progress in Some Active Topics on Complex Networks

    International Nuclear Information System (INIS)

    Gu, J; Zhu, Y; Wang, Q A; Guo, L; Jiang, J; Chi, L; Li, W; Cai, X

    2015-01-01

    Complex networks have been extensively studied across many fields, especially in interdisciplinary areas. It has since long been recognized that topological structures and dynamics are important aspects for capturing the essence of complex networks. The recent years have also witnessed the emergence of several new elements which play important roles in network study. By combining the results of different research orientations in our group, we provide here a review of the recent advances in regards to spectral graph theory, opinion dynamics, interdependent networks, graph energy theory and temporal networks. We hope this will be helpful for the newcomers of those fields to discover new intriguing topics. (paper)

  20. 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.

  1. 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.

  2. Physical Activity Level and Adiposity: Are they Associated with ...

    African Journals Online (AJOL)

    Information on self-reported physical activity (PA) level in association with primary dysmenorrhea (PD) is not readily available on African populations, and there is a dearth of information on the association of adiposity with PD. This study explored the association of PA and adiposity indices with PD and associated menstrual ...

  3. Malondialdehyde level and some enzymatic activities in subclinical ...

    African Journals Online (AJOL)

    The purpose of this study was to evaluate the changes occurring in milk malondialdehyde (MDA) level and some enzymatic activities as a result of subclinical mastitis (SCM) in dairy cows. A total of 124 milk samples were collected from 124 lactating cows from the same herd in the period between the 2nd week after calving ...

  4. Food choices, physical activity levels and other factors associated ...

    African Journals Online (AJOL)

    The aim of the study was to evaluate educators' health behaviours regarding dietary intake and physical activity (PA). A survey was undertaken in 517 educators at 83 primary schools in the Western Cape. Food choices (healthy vs. unhealthy), PA levels, and health knowledge were measured by questionnaire. The six most ...

  5. Physical activity level among children recovering from severe acute malnutrition

    DEFF Research Database (Denmark)

    Babirekere-Iriso, Esther; Rytter, Maren Johanne Heilskov; Namusoke, Hanifa

    2018-01-01

    OBJECTIVE: To assess the level and predictors of physical activity at discharge among children recovering from severe acute malnutrition (SAM). METHODS: We conducted a prospective study among 69 children 6 - 59 months of age admitted with SAM for nutritional rehabilitation at Mulago National...

  6. Seasonal disease activity and serum vitamin D levels in rheumatoid ...

    African Journals Online (AJOL)

    Background: Vitamin D is a steroid hormone that plays essential roles in calcium and phosphorus metabolism, bone formation and mineralization homeostasis, also has a role in the maintenance of immune-homeostasis. Objective: We aimed to investigate seasonal serum vitamin D levels and seasonal disease activity in ...

  7. Physical activity, fitness level and health problems of healthcare ...

    African Journals Online (AJOL)

    The aim of this study was to determine the level of physical activity of healthcare workers using the transtheoretical model (TTM) as a framework and to identify barriers to exercise. A self-administered questionnaire was distributed to 200 randomly selected hospital staff members in South Africa. The weight and height of the ...

  8. 34 CFR 300.704 - State-level activities.

    Science.gov (United States)

    2010-07-01

    ... mental health services for children with disabilities; (iv) To improve the use of technology in the... 34 Education 2 2010-07-01 2010-07-01 false State-level activities. 300.704 Section 300.704 Education Regulations of the Offices of the Department of Education (Continued) OFFICE OF SPECIAL EDUCATION...

  9. Self Reported Physical Activity Levels in Hypertensive Patients ...

    African Journals Online (AJOL)

    This was mainly described as brisk-walking 179(69.1%), jogging 27(10.4%), gymnasium workouts 13(5.1%), dancing 4(1.5), cycling 4(1.5%) and weight lifting ... There is need to engage hypertensive patients on the relevance of physical activity and encourage them to obtain the known benefits by optimizing their levels of ...

  10. INTERCONNECTING NETWORKS WITH DIFFERENT LEVELS OF SECURITY – A PRESENT NATO PROBLEM

    Directory of Open Access Journals (Sweden)

    LIVIU TATOMIR

    2016-07-01

    Full Text Available A situation often met in the Romanian Armed Forces in recent years is the need for interconnecting two networks (domains with different levels of classification. Considering that the Romanian armed troops are involved in numerous missions with NATO partners, solutions, already implemented across the organization, are considered to be applied in domestic systems, also. This paper presents the solutions adopted by NATO in order to solve the problem of cross -domains interconnections. We present the maturity level reached by these solutions and the possibility of implementing these solutions in the Romanian Armed Forces, with or without specific adaptation to our own rules and regulations. The goal is to use a NATO already proved solution to our national classified networks.

  11. Prostaglandin levels and lysosomal enzyme activities in irradiated rats

    International Nuclear Information System (INIS)

    Trocha, P.J.; Catravas, G.N.

    1980-01-01

    Whole-body irradiation of rats results in the release of hydrolases from lysosomes, an increase in lysosomal enzyme activities, and changes in the prostaglandin levels in spleen and liver tissues. A transient increase in the concentration of prostaglandins E and F and leakage of lysosomal hydrolases occurred in both spleen and liver tissues 3-6 hours after the animals were irradiated. Maximal values for hydrolase activities, prostaglandin E and F content, and release of lysosomal enzymes were found 4 days postirradiation in rat spleens whereas in the liver only slight increases were observed at this time period for prostaglandin F levels. On day 7 there was a final rise in the spleen's prostaglandin E and F concentrations and leakage of hydrolases from the lysosomes before returning to near normal values on day 11. The prostaglandin F concentration in liver was also slightly elevated on the 7th day after irradiation and then decreased to control levels. (author)

  12. Anti-Makeup: Learning A Bi-Level Adversarial Network for Makeup-Invariant Face Verification

    OpenAIRE

    Li, Yi; Song, Lingxiao; Wu, Xiang; He, Ran; Tan, Tieniu

    2017-01-01

    Makeup is widely used to improve facial attractiveness and is well accepted by the public. However, different makeup styles will result in significant facial appearance changes. It remains a challenging problem to match makeup and non-makeup face images. This paper proposes a learning from generation approach for makeup-invariant face verification by introducing a bi-level adversarial network (BLAN). To alleviate the negative effects from makeup, we first generate non-makeup images from makeu...

  13. Hybrid Scheduling/Signal-Level Coordination in the Downlink of Multi-Cloud Radio-Access Networks

    KAUST Repository

    Douik, Ahmed; Dahrouj, Hayssam; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim

    2016-01-01

    results suggest that the proposed hybrid scheduling strategy provides appreciable gain as compared to the scheduling-level coordinated networks, with a negligible degradation to signal-level coordination.

  14. MGluR5 mediates the interaction between late-LTP, network activity, and learning.

    Directory of Open Access Journals (Sweden)

    Arthur Bikbaev

    2008-05-01

    Full Text Available Hippocampal synaptic plasticity and learning are strongly regulated by metabotropic glutamate receptors (mGluRs and particularly by mGluR5. Here, we investigated the mechanisms underlying mGluR5-modulation of these phenomena. Prolonged pharmacological blockade of mGluR5 with MPEP produced a profound impairment of spatial memory. Effects were associated with 1 a reduction of mGluR1a-expression in the dentate gyrus; 2 impaired dentate gyrus LTP; 3 enhanced CA1-LTP and 4 suppressed theta (5-10 Hz and gamma (30-100 Hz oscillations in the dentate gyrus. Allosteric potentiation of mGluR1 after mGluR5 blockade significantly ameliorated dentate gyrus LTP, as well as suppression of gamma oscillatory activity. CA3-lesioning prevented MPEP effects on CA1-LTP, suggesting that plasticity levels in CA1 are driven by mGluR5-dependent synaptic and network activity in the dentate gyrus. These data support the hypothesis that prolonged mGluR5-inactivation causes altered hippocampal LTP levels and network activity, which is mediated in part by impaired mGluR1-expression in the dentate gyrus. The consequence is impairment of long-term learning.

  15. Causal Learning and Explanation of Deep Neural Networks via Autoencoded Activations

    OpenAIRE

    Harradon, Michael; Druce, Jeff; Ruttenberg, Brian

    2018-01-01

    Deep neural networks are complex and opaque. As they enter application in a variety of important and safety critical domains, users seek methods to explain their output predictions. We develop an approach to explaining deep neural networks by constructing causal models on salient concepts contained in a CNN. We develop methods to extract salient concepts throughout a target network by using autoencoders trained to extract human-understandable representations of network activations. We then bu...

  16. Three-dimensional neural cultures produce networks that mimic native brain activity.

    Science.gov (United States)

    Bourke, Justin L; Quigley, Anita F; Duchi, Serena; O'Connell, Cathal D; Crook, Jeremy M; Wallace, Gordon G; Cook, Mark J; Kapsa, Robert M I

    2018-02-01

    Development of brain function is critically dependent on neuronal networks organized through three dimensions. Culture of central nervous system neurons has traditionally been limited to two dimensions, restricting growth patterns and network formation to a single plane. Here, with the use of multichannel extracellular microelectrode arrays, we demonstrate that neurons cultured in a true three-dimensional environment recapitulate native neuronal network formation and produce functional outcomes more akin to in vivo neuronal network activity. Copyright © 2017 John Wiley & Sons, Ltd.

  17. 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.

  18. TWO-LEVEL HIERARCHICAL COORDINATION QUEUING METHOD FOR TELECOMMUNICATION NETWORK NODES

    Directory of Open Access Journals (Sweden)

    M. V. Semenyaka

    2014-07-01

    Full Text Available The paper presents hierarchical coordination queuing method. Within the proposed method a queuing problem has been reduced to optimization problem solving that was presented as two-level hierarchical structure. The required distribution of flows and bandwidth allocation was calculated at the first level independently for each macro-queue; at the second level solutions obtained on lower level for each queue were coordinated in order to prevent probable network link overload. The method of goal coordination has been determined for multilevel structure managing, which makes it possible to define the order for consideration of queue cooperation restrictions and calculation tasks distribution between levels of hierarchy. Decisions coordination was performed by the method of Lagrange multipliers. The study of method convergence has been carried out by analytical modeling.

  19. Effects of Curricular Activity on Students' Situational Motivation and Physical Activity Levels

    Science.gov (United States)

    Gao, Zan; Hannon, James C.; Newton, Maria; Huang, Chaoqun

    2011-01-01

    The purpose of this study was to examine (a) the effects of three curricular activities on students' situational motivation (intrinsic motivation [IM], identified regulation [IR], external regulation, and amotivation [AM]) and physical activity (PA) levels, and (b) the predictive strength of situational motivation to PA levels. Four hundred twelve…

  20. Global Production Networks and International Inequality: Making a Case for a Meso-Level Turn in Macro-Comparative Sociology

    Directory of Open Access Journals (Sweden)

    Mathew Mahutga

    2015-08-01

    Full Text Available In this article, I extend recent macro-comparative empirical research on the developmental implications of global production networks. I draw from theories of commodity/value chains, global production networks and economic sociology to identify three contending theoretical perspectives for exactly how the developmental returns to network participants should be distributed-cooperation, exploitation and differential gains-and derive testable hypotheses for each. Adding to recent empirical advances for measuring the average network position of firms at the country level, I evaluate these hypotheses by way of dynamic panel regression models of hourly wage rates in the garment and transportation equipment industries. The results suggest that macro-sociological theories linking underdevelopment to the structure of the world-economy, as well as theories of the distribution of the gains from network participation, miss important variation at the industry level. Cooperation provides a poor account of the distribution of the gains from network participation. Instead, both industries appear to distribute the gains from network participation differentially across network participants. However, the extent of this inequality increases, and the garment industry transitions to exploitation, when global production networks become entrenched organizational logics. Variation in the distribution of the returns to network participation is explicable only by accounting for production-network governance as it varies across industries and over time. I conclude by highlighting the analytical utility to macro-comparative sociology of a turn toward the mesa-level of global industries.

  1. Nano-engineered intrapores in nanoparticles of PtNi networks for increased oxygen reduction reaction activity

    Science.gov (United States)

    Ding, Jieting; Ji, Shan; Wang, Hui; Key, Julian; Brett, Dan J. L.; Wang, Rongfang

    2018-01-01

    Network-like metallic alloys of solid nanoparticles have been frequently reported as promising electrocatalysts for fuel cells. The three-dimensional structure of such networks is rich in pores in the form of voids between nanoparticles, which collectively expose a large surface area for catalytic activity. Herein, we present a novel solution to this problem using a precursor comprising a flocculent core-shell PtNi@Ni to produce PtNi network catalysts with nanoparticle intraporosity after carefully controlled electrochemical dealloying. Physical characterization shows a hierarchical level of nanoporosity (intrapores within nanoparticles and pores between them) evolves during the controlled electrochemical dealloying, and that a Pt-rich surface also forms after 22 cycles of Ni leaching. In ORR cycling, the PtNi networks gain 4-fold activity in both jECSA and jmass over a state of the art Pt/C electrocatalyst, and also significantly exceed previously reported PtNi networks. In ORR degradation tests, the PtNi networks also proved stable, dropping by 30.4% and 62.6% in jECSA and jmass respectively. The enhanced performance of the catalyst is evident, and we also propose that the presented synthesis procedure can be generally applied to developing other metallic networks.

  2. 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.

  3. Activity-Driven Influence Maximization in Social Networks

    DEFF Research Database (Denmark)

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

    2017-01-01

    -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.......Interaction networks consist of a static graph with a timestamped list of edges over which interaction took place. Examples of interaction networks are social networks whose users interact with each other through messages or location-based social networks where people interact by checking...

  4. System level mechanisms of adaptation, learning, memory formation and evolvability: the role of chaperone and other networks.

    Science.gov (United States)

    Gyurko, David M; Soti, Csaba; Stetak, Attila; Csermely, Peter

    2014-05-01

    During the last decade, network approaches became a powerful tool to describe protein structure and dynamics. Here, we describe first the protein structure networks of molecular chaperones, then characterize chaperone containing sub-networks of interactomes called as chaperone-networks or chaperomes. We review the role of molecular chaperones in short-term adaptation of cellular networks in response to stress, and in long-term adaptation discussing their putative functions in the regulation of evolvability. We provide a general overview of possible network mechanisms of adaptation, learning and memory formation. We propose that changes of network rigidity play a key role in learning and memory formation processes. Flexible network topology provides ' learning-competent' state. Here, networks may have much less modular boundaries than locally rigid, highly modular networks, where the learnt information has already been consolidated in a memory formation process. Since modular boundaries are efficient filters of information, in the 'learning-competent' state information filtering may be much smaller, than after memory formation. This mechanism restricts high information transfer to the 'learning competent' state. After memory formation, modular boundary-induced segregation and information filtering protect the stored information. The flexible networks of young organisms are generally in a 'learning competent' state. On the contrary, locally rigid networks of old organisms have lost their 'learning competent' state, but store and protect their learnt information efficiently. We anticipate that the above mechanism may operate at the level of both protein-protein interaction and neuronal networks.

  5. Reciprocal Reinforcement Between Wearable Activity Trackers and Social Network Services in Influencing Physical Activity Behaviors.

    Science.gov (United States)

    Chang, Rebecca Cherng-Shiow; Lu, Hsi-Peng; Yang, Peishan; Luarn, Pin

    2016-07-05

    Wearable activity trackers (WATs) are emerging consumer electronic devices designed to support physical activities (PAs), which are based on successful behavior change techniques focusing on goal-setting and frequent behavioral feedbacks. Despite their utility, data from both recent academic and market research have indicated high attrition rates of WAT users. Concurrently, evidence shows that social support (SS), delivered/obtained via social network services or sites (SNS), could increase adherence and engagement of PA intervention programs. To date, relatively few studies have looked at how WATs and SS may interact and affect PAs. The purpose of this study was to explore how these two Internet and mobile technologies, WATs and SNS, could work together to foster sustainable PA behavior changes and habits among middle-aged adults (40-60 years old) in Taiwan. We used purposive sampling of Executive MBA Students from National Taiwan University of Science and Technology to participate in our qualitative research. In-depth interviews and focus groups were conducted with a total of 15 participants, including 9 WAT users and 6 nonusers. Analysis of the collected materials was done inductively using the thematic approach with no preset categories. Two authors from different professional backgrounds independently annotated and coded the transcripts, and then discussed and debated until consensus was reached on the final themes. The thematic analysis revealed six themes: (1) WATs provided more awareness than motivation in PA with goal-setting and progress monitoring, (2) SS, delivered/obtained via SNS, increased users' adherence and engagement with WATs and vice versa, (3) a broad spectrum of configurations would be needed to deliver WATs with appropriately integrated SS functions, (4) WAT design, style, and appearance mattered even more than those of smartphones, as they are body-worn devices, (5) the user interfaces of WATs left a great deal to be desired, and (6

  6. 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.

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

    OpenAIRE

    Lei, Yanjun; Jiang, Xin; 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 a...

  8. A distributed monitoring system for photovoltaic arrays based on a two-level wireless sensor network

    Science.gov (United States)

    Su, F. P.; Chen, Z. C.; Zhou, H. F.; Wu, L. J.; Lin, P. J.; Cheng, S. Y.; Li, Y. F.

    2017-11-01

    In this paper, a distributed on-line monitoring system based on a two-level wireless sensor network (WSN) is proposed for real time status monitoring of photovoltaic (PV) arrays to support the fine management and maintenance of PV power plants. The system includes the sensing nodes installed on PV modules (PVM), sensing and routing nodes installed on combiner boxes of PV sub-arrays (PVA), a sink node and a data management centre (DMC) running on a host computer. The first level WSN is implemented by the low-cost wireless transceiver nRF24L01, and it is used to achieve single hop communication between the PVM nodes and their corresponding PVA nodes. The second level WSN is realized by the CC2530 based ZigBee network for multi-hop communication among PVA nodes and the sink node. The PVM nodes are used to monitor the PVM working voltage and backplane temperature, and they send the acquired data to their PVA node via the nRF24L01 based first level WSN. The PVA nodes are used to monitor the array voltage, PV string current and environment irradiance, and they send the acquired and received data to the DMC via the ZigBee based second level WSN. The DMC is designed using the MATLAB GUIDE and MySQL database. Laboratory experiment results show that the system can effectively acquire, display, store and manage the operating and environment parameters of PVA in real time.

  9. Anthropogenic noise alters bat activity levels and echolocation calls

    Directory of Open Access Journals (Sweden)

    Jessie P. Bunkley

    2015-01-01

    Full Text Available Negative impacts from anthropogenic noise are well documented for many wildlife taxa. Investigations of the effects of noise on bats however, have not been conducted outside of the laboratory. Bats that hunt arthropods rely on auditory information to forage. Part of this acoustic information can fall within the spectrum of anthropogenic noise, which can potentially interfere with signal reception and processing. Compressor stations associated with natural gas extraction produce broadband noise 24 hours a day, 365 days a year. With over half a million producing gas wells in the U.S. this infrastructure is a major source of noise pollution across the landscape. We conducted a ‘natural experiment’ in the second largest gas extraction field in the U.S. to investigate the potential effects of gas compressor station noise on the activity levels of the local bat assemblage. We used acoustic monitoring to compare the activity level (number of minutes in a night with a bat call of the bat assemblage at sites with compressor stations to sites lacking this infrastructure. We found that activity levels for the Brazilian free-tailed bat (Tadarida brasiliensis were 40% lower at loud compressor sites compared to quieter well pads, whereas the activity levels of four other species (Myotis californicus, M. cillolabrum, M. lucifugus, Parastrellus hesperus were not affected by noise. Furthermore, our results reveal that the assemblage of bat species emitting low frequency (35 kHz echolocation did not exhibit altered activity levels in noise. Lower activity levels of Brazilian free-tailed bats at loud sites indicate a potential reduction in habitat for this species. Additionally, a comparison of echolocation search calls produced by free-tailed bats at sites with and without compressor stations reveal that this species modifies its echolocation search calls in noise—producing longer calls with a narrower bandwidth. Call alterations might affect prey

  10. 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...... structure. The results indicate that the tourist-activated network for the destination is rather sparse and that there are clearly differences in core and peripheral nodes. The findings illustrate the structure of a tourist-activated network and provide implications for technology design and tourism...

  11. New Perspectives on Spontaneous Brain Activity: Dynamic Networks and Energy Matter.

    Science.gov (United States)

    Tozzi, Arturo; Zare, Marzieh; Benasich, April A

    2016-01-01

    Spontaneous brain activity has received increasing attention as demonstrated by the exponential rise in the number of published article on this topic over the last 30 years. Such "intrinsic" brain activity, generated in the absence of an explicit task, is frequently associated with resting-state or default-mode networks (DMN)s. The focus on characterizing spontaneous brain activity promises to shed new light on questions concerning the structural and functional architecture of the brain and how they are related to "mind". However, many critical questions have yet to be addressed. In this review, we focus on a scarcely explored area, specifically the energetic requirements and constraints of spontaneous activity, taking into account both thermodynamical and informational perspectives. We argue that the "classical" definitions of spontaneous activity do not take into account an important feature, that is, the critical thermodynamic energetic differences between spontaneous and evoked brain activity. Spontaneous brain activity is associated with slower oscillations compared with evoked, task-related activity, hence it exhibits lower levels of enthalpy and "free-energy" (i.e., the energy that can be converted to do work), thus supporting noteworthy thermodynamic energetic differences between spontaneous and evoked brain activity. Increased spike frequency during evoked activity has a significant metabolic cost, consequently, brain functions traditionally associated with spontaneous activity, such as mind wandering, require less energy that other nervous activities. We also review recent empirical observations in neuroscience, in order to capture how spontaneous brain dynamics and mental function can be embedded in a non-linear dynamical framework, which considers nervous activity in terms of phase spaces, particle trajectories, random walks, attractors and/or paths at the edge of the chaos. This takes us from the thermodynamic free-energy, to the realm of "variational

  12. Cooperative wireless network control based health and activity monitoring system.

    Science.gov (United States)

    Prakash, R; Ganesh, A Balaji; Girish, Siva V

    2016-10-01

    A real-time cooperative communication based wireless network is presented for monitoring health and activity of an end-user in their environment. The cooperative communication offers better energy consumption and also an opportunity to aware the current location of a user non-intrusively. The link between mobile sensor node and relay node is dynamically established by using Received Signal Strength Indicator (RSSI) and Link Quality Indicator (LQI) based on adaptive relay selection scheme. The study proposes a Linear Acceleration based Transmission Power Decision Control (LA-TPDC) algorithm to further enhance the energy efficiency of cooperative communication. Further, the occurrences of false alarms are carefully prevented by introducing three stages of sequential warning system. The real-time experiments are carried-out by using the nodes, namely mobile sensor node, relay nodes and a destination node which are indigenously developed by using a CC430 microcontroller integrated with an in-built transceiver at 868 MHz. The wireless node performance characteristics, such as energy consumption, Signal-Noise ratio (SNR), Bit Error Rate (BER), Packet Delivery Ratio (PDR) and transmission offset are evaluated for all the participated nodes. The experimental results observed that the proposed linear acceleration based transmission power decision control algorithm almost doubles the battery life time than energy efficient conventional cooperative communication.

  13. Evaluation of the activity levels in fusion reactor blankets

    International Nuclear Information System (INIS)

    Gruber, J.

    1977-05-01

    The activation of a fusion reactor blanket (316 SS or V-10Cr-10Ti as structure) with a minimum lithium inventory has been calculated for 0.83 MW/m 2 wall load. The resulting radiation levels and waste problems are discussed. The dose rate near the steel structure will always be higher than 0.1 rem/h due to its niobium content. After 200 to 100,000 years of decay the potential biological hazard originating from this high level fusion reactor waste (with plutonium recyclation). (orig.) [de

  14. Evaluation of the Performance of Feedforward and Recurrent Neural Networks in Active Cancellation of Sound Noise

    OpenAIRE

    Mehrshad Salmasi; Homayoun Mahdavi-Nasab

    2012-01-01

    Active noise control is based on the destructive interference between the primary noise and generated noise from the secondary source. An antinoise of equal amplitude and opposite phase is generated and combined with the primary noise. In this paper, performance of the neural networks is evaluated in active cancellation of sound noise. For this reason, feedforward and recurrent neural networks are designed and trained. After training, performance of the feedforwrad and recurrent networks in n...

  15. Dynamics on networks: the role of local dynamics and global networks on the emergence of hypersynchronous neural activity.

    Directory of Open Access Journals (Sweden)

    Helmut Schmidt

    2014-11-01

    Full Text Available Graph theory has evolved into a useful tool for studying complex brain networks inferred from a variety of measures of neural activity, including fMRI, DTI, MEG and EEG. In the study of neurological disorders, recent work has discovered differences in the structure of graphs inferred from patient and control cohorts. However, most of these studies pursue a purely observational approach; identifying correlations between properties of graphs and the cohort which they describe, without consideration of the underlying mechanisms. To move beyond this necessitates the development of computational modeling approaches to appropriately interpret network interactions and the alterations in brain dynamics they permit, which in the field of complexity sciences is known as dynamics on networks. In this study we describe the development and application of this framework using modular networks of Kuramoto oscillators. We use this framework to understand functional networks inferred from resting state EEG recordings of a cohort of 35 adults with heterogeneous idiopathic generalized epilepsies and 40 healthy adult controls. Taking emergent synchrony across the global network as a proxy for seizures, our study finds that the critical strength of coupling required to synchronize the global network is significantly decreased for the epilepsy cohort for functional networks inferred from both theta (3-6 Hz and low-alpha (6-9 Hz bands. We further identify left frontal regions as a potential driver of seizure activity within these networks. We also explore the ability of our method to identify individuals with epilepsy, observing up to 80% predictive power through use of receiver operating characteristic analysis. Collectively these findings demonstrate that a computer model based analysis of routine clinical EEG provides significant additional information beyond standard clinical interpretation, which should ultimately enable a more appropriate mechanistic

  16. Performance of a Two-Level Call Admission Control Scheme for DS-CDMA Wireless Networks

    Directory of Open Access Journals (Sweden)

    Fapojuwo Abraham O

    2007-01-01

    Full Text Available We propose a two-level call admission control (CAC scheme for direct sequence code division multiple access (DS-CDMA wireless networks supporting multimedia traffic and evaluate its performance. The first-level admission control assigns higher priority to real-time calls (also referred to as class 0 calls in gaining access to the system resources. The second level admits nonreal-time calls (or class 1 calls based on the resources remaining after meeting the resource needs for real-time calls. However, to ensure some minimum level of performance for nonreal-time calls, the scheme reserves some resources for such calls. The proposed two-level CAC scheme utilizes the delay-tolerant characteristic of non-real-time calls by incorporating a queue to temporarily store those that cannot be assigned resources at the time of initial access. We analyze and evaluate the call blocking, outage probability, throughput, and average queuing delay performance of the proposed two-level CAC scheme using Markov chain theory. The analytic results are validated by simulation results. The numerical results show that the proposed two-level CAC scheme provides better performance than the single-level CAC scheme. Based on these results, it is concluded that the proposed two-level CAC scheme serves as a good solution for supporting multimedia applications in DS-CDMA wireless communication systems.

  17. Performance of a Two-Level Call Admission Control Scheme for DS-CDMA Wireless Networks

    Directory of Open Access Journals (Sweden)

    Abraham O. Fapojuwo

    2007-11-01

    Full Text Available We propose a two-level call admission control (CAC scheme for direct sequence code division multiple access (DS-CDMA wireless networks supporting multimedia traffic and evaluate its performance. The first-level admission control assigns higher priority to real-time calls (also referred to as class 0 calls in gaining access to the system resources. The second level admits nonreal-time calls (or class 1 calls based on the resources remaining after meeting the resource needs for real-time calls. However, to ensure some minimum level of performance for nonreal-time calls, the scheme reserves some resources for such calls. The proposed two-level CAC scheme utilizes the delay-tolerant characteristic of non-real-time calls by incorporating a queue to temporarily store those that cannot be assigned resources at the time of initial access. We analyze and evaluate the call blocking, outage probability, throughput, and average queuing delay performance of the proposed two-level CAC scheme using Markov chain theory. The analytic results are validated by simulation results. The numerical results show that the proposed two-level CAC scheme provides better performance than the single-level CAC scheme. Based on these results, it is concluded that the proposed two-level CAC scheme serves as a good solution for supporting multimedia applications in DS-CDMA wireless communication systems.

  18. Two-level Robust Measurement Fusion Kalman Filter for Clustering Sensor Networks

    Institute of Scientific and Technical Information of China (English)

    ZHANG Peng; QI Wen-Juan; DENG Zi-Li

    2014-01-01

    This paper investigates the distributed fusion Kalman filtering over clustering sensor networks. The sensor network is partitioned as clusters by the nearest neighbor rule and each cluster consists of sensing nodes and cluster-head. Using the minimax robust estimation principle, based on the worst-case conservative system with the conservative upper bounds of noise variances, two-level robust measurement fusion Kalman filter is presented for the clustering sensor network systems with uncertain noise variances. It can significantly reduce the communication load and save energy when the number of sensors is very large. A Lyapunov equation approach for the robustness analysis is presented, by which the robustness of the local and fused Kalman filters is proved. The concept of the robust accuracy is presented, and the robust accuracy relations among the local and fused robust Kalman filters are proved. It is proved that the robust accuracy of the two-level weighted measurement fuser is equal to that of the global centralized robust fuser and is higher than those of each local robust filter and each local weighted measurement fuser. A simulation example shows the correctness and effectiveness of the proposed results.

  19. Structural architecture supports functional organization in the human aging brain at a regionwise and network level.

    Science.gov (United States)

    Zimmermann, Joelle; Ritter, Petra; Shen, Kelly; Rothmeier, Simon; Schirner, Michael; McIntosh, Anthony R

    2016-07-01

    Functional interactions in the brain are constrained by the underlying anatomical architecture, and structural and functional networks share network features such as modularity. Accordingly, age-related changes of structural connectivity (SC) may be paralleled by changes in functional connectivity (FC). We provide a detailed qualitative and quantitative characterization of the SC-FC coupling in human aging as inferred from resting-state blood oxygen-level dependent functional magnetic resonance imaging and diffusion-weighted imaging in a sample of 47 adults with an age range of 18-82. We revealed that SC and FC decrease with age across most parts of the brain and there is a distinct age-dependency of regionwise SC-FC coupling and network-level SC-FC relations. A specific pattern of SC-FC coupling predicts age more reliably than does regionwise SC or FC alone (r = 0.73, 95% CI = [0.7093, 0.8522]). Hence, our data propose that regionwise SC-FC coupling can be used to characterize brain changes in aging. Hum Brain Mapp 37:2645-2661, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  20. Automatic compilation from high-level biologically-oriented programming language to genetic regulatory networks.

    Science.gov (United States)

    Beal, Jacob; Lu, Ting; Weiss, Ron

    2011-01-01

    The field of synthetic biology promises to revolutionize our ability to engineer biological systems, providing important benefits for a variety of applications. Recent advances in DNA synthesis and automated DNA assembly technologies suggest that it is now possible to construct synthetic systems of significant complexity. However, while a variety of novel genetic devices and small engineered gene networks have been successfully demonstrated, the regulatory complexity of synthetic systems that have been reported recently has somewhat plateaued due to a variety of factors, including the complexity of biology itself and the lag in our ability to design and optimize sophisticated biological circuitry. To address the gap between DNA synthesis and circuit design capabilities, we present a platform that enables synthetic biologists to express desired behavior using a convenient high-level biologically-oriented programming language, Proto. The high level specification is compiled, using a regulatory motif based mechanism, to a gene network, optimized, and then converted to a computational simulation for numerical verification. Through several example programs we illustrate the automated process of biological system design with our platform, and show that our compiler optimizations can yield significant reductions in the number of genes (~ 50%) and latency of the optimized engineered gene networks. Our platform provides a convenient and accessible tool for the automated design of sophisticated synthetic biological systems, bridging an important gap between DNA synthesis and circuit design capabilities. Our platform is user-friendly and features biologically relevant compiler optimizations, providing an important foundation for the development of sophisticated biological systems.

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

    NARCIS (Netherlands)

    Hjorth, J.J.J.; Dawitz, J.; Kroon, T.; da Silva Dias Pires, J.H.; Dassen, V.J.; Berkhout, J.A.; Emperador Melero, J.; Nadadhur, A.G.; Alevra, M.; Toonen, R.F.G.; Heine, V.M.; Mansvelder, H.D.; Meredith, R.M.

    2016-01-01

    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

  2. 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...

  3. 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. In this mo...

  4. Distributed state estimation for multi-agent based active distribution networks

    NARCIS (Netherlands)

    Nguyen, H.P.; Kling, W.L.

    2010-01-01

    Along with the large-scale implementation of distributed generators, the current distribution networks have changed gradually from passive to active operation. State estimation plays a vital role to facilitate this transition. In this paper, a suitable state estimation method for the active network

  5. Adaptive Relay Activation in the Network Coding Protocols

    DEFF Research Database (Denmark)

    Pahlevani, Peyman; Roetter, Daniel Enrique Lucani; Fitzek, Frank

    2015-01-01

    State-of-the-art Network coding based routing protocols exploit the link quality information to compute the transmission rate in the intermediate nodes. However, the link quality discovery protocols are usually inaccurate, and introduce overhead in wireless mesh networks. In this paper, we presen...

  6. Finding Influential Spreaders from Human Activity beyond Network Location.

    Science.gov (United States)

    Min, Byungjoon; Liljeros, Fredrik; Makse, Hernán A

    2015-01-01

    Most centralities proposed for identifying influential spreaders on social networks to either spread a message or to stop an epidemic require the full topological information of the network on which spreading occurs. In practice, however, collecting all connections between agents in social networks can be hardly achieved. As a result, such metrics could be difficult to apply to real social networks. Consequently, a new approach for identifying influential people without the explicit network information is demanded in order to provide an efficient immunization or spreading strategy, in a practical sense. In this study, we seek a possible way for finding influential spreaders by using the social mechanisms of how social connections are formed in real networks. We find that a reliable immunization scheme can be achieved by asking people how they interact with each other. From these surveys we find that the probabilistic tendency to connect to a hub has the strongest predictive power for influential spreaders among tested social mechanisms. Our observation also suggests that people who connect different communities is more likely to be an influential spreader when a network has a strong modular structure. Our finding implies that not only the effect of network location but also the behavior of individuals is important to design optimal immunization or spreading schemes.

  7. Finding Influential Spreaders from Human Activity beyond Network Location.

    Directory of Open Access Journals (Sweden)

    Byungjoon Min

    Full Text Available Most centralities proposed for identifying influential spreaders on social networks to either spread a message or to stop an epidemic require the full topological information of the network on which spreading occurs. In practice, however, collecting all connections between agents in social networks can be hardly achieved. As a result, such metrics could be difficult to apply to real social networks. Consequently, a new approach for identifying influential people without the explicit network information is demanded in order to provide an efficient immunization or spreading strategy, in a practical sense. In this study, we seek a possible way for finding influential spreaders by using the social mechanisms of how social connections are formed in real networks. We find that a reliable immunization scheme can be achieved by asking people how they interact with each other. From these surveys we find that the probabilistic tendency to connect to a hub has the strongest predictive power for influential spreaders among tested social mechanisms. Our observation also suggests that people who connect different communities is more likely to be an influential spreader when a network has a strong modular structure. Our finding implies that not only the effect of network location but also the behavior of individuals is important to design optimal immunization or spreading schemes.

  8. Mediating Role of Activity Level in the Depressive Realism Effect

    OpenAIRE

    Blanco, Fernando; Matute, Helena; A. Vadillo, Miguel

    2012-01-01

    Several classic studies have concluded that the accuracy of identifying uncontrollable situations depends heavily on depressive mood. Nondepressed participants tend to exhibit an optimistic illusion of control, whereas depressed participants tend to better detect a lack of control. Recently, we suggested that the different activity levels (measured as the probability of responding during a contingency learning task) exhibited by depressed and nondepressed individuals is partly responsible for...

  9. Determinants of anti-corruption activities at the regional level

    Directory of Open Access Journals (Sweden)

    T. I. Ovchinnikova

    2018-01-01

    Full Text Available The article explores the concept of corruption, defined as an obstacle to economic and social development, created by representatives of the power structures of the country, region, enterprise, weakening the efficiency of management and the institutional foundation of society. Anticorruption activity is presented in the article as conditions created by the state and ensuring that the country's economy is not irreparably damaged by internal and external economic threats. The estimated characteristics of the anti-corruption activities of the regions and the country as a whole, as a rule, are studied in the domestic sources and among foreign authors. Statistical evaluation of the relationship between the level of corruption and indicators: the dynamics of GRP growth, the index of real incomes of the population, the costs of training, health care is made on the basis of the coefficient Pearson correlation. Based on the correlation analysis, stable links were established between the level of corruption and the socio-economic indicators of the region's development: an increase in the level of corruption associated with an increase in the population's spending on education and medicine; a reduction in the level of corruption, as a result of increased incomes of the population and higher wages. The consequences of corruption are presented: legal (the undeveloped legislative base, which involves bribery of powerful people, the growth of corruption in the society, the increase in corruption crimes, the inefficiency of the regulatory framework, social (moral violation, low public evaluation of the activities of power structures, low level of culture and upbringing , economic (bias financial, investment decisions, illegal distribution of property and non-property benefits, the impossibility of competitors Vat with developed countries and others.

  10. Cardiorespiratory fitness and physical activity level in adolescents

    Directory of Open Access Journals (Sweden)

    Viviane Schultz Straatmann

    2014-12-01

    Full Text Available DOI: http://dx.doi.org/10.5007/1980-0037.2015v17n1p21   More objective methods to detect inactive adolescents may help identify young people that are vulnerable to obesity and other chronic diseases. The objective of this study was to examine the association between classifications obtained with the cardiorespiratory fitness test and physical activity level in adolescents, as well as the agreement between tertiles and z-score distribution of the variables generated with these methods (distance covered and total physical activity score. A cross-sectional study was conducted using a random sample of 639 adolescents (61% girls aged 12 to 19 years (mean age of 16 ± 1.8 and categorized into two age groups: 12-13 and 14-19 years, from public schools in Niterói, Rio de Janeiro, Brazil. Cardiorespiratory fitness was assessed by a 9-min run/walk test (T9 and physical activity level by the International Physical Activity Questionnaire (IPAQ. The chi-square test (or Fisher’s exact test and Kruskal-Wallis test were applied for the evaluation of associations, and the weighted kappa coefficient and intraclass correlation coefficient were used to investigate agreement between variables. A level of significance of p<0.05 was adopted. A significant association between the classifications obtained with the two methods was only observed for adolescents aged ≥ 14 years. However, there was agreement between the variables generated with the two methods in both age groups. The median distance covered in the T9 increased according to tertiles of total physical activity score. An association between the classifications obtained with the IPAQ and T9 was only found for older adolescents. However, the continuous variables and variables categorized into tertiles generated with the methods were associated and showed agreement in both age groups.

  11. Object-oriented Approach to High-level Network Monitoring and Management

    Science.gov (United States)

    Mukkamala, Ravi

    2000-01-01

    An absolute prerequisite for the management of large investigating methods to build high-level monitoring computer networks is the ability to measure their systems that are built on top of existing monitoring performance. Unless we monitor a system, we cannot tools. Due to the heterogeneous nature of the hope to manage and control its performance. In this underlying systems at NASA Langley Research Center, paper, we describe a network monitoring system that we use an object-oriented approach for the design, we are currently designing and implementing. Keeping, first, we use UML (Unified Modeling Language) to in mind the complexity of the task and the required model users' requirements. Second, we identify the flexibility for future changes, we use an object-oriented existing capabilities of the underlying monitoring design methodology. The system is built using the system. Third, we try to map the former with the latter. APIs offered by the HP OpenView system.

  12. Mining Community-Level Influence in Microblogging Network: A Case Study on Sina Weibo

    Directory of Open Access Journals (Sweden)

    Yufei Liu

    2017-01-01

    Full Text Available Social influence analysis is important for many social network applications, including recommendation and cybersecurity analysis. We observe that the influence of community including multiple users outweighs the individual influence. Existing models focus on the individual influence analysis, but few studies estimate the community influence that is ubiquitous in online social network. A major challenge lies in that researchers need to take into account many factors, such as user influence, social trust, and user relationship, to model community-level influence. In this paper, aiming to assess the community-level influence effectively and accurately, we formulate the problem of modeling community influence and construct a community-level influence analysis model. It first eliminates the zombie fans and then calculates the user influence. Next, it calculates the user final influence by combining the user influence and the willingness of diffusing theme information. Finally, it evaluates the community influence by comprehensively studying the user final influence, social trust, and relationship tightness between intrausers of communities. To handle real-world applications, we propose a community-level influence analysis algorithm called CIAA. Empirical studies on a real-world dataset from Sina Weibo demonstrate the superiority of the proposed model.

  13. The relationship between postnatal depression, sociodemographic factors, levels of partner support, and levels of physical activity

    Directory of Open Access Journals (Sweden)

    Maryam eSaligeh

    2014-07-01

    Full Text Available Background: postnatal depression (PND is defined as a psychological mood disorder that occurs in a mother within six weeks of her giving birth. It refers to an episode that causes mood disturbance and it could begin in, or extend into, the postpartum period. It is thought to have a high impact upon the mother’s health as well as the family’s functioning and the child’s development. Socio-demographic, psych-social, and physical activity factors may all contribute to postpartum mood and ability to cope with responsibilities. The primary aim of this study was to determine which of these factors predicted PND in postpartum women. A secondary aim was to identify the socio-demographic and psycho-social predictors of physical activity in postpartum women . Methods: The study used a cross-sectional correlational design. A sample of 150 postpartum women was sent a package of six standardised questionnaires. Results: There was no association between physical activity and PND; however, older mothers, mothers of younger children, mothers who are less reluctant to ask for help, and mothers who are more satisfied with the help they get experience lower levels of PND. Mothers of older babies, mothers with more children, and less educated mothers are more likely to engage in caregiving activities, whereas mothers with fewer children and higher levels of partner support are more likely to engage in occupational activities. None of the socio-demographic factors or any of the parenting factors predicted levels of sporting activity.

  14. Inefficient preparatory fMRI-BOLD network activations predict working memory dysfunctions in patients with schizophrenia

    Directory of Open Access Journals (Sweden)

    Anja eBaenninger

    2016-03-01

    Full Text Available Patients with schizophrenia show abnormal dynamics and structure of temporally coherent networks (TCNs assessed using fMRI, which undergo adaptive shifts in preparation for a cognitively demanding task. During working memory (WM tasks, patients with schizophrenia show persistent deficits in TCNs as well as EEG indices of WM. Studying their temporal relationship during WM tasks might provide novel insights into WM performance deficits seen in schizophrenia.Simultaneous EEG-fMRI data were acquired during the performance of a verbal Sternberg WM task with two load levels (load 2 & load 5 in 17 patients with schizophrenia and 17 matched healthy controls. Using covariance mapping, we investigated the relationship of the activity in the TCNs before the memoranda were encoded and EEG spectral power during the retention interval. We assessed four TCNs – default mode network (DMN, dorsal attention network (dAN, left and right working memory networks (WMNs – and three EEG bands – theta, alpha, and beta.In healthy controls, there was a load dependent inverse relation between DMN and frontal-midline theta power and an anti-correlation between DMN and dAN. Both effects were not significantly detectable in patients. In addition, healthy controls showed a left-lateralized load-dependent recruitment of the WMNs. Activation of the WMNs was bilateral in patients, suggesting more resources were recruited for successful performance on the WM task.Our findings support the notion of schizophrenia patients showing deviations in their neurophysiological responses before the retention of relevant information in a verbal WM task. Thus, treatment strategies as neurofeedback targeting pre-states could be beneficial as task performance relies on the preparatory state of the brain.

  15. Associations between personality traits, physical activity level, and muscle strength

    Science.gov (United States)

    Tolea, Magdalena I.; Terracciano, Antonio; Simonsick, Eleanor M.; Metter, E. Jeffrey; Costa, Paul T.; Ferrucci, Luigi

    2013-01-01

    Associations among personality as measured by the Five Factor Model, physical activity, and muscle strength were assessed using data from the Baltimore Longitudinal Study of Aging (N = 1220, age: mean = 58, SD = 16). General linear modeling with adjustment for age, sex, race, and body mass index, and bootstrapping for mediation were used. We found neuroticism and most of its facets to negatively correlate with strength. The extraversion domain and its facets of warmth, activity, and positive-emotions were positively correlated with strength, independent of covariates. Mediation analysis results suggest that these associations are partly explained by physical activity level. Findings extend the evidence of an association between personality and physical function to its strength component and indicate health behavior as an important pathway. PMID:23966753

  16. Physical activity level and exercise in patients with diabetes mellitus.

    Science.gov (United States)

    Duarte, Camila Kümmel; Almeida, Jussara Carnevale de; Merker, Aline Juliana Schneider; Brauer, Fabiane de Oliveira; Rodrigues, Ticiana da Costa

    2012-01-01

    To compare physical activity level (PAL) and care related to exercise in patients with diabetes mellitus (DM). DM outpatients (adult, insulin-user patients) were assessed for PAL (international questionnaire; moderate- and high-level activities, as well as walking, over a typical week) and questioned about formal exercise practice, self-care, and hypoglycemic episodes related to exercise or reasons for not exercising. Two hundred twenty five patients were assessed: 107 (47.6%) had type 2 diabetes mellitus (DM2) and 118 (52.4%) had type 1 diabetes mellitus (DM1), with a larger percentage of patients with DM2 being classified as poorly active [33 (30.7%) versus 12 (10.3%)] and a lower percentage being classified as highly active [9 (8.7%) versus 29 (25%)], compared with patients having DM1. Patients who do not exercise (n = 140) gave different reasons for not doing so: patients with DM2 claimed that they "felt uncomfortable", "presented medical restrictions", and "did not like it"; DM1 patients claimed that they "had no time to exercise", "were lazy", and "had hypoglycemic episodes". Only 85 patients exercised regularly, regardless of the PAL, and 38.8% performed self-care, such as eating, stretching, and capillary glucose monitoring. Patients with DM2 [5 (14.3%)] reported a lower number of hypoglycemic episodes related to exercise than those with DM1 [17 (34%)]. Patients with DM2 have different PAL and behavior related to exercise than those seen in DM1 patients.

  17. Theory-based physical activity beliefs by race and activity levels among older adults.

    Science.gov (United States)

    Kosma, Maria; Cardinal, Bradley J

    2016-01-01

    Given the benefits of physical activity and the high proportion of inactivity among older adults, the purpose was to elicit theory-based behavioral, normative, and control physical activity beliefs among 140 educationally and economically diverse older adults and compare their beliefs by race (Blacks vs. Whites) and physical activity levels (inactive/underactive vs. highly active individuals). This was an elicitation study that took place in eight, mostly rural community settings in a Southeastern US state, such as Council of Aging Offices, retirement centers, and churches. Participants' behavioral, normative, and control beliefs were elicited via in person interviews. A valid and reliable questionnaire was also used to assess their physical activity levels. According to the content analysis, inactive/underactive participants reported fewer physical activity advantages than highly active participants. Common physical activity advantages between the two groups were overall health, emotional functioning, and physical functioning. Similar physical activity advantages were reported among Blacks and Whites with overall health being the most important advantage. The most common physical activity disadvantages and barriers for all four groups were falls, injuries, pain, and health issues. Inactive/underactive individuals and Blacks tended to report more disadvantages and barriers than their peers. Common physical activity supporters were family members, friends and peers, and health-care professionals. In their physical activity motivational programs, health promoters should reinforce physical activity benefits, social support, access to activity programs, and safety when intervening among older adults.

  18. Levels of physical activity in people with chronic pain

    Directory of Open Access Journals (Sweden)

    Romy Parker

    2017-03-01

    Full Text Available Background: People who suffer from chronic pain are thought to have lower levels of physical activity compared to healthy individuals. However, there is a lack of evidence concerning levels of physical activity in South Africans with chronic pain. Objectives: To compare levels of physical activity in a South African sample of people with chronic pain compared to matched controls. Methods: A cross-sectional study was conducted with 24 participants (12 with chronic pain and 12 in the control group matched for age, gender and residential area. Convenience sampling was used. The participants with chronic pain (12 were identified from the Groote Schuur Hospital, Chronic Pain Management Clinic (CPMC waiting list and had not yet received any chronic pain management intervention. Healthy matched controls were selected from volunteers in the community. With the desired alpha level set at 0.05 and the power at 0.9, 45 participants were required to detect a minimum of a 50 per cent difference between groups in levels of physical activity as measured in steps per day using pedometers. The international physical activity questionnaire (IPAQ and the brief pain inventory (BPI were used as measures of physical activity and pain. Objective indicators of physical activity that were used included the 6-minute walk test (6MWT, repeated sit-to-stand test (RSST, 7 days of pedometry and body mass index (BMI. Results: The chronic pain group performed significantly worse on the 6MWT (335 m [30–430] vs 680 m [430–795]; U = 0.5; p < 0.01 and on the RSST (17.9 s [11.83–105] vs 7.85 s [5.5–11.5]; U = 0; p < 0.01. The chronic pain group also had significantly lower scores on pedometry (mean daily: 2985.1 [32.8–13785.4] vs 6409.4 [4207.1–15313.6]; U = 35; p < 0.03. The BMI for the chronic pain group was significantly higher than matched controls (29.36 kg/m2 [18.94–34.63] vs 22.16 kg/m2 [17.1–30.86]; U = 34; p < 0.03. Conclusion: Participants with chronic pain

  19. Differences in leisure-time activities according to level of physical activity in adolescents.

    Science.gov (United States)

    Mota, Jorge; Santos, Maria Paula; Ribeiro, Jose Carlos

    2008-03-01

    The main goals of this study were: (1) to examine the relationship between physical activity (PA) involvement and other leisure activities in a sample of Portuguese youth and (2) to analyze gender differences in PA and leisure-time activity structure. The sample comprised 1123 adolescents that were classified according to PA levels as active (n = 589) and nonactive (n = 534). A questionnaire assessing leisure-time activities was used. Girls were significantly more engaged in social leisure, dutiful, and individual artistic activities during leisure time, whereas boys were more involved in sports and computer and TV viewing activities. Significant associations between PA and social leisure were found in girls (r = .18, P leisure (girls: r = .56, P importance of organized and nonorganized sports/PA during leisure time for overall levels of PA in adolescents.

  20. Functional characterization of GABAA receptor-mediated modulation of cortical neuron network activity in microelectrode array recordings

    DEFF Research Database (Denmark)

    Bader, Benjamin M; Steder, Anne; Klein, Anders Bue

    2017-01-01

    The numerous γ-aminobutyric acid type A receptor (GABAAR) subtypes are differentially expressed and mediate distinct functions at neuronal level. In this study we have investigated GABAAR-mediated modulation of the spontaneous activity patterns of primary neuronal networks from murine frontal...... of the information extractable from the MEA recordings offers interesting insights into the contributions of various GABAAR subtypes/subgroups to cortical network activity and the putative functional interplay between these receptors in these neurons....... cortex by characterizing the effects induced by a wide selection of pharmacological tools at a plethora of activity parameters in microelectrode array (MEA) recordings. The basic characteristics of the primary cortical neurons used in the recordings were studied in some detail, and the expression levels...

  1. Applications of network analysis for adaptive management of artificial drainage systems in landscapes vulnerable to sea level rise

    Science.gov (United States)

    Poulter, Benjamin; Goodall, Jonathan L.; Halpin, Patrick N.

    2008-08-01

    SummaryThe vulnerability of coastal landscapes to sea level rise is compounded by the existence of extensive artificial drainage networks initially built to lower water tables for agriculture, forestry, and human settlements. These drainage networks are found in landscapes with little topographic relief where channel flow is characterized by bi-directional movement across multiple time-scales and related to precipitation, wind, and tidal patterns. The current configuration of many artificial drainage networks exacerbates impacts associated with sea level rise such as salt-intrusion and increased flooding. This suggests that in the short-term, drainage networks might be managed to mitigate sea level rise related impacts. The challenge, however, is that hydrologic processes in regions where channel flow direction is weakly related to slope and topography require extensive parameterization for numerical models which is limited where network size is on the order of a hundred or more kilometers in total length. Here we present an application of graph theoretic algorithms to efficiently investigate network properties relevant to the management of a large artificial drainage system in coastal North Carolina, USA. We created a digital network model representing the observation network topology and four types of drainage features (canal, collector and field ditches, and streams). We applied betweenness-centrality concepts (using Dijkstra's shortest path algorithm) to determine major hydrologic flowpaths based off of hydraulic resistance. Following this, we identified sub-networks that could be managed independently using a community structure and modularity approach. Lastly, a betweenness-centrality algorithm was applied to identify major shoreline entry points to the network that disproportionately control water movement in and out of the network. We demonstrate that graph theory can be applied to solving management and monitoring problems associated with sea level rise

  2. Design of shared unit-dose drug distribution network using multi-level particle swarm optimization.

    Science.gov (United States)

    Chen, Linjie; Monteiro, Thibaud; Wang, Tao; Marcon, Eric

    2018-03-01

    Unit-dose drug distribution systems provide optimal choices in terms of medication security and efficiency for organizing the drug-use process in large hospitals. As small hospitals have to share such automatic systems for economic reasons, the structure of their logistic organization becomes a very sensitive issue. In the research reported here, we develop a generalized multi-level optimization method - multi-level particle swarm optimization (MLPSO) - to design a shared unit-dose drug distribution network. Structurally, the problem studied can be considered as a type of capacitated location-routing problem (CLRP) with new constraints related to specific production planning. This kind of problem implies that a multi-level optimization should be performed in order to minimize logistic operating costs. Our results show that with the proposed algorithm, a more suitable modeling framework, as well as computational time savings and better optimization performance are obtained than that reported in the literature on this subject.

  3. Physical Activity Levels and Well-Being in Older Adults.

    Science.gov (United States)

    Bae, Wonyul; Ik Suh, Young; Ryu, Jungsu; Heo, Jinmoo

    2017-04-01

    The objective of this study was to identify the interconnectedness of different intensity levels of physical activity and psychological (life satisfaction and positive affect) and physical (physical health) well-being. Participants were from the National Study of Midlife in the United States with assessments in 2004 and aged 25 to 74 living in the United States were included in the analyses. We conducted bivariate correlations to examine significant relationships among the study variables. In addition, after multicollinearity among the independent variable was checked, a series of hierarchical regression analyses with physical health, positive affect, and life satisfaction as criterion variables were conducted. The results showed that light physical activities were positively associated with physical health and life satisfaction in summer, whereas light physical activities and all dependent variables were positively correlated in winter. Furthermore, engaging in moderate physical activities was positively related only with physical health. Meanwhile, vigorous physical activities were not associated with life satisfaction, physical health, and positive affect in summer and winter.

  4. Robust Power Supply Restoration for Self-Healing Active Distribution Networks Considering the Availability of Distributed Generation

    Directory of Open Access Journals (Sweden)

    Qiang Yang

    2018-01-01

    Full Text Available The increasing penetration of distributed generations (DGs with intermittent and stochastic characteristics into current power distribution networks can lead to increased fault levels and degradation in network protection. As one of the key requirements of active network management (ANM, efficient power supply restoration solution to guarantee network self-healing capability with full consideration of DG uncertainties is demanded. This paper presents a joint power supply restoration through combining the DG local restoration and switcher operation-based restoration to enhance the self-healing capability in active distribution networks considering the availability of distributed generation. The restoration algorithmic solution is designed to be able to carry out power restoration in parallel upon multiple simultaneous faults to maximize the load restoration while additionally minimizing power loss, topology variation and power flow changes due to switcher operations. The performance of the proposed solution is validated based on a 53-bus distribution network with wind power generators through extensive simulation experiments for a range of fault cases and DG scenarios generated based on Heuristic Moment Matching (HMM method to fully consider the DG randomness. The numerical result in comparison with the existing solutions demonstrates the effectiveness of the proposed power supply restoration solution.

  5. 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

  6. Energy-Efficient Crowdsensing of Human Mobility and Signal Levels in Cellular Networks

    Science.gov (United States)

    Foremski, Paweł; Gorawski, Michał; Grochla, Krzysztof; Polys, Konrad

    2015-01-01

    The paper presents a practical application of the crowdsensing idea to measure human mobility and signal coverage in cellular networks. Currently, virtually everyone is carrying a mobile phone, which may be used as a sensor to gather research data by measuring, e.g., human mobility and radio signal levels. However, many users are unwilling to participate in crowdsensing experiments. This work begins with the analysis of the barriers for engaging people in crowdsensing. A survey showed that people who agree to participate in crowdsensing expect a minimum impact on their battery lifetime and phone usage habits. To address these requirements, this paper proposes an application for measuring the location and signal strength data based on energy-efficient GPS tracking, which allows one to perform the measurements of human mobility and radio signal levels with minimum energy utilization and without any engagement of the user. The method described combines measurements from the accelerometer with effective management of the GPS to monitor the user mobility with the decrease in battery lifetime by approximately 20%. To show the applicability of the proposed platform, the sample results of signal level distribution and coverage maps gathered for an LTE network and representing human mobility are shown. PMID:26340633

  7. Active local distribution network management for embedded generation

    Energy Technology Data Exchange (ETDEWEB)

    White, S.

    2005-07-01

    With the newer electric power transmission networks, there is a requirement for power to flow in two different directions and this calls for more intelligent forms of management. To satisfy these demands, GENEVAC has produced a controller that aims to increase the energy that power plants can feed to the distribution networks. The software and hardware have undergone trials at two 33/11 kV substations in England. The hardware was designed to monitor voltage, current and phase angle at various points in the network. The software estimates the value of the voltages at every node in the network. The results showed good correlation between estimated and measured voltages: other findings are reported. Recommendations for further work are made including development of a full commercial system. The study was conducted by Econnect Ltd under contract to the DTI.

  8. Analyses of students' activity in the Internet social networks

    Directory of Open Access Journals (Sweden)

    Ermakov V.A.

    2016-09-01

    Full Text Available the article focuses on the empirical study of students' behavior in social networks; the study was conducted by statistical data analysis methods obtained by interviewing students.

  9. Impact of Multimedia and Network Services on an Introductory Level Course

    Science.gov (United States)

    Russ, John C.

    1996-01-01

    We will demonstrate and describe the impact of our use of multimedia and network connectivity on a sophomore-level introductory course in materials science. This class services all engineering students, resulting in large (more than 150) class sections with no hands-on laboratory. In 1990 we began to develop computer graphics that might substitute for some laboratory or real-world experiences, and demonstrate relationships hard to show with static textbook images or chalkboard drawings. We created a comprehensive series of modules that cover the entire course content. Called VIMS (Visualizations in Materials Science), these are available in the form of a CD-ROM and also via the internet.

  10. Dynamic Sleep Scheduling on Air Pollution Levels Monitoring with Wireless Sensor Network

    OpenAIRE

    Gezaq Abror; Rusminto Tjatur Widodo; M. Udin Harun Al Rasyid

    2018-01-01

    Wireless Sensor Network (WSN) can be applied for Air Pollution Level Monitoring System that have been determined by the Environmental Impact Management Agency which is  PM10, SO2, O3, NO2 and CO. In WSN, node system is constrained to a limited power supply, so that the node system has a lifetime. To doing lifetime maximization, power management scheme is required and sensor nodes should use energy efficiently. This paper proposes dynamic sleep scheduling using Time Category-Fuzzy Logic (Time-...

  11. 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.

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

    Science.gov (United States)

    Muthalib, Makii; Re, Rebecca; Zucchelli, Lucia; Perrey, Stephane; Contini, Davide; Caffini, Matteo; Spinelli, Lorenzo; Kerr, Graham; Quaresima, Valentina; Ferrari, Marco; Torricelli, Alessandro

    2015-01-01

    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.

  13. How does network structure affect partnerships for promoting physical activity? Evidence from Brazil and Colombia.

    Science.gov (United States)

    Parra, Diana C; Dauti, Marsela; Harris, Jenine K; Reyes, Lissette; Malta, Deborah C; Brownson, Ross C; Quintero, Mario A; Pratt, Michael

    2011-11-01

    The objective of this study was to describe the network structure and factors associated with collaboration in two networks that promote physical activity (PA) in Brazil and Colombia. Organizations that focus on studying and promoting PA in Brazil (35) and Colombia (53) were identified using a modified one-step reputational snowball sampling process. Participants completed an on-line survey between December 2008 and March 2009 for the Brazil network, and between April and June 2009 for the Colombia network. Network stochastic modeling was used to investigate the likelihood of reported inter-organizational collaboration. While structural features of networks were significant predictors of collaboration within each network, the coefficients and other network characteristics differed. Brazil's PA network was decentralized with a larger number of shared partnerships. Colombia's PA network was centralized and collaboration was influenced by perceived importance of peer organizations. On average, organizations in the PA network of Colombia reported facing more barriers (1.5 vs. 2.5 barriers) for collaboration. Future studies should focus on how these different network structures affect the implementation and uptake of evidence-based PA interventions. Copyright © 2011 Elsevier Ltd. All rights reserved.

  14. Putting age-related task activation into large-scale brain networks: A meta-analysis of 114 fMRI studies on healthy aging.

    Science.gov (United States)

    Li, Hui-Jie; Hou, Xiao-Hui; Liu, Han-Hui; Yue, Chun-Lin; Lu, Guang-Ming; Zuo, Xi-Nian

    2015-10-01

    Normal aging is associated with cognitive decline and underlying brain dysfunction. Previous studies concentrated less on brain network changes at a systems level. Our goal was to examine these age-related changes of fMRI-derived activation with a common network parcellation of the human brain function, offering a systems-neuroscience perspective of healthy aging. We conducted a series of meta-analyses on a total of 114 studies that included 2035 older adults and 1845 young adults. Voxels showing significant age-related changes in activation were then overlaid onto seven commonly referenced neuronal networks. Older adults present moderate cognitive decline in behavioral performance during fMRI scanning, and hypo-activate the visual network and hyper-activate both the frontoparietal control and default mode networks. The degree of increased activation in frontoparietal network was associated with behavioral performance in older adults. Age-related changes in activation present different network patterns across cognitive domains. The systems neuroscience approach used here may be useful for elucidating the underlying network mechanisms of various brain plasticity processes during healthy aging. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

  15. State and Federal activities on low-level waste

    International Nuclear Information System (INIS)

    1983-01-01

    With the passage of the Low-Level Waste Policy Act in December 1980, the states have assumed the management responsibility and the federal government has become a facilitator. State and Federal roles in regulation have not altered. This paper reviews the developments over the last two years to point out the progress made and critical steps that lie ahead. Both technological and political aspects are covered, and a conclusion is presented with a look to the future. Since compact development in the tool chosen by the politicans for low-level waste management, the author reviews the present status starting with the northwest compact which has been introduced into the House and Senate and is subject to hearings. The past two years have seen real progress in technology in the broadest sense. An information development and dissemination system was established in 1978 wih the state-by-state assessment of low-level waste disposal. Annual examinations have been made through 1981 which enables one to understand the generation of low-level wastes. Policy level planning by states can be supported by the base level of information available. Incineration of dry active waste and other non-fuel cycle waste is ready to be fully accepted. Much work has been done on volume reduction of liquids. The increased understanding of the ways to make a disposal site work represents a major technolological improvement. Within the DOE system, there is beginning to be a real understanding of the critical parameters in disposal site performance in the East

  16. Leisure activities, caregiving demands and catecholamine levels in dementia caregivers.

    Science.gov (United States)

    Chattillion, Elizabeth A; Mausbach, Brent T; Roepke, Susan K; von Känel, Roland; Mills, Paul J; Dimsdale, Joel E; Allison, Matthew; Ziegler, Michael G; Patterson, Thomas L; Ancoli-Israel, Sonia; Grant, Igor

    2012-01-01

    This study examined whether satisfaction from leisure activities moderates the relationship between caregiving demands (i.e., hours per day spent caring for a spouse with dementia) and resting levels of the catecholamines norepinephrine (NE) and epinephrine (EPI). Spousal caregivers (n = 107; mean age = 73.95 ± 8.12 years) were assessed in home for plasma levels of NE and EPI, amount of care provided, and leisure satisfaction. Regression was used to determine whether leisure satisfaction moderated the relationship between hours providing care per day and catecholamine levels. A significant interaction was found between hours caregiving and leisure satisfaction for NE, but not for EPI. Post hoc regressions were conducted for both NE and EPI. At low leisure satisfaction, time spent caring for a spouse was positively associated with plasma NE (β = 0.41; p = 0.005) and EPI (β = 0.44; p = 0.003). In contrast, at high levels of satisfaction, time caregiving was not significantly associated with plasma NE (β = -0.08; p = 0.57) or EPI (β = 0.23; p = 0.12). These findings suggest that leisure satisfaction may protect caregivers from increases in catecholamines, which have been implicated in cardiovascular risk. Further support for these findings may impact psychological treatments for distressed caregivers.

  17. Low level alpha activity measurements with pulse shape discrimination

    International Nuclear Information System (INIS)

    Noguchi, Masayasu; Satoh, Kaneaki; Higuchi, Hideo.

    1984-01-01

    Pulse shape discrimination of α and β rays with liquid scintillation counting was investigated for the purpose of low level α activity measurements. Various liquid scintillators for pulse shape discrimination were examined by means of pulse rise time analysis. A new scintillator of low cost and of superior characteristics was found. The figure of merits better than 3.5 in risetime spectrum and the energy resolution better than 9% were obtained for carefully prepared samples. The background counting rate for a sample of 10 ml was reduced to 0.013 cpm/MeV in the range of α ray energy 5 to 7 MeV. (author)

  18. Segregation of low-level dry active waste

    International Nuclear Information System (INIS)

    Kornblith, L. Jr.; Naughton, M.D.; Welsh, L.

    1984-01-01

    A program has been carried out to characterize the Dry Active Waste (DAW) stream from a typical PWR power plant in order to determine the usefulness of large-volume DAW monitors for segregating such waste in order to dispose of it in appropriate facilities. A waste monitor using plastic scintillation counters was used for measuring the waste. The monitor had a volume of about 300 liters and an overall efficiency of about 12% for a typical fission product mixture. It provides automatic compensation for background radioactivity and can measure a bag of waste in less than a minute, including background measurements. Six hundred consecutively generated bags of DAW were measured. These had a total activity of about one millicurie and an average specific activity of about 540 nanocuries per kilogram. About half of the bags contained less than 1000 nanocuries and had specific activities of less than 100 nanocuries per kilogram. Based on simplified preliminary calculations, it appears that an evaluation of the risks of disposal of bags such as these in a landfill other than a low-level waste disposal facility could be carried out that would demonstrate that such disposal of half or more of these bags would not result in any substantial hazard, either short or long term

  19. Physical activity level and sedentary behavior among students

    Directory of Open Access Journals (Sweden)

    Diego Augusto Santos Silva

    2009-01-01

    Full Text Available http://dx.doi.org/10.5007/1980-0037.2009v11n3p299   The objective of this study was to determine the physical activity level (PAL and sedentary behavior of students from the city of Aracaju (SE. A total of 1028 students of both genders participated in the study, with a mean age of 15.38 (2.44 years for girls and 15.24 (2.40 years for boys. Among the sample, 24.7% were children and 75.3% were adolescents, with a mean age of 12.07 (0.88 and 16.39 (1.72 years, respectively. An instrument already used in Brazilian studies was applied to identify the average time (hours watching TV per day (hTV and PAL – PAQ-C. Descriptive statistics, t-test for independent samples, Fisher’s exact test and comparison test between two proportions were used for data analysis, with the level of significance set at 5% (p≤0.05. Boys presented a significantly higher physical activity score 2.25 (0.60 than girls. The prevalence of sedentarism was 72.5, 89.3 and 85.2% in the groups of children and adolescents and in the group as a whole, respectively, for girls, and 55.4, 74.8 and 69.8% for boys. No differences in hTV were observed between genders or between sedentary and physically active students (p > 0.05. We conclude that a there is a high prevalence of “sedentary” and “very sedentary” children and adolescents; b boys present a higher PAL than girls; c adolescents are less active than children, and d the number of hTV is high in the group studied.

  20. Physical activity level and sedentary behavior among students

    Directory of Open Access Journals (Sweden)

    Roberto Jerônimo dos Santos Silva

    2009-06-01

    Full Text Available The objective of this study was to determine the physical activity level (PAL and sedentary behavior of students from the city of Aracaju (SE. A total of 1028 students of both genders participated in the study, with a mean age of 15.38 (2.44 years for girls and 15.24 (2.40 years for boys. Among the sample, 24.7% were children and 75.3% were adolescents, with a mean age of 12.07 (0.88 and 16.39 (1.72 years, respectively. An instrument already used in Brazilian studies was applied to identify the average time (hours watching TV per day (hTV and PAL – PAQ-C. Descriptive statistics, t-test for independent samples, Fisher’s exact test and comparison test between two proportions were used for data analysis, with the level of significance set at 5% (p≤0.05. Boys presented a significantly higher physical activity score 2.25 (0.60 than girls. The prevalence of sedentarism was 72.5, 89.3 and 85.2% in the groups of children and adolescents and in the group as a whole, respectively, for girls, and 55.4, 74.8 and 69.8% for boys. No differences in hTV were observed between genders or between sedentary and physically active students (p > 0.05. We conclude that a there is a high prevalence of “sedentary” and “very sedentary” children and adolescents; b boys present a higher PAL than girls; c adolescents are less active than children, and d the number of hTV is high in the group studied.

  1. Simulating ensembles of nonlinear continuous time dynamical systems via active ultra wideband wireless network

    Energy Technology Data Exchange (ETDEWEB)

    Dmitriev, Alexander S.; Yemelyanov, Ruslan Yu. [V.A. Kotelnikov Institute of Radio Engineering and Electronics of the RAS Mokhovaya 11-7, Moscow, 125009 (Russian Federation); Moscow Institute of Physics and Technology (State University) 9 Institutskiy per., Dolgoprudny, Moscow, 141700 (Russian Federation); Gerasimov, Mark Yu. [V.A. Kotelnikov Institute of Radio Engineering and Electronics of the RAS Mokhovaya 11-7, Moscow, 125009 (Russian Federation); Itskov, Vadim V. [Moscow Institute of Physics and Technology (State University) 9 Institutskiy per., Dolgoprudny, Moscow, 141700 (Russian Federation)

    2016-06-08

    The paper deals with a new multi-element processor platform assigned for modelling the behaviour of interacting dynamical systems, i.e., active wireless network. Experimentally, this ensemble is implemented in an active network, the active nodes of which include direct chaotic transceivers and special actuator boards containing microcontrollers for modelling the dynamical systems and an information display unit (colored LEDs). The modelling technique and experimental results are described and analyzed.

  2. 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.

  3. Efficient Uplink Modeling for Dynamic System-Level Simulations of Cellular and Mobile Networks

    Directory of Open Access Journals (Sweden)

    Lobinger Andreas

    2010-01-01

    Full Text Available A novel theoretical framework for uplink simulations is proposed. It allows investigations which have to cover a very long (real- time and which at the same time require a certain level of accuracy in terms of radio resource management, quality of service, and mobility. This is of particular importance for simulations of self-organizing networks. For this purpose, conventional system level simulators are not suitable due to slow simulation speeds far beyond real-time. Simpler, snapshot-based tools are lacking the aforementioned accuracy. The runtime improvements are achieved by deriving abstract theoretical models for the MAC layer behavior. The focus in this work is long term evolution, and the most important uplink effects such as fluctuating interference, power control, power limitation, adaptive transmission bandwidth, and control channel limitations are considered. Limitations of the abstract models will be discussed as well. Exemplary results are given at the end to demonstrate the capability of the derived framework.

  4. Classification of a Driver's cognitive workload levels using artificial neural network on ECG signals.

    Science.gov (United States)

    Tjolleng, Amir; Jung, Kihyo; Hong, Wongi; Lee, Wonsup; Lee, Baekhee; You, Heecheon; Son, Joonwoo; Park, Seikwon

    2017-03-01

    An artificial neural network (ANN) model was developed in the present study to classify the level of a driver's cognitive workload based on electrocardiography (ECG). ECG signals were measured on 15 male participants while they performed a simulated driving task as a primary task with/without an N-back task as a secondary task. Three time-domain ECG measures (mean inter-beat interval (IBI), standard deviation of IBIs, and root mean squared difference of adjacent IBIs) and three frequencydomain ECG measures (power in low frequency, power in high frequency, and ratio of power in low and high frequencies) were calculated. To compensate for individual differences in heart response during the driving tasks, a three-step data processing procedure was performed to ECG signals of each participant: (1) selection of two most sensitive ECG measures, (2) definition of three (low, medium, and high) cognitive workload levels, and (3) normalization of the selected ECG measures. An ANN model was constructed using a feed-forward network and scaled conjugate gradient as a back-propagation learning rule. The accuracy of the ANN classification model was found satisfactory for learning data (95%) and testing data (82%). Copyright © 2016 Elsevier Ltd. All rights reserved.

  5. Design of a Multiobjective Reverse Logistics Network Considering the Cost and Service Level

    Directory of Open Access Journals (Sweden)

    Shuang Li

    2012-01-01

    Full Text Available Reverse logistics, which is induced by various forms of used products and materials, has received growing attention throughout this decade. In a highly competitive environment, the service level is an important criterion for reverse logistics network design. However, most previous studies about product returns only focused on the total cost of the reverse logistics and neglected the service level. To help a manufacturer of electronic products provide quality postsale repair service for their consumer, this paper proposes a multiobjective reverse logistics network optimisation model that considers the objectives of the cost, the total tardiness of the cycle time, and the coverage of customer zones. The Nondominated Sorting Genetic Algorithm II (NSGA-II is employed for solving this multiobjective optimisation model. To evaluate the performance of NSGA-II, a genetic algorithm based on weighted sum approach and Multiobjective Simulated Annealing (MOSA are also applied. The performance of these three heuristic algorithms is compared using numerical examples. The computational results show that NSGA-II outperforms MOSA and the genetic algorithm based on weighted sum approach. Furthermore, the key parameters of the model are tested, and some conclusions are drawn.

  6. Active vision and image/video understanding with decision structures based on the network-symbolic models

    Science.gov (United States)

    Kuvich, Gary

    2003-08-01

    Vision is a part of a larger information system that converts visual information into knowledge structures. These structures drive vision process, resolve ambiguity and uncertainty via feedback projections, and provide image understanding that is an interpretation of visual information in terms of such knowledge models. The ability of human brain to emulate knowledge structures in the form of networks-symbolic models is found. And that means an important shift of paradigm in our knowledge about brain from neural networks to "cortical software". Symbols, predicates and grammars naturally emerge in such active multilevel hierarchical networks, and logic is simply a way of restructuring such models. Brain analyzes an image as a graph-type decision structure created via multilevel hierarchical compression of visual information. Mid-level vision processes like clustering, perceptual grouping, separation of figure from ground, are special kinds of graph/network transformations. They convert low-level image structure into the set of more abstract ones, which represent objects and visual scene, making them easy for analysis by higher-level knowledge structures. Higher-level vision phenomena are results of such analysis. Composition of network-symbolic models works similar to frames and agents, combines learning, classification, analogy together with higher-level model-based reasoning into a single framework. Such models do not require supercomputers. Based on such principles, and using methods of Computational intelligence, an Image Understanding system can convert images into the network-symbolic knowledge models, and effectively resolve uncertainty and ambiguity, providing unifying representation for perception and cognition. That allows creating new intelligent computer vision systems for robotic and defense industries.

  7. Mediating role of activity level in the depressive realism effect.

    Science.gov (United States)

    Blanco, Fernando; Matute, Helena; A Vadillo, Miguel

    2012-01-01

    Several classic studies have concluded that the accuracy of identifying uncontrollable situations depends heavily on depressive mood. Nondepressed participants tend to exhibit an optimistic illusion of control, whereas depressed participants tend to better detect a lack of control. Recently, we suggested that the different activity levels (measured as the probability of responding during a contingency learning task) exhibited by depressed and nondepressed individuals is partly responsible for this effect. The two studies presented in this paper provide further support for this mediational hypothesis, in which mood is the distal cause of the illusion of control operating through activity level, the proximal cause. In Study 1, the probability of responding, P(R), was found to be a mediator variable between the depressive symptoms and the judgments of control. In Study 2, we intervened directly on the mediator variable: The P(R) for both depressed and nondepressed participants was manipulated through instructions. Our results confirm that P(R) manipulation produced differences in the participants' perceptions of uncontrollability. Importantly, the intervention on the mediator variable cancelled the effect of the distal cause; the participants' judgments of control were no longer mood dependent when the P(R) was manipulated. This result supports the hypothesis that the so-called depressive realism effect is actually mediated by the probability of responding.

  8. Mediating role of activity level in the depressive realism effect.

    Directory of Open Access Journals (Sweden)

    Fernando Blanco

    Full Text Available Several classic studies have concluded that the accuracy of identifying uncontrollable situations depends heavily on depressive mood. Nondepressed participants tend to exhibit an optimistic illusion of control, whereas depressed participants tend to better detect a lack of control. Recently, we suggested that the different activity levels (measured as the probability of responding during a contingency learning task exhibited by depressed and nondepressed individuals is partly responsible for this effect. The two studies presented in this paper provide further support for this mediational hypothesis, in which mood is the distal cause of the illusion of control operating through activity level, the proximal cause. In Study 1, the probability of responding, P(R, was found to be a mediator variable between the depressive symptoms and the judgments of control. In Study 2, we intervened directly on the mediator variable: The P(R for both depressed and nondepressed participants was manipulated through instructions. Our results confirm that P(R manipulation produced differences in the participants' perceptions of uncontrollability. Importantly, the intervention on the mediator variable cancelled the effect of the distal cause; the participants' judgments of control were no longer mood dependent when the P(R was manipulated. This result supports the hypothesis that the so-called depressive realism effect is actually mediated by the probability of responding.

  9. Physical activity levels in adolescents: a case study

    Directory of Open Access Journals (Sweden)

    Juan Carlos Sevilla

    2013-01-01

    Full Text Available Physical Activity (PA is very important during childhood and adolescence in order to promote healthy development and prevent obesity. The WHO recommends 60 minutes daily of moderate-vigorous activity (e» 3 METs/day. The main objective of the study is to assess the levels of PA intensity performed daily by adolescents from a school using the triaxial accelerometry system and to know if they achieve the WHO recommendations. The sample size was 60 Spanish adolescents (14.52 ± .854 year-old belongs to the Empordá school (Empúries, Spain. Previous informed consent was obtained from their parents and/or tutors. PA levels were obtained through accelerometry, Body Mass Index (BMI was calculated though weight and height, heart rate (HR and blood pressure (BP were measured using a digital automatic blood pressure monitor. Descriptive for all data was calculated, and T–test (p < .05 was used to analyze the differences between boys and girls. The main result show that males performed PA during longer time and at higher intensity than women. There is a low percentage of students who achieve the WHO recommendations. In conclusion, we believe very important to seek new strategies and methods to involve more adolescents in the practice of PA, and we believe that PA sessions at school are very important.

  10. Mediating Role of Activity Level in the Depressive Realism Effect

    Science.gov (United States)

    Blanco, Fernando; Matute, Helena; A. Vadillo, Miguel

    2012-01-01

    Several classic studies have concluded that the accuracy of identifying uncontrollable situations depends heavily on depressive mood. Nondepressed participants tend to exhibit an optimistic illusion of control, whereas depressed participants tend to better detect a lack of control. Recently, we suggested that the different activity levels (measured as the probability of responding during a contingency learning task) exhibited by depressed and nondepressed individuals is partly responsible for this effect. The two studies presented in this paper provide further support for this mediational hypothesis, in which mood is the distal cause of the illusion of control operating through activity level, the proximal cause. In Study 1, the probability of responding, P(R), was found to be a mediator variable between the depressive symptoms and the judgments of control. In Study 2, we intervened directly on the mediator variable: The P(R) for both depressed and nondepressed participants was manipulated through instructions. Our results confirm that P(R) manipulation produced differences in the participants’ perceptions of uncontrollability. Importantly, the intervention on the mediator variable cancelled the effect of the distal cause; the participants’ judgments of control were no longer mood dependent when the P(R) was manipulated. This result supports the hypothesis that the so-called depressive realism effect is actually mediated by the probability of responding. PMID:23029435

  11. Hierarchical brain networks active in approach and avoidance goal pursuit.

    Science.gov (United States)

    Spielberg, Jeffrey M; Heller, Wendy; Miller, Gregory A

    2013-01-01

    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.

  12. Effects of Vertex Activity and Self-organized Criticality Behavior on a Weighted Evolving Network

    International Nuclear Information System (INIS)

    Zhang Guiqing; Yang Qiuying; Chen Tianlun

    2008-01-01

    Effects of vertex activity have been analyzed on a weighted evolving network. The network is characterized by the probability distribution of vertex strength, each edge weight and evolution of the strength of vertices with different vertex activities. The model exhibits self-organized criticality behavior. The probability distribution of avalanche size for different network sizes is also shown. In addition, there is a power law relation between the size and the duration of an avalanche and the average of avalanche size has been studied for different vertex activities

  13. Modelling temporal networks of human face-to-face contacts with public activity and individual reachability

    Science.gov (United States)

    Zhang, Yi-Qing; Cui, Jing; Zhang, Shu-Min; Zhang, Qi; Li, Xiang

    2016-02-01

    Modelling temporal networks of human face-to-face contacts is vital both for understanding the spread of airborne pathogens and word-of-mouth spreading of information. Although many efforts have been devoted to model these temporal networks, there are still two important social features, public activity and individual reachability, have been ignored in these models. Here we present a simple model that captures these two features and other typical properties of empirical face-to-face contact networks. The model describes agents which are characterized by an attractiveness to slow down the motion of nearby people, have event-triggered active probability and perform an activity-dependent biased random walk in a square box with periodic boundary. The model quantitatively reproduces two empirical temporal networks of human face-to-face contacts which are testified by their network properties and the epidemic spread dynamics on them.

  14. LCL filter design for three-phase two-level power factor correction using line impedance stabilization network

    DEFF Research Database (Denmark)

    Kouchaki, Alireza; Nymand, Morten

    2016-01-01

    This paper presents LCL filter design method for three-phase two-level power factor correction (PFC) using line impedance stabilization network (LISN). A straightforward LCL filter design along with variation in grid impedance is not simply achievable and inevitably lead to an iterative solution...... for filter. By introducing of fast power switches for PFC applications such as silicon-carbide, major current harmonics around the switching frequency drops in the region that LISN can actively provide well-defined impedance for measuring the harmonics (i.e. 9 kHz- 30MHz). Therefore, LISN can be replaced...... is derived using the current ripple behavior of converter-side inductor. The grid-side inductor is achieved as a function of LISN impedance to fulfill the grid regulation. To verify the analyses, an LCL filter is designed for a 5 kW SiC-based PFC. The simulation and experimental results support the validity...

  15. Fitness, but not physical activity, is related to functional integrity of brain networks associated with aging.

    Science.gov (United States)

    Voss, Michelle W; Weng, Timothy B; Burzynska, Agnieszka Z; Wong, Chelsea N; Cooke, Gillian E; Clark, Rachel; Fanning, Jason; Awick, Elizabeth; Gothe, Neha P; Olson, Erin A; McAuley, Edward; Kramer, Arthur F

    2016-05-01

    Greater physical activity and cardiorespiratory fitness are associated with reduced age-related cognitive decline and lower risk for dementia. However, significant gaps remain in the understanding of how physical activity and fitness protect the brain from adverse effects of brain aging. The primary goal of the current study was to empirically evaluate the independent relationships between physical activity and fitness with functional brain health among healthy older adults, as measured by the functional connectivity of cognitively and clinically relevant resting state networks. To build context for fitness and physical activity associations in older adults, we first demonstrate that young adults have greater within-network functional connectivity across a broad range of cortical association networks. Based on these results and previous research, we predicted that individual differences in fitness and physical activity would be most strongly associated with functional integrity of the networks most sensitive to aging. Consistent with this prediction, and extending on previous research, we showed that cardiorespiratory fitness has a positive relationship with functional connectivity of several cortical networks associated with age-related decline, and effects were strongest in the default mode network (DMN). Furthermore, our results suggest that the positive association of fitness with brain function can occur independent of habitual physical activity. Overall, our findings provide further support that cardiorespiratory fitness is an important factor in moderating the adverse effects of aging on cognitively and clinically relevant functional brain networks. Copyright © 2015 Elsevier Inc. All rights reserved.

  16. Fitness, but not physical activity, is related to functional integrity of brain networks associated with aging

    Science.gov (United States)

    Voss, Michelle W.; Weng, Timothy B.; Burzynska, Agnieszka Z.; Wong, Chelsea N.; Cooke, Gillian E.; Clark, Rachel; Fanning, Jason; Awick, Elizabeth; Gothe, Neha P.; Olson, Erin A.; McAuley, Edward; Kramer, Arthur F.

    2015-01-01

    Greater physical activity and cardiorespiratory fitness are associated with reduced age-related cognitive decline and lower risk for dementia. However, significant gaps remain in the understanding of how physical activity and fitness protect the brain from adverse effects of brain aging. The primary goal of the current study was to empirically evaluate the independent relationships between physical activity and fitness with functional brain health among healthy older adults, as measured by the functional connectivity of cognitively and clinically relevant resting state networks. To build context for fitness and physical activity associations in older adults, we first demonstrate that young adults have greater within-network functional connectivity across a broad range of cortical association networks. Based on these results and previous research, we predicted that individual differences in fitness and physical activity would be most strongly associated with functional integrity of the networks most sensitive to aging. Consistent with this prediction, and extending on previous research, we showed that cardiorespiratory fitness has a positive relationship with functional connectivity of several cortical networks associated with age-related decline, and effects were strongest in the Default Mode Network (DMN). Furthermore, our results suggest that the positive association of fitness with brain function can occur independent of habitual physical activity. Overall, our findings provide further support that cardiorespiratory fitness is an important factor in moderating the adverse effects of aging on cognitively and clinically relevant functional brain networks. PMID:26493108

  17. Objectively assessed physical activity levels in Spanish cancer survivors.

    Science.gov (United States)

    Ruiz-Casado, Ana; Verdugo, Ana Soria; Solano, María J Ortega; Aldazabal, Itziar Pagola; Fiuza-Luces, Carmen; Alejo, Lidia Brea; del Hierro, Julio R Padilla; Palomo, Isabel; Aguado-Arroyo, Oscar; Garatachea, Nuria; Cebolla, Héctor; Lucia, Alejandro

    2014-01-01

    To objectively assess physical activity (PA) levels in a cohort of Spanish cancer survivors. Descriptive, cross-sectional. The Hospital Universitario de Fuenlabrada and two healthcare centers in Madrid, Spain. 204 cancer survivors and 115 adults with no history of cancer. Participants wore a triaxial accelerometer for seven or more consecutive days to assess PA levels. Body mass index (BMI), indirect indicators of adiposity (waist circumference, waist-to-hip ratio), and cardiorespiratory fitness also were determined. Light, moderate, vigorous, and total PA (sum of the former). Most (94%) of the cancer survivors met international recommendations for moderate PA, but very few (3%) fulfilled those (75 minutes or more per week) for vigorous PA. Except for lower total (minute per day, p=0.048) and vigorous PA levels (p0.05). A high percentage of the survivors (33%) were obese (BMI greater than 30 kg/m2), and many also showed poor cardiorespiratory fitness (45% were below the 8 metabolic equivalent threshold). Although cancer survivors overall met international PA recommendations for a healthy lifestyle, their BMI and cardiorespiratory profiles were not within the healthy range. Cancer survivors need to be informed about healthy lifestyle habits and should be regularly monitored.

  18. Fast neutron spectra determination by threshold activation detectors using neural networks

    International Nuclear Information System (INIS)

    Kardan, M.R.; Koohi-Fayegh, R.; Setayeshi, S.; Ghiassi-Nejad, M.

    2004-01-01

    Neural network method was used for fast neutron spectra unfolding in spectrometry by threshold activation detectors. The input layer of the neural networks consisted of 11 neurons for the specific activities of neutron-induced nuclear reaction products, while the output layers were fast neutron spectra which had been subdivided into 6, 8, 10, 12, 15 and 20 energy bins. Neural network training was performed by 437 fast neutron spectra and corresponding threshold activation detector readings. The trained neural network have been applied for unfolding 50 spectra, which were not in training sets and the results were compared with real spectra and unfolded spectra by SANDII. The best results belong to 10 energy bin spectra. The neural network was also trained by detector readings with 5% uncertainty and the response of the trained neural network to detector readings with 5%, 10%, 15%, 20%, 25% and 50% uncertainty was compared with real spectra. Neural network algorithm, in comparison with other unfolding methods, is very fast and needless to detector response matrix and any prior information about spectra and also the outputs have low sensitivity to uncertainty in the activity measurements. The results show that the neural network algorithm is useful when a fast response is required with reasonable accuracy

  19. Distributed routing algorithms to manage power flow in agent-based active distribution network

    NARCIS (Netherlands)

    Nguyen, H.P.; Kling, W.L.; Georgiadis, G.; Papatriantafilou, M.; Anh-Tuan, L.; Bertling, L.

    2010-01-01

    The current transition from passive to active electric distribution networks comes with problems and challenges on bi-directional power flow in the network and the uncertainty in the forecast of power generation from grid-connected renewable and distributed energy sources. The power flow management

  20. Managing Nuclear Knowledge: IAEA Activities and International Coordination. Asian Network for Education in Nuclear Technology (ANENT)

    International Nuclear Information System (INIS)

    2007-07-01

    The important role which the International Atomic Energy Agency (IAEA) plays in assisting Member States in the preservation and enhancement of nuclear knowledge and in facilitating international collaboration in this area has been recognized by the General Conference of the International Atomic Energy Agency in resolutions GC(46)/RES/11B, GC(47)/RES/10B, GC(48)/RES/13 and GC(50)/RES/13. The IAEA continues to support the enhancement and stabilization of nuclear education and training with the objective of securing the availability of qualified human resources for the nuclear sector. Its most important approaches are networking regional educational institutions and fostering cooperation to develop harmonized curricula, prepare and disseminate teaching materials. The Asian Network for Education in Nuclear Technology (ANENT), established by the IAEA in 2004, became operational in 2005. An ANENT website has been set up and is being expanded, such as developing a long-distance learning platform. Also, a reference curriculum for nuclear engineering is being developed with the cooperation of external partners.This booklet summarizes the main activities being carried out by the IAEA with regard to the Asian Network for Education in Nuclear Technology (ANENT) and other related activities including those completed during the period 2002–2005. It briefly describes the background information on the events leading to the formation of the ANENT; the terms of reference formulated at the second Coordination Committee meeting held in Vietnam, October 2005; and objectives, strategy and other institutional and managerial policies reaffirmed by the members. CD-ROM attached to the printed booklet containing nearly all of the background material in full text, including policy level papers, reports, presentations made by Member States, and meeting summaries

  1. Dynamical networks: Finding, measuring, and tracking neural population activity using network science

    Directory of Open Access Journals (Sweden)

    Mark D. Humphries

    2017-12-01

    Full Text Available Systems neuroscience is in a headlong rush to record from as many neurons at the same time as possible. As the brain computes and codes using neuron populations, it is hoped these data will uncover the fundamentals of neural computation. But with hundreds, thousands, or more simultaneously recorded neurons come the inescapable problems of visualizing, describing, and quantifying their interactions. Here I argue that network science provides a set of scalable, analytical tools that already solve these problems. By treating neurons as nodes and their interactions as links, a single network can visualize and describe an arbitrarily large recording. I show that with this description we can quantify the effects of manipulating a neural circuit, track changes in population dynamics over time, and quantitatively define theoretical concepts of neural populations such as cell assemblies. Using network science as a core part of analyzing population recordings will thus provide both qualitative and quantitative advances to our understanding of neural computation.

  2. Noise influence on spike activation in a Hindmarsh–Rose small-world neural network

    International Nuclear Information System (INIS)

    Zhe, Sun; Micheletto, Ruggero

    2016-01-01

    We studied the role of noise in neural networks, especially focusing on its relation to the propagation of spike activity in a small sized system. We set up a source of information using a single neuron that is constantly spiking. This element called initiator x o feeds spikes to the rest of the network that is initially quiescent and subsequently reacts with vigorous spiking after a transitional period of time. We found that noise quickly suppresses the initiator’s influence and favors spontaneous spike activity and, using a decibel representation of noise intensity, we established a linear relationship between noise amplitude and the interval from the initiator’s first spike and the rest of the network activation. We studied the same process with networks of different sizes (number of neurons) and found that the initiator x o has a measurable influence on small networks, but as the network grows in size, spontaneous spiking emerges disrupting its effects on networks of more than about N = 100 neurons. This suggests that the mechanism of internal noise generation allows information transmission within a small neural neighborhood, but decays for bigger network domains. We also analyzed the Fourier spectrum of the whole network membrane potential and verified that noise provokes the reduction of main θ and α peaks before transitioning into chaotic spiking. However, network size does not reproduce a similar phenomena; instead we recorded a reduction in peaks’ amplitude, a better sharpness and definition of Fourier peaks, but not the evident degeneration to chaos observed with increasing external noise. This work aims to contribute to the understanding of the fundamental mechanisms of propagation of spontaneous spiking in neural networks and gives a quantitative assessment of how noise can be used to control and modulate this phenomenon in Hindmarsh−Rose (H−R) neural networks. (paper)

  3. Noise influence on spike activation in a Hindmarsh-Rose small-world neural network

    Science.gov (United States)

    Zhe, Sun; Micheletto, Ruggero

    2016-07-01

    We studied the role of noise in neural networks, especially focusing on its relation to the propagation of spike activity in a small sized system. We set up a source of information using a single neuron that is constantly spiking. This element called initiator x o feeds spikes to the rest of the network that is initially quiescent and subsequently reacts with vigorous spiking after a transitional period of time. We found that noise quickly suppresses the initiator’s influence and favors spontaneous spike activity and, using a decibel representation of noise intensity, we established a linear relationship between noise amplitude and the interval from the initiator’s first spike and the rest of the network activation. We studied the same process with networks of different sizes (number of neurons) and found that the initiator x o has a measurable influence on small networks, but as the network grows in size, spontaneous spiking emerges disrupting its effects on networks of more than about N = 100 neurons. This suggests that the mechanism of internal noise generation allows information transmission within a small neural neighborhood, but decays for bigger network domains. We also analyzed the Fourier spectrum of the whole network membrane potential and verified that noise provokes the reduction of main θ and α peaks before transitioning into chaotic spiking. However, network size does not reproduce a similar phenomena; instead we recorded a reduction in peaks’ amplitude, a better sharpness and definition of Fourier peaks, but not the evident degeneration to chaos observed with increasing external noise. This work aims to contribute to the understanding of the fundamental mechanisms of propagation of spontaneous spiking in neural networks and gives a quantitative assessment of how noise can be used to control and modulate this phenomenon in Hindmarsh-Rose (H-R) neural networks.

  4. 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

  5. Activity of cardiorespiratory networks revealed by transsynaptic virus expressing GFP.

    Science.gov (United States)

    Irnaten, M; Neff, R A; Wang, J; Loewy, A D; Mettenleiter, T C; Mendelowitz, D

    2001-01-01

    A fluorescent transneuronal marker capable of labeling individual neurons in a central network while maintaining their normal physiology would permit functional studies of neurons within entire networks responsible for complex behaviors such as cardiorespiratory reflexes. The Bartha strain of pseudorabies virus (PRV), an attenuated swine alpha herpesvirus, can be used as a transsynaptic marker of neural circuits. Bartha PRV invades neuronal networks in the CNS through peripherally projecting axons, replicates in these parent neurons, and then travels transsynaptically to continue labeling the second- and higher-order neurons in a time-dependent manner. A Bartha PRV mutant that expresses green fluorescent protein (GFP) was used to visualize and record from neurons that determine the vagal motor outflow to the heart. Here we show that Bartha PRV-GFP-labeled neurons retain their normal electrophysiological properties and that the labeled baroreflex pathways that control heart rate are unaltered by the virus. This novel transynaptic virus permits in vitro studies of identified neurons within functionally defined neuronal systems including networks that mediate cardiovascular and respiratory function and interactions. We also demonstrate superior laryngeal motorneurons fire spontaneously and synapse on cardiac vagal neurons in the nucleus ambiguus. This cardiorespiratory pathway provides a neural basis of respiratory sinus arrhythmias.

  6. 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...

  7. Active Control of Sound based on Diagonal Recurrent Neural Network

    NARCIS (Netherlands)

    Jayawardhana, Bayu; Xie, Lihua; Yuan, Shuqing

    2002-01-01

    Recurrent neural network has been known for its dynamic mapping and better suited for nonlinear dynamical system. Nonlinear controller may be needed in cases where the actuators exhibit the nonlinear characteristics, or in cases when the structure to be controlled exhibits nonlinear behavior. The

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

    DEFF Research Database (Denmark)

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

    . 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...

  9. 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…

  10. 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.

  11. Adhesion molecules levels in blood correlate with MRI activity and clinical activity in multiple sclerosis

    International Nuclear Information System (INIS)

    Millers, A.; Enina, G.; Platkajis, A.; Metra, M.; Kukaine, R.

    2002-01-01

    Research into pathogenesis of multiple sclerosis (MS) has prompted efforts to identify immunological markers associated with disease activity. Adhesion molecules ICAM-1 and VCAM-1 are associated with inflammatory mediated blood-brain barrier (BBB) dysfunction. In this study investigates the correlation between blood level of circulating ICAM-1 and VCAM-1 and magnetic resonance imaging (MRI) activity in different clinical phases of patients with MS. We show that RRMS and SPMS patients in clinically active phase with Gd-enhancing lesions in CNS had higher blood levels of cICAM-1 and cVCAM-1 compared these parameters levers of RRMS patients in remission stage. These results suggest that cICAM-1 and cVCAM-1 is a sensitive indicator of disease activity associated with BBB inflammatory dysfunction. Elevated blood level of cICAM-1 more strongly correlated with clinical activity and BBB damage, than cVCAM-1 and that could be used as biological marker of disease activity. Circulating VCAM-1 as an early indicator of BBB disturbance, may also serve as marker of beneficial activity in relapses phase of MS course. (authors)

  12. The role of propriospinal neuronal network in transmitting the alternating muscular activities of flexor and extensor in parkinsonian tremor.

    Science.gov (United States)

    Hao, M; He, X; Lan, N

    2012-01-01

    It has been shown that normal cyclic movement of human arm and resting limb tremor in Parkinson's disease (PD) are associated with the oscillatory neuronal activities in different cerebral networks, which are transmitted to the antagonistic muscles via the same spinal pathway. There are mono-synaptic and multi-synaptic corticospinal pathways for conveying motor commands. This study investigates the plausible role of propriospinal neuronal (PN) network in the C3-C4 levels in multi-synaptic transmission of cortical commands for oscillatory movements. A PN network model is constructed based on known neurophysiological connections, and is hypothesized to achieve the conversion of cortical oscillations into alternating antagonistic muscle bursts. Simulations performed with a virtual arm (VA) model indicate that without the PN network, the alternating bursts of antagonistic muscle EMG could not be reliably generated, whereas with the PN network, the alternating pattern of bursts were naturally displayed in the three pairs of antagonist muscles. Thus, it is suggested that oscillations in the primary motor cortex (M1) of single and double tremor frequencies are processed at the PN network to compute the alternating burst pattern in the flexor and extensor muscles.

  13. 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

  14. 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).

  15. Exponential stability of Cohen-Grossberg neural networks with a general class of activation functions

    International Nuclear Information System (INIS)

    Wan Anhua; Wang Miansen; Peng Jigen; Qiao Hong

    2006-01-01

    In this Letter, the dynamics of Cohen-Grossberg neural networks model are investigated. The activation functions are only assumed to be Lipschitz continuous, which provide a much wider application domain for neural networks than the previous results. By means of the extended nonlinear measure approach, new and relaxed sufficient conditions for the existence, uniqueness and global exponential stability of equilibrium of the neural networks are obtained. Moreover, an estimate for the exponential convergence rate of the neural networks is precisely characterized. Our results improve those existing ones

  16. Optimization based on benefit of regional energy suppliers of distributed generation in active distribution network

    Science.gov (United States)

    Huo, Xianxu; Li, Guodong; Jiang, Ling; Wang, Xudong

    2017-08-01

    With the development of electricity market, distributed generation (DG) technology and related policies, regional energy suppliers are encouraged to build DG. Under this background, the concept of active distribution network (ADN) is put forward. In this paper, a bi-level model of intermittent DG considering benefit of regional energy suppliers is proposed. The objective of the upper level is the maximization of benefit of regional energy suppliers. On this basis, the lower level is optimized for each scene. The uncertainties of DG output and load of users, as well as four active management measures, which include demand-side management, curtailing the output power of DG, regulating reactive power compensation capacity and regulating the on-load tap changer, are considered. Harmony search algorithm and particle swarm optimization are combined as a hybrid strategy to solve the model. This model and strategy are tested with IEEE-33 node system, and results of case study indicate that the model and strategy successfully increase the capacity of DG and benefit of regional energy suppliers.

  17. Addressing challenges for future strategic-level emergency management: reframing, networking, and capacity-building.

    Science.gov (United States)

    Bosomworth, Karyn; Owen, Christine; Curnin, Steven

    2017-04-01

    The mounting frequency and intensity of natural hazards, alongside growing interdependencies between social-technical and ecological systems, are placing increased pressure on emergency management. This is particularly true at the strategic level of emergency management, which involves planning for and managing non-routine, high-consequence events. Drawing on the literature, a survey, and interviews and workshops with Australia's senior emergency managers, this paper presents an analysis of five core challenges that these pressures are creating for strategic-level emergency management. It argues that emphasising 'emergency management' as a primary adaptation strategy is a retrograde step that ignores the importance of addressing socio-political drivers of vulnerabilities. Three key suggestions are presented that could assist the country's strategic-level emergency management in tackling these challenges: (i) reframe emergency management as a component of disaster risk reduction rather than them being one and the same; (ii) adopt a network governance approach; and (iii) further develop the capacities of strategic-level emergency managers. © 2017 The Author(s). Disasters © Overseas Development Institute, 2017.

  18. An Artificial Neural Network for Movement Pattern Analysis to Estimate Blood Alcohol Content Level.

    Science.gov (United States)

    Gharani, Pedram; Suffoletto, Brian; Chung, Tammy; Karimi, Hassan A

    2017-12-13

    Impairments in gait occur after alcohol consumption, and, if detected in real-time, could guide the delivery of "just-in-time" injury prevention interventions. We aimed to identify the salient features of gait that could be used for estimating blood alcohol content (BAC) level in a typical drinking environment. We recruited 10 young adults with a history of heavy drinking to test our research app. During four consecutive Fridays and Saturdays, every hour from 8 p.m. to 12 a.m., they were prompted to use the app to report alcohol consumption and complete a 5-step straight-line walking task, during which 3-axis acceleration and angular velocity data was sampled at a frequency of 100 Hz. BAC for each subject was calculated. From sensor signals, 24 features were calculated using a sliding window technique, including energy, mean, and standard deviation. Using an artificial neural network (ANN), we performed regression analysis to define a model determining association between gait features and BACs. Part (70%) of the data was then used as a training dataset, and the results tested and validated using the rest of the samples. We evaluated different training algorithms for the neural network and the result showed that a Bayesian regularization neural network (BRNN) was the most efficient and accurate. Analyses support the use of the tandem gait task paired with our approach to reliably estimate BAC based on gait features. Results from this work could be useful in designing effective prevention interventions to reduce risky behaviors during periods of alcohol consumption.

  19. Contribution to growth and increment analysis on the Italian CONECOFOR Level II Network

    Directory of Open Access Journals (Sweden)

    Emilio AMORINI

    2002-09-01

    Full Text Available The paper deals with the "Estimation of growth and yield" included in the National Programme on Intensive Monitoring of Forest Ecosystems CONECOFOR Aims of the paper are: i to outline the composition and design of Level II PMPs network, also examining the structural characteristics of forest stands; ii to describe the contents of mensurational surveys carried out in winter 1996/97 and 1999/00; iii to analyse the growth rates in progress at each PMP using selected descriptors. Stand origin (11 high forests and 13 stored coppices and transitory crops and the number of forest types tested are focused as the main discriminants of the PMPs network. This composition, together with irregular forestry practice, results in a number of consequences (prevailing age classes, tree densities and related stand structures, growth patterns which cause a high in-and-between variability of all growth parameters. For the purposes of this analysis, the network of the plots was divided into three main sets: broadleaved high forest (i.e. beech stands, 6 PMPs; coniferous forest (i.e. Norway spruce stands, 5 PMPs; coppice forest (i.e. deciduous and evergreen oaks, beech and hardbeam stands, 13 PMPs. The measurement of basic growth variables (dbh and tree height was used to describe the tree populations in each PMP; the calculation of basal area, mean and top dbh, mean and top height, provided the reference dataset at each inventory. The assessment of social class according to Kraft gave information on vertical stand structure and made it possible to analyse growth according to tree layers. Data comparison provided increments in the interval 1997-2000. The occurrence of natural mortality and ingrowth was also assessed to take into account their combined effect on tree population dynamics. No trend was found, due to limited data availability, but it was possible to have a detailed overview of the stand situation and growth rates in PMPs.

  20. An Artificial Neural Network for Movement Pattern Analysis to Estimate Blood Alcohol Content Level

    Directory of Open Access Journals (Sweden)

    Pedram Gharani

    2017-12-01

    Full Text Available Impairments in gait occur after alcohol consumption, and, if detected in real-time, could guide the delivery of “just-in-time” injury prevention interventions. We aimed to identify the salient features of gait that could be used for estimating blood alcohol content (BAC level in a typical drinking environment. We recruited 10 young adults with a history of heavy drinking to test our research app. During four consecutive Fridays and Saturdays, every hour from 8 p.m. to 12 a.m., they were prompted to use the app to report alcohol consumption and complete a 5-step straight-line walking task, during which 3-axis acceleration and angular velocity data was sampled at a frequency of 100 Hz. BAC for each subject was calculated. From sensor signals, 24 features were calculated using a sliding window technique, including energy, mean, and standard deviation. Using an artificial neural network (ANN, we performed regression analysis to define a model determining association between gait features and BACs. Part (70% of the data was then used as a training dataset, and the results tested and validated using the rest of the samples. We evaluated different training algorithms for the neural network and the result showed that a Bayesian regularization neural network (BRNN was the most efficient and accurate. Analyses support the use of the tandem gait task paired with our approach to reliably estimate BAC based on gait features. Results from this work could be useful in designing effective prevention interventions to reduce risky behaviors during periods of alcohol consumption.

  1. How Networks of Informal Trails Cause Landscape Level Damage to Vegetation.

    Science.gov (United States)

    Barros, Agustina; Marina Pickering, Catherine

    2017-07-01

    When visitors are not constrained to remain on formal trails, informal trail networks can develop and damage plant communities in protected areas. These networks can form in areas with low growing vegetation, where formal trails are limited, where there is limited regulation and where vegetation is slow to recover once disturbed. To demonstrate the extent of impacts from unregulated recreational use, we assessed damage to alpine vegetation by hikers and pack animals in the highest protected area in the southern Hemisphere: Aconcagua Park, in the Andes. Within the 237 ha area surveyed in the Horcones Valley, over 19 km of trails were found, nearly all of which (94%) were informal. This network of trails resulted in the direct loss of 11.5 ha of vegetation and extensive fragmentation of alpine meadows (21 fragments) and steppe vegetation (68 fragments). When levels of disturbance off these trails were quantified using rapid visual assessments, 81% of 102 randomly located plots showed evidence of disturbance, with the severity of disturbance greatest close to trails. As a result, vegetation in 90% of the Valley has been damaged by visitor use, nearly all of it from unregulated use. These results highlight the extent to which informal trails and trampling off-trail can cause landscape damage to areas of high conservation value, and hence the importance of better regulation of visitor use. The methodology used for off-trail impact assessment can be easily applied or adapted for other popular protected areas where trampling off-trail is also an issue.

  2. 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.

  3. Prediction of habitual physical activity level and weight status from fundamental movement skill level.

    Science.gov (United States)

    Bryant, Elizabeth Sarah; James, Rob S; Birch, Samantha Louise; Duncan, Mike

    2014-01-01

    Fundamental movement skills (FMS) have been assessed in children in order to investigate the issues of the low proportion of children who meet physical activity (PA) guidelines and rising levels of obesity. The aim of this research was to identify whether previous or current FMS level is a better predictor of PA levels and weight status in children. In January 2012 (year 1), 281 children were recruited from one primary school in the West Midlands, UK. Children performed eight FMS three times, which were videoed and assessed using a subjective checklist. Sprint speed and jump height were measured objectively. Height and mass were measured to calculate the body mass index to determine the weight status. Skinfold calliper readings were used to calculate body fat percentage. One year later, in January 2013, all these tests were repeated on the same children, with the additional collection of PA data via the use of pedometers. Following multiple linear regression, it was identified that prior mastery in FMS was a better predictor of current PA, whereas current FMS was a better predictor of current weight status. Overall, FMS mastery is needed in childhood to be able to participate in PA and maintain a healthy weight status.

  4. The Effect of Gender and Level of Vision on the Physical Activity Level of Children and Adolescents with Visual Impairment

    Science.gov (United States)

    Aslan, Ummuhan Bas; Calik, Bilge Basakci; Kitis, Ali

    2012-01-01

    This study was planned in order to determine physical activity levels of visually impaired children and adolescents and to investigate the effect of gender and level of vision on physical activity level in visually impaired children and adolescents. A total of 30 visually impaired children and adolescents (16 low vision and 14 blind) aged between…

  5. One method of measure low activity level of α, β

    International Nuclear Information System (INIS)

    Sun Shimin

    2003-01-01

    In this paper it is described that several method of measure low activity level of Alpha and Beta, and an circuit diagram for signal of Alpha and Beta to differentiate with method of wave shape identification. With the method, the signal of Beta did not interfere any signal to the count-way of Alpha. For adopted the technology the model JA-3502 of eight detectors of low background Alpha and Beta measuring instrument only have 2.65 x 10 -4 cpm/cm 2 background count rate at count-way of Alpha. Opposite the model FJ-2600 middle area low background Alpha and Beta measuring instrument have 1.27 x 10 -3 cpm/cm 2 background count rate at count-way of Alpha. The latter is 5 times of other

  6. The Interplay of Networking Activities and Internal Knowledge Actions for Subsidiary Influence within MNCs

    DEFF Research Database (Denmark)

    Tavani, Zhaleh Najafi; Giroud, Axèle; Andersson, Ulf

    2012-01-01

    Building on resource dependency theory; this research investigates the joint impacts of subsidiary knowledge based actions (Reverse Knowledge Transfer (RKT) and knowledge development) and networking activities (internal and external embeddedness) on its strategic influence in the multinational co...

  7. 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.

  8. 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

  9. 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.

  10. Cross-layer active predictive congestion control protocol for wireless sensor networks.

    Science.gov (United States)

    Wan, Jiangwen; Xu, Xiaofeng; Feng, Renjian; Wu, Yinfeng

    2009-01-01

    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.

  11. Multi-level policies and adaptive social networks – a conceptual modeling study for maintaining a polycentric governance system

    Directory of Open Access Journals (Sweden)

    Jean-Denis Mathias

    2017-03-01

    Full Text Available Information and collaboration patterns embedded in social networks play key roles in multilevel and polycentric modes of governance. However, modeling the dynamics of such social networks in multilevel settings has been seldom addressed in the literature. Here we use an adaptive social network model to elaborate the interplay between a central and a local government in order to maintain a polycentric governance. More specifically, our analysis explores in what ways specific policy choices made by a central agent affect the features of an emerging social network composed of local organizations and local users. Using two types of stylized policies, adaptive co-management and adaptive one-level management, we focus on the benefits of multi-level adaptive cooperation for network management. Our analysis uses viability theory to explore and to quantify the ability of these policies to achieve specific network properties. Viability theory gives the family of policies that enables maintaining the polycentric governance unlike optimal control that gives a unique blueprint. We found that the viability of the policies can change dramatically depending on the goals and features of the social network. For some social networks, we also found a very large difference between the viability of the adaptive one-level management and adaptive co-management policies. However, results also show that adaptive co-management doesn’t always provide benefits. Hence, we argue that applying viability theory to governance networks can help policy design by analyzing the trade-off between the costs of adaptive co-management and the benefits associated with its ability to maintain desirable social network properties in a polycentric governance framework.

  12. Optimisation of groundwater level monitoring networks using geostatistical modelling based on the Spartan family variogram and a genetic algorithm method

    Science.gov (United States)

    Parasyris, Antonios E.; Spanoudaki, Katerina; Kampanis, Nikolaos A.

    2016-04-01

    Groundwater level monitoring networks provide essential information for water resources management, especially in areas with significant groundwater exploitation for agricultural and domestic use. Given the high maintenance costs of these networks, development of tools, which can be used by regulators for efficient network design is essential. In this work, a monitoring network optimisation tool is presented. The network optimisation tool couples geostatistical modelling based on the Spartan family variogram with a genetic algorithm method and is applied to Mires basin in Crete, Greece, an area of high socioeconomic and agricultural interest, which suffers from groundwater overexploitation leading to a dramatic decrease of groundwater levels. The purpose of the optimisation tool is to determine which wells to exclude from the monitoring network because they add little or no beneficial information to groundwater level mapping of the area. Unlike previous relevant investigations, the network optimisation tool presented here uses Ordinary Kriging with the recently-established non-differentiable Spartan variogram for groundwater level mapping, which, based on a previous geostatistical study in the area leads to optimal groundwater level mapping. Seventy boreholes operate in the area for groundwater abstraction and water level monitoring. The Spartan variogram gives overall the most accurate groundwater level estimates followed closely by the power-law model. The geostatistical model is coupled to an integer genetic algorithm method programmed in MATLAB 2015a. The algorithm is used to find the set of wells whose removal leads to the minimum error between the original water level mapping using all the available wells in the network and the groundwater level mapping using the reduced well network (error is defined as the 2-norm of the difference between the original mapping matrix with 70 wells and the mapping matrix of the reduced well network). The solution to the

  13. Calcium-Oxidant Signaling Network Regulates AMP-activated Protein Kinase (AMPK) Activation upon Matrix Deprivation*

    Science.gov (United States)

    Sundararaman, Ananthalakshmy; Amirtham, Usha; Rangarajan, Annapoorni

    2016-01-01

    The AMP-activated protein kinase (AMPK) has recently been implicated in anoikis resistance. However, the molecular mechanisms that activate AMPK upon matrix detachment remain unexplored. In this study, we show that AMPK activation is a rapid and sustained phenomenon upon matrix deprivation, whereas re-attachment to the matrix leads to its dephosphorylation and inactivation. Because matrix detachment leads to loss of integrin signaling, we investigated whether integrin signaling negatively regulates AMPK activation. However, modulation of focal adhesion kinase or Src, the major downstream components of integrin signaling, failed to cause a corresponding change in AMPK signaling. Further investigations revealed that the upstream AMPK kinases liver kinase B1 (LKB1) and Ca2+/calmodulin-dependent protein kinase kinase β (CaMKKβ) contribute to AMPK activation upon detachment. In LKB1-deficient cells, we found AMPK activation to be predominantly dependent on CaMKKβ. We observed no change in ATP levels under detached conditions at early time points suggesting that rapid AMPK activation upon detachment was not triggered by energy stress. We demonstrate that matrix deprivation leads to a spike in intracellular calcium as well as oxidant signaling, and both these intracellular messengers contribute to rapid AMPK activation upon detachment. We further show that endoplasmic reticulum calcium release-induced store-operated calcium entry contributes to intracellular calcium increase, leading to reactive oxygen species production, and AMPK activation. We additionally show that the LKB1/CaMKK-AMPK axis and intracellular calcium levels play a critical role in anchorage-independent cancer sphere formation. Thus, the Ca2+/reactive oxygen species-triggered LKB1/CaMKK-AMPK signaling cascade may provide a quick, adaptable switch to promote survival of metastasizing cancer cells. PMID:27226623

  14. Network level pavement evaluation with 1 mm 3D survey system

    Directory of Open Access Journals (Sweden)

    Kelvin C.P. Wang

    2015-12-01

    Full Text Available The latest iteration of PaveVision3D Ultra can obtain true 1 mm resolution 3D data at full-lane coverage in all 3 directions at highway speed up to 60 mph. This paper introduces the PaveVision3D Ultra technology for rapid network level pavement survey on approximately 1280 center miles of Oklahoma interstate highways. With sophisticated automated distress analyzer (ADA software interface, the collected 1 mm 3D data provide Oklahoma Department of Transportation (ODOT with comprehensive solutions for automated evaluation of pavement surface including longitudinal profile for roughness, transverse profile for rutting, predicted hydroplaning speed for safety analysis, and cracking and various surface defects for distresses. The pruned exact linear time (PELT method, an optimal partitioning algorithm, is implemented to identify change points and dynamically determine homogeneous segments so as to assist ODOT effectively using the available 1 mm 3D pavement surface condition data for decision-making. The application of 1 mm 3D laser imaging technology for network survey is unprecedented. This innovative technology allows highway agencies to access its options in using the 1 mm 3D system for its design and management purposes, particularly to meet the data needs for pavement management system (PMS, pavement ME design and highway performance monitoring system (HPMS.

  15. Modulation of Network Oscillatory Activity and GABAergic Synaptic Transmission by CB1 Cannabinoid Receptors in the Rat Medial Entorhinal Cortex

    Directory of Open Access Journals (Sweden)

    Nicola H. Morgan

    2008-01-01

    Full Text Available Cannabinoids modulate inhibitory GABAergic neurotransmission in many brain regions. Within the temporal lobe, cannabinoid receptors are highly expressed, and are located presynaptically at inhibitory terminals. Here, we have explored the role of type-1 cannabinoid receptors (CB1Rs at the level of inhibitory synaptic currents and field-recorded network oscillations. We report that arachidonylcyclopropylamide (ACPA; 10 M, an agonist at CB1R, inhibits GABAergic synaptic transmission onto both superficial and deep medial entorhinal (mEC neurones, but this has little effect on network oscillations in beta/gamma frequency bands. By contrast, the CB1R antagonist/inverse agonist LY320135 (500 nM, increased GABAergic synaptic activity and beta/gamma oscillatory activity in superficial mEC, was suppressed, whilst that in deep mEC was enhanced. These data indicate that cannabinoid-mediated effects on inhibitory synaptic activity may be constitutively active in vitro, and that modulation of CB1R activation using inverse agonists unmasks complex effects of CBR function on network activity.

  16. Neuro-fuzzy and neural network techniques for forecasting sea level in Darwin Harbor, Australia

    Science.gov (United States)

    Karimi, Sepideh; Kisi, Ozgur; Shiri, Jalal; Makarynskyy, Oleg

    2013-03-01

    Accurate predictions of sea level with different forecast horizons are important for coastal and ocean engineering applications, as well as in land drainage and reclamation studies. The methodology of tidal harmonic analysis, which is generally used for obtaining a mathematical description of the tides, is data demanding requiring processing of tidal observation collected over several years. In the present study, hourly sea levels for Darwin Harbor, Australia were predicted using two different, data driven techniques, adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network (ANN). Multi linear regression (MLR) technique was used for selecting the optimal input combinations (lag times) of hourly sea level. The input combination comprises current sea level as well as five previous level values found to be optimal. For the ANFIS models, five different membership functions namely triangular, trapezoidal, generalized bell, Gaussian and two Gaussian membership function were tested and employed for predicting sea level for the next 1 h, 24 h, 48 h and 72 h. The used ANN models were trained using three different algorithms, namely, Levenberg-Marquardt, conjugate gradient and gradient descent. Predictions of optimal ANFIS and ANN models were compared with those of the optimal auto-regressive moving average (ARMA) models. The coefficient of determination, root mean square error and variance account statistics were used as comparison criteria. The obtained results indicated that triangular membership function was optimal for predictions with the ANFIS models while adaptive learning rate and Levenberg-Marquardt were most suitable for training the ANN models. Consequently, ANFIS and ANN models gave similar forecasts and performed better than the developed for the same purpose ARMA models for all the prediction intervals.

  17. The Next Generation of Scientists: Examining the Experiences of Graduate Students in Network-Level Social-Ecological Science

    Directory of Open Access Journals (Sweden)

    Michele Romolini

    2013-09-01

    Full Text Available By integrating the research and resources of hundreds of scientists from dozens of institutions, network-level science is fast becoming one scientific model of choice to address complex problems. In the pursuit to confront pressing environmental issues such as climate change, many scientists, practitioners, policy makers, and institutions are promoting network-level research that integrates the social and ecological sciences. To understand how this scientific trend is unfolding among rising scientists, we examined how graduate students experienced one such emergent social-ecological research initiative, Integrated Science for Society and Environment, within the large-scale, geographically distributed Long Term Ecological Research (LTER Network. Through workshops, surveys, and interviews, we found that graduate students faced challenges in how they conceptualized and practiced social-ecological research within the LTER Network. We have presented these conceptual challenges at three scales: the individual/project, the LTER site, and the LTER Network. The level of student engagement with and knowledge of the LTER Network was varied, and students faced different institutional, cultural, and logistic barriers to practicing social-ecological research. These types of challenges are unlikely to be unique to LTER graduate students; thus, our findings are relevant to other scientific networks implementing new social-ecological research initiatives.

  18. Closure Plan for Active Low Level Burial Grounds

    Energy Technology Data Exchange (ETDEWEB)

    SKELLY, W.A.

    2000-11-16

    This plan has been prepared in response to direction from the U.S. Department of Energy. The purpose of the plan is to define approaches that will be implemented to ensure protection of the public and the environment when active Low-Level Burial Grounds (LLBGs) at the Hanford Site are closed. Performance assessments for active burial grounds in the 200 East and West 200 Areas provide current estimates of potential environmental contamination and doses to the ''maximum exposed individual'' from burial ground operation and closure and compare dose estimates to performance objective dose limits for the facilities. This is an Operational Closure Plan. The intent of the guidance in DOE Order 435.1 is that this plan will be a living document, like the facility performance assessments, and will be revised periodically through the operational life of the LLBGs to reflect updated information on waste inventory. management practices, facility transition planning, schedule dates, assessments of post-closure performance, and environmental consequences. Out year dates identified in this plan are tentative. A Final Closure Plan will be prepared in the future when the timing and extent of closure-related activities for LLBGs can be established with greater certainty. After current operations at the LLBGs are concluded, this plan proposes transitioning of these facilities to the Environmental Restoration Program. This action will enable the Environmental Restoration Program to design and implement consistent and coordinated final remedial actions for active and inactive LLBGs. Active and inactive burial grounds in the 200 West and 200 East Areas are commingled. This plan describes approaches that will be implemented during Interim Closure, Final Closure, and Institutional Control Periods to prepare LLBGs for surface barriers, and the construction of barriers, as well as the scope of inspection, monitoring and maintenance practices that will be performed during

  19. Active node determination for correlated data gathering in wireless sensor networks

    OpenAIRE

    Karasabun, Efe

    2009-01-01

    Ankara : The Department of Computer Engineering and the Institute of Engineering and Science of Bilkent University, 2009. Thesis (Master's) -- Bilkent University, 2009. Includes bibliographical references leaves 53-55. In wireless sensor network applications where data gathered by different sensor nodes is correlated, not all sensor nodes need to be active for the wireless sensor network to be functional. However, the sensor nodes that are selected as active should form a co...

  20. Deep Convolutional and LSTM Recurrent Neural Networks for Multimodal Wearable Activity Recognition

    OpenAIRE

    Francisco Javier Ordóñez; Daniel Roggen

    2016-01-01

    Human activity recognition (HAR) tasks have traditionally been solved using engineered features obtained by heuristic processes. Current research suggests that deep convolutional neural networks are suited to automate feature extraction from raw sensor inputs. However, human activities are made of complex sequences of motor movements, and capturing this temporal dynamics is fundamental for successful HAR. Based on the recent success of recurrent neural networks for time series domains, we pro...