WorldWideScience

Sample records for potential network mechanisms

  1. Potential theory for directed networks.

    Directory of Open Access Journals (Sweden)

    Qian-Ming Zhang

    Full Text Available Uncovering factors underlying the network formation is a long-standing challenge for data mining and network analysis. In particular, the microscopic organizing principles of directed networks are less understood than those of undirected networks. This article proposes a hypothesis named potential theory, which assumes that every directed link corresponds to a decrease of a unit potential and subgraphs with definable potential values for all nodes are preferred. Combining the potential theory with the clustering and homophily mechanisms, it is deduced that the Bi-fan structure consisting of 4 nodes and 4 directed links is the most favored local structure in directed networks. Our hypothesis receives strongly positive supports from extensive experiments on 15 directed networks drawn from disparate fields, as indicated by the most accurate and robust performance of Bi-fan predictor within the link prediction framework. In summary, our main contribution is twofold: (i We propose a new mechanism for the local organization of directed networks; (ii We design the corresponding link prediction algorithm, which can not only testify our hypothesis, but also find out direct applications in missing link prediction and friendship recommendation.

  2. Potential Theory for Directed Networks

    Science.gov (United States)

    Zhang, Qian-Ming; Lü, Linyuan; Wang, Wen-Qiang; Zhou, Tao

    2013-01-01

    Uncovering factors underlying the network formation is a long-standing challenge for data mining and network analysis. In particular, the microscopic organizing principles of directed networks are less understood than those of undirected networks. This article proposes a hypothesis named potential theory, which assumes that every directed link corresponds to a decrease of a unit potential and subgraphs with definable potential values for all nodes are preferred. Combining the potential theory with the clustering and homophily mechanisms, it is deduced that the Bi-fan structure consisting of 4 nodes and 4 directed links is the most favored local structure in directed networks. Our hypothesis receives strongly positive supports from extensive experiments on 15 directed networks drawn from disparate fields, as indicated by the most accurate and robust performance of Bi-fan predictor within the link prediction framework. In summary, our main contribution is twofold: (i) We propose a new mechanism for the local organization of directed networks; (ii) We design the corresponding link prediction algorithm, which can not only testify our hypothesis, but also find out direct applications in missing link prediction and friendship recommendation. PMID:23408979

  3. Integrated network analysis reveals potentially novel molecular mechanisms and therapeutic targets of refractory epilepsies.

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    Hongwei Chu

    Full Text Available Epilepsy is a complex neurological disorder and a significant health problem. The pathogenesis of epilepsy remains obscure in a significant number of patients and the current treatment options are not adequate in about a third of individuals which were known as refractory epilepsies (RE. Network medicine provides an effective approach for studying the molecular mechanisms underlying complex diseases. Here we integrated 1876 disease-gene associations of RE and located those genes to human protein-protein interaction (PPI network to obtain 42 significant RE-associated disease modules. The functional analysis of these disease modules showed novel molecular pathological mechanisms of RE, such as the novel enriched pathways (e.g., "presynaptic nicotinic acetylcholine receptors", "signaling by insulin receptor". Further analysis on the relationships between current drug targets and the RE-related disease genes showed the rational mechanisms of most antiepileptic drugs. In addition, we detected ten potential novel drug targets (e.g., KCNA1, KCNA4-6, KCNC3, KCND2, KCNMA1, CAMK2G, CACNB4 and GRM1 located in three RE related disease modules, which might provide novel insights into the new drug discovery for RE therapy.

  4. Multiscale Quantum Mechanics/Molecular Mechanics Simulations with Neural Networks.

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    Shen, Lin; Wu, Jingheng; Yang, Weitao

    2016-10-11

    Molecular dynamics simulation with multiscale quantum mechanics/molecular mechanics (QM/MM) methods is a very powerful tool for understanding the mechanism of chemical and biological processes in solution or enzymes. However, its computational cost can be too high for many biochemical systems because of the large number of ab initio QM calculations. Semiempirical QM/MM simulations have much higher efficiency. Its accuracy can be improved with a correction to reach the ab initio QM/MM level. The computational cost on the ab initio calculation for the correction determines the efficiency. In this paper we developed a neural network method for QM/MM calculation as an extension of the neural-network representation reported by Behler and Parrinello. With this approach, the potential energy of any configuration along the reaction path for a given QM/MM system can be predicted at the ab initio QM/MM level based on the semiempirical QM/MM simulations. We further applied this method to three reactions in water to calculate the free energy changes. The free-energy profile obtained from the semiempirical QM/MM simulation is corrected to the ab initio QM/MM level with the potential energies predicted with the constructed neural network. The results are in excellent accordance with the reference data that are obtained from the ab initio QM/MM molecular dynamics simulation or corrected with direct ab initio QM/MM potential energies. Compared with the correction using direct ab initio QM/MM potential energies, our method shows a speed-up of 1 or 2 orders of magnitude. It demonstrates that the neural network method combined with the semiempirical QM/MM calculation can be an efficient and reliable strategy for chemical reaction simulations.

  5. Neural network approach for the calculation of potential coefficients in quantum mechanics

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    Ossandón, Sebastián; Reyes, Camilo; Cumsille, Patricio; Reyes, Carlos M.

    2017-05-01

    A numerical method based on artificial neural networks is used to solve the inverse Schrödinger equation for a multi-parameter class of potentials. First, the finite element method was used to solve repeatedly the direct problem for different parametrizations of the chosen potential function. Then, using the attainable eigenvalues as a training set of the direct radial basis neural network a map of new eigenvalues was obtained. This relationship was later inverted and refined by training an inverse radial basis neural network, allowing the calculation of the unknown parameters and therefore estimating the potential function. Three numerical examples are presented in order to prove the effectiveness of the method. The results show that the method proposed has the advantage to use less computational resources without a significant accuracy loss.

  6. Mapping human brain networks with cortico-cortical evoked potentials

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    Keller, Corey J.; Honey, Christopher J.; Mégevand, Pierre; Entz, Laszlo; Ulbert, Istvan; Mehta, Ashesh D.

    2014-01-01

    The cerebral cortex forms a sheet of neurons organized into a network of interconnected modules that is highly expanded in humans and presumably enables our most refined sensory and cognitive abilities. The links of this network form a fundamental aspect of its organization, and a great deal of research is focusing on understanding how information flows within and between different regions. However, an often-overlooked element of this connectivity regards a causal, hierarchical structure of regions, whereby certain nodes of the cortical network may exert greater influence over the others. While this is difficult to ascertain non-invasively, patients undergoing invasive electrode monitoring for epilepsy provide a unique window into this aspect of cortical organization. In this review, we highlight the potential for cortico-cortical evoked potential (CCEP) mapping to directly measure neuronal propagation across large-scale brain networks with spatio-temporal resolution that is superior to traditional neuroimaging methods. We first introduce effective connectivity and discuss the mechanisms underlying CCEP generation. Next, we highlight how CCEP mapping has begun to provide insight into the neural basis of non-invasive imaging signals. Finally, we present a novel approach to perturbing and measuring brain network function during cognitive processing. The direct measurement of CCEPs in response to electrical stimulation represents a potentially powerful clinical and basic science tool for probing the large-scale networks of the human cerebral cortex. PMID:25180306

  7. Mechanical response of biopolymer double networks

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    Carroll, Joshua; Das, Moumita

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

  8. Motivation by potential gains and losses affects control processes via different mechanisms in the attentional network.

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    Paschke, Lena M; Walter, Henrik; Steimke, Rosa; Ludwig, Vera U; Gaschler, Robert; Schubert, Torsten; Stelzel, Christine

    2015-05-01

    Attentional control in demanding cognitive tasks can be improved by manipulating the motivational state. Motivation to obtain gains and motivation to avoid losses both usually result in faster reaction times and stronger activation in relevant brain areas such as the prefrontal cortex, but little is known about differences in the underlying neurocognitive mechanisms of these types of motivation in an attentional control context. In the present functional magnetic resonance imaging (fMRI) study, we tested whether potential gain and loss as motivating incentives lead to overlapping or distinct neural effects in the attentional network, and whether one of these conditions is more effective than the other. A Flanker task with word stimuli as targets and distracters was performed by 115 healthy participants. Using a mixed blocked and event-related design allowed us to investigate transient and sustained motivation-related effects. Participants could either gain money (potential gain) or avoid losing money (potential loss) in different task blocks. Participants showed a congruency effect with increased reaction times for incongruent compared to congruent trials. Potential gain led to generally faster responses compared to the neutral condition and to stronger improvements than potential loss. Potential loss also led to shorter response times compared to the neutral condition, but participants improved mainly during incongruent and not during congruent trials. The event-related fMRI data revealed a main effect of congruency with increased activity in the left inferior frontal gyrus (IFG) and inferior frontal junction area (IFJ), the pre-supplementary motor area (pre-SMA), bilateral insula, intraparietal sulcus (IPS) and visual word form area (VWFA). While potential gain led to increased activity in a cluster of the IFJ and the VWFA only during incongruent trials, potential loss was linked to activity increases in these regions during incongruent and congruent trials. The

  9. Development of visible-light responsive and mechanically enhanced "smart" UCST interpenetrating network hydrogels.

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    Xu, Yifei; Ghag, Onkar; Reimann, Morgan; Sitterle, Philip; Chatterjee, Prithwish; Nofen, Elizabeth; Yu, Hongyu; Jiang, Hanqing; Dai, Lenore L

    2017-12-20

    An interpenetrating polymer network (IPN), chlorophyllin-incorporated environmentally responsive hydrogel was synthesized and exhibited the following features: enhanced mechanical properties, upper critical solution temperature (UCST) swelling behavior, and promising visible-light responsiveness. Poor mechanical properties are known challenges for hydrogel-based materials. By forming an interpenetrating network between polyacrylamide (PAAm) and poly(acrylic acid) (PAAc) polymer networks, the mechanical properties of the synthesized IPN hydrogels were significantly improved compared to hydrogels made of a single network of each polymer. The formation of the interpenetrating network was confirmed by Fourier Transform Infrared Spectroscopy (FTIR), the analysis of glass transition temperature, and a unique UCST responsive swelling behavior, which is in contrast to the more prevalent lower critical solution temperature (LCST) behaviour of environmentally responsive hydrogels. The visible-light responsiveness of the synthesized hydrogel also demonstrated a positive swelling behavior, and the effect of incorporating chlorophyllin as the chromophore unit was observed to reduce the average pore size and further enhance the mechanical properties of the hydrogel. This interpenetrating network system shows potential to serve as a new route in developing "smart" hydrogels using visible-light as a simple, inexpensive, and remotely controllable stimulus.

  10. Statistical mechanics of complex networks

    CERN Document Server

    Rubi, Miguel; Diaz-Guilera, Albert

    2003-01-01

    Networks can provide a useful model and graphic image useful for the description of a wide variety of web-like structures in the physical and man-made realms, e.g. protein networks, food webs and the Internet. The contributions gathered in the present volume provide both an introduction to, and an overview of, the multifaceted phenomenology of complex networks. Statistical Mechanics of Complex Networks also provides a state-of-the-art picture of current theoretical methods and approaches.

  11. Plasticity of the MAPK signaling network in response to mechanical stress.

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    Andrea M Pereira

    Full Text Available Cells display versatile responses to mechanical inputs and recent studies have identified the mitogen-activated protein kinase (MAPK cascades mediating the biological effects observed upon mechanical stimulation. Although, MAPK pathways can act insulated from each other, several mechanisms facilitate the crosstalk between the components of these cascades. Yet, the combinatorial complexity of potential molecular interactions between these elements have prevented the understanding of their concerted functions. To analyze the plasticity of the MAPK signaling network in response to mechanical stress we performed a non-saturating epistatic screen in resting and stretched conditions employing as readout a JNK responsive dJun-FRET biosensor. By knocking down MAPKs, and JNK pathway regulators, singly or in pairs in Drosophila S2R+ cells, we have uncovered unexpected regulatory links between JNK cascade kinases, Rho GTPases, MAPKs and the JNK phosphatase Puc. These relationships have been integrated in a system network model at equilibrium accounting for all experimentally validated interactions. This model allows predicting the global reaction of the network to its modulation in response to mechanical stress. It also highlights its context-dependent sensitivity.

  12. Antitumor Mechanisms of Curcumae Rhizoma Based on Network Pharmacology

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    Yan-Hua Bi

    2018-01-01

    Full Text Available Curcumae Rhizoma, a traditional Chinese medication, is commonly used in both traditional treatment and modern clinical care. Its anticancer effects have attracted a great deal of attention, but the mechanisms of action remain obscure. In this study, we screened for the active compounds of Curcumae Rhizoma using a drug-likeness approach. Candidate protein targets with functions related to cancer were predicted by reverse docking and then checked by manual search of the PubMed database. Potential target genes were uploaded to the GeneMANIA server and DAVID 6.8 database for analysis. Finally, compound-target, target-pathway, and compound-target-pathway networks were constructed using Cytoscape 3.3. The results revealed that the anticancer activity of Curcumae Rhizoma potentially involves 13 active compounds, 33 potential targets, and 31 signaling pathways, thus constituting a “multiple compounds, multiple targets, and multiple pathways” network corresponding to the concept of systematic actions in TCM. These findings provide an overview of the anticancer action of Curcumae Rhizoma from a network perspective, as well as setting an example for future studies of other materials used in TCM.

  13. An Inter-Networking Mechanism with Stepwise Synchronization for Wireless Sensor Networks

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    Masayuki Murata

    2011-08-01

    Full Text Available To realize the ambient information society, multiple wireless networks deployed in the region and devices carried by users are required to cooperate with each other. Since duty cycles and operational frequencies are different among networks, we need a mechanism to allow networks to efficiently exchange messages. For this purpose, we propose a novel inter-networking mechanism where two networks are synchronized with each other in a moderate manner, which we call stepwise synchronization. With our proposal, to bridge the gap between intrinsic operational frequencies, nodes near the border of networks adjust their operational frequencies in a stepwise fashion based on the pulse-coupled oscillator model as a fundamental theory of synchronization. Through simulation experiments, we show that the communication delay and the energy consumption of border nodes are reduced, which enables wireless sensor networks to communicate longer with each other.

  14. Sibling cigarette smoking and peer network influences on substance use potential among adolescent: a population based study.

    Science.gov (United States)

    Mahboubi, Samira; Salimi, Yahya; Jorjoran Shushtari, Zahra; Rafiey, Hasan; Sajjadi, Homeira

    2017-12-15

    Background Peer and parental substance use are established predictors for substance use among adolescent, little is known about influence of sibling cigarette smoking and its interaction with peer network on substance use potential that can introduce an important way for substance use prevention programs. Objective The aim of present study was to explore the association of sibling cigarette smoking and peer network with substance use potential among high school students in Tehran. Subjects Data were drawn from the population-based cross-sectional study of among 650 high schools students. Methods Multiple linear regression was used in order to determine the adjusted association between cigarette smoking among family members, peer network, their interaction and substance use potential. Result Having a sister who smokes (B = 3.19; p peer network quality were associated with substance use potential (B = -0.1; p peer network quality score is much more than in who have a sister with a cigarette smoking habit. Conclusion Having a sister who smokes interacts with peer network quality; appears to be one of the important mechanisms for adolescents' tendency to substance use. These findings can help in a better understanding of substance use potential mechanisms, screening efforts and the formulation of prevention programs.

  15. Research on Evolutionary Mechanism of Agile Supply Chain Network via Complex Network Theory

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    Nai-Ru Xu

    2016-01-01

    Full Text Available The paper establishes the evolutionary mechanism model of agile supply chain network by means of complex network theory which can be used to describe the growth process of the agile supply chain network and analyze the complexity of the agile supply chain network. After introducing the process and the suitability of taking complex network theory into supply chain network research, the paper applies complex network theory into the agile supply chain network research, analyzes the complexity of agile supply chain network, presents the evolutionary mechanism of agile supply chain network based on complex network theory, and uses Matlab to simulate degree distribution, average path length, clustering coefficient, and node betweenness. Simulation results show that the evolution result displays the scale-free property. It lays the foundations of further research on agile supply chain network based on complex network theory.

  16. Neural network potential for Al-Mg-Si alloys

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    Kobayashi, Ryo; Giofré, Daniele; Junge, Till; Ceriotti, Michele; Curtin, William A.

    2017-10-01

    The 6000 series Al alloys, which include a few percent of Mg and Si, are important in automotive and aviation industries because of their low weight, as compared to steels, and the fact their strength can be greatly improved through engineered precipitation. To enable atomistic-level simulations of both the processing and performance of this important alloy system, a neural network (NN) potential for the ternary Al-Mg-Si has been created. Training of the NN uses an extensive database of properties computed using first-principles density functional theory, including complex precipitate phases in this alloy. The NN potential accurately reproduces most of the pure Al properties relevant to the mechanical behavior as well as heat of solution, solute-solute, and solute-vacancy interaction energies, and formation energies of small solute clusters and precipitates that are required for modeling the early stage of precipitation and mechanical strengthening. This success not only enables future detailed studies of Al-Mg-Si but also highlights the ability of NN methods to generate useful potentials in complex alloy systems.

  17. Handoff mechanisms in LTE networks

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    Lal, Preeti; Yamini, Vidhu; Mohammed, V. Noor

    2017-11-01

    In this paper, we have analysed and studied the handoff mechanism in Long Term Evaluation (LTE) network. A LTE network has been defined with a set number of macro-cells, micro-cells and mobile devices. In this handoff mechanism distance and speed has been considered as an important parameters. The speed has been detected using the Gauss Markov Mobility Model, and from that distances have been predicted at different instances. In the handover process, Received Signal Power (RSP) for various users has been calculated with respect to base stations at various time intervals and the path loss between transmitter and receiver. A comparative study between path loss models is done in order to improve the signal power. A detailed study has been done on unnecessary handoff probability and handoff failure probability. Simulation results shows that there is an improvement in performance of the above mentioned parameters in the defined network.

  18. Molecular Dynamics Simulations with Quantum Mechanics/Molecular Mechanics and Adaptive Neural Networks.

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    Shen, Lin; Yang, Weitao

    2018-03-13

    Direct molecular dynamics (MD) simulation with ab initio quantum mechanical and molecular mechanical (QM/MM) methods is very powerful for studying the mechanism of chemical reactions in a complex environment but also very time-consuming. The computational cost of QM/MM calculations during MD simulations can be reduced significantly using semiempirical QM/MM methods with lower accuracy. To achieve higher accuracy at the ab initio QM/MM level, a correction on the existing semiempirical QM/MM model is an attractive idea. Recently, we reported a neural network (NN) method as QM/MM-NN to predict the potential energy difference between semiempirical and ab initio QM/MM approaches. The high-level results can be obtained using neural network based on semiempirical QM/MM MD simulations, but the lack of direct MD samplings at the ab initio QM/MM level is still a deficiency that limits the applications of QM/MM-NN. In the present paper, we developed a dynamic scheme of QM/MM-NN for direct MD simulations on the NN-predicted potential energy surface to approximate ab initio QM/MM MD. Since some configurations excluded from the database for NN training were encountered during simulations, which may cause some difficulties on MD samplings, an adaptive procedure inspired by the selection scheme reported by Behler [ Behler Int. J. Quantum Chem. 2015 , 115 , 1032 ; Behler Angew. Chem., Int. Ed. 2017 , 56 , 12828 ] was employed with some adaptions to update NN and carry out MD iteratively. We further applied the adaptive QM/MM-NN MD method to the free energy calculation and transition path optimization on chemical reactions in water. The results at the ab initio QM/MM level can be well reproduced using this method after 2-4 iteration cycles. The saving in computational cost is about 2 orders of magnitude. It demonstrates that the QM/MM-NN with direct MD simulations has great potentials not only for the calculation of thermodynamic properties but also for the characterization of

  19. Integrative Analysis of Genetic, Genomic, and Phenotypic Data for Ethanol Behaviors: A Network-Based Pipeline for Identifying Mechanisms and Potential Drug Targets.

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    Bogenpohl, James W; Mignogna, Kristin M; Smith, Maren L; Miles, Michael F

    2017-01-01

    Complex behavioral traits, such as alcohol abuse, are caused by an interplay of genetic and environmental factors, producing deleterious functional adaptations in the central nervous system. The long-term behavioral consequences of such changes are of substantial cost to both the individual and society. Substantial progress has been made in the last two decades in understanding elements of brain mechanisms underlying responses to ethanol in animal models and risk factors for alcohol use disorder (AUD) in humans. However, treatments for AUD remain largely ineffective and few medications for this disease state have been licensed. Genome-wide genetic polymorphism analysis (GWAS) in humans, behavioral genetic studies in animal models and brain gene expression studies produced by microarrays or RNA-seq have the potential to produce nonbiased and novel insight into the underlying neurobiology of AUD. However, the complexity of such information, both statistical and informational, has slowed progress toward identifying new targets for intervention in AUD. This chapter describes one approach for integrating behavioral, genetic, and genomic information across animal model and human studies. The goal of this approach is to identify networks of genes functioning in the brain that are most relevant to the underlying mechanisms of a complex disease such as AUD. We illustrate an example of how genomic studies in animal models can be used to produce robust gene networks that have functional implications, and to integrate such animal model genomic data with human genetic studies such as GWAS for AUD. We describe several useful analysis tools for such studies: ComBAT, WGCNA, and EW_dmGWAS. The end result of this analysis is a ranking of gene networks and identification of their cognate hub genes, which might provide eventual targets for future therapeutic development. Furthermore, this combined approach may also improve our understanding of basic mechanisms underlying gene x

  20. Hybrid Polymer-Network Hydrogels with Tunable Mechanical Response

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    Sebastian Czarnecki

    2016-03-01

    Full Text Available Hybrid polymer-network gels built by both physical and covalent polymer crosslinking combine the advantages of both these crosslinking types: they exhibit high mechanical strength along with excellent fracture toughness and extensibility. If these materials are extensively deformed, their physical crosslinks can break such that strain energy is dissipated and irreversible fracturing is restricted to high strain only. This mechanism of energy dissipation is determined by the kinetics and thermodynamics of the physical crosslinking contribution. In this paper, we present a poly(ethylene glycol (PEG based material toolkit to control these contributions in a rational and custom fashion. We form well-defined covalent polymer-network gels with regularly distributed additional supramolecular mechanical fuse links, whose strength of connectivity can be tuned without affecting the primary polymer-network composition. This is possible because the supramolecular fuse links are based on terpyridine–metal complexation, such that the mere choice of the fuse-linking metal ion adjusts their kinetics and thermodynamics of complexation–decomplexation, which directly affects the mechanical properties of the hybrid gels. We use oscillatory shear rheology to demonstrate this rational control and enhancement of the mechanical properties of the hybrid gels. In addition, static light scattering reveals their highly regular and well-defined polymer-network structures. As a result of both, the present approach provides an easy and reliable concept for preparing hybrid polymer-network gels with rationally designed properties.

  1. A three-dimensional computational model of collagen network mechanics.

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    Byoungkoo Lee

    Full Text Available Extracellular matrix (ECM strongly influences cellular behaviors, including cell proliferation, adhesion, and particularly migration. In cancer, the rigidity of the stromal collagen environment is thought to control tumor aggressiveness, and collagen alignment has been linked to tumor cell invasion. While the mechanical properties of collagen at both the single fiber scale and the bulk gel scale are quite well studied, how the fiber network responds to local stress or deformation, both structurally and mechanically, is poorly understood. This intermediate scale knowledge is important to understanding cell-ECM interactions and is the focus of this study. We have developed a three-dimensional elastic collagen fiber network model (bead-and-spring model and studied fiber network behaviors for various biophysical conditions: collagen density, crosslinker strength, crosslinker density, and fiber orientation (random vs. prealigned. We found the best-fit crosslinker parameter values using shear simulation tests in a small strain region. Using this calibrated collagen model, we simulated both shear and tensile tests in a large linear strain region for different network geometry conditions. The results suggest that network geometry is a key determinant of the mechanical properties of the fiber network. We further demonstrated how the fiber network structure and mechanics evolves with a local formation, mimicking the effect of pulling by a pseudopod during cell migration. Our computational fiber network model is a step toward a full biomechanical model of cellular behaviors in various ECM conditions.

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

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    El Laithy, Karim; Bogdan, Martin

    2014-04-01

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

  3. Size-dependent mechanical properties of 2D random nanofibre networks

    International Nuclear Information System (INIS)

    Lu, Zixing; Zhu, Man; Liu, Qiang

    2014-01-01

    The mechanical properties of nanofibre networks (NFNs) are size dependent with respect to different fibre diameters. In this paper, a continuum model is developed to reveal the size-dependent mechanical properties of 2D random NFNs. Since such size-dependent behaviours are attributed to different micromechanical mechanisms, the surface effects and the strain gradient (SG) effects are, respectively, introduced into the mechanical analysis of NFNs. Meanwhile, a modified fibre network model is proposed, in which the axial, bending and shearing deformations are incorporated. The closed-form expressions of effective modulus and Poisson's ratio are obtained for NFNs. Different from the results predicted by conventional fibre network model, the present model predicts the size-dependent mechanical properties of NFNs. It is found that both surface effects and SG effects have significant influences on the effective mechanical properties. Moreover, the present results show that the shearing deformation of fibre segment is also crucial to precisely evaluate the effective mechanical properties of NFNs. This work mainly aims to provide an insight into the micromechanical mechanisms of NFNs. Besides, this work is also expected to provide a more accurate theoretical model for 2D fibre networks. (paper)

  4. Adaptive mechanism-based congestion control for networked systems

    Science.gov (United States)

    Liu, Zhi; Zhang, Yun; Chen, C. L. Philip

    2013-03-01

    In order to assure the communication quality in network systems with heavy traffic and limited bandwidth, a new ATRED (adaptive thresholds random early detection) congestion control algorithm is proposed for the congestion avoidance and resource management of network systems. Different to the traditional AQM (active queue management) algorithms, the control parameters of ATRED are not configured statically, but dynamically adjusted by the adaptive mechanism. By integrating with the adaptive strategy, ATRED alleviates the tuning difficulty of RED (random early detection) and shows a better control on the queue management, and achieve a more robust performance than RED under varying network conditions. Furthermore, a dynamic transmission control protocol-AQM control system using ATRED controller is introduced for the systematic analysis. It is proved that the stability of the network system can be guaranteed when the adaptive mechanism is finely designed. Simulation studies show the proposed ATRED algorithm achieves a good performance in varying network environments, which is superior to the RED and Gentle-RED algorithm, and providing more reliable service under varying network conditions.

  5. Contract-Based Incentive Mechanism for Mobile Crowdsourcing Networks

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    Nan Zhao

    2017-09-01

    Full Text Available Mobile crowdsourcing networks (MCNs are a promising method of data collecting and processing by leveraging the mobile devices’ sensing and computing capabilities. However, because of the selfish characteristics of the service provider (SP and mobile users (MUs, crowdsourcing participants only aim to maximize their own benefits. This paper investigates the incentive mechanism between the above two parties to create mutual benefits. By modeling MCNs as a labor market, a contract-based crowdsourcing model with moral hazard is proposed under the asymmetric information scenario. In order to incentivize the potential MUs to participate in crowdsourcing tasks, the optimization problem is formulated to maximize the SP’s utility by jointly examining the crowdsourcing participants’ risk preferences. The impact of crowdsourcing participants’ attitudes of risks on the incentive mechanism has been studied analytically and experimentally. Numerical simulation results demonstrate the effectiveness of the proposed contract design scheme for the crowdsourcing incentive.

  6. Music and Memory in Alzheimer's Disease and The Potential Underlying Mechanisms.

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    Peck, Katlyn J; Girard, Todd A; Russo, Frank A; Fiocco, Alexandra J

    2016-01-01

    With population aging and a projected exponential expansion of persons diagnosed with Alzheimer's disease (AD), the development of treatment and prevention programs has become a fervent area of research and discovery. A growing body of evidence suggests that music exposure can enhance memory and emotional function in persons with AD. However, there is a paucity of research that aims to identify specific underlying neural mechanisms associated with music's beneficial effects in this particular population. As such, this paper reviews existing anecdotal and empirical evidence related to the enhancing effects of music exposure on cognitive function and further provides a discussion on the potential underlying mechanisms that may explain music's beneficial effect. Specifically, this paper will outline the potential role of the dopaminergic system, the autonomic nervous system, and the default network in explaining how music may enhance memory function in persons with AD.

  7. A Security Assessment Mechanism for Software-Defined Networking-Based Mobile Networks

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    Shibo Luo

    2015-12-01

    Full Text Available Software-Defined Networking-based Mobile Networks (SDN-MNs are considered the future of 5G mobile network architecture. With the evolving cyber-attack threat, security assessments need to be performed in the network management. Due to the distinctive features of SDN-MNs, such as their dynamic nature and complexity, traditional network security assessment methodologies cannot be applied directly to SDN-MNs, and a novel security assessment methodology is needed. In this paper, an effective security assessment mechanism based on attack graphs and an Analytic Hierarchy Process (AHP is proposed for SDN-MNs. Firstly, this paper discusses the security assessment problem of SDN-MNs and proposes a methodology using attack graphs and AHP. Secondly, to address the diversity and complexity of SDN-MNs, a novel attack graph definition and attack graph generation algorithm are proposed. In order to quantify security levels, the Node Minimal Effort (NME is defined to quantify attack cost and derive system security levels based on NME. Thirdly, to calculate the NME of an attack graph that takes the dynamic factors of SDN-MN into consideration, we use AHP integrated with the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS as the methodology. Finally, we offer a case study to validate the proposed methodology. The case study and evaluation show the advantages of the proposed security assessment mechanism.

  8. A Security Assessment Mechanism for Software-Defined Networking-Based Mobile Networks.

    Science.gov (United States)

    Luo, Shibo; Dong, Mianxiong; Ota, Kaoru; Wu, Jun; Li, Jianhua

    2015-12-17

    Software-Defined Networking-based Mobile Networks (SDN-MNs) are considered the future of 5G mobile network architecture. With the evolving cyber-attack threat, security assessments need to be performed in the network management. Due to the distinctive features of SDN-MNs, such as their dynamic nature and complexity, traditional network security assessment methodologies cannot be applied directly to SDN-MNs, and a novel security assessment methodology is needed. In this paper, an effective security assessment mechanism based on attack graphs and an Analytic Hierarchy Process (AHP) is proposed for SDN-MNs. Firstly, this paper discusses the security assessment problem of SDN-MNs and proposes a methodology using attack graphs and AHP. Secondly, to address the diversity and complexity of SDN-MNs, a novel attack graph definition and attack graph generation algorithm are proposed. In order to quantify security levels, the Node Minimal Effort (NME) is defined to quantify attack cost and derive system security levels based on NME. Thirdly, to calculate the NME of an attack graph that takes the dynamic factors of SDN-MN into consideration, we use AHP integrated with the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) as the methodology. Finally, we offer a case study to validate the proposed methodology. The case study and evaluation show the advantages of the proposed security assessment mechanism.

  9. Topological structure and mechanics of glassy polymer networks.

    Science.gov (United States)

    Elder, Robert M; Sirk, Timothy W

    2017-11-22

    The influence of chain-level network architecture (i.e., topology) on mechanics was explored for unentangled polymer networks using a blend of coarse-grained molecular simulations and graph-theoretic concepts. A simple extension of the Watts-Strogatz model is proposed to control the graph properties of the network such that the corresponding physical properties can be studied with simulations. The architecture of polymer networks assembled with a dynamic curing approach were compared with the extended Watts-Strogatz model, and found to agree surprisingly well. The final cured structures of the dynamically-assembled networks were nearly an intermediate between lattice and random connections due to restrictions imposed by the finite length of the chains. Further, the uni-axial stress response, character of the bond breaking, and non-affine displacements of fully-cured glassy networks were analyzed as a function of the degree of disorder in the network architecture. It is shown that the architecture strongly affects the network stability, flow stress, onset of bond breaking, and ultimate stress while leaving the modulus and yield point nearly unchanged. The results show that internal restrictions imposed by the network architecture alter the chain-level response through changes to the crosslink dynamics in the flow regime and through the degree of coordinated chain failure at the ultimate stress. The properties considered here are shown to be sensitive to even incremental changes to the architecture and, therefore, the overall network architecture, beyond simple defects, is predicted to be a meaningful physical parameter in the mechanics of glassy polymer networks.

  10. Game Theoretic Problems in Network Economics and Mechanism Design Solutions

    CERN Document Server

    Narahari, Y; Narayanam, Ramasuri; Prakash, Hastagiri

    2009-01-01

    Explores game theoretic modeling and mechanism design for problem solving in Internet and network economics. This monograph contains an exposition of representative game theoretic problems in three different network economics situations and a systematic exploration of mechanism design solutions to these problems.

  11. A Network-Based Pharmacology Study of the Herb-Induced Liver Injury Potential of Traditional Hepatoprotective Chinese Herbal Medicines.

    Science.gov (United States)

    Hong, Ming; Li, Sha; Tan, Hor Yue; Cheung, Fan; Wang, Ning; Huang, Jihan; Feng, Yibin

    2017-04-14

    Herbal medicines are widely used for treating liver diseases and generally regarded as safe due to their extensive use in Traditional Chinese Medicine practice for thousands of years. However, in recent years, there have been increased concerns regarding the long-term risk of Herb-Induced Liver Injury (HILI) in patients with liver dysfunction. Herein, two representative Chinese herbal medicines: one-Xiao-Chai-Hu-Tang (XCHT)-a composite formula, and the other- Radix Polygoni Multiflori (Heshouwu) -a single herb, were analyzed by network pharmacology study. Based on the network pharmacology framework, we exploited the potential HILI effects of XCHT and Heshouwu by predicting the molecular mechanisms of HILI and identified the potential hepatotoxic ingredients in XCHT and Heshouwu . According to our network results, kaempferol and thymol in XCHT and rhein in Heshouwu exhibit the largest number of liver injury target connections, whereby CASP3, PPARG and MCL1 may be potential liver injury targets for these herbal medicines. This network pharmacology assay might serve as a useful tool to explore the underlying molecular mechanism of HILI. Based on the theoretical predictions, further experimental verification should be performed to validate the accuracy of the predicted interactions between herbal ingredients and protein targets in the future.

  12. Mechanized extraction of topology anti-patterns in wireless networks

    NARCIS (Netherlands)

    Woehrle, M.; Bakhshi, R.; Mousavi, M.R.; Derrick, J.; Gnesi, S.; Latella, D.; Treharne, H.

    2012-01-01

    Exhaustive and mechanized formal verification of wireless networks is hampered by the huge number of possible topologies and the large size of the actual networks. However, the generic communication structure in such networks allows for reducing the root causes of faults to faulty (sub-)topologies,

  13. Genetic-and-epigenetic Interspecies Networks for Cross-talk Mechanisms in Human Macrophages and Dendritic Cells During MTB Infection

    Directory of Open Access Journals (Sweden)

    Cheng-Wei Li

    2016-10-01

    Full Text Available Tuberculosis is caused by Mycobacterium tuberculosis (Mtb infection. Mtb is one of the oldest human pathogens, and evolves mechanisms implied in human evolution. The lungs are the first organ exposed to aerosol-transmitted Mtb during gaseous exchange. Therefore, the guards of the immune system in the lungs, such as macrophages (Mϕs and dendritic cells (DCs, are the most important defense against Mtb infection. There have been several studies discussing the functions of Mϕs and DCs during Mtb infection, but the genome-wide pathways and networks are still incomplete. Furthermore, the immune response induced by Mϕs and DCs varies. Therefore, we analyzed the cross-talk genome-wide genetic-and-epigenetic interspecies networks (GWGEINs between Mϕs vs. Mtb and DCs vs. Mtb to determine the varying mechanisms of both the host and pathogen as it relates to Mϕs and DCs during early Mtb infection.First, we performed database mining to construct candidate cross-talk GWGEIN between human cells and Mtb. Then we constructed dynamic models to characterize the molecular mechanisms, including intraspecies gene/microRNA (miRNA regulation networks (GRNs, intraspecies protein-protein interaction networks (PPINs, and the interspecies PPIN of the cross-talk GWGEIN. We applied a system identification method and a system order detection scheme to dynamic models to identify the real cross-talk GWGEINs using the microarray data of Mϕs, DCs and Mtb.After identifying the real cross-talk GWGEINs, the principal network projection (PNP method was employed to construct host-pathogen core networks (HPCNs between Mϕs vs. Mtb and DCs vs. Mtb during infection process. Thus, we investigated the underlying cross-talk mechanisms between the host and the pathogen to determine how the pathogen counteracts host defense mechanisms in Mϕs and DCs during Mtb H37Rv early infection. Based on our findings, we propose Rv1675c as a potential drug target because of its important defensive

  14. Two statistical mechanics aspects of complex networks

    Science.gov (United States)

    Thurner, Stefan; Biely, Christoly

    2006-12-01

    By adopting an ensemble interpretation of non-growing rewiring networks, network theory can be reduced to a counting problem of possible network states and an identification of their associated probabilities. We present two scenarios of how different rewirement schemes can be used to control the state probabilities of the system. In particular, we review how by generalizing the linking rules of random graphs, in combination with superstatistics and quantum mechanical concepts, one can establish an exact relation between the degree distribution of any given network and the nodes’ linking probability distributions. In a second approach, we control state probabilities by a network Hamiltonian, whose characteristics are motivated by biological and socio-economical statistical systems. We demonstrate that a thermodynamics of networks becomes a fully consistent concept, allowing to study e.g. ‘phase transitions’ and computing entropies through thermodynamic relations.

  15. Research on social communication network evolution based on topology potential distribution

    Science.gov (United States)

    Zhao, Dongjie; Jiang, Jian; Li, Deyi; Zhang, Haisu; Chen, Guisheng

    2011-12-01

    Aiming at the problem of social communication network evolution, first, topology potential is introduced to measure the local influence among nodes in networks. Second, from the perspective of topology potential distribution the method of network evolution description based on topology potential distribution is presented, which takes the artificial intelligence with uncertainty as basic theory and local influence among nodes as essentiality. Then, a social communication network is constructed by enron email dataset, the method presented is used to analyze the characteristic of the social communication network evolution and some useful conclusions are got, implying that the method is effective, which shows that topology potential distribution can effectively describe the characteristic of sociology and detect the local changes in social communication network.

  16. Is fertility contagious? Using panel data to disentangle mechanisms of social network influences on fertility decisions.

    Science.gov (United States)

    Lois, Daniel; Arránz Becker, Oliver

    2014-09-01

    Using panel data (N = 1.679 married and cohabiting couples), this paper investigates the presence and causal mechanisms of social contagion processes regarding first births. Results confirmed the hypothesized positive association between the number of network members (friends, acquaintances, siblings) with young children and the respondents' transition rate into parenthood, particularly among younger couples. Several potential intervening mechanisms underlying this social contagion effect were tested. First, evidence was found for observational learning processes in which Ego obtained information on the joys and challenges of parenthood from network members with children. Second, childless respondents tended to feel pressured from couples with children in the network to start a family. Third, results supported the notion of social opportunity costs in that the anticipated loss of social ties after becoming a parent was more likely the fewer parents there were in the network. All three mechanisms exerted a positive impact on both fertility intentions and behavior. Panel regression models relying on intraindividual change scores showed that social learning was the most robust mechanism. An additional indirect test for causality suggested that the findings were unlikely to merely reflect parental status homophily (i.e., selection effects). Copyright © 2013 Elsevier Ltd. All rights reserved.

  17. Novel mechanism of network protection against the new generation of cyber attacks

    Science.gov (United States)

    Milovanov, Alexander; Bukshpun, Leonid; Pradhan, Ranjit

    2012-06-01

    A new intelligent mechanism is presented to protect networks against the new generation of cyber attacks. This mechanism integrates TCP/UDP/IP protocol stack protection and attacker/intruder deception to eliminate existing TCP/UDP/IP protocol stack vulnerabilities. It allows to detect currently undetectable, highly distributed, low-frequency attacks such as distributed denial-of-service (DDoS) attacks, coordinated attacks, botnet, and stealth network reconnaissance. The mechanism also allows insulating attacker/intruder from the network and redirecting the attack to a simulated network acting as a decoy. As a result, network security personnel gain sufficient time to defend the network and collect the attack information. The presented approach can be incorporated into wireless or wired networks that require protection against known and the new generation of cyber attacks.

  18. Study of network resource allocation based on market and game theoretic mechanism

    Science.gov (United States)

    Liu, Yingmei; Wang, Hongwei; Wang, Gang

    2004-04-01

    We work on the network resource allocation issue concerning network management system function based on market-oriented mechanism. The scheme is to model the telecommunication network resources as trading goods in which the various network components could be owned by different competitive, real-world entities. This is a multidisciplinary framework concentrating on the similarity between resource allocation in network environment and the market mechanism in economic theory. By taking an economic (market-based and game theoretic) approach in routing of communication network, we study the dynamic behavior under game-theoretic framework in allocating network resources. Based on the prior work of Gibney and Jennings, we apply concepts of utility and fitness to the market mechanism with an intention to close the gap between experiment environment and real world situation.

  19. An agent-based QoS provisioning mechanism for WDM optical networks

    Science.gov (United States)

    Ouyang, Yong; Zeng, Qingji; Yue, Ling

    2004-04-01

    This paper addresses QoS provisioning mechanisms in the WDM optical networks. With the appearance of metropolitan optical network, a hierarchical metro and wide area optical network will be envisioned in the near future. This hierarchical optical transport network is often divided into optical domains by geography, administration and technology, which usually employ different QoS routing algorithms and policies. To provide end-to-end optical QoS is becoming a new challenge for the optical network design. In this paper, we first give an overview of issues on the QoS provisioning in data, control and management planes of the WDM optical network. And then three provisioning approaches are analyzed and compared. Finally, we propose an agent-based hybrid centralized/distributed QoS provisioning mechanism based on the concept of domain agent. This agent-based hybrid mechanism employs centralized approach in the domain and distributed approach between domains. It offers scalability and intra-domain optimal QoS routing. It also keeps independence and interoperability between domains.

  20. Chimera states in mechanical oscillator networks.

    Science.gov (United States)

    Martens, Erik Andreas; Thutupalli, Shashi; Fourrière, Antoine; Hallatschek, Oskar

    2013-06-25

    The synchronization of coupled oscillators is a fascinating manifestation of self-organization that nature uses to orchestrate essential processes of life, such as the beating of the heart. Although it was long thought that synchrony and disorder were mutually exclusive steady states for a network of identical oscillators, numerous theoretical studies in recent years have revealed the intriguing possibility of "chimera states," in which the symmetry of the oscillator population is broken into a synchronous part and an asynchronous part. However, a striking lack of empirical evidence raises the question of whether chimeras are indeed characteristic of natural systems. This calls for a palpable realization of chimera states without any fine-tuning, from which physical mechanisms underlying their emergence can be uncovered. Here, we devise a simple experiment with mechanical oscillators coupled in a hierarchical network to show that chimeras emerge naturally from a competition between two antagonistic synchronization patterns. We identify a wide spectrum of complex states, encompassing and extending the set of previously described chimeras. Our mathematical model shows that the self-organization observed in our experiments is controlled by elementary dynamical equations from mechanics that are ubiquitous in many natural and technological systems. The symmetry-breaking mechanism revealed by our experiments may thus be prevalent in systems exhibiting collective behavior, such as power grids, optomechanical crystals, or cells communicating via quorum sensing in microbial populations.

  1. Predicting local field potentials with recurrent neural networks.

    Science.gov (United States)

    Kim, Louis; Harer, Jacob; Rangamani, Akshay; Moran, James; Parks, Philip D; Widge, Alik; Eskandar, Emad; Dougherty, Darin; Chin, Sang Peter

    2016-08-01

    We present a Recurrent Neural Network using LSTM (Long Short Term Memory) that is capable of modeling and predicting Local Field Potentials. We train and test the network on real data recorded from epilepsy patients. We construct networks that predict multi-channel LFPs for 1, 10, and 100 milliseconds forward in time. Our results show that prediction using LSTM outperforms regression when predicting 10 and 100 millisecond forward in time.

  2. Network modules uncover mechanisms of skeletal muscle dysfunction in COPD patients

    Directory of Open Access Journals (Sweden)

    Ákos Tényi

    2018-02-01

    Full Text Available Abstract Background Chronic obstructive pulmonary disease (COPD patients often show skeletal muscle dysfunction that has a prominent negative impact on prognosis. The study aims to further explore underlying mechanisms of skeletal muscle dysfunction as a characteristic systemic effect of COPD, potentially modifiable with preventive interventions (i.e. muscle training. The research analyzes network module associated pathways and evaluates the findings using independent measurements. Methods We characterized the transcriptionally active network modules of interacting proteins in the vastus lateralis of COPD patients (n = 15, FEV1 46 ± 12% pred, age 68 ± 7 years and healthy sedentary controls (n = 12, age 65 ± 9  years, at rest and after an 8-week endurance training program. Network modules were functionally evaluated using experimental data derived from the same study groups. Results At baseline, we identified four COPD specific network modules indicating abnormalities in creatinine metabolism, calcium homeostasis, oxidative stress and inflammatory responses, showing statistically significant associations with exercise capacity (VO2 peak, Watts peak, BODE index and blood lactate levels (P < 0.05 each, but not with lung function (FEV1. Training-induced network modules displayed marked differences between COPD and controls. Healthy subjects specific training adaptations were significantly associated with cell bioenergetics (P < 0.05 which, in turn, showed strong relationships with training-induced plasma metabolomic changes; whereas, effects of training in COPD were constrained to muscle remodeling. Conclusion In summary, altered muscle bioenergetics appears as the most striking finding, potentially driving other abnormal skeletal muscle responses. Trial registration The study was based on a retrospectively registered trial (May 2017, ClinicalTrials.gov identifier: NCT03169270

  3. Rumor Spreading Model with Trust Mechanism in Complex Social Networks

    Science.gov (United States)

    Wang, Ya-Qi; Yang, Xiao-Yuan; Han, Yi-Liang; Wang, Xu-An

    2013-04-01

    In this paper, to study rumor spreading, we propose a novel susceptible-infected-removed (SIR) model by introducing the trust mechanism. We derive mean-field equations that describe the dynamics of the SIR model on homogeneous networks and inhomogeneous networks. Then a steady-state analysis is conducted to investigate the critical threshold and the final size of the rumor spreading. We show that the introduction of trust mechanism reduces the final rumor size and the velocity of rumor spreading, but increases the critical thresholds on both networks. Moreover, the trust mechanism not only greatly reduces the maximum rumor influence, but also postpones the rumor terminal time, which provides us with more time to take measures to control the rumor spreading. The theoretical results are confirmed by sufficient numerical simulations.

  4. Identifying potential kidney donors using social networking web sites.

    Science.gov (United States)

    Chang, Alexander; Anderson, Emily E; Turner, Hang T; Shoham, David; Hou, Susan H; Grams, Morgan

    2013-01-01

    Social networking sites like Facebook may be a powerful tool for increasing rates of live kidney donation. They allow for wide dissemination of information and discussion and could lessen anxiety associated with a face-to-face request for donation. However, sparse data exist on the use of social media for this purpose. We searched Facebook, the most popular social networking site, for publicly available English-language pages seeking kidney donors for a specific individual, abstracting information on the potential recipient, characteristics of the page itself, and whether potential donors were tested. In the 91 pages meeting inclusion criteria, the mean age of potential recipients was 37 (range: 2-69); 88% were US residents. Other posted information included the individual's photograph (76%), blood type (64%), cause of kidney disease (43%), and location (71%). Thirty-two percent of pages reported having potential donors tested, and 10% reported receiving a live-donor kidney transplant. Those reporting donor testing shared more potential recipient characteristics, provided more information about transplantation, and had higher page traffic. Facebook is already being used to identify potential kidney donors. Future studies should focus on how to safely, ethically, and effectively use social networking sites to inform potential donors and potentially expand live kidney donation. © 2013 John Wiley & Sons A/S.

  5. An Improved Topology-Potential-Based Community Detection Algorithm for Complex Network

    Directory of Open Access Journals (Sweden)

    Zhixiao Wang

    2014-01-01

    Full Text Available Topology potential theory is a new community detection theory on complex network, which divides a network into communities by spreading outward from each local maximum potential node. At present, almost all topology-potential-based community detection methods ignore node difference and assume that all nodes have the same mass. This hypothesis leads to inaccuracy of topology potential calculation and then decreases the precision of community detection. Inspired by the idea of PageRank algorithm, this paper puts forward a novel mass calculation method for complex network nodes. A node’s mass obtained by our method can effectively reflect its importance and influence in complex network. The more important the node is, the bigger its mass is. Simulation experiment results showed that, after taking node mass into consideration, the topology potential of node is more accurate, the distribution of topology potential is more reasonable, and the results of community detection are more precise.

  6. Unraveling the disease consequences and mechanisms of modular structure in animal social networks

    Science.gov (United States)

    Sah, Pratha; Leu, Stephan T.; Cross, Paul C.; Hudson, Peter J.; Bansal, Shweta

    2017-01-01

    Disease risk is a potential cost of group living. Although modular organization is thought to reduce this cost in animal societies, empirical evidence toward this hypothesis has been conflicting. We analyzed empirical social networks from 43 animal species to motivate our study of the epidemiological consequences of modular structure in animal societies. From these empirical studies, we identified the features of interaction patterns associated with network modularity and developed a theoretical network model to investigate when and how subdivisions in social networks influence disease dynamics. Contrary to prior work, we found that disease risk is largely unaffected by modular structure, although social networks beyond a modular threshold experience smaller disease burden and longer disease duration. Our results illustrate that the lowering of disease burden in highly modular social networks is driven by two mechanisms of modular organization: network fragmentation and subgroup cohesion. Highly fragmented social networks with cohesive subgroups are able to structurally trap infections within a few subgroups and also cause a structural delay to the spread of disease outbreaks. Finally, we show that network models incorporating modular structure are necessary only when prior knowledge suggests that interactions within the population are highly subdivided. Otherwise, null networks based on basic knowledge about group size and local contact heterogeneity may be sufficient when data-limited estimates of epidemic consequences are necessary. Overall, our work does not support the hypothesis that modular structure universally mitigates the disease impact of group living.

  7. Rumor Spreading Model with Trust Mechanism in Complex Social Networks

    International Nuclear Information System (INIS)

    Wang Ya-Qi; Yang Xiao-Yuan; Han Yi-Liang; Wang Xu-An

    2013-01-01

    In this paper, to study rumor spreading, we propose a novel susceptible-infected-removed (SIR) model by introducing the trust mechanism. We derive mean-field equations that describe the dynamics of the SIR model on homogeneous networks and inhomogeneous networks. Then a steady-state analysis is conducted to investigate the critical threshold and the final size of the rumor spreading. We show that the introduction of trust mechanism reduces the final rumor size and the velocity of rumor spreading, but increases the critical thresholds on both networks. Moreover, the trust mechanism not only greatly reduces the maximum rumor influence, but also postpones the rumor terminal time, which provides us with more time to take measures to control the rumor spreading. The theoretical results are confirmed by sufficient numerical simulations. (interdisciplinary physics and related areas of science and technology)

  8. Neonatal brain hemorrhage (NBH) of prematurity: translational mechanisms of the vascular-neural network.

    Science.gov (United States)

    Lekic, Tim; Klebe, Damon; Poblete, Roy; Krafft, Paul R; Rolland, William B; Tang, Jiping; Zhang, John H

    2015-01-01

    Neonatal brain hemorrhage (NBH) of prematurity is an unfortunate consequence of preterm birth. Complications result in shunt dependence and long-term structural changes such as posthemorrhagic hydrocephalus, periventricular leukomalacia, gliosis, and neurological dysfunction. Several animal models are available to study this condition, and many basic mechanisms, etiological factors, and outcome consequences, are becoming understood. NBH is an important clinical condition, of which treatment may potentially circumvent shunt complication, and improve functional recovery (cerebral palsy, and cognitive impairments). This review highlights key pathophysiological findings of the neonatal vascular-neural network in the context of molecular mechanisms targeting the posthemorrhagic hydrocephalus affecting this vulnerable infant population.

  9. Neonatal Brain Hemorrhage (NBH) of Prematurity: Translational Mechanisms of the Vascular-Neural Network

    Science.gov (United States)

    Lekic, Tim; Klebe, Damon; Poblete, Roy; Krafft, Paul R.; Rolland, William B.; Tang, Jiping; Zhang, John H.

    2015-01-01

    Neonatal brain hemorrhage (NBH) of prematurity is an unfortunate consequence of preterm birth. Complications result in shunt dependence and long-term structural changes such as post-hemorrhagic hydrocephalus, periventricular leukomalacia, gliosis, and neurological dysfunction. Several animal models are available to study this condition, and many basic mechanisms, etiological factors, and outcome consequences, are becoming understood. NBH is an important clinical condition, of which treatment may potentially circumvent shunt complication, and improve functional recovery (cerebral palsy, and cognitive impairments). This review highlights key pathophysiological findings of the neonatal vascular-neural network in the context of molecular mechanisms targeting the post-hemorrhagic hydrocephalus affecting this vulnerable infant population. PMID:25620100

  10. Fast Flux Watch: A mechanism for online detection of fast flux networks

    Directory of Open Access Journals (Sweden)

    Basheer N. Al-Duwairi

    2014-07-01

    Full Text Available Fast flux networks represent a special type of botnets that are used to provide highly available web services to a backend server, which usually hosts malicious content. Detection of fast flux networks continues to be a challenging issue because of the similar behavior between these networks and other legitimate infrastructures, such as CDNs and server farms. This paper proposes Fast Flux Watch (FF-Watch, a mechanism for online detection of fast flux agents. FF-Watch is envisioned to exist as a software agent at leaf routers that connect stub networks to the Internet. The core mechanism of FF-Watch is based on the inherent feature of fast flux networks: flux agents within stub networks take the role of relaying client requests to point-of-sale websites of spam campaigns. The main idea of FF-Watch is to correlate incoming TCP connection requests to flux agents within a stub network with outgoing TCP connection requests from the same agents to the point-of-sale website. Theoretical and traffic trace driven analysis shows that the proposed mechanism can be utilized to efficiently detect fast flux agents within a stub network.

  11. Fabrication and Mechanical Characterization of Hydrogel Infused Network Silk Scaffolds

    Directory of Open Access Journals (Sweden)

    Lakshminath Kundanati

    2016-09-01

    Full Text Available Development and characterization of porous scaffolds for tissue engineering and regenerative medicine is of great importance. In recent times, silk scaffolds were developed and successfully tested in tissue engineering and drug release applications. We developed a novel composite scaffold by mechanical infusion of silk hydrogel matrix into a highly porous network silk scaffold. The mechanical behaviour of these scaffolds was thoroughly examined for their possible use in load bearing applications. Firstly, unconfined compression experiments show that the denser composite scaffolds displayed significant enhancement in the elastic modulus as compared to either of the components. This effect was examined and further explained with the help of foam mechanics principles. Secondly, results from confined compression experiments that resemble loading of cartilage in confinement, showed nonlinear material responses for all scaffolds. Finally, the confined creep experiments were performed to calculate the hydraulic permeability of the scaffolds using soil mechanics principles. Our results show that composite scaffolds with some modifications can be a potential candidate for use of cartilage like applications. We hope such approaches help in developing novel scaffolds for tissue engineering by providing an understanding of the mechanics and can further be used to develop graded scaffolds by targeted infusion in specific regions.

  12. Revisiting of Channel Access Mechanisms in Mobile Wireless Networks through Exploiting Physical Layer Technologies

    Directory of Open Access Journals (Sweden)

    Junmei Yao

    2018-01-01

    Full Text Available The wireless local area networks (WLANs have been widely deployed with the rapid development of mobile devices and have further been brought into new applications with infrastructure mobility due to the growth of unmanned aerial vehicles (UAVs. However, the WLANs still face persistent challenge on increasing the network throughput to meet the customer’s requirement and fight against the node mobility. Interference is a well-known issue that would degrade the network performance due to the broadcast characteristics of the wireless signals. Moreover, with infrastructure mobility, the interference becomes the key obstacle in pursuing the channel capacity. Legacy interference management mechanism through the channel access control in the MAC layer design of the 802.11 standard has some well-known drawbacks, such as exposed and hidden terminal problems, inefficient rate adaptation, and retransmission schemes, making the efficient interference management an everlasting research topic over the years. Recently, interference management through exploiting physical layer mechanisms has attracted much research interest and has been proven to be a promising way to improve the network throughput, especially under the infrastructure mobility scenarios which provides more indicators for node dynamics. In this paper, we introduce a series of representative physical layer techniques and analyze how they are exploited for interference management to improve the network performance. We also provide some discussions about the research challenges and give potential future research topics in this area.

  13. Discriminative topological features reveal biological network mechanisms

    Directory of Open Access Journals (Sweden)

    Levovitz Chaya

    2004-11-01

    Full Text Available Abstract Background Recent genomic and bioinformatic advances have motivated the development of numerous network models intending to describe graphs of biological, technological, and sociological origin. In most cases the success of a model has been evaluated by how well it reproduces a few key features of the real-world data, such as degree distributions, mean geodesic lengths, and clustering coefficients. Often pairs of models can reproduce these features with indistinguishable fidelity despite being generated by vastly different mechanisms. In such cases, these few target features are insufficient to distinguish which of the different models best describes real world networks of interest; moreover, it is not clear a priori that any of the presently-existing algorithms for network generation offers a predictive description of the networks inspiring them. Results We present a method to assess systematically which of a set of proposed network generation algorithms gives the most accurate description of a given biological network. To derive discriminative classifiers, we construct a mapping from the set of all graphs to a high-dimensional (in principle infinite-dimensional "word space". This map defines an input space for classification schemes which allow us to state unambiguously which models are most descriptive of a given network of interest. Our training sets include networks generated from 17 models either drawn from the literature or introduced in this work. We show that different duplication-mutation schemes best describe the E. coli genetic network, the S. cerevisiae protein interaction network, and the C. elegans neuronal network, out of a set of network models including a linear preferential attachment model and a small-world model. Conclusions Our method is a first step towards systematizing network models and assessing their predictability, and we anticipate its usefulness for a number of communities.

  14. Investigation of membrane mechanics using spring networks: application to red-blood-cell modelling.

    Science.gov (United States)

    Chen, Mingzhu; Boyle, Fergal J

    2014-10-01

    In recent years a number of red-blood-cell (RBC) models have been proposed using spring networks to represent the RBC membrane. Some results predicted by these models agree well with experimental measurements. However, the suitability of these membrane models has been questioned. The RBC membrane, like a continuum membrane, is mechanically isotropic throughout its surface, but the mechanical properties of a spring network vary on the network surface and change with deformation. In this work spring-network mechanics are investigated in large deformation for the first time via an assessment of the effect of network parameters, i.e. network mesh, spring type and surface constraint. It is found that a spring network is conditionally equivalent to a continuum membrane. In addition, spring networks are employed for RBC modelling to replicate the optical tweezers test. It is found that a spring network is sufficient for modelling the RBC membrane but strain-hardening springs are required. Moreover, the deformation profile of a spring network is presented for the first time via the degree of shear. It is found that spring-network deformation approaches continuous as the mesh density increases. Copyright © 2014 Elsevier B.V. All rights reserved.

  15. Computing with networks of nonlinear mechanical oscillators.

    Directory of Open Access Journals (Sweden)

    Jean C Coulombe

    Full Text Available As it is getting increasingly difficult to achieve gains in the density and power efficiency of microelectronic computing devices because of lithographic techniques reaching fundamental physical limits, new approaches are required to maximize the benefits of distributed sensors, micro-robots or smart materials. Biologically-inspired devices, such as artificial neural networks, can process information with a high level of parallelism to efficiently solve difficult problems, even when implemented using conventional microelectronic technologies. We describe a mechanical device, which operates in a manner similar to artificial neural networks, to solve efficiently two difficult benchmark problems (computing the parity of a bit stream, and classifying spoken words. The device consists in a network of masses coupled by linear springs and attached to a substrate by non-linear springs, thus forming a network of anharmonic oscillators. As the masses can directly couple to forces applied on the device, this approach combines sensing and computing functions in a single power-efficient device with compact dimensions.

  16. Mechanisms of seizure propagation in 2-dimensional centre-surround recurrent networks.

    Directory of Open Access Journals (Sweden)

    David Hall

    Full Text Available Understanding how seizures spread throughout the brain is an important problem in the treatment of epilepsy, especially for implantable devices that aim to avert focal seizures before they spread to, and overwhelm, the rest of the brain. This paper presents an analysis of the speed of propagation in a computational model of seizure-like activity in a 2-dimensional recurrent network of integrate-and-fire neurons containing both excitatory and inhibitory populations and having a difference of Gaussians connectivity structure, an approximation to that observed in cerebral cortex. In the same computational model network, alternative mechanisms are explored in order to simulate the range of seizure-like activity propagation speeds (0.1-100 mm/s observed in two animal-slice-based models of epilepsy: (1 low extracellular [Formula: see text], which creates excess excitation and (2 introduction of gamma-aminobutyric acid (GABA antagonists, which reduce inhibition. Moreover, two alternative connection topologies are considered: excitation broader than inhibition, and inhibition broader than excitation. It was found that the empirically observed range of propagation velocities can be obtained for both connection topologies. For the case of the GABA antagonist model simulation, consistent with other studies, it was found that there is an effective threshold in the degree of inhibition below which waves begin to propagate. For the case of the low extracellular [Formula: see text] model simulation, it was found that activity-dependent reductions in inhibition provide a potential explanation for the emergence of slowly propagating waves. This was simulated as a depression of inhibitory synapses, but it may also be achieved by other mechanisms. This work provides a localised network understanding of the propagation of seizures in 2-dimensional centre-surround networks that can be tested empirically.

  17. Statistical Mechanics of Temporal and Interacting Networks

    Science.gov (United States)

    Zhao, Kun

    In the last ten years important breakthroughs in the understanding of the topology of complexity have been made in the framework of network science. Indeed it has been found that many networks belong to the universality classes called small-world networks or scale-free networks. Moreover it was found that the complex architecture of real world networks strongly affects the critical phenomena defined on these structures. Nevertheless the main focus of the research has been the characterization of single and static networks. Recently, temporal networks and interacting networks have attracted large interest. Indeed many networks are interacting or formed by a multilayer structure. Example of these networks are found in social networks where an individual might be at the same time part of different social networks, in economic and financial networks, in physiology or in infrastructure systems. Moreover, many networks are temporal, i.e. the links appear and disappear on the fast time scale. Examples of these networks are social networks of contacts such as face-to-face interactions or mobile-phone communication, the time-dependent correlations in the brain activity and etc. Understanding the evolution of temporal and multilayer networks and characterizing critical phenomena in these systems is crucial if we want to describe, predict and control the dynamics of complex system. In this thesis, we investigate several statistical mechanics models of temporal and interacting networks, to shed light on the dynamics of this new generation of complex networks. First, we investigate a model of temporal social networks aimed at characterizing human social interactions such as face-to-face interactions and phone-call communication. Indeed thanks to the availability of data on these interactions, we are now in the position to compare the proposed model to the real data finding good agreement. Second, we investigate the entropy of temporal networks and growing networks , to provide

  18. Tunable Coupling to a Mechanical Oscillator Circuit Using a Coherent Feedback Network

    Directory of Open Access Journals (Sweden)

    Joseph Kerckhoff

    2013-06-01

    Full Text Available We demonstrate a fully cryogenic microwave feedback network composed of modular superconducting devices connected by transmission lines and designed to control a mechanical oscillator that is coupled to one of the devices. The network features an electromechanical device and a tunable controller that coherently receives, processes, and feeds back continuous microwave signals that modify the dynamics and readout of the mechanical state. While previous electromechanical systems represent some compromise between efficient control and efficient readout of the mechanical state, as set by the electromagnetic decay rate, the tunable controller produces a closed-loop network that can be dynamically and continuously tuned between both extremes much faster than the mechanical response time. We demonstrate that the microwave decay rate may be modulated by at least a factor of 10 at a rate greater than 10^{4} times the mechanical response rate. The system is easy to build and suggests that some useful functions may arise most naturally at the network level of modular, quantum electromagnetic devices.

  19. Solvable potentials derived from supersymmetric quantum mechanics

    International Nuclear Information System (INIS)

    Levai, G.

    1994-01-01

    The introduction of supersymmetric quantum mechanics has generated renewed interest in solvable problems of non-relativistic quantum mechanics. This approach offers an elegant way to describe different, but isospectral potentials by interpreting the degeneracy of their energy levels in terms of supersymmetry. The original ideas of supersymmetric quantum mechanics have been developed further in many respects in the past ten years, and have been applied to a large variety of physical problems. The purpose of this contribution is to give a survey of supersymmetric quantum mechanics and its applications to solvable quantum mechanical potentials. Its relation to other models describing isospectral potentials is also discussed here briefly, as well as some of its practical applications in various branches of physics. (orig.)

  20. Directed networks' different link formation mechanisms causing degree distribution distinction

    Science.gov (United States)

    Behfar, Stefan Kambiz; Turkina, Ekaterina; Cohendet, Patrick; Burger-Helmchen, Thierry

    2016-11-01

    Within undirected networks, scientists have shown much interest in presenting power-law features. For instance, Barabási and Albert (1999) claimed that a common property of many large networks is that vertex connectivity follows scale-free power-law distribution, and in another study Barabási et al. (2002) showed power law evolution in the social network of scientific collaboration. At the same time, Jiang et al. (2011) discussed deviation from power-law distribution; others indicated that size effect (Bagrow et al., 2008), information filtering mechanism (Mossa et al., 2002), and birth and death process (Shi et al., 2005) could account for this deviation. Within directed networks, many authors have considered that outlinks follow a similar mechanism of creation as inlinks' (Faloutsos et al., 1999; Krapivsky et al., 2001; Tanimoto, 2009) with link creation rate being the linear function of node degree, resulting in a power-law shape for both indegree and outdegree distribution. Some other authors have made an assumption that directed networks, such as scientific collaboration or citation, behave as undirected, resulting in a power-law degree distribution accordingly (Barabási et al., 2002). At the same time, we claim (1) Outlinks feature different degree distributions than inlinks; where different link formation mechanisms cause the distribution distinctions, (2) in/outdegree distribution distinction holds for different levels of system decomposition; therefore this distribution distinction is a property of directed networks. First, we emphasize in/outlink formation mechanisms as causal factors for distinction between indegree and outdegree distributions (where this distinction has already been noticed in Barker et al. (2010) and Baxter et al. (2006)) within a sample network of OSS projects as well as Java software corpus as a network. Second, we analyze whether this distribution distinction holds for different levels of system decomposition: open

  1. Neural networks - Potential appplication in the nuclear industry

    International Nuclear Information System (INIS)

    Yiftah, S.

    1989-01-01

    Neural networks are an emerging technology which is perceived to have potential for solving complex computation problems which cannot be solved by standard computational methods. One such example is the inverse kinematics problem which is considered to be the most difficult problem in robotics. In 1986, only one neural network modelling tool was available, now there are about twenty offered commercially by various companies in North America

  2. Network information provision to potential generators: Appendices

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2001-07-01

    This Code of Practice (CoP) has been prepared to outline the standard of information that Distribution Network Operators (DNOs) should be required to produce in relation to the provision of network maps, schematic diagrams and specific network data. Network information from DNOs may be required by generators (and other customers) in order to assess the potential opportunities available for the connection of new generation plant. Seven Year Statements are published annually by the Transmission Licensees operating in Great Britain, i.e. The National Grid Company, Scottish Power and Scottish Hydro Electric, and contain all the network information relating to each transmission system, e.g. Generation Capacities, System Parameters and Plant Fault Levels. A similar arrangement for DNOs has been outlined in the Electricity Distribution Licence published by Ofgem. Under Condition 25 of the licence, 'The Long Term Development Statement', distribution licence holders are required to make available historic and planned network data. By providing sufficient network information, competition in generation will be improved. At the time of writing, any party interested in assessing distribution network information needs to make contact with the appropriate DNO, identifying the correct department and person. Written applications are then sent to that person, describing the type of network information that is required. Information required from embedded generators by DNOs is specified in detail in both of The Distribution Codes of England and Wales, and Scotland. However, there are no guidelines or details of network information to be provided by DNOs. This Code of Practise is designed to balance this situation and help DNOs, prospective generators and other applicants for information to achieve satisfaction by clarifying expectations. (Author)

  3. The Framework for Simulation of Bioinspired Security Mechanisms against Network Infrastructure Attacks

    Directory of Open Access Journals (Sweden)

    Andrey Shorov

    2014-01-01

    Full Text Available The paper outlines a bioinspired approach named “network nervous system" and methods of simulation of infrastructure attacks and protection mechanisms based on this approach. The protection mechanisms based on this approach consist of distributed prosedures of information collection and processing, which coordinate the activities of the main devices of a computer network, identify attacks, and determine nessesary countermeasures. Attacks and protection mechanisms are specified as structural models using a set-theoretic approach. An environment for simulation of protection mechanisms based on the biological metaphor is considered; the experiments demonstrating the effectiveness of the protection mechanisms are described.

  4. The framework for simulation of bioinspired security mechanisms against network infrastructure attacks.

    Science.gov (United States)

    Shorov, Andrey; Kotenko, Igor

    2014-01-01

    The paper outlines a bioinspired approach named "network nervous system" and methods of simulation of infrastructure attacks and protection mechanisms based on this approach. The protection mechanisms based on this approach consist of distributed procedures of information collection and processing, which coordinate the activities of the main devices of a computer network, identify attacks, and determine necessary countermeasures. Attacks and protection mechanisms are specified as structural models using a set-theoretic approach. An environment for simulation of protection mechanisms based on the biological metaphor is considered; the experiments demonstrating the effectiveness of the protection mechanisms are described.

  5. A Cross-Layer Cooperation Mechanism of Wireless Networks Based on Game Theory

    OpenAIRE

    Chunsheng, Cui; Yongjian, Yang; Liping, Huang

    2014-01-01

    To meet the wireless network congestion control problem, we give a definition of congestion degree classification and propose a mechanism of directed cooperative path net, guided by the wireless network’s cross-layer design methods and node cooperation principles. Considering the virtual collision and “starved” phenomenon in congested networks, the QRD mechanism and channel competition mechanism QPCG are proposed, with introducing the game theory into the cross-layer design. Simulation result...

  6. Understanding "Understanding" Flow for Network-Centric Warfare: Military Knowledge-Flow Mechanics

    National Research Council Canada - National Science Library

    Nissen, Mark

    2002-01-01

    Network-centric warfare (NCW) emphasizes information superiority for battlespace efficacy, but it is clear that the mechanics of how knowledge flows are just as important as those pertaining to the networks and communication...

  7. Independence through social networks: bridging potential among older women and men.

    Science.gov (United States)

    Cornwell, Benjamin

    2011-11-01

    Most studies of older adults' social networks focus on their access to dense networks that yield access to social support. This paper documents gender differences in the extent to which older adults maintain a related, but distinct, form of social capital-bridging potential, which involves serving as a tie between two unconnected parties and thus boosts independence and control of everyday social life. I use egocentric social network data from a national sample of 3,005 older adults--collected in 2005-2006 by the National Social Life, Health, and Aging Project--to compare older men's and women's network bridging potential using multivariate regression analysis. Older women are more likely than older men to have bridging potential in their networks-between both kin and non-kin contacts. These gender differences increase with age. Older women are also more likely to have network members who are not connected to or monopolized by their spouse or partner. Some, but not all, of these gender differences are due to the fact that older women have larger social networks and maintain more ties to people outside of the household. These findings raise important questions about the relational advantages older women have over older men, including greater autonomy, and contradict stereotypes about women having more closely knit, kin-centered networks than men.

  8. Tunable Sparse Network Coding for Multicast Networks

    DEFF Research Database (Denmark)

    Feizi, Soheil; Roetter, Daniel Enrique Lucani; Sørensen, Chres Wiant

    2014-01-01

    This paper shows the potential and key enabling mechanisms for tunable sparse network coding, a scheme in which the density of network coded packets varies during a transmission session. At the beginning of a transmission session, sparsely coded packets are transmitted, which benefits decoding...... complexity. At the end of a transmission, when receivers have accumulated degrees of freedom, coding density is increased. We propose a family of tunable sparse network codes (TSNCs) for multicast erasure networks with a controllable trade-off between completion time performance to decoding complexity...... a mechanism to perform efficient Gaussian elimination over sparse matrices going beyond belief propagation but maintaining low decoding complexity. Supporting simulation results are provided showing the trade-off between decoding complexity and completion time....

  9. Energy-Saving Mechanism in WDM/TDM-PON Based on Upstream Network Traffic

    Directory of Open Access Journals (Sweden)

    Paola Garfias

    2014-08-01

    Full Text Available One of the main challenges of Passive Optical Networks (PONs is the resource (bandwidth and wavelength management. Since it has been shown that access networks consume a significant part of the overall energy of the telecom networks, the resource management schemes should also consider energy minimization strategies. To sustain the increased bandwidth demand of emerging applications in the access section of the network, it is expected that next generation optical access networks will adopt the wavelength division/time division multiplexing (WDM/TDM technique to increase PONs capacity. Compared with traditional PONs, the architecture of a WDM/TDM-PON requires more transceivers/receivers, hence they are expected to consume more energy. In this paper, we focus on the energy minimization in WDM/TDM-PONs and we propose an energy-efficient Dynamic Bandwidth and Wavelength Allocation mechanism whose objective is to turn off, whenever possible, the unnecessary upstream traffic receivers at the Optical Line Terminal (OLT. We evaluate our mechanism in different scenarios and show that the proper use of upstream channels leads to relevant energy savings. Our proposed energy-saving mechanism is able to save energy at the OLT while maintaining the introduced penalties in terms of packet delay and cycle time within an acceptable range. We might highlight the benefits of our proposal as a mechanism that maximizes the channel utilization. Detailed implementation of the proposed algorithm is presented, and simulation results are reported to quantify energy savings and effects on network performance on different network scenarios.

  10. Memory-induced mechanism for self-sustaining activity in networks

    Science.gov (United States)

    Allahverdyan, A. E.; Steeg, G. Ver; Galstyan, A.

    2015-12-01

    We study a mechanism of activity sustaining on networks inspired by a well-known model of neuronal dynamics. Our primary focus is the emergence of self-sustaining collective activity patterns, where no single node can stay active by itself, but the activity provided initially is sustained within the collective of interacting agents. In contrast to existing models of self-sustaining activity that are caused by (long) loops present in the network, here we focus on treelike structures and examine activation mechanisms that are due to temporal memory of the nodes. This approach is motivated by applications in social media, where long network loops are rare or absent. Our results suggest that under a weak behavioral noise, the nodes robustly split into several clusters, with partial synchronization of nodes within each cluster. We also study the randomly weighted version of the models where the nodes are allowed to change their connection strength (this can model attention redistribution) and show that it does facilitate the self-sustained activity.

  11. Testing the effectiveness of network governance mechanisms to foster ambidexterity of agricultural innovation networks in East and Central Africa

    NARCIS (Netherlands)

    Pérez Perdomo, Silvia Andrea; Farrow, Andrew; Trienekens, Jacques H.; Omta, Onno S.W.F.; Velde, van der Gerben

    2017-01-01

    We tested three innovation network governance mechanisms for exploring and exploiting innovation opportunities. We analysed household-level panel data from agricultural innovation networks in Uganda, the Democratic Republic of the Congo and Rwanda. We found that first-order governed networks

  12. Evaluation of Fibrin-Based Interpenetrating Polymer Networks as Potential Biomaterials for Tissue Engineering

    Directory of Open Access Journals (Sweden)

    Olfat Gsib

    2017-12-01

    Full Text Available Interpenetrating polymer networks (IPNs have gained great attention for a number of biomedical applications due to their improved properties compared to individual components alone. In this study, we investigated the capacity of newly-developed naturally-derived IPNs as potential biomaterials for tissue engineering. These IPNs combine the biologic properties of a fibrous fibrin network polymerized at the nanoscale and the mechanical stability of polyethylene oxide (PEO. First, we assessed their cytotoxicity in vitro on L929 fibroblasts. We further evaluated their biocompatibility ex vivo with a chick embryo organotypic culture model. Subcutaneous implantations of the matrices were subsequently conducted on nude mice to investigate their biocompatibility in vivo. Our preliminary data highlighted that our biomaterials were non-cytotoxic (viability above 90%. The organotypic culture showed that the IPN matrices induced higher cell adhesion (across all the explanted organ tissues and migration (skin, intestine than the control groups, suggesting the advantages of using a biomimetic, yet mechanically-reinforced IPN-based matrix. We observed no major inflammatory response up to 12 weeks post implantation. All together, these data suggest that these fibrin-based IPNs are promising biomaterials for tissue engineering.

  13. The mechanism of erythrocyte sedimentation. Part 2: The global collapse of settling erythrocyte network.

    Science.gov (United States)

    Pribush, A; Meyerstein, D; Meyerstein, N

    2010-01-01

    Results reported in the companion paper showed that erythrocytes in quiescent blood are combined into a network followed by the formation of plasma channels within it. This study is focused on structural changes in the settling dispersed phase subsequent to the channeling and the effect of the structural organization on the sedimentation rate. It is suggested that the initial, slow stage of erythrocyte sedimentation is mainly controlled by the gravitational compactness of the collapsed network. The lifetime of RBC network and hence the duration of the slow regime of erythrocyte sedimentation decrease with an increase in the intercellular pair potential and with a decrease in Hct. The gravitational compactness of the collapsed network causes its rupture into individual fragments. The catastrophic collapse of the network transforms erythrocyte sedimentation from slow to fast regime. The size of RBC network fragment is insignificantly affected by Hct and is mainly determined by the intensity of intercellular attractive interactions. When cells were suspended in the weak aggregating medium, the Stokes radius of fragments does not differ measurably from that of individual RBCs. The proposed mechanism provides a reasonable explanation of the effects of RBC aggregation, Hct and the initial height of the blood column on the delayed erythrocyte sedimentation.

  14. Layered Location-Based Security Mechanism for Mobile Sensor Networks: Moving Security Areas

    Directory of Open Access Journals (Sweden)

    Ze Wang

    2015-09-01

    Full Text Available Network security is one of the most important issues in mobile sensor networks (MSNs. Networks are particularly vulnerable in hostile environments because of many factors, such as uncertain mobility, limitations on computation, and the need for storage in mobile nodes. Though some location-based security mechanisms can resist some malicious attacks, they are only suitable for static networks and may sometimes require large amounts of storage. To solve these problems, using location information, which is one of the most important properties in outdoor wireless networks, a security mechanism called a moving security area (MSA is proposed to resist malicious attacks by using mobile nodes’ dynamic location-based keys. The security mechanism is layered by performing different detection schemes inside or outside the MSA. The location-based private keys will be updated only at the appropriate moments, considering the balance of cost and security performance. By transferring parts of the detection tasks from ordinary nodes to the sink node, the memory requirements are distributed to different entities to save limited energy.

  15. Layered Location-Based Security Mechanism for Mobile Sensor Networks: Moving Security Areas.

    Science.gov (United States)

    Wang, Ze; Zhang, Haijuan; Wu, Luqiang; Zhou, Chang

    2015-09-25

    Network security is one of the most important issues in mobile sensor networks (MSNs). Networks are particularly vulnerable in hostile environments because of many factors, such as uncertain mobility, limitations on computation, and the need for storage in mobile nodes. Though some location-based security mechanisms can resist some malicious attacks, they are only suitable for static networks and may sometimes require large amounts of storage. To solve these problems, using location information, which is one of the most important properties in outdoor wireless networks, a security mechanism called a moving security area (MSA) is proposed to resist malicious attacks by using mobile nodes' dynamic location-based keys. The security mechanism is layered by performing different detection schemes inside or outside the MSA. The location-based private keys will be updated only at the appropriate moments, considering the balance of cost and security performance. By transferring parts of the detection tasks from ordinary nodes to the sink node, the memory requirements are distributed to different entities to save limited energy.

  16. Endogenous molecular network reveals two mechanisms of heterogeneity within gastric cancer

    Science.gov (United States)

    Li, Site; Zhu, Xiaomei; Liu, Bingya; Wang, Gaowei; Ao, Ping

    2015-01-01

    Intratumor heterogeneity is a common phenomenon and impedes cancer therapy and research. Gastric cancer (GC) cells have generally been classified into two heterogeneous cellular phenotypes, the gastric and intestinal types, yet the mechanisms of maintaining two phenotypes and controlling phenotypic transition are largely unknown. A qualitative systematic framework, the endogenous molecular network hypothesis, has recently been proposed to understand cancer genesis and progression. Here, a minimal network corresponding to such framework was found for GC and was quantified via a stochastic nonlinear dynamical system. We then further extended the framework to address the important question of intratumor heterogeneity quantitatively. The working network characterized main known features of normal gastric epithelial and GC cell phenotypes. Our results demonstrated that four positive feedback loops in the network are critical for GC cell phenotypes. Moreover, two mechanisms that contribute to GC cell heterogeneity were identified: particular positive feedback loops are responsible for the maintenance of intestinal and gastric phenotypes; GC cell progression routes that were revealed by the dynamical behaviors of individual key components are heterogeneous. In this work, we constructed an endogenous molecular network of GC that can be expanded in the future and would broaden the known mechanisms of intratumor heterogeneity. PMID:25962957

  17. A mechanism design approach to bandwidth allocation in tactical data networks

    Science.gov (United States)

    Mour, Ankur

    The defense sector is undergoing a phase of rapid technological advancement, in the pursuit of its goal of information superiority. This goal depends on a large network of complex interconnected systems - sensors, weapons, soldiers - linked through a maze of heterogeneous networks. The sheer scale and size of these networks prompt behaviors that go beyond conglomerations of systems or `system-of-systems'. The lack of a central locus and disjointed, competing interests among large clusters of systems makes this characteristic of an Ultra Large Scale (ULS) system. These traits of ULS systems challenge and undermine the fundamental assumptions of today's software and system engineering approaches. In the absence of a centralized controller it is likely that system users may behave opportunistically to meet their local mission requirements, rather than the objectives of the system as a whole. In these settings, methods and tools based on economics and game theory (like Mechanism Design) are likely to play an important role in achieving globally optimal behavior, when the participants behave selfishly. Against this background, this thesis explores the potential of using computational mechanisms to govern the behavior of ultra-large-scale systems and achieve an optimal allocation of constrained computational resources Our research focusses on improving the quality and accuracy of the common operating picture through the efficient allocation of bandwidth in tactical data networks among self-interested actors, who may resort to strategic behavior dictated by self-interest. This research problem presents the kind of challenges we anticipate when we have to deal with ULS systems and, by addressing this problem, we hope to develop a methodology which will be applicable for ULS system of the future. We build upon the previous works which investigate the application of auction-based mechanism design to dynamic, performance-critical and resource-constrained systems of interest

  18. Engineering the Mechanical Properties of Polymer Networks with Precise Doping of Primary Defects.

    Science.gov (United States)

    Chan, Doreen; Ding, Yichuan; Dauskardt, Reinhold H; Appel, Eric A

    2017-12-06

    Polymer networks are extensively utilized across numerous applications ranging from commodity superabsorbent polymers and coatings to high-performance microelectronics and biomaterials. For many applications, desirable properties are known; however, achieving them has been challenging. Additionally, the accurate prediction of elastic modulus has been a long-standing difficulty owing to the presence of loops. By tuning the prepolymer formulation through precise doping of monomers, specific primary network defects can be programmed into an elastomeric scaffold, without alteration of their resulting chemistry. The addition of these monomers that respond mechanically as primary defects is used both to understand their impact on the resulting mechanical properties of the materials and as a method to engineer the mechanical properties. Indeed, these materials exhibit identical bulk and surface chemistry, yet vastly different mechanical properties. Further, we have adapted the real elastic network theory (RENT) to the case of primary defects in the absence of loops, thus providing new insights into the mechanism for material strength and failure in polymer networks arising from primary network defects, and to accurately predict the elastic modulus of the polymer system. The versatility of the approach we describe and the fundamental knowledge gained from this study can lead to new advancements in the development of novel materials with precisely defined and predictable chemical, physical, and mechanical properties.

  19. A potential mechanism for allometric trabecular bone scaling in terrestrial mammals.

    Science.gov (United States)

    Christen, Patrik; Ito, Keita; van Rietbergen, Bert

    2015-03-01

    Trabecular bone microstructural parameters, including trabecular thickness, spacing, and number, have been reported to scale with animal size with negative allometry, whereas bone volume fraction is animal size-invariant in terrestrial mammals. As for the majority of scaling patterns described in animals, its underlying mechanism is unknown. However, it has also been found that osteocyte density is inversely related to animal size, possibly adapted to metabolic rate, which shows a negative relationship as well. In addition, the signalling reach of osteocytes is limited by the extent of the lacuno-canalicular network, depending on trabecular dimensions and thus also on animal size. Here we propose animal size-dependent variations in osteocyte density and their signalling influence distance as a potential mechanism for negative allometric trabecular bone scaling in terrestrial mammals. Using an established and tested computational model of bone modelling and remodelling, we run simulations with different osteocyte densities and influence distances mimicking six terrestrial mammals covering a large range of body masses. Simulated trabecular structures revealed negative allometric scaling for trabecular thickness, spacing, and number, constant bone volume fraction, and bone turnover rates inversely related to animal size. These results are in agreement with previous observations supporting our proposal of osteocyte density and influence distance variation as a potential mechanism for negative allometric trabecular bone scaling in terrestrial mammals. The inverse relationship between bone turnover rates and animal size further indicates that trabecular bone scaling may be linked to metabolic rather than mechanical adaptations. © 2015 Anatomical Society.

  20. Fundamental Lifetime Mechanisms in Routing Protocols for Wireless Sensor Networks: A Survey and Open Issues

    Science.gov (United States)

    Eslaminejad, Mohammadreza; Razak, Shukor Abd

    2012-01-01

    Wireless sensor networks basically consist of low cost sensor nodes which collect data from environment and relay them to a sink, where they will be subsequently processed. Since wireless nodes are severely power-constrained, the major concern is how to conserve the nodes' energy so that network lifetime can be extended significantly. Employing one static sink can rapidly exhaust the energy of sink neighbors. Furthermore, using a non-optimal single path together with a maximum transmission power level may quickly deplete the energy of individual nodes on the route. This all results in unbalanced energy consumption through the sensor field, and hence a negative effect on the network lifetime. In this paper, we present a comprehensive taxonomy of the various mechanisms applied for increasing the network lifetime. These techniques, whether in the routing or cross-layer area, fall within the following types: multi-sink, mobile sink, multi-path, power control and bio-inspired algorithms, depending on the protocol operation. In this taxonomy, special attention has been devoted to the multi-sink, power control and bio-inspired algorithms, which have not yet received much consideration in the literature. Moreover, each class covers a variety of the state-of-the-art protocols, which should provide ideas for potential future works. Finally, we compare these mechanisms and discuss open research issues. PMID:23202008

  1. The Potential for a Ka-band (32 GHz) Worldwide VLBI Network

    Science.gov (United States)

    Jacobs, C. S.; Bach, U.; Colomer, F.; Garcia-Miro, C.; Gomez-Gonzalez, J.; Gulyaev, S.; Horiuchi, S.; Ichikawa, R.; Kraus, A.; Kronschnabl, G.; hide

    2012-01-01

    Ka-band (32 GHz, 9mm) Very Long Baseline Interferometric (VLBI) networking has now begun and has tremendous potential for expansion over the next few years. Ka-band VLBI astrometry from NASA's Deep Space Network has already developed a catalog of 470 observable sources with highly accurate positions. Now, several antennas worldwide are planning or are considering adding Ka-band VLBI capability. Thus, there is now an opportunity to create a worldwide Ka-band network with potential for high resolution imaging and astrometry. With baselines approaching a Giga-lambda, a Ka-band network would be able to probe source structure at the nano-radian (200 as) level ( 100X better than Hubble) and thus gain insight into the astrophysics of the most compact regions of emission in active galactic nuclei. We discuss the advantages of Ka-band, show the known sources and candidates, simulate projected baseline (uv) coverage, and discuss potential radio frequency feeds. The combination of these elements demonstrates the feasibility of a worldwide Ka network within the next few years!

  2. Virus spreading in wireless sensor networks with a medium access control mechanism

    International Nuclear Information System (INIS)

    Wang Ya-Qi; Yang Xiao-Yuan

    2013-01-01

    In this paper, an extended version of standard susceptible-infected (SI) model is proposed to consider the influence of a medium access control mechanism on virus spreading in wireless sensor networks. Theoretical analysis shows that the medium access control mechanism obviously reduces the density of infected nodes in the networks, which has been ignored in previous studies. It is also found that by increasing the network node density or node communication radius greatly increases the number of infected nodes. The theoretical results are confirmed by numerical simulations. (general)

  3. Potential fluid mechanic pathways of platelet activation.

    Science.gov (United States)

    Shadden, Shawn C; Hendabadi, Sahar

    2013-06-01

    Platelet activation is a precursor for blood clotting, which plays leading roles in many vascular complications and causes of death. Platelets can be activated by chemical or mechanical stimuli. Mechanically, platelet activation has been shown to be a function of elevated shear stress and exposure time. These contributions can be combined by considering the cumulative stress or strain on a platelet as it is transported. Here, we develop a framework for computing a hemodynamic-based activation potential that is derived from a Lagrangian integral of strain rate magnitude. We demonstrate that such a measure is generally maximized along, and near to, distinguished material surfaces in the flow. The connections between activation potential and these structures are illustrated through stenotic flow computations. We uncover two distinct structures that may explain observed thrombus formation at the apex and downstream of stenoses. More broadly, these findings suggest fundamental relationships may exist between potential fluid mechanic pathways for mechanical platelet activation and the mechanisms governing their transport.

  4. Mechanisms of memory storage in a model perirhinal network.

    Science.gov (United States)

    Samarth, Pranit; Ball, John M; Unal, Gunes; Paré, Denis; Nair, Satish S

    2017-01-01

    The perirhinal cortex supports recognition and associative memory. Prior unit recording studies revealed that recognition memory involves a reduced responsiveness of perirhinal cells to familiar stimuli whereas associative memory formation is linked to increasing perirhinal responses to paired stimuli. Both effects are thought to depend on perirhinal plasticity but it is unclear how the same network could support these opposite forms of plasticity. However, a recent study showed that when neocortical inputs are repeatedly activated, depression or potentiation could develop, depending on the extent to which the stimulated neocortical activity recruited intrinsic longitudinal connections. We developed a biophysically realistic perirhinal model that reproduced these phenomena and used it to investigate perirhinal mechanisms of associative memory. These analyzes revealed that associative plasticity is critically dependent on a specific subset of neurons, termed conjunctive cells (CCs). When the model network was trained with spatially distributed but coincident neocortical inputs, CCs acquired excitatory responses to the paired inputs and conveyed them to distributed perirhinal sites via longitudinal projections. CC ablation during recall abolished expression of the associative memory. However, CC ablation during training did not prevent memory formation because new CCs emerged, revealing that competitive synaptic interactions governs the formation of CC assemblies.

  5. Neural mechanisms tracking popularity in real-world social networks.

    Science.gov (United States)

    Zerubavel, Noam; Bearman, Peter S; Weber, Jochen; Ochsner, Kevin N

    2015-12-08

    Differences in popularity are a key aspect of status in virtually all human groups and shape social interactions within them. Little is known, however, about how we track and neurally represent others' popularity. We addressed this question in two real-world social networks using sociometric methods to quantify popularity. Each group member (perceiver) viewed faces of every other group member (target) while whole-brain functional MRI data were collected. Independent functional localizer tasks were used to identify brain systems supporting affective valuation (ventromedial prefrontal cortex, ventral striatum, amygdala) and social cognition (dorsomedial prefrontal cortex, precuneus, temporoparietal junction), respectively. During the face-viewing task, activity in both types of neural systems tracked targets' sociometric popularity, even when controlling for potential confounds. The target popularity-social cognition system relationship was mediated by valuation system activity, suggesting that observing popular individuals elicits value signals that facilitate understanding their mental states. The target popularity-valuation system relationship was strongest for popular perceivers, suggesting enhanced sensitivity to differences among other group members' popularity. Popular group members also demonstrated greater interpersonal sensitivity by more accurately predicting how their own personalities were perceived by other individuals in the social network. These data offer insights into the mechanisms by which status guides social behavior.

  6. Supersymmetric quantum mechanics and new potentials

    International Nuclear Information System (INIS)

    Drigo Filho, E.

    1988-01-01

    Using the supersymmetric quantum mechanics the following potential are generalized. The particle in the box, Poeschl-Teller and Rosen-Morse. The new potentials are evaluated and their eigenfunctions and spectra are indicated. (author) [pt

  7. The mechanism of synchronization in feed-forward neuronal networks

    International Nuclear Information System (INIS)

    Goedeke, S; Diesmann, M

    2008-01-01

    Synchronization in feed-forward subnetworks of the brain has been proposed to explain the precisely timed spike patterns observed in experiments. While the attractor dynamics of these networks is now well understood, the underlying single neuron mechanisms remain unexplained. Previous attempts have captured the effects of the highly fluctuating membrane potential by relating spike intensity f(U) to the instantaneous voltage U generated by the input. This article shows that f is high during the rise and low during the decay of U(t), demonstrating that the U-dot-dependence of f, not refractoriness, is essential for synchronization. Moreover, the bifurcation scenario is quantitatively described by a simple f(U,U-dot) relationship. These findings suggest f(U,U-dot) as the relevant model class for the investigation of neural synchronization phenomena in a noisy environment

  8. Tailoring the mechanical properties by molecular integration of flexible and stiff polymer networks.

    Science.gov (United States)

    Wan, Haixiao; Shen, Jianxiang; Gao, Naishen; Liu, Jun; Gao, Yangyang; Zhang, Liqun

    2018-03-28

    Designing a multiple-network structure at the molecular level to tailor the mechanical properties of polymeric materials is of great scientific and technological importance. Through the coarse-grained molecular dynamics simulation, we successfully construct an interpenetrating polymer network (IPN) composed of a flexible polymer network and a stiff polymer network. First, we find that there is an optimal chain stiffness for a single network (SN) to achieve the best stress-strain behavior. Then we turn to study the mechanical behaviors of IPNs. The result shows that the stress-strain behaviors of the IPNs appreciably exceed the sum of that of the corresponding single flexible and stiff network, which highlights the advantage of the IPN structure. By systematically varying the stiffness of the stiff polymer network of the IPNs, optimal stiffness also exists to achieve the best performance. We attribute this to a much larger contribution of the non-bonded interaction energy. Last, the effect of the component concentration ratio is probed. With the increase of the concentration of the flexible network, the stress-strain behavior of the IPNs is gradually enhanced, while an optimized concentration (around 60% molar ration) of the stiff network occurs, which could result from the dominant role of the enthalpy rather than the entropy. In general, our work is expected to provide some guidelines to better tailor the mechanical properties of the IPNs made of a flexible network and a stiff network, by manipulating the stiffness of the stiff polymer network and the component concentration ratio.

  9. Epidemic Spread in Networks Induced by Deactivation Mechanism

    International Nuclear Information System (INIS)

    Yu Xiaoling; Wu Xiao; Zhang Duanming; Li Zhihao; Liang Fang; Wang Xiaoyu

    2008-01-01

    We have studied the topology and epidemic spreading behaviors on the networks in which deactivation mechanism and long-rang connection are coexisted. By means of numerical simulation, we find that the clustering coefficient C and the Pearson correlation coefficient r decrease with increasing long-range connection μ and the topological state of the network changes into that of BA model at the end (when μ = 1). For the Susceptible-Infect-Susceptible model of epidemics, the epidemic threshold can reach maximum value at μ = 0.4 and presents two different variable states around μ = 0.4

  10. A distributed incentive compatible pricing mechanism for P2P networks

    Science.gov (United States)

    Zhang, Jie; Zhao, Zheng; Xiong, Xiao; Shi, Qingwei

    2007-09-01

    Peer-to-Peer (P2P) systems are currently receiving considerable interest. However, as experience with P2P networks shows, the selfish behaviors of peers may lead to serious problems of P2P network, such as free-riding and white-washing. In order to solve these problems, there are increasing considerations on reputation system design in the study of P2P networks. Most of the existing works is concerning probabilistic estimation or social networks to evaluate the trustworthiness for a peer to others. However, these models can not be efficient all the time. In this paper, our aim is to provide a general mechanism that can maximize P2P networks social welfare in a way of Vickrey-Clarke-Groves family, while assuming every peer in P2P networks is rational and selfish, which means they only concern about their own outcome. This mechanism has some desirable properties using an O(n) algorithm: (1) incentive compatibility, every peer truly report its connection type; (2) individually rationality; and (3) fully decentralized, we design a multiple-principal multiple-agent model, concerning about the service provider and service requester individually.

  11. Mechanisms of protection of information in computer networks and systems

    Directory of Open Access Journals (Sweden)

    Sergey Petrovich Evseev

    2011-10-01

    Full Text Available Protocols of information protection in computer networks and systems are investigated. The basic types of threats of infringement of the protection arising from the use of computer networks are classified. The basic mechanisms, services and variants of realization of cryptosystems for maintaining authentication, integrity and confidentiality of transmitted information are examined. Their advantages and drawbacks are described. Perspective directions of development of cryptographic transformations for the maintenance of information protection in computer networks and systems are defined and analyzed.

  12. A complex network for studying the transmission mechanisms in stock market

    Science.gov (United States)

    Long, Wen; Guan, Lijing; Shen, Jiangjian; Song, Linqiu; Cui, Lingxiao

    2017-10-01

    This paper introduces a new complex network to describe the volatility transmission mechanisms in stock market. The network can not only endogenize stock market's volatility but also figure out the direction of volatility spillover. In this model, we first use BEKK-GARCH to estimate the volatility spillover effects among Chinese 18 industry sectors. Then, based on the ARCH coefficients and GARCH coefficients, the directional shock networks and variance networks in different stages are constructed separately. We find that the spillover effects and network structures changes in different stages. The results of the topological stability test demonstrate that the connectivity of networks becomes more fragile to selective attacks than stochastic attacks.

  13. A Channel Allocation Mechanism for Cellular Networks

    Directory of Open Access Journals (Sweden)

    Chi-Hua Chen

    2017-04-01

    Full Text Available In cellular networks, call blocking causes lower customer satisfaction and economic loss. Therefore, the channel allocation for call block avoidance is an important issue. This study proposes a mechanism that considers the real-time traffic information (e.g., traffic flow and vehicle speed and the user behavior (e.g., call inter-arrival time and call holding time to analyze the adaptable number of communication calls in the specific cell for channel allocation. In experiments about call block probabilities (CBP, this study simulated two cases that are the situations of the whole day and traffic accident. The simulation results show that all CBPs in the scenario of whole day are less than 21.5% by using the proposed mechanism, which is better than using the static channel allocation (SCA mechanism. Moreover, all CBPs in the scenario of traffic accidents are less than 16.5% by using the proposed mechanism, which is better than using the SCA mechanism. Therefore, the proposed mechanism can decrease the number of CBPs effectively.

  14. Potential for transmission of infections in networks of cattle farms

    Directory of Open Access Journals (Sweden)

    V.V. Volkova

    2010-09-01

    Full Text Available The aim of this analysis is to evaluate how generic properties of networks of livestock farms connected by movements of cattle impact on the potential for spread of infectious diseases. We focus on endemic diseases with long infectious periods in affected cattle, such as bovine tuberculosis. Livestock farm networks provide a rare example of large but fully specified directed contact networks, allowing investigations into how properties of such networks impact the potential for spread of infections within them. Here we quantify the latter in terms of the basic reproduction number, R0, and partition the contributions to R0 from first order moments (mean contact rates and second order moments (variances and covariances of contact rates of the farm contact matrices. We find that the second order properties make a substantial contribution to the magnitude of R0, similarly to that reported for other populations. Importantly, however, we find that the magnitude of these effects depends on exactly how the contacts between farms are defined or weighted. We note that the second order properties of a directed contact network may vary through time even with little change in the mean contact rates or in overall connectedness of the network. Keywords: Basic reproduction number, Infectious disease, Heterogeneity, 20–80 rule, Contact network, Bovine tuberculosis

  15. Statistical mechanics of the fashion game on random networks

    International Nuclear Information System (INIS)

    Sun, YiFan

    2016-01-01

    A model of fashion on networks is studied. This model consists of two groups of agents that are located on a network and have opposite viewpoints towards being fashionable: behaving consistently with either the majority or the minority of adjacent agents. Checking whether the fashion game has a pure Nash equilibrium (pure NE) is a non-deterministic polynomial complete problem. Using replica-symmetric mean field theory, the largest proportion of satisfied agents and the region where at least one pure NE should exist are determined for several types of random networks. Furthermore, a quantitive analysis of the asynchronous best response dynamics yields the phase diagram of existence and detectability of pure NE in the fashion game on some random networks. (paper: classical statistical mechanics, equilibrium and non-equilibrium).

  16. Potential of Social Networking Sites for Distance Education Student Engagement

    Science.gov (United States)

    Lester, Jaime; Perini, Michael

    2010-01-01

    This chapter explores the potential of social networking sites for increasing student engagement for distance education learners. The authors present a modified student engagement model with a focus on the integration of technology, specifically social networking sites for community college distance education learners. The chapter concludes with…

  17. Applications of neural networks to mechanics

    International Nuclear Information System (INIS)

    1997-01-01

    Neural networks have become powerful tools in engineer's techniques. The aim of this conference was to present their application to concrete cases in the domain of mechanics, including the preparation and use of materials. Artificial neurons are non-linear organs which provide an output signal that depends on several differently weighted input signals. Their connection into networks allows to solve problems for which the driving laws are not well known. The applications discussed during this conference deal with: the driving of machines or processes, the control of machines, materials or products, the simulation and forecasting, and the optimization. Three papers dealing with the control of spark ignition engines, the regulation of heating floors and the optimization of energy consumptions in industrial buildings were selected for ETDE and one paper dealing with the optimization of the management of a reprocessed plutonium stock was selected for INIS. (J.S.)

  18. Centrality and get-richer mechanisms in interregional knowledge networks

    DEFF Research Database (Denmark)

    Mitze, Timo; Strotebeck, Falk

    2018-01-01

    and relate them to sector-region-specific and overall regional attributes in an explorative regression approach. The results indicate that fit-get-richer mechanisms proxied by regional endowments and policy factors such as biotech research and development funding categories and human capital matter...... for network formation. We find that these correlations differ across centrality measures and that empirical evidence for a richer-get-richer mechanism is limited....

  19. A Fault Tolerance Mechanism for On-Road Sensor Networks

    Directory of Open Access Journals (Sweden)

    Lei Feng

    2016-12-01

    Full Text Available On-Road Sensor Networks (ORSNs play an important role in capturing traffic flow data for predicting short-term traffic patterns, driving assistance and self-driving vehicles. However, this kind of network is prone to large-scale communication failure if a few sensors physically fail. In this paper, to ensure that the network works normally, an effective fault-tolerance mechanism for ORSNs which mainly consists of backup on-road sensor deployment, redundant cluster head deployment and an adaptive failure detection and recovery method is proposed. Firstly, based on the N − x principle and the sensors’ failure rate, this paper formulates the backup sensor deployment problem in the form of a two-objective optimization, which explains the trade-off between the cost and fault resumption. In consideration of improving the network resilience further, this paper introduces a redundant cluster head deployment model according to the coverage constraint. Then a common solving method combining integer-continuing and sequential quadratic programming is explored to determine the optimal location of these two deployment problems. Moreover, an Adaptive Detection and Resume (ADR protocol is deigned to recover the system communication through route and cluster adjustment if there is a backup on-road sensor mismatch. The final experiments show that our proposed mechanism can achieve an average 90% recovery rate and reduce the average number of failed sensors at most by 35.7%.

  20. Chimera states in mechanical oscillator networks

    DEFF Research Database (Denmark)

    Martens, Erik Andreas; Thutupalli, Shashi; Fourrière, Antoine

    2013-01-01

    of identical oscillators, numerous theoretical studies in recent years have revealed the intriguing possibility of "chimera states," in which the symmetry of the oscillator population is broken into a synchronous part and an asynchronous part. However, a striking lack of empirical evidence raises the question...... of whether chimeras are indeed characteristic of natural systems. This calls for a palpable realization of chimera states without any fine-tuning, from which physical mechanisms underlying their emergence can be uncovered. Here, we devise a simple experiment with mechanical oscillators coupled...... in a hierarchical network to show that chimeras emerge naturally from a competition between two antagonistic synchronization patterns. We identify a wide spectrum of complex states, encompassing and extending the set of previously described chimeras. Our mathematical model shows that the self-organization observed...

  1. Short-term memory of motor network performance via activity-dependent potentiation of Na+/K+ pump function.

    Science.gov (United States)

    Zhang, Hong-Yan; Sillar, Keith T

    2012-03-20

    Brain networks memorize previous performance to adjust their output in light of past experience. These activity-dependent modifications generally result from changes in synaptic strengths or ionic conductances, and ion pumps have only rarely been demonstrated to play a dynamic role. Locomotor behavior is produced by central pattern generator (CPG) networks and modified by sensory and descending signals to allow for changes in movement frequency, intensity, and duration, but whether or how the CPG networks recall recent activity is largely unknown. In Xenopus frog tadpoles, swim bout duration correlates linearly with interswim interval, suggesting that the locomotor network retains a short-term memory of previous output. We discovered an ultraslow, minute-long afterhyperpolarization (usAHP) in network neurons following locomotor episodes. The usAHP is mediated by an activity- and sodium spike-dependent enhancement of electrogenic Na(+)/K(+) pump function. By integrating spike frequency over time and linking the membrane potential of spinal neurons to network performance, the usAHP plays a dynamic role in short-term motor memory. Because Na(+)/K(+) pumps are ubiquitously expressed in neurons of all animals and because sodium spikes inevitably accompany network activity, the usAHP may represent a phylogenetically conserved but largely overlooked mechanism for short-term memory of neural network function. Copyright © 2012 Elsevier Ltd. All rights reserved.

  2. Neural networks and their potential application to nuclear power plants

    International Nuclear Information System (INIS)

    Uhrig, R.E.

    1991-01-01

    A network of artificial neurons, usually called an artificial neural network is a data processing system consisting of a number of highly interconnected processing elements in an architecture inspired by the structure of the cerebral cortex portion of the brain. Hence, neural networks are often capable of doing things which humans or animals do well but which conventional computers often do poorly. Neural networks exhibit characteristics and capabilities not provided by any other technology. Neural networks may be designed so as to classify an input pattern as one of several predefined types or to create, as needed, categories or classes of system states which can be interpreted by a human operator. Neural networks have the ability to recognize patterns, even when the information comprising these patterns is noisy, sparse, or incomplete. Thus, systems of artificial neural networks show great promise for use in environments in which robust, fault-tolerant pattern recognition is necessary in a real-time mode, and in which the incoming data may be distorted or noisy. The application of neural networks, a rapidly evolving technology used extensively in defense applications, alone or in conjunction with other advanced technologies, to some of the problems of operating nuclear power plants has the potential to enhance the safety, reliability and operability of nuclear power plants. The potential applications of neural networking include, but are not limited to diagnosing specific abnormal conditions, identification of nonlinear dynamics and transients, detection of the change of mode of operation, control of temperature and pressure during start-up, signal validation, plant-wide monitoring using autoassociative neural networks, monitoring of check valves, modeling of the plant thermodynamics, emulation of core reload calculations, analysis of temporal sequences in NRC's ''licensee event reports,'' and monitoring of plant parameters

  3. Singular potentials in quantum mechanics

    International Nuclear Information System (INIS)

    Aguilera-Navarro, V.C.; Koo, E. Ley

    1995-10-01

    This paper is a review of some mathematical methods as recently developed and applied to deal with singular potentials in Quantum Mechanics. Regular and singular perturbative methods as well as variational treatments are considered. (author). 25 refs

  4. The effects of topology on the structural, dynamic and mechanical properties of network-forming materials

    International Nuclear Information System (INIS)

    Wilson, Mark

    2012-01-01

    The effects of network topology on the static structural, mechanical and dynamic properties of MX 2 network-forming liquids (with tetrahedral short-range order) are discussed. The network topology is controlled via a single model parameter (the anion polarizability) which effectively constrains the inter-tetrahedral linkages in a physically transparent manner. Critically, it is found to control the balance between the stability of corner- and edge-sharing tetrahedra. A potential rigidity transformation is investigated. The vibrational density of states is investigated, using an instantaneous normal model analysis, as a function of both anion polarizability and temperature. A low frequency peak is seen to appear and is shown to be correlated with the fraction of cations which are linked through solely edge-sharing structural motifs. A modified effective mean atom coordination number is proposed which allows the appearance of the low frequency feature to be understood in terms of a mean field rigidity percolation threshold. (paper)

  5. Cytokines and cytokine networks target neurons to modulate long-term potentiation.

    Science.gov (United States)

    Prieto, G Aleph; Cotman, Carl W

    2017-04-01

    Cytokines play crucial roles in the communication between brain cells including neurons and glia, as well as in the brain-periphery interactions. In the brain, cytokines modulate long-term potentiation (LTP), a cellular correlate of memory. Whether cytokines regulate LTP by direct effects on neurons or by indirect mechanisms mediated by non-neuronal cells is poorly understood. Elucidating neuron-specific effects of cytokines has been challenging because most brain cells express cytokine receptors. Moreover, cytokines commonly increase the expression of multiple cytokines in their target cells, thus increasing the complexity of brain cytokine networks even after single-cytokine challenges. Here, we review evidence on both direct and indirect-mediated modulation of LTP by cytokines. We also describe novel approaches based on neuron- and synaptosome-enriched systems to identify cytokines able to directly modulate LTP, by targeting neurons and synapses. These approaches can test multiple samples in parallel, thus allowing the study of multiple cytokines simultaneously. Hence, a cytokine networks perspective coupled with neuron-specific analysis may contribute to delineation of maps of the modulation of LTP by cytokines. Copyright © 2017 Elsevier Ltd. All rights reserved.

  6. Artificial Neural Network Based Mission Planning Mechanism for Spacecraft

    Science.gov (United States)

    Li, Zhaoyu; Xu, Rui; Cui, Pingyuan; Zhu, Shengying

    2018-04-01

    The ability to plan and react fast in dynamic space environments is central to intelligent behavior of spacecraft. For space and robotic applications, many planners have been used. But it is difficult to encode the domain knowledge and directly use existing techniques such as heuristic to improve the performance of the application systems. Therefore, regarding planning as an advanced control problem, this paper first proposes an autonomous mission planning and action selection mechanism through a multiple layer perceptron neural network approach to select actions in planning process and improve efficiency. To prove the availability and effectiveness, we use autonomous mission planning problems of the spacecraft, which is a sophisticated system with complex subsystems and constraints as an example. Simulation results have shown that artificial neural networks (ANNs) are usable for planning problems. Compared with the existing planning method in EUROPA, the mechanism using ANNs is more efficient and can guarantee stable performance. Therefore, the mechanism proposed in this paper is more suitable for planning problems of spacecraft that require real time and stability.

  7. A Multi-Hop Clustering Mechanism for Scalable IoT Networks.

    Science.gov (United States)

    Sung, Yoonyoung; Lee, Sookyoung; Lee, Meejeong

    2018-03-23

    It is expected that up to 26 billion Internet of Things (IoT) equipped with sensors and wireless communication capabilities will be connected to the Internet by 2020 for various purposes. With a large scale IoT network, having each node connected to the Internet with an individual connection may face serious scalability issues. The scalability problem of the IoT network may be alleviated by grouping the nodes of the IoT network into clusters and having a representative node in each cluster connect to the Internet on behalf of the other nodes in the cluster instead of having a per-node Internet connection and communication. In this paper, we propose a multi-hop clustering mechanism for IoT networks to minimize the number of required Internet connections. Specifically, the objective of proposed mechanism is to select the minimum number of coordinators, which take the role of a representative node for the cluster, i.e., having the Internet connection on behalf of the rest of the nodes in the cluster and to map a partition of the IoT nodes onto the selected set of coordinators to minimize the total distance between the nodes and their respective coordinator under a certain constraint in terms of maximum hop count between the IoT nodes and their respective coordinator. Since this problem can be mapped into a set cover problem which is known as NP-hard, we pursue a heuristic approach to solve the problem and analyze the complexity of the proposed solution. Through a set of experiments with varying parameters, the proposed scheme shows 63-87.3% reduction of the Internet connections depending on the number of the IoT nodes while that of the optimal solution is 65.6-89.9% in a small scale network. Moreover, it is shown that the performance characteristics of the proposed mechanism coincide with expected performance characteristics of the optimal solution in a large-scale network.

  8. Quantifying capability of a local seismic network in terms of locations and focal mechanism solutions of weak earthquakes

    Science.gov (United States)

    Fojtíková, Lucia; Kristeková, Miriam; Málek, Jiří; Sokos, Efthimios; Csicsay, Kristián; Zahradník, Jiří

    2016-01-01

    Extension of permanent seismic networks is usually governed by a number of technical, economic, logistic, and other factors. Planned upgrade of the network can be justified by theoretical assessment of the network capability in terms of reliable estimation of the key earthquake parameters (e.g., location and focal mechanisms). It could be useful not only for scientific purposes but also as a concrete proof during the process of acquisition of the funding needed for upgrade and operation of the network. Moreover, the theoretical assessment can also identify the configuration where no improvement can be achieved with additional stations, establishing a tradeoff between the improvement and additional expenses. This paper presents suggestion of a combination of suitable methods and their application to the Little Carpathians local seismic network (Slovakia, Central Europe) monitoring epicentral zone important from the point of seismic hazard. Three configurations of the network are considered: 13 stations existing before 2011, 3 stations already added in 2011, and 7 new planned stations. Theoretical errors of the relative location are estimated by a new method, specifically developed in this paper. The resolvability of focal mechanisms determined by waveform inversion is analyzed by a recent approach based on 6D moment-tensor error ellipsoids. We consider potential seismic events situated anywhere in the studied region, thus enabling "mapping" of the expected errors. Results clearly demonstrate that the network extension remarkably decreases the errors, mainly in the planned 23-station configuration. The already made three-station extension of the network in 2011 allowed for a few real data examples. Free software made available by the authors enables similar application in any other existing or planned networks.

  9. Mechanical behaviour of textile-reinforced thermoplastics with integrated sensor network components

    International Nuclear Information System (INIS)

    Hufenbach, W.; Adam, F.; Fischer, W.-J.; Kunadt, A.; Weck, D.

    2011-01-01

    Highlights: → Consideration of two types of integrated bus systems for textile-reinforced thermoplastics with embedded sensor networks. → Specimens with bus systems made of flexible printed circuit boards show good mechanical performance compared to the reference. → Inhomogeneous interface and reduced stiffnesses and strengths for specimens with bus systems basing on single copper wires. -- Abstract: The embedding of sensor networks into textile-reinforced thermoplastics enables the design of function-integrative lightweight components suitable for high volume production. In order to investigate the mechanical behaviour of such functionalised composites, two types of bus systems are selected as exemplary components of sensor networks. These elements are embedded into glass fibre-reinforced polypropylene (GF/PP) during the layup process of unconsolidated weft-knitted GF/PP-preforms. Two fibre orientations are considered and orthotropic composite plates are manufactured by hot pressing technology. Micrograph investigations and computer tomography analyses show different interface qualities between the thermoplastic composite and the two types of bus systems. Mechanical tests under tensile and flexural loading indicate a significant influence of the embedded bus system elements on the structural stiffness and strength.

  10. Self-Healing Natural Rubber with Tailorable Mechanical Properties Based on Ionic Supramolecular Hybrid Network.

    Science.gov (United States)

    Xu, Chuanhui; Cao, Liming; Huang, Xunhui; Chen, Yukun; Lin, Baofeng; Fu, Lihua

    2017-08-30

    In most cases, the strength of self-healing supramolecular rubber based on noncovalent bonds is in the order of KPa, which is a challenge for their further applications. Incorporation of conventional fillers can effectively enhance the strength of rubbers, but usually accompanied by a sacrifice of self-healing capability due to that the filler system is independent of the reversible supramolecular network. In the present work, in situ reaction of methacrylic acid (MAA) and excess zinc oxide (ZnO) was realized in natural rubber (NR). Ionic cross-links in NR matrix were obtained by limiting the covalent cross-linking of NR molecules and allowing the in situ polymerization of MAA/ZnO. Because of the natural affinity between Zn 2+ ion-rich domains and ZnO, the residual nano ZnO participated in formation of a reversible ionic supramolecular hybrid network, thus having little obstructions on the reconstruction of ionic cross-links. Meanwhile, the well dispersed residual ZnO could tailor the mechanical properties of NR by changing the MAA/ZnO molar ratios. The present study thus provides a simple method to fabricate a new self-healing NR with tailorable mechanical properties that may have more potential applications.

  11. An energy-efficient leader election mechanism for wireless body area networks

    OpenAIRE

    Zhang , Rongrong; Moungla , Hassine; Mehaoua , Ahmed

    2014-01-01

    International audience; In Wireless Body Area Networks (WBANs), the energy consumption determines the lifetime of the entire network. As a result, how to conserve the energy to prolong the network lifetime becomes a key problem in WBANs. In this paper, to address the energy conservation problem in WBANs, we develop an Energy-Efficient Leader Election mechanism, called EELE. In EELE, each node competes for the leader following the distributed leader election algorithm in which a utility functi...

  12. AUCTION MECHANISMS FOR IMPLEMENTING TRADABLE NETWORK PERMIT MARKETS

    Science.gov (United States)

    Wada, Kentaro; Akamatsu, Takashi

    This paper proposes a new auction mechanism for implementing the tradable network permit markets. Assuming that each user makes a trip from an origin to a destination along a path in a specific time period, we design an auction mechanism that enables each user to purchase a bundle of permits corresponding to a set of links in the user's preferred path. The objective of the proposed mechanism is to achieve a socially optimal state with minimal revelation of users' private information. In order to achieve this, the mechanism employs an evolutionary approach that has an auction phase and a path capacity adjustment phase, which are repeated on a day-to-day basis. We prove that the proposed mechanism has the following desirable properties: (1) truthful bidding is the dominant strategy for each user and (2) the proposed mechanism converges to an approximate socially optimal state in the sense that the achieved value of the social surplus reaches its maximum value when the number of users is large.

  13. The role of endogenous and exogenous mechanisms in the formation of R&D networks

    Science.gov (United States)

    Tomasello, Mario V.; Perra, Nicola; Tessone, Claudio J.; Karsai, Márton; Schweitzer, Frank

    2014-01-01

    We develop an agent-based model of strategic link formation in Research and Development (R&D) networks. Empirical evidence has shown that the growth of these networks is driven by mechanisms which are both endogenous to the system (that is, depending on existing alliances patterns) and exogenous (that is, driven by an exploratory search for newcomer firms). Extant research to date has not investigated both mechanisms simultaneously in a comparative manner. To overcome this limitation, we develop a general modeling framework to shed light on the relative importance of these two mechanisms. We test our model against a comprehensive dataset, listing cross-country and cross-sectoral R&D alliances from 1984 to 2009. Our results show that by fitting only three macroscopic properties of the network topology, this framework is able to reproduce a number of micro-level measures, including the distributions of degree, local clustering, path length and component size, and the emergence of network clusters. Furthermore, by estimating the link probabilities towards newcomers and established firms from the data, we find that endogenous mechanisms are predominant over the exogenous ones in the network formation, thus quantifying the importance of existing structures in selecting partner firms. PMID:25022561

  14. The role of endogenous and exogenous mechanisms in the formation of R&D networks

    Science.gov (United States)

    Tomasello, Mario V.; Perra, Nicola; Tessone, Claudio J.; Karsai, Márton; Schweitzer, Frank

    2014-07-01

    We develop an agent-based model of strategic link formation in Research and Development (R&D) networks. Empirical evidence has shown that the growth of these networks is driven by mechanisms which are both endogenous to the system (that is, depending on existing alliances patterns) and exogenous (that is, driven by an exploratory search for newcomer firms). Extant research to date has not investigated both mechanisms simultaneously in a comparative manner. To overcome this limitation, we develop a general modeling framework to shed light on the relative importance of these two mechanisms. We test our model against a comprehensive dataset, listing cross-country and cross-sectoral R&D alliances from 1984 to 2009. Our results show that by fitting only three macroscopic properties of the network topology, this framework is able to reproduce a number of micro-level measures, including the distributions of degree, local clustering, path length and component size, and the emergence of network clusters. Furthermore, by estimating the link probabilities towards newcomers and established firms from the data, we find that endogenous mechanisms are predominant over the exogenous ones in the network formation, thus quantifying the importance of existing structures in selecting partner firms.

  15. Statistical mechanics of attractor neural network models with synaptic depression

    International Nuclear Information System (INIS)

    Igarashi, Yasuhiko; Oizumi, Masafumi; Otsubo, Yosuke; Nagata, Kenji; Okada, Masato

    2009-01-01

    Synaptic depression is known to control gain for presynaptic inputs. Since cortical neurons receive thousands of presynaptic inputs, and their outputs are fed into thousands of other neurons, the synaptic depression should influence macroscopic properties of neural networks. We employ simple neural network models to explore the macroscopic effects of synaptic depression. Systems with the synaptic depression cannot be analyzed due to asymmetry of connections with the conventional equilibrium statistical-mechanical approach. Thus, we first propose a microscopic dynamical mean field theory. Next, we derive macroscopic steady state equations and discuss the stabilities of steady states for various types of neural network models.

  16. Modeling mechanical properties of cast aluminum alloy using artificial neural network

    International Nuclear Information System (INIS)

    Jokhio, M.H.; Panhwar, M.I.

    2009-01-01

    Modeling is widely used to investigate the mechanical properties of engineering materials due to increasing demand of low cost and high strength to weight ratio for many engineering applications. The aluminum casting alloys are cost competitive material and possess the desired properties. The mechanical properties largely depend upon composition of alloys and their processing method. Alloy design involves controlling mechanical properties via optimization of the composition and processing parameters. For optimization the possible root is empirical modeling and its more refined version is the analysis of the wide range of data using ANN (Artificial Neural Networks) modeling. The modeling of mechanical properties of the aluminum alloys are the main objective of present work. For this purpose, some data were collected and experimentally prepared using conventional casting method. A MLP (Multilayer Perceptron) network was developed, which is trained by using the error back propagation algorithm. (author)

  17. Mechanisms of Winner-Take-All and Group Selection in Neuronal Spiking Networks.

    Science.gov (United States)

    Chen, Yanqing

    2017-01-01

    A major function of central nervous systems is to discriminate different categories or types of sensory input. Neuronal networks accomplish such tasks by learning different sensory maps at several stages of neural hierarchy, such that different neurons fire selectively to reflect different internal or external patterns and states. The exact mechanisms of such map formation processes in the brain are not completely understood. Here we study the mechanism by which a simple recurrent/reentrant neuronal network accomplish group selection and discrimination to different inputs in order to generate sensory maps. We describe the conditions and mechanism of transition from a rhythmic epileptic state (in which all neurons fire synchronized and indiscriminately to any input) to a winner-take-all state in which only a subset of neurons fire for a specific input. We prove an analytic condition under which a stable bump solution and a winner-take-all state can emerge from the local recurrent excitation-inhibition interactions in a three-layer spiking network with distinct excitatory and inhibitory populations, and demonstrate the importance of surround inhibitory connection topology on the stability of dynamic patterns in spiking neural network.

  18. Identifying partial topology of complex dynamical networks via a pinning mechanism

    Science.gov (United States)

    Zhu, Shuaibing; Zhou, Jin; Lu, Jun-an

    2018-04-01

    In this paper, we study the problem of identifying the partial topology of complex dynamical networks via a pinning mechanism. By using the network synchronization theory and the adaptive feedback controlling method, we propose a method which can greatly reduce the number of nodes and observers in the response network. Particularly, this method can also identify the whole topology of complex networks. A theorem is established rigorously, from which some corollaries are also derived in order to make our method more cost-effective. Several numerical examples are provided to verify the effectiveness of the proposed method. In the simulation, an approach is also given to avoid possible identification failure caused by inner synchronization of the drive network.

  19. Diagnosis of mechanical pumping system using neural networks and system parameters analysis

    International Nuclear Information System (INIS)

    Tsai, Tai Ming; Wang, Wei Hui

    2009-01-01

    Normally, a mechanical pumping system is equipped to monitor some of the important input and output signals which are set to the prescribed values. This paper addressed dealing with these signals to establish the database of input- output relation by using a number of neural network models through learning algorithms. These signals encompass normal and abnormal running conditions. The abnormal running conditions were artificially generated. Meanwhile, for the purpose of setting up an on-line diagnosis network, the learning speed and accuracy of three kinds of networks, viz., the backpropagation (BPN), radial basis function (RBF) and adaptive linear (ADALINE) neural networks have been compared and assessed. The assessment criteria of the networks are compared with the correlation result matrix in terms of the neuron vectors. Both BPN and RBF are judged by the maximum vector based on the post-regression analysis, and the ADALINE is judged by the minimum vector based on the least mean square error analysis. By ignoring the neural network training time, it has been shown that if the mechanical diagnosis system is tackled off-line, the RBF method is suggested. However, for on-line diagnosis, the BPN method is recommended

  20. Diagnosis of mechanical pumping system using neural networks and system parameters analysis

    Energy Technology Data Exchange (ETDEWEB)

    Tsai, Tai Ming; Wang, Wei Hui [National Taiwan Ocean University, Keelung (China)

    2009-01-15

    Normally, a mechanical pumping system is equipped to monitor some of the important input and output signals which are set to the prescribed values. This paper addressed dealing with these signals to establish the database of input- output relation by using a number of neural network models through learning algorithms. These signals encompass normal and abnormal running conditions. The abnormal running conditions were artificially generated. Meanwhile, for the purpose of setting up an on-line diagnosis network, the learning speed and accuracy of three kinds of networks, viz., the backpropagation (BPN), radial basis function (RBF) and adaptive linear (ADALINE) neural networks have been compared and assessed. The assessment criteria of the networks are compared with the correlation result matrix in terms of the neuron vectors. Both BPN and RBF are judged by the maximum vector based on the post-regression analysis, and the ADALINE is judged by the minimum vector based on the least mean square error analysis. By ignoring the neural network training time, it has been shown that if the mechanical diagnosis system is tackled off-line, the RBF method is suggested. However, for on-line diagnosis, the BPN method is recommended

  1. Undermining and Strengthening Social Networks through Network Modification

    Science.gov (United States)

    Mellon, Jonathan; Yoder, Jordan; Evans, Daniel

    2016-10-01

    Social networks have well documented effects at the individual and aggregate level. Consequently it is often useful to understand how an attempt to influence a network will change its structure and consequently achieve other goals. We develop a framework for network modification that allows for arbitrary objective functions, types of modification (e.g. edge weight addition, edge weight removal, node removal, and covariate value change), and recovery mechanisms (i.e. how a network responds to interventions). The framework outlined in this paper helps both to situate the existing work on network interventions but also opens up many new possibilities for intervening in networks. In particular use two case studies to highlight the potential impact of empirically calibrating the objective function and network recovery mechanisms as well as showing how interventions beyond node removal can be optimised. First, we simulate an optimal removal of nodes from the Noordin terrorist network in order to reduce the expected number of attacks (based on empirically predicting the terrorist collaboration network from multiple types of network ties). Second, we simulate optimally strengthening ties within entrepreneurial ecosystems in six developing countries. In both cases we estimate ERGM models to simulate how a network will endogenously evolve after intervention.

  2. Networked Learning and Network Science: Potential Applications to Health Professionals' Continuing Education and Development.

    Science.gov (United States)

    Margolis, Alvaro; Parboosingh, John

    2015-01-01

    Prior interpersonal relationships and interactivity among members of professional associations may impact the learning process in continuing medical education (CME). On the other hand, CME programs that encourage interactivity between participants may impact structures and behaviors in these professional associations. With the advent of information and communication technologies, new communication spaces have emerged that have the potential to enhance networked learning in national and international professional associations and increase the effectiveness of CME for health professionals. In this article, network science, based on the application of network theory and other theories, is proposed as an approach to better understand the contribution networking and interactivity between health professionals in professional communities make to their learning and adoption of new practices over time. © 2015 The Alliance for Continuing Education in the Health Professions, the Society for Academic Continuing Medical Education, and the Council on Continuing Medical Education, Association for Hospital Medical Education.

  3. A Glider-Assisted Link Disruption Restoration Mechanism in Underwater Acoustic Sensor Networks.

    Science.gov (United States)

    Jin, Zhigang; Wang, Ning; Su, Yishan; Yang, Qiuling

    2018-02-07

    Underwater acoustic sensor networks (UASNs) have become a hot research topic. In UASNs, nodes can be affected by ocean currents and external forces, which could result in sudden link disruption. Therefore, designing a flexible and efficient link disruption restoration mechanism to ensure the network connectivity is a challenge. In the paper, we propose a glider-assisted restoration mechanism which includes link disruption recognition and related link restoring mechanism. In the link disruption recognition mechanism, the cluster heads collect the link disruption information and then schedule gliders acting as relay nodes to restore the disrupted link. Considering the glider's sawtooth motion, we design a relay location optimization algorithm with a consideration of both the glider's trajectory and acoustic channel attenuation model. The utility function is established by minimizing the channel attenuation and the optimal location of glider is solved by a multiplier method. The glider-assisted restoration mechanism can greatly improve the packet delivery rate and reduce the communication energy consumption and it is more general for the restoration of different link disruption scenarios. The simulation results show that glider-assisted restoration mechanism can improve the delivery rate of data packets by 15-33% compared with cooperative opportunistic routing (OVAR), the hop-by-hop vector-based forwarding (HH-VBF) and the vector based forward (VBF) methods, and reduce communication energy consumption by 20-58% for a typical network's setting.

  4. A Spectrum Allocation Mechanism Based on HJ-DQPSO for Cognitive Radio Networks

    Directory of Open Access Journals (Sweden)

    Zhu Jiang

    2015-11-01

    Full Text Available In cognitive radio network model consisting of secondary users and primary users, in order to solve the difficult multi-objective spectrum allocation issue about maximizing network efficiency and users’ fairness to access network, this paper proposes a new discrete multi-objective combinatorial optimization mechanism—HJ-DQPSO based on Hooke Jeeves (HJ and Quantum Particle Swarm Optimization (QPSO algorithm. The mechanism adopts HJ algorithm to local search to prevent falling into the local optimum, and proposes a discrete QPSO algorithm to match the discrete spectrum assignment model. The mechanism has the advantages of approximating optimal solution, rapid convergence, less parameters, avoiding falling into local optimum. Compared with existing spectrum assignment algorithms, the simulation results show that according to different optimization objectives, the HJ-DQPSO optimization mechanism for multi-objective optimization can better approximate optimal solution and converge fast. We can obtain a reasonable spectrum allocation scheme in the case of satisfying multiple optimization objectives.

  5. Performance Analysis of Congestion Control Mechanism in Software Defined Network (SDN

    Directory of Open Access Journals (Sweden)

    Rahman M. Z. A.

    2017-01-01

    Full Text Available In the near future, the traditional networks architecture will be difficult to be managed. Hence, Software Defined Network (SDN will be an alternative in the future of programmable networks to replace the conventional network architecture. The main idea of SDN architecture is to separate the forwarding plane and control plane of network system, where network operators can program packet forwarding behaviour to improve the network performance. Congestion control is important mechanism for network traffic to improve network capability and achieve high end Quality of Service (QoS. In this paper, extensive simulation is conducted to analyse the performance of SDN by implementing Link Layer Discovery Protocol (LLDP under congested network. The simulation was conducted on Mininet by creating four different fanout and the result was analysed based on differences of matrix performance. As a result, the packet loss and throughput reduction were observed when number of fanout in the topology was increased. By using LLDP protocol, huge reduction in packet loss rate has been achieved while maximizing percentage packet delivery ratio.

  6. Modeling Irrigation Networks for the Quantification of Potential Energy Recovering: A Case Study

    Directory of Open Access Journals (Sweden)

    Modesto Pérez-Sánchez

    2016-06-01

    Full Text Available Water irrigation systems are required to provide adequate pressure levels in any sort of network. Quite frequently, this requirement is achieved by using pressure reducing valves (PRVs. Nevertheless, the possibility of using hydraulic machines to recover energy instead of PRVs could reduce the energy footprint of the whole system. In this research, a new methodology is proposed to help water managers quantify the potential energy recovering of an irrigation water network with adequate conditions of topographies distribution. EPANET has been used to create a model based on probabilities of irrigation and flow distribution in real networks. Knowledge of the flows and pressures in the network is necessary to perform an analysis of economic viability. Using the proposed methodology, a case study has been analyzed in a typical Mediterranean region and the potential available energy has been estimated. The study quantifies the theoretical energy recoverable if hydraulic machines were installed in the network. Particularly, the maximum energy potentially recovered in the system has been estimated up to 188.23 MWh/year with a potential saving of non-renewable energy resources (coal and gas of CO2 137.4 t/year.

  7. Peer pressure and incentive mechanisms in social networks

    Science.gov (United States)

    Deng, Chuang; Ye, Chao; Wang, Lin; Rong, Zhihai; Wang, Xiaofan

    2018-01-01

    Cooperation can be viewed as a social norm that is expected in our society. In this work, a framework based on spatial public goods game theory is established to study how peer pressure and incentive mechanisms can influence the evolution of cooperation. A unified model with adjustable parameters is developed to represent the effects of pure Personal Mechanism, Personal Mechanism with peer pressure and Social Mechanism, which demonstrates that when the sum of rewards plus the peer pressure felt by defectors is larger than the effective cost of cooperation, cooperation can prevail. As the peer pressure is caused by other cooperators in a game, group size and network structure play an important role. In particular, larger group size and more heterogeneous structured population can make defectors feel more peer pressure, which will promote the evolution and sustainment of cooperation.

  8. Communication: Fitting potential energy surfaces with fundamental invariant neural network

    Energy Technology Data Exchange (ETDEWEB)

    Shao, Kejie; Chen, Jun; Zhao, Zhiqiang; Zhang, Dong H., E-mail: zhangdh@dicp.ac.cn [State Key Laboratory of Molecular Reaction Dynamics and Center for Theoretical Computational Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, People’s Republic of China and University of Chinese Academy of Sciences, Beijing 100049, People’s Republic of China. (China)

    2016-08-21

    A more flexible neural network (NN) method using the fundamental invariants (FIs) as the input vector is proposed in the construction of potential energy surfaces for molecular systems involving identical atoms. Mathematically, FIs finitely generate the permutation invariant polynomial (PIP) ring. In combination with NN, fundamental invariant neural network (FI-NN) can approximate any function to arbitrary accuracy. Because FI-NN minimizes the size of input permutation invariant polynomials, it can efficiently reduce the evaluation time of potential energy, in particular for polyatomic systems. In this work, we provide the FIs for all possible molecular systems up to five atoms. Potential energy surfaces for OH{sub 3} and CH{sub 4} were constructed with FI-NN, with the accuracy confirmed by full-dimensional quantum dynamic scattering and bound state calculations.

  9. Hydrogen bond networks determine emergent mechanical and thermodynamic properties across a protein family

    Directory of Open Access Journals (Sweden)

    Dallakyan Sargis

    2008-08-01

    Full Text Available Abstract Background Gram-negative bacteria use periplasmic-binding proteins (bPBP to transport nutrients through the periplasm. Despite immense diversity within the recognized substrates, all members of the family share a common fold that includes two domains that are separated by a conserved hinge. The hinge allows the protein to cycle between open (apo and closed (ligated conformations. Conformational changes within the proteins depend on a complex interplay of mechanical and thermodynamic response, which is manifested as an increase in thermal stability and decrease of flexibility upon ligand binding. Results We use a distance constraint model (DCM to quantify the give and take between thermodynamic stability and mechanical flexibility across the bPBP family. Quantitative stability/flexibility relationships (QSFR are readily evaluated because the DCM links mechanical and thermodynamic properties. We have previously demonstrated that QSFR is moderately conserved across a mesophilic/thermophilic RNase H pair, whereas the observed variance indicated that different enthalpy-entropy mechanisms allow similar mechanical response at their respective melting temperatures. Our predictions of heat capacity and free energy show marked diversity across the bPBP family. While backbone flexibility metrics are mostly conserved, cooperativity correlation (long-range couplings also demonstrate considerable amount of variation. Upon ligand removal, heat capacity, melting point, and mechanical rigidity are, as expected, lowered. Nevertheless, significant differences are found in molecular cooperativity correlations that can be explained by the detailed nature of the hydrogen bond network. Conclusion Non-trivial mechanical and thermodynamic variation across the family is explained by differences within the underlying H-bond networks. The mechanism is simple; variation within the H-bond networks result in altered mechanical linkage properties that directly affect

  10. The mechanism of selective molecular capture in carbon nanotube networks.

    Science.gov (United States)

    Wan, Yu; Guan, Jun; Yang, Xudong; Zheng, Quanshui; Xu, Zhiping

    2014-07-28

    Recently, air pollution issues have drawn significant attention to the development of efficient air filters, and one of the most promising materials for this purpose is nanofibers. We explore here the mechanism of selective molecular capture of volatile organic compounds in carbon nanotube networks by performing atomistic simulations. The results are discussed with respect to the two key parameters that define the performance of nanofiltration, i.e. the capture efficiency and flow resistance, which demonstrate the advantages of carbon nanotube networks with high surface-to-volume ratio and atomistically smooth surfaces. We also reveal the important roles of interfacial adhesion and diffusion that govern selective gas transport through the network.

  11. Radial basis function (RBF) neural network control for mechanical systems design, analysis and Matlab simulation

    CERN Document Server

    Liu, Jinkun

    2013-01-01

    Radial Basis Function (RBF) Neural Network Control for Mechanical Systems is motivated by the need for systematic design approaches to stable adaptive control system design using neural network approximation-based techniques. The main objectives of the book are to introduce the concrete design methods and MATLAB simulation of stable adaptive RBF neural control strategies. In this book, a broad range of implementable neural network control design methods for mechanical systems are presented, such as robot manipulators, inverted pendulums, single link flexible joint robots, motors, etc. Advanced neural network controller design methods and their stability analysis are explored. The book provides readers with the fundamentals of neural network control system design.   This book is intended for the researchers in the fields of neural adaptive control, mechanical systems, Matlab simulation, engineering design, robotics and automation. Jinkun Liu is a professor at Beijing University of Aeronautics and Astronauti...

  12. A Reliable Handoff Mechanism for Mobile Industrial Wireless Sensor Networks.

    Science.gov (United States)

    Ma, Jian; Yang, Dong; Zhang, Hongke; Gidlund, Mikael

    2017-08-04

    With the prevalence of low-power wireless devices in industrial applications, concerns about timeliness and reliability are bound to continue despite the best efforts of researchers to design Industrial Wireless Sensor Networks (IWSNs) to improve the performance of monitoring and control systems. As mobile devices have a major role to play in industrial production, IWSNs should support mobility. However, research on mobile IWSNs and practical tests have been limited due to the complicated resource scheduling and rescheduling compared with traditional wireless sensor networks. This paper proposes an effective mechanism to guarantee the performance of handoff, including a mobility-aware scheme, temporary connection and quick registration. The main contribution of this paper is that the proposed mechanism is implemented not only in our testbed but in a real industrial environment. The results indicate that our mechanism not only improves the accuracy of handoff triggering, but also solves the problem of ping-pong effect during handoff. Compared with the WirelessHART standard and the RSSI-based approach, our mechanism facilitates real-time communication while being more reliable, which can help end-to-end packet delivery remain an average of 98.5% in the scenario of mobile IWSNs.

  13. Mechanisms and neuronal networks involved in reactive and proactive cognitive control of interference in working memory.

    Science.gov (United States)

    Irlbacher, Kerstin; Kraft, Antje; Kehrer, Stefanie; Brandt, Stephan A

    2014-10-01

    Cognitive control can be reactive or proactive in nature. Reactive control mechanisms, which support the resolution of interference, start after its onset. Conversely, proactive control involves the anticipation and prevention of interference prior to its occurrence. The interrelation of both types of cognitive control is currently under debate: Are they mediated by different neuronal networks? Or are there neuronal structures that have the potential to act in a proactive as well as in a reactive manner? This review illustrates the way in which integrating knowledge gathered from behavioral studies, functional imaging, and human electroencephalography proves useful in answering these questions. We focus on studies that investigate interference resolution at the level of working memory representations. In summary, different mechanisms are instrumental in supporting reactive and proactive control. Distinct neuronal networks are involved, though some brain regions, especially pre-SMA, possess functions that are relevant to both control modes. Therefore, activation of these brain areas could be observed in reactive, as well as proactive control, but at different times during information processing. Copyright © 2014 Elsevier Ltd. All rights reserved.

  14. Computation and Communication Evaluation of an Authentication Mechanism for Time-Triggered Networked Control Systems

    Science.gov (United States)

    Martins, Goncalo; Moondra, Arul; Dubey, Abhishek; Bhattacharjee, Anirban; Koutsoukos, Xenofon D.

    2016-01-01

    In modern networked control applications, confidentiality and integrity are important features to address in order to prevent against attacks. Moreover, network control systems are a fundamental part of the communication components of current cyber-physical systems (e.g., automotive communications). Many networked control systems employ Time-Triggered (TT) architectures that provide mechanisms enabling the exchange of precise and synchronous messages. TT systems have computation and communication constraints, and with the aim to enable secure communications in the network, it is important to evaluate the computational and communication overhead of implementing secure communication mechanisms. This paper presents a comprehensive analysis and evaluation of the effects of adding a Hash-based Message Authentication (HMAC) to TT networked control systems. The contributions of the paper include (1) the analysis and experimental validation of the communication overhead, as well as a scalability analysis that utilizes the experimental result for both wired and wireless platforms and (2) an experimental evaluation of the computational overhead of HMAC based on a kernel-level Linux implementation. An automotive application is used as an example, and the results show that it is feasible to implement a secure communication mechanism without interfering with the existing automotive controller execution times. The methods and results of the paper can be used for evaluating the performance impact of security mechanisms and, thus, for the design of secure wired and wireless TT networked control systems. PMID:27463718

  15. Incentive Mechanism for P2P Content Sharing over Heterogenous Access Networks

    Science.gov (United States)

    Sato, Kenichiro; Hashimoto, Ryo; Yoshino, Makoto; Shinkuma, Ryoichi; Takahashi, Tatsuro

    In peer-to-peer (P2P) content sharing, users can share their content by contributing their own resources to one another. However, since there is no incentive for contributing contents or resources to others, users may attempt to obtain content without any contribution. To motivate users to contribute their resources to the service, incentive-rewarding mechanisms have been proposed. On the other hand, emerging wireless technologies, such as IEEE 802.11 wireless local area networks, beyond third generation (B3G) cellular networks and mobile WiMAX, provide high-speed Internet access for wireless users. Using these high-speed wireless access, wireless users can use P2P services and share their content with other wireless users and with fixed users. However, this diversification of access networks makes it difficult to appropriately assign rewards to each user according to their contributions. This is because the cost necessary for contribution is different in different access networks. In this paper, we propose a novel incentive-rewarding mechanism called EMOTIVER that can assign rewards to users appropriately. The proposed mechanism uses an external evaluator and interactive learning agents. We also investigate a way of appropriately controlling rewards based on the system service's quality and managing policy.

  16. Disentangling the Attention Network Test: Behavioral, Event Related Potentials and neural source analyses.

    Directory of Open Access Journals (Sweden)

    Alejandro eGalvao-Carmona

    2014-10-01

    Full Text Available Background. The study of the attentional system remains a challenge for current neuroscience. The Attention Network Test (ANT was designed to study simultaneously three different attentional networks (alerting, orienting and executive based in subtraction of different experimental conditions. However, some studies recommend caution with these calculations due to the interactions between the attentional networks. In particular, it is highly relevant that several interpretations about attentional impairment have arisen from these calculations in diverse pathologies. Event Related Potentials (ERPs and neural source analysis can be applied to disentangle the relationships between these attentional networks not specifically shown by behavioural measures. Results. This study shows that there is a basic level of alerting (tonic alerting in the no cue condition, represented by a slow negative trend in the ERP trace prior to the onset of the target stimuli. A progressive increase in the CNV amplitude related to the amount of information provided by the cue conditions is also shown. Neural source analysis reveals specific modulations of the CNV related to a task-related expectancy presented in the no cue condition; a late modulation triggered by the central cue condition and probably representing a generic motor preparation; and an early and late modulation for spatial cue condition suggesting specific motor and sensory preactivation. Finally, the first component in the information processing of the target stimuli modulated by the interaction between orienting network and the executive system can be represented by N1. Conclusions. The ANT is useful as a paradigm to study specific attentional mechanisms and their interactions. However, calculation of network effects is based in subtractions with non-comparable experimental conditions, as evidenced by the present data, which can induce misinterpretations in the study of the attentional capacity in human

  17. Dissecting the Molecular Mechanisms of Neurodegenerative Diseases through Network Biology

    Directory of Open Access Journals (Sweden)

    Jose A. Santiago

    2017-05-01

    Full Text Available Neurodegenerative diseases are rarely caused by a mutation in a single gene but rather influenced by a combination of genetic, epigenetic and environmental factors. Emerging high-throughput technologies such as RNA sequencing have been instrumental in deciphering the molecular landscape of neurodegenerative diseases, however, the interpretation of such large amounts of data remains a challenge. Network biology has become a powerful platform to integrate multiple omics data to comprehensively explore the molecular networks in the context of health and disease. In this review article, we highlight recent advances in network biology approaches with an emphasis in brain-networks that have provided insights into the molecular mechanisms leading to the most prevalent neurodegenerative diseases including Alzheimer’s (AD, Parkinson’s (PD and Huntington’s diseases (HD. We discuss how integrative approaches using multi-omics data from different tissues have been valuable for identifying biomarkers and therapeutic targets. In addition, we discuss the challenges the field of network medicine faces toward the translation of network-based findings into clinically actionable tools for personalized medicine applications.

  18. An autonomous recovery mechanism against optical distribution network failures in EPON

    Science.gov (United States)

    Liem, Andrew Tanny; Hwang, I.-Shyan; Nikoukar, AliAkbar

    2014-10-01

    Ethernet Passive Optical Network (EPON) is chosen for servicing diverse applications with higher bandwidth and Quality-of-Service (QoS), starting from Fiber-To-The-Home (FTTH), FTTB (business/building) and FTTO (office). Typically, a single OLT can provide services to both residential and business customers on the same Optical Line Terminal (OLT) port; thus, any failures in the system will cause a great loss for both network operators and customers. Network operators are looking for low-cost and high service availability mechanisms that focus on the failures that occur within the drop fiber section because the majority of faults are in this particular section. Therefore, in this paper, we propose an autonomous recovery mechanism that provides protection and recovery against Drop Distribution Fiber (DDF) link faults or transceiver failure at the ONU(s) in EPON systems. In the proposed mechanism, the ONU can automatically detect any signal anomalies in the physical layer or transceiver failure, switching the working line to the protection line and sending the critical event alarm to OLT via its neighbor. Each ONU has a protection line, which is connected to the nearest neighbor ONU, and therefore, when failure occurs, the ONU can still transmit and receive data via the neighbor ONU. Lastly, the Fault Dynamic Bandwidth Allocation for recovery mechanism is presented. Simulation results show that our proposed autonomous recovery mechanism is able to maintain the overall QoS performance in terms of mean packet delay, system throughput, packet loss and EF jitter.

  19. Changes in event-related potential functional networks predict traumatic brain injury in piglets.

    Science.gov (United States)

    Atlan, Lorre S; Lan, Ingrid S; Smith, Colin; Margulies, Susan S

    2018-06-01

    Traumatic brain injury is a leading cause of cognitive and behavioral deficits in children in the US each year. None of the current diagnostic tools, such as quantitative cognitive and balance tests, have been validated to identify mild traumatic brain injury in infants, adults and animals. In this preliminary study, we report a novel, quantitative tool that has the potential to quickly and reliably diagnose traumatic brain injury and which can track the state of the brain during recovery across multiple ages and species. Using 32 scalp electrodes, we recorded involuntary auditory event-related potentials from 22 awake four-week-old piglets one day before and one, four, and seven days after two different injury types (diffuse and focal) or sham. From these recordings, we generated event-related potential functional networks and assessed whether the patterns of the observed changes in these networks could distinguish brain-injured piglets from non-injured. Piglet brains exhibited significant changes after injury, as evaluated by five network metrics. The injury prediction algorithm developed from our analysis of the changes in the event-related potentials functional networks ultimately produced a tool with 82% predictive accuracy. This novel approach is the first application of auditory event-related potential functional networks to the prediction of traumatic brain injury. The resulting tool is a robust, objective and predictive method that offers promise for detecting mild traumatic brain injury, in particular because collecting event-related potentials data is noninvasive and inexpensive. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

  20. Location-based restoration mechanism for multi-domain GMPLS networks

    DEFF Research Database (Denmark)

    Manolova, Anna Vasileva; Calle, Eusibi; Ruepp, Sarah Renée

    2009-01-01

    In this paper we propose and evaluate the efficiency of a location-based restoration mechanism in a dynamic multi-domain GMPLS network. We focus on inter-domain link failures and utilize the correlation between the actual position of a failed link along the path with the applied restoration...

  1. A mechanical wave system to show waveforms similar to quantum mechanical wavefunctions in a potential

    International Nuclear Information System (INIS)

    Faletič, Sergej

    2015-01-01

    Interviews with students suggest that even though they understand the formalism and the formal nature of quantum theory, they still often desire a mental picture of what the equations describe and some tangible experience with the wavefunctions. Here we discuss a mechanical wave system capable of reproducing correctly a mechanical equivalent of a quantum system in a potential, and the resulting waveforms in principle of any form. We have successfully reproduced the finite potential well, the potential barrier and the parabolic potential. We believe that these mechanical waveforms can provide a valuable experience base for introductory students to start from. We aim to show that mechanical systems that are described with the same mathematics as quantum mechanical, indeed behave in the same way. We believe that even if treated purely as a wave phenomenon, the system provides much insight into wave mechanics. This can be especially useful for physics teachers and others who often need to resort to concepts and experience rather than mathematics when explaining physical phenomena. (paper)

  2. Hybrid Scheme for Modeling Local Field Potentials from Point-Neuron Networks

    DEFF Research Database (Denmark)

    Hagen, Espen; Dahmen, David; Stavrinou, Maria L

    2016-01-01

    on populations of network-equivalent multicompartment neuron models with layer-specific synaptic connectivity, can be used with an arbitrary number of point-neuron network populations, and allows for a full separation of simulated network dynamics and LFPs. We apply the scheme to a full-scale cortical network......With rapidly advancing multi-electrode recording technology, the local field potential (LFP) has again become a popular measure of neuronal activity in both research and clinical applications. Proper understanding of the LFP requires detailed mathematical modeling incorporating the anatomical...... and electrophysiological features of neurons near the recording electrode, as well as synaptic inputs from the entire network. Here we propose a hybrid modeling scheme combining efficient point-neuron network models with biophysical principles underlying LFP generation by real neurons. The LFP predictions rely...

  3. Mechanisms of Plastic Deformation in Collagen Networks Induced by Cellular Forces.

    Science.gov (United States)

    Ban, Ehsan; Franklin, J Matthew; Nam, Sungmin; Smith, Lucas R; Wang, Hailong; Wells, Rebecca G; Chaudhuri, Ovijit; Liphardt, Jan T; Shenoy, Vivek B

    2018-01-23

    Contractile cells can reorganize fibrous extracellular matrices and form dense tracts of fibers between neighboring cells. These tracts guide the development of tubular tissue structures and provide paths for the invasion of cancer cells. Here, we studied the mechanisms of the mechanical plasticity of collagen tracts formed by contractile premalignant acinar cells and fibroblasts. Using fluorescence microscopy and second harmonic generation, we quantified the collagen densification, fiber alignment, and strains that remain within the tracts after cellular forces are abolished. We explained these observations using a theoretical fiber network model that accounts for the stretch-dependent formation of weak cross-links between nearby fibers. We tested the predictions of our model using shear rheology experiments. Both our model and rheological experiments demonstrated that increasing collagen concentration leads to substantial increases in plasticity. We also considered the effect of permanent elongation of fibers on network plasticity and derived a phase diagram that classifies the dominant mechanisms of plasticity based on the rate and magnitude of deformation and the mechanical properties of individual fibers. Plasticity is caused by the formation of new cross-links if moderate strains are applied at small rates or due to permanent fiber elongation if large strains are applied over short periods. Finally, we developed a coarse-grained model for plastic deformation of collagen networks that can be employed to simulate multicellular interactions in processes such as morphogenesis, cancer invasion, and fibrosis. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  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. A New Ticket-Based Authentication Mechanism for Fast Handover in Mesh Network

    Science.gov (United States)

    Lai, Yan-Ming; Cheng, Pu-Jen; Lee, Cheng-Chi; Ku, Chia-Yi

    2016-01-01

    Due to the ever-growing popularity mobile devices of various kinds have received worldwide, the demands on large-scale wireless network infrastructure development and enhancement have been rapidly swelling in recent years. A mobile device holder can get online at a wireless network access point, which covers a limited area. When the client leaves the access point, there will be a temporary disconnection until he/she enters the coverage of another access point. Even when the coverages of two neighboring access points overlap, there is still work to do to make the wireless connection smoothly continue. The action of one wireless network access point passing a client to another access point is referred to as the handover. During handover, for security concerns, the client and the new access point should perform mutual authentication before any Internet access service is practically gained/provided. If the handover protocol is inefficient, in some cases discontinued Internet service will happen. In 2013, Li et al. proposed a fast handover authentication mechanism for wireless mesh network (WMN) based on tickets. Unfortunately, Li et al.’s work came with some weaknesses. For one thing, some sensitive information such as the time and date of expiration is sent in plaintext, which increases security risks. For another, Li et al.’s protocol includes the use of high-quality tamper-proof devices (TPDs), and this unreasonably high equipment requirement limits its applicability. In this paper, we shall propose a new efficient handover authentication mechanism. The new mechanism offers a higher level of security on a more scalable ground with the client’s privacy better preserved. The results of our performance analysis suggest that our new mechanism is superior to some similar mechanisms in terms of authentication delay. PMID:27171160

  6. A New Ticket-Based Authentication Mechanism for Fast Handover in Mesh Network.

    Directory of Open Access Journals (Sweden)

    Yan-Ming Lai

    Full Text Available Due to the ever-growing popularity mobile devices of various kinds have received worldwide, the demands on large-scale wireless network infrastructure development and enhancement have been rapidly swelling in recent years. A mobile device holder can get online at a wireless network access point, which covers a limited area. When the client leaves the access point, there will be a temporary disconnection until he/she enters the coverage of another access point. Even when the coverages of two neighboring access points overlap, there is still work to do to make the wireless connection smoothly continue. The action of one wireless network access point passing a client to another access point is referred to as the handover. During handover, for security concerns, the client and the new access point should perform mutual authentication before any Internet access service is practically gained/provided. If the handover protocol is inefficient, in some cases discontinued Internet service will happen. In 2013, Li et al. proposed a fast handover authentication mechanism for wireless mesh network (WMN based on tickets. Unfortunately, Li et al.'s work came with some weaknesses. For one thing, some sensitive information such as the time and date of expiration is sent in plaintext, which increases security risks. For another, Li et al.'s protocol includes the use of high-quality tamper-proof devices (TPDs, and this unreasonably high equipment requirement limits its applicability. In this paper, we shall propose a new efficient handover authentication mechanism. The new mechanism offers a higher level of security on a more scalable ground with the client's privacy better preserved. The results of our performance analysis suggest that our new mechanism is superior to some similar mechanisms in terms of authentication delay.

  7. Thermo-Mechanical Properties of Semi-Degradable Poly(β-amino ester)-co-Methyl Methacrylate Networks under Simulated Physiological Conditions

    Science.gov (United States)

    Safranski, David L.; Crabtree, Jacob C.; Huq, Yameen R.; Gall, Ken

    2011-01-01

    Poly(β-amino ester) networks are being explored for biomedical applications, but they may lack the mechanical properties necessary for long term implantation. The objective of this study is to evaluate the effect of adding methyl methacrylate on networks' mechanical properties under simulated physiological conditions. The networks were synthesized in two parts: (1) a biodegradable crosslinker was formed from a diacrylate and amine, (2) and then varying concentrations of methyl methacrylate were added prior to photopolymerizing the network. Degradation rate, mechanical properties, and glass transition temperature were studied as a function of methyl methacrylate composition. The crosslinking density played a limited role on mechanical properties for these networks, but increasing methyl methacrylate concentration improved the toughness by several orders of magnitude. Under simulated physiological conditions, networks showed increasing toughness or sustained toughness as degradation occurred. This work establishes a method of creating degradable networks with tailorable toughness while undergoing partial degradation. PMID:21966028

  8. Digging into construction: social networks and their potential impact on knowledge transfer.

    Science.gov (United States)

    Carlan, N A; Kramer, D M; Bigelow, P; Wells, R; Garritano, E; Vi, P

    2012-01-01

    A six-year study is exploring the most effective ways to disseminate ideas to reduce musculoskeletal disorders (MSDs) in the construction sector. The sector was targeted because MSDs account for 35% of all lost time injuries. This paper reports on the organization of the construction sector, and maps potential pathways of communication, including social networks, to set the stage for future dissemination. The managers, health and safety specialists, union health and safety representatives, and 28 workers from small, medium and large construction companies participated. Over a three-year period, data were collected from 47 qualitative interviews. Questions were guided by the PARIHS (Promoting Action on Research Implementation in Health Services) knowledge-transfer conceptual framework and adapted for the construction sector. The construction sector is a complex and dynamic sector, with non-linear reporting relationships, and divided and diluted responsibilities. Four networks were identified that can potentially facilitate the dissemination of new knowledge: worksite-project networks; union networks; apprenticeship program networks; and networks established by the Construction Safety Association/Infrastructure Health and Safety Association. Flexible and multi-directional lines of communication must be used in this complex environment. This has implications for the future choice of knowledge transfer strategies.

  9. A dynamic allocation mechanism of delivering capacity in coupled networks

    International Nuclear Information System (INIS)

    Du, Wen-Bo; Zhou, Xing-Lian; Zhu, Yan-Bo; Zheng, Zheng

    2015-01-01

    Traffic process is ubiquitous in many critical infrastructures. In this paper, we introduce a mechanism to dynamically allocate the delivering capacity into the data-packet traffic model on the coupled Internet autonomous-system-level network of South Korea and Japan, and focus on its effect on the transport efficiency. In this mechanism, the total delivering capacity is constant and the lowest-load node will give one unit delivering capacity to the highest-load node at each time step. It is found that the delivering capacity of busy nodes and non-busy nodes can be well balanced and the effective betweenness of busy nodes with interconnections is significantly reduced. Consequently, the transport efficiency such as average traveling time and packet arrival rate is remarkably improved. Our work may shed some light on the traffic dynamics in coupled networks.

  10. Adaptation of coordination mechanisms to network structures

    Directory of Open Access Journals (Sweden)

    Herwig Mittermayer

    2008-12-01

    Full Text Available The coordination efficiency of Supply Chain Management is determined by two opposite poles: benefit from improved planning results and associated coordination cost. The centralization grade, applied coordination mechanisms and IT support have influence on both categories. Therefore three reference types are developed and subsequently detailed in business process models for different network structures. In a simulation study the performance of these organization forms are compared in a process plant network. Coordination benefit is observed if the planning mode is altered by means of a demand planning IT tool. Coordination cost is divided into structural and activity-dependent cost. The activity level rises when reactive planning iterations become necessary as a consequence of inconsistencies among planning levels. Some characteristic influence factors are considered to be a reason for uninfeasible planning. In this study the effect of capacity availability and stochastic machine downtimes is investigated in an uncertain demand situation. Results that if the network runs with high overcapacity, central planning is less likely to increase benefit enough to outweigh associated cost. Otherwise, if capacity constraints are crucial, a central planning mode is recommendable. When also unforeseen machine downtimes are low, the use of sophisticated IT tools is most profitable.

  11. Multi-agent Negotiation Mechanisms for Statistical Target Classification in Wireless Multimedia Sensor Networks

    Science.gov (United States)

    Wang, Xue; Bi, Dao-wei; Ding, Liang; Wang, Sheng

    2007-01-01

    The recent availability of low cost and miniaturized hardware has allowed wireless sensor networks (WSNs) to retrieve audio and video data in real world applications, which has fostered the development of wireless multimedia sensor networks (WMSNs). Resource constraints and challenging multimedia data volume make development of efficient algorithms to perform in-network processing of multimedia contents imperative. This paper proposes solving problems in the domain of WMSNs from the perspective of multi-agent systems. The multi-agent framework enables flexible network configuration and efficient collaborative in-network processing. The focus is placed on target classification in WMSNs where audio information is retrieved by microphones. To deal with the uncertainties related to audio information retrieval, the statistical approaches of power spectral density estimates, principal component analysis and Gaussian process classification are employed. A multi-agent negotiation mechanism is specially developed to efficiently utilize limited resources and simultaneously enhance classification accuracy and reliability. The negotiation is composed of two phases, where an auction based approach is first exploited to allocate the classification task among the agents and then individual agent decisions are combined by the committee decision mechanism. Simulation experiments with real world data are conducted and the results show that the proposed statistical approaches and negotiation mechanism not only reduce memory and computation requirements in WMSNs but also significantly enhance classification accuracy and reliability. PMID:28903223

  12. A novel communication mechanism based on node potential multi-path routing

    Science.gov (United States)

    Bu, Youjun; Zhang, Chuanhao; Jiang, YiMing; Zhang, Zhen

    2016-10-01

    With the network scales rapidly and new network applications emerge frequently, bandwidth supply for today's Internet could not catch up with the rapid increasing requirements. Unfortunately, irrational using of network sources makes things worse. Actual network deploys single-next-hop optimization paths for data transmission, but such "best effort" model leads to the imbalance use of network resources and usually leads to local congestion. On the other hand Multi-path routing can use the aggregation bandwidth of multi paths efficiently and improve the robustness of network, security, load balancing and quality of service. As a result, multi-path has attracted much attention in the routing and switching research fields and many important ideas and solutions have been proposed. This paper focuses on implementing the parallel transmission of multi next-hop data, balancing the network traffic and reducing the congestion. It aimed at exploring the key technologies of the multi-path communication network, which could provide a feasible academic support for subsequent applications of multi-path communication networking. It proposed a novel multi-path algorithm based on node potential in the network. And the algorithm can fully use of the network link resource and effectively balance network link resource utilization.

  13. Statistical mechanics of polymer networks of any topology

    International Nuclear Information System (INIS)

    Duplantier, B.

    1989-01-01

    The statistical mechanics is considered of any polymer network with a prescribed topology, in dimension d, which was introduced previously. The basic direct renormalization theory of the associated continuum model is established. It has a very simple multiplicative structure in terms of the partition functions of the star polymers constituting the vertices of the network. A calculation is made to O(ε 2 ), where d = 4 -ε, of the basic critical dimensions σ L associated with any L=leg vertex (L ≥ 1). From this infinite series of critical exponents, any topology-dependent critical exponent can be derived. This is applied to the configuration exponent γ G of any network G to O(ε 2 ), including L-leg star polymers. The infinite sets of contact critical exponents θ between multiple points of polymers or between the cores of several star polymers are also deduced. As a particular case, the three exponents θ 0 , θ 1 , θ 2 calculated by des Cloizeaux by field-theoretic methods are recovered. The limiting exact logarithmic laws are derived at the upper critical dimension d = 4. The results are generalized to the series of topological exponents of polymer networks near a surface and of tricritical polymers at the Θ-point. Intersection properties of networks of random walks can be studied similarly. The above factorization theory of the partition function of any polymer network over its constituting L-vertices also applies to two dimensions, where it can be related to conformal invariance. The basic critical exponents σ L and thus any topological polymer exponents are then exactly known. Principal results published elsewhere are recalled

  14. Trust Building Mechanisms for Electronic Business Networks and Their Relation to eSkills

    OpenAIRE

    Radoslav Delina; Michal Tkáč

    2010-01-01

    Globalization, supported by information and communication technologies, changes the rules of competitiveness and increases the significance of information, knowledge and network cooperation. In line with this trend, the need for efficient trust-building tools has emerged. The absence of trust building mechanisms and strategies was identified within several studies. Through trust development, participation on e-business network and usage of network services will increase a...

  15. QOS-aware error recovery in wireless body sensor networks using adaptive network coding.

    Science.gov (United States)

    Razzaque, Mohammad Abdur; Javadi, Saeideh S; Coulibaly, Yahaya; Hira, Muta Tah

    2014-12-29

    Wireless body sensor networks (WBSNs) for healthcare and medical applications are real-time and life-critical infrastructures, which require a strict guarantee of quality of service (QoS), in terms of latency, error rate and reliability. Considering the criticality of healthcare and medical applications, WBSNs need to fulfill users/applications and the corresponding network's QoS requirements. For instance, for a real-time application to support on-time data delivery, a WBSN needs to guarantee a constrained delay at the network level. A network coding-based error recovery mechanism is an emerging mechanism that can be used in these systems to support QoS at very low energy, memory and hardware cost. However, in dynamic network environments and user requirements, the original non-adaptive version of network coding fails to support some of the network and user QoS requirements. This work explores the QoS requirements of WBSNs in both perspectives of QoS. Based on these requirements, this paper proposes an adaptive network coding-based, QoS-aware error recovery mechanism for WBSNs. It utilizes network-level and user-/application-level information to make it adaptive in both contexts. Thus, it provides improved QoS support adaptively in terms of reliability, energy efficiency and delay. Simulation results show the potential of the proposed mechanism in terms of adaptability, reliability, real-time data delivery and network lifetime compared to its counterparts.

  16. Composite mechanisms for improving Bubble Rap in delay tolerant networks

    Directory of Open Access Journals (Sweden)

    Sweta Jain

    2014-01-01

    Full Text Available Delay tolerant networks (DTNs are a subset of mobile ad hoc networks where connections are sparse and intermittent. This often results in a network graph which is rarely connected which introduces a challenge in message forwarding because of a lack of end-to-end connectivity towards the destination. Recently, social-based forwarding algorithms are gaining popularity because of the social nature displayed by the node movements in a DTN, especially in application areas like the pocket switched networks. The social-based metrics like community, similarity, centrality etc. are used to determine the carrier to which a node has to forward its message. Composite methods are used to improve the performance of Bubble Rap social-based forwarding algorithm. In the proposed mechanism, a new social metric termed ‘friendship’ has been introduced along with a time-to-live (TTL-based ‘threshold’ and acknowledgement (ACK IDs. Real trace data and working day movement models are used for simulations in the opportunistic network environment simulator to demonstrate that the proposed algorithm gives better delivery ratio than the original Bubble Rap algorithm.

  17. Neural networks and their potential application in nuclear power plants

    International Nuclear Information System (INIS)

    Uhrig, R.E.

    1991-01-01

    A neural network is a data processing system consisting of a number of simple, highly interconnected processing elements in an architecture inspired by the structure of the cerebral cortex portion of the brain. Hence, neural networks are often capable of doing things which humans or animals do well but which conventional computers often do poorly. Neural networks have emerged in the past few years as an area of unusual opportunity for research, development and application to a variety of real world problems. Indeed, neural networks exhibit characteristics and capabilities not provided by any other technology. Examples include reading Japanese Kanji characters and human handwriting, reading a typewritten manuscript aloud, compensating for alignment errors in robots, interpreting very noise signals (e.g., electroencephalograms), modeling complex systems that cannot be modeled mathematically, and predicting whether proposed loans will be good or fail. This paper presents a brief tutorial on neural networks and describes research on the potential applications to nuclear power plants

  18. Comparing Existing Pipeline Networks with the Potential Scale of Future U.S. CO2 Pipeline Networks

    Energy Technology Data Exchange (ETDEWEB)

    Dooley, James J.; Dahowski, Robert T.; Davidson, Casie L.

    2008-02-29

    There is growing interest regarding the potential size of a future U.S. dedicated CO2 pipeline infrastructure if carbon dioxide capture and storage (CCS) technologies are commercially deployed on a large scale. In trying to understand the potential scale of a future national CO2 pipeline network, comparisons are often made to the existing pipeline networks used to deliver natural gas and liquid hydrocarbons to markets within the U.S. This paper assesses the potential scale of the CO2 pipeline system needed under two hypothetical climate policies and compares this to the extant U.S. pipeline infrastructures used to deliver CO2 for enhanced oil recovery (EOR), and to move natural gas and liquid hydrocarbons from areas of production and importation to markets. The data presented here suggest that the need to increase the size of the existing dedicated CO2 pipeline system should not be seen as a significant obstacle for the commercial deployment of CCS technologies.

  19. Computing the Local Field Potential (LFP) from Integrate-and-Fire Network Models

    Science.gov (United States)

    Cuntz, Hermann; Lansner, Anders; Panzeri, Stefano; Einevoll, Gaute T.

    2015-01-01

    Leaky integrate-and-fire (LIF) network models are commonly used to study how the spiking dynamics of neural networks changes with stimuli, tasks or dynamic network states. However, neurophysiological studies in vivo often rather measure the mass activity of neuronal microcircuits with the local field potential (LFP). Given that LFPs are generated by spatially separated currents across the neuronal membrane, they cannot be computed directly from quantities defined in models of point-like LIF neurons. Here, we explore the best approximation for predicting the LFP based on standard output from point-neuron LIF networks. To search for this best “LFP proxy”, we compared LFP predictions from candidate proxies based on LIF network output (e.g, firing rates, membrane potentials, synaptic currents) with “ground-truth” LFP obtained when the LIF network synaptic input currents were injected into an analogous three-dimensional (3D) network model of multi-compartmental neurons with realistic morphology, spatial distributions of somata and synapses. We found that a specific fixed linear combination of the LIF synaptic currents provided an accurate LFP proxy, accounting for most of the variance of the LFP time course observed in the 3D network for all recording locations. This proxy performed well over a broad set of conditions, including substantial variations of the neuronal morphologies. Our results provide a simple formula for estimating the time course of the LFP from LIF network simulations in cases where a single pyramidal population dominates the LFP generation, and thereby facilitate quantitative comparison between computational models and experimental LFP recordings in vivo. PMID:26657024

  20. Computing the Local Field Potential (LFP from Integrate-and-Fire Network Models.

    Directory of Open Access Journals (Sweden)

    Alberto Mazzoni

    2015-12-01

    Full Text Available Leaky integrate-and-fire (LIF network models are commonly used to study how the spiking dynamics of neural networks changes with stimuli, tasks or dynamic network states. However, neurophysiological studies in vivo often rather measure the mass activity of neuronal microcircuits with the local field potential (LFP. Given that LFPs are generated by spatially separated currents across the neuronal membrane, they cannot be computed directly from quantities defined in models of point-like LIF neurons. Here, we explore the best approximation for predicting the LFP based on standard output from point-neuron LIF networks. To search for this best "LFP proxy", we compared LFP predictions from candidate proxies based on LIF network output (e.g, firing rates, membrane potentials, synaptic currents with "ground-truth" LFP obtained when the LIF network synaptic input currents were injected into an analogous three-dimensional (3D network model of multi-compartmental neurons with realistic morphology, spatial distributions of somata and synapses. We found that a specific fixed linear combination of the LIF synaptic currents provided an accurate LFP proxy, accounting for most of the variance of the LFP time course observed in the 3D network for all recording locations. This proxy performed well over a broad set of conditions, including substantial variations of the neuronal morphologies. Our results provide a simple formula for estimating the time course of the LFP from LIF network simulations in cases where a single pyramidal population dominates the LFP generation, and thereby facilitate quantitative comparison between computational models and experimental LFP recordings in vivo.

  1. Impaired action potential initiation in GABAergic interneurons causes hyperexcitable networks in an epileptic mouse model carrying a human Na(V)1.1 mutation.

    Science.gov (United States)

    Hedrich, Ulrike B S; Liautard, Camille; Kirschenbaum, Daniel; Pofahl, Martin; Lavigne, Jennifer; Liu, Yuanyuan; Theiss, Stephan; Slotta, Johannes; Escayg, Andrew; Dihné, Marcel; Beck, Heinz; Mantegazza, Massimo; Lerche, Holger

    2014-11-05

    Mutations in SCN1A and other ion channel genes can cause different epileptic phenotypes, but the precise mechanisms underlying the development of hyperexcitable networks are largely unknown. Here, we present a multisystem analysis of an SCN1A mouse model carrying the NaV1.1-R1648H mutation, which causes febrile seizures and epilepsy in humans. We found a ubiquitous hypoexcitability of interneurons in thalamus, cortex, and hippocampus, without detectable changes in excitatory neurons. Interestingly, somatic Na(+) channels in interneurons and persistent Na(+) currents were not significantly changed. Instead, the key mechanism of interneuron dysfunction was a deficit of action potential initiation at the axon initial segment that was identified by analyzing action potential firing. This deficit increased with the duration of firing periods, suggesting that increased slow inactivation, as recorded for recombinant mutated channels, could play an important role. The deficit in interneuron firing caused reduced action potential-driven inhibition of excitatory neurons as revealed by less frequent spontaneous but not miniature IPSCs. Multiple approaches indicated increased spontaneous thalamocortical and hippocampal network activity in mutant mice, as follows: (1) more synchronous and higher-frequency firing was recorded in primary neuronal cultures plated on multielectrode arrays; (2) thalamocortical slices examined by field potential recordings revealed spontaneous activities and pathological high-frequency oscillations; and (3) multineuron Ca(2+) imaging in hippocampal slices showed increased spontaneous neuronal activity. Thus, an interneuron-specific generalized defect in action potential initiation causes multisystem disinhibition and network hyperexcitability, which can well explain the occurrence of seizures in the studied mouse model and in patients carrying this mutation. Copyright © 2014 the authors 0270-6474/14/3414874-16$15.00/0.

  2. The use of skewness, kurtosis and neural networks for determining corrosion mechanism from electrochemical noise data

    International Nuclear Information System (INIS)

    Reid, S.; Bell, G.E.C.; Edgemon, G.L.

    1998-01-01

    This paper describes the work undertaken to de-skill the complex procedure of determining corrosion mechanisms derived from electrochemical noise data. The use of neural networks is discussed and applied to the real time generated electrochemical noise data files with the purpose of determining characteristics particular to individual types of corrosion mechanisms. The electrochemical noise signals can have a wide dynamic range and various methods of raw data pre-processing prior to neural network analysis were investigated. Normalized data were ultimately used as input to the final network analysis. Various network schemes were designed, trained and tested. Factors such as the network learning schedule and network design were considered before a final network was implemented to achieve a solution. Neural networks trained using general and localized corrosion data from various material environment systems were used to analyze data from simulated nuclear waste tank environments with favorable results

  3. Multi-agent Negotiation Mechanisms for Statistical Target Classification in Wireless Multimedia Sensor Networks

    Directory of Open Access Journals (Sweden)

    Sheng Wang

    2007-10-01

    Full Text Available The recent availability of low cost and miniaturized hardware has allowedwireless sensor networks (WSNs to retrieve audio and video data in real worldapplications, which has fostered the development of wireless multimedia sensor networks(WMSNs. Resource constraints and challenging multimedia data volume makedevelopment of efficient algorithms to perform in-network processing of multimediacontents imperative. This paper proposes solving problems in the domain of WMSNs fromthe perspective of multi-agent systems. The multi-agent framework enables flexible networkconfiguration and efficient collaborative in-network processing. The focus is placed ontarget classification in WMSNs where audio information is retrieved by microphones. Todeal with the uncertainties related to audio information retrieval, the statistical approachesof power spectral density estimates, principal component analysis and Gaussian processclassification are employed. A multi-agent negotiation mechanism is specially developed toefficiently utilize limited resources and simultaneously enhance classification accuracy andreliability. The negotiation is composed of two phases, where an auction based approach isfirst exploited to allocate the classification task among the agents and then individual agentdecisions are combined by the committee decision mechanism. Simulation experiments withreal world data are conducted and the results show that the proposed statistical approachesand negotiation mechanism not only reduce memory and computation requi

  4. QoS-Aware Error Recovery in Wireless Body Sensor Networks Using Adaptive Network Coding

    Science.gov (United States)

    Razzaque, Mohammad Abdur; Javadi, Saeideh S.; Coulibaly, Yahaya; Hira, Muta Tah

    2015-01-01

    Wireless body sensor networks (WBSNs) for healthcare and medical applications are real-time and life-critical infrastructures, which require a strict guarantee of quality of service (QoS), in terms of latency, error rate and reliability. Considering the criticality of healthcare and medical applications, WBSNs need to fulfill users/applications and the corresponding network's QoS requirements. For instance, for a real-time application to support on-time data delivery, a WBSN needs to guarantee a constrained delay at the network level. A network coding-based error recovery mechanism is an emerging mechanism that can be used in these systems to support QoS at very low energy, memory and hardware cost. However, in dynamic network environments and user requirements, the original non-adaptive version of network coding fails to support some of the network and user QoS requirements. This work explores the QoS requirements of WBSNs in both perspectives of QoS. Based on these requirements, this paper proposes an adaptive network coding-based, QoS-aware error recovery mechanism for WBSNs. It utilizes network-level and user-/application-level information to make it adaptive in both contexts. Thus, it provides improved QoS support adaptively in terms of reliability, energy efficiency and delay. Simulation results show the potential of the proposed mechanism in terms of adaptability, reliability, real-time data delivery and network lifetime compared to its counterparts. PMID:25551485

  5. Smart Collision Avoidance and Hazard Routing Mechanism for Intelligent Transport Network

    Science.gov (United States)

    Singh, Gurpreet; Gupta, Pooja; Wahab, Mohd Helmy Abd

    2017-08-01

    The smart vehicular ad-hoc network is the network that consists of vehicles for smooth movement and better management of the vehicular connectivity across the given network. This research paper aims to propose a set of solution for the VANETs consisting of the automatic driven vehicles, also called as the autonomous car. Such vehicular networks are always prone to collision due to the natural or un-natural reasons which must be solved before the large-scale deployment of the autonomous transport systems. The newly designed intelligent transport movement control mechanism is based upon the intelligent data propagation along with the vehicle collision and traffic jam prevention schema [8], which may help the future designs of smart cities to become more robust and less error-prone. In the proposed model, the focus is on designing a new dynamic and robust hazard routing protocol for intelligent vehicular networks for improvement of the overall performance in various aspects. It is expected to improve the overall transmission delay as well as the number of collisions or adversaries across the vehicular network zone.

  6. 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.

  7. Delay-aware adaptive sleep mechanism for green wireless-optical broadband access networks

    Science.gov (United States)

    Wang, Ruyan; Liang, Alei; Wu, Dapeng; Wu, Dalei

    2017-07-01

    Wireless-Optical Broadband Access Network (WOBAN) is capacity-high, reliable, flexible, and ubiquitous, as it takes full advantage of the merits from both optical communication and wireless communication technologies. Similar to other access networks, the high energy consumption poses a great challenge for building up WOBANs. To shot this problem, we can make some load-light Optical Network Units (ONUs) sleep to reduce the energy consumption. Such operation, however, causes the increased packet delay. Jointly considering the energy consumption and transmission delay, we propose a delay-aware adaptive sleep mechanism. Specifically, we develop a new analytical method to evaluate the transmission delay and queuing delay over the optical part, instead of adopting M/M/1 queuing model. Meanwhile, we also analyze the access delay and queuing delay of the wireless part. Based on such developed delay models, we mathematically derive ONU's optimal sleep time. In addition, we provide numerous simulation results to show the effectiveness of the proposed mechanism.

  8. Cross-Layer Service Discovery Mechanism for OLSRv2 Mobile Ad Hoc Networks

    Directory of Open Access Journals (Sweden)

    M. Isabel Vara

    2015-07-01

    Full Text Available Service discovery plays an important role in mobile ad hoc networks (MANETs. The lack of central infrastructure, limited resources and high mobility make service discovery a challenging issue for this kind of network. This article proposes a new service discovery mechanism for discovering and advertising services integrated into the Optimized Link State Routing Protocol Version 2 (OLSRv2. In previous studies, we demonstrated the validity of a similar service discovery mechanism integrated into the previous version of OLSR (OLSRv1. In order to advertise services, we have added a new type-length-value structure (TLV to the OLSRv2 protocol, called service discovery message (SDM, according to the Generalized MANET Packet/Message Format defined in Request For Comments (RFC 5444. Each node in the ad hoc network only advertises its own services. The advertisement frequency is a user-configurable parameter, so that it can be modified depending on the user requirements. Each node maintains two service tables, one to store information about its own services and another one to store information about the services it discovers in the network. We present simulation results, that compare our service discovery integrated into OLSRv2 with the one defined for OLSRv1 and with the integration of service discovery in Ad hoc On-demand Distance Vector (AODV protocol, in terms of service discovery ratio, service latency and network overhead.

  9. Cross-Layer Service Discovery Mechanism for OLSRv2 Mobile Ad Hoc Networks.

    Science.gov (United States)

    Vara, M Isabel; Campo, Celeste

    2015-07-20

    Service discovery plays an important role in mobile ad hoc networks (MANETs). The lack of central infrastructure, limited resources and high mobility make service discovery a challenging issue for this kind of network. This article proposes a new service discovery mechanism for discovering and advertising services integrated into the Optimized Link State Routing Protocol Version 2 (OLSRv2). In previous studies, we demonstrated the validity of a similar service discovery mechanism integrated into the previous version of OLSR (OLSRv1). In order to advertise services, we have added a new type-length-value structure (TLV) to the OLSRv2 protocol, called service discovery message (SDM), according to the Generalized MANET Packet/Message Format defined in Request For Comments (RFC) 5444. Each node in the ad hoc network only advertises its own services. The advertisement frequency is a user-configurable parameter, so that it can be modified depending on the user requirements. Each node maintains two service tables, one to store information about its own services and another one to store information about the services it discovers in the network. We present simulation results, that compare our service discovery integrated into OLSRv2 with the one defined for OLSRv1 and with the integration of service discovery in Ad hoc On-demand Distance Vector (AODV) protocol, in terms of service discovery ratio, service latency and network overhead.

  10. Signaling mechanisms underlying the robustness and tunability of the plant immune network

    Science.gov (United States)

    Kim, Yungil; Tsuda, Kenichi; Igarashi, Daisuke; Hillmer, Rachel A.; Sakakibara, Hitoshi; Myers, Chad L.; Katagiri, Fumiaki

    2014-01-01

    Summary How does robust and tunable behavior emerge in a complex biological network? We sought to understand this for the signaling network controlling pattern-triggered immunity (PTI) in Arabidopsis. A dynamic network model containing four major signaling sectors, the jasmonate, ethylene, PAD4, and salicylate sectors, which together explain up to 80% of the PTI level, was built using data for dynamic sector activities and PTI levels under exhaustive combinatorial sector perturbations. Our regularized multiple regression model had a high level of predictive power and captured known and unexpected signal flows in the network. The sole inhibitory sector in the model, the ethylene sector, was central to the network robustness via its inhibition of the jasmonate sector. The model's multiple input sites linked specific signal input patterns varying in strength and timing to different network response patterns, indicating a mechanism enabling tunability. PMID:24439900

  11. [Exploration on mechanism of anti-influenza virus activity of genus Paeonia based on network pharmacology].

    Science.gov (United States)

    Cai, Ya-Qi; Bao, Ya-Ting; Wang, Hong-Jin; Ren, Xiao-Dong; Huang, Lin-Fang; He, Jie; Liu, Tian-Tian; Zeng, Rui

    2018-04-01

    This paper aimed to investigate the anti-influenza virus activity of the genus Paeonia, screen potential anti-influenza virus compounds and predict targets of anti-influenza virus to explore the mechanism of anti-influenza virus activity. First of all, a total of 301 compounds of the genus Paeonia were summarized from the literatures in recent ten years. The candidate active ingredients from the genus Paeonia were identified by database such as PubChem and Chemical Book. The ligands were constructed by ChemDraw, Avogadro and Discovery Studio Visualizer. Secondly, 23 potential anti-influenza virus targets were developed by combining the target database and the literatures. Uniprot database was used to find the anti-influenza virus targets, and RCSB was used to identify targets associated with anti-influenza virus activity as docked receptor proteins. QuickVina 2.0 software was used for molecular docking. Finally, the Cytoscape 3.5.1 software was used to map the potential activity compounds of the genus Paeonia against influenza virus and the anti-influenza virus target network. Uniprot online database was used to analyze the target GO enrichment and KEGG metabolic pathways. The results showed that 74 compounds of the genus Paeonia had anti-influenza virus effect and 18 potential anti-influenza virus targets were screened. GO analysis concluded that the mechanism of the genus Paeonia anti-influenza virus is consistent with the mechanism of NA anti-influenza virus in order to stop the sprouting, dispersion and diffusion of virus and reduce the ability of virus to infect, so that the infection can be restricted so as to achieve the anti-influenza virus effect. Copyright© by the Chinese Pharmaceutical Association.

  12. QoS-Aware Error Recovery in Wireless Body Sensor Networks Using Adaptive Network Coding

    Directory of Open Access Journals (Sweden)

    Mohammad Abdur Razzaque

    2014-12-01

    Full Text Available Wireless body sensor networks (WBSNs for healthcare and medical applications are real-time and life-critical infrastructures, which require a strict guarantee of quality of service (QoS, in terms of latency, error rate and reliability. Considering the criticality of healthcare and medical applications, WBSNs need to fulfill users/applications and the corresponding network’s QoS requirements. For instance, for a real-time application to support on-time data delivery, a WBSN needs to guarantee a constrained delay at the network level. A network coding-based error recovery mechanism is an emerging mechanism that can be used in these systems to support QoS at very low energy, memory and hardware cost. However, in dynamic network environments and user requirements, the original non-adaptive version of network coding fails to support some of the network and user QoS requirements. This work explores the QoS requirements of WBSNs in both perspectives of QoS. Based on these requirements, this paper proposes an adaptive network coding-based, QoS-aware error recovery mechanism for WBSNs. It utilizes network-level and user-/application-level information to make it adaptive in both contexts. Thus, it provides improved QoS support adaptively in terms of reliability, energy efficiency and delay. Simulation results show the potential of the proposed mechanism in terms of adaptability, reliability, real-time data delivery and network lifetime compared to its counterparts.

  13. Dynamic Mobile RobotNavigation Using Potential Field Based Immune Network

    Directory of Open Access Journals (Sweden)

    Guan-Chun Luh

    2007-04-01

    Full Text Available This paper proposes a potential filed immune network (PFIN for dynamic navigation of mobile robots in an unknown environment with moving obstacles and fixed/moving targets. The Velocity Obstacle method is utilized to determine imminent obstacle collision of a robot moving in the time-varying environment. The response of the overall immune network is derived by the aid of fuzzy system. Simulation results are presented to verify the effectiveness of the proposed methodology in unknown environments with single and multiple moving obstacles

  14. Mechanism of Cerebralcare Granule® for Improving Cognitive Function in Resting-State Brain Functional Networks of Sub-healthy Subjects

    Directory of Open Access Journals (Sweden)

    Jing Li

    2017-07-01

    Full Text Available Cerebralcare Granule® (CG, a Chinese herbal medicine, has been used to ameliorate cognitive impairment induced by ischemia or mental disorders. The ability of CG to improve health status and cognitive function has drawn researchers' attention, but the relevant brain circuits that underlie the ameliorative effects of CG remain unclear. The present study aimed to explore the underlying neurobiological mechanisms of CG in ameliorating cognitive function in sub-healthy subjects using resting-state functional magnetic resonance imaging (fMRI. Thirty sub-healthy participants were instructed to take one 2.5-g package of CG three times a day for 3 months. Clinical cognitive functions were assessed with the Chinese Revised Wechsler Adult Intelligence Scale (WAIS-RC and Wechsler Memory Scale (WMS, and fMRI scans were performed at baseline and the end of intervention. Functional brain network data were analyzed by conventional network metrics (CNM and frequent subgraph mining (FSM. Then 21 other sub-healthy participants were enrolled as a blank control group of cognitive functional. We found that administrating CG can improve the full scale of intelligence quotient (FIQ and Memory Quotient (MQ scores. At the same time, following CG treatment, in CG group, the topological properties of functional brain networks were altered in various frontal, temporal, occipital cortex regions, and several subcortical brain regions, including essential components of the executive attention network, the salience network, and the sensory-motor network. The nodes involved in the FSM results were largely consistent with the CNM findings, and the changes in nodal metrics correlated with improved cognitive function. These findings indicate that CG can improve sub-healthy subjects' cognitive function through altering brain functional networks. These results provide a foundation for future studies of the potential physiological mechanism of CG.

  15. 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.

  16. Molecular inspired models for prediction and control of directional FSO/RF wireless networks

    Science.gov (United States)

    Llorca, Jaime; Milner, Stuart D.; Davis, Christopher C.

    2010-08-01

    Directional wireless networks using FSO and RF transmissions provide wireless backbone support for mobile communications in dynamic environments. The heterogeneous and dynamic nature of such networks challenges their robustness and requires self-organization mechanisms to assure end-to-end broadband connectivity. We developed a framework based on the definition of a potential energy function to characterize robustness in communication networks and the study of first and second order variations of the potential energy to provide prediction and control strategies for network performance optimization. In this paper, we present non-convex molecular potentials such as the Morse Potential, used to describe the potential energy of bonds within molecules, for the characterization of communication links in the presence of physical constraints such as the power available at the network nodes. The inclusion of the Morse Potential translates into adaptive control strategies where forces on network nodes drive the release, retention or reconfiguration of communication links for network performance optimization. Simulation results show the effectiveness of our self-organized control mechanism, where the physical topology reorganizes to maximize the number of source to destination communicating pairs. Molecular Normal Mode Analysis (NMA) techniques for assessing network performance degradation in dynamic networks are also presented. Preliminary results show correlation between peaks in the eigenvalues of the Hessian of the network potential and network degradation.

  17. A simple method for generating exactly solvable quantum mechanical potentials

    CERN Document Server

    Williams, B W

    1993-01-01

    A simple transformation method permitting the generation of exactly solvable quantum mechanical potentials from special functions solving second-order differential equations is reviewed. This method is applied to Gegenbauer polynomials to generate an attractive radial potential. The relationship of this method to the determination of supersymmetric quantum mechanical superpotentials is discussed, and the superpotential for the radial potential is also derived. (author)

  18. Data Network Equipment Energy Use and Savings Potential in Buildings

    Energy Technology Data Exchange (ETDEWEB)

    Lanzisera, Steven; Nordman, Bruce; Brown, Richard E.

    2010-06-09

    Network connectivity has become nearly ubiquitous, and the energy use of the equipment required for this connectivity is growing. Network equipment consists of devices that primarily switch and route Internet Protocol (IP) packets from a source to a destination, and this category specifically excludes edge devices like PCs, servers and other sources and sinks of IP traffic. This paper presents the results of a study of network equipment energy use and includes case studies of networks in a campus, a medium commercial building, and a typical home. The total energy use of network equipment is the product of the stock of equipment in use, the power of each device, and their usage patterns. This information was gathered from market research reports, broadband market penetration studies, field metering, and interviews with network administrators and service providers. We estimate that network equipment in the USA used 18 TWh, or about 1percent of building electricity, in 2008 and that consumption is expected to grow at roughly 6percent per year to 23 TWh in 2012; world usage in 2008 was 51 TWh. This study shows that office building network switches and residential equipment are the two largest categories of energy use consuming 40percent and 30percent of the total respectively. We estimate potential energy savings for different scenarios using forecasts of equipment stock and energy use, and savings estimates range from 20percent to 50percent based on full market penetration of efficient technologies.

  19. A zipper network model of the failure mechanics of extracellular matrices.

    Science.gov (United States)

    Ritter, Michael C; Jesudason, Rajiv; Majumdar, Arnab; Stamenovic, Dimitrije; Buczek-Thomas, Jo Ann; Stone, Phillip J; Nugent, Matthew A; Suki, Béla

    2009-01-27

    Mechanical failure of soft tissues is characteristic of life-threatening diseases, including capillary stress failure, pulmonary emphysema, and vessel wall aneurysms. Failure occurs when mechanical forces are sufficiently high to rupture the enzymatically weakened extracellular matrix (ECM). Elastin, an important structural ECM protein, is known to stretch beyond 200% strain before failing. However, ECM constructs and native vessel walls composed primarily of elastin and proteoglycans (PGs) have been found to fail at much lower strains. In this study, we hypothesized that PGs significantly contribute to tissue failure. To test this, we developed a zipper network model (ZNM), in which springs representing elastin are organized into long wavy fibers in a zipper-like formation and placed within a network of springs mimicking PGs. Elastin and PG springs possessed distinct mechanical and failure properties. Simulations using the ZNM showed that the failure of PGs alone reduces the global failure strain of the ECM well below that of elastin, and hence, digestion of elastin does not influence the failure strain. Network analysis suggested that whereas PGs drive the failure process and define the failure strain, elastin determines the peak and failure stresses. Predictions of the ZNM were experimentally confirmed by measuring the failure properties of engineered elastin-rich ECM constructs before and after digestion with trypsin, which cleaves the core protein of PGs without affecting elastin. This study reveals a role for PGs in the failure properties of engineered and native ECM with implications for the design of engineered tissues.

  20. The Coulomb potential in quantum mechanics and related topics

    International Nuclear Information System (INIS)

    Haeringen, H. van.

    1978-01-01

    This dissertation consists of an analytic study of the Coulomb interaction in nonrelativistic quantum mechanics and some related topics. The author investigates in a number of self-contained articles various interesting and important properties of the Coulomb potential. Some of these properties are shared by other potentials which also play a role in quantum mechanics. For such related interactions a comparative study is made. The principal difficulties in the description of proton-deuteron scattering and break-up reactions, due to the Coulomb interaction, are studied by working out a simple model. The bound states are studied for the Coulomb plus Yamaguchi potential, for the symmetric shifted Coulomb potential, and for local potentials with an inverse-distance-squared asymptotic behaviour. (Auth.)

  1. Analysis of the partnership network in the clean development mechanism

    International Nuclear Information System (INIS)

    Kang, Moon Jung; Park, Jihyoun

    2013-01-01

    The clean development mechanism (CDM) is a global collaborative action proposed at the Kyoto Protocol in response to climate change issues. The CDM contributes to cost-efficient reduction of greenhouse gas emissions in industrialized countries and promotes sustainable development in developing countries. Its fundamental framework is based on partnerships between industrialized and developing countries. This study employs social network analysis to investigate the dynamics of the partnership networks observed in 3816 CDM projects registered in the database of the United Nations Framework Convention on Climate Change over the period of 2005 to 2011. Our three main findings can be summarized as follows. First, the CDM partnership network is a small world; however, its density tends to decrease as the number of participants for a CDM project decreases. Second, the partnership networks’ leading groups tend to shift from partner countries into host countries. Third, a host country that pursues more partnership-based projects takes better control of resources and knowledge-flow in the ego-network formed around that country, and can thus better utilize global resources for its CDM projects. - Highlights: ► We investigate dynamics of the international partnership networks of CDM projects. ► The density of CDM networks tends to decrease by time. ► The partnership networks’ leading groups tend to shift into host countries. ► A host country with more partnerships better utilizes global knowledge resources.

  2. The slow oscillation in cortical and thalamic networks: mechanisms and functions

    Directory of Open Access Journals (Sweden)

    Garrett T. Neske

    2016-01-01

    Full Text Available During even the most quiescent behavioral periods, the cortex and thalamus express rich spontaneous activity in the form of slow (<1 Hz, synchronous network state transitions. Throughout this so-called slow oscillation, cortical and thalamic neurons fluctuate between periods of intense synaptic activity (Up states and almost complete silence (Down states. The two decades since the original characterization of the slow oscillation in the cortex and thalamus have seen considerable advances in deciphering the cellular and network mechanisms associated with this pervasive phenomenon. There are, nevertheless, many questions regarding the slow oscillation that await more thorough illumination, particularly the mechanisms by which Up states initiate and terminate, the functional role of the rhythmic activity cycles in unconscious or minimally conscious states, and the precise relation between Up states and the activated states associated with waking behavior. Given the substantial advances in multineuronal recording and imaging methods in both in vivo and in vitro preparations, the time is ripe to take stock of our current understanding of the slow oscillation and pave the way for future investigations of its mechanisms and functions. My aim in this Review is to provide a comprehensive account of the mechanisms and functions of the slow oscillation, and to suggest avenues for further exploration.

  3. A survey of energy conservation mechanisms for dynamic cluster based wireless sensor networks

    International Nuclear Information System (INIS)

    Enam, R.N.; Tahir, M.; Ahmed, S.; Qureshi, R.

    2018-01-01

    WSN (Wireless Sensor Network) is an emerging technology that has unlimited potential for numerous application areas including military, crisis management, environmental, transportation, medical, home/ city automations and smart spaces. But energy constrained nature of WSNs necessitates that their architecture and communicating protocols to be designed in an energy aware manner. Sensor data collection through clustering mechanisms has become a common strategy in WSN. This paper presents a survey report on the major perspectives with which energy conservation mechanisms has been proposed in dynamic cluster based WSNs so far. All the solutions discussed in this paper focus on the cluster based protocols only.We have covered a vast scale of existing energy efficient protocols and have categorized them in six categories. In the beginning of this paper the fundamentals of the energy constraint issues of WSNs have been discussed and an overview of the causes of energy consumptions at all layers of WSN has been given. Later in this paper several previously proposed energy efficient protocols of WSNs are presented. (author)

  4. A Survey of Energy Conservation Mechanisms for Dynamic Cluster Based Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Rabia Noor Enam

    2018-04-01

    Full Text Available WSN (Wireless Sensor Network is an emerging technology that has unlimited potential for numerous application areas including military, crisis management, environmental, transportation, medical, home/ city automations and smart spaces. But energy constrained nature of WSNs necessitates that their architecture and communicating protocols to be designed in an energy aware manner. Sensor data collection through clustering mechanisms has become a common strategy in WSN. This paper presents a survey report on the major perspectives with which energy conservation mechanisms has been proposed in dynamic cluster based WSNs so far. All the solutions discussed in this paper focus on the cluster based protocols only.We have covered a vast scale of existing energy efficient protocols and have categorized them in six categories. In the beginning of this paper the fundamentals of the energy constraint issues of WSNs have been discussed and an overview of the causes of energy consumptions at all layers of WSN has been given. Later in this paper several previously proposed energy efficient protocols of WSNs are presented.

  5. Deciding where to attend: Large-scale network mechanisms underlying attention and intention revealed by graph-theoretic analysis.

    Science.gov (United States)

    Liu, Yuelu; Hong, Xiangfei; Bengson, Jesse J; Kelley, Todd A; Ding, Mingzhou; Mangun, George R

    2017-08-15

    The neural mechanisms by which intentions are transformed into actions remain poorly understood. We investigated the network mechanisms underlying spontaneous voluntary decisions about where to focus visual-spatial attention (willed attention). Graph-theoretic analysis of two independent datasets revealed that regions activated during willed attention form a set of functionally-distinct networks corresponding to the frontoparietal network, the cingulo-opercular network, and the dorsal attention network. Contrasting willed attention with instructed attention (where attention is directed by external cues), we observed that the dorsal anterior cingulate cortex was allied with the dorsal attention network in instructed attention, but shifted connectivity during willed attention to interact with the cingulo-opercular network, which then mediated communications between the frontoparietal network and the dorsal attention network. Behaviorally, greater connectivity in network hubs, including the dorsolateral prefrontal cortex, the dorsal anterior cingulate cortex, and the inferior parietal lobule, was associated with faster reaction times. These results, shown to be consistent across the two independent datasets, uncover the dynamic organization of functionally-distinct networks engaged to support intentional acts. Copyright © 2017 Elsevier Inc. All rights reserved.

  6. Integration of Electric Vehicles into the Power Distribution Network with a Modified Capacity Allocation Mechanism

    Directory of Open Access Journals (Sweden)

    Junjie Hu

    2017-02-01

    Full Text Available The growing penetration of electric vehicles (EVs represents an operational challenge to system operators, mainly at the distribution level by introducing congestion and voltage drop problems. To solve these potential problems, a two-level coordination approach is proposed in this study. An aggregation entity, i.e., an EV virtual power plant (EV-VPP, is used to facilitate the interaction between the distribution system operator (DSO and EV owners considering the decentralized electricity market structure. In level I, to prevent the line congestion and voltage drop problems, the EV-VPP internally respects the line and voltage constraints when making optimal charging schedules. In level II, to avoid power transformer congestion problems, this paper investigates three different coordination mechanisms, or power transformer capacity allocation mechanisms, between the DSO and the EV-VPPs, considering the case of EVs charging and discharging. The three mechanisms include: (1 a market-based approach; (2 a pro-rata approach; and (3 a newly-proposed constrained market-based approach. A case study considering a 37-bus distribution network and high penetration of electric vehicles is presented to demonstrate the effectiveness of the proposed coordination mechanism, comparing with the existing ones.

  7. Deep Potential Molecular Dynamics: A Scalable Model with the Accuracy of Quantum Mechanics

    Science.gov (United States)

    Zhang, Linfeng; Han, Jiequn; Wang, Han; Car, Roberto; E, Weinan

    2018-04-01

    We introduce a scheme for molecular simulations, the deep potential molecular dynamics (DPMD) method, based on a many-body potential and interatomic forces generated by a carefully crafted deep neural network trained with ab initio data. The neural network model preserves all the natural symmetries in the problem. It is first-principles based in the sense that there are no ad hoc components aside from the network model. We show that the proposed scheme provides an efficient and accurate protocol in a variety of systems, including bulk materials and molecules. In all these cases, DPMD gives results that are essentially indistinguishable from the original data, at a cost that scales linearly with system size.

  8. Information Sharing Mechanism among Mobile Agents In Ad-hoc Network Environment and Its Applications

    Directory of Open Access Journals (Sweden)

    Kunio Umetsuji

    2004-12-01

    Full Text Available Mobile agents are programs that can move from one site to another in a network with their data and states. Mobile agents are expected to be an essential tool in pervasive computing. In multi platform environment, it is important to communicate with mobile agents only using their universal or logical name not using their physical locations. More, in an ad-hoc network environment, an agent can migrate autonomously and communicate with other agents on demand. It is difficult that mobile agent grasps the position information on other agents correctly each other, because mobile agent processes a task while moving a network successively. In order to realize on-demand mutual communication among mobile agents without any centralized servers, we propose a new information sharing mechanism within mobile agents. In this paper, we present a new information sharing mechanism within mobile agents. The method is a complete peer based and requires no agent servers to manage mobile agent locations. Therefore, a mobile agent can get another mobile agent, communicate with it and shares information stored in the agent without any knowledge of the location of the target mobile agent. The basic idea of the mechanism is an introduction of Agent Ring, Agent Chain and Shadow Agent. With this mechanism, each agent can communicate with other agents in a server-less environment, which is suitable for ad-hoc agent network and an agent system can manage agents search and communications efficiently.

  9. Artificial neural networks in prediction of mechanical behavior of concrete at high temperature

    International Nuclear Information System (INIS)

    Mukherjee, A.; Nag Biswas, S.

    1997-01-01

    The behavior of concrete structures that are exposed to extreme thermo-mechanical loading is an issue of great importance in nuclear engineering. The mechanical behavior of concrete at high temperature is non-linear. The properties that regulate its response are highly temperature dependent and extremely complex. In addition, the constituent materials, e.g. aggregates, influence the response significantly. Attempts have been made to trace the stress-strain curve through mathematical models and rheological models. However, it has been difficult to include all the contributing factors in the mathematical model. This paper examines a new programming paradigm, artificial neural networks, for the problem. Implementing a feedforward network and backpropagation algorithm the stress-strain relationship of the material is captured. The neural networks for the prediction of uniaxial behavior of concrete at high temperature has been presented here. The results of the present investigation are very encouraging. (orig.)

  10. Survey of networked control systems and their potential applications in nuclear power plants

    Energy Technology Data Exchange (ETDEWEB)

    Kadri, A. [Univ. of Western Ontario, Dept. of Electrical and Computer Engineering, London, Ontario (Canada)]. E-mail: akadri@uwo.ca

    2006-07-01

    This paper provides an overview of networked control systems (NCSs) and their industrial applications. Most widely used NCSs based on fieldbus technologies; namely, ControlNet, Profibus (DP/PA), and Foundation Fieldbus have been discussed. The objectives and benefits of using such networks are presented and factors influencing their design and implementation are examined. Then, some of the special requirements in controlling nuclear power plant (NPP) have been considered. The potential of applying networked control systems in such installations has been discussed. Finally, the concept of wireless networked control systems is also described. (author)

  11. Burst analysis tool for developing neuronal networks exhibiting highly varying action potential dynamics

    Directory of Open Access Journals (Sweden)

    Fikret Emre eKapucu

    2012-06-01

    Full Text Available In this paper we propose a firing statistics based neuronal network burst detection algorithm for neuronal networks exhibiting highly variable action potential dynamics. Electrical activity of neuronal networks is generally analyzed by the occurrences of spikes and bursts both in time and space. Commonly accepted analysis tools employ burst detection algorithms based on predefined criteria. However, maturing neuronal networks, such as those originating from human embryonic stem cells (hESC, exhibit highly variable network structure and time-varying dynamics. To explore the developing burst/spike activities of such networks, we propose a burst detection algorithm which utilizes the firing statistics based on interspike interval (ISI histograms. Moreover, the algorithm calculates interspike interval thresholds for burst spikes as well as for pre-burst spikes and burst tails by evaluating the cumulative moving average and skewness of the ISI histogram. Because of the adaptive nature of the proposed algorithm, its analysis power is not limited by the type of neuronal cell network at hand. We demonstrate the functionality of our algorithm with two different types of microelectrode array (MEA data recorded from spontaneously active hESC-derived neuronal cell networks. The same data was also analyzed by two commonly employed burst detection algorithms and the differences in burst detection results are illustrated. The results demonstrate that our method is both adaptive to the firing statistics of the network and yields successful burst detection from the data. In conclusion, the proposed method is a potential tool for analyzing of hESC-derived neuronal cell networks and thus can be utilized in studies aiming to understand the development and functioning of human neuronal networks and as an analysis tool for in vitro drug screening and neurotoxicity assays.

  12. Semi-Degradable Poly(β-amino ester) Networks with Temporally-Controlled Enhancement of Mechanical Properties

    Science.gov (United States)

    Safranski, David L.; Weiss, Daiana; Clark, J. Brian; Taylor, W.R.; Gall, Ken

    2014-01-01

    Biodegradable polymers are clinically used in numerous biomedical applications, and classically show a loss in mechanical properties within weeks of implantation. This work demonstrates a new class of semi-degradable polymers that show an increase in mechanical properties through degradation via a controlled shift in a thermal transition. Semi-degradable polymer networks, poly(β-amino ester)-co-methyl methacrylate, were formed from a low glass transition temperature crosslinker, poly(β-amino ester), and high glass transition temperature monomer, methyl methacrylate, which degraded in a manner dependent upon the crosslinker chemical structure. In vitro and in vivo degradation revealed changes in mechanical behavior due to the degradation of the crosslinker from the polymer network. This novel polymer system demonstrates a strategy to temporally control the mechanical behavior of polymers and to enhance the initial performance of smart biomedical devices. PMID:24769113

  13. Exactly Solvable Quantum Mechanical Potentials: An Alternative Approach.

    Science.gov (United States)

    Pronchik, Jeremy N.; Williams, Brian W.

    2003-01-01

    Describes an alternative approach to finding exactly solvable, one-dimensional quantum mechanical potentials. Differs from the usual approach in that instead of starting with a particular potential and seeking solutions to the related Schrodinger equations, it begins with known solutions to second-order ordinary differential equations and seeks to…

  14. Action Potential Modulation of Neural Spin Networks Suggests Possible Role of Spin

    CERN Document Server

    Hu, H P

    2004-01-01

    In this paper we show that nuclear spin networks in neural membranes are modulated by action potentials through J-coupling, dipolar coupling and chemical shielding tensors and perturbed by microscopically strong and fluctuating internal magnetic fields produced largely by paramagnetic oxygen. We suggest that these spin networks could be involved in brain functions since said modulation inputs information carried by the neural spike trains into them, said perturbation activates various dynamics within them and the combination of the two likely produce stochastic resonance thus synchronizing said dynamics to the neural firings. Although quantum coherence is desirable and may indeed exist, it is not required for these spin networks to serve as the subatomic components for the conventional neural networks.

  15. The Mechanism Research of Qishen Yiqi Formula by Module-Network Analysis

    OpenAIRE

    Zheng, Shichao; Zhang, Yanling; Qiao, Yanjiang

    2015-01-01

    Qishen Yiqi formula (QSYQ) has the effect of tonifying Qi and promoting blood circulation, which is widely used to treat the cardiovascular diseases with Qi deficiency and blood stasis syndrome. However, the mechanism of QSYQ to tonify Qi and promote blood circulation is rarely reported at molecular or systems level. This study aimed to elucidate the mechanism of QSYQ based on the protein interaction network (PIN) analysis. The targets’ information of the active components was obtained from C...

  16. Physical organogels: mechanism and kinetics of evaporation of the solvents entrapped within network scaffolding

    International Nuclear Information System (INIS)

    Markovic, Nov; Dutta, Naba K.

    2005-01-01

    A series of hydrocarbon gels (based on leaded petrol and decalin) using physically crosslinked networks have been prepared using Al-salt of fatty acid as the physical gelling agent. The effects of gel network scaffolding on the mechanism and kinetics of evaporation of the solvents from the gels were investigated using conventional, isothermal and modulated thermogravimetric analysis. It has been clearly observed that the evaporation of solvent from gels followed a complex evaporation pattern compared to the pure solvent. It appears that with increase in network scaffolding the maximum rate of evaporation of the solvent decreases and its distribution become broader. The activation energy of evaporation for these solvents was found not to be dramatically dependent on the concentration of the gelator and tightness of the network scaffolding. Amongst different methods employed, isothermal measurements provided reliable information about the mechanism of evaporation. Modulated thermogravimetric analysis proved to be an efficient method to achieve kinetic parameters of evaporation from a single dynamic experiment. Scanning electron microscopy was used to probe for both dry gelator and gel network after evaporation of the solvents for evaluation of their surface morphology

  17. Redundancy and cooperativity in the mechanics of compositely crosslinked filamentous networks.

    Directory of Open Access Journals (Sweden)

    Moumita Das

    Full Text Available The cytoskeleton of living cells contains many types of crosslinkers. Some crosslinkers allow energy-free rotations between filaments and others do not. The mechanical interplay between these different crosslinkers is an open issue in cytoskeletal mechanics. Therefore, we develop a theoretical framework based on rigidity percolation to study a generic filamentous system containing both stretching and bond-bending forces to address this issue. The framework involves both analytical calculations via effective medium theory and numerical simulations on a percolating triangular lattice with very good agreement between both. We find that the introduction of angle-constraining crosslinkers to a semiflexible filamentous network with freely rotating crosslinks can cooperatively lower the onset of rigidity to the connectivity percolation threshold-a result argued for years but never before obtained via effective medium theory. This allows the system to ultimately attain rigidity at the lowest concentration of material possible. We further demonstrate that introducing angle-constraining crosslinks results in mechanical behaviour similar to just freely rotating crosslinked semflexible filaments, indicating redundancy and universality. Our results also impact upon collagen and fibrin networks in biological and bio-engineered tissues.

  18. EXPLOSION POTENTIAL ASSESSMENT OF HEAT EXCHANGER NETWORK AT THE PRELIMINARY DESIGN STAGE

    Directory of Open Access Journals (Sweden)

    MOHSIN PASHA

    2016-07-01

    Full Text Available The failure of Shell and Tube Heat Exchangers (STHE is being extensively observed in the chemical process industries. This failure can cause enormous production loss and have a potential of dangerous consequences such as an explosion, fire and toxic release scenarios. There is an urgent need for assessing the explosion potential of shell and tube heat exchanger at the preliminary design stage. In current work, inherent safety index based approach is used to resolve the highlighted issue. Inherent Safety Index for Shell and Tube Heat Exchanger (ISISTHE is a newly developed index for assessing the inherent safety level of a STHE at the preliminary design stage. This index is composed of preliminary design variables and integrated with the process design simulator (Aspen HYSYS. Process information can easily be transferred from process design simulator to MS Excel spreadsheet owing to this integration. This index could potentially facilitate the design engineer to analyse the worst heat exchanger in the heat exchanger network. Typical heat exchanger network of the steam reforming process is presented as a case study and the worst heat exchanger of this network has been identified. It is inferred from this analysis that shell and tube heat exchangers possess high operating pressure, corrected mean temperature difference (CMTD and flammability and reactive potential needs to be critically analysed at the preliminary design stage.

  19. [Pharmacological mechanism analysis of oligopeptide from Pinctada fucata based on in silico proteolysis and protein interaction network].

    Science.gov (United States)

    Chen, Yan-Kun; Qiao, Lian-Sheng; Huo, Xiao-Qian; Zhang, Xu; Han, Na; Zhang, Yan-Ling

    2017-09-01

    Pinctada fucata oligopeptide is one of key pharmaceutical effective constituents of P. fucata. It is significant to analyze its pharmacological effect and mechanism. This study aims to discover the potential oligopeptides from P. fucata and analyze the mechanism of P. fucata oligopeptide based on in silico technologies and protein interaction network(PIN). First, main protein sequences of P. fucata were collected, and oligopeptides were obtained using in silico gastrointestinal tract proteolysis. Then, key potential targets of P. fucata oligopeptides were obtained through pharmacophore screening. The protein-protein interaction(PPI) of targets was achieved and implemented to construct PIN and analyze the mechanism of P. fucata oligopeptides. P. fucata oligopeptide database was constructed based on in silico technologies, including 458 oligopeptides. Twelve modules were identified from PIN by a graph theoretic clustering algorithm Molecular Complex Detection(MCODE) and analyzed by Gene ontology(GO) enrichment. The results indicated that P. fucata oligopeptides have an effect in treating neurological diseases, such as Alzheimer's disease. In silico proteolysis could be used to analyze the protein sequences of traditional Chinese medicine(TCM). According to the combination of in silico proteolysis and PIN, the biological activity of oligopeptides could be interpreted rapidly based on the known TCM protein sequence. The study provides the methodology basis for rapidly and efficiently implementing the mechanism analysis of TCM oligopeptides. Copyright© by the Chinese Pharmaceutical Association.

  20. Combined centralised and distributed mechanism for utilisation of node association in broadband wireless network

    Science.gov (United States)

    Ulvan, A.; Ulvan, M.; Pranoto, H.

    2018-02-01

    Mobile broadband wireless access system has the stations that might be fixed, nomadic or mobile. Regarding the mobility, the node association procedure is critical for network entry as well as network re-entry during handover. The flexibility and utilisation of MAC protocols scheduling have an important role. The standard provides the Partition Scheme as the scheduling mechanism which separates the allocation of minislots for scheduling. However, minislots cannot be flexibly reserved for centralised and distributed scheduling. In this paper we analysed the scheduling mechanism to improve the utilisation of minislots allocation during the exchange of MAC massages. The centralised and distributed scheduling is implemented in some topology scenarios. The result shows the proposed mechanism has better performance for node association than partition scheme.

  1. Hybrid Scheme for Modeling Local Field Potentials from Point-Neuron Networks.

    Science.gov (United States)

    Hagen, Espen; Dahmen, David; Stavrinou, Maria L; Lindén, Henrik; Tetzlaff, Tom; van Albada, Sacha J; Grün, Sonja; Diesmann, Markus; Einevoll, Gaute T

    2016-12-01

    With rapidly advancing multi-electrode recording technology, the local field potential (LFP) has again become a popular measure of neuronal activity in both research and clinical applications. Proper understanding of the LFP requires detailed mathematical modeling incorporating the anatomical and electrophysiological features of neurons near the recording electrode, as well as synaptic inputs from the entire network. Here we propose a hybrid modeling scheme combining efficient point-neuron network models with biophysical principles underlying LFP generation by real neurons. The LFP predictions rely on populations of network-equivalent multicompartment neuron models with layer-specific synaptic connectivity, can be used with an arbitrary number of point-neuron network populations, and allows for a full separation of simulated network dynamics and LFPs. We apply the scheme to a full-scale cortical network model for a ∼1 mm 2 patch of primary visual cortex, predict laminar LFPs for different network states, assess the relative LFP contribution from different laminar populations, and investigate effects of input correlations and neuron density on the LFP. The generic nature of the hybrid scheme and its public implementation in hybridLFPy form the basis for LFP predictions from other and larger point-neuron network models, as well as extensions of the current application with additional biological detail. © The Author 2016. Published by Oxford University Press.

  2. Physical Layer Network Coding

    DEFF Research Database (Denmark)

    Fukui, Hironori; Yomo, Hironori; Popovski, Petar

    2013-01-01

    of interfering nodes and usage of spatial reservation mechanisms. Specifically, we introduce a reserved area in order to protect the nodes involved in two-way relaying from the interference caused by neighboring nodes. We analytically derive the end-to-end rate achieved by PLNC considering the impact......Physical layer network coding (PLNC) has the potential to improve throughput of multi-hop networks. However, most of the works are focused on the simple, three-node model with two-way relaying, not taking into account the fact that there can be other neighboring nodes that can cause....../receive interference. The way to deal with this problem in distributed wireless networks is usage of MAC-layer mechanisms that make a spatial reservation of the shared wireless medium, similar to the well-known RTS/CTS in IEEE 802.11 wireless networks. In this paper, we investigate two-way relaying in presence...

  3. Memristor-based neural networks

    International Nuclear Information System (INIS)

    Thomas, Andy

    2013-01-01

    The synapse is a crucial element in biological neural networks, but a simple electronic equivalent has been absent. This complicates the development of hardware that imitates biological architectures in the nervous system. Now, the recent progress in the experimental realization of memristive devices has renewed interest in artificial neural networks. The resistance of a memristive system depends on its past states and exactly this functionality can be used to mimic the synaptic connections in a (human) brain. After a short introduction to memristors, we present and explain the relevant mechanisms in a biological neural network, such as long-term potentiation and spike time-dependent plasticity, and determine the minimal requirements for an artificial neural network. We review the implementations of these processes using basic electric circuits and more complex mechanisms that either imitate biological systems or could act as a model system for them. (topical review)

  4. Effect of hydro mechanical coupling on natural fracture network formation in sedimentary basins

    Science.gov (United States)

    Ouraga, Zady; Guy, Nicolas; Pouya, Amade

    2018-05-01

    In sedimentary basin context, numerous phenomena, depending on the geological time span, can result in natural fracture network formation. In this paper, fracture network and dynamic fracture spacing triggered by significant sedimentation rate are studied considering mode I fracture propagation using a coupled hydro-mechanical numerical methods. The focus is put on synthetic geological structure under a constant sedimentation rate on its top. This model contains vertical fracture network initially closed and homogeneously distributed. The fractures are modelled with cohesive zone model undergoing damage and the flow is described by Poiseuille's law. The effect of the behaviour of the rock is studied and the analysis leads to a pattern of fracture network and fracture spacing in the geological layer.

  5. Identification of complex systems by artificial neural networks. Applications to mechanical frictions

    International Nuclear Information System (INIS)

    Dominguez, Manuel

    1998-01-01

    In the frame of complex systems modelization, we describe in this report the contribution of neural networks to mechanical friction modelization. This thesis is divided in three parts, each one corresponding to every stage of the realized work. The first part takes stock of the properties of neural networks by replacing them in the statistic frame of learning theory (particularly: non-linear and non-parametric regression models) and by showing the existing links with other more 'classic' techniques from automatics. We show then how identification models can be integrated in the neural networks description as a larger nonlinear model class. A methodology of neural networks use have been developed. We focused on validation techniques using correlation functions for non-linear systems, and on the use of regularization methods. The second part deals with the problematic of friction in mechanical systems. Particularly, we present the main current identified physical phenomena, which are integrated in advanced friction modelization. Characterization of these phenomena allows us to state a priori knowledge to be used in the identification stage. We expose some of the most well-known friction models: Dahl's model, Reset Integrator and Canuda's dynamical model, which are then used in simulation studies. The last part links the former one by illustrating a real-world application: an electric jack from SFIM-Industries, used in the Very Large Telescope (VLT) control scheme. This part begins with physical system presentation. The results are compared with more 'classic' methods. We finish using neural networks compensation scheme in closed-loop control. (author) [fr

  6. Gene expression profile analysis of colorectal cancer to investigate potential mechanisms using bioinformatics

    Directory of Open Access Journals (Sweden)

    Kou YB

    2015-04-01

    phosphorylation and Parkinson’s disease. DEGs, such as FOS, FN1, PPP1CC, and CYP2B6, may be used as potential targets for CRC diagnosis and treatment. Keywords: molecular mechanisms, network module, enrichment analysis

  7. Semi-degradable poly(β-amino ester) networks with temporally controlled enhancement of mechanical properties.

    Science.gov (United States)

    Safranski, David L; Weiss, Daiana; Clark, J Brian; Taylor, W Robert; Gall, Ken

    2014-08-01

    Biodegradable polymers are clinically used in numerous biomedical applications, and classically show a loss of mechanical properties within weeks of implantation. This work demonstrates a new class of semi-degradable polymers that show an increase in mechanical properties through degradation via a controlled shift in a thermal transition. Semi-degradable polymer networks, poly(β-amino ester)-co-methyl methacrylate, were formed from a low glass transition temperature crosslinker, poly(β-amino ester), and high glass transition temperature monomer, methyl methacrylate, which degraded in a manner dependent upon the crosslinker chemical structure. In vitro and in vivo degradation revealed changes in mechanical behavior due to the degradation of the crosslinker from the polymer network. This novel polymer system demonstrates a strategy to temporally control the mechanical behavior of polymers and to enhance the initial performance of smart biomedical devices. Copyright © 2014 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

  8. Prediction of the anti-inflammatory mechanisms of curcumin by module-based protein interaction network analysis

    Directory of Open Access Journals (Sweden)

    Yanxiong Gan

    2015-11-01

    Full Text Available Curcumin, the medically active component from Curcuma longa (Turmeric, is widely used to treat inflammatory diseases. Protein interaction network (PIN analysis was used to predict its mechanisms of molecular action. Targets of curcumin were obtained based on ChEMBL and STITCH databases. Protein–protein interactions (PPIs were extracted from the String database. The PIN of curcumin was constructed by Cytoscape and the function modules identified by gene ontology (GO enrichment analysis based on molecular complex detection (MCODE. A PIN of curcumin with 482 nodes and 1688 interactions was constructed, which has scale-free, small world and modular properties. Based on analysis of these function modules, the mechanism of curcumin is proposed. Two modules were found to be intimately associated with inflammation. With function modules analysis, the anti-inflammatory effects of curcumin were related to SMAD, ERG and mediation by the TLR family. TLR9 may be a potential target of curcumin to treat inflammation.

  9. Potential energy landscape and robustness of a gene regulatory network: toggle switch.

    Directory of Open Access Journals (Sweden)

    Keun-Young Kim

    2007-03-01

    Full Text Available Finding a multidimensional potential landscape is the key for addressing important global issues, such as the robustness of cellular networks. We have uncovered the underlying potential energy landscape of a simple gene regulatory network: a toggle switch. This was realized by explicitly constructing the steady state probability of the gene switch in the protein concentration space in the presence of the intrinsic statistical fluctuations due to the small number of proteins in the cell. We explored the global phase space for the system. We found that the protein synthesis rate and the unbinding rate of proteins to the gene were small relative to the protein degradation rate; the gene switch is monostable with only one stable basin of attraction. When both the protein synthesis rate and the unbinding rate of proteins to the gene are large compared with the protein degradation rate, two global basins of attraction emerge for a toggle switch. These basins correspond to the biologically stable functional states. The potential energy barrier between the two basins determines the time scale of conversion from one to the other. We found as the protein synthesis rate and protein unbinding rate to the gene relative to the protein degradation rate became larger, the potential energy barrier became larger. This also corresponded to systems with less noise or the fluctuations on the protein numbers. It leads to the robustness of the biological basins of the gene switches. The technique used here is general and can be applied to explore the potential energy landscape of the gene networks.

  10. A Network Pharmacology Approach to Determine the Active Components and Potential Targets of Curculigo Orchioides in the Treatment of Osteoporosis.

    Science.gov (United States)

    Wang, Nani; Zhao, Guizhi; Zhang, Yang; Wang, Xuping; Zhao, Lisha; Xu, Pingcui; Shou, Dan

    2017-10-27

    BACKGROUND Osteoporosis is a complex bone disorder with a genetic predisposition, and is a cause of health problems worldwide. In China, Curculigo orchioides (CO) has been widely used as a herbal medicine in the prevention and treatment of osteoporosis. However, research on the mechanism of action of CO is still lacking. The aim of this study was to identify the absorbable components, potential targets, and associated treatment pathways of CO using a network pharmacology approach. MATERIAL AND METHODS We explored the chemical components of CO and used the five main principles of drug absorption to identify absorbable components. Targets for the therapeutic actions of CO were obtained from the PharmMapper server database. Pathway enrichment analysis was performed using the Comparative Toxicogenomics Database (CTD). Cytoscape was used to visualize the multiple components-multiple target-multiple pathways-multiple disease network for CO. RESULTS We identified 77 chemical components of CO, of which 32 components could be absorbed in the blood. These potential active components of CO regulated 83 targets and affected 58 pathways. Data analysis showed that the genes for estrogen receptor alpha (ESR1) and beta (ESR2), and the gene for 11 beta-hydroxysteroid dehydrogenase type 1, or cortisone reductase (HSD11B1) were the main targets of CO. Endocrine regulatory factors and factors regulating calcium reabsorption, steroid hormone biosynthesis, and metabolic pathways were related to these main targets and to ten corresponding compounds. CONCLUSIONS The network pharmacology approach used in our study has attempted to explain the mechanisms for the effects of CO in the prevention and treatment of osteoporosis, and provides an alternative approach to the investigation of the effects of this complex compound.

  11. Contributions of Social Networking for Innovation

    Directory of Open Access Journals (Sweden)

    Daniela Maria Cartoni

    2013-04-01

    Full Text Available This paper investigates the role of virtual social networks as a mechanism complementary to formal channels of technology transfer represented by ICT and by private centers of R & D in industry. The strengthening of Web 2.0 has provided the expansion of collaborative tools, in particular the social networks, with a strong influence on the spread of knowledge and innovation. To evaluate the potential of virtual networks, a survey had been conducted to identify and describe the characteristics of some of the major social networks used in Brazil (LinkedIn, Orkut and Twitter. Even this phenomenon is not mature, the study identified the potential and benefits of social networks as informal structures that help in generation of knowledge and innovation diffusion, as a field to be explored and developed.

  12. An Authentication and Key Management Mechanism for Resource Constrained Devices in IEEE 802.11-based IoT Access Networks

    Directory of Open Access Journals (Sweden)

    Ki-Wook Kim

    2017-09-01

    Full Text Available Many Internet of Things (IoT services utilize an IoT access network to connect small devices with remote servers. They can share an access network with standard communication technology, such as IEEE 802.11ah. However, an authentication and key management (AKM mechanism for resource constrained IoT devices using IEEE 802.11ah has not been proposed as yet. We therefore propose a new AKM mechanism for an IoT access network, which is based on IEEE 802.11 key management with the IEEE 802.1X authentication mechanism. The proposed AKM mechanism does not require any pre-configured security information between the access network domain and the IoT service domain. It considers the resource constraints of IoT devices, allowing IoT devices to delegate the burden of AKM processes to a powerful agent. The agent has sufficient power to support various authentication methods for the access point, and it performs cryptographic functions for the IoT devices. Performance analysis shows that the proposed mechanism greatly reduces computation costs, network costs, and memory usage of the resource-constrained IoT device as compared to the existing IEEE 802.11 Key Management with the IEEE 802.1X authentication mechanism.

  13. An Authentication and Key Management Mechanism for Resource Constrained Devices in IEEE 802.11-based IoT Access Networks.

    Science.gov (United States)

    Kim, Ki-Wook; Han, Youn-Hee; Min, Sung-Gi

    2017-09-21

    Many Internet of Things (IoT) services utilize an IoT access network to connect small devices with remote servers. They can share an access network with standard communication technology, such as IEEE 802.11ah. However, an authentication and key management (AKM) mechanism for resource constrained IoT devices using IEEE 802.11ah has not been proposed as yet. We therefore propose a new AKM mechanism for an IoT access network, which is based on IEEE 802.11 key management with the IEEE 802.1X authentication mechanism. The proposed AKM mechanism does not require any pre-configured security information between the access network domain and the IoT service domain. It considers the resource constraints of IoT devices, allowing IoT devices to delegate the burden of AKM processes to a powerful agent. The agent has sufficient power to support various authentication methods for the access point, and it performs cryptographic functions for the IoT devices. Performance analysis shows that the proposed mechanism greatly reduces computation costs, network costs, and memory usage of the resource-constrained IoT device as compared to the existing IEEE 802.11 Key Management with the IEEE 802.1X authentication mechanism.

  14. Determining the structure-mechanics relationships of dense microtubule networks with confocal microscopy and magnetic tweezers-based microrheology.

    Science.gov (United States)

    Yang, Yali; Valentine, Megan T

    2013-01-01

    The microtubule (MT) cytoskeleton is essential in maintaining the shape, strength, and organization of cells. Its spatiotemporal organization is fundamental for numerous dynamic biological processes, and mechanical stress within the MT cytoskeleton provides an important signaling mechanism in mitosis and neural development. This raises important questions about the relationships between structure and mechanics in complex MT structures. In vitro, reconstituted cytoskeletal networks provide a minimal model of cell mechanics while also providing a testing ground for the fundamental polymer physics of stiff polymer gels. Here, we describe our development and implementation of a broad tool kit to study structure-mechanics relationships in reconstituted MT networks, including protocols for the assembly of entangled and cross-linked MT networks, fluorescence imaging, microstructure characterization, construction and calibration of magnetic tweezers devices, and mechanical data collection and analysis. In particular, we present the design and assembly of three neodymium iron boron (NdFeB)-based magnetic tweezers devices optimized for use with MT networks: (1) high-force magnetic tweezers devices that enable the application of nano-Newton forces and possible meso- to macroscale materials characterization; (2) ring-shaped NdFeB-based magnetic tweezers devices that enable oscillatory microrheology measurements; and (3) portable magnetic tweezers devices that enable direct visualization of microscale deformation in soft materials under applied force. Copyright © 2013 Elsevier Inc. All rights reserved.

  15. A Glider-Assisted Link Disruption Restoration Mechanism in Underwater Acoustic Sensor Networks

    Directory of Open Access Journals (Sweden)

    Zhigang Jin

    2018-02-01

    Full Text Available Underwater acoustic sensor networks (UASNs have become a hot research topic. In UASNs, nodes can be affected by ocean currents and external forces, which could result in sudden link disruption. Therefore, designing a flexible and efficient link disruption restoration mechanism to ensure the network connectivity is a challenge. In the paper, we propose a glider-assisted restoration mechanism which includes link disruption recognition and related link restoring mechanism. In the link disruption recognition mechanism, the cluster heads collect the link disruption information and then schedule gliders acting as relay nodes to restore the disrupted link. Considering the glider’s sawtooth motion, we design a relay location optimization algorithm with a consideration of both the glider’s trajectory and acoustic channel attenuation model. The utility function is established by minimizing the channel attenuation and the optimal location of glider is solved by a multiplier method. The glider-assisted restoration mechanism can greatly improve the packet delivery rate and reduce the communication energy consumption and it is more general for the restoration of different link disruption scenarios. The simulation results show that glider-assisted restoration mechanism can improve the delivery rate of data packets by 15–33% compared with cooperative opportunistic routing (OVAR, the hop-by-hop vector-based forwarding (HH-VBF and the vector based forward (VBF methods, and reduce communication energy consumption by 20–58% for a typical network’s setting.

  16. Implementation and Evaluation of Multichannel Multi-Interface Routing Mechanism with QoS-Consideration for Ad-Hoc Networks

    Directory of Open Access Journals (Sweden)

    Satoh Hiroki

    2010-01-01

    Full Text Available To accommodate real-time multimedia application while satisfying application-level QoS requirements in a wireless ad-hoc network, we need QoS control mechanisms. We proposed a new routing mechanism for a wireless ad-hoc network composed of nodes equipped with multiple network interfaces. By embedding information about channel usage in control messages of OLSRv2, each node obtains a view of topology and bandwidth information of the whole network. Based on the obtained information, a source node determines a logical path with the maximum available bandwidth to satisfy application-level QoS requirements. In this paper, we evaluated feasibility of the proposal through simulation and practical experiments and confirmed that our proposal effectively transferred multimedia packets over a logical path avoiding congested links. The load on a network is well distributed and the network can accommodate more sessions than OLSRv2 and QOLSR.

  17. Quantum mechanical streamlines. I - Square potential barrier

    Science.gov (United States)

    Hirschfelder, J. O.; Christoph, A. C.; Palke, W. E.

    1974-01-01

    Exact numerical calculations are made for scattering of quantum mechanical particles hitting a square two-dimensional potential barrier (an exact analog of the Goos-Haenchen optical experiments). Quantum mechanical streamlines are plotted and found to be smooth and continuous, to have continuous first derivatives even through the classical forbidden region, and to form quantized vortices around each of the nodal points. A comparison is made between the present numerical calculations and the stationary wave approximation, and good agreement is found between both the Goos-Haenchen shifts and the reflection coefficients. The time-independent Schroedinger equation for real wavefunctions is reduced to solving a nonlinear first-order partial differential equation, leading to a generalization of the Prager-Hirschfelder perturbation scheme. Implications of the hydrodynamical formulation of quantum mechanics are discussed, and cases are cited where quantum and classical mechanical motions are identical.

  18. Deciphering deterioration mechanisms of complex diseases based on the construction of dynamic networks and systems analysis

    Science.gov (United States)

    Li, Yuanyuan; Jin, Suoqin; Lei, Lei; Pan, Zishu; Zou, Xiufen

    2015-03-01

    The early diagnosis and investigation of the pathogenic mechanisms of complex diseases are the most challenging problems in the fields of biology and medicine. Network-based systems biology is an important technique for the study of complex diseases. The present study constructed dynamic protein-protein interaction (PPI) networks to identify dynamical network biomarkers (DNBs) and analyze the underlying mechanisms of complex diseases from a systems level. We developed a model-based framework for the construction of a series of time-sequenced networks by integrating high-throughput gene expression data into PPI data. By combining the dynamic networks and molecular modules, we identified significant DNBs for four complex diseases, including influenza caused by either H3N2 or H1N1, acute lung injury and type 2 diabetes mellitus, which can serve as warning signals for disease deterioration. Function and pathway analyses revealed that the identified DNBs were significantly enriched during key events in early disease development. Correlation and information flow analyses revealed that DNBs effectively discriminated between different disease processes and that dysfunctional regulation and disproportional information flow may contribute to the increased disease severity. This study provides a general paradigm for revealing the deterioration mechanisms of complex diseases and offers new insights into their early diagnoses.

  19. Prediction of mechanical properties of a warm compacted molybdenum prealloy using artificial neural network and adaptive neuro-fuzzy models

    International Nuclear Information System (INIS)

    Zare, Mansour; Vahdati Khaki, Jalil

    2012-01-01

    Highlights: ► ANNs and ANFIS fairly predicted UTS and YS of warm compacted molybdenum prealloy. ► Effects of composition, temperature, compaction pressure on output were studied. ► ANFIS model was in better agreement with experimental data from published article. ► Sintering temperature had the most significant effect on UTS and YS. -- Abstract: Predictive models using artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) were successfully developed to predict yield strength and ultimate tensile strength of warm compacted 0.85 wt.% molybdenum prealloy samples. To construct these models, 48 different experimental data were gathered from the literature. A portion of the data set was randomly chosen to train both ANN with back propagation (BP) learning algorithm and ANFIS model with Gaussian membership function and the rest was implemented to verify the performance of the trained network against the unseen data. The generalization capability of the networks was also evaluated by applying new input data within the domain covered by the training pattern. To compare the obtained results, coefficient of determination (R 2 ), root mean squared error (RMSE) and average absolute error (AAE) indexes were chosen and calculated for both of the models. The results showed that artificial neural network and adaptive neuro-fuzzy system were both potentially strong for prediction of the mechanical properties of warm compacted 0.85 wt.% molybdenum prealloy; however, the proposed ANFIS showed better performance than the ANN model. Also, the ANFIS model was subjected to a sensitivity analysis to find the significant inputs affecting mechanical properties of the samples.

  20. Distributed controller clustering in software defined networks.

    Directory of Open Access Journals (Sweden)

    Ahmed Abdelaziz

    Full Text Available Software Defined Networking (SDN is an emerging promising paradigm for network management because of its centralized network intelligence. However, the centralized control architecture of the software-defined networks (SDNs brings novel challenges of reliability, scalability, fault tolerance and interoperability. In this paper, we proposed a novel clustered distributed controller architecture in the real setting of SDNs. The distributed cluster implementation comprises of multiple popular SDN controllers. The proposed mechanism is evaluated using a real world network topology running on top of an emulated SDN environment. The result shows that the proposed distributed controller clustering mechanism is able to significantly reduce the average latency from 8.1% to 1.6%, the packet loss from 5.22% to 4.15%, compared to distributed controller without clustering running on HP Virtual Application Network (VAN SDN and Open Network Operating System (ONOS controllers respectively. Moreover, proposed method also shows reasonable CPU utilization results. Furthermore, the proposed mechanism makes possible to handle unexpected load fluctuations while maintaining a continuous network operation, even when there is a controller failure. The paper is a potential contribution stepping towards addressing the issues of reliability, scalability, fault tolerance, and inter-operability.

  1. Distributed controller clustering in software defined networks.

    Science.gov (United States)

    Abdelaziz, Ahmed; Fong, Ang Tan; Gani, Abdullah; Garba, Usman; Khan, Suleman; Akhunzada, Adnan; Talebian, Hamid; Choo, Kim-Kwang Raymond

    2017-01-01

    Software Defined Networking (SDN) is an emerging promising paradigm for network management because of its centralized network intelligence. However, the centralized control architecture of the software-defined networks (SDNs) brings novel challenges of reliability, scalability, fault tolerance and interoperability. In this paper, we proposed a novel clustered distributed controller architecture in the real setting of SDNs. The distributed cluster implementation comprises of multiple popular SDN controllers. The proposed mechanism is evaluated using a real world network topology running on top of an emulated SDN environment. The result shows that the proposed distributed controller clustering mechanism is able to significantly reduce the average latency from 8.1% to 1.6%, the packet loss from 5.22% to 4.15%, compared to distributed controller without clustering running on HP Virtual Application Network (VAN) SDN and Open Network Operating System (ONOS) controllers respectively. Moreover, proposed method also shows reasonable CPU utilization results. Furthermore, the proposed mechanism makes possible to handle unexpected load fluctuations while maintaining a continuous network operation, even when there is a controller failure. The paper is a potential contribution stepping towards addressing the issues of reliability, scalability, fault tolerance, and inter-operability.

  2. An energy saving mechanism of EPON networks for real time video transmission

    Science.gov (United States)

    Liu, Chien-Ping; Wu, Ho-Ting; Chiang, Yun-Ting; Chien, Shieh-Chieh; Ke, Kai-Wei

    2015-07-01

    Modern access networks are constructed widely by passive optical networks (PONs) to meet the growing bandwidth demand. However, higher bandwidth means more energy consumption. To save energy, a few research works propose the dual-mode energy saving mechanism that allows the ONU to operate between active and sleep modes periodically. However, such dual-mode energy saving design may induce unnecessary power consumption or packet delay increase in the case where only downstream data exist for most of the time. In this paper, we propose a new tri-mode energy saving scheme for Ethernet PON (EPON). The new tri-mode energy saving design, combining the dual-mode saving mechanism with the doze mode, allows the ONU to switch among these three modes alternatively. In the doze mode, the ONU may receive downstream data while keeping its transmitter close. Such scenario is often observed for real time video downstream transmission. Furthermore, the low packet delay of high priority upstream data can be attained through the use of early wake-up mechanism employed in both energy saving modes. The energy saving and system efficiency can thus be achieved jointly while maintaining the differentiated QoS for data with various priorities. Performance results via simulation have demonstrated the effectiveness of such mechanism.

  3. Self-organization in multilayer network with adaptation mechanisms based on competition

    Science.gov (United States)

    Pitsik, Elena N.; Makarov, Vladimir V.; Nedaivozov, Vladimir O.; Kirsanov, Daniil V.; Goremyko, Mikhail V.

    2018-04-01

    The paper considers the phenomena of competition in multiplex network whose structure evolves corresponding to dynamics of it's elements, forming closed loop of self-learning with the aim to reach the optimal topology. Numerical analysis of proposed model shows that it is possible to obtain scale-invariant structures for corresponding parameters as well as the structures with homogeneous distribution of connections in the layers. Revealed phenomena emerges as the consequence of the self-organization processes related to structure-dynamical selflearning based on homeostasis and homophily, as well as the result of the competition between the network's layers for optimal topology. It was shown that in the mode of partial and cluster synchronization the network reaches scale-free topology of complex nature that is different from layer to layer. However, in the mode of global synchronization the homogeneous topologies on all layer of the network are observed. This phenomenon is tightly connected with the competitive processes that represent themselves as the natural mechanism of reaching the optimal topology of the links in variety of real-world systems.

  4. A New Mechanism for Network Monitoring and Shielding in Wireless LAN

    Directory of Open Access Journals (Sweden)

    Jiujun Cheng

    2014-01-01

    Full Text Available Wireless LAN (WLAN technology is developing rapidly with the help of wireless communication technology and social demand. During the development of WLAN, the security is more and more important, and wireless monitoring and shielding are of prime importance for network security. In this paper, we have explored various security issues of IEEE 802.11 based wireless network and analyzed numerous problems in implementing the wireless monitoring and shielding system. We identify the challenges which monitoring and shielding system needs to be aware of, and then provide a feasible mechanism to avoid those challenges. We implemented an actual wireless LAN monitoring and shielding system on Maemo operating system to monitor wireless network data stream efficiently and solve the security problems of mobile users. More importantly, the system analyzes wireless network protocols efficiently and flexibly, reveals rich information of the IEEE 802.11 protocol such as traffic distribution and different IP connections, and graphically displays later. Moreover, the system running results show that the system has the capability to work stably, and accurately and analyze the wireless protocols efficiently.

  5. The study of diffusion mechanism in network-forming liquid: Silica liquid

    Directory of Open Access Journals (Sweden)

    P. K. Hung

    2016-12-01

    Full Text Available Molecular dynamics simulation is employed to investigate the diffusion mechanism in silica melt, a typical network-forming liquid. From the analysis of SiOx→SiOx±1 and OSiy→OSiy±1 reactions we reveal two moving modes: fast hopping and slow collective moving. Accordingly the atoms diffuse in the melt by simple hopping or through displacing of super-molecule (SM. A cluster analysis is performed for several of atom sets. It is shown that the melt exhibits non-uniform spatial distribution of reaction which causes the dynamics heterogeneity (DH. Further, the network structure of the melt consists of main subnet and large defective subnets. These subnets differ strongly in local environment, chemical composition and atomic density. This result evidences two distinct phases, the structure heterogeneity in silica melt and supports the polymorphism of network-forming liquid. We also find out that the node transformation spreads non-uniformly through the network structure. It takes place mainly in large defective subnet. The strong localization of node transformation is responsible for dynamical slowdown.

  6. Low Complexity Signed Response Based Sybil Attack Detection Mechanism in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    M. Saud Khan

    2016-01-01

    Full Text Available Security is always a major concern in wireless sensor networks (WSNs. Identity based attacks such as spoofing and sybil not only compromise the network but also slow down its performance. This paper proposes a low complexity sybil attack detection scheme, that is, based on signed response (SRES authentication mechanism developed for Global System for Mobile (GSM communications. A probabilistic model is presented which analyzes the proposed authentication mechanism for its probability of sybil attack. The paper also presents a simulation based comparative analysis of the existing sybil attack schemes with respect to the proposed scheme. It is observed that the proposed sybil detection scheme exhibits lesser computational cost and power consumption as compared to the existing schemes for the same sybil detection performance.

  7. Improving the gaussian effective potential: quantum mechanics

    International Nuclear Information System (INIS)

    Eboli, O.J.P.; Thomaz, M.T.; Lemos, N.A.

    1990-08-01

    In order to gain intuition for variational problems in field theory, we analyze variationally the quantum-mechanical anharmonic oscillator [(V(x)sup(k) - sub(2) x sup(2) + sup(λ) - sub(4) λ sup(4)]. Special attention is paid to improvements to the Gaussian effective potential. (author)

  8. The Potential Role of Direct and Indirect Contacts on Infection Spread in Dairy Farm Networks.

    Directory of Open Access Journals (Sweden)

    Gianluigi Rossi

    2017-01-01

    Full Text Available Animals' exchanges are considered the most effective route of between-farm infectious disease transmission. However, despite being often overlooked, the infection spread due to contaminated equipment, vehicles, or personnel proved to be important for several livestock epidemics. This study investigated the role of indirect contacts in a potential infection spread in the dairy farm network of the Province of Parma (Northern Italy. We built between-farm contact networks using data on cattle exchange (direct contacts, and on-farm visits by veterinarians (indirect contacts. We compared the features of the contact structures by using measures on static and temporal networks. We assessed the disease spreading potential of the direct and indirect network structures in the farm system by using data on the infection state of farms by paratuberculosis. Direct and indirect networks showed non-trivial differences with respect to connectivity, contact distribution, and super-spreaders identification. Furthermore, our analyses on paratuberculosis data suggested that the contributions of direct and indirect contacts on diseases spread are apparent at different spatial scales. Our results highlighted the potential role of indirect contacts in between-farm disease spread and underlined the need for a deeper understanding of these contacts to develop better strategies for prevention of livestock epidemics.

  9. A systemic method for evaluating the potential impacts of floods on network infrastructures

    Directory of Open Access Journals (Sweden)

    J. Eleutério

    2013-04-01

    Full Text Available Understanding network infrastructures and their operation under exceptional circumstances is fundamental for dealing with flood risks and improving the resilience of a territory. This work presents a method for evaluating potential network infrastructure dysfunctions and damage in cases of flooding. In contrast to existing approaches, this method analyses network infrastructures on an elementary scale, by considering networks as a group of elements with specific functions and individual vulnerabilities. Our analysis places assets at the centre of the evaluation process, resulting in the construction of damage-dysfunction matrices based on expert interviews. These matrices permit summarising the different vulnerabilities of network infrastructures, describing how the different components are linked to each other and how they can disrupt the operation of the network. They also identify the actions and resources needed to restore the system to operational status following damage and dysfunctions, an essential point when dealing with the question of resilience. The method promotes multi-network analyses and is illustrated by a French case study. Sixty network experts were interviewed during the analysis of the following networks: drinking water supply, waste water, public lighting, gas distribution and electricity supply.

  10. Ab initio Algorithmic Causal Deconvolution of Intertwined Programs and Networks by Generative Mechanism

    KAUST Repository

    Zenil, Hector

    2018-02-18

    To extract and learn representations leading to generative mechanisms from data, especially without making arbitrary decisions and biased assumptions, is a central challenge in most areas of scientific research particularly in connection to current major limitations of influential topics and methods of machine and deep learning as they have often lost sight of the model component. Complex data is usually produced by interacting sources with different mechanisms. Here we introduce a parameter-free model-based approach, based upon the seminal concept of Algorithmic Probability, that decomposes an observation and signal into its most likely algorithmic generative mechanisms. Our methods use a causal calculus to infer model representations. We demonstrate the method ability to distinguish interacting mechanisms and deconvolve them, regardless of whether the objects produce strings, space-time evolution diagrams, images or networks. We numerically test and evaluate our method and find that it can disentangle observations from discrete dynamic systems, random and complex networks. We think that these causal inference techniques can contribute as key pieces of information for estimations of probability distributions complementing other more statistical-oriented techniques that otherwise lack model inference capabilities.

  11. Potential of commercial microwave link network derived rainfall for river runoff simulations

    Science.gov (United States)

    Smiatek, Gerhard; Keis, Felix; Chwala, Christian; Fersch, Benjamin; Kunstmann, Harald

    2017-03-01

    Commercial microwave link networks allow for the quantification of path integrated precipitation because the attenuation by hydrometeors correlates with rainfall between transmitter and receiver stations. The networks, operated and maintained by cellphone companies, thereby provide completely new and country wide precipitation measurements. As the density of traditional precipitation station networks worldwide is significantly decreasing, microwave link derived precipitation estimates receive increasing attention not only by hydrologists but also by meteorological and hydrological services. We investigate the potential of microwave derived precipitation estimates for streamflow prediction and water balance analyses, exemplarily shown for an orographically complex region in the German Alps (River Ammer). We investigate the additional value of link derived rainfall estimations combined with station observations compared to station and weather radar derived values. Our river runoff simulation system employs a distributed hydrological model at 100 × 100 m grid resolution. We analyze the potential of microwave link derived precipitation estimates for two episodes of 30 days with typically moderate river flow and an episode of extreme flooding. The simulation results indicate the potential of this novel precipitation monitoring method: a significant improvement in hydrograph reproduction has been achieved in the extreme flooding period that was characterized by a large number of local strong precipitation events. The present rainfall monitoring gauges alone were not able to correctly capture these events.

  12. Students' Conceptual Difficulties in Quantum Mechanics: Potential Well Problems

    Science.gov (United States)

    Ozcan, Ozgur; Didis, Nilufer; Tasar, Mehmet Fatih

    2009-01-01

    In this study, students' conceptual difficulties about some basic concepts in quantum mechanics like one-dimensional potential well problems and probability density of tunneling particles were identified. For this aim, a multiple choice instrument named Quantum Mechanics Conceptual Test has been developed by one of the researchers of this study…

  13. Supersymmetric quantum mechanics and higher excited states of a non-polynomial potential

    International Nuclear Information System (INIS)

    Drigo Filho, E.; Ricotta, R.M.

    1989-03-01

    Supersymmetric quantum mechanics is used to evaluate new excited states of a non-polynomial potential. This illustrates a method of evaluating higher excited states of quantum mechanical potentials. (A.C.A.S.) [pt

  14. Low and High-Frequency Field Potentials of Cortical Networks ...

    Science.gov (United States)

    Neural networks grown on microelectrode arrays (MEAs) have become an important, high content in vitro assay for assessing neuronal function. MEA experiments typically examine high- frequency (HF) (>200 Hz) spikes, and bursts which can be used to discriminate between different pharmacological agents/chemicals. However, normal brain activity is additionally composed of integrated low-frequency (0.5-100 Hz) field potentials (LFPs) which are filtered out of MEA recordings. The objective of this study was to characterize the relationship between HF and LFP neural network signals, and to assess the relative sensitivity of LFPs to selected neurotoxicants. Rat primary cortical cultures were grown on glass, single-well MEA chips. Spontaneous activity was sampled at 25 kHz and recorded (5 min) (Multi-Channel Systems) from mature networks (14 days in vitro). HF (spike, mean firing rate, MFR) and LF (power spectrum, amplitude) components were extracted from each network and served as its baseline (BL). Next, each chip was treated with either 1) a positive control, bicuculline (BIC, 25μM) or domoic acid (DA, 0.3μM), 2) or a negative control, acetaminophen (ACE, 100μM) or glyphosate (GLY, 100μM), 3) a solvent control (H2O or DMSO:EtOH), or 4) a neurotoxicant, (carbaryl, CAR 5, 30μM ; lindane, LIN 1, 10μM; permethrin, PERM 25, 50μM; triadimefon, TRI 5, 65μM). Post treatment, 5 mins of spontaneous activity was recorded and analyzed. As expected posit

  15. Mechanics of anisotropic spring networks.

    Science.gov (United States)

    Zhang, T; Schwarz, J M; Das, Moumita

    2014-12-01

    We construct and analyze a model for a disordered linear spring network with anisotropy. The modeling is motivated by, for example, granular systems, nematic elastomers, and ultimately cytoskeletal networks exhibiting some underlying anisotropy. The model consists of a triangular lattice with two different bond occupation probabilities, p(x) and p(y), for the linear springs. We develop an effective medium theory (EMT) to describe the network elasticity as a function of p(x) and p(y). We find that the onset of rigidity in the EMT agrees with Maxwell constraint counting. We also find beyond linear behavior in the shear and bulk modulus as a function of occupation probability in the rigid phase for small strains, which differs from the isotropic case. We compare our EMT with numerical simulations to find rather good agreement. Finally, we discuss the implications of extending the reach of effective medium theory as well as draw connections with prior work on both anisotropic and isotropic spring networks.

  16. Clastic polygonal networks around Lyot crater, Mars: Possible formation mechanisms from morphometric analysis

    Science.gov (United States)

    Brooker, L. M.; Balme, M. R.; Conway, S. J.; Hagermann, A.; Barrett, A. M.; Collins, G. S.; Soare, R. J.

    2018-03-01

    Polygonal networks of patterned ground are a common feature in cold-climate environments. They can form through the thermal contraction of ice-cemented sediment (i.e. formed from fractures), or the freezing and thawing of ground ice (i.e. formed by patterns of clasts, or ground deformation). The characteristics of these landforms provide information about environmental conditions. Analogous polygonal forms have been observed on Mars leading to inferences about environmental conditions. We have identified clastic polygonal features located around Lyot crater, Mars (50°N, 30°E). These polygons are unusually large (>100 m diameter) compared to terrestrial clastic polygons, and contain very large clasts, some of which are up to 15 metres in diameter. The polygons are distributed in a wide arc around the eastern side of Lyot crater, at a consistent distance from the crater rim. Using high-resolution imaging data, we digitised these features to extract morphological information. These data are compared to existing terrestrial and Martian polygon data to look for similarities and differences and to inform hypotheses concerning possible formation mechanisms. Our results show the clastic polygons do not have any morphometric features that indicate they are similar to terrestrial sorted, clastic polygons formed by freeze-thaw processes. They are too large, do not show the expected variation in form with slope, and have clasts that do not scale in size with polygon diameter. However, the clastic networks are similar in network morphology to thermal contraction cracks, and there is a potential direct Martian analogue in a sub-type of thermal contraction polygons located in Utopia Planitia. Based upon our observations, we reject the hypothesis that polygons located around Lyot formed as freeze-thaw polygons and instead an alternative mechanism is put forward: they result from the infilling of earlier thermal contraction cracks by wind-blown material, which then became

  17. Complete Neuron-Astrocyte Interaction Model: Digital Multiplierless Design and Networking Mechanism.

    Science.gov (United States)

    Haghiri, Saeed; Ahmadi, Arash; Saif, Mehrdad

    2017-02-01

    Glial cells, also known as neuroglia or glia, are non-neuronal cells providing support and protection for neurons in the central nervous system (CNS). They also act as supportive cells in the brain. Among a variety of glial cells, the star-shaped glial cells, i.e., astrocytes, are the largest cell population in the brain. The important role of astrocyte such as neuronal synchronization, synaptic information regulation, feedback to neural activity and extracellular regulation make the astrocytes play a vital role in brain disease. This paper presents a modified complete neuron-astrocyte interaction model that is more suitable for efficient and large scale biological neural network realization on digital platforms. Simulation results show that the modified complete interaction model can reproduce biological-like behavior of the original neuron-astrocyte mechanism. The modified interaction model is investigated in terms of digital realization feasibility and cost targeting a low cost hardware implementation. Networking behavior of this interaction is investigated and compared between two cases: i) the neuron spiking mechanism without astrocyte effects, and ii) the effect of astrocyte in regulating the neurons behavior and synaptic transmission via controlling the LTP and LTD processes. Hardware implementation on FPGA shows that the modified model mimics the main mechanism of neuron-astrocyte communication with higher performance and considerably lower hardware overhead cost compared with the original interaction model.

  18. Neural Network Models of Simple Mechanical Systems Illustrating the Feasibility of Accelerated Life Testing

    Science.gov (United States)

    Fusaro, Robert L.; Jones, Steven P.; Jansen, Ralph

    1996-01-01

    A complete evaluation of the tribological characteristics of a given material/mechanical system is a time-consuming operation since the friction and wear process is extremely systems sensitive. As a result, experimental designs (i.e., Latin Square, Taguchi) have been implemented in an attempt to not only reduce the total number of experimental combinations needed to fully characterize a material/mechanical system, but also to acquire life data for a system without having to perform an actual life test. Unfortunately, these experimental designs still require a great deal of experimental testing and the output does not always produce meaningful information. In order to further reduce the amount of experimental testing required, this study employs a computer neural network model to investigate different material/mechanical systems. The work focuses on the modeling of the wear behavior, while showing the feasibility of using neural networks to predict life data. The model is capable of defining which input variables will influence the tribological behavior of the particular material/mechanical system being studied based on the specifications of the overall system.

  19. A Mobility-Aware Link Enhancement Mechanism for Vehicular Ad Hoc Networks

    Directory of Open Access Journals (Sweden)

    Kai-Wen Hu

    2008-04-01

    Full Text Available With the growth up of internet in mobile commerce, researchers have reproduced various mobile applications that vary from entertainment and commercial services to diagnostic and safety tools. Mobility management has widely been recognized as one of the most challenging problems for seamless access to wireless networks. In this paper, a novel link enhancement mechanism is proposed to deal with mobility management problem in vehicular ad hoc networks. Two machine learning techniques, namely, particle swarm optimization and fuzzy logic systems, are incorporated into the proposed schemes to enhance the accuracy of prediction of link break and congestion occurrence. The experimental results verify the effectiveness and feasibility of the proposed schemes.

  20. A Mobility-Aware Link Enhancement Mechanism for Vehicular Ad Hoc Networks

    Directory of Open Access Journals (Sweden)

    Huang Chenn-Jung

    2008-01-01

    Full Text Available Abstract With the growth up of internet in mobile commerce, researchers have reproduced various mobile applications that vary from entertainment and commercial services to diagnostic and safety tools. Mobility management has widely been recognized as one of the most challenging problems for seamless access to wireless networks. In this paper, a novel link enhancement mechanism is proposed to deal with mobility management problem in vehicular ad hoc networks. Two machine learning techniques, namely, particle swarm optimization and fuzzy logic systems, are incorporated into the proposed schemes to enhance the accuracy of prediction of link break and congestion occurrence. The experimental results verify the effectiveness and feasibility of the proposed schemes.

  1. Potential usefulness of an artificial neural network for assessing ventricular size

    International Nuclear Information System (INIS)

    Fukuda, Haruyuki; Nakajima, Hideyuki; Usuki, Noriaki; Saiwai, Shigeo; Miyamoto, Takeshi; Inoue, Yuichi; Onoyama, Yasuto.

    1995-01-01

    An artificial neural network approach was applied to assess ventricular size from computed tomograms. Three layer, feed-forward neural networks with a back propagation algorithm were designed to distinguish between three degree of enlargement of the ventricles on the basis of patient's age and six items of computed tomographic information. Data for training and testing the neural network were created with computed tomograms of the brains selected at random from daily examinations. Four radiologists decided by mutual consent subjectively based on their experience whether the ventricles were within normal limits, slightly enlarged, or enlarged for the patient's age. The data for training was obtained from 38 patients. The data for testing was obtained from 47 other patients. The performance of the neural network trained using the data for training was evaluated by the rate of correct answers to the data for testing. The valid solution ratio to response of the test data obtained from the trained neural networks was more than 90% for all conditions in this study. The solutions were completely valid in the neural networks with two or three units at the hidden layer with 2,200 learning iterations, and with two units at the hidden layer with 11,000 learning iterations. The squared error decreased remarkably in the range from 0 to 500 learning iterations, and was close to a contrast over two thousand learning iterations. The neural network with a hidden layer having two or three units showed high decision performance. The preliminary results strongly suggest that the neural network approach has potential utility in computer-aided estimation of enlargement of the ventricles. (author)

  2. Hippocampal network activity is transiently altered by induction of long-term potentiation in the dentate gyrus of freely behaving rats

    Directory of Open Access Journals (Sweden)

    Arthur Bikbaev

    2007-12-01

    Full Text Available A role for oscillatory activity in hippocampal neuronal networks has been proposed in sensory encoding, cognitive functions and synaptic plasticity. In the hippocampus, theta (5–10 Hz and gamma (30–100 Hz oscillations may provide a mechanism for temporal encoding of information, and the basis for formation and retrieval of memory traces. Long-term potentiation (LTP of synaptic transmission, a candidate cellular model of synaptic information storage, is typically induced by high-frequency tetanisation (HFT of afferent pathways. Taking into account the role of oscillatory activity in the processing of information, dynamic changes may occur in hippocampal network activity in the period during HFT and/or soon after it. These changes in rhythmic activity may determine or, at least, contribute to successful potentiation and, in general, to formation of memory. We have found that short-term potentiation (STP and LTP as well LTPfailure are characterised with different profiles of changes in theta and gamma frequencies. Potentiation of synaptic transmission was associated with a significant increase in the relative theta power and mean amplitude of theta cycles in the period encompassing 300 seconds after HFT. Where LTP or STP, but not failure of potentiation, occurred, this facilitation of theta was accompanied by transient increases in gamma power and in the mean amplitude of gamma oscillations within a single theta cycle. Our data support that specific, correlated changes in these parameters are associated with successful synaptic potentiation. These findings suggest that changes in theta-gamma activity associated with induction of LTP may enable synaptic information storage in the hippocampus.

  3. Improving network management with Software Defined Networking

    International Nuclear Information System (INIS)

    Dzhunev, Pavel

    2013-01-01

    Software-defined networking (SDN) is developed as an alternative to closed networks in centers for data processing by providing a means to separate the control layer data layer switches, and routers. SDN introduces new possibilities for network management and configuration methods. In this article, we identify problems with the current state-of-the-art network configuration and management mechanisms and introduce mechanisms to improve various aspects of network management

  4. Self-isospectral periodic potentials and supersymmetric quantum mechanics

    International Nuclear Information System (INIS)

    Dunne, G.; Feinberg, J.

    1998-01-01

    We discuss supersymmetric quantum mechanical models with periodic potentials. The important new feature is that it is possible for both isospectral potentials to support zero modes, in contrast with the standard nonperiodic case where either one or neither (but not both) of the isospectral pair has a zero mode. Thus it is possible to have supersymmetry unbroken and yet also have a vanishing Witten index. We present some explicit exactly soluble examples for which the isospectral potentials have identical band spectra, and which are open-quotes self-isospectralclose quotes in the sense that the potentials have identical shape, but are translated by one half-period relative to one another. copyright 1997 The American Physical Society

  5. Wood Modification at High Temperature and Pressurized Steam: a Relational Model of Mechanical Properties Based on a Neural Network

    Directory of Open Access Journals (Sweden)

    Hong Yang

    2015-07-01

    Full Text Available Thermally modified wood has high dimensional stability and biological durability.But if the process parameters of thermal modification are not appropriate, then there will be a decline in the physical properties of wood.A neural network algorithm was employed in this study to establish the relationship between the process parameters of high-temperature and high-pressure thermal modification and the mechanical properties of the wood. Three important parameters: temperature, relative humidity, and treatment time, were considered as the inputs to the neural network. Back propagation (BP neural network and radial basis function (RBF neural network models for prediction were built and compared. The comparison showed that the RBF neural network model had advantages in network structure, convergence speed, and generalization capacity. On this basis, the inverse model, reflecting the relationship between the process parameters and the mechanical properties of wood, was established. Given the desired mechanical properties of the wood, the thermal modification process parameters could be inversely optimized and predicted. The results indicated that the model has good learning ability and generalization capacity. This is of great importance for the theoretical and applicational studies of the thermal modification of wood.

  6. Modelling of solar energy potential in Nigeria using an artificial neural network model

    International Nuclear Information System (INIS)

    Fadare, D.A.

    2009-01-01

    In this study, an artificial neural network (ANN) based model for prediction of solar energy potential in Nigeria (lat. 4-14 o N, log. 2-15 o E) was developed. Standard multilayered, feed-forward, back-propagation neural networks with different architecture were designed using neural toolbox for MATLAB. Geographical and meteorological data of 195 cities in Nigeria for period of 10 years (1983-1993) from the NASA geo-satellite database were used for the training and testing the network. Meteorological and geographical data (latitude, longitude, altitude, month, mean sunshine duration, mean temperature, and relative humidity) were used as inputs to the network, while the solar radiation intensity was used as the output of the network. The results show that the correlation coefficients between the ANN predictions and actual mean monthly global solar radiation intensities for training and testing datasets were higher than 90%, thus suggesting a high reliability of the model for evaluation of solar radiation in locations where solar radiation data are not available. The predicted solar radiation values from the model were given in form of monthly maps. The monthly mean solar radiation potential in northern and southern regions ranged from 7.01-5.62 to 5.43-3.54 kW h/m 2 day, respectively. A graphical user interface (GUI) was developed for the application of the model. The model can be used easily for estimation of solar radiation for preliminary design of solar applications.

  7. Maximum flow approach to prioritize potential drug targets of Mycobacterium tuberculosis H37Rv from protein-protein interaction network.

    Science.gov (United States)

    Melak, Tilahun; Gakkhar, Sunita

    2015-12-01

    In spite of the implementations of several strategies, tuberculosis (TB) is overwhelmingly a serious global public health problem causing millions of infections and deaths every year. This is mainly due to the emergence of drug-resistance varieties of TB. The current treatment strategies for the drug-resistance TB are of longer duration, more expensive and have side effects. This highlights the importance of identification and prioritization of targets for new drugs. This study has been carried out to prioritize potential drug targets of Mycobacterium tuberculosis H37Rv based on their flow to resistance genes. The weighted proteome interaction network of the pathogen was constructed using a dataset from STRING database. Only a subset of the dataset with interactions that have a combined score value ≥770 was considered. Maximum flow approach has been used to prioritize potential drug targets. The potential drug targets were obtained through comparative genome and network centrality analysis. The curated set of resistance genes was retrieved from literatures. Detail literature review and additional assessment of the method were also carried out for validation. A list of 537 proteins which are essential to the pathogen and non-homologous with human was obtained from the comparative genome analysis. Through network centrality measures, 131 of them were found within the close neighborhood of the centre of gravity of the proteome network. These proteins were further prioritized based on their maximum flow value to resistance genes and they are proposed as reliable drug targets of the pathogen. Proteins which interact with the host were also identified in order to understand the infection mechanism. Potential drug targets of Mycobacterium tuberculosis H37Rv were successfully prioritized based on their flow to resistance genes of existing drugs which is believed to increase the druggability of the targets since inhibition of a protein that has a maximum flow to

  8. A neural-network potential through charge equilibration for WS2: From clusters to sheets

    Science.gov (United States)

    Hafizi, Roohollah; Ghasemi, S. Alireza; Hashemifar, S. Javad; Akbarzadeh, Hadi

    2017-12-01

    In the present work, we use a machine learning method to construct a high-dimensional potential for tungsten disulfide using a charge equilibration neural-network technique. A training set of stoichiometric WS2 clusters is prepared in the framework of density functional theory. After training the neural-network potential, the reliability and transferability of the potential are verified by performing a crystal structure search on bulk phases of WS2 and by plotting energy-area curves of two different monolayers. Then, we use the potential to investigate various triangular nano-clusters and nanotubes of WS2. In the case of nano-structures, we argue that 2H atomic configurations with sulfur rich edges are thermodynamically more stable than the other investigated configurations. We also studied a number of WS2 nanotubes which revealed that 1T tubes with armchair chirality exhibit lower bending stiffness.

  9. Early stiffening and softening of collagen : interplay of deformation mechanisms in biopolymer networks

    NARCIS (Netherlands)

    Kurniawan, N.A.; Wong, Long Hui; Rajagopalan, Raj

    2012-01-01

    Collagen networks, the main structural/mechanical elements in biological tissues, increasingly serve as biomimetic scaffolds for cell behavioral studies, assays, and tissue engineering, and yet their full spectrum of nonlinear behavior remains unclear. Here, with self-assembled type-I collagen as

  10. Neural network approach in multichannel auditory event-related potential analysis.

    Science.gov (United States)

    Wu, F Y; Slater, J D; Ramsay, R E

    1994-04-01

    Even though there are presently no clearly defined criteria for the assessment of P300 event-related potential (ERP) abnormality, it is strongly indicated through statistical analysis that such criteria exist for classifying control subjects and patients with diseases resulting in neuropsychological impairment such as multiple sclerosis (MS). We have demonstrated the feasibility of artificial neural network (ANN) methods in classifying ERP waveforms measured at a single channel (Cz) from control subjects and MS patients. In this paper, we report the results of multichannel ERP analysis and a modified network analysis methodology to enhance automation of the classification rule extraction process. The proposed methodology significantly reduces the work of statistical analysis. It also helps to standardize the criteria of P300 ERP assessment and facilitate the computer-aided analysis on neuropsychological functions.

  11. Solar Energy Potential Estimation in Perak Using Clearness Index and Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Assadi Morteza Khalaji

    2014-07-01

    Full Text Available In this paper solar energy potential has been estimated by two methods which are clearness index and artificial network (ANN methods. The selected region is Seri Iskandar, Perak (4°24´latitude, 100°58´E longitude, 24 m altitude. Experimental data (monthly average daily radiation on horizontal surface was obtained from UTP solar research site in UTP campus. The data include the period of 2010 to 2012 and were used for testing the artificial neural network model and also for determination of clearness index. Also the experimental data of the three meteorological, Ipoh, Bayan Lepas & KLIA were used in calculating the clearness index and for training the neural network. Result shows that clearness index for Seri Iskandar is 0.52, the highest radiation is on February (20.45 MJ/m2/day, annual average is 18.25 MJ/m2/day and clearness index is more accurate than ANN when there is limited data supply. In general, Perak states show strong potential for solar energy application.

  12. Glutamatergic mechanisms for speed control and network operation in the rodent locomotor CPG

    DEFF Research Database (Denmark)

    Talpalar, Adolfo E.; Kiehn, Ole

    2010-01-01

    in mammals have produced conflicting results regarding the necessity and role of the different ionotropic glutamate receptors (GluRs) in the CPG function. Here, we use electrophysiological and pharmacological techniques in the in vitro neonatal mouse lumbar spinal cord to investigate the role of a broad...... mechanisms acting at various network levels. AMPA and kainate receptors are necessary for generating the highest locomotor frequencies. For coordination, NMDARs are more important than non-NMDARs for conveying the rhythmic signal from the network to the motor neurons during long-lasting and steady locomotor...

  13. Growing networks with mixed attachment mechanisms

    International Nuclear Information System (INIS)

    Shao Zhigang; Zou Xianwu; Tan Zhijie; Jin Zhunzhi

    2006-01-01

    Networks grow and evolve when new nodes and links are added in. There are two methods to add the links: uniform attachment and preferential attachment. We take account of the addition of links with mixed attachment between uniform attachment and preferential attachment in proportion. By using numerical simulations and analysis based on a continuum theory, we obtain that the degree distribution P(k) has an extended power-law form P(k) ∼ (k + k 0 ) -γ . When the number of edges k of a node is much larger than a certain value k 0 , the degree distribution reduces to the power-law form P(k) ∼ k -γ ; and when k is much smaller than k 0 , the degree distribution degenerates into the exponential form P(k)∼exp(-yk/k 0 ). It has been found that degree distribution possesses this extended power-law form for many real networks, such as the movie actor network, the citation network of scientific papers and diverse protein interaction networks

  14. An Authentication and Key Management Mechanism for Resource Constrained Devices in IEEE 802.11-based IoT Access Networks

    OpenAIRE

    Kim, Ki-Wook; Han, Youn-Hee; Min, Sung-Gi

    2017-01-01

    Many Internet of Things (IoT) services utilize an IoT access network to connect small devices with remote servers. They can share an access network with standard communication technology, such as IEEE 802.11ah. However, an authentication and key management (AKM) mechanism for resource constrained IoT devices using IEEE 802.11ah has not been proposed as yet. We therefore propose a new AKM mechanism for an IoT access network, which is based on IEEE 802.11 key management with the IEEE 802.1X aut...

  15. Dynamics and genetic fuzzy neural network vibration control design of a smart flexible four-bar linkage mechanism

    International Nuclear Information System (INIS)

    Rong Bao; Rui Xiaoting; Tao Ling

    2012-01-01

    In this paper, a dynamic modeling method and an active vibration control scheme for a smart flexible four-bar linkage mechanism featuring piezoelectric actuators and strain gauge sensors are presented. The dynamics of this smart mechanism is described by the Discrete Time Transfer Matrix Method of Multibody System (MS-DTTMM). Then a nonlinear fuzzy neural network control is employed to suppress the vibration of this smart mechanism. For improving the dynamic performance of the fuzzy neural network, a genetic algorithm based on the MS-DTTMM is designed offline to tune the initial parameters of the fuzzy neural network. The MS-DTTMM avoids the global dynamics equations of the system, which results in the matrices involved are always very small, so the computational efficiency of the dynamic analysis and control system optimization can be greatly improved. Formulations of the method as well as a numerical simulation are given to demonstrate the proposed dynamic method and control scheme.

  16. Mechanism for propagation of rate signals through a 10-layer feedforward neuronal network

    International Nuclear Information System (INIS)

    Jie, Li; Wan-Qing, Yu; Ding, Xu; Feng, Liu; Wei, Wang

    2009-01-01

    Using numerical simulations, we explore the mechanism for propagation of rate signals through a 10-layer feedforward network composed of Hodgkin–Huxley (HH) neurons with sparse connectivity. When white noise is afferent to the input layer, neuronal firing becomes progressively more synchronous in successive layers and synchrony is well developed in deeper layers owing to the feedforward connections between neighboring layers. The synchrony ensures the successful propagation of rate signals through the network when the synaptic conductance is weak. As the synaptic time constant τ syn varies, coherence resonance is observed in the network activity due to the intrinsic property of HH neurons. This makes the output firing rate single-peaked as a function of τ syn , suggesting that the signal propagation can be modulated by the synaptic time constant. These results are consistent with experimental results and advance our understanding of how information is processed in feedforward networks. (cross-disciplinary physics and related areas of science and technology)

  17. Comparative role of potential structure in classical, semiclassical, and quantum mechanics

    International Nuclear Information System (INIS)

    Judson, R.S.; Shi, S.; Rabitz, H.

    1989-01-01

    The corresponding effects of features in the potential on classical, semiclassical, and quantum mechanics are probed using the technique of functional sensitivity analysis. It is shown that the classical and quantum functional sensitivities are equivalent in the classical (small (h/2π)) and harmonic limits. Classical and quantum mechanics are known to react in qualitatively similar ways provided that features on the potential are smooth on the length scale of oscillations in the quantum wave function. By using functional sensitivity analysis, we are able to show in detail how the classical and quantum dynamics differ in the way that they sense the potential. Two examples are given, the first of which is the harmonic oscillator. This problem is well understood by other means but is useful to examine because it illustrates the detailed information about the interaction of the potential and the dynamics which can be provided by functional sensitivity analysis, simplifying the analysis of more complex systems. The second example is the collinear H+H 2 reaction. In that case there are a number of detailed and striking differences between the ways that classical and quantum mechanics react to features on the potential. For features which are broad compared to oscillations in the wave function, the two react in qualitatively the same way. The sensitivities are oscillatory, however, and there are phasing differences between the classical and quantum sensitivity functions. This means that using classical mechanics plus experimental data in an inversion scheme intended to find the ''true'' potential will necessarily introduce sizeable errors

  18. Network information provision to potential generators

    Energy Technology Data Exchange (ETDEWEB)

    Nicholson, G.

    2001-07-01

    At the time of finalising this report, an Ofgem consultation is underway on the form of Distribution Licence Condition 25, which will state the requirements for Distribution Network Operators to provide and publish data. This report is also relevant to the DTI Ofgem Embedded Generation Working Group (EGWG), which has recently completed its report and recommendations. It is hoped that this document will provide an overview of the status, importance, role and benefits of network information, which can be utilised by Generators, Network Operators and other industry players in framing their responses to this and future consultations. (Authors)

  19. Potential of dynamic spectrum allocation in LTE macro networks

    Science.gov (United States)

    Hoffmann, H.; Ramachandra, P.; Kovács, I. Z.; Jorguseski, L.; Gunnarsson, F.; Kürner, T.

    2015-11-01

    In recent years Mobile Network Operators (MNOs) worldwide are extensively deploying LTE networks in different spectrum bands and utilising different bandwidth configurations. Initially, the deployment is coverage oriented with macro cells using the lower LTE spectrum bands. As the offered traffic (i.e. the requested traffic from the users) increases the LTE deployment evolves with macro cells expanded with additional capacity boosting LTE carriers in higher frequency bands complemented with micro or small cells in traffic hotspot areas. For MNOs it is crucial to use the LTE spectrum assets, as well as the installed network infrastructure, in the most cost efficient way. The dynamic spectrum allocation (DSA) aims at (de)activating the available LTE frequency carriers according to the temporal and spatial traffic variations in order to increase the overall LTE system performance in terms of total network capacity by reducing the interference. This paper evaluates the DSA potential of achieving the envisaged performance improvement and identifying in which system and traffic conditions the DSA should be deployed. A self-optimised network (SON) DSA algorithm is also proposed and evaluated. The evaluations have been carried out in a hexagonal and a realistic site-specific urban macro layout assuming a central traffic hotspot area surrounded with an area of lower traffic with a total size of approximately 8 × 8 km2. The results show that up to 47 % and up to 40 % possible DSA gains are achievable with regards to the carried system load (i.e. used resources) for homogenous traffic distribution with hexagonal layout and for realistic site-specific urban macro layout, respectively. The SON DSA algorithm evaluation in a realistic site-specific urban macro cell deployment scenario including realistic non-uniform spatial traffic distribution shows insignificant cell throughput (i.e. served traffic) performance gains. Nevertheless, in the SON DSA investigations, a gain of up

  20. Common gene-network signature of different neurological disorders and their potential implications to neuroAIDS.

    Directory of Open Access Journals (Sweden)

    Vidya Sagar

    Full Text Available The neurological complications of AIDS (neuroAIDS during the infection of human immunodeficiency virus (HIV are symptomized by non-specific, multifaceted neurological conditions and therefore, defining a specific diagnosis/treatment mechanism(s for this neuro-complexity at the molecular level remains elusive. Using an in silico based integrated gene network analysis we discovered that HIV infection shares convergent gene networks with each of twelve neurological disorders selected in this study. Importantly, a common gene network was identified among HIV infection, Alzheimer's disease, Parkinson's disease, multiple sclerosis, and age macular degeneration. An mRNA microarray analysis in HIV-infected monocytes showed significant changes in the expression of several genes of this in silico derived common pathway which suggests the possible physiological relevance of this gene-circuit in driving neuroAIDS condition. Further, this unique gene network was compared with another in silico derived novel, convergent gene network which is shared by seven major neurological disorders (Alzheimer's disease, Parkinson's disease, Multiple Sclerosis, Age Macular Degeneration, Amyotrophic Lateral Sclerosis, Vascular Dementia, and Restless Leg Syndrome. These networks differed in their gene circuits; however, in large, they involved innate immunity signaling pathways, which suggests commonalities in the immunological basis of different neuropathogenesis. The common gene circuits reported here can provide a prospective platform to understand how gene-circuits belonging to other neuro-disorders may be convoluted during real-time neuroAIDS condition and it may elucidate the underlying-and so far unknown-genetic overlap between HIV infection and neuroAIDS risk. Also, it may lead to a new paradigm in understanding disease progression, identifying biomarkers, and developing therapies.

  1. Exploring drug-target interaction networks of illicit drugs.

    Science.gov (United States)

    Atreya, Ravi V; Sun, Jingchun; Zhao, Zhongming

    2013-01-01

    Drug addiction is a complex and chronic mental disease, which places a large burden on the American healthcare system due to its negative effects on patients and their families. Recently, network pharmacology is emerging as a promising approach to drug discovery by integrating network biology and polypharmacology, allowing for a deeper understanding of molecular mechanisms of drug actions at the systems level. This study seeks to apply this approach for investigation of illicit drugs and their targets in order to elucidate their interaction patterns and potential secondary drugs that can aid future research and clinical care. In this study, we extracted 188 illicit substances and their related information from the DrugBank database. The data process revealed 86 illicit drugs targeting a total of 73 unique human genes, which forms an illicit drug-target network. Compared to the full drug-target network from DrugBank, illicit drugs and their target genes tend to cluster together and form four subnetworks, corresponding to four major medication categories: depressants, stimulants, analgesics, and steroids. External analysis of Anatomical Therapeutic Chemical (ATC) second sublevel classifications confirmed that the illicit drugs have neurological functions or act via mechanisms of stimulants, opioids, and steroids. To further explore other drugs potentially having associations with illicit drugs, we constructed an illicit-extended drug-target network by adding the drugs that have the same target(s) as illicit drugs to the illicit drug-target network. After analyzing the degree and betweenness of the network, we identified hubs and bridge nodes, which might play important roles in the development and treatment of drug addiction. Among them, 49 non-illicit drugs might have potential to be used to treat addiction or have addictive effects, including some results that are supported by previous studies. This study presents the first systematic review of the network

  2. Human Brain Networks: Spiking Neuron Models, Multistability, Synchronization, Thermodynamics, Maximum Entropy Production, and Anesthetic Cascade Mechanisms

    Directory of Open Access Journals (Sweden)

    Wassim M. Haddad

    2014-07-01

    Full Text Available Advances in neuroscience have been closely linked to mathematical modeling beginning with the integrate-and-fire model of Lapicque and proceeding through the modeling of the action potential by Hodgkin and Huxley to the current era. The fundamental building block of the central nervous system, the neuron, may be thought of as a dynamic element that is “excitable”, and can generate a pulse or spike whenever the electrochemical potential across the cell membrane of the neuron exceeds a threshold. A key application of nonlinear dynamical systems theory to the neurosciences is to study phenomena of the central nervous system that exhibit nearly discontinuous transitions between macroscopic states. A very challenging and clinically important problem exhibiting this phenomenon is the induction of general anesthesia. In any specific patient, the transition from consciousness to unconsciousness as the concentration of anesthetic drugs increases is very sharp, resembling a thermodynamic phase transition. This paper focuses on multistability theory for continuous and discontinuous dynamical systems having a set of multiple isolated equilibria and/or a continuum of equilibria. Multistability is the property whereby the solutions of a dynamical system can alternate between two or more mutually exclusive Lyapunov stable and convergent equilibrium states under asymptotically slowly changing inputs or system parameters. In this paper, we extend the theory of multistability to continuous, discontinuous, and stochastic nonlinear dynamical systems. In particular, Lyapunov-based tests for multistability and synchronization of dynamical systems with continuously differentiable and absolutely continuous flows are established. The results are then applied to excitatory and inhibitory biological neuronal networks to explain the underlying mechanism of action for anesthesia and consciousness from a multistable dynamical system perspective, thereby providing a

  3. Development of pacemaker properties and rhythmogenic mechanisms in the mouse embryonic respiratory network

    Science.gov (United States)

    Chevalier, Marc; Toporikova, Natalia; Simmers, John; Thoby-Brisson, Muriel

    2016-01-01

    Breathing is a vital rhythmic behavior generated by hindbrain neuronal circuitry, including the preBötzinger complex network (preBötC) that controls inspiration. The emergence of preBötC network activity during prenatal development has been described, but little is known regarding inspiratory neurons expressing pacemaker properties at embryonic stages. Here, we combined calcium imaging and electrophysiological recordings in mouse embryo brainstem slices together with computational modeling to reveal the existence of heterogeneous pacemaker oscillatory properties relying on distinct combinations of burst-generating INaP and ICAN conductances. The respective proportion of the different inspiratory pacemaker subtypes changes during prenatal development. Concomitantly, network rhythmogenesis switches from a purely INaP/ICAN-dependent mechanism at E16.5 to a combined pacemaker/network-driven process at E18.5. Our results provide the first description of pacemaker bursting properties in embryonic preBötC neurons and indicate that network rhythmogenesis undergoes important changes during prenatal development through alterations in both circuit properties and the biophysical characteristics of pacemaker neurons. DOI: http://dx.doi.org/10.7554/eLife.16125.001 PMID:27434668

  4. An active cooperation-aware spectrum allocation mechanism for body sensor networks.

    Science.gov (United States)

    Jiang, Fu; Guo, Ying; Peng, Jun; Hu, Jiankun

    2015-01-28

    A cognitive radio-based spectrum allocation scheme using an active cooperative-aware mechanism is proposed in this paper. The scheme ensures that the primary user and secondary users cooperate actively for their own benefits. The primary user releases some spectrum resources to secondary users to actively stimulate them to actively join the cooperative transmission of the primary user, and secondary users help the primary user to relay data in return, as well as its self-data transmission at the same time. The Stackelberg game is used to evenly and jointly optimize the utilities of both the primary and secondary users. Simulation results show that the proposed active cooperation-aware mechanism could improve the body sensor network performance.

  5. A Reaction-Diffusion-Based Coding Rate Control Mechanism for Camera Sensor Networks

    Directory of Open Access Journals (Sweden)

    Naoki Wakamiya

    2010-08-01

    Full Text Available A wireless camera sensor network is useful for surveillance and monitoring for its visibility and easy deployment. However, it suffers from the limited capacity of wireless communication and a network is easily overflown with a considerable amount of video traffic. In this paper, we propose an autonomous video coding rate control mechanism where each camera sensor node can autonomously determine its coding rate in accordance with the location and velocity of target objects. For this purpose, we adopted a biological model, i.e., reaction-diffusion model, inspired by the similarity of biological spatial patterns and the spatial distribution of video coding rate. Through simulation and practical experiments, we verify the effectiveness of our proposal.

  6. A reaction-diffusion-based coding rate control mechanism for camera sensor networks.

    Science.gov (United States)

    Yamamoto, Hiroshi; Hyodo, Katsuya; Wakamiya, Naoki; Murata, Masayuki

    2010-01-01

    A wireless camera sensor network is useful for surveillance and monitoring for its visibility and easy deployment. However, it suffers from the limited capacity of wireless communication and a network is easily overflown with a considerable amount of video traffic. In this paper, we propose an autonomous video coding rate control mechanism where each camera sensor node can autonomously determine its coding rate in accordance with the location and velocity of target objects. For this purpose, we adopted a biological model, i.e., reaction-diffusion model, inspired by the similarity of biological spatial patterns and the spatial distribution of video coding rate. Through simulation and practical experiments, we verify the effectiveness of our proposal.

  7. Spherical harmonics based descriptor for neural network potentials: Structure and dynamics of Au147 nanocluster.

    Science.gov (United States)

    Jindal, Shweta; Chiriki, Siva; Bulusu, Satya S

    2017-05-28

    We propose a highly efficient method for fitting the potential energy surface of a nanocluster using a spherical harmonics based descriptor integrated with an artificial neural network. Our method achieves the accuracy of quantum mechanics and speed of empirical potentials. For large sized gold clusters (Au 147 ), the computational time for accurate calculation of energy and forces is about 1.7 s, which is faster by several orders of magnitude compared to density functional theory (DFT). This method is used to perform the global minimum optimizations and molecular dynamics simulations for Au 147 , and it is found that its global minimum is not an icosahedron. The isomer that can be regarded as the global minimum is found to be 4 eV lower in energy than the icosahedron and is confirmed from DFT. The geometry of the obtained global minimum contains 105 atoms on the surface and 42 atoms in the core. A brief study on the fluxionality in Au 147 is performed, and it is concluded that Au 147 has a dynamic surface, thus opening a new window for studying its reaction dynamics.

  8. Hydro power potentials of water distribution networks in public universities: A case study

    Directory of Open Access Journals (Sweden)

    Olufemi Adebola KOYA

    2017-06-01

    Full Text Available Public Universities in Southwestern Nigeria are densely populated student-resident campuses, so that provision of regular potable water and electricity are important, but power supply is not optimally available for all the necessary activities. This study assesses the hydropower potential of the water distribution networks in the Universities, with the view to augmenting the inadequate power supplies. The institutions with water distribution configuration capable of accommodating in-pipe turbine are identified; the hydropower parameters, such as the flow characteristics and the pipe geometry are determined to estimate the water power. Global positioning device is used in estimating the elevations of the distribution reservoirs and the nodal points. The hydropower potential of each location is computed incorporating Lucid® Lift-based spherical turbine in the pipeline. From the analysis, the lean and the peak water power are between 1.92 – 3.30 kW and 3.95 – 7.24 kW, respectively, for reservoir-fed distribution networks; while, a minimum of 0.72 kW is got for pipelines associated with borehole-fed overhead tanks. Possible applications of electricity generation from the water distribution networks of the public universities are recommended.

  9. Sewer Networks Optimization by Particle Swarm Optimization with Abilities of Fly-Back Mechanism and Harmony Memory

    Directory of Open Access Journals (Sweden)

    محسن نفیسی

    2014-10-01

    Full Text Available Lack of an efficient sewer network in urban areas threatens public health and may give rise to contagious diseases. Various optimization methods have been developed for use in designing sewers networks in response to a number of requirements such as the high costs of constructing sewer networks, financial limitations, the presence of both discrete and continuous decision variables, and the nonlinear time complexity of such design problems. In this study, the particle swarm optimization algorithm (PSO with the capability of “fly-back” mechanism equipped with the harmony search (HPSO is used for the optimization of sewers network designs. The objective function consists of minimizing the excavation and embedding costs of commercial pipes. The fly-back mechanism and the harmony memory method are used to prevent leaving out variables from the feasible space of the problem in an attempt to enhance model efficiency. Model constraints are satisfied at two levels, which leads to the desirable convergence of the PSO algorithm as compared to the conventional penalty methods in alternative evolutionary algorithms. In order to determine the admissible decision variables, the Manning equation is used as a hydraulic model. The performance of the proposed algorithm is shown by presenting two examples of sewer networks. Compared to the PSO algorithm used in sewer network optimization models, the proposed model exhibits a tangible improvement in cost reduction and a higher computational stability.

  10. Potentials of Industrie 4.0 and Machine Learning for Mechanical Joining

    OpenAIRE

    Jäckel, Mathias

    2017-01-01

    -Sensitivity analysis of the influence of component properties and joining parameters on the joining result for self-pierce riveting -Possibilities to link mechanical joining technologies with the automotive process chain for quality and flexibility improvements -Potential of using machine learning to reduce automotive product development cycles in relation to mechanical joining -Datamining for machine learning at mechanical joining

  11. Inside the Mechanics of Network Development: How Competition and Strategy Reorganize European Air Traffic

    Science.gov (United States)

    Huber, Hans

    2006-01-01

    Air transport forms complex networks that can be measured in order to understand its structural characteristics and functional properties. Recent models for network growth (i.e., preferential attachment, etc.) remain stochastic and do not seek to understand other network-specific mechanisms that may account for their development in a more microscopic way. Air traffic is made up of many constituent airlines that are either privately or publicly owned and that operate their own networks. They follow more or less similar business policies each. The way these airline networks organize among themselves into distinct traffic distributions reveals complex interaction among them, which in turn can be aggregated into larger (macro-) traffic distributions. Our approach allows for a more deterministic methodology that will assess the impact of airline strategies on the distinct distributions for air traffic, particularly inside Europe. One key question this paper is seeking to answer is whether there are distinct patterns of preferential attachment for given classes of airline networks to distinct types of European airports. Conclusions about the advancing degree of concentration in this industry and the airline operators that accelerate this process can be drawn.

  12. A time-based admission control mechanism for IEEE 802.11 ad Hoc networks

    OpenAIRE

    Costa, Luís Henrique M. K.; Cerveira, Carlos Rodrigo

    2006-01-01

    This paper presents a time-based admission control mechanism (TAC) for IEEE 802.11 ad hoc networks. The proposed mechanism was adapted to the QoS AODV routing protocol, which takes the quality of service requirements of the data flow into account in the route discovery process. TAC-AODV estimates the idle time of the physical medium based on the frames listened. The incoming traffic is admitted according to the offered load as well as the intra-flow interference, calculated based on the numbe...

  13. Amino Acid Metabolism and Transport Mechanisms as Potential Antifungal Targets

    Directory of Open Access Journals (Sweden)

    Matthew W. McCarthy

    2018-03-01

    Full Text Available Discovering new drugs for treatment of invasive fungal infections is an enduring challenge. There are only three major classes of antifungal agents, and no new class has been introduced into clinical practice in more than a decade. However, recent advances in our understanding of the fungal life cycle, functional genomics, proteomics, and gene mapping have enabled the identification of new drug targets to treat these potentially deadly infections. In this paper, we examine amino acid transport mechanisms and metabolism as potential drug targets to treat invasive fungal infections, including pathogenic yeasts, such as species of Candida and Cryptococcus, as well as molds, such as Aspergillus fumigatus. We also explore the mechanisms by which amino acids may be exploited to identify novel drug targets and review potential hurdles to bringing this approach into clinical practice.

  14. Studies on the phase diagram of boron employing a neural network potential

    Energy Technology Data Exchange (ETDEWEB)

    Morawietz, Tobias; Behler, Joerg [Lehrstuhl fuer Theoretische Chemie, Ruhr-Universitaet Bochum (Germany); Parrinello, Michele [Department of Chemistry and Applied Biosciences, ETH Zuerich (Switzerland)

    2009-07-01

    The crystalline phases of elemental boron have a structural complexity unique in the periodic table. The complex connection pattern of the icosahedral building blocks forms a formidable challenge for the construction of accurate but efficient potentials. We present a high-dimensional neural network potential for boron, which is based on first-principles calculations and can be systematically improved. The potential is several orders of magnitude faster to evaluate than the underlying density-functional theory calculations and allows to perform long molecular dynamics and metadynamics simulations of large system. By a stepwise refinement of the potential and an application of the potential in metadynamics simulations we show that starting from random atomic positions the structure of {alpha}-boron is predicted in agreement with experiment. Further, pressure-induced phase transitions of {alpha}-boron are discussed.

  15. Realistic Energy Saving Potential of Sleep Mode for Existing and Future Mobile Networks

    DEFF Research Database (Denmark)

    Micallef, Gilbert; Saker, Louai; Elayoubi, Salah Eddine

    2012-01-01

    potential savings, and emphasize some of the expected limitations. Since site measurements show that the energy consumption of base station sites is largely load-independent, this makes such a feature highly effective for reducing the energy consumption of mobile networks during hours of low traffic. After......This paper presents an extensive overview on an energy saving feature referred to as ‘site sleep mode’, designed for existing and future mobile broadband networks. In addition to providing a detailed understanding of the main concept, the paper also provides various studies and results to highlight...

  16. Reliable Communication in Wireless Meshed Networks using Network Coding

    DEFF Research Database (Denmark)

    Pahlevani, Peyman; Paramanathan, Achuthan; Hundebøll, Martin

    2012-01-01

    The advantages of network coding have been extensively studied in the field of wireless networks. Integrating network coding with existing IEEE 802.11 MAC layer is a challenging problem. The IEEE 802.11 MAC does not provide any reliability mechanisms for overheard packets. This paper addresses...... this problem and suggests different mechanisms to support reliability as part of the MAC protocol. Analytical expressions to this problem are given to qualify the performance of the modified network coding. These expressions are confirmed by numerical result. While the suggested reliability mechanisms...

  17. The potential mechanisms for motor complications of Parkinson's disease

    Directory of Open Access Journals (Sweden)

    SUN Sheng-gang

    2013-08-01

    Full Text Available Parkinson's disease (PD is a common neurodegenerative disease. Dopaminergic replacement therapy is still considered as a major treatment for PD. However, long-term dopaminergic replacement therapy for PD patients is frequently associated with the development of motor complications. To date, the mechanisms underlying motor complications have not been completely understood yet. Moreover, parts of motor complications are lack of therapeutic alternatives. All these characters make this disorder difficult and challenging to manage. Increasing number of researches have been proposed in recent years for elucidating the underlying mechanisms of levodopa-related motor complications, resulting in much progression. For better understanding the management of motor complications, here we provide an overview of the current knowledge of the potential mechanisms, including the pharmacodynamic and pharmacokinetic mechanisms of levodopa and levodopa-associated neurotransmitter systems.

  18. Tuning mechanical performance of poly(ethylene glycol) and agarose interpenetrating network hydrogels for cartilage tissue engineering.

    Science.gov (United States)

    Rennerfeldt, Deena A; Renth, Amanda N; Talata, Zsolt; Gehrke, Stevin H; Detamore, Michael S

    2013-11-01

    Hydrogels are attractive for tissue engineering applications due to their incredible versatility, but they can be limited in cartilage tissue engineering applications due to inadequate mechanical performance. In an effort to address this limitation, our team previously reported the drastic improvement in the mechanical performance of interpenetrating networks (IPNs) of poly(ethylene glycol) diacrylate (PEG-DA) and agarose relative to pure PEG-DA and agarose networks. The goal of the current study was specifically to determine the relative importance of PEG-DA concentration, agarose concentration, and PEG-DA molecular weight in controlling mechanical performance, swelling characteristics, and network parameters. IPNs consistently had compressive and shear moduli greater than the additive sum of either single network when compared to pure PEG-DA gels with a similar PEG-DA content. IPNs withstood a maximum stress of up to 4.0 MPa in unconfined compression, with increased PEG-DA molecular weight being the greatest contributing factor to improved failure properties. However, aside from failure properties, PEG-DA concentration was the most influential factor for the large majority of properties. Increasing the agarose and PEG-DA concentrations as well as the PEG-DA molecular weight of agarose/PEG-DA IPNs and pure PEG-DA gels improved moduli and maximum stresses by as much as an order of magnitude or greater compared to pure PEG-DA gels in our previous studies. Although the viability of encapsulated chondrocytes was not significantly affected by IPN formulation, glycosaminoglycan (GAG) content was significantly influenced, with a 12-fold increase over a three-week period in gels with a lower PEG-DA concentration. These results suggest that mechanical performance of IPNs may be tuned with partial but not complete independence from biological performance of encapsulated cells. © 2013 Elsevier Ltd. All rights reserved.

  19. Time dependent mechanical modeling for polymers based on network theory

    Energy Technology Data Exchange (ETDEWEB)

    Billon, Noëlle [MINES ParisTech, PSL-Research University, CEMEF – Centre de mise en forme des matériaux, CNRS UMR 7635, CS 10207 rue Claude Daunesse 06904 Sophia Antipolis Cedex (France)

    2016-05-18

    Despite of a lot of attempts during recent years, complex mechanical behaviour of polymers remains incompletely modelled, making industrial design of structures under complex, cyclic and hard loadings not totally reliable. The non linear and dissipative viscoelastic, viscoplastic behaviour of those materials impose to take into account non linear and combined effects of mechanical and thermal phenomena. In this view, a visco-hyperelastic, viscoplastic model, based on network description of the material has recently been developed and designed in a complete thermodynamic frame in order to take into account those main thermo-mechanical couplings. Also, a way to account for coupled effects of strain-rate and temperature was suggested. First experimental validations conducted in the 1D limit on amorphous rubbery like PMMA in isothermal conditions led to pretty goods results. In this paper a more complete formalism is presented and validated in the case of a semi crystalline polymer, a PA66 and a PET (either amorphous or semi crystalline) are used. Protocol for identification of constitutive parameters is described. It is concluded that this new approach should be the route to accurately model thermo-mechanical behaviour of polymers using a reduced number of parameters of some physical meaning.

  20. A Systems Biology Approach to the Coordination of Defensive and Offensive Molecular Mechanisms in the Innate and Adaptive Host-Pathogen Interaction Networks.

    Science.gov (United States)

    Wu, Chia-Chou; Chen, Bor-Sen

    2016-01-01

    Infected zebrafish coordinates defensive and offensive molecular mechanisms in response to Candida albicans infections, and invasive C. albicans coordinates corresponding molecular mechanisms to interact with the host. However, knowledge of the ensuing infection-activated signaling networks in both host and pathogen and their interspecific crosstalk during the innate and adaptive phases of the infection processes remains incomplete. In the present study, dynamic network modeling, protein interaction databases, and dual transcriptome data from zebrafish and C. albicans during infection were used to infer infection-activated host-pathogen dynamic interaction networks. The consideration of host-pathogen dynamic interaction systems as innate and adaptive loops and subsequent comparisons of inferred innate and adaptive networks indicated previously unrecognized crosstalk between known pathways and suggested roles of immunological memory in the coordination of host defensive and offensive molecular mechanisms to achieve specific and powerful defense against pathogens. Moreover, pathogens enhance intraspecific crosstalk and abrogate host apoptosis to accommodate enhanced host defense mechanisms during the adaptive phase. Accordingly, links between physiological phenomena and changes in the coordination of defensive and offensive molecular mechanisms highlight the importance of host-pathogen molecular interaction networks, and consequent inferences of the host-pathogen relationship could be translated into biomedical applications.

  1. An Active Cooperation-Aware Spectrum Allocation Mechanism for Body Sensor Networks

    Directory of Open Access Journals (Sweden)

    Fu Jiang

    2015-01-01

    Full Text Available A cognitive radio-based spectrum allocation scheme using an active cooperative-aware mechanism is proposed in this paper. The scheme ensures that the primary user and secondary users cooperate actively for their own benefits. The primary user releases some spectrum resources to secondary users to actively stimulate them to actively join the cooperative transmission of the primary user, and secondary users help the primary user to relay data in return, as well as its self-data transmission at the same time. The Stackelberg game is used to evenly and jointly optimize the utilities of both the primary and secondary users. Simulation results show that the proposed active cooperation-aware mechanism could improve the body sensor network performance.

  2. Active Tension Network model reveals an exotic mechanical state realized in epithelial tissues

    Science.gov (United States)

    Noll, Nicholas; Mani, Madhav; Heemskerk, Idse; Streicha, Sebastian; Shraiman, Boris

    Mechanical interactions play a crucial role in epithelial morphogenesis, yet understanding the complex mechanisms through which stress and deformation affect cell behavior remains an open problem. Here we formulate and analyze the Active Tension Network (ATN) model, which assumes that mechanical balance of cells is dominated by cortical tension and introduces tension dependent active remodeling of the cortex. We find that ATNs exhibit unusual mechanical properties: i) ATN behaves as a fluid at short times, but at long times it supports external tension, like a solid; ii) its mechanical equilibrium state has extensive degeneracy associated with a discrete conformal - ''isogonal'' - deformation of cells. ATN model predicts a constraint on equilibrium cell geometry, which we demonstrate to hold in certain epithelial tissues. We further show that isogonal modes are observed in a fruit fly embryo, accounting for the striking variability of apical area of ventral cells and helping understand the early phase of gastrulation. Living matter realizes new and exotic mechanical states, understanding which helps understand biological phenomena.

  3. Properties and toughening mechanisms of PVA/PAM double-network hydrogels prepared by freeze-thawing and anneal-swelling.

    Science.gov (United States)

    Ou, Kangkang; Dong, Xia; Qin, Chengling; Ji, Xinan; He, Jinxin

    2017-08-01

    It is well known that preparation method of hydrogels has a significant effect on their properties. In this paper, freeze-thawing and anneal-swelling were applied to prepare poly(vinyl alcohol)/polyacrylamide (PVA/PAM) double-network hydrogels with covalently and physically cross-linked networks. The properties of these hydrogels were investigated and compared to control hydrogels. Results indicated that hydrogels fabricated by freeze-thawing show larger pores size and higher swelling capacity than those made by anneal-swelling and control hydrogels. Hydrogels prepared by anneal-swelling exhibit higher mechanical strength, energy dissipation, fracture energy, gel fraction and crystallinity than those made by freeze-thawing and control hydrogels. Physical cross-linking plays a key role in formation of physical-chemical double-network. The toughening mechanism of double-network hydrogel is related to their chain-fracture behavior and elasticity. The results also indicated that appropriate methods can endow hydrogels with specific microstructures and properties which would broaden current hydrogels research and applications in biomedical fields. Copyright © 2017 Elsevier B.V. All rights reserved.

  4. Characterisation of anisotropic etching in KOH using network etch rate function model: influence of an applied potential in terms of microscopic properties

    International Nuclear Information System (INIS)

    Nguyen, Q D; Elwenspoek, M

    2006-01-01

    Using the network etch rate function model, the anisotropic etch rate of p-type single crystal silicon was characterised in terms of microscopic properties including step velocity, step and terrace roughening. The anisotropic etch rate data needed have been obtained using a combination of 2 wagon wheel patterns on different substrate and 1 offset trench pattern. Using this procedure the influence of an applied potential has been investigated in terms of microscopic properties. Model parameter trends show a good correlation with chemical/electrochemical reaction mechanism and mono- and dihydride terminated steps reactivity difference. Results also indicate a minimum in (111) terrace roughening which results in a peak in anisotropic ratio at the non-OCP applied potential of -1250 mV vs OCP

  5. Performance Analysis with Network-Enhanced Complexities: On Fading Measurements, Event-Triggered Mechanisms, and Cyber Attacks

    Directory of Open Access Journals (Sweden)

    Derui Ding

    2014-01-01

    Full Text Available Nowadays, the real-world systems are usually subject to various complexities such as parameter uncertainties, time-delays, and nonlinear disturbances. For networked systems, especially large-scale systems such as multiagent systems and systems over sensor networks, the complexities are inevitably enhanced in terms of their degrees or intensities because of the usage of the communication networks. Therefore, it would be interesting to (1 examine how this kind of network-enhanced complexities affects the control or filtering performance; and (2 develop some suitable approaches for controller/filter design problems. In this paper, we aim to survey some recent advances on the performance analysis and synthesis with three sorts of fashionable network-enhanced complexities, namely, fading measurements, event-triggered mechanisms, and attack behaviors of adversaries. First, these three kinds of complexities are introduced in detail according to their engineering backgrounds, dynamical characteristic, and modelling techniques. Then, the developments of the performance analysis and synthesis issues for various networked systems are systematically reviewed. Furthermore, some challenges are illustrated by using a thorough literature review and some possible future research directions are highlighted.

  6. Comparison of Artificial Neural Networks and GIS Based Solar Analysis for Solar Potential Estimation

    Science.gov (United States)

    Konakoǧlu, Berkant; Usta, Ziya; Cömert, Çetin; Gökalp, Ertan

    2016-04-01

    Nowadays, estimation of solar potential plays an important role in planning process for sustainable cities. The use of solar panels, which produces electricity directly from the sun, has become popular in accordance with developing technologies. Since the use of solar panels enables the users to decrease costs and increase yields, the use of solar panels will be more popular in the future. Production of electricity is not convenient for all circumstances. Shading effects, massive clouds and rainy weather are some factors that directly affect the production of electricity from solar energy. Hence, before the installation of solar panels, it is crucial to conduct spatial analysis and estimate the solar potential of the place that the solar panel will be installed. There are several approaches to determine the solar potential. Examination of the applications in the literature reveals that the applications conducted for determining the solar potential are divided into two main categories. Solar potential is estimated either by using artificial neural network approach in which statistical parameters such as the duration of sun shine, number of clear days, solar radiation etc. are used, or by spatial analysis conducted in GIS approaches in which spatial parameters such as, latitude, longitude, slope, aspect etc. are used. In the literature, there are several studies that use both approaches but the literature lacks of a study related to the comparison of these approaches. In this study, Karadeniz Technical University campus has been selected as study area. Monthly average values of the number of clear sky days, air temperature, atmospheric pressure, relative humidity, sunshine duration and solar radiation parameters obtained for the years between 2005 and 2015 will be used to perform artificial neural network analysis to estimate the solar potential of the study area. The solar potential will also be estimated by using GIS-based solar analysis modules. The results of

  7. Determination of the mechanical and physical properties of cartilage by coupling poroelastic-based finite element models of indentation with artificial neural networks.

    Science.gov (United States)

    Arbabi, Vahid; Pouran, Behdad; Campoli, Gianni; Weinans, Harrie; Zadpoor, Amir A

    2016-03-21

    One of the most widely used techniques to determine the mechanical properties of cartilage is based on indentation tests and interpretation of the obtained force-time or displacement-time data. In the current computational approaches, one needs to simulate the indentation test with finite element models and use an optimization algorithm to estimate the mechanical properties of cartilage. The modeling procedure is cumbersome, and the simulations need to be repeated for every new experiment. For the first time, we propose a method for fast and accurate estimation of the mechanical and physical properties of cartilage as a poroelastic material with the aid of artificial neural networks. In our study, we used finite element models to simulate the indentation for poroelastic materials with wide combinations of mechanical and physical properties. The obtained force-time curves are then divided into three parts: the first two parts of the data is used for training and validation of an artificial neural network, while the third part is used for testing the trained network. The trained neural network receives the force-time curves as the input and provides the properties of cartilage as the output. We observed that the trained network could accurately predict the properties of cartilage within the range of properties for which it was trained. The mechanical and physical properties of cartilage could therefore be estimated very fast, since no additional finite element modeling is required once the neural network is trained. The robustness of the trained artificial neural network in determining the properties of cartilage based on noisy force-time data was assessed by introducing noise to the simulated force-time data. We found that the training procedure could be optimized so as to maximize the robustness of the neural network against noisy force-time data. Copyright © 2016 Elsevier Ltd. All rights reserved.

  8. Cascading a systolic array and a feedforward neural network for navigation and obstacle avoidance using potential fields

    Science.gov (United States)

    Plumer, Edward S.

    1991-01-01

    A technique is developed for vehicle navigation and control in the presence of obstacles. A potential function was devised that peaks at the surface of obstacles and has its minimum at the proper vehicle destination. This function is computed using a systolic array and is guaranteed not to have local minima. A feedfoward neural network is then used to control the steering of the vehicle using local potential field information. In this case, the vehicle is a trailer truck backing up. Previous work has demonstrated the capability of a neural network to control steering of such a trailer truck backing to a loading platform, but without obstacles. Now, the neural network was able to learn to navigate a trailer truck around obstacles while backing toward its destination. The network is trained in an obstacle free space to follow the negative gradient of the field, after which the network is able to control and navigate the truck to its target destination in a space of obstacles which may be stationary or movable.

  9. A Network Pharmacology Approach to Uncover the Multiple Mechanisms of Hedyotis diffusa Willd. on Colorectal Cancer

    Directory of Open Access Journals (Sweden)

    Xinkui Liu

    2018-01-01

    Full Text Available Background. As one of the most frequently diagnosed cancer diseases globally, colorectal cancer (CRC remains an important cause of cancer-related death. Although the traditional Chinese herb Hedyotis diffusa Willd. (HDW has been proven to be effective for treating CRC in clinical practice, its definite mechanisms have not been completely deciphered. Objective. The aim of our research is to systematically explore the multiple mechanisms of HDW on CRC. Methods. This study adopted the network pharmacology approach, which was mainly composed of active component gathering, target prediction, CRC gene collection, network analysis, and gene enrichment analysis. Results. The network analysis showed that 10 targets might be the therapeutic targets of HDW on CRC, namely, HRAS, PIK3CA, KRAS, TP53, APC, BRAF, GSK3B, CDK2, AKT1, and RAF1. The gene enrichment analysis implied that HDW probably benefits patients with CRC by modulating pathways related to cancers, infectious diseases, endocrine system, immune system, nervous system, signal transduction, cellular community, and cell motility. Conclusions. This study partially verified and predicted the pharmacological and molecular mechanism of HDW against CRC from a holistic perspective, which will also lay a foundation for the further experimental research and clinical rational application of HDW.

  10. Simultaneous fitting of a potential-energy surface and its corresponding force fields using feedforward neural networks

    Science.gov (United States)

    Pukrittayakamee, A.; Malshe, M.; Hagan, M.; Raff, L. M.; Narulkar, R.; Bukkapatnum, S.; Komanduri, R.

    2009-04-01

    An improved neural network (NN) approach is presented for the simultaneous development of accurate potential-energy hypersurfaces and corresponding force fields that can be utilized to conduct ab initio molecular dynamics and Monte Carlo studies on gas-phase chemical reactions. The method is termed as combined function derivative approximation (CFDA). The novelty of the CFDA method lies in the fact that although the NN has only a single output neuron that represents potential energy, the network is trained in such a way that the derivatives of the NN output match the gradient of the potential-energy hypersurface. Accurate force fields can therefore be computed simply by differentiating the network. Both the computed energies and the gradients are then accurately interpolated using the NN. This approach is superior to having the gradients appear in the output layer of the NN because it greatly simplifies the required architecture of the network. The CFDA permits weighting of function fitting relative to gradient fitting. In every test that we have run on six different systems, CFDA training (without a validation set) has produced smaller out-of-sample testing error than early stopping (with a validation set) or Bayesian regularization (without a validation set). This indicates that CFDA training does a better job of preventing overfitting than the standard methods currently in use. The training data can be obtained using an empirical potential surface or any ab initio method. The accuracy and interpolation power of the method have been tested for the reaction dynamics of H+HBr using an analytical potential. The results show that the present NN training technique produces more accurate fits to both the potential-energy surface as well as the corresponding force fields than the previous methods. The fitting and interpolation accuracy is so high (rms error=1.2 cm-1) that trajectories computed on the NN potential exhibit point-by-point agreement with corresponding

  11. The Potential of the Market for the Kyoto Mechanisms

    International Nuclear Information System (INIS)

    Zhang, Z.X.

    2000-01-01

    The Kyoto Protocol is the first international environmental agreement to set legally binding greenhouse gas (GHG) emissions targets and timetables for Annex I countries. It incorporates emissions trading and two project-based flexibility mechanisms, namely joint implementation (JI) and the clean development mechanism (CDM) to help Annex I countries to meet their Kyoto targets at a lower overall cost. The extent to which their compliance cost can be lowered depends on the size of the market for all three flexibility mechanisms under the Protocol. This article estimates the size of such a market and demonstrates that restrictions on the use of flexibility mechanisms not only reduce potential of the Annex I countries' efficiency gains, but are furthermore not beneficial to developing countries since they restrict the total financial flows to developing countries under the CDM. Thus, from the perspective of husbanding the world's limited resources, the fewer the restrictions on the use of flexibility mechanisms, the greater are the gains from their use

  12. Using neural networks to represent potential surfaces as sums of products.

    Science.gov (United States)

    Manzhos, Sergei; Carrington, Tucker

    2006-11-21

    By using exponential activation functions with a neural network (NN) method we show that it is possible to fit potentials to a sum-of-products form. The sum-of-products form is desirable because it reduces the cost of doing the quadratures required for quantum dynamics calculations. It also greatly facilitates the use of the multiconfiguration time dependent Hartree method. Unlike potfit product representation algorithm, the new NN approach does not require using a grid of points. It also produces sum-of-products potentials with fewer terms. As the number of dimensions is increased, we expect the advantages of the exponential NN idea to become more significant.

  13. Mapping industrial networks as an approach to identify inter-organisational collaborative potential in new product development

    DEFF Research Database (Denmark)

    Parraguez, Pedro; Maier, Anja

    2012-01-01

    . Consequently, identifying and selecting potential partners to establish collaboration agreements can be a key activity in the new product development process. This paper explores the implications of mapping industrial networks with the purpose of identifying inter-organisational collaborative potential...

  14. Mechanism Of Environmental Franchising In The Sustainable Development Potential

    OpenAIRE

    Inna Illyashenko

    2011-01-01

    Reveals the types of environmental franchising: franchise environmental goods, manufacturing, service and environmental business format. Presents the methodological principles for the formation mechanisms of environmental franchise in implementing sustainable development potential. Proved economic, legal and organizational technology contractual relations regarding environmental franchise.

  15. Comparative study of key exchange and authentication methods in application, transport and network level security mechanisms

    Science.gov (United States)

    Fathirad, Iraj; Devlin, John; Jiang, Frank

    2012-09-01

    The key-exchange and authentication are two crucial elements of any network security mechanism. IPsec, SSL/TLS, PGP and S/MIME are well-known security approaches in providing security service to network, transport and application layers; these protocols use different methods (based on their requirements) to establish keying materials and authenticates key-negotiation and participated parties. This paper studies and compares the authenticated key negotiation methods in mentioned protocols.

  16. Prediction of vibration characteristics of a planar mechanism having imperfect joints using neural network

    International Nuclear Information System (INIS)

    Erkaya, Selcuk

    2012-01-01

    Clearance is inevitable in the joints of mechanisms due primarily to the design, manufacturing and assembly processes or a wear effect. Excessive value of joint clearance plays a crucial role and has a significant effect on the kinematic and dynamic performances of the mechanism. In this study, effects of joint clearances on bearing vibrations of mechanism are investigated. An experimental test rig is set up, and a planar slider-crank mechanism having two imperfect joints with radial clearance is used as a model mechanism. Three accelerometers are positioned at different points to measure the bearing vibrations during the mechanism motion. For the different running speeds and clearance sizes, this work provides a neural model to predict and estimate the bearing vibrations of the mechanical systems having imperfect joints. The results show that radial basis function (RBF) neural network has a superior performance for predicting and estimating the vibration characteristics of the mechanical system

  17. Permutation invariant potential energy surfaces for polyatomic reactions using atomistic neural networks

    International Nuclear Information System (INIS)

    Kolb, Brian; Zhao, Bin; Guo, Hua; Li, Jun; Jiang, Bin

    2016-01-01

    The applicability and accuracy of the Behler-Parrinello atomistic neural network method for fitting reactive potential energy surfaces is critically examined in three systems, H + H 2 → H 2 + H, H + H 2 O → H 2 + OH, and H + CH 4 → H 2 + CH 3 . A pragmatic Monte Carlo method is proposed to make efficient choice of the atom-centered mapping functions. The accuracy of the potential energy surfaces is not only tested by fitting errors but also validated by direct comparison in dynamically important regions and by quantum scattering calculations. Our results suggest this method is both accurate and efficient in representing multidimensional potential energy surfaces even when dissociation continua are involved.

  18. In silico analysis of the potential mechanism of telocinobufagin on breast cancer MCF-7 cells.

    Science.gov (United States)

    Dang, Yi-Wu; Lin, Peng; Liu, Li-Min; He, Rong-Quan; Zhang, Li-Jie; Peng, Zhi-Gang; Li, Xiao-Jiao; Chen, Gang

    2018-05-01

    The extractives from a ChanSu, traditional Chinese medicine, have been discovered to possess anti-inflammatory and tumor-suppressing abilities. However, the molecular mechanism of telocinobufagin, a compound extracted from ChanSu, on breast cancer cells has not been clarified. The aim of this study is to investigate the underlying mechanism of telocinobufagin on breast cancer cells. The differentially expressed genes after telocinobufagin treatment on breast cancer cells were searched and downloaded from Gene Expression Omnibus (GEO), ArrayExpress and literatures. Bioinformatics tools were applied to further explore the potential mechanism of telocinobufagin in breast cancer using the Kyoto Encyclopedia of genes and genomes (KEGG) pathway, Gene ontology (GO) enrichment, panther, and protein-protein interaction analyses. To better comprehend the role of telocinobufagin in breast cancer, we also queried the Connectivity Map using the gene expression profiles of telocinobufagin treatment. One GEO accession (GSE85871) provided 1251 differentially expressed genes after telocinobufagin treatment on MCF-7 cells. The pathway of neuroactive ligand-receptor interaction, cell adhesion molecules (CAMs), intestinal immune network for IgA production, hematopoietic cell lineage and calcium signaling pathway were the key pathways from KEGG analysis. IGF1 and KSR1, owning to higher protein levels in breast cancer tissues, IGF1 and KSR1 could be the hub genes related to telocinobufagin treatment. It was indicated that the molecular mechanism of telocinobufagin resembled that of fenspiride. Telocinobufagin might regulate neuroactive ligand-receptor interaction pathway to exert its influences in breast cancer MCF-7 cells, and its molecular mechanism might share some similarities with fenspiride. This study only presented a comprehensive picture of the role of telocinobufagin in breast cancer MCF-7 cells using big data. However, more thorough and deeper researches are required to add

  19. Training Deep Spiking Neural Networks Using Backpropagation.

    Science.gov (United States)

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

    2016-01-01

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

  20. Radiation synthesis and characterization of network structure of natural/synthetic double-network superabsorbent polymers

    International Nuclear Information System (INIS)

    Sen, M.; Hayrabolulu, H.

    2011-01-01

    Complete text of publication follows. Superabsorbent polymers (SAPs) are moderately cross linked, 3-D, hydrophilic network polymers that can absorb and conserve considerable amounts of aqueous fluids even under certain heat or pressure. Because of the unique properties superior to conventional absorbents, SAPs have found potential application in many fields such as hygienic products, disposable diapers, horticulture, gel actuators, drug-delivery systems, as well as water-blocking tapes coal dewatering, water managing materials for the renewal of arid and desert environment, etc. In recent years, naturally available resources, such as polysaccharides have drawn considerable attention for the preparation of SAPs. Since the mechanical properties of polysaccharide based natural polymers are low, researchers have mostly focused on natural/synthetic polymer/monomer mixtures to obtain novel SAPs. The aim of this study is to synthesize and characterization of network structure of novel double-network (DN) hydrogels as a SAP. Hydrogels with high mechanical strength have been prepared by radiation induced polymerization and crosslink of acrylic acid sodium salt in the presence of natural polymer locust bean gum. Liquid retention capacities and absorbency under load (AUL) analysis of synthesized SAPs was performed at different temperatures in water and synthetic urine solution, in order to determine their SAP character. For the characterization of network structure of the semi-IPN hydrogels, the average molecular weight between cross links (M c ) were evaluated by using uniaxial compression and oscillatory dynamical mechanical analyses and the advantage and disadvantage of these two technique for the characterization of network structures were compared.

  1. Investigating the Potential Impacts of Energy Production in the Marcellus Shale Region Using the Shale Network Database

    Science.gov (United States)

    Brantley, S.; Brazil, L.

    2017-12-01

    The Shale Network's extensive database of water quality observations enables educational experiences about the potential impacts of resource extraction with real data. Through tools that are open source and free to use, researchers, educators, and citizens can access and analyze the very same data that the Shale Network team has used in peer-reviewed publications about the potential impacts of hydraulic fracturing on water. The development of the Shale Network database has been made possible through efforts led by an academic team and involving numerous individuals from government agencies, citizen science organizations, and private industry. Thus far, these tools and data have been used to engage high school students, university undergraduate and graduate students, as well as citizens so that all can discover how energy production impacts the Marcellus Shale region, which includes Pennsylvania and other nearby states. This presentation will describe these data tools, how the Shale Network has used them in developing lesson plans, and the resources available to learn more.

  2. Path synthesis of four-bar mechanisms using synergy of polynomial neural network and Stackelberg game theory

    Science.gov (United States)

    Ahmadi, Bahman; Nariman-zadeh, Nader; Jamali, Ali

    2017-06-01

    In this article, a novel approach based on game theory is presented for multi-objective optimal synthesis of four-bar mechanisms. The multi-objective optimization problem is modelled as a Stackelberg game. The more important objective function, tracking error, is considered as the leader, and the other objective function, deviation of the transmission angle from 90° (TA), is considered as the follower. In a new approach, a group method of data handling (GMDH)-type neural network is also utilized to construct an approximate model for the rational reaction set (RRS) of the follower. Using the proposed game-theoretic approach, the multi-objective optimal synthesis of a four-bar mechanism is then cast into a single-objective optimal synthesis using the leader variables and the obtained RRS of the follower. The superiority of using the synergy game-theoretic method of Stackelberg with a GMDH-type neural network is demonstrated for two case studies on the synthesis of four-bar mechanisms.

  3. Optical network democratization.

    Science.gov (United States)

    Nejabati, Reza; Peng, Shuping; Simeonidou, Dimitra

    2016-03-06

    The current Internet infrastructure is not able to support independent evolution and innovation at physical and network layer functionalities, protocols and services, while at same time supporting the increasing bandwidth demands of evolving and heterogeneous applications. This paper addresses this problem by proposing a completely democratized optical network infrastructure. It introduces the novel concepts of the optical white box and bare metal optical switch as key technology enablers for democratizing optical networks. These are programmable optical switches whose hardware is loosely connected internally and is completely separated from their control software. To alleviate their complexity, a multi-dimensional abstraction mechanism using software-defined network technology is proposed. It creates a universal model of the proposed switches without exposing their technological details. It also enables a conventional network programmer to develop network applications for control of the optical network without specific technical knowledge of the physical layer. Furthermore, a novel optical network virtualization mechanism is proposed, enabling the composition and operation of multiple coexisting and application-specific virtual optical networks sharing the same physical infrastructure. Finally, the optical white box and the abstraction mechanism are experimentally evaluated, while the virtualization mechanism is evaluated with simulation. © 2016 The Author(s).

  4. Efficient second order Algorithms for Function Approximation with Neural Networks. Application to Sextic Potentials

    International Nuclear Information System (INIS)

    Gougam, L.A.; Taibi, H.; Chikhi, A.; Mekideche-Chafa, F.

    2009-01-01

    The problem of determining the analytical description for a set of data arises in numerous sciences and applications and can be referred to as data modeling or system identification. Neural networks are a convenient means of representation because they are known to be universal approximates that can learn data. The desired task is usually obtained by a learning procedure which consists in adjusting the s ynaptic weights . For this purpose, many learning algorithms have been proposed to update these weights. The convergence for these learning algorithms is a crucial criterion for neural networks to be useful in different applications. The aim of the present contribution is to use a training algorithm for feed forward wavelet networks used for function approximation. The training is based on the minimization of the least-square cost function. The minimization is performed by iterative second order gradient-based methods. We make use of the Levenberg-Marquardt algorithm to train the architecture of the chosen network and, then, the training procedure starts with a simple gradient method which is followed by a BFGS (Broyden, Fletcher, Glodfarb et Shanno) algorithm. The performances of the two algorithms are then compared. Our method is then applied to determine the energy of the ground state associated to a sextic potential. In fact, the Schrodinger equation does not always admit an exact solution and one has, generally, to solve it numerically. To this end, the sextic potential is, firstly, approximated with the above outlined wavelet network and, secondly, implemented into a numerical scheme. Our results are in good agreement with the ones found in the literature.

  5. Convolutional neural networks for event-related potential detection: impact of the architecture.

    Science.gov (United States)

    Cecotti, H

    2017-07-01

    The detection of brain responses at the single-trial level in the electroencephalogram (EEG) such as event-related potentials (ERPs) is a difficult problem that requires different processing steps to extract relevant discriminant features. While most of the signal and classification techniques for the detection of brain responses are based on linear algebra, different pattern recognition techniques such as convolutional neural network (CNN), as a type of deep learning technique, have shown some interests as they are able to process the signal after limited pre-processing. In this study, we propose to investigate the performance of CNNs in relation of their architecture and in relation to how they are evaluated: a single system for each subject, or a system for all the subjects. More particularly, we want to address the change of performance that can be observed between specifying a neural network to a subject, or by considering a neural network for a group of subjects, taking advantage of a larger number of trials from different subjects. The results support the conclusion that a convolutional neural network trained on different subjects can lead to an AUC above 0.9 by using an appropriate architecture using spatial filtering and shift invariant layers.

  6. Co-Evolutionary Mechanisms of Emotional Bursts in Online Social Dynamics and Networks

    Directory of Open Access Journals (Sweden)

    Bosiljka Tadić

    2013-11-01

    Full Text Available Collective emotional behavior of users is frequently observed on various Web portals; however, its complexity and the role of emotions in the acting mechanisms are still not thoroughly understood. In this work, using the empirical data and agent-based modeling, a parallel analysis is performed of two archetypal systems—Blogs and Internet-Relayed-Chats—both of which maintain self-organized dynamics but not the same communication rules and time scales. The emphasis is on quantifying the collective emotions by means of fractal analysis of the underlying processes as well as topology of social networks, which arise and co-evolve in these stochastic processes. The results reveal that two distinct mechanisms, which are based on different use of emotions (an emotion is characterized by two components, arousal and valence, are intrinsically associated with two classes of emergent social graphs. Their hallmarks are the evolution of communities in accordance with the excess of the negative emotions on popular Blogs, on one side, and smooth spreading of the Bot’s emotional impact over the entire hierarchical network of chats, on the other. Another emphasis of this work is on the understanding of nonextensivity of the emotion dynamics; it was found that, in its own way, each mechanism leads to a reduced phase space of the emotion components when the collective dynamics takes place. That a non-additive entropy describes emotion dynamics, is further confirmed by computing the q-generalized Kolmogorov-Sinai entropy rate in the empirical data of chats as well as in the simulations of interacting emotional agents and Bots.

  7. Active tension network model suggests an exotic mechanical state realized in epithelial tissues

    Science.gov (United States)

    Noll, Nicholas; Mani, Madhav; Heemskerk, Idse; Streichan, Sebastian J.; Shraiman, Boris I.

    2017-12-01

    Mechanical interactions play a crucial role in epithelial morphogenesis, yet understanding the complex mechanisms through which stress and deformation affect cell behaviour remains an open problem. Here we formulate and analyse the active tension network (ATN) model, which assumes that the mechanical balance of cells within a tissue is dominated by cortical tension and introduces tension-dependent active remodelling of the cortex. We find that ATNs exhibit unusual mechanical properties. Specifically, an ATN behaves as a fluid at short times, but at long times supports external tension like a solid. Furthermore, an ATN has an extensively degenerate equilibrium mechanical state associated with a discrete conformal--`isogonal'--deformation of cells. The ATN model predicts a constraint on equilibrium cell geometries, which we demonstrate to approximately hold in certain epithelial tissues. We further show that isogonal modes are observed in the fruit fly embryo, accounting for the striking variability of apical areas of ventral cells and helping understand the early phase of gastrulation. Living matter realizes new and exotic mechanical states, the study of which helps to understand biological phenomena.

  8. Impact of Mechanical down Tilt and Height on the Pilot Coverage of UMTS Networks

    Directory of Open Access Journals (Sweden)

    N. Faruk

    2012-06-01

    Full Text Available The task of planning a network can be very challenging as it involves many careful studies with a lot of considerations and, at times, trial and error. In this paper, the impacts of antenna mechanical down tilt and antenna height on UMTS network performance are studied. First, we used ASSET3G simulation software to design 3G pilot coverage. Optimization techniques were deployed to study the performance of the network. Simulation results show about 2.6% increase in the coverage area when the antenna height was increased from 15 m to 25 m at the same tilt angle of 0 ° The coverage drops by 24% when transiting from 0° to 6° tilt angle was made for 15 m height antenna. The results also indicated that, pilot pollution could be reduced by choosing optimum down tilt angle.

  9. Dynamic functional modules in co-expressed protein interaction networks of dilated cardiomyopathy

    Directory of Open Access Journals (Sweden)

    Oyang Yen-Jen

    2010-10-01

    Full Text Available Abstract Background Molecular networks represent the backbone of molecular activity within cells and provide opportunities for understanding the mechanism of diseases. While protein-protein interaction data constitute static network maps, integration of condition-specific co-expression information provides clues to the dynamic features of these networks. Dilated cardiomyopathy is a leading cause of heart failure. Although previous studies have identified putative biomarkers or therapeutic targets for heart failure, the underlying molecular mechanism of dilated cardiomyopathy remains unclear. Results We developed a network-based comparative analysis approach that integrates protein-protein interactions with gene expression profiles and biological function annotations to reveal dynamic functional modules under different biological states. We found that hub proteins in condition-specific co-expressed protein interaction networks tended to be differentially expressed between biological states. Applying this method to a cohort of heart failure patients, we identified two functional modules that significantly emerged from the interaction networks. The dynamics of these modules between normal and disease states further suggest a potential molecular model of dilated cardiomyopathy. Conclusions We propose a novel framework to analyze the interaction networks in different biological states. It successfully reveals network modules closely related to heart failure; more importantly, these network dynamics provide new insights into the cause of dilated cardiomyopathy. The revealed molecular modules might be used as potential drug targets and provide new directions for heart failure therapy.

  10. Why is social network drinking associated with college students' alcohol use? Focus on psychological mediators.

    Science.gov (United States)

    Reid, Allecia E; Carey, Kate B

    2018-06-04

    Level of drinking in the social network is strongly associated with college students' alcohol use. However, mechanisms through which networks are associated with personal drinking have been underexplored thus far. The present study examined theoretically derived constructs-sociability outcome expectancies, attitudes toward heavy drinking, self-efficacy for use of protective strategies, and descriptive norms-as potential mediators of the association between egocentric social network drinking and personal consumption. College students (N = 274) self-reported their social network's level of alcohol consumption, all mediators, drinks per week, and consequences at both baseline (Time 1) and a 1-month follow-up (Time 2). Autoregressive mediation models focused on the longitudinal associations between Time 1 network drinking and the Time 2 mediators and between the Time 1 mediators and the Time 2 outcomes. Consistent with hypotheses, Time 1 social network drinking was significantly associated with Time 2 drinks per week and consequences. Only attitudes significantly mediated social network associations with drinks per week and consequences, though the proportion of the total effects accounted for by attitudes was small. After accounting for the stability of constructs over time, social network drinking was generally un- or weakly related to sociability expectancies, self-efficacy, and descriptive norms. Results support reducing attitudes toward heavy drinking as a potential avenue for mitigating network effects, but also highlight the need to evaluate additional potential mechanisms of network effects. Intervention efforts that aim to address the social network have the potential to substantially reduce alcohol consumption, thereby enhancing the overall efficacy of alcohol risk-reduction interventions. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  11. Fabrication of microstamps and patterned cell network

    International Nuclear Information System (INIS)

    Seong, Nak Seon; Pak, James Jung Ho; Choi, Ju Hee; Ahn, Dong June; Hwang, Seong Min; Lee, Kyung J.

    2002-01-01

    Elastomeric stamps with micrometer-sized grids are fabricated for building biological cell networks by design. Polymerized polydimethyl-siloxane (PDMS) stamps are cast in a variety of different molds prepared by micro-electro mechanical systems (MEMS) technology. Micro square-grid patterns of 3-aminopropyl triethoxy silane (APS) are successfully imprinted on glass plates, and patterned networks of cardiac cells are obtained as designed. The resulting cellular networks clearly demonstrate that cell attachment and growth are greatly favored on APS-treated thin tracks. Here, we report the technical details related to the fabrication of microstamps, to the stamping procedure, and to the culture method. The potential applications of patterned cellular networks are also discussed

  12. PDMS Network Structure-Property Relationships: Influence of Molecular Architecture on Mechanical and Wetting Properties

    Science.gov (United States)

    Melillo, Matthew Joseph

    Poly(dimethylsiloxane) (PDMS) is one of the most common elastomers, with applications ranging from sealants and marine-antifouling coatings to medical devices and absorbents for water treatment. Fundamental understanding of how liquids spread on the surface of and absorb into and leach out of PDMS networks is of critical importance for the design and use in another application - microfluidic devices. The growing use of PDMS in microfluidic devices raises the concern that some researchers may use this material without fully understanding all of its advantages, drawbacks, and intricacies. The primary goal of this Ph.D. dissertation is to elucidate PDMS network molecular structure to macroscopic property relationships and to demonstrate how molecular architecture can alter dynamic mechanical and wetting characteristics. We prepare PDMS materials by using vinyl/ tetrakis(dimethylsiloxy)silane (TDSS) and silanol/ tetraethylorthosilicate (TEOS) combinations of PDMS end-groups and crosslinkers as two model systems. Under constant curing conditions, we systematically study the effects of polymer molecular weight, loading of crosslinker, and end-group chemical functionality on the extent of gelation and the dynamic mechanical and water wetting properties of end-linked PDMS networks. The extent of the gelation reaction is determined using the Soxhlet extraction to quantify the amount of material that did and did not participate in the crosslinking reactions, termed the gel and sol fractions, respectively. We use the Miller-Macosko model in conjunction with the gel fraction and precise chemical composition (i.e., stoichiometric ratio and molecular weight) to determine the fractions of elastic and pendant material, the molecular weight between chemical crosslinks, and the average effective functionality of the crosslinker molecule. Based on dynamic mechanical testing, we find that the maximum storage moduli are achieved at optimal stoichiometric conditions in the vinyl

  13. Mechanics of Fluctuating Elastic Plates and Fiber Networks

    Science.gov (United States)

    Liang, Xiaojun

    Lipid membranes and fiber networks in biological systems perform important mechanical functions at the cellular and tissue levels. In this thesis I delve into two detailed problems--thermal fluctuation of membranes and non-linear compression response of fiber networks. Typically, membrane fluctuations are analysed by decomposing into normal modes or by molecular simulations. In the first part of my thesis, I propose a new semi-analytic method to calculate the partition function of a membrane. The membrane is viewed as a fluctuating von Karman plate and discretized into triangular elements. Its energy is expressed as a function of nodal displacements, and then the partition function and co-variance matrix are computed using Gaussian integrals. I recover well-known results for the dependence of the projected area of a lipid bilayer membrane on the applied tension, and recent simulation results on the ependence of membrane free energy on geometry, spontaneous curvature and tension. As new applications I use this technique to study a membrane with heterogeneity and different boundary conditions. I also use this technique to study solid membranes by taking account of the non-linear coupling of in-plane strains with out-of-plane deflections using a penalty energy, and apply it to graphene, an ultra-thin two-dimensional solid. The scaling of graphene fluctuations with membrane size is recovered. I am able to capture the dependence of the thermal expansion coefficient of graphene on temperature. Next, I study curvature mediated interactions between inclusions in membranes. I assume the inclusions to be rigid, and show that the elastic and entropic forces between them can compete to yield a local maximum in the free energy if the membrane bending modulus is small. If the spacing between the inclusions is less than this local maximum then the attractive entropic forces dominate and the separation between the inclusions will be determined by short range interactions; if the

  14. Network security

    CERN Document Server

    Perez, André

    2014-01-01

    This book introduces the security mechanisms deployed in Ethernet, Wireless-Fidelity (Wi-Fi), Internet Protocol (IP) and MultiProtocol Label Switching (MPLS) networks. These mechanisms are grouped throughout the book according to the following four functions: data protection, access control, network isolation, and data monitoring. Data protection is supplied by data confidentiality and integrity control services. Access control is provided by a third-party authentication service. Network isolation is supplied by the Virtual Private Network (VPN) service. Data monitoring consists of applying

  15. Gene Expression Correlated with Severe Asthma Characteristics Reveals Heterogeneous Mechanisms of Severe Disease.

    Science.gov (United States)

    Modena, Brian D; Bleecker, Eugene R; Busse, William W; Erzurum, Serpil C; Gaston, Benjamin M; Jarjour, Nizar N; Meyers, Deborah A; Milosevic, Jadranka; Tedrow, John R; Wu, Wei; Kaminski, Naftali; Wenzel, Sally E

    2017-06-01

    Severe asthma (SA) is a heterogeneous disease with multiple molecular mechanisms. Gene expression studies of bronchial epithelial cells in individuals with asthma have provided biological insight and underscored possible mechanistic differences between individuals. Identify networks of genes reflective of underlying biological processes that define SA. Airway epithelial cell gene expression from 155 subjects with asthma and healthy control subjects in the Severe Asthma Research Program was analyzed by weighted gene coexpression network analysis to identify gene networks and profiles associated with SA and its specific characteristics (i.e., pulmonary function tests, quality of life scores, urgent healthcare use, and steroid use), which potentially identified underlying biological processes. A linear model analysis confirmed these findings while adjusting for potential confounders. Weighted gene coexpression network analysis constructed 64 gene network modules, including modules corresponding to T1 and T2 inflammation, neuronal function, cilia, epithelial growth, and repair mechanisms. Although no network selectively identified SA, genes in modules linked to epithelial growth and repair and neuronal function were markedly decreased in SA. Several hub genes of the epithelial growth and repair module were found located at the 17q12-21 locus, near a well-known asthma susceptibility locus. T2 genes increased with severity in those treated with corticosteroids but were also elevated in untreated, mild-to-moderate disease compared with healthy control subjects. T1 inflammation, especially when associated with increased T2 gene expression, was elevated in a subgroup of younger patients with SA. In this hypothesis-generating analysis, gene expression networks in relation to asthma severity provided potentially new insight into biological mechanisms associated with the development of SA and its phenotypes.

  16. A new approach to shortest paths on networks based on the quantum bosonic mechanism

    Energy Technology Data Exchange (ETDEWEB)

    Jiang Xin; Wang Hailong; Tang Shaoting; Ma Lili; Zhang Zhanli; Zheng Zhiming, E-mail: jiangxin@ss.buaa.edu.cn [Key Laboratory of Mathematics, Informatics and Behavioral Semantics, Ministry of Education, Beijing University of Aeronautics and Astronautics, 100191 Beijing (China)

    2011-01-15

    This paper presents quantum bosonic shortest path searching (QBSPS), a natural, practical and highly heuristic physical algorithm for reasoning about the recognition of network structure via quantum dynamics. QBSPS is based on an Anderson-like itinerant bosonic system in which a boson's Green function is used as a navigation pointer for one to accurately approach the terminals. QBSPS is demonstrated by rigorous mathematical and physical proofs and plenty of simulations, showing how it can be used as a greedy routing to seek the shortest path between different locations. In methodology, it is an interesting and new algorithm rooted in the quantum mechanism other than combinatorics. In practice, for the all-pairs shortest-path problem in a random scale-free network with N vertices, QBSPS runs in O({mu}(N) ln ln N) time. In application, we suggest that the corresponding experimental realizations are feasible by considering path searching in quantum optical communication networks; in this situation, the method performs a pure local search on networks without requiring the global structure that is necessary for current graph algorithms.

  17. Social cognitive radio networks

    CERN Document Server

    Chen, Xu

    2015-01-01

    This brief presents research results on social cognitive radio networks, a transformational and innovative networking paradigm that promotes the nexus between social interactions and cognitive radio networks. Along with a review of the research literature, the text examines the key motivation and challenges of social cognitive radio network design. Three socially inspired distributed spectrum sharing mechanisms are introduced: adaptive channel recommendation mechanism, imitation-based social spectrum sharing mechanism, and evolutionarily stable spectrum access mechanism. The brief concludes with a discussion of future research directions which ascertains that exploiting social interactions for distributed spectrum sharing will advance the state-of-the-art of cognitive radio network design, spur a new line of thinking for future wireless networks, and enable novel wireless service and applications.

  18. Permutation invariant potential energy surfaces for polyatomic reactions using atomistic neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Kolb, Brian [Department of Chemistry and Chemical Biology, University of New Mexico, Albuquerque, New Mexico 87131 (United States); Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 (United States); Zhao, Bin; Guo, Hua, E-mail: hguo@unm.edu [Department of Chemistry and Chemical Biology, University of New Mexico, Albuquerque, New Mexico 87131 (United States); Li, Jun [School of Chemistry and Chemical Engineering, Chongqing University, Chongqing 401331 (China); Jiang, Bin [Department of Chemical Physics, University of Science and Technology of China, Hefei, Anhui 230026 (China)

    2016-06-14

    The applicability and accuracy of the Behler-Parrinello atomistic neural network method for fitting reactive potential energy surfaces is critically examined in three systems, H + H{sub 2} → H{sub 2} + H, H + H{sub 2}O → H{sub 2} + OH, and H + CH{sub 4} → H{sub 2} + CH{sub 3}. A pragmatic Monte Carlo method is proposed to make efficient choice of the atom-centered mapping functions. The accuracy of the potential energy surfaces is not only tested by fitting errors but also validated by direct comparison in dynamically important regions and by quantum scattering calculations. Our results suggest this method is both accurate and efficient in representing multidimensional potential energy surfaces even when dissociation continua are involved.

  19. Control system of executive mechanisms of a spectrometer on the IBR-2 reactor as a modern local network of controllers CAN

    International Nuclear Information System (INIS)

    Zhuravlev, V.V.; Kirillov, A.S.; Petukhova, T.B.; Sirotin, A.P.

    2007-01-01

    Controllers SMC-32 and SMC-32-CAN as elements of control systems of executive mechanisms of the IBR-2 spectrometers are submitted. The controllers provide management of executive mechanisms of spectrometers on the consecutive communication line RS232, RS422 (SMC-32, SMC-32-CAN), and on the local network CAN (SMC-32-CAN). The control systems of the executive mechanisms are easily modernized due to connection of additional elements of the local network CAN. Dynamic characteristics of the spectrometers' executive mechanisms are essentially improved. For example, it has been possible to increase the rotation frequency of the step motor DSHI-200 up to 10000 pps. (author)

  20. Social networks and their role in preventing dementia

    OpenAIRE

    Pillai, Jagan A.; Verghese, Joe

    2009-01-01

    Interest in the role of social networks as a protective factor in the development of dementia over the last decade has increased with a number of longitudinal studies being published on the possible association of different lifestyles with dementia. This review examines and provides a summary of the published longitudinal studies exploring the effect of social network on dementia, with particular focus on their relevance to the Indian society. Potential cognitive and biological mechanisms med...

  1. Role of a Water Network around the Mn4CaO5 Cluster in Photosynthetic Water Oxidation: A Fourier Transform Infrared Spectroscopy and Quantum Mechanics/Molecular Mechanics Calculation Study.

    Science.gov (United States)

    Nakamura, Shin; Ota, Kai; Shibuya, Yuichi; Noguchi, Takumi

    2016-01-26

    Photosynthetic water oxidation takes place at the Mn4CaO5 cluster in photosystem II. Around the Mn4CaO5 cluster, a hydrogen bond network is formed by several water molecules, including four water ligands. To clarify the role of this water network in the mechanism of water oxidation, we investigated the effects of the removal of Ca(2+) and substitution with metal ions on the vibrations of water molecules coupled to the Mn4CaO5 cluster by means of Fourier transform infrared (FTIR) difference spectroscopy and quantum mechanics/molecular mechanics (QM/MM) calculations. The OH stretching vibrations of nine water molecules forming a network between D1-D61 and YZ were calculated using the QM/MM method. On the the calculated normal modes, a broad positive feature at 3200-2500 cm(-1) in an S2-minus-S1 FTIR spectrum was attributed to the vibrations of strongly hydrogen-bonded OH bonds of water involving the vibrations of water ligands to a Mn ion and the in-phase coupled vibration of a water network connected to YZ, while bands in the 3700-3500 cm(-1) region were assigned to the coupled vibrations of weakly hydrogen-bonded OH bonds of water. All the water bands were lost upon Ca(2+) depletion and Ba(2+) substitution, which inhibit the S2 → S3 transition, indicating that a solid water network was broken by these treatments. By contrast, Sr(2+) substitution slightly altered the water bands around 3600 cm(-1), reflecting minor modification in water interactions, consistent with the retention of water oxidation activity with a decreased efficiency. These results suggest that the water network around the Mn4CaO5 cluster plays an essential role in the water oxidation mechanism particularly in a concerted process of proton transfer and water insertion during the S2 → S3 transition.

  2. Identification of potential opinion leaders in child health promotion in Sweden using network analysis.

    Science.gov (United States)

    Guldbrandsson, Karin; Nordvik, Monica K; Bremberg, Sven

    2012-08-08

    Opinion leaders are often local individuals with high credibility who can influence other people. Robust effects using opinion leaders in diffusing innovations have been shown in several randomized controlled trials, for example regarding sexually transmitted infections (STI), human immunodeficiency virus (HIV) prevention, mammography rates and caesarean birth delivery rates. In a Cochrane review 2010 it was concluded that the use of opinion leaders can successfully promote evidence-based practice. Thus, using opinion leaders within the public health sector might be one means to speed up the dissemination of health promoting and disease preventing innovations. Social network analysis has been used to trace and map networks, with focus on relationships and positions, in widely spread arenas and topics. The purpose of this study was to use social network analysis in order to identify potential opinion leaders at the arena of child health promotion in Sweden. By using snowball technique a short e-mail question was spread in up to five links, starting from seven initially invited persons. This inquiry resulted in a network consisting of 153 individuals. The most often mentioned actors were researchers, public health officials and paediatricians, or a combination of these professions. Four single individuals were mentioned by five to seven other persons in the network. These individuals obviously possess qualities that make other professionals within the public health sector listen to and trust them. Social network analysis seemed to be a useful method to identify influential persons with high credibility, i.e. potential opinion leaders, at the arena of child health promotion in Sweden. If genuine opinion leaders could be identified directed measures can be carried out in order to spread new and relevant knowledge. This may facilitate for public health actors at the local, regional and national level to more rapidly progress innovations into everyday practice. However

  3. Yogurt and Cardiometabolic Diseases: A Critical Review of Potential Mechanisms.

    Science.gov (United States)

    Fernandez, Melissa Anne; Panahi, Shirin; Daniel, Noémie; Tremblay, Angelo; Marette, André

    2017-11-01

    Associations between yogurt intake and risk of diet-related cardiometabolic diseases (CMDs) have been the subject of recent research in epidemiologic nutrition. A healthy dietary pattern has been identified as a pillar for the prevention of weight gain and CMDs. Epidemiologic studies suggest that yogurt consumption is linked to healthy dietary patterns, lifestyles, and reduced risk of CMDs, particularly type 2 diabetes. However, to our knowledge, few to no randomized controlled trials have investigated yogurt intake in relation to cardiometabolic clinical outcomes. Furthermore, there has been little attempt to clarify the mechanisms that underlie the potential beneficial effects of yogurt consumption on CMDs. Yogurt is a nutrient-dense dairy food and has been suggested to reduce weight gain and prevent CMDs by contributing to intakes of protein, calcium, bioactive lipids, and several other micronutrients. In addition, fermentation with bacterial strains generates bioactive peptides, resulting in a potentially greater beneficial effect of yogurt on metabolic health than nonfermented dairy products such as milk. To date, there is little concrete evidence that the mechanisms proposed in observational studies to explain positive results of yogurt on CMDs or parameters are valid. Many proposed mechanisms are based on assumptions that commercial yogurts contain strain-specific probiotics, that viable yogurt cultures are present in adequate quantities, and that yogurt provides a minimum threshold dose of nutrients or bioactive components capable of exerting a physiologic effect. Therefore, the primary objective of this review is to investigate the plausibility of potential mechanisms commonly cited in the literature in order to shed light on the inverse associations reported between yogurt intake and various cardiometabolic health parameters that are related to its nutrient profile, bacterial constituents, and food matrix. This article reviews current gaps and challenges

  4. Jupiter: Peer-to-Peer Networking Platform over Heterogeneous Networks

    Directory of Open Access Journals (Sweden)

    Norihiro Ishikawa

    2006-10-01

    Full Text Available Peer-to-peer has entered the public limelight over the last few years. Several research projects are underway on peer-to-peer technologies, but no definitive conclusion is currently available. Compared with traditional Internet technologies, peer-to-peer has the potential to realize highly scalable, extensible, and efficient distributed applications. This is because its basic functions realize resource discovery, resource sharing, and load balancing in a highly distributed manner. An easy prediction is the emergence of an environment in which many sensors, people, and many different kinds of objects exist, move, and communicate with one another. Peer-to-peer is one of the most important and suitable technologies for such networking since it supports discovery mechanisms, simple one-to-one communication between devices, free and extensible distribution of resources, and distributed search to handle the enormous number of resources. The purpose of this study is to explore a universal peer-to-peer network architecture that will allow various devices to communicate with one another across various networks. We have been designing architecture and protocols for realizing peer-to-peer networking among various devices. We are currently designing APIs that are available for various peer-to-peer applications and are implementing a prototype called "Jupiter" as a peer-to-peer networking platform over heterogeneous networks.

  5. Sparks in the Fog: Social and Economic Mechanisms as Enablers for Community Network Clouds

    Directory of Open Access Journals (Sweden)

    Muhammad Amin KHAN

    2014-10-01

    Full Text Available Internet and communication technologies have lowered the costs of enabling individuals and communities to collaborate together. This collaboration has provided new services like user-generated content and social computing, as evident from success stories like Wikipedia. Through collaboration, collectively built infrastructures like community wireless mesh networks where users provide the communication network, have also emerged. Community networks have demonstrated successful bandwidth sharing, but have not been able to extend their collective effort to other computing resources like storage and processing. The success of cloud computing has been enabled by economies of scale and the need for elastic, flexible and on-demand provisioning of computing services. The consolidation of today’s cloud technologies offers now the possibility of collectively built community clouds, building upon user-generated content and user-provided networks towards an ecosystem of cloud services. We explore in this paper how social and economic mechanisms can play a role in overcoming the barriers of voluntary resource provisioning in such community clouds, by analysing the costs involved in building these services and how they give value to the participants. We indicate socio-economic policies and how they can be implemented in community networks, to ease the uptake and ensure the sustainability of community clouds.

  6. Electromechanical systems in microtechnology and mechatronics. Electrical, mechanical and acoustic networks, their interactions and applications

    Energy Technology Data Exchange (ETDEWEB)

    Lenk, Arno; Pfeifer, Guenther [Dresden Univ. of Technology (Germany). Faculty of Electrical and Computer Engineering; Ballas, Ruediger G. [Karl Mayer Textile Machinery, Obertshausen (Germany); Werthschuetzky, Roland [Darmstadt Univ. of Technology (Germany). Inst. for Electromechanical Design

    2011-07-01

    Electromechanical systems consisting of electrical, mechanical and acoustic subsystems are of special importance in various technical fields, e.g. precision device engineering, sensor and actuator technology, electroacoustics and medical engineering. Based on a circuit-oriented representation, providing readers with a descriptive engineering design method for these systems is the goal of this textbook. It offers an easy and fast introduction to mechanical, acoustic, fluid, thermal and hydraulic problems through the application of circuit-oriented basic knowledge. The network description methodology, presented in detail, is extended to finite network elements and combined with the finite element method (FEM): the combination of the advantages of both description methods results in novel approaches, especially in the higher frequency range. The book offers numerous current examples of both the design of sensors and actuators and that of direct coupled sensor-actuator systems. The appendix provides more extensive fundamentals for signal description, as well as a compilation of important material characteristics. The textbook is suitable both for graduate students and for engineers working in the fields of electrical engineering, information technology, mechatronics, microtechnology, and mechanical and medical engineering. (orig.)

  7. Estimation of solar potential in Turkey by artificial neural networks using meteorological and geographical data

    Energy Technology Data Exchange (ETDEWEB)

    Sozen, Adnan; Ozalp, Mehmet [Gazi Univ., Mechanical Education Dept., Ankara (Turkey); Arcaklioglu, Erol [Krkkale Univ., Mechanical Engineering Dept., Krkkale (Turkey)

    2004-11-01

    Turkey is located at the Mediterranean at 36 deg and 42 deg N latitudes and has a typical Mediterranean climate. The solar energy potential is very high in Turkey. The yearly average solar radiation is 3.6 kW h/m{sup 2} day, and the total yearly radiation period is {approx}2610 h. This study consists of two cases. Firstly, the main focus of this study is to put forward the solar energy potential in Turkey using artificial neural networks (ANNs). Secondly, in this study, the best approach was investigated for each station by using different learning algorithms and a logistic sigmoid transfer function in the neural network with developed software. In order to train the neural network, meteorological data for last three years (2000-2002) from 17 stations (Ankara, Samsun, Edirne, Istanbul-Goztepe, Van, Izmir, Denizli, Sanl urfa, Mersin, Adana, Gaziantep, Ayd n, Bursa, Diyarbak r, Yozgat, Antalya and Mugla) spread over Turkey were used as training (11 stations) and testing (6 stations) data. Meteorological and geographical data (latitude, longitude, altitude, month, mean sunshine duration and mean temperature) are used in the input layer of the network. Solar radiation is in the output layer. The maximum mean absolute percentage error was found to be less than 6.735% and R{sup 2} values were found to be about 99.893% for the testing stations. However, these values were found to be 4.398% and 99.965% for the training stations. The trained and tested ANN models show greater accuracy for evaluating the solar resource possibilities in regions where a network of monitoring stations has not been established in Turkey. The predicted solar potential values from the ANN are given in the form of monthly maps. These maps are of prime importance for different working disciplines, like scientists, architects, meteorologists and solar engineers, in Turkey. The predictions from the ANN models could enable scientists to locate and design solar energy systems in Turkey and determine the

  8. Estimation of solar potential in Turkey by artificial neural networks using meteorological and geographical data

    International Nuclear Information System (INIS)

    Soezen, Adnan; Arcaklioglu, Erol; Oezalp, Mehmet

    2004-01-01

    Turkey is located at the Mediterranean at 36 deg. and 42 deg. N latitudes and has a typical Mediterranean climate. The solar energy potential is very high in Turkey. The yearly average solar radiation is 3.6 kW h/m 2 day, and the total yearly radiation period is ∼2610 h. This study consists of two cases. Firstly, the main focus of this study is to put forward the solar energy potential in Turkey using artificial neural networks (ANNs). Secondly, in this study, the best approach was investigated for each station by using different learning algorithms and a logistic sigmoid transfer function in the neural network with developed software. In order to train the neural network, meteorological data for last three years (2000-2002) from 17 stations (Ankara, Samsun, Edirne, Istanbul-Goeztepe, Van, Izmir, Denizli, Sanliurfa, Mersin, Adana, Gaziantep, Aydin, Bursa, Diyarbakir, Yozgat, Antalya and Mugla) spread over Turkey were used as training (11 stations) and testing (6 stations) data. Meteorological and geographical data (latitude, longitude, altitude, month, mean sunshine duration and mean temperature) are used in the input layer of the network. Solar radiation is in the output layer. The maximum mean absolute percentage error was found to be less than 6.735% and R 2 values were found to be about 99.893% for the testing stations. However, these values were found to be 4.398% and 99.965% for the training stations. The trained and tested ANN models show greater accuracy for evaluating the solar resource possibilities in regions where a network of monitoring stations has not been established in Turkey. The predicted solar potential values from the ANN are given in the form of monthly maps. These maps are of prime importance for different working disciplines, like scientists, architects, meteorologists and solar engineers, in Turkey. The predictions from the ANN models could enable scientists to locate and design solar energy systems in Turkey and determine the best solar

  9. Software Defined Networking

    DEFF Research Database (Denmark)

    Caba, Cosmin Marius

    Network Service Providers (NSP) often choose to overprovision their networks instead of deploying proper Quality of Services (QoS) mechanisms that allow for traffic differentiation and predictable quality. This tendency of overprovisioning is not sustainable for the simple reason that network...... resources are limited. Hence, to counteract this trend, current QoS mechanisms must become simpler to deploy and operate, in order to motivate NSPs to employ QoS techniques instead of overprovisioning. Software Defined Networking (SDN) represents a paradigm shift in the way telecommunication and data...... generic perspective (e.g. service provisioning speed, resources availability). As a result, new mechanisms for providing QoS are proposed, solutions for SDN-specific QoS challenges are designed and tested, and new network management concepts are prototyped, all aiming to improve QoS for network services...

  10. Synaptic potentiation facilitates memory-like attractor dynamics in cultured in vitro hippocampal networks.

    Directory of Open Access Journals (Sweden)

    Mark Niedringhaus

    Full Text Available Collective rhythmic dynamics from neurons is vital for cognitive functions such as memory formation but how neurons self-organize to produce such activity is not well understood. Attractor-based computational models have been successfully implemented as a theoretical framework for memory storage in networks of neurons. Additionally, activity-dependent modification of synaptic transmission is thought to be the physiological basis of learning and memory. The goal of this study is to demonstrate that using a pharmacological treatment that has been shown to increase synaptic strength within in vitro networks of hippocampal neurons follows the dynamical postulates theorized by attractor models. We use a grid of extracellular electrodes to study changes in network activity after this perturbation and show that there is a persistent increase in overall spiking and bursting activity after treatment. This increase in activity appears to recruit more "errant" spikes into bursts. Phase plots indicate a conserved activity pattern suggesting that a synaptic potentiation perturbation to the attractor leaves it unchanged. Lastly, we construct a computational model to demonstrate that these synaptic perturbations can account for the dynamical changes seen within the network.

  11. Models of intracellular mechanisms of plant bioelectrical potentials caused by combined stimulation

    Directory of Open Access Journals (Sweden)

    D. V. Chernetchenko

    2014-10-01

    Full Text Available This paper deals with bioelectrical potentials of the plants recorded during different types of stimuli and combined stimulus as well. All registrations were observed on the leaves of the corn. We used different stimuli, such as cold, heat, photo- and electrical stimulation, and certain combination of this stimuli. Hardware and software system for automated recording of bioelectrical potentials has been successfully used in this work. We proposed the universal pattern of bioelectrical potentials’ recording which allowed to detect the response of the biological object to different stimuli and various combinations of these stimuli. This pattern can be used for the deeper understanding of biological mechanisms of electrical potentials’ generation in cells and discovering of processes of accommodation of whole organisms to these stimuli. Integrated system of recording and biometrical processing was used for analysis of corn leaves electrical responses to the thermal stimuli. The dynamics of these potentials was studied, with the quantitative analysis of the potential level stabilization.We calculated the ratio of amplitude of response potentials to the first response amplitude. Mathematical models of the plant cell were used for studying of intracellular mechanisms of biopotentials gereration. As a result of modeling, we revealed that electrical response of the cells was based on selectiveconductivity of cell membrane for Н+ and Ca2+ ions. Therefore, we showed the biophysical relation of plant potentials to underlying intracellular biophysical mechanisms during thermal and combined stimulation.

  12. Molecular System Dynamics for Self-Organization in Heterogeneous Wireless Networks

    Directory of Open Access Journals (Sweden)

    Milner StuartD

    2010-01-01

    Full Text Available We have been looking at the properties of physical configurations that occur in nature in order to characterize, predict, and control network robustness in dynamic communication networks. Our framework is based on the definition of a potential energy function to characterize robustness in communication networks and the study of first- and second-order variations of the potential energy to provide prediction and control strategies for network-performance optimization. This paper describes novel investigations within this framework that draw from molecular system dynamics. The Morse potential, which governs the energy stored in bonds within molecules, is considered for the characterization of the potential energy of communication links in the presence of physical constraints such as the power available at the transmitters in a network. The inclusion of the Morse potential translates into improved control strategies, where forces on network nodes drive the release, retention, or reconfiguration of communication links based on their role within the network architecture. The performance of the proposed approach is measured in terms of the number of source-to-destination connections that have an end-to-end communications path. Simulation results show the effectiveness of our control mechanism, where the physical topology reorganizes to maximize the number of source-to-destination communicating pairs. The algorithms developed are completely distributed, show constant time complexity and produce optimal solutions from local interactions, thus preserving the system's self-organizing capability.

  13. Statistical mechanics of the international trade network.

    Science.gov (United States)

    Fronczak, Agata; Fronczak, Piotr

    2012-05-01

    Analyzing real data on international trade covering the time interval 1950-2000, we show that in each year over the analyzed period the network is a typical representative of the ensemble of maximally random weighted networks, whose directed connections (bilateral trade volumes) are only characterized by the product of the trading countries' GDPs. It means that time evolution of this network may be considered as a continuous sequence of equilibrium states, i.e., a quasistatic process. This, in turn, allows one to apply the linear response theory to make (and also verify) simple predictions about the network. In particular, we show that bilateral trade fulfills a fluctuation-response theorem, which states that the average relative change in imports (exports) between two countries is a sum of the relative changes in their GDPs. Yearly changes in trade volumes prove that the theorem is valid.

  14. A Fuzzy Collusive Attack Detection Mechanism for Reputation Aggregation in Mobile Social Networks: A Trust Relationship Based Perspective

    Directory of Open Access Journals (Sweden)

    Bo Zhang

    2016-01-01

    Full Text Available While the mechanism of reputation aggregation proves to be an effective scheme for indicating an individual’s trustworthiness and further identifying malicious ones in mobile social networks, it is vulnerable to collusive attacks from malicious nodes of collaborative frauds. To conquer the challenge of detecting collusive attacks and then identifying colluders for the reputation system in mobile social networks, a fuzzy collusive attack detection mechanism (FCADM is proposed based on nodes’ social relationships, which comprises three parts: trust schedule, malicious node selection, and detection traversing strategy. In the first part, the trust schedule provides the calculation method of interval valued fuzzy social relationships and reputation aggregation for nodes in mobile social networks; further, a set of fuzzy valued factors, that is, item judgment factor, node malicious factor, and node similar factor, is given for evaluating the probability of collusive fraud happening and identifying single malicious nodes in the second part; and moreover, a detection traversing strategy is given based on random walk algorithm under the perspectives of fuzzy valued nodes’ trust schedules and proposed malicious factors. Finally, our empirical results and analysis show that the proposed mechanism in this paper is feasible and effective.

  15. Value Assessment of Distribution Network Reconfiguration: A Danish Case Study

    DEFF Research Database (Denmark)

    Vaskantiras, Georgios; You, Shi

    2016-01-01

    . This paper presents a case study-based analysis to explore the potential value of reconfiguration in detail. The study is performed using a 10kV distribution grid of Denmark, while reconfiguration is applied to minimize the energy losses under both normal and post-fault conditions. The results show......Distribution network reconfiguration is a mechanism that can improve the distribution system performance from multiple perspectives. In the context of smart grid wherein the degrees of automation and intelligence are high, the potential value of network reconfiguration can be significant...

  16. Multilayer network representation of membrane potential and cytosolic calcium concentration dynamics in beta cells

    International Nuclear Information System (INIS)

    Gosak, Marko; Dolenšek, Jurij; Markovič, Rene; Slak Rupnik, Marjan; Marhl, Marko; Stožer, Andraž

    2015-01-01

    Highlights: • Physiological processes within and among pancreatic beta cells are very complex. • We analyze the simultaneous recordings of membrane potential and calcium dynamics. • We represent the interaction patterns among beta cells as a multilayer network. • The nature of the intracellular dynamics is found to rely on the network structure. - Abstract: Modern theory of networks has been recognized as a very successful methodological concept for the description and analysis of complex systems. However, some complex systems are more complex than others. For instance, several real-life systems are constituted by interdependent subsystems and their elements are subjected to different types of interactions that can also change with time. Recently, the multilayer network formalism has been proposed as a general theoretical framework for the description and analysis of such multi-dimensional complex systems and is acquiring more and more prominence in terms of a new research direction. In the present study, we use this methodology for the description of functional connectivity patterns and signal propagation between pancreatic beta cells in an islet of Langerhans at the levels of membrane potential (MP) and cytosolic calcium concentration ([Ca"2"+]_c) dynamics to study the extent of overlap in the two networks and to clarify whether time lags between the two signals in individual cells are in any way dependent on the role these cells play in the functional networks. The two corresponding network layers are constructed on the basis of signal directions and pairwise correlations, whereas the interlayer connections represent the time lag between both measured signals. Our results confirm our previous finding that both MP and [Ca"2"+]_c change spread across an islet in the form of a depolarization and a [Ca"2"+]_c wave, respectively. Both types of waves follow nearly the same path and the networks in both layers have a similar but not entirely the same structure

  17. High-tension electricity network expansions in Argentina: decision mechanisms and willingness-to-pay revelation

    Energy Technology Data Exchange (ETDEWEB)

    Chisari, O.O. [Departamento de Economia y Finanzas, Universidad Argentina de la Empresa, Chile 1142 lo piso, 1073 Buenos Aires (Argentina); Dal-Bo, P. [Department of Economics, University of California, Los Angeles, CA (United States); Romero, C.A. [Departamento de Economia y Finanzas and Centro de Estudios Economicos de la Regulacion, Universidad Argentina de la Empresa, Buenos Aires (Argentina)

    2001-11-01

    This paper describes the procedures established by the present regulation for high-tension network expansions, studies its optimality and points its main problems. According to the present regulatory scheme, the decision to expand the high-tension network system is on the hands of the private sector. A simple model of the Argentine electricity system and its regulation allowed the simulation of cases in which the present 'Public Contest' method could result in the rejection of socially desirable projects and the acceptance of undesirable ones. Three main reasons for the existence of wrong incentives to investment are found. First, since consumers are not included in the mechanism, they have no way to reveal their willingness-to-pay for the investment. Second, the approximation of the future use of the line is done in such a way that it leaves important nodes under represented, thereby affecting the optimality of the mechanism. Third, the profit agents obtain from a line may not be related to their use, e.g. the generators profits depend also on generation costs.

  18. High-tension electricity network expansions in Argentina: decision mechanisms and willingness-to-pay revelation

    International Nuclear Information System (INIS)

    Chisari, O.O.; Dal-Bo, P.; Romero, C.A.

    2001-01-01

    This paper describes the procedures established by the present regulation for high-tension network expansions, studies its optimality and points its main problems. According to the present regulatory scheme, the decision to expand the high-tension network system is on the hands of the private sector. A simple model of the Argentine electricity system and its regulation allowed the simulation of cases in which the present 'Public Contest' method could result in the rejection of socially desirable projects and the acceptance of undesirable ones. Three main reasons for the existence of wrong incentives to investment are found. First, since consumers are not included in the mechanism, they have no way to reveal their willingness-to-pay for the investment. Second, the approximation of the future use of the line is done in such a way that it leaves important nodes under represented, thereby affecting the optimality of the mechanism. Third, the profit agents obtain from a line may not be related to their use, e.g. the generators profits depend also on generation costs

  19. Evaluating the mechanical properties of E-Glass fiber/carbon fiber reinforced interpenetrating polymer networks

    Directory of Open Access Journals (Sweden)

    G. Suresh

    2015-02-01

    Full Text Available A series of vinyl ester and polyurethane interpenetrating polymer networks were prepared by changing the component ratios of VER (Vinyl ester and PU (Polyurethane and the polymerization process was confirmed with Fourier Transform infrared spectroscopy. IPN (Inter Penetrating Polymer Network - VER/PU reinforced Glass and carbon fiber composite laminates were made using the Hand lay up technique. The Mechanical properties of the E-glass and carbon fiber specimens were compared from tests including Tensile, Compressive, Flexural, ILSS (Inter Laminar Shear Strength, Impact & Head Deflection Test (HDT. The IPN Reinforced Carbon fiber specimen showed better results in all the tests than E-Glass fibre reinforced IPN laminate with same thickness of the specimen, according to ASTM standards. It was found that the combination of 60%VER and 40%PU IPN exhibits better impact strength and maximum elongation at break, but at the slight expense of mechanical properties such as tensile, compressive, flexural, ILSS properties. The morphology of the unreinforced and reinforced composites was analyzed with help of scanning electron microscopy.

  20. Microstructure and Mechanical Properties of Heterogeneous Ceramic-Polymer Composite Using Interpenetrating Network

    International Nuclear Information System (INIS)

    Eun-Hee, K.; Yeon-Gil, J.; Chang-Yong, J.

    2012-01-01

    Prepolymer, which can be polymerized by a photo, has been infiltrated into a porous ceramic to improve the addition effect of polymer into the ceramic, as a function of the functionality of prepolymer. It induces the increase in the mechanical properties of the ceramic. The porous alumina (Al 2 O 3 ) and the polyurethane acrylate (PUA) with a network structure by photo-polymerization were used as the matrix and infiltration materials, respectively. The porous Al 2 O 3 matrix without the polymer shows lower values in fracture strength than the composites, since the stress is transmitted more quickly via propagation of cracks from intrinsic defects in the porous matrix. However, in the case of composites, the distribution of stress between hetero phases results in the improved mechanical properties. In addition, the mechanical properties of composites, such as elastic modulus and fracture strength, are enhanced with increasing the functionality of prepolymer attributed to the crosslinking density of polymer.

  1. From Single Target to Multitarget/Network Therapeutics in Alzheimer’s Therapy

    Directory of Open Access Journals (Sweden)

    Hailin Zheng

    2014-01-01

    Full Text Available Brain network dysfunction in Alzheimer’s disease (AD involves many proteins (enzymes, processes and pathways, which overlap and influence one another in AD pathogenesis. This complexity challenges the dominant paradigm in drug discovery or a single-target drug for a single mechanism. Although this paradigm has achieved considerable success in some particular diseases, it has failed to provide effective approaches to AD therapy. Network medicines may offer alternative hope for effective treatment of AD and other complex diseases. In contrast to the single-target drug approach, network medicines employ a holistic approach to restore network dysfunction by simultaneously targeting key components in disease networks. In this paper, we explore several drugs either in the clinic or under development for AD therapy in term of their design strategies, diverse mechanisms of action and disease-modifying potential. These drugs act as multi-target ligands and may serve as leads for further development as network medicines.

  2. An intelligent service matching method for mechanical equipment condition monitoring using the fibre Bragg grating sensor network

    Science.gov (United States)

    Zhang, Fan; Zhou, Zude; Liu, Quan; Xu, Wenjun

    2017-02-01

    Due to the advantages of being able to function under harsh environmental conditions and serving as a distributed condition information source in a networked monitoring system, the fibre Bragg grating (FBG) sensor network has attracted considerable attention for equipment online condition monitoring. To provide an overall conditional view of the mechanical equipment operation, a networked service-oriented condition monitoring framework based on FBG sensing is proposed, together with an intelligent matching method for supporting monitoring service management. In the novel framework, three classes of progressive service matching approaches, including service-chain knowledge database service matching, multi-objective constrained service matching and workflow-driven human-interactive service matching, are developed and integrated with an enhanced particle swarm optimisation (PSO) algorithm as well as a workflow-driven mechanism. Moreover, the manufacturing domain ontology, FBG sensor network structure and monitoring object are considered to facilitate the automatic matching of condition monitoring services to overcome the limitations of traditional service processing methods. The experimental results demonstrate that FBG monitoring services can be selected intelligently, and the developed condition monitoring system can be re-built rapidly as new equipment joins the framework. The effectiveness of the service matching method is also verified by implementing a prototype system together with its performance analysis.

  3. Predictive Modeling of Mechanical Properties of Welded Joints Based on Dynamic Fuzzy RBF Neural Network

    Directory of Open Access Journals (Sweden)

    ZHANG Yongzhi

    2016-10-01

    Full Text Available A dynamic fuzzy RBF neural network model was built to predict the mechanical properties of welded joints, and the purpose of the model was to overcome the shortcomings of static neural networks including structural identification, dynamic sample training and learning algorithm. The structure and parameters of the model are no longer head of default, dynamic adaptive adjustment in the training, suitable for dynamic sample data for learning, learning algorithm introduces hierarchical learning and fuzzy rule pruning strategy, to accelerate the training speed of model and make the model more compact. Simulation of the model was carried out by using three kinds of thickness and different process TC4 titanium alloy TIG welding test data. The results show that the model has higher prediction accuracy, which is suitable for predicting the mechanical properties of welded joints, and has opened up a new way for the on-line control of the welding process.

  4. Estimating the size of the potential market for the Kyoto flexibility mechanisms

    NARCIS (Netherlands)

    Zhang, Z.X.

    2000-01-01

    The Kyoto Protocol incorporates three flexibility mechanisms to help Annex I countries to meet their Kyoto targets at a lower overall cost. This paper aims to estimate the size of the potential market for all three mechanisms over the first commitment period. Based on the national communications

  5. Estimating the size of the potential market for the Kyoto flexibility mechanisms

    NARCIS (Netherlands)

    Zhang, Zhong Xiang

    1999-01-01

    The Kyoto Protocol incorporates emissions trading, joint implementation and the clean development mechanism to help Annex I countries to meet their Kyoto targets at a lower overall cost. This paper aims to estimate the size of the potential market for all three flexibility mechanisms under the Kyoto

  6. Microstructure and Mechanical Properties of Heterogeneous Ceramic-Polymer Composite Using Interpenetrating Network

    OpenAIRE

    Kim, Eun-Hee; Jung, Yeon-Gil; Jo, Chang-Yong

    2012-01-01

    Prepolymer, which can be polymerized by a photo, has been infiltrated into a porous ceramic to improve the addition effect of polymer into the ceramic, as a function of the functionality of prepolymer. It induces the increase in the mechanical properties of the ceramic. The porous alumina (Al2O3) and the polyurethane acrylate (PUA) with a network structure by photo-polymerization were used as the matrix and infiltration materials, respectively. The porous Al2O3 matrix without t...

  7. Integration of Electric Vehicles into the Power Distribution Network with a Modified Capacity Allocation Mechanism

    DEFF Research Database (Denmark)

    Hu, Junjie; Morais, Hugo; Sousa, Tiago

    2017-01-01

    -VPPs, considering the case of EVs charging and discharging. The three mechanisms include: (1) a market-based approach; (2) a pro-rata approach; and (3) a newly-proposed constrained market-based approach. A case study considering a 37-bus distribution network and high penetration of electric vehicles is presented...

  8. [Bone Cell Biology Assessed by Microscopic Approach. Response to mechanical stress by osteocyte network].

    Science.gov (United States)

    Komori, Toshihisa

    2015-10-01

    Osteocytes were considered to be involved in the response to mechanical stress from their network structure. However, it was difficult to prove the function because of the lack of animal models for a long time. Recently, the function of osteocytes was clarified using various knockout and transgenic mice. Osteocyte death causes bone remodeling, which is a repair process induced by osteocyte necrosis but not by the loss of the function of live osteocytes. The osteocyte network mildly inhibits bone formation and mildly stimulates bone resorption in physiological condition. In unloaded condition, it strongly inhibits bone formation and strongly stimulates bone resorption, at least in part, through the induction of Sost in osteocytes and Rankl in osteoblasts.

  9. Quantum Mechanics/Molecular Mechanics Method Combined with Hybrid All-Atom and Coarse-Grained Model: Theory and Application on Redox Potential Calculations.

    Science.gov (United States)

    Shen, Lin; Yang, Weitao

    2016-04-12

    We developed a new multiresolution method that spans three levels of resolution with quantum mechanical, atomistic molecular mechanical, and coarse-grained models. The resolution-adapted all-atom and coarse-grained water model, in which an all-atom structural description of the entire system is maintained during the simulations, is combined with the ab initio quantum mechanics and molecular mechanics method. We apply this model to calculate the redox potentials of the aqueous ruthenium and iron complexes by using the fractional number of electrons approach and thermodynamic integration simulations. The redox potentials are recovered in excellent accordance with the experimental data. The speed-up of the hybrid all-atom and coarse-grained water model renders it computationally more attractive. The accuracy depends on the hybrid all-atom and coarse-grained water model used in the combined quantum mechanical and molecular mechanical method. We have used another multiresolution model, in which an atomic-level layer of water molecules around redox center is solvated in supramolecular coarse-grained waters for the redox potential calculations. Compared with the experimental data, this alternative multilayer model leads to less accurate results when used with the coarse-grained polarizable MARTINI water or big multipole water model for the coarse-grained layer.

  10. Imaging Action Potential in Single Mammalian Neurons by Tracking the Accompanying Sub-Nanometer Mechanical Motion.

    Science.gov (United States)

    Yang, Yunze; Liu, Xian-Wei; Wang, Hui; Yu, Hui; Guan, Yan; Wang, Shaopeng; Tao, Nongjian

    2018-03-28

    Action potentials in neurons have been studied traditionally by intracellular electrophysiological recordings and more recently by the fluorescence detection methods. Here we describe a label-free optical imaging method that can measure mechanical motion in single cells with a sub-nanometer detection limit. Using the method, we have observed sub-nanometer mechanical motion accompanying the action potential in single mammalian neurons by averaging the repeated action potential spikes. The shape and width of the transient displacement are similar to those of the electrically recorded action potential, but the amplitude varies from neuron to neuron, and from one region of a neuron to another, ranging from 0.2-0.4 nm. The work indicates that action potentials may be studied noninvasively in single mammalian neurons by label-free imaging of the accompanying sub-nanometer mechanical motion.

  11. Asynchronous Group Key Distribution on top of the CC2420 Security Mechanisms for Sensor Networks

    DEFF Research Database (Denmark)

    Hansen, Morten Tranberg

    2009-01-01

    scheme with no time synchronization requirements. The scheme decreases the number of key updates by providing them on an as needed basis according to the amount of network traffic. We evaluate the CC2420 radio security mechanism and show how to use it as a basis to implement secure group communication......A sensor network is a network consisting of small, inexpensive, low-powered sensor nodes that communicate to complete a common task. Sensor nodes are characterized by having limited communication and computation capabilities, energy, and storage. They often are deployed in hostile environments...... creating a demand for encryption and authentication of the messages sent between them. Due to severe resource constraints on the sensor nodes, efficient key distribution schemes and secure communication protocols with low overhead are desired. In this paper we present an asynchronous group key distribution...

  12. Power Aware Dynamic Provisioning of HPC Networks

    Energy Technology Data Exchange (ETDEWEB)

    Groves, Taylor [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Grant, Ryan [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2015-10-01

    Future exascale systems are under increased pressure to find power savings. The network, while it consumes a considerable amount of power is often left out of the picture when discussing total system power. Even when network power is being considered, the references are frequently a decade or older and rely on models that lack validation on modern inter- connects. In this work we explore how dynamic mechanisms of an Infiniband network save power and at what granularity we can engage these features. We explore this within the context of the host controller adapter (HCA) on the node and for the fabric, i.e. switches, using three different mechanisms of dynamic link width, frequency and disabling of links for QLogic and Mellanox systems. Our results show that while there is some potential for modest power savings, real world systems need to improved responsiveness to adjustments in order to fully leverage these savings. This page intentionally left blank.

  13. Potential of isotope analysis (C, Cl) to identify dechlorination mechanisms

    Science.gov (United States)

    Cretnik, Stefan; Thoreson, Kristen; Bernstein, Anat; Ebert, Karin; Buchner, Daniel; Laskov, Christine; Haderlein, Stefan; Shouakar-Stash, Orfan; Kliegman, Sarah; McNeill, Kristopher; Elsner, Martin

    2013-04-01

    Chloroethenes are commonly used in industrial applications, and detected as carcinogenic contaminants in the environment. Their dehalogenation is of environmental importance in remediation processes. However, a detailed understanding frequently accounted problem is the accumulation of toxic degradation products such as cis-dichloroethylene (cis-DCE) at contaminated sites. Several studies have addressed the reductive dehalogenation reactions using biotic and abiotic model systems, but a crucial question in this context has remained open: Do environmental transformations occur by the same mechanism as in their corresponding in vitro model systems? The presented study shows the potential to close this research gap using the latest developments in compound specific chlorine isotope analysis, which make it possible to routinely measure chlorine isotope fractionation of chloroethenes in environmental samples and complex reaction mixtures.1,2 In particular, such chlorine isotope analysis enables the measurement of isotope fractionation for two elements (i.e., C and Cl) in chloroethenes. When isotope values of both elements are plotted against each other, different slopes reflect different underlying mechanisms and are remarkably insensitive towards masking. Our results suggest that different microbial strains (G. lovleyi strain SZ, D. hafniense Y51) and the isolated cofactor cobalamin employ similar mechanisms of reductive dechlorination of TCE. In contrast, evidence for a different mechanism was obtained with cobaloxime cautioning its use as a model for biodegradation. The study shows the potential of the dual isotope approach as a tool to directly compare transformation mechanisms of environmental scenarios, biotic transformations, and their putative chemical lab scale systems. Furthermore, it serves as an essential reference when using the dual isotope approach to assess the fate of chlorinated compounds in the environment.

  14. Electrical Potentials Observed During Frictional Stick-Slip - A Semiconductor Mechanism

    Science.gov (United States)

    Leeman, J.; Scuderi, M.; Marone, C.; Saffer, D. M.

    2013-12-01

    coincide with stick-slip failure. This behavior is consistent at both 1 and 30 μm/s loading velocity. At a load point velocity of 100μm/s, the anomalies exhibit sharp potential spikes on the order of 20 volts coincident with stick slip failure events with gradual charging between events. Experiments conducted under 100% humidity and submerged conditions showed no associated electrical anomalies. We interpret that the observed signal is a convolution of two effects: charging of the forcing blocks and anomalies associated with the stress state of the material. Charging of the blocks is accomplished by grain movement along the boundaries during initial arrangement of force chain networks. Anomalies associated with the material originate from electron holes produced when peroxy links are broken. The defects then propagate away from stressed regions during loading, separating charge. A return current results in a potential drop as a semi-homogeneous stress state is attained after failure of the force chain network. Electrical anomalies during material failure could potentially be used to remotely monitor stress states and cracking during the inter-seismic stage of the seismic cycle. Potential changes could result in detectable low-frequency signals that may signal the early stages of failure, providing a modest warning of the event.

  15. Structural network heterogeneities and network dynamics: a possible dynamical mechanism for hippocampal memory reactivation.

    Science.gov (United States)

    Jablonski, Piotr; Poe, Gina; Zochowski, Michal

    2007-03-01

    The hippocampus has the capacity for reactivating recently acquired memories and it is hypothesized that one of the functions of sleep reactivation is the facilitation of consolidation of novel memory traces. The dynamic and network processes underlying such a reactivation remain, however, unknown. We show that such a reactivation characterized by local, self-sustained activity of a network region may be an inherent property of the recurrent excitatory-inhibitory network with a heterogeneous structure. The entry into the reactivation phase is mediated through a physiologically feasible regulation of global excitability and external input sources, while the reactivated component of the network is formed through induced network heterogeneities during learning. We show that structural changes needed for robust reactivation of a given network region are well within known physiological parameters.

  16. Transcriptional Network Analysis Reveals Drought Resistance Mechanisms of AP2/ERF Transgenic Rice

    Directory of Open Access Journals (Sweden)

    Hongryul Ahn

    2017-06-01

    Full Text Available This study was designed to investigate at the molecular level how a transgenic version of rice “Nipponbare” obtained a drought-resistant phenotype. Using multi-omics sequencing data, we compared wild-type rice (WT and a transgenic version (erf71 that had obtained a drought-resistant phenotype by overexpressing OsERF71, a member of the AP2/ERF transcription factor (TF family. A comprehensive bioinformatics analysis pipeline, including TF networks and a cascade tree, was developed for the analysis of multi-omics data. The results of the analysis showed that the presence of OsERF71 at the source of the network controlled global gene expression levels in a specific manner to make erf71 survive longer than WT. Our analysis of the time-series transcriptome data suggests that erf71 diverted more energy to survival-critical mechanisms related to translation, oxidative response, and DNA replication, while further suppressing energy-consuming mechanisms, such as photosynthesis. To support this hypothesis further, we measured the net photosynthesis level under physiological conditions, which confirmed the further suppression of photosynthesis in erf71. In summary, our work presents a comprehensive snapshot of transcriptional modification in transgenic rice and shows how this induced the plants to acquire a drought-resistant phenotype.

  17. The Capacity-Building Stewardship Model: assessment of an agricultural network as a mechanism for improving regional agroecosystem sustainability

    Directory of Open Access Journals (Sweden)

    Alison J. Duff

    2017-03-01

    Full Text Available Working lands have potential to meet agricultural production targets while serving as reservoirs of biological diversity and as sources of ecological services. Yet agricultural policy creates disincentives for this integration of conservation and production goals. While necessary, the development of a policy context that promotes agroecosystem sustainability will take time, and successful implementation will depend on a receptive agricultural audience. As the demands placed on working lands grow, there is a need for regional support networks that build agricultural producers' capacity for land stewardship. We used a social-ecological system framework to illustrate the Healthy Grown Potato Program as an agricultural network case study. Our Capacity-Building Stewardship Model reflects a 20-year experience working in collaboration with potato growers certified under an ecolabel in Wisconsin, USA. The model applies an evolving, modular farm stewardship standard to the entire farm - croplands and noncroplands. The model demonstrates an effective process for facilitating communication and shared learning among program participants, including agricultural producers, university extension specialists, nonprofit conservation partners, and industry representatives. The limitation of the model in practice has been securing funding to support expansion of the program and to ensure that the ecolabel standard is responsive to changes in the social-ecological system. Despite this constraint, the Capacity-Building Stewardship Model reveals an important mechanism for building regional commitment to conservation, with agricultural producers in a leadership role as architects, adopters, and advocates for stewardship behavior. Our experience provides important insight for the application of agri-environment schemes on private lands. The durability of a conservation ethic on working farms is likely to be enhanced when networks engage and support producers in an

  18. Potential mechanisms linking probiotics to diabetes: a narrative review of the literature

    OpenAIRE

    Miraghajani, Maryam; Dehsoukhteh, Somayeh Shahraki; Rafie, Nahid; Hamedani, Sahar Golpour; Sabihi, Sima; Ghiasvand, Reza

    2017-01-01

    ABSTRACT CONTEXT AND OBJECTIVE: Some studies have suggested a wide range of possible mechanisms through which probiotics may play a role in diabetes prevention and treatment. However, the underlying mechanisms are not fully understood. We conducted this study to review the potential mechanisms suggested for the effect of probiotics in diabetes. DESIGN AND SETTING: Narrative review conducted at the Food Security Research Center of Isfahan. METHODS: A search in the electronic databases ME...

  19. Social networks, social support mechanisms, and quality of life after breast cancer diagnosis.

    Science.gov (United States)

    Kroenke, Candyce H; Kwan, Marilyn L; Neugut, Alfred I; Ergas, Isaac J; Wright, Jaime D; Caan, Bette J; Hershman, Dawn; Kushi, Lawrence H

    2013-06-01

    We examined mechanisms through which social relationships influence quality of life (QOL) in breast cancer survivors. This study included 3,139 women from the Pathways Study who were diagnosed with breast cancer from 2006 to 2011 and provided data on social networks (the presence of a spouse or intimate partner, religious/social ties, volunteering, and numbers of close friends and relatives), social support (tangible support, emotional/informational support, affection, positive social interaction), and QOL, measured by the FACT-B, approximately 2 months post diagnosis. We used logistic models to evaluate associations between social network size, social support, and lower versus higher than median QOL scores. We further stratified by stage at diagnosis and treatment. In multivariate-adjusted analyses, women who were characterized as socially isolated had significantly lower FACT-B (OR = 2.18, 95 % CI: 1.72-2.77), physical well-being (WB) (OR = 1.61, 95 % CI: 1.27-2.03), functional WB (OR = 2.08, 95 % CI: 1.65-2.63), social WB (OR = 3.46, 95 % CI: 2.73-4.39), and emotional WB (OR = 1.67, 95 % CI: 1.33-2.11) scores and higher breast cancer symptoms (OR = 1.48, 95 % CI: 1.18-1.87) compared with socially integrated women. Each social network member independently predicted higher QOL. Simultaneous adjustment for social networks and social support partially attenuated associations between social networks and QOL. The strongest mediator and type of social support that was most predictive of QOL outcomes was "positive social interaction." However, each type of support was important depending on outcome, stage, and treatment status. Larger social networks and greater social support were related to higher QOL after a diagnosis of breast cancer. Effective social support interventions need to evolve beyond social-emotional interventions and need to account for disease severity and treatment status.

  20. Social networks, social support mechanisms, and quality of life after breast cancer diagnosis

    Science.gov (United States)

    Kroenke, Candyce H; Kwan, Marilyn L.; Neugut, Alfred I.; Ergas, Isaac J.; Wright, Jaime D.; Caan, Bette J.; Hershman, Dawn; Kushi, Lawrence H.

    2013-01-01

    Purpose We examined mechanisms through which social relationships influence quality of life (QOL) in breast cancer survivors. Methods This study included 3,139 women from the Pathways Study who were diagnosed with breast cancer from 2006-2011 and provided data on social networks (presence of spouse or intimate partner, religious/social ties, volunteering, and numbers of close friends and relatives), social support (tangible, emotional/informational, affection, positive social interaction), and quality of life (QOL), measured by the FACT-B, approximately two months post-diagnosis. We used logistic models to evaluate associations between social network size, social support, and lower vs. higher than median QOL scores. We further stratified by stage at diagnosis and treatment. Results In multivariate-adjusted analyses, women who were characterized as socially isolated had significantly lower FACT-B (OR=2.18, 95%CI:1.72-2.77), physical well-being (WB) (OR=1.61, 95%CI:1.27-2.03), functional WB (OR=2.08, 95%CI:1.65-2.63), social WB (OR=3.46, 95%CI:2.73-4.39), and emotional WB (OR=1.67, 95%CI:1.33-2.11) scores and higher breast cancer symptoms (OR=1.48, 95%CI:1.18-1.87), compared with socially integrated women. Each social network member independently predicted higher QOL. Simultaneous adjustment for social networks and social support partially attenuated associations between social networks and QOL. The strongest mediator and type of social support that was most predictive of QOL outcomes was “positive social interaction”. However, each type of support was important depending on outcome, stage, and treatment status. Conclusions Larger social networks and greater social support were related to higher QOL after a diagnosis of breast cancer. Effective social support interventions need to evolve beyond social-emotional interventions and need to account for disease severity and treatment status. PMID:23657404

  1. Variability in usual care mechanical ventilation for pediatric acute lung injury: the potential benefit of a lung protective computer protocol.

    Science.gov (United States)

    Khemani, Robinder G; Sward, Katherine; Morris, Alan; Dean, J Michael; Newth, Christopher J L

    2011-11-01

    Although pediatric intensivists claim to embrace lung protective ventilation for acute lung injury (ALI), ventilator management is variable. We describe ventilator changes clinicians made for children with hypoxemic respiratory failure, and evaluate the potential acceptability of a pediatric ventilation protocol. This was a retrospective cohort study performed in a tertiary care pediatric intensive care unit (PICU). The study period was from January 2000 to July 2007. We included mechanically ventilated children with PaO(2)/FiO(2) (P/F) ratio less than 300. We assessed variability in ventilator management by evaluating actual changes to ventilator settings after an arterial blood gas (ABG). We evaluated the potential acceptability of a pediatric mechanical ventilation protocol we adapted from National Institutes of Health/National Heart, Lung, and Blood Institute (NIH/NHLBI) Acute Respiratory Distress Syndrome (ARDS) Network protocols by comparing actual practice changes in ventilator settings to changes that would have been recommended by the protocol. A total of 2,719 ABGs from 402 patients were associated with 6,017 ventilator settings. Clinicians infrequently decreased FiO(2), even when the PaO(2) was high (>68 mmHg). The protocol would have recommended more positive end expiratory pressure (PEEP) than was used in actual practice 42% of the time in the mid PaO(2) range (55-68 mmHg) and 67% of the time in the low PaO(2) range (ventilator rate (VR) when the protocol would have recommended a change, even when the pH was greater than 7.45 with PIP at least 35 cmH(2)O. There may be lost opportunities to minimize potentially injurious ventilator settings for children with ALI. A reproducible pediatric mechanical ventilation protocol could prompt clinicians to make ventilator changes that are consistent with lung protective ventilation.

  2. An Efficient Network Coding-Based Fault-Tolerant Mechanism in WBAN for Smart Healthcare Monitoring Systems

    Directory of Open Access Journals (Sweden)

    Yuhuai Peng

    2017-08-01

    Full Text Available As a key technology in smart healthcare monitoring systems, wireless body area networks (WBANs can pre-embed sensors and sinks on body surface or inside bodies for collecting different vital signs parameters, such as human Electrocardiograph (ECG, Electroencephalograph (EEG, Electromyogram (EMG, body temperature, blood pressure, blood sugar, blood oxygen, etc. Using real-time online healthcare, patients can be tracked and monitored in normal or emergency conditions at their homes, hospital rooms, and in Intensive Care Units (ICUs. In particular, the reliability and effectiveness of the packets transmission will be directly related to the timely rescue of critically ill patients with life-threatening injuries. However, traditional fault-tolerant schemes either have the deficiency of underutilised resources or react too slowly to failures. In future healthcare systems, the medical Internet of Things (IoT for real-time monitoring can integrate sensor networks, cloud computing, and big data techniques to address these problems. It can collect and send patient’s vital parameter signal and safety monitoring information to intelligent terminals and enhance transmission reliability and efficiency. Therefore, this paper presents a design in healthcare monitoring systems for a proactive reliable data transmission mechanism with resilience requirements in a many-to-one stream model. This Network Coding-based Fault-tolerant Mechanism (NCFM first proposes a greedy grouping algorithm to divide the topology into small logical units; it then constructs a spanning tree based on random linear network coding to generate linearly independent coding combinations. Numerical results indicate that this transmission scheme works better than traditional methods in reducing the probability of packet loss, the resource redundant rate, and average delay, and can increase the effective throughput rate.

  3. Premature saturation in backpropagation networks: Mechanism and necessary conditions

    International Nuclear Information System (INIS)

    Vitela, J.E.; Reifman, J.

    1997-01-01

    The mechanism that gives rise to the phenomenon of premature saturation of the output units of feedforward multilayer neural networks during training with the standard backpropagation algorithm is described. The entire process of premature saturation is characterized by three distinct stages and it is concluded that the momentum term plays the leading role in the occurrence of the phenomenon. The necessary conditions for the occurrence of premature saturation are presented and a new method is proposed, based on these conditions, that eliminates the occurrence of the phenomenon. Validity of the conditions and the proposed method are illustrated through simulation results. Three case studies are presented. The first two came from a training session for classification of three component failures in a nuclear power plant. The last case, comes from a training session for classification of welded fuel elements

  4. Spike frequency adaptation is a possible mechanism for control of attractor preference in auto-associative neural networks

    Science.gov (United States)

    Roach, James; Sander, Leonard; Zochowski, Michal

    Auto-associative memory is the ability to retrieve a pattern from a small fraction of the pattern and is an important function of neural networks. Within this context, memories that are stored within the synaptic strengths of networks act as dynamical attractors for network firing patterns. In networks with many encoded memories, some attractors will be stronger than others. This presents the problem of how networks switch between attractors depending on the situation. We suggest that regulation of neuronal spike-frequency adaptation (SFA) provides a universal mechanism for network-wide attractor selectivity. Here we demonstrate in a Hopfield type attractor network that neurons minimal SFA will reliably activate in the pattern corresponding to a local attractor and that a moderate increase in SFA leads to the network to converge to the strongest attractor state. Furthermore, we show that on long time scales SFA allows for temporal sequences of activation to emerge. Finally, using a model of cholinergic modulation within the cortex we argue that dynamic regulation of attractor preference by SFA could be critical for the role of acetylcholine in attention or for arousal states in general. This work was supported by: NSF Graduate Research Fellowship Program under Grant No. DGE 1256260 (JPR), NSF CMMI 1029388 (MRZ) and NSF PoLS 1058034 (MRZ & LMS).

  5. Managerial Challenges Within Networks - Emphasizing the Paradox of Network Participation

    DEFF Research Database (Denmark)

    Jakobsen, Morten

    2003-01-01

    Flexibility and access to numerous resources are essential benefits associated with network participation. An important aspect of managing the network participation of a company is to maintain a dynamic portfolio of partners, and thereby keep up the strategic opportunities for development. However......, maintaining the dynamics within a network seems to be a complex challenge. There is a risk that the network ends up in The Paradox of Network Participation. The desired renewal and flexibility are not utilised because the involved parties preserve the existing networks structure consisting of the same...... and thereby sort out the paradox of network participation. Trust and information are mechanisms employed to absorb uncertainty. The relationship between trust and the requirement for information depends on the maturity of the relationship. When trust becomes too important as uncertainty absorption mechanism...

  6. Managerial challenges within networks: emphasizing the paradox of network participation

    DEFF Research Database (Denmark)

    Jakobsen, Morten

    Flexibility and access to numerous resources are essential benefits associated with network participation. An important aspect of managing the network participation of a company is to maintain a dynamic portfolio of partners, and thereby keep up the strategic opportunities for development. However......, maintaining the dynamics within a network seems to be a complex challenge. There is a risk that the network ends up in The Paradox of Network Participation. The desired renewal and flexibility are not utilised because the involved parties preserve the existing networks structure consisting of the same...... and thereby sort out the paradox of network participation. Trust and information are mechanisms employed to absorb uncertainty. The relationship between trust and the requirement for information depends on the maturity of the relationship. When trust becomes too important as uncertainty absorption mechanism...

  7. Cognitive Self-Scheduled Mechanism for Access Control in Noisy Vehicular Ad Hoc Networks

    Directory of Open Access Journals (Sweden)

    Mario Manzano

    2015-01-01

    Full Text Available Within the challenging environment of intelligent transportation systems (ITS, networked control systems such as platooning guidance of autonomous vehicles require innovative mechanisms to provide real-time communications. Although several proposals are currently under discussion, the design of a rapid, efficient, flexible, and reliable medium access control mechanism which meets the specific constraints of such real-time communications applications remains unsolved in this highly dynamic environment. However, cognitive radio (CR combines the capacity to sense the radio spectrum with the flexibility to adapt to transmission parameters in order to maximize system performance and has thus become an effective approach for the design of dynamic spectrum access (DSA mechanisms. This paper presents the enhanced noncooperative cognitive division multiple access (ENCCMA proposal combining time division multiple access (TDMA and frequency division multiple access (FDMA schemes with CR techniques to obtain a mechanism fulfilling the requirements of real-time communications. The analysis presented here considers the IEEE WAVE and 802.11p as reference standards; however, the proposed medium access control (MAC mechanism can be adapted to operate on the physical layer of different standards. The mechanism also offers the advantage of avoiding signaling, thus enhancing system autonomy as well as behavior in adverse scenarios.

  8. A neural network approach to the study of dynamics and structure of molecular systems

    International Nuclear Information System (INIS)

    Getino, C.; Sumpter, B.G.; Noid, D.W.

    1994-01-01

    Neural networks are used to study intramolecular energy flow in molecular systems (tetratomics to macromolecules), developing new techniques for efficient analysis of data obtained from molecular-dynamics and quantum mechanics calculations. Neural networks can map phase space points to intramolecular vibrational energies along a classical trajectory (example of complicated coordinate transformation), producing reasonably accurate values for any region of the multidimensional phase space of a tetratomic molecule. Neural network energy flow predictions are found to significantly enhance the molecular-dynamics method to longer time-scales and extensive averaging of trajectories for macromolecular systems. Pattern recognition abilities of neural networks can be used to discern phase space features. Neural networks can also expand model calculations by interpolation of costly quantum mechanical ab initio data, used to develop semiempirical potential energy functions

  9. The influence of social networks on self-management support: a metasynthesis.

    Science.gov (United States)

    Vassilev, Ivaylo; Rogers, Anne; Kennedy, Anne; Koetsenruijter, Jan

    2014-07-15

    There is increasing recognition that chronic illness management (CIM) is not just an individual but a collective process where social networks can potentially make a considerable contribution to improving health outcomes for people with chronic illness. However, the mechanisms (processes, activities) taking place within social networks are insufficiently understood. The aim of this review was to focus on identifying the mechanisms linking social networks with CIM. Here we consider network mechanisms as located within a broader social context that shapes practices, behaviours, and the multiplicity of functions and roles that network members fulfil. A systematic search of qualitative studies was undertaken on Medline, Embase, and Web for papers published between 1st January 2002 and 1st December 2013. Eligible for inclusion were studies dealing with diabetes, and with conditions or health behaviours relevant for diabetes management; and studies exploring the relationship between social networks, self-management, and deprivation. 25 papers met the inclusion criteria. A qualitative metasynthesis was undertaken and the review followed a line of argument synthesis. The main themes identified were: 1) sharing knowledge and experiences in a personal community; 2) accessing and mediation of resources; 3) self-management support requires awareness of and ability to deal with network relationships. These translated into line of argument synthesis in which three network mechanisms were identified. These were network navigation (identifying and connecting with relevant existing resources in a network), negotiation within networks (re-shaping relationships, roles, expectations, means of engagement and communication between network members), and collective efficacy (developing a shared perception and capacity to successfully perform behaviour through shared effort, beliefs, influence, perseverance, and objectives). These network mechanisms bring to the fore the close

  10. Grapevine rootstocks shape underground bacterial microbiome and networking but not potential functionality.

    Science.gov (United States)

    Marasco, Ramona; Rolli, Eleonora; Fusi, Marco; Michoud, Grégoire; Daffonchio, Daniele

    2018-01-03

    The plant compartments of Vitis vinifera, including the rhizosphere, rhizoplane, root endosphere, phyllosphere and carposphere, provide unique niches that drive specific bacterial microbiome associations. The majority of phyllosphere endophytes originate from the soil and migrate up to the aerial compartments through the root endosphere. Thus, the soil and root endosphere partially define the aerial endosphere in the leaves and berries, contributing to the terroir of the fruit. However, V. vinifera cultivars are invariably grafted onto the rootstocks of other Vitis species and hybrids. It has been hypothesized that the plant species determines the microbiome of the root endosphere and, as a consequence, the aerial endosphere. In this work, we test the first part of this hypothesis. We investigate whether different rootstocks influence the bacteria selected from the surrounding soil, affecting the bacterial diversity and potential functionality of the rhizosphere and root endosphere. Bacterial microbiomes from both the root tissues and the rhizosphere of Barbera cultivars, both ungrafted and grafted on four different rootstocks, cultivated in the same soil from the same vineyard, were characterized by 16S rRNA high-throughput sequencing. To assess the influence of the root genotype on the bacterial communities' recruitment in the root system, (i) the phylogenetic diversity coupled with the predicted functional profiles and (ii) the co-occurrence bacterial networks were determined. Cultivation-dependent approaches were used to reveal the plant-growth promoting (PGP) potential associated with the grafted and ungrafted root systems. Richness, diversity and bacterial community networking in the root compartments were significantly influenced by the rootstocks. Complementary to a shared bacterial microbiome, different subsets of soil bacteria, including those endowed with PGP traits, were selected by the root system compartments of different rootstocks. The interaction

  11. Grapevine rootstocks shape underground bacterial microbiome and networking but not potential functionality

    KAUST Repository

    Marasco, Ramona; Rolli, Eleonora; Fusi, Marco; Michoud, Gregoire; Daffonchio, Daniele

    2018-01-01

    The plant compartments of Vitis vinifera, including the rhizosphere, rhizoplane, root endosphere, phyllosphere and carposphere, provide unique niches that drive specific bacterial microbiome associations. The majority of phyllosphere endophytes originate from the soil and migrate up to the aerial compartments through the root endosphere. Thus, the soil and root endosphere partially define the aerial endosphere in the leaves and berries, contributing to the terroir of the fruit. However, V. vinifera cultivars are invariably grafted onto the rootstocks of other Vitis species and hybrids. It has been hypothesized that the plant species determines the microbiome of the root endosphere and, as a consequence, the aerial endosphere. In this work, we test the first part of this hypothesis. We investigate whether different rootstocks influence the bacteria selected from the surrounding soil, affecting the bacterial diversity and potential functionality of the rhizosphere and root endosphere.Bacterial microbiomes from both the root tissues and the rhizosphere of Barbera cultivars, both ungrafted and grafted on four different rootstocks, cultivated in the same soil from the same vineyard, were characterized by 16S rRNA high-throughput sequencing. To assess the influence of the root genotype on the bacterial communities' recruitment in the root system, (i) the phylogenetic diversity coupled with the predicted functional profiles and (ii) the co-occurrence bacterial networks were determined. Cultivation-dependent approaches were used to reveal the plant-growth promoting (PGP) potential associated with the grafted and ungrafted root systems.Richness, diversity and bacterial community networking in the root compartments were significantly influenced by the rootstocks. Complementary to a shared bacterial microbiome, different subsets of soil bacteria, including those endowed with PGP traits, were selected by the root system compartments of different rootstocks. The interaction

  12. Grapevine rootstocks shape underground bacterial microbiome and networking but not potential functionality

    KAUST Repository

    Marasco, Ramona

    2018-01-03

    The plant compartments of Vitis vinifera, including the rhizosphere, rhizoplane, root endosphere, phyllosphere and carposphere, provide unique niches that drive specific bacterial microbiome associations. The majority of phyllosphere endophytes originate from the soil and migrate up to the aerial compartments through the root endosphere. Thus, the soil and root endosphere partially define the aerial endosphere in the leaves and berries, contributing to the terroir of the fruit. However, V. vinifera cultivars are invariably grafted onto the rootstocks of other Vitis species and hybrids. It has been hypothesized that the plant species determines the microbiome of the root endosphere and, as a consequence, the aerial endosphere. In this work, we test the first part of this hypothesis. We investigate whether different rootstocks influence the bacteria selected from the surrounding soil, affecting the bacterial diversity and potential functionality of the rhizosphere and root endosphere.Bacterial microbiomes from both the root tissues and the rhizosphere of Barbera cultivars, both ungrafted and grafted on four different rootstocks, cultivated in the same soil from the same vineyard, were characterized by 16S rRNA high-throughput sequencing. To assess the influence of the root genotype on the bacterial communities\\' recruitment in the root system, (i) the phylogenetic diversity coupled with the predicted functional profiles and (ii) the co-occurrence bacterial networks were determined. Cultivation-dependent approaches were used to reveal the plant-growth promoting (PGP) potential associated with the grafted and ungrafted root systems.Richness, diversity and bacterial community networking in the root compartments were significantly influenced by the rootstocks. Complementary to a shared bacterial microbiome, different subsets of soil bacteria, including those endowed with PGP traits, were selected by the root system compartments of different rootstocks. The interaction

  13. Driving Interconnected Networks to Supercriticality

    Directory of Open Access Journals (Sweden)

    Filippo Radicchi

    2014-04-01

    Full Text Available Networks in the real world do not exist as isolated entities, but they are often part of more complicated structures composed of many interconnected network layers. Recent studies have shown that such mutual dependence makes real networked systems potentially exposed to atypical structural and dynamical behaviors, and thus there is an urgent necessity to better understand the mechanisms at the basis of these anomalies. Previous research has mainly focused on the emergence of atypical properties in relation to the moments of the intra- and interlayer degree distributions. In this paper, we show that an additional ingredient plays a fundamental role for the possible scenario that an interconnected network can face: the correlation between intra- and interlayer degrees. For sufficiently high amounts of correlation, an interconnected network can be tuned, by varying the moments of the intra- and interlayer degree distributions, in distinct topological and dynamical regimes. When instead the correlation between intra- and interlayer degrees is lower than a critical value, the system enters in a supercritical regime where dynamical and topological phases are no longer distinguishable.

  14. Modeling the citation network by network cosmology.

    Science.gov (United States)

    Xie, Zheng; Ouyang, Zhenzheng; Zhang, Pengyuan; Yi, Dongyun; Kong, Dexing

    2015-01-01

    Citation between papers can be treated as a causal relationship. In addition, some citation networks have a number of similarities to the causal networks in network cosmology, e.g., the similar in-and out-degree distributions. Hence, it is possible to model the citation network using network cosmology. The casual network models built on homogenous spacetimes have some restrictions when describing some phenomena in citation networks, e.g., the hot papers receive more citations than other simultaneously published papers. We propose an inhomogenous causal network model to model the citation network, the connection mechanism of which well expresses some features of citation. The node growth trend and degree distributions of the generated networks also fit those of some citation networks well.

  15. Underlying Mechanisms of Cooperativity, Input Specificity, and Associativity of Long-Term Potentiation Through a Positive Feedback of Local Protein Synthesis

    Directory of Open Access Journals (Sweden)

    Lijie Hao

    2018-05-01

    Full Text Available Long-term potentiation (LTP is a specific form of activity-dependent synaptic plasticity that is a leading mechanism of learning and memory in mammals. The properties of cooperativity, input specificity, and associativity are essential for LTP; however, the underlying mechanisms are unclear. Here, based on experimentally observed phenomena, we introduce a computational model of synaptic plasticity in a pyramidal cell to explore the mechanisms responsible for the cooperativity, input specificity, and associativity of LTP. The model is based on molecular processes involved in synaptic plasticity and integrates gene expression involved in the regulation of neuronal activity. In the model, we introduce a local positive feedback loop of protein synthesis at each synapse, which is essential for bimodal response and synapse specificity. Bifurcation analysis of the local positive feedback loop of brain-derived neurotrophic factor (BDNF signaling illustrates the existence of bistability, which is the basis of LTP induction. The local bifurcation diagram provides guidance for the realization of LTP, and the projection of whole system trajectories onto the two-parameter bifurcation diagram confirms the predictions obtained from bifurcation analysis. Moreover, model analysis shows that pre- and postsynaptic components are required to achieve the three properties of LTP. This study provides insights into the mechanisms underlying the cooperativity, input specificity, and associativity of LTP, and the further construction of neural networks for learning and memory.

  16. Potential mechanisms of phthalate ester embryotoxicity in the abalone Haliotis diversicolor supertexta

    Energy Technology Data Exchange (ETDEWEB)

    Zhou Jin [L-304, Life Sciences Division, Graduate School at Shenzhen, Tsinghua University, Shenzhen University Town, Xili, Shenzhen City 518055 (China); Cai Zhonghua, E-mail: caizh@sz.tsinghua.edu.cn [L-304, Life Sciences Division, Graduate School at Shenzhen, Tsinghua University, Shenzhen University Town, Xili, Shenzhen City 518055 (China); Key Laboratory of Aquatic-Ecology, Tianjin Agricultural University, Lishui Road 112, Tianjin 300384 (China); Xing Kezhi [Key Laboratory of Aquatic-Ecology, Tianjin Agricultural University, Lishui Road 112, Tianjin 300384 (China)

    2011-05-15

    The effects and associated toxicological mechanisms of five phthalate esters (PAEs) on abalone embryonic development were investigated by exposing the embryos to a range of PAEs concentrations (0.05, 0.2, 2 and 10 {mu}g/mL). The results showed that PAEs could significantly reduce embryo hatchability, increase developmental malformations, and suppress the metamorphosis of abalone larvae. The possible toxicological mechanisms of PAEs to abalone embryos included, affecting the Na{sup +}-K{sup +}-pump and Ca{sup 2+}-Mg{sup 2+}-pump activities, altering the peroxidase (POD) level and the malondialdehyde (MDA) production, damaging the extraembryonic membranes structure, as well as disrupting endocrine-related genes (gpx, cyp3a, and 17{beta}-hsd 12) expression properties. Taken together, this work showed that PAEs adversely affected the embryonic ontogeny of abalone. The abilities of PAEs affecting the osmoregulation, inducing oxidative stress, damaging embryo envelope structure, and causing physiological homeostasis disorder, are likely to be a part of the common mechanisms responsible for their embryonic toxicity. - Highlights: > PAEs affected abalone hatchability, morphogenesis and metamorphosis behavior. > The toxicity of the five PAEs to embryogenesis was ranked as DBP > DEP > DMP > DOP > DEHP. > The osmoregulation disorder and oxidative damage are the potential mechanisms. - Potential mechanisms of PAEs on abalone embryogenesis are osmoregulation disorder, oxidative damage and physiological dysfunction.

  17. Potential mechanisms of phthalate ester embryotoxicity in the abalone Haliotis diversicolor supertexta

    International Nuclear Information System (INIS)

    Zhou Jin; Cai Zhonghua; Xing Kezhi

    2011-01-01

    The effects and associated toxicological mechanisms of five phthalate esters (PAEs) on abalone embryonic development were investigated by exposing the embryos to a range of PAEs concentrations (0.05, 0.2, 2 and 10 μg/mL). The results showed that PAEs could significantly reduce embryo hatchability, increase developmental malformations, and suppress the metamorphosis of abalone larvae. The possible toxicological mechanisms of PAEs to abalone embryos included, affecting the Na + -K + -pump and Ca 2+ -Mg 2+ -pump activities, altering the peroxidase (POD) level and the malondialdehyde (MDA) production, damaging the extraembryonic membranes structure, as well as disrupting endocrine-related genes (gpx, cyp3a, and 17β-hsd 12) expression properties. Taken together, this work showed that PAEs adversely affected the embryonic ontogeny of abalone. The abilities of PAEs affecting the osmoregulation, inducing oxidative stress, damaging embryo envelope structure, and causing physiological homeostasis disorder, are likely to be a part of the common mechanisms responsible for their embryonic toxicity. - Highlights: → PAEs affected abalone hatchability, morphogenesis and metamorphosis behavior. → The toxicity of the five PAEs to embryogenesis was ranked as DBP > DEP > DMP > DOP > DEHP. → The osmoregulation disorder and oxidative damage are the potential mechanisms. - Potential mechanisms of PAEs on abalone embryogenesis are osmoregulation disorder, oxidative damage and physiological dysfunction.

  18. Fault Tolerant Mechanism for Multimedia Flows in Wireless Ad Hoc Networks Based on Fast Switching Paths

    Directory of Open Access Journals (Sweden)

    Juan R. Diaz

    2014-01-01

    Full Text Available Multimedia traffic can be forwarded through a wireless ad hoc network using the available resources of the nodes. Several models and protocols have been designed in order to organize and arrange the nodes to improve transmissions along the network. We use a cluster-based framework, called MWAHCA architecture, which optimizes multimedia transmissions over a wireless ad hoc network. It was proposed by us in a previous research work. This architecture is focused on decreasing quality of service (QoS parameters like latency, jitter, and packet loss, but other network features were not developed, like load balance or fault tolerance. In this paper, we propose a new fault tolerance mechanism, using as a base the MWAHCA architecture, in order to recover any multimedia flow crossing the wireless ad hoc network when there is a node failure. The algorithm can run independently for each multimedia flow. The main objective is to keep the QoS parameters as low as possible. To achieve this goal, the convergence time must be controlled and reduced. This paper provides the designed protocol, the analytical model of the algorithm, and a software application developed to test its performance in a real laboratory.

  19. UPPGHA: Uniform Privacy Preservation Group Handover Authentication Mechanism for mMTC in LTE-A Networks

    Directory of Open Access Journals (Sweden)

    Jin Cao

    2018-01-01

    Full Text Available Machine Type Communication (MTC, as one of the most important wireless communication technologies in the future wireless communication, has become the new business growth point of mobile communication network. It is a key point to achieve seamless handovers within Evolved-Universal Terrestrial Radio Access Network (E-UTRAN for massive MTC (mMTC devices in order to support mobility in the Long Term Evolution-Advanced (LTE-A networks. When mMTC devices simultaneously roam from a base station to a new base station, the current handover mechanisms suggested by the Third-Generation Partnership Project (3GPP require several handover signaling interactions, which could cause the signaling load over the access network and the core network. Besides, several distinct handover procedures are proposed for different mobility scenarios, which will increase the system complexity. In this paper, we propose a simple and secure uniform group-based handover authentication scheme for mMTC devices based on the multisignature and aggregate message authentication code (AMAC techniques, which is to fit in with all of the mobility scenarios in the LTE-A networks. Compared with the current 3GPP standards, our scheme can achieve a simple authentication process with robust security protection including privacy preservation and thus avoid signaling congestion. The correctness of the proposed group handover authentication protocol is formally proved in the Canetti-Krawczyk (CK model and verified based on the AVISPA and SPAN.

  20. The Double-Well Potential in Quantum Mechanics: A Simple, Numerically Exact Formulation

    Science.gov (United States)

    Jelic, V.; Marsiglio, F.

    2012-01-01

    The double-well potential is arguably one of the most important potentials in quantum mechanics, because the solution contains the notion of a state as a linear superposition of "classical" states, a concept which has become very important in quantum information theory. It is therefore desirable to have solutions to simple double-well potentials…

  1. The Mechanism Research of Qishen Yiqi Formula by Module-Network Analysis

    Directory of Open Access Journals (Sweden)

    Shichao Zheng

    2015-01-01

    Full Text Available Qishen Yiqi formula (QSYQ has the effect of tonifying Qi and promoting blood circulation, which is widely used to treat the cardiovascular diseases with Qi deficiency and blood stasis syndrome. However, the mechanism of QSYQ to tonify Qi and promote blood circulation is rarely reported at molecular or systems level. This study aimed to elucidate the mechanism of QSYQ based on the protein interaction network (PIN analysis. The targets’ information of the active components was obtained from ChEMBL and STITCH databases and was further used to search against protein-protein interactions by String database. Next, the PINs of QSYQ were constructed by Cytoscape and were analyzed by gene ontology enrichment analysis based on Markov Cluster algorithm. Finally, based on the topological parameters, the properties of scale-free, small world, and modularity of the QSYQ’s PINs were analyzed. And based on function modules, the mechanism of QSYQ was elucidated. The results indicated that Qi-tonifying efficacy of QSYQ may be partly attributed to the regulation of amino acid metabolism, carbohydrate metabolism, lipid metabolism, and cAMP metabolism, while QSYQ improves the blood stasis through the regulation of blood coagulation and cardiac muscle contraction. Meanwhile, the “synergy” of formula compatibility was also illuminated.

  2. Models of Coupled Settlement and Habitat Networks for Biodiversity Conservation: Conceptual Framework, Implementation and Potential Applications

    Directory of Open Access Journals (Sweden)

    Maarten J. van Strien

    2018-04-01

    on potential applications of models of coupled settlement and habitat networks in the development of complex network theory, in the assessment of system resilience and in conservation, transport and urban planning. The development of coupled settlement and habitat network models is important to gain a better system-level understanding of biodiversity conservation under a rapidly urbanizing and growing human population.

  3. Thermomechanical characterization of thiol-epoxy shape memory thermosets for mechanical actuators design

    Science.gov (United States)

    Belmonte, Alberto; Fernández-Francos, Xavier; De la Flor, Silvia

    2018-02-01

    In this paper, shape-memory "thiol-epoxy" polymers are synthesized and characterized as potential thermomechanical actuators. Their thermomechanical properties are investigated through dynamo mechanical and tensile analyses and related to their network structural properties by using "thiol" and "epoxy" compounds of different functionality and structure. Their mechanical properties (resistance at break, elongation limits and strain energy) are related to their shape-memory response under free-recovery conditions and partially-constrained conditions, thus, establishing the connection between network relaxation (free-recovery) with the work output capabilities (partially-constrained). Results show high mechanical performance, achieving high elongation at break values (up to 100%) and stress at break values (up to 50 MPa). The shape-memory experiments reveal strong dependence of the programming conditions and network structure on the recovery efficiency at free-conditions, whereas under partially-constrained conditions, the controlling factors are the mechanical limits at high temperature. Moreover, some recommendations to achieve the maximum work output efficiency for a given operational design of a thermomechanical actuator are deduced.

  4. New Potentials for Old: The Darboux Transformation in Quantum Mechanics

    Science.gov (United States)

    Williams, Brian Wesley; Celius, Tevye C.

    2008-01-01

    The Darboux transformation in quantum mechanics is reviewed at a basic level. Examples of how this transformation leads to exactly solvable potentials related to the "particle in a box" and the harmonic oscillator are shown in detail. The connection between the Darboux transformation and some modern operator based approaches to quantum mechanics…

  5. Energy Harvesting Wireless Sensor Networks: From Characterization to Duty Cycle Dimensioning

    OpenAIRE

    Oueis , Jad; Stanica , Razvan; Valois , Fabrice

    2016-01-01

    International audience; Energy harvesting capabilities are challenging our understanding of wireless sensor networks by adding recharging capacity to sensor nodes. This has a significant impact on the communication paradigm, as networking mechanisms can benefit from these potentially infinite renewable energy sources. In this work, we study the consequences of implementing photovoltaic energy harvesting on the duty cycle of a wireless sensor node, in both outdoor and indoor scenarios. We show...

  6. The Use of RNA Sequencing and Correlation Network Analysis to Study Potential Regulators of Crabapple Leaf Color Transformation.

    Science.gov (United States)

    Yang, Tuo; Li, Keting; Hao, Suxiao; Zhang, Jie; Song, Tingting; Tian, Ji; Yao, Yuncong

    2018-05-01

    Anthocyanins are plant pigments that contribute to the color of leaves, flowers and fruits, and that are beneficial to human health in the form of dietary antioxidants. The study of a transformable crabapple cultivar, 'India magic', which has red buds and green mature leaves, using mRNA profiling of four leaf developmental stages, allowed us to characterize molecular mechanisms regulating red color formation in early leaf development and the subsequent rapid down-regulation of anthocyanin biosynthesis. This analysis of differential gene expression during leaf development revealed that ethylene signaling-responsive genes are up-regulated during leaf pigmentation. Genes in the ethylene response factor (ERF), SPL, NAC, WRKY and MADS-box transcription factor (TF) families were identified in two weighted gene co-expression network analysis (WGCNA) modules as having a close relationship to anthocyanin accumulation. Analyses of network hub genes indicated that SPL TFs are located in central positions within anthocyanin-related modules. Furthermore, cis-motif and yeast one-hybrid assays suggested that several anthocyanin biosynthetic or regulatory genes are potential targets of SPL8 and SPL13B. Transient silencing of these two genes confirmed that they play a role in co-ordinating anthocyanin biosynthesis and crabapple leaf development. We present a high-resolution method for identifying regulatory modules associated with leaf pigmentation, which provides a platform for functional genomic studies of anthocyanin biosynthesis.

  7. Network Coded Software Defined Networking

    DEFF Research Database (Denmark)

    Krigslund, Jeppe; Hansen, Jonas; Roetter, Daniel Enrique Lucani

    2015-01-01

    Software Defined Networking (SDN) and Network Coding (NC) are two key concepts in networking that have garnered a large attention in recent years. On the one hand, SDN's potential to virtualize services in the Internet allows a large flexibility not only for routing data, but also to manage....... This paper advocates for the use of SDN to bring about future Internet and 5G network services by incorporating network coding (NC) functionalities. The inherent flexibility of both SDN and NC provides a fertile ground to envision more efficient, robust, and secure networking designs, that may also...

  8. Energy efficient mechanisms for high-performance Wireless Sensor Networks

    Science.gov (United States)

    Alsaify, Baha'adnan

    2009-12-01

    Due to recent advances in microelectronics, the development of low cost, small, and energy efficient devices became possible. Those advances led to the birth of the Wireless Sensor Networks (WSNs). WSNs consist of a large set of sensor nodes equipped with communication capabilities, scattered in the area to monitor. Researchers focus on several aspects of WSNs. Such aspects include the quality of service the WSNs provide (data delivery delay, accuracy of data, etc...), the scalability of the network to contain thousands of sensor nodes (the terms node and sensor node are being used interchangeably), the robustness of the network (allowing the network to work even if a certain percentage of nodes fails), and making the energy consumption in the network as low as possible to prolong the network's lifetime. In this thesis, we present an approach that can be applied to the sensing devices that are scattered in an area for Sensor Networks. This work will use the well-known approach of using a awaking scheduling to extend the network's lifespan. We designed a scheduling algorithm that will reduce the delay's upper bound the reported data will experience, while at the same time keeps the advantages that are offered by the use of the awaking scheduling -- the energy consumption reduction which will lead to the increase in the network's lifetime. The wakeup scheduling is based on the location of the node relative to its neighbors and its distance from the Base Station (the terms Base Station and sink are being used interchangeably). We apply the proposed method to a set of simulated nodes using the "ONE Simulator". We test the performance of this approach with three other approaches -- Direct Routing technique, the well known LEACH algorithm, and a multi-parent scheduling algorithm. We demonstrate a good improvement on the network's quality of service and a reduction of the consumed energy.

  9. Three-dimensional graphene networks: synthesis,properties and applications

    Institute of Scientific and Technical Information of China (English)

    Yanfeng Ma; Yongsheng Chen

    2015-01-01

    Recently, three-dimensional graphene/graphene oxide(GO) networks(3DGNs) in the form of foams,sponges and aerogels have atracted much atention. 3D structures provide graphene materials with high speciic surface areas, large pore volumes, strong mechanical strengths and fast mass and electron transport,owing to the combination of the 3D porous structures and the excellent intrinsic properties of graphene.his review focuses on the latest advances in the preparation, properties and potential applications of 3D micro-/nano-architectures made of graphene/GO-based networks, with emphasis on graphene foams and sponges.

  10. Transcriptional regulatory network triggered by oxidative signals configures the early response mechanisms of japonica rice to chilling stress

    KAUST Repository

    Yun, Kil-Young; Park, Myoung Ryoul; Mohanty, Bijayalaxmi; Herath, Venura; Xu, Fuyu; Mauleon, Ramil; Wijaya, Edward; Bajic, Vladimir B.; Bruskiewich, Richard; de los Reyes, Benildo G

    2010-01-01

    -plant level analyses established a holistic view of chilling stress response mechanism of japonica rice. Early response regulatory network triggered by oxidative signals is critical for prolonged survival under sub-optimal temperature. Integration of stress

  11. Mechanisms for Prolonging Network Lifetime in Wireless Sensor Networks

    Science.gov (United States)

    Yang, Yinying

    2010-01-01

    Sensors are used to monitor and control the physical environment. A Wireless Sensor Network (WSN) is composed of a large number of sensor nodes that are densely deployed either inside the phenomenon or very close to it [18][5]. Sensor nodes measure various parameters of the environment and transmit data collected to one or more sinks, using…

  12. Network Coded Software Defined Networking

    DEFF Research Database (Denmark)

    Hansen, Jonas; Roetter, Daniel Enrique Lucani; Krigslund, Jeppe

    2015-01-01

    Software defined networking has garnered large attention due to its potential to virtualize services in the Internet, introducing flexibility in the buffering, scheduling, processing, and routing of data in network routers. SDN breaks the deadlock that has kept Internet network protocols stagnant...... for decades, while applications and physical links have evolved. This article advocates for the use of SDN to bring about 5G network services by incorporating network coding (NC) functionalities. The latter constitutes a major leap forward compared to the state-of-the- art store and forward Internet paradigm...

  13. Formation of the controlling mechanism in the management of innovative development of enterprise potential

    Directory of Open Access Journals (Sweden)

    Андрій Анатолійович Пилипенко

    2015-11-01

    Full Text Available The article presents the guidelines for the formation of the controlling mechanism in the activation cycles of innovative activities and the formation of the development programs of the enterprise potential. It is offered understanding the development potential and proved grouping of controlled performance, taking into account the level of innovation ability of the enterprise. It is presented the strategic matrix of determining the composition of performance, determination of monitoring parameters and aspects of controlling mechanism

  14. EARLINET: potential operationality of a research network

    Science.gov (United States)

    Sicard, M.; D'Amico, G.; Comerón, A.; Mona, L.; Alados-Arboledas, L.; Amodeo, A.; Baars, H.; Baldasano, J. M.; Belegante, L.; Binietoglou, I.; Bravo-Aranda, J. A.; Fernández, A. J.; Fréville, P.; García-Vizcaíno, D.; Giunta, A.; Granados-Muñoz, M. J.; Guerrero-Rascado, J. L.; Hadjimitsis, D.; Haefele, A.; Hervo, M.; Iarlori, M.; Kokkalis, P.; Lange, D.; Mamouri, R. E.; Mattis, I.; Molero, F.; Montoux, N.; Muñoz, A.; Muñoz Porcar, C.; Navas-Guzmán, F.; Nicolae, D.; Nisantzi, A.; Papagiannopoulos, N.; Papayannis, A.; Pereira, S.; Preißler, J.; Pujadas, M.; Rizi, V.; Rocadenbosch, F.; Sellegri, K.; Simeonov, V.; Tsaknakis, G.; Wagner, F.; Pappalardo, G.

    2015-11-01

    In the framework of ACTRIS (Aerosols, Clouds, and Trace Gases Research Infrastructure Network) summer 2012 measurement campaign (8 June-17 July 2012), EARLINET organized and performed a controlled exercise of feasibility to demonstrate its potential to perform operational, coordinated measurements and deliver products in near-real time. Eleven lidar stations participated in the exercise which started on 9 July 2012 at 06:00 UT and ended 72 h later on 12 July at 06:00 UT. For the first time, the single calculus chain (SCC) - the common calculus chain developed within EARLINET for the automatic evaluation of lidar data from raw signals up to the final products - was used. All stations sent in real-time measurements of a 1 h duration to the SCC server in a predefined netcdf file format. The pre-processing of the data was performed in real time by the SCC, while the optical processing was performed in near-real time after the exercise ended. 98 and 79 % of the files sent to SCC were successfully pre-processed and processed, respectively. Those percentages are quite large taking into account that no cloud screening was performed on the lidar data. The paper draws present and future SCC users' attention to the most critical parameters of the SCC product configuration and their possible optimal value but also to the limitations inherent to the raw data. The continuous use of SCC direct and derived products in heterogeneous conditions is used to demonstrate two potential applications of EARLINET infrastructure: the monitoring of a Saharan dust intrusion event and the evaluation of two dust transport models. The efforts made to define the measurements protocol and to configure properly the SCC pave the way for applying this protocol for specific applications such as the monitoring of special events, atmospheric modeling, climate research and calibration/validation activities of spaceborne observations.

  15. A network-based biomarker approach for molecular investigation and diagnosis of lung cancer

    Directory of Open Access Journals (Sweden)

    Chen Bor-Sen

    2011-01-01

    Full Text Available Abstract Background Lung cancer is the leading cause of cancer deaths worldwide. Many studies have investigated the carcinogenic process and identified the biomarkers for signature classification. However, based on the research dedicated to this field, there is no highly sensitive network-based method for carcinogenesis characterization and diagnosis from the systems perspective. Methods In this study, a systems biology approach integrating microarray gene expression profiles and protein-protein interaction information was proposed to develop a network-based biomarker for molecular investigation into the network mechanism of lung carcinogenesis and diagnosis of lung cancer. The network-based biomarker consists of two protein association networks constructed for cancer samples and non-cancer samples. Results Based on the network-based biomarker, a total of 40 significant proteins in lung carcinogenesis were identified with carcinogenesis relevance values (CRVs. In addition, the network-based biomarker, acting as the screening test, proved to be effective in diagnosing smokers with signs of lung cancer. Conclusions A network-based biomarker using constructed protein association networks is a useful tool to highlight the pathways and mechanisms of the lung carcinogenic process and, more importantly, provides potential therapeutic targets to combat cancer.

  16. The use of management control mechanisms by public organizations with a network coordination role : A case study in the port industry

    NARCIS (Netherlands)

    Marques, L.; Ribeiro, J. A.; Scapens, R. W.

    2011-01-01

    Our paper addresses two gaps in the literature on management control mechanisms in the context of inter-organizational relationships. Firstly, several studies have focused on one-to-one relationships, but few take a network perspective which analyses the deployment of management control mechanisms

  17. Attentional network task in schizophrenic patients and theirs unaffected first degree relatives: a potential endofenotype.

    Science.gov (United States)

    López, S Guerra; Fuster, J Iglesias; Reyes, M Martín; Collazo, T M Bravo; Quiñones, R Mendoza; Berazain, A Reyes; Rodríguez, M A Pedroso; Días de Villarvilla, T; Bobés, M Antonieta; Valdés-Sosa, M

    2011-01-01

    In recent years, reports of attentional deficits in schizophrenic patients and in their biological relatives have rapidly increased, including an important effort to search for the endophenotypes in order to link specific genes to this illness. Posner et al. developed a test, the Attention Network Test (ANT), to study the neural networks. This test provides a separate measure for each one of the three anatomically-defined attention networks (alerting, orienting and executive control). In this paper, we investigate the attentional performance in 32 schizophrenic patients, 29 unaffected first degree relatives and 29 healthy controls using the ANT through a study of family association. We have studied the efficiency of the segregated executive control, alerting and orienting networks by measuring how response latencies (reaction time) were modified by the cue position and the flanking stimuli. We also studied the familial association of these attentional alterations. The ANOVA revealed main effects of flanker and cue condition and a significant interaction effect between flanker and groups studied. The schizophrenic patients and their relatives had a longer median reaction time than the control group. The probands and their relatives significantly differed from the healthy controls in terms of their conflict resolution; however, the alerting network appeared to be conserved. Our results support the thesis of a specific attentional deficit in schizophrenia and show the segregation of the three attentional networks. The family association of these reported alterations supports the idea of a potential endophenotype in schizophrenia.

  18. Information Warfare-Worthy Jamming Attack Detection Mechanism for Wireless Sensor Networks Using a Fuzzy Inference System

    Directory of Open Access Journals (Sweden)

    Sudip Misra

    2010-04-01

    Full Text Available The proposed mechanism for jamming attack detection for wireless sensor networks is novel in three respects: firstly, it upgrades the jammer to include versatile military jammers; secondly, it graduates from the existing node-centric detection system to the network-centric system making it robust and economical at the nodes, and thirdly, it tackles the problem through fuzzy inference system, as the decision regarding intensity of jamming is seldom crisp. The system with its high robustness, ability to grade nodes with jamming indices, and its true-detection rate as high as 99.8%, is worthy of consideration for information warfare defense purposes.

  19. A review of potential neurotoxic mechanisms among three chlorinated organic solvents

    International Nuclear Information System (INIS)

    Bale, Ambuja S.; Barone, Stan; Scott, Cheryl Siegel; Cooper, Glinda S.

    2011-01-01

    The potential for central nervous system depressant effects from three widely used chlorinated solvents, trichloroethylene (TCE), perchloroethylene (PERC), and dichloromethane (DCM), has been shown in human and animal studies. Commonalities of neurobehavioral and neurophysiological changes for the chlorinated solvents in in vivo studies suggest that there is a common mechanism(s) of action in producing resultant neurotoxicological consequences. The purpose of this review is to examine the mechanistic studies conducted with these chlorinated solvents and to propose potential mechanisms of action for the different neurological effects observed. Mechanistic studies indicate that this solvent class has several molecular targets in the brain. Additionally, there are several pieces of evidence from animal studies indicating this solvent class alters neurochemical functions in the brain. Although earlier evidence indicated that these three chlorinated solvents perturb the lipid bilayer, more recent data suggest an interaction between several specific neuronal receptors produces the resultant neurobehavioral effects. Collectively, TCE, PERC, and DCM have been reported to interact directly with several different classes of neuronal receptors by generally inhibiting excitatory receptors/channels and potentiating the function of inhibitory receptors/channels. Given this mechanistic information and available studies for TCE, DCM, and PERC, we provide hypotheses on primary targets (e.g. ion channel targets) that appear to be most influential in producing the resultant neurological effects. - Research highlights: → Comparison of neurological effects among TCE, PERC, and DCM. → Correlation of mechanistic findings to neurological effects. → Data support that TCE, PERC, and DCM interact with several ion channels to produce neurological changes.

  20. Hyperglycemia Augments the Adipogenic Transdifferentiation Potential of Tenocytes and Is Alleviated by Cyclic Mechanical Stretch.

    Science.gov (United States)

    Wu, Yu-Fu; Huang, Yu-Ting; Wang, Hsing-Kuo; Yao, Chung-Chen Jane; Sun, Jui-Sheng; Chao, Yuan-Hung

    2017-12-28

    Diabetes mellitus is associated with damage to tendons, which may result from cellular dysfunction in response to a hyperglycemic environment. Tenocytes express diminished levels of tendon-associated genes under hyperglycemic conditions. In contrast, mechanical stretch enhances tenogenic differentiation. However, whether hyperglycemia increases the non-tenogenic differentiation potential of tenocytes and whether this can be mitigated by mechanical stretch remains elusive. We explored the in vitro effects of high glucose and mechanical stretch on rat primary tenocytes. Specifically, non-tenogenic gene expression, adipogenic potential, cell migration rate, filamentous actin expression, and the activation of signaling pathways were analyzed in tenocytes treated with high glucose, followed by the presence or absence of mechanical stretch. We analyzed tenocyte phenotype in vivo by immunohistochemistry using an STZ (streptozotocin)-induced long-term diabetic mouse model. High glucose-treated tenocytes expressed higher levels of the adipogenic transcription factors PPAR γ and C/EBPs. PPARγ was also highly expressed in diabetic tendons. In addition, increased adipogenic differentiation and decreased cell migration induced by high glucose implicated a fibroblast-to-adipocyte phenotypic change. By applying mechanical stretch to tenocytes in high-glucose conditions, adipogenic differentiation was repressed, while cell motility was enhanced, and fibroblastic morphology and gene expression profiles were strengthened. In part, these effects resulted from a stretch-induced activation of ERK (extracellular signal-regulated kinases) and a concomitant inactivation of Akt. Our results show that mechanical stretch alleviates the augmented adipogenic transdifferentiation potential of high glucose-treated tenocytes and helps maintain their fibroblastic characteristics. The alterations induced by high glucose highlight possible pathological mechanisms for diabetic tendinopathy

  1. Potential applications of neural networks to nuclear power plants

    International Nuclear Information System (INIS)

    Uhrig, R.E.

    1991-01-01

    Application of neural networks to the operation of nuclear power plants is being investigated under a US Department of Energy sponsored program at the University of Tennessee. Projects include the feasibility of using neural networks for the following tasks: diagnosing specific abnormal conditions, detection of the change of mode of operation, signal validation, monitoring of check valves, plant-wide monitoring using autoassociative neural networks, modeling of the plant thermodynamics, emulation of core reload calculations, monitoring of plant parameters, and analysis of plant vibrations. Each of these projects and its status are described briefly in this article. The objective of each of these projects is to enhance the safety and performance of nuclear plants through the use of neural networks

  2. NQAR: Network Quality Aware Routing in Error-Prone Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Jaewon Choi

    2010-01-01

    Full Text Available We propose a network quality aware routing (NQAR mechanism to provide an enabling method of the delay-sensitive data delivery over error-prone wireless sensor networks. Unlike the existing routing methods that select routes with the shortest arrival latency or the minimum hop count, the proposed scheme adaptively selects the route based on the network qualities including link errors and collisions with minimum additional complexity. It is designed to avoid the paths with potential noise and collision that may cause many non-deterministic backoffs and retransmissions. We propose a generic framework to select a minimum cost route that takes the packet loss rate and collision history into account. NQAR uses a data centric approach to estimate a single-hop delay based on processing time, propagation delay, packet loss rate, number of backoffs, and the retransmission timeout between two neighboring nodes. This enables a source node to choose the shortest expected end-to-end delay path to send a delay-sensitive data. The experiment results show that NQAR reduces the end-to-end transfer delay up to approximately 50% in comparison with the latency-based directed diffusion and the hop count-based directed diffusion under the error-prone network environments. Moreover, NQAR shows better performance than those routing methods in terms of jitter, reachability, and network lifetime.

  3. Software Defined Networking for Improved Wireless Sensor Network Management: A Survey.

    Science.gov (United States)

    Ndiaye, Musa; Hancke, Gerhard P; Abu-Mahfouz, Adnan M

    2017-05-04

    Wireless sensor networks (WSNs) are becoming increasingly popular with the advent of the Internet of things (IoT). Various real-world applications of WSNs such as in smart grids, smart farming and smart health would require a potential deployment of thousands or maybe hundreds of thousands of sensor nodes/actuators. To ensure proper working order and network efficiency of such a network of sensor nodes, an effective WSN management system has to be integrated. However, the inherent challenges of WSNs such as sensor/actuator heterogeneity, application dependency and resource constraints have led to challenges in implementing effective traditional WSN management. This difficulty in management increases as the WSN becomes larger. Software Defined Networking (SDN) provides a promising solution in flexible management WSNs by allowing the separation of the control logic from the sensor nodes/actuators. The advantage with this SDN-based management in WSNs is that it enables centralized control of the entire WSN making it simpler to deploy network-wide management protocols and applications on demand. This paper highlights some of the recent work on traditional WSN management in brief and reviews SDN-based management techniques for WSNs in greater detail while drawing attention to the advantages that SDN brings to traditional WSN management. This paper also investigates open research challenges in coming up with mechanisms for flexible and easier SDN-based WSN configuration and management.

  4. Software Defined Networking for Improved Wireless Sensor Network Management: A Survey

    Directory of Open Access Journals (Sweden)

    Musa Ndiaye

    2017-05-01

    Full Text Available Wireless sensor networks (WSNs are becoming increasingly popular with the advent of the Internet of things (IoT. Various real-world applications of WSNs such as in smart grids, smart farming and smart health would require a potential deployment of thousands or maybe hundreds of thousands of sensor nodes/actuators. To ensure proper working order and network efficiency of such a network of sensor nodes, an effective WSN management system has to be integrated. However, the inherent challenges of WSNs such as sensor/actuator heterogeneity, application dependency and resource constraints have led to challenges in implementing effective traditional WSN management. This difficulty in management increases as the WSN becomes larger. Software Defined Networking (SDN provides a promising solution in flexible management WSNs by allowing the separation of the control logic from the sensor nodes/actuators. The advantage with this SDN-based management in WSNs is that it enables centralized control of the entire WSN making it simpler to deploy network-wide management protocols and applications on demand. This paper highlights some of the recent work on traditional WSN management in brief and reviews SDN-based management techniques for WSNs in greater detail while drawing attention to the advantages that SDN brings to traditional WSN management. This paper also investigates open research challenges in coming up with mechanisms for flexible and easier SDN-based WSN configuration and management.

  5. Resolving structural variability in network models and the brain.

    Directory of Open Access Journals (Sweden)

    Florian Klimm

    2014-03-01

    Full Text Available Large-scale white matter pathways crisscrossing the cortex create a complex pattern of connectivity that underlies human cognitive function. Generative mechanisms for this architecture have been difficult to identify in part because little is known in general about mechanistic drivers of structured networks. Here we contrast network properties derived from diffusion spectrum imaging data of the human brain with 13 synthetic network models chosen to probe the roles of physical network embedding and temporal network growth. We characterize both the empirical and synthetic networks using familiar graph metrics, but presented here in a more complete statistical form, as scatter plots and distributions, to reveal the full range of variability of each measure across scales in the network. We focus specifically on the degree distribution, degree assortativity, hierarchy, topological Rentian scaling, and topological fractal scaling--in addition to several summary statistics, including the mean clustering coefficient, the shortest path-length, and the network diameter. The models are investigated in a progressive, branching sequence, aimed at capturing different elements thought to be important in the brain, and range from simple random and regular networks, to models that incorporate specific growth rules and constraints. We find that synthetic models that constrain the network nodes to be physically embedded in anatomical brain regions tend to produce distributions that are most similar to the corresponding measurements for the brain. We also find that network models hardcoded to display one network property (e.g., assortativity do not in general simultaneously display a second (e.g., hierarchy. This relative independence of network properties suggests that multiple neurobiological mechanisms might be at play in the development of human brain network architecture. Together, the network models that we develop and employ provide a potentially useful

  6. A Social Potential Fields Approach for Self-Deployment and Self-Healing in Hierarchical Mobile Wireless Sensor Networks.

    Science.gov (United States)

    González-Parada, Eva; Cano-García, Jose; Aguilera, Francisco; Sandoval, Francisco; Urdiales, Cristina

    2017-01-09

    Autonomous mobile nodes in mobile wireless sensor networks (MWSN) allow self-deployment and self-healing. In both cases, the goals are: (i) to achieve adequate coverage; and (ii) to extend network life. In dynamic environments, nodes may use reactive algorithms so that each node locally decides when and where to move. This paper presents a behavior-based deployment and self-healing algorithm based on the social potential fields algorithm. In the proposed algorithm, nodes are attached to low cost robots to autonomously navigate in the coverage area. The proposed algorithm has been tested in environments with and without obstacles. Our study also analyzes the differences between non-hierarchical and hierarchical routing configurations in terms of network life and coverage.

  7. Spinal Cord Stimulation: Clinical Efficacy and Potential Mechanisms.

    Science.gov (United States)

    Sdrulla, Andrei D; Guan, Yun; Raja, Srinivasa N

    2018-03-11

    Spinal cord stimulation (SCS) is a minimally invasive therapy used for the treatment of chronic neuropathic pain. SCS is a safe and effective alternative to medications such as opioids, and multiple randomized controlled studies have demonstrated efficacy for difficult-to-treat neuropathic conditions such as failed back surgery syndrome. Conventional SCS is believed mediate pain relief via activation of dorsal column Aβ fibers, resulting in variable effects on sensory and pain thresholds, and measurable alterations in higher order cortical processing. Although potentiation of inhibition, as suggested by Wall and Melzack's gate control theory, continues to be the leading explanatory model, other segmental and supraspinal mechanisms have been described. Novel, non-standard, stimulation waveforms such as high-frequency and burst have been shown in some studies to be clinically superior to conventional SCS, however their mechanisms of action remain to be determined. Additional studies are needed, both mechanistic and clinical, to better understand optimal stimulation strategies for different neuropathic conditions, improve patient selection and optimize efficacy. © 2018 World Institute of Pain.

  8. Construction of high-dimensional neural network potentials using environment-dependent atom pairs.

    Science.gov (United States)

    Jose, K V Jovan; Artrith, Nongnuch; Behler, Jörg

    2012-05-21

    An accurate determination of the potential energy is the crucial step in computer simulations of chemical processes, but using electronic structure methods on-the-fly in molecular dynamics (MD) is computationally too demanding for many systems. Constructing more efficient interatomic potentials becomes intricate with increasing dimensionality of the potential-energy surface (PES), and for numerous systems the accuracy that can be achieved is still not satisfying and far from the reliability of first-principles calculations. Feed-forward neural networks (NNs) have a very flexible functional form, and in recent years they have been shown to be an accurate tool to construct efficient PESs. High-dimensional NN potentials based on environment-dependent atomic energy contributions have been presented for a number of materials. Still, these potentials may be improved by a more detailed structural description, e.g., in form of atom pairs, which directly reflect the atomic interactions and take the chemical environment into account. We present an implementation of an NN method based on atom pairs, and its accuracy and performance are compared to the atom-based NN approach using two very different systems, the methanol molecule and metallic copper. We find that both types of NN potentials provide an excellent description of both PESs, with the pair-based method yielding a slightly higher accuracy making it a competitive alternative for addressing complex systems in MD simulations.

  9. Cytokines and the anorexia of infection: potential mechanisms and treatments.

    Science.gov (United States)

    McCarthy, D O

    2000-04-01

    Anorexia during infection is thought to be mediated by immunoregulatory cytokines such as interleukins 1 and 6 and tumor necrosis factor. This article reviews the potential mechanisms of action by which these cytokines are thought to suppress food intake during infection and examines the proposition that blocking of cytokine activity might be one approach to improving food intake of the infected host.

  10. Potential mechanisms for imperfect synchronization in parkinsonian basal ganglia.

    Directory of Open Access Journals (Sweden)

    Choongseok Park

    Full Text Available Neural activity in the brain of parkinsonian patients is characterized by the intermittently synchronized oscillatory dynamics. This imperfect synchronization, observed in the beta frequency band, is believed to be related to the hypokinetic motor symptoms of the disorder. Our study explores potential mechanisms behind this intermittent synchrony. We study the response of a bursting pallidal neuron to different patterns of synaptic input from subthalamic nucleus (STN neuron. We show how external globus pallidus (GPe neuron is sensitive to the phase of the input from the STN cell and can exhibit intermittent phase-locking with the input in the beta band. The temporal properties of this intermittent phase-locking show similarities to the intermittent synchronization observed in experiments. We also study the synchronization of GPe cells to synaptic input from the STN cell with dependence on the dopamine-modulated parameters. Earlier studies showed how the strengthening of dopamine-modulated coupling may lead to transitions from non-synchronized to partially synchronized dynamics, typical in Parkinson's disease. However, dopamine also affects the cellular properties of neurons. We show how the changes in firing patterns of STN neuron due to the lack of dopamine may lead to transition from a lower to a higher coherent state, roughly matching the synchrony levels observed in basal ganglia in normal and parkinsonian states. The intermittent nature of the neural beta band synchrony in Parkinson's disease is achieved in the model due to the interplay of the timing of STN input to pallidum and pallidal neuronal dynamics, resulting in sensitivity of pallidal output to the phase of the arriving STN input. Thus the mechanism considered here (the change in firing pattern of subthalamic neurons through the dopamine-induced change of membrane properties may be one of the potential mechanisms responsible for the generation of the intermittent synchronization

  11. Visual attention in preterm born adults: specifically impaired attentional sub-mechanisms that link with altered intrinsic brain networks in a compensation-like mode.

    Science.gov (United States)

    Finke, Kathrin; Neitzel, Julia; Bäuml, Josef G; Redel, Petra; Müller, Hermann J; Meng, Chun; Jaekel, Julia; Daamen, Marcel; Scheef, Lukas; Busch, Barbara; Baumann, Nicole; Boecker, Henning; Bartmann, Peter; Habekost, Thomas; Wolke, Dieter; Wohlschläger, Afra; Sorg, Christian

    2015-02-15

    Although pronounced and lasting deficits in selective attention have been observed for preterm born individuals it is unknown which specific attentional sub-mechanisms are affected and how they relate to brain networks. We used the computationally specified 'Theory of Visual Attention' together with whole- and partial-report paradigms to compare attentional sub-mechanisms of pre- (n=33) and full-term (n=32) born adults. Resting-state fMRI was used to evaluate both between-group differences and inter-individual variance in changed functional connectivity of intrinsic brain networks relevant for visual attention. In preterm born adults, we found specific impairments of visual short-term memory (vSTM) storage capacity while other sub-mechanisms such as processing speed or attentional weighting were unchanged. Furthermore, changed functional connectivity was found in unimodal visual and supramodal attention-related intrinsic networks. Among preterm born adults, the individual pattern of changed connectivity in occipital and parietal cortices was systematically associated with vSTM in such a way that the more distinct the connectivity differences, the better the preterm adults' storage capacity. These findings provide first evidence for selectively changed attentional sub-mechanisms in preterm born adults and their relation to altered intrinsic brain networks. In particular, data suggest that cortical changes in intrinsic functional connectivity may compensate adverse developmental consequences of prematurity on visual short-term storage capacity. Copyright © 2014 Elsevier Inc. All rights reserved.

  12. Evolution of Cooperation in Continuous Prisoner's Dilemma Games on Barabasi—Albert Networks with Degree-Dependent Guilt Mechanism

    Science.gov (United States)

    Wang, Xian-Jia; Quan, Ji; Liu, Wei-Bing

    2012-05-01

    This paper studies the continuous prisoner's dilemma games (CPDG) on Barabasi—Albert (BA) networks. In the model, each agent on a vertex of the networks makes an investment and interacts with all of his neighboring agents. Making an investment is costly, but which benefits its neighboring agents, where benefit and cost depend on the level of investment made. The payoff of each agent is given by the sum of payoffs it receives in its interactions with all its neighbors. Not only payoff, individual's guilty emotion in the games has also been considered. The negative guilty emotion produced in comparing with its neighbors can reduce the utility of individuals directly. We assume that the reduction amount depends on the individual's degree and a baseline level parameter. The group's cooperative level is characterized by the average investment of the population. Each player makes his investment in the next step based on a convex combination of the investment of his best neighbors in the last step, his best history strategies in the latest steps which number is controlled by a memory length parameter, and a uniformly distributed random number. Simulation results show that this degree-dependent guilt mechanism can promote the evolution of cooperation dramatically comparing with degree-independent guilt or no guilt cases. Imitation, memory, uncertainty coefficients and network structure also play determinant roles in the cooperation level of the population. All our results may shed some new light on studying the evolution of cooperation based on network reciprocity mechanisms.

  13. Evolution of Cooperation in Continuous Prisoner's Dilemma Games on Barabasi-Albert Networks with Degree-Dependent Guilt Mechanism

    International Nuclear Information System (INIS)

    Wang Xianjia; Quan Ji; Liu Weibing

    2012-01-01

    This paper studies the continuous prisoner's dilemma games (CPDG) on Barabasi-Albert (BA) networks. In the model, each agent on a vertex of the networks makes an investment and interacts with all of his neighboring agents. Making an investment is costly, but which benefits its neighboring agents, where benefit and cost depend on the level of investment made. The payoff of each agent is given by the sum of payoffs it receives in its interactions with all its neighbors. Not only payoff, individual's guilty emotion in the games has also been considered. The negative guilty emotion produced in comparing with its neighbors can reduce the utility of individuals directly. We assume that the reduction amount depends on the individual's degree and a baseline level parameter. The group's cooperative level is characterized by the average investment of the population. Each player makes his investment in the next step based on a convex combination of the investment of his best neighbors in the last step, his best history strategies in the latest steps which number is controlled by a memory length parameter, and a uniformly distributed random number. Simulation results show that this degree-dependent guilt mechanism can promote the evolution of cooperation dramatically comparing with degree-independent guilt or no guilt cases. Imitation, memory, uncertainty coefficients and network structure also play determinant roles in the cooperation level of the population. All our results may shed some new light on studying the evolution of cooperation based on network reciprocity mechanisms. (interdisciplinary physics and related areas of science and technology)

  14. A Bayesian Belief Network approach to assess the potential of non wood forest products for small scale forest owners

    Science.gov (United States)

    Vacik, Harald; Huber, Patrick; Hujala, Teppo; Kurtilla, Mikko; Wolfslehner, Bernhard

    2015-04-01

    It is an integral element of the European understanding of sustainable forest management to foster the design and marketing of forest products, non-wood forest products (NWFPs) and services that go beyond the production of timber. Despite the relevance of NWFPs in Europe, forest management and planning methods have been traditionally tailored towards wood and wood products, because most forest management models and silviculture techniques were developed to ensure a sustained production of timber. Although several approaches exist which explicitly consider NWFPs as management objectives in forest planning, specific models are needed for the assessment of their production potential in different environmental contexts and for different management regimes. Empirical data supporting a comprehensive assessment of the potential of NWFPs are rare, thus making development of statistical models particularly problematic. However, the complex causal relationships between the sustained production of NWFPs, the available ecological resources, as well as the organizational and the market potential of forest management regimes are well suited for knowledge-based expert models. Bayesian belief networks (BBNs) are a kind of probabilistic graphical model that have become very popular to practitioners and scientists mainly due to the powerful probability theory involved, which makes BBNs suitable to deal with a wide range of environmental problems. In this contribution we present the development of a Bayesian belief network to assess the potential of NWFPs for small scale forest owners. A three stage iterative process with stakeholder and expert participation was used to develop the Bayesian Network within the frame of the StarTree Project. The group of participants varied in the stages of the modelling process. A core team, consisting of one technical expert and two domain experts was responsible for the entire modelling process as well as for the first prototype of the network

  15. Promoting adaptive flood risk management: the role and potential of flood recovery mechanisms

    Directory of Open Access Journals (Sweden)

    Priest Sally J

    2016-01-01

    Full Text Available There is a high potential for recovery mechanisms to be used to incentivise the uptake of flood mitigation and loss reduction measures, undertake adaptation and promote community resilience. Indeed, creating a resilient response to flooding requires flood risk management approaches to be aligned and it needs to be ensured that recovery mechanisms to not provide disincentives for individuals and business to take proactive action to reduce risk. However, the degree to which it is desirable and effective for insurers and governments providing compensation to promote resilience and risk reduction depends upon how the cover or compensation is organised and the premiums which are charged. A review of international flood recovery mechanisms has been undertaken to identify firstly the types of schemes that exist and their characteristics. Analysis of existing instruments highlights that there are various potential approaches to encourage or require the uptake of flood mitigation and also discourage the construction of new development in high flood risk. However despite the presence of these instruments, those organising recovery mechanisms could be doing much more to incentivise increased resilience.

  16. Network analysis of microRNAs and their regulation in human ovarian cancer

    KAUST Repository

    Schmeier, Sebastian

    2011-11-03

    Background: MicroRNAs (miRNAs) are small non-coding RNA molecules that repress the translation of messenger RNAs (mRNAs) or degrade mRNAs. These functions of miRNAs allow them to control key cellular processes such as development, differentiation and apoptosis, and they have also been implicated in several cancers such as leukaemia, lung, pancreatic and ovarian cancer (OC). Unfortunately, the specific machinery of miRNA regulation, involving transcription factors (TFs) and transcription co-factors (TcoFs), is not well understood. In the present study we focus on computationally deciphering the underlying network of miRNAs, their targets, and their control mechanisms that have an influence on OC development.Results: We analysed experimentally verified data from multiple sources that describe miRNA influence on diseases, miRNA targeting of mRNAs, and on protein-protein interactions, and combined this data with ab initio transcription factor binding site predictions within miRNA promoter regions. From these analyses, we derived a network that describes the influence of miRNAs and their regulation in human OC. We developed a methodology to analyse the network in order to find the nodes that have the largest potential of influencing the network\\'s behaviour (network hubs). We further show the potentially most influential miRNAs, TFs and TcoFs, showing subnetworks illustrating the involved mechanisms as well as regulatory miRNA network motifs in OC. We find an enrichment of miRNA targeted OC genes in the highly relevant pathways cell cycle regulation and apoptosis.Conclusions: We combined several sources of interaction and association data to analyse and place miRNAs within regulatory pathways that influence human OC. These results represent the first comprehensive miRNA regulatory network analysis for human OC. This suggests that miRNAs and their regulation may play a major role in OC and that further directed research in this area is of utmost importance to enhance

  17. Passive water collection with the integument: mechanisms and their biomimetic potential.

    Science.gov (United States)

    Comanns, Philipp

    2018-05-22

    Several mechanisms of water acquisition have evolved in animals living in arid habitats to cope with limited water supply. They enable access to water sources such as rain, dew, thermally facilitated condensation on the skin, fog, or moisture from a damp substrate. This Review describes how a significant number of animals - in excess of 39 species from 24 genera - have acquired the ability to passively collect water with their integument. This ability results from chemical and structural properties of the integument, which, in each species, facilitate one or more of six basic mechanisms: increased surface wettability, increased spreading area, transport of water over relatively large distances, accumulation and storage of collected water, condensation, and utilization of gravity. Details are described for each basic mechanism. The potential for bio-inspired improvement of technical applications has been demonstrated in many cases, in particular for several wetting phenomena, fog collection and passive, directional transport of liquids. Also considered here are potential applications in the fields of water supply, lubrication, heat exchangers, microfluidics and hygiene products. These present opportunities for innovations, not only in product functionality, but also for fabrication processes, where resources and environmental impact can be reduced. © 2018. Published by The Company of Biologists Ltd.

  18. A scoring mechanism for the rank aggregation of network robustness

    Science.gov (United States)

    Yazdani, Alireza; Dueñas-Osorio, Leonardo; Li, Qilin

    2013-10-01

    To date, a number of metrics have been proposed to quantify inherent robustness of network topology against failures. However, each single metric usually only offers a limited view of network vulnerability to different types of random failures and targeted attacks. When applied to certain network configurations, different metrics rank network topology robustness in different orders which is rather inconsistent, and no single metric fully characterizes network robustness against different modes of failure. To overcome such inconsistency, this work proposes a multi-metric approach as the basis of evaluating aggregate ranking of network topology robustness. This is based on simultaneous utilization of a minimal set of distinct robustness metrics that are standardized so to give way to a direct comparison of vulnerability across networks with different sizes and configurations, hence leading to an initial scoring of inherent topology robustness. Subsequently, based on the inputs of initial scoring a rank aggregation method is employed to allocate an overall ranking of robustness to each network topology. A discussion is presented in support of the presented multi-metric approach and its applications to more realistically assess and rank network topology robustness.

  19. On the determining role of network structure titania in silicone against bacterial colonization: Mechanism and disruption of biofilm

    International Nuclear Information System (INIS)

    Depan, D.; Misra, R.D.K.

    2014-01-01

    Silicone-based biomedical devices are prone to microbial adhesion, which is the primary cause of concern in the functioning of the artificial device. Silicone exhibiting long-term and effective antibacterial ability is highly desirable to prevent implant related infections. In this regard, nanophase titania was incorporated in silicone as an integral part of the silicone network structure through cross-link mechanism, with the objective to reduce bacterial adhesion to a minimum. The bacterial adhesion was studied using crystal violet assay, while the mechanism of inhibition of biofilm formation was studied via electron microscopy. The incorporation of nanophase titania in silicone dramatically reduced the viability of Staphylococcus aureus (S. aureus) and the capability to adhere on the surface of hybrid silicone by ∼ 93% in relation to stand alone silicone. The conclusion of dramatic reduction in the viability of S. aureus is corroborated by different experimental approaches including biofilm inhibition assay, zone of inhibition, and through a novel experiment that involved incubation of biofilm with titania nanoparticles. It is proposed that the mechanism of disruption of bacterial film in the presence of titania involves puncturing of the bacterial cell membrane. - Highlights: • Network structure titania in silicone imparts antimicrobial activity. • Ability to microbial adhesion is significantly reduced. • Antimicrobial mechanism involves rupture of biofilm

  20. Mechanical properties of polymer-infiltrated-ceramic-network materials.

    Science.gov (United States)

    Coldea, Andrea; Swain, Michael V; Thiel, Norbert

    2013-04-01

    To determine and identify correlations between flexural strength, strain at failure, elastic modulus and hardness versus ceramic network densities of a range of novel polymer-infiltrated-ceramic-network (PICN) materials. Four ceramic network densities ranging from 59% to 72% of theoretical density, resin infiltrated PICN as well as pure polymer and dense ceramic cross-sections were subjected to Vickers Indentations (HV 5) for hardness evaluation. The flexural strength and elastic modulus were measured using three-point-bending. The fracture response of PICNs was determined for cracks induced by Vickers-indentation. Optical and scanning electron microscopy (SEM) was employed to observe the indented areas. Depending on the density of the porous ceramic the flexural strength of PICNs ranged from 131 to 160MPa, the hardness values ranged between 1.05 and 2.10GPa and the elastic modulus between 16.4 and 28.1GPa. SEM observations of the indentation induced cracks indicate that the polymer network causes greater crack deflection than the dense ceramic material. The results were compared with simple analytical expressions for property variation of two phase composite materials. This study points out the correlation between ceramic network density, elastic modulus and hardness of PICNs. These materials are considered to more closely imitate natural tooth properties compared with existing dental restorative materials. Copyright © 2013 Academy of Dental Materials. All rights reserved.

  1. Resilient Amorphous Networks Prepared by Photo-Crosslinking High-Molecular-Weight D,L-Lactide and Trimethylene Carbonate Macromers: Mechanical Properties and Shape-Memory Behavior

    NARCIS (Netherlands)

    Sharifi, Shahriar; Grijpma, Dirk W.

    2012-01-01

    Tough networks are prepared by photo-crosslinking high-molecular-weight DLLA and TMC macromers. These amorphous networks exhibit tunable thermal and mechanical properties and have excellent shape-memory features. Variation of the monomer ratio allows adjustment of Tg between approximately −13 and

  2. Brain and Social Networks: Fundamental Building Blocks of Human Experience.

    Science.gov (United States)

    Falk, Emily B; Bassett, Danielle S

    2017-09-01

    How do brains shape social networks, and how do social ties shape the brain? Social networks are complex webs by which ideas spread among people. Brains comprise webs by which information is processed and transmitted among neural units. While brain activity and structure offer biological mechanisms for human behaviors, social networks offer external inducers or modulators of those behaviors. Together, these two axes represent fundamental contributors to human experience. Integrating foundational knowledge from social and developmental psychology and sociology on how individuals function within dyads, groups, and societies with recent advances in network neuroscience can offer new insights into both domains. Here, we use the example of how ideas and behaviors spread to illustrate the potential of multilayer network models. Copyright © 2017 Elsevier Ltd. All rights reserved.

  3. A Spiking Working Memory Model Based on Hebbian Short-Term Potentiation

    Science.gov (United States)

    Fiebig, Florian

    2017-01-01

    A dominant theory of working memory (WM), referred to as the persistent activity hypothesis, holds that recurrently connected neural networks, presumably located in the prefrontal cortex, encode and maintain WM memory items through sustained elevated activity. Reexamination of experimental data has shown that prefrontal cortex activity in single units during delay periods is much more variable than predicted by such a theory and associated computational models. Alternative models of WM maintenance based on synaptic plasticity, such as short-term nonassociative (non-Hebbian) synaptic facilitation, have been suggested but cannot account for encoding of novel associations. Here we test the hypothesis that a recently identified fast-expressing form of Hebbian synaptic plasticity (associative short-term potentiation) is a possible mechanism for WM encoding and maintenance. Our simulations using a spiking neural network model of cortex reproduce a range of cognitive memory effects in the classical multi-item WM task of encoding and immediate free recall of word lists. Memory reactivation in the model occurs in discrete oscillatory bursts rather than as sustained activity. We relate dynamic network activity as well as key synaptic characteristics to electrophysiological measurements. Our findings support the hypothesis that fast Hebbian short-term potentiation is a key WM mechanism. SIGNIFICANCE STATEMENT Working memory (WM) is a key component of cognition. Hypotheses about the neural mechanism behind WM are currently under revision. Reflecting recent findings of fast Hebbian synaptic plasticity in cortex, we test whether a cortical spiking neural network model with such a mechanism can learn a multi-item WM task (word list learning). We show that our model can reproduce human cognitive phenomena and achieve comparable memory performance in both free and cued recall while being simultaneously compatible with experimental data on structure, connectivity, and

  4. Nuclear Magnetic Shielding Constants from Quantum Mechanical/Molecular Mechanical Calculations Using Polarizable Embedding: Role of the Embedding Potential

    DEFF Research Database (Denmark)

    Steinmann, Casper; Olsen, Jógvan Magnus Haugaard; Kongsted, Jacob

    2014-01-01

    We present NMR shielding constants obtained through quantum mechanical/molecular mechanical (QM/MM) embedding calculations. Contrary to previous reports, we show that a relatively small QM region is sufficient, provided that a high-quality embedding potential is used. The calculated averaged NMR...... shielding constants of both acrolein and acetone solvated in water are based on a number of snapshots extracted from classical molecular dynamics simulations. We focus on the carbonyl chromophore in both molecules, which shows large solvation effects, and we study the convergence of shielding constants...

  5. Potential in stochastic differential equations: novel construction

    International Nuclear Information System (INIS)

    Ao, P

    2004-01-01

    There is a whole range of emergent phenomena in a complex network such as robustness, adaptiveness, multiple-equilibrium, hysteresis, oscillation and feedback. Those non-equilibrium behaviours can often be described by a set of stochastic differential equations. One persistent important question is the existence of a potential function. Here we demonstrate that a dynamical structure built into stochastic differential equation allows us to construct such a global optimization potential function. We present an explicit construction procedure to obtain the potential and relevant quantities. In the procedure no reference to the Fokker-Planck equation is needed. The availability of the potential suggests that powerful statistical mechanics tools can be used in nonequilibrium situations. (letter to the editor)

  6. Chemical compounds from anthropogenic environment and immune evasion mechanisms: potential interactions

    Science.gov (United States)

    Kravchenko, Julia; Corsini, Emanuela; Williams, Marc A.; Decker, William; Manjili, Masoud H.; Otsuki, Takemi; Singh, Neetu; Al-Mulla, Faha; Al-Temaimi, Rabeah; Amedei, Amedeo; Colacci, Anna Maria; Vaccari, Monica; Mondello, Chiara; Scovassi, A. Ivana; Raju, Jayadev; Hamid, Roslida A.; Memeo, Lorenzo; Forte, Stefano; Roy, Rabindra; Woodrick, Jordan; Salem, Hosni K.; Ryan, Elizabeth P.; Brown, Dustin G.; Lowe, Leroy; Lyerly, H.Kim

    2015-01-01

    An increasing number of studies suggest an important role of host immunity as a barrier to tumor formation and progression. Complex mechanisms and multiple pathways are involved in evading innate and adaptive immune responses, with a broad spectrum of chemicals displaying the potential to adversely influence immunosurveillance. The evaluation of the cumulative effects of low-dose exposures from the occupational and natural environment, especially if multiple chemicals target the same gene(s) or pathway(s), is a challenge. We reviewed common environmental chemicals and discussed their potential effects on immunosurveillance. Our overarching objective was to review related signaling pathways influencing immune surveillance such as the pathways involving PI3K/Akt, chemokines, TGF-β, FAK, IGF-1, HIF-1α, IL-6, IL-1α, CTLA-4 and PD-1/PDL-1 could individually or collectively impact immunosurveillance. A number of chemicals that are common in the anthropogenic environment such as fungicides (maneb, fluoxastrobin and pyroclostrobin), herbicides (atrazine), insecticides (pyridaben and azamethiphos), the components of personal care products (triclosan and bisphenol A) and diethylhexylphthalate with pathways critical to tumor immunosurveillance. At this time, these chemicals are not recognized as human carcinogens; however, it is known that they these chemicalscan simultaneously persist in the environment and appear to have some potential interfere with the host immune response, therefore potentially contributing to promotion interacting with of immune evasion mechanisms, and promoting subsequent tumor growth and progression. PMID:26002081

  7. Synergistic stiffening in double-fiber networks

    NARCIS (Netherlands)

    Rombouts, W.H.; Giesbers, M.; Lent, van J.W.M.; Wolf, de F.A.; Gucht, van der J.

    2014-01-01

    Many biological materials are composite structures, interpenetrating networks of different types of fibers. The composite nature of such networks leads to superior mechanical properties, but the origin of this mechanical synergism is still poorly understood. Here we study soft composite networks,

  8. Default mode network as a potential biomarker of chemotherapy-related brain injury

    Science.gov (United States)

    Kesler, Shelli R.

    2014-01-01

    Chronic medical conditions and/or their treatments may interact with aging to alter or even accelerate brain senescence. Adult onset cancer, for example, is a disease associated with advanced aging and emerging evidence suggests a profile of subtle but diffuse brain injury following cancer chemotherapy. Breast cancer is currently the primary model for studying these “chemobrain” effects. Given the widespread changes to brain structure and function as well as the common impairment of integrated cognitive skills observed following breast cancer chemotherapy, it is likely that large-scale brain networks are involved. Default mode network (DMN) is a strong candidate considering its preferential vulnerability to aging and sensitivity to toxicity and disease states. Additionally, chemotherapy is associated with several physiologic effects including increased inflammation and oxidative stress that are believed to elevate toxicity in the DMN. Biomarkers of DMN connectivity could aid in the development of treatments for chemotherapy-related cognitive decline. For example, certain nutritional interventions could potentially reduce the metabolic changes (e.g. amyloid beta toxicity) associated with DMN disruption. PMID:24913897

  9. On the Interplay between Entropy and Robustness of Gene Regulatory Networks

    Directory of Open Access Journals (Sweden)

    Bor-Sen Chen

    2010-05-01

    Full Text Available The interplay between entropy and robustness of gene network is a core mechanism of systems biology. The entropy is a measure of randomness or disorder of a physical system due to random parameter fluctuation and environmental noises in gene regulatory networks. The robustness of a gene regulatory network, which can be measured as the ability to tolerate the random parameter fluctuation and to attenuate the effect of environmental noise, will be discussed from the robust H∞ stabilization and filtering perspective. In this review, we will also discuss their balancing roles in evolution and potential applications in systems and synthetic biology.

  10. Potential interaction between transport and stream networks over the lowland rivers in Eastern India.

    Science.gov (United States)

    Roy, Suvendu; Sahu, Abhay Sankar

    2017-07-15

    Extension of transport networks supports good accessibility and associated with the development of a region. However, transport lines have fragmented the regional landscape and disturbed the natural interplay between rivers and their floodplains. Spatial analysis using multiple buffers provides information about the potential interaction between road and stream networks and their impact on channel morphology of a small watershed in the Lower Gangetic Plain. Present study is tried to understand the lateral and longitudinal disconnection in headwater stream by rural roads with the integration of geoinformatics and field survey. Significant (p development, delineation of stream corridor, regular monitoring and engineering efficiency for the construction of road and road-stream crossing might be effective in managing river geomorphology and riverine landscape. Copyright © 2017 Elsevier Ltd. All rights reserved.

  11. Dually cross-linked single network poly(acrylic acid) hydrogels with superior mechanical properties and water absorbency.

    Science.gov (United States)

    Zhong, Ming; Liu, Yi-Tao; Liu, Xiao-Ying; Shi, Fu-Kuan; Zhang, Li-Qin; Zhu, Mei-Fang; Xie, Xu-Ming

    2016-06-28

    Poly(acrylic acid) (PAA) hydrogels with superior mechanical properties, based on a single network structure with dual cross-linking, are prepared by one-pot free radical polymerization. The network structure of the PAA hydrogels is composed of dual cross-linking: a dynamic and reversible ionic cross-linking among the PAA chains enabled by Fe(3+) ions, and a sparse covalent cross-linking enabled by a covalent cross-linker (Bis). Under deformation, the covalently cross-linked PAA chains remain intact to maintain their original configuration, while the Fe(3+)-enabled ionic cross-linking among the PAA chains is broken to dissipate energy and then recombined. It is found that the mechanical properties of the PAA hydrogels are significantly influenced by the contents of covalent cross-linkers, Fe(3+) ions and water, which can be adjusted within a substantial range and thus broaden the applications of the hydrogels. Meanwhile, the PAA hydrogels have excellent recoverability based on the dynamic and reversible ionic cross-linking enabled by Fe(3+) ions. Moreover, the swelling capacity of the PAA hydrogels is as high as 1800 times in deionized water due to the synergistic effects of ionic and covalent cross-linkings. The combination of balanced mechanical properties, efficient recoverability, high swelling capacity and facile preparation provides a new method to obtain high-performance hydrogels.

  12. Spiny Neurons of Amygdala, Striatum and Cortex Use Dendritic Plateau Potentials to Detect Network UP States

    Directory of Open Access Journals (Sweden)

    Katerina D Oikonomou

    2014-09-01

    Full Text Available Spiny neurons of amygdala, striatum, and cerebral cortex share four interesting features: [1] they are the most abundant cell type within their respective brain area, [2] covered by thousands of thorny protrusions (dendritic spines, [3] possess high levels of dendritic NMDA conductances, and [4] experience sustained somatic depolarizations in vivo and in vitro (UP states. In all spiny neurons of the forebrain, adequate glutamatergic inputs generate dendritic plateau potentials (dendritic UP states characterized by (i fast rise, (ii plateau phase lasting several hundred milliseconds and (iii abrupt decline at the end of the plateau phase. The dendritic plateau potential propagates towards the cell body decrementally to induce a long-lasting (longer than 100 ms, most often 200 – 800 ms steady depolarization (~20 mV amplitude, which resembles a neuronal UP state. Based on voltage-sensitive dye imaging, the plateau depolarization in the soma is precisely time-locked to the regenerative plateau potential taking place in the dendrite. The somatic plateau rises after the onset of the dendritic voltage transient and collapses with the breakdown of the dendritic plateau depolarization. We hypothesize that neuronal UP states in vivo reflect the occurrence of dendritic plateau potentials (dendritic UP states. We propose that the somatic voltage waveform during a neuronal UP state is determined by dendritic plateau potentials. A mammalian spiny neuron uses dendritic plateau potentials to detect and transform coherent network activity into a ubiquitous neuronal UP state. The biophysical properties of dendritic plateau potentials allow neurons to quickly attune to the ongoing network activity, as well as secure the stable amplitudes of successive UP states.

  13. A Networks Approach to Modeling Enzymatic Reactions.

    Science.gov (United States)

    Imhof, P

    2016-01-01

    Modeling enzymatic reactions is a demanding task due to the complexity of the system, the many degrees of freedom involved and the complex, chemical, and conformational transitions associated with the reaction. Consequently, enzymatic reactions are not determined by precisely one reaction pathway. Hence, it is beneficial to obtain a comprehensive picture of possible reaction paths and competing mechanisms. By combining individually generated intermediate states and chemical transition steps a network of such pathways can be constructed. Transition networks are a discretized representation of a potential energy landscape consisting of a multitude of reaction pathways connecting the end states of the reaction. The graph structure of the network allows an easy identification of the energetically most favorable pathways as well as a number of alternative routes. © 2016 Elsevier Inc. All rights reserved.

  14. An exploration of options and functions of climate technology centres and networks. Discussion paper

    International Nuclear Information System (INIS)

    De Coninck, H.C.; Wuertenberger, L.; Cochran, J.; Cox, S.; Benioff, R.

    2010-11-01

    This paper responds to a request to UNEP from the UNFCCC Expert Group on Technology Transfer to examine operational modalities for climate technology centres and networks. The paper first discusses possible dimensions for the climate technology centre and network, and it reviews a number of existing networks and centres. It then distinguishes five options for the organizational structure and describes potential operational characteristics for each of these options. All options examined seek to build from existing climate and non-climate-related public and private technology centres, networks, and initiatives. Consistent with the UNFCCC negotiating text and draft technology decision, the paper evaluates potential implementation options and outcomes for each of the functions tentatively assigned to the climate technology centre and network, as well as selected functions of the technology executive committee. Approaches are offered for integrating delivery of these functions through coordinated programmes, and hypothetical examples are given to explain how the technology mechanism might add value in practice. The options presented in this paper are not an exhaustive treatment of potential structures or implementation approaches, and other approaches can be considered.

  15. Possibility and potential of clean development mechanisms in China

    International Nuclear Information System (INIS)

    Gao Weijun; Zhou Nan; Li Haifeng; Kammen, Daniel M

    2007-01-01

    China has become the world's second largest greenhouse gas (GHG) emitter behind the United States. It emits approximately three billion tons of CO 2 equivalents every year. Its growing economy and large population are making a wealthier, more consumption-oriented country. Energy demand is expected to grow 5-10% per year through 2030. Therefore, a large potential of GHG emission reduction in China can be expected. The clean development mechanism (CDM) put forward in the Kyoto Protocol for reductions of GHGs can support the sustainable development of developing countries and help developed countries to achieve their emission reduction targets at low cost. However, there are still many disagreements to be resolved between developing and developed countries. In this letter, we try to introduce the current development of CDM projects in China and discuss its potential and opportunities in the future decades

  16. Probiotics and Alcoholic Liver Disease: Treatment and Potential Mechanisms

    Directory of Open Access Journals (Sweden)

    Fengyuan Li

    2016-01-01

    Full Text Available Despite extensive research, alcohol remains one of the most common causes of liver disease in the United States. Alcoholic liver disease (ALD encompasses a broad spectrum of disorders, including steatosis, steatohepatitis, and cirrhosis. Although many agents and approaches have been tested in patients with ALD and in animals with experimental ALD in the past, there is still no FDA (Food and Drug Administration approved therapy for any stage of ALD. With the increasing recognition of the importance of gut microbiota in the onset and development of a variety of diseases, the potential use of probiotics in ALD is receiving increasing investigative and clinical attention. In this review, we summarize recent studies on probiotic intervention in the prevention and treatment of ALD in experimental animal models and patients. Potential mechanisms underlying the probiotic function are also discussed.

  17. GTSO: Global Trace Synchronization and Ordering Mechanism for Wireless Sensor Network Monitoring Platforms.

    Science.gov (United States)

    Navia, Marlon; Campelo, José Carlos; Bonastre, Alberto; Ors, Rafael

    2017-12-23

    Monitoring is one of the best ways to evaluate the behavior of computer systems. When the monitored system is a distributed system-such as a wireless sensor network (WSN)-the monitoring operation must also be distributed, providing a distributed trace for further analysis. The temporal sequence of occurrence of the events registered by the distributed monitoring platform (DMP) must be correctly established to provide cause-effect relationships between them, so the logs obtained in different monitor nodes must be synchronized. Many of synchronization mechanisms applied to DMPs consist in adjusting the internal clocks of the nodes to the same value as a reference time. However, these mechanisms can create an incoherent event sequence. This article presents a new method to achieve global synchronization of the traces obtained in a DMP. It is based on periodic synchronization signals that are received by the monitor nodes and logged along with the recorded events. This mechanism processes all traces and generates a global post-synchronized trace by scaling all times registered proportionally according with the synchronization signals. It is intended to be a simple but efficient offline mechanism. Its application in a WSN-DMP demonstrates that it guarantees a correct ordering of the events, avoiding the aforementioned issues.

  18. GTSO: Global Trace Synchronization and Ordering Mechanism for Wireless Sensor Network Monitoring Platforms

    Science.gov (United States)

    Bonastre, Alberto; Ors, Rafael

    2017-01-01

    Monitoring is one of the best ways to evaluate the behavior of computer systems. When the monitored system is a distributed system—such as a wireless sensor network (WSN)—the monitoring operation must also be distributed, providing a distributed trace for further analysis. The temporal sequence of occurrence of the events registered by the distributed monitoring platform (DMP) must be correctly established to provide cause-effect relationships between them, so the logs obtained in different monitor nodes must be synchronized. Many of synchronization mechanisms applied to DMPs consist in adjusting the internal clocks of the nodes to the same value as a reference time. However, these mechanisms can create an incoherent event sequence. This article presents a new method to achieve global synchronization of the traces obtained in a DMP. It is based on periodic synchronization signals that are received by the monitor nodes and logged along with the recorded events. This mechanism processes all traces and generates a global post-synchronized trace by scaling all times registered proportionally according with the synchronization signals. It is intended to be a simple but efficient offline mechanism. Its application in a WSN-DMP demonstrates that it guarantees a correct ordering of the events, avoiding the aforementioned issues. PMID:29295494

  19. A Social Potential Fields Approach for Self-Deployment and Self-Healing in Hierarchical Mobile Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Eva González-Parada

    2017-01-01

    Full Text Available Autonomous mobile nodes in mobile wireless sensor networks (MWSN allow self-deployment and self-healing. In both cases, the goals are: (i to achieve adequate coverage; and (ii to extend network life. In dynamic environments, nodes may use reactive algorithms so that each node locally decides when and where to move. This paper presents a behavior-based deployment and self-healing algorithm based on the social potential fields algorithm. In the proposed algorithm, nodes are attached to low cost robots to autonomously navigate in the coverage area. The proposed algorithm has been tested in environments with and without obstacles. Our study also analyzes the differences between non-hierarchical and hierarchical routing configurations in terms of network life and coverage.

  20. Volunteerism: Social Network Dynamics and Education

    Science.gov (United States)

    Ajrouch, Kristine J.; Antonucci, Toni C.; Webster, Noah J.

    2016-01-01

    Objectives . We examine how changes in social networks influence volunteerism through bridging (diversity) and bonding (spending time) mechanisms. We further investigate whether social network change substitutes or amplifies the effects of education on volunteerism. Methods . Data (n = 543) are drawn from a two-wave survey of Social Relations and Health over the Life Course (SRHLC). Zero-inflated negative binomial regressions were conducted to test competing hypotheses about how changes in social network characteristics alone and in conjunction with education level predict likelihood and frequency of volunteering. Results . Changes in social networks were associated with volunteerism: as the proportion of family members decreased and the average number of network members living within a one-hour drive increased over time, participants reported higher odds of volunteering. The substitution hypothesis was supported: social networks that exhibited more geographic proximity and greater contact frequency over-time compensated for lower levels of education to predict volunteering more hours. Discussion . The dynamic role of social networks and the ways in which they may work through bridging and bonding to influence both likelihood and frequency of volunteering are discussed. The potential benefits of volunteerism in light of longer life expectancies and smaller families are also considered. PMID:25512570

  1. A systems biology-based approach to uncovering the molecular mechanisms underlying the effects of dragon's blood tablet in colitis, involving the integration of chemical analysis, ADME prediction, and network pharmacology.

    Directory of Open Access Journals (Sweden)

    Haiyu Xu

    Full Text Available Traditional Chinese medicine (TCM is one of the oldest East Asian medical systems. The present study adopted a systems biology-based approach to provide new insights relating to the active constituents and molecular mechanisms underlying the effects of dragon's blood (DB tablets for the treatment of colitis. This study integrated chemical analysis, prediction of absorption, distribution, metabolism, and excretion (ADME, and network pharmacology. Firstly, a rapid, reliable, and accurate ultra-performance liquid chromatography-electrospray ionization-tandem mass spectrometry method was employed to identify 48 components of DB tablets. In silico prediction of the passive absorption of these compounds, based on Caco-2 cell permeability, and their P450 metabolism enabled the identification of 22 potentially absorbed components and 8 metabolites. Finally, networks were constructed to analyze interactions between these DB components/metabolites absorbed and their putative targets, and between the putative DB targets and known therapeutic targets for colitis. This study provided a great opportunity to deepen the understanding of the complex pharmacological mechanisms underlying the effects of DB in colitis treatment.

  2. Endocrine-disrupting Chemicals: Review of Toxicological Mechanisms Using Molecular Pathway Analysis

    Science.gov (United States)

    Yang, Oneyeol; Kim, Hye Lim; Weon, Jong-Il; Seo, Young Rok

    2015-01-01

    Endocrine disruptors are known to cause harmful effects to human through various exposure routes. These chemicals mainly appear to interfere with the endocrine or hormone systems. As importantly, numerous studies have demonstrated that the accumulation of endocrine disruptors can induce fatal disorders including obesity and cancer. Using diverse biological tools, the potential molecular mechanisms related with these diseases by exposure of endocrine disruptors. Recently, pathway analysis, a bioinformatics tool, is being widely used to predict the potential mechanism or biological network of certain chemicals. In this review, we initially summarize the major molecular mechanisms involved in the induction of the above mentioned diseases by endocrine disruptors. Additionally, we provide the potential markers and signaling mechanisms discovered via pathway analysis under exposure to representative endocrine disruptors, bisphenol, diethylhexylphthalate, and nonylphenol. The review emphasizes the importance of pathway analysis using bioinformatics to finding the specific mechanisms of toxic chemicals, including endocrine disruptors. PMID:25853100

  3. Prediction-Based Energy Saving Mechanism in 3GPP NB-IoT Networks.

    Science.gov (United States)

    Lee, Jinseong; Lee, Jaiyong

    2017-09-01

    The current expansion of the Internet of things (IoT) demands improved communication platforms that support a wide area with low energy consumption. The 3rd Generation Partnership Project introduced narrowband IoT (NB-IoT) as IoT communication solutions. NB-IoT devices should be available for over 10 years without requiring a battery replacement. Thus, a low energy consumption is essential for the successful deployment of this technology. Given that a high amount of energy is consumed for radio transmission by the power amplifier, reducing the uplink transmission time is key to ensure a long lifespan of an IoT device. In this paper, we propose a prediction-based energy saving mechanism (PBESM) that is focused on enhanced uplink transmission. The mechanism consists of two parts: first, the network architecture that predicts the uplink packet occurrence through a deep packet inspection; second, an algorithm that predicts the processing delay and pre-assigns radio resources to enhance the scheduling request procedure. In this way, our mechanism reduces the number of random accesses and the energy consumed by radio transmission. Simulation results showed that the energy consumption using the proposed PBESM is reduced by up to 34% in comparison with that in the conventional NB-IoT method.

  4. Naltrexone ameliorates functional network abnormalities in alcohol‐dependent individuals

    Science.gov (United States)

    Baek, Kwangyeol; Tait, Roger; Elliott, Rebecca; Ersche, Karen D.; Flechais, Remy; McGonigle, John; Murphy, Anna; Nestor, Liam J.; Orban, Csaba; Passetti, Filippo; Paterson, Louise M.; Rabiner, Ilan; Reed, Laurence; Smith, Dana; Suckling, John; Taylor, Eleanor M.; Bullmore, Edward T.; Lingford‐Hughes, Anne R.; Deakin, Bill; Nutt, David J.; Sahakian, Barbara J.; Robbins, Trevor W.; Voon, Valerie

    2017-01-01

    Abstract Naltrexone, an opioid receptor antagonist, is commonly used as a relapse prevention medication in alcohol and opiate addiction, but its efficacy and the mechanisms underpinning its clinical usefulness are not well characterized. In the current study, we examined the effects of 50‐mg naltrexone compared with placebo on neural network changes associated with substance dependence in 21 alcohol and 36 poly‐drug‐dependent individuals compared with 36 healthy volunteers. Graph theoretic and network‐based statistical analysis of resting‐state functional magnetic resonance imaging (MRI) data revealed that alcohol‐dependent subjects had reduced functional connectivity of a dispersed network compared with both poly‐drug‐dependent and healthy subjects. Higher local efficiency was observed in both patient groups, indicating clustered and segregated network topology and information processing. Naltrexone normalized heightened local efficiency of the neural network in alcohol‐dependent individuals, to the same levels as healthy volunteers. Naltrexone failed to have an effect on the local efficiency in abstinent poly‐substance‐dependent individuals. Across groups, local efficiency was associated with substance, but no alcohol exposure implicating local efficiency as a potential premorbid risk factor in alcohol use disorders that can be ameliorated by naltrexone. These findings suggest one possible mechanism for the clinical effects of naltrexone, namely, the amelioration of disrupted network topology. PMID:28247526

  5. Cascading Dynamics of Heterogenous Scale-Free Networks with Recovery Mechanism

    Directory of Open Access Journals (Sweden)

    Shudong Li

    2013-01-01

    Full Text Available In network security, how to use efficient response methods against cascading failures of complex networks is very important. In this paper, concerned with the highest-load attack (HL and random attack (RA on one edge, we define five kinds of weighting strategies to assign the external resources for recovering the edges from cascading failures in heterogeneous scale-free (SF networks. The influence of external resources, the tolerance parameter, and the different weighting strategies on SF networks against cascading failures is investigated carefully. We find that, under HL attack, the fourth kind of weighting method can more effectively improve the integral robustness of SF networks, simultaneously control the spreading velocity, and control the outburst of cascading failures in SF networks than other methods. Moreover, the third method is optimal if we only knew the local structure of SF networks and the uniform assignment is the worst. The simulations of the real-world autonomous system in, Internet have also supported our findings. The results are useful for using efficient response strategy against the emergent accidents and controlling the cascading failures in the real-world networks.

  6. Precise synaptic efficacy alignment suggests potentiation dominated learning

    Directory of Open Access Journals (Sweden)

    Christoph eHartmann

    2016-01-01

    Full Text Available Recent evidence suggests that parallel synapses from the same axonal branch onto the same dendritic branch have almost identical strength. It has been proposed that this alignment is only possible through learning rules that integrate activity over long time spans. However, learning mechanisms such as spike-timing-dependent plasticity (STDP are commonly assumed to be temporally local. Here, we propose that the combination of temporally local STDP and a multiplicative synaptic normalization mechanism is sufficient to explain the alignment of parallel synapses.To address this issue, we introduce three increasingly complex models: First, we model the idealized interaction of STDP and synaptic normalization in a single neuron as a simple stochastic process and derive analytically that the alignment effect can be described by a so-called Kesten process. From this we can derive that synaptic efficacy alignment requires potentiation-dominated learning regimes. We verify these conditions in a single-neuron model with independent spiking activities but more realistic synapses. As expected, we only observe synaptic efficacy alignment for long-term potentiation-biased STDP. Finally, we explore how well the findings transfer to recurrent neural networks where the learning mechanisms interact with the correlated activity of the network. We find that due to the self-reinforcing correlations in recurrent circuits under STDP, alignment occurs for both long-term potentiation- and depression-biased STDP, because the learning will be potentiation dominated in both cases due to the potentiating events induced by correlated activity. This is in line with recent results demonstrating a dominance of potentiation over depression during waking and normalization during sleep. This leads us to predict that individual spine pairs will be more similar in the morning than they are after sleep depriviation.In conclusion, we show that synaptic normalization in conjunction with

  7. Towards the Engineering of Dependable P2P-Based Network Control — The Case of Timely Routing Control Messages

    Science.gov (United States)

    Tutschku, Kurt; Nakao, Akihiro

    This paper introduces a methodology for engineering best-effort P2P algorithms into dependable P2P-based network control mechanism. The proposed method is built upon an iterative approach consisting of improving the original P2P algorithm by appropriate mechanisms and of thorough performance assessment with respect to dependability measures. The potential of the methodology is outlined by the example of timely routing control for vertical handover in B3G wireless networks. In detail, the well-known Pastry and CAN algorithms are enhanced to include locality. By showing how to combine algorithmic enhancements with performance indicators, this case study paves the way for future engineering of dependable network control mechanisms through P2P algorithms.

  8. Experimental resource pulses influence social-network dynamics and the potential for information flow in tool-using crows.

    Science.gov (United States)

    St Clair, James J H; Burns, Zackory T; Bettaney, Elaine M; Morrissey, Michael B; Otis, Brian; Ryder, Thomas B; Fleischer, Robert C; James, Richard; Rutz, Christian

    2015-11-03

    Social-network dynamics have profound consequences for biological processes such as information flow, but are notoriously difficult to measure in the wild. We used novel transceiver technology to chart association patterns across 19 days in a wild population of the New Caledonian crow--a tool-using species that may socially learn, and culturally accumulate, tool-related information. To examine the causes and consequences of changing network topology, we manipulated the environmental availability of the crows' preferred tool-extracted prey, and simulated, in silico, the diffusion of information across field-recorded time-ordered networks. Here we show that network structure responds quickly to environmental change and that novel information can potentially spread rapidly within multi-family communities, especially when tool-use opportunities are plentiful. At the same time, we report surprisingly limited social contact between neighbouring crow communities. Such scale dependence in information-flow dynamics is likely to influence the evolution and maintenance of material cultures.

  9. Potential of dynamic spectrum allocation in LTE macro networks

    NARCIS (Netherlands)

    Hoffmann, H.; Ramachandra, P.; Kovacs, I.Z.; Jorguseski, L.; Gunnarsson, F.; Kurner, T.

    2015-01-01

    In recent years Mobile Network Operators (MNOs) worldwide are extensively deploying LTE networks in different spectrum bands and utilising different bandwidth configurations. Initially, the deployment is coverage oriented with macro cells using the lower LTE spectrum bands. As the offered traffic

  10. Photocrosslinked PLA-PEO-PLA Hydrogels from Self-Assembled Physical Networks: Mechanical Properties and Influence of Assumed Constitutive Relationships

    Science.gov (United States)

    Sanabria-DeLong, Naomi; Crosby, Alfred J.; Tew, Gregory N.

    2014-01-01

    Poly(lactide) – block – poly(ethylene oxide) – block – poly(lactide) [PLA-PEO-PLA] triblock copolymers are known to form physical hydrogels in water, due to the polymer's amphiphilicity. Their mechanical properties, biocompatibility, and biodegradability have made them attractive for use as soft tissue scaffolds. However, the network junction points are not covalently crosslinked and in a highly aqueous environment these hydrogels adsorb more water, transform from gel to sol, and lose the designed mechanical properties. In this report, a hydrogel was formed by using a novel two step approach. In the first step end-functionalized PLA-PEOPLA triblock was self-assembled into a physical hydrogel through hydrophobic micelle network junctions, and then, in the second step, this self-assembled physical network structure was locked into place by photocrosslinking the terminal acrylate groups. In contrast to physical hydrogels, the photocrosslinked gels remained intact in phosphate buffered solution at body temperature. The swelling, degradation, and mechanical properties were characterized and demonstrated extended degradation time (~ 65 days), exponential decrease in modulus with degradation time, and tunable shear modulus (1.6 – 133 kPa) by varying concentration. We also discuss the various constitutive relationships (Hookean, Neo-Hookean, and Mooney-Rivlin) that can be used to describe the stress-strain behavior of these hydrogels. The chosen model and assumptions used for data fitting influences the obtained modulus values by as much as a factor of 3.5, demonstrating the importance of clearly stating one's data fitting parameters so that accurate comparisons can be made within the literature. PMID:18817440

  11. Potential mechanisms linking probiotics to diabetes: a narrative review of the literature

    Directory of Open Access Journals (Sweden)

    Maryam Miraghajani

    Full Text Available ABSTRACT CONTEXT AND OBJECTIVE: Some studies have suggested a wide range of possible mechanisms through which probiotics may play a role in diabetes prevention and treatment. However, the underlying mechanisms are not fully understood. We conducted this study to review the potential mechanisms suggested for the effect of probiotics in diabetes. DESIGN AND SETTING: Narrative review conducted at the Food Security Research Center of Isfahan. METHODS: A search in the electronic databases MEDLINE (PubMed, Cochrane Library, Web of Science and Google scholar was performed up to October 2016. RESULTS: The initial search yielded 1214 reports. After removing duplicates, 704 titles and abstracts were screened. Finally, out of 83 full-text articles that were reviewed for eligibility, 30 articles were included in the final analysis. The anti-diabetic mechanisms for probiotics reported encompass intraluminal and direct effects on the intestinal mucosa and microbiota (n = 13, anti-inflammatory and immunomodulatory effects (n = 10, antioxidative effects (n = 5, effects on endoplasmic reticulum (ER stress and expression of genes involved in glucose homeostasis and insulin resistance (n = 6, with some studies pointing to more than one mechanism. CONCLUSION: The results may throw some light on the capacity of probiotics as a novel approach towards controlling diabetes. However, further human studies are warranted to elucidate and confirm the potential role of probiotics in diabetes prevention and treatment. Also, it needs to be ascertained whether the effectiveness of probiotics in diabetes prevention and treatment is dependent on the strain of the microorganisms.

  12. Reproductive endocrine-disrupting effects of triclosan: Population exposure, present evidence and potential mechanisms

    International Nuclear Information System (INIS)

    Wang, Cai-Feng; Tian, Ying

    2015-01-01

    Triclosan has been used as a broad-spectrum antibacterial agent for over 40 years worldwide. Increasing reports indicate frequent detection and broad exposure to triclosan in the natural environment and the human body. Current laboratory studies in various species provide strong evidence for its disrupting effects on the endocrine system, especially reproductive hormones. Multiple modes of action have been suggested, including disrupting hormone metabolism, displacing hormones from hormone receptors and disrupting steroidogenic enzyme activity. Although epidemiological studies on its effects in humans are mostly negative but conflicting, which is typical of much of the early evidence on the toxicity of EDCs, overall, the evidence suggests that triclosan is an EDC. This article reviews human exposure to triclosan, describes the current evidence regarding its reproductive endocrine-disrupting effects, and discusses potential mechanisms to provide insights for further study on its endocrine-disrupting effects in humans. - Highlights: • Triclosan is widely detected in human urine, blood and breast milk. • Laboratory studies suggest reproductive endocrine-disrupting effects of triclosan. • Laboratory studies suggest estrogenic properties of triclosan. • There are three potential mechanisms regarding the estrogenic effect of triclosan. • Prospective epidemiological studies on vulnerable populations are needed. - This review summarizes current evidence on human exposure to triclosan, and its reproductive endocrine-disrupting effects and potential mechanisms.

  13. Photocrosslinked nanocomposite hydrogels from PEG and silica nanospheres: Structural, mechanical and cell adhesion characteristics

    International Nuclear Information System (INIS)

    Gaharwar, Akhilesh K.; Rivera, Christian; Wu, Chia-Jung; Chan, Burke K.; Schmidt, Gudrun

    2013-01-01

    Photopolymerized hydrogels are extensively investigated for various tissue engineering applications, primarily due to their ability to form hydrogels in a minimally invasive manner. Although photocrosslinkable hydrogels provide necessary biological and chemical characteristics to mimic cellular microenvironments, they often lack sufficient mechanical properties. Recently, nanocomposite approaches have demonstrated potential to overcome these deficits by reinforcing the hydrogel network with. In this study, we investigate some physical, chemical, and biological properties of photocrosslinked poly(ethylene glycol) (PEG)-silica hydrogels. The addition of silica nanospheres significantly suppresses the hydration degree of the PEG hydrogels, indicating surface interactions between the silica nanospheres and the polymer chains. No significant change in hydrogel microstructure or average pore size due to the addition of silica nanospheres was observed. However, addition of silica nanospheres significantly increases both the mechanical strength and the toughness of the hydrogel networks. The biological properties of these nanocomposite hydrogels were evaluated by seeding fibroblast cells on the hydrogel surface. While the PEG hydrogels showed minimum cell adhesion, spreading and proliferation, the addition of silica nanospheres enhanced initial cell adhesion, promoted cell spreading and increased the metabolic activity of the cells. Overall, results indicate that the addition of silica nanospheres improves the mechanical stiffness and cell adhesion properties of PEG hydrogels and can be used for biomedical applications that required controlled cell adhesion. - Graphical abstract: Structural, mechanical and biological properties of photocrosslinked nanocomposite hydrogels from silica and poly(ethylene oxide) are investigated. Silica reinforce the hydrogel network and improved mechanical strength. Addition of induces cell adhesion characteristic properties for various

  14. Governance Mechanisms in Food Community Networks

    NARCIS (Netherlands)

    Pascucci, S.; Lombardi, A.; Cembalo, L.; Dentoni, D.

    2013-01-01

    This paper discusses the concept of the food community network (FCN) and how consumers and farmers organize credence food transactions. The FCN is based on pooling specific resources and using membership-based contracts to assign decision and property rights. It implies an organization based on a

  15. Quantitative analysis of the network structure that underlines the transitioning in mechanical responses of pea protein gels

    NARCIS (Netherlands)

    Munialo, C.D.; Linden, van der E.; Ako, K.; Jongh, de H.H.J.

    2015-01-01

    The objective of this study was to analyze quantitatively the network structure that underlines the transitioning in the mechanical responses of heat-induced pea protein gels. To achieve this, gels were prepared from pea proteins at varying pHs from 3.0 to 4.2 at a fixed 100 mg/mL protein

  16. Network analysis of microRNAs and their regulation in human ovarian cancer

    KAUST Repository

    Schmeier, Sebastian; Schaefer, Ulf; Essack, Magbubah; Bajic, Vladimir B.

    2011-01-01

    Background: MicroRNAs (miRNAs) are small non-coding RNA molecules that repress the translation of messenger RNAs (mRNAs) or degrade mRNAs. These functions of miRNAs allow them to control key cellular processes such as development, differentiation and apoptosis, and they have also been implicated in several cancers such as leukaemia, lung, pancreatic and ovarian cancer (OC). Unfortunately, the specific machinery of miRNA regulation, involving transcription factors (TFs) and transcription co-factors (TcoFs), is not well understood. In the present study we focus on computationally deciphering the underlying network of miRNAs, their targets, and their control mechanisms that have an influence on OC development.Results: We analysed experimentally verified data from multiple sources that describe miRNA influence on diseases, miRNA targeting of mRNAs, and on protein-protein interactions, and combined this data with ab initio transcription factor binding site predictions within miRNA promoter regions. From these analyses, we derived a network that describes the influence of miRNAs and their regulation in human OC. We developed a methodology to analyse the network in order to find the nodes that have the largest potential of influencing the network's behaviour (network hubs). We further show the potentially most influential miRNAs, TFs and TcoFs, showing subnetworks illustrating the involved mechanisms as well as regulatory miRNA network motifs in OC. We find an enrichment of miRNA targeted OC genes in the highly relevant pathways cell cycle regulation and apoptosis.Conclusions: We combined several sources of interaction and association data to analyse and place miRNAs within regulatory pathways that influence human OC. These results represent the first comprehensive miRNA regulatory network analysis for human OC. This suggests that miRNAs and their regulation may play a major role in OC and that further directed research in this area is of utmost importance to enhance our

  17. Mechanical and swelling behaviour of well characterized polybutadiene networks

    Science.gov (United States)

    Mckenna, Gregory B.; Hinkley, Jeffrey A.

    1986-01-01

    Endlinking of hydroxyl-terminated polybutadiene with the appropriate isocyanate has been used to prepare well characterized networks. Two networks have been studied with molecular weights of the prepolymers being 6100 and 2400 g/mole by g.p.c. Cylindrical specimens were prepared and the derivatives of the stored energy function with respect to the stretch invariants were determined by torque and normal force measurements in torsion. From these data the Valanis-Landel (1967) stored energy function derivatives w-prime(lambda) were determined for both networks. The stored energy function for the junction constraint model of Flory (1953, 1977, 1979, 1985) which is a special form of the Valanis-Landel function, has been fitted to that determined from the experiments. The contributions to the stored energy function from the phantom network and from the junction constraints respectively do not agree with predictions from the topologies of the networks. In spite of this, the form of w-prime(lambda) for the junction constraint model gives an excellent 'curve fit' to the data. Comparison is also made with equilibrium swelling.

  18. THE ROLE OF REGIONAL CENTERS AND UNIVERSITY CHILDREN’S HOSPITAL IN DEVELOPMENT OF HOME MECHANICAL VENTILATION NETWORK

    Directory of Open Access Journals (Sweden)

    Rsovac Snezana

    2017-08-01

    Full Text Available Application of home mechanical ventilators represents the future in the treatment of children with chronic respiratory insufficiency. In this way patients are treated in the home environment, they have full support from their families, they are protected against nosocomial infections and their condition is monitored by medical staff. The role of regional centers is very important in the future development of the home mechanical ventilation network. Doctors in these centers under the full support of the University Children's Hospital physicians can assist and monitor the treatment of children on the household respirators.

  19. Network reconfiguration and neuronal plasticity in rhythm-generating networks.

    Science.gov (United States)

    Koch, Henner; Garcia, Alfredo J; Ramirez, Jan-Marino

    2011-12-01

    Neuronal networks are highly plastic and reconfigure in a state-dependent manner. The plasticity at the network level emerges through multiple intrinsic and synaptic membrane properties that imbue neurons and their interactions with numerous nonlinear properties. These properties are continuously regulated by neuromodulators and homeostatic mechanisms that are critical to maintain not only network stability and also adapt networks in a short- and long-term manner to changes in behavioral, developmental, metabolic, and environmental conditions. This review provides concrete examples from neuronal networks in invertebrates and vertebrates, and illustrates that the concepts and rules that govern neuronal networks and behaviors are universal.

  20. Quantum optics of optomechanical networks

    International Nuclear Information System (INIS)

    Stannigel, K.

    2012-01-01

    This thesis proposes various setups in which micro-mechanical resonators and optomechanical systems can be combined with other quantum systems, such as solid-state qubits or atomic ensembles, in a beneficial way. These hybrid systems open up new ways for quantum control, and several protocols and applications for quantum information processing and, in particular, for quantum networks are presented. Part I describes an optically mediated coupling between the vibrational modes of a semi-transparent dielectric membrane and the center-of-mass motion of an atomic ensemble. Using the sophisticated toolbox available for the control of atomic systems, this setting enables an indirect manipulation of the membrane, including, for example, cooling it to the vibrational ground state. A fully quantum mechanical treatment of this open system is given in terms of the quantum stochastic Schrödinger equation. In Part II we explore the potential of optomechanical systems for quantum information processing applications. First, we introduce the concept of an optomechanical transducer, where a micro-mechanical resonator mediates an interaction between a solid-state based qubit on the one hand, and photons in an optical cavity on the other hand. The resulting qubit-light interface is shown to enable quantum state transfers between two distant solid-state qubits, thereby making them available for quantum networking applications. Second, we study multi-mode optomechanical systems in the single-photon single-phonon strong coupling regime. We predict quantum signatures of this interaction, which could be observed in future experiments, and provide a route towards possible applications of these systems as quantum information processing units. Part III presents a dissipative state preparation scheme for cascaded quantum networks. In such networks excitations can only propagate along a single spatial direction and the optomechanical transducer represents one way of realizing them. We show, in

  1. Chemical compounds from anthropogenic environment and immune evasion mechanisms: potential interactions.

    Science.gov (United States)

    Kravchenko, Julia; Corsini, Emanuela; Williams, Marc A; Decker, William; Manjili, Masoud H; Otsuki, Takemi; Singh, Neetu; Al-Mulla, Faha; Al-Temaimi, Rabeah; Amedei, Amedeo; Colacci, Anna Maria; Vaccari, Monica; Mondello, Chiara; Scovassi, A Ivana; Raju, Jayadev; Hamid, Roslida A; Memeo, Lorenzo; Forte, Stefano; Roy, Rabindra; Woodrick, Jordan; Salem, Hosni K; Ryan, Elizabeth P; Brown, Dustin G; Bisson, William H; Lowe, Leroy; Lyerly, H Kim

    2015-06-01

    An increasing number of studies suggest an important role of host immunity as a barrier to tumor formation and progression. Complex mechanisms and multiple pathways are involved in evading innate and adaptive immune responses, with a broad spectrum of chemicals displaying the potential to adversely influence immunosurveillance. The evaluation of the cumulative effects of low-dose exposures from the occupational and natural environment, especially if multiple chemicals target the same gene(s) or pathway(s), is a challenge. We reviewed common environmental chemicals and discussed their potential effects on immunosurveillance. Our overarching objective was to review related signaling pathways influencing immune surveillance such as the pathways involving PI3K/Akt, chemokines, TGF-β, FAK, IGF-1, HIF-1α, IL-6, IL-1α, CTLA-4 and PD-1/PDL-1 could individually or collectively impact immunosurveillance. A number of chemicals that are common in the anthropogenic environment such as fungicides (maneb, fluoxastrobin and pyroclostrobin), herbicides (atrazine), insecticides (pyridaben and azamethiphos), the components of personal care products (triclosan and bisphenol A) and diethylhexylphthalate with pathways critical to tumor immunosurveillance. At this time, these chemicals are not recognized as human carcinogens; however, it is known that they these chemicalscan simultaneously persist in the environment and appear to have some potential interfere with the host immune response, therefore potentially contributing to promotion interacting with of immune evasion mechanisms, and promoting subsequent tumor growth and progression. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  2. Network Analysis of Rodent Transcriptomes in Spaceflight

    Science.gov (United States)

    Ramachandran, Maya; Fogle, Homer; Costes, Sylvain

    2017-01-01

    Network analysis methods leverage prior knowledge of cellular systems and the statistical and conceptual relationships between analyte measurements to determine gene connectivity. Correlation and conditional metrics are used to infer a network topology and provide a systems-level context for cellular responses. Integration across multiple experimental conditions and omics domains can reveal the regulatory mechanisms that underlie gene expression. GeneLab has assembled rich multi-omic (transcriptomics, proteomics, epigenomics, and epitranscriptomics) datasets for multiple murine tissues from the Rodent Research 1 (RR-1) experiment. RR-1 assesses the impact of 37 days of spaceflight on gene expression across a variety of tissue types, such as adrenal glands, quadriceps, gastrocnemius, tibalius anterior, extensor digitorum longus, soleus, eye, and kidney. Network analysis is particularly useful for RR-1 -omics datasets because it reinforces subtle relationships that may be overlooked in isolated analyses and subdues confounding factors. Our objective is to use network analysis to determine potential target nodes for therapeutic intervention and identify similarities with existing disease models. Multiple network algorithms are used for a higher confidence consensus.

  3. Network Partnership Diplomatic Mechanism: The New Path in Sino-Russian Cooperation - On the Sino-Russian Joint Dominance of BRICS Governance Mechanism

    Directory of Open Access Journals (Sweden)

    Zhijie Cheng

    2014-01-01

    Full Text Available 成志杰 王 宛 【内容提要】中俄合作是将来一定时期内国际格局变革与发展的决定性力量。但是,中俄关系存在典型的“二律背反”情结:既借重又怀疑,既合作又防范。处理两国关系,除了原有的双边机制外,中俄还可以通过网状伙伴外交机制进行多边机制下的合作。网状伙伴外交机制主要是指中俄在各个相关多边机制内的互动合作,是双方彼此需要、彼此借重,有效处理双边关系,共同应对国际事务的灵活机制。它具有自身的逻辑。加强和深化中俄合作并不意味着中俄要结盟。网状伙伴外交机制的提出更多是中俄合作的新路径,对于缓解中俄关系中竞争与博弈困境、促进相关国际机制发展等具有重要的意义。金砖国家应该建立金砖国家治理型机制。它需要一个主导性力量中心进行推动。网状伙伴外交机制有利于塑造金砖国家机制的主导性力量中心——中俄联合主导,它是金砖国家治理型机制的内涵之一。中俄联合主导将会在金砖国家机制发展中发挥引领作用。 Sino-Russian cooperation will become an important force in reforming and developing the international system in the near future. However, Sino-Russian relations are complicated since the two countries maintain a guarded attitude towards each other even while cooperating extensively. In addition to furthering bilateral relations, China and Russia can also choose to cooperate through multilateral network mechanisms. This provides opportunities for flexible and strategic cooperation and coordination between the two countries. Strengthening and deepening the Sino-Russian cooperation does not imply forming an actual alliance. The network partnership diplomatic mechanism could play an important role in alleviating competition and mistrust between China and Russia, promoting the development of relevant international

  4. Performance analysis and implementation of proposed mechanism for detection and prevention of security attacks in routing protocols of vehicular ad-hoc network (VANET

    Directory of Open Access Journals (Sweden)

    Parul Tyagi

    2017-07-01

    Full Text Available Next-generation communication networks have become widely popular as ad-hoc networks, broadly categorized as the mobile nodes based on mobile ad-hoc networks (MANET and the vehicular nodes based vehicular ad-hoc networks (VANET. VANET is aimed at maintaining safety to vehicle drivers by begin autonomous communication with the nearby vehicles. Each vehicle in the ad-hoc network performs as an intelligent mobile node characterized by high mobility and formation of dynamic networks. The ad-hoc networks are decentralized dynamic networks that need efficient and secure communication requirements due to the vehicles being persistently in motion. These networks are more susceptible to various attacks like Warm Hole attacks, denial of service attacks and Black Hole Attacks. The paper is a novel attempt to examine and investigate the security features of the routing protocols in VANET, applicability of AODV (Ad hoc On Demand protocol to detect and tackle a particular category of network attacks, known as the Black Hole Attacks. A new algorithm is proposed to enhance the security mechanism of AODV protocol and to introduce a mechanism to detect Black Hole Attacks and to prevent the network from such attacks in which source node stores all route replies in a look up table. This table stores the sequences of all route reply, arranged in ascending order using PUSH and POP operations. The priority is calculated based on sequence number and discard the RREP having presumably very high destination sequence number. The result show that proposed algorithm for detection and prevention of Black Hole Attack increases security in Intelligent Transportation System (ITS and reduces the effect of malicious node in the VANET. NCTUNs simulator is used in this research work.

  5. Application of Cellular Automata to Detection of Malicious Network Packets

    Science.gov (United States)

    Brown, Robert L.

    2014-01-01

    A problem in computer security is identification of attack signatures in network packets. An attack signature is a pattern of bits that characterizes a particular attack. Because there are many kinds of attacks, there are potentially many attack signatures. Furthermore, attackers may seek to avoid detection by altering the attack mechanism so that…

  6. River network and watershed morphology analysis with potential implications towards basin classification

    Science.gov (United States)

    Bugaets, Andrey; Gartsman, Boris; Bugaets, Nadezhda

    2013-04-01

    Generally, the investigation of river network composition and watersheds morphology (fluvial geomorphology), constituting one of the key patterns of land surface, is a fundamental question of Earth Sciences. Recent ideas in this research field are the equilibrium and optimal, in the sense of minimum energy expenditure, river network evolution under constant or slowly varying conditions (Rodriguez-Iturbe, Rinaldo, 1997). It follows to such network behavior as self-similarity, self-affinity and self-organization. That is to say, under relatively stable conditions the river systems tend to some "good composed" form and vice-versa. Lately appearing global free available detailed DEM covers involve new possibilities in this research field. We develop new methodology and program package for river network structure and watershed morphology detailed analysis on the base of ArcMap tools. Different characteristics of river network (e.g. ordering, coefficients of Horton's laws, Shannon entropy, fractal dimension) and basin morphology (e.g. diagrams of average elevation, slope, width and energy index against distance to outlet along streams) could be calculated to find a good indicators of intensity and non-equilibrium of watershed evolution. Watersheds are non-conservative systems in which energy is dissipated by transporting water and sediment in geomorphic adjustment of the slopes and channels. The problem of estimating the amount of energy expenditure associated with overcoming surface and system resistance is extremely complicated to solve. A simplification on a river network scale is to consider energy expenditure to be primarily associated with friction of the fluid. We propose a new technique to analyze the catchment landforms based on so-called "energy function" that is a distribution of total energy index against distance from outlet. As potential energy of water on the hillslopes is transformed into kinetic energy of the flowing fluid-sediment mixture in the runoff

  7. Potential of silicon nanowires structures as nanoscale piezoresistors in mechanical sensors

    International Nuclear Information System (INIS)

    Messina, M; Njuguna, J

    2012-01-01

    This paper presents the design of a single square millimeter 3-axial accelerometer for bio-mechanics measurements that exploit the potential of silicon nanowires structures as nanoscale piezoresistors. The main requirements of this application are miniaturization and high measurement accuracy. Nanowires as nanoscale piezoresistive devices have been chosen as sensing element, due to their high sensitivity and miniaturization achievable. By exploiting the electro-mechanical features of nanowires as nanoscale piezoresistors, the nominal sensor sensitivity is overall boosted by more than 30 times. This approach allows significant higher accuracy and resolution with smaller sensing element in comparison with conventional devices without the need of signal amplification.

  8. Potential Anti-Cancer Activities and Mechanisms of Costunolide and Dehydrocostuslactone

    Directory of Open Access Journals (Sweden)

    Xuejing Lin

    2015-05-01

    Full Text Available Costunolide (CE and dehydrocostuslactone (DE are derived from many species of medicinal plants, such as Saussurea lappa Decne and Laurus nobilis L. They have been reported for their wide spectrum of biological effects, including anti-inflammatory, anticancer, antiviral, antimicrobial, antifungal, antioxidant, antidiabetic, antiulcer, and anthelmintic activities. In recent years, they have caused extensive interest in researchers due to their potential anti-cancer activities for various types of cancer, and their anti-cancer mechanisms, including causing cell cycle arrest, inducing apoptosis and differentiation, promoting the aggregation of microtubule protein, inhibiting the activity of telomerase, inhibiting metastasis and invasion, reversing multidrug resistance, restraining angiogenesis has been studied. This review will summarize anti-cancer activities and associated molecular mechanisms of these two compounds for the purpose of promoting their research and application.

  9. The Potential Role of Cache Mechanism for Complicated Design Optimization

    International Nuclear Information System (INIS)

    Noriyasu, Hirokawa; Fujita, Kikuo

    2002-01-01

    This paper discusses the potential role of cache mechanism for complicated design optimization While design optimization is an application of mathematical programming techniques to engineering design problems over numerical computation, its progress has been coevolutionary. The trend in such progress indicates that more complicated applications become the next target of design optimization beyond growth of computational resources. As the progress in the past two decades had required response surface techniques, decomposition techniques, etc., any new framework must be introduced for the future of design optimization methods. This paper proposes a possibility of what we call cache mechanism for mediating the coming challenge and briefly demonstrates some promises in the idea of Voronoi diagram based cumulative approximation as an example of its implementation, development of strict robust design, extension of design optimization for product variety

  10. Genetic algorithm based on optimization of neural network structure for fault diagnosis of the clutch retainer mechanism of MF 285 tractor

    Directory of Open Access Journals (Sweden)

    S. F Mousavi

    2016-09-01

    Full Text Available Introduction The diagnosis of agricultural machinery faults must be performed at an opportune time, in order to fulfill the agricultural operations in a timely manner and to optimize the accuracy and the integrity of a system, proper monitoring and fault diagnosis of the rotating parts is required. With development of fault diagnosis methods of rotating equipment, especially bearing failure, the security, performance and availability of machines has been increasing. In general, fault detection is conducted through a specific procedure which starts with data acquisition and continues with features extraction, and subsequently failure of the machine would be detected. Several practical methods have been introduced for fault detection in rotating parts of machineries. The review of the literature shows that both Artificial Neural Networks (ANN and Support Vector Machines (SVM have been used for this purpose. However, the results show that SVM is more effective than Artificial Neural Networks in fault detection of such machineries. In some smart detection systems, incorporating an optimized method such as Genetic Algorithm in the Neural Network model, could improve the fault detection procedure. Consequently, the fault detection performance of neural networks may also be improved by combining with the Genetic Algorithm and hence will be comparable with the performance of the Support Vector Machine. In this study, the so called Genetic Algorithm (GA method was used to optimize the structure of the Artificial Neural Networks (ANN for fault detection of the clutch retainer mechanism of Massey Ferguson 285 tractor. Materials and Methods The test rig consists of some electro mechanical parts including the clutch retainer mechanism of Massey Ferguson 285 tractor, a supporting shaft, a single-phase electric motor, a loading mechanism to model the load of the tractor clutch and the corresponding power train gears. The data acquisition section consists of a

  11. Exploring the Therapeutic Mechanism of Desmodium styracifolium on Oxalate Crystal-Induced Kidney Injuries Using Comprehensive Approaches Based on Proteomics and Network Pharmacology

    Directory of Open Access Journals (Sweden)

    Jiebin Hou

    2018-06-01

    Full Text Available Purpose: As a Chinese medicinal herb, Desmodium styracifolium (Osb. Merr (DS has been applied clinically to alleviate crystal-induced kidney injuries, but its effective components and their specific mechanisms still need further exploration. This research first combined the methods of network pharmacology and proteomics to explore the therapeutic protein targets of DS on oxalate crystal-induced kidney injuries to provide a reference for relevant clinical use.Methods: Oxalate-induced kidney injury mouse, rat, and HK-2 cell models were established. Proteins differentially expressed between the oxalate and control groups were respectively screened using iTRAQ combined with MALDI-TOF-MS. The common differential proteins of the three models were further analyzed by molecular docking with DS compounds to acquire differential targets. The inverse docking targets of DS were predicted through the platform of PharmMapper. The protein–protein interaction (PPI relationship between the inverse docking targets and the differential proteins was established by STRING. Potential targets were further validated by western blot based on a mouse model with DS treatment. The effects of constituent compounds, including luteolin, apigenin, and genistein, were investigated based on an oxalate-stimulated HK-2 cell model.Results: Thirty-six common differentially expressed proteins were identified by proteomic analysis. According to previous research, the 3D structures of 15 major constituents of DS were acquired. Nineteen differential targets, including cathepsin D (CTSD, were found using molecular docking, and the component-differential target network was established. Inverse-docking targets including p38 MAPK and CDK-2 were found, and the network of component-reverse docking target was established. Through PPI analysis, 17 inverse-docking targets were linked to differential proteins. The combined network of component-inverse docking target-differential proteins was

  12. Effect of socio-economic status, family smoking and mental health through social network on the substance use potential in adolescents: a mediation analysis.

    Science.gov (United States)

    Sajjadi, H; Jorjoran Shushtari, Z; Mahboubi, S; Rafiey, H; Salimi, Y

    2018-04-01

    Understanding pathways that influence substance use potential (SUP) can help with effective substance use prevention interventions among adolescents. The aim of the present study is to contribute to a better understanding of the SUP of adolescents by examining the mediating role of social network quality in the SUP of Iranian adolescents. A cross-sectional study. Structural equation modeling was conducted to assess the hypothesized model that social network quality would mediate the association of family socio-economic status, a mental health disorder, and family smoking with addiction potential. The model shows a good fit to the data. Social network quality mediated the effect of family smoking on the SUP for boys. A mental health disorder had a positive significant direct effect on addiction potential for both girls and boys. Social network quality mediates the effect of family smoking on boys' addiction potential in the context of Iran. Educational programs based on local societal ways and cultural norms are recommended to change tobacco smoking behavior among family members. In addition, to prevent subsequent substance use among adolescents, more effort is needed to improve their mental health. Copyright © 2018 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

  13. Study Under AC Stimulation on Excitement Properties of Weighted Small-World Biological Neural Networks with Side-Restrain Mechanism

    International Nuclear Information System (INIS)

    Yuan Wujie; Luo Xiaoshu; Jiang Pinqun

    2007-01-01

    In this paper, we propose a new model of weighted small-world biological neural networks based on biophysical Hodgkin-Huxley neurons with side-restrain mechanism. Then we study excitement properties of the model under alternating current (AC) stimulation. The study shows that the excitement properties in the networks are preferably consistent with the behavior properties of a brain nervous system under different AC stimuli, such as refractory period and the brain neural excitement response induced by different intensities of noise and coupling. The results of the study have reference worthiness for the brain nerve electrophysiology and epistemological science.

  14. Una red neuronal binaria para la identificación de mecanismos isomorfos. // A binary Neural network for identifying isomorphic mechanisms.

    Directory of Open Access Journals (Sweden)

    G. Galán Marín

    2002-05-01

    detecting kinematic chain isomorphism havebeen not found to be an efficient solution of the kinematic chain isomorphism problem, classified as NP-hard.This has motivated to attempt a new direction of approach based on neural networks. In this paper we presenta new binary neural network designed for solving this problem. The model is based on appropriate dynamicsfor a binary network in order to always generate fast and correct solutions. Simulation runs for the selectedmechanisms show that our network provides fast and good quality solutions and performs better than thetraditional continuous Hopfield network, because of its easier implementation and smaller computation time.Keywords: isomorphic mechanisms, synthesis of mechanisms, graph isomorphism, binary neuralnetwork, Hopfield networks.

  15. Principals' Conceptions of Instructional Leadership and Their Informal Social Networks: An Exploration of the Mechanisms of the Mesolevel

    Science.gov (United States)

    Rigby, Jessica G.

    2016-01-01

    First-year principals encounter multiple messages about what it means to be instructional leaders; this may matter for how they enact instructional leadership. This cross-case qualitative study uses a qualitative approach of social network analysis to uncover the mechanisms through which first-year principals encountered particular beliefs about…

  16. Do governance choices matter in health care networks?: an exploratory configuration study of health care networks

    Science.gov (United States)

    2013-01-01

    Background Health care networks are widely used and accepted as an organizational form that enables integrated care as well as dealing with complex matters in health care. However, research on the governance of health care networks lags behind. The research aim of our study is to explore the type and importance of governance structure and governance mechanisms for network effectiveness. Methods The study has a multiple case study design and covers 22 health care networks. Using a configuration view, combinations of network governance and other network characteristics were studied on the level of the network. Based on interview and questionnaire data, network characteristics were identified and patterns in the data looked for. Results Neither a dominant (or optimal) governance structure or mechanism nor a perfect fit among governance and other characteristics were revealed, but a number of characteristics that need further study might be related to effective networks such as the role of governmental agencies, legitimacy, and relational, hierarchical, and contractual governance mechanisms as complementary factors. Conclusions Although the results emphasize the situational character of network governance and effectiveness, they give practitioners in the health care sector indications of which factors might be more or less crucial for network effectiveness. PMID:23800334

  17. Introducing serendipity in a social network model of knowledge diffusion

    International Nuclear Information System (INIS)

    Cremonini, Marco

    2016-01-01

    Highlights: • Serendipity as a control mechanism for knowledge diffusion in social network. • Local communication enhanced in the periphery of a network. • Prevalence of hub nodes in the network core mitigated. • Potential disruptive effect on network formation of uncontrolled serendipity. - Abstract: In this paper, we study serendipity as a possible strategy to control the behavior of an agent-based network model of knowledge diffusion. The idea of considering serendipity in a strategic way has been first explored in Network Learning and Information Seeking studies. After presenting the major contributions of serendipity studies to digital environments, we discuss the extension to our model: Agents are enriched with random topics for establishing new communication according to different strategies. The results show how important network properties could be influenced, like reducing the prevalence of hubs in the network’s core and increasing local communication in the periphery, similar to the effects of more traditional self-organization methods. Therefore, from this initial study, when serendipity is opportunistically directed, it appears to behave as an effective and applicable approach to social network control.

  18. Plastic modulation of PTSD resting-state networks by EEG neurofeedback

    Science.gov (United States)

    Kluetsch, Rosemarie C.; Ros, Tomas; Théberge, Jean; Frewen, Paul A.; Calhoun, Vince D.; Schmahl, Christian; Jetly, Rakesh; Lanius, Ruth A.

    2015-01-01

    Objective Electroencephalographic (EEG) neurofeedback training has been shown to produce plastic modulations in salience network and default mode network functional connectivity in healthy individuals. In this study, we investigated whether a single session of neurofeedback training aimed at the voluntary reduction of alpha rhythm (8–12 Hz) amplitude would be related to differences in EEG network oscillations, functional MRI (fMRI) connectivity, and subjective measures of state anxiety and arousal in a group of individuals with PTSD. Method 21 individuals with PTSD related to childhood abuse underwent 30 minutes of EEG neurofeedback training preceded and followed by a resting-state fMRI scan. Results Alpha desynchronizing neurofeedback was associated with decreased alpha amplitude during training, followed by a significant increase (‘rebound’) in resting-state alpha synchronization. This rebound was linked to increased calmness, greater salience network connectivity with the right insula, and enhanced default mode network connectivity with bilateral posterior cingulate, right middle frontal gyrus, and left medial prefrontal cortex. Conclusion Our study represents a first step in elucidating the potential neurobehavioral mechanisms mediating the effects of neurofeedback treatment on regulatory systems in PTSD. Moreover, it documents for the first time a spontaneous EEG ‘rebound’ after neurofeedback, pointing to homeostatic/compensatory mechanisms operating in the brain. PMID:24266644

  19. Chemical structure, network topology, and porosity effects on the mechanical properties of Zeolitic Imidazolate Frameworks

    OpenAIRE

    Tan, J. C.; Bennett, T. D.; Cheetham, A. K.

    2010-01-01

    The mechanical properties of seven zeolitic imidazolate frameworks (ZIFs) based on five unique network topologies have been systematically characterized by single-crystal nanoindentation studies. We demonstrate that the elastic properties of ZIF crystal structures are strongly correlated to the framework density and the underlying porosity. For the systems considered here, the elastic modulus was found to range from 3 to 10 GPa, whereas the hardness property lies between 300 MPa and 1.1 GPa. ...

  20. Scalable, ultra-resistant structural colors based on network metamaterials

    KAUST Repository

    Galinski, Henning

    2017-05-05

    Structural colors have drawn wide attention for their potential as a future printing technology for various applications, ranging from biomimetic tissues to adaptive camouflage materials. However, an efficient approach to realize robust colors with a scalable fabrication technique is still lacking, hampering the realization of practical applications with this platform. Here, we develop a new approach based on large-scale network metamaterials that combine dealloyed subwavelength structures at the nanoscale with lossless, ultra-thin dielectric coatings. By using theory and experiments, we show how subwavelength dielectric coatings control a mechanism of resonant light coupling with epsilon-near-zero regions generated in the metallic network, generating the formation of saturated structural colors that cover a wide portion of the spectrum. Ellipsometry measurements support the efficient observation of these colors, even at angles of 70°. The network-like architecture of these nanomaterials allows for high mechanical resistance, which is quantified in a series of nano-scratch tests. With such remarkable properties, these metastructures represent a robust design technology for real-world, large-scale commercial applications.

  1. Functional MRI studies of the neural mechanisms of human brain attentional networks

    International Nuclear Information System (INIS)

    Hao Jing; Li Kuncheng; Chen Qi; Wang Yan; Peng Xiaozhe; Zhou Xiaolin

    2005-01-01

    Objective: To identify the neural mechanisms of the anterior attention network (AAN) and posterior attention network (PAN) , investigate the possible interaction between them with event-related functional MRI(ER-fMRI). Methods: Eight right-handed healthy volunteers participated in the experiment designed with inhibition of return in visual orienting and Stroop color-word interference effect. The fMRI data were collected on Siemens 1.5 T Sonata MRI systems and analyzed by AFNI to generate the activation map. Results: The data sets from 6 of 8 subjects were used in the study. The functional localizations of the Stroop and IOR, which manifest the function of the AAN and PAN respectively, were consistent with previous imaging researches. On cued locations, left inferior parietal lobule (IPL), area MT/V5, right dorsolateral prefrontal cortex (DLPFC) and left anterior cingulated cortex (ACC) were significantly activated. On uncued locations, right superior parietal lobule (SPL) and bilateral area MT/V5 were significantly activated. Conclusion: The AAN exerts control over the PAN, while its function can be in turn modulated by the PAN. There are interaction between the AAN and PAN. In addition, it is also proved that ER-fMRI is a feasible method to revise preexisting cognitive model and theory. (authors)

  2. Dielectric elastomers, with very high dielectric permittivity, based on silicone and ionic interpenetrating networks

    DEFF Research Database (Denmark)

    Yu, Liyun; Madsen, Frederikke Bahrt; Hvilsted, Søren

    2015-01-01

    permittivity and the Young's modulus of the elastomer. One system that potentially achieves this involves interpenetrating polymer networks (IPNs), based on commercial silicone elastomers and ionic networks from amino- and carboxylic acid-functional silicones. The applicability of these materials as DEs...... are obtained while dielectric breakdown strength and Young's modulus are not compromised. These good overall properties stem from the softening effect and very high permittivity of ionic networks – as high as ε′ = 7500 at 0.1 Hz – while the silicone elastomer part of the IPN provides mechanical integrity...

  3. On the completeness of the natural modes for quantum mechanical potential scattering

    NARCIS (Netherlands)

    Hoenders, B.J.

    1979-01-01

    The set of natural modes, associated with quantum mechanical scattering from a central potential of finite-range is shown to be complete. The natural modes satisfy a non-Hermitian homogeneous integral equation, or alternatively, are solutions of the time independent Schrödinger equation subject to a

  4. Evaluating the Impact of China’s Rail Network Expansions on Local Accessibility: A Market Potential Approach

    Directory of Open Access Journals (Sweden)

    Wenjie Wu

    2016-05-01

    Full Text Available This paper uses a market potential approach to examine the evolution of the rail transport network of China and its spatial distributional impacts on local accessibility, with a particular focus on high-speed rail improvements. Accessibility is measured by using a “market potential” function that was derived from the general equilibrium model of the economic geography literature, and is empirically calculated based on Geographical Information System (GIS techniques. A key finding, albeit from a highly stylized model, is that rail improvements may help raise territorial polarizing patterns across counties. The results point to the profound implications of railroad network expansion on the accessibility dynamics in periphery regions relative to core regions.

  5. Operator algebras for general one-dimensional quantum mechanical potentials with discrete spectrum

    International Nuclear Information System (INIS)

    Wuensche, Alfred

    2002-01-01

    We define general lowering and raising operators of the eigenstates for one-dimensional quantum mechanical potential problems leading to discrete energy spectra and investigate their associative algebra. The Hamilton operator is quadratic in these lowering and raising operators and corresponding representations of operators for action and angle are found. The normally ordered representation of general operators using combinatorial elements such as partitions is derived. The introduction of generalized coherent states is discussed. Linear laws for the spacing of the energy eigenvalues lead to the Heisenberg-Weyl group and general quadratic laws of level spacing to unitary irreducible representations of the Lie group SU(1, 1) that is considered in detail together with a limiting transition from this group to the Heisenberg-Weyl group. The relation of the approach to quantum deformations is discussed. In two appendices, the classical and quantum mechanical treatment of the squared tangent potential is presented as a special case of a system with quadratic level spacing

  6. Service Demand Discovery Mechanism for Mobile Social Networks.

    Science.gov (United States)

    Wu, Dapeng; Yan, Junjie; Wang, Honggang; Wang, Ruyan

    2016-11-23

    In the last few years, the service demand for wireless data over mobile networks has continually been soaring at a rapid pace. Thereinto, in Mobile Social Networks (MSNs), users can discover adjacent users for establishing temporary local connection and thus sharing already downloaded contents with each other to offload the service demand. Due to the partitioned topology, intermittent connection and social feature in such a network, the service demand discovery is challenging. In particular, the service demand discovery is exploited to identify the best relay user through the service registration, service selection and service activation. In order to maximize the utilization of limited network resources, a hybrid service demand discovery architecture, such as a Virtual Dictionary User (VDU) is proposed in this paper. Based on the historical data of movement, users can discover their relationships with others. Subsequently, according to the users activity, VDU is selected to facilitate the service registration procedure. Further, the service information outside of a home community can be obtained through the Global Active User (GAU) to support the service selection. To provide the Quality of Service (QoS), the Service Providing User (SPU) is chosen among multiple candidates. Numerical results show that, when compared with other classical service algorithms, the proposed scheme can improve the successful service demand discovery ratio by 25% under reduced overheads.

  7. Permutation invariant polynomial neural network approach to fitting potential energy surfaces. II. Four-atom systems

    Energy Technology Data Exchange (ETDEWEB)

    Li, Jun; Jiang, Bin; Guo, Hua, E-mail: hguo@unm.edu [Department of Chemistry and Chemical Biology, University of New Mexico, Albuquerque, New Mexico 87131 (United States)

    2013-11-28

    A rigorous, general, and simple method to fit global and permutation invariant potential energy surfaces (PESs) using neural networks (NNs) is discussed. This so-called permutation invariant polynomial neural network (PIP-NN) method imposes permutation symmetry by using in its input a set of symmetry functions based on PIPs. For systems with more than three atoms, it is shown that the number of symmetry functions in the input vector needs to be larger than the number of internal coordinates in order to include both the primary and secondary invariant polynomials. This PIP-NN method is successfully demonstrated in three atom-triatomic reactive systems, resulting in full-dimensional global PESs with average errors on the order of meV. These PESs are used in full-dimensional quantum dynamical calculations.

  8. Quantifying the dynamics of coupled networks of switches and oscillators.

    Directory of Open Access Journals (Sweden)

    Matthew R Francis

    Full Text Available Complex network dynamics have been analyzed with models of systems of coupled switches or systems of coupled oscillators. However, many complex systems are composed of components with diverse dynamics whose interactions drive the system's evolution. We, therefore, introduce a new modeling framework that describes the dynamics of networks composed of both oscillators and switches. Both oscillator synchronization and switch stability are preserved in these heterogeneous, coupled networks. Furthermore, this model recapitulates the qualitative dynamics for the yeast cell cycle consistent with the hypothesized dynamics resulting from decomposition of the regulatory network into dynamic motifs. Introducing feedback into the cell-cycle network induces qualitative dynamics analogous to limitless replicative potential that is a hallmark of cancer. As a result, the proposed model of switch and oscillator coupling provides the ability to incorporate mechanisms that underlie the synchronized stimulus response ubiquitous in biochemical systems.

  9. Memory replay in balanced recurrent networks.

    Directory of Open Access Journals (Sweden)

    Nikolay Chenkov

    2017-01-01

    Full Text Available Complex patterns of neural activity appear during up-states in the neocortex and sharp waves in the hippocampus, including sequences that resemble those during prior behavioral experience. The mechanisms underlying this replay are not well understood. How can small synaptic footprints engraved by experience control large-scale network activity during memory retrieval and consolidation? We hypothesize that sparse and weak synaptic connectivity between Hebbian assemblies are boosted by pre-existing recurrent connectivity within them. To investigate this idea, we connect sequences of assemblies in randomly connected spiking neuronal networks with a balance of excitation and inhibition. Simulations and analytical calculations show that recurrent connections within assemblies allow for a fast amplification of signals that indeed reduces the required number of inter-assembly connections. Replay can be evoked by small sensory-like cues or emerge spontaneously by activity fluctuations. Global-potentially neuromodulatory-alterations of neuronal excitability can switch between network states that favor retrieval and consolidation.

  10. Intermittent synchronization in a network of bursting neurons

    Science.gov (United States)

    Park, Choongseok; Rubchinsky, Leonid L.

    2011-09-01

    Synchronized oscillations in networks of inhibitory and excitatory coupled bursting neurons are common in a variety of neural systems from central pattern generators to human brain circuits. One example of the latter is the subcortical network of the basal ganglia, formed by excitatory and inhibitory bursters of the subthalamic nucleus and globus pallidus, involved in motor control and affected in Parkinson's disease. Recent experiments have demonstrated the intermittent nature of the phase-locking of neural activity in this network. Here, we explore one potential mechanism to explain the intermittent phase-locking in a network. We simplify the network to obtain a model of two inhibitory coupled elements and explore its dynamics. We used geometric analysis and singular perturbation methods for dynamical systems to reduce the full model to a simpler set of equations. Mathematical analysis was completed using three slow variables with two different time scales. Intermittently, synchronous oscillations are generated by overlapped spiking which crucially depends on the geometry of the slow phase plane and the interplay between slow variables as well as the strength of synapses. Two slow variables are responsible for the generation of activity patterns with overlapped spiking, and the other slower variable enhances the robustness of an irregular and intermittent activity pattern. While the analyzed network and the explored mechanism of intermittent synchrony appear to be quite generic, the results of this analysis can be used to trace particular values of biophysical parameters (synaptic strength and parameters of calcium dynamics), which are known to be impacted in Parkinson's disease.

  11. Molecular dynamics study on the evolution of interfacial dislocation network and mechanical properties of Ni-based single crystal superalloys

    Science.gov (United States)

    Li, Nan-Lin; Wu, Wen-Ping; Nie, Kai

    2018-05-01

    The evolution of misfit dislocation network at γ /γ‧ phase interface and tensile mechanical properties of Ni-based single crystal superalloys at various temperatures and strain rates are studied by using molecular dynamics (MD) simulations. From the simulations, it is found that with the increase of loading, the dislocation network effectively inhibits dislocations emitted in the γ matrix cutting into the γ‧ phase and absorbs the matrix dislocations to strengthen itself which increases the stability of structure. Under the influence of the temperature, the initial mosaic structure of dislocation network gradually becomes irregular, and the initial misfit stress and the elastic modulus slowly decline as temperature increasing. On the other hand, with the increase of the strain rate, it almost has no effect on the elastic modulus and the way of evolution of dislocation network, but contributes to the increases of the yield stress and tensile strength. Moreover, tension-compression asymmetry of Ni-based single crystal superalloys is also presented based on MD simulations.

  12. How Do Corporate Governance Mechanisms Affect A Firm’s Potential For Bankruptcy?

    Directory of Open Access Journals (Sweden)

    Rhesa Theodorus Hanani

    2015-03-01

    Full Text Available The purpose of this thesis is to understand the effects of corporate governance mechanisms on the potential for bankruptcy. This study is done by utilizing the linear regression fixed effect vector decomposition model on 30 listed firms from the consumer goods sector of Indonesia Stock Exchange during the 2010-2012 periods. The results of the study indicate that: the board of commissioners’ independence and size of the commissioners’ board pose a significant positive effect on the potential for bankruptcy; the presence of an audit committee and the presence of a nomination and remuneration committee pose a significant negative effect and institutional ownership and managerial ownership do not significantly affect the potential for bankruptcy.

  13. Construction of an interatomic potential for zinc oxide surfaces by high-dimensional neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Artrith, Nongnuch; Morawietz, Tobias; Behler, Joerg [Lehrstuhl fuer Theoretische Chemie, Ruhr-Universitaet Bochum, D-44780 Bochum (Germany)

    2011-07-01

    Zinc oxide (ZnO) is a technologically important material with many applications, e.g. in heterogeneous catalysis. For theoretical studies of the structural properties of ZnO surfaces, defects, and crystal structures it is necessary to simulate large systems over long time-scales with sufficient accuracy. Often, the required system size is not accessible by computationally rather demanding density-functional theory (DFT) calculations. Recently, artificial Neural Networks (NN) trained to first principles data have shown to provide accurate potential-energy surfaces (PESs) for condensed systems. We present the construction and analysis of a NN PES for ZnO. The structural and energetic properties of bulk ZnO and ZnO surfaces are investigated using this potential and compared to DFT calculations.

  14. Spin wave absorber generated by artificial surface anisotropy for spin wave device network

    Directory of Open Access Journals (Sweden)

    Naoki Kanazawa

    2016-09-01

    Full Text Available Spin waves (SWs have the potential to reduce the electric energy loss in signal processing networks. The SWs called magnetostatic forward volume waves (MSFVWs are advantageous for networking due to their isotropic dispersion in the plane of a device. To control the MSFVW flow in a processing network based on yttrium iron garnet, we developed a SW absorber using artificial structures. The mechanical surface polishing method presented in this work can well control extrinsic damping without changing the SW dispersion of the host material. Furthermore, enhancement of the ferromagnetic resonance linewidth over 3 Oe was demonstrated.

  15. Actors and networks in resource conflict resolution under climate change in rural Kenya

    Science.gov (United States)

    Ngaruiya, Grace W.; Scheffran, Jürgen

    2016-05-01

    The change from consensual decision-making arrangements into centralized hierarchical chieftaincy schemes through colonization disrupted many rural conflict resolution mechanisms in Africa. In addition, climate change impacts on land use have introduced additional socio-ecological factors that complicate rural conflict dynamics. Despite the current urgent need for conflict-sensitive adaptation, resolution efficiency of these fused rural institutions has hardly been documented. In this context, we analyse the Loitoktok network for implemented resource conflict resolution structures and identify potential actors to guide conflict-sensitive adaptation. This is based on social network data and processes that are collected using the saturation sampling technique to analyse mechanisms of brokerage. We find that there are three different forms of fused conflict resolution arrangements that integrate traditional institutions and private investors in the community. To effectively implement conflict-sensitive adaptation, we recommend the extension officers, the council of elders, local chiefs and private investors as potential conduits of knowledge in rural areas. In conclusion, efficiency of these fused conflict resolution institutions is aided by the presence of holistic resource management policies and diversification in conflict resolution actors and networks.

  16. Signaling Network Assessment of Mutations and Copy Number Variations Predict Breast Cancer Subtype-Specific Drug Targets

    Directory of Open Access Journals (Sweden)

    Naif Zaman

    2013-10-01

    Full Text Available Individual cancer cells carry a bewildering number of distinct genomic alterations (e.g., copy number variations and mutations, making it a challenge to uncover genomic-driven mechanisms governing tumorigenesis. Here, we performed exome sequencing on several breast cancer cell lines that represent two subtypes, luminal and basal. We integrated these sequencing data and functional RNAi screening data (for the identification of genes that are essential for cell proliferation and survival onto a human signaling network. Two subtype-specific networks that potentially represent core-signaling mechanisms underlying tumorigenesis were identified. Within both networks, we found that genes were differentially affected in different cell lines; i.e., in some cell lines a gene was identified through RNAi screening, whereas in others it was genomically altered. Interestingly, we found that highly connected network genes could be used to correctly classify breast tumors into subtypes on the basis of genomic alterations. Further, the networks effectively predicted subtype-specific drug targets, which were experimentally validated.

  17. Studying the mechanisms of the Somatic Marker Hypothesis in Spiking Neural Networks (SNN

    Directory of Open Access Journals (Sweden)

    Manuel GONZÁLEZ

    2013-07-01

    Full Text Available Normal 0 21 false false false EN-US JA X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Tabla normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:Cambria; mso-ascii-font-family:Cambria; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Cambria; mso-hansi-theme-font:minor-latin; mso-ansi-language:EN-US;} In this paper, a mechanism of emotional bias in decision making is studied using Spiking Neural Networks to simulate the associative and recurrent networks involved. The results obtained are along the lines of those proposed by A. Damasio as part of the Somatic Marker Hypothesis, in particular, that, in absence of emotional input, the decision making is driven by the rational input alone. Appropriate representations for the Objective and Emotional Values are also suggested, provided a spike representation (code of the information.

  18. Studying the mechanisms of the Somatic Marker Hypothesis in Spiking Neural Networks (SNN

    Directory of Open Access Journals (Sweden)

    Alejandro JIMÉNEZ-RODRÍGUEZ

    2012-09-01

    Full Text Available Normal 0 21 false false false EN-US JA X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Tabla normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:Cambria; mso-ascii-font-family:Cambria; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Cambria; mso-hansi-theme-font:minor-latin; mso-ansi-language:EN-US;} In this paper, a mechanism of emotional bias in decision making is studied using Spiking Neural Networks to simulate the associative and recurrent networks involved. The results obtained are along the lines of those proposed by A. Damasio as part of the Somatic Marker Hypothesis, in particular, that, in absence of emotional input, the decision making is driven by the rational input alone. Appropriate representations for the Objective and Emotional Values are also suggested, provided a spike representation (code of the information.

  19. An information spreading model based on online social networks

    Science.gov (United States)

    Wang, Tao; He, Juanjuan; Wang, Xiaoxia

    2018-01-01

    Online social platforms are very popular in recent years. In addition to spreading information, users could review or collect information on online social platforms. According to the information spreading rules of online social network, a new information spreading model, namely IRCSS model, is proposed in this paper. It includes sharing mechanism, reviewing mechanism, collecting mechanism and stifling mechanism. Mean-field equations are derived to describe the dynamics of the IRCSS model. Moreover, the steady states of reviewers, collectors and stiflers and the effects of parameters on the peak values of reviewers, collectors and sharers are analyzed. Finally, numerical simulations are performed on different networks. Results show that collecting mechanism and reviewing mechanism, as well as the connectivity of the network, make information travel wider and faster, and compared to WS network and ER network, the speed of reviewing, sharing and collecting information is fastest on BA network.

  20. Canada's potential role in the Clean Development Mechanism

    International Nuclear Information System (INIS)

    Pape-Salmon, A.

    2000-01-01

    The role that Canada might play in the Kyoto Protocol's Clean Development Mechanism (CDM) is discussed. The CDM prescribes the way in which industrialized countries could create emission reduction credits for greenhouse gas emission reduction projects in developing countries which, in turn they could use to meet their own commitments and possibly reduce their cost of compliance with the Kyoto Protocol. While Canada does not see itself as a CDM project investor, it strongly supports private sector involvement in the CDM and believes that it has a role to play in assisting CDM investments by the Canadian private sector by facilitating desirable outcomes via international negotiations on the rules and modalities for the CDM which would minimize transaction costs; give prominence to aspects that Canada recognizes as necessary precursors to mobilizing private sector involvement in CDM activities; maximize the flexibility for use of the CDM; allow for conversion of credits between different Kyoto Mechanisms; allow for the certification of emissions sequestration from sinks; and maximize the environmental and sustainable development benefits of CDM projects. Canada also supports, along with the other members of the 'Umbrella group', the fewest possible restrictions and significant autonomy to the private sector to implement a variety of project activities in developing countries. This report provides a detailed examination of the Canadian government's views on the CDM, Canada's participation in international emission reduction projects, the factors that drive Canadian demand for greenhouse gas emission reduction offsets and the potential demand for CDM offsets, Canada's greenhouse gas emission inventory and projections, the approach of Canadian corporate investors in the CDM and Canadian technology and expertise in greenhouse gas emission reductions. Various appendices to the report contain further details on a number of cooperation agreements between Canada and other