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Sample records for network motifs control

  1. Topological generalizations of network motifs

    Science.gov (United States)

    Kashtan, N.; Itzkovitz, S.; Milo, R.; Alon, U.

    2004-09-01

    Biological and technological networks contain patterns, termed network motifs, which occur far more often than in randomized networks. Network motifs were suggested to be elementary building blocks that carry out key functions in the network. It is of interest to understand how network motifs combine to form larger structures. To address this, we present a systematic approach to define “motif generalizations”: families of motifs of different sizes that share a common architectural theme. To define motif generalizations, we first define “roles” in a subgraph according to structural equivalence. For example, the feedforward loop triad—a motif in transcription, neuronal, and some electronic networks—has three roles: an input node, an output node, and an internal node. The roles are used to define possible generalizations of the motif. The feedforward loop can have three simple generalizations, based on replicating each of the three roles and their connections. We present algorithms for efficiently detecting motif generalizations. We find that the transcription networks of bacteria and yeast display only one of the three generalizations, the multi-output feedforward generalization. In contrast, the neuronal network of C. elegans mainly displays the multi-input generalization. Forward-logic electronic circuits display a multi-input, multi-output hybrid. Thus, networks which share a common motif can have very different generalizations of that motif. Using mathematical modeling, we describe the information processing functions of the different motif generalizations in transcription, neuronal, and electronic networks.

  2. Biological network motif detection and evaluation.

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    Kim, Wooyoung; Li, Min; Wang, Jianxin; Pan, Yi

    2011-01-01

    Molecular level of biological data can be constructed into system level of data as biological networks. Network motifs are defined as over-represented small connected subgraphs in networks and they have been used for many biological applications. Since network motif discovery involves computationally challenging processes, previous algorithms have focused on computational efficiency. However, we believe that the biological quality of network motifs is also very important. We define biological network motifs as biologically significant subgraphs and traditional network motifs are differentiated as structural network motifs in this paper. We develop five algorithms, namely, EDGEGO-BNM, EDGEBETWEENNESS-BNM, NMF-BNM, NMFGO-BNM and VOLTAGE-BNM, for efficient detection of biological network motifs, and introduce several evaluation measures including motifs included in complex, motifs included in functional module and GO term clustering score in this paper. Experimental results show that EDGEGO-BNM and EDGEBETWEENNESS-BNM perform better than existing algorithms and all of our algorithms are applicable to find structural network motifs as well. We provide new approaches to finding network motifs in biological networks. Our algorithms efficiently detect biological network motifs and further improve existing algorithms to find high quality structural network motifs, which would be impossible using existing algorithms. The performances of the algorithms are compared based on our new evaluation measures in biological contexts. We believe that our work gives some guidelines of network motifs research for the biological networks.

  3. Biological network motif detection and evaluation

    Directory of Open Access Journals (Sweden)

    Kim Wooyoung

    2011-12-01

    Full Text Available Abstract Background Molecular level of biological data can be constructed into system level of data as biological networks. Network motifs are defined as over-represented small connected subgraphs in networks and they have been used for many biological applications. Since network motif discovery involves computationally challenging processes, previous algorithms have focused on computational efficiency. However, we believe that the biological quality of network motifs is also very important. Results We define biological network motifs as biologically significant subgraphs and traditional network motifs are differentiated as structural network motifs in this paper. We develop five algorithms, namely, EDGEGO-BNM, EDGEBETWEENNESS-BNM, NMF-BNM, NMFGO-BNM and VOLTAGE-BNM, for efficient detection of biological network motifs, and introduce several evaluation measures including motifs included in complex, motifs included in functional module and GO term clustering score in this paper. Experimental results show that EDGEGO-BNM and EDGEBETWEENNESS-BNM perform better than existing algorithms and all of our algorithms are applicable to find structural network motifs as well. Conclusion We provide new approaches to finding network motifs in biological networks. Our algorithms efficiently detect biological network motifs and further improve existing algorithms to find high quality structural network motifs, which would be impossible using existing algorithms. The performances of the algorithms are compared based on our new evaluation measures in biological contexts. We believe that our work gives some guidelines of network motifs research for the biological networks.

  4. Polyrhythmic synchronization in bursting networking motifs.

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    Shilnikov, Andrey; Gordon, René; Belykh, Igor

    2008-09-01

    We study the emergence of polyrhythmic dynamics of motifs which are the building block for small inhibitory-excitatory networks, such as central pattern generators controlling various locomotive behaviors of animals. We discover that the pacemaker determining the specific rhythm of such a network composed of realistic Hodgkin-Huxley-type neurons is identified through the order parameter, which is the ratio of the neurons' burst durations or of duty cycles. We analyze different configurations of the motifs and describe the universal mechanisms for synergetics of the bursting patterns. We discuss also the multistability of inhibitory networks that results in polyrhythmicity of its emergent synchronous behaviors. (c) 2008 American Institute of Physics.

  5. Fitness for synchronization of network motifs

    DEFF Research Database (Denmark)

    Vega, Y.M.; Vázquez-Prada, M.; Pacheco, A.F.

    2004-01-01

    We study the synchronization of Kuramoto's oscillators in small parts of networks known as motifs. We first report on the system dynamics for the case of a scale-free network and show the existence of a non-trivial critical point. We compute the probability that network motifs synchronize, and fi...... that the fitness for synchronization correlates well with motifs interconnectedness and structural complexity. Possible implications for present debates about network evolution in biological and other systems are discussed....

  6. Identifying topological motif patterns of human brain functional networks.

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    Wei, Yongbin; Liao, Xuhong; Yan, Chaogan; He, Yong; Xia, Mingrui

    2017-05-01

    Recent imaging connectome studies demonstrated that the human functional brain network follows an efficient small-world topology with cohesive functional modules and highly connected hubs. However, the functional motif patterns that represent the underlying information flow remain largely unknown. Here, we investigated motif patterns within directed human functional brain networks, which were derived from resting-state functional magnetic resonance imaging data with controlled confounding hemodynamic latencies. We found several significantly recurring motifs within the network, including the two-node reciprocal motif and five classes of three-node motifs. These recurring motifs were distributed in distinct patterns to support intra- and inter-module functional connectivity, which also promoted integration and segregation in network organization. Moreover, the significant participation of several functional hubs in the recurring motifs exhibited their critical role in global integration. Collectively, our findings highlight the basic architecture governing brain network organization and provide insight into the information flow mechanism underlying intrinsic brain activities. Hum Brain Mapp 38:2734-2750, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  7. Discovering large network motifs from a complex biological network

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    Terada, Aika; Sese, Jun

    2009-12-01

    Graph structures representing relationships between entries have been studied in statistical analysis, and the results of these studies have been applied to biological networks, whose nodes and edges represent proteins and the relationships between them, respectively. Most of the studies have focused on only graph structures such as scale-free properties and cliques, but the relationships between nodes are also important features since most of the proteins perform their functions by connecting to other proteins. In order to determine such relationships, the problem of network motif discovery has been addressed; network motifs are frequently appearing graph structures in a given graph. However, the methods for network motif discovery are highly restrictive for the application to biological network because they can only be used to find small network motifs or they do not consider noise and uncertainty in observations. In this study, we introduce a new index to measure network motifs called AR index and develop a novel algorithm called ARIANA for finding large motifs even when the network has noise. Experiments using a synthetic network verify that our method can find better network motifs than an existing algorithm. By applying ARIANA to a real complex biological network, we find network motifs associated with regulations of start time of cell functions and generation of cell energies and discover that the cell cycle proteins can be categorized into two different groups.

  8. Modeling gene regulatory network motifs using Statecharts.

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    Fioravanti, Fabio; Helmer-Citterich, Manuela; Nardelli, Enrico

    2012-03-28

    Gene regulatory networks are widely used by biologists to describe the interactions among genes, proteins and other components at the intra-cellular level. Recently, a great effort has been devoted to give gene regulatory networks a formal semantics based on existing computational frameworks.For this purpose, we consider Statecharts, which are a modular, hierarchical and executable formal model widely used to represent software systems. We use Statecharts for modeling small and recurring patterns of interactions in gene regulatory networks, called motifs. We present an improved method for modeling gene regulatory network motifs using Statecharts and we describe the successful modeling of several motifs, including those which could not be modeled or whose models could not be distinguished using the method of a previous proposal.We model motifs in an easy and intuitive way by taking advantage of the visual features of Statecharts. Our modeling approach is able to simulate some interesting temporal properties of gene regulatory network motifs: the delay in the activation and the deactivation of the "output" gene in the coherent type-1 feedforward loop, the pulse in the incoherent type-1 feedforward loop, the bistability nature of double positive and double negative feedback loops, the oscillatory behavior of the negative feedback loop, and the "lock-in" effect of positive autoregulation. We present a Statecharts-based approach for the modeling of gene regulatory network motifs in biological systems. The basic motifs used to build more complex networks (that is, simple regulation, reciprocal regulation, feedback loop, feedforward loop, and autoregulation) can be faithfully described and their temporal dynamics can be analyzed.

  9. Computational analyses of synergism in small molecular network motifs.

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    Yili Zhang

    2014-03-01

    Full Text Available Cellular functions and responses to stimuli are controlled by complex regulatory networks that comprise a large diversity of molecular components and their interactions. However, achieving an intuitive understanding of the dynamical properties and responses to stimuli of these networks is hampered by their large scale and complexity. To address this issue, analyses of regulatory networks often focus on reduced models that depict distinct, reoccurring connectivity patterns referred to as motifs. Previous modeling studies have begun to characterize the dynamics of small motifs, and to describe ways in which variations in parameters affect their responses to stimuli. The present study investigates how variations in pairs of parameters affect responses in a series of ten common network motifs, identifying concurrent variations that act synergistically (or antagonistically to alter the responses of the motifs to stimuli. Synergism (or antagonism was quantified using degrees of nonlinear blending and additive synergism. Simulations identified concurrent variations that maximized synergism, and examined the ways in which it was affected by stimulus protocols and the architecture of a motif. Only a subset of architectures exhibited synergism following paired changes in parameters. The approach was then applied to a model describing interlocked feedback loops governing the synthesis of the CREB1 and CREB2 transcription factors. The effects of motifs on synergism for this biologically realistic model were consistent with those for the abstract models of single motifs. These results have implications for the rational design of combination drug therapies with the potential for synergistic interactions.

  10. Multilayer motif analysis of brain networks

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    Battiston, Federico; Nicosia, Vincenzo; Chavez, Mario; Latora, Vito

    2017-04-01

    In the last decade, network science has shed new light both on the structural (anatomical) and on the functional (correlations in the activity) connectivity among the different areas of the human brain. The analysis of brain networks has made possible to detect the central areas of a neural system and to identify its building blocks by looking at overabundant small subgraphs, known as motifs. However, network analysis of the brain has so far mainly focused on anatomical and functional networks as separate entities. The recently developed mathematical framework of multi-layer networks allows us to perform an analysis of the human brain where the structural and functional layers are considered together. In this work, we describe how to classify the subgraphs of a multiplex network, and we extend the motif analysis to networks with an arbitrary number of layers. We then extract multi-layer motifs in brain networks of healthy subjects by considering networks with two layers, anatomical and functional, respectively, obtained from diffusion and functional magnetic resonance imaging. Results indicate that subgraphs in which the presence of a physical connection between brain areas (links at the structural layer) coexists with a non-trivial positive correlation in their activities are statistically overabundant. Finally, we investigate the existence of a reinforcement mechanism between the two layers by looking at how the probability to find a link in one layer depends on the intensity of the connection in the other one. Showing that functional connectivity is non-trivially constrained by the underlying anatomical network, our work contributes to a better understanding of the interplay between the structure and function in the human brain.

  11. MotifNet: a web-server for network motif analysis.

    Science.gov (United States)

    Smoly, Ilan Y; Lerman, Eugene; Ziv-Ukelson, Michal; Yeger-Lotem, Esti

    2017-06-15

    Network motifs are small topological patterns that recur in a network significantly more often than expected by chance. Their identification emerged as a powerful approach for uncovering the design principles underlying complex networks. However, available tools for network motif analysis typically require download and execution of computationally intensive software on a local computer. We present MotifNet, the first open-access web-server for network motif analysis. MotifNet allows researchers to analyze integrated networks, where nodes and edges may be labeled, and to search for motifs of up to eight nodes. The output motifs are presented graphically and the user can interactively filter them by their significance, number of instances, node and edge labels, and node identities, and view their instances. MotifNet also allows the user to distinguish between motifs that are centered on specific nodes and motifs that recur in distinct parts of the network. MotifNet is freely available at http://netbio.bgu.ac.il/motifnet . The website was implemented using ReactJs and supports all major browsers. The server interface was implemented in Python with data stored on a MySQL database. estiyl@bgu.ac.il or michaluz@cs.bgu.ac.il. Supplementary data are available at Bioinformatics online.

  12. Switch-like Transitions Insulate Network Motifs to Modularize Biological Networks.

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    Atay, Oguzhan; Doncic, Andreas; Skotheim, Jan M

    2016-08-01

    Cellular decisions are made by complex networks that are difficult to analyze. Although it is common to analyze smaller sub-networks known as network motifs, it is unclear whether this is valid, because these motifs are embedded in complex larger networks. Here, we address the general question of modularity by examining the S. cerevisiae pheromone response. We demonstrate that the feedforward motif controlling the cell-cycle inhibitor Far1 is insulated from cell-cycle dynamics by the positive feedback switch that drives reentry to the cell cycle. Before cells switch on positive feedback, the feedforward motif model predicts the behavior of the larger network. Conversely, after the switch, the feedforward motif is dismantled and has no discernable effect on the cell cycle. When insulation is broken, the feedforward motif no longer predicts network behavior. This work illustrates how, despite the interconnectivity of networks, the activity of motifs can be insulated by switches that generate well-defined cellular states. Copyright © 2016 Elsevier Inc. All rights reserved.

  13. RMOD: a tool for regulatory motif detection in signaling network.

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    Jinki Kim

    Full Text Available Regulatory motifs are patterns of activation and inhibition that appear repeatedly in various signaling networks and that show specific regulatory properties. However, the network structures of regulatory motifs are highly diverse and complex, rendering their identification difficult. Here, we present a RMOD, a web-based system for the identification of regulatory motifs and their properties in signaling networks. RMOD finds various network structures of regulatory motifs by compressing the signaling network and detecting the compressed forms of regulatory motifs. To apply it into a large-scale signaling network, it adopts a new subgraph search algorithm using a novel data structure called path-tree, which is a tree structure composed of isomorphic graphs of query regulatory motifs. This algorithm was evaluated using various sizes of signaling networks generated from the integration of various human signaling pathways and it showed that the speed and scalability of this algorithm outperforms those of other algorithms. RMOD includes interactive analysis and auxiliary tools that make it possible to manipulate the whole processes from building signaling network and query regulatory motifs to analyzing regulatory motifs with graphical illustration and summarized descriptions. As a result, RMOD provides an integrated view of the regulatory motifs and mechanism underlying their regulatory motif activities within the signaling network. RMOD is freely accessible online at the following URL: http://pks.kaist.ac.kr/rmod.

  14. RMOD: a tool for regulatory motif detection in signaling network.

    Science.gov (United States)

    Kim, Jinki; Yi, Gwan-Su

    2013-01-01

    Regulatory motifs are patterns of activation and inhibition that appear repeatedly in various signaling networks and that show specific regulatory properties. However, the network structures of regulatory motifs are highly diverse and complex, rendering their identification difficult. Here, we present a RMOD, a web-based system for the identification of regulatory motifs and their properties in signaling networks. RMOD finds various network structures of regulatory motifs by compressing the signaling network and detecting the compressed forms of regulatory motifs. To apply it into a large-scale signaling network, it adopts a new subgraph search algorithm using a novel data structure called path-tree, which is a tree structure composed of isomorphic graphs of query regulatory motifs. This algorithm was evaluated using various sizes of signaling networks generated from the integration of various human signaling pathways and it showed that the speed and scalability of this algorithm outperforms those of other algorithms. RMOD includes interactive analysis and auxiliary tools that make it possible to manipulate the whole processes from building signaling network and query regulatory motifs to analyzing regulatory motifs with graphical illustration and summarized descriptions. As a result, RMOD provides an integrated view of the regulatory motifs and mechanism underlying their regulatory motif activities within the signaling network. RMOD is freely accessible online at the following URL: http://pks.kaist.ac.kr/rmod.

  15. Mapping network motif tunability and robustness in the design of synthetic signaling circuits.

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    Sergio Iadevaia

    Full Text Available Cellular networks are highly dynamic in their function, yet evolutionarily conserved in their core network motifs or topologies. Understanding functional tunability and robustness of network motifs to small perturbations in function and structure is vital to our ability to synthesize controllable circuits. In establishing core sets of network motifs, we selected topologies that are overrepresented in mammalian networks, including the linear, feedback, feed-forward, and bifan circuits. Static and dynamic tunability of network motifs were defined as the motif ability to respectively attain steady-state or transient outputs in response to pre-defined input stimuli. Detailed computational analysis suggested that static tunability is insensitive to the circuit topology, since all of the motifs displayed similar ability to attain predefined steady-state outputs in response to constant inputs. Dynamic tunability, in contrast, was tightly dependent on circuit topology, with some motifs performing superiorly in achieving observed time-course outputs. Finally, we mapped dynamic tunability onto motif topologies to determine robustness of motif structures to changes in topology and identify design principles for the rational assembly of robust synthetic networks.

  16. Assessing the Exceptionality of Coloured Motifs in Networks

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    Lacroix Vincent

    2009-01-01

    Full Text Available Various methods have been recently employed to characterise the structure of biological networks. In particular, the concept of network motif and the related one of coloured motif have proven useful to model the notion of a functional/evolutionary building block. However, algorithms that enumerate all the motifs of a network may produce a very large output, and methods to decide which motifs should be selected for downstream analysis are needed. A widely used method is to assess if the motif is exceptional, that is, over- or under-represented with respect to a null hypothesis. Much effort has been put in the last thirty years to derive -values for the frequencies of topological motifs, that is, fixed subgraphs. They rely either on (compound Poisson and Gaussian approximations for the motif count distribution in Erdös-Rényi random graphs or on simulations in other models. We focus on a different definition of graph motifs that corresponds to coloured motifs. A coloured motif is a connected subgraph with fixed vertex colours but unspecified topology. Our work is the first analytical attempt to assess the exceptionality of coloured motifs in networks without any simulation. We first establish analytical formulae for the mean and the variance of the count of a coloured motif in an Erdös-Rényi random graph model. Using simulations under this model, we further show that a Pólya-Aeppli distribution better approximates the distribution of the motif count compared to Gaussian or Poisson distributions. The Pólya-Aeppli distribution, and more generally the compound Poisson distributions, are indeed well designed to model counts of clumping events. Altogether, these results enable to derive a -value for a coloured motif, without spending time on simulations.

  17. Single promoters as regulatory network motifs

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    Zopf, Christopher; Maheshri, Narendra

    2012-02-01

    At eukaryotic promoters, chromatin can influence the relationship between a gene's expression and transcription factor (TF) activity. This additional complexity might allow single promoters to exhibit dynamical behavior commonly attributed to regulatory motifs involving multiple genes. We investigate the role of promoter chromatin architecture in the kinetics of gene activation using a previously described set of promoter variants based on the phosphate-regulated PHO5 promoter in S. cerevisiae. Accurate quantitative measurement of transcription activation kinetics is facilitated by a controllable and observable TF input to a promoter of interest leading to an observable expression output in single cells. We find the particular architecture of these promoters can result in a significant delay in activation, filtering of noisy TF signals, and a memory of previous activation -- dynamical behaviors reminiscent of a feed-forward loop but only requiring a single promoter. We suggest this is a consequence of chromatin transactions at the promoter, likely passing through a long-lived ``primed'' state between its inactive and competent states. Finally, we show our experimental setup can be generalized as a ``gene oscilloscope'' to probe the kinetics of heterologous promoter architectures.

  18. Triadic motifs in the dependence networks of virtual societies

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    Xie, Wen-Jie; Li, Ming-Xia; Jiang, Zhi-Qiang; Zhou, Wei-Xing

    2014-06-01

    In friendship networks, individuals have different numbers of friends, and the closeness or intimacy between an individual and her friends is heterogeneous. Using a statistical filtering method to identify relationships about who depends on whom, we construct dependence networks (which are directed) from weighted friendship networks of avatars in more than two hundred virtual societies of a massively multiplayer online role-playing game (MMORPG). We investigate the evolution of triadic motifs in dependence networks. Several metrics show that the virtual societies evolved through a transient stage in the first two to three weeks and reached a relatively stable stage. We find that the unidirectional loop motif (M9) is underrepresented and does not appear, open motifs are also underrepresented, while other close motifs are overrepresented. We also find that, for most motifs, the overall level difference of the three avatars in the same motif is significantly lower than average, whereas the sum of ranks is only slightly larger than average. Our findings show that avatars' social status plays an important role in the formation of triadic motifs.

  19. Triadic motifs in the dependence networks of virtual societies.

    Science.gov (United States)

    Xie, Wen-Jie; Li, Ming-Xia; Jiang, Zhi-Qiang; Zhou, Wei-Xing

    2014-06-10

    In friendship networks, individuals have different numbers of friends, and the closeness or intimacy between an individual and her friends is heterogeneous. Using a statistical filtering method to identify relationships about who depends on whom, we construct dependence networks (which are directed) from weighted friendship networks of avatars in more than two hundred virtual societies of a massively multiplayer online role-playing game (MMORPG). We investigate the evolution of triadic motifs in dependence networks. Several metrics show that the virtual societies evolved through a transient stage in the first two to three weeks and reached a relatively stable stage. We find that the unidirectional loop motif (M9) is underrepresented and does not appear, open motifs are also underrepresented, while other close motifs are overrepresented. We also find that, for most motifs, the overall level difference of the three avatars in the same motif is significantly lower than average, whereas the sum of ranks is only slightly larger than average. Our findings show that avatars' social status plays an important role in the formation of triadic motifs.

  20. Detecting Statistically Significant Communities of Triangle Motifs in Undirected Networks

    Science.gov (United States)

    2016-04-26

    Granovetter, M. (1983), “The strength of weak ties: A network theory revisited,” Sociological Theory 1 pp. 201-233. [4] Lancichinetti, A., Fortunato, S...AFRL-AFOSR-UK-TR-2015-0025 Detecting Statistically Signicant Communities of Triangle Motifs in Undirected Networks Marcus Perry IMPERIAL COLLEGE OF...triangle motifs in undirected networks 5a.  CONTRACT NUMBER 5b.  GRANT NUMBER FA9550-15-1-0019 5c.  PROGRAM ELEMENT NUMBER 61102F 6. AUTHOR(S) Marcus Perry

  1. Triadic motifs in the dependence networks of virtual societies

    OpenAIRE

    Xie, Wen-Jie; Li, Ming-Xia; Jiang, Zhi-Qiang; Zhou, Wei-Xing

    2014-01-01

    In friendship networks, individuals have different numbers of friends, and the closeness or intimacy between an individual and her friends is heterogeneous. Using a statistical filtering method to identify relationships about who depends on whom, we construct dependence networks (which are directed) from weighted friendship networks of avatars in more than two hundred virtual societies of a massively multiplayer online role-playing game (MMORPG). We investigate the evolution of triadic motifs...

  2. Stochastic and coherence resonance in feed-forward-loop neuronal network motifs

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    Guo, Daqing; Li, Chunguang

    2009-05-01

    The relationships between noise and complex dynamic behaviors of neuronal ensembles are key questions in computational neuroscience, particularly in understanding some basic signal transmission mechanisms of the brain. Here we systemically investigate both the stochastic resonance (SR) and coherence resonance (CR) in the triple-neuron feed-forward-loop (FFL) network motifs by computational modeling. We use the Izhikevich neuron model as well as the chemical coupling to build the FFL motifs, and consider all possible motif types. The simulation results demonstrate that these motifs can exploit noise to enrich its dynamic performance. With a proper choice of noise intensities, both the SR and CR can be exhibited in many types of the FFLs. On the other hand, our results also indicate that the coupling strength serves as a control parameter, which has great impacts on the stochastic dynamics of the FFL motifs. Additionally, biological implications of presented results in the field of neuroscience are outlined.

  3. Identification of important nodes in directed biological networks: a network motif approach.

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    Pei Wang

    Full Text Available Identification of important nodes in complex networks has attracted an increasing attention over the last decade. Various measures have been proposed to characterize the importance of nodes in complex networks, such as the degree, betweenness and PageRank. Different measures consider different aspects of complex networks. Although there are numerous results reported on undirected complex networks, few results have been reported on directed biological networks. Based on network motifs and principal component analysis (PCA, this paper aims at introducing a new measure to characterize node importance in directed biological networks. Investigations on five real-world biological networks indicate that the proposed method can robustly identify actually important nodes in different networks, such as finding command interneurons, global regulators and non-hub but evolutionary conserved actually important nodes in biological networks. Receiver Operating Characteristic (ROC curves for the five networks indicate remarkable prediction accuracy of the proposed measure. The proposed index provides an alternative complex network metric. Potential implications of the related investigations include identifying network control and regulation targets, biological networks modeling and analysis, as well as networked medicine.

  4. Brain network clustering with information flow motifs

    NARCIS (Netherlands)

    Märtens, M.; Meier, J.M.; Hillebrand, Arjan; Tewarie, Prejaas; Van Mieghem, P.F.A.

    2017-01-01

    Recent work has revealed frequency-dependent global patterns of information flow by a network analysis of magnetoencephalography data of the human brain. However, it is unknown which properties on a small subgraph-scale of those functional brain networks are dominant at different frequencies bands.

  5. Stochastic Resonance in Neuronal Network Motifs with Ornstein-Uhlenbeck Colored Noise

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    Xuyang Lou

    2014-01-01

    Full Text Available We consider here the effect of the Ornstein-Uhlenbeck colored noise on the stochastic resonance of the feed-forward-loop (FFL network motif. The FFL motif is modeled through the FitzHugh-Nagumo neuron model as well as the chemical coupling. Our results show that the noise intensity and the correlation time of the noise process serve as the control parameters, which have great impacts on the stochastic dynamics of the FFL motif. We find that, with a proper choice of noise intensities and the correlation time of the noise process, the signal-to-noise ratio (SNR can display more than one peak.

  6. Dimensionality of social networks using motifs and eigenvalues.

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    Anthony Bonato

    Full Text Available We consider the dimensionality of social networks, and develop experiments aimed at predicting that dimension. We find that a social network model with nodes and links sampled from an m-dimensional metric space with power-law distributed influence regions best fits samples from real-world networks when m scales logarithmically with the number of nodes of the network. This supports a logarithmic dimension hypothesis, and we provide evidence with two different social networks, Facebook and LinkedIn. Further, we employ two different methods for confirming the hypothesis: the first uses the distribution of motif counts, and the second exploits the eigenvalue distribution.

  7. Motifs of Networks from Shear Fractures

    CERN Document Server

    Ghaffari, H O

    2011-01-01

    Rupture's sequence of shear fractures using a transformation form of aperture patterns to complex networks was studied, and then sub-graphs abundance within the corresponding networks was analyzed. Furthermore, to distinguish the role of contact zones and flow of energy in ruptures tips, the contact strings were constructed. The contacts 'strings were connected by using constrained geometrical distance and amount of net-contact area per string, yields directed networks. For shear rupture, we observed approximately similar trend in sub-graphs distribution which were the results of parallel and transversal aperture profiles (a super-family phenomena). We confirmed the same inherent dynamic of sheared fracture yields the nearly same family of sub-graphs. For directed networks, our results confirmed the role of the feed-forward sub-graphs in flow of energy through the development of shear rupture.

  8. Motif structure and cooperation in real-world complex networks

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    Salehi, Mostafa; Rabiee, Hamid R.; Jalili, Mahdi

    2010-12-01

    Networks of dynamical nodes serve as generic models for real-world systems in many branches of science ranging from mathematics to physics, technology, sociology and biology. Collective behavior of agents interacting over complex networks is important in many applications. The cooperation between selfish individuals is one of the most interesting collective phenomena. In this paper we address the interplay between the motifs’ cooperation properties and their abundance in a number of real-world networks including yeast protein-protein interaction, human brain, protein structure, email communication, dolphins’ social interaction, Zachary karate club and Net-science coauthorship networks. First, the amount of cooperativity for all possible undirected subgraphs with three to six nodes is calculated. To this end, the evolutionary dynamics of the Prisoner’s Dilemma game is considered and the cooperativity of each subgraph is calculated as the percentage of cooperating agents at the end of the simulation time. Then, the three- to six-node motifs are extracted for each network. The significance of the abundance of a motif, represented by a Z-value, is obtained by comparing them with some properly randomized versions of the original network. We found that there is always a group of motifs showing a significant inverse correlation between their cooperativity amount and Z-value, i.e. the more the Z-value the less the amount of cooperativity. This suggests that networks composed of well-structured units do not have good cooperativity properties.

  9. Motif-role-fingerprints: the building-blocks of motifs, clustering-coefficients and transitivities in directed networks.

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    Mark D McDonnell

    Full Text Available Complex networks are frequently characterized by metrics for which particular subgraphs are counted. One statistic from this category, which we refer to as motif-role fingerprints, differs from global subgraph counts in that the number of subgraphs in which each node participates is counted. As with global subgraph counts, it can be important to distinguish between motif-role fingerprints that are 'structural' (induced subgraphs and 'functional' (partial subgraphs. Here we show mathematically that a vector of all functional motif-role fingerprints can readily be obtained from an arbitrary directed adjacency matrix, and then converted to structural motif-role fingerprints by multiplying that vector by a specific invertible conversion matrix. This result demonstrates that a unique structural motif-role fingerprint exists for any given functional motif-role fingerprint. We demonstrate a similar result for the cases of functional and structural motif-fingerprints without node roles, and global subgraph counts that form the basis of standard motif analysis. We also explicitly highlight that motif-role fingerprints are elemental to several popular metrics for quantifying the subgraph structure of directed complex networks, including motif distributions, directed clustering coefficient, and transitivity. The relationships between each of these metrics and motif-role fingerprints also suggest new subtypes of directed clustering coefficients and transitivities. Our results have potential utility in analyzing directed synaptic networks constructed from neuronal connectome data, such as in terms of centrality. Other potential applications include anomaly detection in networks, identification of similar networks and identification of similar nodes within networks. Matlab code for calculating all stated metrics following calculation of functional motif-role fingerprints is provided as S1 Matlab File.

  10. Biomarker Motif Discovery by Integrating Mass Spectrometry and PPI Network

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    Zhou, Xiaobo; Wang, Yuan; Wang, Honghui; Pham, Tuan D.; Li, King

    2011-06-01

    Traditional mass spectrometry biomarker discovery studies which focus on single biomarkers or a panel of biomarkers have shown their limitations with low reproducibility. In this paper, we propose a novel biomarker motif discovery approach by integrating both mass spectrometry data and protein interaction network information together to identify biomarkers. A novel Bayesian score method is developed to score the protein subnetwork both from the expression of protein and from the protein interaction network structure. Compared with the previous biomarker discovery method, our biomarker motif identification method not only models the expression of each protein, but also the relationship of proteins affected by the protein-protein interaction network. The experiment results show that our proposed biomarker discovery method has a higher sensitivity and lower false discovery rates than previously used methods. When applying our biomarker motifs discovery approach to the real stroke mass spectrometry data, we can identify several biomarker motifs for ischemic stroke which can achieve a higher classification performance with high biological significance.

  11. How pathogens use linear motifs to perturb host cell networks

    KAUST Repository

    Via, Allegra

    2015-01-01

    Molecular mimicry is one of the powerful stratagems that pathogens employ to colonise their hosts and take advantage of host cell functions to guarantee their replication and dissemination. In particular, several viruses have evolved the ability to interact with host cell components through protein short linear motifs (SLiMs) that mimic host SLiMs, thus facilitating their internalisation and the manipulation of a wide range of cellular networks. Here we present convincing evidence from the literature that motif mimicry also represents an effective, widespread hijacking strategy in prokaryotic and eukaryotic parasites. Further insights into host motif mimicry would be of great help in the elucidation of the molecular mechanisms behind host cell invasion and the development of anti-infective therapeutic strategies.

  12. Event Networks and the Identification of Crime Pattern Motifs.

    Directory of Open Access Journals (Sweden)

    Toby Davies

    Full Text Available In this paper we demonstrate the use of network analysis to characterise patterns of clustering in spatio-temporal events. Such clustering is of both theoretical and practical importance in the study of crime, and forms the basis for a number of preventative strategies. However, existing analytical methods show only that clustering is present in data, while offering little insight into the nature of the patterns present. Here, we show how the classification of pairs of events as close in space and time can be used to define a network, thereby generalising previous approaches. The application of graph-theoretic techniques to these networks can then offer significantly deeper insight into the structure of the data than previously possible. In particular, we focus on the identification of network motifs, which have clear interpretation in terms of spatio-temporal behaviour. Statistical analysis is complicated by the nature of the underlying data, and we provide a method by which appropriate randomised graphs can be generated. Two datasets are used as case studies: maritime piracy at the global scale, and residential burglary in an urban area. In both cases, the same significant 3-vertex motif is found; this result suggests that incidents tend to occur not just in pairs, but in fact in larger groups within a restricted spatio-temporal domain. In the 4-vertex case, different motifs are found to be significant in each case, suggesting that this technique is capable of discriminating between clustering patterns at a finer granularity than previously possible.

  13. Event Networks and the Identification of Crime Pattern Motifs

    Science.gov (United States)

    2015-01-01

    In this paper we demonstrate the use of network analysis to characterise patterns of clustering in spatio-temporal events. Such clustering is of both theoretical and practical importance in the study of crime, and forms the basis for a number of preventative strategies. However, existing analytical methods show only that clustering is present in data, while offering little insight into the nature of the patterns present. Here, we show how the classification of pairs of events as close in space and time can be used to define a network, thereby generalising previous approaches. The application of graph-theoretic techniques to these networks can then offer significantly deeper insight into the structure of the data than previously possible. In particular, we focus on the identification of network motifs, which have clear interpretation in terms of spatio-temporal behaviour. Statistical analysis is complicated by the nature of the underlying data, and we provide a method by which appropriate randomised graphs can be generated. Two datasets are used as case studies: maritime piracy at the global scale, and residential burglary in an urban area. In both cases, the same significant 3-vertex motif is found; this result suggests that incidents tend to occur not just in pairs, but in fact in larger groups within a restricted spatio-temporal domain. In the 4-vertex case, different motifs are found to be significant in each case, suggesting that this technique is capable of discriminating between clustering patterns at a finer granularity than previously possible. PMID:26605544

  14. Network motifs in integrated cellular networks of transcription-regulation and protein-protein interaction

    Science.gov (United States)

    Yeger-Lotem, Esti; Sattath, Shmuel; Kashtan, Nadav; Itzkovitz, Shalev; Milo, Ron; Pinter, Ron Y.; Alon, Uri; Margalit, Hanah

    2004-04-01

    Genes and proteins generate molecular circuitry that enables the cell to process information and respond to stimuli. A major challenge is to identify characteristic patterns in this network of interactions that may shed light on basic cellular mechanisms. Previous studies have analyzed aspects of this network, concentrating on either transcription-regulation or protein-protein interactions. Here we search for composite network motifs: characteristic network patterns consisting of both transcription-regulation and protein-protein interactions that recur significantly more often than in random networks. To this end we developed algorithms for detecting motifs in networks with two or more types of interactions and applied them to an integrated data set of protein-protein interactions and transcription regulation in Saccharomyces cerevisiae. We found a two-protein mixed-feedback loop motif, five types of three-protein motifs exhibiting coregulation and complex formation, and many motifs involving four proteins. Virtually all four-protein motifs consisted of combinations of smaller motifs. This study presents a basic framework for detecting the building blocks of networks with multiple types of interactions.

  15. CyClus3D: a Cytoscape plugin for clustering network motifs in integrated networks.

    Science.gov (United States)

    Audenaert, Pieter; Van Parys, Thomas; Brondel, Florian; Pickavet, Mario; Demeester, Piet; Van de Peer, Yves; Michoel, Tom

    2011-06-01

    Network motifs in integrated molecular networks represent functional relationships between distinct data types. They aggregate to form dense topological structures corresponding to functional modules which cannot be detected by traditional graph clustering algorithms. We developed CyClus3D, a Cytoscape plugin for clustering composite three-node network motifs using a 3D spectral clustering algorithm. Via the Cytoscape plugin manager or http://bioinformatics.psb.ugent.be/software/details/CyClus3D.

  16. MODA: an efficient algorithm for network motif discovery in biological networks.

    Science.gov (United States)

    Omidi, Saeed; Schreiber, Falk; Masoudi-Nejad, Ali

    2009-10-01

    In recent years, interest has been growing in the study of complex networks. Since Erdös and Rényi (1960) proposed their random graph model about 50 years ago, many researchers have investigated and shaped this field. Many indicators have been proposed to assess the global features of networks. Recently, an active research area has developed in studying local features named motifs as the building blocks of networks. Unfortunately, network motif discovery is a computationally hard problem and finding rather large motifs (larger than 8 nodes) by means of current algorithms is impractical as it demands too much computational effort. In this paper, we present a new algorithm (MODA) that incorporates techniques such as a pattern growth approach for extracting larger motifs efficiently. We have tested our algorithm and found it able to identify larger motifs with more than 8 nodes more efficiently than most of the current state-of-the-art motif discovery algorithms. While most of the algorithms rely on induced subgraphs as motifs of the networks, MODA is able to extract both induced and non-induced subgraphs simultaneously. The MODA source code is freely available at: http://LBB.ut.ac.ir/Download/LBBsoft/MODA/

  17. Chromatin states modify network motifs contributing to cell-specific functions

    Science.gov (United States)

    Zhao, Hongying; Liu, Tingting; Liu, Ling; Zhang, Guanxiong; Pang, Lin; Yu, Fulong; Fan, Huihui; Ping, Yanyan; Wang, Li; Xu, Chaohan; Xiao, Yun; Li, Xia

    2015-01-01

    Epigenetic modification can affect many important biological processes, such as cell proliferation and apoptosis. It can alter chromatin conformation and contribute to gene regulation. To investigate how chromatin states associated with network motifs, we assembled chromatin state-modified regulatory networks by combining 269 ChIP-seq data and chromatin states in four cell types. We found that many chromatin states were significantly associated with network motifs, especially for feedforward loops (FFLs). These distinct chromatin state compositions contribute to different expression levels and translational control of targets in FFLs. Strikingly, the chromatin state-modified FFLs were highly cell-specific and, to a large extent, determined cell-selective functions, such as the embryonic stem cell-specific bivalent modification-related FFL with an important role in poising developmentally important genes for expression. Besides, comparisons of chromatin state-modified FFLs between cancerous/stem and primary cell lines revealed specific type of chromatin state alterations that may act together with motif structural changes cooperatively contribute to cell-to-cell functional differences. Combination of these alterations could be helpful in prioritizing candidate genes. Together, this work highlights that a dynamic epigenetic dimension can help network motifs to control cell-specific functions. PMID:26169043

  18. Graph animals, subgraph sampling and motif search in large networks

    CERN Document Server

    Baskerville, Kim; Paczuski, Maya

    2007-01-01

    We generalize a sampling algorithm for lattice animals (connected clusters on a regular lattice) to a Monte Carlo algorithm for `graph animals', i.e. connected subgraphs in arbitrary networks. As with the algorithm in [N. Kashtan et al., Bioinformatics 20, 1746 (2004)], it provides a weighted sample, but the computation of the weights is much faster (linear in the size of subgraphs, instead of super-exponential). This allows subgraphs with up to ten or more nodes to be sampled with very high statistics, from arbitrarily large networks. Using this together with a heuristic algorithm for rapidly classifying isomorphic graphs, we present results for two protein interaction networks obtained using the TAP high throughput method: one of Escherichia coli with 230 nodes and 695 links, and one for yeast (Saccharomyces cerevisiae) with roughly ten times more nodes and links. We find in both cases that most connected subgraphs are strong motifs (Z-scores >10) or anti-motifs (Z-scores <-10) when the null model is the...

  19. Distinct configurations of protein complexes and biochemical pathways revealed by epistatic interaction network motifs

    LENUS (Irish Health Repository)

    Casey, Fergal

    2011-08-22

    Abstract Background Gene and protein interactions are commonly represented as networks, with the genes or proteins comprising the nodes and the relationship between them as edges. Motifs, or small local configurations of edges and nodes that arise repeatedly, can be used to simplify the interpretation of networks. Results We examined triplet motifs in a network of quantitative epistatic genetic relationships, and found a non-random distribution of particular motif classes. Individual motif classes were found to be associated with different functional properties, suggestive of an underlying biological significance. These associations were apparent not only for motif classes, but for individual positions within the motifs. As expected, NNN (all negative) motifs were strongly associated with previously reported genetic (i.e. synthetic lethal) interactions, while PPP (all positive) motifs were associated with protein complexes. The two other motif classes (NNP: a positive interaction spanned by two negative interactions, and NPP: a negative spanned by two positives) showed very distinct functional associations, with physical interactions dominating for the former but alternative enrichments, typical of biochemical pathways, dominating for the latter. Conclusion We present a model showing how NNP motifs can be used to recognize supportive relationships between protein complexes, while NPP motifs often identify opposing or regulatory behaviour between a gene and an associated pathway. The ability to use motifs to point toward underlying biological organizational themes is likely to be increasingly important as more extensive epistasis mapping projects in higher organisms begin.

  20. Form and function in gene regulatory networks: the structure of network motifs determines fundamental properties of their dynamical state space.

    Science.gov (United States)

    Ahnert, S E; Fink, T M A

    2016-07-01

    Network motifs have been studied extensively over the past decade, and certain motifs, such as the feed-forward loop, play an important role in regulatory networks. Recent studies have used Boolean network motifs to explore the link between form and function in gene regulatory networks and have found that the structure of a motif does not strongly determine its function, if this is defined in terms of the gene expression patterns the motif can produce. Here, we offer a different, higher-level definition of the 'function' of a motif, in terms of two fundamental properties of its dynamical state space as a Boolean network. One is the basin entropy, which is a complexity measure of the dynamics of Boolean networks. The other is the diversity of cyclic attractor lengths that a given motif can produce. Using these two measures, we examine all 104 topologically distinct three-node motifs and show that the structural properties of a motif, such as the presence of feedback loops and feed-forward loops, predict fundamental characteristics of its dynamical state space, which in turn determine aspects of its functional versatility. We also show that these higher-level properties have a direct bearing on real regulatory networks, as both basin entropy and cycle length diversity show a close correspondence with the prevalence, in neural and genetic regulatory networks, of the 13 connected motifs without self-interactions that have been studied extensively in the literature. © 2016 The Authors.

  1. A review on models and algorithms for motif discovery in protein-protein interaction networks.

    Science.gov (United States)

    Ciriello, Giovanni; Guerra, Concettina

    2008-03-01

    Several algorithms have been recently designed to identify motifs in biological networks, particularly in protein-protein interaction networks. Motifs correspond to repeated modules in the network that may be of biological interest. The approaches proposed in the literature often differ in the definition of a motif, the way the occurrences of a motif are counted and the way their statistical significance is assessed. This has strong implications on the computational complexity of the discovery process and on the type of results that can be expected. This review presents in a systematic way the different computational settings outlining their main features and limitations.

  2. Transduction motif analysis of gastric cancer based on a human signaling network

    Energy Technology Data Exchange (ETDEWEB)

    Liu, G.; Li, D.Z.; Jiang, C.S.; Wang, W. [Fuzhou General Hospital of Nanjing Command, Department of Gastroenterology, Fuzhou, China, Department of Gastroenterology, Fuzhou General Hospital of Nanjing Command, Fuzhou (China)

    2014-04-04

    To investigate signal regulation models of gastric cancer, databases and literature were used to construct the signaling network in humans. Topological characteristics of the network were analyzed by CytoScape. After marking gastric cancer-related genes extracted from the CancerResource, GeneRIF, and COSMIC databases, the FANMOD software was used for the mining of gastric cancer-related motifs in a network with three vertices. The significant motif difference method was adopted to identify significantly different motifs in the normal and cancer states. Finally, we conducted a series of analyses of the significantly different motifs, including gene ontology, function annotation of genes, and model classification. A human signaling network was constructed, with 1643 nodes and 5089 regulating interactions. The network was configured to have the characteristics of other biological networks. There were 57,942 motifs marked with gastric cancer-related genes out of a total of 69,492 motifs, and 264 motifs were selected as significantly different motifs by calculating the significant motif difference (SMD) scores. Genes in significantly different motifs were mainly enriched in functions associated with cancer genesis, such as regulation of cell death, amino acid phosphorylation of proteins, and intracellular signaling cascades. The top five significantly different motifs were mainly cascade and positive feedback types. Almost all genes in the five motifs were cancer related, including EPOR, MAPK14, BCL2L1, KRT18, PTPN6, CASP3, TGFBR2, AR, and CASP7. The development of cancer might be curbed by inhibiting signal transductions upstream and downstream of the selected motifs.

  3. Systems chemistry: logic gates, arithmetic units, and network motifs in small networks.

    Science.gov (United States)

    Wagner, Nathaniel; Ashkenasy, Gonen

    2009-01-01

    A mixture of molecules can be regarded as a network if all the molecular components participate in some kind of interaction with other molecules--either physical or functional interactions. Template-assisted ligation reactions that direct replication processes can serve as the functional elements that connect two members of a chemical network. In such a process, the template does not necessarily catalyze its own formation, but rather the formation of another molecule, which in turn can operate as a template for reactions within the network medium. It was postulated that even networks made up of small numbers of molecules possess a wealth of molecular information sufficient to perform rather complex behavior. To probe this assumption, we have constructed virtual arrays consisting of three replicating molecules, in which dimer templates are capable of catalyzing reactants to form additional templates. By using realistic parameters from peptides or DNA replication experiments, we simulate the construction of various functional motifs within the networks. Specifically, we have designed and implemented each of the three-element Boolean logic gates, and show how these networks are assembled from four basic "building blocks". We also show how the catalytic pathways can be wired together to perform more complex arithmetic units and network motifs, such as the half adder and half subtractor computational modules, and the coherent feed-forward loop network motifs under different sets of parameters. As in previous studies of chemical networks, some of the systems described display behavior that would be difficult to predict without the numerical simulations. Furthermore, the simulations reveal trends and characteristics that should be useful as "recipes" for future design of experimental functional motifs and for potential integration into modular circuits and molecular computation devices.

  4. Integrating Temporal and Spatial Scales: Human Structural Network Motifs Across Age and Region of Interest Size

    Science.gov (United States)

    Echtermeyer, Christoph; Han, Cheol E.; Rotarska-Jagiela, Anna; Mohr, Harald; Uhlhaas, Peter J.; Kaiser, Marcus

    2011-01-01

    Human brain networks can be characterized at different temporal or spatial scales given by the age of the subject or the spatial resolution of the neuroimaging method. Integration of data across scales can only be successful if the combined networks show a similar architecture. One way to compare networks is to look at spatial features, based on fiber length, and topological features of individual nodes where outlier nodes form single node motifs whose frequency yields a fingerprint of the network. Here, we observe how characteristic single node motifs change over age (12–23 years) and network size (414, 813, and 1615 nodes) for diffusion tensor imaging structural connectivity in healthy human subjects. First, we find the number and diversity of motifs in a network to be strongly correlated. Second, comparing different scales, the number and diversity of motifs varied across the temporal (subject age) and spatial (network resolution) scale: certain motifs might only occur at one spatial scale or for a certain age range. Third, regions of interest which show one motif at a lower resolution may show a range of motifs at a higher resolution which may or may not include the original motif at the lower resolution. Therefore, both the type and localization of motifs differ for different spatial resolutions. Our results also indicate that spatial resolution has a higher effect on topological measures whereas spatial measures, based on fiber lengths, remain more comparable between resolutions. Therefore, spatial resolution is crucial when comparing characteristic node fingerprints given by topological and spatial network features. As node motifs are based on topological and spatial properties of brain connectivity networks, these conclusions are also relevant to other studies using connectome analysis. PMID:21811454

  5. Investigating cellular network heterogeneity and modularity in cancer: a network entropy and unbalanced motif approach.

    Science.gov (United States)

    Cheng, Feixiong; Liu, Chuang; Shen, Bairong; Zhao, Zhongming

    2016-08-26

    Cancer is increasingly recognized as a cellular system phenomenon that is attributed to the accumulation of genetic or epigenetic alterations leading to the perturbation of the molecular network architecture. Elucidation of network properties that can characterize tumor initiation and progression, or pinpoint the molecular targets related to the drug sensitivity or resistance, is therefore of critical importance for providing systems-level insights into tumorigenesis and clinical outcome in the molecularly targeted cancer therapy. In this study, we developed a network-based framework to quantitatively examine cellular network heterogeneity and modularity in cancer. Specifically, we constructed gene co-expressed protein interaction networks derived from large-scale RNA-Seq data across 8 cancer types generated in The Cancer Genome Atlas (TCGA) project. We performed gene network entropy and balanced versus unbalanced motif analysis to investigate cellular network heterogeneity and modularity in tumor versus normal tissues, different stages of progression, and drug resistant versus sensitive cancer cell lines. We found that tumorigenesis could be characterized by a significant increase of gene network entropy in all of the 8 cancer types. The ratio of the balanced motifs in normal tissues is higher than that of tumors, while the ratio of unbalanced motifs in tumors is higher than that of normal tissues in all of the 8 cancer types. Furthermore, we showed that network entropy could be used to characterize tumor progression and anticancer drug responses. For example, we found that kinase inhibitor resistant cancer cell lines had higher entropy compared to that of sensitive cell lines using the integrative analysis of microarray gene expression and drug pharmacological data collected from the Genomics of Drug Sensitivity in Cancer database. In addition, we provided potential network-level evidence that smoking might increase cancer cellular network heterogeneity and

  6. Motif formation and industry specific topologies in the Japanese business firm network

    Science.gov (United States)

    Maluck, Julian; Donner, Reik V.; Takayasu, Hideki; Takayasu, Misako

    2017-05-01

    Motifs and roles are basic quantities for the characterization of interactions among 3-node subsets in complex networks. In this work, we investigate how the distribution of 3-node motifs can be influenced by modifying the rules of an evolving network model while keeping the statistics of simpler network characteristics, such as the link density and the degree distribution, invariant. We exemplify this problem for the special case of the Japanese Business Firm Network, where a well-studied and relatively simple yet realistic evolving network model is available, and compare the resulting motif distribution in the real-world and simulated networks. To better approximate the motif distribution of the real-world network in the model, we introduce both subgraph dependent and global additional rules. We find that a specific rule that allows only for the merging process between nodes with similar link directionality patterns reduces the observed excess of densely connected motifs with bidirectional links. Our study improves the mechanistic understanding of motif formation in evolving network models to better describe the characteristic features of real-world networks with a scale-free topology.

  7. Network motif identification and structure detection with exponential random graph models

    Directory of Open Access Journals (Sweden)

    Munni Begum

    2014-12-01

    Full Text Available Local regulatory motifs are identified in the transcription regulatory network of the most studied model organism Escherichia coli (E. coli through graphical models. Network motifs are small structures in a network that appear more frequently than expected by chance alone. We apply social network methodologies such as p* models, also known as Exponential Random Graph Models (ERGMs, to identify statistically significant network motifs. In particular, we generate directed graphical models that can be applied to study interaction networks in a broad range of databases. The Markov Chain Monte Carlo (MCMC computational algorithms are implemented to obtain the estimates of model parameters to the corresponding network statistics. A variety of ERGMs are fitted to identify statistically significant network motifs in transcription regulatory networks of E. coli. A total of nine ERGMs are fitted to study the transcription factor - transcription factor interactions and eleven ERGMs are fitted for the transcription factor-operon interactions. For both of these interaction networks, arc (a directed edge in a directed network and k-istar (or incoming star structures, for values of k between 2 and 10, are found to be statistically significant local structures or network motifs. The goodness of fit statistics are provided to determine the quality of these models.

  8. Motifs, themes and thematic maps of an integrated Saccharomyces cerevisiae interaction network

    Directory of Open Access Journals (Sweden)

    Andrews Brenda

    2005-06-01

    Full Text Available Abstract Background Large-scale studies have revealed networks of various biological interaction types, such as protein-protein interaction, genetic interaction, transcriptional regulation, sequence homology, and expression correlation. Recurring patterns of interconnection, or 'network motifs', have revealed biological insights for networks containing either one or two types of interaction. Results To study more complex relationships involving multiple biological interaction types, we assembled an integrated Saccharomyces cerevisiae network in which nodes represent genes (or their protein products and differently colored links represent the aforementioned five biological interaction types. We examined three- and four-node interconnection patterns containing multiple interaction types and found many enriched multi-color network motifs. Furthermore, we showed that most of the motifs form 'network themes' – classes of higher-order recurring interconnection patterns that encompass multiple occurrences of network motifs. Network themes can be tied to specific biological phenomena and may represent more fundamental network design principles. Examples of network themes include a pair of protein complexes with many inter-complex genetic interactions – the 'compensatory complexes' theme. Thematic maps – networks rendered in terms of such themes – can simplify an otherwise confusing tangle of biological relationships. We show this by mapping the S. cerevisiae network in terms of two specific network themes. Conclusion Significantly enriched motifs in an integrated S. cerevisiae interaction network are often signatures of network themes, higher-order network structures that correspond to biological phenomena. Representing networks in terms of network themes provides a useful simplification of complex biological relationships.

  9. iRegulon: From a Gene List to a Gene Regulatory Network Using Large Motif and Track Collections

    Science.gov (United States)

    Imrichová, Hana; Van de Sande, Bram; Standaert, Laura; Christiaens, Valerie; Hulselmans, Gert; Herten, Koen; Naval Sanchez, Marina; Potier, Delphine; Svetlichnyy, Dmitry; Kalender Atak, Zeynep; Fiers, Mark; Marine, Jean-Christophe; Aerts, Stein

    2014-01-01

    Identifying master regulators of biological processes and mapping their downstream gene networks are key challenges in systems biology. We developed a computational method, called iRegulon, to reverse-engineer the transcriptional regulatory network underlying a co-expressed gene set using cis-regulatory sequence analysis. iRegulon implements a genome-wide ranking-and-recovery approach to detect enriched transcription factor motifs and their optimal sets of direct targets. We increase the accuracy of network inference by using very large motif collections of up to ten thousand position weight matrices collected from various species, and linking these to candidate human TFs via a motif2TF procedure. We validate iRegulon on gene sets derived from ENCODE ChIP-seq data with increasing levels of noise, and we compare iRegulon with existing motif discovery methods. Next, we use iRegulon on more challenging types of gene lists, including microRNA target sets, protein-protein interaction networks, and genetic perturbation data. In particular, we over-activate p53 in breast cancer cells, followed by RNA-seq and ChIP-seq, and could identify an extensive up-regulated network controlled directly by p53. Similarly we map a repressive network with no indication of direct p53 regulation but rather an indirect effect via E2F and NFY. Finally, we generalize our computational framework to include regulatory tracks such as ChIP-seq data and show how motif and track discovery can be combined to map functional regulatory interactions among co-expressed genes. iRegulon is available as a Cytoscape plugin from http://iregulon.aertslab.org. PMID:25058159

  10. SLIDER: a generic metaheuristic for the discovery of correlated motifs in protein-protein interaction networks.

    Science.gov (United States)

    Boyen, Peter; Van Dyck, Dries; Neven, Frank; van Ham, Roeland C H J; van Dijk, Aalt D J

    2011-01-01

    Correlated motif mining (cmm) is the problem of finding overrepresented pairs of patterns, called motifs, in sequences of interacting proteins. Algorithmic solutions for cmm thereby provide a computational method for predicting binding sites for protein interaction. In this paper, we adopt a motif-driven approach where the support of candidate motif pairs is evaluated in the network. We experimentally establish the superiority of the Chi-square-based support measure over other support measures. Furthermore, we obtain that cmm is an np-hard problem for a large class of support measures (including Chi-square) and reformulate the search for correlated motifs as a combinatorial optimization problem. We then present the generic metaheuristic slider which uses steepest ascent with a neighborhood function based on sliding motifs and employs the Chi-square-based support measure. We show that slider outperforms existing motif-driven cmm methods and scales to large protein-protein interaction networks. The slider-implementation and the data used in the experiments are available on http://bioinformatics.uhasselt.be.

  11. What Determines the Assembly of Transcriptional Network Motifs in Escherichia coli?

    Science.gov (United States)

    Camas, Francisco M.; Poyatos, Juan F.

    2008-01-01

    Transcriptional networks are constituted by a collection of building blocks known as network motifs. Why do motifs appear? An adaptive model of motif emergence was recently questioned in favor of neutralist scenarios. Here, we provide a new picture of motif assembly in Escherichia coli which partially clarifies these contrasting explanations. This is based on characterizing the linkage between motifs and sensing or response specificity of their constituent transcriptional factors (TFs). We find that sensing specificity influences the distribution of autoregulation, while the tendency of a TF to establish feed-forward loops (FFLs) depends on response specificity, i.e., regulon size. Analysis of the latter pattern reveals that coregulation between large regulon-size TFs is common under a network neutral model, leading to the assembly of a great number of FFLs and bifans. In addition, neutral exclusive regulation also leads to a collection of single input modules -the fourth basic motif. On the whole, and even under the conservative neutralist scenario considered, a substantial group of regulatory structures revealed adaptive. These structures visibly function as fully-fledged working units. PMID:18987754

  12. Network motif comparison rationalizes Sec1/Munc18-SNARE regulation mechanism in exocytosis

    Directory of Open Access Journals (Sweden)

    Xia Tian

    2012-03-01

    Full Text Available Abstract Background Network motifs, recurring subnetwork patterns, provide significant insight into the biological networks which are believed to govern cellular processes. Methods We present a comparative network motif experimental approach, which helps to explain complex biological phenomena and increases the understanding of biological functions at the molecular level by exploring evolutionary design principles of network motifs. Results Using this framework to analyze the SM (Sec1/Munc18-SNARE (N-ethylmaleimide-sensitive factor activating protein receptor system in exocytic membrane fusion in yeast and neurons, we find that the SM-SNARE network motifs of yeast and neurons show distinct dynamical behaviors. We identify the closed binding mode of neuronal SM (Munc18-1 and SNARE (syntaxin-1 as the key factor leading to mechanistic divergence of membrane fusion systems in yeast and neurons. We also predict that it underlies the conflicting observations in SM overexpression experiments. Furthermore, hypothesis-driven lipid mixing assays validated the prediction. Conclusion Therefore this study provides a new method to solve the discrepancies and to generalize the functional role of SM proteins.

  13. Prediction of proteasome cleavage motifs by neural networks

    DEFF Research Database (Denmark)

    Kesimir, C.; Nussbaum, A.K.; Schild, H.

    2002-01-01

    physiological conditions. Our algorithm has been trained not only on in vitro data, but also on MHC Class I ligand data, which reflect a combination of immunoproteasome and constitutive proteasome specificity. This feature, together with the use of neural networks, a non-linear classification technique, make...... the prediction of MHC Class I ligand boundaries more accurate: 65% of the cleavage sites and 85% of the non-cleavage sites are correctly determined. Moreover, we show that the neural networks trained on the constitutive proteasome data learns a specificity that differs from that of the networks trained on MHC...... Class I molecules. Here we demonstrate that such an approach produces an accurate prediction of the CTL the epitopes in HIV Nef. The method is available at www.cbs.dtu.dk/services/NetChop/....

  14. Identifying Discriminating Network Motifs in YouTube Spam

    OpenAIRE

    O'Callaghan, Derek; Harrigan, Martin; Carthy, Joe; Cunningham, Pádraig

    2012-01-01

    Like other social media websites, YouTube is not immune from the attention of spammers. In particular, evidence can be found of attempts to attract users to malicious third-party websites. As this type of spam is often associated with orchestrated campaigns, it has a discernible network signature, based on networks derived from comments posted by users to videos. In this paper, we examine examples of different YouTube spam campaigns of this nature, and use a feature selection process to ident...

  15. Motif-Synchronization: A new method for analysis of dynamic brain networks with EEG

    Science.gov (United States)

    Rosário, R. S.; Cardoso, P. T.; Muñoz, M. A.; Montoya, P.; Miranda, J. G. V.

    2015-12-01

    The major aim of this work was to propose a new association method known as Motif-Synchronization. This method was developed to provide information about the synchronization degree and direction between two nodes of a network by counting the number of occurrences of some patterns between any two time series. The second objective of this work was to present a new methodology for the analysis of dynamic brain networks, by combining the Time-Varying Graph (TVG) method with a directional association method. We further applied the new algorithms to a set of human electroencephalogram (EEG) signals to perform a dynamic analysis of the brain functional networks (BFN).

  16. Concise review: the dynamics of induced pluripotency and its behavior captured in gene network motifs.

    Science.gov (United States)

    Muraro, Mauro J; Kempe, Hermannus; Verschure, Pernette J

    2013-05-01

    The flexibility of cellular identity is clearly demonstrated by the possibility to reprogram fully differentiated somatic cells to induced pluripotent stem (iPS) cells through forced expression of a set of transcription factors. The generation of iPS cells is of great interest as they provide a tremendous potential for regenerative medicine and an attractive platform to investigate pluripotency. Despite having gathered much attention, the molecular details and responsible gene regulatory networks during the reprogramming process are largely unresolved. In this review, we analyze the sequence and dynamics of reprogramming to construct a timeline of the molecular events taking place during induced pluripotency. We use this timeline as a road map to explore the distinct phases of the reprogramming process and to suggest gene network motifs that are able to describe its systems behavior. We conclude that the gene networks involved in reprogramming comprise several feedforward loops combined with autoregulatory behavior and one or more AND gate motifs that can explain the observed dynamics of induced pluripotency. Our proposed timeline and derived gene network motif behavior could serve as a tool to understand the systems behavior of reprogramming and identify key transitions and/or transcription factors that influence somatic cell reprogramming. Such a systems biology strategy could provide ways to define and explore the use of additional regulatory factors acting at defined gene network motifs to potentially overcome the current challenges of inefficient, slow, and partial somatic cell reprogramming and hence set ground of using iPS cells for clinical and therapeutic use. Copyright © 2013 AlphaMed Press.

  17. MicroRNA mediated network motifs in autoimmune diseases and its crosstalk between genes, functions and pathways.

    Science.gov (United States)

    Prabahar, Archana; Natarajan, Jeyakumar

    2017-01-01

    Autoimmune diseases (AIDs) are incurable but suppressible diseases whose molecular mechanisms are yet to be elucidated. In this work, we selected five systemic autoimmune diseases such as Rheumatoid Arthritis (RA), Type 1 Diabetes (T1D), Inflammatory Bowel Disease (IBD), Autoimmune Thyroid Disease (ATD) and Systemic Lupus Erythematosus (SLE). Heterogeneous data such as miRNA, transcription factor (TF), target genes and protein-protein interactions involved in these AIDs were integrated to understand their roles at different functional levels of miRNA such as transcription initiation, gene regulatory network formation and post transcriptional regulation. To understand the functional characteristics of these complex biological networks, they can be simplified as network motifs (sub networks) and motif-motif interacting pairs (MMIs). The network motif patterns and motif-motif interacting pairs that occur for the selected five diseases were identified. To further understand the functional association between AIDs, functions and pathways were determined using gene set enrichment analysis and five selected immune signaling pathways (ISPs). The crosstalk within AIDs and between the immune signaling pathways (ISPs) could provide novel insights in deciphering disease mechanisms. This study represents the first investigation of miRNA-TF regulatory network for AIDs and its association with ISPs using sub-network motifs. Copyright © 2016 Elsevier B.V. All rights reserved.

  18. An approach to evaluate the topological significance of motifs and other patterns in regulatory networks

    Directory of Open Access Journals (Sweden)

    Wingender Edgar

    2009-05-01

    Full Text Available Abstract Background The identification of network motifs as statistically over-represented topological patterns has become one of the most promising topics in the analysis of complex networks. The main focus is commonly made on how they operate by means of their internal organization. Yet, their contribution to a network's global architecture is poorly understood. However, this requires switching from the abstract view of a topological pattern to the level of its instances. Here, we show how a recently proposed metric, the pairwise disconnectivity index, can be adapted to survey if and which kind of topological patterns and their instances are most important for sustaining the connectivity within a network. Results The pairwise disconnectivity index of a pattern instance quantifies the dependency of the pairwise connections between vertices in a network on the presence of this pattern instance. Thereby, it particularly considers how the coherence between the unique constituents of a pattern instance relates to the rest of a network. We have applied the method exemplarily to the analysis of 3-vertex topological pattern instances in the transcription networks of a bacteria (E. coli, a unicellular eukaryote (S. cerevisiae and higher eukaryotes (human, mouse, rat. We found that in these networks only very few pattern instances break lots of the pairwise connections between vertices upon the removal of an instance. Among them network motifs do not prevail. Rather, those patterns that are shared by the three networks exhibit a conspicuously enhanced pairwise disconnectivity index. Additionally, these are often located in close vicinity to each other or are even overlapping, since only a small number of genes are repeatedly present in most of them. Moreover, evidence has gathered that the importance of these pattern instances is due to synergistic rather than merely additive effects between their constituents. Conclusion A new method has been proposed

  19. Statistically validated mobile communication networks: the evolution of motifs in European and Chinese data

    Science.gov (United States)

    Li, Ming-Xia; Palchykov, Vasyl; Jiang, Zhi-Qiang; Kaski, Kimmo; Kertész, János; Miccichè, Salvatore; Tumminello, Michele; Zhou, Wei-Xing; Mantegna, Rosario N.

    2014-08-01

    Big data open up unprecedented opportunities for investigating complex systems, including society. In particular, communication data serve as major sources for computational social sciences, but they have to be cleaned and filtered as they may contain spurious information due to recording errors as well as interactions, like commercial and marketing activities, not directly related to the social network. The network constructed from communication data can only be considered as a proxy for the network of social relationships. Here we apply a systematic method, based on multiple-hypothesis testing, to statistically validate the links and then construct the corresponding Bonferroni network, generalized to the directed case. We study two large datasets of mobile phone records, one from Europe and the other from China. For both datasets we compare the raw data networks with the corresponding Bonferroni networks and point out significant differences in the structures and in the basic network measures. We show evidence that the Bonferroni network provides a better proxy for the network of social interactions than the original one. Using the filtered networks, we investigated the statistics and temporal evolution of small directed 3-motifs and concluded that closed communication triads have a formation time scale, which is quite fast and typically intraday. We also find that open communication triads preferentially evolve into other open triads with a higher fraction of reciprocated calls. These stylized facts were observed for both datasets.

  20. The effect of extrinsic noise on the dynamics of simple gene network motifs

    Science.gov (United States)

    Assaf, Michael

    Cellular processes do not follow deterministic rules; even in identical environments genetically identical cells can make random choices leading to different phenotypes. This randomness originates from fluctuations present in the biomolecular interaction networks. Most previous work has been focused on the intrinsic noise of these networks. Yet, especially for high-copy-number biomolecules, extrinsic or environmental noise has been experimentally shown to dominate the variation. Here we develop an analytical formalism that allows for calculation of the combined effect of intrinsic and extrinsic noise on gene expression motifs. We introduce a new and generic method for modeling bounded extrinsic noise as an auxiliary species in the master equation. We focus our study on motifs that can be viewed as the building blocks of genetic switches: a non-regulated gene, a self-inhibiting gene, and a self-promoting gene. The role of the extrinsic noise properties (magnitude, correlation time, and distribution) on the statistics of interest are systematically investigated, and the effect of fluctuations in different reaction rates is compared. Due to its analytical nature, our formalism can be used to quantify the effect of extrinsic noise on the dynamics of biochemical networks and can also be used to improve the interpretation of data from single-cell gene expression experiments.

  1. Dynamics of simple gene-network motifs subject to extrinsic fluctuations

    Science.gov (United States)

    Roberts, Elijah; Be'er, Shay; Bohrer, Chris; Sharma, Rati; Assaf, Michael

    2015-12-01

    Cellular processes do not follow deterministic rules; even in identical environments genetically identical cells can make random choices leading to different phenotypes. This randomness originates from fluctuations present in the biomolecular interaction networks. Most previous work has been focused on the intrinsic noise (IN) of these networks. Yet, especially for high-copy-number biomolecules, extrinsic or environmental noise (EN) has been experimentally shown to dominate the variation. Here, we develop an analytical formalism that allows for calculation of the effect of EN on gene-expression motifs. We introduce a method for modeling bounded EN as an auxiliary species in the master equation. The method is fully generic and is not limited to systems with small EN magnitudes. We focus our study on motifs that can be viewed as the building blocks of genetic switches: a nonregulated gene, a self-inhibiting gene, and a self-promoting gene. The role of the EN properties (magnitude, correlation time, and distribution) on the statistics of interest are systematically investigated, and the effect of fluctuations in different reaction rates is compared. Due to its analytical nature, our formalism can be used to quantify the effect of EN on the dynamics of biochemical networks and can also be used to improve the interpretation of data from single-cell gene-expression experiments.

  2. The effects of time delay on the stochastic resonance in feed-forward-loop neuronal network motifs

    Science.gov (United States)

    Liu, Chen; Wang, Jiang; Yu, Haitao; Deng, Bin; Tsang, K. M.; Chan, W. L.; Wong, Y. K.

    2014-04-01

    The dependence of stochastic resonance in the feed-forward-loop neuronal network motifs on the noise and time delay are studied in this paper. By computational modeling, Izhikevich neuron model with the chemical coupling is used to build the triple-neuron feed-forward-loop motifs with all possible motif types. Numerical results show that the correlation between the periodic subthreshold signal's frequency and the dynamical response of the network motifs is resonantly dependent on the intensity of additive spatiotemporal noise. Interestingly, the excitatory intermediate neuron could induce intermittent stochastic resonance, whereas the inhibitory one weakens its influence on the intermittent mode. More importantly, it is found that the increasing delays can induce the intermittent appearance of regions of stochastic resonance. Based on the effects of the time delay on the stochastic resonance, the reasons and conditions of such intermittent resonance phenomenon are analyzed.

  3. Robustness and backbone motif of a cancer network regulated by miR-17-92 cluster during the G1/S transition.

    Directory of Open Access Journals (Sweden)

    Lijian Yang

    Full Text Available Based on interactions among transcription factors, oncogenes, tumor suppressors and microRNAs, a Boolean model of cancer network regulated by miR-17-92 cluster is constructed, and the network is associated with the control of G1/S transition in the mammalian cell cycle. The robustness properties of this regulatory network are investigated by virtue of the Boolean network theory. It is found that, during G1/S transition in the cell cycle process, the regulatory networks are robustly constructed, and the robustness property is largely preserved with respect to small perturbations to the network. By using the unique process-based approach, the structure of this network is analyzed. It is shown that the network can be decomposed into a backbone motif which provides the main biological functions, and a remaining motif which makes the regulatory system more stable. The critical role of miR-17-92 in suppressing the G1/S cell cycle checkpoint and increasing the uncontrolled proliferation of the cancer cells by targeting a genetic network of interacting proteins is displayed with our model.

  4. Intelligent networked teleoperation control

    CERN Document Server

    Li, Zhijun; Su, Chun-Yi

    2015-01-01

    This book describes a unified framework for networked teleoperation systems involving multiple research fields: networked control systems for linear and nonlinear forms, bilateral teleoperation, trilateral teleoperation, multilateral teleoperation and cooperative teleoperation. It closely examines networked control as a field at the intersection of systems & control and robotics and presents a number of experimental case studies on testbeds for robotic systems, including networked haptic devices, robotic network systems and sensor network systems. The concepts and results outlined are easy to understand, even for readers fairly new to the subject. As such, the book offers a valuable reference work for researchers and engineers in the fields of systems & control and robotics.

  5. Connectomic Insights into Topologically Centralized Network Edges and Relevant Motifs in the Human Brain

    Directory of Open Access Journals (Sweden)

    Mingrui eXia

    2016-04-01

    Full Text Available White matter (WM tracts serve as important material substrates for information transfer across brain regions. However, the topological roles of WM tracts in global brain communications and their underlying microstructural basis remain poorly understood. Here, we employed diffusion magnetic resonance imaging and graph-theoretical approaches to identify the pivotal WM connections in human whole-brain networks and further investigated their wiring substrates (including WM microstructural organization and physical consumption and topological contributions to the brain’s network backbone. We found that the pivotal WM connections with highly topological-edge centrality were primarily distributed in several long-range cortico-cortical connections (including the corpus callosum, cingulum and inferior fronto-occipital fasciculus and some projection tracts linking subcortical regions. These pivotal WM connections exhibited high levels of microstructural organization indicated by diffusion measures (the fractional anisotropy, the mean diffusivity and the axial diffusivity and greater physical consumption indicated by streamline lengths, and contributed significantly to the brain’s hubs and the rich-club structure. Network motif analysis further revealed their heavy participations in the organization of communication blocks, especially in routes involving inter-hemispheric heterotopic and extremely remote intra-hemispheric systems. Computational simulation models indicated the sharp decrease of global network integrity when attacking these highly centralized edges. Together, our results demonstrated high building-cost consumption and substantial communication capacity contributions for pivotal WM connections, which deepens our understanding of the topological mechanisms that govern the organization of human connectomes.

  6. Core regulatory network motif underlies the ocellar complex patterning in Drosophila melanogaster

    Science.gov (United States)

    Aguilar-Hidalgo, D.; Lemos, M. C.; Córdoba, A.

    2015-03-01

    During organogenesis, developmental programs governed by Gene Regulatory Networks (GRN) define the functionality, size and shape of the different constituents of living organisms. Robustness, thus, is an essential characteristic that GRNs need to fulfill in order to maintain viability and reproducibility in a species. In the present work we analyze the robustness of the patterning for the ocellar complex formation in Drosophila melanogaster fly. We have systematically pruned the GRN that drives the development of this visual system to obtain the minimum pathway able to satisfy this pattern. We found that the mechanism underlying the patterning obeys to the dynamics of a 3-nodes network motif with a double negative feedback loop fed by a morphogenetic gradient that triggers the inhibition in a French flag problem fashion. A Boolean modeling of the GRN confirms robustness in the patterning mechanism showing the same result for different network complexity levels. Interestingly, the network provides a steady state solution in the interocellar part of the patterning and an oscillatory regime in the ocelli. This theoretical result predicts that the ocellar pattern may underlie oscillatory dynamics in its genetic regulation.

  7. Novel Strategy for Discrimination of Transcription Factor Binding Motifs Employing Mathematical Neural Network

    Science.gov (United States)

    Sugimoto, Asuka; Sumi, Takuya; Kang, Jiyoung; Tateno, Masaru

    2017-07-01

    Recognition in biological macromolecular systems, such as DNA-protein recognition, is one of the most crucial problems to solve toward understanding the fundamental mechanisms of various biological processes. Since specific base sequences of genome DNA are discriminated by proteins, such as transcription factors (TFs), finding TF binding motifs (TFBMs) in whole genome DNA sequences is currently a central issue in interdisciplinary biophysical and information sciences. In the present study, a novel strategy to create a discriminant function for discrimination of TFBMs by constituting mathematical neural networks (NNs) is proposed, together with a method to determine the boundary of signals (TFBMs) and noise in the NN-score (output) space. This analysis also leads to the mathematical limitation of discrimination in the recognition of features representing TFBMs, in an information geometrical manifold. Thus, the present strategy enables the identification of the whole space of TFBMs, right up to the noise boundary.

  8. Virtualized Network Control (VNC)

    Energy Technology Data Exchange (ETDEWEB)

    Lehman, Thomas [Univ. of Southern California, Los Angeles, CA (United States); Guok, Chin [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Ghani, Nasir [Univ. of New Mexico, Albuquerque, NM (United States)

    2013-01-31

    The focus of this project was on the development of a "Network Service Plane" as an abstraction model for the control and provisioning of multi-layer networks. The primary motivation for this work were the requirements of next generation networked applications which will need to access advanced networking as a first class resource at the same level as compute and storage resources. A new class of "Intelligent Network Services" were defined in order to facilitate the integration of advanced network services into application specific workflows. This new class of network services are intended to enable real-time interaction between the application co-scheduling algorithms and the network for the purposes of workflow planning, real-time resource availability identification, scheduling, and provisioning actions.

  9. SLIDER: A Generic Metaheuristic for the Discovery of Correlated Motifs in Protein-Protein Interaction Networks

    NARCIS (Netherlands)

    Boyen, P.; Dyck, van D.; Neven, F.; Ham, van R.C.H.J.; Dijk, van A.D.J.

    2011-01-01

    Correlated motif mining (CMM) is the problem of finding overrepresented pairs of patterns, called motifs, in sequences of interacting proteins. Algorithmic solutions for CMM thereby provide a computational method for predicting binding sites for protein interaction. In this paper, we adopt a

  10. Controllability of Complex Networks

    Science.gov (United States)

    Liu, Yang; Slotine, Jean-Jacques; Barabasi, Albert-Laszlo

    2011-03-01

    The ultimate proof of our understanding of natural or technological systems is reflected in our ability to control them. While control theory offers mathematical tools to steer engineered systems towards a desired state, we lack a general framework to control complex self-organized systems, like the regulatory network of a cell or the Internet. Here we develop analytical tools to study the controllability of an arbitrary complex directed network, identifying the set of driver nodes whose time-dependent control can guide the system's dynamics. We apply these tools to real and model networks, finding that sparse inhomogeneous networks, which emerge in many real complex systems, are the most difficult to control. In contrast, dense and homogeneous networks can be controlled via a few driver nodes. Counterintuitively, we find that in both model and real systems the driver nodes tend to avoid the hubs. We show that the robustness of control to link failure is determined by a core percolation problem, helping us understand why many complex systems are relatively insensitive to link deletion. The developed approach offers a framework to address the controllability of an arbitrary network, representing a key step towards the eventual control of complex systems.

  11. Structure and Function of the Feed-Forward Loop Network Motif

    National Research Council Canada - National Science Library

    S. Mangan; U. Alon

    2003-01-01

    .... One of these motifs is the feed-forward loop (FFL). The FFL, a three-gene pattern, is composed of two input transcription factors, one of which regulates the other, both jointly regulating a target gene...

  12. Construction of a lncRNA-mediated feed-forward loop network reveals global topological features and prognostic motifs in human cancers.

    Science.gov (United States)

    Ning, Shangwei; Gao, Yue; Wang, Peng; Li, Xiang; Zhi, Hui; Zhang, Yan; Liu, Yue; Zhang, Jizhou; Guo, Maoni; Han, Dong; Li, Xia

    2016-07-19

    Long non-coding RNAs (lncRNAs), transcription factors and microRNAs can form lncRNA-mediated feed-forward loops (L-FFLs), which are functional network motifs that regulate a wide range of biological processes, such as development and carcinogenesis. However, L-FFL network motifs have not been systematically identified, and their roles in human cancers are largely unknown. In this study, we computationally integrated data from multiple sources to construct a global L-FFL network for six types of human cancer and characterized the topological features of the network. Our approach revealed several dysregulated L-FFL motifs common across different cancers or specific to particular cancers. We also found that L-FFL motifs can take part in other types of regulatory networks, such as mRNA-mediated FFLs and ceRNA networks, and form the more complex networks in human cancers. In addition, survival analyses further indicated that L-FFL motifs could potentially serve as prognostic biomarkers. Collectively, this study elucidated the roles of L-FFL motifs in human cancers, which could be beneficial for understanding cancer pathogenesis and treatment.

  13. Launch Control Network Engineer

    Science.gov (United States)

    Medeiros, Samantha

    2017-01-01

    The Spaceport Command and Control System (SCCS) is being built at the Kennedy Space Center in order to successfully launch NASA’s revolutionary vehicle that allows humans to explore further into space than ever before. During my internship, I worked with the Network, Firewall, and Hardware teams that are all contributing to the huge SCCS network project effort. I learned the SCCS network design and the several concepts that are running in the background. I also updated and designed documentation for physical networks that are part of SCCS. This includes being able to assist and build physical installations as well as configurations. I worked with the network design for vehicle telemetry interfaces to the Launch Control System (LCS); this allows the interface to interact with other systems at other NASA locations. This network design includes the Space Launch System (SLS), Interim Cryogenic Propulsion Stage (ICPS), and the Orion Multipurpose Crew Vehicle (MPCV). I worked on the network design and implementation in the Customer Avionics Interface Development and Analysis (CAIDA) lab.

  14. Controllability analysis of transcriptional regulatory networks reveals circular control patterns among transcription factors

    DEFF Research Database (Denmark)

    Österlund, Tobias; Bordel, Sergio; Nielsen, Jens

    2015-01-01

    we analyze the topology and organization of nine transcriptional regulatory networks for E. coli, yeast, mouse and human, and we evaluate how the structure of these networks influences two of their key properties, namely controllability and stability. We calculate the controllability for each network......% for the human network. The high controllability (low number of drivers needed to control the system) in yeast, mouse and human is due to the presence of internal loops in their regulatory networks where the TFs regulate each other in a circular fashion. We refer to these internal loops as circular control...... motifs (CCM). The E. coli transcriptional regulatory network, which does not have any CCMs, shows a hierarchical structure of the transcriptional regulatory network in contrast to the eukaryal networks. The presence of CCMs also has influence on the stability of these networks, as the presence of cycles...

  15. Broadband accelerator control network

    Energy Technology Data Exchange (ETDEWEB)

    Skelly, J.; Clifford, T.; Frankel, R.

    1983-01-01

    A broadband data communications network has been implemented at BNL for control of the Alternating Gradient Synchrotron (AG) proton accelerator, using commercial CATV hardware, dual coaxial cables as the communications medium, and spanning 2.0 km. A 4 MHz bandwidth Digital Control channel using CSMA-CA protocol is provided for digital data transmission, with 8 access nodes available over the length of the RELWAY. Each node consists of an rf modem and a microprocessor-based store-and-forward message handler which interfaces the RELWAY to a branch line implemented in GPIB. A gateway to the RELWAY control channel for the (preexisting) AGS Computerized Accelerator Operating system has been constructed using an LSI-11/23 microprocessor as a device in a GPIB branch line. A multilayer communications protocol has been defined for the Digital Control Channel, based on the ISO Open Systems Interconnect layered model, and a RELWAY Device Language defined as the required universal language for device control on this channel.

  16. Co-regulated transcripts associated to cooperating eSNPs define Bi-fan motifs in human gene networks.

    Science.gov (United States)

    Kreimer, Anat; Pe'er, Itsik

    2014-09-01

    Associations between the level of single transcripts and single corresponding genetic variants, expression single nucleotide polymorphisms (eSNPs), have been extensively studied and reported. However, most expression traits are complex, involving the cooperative action of multiple SNPs at different loci affecting multiple genes. Finding these cooperating eSNPs by exhaustive search has proven to be statistically challenging. In this paper we utilized availability of sequencing data with transcriptional profiles in the same cohorts to identify two kinds of usual suspects: eSNPs that alter coding sequences or eSNPs within the span of transcription factors (TFs). We utilize a computational framework for considering triplets, each comprised of a SNP and two associated genes. We examine pairs of triplets with such cooperating source eSNPs that are both associated with the same pair of target genes. We characterize such quartets through their genomic, topological and functional properties. We establish that this regulatory structure of cooperating quartets is frequent in real data, but is rarely observed in permutations. eSNP sources are mostly located on different chromosomes and away from their targets. In the majority of quartets, SNPs affect the expression of the two gene targets independently of one another, suggesting a mutually independent rather than a directionally dependent effect. Furthermore, the directions in which the minor allele count of the SNP affects gene expression within quartets are consistent, so that the two source eSNPs either both have the same effect on the target genes or both affect one gene in the opposite direction to the other. Same-effect eSNPs are observed more often than expected by chance. Cooperating quartets reported here in a human system might correspond to bi-fans, a known network motif of four nodes previously described in model organisms. Overall, our analysis offers insights regarding the fine motif structure of human regulatory

  17. Neural Networks for Optimal Control

    DEFF Research Database (Denmark)

    Sørensen, O.

    1995-01-01

    Two neural networks are trained to act as an observer and a controller, respectively, to control a non-linear, multi-variable process.......Two neural networks are trained to act as an observer and a controller, respectively, to control a non-linear, multi-variable process....

  18. Controlling Congestion on Complex Networks

    CERN Document Server

    Buzna, Lubos

    2016-01-01

    From the Internet to road networks and the power grid, modern life depends on controlling flows on critical infrastructure networks that often operate in a congested state. Yet, we have a limited understanding of the relative performance of the control mechanisms available to manage congestion and of the interplay between network topology, path layout and congestion control algorithms. Here, we consider two flow algorithms (max-flow and uniform-flow), and two more realistic congestion control schemes (max-min fairness and proportional fairness). We analyse how the algorithms and network topology affect throughput, fairness and the location of bottleneck edges. Our results show that on large random networks a network operator can implement the trade-off (proportional fairness) instead of the fair allocation (max-min fairness) with little sacrifice in throughput. We illustrate how the previously studied uniform-flow approach leaves networks severely underutilised in comparison with congestion control algorithms...

  19. Asynchronous control for networked systems

    CERN Document Server

    Rubio, Francisco; Bencomo, Sebastián

    2015-01-01

    This book sheds light on networked control systems; it describes different techniques for asynchronous control, moving away from the periodic actions of classical control, replacing them with state-based decisions and reducing the frequency with which communication between subsystems is required. The text focuses specially on event-based control. Split into two parts, Asynchronous Control for Networked Systems begins by addressing the problems of single-loop networked control systems, laying out various solutions which include two alternative model-based control schemes (anticipatory and predictive) and the use of H2/H∞ robust control to deal with network delays and packet losses. Results on self-triggering and send-on-delta sampling are presented to reduce the need for feedback in the loop. In Part II, the authors present solutions for distributed estimation and control. They deal first with reliable networks and then extend their results to scenarios in which delays and packet losses may occur. The novel ...

  20. The Construction of Regulatory Network for Insulin-Mediated Genes by Integrating Methods Based on Transcription Factor Binding Motifs and Gene Expression Variations

    Directory of Open Access Journals (Sweden)

    Hyeim Jung

    2015-09-01

    Full Text Available Type 2 diabetes mellitus is a complex metabolic disorder associated with multiple genetic, developmental and environmental factors. The recent advances in gene expression microarray technologies as well as network-based analysis methodologies provide groundbreaking opportunities to study type 2 diabetes mellitus. In the present study, we used previously published gene expression microarray datasets of human skeletal muscle samples collected from 20 insulin sensitive individuals before and after insulin treatment in order to construct insulin-mediated regulatory network. Based on a motif discovery method implemented by iRegulon, a Cytoscape app, we identified 25 candidate regulons, motifs of which were enriched among the promoters of 478 up-regulated genes and 82 down-regulated genes. We then looked for a hierarchical network of the candidate regulators, in such a way that the conditional combination of their expression changes may explain those of their target genes. Using Genomica, a software tool for regulatory network construction, we obtained a hierarchical network of eight regulons that were used to map insulin downstream signaling network. Taken together, the results illustrate the benefits of combining completely different methods such as motif-based regulatory factor discovery and expression level-based construction of regulatory network of their target genes in understanding insulin induced biological processes and signaling pathways.

  1. The Construction of Regulatory Network for Insulin-Mediated Genes by Integrating Methods Based on Transcription Factor Binding Motifs and Gene Expression Variations.

    Science.gov (United States)

    Jung, Hyeim; Han, Seonggyun; Kim, Sangsoo

    2015-09-01

    Type 2 diabetes mellitus is a complex metabolic disorder associated with multiple genetic, developmental and environmental factors. The recent advances in gene expression microarray technologies as well as network-based analysis methodologies provide groundbreaking opportunities to study type 2 diabetes mellitus. In the present study, we used previously published gene expression microarray datasets of human skeletal muscle samples collected from 20 insulin sensitive individuals before and after insulin treatment in order to construct insulin-mediated regulatory network. Based on a motif discovery method implemented by iRegulon, a Cytoscape app, we identified 25 candidate regulons, motifs of which were enriched among the promoters of 478 up-regulated genes and 82 down-regulated genes. We then looked for a hierarchical network of the candidate regulators, in such a way that the conditional combination of their expression changes may explain those of their target genes. Using Genomica, a software tool for regulatory network construction, we obtained a hierarchical network of eight regulons that were used to map insulin downstream signaling network. Taken together, the results illustrate the benefits of combining completely different methods such as motif-based regulatory factor discovery and expression level-based construction of regulatory network of their target genes in understanding insulin induced biological processes and signaling pathways.

  2. Cybersecurity of Critical Control Networks

    Science.gov (United States)

    2015-07-14

    AFRL-OSR-VA-TR-2015-0173 CONGRESSIONAL) CYBERSECURITY OF CRITICAL CONTROL NETWORKS William Mahoney UNIVERSITY OF NEBRASKA Final Report 07/14/2015...Congressional) Cybersecurity of Critical Control Networks 5a. CONTRACT NUMBER 5b. GRANT NUMBER FA9550-10-1-0341 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR...FA9550-10-1-0341 Cybersecurity of Critical Control Networks Report Type Final Report Primary Contact E-mail wmahoney@unomaha.edu Primary

  3. Performance of Networked Control Systems

    Directory of Open Access Journals (Sweden)

    Yingwei Zhang

    2013-01-01

    Full Text Available Data packet dropout is a special kind of time delay problem. In this paper, predictive controllers for networked control systems (NCSs with dual-network are designed by model predictive control method. The contributions are as follows. (1 The predictive control problem of the dual-network is considered. (2 The predictive performance of the dual-network is evaluated. (3 Compared to the popular networked control systems, the optimal controller of the new NCSs with data packets dropout is designed, which can minimize infinite performance index at each sampling time and guarantee the closed-loop system stability. Finally, the simulation results show the feasibility and effectiveness of the controllers designed.

  4. Network Access Control For Dummies

    CERN Document Server

    Kelley, Jay; Wessels, Denzil

    2009-01-01

    Network access control (NAC) is how you manage network security when your employees, partners, and guests need to access your network using laptops and mobile devices. Network Access Control For Dummies is where you learn how NAC works, how to implement a program, and how to take real-world challenges in stride. You'll learn how to deploy and maintain NAC in your environment, identify and apply NAC standards, and extend NAC for greater network security. Along the way you'll become familiar with what NAC is (and what it isn't) as well as the key business drivers for deploying NAC.Learn the step

  5. Neural Networks in Control Applications

    DEFF Research Database (Denmark)

    Sørensen, O.

    The intention of this report is to make a systematic examination of the possibilities of applying neural networks in those technical areas, which are familiar to a control engineer. In other words, the potential of neural networks in control applications is given higher priority than a detailed...... examined, and it appears that considering 'normal' neural network models with, say, 500 samples, the problem of over-fitting is neglible, and therefore it is not taken into consideration afterwards. Numerous model types, often met in control applications, are implemented as neural network models...... Kalmann filter) representing state space description. The potentials of neural networks for control of non-linear processes are also examined, focusing on three different groups of control concepts, all considered as generalizations of known linear control concepts to handle also non-linear processes...

  6. Positive train control shared network.

    Science.gov (United States)

    2015-05-01

    The Interoperable Train Control (ITC) Positive : Train Control (PTC) Shared Network (IPSN) : project investigated anticipated industry benefits : and the level of support for the development of : a hosted technological platform for PTC : messaging ac...

  7. Mutagenesis of GATA motifs controlling the endoderm regulator elt-2 reveals distinct dominant and secondary cis-regulatory elements.

    Science.gov (United States)

    Du, Lawrence; Tracy, Sharon; Rifkin, Scott A

    2016-04-01

    Cis-regulatory elements (CREs) are crucial links in developmental gene regulatory networks, but in many cases, it can be difficult to discern whether similar CREs are functionally equivalent. We found that despite similar conservation and binding capability to upstream activators, different GATA cis-regulatory motifs within the promoter of the C. elegans endoderm regulator elt-2 play distinctive roles in activating and modulating gene expression throughout development. We fused wild-type and mutant versions of the elt-2 promoter to a gfp reporter and inserted these constructs as single copies into the C. elegans genome. We then counted early embryonic gfp transcripts using single-molecule RNA FISH (smFISH) and quantified gut GFP fluorescence. We determined that a single primary dominant GATA motif located 527bp upstream of the elt-2 start codon was necessary for both embryonic activation and later maintenance of transcription, while nearby secondary GATA motifs played largely subtle roles in modulating postembryonic levels of elt-2. Mutation of the primary activating site increased low-level spatiotemporally ectopic stochastic transcription, indicating that this site acts repressively in non-endoderm cells. Our results reveal that CREs with similar GATA factor binding affinities in close proximity can play very divergent context-dependent roles in regulating the expression of a developmentally critical gene in vivo. Copyright © 2016 Elsevier Inc. All rights reserved.

  8. Neural Networks in Control Applications

    DEFF Research Database (Denmark)

    Sørensen, O.

    simulated process and compared. The closing chapter describes some practical experiments, where the different control concepts and training methods are tested on the same practical process operating in very noisy environments. All tests confirm that neural networks also have the potential to be trained......The intention of this report is to make a systematic examination of the possibilities of applying neural networks in those technical areas, which are familiar to a control engineer. In other words, the potential of neural networks in control applications is given higher priority than a detailed...... study of the networks themselves. With this end in view the following restrictions have been made: - Amongst numerous neural network structures, only the Multi Layer Perceptron (a feed-forward network) is applied. - Amongst numerous training algorithms, only four algorithms are examined, all...

  9. HSUPA Transport Network Congestion Control

    Directory of Open Access Journals (Sweden)

    Nádas Szilveszter

    2009-01-01

    Full Text Available The introduction of High Speed Uplink Packet Access (HSUPA greatly improves achievable uplink bitrate but it presents new challenges to be solved in the WCDMA radio access network. In the transport network, bandwidth reservation for HSUPA is not efficient and TCP cannot efficiently resolve congestion because of lower layer retransmissions. This paper proposes an HSUPA transport network flow control algorithm that handles congestion situations efficiently and supports Quality of Service differentiation. In the Radio Network Controller (RNC, transport network congestion is detected. Relying on the standardized control frame, the RNC notifies the Node B about transport network congestion. In case of transport network congestion, the Node B part of the HSUPA flow control instructs the air interface scheduler to reduce the bitrate of the flow to eliminate congestion. The performance analysis concentrates on transport network limited scenarios. It is shown that TCP cannot provide efficient congestion control. The proposed algorithm can achieve high end-user perceived throughput, while maintaining low delay, loss, and good fairness in the transport network.

  10. Cis and trans regulatory mechanisms control AP2-mediated B cell receptor endocytosis via select tyrosine-based motifs.

    Directory of Open Access Journals (Sweden)

    Kathleen Busman-Sahay

    Full Text Available Following antigen recognition, B cell receptor (BCR-mediated endocytosis is the first step of antigen processing and presentation to CD4+ T cells, a crucial component of the initiation and control of the humoral immune response. Despite this, the molecular mechanism of BCR internalization is poorly understood. Recently, studies of activated B cell-like diffuse large B cell lymphoma (ABC DLBCL have shown that mutations within the BCR subunit CD79b leads to increased BCR surface expression, suggesting that CD79b may control BCR internalization. Adaptor protein 2 (AP2 is the major mediator of receptor endocytosis via clathrin-coated pits. The BCR contains five putative AP2-binding YxxØ motifs, including four that are present within two immunoreceptor tyrosine-based activation motifs (ITAMs. Using a combination of in vitro and in situ approaches, we establish that the sole mediator of AP2-dependent BCR internalization is the membrane proximal ITAM YxxØ motif in CD79b, which is a major target of mutation in ABC DLBCL. In addition, we establish that BCR internalization can be regulated at a minimum of two different levels: regulation of YxxØ AP2 binding in cis by downstream ITAM-embedded DCSM and QTAT regulatory elements and regulation in trans by the partner cytoplasmic domain of the CD79 heterodimer. Beyond establishing the basic rules governing BCR internalization, these results illustrate an underappreciated role for ITAM residues in controlling clathrin-dependent endocytosis and highlight the complex mechanisms that control the activity of AP2 binding motifs in this receptor system.

  11. Cis and trans regulatory mechanisms control AP2-mediated B cell receptor endocytosis via select tyrosine-based motifs.

    Science.gov (United States)

    Busman-Sahay, Kathleen; Drake, Lisa; Sitaram, Anand; Marks, Michael; Drake, James R

    2013-01-01

    Following antigen recognition, B cell receptor (BCR)-mediated endocytosis is the first step of antigen processing and presentation to CD4+ T cells, a crucial component of the initiation and control of the humoral immune response. Despite this, the molecular mechanism of BCR internalization is poorly understood. Recently, studies of activated B cell-like diffuse large B cell lymphoma (ABC DLBCL) have shown that mutations within the BCR subunit CD79b leads to increased BCR surface expression, suggesting that CD79b may control BCR internalization. Adaptor protein 2 (AP2) is the major mediator of receptor endocytosis via clathrin-coated pits. The BCR contains five putative AP2-binding YxxØ motifs, including four that are present within two immunoreceptor tyrosine-based activation motifs (ITAMs). Using a combination of in vitro and in situ approaches, we establish that the sole mediator of AP2-dependent BCR internalization is the membrane proximal ITAM YxxØ motif in CD79b, which is a major target of mutation in ABC DLBCL. In addition, we establish that BCR internalization can be regulated at a minimum of two different levels: regulation of YxxØ AP2 binding in cis by downstream ITAM-embedded DCSM and QTAT regulatory elements and regulation in trans by the partner cytoplasmic domain of the CD79 heterodimer. Beyond establishing the basic rules governing BCR internalization, these results illustrate an underappreciated role for ITAM residues in controlling clathrin-dependent endocytosis and highlight the complex mechanisms that control the activity of AP2 binding motifs in this receptor system.

  12. Delays and networked control systems

    CERN Document Server

    Hetel, Laurentiu; Daafouz, Jamal; Johansson, Karl

    2016-01-01

    This edited monograph includes state-of-the-art contributions on continuous time dynamical networks with delays. The book is divided into four parts. The first part presents tools and methods for the analysis of time-delay systems with a particular attention on control problems of large scale or infinite-dimensional systems with delays. The second part of the book is dedicated to the use of time-delay models for the analysis and design of Networked Control Systems. The third part of the book focuses on the analysis and design of systems with asynchronous sampling intervals which occur in Networked Control Systems. The last part of the book exposes several contributions dealing with the design of cooperative control and observation laws for networked control systems. The target audience primarily comprises researchers and experts in the field of control theory, but the book may also be beneficial for graduate students. .

  13. Understanding control of network spreading from network controllability

    Science.gov (United States)

    Sun, Peng Gang; Ma, Xiaoke

    2017-09-01

    How to control the spread of an epidemic or information is a great challenge for us. A dynamic network-based system’s structural controllability provides a new way to control spreading with the minimum input of external signals, and the dynamic system is controllable if the signals can drive it from any initial state to any desired final state in finite time. Therefore, we are motivated to develop a new framework by introducing spreading networks (SNs) to describe the spreading pathways from a global view, and we try to understand the control of the spreading by the structural controllability of the SNs. The SNs are transformed from original networks, in which each node is considered as a single spreading origin. The weights of directed links pointing at its direct contacts in the SNs denote the spreading abilities, which can be determined by a new probability function. Furthermore, we also investigate the impact of the dynamics of network structures on the framework. The results show that sparse homogeneous networks with a higher transmission probability tend to trigger a larger scale of diffusion, which is easier to control. We can also see that an epidemic or information is inclined to diffuse easily on the networks with strong community strengths and heterogeneous community sizes. From the structural controllability of the SNs, we observe that driver nodes for the control of the spread tend not to be the nodes located within the core of original networks or those with high-degree. In addition, the scale of diffusion, the number of driver nodes and positions of nodes are highly associated with the degree distribution of the original networks.

  14. Neural Networks in Control Applications

    DEFF Research Database (Denmark)

    Sørensen, O.

    The intention of this report is to make a systematic examination of the possibilities of applying neural networks in those technical areas, which are familiar to a control engineer. In other words, the potential of neural networks in control applications is given higher priority than a detailed...... study of the networks themselves. With this end in view the following restrictions have been made: - Amongst numerous neural network structures, only the Multi Layer Perceptron (a feed-forward network) is applied. - Amongst numerous training algorithms, only four algorithms are examined, all...... in a recursive form (sample updating). The simplest is the Back Probagation Error Algorithm, and the most complex is the recursive Prediction Error Method using a Gauss-Newton search direction. - Over-fitting is often considered to be a serious problem when training neural networks. This problem is specifically...

  15. Triangle network motifs predict complexes by complementing high-error interactomes with structural information

    Directory of Open Access Journals (Sweden)

    Labudde Dirk

    2009-06-01

    Full Text Available Abstract Background A lot of high-throughput studies produce protein-protein interaction networks (PPINs with many errors and missing information. Even for genome-wide approaches, there is often a low overlap between PPINs produced by different studies. Second-level neighbors separated by two protein-protein interactions (PPIs were previously used for predicting protein function and finding complexes in high-error PPINs. We retrieve second level neighbors in PPINs, and complement these with structural domain-domain interactions (SDDIs representing binding evidence on proteins, forming PPI-SDDI-PPI triangles. Results We find low overlap between PPINs, SDDIs and known complexes, all well below 10%. We evaluate the overlap of PPI-SDDI-PPI triangles with known complexes from Munich Information center for Protein Sequences (MIPS. PPI-SDDI-PPI triangles have ~20 times higher overlap with MIPS complexes than using second-level neighbors in PPINs without SDDIs. The biological interpretation for triangles is that a SDDI causes two proteins to be observed with common interaction partners in high-throughput experiments. The relatively few SDDIs overlapping with PPINs are part of highly connected SDDI components, and are more likely to be detected in experimental studies. We demonstrate the utility of PPI-SDDI-PPI triangles by reconstructing myosin-actin processes in the nucleus, cytoplasm, and cytoskeleton, which were not obvious in the original PPIN. Using other complementary datatypes in place of SDDIs to form triangles, such as PubMed co-occurrences or threading information, results in a similar ability to find protein complexes. Conclusion Given high-error PPINs with missing information, triangles of mixed datatypes are a promising direction for finding protein complexes. Integrating PPINs with SDDIs improves finding complexes. Structural SDDIs partially explain the high functional similarity of second-level neighbors in PPINs. We estimate that

  16. Control and Optimization of Network in Networked Control System

    Directory of Open Access Journals (Sweden)

    Wang Zhiwen

    2014-01-01

    Full Text Available In order to avoid quality of performance (QoP degradation resulting from quality of service (QoS, the solution to network congestion from the point of control theory, which marks departure of our results from the existing methods, is proposed in this paper. The congestion and bandwidth are regarded as state and control variables, respectively; then, the linear time-invariant (LTI model between congestion state and bandwidth of network is established. Consequently, linear quadratic method is used to eliminate the network congestion by allocating bandwidth dynamically. At last, numerical simulation results are given to illustrate the effectiveness of this modeling approach.

  17. Network motif-based identification of transcription factor-target gene relationships by integrating multi-source biological data

    Directory of Open Access Journals (Sweden)

    de los Reyes Benildo G

    2008-04-01

    Full Text Available Abstract Background Integrating data from multiple global assays and curated databases is essential to understand the spatio-temporal interactions within cells. Different experiments measure cellular processes at various widths and depths, while databases contain biological information based on established facts or published data. Integrating these complementary datasets helps infer a mutually consistent transcriptional regulatory network (TRN with strong similarity to the structure of the underlying genetic regulatory modules. Decomposing the TRN into a small set of recurring regulatory patterns, called network motifs (NM, facilitates the inference. Identifying NMs defined by specific transcription factors (TF establishes the framework structure of a TRN and allows the inference of TF-target gene relationship. This paper introduces a computational framework for utilizing data from multiple sources to infer TF-target gene relationships on the basis of NMs. The data include time course gene expression profiles, genome-wide location analysis data, binding sequence data, and gene ontology (GO information. Results The proposed computational framework was tested using gene expression data associated with cell cycle progression in yeast. Among 800 cell cycle related genes, 85 were identified as candidate TFs and classified into four previously defined NMs. The NMs for a subset of TFs are obtained from literature. Support vector machine (SVM classifiers were used to estimate NMs for the remaining TFs. The potential downstream target genes for the TFs were clustered into 34 biologically significant groups. The relationships between TFs and potential target gene clusters were examined by training recurrent neural networks whose topologies mimic the NMs to which the TFs are classified. The identified relationships between TFs and gene clusters were evaluated using the following biological validation and statistical analyses: (1 Gene set enrichment

  18. Visibility graph motifs

    CERN Document Server

    Iacovacci, Jacopo

    2015-01-01

    Visibility algorithms transform time series into graphs and encode dynamical information in their topology, paving the way for graph-theoretical time series analysis as well as building a bridge between nonlinear dynamics and network science. In this work we introduce and study the concept of visibility graph motifs, smaller substructures that appear with characteristic frequencies. We develop a theory to compute in an exact way the motif profiles associated to general classes of deterministic and stochastic dynamics. We find that this simple property is indeed a highly informative and computationally efficient feature capable to distinguish among different dynamics and robust against noise contamination. We finally confirm that it can be used in practice to perform unsupervised learning, by extracting motif profiles from experimental heart-rate series and being able, accordingly, to disentangle meditative from other relaxation states. Applications of this general theory include the automatic classification a...

  19. A Network Traffic Control Enhancement Approach over Bluetooth Networks

    DEFF Research Database (Denmark)

    Son, L.T.; Schiøler, Henrik; Madsen, Ole Brun

    2003-01-01

    This paper analyzes network traffic control issues in Bluetooth data networks as convex optimization problem. We formulate the problem of maximizing of total network flows and minimizing the costs of flows. An adaptive distributed network traffic control scheme is proposed as an approximated...... solution of the stated optimization problem that satisfies quality of service requirements and topologically induced constraints in Bluetooth networks, such as link capacity and node resource limitations. The proposed scheme is decentralized and complies with frequent changes of topology as well...... as capacity limitations and flow requirements in the network. Simulation shows that the performance of Bluetooth networks could be improved by applying the adaptive distributed network traffic control scheme...

  20. Information and control in networks

    CERN Document Server

    Bernhardsson, Bo; Rantzer, Anders

    2014-01-01

    Information and Control in Networks demonstrates the way in which system dynamics and information flows intertwine as they evolve, and the central role played by information in the control of complex networked systems. It is a milestone on the road to that convergence from traditionally independent development of control theory and information theory which has emerged strongly in the last fifteen years, and is now a very active research field. In addition to efforts in control and information theory, the text is witness to strong research in such diverse fields as computer science, mathematics, and statistics. Aspects that are given specialist treatment include: ·                 data-rate theorems; ·                 computation and control over communication networks; ·                 decentralized stochastic control; ·                 Gaussian networks and Gaussian–Markov random fields; and ·                 routability ...

  1. Colored motifs reveal computational building blocks in the C. elegans brain.

    Directory of Open Access Journals (Sweden)

    Jifeng Qian

    Full Text Available BACKGROUND: Complex networks can often be decomposed into less complex sub-networks whose structures can give hints about the functional organization of the network as a whole. However, these structural motifs can only tell one part of the functional story because in this analysis each node and edge is treated on an equal footing. In real networks, two motifs that are topologically identical but whose nodes perform very different functions will play very different roles in the network. METHODOLOGY/PRINCIPAL FINDINGS: Here, we combine structural information derived from the topology of the neuronal network of the nematode C. elegans with information about the biological function of these nodes, thus coloring nodes by function. We discover that particular colorations of motifs are significantly more abundant in the worm brain than expected by chance, and have particular computational functions that emphasize the feed-forward structure of information processing in the network, while evading feedback loops. Interneurons are strongly over-represented among the common motifs, supporting the notion that these motifs process and transduce the information from the sensor neurons towards the muscles. Some of the most common motifs identified in the search for significant colored motifs play a crucial role in the system of neurons controlling the worm's locomotion. CONCLUSIONS/SIGNIFICANCE: The analysis of complex networks in terms of colored motifs combines two independent data sets to generate insight about these networks that cannot be obtained with either data set alone. The method is general and should allow a decomposition of any complex networks into its functional (rather than topological motifs as long as both wiring and functional information is available.

  2. Dynamic Network Security Control Using Software Defined Networking

    Science.gov (United States)

    2016-03-24

    not subject to copyright protection in the United States. AFIT-ENG-MS-16-M-049 DYNAMIC NETWORK SECURITY CONTROL USING SOFTWARE DEFINED NETWORKING... software and tools vetted by industry leaders in networking and security. After considering the technologies previously discussed, the four components...DYNAMIC NETWORK SECURITY CONTROL USING SOFTWARE DEFINED NETWORKING THESIS Michael C. Todd, Captain, USAF AFIT-ENG-MS-16-M-049 DEPARTMENT OF THE AIR

  3. Spectral coarse grained controllability of complex networks

    Science.gov (United States)

    Wang, Pei; Xu, Shuang

    2017-07-01

    With the accumulation of interaction data from various systems, a fundamental question in network science is how to reduce the sizes while keeping certain properties of complex networks. Combined the spectral coarse graining theory and the structural controllability of complex networks, we explore the structural controllability of undirected complex networks during coarse graining processes. We evidence that the spectral coarse grained controllability (SCGC) properties for the Erdös-Rényi (ER) random networks, the scale-free (SF) random networks and the small-world (SW) random networks are distinct from each other. The SW networks are very robust, while the SF networks are sensitive during the coarse graining processes. As an emergent properties for the dense ER networks, during the coarse graining processes, there exists a threshold value of the coarse grained sizes, which separates the controllability of the reduced networks into robust and sensitive to coarse graining. Investigations on some real-world complex networks indicate that the SCGC properties are varied among different categories and different kinds of networks, some highly organized social or biological networks are more difficult to be controlled, while many man-made power networks and infrastructure networks can keep the controllability properties during the coarse graining processes. Furthermore, we speculate that the SCGC properties of complex networks may depend on their degree distributions. The associated investigations have potential implications in the control of large-scale complex networks, as well as in the understanding of the organization of complex networks.

  4. Virtualized Network Control. Final Report

    Energy Technology Data Exchange (ETDEWEB)

    Ghani, Nasir [Univ. of New Mexico, Albuquerque, NM (United States)

    2013-02-01

    This document is the final report for the Virtualized Network Control (VNC) project, which was funded by the United States Department of Energy (DOE) Office of Science. This project was also informally referred to as Advanced Resource Computation for Hybrid Service and TOpology NEtworks (ARCHSTONE). This report provides a summary of the project's activities, tasks, deliverable, and accomplishments. It also provides a summary of the documents, software, and presentations generated as part of this projects activities. Namely, the Appendix contains an archive of the deliverables, documents, and presentations generated a part of this project.

  5. Controllable Molecular Packing Motif and Overlap Type in Organic Nanomaterials for Advanced Optical Properties

    Directory of Open Access Journals (Sweden)

    Taoyu Zou

    2018-01-01

    Full Text Available The optical properties of organic materials are very sensitive to subtle structural modification, and a proper understanding of the structure-property relationship is essential to improve the performance of organic electronic devices. The phase transitions of the η-CuPc to the α-CuPc, then to the β-CuPc were investigated using In situ X-ray diffraction and the differential scanning calorimetry (DSC. The five stages in the phase-transition process from low to high-temperature were observed, which consisted of (1 the η-CuPc; (2 a mixture of the η- and α-CuPc; (3 a mixture of the η-, α- and β-CuPc; (4 a mixture of the α- and β-CuPc; and (5 the β-CuPc. The vibrational and optical properties at different phase-transition stages were correlated to molecular packing motif and molecule overlap type through systematic analyses of the Fourier–transform infrared, Raman and UV-VIS spectra. Moreover, the mechanism for the morphology evolution was also discussed in detail.

  6. The MHC motif viewer

    DEFF Research Database (Denmark)

    Rapin, Nicolas Philippe Jean-Pierre; Hoof, Ilka; Lund, Ole

    2010-01-01

    In vertebrates, the onset of cellular immune reactions is controlled by presentation of peptides in complex with major histocompatibility complex (MHC) molecules to T cell receptors. In humans, MHCs are called human leukocyte antigens (HLAs). Different MHC molecules present different subsets...... is hampered by the lack of tools for browsing and comparing specificity of these molecules. We have developed a Web server, MHC Motif Viewer, which allows the display of the binding motif for MHC class I proteins for human, chimpanzee, rhesus monkey, mouse, and swine, as well as HLA-DR protein sequences...

  7. Controllability of the better chosen partial networks

    Science.gov (United States)

    Liu, Xueming; Pan, Linqiang

    2016-08-01

    How to control large complex networks is a great challenge. Recent studies have proved that the whole network can be sufficiently steered by injecting control signals into a minimum set of driver nodes, and the minimum numbers of driver nodes for many real networks are high, indicating that it is difficult to control them. For some large natural and technological networks, it is impossible and not feasible to control the full network. For example, in biological networks like large-scale gene regulatory networks it is impossible to control all the genes. This prompts us to explore the question how to choose partial networks that are easy for controlling and important in networked systems. In this work, we propose a method to achieve this goal. By computing the minimum driver nodes densities of the partial networks of Erdös-Rényi (ER) networks, scale-free (SF) networks and 23 real networks, we find that our method performs better than random method that chooses nodes randomly. Moreover, we find that the nodes chosen by our method tend to be the essential elements of the whole systems, via studying the nodes chosen by our method of a real human signaling network and a human protein interaction network and discovering that the chosen nodes from these networks tend to be cancer-associated genes. The implementation of our method shows some interesting connections between the structure and the controllability of networks, improving our understanding of the control principles of complex systems.

  8. Unravelling daily human mobility motifs.

    Science.gov (United States)

    Schneider, Christian M; Belik, Vitaly; Couronné, Thomas; Smoreda, Zbigniew; González, Marta C

    2013-07-06

    Human mobility is differentiated by time scales. While the mechanism for long time scales has been studied, the underlying mechanism on the daily scale is still unrevealed. Here, we uncover the mechanism responsible for the daily mobility patterns by analysing the temporal and spatial trajectories of thousands of persons as individual networks. Using the concept of motifs from network theory, we find only 17 unique networks are present in daily mobility and they follow simple rules. These networks, called here motifs, are sufficient to capture up to 90 per cent of the population in surveys and mobile phone datasets for different countries. Each individual exhibits a characteristic motif, which seems to be stable over several months. Consequently, daily human mobility can be reproduced by an analytically tractable framework for Markov chains by modelling periods of high-frequency trips followed by periods of lower activity as the key ingredient.

  9. Robustness of network controllability in cascading failure

    Science.gov (United States)

    Chen, Shi-Ming; Xu, Yun-Fei; Nie, Sen

    2017-04-01

    It is demonstrated that controlling complex networks in practice needs more inputs than that predicted by the structural controllability framework. Besides, considering the networks usually faces to the external or internal failure, we define parameters to evaluate the control cost and the variation of controllability after cascades, exploring the effect of number of control inputs on the controllability for random networks and scale-free networks in the process of cascading failure. For different topological networks, the results show that the robustness of controllability will be stronger through allocating different control inputs and edge capacity.

  10. Comprehensive Identification of Glycated Peptides and Their Glycation Motifs in Plasma and Erythrocytes of Control and Diabetic Subjects

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Qibin; Monroe, Matthew E.; Schepmoes, Athena A.; Clauss, Therese RW; Gritsenko, Marina A.; Meng, Da; Petyuk, Vladislav A.; Smith, Richard D.; Metz, Thomas O.

    2011-07-01

    Non-enzymatic glycation of proteins is implicated in diabetes mellitus and its related complications. In this report, we extend our previous development and refinement of proteomics-based methods for the analysis of non-enzymatically glycated proteins to comprehensively identify glycated proteins in normal and diabetic human plasma and erythrocytes. Using immunodepletion, enrichment, and fractionation strategies, we identified 7749 unique glycated peptides, corresponding to 3742 unique glycated proteins. Semi-quantitative comparisons revealed a number of proteins with glycation levels significantly increased in diabetes relative to control samples and that erythrocyte proteins are more extensively glycated than plasma proteins. A glycation motif analysis revealed amino acids that are favored more than others in the protein primary structures in the vicinity of the glycation sites in both sample types. The glycated peptides and corresponding proteins reported here provide a foundation for the potential identification of novel markers for diabetes, glycemia, or diabetic complications.

  11. Congestion control in satellite networks

    Science.gov (United States)

    Byun, Do Jun

    Due to exponential increases in internet traffic, Active Queue Management (AQM) has been heavily studied by numerous researchers. However, little is known about AQM in satellite networks. A microscopic examination of queueing behavior in satellite networks is conducted to identify problems with applying existing AQM methods. A new AQM method is proposed to overcome the problems and it is validated using a realistic emulation environment and a mathematical model. Three problems that were discovered during the research are discussed in this dissertation. The first problem is oscillatory queueing, which is caused by high buffering due to Performance Enhancing Proxy (PEP) in satellite networks where congestion control after the PEP buffering does not effectively control traffic senders. Existing AQMs that can solve this problem have tail drop queueing that results in consecutive packet drops (global synchronization). A new AQM method called Adaptive Virtual Queue Random Early Detection (AVQRED) is proposed to solve this problem. The second problem is unfair bandwidth sharing caused by inaccurate measurements of per-flow bandwidth usage. AVQRED is enhanced to accurately measure per-flow bandwidth usage to solve this problem without adding much complexity to the algorithm. The third problem is queueing instability caused by buffer flow control where TCP receive windows are adjusted to flow control traffic senders instead of dropping received packets during congestion. Although buffer flow control is quite attractive to satellite networks, queueing becomes unstable because accepting packets instead of dropping them aggravates the congestion level. Furthermore, buffer flow control has abrupt reductions in the TCP receive window size due to high PEP buffering causing more instability. AVQRED with packet drop is proposed to solve this problem. Networks with scarce bandwidth and high propagation delays can not afford to have an unstable AQM. In this research, three problems

  12. Proxy SDN Controller for Wireless Networks

    Directory of Open Access Journals (Sweden)

    Won-Suk Kim

    2016-01-01

    Full Text Available Management of wireless networks as well as wired networks by using software-defined networking (SDN has been highlighted continually. However, control features of a wireless network differ from those of a wired network in several aspects. In this study, we identify the various inefficient points when controlling and managing wireless networks by using SDN and propose SDN-based control architecture called Proxcon to resolve these problems. Proxcon introduces the concept of a proxy SDN controller (PSC for the wireless network control, and the PSC entrusted with the role of a main controller performs control operations and provides the latest network state for a network administrator. To address the control inefficiency, Proxcon supports offloaded SDN operations for controlling wireless networks by utilizing the PSC, such as local control by each PSC, hybrid control utilizing the PSC and the main controller, and locally cooperative control utilizing the PSCs. The proposed architecture and the newly supported control operations can enhance scalability and response time when the logically centralized control plane responds to the various wireless network events. Through actual experiments, we verified that the proposed architecture could address the various control issues such as scalability, response time, and control overhead.

  13. Opinion control in complex networks

    Science.gov (United States)

    Masuda, Naoki

    2015-03-01

    In many political elections, the electorate appears to be a composite of partisan and independent voters. Given that partisans are not likely to convert to a different party, an important goal for a political party could be to mobilize independent voters toward the party with the help of strong leadership, mass media, partisans, and the effects of peer-to-peer influence. Based on the exact solution of classical voter model dynamics in the presence of perfectly partisan voters (i.e., zealots), we propose a computational method that uses pinning control strategy to maximize the share of a party in a social network of independent voters. The party, corresponding to the controller or zealots, optimizes the nodes to be controlled given the information about the connectivity of independent voters and the set of nodes that the opposing party controls. We show that controlling hubs is generally a good strategy, but the optimized strategy is even better. The superiority of the optimized strategy is particularly eminent when the independent voters are connected as directed (rather than undirected) networks.

  14. Flexible Tube-Based Network Control Project

    Data.gov (United States)

    National Aeronautics and Space Administration — The Innovation Laboratory, Inc. builds a control system which controls the topology of an air traffic flow network and the network flow properties which enables Air...

  15. Controllability of flow-conservation networks

    Science.gov (United States)

    Zhao, Chen; Zeng, An; Jiang, Rui; Yuan, Zhengzhong; Wang, Wen-Xu

    2017-07-01

    The ultimate goal of exploring complex networks is to control them. As such, controllability of complex networks has been intensively investigated. Despite recent advances in studying the impact of a network's topology on its controllability, a comprehensive understanding of the synergistic impact of network topology and dynamics on controllability is still lacking. Here, we explore the controllability of flow-conservation networks, trying to identify the minimal number of driver nodes that can guide the network to any desirable state. We develop a method to analyze the controllability on flow-conservation networks based on exact controllability theory, transforming the original analysis on adjacency matrix to Laplacian matrix. With this framework, we systematically investigate the impact of some key factors of networks, including link density, link directionality, and link polarity, on the controllability of these networks. We also obtain the analytical equations by investigating the network's structural properties approximatively and design the efficient tools. Finally, we consider some real networks with flow dynamics, finding that their controllability is significantly different from that predicted by only considering the topology. These findings deepen our understanding of network controllability with flow-conservation dynamics and provide a general framework to incorporate real dynamics in the analysis of network controllability.

  16. Constrained target controllability of complex networks

    Science.gov (United States)

    Guo, Wei-Feng; Zhang, Shao-Wu; Wei, Ze-Gang; Zeng, Tao; Liu, Fei; Zhang, Jingsong; Wu, Fang-Xiang; Chen, Luonan

    2017-06-01

    It is of great theoretical interest and practical significance to study how to control a system by applying perturbations to only a few driver nodes. Recently, a hot topic of modern network researches is how to determine driver nodes that allow the control of an entire network. However, in practice, to control a complex network, especially a biological network, one may know not only the set of nodes which need to be controlled (i.e. target nodes), but also the set of nodes to which only control signals can be applied (i.e. constrained control nodes). Compared to the general concept of controllability, we introduce the concept of constrained target controllability (CTC) of complex networks, which concerns the ability to drive any state of target nodes to their desirable state by applying control signals to the driver nodes from the set of constrained control nodes. To efficiently investigate the CTC of complex networks, we further design a novel graph-theoretic algorithm called CTCA to estimate the ability of a given network to control targets by choosing driver nodes from the set of constrained control nodes. We extensively evaluate the CTC of numerous real complex networks. The results indicate that biological networks with a higher average degree are easier to control than biological networks with a lower average degree, while electronic networks with a lower average degree are easier to control than web networks with a higher average degree. We also show that our CTCA can more efficiently produce driver nodes for target-controlling the networks than existing state-of-the-art methods. Moreover, we use our CTCA to analyze two expert-curated bio-molecular networks and compare to other state-of-the-art methods. The results illustrate that our CTCA can efficiently identify proven drug targets and new potentials, according to the constrained controllability of those biological networks.

  17. FastMotif: spectral sequence motif discovery

    National Research Council Canada - National Science Library

    Colombo, Nicoló; Vlassis, Nikos

    2015-01-01

    ... datasets produced by modern high-throughput sequencing technologies. We present FastMotif, a new motif discovery algorithm that is built on a recent machine learning technique referred to as Method of Moments...

  18. Adaptive optimization and control using neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Mead, W.C.; Brown, S.K.; Jones, R.D.; Bowling, P.S.; Barnes, C.W.

    1993-10-22

    Recent work has demonstrated the ability of neural-network-based controllers to optimize and control machines with complex, non-linear, relatively unknown control spaces. We present a brief overview of neural networks via a taxonomy illustrating some capabilities of different kinds of neural networks. We present some successful control examples, particularly the optimization and control of a small-angle negative ion source.

  19. Simplified LQG Control with Neural Networks

    DEFF Research Database (Denmark)

    Sørensen, O.

    1997-01-01

    A new neural network application for non-linear state control is described. One neural network is modelled to form a Kalmann predictor and trained to act as an optimal state observer for a non-linear process. Another neural network is modelled to form a state controller and trained to produce...

  20. Synchronizability on complex networks via pinning control

    Indian Academy of Sciences (India)

    pinning strategies have different pinning synchronizability on the same complex network, and the synchronizability with pinning control is consistent with one without pinning control in various complex networks. Keywords. Complex network; the pinning synchronization; synchronizability. PACS Nos 05.45.Xt; 89.75.−k; 05.45.

  1. Opinion control in complex networks

    CERN Document Server

    Masuda, Naoki

    2014-01-01

    In many instances of election, the electorate appears to be a composite of partisan and independent voters. Given that partisans are not likely to convert to a different party, a main goal for a party could be to mobilize independent voters toward the party with the help of strong leadership, mass media, partisans, and effects of peer-to-peer influence. Based on the exact solution of the classical voter model dynamics in the presence of perfectly partisan voters (i.e., zealots), we propose a computational method to maximize the share of the party in a social network of independent voters by pinning control strategy. The party, corresponding to the controller or zealots, optimizes the nodes to be controlled given the information about the connectivity of independent voters and the set of nodes that the opponent party controls. We show that controlling hubs is generally a good strategy, whereas the optimized strategy is even better. The superiority of the optimized strategy is particularly eminent when the inde...

  2. Controlling complex networks with conformity behavior

    Science.gov (United States)

    Wang, Xu-Wen; Nie, Sen; Wang, Wen-Xu; Wang, Bing-Hong

    2015-09-01

    Controlling complex networks accompanied by common conformity behavior is a fundamental problem in social and physical science. Conformity behavior that individuals tend to follow the majority in their neighborhood is common in human society and animal communities. Despite recent progress in understanding controllability of complex networks, the existent controllability theories cannot be directly applied to networks associated with conformity. Here we propose a simple model to incorporate conformity-based decision making into the evolution of a network system, which allows us to employ the exact controllability theory to explore the controllability of such systems. We offer rigorous theoretical results of controllability for representative regular networks. We also explore real networks in different fields and some typical model networks, finding some interesting results that are different from the predictions of structural and exact controllability theory in the absence of conformity. We finally present an example of steering a real social network to some target states to further validate our controllability theory and tools. Our work offers a more realistic understanding of network controllability with conformity behavior and can have potential applications in networked evolutionary games, opinion dynamics and many other complex networked systems.

  3. Model-based control of networked systems

    CERN Document Server

    Garcia, Eloy; Montestruque, Luis A

    2014-01-01

    This monograph introduces a class of networked control systems (NCS) called model-based networked control systems (MB-NCS) and presents various architectures and control strategies designed to improve the performance of NCS. The overall performance of NCS considers the appropriate use of network resources, particularly network bandwidth, in conjunction with the desired response of the system being controlled.   The book begins with a detailed description of the basic MB-NCS architecture that provides stability conditions in terms of state feedback updates . It also covers typical problems in NCS such as network delays, network scheduling, and data quantization, as well as more general control problems such as output feedback control, nonlinear systems stabilization, and tracking control.   Key features and topics include: Time-triggered and event-triggered feedback updates Stabilization of uncertain systems subject to time delays, quantization, and extended absence of feedback Optimal control analysis and ...

  4. Logistic control in automated transportation networks

    NARCIS (Netherlands)

    Ebben, Mark

    2001-01-01

    Increasing congestion problems lead to a search for alternative transportation systems. Automated transportation networks, possibly underground, are an option. Logistic control systems are essential for future implementations of such automated transportation networks. This book contributes to the

  5. Controller placement problem in industrial networks

    OpenAIRE

    Macián Ribera, Sergi

    2016-01-01

    SDN is the new trend in networks, for next Mobile and optical networks. Dimensioning, design and optimization of Software Defined Optical Networks. To be done at Technical University Munich (TUM) In this work the Controller Placement Problem (CPP) for SDN architecture is studied when it is applied to industrial networks. En este trabajo se estudia el problema CPP (controller placement problem) para la arquitectura SDN, aplicado a redes industriales. En aquest treball s'estudia el pro...

  6. The Organization of Controller Motifs Leading to Robust Plant Iron Homeostasis.

    Directory of Open Access Journals (Sweden)

    Oleg Agafonov

    Full Text Available Iron is an essential element needed by all organisms for growth and development. Because iron becomes toxic at higher concentrations iron is under homeostatic control. Plants face also the problem that iron in the soil is tightly bound to oxygen and difficult to access. Plants have therefore developed special mechanisms for iron uptake and regulation. During the last years key components of plant iron regulation have been identified. How these components integrate and maintain robust iron homeostasis is presently not well understood. Here we use a computational approach to identify mechanisms for robust iron homeostasis in non-graminaceous plants. In comparison with experimental results certain control arrangements can be eliminated, among them that iron homeostasis is solely based on an iron-dependent degradation of the transporter IRT1. Recent IRT1 overexpression experiments suggested that IRT1-degradation is iron-independent. This suggestion appears to be misleading. We show that iron signaling pathways under IRT1 overexpression conditions become saturated, leading to a breakdown in iron regulation and to the observed iron-independent degradation of IRT1. A model, which complies with experimental data places the regulation of cytosolic iron at the transcript level of the transcription factor FIT. Including the experimental observation that FIT induces inhibition of IRT1 turnover we found a significant improvement in the system's response time, suggesting a functional role for the FIT-mediated inhibition of IRT1 degradation. By combining iron uptake with storage and remobilization mechanisms a model is obtained which in a concerted manner integrates iron uptake, storage and remobilization. In agreement with experiments the model does not store iron during its high-affinity uptake. As an iron biofortification approach we discuss the possibility how iron can be accumulated even during high-affinity uptake.

  7. 2016 Network Games, Control, and Optimization Conference

    CERN Document Server

    Jimenez, Tania; Solan, Eilon

    2017-01-01

    This contributed volume offers a collection of papers presented at the 2016 Network Games, Control, and Optimization conference (NETGCOOP), held at the University of Avignon in France, November 23-25, 2016. These papers highlight the increasing importance of network control and optimization in many networking application domains, such as mobile and fixed access networks, computer networks, social networks, transportation networks, and, more recently, electricity grids and biological networks. Covering a wide variety of both theoretical and applied topics in the areas listed above, the authors explore several conceptual and algorithmic tools that are needed for efficient and robust control operation, performance optimization, and better understanding the relationships between entities that may be acting cooperatively or selfishly in uncertain and possibly adversarial environments. As such, this volume will be of interest to applied mathematicians, computer scientists, engineers, and researchers in other relate...

  8. Filtering and control of wireless networked systems

    CERN Document Server

    Zhang, Dan; Yu, Li

    2017-01-01

    This self-contained book, written by leading experts, offers a cutting-edge, in-depth overview of the filtering and control of wireless networked systems. It addresses the energy constraint and filter/controller gain variation problems, and presents both the centralized and the distributed solutions. The first two chapters provide an introduction to networked control systems and basic information on system analysis. Chapters (3–6) then discuss the centralized filtering of wireless networked systems, presenting different approaches to deal with energy efficiency and filter/controller gain variation problems. The next part (chapters 7–10) explores the distributed filtering of wireless networked systems, addressing the main problems of energy constraint and filter gain variation. The final part (chapters 11–14) focuses on the distributed control of wireless networked systems. networked systems for communication and control applications, the bo...

  9. PID Controller Based on Memristive CMAC Network

    Directory of Open Access Journals (Sweden)

    Lidan Wang

    2013-01-01

    Full Text Available Compound controller which consists of CMAC network and PID network is mainly used in control system, especially in robot control. It can realize nonlinear tracking control of the real-time dynamic trajectory and possesses good approximation effect. According to the structure and principle of the compound controller, memristor is introduced to CMAC network to be a compound controller in this paper. The new PID controller based on memristive CMAC network is built up by replacing the synapse in the original controller by memristors. The effect of curve approximation is obtained by MATLAB simulation experiments. This network improves the response and learning speed of the system and processes better robustness and antidisturbance performance.

  10. Control theory of digitally networked dynamic systems

    CERN Document Server

    Lunze, Jan

    2013-01-01

    The book gives an introduction to networked control systems and describes new modeling paradigms, analysis methods for event-driven, digitally networked systems, and design methods for distributed estimation and control. Networked model predictive control is developed as a means to tolerate time delays and packet loss brought about by the communication network. In event-based control the traditional periodic sampling is replaced by state-dependent triggering schemes. Novel methods for multi-agent systems ensure complete or clustered synchrony of agents with identical or with individual dynamic

  11. Additive Feed Forward Control with Neural Networks

    DEFF Research Database (Denmark)

    Sørensen, O.

    1999-01-01

    This paper demonstrates a method to control a non-linear, multivariable, noisy process using trained neural networks. The basis for the method is a trained neural network controller acting as the inverse process model. A training method for obtaining such an inverse process model is applied....... A suitable 'shaped' (low-pass filtered) reference is used to overcome problems with excessive control action when using a controller acting as the inverse process model. The control concept is Additive Feed Forward Control, where the trained neural network controller, acting as the inverse process model......, is placed in a supplementary pure feed-forward path to an existing feedback controller. This concept benefits from the fact, that an existing, traditional designed, feedback controller can be retained without any modifications, and after training the connection of the neural network feed-forward controller...

  12. Distributed medium access control in wireless networks

    CERN Document Server

    Wang, Ping

    2013-01-01

    This brief investigates distributed medium access control (MAC) with QoS provisioning for both single- and multi-hop wireless networks including wireless local area networks (WLANs), wireless ad hoc networks, and wireless mesh networks. For WLANs, an efficient MAC scheme and a call admission control algorithm are presented to provide guaranteed QoS for voice traffic and, at the same time, increase the voice capacity significantly compared with the current WLAN standard. In addition, a novel token-based scheduling scheme is proposed to provide great flexibility and facility to the network servi

  13. SLiMScape 3.x: a Cytoscape 3 app for discovery of Short Linear Motifs in protein interaction networks [version 1; referees: 2 approved

    Directory of Open Access Journals (Sweden)

    Emily Olorin

    2015-08-01

    Full Text Available Short linear motifs (SLiMs are small protein sequence patterns that mediate a large number of critical protein-protein interactions, involved in processes such as complex formation, signal transduction, localisation and stabilisation. SLiMs show rapid evolutionary dynamics and are frequently the targets of molecular mimicry by pathogens. Identifying enriched sequence patterns due to convergent evolution in non-homologous proteins has proven to be a successful strategy for computational SLiM prediction. Tools of the SLiMSuite package use this strategy, using a statistical model to identify SLiM enrichment based on the evolutionary relationships, amino acid composition and predicted disorder of the input proteins. The quality of input data is critical for successful SLiM prediction. Cytoscape provides a user-friendly, interactive environment to explore interaction networks and select proteins based on common features, such as shared interaction partners. SLiMScape embeds tools of the SLiMSuite package for de novo SLiM discovery (SLiMFinder and QSLiMFinder and identifying occurrences/enrichment of known SLiMs (SLiMProb within this interactive framework. SLiMScape makes it easier to (1 generate high quality hypothesis-driven datasets for these tools, and (2 visualise predicted SLiM occurrences within the context of the network. To generate new predictions, users can select nodes from a protein network or provide a set of Uniprot identifiers. SLiMProb also requires additional query motif input. Jobs are then run remotely on the SLiMSuite server (http://rest.slimsuite.unsw.edu.au for subsequent retrieval and visualisation. SLiMScape can also be used to retrieve and visualise results from jobs run directly on the server. SLiMScape and SLiMSuite are open source and freely available via GitHub under GNU licenses.

  14. Electronic and geometric structures of Au30 clusters: a network of 2e-superatom Au cores protected by tridentate protecting motifs with u3-S.

    Science.gov (United States)

    Tian, Zhimei; Cheng, Longjiu

    2016-01-14

    Density functional theory calculations have been performed to study the experimentally synthesized Au30S(SR)18 and two related Au30(SR)18 and Au30S2(SR)18 clusters. The patterns of thiolate ligands on the gold cores for the three thiolate-protected Au30 nanoclusters are on the basis of the "divide and protect" concept. A novel extended protecting motif with u3-S, S(Au2(SR)2)2AuSR, is discovered, which is termed the tridentate protecting motif. The Au cores of Au30S(SR)18, Au30(SR)18 and Au30S2(SR)18 clusters are Au17, Au20 and Au14, respectively. The superatom-network (SAN) model and the superatom complex (SAC) model are used to explain the chemical bonding patterns, which are verified by chemical bonding analysis based on the adaptive natural density partitioning (AdNDP) method and aromatic analysis on the basis of the nucleus-independent chemical shift (NICS) method. The Au17 core of the Au30S(SR)18 cluster can be viewed as a SAN of one Au6 superatom and four Au4 superatoms. The shape of the Au6 core is identical to that revealed in the recently synthesized Au18(SR)14 cluster. The Au20 core of the Au30(SR)18 cluster can be viewed as a SAN of two Au6 superatoms and four Au4 superatoms. The Au14 core of Au30S2(SR)18 can be regarded as a SAN of two pairs of two vertex-sharing Au4 superatoms. Meanwhile, the Au14 core is an 8e-superatom with 1S(2)1P(6) configuration. Our work may aid understanding and give new insights into the chemical synthesis of thiolate-protected Au clusters.

  15. Pengembangan Motif Batik Khas Bali

    Directory of Open Access Journals (Sweden)

    Irfa'ina Rohana Salma

    2016-04-01

    Full Text Available ABSTRAKIndustri batik berkembang pesat di Bali, namun motif-motif batiknya tidak mencerminkan identitas khas daerah. Oleh karena itu perlu diciptakan desain motif batik khas Bali yang sumber inspirasinya digali budaya dan alam Bali. Tujuan penelitian dan penciptaan seni ini adalah untuk menghasilkan motif batik yang mempunyai bentuk  unik dan karakteristik sehingga dapat mencerminkan budaya dan alam Bali. Metode yang digunakan yaitu pengumpulan data, perancangan motif, perwujudan menjadi batik, serta uji estetikanya. Dari penciptaan seni ini berhasil diciptakan 5 motif batik yaitu: (1 Motif Jepun Alit; (2 Motif Jepun Ageng; (3 Motif Sekar Jagad Bali; (4 Motif Teratai Banji; dan (5 Motif Poleng Biru. Berdasarkan hasil penilaian “Selera Estetika” diketahui bahwa motif yang paling banyak disukai adalah Motif Jepun Alit, Motif Sekar Jagad Bali,  dan Motif Teratai Banji. Kata kunci: Motif Jepun Alit, Motif Jepun Ageng, Motif Sekar Jagad Bali, Motif Teratai Banji, Motif Poleng Biru ABSTRACT Batik industry is growing rapidly in Bali, but its batik motifs do not reflect the typical regional identities. Therefore, it is necessary to create a distinctive design motif source of Bali excavated  from the repertoire of traditional Balinese arts and culture. The purpose of this research and its art creation is to produce batik motifs that have a unique shape and characteristics  to reflect the Balinese culture and natural surroundings. The method used by gathering and collecting data, designing motifs to  become the embodiment of batik. From the creation of this art had been created 5 motifs, namely: (1 Motif Jepun Alit; (2 Motif Jepun Ageng; (3 Motif Sekar Jagad Bali; (4 Motif Teratai Banji; and (5 Motif Poleng Biru. Based on the results of aesthetical assessment known that the most preferred motif are  Motif Jepun Alit, Motif Sekar Jagad Bali, and Motif Teratai Banji. Key words: Motif Jepun Alit, Motif Jepun Ageng, Motif Sekar Jagad Bali, Motif

  16. Cloud-based Networked Visual Servo Control

    DEFF Research Database (Denmark)

    Wu, Haiyan; Lu, Lei; Chen, Chih-Chung

    2013-01-01

    feedback, ii) a stabilizing control law for the networked visual servo control system with time-varying feedback time delay, and iii) a sending rate scheduling strategy aiming at reducing the communication network load. The performance of the networked visual servo control system with sending rate......The performance of vision-based control systems, in particular of highly dynamic vision-based motion control systems, is often limited by the low sampling rate of the visual feedback caused by the long image processing time. In order to overcome this problem, the networked visual servo control......, which integrates networked computational resources for cloud image processing, is considered in this article. The main contributions of this article are i) a real-time transport protocol for transmitting large volume image data on a cloud computing platform, which enables high sampling rate visual...

  17. Trends in Integrated Ship Control Networking

    DEFF Research Database (Denmark)

    Jørgensen, N.; Nielsen, Jens Frederik Dalsgaard

    1997-01-01

    Integrated Ship Control systems can be designed as robust, distributed, autonomous control systems. The EU funded ATOMOS and ATOMOS II projects involves both technical and non technical aspects of this process. A reference modelling concept giving an outline of a generic ISC system covering...... the network and the equipment connected to it, a framework for verification of network functionality and performance by simulation and a general distribution platform for ISC systems, The ATOMOS Network, are results of this work....

  18. Neural Networks for Non-linear Control

    DEFF Research Database (Denmark)

    Sørensen, O.

    1994-01-01

    This paper describes how a neural network, structured as a Multi Layer Perceptron, is trained to predict, simulate and control a non-linear process.......This paper describes how a neural network, structured as a Multi Layer Perceptron, is trained to predict, simulate and control a non-linear process....

  19. Stress controls the mechanics of collagen networks

    Science.gov (United States)

    Licup, Albert James; Münster, Stefan; Sharma, Abhinav; Sheinman, Michael; Jawerth, Louise M.; Fabry, Ben; Weitz, David A.; MacKintosh, Fred C.

    2015-01-01

    Collagen is the main structural and load-bearing element of various connective tissues, where it forms the extracellular matrix that supports cells. It has long been known that collagenous tissues exhibit a highly nonlinear stress–strain relationship, although the origins of this nonlinearity remain unknown. Here, we show that the nonlinear stiffening of reconstituted type I collagen networks is controlled by the applied stress and that the network stiffness becomes surprisingly insensitive to network concentration. We demonstrate how a simple model for networks of elastic fibers can quantitatively account for the mechanics of reconstituted collagen networks. Our model points to the important role of normal stresses in determining the nonlinear shear elastic response, which can explain the approximate exponential relationship between stress and strain reported for collagenous tissues. This further suggests principles for the design of synthetic fiber networks with collagen-like properties, as well as a mechanism for the control of the mechanics of such networks. PMID:26195769

  20. Discovery of Novel Human Gene Regulatory Modules from Gene Co-expression and Promoter Motif Analysis.

    Science.gov (United States)

    Ma, Shisong; Snyder, Michael; Dinesh-Kumar, Savithramma P

    2017-07-17

    Deciphering gene regulatory networks requires identification of gene expression modules. We describe a novel bottom-up approach to identify gene modules regulated by cis-regulatory motifs from a human gene co-expression network. Target genes of a cis-regulatory motif were identified from the network via the motif's enrichment or biased distribution towards transcription start sites in the promoters of co-expressed genes. A gene sub-network containing the target genes was extracted and used to derive gene modules. The analysis revealed known and novel gene modules regulated by the NF-Y motif. The binding of NF-Y proteins to these modules' gene promoters were verified using ENCODE ChIP-Seq data. The analyses also identified 8,048 Sp1 motif target genes, interestingly many of which were not detected by ENCODE ChIP-Seq. These target genes assemble into house-keeping, tissues-specific developmental, and immune response modules. Integration of Sp1 modules with genomic and epigenomic data indicates epigenetic control of Sp1 targets' expression in a cell/tissue specific manner. Finally, known and novel target genes and modules regulated by the YY1, RFX1, IRF1, and 34 other motifs were also identified. The study described here provides a valuable resource to understand transcriptional regulation of various human developmental, disease, or immunity pathways.

  1. Modeling, Optimization & Control of Hydraulic Networks

    DEFF Research Database (Denmark)

    Tahavori, Maryamsadat

    2014-01-01

    in water network is pressure management. By reducing the pressure in the water network, the leakage can be reduced significantly. Also it reduces the amount of energy consumption in water networks. The primary purpose of this work is to develop control algorithms for pressure control in water supply....... The nonlinear network model is derived based on the circuit theory. A suitable projection is used to reduce the state vector and to express the model in standard state-space form. Then, the controllability of nonlinear nonaffine hydraulic networks is studied. The Lie algebra-based controllability matrix is used...... to solve nonlinear optimal control problems. In the water supply system model, the hydraulic resistance of the valve is estimated by real data and it is considered to be a disturbance. The disturbance in our system is updated every 24 hours based on the amount of water usage by consumers every day. Model...

  2. Mining Conditional Phosphorylation Motifs.

    Science.gov (United States)

    Liu, Xiaoqing; Wu, Jun; Gong, Haipeng; Deng, Shengchun; He, Zengyou

    2014-01-01

    Phosphorylation motifs represent position-specific amino acid patterns around the phosphorylation sites in the set of phosphopeptides. Several algorithms have been proposed to uncover phosphorylation motifs, whereas the problem of efficiently discovering a set of significant motifs with sufficiently high coverage and non-redundancy still remains unsolved. Here we present a novel notion called conditional phosphorylation motifs. Through this new concept, the motifs whose over-expressiveness mainly benefits from its constituting parts can be filtered out effectively. To discover conditional phosphorylation motifs, we propose an algorithm called C-Motif for a non-redundant identification of significant phosphorylation motifs. C-Motif is implemented under the Apriori framework, and it tests the statistical significance together with the frequency of candidate motifs in a single stage. Experiments demonstrate that C-Motif outperforms some current algorithms such as MMFPh and Motif-All in terms of coverage and non-redundancy of the results and efficiency of the execution. The source code of C-Motif is available at: https://sourceforge. net/projects/cmotif/.

  3. 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.

  4. 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.

  5. Detecting controlling nodes of boolean regulatory networks.

    Science.gov (United States)

    Schober, Steffen; Kracht, David; Heckel, Reinhard; Bossert, Martin

    2011-10-11

    Boolean models of regulatory networks are assumed to be tolerant to perturbations. That qualitatively implies that each function can only depend on a few nodes. Biologically motivated constraints further show that functions found in Boolean regulatory networks belong to certain classes of functions, for example, the unate functions. It turns out that these classes have specific properties in the Fourier domain. That motivates us to study the problem of detecting controlling nodes in classes of Boolean networks using spectral techniques. We consider networks with unbalanced functions and functions of an average sensitivity less than 23k, where k is the number of controlling variables for a function. Further, we consider the class of 1-low networks which include unate networks, linear threshold networks, and networks with nested canalyzing functions. We show that the application of spectral learning algorithms leads to both better time and sample complexity for the detection of controlling nodes compared with algorithms based on exhaustive search. For a particular algorithm, we state analytical upper bounds on the number of samples needed to find the controlling nodes of the Boolean functions. Further, improved algorithms for detecting controlling nodes in large-scale unate networks are given and numerically studied.

  6. Controlling congestion on complex networks: fairness, efficiency and network structure.

    Science.gov (United States)

    Buzna, Ľuboš; Carvalho, Rui

    2017-08-22

    We consider two elementary (max-flow and uniform-flow) and two realistic (max-min fairness and proportional fairness) congestion control schemes, and analyse how the algorithms and network structure affect throughput, the fairness of flow allocation, and the location of bottleneck edges. The more realistic proportional fairness and max-min fairness algorithms have similar throughput, but path flow allocations are more unequal in scale-free than in random regular networks. Scale-free networks have lower throughput than their random regular counterparts in the uniform-flow algorithm, which is favoured in the complex networks literature. We show, however, that this relation is reversed on all other congestion control algorithms for a region of the parameter space given by the degree exponent γ and average degree 〈k〉. Moreover, the uniform-flow algorithm severely underestimates the network throughput of congested networks, and a rich phenomenology of path flow allocations is only present in the more realistic α-fair family of algorithms. Finally, we show that the number of paths passing through an edge characterises the location of a wide range of bottleneck edges in these algorithms. Such identification of bottlenecks could provide a bridge between the two fields of complex networks and congestion control.

  7. MPC control of water supply networks

    DEFF Research Database (Denmark)

    Baunsgaard, Kenneth Marx Hoe; Ravn, Ole; Kallesoe, Carsten Skovmose

    2016-01-01

    This paper investigates the modelling and predictive control of a drinking water supply network with the aim of minimising the energy and economic cost. A model predictive controller, MPC, is applied to a nonlinear model of a drinking water network that follows certain constraints to maintain......, controlling the drinking water supply network with the MPC showed reduction of the energy and the economic cost of running the system. This has been achieved by minimising actuator control effort and by shifting the actuator use towards the night time, where energy prices are lower. Along with energy cost...

  8. Exploring comprehensive within-motif dependence of transcription factor binding in Escherichia coli.

    Science.gov (United States)

    Yang, Chi; Chang, Chuan-Hsiung

    2015-11-23

    Modeling the binding of transcription factors helps to decipher the control logic behind transcriptional regulatory networks. Position weight matrix is commonly used to describe a binding motif but assumes statistical independence between positions. Although current approaches take within-motif dependence into account for better predictive performance, these models usually rely on prior knowledge and incorporate simple positional dependence to describe binding motifs. The inability to take complex within-motif dependence into account may result in an incomplete representation of binding motifs. In this work, we applied association rule mining techniques and constructed models to explore within-motif dependence for transcription factors in Escherichia coli. Our models can reflect transcription factor-DNA recognition where the explored dependence correlates with the binding specificity. We also propose a graphical representation of the explored within-motif dependence to illustrate the final binding configurations. Understanding the binding configurations also enables us to fine-tune or design transcription factor binding sites, and we attempt to present the configurations through exploring within-motif dependence.

  9. Emergence of bimodality in controlling complex networks

    CERN Document Server

    Jia, Tao; Csóka, Endre; Pósfai, Márton; Slotine, Jean-Jacques; Barabási, Albert-László

    2015-01-01

    Our ability to control complex systems is a fundamental challenge of contemporary science. Recently introduced tools to identify the driver nodes, nodes through which we can achieve full control, predict the existence of multiple control configurations, prompting us to classify each node in a network based on their role in control. Accordingly a node is critical, intermittent or redundant if it acts as a driver node in all, some or none of the control configurations. Here we develop an analytical framework to identify the category of each node, leading to the discovery of two distinct control modes in complex systems: centralized vs distributed control. We predict the control mode for an arbitrary network and show that one can alter it through small structural perturbations. The uncovered bimodality has implications from network security to organizational research and offers new insights into the dynamics and control of complex systems.

  10. Assessing the effects of symmetry on motif discovery and modeling.

    Directory of Open Access Journals (Sweden)

    Lala M Motlhabi

    Full Text Available BACKGROUND: Identifying the DNA binding sites for transcription factors is a key task in modeling the gene regulatory network of a cell. Predicting DNA binding sites computationally suffers from high false positives and false negatives due to various contributing factors, including the inaccurate models for transcription factor specificity. One source of inaccuracy in the specificity models is the assumption of asymmetry for symmetric models. METHODOLOGY/PRINCIPAL FINDINGS: Using simulation studies, so that the correct binding site model is known and various parameters of the process can be systematically controlled, we test different motif finding algorithms on both symmetric and asymmetric binding site data. We show that if the true binding site is asymmetric the results are unambiguous and the asymmetric model is clearly superior to the symmetric model. But if the true binding specificity is symmetric commonly used methods can infer, incorrectly, that the motif is asymmetric. The resulting inaccurate motifs lead to lower sensitivity and specificity than would the correct, symmetric models. We also show how the correct model can be obtained by the use of appropriate measures of statistical significance. CONCLUSIONS/SIGNIFICANCE: This study demonstrates that the most commonly used motif-finding approaches usually model symmetric motifs incorrectly, which leads to higher than necessary false prediction errors. It also demonstrates how alternative motif-finding methods can correct the problem, providing more accurate motif models and reducing the errors. Furthermore, it provides criteria for determining whether a symmetric or asymmetric model is the most appropriate for any experimental dataset.

  11. Multitasking of neuropeptide Y through the lens of motifs.

    Science.gov (United States)

    Myslobodsky, Michael

    2009-01-01

    Networks controlling ingestion-related peptides are also known to be the targets and signals for numerous other systems. Yet, their topological properties are still ill understood. The Ingenuity Pathway Analysis (IPA) was employed to represent molecules engaged in feeding as nodes, and the interactions between them as edges. Using extracted molecules as 'seeds' for core analysis it was possible to scrutinize some of the complex relationships of sub-networks and the so-called 'motifs' well outside the neighborhoods of their classical roles. Contrary to the requirements for modular structure, the orexigenic and anorexigenic neuropeptides do not represent two types of modules. They are densely interconnected. Functional annotations showed that the same molecules are recruited ad-hoc from a larger 'repository' and assembled into dynamic networks for executing diverse physiological functions and behaviors. Some molecules clustered in motifs appear as the multipurpose entities for cell-to-cell signaling, organismal development, cellular movement, growth and proliferation, endocrine system development and tissue morphology, etc. that apparently become active in early ontogeny. Based mostly on neuropeptide Y (NPY), my arguments here will focus on the potential benefits of exploring motifs in network controlling ingestion for generating insights for polypharmacy of obesity-related targets and co-morbid disorders. Recent patents describing new NPY receptor antagonists directed to treat obesity and cardiovascular disorders were cited.

  12. Advanced mobile networking, sensing, and controls.

    Energy Technology Data Exchange (ETDEWEB)

    Feddema, John Todd; Kilman, Dominique Marie; Byrne, Raymond Harry; Young, Joseph G.; Lewis, Christopher L.; Van Leeuwen, Brian P.; Robinett, Rush D. III; Harrington, John J.

    2005-03-01

    This report describes an integrated approach for designing communication, sensing, and control systems for mobile distributed systems. Graph theoretic methods are used to analyze the input/output reachability and structural controllability and observability of a decentralized system. Embedded in each network node, this analysis will automatically reconfigure an ad hoc communication network for the sensing and control task at hand. The graph analysis can also be used to create the optimal communication flow control based upon the spatial distribution of the network nodes. Edge coloring algorithms tell us that the minimum number of time slots in a planar network is equal to either the maximum number of adjacent nodes (or degree) of the undirected graph plus some small number. Therefore, the more spread out that the nodes are, the fewer number of time slots are needed for communication, and the smaller the latency between nodes. In a coupled system, this results in a more responsive sensor network and control system. Network protocols are developed to propagate this information, and distributed algorithms are developed to automatically adjust the number of time slots available for communication. These protocols and algorithms must be extremely efficient and only updated as network nodes move. In addition, queuing theory is used to analyze the delay characteristics of Carrier Sense Multiple Access (CSMA) networks. This report documents the analysis, simulation, and implementation of these algorithms performed under this Laboratory Directed Research and Development (LDRD) effort.

  13. Robust Multiobjective Controllability of Complex Neuronal Networks.

    Science.gov (United States)

    Tang, Yang; Gao, Huijun; Du, Wei; Lu, Jianquan; Vasilakos, Athanasios V; Kurths, Jurgen

    2016-01-01

    This paper addresses robust multiobjective identification of driver nodes in the neuronal network of a cat's brain, in which uncertainties in determination of driver nodes and control gains are considered. A framework for robust multiobjective controllability is proposed by introducing interval uncertainties and optimization algorithms. By appropriate definitions of robust multiobjective controllability, a robust nondominated sorting adaptive differential evolution (NSJaDE) is presented by means of the nondominated sorting mechanism and the adaptive differential evolution (JaDE). The simulation experimental results illustrate the satisfactory performance of NSJaDE for robust multiobjective controllability, in comparison with six statistical methods and two multiobjective evolutionary algorithms (MOEAs): nondominated sorting genetic algorithms II (NSGA-II) and nondominated sorting composite differential evolution. It is revealed that the existence of uncertainties in choosing driver nodes and designing control gains heavily affects the controllability of neuronal networks. We also unveil that driver nodes play a more drastic role than control gains in robust controllability. The developed NSJaDE and obtained results will shed light on the understanding of robustness in controlling realistic complex networks such as transportation networks, power grid networks, biological networks, etc.

  14. Congestion control and routing over satellite networks

    Science.gov (United States)

    Cao, Jinhua

    Satellite networks and transmissions find their application in fields of computer communications, telephone communications, television broadcasting, transportation, space situational awareness systems and so on. This thesis mainly focuses on two networking issues affecting satellite networking: network congestion control and network routing optimization. Congestion, which leads to long queueing delays, packet losses or both, is a networking problem that has drawn the attention of many researchers. The goal of congestion control mechanisms is to ensure high bandwidth utilization while avoiding network congestion by regulating the rate at which traffic sources inject packets into a network. In this thesis, we propose a stable congestion controller using data-driven, safe switching control theory to improve the dynamic performance of satellite Transmission Control Protocol/Active Queue Management (TCP/AQM) networks. First, the stable region of the Proportional-Integral (PI) parameters for a nominal model is explored. Then, a PI controller, whose parameters are adaptively tuned by switching among members of a given candidate set, using observed plant data, is presented and compared with some classical AQM policy examples, such as Random Early Detection (RED) and fixed PI control. A new cost detectable switching law with an interval cost function switching algorithm, which improves the performance and also saves the computational cost, is developed and compared with a law commonly used in the switching control literature. Finite-gain stability of the system is proved. A fuzzy logic PI controller is incorporated as a special candidate to achieve good performance at all nominal points with the available set of candidate controllers. Simulations are presented to validate the theory. An effocient routing algorithm plays a key role in optimizing network resources. In this thesis, we briefly analyze Low Earth Orbit (LEO) satellite networks, review the Cross Entropy (CE

  15. Control of autonomous robot using neural networks

    Science.gov (United States)

    Barton, Adam; Volna, Eva

    2017-07-01

    The aim of the article is to design a method of control of an autonomous robot using artificial neural networks. The introductory part describes control issues from the perspective of autonomous robot navigation and the current mobile robots controlled by neural networks. The core of the article is the design of the controlling neural network, and generation and filtration of the training set using ART1 (Adaptive Resonance Theory). The outcome of the practical part is an assembled Lego Mindstorms EV3 robot solving the problem of avoiding obstacles in space. To verify models of an autonomous robot behavior, a set of experiments was created as well as evaluation criteria. The speed of each motor was adjusted by the controlling neural network with respect to the situation in which the robot was found.

  16. Self-Control in Sparsely Coded Networks

    Science.gov (United States)

    Dominguez, D. R. C.; Bollé, D.

    1998-03-01

    A complete self-control mechanism is proposed in the dynamics of neural networks through the introduction of a time-dependent threshold, determined in function of both the noise and the pattern activity in the network. Especially for sparsely coded models this mechanism is shown to considerably improve the storage capacity, the basins of attraction, and the mutual information content.

  17. Neural PID Control Strategy for Networked Process Control

    Directory of Open Access Journals (Sweden)

    Jianhua Zhang

    2013-01-01

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

  18. FastMotif: spectral sequence motif discovery.

    Science.gov (United States)

    Colombo, Nicoló; Vlassis, Nikos

    2015-08-15

    Sequence discovery tools play a central role in several fields of computational biology. In the framework of Transcription Factor binding studies, most of the existing motif finding algorithms are computationally demanding, and they may not be able to support the increasingly large datasets produced by modern high-throughput sequencing technologies. We present FastMotif, a new motif discovery algorithm that is built on a recent machine learning technique referred to as Method of Moments. Based on spectral decompositions, our method is robust to model misspecifications and is not prone to locally optimal solutions. We obtain an algorithm that is extremely fast and designed for the analysis of big sequencing data. On HT-Selex data, FastMotif extracts motif profiles that match those computed by various state-of-the-art algorithms, but one order of magnitude faster. We provide a theoretical and numerical analysis of the algorithm's robustness and discuss its sensitivity with respect to the free parameters. The Matlab code of FastMotif is available from http://lcsb-portal.uni.lu/bioinformatics. vlassis@adobe.com Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  19. Optical network control plane for multi-domain networking

    DEFF Research Database (Denmark)

    Manolova, Anna Vasileva

    This thesis focuses on multi-domain routing for traffice engineering and survivability support in optical transport networks under the Generalized Multi-Protocol Label Switching (GMPLS) control framework. First, different extensions to the Border Gateway Protocol for multi-domain Traffic Engineer......This thesis focuses on multi-domain routing for traffice engineering and survivability support in optical transport networks under the Generalized Multi-Protocol Label Switching (GMPLS) control framework. First, different extensions to the Border Gateway Protocol for multi-domain Traffic...... process are not enough for efficient TE in mesh multi-domain networks. Enhancing the protocol with multi-path dissemination capability, combined with the employment of an end-to-end TE metric proves to be a highly efficient solution. Simulation results show good performance characteristics of the proposed...... is not as essential for improved network performance as the length of the provided paths. Second, the issue of multi-domain survivability support is analyzed. An AS-disjoint paths is beneficial not only for resilience support, but also for facilitating adequate network reactions to changes in the network, which...

  20. Inferring network connectivity by delayed feedback control.

    Directory of Open Access Journals (Sweden)

    Dongchuan Yu

    Full Text Available We suggest a control based approach to topology estimation of networks with N elements. This method first drives the network to steady states by a delayed feedback control; then performs structural perturbations for shifting the steady states M times; and finally infers the connection topology from the steady states' shifts by matrix inverse algorithm (M = N or l(1-norm convex optimization strategy applicable to estimate the topology of sparse networks from M << N perturbations. We discuss as well some aspects important for applications, such as the topology reconstruction quality and error sources, advantages and disadvantages of the suggested method, and the influence of (control perturbations, inhomegenity, sparsity, coupling functions, and measurement noise. Some examples of networks with Chua's oscillators are presented to illustrate the reliability of the suggested technique.

  1. MOCCS: Clarifying DNA-binding motif ambiguity using ChIP-Seq data.

    Science.gov (United States)

    Ozaki, Haruka; Iwasaki, Wataru

    2016-08-01

    As a key mechanism of gene regulation, transcription factors (TFs) bind to DNA by recognizing specific short sequence patterns that are called DNA-binding motifs. A single TF can accept ambiguity within its DNA-binding motifs, which comprise both canonical (typical) and non-canonical motifs. Clarification of such DNA-binding motif ambiguity is crucial for revealing gene regulatory networks and evaluating mutations in cis-regulatory elements. Although chromatin immunoprecipitation sequencing (ChIP-seq) now provides abundant data on the genomic sequences to which a given TF binds, existing motif discovery methods are unable to directly answer whether a given TF can bind to a specific DNA-binding motif. Here, we report a method for clarifying the DNA-binding motif ambiguity, MOCCS. Given ChIP-Seq data of any TF, MOCCS comprehensively analyzes and describes every k-mer to which that TF binds. Analysis of simulated datasets revealed that MOCCS is applicable to various ChIP-Seq datasets, requiring only a few minutes per dataset. Application to the ENCODE ChIP-Seq datasets proved that MOCCS directly evaluates whether a given TF binds to each DNA-binding motif, even if known position weight matrix models do not provide sufficient information on DNA-binding motif ambiguity. Furthermore, users are not required to provide numerous parameters or background genomic sequence models that are typically unavailable. MOCCS is implemented in Perl and R and is freely available via https://github.com/yuifu/moccs. By complementing existing motif-discovery software, MOCCS will contribute to the basic understanding of how the genome controls diverse cellular processes via DNA-protein interactions. Copyright © 2016 Elsevier Ltd. All rights reserved.

  2. Motif-based embedding for graph clustering

    Science.gov (United States)

    Lim, Sungsu; Lee, Jae-Gil

    2016-12-01

    Community detection in complex networks is a fundamental problem that has been extensively studied owing to its wide range of applications. However, because community detection methods typically rely on the relations between vertices in networks, they may fail to discover higher-order graph substructures, called the network motifs. In this paper, we propose a novel embedding method for graph clustering that considers higher-order relationships involving multiple vertices. We show that our embedding method, which we call motif-based embedding, is more effective in detecting communities than existing graph embedding methods, spectral embedding and force-directed embedding, both theoretically and experimentally.

  3. Next Generation Network Routing and Control Plane

    DEFF Research Database (Denmark)

    Fu, Rong

    proved, the dominating Border Gateway Protocol (BGP) cannot address all the issues that in inter-domain QoS routing. Thus a new protocol or network architecture has to be developed to be able to carry the inter-domain traffic with the QoS and TE consideration. Moreover, the current network control also......-domain. It is a routing component that flexibly supports path computation with different requirements, constraints and areas. It is also can be seen as part of NGN transport control plane, which integrates with the other functions. In the aspect of resource control, an NGN release Resource and Admission Control Functions...... of Service classes. Under the NGN context, there are plenty of proposals intending to accommodate the issues listed above. Path Computation Elements (PCE) proposed by IETF designs suitable network architecture that aiming at compute the QoS based paths for traffic transportation through intra- and inter...

  4. On the Design of Energy Efficient Optical Networks with Software Defined Networking Control Across Core and Access Networks

    DEFF Research Database (Denmark)

    Wang, Jiayuan; Yan, Ying; Dittmann, Lars

    2013-01-01

    This paper presents a Software Defined Networking (SDN) control plane based on an overlay GMPLS control model. The SDN control platform manages optical core networks (WDM/DWDM networks) and the associated access networks (GPON networks), which makes it possible to gather global information...

  5. Tobacco Control Research, Dissemination and Networking in ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    Tobacco Control Research, Dissemination and Networking in Lebanon. The Tobacco Control Research Group (TCRG), University of Beirut (AUB), is a multidisciplinary team of professionals from the health sciences, medicine, chemistry and engineering departments. The Group was established in 1999 with IDRC support ...

  6. Neural network topology design for nonlinear control

    Science.gov (United States)

    Haecker, Jens; Rudolph, Stephan

    2001-03-01

    Neural networks, especially in nonlinear system identification and control applications, are typically considered to be black-boxes which are difficult to analyze and understand mathematically. Due to this reason, an in- depth mathematical analysis offering insight into the different neural network transformation layers based on a theoretical transformation scheme is desired, but up to now neither available nor known. In previous works it has been shown how proven engineering methods such as dimensional analysis and the Laplace transform may be used to construct a neural controller topology for time-invariant systems. Using the knowledge of neural correspondences of these two classical methods, the internal nodes of the network could also be successfully interpreted after training. As further extension to these works, the paper describes the latest of a theoretical interpretation framework describing the neural network transformation sequences in nonlinear system identification and control. This can be achieved By incorporation of the method of exact input-output linearization in the above mentioned two transform sequences of dimensional analysis and the Laplace transformation. Based on these three theoretical considerations neural network topologies may be designed in special situations by pure translation in the sense of a structural compilation of the known classical solutions into their correspondent neural topology. Based on known exemplary results, the paper synthesizes the proposed approach into the visionary goals of a structural compiler for neural networks. This structural compiler for neural networks is intended to automatically convert classical control formulations into their equivalent neural network structure based on the principles of equivalence between formula and operator, and operator and structure which are discussed in detail in this work.

  7. Somatic surveillance: corporeal control through information networks

    OpenAIRE

    Monahan, Torin; Wall, Tyler

    2007-01-01

    Somatic surveillance is the increasingly invasive technological monitoring of and intervention into body functions. Within this type of surveillance regime, bodies are recast as nodes on vast information networks, enabling corporeal control through remote network commands, automated responses, or self-management practices. In this paper, we investigate three developments in somatic surveillance: nanotechnology systems for soldiers on the battlefield, commercial body-monitoring systems for hea...

  8. Social Network Privacy via Evolving Access Control

    Science.gov (United States)

    di Crescenzo, Giovanni; Lipton, Richard J.

    We study the problem of limiting privacy loss due to data shared in a social network, where the basic underlying assumptions are that users are interested in sharing data and cannot be assumed to constantly follow appropriate privacy policies. Note that if these two assumptions do not hold, social network privacy is theoretically very easy to achieve; for instance, via some form of access control and confidentiality transformation on the data.

  9. Decentralized control of ecological and biological networks through Evolutionary Network Control

    Directory of Open Access Journals (Sweden)

    Alessandro Ferrarini

    2016-09-01

    Full Text Available Evolutionary Network Control (ENC has been recently introduced to allow the control of any kind of ecological and biological networks, with an arbitrary number of nodes and links, acting from inside and/or outside. To date, ENC has been applied using a centralized approach where an arbitrary number of network nodes and links could be tamed. This approach has shown to be effective in the control of ecological and biological networks. However a decentralized control, where only one node and the correspondent input/output links are controlled, could be more economic from a computational viewpoint, in particular when the network is very large (i.e. big data. In this view, ENC is upgraded here to realize the decentralized control of ecological and biological nets.

  10. Scheduled Controller Design of Congestion Control Considering Network Resource Constraints

    Science.gov (United States)

    Naito, Hiroyuki; Azuma, Takehito; Fujita, Masayuki

    In this paper, we consider a dynamical model of computer networks and derive a synthesis method for congestion control. First, we show a model of TCP/AQM (Transmission Control Protocol/Active Queue Management) as a dynamical model of computer networks. The dynamical model of TCP/AQM networks consists of models of TCP window size, queue length and AQM mechanisms. Second, we propose to describe the dynamical model of TCP/AQM networks as linear systems with self-scheduling parameters, which also depend on information delay. Here we focus on the constraints on the maximum queue length and TCP window-size, which are the network resources in TCP/AQM networks. We derive TCP/AQM networks as the LPV system (linear parameter varying system) with information delay and self-scheduling parameter. We design a memoryless state feedback controller of the LPV system based on a gain-scheduling method. Finally, the effectiveness of the proposed method is evaluated by using MATLAB and the well-known ns-2 (Network Simulator Ver.2) simulator.

  11. Multi-layered control of Galectin-8 mediated autophagy during adenovirus cell entry through a conserved PPxY motif in the viral capsid.

    Directory of Open Access Journals (Sweden)

    Charlotte Montespan

    2017-02-01

    Full Text Available Cells employ active measures to restrict infection by pathogens, even prior to responses from the innate and humoral immune defenses. In this context selective autophagy is activated upon pathogen induced membrane rupture to sequester and deliver membrane fragments and their pathogen contents for lysosomal degradation. Adenoviruses, which breach the endosome upon entry, escape this fate by penetrating into the cytosol prior to autophagosome sequestration of the ruptured endosome. We show that virus induced membrane damage is recognized through Galectin-8 and sequesters the autophagy receptors NDP52 and p62. We further show that a conserved PPxY motif in the viral membrane lytic protein VI is critical for efficient viral evasion of autophagic sequestration after endosomal lysis. Comparing the wildtype with a PPxY-mutant virus we show that depletion of Galectin-8 or suppression of autophagy in ATG5-/- MEFs rescues infectivity of the PPxY-mutant virus while depletion of the autophagy receptors NDP52, p62 has only minor effects. Furthermore we show that wildtype viruses exploit the autophagic machinery for efficient nuclear genome delivery and control autophagosome formation via the cellular ubiquitin ligase Nedd4.2 resulting in reduced antigenic presentation. Our data thus demonstrate that a short PPxY-peptide motif in the adenoviral capsid permits multi-layered viral control of autophagic processes during entry.

  12. [The network of official medicines control laboratories].

    Science.gov (United States)

    Buchheit, K-H; Wanko, R

    2014-10-01

    Licensing, control and surveillance by competent authorities is the basis for ensuring efficacy, safety and quality of medicines in Europe. The control of the quality of medicines by national control laboratories, known as Official Medicines Control Laboratories (OMCLs) is an essential step in this process; it encompasses controls before and after granting a marketing authorisation. For certain groups of biomedical medicines (vaccines for human and veterinary use, medicines derived from human plasma) even each batch is controlled before it can be placed on the market. As single OMCLs would not be able to cope with their task, given the large number and diversity of medicines, in 1994 the OMCL network was founded upon initiative of the European Directorate for the Quality of Medicines & HealthCare, in close collaboration with the Commission of the European Union. Currently 68 OMCLs from 39 countries are part of the network. Prerequisite for the smooth operation of the OMCL network is the harmonisation of the quality management system of the individual OMCLs, based on the ISO 17025 standard, internal guidelines and the European Pharmacopoeia. Compliance with these standards is checked through regular audits, thus creating the basis for mutual recognition of test results. The collaboration in the OMCL network for the surveillance of the medicines market, the official control authority batch release and the fight against counterfeiting and illegal medicines enables OMCLs to keep pace with the developments in the field of medicines and to control the broad spectrum of medicines. In the 20 years since its start, the OMCL network has become a European success story.

  13. Motif signatures of transcribed enhancers

    KAUST Repository

    Kleftogiannis, Dimitrios

    2017-09-14

    In mammalian cells, transcribed enhancers (TrEn) play important roles in the initiation of gene expression and maintenance of gene expression levels in spatiotemporal manner. One of the most challenging questions in biology today is how the genomic characteristics of enhancers relate to enhancer activities. This is particularly critical, as several recent studies have linked enhancer sequence motifs to specific functional roles. To date, only a limited number of enhancer sequence characteristics have been investigated, leaving space for exploring the enhancers genomic code in a more systematic way. To address this problem, we developed a novel computational method, TELS, aimed at identifying predictive cell type/tissue specific motif signatures. We used TELS to compile a comprehensive catalog of motif signatures for all known TrEn identified by the FANTOM5 consortium across 112 human primary cells and tissues. Our results confirm that distinct cell type/tissue specific motif signatures characterize TrEn. These signatures allow discriminating successfully a) TrEn from random controls, proxy of non-enhancer activity, and b) cell type/tissue specific TrEn from enhancers expressed and transcribed in different cell types/tissues. TELS codes and datasets are publicly available at http://www.cbrc.kaust.edu.sa/TELS.

  14. The Verrucomicrobia LexA-binding Motif: Insights into the Evolutionary Dynamics of the SOS Response

    Directory of Open Access Journals (Sweden)

    Ivan Erill

    2016-07-01

    Full Text Available The SOS response is the primary bacterial mechanism to address DNA damage, coordinating multiple cellular processes that include DNA repair, cell division and translesion synthesis. In contrast to other regulatory systems, the composition of the SOS genetic network and the binding motif of its transcriptional repressor, LexA, have been shown to vary greatly across bacterial clades, making it an ideal system to study the co-evolution of transcription factors and their regulons. Leveraging comparative genomics approaches and prior knowledge on the core SOS regulon, here we define the binding motif of the Verrucomicrobia, a recently described phylum of emerging interest due to its association with eukaryotic hosts. Site directed mutagenesis of the Verrucomicrobium spinosum recA promoter confirms that LexA binds a 14 bp palindromic motif with consensus sequence TGTTC-N4-GAACA. Computational analyses suggest that recognition of this novel motif is determined primarily by changes in base-contacting residues of the third alpha helix of the LexA helix-turn-helix DNA binding motif. In conjunction with comparative genomics analysis of the LexA regulon in the Verrucomicrobia phylum, electrophoretic shift assays reveal that LexA binds to operators in the promoter region of DNA repair genes and a mutagenesis cassette in this organism, and identify previously unreported components of the SOS response. The identification of tandem LexA-binding sites generating instances of other LexA-binding motifs in the lexA gene promoter of Verrucomicrobia species leads us to postulate a novel mechanism for LexA-binding motif evolution. This model, based on gene duplication, successfully addresses outstanding questions in the intricate co-evolution of the LexA protein, its binding motif and the regulatory network it controls.

  15. Controls from remote through Social networks

    Directory of Open Access Journals (Sweden)

    Alessandra Ingrao

    2016-03-01

    Full Text Available The Author focuses on the recently reformed provisions regulating the employer’s power to control from remote the employees’ activities (art. 4 of the Workers Statute, with particular regard to controls performed by means of Social networks.Such controls are in fact extremely powerful due to the versatile and multi-purpose character of Social networks, which may also be used as a working device. A widespread case law shows indeed that employer’s controls may cost a worker his job.Therefore, after the reform, all employees will have to read carefully the employer’s Privacy policies, before accessing socials during the worktime to express opinions and/or frustrations.

  16. Controllable Buoys and Networked Buoy Systems

    Science.gov (United States)

    Davoodi, Faranak (Inventor); Davoudi, Farhooman (Inventor)

    2017-01-01

    Buoyant sensor networks are described, comprising floating buoys with sensors and energy harvesting capabilities. The buoys can control their buoyancy and motion, and can organize communication in a distributed fashion. Some buoys may have tethered underwater vehicles with a smart spooling system that allows the vehicles to dive deep underwater while remaining in communication and connection with the buoys.

  17. Distributed control network for optogenetic experiments

    Science.gov (United States)

    Kasprowicz, G.; Juszczyk, B.; Mankiewicz, L.

    2014-11-01

    Nowadays optogenetic experiments are constructed to examine social behavioural relations in groups of animals. A novel concept of implantable device with distributed control network and advanced positioning capabilities is proposed. It is based on wireless energy transfer technology, micro-power radio interface and advanced signal processing.

  18. Efficient exact motif discovery.

    Science.gov (United States)

    Marschall, Tobias; Rahmann, Sven

    2009-06-15

    The motif discovery problem consists of finding over-represented patterns in a collection of biosequences. It is one of the classical sequence analysis problems, but still has not been satisfactorily solved in an exact and efficient manner. This is partly due to the large number of possibilities of defining the motif search space and the notion of over-representation. Even for well-defined formalizations, the problem is frequently solved in an ad hoc manner with heuristics that do not guarantee to find the best motif. We show how to solve the motif discovery problem (almost) exactly on a practically relevant space of IUPAC generalized string patterns, using the p-value with respect to an i.i.d. model or a Markov model as the measure of over-representation. In particular, (i) we use a highly accurate compound Poisson approximation for the null distribution of the number of motif occurrences. We show how to compute the exact clump size distribution using a recently introduced device called probabilistic arithmetic automaton (PAA). (ii) We define two p-value scores for over-representation, the first one based on the total number of motif occurrences, the second one based on the number of sequences in a collection with at least one occurrence. (iii) We describe an algorithm to discover the optimal pattern with respect to either of the scores. The method exploits monotonicity properties of the compound Poisson approximation and is by orders of magnitude faster than exhaustive enumeration of IUPAC strings (11.8 h compared with an extrapolated runtime of 4.8 years). (iv) We justify the use of the proposed scores for motif discovery by showing our method to outperform other motif discovery algorithms (e.g. MEME, Weeder) on benchmark datasets. We also propose new motifs on Mycobacterium tuberculosis. The method has been implemented in Java. It can be obtained from http://ls11-www.cs.tu-dortmund.de/people/marschal/paa_md/.

  19. Independent control of gamma and theta activity by distinct interneuron networks in the olfactory bulb.

    Science.gov (United States)

    Fukunaga, Izumi; Herb, Jan T; Kollo, Mihaly; Boyden, Edward S; Schaefer, Andreas T

    2014-09-01

    Circuits in the brain possess the ability to orchestrate activities on different timescales, but the manner in which distinct circuits interact to sculpt diverse rhythms remains unresolved. The olfactory bulb is a classic example of a place in which slow theta and fast gamma rhythms coexist. Furthermore, inhibitory interneurons that are generally implicated in rhythm generation are segregated into distinct layers, neatly separating local and global motifs. We combined intracellular recordings in vivo with circuit-specific optogenetic interference to examine the contribution of inhibition to rhythmic activity in the mouse olfactory bulb. We found that the two inhibitory circuits controlled rhythms on distinct timescales: local, glomerular networks coordinated theta activity, regulating baseline and odor-evoked inhibition, whereas granule cells orchestrated gamma synchrony and spike timing. Notably, granule cells did not contribute to baseline rhythms or sniff-coupled odor-evoked inhibition. Thus, activities on theta and gamma timescales are controlled by separate, dissociable inhibitory networks in the olfactory bulb.

  20. Towards Controlling Latency in Wireless Networks

    KAUST Repository

    Bouacida, Nader

    2017-04-24

    Wireless networks are undergoing an unprecedented revolution in the last decade. With the explosion of delay-sensitive applications in the Internet (i.e., online gaming and VoIP), latency becomes a major issue for the development of wireless technology. Taking advantage of the significant decline in memory prices, industrialists equip the network devices with larger buffering capacities to improve the network throughput by limiting packets drops. Over-buffering results in increasing the time that packets spend in the queues and, thus, introducing more latency in networks. This phenomenon is known as “bufferbloat”. While throughput is the dominant performance metric, latency also has a huge impact on user experience not only for real-time applications but also for common applications like web browsing, which is sensitive to latencies in order of hundreds of milliseconds. Concerns have arisen about designing sophisticated queue management schemes to mitigate the effects of such phenomenon. My thesis research aims to solve bufferbloat problem in both traditional half-duplex and cutting-edge full-duplex wireless systems by reducing delay while maximizing wireless links utilization and fairness. Our work shed lights on buffer management algorithms behavior in wireless networks and their ability to reduce latency resulting from excessive queuing delays inside oversized static network buffers without a significant loss in other network metrics. First of all, we address the problem of buffer management in wireless full-duplex networks by using Wireless Queue Management (WQM), which is an active queue management technique for wireless networks. Our solution is based on Relay Full-Duplex MAC (RFD-MAC), an asynchronous media access control protocol designed for relay full-duplexing. Compared to the default case, our solution reduces the end-to-end delay by two orders of magnitude while achieving similar throughput in most of the cases. In the second part of this thesis

  1. Control of Recombination Directionality by the Listeria Phage A118 Protein Gp44 and the Coiled-Coil Motif of Its Serine Integrase.

    Science.gov (United States)

    Mandali, Sridhar; Gupta, Kushol; Dawson, Anthony R; Van Duyne, Gregory D; Johnson, Reid C

    2017-06-01

    The serine integrase of phage A118 catalyzes integrative recombination between attP on the phage and a specific attB locus on the chromosome of Listeria monocytogenes , but it is unable to promote excisive recombination between the hybrid attL and attR sites found on the integrated prophage without assistance by a recombination directionality factor (RDF). We have identified and characterized the phage-encoded RDF Gp44, which activates the A118 integrase for excision and inhibits integration. Gp44 binds to the C-terminal DNA binding domain of integrase, and we have localized the primary binding site to be within the mobile coiled-coil (CC) motif but distinct from the distal tip of the CC that is required for recombination. This interaction is sufficient to inhibit integration, but a second interaction involving the N-terminal end of Gp44 is also required to activate excision. We provide evidence that these two contacts modulate the trajectory of the CC motifs as they extend out from the integrase core in a manner dependent upon the identities of the four att sites. Our results support a model whereby Gp44 shapes the Int-bound complexes to control which att sites can synapse and recombine. IMPORTANCE Serine integrases mediate directional recombination between bacteriophage and bacterial chromosomes. These highly regulated site-specific recombination reactions are integral to the life cycle of temperate phage and, in the case of Listeria monocytogenes lysogenized by A118 family phage, are an essential virulence determinant. Serine integrases are also utilized as tools for genetic engineering and synthetic biology because of their exquisite unidirectional control of the DNA exchange reaction. Here, we identify and characterize the recombination directionality factor (RDF) that activates excision and inhibits integration reactions by the phage A118 integrase. We provide evidence that the A118 RDF binds to and modulates the trajectory of the long coiled-coil motif that

  2. Fusion Control of Flexible Logic Control and Neural Network

    Directory of Open Access Journals (Sweden)

    Lihua Fu

    2014-01-01

    Full Text Available Based on the basic physical meaning of error E and error variety EC, this paper analyzes the logical relationship between them and uses Universal Combinatorial Operation Model in Universal Logic to describe it. Accordingly, a flexible logic control method is put forward to realize effective control on multivariable nonlinear system. In order to implement fusion control with artificial neural network, this paper proposes a new neuron model of Zero-level Universal Combinatorial Operation in Universal Logic. And the artificial neural network of flexible logic control model is implemented based on the proposed neuron model. Finally, stability control, anti-interference control of double inverted-pendulum system, and free walking of cart pendulum system on a level track are realized, showing experimentally the feasibility and validity of this method.

  3. Plug & Play Control of Hydraulic Networks

    DEFF Research Database (Denmark)

    Jensen, Tom Nørgaard

    2012-01-01

    Process Control research program, which the work presented here is a part of. An industrial case study involving a large-scale hydraulic network with non-linear dynamics is studied. The hydraulic network underlies a district heating system, which provides heating water to a number of end-users in a city...... district. The case study considers a novel approach to the design of district heating systems in which the diameter of the pipes used in the system is reduced in order to reduce the heat losses in the system, thereby making it profitable to provide district heating to areas with low energy demands. The new...

  4. Flexible body control using neural networks

    Science.gov (United States)

    Mccullough, Claire L.

    1992-01-01

    Progress is reported on the control of Control Structures Interaction suitcase demonstrator (a flexible structure) using neural networks and fuzzy logic. It is concluded that while control by neural nets alone (i.e., allowing the net to design a controller with no human intervention) has yielded less than optimal results, the neural net trained to emulate the existing fuzzy logic controller does produce acceptible system responses for the initial conditions examined. Also, a neural net was found to be very successful in performing the emulation step necessary for the anticipatory fuzzy controller for the CSI suitcase demonstrator. The fuzzy neural hybrid, which exhibits good robustness and noise rejection properties, shows promise as a controller for practical flexible systems, and should be further evaluated.

  5. King post truss as a motif for internal structure of (meta)material with controlled elastic properties

    Science.gov (United States)

    Turco, Emilio; Giorgio, Ivan; Misra, Anil; dell'Isola, Francesco

    2017-10-01

    One of the most interesting challenges in the modern theory of materials consists in the determination of those microstructures which produce, at the macro-level, a class of metamaterials whose elastic range is many orders of magnitude wider than the one exhibited by `standard' materials. In dell'Isola et al. (2015 Zeitschrift für angewandte Mathematik und Physik 66, 3473-3498. (doi:10.1007/s00033-015-0556-4)), it was proved that, with a pantographic microstructure constituted by `long' micro-beams it is possible to obtain metamaterials whose elastic range spans up to an elongation exceeding 30%. In this paper, we demonstrate that the same behaviour can be obtained by means of an internal microstructure based on a king post motif. This solution shows many advantages: it involves only microbeams; all constituting beams are undergoing only extension or compression; all internal constraints are terminal pivots. While the elastic deformation energy can be determined as easily as in the case of long-beam microstructure, the proposed design seems to have obvious remarkable advantages: it seems to be more damage resistant and therefore to be able to have a wider elastic range; it can be realized with the same three-dimensional printing technology; it seems to be less subject to compression buckling. The analysis which we present here includes: (i) the determination of Hencky-type discrete models for king post trusses, (ii) the application of an effective integration scheme to a class of relevant deformation tests for the proposed metamaterial and (iii) the numerical determination of an equivalent second gradient continuum model. The numerical tools which we have developed and which are presented here can be readily used to develop an extensive measurement campaign for the proposed metamaterial.

  6. Evolution of Controllability in Interbank Networks

    Science.gov (United States)

    Delpini, Danilo; Battiston, Stefano; Riccaboni, Massimo; Gabbi, Giampaolo; Pammolli, Fabio; Caldarelli, Guido

    2013-04-01

    The Statistical Physics of Complex Networks has recently provided new theoretical tools for policy makers. Here we extend the notion of network controllability to detect the financial institutions, i.e. the drivers, that are most crucial to the functioning of an interbank market. The system we investigate is a paradigmatic case study for complex networks since it undergoes dramatic structural changes over time and links among nodes can be observed at several time scales. We find a scale-free decay of the fraction of drivers with increasing time resolution, implying that policies have to be adjusted to the time scales in order to be effective. Moreover, drivers are often not the most highly connected ``hub'' institutions, nor the largest lenders, contrary to the results of other studies. Our findings contribute quantitative indicators which can support regulators in developing more effective supervision and intervention policies.

  7. Networked control of microgrid system of systems

    Science.gov (United States)

    Mahmoud, Magdi S.; Rahman, Mohamed Saif Ur; AL-Sunni, Fouad M.

    2016-08-01

    The microgrid has made its mark in distributed generation and has attracted widespread research. However, microgrid is a complex system which needs to be viewed from an intelligent system of systems perspective. In this paper, a network control system of systems is designed for the islanded microgrid system consisting of three distributed generation units as three subsystems supplying a load. The controller stabilises the microgrid system in the presence of communication infractions such as packet dropouts and delays. Simulation results are included to elucidate the effectiveness of the proposed control strategy.

  8. Neural network controller for underwater work ROV. Suichu sagyoyo ROV no neural network controller

    Energy Technology Data Exchange (ETDEWEB)

    Yoshida, Y.; Kidoshi, H.; Arahata, M.; Shoji, K.; Takahashi, Y. (Ishikawajima-Harima Heavy Industries, Co. Ltd., Tokyo (Japan))

    1993-07-01

    The previous underwater work ROV (remotely operated vehicle) has been controlled manually because its dynamic properties are changeable underwater. Ishikawajima-Harima Heavy Industries (IHI) has applied a neural network to an adaptive controller for the ROV. This paper describes objectives of the research, design of control logic, and tank experiments on a model ROV. For the neural network, manual operation was used to provide the initial learning data for the neural network in order to initialize control parameters for optimization. The model ROV was designed to achieve and maintain constant depth in normal operation. As a consequence of the tank experiments, it was demonstrated that the controller can acquire skill of operators, can further improve the acquired skill of operators, and can construct an automatic control system autonomically even if any dynamic properties are not known. 6 refs., 8 figs.

  9. Improving Control Mechanism at Routers in TCP/IP Network

    Directory of Open Access Journals (Sweden)

    Nguyen Kim Quoc

    2014-09-01

    Full Text Available The existing control mechanisms at the network nodes have a good active and very effective at each local router, but they do not still strong enough to control nonlinear and dynamical behaviour of the network. Therefore, the control system requirements must be designed to be flexible to fully grasp the important status information of the variation and intelligent control methods to control network congestion in nonlinear network. To solve this problem, we propose a solution combined fuzzy reasoning with neural network control put on active queue management mechanisms at the network nodes.

  10. Call Admission Control in Mobile Cellular Networks

    CERN Document Server

    Ghosh, Sanchita

    2013-01-01

    Call Admission Control (CAC) and Dynamic Channel Assignments (DCA) are important decision-making problems in mobile cellular communication systems. Current research in mobile communication considers them as two independent problems, although the former greatly depends on the resulting free channels obtained as the outcome of the latter. This book provides a solution to the CAC problem, considering DCA as an integral part of decision-making for call admission. Further, current technical resources ignore movement issues of mobile stations and fluctuation in network load (incoming calls) in the control strategy used for call admission. In addition, the present techniques on call admission offers solution globally for the entire network, instead of considering the cells independently.      CAC here has been formulated by two alternative approaches. The first approach aimed at handling the uncertainty in the CAC problem by employing fuzzy comparators.  The second approach is concerned with formulation of CAC ...

  11. Coordinated Voltage Control of Active Distribution Network

    Directory of Open Access Journals (Sweden)

    Xie Jiang

    2016-01-01

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

  12. Model Predictive Control of Sewer Networks

    DEFF Research Database (Denmark)

    Pedersen, Einar B.; Herbertsson, Hannes R.; Niemann, Henrik

    2016-01-01

    The developments in solutions for management of urban drainage are of vital importance, as the amount of sewer water from urban areas continues to increase due to the increase of the world’s population and the change in the climate conditions. How a sewer network is structured, monitored and cont...... benchmark model. Due to the inherent constraints the applied approach is based on Model Predictive Control....

  13. Stochastic modelling and control of communication networks

    OpenAIRE

    Zuraniewski, P.W.

    2011-01-01

    The unprecedented growth of the Information Technologies sector observed within the past years creates an excellent opportunity to conduct new, exciting and interdisciplinary research. Increasing complexity of the communication networks calls for incorporating rigorously developed and reliable methods for traffic control and management. Mathematics may offer extremely valuable tools to achieve these goals but transforming an engineering problem into the mathematical one requires a good unders...

  14. Disruption to control network function correlates with altered dynamic connectivity in the wider autism spectrum

    Directory of Open Access Journals (Sweden)

    N. de Lacy

    2017-01-01

    Full Text Available Autism is a common developmental condition with a wide, variable range of co-occurring neuropsychiatric symptoms. Contrasting with most extant studies, we explored whole-brain functional organization at multiple levels simultaneously in a large subject group reflecting autism's clinical diversity, and present the first network-based analysis of transient brain states, or dynamic connectivity, in autism. Disruption to inter-network and inter-system connectivity, rather than within individual networks, predominated. We identified coupling disruption in the anterior-posterior default mode axis, and among specific control networks specialized for task start cues and the maintenance of domain-independent task positive status, specifically between the right fronto-parietal and cingulo-opercular networks and default mode network subsystems. These appear to propagate downstream in autism, with significantly dampened subject oscillations between brain states, and dynamic connectivity configuration differences. Our account proposes specific motifs that may provide candidates for neuroimaging biomarkers within heterogeneous clinical populations in this diverse condition.

  15. A comprehensive Network Security Risk Model for process control networks.

    Science.gov (United States)

    Henry, Matthew H; Haimes, Yacov Y

    2009-02-01

    The risk of cyber attacks on process control networks (PCN) is receiving significant attention due to the potentially catastrophic extent to which PCN failures can damage the infrastructures and commodity flows that they support. Risk management addresses the coupled problems of (1) reducing the likelihood that cyber attacks would succeed in disrupting PCN operation and (2) reducing the severity of consequences in the event of PCN failure or manipulation. The Network Security Risk Model (NSRM) developed in this article provides a means of evaluating the efficacy of candidate risk management policies by modeling the baseline risk and assessing expectations of risk after the implementation of candidate measures. Where existing risk models fall short of providing adequate insight into the efficacy of candidate risk management policies due to shortcomings in their structure or formulation, the NSRM provides model structure and an associated modeling methodology that captures the relevant dynamics of cyber attacks on PCN for risk analysis. This article develops the NSRM in detail in the context of an illustrative example.

  16. Towards structural controllability of local-world networks

    Energy Technology Data Exchange (ETDEWEB)

    Sun, Shiwen, E-mail: sunsw80@126.com [Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology, Tianjin University of Technology, Tianjin 300384 (China); Key Laboratory of Computer Vision and System (Tianjin University of Technology), Ministry of Education, Tianjin 300384 (China); Ma, Yilin; Wu, Yafang; Wang, Li; Xia, Chengyi [Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology, Tianjin University of Technology, Tianjin 300384 (China); Key Laboratory of Computer Vision and System (Tianjin University of Technology), Ministry of Education, Tianjin 300384 (China)

    2016-05-20

    Controlling complex networks is of vital importance in science and engineering. Meanwhile, local-world effect is an important ingredient which should be taken into consideration in the complete description of real-world complex systems. In this letter, structural controllability of a class of local-world networks is investigated. Through extensive numerical simulations, firstly, effects of local world size M and network size N on structural controllability are examined. For local-world networks with sparse topological configuration, compared to network size, local-world size can induce stronger influence on controllability, however, for dense networks, controllability is greatly affected by network size and local-world effect can be neglected. Secondly, relationships between controllability and topological properties are analyzed. Lastly, the robustness of local-world networks under targeted attacks regarding structural controllability is discussed. These results can help to deepen the understanding of structural complexity and connectivity patterns of complex systems. - Highlights: • Structural controllability of a class of local-world networks is investigated. • For sparse local-world networks, compared to network size, local-world size can bring stronger influence on controllability. • For dense networks, controllability is greatly affected by network size and the effect of local-world size can be neglected. • Structural controllability against targeted node attacks is discussed.

  17. Analysis and design of networked control systems

    CERN Document Server

    You, Keyou; Xie, Lihua

    2015-01-01

    This monograph focuses on characterizing the stability and performance consequences of inserting limited-capacity communication networks within a control loop. The text shows how integration of the ideas of control and estimation with those of communication and information theory can be used to provide important insights concerning several fundamental problems such as: ·         minimum data rate for stabilization of linear systems over noisy channels; ·         minimum network requirement for stabilization of linear systems over fading channels; and ·         stability of Kalman filtering with intermittent observations. A fundamental link is revealed between the topological entropy of linear dynamical systems and the capacities of communication channels. The design of a logarithmic quantizer for the stabilization of linear systems under various network environments is also extensively discussed and solutions to many problems of Kalman filtering with intermittent observations are de...

  18. Plant community composition determines the strength of top-down control in a soil food web motif.

    Science.gov (United States)

    Thakur, Madhav Prakash; Eisenhauer, Nico

    2015-03-16

    Top-down control of prey by predators are magnified in productive ecosystems due to higher sustenance of prey communities. In soil micro-arthropod food webs, plant communities regulate the availability of basal resources like soil microbial biomass. Mixed plant communities are often associated with higher microbial biomass than monocultures. Therefore, top-down control is expected to be higher in soil food webs of mixed plant communities. Moreover, higher predator densities can increase the suppression of prey, which can induce interactive effects between predator densities and plant community composition on prey populations. Here, we tested the effects of predator density (predatory mites) on prey populations (Collembola) in monoculture and mixed plant communities. We hypothesized that top-down control would increase with predator density but only in the mixed plant community. Our results revealed two contrasting patterns of top-down control: stronger top-down control of prey communities in the mixed plant community, but weaker top-down control in plant monocultures in high predator density treatments. As expected, higher microbial community biomass in the mixed plant community sustained sufficiently high prey populations to support high predator density. Our results highlight the roles of plant community composition and predator densities in regulating top-down control of prey in soil food webs.

  19. neural network based load frequency control for restructuring power

    African Journals Online (AJOL)

    2012-03-01

    Mar 1, 2012 ... Abstract. In this study, an artificial neural network (ANN) application of load frequency control. (LFC) of a Multi-Area power system by using a neural network controller is presented. The comparison between a conventional Proportional Integral (PI) controller and the proposed artificial neural networks ...

  20. Efficient Access Control in Multimedia Social Networks

    Science.gov (United States)

    Sachan, Amit; Emmanuel, Sabu

    Multimedia social networks (MMSNs) have provided a convenient way to share multimedia contents such as images, videos, blogs, etc. Contents shared by a person can be easily accessed by anybody else over the Internet. However, due to various privacy, security, and legal concerns people often want to selectively share the contents only with their friends, family, colleagues, etc. Access control mechanisms play an important role in this situation. With access control mechanisms one can decide the persons who can access a shared content and who cannot. But continuously growing content uploads and accesses, fine grained access control requirements (e.g. different access control parameters for different parts in a picture), and specific access control requirements for multimedia contents can make the time complexity of access control to be very large. So, it is important to study an efficient access control mechanism suitable for MMSNs. In this chapter we present an efficient bit-vector transform based access control mechanism for MMSNs. The proposed approach is also compatible with other requirements of MMSNs, such as access rights modification, content deletion, etc. Mathematical analysis and experimental results show the effectiveness and efficiency of our proposed approach.

  1. Identification and Position Control of Marine Helm using Artificial Neural Network Neural Network

    Directory of Open Access Journals (Sweden)

    Hui ZHU

    2008-02-01

    Full Text Available If nonlinearities such as saturation of the amplifier gain and motor torque, gear backlash, and shaft compliances- just to name a few - are considered in the position control system of marine helm, traditional control methods are no longer sufficient to be used to improve the performance of the system. In this paper an alternative approach to traditional control methods - a neural network reference controller - is proposed to establish an adaptive control of the position of the marine helm to achieve the controlled variable at the command position. This neural network controller comprises of two neural networks. One is the plant model network used to identify the nonlinear system and the other the controller network used to control the output to follow the reference model. The experimental results demonstrate that this adaptive neural network reference controller has much better control performance than is obtained with traditional controllers.

  2. Neural Network Control of Asymmetrical Multilevel Converters

    Directory of Open Access Journals (Sweden)

    Patrice WIRA

    2009-12-01

    Full Text Available This paper proposes a neural implementation of a harmonic eliminationstrategy (HES to control a Uniform Step Asymmetrical Multilevel Inverter(USAMI. The mapping between the modulation rate and the requiredswitching angles is learned and approximated with a Multi-Layer Perceptron(MLP neural network. After learning, appropriate switching angles can bedetermined with the neural network leading to a low-computational-costneural controller which is well suited for real-time applications. Thistechnique can be applied to multilevel inverters with any number of levels. Asan example, a nine-level inverter and an eleven-level inverter are consideredand the optimum switching angles are calculated on-line. Comparisons to thewell-known sinusoidal pulse-width modulation (SPWM have been carriedout in order to evaluate the performance of the proposed approach. Simulationresults demonstrate the technical advantages of the proposed neuralimplementation over the conventional method (SPWM in eliminatingharmonics while controlling a nine-level and eleven-level USAMI. Thisneural approach is applied for the supply of an asynchronous machine andresults show that it ensures a highest quality torque by efficiently cancelingthe harmonics generated by the inverters.

  3. Functionalization of reactive polymer multilayers with RGD and an anti-fouling motif: RGD density provides control over human corneal epithelial cell-substrate interactions

    Science.gov (United States)

    Tocce, Elizabeth J.; Broderick, Adam H.; Murphy, Kaitlin C.; Liliensiek, Sara J.; Murphy, Christopher J.; Lynn, David M.; Nealey, Paul F.

    2011-01-01

    Our study demonstrates that substrates fabricated using a ‘reactive’ layer-by-layer approach promote well-defined cell-substrate interactions of human corneal epithelial cells. Specifically, crosslinked and amine-reactive polymer multilayers were produced by alternating ‘reactive’ deposition of an azlactone-functionalized polymer [poly(2-vinyl-4,4-dimethylazlactone)] and a primary amine-containing polymer [branched poly(ethylene imine)]. Advantages of our system include a 5 to 30-fold decrease in deposition time compared to traditional polyelectrolyte films and direct modification of the films with peptides. Our films react with mixtures of an adhesion-promoting peptide containing Arg-Gly-Asp (RGD) and the small molecule d-glucamine, a chemical motif which is non-fouling. Resulting surfaces prevent protein adsorption and promote cell attachment through specific peptide interactions. The specificity of cell attachment via immobilized RGD sequences was verified using both a scrambled RDG peptide control as well as soluble-RGD competitive assays. Films were functionalized with monotonically increasing surface densities of RGD which resulted in both increased cell attachment and the promotion of a tri-phasic proliferative response of a human corneal epithelial cell line (hTCEpi). The ability to treat PEI/PVDMA films with peptides for controlled cell-substrate interactions enables the use of these films in a wide range of biological applications. PMID:21972074

  4. Comprehensive Identification of Glycated Peptides and Their Glycation Motifs in Plasma and Erythrocytes of Control and Diabetic Subjects

    OpenAIRE

    Zhang, Qibin; Monroe, Matthew E.; Schepmoes, Athena A.; Clauss, Therese R. W.; Gritsenko, Marina A.; Meng, Da; Petyuk, Vladislav A.; Smith, Richard D.; Metz, Thomas O.

    2011-01-01

    Non-enzymatic glycation of proteins sets the stage for formation of advanced glycation end-products and development of chronic complications of diabetes. In this report, we extended our previous methods on proteomics analysis of glycated proteins to comprehensively identify glycated proteins in control and diabetic human plasma and erythrocytes. Using immunodepletion, enrichment, and fractionation strategies, we identified 7749 unique glycated peptides, corresponding to 3742 unique glycated p...

  5. MHC motif viewer

    DEFF Research Database (Denmark)

    Rapin, Nicolas Philippe Jean-Pierre; Hoof, Ilka; Lund, Ole

    2008-01-01

    viewer, that allows the display of the likely binding motif for all human class I proteins of the loci HLA A, B, C, and E and for MHC class I molecules from chimpanzee (Pan troglodytes), rhesus monkey (Macaca mulatta), and mouse (Mus musculus). Furthermore, it covers all HLA-DR protein sequences...

  6. Fingerprint motifs of phytases

    African Journals Online (AJOL)

    Fan CM

    2013-03-06

    Mar 6, 2013 ... unique sequences including 131 prokaryotic and 102 eukaryotic phytase sequences covered phytases from. 190 species including 131 bacterium sequences, 70 fungus sequences, 27 plant sequences, one animal sequence and four yeast sequences. For motif analysis, 54 sequences were randomly.

  7. [Personal motif in art].

    Science.gov (United States)

    Gerevich, József

    2015-01-01

    One of the basic questions of the art psychology is whether a personal motif is to be found behind works of art and if so, how openly or indirectly it appears in the work itself. Analysis of examples and documents from the fine arts and literature allow us to conclude that the personal motif that can be identified by the viewer through symbols, at times easily at others with more difficulty, gives an emotional plus to the artistic product. The personal motif may be found in traumatic experiences, in communication to the model or with other emotionally important persons (mourning, disappointment, revenge, hatred, rivalry, revolt etc.), in self-searching, or self-analysis. The emotions are expressed in artistic activity either directly or indirectly. The intention nourished by the artist's identity (Kunstwollen) may stand in the way of spontaneous self-expression, channelling it into hidden paths. Under the influence of certain circumstances, the artist may arouse in the viewer, consciously or unconsciously, an illusionary, misleading image of himself. An examination of the personal motif is one of the important research areas of art therapy.

  8. Neural Networks for Modeling and Control of Particle Accelerators

    CERN Document Server

    Edelen, A.L.; Chase, B.E.; Edstrom, D.; Milton, S.V.; Stabile, P.

    2016-01-01

    We describe some of the challenges of particle accelerator control, highlight recent advances in neural network techniques, discuss some promising avenues for incorporating neural networks into particle accelerator control systems, and describe a neural network-based control system that is being developed for resonance control of an RF electron gun at the Fermilab Accelerator Science and Technology (FAST) facility, including initial experimental results from a benchmark controller.

  9. Predictive Control of Networked Multiagent Systems via Cloud Computing.

    Science.gov (United States)

    Liu, Guo-Ping

    2017-01-18

    This paper studies the design and analysis of networked multiagent predictive control systems via cloud computing. A cloud predictive control scheme for networked multiagent systems (NMASs) is proposed to achieve consensus and stability simultaneously and to compensate for network delays actively. The design of the cloud predictive controller for NMASs is detailed. The analysis of the cloud predictive control scheme gives the necessary and sufficient conditions of stability and consensus of closed-loop networked multiagent control systems. The proposed scheme is verified to characterize the dynamical behavior and control performance of NMASs through simulations. The outcome provides a foundation for the development of cooperative and coordinative control of NMASs and its applications.

  10. Rate of hydrolysis in ATP synthase is fine-tuned by  -subunit motif controlling active site conformation

    KAUST Repository

    Beke-Somfai, T.

    2013-01-23

    Computer-designed artificial enzymes will require precise understanding of how conformation of active sites may control barrier heights of key transition states, including dependence on structure and dynamics at larger molecular scale. F(o)F(1) ATP synthase is interesting as a model system: a delicate molecular machine synthesizing or hydrolyzing ATP using a rotary motor. Isolated F(1) performs hydrolysis with a rate very sensitive to ATP concentration. Experimental and theoretical results show that, at low ATP concentrations, ATP is slowly hydrolyzed in the so-called tight binding site, whereas at higher concentrations, the binding of additional ATP molecules induces rotation of the central γ-subunit, thereby forcing the site to transform through subtle conformational changes into a loose binding site in which hydrolysis occurs faster. How the 1-Å-scale rearrangements are controlled is not yet fully understood. By a combination of theoretical approaches, we address how large macromolecular rearrangements may manipulate the active site and how the reaction rate changes with active site conformation. Simulations reveal that, in response to γ-subunit position, the active site conformation is fine-tuned mainly by small α-subunit changes. Quantum mechanics-based results confirm that the sub-Ångström gradual changes between tight and loose binding site structures dramatically alter the hydrolysis rate.

  11. Induction of DNA Demethylation Depending on Two Sets of Sox2 and Adjacent Oct3/4 Binding Sites (Sox-Oct Motifs) within the Mouse H19/Insulin-like Growth Factor 2 (Igf2) Imprinted Control Region

    Science.gov (United States)

    Hori, Naohiro; Yamane, Mariko; Kouno, Kaori; Sato, Kenzo

    2012-01-01

    DNA demethylation is used to establish and maintain an unmethylated state. The molecular mechanisms to induce DNA demethylation at a particular genomic locus remain unclear. The mouse H19/insulin-like growth factor 2 (Igf2) imprinted control region (ICR) is a methylation state-sensitive insulator that regulates transcriptional activation of both genes. The unmethylated state of the ICR established in female germ cells is maintained during development, resisting the wave of genome-wide de novo methylation. We previously demonstrated that a DNA fragment (fragment b) derived from this ICR-induced DNA demethylation when it was transfected into undifferentiated mouse embryonal carcinoma cell lines. Moreover, two octamer motifs within fragment b were necessary to induce this DNA demethylation. Here, we demonstrated that both octamer motifs and their flanking sequences constitute Sox-Oct motifs (SO1 and SO2) and that the SO1 region, which requires at least four additional elements, including the SO2 region, contributes significantly to the induction of high-frequency DNA demethylation as a Sox-Oct motif. Moreover, RNAi-mediated inhibition of Oct3/4 expression in P19 cells resulted in a reduced DNA demethylation frequency of fragment b but not of the adenine phosphoribosyltransferase gene CpG island. The Sox motif of SO1 could function as a sensor for a hypermethylated state of the ICR to repress demethylation activity. These results indicate that Sox-Oct motifs in the ICR determine the cell type, DNA region, and allele specificity of DNA demethylation. We propose a link between the mechanisms for maintenance of the unmethylated state of the H19/Igf2 ICR and the undifferentiated cell-specific induction of DNA demethylation. PMID:23115243

  12. No tradeoff between versatility and robustness in gene circuit motifs

    OpenAIRE

    Payne Joshua L.

    2016-01-01

    Circuit motifs are small directed subgraphs that appear in real world networks significantly more often than in randomized networks. In the Boolean model of gene circuits most motifs are realized by multiple circuit genotypes. Each of a motif’s constituent circuit genotypes may have one or more functions which are embodied in the expression patterns the circuit forms in response to specific initial conditions. Recent enumeration of a space of nearly 17 million three gene circuit genotypes rev...

  13. ActiveMotif: Interactive motif discovery with human feedback.

    Science.gov (United States)

    Younghoon Kim; Woonghee Lee; Keonwoo Kim

    2017-07-01

    Motif detection, which is to discover short patterns involved in many important biological processes, has been recently raised as an important task in bioinformatics. The traditional algorithms to find a sequence motif have been developed using machine learning only without involving the experience and domain knowledge of human experts effectively. In this paper, we propose an interactive motif discovery system by introducing a new learning algorithm, by generalizing a well-known statistical motif model, whose inference can be shepherded by human feedback.

  14. Network Traffic Features for Anomaly Detection in Specific Industrial Control System Network

    Directory of Open Access Journals (Sweden)

    Matti Mantere

    2013-09-01

    Full Text Available The deterministic and restricted nature of industrial control system networks sets them apart from more open networks, such as local area networks in office environments. This improves the usability of network security, monitoring approaches that would be less feasible in more open environments. One of such approaches is machine learning based anomaly detection. Without proper customization for the special requirements of the industrial control system network environment, many existing anomaly or misuse detection systems will perform sub-optimally. A machine learning based approach could reduce the amount of manual customization required for different industrial control system networks. In this paper we analyze a possible set of features to be used in a machine learning based anomaly detection system in the real world industrial control system network environment under investigation. The network under investigation is represented by architectural drawing and results derived from network trace analysis. The network trace is captured from a live running industrial process control network and includes both control data and the data flowing between the control network and the office network. We limit the investigation to the IP traffic in the traces.

  15. An Efficient Congestion Control Protocol for Wired/Wireless Networks

    OpenAIRE

    Hanaa Torkey; Gamal ATTIYA; Ahmed Abdel Nabi

    2014-01-01

    Recently, wide spectrum of heterogeneous wireless access networks integrate with high speed wired networks to deliver Internet services. End-to-end service delivery with satisfactory quality is challenging issue in such network architectures. Although the Internet transport control protocol (TCP) addresses such challenge, it has poor performance with high speed wired networks (i.e. high bandwidth-delay product). Moreover, it behaves badly with wireless access networks (i.e. misinterpretation ...

  16. Intelligent Joint Admission Control for Next Generation Wireless Networks

    OpenAIRE

    Abdulqader M. Mohsen; Al-Akwaa, Fadhl M.; Mohammed M. Alkhawlani

    2012-01-01

    The Heterogeneous Wireless Network (HWN) integrates different wireless networks into one common network. The integrated networks often overlap coverage in the same wireless service areas, leading to the availability of a great variety of innovative services based on user demands in a cost-efficient manner. Joint Admission Control (JAC) handles all new or handoff service requests in the HWN. It checks whether the incoming service request to the selected Radio Access Network (RAN) by the initia...

  17. Pinning control of complex networked systems synchronization, consensus and flocking of networked systems via pinning

    CERN Document Server

    Su, Housheng

    2013-01-01

    Synchronization, consensus and flocking are ubiquitous requirements in networked systems. Pinning Control of Complex Networked Systems investigates these requirements by using the pinning control strategy, which aims to control the whole dynamical network with huge numbers of nodes by imposing controllers for only a fraction of the nodes. As the direct control of every node in a dynamical network with huge numbers of nodes might be impossible or unnecessary, it’s then very important to use the pinning control strategy for the synchronization of complex dynamical networks. The research on pinning control strategy in consensus and flocking of multi-agent systems can not only help us to better understand the mechanisms of natural collective phenomena, but also benefit applications in mobile sensor/robot networks. This book offers a valuable resource for researchers and engineers working in the fields of control theory and control engineering.   Housheng Su is an Associate Professor at the Department of Contro...

  18. Neural Network for Optimization of Existing Control Systems

    DEFF Research Database (Denmark)

    Madsen, Per Printz

    1995-01-01

    The purpose of this paper is to develop methods to use Neural Network based Controllers (NNC) as an optimization tool for existing control systems.......The purpose of this paper is to develop methods to use Neural Network based Controllers (NNC) as an optimization tool for existing control systems....

  19. Network resource control for grid workflow management systems

    NARCIS (Netherlands)

    Strijkers, R.J.; Cristea, M.; Korkhov, V.; Marchal, D.; Belloum, A.; Laat, C.de; Meijer, R.J.

    2010-01-01

    Grid workflow management systems automate the orchestration of scientific applications with large computational and data processing needs, but lack control over network resources. Consequently, the management system cannot prevent multiple communication intensive applications to compete for network

  20. Control and estimation methods over communication networks

    CERN Document Server

    Mahmoud, Magdi S

    2014-01-01

    This book provides a rigorous framework in which to study problems in the analysis, stability and design of networked control systems. Four dominant sources of difficulty are considered: packet dropouts, communication bandwidth constraints, parametric uncertainty, and time delays. Past methods and results are reviewed from a contemporary perspective, present trends are examined, and future possibilities proposed. Emphasis is placed on robust and reliable design methods. New control strategies for improving the efficiency of sensor data processing and reducing associated time delay are presented. The coverage provided features: ·        an overall assessment of recent and current fault-tolerant control algorithms; ·        treatment of several issues arising at the junction of control and communications; ·        key concepts followed by their proofs and efficient computational methods for their implementation; and ·        simulation examples (including TrueTime simulations) to...

  1. Controllability of giant connected components in a directed network

    Science.gov (United States)

    Liu, Xueming; Pan, Linqiang; Stanley, H. Eugene; Gao, Jianxi

    2017-04-01

    When controlling a complex networked system it is not feasible to control the full network because many networks, including biological, technological, and social systems, are massive in size and complexity. But neither is it necessary to control the full network. In complex networks, the giant connected components provide the essential information about the entire system. How to control these giant connected components of a network remains an open question. We derive the mathematical expression of the degree distributions for four types of giant connected components and develop an analytic tool for studying the controllability of these giant connected components. We find that for both Erdős-Rényi (ER) networks and scale-free (SF) networks with p fraction of remaining nodes, the minimum driver node density to control the giant component first increases and then decreases as p increases from zero to one, showing a peak at a critical point p =pm . We find that, for ER networks, the peak value of the driver node density remains the same regardless of its average degree and that it is determined by pm . In addition, we find that for SF networks the minimum driver node densities needed to control the giant components of networks decrease as the degree distribution exponents increase. Comparing the controllability of the giant components of ER networks and SF networks, we find that when the fraction of remaining nodes p is low, the giant in-connected, out-connected, and strong-connected components in ER networks have lower controllability than those in SF networks.

  2. Unmasking functional motifs within disordered regions of proteins.

    Science.gov (United States)

    Das, Rahul K; Mao, Albert H; Pappu, Rohit V

    2012-04-17

    Eukaryotic proteins often possess long stretches that fail to adopt well-defined, three-dimensional structures. These intrinsically disordered regions are associated with cell signaling through the enrichment of hub proteins of networks and as targets for posttranslational modifications. Although disordered regions are readily identified because of their distinct sequence characteristics, it is difficult to predict the functions associated with these regions. This is because disordered regions often house short (two- to five-residue) linear motifs that mediate intermolecular interactions. Predicting their function requires the ability to identify the functionally relevant motifs. If one assumes that functional motifs are highly conserved as compared to background sequence contexts, then a suitable comparative genomics approach proves to be powerful in unmasking functional motifs that are part of disordered regions. This approach has successfully identified known functional motifs and predicted a set of new motifs that might yield important insights regarding previously unknown functionalities for disordered regions. Given knowledge of highly conserved motifs, one can assess whether the rapidly changing sequence contexts are actuators of the functionalities of short linear motifs within disordered regions. This should have important implications for engineering and targeting hub proteins in signaling networks.

  3. Fault Detection for Quantized Networked Control Systems

    Directory of Open Access Journals (Sweden)

    Wei-Wei Che

    2013-01-01

    Full Text Available The fault detection problem in the finite frequency domain for networked control systems with signal quantization is considered. With the logarithmic quantizer consideration, a quantized fault detection observer is designed by employing a performance index which is used to increase the fault sensitivity in finite frequency domain. The quantized measurement signals are dealt with by utilizing the sector bound method, in which the quantization error is treated as sector-bounded uncertainty. By using the Kalman-Yakubovich-Popov (GKYP Lemma, an iterative LMI-based optimization algorithm is developed for designing the quantized fault detection observer. And a numerical example is given to illustrate the effectiveness of the proposed method.

  4. Urgent epidemic control mechanism for aviation networks

    KAUST Repository

    Peng, Chengbin

    2011-01-01

    In the current century, the highly developed transportation system can not only boost the economy, but also greatly accelerate the spreading of epidemics. While some epidemic diseases may infect quite a number of people ahead of our awareness, the health care resources such as vaccines and the medical staff are usually locally or even globally insufficient. In this research, with the network of major aviation routes as an example, we present a method to determine the optimal locations to allocate the medical service in order to minimize the impact of the infectious disease with limited resources. Specifically, we demonstrate that when the medical resources are insufficient, we should concentrate our efforts on the travelers with the objective of effectively controlling the spreading rate of the epidemic diseases. © 2011 Springer-Verlag Berlin Heidelberg.

  5. Application framework for programmable network control

    NARCIS (Netherlands)

    Strijkers, R.; Cristea, M.; de Laat, C.; Meijer, R.; Clemm, A.; Wolter, R.

    2011-01-01

    We present a framework that enables application developers to create complex and application specific network services. The essence of our approach is to utilize programmable network elements to create a software representation of network elements in the application. We show that the typical pattern

  6. MQCC: Maximum Queue Congestion Control for Multipath Networks with Blockage

    Science.gov (United States)

    2015-10-19

    Design, Implementation and Evaluation of Congestion Control for Multipath TCP ,” in Proc. of USENIX Conference on Networked Systems Design and...MQCC: Maximum Queue Congestion Control for Multipath Networks with Blockage Scott Pudlewski, Brooke Shrader, Laura Herrera, Nathaniel M. Jones...queue-based (MQCC) congestion control algorithm. MQCC uses average buffer occupancy as a measure of the congestion in a network (as opposed to packet

  7. Near-Minimal Node Control of Networked Evolutionary Games

    NARCIS (Netherlands)

    Riehl, James Robert; Cao, Ming

    2014-01-01

    We investigate a problem related to the controllability of networked evolutionary games, first presenting an algorithm that computes a near-minimal set of nodes to drive all nodes in a tree network to a desired strategy, and then briefly discussing an algorithm that works for arbitrary networks

  8. CFO finance network centrality, errors and internal control material weaknessess

    NARCIS (Netherlands)

    Schabus, M.

    2015-01-01

    CFOs finance networks matter in determining certain accounting and reporting outcomes. Drawing on social network theory, this study shows that CFO centrality in a network of financial experts is inversely related to the occurrence of restatements due to errors and disclosure of internal control

  9. Comparative genomic reconstruction of transcriptional networks controlling central metabolism in the Shewanella genus

    Energy Technology Data Exchange (ETDEWEB)

    Rodionov, Dmitry A.; Novichkov, Pavel; Stavrovskaya, Elena D.; Rodionova, Irina A.; Li, Xiaoqing; Kazanov, Marat D.; Ravcheev, Dmitry A.; Gerasimova, Anna V.; Kazakov, Alexey E.; Kovaleva, Galina Y.; Permina, Elizabeth A.; Laikova, Olga N.; Overbeek, Ross; Romine, Margaret F.; Fredrickson, Jim K.; Arkin, Adam P.; Dubchak, Inna; Osterman, Andrei L.; Gelfand, Mikhail S.

    2011-06-15

    Genome-scale prediction of gene regulation and reconstruction of transcriptional regulatory networks in bacteria is one of the critical tasks of modern genomics. Despite the growing number of genome-scale gene expression studies, our abilities to convert the results of these studies into accurate regulatory annotations and to project them from model to other organisms are extremely limited. The comparative genomics approaches and computational identification of regulatory sites are useful for the in silico reconstruction of transcriptional regulatory networks in bacteria. The Shewanella genus is comprised of metabolically versatile gamma-proteobacteria, whose lifestyles and natural environments are substantially different from Escherichia coli and other model bacterial species. To explore conservation and variations in the Shewanella transcriptional networks we analyzed the repertoire of transcription factors and performed genomics-based reconstruction and comparative analysis of regulons in 16 Shewanella genomes. The inferred regulatory network includes 82 transcription factors and their DNA binding sites, 8 riboswitches and 6 translational attenuators. Forty five regulons were newly inferred from the genome context analysis, whereas others were propagated from previously characterized regulons in the Enterobacteria and Pseudomonas spp.. However, even orthologous regulators with conserved DNA-binding motifs may control substantially different gene sets, revealing striking differences in regulatory strategies between the Shewanella spp. and E. coli. Multiple examples of regulatory network rewiring include regulon contraction and expansion (as in the case of PdhR, HexR, FadR), and numerous cases of recruiting non-orthologous regulators to control equivalent pathways (e.g. NagR for N-acetylglucosamine catabolism and PsrA for fatty acid degradation) and, conversely, orthologous regulators to control distinct pathways (e.g. TyrR, ArgR, Crp).

  10. An improved method for network congestion control

    Science.gov (United States)

    Qiao, Xiaolin

    2013-03-01

    The rapid progress of the wireless network technology has great convenience on the people's life and work. However, because of its openness, the mobility of the terminal and the changing topology, the wireless network is more susceptible to security attacks. Authentication and key agreement is the base of the network security. The authentication and key agreement mechanism can prevent the unauthorized user from accessing the network, resist malicious network to deceive the lawful user, encrypt the session data by using the exchange key and provide the identification of the data origination. Based on characteristics of the wireless network, this paper proposed a key agreement protocol for wireless network. The authentication of protocol is based on Elliptic Curve Cryptosystems and Diffie-Hellman.

  11. Complex systems and networks dynamics, controls and applications

    CERN Document Server

    Yu, Xinghuo; Chen, Guanrong; Yu, Wenwu

    2016-01-01

    This elementary book provides some state-of-the-art research results on broad disciplinary sciences on complex networks. It presents an in-depth study with detailed description of dynamics, controls and applications of complex networks. The contents of this book can be summarized as follows. First, the dynamics of complex networks, for example, the cluster dynamic analysis by using kernel spectral methods, community detection algorithms in bipartite networks, epidemiological modeling with demographics and epidemic spreading on multi-layer networks, are studied. Second, the controls of complex networks are investigated including topics like distributed finite-time cooperative control of multi-agent systems by applying homogenous-degree and Lyapunov methods, composite finite-time containment control for disturbed second-order multi-agent systems, fractional-order observer design of multi-agent systems, chaos control and anticontrol of complex systems via Parrondos game and many more. Third, the applications of ...

  12. Implementing controlled-unitary operations over the butterfly network

    Science.gov (United States)

    Soeda, Akihito; Kinjo, Yoshiyuki; Turner, Peter S.; Murao, Mio

    2014-12-01

    We introduce a multiparty quantum computation task over a network in a situation where the capacities of both the quantum and classical communication channels of the network are limited and a bottleneck occurs. Using a resource setting introduced by Hayashi [1], we present an efficient protocol for performing controlled-unitary operations between two input nodes and two output nodes over the butterfly network, one of the most fundamental networks exhibiting the bottleneck problem. This result opens the possibility of developing a theory of quantum network coding for multiparty quantum computation, whereas the conventional network coding only treats multiparty quantum communication.

  13. Implementing controlled-unitary operations over the butterfly network

    Energy Technology Data Exchange (ETDEWEB)

    Soeda, Akihito; Kinjo, Yoshiyuki; Turner, Peter S. [Department of Physics, Graduate School of Science, The University of Tokyo, Tokyo (Japan); Murao, Mio [Department of Physics, Graduate School of Science, The University of Tokyo, Tokyo, Japan and NanoQuine, The University of Tokyo, Tokyo (Japan)

    2014-12-04

    We introduce a multiparty quantum computation task over a network in a situation where the capacities of both the quantum and classical communication channels of the network are limited and a bottleneck occurs. Using a resource setting introduced by Hayashi [1], we present an efficient protocol for performing controlled-unitary operations between two input nodes and two output nodes over the butterfly network, one of the most fundamental networks exhibiting the bottleneck problem. This result opens the possibility of developing a theory of quantum network coding for multiparty quantum computation, whereas the conventional network coding only treats multiparty quantum communication.

  14. Adaptive bridge control strategy for opinion evolution on social networks.

    Science.gov (United States)

    Qian, Cheng; Cao, Jinde; Lu, Jianquan; Kurths, Jürgen

    2011-06-01

    In this paper, we present an efficient opinion control strategy for complex networks, in particular, for social networks. The proposed adaptive bridge control (ABC) strategy calls for controlling a special kind of nodes named bridge and requires no knowledge of the node degrees or any other global or local knowledge, which are necessary for some other immunization strategies including targeted immunization and acquaintance immunization. We study the efficiency of the proposed ABC strategy on random networks, small-world networks, scale-free networks, and the random networks adjusted by the edge exchanging method. Our results show that the proposed ABC strategy is efficient for all of these four kinds of networks. Through an adjusting clustering coefficient by the edge exchanging method, it is found out that the efficiency of our ABC strategy is closely related with the clustering coefficient. The main contributions of this paper can be listed as follows: (1) A new high-order social network is proposed to describe opinion dynamic. (2) An algorithm, which does not require the knowledge of the nodes' degree and other global∕local network structure information, is proposed to control the "bridges" more accurately and further control the opinion dynamics of the social networks. The efficiency of our ABC strategy is illustrated by numerical examples. (3) The numerical results indicate that our ABC strategy is more efficient for networks with higher clustering coefficient.

  15. An algorithmic perspective of de novo cis-regulatory motif finding based on ChIP-seq data.

    Science.gov (United States)

    Liu, Bingqiang; Yang, Jinyu; Li, Yang; McDermaid, Adam; Ma, Qin

    2017-03-08

    Transcription factors are proteins that bind to specific DNA sequences and play important roles in controlling the expression levels of their target genes. Hence, prediction of transcription factor binding sites (TFBSs) provides a solid foundation for inferring gene regulatory mechanisms and building regulatory networks for a genome. Chromatin immunoprecipitation sequencing (ChIP-seq) technology can generate large-scale experimental data for such protein-DNA interactions, providing an unprecedented opportunity to identify TFBSs (a.k.a. cis-regulatory motifs). The bottleneck, however, is the lack of robust mathematical models, as well as efficient computational methods for TFBS prediction to make effective use of massive ChIP-seq data sets in the public domain. The purpose of this study is to review existing motif-finding methods for ChIP-seq data from an algorithmic perspective and provide new computational insight into this field. The state-of-the-art methods were shown through summarizing eight representative motif-finding algorithms along with corresponding challenges, and introducing some important relative functions according to specific biological demands, including discriminative motif finding and cofactor motifs analysis. Finally, potential directions and plans for ChIP-seq-based motif-finding tools were showcased in support of future algorithm development. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  16. Minimizing communication cost among distributed controllers in software defined networks

    Science.gov (United States)

    Arlimatti, Shivaleela; Elbreiki, Walid; Hassan, Suhaidi; Habbal, Adib; Elshaikh, Mohamed

    2016-08-01

    Software Defined Networking (SDN) is a new paradigm to increase the flexibility of today's network by promising for a programmable network. The fundamental idea behind this new architecture is to simplify network complexity by decoupling control plane and data plane of the network devices, and by making the control plane centralized. Recently controllers have distributed to solve the problem of single point of failure, and to increase scalability and flexibility during workload distribution. Even though, controllers are flexible and scalable to accommodate more number of network switches, yet the problem of intercommunication cost between distributed controllers is still challenging issue in the Software Defined Network environment. This paper, aims to fill the gap by proposing a new mechanism, which minimizes intercommunication cost with graph partitioning algorithm, an NP hard problem. The methodology proposed in this paper is, swapping of network elements between controller domains to minimize communication cost by calculating communication gain. The swapping of elements minimizes inter and intra communication cost among network domains. We validate our work with the OMNeT++ simulation environment tool. Simulation results show that the proposed mechanism minimizes the inter domain communication cost among controllers compared to traditional distributed controllers.

  17. Adaptive Dynamics, Control, and Extinction in Networked Populations

    Science.gov (United States)

    2015-07-09

    Adaptive Dynamics, Control, and Extinction in Networked Populations Ira B. Schwartz US Naval Research Laboratory Code 6792 Nonlinear System Dynamics...theory of large deviations to stochastic network extinction to predict extinction times. In particular, we use the theory to find the most probable...paths leading to extinction . We then apply the methodology to network models and discover how mean extinction times scale with network parameters in Erdos

  18. Intelligent Control of Urban Road Networks: Algorithms, Systems and Communications

    Science.gov (United States)

    Smith, Mike

    This paper considers control in road networks. Using a simple example based on the well-known Braess network [1] the paper shows that reducing delay for traffic, assuming that the traffic distribution is fixed, may increase delay when travellers change their travel choices in light of changes in control settings and hence delays. It is shown that a similar effect occurs within signal controlled networks. In this case the effect appears at first sight to be much stronger: the overall capacity of a network may be substantially reduced by utilising standard responsive signal control algorithms. In seeking to reduce delays for existing flows, these policies do not allow properly for consequent routeing changes by travellers. Control methods for signal-controlled networks that do take proper account of the reactions of users are suggested; these require further research, development, and careful real-life trials.

  19. Gene networks controlling Arabidopsis thaliana flower development.

    Science.gov (United States)

    Ó'Maoiléidigh, Diarmuid Seosamh; Graciet, Emmanuelle; Wellmer, Frank

    2014-01-01

    The formation of flowers is one of the main models for studying the regulatory mechanisms that underlie plant development and evolution. Over the past three decades, extensive genetic and molecular analyses have led to the identification of a large number of key floral regulators and to detailed insights into how they control flower morphogenesis. In recent years, genome-wide approaches have been applied to obtaining a global view of the gene regulatory networks underlying flower formation. Furthermore, mathematical models have been developed that can simulate certain aspects of this process and drive further experimentation. Here, we review some of the main findings made in the field of Arabidopsis thaliana flower development, with an emphasis on recent advances. In particular, we discuss the activities of the floral organ identity factors, which are pivotal for the specification of the different types of floral organs, and explore the experimental avenues that may elucidate the molecular mechanisms and gene expression programs through which these master regulators of flower development act. © 2013 The Authors. New Phytologist © 2013 New Phytologist Trust.

  20. Active Engine Mounting Control Algorithm Using Neural Network

    Directory of Open Access Journals (Sweden)

    Fadly Jashi Darsivan

    2009-01-01

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

  1. Deterministic learning enhanced neutral network control of unmanned helicopter

    Directory of Open Access Journals (Sweden)

    Yiming Jiang

    2016-11-01

    Full Text Available In this article, a neural network–based tracking controller is developed for an unmanned helicopter system with guaranteed global stability in the presence of uncertain system dynamics. Due to the coupling and modeling uncertainties of the helicopter systems, neutral networks approximation techniques are employed to compensate the unknown dynamics of each subsystem. In order to extend the semiglobal stability achieved by conventional neural control to global stability, a switching mechanism is also integrated into the control design, such that the resulted neural controller is always valid without any concern on either initial conditions or range of state variables. In addition, deterministic learning is applied to the neutral network learning control, such that the adaptive neutral networks are able to store the learned knowledge that could be reused to construct neutral network controller with improved control performance. Simulation studies are carried out on a helicopter model to illustrate the effectiveness of the proposed control design.

  2. Positive train control interoperability and networking research : final report.

    Science.gov (United States)

    2015-12-01

    This document describes the initial development of an ITC PTC Shared Network (IPSN), a hosted : environment to support the distribution, configuration management, and IT governance of Interoperable : Train Control (ITC) Positive Train Control (PTC) s...

  3. Smart Control of Energy Distribution Grids over Heterogeneous Communication Networks

    DEFF Research Database (Denmark)

    Schwefel, Hans-Peter; Silva, Nuno; Olsen, Rasmus Løvenstein

    2018-01-01

    Off-the shelf wireless communication technologies reduce infrastructure deployment costs and are thus attractive for distribution system control. Wireless communication however may lead to variable network performance. Hence the impact of this variability on overall distribution system control be...

  4. Using a Control System Ethernet Network as a Field Bus

    CERN Document Server

    De Van, William R; Lawson, Gregory S; Wagner, William H; Wantland, David M; Williams, Ernest

    2005-01-01

    A major component of a typical accelerator distributed control system (DCS) is a dedicated, large-scale local area communications network (LAN). The SNS EPICS-based control system uses a LAN based on the popular IEEE-802.3 set of standards (Ethernet). Since the control system network infrastructure is available throughout the facility, and since Ethernet-based controllers are readily available, it is tempting to use the control system LAN for "fieldbus" communications to low-level control devices (e.g. vacuum controllers; remote I/O). These devices may or may not be compatible with the high-level DCS protocols. This paper presents some of the benefits and risks of combining high-level DCS communications with low-level "field bus" communications on the same network, and describes measures taken at SNS to promote compatibility between devices connected to the control system network.

  5. Connected Dominating Set Based Topology Control in Wireless Sensor Networks

    Science.gov (United States)

    He, Jing

    2012-01-01

    Wireless Sensor Networks (WSNs) are now widely used for monitoring and controlling of systems where human intervention is not desirable or possible. Connected Dominating Sets (CDSs) based topology control in WSNs is one kind of hierarchical method to ensure sufficient coverage while reducing redundant connections in a relatively crowded network.…

  6. Implementation of neural network based non-linear predictive control

    DEFF Research Database (Denmark)

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

    1999-01-01

    of non-linear systems. GPC is model based and in this paper we propose the use of a neural network for the modeling of the system. Based on the neural network model, a controller with extended control horizon is developed and the implementation issues are discussed, with particular emphasis...

  7. Mitigating the controller performance bottlenecks in Software Defined Networks

    DEFF Research Database (Denmark)

    Caba, Cosmin Marius; Soler, José

    2016-01-01

    The centralization of the control plane decision logic in Software Defined Networking (SDN) has raised concerns regarding the performance of the SDN Controller (SDNC) when the network scales up. A number of solutions have been proposed in the literature to address these concerns. This paper...

  8. A control model for district heating networks with storage

    NARCIS (Netherlands)

    Scholten, Tjeert; De Persis, Claudio; Tesi, Pietro

    2014-01-01

    In [1] pressure control of hydraulic networks is investigated. We extend this work to district heating systems with storage capabilities and derive a model taking the topology of the network into account. The goal for the derived model is that it should allow for control of the storage level and

  9. Distributed Estimation and Control for Robotic Networks

    NARCIS (Netherlands)

    Simonetto, A.

    2012-01-01

    Mobile robots that communicate and cooperate to achieve a common task have been the subject of an increasing research interest in recent years. These possibly heterogeneous groups of robots communicate locally via a communication network and therefore are usually referred to as robotic networks.

  10. Projection learning algorithm for threshold - controlled neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Reznik, A.M.

    1995-03-01

    The projection learning algorithm proposed in [1, 2] and further developed in [3] substantially improves the efficiency of memorizing information and accelerates the learning process in neural networks. This algorithm is compatible with the completely connected neural network architecture (the Hopfield network [4]), but its application to other networks involves a number of difficulties. The main difficulties include constraints on interconnection structure and the need to eliminate the state uncertainty of latent neurons if such are present in the network. Despite the encouraging preliminary results of [3], further extension of the applications of the projection algorithm therefore remains problematic. In this paper, which is a continuation of the work begun in [3], we consider threshold-controlled neural networks. Networks of this type are quite common. They represent the receptor neuron layers in some neurocomputer designs. A similar structure is observed in the lower divisions of biological sensory systems [5]. In multilayer projection neural networks with lateral interconnections, the neuron layers or parts of these layers may also have the structure of a threshold-controlled completely connected network. Here the thresholds are the potentials delivered through the projection connections from other parts of the network. The extension of the projection algorithm to the class of threshold-controlled networks may accordingly prove to be useful both for extending its technical applications and for better understanding of the operation of the nervous system in living organisms.

  11. Design and Simulation Analysis for Integrated Vehicle Chassis-Network Control System Based on CAN Network

    Directory of Open Access Journals (Sweden)

    Wei Yu

    2016-01-01

    Full Text Available Due to the different functions of the system used in the vehicle chassis control, the hierarchical control strategy also leads to many kinds of the network topology structure. According to the hierarchical control principle, this research puts forward the integrated control strategy of the chassis based on supervision mechanism. The purpose is to consider how the integrated control architecture affects the control performance of the system after the intervention of CAN network. Based on the principle of hierarchical control and fuzzy control, a fuzzy controller is designed, which is used to monitor and coordinate the ESP, AFS, and ARS. And the IVC system is constructed with the upper supervisory controller and three subcontrol systems on the Simulink platform. The network topology structure of IVC is proposed, and the IVC communication matrix based on CAN network communication is designed. With the common sensors and the subcontrollers as the CAN network independent nodes, the network induced delay and packet loss rate on the system control performance are studied by simulation. The results show that the simulation method can be used for designing the communication network of the vehicle.

  12. Optimal traffic control in highway transportation networks using linear programming

    KAUST Repository

    Li, Yanning

    2014-06-01

    This article presents a framework for the optimal control of boundary flows on transportation networks. The state of the system is modeled by a first order scalar conservation law (Lighthill-Whitham-Richards PDE). Based on an equivalent formulation of the Hamilton-Jacobi PDE, the problem of controlling the state of the system on a network link in a finite horizon can be posed as a Linear Program. Assuming all intersections in the network are controllable, we show that the optimization approach can be extended to an arbitrary transportation network, preserving linear constraints. Unlike previously investigated transportation network control schemes, this framework leverages the intrinsic properties of the Halmilton-Jacobi equation, and does not require any discretization or boolean variables on the link. Hence this framework is very computational efficient and provides the globally optimal solution. The feasibility of this framework is illustrated by an on-ramp metering control example.

  13. Transient and permanent error control for networks-on-chip

    CERN Document Server

    Yu, Qiaoyan

    2012-01-01

    This book addresses reliability and energy efficiency of on-chip networks using a configurable error control coding (ECC) scheme for datalink-layer transient error management. The method can adjust both error detection and correction strengths at runtime by varying the number of redundant wires for parity-check bits. Methods are also presented to tackle joint transient and permanent error correction, exploiting the redundant resources already available on-chip. A parallel and flexible network simulator is also introduced, which facilitates examining the impact of various error control methods on network-on-chip performance. Includes a complete survey of error control methods for reliable networks-on-chip, evaluated for reliability, energy and performance metrics; Provides analysis of error control in various network-on-chip layers, as well as presentation of an innovative multi-layer error control coding technique; Presents state-of-the-art solutions to address simultaneously reliability, energy and performan...

  14. Epigenetics and Why Biological Networks are More Controllable than Expected

    Science.gov (United States)

    Motter, Adilson

    2013-03-01

    A fundamental property of networks is that perturbations to one node can affect other nodes, potentially causing the entire system to change behavior or fail. In this talk, I will show that it is possible to exploit this same principle to control network behavior. This approach takes advantage of the nonlinear dynamics inherent to real networks, and allows bringing the system to a desired target state even when this state is not directly accessible or the linear counterpart is not controllable. Applications show that this framework permits both reprogramming a network to a desired task as well as rescuing networks from the brink of failure, which I will illustrate through various biological problems. I will also briefly review the progress our group has made over the past 5 years on related control of complex networks in non-biological domains.

  15. Control Strategy on Worms Spread in Complex Networks

    Science.gov (United States)

    Xianmei, Fang

    First, a preliminary understanding of what is meant by complex network and its features, and network worm virus that understanding and analysis of the emergence and development of the worm, the worm to understand the current situation, focus on the worm propagation model (simple propagation model, Kermack-Mckendrick model, SIS model, two-factor model, BCM model - network worms against the model). Contact the characteristics of complex networks and the worm theory, detection and prevention of worms and an important node in the network-based control strategy (target immunity, virus containment) for a simple discussion.

  16. VNEC - A Virtual Network Experiment Controller

    Science.gov (United States)

    Gagnon, François; Dej, Tomas; Esfandiari, Babak

    This paper presents VNEC, a tool to specify and execute network experiments in a virtual environment. The user first formulates the network topology and then provides the tasks that should be performed by the computers together with their execution. Next, VNEC initializes the environment by powering up and configuring the virtual machines to match the desired network topology. Finally, commands are dispatched to the right virtual machines in the specified order. VNEC provides an environment for several types of research experiments such as virus propagation patterns and reactions of different targets against a given attack.

  17. GC-elements controlling HRAS transcription form i-motif structures unfolded by heterogeneous ribonucleoprotein particle A1

    DEFF Research Database (Denmark)

    Miglietta, Giulia; Cogoi, Susanna; Pedersen, Erik Bjerregaard

    2015-01-01

    HRAS is regulated by two neighbouring quadruplex-forming GC-elements (hras-1 and hras-2), located upstream of the major transcription start sites (doi: 10.1093/nar/gku 5784). In this study we demonstrate that the C-rich strands of hras-1 and hras-2 fold into i-motif conformations (iMs) characteri......HRAS is regulated by two neighbouring quadruplex-forming GC-elements (hras-1 and hras-2), located upstream of the major transcription start sites (doi: 10.1093/nar/gku 5784). In this study we demonstrate that the C-rich strands of hras-1 and hras-2 fold into i-motif conformations (i...

  18. Learning “graph-mer” Motifs that Predict Gene Expression Trajectories in Development

    Science.gov (United States)

    Li, Xuejing; Panea, Casandra; Wiggins, Chris H.; Reinke, Valerie; Leslie, Christina

    2010-01-01

    A key problem in understanding transcriptional regulatory networks is deciphering what cis regulatory logic is encoded in gene promoter sequences and how this sequence information maps to expression. A typical computational approach to this problem involves clustering genes by their expression profiles and then searching for overrepresented motifs in the promoter sequences of genes in a cluster. However, genes with similar expression profiles may be controlled by distinct regulatory programs. Moreover, if many gene expression profiles in a data set are highly correlated, as in the case of whole organism developmental time series, it may be difficult to resolve fine-grained clusters in the first place. We present a predictive framework for modeling the natural flow of information, from promoter sequence to expression, to learn cis regulatory motifs and characterize gene expression patterns in developmental time courses. We introduce a cluster-free algorithm based on a graph-regularized version of partial least squares (PLS) regression to learn sequence patterns—represented by graphs of k-mers, or “graph-mers”—that predict gene expression trajectories. Applying the approach to wildtype germline development in Caenorhabditis elegans, we found that the first and second latent PLS factors mapped to expression profiles for oocyte and sperm genes, respectively. We extracted both known and novel motifs from the graph-mers associated to these germline-specific patterns, including novel CG-rich motifs specific to oocyte genes. We found evidence supporting the functional relevance of these putative regulatory elements through analysis of positional bias, motif conservation and in situ gene expression. This study demonstrates that our regression model can learn biologically meaningful latent structure and identify potentially functional motifs from subtle developmental time course expression data. PMID:20454681

  19. Learning "graph-mer" motifs that predict gene expression trajectories in development.

    Directory of Open Access Journals (Sweden)

    Xuejing Li

    2010-04-01

    Full Text Available A key problem in understanding transcriptional regulatory networks is deciphering what cis regulatory logic is encoded in gene promoter sequences and how this sequence information maps to expression. A typical computational approach to this problem involves clustering genes by their expression profiles and then searching for overrepresented motifs in the promoter sequences of genes in a cluster. However, genes with similar expression profiles may be controlled by distinct regulatory programs. Moreover, if many gene expression profiles in a data set are highly correlated, as in the case of whole organism developmental time series, it may be difficult to resolve fine-grained clusters in the first place. We present a predictive framework for modeling the natural flow of information, from promoter sequence to expression, to learn cis regulatory motifs and characterize gene expression patterns in developmental time courses. We introduce a cluster-free algorithm based on a graph-regularized version of partial least squares (PLS regression to learn sequence patterns--represented by graphs of k-mers, or "graph-mers"--that predict gene expression trajectories. Applying the approach to wildtype germline development in Caenorhabditis elegans, we found that the first and second latent PLS factors mapped to expression profiles for oocyte and sperm genes, respectively. We extracted both known and novel motifs from the graph-mers associated to these germline-specific patterns, including novel CG-rich motifs specific to oocyte genes. We found evidence supporting the functional relevance of these putative regulatory elements through analysis of positional bias, motif conservation and in situ gene expression. This study demonstrates that our regression model can learn biologically meaningful latent structure and identify potentially functional motifs from subtle developmental time course expression data.

  20. Learning "graph-mer" motifs that predict gene expression trajectories in development.

    Science.gov (United States)

    Li, Xuejing; Panea, Casandra; Wiggins, Chris H; Reinke, Valerie; Leslie, Christina

    2010-04-29

    A key problem in understanding transcriptional regulatory networks is deciphering what cis regulatory logic is encoded in gene promoter sequences and how this sequence information maps to expression. A typical computational approach to this problem involves clustering genes by their expression profiles and then searching for overrepresented motifs in the promoter sequences of genes in a cluster. However, genes with similar expression profiles may be controlled by distinct regulatory programs. Moreover, if many gene expression profiles in a data set are highly correlated, as in the case of whole organism developmental time series, it may be difficult to resolve fine-grained clusters in the first place. We present a predictive framework for modeling the natural flow of information, from promoter sequence to expression, to learn cis regulatory motifs and characterize gene expression patterns in developmental time courses. We introduce a cluster-free algorithm based on a graph-regularized version of partial least squares (PLS) regression to learn sequence patterns--represented by graphs of k-mers, or "graph-mers"--that predict gene expression trajectories. Applying the approach to wildtype germline development in Caenorhabditis elegans, we found that the first and second latent PLS factors mapped to expression profiles for oocyte and sperm genes, respectively. We extracted both known and novel motifs from the graph-mers associated to these germline-specific patterns, including novel CG-rich motifs specific to oocyte genes. We found evidence supporting the functional relevance of these putative regulatory elements through analysis of positional bias, motif conservation and in situ gene expression. This study demonstrates that our regression model can learn biologically meaningful latent structure and identify potentially functional motifs from subtle developmental time course expression data.

  1. Stochastic modelling and control of communication networks

    NARCIS (Netherlands)

    Zuraniewski, P.W.

    2011-01-01

    The unprecedented growth of the Information Technologies sector observed within the past years creates an excellent opportunity to conduct new, exciting and interdisciplinary research. Increasing complexity of the communication networks calls for incorporating rigorously developed and reliable

  2. The GATA and SORLIP motifs in the 3-hydroxy-3-methylglutaryl-CoA reductase promoter of Picrorhiza kurrooa for the control of light-mediated expression.

    Science.gov (United States)

    Kawoosa, Tabasum; Gahlan, Parul; Devi, Aribam Surbala; Kumar, Sanjay

    2014-03-01

    Light upregulates the expression of 3-hydroxy-3-methylglutaryl-CoA reductase (HMGR) in Picrorhiza kurrooa, an endangered medicinal herb. Upstream sequences of HMGR of P. kurrooa (PropkHMGR) were analyzed in relation to its role in light-mediated regulation of gene expression. GATA motif in PropkHMGR exhibited stronger DNA-protein interaction with the nuclear extract of dark-exposed plants in contrast to SORLIP that exhibited stronger binding with the nuclear extract of light-exposed plants. Analysis of PropkHMGR (PropkHMGR-D1, -1,059/-1) and its deletion fragments PropkHMGR-D2 (-825/-1), PropkHMGR-D3 (-651/-1), PropkHMGR-D4 (-452/-1), and PropkHMGR-D5 (-101/-1) in Arabidopsis thaliana showed PropkHMGR to regulate gene expression [β-glucuronidase (GUS) was used as a reporter gene] at all the developmental stages but only in actively dividing tissues, excluding anthers. Whereas, PropkHMGR-D2 regulated GUS expression in relatively older seedlings but the expression was observed only in shoot apical meristem, root tips, and anthers. PropkHMGR-mediated gene expression was higher in dark as compared to that in the light in Arabidopsis across four temperatures studied. As opposed to the results in P. kurrooa, GATA motifs exhibited DNA-protein interaction with nuclear extract of light-exposed plants of Arabidopsis. SORLIP motifs in Arabidopsis also exhibited DNA-protein interaction with nuclear extract of light-exposed plants as in P. kurrooa. Data showed that (1) PropkHMGR regulated light-mediated gene expression and (2) GATA motif exhibited an inverse relationship between strength of DNA-protein interaction and the gene expression whereas the relationship was species specific for SORLIP.

  3. Control of Pathogenicity and Disease Specificity of a T-Lymphomagenic Gammaretrovirus by E-Box Motifs but Not by an Overlapping Glucocorticoid Response Element▿

    Science.gov (United States)

    Ejegod, Ditte; Sørensen, Karina Dalsgaard; Mossbrugger, Ilona; Quintanilla-Martinez, Leticia; Schmidt, Jörg; Pedersen, Finn Skou

    2009-01-01

    Although transcription factors of the basic helix-loop-helix family have been shown to regulate enhancers of lymphomagenic gammaretroviruses through E-box motifs, the overlap of an E-box motif (Egre) with the glucocorticoid response element (GRE) has obscured their function in vivo. We report here that Egre, but not the GRE, affects disease induction by the murine T-lymphomagenic SL3-3 virus. Mutating all three copies of Egre prolonged the tumor latency period from 60 to 109 days. Further mutating an E-box motif (Ea/s) outside the enhancer prolonged the latency period to 180 days, suggesting that Ea/s works as a backup site for Egre. While wild-type SL3-3 and GRE and Ea/s mutants exclusively induced T-cell lymphomas with wild-type latencies mainly of the CD4+ CD8− phenotype, Egre as well as the Egre and Ea/s mutants induced B-cell lymphomas and myeloid leukemia in addition to T-cell lymphomas. T-cell lymphomas induced by the two Egre mutants had the same phenotype as those induced by wild-type SL3-3, indicating the incomplete disruption of T-cell lymphomagenesis, which is in contrast to previous findings for a Runx site mutant of SL3-3. Mutating the Egre site or Egre and Ea/s triggered several tumor phenotype-associated secondary enhancer changes encompassing neighboring sites, none of which led to the regeneration of an E-box motif. Taken together, our results demonstrate a role for the E-box but not the GRE in T lymphomagenesis by SL3-3, unveil an inherent broader disease specificity of the virus, and strengthen the notion of selection for more potent enhancer variants of mutated viruses during tumor development. PMID:18945767

  4. Dynamics and control of diseases in networks with community structure.

    Directory of Open Access Journals (Sweden)

    Marcel Salathé

    2010-04-01

    Full Text Available The dynamics of infectious diseases spread via direct person-to-person transmission (such as influenza, smallpox, HIV/AIDS, etc. depends on the underlying host contact network. Human contact networks exhibit strong community structure. Understanding how such community structure affects epidemics may provide insights for preventing the spread of disease between communities by changing the structure of the contact network through pharmaceutical or non-pharmaceutical interventions. We use empirical and simulated networks to investigate the spread of disease in networks with community structure. We find that community structure has a major impact on disease dynamics, and we show that in networks with strong community structure, immunization interventions targeted at individuals bridging communities are more effective than those simply targeting highly connected individuals. Because the structure of relevant contact networks is generally not known, and vaccine supply is often limited, there is great need for efficient vaccination algorithms that do not require full knowledge of the network. We developed an algorithm that acts only on locally available network information and is able to quickly identify targets for successful immunization intervention. The algorithm generally outperforms existing algorithms when vaccine supply is limited, particularly in networks with strong community structure. Understanding the spread of infectious diseases and designing optimal control strategies is a major goal of public health. Social networks show marked patterns of community structure, and our results, based on empirical and simulated data, demonstrate that community structure strongly affects disease dynamics. These results have implications for the design of control strategies.

  5. Performance evaluation of power control algorithms in wireless cellular networks

    Science.gov (United States)

    Temaneh-Nyah, C.; Iita, V.

    2014-10-01

    Power control in a mobile communication network intents to control the transmission power levels in such a way that the required quality of service (QoS) for the users is guaranteed with lowest possible transmission powers. Most of the studies of power control algorithms in the literature are based on some kind of simplified assumptions which leads to compromise in the validity of the results when applied in a real environment. In this paper, a CDMA network was simulated. The real environment was accounted for by defining the analysis area and the network base stations and mobile stations are defined by their geographical coordinates, the mobility of the mobile stations is accounted for. The simulation also allowed for a number of network parameters including the network traffic, and the wireless channel models to be modified. Finally, we present the simulation results of a convergence speed based comparative analysis of three uplink power control algorithms.

  6. Control of coupled oscillator networks with application to microgrid technologies

    Science.gov (United States)

    Arenas, Alex

    The control of complex systems and network-coupled dynamical systems is a topic of vital theoretical importance in mathematics and physics with a wide range of applications in engineering and various other sciences. Motivated by recent research into smart grid technologies, we study the control of synchronization and consider the important case of networks of coupled phase oscillators with nonlinear interactions-a paradigmatic example that has guided our understanding of self-organization for decades. We develop a method for control based on identifying and stabilizing problematic oscillators, resulting in a stable spectrum of eigenvalues, and in turn a linearly stable syn- chronized state. The amount of control, that is, number of oscillators, required to stabilize the network is primarily dictated by the coupling strength, dynamical heterogeneity, and mean degree of the network, and depends little on the structural heterogeneity of the network itself.

  7. Control of coupled oscillator networks with application to microgrid technologies.

    Science.gov (United States)

    Skardal, Per Sebastian; Arenas, Alex

    2015-08-01

    The control of complex systems and network-coupled dynamical systems is a topic of vital theoretical importance in mathematics and physics with a wide range of applications in engineering and various other sciences. Motivated by recent research into smart grid technologies, we study the control of synchronization and consider the important case of networks of coupled phase oscillators with nonlinear interactions-a paradigmatic example that has guided our understanding of self-organization for decades. We develop a method for control based on identifying and stabilizing problematic oscillators, resulting in a stable spectrum of eigenvalues, and in turn a linearly stable synchronized state. The amount of control, that is, number of oscillators, required to stabilize the network is primarily dictated by the coupling strength, dynamical heterogeneity, and mean degree of the network, and depends little on the structural heterogeneity of the network itself.

  8. Structural alphabet motif discovery and a structural motif database.

    Science.gov (United States)

    Ku, Shih-Yen; Hu, Yuh-Jyh

    2012-01-01

    This study proposes a general framework for structural motif discovery. The framework is based on a modular design in which the system components can be modified or replaced independently to increase its applicability to various studies. It is a two-stage approach that first converts protein 3D structures into structural alphabet sequences, and then applies a sequence motif-finding tool to these sequences to detect conserved motifs. We named the structural motif database we built the SA-Motifbase, which provides the structural information conserved at different hierarchical levels in SCOP. For each motif, SA-Motifbase presents its 3D view; alphabet letter preference; alphabet letter frequency distribution; and the significance. SA-Motifbase is available at http://bioinfo.cis.nctu.edu.tw/samotifbase/. Copyright © 2011 Elsevier Ltd. All rights reserved.

  9. ATP-binding motifs play key roles in Krp1p, kinesin-related protein 1, function for bi-polar growth control in fission yeast.

    Science.gov (United States)

    Rhee, Dong Keun; Cho, Bon A; Kim, Hyong Bai

    2005-06-03

    Kinesin is a microtubule-based motor protein with various functions related to the cell growth and division. It has been reported that Krp1p, kinesin-related protein 1, which belongs to the kinesin heavy chain superfamily, localizes on microtubules and may play an important role in cytokinesis. However, the function of Krp1p has not been fully elucidated. In this study, we overexpressed an intact form and three different mutant forms of Krp1p in fission yeast constructed by site-directed mutagenesis in two ATP-binding motifs or by truncation of the leucine zipper-like motif (LZiP). We observed hyper-extended microtubules and the aberrant nuclear shape in Krp1p-overexpressed fission yeast. As a functional consequence, a point mutation of ATP-binding domain 1 (G89E) in Krp1p reversed the effect of Krp1p overexpression in fission yeast, whereas the specific mutation in ATP-binding domain 2 (G238E) resulted in the altered cell polarity. Additionally, truncation of the leucine zipper-like domain (LZiP) at the C-terminal of Krp1p showed a normal nuclear division. Taken together, we suggest that krp1p is involved in regulation of cell-polarized growth through ATP-binding motifs in fission yeast.

  10. SLiMScape: a protein short linear motif analysis plugin for Cytoscape.

    Science.gov (United States)

    O'Brien, Kevin T; Haslam, Niall J; Shields, Denis C

    2013-07-15

    Computational protein short linear motif discovery can use protein interaction information to search for motifs among proteins which share a common interactor. Cytoscape provides a visual interface for protein networks but there is no streamlined way to rapidly visualize motifs in a network of proteins, or to integrate computational discovery with such visualizations. We present SLiMScape, a Cytoscape plugin, which enables both de novo motif discovery and searches for instances of known motifs. Data is presented using Cytoscape's visualization features thus providing an intuitive interface for interpreting results. The distribution of discovered or user-defined motifs may be selectively displayed and the distribution of protein domains may be viewed simultaneously. To facilitate this SLiMScape automatically retrieves domains for each protein. SLiMScape provides a platform for performing short linear motif analyses of protein interaction networks by integrating motif discovery and search tools in a network visualization environment. This significantly aids in the discovery of novel short linear motifs and in visualizing the distribution of known motifs.

  11. Robust receding horizon control for networked and distributed nonlinear systems

    CERN Document Server

    Li, Huiping

    2017-01-01

    This book offers a comprehensive, easy-to-understand overview of receding-horizon control for nonlinear networks. It presents novel general strategies that can simultaneously handle general nonlinear dynamics, system constraints, and disturbances arising in networked and large-scale systems and which can be widely applied. These receding-horizon-control-based strategies can achieve sub-optimal control performance while ensuring closed-loop stability: a feature attractive to engineers. The authors address the problems of networked and distributed control step-by-step, gradually increasing the level of challenge presented. The book first introduces the state-feedback control problems of nonlinear networked systems and then studies output feedback control problems. For large-scale nonlinear systems, disturbance is considered first, then communication delay separately, and lastly the simultaneous combination of delays and disturbances. Each chapter of this easy-to-follow book not only proposes and analyzes novel ...

  12. System Identification, Prediction, Simulation and Control with Neural Networks

    DEFF Research Database (Denmark)

    Sørensen, O.

    1997-01-01

    a Gauss-Newton search direction is applied. 3) Amongst numerous model types, often met in control applications, only the Non-linear ARMAX (NARMAX) model, representing input/output description, is examined. A simulated example confirms that a neural network has the potential to perform excellent System...... Identification, Prediction, Simulation and Control of a dynamic, non-linear and noisy process. Further, the difficulties to control a practical non-linear laboratory process in a satisfactory way by using a traditional controller are overcomed by using a trained neural network to perform non-linear System......The intention of this paper is to make a systematic examination of the possibilities of applying neural networks in those technical areas, which are familiar to a control engineer. In other words, the potential of neural networks in control applications is given higher priority than a detailed...

  13. Hyper conserved elements in vertebrate mRNA 3'-UTRs reveal a translational network of RNA-binding proteins controlled by HuR.

    Science.gov (United States)

    Dassi, Erik; Zuccotti, Paola; Leo, Sara; Provenzani, Alessandro; Assfalg, Michael; D'Onofrio, Mariapina; Riva, Paola; Quattrone, Alessandro

    2013-03-01

    Little is known regarding the post-transcriptional networks that control gene expression in eukaryotes. Additionally, we still need to understand how these networks evolve, and the relative role played in them by their sequence-dependent regulatory factors, non-coding RNAs (ncRNAs) and RNA-binding proteins (RBPs). Here, we used an approach that relied on both phylogenetic sequence sharing and conservation in the whole mapped 3'-untranslated regions (3'-UTRs) of vertebrate species to gain knowledge on core post-transcriptional networks. The identified human hyper conserved elements (HCEs) were predicted to be preferred binding sites for RBPs and not for ncRNAs, namely microRNAs and long ncRNAs. We found that the HCE map identified a well-known network that post-transcriptionally regulates histone mRNAs. We were then able to discover and experimentally confirm a translational network composed of RNA Recognition Motif (RRM)-type RBP mRNAs that are positively controlled by HuR, another RRM-type RBP. HuR shows a preference for these RBP mRNAs bound in stem-loop motifs, confirming its role as a 'regulator of regulators'. Analysis of the transcriptome-wide HCE distribution revealed a profile of prevalently small clusters separated by unconserved intercluster RNA stretches, which predicts the formation of discrete small ribonucleoprotein complexes in the 3'-UTRs.

  14. Operational predictive optimal control of Barcelona water transport network

    OpenAIRE

    Pascual, J.; Romera, J.; Puig, V.; Cembrano, G.; Creus, R.; Minoves, M.

    2013-01-01

    This paper describes the application of model-based predictive control (MPC) techniques to the supervisory flow management in large-scale drinking water networks including a telemetry/telecontrol system. MPC is used to generate flow control strategies (set-points for the regulatory controllers) from the sources to the consumer areas to meet future demands, optimizing performance indexes associated to operational goals such as economic cost, safety storage volumes in the network and smoothness...

  15. Neural-Network Control Of Prosthetic And Robotic Hands

    Science.gov (United States)

    Buckley, Theresa M.

    1991-01-01

    Electronic neural networks proposed for use in controlling robotic and prosthetic hands and exoskeletal or glovelike electromechanical devices aiding intact but nonfunctional hands. Specific to patient, who activates grasping motion by voice command, by mechanical switch, or by myoelectric impulse. Patient retains higher-level control, while lower-level control provided by neural network analogous to that of miniature brain. During training, patient teaches miniature brain to perform specialized, anthropomorphic movements unique to himself or herself.

  16. Topology Control in Aerial Multi Beam Directional Networks

    Science.gov (United States)

    2017-04-24

    Topology Control in Aerial Multi-Beam Directional Networks Brian Proulx, Nathaniel M. Jones, Jennifer Madiedo, Greg Kuperman {brian.proulx, njones...significant interference. Topology control (i.e., selecting a subset of neighbors to communicate with) is vital to reduce the interference. Good topology... control balances the number of links utilized to achieve fewer collisions while maintaining robust network connectivity. In this work, we discuss the

  17. IDENTIFICATION AND CONTROL OF AN ASYNCHRONOUS MACHINE USING NEURAL NETWORKS

    Directory of Open Access Journals (Sweden)

    A ZERGAOUI

    2000-06-01

    Full Text Available In this work, we present the application of artificial neural networks to the identification and control of the asynchronous motor, which is a complex nonlinear system with variable internal dynamics.  We show that neural networks can be applied to control the stator currents of the induction motor.  The results of the different simulations are presented to evaluate the performance of the neural controller proposed.

  18. Cellular automata simulation of topological effects on the dynamics of feed-forward motifs

    Science.gov (United States)

    Apte, Advait A; Cain, John W; Bonchev, Danail G; Fong, Stephen S

    2008-01-01

    Background Feed-forward motifs are important functional modules in biological and other complex networks. The functionality of feed-forward motifs and other network motifs is largely dictated by the connectivity of the individual network components. While studies on the dynamics of motifs and networks are usually devoted to the temporal or spatial description of processes, this study focuses on the relationship between the specific architecture and the overall rate of the processes of the feed-forward family of motifs, including double and triple feed-forward loops. The search for the most efficient network architecture could be of particular interest for regulatory or signaling pathways in biology, as well as in computational and communication systems. Results Feed-forward motif dynamics were studied using cellular automata and compared with differential equation modeling. The number of cellular automata iterations needed for a 100% conversion of a substrate into a target product was used as an inverse measure of the transformation rate. Several basic topological patterns were identified that order the specific feed-forward constructions according to the rate of dynamics they enable. At the same number of network nodes and constant other parameters, the bi-parallel and tri-parallel motifs provide higher network efficacy than single feed-forward motifs. Additionally, a topological property of isodynamicity was identified for feed-forward motifs where different network architectures resulted in the same overall rate of the target production. Conclusion It was shown for classes of structural motifs with feed-forward architecture that network topology affects the overall rate of a process in a quantitatively predictable manner. These fundamental results can be used as a basis for simulating larger networks as combinations of smaller network modules with implications on studying synthetic gene circuits, small regulatory systems, and eventually dynamic whole-cell models

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

    Science.gov (United States)

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

    2015-12-01

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

  20. AUTOMATIC CONTROL OF INTELLECTUAL RIGHTS IN THE GLOBAL COMPUTER NETWORKS

    OpenAIRE

    Anatoly P. Yakimaho; Victoriya V. Bessarabova

    2013-01-01

    The problems of use of subjects of intellectual property in the global computer networks are stated. The main attention is focused on the ways of problems solutions arising during the work in computer networks. Legal problems of information society are considered. The analysis of global computer networks as places for the organization of collective management by copyrights in the world scale is carried out. Issues of creation of a system of automatic control of property rights of authors and ...

  1. Mission-Aware Medium Access Control in Random Access Networks

    OpenAIRE

    Park, Jaeok; Van Der Schaar, Mihaela

    2009-01-01

    We study mission-critical networking in wireless communication networks, where network users are subject to critical events such as emergencies and crises. If a critical event occurs to a user, the user needs to send necessary information for help as early as possible. However, most existing medium access control (MAC) protocols are not adequate to meet the urgent need for information transmission by users in a critical situation. In this paer, we propose a novel class of MAC protocols that u...

  2. Resource Allocation and Cross Layer Control in Wireless Networks

    Science.gov (United States)

    2006-08-25

    Modiano , and J. Tsitsiklis, �Optimal energy allocation and admis- sion control for communication satellites,�IEEE Transactions on Networking, vol. 11...E. Modiano , �Improving delay in ad-hoc mobile networks via redundant packet transfers,�in Proceedings of Conference on Information Sciences and...M. J. Neely, E. Modiano , and C.-P. Li, �Fairness and optimal stochastic con- trol for heterogeneous networks,�in Proceedings of IEEE INFOCOM, Miami

  3. Dissecting the fission yeast regulatory network reveals phase-specific control elements of its cell cycle

    Directory of Open Access Journals (Sweden)

    Liu Liwen

    2009-09-01

    Full Text Available Abstract Background Fission yeast Schizosaccharomyces pombe and budding yeast Saccharomyces cerevisiae are among the original model organisms in the study of the cell-division cycle. Unlike budding yeast, no large-scale regulatory network has been constructed for fission yeast. It has only been partially characterized. As a result, important regulatory cascades in budding yeast have no known or complete counterpart in fission yeast. Results By integrating genome-wide data from multiple time course cell cycle microarray experiments we reconstructed a gene regulatory network. Based on the network, we discovered in addition to previously known regulatory hubs in M phase, a new putative regulatory hub in the form of the HMG box transcription factor SPBC19G7.04. Further, we inferred periodic activities of several less known transcription factors over the course of the cell cycle, identified over 500 putative regulatory targets and detected many new phase-specific and conserved cis-regulatory motifs. In particular, we show that SPBC19G7.04 has highly significant periodic activity that peaks in early M phase, which is coordinated with the late G2 activity of the forkhead transcription factor fkh2. Finally, using an enhanced Bayesian algorithm to co-cluster the expression data, we obtained 31 clusters of co-regulated genes 1 which constitute regulatory modules from different phases of the cell cycle, 2 whose phase order is coherent across the 10 time course experiments, and 3 which lead to identification of phase-specific control elements at both the transcriptional and post-transcriptional levels in S. pombe. In particular, the ribosome biogenesis clusters expressed in G2 phase reveal new, highly conserved RNA motifs. Conclusion Using a systems-level analysis of the phase-specific nature of the S. pombe cell cycle gene regulation, we have provided new testable evidence for post-transcriptional regulation in the G2 phase of the fission yeast cell cycle

  4. Direct Adaptive Aircraft Control Using Dynamic Cell Structure Neural Networks

    Science.gov (United States)

    Jorgensen, Charles C.

    1997-01-01

    A Dynamic Cell Structure (DCS) Neural Network was developed which learns topology representing networks (TRNS) of F-15 aircraft aerodynamic stability and control derivatives. The network is integrated into a direct adaptive tracking controller. The combination produces a robust adaptive architecture capable of handling multiple accident and off- nominal flight scenarios. This paper describes the DCS network and modifications to the parameter estimation procedure. The work represents one step towards an integrated real-time reconfiguration control architecture for rapid prototyping of new aircraft designs. Performance was evaluated using three off-line benchmarks and on-line nonlinear Virtual Reality simulation. Flight control was evaluated under scenarios including differential stabilator lock, soft sensor failure, control and stability derivative variations, and air turbulence.

  5. Submodularity in dynamics and control of networked systems

    CERN Document Server

    Clark, Andrew; Bushnell, Linda; Poovendran, Radha

    2016-01-01

    This book presents a framework for the control of networked systems utilizing submodular optimization techniques. The main focus is on selecting input nodes for the control of networked systems, an inherently discrete optimization problem with applications in power system stability, social influence dynamics, and the control of vehicle formations. The first part of the book is devoted to background information on submodular functions, matroids, and submodular optimization, and presents algorithms for distributed submodular optimization that are scalable to large networked systems. In turn, the second part develops a unifying submodular optimization approach to controlling networked systems based on multiple performance and controllability criteria. Techniques are introduced for selecting input nodes to ensure smooth convergence, synchronization, and robustness to environmental and adversarial noise. Submodular optimization is the first unifying approach towards guaranteeing both performance and controllabilit...

  6. Nephila clavipes Flagelliform silk-like GGX motifs contribute to extensibility and spacer motifs contribute to strength in synthetic spider silk fibers.

    Science.gov (United States)

    Adrianos, Sherry L; Teulé, Florence; Hinman, Michael B; Jones, Justin A; Weber, Warner S; Yarger, Jeffery L; Lewis, Randolph V

    2013-06-10

    Flagelliform spider silk is the most extensible silk fiber produced by orb weaver spiders, though not as strong as the dragline silk of the spider. The motifs found in the core of the Nephila clavipes flagelliform Flag protein are GGX, spacer, and GPGGX. Flag does not contain the polyalanine motif known to provide the strength of dragline silk. To investigate the source of flagelliform fiber strength, four recombinant proteins were produced containing variations of the three core motifs of the Nephila clavipes flagelliform Flag protein that produces this type of fiber. The as-spun fibers were processed in 80% aqueous isopropanol using a standardized process for all four fiber types, which produced improved mechanical properties. Mechanical testing of the recombinant proteins determined that the GGX motif contributes extensibility and the spacer motif contributes strength to the recombinant fibers. Recombinant protein fibers containing the spacer motif were stronger than the proteins constructed without the spacer that contained only the GGX motif or the combination of the GGX and GPGGX motifs. The mechanical and structural X-ray diffraction analysis of the recombinant fibers provide data that suggests a functional role of the spacer motif that produces tensile strength, though the spacer motif is not clearly defined structurally. These results indicate that the spacer is likely a primary contributor of strength, with the GGX motif supplying mobility to the protein network of native N. clavipes flagelliform silk fibers.

  7. Input graph: the hidden geometry in controlling complex networks

    Science.gov (United States)

    Zhang, Xizhe; Lv, Tianyang; Pu, Yuanyuan

    2016-11-01

    The ability to control a complex network towards a desired behavior relies on our understanding of the complex nature of these social and technological networks. The existence of numerous control schemes in a network promotes us to wonder: what is the underlying relationship of all possible input nodes? Here we introduce input graph, a simple geometry that reveals the complex relationship between all control schemes and input nodes. We prove that the node adjacent to an input node in the input graph will appear in another control scheme, and the connected nodes in input graph have the same type in control, which they are either all possible input nodes or not. Furthermore, we find that the giant components emerge in the input graphs of many real networks, which provides a clear topological explanation of bifurcation phenomenon emerging in dense networks and promotes us to design an efficient method to alter the node type in control. The findings provide an insight into control principles of complex networks and offer a general mechanism to design a suitable control scheme for different purposes.

  8. Neural Networks for Modeling and Control of Particle Accelerators

    Science.gov (United States)

    Edelen, A. L.; Biedron, S. G.; Chase, B. E.; Edstrom, D.; Milton, S. V.; Stabile, P.

    2016-04-01

    Particle accelerators are host to myriad nonlinear and complex physical phenomena. They often involve a multitude of interacting systems, are subject to tight performance demands, and should be able to run for extended periods of time with minimal interruptions. Often times, traditional control techniques cannot fully meet these requirements. One promising avenue is to introduce machine learning and sophisticated control techniques inspired by artificial intelligence, particularly in light of recent theoretical and practical advances in these fields. Within machine learning and artificial intelligence, neural networks are particularly well-suited to modeling, control, and diagnostic analysis of complex, nonlinear, and time-varying systems, as well as systems with large parameter spaces. Consequently, the use of neural network-based modeling and control techniques could be of significant benefit to particle accelerators. For the same reasons, particle accelerators are also ideal test-beds for these techniques. Many early attempts to apply neural networks to particle accelerators yielded mixed results due to the relative immaturity of the technology for such tasks. The purpose of this paper is to re-introduce neural networks to the particle accelerator community and report on some work in neural network control that is being conducted as part of a dedicated collaboration between Fermilab and Colorado State University (CSU). We describe some of the challenges of particle accelerator control, highlight recent advances in neural network techniques, discuss some promising avenues for incorporating neural networks into particle accelerator control systems, and describe a neural network-based control system that is being developed for resonance control of an RF electron gun at the Fermilab Accelerator Science and Technology (FAST) facility, including initial experimental results from a benchmark controller.

  9. Guaranteed Cost Fault-Tolerant Control for Networked Control Systems with Sensor Faults

    Directory of Open Access Journals (Sweden)

    Qixin Zhu

    2015-01-01

    Full Text Available For the large scale and complicated structure of networked control systems, time-varying sensor faults could inevitably occur when the system works in a poor environment. Guaranteed cost fault-tolerant controller for the new networked control systems with time-varying sensor faults is designed in this paper. Based on time delay of the network transmission environment, the networked control systems with sensor faults are modeled as a discrete-time system with uncertain parameters. And the model of networked control systems is related to the boundary values of the sensor faults. Moreover, using Lyapunov stability theory and linear matrix inequalities (LMI approach, the guaranteed cost fault-tolerant controller is verified to render such networked control systems asymptotically stable. Finally, simulations are included to demonstrate the theoretical results.

  10. Analysis of Basic Transmission Networks for Integrated Ship Control Systems

    DEFF Research Database (Denmark)

    Hansen, T.N.; Granum-Jensen, M.

    1993-01-01

    Description of a computer network for Integrated Ship Control Systems which is going to be developed as part of an EC-project. Today equipment of different make are not able to communicate with each other because most often each supplier of ISC systems has got their own proprietary network.....

  11. Analysis and control of flows in pressurized hydraulic networks

    NARCIS (Netherlands)

    Gupta, R.K.

    2006-01-01

    Analysis, design and flow control problems in pressurized hydraulic networks such as water transmission and distribution systems consisting of pipes and other appurtenant components such as reservoirs, pumps, valves and surge devices are dealt with from the prospective of network synthesis aiming at

  12. Distributed control of networked Lur’e systems

    NARCIS (Netherlands)

    Zhang, Fan

    2015-01-01

    In this thesis we systematically study distributed control of networked Lur'e systems, specifically, robust synchronization problems and cooperative robust output regulation problems. In such nonlinear multi-agent networks, the model of each agent dynamics is taken as a Lur'e system that consists of

  13. The limits of de novo DNA motif discovery.

    Science.gov (United States)

    Simcha, David; Price, Nathan D; Geman, Donald

    2012-01-01

    A major challenge in molecular biology is reverse-engineering the cis-regulatory logic that plays a major role in the control of gene expression. This program includes searching through DNA sequences to identify "motifs" that serve as the binding sites for transcription factors or, more generally, are predictive of gene expression across cellular conditions. Several approaches have been proposed for de novo motif discovery-searching sequences without prior knowledge of binding sites or nucleotide patterns. However, unbiased validation is not straightforward. We consider two approaches to unbiased validation of discovered motifs: testing the statistical significance of a motif using a DNA "background" sequence model to represent the null hypothesis and measuring performance in predicting membership in gene clusters. We demonstrate that the background models typically used are "too null," resulting in overly optimistic assessments of significance, and argue that performance in predicting TF binding or expression patterns from DNA motifs should be assessed by held-out data, as in predictive learning. Applying this criterion to common motif discovery methods resulted in universally poor performance, although there is a marked improvement when motifs are statistically significant against real background sequences. Moreover, on synthetic data where "ground truth" is known, discriminative performance of all algorithms is far below the theoretical upper bound, with pronounced "over-fitting" in training. A key conclusion from this work is that the failure of de novo discovery approaches to accurately identify motifs is basically due to statistical intractability resulting from the fixed size of co-regulated gene clusters, and thus such failures do not necessarily provide evidence that unfound motifs are not active biologically. Consequently, the use of prior knowledge to enhance motif discovery is not just advantageous but necessary. An implementation of the LR and ALR

  14. The limits of de novo DNA motif discovery.

    Directory of Open Access Journals (Sweden)

    David Simcha

    Full Text Available A major challenge in molecular biology is reverse-engineering the cis-regulatory logic that plays a major role in the control of gene expression. This program includes searching through DNA sequences to identify "motifs" that serve as the binding sites for transcription factors or, more generally, are predictive of gene expression across cellular conditions. Several approaches have been proposed for de novo motif discovery-searching sequences without prior knowledge of binding sites or nucleotide patterns. However, unbiased validation is not straightforward. We consider two approaches to unbiased validation of discovered motifs: testing the statistical significance of a motif using a DNA "background" sequence model to represent the null hypothesis and measuring performance in predicting membership in gene clusters. We demonstrate that the background models typically used are "too null," resulting in overly optimistic assessments of significance, and argue that performance in predicting TF binding or expression patterns from DNA motifs should be assessed by held-out data, as in predictive learning. Applying this criterion to common motif discovery methods resulted in universally poor performance, although there is a marked improvement when motifs are statistically significant against real background sequences. Moreover, on synthetic data where "ground truth" is known, discriminative performance of all algorithms is far below the theoretical upper bound, with pronounced "over-fitting" in training. A key conclusion from this work is that the failure of de novo discovery approaches to accurately identify motifs is basically due to statistical intractability resulting from the fixed size of co-regulated gene clusters, and thus such failures do not necessarily provide evidence that unfound motifs are not active biologically. Consequently, the use of prior knowledge to enhance motif discovery is not just advantageous but necessary. An implementation of

  15. Complex Dynamical Network Control for Trajectory Tracking Using Delayed Recurrent Neural Networks

    Directory of Open Access Journals (Sweden)

    Jose P. Perez

    2014-01-01

    Full Text Available In this paper, the problem of trajectory tracking is studied. Based on the V-stability and Lyapunov theory, a control law that achieves the global asymptotic stability of the tracking error between a delayed recurrent neural network and a complex dynamical network is obtained. To illustrate the analytic results, we present a tracking simulation of a dynamical network with each node being just one Lorenz’s dynamical system and three identical Chen’s dynamical systems.

  16. Genome-wide analysis of cis-regulatory element structure and discovery of motif-driven gene co-expression networks in grapevine.

    Science.gov (United States)

    Wong, Darren Chern Jan; Lopez Gutierrez, Rodrigo; Gambetta, Gregory Alan; Castellarin, Simone Diego

    2017-06-01

    Coordinated transcriptional and metabolic reprogramming ensures a plant's continued growth and survival under adverse environmental conditions. Transcription factors (TFs) act to modulate gene expression through complex cis-regulatory element (CRE) interactions. Genome-wide analysis of known plant CREs was performed for all currently predicted protein-coding gene promoters in grapevine (Vitis vinifera L.). Many CREs such as abscisic acid (ABA)-responsive, drought-responsive, auxin-responsive, and evening elements, exhibit bona fide CRE properties such as strong position bias towards the transcription start site (TSS) and over-representation when compared with random promoters. Genes containing these CREs are enriched in a large repertoire of plant biological pathways. Large-scale transcriptome analyses also show that these CREs are highly implicated in grapevine development and stress response. Numerous CRE-driven modules in condition-specific gene co-expression networks (GCNs) were identified and many of these modules were highly enriched for plant biological functions. Several modules corroborate known roles of CREs in drought response, pathogen defense, cell wall metabolism, and fruit ripening, whereas others reveal novel functions in plants. Comparisons with Arabidopsis suggest a general conservation in promoter architecture, gene expression dynamics, and GCN structure across species. Systems analyses of CREs provide insights into the grapevine cis-regulatory code and establish a foundation for future genomic studies in grapevine. © The Author 2017. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.

  17. Public authority control strategy for opinion evolution in social networks

    Science.gov (United States)

    Chen, Xi; Xiong, Xi; Zhang, Minghong; Li, Wei

    2016-08-01

    This paper addresses the need to deal with and control public opinion and rumors. Existing strategies to control public opinion include degree, random, and adaptive bridge control strategies. In this paper, we use the HK model to present a public opinion control strategy based on public authority (PA). This means utilizing the influence of expert or high authority individuals whose opinions we control to obtain the optimum effect in the shortest time possible and thus reach a consensus of public opinion. Public authority (PA) is only influenced by individuals' attributes (age, economic status, and education level) and not their degree distribution; hence, in this paper, we assume that PA complies with two types of public authority distribution (normal and power-law). According to the proposed control strategy, our experiment is based on random, degree, and public authority control strategies in three different social networks (small-world, scale-free, and random) and we compare and analyze the strategies in terms of convergence time (T), final number of controlled agents (C), and comprehensive efficiency (E). We find that different network topologies and the distribution of the PA in the network can influence the final controlling effect. While the effect of PA strategy differs in different network topology structures, all structures achieve comprehensive efficiency with any kind of public authority distribution in any network. Our findings are consistent with several current sociological phenomena and show that in the process of public opinion/rumor control, considerable attention should be paid to high authority individuals.

  18. Public authority control strategy for opinion evolution in social networks.

    Science.gov (United States)

    Chen, Xi; Xiong, Xi; Zhang, Minghong; Li, Wei

    2016-08-01

    This paper addresses the need to deal with and control public opinion and rumors. Existing strategies to control public opinion include degree, random, and adaptive bridge control strategies. In this paper, we use the HK model to present a public opinion control strategy based on public authority (PA). This means utilizing the influence of expert or high authority individuals whose opinions we control to obtain the optimum effect in the shortest time possible and thus reach a consensus of public opinion. Public authority (PA) is only influenced by individuals' attributes (age, economic status, and education level) and not their degree distribution; hence, in this paper, we assume that PA complies with two types of public authority distribution (normal and power-law). According to the proposed control strategy, our experiment is based on random, degree, and public authority control strategies in three different social networks (small-world, scale-free, and random) and we compare and analyze the strategies in terms of convergence time (T), final number of controlled agents (C), and comprehensive efficiency (E). We find that different network topologies and the distribution of the PA in the network can influence the final controlling effect. While the effect of PA strategy differs in different network topology structures, all structures achieve comprehensive efficiency with any kind of public authority distribution in any network. Our findings are consistent with several current sociological phenomena and show that in the process of public opinion/rumor control, considerable attention should be paid to high authority individuals.

  19. The Life-Changing Magic of Nonlinearity in Network Control

    Science.gov (United States)

    Cornelius, Sean

    The proper functioning and reliability of many man-made and natural systems is fundamentally tied to our ability to control them. Indeed, applications as diverse as ecosystem management, emergency response and cell reprogramming all, at their heart, require us to drive a system to--or keep it in--a desired state. This process is complicated by the nonlinear dynamics inherent to most real systems, which has traditionally been viewed as the principle obstacle to their control. In this talk, I will discuss two ways in which nonlinearity turns this view on its head, in fact representing an asset to the control of complex systems. First, I will show how nonlinearity in the form of multistability allows one to systematically design control interventions that can deliberately induce ``reverse cascading failures'', in which a network spontaneously evolves to a desirable (rather than a failed) state. Second, I will show that nonlinearity in the form of time-varying dynamics unexpectedly makes temporal networks easier to control than their static counterparts, with the former enjoying dramatic and simultaneous reductions in all costs of control. This is true despite the fact that temporality tends to fragment a network's structure, disrupting the paths that allow the directly-controlled or ``driver'' nodes to communicate with the rest of the network. Taken together, these studies shed new light on the crucial role of nonlinearity in network control, and provide support to the idea we can control nonlinearity, rather than letting nonlinearity control us.

  20. Energy scaling and reduction in controlling complex networks

    Science.gov (United States)

    Chen, Yu-Zhong; Wang, Le-Zhi; Wang, Wen-Xu; Lai, Ying-Cheng

    2016-01-01

    Recent works revealed that the energy required to control a complex network depends on the number of driving signals and the energy distribution follows an algebraic scaling law. If one implements control using a small number of drivers, e.g. as determined by the structural controllability theory, there is a high probability that the energy will diverge. We develop a physical theory to explain the scaling behaviour through identification of the fundamental structural elements, the longest control chains (LCCs), that dominate the control energy. Based on the LCCs, we articulate a strategy to drastically reduce the control energy (e.g. in a large number of real-world networks). Owing to their structural nature, the LCCs may shed light on energy issues associated with control of nonlinear dynamical networks. PMID:27152220

  1. PID Neural Network Based Speed Control of Asynchronous Motor Using Programmable Logic Controller

    Directory of Open Access Journals (Sweden)

    MARABA, V. A.

    2011-11-01

    Full Text Available This paper deals with the structure and characteristics of PID Neural Network controller for single input and single output systems. PID Neural Network is a new kind of controller that includes the advantages of artificial neural networks and classic PID controller. Functioning of this controller is based on the update of controller parameters according to the value extracted from system output pursuant to the rules of back propagation algorithm used in artificial neural networks. Parameters obtained from the application of PID Neural Network training algorithm on the speed model of the asynchronous motor exhibiting second order linear behavior were used in the real time speed control of the motor. Programmable logic controller (PLC was used as real time controller. The real time control results show that reference speed successfully maintained under various load conditions.

  2. Integrated control platform for converged optical and wireless networks

    DEFF Research Database (Denmark)

    Yan, Ying

    rates, whereas optical networks can offer much higher data rates but only provide fixed connection structures. Their complementary characteristics make the integration of the two networks a promising trend for next generation networks. With combined strengths, the converged network will provide both...... high data rate services and connectivity at anytime and anywhere. One major challenge in the interworking is how to achieve seamless integration. There are many aspects involved in designing an integrated control platform, such as QoS provisioning, mobility, and resiliency. This dissertation introduces...

  3. Intelligent Servo Drives Control Based on a Single Fieldbus Network

    Directory of Open Access Journals (Sweden)

    D. Puiu

    2010-11-01

    Full Text Available Due to the quick evolution of manufacturing processes, the demand for more flexible automation systems is on the rise. To answer these requirements, distributed motion control architecture based on intelligent drives tends more and more to replace the traditional solutions. This paper presents the control of an articulated arm robot with two local intelligent servo drives connected on a CAN network to a motion controller which receives the trajectory of the robot from a computer. The control structure is based on a single CAN network where local intelligent servo drives, a motion controller and a computer are connected.

  4. Coactivation of Cognitive Control Networks During Task Switching.

    Science.gov (United States)

    Yin, Shouhang; Deák, Gedeon; Chen, Antao

    2017-12-14

    The ability to flexibly switch between tasks is considered an important component of cognitive control that involves frontal and parietal cortical areas. The present study was designed to characterize network dynamics across multiple brain regions during task switching. Functional magnetic resonance images (fMRI) were captured during a standard rule-switching task to identify switching-related brain regions. Multiregional psychophysiological interaction (PPI) analysis was used to examine effective connectivity between these regions. During switching trials, behavioral performance declined and activation of a generic cognitive control network increased. Concurrently, task-related connectivity increased within and between cingulo-opercular and fronto-parietal cognitive control networks. Notably, the left inferior frontal junction (IFJ) was most consistently coactivated with the 2 cognitive control networks. Furthermore, switching-dependent effective connectivity was negatively correlated with behavioral switch costs. The strength of effective connectivity between left IFJ and other regions in the networks predicted individual differences in switch costs. Task switching was supported by coactivated connections within cognitive control networks, with left IFJ potentially acting as a key hub between the fronto-parietal and cingulo-opercular networks. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  5. Evidence for the role of transposons in the recruitment of cis-regulatory motifs during the evolution of C4 photosynthesis.

    Science.gov (United States)

    Cao, Chensi; Xu, Jiajia; Zheng, Guangyong; Zhu, Xin-Guang

    2016-03-08

    C4 photosynthesis evolved from C3 photosynthesis and has higher light, water, and nitrogen use efficiencies. Several C4 photosynthesis genes show cell-specific expression patterns, which are required for these high resource-use efficiencies. However, the mechanisms underlying the evolution of cis-regulatory elements that control these cell-specific expression patterns remain elusive. In the present study, we tested the hypothesis that the cis-regulatory motifs related to C4 photosynthesis genes were recruited from non-photosynthetic genes and further examined potential mechanisms facilitating this recruitment. We examined 65 predicted bundle sheath cell-specific motifs, 17 experimentally validated cell-specific cis-regulatory elements, and 1,034 motifs derived from gene regulatory networks. Approximately 7, 5, and 1,000 of these three categories of motifs, respectively, were apparently recruited during the evolution of C4 photosynthesis. In addition, we checked 1) the distance between the acceptors and the donors of potentially recruited motifs in a chromosome, and 2) whether the potentially recruited motifs reside within the overlapping region of transposable elements and the promoter of donor genes. The results showed that 7, 4, and 658 of the potentially recruited motifs might have moved via the transposable elements. Furthermore, the potentially recruited motifs showed higher binding affinity to transcription factors compared to randomly generated sequences of the same length as the motifs. This study provides molecular evidence supporting the hypothesis that transposon-driven recruitment of pre-existing cis-regulatory elements from non-photosynthetic genes into photosynthetic genes plays an important role during C4 evolution. The findings of the present study coincide with the observed repetitive emergence of C4 during evolution.

  6. Characterizing and controlling intrinsic biases of lambda exonuclease in nascent strand sequencing reveals phasing between nucleosomes and G-quadruplex motifs around a subset of human replication origins

    DEFF Research Database (Denmark)

    Foulk, M. S.; Urban, J. M.; Casella, Cinzia

    2015-01-01

    Nascent strand sequencing (NS-seq) is used to discover DNA replication origins genome-wide, allowing identification of features for their specification. NS-seq depends on the ability of lambda exonuclease (lambda-exo) to efficiently digest parental DNA while leaving RNA-primer protected nascent...... are not general determinants for origin specification but may play a role for a subset. Interestingly, we observed a periodic spacing of G4 motifs and nucleosomes around the peak summits, suggesting that G4s may position nucleosomes at this subset of origins. Finally, we demonstrate that use of Na+ instead of K...

  7. Smart Home: Controlling and Monitoring Households Appliances Using Gsm Network

    National Research Council Canada - National Science Library

    Budi Rahmadya; Fahrul Ghazi; Derisma

    2016-01-01

    This study discussed about using the smart home automation systems for household appliances such as lights and fans, by utilizing the GSM network as a communication medium to control and monitor the household appliances...

  8. The value of peripheral nodes in controlling multilayer networks

    CERN Document Server

    Zhang, Yan; Schweitzer, Frank

    2015-01-01

    We analyze the controllability of a two-layer network, where driver nodes can be chosen only from one layer. Each layer contains a scale-free network with directed links. The dynamics of nodes depends on the incoming links from other nodes (reputation dynamics). We find that the controllable part of the network is larger when choosing peripherial nodes to connect the two layers. The control is as efficient for peripherial nodes as driver nodes as it is for more central nodes. If we assume a cost to utilize nodes which is proportional to their degree, utilizing peripherial nodes to connect the two layers or to act as driver nodes is not only the most cost-efficient solution, it is also the one that gives us the best performance in controlling the two-layer network.

  9. Neighbor-friendly autonomous power control in wireless heterogeneous networks

    National Research Council Canada - National Science Library

    Torrea-Duran, Rodolfo; Tsiaflakis, Paschalis; Vandendorpe, Luc; Moonen, Marc

    2014-01-01

    .... To solve this problem, we propose a neighbor-friendly autonomous algorithm for power control in wireless heterogeneous networks that protects victim users from neighboring cells through a penalty...

  10. Neural Network Predictive Control for Vanadium Redox Flow Battery

    Directory of Open Access Journals (Sweden)

    Hai-Feng Shen

    2013-01-01

    Full Text Available The vanadium redox flow battery (VRB is a nonlinear system with unknown dynamics and disturbances. The flowrate of the electrolyte is an important control mechanism in the operation of a VRB system. Too low or too high flowrate is unfavorable for the safety and performance of VRB. This paper presents a neural network predictive control scheme to enhance the overall performance of the battery. A radial basis function (RBF network is employed to approximate the dynamics of the VRB system. The genetic algorithm (GA is used to obtain the optimum initial values of the RBF network parameters. The gradient descent algorithm is used to optimize the objective function of the predictive controller. Compared with the constant flowrate, the simulation results show that the flowrate optimized by neural network predictive controller can increase the power delivered by the battery during the discharge and decrease the power consumed during the charge.

  11. Passivity-based control and estimation in networked robotics

    CERN Document Server

    Hatanaka, Takeshi; Fujita, Masayuki; Spong, Mark W

    2015-01-01

    Highlighting the control of networked robotic systems, this book synthesizes a unified passivity-based approach to an emerging cross-disciplinary subject. Thanks to this unified approach, readers can access various state-of-the-art research fields by studying only the background foundations associated with passivity. In addition to the theoretical results and techniques,  the authors provide experimental case studies on testbeds of robotic systems  including networked haptic devices, visual robotic systems,  robotic network systems and visual sensor network systems. The text begins with an introduction to passivity and passivity-based control together with the other foundations needed in this book. The main body of the book consists of three parts. The first examines how passivity can be utilized for bilateral teleoperation and demonstrates the inherent robustness of the passivity-based controller against communication delays. The second part emphasizes passivity’s usefulness for visual feedback control ...

  12. STIMULUS: End-System Network Interface Controller for 100 Gb/s Wide Area Networks

    Energy Technology Data Exchange (ETDEWEB)

    Zarkesh-Ha, Payman [University of New Mexico

    2014-09-12

    The main goal of this research grant is to develop a system-level solution leveraging novel technologies that enable network communications at 100 Gb/s or beyond. University of New Mexico in collaboration with Acadia Optronics LLC has been working on this project to develop the 100 Gb/s Network Interface Controller (NIC) under this Department of Energy (DOE) grant.

  13. The Vital Network: An Algorithmic Milieu of Communication and Control

    Directory of Open Access Journals (Sweden)

    Sandra Robinson

    2016-09-01

    Full Text Available The biological turn in computing has influenced the development of algorithmic control and what I call the vital network: a dynamic, relational, and generative assemblage that is self-organizing in response to the heterogeneity of contemporary network processes, connections, and communication. I discuss this biological turn in computation and control for communication alongside historically significant developments in cybernetics that set out the foundation for the development of self-regulating computer systems. Control is shifting away from models that historically relied on the human-animal model of cognition to govern communication and control, as in early cybernetics and computer science, to a decentred, nonhuman model of control by algorithm for communication and networks. To illustrate the rise of contemporary algorithmic control, I outline a particular example, that of the biologically-inspired routing algorithm known as a ‘quorum sensing’ algorithm. The increasing expansion of algorithms as a sense-making apparatus is important in the context of social media, but also in the subsystems that coordinate networked flows of information. In that domain, algorithms are not inferring categories of identity, sociality, and practice associated with Internet consumers, rather, these algorithms are designed to act on information flows as they are transmitted along the network. The development of autonomous control realized through the power of the algorithm to monitor, sort, organize, determine, and transmit communication is the form of control emerging as a postscript to Gilles Deleuze’s ‘postscript on societies of control.’

  14. Identifying novel sequence variants of RNA 3D motifs

    Science.gov (United States)

    Zirbel, Craig L.; Roll, James; Sweeney, Blake A.; Petrov, Anton I.; Pirrung, Meg; Leontis, Neocles B.

    2015-01-01

    Predicting RNA 3D structure from sequence is a major challenge in biophysics. An important sub-goal is accurately identifying recurrent 3D motifs from RNA internal and hairpin loop sequences extracted from secondary structure (2D) diagrams. We have developed and validated new probabilistic models for 3D motif sequences based on hybrid Stochastic Context-Free Grammars and Markov Random Fields (SCFG/MRF). The SCFG/MRF models are constructed using atomic-resolution RNA 3D structures. To parameterize each model, we use all instances of each motif found in the RNA 3D Motif Atlas and annotations of pairwise nucleotide interactions generated by the FR3D software. Isostericity relations between non-Watson–Crick basepairs are used in scoring sequence variants. SCFG techniques model nested pairs and insertions, while MRF ideas handle crossing interactions and base triples. We use test sets of randomly-generated sequences to set acceptance and rejection thresholds for each motif group and thus control the false positive rate. Validation was carried out by comparing results for four motif groups to RMDetect. The software developed for sequence scoring (JAR3D) is structured to automatically incorporate new motifs as they accumulate in the RNA 3D Motif Atlas when new structures are solved and is available free for download. PMID:26130723

  15. Graphs for information security control in software defined networks

    Science.gov (United States)

    Grusho, Alexander A.; Abaev, Pavel O.; Shorgin, Sergey Ya.; Timonina, Elena E.

    2017-07-01

    Information security control in software defined networks (SDN) is connected with execution of the security policy rules regulating information accesses and protection against distribution of the malicious code and harmful influences. The paper offers a representation of a security policy in the form of hierarchical structure which in case of distribution of resources for the solution of tasks defines graphs of admissible interactions in a networks. These graphs define commutation tables of switches via the SDN controller.

  16. Impact of SDN Controllers Deployment on Network Availability

    OpenAIRE

    Nencioni, Gianfranco; Helvik, Bjarne Emil; Gonzalez, Andres Javier; Heegaard, Poul Einar; Kamisinski, Andrzej

    2016-01-01

    Software-defined networking (SDN) promises to improve the programmability and flexibility of networks, but it may bring also new challenges that need to be explored. The purpose of this technical report is to assess how the deployment of the SDN controllers affects the overall availability of SDN. For this, we have varied the number, homing and location of SDN controllers. A two-level modelling approach that is used to evaluate the availability of the studied scenarios. Our results show how n...

  17. A hyperstable neural network for the modelling and control of ...

    Indian Academy of Sciences (India)

    A multivariable hyperstable robust adaptive decoupling control algorithm based on a neural network is presented for the control of nonlinear multivariable coupled systems with unknown parameters and structure. The Popov theorem is used in the design of the controller. The modelling errors, coupling action and other ...

  18. Brain and cognitive reserve: Translation via network control theory.

    Science.gov (United States)

    Medaglia, John Dominic; Pasqualetti, Fabio; Hamilton, Roy H; Thompson-Schill, Sharon L; Bassett, Danielle S

    2017-04-01

    Traditional approaches to understanding the brain's resilience to neuropathology have identified neurophysiological variables, often described as brain or cognitive "reserve," associated with better outcomes. However, mechanisms of function and resilience in large-scale brain networks remain poorly understood. Dynamic network theory may provide a basis for substantive advances in understanding functional resilience in the human brain. In this perspective, we describe recent theoretical approaches from network control theory as a framework for investigating network level mechanisms underlying cognitive function and the dynamics of neuroplasticity in the human brain. We describe the theoretical opportunities offered by the application of network control theory at the level of the human connectome to understand cognitive resilience and inform translational intervention. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

  19. The application of neural network PID controller to control the light gasoline etherification

    Science.gov (United States)

    Cheng, Huanxin; Zhang, Yimin; Kong, Lingling; Meng, Xiangyong

    2017-06-01

    Light gasoline etherification technology can effectively improve the quality of gasoline, which is environmental- friendly and economical. By combining BP neural network and PID control and using BP neural network self-learning ability for online parameter tuning, this method optimizes the parameters of PID controller and applies this to the Fcc gas flow control to achieve the control of the final product- heavy oil concentration. Finally, through MATLAB simulation, it is found that the PID control based on BP neural network has better controlling effect than traditional PID control.

  20. Controlling technology costs as integrated networks expand.

    Science.gov (United States)

    Halverson, K

    1995-01-01

    The expansion of integrated healthcare networks is changing the way radiology technology should be acquired and maintained. Some significant effects are that utilization will decline with managed care; the radiology department is now a cost center, not a source of revenue; and integrated networks find themselves with redundant technology and excess radiology equipment. While hospitals shoulder additional financial risk associated with managed care, responsibility for finding solutions to new problems falls to the radiology administrator. Administrators can take the following steps to effectively reduce expense and risk: Understand current usage. Eliminate redundancies. Prioritize modalities. Find new financing opportunities. Lease equipment. Purchase reconditioned equipment. Redeploy assets instead of buying new. Radiology administrators who view these problems as a challenging puzzle will naturally explore creative options. They will provide the greatest flexibility and best position for their department's contributions to the hospital's overall strategic goals.

  1. Controlling Intervention Hazards in the Network MNC

    OpenAIRE

    Foss, Kirsten; Foss, Nicolai J.; Nell, Phillip C.

    2011-01-01

    The MNC literature treats the (parent) HQ as entirely benevolent with respect to their perceived and actual intentions when they intervene at lower levels of the MNC. However, HQ may intervene in subsidiaries in ways that demotivate subsidiary employees and managers (and therefore harm value-creation). This may happen even if such intervention is benevolent in its intentions. We argue that the movement away from more traditional hierarchical forms of the MNC and towards network MNCs placed in...

  2. Wireless sensor network for streetlight monitoring and control

    Science.gov (United States)

    Huang, Xin-Ming; Ma, Jing; Leblanc, Lawrence E.

    2004-08-01

    Wireless sensor network has attracted considerable research attention as the world becomes more information oriented. This technology provides an opportunity of innovations in traditional industries. Management and control of streetlight system is a labor-intensive high-cost task for public facility operations. This paper applies wireless sensor network technology in streetlight monitoring and control. Wireless sensor networks are employed to replace traditional physical patrol maintenance and manual switching on every lamp in the street or along the highway at the aim of reducing the maintenance and management expense. Active control is used to preserve energy cost while ensuring public safety. A proof-of-concept network architecture operated at 900 MHz industrial, scientific, and medical (ISM) band is designed for a two-way wireless telemetry system in streetlight remote control and monitoring. The radio architecture, multi-hop protocol and system interface are discussed in detail. MOTES sensor nodes are used in simulation and experimental tests. Simulation results show that the sensor network approach provides an efficient solution to monitor and control lighting infrastructures through wireless links. The unique application in this paper addresses an immediate need in streetlight control and monitoring, the architecture developed in this research could also serve as a platform for many other applications and researches in wireless sensor network.

  3. Software Defined Networking (SDN) controlled all optical switching networks with multi-dimensional switching architecture

    Science.gov (United States)

    Zhao, Yongli; Ji, Yuefeng; Zhang, Jie; Li, Hui; Xiong, Qianjin; Qiu, Shaofeng

    2014-08-01

    Ultrahigh throughout capacity requirement is challenging the current optical switching nodes with the fast development of data center networks. Pbit/s level all optical switching networks need to be deployed soon, which will cause the high complexity of node architecture. How to control the future network and node equipment together will become a new problem. An enhanced Software Defined Networking (eSDN) control architecture is proposed in the paper, which consists of Provider NOX (P-NOX) and Node NOX (N-NOX). With the cooperation of P-NOX and N-NOX, the flexible control of the entire network can be achieved. All optical switching network testbed has been experimentally demonstrated with efficient control of enhanced Software Defined Networking (eSDN). Pbit/s level all optical switching nodes in the testbed are implemented based on multi-dimensional switching architecture, i.e. multi-level and multi-planar. Due to the space and cost limitation, each optical switching node is only equipped with four input line boxes and four output line boxes respectively. Experimental results are given to verify the performance of our proposed control and switching architecture.

  4. Fluid Limits of Optimally Controlled Queueing Networks

    OpenAIRE

    Guodong Pang; Day, Martin V.

    2007-01-01

    We consider a class of queueing processes represented by a Skorokhod problem coupled with a controlled point process. Posing a discounted control problem for such processes, we show that the optimal value functions converge, in the fluid limit, to the value of an analogous deterministic control problem for fluid processes. Peer Reviewed

  5. Fluid Limits of Optimally Controlled Queueing Networks

    Directory of Open Access Journals (Sweden)

    Guodong Pang

    2007-01-01

    Full Text Available We consider a class of queueing processes represented by a Skorokhod problem coupled with a controlled point process. Posing a discounted control problem for such processes, we show that the optimal value functions converge, in the fluid limit, to the value of an analogous deterministic control problem for fluid processes.

  6. The MHC motif viewer: a visualization tool for MHC binding motifs

    DEFF Research Database (Denmark)

    Rapin, Nicolas; Hoof, Ilka; Lund, Ole

    2010-01-01

    In vertebrates, the onset of cellular immune reactions is controlled by presentation of peptides in complex with major histocompatibility complex (MHC) molecules to T cell receptors. In humans, MHCs are called human leukocyte antigens (HLAs). Different MHC molecules present different subsets...... is hampered by the lack of tools for browsing and comparing specificity of these molecules. We have developed a Web server, MHC Motif Viewer, which allows the display of the binding motif for MHC class I proteins for human, chimpanzee, rhesus monkey, mouse, and swine, as well as HLA-DR protein sequences...

  7. Generalized Mutual Synchronization between Two Controlled Interdependent Networks

    Directory of Open Access Journals (Sweden)

    Quan Xu

    2014-01-01

    Full Text Available This paper mainly focuses on the generalized mutual synchronization between two controlled interdependent networks. First, we propose the general model of controlled interdependent networks A and B with time-varying internetwork delays coupling. Then, by constructing Lyapunov functions and utilizing adaptive control technique, some sufficient conditions are established to ensure that the mutual synchronization errors between the state variables of networks A and B can asymptotically converge to zero. Finally, two numerical examples are given to illustrate the effectiveness of the theoretical results and to explore potential application in future smart grid. The simulation results also show how interdependent topologies and internetwork coupling delays influence the mutual synchronizability, which help to design interdependent networks with optimal mutual synchronizability.

  8. Can We Control Contaminant Transport In Hydrologic Networks? Application Of Control Theory Concepts To Watershed Management

    Science.gov (United States)

    Yeghiazarian, L.; Riasi, M. S.

    2016-12-01

    Although controlling the level of contamination everywhere in the surface water network may not be feasible, it is vital to maintain safe water quality levels in specific areas, e.g. recreational waters. The question then is "what is the most efficient way to fully/partially control water quality in surface water networks?". This can be posed as a control problem where the goal is to efficiently drive the system to a desired state by manipulating few input variables. Such problems reduce to (1) finding the best control locations in the network to influence the state of the system; and (2) choosing the time-variant inputs at the control locations to achieve the desired state of the system with minimum effort. We demonstrate that the optimal solution to control the level of contamination in the network can be found through application of control theory concepts to transport in dendritic surface water networks.

  9. Role extraction in complex networks and its application in control of networks

    Science.gov (United States)

    Zhou, Mingyang; He, Xingsheng; Fu, Zhongqian; Zhuo, Zhao

    2016-01-01

    Given a large network, dynamics of the network are determined by both nodes' features and network connections. Some features could be extracted from node labels and other kinds of priori knowledge. But how to perform the feature classification without priori knowledge is a challenge. This paper addresses the key problem: how do we conduct role extraction in networks with only edge connections known? On the basis of behavior differences in dynamics, nodes are classified into three role groups: Leaders(L), Communicators(C) and Members(M). Unlike traditional community detections, we detect overlapping communities by link clustering first and then classify nodes according to the community entropy, which describes the disorder of how many different communities a node connects to. We propose a time saving and unsupervised learning approach for automatically discovering nodes' roles based solely on network topology. The effectiveness of this method is demonstrated on six real-world networks through pinning control. By controlling communicator nodes, the controllability is enhanced and the cost for control is reduced obviously in networks with strong community structure.

  10. Control Plane Strategies for Elastic Optical Networks

    DEFF Research Database (Denmark)

    Turus, Ioan

    Networks (EONs) concept is proposed as a solution to enable a more flexible handling of the optical capacity and allows an increase of available capacity over the existing optical infrastructure. One main requirement for enabling EONs is to have a flexible spectrum structure (i.e.Flex-Grid) which allows...... consumption. EONs offer the opportunity of deploying energy efficiency strategies, which benefit from the flexible nature of elastic optoelectronic devices. This thesis proposes and investigates different approaches for reducing power consumption based on EONs in realistic dynamic traffic scenarios....

  11. FIPA agent based network distributed control system

    Energy Technology Data Exchange (ETDEWEB)

    D. Abbott; V. Gyurjyan; G. Heyes; E. Jastrzembski; C. Timmer; E. Wolin

    2003-03-01

    A control system with the capabilities to combine heterogeneous control systems or processes into a uniform homogeneous environment is discussed. This dynamically extensible system is an example of the software system at the agent level of abstraction. This level of abstraction considers agents as atomic entities that communicate to implement the functionality of the control system. Agents' engineering aspects are addressed by adopting the domain independent software standard, formulated by FIPA. Jade core Java classes are used as a FIPA specification implementation. A special, lightweight, XML RDFS based, control oriented, ontology markup language is developed to standardize the description of the arbitrary control system data processor. Control processes, described in this language, are integrated into the global system at runtime, without actual programming. Fault tolerance and recovery issues are also addressed.

  12. Identifiability and inference of pathway motifs by epistasis analysis

    Science.gov (United States)

    Phenix, Hilary; Perkins, Theodore; Kærn, Mads

    2013-06-01

    The accuracy of genetic network inference is limited by the assumptions used to determine if one hypothetical model is better than another in explaining experimental observations. Most previous work on epistasis analysis—in which one attempts to infer pathway relationships by determining equivalences among traits following mutations—has been based on Boolean or linear models. Here, we delineate the ultimate limits of epistasis-based inference by systematically surveying all two-gene network motifs and use symbolic algebra with arbitrary regulation functions to examine trait equivalences. Our analysis divides the motifs into equivalence classes, where different genetic perturbations result in indistinguishable experimental outcomes. We demonstrate that this partitioning can reveal important information about network architecture, and show, using simulated data, that it greatly improves the accuracy of genetic network inference methods. Because of the minimal assumptions involved, equivalence partitioning has broad applicability for gene network inference.

  13. Controllability of Boolean networks via input controls under Harvey's update scheme

    Science.gov (United States)

    Luo, Chao; Zhang, Xiaolin; Shao, Rui; Zheng, YuanJie

    2016-02-01

    In this article, the controllability of Boolean networks via input controls under Harvey's update scheme is investigated. First, the model of Boolean control networks under Harvey's stochastic update is proposed, by means of semi-tensor product approach, which is converted into discrete-time linear representation. And, a general formula of control-depending network transition matrix is provided. Second, based on discrete-time dynamics, controllability of the proposed model is analytically discussed by revealing the necessary and sufficient conditions of the reachable sets, respectively, for three kinds of controls, i.e., free Boolean control sequence, input control networks, and close-loop control. Examples are showed to demonstrate the effectiveness and feasibility of the proposed scheme.

  14. A Network Scheduling Model for Distributed Control Simulation

    Science.gov (United States)

    Culley, Dennis; Thomas, George; Aretskin-Hariton, Eliot

    2016-01-01

    Distributed engine control is a hardware technology that radically alters the architecture for aircraft engine control systems. Of its own accord, it does not change the function of control, rather it seeks to address the implementation issues for weight-constrained vehicles that can limit overall system performance and increase life-cycle cost. However, an inherent feature of this technology, digital communication networks, alters the flow of information between critical elements of the closed-loop control. Whereas control information has been available continuously in conventional centralized control architectures through virtue of analog signaling, moving forward, it will be transmitted digitally in serial fashion over the network(s) in distributed control architectures. An underlying effect is that all of the control information arrives asynchronously and may not be available every loop interval of the controller, therefore it must be scheduled. This paper proposes a methodology for modeling the nominal data flow over these networks and examines the resulting impact for an aero turbine engine system simulation.

  15. Noise Control for a Moving Evaluation Point Using Neural Networks

    Science.gov (United States)

    Maeda, Toshiki; Shiraishi, Toshihiko

    2016-09-01

    This paper describes the noise control for a moving evaluation point using neural networks by making the best use of its learning ability. Noise control is a technology which is effective on low-frequency noise. Based on the principle of superposition, a primary sound wave can be cancelled at an evaluation point by emitting a secondary opposite sound wave. To obtain good control performance, it is important to precisely identify the characteristics of all the sound paths. One of the most popular algorithms of noise control is filtered-x LMS algorithm. This algorithm can deliver a good result while all the sound paths do not change. However, the control system becomes uncontrollable while the evaluation point is moving. To solve the problem, the characteristics of all the paths are must be identified at all time. In this paper, we applied neural networks with the learning ability to the noise control system to follow the time-varying paths and verified its control performance by numerical simulations. Then, dropout technique for the networks is also applied. Dropout is a technique that prevent the network from overfitting and enables better control performance. By applying dropout for noise control, it prevents the system from diverging.

  16. A source-controlled data center network model.

    Directory of Open Access Journals (Sweden)

    Yang Yu

    Full Text Available The construction of data center network by applying SDN technology has become a hot research topic. The SDN architecture has innovatively separated the control plane from the data plane which makes the network more software-oriented and agile. Moreover, it provides virtual multi-tenancy, effective scheduling resources and centralized control strategies to meet the demand for cloud computing data center. However, the explosion of network information is facing severe challenges for SDN controller. The flow storage and lookup mechanisms based on TCAM device have led to the restriction of scalability, high cost and energy consumption. In view of this, a source-controlled data center network (SCDCN model is proposed herein. The SCDCN model applies a new type of source routing address named the vector address (VA as the packet-switching label. The VA completely defines the communication path and the data forwarding process can be finished solely relying on VA. There are four advantages in the SCDCN architecture. 1 The model adopts hierarchical multi-controllers and abstracts large-scale data center network into some small network domains that has solved the restriction for the processing ability of single controller and reduced the computational complexity. 2 Vector switches (VS developed in the core network no longer apply TCAM for table storage and lookup that has significantly cut down the cost and complexity for switches. Meanwhile, the problem of scalability can be solved effectively. 3 The SCDCN model simplifies the establishment process for new flows and there is no need to download flow tables to VS. The amount of control signaling consumed when establishing new flows can be significantly decreased. 4 We design the VS on the NetFPGA platform. The statistical results show that the hardware resource consumption in a VS is about 27% of that in an OFS.

  17. A source-controlled data center network model.

    Science.gov (United States)

    Yu, Yang; Liang, Mangui; Wang, Zhe

    2017-01-01

    The construction of data center network by applying SDN technology has become a hot research topic. The SDN architecture has innovatively separated the control plane from the data plane which makes the network more software-oriented and agile. Moreover, it provides virtual multi-tenancy, effective scheduling resources and centralized control strategies to meet the demand for cloud computing data center. However, the explosion of network information is facing severe challenges for SDN controller. The flow storage and lookup mechanisms based on TCAM device have led to the restriction of scalability, high cost and energy consumption. In view of this, a source-controlled data center network (SCDCN) model is proposed herein. The SCDCN model applies a new type of source routing address named the vector address (VA) as the packet-switching label. The VA completely defines the communication path and the data forwarding process can be finished solely relying on VA. There are four advantages in the SCDCN architecture. 1) The model adopts hierarchical multi-controllers and abstracts large-scale data center network into some small network domains that has solved the restriction for the processing ability of single controller and reduced the computational complexity. 2) Vector switches (VS) developed in the core network no longer apply TCAM for table storage and lookup that has significantly cut down the cost and complexity for switches. Meanwhile, the problem of scalability can be solved effectively. 3) The SCDCN model simplifies the establishment process for new flows and there is no need to download flow tables to VS. The amount of control signaling consumed when establishing new flows can be significantly decreased. 4) We design the VS on the NetFPGA platform. The statistical results show that the hardware resource consumption in a VS is about 27% of that in an OFS.

  18. A source-controlled data center network model

    Science.gov (United States)

    Yu, Yang; Liang, Mangui; Wang, Zhe

    2017-01-01

    The construction of data center network by applying SDN technology has become a hot research topic. The SDN architecture has innovatively separated the control plane from the data plane which makes the network more software-oriented and agile. Moreover, it provides virtual multi-tenancy, effective scheduling resources and centralized control strategies to meet the demand for cloud computing data center. However, the explosion of network information is facing severe challenges for SDN controller. The flow storage and lookup mechanisms based on TCAM device have led to the restriction of scalability, high cost and energy consumption. In view of this, a source-controlled data center network (SCDCN) model is proposed herein. The SCDCN model applies a new type of source routing address named the vector address (VA) as the packet-switching label. The VA completely defines the communication path and the data forwarding process can be finished solely relying on VA. There are four advantages in the SCDCN architecture. 1) The model adopts hierarchical multi-controllers and abstracts large-scale data center network into some small network domains that has solved the restriction for the processing ability of single controller and reduced the computational complexity. 2) Vector switches (VS) developed in the core network no longer apply TCAM for table storage and lookup that has significantly cut down the cost and complexity for switches. Meanwhile, the problem of scalability can be solved effectively. 3) The SCDCN model simplifies the establishment process for new flows and there is no need to download flow tables to VS. The amount of control signaling consumed when establishing new flows can be significantly decreased. 4) We design the VS on the NetFPGA platform. The statistical results show that the hardware resource consumption in a VS is about 27% of that in an OFS. PMID:28328925

  19. Microcontroller Protocol for Secure Broadcast in Controller Area Networks

    OpenAIRE

    B Vijayalakshmi; Kumar, K

    2014-01-01

    Controller Area Network is a bus commonly used by controllers inside vehicles and in various industrial control applications. In the past controllers were assumed to operate in secure perimeters, but today these environments are well connected to the outside world and recent incidents showed them extremely vulnerable to cyber-attacks. To withstand such threats, one can implement security in the application layer of CAN. Here we design, refine and implement a broadcast authenti...

  20. A Network Access Control Framework for 6LoWPAN Networks

    Science.gov (United States)

    Oliveira, Luís M. L.; Rodrigues, Joel J. P. C.; de Sousa, Amaro F.; Lloret, Jaime

    2013-01-01

    Low power over wireless personal area networks (LoWPAN), in particular wireless sensor networks, represent an emerging technology with high potential to be employed in critical situations like security surveillance, battlefields, smart-grids, and in e-health applications. The support of security services in LoWPAN is considered a challenge. First, this type of networks is usually deployed in unattended environments, making them vulnerable to security attacks. Second, the constraints inherent to LoWPAN, such as scarce resources and limited battery capacity, impose a careful planning on how and where the security services should be deployed. Besides protecting the network from some well-known threats, it is important that security mechanisms be able to withstand attacks that have not been identified before. One way of reaching this goal is to control, at the network access level, which nodes can be attached to the network and to enforce their security compliance. This paper presents a network access security framework that can be used to control the nodes that have access to the network, based on administrative approval, and to enforce security compliance to the authorized nodes. PMID:23334610

  1. Digitally Controlled Linear Four-Port Network

    Directory of Open Access Journals (Sweden)

    V. Michalek

    1994-09-01

    Full Text Available The paper deals with the design of a universal linear multipart. The circuit is based on digitally controlled multiple voltage-controlled voltage sources (MVCVSs. The main advantages of this control are accuracy, invariability, and very small area requirements. The whole system is simply connected to a PC via its parallel port. This multipart can generally be used as a building block for any model of a nonlinear dynamic system, namely for the piecewise-linear (PWL model in both explicit and implicit forms.

  2. Some thoughts on the control of network systems

    Directory of Open Access Journals (Sweden)

    Alessandro Ferrarini

    2011-12-01

    Full Text Available The controllability of network-like systems is becoming a trendy key-issue in many disciplines, including ecology and biology. To control a biological, ecological or economic system is to make it behave according to our wishes, at the least possible cost. In this paper, I propose some ideas on networks control that do not precisely follow recent papers on the argument. By the way, since this scientific topic is still in open evolution, discordant thoughts might be helpful to the debate.

  3. Stability and synchronization control of stochastic neural networks

    CERN Document Server

    Zhou, Wuneng; Zhou, Liuwei; Tong, Dongbing

    2016-01-01

    This book reports on the latest findings in the study of Stochastic Neural Networks (SNN). The book collects the novel model of the disturbance driven by Levy process, the research method of M-matrix, and the adaptive control method of the SNN in the context of stability and synchronization control. The book will be of interest to university researchers, graduate students in control science and engineering and neural networks who wish to learn the core principles, methods, algorithms and applications of SNN.

  4. Practical Application of Neural Networks in State Space Control

    DEFF Research Database (Denmark)

    Bendtsen, Jan Dimon

    theoretic notions followed by a detailed description of the topology, neuron functions and learning rules of the two types of neural networks treated in the thesis, the multilayer perceptron and the neurofuzzy networks. In both cases, a Least Squares second-order gradient method is used to train....... Then the controller is shown to work on a simulation example. We also address the potential problem of too rapidly fluctuating parameters by including regularization in the learning rule. Next we develop a direct adaptive certainty-equivalence controller based on neurofuzzy models. The control loop is proven...

  5. Contrasting network and modular perspectives on inhibitory control.

    Science.gov (United States)

    Hampshire, Adam; Sharp, David J

    2015-08-01

    A prominent theory proposes that the right inferior frontal cortex of the human brain houses a dedicated region for motor response inhibition. However, there is growing evidence to support the view that this inhibitory control hypothesis is incorrect. Here, we discuss evidence in favour of our alternative hypothesis, which states that response inhibition is one example of a broader class of control processes that are supported by the same set of frontoparietal networks. These domain-general networks exert control by modulating local lateral inhibition processes, which occur ubiquitously throughout the cortex. We propose that to fully understand the neural basis of behavioural control requires a more holistic approach that considers how common network mechanisms support diverse cognitive processes. Copyright © 2015 Elsevier Ltd. All rights reserved.

  6. Dual adaptive dynamic control of mobile robots using neural networks.

    Science.gov (United States)

    Bugeja, Marvin K; Fabri, Simon G; Camilleri, Liberato

    2009-02-01

    This paper proposes two novel dual adaptive neural control schemes for the dynamic control of nonholonomic mobile robots. The two schemes are developed in discrete time, and the robot's nonlinear dynamic functions are assumed to be unknown. Gaussian radial basis function and sigmoidal multilayer perceptron neural networks are used for function approximation. In each scheme, the unknown network parameters are estimated stochastically in real time, and no preliminary offline neural network training is used. In contrast to other adaptive techniques hitherto proposed in the literature on mobile robots, the dual control laws presented in this paper do not rely on the heuristic certainty equivalence property but account for the uncertainty in the estimates. This results in a major improvement in tracking performance, despite the plant uncertainty and unmodeled dynamics. Monte Carlo simulation and statistical hypothesis testing are used to illustrate the effectiveness of the two proposed stochastic controllers as applied to the trajectory-tracking problem of a differentially driven wheeled mobile robot.

  7. Structure-based control of complex networks with nonlinear dynamics

    CERN Document Server

    Zañudo, Jorge G T; Albert, Réka

    2016-01-01

    Given the network of interactions underlying a complex system, what can we learn about controlling such a system solely from its structure? Over a century of research in control theory has given us tools to answer this question, which were widely applied in science and engineering. Yet the current tools do not always consider the inherently nonlinear dynamics of real systems and the naturally occurring system states in their definition of "control", a term whose interpretation varies across disciplines. Here we use a new mathematical framework for structure-based control of networks governed by a broad class of nonlinear dynamics that includes the major dynamic models of biological, technological, and social processes. This framework provides realizable node overrides that steer a system towards any of its natural long term dynamic behaviors and which are guaranteed to be effective regardless of the dynamic details and parameters of the underlying system. We use this framework on several real networks, compar...

  8. Representational Similarity Analysis Reveals Heterogeneous Networks Supporting Speech Motor Control

    DEFF Research Database (Denmark)

    Zheng, Zane; Cusack, Rhodri; Johnsrude, Ingrid

    The everyday act of speaking involves the complex processes of speech motor control. One important feature of such control is regulation of articulation when auditory concomitants of speech do not correspond to the intended motor gesture. While theoretical accounts of speech monitoring posit...... is supported by a complex neural network that is involved in linguistic, motoric and sensory processing. With the aid of novel real-time acoustic analyses and representational similarity analyses of fMRI signals, our data show functionally differentiated networks underlying auditory feedback control of speech....... multiple functional components required for detection of errors in speech planning (e.g., Levelt, 1983), neuroimaging studies generally indicate either single brain regions sensitive to speech production errors, or small, discrete networks. Here we demonstrate that the complex system controlling speech...

  9. An artificial neural network controller for intelligent transportation systems applications

    Energy Technology Data Exchange (ETDEWEB)

    Vitela, J.E.; Hanebutte, U.R.; Reifman, J. [Argonne National Lab., IL (United States). Reactor Analysis Div.

    1996-04-01

    An Autonomous Intelligent Cruise Control (AICC) has been designed using a feedforward artificial neural network, as an example for utilizing artificial neural networks for nonlinear control problems arising in intelligent transportation systems applications. The AICC is based on a simple nonlinear model of the vehicle dynamics. A Neural Network Controller (NNC) code developed at Argonne National Laboratory to control discrete dynamical systems was used for this purpose. In order to test the NNC, an AICC-simulator containing graphical displays was developed for a system of two vehicles driving in a single lane. Two simulation cases are shown, one involving a lead vehicle with constant velocity and the other a lead vehicle with varying acceleration. More realistic vehicle dynamic models will be considered in future work.

  10. Epidemic Propagation of Control Plane Failures in GMPLS Controlled Optical Transport Networks

    DEFF Research Database (Denmark)

    Ruepp, Sarah Renée; Fagertun, Anna Manolova

    2013-01-01

    In this paper, we investigate the behaviour of a dataplane-decoupled GMPLS control plane, when it is affected by failures that spread in the network in an epidemic manner. In particular, we consider network nodes to be either fully functional, or having a failed control plane, or having both...... a failed control and data plane. Through large-scale network simulation, we evaluate the effect of epidemically spreading control plane failures in terms of blocked connections requests and the amount of stranded capacity due to a dysfunctional control plane. Furthermore, we investigate the effect...

  11. Trust-Based Collaborative Control for Teams on Communication Networks

    Science.gov (United States)

    2012-02-11

    year only [1] S. Ferrari, S. Jagannathan , and F.L. Lewis, “Special Issue on Approximate Dynamic Programming and Reinforcement Learning,” Journal of...to appear, 2012. [17] H. Xu, S. Jagannathan , and F.L. Lewis, “Stochastic Optimal Control of Unknown Linear Networked Control System in the Presence

  12. Neural Network Based Load Frequency Control for Restructuring ...

    African Journals Online (AJOL)

    Electric load variations can happen independently in both units. Both neural controllers are trained with the back propagation-through-time algorithm. Use of a neural network to model the dynamic system is avoided by introducing the Jacobian matrices of the system in the back propagation chain used in controller training.

  13. Synchronization of general complex networks via adaptive control ...

    Indian Academy of Sciences (India)

    2014-03-07

    Mar 7, 2014 ... 3Artificial Intelligence Key Laboratory of Sichuan Province, Sichuan University of Science &. Engineering, Zigong, Sichuan, 643000, People's Republic of China ...... inputs ui(t) (i = 1, 2, 3) and the values of control inputs are acceptable. From figures 1–5, it is easy to see that the controlled complex network ...

  14. Distributed MPC for controlling mu-CHPs in a network

    NARCIS (Netherlands)

    Larsen, Gunn; Trip, Sebastian; van Foreest, Nicky; Scherpen, Jacquelien M.A.

    2012-01-01

    This paper describes a dynamic price mechanism to coordinate electricity generation from micro Combined Heat and Power (mu-CHP) systems in a network of households. The control is done on household level in a completely distributed manner. Distributed Model Predictive control is applied to the

  15. Four Degree Freedom Robot Arm with Fuzzy Neural Network Control

    Directory of Open Access Journals (Sweden)

    Şinasi Arslan

    2013-01-01

    Full Text Available In this study, the control of four degree freedom robot arm has been realized with the computed torque control method.. It is usually required that the four jointed robot arm has high precision capability and good maneuverability for using in industrial applications. Besides, high speed working and external applied loads have been acting as important roles. For those purposes, the computed torque control method has been developed in a good manner that the robot arm can track the given trajectory, which has been able to enhance the feedback control together with fuzzy neural network control. The simulation results have proved that the computed torque control with the neural network has been so successful in robot control.

  16. On the Need of Novel Medium Access Control Schemes for Network Coding enabled Wireless Mesh Networks

    DEFF Research Database (Denmark)

    Paramanathan, Achuthan; Pahlevani, Peyman; Roetter, Daniel Enrique Lucani

    2013-01-01

    This paper advocates for a new Medium Access Control (MAC) strategy for wireless meshed networks by identifying overload scenarios in order to provide additional channel access priority to the relay. The key behind our MAC protocol is that the relay will adjust its back off window size according...... that network coding will improve the throughput in such systems, but our novel medium access scheme improves the performance in the cross topology by another 66 % for network coding and 150 % for classical forwarding in theory. These gains translate in a theoretical gain of 33 % of network coding over...... classical forwarding when both systems implement the improved MAC. However, our measurement results show an even larger gain for network coding, namely, up to 65 % over forwarding, as it copes better with channel losses under high load scenarios....

  17. Evolution of networks and sequences in eukaryotic cell cycle control.

    Science.gov (United States)

    Cross, Frederick R; Buchler, Nicolas E; Skotheim, Jan M

    2011-12-27

    The molecular networks regulating the G1-S transition in budding yeast and mammals are strikingly similar in network structure. However, many of the individual proteins performing similar network roles appear to have unrelated amino acid sequences, suggesting either extremely rapid sequence evolution, or true polyphyly of proteins carrying out identical network roles. A yeast/mammal comparison suggests that network topology, and its associated dynamic properties, rather than regulatory proteins themselves may be the most important elements conserved through evolution. However, recent deep phylogenetic studies show that fungal and animal lineages are relatively closely related in the opisthokont branch of eukaryotes. The presence in plants of cell cycle regulators such as Rb, E2F and cyclins A and D, that appear lost in yeast, suggests cell cycle control in the last common ancestor of the eukaryotes was implemented with this set of regulatory proteins. Forward genetics in non-opisthokonts, such as plants or their green algal relatives, will provide direct information on cell cycle control in these organisms, and may elucidate the potentially more complex cell cycle control network of the last common eukaryotic ancestor.

  18. Energy management and multi-layer control of networked microgrids

    Science.gov (United States)

    Zamora, Ramon

    Networked microgrids is a group of neighboring microgrids that has ability to interchange power when required in order to increase reliability and resiliency. Networked microgrid can operate in different possible configurations including: islanded microgrid, a grid-connected microgrid without a tie-line converter, a grid-connected microgrid with a tie-line converter, and networked microgrids. These possible configurations and specific characteristics of renewable energy offer challenges in designing control and management algorithms for voltage, frequency and power in all possible operating scenarios. In this work, control algorithm is designed based on large-signal model that enables microgrid to operate in wide range of operating points. A combination between PI controller and feed-forward measured system responses will compensate for the changes in operating points. The control architecture developed in this work has multi-layers and the outer layer is slower than the inner layer in time response. The main responsibility of the designed controls are to regulate voltage magnitude and frequency, as well as output power of the DG(s). These local controls also integrate with a microgrid level energy management system or microgrid central controller (MGCC) for power and energy balance for. the entire microgrid in islanded, grid-connected, or networked microgid mode. The MGCC is responsible to coordinate the lower level controls to have reliable and resilient operation. In case of communication network failure, the decentralized energy management will operate locally and will activate droop control. Simulation results indicate the superiority of designed control algorithms compared to existing ones.

  19. Optimization of stochastic discrete systems and control on complex networks computational networks

    CERN Document Server

    Lozovanu, Dmitrii

    2014-01-01

    This book presents the latest findings on stochastic dynamic programming models and on solving optimal control problems in networks. It includes the authors' new findings on determining the optimal solution of discrete optimal control problems in networks and on solving game variants of Markov decision problems in the context of computational networks. First, the book studies the finite state space of Markov processes and reviews the existing methods and algorithms for determining the main characteristics in Markov chains, before proposing new approaches based on dynamic programming and combinatorial methods. Chapter two is dedicated to infinite horizon stochastic discrete optimal control models and Markov decision problems with average and expected total discounted optimization criteria, while Chapter three develops a special game-theoretical approach to Markov decision processes and stochastic discrete optimal control problems. In closing, the book's final chapter is devoted to finite horizon stochastic con...

  20. Carrier ethernet network control plane based on the Next Generation Network

    DEFF Research Database (Denmark)

    Fu, Rong; Wang, Yanmeng; Berger, Michael Stubert

    2008-01-01

    architecture. The approaches to QoS mapping, label distribution and connection and admission control (CAC) are specified here. At last, a simple T-MPLS based Carrier Ethernet network model with three kinds of users (VoIP, VoD and HTTP) and a RACE based control module is simulated in OPNET. The model is aiming...

  1. Intrusion Detection in Networked Control Systems: From System Knowledge to Network Security

    NARCIS (Netherlands)

    Caselli, M.

    2016-01-01

    Networked control system‿ (NCS) is an umbrella term encompassing a broad variety of infrastructures such as industrial control systems (ICSs) and building automation systems (BASs). Nowadays, all these infrastructures play an important role in several aspects of our daily life, from managing

  2. REAL TIME ANALYSIS OF WIRELESS CONTROLLER AREA NETWORK

    Directory of Open Access Journals (Sweden)

    Gerardine Immaculate Mary

    2014-09-01

    Full Text Available It is widely known that Control Area Networks (CAN are used in real-time, distributed and parallel processing which cover manufacture plants, humanoid robots, networking fields, etc., In applications where wireless conditions are encountered it is convenient to continue the exchange of CAN frames within the Wireless CAN (WCAN. The WCAN considered in this research is based on wireless token ring protocol (WTRP; a MAC protocol for wireless networks to reduce the number of retransmissions due to collision and the wired counterpart CAN attribute on message based communication. WCAN uses token frame method to provide channel access to the nodes in the system. This method allow all the nodes to share common broadcast channel by taken turns in transmitting upon receiving the token frame which is circulating within the network for specified amount of time. This method provides high throughput in bounded latency environment, consistent and predictable delays and good packet delivery ratio. The most important factor to consider when evaluating a control network is the end-to-end time delay between sensors, controllers, and actuators. The correct operation of a control system depends on the timeliness of the data coming over the network, and thus, a control network should be able to guarantee message delivery within a bounded transmission time. The proposed WCAN is modeled and simulated using QualNet, and its average end to end delay and packet delivery ratio (PDR are calculated. The parameters boundaries of WCAN are evaluated to guarantee a maximum throughput and a minimum latency time, in the case of wireless communications, precisely WCAN.

  3. A cluster refinement algorithm for motif discovery.

    Science.gov (United States)

    Li, Gang; Chan, Tak-Ming; Leung, Kwong-Sak; Lee, Kin-Hong

    2010-01-01

    Finding Transcription Factor Binding Sites, i.e., motif discovery, is crucial for understanding the gene regulatory relationship. Motifs are weakly conserved and motif discovery is an NP-hard problem. We propose a new approach called Cluster Refinement Algorithm for Motif Discovery (CRMD). CRMD employs a flexible statistical motif model allowing a variable number of motifs and motif instances. CRMD first uses a novel entropy-based clustering to find complete and good starting candidate motifs from the DNA sequences. CRMD then employs an effective greedy refinement to search for optimal motifs from the candidate motifs. The refinement is fast, and it changes the number of motif instances based on the adaptive thresholds. The performance of CRMD is further enhanced if the problem has one occurrence of motif instance per sequence. Using an appropriate similarity test of motifs, CRMD is also able to find multiple motifs. CRMD has been tested extensively on synthetic and real data sets. The experimental results verify that CRMD usually outperforms four other state-of-the-art algorithms in terms of the qualities of the solutions with competitive computing time. It finds a good balance between finding true motif instances and screening false motif instances, and is robust on problems of various levels of difficulty.

  4. Wireless Sensor/Actuator Network Design for Mobile Control Applications

    Directory of Open Access Journals (Sweden)

    Youxian Sung

    2007-10-01

    Full Text Available Wireless sensor/actuator networks (WSANs are emerging as a new generationof sensor networks. Serving as the backbone of control applications, WSANs will enablean unprecedented degree of distributed and mobile control. However, the unreliability ofwireless communications and the real-time requirements of control applications raise greatchallenges for WSAN design. With emphasis on the reliability issue, this paper presents anapplication-level design methodology for WSANs in mobile control applications. Thesolution is generic in that it is independent of the underlying platforms, environment,control system models, and controller design. To capture the link quality characteristics interms of packet loss rate, experiments are conducted on a real WSAN system. From theexperimental observations, a simple yet efficient method is proposed to deal withunpredictable packet loss on actuator nodes. Trace-based simulations give promisingresults, which demonstrate the effectiveness of the proposed approach.

  5. Adaptive model predictive process control using neural networks

    Science.gov (United States)

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

    1997-08-19

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

  6. Expanding the NATO Movement Control Network

    Science.gov (United States)

    2016-05-17

    mander of the 624th Movement Con- trol Team, 39th Transportation Battalion (Movement Control), 16th Sustainment Brigade, at Kleber Kaserne, Germany . He...Philip Stephens) 31 Army Sustainment November–December 2015 Challenges of Moving in Europe...have been operating in Germany and Italy since the end of World War II and understand those nations’ requirements well, but recent changes in

  7. Controlling high speed automated transport network operations

    NARCIS (Netherlands)

    de Feijter, R.

    2006-01-01

    This thesis presents a framework for the control of automated guided vehicles (AGVs). The framework implements the transport system as a community of cooperating agents. Besides the architecture and elements of the framework a wide range of infrastructure scene templates is described. These scene

  8. Modelling and control of cell reaction networks

    NARCIS (Netherlands)

    S. Jha; J.H. van Schuppen (Jan)

    2001-01-01

    textabstractThe project aims at a study of the nonlinear systems arising in the biochemical processes occuring inside a cell. The cellular regulation has been formulated in the more familiar framework used in control and system theory in terms of inputs as the variables which can be influenced

  9. Control of a hybrid compensator in a power network by an artificial neural network

    Directory of Open Access Journals (Sweden)

    I. S. Shaw

    1998-07-01

    Full Text Available Increased interest in the elimination of distortion in electrical power networks has led to the development of various compensator topologies. The increasing cost of electrical energy necessitates the cost-effective operation of any of these topologies. This paper considers the development of an artificial neural network based controller, trained by means of the backpropagation method, that ensures the cost-effective operation of the hybrid compensator consisting of various converters and filters.

  10. Adaptive traffic control systems for urban networks

    Directory of Open Access Journals (Sweden)

    Radivojević Danilo

    2017-01-01

    Full Text Available Adaptive traffic control systems represent complex, but powerful tool for improvement of traffic flow conditions in locations or zones where applied. Many traffic agencies, especially those that have a large number of signalized intersections with high variability of the traffic demand, choose to apply some of the adaptive traffic control systems. However, those systems are manufactured and offered by multiple vendors (companies that are competing for the market share. Due to that fact, besides the information available from the vendors themselves, or the information from different studies conducted on different continents, very limited amount of information is available about the details how those systems are operating. The reason for that is the protecting of the intellectual property from plagiarism. The primary goal of this paper is to make a brief analysis of the functionalities, characteristics, abilities and results of the most recognized, but also less known adaptive traffic control systems to the professional public and other persons with interest in this subject.

  11. DMINDA: an integrated web server for DNA motif identification and analyses

    Science.gov (United States)

    Ma, Qin; Zhang, Hanyuan; Mao, Xizeng; Zhou, Chuan; Liu, Bingqiang; Chen, Xin; Xu, Ying

    2014-01-01

    DMINDA (DNA motif identification and analyses) is an integrated web server for DNA motif identification and analyses, which is accessible at http://csbl.bmb.uga.edu/DMINDA/. This web site is freely available to all users and there is no login requirement. This server provides a suite of cis-regulatory motif analysis functions on DNA sequences, which are important to elucidation of the mechanisms of transcriptional regulation: (i) de novo motif finding for a given set of promoter sequences along with statistical scores for the predicted motifs derived based on information extracted from a control set, (ii) scanning motif instances of a query motif in provided genomic sequences, (iii) motif comparison and clustering of identified motifs, and (iv) co-occurrence analyses of query motifs in given promoter sequences. The server is powered by a backend computer cluster with over 150 computing nodes, and is particularly useful for motif prediction and analyses in prokaryotic genomes. We believe that DMINDA, as a new and comprehensive web server for cis-regulatory motif finding and analyses, will benefit the genomic research community in general and prokaryotic genome researchers in particular. PMID:24753419

  12. DMINDA: an integrated web server for DNA motif identification and analyses.

    Science.gov (United States)

    Ma, Qin; Zhang, Hanyuan; Mao, Xizeng; Zhou, Chuan; Liu, Bingqiang; Chen, Xin; Xu, Ying

    2014-07-01

    DMINDA (DNA motif identification and analyses) is an integrated web server for DNA motif identification and analyses, which is accessible at http://csbl.bmb.uga.edu/DMINDA/. This web site is freely available to all users and there is no login requirement. This server provides a suite of cis-regulatory motif analysis functions on DNA sequences, which are important to elucidation of the mechanisms of transcriptional regulation: (i) de novo motif finding for a given set of promoter sequences along with statistical scores for the predicted motifs derived based on information extracted from a control set, (ii) scanning motif instances of a query motif in provided genomic sequences, (iii) motif comparison and clustering of identified motifs, and (iv) co-occurrence analyses of query motifs in given promoter sequences. The server is powered by a backend computer cluster with over 150 computing nodes, and is particularly useful for motif prediction and analyses in prokaryotic genomes. We believe that DMINDA, as a new and comprehensive web server for cis-regulatory motif finding and analyses, will benefit the genomic research community in general and prokaryotic genome researchers in particular. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

  13. Adaptive Reference Control for Pressure Management in Water Networks

    DEFF Research Database (Denmark)

    Kallesøe, Carsten; Jensen, Tom Nørgaard; Wisniewski, Rafal

    2015-01-01

    Water scarcity is an increasing problem worldwide and at the same time a huge amount of water is lost through leakages in the distribution network. It is well known that improved pressure control can lower the leakage problems. In this work water networks with a single pressure actuator and several....... Subsequently, these relations are exploited in an adaptive reference control scheme for the actuator pressure that ensures constant pressure at the critical points. Numerical experiments underpin the results. © Copyright IEEE - All rights reserved....

  14. Probabilistic Priority Message Checking Modeling Based on Controller Area Networks

    Science.gov (United States)

    Lin, Cheng-Min

    Although the probabilistic model checking tool called PRISM has been applied in many communication systems, such as wireless local area network, Bluetooth, and ZigBee, the technique is not used in a controller area network (CAN). In this paper, we use PRISM to model the mechanism of priority messages for CAN because the mechanism has allowed CAN to become the leader in serial communication for automobile and industry control. Through modeling CAN, it is easy to analyze the characteristic of CAN for further improving the security and efficiency of automobiles. The Markov chain model helps us to model the behaviour of priority messages.

  15. Adaptive nonlinear control of missiles using neural networks

    Science.gov (United States)

    McFarland, Michael Bryan

    Research has shown that neural networks can be used to improve upon approximate dynamic inversion for control of uncertain nonlinear systems. In one architecture, the neural network adaptively cancels inversion errors through on-line learning. Such learning is accomplished by a simple weight update rule derived from Lyapunov theory, thus assuring stability of the closed-loop system. In this research, previous results using linear-in-parameters neural networks were reformulated in the context of a more general class of composite nonlinear systems, and the control scheme was shown to possess important similarities and major differences with established methods of adaptive control. The neural-adaptive nonlinear control methodology in question has been used to design an autopilot for an anti-air missile with enhanced agile maneuvering capability, and simulation results indicate that this approach is a feasible one. There are, however, certain difficulties associated with choosing the proper network architecture which make it difficult to achieve the rapid learning required in this application. Accordingly, this technique has been further extended to incorporate the important class of feedforward neural networks with a single hidden layer. These neural networks feature well-known approximation capabilities and provide an effective, although nonlinear, parameterization of the adaptive control problem. Numerical results from a six-degree-of-freedom nonlinear agile anti-air missile simulation demonstrate the effectiveness of the autopilot design based on multilayer networks. Previous work in this area has implicitly assumed precise knowledge of the plant order, and made no allowances for unmodeled dynamics. This thesis describes an approach to the problem of controlling a class of nonlinear systems in the face of both unknown nonlinearities and unmodeled dynamics. The proposed methodology is similar to robust adaptive control techniques derived for control of linear

  16. ACTS TDMA network control. [Advanced Communication Technology Satellite

    Science.gov (United States)

    Inukai, T.; Campanella, S. J.

    1984-01-01

    This paper presents basic network control concepts for the Advanced Communications Technology Satellite (ACTS) System. Two experimental systems, called the low-burst-rate and high-burst-rate systems, along with ACTS ground system features, are described. The network control issues addressed include frame structures, acquisition and synchronization procedures, coordinated station burst-time plan and satellite-time plan changes, on-board clock control based on ground drift measurements, rain fade control by means of adaptive forward-error-correction (FEC) coding and transmit power augmentation, and reassignment of channel capacities on demand. The NASA ground system, which includes a primary station, diversity station, and master control station, is also described.

  17. Connection adaption for control of networked mobile chaotic agents.

    Science.gov (United States)

    Zhou, Jie; Zou, Yong; Guan, Shuguang; Liu, Zonghua; Xiao, Gaoxi; Boccaletti, S

    2017-11-22

    In this paper, we propose a strategy for the control of mobile chaotic oscillators by adaptively rewiring connections between nearby agents with local information. In contrast to the dominant adaptive control schemes where coupling strength is adjusted continuously according to the states of the oscillators, our method does not request adaption of coupling strength. As the resulting interaction structure generated by this proposed strategy is strongly related to unidirectional chains, by investigating synchronization property of unidirectional chains, we reveal that there exists a certain coupling range in which the agents could be controlled regardless of the length of the chain. This feature enables the adaptive strategy to control the mobile oscillators regardless of their moving speed. Compared with existing adaptive control strategies for networked mobile agents, our proposed strategy is simpler for implementation where the resulting interaction networks are kept unweighted at all time.

  18. An architecture for designing fuzzy logic controllers using neural networks

    Science.gov (United States)

    Berenji, Hamid R.

    1991-01-01

    Described here is an architecture for designing fuzzy controllers through a hierarchical process of control rule acquisition and by using special classes of neural network learning techniques. A new method for learning to refine a fuzzy logic controller is introduced. A reinforcement learning technique is used in conjunction with a multi-layer neural network model of a fuzzy controller. The model learns by updating its prediction of the plant's behavior and is related to the Sutton's Temporal Difference (TD) method. The method proposed here has the advantage of using the control knowledge of an experienced operator and fine-tuning it through the process of learning. The approach is applied to a cart-pole balancing system.

  19. Discrete-event control of stochastic networks multimodularity and regularity

    CERN Document Server

    Altman, Eitan; Hordijk, Arie

    2003-01-01

    Opening new directions in research in both discrete event dynamic systems as well as in stochastic control, this volume focuses on a wide class of control and of optimization problems over sequences of integer numbers. This is a counterpart of convex optimization in the setting of discrete optimization. The theory developed is applied to the control of stochastic discrete-event dynamic systems. Some applications are admission, routing, service allocation and vacation control in queueing networks. Pure and applied mathematicians will enjoy reading the book since it brings together many disciplines in mathematics: combinatorics, stochastic processes, stochastic control and optimization, discrete event dynamic systems, algebra.

  20. Networked vision system using a Prolog controller

    Science.gov (United States)

    Batchelor, B. G.; Caton, S. J.; Chatburn, L. T.; Crowther, R. A.; Miller, J. W. V.

    2005-11-01

    Prolog offers a very different style of programming compared to conventional languages; it can define object properties and abstract relationships in a way that Java, C, C++, etc. find awkward. In an accompanying paper, the authors describe how a distributed web-based vision systems can be built using elements that may even be located on different continents. One particular system of this general type is described here. The top-level controller is a Prolog program, which operates one, or more, image processing engines. This type of function is natural to Prolog, since it is able to reason logically using symbolic (non-numeric) data. Although Prolog is not suitable for programming image processing functions directly, it is ideal for analysing the results derived by an image processor. This article describes the implementation of two systems, in which a Prolog program controls several image processing engines, a simple robot, a pneumatic pick-and-place arm), LED illumination modules and a various mains-powered devices.

  1. Experimental determination of group flux control coefficients in metabolic networks

    Energy Technology Data Exchange (ETDEWEB)

    Simpson, T.W.; Shimizu, Hiroshi; Stephanopoulos, G. [Massachusetts Inst. of Tech., Cambridge, MA (United States). Dept. of Chemical Engineering

    1998-04-20

    Grouping of reactions around key metabolite branch points can facilitate the study of metabolic control of complex metabolic networks. This top-down Metabolic Control Analysis is exemplified through the introduction of group control coefficients whose magnitudes provide a measure of the relative impact of each reaction group on the overall network flux, as well as on the overall network stability, following enzymatic amplification. In this article, the authors demonstrate the application of previously developed theory to the determination of group flux control coefficients. Experimental data for the changes in metabolic fluxes obtained in response to the introduction of six different environmental perturbations are used to determine the group flux control coefficients for three reaction groups formed around the phosphoenolpyruvate/pyruvate branch point. The consistency of the obtained group flux control coefficient estimates is systematically analyzed to ensure that all necessary conditions are satisfied. The magnitudes of the determined control coefficients suggest that the control of lysine production flux in Corynebacterium glutamicum cells at a growth base state resides within the lysine biosynthetic pathway that begins with the PEP/PYR carboxylation anaplorotic pathway.

  2. Spiking neural network-based control chart pattern recognition

    Directory of Open Access Journals (Sweden)

    Medhat H.A. Awadalla

    2012-03-01

    Full Text Available Due to an increasing competition in products, consumers have become more critical in choosing products. The quality of products has become more important. Statistical Process Control (SPC is usually used to improve the quality of products. Control charting plays the most important role in SPC. Control charts help to monitor the behavior of the process to determine whether it is stable or not. Unnatural patterns in control charts mean that there are some unnatural causes for variations in SPC. Spiking neural networks (SNNs are the third generation of artificial neural networks that consider time as an important feature for information representation and processing. In this paper, a spiking neural network architecture is proposed to be used for control charts pattern recognition (CCPR. Furthermore, enhancements to the SpikeProp learning algorithm are proposed. These enhancements provide additional learning rules for the synaptic delays, time constants and for the neurons thresholds. Simulated experiments have been conducted and the achieved results show a remarkable improvement in the overall performance compared with artificial neural networks.

  3. Steam turbine stress control using NARX neural network

    Science.gov (United States)

    Dominiczak, Krzysztof; Rzadkowski, Romuald; Radulski, Wojciech

    2015-11-01

    Considered here is concept of steam turbine stress control, which is based on Nonlinear AutoRegressive neural networks with eXogenous inputs. Using NARX neural networks,whichwere trained based on experimentally validated FE model allows to control stresses in protected thickwalled steam turbine element with FE model quality. Additionally NARX neural network, which were trained base on FE model, includes: nonlinearity of steam expansion in turbine steam path during transients, nonlinearity of heat exchange inside the turbine during transients and nonlinearity of material properties during transients. In this article NARX neural networks stress controls is shown as an example of HP rotor of 18K390 turbine. HP part thermodynamic model as well as heat exchange model in vicinity of HP rotor,whichwere used in FE model of the HP rotor and the HP rotor FE model itself were validated based on experimental data for real turbine transient events. In such a way it is ensured that NARX neural network behave as real HP rotor during steam turbine transient events.

  4. The Adaptive Neural Network Control of Quadrotor Helicopter

    Directory of Open Access Journals (Sweden)

    A. S. Yushenko

    2017-01-01

    Full Text Available The current steady-rising interest in using the unmanned multi-rotor aerial vehicles (UMAV designed to solve a wide range of tasks is, mainly, due to their simple design and high weight-carrying capacity as compared to classical helicopter options. Unfortunately, to solve a problem of multi-copter control is complicated because of essential nonlinearity and environmental perturbations. The most widely spread PID controllers and linear-quadratic regulators do not quite well cope with this task. The need arises for the prompt adjustment of PID controller coefficients in the course of operation or their complete re-tuning in cases of changing parameters of the control object.One of the control methods under changing conditions is the use of the sliding mode. This technology enables us to reach the stabilization and proper operation of the controlled system even under accidental external exposures and when there is a lack of the reasonably accurate mathematical model of the control object. The sliding principle is to ensure the system motion in the immediate vicinity of the sliding surface in the phase space. On the other hand, the sliding mode has some essential disadvantages. The most significant one is the high-frequency jitter of the system near the sliding surface. The sliding mode also implies the complete knowledge of the system dynamics. Various methods have been proposed to eliminate these drawbacks. For example, A.G. Aissaoui’s, H. Abid’s and M. Abid’s paper describes the application of fuzzy logic to control a drive and in Lon-Chen Hung’s and Hung-Yuan Chung’s paper an artificial neural network is used for the manipulator control.This paper presents a method of the quad-copter control with the aid of a neural network controller. This method enables us to control the system without a priori information on parameters of the dynamic model of the controlled object. The main neural network is a MIMO (“Multiple Input Multiple

  5. Information spread in networks: Games, optimal control, and stabilization

    Science.gov (United States)

    Khanafer, Ali

    This thesis focuses on designing efficient mechanisms for controlling information spread in networks. We consider two models for information spread. The first one is the well-known distributed averaging dynamics. The second model is a nonlinear one that describes virus spread in computer and biological networks. We seek to design optimal, robust, and stabilizing controllers under practical constraints. For distributed averaging networks, we study the interaction between a network designer and an adversary. We consider two types of attacks on the network. In Attack-I, the adversary strategically disconnects a set of links to prevent the nodes from reaching consensus. Meanwhile, the network designer assists the nodes in reaching consensus by changing the weights of a limited number of links in the network. We formulate two problems to describe this competition where the order in which the players act is reversed in the two problems. Although the canonical equations provided by the Pontryagin's Maximum Principle (MP) seem to be intractable, we provide an alternative characterization for the optimal strategies that makes connection to potential theory. Further, we provide a sufficient condition for the existence of a saddle-point equilibrium (SPE) for the underlying zero-sum game. In Attack-II, the designer and the adversary are both capable of altering the measurements of all nodes in the network by injecting global signals. We impose two constraints on both players: a power constraint and an energy constraint. We assume that the available energy to each player is not sufficient to operate at maximum power throughout the horizon of the game. We show the existence of an SPE and derive the optimal strategies in closed form for this attack scenario. As an alternative to the "network designer vs. adversary" framework, we investigate the possibility of stabilizing unknown network diffusion processes using a distributed mechanism, where the uncertainty is due to an attack

  6. Adaptive control of call acceptance in WCDMA network

    Directory of Open Access Journals (Sweden)

    Milan Manojle Šunjevarić

    2013-10-01

    Full Text Available In this paper, an overview of the algorithms for access control in mobile wireless networks is presented. A review of adaptive control methods of accepting a call in WCDMA networks is discussed, based on the overview of the algorithms used for this purpose, and their comparison. Appropriate comments and conculsions in comparison with the basic characteristics of these algorithms are given. The OVSF codes are explained as well as how the allocation method influences the capacity and probability of blocking.. Introduction We are witnessing a steady increase in the number of demands placed upon modern wireless networks. New applications and an increasing number of users as well as user activities growth in recent years reinforce the need for an efficient use of the spectrum and its proper distribution among different applications and classes of services. Besides humans, the last few years saw different computers, machines, applications, and, in the future, many other devices, RFID applications, and finally networked objects, as a new kind of wireless networks "users". Because of the exceptional rise in the number of users, the demands placed upon modern wireless networks are becoming larger, and spectrum management plays an important role. For these reasons, choosing an appropriate call admission control algorithm is of great importance. Multiple access and resource management in wireless networks Radio resource management of mobile networks is a set of algorithms to manage the use of radio resources with the aim is to maximize the total capacity of wireless systems with equal distribution of resources to users. Management of radio resources in cellular networks is usually located in the base station controller, the base station and the mobile terminal, and is based on decisions made on appropriate measurement and feedback. It is often defined as the maximum volume of traffic load that the system can provide for some of the requirements for the

  7. Formation control for a network of small-scale robots.

    Science.gov (United States)

    Kim, Yoonsoo

    2014-10-01

    In this paper, a network of small-scale robots (typically centimeter-scale robots) equipped with artificial actuators such as electric motors is considered. The purpose of this network is to have the robots keep a certain formation shape (or change to another formation shape) during maneuvers. The network has a fixed communication topology in the sense that robots have a fixed group of neighbors to communicate during maneuvers. Assuming that each robot and its actuator can be modeled as a linear system, a decentralized control law (such that each robot activates its actuator based on the information from its neighbors only) is introduced to achieve the purpose of formation keeping or change. A linear matrix inequality (LMI) for deriving the upper bound on the actuator's time constant is also presented. Simulation results are shown to demonstrate the merit of the introduced control law.

  8. Sparse Packetized Predictive Control for Networked Control over Erasure Channels

    DEFF Research Database (Denmark)

    Nagahara, Masaaki; Quevedo, Daniel E.; Østergaard, Jan

    2014-01-01

    We study feedback control over erasure channels with packet-dropouts. To achieve robustness with respect to packet-dropouts, the controller transmits data packets containing plant input predictions, which minimize a finite horizon cost function. To reduce the data size of packets, we propose...... to adopt sparsity-promoting optimizations, namely, l1 - l2 and l2-constrained l0 optimizations, for which efficient algorithms exist. We show how to design the tuning parameters to ensure (practical) stability of the resulting feedback control systems when the number of consecutive packet...

  9. High Resolution Sensing and Control of Urban Water Networks

    Science.gov (United States)

    Bartos, M. D.; Wong, B. P.; Kerkez, B.

    2016-12-01

    We present a framework to enable high-resolution sensing, modeling, and control of urban watersheds using (i) a distributed sensor network based on low-cost cellular-enabled motes, (ii) hydraulic models powered by a cloud computing infrastructure, and (iii) automated actuation valves that allow infrastructure to be controlled in real time. This platform initiates two major advances. First, we achieve a high density of measurements in urban environments, with an anticipated 40+ sensors over each urban area of interest. In addition to new measurements, we also illustrate the design and evaluation of a "smart" control system for real-world hydraulic networks. This control system improves water quality and mitigates flooding by using real-time hydraulic models to adaptively control releases from retention basins. We evaluate the potential of this platform through two ongoing deployments: (i) a flood monitoring network in the Dallas-Fort Worth metropolitan area that detects and anticipates floods at the level of individual roadways, and (ii) a real-time hydraulic control system in the city of Ann Arbor, MI—soon to be one of the most densely instrumented urban watersheds in the United States. Through these applications, we demonstrate that distributed sensing and control of water infrastructure can improve flash flood predictions, emergency response, and stormwater contaminant mitigation.

  10. H∞ Guaranteed Cost Control for Networked Control Systems under Scheduling Policy Based on Predicted Error

    Directory of Open Access Journals (Sweden)

    Qixin Zhu

    2014-01-01

    Full Text Available Scheduling policy based on model prediction error is presented to reduce energy consumption and network conflicts at the actuator node, where the characters of networked control systems are considered, such as limited network bandwidth, limited node energy, and high collision probability. The object model is introduced to predict the state of system at the sensor node. And scheduling threshold is set at the controller node. Control signal is transmitted only if the absolute value of prediction error is larger than the threshold value. Furthermore, the model of networked control systems under scheduling policy based on predicted error is established by taking uncertain parameters and long time delay into consideration. The design method of H∞ guaranteed cost controller is presented by using the theory of Lyapunov and linear matrix inequality (LMI. Finally, simulations are included to demonstrate the theoretical results.

  11. Converging Redundant Sensor Network Information for Improved Building Control

    Energy Technology Data Exchange (ETDEWEB)

    Dale Tiller; D. Phil; Gregor Henze; Xin Guo

    2007-09-30

    This project investigated the development and application of sensor networks to enhance building energy management and security. Commercial, industrial and residential buildings often incorporate systems used to determine occupancy, but current sensor technology and control algorithms limit the effectiveness of these systems. For example, most of these systems rely on single monitoring points to detect occupancy, when more than one monitoring point could improve system performance. Phase I of the project focused on instrumentation and data collection. During the initial project phase, a new occupancy detection system was developed, commissioned and installed in a sample of private offices and open-plan office workstations. Data acquisition systems were developed and deployed to collect data on space occupancy profiles. Phase II of the project demonstrated that a network of several sensors provides a more accurate measure of occupancy than is possible using systems based on single monitoring points. This phase also established that analysis algorithms could be applied to the sensor network data stream to improve the accuracy of system performance in energy management and security applications. In Phase III of the project, the sensor network from Phase I was complemented by a control strategy developed based on the results from the first two project phases: this controller was implemented in a small sample of work areas, and applied to lighting control. Two additional technologies were developed in the course of completing the project. A prototype web-based display that portrays the current status of each detector in a sensor network monitoring building occupancy was designed and implemented. A new capability that enables occupancy sensors in a sensor network to dynamically set the 'time delay' interval based on ongoing occupant behavior in the space was also designed and implemented.

  12. Control of Resources for Economic Development in Food Networks

    DEFF Research Database (Denmark)

    Brink, Tove

    2010-01-01

    of preferences on the control of resources, the significant benefit of oral instructions and the significant negative impact from supervising product quality on economic development in the context of the food networking SMEs. Previous level of knowledge has no significant influence on their economic development...... to control resources for innovation to add value and economic development. This paper reveals how crossing dynamic composite underlying boundaries can have an impact on control of resources for economic development in food networking SMEs .The analyses in this paper shows the broad and significant impact......The challenge of economic development in the 21st century is linked to innovation. Enabling innovation contains a wide span from the new idea to learning how to provide value through the new idea and continuing to how to control resources to perform at prime. The focus in this paper is set on how...

  13. Two stage neural network modelling for robust model predictive control.

    Science.gov (United States)

    Patan, Krzysztof

    2017-11-02

    The paper proposes a novel robust model predictive control scheme realized by means of artificial neural networks. The neural networks are used twofold: to design the so-called fundamental model of a plant and to catch uncertainty associated with the plant model. In order to simplify the optimization process carried out within the framework of predictive control an instantaneous linearization is applied which renders it possible to define the optimization problem in the form of constrained quadratic programming. Stability of the proposed control system is also investigated by showing that a cost function is monotonically decreasing with respect to time. Derived robust model predictive control is tested and validated on the example of a pneumatic servomechanism working at different operating regimes. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  14. Neural networks for process control and optimization: two industrial applications.

    Science.gov (United States)

    Bloch, Gérard; Denoeux, Thierry

    2003-01-01

    The two most widely used neural models, multilayer perceptron (MLP) and radial basis function network (RBFN), are presented in the framework of system identification and control. The main steps for building such nonlinear black box models are regressor choice, selection of internal architecture, and parameter estimation. The advantages of neural network models are summarized: universal approximation capabilities, flexibility, and parsimony. Two applications are described in steel industry and water treatment, respectively, the control of alloying process in a hot dipped galvanizing line and the control of a coagulation process in a drinking water treatment plant. These examples highlight the interest of neural techniques, when complex nonlinear phenomena are involved, but the empirical knowledge of control operators can be learned.

  15. Handling uncertainty and networked structure in robot control

    CERN Document Server

    Tamás, Levente

    2015-01-01

    This book focuses on two challenges posed in robot control by the increasing adoption of robots in the everyday human environment: uncertainty and networked communication. Part I of the book describes learning control to address environmental uncertainty. Part II discusses state estimation, active sensing, and complex scenario perception to tackle sensing uncertainty. Part III completes the book with control of networked robots and multi-robot teams. Each chapter features in-depth technical coverage and case studies highlighting the applicability of the techniques, with real robots or in simulation. Platforms include mobile ground, aerial, and underwater robots, as well as humanoid robots and robot arms. Source code and experimental data are available at http://extras.springer.com. The text gathers contributions from academic and industry experts, and offers a valuable resource for researchers or graduate students in robot control and perception. It also benefits researchers in related areas, such as computer...

  16. On-board congestion control for satellite packet switching networks

    Science.gov (United States)

    Chu, Pong P.

    1991-01-01

    It is desirable to incorporate packet switching capability on-board for future communication satellites. Because of the statistical nature of packet communication, incoming traffic fluctuates and may cause congestion. Thus, it is necessary to incorporate a congestion control mechanism as part of the on-board processing to smooth and regulate the bursty traffic. Although there are extensive studies on congestion control for both baseband and broadband terrestrial networks, these schemes are not feasible for space based switching networks because of the unique characteristics of satellite link. Here, we propose a new congestion control method for on-board satellite packet switching. This scheme takes into consideration the long propagation delay in satellite link and takes advantage of the the satellite's broadcasting capability. It divides the control between the ground terminals and satellite, but distributes the primary responsibility to ground terminals and only requires minimal hardware resource on-board satellite.

  17. Controlling self-organized criticality in complex networks

    CERN Document Server

    Cajueiro, Daniel O

    2013-01-01

    A control scheme to reduce the size of avalanches of the Bak-Tang-Wiesenfeld model on complex networks is proposed. Three network types are considered: those proposed by Erd\\H{o}s-Renyi, Goh-Kahng-Kim, and a real network representing the main connections of the electrical power grid of the western United States. The control scheme is based on the idea of triggering avalanches in the highest degree nodes that are near to become critical. We show that this strategy works in the sense that the dissipation of mass occurs most locally avoiding larger avalanches. We also compare this strategy with a random strategy where the nodes are chosen randomly. Although the random control has some ability to reduce the probability of large avalanches, its performance is much worse than the one based on the choice of the highest degree nodes. Finally, we argue that the ability of the proposed control scheme is related to its ability to reduce the concentration of mass on the network.

  18. Model-based Compositional Design of Networked Control Systems

    Science.gov (United States)

    2013-12-01

    systems such as tele- robots for surgery , implanted heart monitors, nanoscale di- agnostic instruments, digital protheses and other medical devices, as...exploration, surgery , search and rescue missions, hazardous environment and other various military applications. An n-degrees of freedom robotic manipulator...lives. Examples of these systems include process control, automotive systems, networked robotics , medical systems, electrical power grids and

  19. Adaptive Media Access Control for Energy Harvesting - Wireless Sensor Networks

    DEFF Research Database (Denmark)

    Fafoutis, Xenofon; Dragoni, Nicola

    2012-01-01

    ODMAC (On-Demand Media Access Control) is a recently proposed MAC protocol designed to support individual duty cycles for Energy Harvesting — Wireless Sensor Networks (EH-WSNs). Individual duty cycles are vital for EH-WSNs, because they allow nodes to adapt their energy consumption to the ever...

  20. Ubiquitous access control and policy management in personal networks

    DEFF Research Database (Denmark)

    Kyriazanos, Dimitris M.; Stassinopoulos, George I.; Prasad, Neeli R.

    2006-01-01

    In this paper the authors present the challenges for enabling Security Policies Management and subsequent Ubiquitous Access Control on the Personal Network (PN) environment. A solution based on Security Profiles is proposed, supporting both partially distributed architectures-having in this case...

  1. Specification Mining for Intrusion Detection in Networked Control Systems

    NARCIS (Netherlands)

    Caselli, M.; Zambon, Emmanuele; Amann, Johanna; Sommer, Robin; Kargl, Frank

    2016-01-01

    This paper discusses a novel approach to specification-based intrusion detection in the field of networked control systems. Our approach reduces the substantial human effort required to deploy a specification-based intrusion detection system by automating the development of its specification rules.

  2. Mitotic control of human papillomavirus genome-containing cells is regulated by the function of the PDZ-binding motif of the E6 oncoprotein.

    Science.gov (United States)

    Marsh, Elizabeth K; Delury, Craig P; Davies, Nicholas J; Weston, Christopher J; Miah, Mohammed A L; Banks, Lawrence; Parish, Joanna L; Higgs, Martin R; Roberts, Sally

    2017-03-21

    The function of a conserved PDS95/DLG1/ZO1 (PDZ) binding motif (E6 PBM) at the C-termini of E6 oncoproteins of high-risk human papillomavirus (HPV) types contributes to the development of HPV-associated malignancies. Here, using a primary human keratinocyte-based model of the high-risk HPV18 life cycle, we identify a novel link between the E6 PBM and mitotic stability. In cultures containing a mutant genome in which the E6 PBM was deleted there was an increase in the frequency of abnormal mitoses, including multinucleation, compared to cells harboring the wild type HPV18 genome. The loss of the E6 PBM was associated with a significant increase in the frequency of mitotic spindle defects associated with anaphase and telophase. Furthermore, cells carrying this mutant genome had increased chromosome segregation defects and they also exhibited greater levels of genomic instability, as shown by an elevated level of centromere-positive micronuclei. In wild type HPV18 genome-containing organotypic cultures, the majority of mitotic cells reside in the suprabasal layers, in keeping with the hyperplastic morphology of the structures. However, in mutant genome-containing structures a greater proportion of mitotic cells were retained in the basal layer, which were often of undefined polarity, thus correlating with their reduced thickness. We conclude that the ability of E6 to target cellular PDZ proteins plays a critical role in maintaining mitotic stability of HPV infected cells, ensuring stable episome persistence and vegetative amplification.

  3. Structure and Controls of the Global Virtual Water Trade Network

    Science.gov (United States)

    Suweis, S. S.

    2011-12-01

    Recurrent or ephemeral water shortages are a crucial global challenge, in particular because of their impacts on food production. The global character of this challenge is reflected in the trade among nations of virtual water, i.e. the amount of water used to produce a given commodity. We build, analyze and model the network describing the transfer of virtual water between world nations for staple food products. We find that all the key features of the network are well described by a model, the fitness model, that reproduces both the topological and weighted properties of the global virtual water trade network, by assuming as sole controls each country's gross domestic product and yearly rainfall on agricultural areas. We capture and quantitatively describe the high degree of globalization of water trade and show that a small group of nations play a key role in the connectivity of the network and in the global redistribution of virtual water. Finally, we illustrate examples of prediction of the structure of the network under future political, economic and climatic scenarios, suggesting that the crucial importance of the countries that trade large volumes of water will be strengthened. Our results show the importance of incorporating a network framework in the study of virtual water trades and provide a model to study the structure and resilience of the GVWTN under future scenarios for social, economic and climate change.

  4. Adaptive PID control based on orthogonal endocrine neural networks.

    Science.gov (United States)

    Milovanović, Miroslav B; Antić, Dragan S; Milojković, Marko T; Nikolić, Saša S; Perić, Staniša Lj; Spasić, Miodrag D

    2016-12-01

    A new intelligent hybrid structure used for online tuning of a PID controller is proposed in this paper. The structure is based on two adaptive neural networks, both with built-in Chebyshev orthogonal polynomials. First substructure network is a regular orthogonal neural network with implemented artificial endocrine factor (OENN), in the form of environmental stimuli, to its weights. It is used for approximation of control signals and for processing system deviation/disturbance signals which are introduced in the form of environmental stimuli. The output values of OENN are used to calculate artificial environmental stimuli (AES), which represent required adaptation measure of a second network-orthogonal endocrine adaptive neuro-fuzzy inference system (OEANFIS). OEANFIS is used to process control, output and error signals of a system and to generate adjustable values of proportional, derivative, and integral parameters, used for online tuning of a PID controller. The developed structure is experimentally tested on a laboratory model of the 3D crane system in terms of analysing tracking performances and deviation signals (error signals) of a payload. OENN-OEANFIS performances are compared with traditional PID and 6 intelligent PID type controllers. Tracking performance comparisons (in transient and steady-state period) showed that the proposed adaptive controller possesses performances within the range of other tested controllers. The main contribution of OENN-OEANFIS structure is significant minimization of deviation signals (17%-79%) compared to other controllers. It is recommended to exploit it when dealing with a highly nonlinear system which operates in the presence of undesirable disturbances. Copyright © 2016 Elsevier Ltd. All rights reserved.

  5. Equipment to Support Development of Neuronal Network Controlled Robots

    Science.gov (United States)

    2016-06-25

    Equipment to Support Development of Neuronal Network Controlled Robots With this award, our team purchased an ALA 2-channel stimulus generator, an...34 laser cutter, and a Rethink Robotics Baxter Robot . This equipment supported two ARO awards, a DARPA award and two NSF-funded projects. The views...Controlled Robots Report Title With this award, our team purchased an ALA 2-channel stimulus generator, an ALA 60-channel amplifier with pre-filter

  6. Controllable Soluble Protein Concentration Gradients in Hydrogel Networks**

    OpenAIRE

    Peret, Brian J.; William L Murphy

    2008-01-01

    Here we report controlled formation of sustained, soluble protein concentration gradients within hydrated polymer networks. The approach involves spatially localizing proteins or biodegradable, protein-loaded microspheres within hydrogels to form a protein-releasing “depot”. Soluble protein concentration gradients are then formed as the released protein diffuses away from the localized source. Control over key gradient parameters, including maximum concentration, gradient magnitude, slope, an...

  7. Scalable Harmonization of Complex Networks With Local Adaptive Controllers

    Czech Academy of Sciences Publication Activity Database

    Kárný, Miroslav; Herzallah, R.

    2017-01-01

    Roč. 47, č. 3 (2017), s. 394-404 ISSN 2168-2216 R&D Projects: GA ČR GA13-13502S Institutional support: RVO:67985556 Keywords : Adaptive control * Adaptive estimation * Bayes methods * Complex networks * Decentralized control * Feedback * Feedforward systems * Recursive estimation Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 2.350, year: 2016 http://library.utia.cas.cz/separaty/2016/AS/karny-0457337.pdf

  8. Piecewise-linear artificial neural networks for PID controller tuning

    Directory of Open Access Journals (Sweden)

    Petr Doležel

    2012-12-01

    Full Text Available A new algorithm of PID controller tuning is presented in this paper. It is well known that there have been introduced manytechniques for PID controller tuning, both theoretical and experimental ones. However, this algorithm is suitable especially forhighly nonlinear processes. It uses a model of the controlled process in the shape of piecewise-linear neural network which islinearized continuously and resulting linearized model is used for PID controller online tuning. While at the beginning of the paperthe algorithm is described in theory, at the end there are mentioned some practical applications

  9. Linear Matrix Inequalities in Multirate Control over Networks

    Directory of Open Access Journals (Sweden)

    Ángel Cuenca

    2012-01-01

    Full Text Available This paper faces two of the main drawbacks in networked control systems: bandwidth constraints and timevarying delays. The bandwidth limitations are solved by using multirate control techniques. The resultant multirate controller must ensure closed-loop stability in the presence of time-varying delays. Some stability conditions and a state feedback controller design are formulated in terms of linear matrix inequalities. The theoretical proposal is validated in two different experimental environments: a crane-based test-bed over Ethernet, and a maglev based platform over Profibus.

  10. Adaptive Gain Scheduled Semiactive Vibration Control Using a Neural Network

    Directory of Open Access Journals (Sweden)

    Kazuhiko Hiramoto

    2018-01-01

    Full Text Available We propose an adaptive gain scheduled semiactive control method using an artificial neural network for structural systems subject to earthquake disturbance. In order to design a semiactive control system with high control performance against earthquakes with different time and/or frequency properties, multiple semiactive control laws with high performance for each of multiple earthquake disturbances are scheduled with an adaptive manner. Each semiactive control law to be scheduled is designed based on the output emulation approach that has been proposed by the authors. As the adaptive gain scheduling mechanism, we introduce an artificial neural network (ANN. Input signals of the ANN are the measured earthquake disturbance itself, for example, the acceleration, velocity, and displacement. The output of the ANN is the parameter for the scheduling of multiple semiactive control laws each of which has been optimized for a single disturbance. Parameters such as weight and bias in the ANN are optimized by the genetic algorithm (GA. The proposed design method is applied to semiactive control design of a base-isolated building with a semiactive damper. With simulation study, the proposed adaptive gain scheduling method realizes control performance exceeding single semiactive control optimizing the average of the control performance subject to various earthquake disturbances.

  11. MEET: motif elements estimation toolkit.

    Science.gov (United States)

    Pairó, Erola; Maynou, Joan; Vallverdú, Montserrat; Caminal, Pere; Marco, Santiago; Perera, Alexandre

    2011-01-01

    MEET is an R package that integrates a set of algorithms for the detection of transcription factor binding sites (TFBS). The MEET R package includes five motif searching algorithms: MEME/MAST(Multiple Expectation-Maximization for Motif Elicitation), Q-residuals, MDscan (Motif Discovery scan), ITEME (Information Theory Elements for Motif Estimation) and MATCH. In addition MEET allows the user to work with different alignment algorithms: MUSCLE (Multiple Sequence Comparison by Log-Expectation), ClustalW and MEME. The package can work in two modes, training and detection. The training mode allows the user to choose the best parameters of a detector. Once the parameters are chosen, the detection mode allows to analyze a genome looking for binding sites. Both modes can combine the different alignment and detection methods, offering multiple possibilities. Combining the alignments and the detection algorithms makes possible the comparison between detection models at the same level, without having to care about the differences produced during the alignment process. The MEET R package can be downloaded from http://sisbio.recerca.upc.edu/R/MEET_1.0. tar.gz.

  12. Discovering motifs in ranked lists of DNA sequences.

    Directory of Open Access Journals (Sweden)

    Eran Eden

    2007-03-01

    Full Text Available Computational methods for discovery of sequence elements that are enriched in a target set compared with a background set are fundamental in molecular biology research. One example is the discovery of transcription factor binding motifs that are inferred from ChIP-chip (chromatin immuno-precipitation on a microarray measurements. Several major challenges in sequence motif discovery still require consideration: (i the need for a principled approach to partitioning the data into target and background sets; (ii the lack of rigorous models and of an exact p-value for measuring motif enrichment; (iii the need for an appropriate framework for accounting for motif multiplicity; (iv the tendency, in many of the existing methods, to report presumably significant motifs even when applied to randomly generated data. In this paper we present a statistical framework for discovering enriched sequence elements in ranked lists that resolves these four issues. We demonstrate the implementation of this framework in a software application, termed DRIM (discovery of rank imbalanced motifs, which identifies sequence motifs in lists of ranked DNA sequences. We applied DRIM to ChIP-chip and CpG methylation data and obtained the following results. (i Identification of 50 novel putative transcription factor (TF binding sites in yeast ChIP-chip data. The biological function of some of them was further investigated to gain new insights on transcription regulation networks in yeast. For example, our discoveries enable the elucidation of the network of the TF ARO80. Another finding concerns a systematic TF binding enhancement to sequences containing CA repeats. (ii Discovery of novel motifs in human cancer CpG methylation data. Remarkably, most of these motifs are similar to DNA sequence elements bound by the Polycomb complex that promotes histone methylation. Our findings thus support a model in which histone methylation and CpG methylation are mechanistically linked

  13. Active Vibration Control of the Smart Plate Using Artificial Neural Network Controller

    Directory of Open Access Journals (Sweden)

    Mohit

    2015-01-01

    Full Text Available The active vibration control (AVC of a rectangular plate with single input and single output approach is investigated using artificial neural network. The cantilever plate of finite length, breadth, and thickness having piezoelectric patches as sensors/actuators fixed at the upper and lower surface of the metal plate is considered for examination. The finite element model of the cantilever plate is utilized to formulate the whole strategy. The compact RIO and MATLAB simulation software are exercised to get the appropriate results. The cantilever plate is subjected to impulse input and uniform white noise disturbance. The neural network is trained offline and tuned with LQR controller. The various training algorithms to tune the neural network are exercised. The best efficient algorithm is finally considered to tune the neural network controller designed for active vibration control of the smart plate.

  14. Mechanisms of Zero-Lag Synchronization in Cortical Motifs

    Science.gov (United States)

    Gollo, Leonardo L.; Mirasso, Claudio; Sporns, Olaf; Breakspear, Michael

    2014-01-01

    Zero-lag synchronization between distant cortical areas has been observed in a diversity of experimental data sets and between many different regions of the brain. Several computational mechanisms have been proposed to account for such isochronous synchronization in the presence of long conduction delays: Of these, the phenomenon of “dynamical relaying” – a mechanism that relies on a specific network motif – has proven to be the most robust with respect to parameter mismatch and system noise. Surprisingly, despite a contrary belief in the community, the common driving motif is an unreliable means of establishing zero-lag synchrony. Although dynamical relaying has been validated in empirical and computational studies, the deeper dynamical mechanisms and comparison to dynamics on other motifs is lacking. By systematically comparing synchronization on a variety of small motifs, we establish that the presence of a single reciprocally connected pair – a “resonance pair” – plays a crucial role in disambiguating those motifs that foster zero-lag synchrony in the presence of conduction delays (such as dynamical relaying) from those that do not (such as the common driving triad). Remarkably, minor structural changes to the common driving motif that incorporate a reciprocal pair recover robust zero-lag synchrony. The findings are observed in computational models of spiking neurons, populations of spiking neurons and neural mass models, and arise whether the oscillatory systems are periodic, chaotic, noise-free or driven by stochastic inputs. The influence of the resonance pair is also robust to parameter mismatch and asymmetrical time delays amongst the elements of the motif. We call this manner of facilitating zero-lag synchrony resonance-induced synchronization, outline the conditions for its occurrence, and propose that it may be a general mechanism to promote zero-lag synchrony in the brain. PMID:24763382

  15. Tuning RED parameters in satellite networks using control theory

    Science.gov (United States)

    Sridharan, Mukundan; Durresi, Arjan; Chellappan, Sriram; Ozbay, Hitay; Jain, Raj

    2003-08-01

    Congestion in the Internet results in wasted bandwidth and also stands in the way of guaranteeing QoS. The effect of congestion is multiplied many fold in Satellite networks, where the resources are very expensive. Thus congestion control has a special significance in the performance of Satellite networks. In today's Internet, congestion control is implemented mostly using some form of the de facto standard, RED. But tuning of parameters in RED has been a major problem throughout. Achieving high throughput with corresponding low delays is the main goal in parameter setting. It is also desired to keep the oscillations in the queue low to reduce jitter, so that the QoS guarantees can be improved. In this paper, we use a previously linearized fluid flow model of TCP-RED to study the performance and stability of the Queue in the router. We use classical control tools like Tracking Error minimization and Delay Margin to study the performance, stability of the system. We use the above-mentioned tools to provide guidelines for setting the parameters in RED, such that the throughput, delay and jitter of the system are optimized. Thus we provide guidelines for optimizing satellite IP networks. We apply our results exclusively for optimizing the performance of satellite networks, where the effects of congestion are much pronounced and need for optimization is much important. We use ns simulator to validate our results to support our analysis.

  16. Context-Based Topology Control for Wireless Mesh Networks

    Directory of Open Access Journals (Sweden)

    Pragasen Mudali

    2016-01-01

    Full Text Available Topology Control has been shown to provide several benefits to wireless ad hoc and mesh networks. However these benefits have largely been demonstrated using simulation-based evaluations. In this paper, we demonstrate the negative impact that the PlainTC Topology Control prototype has on topology stability. This instability is found to be caused by the large number of transceiver power adjustments undertaken by the prototype. A context-based solution is offered to reduce the number of transceiver power adjustments undertaken without sacrificing the cumulative transceiver power savings and spatial reuse advantages gained from employing Topology Control in an infrastructure wireless mesh network. We propose the context-based PlainTC+ prototype and show that incorporating context information in the transceiver power adjustment process significantly reduces topology instability. In addition, improvements to network performance arising from the improved topology stability are also observed. Future plans to add real-time context-awareness to PlainTC+ will have the scheme being prototyped in a software-defined wireless mesh network test-bed being planned.

  17. Controllable Reconfiguration of Polymer-grafted Nanoparticle Networks Under Torsion

    Science.gov (United States)

    Zhang, Tao; Mbanga, Badel; Yashin, Victor; Balazs, Anna

    We use 3D computational modeling to study mechanically-induced changes in the structure of networks formed from polymer-grafted nanoparticles (PGNs). The nanoparticles rigid cores are decorated with a corona of grafted polymers, which contain reactive functional groups at the chain ends. With the overlap of the grafted polymers, these reactive groups can form labile bonds, which can reform after breakage. These PGN networks consist of two types of nanoparticles, which differ in the reactive functional groups at the chain ends. The energy of the labile bonds that are formed depends on the nature of these reactive groups. We demonstrate that the application of a rotational deformation results in a controllable reconfiguration of the network. Depending on the labile bond energies, the PGN networks are shown to exhibit a deformation-induced phase separation. The restructuring process can be controlled by boundary conditions. We can create complicated morphology such as spiral, with enhanced mechanical properties. Our results provide guidelines for designing mechano-mutable PGN-based materials whose nanoscale structures can be controllably changed under an applied mechanical action.

  18. Network efficient power control for wireless communication systems.

    Science.gov (United States)

    Campos-Delgado, Daniel U; Luna-Rivera, Jose Martin; Martinez-Sánchez, C J; Gutierrez, Carlos A; Tecpanecatl-Xihuitl, J L

    2014-01-01

    We introduce a two-loop power control that allows an efficient use of the overall power resources for commercial wireless networks based on cross-layer optimization. This approach maximizes the network's utility in the outer-loop as a function of the averaged signal to interference-plus-noise ratio (SINR) by considering adaptively the changes in the network characteristics. For this purpose, the concavity property of the utility function was verified with respect to the SINR, and an iterative search was proposed with guaranteed convergence. In addition, the outer-loop is in charge of selecting the detector that minimizes the overall power consumption (transmission and detection). Next the inner-loop implements a feedback power control in order to achieve the optimal SINR in the transmissions despite channel variations and roundtrip delays. In our proposal, the utility maximization process and detector selection and feedback power control are decoupled problems, and as a result, these strategies are implemented at two different time scales in the two-loop framework. Simulation results show that substantial utility gains may be achieved by improving the power management in the wireless network.

  19. Nrf2 is controlled by two distinct β-TrCP recognition motifs in its Neh6 domain, one of which can be modulated by GSK-3 activity.

    Science.gov (United States)

    Chowdhry, Sudhir; Zhang, Yiguo; McMahon, Michael; Sutherland, Calum; Cuadrado, Antonio; Hayes, John D.

    2012-01-01

    Identification of regulatable mechanisms by which transcription factor NF-E2 p45-related factor 2 (Nrf2) is repressed will allow strategies to be designed that counter drug resistance associated with its up-regulation in tumours that harbour somatic mutations in Kelch-like ECH-associated protein-1 (Keap1), a gene that encodes a joint adaptor and substrate receptor for the Cul3-Rbx1/Roc1 ubiquitin ligase. We now show that mouse Nrf2 contains two binding sites for β-transducin repeat-containing protein (β-TrCP), which acts as a substrate receptor for the Skp1-Cul1-Rbx1/Roc1 ubiquitin ligase complex. Deletion of either binding site in Nrf2 decreased β-TrCP-mediated ubiquitylation of the transcription factor. The ability of one of the two β-TrCP-binding sites to serve as a degron could be both increased and decreased by manipulation of glycogen synthase kinase-3 (GSK-3) activity. Biotinylated-peptide pull-down assays identified DSGIS338 and DSAPGS378 as the two β-TrCP-binding motifs in Nrf2. Significantly, our pull-down assays indicated that β-TrCP binds a phosphorylated version of DSGIS more tightly than its non-phosphorylated counterpart, whereas this was not the case for DSAPGS. These data suggest that DSGIS, but not DSAPGS, contains a functional GSK-3 phosphorylation site. Activation of GSK-3 in Keap1-null mouse embryonic fibroblasts (MEFs), or in human lung A549 cells that contain mutant Keap1, by inhibition of the phosphoinositide 3-kinase (PI3K) – protein kinase B (PKB)/Akt pathway markedly reduced endogenous Nrf2 protein and decreased to 10-50% of normal the levels of mRNA for prototypic Nrf2-regulated enzymes, including the glutamate-cysteine ligase catalytic and modifier subunits, glutathione S-transferases Alpha-1 and Mu-1, heme oxygenase-1 and NAD(P)H:quinone oxidoreductase-1. Pre-treatment of Keap1−/− MEFs or A549 cells with the LY294002 PI3K inhibitor or the MK-2206 PKB/Akt inhibitor increased their sensitivity to acrolein, chlorambucil and

  20. Iterative Learning Control with Forgetting Factor for Urban Road Network

    Directory of Open Access Journals (Sweden)

    Tianyi Lan

    2017-01-01

    Full Text Available In order to improve the traffic condition, a novel iterative learning control (ILC algorithm with forgetting factor for urban road network is proposed by using the repeat characteristics of traffic flow in this paper. Rigorous analysis shows that the proposed ILC algorithm can guarantee the asymptotic convergence. Through iterative learning control of the traffic signals, the number of vehicles on each road in the network can gradually approach the desired level, thereby preventing oversaturation and traffic congestion. The introduced forgetting factor can effectively adjust the control input according to the states of the system and filter along the direction of the iteration. The results show that the forgetting factor has an important effect on the robustness of the system. The theoretical analysis and experimental simulations are given to verify the validity of the proposed method.

  1. Spontaneous centralization of control in a network of company ownerships.

    Directory of Open Access Journals (Sweden)

    Sebastian M Krause

    Full Text Available We introduce a model for the adaptive evolution of a network of company ownerships. In a recent work it has been shown that the empirical global network of corporate control is marked by a central, tightly connected "core" made of a small number of large companies which control a significant part of the global economy. Here we show how a simple, adaptive "rich get richer" dynamics can account for this characteristic, which incorporates the increased buying power of more influential companies, and in turn results in even higher control. We conclude that this kind of centralized structure can emerge without it being an explicit goal of these companies, or as a result of a well-organized strategy.

  2. Control of Stochastic and Induced Switching in Biophysical Networks

    Science.gov (United States)

    Wells, Daniel K.; Kath, William L.; Motter, Adilson E.

    2015-07-01

    Noise caused by fluctuations at the molecular level is a fundamental part of intracellular processes. While the response of biological systems to noise has been studied extensively, there has been limited understanding of how to exploit it to induce a desired cell state. Here we present a scalable, quantitative method based on the Freidlin-Wentzell action to predict and control noise-induced switching between different states in genetic networks that, conveniently, can also control transitions between stable states in the absence of noise. We apply this methodology to models of cell differentiation and show how predicted manipulations of tunable factors can induce lineage changes, and further utilize it to identify new candidate strategies for cancer therapy in a cell death pathway model. This framework offers a systems approach to identifying the key factors for rationally manipulating biophysical dynamics, and should also find use in controlling other classes of noisy complex networks.

  3. Predictive Closed-Loop Power Control for CDMA Cellular Networks

    Science.gov (United States)

    Choe, Sangho; Uysal, Murat

    In this paper, we present and analyze a predictive closedloop power control (CLPC) scheme which employs a comb-type sample arrangement to effectively compensate multiple power control group (PCG) delays over mobile fading channels. We consider both least squares and recursive least squares filters in our CLPC scheme. The effects of channel estimation error, prediction filter error, and power control bit transmission error on the performance of the proposed CLPC method along with competing non-predictive and predictive CLPC schemes are thoroughly investigated. Our results clearly indicate the superiority of the proposed scheme with its improved robustness under non-ideal conditions. Furthermore, we carry out a Monte-Carlo simulation study of a 5×5 square grid cellular network and evaluate the user capacity. Capacity improvements up to 90% are observed for a typical cellular network scenario.

  4. Camera Control and Geo-Registration for Video Sensor Networks

    Science.gov (United States)

    Davis, James W.

    With the use of large video networks, there is a need to coordinate and interpret the video imagery for decision support systems with the goal of reducing the cognitive and perceptual overload of human operators. We present computer vision strategies that enable efficient control and management of cameras to effectively monitor wide-coverage areas, and examine the framework within an actual multi-camera outdoor urban video surveillance network. First, we construct a robust and precise camera control model for commercial pan-tilt-zoom (PTZ) video cameras. In addition to providing a complete functional control mapping for PTZ repositioning, the model can be used to generate wide-view spherical panoramic viewspaces for the cameras. Using the individual camera control models, we next individually map the spherical panoramic viewspace of each camera to a large aerial orthophotograph of the scene. The result provides a unified geo-referenced map representation to permit automatic (and manual) video control and exploitation of cameras in a coordinated manner. The combined framework provides new capabilities for video sensor networks that are of significance and benefit to the broad surveillance/security community.

  5. TCP flow control using link layer information in mobile networks

    Science.gov (United States)

    Koga, Hiroyuki; Kawahara, Kenji; Oie, Yuji

    2002-07-01

    Mobile Networks have been expanding and IMT-2000 further increases their available bandwidth over wireless links. However, TCP, which is a reliable end-to-end transport protocol, is tuned to perform well in wired networks where bit error rates are very low and packet loss occurs mostly because of congestion. Although a TCP sender can execute flow control to utilize as much available bandwidth as possible in wired networks, it cannot work well in wireless networks characterized by high bit error rates. In the next generation mobile systems, sophisticated error recovery technologies of FEC and ARQ are indeed employed over wireless links, i.e., over Layer 2, to avoid performance degradation of upper layers. However, multiple retransmissions by Layer 2 ARQ can adversely increase transmission delay of TCP segments, which will further make TCP unnecessarily increase RTO (Retransmission TimeOut). Furthermore, a link bandwidth assigned to TCP flows can change in response to changing air conditions to use wireless links efficiently. TCP thus has to adapt its transmission rate according to the changing available bandwidth. The major goal of this study is to develop a receiver-based effective TCP flow control without any modification on TCP senders, which are probably connected with wired networks. For this end, we propose a TCP flow control employing some Layer 2 information on a wireless link at the mobile station. Our performance evaluation of the proposed TCP shows that the receiver-based TCP flow control can moderate the performance degradation very well even if FER on Layer 2 is high.

  6. The network control system of high-bay warehouse

    Directory of Open Access Journals (Sweden)

    Malaka Julian

    2017-01-01

    Full Text Available Presentation of developing a method of automation of the storage process using electric drives with frequency converters, logic control and communication in industrial networks was the main purpose of this article. A connection structure was proposed to exchange information between devices that are part of a high-storage warehouse. It was assumed that modern communication protocols are used to synchronize the drives and to create a central control and information center in the PLC. The results of theoretical considerations were applied in practice by performing a laboratory model of a high storage warehouse with a developed automatic control system. Benefits of the proposed solutions was shown in the conclusions.

  7. A novel excitatory network for the control of breathing

    Science.gov (United States)

    Anderson, Tatiana M.; Garcia, Alfredo J.; Baertsch, Nathan A.; Pollak, Julia; Bloom, Jacob C.; Wei, Aguan D.; Rai, Karan G.; Ramirez, Jan-Marino

    2017-01-01

    Breathing must be tightly coordinated with other behaviors such as vocalization, swallowing, and coughing. These behaviors occur after inspiration, during a respiratory phase termed postinspiration1. Failure to coordinate postinspiration with inspiration can result in aspiration pneumonia, the leading cause of death in Alzheimer’s disease, Parkinson’s disease, dementia, and other neurodegenerative diseases2. Here we describe an excitatory network that generates the neuronal correlate for postinspiratory activity. Glutamatergic-cholinergic neurons form the basis of this network, while GABAergic inhibition establishes the timing and coordination with inspiration. We refer to this novel network as the postinspiratory complex (PiCo). PiCo has autonomous rhythm generating properties and is necessary and sufficient for postinspiratory activity in vivo. PiCo also has distinct responses to neuromodulators when compared with other excitatory brainstem networks. Based on the discovery of PiCo we propose that each of the three phases of breathing is generated by a distinct excitatory network: The preBötzinger complex, which has been linked to inspiration3,4, the PiCo as described here for the neuronal control of postinspiration, and the Lateral parafacial region (pFL) which has been associated with active expiration, a respiratory phase recruited during high metabolic demand4,5,. PMID:27462817

  8. Evaluating network-level predictors of behavior change among injection networks enrolled in the HPTN 037 randomized controlled trial.

    Science.gov (United States)

    Smith, Laramie R; Strathdee, Steffanie A; Metzger, David; Latkin, Carl

    2017-06-01

    Little is known about ways network-level factors that may influence the adoption of combination prevention behaviors among injection networks, or how network-oriented interventions might moderate this behavior change process. A total of 232 unique injection risk networks in Philadelphia, PA, were randomized to a peer educator network-oriented intervention or standard of care control arm. Network-level aggregates reflecting the injection networks' baseline substance use dynamics, social interactions, and the networks exposure to gender- and structural-related vulnerabilities were calculated and used to predict changes in the proportion of network members adopting safer injection practices at 6-month follow-up. At follow-up, safer injection practices were observed among 46.31% of a network's members on average. In contrast, 25.7% of networks observed no change. Controlling for the effects of the intervention, significant network-level factors influencing network-level behavior change reflected larger sized injection networks (b=2.20, p=0.013) with a greater proportion of members who shared needles (b=0.29, pnetwork's safer injection practices were also observed for networks with fewer new network members (b=-0.31, p=0.008), and for networks whose members were proportionally less likely to have experienced incarceration (b=-0.20, p=0.012) or more likely to have been exposed to drug treatment (b=0.17, p=0.034) in the 6-months prior to baseline. A significant interaction suggested the intervention uniquely facilitated change in safer injection practices among female-only networks (b=-0.32, p=0.046). Network-level factors offer insights into ways injection networks might be leveraged to promote combination prevention efforts. Copyright © 2017 Elsevier B.V. All rights reserved.

  9. Network-Cognizant Voltage Droop Control for Distribution Grids

    Energy Technology Data Exchange (ETDEWEB)

    Baker, Kyri; Bernstein, Andrey; Dall' Anese, Emiliano; Zhao, Changhong

    2017-01-01

    This paper examines distribution systems with a high integration of distributed energy resources (DERs) and addresses the design of local control methods for real-time voltage regulation. Particularly, the paper focuses on proportional control strategies where the active and reactive output-powers of DERs are adjusted in response to (and proportionally to) local changes in voltage levels. The design of the voltage-active power and voltage-reactive power characteristics leverages suitable linear approximation of the AC power-flow equations and is network-cognizant; that is, the coefficients of the controllers embed information on the location of the DERs and forecasted non-controllable loads/injections and, consequently, on the effect of DER power adjustments on the overall voltage profile. A robust approach is pursued to cope with uncertainty in the forecasted non-controllable loads/power injections. Stability of the proposed local controllers is analytically assessed and numerically corroborated.

  10. Analog neural network control method proposed for use in a backup satellite control mode

    Energy Technology Data Exchange (ETDEWEB)

    Frigo, J.R.; Tilden, M.W.

    1998-03-01

    The authors propose to use an analog neural network controller implemented in hardware, independent of the active control system, for use in a satellite backup control mode. The controller uses coarse sun sensor inputs. The field of view of the sensors activate the neural controller, creating an analog dead band with respect to the direction of the sun on each axis. This network controls the orientation of the vehicle toward the sunlight to ensure adequate power for the system. The attitude of the spacecraft is stabilized with respect to the ambient magnetic field on orbit. This paper develops a model of the controller using real-time coarse sun sensor data and a dynamic model of a prototype system based on a satellite system. The simulation results and the feasibility of this control method for use in a satellite backup control mode are discussed.

  11. Motif discovery in ranked lists of sequences

    DEFF Research Database (Denmark)

    Nielsen, Morten Muhlig; Tataru, Paula; Madsen, Tobias

    2016-01-01

    . These features make Regmex well suited for a range of biological sequence analysis problems related to motif discovery, exemplified by microRNA seed enrichment, but also including enrichment problems involving complex motifs and combinations of motifs. We demonstrate a number of usage scenarios that take......Motif analysis has long been an important method to characterize biological functionality and the current growth of sequencing-based genomics experiments further extends its potential. These diverse experiments often generate sequence lists ranked by some functional property. There is therefore...... a growing need for motif analysis methods that can exploit this coupled data structure and be tailored for specific biological questions. Here, we present an exploratory motif analysis tool, Regmex (REGular expression Motif EXplorer), which offers several methods to evaluate the correlation of motifs...

  12. A Survey of Access Control Models in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Htoo Aung Maw

    2014-06-01

    Full Text Available Wireless sensor networks (WSNs have attracted considerable interest in the research community, because of their wide range of applications. However, due to the distributed nature of WSNs and their deployment in remote areas, these networks are vulnerable to numerous security threats that can adversely affect their proper functioning. Resource constraints in sensor nodes mean that security mechanisms with a large overhead of computation and communication are impractical to use in WSNs; security in sensor networks is, therefore, a challenge. Access control is a critical security service that offers the appropriate access privileges to legitimate users and prevents illegitimate users from unauthorized access. However, access control has not received much attention in the context of WSNs. This paper provides an overview of security threats and attacks, outlines the security requirements and presents a state-of-the-art survey on access control models, including a comparison and evaluation based on their characteristics in WSNs. Potential challenging issues for access control schemes in WSNs are also discussed.

  13. Level Controlled Gossip Based Tsunami Warning Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Santosh BHIMA

    2009-07-01

    Full Text Available This paper deals with a warning system based on distributed sensor networks employing level controlled gossip. Level controlled gossip is a technique that is being proposed which employs leveling and gossiping together. This technique reduces the number of messages by transmitting messages in the direction of base station and thereby increasing the life time of sensor network. By using various power levels at base station the sensor field is hierarchically partitioned into levels of increasing radius (containing various sensor nodes. The algorithm divides the entire sensor network into logical concentric zones based on proximity from the base station, whereby the packet is transmitted from a node of higher depth to nodes in the next zone with lesser depth. The transmission probability increases with the proximity of the Tsunami wave to the base station. The primary advantage of the protocol is transmitting a critical event with higher probability and at the same time conserving life time of the network for future monitoring.

  14. Towards resolving the transcription factor network controlling myelin gene expression.

    Science.gov (United States)

    Fulton, Debra L; Denarier, Eric; Friedman, Hana C; Wasserman, Wyeth W; Peterson, Alan C

    2011-10-01

    In the central nervous system (CNS), myelin is produced from spirally-wrapped oligodendrocyte plasma membrane and, as exemplified by the debilitating effects of inherited or acquired myelin abnormalities in diseases such as multiple sclerosis, it plays a critical role in nervous system function. Myelin sheath production coincides with rapid up-regulation of numerous genes. The complexity of their subsequent expression patterns, along with recently recognized heterogeneity within the oligodendrocyte lineage, suggest that the regulatory networks controlling such genes drive multiple context-specific transcriptional programs. Conferring this nuanced level of control likely involves a large repertoire of interacting transcription factors (TFs). Here, we combined novel strategies of computational sequence analyses with in vivo functional analysis to establish a TF network model of coordinate myelin-associated gene transcription. Notably, the network model captures regulatory DNA elements and TFs known to regulate oligodendrocyte myelin gene transcription and/or oligodendrocyte development, thereby validating our approach. Further, it links to numerous TFs with previously unsuspected roles in CNS myelination and suggests collaborative relationships amongst both known and novel TFs, thus providing deeper insight into the myelin gene transcriptional network.

  15. Automated large-scale control of gene regulatory networks.

    Science.gov (United States)

    Tan, Mehmet; Alhajj, Reda; Polat, Faruk

    2010-04-01

    Controlling gene regulatory networks (GRNs) is an important and hard problem. As it is the case in all control problems, the curse of dimensionality is the main issue in real applications. It is possible that hundreds of genes may regulate one biological activity in an organism; this implies a huge state space, even in the case of Boolean models. This is also evident in the literature that shows that only models of small portions of the genome could be used in control applications. In this paper, we empower our framework for controlling GRNs by eliminating the need for expert knowledge to specify some crucial threshold that is necessary for producing effective results. Our framework is characterized by applying the factored Markov decision problem (FMDP) method to the control problem of GRNs. The FMDP is a suitable framework for large state spaces as it represents the probability distribution of state transitions using compact models so that more space and time efficient algorithms could be devised for solving control problems. We successfully mapped the GRN control problem to an FMDP and propose a model reduction algorithm that helps find approximate solutions for large networks by using existing FMDP solvers. The test results reported in this paper demonstrate the efficiency and effectiveness of the proposed approach.

  16. Design and implementation of a new fuzzy PID controller for networked control systems.

    Science.gov (United States)

    Fadaei, A; Salahshoor, K

    2008-10-01

    This paper presents a practical network platform to design and implement a networked-based cascade control system linking a Smar Foundation Fieldbus (FF) controller (DFI-302) and a Siemens programmable logic controller (PLC-S7-315-2DP) through Industrial Ethernet to a laboratory pilot plant. In the presented network configuration, the Smar OPC tag browser and Siemens WinCC OPC Channel provide the communicating interface between the two controllers. The paper investigates the performance of a PID controller implemented in two different possible configurations of FF function block (FB) and networked control system (NCS) via a remote Siemens PLC. In the FB control system implementation, the desired set-point is provided by the Siemens Human-Machine Interface (HMI) software (i.e, WinCC) via an Ethernet Modbus link. While, in the NCS implementation, the cascade loop is realized in remote Siemens PLC station and the final element set-point is sent to the Smar FF station via Ethernet bus. A new fuzzy PID control strategy is then proposed to improve the control performances of the networked-based control systems due to an induced transmission delay degradation effect. The proposed strategy utilizes an innovative idea based on sectionalizing the error signal of the step response into three different functional zones. The supporting philosophy behind these three functional zones is to decompose the desired control objectives in terms of rising time, settling time and steady-state error measures maintained by an appropriate PID-type controller in each zone. Then, fuzzy membership factors are defined to configure the control signal on the basis of the fuzzy weighted PID outputs of all three zones. The obtained results illustrate the effectiveness of the proposed fuzzy PID control scheme in improving the performances of the implemented NCS for different transportation delays.

  17. Application of Fuzzy-Logic Controller and Neural Networks Controller in Gas Turbine Speed Control and Overheating Control and Surge Control on Transient Performance

    Science.gov (United States)

    Torghabeh, A. A.; Tousi, A. M.

    2007-08-01

    This paper presents Fuzzy Logic and Neural Networks approach to Gas Turbine Fuel schedules. Modeling of non-linear system using feed forward artificial Neural Networks using data generated by a simulated gas turbine program is introduced. Two artificial Neural Networks are used , depicting the non-linear relationship between gas generator speed and fuel flow, and turbine inlet temperature and fuel flow respectively . Off-line fast simulations are used for engine controller design for turbojet engine based on repeated simulation. The Mamdani and Sugeno models are used to expression the Fuzzy system . The linguistic Fuzzy rules and membership functions are presents and a Fuzzy controller will be proposed to provide an Open-Loop control for the gas turbine engine during acceleration and deceleration . MATLAB Simulink was used to apply the Fuzzy Logic and Neural Networks analysis. Both systems were able to approximate functions characterizing the acceleration and deceleration schedules . Surge and Flame-out avoidance during acceleration and deceleration phases are then checked . Turbine Inlet Temperature also checked and controls by Neural Networks controller. This Fuzzy Logic and Neural Network Controllers output results are validated and evaluated by GSP software . The validation results are used to evaluate the generalization ability of these artificial Neural Networks and Fuzzy Logic controllers.

  18. Capacity Limit, Link Scheduling and Power Control in Wireless Networks

    Science.gov (United States)

    Zhou, Shan

    2013-01-01

    The rapid advancement of wireless technology has instigated the broad deployment of wireless networks. Different types of networks have been developed, including wireless sensor networks, mobile ad hoc networks, wireless local area networks, and cellular networks. These networks have different structures and applications, and require different…

  19. A normalized PID controller in networked control systems with varying time delays.

    Science.gov (United States)

    Tran, Hoang-Dung; Guan, Zhi-Hong; Dang, Xuan-Kien; Cheng, Xin-Ming; Yuan, Fu-Shun

    2013-09-01

    It requires not only simplicity and flexibility but also high specified stability and robustness of system to design a PI/PID controller in such complicated networked control systems (NCSs) with delays. By gain and phase margins approach, this paper proposes a novel normalized PI/PID controller for NCSs based on analyzing the stability and robustness of system under the effect of network-induced delays. Specifically, We take into account the total measured network delays to formulate the gain and phase margins of the closed-loop system in the form of a set of equations. With pre-specified values of gain and phase margins, this set of equations is then solved for calculating the closed forms of control parameters which enable us to propose the normalized PI/PID controller simultaneously satisfying the following two requirements: (1) simplicity without re-solving the optimization problem for a new process, (2) high flexibility to cope with large scale of random delays and deal with many different processes in different conditions of network. Furthermore, in our method, the upper bound of random delay can be estimated to indicate the operating domain of proposed PI/PID controller. Finally, simulation results are shown to demonstrate the advantages of our proposed controller in many situations of network-induced delays. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

  20. MODIS: an audio motif discovery software

    OpenAIRE

    Catanese, Laurence; Souviraà-Labastie, Nathan; Qu, Bingqing; Campion, Sébastien; Gravier, Guillaume; Vincent, Emmanuel; Bimbot, Frédéric

    2013-01-01

    International audience; MODIS is a free speech and audio motif discovery software developed at IRISA Rennes. Motif discovery is the task of discovering and collecting occurrences of repeating patterns in the absence of prior knowledge, or training material. MODIS is based on a generic approach to mine repeating audio sequences, with tolerance to motif variability. The algorithm implementation allows to process large audio streams at a reasonable speed where motif discovery often requires huge...

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

    Science.gov (United States)

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

    2013-03-01

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

  2. Neural Network Control for a Batch Distillation Column

    Directory of Open Access Journals (Sweden)

    Duraid Fadhil Ahmed

    2016-07-01

    Full Text Available The  present  work  deals  with  studying  the  dynamic  behavior  of  a  batch  distillation  column  and implemented  two  types  of  control  strategies  for  the  separation  different  types  of  binary  systems.  The model  was  derived  and  then  simulated  using  "MATLAB"  program.  The  experimental  data  of  dynamic behavior  were  to  tune  the  parameters  of  PID  controller  and  developed  the  training  of  neural  networks controller by using supervised  learning algorithms. The simulation results show a qualitatively acceptable behavior.  This  study  shows  also  that  the  response  of  PID  controller  was  oscillatory  behavior  with  high offset value while neural network controller gave less offset value and less  time to reach the steady state. In general, a good improvement is achieved when the  neural network controller  is used compared with PID control.

  3. A Framework and Comparative Analysis of Control Plane Security of SDN and Conventional Networks

    OpenAIRE

    Abdou, AbdelRahman; van Oorschot, Paul C.; Wan, Tao

    2017-01-01

    Software defined networking implements the network control plane in an external entity, rather than in each individual device as in conventional networks. This architectural difference implies a different design for control functions necessary for essential network properties, e.g., loop prevention and link redundancy. We explore how such differences redefine the security weaknesses in the SDN control plane and provide a framework for comparative analysis which focuses on essential network pr...

  4. Gene networks controlling the initiation of flower development.

    Science.gov (United States)

    Wellmer, Frank; Riechmann, José L

    2010-12-01

    The onset of flower formation is a key regulatory event during the life cycle of angiosperm plants, which marks the beginning of the reproductive phase of development. It has been shown that floral initiation is under tight genetic control, and deciphering the underlying molecular mechanisms has been a main area of interest in plant biology for the past two decades. Here, we provide an overview of the developmental and genetic processes that occur during floral initiation. We further review recent studies that have led to the genome-wide identification of target genes of key floral regulators and discuss how they have contributed to an in-depth understanding of the gene regulatory networks controlling early flower development. We focus especially on a master regulator of floral initiation in Arabidopsis thaliana APETALA1 (AP1), but also outline what is known about the AP1 network in other plant species and the evolutionary implications. Copyright © 2010 Elsevier Ltd. All rights reserved.

  5. Diagnostics and control of pressurized reactors using artificial neural networks

    Science.gov (United States)

    Ikonomopoulos, Andreas; Tsoukalas, Lefteri H.; Uhrig, Robert E.

    1992-09-01

    A methodology employing artificial neural networks and fuzzy arithmetic in the diagnosis and control of complex systems such as pressurized water reactors is presented. Fuzzy numbers represent the linguistic values of plant-specific variables, e.g., performance or availability. The notion of a virtual instrument, i.e., a software-based measuring device calibrated to the idiosyncrasies of a specific system is used. Neural networks perform a mapping of physically measurable parameters to fuzzy numbers called Virtual Measurement Values (VMV). The methodology is tested with start-up data from an experimental nuclear reactor. The results demonstrate the very good capacity of such virtual instruments for failure-tolerance and suggest the possibility of developing alternative algorithms for diagnostics and control.

  6. Control capacity and a random sampling method in exploring controllability of complex networks.

    Science.gov (United States)

    Jia, Tao; Barabási, Albert-László

    2013-01-01

    Controlling complex systems is a fundamental challenge of network science. Recent advances indicate that control over the system can be achieved through a minimum driver node set (MDS). The existence of multiple MDS's suggests that nodes do not participate in control equally, prompting us to quantify their participations. Here we introduce control capacity quantifying the likelihood that a node is a driver node. To efficiently measure this quantity, we develop a random sampling algorithm. This algorithm not only provides a statistical estimate of the control capacity, but also bridges the gap between multiple microscopic control configurations and macroscopic properties of the network under control. We demonstrate that the possibility of being a driver node decreases with a node's in-degree and is independent of its out-degree. Given the inherent multiplicity of MDS's, our findings offer tools to explore control in various complex systems.

  7. Mathematical inference and control of molecular networks from perturbation experiments

    Science.gov (United States)

    Mohammed-Rasheed, Mohammed

    in order to affect the time evolution of molecular activity in a desirable manner. In this proposal, we address both the inference and control problems of GRNs. In the first part of the thesis, we consider the control problem. We assume that we are given a general topology network structure, whose dynamics follow a discrete-time Markov chain model. We subsequently develop a comprehensive framework for optimal perturbation control of the network. The aim of the perturbation is to drive the network away from undesirable steady-states and to force it to converge to a unique desirable steady-state. The proposed framework does not make any assumptions about the topology of the initial network (e.g., ergodicity, weak and strong connectivity), and is thus applicable to general topology networks. We define the optimal perturbation as the minimum-energy perturbation measured in terms of the Frobenius norm between the initial and perturbed networks. We subsequently demonstrate that there exists at most one optimal perturbation that forces the network into the desirable steady-state. In the event where the optimal perturbation does not exist, we construct a family of sub-optimal perturbations that approximate the optimal solution arbitrarily closely. In the second part of the thesis, we address the inference problem of GRNs from time series data. We model the dynamics of the molecules using a system of ordinary differential equations corrupted by additive white noise. For large-scale networks, we formulate the inference problem as a constrained maximum likelihood estimation problem. We derive the molecular interactions that maximize the likelihood function while constraining the network to be sparse. We further propose a procedure to recover weak interactions based on the Bayesian information criterion. For small-size networks, we investigated the inference of a globally stable 7-gene melanoma genetic regulatory network from genetic perturbation experiments. We considered five

  8. Simulasi Virtual Local Area Network (VLAN Berbasis Software Defined Network (SDN Menggunakan POX Controller

    Directory of Open Access Journals (Sweden)

    Rohmat Tulloh

    2015-11-01

    Full Text Available VLAN (Virtual LAN merupakan sebuah teknologi yang dapat mengkonfigurasi jaringan logis independen dari struktur jaringan fisik. Hasil dari penelitian sebelumnya sudah diprediksi bahwa dibutuhkan Virtual Network yang akhirnya terciptalah VLAN. Namun paradigma jaringan saat ini tidak flexible, ketergantungan terhadap vendor sangat besar karena fungsi data plane dan control plane berada dalam satu paket device. SDN (Software defined network yang merupakan salahsatu evolusi teknologi jaringan sesuai dengan tuntutan yang berkembang dimana memisahkan fungsi data plane dan control plane pada suatu perangkat. POX Controller digunakan untuk men-simulasikan dan menguji Platform SDN (Software defined network. Pada penelitian ini menggunakan Openflow versi 1.0 untuk memasang header VLAN sehingga penelitian ini difokuskan untuk mengevaluasi performa forwarding VLAN yang memanfaatkan Openflow sebagai control plane dapat berfungsi dengan baik. Hasil penelitian ini mengusulkan penerapan karakteristik teknologi VLAN pada SDN karena telah berjalan dengan benar sesuai hasil pengujian konektifitas, verifikasi dan keamanan. Kemudian hasil pengujian lanjutan untuk melihat pengaruh SDN dengan skenario penambahan jumlah VLAN ID didapatkan bahwa set-up time akan bertambah seiring meningkatnya jumlah host dan dengan menggunakan protokol OpenFlow, latency yang terjadi di jaringan dapat dipantau dengan parameter round trip time (RTT yang stabil direntang 0,2 sampai 6 second walaupun jumlah vlan_id dan background traffic bertambah.

  9. Acute aerobic exercise alters executive control network in preadolescent children

    OpenAIRE

    Chen, Ai-Guo

    2017-01-01

    The present study aimed to investigate the effect of acute aerobic exercise on executive function (EF) and executive control network (ECN) in preadolescent children, and further explored the neural basis of acute aerobic exercise on EF in these children. We used a within-subjects design with a counterbalanced order. Nine healthy, right-handed children were scanned with resting-state functional magnetic resonance imaging and performed an EF task both in baseline session and exercise session. T...

  10. Parental control of children using the internet and social networks

    OpenAIRE

    Zuković Slađana; Slijepčević Senka

    2015-01-01

    The paper starts from the standpoint that the expansion of the Internet imposes a need for instructing the parents to adequately guide children to use safely this virtual space. That is why we present the results of an empirical research, aimed at establishing how parents control the behaviour of their children on the Internet and social networks. The research was conducted on a sample of 105 parents of the sixth grade elementary school pupils, and the applied questionnaire was construed for ...

  11. On a multi-channel stochastic network with controlled input

    Science.gov (United States)

    Livinska, Hanna; Lebedev, Eugene

    2017-06-01

    In this paper stationary properties of queueing network of the type [M|M|∞]r are investigated provided that the input flow is controlled by a Markov chain. We consider two cases. In the one-dimensional case a generating function of the stationary distribution is obtained. The form of the generating function is a matrix version of the well-known Takasc formula. For a multivariate service process the condition of a stationary regime existence and a correlation matrix are found.

  12. Novel methods of utilizing Jitter for Network Congestion Control

    Directory of Open Access Journals (Sweden)

    Ivan

    2013-12-01

    Full Text Available This paper proposes a novel paradigm for network congestion control. Instead of perpetual conflict as in TCP, a proof-of-concept first-ever protocol enabling inter-flow communication without infrastructure support thru a side channel constructed on generic FIFO queue behaviour is presented. This enables independent flows passing thru the same bottleneck queue to communicate and achieve fair capacity sharing and a stable equilibrium state in a rapid fashion.

  13. Control Capacity and A Random Sampling Method in Exploring Controllability of Complex Networks

    OpenAIRE

    Jia, Tao; Barab?si, Albert-L?szl?

    2013-01-01

    Controlling complex systems is a fundamental challenge of network science. Recent advances indicate that control over the system can be achieved through a minimum driver node set (MDS). The existence of multiple MDS's suggests that nodes do not participate in control equally, prompting us to quantify their participations. Here we introduce control capacity quantifying the likelihood that a node is a driver node. To efficiently measure this quantity, we develop a random sampling algorithm. Thi...

  14. Resilient Wireless Sensor Networks Using Topology Control: A Review

    Science.gov (United States)

    Huang, Yuanjiang; Martínez, José-Fernán; Sendra, Juana; López, Lourdes

    2015-01-01

    Wireless sensor networks (WSNs) may be deployed in failure-prone environments, and WSNs nodes easily fail due to unreliable wireless connections, malicious attacks and resource-constrained features. Nevertheless, if WSNs can tolerate at most losing k − 1 nodes while the rest of nodes remain connected, the network is called k − connected. k is one of the most important indicators for WSNs’ self-healing capability. Following a WSN design flow, this paper surveys resilience issues from the topology control and multi-path routing point of view. This paper provides a discussion on transmission and failure models, which have an important impact on research results. Afterwards, this paper reviews theoretical results and representative topology control approaches to guarantee WSNs to be k − connected at three different network deployment stages: pre-deployment, post-deployment and re-deployment. Multi-path routing protocols are discussed, and many NP-complete or NP-hard problems regarding topology control are identified. The challenging open issues are discussed at the end. This paper can serve as a guideline to design resilient WSNs. PMID:26404272

  15. A survey of trust, control and information in networks

    DEFF Research Database (Denmark)

    Jakobsen, Morten

    This paper focuses on which characteristics managers take into account when they choose and evaluate business partners, and the interrelationship between the constructs trust, control and information. The paper is based on a survey which includes 101 small and middle-sized manufacturing companies...... in Denmark. The results show that managers frequently express that trust is an important aspect of a good relationship. Also product-related attributes and relational attributes have a bearing in a network setting. On the other hand, no significant correlation between neither trust and control nor trust...

  16. Qualitative analysis and control of complex neural networks with delays

    CERN Document Server

    Wang, Zhanshan; Zheng, Chengde

    2016-01-01

    This book focuses on the stability of the dynamical neural system, synchronization of the coupling neural system and their applications in automation control and electrical engineering. The redefined concept of stability, synchronization and consensus are adopted to provide a better explanation of the complex neural network. Researchers in the fields of dynamical systems, computer science, electrical engineering and mathematics will benefit from the discussions on complex systems. The book will also help readers to better understand the theory behind the control technique and its design.

  17. Improved methods in neural network-based adaptive output feedback control, with applications to flight control

    Science.gov (United States)

    Kim, Nakwan

    Utilizing the universal approximation property of neural networks, we develop several novel approaches to neural network-based adaptive output feedback control of nonlinear systems, and illustrate these approaches for several flight control applications. In particular, we address the problem of non-affine systems and eliminate the fixed point assumption present in earlier work. All of the stability proofs are carried out in a form that eliminates an algebraic loop in the neural network implementation. An approximate input/output feedback linearizing controller is augmented with a neural network using input/output sequences of the uncertain system. These approaches permit adaptation to both parametric uncertainty and unmodeled dynamics. All physical systems also have control position and rate limits, which may either deteriorate performance or cause instability for a sufficiently high control bandwidth. Here we apply a method for protecting an adaptive process from the effects of input saturation and time delays, known as "pseudo control hedging". This method was originally developed for the state feedback case, and we provide a stability analysis that extends its domain of applicability to the case of output feedback. The approach is illustrated by the design of a pitch-attitude flight control system for a linearized model of an R-50 experimental helicopter, and by the design of a pitch-rate control system for a 58-state model of a flexible aircraft consisting of rigid body dynamics coupled with actuator and flexible modes. A new approach to augmentation of an existing linear controller is introduced. It is especially useful when there is limited information concerning the plant model, and the existing controller. The approach is applied to the design of an adaptive autopilot for a guided munition. Design of a neural network adaptive control that ensures asymptotically stable tracking performance is also addressed.

  18. Dynamic Cooperative Clustering Based Power Assignment: Network Capacity and Lifetime Efficient Topology Control in Cooperative Ad Hoc Networks

    Directory of Open Access Journals (Sweden)

    Xiao-Hong Li

    2014-01-01

    Full Text Available Cooperative communication (CC is used in topology control as it can reduce the transmission power and expand the transmission range. However, all previous research on topology control under the CC model focused on maintaining network connectivity and minimizing the total energy consumption, which would lead to low network capacity, transmission interruption, or even network paralysis. Meanwhile, without considering the balance of energy consumption in the network, it would reduce the network lifetime and greatly affect the network performance. This paper tries to solve the above problems existing in the research on topology control under the CC model by proposing a power assignment (DCCPA algorithm based on dynamic cooperative clustering in cooperative ad hoc networks. The new algorithm clusters the network to maximize network capacity and makes the clusters communicate with each other by CC. To reduce the number of redundant links between clusters, we design a static clustering method by using Kruskal algorithm. To maximize the network lifetime, we also propose a cluster head rotating method which can reach a good tradeoff between residual energy and distance for the cluster head reselection. Experimental results show that DCCPA can improve 80% network capacity with Cooperative Bridges algorithm; meanwhile, it can improve 20% network lifetime.

  19. Development of cognitive and affective control networks and decision making.

    Science.gov (United States)

    Kar, Bhoomika R; Vijay, Nivita; Mishra, Shreyasi

    2013-01-01

    Cognitive control and decision making are two important research areas in the realm of higher-order cognition. Control processes such as interference control and monitoring in cognitive and affective contexts have been found to influence the process of decision making. Development of control processes follows a gradual growth pattern associated with the prolonged maturation of underlying neural circuits including the lateral prefrontal cortex, anterior cingulate, and the medial prefrontal cortex. These circuits are also involved in the control of processes that influences decision making, particularly with respect to choice behavior. Developmental studies on affective control have shown distinct patterns of brain activity with adolescents showing greater activation of amygdala whereas adults showing greater activity in ventral prefrontal cortex. Conflict detection, monitoring, and adaptation involve anticipation and subsequent performance adjustments which are also critical to complex decision making. We discuss the gradual developmental patterns observed in two of our studies on conflict monitoring and adaptation in affective and nonaffective contexts. Findings of these studies indicate the need to look at the differences in the effects of the development of cognitive and affective control on decision making in children and particularly adolescents. Neuroimaging studies have shown the involvement of separable neural networks for cognitive (medial prefrontal cortex and anterior cingulate) and affective control (amygdala, ventral medial prefrontal cortex) shows that one system can affect the other also at the neural level. Hence, an understanding of the interaction and balance between the cognitive and affective brain networks may be crucial for self-regulation and decision making during the developmental period, particularly late childhood and adolescence. The chapter highlights the need for empirical investigation on the interaction between the different aspects

  20. Learning anticipation via spiking networks: application to navigation control.

    Science.gov (United States)

    Arena, Paolo; Fortuna, Luigi; Frasca, Mattia; Patané, Luca

    2009-02-01

    In this paper, we introduce a network of spiking neurons devoted to navigation control. Three different examples, dealing with stimuli of increasing complexity, are investigated. In the first one, obstacle avoidance in a simulated robot is achieved through a network of spiking neurons. In the second example, a second layer is designed aiming to provide the robot with a target approaching system, making it able to move towards visual targets. Finally, a network of spiking neurons for navigation based on visual cues is introduced. In all cases, the robot was assumed to rely on some a priori known responses to low-level sensors (i.e., to contact sensors in the case of obstacles, to proximity target sensors in the case of visual targets, or to the visual target for navigation with visual cues). Based on their knowledge, the robot has to learn the response to high-level stimuli (i.e., range finder sensors or visual input). The biologically plausible paradigm of spike-timing-dependent plasticity (STDP) is included in the network to make the system able to learn high-level responses that guide navigation through a simple unstructured environment. The learning procedure is based on classical conditioning.

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

    Science.gov (United States)

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

    2014-09-01

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

  2. The Study of Maglev Train Control and Diagnosis Networks Based on Role Automation Decentralization

    National Research Council Canada - National Science Library

    LIU, Zhigang; WANG, Qi; TAN, Yongdong

    2008-01-01

    The control and diagnosis networks in Maglev Train are the most important parts. In the paper, the control and diagnosis network structures are discussed, and the disadvantages of them are described and analyzed...

  3. Messaging Performance of FIPA Interaction Protocols in Networked Embedded Controllers

    Directory of Open Access Journals (Sweden)

    Omar Jehovani López Orozco

    2007-12-01

    Full Text Available Agent-based technologies in production control systems could facilitate seamless reconfiguration and integration of mechatronic devices/modules into systems. Advances in embedded controllers which are continuously improving computational capabilities allow for software modularization and distribution of decisions. Agent platforms running on embedded controllers could hide the complexity of bootstrap and communication. Therefore, it is important to investigate the messaging performance of the agents whose main motivation is the resource allocation in manufacturing systems (i.e., conveyor system. The tests were implemented using the FIPA-compliant JADE-LEAP agent platform. Agent containers were distributed through networked embedded controllers, and agents were communicating using request and contract-net FIPA interaction protocols. The test scenarios are organized in intercontainer and intracontainer communications. The work shows the messaging performance for the different test scenarios using both interaction protocols.

  4. Detecting correlations among functional-sequence motifs

    Science.gov (United States)

    Pirino, Davide; Rigosa, Jacopo; Ledda, Alice; Ferretti, Luca

    2012-06-01

    Sequence motifs are words of nucleotides in DNA with biological functions, e.g., gene regulation. Identification of such words proceeds through rejection of Markov models on the expected motif frequency along the genome. Additional biological information can be extracted from the correlation structure among patterns of motif occurrences. In this paper a log-linear multivariate intensity Poisson model is estimated via expectation maximization on a set of motifs along the genome of E. coli K12. The proposed approach allows for excitatory as well as inhibitory interactions among motifs and between motifs and other genomic features like gene occurrences. Our findings confirm previous stylized facts about such types of interactions and shed new light on genome-maintenance functions of some particular motifs. We expect these methods to be applicable to a wider set of genomic features.

  5. A molecular quantum spin network controlled by a single qubit.

    Science.gov (United States)

    Schlipf, Lukas; Oeckinghaus, Thomas; Xu, Kebiao; Dasari, Durga Bhaktavatsala Rao; Zappe, Andrea; de Oliveira, Felipe Fávaro; Kern, Bastian; Azarkh, Mykhailo; Drescher, Malte; Ternes, Markus; Kern, Klaus; Wrachtrup, Jörg; Finkler, Amit

    2017-08-01

    Scalable quantum technologies require an unprecedented combination of precision and complexity for designing stable structures of well-controllable quantum systems on the nanoscale. It is a challenging task to find a suitable elementary building block, of which a quantum network can be comprised in a scalable way. We present the working principle of such a basic unit, engineered using molecular chemistry, whose collective control and readout are executed using a nitrogen vacancy (NV) center in diamond. The basic unit we investigate is a synthetic polyproline with electron spins localized on attached molecular side groups separated by a few nanometers. We demonstrate the collective readout and coherent manipulation of very few (≤ 6) of these S = 1/2 electronic spin systems and access their direct dipolar coupling tensor. Our results show that it is feasible to use spin-labeled peptides as a resource for a molecular qubit-based network, while at the same time providing simple optical readout of single quantum states through NV magnetometry. This work lays the foundation for building arbitrary quantum networks using well-established chemistry methods, which has many applications ranging from mapping distances in single molecules to quantum information processing.

  6. Remote controlled gate controller using a GSM network and Arduino platform

    Directory of Open Access Journals (Sweden)

    Pospisilik Martin

    2016-01-01

    Full Text Available Most remote controllers for entrance gates operate on free frequencies 433 or 868 MHz. However, this technology limits the user comfort, as it is usually not common that bi-directional communication is established. A higher comfort of controlling the entrance gates can be achieved by employing the GSM network for transmission of commands and messages between the gate controller and the user. In this case, only a conventional GSM cellular phone is needed to control the gate. A description of such a controller based on the GSM module and Arduino controller is provided in this paper.

  7. A QoS-Oriented Congestion Control Mechanism for Satellite Networks

    OpenAIRE

    Heyu Liu; Fuchun Sun

    2014-01-01

    The sharply increasing amount of data, which are transferred by the satellite network, requires the satellite network to provide quality-of-service (QoS). However, the upsurge in the data flow leads to the network congestion, impeding its ability to offer QoS. Congestion control mechanisms, deployed in the ground networks, have been thoroughly studied. But those deployed in the satellite networks have not been studied yet. As satellite networks are now important supplements to the ground back...

  8. Kopi dan Kakao dalam Kreasi Motif Batik Khas Jember

    Directory of Open Access Journals (Sweden)

    Irfa'ina Rohana Salma

    2015-06-01

    Full Text Available ABSTRAK Batik Jember selama ini identik dengan motif daun tembakau. Visualisasi daun tembakau dalam motif Batik Jember cukup lemah, yaitu kurang berkarakter karena motif yang muncul adalah seperti gambar daun pada umumnya. Oleh karena itu perlu diciptakan desain motif batik khas Jember yang sumber inspirasinya digali dari kekayaan alam lainnya dari Jember yang mempunyai bentuk spesifik dan karakteristik sehingga identitas motif bisa didapatkan dengan lebih kuat. Hasil alam khas Jember tersebut adalah kopi dan kakao. Tujuan penciptaan seni ini adalah untuk menghasilkan motif batik  baru yang mempunyai ciri khas Jember. Metode yang digunakan yaitu pengumpulan data, pengamatan mendalam terhadap objek penciptaan, pengkajian sumber inspirasi, pembuatan desain motif, dan perwujudan menjadi batik. Dari penciptaan seni ini berhasil dikreasikan 6 (enam motif batik yaitu: (1 Motif Uwoh Kopi; (2 Motif Godong Kopi;  (3 Motif Ceplok Kakao; (4 Motif Kakao Raja; (5 Motif Kakao Biru; dan (6 Motif Wiji Mukti. Berdasarkan hasil penilaian “Selera Estetika” diketahui bahwa motif yang paling banyak disukai adalah Motif Uwoh Kopi dan Motif Kakao Raja. Kata kunci: Motif Woh Kopi, Motif Godong Kopi, Motif Ceplok Kakao, Motif Kakao Raja, Motif Kakao Biru, Motif Wiji Mukti ABSTRACTBatik Jember is synonymous with tobacco leaf motif. Tobacco leaf shape is quite weak in the visual appearance characterized as that motif emerges like a picture of leaves in general. Therefore, it is necessary to create a distinctive design motif extracted from other natural resources of Jember that have specific shapes and characteristics that can be obtained as the stronger motif identity. The typical natural resources from Jember are coffee and cocoa. The purpose of the creation of this art is to produce the unique, creative and innovative batik and have specific characteristics of Jember. The method used are data collection, observation of the object, reviewing inspiration sources

  9. Improved Road-Network-Flow Control Strategy Based on Macroscopic Fundamental Diagrams and Queuing Length in Connected-Vehicle Network

    Directory of Open Access Journals (Sweden)

    Xiaohui Lin

    2017-01-01

    Full Text Available Connected-vehicles network provides opportunities and conditions for improving traffic signal control, and macroscopic fundamental diagrams (MFD can control the road network at the macrolevel effectively. This paper integrated proposed real-time access to the number of mobile vehicles and the maximum road queuing length in the Connected-vehicles network. Moreover, when implementing a simple control strategy to limit the boundary flow of a road network based on MFD, we determined whether the maximum queuing length of each boundary section exceeds the road-safety queuing length in real-time calculations and timely adjusted the road-network influx rate to avoid the overflow phenomenon in the boundary section. We established a road-network microtraffic simulation model in VISSIM software taking a district as the experimental area, determined MFD of the region based on the number of mobile vehicles, and weighted traffic volume of the road network. When the road network was tending to saturate, we implemented a simple control strategy and our algorithm limits the boundary flow. Finally, we compared the traffic signal control indicators with three strategies: (1 no control strategy, (2 boundary control, and (3 boundary control with limiting queue strategy. The results show that our proposed algorithm is better than the other two.

  10. Wearable Device Control Platform Technology for Network Application Development

    Directory of Open Access Journals (Sweden)

    Heejung Kim

    2016-01-01

    Full Text Available Application development platform is the most important environment in IT industry. There are a variety of platforms. Although the native development enables application to optimize, various languages and software development kits need to be acquired according to the device. The coexistence of smart devices and platforms has rendered the native development approach time and cost consuming. Cross-platform development emerged as a response to these issues. These platforms generate applications for multiple devices based on web languages. Nevertheless, development requires additional implementation based on a native language because of the coverage and functions of supported application programming interfaces (APIs. Wearable devices have recently attracted considerable attention. These devices only support Bluetooth-based interdevice communication, thereby making communication and device control impossible beyond a certain range. We propose Network Application Agent (NetApp-Agent in order to overcome issues. NetApp-Agent based on the Cordova is a wearable device control platform for the development of network applications, controls input/output functions of smartphones and wearable/IoT through the Cordova and Native API, and enables device control and information exchange by external users by offering a self-defined API. We confirmed the efficiency of the proposed platform through experiments and a qualitative assessment of its implementation.

  11. Model of nonhierarchical control in distributed sensor networks

    Science.gov (United States)

    Meinkoehn, Jens; Knoll, A.

    1992-11-01

    In this paper a model of lateral coordination control in sensor networks is proposed. It is based on the notion of negotiated cooperation between pairs of equal and autonomously acting sensor nodes. The actual communication phase is preceded by a bidding scheme to establish appropriate communication links. This model incorporates the aspect of network self- organization in order to adapt to changing environmental conditions. The cooperation is modelled on human behavior in the case of a task being worked on sequentially by team members with equal rights but different capabilities. To this end, a generalized approach to the organization of distributed systems is given and a cooperation protocol is described to achieve the desired lateral coordination. The qualitative reasoning is supplemented by simulation results to support the superiority of lateral over pure vertical coordination, particularly under severe environmental conditions, such as sensor failure.

  12. Assessing Local Structure Motifs Using Order Parameters for Motif Recognition, Interstitial Identification, and Diffusion Path Characterization

    Directory of Open Access Journals (Sweden)

    Nils E. R. Zimmermann

    2017-11-01

    Full Text Available Structure–property relationships form the basis of many design rules in materials science, including synthesizability and long-term stability of catalysts, control of electrical and optoelectronic behavior in semiconductors, as well as the capacity of and transport properties in cathode materials for rechargeable batteries. The immediate atomic environments (i.e., the first coordination shells of a few atomic sites are often a key factor in achieving a desired property. Some of the most frequently encountered coordination patterns are tetrahedra, octahedra, body and face-centered cubic as well as hexagonal close packed-like environments. Here, we showcase the usefulness of local order parameters to identify these basic structural motifs in inorganic solid materials by developing classification criteria. We introduce a systematic testing framework, the Einstein crystal test rig, that probes the response of order parameters to distortions in perfect motifs to validate our approach. Subsequently, we highlight three important application cases. First, we map basic crystal structure information of a large materials database in an intuitive manner by screening the Materials Project (MP database (61,422 compounds for element-specific motif distributions. Second, we use the structure-motif recognition capabilities to automatically find interstitials in metals, semiconductor, and insulator materials. Our Interstitialcy Finding Tool (InFiT facilitates high-throughput screenings of defect properties. Third, the order parameters are reliable and compact quantitative structure descriptors for characterizing diffusion hops of intercalants as our example of magnesium in MnO2-spinel indicates. Finally, the tools developed in our work are readily and freely available as software implementations in the pymatgen library, and we expect them to be further applied to machine-learning approaches for emerging applications in materials science.

  13. Non-Markovian quantum feedback networks II: Controlled flows

    Science.gov (United States)

    Gough, John E.

    2017-06-01

    The concept of a controlled flow of a dynamical system, especially when the controlling process feeds information back about the system, is of central importance in control engineering. In this paper, we build on the ideas presented by Bouten and van Handel [Quantum Stochastics and Information: Statistics, Filtering and Control (World Scientific, 2008)] and develop a general theory of quantum feedback. We elucidate the relationship between the controlling processes, Z, and the measured processes, Y, and to this end we make a distinction between what we call the input picture and the output picture. We should note that the input-output relations for the noise fields have additional terms not present in the standard theory but that the relationship between the control processes and measured processes themselves is internally consistent—we do this for the two main cases of quadrature measurement and photon-counting measurement. The theory is general enough to include a modulating filter which post-processes the measurement readout Y before returning to the system. This opens up the prospect of applying very general engineering feedback control techniques to open quantum systems in a systematic manner, and we consider a number of specific modulating filter problems. Finally, we give a brief argument as to why most of the rules for making instantaneous feedback connections [J. Gough and M. R. James, Commun. Math. Phys. 287, 1109 (2009)] ought to apply for controlled dynamical networks as well.

  14. Congestion control algorithms in wireless sensor networks: Trends and opportunities

    Directory of Open Access Journals (Sweden)

    Syed Afsar Shah

    2017-07-01

    Full Text Available Congestion control is an extremely important area within wireless sensor networks (WSN, where traffic becomes greater than the aggregated or individual capacity of the underlying channels. Therefore, special considerations are required to develop more sophisticated techniques to avoid, detect, and resolve congestion. The constrained resources of the WSN must be considered while devising such techniques to achieve the maximum throughput. Various approaches have been introduced in the past few years that include routing protocols aided with congestion detection and control mechanism, and dedicated congestion control protocols. In the former schemes, the congestion avoidance is performed by the sink node that causes topology reset and bulk traffic drop. As a consequence, the latter mentioned congestion control protocols addressing the congestion avoidance, detection, and resolution were introduced at the node level. In this paper, we explore mechanisms for controlling congestion in the WSNs and present a comparative study. The congestion control schemes are categorized as centralized with partial congestion control and distributed with dedicated congestion control.

  15. Neural network based adaptive control for nonlinear dynamic regimes

    Science.gov (United States)

    Shin, Yoonghyun

    Adaptive control designs using neural networks (NNs) based on dynamic inversion are investigated for aerospace vehicles which are operated at highly nonlinear dynamic regimes. NNs play a key role as the principal element of adaptation to approximately cancel the effect of inversion error, which subsequently improves robustness to parametric uncertainty and unmodeled dynamics in nonlinear regimes. An adaptive control scheme previously named 'composite model reference adaptive control' is further developed so that it can be applied to multi-input multi-output output feedback dynamic inversion. It can have adaptive elements in both the dynamic compensator (linear controller) part and/or in the conventional adaptive controller part, also utilizing state estimation information for NN adaptation. This methodology has more flexibility and thus hopefully greater potential than conventional adaptive designs for adaptive flight control in highly nonlinear flight regimes. The stability of the control system is proved through Lyapunov theorems, and validated with simulations. The control designs in this thesis also include the use of 'pseudo-control hedging' techniques which are introduced to prevent the NNs from attempting to adapt to various actuation nonlinearities such as actuator position and rate saturations. Control allocation is introduced for the case of redundant control effectors including thrust vectoring nozzles. A thorough comparison study of conventional and NN-based adaptive designs for a system under a limit cycle, wing-rock, is included in this research, and the NN-based adaptive control designs demonstrate their performances for two highly maneuverable aerial vehicles, NASA F-15 ACTIVE and FQM-117B unmanned aerial vehicle (UAV), operated under various nonlinearities and uncertainties.

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

    Directory of Open Access Journals (Sweden)

    A. A. Noskov

    2015-01-01

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

  17. TCP Congestion Control for the Networks with Markovian Jump Parameters

    Directory of Open Access Journals (Sweden)

    MOMENI, H. R.

    2011-05-01

    Full Text Available This paper is concerned with the problem of TCP congestion control for the class of communication networks with random parameters. The linear dynamic model of TCP New Reno in congestion avoidance mode is considered which contains round trip delays in both state and input. The randomness of link capacity, round trip time delay and the number of TCP sessions is modeled with a continuous-time finite state Markov process. An Active Queue Management (AQM technique is then used to adjust the queue level of the congested link to a predefined value. For this purpose, a dynamic output feedback controller with mode dependent parameters is synthesized to stochastically stabilize the TCP/AQM dynamics. The procedure of the control synthesis is implemented by solving a linear matrix inequality (LMI. The results are tested within a simulation example and the effectiveness of the proposed design method is verified.

  18. Neural network output feedback control of robot formations.

    Science.gov (United States)

    Dierks, Travis; Jagannathan, Sarangapani

    2010-04-01

    In this paper, a combined kinematic/torque output feedback control law is developed for leader-follower-based formation control using backstepping to accommodate the dynamics of the robots and the formation in contrast with kinematic-based formation controllers. A neural network (NN) is introduced to approximate the dynamics of the follower and its leader using online weight tuning. Furthermore, a novel NN observer is designed to estimate the linear and angular velocities of both the follower robot and its leader. It is shown, by using the Lyapunov theory, that the errors for the entire formation are uniformly ultimately bounded while relaxing the separation principle. In addition, the stability of the formation in the presence of obstacles, is examined using Lyapunov methods, and by treating other robots in the formation as obstacles, collisions within the formation are prevented. Numerical results are provided to verify the theoretical conjectures.

  19. An interaction-motif-based scoring function for protein-ligand docking

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    Xie Zhong-Ru

    2010-06-01

    Full Text Available Abstract Background A good scoring function is essential for molecular docking computations. In conventional scoring functions, energy terms modeling pairwise interactions are cumulatively summed, and the best docking solution is selected. Here, we propose to transform protein-ligand interactions into three-dimensional geometric networks, from which recurring network substructures, or network motifs, are selected and used to provide probability-ranked interaction templates with which to score docking solutions. Results A novel scoring function for protein-ligand docking, MotifScore, was developed. It is non-energy-based, and docking is, instead, scored by counting the occurrences of motifs of protein-ligand interaction networks constructed using structures of protein-ligand complexes. MotifScore has been tested on a benchmark set established by others to assess its ability to identify near-native complex conformations among a set of decoys. In this benchmark test, 84% of the highest-scored docking conformations had root-mean-square deviations (rmsds below 2.0 Å from the native conformation, which is comparable with the best of several energy-based docking scoring functions. Many of the top motifs, which comprise a multitude of chemical groups that interact simultaneously and make a highly significant contribution to MotifScore, capture recurrent interacting patterns beyond pairwise interactions. Conclusions While providing quite good docking scores, MotifScore is quite different from conventional energy-based functions. MotifScore thus represents a new, network-based approach for exploring problems associated with molecular docking.

  20. Heme controls ferroportin1 (FPN1) transcription involving Bach1, Nrf2 and a MARE/ARE sequence motif at position -7007 of the FPN1 promoter.

    Science.gov (United States)

    Marro, Samuele; Chiabrando, Deborah; Messana, Erika; Stolte, Jens; Turco, Emilia; Tolosano, Emanuela; Muckenthaler, Martina U

    2010-08-01

    Macrophages of the reticuloendothelial system play a key role in recycling iron from hemoglobin of senescent or damaged erythrocytes. Heme oxygenase 1 degrades the heme moiety and releases inorganic iron that is stored in ferritin or exported to the plasma via the iron export protein ferroportin. In the plasma, iron binds to transferrin and is made available for de novo red cell synthesis. The aim of this study was to gain insight into the regulatory mechanisms that control the transcriptional response of iron export protein ferroportin to hemoglobin in macrophages. Iron export protein ferroportin mRNA expression was analyzed in RAW264.7 mouse macrophages in response to hemoglobin, heme, ferric ammonium citrate or protoporphyrin treatment or to siRNA mediated knockdown or overexpression of Btb And Cnc Homology 1 or nuclear accumulation of Nuclear Factor Erythroid 2-like. Iron export protein ferroportin promoter activity was analyzed using reporter constructs that contain specific truncations of the iron export protein ferroportin promoter or mutations in a newly identified MARE/ARE element. We show that iron export protein ferroportin is transcriptionally co-regulated with heme oxygenase 1 by heme, a degradation product of hemoglobin. The protoporphyrin ring of heme is sufficient to increase iron export protein ferroportin transcriptional activity while the iron released from the heme moiety controls iron export protein ferroportin translation involving the IRE in the 5'untranslated region. Transcription of iron export protein ferroportin is inhibited by Btb and Cnc Homology 1 and activated by Nuclear Factor Erythroid 2-like involving a MARE/ARE element located at position -7007/-7016 of the iron export protein ferroportin promoter. This finding suggests that heme controls a macrophage iron recycling regulon involving Btb and Cnc Homology 1 and Nuclear Factor Erythroid 2-like to assure the coordinated degradation of heme by heme oxygenase 1, iron storage and

  1. Output feedback control of a quadrotor UAV using neural networks.

    Science.gov (United States)

    Dierks, Travis; Jagannathan, Sarangapani

    2010-01-01

    In this paper, a new nonlinear controller for a quadrotor unmanned aerial vehicle (UAV) is proposed using neural networks (NNs) and output feedback. The assumption on the availability of UAV dynamics is not always practical, especially in an outdoor environment. Therefore, in this work, an NN is introduced to learn the complete dynamics of the UAV online, including uncertain nonlinear terms like aerodynamic friction and blade flapping. Although a quadrotor UAV is underactuated, a novel NN virtual control input scheme is proposed which allows all six degrees of freedom (DOF) of the UAV to be controlled using only four control inputs. Furthermore, an NN observer is introduced to estimate the translational and angular velocities of the UAV, and an output feedback control law is developed in which only the position and the attitude of the UAV are considered measurable. It is shown using Lyapunov theory that the position, orientation, and velocity tracking errors, the virtual control and observer estimation errors, and the NN weight estimation errors for each NN are all semiglobally uniformly ultimately bounded (SGUUB) in the presence of bounded disturbances and NN functional reconstruction errors while simultaneously relaxing the separation principle. The effectiveness of proposed output feedback control scheme is then demonstrated in the presence of unknown nonlinear dynamics and disturbances, and simulation results are included to demonstrate the theoretical conjecture.

  2. Statistical tests to compare motif count exceptionalities

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    Vandewalle Vincent

    2007-03-01

    Full Text Available Abstract Background Finding over- or under-represented motifs in biological sequences is now a common task in genomics. Thanks to p-value calculation for motif counts, exceptional motifs are identified and represent candidate functional motifs. The present work addresses the related question of comparing the exceptionality of one motif in two different sequences. Just comparing the motif count p-values in each sequence is indeed not sufficient to decide if this motif is significantly more exceptional in one sequence compared to the other one. A statistical test is required. Results We develop and analyze two statistical tests, an exact binomial one and an asymptotic likelihood ratio test, to decide whether the exceptionality of a given motif is equivalent or significantly different in two sequences of interest. For that purpose, motif occurrences are modeled by Poisson processes, with a special care for overlapping motifs. Both tests can take the sequence compositions into account. As an illustration, we compare the octamer exceptionalities in the Escherichia coli K-12 backbone versus variable strain-specific loops. Conclusion The exact binomial test is particularly adapted for small counts. For large counts, we advise to use the likelihood ratio test which is asymptotic but strongly correlated with the exact binomial test and very simple to use.

  3. An Algorithm for Motif Discovery with Iteration on Lengths of Motifs.

    Science.gov (United States)

    Fan, Yetian; Wu, Wei; Yang, Jie; Yang, Wenyu; Liu, Rongrong

    2015-01-01

    Analysis of DNA sequence motifs is becoming increasingly important in the study of gene regulation, and the identification of motif in DNA sequences is a complex problem in computational biology. Motif discovery has attracted the attention of more and more researchers, and varieties of algorithms have been proposed. Most existing motif discovery algorithms fix the motif's length as one of the input parameters. In this paper, a novel method is proposed to identify the optimal length of the motif and the optimal motif with that length, through an iteration process on increasing length numbers. For each fixed length, a modified genetic algorithm (GA) is used for finding the optimal motif with that length. Three operators are used in the modified GA: Mutation that is similar to the one used in usual GA but is modified to avoid local optimum in our case, and Addition and Deletion that are proposed by us for the problem. A criterion is given for singling out the optimal length in the increasing motif's lengths. We call this method AMDILM (an algorithm for motif discovery with iteration on lengths of motifs). The experiments on simulated data and real biological data show that AMDILM can accurately identify the optimal motif length. Meanwhile, the optimal motifs discovered by AMDILM are consistent with the real ones and are similar with the motifs obtained by the three well-known methods: Gibbs Sampler, MEME and Weeder.

  4. Design and Research on Automotive Controller Area Network Bus Analyzer

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    Hongwei CUI

    2014-03-01

    Full Text Available The detection method of automotive controller area network bus is researched in this paper. Failure identifying of CAN bus under different working conditions has been realized. In order to realizing intelligent failure diagnosis, data fusion means has been put forward in this paper. The composition of analysis and detection system is introduced. By analyzing and processing the data of CAN bus and sensors, work condition of automotive is achieved. Multi-pattern data fusion model and algorithm for failure diagnosis are researched. The analyzer and detection system designed in this paper can be applied to automotive fault analysis, troubleshooting and maintenance.

  5. Robust control of integrated motor-transmission powertrain system over controller area network for automotive applications

    Science.gov (United States)

    Zhu, Xiaoyuan; Zhang, Hui; Cao, Dongpu; Fang, Zongde

    2015-06-01

    Integrated motor-transmission (IMT) powertrain system with directly coupled motor and gearbox is a good choice for electric commercial vehicles (e.g., pure electric buses) due to its potential in motor size reduction and energy efficiency improvement. However, the controller design for powertrain oscillation damping becomes challenging due to the elimination of damping components. On the other hand, as controller area network (CAN) is commonly adopted in modern vehicle system, the network-induced time-varying delays that caused by bandwidth limitation will further lead to powertrain vibration or even destabilize the powertrain control system. Therefore, in this paper, a robust energy-to-peak controller is proposed for the IMT powertrain system to address the oscillation damping problem and also attenuate the external disturbance. The control law adopted here is based on a multivariable PI control, which ensures the applicability and performance of the proposed controller in engineering practice. With the linearized delay uncertainties characterized by polytopic inclusions, a delay-free closed-loop augmented system is established for the IMT powertrain system under discrete-time framework. The proposed controller design problem is then converted to a static output feedback (SOF) controller design problem where the feedback control gains are obtained by solving a set of linear matrix inequalities (LMIs). The effectiveness as well as robustness of the proposed controller is demonstrated by comparing its performance against that of a conventional PI controller.

  6. Control of 12-Cylinder Camless Engine with Neural Networks

    Directory of Open Access Journals (Sweden)

    Ashhab Moh’d Sami

    2017-01-01

    Full Text Available The 12-cyliner camless engine breathing process is modeled with artificial neural networks (ANN’s. The inputs to the net are the intake valve lift (IVL and intake valve closing timing (IVC whereas the output of the net is the cylinder air charge (CAC. The ANN is trained with data collected from an engine simulation model which is based on thermodynamics principles and calibrated against real engine data. A method for adapting single-output feed-forward neural networks is proposed and applied to the camless engine ANN model. As a consequence the overall 12-cyliner camless engine feedback controller is upgraded and the necessary changes are implemented in order to contain the adaptive neural network with the objective of tracking the cylinder air charge (driver’s torque demand while minimizing the pumping losses (increasing engine efficiency. All the needed measurements are extracted only from the two conventional and inexpensive sensors, namely, the mass air flow through the throttle body (MAF and the intake manifold absolute pressure (MAP sensors. The feedback controller’s capability is demonstrated through computer simulation.

  7. An Efficient Wireless Sensor Network for Industrial Monitoring and Control

    Directory of Open Access Journals (Sweden)

    Juan Aponte-Luis

    2018-01-01

    Full Text Available This paper presents the design of a wireless sensor network particularly designed for remote monitoring and control of industrial parameters. The article describes the network components, protocol and sensor deployment, aimed to accomplish industrial constraint and to assure reliability and low power consumption. A particular case of study is presented. The system consists of a base station, gas sensing nodes, a tree-based routing scheme for the wireless sensor nodes and a real-time monitoring application that operates from a remote computer and a mobile phone. The system assures that the industrial safety quality and the measurement and monitoring system achieves an efficient industrial monitoring operations. The robustness of the developed system and the security in the communications have been guaranteed both in hardware and software level. The system is flexible and can be adapted to different environments. The testing of the system confirms the feasibility of the proposed implementation and validates the functional requirements of the developed devices, the networking solution and the power consumption management.

  8. An Efficient Wireless Sensor Network for Industrial Monitoring and Control.

    Science.gov (United States)

    Aponte-Luis, Juan; Gómez-Galán, Juan Antonio; Gómez-Bravo, Fernando; Sánchez-Raya, Manuel; Alcina-Espigado, Javier; Teixido-Rovira, Pedro Miguel

    2018-01-10

    This paper presents the design of a wireless sensor network particularly designed for remote monitoring and control of industrial parameters. The article describes the network components, protocol and sensor deployment, aimed to accomplish industrial constraint and to assure reliability and low power consumption. A particular case of study is presented. The system consists of a base station, gas sensing nodes, a tree-based routing scheme for the wireless sensor nodes and a real-time monitoring application that operates from a remote computer and a mobile phone. The system assures that the industrial safety quality and the measurement and monitoring system achieves an efficient industrial monitoring operations. The robustness of the developed system and the security in the communications have been guaranteed both in hardware and software level. The system is flexible and can be adapted to different environments. The testing of the system confirms the feasibility of the proposed implementation and validates the functional requirements of the developed devices, the networking solution and the power consumption management.

  9. Idiotypic immune networks in mobile-robot control.

    Science.gov (United States)

    Whitbrook, Amanda M; Aickelin, Uwe; Garibaldi, Jonathan M

    2007-12-01

    Jerne's idiotypic-network theory postulates that the immune response involves interantibody stimulation and suppression, as well as matching to antigens. The theory has proved the most popular artificial immune system (AIS) model for incorporation into behavior-based robotics, but guidelines for implementing idiotypic selection are scarce. Furthermore, the direct effects of employing the technique have not been demonstrated in the form of a comparison with nonidiotypic systems. This paper aims to address these issues. A method for integrating an idiotypic AIS network with a reinforcement-learning (RL)-based control system is described, and the mechanisms underlying antibody stimulation and suppression are explained in detail. Some hypotheses that account for the network advantage are put forward and tested using three systems with increasing idiotypic complexity. The basic RL, a simplified hybrid AIS-RL that implements idiotypic selection independently of derived concentration levels, and a full hybrid AIS-RL scheme are examined. The test bed takes the form of a simulated Pioneer robot that is required to navigate through maze worlds detecting and tracking door markers.

  10. Evolution of Wireless Sensor Networks for Industrial Control

    Directory of Open Access Journals (Sweden)

    Arthur Low

    2013-05-01

    Full Text Available Technologies evolve in a process of gradual scientific change, but the commercial application of technologies is discontinuous. Managers interested in technology evolution can integrate these contrasting ideas using a powerful theoretical framework, based on the concept of punctuated equilibrium from evolutionary biology. The framework, which enables the differentiation of the technical evolution of a technology from its market application, is used in this article to compare the two standards for wireless sensor networks (WSN for industrial instrumentation and control: WirelessHART and ISA100.11a. The two WSN standards are the product of two different market contexts, which have selected different minimum viable technologies for evolution in their respective niches. Network security issues present some important selection criteria. Both WSN standards implement security countermeasures against localized wireless network attacks based on the application of the AES encryption standard, but some specific security threats – some local, others remotely launched – are only well-defended by the adoption of public-key cryptographic (PKC protocols, which only ISA100.11a supports. This article concludes that the mainstream market potential of the Internet has influenced the evolution of ISA100.11a and will continue to demand that each WSN standard evolve in ways that are difficult to predict.

  11. Mars Digital Image Model 2.1 Control Network

    Science.gov (United States)

    Archinal, B. A.; Kirk, R. L.; Duxbury, T. C.; Lee, E. M.; Sucharski, R.; Cook, D.

    2003-01-01

    USGS is currently preparing a new version of its global Mars digital image mosaic, which will be known as MDIM 2.1. As part of this process we are completing a new photogrammetric solution of the global Mars control network. This is an improved version of the network established earlier by RAND and USGS personnel, as partially described previously. MDIM 2.1 will have many improvements over earlier Viking Orbiter (VO) global mosaics. Geometrically, it will be an orthoimage product, draped on Mars Orbiter Laser Altimeter (MOLA) derived topography, thus accounting properly for the commonly oblique VO imagery. Through the network being described here it will be tied to the newly defined IAU/IAG 2000 Mars coordinate system via ties to MOLA data. Thus, MDIM 2.1 will provide complete global orthorectified imagery coverage of Mars at the resolution of 1/256 deg of MDIM 2.0, and be compatible with MOLA and other products produced in the current coordinate system.

  12. Rbfox2 controls autoregulation in RNA-binding protein networks.

    Science.gov (United States)

    Jangi, Mohini; Boutz, Paul L; Paul, Prakriti; Sharp, Phillip A

    2014-03-15

    The tight regulation of splicing networks is critical for organismal development. To maintain robust splicing patterns, many splicing factors autoregulate their expression through alternative splicing-coupled nonsense-mediated decay (AS-NMD). However, as negative autoregulation results in a self-limiting window of splicing factor expression, it is unknown how variations in steady-state protein levels can arise in different physiological contexts. Here, we demonstrate that Rbfox2 cross-regulates AS-NMD events within RNA-binding proteins to alter their expression. Using individual nucleotide-resolution cross-linking immunoprecipitation coupled to high-throughput sequencing (iCLIP) and mRNA sequencing, we identified >200 AS-NMD splicing events that are bound by Rbfox2 in mouse embryonic stem cells. These "silent" events are characterized by minimal apparent splicing changes but appreciable changes in gene expression upon Rbfox2 knockdown due to degradation of the NMD-inducing isoform. Nearly 70 of these AS-NMD events fall within genes encoding RNA-binding proteins, many of which are autoregulated. As with the coding splicing events that we found to be regulated by Rbfox2, silent splicing events are evolutionarily conserved and frequently contain the Rbfox2 consensus UGCAUG. Our findings uncover an unexpectedly broad and multilayer regulatory network controlled by Rbfox2 and offer an explanation for how autoregulatory splicing networks are tuned.

  13. Overflow control mechanism (OCM) for Ethernet passive optical networks (EPONs)

    Science.gov (United States)

    Hajduczenia, Marek; da Silva, Henrique J. A.; Monteiro, Paulo P.

    2007-05-01

    The nonfragmentable nature of Ethernet data frames, as well as operation of the priority oriented packet schedulers in the optical network units, in conjunction with heavy network load conditions and the lack of detailed knowledge about the queue's composition at the optical line terminal (OLT) level, result in the creation of upstream channel slot remainders. The existing methods, in the form of nonpreemptive packet schedulers and multithreshold reporting process defined vaguely by the IEEE 802.3-2005 standard, result in either increased packet delay or Ethernet passive optical network (EPON) system incompatibility, respectively, since threshold processing was never officially defined in the scope of the respective EPON standard. We propose an alternative approach, based on basic modifications of the standard and extended GATE multipoint control protocol data unit format and meaning, allowing for the OLT packet scheduling agent to grant always exactly the requested slot size, thus preventing creation of any upstream channel slot remainders. It is estimated that, on average, ˜3% of upstream channel bandwidth can be salvaged when slot remainders are absent in the upstream channel transmission.

  14. Microglia Control Neuronal Network Excitability via BDNF Signalling

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    Francesco Ferrini

    2013-01-01

    Full Text Available Microglia-neuron interactions play a crucial role in several neurological disorders characterized by altered neural network excitability, such as epilepsy and neuropathic pain. While a series of potential messengers have been postulated as substrates of the communication between microglia and neurons, including cytokines, purines, prostaglandins, and nitric oxide, the specific links between messengers, microglia, neuronal networks, and diseases have remained elusive. Brain-derived neurotrophic factor (BDNF released by microglia emerges as an exception in this riddle. Here, we review the current knowledge on the role played by microglial BDNF in controlling neuronal excitability by causing disinhibition. The efforts made by different laboratories during the last decade have collectively provided a robust mechanistic paradigm which elucidates the mechanisms involved in the synthesis and release of BDNF from microglia, the downstream TrkB-mediated signals in neurons, and the biophysical mechanism by which disinhibition occurs, via the downregulation of the K+-Cl− cotransporter KCC2, dysrupting Cl−homeostasis, and hence the strength of GABAA- and glycine receptor-mediated inhibition. The resulting altered network activity appears to explain several features of the associated pathologies. Targeting the molecular players involved in this canonical signaling pathway may lead to novel therapeutic approach for ameliorating a wide array of neural dysfunctions.

  15. Screening of Genetic Switches Based on the Twister Ribozyme Motif.

    Science.gov (United States)

    Felletti, Michele; Klauser, Benedikt; Hartig, Jörg S

    2016-01-01

    The recent description of a new class of small endonucleolytic ribozymes termed twister opened new avenues into the development of artificial riboswitches, providing new tools for the development of artificial genetic circuits in bacteria. Here we present a method to develop new ligand-dependent riboswitches, employing the newly described catalytic motif as an expression platform in conjugation with naturally occurring or in vitro-selected aptameric domains. The twister motif is an outstandingly flexible tool for the development of highly active ribozyme-based riboswitches able to control gene expression in a ligand-dependent manner in Escherichia coli.

  16. Interactive control over a programmable computer network using a multi-touch surface

    NARCIS (Netherlands)

    Strijkers, R.J.; Muller, L.; Cristea, M.L.; Belleman, R.; de Laat, C.; Sloot, P.; Meijer, R.

    2009-01-01

    This article introduces the Interactive Network concept and describes the design and implementation of the first prototype. In an Interactive Network humans become an integral part of the control system to manage programmable networks and grid networks. The implementation consists of a multi-touch

  17. rMotifGen: random motif generator for DNA and protein sequences

    Directory of Open Access Journals (Sweden)

    Hardin C Timothy

    2007-08-01

    Full Text Available Abstract Background Detection of short, subtle conserved motif regions within a set of related DNA or amino acid sequences can lead to discoveries about important regulatory domains such as transcription factor and DNA binding sites as well as conserved protein domains. In order to help assess motif detection algorithms on motifs with varying properties and levels of conservation, we have developed a computational tool, rMotifGen, with the sole purpose of generating a number of random DNA or protein sequences containing short sequence motifs. Each motif consensus can be user-defined, randomly generated, or created from a position-specific scoring matrix (PSSM. Insertions and mutations within these motifs are created according to user-defined parameters and substitution matrices. The resulting sequences can be helpful in mutational simulations and in testing the limits of motif detection algorithms. Results Two implementations of rMotifGen have been created, one providing a graphical user interface (GUI for random motif construction, and the other serving as a command line interface. The second implementation has the added advantages of platform independence and being able to be called in a batch mode. rMotifGen was used to construct sample sets of sequences containing DNA motifs and amino acid motifs that were then tested against the Gibbs sampler and MEME packages. Conclusion rMotifGen provides an efficient and convenient method for creating random DNA or amino acid sequences with a variable number of motifs, where the instance of each motif can be incorporated using a position-specific scoring matrix (PSSM or by creating an instance mutated from its corresponding consensus using an evolutionary model based on substitution matrices. rMotifGen is freely available at: http://bioinformatics.louisville.edu/brg/rMotifGen/.

  18. Web based educational tool for neural network robot control

    Directory of Open Access Journals (Sweden)

    Jure Čas

    2007-05-01

    Full Text Available Abstract— This paper describes the application for teleoperations of the SCARA robot via the internet. The SCARA robot is used by students of mehatronics at the University of Maribor as a remote educational tool. The developed software consists of two parts i.e. the continuous neural network sliding mode controller (CNNSMC and the graphical user interface (GUI. Application is based on two well-known commercially available software packages i.e. MATLAB/Simulink and LabVIEW. Matlab/Simulink and the DSP2 Library for Simulink are used for control algorithm development, simulation and executable code generation. While this code is executing on the DSP-2 Roby controller and through the analog and digital I/O lines drives the real process, LabVIEW virtual instrument (VI, running on the PC, is used as a user front end. LabVIEW VI provides the ability for on-line parameter tuning, signal monitoring, on-line analysis and via Remote Panels technology also teleoperation. The main advantage of a CNNSMC is the exploitation of its self-learning capability. When friction or an unexpected impediment occurs for example, the user of a remote application has no information about any changed robot dynamic and thus is unable to dispatch it manually. This is not a control problem anymore because, when a CNNSMC is used, any approximation of changed robot dynamic is estimated independently of the remote’s user. Index Terms—LabVIEW; Matlab/Simulink; Neural network control; remote educational tool; robotics

  19. Distributed Interplanetary Delay/Disruption Tolerant Network (DTN) Monitor and Control System

    Science.gov (United States)

    Wang, Shin-Ywan

    2012-01-01

    The main purpose of Distributed interplanetary Delay Tolerant Network Monitor and Control System as a DTN system network management implementation in JPL is defined to provide methods and tools that can monitor the DTN operation status, detect and resolve DTN operation failures in some automated style while either space network or some heterogeneous network is infused with DTN capability. In this paper, "DTN Monitor and Control system in Deep Space Network (DSN)" exemplifies a case how DTN Monitor and Control system can be adapted into a space network as it is DTN enabled.

  20. Characterization of the CrbS/R Two-Component System in Pseudomonas fluorescens Reveals a New Set of Genes under Its Control and a DNA Motif Required for CrbR-Mediated Transcriptional Activation

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    Edgardo Sepulveda

    2017-11-01

    Full Text Available The CrbS/R system is a two-component signal transduction system that regulates acetate utilization in Vibrio cholerae, P. aeruginosa, and P. entomophila. CrbS is a hybrid histidine kinase that belongs to a recently identified family, in which the signaling domain is fused to an SLC5 solute symporter domain through aSTAC domain. Upon activation by CrbS, CrbR activates transcription of the acs gene, which encodes an acetyl-CoA synthase (ACS, and the actP gene, which encodes an acetate/solute symporter. In this work, we characterized the CrbS/R system in Pseudomonas fluorescens SBW25. Through the quantitative proteome analysis of different mutants, we were able to identify a new set of genes under its control, which play an important role during growth on acetate. These results led us to the identification of a conserved DNA motif in the putative promoter region of acetate-utilization genes in the Gammaproteobacteria that is essential for the CrbR-mediated transcriptional activation of genes under acetate-utilizing conditions. Finally, we took advantage of the existence of a second SLC5-containing two-component signal transduction system in P. fluorescens, CbrA/B, to demonstrate that the activation of the response regulator by the histidine kinase is not dependent on substrate transport through the SLC5 domain.