Schwarz, J. M.; Zhang, Tao
2015-03-01
The actin cytoskeleton provides the cell with structural integrity and allows it to change shape to crawl along a surface, for example. The actin cytoskeleton can be modeled as a semiflexible biopolymer network that modifies its morphology in response to both external and internal stimuli. Just inside the inner nuclear membrane of a cell exists a network of filamentous lamin that presumably protects the heart of the cell nucleus--the DNA. Lamins are intermediate filaments that can also be modeled as semiflexible biopolymers. It turns out that the actin cytoskeletal biopolymer network and the lamin biopolymer network are coupled via a sequence of proteins that bridge the outer and inner nuclear membranes. We, therefore, probe the consequences of such a coupling via numerical simulations to understand the resulting deformations in the lamin network in response to perturbations in the cytoskeletal network. Such study could have implications for mechanical mechanisms of the regulation of transcription, since DNA--yet another semiflexible polymer--contains lamin-binding domains, and, thus, widen the field of epigenetics.
Mutoh, Katsuya; Abe, Jiro
2014-09-07
The bridged imidazole dimers are some of the attractive fast photochromic compounds which have potential applications to the ophthalmic lenses, real-time hologram and molecular machines. The strategy for expanding their photochromic properties such as the colour variation and tuning the decolouration rates has been vigorously investigated, but the insight into the structural changes along the photochromic reactions has not been demonstrated in detail. Here, we demonstrated the pressure dependence of the radical-radical recombination reaction of the bridged imidazole dimers. The radical-radical interaction can be controlled by applying high pressure. Our results give fundamental information about the molecular dynamics of the bridged imidazole dimers, leading to the development of new functional photochromic machines and pressure-sensitive photochromic materials.
Energy Technology Data Exchange (ETDEWEB)
Abelev, B. [Lawrence Livermore National Laboratory, Livermore, CA (United States); Abrahantes Quintana, A. [Centro de Aplicaciones Tecnologicas y Desarrollo Nuclear (CEADEN), Havana (Cuba); Adamova, D. [Nuclear Physics Institute, Academy of Sciences of the Czech Republic, Rez u Prahy (Czech Republic); Adare, A.M. [Yale University, New Haven, CT (United States); Aggarwal, M.M. [Physics Department, Panjab University, Chandigarh (India); Aglieri Rinella, G. [European Organization for Nuclear Research (CERN), Geneva (Switzerland); Agocs, A.G. [KFKI Research Institute for Particle and Nuclear Physics, Hungarian Academy of Sciences, Budapest (Hungary); Agostinelli, A. [Dipartimento di Fisica dell' Universita and Sezione INFN, Bologna (Italy); Aguilar Salazar, S. [Instituto de Fisica, Universidad Nacional Autonoma de Mexico, Mexico City (Mexico); Ahammed, Z. [Variable Energy Cyclotron Centre, Kolkata (India); Ahmad, N.; Ahmad Masoodi, A. [Department of Physics, Aligarh Muslim University, Aligarh (India); Ahn, S.U. [Laboratoire de Physique Corpusculaire (LPC), Clermont Universite, Universite Blaise Pascal, CNRS-IN2P3, Clermont-Ferrand (France); Gangneung-Wonju National University, Gangneung (Korea, Republic of); Akindinov, A. [Institute for Theoretical and Experimental Physics, Moscow (Russian Federation); Aleksandrov, D. [Russian Research Centre Kurchatov Institute, Moscow (Russian Federation); Alessandro, B. [Sezione INFN, Turin (Italy); Alfaro Molina, R. [Instituto de Fisica, Universidad Nacional Autonoma de Mexico, Mexico City (Mexico); and others
2012-10-22
The first measurements of the invariant differential cross sections of inclusive {pi}{sup 0} and {eta} meson production at mid-rapidity in proton-proton collisions at {radical}(s)=0.9 TeV and {radical}(s)=7 TeV are reported. The {pi}{sup 0} measurement covers the ranges 0.4
Coupled oscillators on evolving networks
Singh, R. K.; Bagarti, Trilochan
2016-12-01
In this work we study coupled oscillators on evolving networks. We find that the steady state behavior of the system is governed by the relative values of the spread in natural frequencies and the global coupling strength. For coupling strong in comparison to the spread in frequencies, the system of oscillators synchronize and when coupling strength and spread in frequencies are large, a phenomenon similar to amplitude death is observed. The network evolution provides a mechanism to build inter-oscillator connections and once a dynamic equilibrium is achieved, oscillators evolve according to their local interactions. We also find that the steady state properties change by the presence of additional time scales. We demonstrate these results based on numerical calculations studying dynamical evolution of limit-cycle and van der Pol oscillators.
Stochastic coupling of two random Boolean networks
Energy Technology Data Exchange (ETDEWEB)
Ho, M.-C. [Department of Physics, National Kaohsiung Normal University, Kaohsiung, Taiwan (China)]. E-mail: t1603@nknucc.nknu.edu.tw; Hung, Y.-C. [Department of Physics, National Sun Yat-sen University, Kaohsiung, Taiwan (China)]. E-mail: d9123801@student.nsysu.edu.tw; Jiang, I-M. [Department of Physics, National Sun Yat-sen University, Kaohsiung, Taiwan (China)
2005-08-29
We study the dynamics of two coupled random Boolean networks. Based on the Boolean model studied by Andrecut and Ali [Int. J. Mod. Phys. B 15 (2001) 17] and the stochastic coupling techniques, the density evolution of networks is precisely described by two deterministic coupled polynomial maps. The iteration results of the model match the real networks well. By using MSE and the maximal Lyapunov exponents, the synchronization phenomena of coupled networks is also under our discussion.
Energy Technology Data Exchange (ETDEWEB)
Roach-Bellino, M.
1994-02-01
The Z + {gamma} cross-section x branching ratio in the electron channel has been measured using the inclusive Z data sample from the CDF 1988--1989 collider run, for which the total integrated luminosity was 4.05 {plus_minus} 0.28 pb{sup {minus}1}. Two Z{gamma} candidates are observed from central photon events with {Delta}R/{sub {gamma}} > 0.7 and E{sub t}{sup {gamma}} > 5.0 GeV. From these events the {sigma} * BR(Z + {gamma}) is measured and compared with SM predictions: {sigma} * BR(Z + {gamma}){sub e} = 6.8{sub {minus}5.7}{sup +5.7}(stat + syst)pb {sigma} * BR(Z + {gamma})SM = 4.7{sub {minus}4.7}{sup +0.7}(stat + syst)pb. From this ZZ{sub {gamma}} cross section measurement limits on the Z{sub {gamma}{gamma}} and couplings for three different choices of compositeness scale {Lambda}{sub Z} are obtained. The experimental sensitivity to the h{sub 30}{sup Z,{gamma}}/h{sub 10}{sup Z,{gamma}} couplings is in the range of {Lambda}{sub Z} {approximately} 450--500 GeV and for the h{sub 40}{sup Z{gamma}}/h{sub 20}{sup Z,{gamma}} couplings {Lambda}{sub Z} {approximately} 300 GeV.
Energy Technology Data Exchange (ETDEWEB)
Alhroob, Muhammad
2013-03-15
This thesis represents the search for single top-quark production through flavour changing neutral currents using data collected by the ATLAS detector in 2011, at a centre-of-mass energy of {radical}(s)=7 TeV, corresponding to an integrated luminosity of 2.05 fb{sup -1}. Candidate events are selected with one isolated lepton, missing transverse momentum associated to the undetected neutrino and a jet originated from the hadronisation of a b quark. Given the large expected number of background events and the small number of expected signal events, a neural network classifier is developed to combine many kinematic variables to create a powerful separator in order classify the events as a signal- or a background-like events. As no sign of new physics is seen in the neural network output distribution, a Bayesian statistical method is used to set an upper limit at 95% confidence level (C.L.) on the single top-quark production cross section through FCNC processes. The observed upper limit at 95% C.L. on the cross-section multiplied by the t{yields}Wb branching fraction is measured to be {sigma}{sub qg{yields}t} x B(t {yields}Wb)< 3.9 pb. This upper limit is converted using a model-independent approach into upper limits on the coupling strengths (K{sub ugt})/({Lambda})<6.9.10{sup -3} TeV{sup -1} and (K{sub cgt})/({Lambda})<1.6.10{sup -2} TeV{sup -1}, where {Lambda} is the new physics scale, and on the branching fractions B(t{yields}ug)<5.7 .10{sup -5} and B(t{yields}cg)< 2.7.10{sup -4}. The limits on the branching fractions are the world's best limits to date and significantly improving the previous limits obtained by the DOe collaboration by a factor of 15.
Synchronization of Intermittently Coupled Dynamical Networks
Directory of Open Access Journals (Sweden)
Gang Zhang
2013-01-01
Full Text Available This paper investigates the synchronization phenomenon of an intermittently coupled dynamical network in which the coupling among nodes can occur only at discrete instants and the coupling configuration of the network is time varying. A model of intermittently coupled dynamical network consisting of identical nodes is introduced. Based on the stability theory for impulsive differential equations, some synchronization criteria for intermittently coupled dynamical networks are derived. The network synchronizability is shown to be related to the second largest and the smallest eigenvalues of the coupling matrix, the coupling strength, and the impulsive intervals. Using the chaotic Chua system and Lorenz system as nodes of a dynamical network for simulation, respectively, the theoretical results are verified and illustrated.
Energy Technology Data Exchange (ETDEWEB)
Kweon, Min Jung [Universitaet Heidelberg Physikalisches Institut, Heidelberg (Germany); Collaboration: ALICE-Collaboration
2011-07-01
The measurement of single electrons from heavy flavor hadron decays at RHIC indicates strong coupling of heavy quarks to the medium produced in ultra relativistic heavy-ion collisions. The LHC extends greatly the kinematic range to high transverse momentum which enables new tests of heavy quark jet dynamics. The beauty hadrons and jets containing beauty hadrons have distinctive properties, which allow for their clear identification. We introduce methods to preferentially select electrons from beauty hadron decays by minimum distance of closest approach cuts and by reconstructing secondary vertices. The first analysis applying these techniques in the ALICE experiment for p+p collisions at {radical}(s)=7 TeV is presented. The analysis status of the data from Pb+Pb collisions, which will allow us to understand beauty quark energy loss in the medium, is also reported.
Laccase catalyzed grafting of-N-OH type mediators to lignin via radical-radical coupling
DEFF Research Database (Denmark)
Munk, Line; Punt, A. M.; Kabel, M. A.
2017-01-01
by laccases from Trametes versicolor and Pleurotus ostreatus by quantitative analysis of the reaction outcome by pyrolysis gas chromatography mass spectroscopy. The two laccases were equally efficient in catalyzing grafting, but only-N-OH type mediators grafted. HPI (N-hydroxyacetanilide) grafted 7-10 times...
Adaptive synchronization of asymmetric coupled networks with multiple coupling delays
Sun, Weiwei; Hao, Fei; Chen, Xia
2012-05-01
The synchronization problem of asymmetric networks with multiple coupled delays is investigated in this paper. By using Lyapunov stability theory and Lasalle's invariance principle, several synchronization criteria are deduced for both asymmetric networks with and without norm uncertainties. Furthermore, the synchronization problem of a special complex network with each node being a Lurie system is studied. The main results show that the states of all nodes of networks globally asymptotically synchronize to a desired synchronization state by designing suitable adaptive controllers, and these controllers have strong robustness against the uncertain coupling matrixes. Finally, several illustrative examples with numerical simulations are given to show the feasibility and efficiency of theoretical results.
Light vector meson production in pp collisions at {radical}(s)=7 TeV
Energy Technology Data Exchange (ETDEWEB)
Abelev, B. [Lawrence Livermore National Laboratory, Livermore, CA (United States); Abrahantes Quintana, A. [Centro de Aplicaciones Tecnologicas y Desarrollo Nuclear (CEADEN), Havana (Cuba); Adamova, D. [Nuclear Physics Institute, Academy of Sciences of the Czech Republic, Rez u Prahy (Czech Republic); Adare, A.M. [Yale University, New Haven, CT (United States); Aggarwal, M.M. [Physics Department, Panjab University, Chandigarh (India); Aglieri Rinella, G. [European Organization for Nuclear Research (CERN), Geneva (Switzerland); Agocs, A.G. [KFKI Research Institute for Particle and Nuclear Physics, Hungarian Academy of Sciences, Budapest (Hungary); Agostinelli, A. [Dipartimento di Fisica dell' Universita and Sezione INFN, Bologna (Italy); Aguilar Salazar, S. [Instituto de Fisica, Universidad Nacional Autonoma de Mexico, Mexico City (Mexico); Ahammed, Z. [Variable Energy Cyclotron Centre, Kolkata (India); Ahmad, N.; Ahmad Masoodi, A. [Department of Physics, Aligarh Muslim University, Aligarh (India); Ahn, S.U. [Laboratoire de Physique Corpusculaire (LPC), Clermont Universite, Universite Blaise Pascal, CNRS-IN2P3, Clermont-Ferrand (France); Gangneung-Wonju National University, Gangneung (Korea, Republic of); Akindinov, A. [Institute for Theoretical and Experimental Physics, Moscow (Russian Federation); Aleksandrov, D. [Russian Research Centre Kurchatov Institute, Moscow (Russian Federation); Alessandro, B. [Sezione INFN, Turin (Italy); Alfaro Molina, R. [Instituto de Fisica, Universidad Nacional Autonoma de Mexico, Mexico City (Mexico); and others
2012-04-20
The ALICE experiment has measured low-mass dimuon production in pp collisions at {radical}(s)=7 TeV in the dimuon rapidity region 2.5
Observation of X(3872) production in pp collisions at {radical}(s)=7 TeV
Energy Technology Data Exchange (ETDEWEB)
Aaij, R. [Nikhef National Institute for Subatomic Physics, Amsterdam (Netherlands); Abellan Beteta, C. [Universitat de Barcelona, Barcelona (Spain); Adeva, B. [Universidad de Santiago de Compostela, Santiago de Compostela (ES)] (and others)
2012-05-15
Using 34.7 pb{sup -1} of data collected with the LHCb detector, the inclusive production of the X(3872) meson in pp collisions at {radical}(s)=7 TeV is observed for the first time. Candidates are selected in the X(3872){yields}J/{psi}{pi}{sup +}{pi}{sup -} decay mode, and used to measure where {sigma}(pp{yields}X(3872)+anything) is the inclusive production cross section of X(3872) mesons with rapidity in the range 2.5-4.5 and transverse momentum in the range 5-20 GeV/c. In addition the masses of both the X(3872) and {psi}(2S) mesons, reconstructed in the J/{psi}{pi}{sup +}{pi}{sup -} final state, are measured to be m{sub X(3872)} = 3871.95 {+-}0.48(stat){+-}0.12(syst) MeV/c{sup 2} and m{sub {psi}}{sub (2S)} = 3686.12{+-}0.06(stat){+-}0.10(syst) MeV/c{sup 2}. (orig.)
J/{psi} production in {radical}(s)=7 TeV pp collisions
Energy Technology Data Exchange (ETDEWEB)
Kramer, Frederick
2012-07-01
In the first part of this work the inclusive cross section for J/{psi} production in inelastic {radical}(s) = 7 TeV pp collisions has been determined within vertical stroke y vertical stroke < 0.9 and in the decay channel J/{psi} {yields} e{sup +}e{sup -}. The result for the integrated value is: {sigma}{sub J/{psi}}(vertical stroke y vertical stroke < 0.9) = 10.7 {+-} 0.8 (stat.) {+-} 1.4 (syst.) {+-} 0.4 (lumi.) {mu}b. Together with the ALICE measurement in the {mu}{sup +}{mu}{sup -} decay channel at forward rapidities and data from other experiments this result fills the gap at mid-rapidity for a comprehensive measurement of the J/{psi} rapidity distribution. Furthermore, results of the differential analysis as a function of the J/{psi} transverse momentum were presented. Finally the data are shown together with various theoretical predictions representing the current status of the three most common theoretical approaches for the description of quarkonia production: the Color-Singlet Model, the Color-Evaporation Model and NRQCD.
Synchronization in complex networks with adaptive coupling
Zhang, Rong; Hu, Manfeng; Xu, Zhenyuan
2007-08-01
Generally it is very difficult to realized synchronization for some complex networks. In order to synchronize, the coupling coefficient of networks has to be very large, especially when the number of coupled nodes is larger. In this Letter, we consider the problem of synchronization in complex networks with adaptive coupling. A new concept about asymptotic stability is presented, then we proved by using the well-known LaSalle invariance principle, that the state of such a complex network can synchronize an arbitrary assigned state of an isolated node of the network as long as the feedback gain is positive. Unified system is simulated as the nodes of adaptive coupling complex networks with different topologies.
Synchronization in complex networks with adaptive coupling
Energy Technology Data Exchange (ETDEWEB)
Zhang Rong [School of Science, Southern Yangtze University, Wuxi 214122 (China); School of Information Engineering, Southern Yangtze University, Wuxi 214122 (China)], E-mail: ronia62@yahoo.com; Hu Manfeng [School of Science, Southern Yangtze University, Wuxi 214122 (China); School of Information Engineering, Southern Yangtze University, Wuxi 214122 (China); Xu Zhenyuan [School of Science, Southern Yangtze University, Wuxi 214122 (China)
2007-08-20
Generally it is very difficult to realized synchronization for some complex networks. In order to synchronize, the coupling coefficient of networks has to be very large, especially when the number of coupled nodes is larger. In this Letter, we consider the problem of synchronization in complex networks with adaptive coupling. A new concept about asymptotic stability is presented, then we proved by using the well-known LaSalle invariance principle, that the state of such a complex network can synchronize an arbitrary assigned state of an isolated node of the network as long as the feedback gain is positive. Unified system is simulated as the nodes of adaptive coupling complex networks with different topologies.
Measurement of the forward energy flow in pp collisions at {radical}(s) = 7 TeV
Energy Technology Data Exchange (ETDEWEB)
Aaij, R. [Nikhef National Institute for Subatomic Physics, Amsterdam (Netherlands); Abellan Beteta, C. [Universitat de Barcelona, Barcelona (Spain); Adametz, A. [Ruprecht-Karls-Universitaet Heidelberg, Physikalisches Institut, Heidelberg (Germany)] [and others; Collaboration: The LHCb Collaboration
2013-05-15
The energy flow created in pp collisions at {radical}(s) = 7 TeV is studied within the pseudorapidity range 1.9<{eta}<4.9 with data collected by the LHCb experiment. The measurements are performed for inclusive minimum-bias interactions, hard scattering processes and events with an enhanced or suppressed diffractive contribution. The results are compared to predictions given by Pythia-based and cosmic-ray event generators, which provide different models of soft hadronic interactions. (orig.)
Measurement of {upsilon} production in pp collisions at {radical}(s)=7 TeV
Energy Technology Data Exchange (ETDEWEB)
Aaij, R. [Nikhef National Institute for Subatomic Physics, Amsterdam (Netherlands); Abellan Beteta, C. [Universitat de Barcelona, Barcelona (Spain); Adeva, B. [Universidad de Santiago de Compostela, Santiago de Compostela (ES)] (and others)
2012-06-15
The production of {upsilon}(1S), {upsilon}(2S) and {upsilon}(3S) mesons in proton-proton collisions at the centre-of-mass energy of {radical}(s)=7 TeV is studied with the LHCb detector. The analysis is based on a data sample of 25 pb{sup -1} collected at the Large Hadron Collider. The {upsilon} mesons are reconstructed in the decay mode {upsilon}{yields}{mu}{sup +}{mu}- and the signal yields are extracted from a fit to the {mu}{sup +}{mu}{sup -} invariant mass distributions. The differential production cross-sections times dimuon branching fractions are measured as a function of the {upsilon} transverse momentum p{sub T} and rapidity {gamma}, over the range p{sub T}<15 GeV/c and 2.0
Synchronization of impulsively coupled complex networks
Institute of Scientific and Technical Information of China (English)
Sun Wen; Chen Zhong; Chen Shi-Hua
2012-01-01
We investigate the synchronization of complex networks,which are impulsively coupled only at discrete instants.Based on the comparison theory of impulsive differential systems,a distributed impulsive control scheme is proposed for complex dynamical networks to achieve synchronization.The proposed scheme not only takes into account the influence of all nodes to network synchronization,which depends on the weight of each node in the network,but also provides us with a flexible method to select the synchronized state of the network.In addition,it is unnecessary for the impulsive coupling matrix to be symmetrical.Finally,the proposed control scheme is applied to a chaotic Lorenz network and Chua's circuit network.Numerical simulations are used to illustrate the validity of this control scheme.
Information filtering on coupled social networks.
Nie, Da-Cheng; Zhang, Zi-Ke; Zhou, Jun-Lin; Fu, Yan; Zhang, Kui
2014-01-01
In this paper, based on the coupled social networks (CSN), we propose a hybrid algorithm to nonlinearly integrate both social and behavior information of online users. Filtering algorithm, based on the coupled social networks, considers the effects of both social similarity and personalized preference. Experimental results based on two real datasets, Epinions and Friendfeed, show that the hybrid pattern can not only provide more accurate recommendations, but also enlarge the recommendation coverage while adopting global metric. Further empirical analyses demonstrate that the mutual reinforcement and rich-club phenomenon can also be found in coupled social networks where the identical individuals occupy the core position of the online system. This work may shed some light on the in-depth understanding of the structure and function of coupled social networks.
Information filtering on coupled social networks.
Directory of Open Access Journals (Sweden)
Da-Cheng Nie
Full Text Available In this paper, based on the coupled social networks (CSN, we propose a hybrid algorithm to nonlinearly integrate both social and behavior information of online users. Filtering algorithm, based on the coupled social networks, considers the effects of both social similarity and personalized preference. Experimental results based on two real datasets, Epinions and Friendfeed, show that the hybrid pattern can not only provide more accurate recommendations, but also enlarge the recommendation coverage while adopting global metric. Further empirical analyses demonstrate that the mutual reinforcement and rich-club phenomenon can also be found in coupled social networks where the identical individuals occupy the core position of the online system. This work may shed some light on the in-depth understanding of the structure and function of coupled social networks.
Applications of Pulse-Coupled Neural Networks
Ma, Yide; Wang, Zhaobin
2011-01-01
"Applications of Pulse-Coupled Neural Networks" explores the fields of image processing, including image filtering, image segmentation, image fusion, image coding, image retrieval, and biometric recognition, and the role of pulse-coupled neural networks in these fields. This book is intended for researchers and graduate students in artificial intelligence, pattern recognition, electronic engineering, and computer science. Prof. Yide Ma conducts research on intelligent information processing, biomedical image processing, and embedded system development at the School of Information Sci
Synchronization of coupled chaotic dynamics on networks
Indian Academy of Sciences (India)
R E Amritkar; Sarika Jalan
2005-03-01
We review some recent work on the synchronization of coupled dynamical systems on a variety of networks. When nodes show synchronized behaviour, two interesting phenomena can be observed. First, there are some nodes of the floating type that show intermittent behaviour between getting attached to some clusters and evolving independently. Secondly, two different ways of cluster formation can be identified, namely self-organized clusters which have mostly intra-cluster couplings and driven clusters which have mostly inter-cluster couplings.
First measurements of beauty quark production at {radical}(s)=7TeV with the CMS experiment
Energy Technology Data Exchange (ETDEWEB)
Chiochia, Vincenzo [Universitaet Zuerich, Physik-Institut, Winterthurerstr. 190, 8057 Zuerich (Switzerland)
2011-04-01
This article summarizes the first measurements of inclusive beauty production cross section in proton-proton collisions at {radical}(s)=7TeV and central rapidities. The results are based on different techniques, such as the identification of semileptonic b-decays into muons and inclusive jet measurements with secondary vertex tagging. The measurements probe b-quark production in different regions of transverse momenta. The experimental results are compared with next-to-leading order QCD predictions and various Monte Carlo models.
Measurement of J/{psi} polarization in pp collisions at {radical}(s) =7 TeV
Energy Technology Data Exchange (ETDEWEB)
Aaij, R. [Nikhef National Institute for Subatomic Physics, Amsterdam (Netherlands); Abellan Beteta, C. [Universitat de Barcelona, Barcelona (Spain); Adeva, B. [Universidad de Santiago de Compostela, Santiago de Compostela (Spain); Collaboration: The LHCb Collaboration; and others
2013-11-15
An angular analysis of the decay J/{psi} {yields} {mu}{sup +}{mu}{sup -} is performed to measure the polarization of prompt J/{psi} mesons produced in pp collisions at {radical}(s) =7 TeV. The dataset corresponds to an integrated luminosity of 0.37 fb{sup -1} collected with the LHCb detector. The measurement is presented as a function of transverse momentum, p{sub T}, and rapidity, y, of the J/{psi} meson, in the kinematic region 2
Coupling between time series: a network view
Mehraban, Saeed; Zamani, Maryam; Jafari, Gholamreza
2013-01-01
Recently, the visibility graph has been introduced as a novel view for analyzing time series, which maps it to a complex network. In this paper, we introduce new algorithm of visibility, "cross-visibility", which reveals the conjugation of two coupled time series. The correspondence between the two time series is mapped to a network, "the cross-visibility graph", to demonstrate the correlation between them. We applied the algorithm to several correlated and uncorrelated time series, generated by the linear stationary ARFIMA process. The results demonstrate that the cross-visibility graph associated with correlated time series with power-law auto-correlation is scale-free. If the time series are uncorrelated, the degree distribution of their cross-visibility network deviates from power-law. For more clarifying the process, we applied the algorithm to real-world data from the financial trades of two companies, and observed significant small-scale coupling in their dynamics.
Energy Technology Data Exchange (ETDEWEB)
Aaij, R. [Nikhef National Institute for Subatomic Physics, Amsterdam (Netherlands); Abellan Beteta, C. [Barcelona Univ. (Spain); Adeva, B. [Universidad de Santiago de Compostela, Santiago de Compostela (ES)] (and others)
2012-04-15
Charged particle production in proton-proton collisions is studied with the LHCb detector at a centre-of-mass energy of {radical}(s) = 7 TeV in different intervals of pseudorapidity {eta}. Charged particles are reconstructed close to the interaction region in the vertex detector, which provides high reconstruction efficiency in the {eta} ranges -2.5<{eta}<-2.0 and 2.0<{eta}<4.5. The data were taken with a minimum bias trigger, only requiring one or more reconstructed tracks in the vertex detector. By selecting an event sample with at least one track with a transverse momentum greater than 1 GeV/c a hard QCD subsample is investigated. Several event generators are compared with the data; none are able to describe fully the multiplicity distributions or the charged particle density distribution as a function of {eta}. In general, the models underestimate charged particle production. (orig.)
Measurement of the inclusive {phi} cross-section in pp collisions at {radical}(s)=7 TeV
Energy Technology Data Exchange (ETDEWEB)
Aaij, R. [Nikhef National Institute for Subatomic Physics, Amsterdam (Netherlands); Adeva, B. [Universidad de Santiago de Compostela, Santiago de Compostela (Spain); Adinolfi, M. [H.H. Wills Physics Laboratory, University of Bristol, Bristol (United Kingdom); Adrover, C. [CPPM, Aix-Marseille Universite, CNRS/IN2P3, Marseille (France); Affolder, A. [Oliver Lodge Laboratory, University of Liverpool, Liverpool (United Kingdom); Ajaltouni, Z. [Clermont Universite, Universite Blaise Pascal, CNRS/IN2P3, LPC, Clermont-Ferrand (France); Albrecht, J. [European Organization for Nuclear Research (CERN), Geneva (Switzerland); Alessio, F. [CPPM, Aix-Marseille Universite, CNRS/IN2P3, Marseille (France); European Organization for Nuclear Research (CERN), Geneva (Switzerland); Alexander, M. [School of Physics and Astronomy, University of Glasgow, Glasgow (United Kingdom); Alkhazov, G. [Petersburg Nuclear Physics Institute (PNPI), Gatchina (Russian Federation); Alvarez Cartelle, P. [Universidad de Santiago de Compostela, Santiago de Compostela (Spain); Alves, A.A. [Sezione INFN di Roma La Sapienza, Roma (Italy); Amato, S. [Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro (Brazil); Amhis, Y. [Ecole Polytechnique Federale de Lausanne (EPFL), Lausanne (Switzerland); Anderson, J. [Physik-Institut, Universitaet Zuerich, Zuerich (Switzerland); Appleby, R.B. [School of Physics and Astronomy, University of Manchester, Manchester (United Kingdom); Aquines Gutierrez, O. [Max-Planck-Institut fuer Kernphysik (MPIK), Heidelberg (Germany); Arrabito, L. [CC-IN2P3, CNRS/IN2P3, Lyon-Villeurbanne (France); Artamonov, A. [Institute for High Energy Physics (IHEP), Protvino (Russian Federation); Artuso, M. [Syracuse University, Syracuse, NY (United States); European Organization for Nuclear Research (CERN), Geneva (Switzerland)
2011-09-14
The cross-section for inclusive {phi} meson production in pp collisions at a centre-of-mass energy of {radical}(s)=7 TeV has been measured with the LHCb detector at the Large Hadron Collider. The differential cross-section is measured as a function of the {phi} transverse momentum p{sub T} and rapidity y in the region 0.6
Detecting synchronization in coupled stochastic ecosystem networks
Energy Technology Data Exchange (ETDEWEB)
Kouvaris, N. [Institute of Physical Chemistry, National Center for Scientific Research ' Demokritos' , 15310 Athens (Greece); Department of Mathematical, Physical and Computational Science, Faculty of Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki (Greece); Provata, A. [Institute of Physical Chemistry, National Center for Scientific Research ' Demokritos' , 15310 Athens (Greece); Kugiumtzis, D., E-mail: dkugiu@gen.auth.g [Department of Mathematical, Physical and Computational Science, Faculty of Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki (Greece)
2010-01-11
Instantaneous phase difference, synchronization index and mutual information are considered in order to detect phase transitions, collective behaviours and synchronization phenomena that emerge for different levels of diffusive and reactive activity in stochastic networks. The network under investigation is a spatial 2D lattice which serves as a substrate for Lotka-Volterra dynamics with 3rd order nonlinearities. Kinetic Monte Carlo simulations demonstrate that the system spontaneously organizes into a number of asynchronous local oscillators, when only nearest neighbour interactions are considered. In contrast, the oscillators can be correlated, phase synchronized and completely synchronized when introducing different interactivity rules (diffusive or reactive) for nearby and distant species. The quantitative measures of synchronization show that long distance diffusion coupling induces phase synchronization after a well defined transition point, while long distance reaction coupling induces smeared phase synchronization.
Design of coupling resistor networks for neural network hardware
Barkan, Ozdal; Smith, W. R.; Persky, George
1990-06-01
The specification of an artificial neural network includes (1) the transformation relating each neuron's output voltage to its input voltage, and (2) a set of coupling weight factors expressing the input voltage of any neuron as a linear combination of the output voltages of other neurons. In analog VLSI chips for direct hardware implementation of these networks, neurons are often represented by amplifier elements (e.g. operational amplifiers or opamps), and resistors or active transconductances are used to couple signals from the outputs of certain neurons to the inputs of other neurons. Each coupling conductance is proportional to a single, corresponding coupling weight only under the following 'ideal' conditions: (1) each opamp has negligible output impedance, and (2) the input voltage of each opamp is developed across a low-resistance sampling resistor that is not loaded by the opamp itself. By contrast, the output impedance of a practical opamp may not be negligible in comparison to that of the high-fan network that it drives, and the sampling resistances on the opamp inputs cannot be arbitrarily low lest the input voltages be corrupted by unavoidable opamp input voltage offsets.
State dependent computation using coupled recurrent networks
Rutishauser, Ueli
2008-01-01
Although conditional branching between possible behavioural states is a hallmark of intelligent behavior, very little is known about the neuronal mechanisms that support this processing. In a step toward solving this problem we demonstrate by theoretical analysis and simulation how networks of richly inter-connected neurons, such as those observed in the superficial layers of the neocortex, can embed reliable robust finite state machines. We show how a multi-stable neuronal network containing a number of states can be created very simply, by coupling two recurrent networks whose synaptic weights have been configured for soft winner-take-all (sWTA) performance. These two sWTAs have simple, homogenous locally recurrent connectivity except for a small fraction of recurrent cross-connections between them, which are used to embed the required states. This coupling between the maps allows the network to continue to express the current state even after the input that elicted that state is withdrawn. In addition, a s...
Transportation dynamic on coupled networks with limited bandwidth
Li, Ming; Wang, Bing-Hong
2016-01-01
The communication networks in real world often couple with each other to save costs, which results in any network does not have a stand-alone function and efficiency. To investigate this, in this paper we propose a transportation model on two coupled networks with bandwidth sharing. We find that the free-flow state and the congestion state can coexist in the two coupled networks, and the free-flow path and congestion path can coexist in each network. Considering three bandwidth-sharing mechanisms, random, assortative and disassortative couplings, we also find that the transportation capacity of the network only depends on the coupling mechanism, and the fraction of coupled links only affects the performance of the system in the congestion state, such as the traveling time. In addition, with assortative coupling, the traffic capacity of the system will decrease significantly. However, the disassortative coupling has little influence on the transportation capacity of the system, which provides a good strategy t...
Interdependencies and Causalities in Coupled Financial Networks.
Vodenska, Irena; Aoyama, Hideaki; Fujiwara, Yoshi; Iyetomi, Hiroshi; Arai, Yuta
2016-01-01
We explore the foreign exchange and stock market networks for 48 countries from 1999 to 2012 and propose a model, based on complex Hilbert principal component analysis, for extracting significant lead-lag relationships between these markets. The global set of countries, including large and small countries in Europe, the Americas, Asia, and the Middle East, is contrasted with the limited scopes of targets, e.g., G5, G7 or the emerging Asian countries, adopted by previous works. We construct a coupled synchronization network, perform community analysis, and identify formation of four distinct network communities that are relatively stable over time. In addition to investigating the entire period, we divide the time period into into "mild crisis," (1999-2002), "calm," (2003-2006) and "severe crisis" (2007-2012) sub-periods and find that the severe crisis period behavior dominates the dynamics in the foreign exchange-equity synchronization network. We observe that in general the foreign exchange market has predictive power for the global stock market performances. In addition, the United States, German and Mexican markets have forecasting power for the performances of other global equity markets.
Interdependencies and Causalities in Coupled Financial Networks.
Directory of Open Access Journals (Sweden)
Irena Vodenska
Full Text Available We explore the foreign exchange and stock market networks for 48 countries from 1999 to 2012 and propose a model, based on complex Hilbert principal component analysis, for extracting significant lead-lag relationships between these markets. The global set of countries, including large and small countries in Europe, the Americas, Asia, and the Middle East, is contrasted with the limited scopes of targets, e.g., G5, G7 or the emerging Asian countries, adopted by previous works. We construct a coupled synchronization network, perform community analysis, and identify formation of four distinct network communities that are relatively stable over time. In addition to investigating the entire period, we divide the time period into into "mild crisis," (1999-2002, "calm," (2003-2006 and "severe crisis" (2007-2012 sub-periods and find that the severe crisis period behavior dominates the dynamics in the foreign exchange-equity synchronization network. We observe that in general the foreign exchange market has predictive power for the global stock market performances. In addition, the United States, German and Mexican markets have forecasting power for the performances of other global equity markets.
Kinetics Studies of Radical-Radical Reactions (I): The NO2 + N2H3 System
2013-08-01
the potential energy surface for the NO2 + N2H3 system and have established the most likely reaction mechanism. The technique of laser photolysis...configuration interactions and coupled-cluster theories with single and double excitations, and correction for triple excitations. Specifically, the...differentially pumped chamber containing an electron impact ionization quadrupole mass spectrometer. 4. Results and Discussion To our knowledge
Energy Technology Data Exchange (ETDEWEB)
Sen, Niladri
2011-11-15
Energy flow, dE/d{eta}, has been measured in proton-proton collisions at the lhc, for two centre-of-mass energies, {radical}(s)=0.9 TeV and 7 TeV, using an integrated luminosity of 239 {mu}b{sup -1} and 206 {mu}b{sup -1} respectively. The measurements were made in a previously unexplored phase space (3.15 < vertical stroke {eta} vertical stroke < 4.9) using the CMS detector for two separate event topologies: minimum bias events and events with a hard scale set by the transverse momentum of the jets in a di-jet system. Data from each of the measurements have been compared to leading order Monte Carlo pp-collision event generators that use k{sub T}{sup 2}-, Q{sup 2}- and angular-ordered parton showers. The forward energy ow measurements are shown to be sensitive to the models and tuning parameters in both their shape and magnitude. The necessity of underlying event models in order to describe data will be demonstrated. In addition, predictions from cosmic-ray event generators are shown to describe data consistently well for each of the measurements. (orig.)
Cascading failures in coupled networks: The critical role of node-coupling strength across networks.
Liu, Run-Ran; Li, Ming; Jia, Chun-Xiao
2016-10-17
The robustness of coupled networks against node failure has been of interest in the past several years, while most of the researches have considered a very strong node-coupling method, i.e., once a node fails, its dependency partner in the other network will fail immediately. However, this scenario cannot cover all the dependency situations in real world, and in most cases, some nodes cannot go so far as to fail due to theirs self-sustaining ability in case of the failures of their dependency partners. In this paper, we use the percolation framework to study the robustness of interdependent networks with weak node-coupling strength across networks analytically and numerically, where the node-coupling strength is controlled by an introduced parameter α. If a node fails, each link of its dependency partner will be removed with a probability 1-α. By tuning the fraction of initial preserved nodes p, we find a rich phase diagram in the plane p-α, with a crossover point at which a first-order percolation transition changes to a second-order percolation transition.
Searching for t anti t resonances in the ATLAS experiment at {radical}(s) = 7 TeV
Energy Technology Data Exchange (ETDEWEB)
Gomez Fajardo, Luz Stella [Desy, Zeuthen (Germany)
2012-07-01
New resonances decaying into top quark pairs (t anti t) are predicted by many models beyond the standard model and its pursuit is one of the targets of the ATLAS experiment at the CERN Large Hadron Collider (LHC). For this goal, two final topologies are considered: e+jets and {mu}+jets, resulting from the decay chain in which one of the W bosons from top quark decay decays into an electron or a muon and a neutrino, and the other decays hadronically. This study searches for a resonance in the t anti t mass spectrum where the t anti t pair is reconstructed from identified decay products: jets, leptons and a neutrino. This presentation describes the search for the t anti t resonances in the l+jets final states along with the topology of the highly boosted top candidates where rather than trying to resolve the jets individually, the complete decay products is reconstructed as a single fat jet. For this analysis data collected by the ATLAS experiment in 2011 at {radical}(s)=7 TeV pp collisions are used. A description of the data-driven studies of the background as well as comparisons of the data with the expectations is shown.
Measurement of J/{psi} production in pp collisions at {radical}(s)=7 TeV
Energy Technology Data Exchange (ETDEWEB)
Aaij, R.; Amoraal, J.; Bauer, T.; Beuzekom, M. van; Bos, E.; Carvalho Akiba, K.; Coco, V.; Eijk, D. van; Farinelli, C.; Hulsbergen, W.; Jans, E.; Jansen, F.; Koppenburg, P.; Kozlinskiy, A.; Leerdam, J. van; Merk, M.; Mous, I.; Oggero, S.; Pellegrino, A.; Pree, T. du; Serra, N.; Storaci, B.; Terrier, H.; Tuning, N.; Wiggers, L.; Ybeles Smit, G. [Nikhef National Institute for Subatomic Physics, Amsterdam (Netherlands); Adeva, B.; Cartelle, P.A.; Carson, L.; Cid Vidal, X.; Esperante Pereira, D.; Albor, V.F.; Fungueirino Pazos, J.L.; Gallas Torreira, A.; Morata, J.A.H.; Iglesias Escudero, C.; Pazos Alvarez, A.; Trigo, E.P.; Plo Casasus, M.; Cobo, C.R.; Perez, P.R.; Saborido Silva, J.J.; Seco, M.; Vazquez Regueiro, P.; Visniakov, J. [Universidad de Santiago de Compostela, Santiago de Compostela (Spain); Adinolfi, M.; Brook, N.H.; Coombes, M.; Hampson, T.; Imong, J.; Naik, P.; Rademacker, J.H.; Solomin, A.; Velthuis, J.J.; Voong, D. [University of Bristol, H.H. Wills Physics Laboratory, Bristol (United Kingdom); Adrover, C.; Aslanides, E.; Cogan, J.; Khanji, B.; Le Gac, R.; Leroy, O.; Mancinelli, G.; Maurice, E.; Sapunov, M.; Serrano, J.; Tsaregorodtsev, A. [Aix-Marseille Universite, CNRS/IN2P3, CPPM, Marseille (France); Affolder, A.; Bowcock, T.J.V.; Brown, H.; Casse, G.; Donleavy, S.; Hennessy, K.; Hicks, E.; Huse, T.; Hutchcroft, D.; Liles, M.; Mylroie-Smith, J.; Patel, G.D.; Rinnert, K.; Shears, T. [University of Liverpool, Oliver Lodge Lab., Liverpool (United Kingdom); Ajaltouni, Z.; Deschamps, O.; Henrard, P.; Jahjah Hussein, M.; Lefevre, R.; Gioi, L. Li; Monteil, S.; Niess, V.; Perret, P.; Roa Romero, D.A.; Sobczak, K. [Univ. Blaise Pascal, CNRS/IN2P3, LPC, Clermont Univ., Clermont-Ferrand (France); Albrecht, J.; Barschel, C.; Buytaert, J.; Caicedo Carvajal, J.M.; Cattaneo, M.; Charpentier, P.; Clemencic, M.; Closier, J.; Collins, P.; Corti, G.; D' Ambrosio, C.; Dijkstra, H.; Ferro-Luzzi, M.; Forty, R.; Frank, M.; Frei, C.; Garnier, J.C. [and others
2011-05-15
The production of J/{psi} mesons in proton-proton collisions at {radical}(s)=7 {proportional_to} TeV is studied with the LHCb detector at the LHC. The differential cross-section for prompt J/{psi} production is measured as a function of the J/{psi} transverse momentum p{sub T} and rapidity y in the fiducial region p{sub T} in[0;14]{proportional_to}GeV mskip-2{mu} mskip-1mu c and y element of [2.0;4.5]. The differential cross-section and fraction of J/{psi} from b-hadron decays are also measured in the same p{sub T} and y ranges. The analysis is based on a data sample corresponding to an integrated luminosity of 5.2 pb{sup -1}. The measured cross-sections integrated over the fiducial region are for prompt J/{psi} production and for J/{psi} from b-hadron decays, where the first uncertainty is statistical and the second systematic. The prompt J/{psi} production cross-section is obtained assuming no J/{psi} polarisation and the third error indicates the acceptance uncertainty due to this assumption. (orig.)
Measurement of {psi}(2S) meson production in pp collisions at {radical}(s)=7 TeV
Energy Technology Data Exchange (ETDEWEB)
Aaij, R. [Nikhef National Institute for Subatomic Physics, Amsterdam (Netherlands); Abellan Beteta, C. [Universitat de Barcelona, Barcelona (Spain); Adeva, B. [Universidad de Santiago de Compostela, Santiago de Compostela (Spain)] [and others; Collaboration: LHCb Collaboration
2012-08-15
The differential cross-section for the inclusive production of {psi}(2S) mesons in pp collisions at {radical}(s)=7 TeV has been measured with the LHCb detector. The data sample corresponds to an integrated luminosity of 36 pb{sup -1}. The {psi}(2S) mesons are reconstructed in the decay channels {psi}(2S){yields}{mu}{sup +}{mu}{sup -} and {psi}(2S){yields}J/{psi}{pi}{sup +}{pi}{sup -}, with the J/{psi} meson decaying into two muons. Results are presented both for promptly produced {psi}(2S) mesons and for those originating from b-hadron decays. In the kinematic range p{sub T}({psi}(2S)){<=}16 GeV/c and 2
Erosion of synchronization: Coupling heterogeneity and network structure
Skardal, Per Sebastian; Taylor, Dane; Sun, Jie; Arenas, Alex
2016-06-01
We study the dynamics of network-coupled phase oscillators in the presence of coupling frustration. It was recently demonstrated that in heterogeneous network topologies, the presence of coupling frustration causes perfect phase synchronization to become unattainable even in the limit of infinite coupling strength. Here, we consider the important case of heterogeneous coupling functions and extend previous results by deriving analytical predictions for the total erosion of synchronization. Our analytical results are given in terms of basic quantities related to the network structure and coupling frustration. In addition to fully heterogeneous coupling, where each individual interaction is allowed to be distinct, we also consider partially heterogeneous coupling and homogeneous coupling in which the coupling functions are either unique to each oscillator or identical for all network interactions, respectively. We demonstrate the validity of our theory with numerical simulations of multiple network models, and highlight the interesting effects that various coupling choices and network models have on the total erosion of synchronization. Finally, we consider some special network structures with well-known spectral properties, which allows us to derive further analytical results.
Exponential Synchronization of the Linearly Coupled Dynamical Networks with Delays
Institute of Scientific and Technical Information of China (English)
Xiwei LIU; Tianping CHEN
2007-01-01
In this paper, the authors investigate the synchronization of an array of linearly coupled identical dynamical systems with a delayed coupling. Here the coupling matrix can be asymmetric and reducible. Some criteria ensuring delay-independent and delay-dependent global synchronization are derived respectively. It is shown that if the coupling delay is less than a positive threshold, then the coupled network will be synchronized. On the other hand, with the increase of coupling delay, the synchronization stability of the network will be restrained, even eventually de-synchronized.
Wang, Zhengxin; Duan, Zhisheng; Cao, Jinde
2012-03-01
This paper aims to investigate the synchronization problem of coupled dynamical networks with nonidentical Duffing-type oscillators without or with coupling delays. Different from cluster synchronization of nonidentical dynamical networks in the previous literature, this paper focuses on the problem of complete synchronization, which is more challenging than cluster synchronization. By applying an impulsive controller, some sufficient criteria are obtained for complete synchronization of the coupled dynamical networks of nonidentical oscillators. Furthermore, numerical simulations are given to verify the theoretical results.
Pinning impulsive directed coupled delayed dynamical network and its applications
Lin, Chunnan; Wu, Quanjun; Xiang, Lan; Zhou, Jin
2015-01-01
The main objective of the present paper is to further investigate pinning synchronisation of a complex delayed dynamical network with directionally coupling by a single impulsive controller. By developing the analysis procedure of pinning impulsive stability for undirected coupled dynamical network previously, some simple yet general criteria of pinning impulsive synchronisation for such directed coupled network are derived analytically. It is shown that a single impulsive controller can always pin a given directed coupled network to a desired homogenous solution, including an equilibrium point, a periodic orbit, or a chaotic orbit. Subsequently, the theoretical results are illustrated by a directed small-world complex network which is a cellular neural network (CNN) and a directed scale-free complex network with the well-known Hodgkin-Huxley neuron oscillators. Numerical simulations are finally given to demonstrate the effectiveness of the proposed control methodology.
Similar Others in Same-Sex Couples' Social Networks.
LeBlanc, Allen J; Frost, David M; Alston-Stepnitz, Eli; Bauermeister, Jose; Stephenson, Rob; Woodyatt, Cory R; de Vries, Brian
2015-01-01
Same-sex couples experience unique minority stressors. It is known that strong social networks facilitate access to psychosocial resources that help people reduce and manage stress. However, little is known about the social networks of same-sex couples, in particular their connections to other same-sex couples, which is important to understand given that the presence of similar others in social networks can ameliorate social stress for stigmatized populations. In this brief report, we present data from a diverse sample of 120 same-sex couples in Atlanta and San Francisco. The median number of other same-sex couples known was 12; couples where one partner was non-Hispanic White and the other a person of color knew relatively few other same-sex couples; and there was a high degree of homophily within the social networks of same-sex couples. These data establish a useful starting point for future investigations of couples' social networks, especially couples whose relationships are stigmatized or marginalized in some way. Better understandings of the size, composition, and functions of same-sex couples' social networks are critically needed.
Institute of Scientific and Technical Information of China (English)
Tang Yang; Zhong Hui-Huang; Fang Jian-An
2008-01-01
A general model of linearly stochastically coupled identical connected neural networks with hybrid coupling is proposed,which is composed of constant coupling,coupling discrete time-varying delay and coupling distributed timevarying delay.All the coupling terms are subjected to stochastic disturbances described in terms of Brownian motion,which reflects a more realistic dynamical behaviour of coupled systems in practice.Based on a simple adaptive feedback controller and stochastic stability theory,several sufficient criteria are presented to ensure the synchronization of linearly stochastically coupled complex networks with coupling mixed time-varying delays.Finally,numerical simulatious illustrated by scale-free complex networks verify the effectiveness of the proposed controllers.
Adaptive synchronization in an array of asymmetric coupled neural networks
Institute of Scientific and Technical Information of China (English)
Gao Ming; Cui Bao-Tong
2009-01-01
This paper investigates the global synchronization in an array of linearly coupled neural networks with constant and delayed coupling. By a simple combination of adaptive control and linear feedback with the updated laws, some sufficient conditions are derived for global synchronization of the coupled neural networks. The coupling configuration matrix is assumed to be asymmetric, which is more coincident with the realistic network. It is shown that the approaches developed here extend and improve the earlier works. Finally, numerical simulations are presented to demonstrate the effectiveness of the theoretical results.
Dissipative Topological Defects in Coupled Laser Networks
Pal, Vishwa; Chriki, Ronen; Friesem, Asher A; Davidson, Nir
2016-01-01
Topologically protected defects have been observed and studied in a wide range of fields, such as cosmology, spin systems, cold atoms and optics as they are quenched across a phase transition into an ordered state. Revealing their origin and control is becoming increasingly important field of research, as they limit the coherence of the system and its ability to approach a fully ordered state. Here, we present dissipative topological defects in a 1-D ring network of phase-locked lasers, and show how their formation is related to the Kibble-Zurek mechanism and is governed in a universal manner by two competing time scales of the lasers, namely the phase locking time and synchronization time of their amplitude fluctuations. The ratio between these two time scales depends on the system parameters such as gain and coupling strength, and thus offers the possibility to control the probability of topological defects in the system. Enabling the system to dissipate to the fully ordered, defect-free state can be exploi...
New Magnetically Coupled Impedance (Z-) Source Networks
DEFF Research Database (Denmark)
Siwakoti, Yam Prasad; Blaabjerg, Frede; Loh, Poh Chiang
2016-01-01
by their discontinuous currents drawn from the sources and/or high stresses experienced by their components. This paper thus proposes three new MCIS networks named respectively as quasi-Y-source, quasi-Γ-Z-source and quasi-T-source or quasi-Trans-Z-source networks. These new networks inherit all advantages....... Derivations of all two-winding MCIS networks, including existing and new networks, from the generalized three-winding MCIS networks are then systematically illustrated, before comparing them. Operational principles, mathematical derivations, simulation and experimental results of all studied networks have...
Coupling Strength and System Size Induce Firing Activity of Globally Coupled Neural Network
Institute of Scientific and Technical Information of China (English)
WEI Du-Qu; LUO Xiao-Shu; ZOU Yan-Li
2008-01-01
We investigate how firing activity of globally coupled neural network depends on the coupling strength C and system size N.Network elements are described by space-clamped FitzHugh-Nagumo (SCFHN) neurons with the values of parameters at which no firing activity occurs.It is found that for a given appropriate coupling strength,there is an intermediate range of system size where the firing activity of globally coupled SCFHN neural network is induced and enhanced.On the other hand,for a given intermediate system size level,there ex/sts an optimal value of coupling strength such that the intensity of firing activity reaches its maximum.These phenomena imply that the coupling strength and system size play a vital role in firing activity of neural network.
Chaos synchronization of two stochastically coupled random Boolean networks
Energy Technology Data Exchange (ETDEWEB)
Hung, Y.-C. [Department of Physics, National Sun Yat-sen University, Kaohsiung, Taiwan (China) and Nonlinear Science Group, Department of Physics, National Kaohsiung Normal University, Kaohsiung, Taiwan (China)]. E-mail: d9123801@student.nsysu.edu.tw; Ho, M.-C. [Nonlinear Science Group, Department of Physics, National Kaohsiung Normal University, Kaohsiung, Taiwan (China)]. E-mail: t1603@nknucc.nknu.edu.tw; Lih, J.-S. [Department of Physics and Geoscience, National Pingtung University of Education, Pingtung, Taiwan (China); Nonlinear Science Group, Department of Physics, National Kaohsiung Normal University, Kaohsiung, Taiwan (China); Jiang, I-M. [Department of Physics, National Sun Yat-sen University, Kaohsiung, Taiwan (China); Nonlinear Science Group, Department of Physics, National Kaohsiung Normal University, Kaohsiung, Taiwan (China)
2006-07-24
In this Letter, we study the chaos synchronization of two stochastically coupled random Boolean networks (RBNs). Instead of using the 'site-by-site and all-to-all' coupling, the coupling mechanism we consider here is that: the nth cell in a network is linked by an arbitrarily chosen cell in the other network with probability {rho}, and it possesses no links with probability 1-{rho}. The mechanism is useful to investigate the coevolution of biological species via horizontal genetic exchange. We show that the density evolution of networks can be described by two deterministic coupled polynomial maps. The complete synchronization occurs when the coupling parameter exceeds a critical value. Moreover, the reverse bifurcations in inhomogeneous condition are observed and under our discussion.
Coupling entropy of co-processing model on social networks
Zhang, Zhanli
2015-08-01
Coupling entropy of co-processing model on social networks is investigated in this paper. As one crucial factor to determine the processing ability of nodes, the information flow with potential time lag is modeled by co-processing diffusion which couples the continuous time processing and the discrete diffusing dynamics. Exact results on master equation and stationary state are achieved to disclose the formation. In order to understand the evolution of the co-processing and design the optimal routing strategy according to the maximal entropic diffusion on networks, we propose the coupling entropy comprehending the structural characteristics and information propagation on social network. Based on the analysis of the co-processing model, we analyze the coupling impact of the structural factor and information propagating factor on the coupling entropy, where the analytical results fit well with the numerical ones on scale-free social networks.
Quantifying the dynamics of coupled networks of switches and oscillators.
Directory of Open Access Journals (Sweden)
Matthew R Francis
Full Text Available Complex network dynamics have been analyzed with models of systems of coupled switches or systems of coupled oscillators. However, many complex systems are composed of components with diverse dynamics whose interactions drive the system's evolution. We, therefore, introduce a new modeling framework that describes the dynamics of networks composed of both oscillators and switches. Both oscillator synchronization and switch stability are preserved in these heterogeneous, coupled networks. Furthermore, this model recapitulates the qualitative dynamics for the yeast cell cycle consistent with the hypothesized dynamics resulting from decomposition of the regulatory network into dynamic motifs. Introducing feedback into the cell-cycle network induces qualitative dynamics analogous to limitless replicative potential that is a hallmark of cancer. As a result, the proposed model of switch and oscillator coupling provides the ability to incorporate mechanisms that underlie the synchronized stimulus response ubiquitous in biochemical systems.
Adaptive synchronization of two nonlinearly coupled complex dynamical networks with delayed coupling
Zheng, Song; Wang, Shuguo; Dong, Gaogao; Bi, Qinsheng
2012-01-01
This paper investigates the adaptive synchronization between two nonlinearly delay-coupled complex networks with the bidirectional actions and nonidentical topological structures. Based on LaSalle's invariance principle, some criteria for the synchronization between two coupled complex networks are achieved via adaptive control. To validate the proposed methods, the unified chaotic system as the nodes of the networks are analyzed in detail, and numerical simulations are given to illustrate the theoretical results.
Anti-synchronization Between Coupled Networks with Two Active Forms*
Institute of Scientific and Technical Information of China (English)
WU Yong-Qing; SUN Wei-Gang; LI Shan-Shan
2011-01-01
This paper studies anti-synchronization and its control between two coupled networks with nonlinear signal's connection and the inter-network actions. If anti-synchronization does not exist between two such networks, adaptive controllers are designed to anti-synchronize them. Different node dynamics and nonidentical topological structures are considered and useful criteria for anti-synchronization between two networks are given. Numerical examples are presented to show the efficiency of our derived results.
Contagion processes on the static and activity driven coupling networks
Lei, Yanjun; Guo, Quantong; Ma, Yifang; Li, Meng; Zheng, Zhiming
2015-01-01
The evolution of network structure and the spreading of epidemic are common coexistent dynamical processes. In most cases, network structure is treated either static or time-varying, supposing the whole network is observed in a same time window. In this paper, we consider the epidemic spreading on a network consisting of both static and time-varying structures. At meanwhile, the time-varying part and the epidemic spreading are supposed to be of the same time scale. We introduce a static and activity driven coupling (SADC) network model to characterize the coupling between static (strong) structure and dynamic (weak) structure. Epidemic thresholds of SIS and SIR model are studied on SADC both analytically and numerically with various coupling strategies, where the strong structure is of homogeneous or heterogeneous degree distribution. Theoretical thresholds obtained from SADC model can both recover and generalize the classical results in static and time-varying networks. It is demonstrated that weak structure...
Color coherent radiation in multijet events from p{bar p} collisions at {radical}s = 1.8 TeV
Energy Technology Data Exchange (ETDEWEB)
Abachi, S.; Ahn, S.; Baldin, B. [and others
1995-08-01
We report on a study of color coherence effects in p{bar p} collisions based on data collected by the D0 detector during the 1992-1993 run of the Fermilab Tevatron collider at the center of mass energy {radical}s = 1.8 TeV. We demonstrate initial-to-final state color interference effects by measuring spatial correlations between soft and hard jets in multijet events. The data are compared to Monte Carlo simulations with different color coherence implementations and to the predictions of a NLO parton level calculation.
A study of b anti b production in e{sup +}e{sup -} collisions at {radical}(s)=130 -207 GeV
Energy Technology Data Exchange (ETDEWEB)
Abdallah, J.; Antilogus, P.; Augustin, J.E.; Baubillier, M.; Berggren, M.; Da Silva, W.; Kapusta, F.; Savoy-Navarro, A. [Univ. Paris VI et VII, LPNHE, IN2P3-CNRS, Paris Cedex 05 (France); Abreu, P.; Andringa, S.; Anjos, N.; Castro, N.; Espirito Santo, M.C.; Goncalves, P.; Moreno, S.; Onofre, A.; Peralta, L.; Pimenta, M.; Tome, B.; Veloso, F. [LIP, IST, FCUL, Lisboa Codex (Portugal); Adam, W.; Buschbeck, B.; Leder, G.; Liko, D.; MacNaughton, J.; Mandl, F.; Mitaroff, W.; Strauss, J. [Oesterr. Akad. d. Wissensch., Institut fuer Hochenergiephysik, Vienna (Austria); Adzic, P.; Fanourakis, G.; Kokkinias, P.; Loukas, D.; Markou, A.; Mastroyiannopoulos, N.; Nassiakou, M.; Tzamarias, S.; Zupan, M. [N.C.S.R. Demokritos, Institute of Nuclear Physics, P.O. Box 60228, Athens (Greece); Albrecht, T.; Allmendinger, T.; Apel, W.D.; Boer, W. de; Feindt, M.; Haag, C.; Hauler, F.; Hennecke, M.; Jungermann, L.; Kerzel, U.; Moch, M.; Rehn, J.; Sander, C.; Stanitzki, M.; Weiser, C. [Universitaet Karlsruhe, Institut fuer Experimentelle Kernphysik, Postfach 6980, Karlsruhe (Germany); Alemany-Fernandez, R.; Ask, S.; Augustinus, A.; Baillon, P.; Battaglia, M.; Camporesi, T.; Carena, F.; Charpentier, P.; Chierici, R.; Chudoba, J.; Chung, S.U.; Collins, P.; Elsing, M.; Foeth, H.; Gavillet, P.; Holt, P.J.; Joram, C.; Kjaer, N.J.; Marin, J.C.; Mariotti, C.; Pape, L.; Parzefall, U.; Piotto, E.; Poireau, V.; Rebecchi, P.; Schwickerath, U.; Spassov, T.; Treille, D.; Van Eldik, J.; Van Vulpen, I.; Wicke, D. [CERN, Geneva 23 (Switzerland); Allport, P.P.; Booth, P.S.L.; Bowcock, T.J.V.; Houlden, M.A.; Jackson, J.N.; King, B.T.; Mc Nulty, R.; Palacios, J.P.; Tobin, M.; Washbrook, A.J. [University of Liverpool, Department of Physics, P.O. Box 147, Liverpool (United Kingdom); Amaldi, U.; Bonesini, M.; Calvi, M.; Matteuzzi, C.; Paganoni, M.; Pullia, A.; Tabarelli, T.; Tonazzo, A. [Univ. di Milano-Bicocca (Italy); INFN-MILANO, Dipartimento di Fisica, Milan (Italy)] [and others
2009-03-15
Measurements are presented of R{sub b}, the ratio of the b anti b cross-section to the q anti q cross-section in e{sup +}e{sup -} collisions, and the forward-backward asymmetry A{sub FB}{sup b} at twelve energy points in the range {radical}(s)=130-07 GeV. These results are found to be consistent with the Standard Model expectations. The measurements are used to set limits on new physics scenarios involving contact interactions. (orig.) 2.
Coupled actin-lamin biopolymer networks and protecting DNA
Zhang, Tao; Rocklin, D. Zeb; Mao, Xiaoming; Schwarz, J. M.
The mechanical properties of cells are largely determined by networks of semiflexible biopolymers forming the cytoskeleton. Similarly, the mechanical properties of cell nuclei are also largely determined by networks of semiflexible biopolymers forming the nuclear cytoskeleton. In particular, a network of filamentous lamin sits just inside the inner nuclear membrane to presumably protect the heart of the cell nucleus--the DNA. It has been demonstrated over the past decade that the actin cytoskeletal biopolymer network and the lamin biopolymer network are coupled via a sequence of proteins bridging the outer and inner nuclear membranes, known as the LINC complex. We, therefore, probe the consequences of such a coupling in a model biopolymer network system via numerical simulations to understand the resulting deformations in the lamin network in response to perturbations in the actin cytoskeletal network. We find, for example, that the force transmission across the coupled system can depend sensitively on the concentration of LINC complexes. Such study could have implications for mechanical mechanisms of the regulation of transcription since DNA couples to lamin via lamin-binding domains so that deformations in the lamin network may result in deformations in the DNA.
Control of coupled oscillator networks with application to microgrid technologies.
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.
Workshop: Theory an Applications of Coupled Cell Networks
2006-03-22
Economia and Centro de Matematica, Universidade do Porto) Application of coupled cell systems have been made to a wide range of problems in the physical and...the propagation of perturbations across the optical spectrum. Minimal coupled cell networks M. Aguiar (Faculdade de Economia do Porto), A.P.S. Dias
Stimulus-dependent synchronization in delayed-coupled neuronal networks.
Esfahani, Zahra G; Gollo, Leonardo L; Valizadeh, Alireza
2016-03-22
Time delay is a general feature of all interactions. Although the effects of delayed interaction are often neglected when the intrinsic dynamics is much slower than the coupling delay, they can be crucial otherwise. We show that delayed coupled neuronal networks support transitions between synchronous and asynchronous states when the level of input to the network changes. The level of input determines the oscillation period of neurons and hence whether time-delayed connections are synchronizing or desynchronizing. We find that synchronizing connections lead to synchronous dynamics, whereas desynchronizing connections lead to out-of-phase oscillations in network motifs and to frustrated states with asynchronous dynamics in large networks. Since the impact of a neuronal network to downstream neurons increases when spikes are synchronous, networks with delayed connections can serve as gatekeeper layers mediating the firing transfer to other regions. This mechanism can regulate the opening and closing of communicating channels between cortical layers on demand.
Mean Square Synchronization of Stochastic Nonlinear Delayed Coupled Complex Networks
Directory of Open Access Journals (Sweden)
Chengrong Xie
2013-01-01
Full Text Available We investigate the problem of adaptive mean square synchronization for nonlinear delayed coupled complex networks with stochastic perturbation. Based on the LaSalle invariance principle and the properties of the Weiner process, the controller and adaptive laws are designed to ensure achieving stochastic synchronization and topology identification of complex networks. Sufficient conditions are given to ensure the complex networks to be mean square synchronization. Furthermore, numerical simulations are also given to demonstrate the effectiveness of the proposed scheme.
Cascades with coupled map lattices in preferential attachment community networks
Institute of Scientific and Technical Information of China (English)
Cui Di; Gao Zi-You; Zhao Xiao-Mei
2008-01-01
In this paper,cascading failure is studied by coupled map lattice (CML) methods in preferential attachment community networks.It is found that external perturbation R is increasing with modularity Q growing by simulation.In particular,the large modularity Q can hold off the cascading failure dynamic process in community networks.Furthermore,different attack strategies also greatly affect the cascading failure dynamic process. It is particularly significant to control cascading failure process in real community networks.
Measurement of prompt hadron production ratios in pp collisions at {radical}(s) = 0.9 and 7 TeV
Energy Technology Data Exchange (ETDEWEB)
Aaij, R. [Nikhef National Institute for Subatomic Physics, Amsterdam (Netherlands); Abellan Beteta, C. [Universitat de Barcelona, Barcelona (Spain); Adametz, A. [Ruprecht-Karls-Universitaet Heidelberg, Physikalisches Institut, Heidelberg (Germany)] [and others; Collaboration: The LHCb Collaboration
2012-10-15
The charged-particle production ratios anti p/p, K{sup -}/K {sup +}, {pi}{sup -}/{pi} {sup +}, (p+ anti p)/({pi}{sup +} + {pi}{sup -}), (K {sup +}+K {sup -})/({pi} {sup +}+{pi} {sup -}) and (p + anti p)/(K{sup +} + K{sup -}) are measured with the LHCb detector using 0.3 nb{sup -1} of pp collisions delivered by the LHC at {radical}(s) = 0.9 TeV and 1.8 nb{sup -1} at {radical}(s) = 7 TeV. The measurements are performed as a function of transverse momentum p{sub T} and pseudorapidity {eta}. The production ratios are compared to the predictions of several Monte Carlo generator settings, none of which are able to describe adequately all observables. The ratio anti p/p is also considered as a function of rapidity loss, {Delta}y{identical_to}y{sub beam}-y, and is used to constrain models of baryon transport. (orig.)
Synchronization in an array of coupled Boolean networks
Energy Technology Data Exchange (ETDEWEB)
Li, Rui, E-mail: rui.li@pku.edu.cn [State Key Laboratory for Turbulence and Complex Systems, College of Engineering, Peking University, Beijing 100871 (China); Chu, Tianguang, E-mail: chutg@pku.edu.cn [State Key Laboratory for Turbulence and Complex Systems, College of Engineering, Peking University, Beijing 100871 (China)
2012-10-01
This Letter presents an analytical study of synchronization in an array of coupled deterministic Boolean networks. A necessary and sufficient criterion for synchronization is established based on algebraic representations of logical dynamics in terms of the semi-tensor product of matrices. Some basic properties of a synchronized array of Boolean networks are then derived for the existence of transient states and the upper bound of the number of fixed points. Particularly, an interesting consequence indicates that a “large” mismatch between two coupled Boolean networks in the array may result in loss of synchrony in the entire system. Examples, including the Boolean model of coupled oscillations in the cell cycle, are given to illustrate the present results. -- Highlights: ► We analytically study synchronization in an array of coupled Boolean networks. ► The study is based on the algebraic representations of logical dynamics. ► A necessary and sufficient algebraic criterion for synchronization is established. ► It reveals some basic properties of a synchronized array of Boolean networks. ► A large mismatch between two coupled networks may result in the loss of synchrony.
Delay-induced driven patterns in coupled Cayley tree networks
Singh, Aradhana
2013-01-01
We study effects of delay in diffusively coupled logistic maps on the Cayley tree networks. We find that smaller coupling values exhibits sensitiveness for value of delay, and leads to different cluster patterns of self-organized and driven types. Whereas larger coupling strengths are very robust against change in delay values, and leads to stable driven clusters comprising only nodes from last generation of the Calaye tree. Furthermore, introduction of delay exhibits suppression as well as enhancement of synchronization depending upon coupling strength values, hence demonstrating richness of the model. To the end we relate the results with social conflicts and cooperation observed in families.
Synchronization in output-coupled temporal Boolean networks
Lu, Jianquan; Zhong, Jie; Tang, Yang; Huang, Tingwen; Cao, Jinde; Kurths, Jürgen
2014-09-01
This paper presents an analytical study of synchronization in an array of output-coupled temporal Boolean networks. A temporal Boolean network (TBN) is a logical dynamic system developed to model Boolean networks with regulatory delays. Both state delay and output delay are considered, and these two delays are assumed to be different. By referring to the algebraic representations of logical dynamics and using the semi-tensor product of matrices, the output-coupled TBNs are firstly converted into a discrete-time algebraic evolution system, and then the relationship between the states of coupled TBNs and the initial state sequence is obtained. Then, some necessary and sufficient conditions are derived for the synchronization of an array of TBNs with an arbitrary given initial state sequence. Two numerical examples including one epigenetic model are finally given to illustrate the obtained results.
Ocean-atmosphere coupling from a climate network perspective
Wiedermann, Marc; Donges, Jonathan F.; Donner, Reik V.; Kurths, Jürgen
2014-05-01
In recent years extensive studies on the climate system have been carried out making use of advanced complex network statistics. However, most previous studies have been characterized by two conceptual restrictions: First, in most cases network measures have been computed without taking into account the topology of the discrete grid, regular or irregular, that climate data is typically stored on. To overcome this problem, the concept of node splitting invariant network measures has been introduced considering individual node weights, for example according to the surface area a node represents, when computing network measures [1]. Second, the great majority of recent studies have been focussing on single climatological fields located on surfaces parallel to or directly on the Earth's surface. A recent work introduced a methodology for quantifying interaction structures between geopotential height fields at different isobaric surfaces by proposing general definitions for network measures dealing with a network of networks composed from distinct subnetworks [2]. In this work, we combine both, the node-weighting scheme as well as the interacting network measure approach. For this purpose, we invent new node-weighted cross-network measures that provide a general tool for quantifying interaction structures in multilayer networks that is applicable to many fields beyond the study of the climate system, such as communication, social or trade networks. Our new approach is utilized for studying ocean-atmosphere coupling in the northern hemisphere. Specifically, we construct 18 coupled climate networks based on monthly data from the ERA 40 reanalysis, each consisting of two subnetworks. In all cases, one subnetwork represents sea-surface temperature (SST) anomalies while the other is based on the geopotential height (HGT) of isobaric surfaces at different pressure levels. By investigating the connectivity of the resulting interdependent network structures, we identify a
Synchronization Stability in Weighted Complex Networks with Coupling Delays
Institute of Scientific and Technical Information of China (English)
WANG Qing-Yun; DUAN Zhi-Sheng; CHEN Guan-Rong; LU Qi-Shao
2009-01-01
Realistic networks display not only a complex topological structure, but also a heterogeneous distribution of weights in connection strengths.In addition, the information spreading through a complex network is often associated with time delays due to the finite speed of signal transmission over a distance.Hence, the weighted complex network with coupling delays have meaningful implications in real world, and resultantly ga/ns increasing attention in various fields of science and engineering.Based on the theory of asymptotic stability of linear time-delay systems, synchronization stability of the weighted complex dynamical network with coupling delays is investigated, and simple criteria are obtained for both delay-independent and delay-dependent stabilities of synchronization states.The obtained criteria in this paper encompass the established results in the literature as special cases.Some examples are given to illustrate the theoretical results.
Local dynamics of gap-junction-coupled interneuron networks
Lau, Troy; Gage, Gregory J.; Berke, Joshua D.; Zochowski, Michal
2010-03-01
Interneurons coupled by both electrical gap-junctions (GJs) and chemical GABAergic synapses are major components of forebrain networks. However, their contributions to the generation of specific activity patterns, and their overall contributions to network function, remain poorly understood. Here we demonstrate, using computational methods, that the topological properties of interneuron networks can elicit a wide range of activity dynamics, and either prevent or permit local pattern formation. We systematically varied the topology of GJ and inhibitory chemical synapses within simulated networks, by changing connection types from local to random, and changing the total number of connections. As previously observed we found that randomly coupled GJs lead to globally synchronous activity. In contrast, we found that local GJ connectivity may govern the formation of highly spatially heterogeneous activity states. These states are inherently temporally unstable when the input is uniformly random, but can rapidly stabilize when the network detects correlations or asymmetries in the inputs. We show a correspondence between this feature of network activity and experimental observations of transient stabilization of striatal fast-spiking interneurons (FSIs), in electrophysiological recordings from rats performing a simple decision-making task. We suggest that local GJ coupling enables an active search-and-select function of striatal FSIs, which contributes to the overall role of cortical-basal ganglia circuits in decision-making.
Self-Organization in Coupled Map Scale-Free Networks
Institute of Scientific and Technical Information of China (English)
LIANG Xiao-Ming; L(U) Hua-ping; LIU Zong-Hua
2008-01-01
We study the self-organization of phase synchronization in coupled map scale-free networks with chaotic logistic map at each node and find that a variety of ordered spatiotemporal patterns emerge spontaneously in a regime of coupling strength.These ordered behaviours will change with the increase of the average links and are robust to both the system size and parameter mismatch.A heuristic theory is given to explain the mechanism of serf-organization and to figure out the regime of coupling for the ordered spatiotemporal patterns.
The Fragility of Interdependency: Coupled Networks Switching Phenomena
Stanley, H. Eugene
2013-03-01
Recent disasters ranging from abrupt financial ``flash crashes'' and large-scale power outages to sudden death among the elderly dramatically exemplify the fact that the most dangerous vulnerability is hiding in the many interdependencies among different networks. In the past year, we have quantified failures in model of interconnected networks, and demonstrated the need to consider mutually dependent network properties in designing resilient systems. Specifically, we have uncovered new laws governing the nature of switching phenomena in coupled networks, and found that phenomena that are continuous ``second order'' phase transitions in isolated networks become discontinuous abrupt ``first order'' transitions in interdependent networks [S. V. Buldyrev, R. Parshani, G. Paul, H. E. Stanley, and S. Havlin, ``Catastrophic Cascade of Failures in Interdependent Networks,'' Nature 464, 1025 (2010); J. Gao, S. V. Buldyrev, H. E. Stanley, and S. Havlin, ``Novel Behavior of Networks Formed from Interdependent Networks,'' Nature Physics 8, 40 (2012). We conclude by discussing the network basis for understanding sudden death in the elderly, and the possibility that financial ``flash crashes'' are not unlike the catastrophic first-order failure incidents occurring in coupled networks. Specifically, we study the coupled networks that are responsible for financial fluctuations. It appears that ``trend switching phenomena'' that we uncover are remarkably independent of the scale over which they are analyzed. For example, we find that the same laws governing the formation and bursting of the largest financial bubbles also govern the tiniest finance bubbles, over a factor of 1,000,000,000 in time scale [T. Preis, J. Schneider, and H. E. Stanley, ``Switching Processes in Financial Markets,'' Proc. Natl. Acad. Sci. USA 108, 7674 (2011); T. Preis and H. E. Stanley, ``Bubble Trouble: Can a Law Describe Bubbles and Crashes in Financial Markets?'' Physics World 24, No. 5, 29 (May 2011
Controllable coupling of distributed qubits within a microtoroidal cavity network
Hu, C.; Xia, Y.; Song, J.
2012-05-01
We propose a scheme to control the coupling between two arbitrary atoms scattered within a quantum network composed of microtoroidal cavities linked by a ring-fibre. The atom-atom effective couplings are induced by pairing of off-resonant Raman transitions. The couplings can be arbitrarily controlled by adjusting classical fields. Compared with the previous scheme [S.B. Zheng, C.P. Yang, F. Nori, Phys. Rev. A 82, 042327 (2010)], the present scheme uses microtoroidal cavities with higher coupling efficiency than Fabry-Perot cavities. Furthermore, the scheme is not only suitable for the short-fibre limit, but also for multiple fibre modes. The added fibre modes can play a positive role, especially when the coupling rate between cavity-mode and fibre-mode is not large. In addition, a wider frequency domain of fibre modes can be used in this scheme.
Cascades on a stochastic pulse-coupled network.
Wray, C M; Bishop, S R
2014-09-12
While much recent research has focused on understanding isolated cascades of networks, less attention has been given to dynamical processes on networks exhibiting repeated cascades of opposing influence. An example of this is the dynamic behaviour of financial markets where cascades of buying and selling can occur, even over short timescales. To model these phenomena, a stochastic pulse-coupled oscillator network with upper and lower thresholds is described and analysed. Numerical confirmation of asynchronous and synchronous regimes of the system is presented, along with analytical identification of the fixed point state vector of the asynchronous mean field system. A lower bound for the finite system mean field critical value of network coupling probability is found that separates the asynchronous and synchronous regimes. For the low-dimensional mean field system, a closed-form equation is found for cascade size, in terms of the network coupling probability. Finally, a description of how this model can be applied to interacting agents in a financial market is provided.
Synchronization of networks with time-varying couplings
Institute of Scientific and Technical Information of China (English)
LU Wen-lian; CHEN Tian-ping
2013-01-01
In this paper, we present a review of our recent works on complete synchro-nization analyses of networks of the coupled dynamical systems with time-varying cou-plings. The main approach is composed of algebraic graph theory and dynamic system method. More precisely, the Hajnal diameter of matrix sequence plays a key role in in-vestigating synchronization dynamics and the joint graph across time periods possessing spanning tree is a doorsill for time-varying topologies to reach synchronization. These techniques with proper modification count for diverse models of networks of the cou-pled systems, including discrete-time and continuous-time models, linear and nonlinear models, deterministic and stochastic time-variations. Alternatively, transverse stability analysis of general time-varying dynamic systems can be employed for synchronization study as a special case and proved to be equivalent to Hajnal diameter.
Modelling small-patterned neuronal networks coupled to microelectrode arrays
Massobrio, Paolo; Martinoia, Sergio
2008-09-01
Cultured neurons coupled to planar substrates which exhibit 'well-defined' two-dimensional network architectures can provide valuable insights into cell-to-cell communication, network dynamics versus topology, and basic mechanisms of synaptic plasticity and learning. In the literature several approaches were presented to drive neuronal growth, such as surface modification by silane chemistry, photolithographic techniques, microcontact printing, microfluidic channel flow patterning, microdrop patterning, etc. This work presents a computational model fit for reproducing and explaining the dynamics exhibited by small-patterned neuronal networks coupled to microelectrode arrays (MEAs). The model is based on the concept of meta-neuron, i.e., a small spatially confined number of actual neurons which perform single macroscopic functions. Each meta-neuron is characterized by a detailed morphology, and the membrane channels are modelled by simple Hodgkin-Huxley and passive kinetics. The two main findings that emerge from the simulations can be summarized as follows: (i) the increasing complexity of meta-neuron morphology reflects the variations of the network dynamics as a function of network development; (ii) the dynamics displayed by the patterned neuronal networks considered can be explained by hypothesizing the presence of several short- and a few long-term distance interactions among small assemblies of neurons (i.e., meta-neurons).
Data mechanics and coupling geometry on binary bipartite networks.
Directory of Open Access Journals (Sweden)
Hsieh Fushing
Full Text Available We quantify the notion of pattern and formalize the process of pattern discovery under the framework of binary bipartite networks. Patterns of particular focus are interrelated global interactions between clusters on its row and column axes. A binary bipartite network is built into a thermodynamic system embracing all up-and-down spin configurations defined by product-permutations on rows and columns. This system is equipped with its ferromagnetic energy ground state under Ising model potential. Such a ground state, also called a macrostate, is postulated to congregate all patterns of interest embedded within the network data in a multiscale fashion. A new computing paradigm for indirect searching for such a macrostate, called Data Mechanics, is devised by iteratively building a surrogate geometric system with a pair of nearly optimal marginal ultrametrics on row and column spaces. The coupling measure minimizing the Gromov-Wasserstein distance of these two marginal geometries is also seen to be in the vicinity of the macrostate. This resultant coupling geometry reveals multiscale block pattern information that characterizes multiple layers of interacting relationships between clusters on row and on column axes. It is the nonparametric information content of a binary bipartite network. This coupling geometry is then demonstrated to shed new light and bring resolution to interaction issues in community ecology and in gene-content-based phylogenetics. Its implied global inferences are expected to have high potential in many scientific areas.
Biased imitation in coupled evolutionary games in interdependent networks
Santos, M D; Mendes, J F F
2014-01-01
We explore the evolutionary dynamics of two games - the Prisoner's Dilemma and the Snowdrift Game - played within distinct networks (layers) of interdependent networks. In these networks imitation and interaction between individuals of opposite layers is established through interlinks. We explore an update rule in which revision of strategies is a biased imitation process: individuals imitate neighbors from the same layer with probability p, and neighbors from the second layer with complementary probability 1 - p. We demonstrate that a small decrease of p from p = 1 (which corresponds to forbidding strategy transfer between layers) is sufficient to promote cooperation in the Prisoner's Dilemma subpopulation. This, on the other hand, is detrimental for cooperation in the Snowdrift Game subpopulation. We provide results of extensive computer simulations for the case in which layers are modelled as regular random networks, and support this study with analytical results for coupled well-mixed populations.
Mapping QoS Classes in Loose Coupling Heterogeneous Networks
Directory of Open Access Journals (Sweden)
Firas Ousta
2014-10-01
Full Text Available One of the main objectives of Heterogeneous Wireless Access Networks (HWAN is to integrate the different wireless access technologies, such as Universal Mobile Telecommunication System (UMTS, Worldwide Interoperability for Microwave Access (WiMAX and Wireless Local Area Network (WLAN, with a common IP-based network in order to offer mobile users continuous and unified service in a transparent way. However, one of the major issues is to support end-to-end Quality of Service (QoS across all these technologies at all stages of the service from set-up to handoff. We present, in this study, a novel method of mapping QoS of UMTS and WiMAX over a loose coupling environment across Internet Protocol/Differentiated Service (IP/DiffServ network.
Coupling chemical networks to hydrogels controls oscillatory behavior
Reeves, Daniel; Pérez-Mercader, Juan
2015-01-01
In this letter, we demonstrate that oscillations and excitable behavior can be imparted to a chemical network by coupling the network to an active hydrogel. We discuss two mechanisms by which the mechanical response of the gel to the embedded chemical reactant provides feedback into the chemistry. These feedback mechanisms can be applied to control existing chemical oscillations as well as create new oscillations under some conditions. We analyze two model systems to demonstrate these two effects, respectively: a theoretical system that exhibits no excitability in the absence of a gel, and the Oregonator model of the Belousov-Zhabotinsky reaction in which the metal catalyst is intercalated into the polymer network. This work can aid in designing new materials that harness these feedbacks to create, control, and stabilize oscillatory and excitable chemical behavior in both oscillatory and non-oscillatory chemical networks.
Biased imitation in coupled evolutionary games in interdependent networks
Santos, M. D.; Dorogovtsev, S. N.; Mendes, J. F. F.
2014-03-01
We explore the evolutionary dynamics of two games--the Prisoner's Dilemma and the Snowdrift Game--played within distinct networks (layers) of interdependent networks. In these networks imitation and interaction between individuals of opposite layers is established through interlinks. We explore an update rule in which revision of strategies is a biased imitation process: individuals imitate neighbors from the same layer with probability p, and neighbors from the second layer with complementary probability 1 - p. We demonstrate that a small decrease of p from p = 1 (which corresponds to forbidding strategy transfer between layers) is sufficient to promote cooperation in the Prisoner's Dilemma subpopulation. This, on the other hand, is detrimental for cooperation in the Snowdrift Game subpopulation. We provide results of extensive computer simulations for the case in which layers are modelled as regular random networks, and support this study with analytical results for coupled well-mixed populations.
Coupled Oscillations and Circadian Rhythms in Molecular Replication Networks.
Wagner, Nathaniel; Alasibi, Samaa; Peacock-Lopez, Enrique; Ashkenasy, Gonen
2015-01-02
Living organisms often display rhythmic and oscillatory behavior. We investigate here a challenge in contemporary Systems Chemistry, that is, to construct "bottom-up" molecular networks that display such complex behavior. We first describe oscillations during self-replication by applying kinetic parameters relevant to peptide replication in an open environment. Small networks of coupled oscillators are then constructed in silico, producing various functions such as logic gates, integrators, counters, triggers, and detectors. These networks are finally utilized to simulate the connectivity and network topology of the Kai proteins circadian clocks from the S. elongatus cyanobacteria, thus producing rhythms whose constant frequency is independent of the input intake rate and robust toward concentration fluctuations. We suggest that this study helps further reveal the underlying principles of biological clocks and may provide clues into their emergence in early molecular evolution.
Abnormal cross-frequency coupling in the tinnitus network.
Directory of Open Access Journals (Sweden)
Ilya eAdamchic
2014-09-01
Full Text Available Neuroimaging studies have identified networks of brain areas and oscillations associated with tinnitus perception. However, how these regions relate to perceptual characteristics of tinnitus, and how oscillations in various frequency bands are associated with communications within the tinnitus network is still incompletely understood. Recent evidence suggests that apart from changes of the tinnitus severity the changes of tinnitus dominant pitch also have modulating effect on the neuronal activity in a number of brain areas within the tinnitus network. Therefore, in a re-analysis of an existing dataset, we sought to determine how the oscillations in the tinnitus network in the various frequency bands interact. We also investigate how changes of tinnitus loudness, annoyance and pitch affect cross-frequency interaction both within and between nodes of the tinnitus network. Results of this study provide evidence that in tinnitus patients, aside from the previously described changes of oscillatory activity, there are also changes of cross-frequency coupling (CFC; phase-amplitude CFC was increased in tinnitus patients within the auditory cortex and the dorsolateral prefrontal regions between the phase of delta-theta and the amplitude of gamma oscillations (Modulation Index [MI] 0.17 in tinnitus patients vs. 0.08 in tinnitus free controls. Moreover, theta phase in the anterior cingulate region modulated gamma in the auditory (MI 0.1 and dorsolateral prefrontal regions (MI 0.19. Reduction of tinnitus severity after acoustic coordinated reset therapy led to a partial normalization of abnormal CFC. Also treatment induced changes in tinnitus pitch significantly modulated changes in CFC. Thus, tinnitus perception is associated with a more pronounced CFC within and between nodes of the tinnitus network. Cross-frequency coupling can coordinate tinnitus-relevant activity in the tinnitus network providing a mechanism for effective communication between nodes
Correlated loss of ecosystem services in coupled mutualistic networks.
Albrecht, Jörg; Berens, Dana Gertrud; Jaroszewicz, Bogdan; Selva, Nuria; Brandl, Roland; Farwig, Nina
2014-05-08
Networks of species interactions promote biodiversity and provide important ecosystem services. These networks have traditionally been studied in isolation, but species are commonly involved in multiple, diverse types of interaction. Therefore, whether different types of species interaction networks coupled through shared species show idiosyncratic or correlated responses to habitat degradation is unresolved. Here we study the collective response of coupled mutualistic networks of plants and their pollinators and seed dispersers to the degradation of Europe's last relict of old-growth lowland forest (Białowieża, Poland). We show that logging of old-growth forests has correlated effects on the number of partners and interactions of plants in both mutualisms, and that these effects are mediated by shifts in plant densities on logged sites. These results suggest bottom-up-controlled effects of habitat degradation on plant-animal mutualistic networks, and predict that the conversion of primary old-growth forests to secondary habitats may cause a parallel loss of multiple animal-mediated ecosystem services.
Chaotic phenomena in Josephson circuits coupled quantum cellular neural networks
Institute of Scientific and Technical Information of China (English)
Wang Sen; Cai Li; Li Qin; Wu Gang
2007-01-01
In this paper the nonlinear dynamical behaviour of a quantum cellular neural network (QCNN) by coupling Josephson circuits was investigated and it was shown that the QCNN using only two of them can cause the onset of chaotic oscillation. The theoretical analysis and simulation for the two Josephson-circuits-coupled QCNN have been done by using the amplitude and phase as state variables. The complex chaotic behaviours can be observed and then proved by calculating Lyapunov exponents. The study provides valuable information about QCNNs for future application in high-parallel signal processing and novel chaotic generators.
Electronic nonadiabatic effects in low temperature radical-radical reactions. I. C(3P) + OH(2Π).
Maergoiz, A I; Nikitin, E E; Troe, J
2014-07-28
The formation of collision complexes, as a first step towards reaction, in collisions between two open-electronic shell radicals is treated within an adiabatic channel approach. Adiabatic channel potentials are constructed on the basis of asymptotic electrostatic, induction, dispersion, and exchange interactions, accounting for spin-orbit coupling within the multitude of electronic states arising from the separated reactants. Suitable coupling schemes (such as rotational + electronic) are designed to secure maximum adiabaticity of the channels. The reaction between C((3)P) and OH((2)Π) is treated as a representative example. The results show that the low temperature association rate coefficients in general cannot be represented by results obtained with a single (generally the lowest) potential energy surface of the adduct, asymptotically reaching the lowest fine-structure states of the reactants, and a factor accounting for the thermal population of the latter states. Instead, the influence of non-Born-Oppenheimer couplings within the multitude of electronic states arising during the encounter markedly increases the capture rates. This effect extends up to temperatures of several hundred K.
Isochronous dynamics in pulse coupled oscillator networks with delay
Li, Pan; Lin, Wei; Efstathiou, Konstantinos
2017-05-01
We consider a network of identical pulse-coupled oscillators with delay and all-to-all coupling. We demonstrate that the discontinuous nature of the dynamics induces the appearance of isochronous regions—subsets of the phase space filled with periodic orbits having the same period. For each fixed value of the network parameters, such an isochronous region corresponds to a subset of initial states on an appropriate surface of section with non-zero dimensions such that all periodic orbits in this set have qualitatively similar dynamical behaviour. We analytically and numerically study in detail such an isochronous region, give proof of its existence, and describe its properties. We further describe other isochronous regions that appear in the system.
Pattern Selection in Network of Coupled Multi-Scroll Attractors.
Li, Fan; Ma, Jun
2016-01-01
Multi-scroll chaotic attractor makes the oscillator become more complex in dynamic behaviors. The collective behaviors of coupled oscillators with multi-scroll attractors are investigated in the regular network in two-dimensional array, which the local kinetics is described by an improved Chua circuit. A feasible scheme of negative feedback with diversity is imposed on the network to stabilize the spatial patterns. Firstly, the Chua circuit is improved by replacing the nonlinear term with Sine function to generate infinite aquariums so that multi-scroll chaotic attractors could be generated under appropriate parameters, which could be detected by calculating the Lyapunov exponent in the parameter region. Furthermore, negative feedback with different gains (D1, D2) is imposed on the local square center area A2 and outer area A1 of the network, it is found that spiral wave, target wave could be developed in the network under appropriate feedback gain with diversity and size of controlled area. Particularly, homogeneous state could be reached after synchronization by selecting appropriate feedback gain and controlled size in the network. Finally, the distribution for statistical factors of synchronization is calculated in the two-parameter space to understand the transition of pattern region. It is found that developed spiral waves, target waves often are associated with smaller factor of synchronization. These results show that emergence of sustained spiral wave and continuous target wave could be effective for further suppression of spatiotemporal chaos in network by generating stable pacemaker completely.
Pattern Selection in Network of Coupled Multi-Scroll Attractors.
Directory of Open Access Journals (Sweden)
Fan Li
Full Text Available Multi-scroll chaotic attractor makes the oscillator become more complex in dynamic behaviors. The collective behaviors of coupled oscillators with multi-scroll attractors are investigated in the regular network in two-dimensional array, which the local kinetics is described by an improved Chua circuit. A feasible scheme of negative feedback with diversity is imposed on the network to stabilize the spatial patterns. Firstly, the Chua circuit is improved by replacing the nonlinear term with Sine function to generate infinite aquariums so that multi-scroll chaotic attractors could be generated under appropriate parameters, which could be detected by calculating the Lyapunov exponent in the parameter region. Furthermore, negative feedback with different gains (D1, D2 is imposed on the local square center area A2 and outer area A1 of the network, it is found that spiral wave, target wave could be developed in the network under appropriate feedback gain with diversity and size of controlled area. Particularly, homogeneous state could be reached after synchronization by selecting appropriate feedback gain and controlled size in the network. Finally, the distribution for statistical factors of synchronization is calculated in the two-parameter space to understand the transition of pattern region. It is found that developed spiral waves, target waves often are associated with smaller factor of synchronization. These results show that emergence of sustained spiral wave and continuous target wave could be effective for further suppression of spatiotemporal chaos in network by generating stable pacemaker completely.
Coupled disease-behavior dynamics on complex networks: A review
Wang, Zhen; Andrews, Michael A.; Wu, Zhi-Xi; Wang, Lin; Bauch, Chris T.
2015-12-01
It is increasingly recognized that a key component of successful infection control efforts is understanding the complex, two-way interaction between disease dynamics and human behavioral and social dynamics. Human behavior such as contact precautions and social distancing clearly influence disease prevalence, but disease prevalence can in turn alter human behavior, forming a coupled, nonlinear system. Moreover, in many cases, the spatial structure of the population cannot be ignored, such that social and behavioral processes and/or transmission of infection must be represented with complex networks. Research on studying coupled disease-behavior dynamics in complex networks in particular is growing rapidly, and frequently makes use of analysis methods and concepts from statistical physics. Here, we review some of the growing literature in this area. We contrast network-based approaches to homogeneous-mixing approaches, point out how their predictions differ, and describe the rich and often surprising behavior of disease-behavior dynamics on complex networks, and compare them to processes in statistical physics. We discuss how these models can capture the dynamics that characterize many real-world scenarios, thereby suggesting ways that policy makers can better design effective prevention strategies. We also describe the growing sources of digital data that are facilitating research in this area. Finally, we suggest pitfalls which might be faced by researchers in the field, and we suggest several ways in which the field could move forward in the coming years.
Two networks of electrically coupled inhibitory neurons in neocortex
Gibson, Jay R.; Beierlein, Michael; Connors, Barry W.
1999-11-01
Inhibitory interneurons are critical to sensory transformations, plasticity and synchronous activity in the neocortex. There are many types of inhibitory neurons, but their synaptic organization is poorly understood. Here we describe two functionally distinct inhibitory networks comprising either fast-spiking (FS) or low-threshold spiking (LTS) neurons. Paired-cell recordings showed that inhibitory neurons of the same type were strongly interconnected by electrical synapses, but electrical synapses between different inhibitory cell types were rare. The electrical synapses were strong enough to synchronize spikes in coupled interneurons. Inhibitory chemical synapses were also common between FS cells, and between FS and LTS cells, but LTS cells rarely inhibited one another. Thalamocortical synapses, which convey sensory information to the cortex, specifically and strongly excited only the FS cell network. The electrical and chemical synaptic connections of different types of inhibitory neurons are specific, and may allow each inhibitory network to function independently.
An Efficient Method For Multichannel Wireless Mesh Networks With Pulse Coupled Neural Network
Sobana, S
2012-01-01
Multi cast communication is a key technology for wireless mesh networks. Multicast provides efficient data distribution among a group of nodes, Generally sensor networks and MANETs uses multicast algorithms which are designed to be energy efficient and to achieve optimal route discovery among mobile nodes whereas wireless mesh networks needs to maximize throughput. Here we propose two multicast algorithms: The Level Channel Assignment (LCA) algorithm and the Multi-Channel Multicast (MCM) algorithm to improve the throughput for multichannel sand multi interface mesh networks. The algorithm builds efficient multicast trees by minimizing the number of relay nodes and total hop count distance of the trees. Shortest path computation is a classical combinatorial optimization problem. Neural networks have been used for processing path optimization problem. Pulse Coupled Neural Networks (PCNNS) suffer from high computational cast for very long paths we propose a new PCNN modal called dual source PCNN (DSPCNN) which c...
Energy Technology Data Exchange (ETDEWEB)
Aamodt, K. [Department of Physics, University of Oslo, Oslo (Norway); Abel, N. [Kirchhoff-Institut fuer Physik, Ruprecht-Karls-Universitaet Heidelberg, Heidelberg (Germany); Abeysekara, U. [Physics Department, Creighton University, Omaha, NE (United States); Abrahantes Quintana, A. [Centro de Aplicaciones Tecnologicas y Desarrollo Nuclear (CEADEN), Havana (Cuba); Abramyan, A. [Yerevan Physics Institute, Yerevan (Armenia); Adamova, D. [Nuclear Physics Institute, Academy of Sciences of the Czech Republic, Rez u Prahy (Czech Republic); Aggarwal, M.M. [Physics Department, Panjab University, Chandigarh (India); Aglieri Rinella, G. [European Organization for Nuclear Research (CERN), Geneva (Switzerland); Agocs, A.G. [KFKI Research Institute for Particle and Nuclear Physics, Hungarian Academy of Sciences, Budapest (Hungary); Aguilar Salazar, S. [Instituto de Fisica, Universidad Nacional Autonoma de Mexico, Mexico City (Mexico); Ahammed, Z. [Variable Energy Cyclotron Centre, Kolkata (India); Ahmad, A.; Ahmad, N. [Department of Physics Aligarh Muslim University, Aligarh (India); Ahn, S.U. [Gangneung-Wonju National University, Gangneung (Korea, Republic of); Akimoto, R. [University of Tokyo, Tokyo (Japan); Akindinov, A. [Institute for Theoretical and Experimental Physics, Moscow (Russian Federation); Aleksandrov, D. [Russian Research Centre Kurchatov Institute, Moscow (Russian Federation); Alessandro, B. [Sezione INFN, Turin (Italy); Alfaro Molina, R. [Instituto de Fisica, Universidad Nacional Autonoma de Mexico, Mexico City (Mexico); Alici, A. [Dipartimento di Fisica dell' Universita and Sezione INFN, Bologna (Italy)
2010-09-27
The inclusive charged particle transverse momentum distribution is measured in proton-proton collisions at {radical}(s)=900 GeV at the LHC using the ALICE detector. The measurement is performed in the central pseudorapidity region (|{eta}|<0.8) over the transverse momentum range 0.15
{sub INEL}=0.483{+-}0.001 (stat.){+-}0.007 (syst.) GeV/c and
{sub NSD}=0.489{+-}0.001 (stat.){+-}0.007 (syst.) GeV/c, respectively. The data exhibit a slightly larger
than measurements in wider pseudorapidity intervals. The results are compared to simulations with the Monte Carlo event generators PYTHIA and PHOJET.
Energy Technology Data Exchange (ETDEWEB)
Aamodt, K. [University of Bergen, Department of Physics and Technology, Bergen (Norway); Abrahantes Quintana, A. [Centro de Aplicaciones Tecnologicas y Desarrollo Nuclear (CEADEN), Havana (Cuba); Adamova, D. [Nuclear Physics Inst., Academy of Sciences, Rez (CZ)] (and others)
2011-03-15
The production of mesons containing strange quarks (K{sup 0}{sub S}, {phi}) and both singly and doubly strange baryons ({lambda}, anti {lambda}, and {xi}{sup -}+ anti {xi}{sup +}) are measured at mid-rapidity in pp collisions at {radical}(s) = 0.9 TeV with the ALICE experiment at the LHC. The results are obtained from the analysis of about 250 k minimum bias events recorded in 2009. Measurements of yields (dN/dy) and transverse momentum spectra at mid-rapidity for inelastic pp collisions are presented. For mesons, we report yields (left angle dN/dy right angle) of 0.184{+-}0.002(stat.){+-}0.006(syst.) for K{sup 0}{sub S} and 0.021{+-}0.004(stat.){+-}0.003(syst.) for {phi}. For baryons, we find left angle dN/dy right angle =0.048{+-}0.001(stat.){+-}0.004(syst.) for {lambda}, 0.047{+-}0.002(stat.){+-}0.005(syst.) for anti {lambda} and 0.0101{+-}0.0020(stat.){+-}0.0009(syst.) for {xi}{sup +} anti {xi}{sup +}. The results are also compared with predictions for identified particle spectra from QCD-inspired models and provide a baseline for comparisons with both future pp measurements at higher energies and heavy-ion collisions. (orig.)
Energy Technology Data Exchange (ETDEWEB)
Lehmacher, Marc
2013-06-15
This dissertation presents a measurement of the flavour composition of dijet events produced in proton-proton collisions at a center-of-mass energy {radical}(s)=7 TeV. The data is reconstructed with the ATLAS detector at the LHC and the full data sample of 2010 is used. Three types of jet flavours, bottom, charm and light, are distinguished and thus six possible flavour combinations are identified in the dijet events. Kinematic variables, based on the properties of displaced decay vertices and optimised for jet flavour identification, are employed in an event-based likelihood fit. Multidimensional templates derived from Monte Carlo are used to measure the fractions of the six dijet flavour states as functions of the leading jet transverse momentum in the range 40 GeV to 500 GeV and jet rapidity vertical stroke y vertical stroke <2.1. The fit results agree with the predictions of leading- and next-to-leading-order calculations, with the exception of the dijet fraction composed of a bottom and a light flavour jet, which is underestimated by all models at large transverse jet momenta. In addition, the difference between bottom jet production rates in leading and subleading jets is measured and found to be consistent with the next-to-leadingorder predictions. The ability to identify jets containing two b-hadrons is demonstrated and used to identify a deficiency in the predictions of leading order Monte Carlo for the contribution of these jets to dijet production.
Energy Technology Data Exchange (ETDEWEB)
Mueller, Karl Klemens
2013-08-15
This thesis reports the measurement of the Z boson transverse momentum distribution in proton-proton collisions at {radical}(s)=7 TeV, inclusive in Z rapidity and subdivided in three rapidity intervals. The measurement uses data taken with the ATLAS detector in 2011 corresponding to an integrated luminosity of 4.7 fb{sup -1}, from which 1.8 million events with Z bosons decaying into muon pairs are selected. After subtracting the expected background distribution, the transverse momentum distribution of candidate events is unfolded to the Born level, correcting for efficiency and resolution effects as well as QED final state radiation. The transverse momentum distribution is measured up to a transverse momentum of 800GeV with a precision of <1.5% for p{sub T}<150 GeV. The measurement is compared with higher order perturbative QCD predictions and common parton shower event generators. The prediction from resummed QCD combined with fixed order perturbative QCD provides a good description of the measurement. The measured cross sections provide an important input to the tuning of parton shower event generators.
Search for charged Higgs bosons in e{sup +}e{sup -} collisions at {radical}(s)=189-209 GeV
Energy Technology Data Exchange (ETDEWEB)
Abbiendi, G.; Braibant, S.; Capiluppi, P.; Ciocca, C.; Cuffiani, M.; Dallavalle, M.; Fabbri, F.; Giacomelli, G.; Giacomelli, P.; Mader, W.; Mes, H.; Renkel, P.; Ainsley, C.; Batley, R.J.; Carter, J.R.; Hill, J.C.; Tasevsky, M.; Voss, H.; Vossebeld, J.; Aakesson, P.F.; Barberio, E.; Burckhart, H.J.; Roeck, A. de; Wolf, E.A. de; Ferrari, P.; Frey, A.; Gruwe, M.; Hauschild, M.; Hawkings, R.; McKenna, J.; Neal, H.A.; Pilcher, J.E.; Plane, D.E.; Przybycien, M.; Quadt, A.; Sachs, K.; Schaile, A.D.; Scharff-Hansen, P.; Schieck, J.; Schumacher, M.; Sherwood, P.; Stroehmer, R.; Torrence, E.; Vertesi, R.; Verzocchi, M.; Watson, A.T.; Watson, N.K.; Alexander, G.; Bella, G.; Etzion, E.; Grunhaus, J.; Trigger, I.; Anagnostou, G.; Bell, P.J.; Charlton, D.G.; Hawkes, C.M.; Jovanovic, P.; Nanjo, H.; Trocsanyi, Z.; Ward, C.P.; Ward, D.R.; Watkins, P.M.; Wermes, N.; Anderson, K.J.; Gupta, A.; Meijers, F.; Oh, A.; Pasztor, G.; Sobie, R.; Tarem, S.; Asai, S.; Ishii, K.; Kanzaki, J.; Kawagoe, K.; Kawamoto, T.; Kobayashi, T.; Komamiya, S.; Martin, A.J.; Meyer, N.; Miller, D.J.; Mutter, A.; Nagai, K.; Okpara, A.; Runge, K.; Thomson, M.A.; Tsur, E.; Wolf, G.; Axen, D.; Loebinger, F.K.; Mashimo, T.; Bailey, I.; Karlen, D.; Keeler, R.K.; Maettig, P.; Rembser, C.; Skuja, A.; Barillari, T.; Bethke, S.; Kluth, S.; Oreglia, M.J.; Pooth, O.; Schaile, O.; Barlow, R.J.; Duerdoth, I.P.; Ford, M.; Lafferty, G.D.; Lloyd, S.L.; Marcellini, S.; Pahl, C.; Smith, A.M.; Wengler, T.; Wilson, J.A.; Bechtle, P.; Behnke, T.; Desch, K.; Hamann, M.; Heuer, R.D.; Kraemer, T.; Kuhl, T.; McPherson, R.A.; Merritt, F.S.; Bell, K.W.; Brown, R.M.; Kennedy, B.W.; Bellerive, A.; Carnegie, R.K.; Junk, T.R.; Krieger, P.; Menges, W.; Rozen, Y.; Benelli, G.; Campana, S.; Gary, J.W.; Giunta, M.; Hanson, G.G.; Orito, S.; Seuster, R.; Wyatt, T.R.; Biebel, O.; Boutemeur, M.; Dubbert, J.; Duckeck, G.; Fiedler, F.; Saeki, T.; Sarkisyan, E.K.G.; Stahl, A.; Ueda, I.; Boeriu, O.; Fleck, I.; Herten, G.; Levinson, L.; Ludwig, A.; Mikenberg, G.; Mohr, W.; Rossi, A.M.; Ujvari, B.; Bock, P.; Igo-Kemenes, P.; Krogh, J. von; O' Neale, S.W.; Carter, A.A.; Lillich, J.; Marchant, T.E.; Mori, T.; Chang, C.Y.; Hoffman, K.; Kellogg, R.G.; Shen, B.C.; Vannerem, P.; Csilling, A.; Hajdu, C.; Horvath, D.; Dado, S.; Goldberg, J.; Harel, A.; Landsman, H.; Roney, J.M.; Strom, D.; Yamashita, S.; Dienes, B.; Krasznahorkay, A.; Toya, D.; Turner-Watson, M.F.; Vollmer, C.F.; Duchovni, E.; Gross, E.; Kupper, M.; Lellouch, D.; Letts, J.; Michelini, A.; Rabbertz, K.; Wilson, G.W.; Gagnon, P.; Geich-Gimbel, C.; Kobel, M.; Lu, J.; Ludwig, J.; Schoerner-Sadenius, T.; Wells, P.S.; Jeremie, H.; Lanske, D.; Pinfold, J.; Schroeder, M.; Soeldner-Rembold, S.; Mihara, S.; Shears, T.G.; Nakamura, I.; Pater, J.R.; Spano, F.; Teuscher, R.; Collaboration: OPAL Collaboration
2012-07-15
A search is made for charged Higgs bosons predicted by Two-Higgs-Doublet extensions of the Standard Model (2HDM) using electron-positron collision data collected by the OPAL experiment at {radical}(s)=189-209 GeV, corresponding to an integrated luminosity of approximately 600 pb{sup -1}. Charged Higgs bosons are assumed to be pair-produced and to decay into q anti q, {tau}{nu}{sub {tau}} or AW{sup {+-}}. No signal is observed. Model-independent limits on the charged Higgs-boson production cross section are derived by combining these results with previous searches at lower energies. Under the assumption BR(H{sup {+-}}{yields}{tau}{nu}{sub {tau}}) + BR(H{sup {+-}}{yields}q anti q)=1, motivated by general 2HDM type II models, excluded areas on the [m{sub H}{sup {+-}}, BR(H{sup {+-}}{yields}{tau}{nu}{sub {tau}})] plane are presented and charged Higgs bosons are excluded up to a mass of 76.3 GeV at 95 % confidence level, independent of the branching ratio BR(H{sup {+-}}{yields}{tau}{nu}{sub {tau}}). A scan of the 2HDM type I model parameter space is performed and limits on the Higgs-boson masses m{sub H}{sup {+-}} and m{sub A} are presented for different choices of tan {beta}. (orig.)
New measurement of the p-{anti p} total cross section at {radical}S = 1.8 TeV
Energy Technology Data Exchange (ETDEWEB)
Avila, C.; Guss, C.; Mondardini, M.R. [Cornell Univ., Ithaca, NY (United States). Lab. of Nuclear Studies
1997-09-01
A new type of detector capable of reaching very small angles was successfully used in Fermilab E811 in Jan. 1996. It consists of a bundle of 15,000 scintillating fibers each of 100 {micro}m diameter. The fibers are oriented parallel to the beam and gave a measuring resolution of 38 {micro}m transverse to the beam. In this report the authors analyzed about 50,000 elastics as close as 3 mm from the beam. Simulated data runs show that the total cross section should be obtained to an accuracy of {+-}2%. The smallest t-bin used has a background subtraction of {approximately}20%, but for most of the t-bins the background is much smaller and the detection efficiency is over 95%. Very preliminary analysis gives a total cross section of {approximately}71 mb at {radical}s = 1.8 TeV using a luminosity-independent method. This is consistent with the earlier Fermilab E710 result which used a different kind of elastic detector. The rho-value analysis has not yet been completed. A personal interpretation (by Orear) of a slower rise in the total cross section is given at the end.
Energy Technology Data Exchange (ETDEWEB)
Aaij, R. [Nikhef National Institute for Subatomic Physics, Amsterdam (Netherlands); Abellan Beteta, C. [Universitat de Barcelona, Barcelona (Spain); Adeva, B. [Universidad de Santiago de Compostela, Santiago de Compostela (Spain); Adinolfi, M. [H.H. Wills Physics Laboratory, University of Bristol, Bristol (United Kingdom); Adrover, C. [CPPM, Aix-Marseille Universite, CNRS/IN2P3, Marseille (France); Affolder, A. [Oliver Lodge Laboratory, University of Liverpool, Liverpool (United Kingdom); Ajaltouni, Z. [Clermont Universite, Universite Blaise Pascal, CNRS/IN2P3, LPC, Clermont-Ferrand (France); Albrecht, J.; Alessio, F. [European Organization for Nuclear Research (CERN), Geneva (Switzerland); Alexander, M. [School of Physics and Astronomy, University of Glasgow, Glasgow (United Kingdom); Ali, S. [Nikhef National Institute for Subatomic Physics, Amsterdam (Netherlands); Alkhazov, G. [Petersburg Nuclear Physics Institute (PNPI), Gatchina (Russian Federation); Alvarez Cartelle, P. [Universidad de Santiago de Compostela, Santiago de Compostela (Spain); Alves, A.A. [Sezione INFN di Roma La Sapienza, Roma (Italy); Amato, S. [Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro (Brazil); Amhis, Y. [Ecole Polytechnique Federale de Lausanne (EPFL), Lausanne (Switzerland); Anderson, J. [Physik-Institut, Universitaet Zuerich, Zuerich (Switzerland); Appleby, R.B. [School of Physics and Astronomy, University of Manchester, Manchester (United Kingdom); Aquines Gutierrez, O. [Max-Planck-Institut fuer Kernphysik (MPIK), Heidelberg (Germany); Archilli, F. [Laboratori Nazionali dell' INFN di Frascati, Frascati (Italy); European Organization for Nuclear Research (CERN), Geneva (Switzerland); and others
2012-12-05
The prompt production of charmonium {chi}{sub c} and J/{psi} states is studied in proton-proton collisions at a centre-of-mass energy of {radical}(s)=7 TeV at the Large Hadron Collider. The {chi}{sub c} and J/{psi} mesons are identified through their decays {chi}{sub c}{yields}J/{psi}{gamma} and J/{psi}{yields}{mu}{sup +}{mu}{sup -} using 36 pb{sup -1} of data collected by the LHCb detector in 2010. The ratio of the prompt production cross-sections for {chi}{sub c} and J/{psi}, {sigma}({chi}{sub c}{yields}J/{psi}{gamma})/{sigma}(J/{psi}), is determined as a function of the J/{psi} transverse momentum in the range 2
Coupling Mechanism of the Tourism Industrial Network Based on Circular Economy
Han, Xinming; Zheng, Xiangjiang
2009-01-01
This paper summarizes the research situation of circular economy and tourism industrial network at home and abroad, introduces the concept and characteristics of tourism industrial network, and analyzes the coupling mechanism of tourism industrial network based on circular economy.
Correlated Fluctuations in Strongly Coupled Binary Networks Beyond Equilibrium
Directory of Open Access Journals (Sweden)
David Dahmen
2016-08-01
Full Text Available Randomly coupled Ising spins constitute the classical model of collective phenomena in disordered systems, with applications covering glassy magnetism and frustration, combinatorial optimization, protein folding, stock market dynamics, and social dynamics. The phase diagram of these systems is obtained in the thermodynamic limit by averaging over the quenched randomness of the couplings. However, many applications require the statistics of activity for a single realization of the possibly asymmetric couplings in finite-sized networks. Examples include reconstruction of couplings from the observed dynamics, representation of probability distributions for sampling-based inference, and learning in the central nervous system based on the dynamic and correlation-dependent modification of synaptic connections. The systematic cumulant expansion for kinetic binary (Ising threshold units with strong, random, and asymmetric couplings presented here goes beyond mean-field theory and is applicable outside thermodynamic equilibrium; a system of approximate nonlinear equations predicts average activities and pairwise covariances in quantitative agreement with full simulations down to hundreds of units. The linearized theory yields an expansion of the correlation and response functions in collective eigenmodes, leads to an efficient algorithm solving the inverse problem, and shows that correlations are invariant under scaling of the interaction strengths.
Correlated Fluctuations in Strongly Coupled Binary Networks Beyond Equilibrium
Dahmen, David; Bos, Hannah; Helias, Moritz
2016-07-01
Randomly coupled Ising spins constitute the classical model of collective phenomena in disordered systems, with applications covering glassy magnetism and frustration, combinatorial optimization, protein folding, stock market dynamics, and social dynamics. The phase diagram of these systems is obtained in the thermodynamic limit by averaging over the quenched randomness of the couplings. However, many applications require the statistics of activity for a single realization of the possibly asymmetric couplings in finite-sized networks. Examples include reconstruction of couplings from the observed dynamics, representation of probability distributions for sampling-based inference, and learning in the central nervous system based on the dynamic and correlation-dependent modification of synaptic connections. The systematic cumulant expansion for kinetic binary (Ising) threshold units with strong, random, and asymmetric couplings presented here goes beyond mean-field theory and is applicable outside thermodynamic equilibrium; a system of approximate nonlinear equations predicts average activities and pairwise covariances in quantitative agreement with full simulations down to hundreds of units. The linearized theory yields an expansion of the correlation and response functions in collective eigenmodes, leads to an efficient algorithm solving the inverse problem, and shows that correlations are invariant under scaling of the interaction strengths.
Rescue of endemic states in interconnected networks with adaptive coupling
Vazquez, F; Miguel, M San
2015-01-01
We study the Susceptible-Infected-Susceptible model of epidemic spreading on two layers of networks interconnected by adaptive links, which are rewired at random to avoid contacts between infected and susceptible nodes at the interlayer. We find that the rewiring reduces the effective connectivity for the transmission of the disease between layers, and may even totally decouple the networks. Weak endemic states, in which the epidemics spreads only if the two layers are interconnected, show a transition from the endemic to the healthy phase when the rewiring overcomes a threshold value that depends on the infection rate, the strength of the coupling and the mean connectivity of the networks. In the strong endemic scenario, in which the epidemics is able to spread on each separate network, the prevalence in each layer decreases when increasing the rewiring, arriving to single network values only in the limit of infinitely fast rewiring. We also find that finite-size effects are amplified by the rewiring, as the...
Detecting effective connectivity in networks of coupled neuronal oscillators.
Boykin, Erin R; Khargonekar, Pramod P; Carney, Paul R; Ogle, William O; Talathi, Sachin S
2012-06-01
The application of data-driven time series analysis techniques such as Granger causality, partial directed coherence and phase dynamics modeling to estimate effective connectivity in brain networks has recently gained significant prominence in the neuroscience community. While these techniques have been useful in determining causal interactions among different regions of brain networks, a thorough analysis of the comparative accuracy and robustness of these methods in identifying patterns of effective connectivity among brain networks is still lacking. In this paper, we systematically address this issue within the context of simple networks of coupled spiking neurons. Specifically, we develop a method to assess the ability of various effective connectivity measures to accurately determine the true effective connectivity of a given neuronal network. Our method is based on decision tree classifiers which are trained using several time series features that can be observed solely from experimentally recorded data. We show that the classifiers constructed in this work provide a general framework for determining whether a particular effective connectivity measure is likely to produce incorrect results when applied to a dataset.
Epidemic spreading on one-way-coupled networks
Wang, Lingna; Sun, Mengfeng; Chen, Shanshan; Fu, Xinchu
2016-09-01
Numerous real-world networks (e.g., social, communicational, and biological networks) have been observed to depend on each other, and this results in interconnected networks with different topology structures and dynamics functions. In this paper, we focus on the scenario of epidemic spreading on one-way-coupled networks comprised of two subnetworks, which can manifest the transmission of some zoonotic diseases. By proposing a mathematical model through mean-field approximation approach, we prove the global stability of the disease-free and endemic equilibria of this model. Through the theoretical and numerical analysis, we obtain interesting results: the basic reproduction number R0 of the whole network is the maximum of the basic reproduction numbers of the two subnetworks; R0 is independent of the cross-infection rate and cross contact pattern; R0 increases rapidly with the growth of inner infection rate if the inner contact pattern is scale-free; in order to eradicate zoonotic diseases from human beings, we must simultaneously eradicate them from animals; bird-to-bird infection rate has bigger impact on the human's average infected density than bird-to-human infection rate.
Experimental multistable states for small network of coupled pendula
Dudkowski, Dawid; Grabski, Juliusz; Wojewoda, Jerzy; Perlikowski, Przemyslaw; Maistrenko, Yuri; Kapitaniak, Tomasz
2016-07-01
Chimera states are dynamical patterns emerging in populations of coupled identical oscillators where different groups of oscillators exhibit coexisting synchronous and incoherent behaviors despite homogeneous coupling. Although these states are typically observed in the large ensembles of oscillators, recently it has been shown that so-called weak chimera states may occur in the systems with small numbers of oscillators. Here, we show that similar multistable states demonstrating partial frequency synchronization, can be observed in simple experiments with identical mechanical oscillators, namely pendula. The mathematical model of our experiment shows that the observed multistable states are controlled by elementary dynamical equations, derived from Newton’s laws that are ubiquitous in many physical and engineering systems. Our finding suggests that multistable chimera-like states are observable in small networks relevant to various real-world systems.
Analog implementation of pulse-coupled neural networks.
Ota, Y; Wilamowski, B M
1999-01-01
This paper presents a compact architecture for analog CMOS hardware implementation of voltage-mode pulse-coupled neural networks (PCNN's). The hardware implementation methods shows inherent fault tolerance specialties and high speed, which is usually more than an order of magnitude over the software counterpart. A computational style described in this article mimics a biological neural network using pulse-stream signaling and analog summation and multiplication. Pulse-stream encoding technique uses pulse streams to carry information and control analog circuitry, while storing further analog information on the time axis. The main feature of the proposed neuron circuit is that the structure is compact, yet exhibiting all the basic properties of natural biological neurons. Functional and structural forms of neural and synaptic functions are presented along with simulation results. Finally, the proposed design is applied to image processing to demonstrate successful restoration of images and their features.
Cross-Frequency Coupling in Real and Virtual Brain Networks
Directory of Open Access Journals (Sweden)
Viktor eJirsa
2013-07-01
Full Text Available Information processing in the brain is thought to rely on the convergence and divergence of oscillatory behaviors of widely distributed brain areas. This information flow is captured in its simplest form via the concepts of synchronization and desynchronization and related metrics. More complex forms of information flow are transient synchronizations and multi-frequency behaviors with metrics related to cross-frequency coupling (CFC. It is supposed that CFC plays a crucial role in the organization of large-scale networks and functional integration across large distances. In this study we describe different CFC measures and test their applicability in simulated and real electroencephalographic (EEG data obtained during resting state. For these purposes, we derive generic oscillator equations from full brain network models. We systematically model and simulate the various scenarios of cross-frequency coupling under the influence of noise to obtain biologically realistic oscillator dynamics. We find that (i specific CFC-measures detect correctly in most cases the nature of CFC under noise conditions, (ii bispectrum and bicoherence correctly detect the CFCs in simulated data, (iii empirical resting state EEG show a prominent delta-alpha CFC as identified by specific CFC measures and the more classic bispectrum and bicoherence. This coupling was mostly asymmetric (directed and generally higher in the eyes-closed than in the eyes-open condition. In conjunction, these two sets of measures provide a powerful toolbox to reveal the nature of couplings from experimental data and as such allow inference on the brain state dependent information processing. Methodological advantages of using CFC measures and theoretical significance of delta and alpha interactions during resting and other brain states are discussed.
Energy Technology Data Exchange (ETDEWEB)
Aamodt, K. [Department of Physics and Technology, University of Bergen, Bergen (Norway); Abrahantes Quintana, A. [Centro de Aplicaciones Tecnologicas y Desarrollo Nuclear (CEADEN), Havana (Cuba); Adamova, D. [Nuclear Physics Institute, Academy of Sciences of the Czech Republic, Rez u Prahy (Czech Republic); Adare, A.M. [Yale University, New Haven, CT (United States); Aggarwal, M.M. [Physics Department, Panjab University, Chandigarh (India); Aglieri Rinella, G. [European Organization for Nuclear Research (CERN), Geneva (Switzerland); Agocs, A.G. [KFKI Research Institute for Particle and Nuclear Physics, Hungarian Academy of Sciences, Budapest (Hungary); Agostinelli, A. [Dipartimento di Fisica dell' Universita and Sezione INFN, Bologna (Italy); Aguilar Salazar, S. [Instituto de Fisica, Universidad Nacional Autonoma de Mexico, Mexico City (Mexico); Ahammed, Z. [Variable Energy Cyclotron Centre, Kolkata (India); Ahmad, N.; Ahmad Masoodi, A. [Department of Physics, Aligarh Muslim University, Aligarh (India); Ahn, S.U. [Gangneung-Wonju National University, Gangneung (Korea, Republic of); Akindinov, A. [Institute for Theoretical and Experimental Physics, Moscow (Russian Federation); Aleksandrov, D. [Russian Research Centre Kurchatov Institute, Moscow (Russian Federation); Alessandro, B. [Sezione INFN, Turin (Italy); Alfaro Molina, R. [Instituto de Fisica, Universidad Nacional Autonoma de Mexico, Mexico City (Mexico); Alici, A. [Centro Fermi - Centro Studi e Ricerche e Museo Storico della Fisica ' Enrico Fermi' , Rome (Italy); Alkin, A. [Bogolyubov Institute for Theoretical Physics, Kiev (Ukraine); Almaraz Avina, E. [Instituto de Fisica, Universidad Nacional Autonoma de Mexico, Mexico City (Mexico)
2011-10-25
The ALICE experiment at the LHC has studied inclusive J/{psi} production at central and forward rapidities in pp collisions at {radical}(s)=7 TeV. In this Letter, we report on the first results obtained detecting the J/{psi} through the dilepton decay into e{sup +}e{sup -} and {mu}{sup +}{mu}{sup -} pairs in the rapidity ranges |y|<0.9 and 2.5
Bubbling effect in the electro-optic delayed feedback oscillator coupled network
Liu, Lingfeng; Lin, Jun; Miao, Suoxia
2017-03-01
Synchronization in the optical systems coupled network always suffers from bubbling events. In this paper, we numerically investigate the statistical properties of the synchronization characteristics and bubbling effects in the electro-optic delayed feedback oscillator coupled network with different coupling strength, delay time and gain coefficient. Furthermore, we compare our results with the synchronization properties of semiconductor laser (SL) coupled network, which indicates that the electro-optic delayed feedback oscillator can be better to suppress the bubbling effects in the synchronization of coupled network under the same conditions.
Modeling of price and profit in coupled-ring networks
Tangmongkollert, Kittiwat; Suwanna, Sujin
2016-06-01
We study the behaviors of magnetization, price, and profit profiles in ring networks in the presence of the external magnetic field. The Ising model is used to determine the state of each node, which is mapped to the buy-or-sell state in a financial market, where +1 is identified as the buying state, and -1 as the selling state. Price and profit mechanisms are modeled based on the assumption that price should increase if demand is larger than supply, and it should decrease otherwise. We find that the magnetization can be induced between two rings via coupling links, where the induced magnetization strength depends on the number of the coupling links. Consequently, the price behaves linearly with time, where its rate of change depends on the magnetization. The profit grows like a quadratic polynomial with coefficients dependent on the magnetization. If two rings have opposite direction of net spins, the price flows in the direction of the majority spins, and the network with the minority spins gets a loss in profit.
Effects of Leakage Inductances on Magnetically Coupled Y-Source Network
DEFF Research Database (Denmark)
Siwakoti, Yam P.; Loh, Poh Chiang; Blaabjerg, Frede
2014-01-01
Coupled inductors have been used with impedance-source networks, extended from the earlier Z-source network, to keep their shoot-through times short, while providing high-voltage gains. A commonly stated requirement for these networks is that their magnetic couplings must be strong or their leaka...
Lai, Pik-Yin
2017-02-01
Reconstructing network connection topology and interaction strengths solely from measurement of the dynamics of the nodes is a challenging inverse problem of broad applicability in various areas of science and engineering. For a discrete-time step network under noises whose noise-free dynamics is stationary, we derive general analytic results relating the weighted connection matrix of the network to the correlation functions obtained from time-series measurements of the nodes for networks with one-dimensional intrinsic node dynamics. Information about the intrinsic node dynamics and the noise strengths acting on the nodes can also be obtained. Based on these results, we develop a scheme that can reconstruct the above information of the network using only the time-series measurements of node dynamics as input. Reconstruction formulas for higher-dimensional node dynamics are also derived and illustrated with a two-dimensional node dynamics network system. Furthermore, we extend our results and obtain a reconstruction scheme even for the cases when the noise-free dynamics is periodic. We demonstrate that our method can give accurate reconstruction results for weighted directed networks with linear or nonlinear node dynamics of various connection topologies, and with linear or nonlinear couplings.
Information Filtering via Biased Random Walk on Coupled Social Network
Directory of Open Access Journals (Sweden)
Da-Cheng Nie
2014-01-01
Full Text Available The recommender systems have advanced a great deal in the past two decades. However, most researchers focus their attentions on mining the similarities among users or objects in recommender systems and overlook the social influence which plays an important role in users’ purchase process. In this paper, we design a biased random walk algorithm on coupled social networks which gives recommendation results based on both social interests and users’ preference. Numerical analyses on two real data sets, Epinions and Friendfeed, demonstrate the improvement of recommendation performance by taking social interests into account, and experimental results show that our algorithm can alleviate the user cold-start problem more effectively compared with the mass diffusion and user-based collaborative filtering methods.
Event-based cluster synchronization of coupled genetic regulatory networks
Yue, Dandan; Guan, Zhi-Hong; Li, Tao; Liao, Rui-Quan; Liu, Feng; Lai, Qiang
2017-09-01
In this paper, the cluster synchronization of coupled genetic regulatory networks with a directed topology is studied by using the event-based strategy and pinning control. An event-triggered condition with a threshold consisting of the neighbors' discrete states at their own event time instants and a state-independent exponential decay function is proposed. The intra-cluster states information and extra-cluster states information are involved in the threshold in different ways. By using the Lyapunov function approach and the theories of matrices and inequalities, we establish the cluster synchronization criterion. It is shown that both the avoidance of continuous transmission of information and the exclusion of the Zeno behavior are ensured under the presented triggering condition. Explicit conditions on the parameters in the threshold are obtained for synchronization. The stability criterion of a single GRN is also given under the reduced triggering condition. Numerical examples are provided to validate the theoretical results.
An Efficient Method For Multichannel Wireless Mesh Networks With Pulse Coupled Neural Network
Directory of Open Access Journals (Sweden)
S.Sobana
2012-01-01
Full Text Available Multi cast communication is a key technology for wireless mesh networks. Multicast provides efficient data distribution among a group of nodes, Generally sensor networks and MANETs uses multicast algorithms which are designed to be energy efficient and to achieve optimal route discovery among mobile nodes whereas wireless mesh networks needs to maximize throughput. Here we propose two multicast algorithms: The Level Channel Assignment (LCA algorithm and the Multi-Channel Multicast (MCM algorithm to improve the throughput for multichannel sand multi interface mesh networks. The algorithm builds efficient multicast trees by minimizing the number of relay nodes and total hop count distance of the trees. Shortest path computation is a classical combinatorial optimization problem. Neural networks have been used for processing path optimization problem. Pulse Coupled Neural Networks (PCNNS suffer from high computational cast for very long paths we propose a new PCNN modal called dual source PCNN (DSPCNN which can improve the computational efficiency two auto waves are produced by DSPCNN one comes from source neuron and other from goal neuron when the auto waves from these two sources meet the DSPCNN stops and then the shortest path is found by backtracking the two auto waves.
Quantifying phase-amplitude coupling in neuronal network oscillations.
Onslow, Angela C E; Bogacz, Rafal; Jones, Matthew W
2011-03-01
Neuroscience time series data from a range of techniques and species reveal complex, non-linear interactions between different frequencies of neuronal network oscillations within and across brain regions. Here, we briefly review the evidence that these nested, cross-frequency interactions act in concert with linearly covariant (within-frequency) activity to dynamically coordinate functionally related neuronal ensembles during behaviour. Such studies depend upon reliable quantification of cross-frequency coordination, and we compare the properties of three techniques used to measure phase-amplitude coupling (PAC)--Envelope-to-Signal Correlation (ESC), the Modulation Index (MI) and Cross-Frequency Coherence (CFC)--by standardizing their filtering algorithms and systematically assessing their robustness to noise and signal amplitude using artificial signals. Importantly, we also introduce a freely-downloadable method for estimating statistical significance of PAC, a step overlooked in the majority of published studies. We find that varying data length and noise levels leads to the three measures differentially detecting false positives or correctly identifying frequency bands of interaction; these conditions should therefore be taken into careful consideration when selecting PAC analyses. Finally, we demonstrate the utility of the three measures in quantifying PAC in local field potential data simultaneously recorded from rat hippocampus and prefrontal cortex, revealing a novel finding of prefrontal cortical theta phase modulating hippocampal gamma power. Future adaptations that allow detection of time-variant PAC should prove essential in deciphering the roles of cross-frequency coupling in mediating or reflecting nervous system function.
Energy Technology Data Exchange (ETDEWEB)
Nagano, Kunihiro [Tokyo Univ., Tokyo (Japan)
2000-02-01
The charged-current e{sup +}p deep inelastic scattering cross sections were measured at {radical}s=300 GeV in the kinematic region Q{sup 2} > 200 GeV{sup 2}. The analysis is based on the 46.6 pb{sup -1} e{sup +}p collision data collected by ZEUS at HERA during the running years from 1994 to 1997. The single differential cross sections d{sigma}/dQ{sup 2}, d{sigma}/dx and d{sigma}/dy were measured. Compared with our previous measurement, both the statistical and systematic errors were reduced. The explored kinematic region was extended to high Q{sup 2} and high x regions: d{sigma}/dQ{sup 2} was measured up to Q{sup 2}=30000 GeV{sup 2}, and d{sigma}/dx was measured up to x=0.65. The double differential cross section as a function of x and Q{sup 2}, d{sup 2}{sigma}/dxdQ{sup 2}, was also measured. This is the first measurement for the e{sup +}p charged-current interaction. The measured cross sections were compared with the Standard Model predictions obtained with CTEQ 4D, MRSA and GRV 94 parton density functions, respectively, which were evolved according to the next-to-leading-order QCD evolution equation. The cross sections were consistent with these predictions except for the high x region, x > or approx. 0.1, where d{sigma}/dx exhibited an excess. The double differential cross section d{sup 2}{sigma}/dxdQ{sup 2} exhibited this high-x excess in a wide range of Q{sup 2}. This observation suggests that the d-quark density in the high x region is underestimated in the current parton density functions. The propagator mass was extracted from d{sigma}/dQ{sup 2} as M{sub W}=83.4{+-}2.8(stat.){sub -2.1}{sup +1.6}(syst.){+-}2.7(pdf) GeV. This value is in agreement with the mass of W{sup {+-}}-boson obtained by the direct mass measurements at LEP and Tevatron. (author)
Energy Technology Data Exchange (ETDEWEB)
Marienfeld, Markus
2011-07-15
The start of proton-proton collisions at the LHC inaugurates a new era in high-energy physics. It enables the possibility of discoveries at the high-energy frontier and also allows for studies of known Standard Model processes with unrivalled precision. Top quark pairs are produced at high rates and allow for precision measurements of the properties of the top quark with high statistics. The measurement of the top quark pair production cross section in proton-proton collisions at {radical}(s)=7 TeV is presented using the dileptonic decay channel with a muon-electron pair in the final state. The data sample, which is used in this analysis, corresponds the complete 2010 data taking period with an integrated luminosity of 35.9 pb{sup -1}. Top quark pair candidate events are selected in a cut-based event selection. Based on 59 observed muon-electron events in the final state event sample, the top quark pair production cross section is measured to be {sigma}{sub t} {sub anti} {sub t}=(156{+-}25(stat.){+-}14(sys.)) pb. Furthermore, a kinematic event reconstruction is applied, which is complementary to the use of b-tagging techniques, and validates the top quark-like topology of the selected events. First results from the measurement of differential cross sections based on the data from the complete 2010 data taking period are presented. For the first time in the CMS collaboration, the cross section of the production of top quark pairs is measured differentially as a function of the kinematic observables of the final state objects, such as the transverse momentum p{sub T} of the leptons and the invariant mass of the lepton pair. Based on the solution of the kinematic event reconstruction, the cross section is also calculated differentially as a function of the kinematic properties of the reconstructed top-antitop quark pair. First results from the measurement of differential cross sections as a function of the kinematics of the final state leptons are presented, using the data recorded in the first part of the 2011 data taking period. (orig.)
The synchronization of FitzHugh-Nagumo neuron network coupled by gap junction
Institute of Scientific and Technical Information of China (English)
Zhan Yong; Zhang Su-Hua; Zhao Tong-Jun; An Hai-Long; Zhang Zhen-Dong; Han Ying-Rong; Liu Hui; Zhang Yu-Hong
2008-01-01
It is well known that the strong coupling can synchronize a network of nonlinear oscillators. Synchronization provides the basis of the remarkable computational performance of the brain. In this paper the FitzHugh-Nagumo neuron network is constructed. The dependence of the synchronization on the coupling strength, the noise intensity and the size of the neuron network has been discussed. The results indicate that the coupling among neurons works to improve the synchronization, and noise increases the neuron random dynamics and the local fluctuations; the larger the size of network, the worse the synchronization. The dependence of the synchronization on the strength of the electric synapse coupling and chemical synapse coupling has also been discussed, which proves that electric synapse coupling can enhance the synchronization of the neuron network largely.
Adaptive output regulation and circuit realization for a class of attenuated coupled networks
Jin, Xiao-Zheng; Park, Ju H.
2015-09-01
In this paper, an adaptive regulation method for couplings and its physical implementation are presented to deal with the problem of output synchronization of networks. The networks are supposed to suffer from a fault described by network attenuation. For the sake of eliminating the adverse impact of network attenuation, a self-regulating network is introduced by adjusting coupling strength based on adaptive technique. By using the Lyapunov stability theory for a synchronization error system, asymptotic output synchronization of the overall networks can be established for the attenuated couplings even without any control input. Moreover, based on the adaptive regulation strategy, an approach for application of knowledge of electricity is proposed to physically realize the self-regulating networks. Finally, numerical simulations on a Rössler oscillator network are given to illustrate the effectiveness of the derived results.
Effects of leakage inductances on magnetically-coupled impedance-source networks
DEFF Research Database (Denmark)
Siwakoti, Yam P.; Loh, Poh Chiang; Blaabjerg, Frede
2014-01-01
Coupled inductors have lately been used with impedance-source networks for keeping their shoot-through times short, while providing higher voltage boosts. The parameter that is critical to the operation of such impedance network based converter with coupled inductors is the leakage inductances. H...
Institute of Scientific and Technical Information of China (English)
Yang Xinsong; Cao Jinde
2012-01-01
In this article,we consider the global chaotic synchronization of general coupled neural networks,in which subsystems have both discrete and distributed delays.Stochastic perturbations between subsystems are also considered.On the basis of two simple adaptive pinning feedback control schemes,Lyapunov functional method,and stochastic analysis approach,several sufficient conditions are developed to guarantee global synchronization of the coupled neural networks with two kinds of delay couplings,even if only partial states of the nodes are coupled.The outer-coupling matrices may be symmetric or asymmetric.Unlike existing results that an isolate node is introduced as the pinning target,we pin to help the network realizing synchronization without introducing any isolate node when the network is not synchronized.As a by product,sufficient conditions under which the network realizes synchronization without control are derived.Numerical simulations confirm the effectiveness of the obtained results.
Electrolarynx Voice Recognition Utilizing Pulse Coupled Neural Network
Directory of Open Access Journals (Sweden)
Fatchul Arifin
2010-08-01
Full Text Available The laryngectomies patient has no ability to speak normally because their vocal chords have been removed. The easiest option for the patient to speak again is by using electrolarynx speech. This tool is placed on the lower chin. Vibration of the neck while speaking is used to produce sound. Meanwhile, the technology of "voice recognition" has been growing very rapidly. It is expected that the technology of "voice recognition" can also be used by laryngectomies patients who use electrolarynx.This paper describes a system for electrolarynx speech recognition. Two main parts of the system are feature extraction and pattern recognition. The Pulse Coupled Neural Network – PCNN is used to extract the feature and characteristic of electrolarynx speech. Varying of β (one of PCNN parameter also was conducted. Multi layer perceptron is used to recognize the sound patterns. There are two kinds of recognition conducted in this paper: speech recognition and speaker recognition. The speech recognition recognizes specific speech from every people. Meanwhile, speaker recognition recognizes specific speech from specific person. The system ran well. The "electrolarynx speech recognition" has been tested by recognizing of “A” and "not A" voice. The results showed that the system had 94.4% validation. Meanwhile, the electrolarynx speaker recognition has been tested by recognizing of “saya” voice from some different speakers. The results showed that the system had 92.2% validation. Meanwhile, the best β parameter of PCNN for electrolarynx recognition is 3.
Energy Technology Data Exchange (ETDEWEB)
Neusiedl, Andrea
2012-11-19
In hadronic collisions, a large amount of processes with large momentum transfer produce a pair of high-p{sub T} jets. Their production rate and event properties can be predicted with good precision using perturbative Quantum Chromodynamics (QCD). The production of bottom-quarks in such collisions is a benchmark process in perturbative QCD because they probe the underlying strong dynamics at a well-defined scale. Because of their large mass, bottom-flavoured particles hold the most direct correspondence between the parton-level production and the observed hadron level. The large pair production rate of bottom-quarks and their corresponding decay products makes them important as background source for many analyses including searches for new physics. Besides this, quarks of the third generation could take an exceptional position among the quarks concerning the sensitivity to new massive objects. Studies on the fraction of jets containing bottom-flavoured particles, known as b-jets, relative to all-flavour jets could reveal such new phenomena. In this thesis the production rate of and the correlation between pairs of b-jets is measured. The invariant dijet mass spectrum is searched for indications for a new resonance in context of physics beyond the Standard Model. At the Large Hadron Collider (LHC) two proton beams at a centre-of-mass energy of {radical}(s)=7 TeV collide, producing a large number of such pairs of b-jets. This measurement makes use of the data recorded with the ATLAS detector. The total integrated luminosity available for the analysis is about 34 pb{sup -1}. b-jets are identified via their long lifetime and the reconstruction of their charged decay products. For this analysis differences between jets originating from light objects, like gluons and light quarks, compared to jets containing bottom-flavoured objects have to be taken into account. The jet energy scale of b-jets is established and the additional uncertainty on the jet energy measurement is determined. Detector effects in the jet reconstruction special to b-jets are studied in order to make the measurement independent of the detector and to correct them to hadron level. Then the cross section measured is compared to next-to-leading order Monte-Carlo predictions. These next-to-leading order predictions are in agreement with ATLAS data. Consequently, the underlying production mechanism is confirmed to also be valid in this new energy regime of the LHC. However, first indications for deviations in the description of next-to-leading processes are discovered. Up to an invariant dijet mass of about 1.7 TeV no evidence for a new resonance decaying into a pair of high-p{sub T} b-jets is found. Therefore, model-independent upper limits are calculated for signals following a Gaussian distribution with different signal widths.
Fahr, Askar; Halpern, Joshua B.; Tardy, Dwight C.
2007-01-01
of C-C and C-H bond ruptures, cyclization, decyclization, and complex decompositions are discussed in terms of energetics and structural properties. The pressure dependence of the product yields were computed and dominant reaction paths in this chemically activated system were determined. Both modeling and experiment suggest that the observed pressure dependence of [1-C4H8]/[C4H10] is due to decomposition of the chemically activated combination adduct 1-C4H8* in which the weaker allylic C-C bond is broken: H2C=CHCH2CH3 yields C3H5 + CH3. This reaction occurs even at moderate pressures of approx.200 Torr (26 kPa) and becomes more significant at lower pressures. The additional products detected at lower pressures are formed from secondary radical-radical reactions involving allyl, methyl, ethyl, and vinyl radicals. The modeling studies have extended the predictions of product distributions to different temperatures (200-700 K) and a wider range of pressures (10(exp -3) - 10(exp 5) Torr). These calculations indicate that the high-pressure [1-C4H8]/[C4H10] yield ratio is 1.3 +/- 0.1.
Energy Technology Data Exchange (ETDEWEB)
Lange, Joern
2013-09-15
Modern particle-physics experiments like the ones at the Large Hadron Collider (LHC) are global and interdisciplinary endeavours comprising a variety of different fields. In this work, two different aspects are dealt with: on the one hand a top-quark physics analysis and on the other hand research and development towards radiation-hard silicon tracking detectors. The high centre-of-mass energy and luminosity at the LHC allow for a detailed investigation of top-quark-pair (t anti t) pro duction properties. Normalised differential t anti t cross sections (1)/({sigma}) (d{sigma}{sub t} {sub anti} {sub t})/(dX) are measured as a function of nine different kinematic variables X of the t anti t system, the top quarks and their decay products (b jets and leptons). The analysis is performed using data of proton-proton collisions at {radical}(s) = 7 TeV recorded by the CMS experiment in 2011, corresponding to an integrated luminosity of 5 fb{sup -1}. A high-purity sample of t anti t events is selected according to the topology of the lepton+jets decay channel. Lepton-selection and trigger efficiencies are determined with data-driven methods. The top-quark four-vectors are reconstructed using a constrained kinematic fit. The reconstructed distributions are corrected for background and detector effects using a regularised unfolding technique. By normalising the differential cross sections with the in-situ measured total cross section, correlated systematic uncertainties are reduced, achieving a precision of typically 4-11%. The results are compared to standard-model predictions from Monte-Carlo event generators and approximate next-to-next-to-leading-order (NNLO) perturbative QCD calculations. A good agreement is observed. A high-luminosity upgrade of the LHC (HL-LHC) is envisaged for 2022, which implies increased radiation levels for the silicon tracking detectors. The innermost pixel layer is expected to be exposed to a 1-MeV-neutron-equivalent fluence in the order of 10{sup 16} cm{sup -2}. The novel effect of radiation-induced charge multiplication (CM) is studied as an option to overcome the expected signal-to-noise degradation due to radiation damage (mainly due to charge-carrier trapping). Epitaxial silicon pad diodes of 75-150 {mu}m thickness and of standard and oxygen-enriched materials are investigated after irradiation with 24 GeV protons up to equivalent fluences of 10{sup 16} cm{sup -2}. Charge collection in response to different radiation (670, 830, 1060 nm laser light, {alpha} and {beta} particles) is studied with the transient-current technique and a {sup 90}Sr {beta} setup. The different penetration properties of the radiation types are used to localise the CM region. The dependence of CM on voltage, fluence, thickness, material, temperature and annealing time is studied, as well as its proportionality, spatial uniformity and long-term stability. The absolute amount of charge in response to {beta} particles is measured, and the impact of CM on noise, signal-to-noise and the charge-spectrum width is investigated. Implications for realistic segmented devices at the HL-LHC are discussed.
Border Figure Detection Using a Phase Oscillator Network with Dynamical Coupling
Directory of Open Access Journals (Sweden)
L. H. A. Monteiro
2008-01-01
Full Text Available Oscillator networks have been developed in order to perform specific tasks related to image processing. Here we analytically investigate the existence of synchronism in a pair of phase oscillators that are short-range dynamically coupled. Then, we use these analytical results to design a network able of detecting border of black-and-white figures. Each unit composing this network is a pair of such phase oscillators and is assigned to a pixel in the image. The couplings among the units forming the network are also dynamical. Border detection emerges from the network activity.
Wang, Jin-Liang; Wu, Huai-Ning; Huang, Tingwen; Ren, Shun-Yan
2016-04-01
Two types of coupled neural networks with reaction-diffusion terms are considered in this paper. In the first one, the nodes are coupled through their states. In the second one, the nodes are coupled through the spatial diffusion terms. For the former, utilizing Lyapunov functional method and pinning control technique, we obtain some sufficient conditions to guarantee that network can realize synchronization. In addition, considering that the theoretical coupling strength required for synchronization may be much larger than the needed value, we propose an adaptive strategy to adjust the coupling strength for achieving a suitable value. For the latter, we establish a criterion for synchronization using the designed pinning controllers. It is found that the coupled reaction-diffusion neural networks with state coupling under the given linear feedback pinning controllers can realize synchronization when the coupling strength is very large, which is contrary to the coupled reaction-diffusion neural networks with spatial diffusion coupling. Moreover, a general criterion for ensuring network synchronization is derived by pinning a small fraction of nodes with adaptive feedback controllers. Finally, two examples with numerical simulations are provided to demonstrate the effectiveness of the theoretical results.
Indian Academy of Sciences (India)
Arturo C Martí; Marcelo Ponce; Cristina Masoller
2008-06-01
We review our recent work on the synchronization of a network of delay-coupled maps, focusing on the interplay of the network topology and the delay times that take into account the finite velocity of propagation of interactions. We assume that the elements of the network are identical ( logistic maps in the regime where the individual maps, without coupling, evolve in a chaotic orbit) and that the coupling strengths are uniform throughout the network. We show that if the delay times are su±ciently heterogeneous, for adequate coupling strength the network synchronizes in a spatially homogeneous steady state, which is unstable for the individual maps without coupling. This synchronization behavior is referred to as `suppression of chaos by random delays' and is in contrast with the synchronization when all the interaction delay times are homogeneous, because with homogeneous delays the network synchronizes in a state where the elements display in-phase time-periodic or chaotic oscillations. We analyze the influence of the network topology considering four different types of networks: two regular (a ring-type and a ring-type with a central node) and two random (free-scale Barabasi-Albert and small-world Newman-Watts). We find that when the delay times are sufficiently heterogeneous the synchronization behavior is largely independent of the network topology but depends on the network's connectivity, i.e., on the average number of neighbors per node.
Li, Ting-Ting; Li, Cheng-Ren; Wang, Chen; He, Fang-Jun; Zhou, Guang-Ye; Sun, Jing-Chang; Han, Fei
2016-12-01
A new synchronization technique of inner and outer couplings is proposed in this work to investigate the synchronization of network group. Some Haken-Lorenz lasers with chaos behaviors are taken as the nodes to construct a few nearest neighbor complex networks and those sub-networks are also connected to form a network group. The effective node controllers are designed based on Lyapunov function and the complete synchronization among the sub-networks is realized perfectly under inner and outer couplings. The work is of potential applications in the cooperation output of lasers and the communication network. Project supported by the National Natural Science Foundation of China (Grant No. 11004092), the Natural Science Foundation of Liaoning Province, China (Grant Nos. 2015020079 and 201602455), and the Foundation of Education Department of Liaoning Province, China (Grant No. L201683665)
Analysis of Road Traffic Network Cascade Failures with Coupled Map Lattice Method
Directory of Open Access Journals (Sweden)
Yanan Zhang
2015-01-01
Full Text Available In recent years, there is growing literature concerning the cascading failure of network characteristics. The object of this paper is to investigate the cascade failures on road traffic network, considering the aeolotropism of road traffic network topology and road congestion dissipation in traffic flow. An improved coupled map lattice (CML model is proposed. Furthermore, in order to match the congestion dissipation, a recovery mechanism is put forward in this paper. With a real urban road traffic network in Beijing, the cascading failures are tested using different attack strategies, coupling strengths, external perturbations, and attacked road segment numbers. The impacts of different aspects on road traffic network are evaluated based on the simulation results. The findings confirmed the important roles that these characteristics played in the cascading failure propagation and dissipation on road traffic network. We hope these findings are helpful to find out the optimal road network topology and avoid cascading failure on road network.
Synchronization of coupled large-scale Boolean networks
Energy Technology Data Exchange (ETDEWEB)
Li, Fangfei, E-mail: li-fangfei@163.com [Department of Mathematics, East China University of Science and Technology, No. 130, Meilong Road, Shanghai, Shanghai 200237 (China)
2014-03-15
This paper investigates the complete synchronization and partial synchronization of two large-scale Boolean networks. First, the aggregation algorithm towards large-scale Boolean network is reviewed. Second, the aggregation algorithm is applied to study the complete synchronization and partial synchronization of large-scale Boolean networks. Finally, an illustrative example is presented to show the efficiency of the proposed results.
Synchronization of coupled large-scale Boolean networks
Li, Fangfei
2014-03-01
This paper investigates the complete synchronization and partial synchronization of two large-scale Boolean networks. First, the aggregation algorithm towards large-scale Boolean network is reviewed. Second, the aggregation algorithm is applied to study the complete synchronization and partial synchronization of large-scale Boolean networks. Finally, an illustrative example is presented to show the efficiency of the proposed results.
Zhang, Wei; Li, Chuandong; Huang, Tingwen; He, Xing
2015-12-01
Synchronization of an array of linearly coupled memristor-based recurrent neural networks with impulses and time-varying delays is investigated in this brief. Based on the Lyapunov function method, an extended Halanay differential inequality and a new delay impulsive differential inequality, some sufficient conditions are derived, which depend on impulsive and coupling delays to guarantee the exponential synchronization of the memristor-based recurrent neural networks. Impulses with and without delay and time-varying delay are considered for modeling the coupled neural networks simultaneously, which renders more practical significance of our current research. Finally, numerical simulations are given to verify the effectiveness of the theoretical results.
Synchronization and Bifurcation Analysis in Coupled Networks of Discrete-Time Systems
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
Synchronization and bifurcation analysis in coupled networks of discrete-time systems are investigated in the present paper. We mainly focus on some special coupling matrix, i.e., the sum of each row equals a nonzero constant u and the network connection is directed. A result that the network can reach a new synchronous state, which is not the asymptotic limit set determined by the node state equation, is derived. It is interesting that the network exhibits bifurcation if we regard the constant u as a bifurcation parameter at the synchronous state. Numerical simulations are given to show the efficiency of our derived conclusions.
Social Recommender Systems Based on Coupling Network Structure Analysis
Hu, Xiao; Chen, Xiaolong; Zhang, Zi-Ke
2012-01-01
The past few years has witnessed the great success of recommender systems, which can significantly help users find relevant and interesting items for them in the information era. However, a vast class of researches in this area mainly focus on predicting missing links in bipartite user-item networks (represented as behavioral networks). Comparatively, the social impact, especially the network structure based properties, is relatively lack of study. In this paper, we firstly obtain five corresponding network-based features, including user activity, average neighbors' degree, clustering coefficient, assortative coefficient and discrimination, from social and behavioral networks, respectively. A hybrid algorithm is proposed to integrate those features from two respective networks. Subsequently, we employ a machine learning process to use those features to provide recommendation results in a binary classifier method. Experimental results on a real dataset, Flixster, suggest that the proposed method can significan...
Output-threshold coupled neural network for solving the shortest path problems
Institute of Scientific and Technical Information of China (English)
ZHANG Junying; WANG Defeng; SHI Meihong; WANG Joseph Yue
2004-01-01
This paper presents a coupled neural network, called output-threshold coupled neural network (OTCNN), which can mimic the autowaves in the present pulsed coupled neural networks (PCNNs), by the construction of mutual coupling between neuron outputs and the threshold of a neuron. Based on its autowaves, this paper presents a method for finding the shortest path in shortest time with OTCNNs. The method presented here features much fewer neurons needed, simplicity of the structure of the neurons and the networks, and large scale of parallel computation. It is shown that OTCNN is very effective in finding the shortest paths from a single start node to multiple destination nodes for asymmetric weighted graph, with a number of iterations proportional only to the length of the shortest paths, but independent of the complexity of the graph and the total number of existing paths in the graph. Finally, examples for finding the shortest path are presented.
Passivity and robust synchronisation of switched interval coupled neural networks with time delay
Li, Ning; Cao, Jinde
2016-09-01
This paper is concerned with passivity and robust synchronisation of switched coupled neural networks with uncertain parameters. First, the mathematical model of switched coupled neural networks with interval uncertain parameters is established, which consists of L modes and switches from one mode to another according to the switching rule. Second, by employing passivity theory and linear matrix inequality techniques, delay-independent and delay-dependent conditions are derived to guarantee the passivity of switched interval coupled neural networks. Moreover, based on the proposed passivity results, global synchronisation criteria can be obtained for switched coupled neural networks with or without uncertain parameters. Finally, an illustrative example is provided to demonstrate the effectiveness of the obtained results.
Barreiro, Andrea K.; Ly, Cheng
2017-08-01
Rapid experimental advances now enable simultaneous electrophysiological recording of neural activity at single-cell resolution across large regions of the nervous system. Models of this neural network activity will necessarily increase in size and complexity, thus increasing the computational cost of simulating them and the challenge of analyzing them. Here we present a method to approximate the activity and firing statistics of a general firing rate network model (of the Wilson-Cowan type) subject to noisy correlated background inputs. The method requires solving a system of transcendental equations and is fast compared to Monte Carlo simulations of coupled stochastic differential equations. We implement the method with several examples of coupled neural networks and show that the results are quantitatively accurate even with moderate coupling strengths and an appreciable amount of heterogeneity in many parameters. This work should be useful for investigating how various neural attributes qualitatively affect the spiking statistics of coupled neural networks.
Efficient shortest-path-tree computation in network routing based on pulse-coupled neural networks.
Qu, Hong; Yi, Zhang; Yang, Simon X
2013-06-01
Shortest path tree (SPT) computation is a critical issue for routers using link-state routing protocols, such as the most commonly used open shortest path first and intermediate system to intermediate system. Each router needs to recompute a new SPT rooted from itself whenever a change happens in the link state. Most commercial routers do this computation by deleting the current SPT and building a new one using static algorithms such as the Dijkstra algorithm at the beginning. Such recomputation of an entire SPT is inefficient, which may consume a considerable amount of CPU time and result in a time delay in the network. Some dynamic updating methods using the information in the updated SPT have been proposed in recent years. However, there are still many limitations in those dynamic algorithms. In this paper, a new modified model of pulse-coupled neural networks (M-PCNNs) is proposed for the SPT computation. It is rigorously proved that the proposed model is capable of solving some optimization problems, such as the SPT. A static algorithm is proposed based on the M-PCNNs to compute the SPT efficiently for large-scale problems. In addition, a dynamic algorithm that makes use of the structure of the previously computed SPT is proposed, which significantly improves the efficiency of the algorithm. Simulation results demonstrate the effective and efficient performance of the proposed approach.
Multimode dynamics in a network with resource mediated coupling
DEFF Research Database (Denmark)
Postnov, D.E.; Sosnovtseva, Olga; Scherbakov, P.
2008-01-01
The purpose of this paper is to study the special forms of multimode dynamics that one can observe in systems with resource- mediated coupling, i. e., systems of self- sustained oscillators in which the coupling takes place via the distribution of primary resources that controls the oscillatory...... state of the individual unit. With this coupling, a spatially inhomogenous state with mixed high and lowamplitude oscillations in the individual units can arise. To examine generic phenomena associated with this type of interaction we consider a chain of resistively coupled electronic oscillators...... connected to a common power supply. The two- oscillator system displays antiphase synchronization, and it is interesting to note that two- mode oscillations continue to exist outside of the parameter range in which oscillations occur for the individual unit. At low coupling strengths, the multioscillator...
The spike timing precision of FitzHugh-Nagumo neuron network coupled by gap junctions
Institute of Scientific and Technical Information of China (English)
Zhang Su-Hua; Zhan Yong; Yu Hui; An Hai-Long; Zhao Tong-Jun
2006-01-01
It has been proved recently that the spike timing can play an important role in information transmission, so in this paper we develop a network with N-unit FitzHugh-Nagumo neurons coupled by gap junctions and discuss the dependence of the spike timing precision on synaptic coupling strength, the noise intensity and the size of the neuron ensemble. The calculated results show that the spike timing precision decreases as the noise intensity increases; and the ensemble spike timing precision increases with coupling strength increasing. The electric synapse coupling has a more important effect on the spike timing precision than the chemical synapse coupling.
Chimera patterns induced by distance-dependent power-law coupling in ecological networks
Banerjee, Tanmoy; Dutta, Partha Sharathi; Zakharova, Anna; Schöll, Eckehard
2016-09-01
This paper reports the occurrence of several chimera patterns and the associated transitions among them in a network of coupled oscillators, which are connected by a long-range interaction that obeys a distance-dependent power law. This type of interaction is common in physics and biology and constitutes a general form of coupling scheme, where by tuning the power-law exponent of the long-range interaction the coupling topology can be varied from local via nonlocal to global coupling. To explore the effect of the power-law coupling on collective dynamics, we consider a network consisting of a realistic ecological model of oscillating populations, namely the Rosenzweig-MacArthur model, and show that the variation of the power-law exponent mediates transitions between spatial synchrony and various chimera patterns. We map the possible spatiotemporal states and their scenarios that arise due to the interplay between the coupling strength and the power-law exponent.
Pinning Synchronization of Delayed Neural Networks with Nonlinear Inner-Coupling
Directory of Open Access Journals (Sweden)
Yangling Wang
2011-01-01
Full Text Available Without assuming the symmetry and irreducibility of the outer-coupling weight configuration matrices, we investigate the pinning synchronization of delayed neural networks with nonlinear inner-coupling. Some delay-dependent controlled stability criteria in terms of linear matrix inequality (LMI are obtained. An example is presented to show the application of the criteria obtained in this paper.
Energy Technology Data Exchange (ETDEWEB)
Hao Yinghang [School of Physics, Ludong University, Yantai 264025 (China); Gong, Yubing, E-mail: gongyubing09@hotmail.co [School of Physics, Ludong University, Yantai 264025 (China); Wang Li; Ma Xiaoguang; Yang Chuanlu [School of Physics, Ludong University, Yantai 264025 (China)
2011-04-15
Research highlights: Single synchronization transition for gap-junctional coupling. Multiple synchronization transitions for chemical synaptic coupling. Gap junctions and chemical synapses have different impacts on synchronization transition. Chemical synapses may play a dominant role in neurons' information processing. - Abstract: In this paper, we have studied time delay- and coupling strength-induced synchronization transitions in scale-free modified Hodgkin-Huxley (MHH) neuron networks with gap-junctions and chemical synaptic coupling. It is shown that the synchronization transitions are much different for these two coupling types. For gap-junctions, the neurons exhibit a single synchronization transition with time delay and coupling strength, while for chemical synapses, there are multiple synchronization transitions with time delay, and the synchronization transition with coupling strength is dependent on the time delay lengths. For short delays we observe a single synchronization transition, whereas for long delays the neurons exhibit multiple synchronization transitions as the coupling strength is varied. These results show that gap junctions and chemical synapses have different impacts on the pattern formation and synchronization transitions of the scale-free MHH neuronal networks, and chemical synapses, compared to gap junctions, may play a dominant and more active function in the firing activity of the networks. These findings would be helpful for further understanding the roles of gap junctions and chemical synapses in the firing dynamics of neuronal networks.
H∞-Based Pinning Synchronization of General Complex Dynamical Networks with Coupling Delays
Directory of Open Access Journals (Sweden)
Bowen Du
2013-01-01
Full Text Available This paper investigates the synchronization of complex dynamical networks with coupling delays and external disturbances by applying local feedback injections to a small fraction of nodes in the whole network. Based on H∞ control theory, some delay-independent and -dependent synchronization criteria with a prescribed H∞ disturbances attenuation index are derived for such controlled networks in terms of linear matrix inequalities (LMIs, which guarantee that by placing a small number of feedback controllers on some nodes, the whole network can be pinned to reach network synchronization. A simulation example is included to validate the theoretical results.
Evolution of a G protein-coupled receptor response by mutations in regulatory network interactions
DEFF Research Database (Denmark)
Di Roberto, Raphaël B; Chang, Belinda; Trusina, Ala
2016-01-01
All cellular functions depend on the concerted action of multiple proteins organized in complex networks. To understand how selection acts on protein networks, we used the yeast mating receptor Ste2, a pheromone-activated G protein-coupled receptor, as a model system. In Saccharomyces cerevisiae,...
Evolution of a G protein-coupled receptor response by mutations in regulatory network interactions
DEFF Research Database (Denmark)
Di Roberto, Raphaël B; Chang, Belinda; Trusina, Ala;
2016-01-01
All cellular functions depend on the concerted action of multiple proteins organized in complex networks. To understand how selection acts on protein networks, we used the yeast mating receptor Ste2, a pheromone-activated G protein-coupled receptor, as a model system. In Saccharomyces cerevisiae...
Adaptive coupled synchronization of non-autonomous systems in ring networks
Institute of Scientific and Technical Information of China (English)
Guo Liu-Xiao; Xu Zhen-Yuan; Hu Man-Feng
2008-01-01
The adaptive coupled synchronization method for non-autonomous systems is proposed. This method can avoid estimating the value of coupling coefficient.Under the uniform Lipschitz assumption, we derive the asymptotical synchronization for a general coupling ring network with N identical non-autonomons systems, even when N is large enough. Strict theoretical proofs are given. Numerical simulations illustrate the effectiveness of the present method.
Energy Technology Data Exchange (ETDEWEB)
Abachi, S.; D0 Collaboration
1995-07-01
The global topologies of three- and four-jet events produced in {bar p}p interactions are described. the three- and four-jet events are selected from data recorded by the D0 detector at the Tevatron Collider operating at a center-of-mass energy of {radical}s = 1800 GeV. the measured normalized distributions of various topological variables are compared with parton-level predictions of the tree- level QCD calculations. The parton-level QCD calculations are found to be in good agreement with the data. The studies also show that the topological distributions of the different subprocesses involving different numbers of quarks are very similar and reproduce the measured distributions well.
Multimode dynamics in a network with resource mediated coupling
Postnov, D. E.; Sosnovtseva, O. V.; Scherbakov, P.; Mosekilde, E.
2008-03-01
The purpose of this paper is to study the special forms of multimode dynamics that one can observe in systems with resource-mediated coupling, i.e., systems of self-sustained oscillators in which the coupling takes place via the distribution of primary resources that controls the oscillatory state of the individual unit. With this coupling, a spatially inhomogenous state with mixed high and low-amplitude oscillations in the individual units can arise. To examine generic phenomena associated with this type of interaction we consider a chain of resistively coupled electronic oscillators connected to a common power supply. The two-oscillator system displays antiphase synchronization, and it is interesting to note that two-mode oscillations continue to exist outside of the parameter range in which oscillations occur for the individual unit. At low coupling strengths, the multi-oscillator system shows high dimensional quasiperiodicity with little tendency for synchronization. At higher coupling strengths, one typically observes spatial clustering involving a few oscillating units. We describe three different scenarios according to which the cluster can slide along the chain as the bias voltage changes.
Topology identification of the complex networks with non-delayed and delayed coupling
Guo, Wanli; Chen, Shihua; Sun, Wen
2009-10-01
In practical situation, there exists many uncertain information in complex networks, such as the topological structures. So the topology identification is an important issue in the research of the complex networks. Based on LaSalle's invariance principle, in this Letter, an adaptive controlling method is proposed to identify the topology of a weighted general complex network model with non-delayed and delayed coupling. Finally, simulation results show that the method is effective.
Topology identification of the complex networks with non-delayed and delayed coupling
Energy Technology Data Exchange (ETDEWEB)
Guo Wanli, E-mail: guowanliff@163.co [School of Mathematics and Statistics, Wuhan University, Wuhan 430072 (China); Chen Shihua; Sun Wen [School of Mathematics and Statistics, Wuhan University, Wuhan 430072 (China)
2009-10-05
In practical situation, there exists many uncertain information in complex networks, such as the topological structures. So the topology identification is an important issue in the research of the complex networks. Based on LaSalle's invariance principle, in this Letter, an adaptive controlling method is proposed to identify the topology of a weighted general complex network model with non-delayed and delayed coupling. Finally, simulation results show that the method is effective.
Synchronization of fluctuating delay-coupled chaotic networks
Jiménez-Martín, Manuel; Rodríguez-Laguna, Javier; D'Huys, Otti; de la Rubia, Javier; Korutcheva, Elka
2017-05-01
We study the synchronization of chaotic units connected through time-delayed fluctuating interactions. Focusing on small-world networks of Bernoulli and Logistic units with a fixed chiral backbone, we compare the synchronization properties of static and fluctuating networks in the regime of large delays. We find that random network switching may enhance the stability of synchronized states. Synchronization appears to be maximally stable when fluctuations are much faster than the time-delay, whereas it disappears for very slow fluctuations. For fluctuation time scales of the order of the time-delay, we report a resynchronizing effect in finite-size networks. Moreover, we observe characteristic oscillations in all regimes, with a periodicity related to the time-delay, as the system approaches or drifts away from the synchronized state.
Donges, Jonathan F; Marwan, Norbert; Zou, Yong; Kurths, Juergen
2011-01-01
Network theory provides various tools for investigating the structural or functional topology of many complex systems found in nature, technology and society. Nevertheless, it has recently been realised that a considerable number of systems of interest should be treated, more appropriately, as interacting networks or networks of networks. Here we introduce a novel graph-theoretical framework for studying the interaction structure between subnetworks embedded within a complex network of networks. This framework allows us to quantify the structural role of single vertices or whole subnetworks with respect to the interaction of a pair of subnetworks on local, mesoscopic and global topological scales. Climate networks have recently been shown to be a powerful tool for the analysis of climatological data. Applying the general framework for studying interacting networks, we introduce coupled climate subnetworks to represent and investigate the topology of statistical relationships between the fields of distinct cli...
Wen, Sun; Chen, Shihua; Guo, Wanli
2008-10-01
This Letter investigates the global synchronization of a general complex dynamical network with non-delayed and delayed coupling. Based on Lasalle's invariance principle, adaptive global synchronization criteria is obtained. Analytical result shows that under the designed adaptive controllers, a general complex dynamical network with non-delayed and delayed coupling can globally asymptotically synchronize to a given trajectory. What is more, the node dynamic need not satisfy the very strong and conservative uniformly Lipschitz condition and the coupling matrix is not assumed to be symmetric or irreducible. Finally, numerical simulations are presented to verify the effectiveness of the proposed synchronization criteria.
Xu, Yuhua; Zhou, Wuneng; Fang, Jian'an; Sun, Wen
2010-04-01
This Letter investigates the synchronization of a general complex dynamical network with non-derivative and derivative coupling. Based on LaSalle's invariance principle, adaptive synchronization criteria are obtained. Analytical result shows that under the designed adaptive controllers, a general complex dynamical network with non-derivative and derivative coupling can asymptotically synchronize to a given trajectory, and several useful criteria for synchronization are given. What is more, the coupling matrix is not assumed to be symmetric or irreducible. Finally, simulations results show the method is effective.
Energy Technology Data Exchange (ETDEWEB)
Xu Yuhua, E-mail: yuhuaxu2004@163.co [College of Information Science and Technology, Donghua University, Shanghai 201620 (China) and Department of Maths, Yunyang Teachers' College, Hubei 442000 (China); Zhou Wuneng, E-mail: wnzhou@163.co [College of Information Science and Technology, Donghua University, Shanghai 201620 (China); Fang Jian' an [College of Information Science and Technology, Donghua University, Shanghai 201620 (China); Sun Wen [School of Mathematics and Information, Yangtze University, Hubei Jingzhou 434023 (China)
2010-04-05
This Letter investigates the synchronization of a general complex dynamical network with non-derivative and derivative coupling. Based on LaSalle's invariance principle, adaptive synchronization criteria are obtained. Analytical result shows that under the designed adaptive controllers, a general complex dynamical network with non-derivative and derivative coupling can asymptotically synchronize to a given trajectory, and several useful criteria for synchronization are given. What is more, the coupling matrix is not assumed to be symmetric or irreducible. Finally, simulations results show the method is effective.
Energy Technology Data Exchange (ETDEWEB)
Wen Sun [College of Mathematics and Statistics, Wuhan University, Wuhan 430072 (China)], E-mail: sunwen_2201@163.com; Chen Shihua; Guo Wanli [College of Mathematics and Statistics, Wuhan University, Wuhan 430072 (China)
2008-10-13
This Letter investigates the global synchronization of a general complex dynamical network with non-delayed and delayed coupling. Based on Lasalle's invariance principle, adaptive global synchronization criteria is obtained. Analytical result shows that under the designed adaptive controllers, a general complex dynamical network with non-delayed and delayed coupling can globally asymptotically synchronize to a given trajectory. What is more, the node dynamic need not satisfy the very strong and conservative uniformly Lipschitz condition and the coupling matrix is not assumed to be symmetric or irreducible. Finally, numerical simulations are presented to verify the effectiveness of the proposed synchronization criteria.
Chaotic Griffiths Phase with Anomalous Lyapunov Spectra in Coupled Map Networks.
Shinoda, Kenji; Kaneko, Kunihiko
2016-12-16
Dynamics of coupled chaotic oscillators on a network are studied using coupled maps. Within a broad range of parameter values representing the coupling strength or the degree of elements, the system repeats formation and split of coherent clusters. The distribution of the cluster size follows a power law with the exponent α, which changes with the parameter values. The number of positive Lyapunov exponents and their spectra are scaled anomalously with the power of the system size with the exponent β, which also changes with the parameters. The scaling relation α∼2(β+1) is uncovered, which is universal independent of parameters and among random networks.
He, Wangli; Qian, Feng; Cao, Jinde
2017-01-01
This paper investigates pinning synchronization of coupled neural networks with both current-state coupling and distributed-delay coupling via impulsive control. A novel impulse pinning strategy involving pinning ratio is proposed and a general criterion is derived to ensure an array of neural networks with two different topologies synchronizes with the desired trajectory. In order to handle the difficulties of high-dimension criteria, some inequality techniques and matrix decomposition methods through simultaneous diagonalization of two matrices are introduced and low-dimensional criteria are obtained. Finally, an illustrative example is given to show the effectiveness of the proposed method. Copyright © 2016 Elsevier Ltd. All rights reserved.
Geometric detection of coupling directions by means of inter-system recurrence networks
Feldhoff, Jan H; Donges, Jonathan F; Marwan, N; Kurths, J; 10.1016/j.physleta.2012.10.008
2013-01-01
We introduce a geometric method for identifying the coupling direction between two dynamical systems based on a bivariate extension of recurrence network analysis. Global characteristics of the resulting inter-system recurrence networks provide a correct discrimination for weakly coupled R\\"ossler oscillators not yet displaying generalised synchronisation. Investigating two real-world palaeoclimate time series representing the variability of the Asian monsoon over the last 10,000 years, we observe indications for a considerable influence of the Indian summer monsoon on climate in Eastern China rather than vice versa. The proposed approach can be directly extended to studying $K>2$ coupled subsystems.
Geometric detection of coupling directions by means of inter-system recurrence networks
Energy Technology Data Exchange (ETDEWEB)
Feldhoff, Jan H. [Potsdam Institute for Climate Impact Research, P.O. Box 60 12 03, 14412 Potsdam (Germany); Department of Physics, Humboldt University, Newtonstr. 15, 12489 Berlin (Germany); Donner, Reik V., E-mail: reik.donner@pik-potsdam.de [Potsdam Institute for Climate Impact Research, P.O. Box 60 12 03, 14412 Potsdam (Germany); Donges, Jonathan F. [Potsdam Institute for Climate Impact Research, P.O. Box 60 12 03, 14412 Potsdam (Germany); Department of Physics, Humboldt University, Newtonstr. 15, 12489 Berlin (Germany); Marwan, Norbert [Potsdam Institute for Climate Impact Research, P.O. Box 60 12 03, 14412 Potsdam (Germany); Kurths, Jürgen [Potsdam Institute for Climate Impact Research, P.O. Box 60 12 03, 14412 Potsdam (Germany); Department of Physics, Humboldt University, Newtonstr. 15, 12489 Berlin (Germany); Institute for Complex Systems and Mathematical Biology, University of Aberdeen, Aberdeen AB243UE (United Kingdom)
2012-10-15
We introduce a geometric method for identifying the coupling direction between two dynamical systems based on a bivariate extension of recurrence network analysis. Global characteristics of the resulting inter-system recurrence networks provide a correct discrimination for weakly coupled Rössler oscillators not yet displaying generalised synchronisation. Investigating two real-world palaeoclimate time series representing the variability of the Asian monsoon over the last 10,000 years, we observe indications for a considerable influence of the Indian summer monsoon on climate in Eastern China rather than vice versa. The proposed approach can be directly extended to studying K>2 coupled subsystems.
Chaotic Griffiths Phase with Anomalous Lyapunov Spectra in Coupled Map Networks
Shinoda, Kenji; Kaneko, Kunihiko
2016-12-01
Dynamics of coupled chaotic oscillators on a network are studied using coupled maps. Within a broad range of parameter values representing the coupling strength or the degree of elements, the system repeats formation and split of coherent clusters. The distribution of the cluster size follows a power law with the exponent α , which changes with the parameter values. The number of positive Lyapunov exponents and their spectra are scaled anomalously with the power of the system size with the exponent β , which also changes with the parameters. The scaling relation α ˜2 (β +1 ) is uncovered, which is universal independent of parameters and among random networks.
Generalized Projective Synchronization between Two Complex Networks with Time-Varying Coupling Delay
Institute of Scientific and Technical Information of China (English)
SUN Mei; ZENG Chang-Yan; TIAN Li-Xin
2009-01-01
Generalized projective synchronization (GPS) between two complex networks with time-varying coupling delay is investigated. Based on the Lyapunov stability theory, a nonlinear controller and adaptive updated laws are designed. Feasibility of the proposed scheme is proven in theory. Moreover, two numerical examples are presented, using the energy resource system and Lü's system [Physica A 382 (2007) 672] as the nodes of the networks. GPS between two energy resource complex networks with time-varying coupling delay is achieved. This study can widen the application range of the generalized synchronization methods and will be instructive for the demand-supply of energy resource in some regions of China.
Wu, Yuanyuan; Cao, Jinde; Li, Qingbo; Alsaedi, Ahmed; Alsaadi, Fuad E
2017-01-01
This paper deals with the finite-time synchronization problem for a class of uncertain coupled switched neural networks under asynchronous switching. By constructing appropriate Lyapunov-like functionals and using the average dwell time technique, some sufficient criteria are derived to guarantee the finite-time synchronization of considered uncertain coupled switched neural networks. Meanwhile, the asynchronous switching feedback controller is designed to finite-time synchronize the concerned networks. Finally, two numerical examples are introduced to show the validity of the main results. Copyright © 2016 Elsevier Ltd. All rights reserved.
Adaptive Synchronization between Two Different Complex Networks with Time-Varying Delay Coupling
Institute of Scientific and Technical Information of China (English)
CHEN Jian-Rui; JIAO Li-Cheng; WU Jian-She; WANG Xiao-Hua
2009-01-01
A new general network model for two complex networks with time-varying delay coupling is presented.Then we investigate its synchronization phenomena.The two complex networks of the model differ in dynamic nodes,the number of nodes and the coupling connections.By using adaptive controllers,a synchronization criterion is derived.Numerical examples are given to demonstrate the effectiveness of the obtained synchronization criterion.This study may widen the application range of synchronization,such as in chaotic secure communication.
A novel framework of classical and quantum prisoner's dilemma games on coupled networks.
Deng, Xinyang; Zhang, Qi; Deng, Yong; Wang, Zhen
2016-03-15
Evolutionary games on multilayer networks are attracting growing interest. While among previous studies, the role of quantum games in such a infrastructure is still virgin and may become a fascinating issue across a myriad of research realms. To mimick two kinds of different interactive environments and mechanisms, in this paper a new framework of classical and quantum prisoner's dilemma games on two-layer coupled networks is considered. Within the proposed model, the impact of coupling factor of networks and entanglement degree in quantum games on the evolutionary process has been studied. Simulation results show that the entanglement has no impact on the evolution of the classical prisoner's dilemma, while the rise of the coupling factor obviously impedes cooperation in this game, and the evolution of quantum prisoner's dilemma is greatly impacted by the combined effect of entanglement and coupling.
A novel framework of classical and quantum prisoner’s dilemma games on coupled networks
Deng, Xinyang; Zhang, Qi; Deng, Yong; Wang, Zhen
2016-03-01
Evolutionary games on multilayer networks are attracting growing interest. While among previous studies, the role of quantum games in such a infrastructure is still virgin and may become a fascinating issue across a myriad of research realms. To mimick two kinds of different interactive environments and mechanisms, in this paper a new framework of classical and quantum prisoner’s dilemma games on two-layer coupled networks is considered. Within the proposed model, the impact of coupling factor of networks and entanglement degree in quantum games on the evolutionary process has been studied. Simulation results show that the entanglement has no impact on the evolution of the classical prisoner’s dilemma, while the rise of the coupling factor obviously impedes cooperation in this game, and the evolution of quantum prisoner’s dilemma is greatly impacted by the combined effect of entanglement and coupling.
The role of coupling-frequency weighting exponent on synchronization of a power network
Yang, Li-xin; Jiang, Jun
2016-12-01
Second-order Kuramoto-like oscillators with dissimilar natural frequencies are used as a coarse-scale model for an electrical power network that contains generators and consumers. This paper proposes a new power network model with coupling-frequency weighting exponent. Furthermore, the influence of the weighting exponent on synchronization of a power network is investigated through numerical simulations. It is observed that the synchronizability is significantly influenced by the coupling-frequency weighting coefficient with different magnitude categories. Furthermore, the synchronization cost caused by phase differences of power plants on the synchronization of the proposed power network model is studied. Numerical simulation shows that the synchronization cost will get larger with the coupling-frequency weighting exponent increasing further.
Indian Academy of Sciences (India)
Suman Acharyya; R E Amritkar
2015-02-01
The extension of the master stability function (MSF) to analyse stability of generalized synchronization for coupled nearly identical oscillators is discussed. The nearly identical nature of the coupled oscillators is due to some parameter mismatch while the dynamical equations are the same for all the oscillators. From the stability criteria of the MSF, we construct optimal networks with better synchronization property, i.e., the synchronization is stable for widest possible range of coupling parameters. In the optimized networks the nodes with parameter value at one extreme are selected as hubs. The pair of nodes with larger parameter difference are preferred to create links in the optimized networks, and the optimized networks are found to be disassortative in nature, i.e., the nodes with high degree tend to connect with nodes with low degree.
Network analysis of perception-action coupling in infants
Directory of Open Access Journals (Sweden)
Naama eRotem-Kohavi
2014-04-01
Full Text Available The functional networks that support action observation are of great interest in understanding the development of social cognition and motor learning. How infants learn to represent and understand the world around them remains one of the most intriguing questions in developmental cognitive neuroscience. Recently, mathematical measures derived from graph theory have been used to study connectivity networks in the developing brain. Thus far, this type of analysis in infancy has only been applied to the resting state. In this study, we recorded electroencephalography (EEG from infants (ages 4-11 months of age and adults while they observed three types of actions: a reaching for an object, b walking and c object motion. Graph theory based analysis was applied to these data to evaluate changes in brain networks. Global metrics that provide measures of the structural properties of the network (characteristic path, density, global efficiency, and modularity were calculated for each group and for each condition. We found statistically significant differences in measures for the observation of walking condition only. Specifically, in comparison to adults, infants showed increased density and global efficiency in combination with decreased modularity during observation of an action that is not within their motor repertoire (i.e. independent walking, suggesting a less structured organization. There were no group differences in global metric measures for observation of object motion or for observation of actions that are within the repertoire of infants (i.e. reaching. These preliminary results suggest that infants and adults may share a basic functional network for action observation that is sculpted by experience. Motor experience may lead to a shift towards a more efficient functional network.
Analysis of Cell Load Coupling for LTE Network Planning and Optimization
Siomina, Iana
2012-01-01
System-centric modeling and analysis are of key significance in planning and optimizing cellular networks. In this paper, we provide a mathematical analysis of performance modeling for LTE networks. The system model characterizes the coupling relation between the cell load factors, taking into account non-uniform traffic demand and interference between the cells with arbitrary network topology. Solving the model enables a network-wide performance evaluation in resource consumption. We develop and prove both sufficient and necessary conditions for the feasibility of the load-coupling system, and provide results related to computational aspects for numerically approaching the solution. The theoretical findings are accompanied with experimental results to instructively illustrate the application in optimizing LTE network configuration.
Coherence resonance in globally coupled neuronal networks with different neuron numbers
Institute of Scientific and Technical Information of China (English)
Ning Wei-Lian; Zhang Zheng-Zhen; Zeng Shang-You; Luo Xiao-Shu; Hu Jin-Lin; Zeng Shao-Wen; Qiu Yi; Wu Hui-Si
2012-01-01
Because a brain consists of tremendous neuronal networks with different neuron numbers ranging from tens to tens of thousands,we study the coherence resonance due to ion channel noises in globally coupled neuronal networks with different neuron numbers.We confirm that for all neuronal networks with different neuron numbers there exist the array enhanced coherence resonance and the optimal synaptic conductance to cause the maximal spiking coherence.Furthermoremore,the enhancement effects of coupling on spiking coherence and on optimal synaptic conductance are almost the same,regardless of the neuron numbers in the neuronal networks.Therefore for all the neuronal networks with different neuron numbers in the brain,relative weak synaptic conductance (0.1 mS/cm2) is sufficient to induce the maximal spiking coherence and the best sub-threshold signal encoding.
Co-regulation of metabolic genes is better explained by flux coupling than by network distance.
Directory of Open Access Journals (Sweden)
Richard A Notebaart
2008-01-01
Full Text Available To what extent can modes of gene regulation be explained by systems-level properties of metabolic networks? Prior studies on co-regulation of metabolic genes have mainly focused on graph-theoretical features of metabolic networks and demonstrated a decreasing level of co-expression with increasing network distance, a naïve, but widely used, topological index. Others have suggested that static graph representations can poorly capture dynamic functional associations, e.g., in the form of dependence of metabolic fluxes across genes in the network. Here, we systematically tested the relative importance of metabolic flux coupling and network position on gene co-regulation, using a genome-scale metabolic model of Escherichia coli. After validating the computational method with empirical data on flux correlations, we confirm that genes coupled by their enzymatic fluxes not only show similar expression patterns, but also share transcriptional regulators and frequently reside in the same operon. In contrast, we demonstrate that network distance per se has relatively minor influence on gene co-regulation. Moreover, the type of flux coupling can explain refined properties of the regulatory network that are ignored by simple graph-theoretical indices. Our results underline the importance of studying functional states of cellular networks to define physiologically relevant associations between genes and should stimulate future developments of novel functional genomic tools.
Mao, Liang; Yang, Yan
2012-01-01
Human-disease interactions involve the transmission of infectious diseases among individuals and the practice of preventive behavior by individuals. Both infectious diseases and preventive behavior diffuse simultaneously through human networks and interact with one another, but few existing models have coupled them together. This article proposes a conceptual framework to fill this knowledge gap and illustrates the model establishment. The conceptual model consists of two networks and two diffusion processes. The two networks include: an infection network that transmits diseases and a communication network that channels inter-personal influence regarding preventive behavior. Both networks are composed of same individuals but different types of interactions. This article further introduces modeling approaches to formulize such a framework, including the individual-based modeling approach, network theory, disease transmission models and behavioral models. An illustrative model was implemented to simulate a coupled-diffusion process during an influenza epidemic. The simulation outcomes suggest that the transmission probability of a disease and the structure of infection network have profound effects on the dynamics of coupled-diffusion. The results imply that current models may underestimate disease transmissibility parameters, because human preventive behavior has not been considered. This issue calls for a new interdisciplinary study that incorporates theories from epidemiology, social science, behavioral science, and health psychology. Copyright © 2011 Elsevier Ltd. All rights reserved.
Coupling conditions for the shallow water equations on a network
Caputo, Jean-Guy; Gleyse, Bernard
2015-01-01
We study numerically and analytically how nonlinear shallow water waves propagate in a fork. Using a homothetic reduction procedure, conservation laws and numerical analysis in a 2D domain, we obtain angle dependent coupling conditions for the water height and the velocity. We compare these to the ones for a class of scalar nonlinear wave equations for which the angle plays no role.
Coupled interference based rate adaptation in ad hoc networks
CSIR Research Space (South Africa)
Awuor, F
2011-09-01
Full Text Available on Karush-Kuhn-Tucker (KKT) conditions. The users determine data rates based on their local observations (i.e. coupled interference). Both pricing and limited message passing mechanisms are employed in the NUM wherein pricing restrict users from self...
Switching dynamics of single and coupled VO2-based oscillators as elements of neural networks
Velichko, Andrey; Belyaev, Maksim; Putrolaynen, Vadim; Pergament, Alexander; Perminov, Valentin
2017-01-01
In the present paper, we report on the switching dynamics of both single and coupled VO2-based oscillators, with resistive and capacitive coupling, and explore the capability of their application in oscillatory neural networks. Based on these results, we further select an adequate SPICE model to describe the modes of operation of coupled oscillator circuits. Physical mechanisms influencing the time of forward and reverse electrical switching, that determine the applicability limits of the proposed model, are identified. For the resistive coupling, it is shown that synchronization takes place at a certain value of the coupling resistance, though it is unstable and a synchronization failure occurs periodically. For the capacitive coupling, two synchronization modes, with weak and strong coupling, are found. The transition between these modes is accompanied by chaotic oscillations. A decrease in the width of the spectrum harmonics in the weak-coupling mode, and its increase in the strong-coupling one, is detected. The dependences of frequencies and phase differences of the coupled oscillatory circuits on the coupling capacitance are found. Examples of operation of coupled VO2 oscillators as a central pattern generator are demonstrated.
Reconfiguration of Intrinsic Functional Coupling Patterns Following Circumscribed Network Lesions.
Eldaief, Mark C; McMains, Stephanie; Hutchison, R Matthew; Halko, Mark A; Pascual-Leone, Alvaro
2016-05-25
Communication between cortical regions is necessary for optimal cognitive processing. Functional relationships between cortical regions can be inferred through measurements of temporal synchrony in spontaneous activity patterns. These relationships can be further elaborated by surveying effects of cortical lesions upon inter-regional connectivity. Lesions to cortical hubs and heteromodal association regions are expected to induce distributed connectivity changes and higher-order cognitive deficits, yet their functional consequences remain relatively unexplored. Here, we used resting-state fMRI to investigate intrinsic functional connectivity (FC) and graph theoretical metrics in 12 patients with circumscribed lesions of the medial prefrontal cortex (mPFC) portion of the Default Network (DN), and compared these metrics with those observed in healthy matched comparison participants and a sample of 1139 healthy individuals. Despite significant mPFC destruction, patients did not demonstrate weakened intrinsic FC among undamaged DN nodes. Instead, network-specific changes were manifested as weaker negative correlations between the DN and attentional and somatomotor networks. These findings conflict with the DN being a homogenous system functionally anchored at mPFC. Rather, they implicate a role for mPFC in mediating cross-network functional interactions. More broadly, our data suggest that lesions to association cortical hubs might induce clinical deficits by disrupting communication between interacting large-scale systems.
Coupling production networks and regional assets in manufacturing clusters
L.M. da Costa Monteiro de Carvalho (Luís); W. van Winden (Willem)
2007-01-01
textabstractParadoxically, the ongoing process of globalisation goes hand in hand with a surge of interest in the ‘local’ sources of firm competitiveness. In this paper, we develop a frame of analysis that helps to understand ‘coupling’ of production networks and regional development. Our aim is to
Compressive sensing reconstruction of feed-forward connectivity in pulse-coupled nonlinear networks
Barranca, Victor J.; Zhou, Douglas; Cai, David
2016-06-01
Utilizing the sparsity ubiquitous in real-world network connectivity, we develop a theoretical framework for efficiently reconstructing sparse feed-forward connections in a pulse-coupled nonlinear network through its output activities. Using only a small ensemble of random inputs, we solve this inverse problem through the compressive sensing theory based on a hidden linear structure intrinsic to the nonlinear network dynamics. The accuracy of the reconstruction is further verified by the fact that complex inputs can be well recovered using the reconstructed connectivity. We expect this Rapid Communication provides a new perspective for understanding the structure-function relationship as well as compressive sensing principle in nonlinear network dynamics.
Compressive sensing reconstruction of feed-forward connectivity in pulse-coupled nonlinear networks.
Barranca, Victor J; Zhou, Douglas; Cai, David
2016-06-01
Utilizing the sparsity ubiquitous in real-world network connectivity, we develop a theoretical framework for efficiently reconstructing sparse feed-forward connections in a pulse-coupled nonlinear network through its output activities. Using only a small ensemble of random inputs, we solve this inverse problem through the compressive sensing theory based on a hidden linear structure intrinsic to the nonlinear network dynamics. The accuracy of the reconstruction is further verified by the fact that complex inputs can be well recovered using the reconstructed connectivity. We expect this Rapid Communication provides a new perspective for understanding the structure-function relationship as well as compressive sensing principle in nonlinear network dynamics.
Li, Qun; Zheng, Chen-Guang; Cheng, Ning; Wang, Yi-Yi; Yin, Tao; Zhang, Tao
2016-06-01
An increasing number of studies pays attention to cross-frequency coupling in neuronal oscillations network, as it is considered to play an important role in exchanging and integrating of information. In this study, two generalized algorithms, phase-amplitude coupling-evolution map approach and phase-amplitude coupling-conditional mutual information which have been developed and applied originally in an identical rhythm, are generalized to measure cross-frequency coupling. The effectiveness of quantitatively distinguishing the changes of coupling strength from the measurement of phase-amplitude coupling (PAC) is demonstrated based on simulation data. The data suggest that the generalized algorithms are able to effectively evaluate the strength of PAC, which are consistent with those traditional approaches, such as PAC-PLV and PAC-MI. Experimental data, which are local field potentials obtained from anaesthetized SD rats, have also been analyzed by these two generalized approaches. The data show that the theta-low gamma PAC in the hippocampal CA3-CA1 network is significantly decreased in the glioma group compared to that in the control group. The results, obtained from either simulation data or real experimental signals, are consistent with that of those traditional approaches PAC-MI and PAC-PLV. It may be considered as a proper indicator for the cross frequency coupling in sub-network, such as the hippocampal CA3 and CA1.
Photomechanically coupled viscoelasticity of azobenzene polyimide polymer networks
Roberts, Dennice; Worden, Matt; Chowdhury, Sadiyah; Oates, William S.
2017-07-01
Polyimide-based azobenzene polymer networks have demonstrated superior photomechanical performance over more conventional azobenzene-doped pendent and cross-linked polyacrylate networks. These materials exhibit larger yield stress and glass transition temperatures and thus provide robustness for active control of adaptive structures directly with polarized, visible light. Whereas photochemical reactions clearly lead to deformation, as indicated by a rotation of a linear polarized light source, temperature and viscoelasticity can also influence deformation and complicate interpretation of the photostrictive and shape memory constitutive behavior. To better understand this behavior we develop a rate-dependent constitutive model and experimentally quantify the material behavior in these materials. The rate dependent deformation induced in these materials is quantified experimentally through photomechanical stress measurements and infrared camera measurements. Bayesian uncertainty analysis is used to assess the role of internal polymer network evolution and azobenzene excitation on both thermomechanical and photomechanical deformation in the presence polarized light of different orientations. A modified Arrhenius relation is proposed and validated using Bayesian statistics which provide connections between free volume, shape memory, and polarized light.
Synchrony and chaos in coupled oscillators and neural networks
Raghavachari, Sridhar
1999-09-01
This dissertation studies the dynamics of ensembles of coupled, dynamical elements with discrete and continuous time dynamics. Specific problems include the appearance of synchronous behavior in an ensemble of dynamical elements. We show that the dynamics of coupled map lattices with connectivity that scales with inter-site distance exhibit a transition from spatial disorder to spatially uniform temporal chaos as the scaling varies. We investigate the eigenvalue spectrum of the stochastic matrix characterizing fluctuations from the uniform state numerically and show that the spectrum is bounded, real and the largest eigenvalue (corresponding to the uniform solution) has a gap separating it from the remaining N-1 eigenvalues which correspond to non-uniform solutions. The width of this gap depends on the scaling exponent. We relate the stability of the uniform state to this gap and show that the state is globally stable even in a strongly chaotic region of the uncoupled map. Bursting is a prototypical pattern of voltage oscillations of membrane potentials of biological cells, where the membrane potential alternates between fast oscillations and a slow drift. These complex oscillations arise as a result of interactions between the kinetics of fast and slow ion channels. While bursting in isolated cells Is, well understood, the study of populations of interacting bursters is less developed. We study a one- dimensional continuum model of bursting and show that a spatial wave of bursting separating active and quiescent cells extinguishes synchronous bursting when the coupling is weak. This result places bounds on the measured values of coupling strength between secretory cells in the pancreas. The interactions of cellular and synaptic mechanisms acting on several timescales control rhythmic behavior in animals, such as locomotion, digestion and respiration. We explore a simple rhythmic circuit model with two cells reciprocally inhibiting each other with fast and slow
Effect of Coupling on the Epidemic Threshold in Interconnected Complex Networks: A Spectral Analysis
Sahneh, Faryad Darabi; Chowdhury, Fahmida N
2012-01-01
In epidemic modeling, the term infection strength indicates the ratio of infection rate and cure rate. If the infection strength is higher than a certain threshold -- which we define as the epidemic threshold - then the epidemic spreads through the population and persists in the long run. For a single generic graph representing the contact network of the population under consideration, the epidemic threshold turns out to be equal to the inverse of the spectral radius of the contact graph. However, in a real world scenario it is not possible to isolate a population completely: there is always some interconnection with another network, which partially overlaps with the contact network. Results for epidemic threshold in interconnected networks are limited to homogeneous mixing populations and degree distribution arguments. In this paper, we adopt a spectral approach. We show how the epidemic threshold in a given network changes as a result of being coupled with another network with fixed infection strength. In o...
Weight Identification of a Weighted Bipartite Graph Complex Dynamical Network with Coupling Delay
Directory of Open Access Journals (Sweden)
Jia Zhen
2010-01-01
Full Text Available Abstract We propose a network model, a weighted bipartite complex dynamical network with coupling delay, and present a scheme for identifying the weights of the network. Based on adaptive synchronization technique, weight trackers are designed for identifying the edge weights between nodes of the network by monitoring the dynamical evolution of the synchronous networks with drive-response structure. The conclusion is proved theoretically by Lyapunovs stability theory and LaSalle's invariance principle. Compared with the similar works, taking into consideration the structural characteristics of the network, the tracking devices designed in our paper are more effective and more easy to implement. Finally, numerical simulations show the effectiveness of the proposed method.
Experimental observation of chimera and cluster states in a minimal globally coupled network
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Hart, Joseph D. [Institute for Research in Electronics and Applied Physics, University of Maryland, College Park, Maryland 20742 (United States); Department of Physics, University of Maryland, College Park, Maryland 20742 (United States); Bansal, Kanika [Department of Mathematics, University at Buffalo, SUNY Buffalo, New York 14260 (United States); US Army Research Laboratory, Aberdeen Proving Ground, Maryland 21005 (United States); Murphy, Thomas E. [Institute for Research in Electronics and Applied Physics, University of Maryland, College Park, Maryland 20742 (United States); Department of Electrical and Computer Engineering, University of Maryland, College Park, Maryland 20742 (United States); Roy, Rajarshi [Institute for Research in Electronics and Applied Physics, University of Maryland, College Park, Maryland 20742 (United States); Department of Physics, University of Maryland, College Park, Maryland 20742 (United States); Institute for Physical Science and Technology, University of Maryland, College Park, Maryland 20742 (United States)
2016-09-15
A “chimera state” is a dynamical pattern that occurs in a network of coupled identical oscillators when the symmetry of the oscillator population is broken into synchronous and asynchronous parts. We report the experimental observation of chimera and cluster states in a network of four globally coupled chaotic opto-electronic oscillators. This is the minimal network that can support chimera states, and our study provides new insight into the fundamental mechanisms underlying their formation. We use a unified approach to determine the stability of all the observed partially synchronous patterns, highlighting the close relationship between chimera and cluster states as belonging to the broader phenomenon of partial synchronization. Our approach is general in terms of network size and connectivity. We also find that chimera states often appear in regions of multistability between global, cluster, and desynchronized states.
Lag Synchronization of Memristor-Based Coupled Neural Networks via ω-Measure.
Li, Ning; Cao, Jinde
2016-03-01
This paper deals with the lag synchronization problem of memristor-based coupled neural networks with or without parameter mismatch using two different algorithms. Firstly, we consider the memristor-based neural networks with parameter mismatch, lag complete synchronization cannot be achieved due to parameter mismatch, the concept of lag quasi-synchronization is introduced. Based on the ω-measure method and generalized Halanay inequality, the error level is estimated, a new lag quasi-synchronization scheme is proposed to ensure that coupled memristor-based neural networks are in a state of lag synchronization with an error level. Secondly, by constructing Lyapunov functional and applying common Halanary inequality, several lag complete synchronization criteria for the memristor-based neural networks with parameter match are given, which are easy to verify. Finally, two examples are given to illustrate the effectiveness of the proposed lag quasi-synchronization or lag complete synchronization criteria, which well support theoretical results.
Spin-glass phase in a neutral network with asymmetric couplings
Kree, R.; Widmaier, D.; Zippelius, A.
1988-12-01
The author studies the phase diagram of a neural network model which has learnt with the ADALINE algorithm, starting from tabula non rasa conditions. The resulting synaptic efficacies are not symmetric under an exchange of the pre- and post-synaptic neuron. In contrast to several other models which have been discussed in the literature, he finds a spin-glass phase in the asymmetrically coupled network. The main difference compared with the other models consists of long-ranged Gaussian correlations in the ensemble of couplings.
Marinelli, Dimitri; Aquilanti, Vincenzo; Anderson, Roger W; Bitencourt, Ana Carla P; Ragni, Mirco
2014-01-01
A unified vision of the symmetric coupling of angular momenta and of the quantum mechanical volume operator is illustrated. The focus is on the quantum mechanical angular momentum theory of Wigner's 6j symbols and on the volume operator of the symmetric coupling in spin network approaches: here, crucial to our presentation are an appreciation of the role of the Racah sum rule and the simplification arising from the use of Regge symmetry. The projective geometry approach permits the introduction of a symmetric representation of a network of seven spins or angular momenta. Results of extensive computational investigations are summarized, presented and briefly discussed.
Institute of Scientific and Technical Information of China (English)
王延敏; 姚平经
2003-01-01
In this paper, a new approach using artificial neural network and genetic algorithm for the optimization of the thermally coupled distillation is presented. Mathematical model can be constructed with artificial neural network based on the simulation results with ASPEN PLUS. Modified genetic algorithm was used to optimize the model. With the proposed model and optimization arithmetic, mathematical model can be calculated, decision variables and target value can be reached automatically and quickly. A practical example is used to demonstrate the algorithm.
Chai, Yuan; Chen, Li-Qun
2014-03-01
In this paper, we propose a novel approach for simultaneously identifying unknown parameters and synchronizing time-delayed complex community networks with nonidentical nodes. Based on the LaSalle's invariance principle, a criterion is established by constructing an effective control identification scheme and adjusting automatically the adaptive coupling strength. The proposed control law is applied to a complex community network which is periodically synchronized with different chaotic states. Numerical simulations are conducted to demonstrate the feasibility of the proposed method.
Synchronization of time-delay chaotic systems on small-world networks with delayed coupling
Institute of Scientific and Technical Information of China (English)
Qi Wei; Wang Ying-Hai
2009-01-01
By using the well-known Ikeda model as the node dynamics,this paper studies synchronization of time-delay systems on small-world networks where the connections between units involve time delays.It shows that,in contrast with the undelayed case,networks with delays can actually synchronize more easily.Specifically,for randomly distributed delays,time-delayed mutual coupling suppresses the chaotic behaviour by stabilizing a fixed point that is unstable for the uncoupled dynamical system.
Synchronization criteria for coupled Hopfield neural networks with time-varying delays
Institute of Scientific and Technical Information of China (English)
M.J. Park; O.M. Kwon; Ju H. Park; S.M. Lee; E.J. Cha
2011-01-01
This paper proposes new delay-dependent synchronization criteria for coupled Hopfield neural networks with time-varying delays.By construction of a suitable Lyapunov-Krasovskii's functional and use of Finsler's lemma,novel synchronization criteria for the networks are established in terms of linear matrix inequalities (LMIs) which can be easily solved by various effective optimization algorithms.Two numerical examples are given to illustrate the effectiveness of the proposed methods.
Exacerbated vulnerability of coupled socio-economic risk in complex networks
Zhang, Xin; Feng, Ling; Berman, Yonatan; Hu, Ning; Stanley, H. Eugene
2016-10-01
The study of risk contagion in economic networks has most often focused on the financial liquidities of institutions and assets. In practice the agents in a network affect each other through social contagion, i.e., through herd behavior and the tendency to follow leaders. We study the coupled risk between social and economic contagion and find it significantly more severe than when economic risk is considered alone. Using the empirical network from the China venture capital market we find that the system exhibits an extreme risk of abrupt phase transition and large-scale damage, which is in clear contrast to the smooth phase transition traditionally observed in economic contagion alone. We also find that network structure impacts market resilience and that the randomization of the social network of the market participants can reduce system fragility when there is herd behavior. Our work indicates that under coupled contagion mechanisms network resilience can exhibit a fundamentally different behavior, i.e., an abrupt transition. It also reveals the extreme risk when a system has coupled socio-economic risks, and this could be of interest to both policy makers and market practitioners.
Directory of Open Access Journals (Sweden)
Jian-An Wang
2014-01-01
Full Text Available The sampled-data synchronization problem for complex networks with random coupling strengths, probabilistic time-varying coupling delay, and distributed delay (mixed delays is investigated. The sampling period is assumed to be time varying and bounded. By using the properties of random variables and input delay approach, new synchronization error dynamics are constructed. Based on the delay decomposition method and reciprocally convex approach, a delay-dependent mean square synchronization condition is established in terms of linear matrix inequalities (LMIs. According to the proposed condition, an explicit expression for a set of desired sampled-data controllers can be achieved by solving LMIs. Numerical examples are given to demonstrate the effectiveness of the theoretical results.
Coevolution of synchronization and cooperation in networks of coupled oscillators
Antonioni, Alberto
2016-01-01
Despite the large number of studies on the framework of synchronization, none of the previous research made the hypothesis that synchronization occurs at a given cost for involved individuals. The introduction of costly interactions leads, instead, to the formulation of a dichotomous scenario in which an individual may decide to cooperate and pay the cost in order to get synchronized with the rest of the population. Alternatively, the same individual can decide to free ride, without incurring in any cost, waiting that others get synchronized to her state. The emergence of synchronization may thus be seen as the byproduct of an evolutionary game in which individuals decide their behavior according to the benefit/cost ratio they receive in the past. We study the onset of cooperation/synchronization in networked populations of Kuramoto oscillators and report how topology is essential in order for cooperation to thrive. We display also how different classes of topology foster differently synchronization both at a...
Coupling effect of nodes popularity and similarity on social network persistence
Jin, Xiaogang; Jin, Cheng; Huang, Jiaxuan; Min, Yong
2017-02-01
Network robustness represents the ability of networks to withstand failures and perturbations. In social networks, maintenance of individual activities, also called persistence, is significant towards understanding robustness. Previous works usually consider persistence on pre-generated network structures; while in social networks, the network structure is growing with the cascading inactivity of existed individuals. Here, we address this challenge through analysis for nodes under a coevolution model, which characterizes individual activity changes under three network growth modes: following the descending order of nodes’ popularity, similarity or uniform random. We show that when nodes possess high spontaneous activities, a popularity-first growth mode obtains highly persistent networks; otherwise, with low spontaneous activities, a similarity-first mode does better. Moreover, a compound growth mode, with the consecutive joining of similar nodes in a short period and mixing a few high popularity nodes, obtains the highest persistence. Therefore, nodes similarity is essential for persistent social networks, while properly coupling popularity with similarity further optimizes the persistence. This demonstrates the evolution of nodes activity not only depends on network topology, but also their connective typology.
Modeling synchronization in networks of delay-coupled fiber ring lasers.
Lindley, Brandon S; Schwartz, Ira B
2011-11-21
We study the onset of synchronization in a network of N delay-coupled stochastic fiber ring lasers with respect to various parameters when the coupling power is weak. In particular, for groups of three or more ring lasers mutually coupled to a central hub laser, we demonstrate a robust tendency toward out-of-phase (achronal) synchronization between the N-1 outer lasers and the single inner laser. In contrast to the achronal synchronization, we find the outer lasers synchronize with zero-lag (isochronal) with respect to each other, thus forming a set of N-1 coherent fiber lasers. © 2011 Optical Society of America
Feedback control design for the complete synchronisation of two coupled Boolean networks
Li, Fangfei
2016-09-01
In the literatures, to design state feedback controllers to make the response Boolean network synchronise with the drive Boolean network is rarely considered. Motivated by this, feedback control design for the complete synchronisation of two coupled Boolean networks is investigated in this paper. A necessary condition for the existence of a state feedback controller achieving the complete synchronisation is established first. Then, based on the necessary condition, the feedback control law is proposed. Finally, an example is worked out to illustrate the proposed design procedure.
Self-organized synchronous oscillations in a network of excitable cells coupled by gap junctions.
Lewis, T J; Rinzel, J
2000-11-01
Recent evidence suggests that electrical coupling plays a role in generating oscillatory behaviour in networks of neurons; however, the underlying mechanisms have not been identified. Using a cellular automata model proposed by Traub et al (Traub R D, Schmitz D, Jefferys J G and Draguhn A 1999 High-frequency population oscillations are predicted to occur in hippocampal pyramidal neural networks interconnected by axo-axonal gap junctions Neuroscience 92 407-26), we describe a novel mechanism for self-organized oscillations in networks that have strong, sparse random electrical coupling via gap junctions. The network activity is generated by random spontaneous activity that is moulded into regular population oscillations by the propagation of activity through the network. We explain how this activity gives rise to particular dependences of mean oscillation frequency on network connectivity parameters and on the rate of spontaneous activity, and we derive analytical expressions to approximate the mean frequency and variance of the oscillations. In doing so, we provide insight into possible mechanisms for frequency control and modulation in networks of neurons.
Modeling networks of coupled enzymatic reactions using the total quasi-steady state approximation.
Directory of Open Access Journals (Sweden)
Andrea Ciliberto
2007-03-01
Full Text Available In metabolic networks, metabolites are usually present in great excess over the enzymes that catalyze their interconversion, and describing the rates of these reactions by using the Michaelis-Menten rate law is perfectly valid. This rate law assumes that the concentration of enzyme-substrate complex (C is much less than the free substrate concentration (S0. However, in protein interaction networks, the enzymes and substrates are all proteins in comparable concentrations, and neglecting C with respect to S0 is not valid. Borghans, DeBoer, and Segel developed an alternative description of enzyme kinetics that is valid when C is comparable to S0. We extend this description, which Borghans et al. call the total quasi-steady state approximation, to networks of coupled enzymatic reactions. First, we analyze an isolated Goldbeter-Koshland switch when enzymes and substrates are present in comparable concentrations. Then, on the basis of a real example of the molecular network governing cell cycle progression, we couple two and three Goldbeter-Koshland switches together to study the effects of feedback in networks of protein kinases and phosphatases. Our analysis shows that the total quasi-steady state approximation provides an excellent kinetic formalism for protein interaction networks, because (1 it unveils the modular structure of the enzymatic reactions, (2 it suggests a simple algorithm to formulate correct kinetic equations, and (3 contrary to classical Michaelis-Menten kinetics, it succeeds in faithfully reproducing the dynamics of the network both qualitatively and quantitatively.
Lagrangian Modeling and Control of Switching Networks with Integrated Coupled Magnetics
Scherpen, Jacquelien M.A.; Jeltsema, Dimitri; Klaassens, J. Ben
2000-01-01
In this paper a method is presented to build an Euler-Lagrange model for electrical networks, including switches and integrated (non-ideal) coupled-magnetics, in a structured general way. One of the advantages of emphasizing the physical structure of these systems is its functionality during the
Expansion of Elderly Couples' IADL Caregiver Networks beyond the Marital Dyad
Feld, Sheila; Dunkle, Ruth E.; Schroepfer, Tracy; Shen, Huei-Wern
2006-01-01
Factors influencing expansion of instrumental activities of daily living (IADL) caregiver networks beyond the spouse/partner were studied, using data from the Asset and Health Dynamics among the Oldest Old (AHEAD) nationally representative sample of American elders (ages 70 and older). Analyses were based on 427 Black and White couples in which…
Lagrangian Modeling and Control of Switching Networks with Integrated Coupled Magnetics
Scherpen, Jacquelien M.A.; Jeltsema, Dimitri; Klaassens, J. Ben
2000-01-01
In this paper a method is presented to build an Euler-Lagrange model for electrical networks, including switches and integrated (non-ideal) coupled-magnetics, in a structured general way. One of the advantages of emphasizing the physical structure of these systems is its functionality during the con
Towards a precise measurement of the top quark Yukawa coupling at the ILC
Energy Technology Data Exchange (ETDEWEB)
Juste, A.
2005-12-01
A precise measurement of the top quark Yukawa coupling is of great importance, since it may shed light on the mechanism of EWSB. We study the prospects of such measurement during the first phase of the ILC at {radical}s = 500 GeV, focusing in particular on recent theoretical developments as well as the potential benefits of beam polarization. It is shown that both yield improvements that could possibly lead to a measurement competitive with the LHC.
Spatiotemporal Dynamics of a Network of Coupled Time-Delay Digital Tanlock Loops
Paul, Bishwajit; Banerjee, Tanmoy; Sarkar, B. C.
The time-delay digital tanlock loop (TDTLs) is an important class of phase-locked loop that is widely used in electronic communication systems. Although nonlinear dynamics of an isolated TDTL has been studied in the past but the collective behavior of TDTLs in a network is an important topic of research and deserves special attention as in practical communication systems separate entities are rarely isolated. In this paper, we carry out the detailed analysis and numerical simulations to explore the spatiotemporal dynamics of a network of a one-dimensional ring of coupled TDTLs with nearest neighbor coupling. The equation representing the network is derived and we carry out analytical calculations using the circulant matrix formalism to obtain the stability criteria. An extensive numerical simulation reveals that with the variation of gain parameter and coupling strength the network shows a variety of spatiotemporal dynamics such as frozen random pattern, pattern selection, spatiotemporal intermittency and fully developed spatiotemporal chaos. We map the distinct dynamical regions of the system in two-parameter space. Finally, we quantify the spatiotemporal dynamics by using quantitative measures like Lyapunov exponent and the average quadratic deviation of the full network.
Cascading failures in coupled networks with both inner-dependency and inter-dependency links.
Liu, Run-Ran; Li, Ming; Jia, Chun-Xiao; Wang, Bing-Hong
2016-05-04
We study the percolation in coupled networks with both inner-dependency and inter-dependency links, where the inner- and inter-dependency links represent the dependencies between nodes in the same or different networks, respectively. We find that when most of dependency links are inner- or inter-ones, the coupled networks system is fragile and makes a discontinuous percolation transition. However, when the numbers of two types of dependency links are close to each other, the system is robust and makes a continuous percolation transition. This indicates that the high density of dependency links could not always lead to a discontinuous percolation transition as the previous studies. More interestingly, although the robustness of the system can be optimized by adjusting the ratio of the two types of dependency links, there exists a critical average degree of the networks for coupled random networks, below which the crossover of the two types of percolation transitions disappears, and the system will always demonstrate a discontinuous percolation transition. We also develop an approach to analyze this model, which is agreement with the simulation results well.
Wu, Xiangjun; Lu, Hongtao
2010-08-01
In this Letter, generalized projective synchronization (GPS) between two different complex dynamical networks with delayed coupling is investigated. Two complex networks are distinct if they have diverse node dynamics, or different number of nodes, or different topological structures. By using the adaptive control scheme, a sufficient synchronization criterion for this GPS is derived based on the LaSalle invariance principle. Three corollaries are also obtained. It is noticed that the synchronization speed sensitively depends on the adjustable positive constants μ. Furthermore, the coupling configuration matrix is not necessary to be symmetric or irreducible, and the inner coupling matrix need not be symmetric. In addition, the node dynamic need not satisfy the very strong and conservative uniformly Lipschitz condition. Numerical simulations further demonstrate the feasibility and effectiveness of the theoretical results.
Energy Technology Data Exchange (ETDEWEB)
Wu Xiangjun, E-mail: wuhsiang@yahoo.c [Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240 (China); Institute of Complex Intelligent Network System, Henan University, Kaifeng 475004 (China); Computing Center, Henan University, Kaifeng 475004 (China); Lu Hongtao [Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240 (China)
2010-08-23
In this Letter, generalized projective synchronization (GPS) between two different complex dynamical networks with delayed coupling is investigated. Two complex networks are distinct if they have diverse node dynamics, or different number of nodes, or different topological structures. By using the adaptive control scheme, a sufficient synchronization criterion for this GPS is derived based on the LaSalle invariance principle. Three corollaries are also obtained. It is noticed that the synchronization speed sensitively depends on the adjustable positive constants {mu}{sub i}. Furthermore, the coupling configuration matrix is not necessary to be symmetric or irreducible, and the inner coupling matrix need not be symmetric. In addition, the node dynamic need not satisfy the very strong and conservative uniformly Lipschitz condition. Numerical simulations further demonstrate the feasibility and effectiveness of the theoretical results.
Impact of pore size variability and network coupling on electrokinetic transport in porous media
Alizadeh, Shima; Bazant, Martin Z.; Mani, Ali
2016-11-01
We have developed and validated an efficient and robust computational model to study the coupled fluid and ion transport through electrokinetic porous media, which are exposed to external gradients of pressure, electric potential, and concentration. In our approach a porous media is modeled as a network of many pores through which the transport is described by the coupled Poisson-Nernst-Planck-Stokes equations. When the pore sizes are random, the interactions between various modes of transport may provoke complexities such as concentration polarization shocks and internal flow circulations. These phenomena impact mixing and transport in various systems including deionization and filtration systems, supercapacitors, and lab-on-a-chip devices. In this work, we present simulations of massive networks of pores and we demonstrate the impact of pore size variation, and pore-pore coupling on the overall electrokinetic transport in porous media.
Pinning cluster synchronization in an array of coupled neural networks under event-based mechanism.
Li, Lulu; Ho, Daniel W C; Cao, Jinde; Lu, Jianquan
2016-04-01
Cluster synchronization is a typical collective behavior in coupled dynamical systems, where the synchronization occurs within one group, while there is no synchronization among different groups. In this paper, under event-based mechanism, pinning cluster synchronization in an array of coupled neural networks is studied. A new event-triggered sampled-data transmission strategy, where only local and event-triggering states are utilized to update the broadcasting state of each agent, is proposed to realize cluster synchronization of the coupled neural networks. Furthermore, a self-triggered pinning cluster synchronization algorithm is proposed, and a set of iterative procedures is given to compute the event-triggered time instants. Hence, this will reduce the computational load significantly. Finally, an example is given to demonstrate the effectiveness of the theoretical results.
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Abbiendi, G.; Braibant, S.; Capiluppi, P.; Ciocca, C.; Cuffiani, M.; Dallavalle, M.; Fabbri, F.; Giacomelli, G.; Giacomelli, P.; Mader, W.; Mes, H.; Renkel, P. [Univ. di Bologna (Italy); INFN, Bologna (Italy); Ainsley, C.; Batley, R.J.; Carter, J.R.; Hill, J.C.; Tasevsky, M.; Voss, H.; Vossebeld, J. [Cavendish Lab., Cambridge (United Kingdom); Aakesson, P.F.; Barberio, E.; Burckhart, H.J.; Roeck, A. de; Wolf, E.A. de; Ferrari, P.; Frey, A.; Gruwe, M.; Hauschild, M.; Hawkings, R.; Heuer, R.D.; McKenna, J.; Neal, H.A.; Pilcher, J.E.; Plane, D.E.; Przybycien, M.; Quadt, A.; Sachs, K.; Schaile, A.D.; Scharff-Hansen, P.; Schieck, J.; Schumacher, M.; Sherwood, P.; Stroehmer, R.; Torrence, E.; Vertesi, R.; Verzocchi, M.; Watson, A.T.; Watson, N.K. [European Organisation for Nuclear Research, CERN, Geneva 23 (Switzerland); Alexander, G.; Bella, G.; Etzion, E.; Grunhaus, J.; Trigger, I. [Tel Aviv Univ., Dept. of Physics and Astronomy, Tel Aviv (Israel); Anagnostou, G.; Bell, P.J.; Charlton, D.G.; Hawkes, C.M.; Jovanovic, P.; Nanjo, H.; Trocsanyi, Z.; Ward, C.P.; Ward, D.R.; Watkins, P.M.; Wermes, N. [Univ. of Birmingham, School of Physics and Astronomy, Birmingham (United Kingdom); Anderson, K.J.; Gupta, A.; Meijers, F.; O' Neale, S.W.; Pasztor, G.; Sobie, R.; Tarem, S. [Univ. of Chicago, Enrico Fermi Inst. and Dept. of Physics, Chicago, IL (United States); Asai, S.; Ishii, K.; Kanzaki, J.; Kawagoe, K.; Kawamoto, T.; Kobayashi, T.; Komamiya, S.; Martin, A.J.; Meyer, N.; Miller, D.J.; Mutter, A.; Nagai, K.; Oh, A.; Runge, K.; Thomson, M.A.; Tsur, E.; Wolf, G. [Univ. of Tokyo (Japan); Kobe Univ. (Japan); Axen, D.; Loebinger, F.K.; Mashimo, T. [Univ. of British Columbia, Dept. of Physics, Vancouver, BC (Canada); Bailey, I.; Karlen, D.; Keeler, R.K.; Maettig, P.; Rembser, C.; Skuja, A. [Univ. of Victoria (Canada); Barillari, T.; Bethke, S.; Kluth, S.; Oreglia, M.J.; Pooth, O.; Schaile, O. [Max-Planck-Inst. fuer Physik, Muenchen (Germany)] [and others
2011-09-15
Hadronic event shape distributions from e{sup +}e{sup -} annihilation measured by the OPAL experiment at centre-of-mass energies between 91 GeV and 209 GeV are used to determine the strong coupling {alpha}{sub S}. The results are based on QCD predictions complete to the next-to-next-to-leading order (NNLO), and on NNLO calculations matched to the resummed next-to-leading-log-approximation terms (NNLO + NLLA). The combined NNLO result from all variables and centre-of-mass energies is while the combined NNLO + NLLA result is The completeness of the NNLO and NNLO + NLLA results with respect to missing higher order contributions, studied by varying the renormalization scale, is improved compared to previous results based on NLO or NLO + NLLA predictions only. The observed energy dependence of {alpha}{sub S} agrees with the QCD prediction of asymptotic freedom and excludes the absence of running. (orig.)
Tang, Ze; Park, Ju H.; Lee, Tae H.
2016-10-01
This paper is devoted to the cluster synchronization issue of nonlinearly coupled Lur'e networks under the distributed adaptive pinning control strategy. The time-varying delayed networks consisted of identical and nonidentical Lur'e systems are discussed respectively by applying the edge-based pinning control scheme. In each cluster, the edges belonging to the spanning tree are pinned. In view of the nonlinearly couplings of the networks, for the first time, an efficient distributed nonlinearly adaptive update law based on the local information of the dynamical behaviors of node is proposed. Sufficient criteria for the achievement of cluster synchronization are derived based on S-procedure, Kronecker product and Lyapunov stability theory. Additionally, some illustrative examples are provided to demonstrate the effectiveness of the theoretical results.
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Chatrchyan, S.; Khachatryan, V.; Sirunyan, A.M. [Yerevan Physics Institute, Yerevan (Armenia)] [and others; Collaboration: The CMS Collaboration
2012-11-15
A study of dijet production in proton-proton collisions was performed at {radical}s=7 TeV for jets with p{sub T}>35 GeV and vertical stroke y vertical stroke <4.7 using data collected with the CMS detector at the LHC in 2010. Events with at least one pair of jets are denoted as ''inclusive''. Events with exactly one pair of jets are called ''exclusive''. The ratio of the cross section of all pairwise combinations of jets to the exclusive dijet cross section as a function of the rapidity difference between jets vertical stroke {Delta}y vertical stroke is measured for the first time up to vertical stroke {Delta}y vertical stroke =9.2. The ratio of the cross section for the pair consisting of the most forward and the most backward jet from the inclusive sample to the exclusive dijet cross section is also presented. The predictions of the Monte Carlo event generators pythia6 and pythia8 agree with the measurements. In both ratios the herwig++ generator exhibits a more pronounced rise versus vertical stroke {Delta}y vertical stroke than observed in the data. The BFKL-motivated generators cascade and hej+ariadne predict for these ratios a significantly stronger rise than observed. (orig.)
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Zimmermann, Simone
2013-08-15
This dissertation presents a search for long-lived, multi-charged particles using the ATLAS detector at the LHC. Motivation for this search arose from an unexploited search regime at ATLAS of stable massive particles with electric charges of vertical stroke q vertical stroke = 2e to vertical stroke q vertical stroke = 5e. Additional motivation can be found in several beyond the Standard Model physics theories. Proton-proton collisions recorded during the 2011 LHC running at {radical}(s)=7 TeV, corresponding to an integrated luminosity of 4.4 fb{sup -1}, are examined in a signature-based analysis. The search seeks out charged particle tracks exhibiting anomalously high ionization consistent with stable massive particles with electric charges in the range from vertical stroke q vertical stroke =2e to vertical stroke q vertical stroke =6e. For this search, new variables of specific energy loss per path length dE/dx are used in the candidate selection. One of these variables, the TRT dE/dx, is developed in the course of this thesis and is described in detail. No excess is observed with respect to the prediction of Standard Model processes. The 95% C.L. upper cross section limits are also interpreted as mass exclusion limits for a simplified Drell-Yan production model.
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Grudberg, P.M. [California Univ., Berkeley, CA (United States)
1997-12-31
This thesis reports on the measurement of the W and Z boson inclusive production cross sections ({sigma}{sub W} and {sigma}{sub Z}) times electronic branching ratios (Br(W {yields} e{nu}) and Br(Z {yields} ee)) in p{anti p} collisions at {radical}s = 1.8 TeV. The analysis is based on 12.8 pb{sup -1} of data taken in the 1992-1993 run by the D0 detector at the Fermilab Tevatron collider; the cross sections were measured to be: {sigma}{sub W} {center_dot} Br(W {yields} e{nu}) = 2. 36 {+-} 0.02 {+-} 0.07 {+-} 0.13 nb and {sigma}{sub Z} {center_dot} Br(Z {yields} ee) = 0.218 {+-} 0.008 {+-} 0.008 {+-} 0.012 nb. The first error is statistical, the second error represents the non- luminosity systematic error, and the third error shows the uncertainty in the luminosity determination. Future prospects for similar measurements based on larger samples of data are discussed.
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Schreiber, C.; Werner, K.; Aichelin, J. [Universite de Nantes, SUBATECH (France)
2012-05-15
Based on results obtained with event generators we have launched the core-corona model. It describes in a simplified way but quite successfully the centrality dependence of multiplicity and
of identified particles observed in heavy-ion reactions at beam energies between {radical}s = 17 and 200 GeV. Also the centrality dependence of the elliptic flow, {upsilon}{sub 2}, for all charged and identified particles could be explained in this model. Here we extend this analysis and study the centrality dependence of single-particle spectra of K{sup -} and p-bar measured by the PHENIX, STAR, and BRAHMS Collaborations. We find that also for these particles the analysis of the spectra in the core-corona model suffers from differences in the data published by the different experimental groups, notably for the pp collisions. As for protons and K{sup +}, for each experience the data agree well with the prediction of the core-corona model but the values of the two necessary parameters depend on the experiments. We show as well that the average momentum as a function of the centrality depends in a very sensitive way on the particle species and may be quite different for particles which have about the same mass. Therefore the idea to interpret this centrality dependence as a consequence of a collective expansion of the system, as done in blast way fits, may be premature.
Energy Technology Data Exchange (ETDEWEB)
Aaij, R. [Nikhef National Institute for Subatomic Physics, Amsterdam (Netherlands); Abellan Beteta, C. [Universitat de Barcelona, Barcelona (Spain); Adeva, B. [Universidad de Santiago de Compostela, Santiago de Compostela (Spain); Adinolfi, M. [H.H. Wills Physics Laboratory, University of Bristol, Bristol (United Kingdom); Adrover, C. [CPPM, Aix-Marseille Universite, CNRS/IN2P3, Marseille (France); Affolder, A. [Oliver Lodge Laboratory, University of Liverpool, Liverpool (United Kingdom); Ajaltouni, Z. [Clermont Universite, Universite Blaise Pascal, CNRS/IN2P3, LPC, Clermont-Ferrand (France); Albrecht, J.; Alessio, F. [European Organization for Nuclear Research (CERN), Geneva (Switzerland); Alexander, M. [School of Physics and Astronomy, University of Glasgow, Glasgow (United Kingdom); Alkhazov, G. [Petersburg Nuclear Physics Institute (PNPI), Gatchina (Russian Federation); Alvarez Cartelle, P. [Universidad de Santiago de Compostela, Santiago de Compostela (Spain); Alves, A.A. [Sezione INFN di Roma La Sapienza, Roma (Italy); Amato, S. [Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro (Brazil); Amhis, Y. [Ecole Polytechnique Federale de Lausanne (EPFL), Lausanne (Switzerland); Anderson, J. [Physik-Institut, Universitaet Zuerich, Zuerich (Switzerland); Appleby, R.B. [School of Physics and Astronomy, University of Manchester, Manchester (United Kingdom); Aquines Gutierrez, O. [Max-Planck-Institut fuer Kernphysik (MPIK), Heidelberg (Germany); Archilli, F. [Laboratori Nazionali dell' INFN di Frascati, Frascati (Italy); European Organization for Nuclear Research (CERN), Geneva (Switzerland); Arrabito, L. [CC-IN2P3, CNRS/IN2P3, Lyon-Villeurbanne (France); and others
2012-08-14
The prompt production of the charmonium {chi}{sub c1} and {chi}{sub c2} mesons has been studied in proton-proton collisions at the Large Hadron Collider at a centre-of-mass energy of {radical}(s)=7 TeV. The {chi}{sub c} mesons are identified through their decays {chi}{sub c}{yields}J/{psi}{gamma} with J/{psi}{yields}{mu}{sup +}{mu}{sup -} using 36 pb{sup -1} of data collected by the LHCb detector in 2010. The ratio of the prompt production cross-sections for the two {chi}{sub c} spin states, {sigma}({chi}{sub c2})/{sigma}({chi}{sub c1}), has been determined as a function of the J/{psi} transverse momentum, p{sub T}{sup J/{psi}}, in the range from 2 to 15 GeV/c. The results are in agreement with the next-to-leading order non-relativistic QCD model at high p{sub T}{sup J/{psi}} and lie consistently above the pure leading-order colour-singlet prediction.
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Klute, M.
2004-02-01
A preliminary measurement of the t anti t production cross section at {radical}s=1.96 TeV is presented. The {mu}-plus-jets final state is analyzed in a data sample of 94 pb{sup -1} and a total of 14 events are selected with a background expectation of 11.7{+-}1.9 events. The measurement yields: {sigma}{sub p} {sub anti} {sub p{yields}}{sub t} {sub anti} {sub t+X}=2.4{sub -3.5}{sup +4.2}(stat.){sub -2.6}{sup +2.5}(syst.){+-}0.3(lumi.) pb. The analysis, being part of a larger effort to re-observe the top quark in Tevatron Run II data and to measure the production cross section, is combined with results from the available analysis channels. The combined result yields: {sigma}{sub p} {sub anti} {sub p{yields}}{sub t} {sub anti} {sub t+X}=8.1{sub -2.0}{sup +2.2}(stat.){sub -1.4}{sup +1.6}(syst.){+-}0.8(lumi.) pb.
Sparse networks of directly coupled, polymorphic, and functional side chains in allosteric proteins.
Soltan Ghoraie, Laleh; Burkowski, Forbes; Zhu, Mu
2015-03-01
Recent studies have highlighted the role of coupled side-chain fluctuations alone in the allosteric behavior of proteins. Moreover, examination of X-ray crystallography data has recently revealed new information about the prevalence of alternate side-chain conformations (conformational polymorphism), and attempts have been made to uncover the hidden alternate conformations from X-ray data. Hence, new computational approaches are required that consider the polymorphic nature of the side chains, and incorporate the effects of this phenomenon in the study of information transmission and functional interactions of residues in a molecule. These studies can provide a more accurate understanding of the allosteric behavior. In this article, we first present a novel approach to generate an ensemble of conformations and an efficient computational method to extract direct couplings of side chains in allosteric proteins, and provide sparse network representations of the couplings. We take the side-chain conformational polymorphism into account, and show that by studying the intrinsic dynamics of an inactive structure, we are able to construct a network of functionally crucial residues. Second, we show that the proposed method is capable of providing a magnified view of the coupled and conformationally polymorphic residues. This model reveals couplings between the alternate conformations of a coupled residue pair. To the best of our knowledge, this is the first computational method for extracting networks of side chains' alternate conformations. Such networks help in providing a detailed image of side-chain dynamics in functionally important and conformationally polymorphic sites, such as binding and/or allosteric sites. © 2014 Wiley Periodicals, Inc.
Schreiter, Juerg; Ramacher, Ulrich; Heittmann, Arne; Matolin, Daniel; Schuffny, Rene
2004-05-01
We present a cellular pulse coupled neural network with adaptive weights and its analog VLSI implementation. The neural network operates on a scalar image feature, such as grey scale or the output of a spatial filter. It detects segments and marks them with synchronous pulses of the corresponding neurons. The network consists of integrate-and-fire neurons, which are coupled to their nearest neighbors via adaptive synaptic weights. Adaptation follows either one of two empirical rules. Both rules lead to spike grouping in wave like patterns. This synchronous activity binds groups of neurons and labels the corresponding image segments. Applications of the network also include feature preserving noise removal, image smoothing, and detection of bright and dark spots. The adaptation rules are insensitive for parameter deviations, mismatch and non-ideal approximation of the implied functions. That makes an analog VLSI implementation feasible. Simulations showed no significant differences in the synchronization properties between networks using the ideal adaptation rules and networks resembling implementation properties such as randomly distributed parameters and roughly implemented adaptation functions. A prototype is currently being designed and fabricated using an Infineon 130nm technology. It comprises a 128 × 128 neuron array, analog image memory, and an address event representation pulse output.
Predictors of coupling between structural and functional cortical networks in normal aging.
Romero-Garcia, Rafael; Atienza, Mercedes; Cantero, Jose L
2014-06-01
Understanding how the mammalian neocortex creates cognition largely depends on knowledge about large-scale cortical organization. Accumulated evidence has illuminated cortical substrates of cognition across the lifespan, but how topological properties of cortical networks support structure-function relationships in normal aging remains an open question. Here we investigate the role of connections (i.e., short/long and direct/indirect) and node properties (i.e., centrality and modularity) in predicting functional-structural connectivity coupling in healthy elderly subjects. Connectivity networks were derived from correlations of cortical thickness and cortical glucose consumption in resting state. Local-direct connections (i.e., nodes separated by less than 30 mm) and node modularity (i.e., a set of nodes highly interconnected within a topological community and sparsely interconnected with nodes from other modules) in the functional network were identified as the main determinants of coupling between cortical networks, suggesting that the structural network in aging is mainly constrained by functional topological properties involved in the segregation of information, likely due to aging-related deficits in functional integration. This hypothesis is supported by an enhanced connectivity between cortical regions of different resting-state networks involved in sensorimotor and memory functions in detrimental to associations between fronto-parietal regions supporting executive processes. Taken collectively, these findings open new avenues to identify aging-related failures in the anatomo-functional organization of the neocortical mantle, and might contribute to early detection of prevalent neurodegenerative conditions occurring in the late life.
Hofman, Erwin
2010-01-01
Collaborative innovation projects that involve suppliers, customers, and sometimes even competitors can be a challenging undertaking. Nonetheless, specialization and organizational loose coupling makes companies increasingly dependent upon resources that are only externally available. This study foc
Mori, Hiroki; Okuyama, Yuji; Asada, Minoru
2017-01-01
Chaotic itinerancy is a phenomenon in which the state of a nonlinear dynamical system spontaneously explores and attracts certain states in a state space. From this perspective, the diverse behavior of animals and its spontaneous transitions lead to a complex coupled dynamical system, including a physical body and a brain. Herein, a series of simulations using different types of non-linear oscillator networks (i.e., regular, small-world, scale-free, random) with a musculoskeletal model (i.e., a snake-like robot) as a physical body are conducted to understand how the chaotic itinerancy of bodily behavior emerges from the coupled dynamics between the body and the brain. A behavior analysis (behavior clustering) and network analysis for the classified behavior are then applied. The former consists of feature vector extraction from the motions and classification of the movement patterns that emerged from the coupled dynamics. The network structures behind the classified movement patterns are revealed by estimating the “information networks” different from the given non-linear oscillator networks based on the transfer entropy which finds the information flow among neurons. The experimental results show that: (1) the number of movement patterns and their duration depend on the sensor ratio to control the balance of strength between the body and the brain dynamics and on the type of the given non-linear oscillator networks; and (2) two kinds of information networks are found behind two kinds movement patterns with different durations by utilizing the complex network measures, clustering coefficient and the shortest path length with a negative and a positive relationship with the duration periods of movement patterns. The current results seem promising for a future extension of the method to a more complicated body and environment. Several requirements are also discussed. PMID:28796797
Xu, Yong; Lu, Renquan; Shi, Peng; Tao, Jie; Xie, Shengli
2017-01-24
This paper studies the issue of robust state estimation for coupled neural networks with parameter uncertainty and randomly occurring distributed delays, where the polytopic model is employed to describe the parameter uncertainty. A set of Bernoulli processes with different stochastic properties are introduced to model the randomly occurrences of the distributed delays. Novel state estimators based on the local coupling structure are proposed to make full use of the coupling information. The augmented estimation error system is obtained based on the Kronecker product. A new Lyapunov function, which depends both on the polytopic uncertainty and the coupling information, is introduced to reduce the conservatism. Sufficient conditions, which guarantee the stochastic stability and the l₂-l∞ performance of the augmented estimation error system, are established. Then, the estimator gains are further obtained on the basis of these conditions. Finally, a numerical example is used to prove the effectiveness of the results.
The antiferromagnetic cross-coupled spin ladder: Quantum fidelity and tensor networks approach
Chen, Xi-Hao; Cho, Sam Young; Zhou, Huan-Qiang; Batchelor, Murray T.
2016-05-01
We investigate the phase diagram of the cross-coupled Heisenberg spin ladder with antiferromagnetic couplings. For this model, the results for the existence of the columnar dimer phase, which was predicted on the basis of weak coupling field theory renormalization group arguments, have been conflicting. The numerical work on this model has been based on various approaches, including exact diagonalization, series expansions and density-matrix renormalization group calculations. Using the recently-developed tensor network states and groundstate fidelity approach for quantum spin ladders, we find no evidence for the existence of the columnar dimer phase. We also provide an argument based on the symmetry of the Hamiltonian, which suggests that the phase diagram for antiferromagnetic couplings consists of a single line separating the rung-singlet and the Haldane phases.
Average Synchronization and Temporal Order in a Noisy Neuronal Network with Coupling Delay
Institute of Scientific and Technical Information of China (English)
WANG Qing-Yun; DUAN Zhi-Sheng; LU Qi-Shao
2007-01-01
Average synchronization and temporal order characterized by the rate of firing are studied in a spatially extended network system with the coupling time delay, which is locally modelled by a two-dimensional Rulkov map neuron.It is shown that there exists an optimal noise level, where average synchronization and temporal order are maximum irrespective of the coupling time delay. Furthermore, it is found that temporal order is weakened when the coupling time delay appears. However, the coupling time delay has a twofold effect on average synchronization,one associated with its increase, the other with its decrease. This clearly manifests that random perturbations and time delay play a complementary role in synchronization and temporal order.
Recovery of couplings and parameters of elements in networks of time-delay systems from time series
Sysoev, I. V.; Ponomarenko, V. I.; Kulminskiy, D. D.; Prokhorov, M. D.
2016-11-01
We propose a method for the recovery of coupling architecture and the parameters of elements in networks consisting of coupled oscillators described by delay-differential equations. For each oscillator in the network, we introduce an objective function characterizing the distance between the points of the reconstructed nonlinear function. The proposed method is based on the minimization of this objective function and the separation of the recovered coupling coefficients into significant and insignificant coefficients. The efficiency of the method is shown for chaotic time series generated by model equations of diffusively coupled time-delay systems and for experimental chaotic time series gained from coupled electronic oscillators with time-delayed feedback.
Picallo, Clara B.; Riecke, Hermann
2011-03-01
Motivated by recent observations in neuronal systems we investigate all-to-all networks of nonidentical oscillators with adaptive coupling. The adaptation models spike-timing-dependent plasticity in which the sum of the weights of all incoming links is conserved. We find multiple phase-locked states that fall into two classes: near-synchronized states and splay states. Among the near-synchronized states are states that oscillate with a frequency that depends only very weakly on the coupling strength and is essentially given by the frequency of one of the oscillators, which is, however, neither the fastest nor the slowest oscillator. In sufficiently large networks the adaptive coupling is found to develop effective network topologies dominated by one or two loops. This results in a multitude of stable splay states, which differ in their firing sequences. With increasing coupling strength their frequency increases linearly and the oscillators become less synchronized. The essential features of the two classes of states are captured analytically in perturbation analyses of the extended Kuramoto model used in the simulations.
Lossouarn, B.; Deü, J.-F.; Aucejo, M.; Cunefare, K. A.
2016-11-01
Multimodal damping can be achieved by coupling a mechanical structure to an electrical network exhibiting similar modal properties. Focusing on a plate, a new topology for such an electrical analogue is found from a finite difference approximation of the Kirchhoff-Love theory and the use of the direct electromechanical analogy. Discrete models based on element dynamic stiffness matrices are proposed to simulate square plate unit cells coupled to their electrical analogues through two-dimensional piezoelectric transducers. A setup made of a clamped plate covered with an array of piezoelectric patches is built in order to validate the control strategy and the numerical models. The analogous electrical network is implemented with passive components as inductors, transformers and the inherent capacitance of the piezoelectric patches. The effect of the piezoelectric coupling on the dynamics of the clamped plate is significant as it creates the equivalent of a multimodal tuned mass damping. An adequate tuning of the network then yields a broadband vibration reduction. In the end, the use of an analogous electrical network appears as an efficient solution for the multimodal control of a plate.
Experimental mapping of nonlinear dynamics in synchronized coupled semiconductor laser networks
Argyris, Apostolos; Bourmpos, Michail; Syvridis, Dimitris
2015-05-01
The potential of conventional semiconductor lasers to generate complex and chaotic dynamics at a bandwidth that extends up to tens of GHz turns them into useful components in applications oriented to sensing and security. Specifically, latest theoretical and experimental works have demonstrated the capability of mutually coupled semiconductor lasers to exhibit a joint behaviour under various conditions. In an uncoupled network consisting of N similar SLs - representing autonomous nodes in the network - each node emits an optical signal of various dynamics depending on its biasing conditions and internal properties. These nodes remain unsynchronized unless appropriate coupling and biasing conditions apply. A synchronized behaviour can be in principle observed in sub-groups of lasers or in the overall laser network. In the present work, experimental topologies that employ eight SLs, under diverse biasing and coupling conditions, are built and investigated. The deployed systems incorporate off-the-shelf fiber-optic communications components operating at the 1550nm spectral window. The role of emission wavelength detuning of each participating node in the network - at GHz level - is evaluated.
Large-Scale Brain Network Coupling Predicts Total Sleep Deprivation Effects on Cognitive Capacity.
Directory of Open Access Journals (Sweden)
Yu Lei
Full Text Available Interactions between large-scale brain networks have received most attention in the study of cognitive dysfunction of human brain. In this paper, we aimed to test the hypothesis that the coupling strength of large-scale brain networks will reflect the pressure for sleep and will predict cognitive performance, referred to as sleep pressure index (SPI. Fourteen healthy subjects underwent this within-subject functional magnetic resonance imaging (fMRI study during rested wakefulness (RW and after 36 h of total sleep deprivation (TSD. Self-reported scores of sleepiness were higher for TSD than for RW. A subsequent working memory (WM task showed that WM performance was lower after 36 h of TSD. Moreover, SPI was developed based on the coupling strength of salience network (SN and default mode network (DMN. Significant increase of SPI was observed after 36 h of TSD, suggesting stronger pressure for sleep. In addition, SPI was significantly correlated with both the visual analogue scale score of sleepiness and the WM performance. These results showed that alterations in SN-DMN coupling might be critical in cognitive alterations that underlie the lapse after TSD. Further studies may validate the SPI as a potential clinical biomarker to assess the impact of sleep deprivation.
Noise-sustained synchronization between electrically coupled FitzHugh-Nagumo networks
Cascallares, Guadalupe; Sánchez, Alejandro D.; dell'Erba, Matías G.; Izús, Gonzalo G.
2015-09-01
We investigate the capability of electrical synapses to transmit the noise-sustained network activity from one network to another. The particular setup we consider is two identical rings with excitable FitzHugh-Nagumo cell dynamics and nearest-neighbor antiphase intra-ring coupling, electrically coupled between corresponding nodes. The whole system is submitted to independent local additive Gaussian white noises with common intensity η, but only one ring is externally forced by a global adiabatic subthreshold harmonic signal. We then seek conditions for a particular noise level to promote synchronized stable firing patterns. By running numerical integrations with increasing η, we observe the excitation activity to become spatiotemporally self-organized, until η is so strong that spoils sync between networks for a given value of the electric coupling strength. By means of a four-cell model and calculating the stationary probability distribution, we obtain a (signal-dependent) non-equilibrium potential landscape which explains qualitatively the observed regimes, and whose barrier heights give a good estimate of the optimal noise intensity for the sync between networks.
Directory of Open Access Journals (Sweden)
Xinsong Yang
2013-01-01
Full Text Available This paper investigates global synchronization in an array of coupled neural networks with time-varying delays and unbounded distributed delays. In the coupled neural networks, limited transmission efficiency between coupled nodes, which makes the model more practical, is considered. Based on a novel integral inequality and the Lyapunov functional method, sufficient synchronization criteria are derived. The derived synchronization criteria are formulated by linear matrix inequalities (LMIs and can be easily verified by using Matlab LMI Toolbox. It is displayed that, when some of the transmission efficiencies are limited, the dynamics of the synchronized state are different from those of the isolated node. Furthermore, the transmission efficiency and inner coupling matrices between nodes play important roles in the final synchronized state. The derivative of the time-varying delay can be any given value, and the time-varying delay can be unbounded. The outer-coupling matrices can be symmetric or asymmetric. Numerical simulations are finally given to demonstrate the effectiveness of the theoretical results.
Energy Technology Data Exchange (ETDEWEB)
Gong Yubing, E-mail: gongyubing09@hotmail.co [School of Physics, Ludong University, Yantai 264025 (China); Xie Yanhang; Lin Xiu; Hao Yinghang; Ma Xiaoguang [School of Physics, Ludong University, Yantai 264025 (China)
2010-12-15
Research highlights: Chemical delay and chemical coupling can tame chaotic bursting. Chemical delay-induced transitions from bursting synchronization to intermittent multiple spiking synchronizations. Chemical coupling-induced different types of delay-dependent firing transitions. - Abstract: Chemical synaptic connections are more common than electric ones in neurons, and information transmission delay is especially significant for the synapses of chemical type. In this paper, we report a phenomenon of ordering spatiotemporal chaos and synchronization transitions by the delays and coupling through chemical synapses of modified Hodgkin-Huxley (MHH) neurons on scale-free networks. As the delay {tau} is increased, the neurons exhibit transitions from bursting synchronization (BS) to intermittent multiple spiking synchronizations (SS). As the coupling g{sub syn} is increased, the neurons exhibit different types of firing transitions, depending on the values of {tau}. For a smaller {tau}, there are transitions from spatiotemporal chaotic bursting (SCB) to BS or SS; while for a larger {tau}, there are transitions from SCB to intermittent multiple SS. These findings show that the delays and coupling through chemical synapses can tame the chaotic firings and repeatedly enhance the firing synchronization of neurons, and hence could play important roles in the firing activity of the neurons on scale-free networks.
Synchronous bursts on scale-free neuronal networks with attractive and repulsive coupling.
Directory of Open Access Journals (Sweden)
Qingyun Wang
Full Text Available This paper investigates the dependence of synchronization transitions of bursting oscillations on the information transmission delay over scale-free neuronal networks with attractive and repulsive coupling. It is shown that for both types of coupling, the delay always plays a subtle role in either promoting or impairing synchronization. In particular, depending on the inherent oscillation period of individual neurons, regions of irregular and regular propagating excitatory fronts appear intermittently as the delay increases. These delay-induced synchronization transitions are manifested as well-expressed minima in the measure for spatiotemporal synchrony. For attractive coupling, the minima appear at every integer multiple of the average oscillation period, while for the repulsive coupling, they appear at every odd multiple of the half of the average oscillation period. The obtained results are robust to the variations of the dynamics of individual neurons, the system size, and the neuronal firing type. Hence, they can be used to characterize attractively or repulsively coupled scale-free neuronal networks with delays.
Lane, Brian J; Samarth, Pranit; Ransdell, Joseph L; Nair, Satish S; Schulz, David J
2016-01-01
Motor neurons of the crustacean cardiac ganglion generate virtually identical, synchronized output despite the fact that each neuron uses distinct conductance magnitudes. As a result of this variability, manipulations that target ionic conductances have distinct effects on neurons within the same ganglion, disrupting synchronized motor neuron output that is necessary for proper cardiac function. We hypothesized that robustness in network output is accomplished via plasticity that counters such destabilizing influences. By blocking high-threshold K+ conductances in motor neurons within the ongoing cardiac network, we discovered that compensation both resynchronized the network and helped restore excitability. Using model findings to guide experimentation, we determined that compensatory increases of both GA and electrical coupling restored function in the network. This is one of the first direct demonstrations of the physiological regulation of coupling conductance in a compensatory context, and of synergistic plasticity across cell- and network-level mechanisms in the restoration of output. DOI: http://dx.doi.org/10.7554/eLife.16879.001 PMID:27552052
Haak, Danielle M; Fath, Brian D; Forbes, Valery E; Martin, Dustin R; Pope, Kevin L
2017-04-01
Network analysis is used to address diverse ecological, social, economic, and epidemiological questions, but few efforts have been made to combine these field-specific analyses into interdisciplinary approaches that effectively address how complex systems are interdependent and connected to one another. Identifying and understanding these cross-boundary connections improves natural resource management and promotes proactive, rather than reactive, decisions. This research had two main objectives; first, adapt the framework and approach of infectious disease network modeling so that it may be applied to the socio-ecological problem of spreading aquatic invasive species, and second, use this new coupled model to simulate the spread of the invasive Chinese mystery snail (Bellamya chinensis) in a reservoir network in Southeastern Nebraska, USA. The coupled model integrates an existing social network model of how anglers move on the landscape with new reservoir-specific ecological network models. This approach allowed us to identify 1) how angler movement among reservoirs aids in the spread of B. chinensis, 2) how B. chinensis alters energy flows within individual-reservoir food webs, and 3) a new method for assessing the spread of any number of non-native or invasive species within complex, social-ecological systems. Copyright © 2016 Elsevier Ltd. All rights reserved.
On Couple-Group Consensus of Multiagent Networks with Communication and Input Time Delays
Directory of Open Access Journals (Sweden)
Liang-hao Ji
2016-01-01
Full Text Available This paper investigated the couple-group consensus problems of the multiagent networks with the influence of communication and input time delays. Based on the frequency-domain theory, some algebraic criteria are addressed analytically. From the results, it is found that the input time delays and the coupling strengths between agents of the systems play a crucial role in reaching group consensus. The convergence of the system is independent of the communication delays, but it will affect the convergence rate of the system. Finally, several simulated examples are provided to verify the validity and correctness of our theoretical results.
The G Protein-Coupled Receptor Heterodimer Network (GPCR-HetNet and Its Hub Components
Directory of Open Access Journals (Sweden)
Dasiel O. Borroto-Escuela
2014-05-01
Full Text Available G protein-coupled receptors (GPCRs oligomerization has emerged as a vital characteristic of receptor structure. Substantial experimental evidence supports the existence of GPCR-GPCR interactions in a coordinated and cooperative manner. However, despite the current development of experimental techniques for large-scale detection of GPCR heteromers, in order to understand their connectivity it is necessary to develop novel tools to study the global heteroreceptor networks. To provide insight into the overall topology of the GPCR heteromers and identify key players, a collective interaction network was constructed. Experimental interaction data for each of the individual human GPCR protomers was obtained manually from the STRING and SCOPUS databases. The interaction data were used to build and analyze the network using Cytoscape software. The network was treated as undirected throughout the study. It is comprised of 156 nodes, 260 edges and has a scale-free topology. Connectivity analysis reveals a significant dominance of intrafamily versus interfamily connections. Most of the receptors within the network are linked to each other by a small number of edges. DRD2, OPRM, ADRB2, AA2AR, AA1R, OPRK, OPRD and GHSR are identified as hubs. In a network representation 10 modules/clusters also appear as a highly interconnected group of nodes. Information on this GPCR network can improve our understanding of molecular integration. GPCR-HetNet has been implemented in Java and is freely available at http://www.iiia.csic.es/~ismel/GPCR-Nets/index.html.
The G protein-coupled receptor heterodimer network (GPCR-HetNet) and its hub components.
Borroto-Escuela, Dasiel O; Brito, Ismel; Romero-Fernandez, Wilber; Di Palma, Michael; Oflijan, Julia; Skieterska, Kamila; Duchou, Jolien; Van Craenenbroeck, Kathleen; Suárez-Boomgaard, Diana; Rivera, Alicia; Guidolin, Diego; Agnati, Luigi F; Fuxe, Kjell
2014-05-14
G protein-coupled receptors (GPCRs) oligomerization has emerged as a vital characteristic of receptor structure. Substantial experimental evidence supports the existence of GPCR-GPCR interactions in a coordinated and cooperative manner. However, despite the current development of experimental techniques for large-scale detection of GPCR heteromers, in order to understand their connectivity it is necessary to develop novel tools to study the global heteroreceptor networks. To provide insight into the overall topology of the GPCR heteromers and identify key players, a collective interaction network was constructed. Experimental interaction data for each of the individual human GPCR protomers was obtained manually from the STRING and SCOPUS databases. The interaction data were used to build and analyze the network using Cytoscape software. The network was treated as undirected throughout the study. It is comprised of 156 nodes, 260 edges and has a scale-free topology. Connectivity analysis reveals a significant dominance of intrafamily versus interfamily connections. Most of the receptors within the network are linked to each other by a small number of edges. DRD2, OPRM, ADRB2, AA2AR, AA1R, OPRK, OPRD and GHSR are identified as hubs. In a network representation 10 modules/clusters also appear as a highly interconnected group of nodes. Information on this GPCR network can improve our understanding of molecular integration. GPCR-HetNet has been implemented in Java and is freely available at http://www.iiia.csic.es/~ismel/GPCR-Nets/index.html.
Persistent homology of time-dependent functional networks constructed from coupled time series
Stolz, Bernadette J.; Harrington, Heather A.; Porter, Mason A.
2017-04-01
We use topological data analysis to study "functional networks" that we construct from time-series data from both experimental and synthetic sources. We use persistent homology with a weight rank clique filtration to gain insights into these functional networks, and we use persistence landscapes to interpret our results. Our first example uses time-series output from networks of coupled Kuramoto oscillators. Our second example consists of biological data in the form of functional magnetic resonance imaging data that were acquired from human subjects during a simple motor-learning task in which subjects were monitored for three days during a five-day period. With these examples, we demonstrate that (1) using persistent homology to study functional networks provides fascinating insights into their properties and (2) the position of the features in a filtration can sometimes play a more vital role than persistence in the interpretation of topological features, even though conventionally the latter is used to distinguish between signal and noise. We find that persistent homology can detect differences in synchronization patterns in our data sets over time, giving insight both on changes in community structure in the networks and on increased synchronization between brain regions that form loops in a functional network during motor learning. For the motor-learning data, persistence landscapes also reveal that on average the majority of changes in the network loops take place on the second of the three days of the learning process.
Discrete fracture network modeling of hydraulic stimulation coupling flow and geomechanics
McClure, Mark
2013-01-01
Discrete Fracture Network Modeling of Hydraulic Stimulation describes the development and testing of a model that couples fluid-flow, deformation, friction weakening, and permeability evolution in large, complex two-dimensional discrete fracture networks. The model can be used to explore the behavior of hydraulic stimulation in settings where matrix permeability is low and preexisting fractures play an important role, such as Enhanced Geothermal Systems and gas shale. Used also to describe pure shear stimulation, mixed-mechanism stimulation, or pure opening-mode stimulation. A variety of nov
Comparison of Synchronization Ability of Four Types of Regular Coupled Networks
Institute of Scientific and Technical Information of China (English)
WANG Hai-Xia; LU Qi-Shao; SHI Xia
2012-01-01
We investigate the synchronization ability of four types of regular coupled networks. By introducing the proper error variables and Lyapunov functions, we turn the stability of synchronization manifold into that of null solution of error equations, further, into the negative definiteness of some symmetric matrices, thus we get the sufficient synchronization stability conditions. To test the valid of the results, we take the Chua's circuit as an example. Although the theoretical synchronization thresholds appear to be very conservative, they provide new insights about the influence of topology and scale of networks on synchronization, and that the theoretical results and our numerical simulations are consistent.
Synchronization of Coupled Oscillators on Newman-Watts Small-World Networks
Institute of Scientific and Technical Information of China (English)
GUAN Jian-Yue; XU Xin-Jian; WU Zhi-Xi; WANG Ying-Hai
2006-01-01
We investigate the collection behaviour of coupled phase oscillators on Newman- Watts small-world networks in one and two dimensions. Each component of the network is assumed as an oscillator and each interacts with the others following the Kuramoto model. We then study the onset of global synchronization of phases and frequencies based on dynamic simulations and finite-size scah'ng. Both the phase and frequency synchronization are observed to emerge in the presence of a tiny fraction of shortcuts and enhanced with the increases of nearest neighbours and lattice dimensions.
Wu, Yanan; Gong, Yubing; Xu, Bo
2013-12-01
Recently, multiple coherence resonance induced by time delay has been observed in neuronal networks with constant coupling strength. In this paper, by employing Newman-Watts Hodgkin-Huxley neuron networks with time-periodic coupling strength, we study how the temporal coherence of spiking behavior and coherence resonance by time delay change when the frequency of periodic coupling strength is varied. It is found that delay induced coherence resonance is dependent on periodic coupling strength and increases when the frequency of periodic coupling strength increases. Periodic coupling strength can also induce multiple coherence resonance, and the coherence resonance occurs when the frequency of periodic coupling strength is approximately multiple of the spiking frequency. These results show that for periodic coupling strength time delay can more frequently optimize the temporal coherence of spiking activity, and periodic coupling strength can repetitively optimize the temporal coherence of spiking activity as well. Frequency locking may be the mechanism for multiple coherence resonance induced by periodic coupling strength. These findings imply that periodic coupling strength is more efficient for enhancing the temporal coherence of spiking activity of neuronal networks, and thus it could play a more important role in improving the time precision of information processing and transmission in neural networks.
Energy Technology Data Exchange (ETDEWEB)
Li Yanlong [Institute of Theoretical Physics, Lanzhou University of Technology, Lanzhou 730050 (China) and Institute of Theoretical Physics, Lanzhou University, Lanzhou 730000 (China)], E-mail: liyl20031@126.com; Wu Min; Ma Jun [Institute of Theoretical Physics, Lanzhou University of Technology, Lanzhou 730050 (China); Chen Zhaoyang [Department of Chemistry, George Washington University, Washington, DC 20052 (United States); Wang Yinghai [Institute of Theoretical Physics, Lanzhou University, Lanzhou 730000 (China)
2009-02-15
A scheme of de-synchronization via pulse stimulation is numerically investigated in the Hindmarsh Rose globally coupled neural networks. The simulations show that synchronization evolves into de-synchronization in the globally coupled HR neural network when a part (about 10%) of neurons are stimulated with a pulse current signal. The network de-synchronization appears to be sensitive to the stimulation parameters. For the case of the same stimulation intensity, those weakly coupled networks reach de-synchronization more easily than strongly coupled networks. There exists a homologous asymptotic behavior in the region of higher frequency, and exist the optimal stimulation interval and period of continuous stimulation time when other stimulation parameters remain invariable.
Liang Xu; Junping Du; Qingping Li
2013-01-01
In the nonsubsampled contourlet transform (NSCT) domain, a novel image fusion algorithm based on the visual attention model and pulse coupled neural networks (PCNNs) is proposed. For the fusion of high-pass subbands in NSCT domain, a saliency-motivated PCNN model is proposed. The main idea is that high-pass subband coefficients are combined with their visual saliency maps as input to motivate PCNN. Coefficients with large firing times are employed as the fused high-pass subband coefficients. ...
Doshi, Urmi; Holliday, Michael J; Eisenmesser, Elan Z; Hamelberg, Donald
2016-04-26
Detailed understanding of how conformational dynamics orchestrates function in allosteric regulation of recognition and catalysis remains ambiguous. Here, we simulate CypA using multiple-microsecond-long atomistic molecular dynamics in explicit solvent and carry out NMR experiments. We analyze a large amount of time-dependent multidimensional data with a coarse-grained approach and map key dynamical features within individual macrostates by defining dynamics in terms of residue-residue contacts. The effects of substrate binding are observed to be largely sensed at a location over 15 Å from the active site, implying its importance in allostery. Using NMR experiments, we confirm that a dynamic cluster of residues in this distal region is directly coupled to the active site. Furthermore, the dynamical network of interresidue contacts is found to be coupled and temporally dispersed, ranging over 4 to 5 orders of magnitude. Finally, using network centrality measures we demonstrate the changes in the communication network, connectivity, and influence of CypA residues upon substrate binding, mutation, and during catalysis. We identify key residues that potentially act as a bottleneck in the communication flow through the distinct regions in CypA and, therefore, as targets for future mutational studies. Mapping these dynamical features and the coupling of dynamics to function has crucial ramifications in understanding allosteric regulation in enzymes and proteins, in general.
Tanaka, Manabu; Fujita, Remi; Nishide, Hiroyuki
2009-01-01
The novel gold nanoparticle, which was stabilized with pi-conjugated molecules bearing functional groups at the terminals, was prepared via conventional procedure by using 5-bromo-2,2'-bithiophene-5'-thiol as a stabilizer. The gold nanoparticle (ca. 3 nm-diameter) showed good dispersion stability in various organic solvents, and its electrochemical and spectroscopic study revealed peculiar properties originated in the pi-conjugated molecular stabilizer, bithiophene derivative. The Pd-catalyzed coupling reaction on the gold nanoparticle was first achieved by using the gold nanoparticle bearing bromo groups at the particle surface and the model boronic acid molecule, 5-formyl-2-thiopheneboronic acid, to yield the terthiophene derivatives on the gold nanoparticle. The 1H-NMR, UV, and TGA analysis supported the progress of the coupling reaction on the gold nanoparticle. This Pd-catalyzed coupling reaction was applied with the borate-terminated polythiophene to form polythiophene/gold nanoparticle alternate network film. The electron microscopic images supported the formation of the network structure. The high electric conductivity on the network film suggested that the conductive characteristic of the film originated from that of the pi-conjugated polythiophene backbone connected with the gold nanoparticle.
Lossouarn, B.; Aucejo, M.; Deü, J.-F.
2015-04-01
An elastic lattice of point masses can be a suitable representation of a continuous rod for the study of longitudinal wave propagation. By extrapolating the classical tuned mass damping strategy, a multimodal tuned mass damper is introduced from the coupling of two lattices having the same modal properties. The aim of the study is then to implement this multimodal control on a rod coupled to an electrical network. The electromechanical analogy applied to a lattice gives the required network, and the energy conversion is performed with piezoelectric patches. The coupled problem is modeled by a novel semi-continuous transfer matrix formulation, which is experimentally validated by a setup involving a rod equipped with 20 pairs of piezoelectric patches. The broadband efficiency of the multimodal control is also experimentally proved with vibration reductions up to 25 dB on the four first resonances of the rod. Finally, the practical interest of the network is pointed out, as it limits the required inductance. This is confirmed by the present purely passive setup that only involves standard low value inductors.
Systemic risk in multiplex networks with asymmetric coupling and threshold feedback
Burkholz, Rebekka; Garas, Antonios; Schweitzer, Frank
2015-01-01
We study cascades on a two-layer multiplex network, with asymmetric feedback that depends on the coupling strength between the layers. Based on an analytical branching process approximation, we calculate the systemic risk measured by the final fraction of failed nodes on a reference layer. The results are compared with the case of a single layer network that is an aggregated representation of the two layers. We find that systemic risk in the two-layer network is smaller than in the aggregated one only if the coupling strength between the two layers is small. Above a critical coupling strength, systemic risk is increased because of the mutual amplification of cascades in the two layers. We even observe sharp phase transitions in the cascade size that are less pronounced on the aggregated layer. Our insights can be applied to a scenario where firms decide whether they want to split their business into a less risky core business and a more risky subsidiary business. In most cases, this may lead to a drastic incr...
A Nanotechnology-Ready Computing Scheme based on a Weakly Coupled Oscillator Network
Vodenicarevic, Damir; Locatelli, Nicolas; Abreu Araujo, Flavio; Grollier, Julie; Querlioz, Damien
2017-01-01
With conventional transistor technologies reaching their limits, alternative computing schemes based on novel technologies are currently gaining considerable interest. Notably, promising computing approaches have proposed to leverage the complex dynamics emerging in networks of coupled oscillators based on nanotechnologies. The physical implementation of such architectures remains a true challenge, however, as most proposed ideas are not robust to nanotechnology devices’ non-idealities. In this work, we propose and investigate the implementation of an oscillator-based architecture, which can be used to carry out pattern recognition tasks, and which is tailored to the specificities of nanotechnologies. This scheme relies on a weak coupling between oscillators, and does not require a fine tuning of the coupling values. After evaluating its reliability under the severe constraints associated to nanotechnologies, we explore the scalability of such an architecture, suggesting its potential to realize pattern recognition tasks using limited resources. We show that it is robust to issues like noise, variability and oscillator non-linearity. Defining network optimization design rules, we show that nano-oscillator networks could be used for efficient cognitive processing. PMID:28322262
Systemic risk in multiplex networks with asymmetric coupling and threshold feedback
Burkholz, Rebekka; Leduc, Matt V.; Garas, Antonios; Schweitzer, Frank
2016-06-01
We study cascades on a two-layer multiplex network, with asymmetric feedback that depends on the coupling strength between the layers. Based on an analytical branching process approximation, we calculate the systemic risk measured by the final fraction of failed nodes on a reference layer. The results are compared with the case of a single layer network that is an aggregated representation of the two layers. We find that systemic risk in the two-layer network is smaller than in the aggregated one only if the coupling strength between the two layers is small. Above a critical coupling strength, systemic risk is increased because of the mutual amplification of cascades in the two layers. We even observe sharp phase transitions in the cascade size that are less pronounced on the aggregated layer. Our insights can be applied to a scenario where firms decide whether they want to split their business into a less risky core business and a more risky subsidiary business. In most cases, this may lead to a drastic increase of systemic risk, which is underestimated in an aggregated approach.
A Nanotechnology-Ready Computing Scheme based on a Weakly Coupled Oscillator Network
Vodenicarevic, Damir; Locatelli, Nicolas; Abreu Araujo, Flavio; Grollier, Julie; Querlioz, Damien
2017-03-01
With conventional transistor technologies reaching their limits, alternative computing schemes based on novel technologies are currently gaining considerable interest. Notably, promising computing approaches have proposed to leverage the complex dynamics emerging in networks of coupled oscillators based on nanotechnologies. The physical implementation of such architectures remains a true challenge, however, as most proposed ideas are not robust to nanotechnology devices’ non-idealities. In this work, we propose and investigate the implementation of an oscillator-based architecture, which can be used to carry out pattern recognition tasks, and which is tailored to the specificities of nanotechnologies. This scheme relies on a weak coupling between oscillators, and does not require a fine tuning of the coupling values. After evaluating its reliability under the severe constraints associated to nanotechnologies, we explore the scalability of such an architecture, suggesting its potential to realize pattern recognition tasks using limited resources. We show that it is robust to issues like noise, variability and oscillator non-linearity. Defining network optimization design rules, we show that nano-oscillator networks could be used for efficient cognitive processing.
Construction of a pulse-coupled dipole network capable of fear-like and relief-like responses
Lungsi Sharma, B.
2016-07-01
The challenge for neuroscience as an interdisciplinary programme is the integration of ideas among the disciplines to achieve a common goal. This paper deals with the problem of deriving a pulse-coupled neural network that is capable of demonstrating behavioural responses (fear-like and relief-like). Current pulse-coupled neural networks are designed mostly for engineering applications, particularly image processing. The discovered neural network was constructed using the method of minimal anatomies approach. The behavioural response of a level-coded activity-based model was used as a reference. Although the spiking-based model and the activity-based model are of different scales, the use of model-reference principle means that the characteristics that is referenced is its functional properties. It is demonstrated that this strategy of dissection and systematic construction is effective in the functional design of pulse-coupled neural network system with nonlinear signalling. The differential equations for the elastic weights in the reference model are replicated in the pulse-coupled network geometrically. The network reflects a possible solution to the problem of punishment and avoidance. The network developed in this work is a new network topology for pulse-coupled neural networks. Therefore, the model-reference principle is a powerful tool in connecting neuroscience disciplines. The continuity of concepts and phenomena is further maintained by systematic construction using methods like the method of minimal anatomies.
Sigvardt, K A; Miller, W L
1998-11-16
The primary functions of spinal locomotor central pattern generators (CPGs) are to provide oscillatory motor commands to individual joints or segments and to control the precise timing of those commands across all joints or segments for efficient, coordinated locomotor behavior. Our ability to understand the neuronal mechanisms underlying intersegmental coordination has been hampered by the complexity of propriospinal interconnectivity and the paucity of quantitative data on the magnitude and timing of those connections. Theoretical approaches have therefore been employed to discover general rules by which CPG-like oscillator systems must be constructed to produce appropriate coordinated locomotor behavior; the locomotor CPG is represented as a network of oscillators, where each oscillator generates local motor output and interoscillator coupling provides intersegmental coordination. Mathematical analysis of such coupled oscillator systems has provided a number of experimentally testable predictions regarding the link between coupling and coordination. Application of these network-level predictions to the results of electrophysiological experiments has required data analysis methods that can relate the behavior of the in vitro spinal cord to the variables employed by the mathematical model. Hence, our most recent work has focused on developing analytic tools for quantifying the changes in locomotor output that result form experimental manipulations of the propriospinal system in terms of frequency, intersegmental phase, and intersegmental correlation. Results of recent experiments can now be used to put further constraints on the allowable kinds of intersegmental coupling provided by mathematical modeling of the system.
FunCoup 3.0: database of genome-wide functional coupling networks.
Schmitt, Thomas; Ogris, Christoph; Sonnhammer, Erik L L
2014-01-01
We present an update of the FunCoup database (http://FunCoup.sbc.su.se) of functional couplings, or functional associations, between genes and gene products. Identifying these functional couplings is an important step in the understanding of higher level mechanisms performed by complex cellular processes. FunCoup distinguishes between four classes of couplings: participation in the same signaling cascade, participation in the same metabolic process, co-membership in a protein complex and physical interaction. For each of these four classes, several types of experimental and statistical evidence are combined by Bayesian integration to predict genome-wide functional coupling networks. The FunCoup framework has been completely re-implemented to allow for more frequent future updates. It contains many improvements, such as a regularization procedure to automatically downweight redundant evidences and a novel method to incorporate phylogenetic profile similarity. Several datasets have been updated and new data have been added in FunCoup 3.0. Furthermore, we have developed a new Web site, which provides powerful tools to explore the predicted networks and to retrieve detailed information about the data underlying each prediction.
Information Theoretic Measures to Infer Feedback Dynamics in Coupled Logistic Networks
Directory of Open Access Journals (Sweden)
Allison Goodwell
2015-10-01
Full Text Available A process network is a collection of interacting time series nodes, in which interactions can range from weak dependencies to complete synchronization. Between these extremes, nodes may respond to each other or external forcing at certain time scales and strengths. Identification of such dependencies from time series can reveal the complex behavior of the system as a whole. Since observed time series datasets are often limited in length, robust measures are needed to quantify strengths and time scales of interactions and their unique contributions to the whole system behavior. We generate coupled chaotic logistic networks with a range of connectivity structures, time scales, noise, and forcing mechanisms, and compute variance and lagged mutual information measures to evaluate how detected time dependencies reveal system behavior. When a target node is detected to receive information from multiple sources, we compute conditional mutual information and total shared information between each source node pair to identify unique or redundant sources. While variance measures capture synchronization trends, combinations of information measures provide further distinctions regarding drivers, redundancies, and time dependencies within the network. We find that imposed network connectivity often leads to induced feedback that is identified as redundant links, and cannot be distinguished from imposed causal linkages. We find that random or external driving nodes are more likely to provide unique information than mutually dependent nodes in a highly connected network. In process networks constructed from observed data, the methods presented can be used to infer connectivity, dominant interactions, and systemic behavioral shift.
Dynamics and bifurcations in a Dn-symmetric Hamiltonian network. Application to coupled gyroscopes
Buono, Pietro-Luciano; Chan, Bernard S.; Palacios, Antonio; In, Visarath
2015-01-01
The advent of novel engineered or smart materials, whose properties can be significantly altered in a controlled fashion by external stimuli, has stimulated the design and fabrication of smaller, faster, and more energy-efficient devices. As the need for even more powerful devices grows, networks have become popular alternatives to advance the fundamental limits of performance of individual units. In many cases, the collective rhythmic behavior of a network can be studied through the classical theory of nonlinear oscillators or through the more recent development of the coupled cell formalism. However, the current theory does not account yet for networks in which cells, or individual units, possess a Hamiltonian structure. One such example is a ring array of vibratory gyroscopes, where certain network topologies favor stable synchronized oscillations. Previous perturbation-based studies have shown that synchronized oscillations may, in principle, increase performance by reducing phase drift. The governing equations for larger array sizes are, however, not amenable to similar analysis. To circumvent this problem, the model equations are now reformulated in a Hamiltonian structure and the corresponding normal forms are derived. Through a normal form analysis, we investigate the effects of various coupling schemes and unravel the nature of the bifurcations that lead a ring of gyroscopes of any size into and out of synchronization. The Hamiltonian approach can, in principle, be readily extended to other symmetry-related systems.
Synchronization in a network of delay coupled maps with stochastically switching topologies
Nag, Mayurakshi; Poria, Swarup
2016-10-01
The synchronization behavior of delay coupled chaotic smooth unimodal maps over a ring network with stochastic switching of links at every time step is reported in this paper. It is observed that spatiotemporal synchronization never appears for nearest neighbor connections; however, stochastic switching of connections with homogeneous delay $(\\tau)$ is capable of synchronizing the network to homogeneous steady state or periodic orbit or synchronized chaotically oscillating state depending on the delay parameter, stochasticity parameter and map parameters. Linear stability analysis of the synchronized state is done analytically for unit delay and the value of the critical coupling strength, at which the onset of synchronization occurs is determined analytically. The logistic map $rx(1-x)$ (a smooth unimodal map) is chosen for numerical simulation purpose. Synchronized steady state or synchronized period-2 orbit is stabilized for delay $\\tau=1$. On the other hand for delay $\\tau=2$ the network is stabilized to the fixed point of the local map. Numerical simulation results are in good agreement with the analytically obtained linear stability analysis results. Another interesting observation is the existence of synchronized chaos in the network for delay $\\tau>2$. Calculating synchronization error and plotting time series data and Poincare first return map the existence of synchronized chaos is confirmed. The results hold good for other smooth unimodal maps also.
Self-organized network of fractal-shaped components coupled through statistical interaction.
Ugajin, R
2001-09-01
A dissipative dynamics is introduced to generate self-organized networks of interacting objects, which we call coupled-fractal networks. The growth model is constructed based on a growth hypothesis in which the growth rate of each object is a product of the probability of receiving source materials from faraway and the probability of receiving adhesives from other grown objects, where each object grows to be a random fractal if isolated, but connects with others if glued. The network is governed by the statistical interaction between fractal-shaped components, which can only be identified in a statistical manner over ensembles. This interaction is investigated using the degree of correlation between fractal-shaped components, enabling us to determine whether it is attractive or repulsive.
Mobility-enhanced signal response in metapopulation networks of coupled oscillators
Shen, Chuansheng; Hou, Zhonghuai
2013-01-01
We investigate the effect of mobility on the response of coupled oscillators to a subthreshold external signal in metapopulation networks, wherein each node represents a subpopulation with overdamped bistable oscillators that can randomly diffuse between nodes. With increasing mobility rate, the oscillators undergo transitions from intrawell to interwell motion, demonstrating clearly mobility-enhanced signal amplification. Moreover, the response shows nonmonotonic dependence on the mobility rate, i.e., a maximal gain occurs at a moderate level of mobility. This interesting phenomenon is robust against variations in the overall density, network size, as well as network topology. In addition, a simple mean-field analysis is carried out to qualitatively illustrate the simulation results.
A dynamically coupled allosteric network underlies binding cooperativity in Src kinase.
Foda, Zachariah H; Shan, Yibing; Kim, Eric T; Shaw, David E; Seeliger, Markus A
2015-01-20
Protein tyrosine kinases are attractive drug targets because many human diseases are associated with the deregulation of kinase activity. However, how the catalytic kinase domain integrates different signals and switches from an active to an inactive conformation remains incompletely understood. Here we identify an allosteric network of dynamically coupled amino acids in Src kinase that connects regulatory sites to the ATP- and substrate-binding sites. Surprisingly, reactants (ATP and peptide substrates) bind with negative cooperativity to Src kinase while products (ADP and phosphopeptide) bind with positive cooperativity. We confirm the molecular details of the signal relay through the allosteric network by biochemical studies. Experiments on two additional protein tyrosine kinases indicate that the allosteric network may be largely conserved among these enzymes. Our work provides new insights into the regulation of protein tyrosine kinases and establishes a potential conduit by which resistance mutations to ATP-competitive kinase inhibitors can affect their activity.
Chimeralike states in a network of oscillators under attractive and repulsive global coupling
Mishra, Arindam; Hens, Chittaranjan; Bose, Mridul; Roy, Prodyot K.; Dana, Syamal K.
2015-12-01
We report chimeralike states in an ensemble of oscillators using a type of global coupling consisting of two components: attractive and repulsive mean-field feedback. We identify the existence of two types of chimeralike states in a bistable Liénard system; in one type, both the coherent and the incoherent populations are in chaotic states (which we refer to as chaos-chaos chimeralike states) and, in another type, the incoherent population is in periodic state while the coherent population has irregular small oscillation. We find a metastable state in a parameter regime of the Liénard system where the coherent and noncoherent states migrate in time from one to another subpopulation. The relative size of the incoherent subpopulation, in the chimeralike states, remains almost stable with increasing size of the network. The generality of the coupling configuration in the origin of the chimeralike states is tested, using a second example of bistable system, the van der Pol-Duffing oscillator where the chimeralike states emerge as weakly chaotic in the coherent subpopulation and chaotic in the incoherent subpopulation. Furthermore, we apply the coupling, in a simplified form, to form a network of the chaotic Rössler system where both the noncoherent and the coherent subpopulations show chaotic dynamics.
Mean field dynamics of networks of delay-coupled noisy excitable units
Energy Technology Data Exchange (ETDEWEB)
Franović, Igor, E-mail: franovic@ipb.ac.rs [Scientific Computing Laboratory, Institute of Physics Belgrade, University of Belgrade, Pregrevica 118, 11080 Belgrade (Serbia); Todorović, Kristina; Burić, Nikola [Department of Physics and Mathematics, Faculty of Pharmacy, University of Belgrade, Vojvode Stepe 450, Belgrade (Serbia); Vasović, Nebojša [Department of Applied Mathematics, Faculty of Mining and Geology, University of Belgrade, PO Box 162, Belgrade (Serbia)
2016-06-08
We use the mean-field approach to analyze the collective dynamics in macroscopic networks of stochastic Fitzhugh-Nagumo units with delayed couplings. The conditions for validity of the two main approximations behind the model, called the Gaussian approximation and the Quasi-independence approximation, are examined. It is shown that the dynamics of the mean-field model may indicate in a self-consistent fashion the parameter domains where the Quasi-independence approximation fails. Apart from a network of globally coupled units, we also consider the paradigmatic setup of two interacting assemblies to demonstrate how our framework may be extended to hierarchical and modular networks. In both cases, the mean-field model can be used to qualitatively analyze the stability of the system, as well as the scenarios for the onset and the suppression of the collective mode. In quantitative terms, the mean-field model is capable of predicting the average oscillation frequency corresponding to the global variables of the exact system.
Local residue coupling strategies by neural network for InSAR phase unwrapping
Refice, Alberto; Satalino, Giuseppe; Chiaradia, Maria T.
1997-12-01
Phase unwrapping is one of the toughest problems in interferometric SAR processing. The main difficulties arise from the presence of point-like error sources, called residues, which occur mainly in close couples due to phase noise. We present an assessment of a local approach to the resolution of these problems by means of a neural network. Using a multi-layer perceptron, trained with the back- propagation scheme on a series of simulated phase images, fashion the best pairing strategies for close residue couples. Results show that god efficiencies and accuracies can have been obtained, provided a sufficient number of training examples are supplied. Results show that good efficiencies and accuracies can be obtained, provided a sufficient number of training examples are supplied. The technique is tested also on real SAR ERS-1/2 tandem interferometric images of the Matera test site, showing a good reduction of the residue density. The better results obtained by use of the neural network as far as local criteria are adopted appear justified given the probabilistic nature of the noise process on SAR interferometric phase fields and allows to outline a specifically tailored implementation of the neural network approach as a very fast pre-processing step intended to decrease the residue density and give sufficiently clean images to be processed further by more conventional techniques.
Leiser, Randolph J.; Rotstein, Horacio G.
2017-08-01
Oscillations in far-from-equilibrium systems (e.g., chemical, biochemical, biological) are generated by the nonlinear interplay of positive and negative feedback effects operating at different time scales. Relaxation oscillations emerge when the time scales between the activators and the inhibitors are well separated. In addition to the large-amplitude oscillations (LAOs) or relaxation type, these systems exhibit small-amplitude oscillations (SAOs) as well as abrupt transitions between them (canard phenomenon). Localized cluster patterns in networks of relaxation oscillators consist of one cluster oscillating in the LAO regime or exhibiting mixed-mode oscillations (LAOs interspersed with SAOs), while the other oscillates in the SAO regime. Because the individual oscillators are monostable, localized patterns are a network phenomenon that involves the interplay of the connectivity and the intrinsic dynamic properties of the individual nodes. Motivated by experimental and theoretical results on the Belousov-Zhabotinsky reaction, we investigate the mechanisms underlying the generation of localized patterns in globally coupled networks of piecewise-linear relaxation oscillators where the global feedback term affects the rate of change of the activator (fast variable) and depends on the weighted sum of the inhibitor (slow variable) at any given time. We also investigate whether these patterns are affected by the presence of a diffusive type of coupling whose synchronizing effects compete with the symmetry-breaking global feedback effects.
Mean field dynamics of networks of delay-coupled noisy excitable units
Franović, Igor; Todorović, Kristina; Vasović, Nebojša; Burić, Nikola
2016-06-01
We use the mean-field approach to analyze the collective dynamics in macroscopic networks of stochastic Fitzhugh-Nagumo units with delayed couplings. The conditions for validity of the two main approximations behind the model, called the Gaussian approximation and the Quasi-independence approximation, are examined. It is shown that the dynamics of the mean-field model may indicate in a self-consistent fashion the parameter domains where the Quasi-independence approximation fails. Apart from a network of globally coupled units, we also consider the paradigmatic setup of two interacting assemblies to demonstrate how our framework may be extended to hierarchical and modular networks. In both cases, the mean-field model can be used to qualitatively analyze the stability of the system, as well as the scenarios for the onset and the suppression of the collective mode. In quantitative terms, the mean-field model is capable of predicting the average oscillation frequency corresponding to the global variables of the exact system.
A rapid and sensitive assay of intercellular coupling by voltage imaging of gap junction networks.
Ceriani, Federico; Mammano, Fabio
2013-10-21
A variety of mechanisms that govern connexin channel gating and permeability regulate coupling in gap junction networks. Mutations in connexin genes have been linked to several pathologies, including cardiovascular anomalies, peripheral neuropathy, skin disorders, cataracts and deafness. Gap junction coupling and its patho-physiological alterations are commonly assayed by microinjection experiments with fluorescent tracers, which typically require several minutes to allow dye transfer to a limited number of cells. Comparable or longer time intervals are required by fluorescence recovery after photobleaching experiments. Paired electrophysiological recordings have excellent time resolution but provide extremely limited spatial information regarding network connectivity. Here, we developed a rapid and sensitive method to assay gap junction communication using a combination of single cell electrophysiology, large-scale optical recordings and a digital phase-sensitive detector to extract signals with a known frequency from Vf2.1.Cl, a novel fluorescent sensor of plasma membrane potential. Tests performed in HeLa cell cultures confirmed that suitably encoded Vf2.1.Cl signals remained confined within the network of cells visibly interconnected by fluorescently tagged gap junction channels. We used this method to visualize instantly intercellular connectivity over the whole field of view (hundreds of cells) in cochlear organotypic cultures from postnatal mice. A simple resistive network model reproduced accurately the spatial dependence of the electrical signals throughout the cellular network. Our data suggest that each pair of cochlear non-sensory cells of the lesser epithelial ridge is coupled by ~1500 gap junction channels, on average. Junctional conductance was reduced by 14% in cochlear cultures harboring the T5M mutation of connexin30, which induces a moderate hearing loss in connexin30T5M/T5M knock-in mice, and by 91% in cultures from connexin30-/- mice, which are
Energy Technology Data Exchange (ETDEWEB)
Abt, I. [Max-Planck-Institut fuer Physik, Werner-Heisenberg-Institut, Muenchen (Germany); Adams, M. [Dortmund Univ. (Germany). Inst. fuer Physik; Agari, M. [Max-Planck-Institut fuer Kernphysik, Heidelberg (DE)] (and others)
2008-07-15
A measurement of the ratio R{sub {chi}{sub c}}=({chi}{sub c} {yields} J/{psi}+{gamma})/J/{psi} in pC, pTi and pW interactions at 920 GeV/c ({radical}(s)=41.6 GeV) in the Feynman-x range -0.35
Irregular Segmented Region Compression Coding Based on Pulse Coupled Neural Network
Institute of Scientific and Technical Information of China (English)
MA Yi-de; QI Chun-liang; QIAN Zhi-bai; SHI Fei; ZHANG Bei-dou
2006-01-01
An irregular segmented region coding algorithm based on pulse coupled neural network(PCNN) is presented. PCNN has the property of pulse-coupled and changeable threshold, through which these adjacent pixels with approximate gray values can be activated simultaneously. One can draw a conclusion that PCNN has the advantage of realizing the regional segmentation, and the details of original image can be achieved by the parameter adjustment of segmented images, and at the same time, the trivial segmented regions can be avoided. For the better approximation of irregular segmented regions, the Gram-Schmidt method, by which a group of orthonormal basis functions is constructed from a group of linear independent initial base functions, is adopted. Because of the orthonormal reconstructing method, the quality of reconstructed image can be greatly improved and the progressive image transmission will also be possible.
Impact of asymptomatic infection on coupled disease-behavior dynamics in complex networks
Zhang, Hai-Feng; Chen, Han-Shuang; Liu, Can; Small, Michael
2016-01-01
Studies on how to model the interplay between diseases and behavioral responses (so-called coupled disease-behavior interaction) have attracted increasing attention. Owing to the lack of obvious clinical evidence of diseases, or the incomplete information related to the disease, the risks of infection cannot be perceived and may lead to inappropriate behavioral responses. Therefore, how to quantitatively analyze the impacts of asymptomatic infection on the interplay between diseases and behavioral responses is of particular importance. In this Letter, under the complex network framework, we study the coupled disease-behavior interaction model by dividing infectious individuals into two states: U-state (without evident clinical symptoms, labelled as U) and I-state (with evident clinical symptoms, labelled as I). A susceptible individual can be infected by U- or I-nodes, however, since the U-nodes cannot be easily observed, susceptible individuals take behavioral responses \\emph{only} when they contact I-nodes....
Barnes, Jessica J; Nobre, Anna Christina; Woolrich, Mark W; Baker, Kate; Astle, Duncan E
2016-08-24
Working memory is a capacity upon which many everyday tasks depend and which constrains a child's educational progress. We show that a child's working memory can be significantly enhanced by intensive computer-based training, relative to a placebo control intervention, in terms of both standardized assessments of working memory and performance on a working memory task performed in a magnetoencephalography scanner. Neurophysiologically, we identified significantly increased cross-frequency phase amplitude coupling in children who completed training. Following training, the coupling between the upper alpha rhythm (at 16 Hz), recorded in superior frontal and parietal cortex, became significantly coupled with high gamma activity (at ∼90 Hz) in inferior temporal cortex. This altered neural network activity associated with cognitive skill enhancement is consistent with a framework in which slower cortical rhythms enable the dynamic regulation of higher-frequency oscillatory activity related to task-related cognitive processes. Whether we can enhance cognitive abilities through intensive training is one of the most controversial topics of cognitive psychology in recent years. This is particularly controversial in childhood, where aspects of cognition, such as working memory, are closely related to school success and are implicated in numerous developmental disorders. We provide the first neurophysiological account of how working memory training may enhance ability in childhood, using a brain recording technique called magnetoencephalography. We borrowed an analysis approach previously used with intracranial recordings in adults, or more typically in other animal models, called "phase amplitude coupling." Copyright © 2016 Barnes et al.
Barnes, Jessica J.; Nobre, Anna Christina; Woolrich, Mark W.; Baker, Kate
2016-01-01
Working memory is a capacity upon which many everyday tasks depend and which constrains a child's educational progress. We show that a child's working memory can be significantly enhanced by intensive computer-based training, relative to a placebo control intervention, in terms of both standardized assessments of working memory and performance on a working memory task performed in a magnetoencephalography scanner. Neurophysiologically, we identified significantly increased cross-frequency phase amplitude coupling in children who completed training. Following training, the coupling between the upper alpha rhythm (at 16 Hz), recorded in superior frontal and parietal cortex, became significantly coupled with high gamma activity (at ∼90 Hz) in inferior temporal cortex. This altered neural network activity associated with cognitive skill enhancement is consistent with a framework in which slower cortical rhythms enable the dynamic regulation of higher-frequency oscillatory activity related to task-related cognitive processes. SIGNIFICANCE STATEMENT Whether we can enhance cognitive abilities through intensive training is one of the most controversial topics of cognitive psychology in recent years. This is particularly controversial in childhood, where aspects of cognition, such as working memory, are closely related to school success and are implicated in numerous developmental disorders. We provide the first neurophysiological account of how working memory training may enhance ability in childhood, using a brain recording technique called magnetoencephalography. We borrowed an analysis approach previously used with intracranial recordings in adults, or more typically in other animal models, called “phase amplitude coupling.” PMID:27559180
Directory of Open Access Journals (Sweden)
Constantine G. Kakoyiannis
2010-01-01
Full Text Available Wireless sensors emerged as narrowband, resource-constrained devices to provide monitoring services over a wide life span. Future applications of sensor networks are multimedia-driven and include sensor mobility. Thus, sensors must combine small size, large bandwidth, and diversity capabilities. Compact arrays, offering transmit/receive diversity, suffer from strong mutual coupling (MC, which causes lower antenna efficiency, loss of bandwidth, and signal correlation. An efficient technique to reduce coupling in compact arrays is described herein: a defect was inserted in the ground plane (GNDP area between each pair of elements. The defect disturbed the GNDP currents and offered multidecibel coupling suppression, bandwidth recovery, and reduction of in-band correlation. Minimal pattern distortion was estimated. Computational results were supported by measurements. The bandwidth of unloaded arrays degraded gracefully from 38% to 28% with decreasing interelement distance (0.25 to 0.10. Defect-loaded arrays exhibited active impedance bandwidths 37–45%, respectively. Measured coupling was reduced by 15–20 dB.
Gong, Dawei; Lewis, Frank L; Wang, Liping; Xu, Ke
2016-05-01
In this paper, a novel pinning synchronization (synchronization with pinning control) scheme for an array of neural networks with hybrid coupling is investigated. The main contributions are as follows: (1) A novel pinning control strategy is proposed for the first time. Pinning control schemes are introduced as an array of column vector. The controllers are designed as simple linear systems, which are easy to be analyzed or tested. (2) Augmented Lyapunov-Krasovskii functional (LKF) is applied to introduce more relax variables, which can alleviate the requirements of the positive definiteness of the matrix. (3) Based on the appropriate LKF, by introducing some free weighting matrices, some novel synchronization criteria are derived. Furthermore, the proposed pinning control scheme described by column vector can also be expanded to almost all the other array of neural networks. Finally, numerical examples are provided to show the effectiveness of the proposed results.
Directory of Open Access Journals (Sweden)
Ze Tang
2013-01-01
Full Text Available We focus on the cluster synchronization problem for a kind of general networks with nondelayed and delayed coupling. Based on the pinning control scheme, a small fraction of the nodes in each cluster are pinned for successful control, and the states of the whole dynamical networks can be globally forced to the objective cluster states. Sufficient conditions are derived to guarantee the realization of the cluster synchronization pattern for all initial values by means of the Lyapunov stability theorem and linear matrix inequalities (LMIs. By using the adaptive update law, relative smaller control gains are obtained, and hence the control cost can be substantially lower. Numerical simulations are also exploited to demonstrate the effectiveness and validity of the main result.
Coupling sample paths to the partial thermodynamic limit in stochastic chemical reaction networks
Levien, Ethan
2016-01-01
We present a new technique for reducing the variance in Monte Carlo estimators of stochastic chemical reaction networks. Our method makes use of the fact that many stochastic reaction networks converge to piecewise deterministic Markov processes in the large system-size limit. The statistics of the piecewise deterministic process can be obtained much more efficiently than those of the exact process. By coupling sample paths of the exact model to the piecewise deterministic process we are able to reduce the variance, and hence the computational complexity of the Monte Carlo estimator. In addition to rigorous results concerning the asymptotic behavior of our method, numerical simulations are performed on some simple biological models suggesting that significant computational gains are made for even moderate system-sizes.
Manifestation of Coupled Geometric Complexity in Urban Road Networks under Mono-Centric Assumption
Peiravian, Farideddin
2015-01-01
This article analyzes the complex geometry of urban transportation networks as a gateway to understanding their encompassing urban systems. Using a proposed ring-buffer approach and applying it to 50 urban areas in the United States, we measure road lengths in concentric rings from carefully-selected urban centers and study how the trends evolve as we move away from these centers. Overall, we find that the complexity of urban transportation networks is naturally coupled, consisting of two distinct patterns: (1) a fractal component (i.e., power law) that represent a uniform grid, and (2) a second component that can be exponential, power law, or logarithmic that captures changes in road density. From this second component, we introduce two new indices, density index and decay index, which jointly capture essential characteristics of urban systems and therefore can help us gain new insights into how cities evolve.
Directory of Open Access Journals (Sweden)
Levente Czumbil
2015-12-01
Full Text Available The current paper presents an artificial intelligence based technique applied in the investigation of electromagnetic interference problems between high voltage power lines (HVPL and nearby underground metallic pipelines (MP. An artificial neural network (NN solution has been implemented by the authors to evaluate the inductive coupling between HVPL and MP for different constructive geometries of an electromagnetic interference problem considering a multi-layer soil structure. Obtained results are compared to solutions provided by a finite element method (FEM based analysis and considered as reference. The advantage of the proposed method yields in a simplified computation model compared to FEM, and implicitly a lower computational time.
Improved pulse-coupled neural network for target segmentation in infrared images
Kong, Xiangwei; Huang, Jing; Shi, Hao
2001-09-01
This paper presents a new image segmentation algorithm based on the pulse coupled neural network (PCNN) and histogram method for infrared images. The proposed algorithm abandons entirely the mechanism of the time exponential decaying function and uses the results of the gray-level histogram analysis as the interior thresholds of PCNN, meanwhile, it keeps the advantage of briding small spatial gaps and minor intensity variations. Experiment results demonstrate that the proposed algorithm can get more complete region and edge information in infrared images. It is also of much lower complexity and of high speed than the original one.
A BOD-DO coupling model for water quality simulation by artificial neural network
Institute of Scientific and Technical Information of China (English)
郭劲松; LONG; Tengrui; 等
2002-01-01
A one-dimensional BOD-DO coupling model for water quality simulation is presented,which adopts Streeter-Phelps equations and the theory of back-propagation artificial neural network.The water quality data of Yangtze River in the Chongqing region in the year of 1989 are divided into 5 groups and used in the learning and testing courses of this model.The result shows that such model is feasible for water quality simulation and is more accurate than traditional models.
Lu, Tao; Liang, Hua; Li, Hongzhe; Wu, Hulin
2011-01-01
Gene regulation is a complicated process. The interaction of many genes and their products forms an intricate biological network. Identification of this dynamic network will help us understand the biological process in a systematic way. However, the construction of such a dynamic network is very challenging for a high-dimensional system. In this article we propose to use a set of ordinary differential equations (ODE), coupled with dimensional reduction by clustering and mixed-effects modeling techniques, to model the dynamic gene regulatory network (GRN). The ODE models allow us to quantify both positive and negative gene regulations as well as feedback effects of one set of genes in a functional module on the dynamic expression changes of the genes in another functional module, which results in a directed graph network. A five-step procedure, Clustering, Smoothing, regulation Identification, parameter Estimates refining and Function enrichment analysis (CSIEF) is developed to identify the ODE-based dynamic GRN. In the proposed CSIEF procedure, a series of cutting-edge statistical methods and techniques are employed, that include non-parametric mixed-effects models with a mixture distribution for clustering, nonparametric mixed-effects smoothing-based methods for ODE models, the smoothly clipped absolute deviation (SCAD)-based variable selection, and stochastic approximation EM (SAEM) approach for mixed-effects ODE model parameter estimation. The key step, the SCAD-based variable selection of the proposed procedure is justified by investigating its asymptotic properties and validated by Monte Carlo simulations. We apply the proposed method to identify the dynamic GRN for yeast cell cycle progression data. We are able to annotate the identified modules through function enrichment analyses. Some interesting biological findings are discussed. The proposed procedure is a promising tool for constructing a general dynamic GRN and more complicated dynamic networks.
Tunable Coupling to a Mechanical Oscillator Circuit Using a Coherent Feedback Network
Directory of Open Access Journals (Sweden)
Joseph Kerckhoff
2013-06-01
Full Text Available We demonstrate a fully cryogenic microwave feedback network composed of modular superconducting devices connected by transmission lines and designed to control a mechanical oscillator that is coupled to one of the devices. The network features an electromechanical device and a tunable controller that coherently receives, processes, and feeds back continuous microwave signals that modify the dynamics and readout of the mechanical state. While previous electromechanical systems represent some compromise between efficient control and efficient readout of the mechanical state, as set by the electromagnetic decay rate, the tunable controller produces a closed-loop network that can be dynamically and continuously tuned between both extremes much faster than the mechanical response time. We demonstrate that the microwave decay rate may be modulated by at least a factor of 10 at a rate greater than 10^{4} times the mechanical response rate. The system is easy to build and suggests that some useful functions may arise most naturally at the network level of modular, quantum electromagnetic devices.
Synchronization and array-enhanced resonances in delayed coupled neuronal network with channel noise
Chen, Jianchun; Ding, Shaojie; Li, Hui; He, Guolong; Zhang, Xuejuan
2014-09-01
This paper studies the combined effect of transmission delay and channel fluctuations on population behaviors of an excitatory Erdös-Rényi neuronal network. First, it is found that the network reaches a perfect spatial temporal coherence at a suitable membrane size. Such a coherence resonance is stimulus-free and is array-enhanced. Second, the presence of transmission delay can induce intermittent changes of the population dynamics. Besides, two resonant peaks of the population firing rate are observed as delay changes: one is at τd≈7ms for all membrane areas, which reflects the resonance between the delayed interaction and the intrinsic period of channel kinetics; the other occurs when the transmission delay equals to the mean inter-spike intervals of the population firings in the absence of delay, which reflects the resonance between the delayed interaction and the firing period of the non-delayed system. Third, concerning the impact of network topology and population size, it is found that decreasing the connection probability does not change the range of transmission delay but broadens the range of synaptic coupling that supports population neurons to generate action potentials synchronously and temporally coherently. Furthermore, there exists a critical connection probability that distinguishes the population dynamics into an asynchronous and synchronous state. All the results we obtained are based on networks of size N = 500, which are shown to be robust to further increasing the population size.
Wang, Qi; Gong, Yubing; Wu, Yanan
2015-11-01
Introducing adaptive coupling in delayed neuronal networks and regulating the dissipative parameter (DP) of adaptive coupling by noise, we study the effect of fluctuations of the changing rate of adaptive coupling on the synchronization of the neuronal networks. It is found that time delay can induce synchronization transitions for intermediate DP values, and the synchronization transitions become strongest when DP is optimal. As the intensity of DP noise is varied, the neurons can also exhibit synchronization transitions, and the phenomenon is delay-dependent and is enhanced for certain time delays. Moreover, the synchronization transitions change with the change of DP and become strongest when DP is optimal. These results show that randomly changing adaptive coupling can considerably change the synchronization of the neuronal networks, and hence could play a crucial role in the information processing and transmission in neural systems.
Partial synchronization in networks of non-linearly coupled oscillators: The Deserter Hubs Model
Energy Technology Data Exchange (ETDEWEB)
Freitas, Celso, E-mail: cbnfreitas@gmail.com; Macau, Elbert, E-mail: elbert.macau@inpe.br [Associate Laboratory for Computing and Applied Mathematics - LAC, Brazilian National Institute for Space Research - INPE (Brazil); Pikovsky, Arkady, E-mail: pikovsky@uni-potsdam.de [Department of Physics and Astronomy, University of Potsdam, Germany and Department of Control Theory, Nizhni Novgorod State University, Gagarin Av. 23, 606950, Nizhni Novgorod (Russian Federation)
2015-04-15
We study the Deserter Hubs Model: a Kuramoto-like model of coupled identical phase oscillators on a network, where attractive and repulsive couplings are balanced dynamically due to nonlinearity of interactions. Under weak force, an oscillator tends to follow the phase of its neighbors, but if an oscillator is compelled to follow its peers by a sufficient large number of cohesive neighbors, then it actually starts to act in the opposite manner, i.e., in anti-phase with the majority. Analytic results yield that if the repulsion parameter is small enough in comparison with the degree of the maximum hub, then the full synchronization state is locally stable. Numerical experiments are performed to explore the model beyond this threshold, where the overall cohesion is lost. We report in detail partially synchronous dynamical regimes, like stationary phase-locking, multistability, periodic and chaotic states. Via statistical analysis of different network organizations like tree, scale-free, and random ones, we found a measure allowing one to predict relative abundance of partially synchronous stationary states in comparison to time-dependent ones.
Self-organized network of phase oscillators coupled by activity-dependent interactions.
Aoki, Takaaki; Aoyagi, Toshio
2011-12-01
We investigate a network of coupled phase oscillators whose interactions evolve dynamically depending on the relative phases between the oscillators. We found that this coevolving dynamical system robustly yields three basic states of collective behavior with their self-organized interactions. The first is the two-cluster state, in which the oscillators are organized into two synchronized groups. The second is the coherent state, in which the oscillators are arranged sequentially in time. The third is the chaotic state, in which the relative phases between oscillators and their coupling weights are chaotically shuffled. Furthermore, we demonstrate that self-assembled multiclusters can be designed by controlling the weight dynamics. Note that the phase patterns of the oscillators and the weighted network of interactions between them are simultaneously organized through this coevolving dynamics. We expect that these results will provide new insight into self-assembly mechanisms by which the collective behavior of a rhythmic system emerges as a result of the dynamics of adaptive interactions.
Wu, Xiaoqun
2008-02-01
Many existing papers investigated the geometric features, control and synchronization of complex dynamical networks provided with certain topology. However, the exact topology of a network is sometimes unknown or uncertain. Based on LaSalle’s invariance principle, we propose an adaptive feedback technique to identify the exact topology of a weighted general complex dynamical network model with time-varying coupling delay. By receiving the network nodes evolution, the topology of such a kind of network with identical or different nodes, or even with varying topology can be monitored. In comparison with previous methods, time delay is taken into account in this simple, analytical and systematic synchronization-based technique. Particularly, the weight configuration matrix is not necessarily symmetric or irreducible, and the inner-coupling matrix need not be symmetric. Illustrative simulations are provided to verify the correctness and effectiveness of the proposed scheme.
Zhang, Huaguang; Tian, Hui; Wang, Zhanshan; Hou, Yanfang
2016-12-01
A novel synchronization analysis method is developed to solve the complete synchronization problem of many Boolean networks (BNs) coupled in the leader-follower configuration. First, an error system is constructed in terms of the algebraic representation using the semitensor product of matrices. Then, the synchronization problem of coupled BNs is converted into a problem whether all the trajectories of the error system are convergent to the zero vector. Second, according to the structure analysis of this error system, which is in the form of a switched system with leader BN states as the switching signal, a necessary and sufficient synchronization condition is derived. An algorithm is developed, which helps to determine as soon as possible whether complete synchronization among coupled BNs is achieved. Finally, a constructive design approach to follower BNs is provided. All of these follower BNs designed by our approach can completely synchronize with a given leader BN from the (Tt+1) th step at most, where Tt is the transient period of the leader BN.
Directory of Open Access Journals (Sweden)
Jun Zhou
2017-01-01
Full Text Available As an unconventional energy, coalbed methane (CBM mainly exists in coal bed with adsorption, whose productivity is different from conventional gas reservoir. This paper explains the wellbore pressure drop, surface pipeline network simulation, and reservoir calculation model of CBM. A coupled surface/wellbore/reservoir calculation architecture was presented, to coordinate the gas production in each calculation period until the balance of surface/wellbore/reservoir. This coupled calculation method was applied to a CBM field for predicting production. The daily gas production increased year by year at the first time and then decreased gradually after several years, while the daily water production was reduced all the time with the successive decline of the formation pressure. The production of gas and water in each well is almost the same when the structure is a star. When system structure is a dendritic surface system, the daily gas production ranked highest at the well which is the nearest to the surface system collection point and lowest at the well which is the farthest to the surface system collection point. This coupled calculation method could be used to predict the water production, gas production, and formation pressure of a CBM field during a period of time.
Directory of Open Access Journals (Sweden)
Wei Zhang
2014-01-01
Full Text Available River networks and estuaries are very common in coastal areas. Runoff from the upper stream interacts with tidal current from open sea in these two systems, leading to a complex hydrodynamics process. Therefore, it is necessary to consider the two systems as a whole to study the flow and suspended sediment transport. Firstly, a 1D model is established in the Pearl River network and a 3D model is applied in its estuary. As sufficient mass exchanges between the river network and its estuary, a strict mathematical relationship of water level at the interfaces can be adopted to couple the 1D model with the 3D model. By doing so, the coupled model does not need to have common nested grids. The river network exchanges the suspended sediment with its estuary by adding the continuity conditions at the interfaces. The coupled model is, respectively, calibrated in the dry season and the wet season. The results demonstrate that the coupled model works excellently in simulating water level and discharge. Although there are more errors in simulating suspended sediment concentration due to some reasons, the coupled model is still good enough to evaluate the suspended sediment transport in river network and estuary systems.
Chandrasekar, A; Rakkiyappan, R; Cao, Jinde
2015-10-01
This paper studies the impulsive synchronization of Markovian jumping randomly coupled neural networks with partly unknown transition probabilities via multiple integral approach. The array of neural networks are coupled in a random fashion which is governed by Bernoulli random variable. The aim of this paper is to obtain the synchronization criteria, which is suitable for both exactly known and partly unknown transition probabilities such that the coupled neural network is synchronized with mixed time-delay. The considered impulsive effects can be synchronized at partly unknown transition probabilities. Besides, a multiple integral approach is also proposed to strengthen the Markovian jumping randomly coupled neural networks with partly unknown transition probabilities. By making use of Kronecker product and some useful integral inequalities, a novel Lyapunov-Krasovskii functional was designed for handling the coupled neural network with mixed delay and then impulsive synchronization criteria are solvable in a set of linear matrix inequalities. Finally, numerical examples are presented to illustrate the effectiveness and advantages of the theoretical results. Copyright © 2015 Elsevier Ltd. All rights reserved.
Directory of Open Access Journals (Sweden)
Sean P Parsons
2016-02-01
Full Text Available Pacemaker activities generated by networks of interstitial cells of Cajal (ICC, in conjunction with the enteric nervous system, orchestrate most motor patterns in the gastrointestinal tract. It was our objective to understand the role of network features of ICC associated with the myenteric plexus (ICC-MP in the shaping of motor patterns of the small intestine. To that end, a model of weakly coupled oscillators (oscillators influence each other's phase but not amplitude was created with most parameters derived from experimental data. The ICC network is a uniform two dimensional network coupled by gap junctions. All ICC generate pacemaker (slow wave activity with a frequency gradient in mice from 50/min at the proximal end of the intestine to 40/min at the distal end. Key features of motor patterns, directly related to the underlying pacemaker activity, are frequency steps and dislocations. These were accurately mimicked by reduction of coupling strength at a point in the chain of oscillators. When coupling strength was expressed as a product of gap junction density and conductance, and gap junction density was varied randomly along the chain (i.e. spatial noise with a long-tailed distribution, plateau steps occurred at points of low density. As gap junction conductance was decreased, the number of plateaus increased, mimicking the effect of the gap junction inhibitor carbenoxolone. When spatial noise was added to the natural interval gradient, as gap junction conductance decreased, the number of plateaus increased as before but in addition the phase waves frequently changed direction of apparent propagation, again mimicking the effect of carbenoxolone. In summary, key features of the motor patterns that are governed by pacemaker activity may be a direct consequence of biological noise, specifically spatial noise in gap junction coupling and pacemaker frequency.
Parsons, Sean P.; Huizinga, Jan D.
2016-01-01
Pacemaker activities generated by networks of interstitial cells of Cajal (ICC), in conjunction with the enteric nervous system, orchestrate most motor patterns in the gastrointestinal tract. It was our objective to understand the role of network features of ICC associated with the myenteric plexus (ICC-MP) in the shaping of motor patterns of the small intestine. To that end, a model of weakly coupled oscillators (oscillators influence each other's phase but not amplitude) was created with most parameters derived from experimental data. The ICC network is a uniform two dimensional network coupled by gap junctions. All ICC generate pacemaker (slow wave) activity with a frequency gradient in mice from 50/min at the proximal end of the intestine to 40/min at the distal end. Key features of motor patterns, directly related to the underlying pacemaker activity, are frequency steps and dislocations. These were accurately mimicked by reduction of coupling strength at a point in the chain of oscillators. When coupling strength was expressed as a product of gap junction density and conductance, and gap junction density was varied randomly along the chain (i.e., spatial noise) with a long-tailed distribution, plateau steps occurred at pointsof low density. As gap junction conductance was decreased, the number of plateaus increased, mimicking the effect of the gap junction inhibitor carbenoxolone. When spatial noise was added to the natural interval gradient, as gap junction conductance decreased, the number of plateaus increased as before but in addition the phase waves frequently changed direction of apparent propagation, again mimicking the effect of carbenoxolone. In summary, key features of the motor patterns that are governed by pacemaker activity may be a direct consequence of biological noise, specifically spatial noise in gap junction coupling and pacemaker frequency. PMID:26869875
Parsons, Sean P; Huizinga, Jan D
2016-01-01
Pacemaker activities generated by networks of interstitial cells of Cajal (ICC), in conjunction with the enteric nervous system, orchestrate most motor patterns in the gastrointestinal tract. It was our objective to understand the role of network features of ICC associated with the myenteric plexus (ICC-MP) in the shaping of motor patterns of the small intestine. To that end, a model of weakly coupled oscillators (oscillators influence each other's phase but not amplitude) was created with most parameters derived from experimental data. The ICC network is a uniform two dimensional network coupled by gap junctions. All ICC generate pacemaker (slow wave) activity with a frequency gradient in mice from 50/min at the proximal end of the intestine to 40/min at the distal end. Key features of motor patterns, directly related to the underlying pacemaker activity, are frequency steps and dislocations. These were accurately mimicked by reduction of coupling strength at a point in the chain of oscillators. When coupling strength was expressed as a product of gap junction density and conductance, and gap junction density was varied randomly along the chain (i.e., spatial noise) with a long-tailed distribution, plateau steps occurred at pointsof low density. As gap junction conductance was decreased, the number of plateaus increased, mimicking the effect of the gap junction inhibitor carbenoxolone. When spatial noise was added to the natural interval gradient, as gap junction conductance decreased, the number of plateaus increased as before but in addition the phase waves frequently changed direction of apparent propagation, again mimicking the effect of carbenoxolone. In summary, key features of the motor patterns that are governed by pacemaker activity may be a direct consequence of biological noise, specifically spatial noise in gap junction coupling and pacemaker frequency.
Chow, Ronald; Mok, Daniel K W; Lee, Edmond P F; Dyke, John M
2016-11-09
A theoretical study has been made of the BrO + HO2 reaction, a radical-radical reaction which contributes to ozone depletion in the atmosphere via production of HOBr. Reaction enthalpies, activation energies and mechanisms have been determined for five reaction channels. Also rate coefficients have been calculated, in the atmospherically important temperature range 200-400 K, for the two channels with the lowest activation energies, both of which produce HOBr: (R1a) HOBr(X(1)A') + O2(X(3)Σ) and (R1b) HOBr(X(1)A') + O2(a(1)Δg). The other channels considered are: (R2) BrO + HO2 → HBr + O3, (R3) BrO + HO2 → OBrO + OH and (R4) BrO + HO2 → BrOO + OH. For all channels, geometry optimization and frequency calculations were carried out at the M06-2X/AVDZ level, while relative energies of the stationary points on the reaction surface were improved at a higher level (BD(TQ)/CBS or CCSD(T)/CBS). The computed standard reaction enthalpies (ΔH) for channels (R1a), (R1b), (R2), (R3) and (R4) are -47.5, -25.0, -4.3, 14.9 and 5.9 kcal mol(-1), and the corresponding computed activation energies (ΔE) are 2.53, -3.07, 11.83, 35.0 and 37.81 kcal mol(-1). These values differ significantly from those obtained in earlier work by Kaltsoyannis and Rowley (Phys. Chem. Chem. Phys., 2002, 4, 419-427), particularly for channel (R1b), and reasons for this are discussed. In particular, the importance of obtaining an open-shell singlet wavefunction, rather than a closed-shell singlet wavefunction, for the transition state of this channel is emphasized. Rate coefficient calculations from computed potential energy surfaces were made for BrO + HO2 for the first time. Although channel (R1a) is the most exothermic, channel (R1b) has the lowest barrier height, which is negative (at -3.07 kcal mol(-1)). Most rate coefficient calculations were therefore made for (R1b). A two transition state model has been used, involving an outer and an inner transition state. The inner transition state was
Gosav, S.; Praisler, M.; Dorohoi, D. O.; Popa, G.
2005-06-01
A pure neural network (NN) and several neural networks coupled with principal component analysis (PC-NN) have been developed in order to identify illicit amphetamines necessary in the investigation of drugs of abuse for epidemiological, clinical, and forensic purposes. The NN system has as input variables 260 spectral data, representing absorption intensities measured for each normalized infrared spectrum at 260 wavenumbers 10 cm -1 apart. In the case of PC-NN systems, the original spectral data (absorption intensities) have been compressed with the principal component analysis method (PCA), the scores of the principal components (PCs) being the inputs of these systems. We have built nine PC-NN systems, which have a different number of input variables: 3PCs, 4PCs, 5PCs, 6PCs, 7PCs, 8PCs, 9PCs, 10PCs and 15PCs. All systems are specialized to distinguish between stimulant amphetamines (class code M), hallucinogenic amphetamines (class code T) and nonamphetamines (class code N). We are now presenting a comparison of the validation results obtained for the NN system and for the best PC-NN system based on the scores of the first nine PCs (9PC-NN). The NN system correctly classifies all the positive samples, as opposed to the 9PC-NN system, which is characterized by a true positive rate (TP) of 90.91%. The true negative rate (TN) obtained for the first system (83.33%) is slightly higher than in the case of the later system (82.71%). Thus, the NN system is more sensitive and selective than the 9PC-NN system. We are also presenting a spectroscopic analysis of the false negative samples obtained in the case of 9PC-NN system.
Hu, Cheng; Yu, Juan; Chen, Zhanheng; Jiang, Haijun; Huang, Tingwen
2017-05-01
In this paper, the fixed-time stability of dynamical systems and the fixed-time synchronization of coupled discontinuous neural networks are investigated under the framework of Filippov solution. Firstly, by means of reduction to absurdity, a theorem of fixed-time stability is established and a high-precision estimation of the settling-time is given. It is shown by theoretic proof that the estimation bound of the settling time given in this paper is less conservative and more accurate compared with the classical results. Besides, as an important application, the fixed-time synchronization of coupled neural networks with discontinuous activation functions is proposed. By designing a discontinuous control law and using the theory of differential inclusions, some new criteria are derived to ensure the fixed-time synchronization of the addressed coupled networks. Finally, two numerical examples are provided to show the effectiveness and validity of the theoretical results. Copyright © 2017 Elsevier Ltd. All rights reserved.
Skouloudis, A. N.; Rickerby, D. G.
2012-12-01
Leptospirosis became recently a major public-health problem that is closely related with the environment (Nature review Oct 2009, Vol 7, pp 736-747). This disease originates from zoonotic pathogens associated with asymptomatic rodent carriers. Unfortunately, it effects human populations via various direct and indirect routes. This disease can claim many victims with large outbreaks during natural disasters or floods occurring during seasonal conditions. The severity of the illness ranges from subclinical infection to a fulminating fatal disease. Improved water quality monitoring techniques based on biosensor, optical, micro-fluidic and information technologies are leading to radical changes in our ability to perceive and monitor the aquatic environment. Biosensors are capable of providing specific, high spatial resolution information and allow unattended operation that will be particularly useful for water borne related diseases. Current research on biosensors is leading to solutions to problems for several contaminants that were previously irresolvable due to their high degree of complexity. Networking of the sensors enables sensitive monitoring systems allowing real-time monitoring of pollutants and facilitates data transmission between the measurement points and central control stations for continuous surveillance and to provide an early warning capability. The application of intelligent biosensor networks for water quality monitoring and detection of localized sources of pollution are discussed together with the setting up of a methodology that utilizes images from satellite coupled with in-situ sensors for anticipating the zones of potential evolution of this disease and assessing the population at risk. Environmental and climatic conditions that are associated the outbreaks are described and the rational of combining earth observations coupled with advanced in-situ biosensors is explained. The implementation of sensor networks for data collection and exposure
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Sebastien Naze
2015-05-01
Full Text Available Epileptic seizure dynamics span multiple scales in space and time. Understanding seizure mechanisms requires identifying the relations between seizure components within and across these scales, together with the analysis of their dynamical repertoire. Mathematical models have been developed to reproduce seizure dynamics across scales ranging from the single neuron to the neural population. In this study, we develop a network model of spiking neurons and systematically investigate the conditions, under which the network displays the emergent dynamic behaviors known from the Epileptor, which is a well-investigated abstract model of epileptic neural activity. This approach allows us to study the biophysical parameters and variables leading to epileptiform discharges at cellular and network levels. Our network model is composed of two neuronal populations, characterized by fast excitatory bursting neurons and regular spiking inhibitory neurons, embedded in a common extracellular environment represented by a slow variable. By systematically analyzing the parameter landscape offered by the simulation framework, we reproduce typical sequences of neural activity observed during status epilepticus. We find that exogenous fluctuations from extracellular environment and electro-tonic couplings play a major role in the progression of the seizure, which supports previous studies and further validates our model. We also investigate the influence of chemical synaptic coupling in the generation of spontaneous seizure-like events. Our results argue towards a temporal shift of typical spike waves with fast discharges as synaptic strengths are varied. We demonstrate that spike waves, including interictal spikes, are generated primarily by inhibitory neurons, whereas fast discharges during the wave part are due to excitatory neurons. Simulated traces are compared with in vivo experimental data from rodents at different stages of the disorder. We draw the conclusion
Coupled dynamics of node and link states in complex networks: A model for language competition
Carro, Adrián; Miguel, Maxi San
2016-01-01
Inspired by language competition processes, we present a model of coupled evolution of node and link states. In particular, we focus on the interplay between the use of a language and the preference or attitude of the speakers towards it, which we model, respectively, as a property of the interactions between speakers (a link state) and as a property of the speakers themselves (a node state). Furthermore, we restrict our attention to the case of two socially equivalent languages and to socially inspired network topologies based on a mechanism of triadic closure. As opposed to most of the previous literature, where language extinction is an inevitable outcome of the dynamics, we find a broad range of possible asymptotic configurations, which we classify as: frozen extinction states, frozen coexistence states, and dynamically trapped coexistence states. Moreover, metastable coexistence states with very long survival times and displaying a non-trivial dynamics are found to be abundant. Interestingly, a system si...
Du, Songlin; Yan, Yaping; Ma, Yide
2015-03-01
A novel image segmentation algorithm which uses quantum entropy and pulse-coupled neural networks (PCNN) is proposed in this paper. Optimal iteration of the PCNN is one of the key factors affecting segmentation accuracy. We borrow quantum entropy from quantum information to act as a criterion in determining optimal iteration of the PCNN. Optimal iteration is captured while total quantum entropy of the segments reaches a maximum. Moreover, compared with other PCNN-employed algorithms, the proposed algorithm works without any manual intervention, because all parameters of the PCNN are set automatically. Experimental results prove that the proposed method can achieve much lower probabilities of error segmentation than other PCNN-based image segmentation algorithms, and this suggests that higher image segmentation quality is achieved by the proposed method.
Filtering images contaminated with pep and salt type noise with pulse-coupled neural networks
Institute of Scientific and Technical Information of China (English)
ZHANG Junying; LU Zhijun; SHI Lin; DONG Jiyang; SHI Meihong
2005-01-01
Pulse coupled neural network (PCNN) has a specific feature that the fire of one neuron can capture its adjacent neurons to fire due to their spatial proximity and intensity similarity. In this paper, it is indicated that this feature itself is a very good mechanism for image filtering when the image is damaged with pep and salt (PAS) type noise. An adaptive filtering method, in which the noisy pixels are first located and then filtered based on the output of the PCNN, is presented. The threshold function of a neuron in the PCNN is designed when it is used for filtering random PAS and extreme PAS noise contaminated image respectively. The filtered image has no distortion for noisy pixels and only less mistiness for non-noisy pixels, compared with the conventional window-based filtering method. Excellent experimental results show great effectiveness and efficiency of the proposed method, especially for heavy-noise contaminated images.
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Liang Xu
2013-01-01
Full Text Available In the nonsubsampled contourlet transform (NSCT domain, a novel image fusion algorithm based on the visual attention model and pulse coupled neural networks (PCNNs is proposed. For the fusion of high-pass subbands in NSCT domain, a saliency-motivated PCNN model is proposed. The main idea is that high-pass subband coefficients are combined with their visual saliency maps as input to motivate PCNN. Coefficients with large firing times are employed as the fused high-pass subband coefficients. Low-pass subband coefficients are merged to develop a weighted fusion rule based on firing times of PCNN. The fused image contains abundant detailed contents from source images and preserves effectively the saliency structure while enhancing the image contrast. The algorithm can preserve the completeness and the sharpness of object regions. The fused image is more natural and can satisfy the requirement of human visual system (HVS. Experiments demonstrate that the proposed algorithm yields better performance.
Stabilization of Networked Distributed Systems with Partial and Event-Based Couplings
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Sufang Zhang
2015-01-01
Full Text Available The stabilization problem of networked distributed systems with partial and event-based couplings is investigated. The channels, which are used to transmit different levels of information of agents, are considered. The channel matrix is introduced to indicate the work state of the channels. An event condition is designed for each channel to govern the sampling instants of the channel. Since the event conditions are separately given for different channels, the sampling instants of channels are mutually independent. To stabilize the system, the state feedback controllers are implemented in the system. The control signals also suffer from the two communication constraints. The sufficient conditions in terms of linear matrix equalities are proposed to ensure the stabilization of the controlled system. Finally, a numerical example is given to demonstrate the advantage of our results.
Energy Technology Data Exchange (ETDEWEB)
Lafranceschina, Jacopo, E-mail: jlafranceschina@alaska.edu; Wackerbauer, Renate, E-mail: rawackerbauer@alaska.edu [Department of Physics, University of Alaska, Fairbanks, Alaska 99775-5920 (United States)
2015-01-15
Spatiotemporal chaos collapses to either a rest state or a propagating pulse solution in a ring network of diffusively coupled, excitable Morris-Lecar neurons. Weak excitatory synapses can increase the Lyapunov exponent, expedite the collapse, and promote the collapse to the rest state rather than the pulse state. A single traveling pulse solution may no longer be asymptotic for certain combinations of network topology and (weak) coupling strengths, and initiate spatiotemporal chaos. Multiple pulses can cause chaos initiation due to diffusive and synaptic pulse-pulse interaction. In the presence of chaos initiation, intermittent spatiotemporal chaos exists until typically a collapse to the rest state.
Institute of Scientific and Technical Information of China (English)
MIN LeQuan; YU Na
2002-01-01
Some criteria for the local activity theory in two-port cellular neural network cells with three local state variables are applied to a coupled Lorenz-cell model. The numerical simulation exhibited that emergence may exist if the selected cell parameters are nearby or on the edge of chaos domain. The local activity theory has provided a new tool of studying the complexity of high dimensional coupled nonlinear physical systems.
Mosha, Idda H; Ruben, Ruerd
2013-09-01
Family planning utilization in Tanzania is low. This study was cross sectional. It examined family planning use and socio demographic variables, social networks, knowledge and communication among the couples, whereby a stratified sample of 440 women of reproductive age (18-49), married or cohabiting was studied in Mwanza, Tanzania. A structured questionnaire with questions on knowledge, communication among the couples and practice of family planning was used. Descriptive statistics and Logistic regression were used to identify factors associated with family planning (FP) use at four levels. The findings showed that majority (73.2%) of respondents have not used family planning. Wealth was positive related to FP use (p=.000, OR = 3.696, and 95% C.I = 1.936 lower and upper 7.055). Religion was associated with FP use (p=.002, OR =2.802, 95% C.I = 1.476 lower and 5.321 upper), communication and FP use were significantly associated, (p=.000, OR = 0.323 and 95% C.I = 0.215) lower and upper = 0.483), social network and FP use (p=.000, OR = 2.162 and 95% C.I = 1.495 lower and upper =3.125) and knowledge and FP use(p=.000, OR = 2.224 and 95% C.I = 1.509 lower and upper =3.278). Wealth showed a significant association with FP use (p=.001, OR = 1.897, 95% C.I = 0.817 lower and 4.404).Urban area was positively associated with FP use (p= .000, OR = 0.008 and 95% C.I = 0.001 lower and upper =0.09), semi urban was significant at (p= .004, OR = 3.733 and C.I = 1.513 lower and upper =9.211). Information, education and communication materials and to promote family planning in Tanzania should designed and promoted.
Lecrux, C; Hamel, E
2016-10-05
Brain imaging techniques that use vascular signals to map changes in neuronal activity, such as blood oxygenation level-dependent functional magnetic resonance imaging, rely on the spatial and temporal coupling between changes in neurophysiology and haemodynamics, known as 'neurovascular coupling (NVC)'. Accordingly, NVC responses, mapped by changes in brain haemodynamics, have been validated for different stimuli under physiological conditions. In the cerebral cortex, the networks of excitatory pyramidal cells and inhibitory interneurons generating the changes in neural activity and the key mediators that signal to the vascular unit have been identified for some incoming afferent pathways. The neural circuits recruited by whisker glutamatergic-, basal forebrain cholinergic- or locus coeruleus noradrenergic pathway stimulation were found to be highly specific and discriminative, particularly when comparing the two modulatory systems to the sensory response. However, it is largely unknown whether or not NVC is still reliable when brain states are altered or in disease conditions. This lack of knowledge is surprising since brain imaging is broadly used in humans and, ultimately, in conditions that deviate from baseline brain function. Using the whisker-to-barrel pathway as a model of NVC, we can interrogate the reliability of NVC under enhanced cholinergic or noradrenergic modulation of cortical circuits that alters brain states.This article is part of the themed issue 'Interpreting BOLD: a dialogue between cognitive and cellular neuroscience'.
Huijbers, Willem; Pennartz, Cyriel M. A.; Cabeza, Roberto; Daselaar, Sander M.
2011-01-01
The brain's default mode network (DMN) is activated during internally-oriented tasks and shows strong coherence in spontaneous rest activity. Despite a surge of recent interest, the functional role of the DMN remains poorly understood. Interestingly, the DMN activates during retrieval of past events but deactivates during encoding of novel events into memory. One hypothesis is that these opposing effects reflect a difference between attentional orienting towards internal events, such as retrieved memories, vs. external events, such as to-be-encoded stimuli. Another hypothesis is that hippocampal regions are coupled with the DMN during retrieval but decoupled from the DMN during encoding. The present fMRI study investigated these two hypotheses by combining a resting-state coherence analysis with a task that measured the encoding and retrieval of both internally-generated and externally-presented events. Results revealed that the main DMN regions were activated during retrieval but deactivated during encoding. Counter to the internal orienting hypothesis, this pattern was not modulated by whether memory events were internal or external. Consistent with the hippocampal coupling hypothesis, the hippocampus behaved like other DMN regions during retrieval but not during encoding. Taken together, our findings clarify the relationship between the DMN and the neural correlates of memory retrieval and encoding. PMID:21494597
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Willem Huijbers
Full Text Available The brain's default mode network (DMN is activated during internally-oriented tasks and shows strong coherence in spontaneous rest activity. Despite a surge of recent interest, the functional role of the DMN remains poorly understood. Interestingly, the DMN activates during retrieval of past events but deactivates during encoding of novel events into memory. One hypothesis is that these opposing effects reflect a difference between attentional orienting towards internal events, such as retrieved memories, vs. external events, such as to-be-encoded stimuli. Another hypothesis is that hippocampal regions are coupled with the DMN during retrieval but decoupled from the DMN during encoding. The present fMRI study investigated these two hypotheses by combining a resting-state coherence analysis with a task that measured the encoding and retrieval of both internally-generated and externally-presented events. Results revealed that the main DMN regions were activated during retrieval but deactivated during encoding. Counter to the internal orienting hypothesis, this pattern was not modulated by whether memory events were internal or external. Consistent with the hippocampal coupling hypothesis, the hippocampus behaved like other DMN regions during retrieval but not during encoding. Taken together, our findings clarify the relationship between the DMN and the neural correlates of memory retrieval and encoding.
Multi-field coupled sensing network for health monitoring of composite bolted joint
Wang, Yishou; Qing, Xinlin; Dong, Liang; Banerjee, Sourav
2016-04-01
Advanced fiber reinforced composite materials are becoming the main structural materials of next generation of aircraft because of their high strength and stiffness to weight ratios, and excellent designability. As key components of large composite structures, joints play important roles to ensure the integrity of the composite structures. However, it is very difficult to analyze the strength and failure modes of composite joints due to their complex nonlinear coupling factors. Therefore, there is a need to monitor, diagnose, evaluate and predict the structure state of composite joints. This paper proposes a multi-field coupled sensing network for health monitoring of composite bolted joints. Major work of this paper includes: 1) The concept of multifunctional sensor layer integrated with eddy current sensors, Rogowski coil and arrayed piezoelectric sensors; 2) Development of the process for integrating the eddy current sensor foil, Rogowski coil and piezoelectric sensor array in multifunctional sensor layer; 3) A new concept of smart composite joint with multifunctional sensing capability. The challenges for building such a structural state sensing system and some solutions to address the challenges are also discussed in the study.
Near-Field Coupling Communication Technology For Human-Area Networking
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Ryoji Nagai
2012-12-01
Full Text Available We propose a human-area networking technology that uses the surface of the human body as a data transmission path and uses near-field coupling TRXs. This technology aims to achieve a "touch and connect" form of communication and a new concept of "touch the world" by using a quasi-electrostatic field signal that propagates along the surface of the human body. This paper explains the principles underlying near-field coupling communication. Special attention has been paid to common-mode noise since our communication system is strongly susceptible to this. We designed and made a common-mode choke coil and a transformer to act as common-mode noise filters to suppress common-mode noise. Moreover, we describe how we evaluated the quality of communication using a phantom model with the same electrical properties as the human body and present the experimental results for the packet error rate (PER as a function of the signal to noise ratio (SNR both with the common-mode choke coil or the transformer and without them. Finally, we found that our system achieved a PER of less than 10-2 in general office rooms using raised floors, which corresponded to the quality of communication demanded by communication services in ordinary office spaces.
Near-Field Coupling Communication Technology For Human-Area Networking
Directory of Open Access Journals (Sweden)
Ryoji Nagai
2012-12-01
Full Text Available We propose a human-area networking technology that uses the surface of the human body as a data transmission path and uses near-field coupling TRXs. This technology aims to achieve a "touch and connect" form of communication and a new concept of "touch the world" by using a quasi-electrostatic field signal that propagates along the surface of the human body. This paper explains the principles underlying near-field coupling communication. Special attention has been paid to common-mode noise since our communication system is strongly susceptible to this. We designed and made a common-mode choke coil and a transformer to act as common-mode noise filters to suppress common-mode noise. Moreover, we describe how we evaluated the quality of communication using a phantom model with the same electrical properties as the human body and present the experimental results for the packet error rate (PER as a function of the signal to noise ratio (SNR both with the common-mode choke coil or the transformer and without them. Finally, we found that our system achieved a PER of less than 10-2 in general office rooms using raised floors, which corresponded to the quality of communication demanded by communication services in ordinary office spaces.
Network reciprocity created in prisoner's dilemma games by coupling two mechanisms
Tanimoto, Jun; Kishimoto, Nobuyuki
2015-04-01
We found that a nontrivial enhancement of network reciprocity for 2 × 2 prisoner's dilemma games can be achieved by coupling two mechanisms. The first mechanism presumes a larger strategy update neighborhood than the conventional first neighborhood on the underlying network. The second is the strategy-shifting rule. At the initial time step, the averaged cooperation extent is assumed to be 0.5. In the case of strategy shifting, an agent adopts a continuous strategy definition during the initial period of a simulation episode (when the global cooperation fraction decreases from its initial value of 0.5; that is, the enduring period). The agent then switches to a discrete strategy definition in the time period afterwards (when the global cooperation fraction begins to increase again; that is, the expanding period). We explored why this particular enhancement comes about, and to summarize, the continuous strategy during the initial period relaxes the conditions for the survival of relatively cooperative clusters, and the large strategy adaptation neighborhood allows those cooperative clusters to expand easily.
Elastic coupling of nascent apCAM adhesions to flowing actin networks.
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Cecile O Mejean
Full Text Available Adhesions are multi-molecular complexes that transmit forces generated by a cell's acto-myosin networks to external substrates. While the physical properties of some of the individual components of adhesions have been carefully characterized, the mechanics of the coupling between the cytoskeleton and the adhesion site as a whole are just beginning to be revealed. We characterized the mechanics of nascent adhesions mediated by the immunoglobulin-family cell adhesion molecule apCAM, which is known to interact with actin filaments. Using simultaneous visualization of actin flow and quantification of forces transmitted to apCAM-coated beads restrained with an optical trap, we found that adhesions are dynamic structures capable of transmitting a wide range of forces. For forces in the picoNewton scale, the nascent adhesions' mechanical properties are dominated by an elastic structure which can be reversibly deformed by up to 1 µm. Large reversible deformations rule out an interface between substrate and cytoskeleton that is dominated by a number of stiff molecular springs in parallel, and favor a compliant cross-linked network. Such a compliant structure may increase the lifetime of a nascent adhesion, facilitating signaling and reinforcement.
Cluster synchronization in networks of identical oscillators with α -function pulse coupling
Chen, Bolun; Engelbrecht, Jan R.; Mirollo, Renato
2017-02-01
We study a network of N identical leaky integrate-and-fire model neurons coupled by α -function pulses, weighted by a coupling parameter K . Studies of the dynamics of this system have mostly focused on the stability of the fully synchronized and the fully asynchronous splay states, which naturally depends on the sign of K , i.e., excitation vs inhibition. We find that there is also a rich set of attractors consisting of clusters of fully synchronized oscillators, such as fixed (N -1 ,1 ) states, which have synchronized clusters of sizes N -1 and 1, as well as splay states of clusters with equal sizes greater than 1. Additionally, we find limit cycles that clarify the stability of previously observed quasiperiodic behavior. Our framework exploits the neutrality of the dynamics for K =0 which allows us to implement a dimensional reduction strategy that simplifies the dynamics to a continuous flow on a codimension 3 subspace with the sign of K determining the flow direction. This reduction framework naturally incorporates a hierarchy of partially synchronized subspaces in which the new attracting states lie. Using high-precision numerical simulations, we describe completely the sequence of bifurcations and the stability of all fixed points and limit cycles for N =2 -4 . The set of possible attracting states can be used to distinguish different classes of neuron models. For instance from our previous work [Chaos 24, 013114 (2014), 10.1063/1.4858458] we know that of the types of partially synchronized states discussed here, only the (N -1 ,1 ) states can be stable in systems of identical coupled sinusoidal (i.e., Kuramoto type) oscillators, such as θ -neuron models. Upon introducing a small variation in individual neuron parameters, the attracting fixed points we discuss here generalize to equivalent fixed points in which neurons need not fire coincidently.
A turbulent transport network model in MULTIFLUX coupled with TOUGH2
Energy Technology Data Exchange (ETDEWEB)
Danko, G.; Bahrami, D.; Birkholzer, J.T.
2011-02-15
A new numerical method is described for the fully iterated, conjugate solution of two discrete submodels, involving (a) a transport network model for heat, moisture, and airflows in a high-permeability, air-filled cavity; and (b) a variably saturated fractured porous medium. The transport network submodel is an integrated-parameter, computational fluid dynamics solver, describing the thermal-hydrologic transport processes in the flow channel system of the cavity with laminar or turbulent flow and convective heat and mass transport, using MULTIFLUX. The porous medium submodel, using TOUGH2, is a solver for the heat and mass transport in the fractured rock mass. The new model solution extends the application fields of TOUGH2 by integrating it with turbulent flow and transport in a discrete flow network system. We present demonstrational results for a nuclear waste repository application at Yucca Mountain with the most realistic model assumptions and input parameters including the geometrical layout of the nuclear spent fuel and waste with variable heat load for the individual containers. The MULTIFLUX and TOUGH2 model elements are fully iterated, applying a programmed reprocessing of the Numerical Transport Code Functionalization model-element in an automated Outside Balance Iteration loop. The natural, convective airflow field and the heat and mass transport in a representative emplacement drift during postclosure are explicitly solved in the new model. The results demonstrate that the direction and magnitude of the air circulation patterns and all transport modes are strongly affected by the heat and moisture transport processes in the surrounding rock, justifying the need for a coupled, fully iterated model solution such as the one presented in the paper.
Abdelbaki, Chérifa; Benchaib, Mohamed Mouâd; Benziada, Salim; Mahmoudi, Hacène; Goosen, Mattheus
2016-04-01
For more effective management of water distribution network in an arid region, Mapinfo GIS (8.0) software was coupled with a hydraulic model (EPANET 2.0) and applied to a case study region, Chetouane, situated in the north-west of Algeria. The area is characterized not only by water scarcity but also by poor water management practices. The results showed that a combination of GIS and modeling permits network operators to better analyze malfunctions with a resulting more rapid response as well as facilitating in an improved understanding of the work performed on the network. The grouping of GIS and modeling as an operating tool allows managers to diagnosis a network, to study solutions of problems and to predict future situations. The later can assist them in making informed decisions to ensure an acceptable performance level for optimal network operation.
Abdelbaki, Chérifa; Benchaib, Mohamed Mouâd; Benziada, Salim; Mahmoudi, Hacène; Goosen, Mattheus
2017-06-01
For more effective management of water distribution network in an arid region, Mapinfo GIS (8.0) software was coupled with a hydraulic model (EPANET 2.0) and applied to a case study region, Chetouane, situated in the north-west of Algeria. The area is characterized not only by water scarcity but also by poor water management practices. The results showed that a combination of GIS and modeling permits network operators to better analyze malfunctions with a resulting more rapid response as well as facilitating in an improved understanding of the work performed on the network. The grouping of GIS and modeling as an operating tool allows managers to diagnosis a network, to study solutions of problems and to predict future situations. The later can assist them in making informed decisions to ensure an acceptable performance level for optimal network operation.
Ribeiro, Andre S.
2007-06-01
Genetic toggle switches (TSs) are one of the best studied small gene regulatory networks (GRNs), due to their simplicity and relevant role. They have been interpreted as decision circuits in cell differentiation, a process long hypothesized to be bistable [1], or as cellular memory units [2]. In these contexts, they must be reliable. Once a “decision” is made, the system must remain stable. One way to gain stability is by duplicating the genes of a TS and coupling the two TSs. Using a recent modeling strategy of GRNs, driven by a delayed stochastic simulation algorithm (delayed SSA) that allows modeling transcription and translation as multidelayed reactions, we analyze the stability of systems of coupled TSs. For this, we introduce the coupling strength (C) , a parameter to characterize the GRN structure, against which we compare the GRN stability (S) . We first show that time delays in transcription, associated to the promoter region release, ensure bistability of a TS, given no cooperative binding or self-activation reactions. Next, we couple two TSs and measure their toggling frequencies as C varies. Three dynamical regimes are observed: (i) for weak coupling, high frequency synchronized oscillations, (ii) for average coupling, low frequency synchronized oscillations, and (iii) for strong coupling the system becomes stable after a transient, in one of two steady states. The system stability, S , goes through a first order phase transition as C increases, in the average coupling regime. After, we study the effects of spatial separation in two compartments on the dynamics of two coupled TSs, where spatial separation is modeled as normally distributed random time delayed reactions. The phase transition of S , as C increases, occurs for lower values of C than when the two TSs are in the same compartment. Finally, we couple weakly and homogeneously several TSs within a single compartment and observe that as the number of coupled TSs increases, the system goes
Tiwari, Abhinav; Igoshin, Oleg A
2012-10-01
Biochemical regulatory networks governing diverse cellular processes such as stress-response, differentiation and cell cycle often contain coupled feedback loops. We aim at understanding how features of feedback architecture, such as the number of loops, the sign of the loops and the type of their coupling, affect network dynamical performance. Specifically, we investigate how bistability range, maximum open-loop gain and switching times of a network with transcriptional positive feedback are affected by additive or multiplicative coupling with another positive- or negative-feedback loop. We show that a network's bistability range is positively correlated with its maximum open-loop gain and that both quantities depend on the sign of the feedback loops and the type of feedback coupling. Moreover, we find that the addition of positive feedback could decrease the bistability range if we control the basal level in the signal-response curves of the two systems. Furthermore, the addition of negative feedback has the capacity to increase the bistability range if its dissociation constant is much lower than that of the positive feedback. We also find that the addition of a positive feedback to a bistable network increases the robustness of its bistability range, whereas the addition of a negative feedback decreases it. Finally, we show that the switching time for a transition from a high to a low steady state increases with the effective fold change in gene regulation. In summary, we show that the effect of coupled feedback loops on the bistability range and switching times depends on the underlying mechanistic details.
Directory of Open Access Journals (Sweden)
George Chukwudi Nganya
2016-01-01
Full Text Available The increase in demand for real-time applications such as video and audio streams data transfer has resulted in the need to find a means of managing the increasing numbers of users in the mobile wireless system without affecting the quality of service (QoS requirements. In their work, A. K. Salkintzis, C. Fors, and R. Pazhyannur, stated that one of the approaches to meeting the high user demands is to interwork two different but complementary networks, the Universal Mobile Telecommunication Systems (UMTS which has a high mobility but low-data rate circuit-switched and packet-switched services, and the Wireless Local Area Network (WLAN which has a high-data rate circuit-switched service but limited mobility coverage confined to a smaller area called the hot-spot [1]. The idea is to interwork the two networks such that seamless mobility could be achieved. In this paper, the tight coupling of the WLAN at the SGSN of the UMTS for the possibility of achieving a seamless mobility is examined. The performance of this integration approach is evaluated using this QoS parameters, namely buffer overflow, Ethernet delay, throughput and Ethernet load. A simulation of this integration approach using an OPNET Modeler 14.0 is performed and the simulation results analyzed. We performed a simulation of the WLAN AP tightly coupled to the SGSN node of the UMTS network. Also performed in this research are simulations of different scenarios of the tight coupling approach at the SGSN by varying the number of users in the integrated UMTS and WLAN network to show the effect the number of users connected to both networks has towards achieving seamless mobility in the interworked network. From our study review and the simulation results of this interworking approach, we propose that coupling the WLAN AP and the UMTS network at the SGSN of the UMTS, and using a suitable mobility protocol, has the possibility of providing a seamless mobility between these complementary
Directory of Open Access Journals (Sweden)
Changgui Gu
Full Text Available The suprachiasmatic nucleus (SCN is the master circadian clock in mammals and is composed of thousands of neuronal oscillators expressing different intrinsic periods. These oscillators form a coupled network with a free-running period around 24 h in constant darkness and entrainable to the external light-dark cycle (T cycle. Coupling plays an important role in setting the period of the network and its range of entrainment. Experiments in rats have shown that two subgroups of oscillators within the SCN, a ventrolateral (VL subgroup that receives photic input and a dorsomedial (DM subgroup that is coupled to VL, can be desynchronized under a short (22-h T cycle, with VL entrained to the cycle and DM free-running. We use a modified Goodwin model to understand how entrainment of the subgroups to short (22-h and long (26-h T cycles is influenced by light intensity, the proportion of neurons that receives photic input, and coupling heterogeneity. We find that the model's critical value for the proportion of photically-sensitive neurons is in accord with actual experimental estimates, while the model's inclusion of dispersed coupling can account for the experimental observation that VL and DM desynchronize more readily under the 22-h than under the 26-h T cycle. Heterogeneous intercellular coupling within the SCN is likely central to the generation of complex behavioral patterns.
Institute of Scientific and Technical Information of China (English)
2016-01-01
Soil moisture simulation and prediction in semi-arid regions are important for agricultural production, soil conservation andclimate change. However, considerable heterogeneity in the spatial distribution of soil moisture, and poor ability of distributedhydrological models to estimate it, severely impact the use of soil moisture models in research and practical applications. Inthis study, a newly-developed technique of coupled （WA-ANN） wavelet analysis （WA） and artificial neural network （ANN）was applied for a multi-layer soil moisture simulation in the Pailugou catchment of the Qilian Mountains, Gansu Province,China. Datasets included seven meteorological factors： air and land surface temperatures, relative humidity, global radiation,atmospheric pressure, wind speed, precipitation, and soil water content at 20, 40, 60, 80, 120 and 160 cm. To investigate theeffectiveness of WA-ANN, ANN was applied by itself to conduct a comparison. Three main findings of this study were： （1）ANN and WA-ANN provided a statistically reliable and robust prediction of soil moisture in both the root zone and deepestsoil layer studied （NSE 〉0.85, NSE means Nash-Sutcliffe Efficiency coefficient）; （2） when input meteorological factors weretransformed using maximum signal to noise ratio （SNR） and one-dimensional auto de-noising algorithm （heursure） in WA,the coupling technique improved the performance of ANN especially for soil moisture at 160 cm depth; （3） the results ofmulti-layer soil moisture prediction indicated that there may be different sources of water at different soil layers, and this canbe used as an indicator of the maximum impact depth of meteorological factors on the soil water content at this study site. Weconclude that our results show that appropriate simulation methodology can provide optimal simulation with a minimumdistortion of the raw-time series; the new method used here is applicable to soil sciences and management
Institute of Scientific and Technical Information of China (English)
JunJun Yang; ZhiBin He; WeiJun Zhao; Jun Du; LongFei Chen; Xi Zhu
2016-01-01
Soil moisture simulation and prediction in semi-arid regions are important for agricultural production, soil conservation and climate change. However, considerable heterogeneity in the spatial distribution of soil moisture, and poor ability of distributed hydrological models to estimate it, severely impact the use of soil moisture models in research and practical applications. In this study, a newly-developed technique of coupled (WA-ANN) wavelet analysis (WA) and artificial neural network (ANN) was applied for a multi-layer soil moisture simulation in the Pailugou catchment of the Qilian Mountains, Gansu Province, China. Datasets included seven meteorological factors: air and land surface temperatures, relative humidity, global radiation, atmospheric pressure, wind speed, precipitation, and soil water content at 20, 40, 60, 80, 120 and 160 cm. To investigate the effectiveness of WA-ANN, ANN was applied by itself to conduct a comparison. Three main findings of this study were: (1) ANN and WA-ANN provided a statistically reliable and robust prediction of soil moisture in both the root zone and deepest soil layer studied (NSE >0.85, NSE means Nash-Sutcliffe Efficiency coefficient); (2) when input meteorological factors were transformed using maximum signal to noise ratio (SNR) and one-dimensional auto de-noising algorithm (heursure) in WA, the coupling technique improved the performance of ANN especially for soil moisture at 160 cm depth; (3) the results of multi-layer soil moisture prediction indicated that there may be different sources of water at different soil layers, and this can be used as an indicator of the maximum impact depth of meteorological factors on the soil water content at this study site. We conclude that our results show that appropriate simulation methodology can provide optimal simulation with a minimum distortion of the raw-time series; the new method used here is applicable to soil sciences and management applications.
Barreiro, Andrea K; Gautam, Shree Hari; Shew, Woodrow L; Ly, Cheng
2017-10-02
Determining how synaptic coupling within and between regions is modulated during sensory processing is an important topic in neuroscience. Electrophysiological recordings provide detailed information about neural spiking but have traditionally been confined to a particular region or layer of cortex. Here we develop new theoretical methods to study interactions between and within two brain regions, based on experimental measurements of spiking activity simultaneously recorded from the two regions. By systematically comparing experimentally-obtained spiking statistics to (efficiently computed) model spike rate statistics, we identify regions in model parameter space that are consistent with the experimental data. We apply our new technique to dual micro-electrode array in vivo recordings from two distinct regions: olfactory bulb (OB) and anterior piriform cortex (PC). Our analysis predicts that: i) inhibition within the afferent region (OB) has to be weaker than the inhibition within PC, ii) excitation from PC to OB is generally stronger than excitation from OB to PC, iii) excitation from PC to OB and inhibition within PC have to both be relatively strong compared to presynaptic inputs from OB. These predictions are validated in a spiking neural network model of the OB-PC pathway that satisfies the many constraints from our experimental data. We find when the derived relationships are violated, the spiking statistics no longer satisfy the constraints from the data. In principle this modeling framework can be adapted to other systems and be used to investigate relationships between other neural attributes besides network connection strengths. Thus, this work can serve as a guide to further investigations into the relationships of various neural attributes within and across different regions during sensory processing.
Kalteh, Aman Mohammad
2013-04-01
Reliable and accurate forecasts of river flow is needed in many water resources planning, design development, operation and maintenance activities. In this study, the relative accuracy of artificial neural network (ANN) and support vector regression (SVR) models coupled with wavelet transform in monthly river flow forecasting is investigated, and compared to regular ANN and SVR models, respectively. The relative performance of regular ANN and SVR models is also compared to each other. For this, monthly river flow data of Kharjegil and Ponel stations in Northern Iran are used. The comparison of the results reveals that both ANN and SVR models coupled with wavelet transform, are able to provide more accurate forecasting results than the regular ANN and SVR models. However, it is found that SVR models coupled with wavelet transform provide better forecasting results than ANN models coupled with wavelet transform. The results also indicate that regular SVR models perform slightly better than regular ANN models.
DEFF Research Database (Denmark)
Montagud, Arnau; Zelezniak, Aleksej; Navarro, Emilio
2011-01-01
activities and metabolic physiology, flux coupling analysis was performed for iSyn811 under four different growth conditions, viz., autotrophy, mixotrophy, heterotrophy, and light-activated heterotrophy (LH). Initial steps of carbon acquisition and catabolism formed the versatile center of the flux coupling...... and reporter flux coupling groups - regulatory hot spots during metabolic shifts triggered by the availability of light. Overall, flux coupling analysis provided insight into the structural organization of Synechocystis sp. PCC6803 metabolic network toward designing of a photosynthesis-based production......-scale metabolic model is a pre-requisite toward achieving a proficient photosynthetic cell factory. To this end, we report iSyn811, an upgraded genome-scale metabolic model of Synechocystis sp. PCC6803 consisting of 956 reactions and accounting for 811 genes. To gain insights into the interplay between flux...
Optimization of a hardware implementation for pulse coupled neural networks for image applications
Gimeno Sarciada, Jesús; Lamela Rivera, Horacio; Warde, Cardinal
2010-04-01
Pulse Coupled Neural Networks are a very useful tool for image processing and visual applications, since it has the advantages of being invariant to image changes as rotation, scale, or certain distortion. Among other characteristics, the PCNN changes a given image input into a temporal representation which can be easily later analyzed for pattern recognition. The structure of a PCNN though, makes it necessary to determine all of its parameters very carefully in order to function optimally, so that the responses to the kind of inputs it will be subjected are clearly discriminated allowing for an easy and fast post-processing yielding useful results. This tweaking of the system is a taxing process. In this paper we analyze and compare two methods for modeling PCNNs. A purely mathematical model is programmed and a similar circuital model is also designed. Both are then used to determine the optimal values of the several parameters of a PCNN: gain, threshold, time constants for feed-in and threshold and linking leading to an optimal design for image recognition. The results are compared for usefulness, accuracy and speed, as well as the performance and time requirements for fast and easy design, thus providing a tool for future ease of management of a PCNN for different tasks.
Fu, J C; Chen, C C; Chai, J W; Wong, S T C; Li, I C
2010-06-01
We propose an automatic hybrid image segmentation model that integrates the statistical expectation maximization (EM) model and the spatial pulse coupled neural network (PCNN) for brain magnetic resonance imaging (MRI) segmentation. In addition, an adaptive mechanism is developed to fine tune the PCNN parameters. The EM model serves two functions: evaluation of the PCNN image segmentation and adaptive adjustment of the PCNN parameters for optimal segmentation. To evaluate the performance of the adaptive EM-PCNN, we use it to segment MR brain image into gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF). The performance of the adaptive EM-PCNN is compared with that of the non-adaptive EM-PCNN, EM, and Bias Corrected Fuzzy C-Means (BCFCM) algorithms. The result is four sets of boundaries for the GM and the brain parenchyma (GM+WM), the two regions of most interest in medical research and clinical applications. Each set of boundaries is compared with the golden standard to evaluate the segmentation performance. The adaptive EM-PCNN significantly outperforms the non-adaptive EM-PCNN, EM, and BCFCM algorithms in gray mater segmentation. In brain parenchyma segmentation, the adaptive EM-PCNN significantly outperforms the BCFCM only. However, the adaptive EM-PCNN is better than the non-adaptive EM-PCNN and EM on average. We conclude that of the three approaches, the adaptive EM-PCNN yields the best results for gray matter and brain parenchyma segmentation.
Knowledge evolution in physics research: An analysis of bibliographic coupling networks.
Liu, Wenyuan; Nanetti, Andrea; Cheong, Siew Ann
2017-01-01
Even as we advance the frontiers of physics knowledge, our understanding of how this knowledge evolves remains at the descriptive levels of Popper and Kuhn. Using the American Physical Society (APS) publications data sets, we ask in this paper how new knowledge is built upon old knowledge. We do so by constructing year-to-year bibliographic coupling networks, and identify in them validated communities that represent different research fields. We then visualize their evolutionary relationships in the form of alluvial diagrams, and show how they remain intact through APS journal splits. Quantitatively, we see that most fields undergo weak Popperian mixing, and it is rare for a field to remain isolated/undergo strong mixing. The sizes of fields obey a simple linear growth with recombination. We can also reliably predict the merging between two fields, but not for the considerably more complex splitting. Finally, we report a case study of two fields that underwent repeated merging and splitting around 1995, and how these Kuhnian events are correlated with breakthroughs on Bose-Einstein condensation (BEC), quantum teleportation, and slow light. This impact showed up quantitatively in the citations of the BEC field as a larger proportion of references from during and shortly after these events.
Image segmentation of em bryonic plant cell using pulse-coupled neural networks
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
Traditional image segmentation algorithms exhibit weak performance for plant cells which have complex structure. On the other hand, pulse-coupled neural network (PCNN) based on Eckhorn's model of the cat visual cortex should be suitable to the segmentation of plant cell image.But the present theories cannot explain the relationship between the parameters of PCNN mathematical model and the effect of segmentation. Satisfactory results usually require time-consuming selection of experimental parameters. Meanwhile, in a proper, selected parametric model, the number of iteration determines the segmented effect evaluated by visual judgment, which decreases the efficiency of image segmentation. To avoid these flaws, this note proposes a new PCNN algorithm for automatically segmenting plant embryonic cell image based on the maximum entropy principle. The algorithm produces a desirable result. In addition, a model with proper parameters can automatically determine the number of iteration, avoid visual judgment, enhance the speed of segmentation and will be utilized subsequently by accurate quantitative analysis of micro-molecules of plant cell. So this algorithm is valuable for theoretical investigation and application of PCNN.``
[Qualitative analysis of Raman spectra based on pulse coupled neural network].
Wang, Cheng; Li, Shao-fa; Wu, Zheng-jie; He, Kai; Huang, Yao-xiong
2010-09-01
By studying on pulse coupled neural network (PCNN) and Raman spectra qualitative analysis, a method based on PCNN for Raman spectra qualitative analysis was proposed. After encoding the Raman spectra by using PCNN neurons' characteristics of fatigue and refractory period, the improved Horspool algorithm was used to match the code corresponding to the detected sample with all of the base code in the database one by one, and then their matching similarity was acquired to determine the sample type. Experimental results and analysis of data proved that the method proposed in this paper is accurate and effective for Raman spectra qualitative analysis. Meanwhile, traditional qualitative analysis method based on spectral template has some deficiencies, like that it is difficult to determine the characteristic peak of the detected sample and the matching analysis process has a high degree of redundancy. While our proposed method not only can avoid these deficiencies very well, but also needs a small amount of data storage. The requirement of the storage space was only 5.8% of that used in the traditional qualitative analysis method based on spectral template.
Blood Cell Segmentation Based on Improved Pulse Coupled Neural Network and Fuzzy Entropy
Directory of Open Access Journals (Sweden)
Zhanbo Liu
2016-12-01
Full Text Available In the field of biomedical image processing, because of the low intensity and brightness of the cell image, and the complex structure of the cell image, the segmentation of cell images is very difficult. A large number of studies have shown that the Pulse Coupled Neural Networks (PCNN is suitable for image segmentation. However, the traditional PCNN must set a large number of parameters in image segmentation, and the optimal number of iterations cannot be automatically determined. In this paper, a new improved PCNN model is proposed. The work of improved PCNN includes the acceptance portion of the PCNN model being simplified and the connection portion of PCNN being improved. In addition, the maximum fuzzy entropy is used as the criterion to determine the optimal number of iterations. Experimental results on blood cell image segmentation show that this proposed method can automatically determine the number of loop iterations and automatically select the best threshold. It also has the characteristics of fast convergence, high accuracy and good segmentation effect in blood cell image segmentation processing.
Energy Technology Data Exchange (ETDEWEB)
Huang, Hai; Plummer, Mitchell; Podgorney, Robert
2013-02-01
Advancement of EGS requires improved prediction of fracture development and growth during reservoir stimulation and long-term operation. This, in turn, requires better understanding of the dynamics of the strongly coupled thermo-hydro-mechanical (THM) processes within fractured rocks. We have developed a physically based rock deformation and fracture propagation simulator by using a quasi-static discrete element model (DEM) to model mechanical rock deformation and fracture propagation induced by thermal stress and fluid pressure changes. We also developed a network model to simulate fluid flow and heat transport in both fractures and porous rock. In this paper, we describe results of simulations in which the DEM model and network flow & heat transport model are coupled together to provide realistic simulation of the changes of apertures and permeability of fractures and fracture networks induced by thermal cooling and fluid pressure changes within fractures. Various processes, such as Stokes flow in low velocity pores, convection-dominated heat transport in fractures, heat exchange between fluid-filled fractures and solid rock, heat conduction through low-permeability matrices and associated mechanical deformations are all incorporated into the coupled model. The effects of confining stresses, developing thermal stress and injection pressure on the permeability evolution of fracture and fracture networks are systematically investigated. Results are summarized in terms of implications for the development and evolution of fracture distribution during hydrofracturing and thermal stimulation for EGS.
Directory of Open Access Journals (Sweden)
Fuchun Ren
2015-01-01
Full Text Available Risk and resilience are important and challenging issues in complex network systems since a single failure may trigger a whole collapse of the systems due to cascading effect. New theories, models, and methods are urgently demanded to deal with this challenge. In this paper, a coupled map lattices (CML based approach is adopted to analyze the risk of cascading process in Watts-Strogatz (WS small-world network and Barabási and Albert (BA scale-free network, respectively. Then, to achieve an effective and robust system and provide guidance in countering the cascading failure, a modified CML model with recovery strategy factor is proposed. Numerical simulations are put forward based on small-world CML and scale-free CML. The simulation results reveal that appropriate recovery strategies would significantly improve the resilience of networks.
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H. L. Sneha
2013-01-01
Full Text Available The current focus in defense arena is towards the stealth technology with an emphasis to control the radar cross-section (RCS. The scattering from the antennas mounted over the platform is of prime importance especially for a low-observable aerospace vehicle. This paper presents the analysis of the scattering cross section of a uniformly spaced linear dipole array. Two types of feed networks, that is, series and parallel feed networks, are considered. The total RCS of phased array with either kind of feed network is obtained by following the signal as it enters through the aperture and travels through the feed network. The RCS estimation of array is done including the mutual coupling effect between the dipole elements in three configurations, that is, side-by-side, collinear, and parallel-in-echelon. The results presented can be useful while designing a phased array with optimum performance towards low observability.
Hines, David E.; Lisa, Jessica A.; Song, Bongkeun; Tobias, Craig R.; Borrett, Stuart R.
2012-06-01
Estuaries serve important ecological and economic functions including habitat provision and the removal of nutrients. Eutrophication can overwhelm the nutrient removal capacity of estuaries and poses a widely recognized threat to the health and function of these ecosystems. Denitrification and anaerobic ammonium oxidation (anammox) are microbial processes responsible for the removal of fixed nitrogen and diminish the effects of eutrophication. Both of these microbial removal processes can be influenced by direct inputs of dissolved inorganic nitrogen substrates or supported by microbial interactions with other nitrogen transforming pathways such as nitrification and dissimilatory nitrate reduction to ammonium (DNRA). The coupling of nitrogen removal pathways to other transformation pathways facilitates the removal of some forms of inorganic nitrogen; however, differentiating between direct and coupled nitrogen removal is difficult. Network modeling provides a tool to examine interactions among microbial nitrogen cycling processes and to determine the within-system history of nitrogen involved in denitrification and anammox. To examine the coupling of nitrogen cycling processes, we built a nitrogen budget mass balance network model in two adjacent 1 cm3 sections of bottom water and sediment in the oligohaline portion of the Cape Fear River Estuary, NC, USA. Pathway, flow, and environ ecological network analyses were conducted to characterize the organization of nitrogen flow in the estuary and to estimate the coupling of nitrification to denitrification and of nitrification and DNRA to anammox. Centrality analysis indicated NH4+ is the most important form of nitrogen involved in removal processes. The model analysis further suggested that direct denitrification and coupled nitrification-denitrification had similar contributions to nitrogen removal while direct anammox was dominant to coupled forms of anammox. Finally, results also indicated that partial
Energy Technology Data Exchange (ETDEWEB)
Wu Hao; Jiang Huijun [Hefei National Laboratory for Physical Sciences at the Microscale and Department of Chemical Physics, University of Science and Technology of China, Hefei, Anhui 230026 (China); Hou Zhonghuai, E-mail: hzhlj@ustc.edu.cn [Hefei National Laboratory for Physical Sciences at the Microscale and Department of Chemical Physics, University of Science and Technology of China, Hefei, Anhui 230026 (China)
2011-10-15
Highlights: > We compare neuronal dynamics in dependence on two types of delayed coupling. > Distinct results induced by different delayed coupling can be achieved. > Time delays in type 1 coupling can induce a most spatiotemporal ordered state. > For type 2 coupling, the systems exhibit synchronization transitions with delay. - Abstract: We investigate temporal coherence and spatial synchronization on small-world networks consisting of noisy Terman-Wang (TW) excitable neurons in dependence on two types of time-delayed coupling: {l_brace}x{sub j}(t - {tau}) - x{sub i}(t){r_brace} and {l_brace}x{sub j}(t - {tau}) - x{sub i}(t - {tau}){r_brace}. For the former case, we show that time delay in the coupling can dramatically enhance temporal coherence and spatial synchrony of the noise-induced spike trains. In addition, if the delay time {tau} is tuned to nearly match the intrinsic spike period of the neuronal network, the system dynamics reaches a most ordered state, which is both periodic in time and nearly synchronized in space, demonstrating an interesting resonance phenomenon with delay. For the latter case, however, we cannot achieve a similar spatiotemporal ordered state, but the neuronal dynamics exhibits interesting synchronization transitions with time delay from zigzag fronts of excitations to dynamic clustering anti-phase synchronization (APS), and further to clustered chimera states which have spatially distributed anti-phase coherence separated by incoherence. Furthermore, we also show how these findings are influenced by the change of the noise intensity and the rewiring probability of the small-world networks. Finally, qualitative analysis is given to illustrate the numerical results.
Tang, Chen; Lu, Wenjing; Chen, Song; Zhang, Zhen; Li, Botao; Wang, Wenping; Han, Lin
2007-10-20
We extend and refine previous work [Appl. Opt. 46, 2907 (2007)]. Combining the coupled nonlinear partial differential equations (PDEs) denoising model with the ordinary differential equations enhancement method, we propose the new denoising and enhancing model for electronic speckle pattern interferometry (ESPI) fringe patterns. Meanwhile, we propose the backpropagation neural networks (BPNN) method to obtain unwrapped phase values based on a skeleton map instead of traditional interpolations. We test the introduced methods on the computer-simulated speckle ESPI fringe patterns and experimentally obtained fringe pattern, respectively. The experimental results show that the coupled nonlinear PDEs denoising model is capable of effectively removing noise, and the unwrapped phase values obtained by the BPNN method are much more accurate than those obtained by the well-known traditional interpolation. In addition, the accuracy of the BPNN method is adjustable by changing the parameters of networks such as the number of neurons.
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Hrishikesh M Rao
2016-06-01
Full Text Available As we look around a scene, we perceive it as continuous and stable even though each saccadic eye movement changes the visual input to the retinas. How the brain achieves this perceptual stabilization is unknown, but a major hypothesis is that it relies on presaccadic remapping, a process in which neurons shift their visual sensitivity to a new location in the scene just before each saccade. This hypothesis is difficult to test in vivo because complete, selective inactivation of remapping is currently intractable. We tested it in silico with a hierarchical, sheet-based neural network model of the visual and oculomotor system. The model generated saccadic commands to move a video camera abruptly. Visual input from the camera and internal copies of the saccadic movement commands, or corollary discharge, converged at a map-level simulation of the frontal eye field (FEF, a primate brain area known to receive such inputs. FEF output was combined with eye position signals to yield a suitable coordinate frame for guiding arm movements of a robot. Our operational definition of perceptual stability was useful stability, quantified as continuously accurate pointing to a visual object despite camera saccades. During training, the emergence of useful stability was correlated tightly with the emergence of presaccadic remapping in the FEF. Remapping depended on corollary discharge but its timing was synchronized to the updating of eye position. When coupled to predictive eye position signals, remapping served to stabilize the target representation for continuously accurate pointing. Graded inactivations of pathways in the model replicated, and helped to interpret, previous in vivo experiments. The results support the hypothesis that visual stability requires presaccadic remapping, provide explanations for the function and timing of remapping, and offer testable hypotheses for in vivo studies. We conclude that remapping allows for seamless coordinate frame
Xie, Weiying; Ma, Yide; Li, Yunsong
2015-05-01
A novel approach to mammographic image segmentation, termed as PCNN-based level set algorithm, is presented in this paper. Just as its name implies, a method based on pulse coupled neural network (PCNN) in conjunction with the variational level set method for medical image segmentation. To date, little work has been done on detecting the initial zero level set contours based on PCNN algorithm for latterly level set evolution. When all the pixels of the input image are fired by PCNN, the small pixel value will be a much more refined segmentation. In mammographic image, the breast tumor presents big pixel value. Additionally, the mammographic image with predominantly dark region, so that we firstly obtain the negative of mammographic image with predominantly dark region except the breast tumor before all the pixels of an input image are fired by PCNN. Therefore, in here, PCNN algorithm is employed to achieve mammary-specific, initial mass contour detection. After that, the initial contours are all extracted. We define the extracted contours as the initial zero level set contours for automatic mass segmentation by variational level set in mammographic image analysis. What's more, a new proposed algorithm improves external energy of variational level set method in terms of mammographic images in low contrast. In accordance with the gray scale of mass region in mammographic image is higher than the region surrounded, so the Laplace operator is used to modify external energy, which could make the bright spot becoming much brighter than the surrounded pixels in the image. A preliminary evaluation of the proposed method performs on a known public database namely MIAS, rather than synthetic images. The experimental results demonstrate that our proposed approach can potentially obtain better masses detection results in terms of sensitivity and specificity. Ultimately, this algorithm could lead to increase both sensitivity and specificity of the physicians' interpretation of
Coupled dynamics of node and link states in complex networks: a model for language competition
Carro, Adrián; Toral, Raúl; San Miguel, Maxi
2016-11-01
Inspired by language competition processes, we present a model of coupled evolution of node and link states. In particular, we focus on the interplay between the use of a language and the preference or attitude of the speakers towards it, which we model, respectively, as a property of the interactions between speakers (a link state) and as a property of the speakers themselves (a node state). Furthermore, we restrict our attention to the case of two socially equivalent languages and to socially inspired network topologies based on a mechanism of triadic closure. As opposed to most of the previous literature, where language extinction is an inevitable outcome of the dynamics, we find a broad range of possible asymptotic configurations, which we classify as: frozen extinction states, frozen coexistence states, and dynamically trapped coexistence states. Moreover, metastable coexistence states with very long survival times and displaying a non-trivial dynamics are found to be abundant. Interestingly, a system size scaling analysis shows, on the one hand, that the probability of language extinction vanishes exponentially for increasing system sizes and, on the other hand, that the time scale of survival of the non-trivial dynamical metastable states increases linearly with the size of the system. Thus, non-trivial dynamical coexistence is the only possible outcome for large enough systems. Finally, we show how this coexistence is characterized by one of the languages becoming clearly predominant while the other one becomes increasingly confined to ‘ghetto-like’ structures: small groups of bilingual speakers arranged in triangles, with a strong preference for the minority language, and using it for their intra-group interactions while they switch to the predominant language for communications with the rest of the population.
Directory of Open Access Journals (Sweden)
Kavitha SRINIVASAN
2014-09-01
Full Text Available Background: In the review of medical imaging techniques, an important fact that emerged is that radiologists and physicians still are in a need of high-resolution medical images with complementary information from different modalities to ensure efficient analysis. This requirement should have been sorted out using fusion techniques with the fused image being used in image-guided surgery, image-guided radiotherapy and non-invasive diagnosis. Aim: This paper focuses on Dual Channel Pulse Coupled Neural Network (PCNN Algorithm for fusion of multimodality brain images and the fused image is further analyzed using subjective (human perception and objective (statistical measures for the quality analysis. Material and Methods: The modalities used in fusion are CT, MRI with subtypes T1/T2/PD/GAD, PET and SPECT, since the information from each modality is complementary to one another. The objective measures selected for evaluation of fused image were: Information Entropy (IE - image quality, Mutual Information (MI – deviation in fused to the source images and Signal to Noise Ratio (SNR – noise level, for analysis. Eight sets of brain images with different modalities (T2 with T1, T2 with CT, PD with T2, PD with GAD, T2 with GAD, T2 with SPECT-Tc, T2 with SPECT-Ti, T2 with PET are chosen for experimental purpose and the proposed technique is compared with existing fusion methods such as the Average method, the Contrast pyramid, the Shift Invariant Discrete Wavelet Transform (SIDWT with Harr and the Morphological pyramid, using the selected measures to ascertain relative performance. Results: The IE value and SNR value of the fused image derived from dual channel PCNN is higher than other fusion methods, shows that the quality is better with less noise. Conclusion: The fused image resulting from the proposed method retains the contrast, shape and texture as in source images without false information or information loss.
Wang, Kai; Teng, Zhidong; Jiang, Haijun
2012-10-01
In this paper, the adaptive synchronization in an array of linearly coupled neural networks with reaction-diffusion terms and time delays is discussed. Based on the LaSalle invariant principle of functional differential equations and the adaptive feedback control technique, some sufficient conditions for adaptive synchronization of such a system are obtained. Finally, a numerical example is given to show the effectiveness of the proposed synchronization method.
Jafri, Madiha; Ely, Jay; Vahala, Linda
2006-01-01
Neural Network Modeling is introduced in this paper to classify and predict Interference Path Loss measurements on Airbus 319 and 320 airplanes. Interference patterns inside the aircraft are classified and predicted based on the locations of the doors, windows, aircraft structures and the communication/navigation system-of-concern. Modeled results are compared with measured data and a plan is proposed to enhance the modeling for better prediction of electromagnetic coupling problems inside aircraft.
Cohen, Eyal; Malka, Dror; Shemer, Amir; Shahmoon, Asaf; London, Michael; Zalevsky, Zeev
2017-02-01
Hardware implementation of artificial neural networks facilitates real-time parallel processing of massive data sets. Optical neural networks offer low-volume 3D connectivity together with large bandwidth and minimal heat production in contrast to electronic implementation. Here, we present a DMD based approaches to realize energetically efficient light coupling into a multi-core fiber realizing a unique design for in-fiber optical neural networks. Neurons and synapses are realized as individual cores in a multi-core fiber. Optical signals are transferred transversely between cores by means of optical coupling. Pump driven amplification in Erbium-doped cores mimics synaptic interactions. In order to dynamically and efficiently couple light into the multi-core fiber a DMD based micro mirror device is used to perform proper beam shaping operation. The beam shaping reshapes the light into a large set of points in space matching the positions of the required cores in the entrance plane to the multi-core fiber.
Huang, Zhihua; Lin, Honghuan; Xu, Dangpeng; Li, Mingzhong; Wang, Jianjun; Deng, Ying; Zhang, Rui; Zhang, Yongliang; Tian, Xiaocheng; Wei, Xiaofeng
2013-07-15
Collective laser coupling of the fiber array in the inertial confinement fusion (ICF) laser driver based on the concept of fiber amplification network (FAN) is researched. The feasible parameter space is given for laser coupling of the fundamental, second and third harmonic waves by neglecting the influence of the frequency conversion on the beam quality under the assumption of beam quality factor conservation. Third harmonic laser coupling is preferred due to its lower output energy requirement from a single fiber amplifier. For coplanar fiber array, the energy requirement is around 0.4 J with an effective mode field diameter of around 500 μm while maintaining the fundamental mode operation which is more than one order of magnitude higher than what can be achieved with state-of-the-art technology. Novel waveguide structure needs to be developed to enlarge the fundamental mode size while mitigating the catastrophic self-focusing effect.
Vergara, Christian; Lange, Matthias; Palamara, Simone; Lassila, Toni; Frangi, Alejandro F.; Quarteroni, Alfio
2016-03-01
We present a model for the electrophysiology in the heart to handle the electrical propagation through the Purkinje system and in the myocardium, with two-way coupling at the Purkinje-muscle junctions. In both the subproblems the monodomain model is considered, whereas at the junctions a resistor element is included that induces an orthodromic propagation delay from the Purkinje network towards the heart muscle. We prove a sufficient condition for convergence of a fixed-point iterative algorithm to the numerical solution of the coupled problem. Numerical comparison of activation patterns is made with two different combinations of models for the coupled Purkinje network/myocardium system, the eikonal/eikonal and the monodomain/monodomain models. Test cases are investigated for both physiological and pathological activation of a model left ventricle. Finally, we prove the reliability of the monodomain/monodomain coupling on a realistic scenario. Our results underlie the importance of using physiologically realistic Purkinje-trees with propagation solved using the monodomain model for simulating cardiac activation.
Privman, Vladimir; Arugula, Mary A; Halámek, Jan; Pita, Marcos; Katz, Evgeny
2009-04-16
We develop an approach aimed at optimizing the parameters of a network of biochemical logic gates for reduction of the "analog" noise buildup. Experiments for three coupled enzymatic AND gates are reported, illustrating our procedure. Specifically, starch, one of the controlled network inputs, is converted to maltose by beta-amylase. With the use of phosphate (another controlled input), maltose phosphorylase then produces glucose. Finally, nicotinamide adenine dinucleotide (NAD(+)), the third controlled input, is reduced under the action of glucose dehydrogenase to yield the optically detected signal. Network functioning is analyzed by varying selective inputs and fitting standardized few-parameters "response-surface" functions assumed for each gate. This allows a certain probe of the individual gate quality, but primarily yields information on the relative contribution of the gates to noise amplification. The derived information is then used to modify our experimental system to put it in a regime of a less noisy operation.
Directory of Open Access Journals (Sweden)
M Soltani
Full Text Available Modeling of interstitial fluid flow involves processes such as fluid diffusion, convective transport in extracellular matrix, and extravasation from blood vessels. To date, majority of microvascular flow modeling has been done at different levels and scales mostly on simple tumor shapes with their capillaries. However, with our proposed numerical model, more complex and realistic tumor shapes and capillary networks can be studied. Both blood flow through a capillary network, which is induced by a solid tumor, and fluid flow in tumor's surrounding tissue are formulated. First, governing equations of angiogenesis are implemented to specify the different domains for the network and interstitium. Then, governing equations for flow modeling are introduced for different domains. The conservation laws for mass and momentum (including continuity equation, Darcy's law for tissue, and simplified Navier-Stokes equation for blood flow through capillaries are used for simulating interstitial and intravascular flows and Starling's law is used for closing this system of equations and coupling the intravascular and extravascular flows. This is the first study of flow modeling in solid tumors to naturalistically couple intravascular and extravascular flow through a network. This network is generated by sprouting angiogenesis and consisting of one parent vessel connected to the network while taking into account the non-continuous behavior of blood, adaptability of capillary diameter to hemodynamics and metabolic stimuli, non-Newtonian blood flow, and phase separation of blood flow in capillary bifurcation. The incorporation of the outlined components beyond the previous models provides a more realistic prediction of interstitial fluid flow pattern in solid tumors and surrounding tissues. Results predict higher interstitial pressure, almost two times, for realistic model compared to the simplified model.
Agerskov, Claus; Mortensen, Rasmus M; Bohr, Henrik G
2015-01-01
A study is presented on how well possible drug-molecules can be predicted with respect to their function and binding to a selection of neuro-receptors by the use of artificial neural networks. The ligands investigated in this study are chosen to be corresponding to the G protein-coupled receptors µ-opioid, serotonin 2B (5-HT2B) and metabotropic glutamate D5. They are selected due to the availability of pharmacological drug-molecule binding data for these receptors. Feedback and deep belief artificial neural network architectures (NNs) were chosen to perform the task of aiding drugdesign. This is done by training on structural features, selected using a "minimum redundancy, maximum relevance"-test, and testing for successful prediction of categorized binding strength. An extensive comparison of the neural network performances was made in order to select the optimal architecture. Deep belief networks, trained with greedy learning algorithms, showed superior performance in prediction over the simple feedback NNs. The best networks obtained scores of more than 90 % accuracy in predicting the degree of binding drug molecules to the mentioned receptors and with a maximal Matthew`s coefficient of 0.925. The performance of 8 category networks (8 output classes for binding strength) obtained a prediction accuracy of above 60 %. After training the networks, tests were done on how well the systems could be used as an aid in designing candidate drug molecules. Specifically, it was shown how a selection of chemical characteristics could give the lowest observed IC50 values, meaning largest bio-effect pr. nM substance, around 0.03-0.06 nM. These ligand characteristics could be total number of atoms, their types etc. In conclusion, deep belief networks trained on drug-molecule structures were demonstrated as powerful computational tools, able to aid in drug-design in a fast and cheap fashion, compared to conventional pharmacological techniques.
Amir, Ofra; Grosz, Barbara J.; Gajos, Krzysztof Z.
2016-01-01
Complex collaborative activities such as treating patients, co-authoring documents and developing software are often characterized by teamwork that is loosely coupled and extends in time. To remain coordinated and avoid conflicts, team members need to identify dependencies between their activities — which though loosely coupled may interact — and share information appropriately. The loose-coupling of tasks increases the difficulty of identifying dependencies, with the result that team members...
Synchronization in networks of mutually delay-coupled phase-locked loops
Pollakis, Alexandros; Wetzel, Lucas; Jörg, David J.; Rave, Wolfgang; Fettweis, Gerhard; Jülicher, Frank
2014-11-01
Electronic components that perform tasks in a concerted way rely on a common time reference. For instance, parallel computing demands synchronous clocking of multiple cores or processors to reliably carry out joint computations. Here, we show that mutually coupled phase-locked loops (PLLs) enable synchronous clocking in large-scale systems with transmission delays. We present a phase description of coupled PLLs that includes filter kernels and delayed signal transmission. We find that transmission delays in the coupling enable the existence of stable synchronized states, while instantaneously coupled PLLs do not tend to synchronize. We show how filtering and transmission delays govern the collective frequency and the time scale of synchronization.
Institute of Scientific and Technical Information of China (English)
张海峰; 武瑞馨; 傅新楚
2006-01-01
In this paper, the coupling function of the complex dynamical networks was generalized, and the conditions for the stability of synchronization were given. We illustrate the impact of coupling function on the synchronization of complex dynamical networks, that is, the coupling strength can not assure the stability of synchronization when the coupling function is linear. However we can modulate coupling function to achieve stability of synchronization without changing coupling strength.
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
The nonlinear dynamical behaviors of artificial neural network (ANN) and their application to science and engineering were summarized. The mechanism of two kinds of dynamical processes, i.e. weight dynamics and activation dynamics in neural networks, and the stability of computing in structural analysis and design were stated briefly. It was successfully applied to nonlinear neural network to evaluate the stability of underground stope structure in a gold mine. With the application of BP network, it is proven that the neuro-computing is a practical and advanced tool for solving large-scale underground rock engineering problems.
Gerlach, Kathy D; Spreng, R Nathan; Madore, Kevin P; Schacter, Daniel L
2014-12-01
We spend much of our daily lives imagining how we can reach future goals and what will happen when we attain them. Despite the prevalence of such goal-directed simulations, neuroimaging studies on planning have mainly focused on executive processes in the frontal lobe. This experiment examined the neural basis of process simulations, during which participants imagined themselves going through steps toward attaining a goal, and outcome simulations, during which participants imagined events they associated with achieving a goal. In the scanner, participants engaged in these simulation tasks and an odd/even control task. We hypothesized that process simulations would recruit default and frontoparietal control network regions, and that outcome simulations, which allow us to anticipate the affective consequences of achieving goals, would recruit default and reward-processing regions. Our analysis of brain activity that covaried with process and outcome simulations confirmed these hypotheses. A functional connectivity analysis with posterior cingulate, dorsolateral prefrontal cortex and anterior inferior parietal lobule seeds showed that their activity was correlated during process simulations and associated with a distributed network of default and frontoparietal control network regions. During outcome simulations, medial prefrontal cortex and amygdala seeds covaried together and formed a functional network with default and reward-processing regions. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.
Directory of Open Access Journals (Sweden)
Nadja Razavi
Full Text Available INTRODUCTION: The cerebral resting state in schizophrenia is altered, as has been demonstrated separately by electroencephalography (EEG and functional magnetic resonance imaging (fMRI resting state networks (RSNs. Previous simultaneous EEG/fMRI findings in healthy controls suggest that a consistent spatiotemporal coupling between neural oscillations (EEG frequency correlates and RSN activity is necessary to organize cognitive processes optimally. We hypothesized that this coupling is disorganized in schizophrenia and related psychotic disorders, in particular regarding higher cognitive RSNs such as the default-mode (DMN and left-working-memory network (LWMN. METHODS: Resting state was investigated in eleven patients with a schizophrenia spectrum disorder (n = 11 and matched healthy controls (n = 11 using simultaneous EEG/fMRI. The temporal association of each RSN to topographic spectral changes in the EEG was assessed by creating Covariance Maps. Group differences within, and group similarities across frequencies were estimated for the Covariance Maps. RESULTS: The coupling of EEG frequency bands to the DMN and the LWMN respectively, displayed significant similarities that were shifted towards lower EEG frequencies in patients compared to healthy controls. CONCLUSIONS: By combining EEG and fMRI, each measuring different properties of the same pathophysiology, an aberrant relationship between EEG frequencies and altered RSNs was observed in patients. RSNs of patients were related to lower EEG frequencies, indicating functional alterations of the spatiotemporal coupling. SIGNIFICANCE: The finding of a deviant and shifted coupling between RSNs and related EEG frequencies in patients with a schizophrenia spectrum disorder is significant, as it might indicate how failures in the processing of internal and external stimuli, as commonly seen during this symptomatology (i.e. thought disorders, hallucinations, arise.
The Role of Romantic Partners, Family, and Peer Networks in Dating Couples' Views about Cohabitation
Manning, Wendy D.; Cohen, Jessica A.; Smock, Pamela J.
2011-01-01
Emerging adults are increasingly cohabiting, but few studies have considered the role of social context in the formation of their views of cohabitation. Drawing on 40 semistructured interviews with dating couples, we explored the role of romantic partners, family, and peers on evaluations of cohabitation. In couples where each member had a…
Amsalem, Oren; Van Geit, Werner; Muller, Eilif; Markram, Henry; Segev, Idan
2016-08-01
In the neocortex, inhibitory interneurons of the same subtype are electrically coupled with each other via dendritic gap junctions (GJs). The impact of multiple GJs on the biophysical properties of interneurons and thus on their input processing is unclear. The present experimentally based theoretical study examined GJs in L2/3 large basket cells (L2/3 LBCs) with 3 goals in mind: (1) To evaluate the errors due to GJs in estimating the cable properties of individual L2/3 LBCs and suggest ways to correct these errors when modeling these cells and the networks they form; (2) to bracket the GJ conductance value (0.05-0.25 nS) and membrane resistivity (10 000-40 000 Ω cm(2)) of L2/3 LBCs; these estimates are tightly constrained by in vitro input resistance (131 ± 18.5 MΩ) and the coupling coefficient (1-3.5%) of these cells; and (3) to explore the functional implications of GJs, and show that GJs: (i) dynamically modulate the effective time window for synaptic integration; (ii) improve the axon's capability to encode rapid changes in synaptic inputs; and (iii) reduce the orientation selectivity, linearity index, and phase difference of L2/3 LBCs. Our study provides new insights into the role of GJs and calls for caution when using in vitro measurements for modeling electrically coupled neuronal networks.
Hanapi, Zurina Mohd; Othman, Mohamed; Zukarnain, Zuriati Ahmad
2017-01-01
Recently, Pulse Coupled Oscillator (PCO)-based travelling waves have attracted substantial attention by researchers in wireless sensor network (WSN) synchronization. Because WSNs are generally artificial occurrences that mimic natural phenomena, the PCO utilizes firefly synchronization of attracting mating partners for modelling the WSN. However, given that sensor nodes are unable to receive messages while transmitting data packets (due to deafness), the PCO model may not be efficient for sensor network modelling. To overcome this limitation, this paper proposed a new scheme called the Travelling Wave Pulse Coupled Oscillator (TWPCO). For this, the study used a self-organizing scheme for energy-efficient WSNs that adopted travelling wave biologically inspired network systems based on phase locking of the PCO model to counteract deafness. From the simulation, it was found that the proposed TWPCO scheme attained a steady state after a number of cycles. It also showed superior performance compared to other mechanisms, with a reduction in the total energy consumption of 25%. The results showed that the performance improved by 13% in terms of data gathering. Based on the results, the proposed scheme avoids the deafness that occurs in the transmit state in WSNs and increases the data collection throughout the transmission states in WSNs. PMID:28056020
Al-Mekhlafi, Zeyad Ghaleb; Hanapi, Zurina Mohd; Othman, Mohamed; Zukarnain, Zuriati Ahmad
2017-01-01
Recently, Pulse Coupled Oscillator (PCO)-based travelling waves have attracted substantial attention by researchers in wireless sensor network (WSN) synchronization. Because WSNs are generally artificial occurrences that mimic natural phenomena, the PCO utilizes firefly synchronization of attracting mating partners for modelling the WSN. However, given that sensor nodes are unable to receive messages while transmitting data packets (due to deafness), the PCO model may not be efficient for sensor network modelling. To overcome this limitation, this paper proposed a new scheme called the Travelling Wave Pulse Coupled Oscillator (TWPCO). For this, the study used a self-organizing scheme for energy-efficient WSNs that adopted travelling wave biologically inspired network systems based on phase locking of the PCO model to counteract deafness. From the simulation, it was found that the proposed TWPCO scheme attained a steady state after a number of cycles. It also showed superior performance compared to other mechanisms, with a reduction in the total energy consumption of 25%. The results showed that the performance improved by 13% in terms of data gathering. Based on the results, the proposed scheme avoids the deafness that occurs in the transmit state in WSNs and increases the data collection throughout the transmission states in WSNs.
Ratas, Irmantas; Pyragas, Kestutis
2016-09-01
We analyze the dynamics of a large network of coupled quadratic integrate-and-fire neurons, which represent the canonical model for class I neurons near the spiking threshold. The network is heterogeneous in that it includes both inherently spiking and excitable neurons. The coupling is global via synapses that take into account the finite width of synaptic pulses. Using a recently developed reduction method based on the Lorentzian ansatz, we derive a closed system of equations for the neuron's firing rate and the mean membrane potential, which are exact in the infinite-size limit. The bifurcation analysis of the reduced equations reveals a rich scenario of asymptotic behavior, the most interesting of which is the macroscopic limit-cycle oscillations. It is shown that the finite width of synaptic pulses is a necessary condition for the existence of such oscillations. The robustness of the oscillations against aging damage, which transforms spiking neurons into nonspiking neurons, is analyzed. The validity of the reduced equations is confirmed by comparing their solutions with the solutions of microscopic equations for the finite-size networks.
Philips, Ryan T; Chhabria, Karishma; Chakravarthy, V Srinivasa
2016-01-01
Cerebral vascular dynamics are generally thought to be controlled by neural activity in a unidirectional fashion. However, both computational modeling and experimental evidence point to the feedback effects of vascular dynamics on neural activity. Vascular feedback in the form of glucose and oxygen controls neuronal ATP, either directly or via the agency of astrocytes, which in turn modulates neural firing. Recently, a detailed model of the neuron-astrocyte-vessel system has shown how vasomotion can modulate neural firing. Similarly, arguing from known cerebrovascular physiology, an approach known as "hemoneural hypothesis" postulates functional modulation of neural activity by vascular feedback. To instantiate this perspective, we present a computational model in which a network of "vascular units" supplies energy to a neural network. The complex dynamics of the vascular network, modeled by a network of oscillators, turns neurons ON and OFF randomly. The informational consequence of such dynamics is explored in the context of an auto-encoder network. In the proposed model, each vascular unit supplies energy to a subset of hidden neurons of an autoencoder network, which constitutes its "projective field." Neurons that receive adequate energy in a given trial have reduced threshold, and thus are prone to fire. Dynamics of the vascular network are governed by changes in the reconstruction error of the auto-encoder network, interpreted as the neuronal demand. Vascular feedback causes random inactivation of a subset of hidden neurons in every trial. We observe that, under conditions of desynchronized vascular dynamics, the output reconstruction error is low and the feature vectors learnt are sparse and independent. Our earlier modeling study highlighted the link between desynchronized vascular dynamics and efficient energy delivery in skeletal muscle. We now show that desynchronized vascular dynamics leads to efficient training in an auto-encoder neural network.
Institute of Scientific and Technical Information of China (English)
Yang Dai; YunZe Cai; Xiao-Ming Xu
2009-01-01
Exponential estimates and sufficient conditions for the exponential synchronization of complex dynamical networks with bounded time-varying delays are given in terms of linear matrix inequalities (LMIs). A generalized complex networks model involving both neutral delays and retarded ones is presented. The exponential synchronization problem of the complex networks is converted equivalently into the exponential stability problem of a group of uncorrelated delay functional differential equations with mixed time-varying delays. By utilizing the free weighting matrix technique, a less conservative delay-dependent synchronization criterion is derived. An illustrative example is provided to demonstrate the effectiveness of the proposed method.
Watanabe, Tomohiko; Sugitani, Yoshiki; Konishi, Keiji; Hara, Naoyuki
2017-01-01
The present paper studies amplitude death in high-dimensional maps coupled by time-delay connections. A linear stability analysis provides several sufficient conditions for an amplitude death state to be unstable, i.e., an odd number property and its extended properties. Furthermore, necessary conditions for stability are provided. These conditions, which reduce trial-and-error tasks for design, and the convex direction, which is a popular concept in the field of robust control, allow us to propose a design procedure for system parameters, such as coupling strength, connection delay, and input-output matrices, for a given network topology. These analytical results are confirmed numerically using delayed logistic maps, generalized Henon maps, and piecewise linear maps.
Ge, Ji; Wang, YaoNan; Zhou, BoWen; Zhang, Hui
2009-01-01
A biologically inspired spiking neural network model, called pulse-coupled neural networks (PCNN), has been applied in an automatic inspection machine to detect visible foreign particles intermingled in glucose or sodium chloride injection liquids. Proper mechanisms and improved spin/stop techniques are proposed to avoid the appearance of air bubbles, which increases the algorithms' complexity. Modified PCNN is adopted to segment the difference images, judging the existence of foreign particles according to the continuity and smoothness properties of their moving traces. Preliminarily experimental results indicate that the inspection machine can detect the visible foreign particles effectively and the detection speed, accuracy and correct detection rate also satisfying the needs of medicine preparation. PMID:22412318
Security Enhancement With Optimal QOS Using EAP-AKA In Hybrid Coupled 3G-WLAN Convergence Network
Shankar, R; Dananjayan, P; 10.5121/iju.2010.1303
2010-01-01
The third generation partnership project (3GPP) has addressed the feasibility of interworking and specified the interworking architecture and security architecture for third generation (3G)-wireless local area network (WLAN), it is developing, system architecture evolution (SAE)/ long term evolution (LTE) architecture, for the next generation mobile communication system. To provide a secure 3G-WLAN interworking in the SAE/LTE architecture, Extensible authentication protocol-authentication and key agreement (EAP-AKA) is used. However, EAP-AKA have several vulnerabilities. Therefore, this paper not only analyses the threats and attacks in 3G-WLAN interworking but also proposes a new authentication and key agreement protocol based on EAP-AKA. The proposed protocol combines elliptic curve Diffie-Hellman (ECDH) with symmetric key cryptosystem to overcome the vulnerabilities. The proposed protocol is used in hybrid coupled 3G-WLAN convergence network to analyse its efficiency in terms of QoS metrics, the results ob...
Liu, Li; Shi, Haiying; Huo, Liqin; Zhang, Feng; Zheng, Chongxun; You, Jia; He, Xining; Zhang, Jie
2011-10-01
This paper is to provide a basis for the establishment of an early diagnostic system for hypoxic-ischemic encephalopathy (HIE) by performing segmentation and feature extraction of lesions on the MR images of neonatal babies with HIE. The segmentation on MR images of HIE based on the genetic algorithm (GA) combined with a pulse-coupled neural network (PCNN) were carried out. There were better segmentation results by using PCNN segmentation based on GA than PCNN segmentation with fixed parameters. The data suggested that a PCNN based on GA could provide effective assistance for diagnosis and research.
Armando Carravetta; Lauro Antipodi; Umberto Golia; Oreste Fecarotta
2017-01-01
The management of a water distribution network (WDN) is performed by valve and pump control, to regulate both the pressure and the discharge between certain limits. The energy that is usually merely dissipated by valves can instead be converted and used to partially supply the pumping stations. Pumps used as turbines (PAT) can be used in order to both reduce pressure and recover energy, with proven economic benefits. The direct coupling of the PAT shaft with the pump shaft in a PAT-pump turbo...
Directory of Open Access Journals (Sweden)
Tao Dong
2013-01-01
Full Text Available This paper considers the problem of the convergence of the consensus algorithm for multiple agents in a directed network where each agent is governed by double-integrator dynamics and coupling time delay. The advantage of this protocol is that almost all the existing linear local interaction consensus protocols can be considered as special cases of the present paper. By combining algebraic graph theory and matrix theory and studying the distribution of the eigenvalues of the associated characteristic equation, some necessary and sufficient conditions are derived for reaching the second-order consensus. Finally, an illustrative example is also given to support the theoretical results.
Directory of Open Access Journals (Sweden)
Ryan T Canolty
Full Text Available Understanding the principles governing the dynamic coordination of functional brain networks remains an important unmet goal within neuroscience. How do distributed ensembles of neurons transiently coordinate their activity across a variety of spatial and temporal scales? While a complete mechanistic account of this process remains elusive, evidence suggests that neuronal oscillations may play a key role in this process, with different rhythms influencing both local computation and long-range communication. To investigate this question, we recorded multiple single unit and local field potential (LFP activity from microelectrode arrays implanted bilaterally in macaque motor areas. Monkeys performed a delayed center-out reach task either manually using their natural arm (Manual Control, MC or under direct neural control through a brain-machine interface (Brain Control, BC. In accord with prior work, we found that the spiking activity of individual neurons is coupled to multiple aspects of the ongoing motor beta rhythm (10-45 Hz during both MC and BC, with neurons exhibiting a diversity of coupling preferences. However, here we show that for identified single neurons, this beta-to-rate mapping can change in a reversible and task-dependent way. For example, as beta power increases, a given neuron may increase spiking during MC but decrease spiking during BC, or exhibit a reversible shift in the preferred phase of firing. The within-task stability of coupling, combined with the reversible cross-task changes in coupling, suggest that task-dependent changes in the beta-to-rate mapping play a role in the transient functional reorganization of neural ensembles. We characterize the range of task-dependent changes in the mapping from beta amplitude, phase, and inter-hemispheric phase differences to the spike rates of an ensemble of simultaneously-recorded neurons, and discuss the potential implications that dynamic remapping from oscillatory activity to
Directory of Open Access Journals (Sweden)
Lin Wang
2012-01-01
Full Text Available Studies were done on analysis of biological processes in the same high expression (fold change ≥2 activated PTHLH feedback-mediated cell adhesion gene ontology (GO network of human hepatocellular carcinoma (HCC compared with the corresponding low expression activated GO network of no-tumor hepatitis/cirrhotic tissues (HBV or HCV infection. Activated PTHLH feedback-mediated cell adhesion network consisted of anaphase-promoting complex-dependent proteasomal ubiquitin-dependent protein catabolism, cell adhesion, cell differentiation, cell-cell signaling, G-protein-coupled receptor protein signaling pathway, intracellular transport, metabolism, phosphoinositide-mediated signaling, positive regulation of transcription, regulation of cyclin-dependent protein kinase activity, regulation of transcription, signal transduction, transcription, and transport in HCC. We proposed activated PTHLH coupling feedback phosphoinositide to G-protein receptor signal-induced cell adhesion network. Our hypothesis was verified by the different activated PTHLH feedback-mediated cell adhesion GO network of HCC compared with the corresponding inhibited GO network of no-tumor hepatitis/cirrhotic tissues, or the same compared with the corresponding inhibited GO network of HCC. Activated PTHLH coupling feedback phosphoinositide to G-protein receptor signal-induced cell adhesion network included BUB1B, GNG10, PTHR2, GNAZ, RFC4, UBE2C, NRXN3, BAP1, PVRL2, TROAP, and VCAN in HCC from GEO dataset using gene regulatory network inference method and our programming.
Hosseini, Zhaleh; Marashi, Sayed-Amir
2015-05-01
Flux coupling analysis is a method for investigating the connections between reactions of metabolic networks. Here, we construct the hierarchical flux coupling graph for the reactions of the Escherichia coli metabolic network model to determine the level of each reaction in the graph. This graph is constructed based on flux coupling analysis of metabolic network: if zero flux through reaction a results in zero flux through reaction b (and not vice versa), then reaction a is located at the top of reaction b in the flux coupling graph. We show that in general, more important, older and essential reactions are located at the top of the graph. Strikingly, genes corresponding to these reactions are found to be the genes which are most regulated.
Marginal chimera state at cross-frequency locking of pulse-coupled neural networks
Bolotov, M. I.; Osipov, G. V.; Pikovsky, A.
2016-03-01
We consider two coupled populations of leaky integrate-and-fire neurons. Depending on the coupling strength, mean fields generated by these populations can have incommensurate frequencies or become frequency locked. In the observed 2:1 locking state of the mean fields, individual neurons in one population are asynchronous with the mean fields, while in another population they have the same frequency as the mean field. These synchronous neurons form a chimera state, where part of them build a fully synchronized cluster, while other remain scattered. We explain this chimera as a marginal one, caused by a self-organized neutral dynamics of the effective circle map.
Finger, Holger; König, Peter
2013-01-01
Synchronization has been suggested as a mechanism of binding distributed feature representations facilitating segmentation of visual stimuli. Here we investigate this concept based on unsupervised learning using natural visual stimuli. We simulate dual-variable neural oscillators with separate activation and phase variables. The binding of a set of neurons is coded by synchronized phase variables. The network of tangential synchronizing connections learned from the induced activations exhibits small-world properties and allows binding even over larger distances. We evaluate the resulting dynamic phase maps using segmentation masks labeled by human experts. Our simulation results show a continuously increasing phase synchrony between neurons within the labeled segmentation masks. The evaluation of the network dynamics shows that the synchrony between network nodes establishes a relational coding of the natural image inputs. This demonstrates that the concept of binding by synchrony is applicable in the context of unsupervised learning using natural visual stimuli.
Directory of Open Access Journals (Sweden)
Holger eFinger
2014-01-01
Full Text Available Synchronization has been suggested as a mechanism of binding distributed feature representations facilitating segmentation of visual stimuli. Here we investigate this concept based on unsupervised learning using natural visual stimuli. We simulate dual-variable neural oscillators with separate activation and phase variables. The binding of a set of neurons is coded by synchronized phase variables. The network of tangential synchronizing connections learned from the induced activations exhibits small-world properties and allows binding even over larger distances. We evaluate the resulting dynamic phase maps using segmentation masks labeled by human experts. Our simulation results show a continuously increasing phase synchrony between neurons within the labeled segmentation masks. The evaluation of the network dynamics shows that the synchrony between network nodes establishes a relational coding of the natural image inputs. This demonstrates that the concept of binding by synchrony is applicable in the context of unsupervised learning using natural visual stimuli.
Wei, Ruihan; Parsons, Sean P; Huizinga, Jan D
2017-03-01
What is the central question of this study? What are the effects of interstitial cells of Cajal (ICC) network perturbations on intestinal pacemaker activity and motor patterns? What is the main finding and its importance? Two-dimensional modelling of the ICC pacemaker activity according to a phase model of weakly coupled oscillators showed that network properties (coupling strength between oscillators, frequency gradient and frequency noise) strongly influence pacemaker network activity and subsequent motor patterns. The model explains motor patterns observed in physiological conditions and provides predictions and testable hypotheses for effects of ICC loss and frequency modulation on the motor patterns. Interstitial cells of Cajal (ICC) are the pacemaker cells of gut motility and are associated with motility disorders. Interstitial cells of Cajal form a network, but the contributions of its network properties to gut physiology and dysfunction are poorly understood. We modelled an ICC network as a two-dimensional network of weakly coupled oscillators with a frequency gradient and showed changes over time in video and graphical formats. Model parameters were obtained from slow-wave-driven contraction patterns in the mouse intestine and pacemaker slow-wave activities from the cat intestine. Marked changes in propagating oscillation patterns (including changes from propagation to non-propagating) were observed by changing network parameters (coupling strength between oscillators, the frequency gradient and frequency noise), which affected synchronization, propagation velocity and occurrence of dislocations (termination of an oscillation). Complete uncoupling of a circumferential ring of oscillators caused the proximal and distal section to desynchronize, but complete synchronization was maintained with only a single oscillator connecting the sections with high enough coupling. The network of oscillators could withstand loss; even with 40% of oscillators lost randomly
Sensor-coupled fractal gene regulatory networks for locomotion control of a modular snake robot
DEFF Research Database (Denmark)
Zahadat, Payam; Christensen, David Johan; Katebi, Serajeddin
2013-01-01
In this paper we study fractal gene regulatory network (FGRN) controllers based on sensory information. The FGRN controllers are evolved to control a snake robot consisting of seven simulated ATRON modules. Each module contains three tilt sensors which represent the direction of gravity in the co......In this paper we study fractal gene regulatory network (FGRN) controllers based on sensory information. The FGRN controllers are evolved to control a snake robot consisting of seven simulated ATRON modules. Each module contains three tilt sensors which represent the direction of gravity...
Energy Technology Data Exchange (ETDEWEB)
Shi, Xiangli [Environment Research Institute, Shandong University, Jinan 250100 (China); Yu, Wanni [Environment Research Institute, Shandong University, Jinan 250100 (China); College of Resources and Environment, Linyi University, Linyi 276000 (China); Xu, Fei [Environment Research Institute, Shandong University, Jinan 250100 (China); Zhang, Qingzhu, E-mail: zqz@sdu.edu.cn [Environment Research Institute, Shandong University, Jinan 250100 (China); Hu, Jingtian; Wang, Wenxing [Environment Research Institute, Shandong University, Jinan 250100 (China)
2015-09-15
Highlights: • We studied the formation of PBCDD/Fs from the reaction of three CPRs with BPRs. • The substitution pattern of halogenated phenols determines those of PBCDD/Fs. • The substitution of halogenated phenols influence the coupling of phenoxy radicals. • The rate constants of the crucial elementary steps were evaluated. - Abstract: Quantum chemical calculations were carried out to investigate the homogeneous gas-phase formation of mixed polybrominated/chlorinated dibenzo-p-dioxins/benzofurans (PBCDD/Fs) from the cross-condensation of 2-chlorophenoxy radical (2-CPR) with 2-bromophenoxy radical (2-BPR), 2,4-dichlorophenoxy radical (2,4-DCPR) with 2,4-dibromophenoxy radical (2,4-DBPR), and 2,4,6-trichlorophenoxy radical (2,4,6-TCPR) with 2,4,6-tribromophenoxy radical (2,4,6-TBPR). The geometrical parameters and vibrational frequencies were calculated at the MPWB1K/6-31+G(d,p) level, and single-point energy calculations were performed at the MPWB1K/6-311+G(3df,2p) level of theory. The rate constants of the crucial elementary reactions were evaluated by the canonical variational transition-state (CVT) theory with the small curvature tunneling (SCT) correction over a wide temperature range of 600–1200 K. Studies show that the substitution pattern of halogenated phenols not only determines the substitution pattern of the resulting PBCDD/Fs, but also has a significant influence on the formation mechanism of PBCDD/Fs, especially on the coupling of the halogenated phenoxy radicals.
Energy transfer efficiency in the chromophore network strongly coupled to a vibrational mode.
Mourokh, Lev G; Nori, Franco
2015-11-01
Using methods from condensed matter and statistical physics, we examine the transport of excitons through the photosynthetic complex from a receiving antenna to a reaction center. Writing the equations of motion for the exciton creation-annihilation operators, we are able to describe the exciton dynamics, even in the regime when the reorganization energy is of the order of the intrasystem couplings. We determine the exciton transfer efficiency in the presence of a quenching field and protein environment. While the majority of the protein vibrational modes are treated as a heat bath, we address the situation when specific modes are strongly coupled to excitons and examine the effects of these modes on the energy transfer efficiency in the steady-state regime. Using the structural parameters of the Fenna-Matthews-Olson complex, we find that, for vibrational frequencies below 16 meV, the exciton transfer is drastically suppressed. We attribute this effect to the formation of a "mixed exciton-vibrational mode" where the exciton is transferred back and forth between the two pigments with the absorption or emission of vibrational quanta, instead of proceeding to the reaction center. The same effect suppresses the quantum beating at the vibrational frequency of 25 meV. We also show that the efficiency of the energy transfer can be enhanced when the vibrational mode strongly couples to the third pigment only, instead of coupling to the entire system.
Wang, Yongqiang; Hori, Yutaka; Hara, Shinji; Doyle, Francis J
2014-01-01
Most biological rhythms are generated by a population of cellular oscillators coupled through intercellular signaling. Recent experimental evidence shows that the collective period may differ significantly from the autonomous period in the presence of intercellular delays. The phenomenon has been investigated using delay-coupled phase oscillators, but the proposed phase model contains no direct biological mechanism, which may weaken the model's reliability in unraveling biophysical principles. Based on a published gene regulatory oscillator model, we analyze the collective period of delay-coupled biological oscillators using the multivariable harmonic balance technique. We prove that, in contradiction to the common intuition that the collective period increases linearly with the coupling delay, the collective period turns out to be a periodic function of the intercellular delay. More surprisingly, the collective period may even decrease with the intercellular delay when the delay resides in certain regions. The collective period is given in a closed-form in terms of biochemical reaction constants and thus provides biological insights as well as guidance in synthetic-biological-oscillator design. Simulation results are given based on a segmentation clock model to confirm the theoretical predictions.
Directory of Open Access Journals (Sweden)
Jon eLópez-Azcárate
2013-10-01
Full Text Available The brain's ability to integrate different behavioral and cognitive processes relies on its capacity to generate neural oscillations in a cooperative and coordinated manner. Cross-frequency coupling (CFC has recently been proposed as one of the mechanisms involved in organizing brain activity. Here we investigated the phase-to-amplitude CFC (PA-CFC patterns of the oscillatory activity in the cortico-basal ganglia network of healthy, freely moving rats. Within-structure analysis detected consistent PA-CFC patterns in the four regions analyzed, with the phase of delta waves modulating the amplitude of activity in the gamma (low-gamma ~50 Hz; high-gamma ~80 Hz and high frequency ranges (high frequency oscillations HFO, ~150 Hz. Between-structure analysis revealed that the phase of delta waves parses the occurrence of transient episodes of coherence in the gamma and high frequency bands across the entire network, providing temporal windows of coherence between different structures. Significantly, this specific spatio-temporal organization was affected by the action of dopaminergic drugs. Taken together, our findings suggest that delta-mediated PA-CFC plays a key role in the organization of local and distant activities in the rat cortico-basal ganglia network by fine-tuning the timing of synchronization events across different structures.
Validation and quantification of uncertainty in coupled climate models using network analysis
Energy Technology Data Exchange (ETDEWEB)
Bracco, Annalisa [Georgia Inst. of Technology, Atlanta, GA (United States)
2015-08-10
We developed a fast, robust and scalable methodology to examine, quantify, and visualize climate patterns and their relationships. It is based on a set of notions, algorithms and metrics used in the study of graphs, referred to as complex network analysis. This approach can be applied to explain known climate phenomena in terms of an underlying network structure and to uncover regional and global linkages in the climate system, while comparing general circulation models outputs with observations. The proposed method is based on a two-layer network representation, and is substantially new within the available network methodologies developed for climate studies. At the first layer, gridded climate data are used to identify ‘‘areas’’, i.e., geographical regions that are highly homogeneous in terms of the given climate variable. At the second layer, the identified areas are interconnected with links of varying strength, forming a global climate network. The robustness of the method (i.e. the ability to separate between topological distinct fields, while identifying correctly similarities) has been extensively tested. It has been proved that it provides a reliable, fast framework for comparing and ranking the ability of climate models of reproducing observed climate patterns and their connectivity. We further developed the methodology to account for lags in the connectivity between climate patterns and refined our area identification algorithm to account for autocorrelation in the data. The new methodology based on complex network analysis has been applied to state-of-the-art climate model simulations that participated to the last IPCC (International Panel for Climate Change) assessment to verify their performances, quantify uncertainties, and uncover changes in global linkages between past and future projections. Network properties of modeled sea surface temperature and rainfall over 1956–2005 have been constrained towards observations or reanalysis data sets
Dynamic Coupling and Allosteric Networks in the α Subunit of Heterotrimeric G Proteins*
Yao, Xin-Qiu; Malik, Rabia U.; Griggs, Nicholas W.; Skjærven, Lars; Traynor, John R.; Sivaramakrishnan, Sivaraj; Grant, Barry J.
2016-01-01
G protein α subunits cycle between active and inactive conformations to regulate a multitude of intracellular signaling cascades. Important structural transitions occurring during this cycle have been characterized from extensive crystallographic studies. However, the link between observed conformations and the allosteric regulation of binding events at distal sites critical for signaling through G proteins remain unclear. Here we describe molecular dynamics simulations, bioinformatics analysis, and experimental mutagenesis that identifies residues involved in mediating the allosteric coupling of receptor, nucleotide, and helical domain interfaces of Gαi. Most notably, we predict and characterize novel allosteric decoupling mutants, which display enhanced helical domain opening, increased rates of nucleotide exchange, and constitutive activity in the absence of receptor activation. Collectively, our results provide a framework for explaining how binding events and mutations can alter internal dynamic couplings critical for G protein function. PMID:26703464
Small, Michael
2015-12-01
Mean field compartmental models of disease transmission have been successfully applied to a host of different scenarios, and the Kermack-McKendrick equations are now a staple of mathematical biology text books. In Susceptible-Infected-Removed format these equations provide three coupled first order ordinary differential equations with a very mild nonlinearity and they are very well understood. However, underpinning these equations are two important assumptions: that the population is (a) homogeneous, and (b) well-mixed. These assumptions become closest to being true for diseases infecting a large portion of the population for which inevitable individual effects can be averaged away. Emerging infectious disease (such as, in recent times, SARS, avian influenza, swine flu and ebola) typically does not conform to this scenario. Individual contacts and peculiarities of the transmission network play a vital role in understanding the dynamics of such relatively rare infections - particularly during the early stages of an outbreak.
An Increase in Tobacco Craving Is Associated with Enhanced Medial Prefrontal Cortex Network Coupling
Janes, Amy C.; Farmer, Stacey; Frederick, Blaise deB.; Nickerson, Lisa D.; Lukas, Scott E.
2014-01-01
Craving is a key aspect of drug dependence that is thought to motivate continued drug use. Numerous brain regions have been associated with craving, suggesting that craving is mediated by a distributed brain network. Whether an increase in subjective craving is associated with enhanced interactions among brain regions was evaluated using resting state functional magnetic imaging (fMRI) in nicotine dependent participants. We focused on craving-related changes in the orbital and medial prefront...
Odor recognition and segmentation by coupled olfactory bulb and cortical networks
Li, Z; Li, Zhaoping; Hertz, John
1999-01-01
We present a model of a coupled system of the olfactory bulb and cortex. Odor inputs to the epithelium are transformed to oscillatory bulbar activities. The cortex recognizes the odor by resonating to the bulbar oscillating pattern when the amplitude and phase patterns from the bulb match an odor memory stored in the intracortical synapses. We assume a cortical structure which transforms the odor information in the oscillatory pattern to a slow DC feedback signal to the bulb. This feedback suppresses the bulbar response to the pre-existing odor, allowing subsequent odor objects to be segmented out for recognition.
Ji, Xiaoxi; Zhang, Jie; Ge, Tian; Sun, Li; Wang, Yufeng; Feng, Jianfeng
2011-01-01
To uncover the underlying mechanisms of mental disorders such as attention deficit hyperactivity disorder (ADHD) for improving both early diagnosis and therapy, it is increasingly recognized that we need a better understanding of how the brain's functional connections are altered. A new brain wide association study (BWAS) has been developed and used to investigate functional connectivity changes in the brains of patients suffering from ADHD using resting state fMRI data. To reliably find out the most significantly altered functional connectivity links and associate them with ADHD, a meta-analysis on a cohort of ever reported largest population comprising 249 patients and 253 healthy controls is carried out. The greatest change in ADHD patients was the increased coupling of the saliency network involving the anterior cingulate gyrus and anterior insula. A voxel-based morphometry analysis was also carried out but this revealed no evidence in the ADHD patients for altered grey matter volumes in the regions showi...
Das, Sudeb; Kundu, Malay Kumar
2012-10-01
In this article, a novel multimodal medical image fusion (MIF) method based on non-subsampled contourlet transform (NSCT) and pulse-coupled neural network (PCNN) is presented. The proposed MIF scheme exploits the advantages of both the NSCT and the PCNN to obtain better fusion results. The source medical images are first decomposed by NSCT. The low-frequency subbands (LFSs) are fused using the 'max selection' rule. For fusing the high-frequency subbands (HFSs), a PCNN model is utilized. Modified spatial frequency in NSCT domain is input to motivate the PCNN, and coefficients in NSCT domain with large firing times are selected as coefficients of the fused image. Finally, inverse NSCT (INSCT) is applied to get the fused image. Subjective as well as objective analysis of the results and comparisons with state-of-the-art MIF techniques show the effectiveness of the proposed scheme in fusing multimodal medical images.
Tsuda, Toshitaka; Yamamoto, Mamoru; Hashiguchi, Hiroyuki; Shiokawa, Kazuo; Ogawa, Yasunobu; Nozawa, Satonori; Miyaoka, Hiroshi; Yoshikawa, Akimasa
2016-09-01
The solar energy can mainly be divided into two categories: the solar radiation and the solar wind. The former maximizes at the equator, generating various disturbances over a wide height range and causing vertical coupling processes of the atmosphere between the troposphere and middle and upper atmospheres by upward propagating atmospheric waves. The energy and material flows that occur in all height regions of the equatorial atmosphere are named as "Equatorial Fountain." These processes from the bottom also cause various space weather effects, such as satellite communication and Global Navigation Satellite System positioning. While, the electromagnetic energy and high-energy plasma particles in the solar wind converge into the polar region through geomagnetic fields. These energy/particle inflow results in auroral Joule heating and ion drag of the atmosphere particularly during geomagnetic storms and substorms. The ion outflow from the polar ionosphere controls ambient plasma constituents in the magnetosphere and may cause long-term variation of the atmosphere. We propose to clarify these overall coupling processes in the solar-terrestrial system from the bottom and from above through high-resolution observations at key latitudes in the equator and in the polar region. We will establish a large radar with active phased array antenna, called the Equatorial Middle and Upper atmosphere radar, in west Sumatra, Indonesia. We will participate in construction of the EISCAT_3D radar in northern Scandinavia. These radars will enhance the existing international radar network. We will also develop a global observation network of compact radio and optical remote sensing equipment from the equator to polar region.
Institute of Scientific and Technical Information of China (English)
HAN Dong; FANG Hong-wei; BAI Jing; HE Guo-jian
2011-01-01
A coupled one-dimensional(1-D)and two-dimensional(2-D)channel network mathematical model is proposed for flow calculations at nodes in a channel network system in this article.For the 1-D model,the finite difference method is used to discretize the Saint-Venant equations in all channels of a looped network.The Alternating Direction Implicit(ADI)method is adopted for the 2-D model at the nodes.In the coupled model,the 1-D model provides a good approximation with small computational effort,while the 2-D model is applied for complex topography to achieve a high accuracy.An Artificial Neural Network(ANN)method is used for the data exchange and the connectivity between the 1-D and 2-D models.The coupled model is applied to the Jingjiang-Dongting Lake region,to simulate the tremendous looped channel network system,and the results are compared with field data.The good agreement shows that the coupled hydraulic model is more effective than the conventional 1-D model.
Dogonowski, Anne-Marie; Siebner, Hartwig R; Sørensen, Per Soelberg; Wu, Xingchen; Biswal, Bharat; Paulson, Olaf B; Dyrby, Tim B; Skimminge, Arnold; Blinkenberg, Morten; Madsen, Kristoffer H
2013-04-01
Multiple sclerosis (MS) impairs signal transmission along cortico-cortical and cortico-subcortical connections, affecting functional integration within the motor network. Functional magnetic resonance imaging (fMRI) during motor tasks has revealed altered functional connectivity in MS, but it is unclear how much motor disability contributed to these abnormal functional interaction patterns. To avoid any influence of impaired task performance, we examined disease-related changes in functional motor connectivity in MS at rest. A total of 42 patients with MS and 30 matched controls underwent a 20-minute resting-state fMRI session at 3 Tesla. Independent component analysis was applied to the fMRI data to identify disease-related changes in motor resting-state connectivity. Patients with MS showed a spatial expansion of motor resting-state connectivity in deep subcortical nuclei but not at the cortical level. The anterior and middle parts of the putamen, adjacent globus pallidus, anterior and posterior thalamus and the subthalamic region showed stronger functional connectivity with the motor network in the MS group compared with controls. MS is characterised by more widespread motor connectivity in the basal ganglia while cortical motor resting-state connectivity is preserved. The expansion of subcortical motor resting-state connectivity in MS indicates less efficient funnelling of neural processing in the executive motor cortico-basal ganglia-thalamo-cortical loops.
Fortier, Pierre A
2010-07-21
Gap junctions can exhibit rectification of conductance. Some reports use inequality of coupling coefficients as the first sign of the possible existence of rectification (Devor and Yarom, 2002; Fan et al., 2005; Levavi-Sivan et al., 2005; Mann-Metzer and Yarom, 1999; Nolan et al., 1999; Szabadics et al., 2001). However, mathematical modeling and simulations of electrotonic coupling between an isolated pair of neurons showed conditions where the coupling coefficients were unreliable indicators of rectification. On the other hand, the transfer resistances were found to be reliable indicators of junctional rectification. The existing mathematical model of cell coupling (Bennett, 1966; Devor and Yarom, 2002; Verselis and Veenstra, 2000) was extended in order to measure rectification of the junctional conductances directly between dual-recorded neurons whether isolated or surrounded by a simulated 3-dimensional network of heterogeneous cells whose gap junctions offered parallel paths for current flow between the recorded neurons. The results showed that the transfer resistances could still detect rectification of the gap junction linking the dual-recorded neurons when embedded in a coupled cell network and that a mathematical model could estimate the conductances in both directions through this gap junction using only data that would be available from real dual-intracellular penetrations which allow electrophysiological recordings and intracellular staining. Rectification of gap junctions in unrecorded cells of a biologically realistic coupled cell network had negligible effects on the voltage responses of the dual-recorded neurons because of minimal current passing through these surrounding cells.
Godinez-Azcuaga, Valery F.; Shu, Fong; Finlayson, Richard D.; O'Donnell, Bruce W.
2004-07-01
This paper presents the results obtained during the development of a semi-real-time monitoring methodology based on Neural Network Pattern Recognition of Acoustic Emission (AE) signals for early detection of cracks in couplings used in aircraft and engine drive systems. AE signals were collected in order to establish a baseline of a gear-testing fixture background noise and its variations due to rotational speed and torque. Also, simulated cracking signals immersed in background noise were collected. EDM notches were machined in the driving gear and the load on the gearbox was increased until damaged was induced. Using these data, a Neural Network Signal Classifier (NNSC) was implemented and tested. The testing showed that the NNSC was capable of correctly identifying six different classes of AE signals corresponding to different gearbox operation conditions. Also, a semi-real-time classification software was implemented. This software includes functions that allow the user to view and classify AE data from a dynamic process as they are recorded at programmable time intervals. The software is capable of monitoring periodic statistics of AE data, which can be used as an indicator of damage presence and severity in a dynamic system. The semi-real-time classification software was successfully tested in situations where a delay of 10 seconds between data acquisition and classification was achieved with a hit rate of 50 hits/second per channel on eight active AE channels.
Woldegebriel, Michael; Derks, Eduard
2017-01-17
In this work, a novel probabilistic untargeted feature detection algorithm for liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS) using artificial neural network (ANN) is presented. The feature detection process is approached as a pattern recognition problem, and thus, ANN was utilized as an efficient feature recognition tool. Unlike most existing feature detection algorithms, with this approach, any suspected chromatographic profile (i.e., shape of a peak) can easily be incorporated by training the network, avoiding the need to perform computationally expensive regression methods with specific mathematical models. In addition, with this method, we have shown that the high-resolution raw data can be fully utilized without applying any arbitrary thresholds or data reduction, therefore improving the sensitivity of the method for compound identification purposes. Furthermore, opposed to existing deterministic (binary) approaches, this method rather estimates the probability of a feature being present/absent at a given point of interest, thus giving chance for all data points to be propagated down the data analysis pipeline, weighed with their probability. The algorithm was tested with data sets generated from spiked samples in forensic and food safety context and has shown promising results by detecting features for all compounds in a computationally reasonable time.
Streeter, K A; Sunshine, M D; Patel, S R; Liddell, S S; Denholtz, L E; Reier, P J; Fuller, D D; Baekey, D M
2017-03-01
Midcervical spinal interneurons form a complex and diffuse network and may be involved in modulating phrenic motor output. The intent of the current work was to enable a better understanding of midcervical "network-level" connectivity by pairing the neurophysiological multielectrode array (MEA) data with histological verification of the recording locations. We first developed a method to deliver 100-nA currents to electroplate silver onto and subsequently deposit silver from electrode tips after obtaining midcervical (C3-C5) recordings using an MEA in anesthetized and ventilated adult rats. Spinal tissue was then fixed, harvested, and histologically processed to "develop" the deposited silver. Histological studies verified that the silver deposition method discretely labeled (50-μm resolution) spinal recording locations between laminae IV and X in cervical segments C3-C5. Using correlative techniques, we next tested the hypothesis that midcervical neuronal discharge patterns are temporally linked. Cross-correlation histograms produced few positive peaks (5.3%) in the range of 0-0.4 ms, but 21.4% of neuronal pairs had correlogram peaks with a lag of ≥0.6 ms. These results are consistent with synchronous discharge involving mono- and polysynaptic connections among midcervical neurons. We conclude that there is a high degree of synaptic connectivity in the midcervical spinal cord and that the silver-labeling method can reliably mark metal electrode recording sites and "map" interneuron populations, thereby providing a low-cost and effective tool for use in MEA experiments. We suggest that this method will be useful for further exploration of midcervical network connectivity.NEW & NOTEWORTHY We describe a method that reliably identifies the locations of multielectrode array (MEA) recording sites while preserving the surrounding tissue for immunohistochemistry. To our knowledge, this is the first cost-effective method to identify the anatomic locations of neuronal
Modelling cell cycle synchronisation in networks of coupled radial glial cells.
Barrack, Duncan S; Thul, Rüdiger; Owen, Markus R
2015-07-21
Radial glial cells play a crucial role in the embryonic mammalian brain. Their proliferation is thought to be controlled, in part, by ATP mediated calcium signals. It has been hypothesised that these signals act to locally synchronise cell cycles, so that clusters of cells proliferate together, shedding daughter cells in uniform sheets. In this paper we investigate this cell cycle synchronisation by taking an ordinary differential equation model that couples the dynamics of intracellular calcium and the cell cycle and extend it to populations of cells coupled via extracellular ATP signals. Through bifurcation analysis we show that although ATP mediated calcium release can lead to cell cycle synchronisation, a number of other asynchronous oscillatory solutions including torus solutions dominate the parameter space and cell cycle synchronisation is far from guaranteed. Despite this, numerical results indicate that the transient and not the asymptotic behaviour of the system is important in accounting for cell cycle synchronisation. In particular, quiescent cells can be entrained on to the cell cycle via ATP mediated calcium signals initiated by a driving cell and crucially will cycle in near synchrony with the driving cell for the duration of neurogenesis. This behaviour is highly sensitive to the timing of ATP release, with release at the G1/S phase transition of the cell cycle far more likely to lead to near synchrony than release during mid G1 phase. This result, which suggests that ATP release timing is critical to radial glia cell cycle synchronisation, may help us to understand normal and pathological brain development.
Institute of Scientific and Technical Information of China (English)
Brahim Mohamedi; Salah Hanini; Abdelrahmane Ararem; Nacim Mellel
2015-01-01
The present study is to develop a new user-defined function using artificial neural networks intent Com-putational Fluid Dynamics (CFD) simulation for the prediction of water-vapor multiphase flows through fuel assemblies of nuclear reactor. Indeed, the provision of accurate material data especially for water and steam over a wider range of temperatures and pressures is an essential requirement for conducting CFD simulations in nuclear engineering thermal hydraulics. Contrary to the commercial CFD solver ANSYS-CFX, where the industrial standard IAPWS-IF97 (International Association for the Properties of Water and Steam-Industrial Formulation 1997) is implemented in the ANSYS-CFX internal material database, the solver ANSYS-FLUENT provides only the possibility to use equation of state (EOS), like ideal gas law, Redlich-Kwong EOS and piece-wise polynomial interpolations. For that purpose, new approach is used to implement the thermophysical prop-erties of water and steam for subcooled water in CFD solver ANSYS-FLUENT. The technique is based on artificial neural networks of multi-layer type to accurately predict 10 thermodynamic and transport properties of the density, specific heat, dynamic viscosity, thermal conductivity and speed of sound on saturated liquid and saturated vapor. Temperature is used as single input parameter, the maximum absolute error predicted by the artificial neural networks ANNs, was around 3%. Thus, the numerical investigation under CFD solver ANSYS-FLUENT becomes competitive with other CFD codes of which ANSYS-CFX in this area. In fact, the coupling of the Rensselaer Polytechnical Institute (RPI) wall boiling model and the developed Neural-UDF (User Defined Function) was found to be useful in predicting the vapor volume fraction in subcooled boiling flow.
Directory of Open Access Journals (Sweden)
T. Zelder
2007-06-01
Full Text Available Contactless vector network analysis based on a diversity calibration is investigated for the measurement of embedded devices in planar circuits. Conventional contactless measurement systems based on two probes for each measurement port have the disadvantage that the signal-to-noise system dynamics strongly depends on the distance between the contactless probes.
In order to avoid a decrease in system dynamics a diversity based measurement system is presented. The measurement setup uses one inductive and two capacitive probes. As an inductive probe a half magnetic loop in combination with a broadband balun is introduced. In order to eliminate systematic errors from the measurement results a diversity calibration algorithm is presented. Simulation and measurement results for a one-port configuration are shown.
Energy and Carbon Flux Coupling: Multi-ecosystem Comparisons Using Artificial Neural Network
Directory of Open Access Journals (Sweden)
Assefa M. Melesse
2005-01-01
Full Text Available A multi-ecosystems carbon flux simulation from energy fluxes is presented. A new statistical learning technique based on Artificial Neural Network (ANN back propagation algorithm and multi-layer perceptron architecture was used in the CO2 simulation. Four input layers (net radiation, soil heat flux, sensible and latent heat flux were used for training (calibration and testing (verification of model outputs. The 15-days half-hourly (grassland and hourly (forest and cropland micrometeorological data from eddy covariance observations of AmeriFlux towers were divided into training (5-days and testing (10-days sets. Results show that the ANN-based technique predicts CO2 flux with testing R2 values of 0.86, 0.75 and 0.94 for forest, grassland and cropland ecosystems, respectively. The technique is reliable and efficient to estimate regional or global CO2 fluxes from point measurements and understand the spatiotemporal budget of the CO2 fluxes.
A global homogenizing coupled pattern of interdep endent networks%一种全局同质化相依网络耦合模式∗
Institute of Scientific and Technical Information of China (English)
高彦丽; 陈世明
2016-01-01
Many infrastructure networks interact with and depend on each other to provide proper functionality. The interde-pendence between networks has catastrophic effects on their robustness. Events taking place in one system can propagate to any other coupled system. Recently, great efforts have been dedicated to the research on how the coupled pattern between two networks affects the robustness of interdependent networks. However, how to dynamically construct the links between two interdependent networks to obtain stronger robustness is rarely studied. To fill this gap, a global homogenizing coupled pattern between two scale-free networks is proposed in this paper. Making the final degrees of nodes distributed evenly is the principle for building the dependency links, which has the following two merits. First, the system robustness against random failure is enhanced by compressing the broadness of degree distribution. Second, the system invulnerability against targeted attack is improved by avoiding dependence on high-degree nodes. In order to better investigate its eﬃciency on improving the robustness of coupled networks against cascading failures, we adopt other four kinds of coupled patterns to make a comparative analysis, i.e., the assortative link (AL), the disassortative link (DL), the random link (RL) and global random link (GRL). We construct the BA-BA interdependent networks with the above 5 coupled patterns respectively. After applying targeted attacks and random failures to the networks, we use the ratio of giant component size after cascades to initial network size to measure the robustness of the coupled networks. It is numerically found that the interdependent network based on global homogenizing coupled pattern shows the strongest robustness under targeted attacks or random failures. The global homogenizing coupled pattern is more eﬃcient to avoid the cascading propagation under targeted attack than random failure. Finally, the reasonable expla
Energy Technology Data Exchange (ETDEWEB)
Golling, T.
2005-01-01
Two alternative measurements of the tt production cross section at {radical}(s)=1.96 TeV in proton-antiproton collisions in the lepton+jets channel are presented. The tt production cross section is extracted by combining the kinematic event information in a multivariate discriminant. The measurement yields {sigma}{sub p} {sub anti} {sub p{yields}}{sub t} {sub anti} {sub t+X} = 5.13{sub -1.57}{sup +1.76} (stat) {sub -1.10}{sup +0.96} (syst) {+-}0.33 (lumi) pb in the muon+jets channel, using 229.1 pb{sup -1}, and in the combination with the electron+jets channel (226.3 pb{sup -1}) {sigma}{sub p} {sub anti} {sub p{yields}}{sub t} {sub anti} {sub t}+X = 6.60{sub -1.28}{sup +1.37} (stat) {sub -1.11}{sup +1.25} (syst) {+-} 0.43 (lumi) pb. The second measurement presented reconstructs explicitly secondary vertices to do lifetime b-tagging. The measurement combines the muon+jets and the electron+jets channel, using 158.4 pb{sup -1} and 168.8 pb{sup -1}, respectively: {sigma}{sub p} {sub anti} {sub p{yields}}{sub t} {sub anti} {sub t+X} = 8.24{sub -1.25}{sup +1.34} (stat) {sub -1.63}{sup +1.89} (syst) {+-} 0.54 (lumi) pb. (orig.)
Institute of Scientific and Technical Information of China (English)
ZHANG Gui-Qing; ZHANG Ying-Yue; CHEN Tian-Lun
2007-01-01
Effects of aging and self-organized criticality in a pulse-coupled integrate-and-fire neuron model based on small world networks have been studied. We give the degree distribution of aging network, average shortest path length,the diameter of our network, and the clustering coefficient, and find that our neuron model displays the power-law behavior, and with the number of added links increasing, the effects of aging become smaller and smaller. This shows that if the brain works at the self-organized criticality state, it can relieve some effects caused by aging.
Intelligent sensors research using pulse-coupled neural networks for focal plane image processing
Tarr, Gregory L.; Carreras, Richard A.; DeHainaut, Christopher R.; Clastres, Xavier; Freyss, Laurent; Samuelides, Manuel
1996-03-01
An important difference between biological vision systems and their electronic counterparts is the large number of feedback signals controlling each aspect of the image collection process. For every forward path of information in the brain, from sensor to comprehension, there appears to be several neural bundles which send information back to the sensor to modify the way the information is collected. In this paper we will examine the role of such feedback signals and suggest algorithms for intelligent processing of images directly on the focal plane, using feedback. We consider first what form these signals might take and how they can be used to implement functions common to conventional image processing with the objective of moving the computation out of the digital domain and place much of its on the focal plane, or analog processing close to the focal plane. While this work falls under the general heading of artificial neural networks, it goes beyond the static processing of signals suggested by the McCulloch and Pitts model of the neuron and the Laplacian image processing suggested by Carver Mead by including the dynamics of temporal encoding in the analysis process.
Indian Academy of Sciences (India)
A B Dariane; S Azimi; A Zakerinej
2014-10-01
Snow Water Equivalent (SWE) is an important parameter in hydrologic engineering involving the stream-flow forecasting of high-elevation watersheds. In this paper, the application of classic Artificial Neural Network model (ANN) and a hybrid model combining the wavelet and ANN (WANN) is investigated in estimating the value of SWE in a mountainous basin. In addition, k-fold cross validation method is used in order to achieve a more reliable and robust model. In this regard, microwave images acquired from Spectral Sensor Microwave Imager (SSM/I) are used to estimate the SWE of Tehran sub-basins during 1992–2008 period. Also for obtaining measured SWE within the corresponding Equal-Area Scalable Earth-Grid (EASE-Grid) cell of SSM/I image, approach of Cell-SWE extraction using height–SWE relations is applied in order to reach more precise estimations. The obtained results reveal that the wavelet-ANN model significantly increases the accuracy of estimations, mainly because of using multi-scale time series as the ANN inputs. The Nash–Sutcliffe Index (NSE) for ANN and WANN models is respectively 0.09 and 0.44 which shows a firm improvement of 0.35 in NSE parameter when WANN is applied. Similar trend is observed in other parameters including RMSE where the value is 0.3 for ANN and 0.07 for WANN.
面向成本-收益好的无标度耦合网络构建方法∗%A toward cost-effective scale-free coupling network construction metho d
Institute of Scientific and Technical Information of China (English)
金学广; 寿国础; 胡怡红; 郭志刚
2016-01-01
Large network average path length will cause large network delay which brings diﬃculty in supporting the time sensitive services and applications. Large hop distance between source node and destination node in traditional network leads to significant network delay. By adding long-ranged links, path length from source node to destiny node will be reduced and original network can be transformed into a scale-free network with a small network average path length. The network delay is optimized by minimizing hop distance, in which information can transfer more eﬃciently and rapidly. Adding links can lower network delay effectively, but on the other hand, it will increase its cost. Common network construction methods focus on separating networks that are very different from each other and mostly unaware of each other, such as fixed and mobile networks planning. But in many real networks, networks are dependent on each other; therefore ignoring these network interactions cannot become more eﬃcient. Cost and effectiveness play a key role in real network construction and layering network is an effective way to analyze coupling network especially in heterogeneous network. In this paper, the model of a toward cost-effective scale-free coupling network construction method is proposed. It combines the advantages of layered network and cost-effective indicator. A layered coupling network model is established in which network is divided into several networks based on link property. Links in the same layer have the same property and the upper layer capability is higher than lower layer capability. The nodes in the upper network are selected from the lower layer network coupling with the corresponding nodes with the same spatial location. Based on the network optimization and evolving network researches, the increases of node degree and local network radius are supposed to be continuous, moreover cost-effective indicator is introduced which characterizes the costs and
The polarity protein Par6 is coupled to the microtubule network during molluscan early embryogenesis
Energy Technology Data Exchange (ETDEWEB)
Homma, Taihei [Department of Biophysics and Biochemistry, Graduate School of Science, The University of Tokyo, Hongo, Bunkyo-ku, Tokyo 113-0033 (Japan); Shimizu, Miho [Kuroda Chiromorphology Team, ERATO-SORST, JST, Komaba, Meguro-ku, Tokyo 153-8902 (Japan); Kuroda, Reiko, E-mail: ckuroda@mail.ecc.u-tokyo.ac.jp [Department of Biophysics and Biochemistry, Graduate School of Science, The University of Tokyo, Hongo, Bunkyo-ku, Tokyo 113-0033 (Japan); Kuroda Chiromorphology Team, ERATO-SORST, JST, Komaba, Meguro-ku, Tokyo 153-8902 (Japan); Department of Life Sciences, Graduate School of Arts and Sciences, The University of Tokyo, Komaba, Meguro-ku, Tokyo 153-8902 (Japan)
2011-01-07
Research highlights: {yields} The cDNAs encoding Par6 and aPKC homologues were cloned from the snail Lymnaea stagnalis. {yields} L. stagnalis Par6 directly interacts with tubulin and microtubules and localizes to the microtubule cytoskeleton during the early embryogenesis. {yields} Identical sequence and localization of LsPar6 for the dextral and the sinistral snails exclude the possibility of the gene being the primary determinant of body handedness. -- Abstract: Cell polarity, which directs the orientation of asymmetric cell division and segregation of fate determinants, is a fundamental feature of development and differentiation. Regulators of polarity have been extensively studied, and the critical importance of the Par (partitioning-defective) complex as the polarity machinery is now recognized in a wide range of eukaryotic systems. The Par polarity module is evolutionarily conserved, but its mechanism and cooperating factors vary among different systems. Here we describe the cloning and characterization of a pond snail Lymnaea stagnalis homologue of partitioning-defective 6 (Lspar6). The protein product LsPar6 shows high affinity for microtubules and localizes to the mitotic apparatus during embryonic cell division. In vitro assays revealed direct binding of LsPar6 to tubulin and microtubules, which is the first evidence of the direct interaction between the two proteins. The interaction is mediated by two distinct regions of LsPar6 both located in the N-terminal half. Atypical PKC, a functional partner of Par6, was also found to localize to the mitotic spindle. These results suggest that the L. stagnalis Par complex employs the microtubule network in cell polarity processes during the early embryogenesis. Identical sequence and localization of LsPar6 for the dextral and the sinistral snails exclude the possibility of the gene being the primary determinant of handedness.
Study on Cascading Failures′Model of Edge in Coupled Networks%耦合网络边相继故障模型研究
Institute of Scientific and Technical Information of China (English)
王建伟; 蒋晨; 孙恩慧
2014-01-01
In order to deal with cascading failures in coupled networks, this study analyzes the dynamics mechanism of cascading failures and propose the cascading failures′model of edge in coupled networks.To improve the robustness of coupled networks a-gainst cascading failures, according to different measures, this study takes multiple perspectives to analyze the correlation be-tween the robustness of coupled networks with different link patterns and some parameters in our model.this study then discusses the influences of link patterns of coupled networks and the basic network model on cascading failures and states the whole protec-tion strategies in the proposed model.This study finds: the assortative link pattern can enhance the robustness of coupled net-works against cascading failures;the more similar the topological structures of two interdependent networks, the stronger the net-work robustness against cascading failures;the robustness of coupled networks has a positive correlation with the average degree;an appropriate increase in the number of symmetrical edges between two networks can improve the network robustness.Finally, the cascading failures′model of edge in the real coupled power grid is analyzed.%针对耦合网络上频发的相继故障问题，通过分析边级联故障蔓延的动力学演化机制，构建耦合网络上边相继故障模型。以提高耦合网络整体抵制相继故障能力为出发点，依据不同度量指标，多角度分析具有不同耦合模式的耦合网络鲁棒性与模型参数之间的关联性，研究耦合网络间耦合模式和网络基本模型等因素对相继故障的影响，探讨耦合网络边相继故障模型的整体保护策略。研究结果表明，同配连接模式能够增强耦合网络抵制级联故障的鲁棒性；相互依赖的两个耦合网络之间拓扑结构越相似，网络抵制相继故障的鲁棒性越强；耦合网络鲁棒性与网络平均度正相关；适当的增加
Scherb, Anke; Papakosta, Panagiota; Straub, Daniel
2014-05-01
Wildfires cause severe damages to ecosystems, socio-economic assets, and human lives in the Mediterranean. To facilitate coping with wildfire risks, an understanding of the factors influencing wildfire occurrence and behavior (e.g. human activity, weather conditions, topography, fuel loads) and their interaction is of importance, as is the implementation of this knowledge in improved wildfire hazard and risk prediction systems. In this project, a probabilistic wildfire risk prediction model is developed, with integrated fire occurrence and fire propagation probability and potential impact prediction on natural and cultivated areas. Bayesian Networks (BNs) are used to facilitate the probabilistic modeling. The final BN model is a spatial-temporal prediction system at the meso scale (1 km2 spatial and 1 day temporal resolution). The modeled consequences account for potential restoration costs and production losses referred to forests, agriculture, and (semi-) natural areas. BNs and a geographic information system (GIS) are coupled within this project to support a semi-automated BN model parameter learning and the spatial-temporal risk prediction. The coupling also enables the visualization of prediction results by means of daily maps. The BN parameters are learnt for Cyprus with data from 2006-2009. Data from 2010 is used as validation data set. A special focus is put on the performance evaluation of the BN for fire occurrence, which is modeled as binary classifier and thus, could be validated by means of Receiver Operator Characteristic (ROC) curves. With the final best models, AUC values of more than 70% for validation could be achieved, which indicates potential for reliable prediction performance via BN. Maps of selected days in 2010 are shown to illustrate final prediction results. The resulting system can be easily expanded to predict additional expected damages in the mesoscale (e.g. building and infrastructure damages). The system can support planning of
Chen, Jun; Shibata, Tadashi
2007-04-01
Pulse-coupled neural networks (PCNNs) are biologically inspired algorithms that have been shown to be highly effective for image feature generation. However, conventional PCNNs are software-oriented algorithms that are too complicated to implement as very-large-scale integration (VLSI) hardware. To employ PCNNs in image-feature-generation VLSIs, a hardware-implementation-friendly PCNN is proposed here. By introducing the concepts of exponentially decaying output and a one-branch dendritic tree, the new PCNN eliminates the large number of convolution operators and floating-point multipliers in conventional PCNNs without compromising its performance at image feature generation. As an analog VLSI implementation of the new PCNN, an image-feature-generation circuit is proposed. By employing floating-gate metal-oxide-semiconductor (MOS) technology, the circuit achieves a full voltage-mode implementation of the PCNN in a compact structure. Inheriting the merits of the PCNN, the circuit is capable of generating rotation-independent and translation-independent features for input patterns, which has been verified by SPICE simulation.
Directory of Open Access Journals (Sweden)
Haiyan Li
2010-01-01
Full Text Available A novel method, called adaptive pulse coupled neural network (AD-PCNN using a two-stage denoising strategy, is proposed to reduce noise and speckle in the spectrograms of Doppler blood flow signals. AD-PCNN contains an adaptive thresholding PCNN and a threshold decaying PCNN. Firstly, PCNN pulses based on the adaptive threshold filter a part of background noise in the spectrogram while isolating the remained noise and speckles. Subsequently, the speckles and noise of the denoised spectrogram are detected by the pulses generated through the threshold decaying PCNN and then are iteratively removed by the intensity variation to speckle or noise neurons. The relative root mean square (RRMS error of the maximum frequency extracted from the AD-PCNN spectrogram of the simulated Doppler blood flow signals is decreased 25.2% on average compared to that extracted from the MPWD (matching pursuit with Wigner Distribution spectrogram, and the RRMS error of the AD-PCNN spectrogram is decreased 10.8% on average compared to MPWD spectrogram. Experimental results of synthetic and clinical signals show that the proposed method is better than the MPWD in improving the accuracy of the spectrograms and their maximum frequency curves.
Jin, Xin; Nie, Rencan; Zhou, Dongming; Yao, Shaowen; Chen, Yanyan; Yu, Jiefu; Wang, Quan
2016-11-01
A novel method for the calculation of DNA sequence similarity is proposed based on simplified pulse-coupled neural network (S-PCNN) and Huffman coding. In this study, we propose a coding method based on Huffman coding, where the triplet code was used as a code bit to transform DNA sequence into numerical sequence. The proposed method uses the firing characters of S-PCNN neurons in DNA sequence to extract features. Besides, the proposed method can deal with different lengths of DNA sequences. First, according to the characteristics of S-PCNN and the DNA primary sequence, the latter is encoded using Huffman coding method, and then using the former, the oscillation time sequence (OTS) of the encoded DNA sequence is extracted. Simultaneously, relevant features are obtained, and finally the similarities or dissimilarities of the DNA sequences are determined by Euclidean distance. In order to verify the accuracy of this method, different data sets were used for testing. The experimental results show that the proposed method is effective.
Tuan, P. H.; Liang, H. C.; Tung, J. C.; Chiang, P. Y.; Huang, K. F.; Chen, Y. F.
2015-12-01
The coupling interaction between the driving source and the RLC network is explored and characterized as the effective impedance. The mathematical form of the derived effective impedance is verified to be identical to the meromorphic function of the singular billiards with a truncated basis. By using the derived impedance function, the resonant modes of the RLC network can be divided into the open-circuit and short-circuit states to manifest the evolution of eigenvalues and eigenstates from closed quantum billiards to the singular billiards with a truncated basis in the strongly coupled limit. The substantial differences of the wave patterns between the uncoupled and strongly coupled eigenmodes in the two-dimensional wave systems can be clearly revealed with the RLC network. Finally, the short-circuit resonant states are exploited to confirm that the experimental Chladni nodal-line patterns in the vibrating plate are the resonant modes subject to the strong coupling between the oscillation system and the driving source.
Ramachandran, Hema; Pillai, K. P. P.; Bindu, G. R.
2016-08-01
A two-port network model for a wireless power transfer system taking into account the distributed capacitances using PP network topology with top coupling is developed in this work. The operating and maximum power transfer efficiencies are determined analytically in terms of S-parameters. The system performance predicted by the model is verified with an experiment consisting of a high power home light load of 230 V, 100 W and is tested for two forced resonant frequencies namely, 600 kHz and 1.2 MHz. The experimental results are in close agreement with the proposed model.
Chicoli, Amanda; Paley, Derek A.
2016-11-01
Individuals in a group may obtain information from other group members about the environment, including the location of a food source or the presence of a predator. Here, we model how information spreads in a group using a susceptible-infected-removed epidemic model. We apply this model to a simulated shoal of fish using the motion dynamics of a coupled oscillator model, in order to test the biological hypothesis that polarized or aligned shoaling leads to faster and more accurate escape responses. The contributions of this study are the (i) application of a probabilistic model of epidemics to the study of collective animal behavior; (ii) testing the biological hypothesis that group cohesion improves predator escape; (iii) quantification of the effect of social cues on startle propagation; and (iv) investigation of the variation in response based on network connectivity. We find that when perfectly aligned individuals in a group are startled, there is a rapid escape by individuals that directly detect the threat, as well as by individuals responding to their neighbors. However, individuals that are not startled do not head away from the threat. In startled groups that are randomly oriented, there is a rapid, accurate response by individuals that directly detect the threat, followed by less accurate responses by individuals responding to neighbor cues. Over the simulation duration, however, even unstartled individuals head away from the threat. This study illustrates a potential speed-accuracy trade-off in the startle response of animal groups, in agreement with several previous experimental studies. Additionally, the model can be applied to a variety of group decision-making processes, including those involving higher-dimensional motion.
Wostenberg, Christopher; Ceres, Pablo; Polaski, Jacob T; Batey, Robert T
2015-11-06
RNA folding in vivo is significantly influenced by transcription, which is not necessarily recapitulated by Mg(2+)-induced folding of the corresponding full-length RNA in vitro. Riboswitches that regulate gene expression at the transcriptional level are an ideal system for investigating this aspect of RNA folding as ligand-dependent termination is obligatorily co-transcriptional, providing a clear readout of the folding outcome. The folding of representative members of the SAM-I family of riboswitches has been extensively analyzed using approaches focusing almost exclusively upon Mg(2+) and/or S-adenosylmethionine (SAM)-induced folding of full-length transcripts of the ligand binding domain. To relate these findings to co-transcriptional regulatory activity, we have investigated a set of structure-guided mutations of conserved tertiary architectural elements of the ligand binding domain using an in vitro single-turnover transcriptional termination assay, complemented with phylogenetic analysis and isothermal titration calorimetry data. This analysis revealed a conserved internal loop adjacent to the SAM binding site that significantly affects ligand binding and regulatory activity. Conversely, most single point mutations throughout key conserved features in peripheral tertiary architecture supporting the SAM binding pocket have relatively little impact on riboswitch activity. Instead, a secondary structural element in the peripheral subdomain appears to be the key determinant in observed differences in regulatory properties across the SAM-I family. These data reveal a highly coupled network of tertiary interactions that promote high-fidelity co-transcriptional folding of the riboswitch but are only indirectly linked to regulatory tuning.
Institute of Scientific and Technical Information of China (English)
LIU Jian; ZHENG Shu; YU Jie-kai; ZHANG Jian-min; CHEN Zhe
2005-01-01
To screen and evaluate protein biomarkers for the detection of gliomas (Astrocytoma grade Ⅰ-Ⅳ) from healthy individuals and gliomas from brain benign tumors by using surface enhanced laser desorption/ionization time of flight mass spectrometry (SELDI-TOF-MS) coupled with an artificial neural network (ANN) algorithm. SELDI-TOF-MS protein fingerprinting of serum from 105 brain tumor patients and healthy individuals, included 28 patients with glioma (Astrocytoma Ⅰ-Ⅳ), 37 patients with brain benign tumor, and 40 age-matched healthy individuals. Two thirds of the total samples of every compared pair as training set were used to set up discriminating patterns, and one third of total samples of every compared pair as test set were used to cross-validate; simultaneously, discriminate-cluster analysis derived SPSS 10.0 software was used to compare Astrocytoma grade Ⅰ-Ⅱ with grade Ⅲ-Ⅳ ones. An accuracy of 95.7%, sensitivity of 88.9%, specificity of 100%, positive predictive value of 90% and negative predictive value of 100% were obtained in a blinded test set comparing gliomas patients with healthy individuals; an accuracy of 86.4%, sensitivity of 88.9%, specificity of 84.6%, positive predictive value of 90% and negative predictive value of 85.7% were obtained when patient's gliomas was compared with benign brain tumor. Total accuracy of 85.7%, accuracy of grade Ⅰ-Ⅱ Astrocytoma was 86.7%, accuracy ofⅢ-Ⅳ Astrocytoma was 84.6% were obtained when grade Ⅰ-Ⅱ Astrocytoma was compared with grade Ⅲ-Ⅳ ones (discriminant analysis). SELDI-TOF-MS combined with bioinformatics tools, could greatly facilitate the discovery of better biomarkers. The high sensitivity and specificity achieved by the use of selected biomarkers showed great potential application for the discrimination of gliomas patients from healthy individuals and glioma from brain benign tumors.
Energy Technology Data Exchange (ETDEWEB)
Malaescu, B. [European Organization for Nuclear Research (CERN), Geneva (Switzerland); Starovoitov, P. [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany)
2012-03-15
We perform a determination of the strong coupling constant using the latest ATLAS inclusive jet cross section data, from proton-proton collisions at {radical}(s)=7 TeV, and their full information on the bin-to-bin correlations. Several procedures for combining the statistical information from the different data inputs are studied and compared. The theoretical prediction is obtained using NLO QCD, and it also includes non-perturbative corrections. Our determination uses inputs with transverse momenta between 45 and 600 GeV, the running of the strong coupling being also tested in this range. Good agreement is observed when comparing our result with the world average at the Z-boson scale, as well as with the most recent results from the Tevatron. (orig.)
Directory of Open Access Journals (Sweden)
Xuefei Wu
2015-10-01
Full Text Available In this paper, the exponentially synchronization in the mean square is investigated for two different stochastic complex networks with hybrid coupling and time-varying delay via pinning control. By utilizing the Lyapunov stability theory, stochastic analysis theory, as well as matrix analysis, the sufficient conditions are derived to guarantee the exponential synchronization for any initial values through a feedback scheme. The numerical simulation is provided to show the effectiveness of the theoretical results.
Yilmaz, Ergin; Baysal, Veli; Ozer, Mahmut
2015-08-01
We investigate the effects of time-periodic coupling strength on the temporal coherence or firing regularity of a scale-free network consisting of stochastic Hodgkin-Huxley (H-H) neurons. The temporal coherence exhibits a resonance-like behavior depending on the cell size or the channel noise intensity. The best temporal coherence requires an optimal channel noise intensity, and this coherence can be significantly increased by time-periodic coupling strength when its frequency matches the integer multiples of the intrinsic subthreshold oscillation frequency of H-H neuron. Particularly, we find the multiple-coherence resonance depending on frequency of time-periodic coupling strength at the optimal noise intensity. We also obtain a resonance-like dependence of temporal coherence on the amplitude of time-periodic coupling strength. Additionally, we investigate the effects of average degree on the temporal coherence and find that the temporal coherence exhibits a resonance-like behavior with respect to the network average degree, indicating that the best regularity requires an optimal average degree.
相互依存网络间的拓扑构建方法%Topological coupling method between interdependent networks
Institute of Scientific and Technical Information of China (English)
李稳国; 邓曙光; 杨冰; 肖卫初
2014-01-01
To reduce cascading failures of interdependent networks, it introduces a topological coupling strategy that a network connects another network with same position nodes, by drawing on the experience of inter-similarity coupling, after defining normalized degree, inter-assortativity coefficient and inter-clustering coefficient. Adopting breadth first search algorithm and taking hub node as initial search node, the strategy can improve the matching degree of inter-similarity and extend the application scene. Interdependent ER networks and SR networks are taken as examples and simulated, the result of the experiment implies that the coupling algorithm leads to change from a first to second order percolation transition, and can improve robustness of interdependent networks compared to random coupling algorithm under targeted attacks, random attacks and targeted defenses.%为减小相互依存网络间的相继故障，在对归一化度、网络间的匹配系数及网络间的簇系数定义的基础上，借鉴网络间相似拓扑耦合思想，相互提出一种网络间同地位节点耦合的拓扑构建方法，该方法以核心节点作为搜索源节点采用广度优先搜索算法，逐级搜索并最大化网络同地位节点对的匹配，以提高相似匹配度和扩展应用场景。并以相互依存的随机网络和相互依存的无标度网络作为实例进行仿真，实验表明：此拓扑连接方法下，网络间故障渗流相变从一维非连续相变转变为二维连续相变到；相比于随机拓扑耦合网络在随机攻击、目的攻击及防御情况下，该拓扑耦合下的相互依存网络的鲁棒性均明显增强。
Directory of Open Access Journals (Sweden)
Ali Ghorbani
2017-01-01
Full Text Available Coupled Piled Raft Foundations (CPRFs are broadly applied to share heavy loads of superstructures between piles and rafts and reduce total and differential settlements. Settlements induced by static/coupled static-dynamic loads are one of the main concerns of engineers in designing CPRFs. Evaluation of induced settlements of CPRFs has been commonly carried out using three-dimensional finite element/finite difference modeling or through expensive real-scale/prototype model tests. Since the analyses, especially in the case of coupled static-dynamic loads, are not simply conducted, this paper presents two practical methods to gain the values of settlement. First, different nonlinear finite difference models under different static and coupled static-dynamic loads are developed to calculate exerted settlements. Analyses are performed with respect to different axial loads and pile’s configurations, numbers, lengths, diameters, and spacing for both loading cases. Based on the results of well-validated three-dimensional finite difference modeling, artificial neural networks and evolutionary polynomial regressions are then applied and introduced as capable methods to accurately present both static and coupled static-dynamic settlements. Also, using a sensitivity analysis based on Cosine Amplitude Method, axial load is introduced as the most influential parameter, while the ratio l/d is reported as the least effective parameter on the settlements of CPRFs.
Coupled One and Two Dimensional Model for River Network Flow and Sediment Transport%一二维耦合河网水沙模型研究
Institute of Scientific and Technical Information of China (English)
吕文丽; 张旭
2011-01-01
Based on previous research, a new one and two-dimensional coupled model of river water and sediment was proposed.With reference to the three-level solution for one-dimensional river network water mode, the two-dimensional river section will be generalized to river section within the river network.One and two dimensional coupled river network sediment model will be established with the balance of flow amount and sediment transport.The model sets up the chasing relationship between variables of water level and sediment content at the end and first section to further establish matrix equations of the whole one and two-dimensional river network node water level and sediment content.Though the verification and calculation for generalized river network from Datong to Zhenjiang in the lower reaches of the Yangtze River, it is found that the model is of great practical value.%借鉴河网水流的三级解法,将二维河段概化为河网内部河段,通过河网节点流量和输沙量的平衡,建立一二维耦合河网水沙模型.模型采用全隐式方法建立二维河段以首末断面的水位和含沙量为中间变量的矩阵追赶关系,进而建立整个一二维河网的节点水位及含沙量的矩阵方程组.对方程组的求解,可实现一二维水沙模型的耦合求解.通过对长江下游大通至镇江概化河网的验证计算,表明模型具有很好的实用价值.
Directory of Open Access Journals (Sweden)
Jianwen Feng
2015-01-01
synchronization between two complex networks. Secondly, impulsive control is added to the nodes of corresponding response network. Based on the generalized inequality about time-varying delayed different equation, the sufficient conditions for outer synchronization are derived. Finally, some examples are presented to demonstrate the effectiveness and feasibility of the results obtained in this paper.
Grzegorczyk, Marco; Husmeier, Dirk
2012-01-01
An important and challenging problem in systems biology is the inference of gene regulatory networks from short non-stationary time series of transcriptional profiles. A popular approach that has been widely applied to this end is based on dynamic Bayesian networks (DBNs), although traditional homog
Grzegorczyk, Marco; Husmeier, Dirk
2012-01-01
An important and challenging problem in systems biology is the inference of gene regulatory networks from short non-stationary time series of transcriptional profiles. A popular approach that has been widely applied to this end is based on dynamic Bayesian networks (DBNs), although traditional
DEFF Research Database (Denmark)
Agerskov, Claus; Mortensen, Rasmus M.; Bohr, Henrik G.
2015-01-01
networks, trained with greedy learning algorithms, showed superior performance in prediction over the simple feedback NNs. The best networks obtained scores of more than 90 % accuracy in predicting the degree of binding drug molecules to the mentioned receptors and with a maximal Matthew's coefficient of 0......-design. This is done by training on structural features, selected using a "minimum redundancy, maximum relevance"-test, and testing for successful prediction of categorized binding strength. An extensive comparison of the neural network performances was made in order to select the optimal architecture. Deep belief.......925. The performance of 8 category networks (8 output classes for binding strength) obtained a prediction accuracy of above 60 %. After training the networks, tests were done on how well the systems could be used as an aid in designing candidate drug molecules. Specifically, it was shown how a selection of chemical...
Institute of Scientific and Technical Information of China (English)
徐莹; 王春妮; 靳伍银; 马军
2015-01-01
Distinct rhythm and self-organization in collective electric activities of neurons could be observed in a neuronal system composed of a large number of neurons. It is found that target wave can be induced in the network by imposing continuous local periodical force or introducing local heterogeneity in the network;and these target waves can regulate the wave propagation and development as‘pacemaker’ in the network or media. A regular neuronal network is constructed in two-dimensional space, in which the local kinetics can be described by Hindmarsh-Rose neuron model, the emergence and development of ordered waves are investigated by introducing gradient coupling between neurons. For simplicity, the center area is selected by the largest coupling intensity, which is gradually decreased at certain step with increasing distance from the center area. It is found that the spiral wave and/or the target wave can be induced by appropriate selection of gradient coupling, and both waves can occupy the network, and then the collective behaviors of the network can be regulated to show ordered states. Particularly, the ordered wave can be effective to dominate the collective behavior of neuronal networks, even as the stochastic values are used for initial states. These results associated with the gradient coupling on the regulating collective behaviors could be useful to understand the self-organization behaviors in neuronal networks.
Institute of Scientific and Technical Information of China (English)
CHEN Nan-xiang; CAO Lian-hai; HUANG Qiang
2005-01-01
Scientific forecasting water yield of mine is of great significance to the safety production of mine and the colligated using of water resources. The paper established the forecasting model for water yield of mine, combining neural network with the partial least square method. Dealt with independent variables by the partial least square method, it can not only solve the relationship between independent variables but also reduce the input dimensions in neural network model, and then use the neural network which can solve the non-linear problem better. The result of an example shows that the prediction has higher precision in forecasting and fitting.
Wells, Chad R.; Galvani, Alison P.
2015-12-01
In a loop of dynamic feedback, behavior such as the decision to vaccinate, hand washing, or avoidance influences the progression of the epidemic, yet behavior is driven by the individual's and population's perceived risk of infection during an outbreak. In what we believe will become a seminal paper that stimulates future research as well as an informative teaching aid, Wang et. al. comprehensively review methodological advances that have been used to incorporate human behavior into epidemiological models on the effects of coupling disease transmission and behavior on complex social networks [1]. As illustrated by the recent outbreaks of measles and Middle Eastern Respiratory Syndrome (MERS), here we highlight the importance of coupling behavior and disease transmission that Wang et al. address.
Yoshimura, Tetsuzo; Nawata, Hideyuki
2017-01-01
The self-organized lightwave network (SOLNET) provides "optical solder," which enables self-aligned optical couplings between misaligned optical devices with different core sizes. We propose a low-cost SOLNET formation method, in which write beams are generated within optical devices by excitation lights from outside. Simulations based on the finite-difference time-domain method reveal that the two-photon processes enhance optical-solder capabilities. In couplings between 600-nm-wide waveguides opposed with 32-μm distance a wide lateral misalignment tolerance of 2 μm to maintain <1 dB loss at 650 nm in wavelength is obtained. The coupling loss at 1-μm lateral misalignment is 0.4 dB. In couplings between 3-μm-wide and 600-nm-wide waveguides, losses at 650 nm are 0.1 dB for no misalignments and 0.9 dB for 1-μm misalignment. These results suggest that SOLNETs provide optical solder with mode size converting functions.
Markstrom, Steven L.
2012-01-01
A software program, called P2S, has been developed which couples the daily stream temperature simulation capabilities of the U.S. Geological Survey Stream Network Temperature model with the watershed hydrology simulation capabilities of the U.S. Geological Survey Precipitation-Runoff Modeling System. The Precipitation-Runoff Modeling System is a modular, deterministic, distributed-parameter, physical-process watershed model that simulates hydrologic response to various combinations of climate and land use. Stream Network Temperature was developed to help aquatic biologists and engineers predict the effects of changes that hydrology and energy have on water temperatures. P2S will allow scientists and watershed managers to evaluate the effects of historical climate and projected climate change, landscape evolution, and resource management scenarios on watershed hydrology and in-stream water temperature.
Energy Technology Data Exchange (ETDEWEB)
Abazov, V.M.; /Dubna, JINR; Abbott, B.; /Oklahoma U.; Abolins, M.; /Michigan State U.; Acharya, B.S.; /Tata Inst.; Adams, M.; /Illinois U., Chicago; Adams, T.; /Florida State U.; Aguilo, E.; /Alberta U. /Simon Fraser U. /York U., Canada /McGill U.; Ahsan, M.; /Kansas State U.; Alexeev, G.D.; /Dubna, JINR; Alkhazov, G.; /St. Petersburg, INP; Alton, A.; /Michigan U. /Northeastern U.
2009-11-01
We determine the strong coupling constant {alpha}{sub s} and its energy dependence from the p{sub T} dependence of the inclusive jet cross section in p{bar p} collisions at {radical}s = 1.96 TeV. The strong coupling constant is determined over the transverse momentum range 50 < p{sub T} < 145 GeV. Using perturbative QCD calculations to order {Omicron}({alpha}{sub s}{sup 3}) combined with {Omicron}({alpha}{sub s}{sup 4}) contributions from threshold corrections, we obtain {alpha}{sub s}(M{sub Z}) = 0.1173{sub -0.0049}{sup +0.0041}. This is the most precise result obtained at a hadron-hadron collider.
Zheng, Xue-Li; Song, Ji-Peng; Ling, Tao; Hu, Zhen Peng; Yin, Peng-Fei; Davey, Kenneth; Du, Xi-Wen; Qiao, Shi-Zhang
2016-06-01
T. Ling, X.-W. Du, S. Z. Qiao, and co-workers report strongly coupled Nafion molecules and ordered-porous CdS networks for visible-light water splitting. The image conceptually shows how the three-dimensional ordered structure effectively harvests incoming light. As described on page 4935, the inorganic CdS skeleton is homogeneously passivated by the organic Nafion molecules to facilitate hydrogen generation. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Tian, H; Liu, C; Gao, X D; Yao, W B
2013-03-01
Granulocyte colony-stimulating factor (G-CSF) is a cytokine widely used in cancer patients receiving high doses of chemotherapeutic drugs to prevent the chemotherapy-induced suppression of white blood cells. The production of recombinant G-CSF should be increased to meet the increasing market demand. This study aims to model and optimize the carbon source of auto-induction medium to enhance G-CSF production using artificial neural networks coupled with genetic algorithm. In this approach, artificial neural networks served as bioprocess modeling tools, and genetic algorithm (GA) was applied to optimize the established artificial neural network models. Two artificial neural network models were constructed: the back-propagation (BP) network and the radial basis function (RBF) network. The root mean square error, coefficient of determination, and standard error of prediction of the BP model were 0.0375, 0.959, and 8.49 %, respectively, whereas those of the RBF model were 0.0257, 0.980, and 5.82 %, respectively. These values indicated that the RBF model possessed higher fitness and prediction accuracy than the BP model. Under the optimized auto-induction medium, the predicted maximum G-CSF yield by the BP-GA approach was 71.66 %, whereas that by the RBF-GA approach was 75.17 %. These predicted values are in agreement with the experimental results, with 72.4 and 76.014 % for the BP-GA and RBF-GA models, respectively. These results suggest that RBF-GA is superior to BP-GA. The developed approach in this study may be helpful in modeling and optimizing other multivariable, non-linear, and time-variant bioprocesses.
Directory of Open Access Journals (Sweden)
Mohammad Heidari
2013-01-01
Full Text Available In this study, the static pull-in instability of beam-type micro-electromechanical system (MEMS is theoretically investigated. Considering the mid-plane stretching as the source of the nonlinearity in the beam behavior, a nonlinear size dependent Euler-Bernoulli beam model is used based on a modified couple stress theory, capable of capturing the size effect. Two supervised neural networks, namely, back propagation (BP and radial basis function (RBF, have been used for modeling the static pull-in instability of microcantilever beam. These networks have four inputs of length, width, gap, and the ratio of height to scale parameter of beam as the independent process variables, and the output is static pull-in voltage of microbeam. Numerical data employed for training the networks and capabilities of the models in predicting the pull-in instability behavior has been verified. Based on verification errors, it is shown that the radial basis function of neural network is superior in this particular case and has the average errors of 4.55% in predicting pull-in voltage of cantilever microbeam. Further analysis of pull-in instability of beam under different input conditions has been investigated and comparison results of modeling with numerical considerations show a good agreement, which also proves the feasibility and effectiveness of the adopted approach.
Directory of Open Access Journals (Sweden)
Wilten eNicola
2016-02-01
Full Text Available A fundamental question in computational neuroscience is how to connect a network of spiking neurons to produce desired macroscopic or mean field dynamics. One possible approach is through the Neural Engineering Framework (NEF. The NEF approach requires quantities called decoders which are solved through an optimization problem requiring large matrix inversion. Here, we show how a decoder can be obtained analytically for type I and certain type II firing rates as a function of the heterogeneity of its associated neuron. These decoders generate approximants for functions that converge to the desired function in mean-squared error like 1/N, where N is the number of neurons in the network. We refer to these decoders as scale-invariant decoders due to their structure. These decoders generate weights for a network of neurons through the NEF formula for weights. These weights force the spiking network to have arbitrary and prescribed mean field dynamics. The weights generated with scale-invariant decoders all lie on low dimensional hypersurfaces asymptotically. We demonstrate the applicability of these scale-invariant decoders and weight surfaces by constructing networks of spiking theta neurons that replicate the dynamics of various well known dynamical systems such as the neural integrator, Van der Pol system and the Lorenz system. As these decoders are analytically determined and non-unique, the weights are also analytically determined and non-unique. We discuss the implications for measured weights of neuronal networks
Search for W'->tb resonances with left- and right-handed couplings to fermions
Energy Technology Data Exchange (ETDEWEB)
Abazov, Victor Mukhamedovich; /Dubna, JINR; Abbott, Braden Keim; /Oklahoma U.; Acharya, Bannanje Sripath; /Tata Inst.; Adams, Mark Raymond; /Illinois U., Chicago; Adams, Todd; /Florida State U.; Alexeev, Guennadi D.; /Dubna, JINR; Alkhazov, Georgiy D.; /St. Petersburg, INP; Alton, Andrew K.; /Michigan U. /Augustana Coll., Sioux Falls; Alverson, George O.; /Northeastern U.; Alves, Gilvan Augusto; /Rio de Janeiro, CBPF; Ancu, Lucian Stefan; /Nijmegen U. /Fermilab
2011-01-01
We present a search for the production of a heavy gauge boson, W{prime}, that decays to third-generation quarks, by the D0 Collaboration in p{bar p} collisions at {radical}s = 1.96 TeV. We set 95% confidence level upper limits on the production cross section times branching fraction. For the first time, we set limits for arbitrary combinations of left- and right-handed couplings of the W{prime} boson to fermions. For couplings with the same strength as the standard model W boson, we set the following limits for M(W{prime}) > m({nu}{sub R}): M(W{prime}) > 863 GeV for purely left-handed couplings, M(W{prime}) > 885 GeV for purely right-handed couplings, and M(W{prime}) > 916 GeV if both left- and right-handed couplings are present. The limit for right-handed couplings improves for M(W{prime}) < m({nu}{sub R}) to M(W{prime}) > 890 GeV.
Coupling strength versus coupling impact in nonidentical bidirectionally coupled dynamics
Laiou, Petroula; Andrzejak, Ralph G.
2017-01-01
The understanding of interacting dynamics is important for the characterization of real-world networks. In general, real-world networks are heterogeneous in the sense that each node of the network is a dynamics with different properties. For coupled nonidentical dynamics symmetric interactions are not straightforwardly defined from the coupling strength values. Thus, a challenging issue is whether we can define a symmetric interaction in this asymmetric setting. To address this problem we introduce the notion of the coupling impact. The coupling impact considers not only the coupling strength but also the energy of the individual dynamics, which is conveyed via the coupling. To illustrate this concept, we follow a data-driven approach by analyzing signals from pairs of coupled model dynamics using two different connectivity measures. We find that the coupling impact, but not the coupling strength, correctly detects a symmetric interaction between pairs of coupled dynamics regardless of their degree of asymmetry. Therefore, this approach allows us to reveal the real impact that one dynamics has on the other and hence to define symmetric interactions in pairs of nonidentical dynamics.
Institute of Scientific and Technical Information of China (English)
王国红; 贾楠; 邢蕊
2013-01-01
Competition outside of the region may lead to the overall migration and the cavitation in the develop-ment process of industrial clusters. Fostering innovation incubator network for SMEs is an effective way to deal with cluster risks. The paper defines the meaning of innovation incubation network and collaborative innovation network of SMEs in clusters, analyzes the relation schema, and determines the coupling domain between the two. System dynamics is used to analyze the coupling mechanism. Policy advices to improve the effect of coupling and the regional innovation capacity are put forward. Dalian Double D Innovation Incubator is analyzed as an ex-emplary case.% 在产业集群的发展过程中，区域外的竞争可能会导致集群的整体迁移和空洞现象，培育面向中小企业的创新孵化网络是应对集群风险的有效途径。界定了创新孵化网络与集群中小企业协同创新网络的内涵，分析了二者之间的关系模式，确定了二者的耦合域，应用系统动力学方法分析了二者之间的耦合作用机制，提出了促进二者之间耦合作用、提高区域创新能力的政策建议，并以大连双D港创业孵化中心为对象进行了案例分析。
Gameiro, Sofia; Boivin, Jacky; Canavarro, Maria Cristina; Moura-Ramos, Mariana; Soares, Isabel
2010-04-01
Research showed that following the birth of a first child, parents increase contact with family members and diminish contact with friends, however, these changes may differ when conception is achieved through assisted reproductive technologies (ART). Based on the convoy model (Kahn & Antonucci, 1980) perspective of close relationships, we examined changes across the transition to parenthood in the social networks and support of men and women that conceived spontaneously or through ART. Thirty one women and 22 men (22 couples) that conceived through ART and 28 women and 24 men (24 couples) with a spontaneous conception provided data on social network and support from nuclear family, extended family, and friends twice: at 24-weeks pregnancy and 4-months postpartum. Results demonstrated that, regardless of method of conception, during the transition to parenthood new parents showed a strong nesting movement towards their nuclear family, perceiving increasing levels of nuclear family support across time. Extended family seemed to have only a secondary role on the social nesting movement and a withdrawal from friends was also observed. Considering the primary role nuclear family members seem to have on providing effective support to child-rearing, a greater emphasis on the importance of parents' relationship with their own parents and siblings could be made and social and working policies that prevent the displacement of families geographically also should be considered.
Heidari, Mohammad; Heidari, Ali; Homaei, Hadi
2014-01-01
The static pull-in instability of beam-type microelectromechanical systems (MEMS) is theoretically investigated. Two engineering cases including cantilever and double cantilever microbeam are considered. Considering the midplane stretching as the source of the nonlinearity in the beam behavior, a nonlinear size-dependent Euler-Bernoulli beam model is used based on a modified couple stress theory, capable of capturing the size effect. By selecting a range of geometric parameters such as beam lengths, width, thickness, gaps, and size effect, we identify the static pull-in instability voltage. A MAPLE package is employed to solve the nonlinear differential governing equations to obtain the static pull-in instability voltage of microbeams. Radial basis function artificial neural network with two functions has been used for modeling the static pull-in instability of microcantilever beam. The network has four inputs of length, width, gap, and the ratio of height to scale parameter of beam as the independent process variables, and the output is static pull-in voltage of microbeam. Numerical data, employed for training the network, and capabilities of the model have been verified in predicting the pull-in instability behavior. The output obtained from neural network model is compared with numerical results, and the amount of relative error has been calculated. Based on this verification error, it is shown that the radial basis function of neural network has the average error of 4.55% in predicting pull-in voltage of cantilever microbeam. Further analysis of pull-in instability of beam under different input conditions has been investigated and comparison results of modeling with numerical considerations shows a good agreement, which also proves the feasibility and effectiveness of the adopted approach. The results reveal significant influences of size effect and geometric parameters on the static pull-in instability voltage of MEMS.
Institute of Scientific and Technical Information of China (English)
无
2011-01-01
The drag force of water flow through single fracture and the coupling characteristics of seepage and stress in single fracture surface are analyzed,and a three dimensional model of coupled unsteady seepage and stress fields is proposed.This model is used to the analysis of foundation rock mass of a high dam.If the coupling effects are considered,the changes of boundary heads have less influence on the inner head of rock mass,and the strong permeability of main fractures appears.If the coupling effects are not considered,the fractures distribution affects the inner head more greatly.When the upstream water head declines,the inner head of dam foundation slightly declines and the hydraulic gradient distribution becomes smoother.A bigger upstream water level declining velocity has a stronger lag effect,meanwhile the values of stress components change more greatly.Therefore the upstream water level declining velocity directly affects the stability of rock mass in dam foundation and we should take into account the above factors to make sure the safety of the dam during reservoir level fluctuation period.
Huang, Daizheng; Wu, Zhihui
2017-01-01
Accurately predicting the trend of outpatient visits by mathematical modeling can help policy makers manage hospitals effectively, reasonably organize schedules for human resources and finances, and appropriately distribute hospital material resources. In this study, a hybrid method based on empirical mode decomposition and back-propagation artificial neural networks optimized by particle swarm optimization is developed to forecast outpatient visits on the basis of monthly numbers. The data outpatient visits are retrieved from January 2005 to December 2013 and first obtained as the original time series. Second, the original time series is decomposed into a finite and often small number of intrinsic mode functions by the empirical mode decomposition technique. Third, a three-layer back-propagation artificial neural network is constructed to forecast each intrinsic mode functions. To improve network performance and avoid falling into a local minimum, particle swarm optimization is employed to optimize the weights and thresholds of back-propagation artificial neural networks. Finally, the superposition of forecasting results of the intrinsic mode functions is regarded as the ultimate forecasting value. Simulation indicates that the proposed method attains a better performance index than the other four methods.
Huang, Daizheng; Wu, Zhihui
2017-01-01
Accurately predicting the trend of outpatient visits by mathematical modeling can help policy makers manage hospitals effectively, reasonably organize schedules for human resources and finances, and appropriately distribute hospital material resources. In this study, a hybrid method based on empirical mode decomposition and back-propagation artificial neural networks optimized by particle swarm optimization is developed to forecast outpatient visits on the basis of monthly numbers. The data outpatient visits are retrieved from January 2005 to December 2013 and first obtained as the original time series. Second, the original time series is decomposed into a finite and often small number of intrinsic mode functions by the empirical mode decomposition technique. Third, a three-layer back-propagation artificial neural network is constructed to forecast each intrinsic mode functions. To improve network performance and avoid falling into a local minimum, particle swarm optimization is employed to optimize the weights and thresholds of back-propagation artificial neural networks. Finally, the superposition of forecasting results of the intrinsic mode functions is regarded as the ultimate forecasting value. Simulation indicates that the proposed method attains a better performance index than the other four methods. PMID:28222194
Grzegorczyk, Marco; Husmeier, Dirk
2013-01-01
To relax the homogeneity assumption of classical dynamic Bayesian networks (DBNs), various recent studies have combined DBNs with multiple changepoint processes. The underlying assumption is that the parameters associated with time series segments delimited by multiple changepoints are a priori inde
Liu, Long; Sun, Jun; Xu, Wenbo; Du, Guocheng; Chen, Jian
2009-01-01
Hyaluronic acid (HA) is a natural biopolymer with unique physiochemical and biological properties and finds a wide range of applications in biomedical and cosmetic fields. It is important to increase HA production to meet the increasing HA market demand. This work is aimed to model and optimize the amino acids addition to enhance HA production of Streptococcus zooepidemicus with radial basis function (RBF) neural network coupling quantum-behaved particle swarm optimization (QPSO) algorithm. In the RBF-QPSO approach, RBF neural network is used as a bioprocess modeling tool and QPSO algorithm is applied to conduct the optimization with the established RBF neural network black model as the objective function. The predicted maximum HA yield was 6.92 g/L under the following conditions: arginine 0.062 g/L, cysteine 0.036 g/L, and lysine 0.043 g/L. The optimal amino acids addition allowed HA yield increased from 5.0 g/L of the control to 6.7 g/L in the validation experiments. Moreover, the modeling and optimization capacity of the RBF-QPSO approach was compared with that of response surface methodology (RSM). It was indicated that the RBF-QPSO approach gave a slightly better modeling and optimization result compared with RSM. The developed RBF-QPSO approach in this work may be helpful for the modeling and optimization of the other multivariable, nonlinear, time-variant bioprocesses.
Directory of Open Access Journals (Sweden)
Ramesh Ummanni
Full Text Available Prostate cancer (PCa is the most common type of cancer found in men and among the leading causes of cancer death in the western world. In the present study, we compared the individual protein expression patterns from histologically characterized PCa and the surrounding benign tissue obtained by manual micro dissection using highly sensitive two-dimensional differential gel electrophoresis (2D-DIGE coupled with mass spectrometry. Proteomic data revealed 118 protein spots to be differentially expressed in cancer (n = 24 compared to benign (n = 21 prostate tissue. These spots were analysed by MALDI-TOF-MS/MS and 79 different proteins were identified. Using principal component analysis we could clearly separate tumor and normal tissue and two distinct tumor groups based on the protein expression pattern. By using a systems biology approach, we could map many of these proteins both into major pathways involved in PCa progression as well as into a group of potential diagnostic and/or prognostic markers. Due to complexity of the highly interconnected shortest pathway network, the functional sub networks revealed some of the potential candidate biomarker proteins for further validation. By using a systems biology approach, our study revealed novel proteins and molecular networks with altered expression in PCa. Further functional validation of individual proteins is ongoing and might provide new insights in PCa progression potentially leading to the design of novel diagnostic and therapeutic strategies.
一种耦合赋权的网络安全评价模型%Network Security Assessment Model of Coupling Empowerment
Institute of Scientific and Technical Information of China (English)
陈华喜; 郭有强; 姚保峰
2011-01-01
采用加速遗传算法的模糊层次分析法(AHP)筛选指标,构建计算机网络安全评价指标体系,提出基于主客观赋权相结合的改进AHP以及信息熵耦合赋权法,对影响网络安全的因索重要性进行排序,利用模糊综合评判法建立网络安全评价模型.实例应用结果表明,该模型的评价结果客观合理.%By means of accelerating the fuzzy Analytic Hierarchy Process(AHP) screening index of genetic algorithm, this paper constructs evaluation index system of computer network security, puts forward the information entropy with objective and subjective empowerment and improved AHP coupling weighting, sequences the influence factors of network security, the network safety evaluation model is established with the fuzzy comprehensive evaluation method. Application results show that the evaluate results of this model are objective and reasonable.
Energy Technology Data Exchange (ETDEWEB)
Lambert, D.
2003-12-19
We present a measurement of {sigma}(b{bar b})/{sigma}(q{bar q}) in the annihilation process e{sup +}e{sup -} {yields} q{bar q} {yields} hadrons at {radical}s = 29 GeV. The analysis is based on 66 pb{sup -1} of data collected between 1984 and 1986 with the TPC/2{gamma} detector at PEP. To identify bottom events, we use a neural network with inputs that are computed from the 3-momenta of all of the observed charged hadrons in each event. We also present a study of bias in techniques for measuring inclusive {pi}{sup {+-}}, K{sup {+-}}, and p/{bar p} production in the annihilation process e{sup +}e{sup -} {yields} b{bar b} {yields} hadrons at {radical}s = 29 GeV, using a neural network to identify bottom-quark jets. In this study, charged particles are identified by a simultaneous measurement of momentum and ionization energy loss (dE/dx).
Institute of Scientific and Technical Information of China (English)
郭晓永; 李俊民
2011-01-01
We introduce a hybrid feedback control scheme to design a controller for the projective synchronization of complex dynamical networks with unknown periodically time-varying parameters.A differential-difference mixed parametric learning law and an adaptive learning control law are constructed to ensure the asymptotic convergence of the error in the sense of square error norm.Moreover,numerical simulation results are used to verify the effectiveness of the proposed method.%We introduce a hybrid feedback control scheme to design a controller for the projective synchronization of complex dynamical networks with unknown periodically time-varying parameters. A differential-difference mixed parametric learning law and an adaptive learning control law are constructed to ensure the asymptotic convergence of the error in the sense of square error norm. Moreover, numerical simulation results are used to verify the effectiveness of the proposed method.
Hu, Jinyu; Gao, Zhiwei
2012-01-01
In this study, a gene positive network is proposed based on a weighted undirected graph, where the weight represents the positive correlation of the genes. A Pearson agglomerative clustering algorithm is employed to build a clustering tree, where dotted lines cut the tree from bottom to top leading to a number of subsets of the modules. In order to achieve better module partitions, the Pearson correlation coefficient modularity is addressed to seek optimal module decomposition by selecting an...
Bedont, Joseph L; LeGates, Tara A; Buhr, Ethan; Bathini, Abhijith; Ling, Jonathan P; Bell, Benjamin; Wu, Mark N; Wong, Philip C; Van Gelder, Russell N; Mongrain, Valerie; Hattar, Samer; Blackshaw, Seth
2017-01-09
The suprachiasmatic nucleus (SCN) is the central circadian clock in mammals. It is entrained by light but resistant to temperature shifts that entrain peripheral clocks [1-5]. The SCN expresses many functionally important neuropeptides, including vasoactive intestinal peptide (VIP), which drives light entrainment, synchrony, and amplitude of SCN cellular clocks and organizes circadian behavior [5-16]. The transcription factor LHX1 drives SCN Vip expression, and cellular desynchrony in Lhx1-deficient SCN largely results from Vip loss [17, 18]. LHX1 regulates many genes other than Vip, yet activity rhythms in Lhx1-deficient mice are similar to Vip(-/-) mice under light-dark cycles and only somewhat worse in constant conditions. We suspected that LHX1 targets other than Vip have circadian functions overlooked in previous studies. In this study, we compared circadian sleep and temperature rhythms of Lhx1- and Vip-deficient mice and found loss of acute light control of sleep in Lhx1 but not Vip mutants. We also found loss of circadian resistance to fever in Lhx1 but not Vip mice, which was partially recapitulated by heat application to cultured Lhx1-deficient SCN. Having identified VIP-independent functions of LHX1, we mapped the VIP-independent transcriptional network downstream of LHX1 and a largely separable VIP-dependent transcriptional network. The VIP-independent network does not affect core clock amplitude and synchrony, unlike the VIP-dependent network. These studies identify Lhx1 as the first gene required for temperature resistance of the SCN clockworks and demonstrate that acute light control of sleep is routed through the SCN and its immediate output regions.
Security Enhancement With Optimal QOS Using EAP-AKA In Hybrid Coupled 3G-WLAN Convergence Network
R Shankar; Timothy Rajkumar.K; P Dananjayan
2010-01-01
The third generation partnership project (3GPP) has addressed the feasibility of interworking and specified the interworking architecture and security architecture for third generation (3G)-wireless local area network (WLAN), it is developing, system architecture evolution (SAE)/ long term evolution (LTE) architecture, for the next generation mobile communication system. To provide a secure 3G-WLAN interworking in the SAE/LTE architecture, Extensible authentication protocol-authentication and...
Institute of Scientific and Technical Information of China (English)
罗剑飞; 林炜铁; 蔡小龙; 李敬源
2012-01-01
Two artificial intelligence techniques, artificial neural network and genetic algorithm, were applied to optimize the fermentation medium for improving the nitrite oxidization rate of nitrite oxidizing bacteria. Experiments were conducted with the composition of medium components obtained by genetic algorithm, and the experimental data were used to build a BP (back propagation) neural network model. The concentrations of six medium components were used as input vectors, and the nitrite oxidization rate was used as output vector of the model. The BP neural network model was used as the objective function of genetic algorithm to find the optimum medium composition for the maximum nitrite oxidization rate. The maximum nitrite oxidization rate was 0.952 g 2 NO-2-N·(g MLSS)-1·d-1 , obtained at the genetic algorithm optimized concentration of medium components (g·L-1 ): NaCl 0.58, MgSO 4 ·7H 2 O 0.14, FeSO 4 ·7H 2 O 0.141, KH 2 PO 4 0.8485, NaNO 2 2.52, and NaHCO 3 3.613. Validation experiments suggest that the experimental results are consistent with the best result predicted by the model. A scale-up experiment shows that the nitrite degraded completely after 34 h when cultured in the optimum medium, which is 10 h less than that cultured in the initial medium.
Grzegorczyk, Marco; Husmeier, Dirk
2012-07-12
An important and challenging problem in systems biology is the inference of gene regulatory networks from short non-stationary time series of transcriptional profiles. A popular approach that has been widely applied to this end is based on dynamic Bayesian networks (DBNs), although traditional homogeneous DBNs fail to model the non-stationarity and time-varying nature of the gene regulatory processes. Various authors have therefore recently proposed combining DBNs with multiple changepoint processes to obtain time varying dynamic Bayesian networks (TV-DBNs). However, TV-DBNs are not without problems. Gene expression time series are typically short, which leaves the model over-flexible, leading to over-fitting or inflated inference uncertainty. In the present paper, we introduce a Bayesian regularization scheme that addresses this difficulty. Our approach is based on the rationale that changes in gene regulatory processes appear gradually during an organism's life cycle or in response to a changing environment, and we have integrated this notion in the prior distribution of the TV-DBN parameters. We have extensively tested our regularized TV-DBN model on synthetic data, in which we have simulated short non-homogeneous time series produced from a system subject to gradual change. We have then applied our method to real-world gene expression time series, measured during the life cycle of Drosophila melanogaster, under artificially generated constant light condition in Arabidopsis thaliana, and from a synthetically designed strain of Saccharomyces cerevisiae exposed to a changing environment.
Institute of Scientific and Technical Information of China (English)
卫亭; 杨晓丽; 孙中奎
2015-01-01
Notingthattherandomnoiseandtimedelayareprevalentincomplexnetworksandthetopologyofa network is often unknown or partially unknown, based on the principle of random generalized projective lag synchronization,an approach was proposed to estimate the system parameters and topological structure of delay-coupled complex networks under circumstance noise.By constructing an appropriate controller and adaptive updating rules,the unknown network parameters and topological structure of the concerned networks were identified simultaneously.The accuracy of the method was rigorously proved by the LaSalle-type theorem for stochastic differential delay equations.An example of network with chaotic oscillator was provided to illustrate the method.The numerical results indicate that the unknown network parameters and topological structure can be accurately identified,and yet the proposed method is robust against the time delay,the update gain and the network topology.%针对随机噪声及时间滞后普遍存在于耦合网络，且其结构往往未知或部分未知问题，基于网络间随机广义投影滞后同步原理，通过合理设计控制器与自适应更新规则，构建辨识网络模型未知动力学参数及拓扑结构的识别方案；结合随机时滞微分方程LaSalle型不变性原理，从数学上严格证明识别方案的准确性。通过具体网络模型，借助计算仿真验证识别方案的有效性。数值模拟结果表明，网络未知动力学参数及拓扑结构不但能准确辨识，且识别方案不依赖耦合时滞、更新增益及网络拓扑结构等选取。
Energy Technology Data Exchange (ETDEWEB)
Abazov, V.M.; Abbott, B.; Abolins, M.; Acharya, B.S.; Adams, M.; Adams, T.; Agelou, M.; Agram, J.-L.; Ahn, S.H.; Ahsan, M.; Alexeev, G.D.; Alkhazov, G.; Alton, A.; Alverson, G.; Alves, G.A.; Anastasoaie, M.; Andeen, T.; Anderson, S.; Andrieu, B.; Arnoud, Y.; Askew, A.; /Buenos Aires U. /Rio de Janeiro, CBPF /Rio de Janeiro State U. /Sao
2005-02-01
The authors present a measurement of the Z{gamma} production cross section and limits on anomalous ZZ{gamma} and Z{gamma}{gamma} couplings for form-factor scales of {Lambda} = 750 and 1000 GeV. The measurement is based on 138 (152) candidate events in the ee{gamma} ({mu}{mu}{gamma}) final state using 320 (290) pb{sup -1} of p{bar p} collisions at {radical}s = 1.96 TeV. The 95% C.L. limits on real and imaginary parts of individual anomalous couplings are |h{sub 10,30}{sup Z}| < 0.23, |h{sub 20,40}{sup Z}| < 0.020, |h{sub 10,30}{gamma}| < 0.23, and |h{sub 20,40}{gamma}| < 0.019 for {Lambda} = 1000 GeV.
Directory of Open Access Journals (Sweden)
Xiaojing eFang
2016-02-01
Full Text Available Previous studies investigated the distinct roles played by different cognitive regions and suggested that the patterns of connectivity of these regions are associated with working memory. However, the specific causal mechanism through which the neuronal circuits that involve these brain regions contribute to working memory is still unclear. Here, in a large sample of healthy young adults, we first identified the core working memory regions by linking working memory accuracy to resting-state functional connectivity with the bilateral dorsolateral prefrontal cortex (a principal region in the central-executive network. Then a spectral dynamic causal modeling analysis was performed to quantify the effective connectivity between these regions. Finally, the effective connectivity was correlated with working memory accuracy to characterize the relationship between these connections and working memory performance. We found that the functional connections between the bilateral dorsolateral prefrontal cortex and the dorsal anterior cingulate cortex and between the right dorsolateral prefrontal cortex and the left orbital fronto-insular cortex were correlated with working memory accuracy. Furthermore, the effective connectivity from the dorsal anterior cingulate cortex to the bilateral dorsolateral prefrontal cortex and from the right dorsolateral prefrontal cortex to the left orbital fronto-insular cortex could predict individual differences in working memory. Because the dorsal anterior cingulate cortex and orbital fronto-insular cortex are core regions of the salience network, we inferred that the inter- and causal-connectivity between core regions within the central-executive and salience networks is functionally relevant for working memory performance. In summary, the current study identified the dorsolateral prefrontal cortex-related resting-state effective connectivity underlying working memory and suggests that individual differences in cognitive
Directory of Open Access Journals (Sweden)
Jinyu Hu
2012-01-01
Full Text Available In this study, a gene positive network is proposed based on a weighted undirected graph, where the weight represents the positive correlation of the genes. A Pearson agglomerative clustering algorithm is employed to build a clustering tree, where dotted lines cut the tree from bottom to top leading to a number of subsets of the modules. In order to achieve better module partitions, the Pearson correlation coefficient modularity is addressed to seek optimal module decomposition by selecting an optimal threshold value. For the liver cancer gene network under study, we obtain a strong threshold value at 0.67302, and a very strong correlation threshold at 0.80086. On the basis of these threshold values, fourteen strong modules and thirteen very strong modules are obtained respectively. A certain degree of correspondence between the two types of modules is addressed as well. Finally, the biological significance of the two types of modules is analyzed and explained, which shows that these modules are closely related to the proliferation and metastasis of liver cancer. This discovery of the new modules may provide new clues and ideas for liver cancer treatment.
Brault, A; Lucor, D
2016-01-01
SUMMARY This work aims at quantifying the effect of inherent uncertainties from cardiac output on the sensitivity of a human compliant arterial network response based on stochastic simulations of a reduced-order pulse wave propagation model. A simple pulsatile output form is utilized to reproduce the most relevant cardiac features with a minimum number of parameters associated with left ventricle dynamics. Another source of critical uncertainty is the spatial heterogeneity of the aortic compliance which plays a key role in the propagation and damping of pulse waves generated at each cardiac cycle. A continuous representation of the aortic stiffness in the form of a generic random field of prescribed spatial correlation is then considered. Resorting to a stochastic sparse pseudospectral method, we investigate the spatial sensitivity of the pulse pressure and waves reflection magnitude with respect to the different model uncertainties. Results indicate that uncertainties related to the shape and magnitude of th...
Alexander, R.B.; Böhlke, J.K.; Boyer, E.W.; David, M.B.; Harvey, J.W.; Mulholland, P.J.; Seitzinger, S.P.; Tobias, C.R.; Tonitto, C.; Wollheim, W.M.
2009-01-01
The importance of lotic systems as sinks for nitrogen inputs is well recognized. A fraction of nitrogen in streamflow is removed to the atmosphere via denitrification with the remainder exported in streamflow as nitrogen loads. At the watershed scale, there is a keen interest in understanding the factors that control the fate of nitrogen throughout the stream channel network, with particular attention to the processes that deliver large nitrogen loads to sensitive coastal ecosystems. We use a dynamic stream transport model to assess biogeochemical (nitrate loadings, concentration, temperature) and hydrological (discharge, depth, velocity) effects on reach-scale denitrification and nitrate removal in the river networks of two watersheds having widely differing levels of nitrate enrichment but nearly identical discharges. Stream denitrification is estimated by regression as a nonlinear function of nitrate concentration, streamflow, and temperature, using more than 300 published measurements from a variety of US streams. These relations are used in the stream transport model to characterize nitrate dynamics related to denitrification at a monthly time scale in the stream reaches of the two watersheds. Results indicate that the nitrate removal efficiency of streams, as measured by the percentage of the stream nitrate flux removed via denitrification per unit length of channel, is appreciably reduced during months with high discharge and nitrate flux and increases during months of low-discharge and flux. Biogeochemical factors, including land use, nitrate inputs, and stream concentrations, are a major control on reach-scale denitrification, evidenced by the disproportionately lower nitrate removal efficiency in streams of the highly nitrate-enriched watershed as compared with that in similarly sized streams in the less nitrate-enriched watershed. Sensitivity analyses reveal that these important biogeochemical factors and physical hydrological factors contribute nearly
Andrade, Maria; Melazzi, Nicola; Walker, Richard; Hussmann, Heinrich; Venieris, Iakovos
2014-01-01
Convergence proposes the enhancement of the Internet with a novel, content-centric, publish–subscribe service model based on the versatile digital item (VDI): a common container for all kinds of digital content, including digital representations of real-world resources. VDIs will serve the needs of the future Internet, providing a homogeneous method for handling structured information, incorporating security and privacy mechanisms. CONVERGENCE subsumes the following areas of research: · definition of the VDI as a new fundamental unit of distribution and transaction; · content-centric networking functionality to complement or replace IP-address-based routing; · security and privacy protection mechanisms; · open-source middleware, including a community dictionary service to enable rich semantic searches; · applications, tested under real-life conditions. This book shows how CONVERGENCE allows publishing, searching and subscri...
Keough, James M; Zuniga, Ashley N; Jenson, David L; Barry, Bridgette A
2013-02-07
In photosynthetic oxygen evolution, redox active tyrosine Z (YZ) plays an essential role in proton-coupled electron transfer (PCET) reactions. Four sequential photooxidation reactions are necessary to produce oxygen at a Mn(4)CaO(5) cluster. The sequentially oxidized states of this oxygen-evolving cluster (OEC) are called the S(n) states, where n refers to the number of oxidizing equivalents stored. The neutral radical, YZ•, is generated and then acts as an electron transfer intermediate during each S state transition. In the X-ray structure, YZ, Tyr161 of the D1 subunit, is involved in an extensive hydrogen bonding network, which includes calcium-bound water. In electron paramagnetic resonance experiments, we measured the YZ• recombination rate, in the presence of an intact Mn(4)CaO(5) cluster. We compared the S(0) and S(2) states, which differ in Mn oxidation state, and found a significant difference in the YZ• decay rate (t(1/2) = 3.3 ± 0.3 s in S(0); t(1/2) = 2.1 ± 0.3 s in S(2)) and in the solvent isotope effect (SIE) on the reaction (1.3 ± 0.3 in S(0); 2.1 ± 0.3 in S(2)). Although the YZ site is known to be solvent accessible, the recombination rate and SIE were pH independent in both S states. To define the origin of these effects, we measured the YZ• recombination rate in the presence of ammonia, which inhibits oxygen evolution and disrupts the hydrogen bond network. We report that ammonia dramatically slowed the YZ• recombination rate in the S(2) state but had a smaller effect in the S(0) state. In contrast, ammonia had no significant effect on YD•, the stable tyrosyl radical. Therefore, the alterations in YZ• decay, observed with S state advancement, are attributed to alterations in OEC hydrogen bonding and consequent differences in the YZ midpoint potential/pK(a). These changes may be caused by activation of metal-bound water molecules, which hydrogen bond to YZ. These observations document the importance of redox control in proton-coupled
Bahrami, Saeed; Doulati Ardejani, Faramarz; Baafi, Ernest
2016-05-01
In this study, hybrid models are designed to predict groundwater inflow to an advancing open pit mine and the hydraulic head (HH) in observation wells at different distances from the centre of the pit during its advance. Hybrid methods coupling artificial neural network (ANN) with genetic algorithm (GA) methods (ANN-GA), and simulated annealing (SA) methods (ANN-SA), were utilised. Ratios of depth of pit penetration in aquifer to aquifer thickness, pit bottom radius to its top radius, inverse of pit advance time and the HH in the observation wells to the distance of observation wells from the centre of the pit were used as inputs to the networks. To achieve the objective two hybrid models consisting of ANN-GA and ANN-SA with 4-5-3-1 arrangement were designed. In addition, by switching the last argument of the input layer with the argument of the output layer of two earlier models, two new models were developed to predict the HH in the observation wells for the period of the mining process. The accuracy and reliability of models are verified by field data, results of a numerical finite element model using SEEP/W, outputs of simple ANNs and some well-known analytical solutions. Predicted results obtained by the hybrid methods are closer to the field data compared to the outputs of analytical and simple ANN models. Results show that despite the use of fewer and simpler parameters by the hybrid models, the ANN-GA and to some extent the ANN-SA have the ability to compete with the numerical models.
Energy Technology Data Exchange (ETDEWEB)
Zhou, Jing [Idaho National Lab. (INL), Idaho Falls, ID (United States); Huang, Hai [Idaho National Lab. (INL), Idaho Falls, ID (United States); Mattson, Earl [Idaho National Lab. (INL), Idaho Falls, ID (United States); Wang, Herb F. [Univ. of Wisconsin, Madison, WI (United States); Haimson, Bezalel C. [Univ. of Wisconsin, Madison, WI (United States); Doe, Thomas W. [Golder Associates Inc., Redmond, VA (United States); Oldenburg, Curtis M. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Dobson, Patrick F. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
2017-02-01
Aimed at supporting the design of hydraulic fracturing experiments at the kISMET site, ~1500 m below ground in a deep mine, we performed pre-experimental hydraulic fracturing simulations in order to estimate the breakdown pressure, propagation pressure, fracture geometry, and the magnitude of induced seismicity using a newly developed fully coupled three-dimensional (3D) network flow and quasi-static discrete element model (DEM). The quasi-static DEM model, which is constructed by Delaunay tessellation of the rock volume, considers rock fabric heterogeneities by using the “disordered” DEM mesh and adding random perturbations to the stiffness and tensile/shear strengths of individual DEM elements and the elastic beams between them. A conjugate 3D flow network based on the DEM lattice is constructed to calculate the fluid flow in both the fracture and porous matrix. One distinctive advantage of the model is that fracturing is naturally described by the breakage of elastic beams between DEM elements. It is also extremely convenient to introduce mechanical anisotropy into the model by simply assigning orientation-dependent tensile/shear strengths to the elastic beams. In this paper, the 3D hydraulic fracturing model was verified against the analytic solution for a penny-shaped crack model. We applied the model to simulate fracture propagation from a vertical open borehole based on initial estimates of rock mechanical properties and in-situ stress conditions. The breakdown pressure and propagation pressure are directly obtained from the simulation. In addition, the released elastic strain energies of individual fracturing events were calculated and used as a conservative estimate for the magnitudes of the potential induced seismic activities associated with fracturing. The comparisons between model predictions and experimental results are still ongoing.
Dessy, Raymond E., Ed.
1982-01-01
Discusses five approaches used by industry/colleges to provide local area network (LAN) capabilities in the analytical laboratory: (1) mixed baseband bus network coupled to a star net; (2) broadband bus network; (3) ring network; (4) star network coupled to broadband net; and (5) simple multiprocessor center. Part I (September issue) focused on…
Energy Technology Data Exchange (ETDEWEB)
Deguchi, H; Nawa, D; Hashimoto, Y; Mito, M; Takagi, S [Faculty of Engineering, Kyushu Institute of Technology, Kitakyushu 804-8550 (Japan); Hagiwara, M [Faculty of Engineering and Design, Kyoto Institute of Technology, Kyoto 606-8585 (Japan); Koyama, K, E-mail: deguchi@tobata.isc.kyutech.ac.j [Faculty of Integrated Arts and Sciences, University of Tokushima, Tokushima 770-8502 (Japan)
2009-03-01
Ceramic YBa{sub 2}Cu{sub 4}O{sub 8} samples composed of sub-micron size grains are considered as random Josephson-coupled networks of 0 and pi junctions, and they show successive phase transitions. The first transition occurs inside each grain at T{sub c1} and the second transition occurs among the grains at T{sub c2} (> T{sub c1}), where a negative divergence of nonlinear susceptibility is found. This critical phenomenon at T{sub c2} suggests the onset of the chiral-glass phase, as predicted by Kawamura and Li. We measured the temperature dependencies of the current-voltage characteristics of the samples and derived the linear and nonlinear resistivities. With decreases in temperature, linear resistivity decreased monotonously and remained at a finite value at temperatures less than T{sub c2}, while nonlinear resistivity diminished continuously for temperatures moving towards T{sub c2}. These results are consistent with the theoretical predictions.
Jacob, Samuel; Banerjee, Rintu
2016-08-01
A novel approach to overcome the acidification problem has been attempted in the present study by codigesting industrial potato waste (PW) with Pistia stratiotes (PS, an aquatic weed). The effectiveness of codigestion of the weed and PW was tested in an equal (1:1) proportion by weight with substrate concentration of 5g total solid (TS)/L (2.5gPW+2.5gPS) which resulted in enhancement of methane yield by 76.45% as compared to monodigestion of PW with a positive synergistic effect. Optimization of process parameters was conducted using central composite design (CCD) based response surface methodology (RSM) and artificial neural network (ANN) coupled genetic algorithm (GA) model. Upon comparison of these two optimization techniques, ANN-GA model obtained through feed forward back propagation methodology was found to be efficient and yielded 447.4±21.43LCH4/kgVSfed (0.279gCH4/kgCODvs) which is 6% higher as compared to the CCD-RSM based approach. Copyright © 2016 Elsevier Ltd. All rights reserved.
Measurement of trilinear gauge boson couplings from at {\\boldmath$\\sqrt{s}=1.96$} TeV
Energy Technology Data Exchange (ETDEWEB)
Abazov, Victor Mukhamedovich; /Dubna, JINR; Abbott, Braden Keim; /Oklahoma U.; Abolins, Maris A.; /Michigan State U.; Acharya, Bannanje Sripath; /Tata Inst.; Adams, Mark Raymond; /Illinois U., Chicago; Adams, Todd; /Florida State U.; Aguilo, Ernest; /Alberta U. /Simon Fraser U. /York U., Canada /McGill U.; Ahsan, Mahsana; /Kansas State U.; Alexeev, Guennadi D.; /Dubna, JINR; Alkhazov, Georgiy D.; /St. Petersburg, INP; Alton, Andrew K.; /Michigan U. /Augustana Coll., Sioux Falls /Northeastern U.
2009-07-01
We present a direct measurement of trilinear gauge boson couplings at gammaWW and ZWW vertices in WW and WZ events produced in p{bar p} collisions at {radical}s = 1.96 TeV. We consider events with one electron or muon, missing transverse energy, and at least two jets. The data were collected using the D0 detector and correspond to 1.1 fb{sup -1} of integrated luminosity. Considering two different relations between the couplings at the gammaWW and ZWW vertices, we measure these couplings at 68% C.L. to be kappa{sub gamma} = 1.07{sub -0.29}{sup +0.26}, lambda = 0.00{sub -0.06}{sup +0.06}, and g{sub 1}{sup Z} = 1.04{sup -0.09}{sup +0.09} in a scenario respecting SU(2){sub L}[direct-product]U(1){sub Y} gauge symmetry and kappa = 1.04{sub -0.11}{sup +0.11} and lambda=0.00{sub -0.06}{sup +0.06} in an 'equal couplings' scenario.
Institute of Scientific and Technical Information of China (English)
张巍; 党兴华
2012-01-01
Based on the analysis of coupling relationship of the enterprise' s organizational learning capability and network embeddedness capability in technological innovation networks, an evaluation model of coupling relations is set up by means of synergistic theory in this paper. Finally, the model is used to evaluate the coupling degree of D enterprise, a core in the technological innovation networks, between enterprise' s organizational learning capability and network embeddedness capability, and the results show that the two factors of enterprise in D innovation network are of middle coupling degree and middle coordination degree, and there is still room for improvement in the relations.%从组织学习能力与网络嵌入能力这两个技术创新能力子系统的关系出发,分析了技术创新网络中企业组织学习能力与网络嵌入能力的交互耦合关系,构建其耦合关系模型,并对以D企业为核心的技术创新网络中企业组织学习能力和网络嵌入能力的耦合度与耦合协调度进行了分析评价,结果表明,以D企业为核心的技术创新网络中企业的组织学习能力与网络嵌入能力处于中度耦合、中度协调耦合状态,仍有进一步改善的空间.
Power, M. E.; Moreno-Mateos, D.; Uno, H.; Bode, C.; Rainey, W.
2010-12-01
Background/Question/Methods. Network configuration of river drainages affects ecological exchange between mainstem channels and smaller tributaries, and between coupled terrestrial and aquatic habitats. Seasonal complementarity of fluxes may enhance predator densities and persistence in linked habitats under continental climate regimes (Nakano and Murakami 2001). In a Mediterranean watershed (the upper South Fork Eel River of Northern California (39°44’N, 123°37’W)), we studied spatial and seasonal patterns in insect fluxes among river, wetland, and forest habitats. We quantified insect emergence with vertical traps, and lateral fluxes between six wetland and eight river reaches and the upland forest adjacent to each. Insect horizontal fluxes were sampled using sticky traps along 50-150 m transects from the moister to the dryer habitats. We also studied vertical gradients of insect fluxes over rivers (up to 7 m) and in the forest (up to 40 m). Ca. 1800 traps and 40,000 insects were quantified. Results/Conclusions. In contrast to linked forest-river ecosystems in Hokkaido, peaks of insect fluxes in aquatic versus terrestrial habitats of the Eel River basin were less offset, and the seasonality of terrestrial versus river peaks was reversed. From late April through May, when the whole landscape was moist, there was no spatial variation in insect abundance-activity along forest, wetland, or river transects, and abundances averaged 315 insects m-2d-1. As the uplands dried out, from June to September, insect abundance peaked in wetlands and near the river, but dropped in the forest to average 32 insects m-2d-1 . The wetlands, with three abundance peaks distributed through spring, summer, and fall, maintained insect fluxes when river and forest fluxes were low. Vertically arrayed sticky traps over the river documented maximal insect activity-abundance near the water surface. In some positions, movements appeared random (equal downstream and upstream fluxes), but at
Institute of Scientific and Technical Information of China (English)
屈小波; 闫敬文; 肖弘智; 朱自谦
2008-01-01
Nonsubsampled contourlet transform (NSCT) provides flexible multiresolution, anisotropy, and directional expansion for images. Compared with the original contourlet transform, it is shift-invariant and can overcome the pseudo-Gibbs phenomena around singularities. Pulse coupled neural networks (PCNN) is a visual cortex-inspired neural network and characterized by the global coupling and pulse synchronization of neurons. It has been proven suitable for image processing and successfully employed in image fusion. In this paper, NSCT is associated with PCNN and used in image fusion to make full use of the characteristics of them. Spatial frequency in NSCT domain is input to motivate PCNN and coefficients in NSCT domain with large firing times are selected as coefficients of the fused image. Experimental results demonstrate that the proposed algorithm outperforms typical wavelet-based, contourlet-based, PCNN-based, and contourlet-PCNN-based fusion algorithms in terms of objective criteria and visual appearance.
Institute of Scientific and Technical Information of China (English)
杨娜; 陈后金; 李艳凤; 郝晓莉; 姚畅
2013-01-01
提出了一种改进的脉冲耦合神经网络(Receptive field-pulse coupled neural networks,RF-PCNN)模型.通过感受野模型对连接矩阵的优化,使脉冲耦合神经网络(Pulse coupled neural networks,PCNN)模型具有了方向性和尺度性,能够更好地模拟视觉细胞图像分割的功能.试验结果表明:RF-PCNN模型对自然环境中车辆图像分割的有效性,分割结果具有较高的边界检出率,较好地解决了图像分割中车牌区域存在的欠分割和过分割问题.
Suk, Heejun
2016-08-01
This paper presents a semi-analytical procedure for solving coupled the multispecies reactive solute transport equations, with a sequential first-order reaction network on spatially or temporally varying flow velocities and dispersion coefficients involving distinct retardation factors. This proposed approach was developed to overcome the limitation reported by Suk (2013) regarding the identical retardation values for all reactive species, while maintaining the extensive capability of the previous Suk method involving spatially variable or temporally variable coefficients of transport, general initial conditions, and arbitrary temporal variable inlet concentration. The proposed approach sequentially calculates the concentration distributions of each species by employing only the generalized integral transform technique (GITT). Because the proposed solutions for each species' concentration distributions have separable forms in space and time, the solution for subsequent species (daughter species) can be obtained using only the GITT without the decomposition by change-of-variables method imposing the limitation of identical retardation values for all the reactive species by directly substituting solutions for the preceding species (parent species) into the transport equation of subsequent species (daughter species). The proposed solutions were compared with previously published analytical solutions or numerical solutions of the numerical code of the Two-Dimensional Subsurface Flow, Fate and Transport of Microbes and Chemicals (2DFATMIC) in three verification examples. In these examples, the proposed solutions were well matched with previous analytical solutions and the numerical solutions obtained by 2DFATMIC model. A hypothetical single-well push-pull test example and a scale-dependent dispersion example were designed to demonstrate the practical application of the proposed solution to a real field problem.
Directory of Open Access Journals (Sweden)
R.R. Siva Kiran
2017-03-01
Full Text Available The present study deals with the application of artificial intelligence techniques coupled with Box–Behnken (BB design to model the process parameters for biosorption of cadmium using live Spirulina (Arthrospira spp. as adsorbent in open race way pond with Zarrouk medium. The biomass concentration of Spirulina spp. decreased to half at 4 ppm Cd (II after 8 days. Based on the LCt50 values, 3.69 ppm (8th day, Spirulina (Arthospira maxima showed maximum tolerance. Considerable growth and bioaccumulation of Spirulina spp. is observed below 1 ppm and tolerant up to 3 ppm. The cadmium adsorption on Spirulina spp. showed good correlation (R2 = 0.99 when applied to Freundlich equation and data fit into pseudo second order kinetics. A four factorial, three blocks and three level Box–Behnken design with initial concentration (1 ppb to 5 ppb, biosorbant dosage (0.1 gdw to 0.2 gdw, agitation speed (12 rpm to 16 rpm and pH (6 to 8 as independent variables and percentage adsorption as dependent variable were selected for study. The data were further processed using artificial neural network model and DIRECT algorithm for better optimization. The final Cd (II concentration of <0.5 ppb was achieved with 1 ppb initial concentration under optimal conditions. A continuous desorption process was also developed for removal of cadmium from Spirulina (Arthrospira sp.
基于脉冲耦合神经网络的零水印算法%ZERO-WATERMARKING ALGORITHM BASED ON PULSE-COUPLED NEURAL NETWORK
Institute of Scientific and Technical Information of China (English)
王晓珍; 王晅
2014-01-01
Aiming at the problem of existing zero-watermarking algorithms to be sensitive to the variations of images in illumination, rotation,position and scale,we propose a zero-watermarking algorithm which is based on pulse-coupled neural network (M-PCNN).The method imitates the perception process of biological vision,decomposes the images into a recognition sequence composed of a body of binary images,and then calculates the entropy of each binary image in the sequence and uses them as image ’s zero-watermarking features. Theoretical and experimental results show that the proposed approach can describe the global characteristics of the image and is robust to image’s variations in illumination,rotation and position than the existing zero-watermarking algorithms.It is also has lower dimensions.%针对现有的零水印算法对图像的光照、旋转、位置、尺度变化较为敏感的问题，提出一种基于脉冲耦合神经网络（M-PCNN）的零水印算法。该方法模拟生物视觉的感知过程，将图像分解成由若干二值图像组成的认知序列，计算序列中的每幅二值图像的熵作为图像零水印特征。理论与实验结果表明，该方法与现有的零水印算法相比，可以描述图像的全局特征，对图像的光照、旋转、位置等变化有较强的鲁棒性，而且具有较低的维数。
Brault, Antoine; Dumas, Laurent; Lucor, Didier
2016-12-10
This work aims at quantifying the effect of inherent uncertainties from cardiac output on the sensitivity of a human compliant arterial network response based on stochastic simulations of a reduced-order pulse wave propagation model. A simple pulsatile output form is used to reproduce the most relevant cardiac features with a minimum number of parameters associated with left ventricle dynamics. Another source of significant uncertainty is the spatial heterogeneity of the aortic compliance, which plays a key role in the propagation and damping of pulse waves generated at each cardiac cycle. A continuous representation of the aortic stiffness in the form of a generic random field of prescribed spatial correlation is then considered. Making use of a stochastic sparse pseudospectral method, we investigate the sensitivity of the pulse pressure and waves reflection magnitude over the arterial tree with respect to the different model uncertainties. Results indicate that uncertainties related to the shape and magnitude of the prescribed inlet flow in the proximal aorta can lead to potent variation of both the mean value and standard deviation of blood flow velocity and pressure dynamics due to the interaction of different wave propagation and reflection features. Lack of accurate knowledge in the stiffness properties of the aorta, resulting in uncertainty in the pulse wave velocity in that region, strongly modifies the statistical response, with a global increase in the variability of the quantities of interest and a spatial redistribution of the regions of higher sensitivity. These results will provide some guidance in clinical data acquisition and future coupling of arterial pulse wave propagation reduced-order model with more complex beating heart models.
Coupled transfers; Transferts couples
Energy Technology Data Exchange (ETDEWEB)
Nicolas, X.; Lauriat, G.; Jimenez-Rondan, J. [Universite de Marne-la-Vallee, Lab. d' Etudes des Transferts d' Energie et de Matiere (LETEM), 77 (France); Bouali, H.; Mezrhab, A. [Faculte des Sciences, Dept. de Physique, Lab. de Mecanique et Energetique, Oujda (Morocco); Abid, C. [Ecole Polytechnique Universitaire de Marseille, IUSTI UMR 6595, 13 Marseille (France); Stoian, M.; Rebay, M.; Lachi, M.; Padet, J. [Faculte des Sciences, Lab. de Thermomecanique, UTAP, 51 - Reims (France); Mladin, E.C. [Universitaire Polytechnique Bucarest, Faculte de Genie Mecanique, Bucarest (Romania); Mezrhab, A. [Faculte des Sciences, Lab. de Mecanique et Energetique, Dept. de Physique, Oujda (Morocco); Abid, C.; Papini, F. [Ecole Polytechnique, IUSTI, 13 - Marseille (France); Lorrette, C.; Goyheneche, J.M.; Boechat, C.; Pailler, R. [Laboratoire des Composites ThermoStructuraux, UMR 5801, 33 - Pessac (France); Ben Salah, M.; Askri, F.; Jemni, A.; Ben Nasrallah, S. [Ecole Nationale d' Ingenieurs de Monastir, Lab. d' Etudes des Systemes Thermiques et Energetiques (Tunisia); Grine, A.; Desmons, J.Y.; Harmand, S. [Laboratoire de Mecanique et d' Energetique, 59 - Valenciennes (France); Radenac, E.; Gressier, J.; Millan, P. [ONERA, 31 - Toulouse (France); Giovannini, A. [Institut de Mecanique des Fluides de Toulouse, 31 (France)
2005-07-01
This session about coupled transfers gathers 30 articles dealing with: numerical study of coupled heat transfers inside an alveolar wall; natural convection/radiant heat transfer coupling inside a plugged and ventilated chimney; finite-volume modeling of the convection-conduction coupling in non-stationary regime; numerical study of the natural convection/radiant heat transfer coupling inside a partitioned cavity; modeling of the thermal conductivity of textile reinforced composites: finite element homogenization on a full periodical pattern; application of the control volume method based on non-structured finite elements to the problems of axisymmetrical radiant heat transfers in any geometries; modeling of convective transfers in transient regime on a flat plate; a conservative method for the non-stationary coupling of aero-thermal engineering codes; measurement of coupled heat transfers (forced convection/radiant transfer) inside an horizontal duct; numerical simulation of the combustion of a water-oil emulsion droplet; numerical simulation study of heat and mass transfers inside a reactor for nano-powders synthesis; reduction of a combustion and heat transfer model of a direct injection diesel engine; modeling of heat transfers inside a knocking operated spark ignition engine; heat loss inside an internal combustion engine, thermodynamical and flamelet model, composition effects of CH{sub 4}H{sub 2} mixtures; experimental study and modeling of the evolution of a flame on a solid fuel; heat transfer for laminar subsonic jet of oxygen plasma impacting an obstacle; hydrogen transport through a A-Si:H layer submitted to an hydrogen plasma: temperature effects; thermal modeling of the CO{sub 2} laser welding of a magnesium alloy; radiant heat transfer inside a 3-D environment: application of the finite volume method in association with the CK model; optimization of the infrared baking of two types of powder paints; optimization of the emission power of an infrared
Wang, Lin; Huang, Juxiang; Jiang, Minghu; Lin, Hong
2012-06-01
We constructed the low-expression tissue-specific transplantation antigen P35B (TSTA3) immune response-mediated metabolism coupling cell cycle to postreplication repair network in no-tumor hepatitis/cirrhotic tissues (HBV or HCV infection) compared with high-expression (fold change ≥ 2) human hepatocellular carcinoma in GEO data set, by using integration of gene regulatory network inference method with gene ontology analysis of TSTA3-activated up- and downstream networks. Our results showed TSTA3 upstream-activated CCNB2, CKS1B, ELAVL3, GAS7, NQO1, NTN1, OCRL, PLA2G1B, REG3A, SSTR5, etc. and TSTA3 downstream-activated BAP1, BRCA1, CCL20, MCM2, MS4A2, NTN1, REG1A, TP53I11, VCAN, SLC16A3, etc. in no-tumor hepatitis/cirrhotic tissues. TSTA3-activated network enhanced the regulation of apoptosis, cyclin-dependent protein kinase activity, cell migration, insulin secretion, transcription, cell division, cell proliferation, DNA replication, postreplication repair, cell differentiation, T-cell homeostasis, neutrophil-mediated immunity, neutrophil chemotaxis, interleukin-8 production, inflammatory response, immune response, B-cell activation, humoral immune response, actin filament organization, xenobiotic metabolism, lipid metabolism, phospholipid metabolism, leukotriene biosynthesis, organismal lipid catabolism, phosphatidylcholine metabolism, arachidonic acid secretion, activation of phospholipase A2, deoxyribonucleotide biosynthesis, heterophilic cell adhesion, activation of MAPK activity, signal transduction by p53 class mediator resulting in transcription of p21 class mediator, G-protein-coupled receptor protein signaling pathway, response to toxin, acute-phase response, DNA damage response, intercellular junction assembly, cell communication, and cell recognition, as a result of inducing immune response-mediated metabolism coupling cell cycle to postreplication repair in no-tumor hepatitis/cirrhotic tissues.
Vulnerability of network of networks
Havlin, S.; Kenett, D. Y.; Bashan, A.; Gao, J.; Stanley, H. E.
2014-10-01
Our dependence on networks - be they infrastructure, economic, social or others - leaves us prone to crises caused by the vulnerabilities of these networks. There is a great need to develop new methods to protect infrastructure networks and prevent cascade of failures (especially in cases of coupled networks). Terrorist attacks on transportation networks have traumatized modern societies. With a single blast, it has become possible to paralyze airline traffic, electric power supply, ground transportation or Internet communication. How, and at which cost can one restructure the network such that it will become more robust against malicious attacks? The gradual increase in attacks on the networks society depends on - Internet, mobile phone, transportation, air travel, banking, etc. - emphasize the need to develop new strategies to protect and defend these crucial networks of communication and infrastructure networks. One example is the threat of liquid explosives a few years ago, which completely shut down air travel for days, and has created extreme changes in regulations. Such threats and dangers warrant the need for new tools and strategies to defend critical infrastructure. In this paper we review recent advances in the theoretical understanding of the vulnerabilities of interdependent networks with and without spatial embedding, attack strategies and their affect on such networks of networks as well as recently developed strategies to optimize and repair failures caused by such attacks.
Institute of Scientific and Technical Information of China (English)
杨娜; 陈后金; 郝晓莉; 李艳凤
2013-01-01
The license plate of the moving vehicle image has some characteristics such as small proportion, random positions and different sizes. The plate regions are easily in a state of under-segmentation and over-segmentation when we segment the vehicle images. Pulse coupled neural network(PCNN) is known as the third generation neural network and is widely used in image segmentation. In the process of image segmentation which uses pulse coupled neural networks to simulate human vision, traditional PCNN model can't meet the scale change needs for image segmentation because of the fixed values in the connection weight matrix. In order to solve this problem, the method of image segmentation based on pulse coupled neural networks of multi-scale space was proposed. The scale space was introduced into traditional PCNN model to make the model possess the scale characteristics and improve the system' s ability to segment license plate image adaptively.%运动车辆图像中车牌具有所占比例小、位置不固定和大小不一的特点,因此,对车辆图像分割时车牌区域容易产生过分割与欠分割问题.脉冲耦合神经网络(Pulse Coupled Neural Network,PCNN)被誉为“第三代神经网络”并广泛应用于图像分割.在利用PCNN模拟人类视觉的图像分割过程中,由于传统PCNN模型中的连接矩阵使用固定值表示,使得PCNN模型不能满足图像分割时尺度变化的需求.为了解决这个问题,本文提出了基于多尺度空间PCNN模型的车辆图像分割算法,将尺度空间引入PCNN模型,使PCNN模型具有了尺度特性,提高了系统自适应分割车牌图像的能力.
Generic flux coupling analysis
Reimers, A.C.; Goldstein, Y.; Bockmayr, A.
2015-01-01
Flux coupling analysis (FCA) has become a useful tool for aiding metabolic reconstructions and guiding genetic manipulations. Originally, it was introduced for constraint-based models of metabolic networks that are based on the steady-state assumption. Recently, we have shown that the steady-state a
Localized attack on clustering networks
Dong, Gaogao; Du, Ruijin; Shao, Shuai; Stanley, H Eugene; Shlomo, Havlin
2016-01-01
Clustering network is one of which complex network attracting plenty of scholars to discuss and study the structures and cascading process. We primarily analyzed the effect of clustering coefficient to other various of the single clustering network under localized attack. These network models including double clustering network and star-like NON with clustering and random regular (RR) NON of ER networks with clustering are made up of at least two networks among which exist interdependent relation among whose degree of dependence is measured by coupling strength. We show both analytically and numerically, how the coupling strength and clustering coefficient effect the percolation threshold, size of giant component, critical coupling point where the behavior of phase transition changes from second order to first order with the increase of coupling strength between the networks. Last, we study the two types of clustering network: one type is same with double clustering network in which each subnetwork satisfies ...
Tierz, Pablo; Woodhouse, Mark; Phillips, Jeremy; Sandri, Laura; Selva, Jacopo; Marzocchi, Warner; Odbert, Henry
2017-04-01
Volcanoes are extremely complex physico-chemical systems where magma formed at depth breaks into the planet's surface resulting in major hazards from local to global scales. Volcano physics are dominated by non-linearities, and complicated spatio-temporal interrelationships which make volcanic hazards stochastic (i.e. not deterministic) by nature. In this context, probabilistic assessments are required to quantify the large uncertainties related to volcanic hazards. Moreover, volcanoes are typically multi-hazard environments where different hazardous processes can occur whether simultaneously or in succession. In particular, explosive volcanoes are able to accumulate, through tephra fallout and Pyroclastic Density Currents (PDCs), large amounts of pyroclastic material into the drainage basins surrounding the volcano. This addition of fresh particulate material alters the local/regional hydrogeological equilibrium and increases the frequency and magnitude of sediment-rich aqueous flows, commonly known as lahars. The initiation and volume of rain-triggered lahars may depend on: rainfall intensity and duration; antecedent rainfall; terrain slope; thickness, permeability and hydraulic diffusivity of the tephra deposit; etc. Quantifying these complex interrelationships (and their uncertainties), in a tractable manner, requires a structured but flexible probabilistic approach. A Bayesian Belief Network (BBN) is a directed acyclic graph that allows the representation of the joint probability distribution for a set of uncertain variables in a compact and efficient way, by exploiting unconditional and conditional independences between these variables. Once constructed and parametrized, the BBN uses Bayesian inference to perform causal (e.g. forecast) and/or evidential reasoning (e.g. explanation) about query variables, given some evidence. In this work, we illustrate how BBNs can be used to model the influence of several variables on the generation of rain-triggered lahars
Trifonova, Tatiana; Tulenev, Nikita; Trifonov, Dmitriy; Arakelian, Sergei
2014-05-01
1. Surface water and groundwater interaction model under conditions of huge level of precipitation in catastrophic floods and mudflows for mountain river watershed is introduced. Seismic processes and volcanic activity impact on the formation of disastrous floods due to dramatic change of the pressure field in groundwater horizons, is under discussion for such a triple coupling system, i.e. surface water - groundwater - crack network. Under the conception we analyze recent (2013) catastrophic water events: the catastrophic floods in Western Europe (May-June, 2013), in the Amur river basin, Russia/China (Aug.-Sept, 2013) and in Colorado, USA (Sept. 12-15,2013). In addition, a separate analysis is carried out for debris event in the Krimsk-city, Caucasus (Krasnodar) region, Russia (July 06-07, 2012). 2. There is a group of problems determined by dramatic discrepancies in water mass balance and other vital parameters, on the one hand, by estimation for different types of atmospheric precipitation (both torrential rain and continuous precipitations) and, on the other hand, for observable natural water events (i.e. catastrophic floods and/or mudflows/debris) on concrete territory. Analysis of many facts result in conclusion that we have the hard comparable/coincidence parameters under traditional conception for discussed events as an isolated/closed (river + rain) runoff-system. In contrast, the reasonable point of view does exist if we take into account the contribution of extra water source, which should be localized in river channel, i.e. functioning of open [(river + rain) + groundwater] flow-system has a principal meaning to understand the events occurrence. 3. The analysis and modeling for the events are carried out by us taking into account the following databases: (i) groundwater map dislocation, it resources and flow balance in studied areas, especially near the land surface being unstable in hydrological sense by many reasons, as well due to heavy rain
RESEARCH ON THE WATERPOWER COUPLING CHARACTER IN THE DISTRICT HEATING SYSTEMS
Institute of Scientific and Technical Information of China (English)
YUAN Liang
2004-01-01
In the paper, the concept of the heating network coupling is introduced. A mathematical modal of heating network in water power is established. The coupling degree of the heating network is also calculated trough the liquid increasing matrix
Institute of Scientific and Technical Information of China (English)
于艾清; 顾幸生
2008-01-01
Scheduling jobs on identical machines is a situation frequently encountered in various manufacturing