Common neighbours and the local-community-paradigm for topological link prediction in bipartite networks

Science.gov (United States)

Daminelli, Simone; Thomas, Josephine Maria; Durán, Claudio; Vittorio Cannistraci, Carlo

2015-11-01

Bipartite networks are powerful descriptions of complex systems characterized by two different classes of nodes and connections allowed only across but not within the two classes. Unveiling physical principles, building theories and suggesting physical models to predict bipartite links such as product-consumer connections in recommendation systems or drug-target interactions in molecular networks can provide priceless information to improve e-commerce or to accelerate pharmaceutical research. The prediction of nonobserved connections starting from those already present in the topology of a network is known as the link-prediction problem. It represents an important subject both in many-body interaction theory in physics and in new algorithms for applied tools in computer science. The rationale is that the existing connectivity structure of a network can suggest where new connections can appear with higher likelihood in an evolving network, or where nonobserved connections are missing in a partially known network. Surprisingly, current complex network theory presents a theoretical bottle-neck: a general framework for local-based link prediction directly in the bipartite domain is missing. Here, we overcome this theoretical obstacle and present a formal definition of common neighbour index and local-community-paradigm (LCP) for bipartite networks. As a consequence, we are able to introduce the first node-neighbourhood-based and LCP-based models for topological link prediction that utilize the bipartite domain. We performed link prediction evaluations in several networks of different size and of disparate origin, including technological, social and biological systems. Our models significantly improve topological prediction in many bipartite networks because they exploit local physical driving-forces that participate in the formation and organization of many real-world bipartite networks. Furthermore, we present a local-based formalism that allows to intuitively

Effects of the bipartite structure of a network on performance of recommenders

Science.gov (United States)

Wang, Qing-Xian; Li, Jian; Luo, Xin; Xu, Jian-Jun; Shang, Ming-Sheng

2018-02-01

Recommender systems aim to predict people's preferences for online items by analyzing their historical behaviors. A recommender can be modeled as a high-dimensional and sparse bipartite network, where the key issue is to understand the relation between the network structure and a recommender's performance. To address this issue, we choose three network characteristics, clustering coefficient, network density and user-item ratio, as the analyzing targets. For the cluster coefficient, we adopt the Degree-preserving rewiring algorithm to obtain a series of bipartite network with varying cluster coefficient, while the degree of user and item keep unchanged. Furthermore, five state-of-the-art recommenders are applied on two real datasets. The performances of recommenders are measured by both numerical and physical metrics. These results show that a recommender's performance is positively related to the clustering coefficient of a bipartite network. Meanwhile, higher density of a bipartite network can provide more accurate but less diverse or novel recommendations. Furthermore, the user-item ratio is positively correlated with the accuracy metrics but negatively correlated with the diverse and novel metrics.

Two classes of bipartite networks: nested biological and social systems.

Science.gov (United States)

Burgos, Enrique; Ceva, Horacio; Hernández, Laura; Perazzo, R P J; Devoto, Mariano; Medan, Diego

2008-10-01

Bipartite graphs have received some attention in the study of social networks and of biological mutualistic systems. A generalization of a previous model is presented, that evolves the topology of the graph in order to optimally account for a given contact preference rule between the two guilds of the network. As a result, social and biological graphs are classified as belonging to two clearly different classes. Projected graphs, linking the agents of only one guild, are obtained from the original bipartite graph. The corresponding evolution of its statistical properties is also studied. An example of a biological mutualistic network is analyzed in detail, and it is found that the model provides a very good fitting of all the main statistical features. The model also provides a proper qualitative description of the same features observed in social webs, suggesting the possible reasons underlying the difference in the organization of these two kinds of bipartite networks.

Introduction into bi-partite networks in python

OpenAIRE

Kasberger, Stefan

2016-01-01

This essay and the related computation delivers a comprehensive introduction into the concept of bipartite networks, a class of networks whose nodes are divided into two sets and only the connection between two nodes in different sets is allowed (Easley and Kleinberg, 2010). The analysis and visualization is done in the programming language Python and offers easy to understand first steps in both fields, network analyses and python programming. As data a collaboration network of github users ...

Inferring monopartite projections of bipartite networks: an entropy-based approach

Science.gov (United States)

Saracco, Fabio; Straka, Mika J.; Di Clemente, Riccardo; Gabrielli, Andrea; Caldarelli, Guido; Squartini, Tiziano

2017-05-01

Bipartite networks are currently regarded as providing a major insight into the organization of many real-world systems, unveiling the mechanisms driving the interactions occurring between distinct groups of nodes. One of the most important issues encountered when modeling bipartite networks is devising a way to obtain a (monopartite) projection on the layer of interest, which preserves as much as possible the information encoded into the original bipartite structure. In the present paper we propose an algorithm to obtain statistically-validated projections of bipartite networks, according to which any two nodes sharing a statistically-significant number of neighbors are linked. Since assessing the statistical significance of nodes similarity requires a proper statistical benchmark, here we consider a set of four null models, defined within the exponential random graph framework. Our algorithm outputs a matrix of link-specific p-values, from which a validated projection is straightforwardly obtainable, upon running a multiple hypothesis testing procedure. Finally, we test our method on an economic network (i.e. the countries-products World Trade Web representation) and a social network (i.e. MovieLens, collecting the users’ ratings of a list of movies). In both cases non-trivial communities are detected: while projecting the World Trade Web on the countries layer reveals modules of similarly-industrialized nations, projecting it on the products layer allows communities characterized by an increasing level of complexity to be detected; in the second case, projecting MovieLens on the films layer allows clusters of movies whose affinity cannot be fully accounted for by genre similarity to be individuated.

A simple model of bipartite cooperation for ecological and organizational networks.

Science.gov (United States)

Saavedra, Serguei; Reed-Tsochas, Felix; Uzzi, Brian

2009-01-22

In theoretical ecology, simple stochastic models that satisfy two basic conditions about the distribution of niche values and feeding ranges have proved successful in reproducing the overall structural properties of real food webs, using species richness and connectance as the only input parameters. Recently, more detailed models have incorporated higher levels of constraint in order to reproduce the actual links observed in real food webs. Here, building on previous stochastic models of consumer-resource interactions between species, we propose a highly parsimonious model that can reproduce the overall bipartite structure of cooperative partner-partner interactions, as exemplified by plant-animal mutualistic networks. Our stochastic model of bipartite cooperation uses simple specialization and interaction rules, and only requires three empirical input parameters. We test the bipartite cooperation model on ten large pollination data sets that have been compiled in the literature, and find that it successfully replicates the degree distribution, nestedness and modularity of the empirical networks. These properties are regarded as key to understanding cooperation in mutualistic networks. We also apply our model to an extensive data set of two classes of company engaged in joint production in the garment industry. Using the same metrics, we find that the network of manufacturer-contractor interactions exhibits similar structural patterns to plant-animal pollination networks. This surprising correspondence between ecological and organizational networks suggests that the simple rules of cooperation that generate bipartite networks may be generic, and could prove relevant in many different domains, ranging from biological systems to human society.

Chimera states in bipartite networks of FitzHugh-Nagumo oscillators

Science.gov (United States)

Wu, Zhi-Min; Cheng, Hong-Yan; Feng, Yuee; Li, Hai-Hong; Dai, Qiong-Lin; Yang, Jun-Zhong

2018-04-01

Chimera states consisting of spatially coherent and incoherent domains have been observed in different topologies such as rings, spheres, and complex networks. In this paper, we investigate bipartite networks of nonlocally coupled FitzHugh-Nagumo (FHN) oscillators in which the units are allocated evenly to two layers, and FHN units interact with each other only when they are in different layers. We report the existence of chimera states in bipartite networks. Owing to the interplay between chimera states in the two layers, many types of chimera states such as in-phase chimera states, antiphase chimera states, and out-of-phase chimera states are classified. Stability diagrams of several typical chimera states in the coupling strength-coupling radius plane, which show strong multistability of chimera states, are explored.

Effect of the social influence on topological properties of user-object bipartite networks

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Liu, Jian-Guo; Hu, Zhaolong; Guo, Qiang

2013-11-01

Social influence plays an important role in analyzing online users' collective behaviors [Salganik et al., Science 311, 854 (2006)]. However, the effect of the social influence from the viewpoint of theoretical model is missing. In this paper, by taking into account the social influence and users' preferences, we develop a theoretical model to analyze the topological properties of user-object bipartite networks, including the degree distribution, average nearest neighbor degree and the bipartite clustering coefficient, as well as topological properties of the original user-object networks and their unipartite projections. According to the users' preferences and the global ranking effect, we analyze the theoretical results for two benchmark data sets, Amazon and Bookcrossing, which are approximately consistent with the empirical results. This work suggests that this model is feasible to analyze topological properties of bipartite networks in terms of the social influence and the users' preferences.

Enhanced capital-asset pricing model for the reconstruction of bipartite financial networks

Science.gov (United States)

Squartini, Tiziano; Almog, Assaf; Caldarelli, Guido; van Lelyveld, Iman; Garlaschelli, Diego; Cimini, Giulio

2017-09-01

Reconstructing patterns of interconnections from partial information is one of the most important issues in the statistical physics of complex networks. A paramount example is provided by financial networks. In fact, the spreading and amplification of financial distress in capital markets are strongly affected by the interconnections among financial institutions. Yet, while the aggregate balance sheets of institutions are publicly disclosed, information on single positions is mostly confidential and, as such, unavailable. Standard approaches to reconstruct the network of financial interconnection produce unrealistically dense topologies, leading to a biased estimation of systemic risk. Moreover, reconstruction techniques are generally designed for monopartite networks of bilateral exposures between financial institutions, thus failing in reproducing bipartite networks of security holdings (e.g., investment portfolios). Here we propose a reconstruction method based on constrained entropy maximization, tailored for bipartite financial networks. Such a procedure enhances the traditional capital-asset pricing model (CAPM) and allows us to reproduce the correct topology of the network. We test this enhanced CAPM (ECAPM) method on a dataset, collected by the European Central Bank, of detailed security holdings of European institutional sectors over a period of six years (2009-2015). Our approach outperforms the traditional CAPM and the recently proposed maximum-entropy CAPM both in reproducing the network topology and in estimating systemic risk due to fire sales spillovers. In general, ECAPM can be applied to the whole class of weighted bipartite networks described by the fitness model.

Information Filtering via Clustering Coefficients of User-Object Bipartite Networks

Science.gov (United States)

Guo, Qiang; Leng, Rui; Shi, Kerui; Liu, Jian-Guo

The clustering coefficient of user-object bipartite networks is presented to evaluate the overlap percentage of neighbors rating lists, which could be used to measure interest correlations among neighbor sets. The collaborative filtering (CF) information filtering algorithm evaluates a given user's interests in terms of his/her friends' opinions, which has become one of the most successful technologies for recommender systems. In this paper, different from the object clustering coefficient, users' clustering coefficients of user-object bipartite networks are introduced to improve the user similarity measurement. Numerical results for MovieLens and Netflix data sets show that users' clustering effects could enhance the algorithm performance. For MovieLens data set, the algorithmic accuracy, measured by the average ranking score, can be improved by 12.0% and the diversity could be improved by 18.2% and reach 0.649 when the recommendation list equals to 50. For Netflix data set, the accuracy could be improved by 14.5% at the optimal case and the popularity could be reduced by 13.4% comparing with the standard CF algorithm. Finally, we investigate the sparsity effect on the performance. This work indicates the user clustering coefficients is an effective factor to measure the user similarity, meanwhile statistical properties of user-object bipartite networks should be investigated to estimate users' tastes.

Uncovering collective listening habits and music genres in bipartite networks

Science.gov (United States)

Lambiotte, R.; Ausloos, M.

2005-12-01

In this paper, we analyze web-downloaded data on people sharing their music library, that we use as their individual musical signatures. The system is represented by a bipartite network, nodes being the music groups and the listeners. Music groups’ audience size behaves like a power law, but the individual music library size is an exponential with deviations at small values. In order to extract structures from the network, we focus on correlation matrices, that we filter by removing the least correlated links. This percolation idea-based method reveals the emergence of social communities and music genres, that are visualized by a branching representation. Evidence of collective listening habits that do not fit the neat usual genres defined by the music industry indicates an alternative way of classifying listeners and music groups. The structure of the network is also studied by a more refined method, based upon a random walk exploration of its properties. Finally, a personal identification-community imitation model for growing bipartite networks is outlined, following Potts ingredients. Simulation results do reproduce quite well the empirical data.

Bipartite quantum states and random complex networks

International Nuclear Information System (INIS)

Garnerone, Silvano; Zanardi, Paolo; Giorda, Paolo

2012-01-01

We introduce a mapping between graphs and pure quantum bipartite states and show that the associated entanglement entropy conveys non-trivial information about the structure of the graph. Our primary goal is to investigate the family of random graphs known as complex networks. In the case of classical random graphs, we derive an analytic expression for the averaged entanglement entropy S-bar while for general complex networks we rely on numerics. For a large number of nodes n we find a scaling S-bar ∼c log n +g e where both the prefactor c and the sub-leading O(1) term g e are characteristic of the different classes of complex networks. In particular, g e encodes topological features of the graphs and is named network topological entropy. Our results suggest that quantum entanglement may provide a powerful tool for the analysis of large complex networks with non-trivial topological properties. (paper)

Effect of attachment strategies on bipartite networks

DEFF Research Database (Denmark)

Ganguly, N.; Saha, S.; Maiti, A.

2013-01-01

Bipartite systems show remarkable variations in their topological asymptotic properties, e. g., in their degree distribution. Such variations depend on the underlying growth dynamics. A scenario of particular importance is when the two partitions of the bipartite structure do not grow at an equal...

Balanced Bipartite Graph Based Register Allocation for Network Processors in Mobile and Wireless Networks

Directory of Open Access Journals (Sweden)

Feilong Tang

2010-01-01

Full Text Available Mobile and wireless networks are the integrant infrastructure of mobile and pervasive computing that aims at providing transparent and preferred information and services for people anytime anywhere. In such environments, end-to-end network bandwidth is crucial to improve user's transparent experience when providing on-demand services such as mobile video playing. As a result, powerful computing power is required for networked nodes, especially for routers. General-purpose processors cannot meet such requirements due to their limited processing ability, and poor programmability and scalability. Intel's network processor IXP is specially designed for fast packet processing to achieve a broad bandwidth. IXP provides a large number of registers to reduce the number of memory accesses. Registers in an IXP are physically partitioned as two banks so that two source operands in an instruction have to come from the two banks respectively, which makes the IXP register allocation tricky and different from conventional ones. In this paper, we investigate an approach for efficiently generating balanced bipartite graph and register allocation algorithms for the dual-bank register allocation in IXPs. The paper presents a graph uniform 2-way partition algorithm (FPT, which provides an optimal solution to the graph partition, and a heuristic algorithm for generating balanced bipartite graph. Finally, we design a framework for IXP register allocation. Experimental results demonstrate the framework and the algorithms are efficient in register allocation for IXP network processors.

SibRank: Signed bipartite network analysis for neighbor-based collaborative ranking

Science.gov (United States)

Shams, Bita; Haratizadeh, Saman

2016-09-01

Collaborative ranking is an emerging field of recommender systems that utilizes users' preference data rather than rating values. Unfortunately, neighbor-based collaborative ranking has gained little attention despite its more flexibility and justifiability. This paper proposes a novel framework, called SibRank that seeks to improve the state of the art neighbor-based collaborative ranking methods. SibRank represents users' preferences as a signed bipartite network, and finds similar users, through a novel personalized ranking algorithm in signed networks.

A mathematical model for generating bipartite graphs and its application to protein networks

International Nuclear Information System (INIS)

Nacher, J C; Ochiai, T; Hayashida, M; Akutsu, T

2009-01-01

Complex systems arise in many different contexts from large communication systems and transportation infrastructures to molecular biology. Most of these systems can be organized into networks composed of nodes and interacting edges. Here, we present a theoretical model that constructs bipartite networks with the particular feature that the degree distribution can be tuned depending on the probability rate of fundamental processes. We then use this model to investigate protein-domain networks. A protein can be composed of up to hundreds of domains. Each domain represents a conserved sequence segment with specific functional tasks. We analyze the distribution of domains in Homo sapiens and Arabidopsis thaliana organisms and the statistical analysis shows that while (a) the number of domain types shared by k proteins exhibits a power-law distribution, (b) the number of proteins composed of k types of domains decays as an exponential distribution. The proposed mathematical model generates bipartite graphs and predicts the emergence of this mixing of (a) power-law and (b) exponential distributions. Our theoretical and computational results show that this model requires (1) growth process and (2) copy mechanism.

A mathematical model for generating bipartite graphs and its application to protein networks

Science.gov (United States)

Nacher, J. C.; Ochiai, T.; Hayashida, M.; Akutsu, T.

2009-12-01

Complex systems arise in many different contexts from large communication systems and transportation infrastructures to molecular biology. Most of these systems can be organized into networks composed of nodes and interacting edges. Here, we present a theoretical model that constructs bipartite networks with the particular feature that the degree distribution can be tuned depending on the probability rate of fundamental processes. We then use this model to investigate protein-domain networks. A protein can be composed of up to hundreds of domains. Each domain represents a conserved sequence segment with specific functional tasks. We analyze the distribution of domains in Homo sapiens and Arabidopsis thaliana organisms and the statistical analysis shows that while (a) the number of domain types shared by k proteins exhibits a power-law distribution, (b) the number of proteins composed of k types of domains decays as an exponential distribution. The proposed mathematical model generates bipartite graphs and predicts the emergence of this mixing of (a) power-law and (b) exponential distributions. Our theoretical and computational results show that this model requires (1) growth process and (2) copy mechanism.

A mathematical model for generating bipartite graphs and its application to protein networks

Energy Technology Data Exchange (ETDEWEB)

Nacher, J C [Department of Complex Systems, Future University-Hakodate (Japan); Ochiai, T [Faculty of Engineering, Toyama Prefectural University (Japan); Hayashida, M; Akutsu, T [Bioinformatics Center, Institute for Chemical Research, Kyoto University (Japan)

2009-12-04

Complex systems arise in many different contexts from large communication systems and transportation infrastructures to molecular biology. Most of these systems can be organized into networks composed of nodes and interacting edges. Here, we present a theoretical model that constructs bipartite networks with the particular feature that the degree distribution can be tuned depending on the probability rate of fundamental processes. We then use this model to investigate protein-domain networks. A protein can be composed of up to hundreds of domains. Each domain represents a conserved sequence segment with specific functional tasks. We analyze the distribution of domains in Homo sapiens and Arabidopsis thaliana organisms and the statistical analysis shows that while (a) the number of domain types shared by k proteins exhibits a power-law distribution, (b) the number of proteins composed of k types of domains decays as an exponential distribution. The proposed mathematical model generates bipartite graphs and predicts the emergence of this mixing of (a) power-law and (b) exponential distributions. Our theoretical and computational results show that this model requires (1) growth process and (2) copy mechanism.

Bipartite Networks of Wikipediaʼs Articles and Authors: a Meso-level Approach

DEFF Research Database (Denmark)

Jesus, Rut; Hansen-Schwartz, Martin; Jørgensen, Sune Lehmann

2009-01-01

This exploratory study investigates the bipartite network of articles linked by common editors in Wikipedia, 'The Free Encyclopedia that Anyone Can Edit'. We use the articles in the categories (to depth three) of Physics and Philosophy and extract and focus on significant editors (at least 7 or 10...

Bipartite networks improve understanding of effects of waterbody size and angling method on angler–fish interactions

Science.gov (United States)

Chizinski, Christopher J.; Martin, Dustin R.; Shizuka, Daizaburo; Pope, Kevin L.

2018-01-01

Networks used to study interactions could provide insights to fisheries. We compiled data from 27 297 interviews of anglers across waterbodies that ranged in size from 1 to 12 113 ha. Catch rates of fish species among anglers grouped by species targeted generally differed between angling methods (bank or boat). We constructed angler–catch bipartite networks (angling method specific) between anglers and fish and measured several network metrics. There was considerable variation in networks among waterbodies, with multiple metrics influenced by waterbody size. Number of species-targeting angler groups and number of fish species caught increased with increasing waterbody size. Mean number of links for species-targeting angler groups and fish species caught also increased with waterbody size. Connectance (realized proportion of possible links) of angler–catch interaction networks decreased slower for boat anglers than for bank anglers with increasing waterbody size. Network specialization (deviation of number of interactions from expected) was not significantly related to waterbody size or angling methods. Application of bipartite networks in fishery science requires careful interpretation of outputs, especially considering the numerous confounding factors prevalent in recreational fisheries.

Identifying online user reputation of user-object bipartite networks

Science.gov (United States)

Liu, Xiao-Lu; Liu, Jian-Guo; Yang, Kai; Guo, Qiang; Han, Jing-Ti

2017-02-01

Identifying online user reputation based on the rating information of the user-object bipartite networks is important for understanding online user collective behaviors. Based on the Bayesian analysis, we present a parameter-free algorithm for ranking online user reputation, where the user reputation is calculated based on the probability that their ratings are consistent with the main part of all user opinions. The experimental results show that the AUC values of the presented algorithm could reach 0.8929 and 0.8483 for the MovieLens and Netflix data sets, respectively, which is better than the results generated by the CR and IARR methods. Furthermore, the experimental results for different user groups indicate that the presented algorithm outperforms the iterative ranking methods in both ranking accuracy and computation complexity. Moreover, the results for the synthetic networks show that the computation complexity of the presented algorithm is a linear function of the network size, which suggests that the presented algorithm is very effective and efficient for the large scale dynamic online systems.

Bank-firm credit network in Japan: an analysis of a bipartite network.

Science.gov (United States)

Marotta, Luca; Miccichè, Salvatore; Fujiwara, Yoshi; Iyetomi, Hiroshi; Aoyama, Hideaki; Gallegati, Mauro; Mantegna, Rosario N

2015-01-01

We investigate the networked nature of the Japanese credit market. Our investigation is performed with tools of network science. In our investigation we perform community detection with an algorithm which is identifying communities composed of both banks and firms. We show that the communities obtained by directly working on the bipartite network carry information about the networked nature of the Japanese credit market. Our analysis is performed for each calendar year during the time period from 1980 to 2011. To investigate the time evolution of the networked structure of the credit market we introduce a new statistical method to track the time evolution of detected communities. We then characterize the time evolution of communities by detecting for each time evolving set of communities the over-expression of attributes of firms and banks. Specifically, we consider as attributes the economic sector and the geographical location of firms and the type of banks. In our 32-year-long analysis we detect a persistence of the over-expression of attributes of communities of banks and firms together with a slow dynamic of changes from some specific attributes to new ones. Our empirical observations show that the credit market in Japan is a networked market where the type of banks, geographical location of firms and banks, and economic sector of the firm play a role in shaping the credit relationships between banks and firms.

The Random Walk Model Based on Bipartite Network

Directory of Open Access Journals (Sweden)

Zhang Man-Dun

2016-01-01

Full Text Available With the continuing development of the electronic commerce and growth of network information, there is a growing possibility for citizens to be confused by the information. Though the traditional technology of information retrieval have the ability to relieve the overload of information in some extent, it can not offer a targeted personality service based on user’s interests and activities. In this context, the recommendation algorithm arose. In this paper, on the basis of conventional recommendation, we studied the scheme of random walk based on bipartite network and the application of it. We put forward a similarity measurement based on implicit feedback. In this method, a uneven character vector is imported(the weight of item in the system. We put forward a improved random walk pattern which make use of partial or incomplete neighbor information to create recommendation information. In the end, there is an experiment in the real data set, the recommendation accuracy and practicality are improved. We promise the reality of the result of the experiment

Modeling the spread of vector-borne diseases on bipartite networks.

Directory of Open Access Journals (Sweden)

Donal Bisanzio

Full Text Available BACKGROUND: Vector-borne diseases for which transmission occurs exclusively between vectors and hosts can be modeled as spreading on a bipartite network. METHODOLOGY/PRINCIPAL FINDINGS: In such models the spreading of the disease strongly depends on the degree distribution of the two classes of nodes. It is sufficient for one of the classes to have a scale-free degree distribution with a slow enough decay for the network to have asymptotically vanishing epidemic threshold. Data on the distribution of Ixodes ricinus ticks on mice and lizards from two independent studies are well described by a scale-free distribution compatible with an asymptotically vanishing epidemic threshold. The commonly used negative binomial, instead, cannot describe the right tail of the empirical distribution. CONCLUSIONS/SIGNIFICANCE: The extreme aggregation of vectors on hosts, described by the power-law decay of the degree distribution, makes the epidemic threshold decrease with the size of the network and vanish asymptotically.

Non-parametric co-clustering of large scale sparse bipartite networks on the GPU

DEFF Research Database (Denmark)

Hansen, Toke Jansen; Mørup, Morten; Hansen, Lars Kai

2011-01-01

of row and column clusters from a hypothesis space of an infinite number of clusters. To reach large scale applications of co-clustering we exploit that parameter inference for co-clustering is well suited for parallel computing. We develop a generic GPU framework for efficient inference on large scale...... sparse bipartite networks and achieve a speedup of two orders of magnitude compared to estimation based on conventional CPUs. In terms of scalability we find for networks with more than 100 million links that reliable inference can be achieved in less than an hour on a single GPU. To efficiently manage...

Bank-Firm Credit Network in Japan: An Analysis of a Bipartite Network

Science.gov (United States)

Marotta, Luca; Miccichè, Salvatore; Fujiwara, Yoshi; Iyetomi, Hiroshi; Aoyama, Hideaki; Gallegati, Mauro; Mantegna, Rosario N.

2015-01-01

We investigate the networked nature of the Japanese credit market. Our investigation is performed with tools of network science. In our investigation we perform community detection with an algorithm which is identifying communities composed of both banks and firms. We show that the communities obtained by directly working on the bipartite network carry information about the networked nature of the Japanese credit market. Our analysis is performed for each calendar year during the time period from 1980 to 2011. To investigate the time evolution of the networked structure of the credit market we introduce a new statistical method to track the time evolution of detected communities. We then characterize the time evolution of communities by detecting for each time evolving set of communities the over-expression of attributes of firms and banks. Specifically, we consider as attributes the economic sector and the geographical location of firms and the type of banks. In our 32-year-long analysis we detect a persistence of the over-expression of attributes of communities of banks and firms together with a slow dynamic of changes from some specific attributes to new ones. Our empirical observations show that the credit market in Japan is a networked market where the type of banks, geographical location of firms and banks, and economic sector of the firm play a role in shaping the credit relationships between banks and firms. PMID:25933413

Response to defects in multipartite and bipartite entanglement of isotropic quantum spin networks

Science.gov (United States)

Roy, Sudipto Singha; Dhar, Himadri Shekhar; Rakshit, Debraj; SenDe, Aditi; Sen, Ujjwal

2018-05-01

Quantum networks are an integral component in performing efficient computation and communication tasks that are not accessible using classical systems. A key aspect in designing an effective and scalable quantum network is generating entanglement between its nodes, which is robust against defects in the network. We consider an isotropic quantum network of spin-1/2 particles with a finite fraction of defects, where the corresponding wave function of the network is rotationally invariant under the action of local unitaries. By using quantum information-theoretic concepts like strong subadditivity of von Neumann entropy and approximate quantum telecloning, we prove analytically that in the presence of defects, caused by loss of a finite fraction of spins, the network, composed of a fixed numbers of lattice sites, sustains genuine multisite entanglement and at the same time may exhibit finite moderate-range bipartite entanglement, in contrast to the network with no defects.

Epidemic spread in bipartite network by considering risk awareness

Science.gov (United States)

Han, She; Sun, Mei; Ampimah, Benjamin Chris; Han, Dun

2018-02-01

Human awareness plays an important role in the spread of infectious diseases and the control of propagation patterns. Exploring the interplay between human awareness and epidemic spreading is a topic that has been receiving increasing attention. Considering the fact, some well-known diseases only spread between different species we propose a theoretical analysis of the Susceptible-Infected-Susceptible (SIS) epidemic spread from the perspective of bipartite network and risk aversion. Using mean field theory, the epidemic threshold is calculated theoretically. Simulation results are consistent with the proposed analytic model. The results show that, the final infection density is negative linear with the value of individuals' risk awareness. Therefore, the epidemic spread could be effectively suppressed by improving individuals' risk awareness.

Competition for popularity in bipartite networks

Science.gov (United States)

Beguerisse Díaz, Mariano; Porter, Mason A.; Onnela, Jukka-Pekka

2010-12-01

We present a dynamical model for rewiring and attachment in bipartite networks. Edges are placed between nodes that belong to catalogs that can either be fixed in size or growing in size. The model is motivated by an empirical study of data from the video rental service Netflix, which invites its users to give ratings to the videos available in its catalog. We find that the distribution of the number of ratings given by users and that of the number of ratings received by videos both follow a power law with an exponential cutoff. We also examine the activity patterns of Netflix users and find bursts of intense video-rating activity followed by long periods of inactivity. We derive ordinary differential equations to model the acquisition of edges by the nodes over time and obtain the corresponding time-dependent degree distributions. We then compare our results with the Netflix data and find good agreement. We conclude with a discussion of how catalog models can be used to study systems in which agents are forced to choose, rate, or prioritize their interactions from a large set of options.

A bipartite fitness model for online music streaming services

Science.gov (United States)

Pongnumkul, Suchit; Motohashi, Kazuyuki

2018-01-01

This paper proposes an evolution model and an analysis of the behavior of music consumers on online music streaming services. While previous studies have observed power-law degree distributions of usage in online music streaming services, the underlying behavior of users has not been well understood. Users and songs can be described using a bipartite network where an edge exists between a user node and a song node when the user has listened that song. The growth mechanism of bipartite networks has been used to understand the evolution of online bipartite networks Zhang et al. (2013). Existing bipartite models are based on a preferential attachment mechanism László Barabási and Albert (1999) in which the probability that a user listens to a song is proportional to its current popularity. This mechanism does not allow for two types of real world phenomena. First, a newly released song with high quality sometimes quickly gains popularity. Second, the popularity of songs normally decreases as time goes by. Therefore, this paper proposes a new model that is more suitable for online music services by adding fitness and aging functions to the song nodes of the bipartite network proposed by Zhang et al. (2013). Theoretical analyses are performed for the degree distribution of songs. Empirical data from an online streaming service, Last.fm, are used to confirm the degree distribution of the object nodes. Simulation results show improvements from a previous model. Finally, to illustrate the application of the proposed model, a simplified royalty cost model for online music services is used to demonstrate how the changes in the proposed parameters can affect the costs for online music streaming providers. Managerial implications are also discussed.

Localization in random bipartite graphs: Numerical and empirical study

Science.gov (United States)

Slanina, František

2017-05-01

We investigate adjacency matrices of bipartite graphs with a power-law degree distribution. Motivation for this study is twofold: first, vibrational states in granular matter and jammed sphere packings; second, graphs encoding social interaction, especially electronic commerce. We establish the position of the mobility edge and show that it strongly depends on the power in the degree distribution and on the ratio of the sizes of the two parts of the bipartite graph. At the jamming threshold, where the two parts have the same size, localization vanishes. We found that the multifractal spectrum is nontrivial in the delocalized phase, but still near the mobility edge. We also study an empirical bipartite graph, namely, the Amazon reviewer-item network. We found that in this specific graph the mobility edge disappears, and we draw a conclusion from this fact regarding earlier empirical studies of the Amazon network.

MRI findings in bipartite patella

International Nuclear Information System (INIS)

Kavanagh, Eoin C.; Zoga, Adam; Omar, Imran; Ford, Stephanie; Eustace, Stephen; Schweitzer, Mark

2007-01-01

Bipartite patella is a known cause of anterior knee pain. Our purpose was to detail the magnetic resonance imaging (MRI) features of bipartite patella in a retrospective cohort of patients imaged at our institution. MRI exams from 53 patients with findings of bipartite patella were evaluated to assess for the presence of bone marrow edema within the bipartite fragment and for the presence of abnormal signal across the synchondrosis or pseudarthrosis. Any other significant knee pathology seen at MRI was also recorded. We also reviewed 400 consecutive knee MRI studies to determine the MRI prevalence of bipartite patella. Of the 53 patients with bipartite patella 40 (75%) were male; 35 (66%) had edema within the bipartite fragment. Of the 18 with no edema an alternative explanation for knee pain was found in 13 (72%). Edema within the bipartite fragment was the sole finding in 26 of 53 (49%) patients. Bipartite patella was seen in 3 (0.7%) of 400 patients. In patients with bipartite patella at knee MRI, bone marrow edema within the bipartite fragment was the sole finding on knee MRI in almost half of the patients in our series. (orig.)

Emergent bipartiteness in a society of knights and knaves

International Nuclear Information System (INIS)

Del Genio, C I; Gross, T

2011-01-01

We propose a simple model of a social network based on the so-called knights-and-knaves puzzles. The model describes the formation of networks between two classes of agents where links are formed by agents introducing their neighbors to others of their own class. We show that if the proportion of knights and knaves is within a certain range, the network self-organizes to a perfectly bipartite state. However, if the excess of one of the two classes is greater than a threshold value, bipartiteness is not observed. We offer a detailed theoretical analysis of the behavior of the model, investigate its behavior in the thermodynamic limit and argue that it provides a simple example of a topology-driven model whose behavior is strongly reminiscent of first-order phase transitions far from equilibrium. (paper)

A quantum logic network for implementing optimal symmetric universal and phase-covariant telecloning of a bipartite entangled state

International Nuclear Information System (INIS)

Meng Fanyu; Zhu Aidong

2008-01-01

A quantum logic network to implement quantum telecloning is presented in this paper. The network includes two parts: the first part is used to create the telecloning channel and the second part to teleport the state. It can be used not only to implement universal telecloning for a bipartite entangled state which is completely unknown, but also to implement the phase-covariant telecloning for one that is partially known. Furthermore, the network can also be used to construct a tele-triplicator. It can easily be implemented in experiment because only single- and two-qubit operations are used in the network.

Rendezvous effects in the diffusion process on bipartite metapopulation networks.

Science.gov (United States)

Cao, Lang; Li, Xun; Wang, Bing; Aihara, Kazuyuki

2011-10-01

Epidemic outbreaks have been shown to be closely related to the rendezvous-induced transmission of infection, which is caused by casual contact with infected individuals in public gatherings. To investigate rendezvous effects in the spread of infectious diseases, we propose an epidemic model on metapopulation networks bipartite-divided into two sets of location and rendezvous nodes. At a given transition rate γ(kk')(p), each individual transfers from location k to rendezvous p (where rendezvous-induced disease incidence occurs) and thereafter moves to location k'. We find that the eigenstructure of a transition-rate-dependent matrix determines the epidemic threshold condition. Both analytical and numerical results show that rendezvous-induced transmission accelerates the progress of infectious diseases, implying the significance of outbreak control measures including prevention of public gatherings or decentralization of a large-scale rendezvous into downsized ones.

Bipartite consensus for multi-agent systems with antagonistic interactions and communication delays

Science.gov (United States)

Guo, Xing; Lu, Jianquan; Alsaedi, Ahmed; Alsaadi, Fuad E.

2018-04-01

This paper studies the consensus problems over signed digraphs with arbitrary finite communication delays. For the considered system, the information flow is directed and only locally delayed information can be used for each node. We derive that bipartite consensus of this system can be realized when the associated signed digraph is strongly connected. Furthermore, for structurally balanced networks, this paper studies the pinning partite consensus for the considered system. we design a pinning scheme to pin any one agent in the signed network, and obtain that the network achieves pinning bipartite consensus with any initial conditions. Finally, two examples are provided to demonstrate the effectiveness of our main results.

Dynamics of bloggers’ communities: Bipartite networks from empirical data and agent-based modeling

Science.gov (United States)

Mitrović, Marija; Tadić, Bosiljka

2012-11-01

We present an analysis of the empirical data and the agent-based modeling of the emotional behavior of users on the Web portals where the user interaction is mediated by posted comments, like Blogs and Diggs. We consider the dataset of discussion-driven popular Diggs, in which all comments are screened by machine-learning emotion detection in the text, to determine positive and negative valence (attractiveness and aversiveness) of each comment. By mapping the data onto a suitable bipartite network, we perform an analysis of the network topology and the related time-series of the emotional comments. The agent-based model is then introduced to simulate the dynamics and to capture the emergence of the emotional behaviors and communities. The agents are linked to posts on a bipartite network, whose structure evolves through their actions on the posts. The emotional states (arousal and valence) of each agent fluctuate in time, subject to the current contents of the posts to which the agent is exposed. By an agent’s action on a post its current emotions are transferred to the post. The model rules and the key parameters are inferred from the considered empirical data to ensure their realistic values and mutual consistency. The model assumes that the emotional arousal over posts drives the agent’s action. The simulations are preformed for the case of constant flux of agents and the results are analyzed in full analogy with the empirical data. The main conclusions are that the emotion-driven dynamics leads to long-range temporal correlations and emergent networks with community structure, that are comparable with the ones in the empirical system of popular posts. In view of pure emotion-driven agents actions, this type of comparisons provide a quantitative measure for the role of emotions in the dynamics on real blogs. Furthermore, the model reveals the underlying mechanisms which relate the post popularity with the emotion dynamics and the prevalence of negative

Beyond ectomycorrhizal bipartite networks: projected networks demonstrate contrasted patterns between early- and late-successional plants in Corsica.

Directory of Open Access Journals (Sweden)

Adrien eTaudiere

2015-10-01

Full Text Available The ectomycorrhizal (ECM symbiosis connects mutualistic plants and fungal species into bipartite networks. While links between one focal ECM plant and its fungal symbionts have been widely documented, systemic views of ECM networks are lacking, in particular, concerning the ability of fungal species to mediate indirect ecological interactions between ECM plant species (projected-ECM networks. We assembled a large dataset of plant-fungi associations at the species level and at the scale of Corsica using molecular data and unambiguously host-assigned records to: (i examine the correlation between the number of fungal symbionts of a plant species and the average specialization of these fungal species, (ii explore the structure of the plant-plant projected network and (iii compare plant association patterns in regard to their position along the ecological succession. Our analysis reveals no trade-off between specialization of plants and specialization of their partners and a saturation of the plant projected network. Moreover, there is a significantly lower-than-expected sharing of partners between early- and late-successional plant species, with fewer fungal partners for early-successional ones and similar average specialization of symbionts of early- and late-successional plants. Our work paves the way for ecological readings of Mediterranean landscapes that include the astonishing diversity of below-ground interactions.

A Bipartite Network-based Method for Prediction of Long Non-coding RNA–protein Interactions

Directory of Open Access Journals (Sweden)

Mengqu Ge

2016-02-01

Full Text Available As one large class of non-coding RNAs (ncRNAs, long ncRNAs (lncRNAs have gained considerable attention in recent years. Mutations and dysfunction of lncRNAs have been implicated in human disorders. Many lncRNAs exert their effects through interactions with the corresponding RNA-binding proteins. Several computational approaches have been developed, but only few are able to perform the prediction of these interactions from a network-based point of view. Here, we introduce a computational method named lncRNA–protein bipartite network inference (LPBNI. LPBNI aims to identify potential lncRNA–interacting proteins, by making full use of the known lncRNA–protein interactions. Leave-one-out cross validation (LOOCV test shows that LPBNI significantly outperforms other network-based methods, including random walk (RWR and protein-based collaborative filtering (ProCF. Furthermore, a case study was performed to demonstrate the performance of LPBNI using real data in predicting potential lncRNA–interacting proteins.

Bipartite Graphs as Models of Population Structures in Evolutionary Multiplayer Games

Science.gov (United States)

Peña, Jorge; Rochat, Yannick

2012-01-01

By combining evolutionary game theory and graph theory, “games on graphs” study the evolutionary dynamics of frequency-dependent selection in population structures modeled as geographical or social networks. Networks are usually represented by means of unipartite graphs, and social interactions by two-person games such as the famous prisoner’s dilemma. Unipartite graphs have also been used for modeling interactions going beyond pairwise interactions. In this paper, we argue that bipartite graphs are a better alternative to unipartite graphs for describing population structures in evolutionary multiplayer games. To illustrate this point, we make use of bipartite graphs to investigate, by means of computer simulations, the evolution of cooperation under the conventional and the distributed N-person prisoner’s dilemma. We show that several implicit assumptions arising from the standard approach based on unipartite graphs (such as the definition of replacement neighborhoods, the intertwining of individual and group diversity, and the large overlap of interaction neighborhoods) can have a large impact on the resulting evolutionary dynamics. Our work provides a clear example of the importance of construction procedures in games on graphs, of the suitability of bigraphs and hypergraphs for computational modeling, and of the importance of concepts from social network analysis such as centrality, centralization and bipartite clustering for the understanding of dynamical processes occurring on networked population structures. PMID:22970237

Identifying the Gene Signatures from Gene-Pathway Bipartite Network Guarantees the Robust Model Performance on Predicting the Cancer Prognosis

Directory of Open Access Journals (Sweden)

Li He

2014-01-01

Full Text Available For the purpose of improving the prediction of cancer prognosis in the clinical researches, various algorithms have been developed to construct the predictive models with the gene signatures detected by DNA microarrays. Due to the heterogeneity of the clinical samples, the list of differentially expressed genes (DEGs generated by the statistical methods or the machine learning algorithms often involves a number of false positive genes, which are not associated with the phenotypic differences between the compared clinical conditions, and subsequently impacts the reliability of the predictive models. In this study, we proposed a strategy, which combined the statistical algorithm with the gene-pathway bipartite networks, to generate the reliable lists of cancer-related DEGs and constructed the models by using support vector machine for predicting the prognosis of three types of cancers, namely, breast cancer, acute myeloma leukemia, and glioblastoma. Our results demonstrated that, combined with the gene-pathway bipartite networks, our proposed strategy can efficiently generate the reliable cancer-related DEG lists for constructing the predictive models. In addition, the model performance in the swap analysis was similar to that in the original analysis, indicating the robustness of the models in predicting the cancer outcomes.

Bipartite Networks of Universities and Companies: Recruiting New Graduates in Japan

Science.gov (United States)

Takahashi, Katsuhide; Kobayashi, Yuh; Kondo, Yohei; Takayasu, Hideki; Takayasu, Misako

We investigated the bipartite Universities-Companies Network in Japan in terms of companies' recruitment of new graduates. In Japan, graduates of universities are typically hired by companies upon their graduation. To examine socially accepted ideas about this recruiting system, we combined different types of data on education, recruitment and corporate finance. The hypothesis that graduates from prestigious universities have the advantage of entering excellent companies was verified by examining the determinants of ratio of graduates entering top-ranked companies. Through hierarchical clustering, we obtained classification trees and observed the stability of their structure, as well as interesting changes corresponding to the business climate. We also calculated weighted HITS hub and authority values for each university and company and identified the links between the results of this analysis and those above. Finally, analysis of all the data indicated that excellent companies recruiting many graduates from prestigious universities do not necessarily show superb performance in profit-making and growth.

From Ecology to Finance (and Back?): A Review on Entropy-Based Null Models for the Analysis of Bipartite Networks

Science.gov (United States)

Straka, Mika J.; Caldarelli, Guido; Squartini, Tiziano; Saracco, Fabio

2018-04-01

Bipartite networks provide an insightful representation of many systems, ranging from mutualistic networks of species interactions to investment networks in finance. The analyses of their topological structures have revealed the ubiquitous presence of properties which seem to characterize many—apparently different—systems. Nestedness, for example, has been observed in biological plant-pollinator as well as in country-product exportation networks. Due to the interdisciplinary character of complex networks, tools developed in one field, for example ecology, can greatly enrich other areas of research, such as economy and finance, and vice versa. With this in mind, we briefly review several entropy-based bipartite null models that have been recently proposed and discuss their application to real-world systems. The focus on these models is motivated by the fact that they show three very desirable features: analytical character, general applicability, and versatility. In this respect, entropy-based methods have been proven to perform satisfactorily both in providing benchmarks for testing evidence-based null hypotheses and in reconstructing unknown network configurations from partial information. Furthermore, entropy-based models have been successfully employed to analyze ecological as well as economic systems. As an example, the application of entropy-based null models has detected early-warning signals, both in economic and financial systems, of the 2007-2008 world crisis. Moreover, they have revealed a statistically-significant export specialization phenomenon of country export baskets in international trade, a result that seems to reconcile Ricardo's hypothesis in classical economics with recent findings on the (empirical) diversification industrial production at the national level. Finally, these null models have shown that the information contained in the nestedness is already accounted for by the degree sequence of the corresponding graphs.

Bone-scintigraphy in painful bipartite patella

International Nuclear Information System (INIS)

Iossifidis, A.; Brueton, R.N.; Nunan, T.O.

1995-01-01

Although, the use of technetium scintigraphy in the assessment of anterior knee pain has been described, no reference has been made to the scintigraphic appearances of painful bipartite patella. We report the scintigraphic-appearances of painful bipartite patella in 25-year-old man a 2 1/2 years history of unexplained patellar pain. Painful bipartite patella is a rare cause of chronic post-traumatic patellar pain. Bone scintigraphy, by demonstrating increased uptake by the painful accessory bipartite fragment, appears to be an imaging method of choice in the diagnosis of this condition. (orig./MG)

Complexity of Products of Some Complete and Complete Bipartite Graphs

Directory of Open Access Journals (Sweden)

S. N. Daoud

2013-01-01

Full Text Available The number of spanning trees in graphs (networks is an important invariant; it is also an important measure of reliability of a network. In this paper, we derive simple formulas of the complexity, number of spanning trees, of products of some complete and complete bipartite graphs such as cartesian product, normal product, composition product, tensor product, and symmetric product, using linear algebra and matrix analysis techniques.

Controlling bi-partite entanglement in multi-qubit systems

International Nuclear Information System (INIS)

Plesch, Martin; Novotny, Jaroslav; Dzurakova, Zuzana; Buzek, VladimIr

2004-01-01

Bi-partite entanglement in multi-qubit systems cannot be shared freely. The rules of quantum mechanics impose bounds on how multi-qubit systems can be correlated. In this paper, we utilize a concept of entangled graphs with weighted edges in order to analyse pure quantum states of multi-qubit systems. Here qubits are represented by vertexes of the graph, while the presence of bi-partite entanglement is represented by an edge between corresponding vertexes. The weight of each edge is defined to be the entanglement between the two qubits connected by the edge, as measured by the concurrence. We prove that each entangled graph with entanglement bounded by a specific value of the concurrence can be represented by a pure multi-qubit state. In addition, we present a logic network with O(N 2 ) elementary gates that can be used for preparation of the weighted entangled graphs of N qubits

Controlling bi-partite entanglement in multi-qubit systems

Science.gov (United States)

Plesch, Martin; Novotný, Jaroslav; Dzuráková, Zuzana; Buzek, Vladimír

2004-02-01

Bi-partite entanglement in multi-qubit systems cannot be shared freely. The rules of quantum mechanics impose bounds on how multi-qubit systems can be correlated. In this paper, we utilize a concept of entangled graphs with weighted edges in order to analyse pure quantum states of multi-qubit systems. Here qubits are represented by vertexes of the graph, while the presence of bi-partite entanglement is represented by an edge between corresponding vertexes. The weight of each edge is defined to be the entanglement between the two qubits connected by the edge, as measured by the concurrence. We prove that each entangled graph with entanglement bounded by a specific value of the concurrence can be represented by a pure multi-qubit state. In addition, we present a logic network with O(N2) elementary gates that can be used for preparation of the weighted entangled graphs of N qubits.

Groupies in random bipartite graphs

OpenAIRE

Yilun Shang

2010-01-01

A vertex $v$ of a graph $G$ is called a groupie if its degree is notless than the average of the degrees of its neighbors. In thispaper we study the influence of bipartition $(B_1,B_2)$ on groupiesin random bipartite graphs $G(B_1,B_2,p)$ with both fixed $p$ and$p$ tending to zero.

Stable configurations in social networks

Science.gov (United States)

Bronski, Jared C.; DeVille, Lee; Ferguson, Timothy; Livesay, Michael

2018-06-01

We present and analyze a model of opinion formation on an arbitrary network whose dynamics comes from a global energy function. We study the global and local minimizers of this energy, which we call stable opinion configurations, and describe the global minimizers under certain assumptions on the friendship graph. We show a surprising result that the number of stable configurations is not necessarily monotone in the strength of connection in the social network, i.e. the model sometimes supports more stable configurations when the interpersonal connections are made stronger.

Separable decompositions of bipartite mixed states

Science.gov (United States)

Li, Jun-Li; Qiao, Cong-Feng

2018-04-01

We present a practical scheme for the decomposition of a bipartite mixed state into a sum of direct products of local density matrices, using the technique developed in Li and Qiao (Sci. Rep. 8:1442, 2018). In the scheme, the correlation matrix which characterizes the bipartite entanglement is first decomposed into two matrices composed of the Bloch vectors of local states. Then, we show that the symmetries of Bloch vectors are consistent with that of the correlation matrix, and the magnitudes of the local Bloch vectors are lower bounded by the correlation matrix. Concrete examples for the separable decompositions of bipartite mixed states are presented for illustration.

Quantum open system theory: bipartite aspects.

Science.gov (United States)

Yu, T; Eberly, J H

2006-10-06

We demonstrate in straightforward calculations that even under ideally weak noise the relaxation of bipartite open quantum systems contains elements not previously encountered in quantum noise physics. While additivity of decay rates is known to be generic for decoherence of a single system, we demonstrate that it breaks down for bipartite coherence of even the simplest composite systems.

An Extended HITS Algorithm on Bipartite Network for Features Extraction of Online Customer Reviews

Directory of Open Access Journals (Sweden)

Chen Liu

2018-05-01

Full Text Available How to acquire useful information intelligently in the age of information explosion has become an important issue. In this context, sentiment analysis emerges with the growth of the need of information extraction. One of the most important tasks of sentiment analysis is feature extraction of entities in consumer reviews. This paper first constitutes a directed bipartite feature-sentiment relation network with a set of candidate features-sentiment pairs that is extracted by dependency syntax analysis from consumer reviews. Then, a novel method called MHITS which combines PMI with weighted HITS algorithm is proposed to rank these candidate product features to find out real product features. Empirical experiments indicate the effectiveness of our approach across different kinds and various data sizes of product. In addition, the effect of the proposed algorithm is not the same for the corpus with different proportions of the word pair that includes the “bad”, “good”, “poor”, “pretty good”, “not bad” these general collocation words.

Effect of Bipartite Hallucal Sesamoid on Hallux Valgus Surgery.

Science.gov (United States)

Park, Young Hwan; Jeong, Chan Dong; Choi, Gi Won; Kim, Hak Jun

2017-06-01

Bipartite hallucal sesamoids are often found in patients with hallux valgus. However, it is unknown whether bipartite hallucal sesamoids affect the results of hallux valgus surgery or not. The purpose of the present study was to evaluate the outcomes of chevron osteotomy for hallux valgus with and without bipartite hallucal sesamoid. A total of 152 patients (168 feet) treated with distal or proximal chevron osteotomy for hallux valgus constituted the study cohort. The 168 feet were divided into 2 groups: bipartite hallucal sesamoid (31 feet) and without bipartite hallucal sesamoid (137 feet). Hallux valgus angle (HVA), intermetatarsal angle (IMA), distal metatarsal articular angle (DMAA), tibial sesamoid position, and first metatarsal length were measured for radiographic outcomes and the American Orthopaedic Foot & Ankle Society (AOFAS) hallux metatarsophalangeal-interphalangeal (MTP-IP) score was measured for clinical outcomes. All radiographic measurements and the AOFAS score showed significant ( P .05) were found between the 2 groups in terms of HVA, IMA, DMAA, tibial sesamoid position, metatarsal shortening, and AOFAS score on final follow-up. This study suggests that bipartite hallucal sesamoids do not affect the results of hallux valgus surgery. Level III, retrospective comparative study.

Data transfer using complete bipartite graph

Science.gov (United States)

Chandrasekaran, V. M.; Praba, B.; Manimaran, A.; Kailash, G.

2017-11-01

Information exchange extent is an estimation of the amount of information sent between two focuses on a framework in a given time period. It is an extremely significant perception in present world. There are many ways of message passing in the present situations. Some of them are through encryption, decryption, by using complete bipartite graph. In this paper, we recommend a method for communication using messages through encryption of a complete bipartite graph.

Bipartite binomial heaps

DEFF Research Database (Denmark)

Elmasry, Amr; Jensen, Claus; Katajainen, Jyrki

2017-01-01

the (total) number of elements stored in the data structure(s) prior to the operation. As the resulting data structure consists of two components that are different variants of binomial heaps, we call it a bipartite binomial heap. Compared to its counterpart, a multipartite binomial heap, the new structure...

Quantum trajectory approach to the geometric phase: open bipartite systems

International Nuclear Information System (INIS)

Yi, X X; Liu, D P; Wang, W

2005-01-01

Through the quantum trajectory approach, we calculate the geometric phase acquired by a bipartite system subjected to decoherence. The subsystems that compose the bipartite system interact with each other and then are entangled in the evolution. The geometric phase due to the quantum jump for both the bipartite system and its subsystems is calculated and analysed. As an example, we present two coupled spin-1/2 particles to detail the calculations

Ranking stability and super-stable nodes in complex networks.

Science.gov (United States)

Ghoshal, Gourab; Barabási, Albert-László

2011-07-19

Pagerank, a network-based diffusion algorithm, has emerged as the leading method to rank web content, ecological species and even scientists. Despite its wide use, it remains unknown how the structure of the network on which it operates affects its performance. Here we show that for random networks the ranking provided by pagerank is sensitive to perturbations in the network topology, making it unreliable for incomplete or noisy systems. In contrast, in scale-free networks we predict analytically the emergence of super-stable nodes whose ranking is exceptionally stable to perturbations. We calculate the dependence of the number of super-stable nodes on network characteristics and demonstrate their presence in real networks, in agreement with the analytical predictions. These results not only deepen our understanding of the interplay between network topology and dynamical processes but also have implications in all areas where ranking has a role, from science to marketing.

Bipartite Network Analysis of the Archaeal Virosphere: Evolutionary Connections between Viruses and Capsidless Mobile Elements.

Science.gov (United States)

Iranzo, Jaime; Koonin, Eugene V; Prangishvili, David; Krupovic, Mart

2016-12-15

Archaea and particularly hyperthermophilic crenarchaea are hosts to many unusual viruses with diverse virion shapes and distinct gene compositions. As is typical of viruses in general, there are no universal genes in the archaeal virosphere. Therefore, to obtain a comprehensive picture of the evolutionary relationships between viruses, network analysis methods are more productive than traditional phylogenetic approaches. Here we present a comprehensive comparative analysis of genomes and proteomes from all currently known taxonomically classified and unclassified, cultivated and uncultivated archaeal viruses. We constructed a bipartite network of archaeal viruses that includes two classes of nodes, the genomes and gene families that connect them. Dissection of this network using formal community detection methods reveals strong modularity, with 10 distinct modules and 3 putative supermodules. However, compared to similar previously analyzed networks of eukaryotic and bacterial viruses, the archaeal virus network is sparsely connected. With the exception of the tailed viruses related to bacteriophages of the order Caudovirales and the families Turriviridae and Sphaerolipoviridae that are linked to a distinct supermodule of eukaryotic and bacterial viruses, there are few connector genes shared by different archaeal virus modules. In contrast, most of these modules include, in addition to viruses, capsidless mobile elements, emphasizing tight evolutionary connections between the two types of entities in archaea. The relative contributions of distinct evolutionary origins, in particular from nonviral elements, and insufficient sampling to the sparsity of the archaeal virus network remain to be determined by further exploration of the archaeal virosphere. Viruses infecting archaea are among the most mysterious denizens of the virosphere. Many of these viruses display no genetic or even morphological relationship to viruses of bacteria and eukaryotes, raising questions

A Partial Order on Bipartite Graphs with n Vertices

Directory of Open Access Journals (Sweden)

Emil Daniel Schwab

2009-01-01

Full Text Available The paper examines a partial order on bipartite graphs (X1, X2, E with n vertices, X1∪X2={1,2,…,n}. The basis of such bipartite graph is X1 = {1,2,…,k}, 0≤k≤n. If U = (X1, X2, E(U and V = (Y1,Y2, E(V then U≤V iff |X1| ≤ |Y1| and {(i,jE(U: j>|Y1|} = ={(i,jE(V:i≤|X1|}. This partial order is a natural partial order of subobjects of an object in a triangular category with bipartite graphs as morphisms.

Modeling online social signed networks

Science.gov (United States)

Li, Le; Gu, Ke; Zeng, An; Fan, Ying; Di, Zengru

2018-04-01

People's online rating behavior can be modeled by user-object bipartite networks directly. However, few works have been devoted to reveal the hidden relations between users, especially from the perspective of signed networks. We analyze the signed monopartite networks projected by the signed user-object bipartite networks, finding that the networks are highly clustered with obvious community structure. Interestingly, the positive clustering coefficient is remarkably higher than the negative clustering coefficient. Then, a Signed Growing Network model (SGN) based on local preferential attachment is proposed to generate a user's signed network that has community structure and high positive clustering coefficient. Other structural properties of the modeled networks are also found to be similar to the empirical networks.

Strong monogamy of bipartite and genuine multipartite entanglement: the Gaussian case.

Science.gov (United States)

Adesso, Gerardo; Illuminati, Fabrizio

2007-10-12

We demonstrate the existence of general constraints on distributed quantum correlations, which impose a trade-off on bipartite and multipartite entanglement at once. For all N-mode Gaussian states under permutation invariance, we establish exactly a monogamy inequality, stronger than the traditional one, that by recursion defines a proper measure of genuine N-partite entanglement. Strong monogamy holds as well for subsystems of arbitrary size, and the emerging multipartite entanglement measure is found to be scale invariant. We unveil its operational connection with the optimal fidelity of continuous variable teleportation networks.

Three methods to distill multipartite entanglement over bipartite noisy channels

International Nuclear Information System (INIS)

Lee, Soojoon; Park, Jungjoon

2008-01-01

We first assume that there are only bipartite noisy qubit channels in a given multipartite system, and present three methods to distill the general Greenberger-Horne-Zeilinger state. By investigating the methods, we show that multipartite entanglement distillation by bipartite entanglement distillation has higher yield than ones in the previous multipartite entanglement distillations

Ecological, historical and evolutionary determinants of modularity in weighted seed-dispersal networks

DEFF Research Database (Denmark)

Schleuning, Matthias; Ingmann, Lili; Strauß, Rouven

2014-01-01

Modularity is a recurrent and important property of bipartite ecological networks. Although well-resolved ecological networks describe interaction frequencies between species pairs, modularity of bipartite networks has been analysed only on the basis of binary presence-absence data. We employ a new...... algorithm to detect modularity in weighted bipartite networks in a global analysis of avian seed-dispersal networks. We define roles of species, such as connector values, for weighted and binary networks and associate them with avian species traits and phylogeny. The weighted, but not binary, analysis...... identified a positive relationship between climatic seasonality and modularity, whereas past climate stability and phylogenetic signal were only weakly related to modularity. Connector values were associated with foraging behaviour and were phylogenetically conserved. The weighted modularity analysis...

Building versatile bipartite probes for quantum metrology

Science.gov (United States)

Farace, Alessandro; De Pasquale, Antonella; Adesso, Gerardo; Giovannetti, Vittorio

2016-01-01

We consider bipartite systems as versatile probes for the estimation of transformations acting locally on one of the subsystems. We investigate what resources are required for the probes to offer a guaranteed level of metrological performance, when the latter is averaged over specific sets of local transformations. We quantify such a performance via the average skew information (AvSk), a convex quantity which we compute in closed form for bipartite states of arbitrary dimensions, and which is shown to be strongly dependent on the degree of local purity of the probes. Our analysis contrasts and complements the recent series of studies focused on the minimum, rather than the average, performance of bipartite probes in local estimation tasks, which was instead determined by quantum correlations other than entanglement. We provide explicit prescriptions to characterize the most reliable states maximizing the AvSk, and elucidate the role of state purity, separability and correlations in the classification of optimal probes. Our results can help in the identification of useful resources for sensing, estimation and discrimination applications when complete knowledge of the interaction mechanism realizing the local transformation is unavailable, and access to pure entangled probes is technologically limited.

Building versatile bipartite probes for quantum metrology

International Nuclear Information System (INIS)

Farace, Alessandro; Pasquale, Antonella De; Giovannetti, Vittorio; Adesso, Gerardo

2016-01-01

We consider bipartite systems as versatile probes for the estimation of transformations acting locally on one of the subsystems. We investigate what resources are required for the probes to offer a guaranteed level of metrological performance, when the latter is averaged over specific sets of local transformations. We quantify such a performance via the average skew information (AvSk), a convex quantity which we compute in closed form for bipartite states of arbitrary dimensions, and which is shown to be strongly dependent on the degree of local purity of the probes. Our analysis contrasts and complements the recent series of studies focused on the minimum, rather than the average, performance of bipartite probes in local estimation tasks, which was instead determined by quantum correlations other than entanglement. We provide explicit prescriptions to characterize the most reliable states maximizing the AvSk, and elucidate the role of state purity, separability and correlations in the classification of optimal probes. Our results can help in the identification of useful resources for sensing, estimation and discrimination applications when complete knowledge of the interaction mechanism realizing the local transformation is unavailable, and access to pure entangled probes is technologically limited. (paper)

Bipartite Community Structure of eQTLs.

Science.gov (United States)

Platig, John; Castaldi, Peter J; DeMeo, Dawn; Quackenbush, John

2016-09-01

Genome Wide Association Studies (GWAS) and expression quantitative trait locus (eQTL) analyses have identified genetic associations with a wide range of human phenotypes. However, many of these variants have weak effects and understanding their combined effect remains a challenge. One hypothesis is that multiple SNPs interact in complex networks to influence functional processes that ultimately lead to complex phenotypes, including disease states. Here we present CONDOR, a method that represents both cis- and trans-acting SNPs and the genes with which they are associated as a bipartite graph and then uses the modular structure of that graph to place SNPs into a functional context. In applying CONDOR to eQTLs in chronic obstructive pulmonary disease (COPD), we found the global network "hub" SNPs were devoid of disease associations through GWAS. However, the network was organized into 52 communities of SNPs and genes, many of which were enriched for genes in specific functional classes. We identified local hubs within each community ("core SNPs") and these were enriched for GWAS SNPs for COPD and many other diseases. These results speak to our intuition: rather than single SNPs influencing single genes, we see groups of SNPs associated with the expression of families of functionally related genes and that disease SNPs are associated with the perturbation of those functions. These methods are not limited in their application to COPD and can be used in the analysis of a wide variety of disease processes and other phenotypic traits.

Perioperative management of facial bipartition surgery

Directory of Open Access Journals (Sweden)

Caruselli M

2015-11-01

Full Text Available Marco Caruselli,1 Michael Tsapis,1,2 Fabrice Ughetto,1 Gregoire Pech-Gourg,3 Dario Galante,4 Olivier Paut1 1Anesthesia and Intensive Care Unit, La Timone Children’s Hospital, 2Pediatric Transport Team, SAMU 13, La Timone Hospital, 3Pediatric Neurosurgery Unit, La Timone Children’s Hospital, Marseille, France; 4Anesthesia and Intensive Care Unit, University Hospital Ospedali Riuniti of Foggia, Foggia, Italy Abstract: Severe craniofacial malformations, such as Crouzon, Apert, Saethre-Chotzen, and Pfeiffer syndromes, are very rare conditions (one in 50,000/100,000 live births that often require corrective surgery. Facial bipartition is the more radical corrective surgery. It is a high-risk intervention and needs complex perioperative management and a multidisciplinary approach. Keywords: craniofacial surgery, facial bipartition surgery, craniofacial malformations, pediatric anesthesia

Traumatic separation of a type I patella bipartite in a sportsman

DEFF Research Database (Denmark)

Ottesen, Casper Smedegaard; Barfod, Kristoffer Weisskirchner; Holck, Kim

2014-01-01

fibrocartilage was found on both parts of the patella. Asymptomatic patella bi-partite was found on X-ray imaging of the patient's left knee, and he was diagnosed to have traumatic separation of a type I patella bipartite. The diagnosis was confirmed by surgical and radiological findings....

Weighted Scale-Free Network Properties of Ecological Network

International Nuclear Information System (INIS)

Lee, Jae Woo; Maeng, Seong Eun

2013-01-01

We investigate the scale-free network properties of the bipartite ecological network, in particular, the plant-pollinator network. In plant-pollinator network, the pollinators visit the plant to get the nectars. In contrast to the other complex network, the plant-pollinator network has not only the trophic relationships among the interacting partners but also the complexities of the coevolutionary effects. The interactions between the plant and pollinators are beneficial relations. The plant-pollinator network is a bipartite and weighted network. The networks have two types of the nodes: plant and pollinator. We consider the visiting frequency of a pollinator to a plant as the weighting value of the link. We defined the strength of a node as the sum of the weighting value of the links. We reported the cumulative distribution function (CDF) of the degree and the strength of the plant-pollinator network. The CDF of the plants followed stretched exponential functions for both degree and strength, but the CDF of the pollinators showed the power law for both degree and strength. The average strength of the links showed the nonlinear dependence on the degree of the networks.

Multiple Substrate Usage of Coxiella burnetii to Feed a Bipartite Metabolic Network

Directory of Open Access Journals (Sweden)

Ina Häuslein

2017-06-01

Full Text Available The human pathogen Coxiella burnetii causes Q-fever and is classified as a category B bio-weapon. Exploiting the development of the axenic growth medium ACCM-2, we have now used 13C-labeling experiments and isotopolog profiling to investigate the highly diverse metabolic network of C. burnetii. To this aim, C. burnetii RSA 439 NMII was cultured in ACCM-2 containing 5 mM of either [U-13C3]serine, [U-13C6]glucose, or [U-13C3]glycerol until the late-logarithmic phase. GC/MS-based isotopolog profiling of protein-derived amino acids, methanol-soluble polar metabolites, fatty acids, and cell wall components (e.g., diaminopimelate and sugars from the labeled bacteria revealed differential incorporation rates and isotopolog profiles. These data served to decipher the diverse usages of the labeled substrates and the relative carbon fluxes into the core metabolism of the pathogen. Whereas, de novo biosynthesis from any of these substrates could not be found for histidine, isoleucine, leucine, lysine, phenylalanine, proline and valine, the other amino acids and metabolites under study acquired 13C-label at specific rates depending on the nature of the tracer compound. Glucose was directly used for cell wall biosynthesis, but was also converted into pyruvate (and its downstream metabolites through the glycolytic pathway or into erythrose 4-phosphate (e.g., for the biosynthesis of tyrosine via the non-oxidative pentose phosphate pathway. Glycerol efficiently served as a gluconeogenetic substrate and could also be used via phosphoenolpyruvate and diaminopimelate as a major carbon source for cell wall biosynthesis. In contrast, exogenous serine was mainly utilized in downstream metabolic processes, e.g., via acetyl-CoA in a complete citrate cycle with fluxes in the oxidative direction and as a carbon feed for fatty acid biosynthesis. In summary, the data reflect multiple and differential substrate usages by C. burnetii in a bipartite-type metabolic network

Bipartite Bell Inequality and Maximal Violation

International Nuclear Information System (INIS)

Li Ming; Fei Shaoming; Li-Jost Xian-Qing

2011-01-01

We present new bell inequalities for arbitrary dimensional bipartite quantum systems. The maximal violation of the inequalities is computed. The Bell inequality is capable of detecting quantum entanglement of both pure and mixed quantum states more effectively. (general)

Improving information filtering via network manipulation

Science.gov (United States)

Zhang, Fuguo; Zeng, An

2012-12-01

The recommender system is a very promising way to address the problem of overabundant information for online users. Although the information filtering for the online commercial systems has received much attention recently, almost all of the previous works are dedicated to design new algorithms and consider the user-item bipartite networks as given and constant information. However, many problems for recommender systems such as the cold-start problem (i.e., low recommendation accuracy for the small-degree items) are actually due to the limitation of the underlying user-item bipartite networks. In this letter, we propose a strategy to enhance the performance of the already existing recommendation algorithms by directly manipulating the user-item bipartite networks, namely adding some virtual connections to the networks. Numerical analyses on two benchmark data sets, MovieLens and Netflix, show that our method can remarkably improves the recommendation performance. Specifically, it not only improves the recommendations accuracy (especially for the small-degree items), but also helps the recommender systems generate more diverse and novel recommendations.

Bipartite Fuzzy Stochastic Differential Equations with Global Lipschitz Condition

Directory of Open Access Journals (Sweden)

Marek T. Malinowski

2016-01-01

Full Text Available We introduce and analyze a new type of fuzzy stochastic differential equations. We consider equations with drift and diffusion terms occurring at both sides of equations. Therefore we call them the bipartite fuzzy stochastic differential equations. Under the Lipschitz and boundedness conditions imposed on drifts and diffusions coefficients we prove existence of a unique solution. Then, insensitivity of the solution under small changes of data of equation is examined. Finally, we mention that all results can be repeated for solutions to bipartite set-valued stochastic differential equations.

Design of a tripartite network for the prediction of drug targets

Science.gov (United States)

Kunimoto, Ryo; Bajorath, Jürgen

2018-02-01

Drug-target networks have aided in many target prediction studies aiming at drug repurposing or the analysis of side effects. Conventional drug-target networks are bipartite. They contain two different types of nodes representing drugs and targets, respectively, and edges indicating pairwise drug-target interactions. In this work, we introduce a tripartite network consisting of drugs, other bioactive compounds, and targets from different sources. On the basis of analog relationships captured in the network and so-called neighbor targets of drugs, new drug targets can be inferred. The tripartite network was found to have a stable structure and simulated network growth was accompanied by a steady increase in assortativity, reflecting increasing correlation between degrees of connected nodes leading to even network connectivity. Local drug environments in the tripartite network typically contained neighbor targets and revealed interesting drug-compound-target relationships for further analysis. Candidate targets were prioritized. The tripartite network design extends standard drug-target networks and provides additional opportunities for drug target prediction.

Mutually Unbiased Maximally Entangled Bases for the Bipartite System Cd⊗ C^{dk}

Science.gov (United States)

Nan, Hua; Tao, Yuan-Hong; Wang, Tian-Jiao; Zhang, Jun

2016-10-01

The construction of maximally entangled bases for the bipartite system Cd⊗ Cd is discussed firstly, and some mutually unbiased bases with maximally entangled bases are given, where 2≤ d≤5. Moreover, we study a systematic way of constructing mutually unbiased maximally entangled bases for the bipartite system Cd⊗ C^{dk}.

Bipartite Diametrical Graphs of Diameter 4 and Extreme Orders

Directory of Open Access Journals (Sweden)

Salah Al-Addasi

2008-01-01

in which this upper bound is attained, this graph can be viewed as a generalization of the Rhombic Dodecahedron. Then we show that for any ≥2, the graph (2,2 is the unique (up to isomorphism bipartite diametrical graph of diameter 4 and partite sets of cardinalities 2 and 2, and hence in particular, for =3, the graph (6,8 which is just the Rhombic Dodecahedron is the unique (up to isomorphism bipartite diametrical graph of such a diameter and cardinalities of partite sets. Thus we complete a characterization of -graphs of diameter 4 and cardinality of the smaller partite set not exceeding 6. We prove that the neighborhoods of vertices of the larger partite set of (2,2 form a matroid whose basis graph is the hypercube . We prove that any -graph of diameter 4 is bipartite self complementary, thus in particular (2,2. Finally, we study some additional properties of (2,2 concerning the order of its automorphism group, girth, domination number, and when being Eulerian.

Eigenvalues and expansion of bipartite graphs

DEFF Research Database (Denmark)

Høholdt, Tom; Janwa, Heeralal

2012-01-01

We prove lower bounds on the largest and second largest eigenvalue of the adjacency matrix of bipartite graphs and give necessary and sufficient conditions for equality. We give several examples of classes that are optimal with respect to the bouns. We prove that BIBD-graphs are characterized by ...

Comment on "Protecting bipartite entanglement by quantum interferences"

Science.gov (United States)

Nair, Anjali N.; Arun, R.

2018-03-01

In an interesting article [Phys. Rev. A 81, 052341 (2010), 10.1103/PhysRevA.81.052341], Das and Agarwal have discussed the preservation of bipartite entanglement in three-level atoms employing the coherences induced by spontaneous emission. The authors considered various initially entangled qubits prepared from two V -type three-level atoms and showed that more than 50 % of the initial (bipartite) entanglement can be preserved in steady state due to vacuum-induced coherence. In this Comment, we point out that their analytical formulas for the entanglement measure contain errors affecting all the numerical results of that article. We substantiate our claim by giving correct analytical results for the time evolution of the two-atom system.

Scatter networks: a new approach for analysing information scatter

International Nuclear Information System (INIS)

Adamic, Lada A; Suresh, K; Shi Xiaolin

2007-01-01

Information on any given topic is often scattered across the Web. Previously this scatter has been characterized through the inequality of distribution of facts (i.e. pieces of information) across webpages. Such an approach conceals how specific facts (e.g. rare facts) occur in specific types of pages (e.g. fact-rich pages). To reveal such regularities, we construct bipartite networks, consisting of two types of vertices: the facts contained in webpages and the webpages themselves. Such a representation enables the application of a series of network analysis techniques, revealing structural features such as connectivity, robustness and clustering. Not only does network analysis yield new insights into information scatter, but we also illustrate the benefit of applying new and existing analysis techniques directly to a bipartite network as opposed to its one-mode projection. We discuss the implications of each network feature to the users' ability to find comprehensive information online. Finally, we compare the bipartite graph structure of webpages and facts with the hyperlink structure between the webpages

Inseparability inequalities for higher order moments for bipartite systems

International Nuclear Information System (INIS)

Agarwal, G S; Biswas, Asoka

2005-01-01

There are several examples of bipartite entangled states of continuous variables for which the existing criteria for entanglement using the inequalities involving the second-order moments are insufficient. We derive new inequalities involving higher order correlation, for testing entanglement in non-Gaussian states. In this context, we study an example of a non-Gaussian state, which is a bipartite entangled state of the form Ψ(x a , x b ) ∝ (αx a + βx b ) e -(x a 2 +x b 2 )/2 . Our results open up an avenue to search for new inequalities to test entanglement in non-Gaussian states

Additional Quantum Properties of Entangled Bipartite Qubit Systems Coupled to Photon Baths

International Nuclear Information System (INIS)

Quintana, C

2016-01-01

The time evolution of an entangled bi-partite qubit interacting with two independent photon baths in isolated cavities is not unitary. It is shown that the bi-partite qubit oscillates between pure and mixed states, and that the initial entanglement is lost and recovered in time by time as a consequence of its interaction with the baths. (paper)

Relativistic quantum correlations in bipartite fermionic states

Indian Academy of Sciences (India)

2016-09-21

Sep 21, 2016 ... particles on different types of correlations present in bipartite quantum states are investigated. In particular, the ... the focus of research for the last few years. Many re- ..... figures, the qualitative behaviour of all the three types ...

Dynamic Matchings in Convex Bipartite Graphs

DEFF Research Database (Denmark)

Brodal, Gerth Stølting; Georgiadis, Loukas; Hansen, Kristoffer Arnsfelt

2007-01-01

We consider the problem of maintaining a maximum matching in a convex bipartite graph G = (V,E) under a set of update operations which includes insertions and deletions of vertices and edges. It is not hard to show that it is impossible to maintain an explicit representation of a maximum matching...

On bipartite pure-state entanglement structure in terms of disentanglement

Science.gov (United States)

Herbut, Fedor

2006-12-01

Schrödinger's disentanglement [E. Schrödinger, Proc. Cambridge Philos. Soc. 31, 555 (1935)], i.e., remote state decomposition, as a physical way to study entanglement, is carried one step further with respect to previous work in investigating the qualitative side of entanglement in any bipartite state vector. Remote measurement (or, equivalently, remote orthogonal state decomposition) from previous work is generalized to remote linearly independent complete state decomposition both in the nonselective and the selective versions. The results are displayed in terms of commutative square diagrams, which show the power and beauty of the physical meaning of the (antiunitary) correlation operator inherent in the given bipartite state vector. This operator, together with the subsystem states (reduced density operators), constitutes the so-called correlated subsystem picture. It is the central part of the antilinear representation of a bipartite state vector, and it is a kind of core of its entanglement structure. The generalization of previously elaborated disentanglement expounded in this article is a synthesis of the antilinear representation of bipartite state vectors, which is reviewed, and the relevant results of [Cassinelli et al., J. Math. Anal. Appl. 210, 472 (1997)] in mathematical analysis, which are summed up. Linearly independent bases (finite or infinite) are shown to be almost as useful in some quantum mechanical studies as orthonormal ones. Finally, it is shown that linearly independent remote pure-state preparation carries the highest probability of occurrence. This singles out linearly independent remote influence from all possible ones.

Uncovering the essential links in online commercial networks

Science.gov (United States)

Zeng, Wei; Fang, Meiling; Shao, Junming; Shang, Mingsheng

2016-09-01

Recommender systems are designed to effectively support individuals' decision-making process on various web sites. It can be naturally represented by a user-object bipartite network, where a link indicates that a user has collected an object. Recently, research on the information backbone has attracted researchers' interests, which is a sub-network with fewer nodes and links but carrying most of the relevant information. With the backbone, a system can generate satisfactory recommenda- tions while saving much computing resource. In this paper, we propose an enhanced topology-aware method to extract the information backbone in the bipartite network mainly based on the information of neighboring users and objects. Our backbone extraction method enables the recommender systems achieve more than 90% of the accuracy of the top-L recommendation, however, consuming only 20% links. The experimental results show that our method outperforms the alternative backbone extraction methods. Moreover, the structure of the information backbone is studied in detail. Finally, we highlight that the information backbone is one of the most important properties of the bipartite network, with which one can significantly improve the efficiency of the recommender system.

Relativistic quantum correlations in bipartite fermionic states

Indian Academy of Sciences (India)

The influences of relative motion, the size of the wave packet and the average momentum of the particles on different types of correlations present in bipartite quantum states are investigated. In particular, the dynamics of the quantum mutual information, the classical correlation and the quantum discord on the ...

Induced bipartite entanglement from three qubit states and quantum teleportation

Energy Technology Data Exchange (ETDEWEB)

Park, Dae-Kil; Son, Jin-Woo; Cha, Seong-Keuck [Kyungnam University, Masan (Korea, Republic of)

2010-06-15

Only Greenberger-Horne-Zeilinger and W states are well known to have genuine tripartite entanglement in all three qubit states. The entanglement of quantum state is also well known to play an important role in various quantum information processes. Then, the following question naturally arises: which one is better between the Greenberger-Horne-Zeilinger and the W states in real quantum information processing? We try to give an answer to this question from two aspects. First, we compute the induced bipartite entanglement for a mixture consisting of Greenberger-Horne-Zeilinger and W states. If the entanglement is the only physical resource for information processing, the induced bipartite entanglement suggests that Greenberger-Horne-Zeilinger and W states are equally good. Second, we choose the bipartite teleportation scheme as an example of quantum information processing using the mixture as a quantum channel and compute the average fidelities. Our calculation shows that the W state is slightly more robust than the Greenberger-Horne-Zeilinger state when a small perturbation disturbs the teleportation process. This slight discrepancy seems to imply that entanglement is not the only resource for quantum information processing.

Induced bipartite entanglement from three qubit states and quantum teleportation

International Nuclear Information System (INIS)

Park, Dae-Kil; Son, Jin-Woo; Cha, Seong-Keuck

2010-01-01

Only Greenberger-Horne-Zeilinger and W states are well known to have genuine tripartite entanglement in all three qubit states. The entanglement of quantum state is also well known to play an important role in various quantum information processes. Then, the following question naturally arises: which one is better between the Greenberger-Horne-Zeilinger and the W states in real quantum information processing? We try to give an answer to this question from two aspects. First, we compute the induced bipartite entanglement for a mixture consisting of Greenberger-Horne-Zeilinger and W states. If the entanglement is the only physical resource for information processing, the induced bipartite entanglement suggests that Greenberger-Horne-Zeilinger and W states are equally good. Second, we choose the bipartite teleportation scheme as an example of quantum information processing using the mixture as a quantum channel and compute the average fidelities. Our calculation shows that the W state is slightly more robust than the Greenberger-Horne-Zeilinger state when a small perturbation disturbs the teleportation process. This slight discrepancy seems to imply that entanglement is not the only resource for quantum information processing.

Quantumness of bipartite states in terms of conditional entropies

International Nuclear Information System (INIS)

Li, Nan; Luo, Shunlong; Zhang, Zhengmin

2007-01-01

Quantum discord, as defined by Olliver and Zurek (2002 Phys. Rev. Lett. 88 017901) as the difference of two natural quantum extensions of the classical mutual information, plays an interesting role in characterizing quantumness of correlations. Inspired by this idea, we will study quantumness of bipartite states arising from different quantum analogs of the classical conditional entropy. Our approach is intrinsic, in contrast to the Olliver-Zurek method that involves extrinsic local measurements. For this purpose, we introduce two alternative variants of quantum conditional entropies via conditional density operators, which in turn are intuitive quantum extensions of equivalent classical expressions for the conditional probability. The significance of these quantum conditional entropies in characterizing quantumness of bipartite states is illustrated through several examples

Asystasia mosaic Madagascar virus: a novel bipartite begomovirus infecting the weed Asystasia gangetica in Madagascar.

Science.gov (United States)

De Bruyn, Alexandre; Harimalala, Mireille; Hoareau, Murielle; Ranomenjanahary, Sahondramalala; Reynaud, Bernard; Lefeuvre, Pierre; Lett, Jean-Michel

2015-06-01

Here, we describe for the first time the complete genome sequence of a new bipartite begomovirus in Madagascar isolated from the weed Asystasia gangetica (Acanthaceae), for which we propose the tentative name asystasia mosaic Madagascar virus (AMMGV). DNA-A and -B nucleotide sequences of AMMGV were only distantly related to known begomovirus sequence and shared highest nucleotide sequence identity of 72.9 % (DNA-A) and 66.9 % (DNA-B) with a recently described bipartite begomovirus infecting Asystasia sp. in West Africa. Phylogenetic analysis demonstrated that this novel virus from Madagascar belongs to a new lineage of Old World bipartite begomoviruses.

Bipartite separability and nonlocal quantum operations on graphs

Science.gov (United States)

Dutta, Supriyo; Adhikari, Bibhas; Banerjee, Subhashish; Srikanth, R.

2016-07-01

In this paper we consider the separability problem for bipartite quantum states arising from graphs. Earlier it was proved that the degree criterion is the graph-theoretic counterpart of the familiar positive partial transpose criterion for separability, although there are entangled states with positive partial transpose for which the degree criterion fails. Here we introduce the concept of partially symmetric graphs and degree symmetric graphs by using the well-known concept of partial transposition of a graph and degree criteria, respectively. Thus, we provide classes of bipartite separable states of dimension m ×n arising from partially symmetric graphs. We identify partially asymmetric graphs that lack the property of partial symmetry. We develop a combinatorial procedure to create a partially asymmetric graph from a given partially symmetric graph. We show that this combinatorial operation can act as an entanglement generator for mixed states arising from partially symmetric graphs.

A Family of Bipartite |Cardinality Matching Problems Solvable in O(n\\^2) Time

DEFF Research Database (Denmark)

Clausen, Jens; Krarup, J.

1995-01-01

For a given, unweighted bipartite graph G with 2n non isolated vertices, we consider the so called bipartite cardinality matching problem (BCMP) for which the time complexity of the fastest exact algorithm available is O(n/sup 5/2/ ). We devise a greedy algorithm which either finds a perfect...... matching in O(n/sup 2/ ) time or identifies cycle of length 4 in the complement G of G...

BATAS ATAS BILANGAN RAMSEY UNTUK GRAF BINTANG DAN GRAF BIPARTIT LENGKAP

OpenAIRE

Rosyida, Isnaini

2008-01-01

Misal G dan H dua buah graf sebarang, bilangan Ramsey R(G,H) adalah bilangan asli terkecil n sehingga untuk setiap graf F dengan n titik akan memuat G atau komplemen dari F memuat H. Makalah ini akan membahas batas atas dari bilangan Ramsey untuk graf bintang Sn dan graf bipartit lengkap Kp,q. Khususnya, kita akan menunjukkan batas atas dari R(Sn, K2,q) serta batas atas dari R(Sn, Kp,q) untuk n ≥ 5, 3 ≤ p ≤ n-1 dan q ≤ 2.Kata Kunci : Bilangan Ramsey, Graf Bintang dan Bipartit

Schur complements of matrices with acyclic bipartite graphs

DEFF Research Database (Denmark)

Britz, Thomas Johann; Olesky, D.D.; van den Driessche, P.

2005-01-01

Bipartite graphs are used to describe the generalized Schur complements of real matrices having nos quare submatrix with two or more nonzero diagonals. For any matrix A with this property, including any nearly reducible matrix, the sign pattern of each generalized Schur complement is shown to be ...

Statistical Mechanics of a Simplified Bipartite Matching Problem: An Analytical Treatment

Science.gov (United States)

Dell'Erba, Matías Germán

2012-03-01

We perform an analytical study of a simplified bipartite matching problem in which there exists a constant matching energy, and both heterosexual and homosexual pairings are allowed. We obtain the partition function in a closed analytical form and we calculate the corresponding thermodynamic functions of this model. We conclude that the model is favored at high temperatures, for which the probabilities of heterosexual and homosexual pairs tend to become equal. In the limits of low and high temperatures, the system is extensive, however this property is lost in the general case. There exists a relation between the matching energies for which the system becomes more stable under external (thermal) perturbations. As the difference of energies between the two possible matches increases the system becomes more ordered, while the maximum of entropy is achieved when these energies are equal. In this limit, there is a first order phase transition between two phases with constant entropy.

Upper bounds on entangling rates of bipartite Hamiltonians

International Nuclear Information System (INIS)

Bravyi, Sergey

2007-01-01

We discuss upper bounds on the rate at which unitary evolution governed by a nonlocal Hamiltonian can generate entanglement in a bipartite system. Given a bipartite Hamiltonian H coupling two finite dimensional particles A and B, the entangling rate is shown to be upper bounded by c log(d) parallel H parallel, where d is the smallest dimension of the interacting particles parallel H parallel is the operator norm of H, and c is a constant close to 1. Under certain restrictions on the initial state we prove an analogous upper bound for the ancilla-assisted entangling rate with a constant c that does not depend upon dimensions of local ancillas. The restriction is that the initial state has at most two distinct Schmidt coefficients (each coefficient may have arbitrarily large multiplicity). Our proof is based on analysis of a mixing rate - a functional measuring how fast entropy can be produced if one mixes a time-independent state with a state evolving unitarily

Dynamic motifs in socio-economic networks

Science.gov (United States)

Zhang, Xin; Shao, Shuai; Stanley, H. Eugene; Havlin, Shlomo

2014-12-01

Socio-economic networks are of central importance in economic life. We develop a method of identifying and studying motifs in socio-economic networks by focusing on “dynamic motifs,” i.e., evolutionary connection patterns that, because of “node acquaintances” in the network, occur much more frequently than random patterns. We examine two evolving bi-partite networks: i) the world-wide commercial ship chartering market and ii) the ship build-to-order market. We find similar dynamic motifs in both bipartite networks, even though they describe different economic activities. We also find that “influence” and “persistence” are strong factors in the interaction behavior of organizations. When two companies are doing business with the same customer, it is highly probable that another customer who currently only has business relationship with one of these two companies, will become customer of the second in the future. This is the effect of influence. Persistence means that companies with close business ties to customers tend to maintain their relationships over a long period of time.

Improved personalized recommendation based on a similarity network

Science.gov (United States)

Wang, Ximeng; Liu, Yun; Xiong, Fei

2016-08-01

A recommender system helps individual users find the preferred items rapidly and has attracted extensive attention in recent years. Many successful recommendation algorithms are designed on bipartite networks, such as network-based inference or heat conduction. However, most of these algorithms define the resource-allocation methods for an average allocation. That is not reasonable because average allocation cannot indicate the user choice preference and the influence between users which leads to a series of non-personalized recommendation results. We propose a personalized recommendation approach that combines the similarity function and bipartite network to generate a similarity network that improves the resource-allocation process. Our model introduces user influence into the recommender system and states that the user influence can make the resource-allocation process more reasonable. We use four different metrics to evaluate our algorithms for three benchmark data sets. Experimental results show that the improved recommendation on a similarity network can obtain better accuracy and diversity than some competing approaches.

Transformation of bipartite non-maximally entangled states into a ...

Indian Academy of Sciences (India)

We present two schemes for transforming bipartite non-maximally entangled states into a W state in cavity QED system, by using highly detuned interactions and the resonant interactions between ... Proceedings of the International Workshop/Conference on Computational Condensed Matter Physics and Materials Science

Congenital bipartite atlas with hypodactyly in a dog: clinical, radiographic and CT findings.

Science.gov (United States)

Wrzosek, M; Płonek, M; Zeira, O; Bieżyński, J; Kinda, W; Guziński, M

2014-07-01

A three-year-old Border collie was diagnosed with a bipartite atlas and bilateral forelimb hypodactyly. The dog showed signs of acute, non-progressive neck pain, general stiffness and right thoracic limb non-weight-bearing lameness. Computed tomography imaging revealed a bipartite atlas with abaxial vertical bone proliferation, which was the cause of the clinical signs. In addition, bilateral hypodactyly of the second and fifth digits was incidentally found. This report suggests that hypodactyly may be associated with atlas malformations. © 2014 British Small Animal Veterinary Association.

Localization of an Underwater Control Network Based on Quasi-Stable Adjustment

Science.gov (United States)

Chen, Xinhua; Zhang, Hongmei; Feng, Jie

2018-01-01

There exists a common problem in the localization of underwater control networks that the precision of the absolute coordinates of known points obtained by marine absolute measurement is poor, and it seriously affects the precision of the whole network in traditional constraint adjustment. Therefore, considering that the precision of underwater baselines is good, we use it to carry out quasi-stable adjustment to amend known points before constraint adjustment so that the points fit the network shape better. In addition, we add unconstrained adjustment for quality control of underwater baselines, the observations of quasi-stable adjustment and constrained adjustment, to eliminate the unqualified baselines and improve the results’ accuracy of the two adjustments. Finally, the modified method is applied to a practical LBL (Long Baseline) experiment and obtains a mean point location precision of 0.08 m, which improves by 38% compared with the traditional method. PMID:29570627

Functional analysis of bipartite begomovirus coat protein promoter sequences

International Nuclear Information System (INIS)

Lacatus, Gabriela; Sunter, Garry

2008-01-01

We demonstrate that the AL2 gene of Cabbage leaf curl virus (CaLCuV) activates the CP promoter in mesophyll and acts to derepress the promoter in vascular tissue, similar to that observed for Tomato golden mosaic virus (TGMV). Binding studies indicate that sequences mediating repression and activation of the TGMV and CaLCuV CP promoter specifically bind different nuclear factors common to Nicotiana benthamiana, spinach and tomato. However, chromatin immunoprecipitation demonstrates that TGMV AL2 can interact with both sequences independently. Binding of nuclear protein(s) from different crop species to viral sequences conserved in both bipartite and monopartite begomoviruses, including TGMV, CaLCuV, Pepper golden mosaic virus and Tomato yellow leaf curl virus suggests that bipartite begomoviruses bind common host factors to regulate the CP promoter. This is consistent with a model in which AL2 interacts with different components of the cellular transcription machinery that bind viral sequences important for repression and activation of begomovirus CP promoters

Computationally Efficient Nonlinear Bell Inequalities for Quantum Networks

Science.gov (United States)

Luo, Ming-Xing

2018-04-01

The correlations in quantum networks have attracted strong interest with new types of violations of the locality. The standard Bell inequalities cannot characterize the multipartite correlations that are generated by multiple sources. The main problem is that no computationally efficient method is available for constructing useful Bell inequalities for general quantum networks. In this work, we show a significant improvement by presenting new, explicit Bell-type inequalities for general networks including cyclic networks. These nonlinear inequalities are related to the matching problem of an equivalent unweighted bipartite graph that allows constructing a polynomial-time algorithm. For the quantum resources consisting of bipartite entangled pure states and generalized Greenberger-Horne-Zeilinger (GHZ) states, we prove the generic nonmultilocality of quantum networks with multiple independent observers using new Bell inequalities. The violations are maximal with respect to the presented Tsirelson's bound for Einstein-Podolsky-Rosen states and GHZ states. Moreover, these violations hold for Werner states or some general noisy states. Our results suggest that the presented Bell inequalities can be used to characterize experimental quantum networks.

Bipartite entanglement in continuous variable cluster states

Energy Technology Data Exchange (ETDEWEB)

Cable, Hugo; Browne, Daniel E, E-mail: cqthvc@nus.edu.s, E-mail: d.browne@ucl.ac.u [Centre for Quantum Technologies, National University of Singapore, 3 Science Drive 2, Singapore 117543 (Singapore)

2010-11-15

A study of the entanglement properties of Gaussian cluster states, proposed as a universal resource for continuous variable (CV) quantum computing is presented in this paper. The central aim is to compare mathematically idealized cluster states defined using quadrature eigenstates, which have infinite squeezing and cannot exist in nature, with Gaussian approximations that are experimentally accessible. Adopting widely used definitions, we first review the key concepts, by analysing a process of teleportation along a CV quantum wire in the language of matrix product states. Next we consider the bipartite entanglement properties of the wire, providing analytic results. We proceed to grid cluster states, which are universal for the qubit case. To extend our analysis of the bipartite entanglement, we adopt the entropic-entanglement width, a specialized entanglement measure introduced recently by Van den Nest et al (2006 Phys. Rev. Lett. 97 150504), adapting their definition to the CV context. Finally, we consider the effects of photonic loss, extending our arguments to mixed states. Cumulatively our results point to key differences in the properties of idealized and Gaussian cluster states. Even modest loss rates are found to strongly limit the amount of entanglement. We discuss the implications for the potential of CV analogues for measurement-based quantum computation.

Co-clustering Analysis of Weblogs Using Bipartite Spectral Projection Approach

DEFF Research Database (Denmark)

Xu, Guandong; Zong, Yu; Dolog, Peter

2010-01-01

Web clustering is an approach for aggregating Web objects into various groups according to underlying relationships among them. Finding co-clusters of Web objects is an interesting topic in the context of Web usage mining, which is able to capture the underlying user navigational interest...... and content preference simultaneously. In this paper we will present an algorithm using bipartite spectral clustering to co-cluster Web users and pages. The usage data of users visiting Web sites is modeled as a bipartite graph and the spectral clustering is then applied to the graph representation of usage...... data. The proposed approach is evaluated by experiments performed on real datasets, and the impact of using various clustering algorithms is also investigated. Experimental results have demonstrated the employed method can effectively reveal the subset aggregates of Web users and pages which...

Controlled teleportation of a 3-dimensional bipartite quantum state

International Nuclear Information System (INIS)

Cao Haijing; Chen Zhonghua; Song Heshan

2008-01-01

A controlled teleportation scheme of an unknown 3-dimensional (3D) two-particle quantum state is proposed, where a 3D Bell state and 3D GHZ state function as the quantum channel. This teleportation scheme can be directly generalized to teleport an unknown d-dimensional bipartite quantum state

Correlation/Communication complexity of generating bipartite states

OpenAIRE

Jain, Rahul; Shi, Yaoyun; Wei, Zhaohui; Zhang, Shengyu

2012-01-01

We study the correlation complexity (or equivalently, the communication complexity) of generating a bipartite quantum state $\\rho$. When $\\rho$ is a pure state, we completely characterize the complexity for approximately generating $\\rho$ by a corresponding approximate rank, closing a gap left in Ambainis, Schulman, Ta-Shma, Vazirani and Wigderson (SIAM Journal on Computing, 32(6):1570-1585, 2003). When $\\rho$ is a classical distribution $P(x,y)$, we tightly characterize the complexity of gen...

Combinatorial optimization networks and matroids

CERN Document Server

Lawler, Eugene

2011-01-01

Perceptively written text examines optimization problems that can be formulated in terms of networks and algebraic structures called matroids. Chapters cover shortest paths, network flows, bipartite matching, nonbipartite matching, matroids and the greedy algorithm, matroid intersections, and the matroid parity problems. A suitable text or reference for courses in combinatorial computing and concrete computational complexity in departments of computer science and mathematics.

Complete genome sequence of a new bipartite begomovirus infecting fluted pumpkin (Telfairia occidentalis) plants in Cameroon.

Science.gov (United States)

Leke, Walter N; Khatabi, Behnam; Fondong, Vincent N; Brown, Judith K

2016-08-01

The complete genome sequence was determined and characterized for a previously unreported bipartite begomovirus from fluted pumpkin (Telfairia occidentalis, family Cucurbitaceae) plants displaying mosaic symptoms in Cameroon. The DNA-A and DNA-B components were ~2.7 kb and ~2.6 kb in size, and the arrangement of viral coding regions on the genomic components was like those characteristic of other known bipartite begomoviruses originating in the Old World. While the DNA-A component was more closely related to that of chayote yellow mosaic virus (ChaYMV), at 78 %, the DNA-B component was more closely related to that of soybean chlorotic blotch virus (SbCBV), at 64 %. This newly discovered bipartite Old World virus is herein named telfairia mosaic virus (TelMV).

Ordering non-bipartite unicyclic graphs with pendant vertices by the least Q-eigenvalue

Directory of Open Access Journals (Sweden)

Shu-Guang Guo

2016-05-01

Full Text Available Abstract A unicyclic graph is a connected graph whose number of edges is equal to the number of vertices. Fan et al. (Discrete Math. 313:903-909, 2013 and Liu et al. (Electron. J. Linear Algebra 26:333-344, 2013 determined, independently, the unique unicyclic graph whose least Q-eigenvalue attains the minimum among all non-bipartite unicyclic graphs of order n with k pendant vertices. In this paper, we extend their results and determine the first three non-bipartite unicyclic graphs of order n with k pendant vertices ordering by least Q-eigenvalue.

Transformation of bipartite non-maximally entangled states into a ...

Indian Academy of Sciences (India)

We present two schemes for transforming bipartite non-maximally entangled states into a W state in cavity QED system, by using highly detuned interactions and the resonant interactions between two-level atoms and a single-mode cavity field. A tri-atom W state can be generated by adjusting the interaction times between ...

One-sided interval edge-colorings of bipartite graphs

DEFF Research Database (Denmark)

Casselgren, Carl Johan; Toft, Bjarne

2016-01-01

Let G be a bipartite graph with parts X and Y . An X-interval coloring of G is a proper edge coloring of G by integers such that the colors on the edges incident to any vertex in X form an interval. Denote by χ′int(G,X) the minimum k such that G has an X-interval coloring with k colors. In this p...

Phase-controlled localization and directed transport in an optical bipartite lattice.

Science.gov (United States)

Hai, Kuo; Luo, Yunrong; Lu, Gengbiao; Hai, Wenhua

2014-02-24

We investigate coherent control of a single atom interacting with an optical bipartite lattice via a combined high-frequency modulation. Our analytical results show that the quantum tunneling and dynamical localization can depend on phase difference between the modulation components, which leads to a different route for the coherent destruction of tunneling and a convenient phase-control method for stabilizing the system to implement the directed transport of atom. The similar directed transport and the phase-controlled quantum transition are revealed for the corresponding many-particle system. The results can be referable for experimentally manipulating quantum transport and transition of cold atoms in the tilted and shaken optical bipartite lattice or of analogical optical two-mode quantum beam splitter, and also can be extended to other optical and solid-state systems.

Identification and functional characterization of a novel bipartite nuclear localization sequence in ARID1A

Energy Technology Data Exchange (ETDEWEB)

Bateman, Nicholas W. [Women' s Health Integrated Research Center at Inova Health System, Gynecologic Cancer Center of Excellence, Annandale 22003, VA (United States); The John P. Murtha Cancer Center, Walter Reed National Military Medical Center, 8901 Wisconsin Avenue, Bethesda 20889, MD (United States); Shoji, Yutaka [Department of Obstetrics, Gynecology and Reproductive Biology, Michigan State University, Grand Rapids 49503, MI (United States); Conrads, Kelly A.; Stroop, Kevin D. [Women' s Health Integrated Research Center at Inova Health System, Gynecologic Cancer Center of Excellence, Annandale 22003, VA (United States); Hamilton, Chad A. [Women' s Health Integrated Research Center at Inova Health System, Gynecologic Cancer Center of Excellence, Annandale 22003, VA (United States); The John P. Murtha Cancer Center, Walter Reed National Military Medical Center, 8901 Wisconsin Avenue, Bethesda 20889, MD (United States); Gynecologic Oncology Service, Department of Obstetrics and Gynecology, Walter Reed National Military Medical Center, 8901 Wisconsin Ave, MD, Bethesda, 20889 (United States); Department of Obstetrics and Gynecology, Uniformed Services University of the Health Sciences, Bethesda 20814, MD (United States); Darcy, Kathleen M. [Women' s Health Integrated Research Center at Inova Health System, Gynecologic Cancer Center of Excellence, Annandale 22003, VA (United States); The John P. Murtha Cancer Center, Walter Reed National Military Medical Center, 8901 Wisconsin Avenue, Bethesda 20889, MD (United States); Maxwell, George L. [Department of Obstetrics and Gynecology, Inova Fairfax Hospital, Falls Church, VA 22042 (United States); Risinger, John I. [Department of Obstetrics, Gynecology and Reproductive Biology, Michigan State University, Grand Rapids 49503, MI (United States); and others

2016-01-01

AT-rich interactive domain-containing protein 1A (ARID1A) is a recently identified nuclear tumor suppressor frequently altered in solid tumor malignancies. We have identified a bipartite-like nuclear localization sequence (NLS) that contributes to nuclear import of ARID1A not previously described. We functionally confirm activity using GFP constructs fused with wild-type or mutant NLS sequences. We further show that cyto-nuclear localized, bipartite NLS mutant ARID1A exhibits greater stability than nuclear-localized, wild-type ARID1A. Identification of this undescribed functional NLS within ARID1A contributes vital insights to rationalize the impact of ARID1A missense mutations observed in patient tumors. - Highlights: • We have identified a bipartite nuclear localization sequence (NLS) in ARID1A. • Confirmation of the NLS was performed using GFP constructs. • NLS mutant ARID1A exhibits greater stability than wild-type ARID1A.

Bipartite entangled stabilizer mutually unbiased bases as maximum cliques of Cayley graphs

Science.gov (United States)

van Dam, Wim; Howard, Mark

2011-07-01

We examine the existence and structure of particular sets of mutually unbiased bases (MUBs) in bipartite qudit systems. In contrast to well-known power-of-prime MUB constructions, we restrict ourselves to using maximally entangled stabilizer states as MUB vectors. Consequently, these bipartite entangled stabilizer MUBs (BES MUBs) provide no local information, but are sufficient and minimal for decomposing a wide variety of interesting operators including (mixtures of) Jamiołkowski states, entanglement witnesses, and more. The problem of finding such BES MUBs can be mapped, in a natural way, to that of finding maximum cliques in a family of Cayley graphs. Some relationships with known power-of-prime MUB constructions are discussed, and observables for BES MUBs are given explicitly in terms of Pauli operators.

Bipartite entangled stabilizer mutually unbiased bases as maximum cliques of Cayley graphs

International Nuclear Information System (INIS)

Dam, Wim van; Howard, Mark

2011-01-01

We examine the existence and structure of particular sets of mutually unbiased bases (MUBs) in bipartite qudit systems. In contrast to well-known power-of-prime MUB constructions, we restrict ourselves to using maximally entangled stabilizer states as MUB vectors. Consequently, these bipartite entangled stabilizer MUBs (BES MUBs) provide no local information, but are sufficient and minimal for decomposing a wide variety of interesting operators including (mixtures of) Jamiolkowski states, entanglement witnesses, and more. The problem of finding such BES MUBs can be mapped, in a natural way, to that of finding maximum cliques in a family of Cayley graphs. Some relationships with known power-of-prime MUB constructions are discussed, and observables for BES MUBs are given explicitly in terms of Pauli operators.

Coupling-Induced Bipartite Pointer States in Arrays of Electron Billiards: Quantum Darwinism in Action?

Science.gov (United States)

Brunner, R.; Akis, R.; Ferry, D. K.; Kuchar, F.; Meisels, R.

2008-07-01

We discuss a quantum system coupled to the environment, composed of an open array of billiards (dots) in series. Beside pointer states occurring in individual dots, we observe sets of robust states which arise only in the array. We define these new states as bipartite pointer states, since they cannot be described in terms of simple linear combinations of robust single-dot states. The classical existence of bipartite pointer states is confirmed by comparing the quantum-mechanical and classical results. The ability of the robust states to create “offspring” indicates that quantum Darwinism is in action.

Tau can switch microtubule network organizations: from random networks to dynamic and stable bundles.

Science.gov (United States)

Prezel, Elea; Elie, Auréliane; Delaroche, Julie; Stoppin-Mellet, Virginie; Bosc, Christophe; Serre, Laurence; Fourest-Lieuvin, Anne; Andrieux, Annie; Vantard, Marylin; Arnal, Isabelle

2018-01-15

In neurons, microtubule networks alternate between single filaments and bundled arrays under the influence of effectors controlling their dynamics and organization. Tau is a microtubule bundler that stabilizes microtubules by stimulating growth and inhibiting shrinkage. The mechanisms by which tau organizes microtubule networks remain poorly understood. Here, we studied the self-organization of microtubules growing in the presence of tau isoforms and mutants. The results show that tau's ability to induce stable microtubule bundles requires two hexapeptides located in its microtubule-binding domain and is modulated by its projection domain. Site-specific pseudophosphorylation of tau promotes distinct microtubule organizations: stable single microtubules, stable bundles, or dynamic bundles. Disease-related tau mutations increase the formation of highly dynamic bundles. Finally, cryo-electron microscopy experiments indicate that tau and its variants similarly change the microtubule lattice structure by increasing both the protofilament number and lattice defects. Overall, our results uncover novel phosphodependent mechanisms governing tau's ability to trigger microtubule organization and reveal that disease-related modifications of tau promote specific microtubule organizations that may have a deleterious impact during neurodegeneration. © 2018 Prezel, Elie, et al. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

3-biplacement of bipartite graphs

Directory of Open Access Journals (Sweden)

Lech Adamus

2008-01-01

Full Text Available Let \\(G=(L,R;E\\ be a bipartite graph with color classes \\(L\\ and \\(R\\ and edge set \\(E\\. A set of two bijections \\(\\{\\varphi_1 , \\varphi_2\\}\\, \\(\\varphi_1 , \\varphi_2 :L \\cup R \\to L \\cup R\\, is said to be a \\(3\\-biplacement of \\(G\\ if \\(\\varphi_1(L= \\varphi_2(L = L\\ and \\(E \\cap \\varphi_1^*(E=\\emptyset\\, \\(E \\cap \\varphi_2^*(E=\\emptyset\\, \\(\\varphi_1^*(E \\cap \\varphi_2^*(E=\\emptyset\\, where \\(\\varphi_1^*\\, \\(\\varphi_2^*\\ are the maps defined on \\(E\\, induced by \\(\\varphi_1\\, \\(\\varphi_2\\, respectively. We prove that if \\(|L| = p\\, \\(|R| = q\\, \\(3 \\leq p \\leq q\\, then every graph \\(G=(L,R;E\\ of size at most \\(p\\ has a \\(3\\-biplacement.

Faster Double-Size Bipartite Multiplication out of Montgomery Multipliers

Science.gov (United States)

Yoshino, Masayuki; Okeya, Katsuyuki; Vuillaume, Camille

This paper proposes novel algorithms for computing double-size modular multiplications with few modulus-dependent precomputations. Low-end devices such as smartcards are usually equipped with hardware Montgomery multipliers. However, due to progresses of mathematical attacks, security institutions such as NIST have steadily demanded longer bit-lengths for public-key cryptography, making the multipliers quickly obsolete. In an attempt to extend the lifespan of such multipliers, double-size techniques compute modular multiplications with twice the bit-length of the multipliers. Techniques are known for extending the bit-length of classical Euclidean multipliers, of Montgomery multipliers and the combination thereof, namely bipartite multipliers. However, unlike classical and bipartite multiplications, Montgomery multiplications involve modulus-dependent precomputations, which amount to a large part of an RSA encryption or signature verification. The proposed double-size technique simulates double-size multiplications based on single-size Montgomery multipliers, and yet precomputations are essentially free: in an 2048-bit RSA encryption or signature verification with public exponent e=216+1, the proposal with a 1024-bit Montgomery multiplier is at least 1.5 times faster than previous double-size Montgomery multiplications.

Magnetic resonance imaging findings in bipartite medial cuneiform – a potential pitfall in diagnosis of midfoot injuries: a case series

Directory of Open Access Journals (Sweden)

Elias Ilan

2008-08-01

Full Text Available Abstract Introduction The bipartite medial cuneiform is an uncommon developmental osseous variant in the midfoot. To our knowledge, Magnetic Resonance Imaging (MRI characteristics of a non-symptomatic bipartite medial cuneiform have not been described in the orthopaedic literature. It is important for orthopaedic foot and ankle surgeons, musculoskeletal radiologists, and for podiatrists to identify this osseous variant as it may be mistakenly diagnosed as a fracture or not recognized as a source of non-traumatic or traumatic foot pain, which may sometimes even require surgical treatment. Case presentations In this report, we describe the characteristics of three cases of bipartite medial cuneiform on Magnetic Resonance Imaging and contrast its appearance to that of a medial cuneiform fracture. Conclusion A bipartite medial cuneiform is a rare developmental anomaly of the midfoot and may be the source of midfoot pain. Knowledge about its characteristic appearance on magnetic resonance imaging is important because it is a potential pitfall in diagnosis of midfoot injuries.

Bipartite fidelity and Loschmidt echo of the bosonic conformal interface

Science.gov (United States)

Zhou, Tianci; Lin, Mao

2017-12-01

We study the quantum quench problem for a class of bosonic conformal interfaces by computing the Loschmidt echo and the bipartite fidelity. The quench can be viewed as a sudden change of boundary conditions parametrized by θ when connecting two one-dimensional critical systems. They are classified by S (θ ) matrices associated with the current scattering processes on the interface. The resulting Loschmidt echo of the quench has long time algebraic decay t-α, whose exponent also appears in the finite size bipartite fidelity as L-α/2. We perform analytic and numerical calculations of the exponent α , and find that it has a quadratic dependence on the change of θ if the prior and post-quench boundary conditions are of the same type of S , while remaining 1/4 otherwise. Possible physical realizations of these interfaces include, for instance, connecting different quantum wires (Luttinger liquids), quench of the topological phase edge states, etc., and the exponent can be detected in an x-ray edge singularity-type experiment.

Bipartite hallucal sesamoid bones: relationship with hallux valgus and metatarsal index

Energy Technology Data Exchange (ETDEWEB)

Munuera, Pedro V.; Dominguez, Gabriel [University of Seville, Department of Podiatrics, Seville (Spain); Centro Docente de Fisioterapia y Podologia, Departamento de Podologia, Seville (Spain); Reina, Maria; Trujillo, Piedad [Centro Docente de Fisioterapia y Podologia, Departamento de Podologia, Seville (Spain)

2007-11-15

The objective was to relate the incidence of the partition of the hallucal sesamoid bones to the size of the first metatarsal and the hallux valgus deformity. In a sample of 474 radiographs, the frequency of appearance of bipartite sesamoids was studied. The length and relative protrusion of the first metatarsal, and the hallux abductus angle, were measured and compared between the feet with and without sesamoid partition. The results showed that 14.6% of the feet studied had at least one partite sesamoid, that the sesamoid most frequently divided was the medial, and that unilateral partition was the most common. No difference was found in the incidence of partite sesamoids between men and women, or between left and right feet. Protrusion and length of the first metatarsal are greater in feet with partite sesamoids than in feet without this condition. A significantly higher incidence of bipartite medial sesamoid was obtained in feet with hallux valgus compared with normal feet. (orig.)

Bipartite hallucal sesamoid bones: relationship with hallux valgus and metatarsal index

International Nuclear Information System (INIS)

Munuera, Pedro V.; Dominguez, Gabriel; Reina, Maria; Trujillo, Piedad

2007-01-01

The objective was to relate the incidence of the partition of the hallucal sesamoid bones to the size of the first metatarsal and the hallux valgus deformity. In a sample of 474 radiographs, the frequency of appearance of bipartite sesamoids was studied. The length and relative protrusion of the first metatarsal, and the hallux abductus angle, were measured and compared between the feet with and without sesamoid partition. The results showed that 14.6% of the feet studied had at least one partite sesamoid, that the sesamoid most frequently divided was the medial, and that unilateral partition was the most common. No difference was found in the incidence of partite sesamoids between men and women, or between left and right feet. Protrusion and length of the first metatarsal are greater in feet with partite sesamoids than in feet without this condition. A significantly higher incidence of bipartite medial sesamoid was obtained in feet with hallux valgus compared with normal feet. (orig.)

Dynamics of slow and fast systems on complex networks

Indian Academy of Sciences (India)

synchrony in oscillator networks [10]. In power grids and the Internet it has been shown that heterogeneity due to different loads on nodes can cause a cascade ..... from that of the bipartite one even when they start from the same initial conditions. In the network of 3 sys- tems the configurations 3 and 4 exhibited frequency.

On the balanced case of the Brualdi-Shen conjecture on 4-cycle decompositions of Eulerian bipartite tournaments

Directory of Open Access Journals (Sweden)

Rafael Del Valle Vega

2015-10-01

Full Text Available The Brualdi-Shen Conjecture on Eulerian Bipartite Tournaments states that any such graph can be decomposed into oriented 4-cycles. In this article we prove the balanced case of the mentioned conjecture. We show that for any $2n\\times 2n$ bipartite graph $G=(U\\cup V, E$ in which each vertex has $n$-neighbors with biadjacency matrix $M$ (or its transpose there is a proper edge coloring of a column permutation of $M$ denoted $M^{\\sigma}$ in which the nonzero entries of each of the $first$ $n$ columns are colored with elements from the set $\\{n+1, n+2, \\ldots, 2n\\}$ and the nonzero entries of each of the $last$  $n$ columns are colored with elements from the set $\\{1, 2, \\ldots, n\\}$ and if the nonzero entry $M^{\\sigma}_{r,j}$ is colored with color $i$ then $M^{\\sigma}_{r,i}$ must be a zero entry. Such a coloring will induce an oriented 4-cycle decomposition of the bipartite tournament corresponding to $M$. We achieve this by constructing an euler tour on the bipartite tournament which avoids traversing both pair of edges of any two internally disjoint $s$-$t$ 2-paths consecutively, where $s$ and $t$ belong to $V$.

Convergence analysis of directed signed networks via an M-matrix approach

Science.gov (United States)

Meng, Deyuan

2018-04-01

This paper aims at solving convergence problems on directed signed networks with multiple nodes, where interactions among nodes are described by signed digraphs. The convergence analysis is achieved by matrix-theoretic and graph-theoretic tools, in which M-matrices play a central role. The fundamental digon sign-symmetry assumption upon signed digraphs can be removed with the proposed analysis approach. Furthermore, necessary and sufficient conditions are established for semi-positive and positive stabilities of Laplacian matrices of signed digraphs, respectively. A benefit of this result is that given strong connectivity, a directed signed network can achieve bipartite consensus (or state stability) if and only if the signed digraph associated with it is structurally balanced (or unbalanced). If the interactions between nodes are described by a signed digraph only with spanning trees, a directed signed network can achieve interval bipartite consensus (or state stability) if and only if the signed digraph contains a structurally balanced (or unbalanced) rooted subgraph. Simulations are given to illustrate the developed results by considering signed networks associated with digon sign-unsymmetric signed digraphs.

There is no non-zero stable fixed point for dense networks in the homogeneous Kuramoto model

International Nuclear Information System (INIS)

Taylor, Richard

2012-01-01

This paper is concerned with the existence of multiple stable fixed point solutions of the homogeneous Kuramoto model. We develop a necessary condition for the existence of stable fixed points for the general network Kuramoto model. This condition is applied to show that for sufficiently dense n-node networks, with node degrees at least 0.9395(n−1), the homogeneous (equal frequencies) model has only one stable fixed point solution over the full space of phase angles in the range −π to π. This is the zero fixed point solution defined by all phase angle differences being zero. This result, together with existing research, proves a conjecture of Verwoerd and Mason (2007 Proc. of the American Control Conf. pp 4613–8) that for the complete network and the homogeneous model, the zero fixed point has a basin of attraction consisting of the entire space minus a set of measure zero. The necessary conditions are also tested to see how close to sufficiency they might be by applying them to a class of regular degree networks studied by Wiley et al (2006 Chaos 16 015103). (paper)

Tripartite to Bipartite Entanglement Transformations and Polynomial Identity Testing

OpenAIRE

Chitambar, Eric; Duan, Runyao; Shi, Yaoyun

2009-01-01

We consider the problem of deciding if a given three-party entangled pure state can be converted, with a non-zero success probability, into a given two-party pure state through local quantum operations and classical communication. We show that this question is equivalent to the well-known computational problem of deciding if a multivariate polynomial is identically zero. Efficient randomized algorithms developed to study the latter can thus be applied to the question of tripartite to bipartit...

The effect of habitat modification on plant-pollinator network

Science.gov (United States)

Aminatun, Tien; Putra, Nugroho Susetya

2017-08-01

The research aimed to determine; (1) the mutualism interaction pattern of plant-pollinator on several habitat modifications; and (2) the habitat modification which showed the most stable pattern of interaction. The study was conducted in one planting season with 20 plots which each plot had 2x2 m2 width and 2 m spacing among plots, and each plot was planted with the same variety of tomato plants, i.e. "intan". Nitrogen manipulation treatment was conducted with four kinds of fertilizers, i.e. NPK (code PU), compost (code PKM), vermicompost (code PC), and manure (code PK). Each treatment had 5 plot replications. We observed the growth of tomato plants, weed and arthropod populationstwo weekly while pollinator visitation twice a week during tomato plant flowering with counting population and visitation frequence of each pollinator on each sample of tomato plants. The nectar of tomato plant flower of each treatment was tested in laboratory to see its reducing sugar and sucrose. Oganic matter and nitrogen of the soil samples of each treatment were tested in laboratory in the beginning and the end of this research. We analized the plant-pollinator network with bipartite program in R-statistics, and the abiotic and other biotic factors with descriptive analysis. The results of the research were; (1) the mutualism interaction pattern of plant-pollinator network of four treatments were varied, and (2) The pattern of plant-pollinator network of NPK fertilizer treatment showed the more stable interaction based on analysis of interaction evenness, Shannon diversity, frequency and longevity of pollinator visitation.

Ultra-stable long distance optical frequency distribution using the Internet fiber network.

Science.gov (United States)

Lopez, Olivier; Haboucha, Adil; Chanteau, Bruno; Chardonnet, Christian; Amy-Klein, Anne; Santarelli, Giorgio

2012-10-08

We report an optical link of 540 km for ultrastable frequency distribution over the Internet fiber network. The stable frequency optical signal is processed enabling uninterrupted propagation on both directions. The robustness and the performance of the link are enhanced by a cost effective fully automated optoelectronic station. This device is able to coherently regenerate the return optical signal with a heterodyne optical phase locking of a low noise laser diode. Moreover the incoming signal polarization variation are tracked and processed in order to maintain beat note amplitudes within the operation range. Stable fibered optical interferometer enables optical detection of the link round trip phase signal. The phase-noise compensated link shows a fractional frequency instability in 10 Hz bandwidth of 5 × 10(-15) at one second measurement time and 2 × 10(-19) at 30,000 s. This work is a significant step towards a sustainable wide area ultrastable optical frequency distribution and comparison network.

From standard alpha-stable Lévy motions to horizontal visibility networks: dependence of multifractal and Laplacian spectrum

Science.gov (United States)

Zou, Hai-Long; Yu, Zu-Guo; Anh, Vo; Ma, Yuan-Lin

2018-05-01

In recent years, researchers have proposed several methods to transform time series (such as those of fractional Brownian motion) into complex networks. In this paper, we construct horizontal visibility networks (HVNs) based on the -stable Lévy motion. We aim to study the relations of multifractal and Laplacian spectrum of transformed networks on the parameters and of the -stable Lévy motion. First, we employ the sandbox algorithm to compute the mass exponents and multifractal spectrum to investigate the multifractality of these HVNs. Then we perform least squares fits to find possible relations of the average fractal dimension , the average information dimension and the average correlation dimension against using several methods of model selection. We also investigate possible dependence relations of eigenvalues and energy on , calculated from the Laplacian and normalized Laplacian operators of the constructed HVNs. All of these constructions and estimates will help us to evaluate the validity and usefulness of the mappings between time series and networks, especially between time series of -stable Lévy motions and HVNs.

Predicting non-linear dynamics by stable local learning in a recurrent spiking neural network.

Science.gov (United States)

Gilra, Aditya; Gerstner, Wulfram

2017-11-27

The brain needs to predict how the body reacts to motor commands, but how a network of spiking neurons can learn non-linear body dynamics using local, online and stable learning rules is unclear. Here, we present a supervised learning scheme for the feedforward and recurrent connections in a network of heterogeneous spiking neurons. The error in the output is fed back through fixed random connections with a negative gain, causing the network to follow the desired dynamics. The rule for Feedback-based Online Local Learning Of Weights (FOLLOW) is local in the sense that weight changes depend on the presynaptic activity and the error signal projected onto the postsynaptic neuron. We provide examples of learning linear, non-linear and chaotic dynamics, as well as the dynamics of a two-link arm. Under reasonable approximations, we show, using the Lyapunov method, that FOLLOW learning is uniformly stable, with the error going to zero asymptotically.

Looking for chemical reaction networks exhibiting a drift along a manifold of marginally stable states.

Science.gov (United States)

Brogioli, Doriano

2013-02-07

I recently reported some examples of mass-action equations that have a continuous manifold of marginally stable stationary states [Brogioli, D., 2010. Marginally stable chemical systems as precursors of life. Phys. Rev. Lett. 105, 058102; Brogioli, D., 2011. Marginal stability in chemical systems and its relevance in the origin of life. Phys. Rev. E 84, 031931]. The corresponding chemical reaction networks show nonclassical effects, i.e. a violation of the mass-action equations, under the effect of the concentration fluctuations: the chemical system drifts along the marginally stable states. I proposed that this effect is potentially involved in abiogenesis. In the present paper, I analyze the mathematical properties of mass-action equations of marginally stable chemical reaction networks. The marginal stability implies that the mass-action equations obey some conservation law; I show that the mathematical properties of the conserved quantity characterize the motion along the marginally stable stationary state manifold, i.e. they allow to predict if the fluctuations give rise to a random walk or a drift under the effect of concentration fluctuations. Moreover, I show that the presence of the drift along the manifold of marginally stable stationary-states is a critical property, i.e. at least one of the reaction constants must be fine tuned in order to obtain the drift. Copyright © 2012 Elsevier Ltd. All rights reserved.

Catalytic transformations for bipartite pure states

International Nuclear Information System (INIS)

Turgut, S

2007-01-01

Entanglement catalysis is a phenomenon that usually enhances the conversion probability in the transformation of entangled states by the temporary involvement of another entangled state (so-called catalyst), where after the process is completed the catalyst is returned to the same state. For some pairs of bipartite pure entangled states, catalysis enables a transformation with unit probability of success, in which case the respective Schmidt coefficients of the states are said to satisfy the trumping relation, a mathematical relation which is an extension of the majorization relation. This paper provides all necessary and sufficient conditions for the trumping and two other associated relations. Using these conditions, the least upper bound of conversion probabilities using catalysis is also obtained. Moreover, best conversion ratios achievable with catalysis are found for transformations involving many copies of states

Detecting quantum critical points using bipartite fluctuations.

Science.gov (United States)

Rachel, Stephan; Laflorencie, Nicolas; Song, H Francis; Le Hur, Karyn

2012-03-16

We show that the concept of bipartite fluctuations F provides a very efficient tool to detect quantum phase transitions in strongly correlated systems. Using state-of-the-art numerical techniques complemented with analytical arguments, we investigate paradigmatic examples for both quantum spins and bosons. As compared to the von Neumann entanglement entropy, we observe that F allows us to find quantum critical points with much better accuracy in one dimension. We further demonstrate that F can be successfully applied to the detection of quantum criticality in higher dimensions with no prior knowledge of the universality class of the transition. Promising approaches to experimentally access fluctuations are discussed for quantum antiferromagnets and cold gases.

Quantum correlations for bipartite continuous-variable systems

Science.gov (United States)

Ma, Ruifen; Hou, Jinchuan; Qi, Xiaofei; Wang, Yangyang

2018-04-01

Two quantum correlations Q and Q_P for (m+n)-mode continuous-variable systems are introduced in terms of average distance between the reduced states under the local Gaussian positive operator-valued measurements, and analytical formulas of these quantum correlations for bipartite Gaussian states are provided. It is shown that the product states do not contain these quantum correlations, and conversely, all (m+n)-mode Gaussian states with zero quantum correlations are product states. Generally, Q≥ Q_{P}, but for the symmetric two-mode squeezed thermal states, these quantum correlations are the same and a computable formula is given. In addition, Q is compared with Gaussian geometric discord for symmetric squeezed thermal states.

Discord as a quantum resource for bi-partite communication

International Nuclear Information System (INIS)

Chrzanowski, Helen M.; Assad, Syed M.; Symul, Thomas; Lam, Ping Koy; Gu, Mile; Modi, Kavan; Vedral, Vlatko; Ralph, Timothy C.

2014-01-01

Coherent interactions that generate negligible entanglement can still exhibit unique quantum behaviour. This observation has motivated a search beyond entanglement for a complete description of all quantum correlations. Quantum discord is a promising candidate. Here, we experimentally demonstrate that under certain measurement constraints, discord between bipartite systems can be consumed to encode information that can only be accessed by coherent quantum interactions. The inability to access this information by any other means allows us to use discord to directly quantify this ‘quantum advantage’

Bi-directional astrocytic regulation of neuronal activity within a network

Directory of Open Access Journals (Sweden)

Susan Yu Gordleeva

2012-11-01

Full Text Available The concept of a tripartite synapse holds that astrocytes can affect both the pre- and postsynaptic compartments through the Ca2+-dependent release of gliotransmitters. Because astrocytic Ca2+ transients usually last for a few seconds, we assumed that astrocytic regulation of synaptic transmission may also occur on the scale of seconds. Here, we considered the basic physiological functions of tripartite synapses and investigated astrocytic regulation at the level of neural network activity. The firing dynamics of individual neurons in a spontaneous firing network was described by the Hodgkin-Huxley model. The neurons received excitatory synaptic input driven by the Poisson spike train with variable frequency. The mean field concentration of the released neurotransmitter was used to describe the presynaptic dynamics. The amplitudes of the excitatory postsynaptic currents (PSCs obeyed the gamma distribution law. In our model, astrocytes depressed the presynaptic release and enhanced the postsynaptic currents. As a result, low frequency synaptic input was suppressed while high frequency input was amplified. The analysis of the neuron spiking frequency as an indicator of network activity revealed that tripartite synaptic transmission dramatically changed the local network operation compared to bipartite synapses. Specifically, the astrocytes supported homeostatic regulation of the network activity by increasing or decreasing firing of the neurons. Thus, the astrocyte activation may modulate a transition of neural network into bistable regime of activity with two stable firing levels and spontaneous transitions between them.

Nonclassicality and entanglement criteria for bipartite optical fields characterized by quadratic detectors

Czech Academy of Sciences Publication Activity Database

Peřina Jr., J.; Arkhipov, I.I.; Michálek, Václav; Haderka, Ondřej

2017-01-01

Roč. 96, č. 4 (2017), s. 1-15, č. článku 043845. ISSN 2469-9926 Institutional support: RVO:68378271 Keywords : parametric down-conversion * photon statistic * bipartite optical fields * quadratic detectors Subject RIV: BH - Optics, Masers, Lasers OBOR OECD: Optics (including laser optics and quantum optics) Impact factor: 2.925, year: 2016

Forbidden regimes in the distribution of bipartite quantum correlations due to multiparty entanglement

Energy Technology Data Exchange (ETDEWEB)

Kumar, Asutosh [Harish-Chandra Research Institute, Chhatnag Road, Jhunsi, Allahabad 211019 (India); Homi Bhabha National Institute, Anushaktinagar, Mumbai 400094 (India); Dhar, Himadri Shekhar [Harish-Chandra Research Institute, Chhatnag Road, Jhunsi, Allahabad 211019 (India); Institute for Theoretical Physics, Vienna University of Technology, Wiedner Hauptstraße 8-10/136, A-1040 Vienna (Austria); Prabhu, R. [Harish-Chandra Research Institute, Chhatnag Road, Jhunsi, Allahabad 211019 (India); Department of Physics, Indian Institute of Technology Patna, Patna 800013 (India); Sen, Aditi [Harish-Chandra Research Institute, Chhatnag Road, Jhunsi, Allahabad 211019 (India); Homi Bhabha National Institute, Anushaktinagar, Mumbai 400094 (India); Sen, Ujjwal, E-mail: ujjwal@hri.res.in [Harish-Chandra Research Institute, Chhatnag Road, Jhunsi, Allahabad 211019 (India); Homi Bhabha National Institute, Anushaktinagar, Mumbai 400094 (India)

2017-05-25

Monogamy is a nonclassical property that limits the distribution of quantum correlation among subparts of a multiparty system. We show that monogamy scores for different quantum correlation measures are bounded above by functions of genuine multipartite entanglement for a large majority of pure multiqubit states. The bound is universal for all three-qubit pure states. We derive necessary conditions to characterize the states that violate the bound, which can also be observed by numerical simulation for a small set of states, generated Haar uniformly. The results indicate that genuine multipartite entanglement restricts the distribution of bipartite quantum correlations in a multiparty system. - Highlights: • Monogamy is an intrinsic property of several quantum characteristics including entanglement. • It is possible to quantify monogamy by using the so-called monogamy scores. • Genuine multisite entanglement can be used to bound monogamy scores. • Distribution of bipartite entanglement in a system is, therefore, restricted by its multisite entanglement content.

Vulnerability analysis and passenger source prediction in urban rail transit networks.

Directory of Open Access Journals (Sweden)

Junjie Wang

Full Text Available Based on large-scale human mobility data collected in San Francisco and Boston, the morning peak urban rail transit (URT ODs (origin-destination matrix were estimated and the most vulnerable URT segments, those capable of causing the largest service interruptions, were identified. In both URT networks, a few highly vulnerable segments were observed. For this small group of vital segments, the impact of failure must be carefully evaluated. A bipartite URT usage network was developed and used to determine the inherent connections between urban rail transits and their passengers' travel demands. Although passengers' origins and destinations were easy to locate for a large number of URT segments, a few show very complicated spatial distributions. Based on the bipartite URT usage network, a new layer of the understanding of a URT segment's vulnerability can be achieved by taking the difficulty of addressing the failure of a given segment into account. Two proof-of-concept cases are described here: Possible transfer of passenger flow to the road network is here predicted in the cases of failures of two representative URT segments in San Francisco.

Some Congruence Properties of a Restricted Bipartition Function cN(n

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Nipen Saikia

2016-01-01

Full Text Available Let cN(n denote the number of bipartitions (λ,μ of a positive integer n subject to the restriction that each part of μ is divisible by N. In this paper, we prove some congruence properties of the function cN(n for N=7, 11, and 5l, for any integer l≥1, by employing Ramanujan’s theta-function identities.

Topology of the Erasmus student mobility network

Science.gov (United States)

Derzsi, A.; Derzsy, N.; Káptalan, E.; Néda, Z.

2011-07-01

The collaboration network generated by the Erasmus student mobilities in the year 2003 is analyzed and modeled. Nodes of this bipartite network are European universities and links are the Erasmus mobilities between these universities. This network is a complex directed and weighted graph. The non-directed and non-weighted projection of this network does not exhibit a scale-free nature, but proves to be a small-word type random network with a giant component. The connectivity data indicates an exponential degree distribution, a relatively high clustering coefficient and a small radius. It can be easily modeled by using a simple configuration model and arguing the exponential degree distribution. The weighted and directed version of the network can also be described by means of simple random network models.

Synchronisation of networked Kuramoto oscillators under stable Lévy noise

Science.gov (United States)

Kalloniatis, Alexander C.; Roberts, Dale O.

2017-01-01

We study the Kuramoto model on several classes of network topologies examining the dynamics under the influence of Lévy noise. Such noise exhibits heavier tails than Gaussian and allows us to understand how 'shocks' influence the individual oscillator and collective system behaviour. Skewed α-stable Lévy noise, equivalent to fractional diffusion perturbations, are considered. We perform numerical simulations for Erdős-Rényi (ER) and Barabási-Albert (BA) scale free networks of size N = 1000 while varying the Lévy index α for the noise. We find that synchrony now assumes a surprising variety of forms, not seen for Gaussian-type noise, and changing with α: a noise-generated drift, a smooth α dependence of the point of cross-over of ER and BA networks in the degree of synchronisation, and a severe loss of synchronisation at low values of α. We also show that this robustness of the BA network across most values of α can also be understood as a consequence of the Laplacian of the graph working within the fractional Fokker-Planck equation of the linearised system, close to synchrony, with both eigenvalues and eigenvectors alternately contributing in different regimes of α.

The players may change but the game remains: network analyses of ruminal microbiomes suggest taxonomic differences mask functional similarity

OpenAIRE

Taxis, Tasia M.; Wolff, Sara; Gregg, Sarah J.; Minton, Nicholas O.; Zhang, Chiqian; Dai, Jingjing; Schnabel, Robert D.; Taylor, Jeremy F.; Kerley, Monty S.; Pires, J. Chris; Lamberson, William R.; Conant, Gavin C.

2015-01-01

By mapping translated metagenomic reads to a microbial metabolic network, we show that ruminal ecosystems that are rather dissimilar in their taxonomy can be considerably more similar at the metabolic network level. Using a new network bi-partition approach for linking the microbial network to a bovine metabolic network, we observe that these ruminal metabolic networks exhibit properties consistent with distinct metabolic communities producing similar outputs from common inputs. For instance,...

Controllability of Train Service Network

Directory of Open Access Journals (Sweden)

Xuelei Meng

2015-01-01

Full Text Available Train service network is a network form of train service plan. The controllability of the train service plan determines the recovery possibility of the train service plan in emergencies. We first build the small-world model for train service network and analyze the scale-free character of it. Then based on the linear network controllability theory, we discuss the LB model adaptability in train service network controllability analysis. The LB model is improved and we construct the train service network and define the connotation of the driver nodes based on the immune propagation and cascading failure in the train service network. An algorithm to search for the driver nodes, turning the train service network into a bipartite graph, is proposed and applied in the train service network. We analyze the controllability of the train service network of China with the method and the results of the computing case prove the feasibility of it.

iBGP: A Bipartite Graph Propagation Approach for Mobile Advertising Fraud Detection

Directory of Open Access Journals (Sweden)

Jinlong Hu

2017-01-01

Full Text Available Online mobile advertising plays a vital financial role in supporting free mobile apps, but detecting malicious apps publishers who generate fraudulent actions on the advertisements hosted on their apps is difficult, since fraudulent traffic often mimics behaviors of legitimate users and evolves rapidly. In this paper, we propose a novel bipartite graph-based propagation approach, iBGP, for mobile apps advertising fraud detection in large advertising system. We exploit the characteristics of mobile advertising user’s behavior and identify two persistent patterns: power law distribution and pertinence and propose an automatic initial score learning algorithm to formulate both concepts to learn the initial scores of non-seed nodes. We propose a weighted graph propagation algorithm to propagate the scores of all nodes in the user-app bipartite graphs until convergence. To extend our approach for large-scale settings, we decompose the objective function of the initial score learning model into separate one-dimensional problems and parallelize the whole approach on an Apache Spark cluster. iBGP was applied on a large synthetic dataset and a large real-world mobile advertising dataset; experiment results demonstrate that iBGP significantly outperforms other popular graph-based propagation methods.

Multipartite-to-bipartite entanglement transformations and polynomial identity testing

International Nuclear Information System (INIS)

Chitambar, Eric; Duan Runyao; Shi Yaoyun

2010-01-01

We consider the problem of deciding if some multiparty entangled pure state can be converted, with a nonzero success probability, into a given bipartite pure state shared between two specified parties through local quantum operations and classical communication. We show that this question is equivalent to the well-known computational problem of deciding if a multivariate polynomial is identically zero. Efficient randomized algorithms developed to study the latter can thus be applied to our question. As a result, a given transformation is possible if and only if it is generically attainable by a simple randomized protocol.

Improving the recommender algorithms with the detected communities in bipartite networks

Science.gov (United States)

Zhang, Peng; Wang, Duo; Xiao, Jinghua

2017-04-01

Recommender system offers a powerful tool to make information overload problem well solved and thus gains wide concerns of scholars and engineers. A key challenge is how to make recommendations more accurate and personalized. We notice that community structures widely exist in many real networks, which could significantly affect the recommendation results. By incorporating the information of detected communities in the recommendation algorithms, an improved recommendation approach for the networks with communities is proposed. The approach is examined in both artificial and real networks, the results show that the improvement on accuracy and diversity can be 20% and 7%, respectively. This reveals that it is beneficial to classify the nodes based on the inherent properties in recommender systems.

An Energy Efficient Stable Election-Based Routing Algorithm for Wireless Sensor Networks

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Weiwei Yuan

2013-10-01

Full Text Available Sensor nodes usually have limited energy supply and they are impractical to recharge. How to balance traffic load in sensors in order to increase network lifetime is a very challenging research issue. Many clustering algorithms have been proposed recently for wireless sensor networks (WSNs. However, sensor networks with one fixed sink node often suffer from a hot spots problem since nodes near sinks have more traffic burden to forward during a multi-hop transmission process. The use of mobile sinks has been shown to be an effective technique to enhance network performance features such as latency, energy efficiency, network lifetime, etc. In this paper, a modified Stable Election Protocol (SEP, which employs a mobile sink, has been proposed for WSNs with non-uniform node distribution. The decision of selecting cluster heads by the sink is based on the minimization of the associated additional energy and residual energy at each node. Besides, the cluster head selects the shortest path to reach the sink between the direct approach and the indirect approach with the use of the nearest cluster head. Simulation results demonstrate that our algorithm has better performance than traditional routing algorithms, such as LEACH and SEP.

The study of entanglement and teleportation of the harmonic oscillator bipartite coherent states

Directory of Open Access Journals (Sweden)

A Rabeie and

2015-01-01

Full Text Available In this paper, we reproduce the harmonic oscillator bipartite coherent states with imperfect cloning of coherent states. We show that if these entangled coherent states are embedded in a vacuum environment, their entanglement is degraded but not totally lost . Also, the optimal fidelity of these states is worked out for investigating their teleportation

Asymptotic adaptive bipartite entanglement-distillation protocol

International Nuclear Information System (INIS)

Hostens, Erik; Dehaene, Jeroen; De Moor, Bart

2006-01-01

We present an asymptotic bipartite entanglement-distillation protocol that outperforms all existing asymptotic schemes. This protocol is based on the breeding protocol with the incorporation of two-way classical communication. Like breeding, the protocol starts with an infinite number of copies of a Bell-diagonal mixed state. Breeding can be carried out as successive stages of partial information extraction, yielding the same result: one bit of information is gained at the cost (measurement) of one pure Bell state pair (ebit). The basic principle of our protocol is at every stage to replace measurements on ebits by measurements on a finite number of copies, whenever there are two equiprobable outcomes. In that case, the entropy of the global state is reduced by more than one bit. Therefore, every such replacement results in an improvement of the protocol. We explain how our protocol is organized as to have as many replacements as possible. The yield is then calculated for Werner states

Environmental controls on stable isotopes of precipitation in Lanzhou, China: An enhanced network at city scale.

Science.gov (United States)

Chen, Fenli; Zhang, Mingjun; Wang, Shengjie; Qiu, Xue; Du, Mingxia

2017-12-31

Stable hydrogen and oxygen isotopes in precipitation are very sensitive to environmental changes, and can record evolution of water cycle. The Lanzhou city in northwestern China is jointly influenced by the monsoon and westerlies, which is considered as a vital platform to investigate the moisture regime for this region. Since 2011, an observation network of stable isotopes in precipitation was established across the city, and four stations were included in the network. In 2013, six more sampling stations were added, and the enhanced network might provide more meaningful information on spatial incoherence and synoptic process. This study focused on the variations of stable isotopes (δ 18 O and δD) in precipitation and the environmental controls based on the 1432 samples in this enhanced network from April 2011 to October 2014. The results showed that the precipitation isotopes had great spatial diversity, and the neighboring stations may present large difference in δD and δ 18 O. Based on the observation at ten sampling sites, an isoscape in precipitation was calculated, and the method is useful to produce isoscape for small domains. The temperature effect and amount effect was reconsidered based on the dataset. Taking meteorological parameters (temperature, precipitation amount, relative humidity, water vapor pressure and dew point temperature) as variables in a multi-linear regression, the result of coefficients for these meteorological parameters were calculated. Some cases were also involved in this study, and the isotopic characteristics during one event or continuous days were used to understand the environmental controls on precipitation isotopes. Copyright © 2017 Elsevier B.V. All rights reserved.

Disentangling the co-structure of multilayer interaction networks: degree distribution and module composition in two-layer bipartite networks.

Science.gov (United States)

Astegiano, Julia; Altermatt, Florian; Massol, François

2017-11-13

Species establish different interactions (e.g. antagonistic, mutualistic) with multiple species, forming multilayer ecological networks. Disentangling network co-structure in multilayer networks is crucial to predict how biodiversity loss may affect the persistence of multispecies assemblages. Existing methods to analyse multilayer networks often fail to consider network co-structure. We present a new method to evaluate the modular co-structure of multilayer networks through the assessment of species degree co-distribution and network module composition. We focus on modular structure because of its high prevalence among ecological networks. We apply our method to two Lepidoptera-plant networks, one describing caterpillar-plant herbivory interactions and one representing adult Lepidoptera nectaring on flowers, thereby possibly pollinating them. More than 50% of the species established either herbivory or visitation interactions, but not both. These species were over-represented among plants and lepidopterans, and were present in most modules in both networks. Similarity in module composition between networks was high but not different from random expectations. Our method clearly delineates the importance of interpreting multilayer module composition similarity in the light of the constraints imposed by network structure to predict the potential indirect effects of species loss through interconnected modular networks.

Anderson localization in bipartite lattices

International Nuclear Information System (INIS)

Fabrizio, Michele; Castellani, Claudio

2000-01-01

We study the localization properties of a disordered tight-binding Hamiltonian on a generic bipartite lattice close to the band center. By means of a fermionic replica trick method, we derive the effective non-linear σ-model describing the diffusive modes, which we analyse by using the Wilson-Polyakov renormalization group. In addition to the standard parameters which define the non-linear σ-model, namely, the conductance and the external frequency, a new parameter enters, which may be related to the fluctuations of the staggered density of states. We find that, when both the regular hopping and the disorder only couple one sublattice to the other, the quantum corrections to the Kubo conductivity vanish at the band center, thus implying the existence of delocalized states. In two dimensions, the RG equations predict that the conductance flows to a finite value, while both the density of states and the staggered density of states fluctuations diverge. In three dimensions, we find that, sufficiently close to the band center, all states are extended, independently of the disorder strength. We also discuss the role of various symmetry breaking terms, as a regular hopping between same sublattices, or an on-site disorder

Anderson localization in bipartite lattices

International Nuclear Information System (INIS)

Fabrizio, M.; Castellani, C.

2000-04-01

We study the localization properties of a disordered tight-binding Hamiltonian on a generic bipartite lattice close to the band center. By means of a fermionic replica trick method, we derive the effective non-linear σ-model describing the diffusive modes, which we analyse by using the Wilson-Polyakov renormalization group. In addition to the standard parameters which define the non-linear σ-model, namely the conductance and the external frequency, a new parameter enters, which may be related to the fluctuations of the staggered density of states. We find that, when both the regular hopping and the disorder only couple one sublattice to the other, the quantum corrections to the Kubo conductivity vanish at the band center, thus implying the existence of delocalized states. In two dimensions, the RG equations predict that the conductance flows to a finite value, while both the density of states and the staggered density of states fluctuations diverge. In three dimensions, we find that, sufficiently close to the band center, all states are extended, independently of the disorder strength. We also discuss the role of various symmetry breaking terms, as a regular hopping between same sublattices, or an on-site disorder. (author)

iBGP: A Bipartite Graph Propagation Approach for Mobile Advertising Fraud Detection

OpenAIRE

Hu, Jinlong; Liang, Junjie; Dong, Shoubin

2017-01-01

Online mobile advertising plays a vital financial role in supporting free mobile apps, but detecting malicious apps publishers who generate fraudulent actions on the advertisements hosted on their apps is difficult, since fraudulent traffic often mimics behaviors of legitimate users and evolves rapidly. In this paper, we propose a novel bipartite graph-based propagation approach, iBGP, for mobile apps advertising fraud detection in large advertising system. We exploit the characteristics of m...

Nonadditivity of quantum and classical capacities for entanglement breaking multiple-access channels and the butterfly network

International Nuclear Information System (INIS)

Grudka, Andrzej; Horodecki, Pawel

2010-01-01

We analyze quantum network primitives which are entanglement breaking. We show superadditivity of quantum and classical capacity regions for quantum multiple-access channels and the quantum butterfly network. Since the effects are especially visible at high noise they suggest that quantum information effects may be particularly helpful in the case of the networks with occasional high noise rates. The present effects provide a qualitative borderline between superadditivities of bipartite and multipartite systems.

Bipartite field theories: from D-brane probes to scattering amplitudes

Science.gov (United States)

Franco, Sebastián

2012-11-01

We introduce and initiate the investigation of a general class of 4d, {N}=1 quiver gauge theories whose Lagrangian is defined by a bipartite graph on a Riemann surface, with or without boundaries. We refer to such class of theories as Bipartite Field Theories (BFTs). BFTs underlie a wide spectrum of interesting physical systems, including: D3-branes probing toric Calabi-Yau 3-folds, their mirror configurations of D6-branes, cluster integrable systems in (0 + 1) dimensions and leading singularities in scattering amplitudes for {N}=4 SYM. While our discussion is fully general, we focus on models that are relevant for scattering amplitudes. We investigate the BFT perspective on graph modifications, the emergence of Calabi-Yau manifolds (which arise as the master and moduli spaces of BFTs), the translation between square moves in the graph and Seiberg duality and the identification of dual theories by means of the underlying Calabi-Yaus, the phenomenon of loop reduction and the interpretation of the boundary operator for cells in the positive Grassmannian as higgsing in the BFT. We develop a technique based on generalized Kasteleyn matrices that permits an efficient determination of the Calabi-Yau geometries associated to arbitrary graphs. Our techniques allow us to go beyond the planar limit by both increasing the number of boundaries of the graphs and the genus of the underlying Riemann surface. Our investigation suggests a central role for Calabi-Yau manifolds in the context of leading singularities, whose full scope is yet to be uncovered.

Ranking species in mutualistic networks

Science.gov (United States)

Domínguez-García, Virginia; Muñoz, Miguel A.

2015-02-01

Understanding the architectural subtleties of ecological networks, believed to confer them enhanced stability and robustness, is a subject of outmost relevance. Mutualistic interactions have been profusely studied and their corresponding bipartite networks, such as plant-pollinator networks, have been reported to exhibit a characteristic ``nested'' structure. Assessing the importance of any given species in mutualistic networks is a key task when evaluating extinction risks and possible cascade effects. Inspired in a recently introduced algorithm -similar in spirit to Google's PageRank but with a built-in non-linearity- here we propose a method which -by exploiting their nested architecture- allows us to derive a sound ranking of species importance in mutualistic networks. This method clearly outperforms other existing ranking schemes and can become very useful for ecosystem management and biodiversity preservation, where decisions on what aspects of ecosystems to explicitly protect need to be made.

Application of Bipartite Entangled States to Quantum Mechanical Version of Complex Wavelet Transforms

International Nuclear Information System (INIS)

Fan Hongyi; Lu Hailiang; Xu Xuefen

2006-01-01

We introduce the bipartite entangled states to present a quantum mechanical version of complex wavelet transform. Using the technique of integral within an ordered product of operators we show that the complex wavelet transform can be studied in terms of various quantum state vectors in two-mode Fock space. In this way the creterion for mother wavelet can be examined quantum-mechanically and therefore more deeply.

Atom-number squeezing and bipartite entanglement of two-component Bose-Einstein condensates: analytical results

Energy Technology Data Exchange (ETDEWEB)

Jin, G R; Wang, X W; Li, D; Lu, Y W, E-mail: grjin@bjtu.edu.c [Department of Physics, Beijing Jiaotong University, Beijing 100044 (China)

2010-02-28

We investigate spin dynamics of a two-component Bose-Einstein condensate with weak Josephson coupling. Analytical expressions of atom-number squeezing and bipartite entanglement are presented for atom-atom repulsive interactions. For attractive interactions, there is no number squeezing; however, the squeezing parameter is still useful to recognize the appearance of Schroedinger's cat state.

Enhanced capital-asset pricing model for the reconstruction of bipartite financial networks

NARCIS (Netherlands)

Squartini, Tiziano; Almog, Assaf; Caldarelli, Guido; Van Lelyveld, Iman; Garlaschelli, Diego; Cimini, Giulio

2017-01-01

Reconstructing patterns of interconnections from partial information is one of the most important issues in the statistical physics of complex networks. A paramount example is provided by financial networks. In fact, the spreading and amplification of financial distress in capital markets are

Stable amplitude chimera states in a network of locally coupled Stuart-Landau oscillators

Science.gov (United States)

Premalatha, K.; Chandrasekar, V. K.; Senthilvelan, M.; Lakshmanan, M.

2018-03-01

We investigate the occurrence of collective dynamical states such as transient amplitude chimera, stable amplitude chimera, and imperfect breathing chimera states in a locally coupled network of Stuart-Landau oscillators. In an imperfect breathing chimera state, the synchronized group of oscillators exhibits oscillations with large amplitudes, while the desynchronized group of oscillators oscillates with small amplitudes, and this behavior of coexistence of synchronized and desynchronized oscillations fluctuates with time. Then, we analyze the stability of the amplitude chimera states under various circumstances, including variations in system parameters and coupling strength, and perturbations in the initial states of the oscillators. For an increase in the value of the system parameter, namely, the nonisochronicity parameter, the transient chimera state becomes a stable chimera state for a sufficiently large value of coupling strength. In addition, we also analyze the stability of these states by perturbing the initial states of the oscillators. We find that while a small perturbation allows one to perturb a large number of oscillators resulting in a stable amplitude chimera state, a large perturbation allows one to perturb a small number of oscillators to get a stable amplitude chimera state. We also find the stability of the transient and stable amplitude chimera states and traveling wave states for an appropriate number of oscillators using Floquet theory. In addition, we also find the stability of the incoherent oscillation death states.

Partial recovery of entanglement in bipartite-entanglement transformations

International Nuclear Information System (INIS)

Bandyopadhyay, Somshubhro; Roychowdhury, Vwani; Vatan, Farrokh

2002-01-01

Any deterministic bipartite-entanglement transformation involving finite copies of pure states and carried out using local operations and classical communication (LOCC) results in a net loss of entanglement. We show that for almost all such transformations, partial recovery of lost entanglement is achievable by using 2x2 auxiliary entangled states, no matter how large the dimensions of the parent states are. For the rest of the special cases of deterministic LOCC transformations, we show that the dimension of the auxiliary entangled state depends on the presence of equalities in the majorization relations of the parent states. We show that genuine recovery is still possible using auxiliary states in dimensions less than that of the parent states for all patterns of majorization relations except only one special case

The simplest problem in the collective dynamics of neural networks: is synchrony stable?

International Nuclear Information System (INIS)

Timme, Marc; Wolf, Fred

2008-01-01

For spiking neural networks we consider the stability problem of global synchrony, arguably the simplest non-trivial collective dynamics in such networks. We find that even this simplest dynamical problem—local stability of synchrony—is non-trivial to solve and requires novel methods for its solution. In particular, the discrete mode of pulsed communication together with the complicated connectivity of neural interaction networks requires a non-standard approach. The dynamics in the vicinity of the synchronous state is determined by a multitude of linear operators, in contrast to a single stability matrix in conventional linear stability theory. This unusual property qualitatively depends on network topology and may be neglected for globally coupled homogeneous networks. For generic networks, however, the number of operators increases exponentially with the size of the network. We present methods to treat this multi-operator problem exactly. First, based on the Gershgorin and Perron–Frobenius theorems, we derive bounds on the eigenvalues that provide important information about the synchronization process but are not sufficient to establish the asymptotic stability or instability of the synchronous state. We then present a complete analysis of asymptotic stability for topologically strongly connected networks using simple graph-theoretical considerations. For inhibitory interactions between dissipative (leaky) oscillatory neurons the synchronous state is stable, independent of the parameters and the network connectivity. These results indicate that pulse-like interactions play a profound role in network dynamical systems, and in particular in the dynamics of biological synchronization, unless the coupling is homogeneous and all-to-all. The concepts introduced here are expected to also facilitate the exact analysis of more complicated dynamical network states, for instance the irregular balanced activity in cortical neural networks

Bipartite Anterior Extraperitoneal Teratoma: Evidence for the Embryological Origins of Teratomas?

Directory of Open Access Journals (Sweden)

D. J. B. Keene

2011-01-01

Full Text Available Teratomas are thought to arise from totipotent primordial germ cells (PGCs Dehner (1983 which may miss their target destination Moore and Persaud (1984. Teratomas can occur anywhere from the brain to the coccygeal area but are usually in the midline close to the embryological position of the gonadal ridges Bale (1984, Nguyen and Laberge (2000. We report a case of a bipartite anterior extraperitoneal teratoma. This is an unusual position for a teratoma, but one which may support the “missed target” theory of embryology.

Study of Chromatic parameters of Line, Total, Middle graphs and Graph operators of Bipartite graph

Science.gov (United States)

Nagarathinam, R.; Parvathi, N.

2018-04-01

Chromatic parameters have been explored on the basis of graph coloring process in which a couple of adjacent nodes receives different colors. But the Grundy and b-coloring executes maximum colors under certain restrictions. In this paper, Chromatic, b-chromatic and Grundy number of some graph operators of bipartite graph has been investigat

Stable Chimeras and Independently Synchronizable Clusters

Science.gov (United States)

Cho, Young Sul; Nishikawa, Takashi; Motter, Adilson E.

2017-08-01

Cluster synchronization is a phenomenon in which a network self-organizes into a pattern of synchronized sets. It has been shown that diverse patterns of stable cluster synchronization can be captured by symmetries of the network. Here, we establish a theoretical basis to divide an arbitrary pattern of symmetry clusters into independently synchronizable cluster sets, in which the synchronization stability of the individual clusters in each set is decoupled from that in all the other sets. Using this framework, we suggest a new approach to find permanently stable chimera states by capturing two or more symmetry clusters—at least one stable and one unstable—that compose the entire fully symmetric network.

Flux networks in metabolic graphs

International Nuclear Information System (INIS)

Warren, P B; Queiros, S M Duarte; Jones, J L

2009-01-01

A metabolic model can be represented as a bipartite graph comprising linked reaction and metabolite nodes. Here it is shown how a network of conserved fluxes can be assigned to the edges of such a graph by combining the reaction fluxes with a conserved metabolite property such as molecular weight. A similar flux network can be constructed by combining the primal and dual solutions to the linear programming problem that typically arises in constraint-based modelling. Such constructions may help with the visualization of flux distributions in complex metabolic networks. The analysis also explains the strong correlation observed between metabolite shadow prices (the dual linear programming variables) and conserved metabolite properties. The methods were applied to recent metabolic models for Escherichia coli, Saccharomyces cerevisiae and Methanosarcina barkeri. Detailed results are reported for E. coli; similar results were found for other organisms

Epidemic spreading on dynamical networks with temporary hubs and stable scale-free degree distribution

International Nuclear Information System (INIS)

Wu, An-Cai

2014-01-01

Recent empirical analyses of some realistic dynamical networks have demonstrated that their degree distributions are stable scale-free (SF), but the instantaneous well-connected hubs at one point of time can quickly become weakly connected. Motivated by these empirical results, we propose a simple toy dynamical agent-to-agent contact network model, in which each agent stays at one node of a static underlay network and the nearest neighbors swap their positions with each other. Although the degree distribution of the dynamical network model at any one time is equal to that in the static underlay network, the numbers and identities of each agent’s contacts will change over time. It is found that the dynamic interaction tends to suppress epidemic spreading in terms of larger epidemic threshold, smaller prevalence (the fraction of infected individuals) and smaller velocity of epidemic outbreak. Furthermore, the dynamic interaction results in the prevalence to undergo a phase transition at a finite threshold of the epidemic spread rate in the thermodynamic limit, which is in contradiction to the absence of an epidemic threshold in static SF networks. Some of these findings obtained from heterogeneous mean-field theory are in good agreement with numerical simulations. (paper)

User Matching with Relation to the Stable Marriage Problem in Cognitive Radio Networks

KAUST Repository

Hamza, Doha R.

2017-03-20

We consider a network comprised of multiple primary users (PUs) and multiple secondary users (SUs), where the SUs seek access to a set of orthogonal channels each occupied by one PU. Only one SU is allowed to coexist with a given PU. We propose a distributed matching algorithm to pair the network users, where a Stackelberg game model is assumed for the interaction between the paired PU and SU. The selected secondary is given access in exchange for monetary compensation to the primary. The PU optimizes the interference price it charges to a given SU and the power allocation to maintain communication. The SU optimizes its power demand so as to maximize its utility. Our algorithm provides a unique stable matching. Numerical results indicate the advantage of the proposed algorithm over other reference schemes.

Complex systems and networks dynamics, controls and applications

CERN Document Server

Yu, Xinghuo; Chen, Guanrong; Yu, Wenwu

2016-01-01

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

Entanglement dynamics of a pure bipartite system in dissipative environments

Energy Technology Data Exchange (ETDEWEB)

Tahira, Rabia; Ikram, Manzoor; Azim, Tasnim; Suhail Zubairy, M [Centre for Quantum Physics, COMSATS Institute of Information Technology, Islamabad (Pakistan)

2008-10-28

We investigate the phenomenon of sudden death of entanglement in a bipartite system subjected to dissipative environments with arbitrary initial pure entangled state between two atoms. We find that in a vacuum reservoir the presence of the state where both atoms are in excited states is a necessary condition for the sudden death of entanglement. Otherwise entanglement remains for an infinite time and decays asymptotically with the decay of individual qubits. For pure 2-qubit entangled states in a thermal environment, we observe that the sudden death of entanglement always happens. The sudden death time of the entangled states is related to the temperature of the reservoir and the initial preparation of the entangled states.

Entanglement dynamics of a pure bipartite system in dissipative environments

International Nuclear Information System (INIS)

Tahira, Rabia; Ikram, Manzoor; Azim, Tasnim; Suhail Zubairy, M

2008-01-01

We investigate the phenomenon of sudden death of entanglement in a bipartite system subjected to dissipative environments with arbitrary initial pure entangled state between two atoms. We find that in a vacuum reservoir the presence of the state where both atoms are in excited states is a necessary condition for the sudden death of entanglement. Otherwise entanglement remains for an infinite time and decays asymptotically with the decay of individual qubits. For pure 2-qubit entangled states in a thermal environment, we observe that the sudden death of entanglement always happens. The sudden death time of the entangled states is related to the temperature of the reservoir and the initial preparation of the entangled states.

Spin-1 Dirac-Weyl fermions protected by bipartite symmetry

Energy Technology Data Exchange (ETDEWEB)

Lin, Zeren [College of Chemistry and Molecular Engineering, Peking University, Beijing 100871 (China); School of Physics, Peking University, Beijing 100871 (China); Liu, Zhirong, E-mail: LiuZhiRong@pku.edu.cn [College of Chemistry and Molecular Engineering, Peking University, Beijing 100871 (China); Center for Nanochemistry, Beijing National Laboratory for Molecular Sciences (BNLMS), Peking University, Beijing 100871 (China)

2015-12-07

We propose that bipartite symmetry allows spin-1 Dirac-Weyl points, a generalization of the spin-1/2 Dirac points in graphene, to appear as topologically protected at the Fermi level. In this spirit, we provide methodology to construct spin-1 Dirac-Weyl points of this kind in a given 2D space group and get the classification of the known spin-1 systems in the literature. We also apply the workflow to predict two new systems, P3m1-9 and P31m-15, to possess spin-1 at K/K′ in the Brillouin zone of hexagonal lattice. Their stability under various strains is investigated and compared with that of T{sub 3}, an extensively studied model of ultracold atoms trapped in optical lattice with spin-1 also at K/K′.

Lagged correlation networks

Science.gov (United States)

Curme, Chester

Technological advances have provided scientists with large high-dimensional datasets that describe the behaviors of complex systems: from the statistics of energy levels in complex quantum systems, to the time-dependent transcription of genes, to price fluctuations among assets in a financial market. In this environment, where it may be difficult to infer the joint distribution of the data, network science has flourished as a way to gain insight into the structure and organization of such systems by focusing on pairwise interactions. This work focuses on a particular setting, in which a system is described by multivariate time series data. We consider time-lagged correlations among elements in this system, in such a way that the measured interactions among elements are asymmetric. Finally, we allow these interactions to be characteristically weak, so that statistical uncertainties may be important to consider when inferring the structure of the system. We introduce a methodology for constructing statistically validated networks to describe such a system, extend the methodology to accommodate interactions with a periodic component, and show how consideration of bipartite community structures in these networks can aid in the construction of robust statistical models. An example of such a system is a financial market, in which high frequency returns data may be used to describe contagion, or the spreading of shocks in price among assets. These data provide the experimental testing ground for our methodology. We study NYSE data from both the present day and one decade ago, examine the time scales over which the validated lagged correlation networks exist, and relate differences in the topological properties of the networks to an increasing economic efficiency. We uncover daily periodicities in the validated interactions, and relate our findings to explanations of the Epps Effect, an empirical phenomenon of financial time series. We also study bipartite community

Enhancing non-local correlations in the bipartite partitions of two qubit-system with non-mutual interaction

Energy Technology Data Exchange (ETDEWEB)

Mohamed, A.-B.A., E-mail: abdelbastm@yahoo.com [College of Sciences and Humanities, Prince Sattam Bin Abdulaziz University, Al-Aflaj (Saudi Arabia); Faculty of Science, Assiut University, Assiut (Egypt); Joshi, A., E-mail: mcbamji@gmail.com [Physics Department, Adelphi University Garden City, NY 11530 (United States); Department of Physics and Optical Engineering, RHIT, Terra Haute IN 47803 (United States); Hassan, S.S., E-mail: shoukryhassan@hotmail.com [Department of Mathematics, College of Science, University of Bahrain, P.O. Box 32038 (Bahrain)

2016-03-15

Several quantum-mechanical correlations, notably, quantum entanglement, measurement-induced nonlocality and Bell nonlocality are studied for a two qubit-system having no mutual interaction. Analytical expressions for the measures of these quantum-mechanical correlations of different bipartite partitions of the system are obtained, for initially two entangled qubits and the two photons are in their vacuum states. It is found that the qubits-fields interaction leads to the loss and gain of the initial quantum correlations. The lost initial quantum correlations transfer from the qubits to the cavity fields. It is found that the maximal violation of Bell’s inequality is occurring when the quantum correlations of both the logarithmic negativity and measurement-induced nonlocality reach particular values. The maximal violation of Bell’s inequality occurs only for certain bipartite partitions of the system. The frequency detuning leads to quick oscillations of the quantum correlations and inhibits their transfer from the qubits to the cavity modes. It is also found that the dynamical behavior of the quantum correlation clearly depends on the qubit distribution angle.

Maximal violation of a bipartite three-setting, two-outcome Bell inequality using infinite-dimensional quantum systems

International Nuclear Information System (INIS)

Pal, Karoly F.; Vertesi, Tamas

2010-01-01

The I 3322 inequality is the simplest bipartite two-outcome Bell inequality beyond the Clauser-Horne-Shimony-Holt (CHSH) inequality, consisting of three two-outcome measurements per party. In the case of the CHSH inequality the maximal quantum violation can already be attained with local two-dimensional quantum systems; however, there is no such evidence for the I 3322 inequality. In this paper a family of measurement operators and states is given which enables us to attain the maximum quantum value in an infinite-dimensional Hilbert space. Further, it is conjectured that our construction is optimal in the sense that measuring finite-dimensional quantum systems is not enough to achieve the true quantum maximum. We also describe an efficient iterative algorithm for computing quantum maximum of an arbitrary two-outcome Bell inequality in any given Hilbert space dimension. This algorithm played a key role in obtaining our results for the I 3322 inequality, and we also applied it to improve on our previous results concerning the maximum quantum violation of several bipartite two-outcome Bell inequalities with up to five settings per party.

On the Control of Consensus Networks: Theory and Applications

Science.gov (United States)

Hudoba de Badyn, Mathias

Signed networks allow the study of positive and negative interactions between agents. In this thesis, three papers are presented that address controllability of networked dynamics. First, controllability of signed consensus networks is approached from a symmetry perspective, for both linear and nonlinear consensus protocols. It is shown that the graph-theoretic property of signed networks known as structural balance renders the consensus protocol uncontrollable when coupled with a certain type of symmetry. Stabilizability and output controllability of signed linear consensus is also examined, as well as a data-driven approach to finding bipartite consensus stemming from structural balance for signed nonlinear consensus. Second, an algorithm is constructed that allows one to grow a network while preserving controllability, and some generalizations of this algorithm are presented. Submodular optimization is used to analyze a second algorithm that adds nodes to a network to maximize the network connectivity.

Application of Bipartite and Tripartite Entangled State Representations in Quantum Teleportation of Continuous Variables

Institute of Scientific and Technical Information of China (English)

YUAN Hong-Chun; QI Kai-Guo

2005-01-01

We mostly investigate two schemes. One is to teleport a multi-mode W-type entangled coherent state using a peculiar bipartite entangled state as the quantum channel different from other proposals. Based on our formalism,teleporting multi-mode coherent state or squeezed state is also possible. Another is that the tripartite entangled state is used as the quantum channel of controlled teleportation of an arbitrary and unknown continuous variable in the case of three participators.

Biclique communities

DEFF Research Database (Denmark)

Jørgensen, Sune Lehmann; Hansen-Schwartz, Martin; Hansen, Lars Kai

2008-01-01

We present a method for detecting communities in bipartite networks. Based on an extension of the k-clique community detection algorithm, we demonstrate how modular structure in bipartite networks presents itself as overlapping bicliques. If bipartite information is available, the biclique...... community detection algorithm retains all of the advantages of the k-clique algorithm, but avoids discarding important structural information when performing a one-mode projection of the network. Further, the biclique community detection algorithm provides a level of flexibility by incorporating independent...

Mixture models with entropy regularization for community detection in networks

Science.gov (United States)

Chang, Zhenhai; Yin, Xianjun; Jia, Caiyan; Wang, Xiaoyang

2018-04-01

Community detection is a key exploratory tool in network analysis and has received much attention in recent years. NMM (Newman's mixture model) is one of the best models for exploring a range of network structures including community structure, bipartite and core-periphery structures, etc. However, NMM needs to know the number of communities in advance. Therefore, in this study, we have proposed an entropy regularized mixture model (called EMM), which is capable of inferring the number of communities and identifying network structure contained in a network, simultaneously. In the model, by minimizing the entropy of mixing coefficients of NMM using EM (expectation-maximization) solution, the small clusters contained little information can be discarded step by step. The empirical study on both synthetic networks and real networks has shown that the proposed model EMM is superior to the state-of-the-art methods.

The Network of U.S. Mutual Fund Investments: Diversification, Similarity and Fragility throughout the Global Financial Crisis

OpenAIRE

Delpini, Danilo; Battiston, Stefano; Caldarelli, Guido; Riccaboni, Massimo

2018-01-01

Network theory proved recently to be useful in the quantification of many properties of financial systems. The analysis of the structure of investment portfolios is a major application since their eventual correlation and overlap impact the actual risk diversification by individual investors. We investigate the bipartite network of US mutual fund portfolios and their assets. We follow its evolution during the Global Financial Crisis and analyse the interplay between diversification, as unders...

Generalised power graph compression reveals dominant relationship patterns in complex networks.

Science.gov (United States)

Ahnert, Sebastian E

2014-03-25

We introduce a framework for the discovery of dominant relationship patterns in complex networks, by compressing the networks into power graphs with overlapping power nodes. When paired with enrichment analysis of node classification terms, the most compressible sets of edges provide a highly informative sketch of the dominant relationship patterns that define the network. In addition, this procedure also gives rise to a novel, link-based definition of overlapping node communities in which nodes are defined by their relationships with sets of other nodes, rather than through connections within the community. We show that this completely general approach can be applied to undirected, directed, and bipartite networks, yielding valuable insights into the large-scale structure of real-world networks, including social networks and food webs. Our approach therefore provides a novel way in which network architecture can be studied, defined and classified.

Effect of bipartition on spectral properties of nanorings

International Nuclear Information System (INIS)

Gutiérrez, W.; García, L.F.; Mikhailov, I.D.

2013-01-01

The effects of a special topological transformation on the energy levels, far-infrared spectra and magnetization of one electron inside a semiconductor nanoring under magnetic fields are studied. We have called this transformation as bipartition, and it is defined by a change in ring topological structure, when its shape is changed successively from a single oval-shaped loop up to quasi-two disconnected loops. Our results show that in the course of such transformation the low-lying energies dependencies with multiple crossovers between them, typical for the free electron rotation along an almost circular loop, are converted into a set of non-crossing double plaits related to a sub-barrier electron tunneling along a strongly non-circular loop in a quasi-local state. Also, we find that during the restructuring of the oval-shaped nanostructures the selection rules for the dipole transitions are changed allowing the appearance of additional peaks in the FIR spectrum

Measuring Asymmetry in Insect-Plant Networks

Energy Technology Data Exchange (ETDEWEB)

Cruz, Claudia P T [Programa de Pos-Graduacao em Fisica, Universidade Federal do Rio Grande do Norte, UFRN - Campus Universitario, Lagoa Nova, CEP 59078 972, Natal, RN (Brazil); De Almeida, Adriana M [Departamento de Botanica, Ecologia e Zoologia, Centro de Biociencias, Universidade Federal do Rio Grande do Norte, UFRN - Campus Universitario, Lagoa Nova, CEP 59078 972, Natal, RN (Brazil); Corso, Gilberto, E-mail: claudia@dfte.ufrn.br, E-mail: adrianam@ufrn.br, E-mail: corso@cb.ufrn.br [Departamento de Biofisica e Farmacologia, Centro de Biociencias, Universidade Federal do Rio Grande do Norte, UFRN - Campus Universitario, Lagoa Nova, CEP 59078 972, Natal, RN (Brazil)

2011-03-01

In this work we focus on interaction networks between insects and plants and in the characterization of insect plant asymmetry, an important issue in coevolution and evolutionary biology. We analyze in particular the asymmetry in the interaction matrix of animals (herbivorous insects) and plants (food resource for the insects). Instead of driving our attention to the interaction matrix itself we derive two networks associated to the bipartite network: the animal network, D{sub 1}, and the plant network, D{sub 2}. These networks are constructed according to the following recipe: two animal species are linked once if they interact with the same plant. In a similar way, in the plant network, two plants are linked if they interact with the same animal. To explore the asymmetry between D{sub 2} and D{sub 1} we test for a set of 23 networks from the ecologic literature networks: the difference in size, {Delta}L, clustering coefficient difference, {Delta}C, and mean connectivity difference, {Delta}. We used a nonparametric statistical test to check the differences in {Delta}L, {Delta}C and {Delta}. Our results indicate that {Delta}L and {Delta} show a significative asymmetry.

Local hypothesis testing between a pure bipartite state and the white noise state

OpenAIRE

Owari, Masaki; Hayashi, Masahito

2010-01-01

In this paper, we treat a local discrimination problem in the framework of asymmetric hypothesis testing. We choose a known bipartite pure state $\\ket{\\Psi}$ as an alternative hypothesis, and the completely mixed state as a null hypothesis. As a result, we analytically derive an optimal type 2 error and an optimal POVM for one-way LOCC POVM and Separable POVM. For two-way LOCC POVM, we study a family of simple three-step LOCC protocols, and show that the best protocol in this family has stric...

Referee Networks and Their Spectral Properties

Science.gov (United States)

Slanina, F.; Zhang, Y.-Ch.

2005-09-01

The bipartite graph connecting products and reviewers of that product is studied empirically in the case of amazon.com. We find that the network has power-law degree distribution on the side of reviewers, while on the side of products the distribution is better fitted by stretched exponential. The spectrum of normalised adjacency matrix shows power-law tail in the density of states. Establishing the community structures by finding localised eigenstates is not straightforward as the localised and delocalised states are mixed throughout the whole support of the spectrum.

Bipartite discrimination of independently prepared quantum states as a counterexample to a parallel repetition conjecture

Science.gov (United States)

Akibue, Seiseki; Kato, Go

2018-04-01

For distinguishing quantum states sampled from a fixed ensemble, the gap in bipartite and single-party distinguishability can be interpreted as a nonlocality of the ensemble. In this paper, we consider bipartite state discrimination in a composite system consisting of N subsystems, where each subsystem is shared between two parties and the state of each subsystem is randomly sampled from a particular ensemble comprising the Bell states. We show that the success probability of perfectly identifying the state converges to 1 as N →∞ if the entropy of the probability distribution associated with the ensemble is less than 1, even if the success probability is less than 1 for any finite N . In other words, the nonlocality of the N -fold ensemble asymptotically disappears if the probability distribution associated with each ensemble is concentrated. Furthermore, we show that the disappearance of the nonlocality can be regarded as a remarkable counterexample of a fundamental open question in theoretical computer science, called a parallel repetition conjecture of interactive games with two classically communicating players. Measurements for the discrimination task include a projective measurement of one party represented by stabilizer states, which enable the other party to perfectly distinguish states that are sampled with high probability.

Information Filtering via Heterogeneous Diffusion in Online Bipartite Networks.

Science.gov (United States)

Zhang, Fu-Guo; Zeng, An

2015-01-01

The rapid expansion of Internet brings us overwhelming online information, which is impossible for an individual to go through all of it. Therefore, recommender systems were created to help people dig through this abundance of information. In networks composed by users and objects, recommender algorithms based on diffusion have been proven to be one of the best performing methods. Previous works considered the diffusion process from user to object, and from object to user to be equivalent. We show in this work that it is not the case and we improve the quality of the recommendation by taking into account the asymmetrical nature of this process. We apply this idea to modify the state-of-the-art recommendation methods. The simulation results show that the new methods can outperform these existing methods in both recommendation accuracy and diversity. Finally, this modification is checked to be able to improve the recommendation in a realistic case.

Computing Tutte polynomials of contact networks in classrooms

Science.gov (United States)

Hincapié, Doracelly; Ospina, Juan

2013-05-01

Objective: The topological complexity of contact networks in classrooms and the potential transmission of an infectious disease were analyzed by sex and age. Methods: The Tutte polynomials, some topological properties and the number of spanning trees were used to algebraically compute the topological complexity. Computations were made with the Maple package GraphTheory. Published data of mutually reported social contacts within a classroom taken from primary school, consisting of children in the age ranges of 4-5, 7-8 and 10-11, were used. Results: The algebraic complexity of the Tutte polynomial and the probability of disease transmission increases with age. The contact networks are not bipartite graphs, gender segregation was observed especially in younger children. Conclusion: Tutte polynomials are tools to understand the topology of the contact networks and to derive numerical indexes of such topologies. It is possible to establish relationships between the Tutte polynomial of a given contact network and the potential transmission of an infectious disease within such network

E6 and the bipartite entanglement of three qutrits

International Nuclear Information System (INIS)

Duff, M. J.; Ferrara, S.

2007-01-01

Recent investigations have established an analogy between the entropy of four-dimensional supersymmetric black holes in string theory and entanglement in quantum information theory. Examples include: (1) N=2 STU black holes and the tripartite entanglement of three qubits (2-state systems), where the common symmetry is [SL(2)] 3 and (2) N=8 black holes and the tripartite entanglement of seven qubits where the common symmetry is E 7 superset of [SL(2)] 7 . Here we present another example: N=8 black holes (or black strings) in five dimensions and the bipartite entanglement of three qutrits (3-state systems), where the common symmetry is E 6 superset of [SL(3)] 3 . Both the black hole (or black string) entropy and the entanglement measure are provided by the Cartan cubic E 6 invariant. Similar analogies exist for magic N=2 supergravity black holes in both four and five dimensions

The General Evolving Model for Energy Supply-Demand Network with Local-World

Science.gov (United States)

Sun, Mei; Han, Dun; Li, Dandan; Fang, Cuicui

2013-10-01

In this paper, two general bipartite network evolving models for energy supply-demand network with local-world are proposed. The node weight distribution, the "shifting coefficient" and the scaling exponent of two different kinds of nodes are presented by the mean-field theory. The numerical results of the node weight distribution and the edge weight distribution are also investigated. The production's shifted power law (SPL) distribution of coal enterprises and the installed capacity's distribution of power plants in the US are obtained from the empirical analysis. Numerical simulations and empirical results are given to verify the theoretical results.

Stable architectures for deep neural networks

Science.gov (United States)

Haber, Eldad; Ruthotto, Lars

2018-01-01

Deep neural networks have become invaluable tools for supervised machine learning, e.g. classification of text or images. While often offering superior results over traditional techniques and successfully expressing complicated patterns in data, deep architectures are known to be challenging to design and train such that they generalize well to new data. Critical issues with deep architectures are numerical instabilities in derivative-based learning algorithms commonly called exploding or vanishing gradients. In this paper, we propose new forward propagation techniques inspired by systems of ordinary differential equations (ODE) that overcome this challenge and lead to well-posed learning problems for arbitrarily deep networks. The backbone of our approach is our interpretation of deep learning as a parameter estimation problem of nonlinear dynamical systems. Given this formulation, we analyze stability and well-posedness of deep learning and use this new understanding to develop new network architectures. We relate the exploding and vanishing gradient phenomenon to the stability of the discrete ODE and present several strategies for stabilizing deep learning for very deep networks. While our new architectures restrict the solution space, several numerical experiments show their competitiveness with state-of-the-art networks.

Multidimensional scaling of ideological landscape on social network sites

Science.gov (United States)

Lee, Deokjae; Hahn, Kyu S.; Park, Juyong

2012-02-01

Social network sites (SNSs) are valuable source of information on various subjects in network science. Recently, political activity of SNSs users has increasing attention and is an interesting interdisciplinary subject of physical and social science. In this work, we measure ideological positions of the legislators of U.S. and South Korea (S.K.) evaluated by Twitter users, using the information employed in the bipartite network structure of the legislators and their Twitter followers. We compare the result with ideological positions constructed from roll call record of the legislators. This shows there is a discrepancy between the ideological positions evaluated by Twitter users and actual positions estimated from roll call votes in S.K. We also asses the ideological positions of the Twitter users themselves and analyze the distribution of the positions.

The Global Network of Isotopes in Rivers (GNIR): Integration of Stable Water Isotopes in Riverine Research and Management

International Nuclear Information System (INIS)

Halder, J.; Terzer, S.; Wassenaar, L.; Araguas, L.; Aggarwal, P.

2015-01-01

Rivers play a crucial role in the global water cycle as watershed-integrating hydrological conduits for returning terrestrial precipitation, runoff, surface and groundwater, as well as melting snow and ice back to the world’s oceans. The IAEA Global Network of Isotopes in Rivers (GNIR) is the coherent extension of the IAEA Global Network for Isotopes in Precipitation (GNIP) and aims to fill the informational data gaps between rainfall and river discharge. Whereas the GNIP has been surveying the stable hydrogen and oxygen isotopes, and tritium composition in precipitation, the objective of GNIR is to accumulate and disseminate riverine isotope data. We introduce the new global database of riverine water isotopes and evaluate its current long-term data holdings with the objective to improve the application of water isotopes and to inform water managers and researchers. An evaluation of current GNIR database holdings confirmed that seasonal variations of the stable water isotope composition in rivers are closely coupled to precipitation and snow-melt water run-off on a global scale. Rivers could be clustered on the basis of seasonal variations in their isotope composition and latitude. Results showed furthermore, that there were periodic phases within each of these groupings and additional modelling exercises allowed a priori prediction of the seasonal variability as well as the isotopic composition of stable water isotopes in rivers. This predictive capacity will help to improve existing and new sampling strategies, help to validate and interpret riverine isotope data, and identify important catchment processes. Hence, the IAEA promulgates and supports longterm hydrological isotope observation networks and the application of isotope studies complementary with conventional hydrological, water quality, and ecological studies. (author)

Inefficiency and classical communication bounds for conversion between partially entangled pure bipartite states

International Nuclear Information System (INIS)

Fortescue, Ben; Lo, H.-K.

2005-01-01

We derive lower limits on the inefficiency and classical communication costs of dilution between two-term bipartite pure states that are partially entangled. We first calculate explicit relations between the allowable error and classical communication costs of entanglement dilution using a previously described protocol, then consider a two-stage dilution from singlets with this protocol followed by some unknown protocol for conversion between partially entangled states. Applying overall lower bounds on classical communication and inefficiency to this two-stage protocol, we derive bounds for the unknown protocol. In addition we derive analogous (but looser) bounds for general pure states

Forbidden regimes in the distribution of bipartite quantum correlations due to multiparty entanglement

Science.gov (United States)

Kumar, Asutosh; Dhar, Himadri Shekhar; Prabhu, R.; Sen(De), Aditi; Sen, Ujjwal

2017-05-01

Monogamy is a nonclassical property that limits the distribution of quantum correlation among subparts of a multiparty system. We show that monogamy scores for different quantum correlation measures are bounded above by functions of genuine multipartite entanglement for a large majority of pure multiqubit states. The bound is universal for all three-qubit pure states. We derive necessary conditions to characterize the states that violate the bound, which can also be observed by numerical simulation for a small set of states, generated Haar uniformly. The results indicate that genuine multipartite entanglement restricts the distribution of bipartite quantum correlations in a multiparty system.

No-signaling, perfect bipartite dichotomic correlations and local randomness

International Nuclear Information System (INIS)

Seevinck, M. P.

2011-01-01

The no-signaling constraint on bi-partite correlations is reviewed. It is shown that in order to obtain non-trivial Bell-type inequalities that discern no-signaling correlations from more general ones, one must go beyond considering expectation values of products of observables only. A new set of nontrivial no-signaling inequalities is derived which have a remarkably close resemblance to the CHSH inequality, yet are fundamentally different. A set of inequalities by Roy and Singh and Avis et al., which is claimed to be useful for discerning no-signaling correlations, is shown to be trivially satisfied by any correlation whatsoever. Finally, using the set of newly derived no-signaling inequalities a result with potential cryptographic consequences is proven: if different parties use identical devices, then, once they have perfect correlations at spacelike separation between dichotomic observables, they know that because of no-signaling the local marginals cannot but be completely random.

All pure bipartite entangled states can be self-tested

Science.gov (United States)

Coladangelo, Andrea; Goh, Koon Tong; Scarani, Valerio

2017-05-01

Quantum technologies promise advantages over their classical counterparts in the fields of computation, security and sensing. It is thus desirable that classical users are able to obtain guarantees on quantum devices, even without any knowledge of their inner workings. That such classical certification is possible at all is remarkable: it is a consequence of the violation of Bell inequalities by entangled quantum systems. Device-independent self-testing refers to the most complete such certification: it enables a classical user to uniquely identify the quantum state shared by uncharacterized devices by simply inspecting the correlations of measurement outcomes. Self-testing was first demonstrated for the singlet state and a few other examples of self-testable states were reported in recent years. Here, we address the long-standing open question of whether every pure bipartite entangled state is self-testable. We answer it affirmatively by providing explicit self-testing correlations for all such states.

The influence of tie strength on evolutionary games on networks: An empirical investigation

Science.gov (United States)

Buesser, Pierre; Peña, Jorge; Pestelacci, Enea; Tomassini, Marco

2011-11-01

Extending previous work on unweighted networks, we present here a systematic numerical investigation of standard evolutionary games on weighted networks. In the absence of any reliable model for generating weighted social networks, we attribute weights to links in a few ways supported by empirical data ranging from totally uncorrelated to weighted bipartite networks. The results of the extensive simulation work on standard complex network models show that, except in a case that does not seem to be common in social networks, taking the tie strength into account does not change in a radical manner the long-run steady-state behavior of the studied games. Besides model networks, we also included a real-life case drawn from a coauthorship network. In this case also, taking the weights into account only changes the results slightly with respect to the raw unweighted graph, although to draw more reliable conclusions on real social networks many more cases should be studied as these weighted networks become available.

The minimal entanglement of bipartite decompositions as a witness of strong entanglement in a quantum system

OpenAIRE

Zenchuk, A. I.

2010-01-01

We {characterize the multipartite entanglement in a quantum system by the quantity} which vanishes if only the quantum system may be decomposed into two weakly entangled subsystems, unlike measures of multipartite entanglement introduced before. We refer to this {quantity} as the minimal entanglement of bipartite decompositions (MEBD). Big MEBD means that the system may not be decomposed into two weakly entangled subsystems. MEBD allows one to define, for instance, whether the given quantum s...

Drivers of compartmentalization in a Mediterranean pollination network

DEFF Research Database (Denmark)

Gonzalez, Ana M. Martin; Allesina, Stefano; Rodrigo, Anselm

2012-01-01

We study compartmentalization in a Mediterranean pollination network using three different analytical approaches: unipartite modularity (UM), bipartite modularity (BM) and the group model (GM). Our objectives are to compare compartments obtained with these three approaches and to explore the role...... of several species attributes related to pollination syndromes, species phenology, abundance and connectivity in structuring compartmentalization. BM could not identify compartments in our network. By contrast, UM revealed four modules composed of plants and pollinators, and GM four groups of plants and five...... of pollinators. Phenology had a major influence on compartmentalization, and compartments (both UM and GM) had distinct phenophases. Compartments were also strongly characterized by species degree (number of connections) and betweenness centrality. These two attributes were highly related to each other...

On Consensus of Star-Composed Networks with an Application of Laplacian Spectrum

Directory of Open Access Journals (Sweden)

Da Huang

2017-01-01

Full Text Available In this paper, we mainly study the performance of star-composed networks which can achieve consensus. Specifically, we investigate the convergence speed and robustness of the consensus of the networks, which can be measured by the smallest nonzero eigenvalue λ2 of the Laplacian matrix and the H2 norm of the graph, respectively. In particular, we introduce the notion of the corona of two graphs to construct star-composed networks and apply the Laplacian spectrum to discuss the convergence speed and robustness for the communication network. Finally, the performances of the star-composed networks have been compared, and we find that the network in which the centers construct a balanced complete bipartite graph has the most advantages of performance. Our research would provide a new insight into the combination between the field of consensus study and the theory of graph spectra.

Bipartite non-classical correlations for a lossy two connected qubit-cavity systems: trace distance discord and Bell's non-locality

Science.gov (United States)

Mohamed, Abdel-Baset A.

2018-04-01

In this paper, some non-classical correlations are investigated for bipartite partitions of two qubits trapped in two spatially separated cavities connected by an optical fiber. The results show that the trace distance discord and Bell's non-locality introduce other quantum correlations beyond the entanglement. Moreover, the correlation functions of the trace distance discord and the Bell's non-locality are very sensitive to the initial correlations, the coupling strengths, and the dissipation rates of the cavities. The fluctuations of the correlation functions between their initial values and gained (loss) values appear due to the unitary evolution of the system. These fluctuations depend on the chosen initial correlations between the two subsystems. The maximal violations of Bell's inequality occur when the logarithmic negativity and the trace distance discord reach certain values. It is shown that the robustness of the non-classical correlations, against the dissipation rates of the cavities, depends on the bipartite partitions reduced density matrices of the system, and is also greatly enhanced by choosing appropriate coupling strengths.

Bell Labs Algorithms Pow Wow

National Research Council Canada - National Science Library

Shepherd, F

2004-01-01

... biclique cover, metric labeling, priority Steiner Tree, network design: orientation constraints edge-coloring dynamic bipartite multi-graphs, edge coloring bipartite multi-hypergraphs, optimal cost chromatic partition (OCCP...

Controlling transfer of quantum correlations among bi-partitions of a composite quantum system by combining different noisy environments

International Nuclear Information System (INIS)

Zhang Xiu-Xing; Li Fu-Li

2011-01-01

The correlation dynamics are investigated for various bi-partitions of a composite quantum system consisting of two qubits and two independent and non-identical noisy environments. The two qubits have no direct interaction with each other and locally interact with their environments. Classical and quantum correlations including the entanglement are initially prepared only between the two qubits. We find that contrary to the identical noisy environment case, the quantum correlation transfer direction can be controlled by combining different noisy environments. The amplitude-damping environment determines whether there exists the entanglement transfer among bi-partitions of the system. When one qubit is coupled to an amplitude-damping environment and the other one to a bit-flip one, we find a very interesting result that all the quantum and the classical correlations, and even the entanglement, originally existing between the qubits, can be completely transferred without any loss to the qubit coupled to the bit-flit environment and the amplitude-damping environment. We also notice that it is possible to distinguish the quantum correlation from the classical correlation and the entanglement by combining different noisy environments. (general)

The stable fixtures problem with payments

NARCIS (Netherlands)

Biró, Péter; Kern, Walter; Paulusma, Daniël; Wojuteczky, Péter

2017-01-01

We consider multiple partners matching games (G,b,w), where G is a graph with an integer vertex capacity function b and an edge weighting w. If G is bipartite, these games are called multiple partners assignment games. We give a polynomial-time algorithm that either finds that a given multiple

Measuring structural similarity in large online networks.

Science.gov (United States)

Shi, Yongren; Macy, Michael

2016-09-01

Structural similarity based on bipartite graphs can be used to detect meaningful communities, but the networks have been tiny compared to massive online networks. Scalability is important in applications involving tens of millions of individuals with highly skewed degree distributions. Simulation analysis holding underlying similarity constant shows that two widely used measures - Jaccard index and cosine similarity - are biased by the distribution of out-degree in web-scale networks. However, an alternative measure, the Standardized Co-incident Ratio (SCR), is unbiased. We apply SCR to members of Congress, musical artists, and professional sports teams to show how massive co-following on Twitter can be used to map meaningful affiliations among cultural entities, even in the absence of direct connections to one another. Our results show how structural similarity can be used to map cultural alignments and demonstrate the potential usefulness of social media data in the study of culture, politics, and organizations across the social and behavioral sciences. Copyright © 2016 Elsevier Inc. All rights reserved.

Matching theory

CERN Document Server

Plummer, MD

1986-01-01

This study of matching theory deals with bipartite matching, network flows, and presents fundamental results for the non-bipartite case. It goes on to study elementary bipartite graphs and elementary graphs in general. Further discussed are 2-matchings, general matching problems as linear programs, the Edmonds Matching Algorithm (and other algorithmic approaches), f-factors and vertex packing.

One- and two-cluster synchronized dynamics of non-diffusively coupled Tchebycheff map networks

International Nuclear Information System (INIS)

Schäfer, Mirko; Greiner, Martin

2012-01-01

We use the master stability formalism to discuss one- and two-cluster synchronization of coupled Tchebycheff map networks. For diffusively coupled map systems, the one-cluster synchronized dynamics is given by the behaviour of the individual maps, and the coupling only determines the stability of the coherent state. For the case of non-diffusive coupling and for two-cluster synchronization, the synchronized dynamics on networks is different from the behaviour of the single individual map. Depending on the coupling, we study numerically the characteristics of various forms of the resulting synchronized dynamics. The stability properties of the respective one-cluster synchronized states are discussed for arbitrary network structures. For the case of two-cluster synchronization on bipartite networks we also present analytical expressions for fixed points and zig-zag patterns, and explicitly determine the linear stability of these orbits for the special case of ring-networks.

Protein Inference from the Integration of Tandem MS Data and Interactome Networks.

Science.gov (United States)

Zhong, Jiancheng; Wang, Jianxing; Ding, Xiaojun; Zhang, Zhen; Li, Min; Wu, Fang-Xiang; Pan, Yi

2017-01-01

Since proteins are digested into a mixture of peptides in the preprocessing step of tandem mass spectrometry (MS), it is difficult to determine which specific protein a shared peptide belongs to. In recent studies, besides tandem MS data and peptide identification information, some other information is exploited to infer proteins. Different from the methods which first use only tandem MS data to infer proteins and then use network information to refine them, this study proposes a protein inference method named TMSIN, which uses interactome networks directly. As two interacting proteins should co-exist, it is reasonable to assume that if one of the interacting proteins is confidently inferred in a sample, its interacting partners should have a high probability in the same sample, too. Therefore, we can use the neighborhood information of a protein in an interactome network to adjust the probability that the shared peptide belongs to the protein. In TMSIN, a multi-weighted graph is constructed by incorporating the bipartite graph with interactome network information, where the bipartite graph is built with the peptide identification information. Based on multi-weighted graphs, TMSIN adopts an iterative workflow to infer proteins. At each iterative step, the probability that a shared peptide belongs to a specific protein is calculated by using the Bayes' law based on the neighbor protein support scores of each protein which are mapped by the shared peptides. We carried out experiments on yeast data and human data to evaluate the performance of TMSIN in terms of ROC, q-value, and accuracy. The experimental results show that AUC scores yielded by TMSIN are 0.742 and 0.874 in yeast dataset and human dataset, respectively, and TMSIN yields the maximum number of true positives when q-value less than or equal to 0.05. The overlap analysis shows that TMSIN is an effective complementary approach for protein inference.

Reduction of multipartite qubit density matrixes to bipartite qubit density matrixes and criteria of partial separability of multipartite qubit density matrixes

OpenAIRE

Zhong, Zai-Zhe

2004-01-01

The partial separability of multipartite qubit density matrixes is strictly defined. We give a reduction way from N-partite qubit density matrixes to bipartite qubit density matrixes, and prove a necessary condition that a N-partite qubit density matrix to be partially separable is its reduced density matrix to satisfy PPT condition.

Detection of stable community structures within gut microbiota co-occurrence networks from different human populations.

Science.gov (United States)

Jackson, Matthew A; Bonder, Marc Jan; Kuncheva, Zhana; Zierer, Jonas; Fu, Jingyuan; Kurilshikov, Alexander; Wijmenga, Cisca; Zhernakova, Alexandra; Bell, Jordana T; Spector, Tim D; Steves, Claire J

2018-01-01

Microbes in the gut microbiome form sub-communities based on shared niche specialisations and specific interactions between individual taxa. The inter-microbial relationships that define these communities can be inferred from the co-occurrence of taxa across multiple samples. Here, we present an approach to identify comparable communities within different gut microbiota co-occurrence networks, and demonstrate its use by comparing the gut microbiota community structures of three geographically diverse populations. We combine gut microbiota profiles from 2,764 British, 1,023 Dutch, and 639 Israeli individuals, derive co-occurrence networks between their operational taxonomic units, and detect comparable communities within them. Comparing populations we find that community structure is significantly more similar between datasets than expected by chance. Mapping communities across the datasets, we also show that communities can have similar associations to host phenotypes in different populations. This study shows that the community structure within the gut microbiota is stable across populations, and describes a novel approach that facilitates comparative community-centric microbiome analyses.

Conditional mutual information of bipartite unitaries and scrambling

Energy Technology Data Exchange (ETDEWEB)

Ding, Dawei; Hayden, Patrick; Walter, Michael [Stanford Institute for Theoretical Physics, Department of Physics, Stanford University,382 Via Pueblo, Stanford, CA 94305 (United States)

2016-12-28

One way to diagnose chaos in bipartite unitary channels is via the tripartite information of the corresponding Choi state, which for certain choices of the subsystems reduces to the negative conditional mutual information (CMI). We study this quantity from a quantum information-theoretic perspective to clarify its role in diagnosing scrambling. When the CMI is zero, we find that the channel has a special normal form consisting of local channels between individual inputs and outputs. However, we find that arbitrarily low CMI does not imply arbitrary proximity to a channel of this form, although it does imply a type of approximate recoverability of one of the inputs. When the CMI is maximal, we find that the residual channel from an individual input to an individual output is completely depolarizing when the other input is maximally mixed. However, we again find that this result is not robust. We also extend some of these results to the multipartite case and to the case of Haar-random pure input states. Finally, we look at the relationship between tripartite information and its Rényi-2 version which is directly related to out-of-time-order correlation functions. In particular, we demonstrate an arbitrarily large gap between the two quantities.

The value of conflict in stable social networks

Science.gov (United States)

Pramukkul, Pensri; Svenkeson, Adam; West, Bruce J.; Grigolini, Paolo

2015-09-01

A cooperative network model of sociological interest is examined to determine the sensitivity of the global dynamics to having a fraction of the members behaving uncooperatively, that is, being in conflict with the majority. We study a condition where in the absence of these uncooperative individuals, the contrarians, the control parameter exceeds a critical value and the network is frozen in a state of consensus. The network dynamics change with variations in the percentage of contrarians, resulting in a balance between the value of the control parameter and the percentage of those in conflict with the majority. We show that, as a finite-size effect, the transmission of information from a network B to a network A, with a small fraction of lookout members in A who adopt the behavior of B, becomes maximal when both networks are assigned the same critical percentage of contrarians.

Scaling down from species to individuals: a flower-visitation network between individual honeybees and thistle plants

DEFF Research Database (Denmark)

Dupont, Yoko; Nielsen, Kristian T.; Olesen, Jens Mogens

2011-01-01

stems and monitored all floral visits. The constructed bipartite network of individual plants and bees had a high connectance and low nestedness, but it was not significantly modular. Frequency distributions of number of links per species (i.e. linkage level) had their best fit to a truncated power law......, and interactions were asymmetrical. Unipartite networks of either plants or bees had exceedingly short average path length and high clustering. Linkage level of plants increased with their number of flower heads and height of inflorescence (floral display parameters). Overall, the individual network of honeybees...... and thistles was denser linked than what is known from species pollination networks. Characteristics of both plants (e.g. floral display) and animals (e.g. foraging behaviour) are likely to generate this intra–specific, inter–individual link pattern. Such features of individual–individual networks may scale up...

Dynamics of chaotic strings

International Nuclear Information System (INIS)

Schaefer, Mirko

2011-01-01

The main topic of this thesis is the investigation of dynamical properties of coupled Tchebycheff map networks. The results give insights into the chaotic string model and its network generalization from a dynamical point of view. As a first approach, discrete symmetry transformations of the model are studied. These transformations are formulated in a general way in order to be also applicable to similar dynamics on bipartite network structures. The dynamics is studied numerically via Lyapunov measures, spatial correlations, and ergodic properties. It is shown that the zeros of the interaction energy are distinguished only with respect to this specific observable, but not by a more general dynamical principle. The original chaotic string model is defined on a one-dimensional lattice (ring-network) as the underlying network topology. This thesis studies a modification of the model based on the introduction of tunable disorder. The effects of inhomogeneous coupling weights as well as small-world perturbations of the ring-network structure on the interaction energy are discussed. Synchronization properties of the chaotic string model and its network generalization are studied in later chapters of this thesis. The analysis is based on the master stability formalism, which relates the stability of the synchronized state to the spectral properties of the network. Apart from complete synchronization, where the dynamics at all nodes of the network coincide, also two-cluster synchronization on bipartite networks is studied. For both types of synchronization it is shown that depending on the type of coupling the synchronized dynamics can display chaotic as well as periodic or quasi-periodic behaviour. The semi-analytical calculations reveal that the respective synchronized states are often stable for a wide range of coupling values even for the ring-network, although the respective basins of attraction may inhabit only a small fraction of the phase space. To provide

Modular architectures for quantum networks

Science.gov (United States)

Pirker, A.; Wallnöfer, J.; Dür, W.

2018-05-01

We consider the problem of generating multipartite entangled states in a quantum network upon request. We follow a top-down approach, where the required entanglement is initially present in the network in form of network states shared between network devices, and then manipulated in such a way that the desired target state is generated. This minimizes generation times, and allows for network structures that are in principle independent of physical links. We present a modular and flexible architecture, where a multi-layer network consists of devices of varying complexity, including quantum network routers, switches and clients, that share certain resource states. We concentrate on the generation of graph states among clients, which are resources for numerous distributed quantum tasks. We assume minimal functionality for clients, i.e. they do not participate in the complex and distributed generation process of the target state. We present architectures based on shared multipartite entangled Greenberger–Horne–Zeilinger states of different size, and fully connected decorated graph states, respectively. We compare the features of these architectures to an approach that is based on bipartite entanglement, and identify advantages of the multipartite approach in terms of memory requirements and complexity of state manipulation. The architectures can handle parallel requests, and are designed in such a way that the network state can be dynamically extended if new clients or devices join the network. For generation or dynamical extension of the network states, we propose a quantum network configuration protocol, where entanglement purification is used to establish high fidelity states. The latter also allows one to show that the entanglement generated among clients is private, i.e. the network is secure.

The bipartite mitochondrial genome of Ruizia karukerae (Rhigonematomorpha, Nematoda).

Science.gov (United States)

Kim, Taeho; Kern, Elizabeth; Park, Chungoo; Nadler, Steven A; Bae, Yeon Jae; Park, Joong-Ki

2018-05-10

Mitochondrial genes and whole mitochondrial genome sequences are widely used as molecular markers in studying population genetics and resolving both deep and shallow nodes in phylogenetics. In animals the mitochondrial genome is generally composed of a single chromosome, but mystifying exceptions sometimes occur. We determined the complete mitochondrial genome of the millipede-parasitic nematode Ruizia karukerae and found its mitochondrial genome consists of two circular chromosomes, which is highly unusual in bilateral animals. Chromosome I is 7,659 bp and includes six protein-coding genes, two rRNA genes and nine tRNA genes. Chromosome II comprises 7,647 bp, with seven protein-coding genes and 16 tRNA genes. Interestingly, both chromosomes share a 1,010 bp sequence containing duplicate copies of cox2 and three tRNA genes (trnD, trnG and trnH), and the nucleotide sequences between the duplicated homologous gene copies are nearly identical, suggesting a possible recent genesis for this bipartite mitochondrial genome. Given that little is known about the formation, maintenance or evolution of abnormal mitochondrial genome structures, R. karukerae mtDNA may provide an important early glimpse into this process.

Hybrid recommendation methods in complex networks.

Science.gov (United States)

Fiasconaro, A; Tumminello, M; Nicosia, V; Latora, V; Mantegna, R N

2015-07-01

We propose two recommendation methods, based on the appropriate normalization of already existing similarity measures, and on the convex combination of the recommendation scores derived from similarity between users and between objects. We validate the proposed measures on three data sets, and we compare the performance of our methods to other recommendation systems recently proposed in the literature. We show that the proposed similarity measures allow us to attain an improvement of performances of up to 20% with respect to existing nonparametric methods, and that the accuracy of a recommendation can vary widely from one specific bipartite network to another, which suggests that a careful choice of the most suitable method is highly relevant for an effective recommendation on a given system. Finally, we study how an increasing presence of random links in the network affects the recommendation scores, finding that one of the two recommendation algorithms introduced here can systematically outperform the others in noisy data sets.

Neural Correlates of Phrase Rhythm: An EEG Study of Bipartite vs. Rondo Sonata Form

Directory of Open Access Journals (Sweden)

Antonio Fernández-Caballero

2017-04-01

Full Text Available This paper introduces the neural correlates of phrase rhythm. In short, phrase rhythm is the rhythmic aspect of phrase construction and the relationships between phrases. For the sake of establishing the neural correlates, a musical experiment has been designed to induce music-evoked stimuli related to phrase rhythm. Brain activity is monitored through electroencephalography (EEG by using a brain–computer interface. The power spectral value of each EEG channel is estimated to obtain how power variance distributes as a function of frequency. Our experiment shows statistical differences in theta and alpha bands in the phrase rhythm variations of two classical sonatas, one in bipartite form and the other in rondo form.

Network structure and institutional complexity in an ecology of water management games

Directory of Open Access Journals (Sweden)

Mark Lubell

2014-12-01

Full Text Available Social-ecological systems are governed by a complex of ecology of games featuring multiple actors, policy institutions, and issues, and not just single institutions operating in isolation. We update Long's (1958 ecology of games to analyze the coordinating roles of actors and institutions in the context of the ecology of water management games in San Francisco Bay, California. The ecology of games is operationalized as a bipartite network with actors participating in institutions, and exponential random graph models are used to test hypotheses about the structural features of the network. We found that policy coordination is facilitated mostly by federal and state agencies and collaborative institutions that span geographic boundaries. Network configurations associated with closure show the most significant departures from the predicted model values, consistent with the Berardo and Scholz (2010 "risk hypothesis" that closure is important for solving cooperation problems.

The players may change but the game remains: network analyses of ruminal microbiomes suggest taxonomic differences mask functional similarity

Science.gov (United States)

Taxis, Tasia M.; Wolff, Sara; Gregg, Sarah J.; Minton, Nicholas O.; Zhang, Chiqian; Dai, Jingjing; Schnabel, Robert D.; Taylor, Jeremy F.; Kerley, Monty S.; Pires, J. Chris; Lamberson, William R.; Conant, Gavin C.

2015-01-01

By mapping translated metagenomic reads to a microbial metabolic network, we show that ruminal ecosystems that are rather dissimilar in their taxonomy can be considerably more similar at the metabolic network level. Using a new network bi-partition approach for linking the microbial network to a bovine metabolic network, we observe that these ruminal metabolic networks exhibit properties consistent with distinct metabolic communities producing similar outputs from common inputs. For instance, the closer in network space that a microbial reaction is to a reaction found in the host, the lower will be the variability of its enzyme copy number across hosts. Similarly, these microbial enzymes that are nearby to host nodes are also higher in copy number than are more distant enzymes. Collectively, these results demonstrate a widely expected pattern that, to our knowledge, has not been explicitly demonstrated in microbial communities: namely that there can exist different community metabolic networks that have the same metabolic inputs and outputs but differ in their internal structure. PMID:26420832

Topological network entanglement as order parameter for the emergence of geometry

International Nuclear Information System (INIS)

Diamantini, M Cristina; Trugenberger, Carlo A

2017-01-01

We show that, in discrete models of quantum gravity, emergent geometric space can be viewed as the entanglement pattern in a mixed quantum state of the ‘universe’, characterized by a universal topological network entanglement. As a concrete example we analyze the recently proposed model in which geometry emerges due to the condensation of 4-cycles in random regular bipartite graphs, driven by the combinatorial Ollivier–Ricci curvature. Using this model we show that the emergence of geometric order decreases the entanglement entropy of random configurations. The lowest geometric entanglement entropy is realized in four dimensions. (paper)

The N Terminus of the Retinoblastoma Protein Inhibits DNA Replication via a Bipartite Mechanism Disrupted in Partially Penetrant Retinoblastomas

Science.gov (United States)

Borysov, Sergiy I.; Nepon-Sixt, Brook S.

2015-01-01

The N-terminal domain of the retinoblastoma (Rb) tumor suppressor protein (RbN) harbors in-frame exon deletions in partially penetrant hereditary retinoblastomas and is known to impair cell growth and tumorigenesis. However, how such RbN deletions contribute to Rb tumor- and growth-suppressive functions is unknown. Here we establish that RbN directly inhibits DNA replication initiation and elongation using a bipartite mechanism involving N-terminal exons lost in cancer. Specifically, Rb exon 7 is necessary and sufficient to target and inhibit the replicative CMG helicase, resulting in the accumulation of inactive CMGs on chromatin. An independent N-terminal loop domain, which forms a projection, specifically blocks DNA polymerase α (Pol-α) and Ctf4 recruitment without affecting DNA polymerases ε and δ or the CMG helicase. Individual disruption of exon 7 or the projection in RbN or Rb, as occurs in inherited cancers, partially impairs the ability of Rb/RbN to inhibit DNA replication and block G1-to-S cell cycle transit. However, their combined loss abolishes these functions of Rb. Thus, Rb growth-suppressive functions include its ability to block replicative complexes via bipartite, independent, and additive N-terminal domains. The partial loss of replication, CMG, or Pol-α control provides a potential molecular explanation for how N-terminal Rb loss-of-function deletions contribute to the etiology of partially penetrant retinoblastomas. PMID:26711265

Ag-bridged Ag{sub 2}O nanowire network/TiO{sub 2} nanotube array p–n heterojunction as a highly efficient and stable visible light photocatalyst

Energy Technology Data Exchange (ETDEWEB)

Liu, Chengbin, E-mail: chem_cbliu@hnu.edu.cn [Key Laboratory of Jiangxi Province for Persistent Pollutants Control and Resources Recycle, Nanchang Hangkong University, Nanchang 330063 (China); State Key Laboratory of Chemo/Biosensing and Chemometrics, Hunan University, Changsha 410082 (China); Cao, Chenghao [State Key Laboratory of Chemo/Biosensing and Chemometrics, Hunan University, Changsha 410082 (China); Luo, Xubiao [Key Laboratory of Jiangxi Province for Persistent Pollutants Control and Resources Recycle, Nanchang Hangkong University, Nanchang 330063 (China); Luo, Shenglian [Key Laboratory of Jiangxi Province for Persistent Pollutants Control and Resources Recycle, Nanchang Hangkong University, Nanchang 330063 (China); State Key Laboratory of Chemo/Biosensing and Chemometrics, Hunan University, Changsha 410082 (China)

2015-03-21

Graphical abstract: A unique Ag-bridged Ag{sub 2}O nanowire network/TiO{sub 2} nanotube array p–n heterojunction was fabricated by simple electrochemical method. The heterostructures exhibit high photocatalytic activity and excellent recycling performance. - Highlights: • Ag-bridged Ag{sub 2}O nanowire network self-stability structure. • Ag{sub 2}O nanowire network/TiO{sub 2} nanotube p–n heterojunction. • High visible light photocatalytic activity. • Highly stable recycling performance. - Abstract: A unique Ag-bridged Ag{sub 2}O nanowire network/TiO{sub 2} nanotube array p–n heterojunction (Ag–Ag{sub 2}O/TiO{sub 2} NT) was fabricated by simple electrochemical method. Ag nanoparticles were firstly electrochemically deposited onto the surface of TiO{sub 2} NT and then were partly oxidized to Ag{sub 2}O nanowires while the rest of Ag mother nanoparticles were located at the junctions of Ag{sub 2}O nanowire network. The Ag–Ag{sub 2}O/TiO{sub 2} NT heterostructure exhibited strong visible-light response, effective separation of photogenerated carriers, and high adsorption capacity. The integration of Ag–Ag{sub 2}O self-stability structure and p–n heterojunction permitted high and stable photocatalytic activity of Ag–Ag{sub 2}O/TiO{sub 2} NT heterostructure photocatalyst. Under 140-min visible light irradiation, the photocatalytic removal efficiency of both dye acid orange 7 (AO7) and industrial chemical p-nitrophenol (PNP) over Ag–Ag{sub 2}O/TiO{sub 2} NT reached nearly 100% much higher than 17% for AO7 or 13% for PNP over bare TiO{sub 2} NT. After 5 successive cycles under 600-min simulated solar light irradiation, Ag–Ag{sub 2}O/TiO{sub 2} NT remained highly stable photocatalytic activity.

Editorial Commentary: Got Evidence? What We Really Need Is an Algorithm for Treating Symptomatic Bipartite Patella.

Science.gov (United States)

Fithian, Donald C

2018-05-01

Bipartite patella is an uncommon but potentially troublesome problem for young athletes. Numerous uncontrolled retrospective studies have reported good results after various treatments. What is needed are studies that will guide workup and support treatment decisions based on the condition of the cartilage surfaces of the fragment, presence of pseudoarthrosis, and size and location of the fragment. To support decisions, we need prospective comparative studies, either randomized or, at least, prospective cohort studies that identify patients at the time of presentation, document key decision points, and follow patients to successful resolution of symptoms. Copyright © 2018 Arthroscopy Association of North America. Published by Elsevier Inc. All rights reserved.

Entanglement dynamics of high-dimensional bipartite field states inside the cavities in dissipative environments

Energy Technology Data Exchange (ETDEWEB)

Tahira, Rabia; Ikram, Manzoor; Zubairy, M Suhail [Centre for Quantum Physics, COMSATS Institute of Information Technology, Islamabad (Pakistan); Bougouffa, Smail [Department of Physics, Faculty of Science, Taibah University, PO Box 30002, Madinah (Saudi Arabia)

2010-02-14

We investigate the phenomenon of sudden death of entanglement in a high-dimensional bipartite system subjected to dissipative environments with an arbitrary initial pure entangled state between two fields in the cavities. We find that in a vacuum reservoir, the presence of the state where one or more than one (two) photons in each cavity are present is a necessary condition for the sudden death of entanglement. Otherwise entanglement remains for infinite time and decays asymptotically with the decay of individual qubits. For pure two-qubit entangled states in a thermal environment, we observe that sudden death of entanglement always occurs. The sudden death time of the entangled states is related to the number of photons in the cavities, the temperature of the reservoir and the initial preparation of the entangled states.

Entanglement dynamics of high-dimensional bipartite field states inside the cavities in dissipative environments

International Nuclear Information System (INIS)

Tahira, Rabia; Ikram, Manzoor; Zubairy, M Suhail; Bougouffa, Smail

2010-01-01

We investigate the phenomenon of sudden death of entanglement in a high-dimensional bipartite system subjected to dissipative environments with an arbitrary initial pure entangled state between two fields in the cavities. We find that in a vacuum reservoir, the presence of the state where one or more than one (two) photons in each cavity are present is a necessary condition for the sudden death of entanglement. Otherwise entanglement remains for infinite time and decays asymptotically with the decay of individual qubits. For pure two-qubit entangled states in a thermal environment, we observe that sudden death of entanglement always occurs. The sudden death time of the entangled states is related to the number of photons in the cavities, the temperature of the reservoir and the initial preparation of the entangled states.

A network flow algorithm to position tiles for LAMOST

International Nuclear Information System (INIS)

Li Guangwei; Zhao Gang

2009-01-01

We introduce the network flow algorithm used by the Sloan Digital Sky Survey (SDSS) into the sky survey of the Large sky Area Multi-Object fiber Spectroscopic Telescope (LAMOST) to position tiles. Because fibers in LAMOST's focal plane are distributed uniformly, we cannot use SDSS' method directly. To solve this problem, firstly we divide the sky into many small blocks, and we also assume that all the targets that are in the same block have the same position, which is the center of the block. Secondly, we give a value to limit the number of the targets that the LAMOST focal plane can collect in one square degree so that it cannot collect too many targets in one small block. Thirdly, because the network flow algorithm used in this paper is a bipartite network, we do not use the general solution algorithm that was used by SDSS. Instead, we give our new faster solution method for this special network. Compared with the Convergent Mean Shift Algorithm, the network flow algorithm can decrease observation times with improved mean imaging quality. This algorithm also has a very fast running speed. It can distribute millions of targets in a few minutes using a common personal computer.

Ground states, magnetization plateaus and bipartite entanglement of frustrated spin-1/2 Ising-Heisenberg and Heisenberg triangular tubes

International Nuclear Information System (INIS)

Alécio, Raphael C.; Lyra, Marcelo L.; Strečka, Jozef

2016-01-01

The ground-state phase diagram, magnetization process and bipartite entanglement of the frustrated spin-1/2 Ising-Heisenberg and Heisenberg triangular tube (three-leg ladder) are investigated in a non-zero external magnetic field. The exact ground-state phase diagram of the spin-1/2 Ising-Heisenberg tube with Heisenberg intra-rung and Ising inter-rung couplings consists of six distinct gapped phases, which manifest themselves in a magnetization curve as intermediate plateaus at zero, one-third and two-thirds of the saturation magnetization. Four out of six available ground states exhibit quantum entanglement between two spins from the same triangular unit evidenced by a non-zero concurrence. Density-matrix renormalization group calculations are used in order to construct the ground-state phase diagram of the analogous but purely quantum spin-1/2 Heisenberg tube with Heisenberg intra- and inter-rung couplings, which consists of four gapped and three gapless phases. The Heisenberg tube shows a continuous change of the magnetization instead of a plateau at zero magnetization, while the intermediate one-third and two-thirds plateaus may be present or not in the zero-temperature magnetization curve. - Highlights: • Ground-state properties of Ising-Heisenberg and full Heisenberg spin tubes are studied. • Phases with 1/3 and 2/3 magnetization plateaus are present in both models. • We unveil the region in the parameter space on which inter-rung quantum fluctuations are relevant. • The full Heisenberg tube exhibits quantum bipartite entanglement between intra- as well as inter-rung spins.

A Network Model of Interpersonal Alignment in Dialog

Directory of Open Access Journals (Sweden)

Alexander Mehler

2010-06-01

Full Text Available In dyadic communication, both interlocutors adapt to each other linguistically, that is, they align interpersonally. In this article, we develop a framework for modeling interpersonal alignment in terms of the structural similarity of the interlocutors’ dialog lexica. This is done by means of so-called two-layer time-aligned network series, that is, a time-adjusted graph model. The graph model is partitioned into two layers, so that the interlocutors’ lexica are captured as subgraphs of an encompassing dialog graph. Each constituent network of the series is updated utterance-wise. Thus, both the inherent bipartition of dyadic conversations and their gradual development are modeled. The notion of alignment is then operationalized within a quantitative model of structure formation based on the mutual information of the subgraphs that represent the interlocutor’s dialog lexica. By adapting and further developing several models of complex network theory, we show that dialog lexica evolve as a novel class of graphs that have not been considered before in the area of complex (linguistic networks. Additionally, we show that our framework allows for classifying dialogs according to their alignment status. To the best of our knowledge, this is the first approach to measuring alignment in communication that explores the similarities of graph-like cognitive representations.

Case report of right hamate hook fracture in a patient with previous fracture history of left hamate hook: is it hamate bipartite?

Directory of Open Access Journals (Sweden)

Norton Sandra

2006-10-01

Full Text Available Abstract Background Hamate hook fracture is a common fracture in golfers and others who play sports that involve rackets or sticks such as tennis or hockey. This patient had a previous hamate fracture in the opposing wrist along with potential features of hamate bipartite. Case presentation A 19 year old male presented with a complaint of right wrist pain on the ulnar side of the wrist with no apparent mechanism of injury. The pain came on gradually one week before being seen in the office and he reported no prior care for the complaint. His history includes traumatic left hamate hook fracture with surgical excision. Conclusion The patient was found to have marked tenderness over the hamate and with a prior fracture to the other wrist, computed tomography of the wrist was ordered revealing a fracture to the hamate hook in the right wrist. He was referred for surgical evaluation and the hook of the hamate was excised. Post-surgically, the patient was able to return to normal activity within eight weeks. This case is indicative of fracture rather than hamate bipartite. This fracture should be considered in a case of ulnar sided wrist pain where marked tenderness is noted over the hamate, especially after participation in club or racket sports.

NAP: The Network Analysis Profiler, a web tool for easier topological analysis and comparison of medium-scale biological networks.

Science.gov (United States)

Theodosiou, Theodosios; Efstathiou, Georgios; Papanikolaou, Nikolas; Kyrpides, Nikos C; Bagos, Pantelis G; Iliopoulos, Ioannis; Pavlopoulos, Georgios A

2017-07-14

Nowadays, due to the technological advances of high-throughput techniques, Systems Biology has seen a tremendous growth of data generation. With network analysis, looking at biological systems at a higher level in order to better understand a system, its topology and the relationships between its components is of a great importance. Gene expression, signal transduction, protein/chemical interactions, biomedical literature co-occurrences, are few of the examples captured in biological network representations where nodes represent certain bioentities and edges represent the connections between them. Today, many tools for network visualization and analysis are available. Nevertheless, most of them are standalone applications that often (i) burden users with computing and calculation time depending on the network's size and (ii) focus on handling, editing and exploring a network interactively. While such functionality is of great importance, limited efforts have been made towards the comparison of the topological analysis of multiple networks. Network Analysis Provider (NAP) is a comprehensive web tool to automate network profiling and intra/inter-network topology comparison. It is designed to bridge the gap between network analysis, statistics, graph theory and partially visualization in a user-friendly way. It is freely available and aims to become a very appealing tool for the broader community. It hosts a great plethora of topological analysis methods such as node and edge rankings. Few of its powerful characteristics are: its ability to enable easy profile comparisons across multiple networks, find their intersection and provide users with simplified, high quality plots of any of the offered topological characteristics against any other within the same network. It is written in R and Shiny, it is based on the igraph library and it is able to handle medium-scale weighted/unweighted, directed/undirected and bipartite graphs. NAP is available at http://bioinformatics.med.uoc.gr/NAP .

Network topology: patterns and mechanisms in plant-herbivore and host-parasitoid food webs.

Science.gov (United States)

Cagnolo, Luciano; Salvo, Adriana; Valladares, Graciela

2011-03-01

1. Biological communities are organized in complex interaction networks such as food webs, which topology appears to be non-random. Gradients, compartments, nested subsets and even combinations of these structures have been shown in bipartite networks. However, in most studies only one pattern is tested against randomness and mechanistic hypotheses are generally lacking. 2. Here we examined the topology of regional, coexisting plant-herbivore and host-parasitoid food webs to discriminate between the mentioned network patterns. We also evaluated the role of species body size, local abundance, regional frequency and phylogeny as determinants of network topology. 3. We found both food webs to be compartmented, with interaction range boundaries imposed by host phylogeny. Species degree within compartments was mostly related to their regional frequency and local abundance. Only one compartment showed an internal nested structure in the distribution of interactions between species, but species position within this compartment was unrelated to species size or abundance. 4. These results suggest that compartmentalization may be more common than previously considered, and that network structure is a result of multiple, hierarchical, non-exclusive processes. © 2010 The Authors. Journal compilation © 2010 British Ecological Society.

Uncovering packaging features of co-regulated modules based on human protein interaction and transcriptional regulatory networks

Directory of Open Access Journals (Sweden)

He Weiming

2010-07-01

Full Text Available Abstract Background Network co-regulated modules are believed to have the functionality of packaging multiple biological entities, and can thus be assumed to coordinate many biological functions in their network neighbouring regions. Results Here, we weighted edges of a human protein interaction network and a transcriptional regulatory network to construct an integrated network, and introduce a probabilistic model and a bipartite graph framework to exploit human co-regulated modules and uncover their specific features in packaging different biological entities (genes, protein complexes or metabolic pathways. Finally, we identified 96 human co-regulated modules based on this method, and evaluate its effectiveness by comparing it with four other methods. Conclusions Dysfunctions in co-regulated interactions often occur in the development of cancer. Therefore, we focussed on an example co-regulated module and found that it could integrate a number of cancer-related genes. This was extended to causal dysfunctions of some complexes maintained by several physically interacting proteins, thus coordinating several metabolic pathways that directly underlie cancer.

Singularity of classical and quantum correlations at critical points of the Lipkin-Meshkov-Glick model in bipartition and tripartition of spins

OpenAIRE

Xiu-Xing, Zhang; Fu-Li, Li

2012-01-01

We study the classical correlation (CC) and quantum discord (QD) between two spin subgroups of the Lipkin-Meshkov-Glick (LMG) model in both binary and trinary decompositions of spins. In the case of bipartition, we find that the classical correlations and all the quantum correlations including the QD, the entanglement of formation (EoF) and the logarithmic negativity (LN) are divergent in the same singular behavior at the critical point of the LMG model. In the case of tripartition, however, ...

Network theory and its applications in economic systems

Science.gov (United States)

Huang, Xuqing

This dissertation covers the two major parts of my Ph.D. research: i) developing theoretical framework of complex networks; and ii) applying complex networks models to quantitatively analyze economics systems. In part I, we focus on developing theories of interdependent networks, which includes two chapters: 1) We develop a mathematical framework to study the percolation of interdependent networks under targeted-attack and find that when the highly connected nodes are protected and have lower probability to fail, in contrast to single scale-free (SF) networks where the percolation threshold pc = 0, coupled SF networks are significantly more vulnerable with pc significantly larger than zero. 2) We analytically demonstrates that clustering, which quantifies the propensity for two neighbors of the same vertex to also be neighbors of each other, significantly increases the vulnerability of the system. In part II, we apply the complex networks models to study economics systems, which also includes two chapters: 1) We study the US corporate governance network, in which nodes representing directors and links between two directors representing their service on common company boards, and propose a quantitative measure of information and influence transformation in the network. Thus we are able to identify the most influential directors in the network. 2) We propose a bipartite networks model to simulate the risk propagation process among commercial banks during financial crisis. With empirical bank's balance sheet data in 2007 as input to the model, we find that our model efficiently identifies a significant portion of the actual failed banks reported by Federal Deposit Insurance Corporation during the financial crisis between 2008 and 2011. The results suggest that complex networks model could be useful for systemic risk stress testing for financial systems. The model also identifies that commercial rather than residential real estate assets are major culprits for the

The family Rhabdoviridae: Mono- and bipartite negative-sense RNA viruses with diverse genome organization and common evolutionary origins

Science.gov (United States)

Dietzgen, Ralf G.; Kondo, Hideki; Goodin, Michael M.; Kurath, Gael; Vasilakis, Nikos

2017-01-01

The family Rhabdoviridae consists of mostly enveloped, bullet-shaped or bacilliform viruses with a negative-sense, single-stranded RNA genome that infect vertebrates, invertebrates or plants. This ecological diversity is reflected by the diversity and complexity of their genomes. Five canonical structural protein genes are conserved in all rhabdoviruses, but may be overprinted, overlapped or interspersed with several novel and diverse accessory genes. This review gives an overview of the characteristics and diversity of rhabdoviruses, their taxonomic classification, replication mechanism, properties of classical rhabdoviruses such as rabies virus and rhabdoviruses with complex genomes, rhabdoviruses infecting aquatic species, and plant rhabdoviruses with both mono- and bipartite genomes.

Yeast ribonuclease III uses a network of multiple hydrogen bonds for RNA binding and cleavage.

Science.gov (United States)

Lavoie, Mathieu; Abou Elela, Sherif

2008-08-19

Members of the bacterial RNase III family recognize a variety of short structured RNAs with few common features. It is not clear how this group of enzymes supports high cleavage fidelity while maintaining a broad base of substrates. Here we show that the yeast orthologue of RNase III (Rnt1p) uses a network of 2'-OH-dependent interactions to recognize substrates with different structures. We designed a series of bipartite substrates permitting the distinction between binding and cleavage defects. Each substrate was engineered to carry a single or multiple 2'- O-methyl or 2'-fluoro ribonucleotide substitutions to prevent the formation of hydrogen bonds with a specific nucleotide or group of nucleotides. Interestingly, introduction of 2'- O-methyl ribonucleotides near the cleavage site increased the rate of catalysis, indicating that 2'-OH are not required for cleavage. Substitution of nucleotides in known Rnt1p binding site with 2'- O-methyl ribonucleotides inhibited cleavage while single 2'-fluoro ribonucleotide substitutions did not. This indicates that while no single 2'-OH is essential for Rnt1p cleavage, small changes in the substrate structure are not tolerated. Strikingly, several nucleotide substitutions greatly increased the substrate dissociation constant with little or no effect on the Michaelis-Menten constant or rate of catalysis. Together, the results indicate that Rnt1p uses a network of nucleotide interactions to identify its substrate and support two distinct modes of binding. One mode is primarily mediated by the dsRNA binding domain and leads to the formation of stable RNA/protein complex, while the other requires the presence of the nuclease and N-terminal domains and leads to RNA cleavage.

Fragility in dynamic networks: application to neural networks in the epileptic cortex.

Science.gov (United States)

Sritharan, Duluxan; Sarma, Sridevi V

2014-10-01

Epilepsy is a network phenomenon characterized by atypical activity at the neuronal and population levels during seizures, including tonic spiking, increased heterogeneity in spiking rates, and synchronization. The etiology of epilepsy is unclear, but a common theme among proposed mechanisms is that structural connectivity between neurons is altered. It is hypothesized that epilepsy arises not from random changes in connectivity, but from specific structural changes to the most fragile nodes or neurons in the network. In this letter, the minimum energy perturbation on functional connectivity required to destabilize linear networks is derived. Perturbation results are then applied to a probabilistic nonlinear neural network model that operates at a stable fixed point. That is, if a small stimulus is applied to the network, the activation probabilities of each neuron respond transiently but eventually recover to their baseline values. When the perturbed network is destabilized, the activation probabilities shift to larger or smaller values or oscillate when a small stimulus is applied. Finally, the structural modifications to the neural network that achieve the functional perturbation are derived. Simulations of the unperturbed and perturbed networks qualitatively reflect neuronal activity observed in epilepsy patients, suggesting that the changes in network dynamics due to destabilizing perturbations, including the emergence of an unstable manifold or a stable limit cycle, may be indicative of neuronal or population dynamics during seizure. That is, the epileptic cortex is always on the brink of instability and minute changes in the synaptic weights associated with the most fragile node can suddenly destabilize the network to cause seizures. Finally, the theory developed here and its interpretation of epileptic networks enables the design of a straightforward feedback controller that first detects when the network has destabilized and then applies linear state

Stable isotope views on ecosystem function: challenging or challenged?

Science.gov (United States)

Resco, Víctor; Querejeta, José I; Ogle, Kiona; Voltas, Jordi; Sebastià, Maria-Teresa; Serrano-Ortiz, Penélope; Linares, Juan C; Moreno-Gutiérrez, Cristina; Herrero, Asier; Carreira, José A; Torres-Cañabate, Patricia; Valladares, Fernando

2010-06-23

Stable isotopes and their potential for detecting various and complex ecosystem processes are attracting an increasing number of scientists. Progress is challenging, particularly under global change scenarios, but some established views have been challenged. The IX meeting of the Spanish Association of Terrestrial Ecology (AAET, Ubeda, 18-22 October 2009) hosted a symposium on the ecology of stable isotopes where the linear mixing model approach of partitioning sinks and sources of carbon and water fluxes within an ecosystem was challenged, and new applications of stable isotopes for the study of plant interactions were evaluated. Discussion was also centred on the need for networks that monitor ecological processes using stable isotopes and key ideas for fostering future research with isotopes.

Integration versus Outsourcing in Stable Industry Equilibrium with Communication Networks

OpenAIRE

Okamoto, Yusuke

2006-01-01

For the selection of a firm's structure between vertical integration and arm's-length outsourcing, the importance of the thickness of the market had been emphasized in the previous literature. Here we take account of communication networks such as telephone, telex, fax, and the Internet. By doing so, we could illustrate the relationship between communication networks and the make-or-buy decision. With communication network technology differing in each type of firm, both vertically integrated ...

Spatial-Frequency Azimuthally Stable Cartography of Biological Polycrystalline Networks

Directory of Open Access Journals (Sweden)

V. A. Ushenko

2013-01-01

Full Text Available A new azimuthally stable polarimetric technique processing microscopic images of optically anisotropic structures of biological tissues histological sections is proposed. It has been used as a generalized model of phase anisotropy definition of biological tissues by using superposition of Mueller matrices of linear birefringence and optical activity. The matrix element M44 has been chosen as the main information parameter, whose value is independent of the rotation angle of both sample and probing beam polarization plane. For the first time, the technique of concerted spatial-frequency filtration has been used in order to separate the manifestation of linear birefringence and optical activity. Thereupon, the method of azimuthally stable spatial-frequency cartography of biological tissues histological sections has been elaborated. As the analyzing tool, complex statistic, correlation, and fractal analysis of coordinate distributions of M44 element has been performed. The possibility of using the biopsy of the uterine wall tissue in order to differentiate benign (fibromyoma and malignant (adenocarcinoma conditions has been estimated.

The family Rhabdoviridae: mono- and bipartite negative-sense RNA viruses with diverse genome organization and common evolutionary origins.

Science.gov (United States)

Dietzgen, Ralf G; Kondo, Hideki; Goodin, Michael M; Kurath, Gael; Vasilakis, Nikos

2017-01-02

The family Rhabdoviridae consists of mostly enveloped, bullet-shaped or bacilliform viruses with a negative-sense, single-stranded RNA genome that infect vertebrates, invertebrates or plants. This ecological diversity is reflected by the diversity and complexity of their genomes. Five canonical structural protein genes are conserved in all rhabdoviruses, but may be overprinted, overlapped or interspersed with several novel and diverse accessory genes. This review gives an overview of the characteristics and diversity of rhabdoviruses, their taxonomic classification, replication mechanism, properties of classical rhabdoviruses such as rabies virus and rhabdoviruses with complex genomes, rhabdoviruses infecting aquatic species, and plant rhabdoviruses with both mono- and bipartite genomes. Copyright © 2016 Elsevier B.V. All rights reserved.

Stable isotope views on ecosystem function: challenging or challenged?

Science.gov (United States)

Resco, Víctor; Querejeta, José I.; Ogle, Kiona; Voltas, Jordi; Sebastià, Maria-Teresa; Serrano-Ortiz, Penélope; Linares, Juan C.; Moreno-Gutiérrez, Cristina; Herrero, Asier; Carreira, José A.; Torres-Cañabate, Patricia; Valladares, Fernando

2010-01-01

Stable isotopes and their potential for detecting various and complex ecosystem processes are attracting an increasing number of scientists. Progress is challenging, particularly under global change scenarios, but some established views have been challenged. The IX meeting of the Spanish Association of Terrestrial Ecology (AAET, Úbeda, 18–22 October 2009) hosted a symposium on the ecology of stable isotopes where the linear mixing model approach of partitioning sinks and sources of carbon and water fluxes within an ecosystem was challenged, and new applications of stable isotopes for the study of plant interactions were evaluated. Discussion was also centred on the need for networks that monitor ecological processes using stable isotopes and key ideas for fostering future research with isotopes. PMID:20015858

Entanglement in bipartite pure states of an interacting boson gas obtained by local projective measurements

International Nuclear Information System (INIS)

Paraan, Francis N. C.; Korepin, Vladimir E.; Molina-Vilaplana, Javier; Bose, Sougato

2011-01-01

We quantify the extractable entanglement of excited states of a Lieb-Liniger gas that are obtained from coarse-grained measurements on the ground state in which the boson number in one of two complementary contiguous partitions of the gas is determined. Numerically exact results obtained from the coordinate Bethe ansatz show that the von Neumann entropy of the resulting bipartite pure state increases monotonically with the strength of repulsive interactions and saturates to the impenetrable-boson limiting value. We also present evidence indicating that the largest amount of entanglement can be extracted from the most probable projected state having half the number of bosons in a given partition. Our study points to a fundamental difference between the nature of the entanglement in free-bosonic and free-fermionic systems, with the entanglement in the former being zero after projection, while that in the latter (corresponding to the impenetrable-boson limit) being nonzero.

Detecting phase boundaries of quantum spin-1/2 XXZ ladder via bipartite and multipartite entanglement transitions

Science.gov (United States)

Singha Roy, Sudipto; Dhar, Himadri Shekhar; Rakshit, Debraj; Sen(De), Aditi; Sen, Ujjwal

2017-12-01

Phase transition in quantum many-body systems inevitably causes changes in certain physical properties which then serve as potential indicators of critical phenomena. Besides the traditional order parameters, characterization of quantum entanglement has proven to be a computationally efficient and successful method for detection of phase boundaries, especially in one-dimensional models. Here we determine the rich phase diagram of the ground states of a quantum spin-1/2 XXZ ladder by analyzing the variation of bipartite and multipartite entanglements. Our study characterizes the different ground state phases and notes the correspondence with known results, while highlighting the finer details that emerge from the behavior of ground state entanglement. Analysis of entanglement in the ground state provides a clearer picture of the complex ground state phase diagram of the system using only a moderate-size model.

Influence of intrinsic decoherence on tripartite entanglement and bipartite fidelity of polar molecules in pendular states

Energy Technology Data Exchange (ETDEWEB)

Han, Jia-Xing; Hu, Yuan; Jin, Yu [Key Laboratory of Micro-Nano Measurement-Manipulation and Physics (Ministry of Education), School of Physics and Nuclear Energy Engineering, Beihang University, Xueyuan Road No. 37, Beijing 100191 (China); Zhang, Guo-Feng, E-mail: gf1978zhang@buaa.edu.cn [Key Laboratory of Micro-Nano Measurement-Manipulation and Physics (Ministry of Education), School of Physics and Nuclear Energy Engineering, Beihang University, Xueyuan Road No. 37, Beijing 100191 (China); State Key Laboratory of Software Development Environment, Beihang University, Xueyuan Road No. 37, Beijing 100191 (China); State Key Laboratory of Low-Dimensional Quantum Physics, Tsinghua University, Beijing 100084 (China); Key Laboratory of Quantum Information, University of Science and Technology of China, Chinese Academy of Sciences, Hefei 230026 (China)

2016-04-07

An array of ultracold polar molecules trapped in an external electric field is regarded as a promising carrier of quantum information. Under the action of this field, molecules are compelled to undergo pendular oscillations by the Stark effect. Particular attention has been paid to the influence of intrinsic decoherence on the model of linear polar molecular pendular states, thereby we evaluate the tripartite entanglement with negativity, as well as fidelity of bipartite quantum systems for input and output signals using electric dipole moments of polar molecules as qubits. According to this study, we consider three typical initial states for both systems, respectively, and investigate the temporal evolution with variable values of the external field intensity, the intrinsic decoherence factor, and the dipole-dipole interaction. Thus, we demonstrate the sound selection of these three main parameters to obtain the best entanglement degree and fidelity.

Electrodeposited Structurally Stable V2O5 Inverse Opal Networks as High Performance Thin Film Lithium Batteries.

Science.gov (United States)

Armstrong, Eileen; McNulty, David; Geaney, Hugh; O'Dwyer, Colm

2015-12-09

High performance thin film lithium batteries using structurally stable electrodeposited V2O5 inverse opal (IO) networks as cathodes provide high capacity and outstanding cycling capability and also were demonstrated on transparent conducting oxide current collectors. The superior electrochemical performance of the inverse opal structures was evaluated through galvanostatic and potentiodynamic cycling, and the IO thin film battery offers increased capacity retention compared to micron-scale bulk particles from improved mechanical stability and electrical contact to stainless steel or transparent conducting current collectors from bottom-up electrodeposition growth. Li(+) is inserted into planar and IO structures at different potentials, and correlated to a preferential exposure of insertion sites of the IO network to the electrolyte. Additionally, potentiodynamic testing quantified the portion of the capacity stored as surface bound capacitive charge. Raman scattering and XRD characterization showed how the IO allows swelling into the pore volume rather than away from the current collector. V2O5 IO coin cells offer high initial capacities, but capacity fading can occur with limited electrolyte. Finally, we demonstrate that a V2O5 IO thin film battery prepared on a transparent conducting current collector with excess electrolyte exhibits high capacities (∼200 mAh g(-1)) and outstanding capacity retention and rate capability.

Finding Non-Zero Stable Fixed Points of the Weighted Kuramoto model is NP-hard

OpenAIRE

Taylor, Richard

2015-01-01

The Kuramoto model when considered over the full space of phase angles [$0,2\\pi$) can have multiple stable fixed points which form basins of attraction in the solution space. In this paper we illustrate the fundamentally complex relationship between the network topology and the solution space by showing that determining the possibility of multiple stable fixed points from the network topology is NP-hard for the weighted Kuramoto Model. In the case of the unweighted model this problem is shown...

Dynamic Innovation strategies and stable networks in the construction industry

DEFF Research Database (Denmark)

Andersen, Poul Houman; Cook, Nicole; Marceau, Jane

2004-01-01

This paper investigate the role of interorganisational networking for technology diffusion in an industry characterized by very limited R&D activity. Udgivelsesdato: APR......This paper investigate the role of interorganisational networking for technology diffusion in an industry characterized by very limited R&D activity. Udgivelsesdato: APR...

Effect of two-qutrit entanglement on quantum speed limit time of a bipartite V-type open system

Energy Technology Data Exchange (ETDEWEB)

Behzadi, N., E-mail: n.behzadi@tabrizu.ac.ir [Research Institute for Fundamental Sciences, University of Tabriz (Iran, Islamic Republic of); Ahansaz, B.; Ektesabi, A.; Faizi, E. [Physics Department, Azarbaijan Shahid Madani University, Tabriz (Iran, Islamic Republic of)

2017-03-15

In the present paper, quantum speed limit (QSL) time of a bipartite V-type three-level atomic system under the effect of two-qutrit entanglement is investigated. Each party interacts with own independent reservoir. By considering two local unitarily equivalent Werner states and the Horodecki PPT state, as initial states, the QSL time is evaluated for each of them in the respective entangled regions. It is counterintuitively observed that the effect of entanglement on the QSL time driven from each of the initial Werner states are completely different when the degree of non-Markovianity is considerable. In addition, it is interesting that the effect of entanglement of the non-equivalent Horodecki state on the calculated QSL time displays an intermediate behavior relative to the cases obtained for the Werner states.

Reaction factoring and bipartite update graphs accelerate the Gillespie Algorithm for large-scale biochemical systems.

Science.gov (United States)

Indurkhya, Sagar; Beal, Jacob

2010-01-06

ODE simulations of chemical systems perform poorly when some of the species have extremely low concentrations. Stochastic simulation methods, which can handle this case, have been impractical for large systems due to computational complexity. We observe, however, that when modeling complex biological systems: (1) a small number of reactions tend to occur a disproportionately large percentage of the time, and (2) a small number of species tend to participate in a disproportionately large percentage of reactions. We exploit these properties in LOLCAT Method, a new implementation of the Gillespie Algorithm. First, factoring reaction propensities allows many propensities dependent on a single species to be updated in a single operation. Second, representing dependencies between reactions with a bipartite graph of reactions and species requires only storage for reactions, rather than the required for a graph that includes only reactions. Together, these improvements allow our implementation of LOLCAT Method to execute orders of magnitude faster than currently existing Gillespie Algorithm variants when simulating several yeast MAPK cascade models.

Quantum teleportation via noisy bipartite and tripartite accelerating quantum states: beyond the single mode approximation

Science.gov (United States)

Zounia, M.; Shamirzaie, M.; Ashouri, A.

2017-09-01

In this paper quantum teleportation of an unknown quantum state via noisy maximally bipartite (Bell) and maximally tripartite (Greenberger-Horne-Zeilinger (GHZ)) entangled states are investigated. We suppose that one of the observers who would receive the sent state accelerates uniformly with respect to the sender. The interactions of the quantum system with its environment during the teleportation process impose noises. These (unital and nonunital) noises are: phase damping, phase flip, amplitude damping and bit flip. In expressing the modes of the Dirac field used as qubits, in the accelerating frame, the so-called single mode approximation is not imposed. We calculate the fidelities of teleportation, and discuss their behaviors using suitable plots. The effects of noise, acceleration and going beyond the single mode approximation are discussed. Although the Bell states bring higher fidelities than GHZ states, the global behaviors of the two quantum systems with respect to some noise types, and therefore their fidelities, are different.

Integration of Phenotypic Metadata and Protein Similarity in Archaea Using a Spectral Bipartitioning Approach

Energy Technology Data Exchange (ETDEWEB)

Hooper, Sean D.; Anderson, Iain J; Pati, Amrita; Dalevi, Daniel; Mavromatis, Konstantinos; Kyrpides, Nikos C

2009-01-01

In order to simplify and meaningfully categorize large sets of protein sequence data, it is commonplace to cluster proteins based on the similarity of those sequences. However, it quickly becomes clear that the sequence flexibility allowed a given protein varies significantly among different protein families. The degree to which sequences are conserved not only differs for each protein family, but also is affected by the phylogenetic divergence of the source organisms. Clustering techniques that use similarity thresholds for protein families do not always allow for these variations and thus cannot be confidently used for applications such as automated annotation and phylogenetic profiling. In this work, we applied a spectral bipartitioning technique to all proteins from 53 archaeal genomes. Comparisons between different taxonomic levels allowed us to study the effects of phylogenetic distances on cluster structure. Likewise, by associating functional annotations and phenotypic metadata with each protein, we could compare our protein similarity clusters with both protein function and associated phenotype. Our clusters can be analyzed graphically and interactively online.

Using module analysis for multiple choice responses

DEFF Research Database (Denmark)

Brewe, Eric; Bruun, Jesper; Bearden, Ian

2016-01-01

We describe a methodology for carrying out a network analysis of Force Concept Inventory (FCI) responses that aims to identify communities of incorrect responses. This method first treats FCI responses as a bipartite, student X response, network. We then use Locally Adaptive Network Sparsificatio...

An a posteriori measure of network modularity [v3; ref status: indexed, http://f1000r.es/2ju

Directory of Open Access Journals (Sweden)

Timothée Poisot

2013-12-01

Full Text Available Measuring the modularity of networks, and how it deviates from random expectations, important to understand their structure and emerging properties. Several measures exist to assess modularity, which when applied to the same network, can return both different modularity values (i.e. different estimates of how modular the network is and different module compositions (i.e. different groups of species forming said modules. More importantly, as each optimization method uses a different optimization criterion, there is a need to have an a posteriori measure serving as an equivalent of a goodness-of-fit. In this article, I propose such a measure of modularity, which is simply defined as the ratio of interactions established between members of the same modules vs. members of different modules. I apply this measure to a large dataset of 290 ecological networks representing host–parasite (bipartite and predator–prey (unipartite interactions, to show how the results are easy to interpret and present especially to a broad audience not familiar with modularity analyses, but still can reveal new features about modularity and the ways to measure it.

Correlated network of networks enhances robustness against catastrophic failures.

Science.gov (United States)

Min, Byungjoon; Zheng, Muhua

2018-01-01

Networks in nature rarely function in isolation but instead interact with one another with a form of a network of networks (NoN). A network of networks with interdependency between distinct networks contains instability of abrupt collapse related to the global rule of activation. As a remedy of the collapse instability, here we investigate a model of correlated NoN. We find that the collapse instability can be removed when hubs provide the majority of interconnections and interconnections are convergent between hubs. Thus, our study identifies a stable structure of correlated NoN against catastrophic failures. Our result further suggests a plausible way to enhance network robustness by manipulating connection patterns, along with other methods such as controlling the state of node based on a local rule.

Resource Allocation for Downlink Multi-Cell OFDMA Cognitive Radio Network Using Hungarian Method

Directory of Open Access Journals (Sweden)

N. Forouzan

2013-12-01

Full Text Available This paper considers the problem of resource allocation for downlink part of an OFDM-based multi-cell cognitive radio network which consists of multiple secondary transmitters and receivers communicating simultaneously in the presence of multiple primary users. We present a new framework to maximize the total data throughput of secondary users by means of subchannel assignment, while ensuring interference leakage to PUs is below a threshold. In this framework, we first formulate the resource allocation problem as a nonlinear and non-convex optimization problem. Then we represent the problem as a maximum weighted matching in a bipartite graph and propose an iterative algorithm based on Hungarian method to solve it. The present contribution develops an efficient subchannel allocation algorithm that assigns subchannels to the secondary users without the perfect knowledge of fading channel gain between cognitive radio transmitter and primary receivers. The performance of the proposed subcarrier allocation algorithm is compared with a blind subchannel allocation as well as another scheme with the perfect knowledge of channel-state information. Simulation results reveal that a significant performance advantage can still be realized, even if the optimization at the secondary network is based on imperfect network information.

Singularities of classical and quantum correlations at critical points of the Lipkin–Meshkov–Glick model in bipartitions and tripartitions of spins

International Nuclear Information System (INIS)

Zhang, Xiu-xing; Li, Fu-li

2013-01-01

By using the lowest order expansion in the number of spins, we study the classical correlation (CC) and quantum correlations (QCs) between two spin subgroups of the Lipkin–Meshkov–Glick (LMG) model in both binary and trinary decompositions of spins. In the case of bipartitions, we find that the CC and all the QCs are divergent in the same singular behavior at the critical point of the LMG model. In the case of tripartitions, however, the CC is still divergent but the QCs remain finite at the critical point. The present result shows that the CC is very robust but the QCs are much frangible to the environment disturbance.

Free-anchored Nb2O5@graphene networks for ultrafast-stable lithium storage

Science.gov (United States)

Deng, Qinglin; Li, Mengjiao; Wang, Junyong; Jiang, Kai; Hu, Zhigao; Chu, Junhao

2018-05-01

Orthorhombic Nb2O5 (T-Nb2O5) has structural merit but poor electrical conductivity, limiting their applications in energy storage. Although graphene is frequently adopted to effectively improve its electrochemical properties, the ordinary modified methods cannot meet the growing demands for high-performance. Here, we demonstrate that different graphene modified routes play a vital role in affecting the electrochemical performances of T-Nb2O5. By only manual shaking within one minute, Nb2O5 nano-particles can be rapidly adsorbed onto graphene, then the free-anchored T-Nb2O5@graphene three-dimensional networks can be successfully prepared based on hydrogel method. As for the application in lithium-ion batteries, it performs outstanding rate character (129 mA h g-1 (25C rate), 110 mA h g-1 (50C rate) and 90 mA h g-1 (100C rate), correspond to 79%, 67% and 55% capacity of 0.5C rate, respectively) and excellent long-term cycling feature (˜70% capacity retention after 20000 cycles). Moreover, it still maintains similar ultrafast-stable lithium storage performances when Cu foil is substituted by Al foil as current collector. In addition, relevant kinetics mechanisms are also expounded. This work provides a versatile strategy for the preparation of graphene modified Nb2O5 or other types of nanoparticles.

Community Core Evolution in Mobile Social Networks

Directory of Open Access Journals (Sweden)

Hao Xu

2013-01-01

Full Text Available Community detection in social networks attracts a lot of attention in the recent years. Existing methods always depict the relationship of two nodes using the temporary connection. However, these temporary connections cannot be fully recognized as the real relationships when the history connections among nodes are considered. For example, a casual visit in Facebook cannot be seen as an establishment of friendship. Hence, our question is the following: how to cluster the real friends in mobile social networks? In this paper, we study the problem of detecting the stable community core in mobile social networks. The cumulative stable contact is proposed to depict the relationship among nodes. The whole process is divided into timestamps. Nodes and their connections can be added or removed at each timestamp, and historical contacts are considered when detecting the community core. Also, community cores can be tracked through the incremental computing, which can help to recognize the evolving of community structure. Empirical studies on real-world social networks demonstrate that our proposed method can effectively detect stable community cores in mobile social networks.

Community core evolution in mobile social networks.

Science.gov (United States)

Xu, Hao; Xiao, Weidong; Tang, Daquan; Tang, Jiuyang; Wang, Zhenwen

2013-01-01

Community detection in social networks attracts a lot of attention in the recent years. Existing methods always depict the relationship of two nodes using the temporary connection. However, these temporary connections cannot be fully recognized as the real relationships when the history connections among nodes are considered. For example, a casual visit in Facebook cannot be seen as an establishment of friendship. Hence, our question is the following: how to cluster the real friends in mobile social networks? In this paper, we study the problem of detecting the stable community core in mobile social networks. The cumulative stable contact is proposed to depict the relationship among nodes. The whole process is divided into timestamps. Nodes and their connections can be added or removed at each timestamp, and historical contacts are considered when detecting the community core. Also, community cores can be tracked through the incremental computing, which can help to recognize the evolving of community structure. Empirical studies on real-world social networks demonstrate that our proposed method can effectively detect stable community cores in mobile social networks.

Popularity and Novelty Dynamics in Evolving Networks.

Science.gov (United States)

Abbas, Khushnood; Shang, Mingsheng; Abbasi, Alireza; Luo, Xin; Xu, Jian Jun; Zhang, Yu-Xia

2018-04-20

Network science plays a big role in the representation of real-world phenomena such as user-item bipartite networks presented in e-commerce or social media platforms. It provides researchers with tools and techniques to solve complex real-world problems. Identifying and predicting future popularity and importance of items in e-commerce or social media platform is a challenging task. Some items gain popularity repeatedly over time while some become popular and novel only once. This work aims to identify the key-factors: popularity and novelty. To do so, we consider two types of novelty predictions: items appearing in the popular ranking list for the first time; and items which were not in the popular list in the past time window, but might have been popular before the recent past time window. In order to identify the popular items, a careful consideration of macro-level analysis is needed. In this work we propose a model, which exploits item level information over a span of time to rank the importance of the item. We considered ageing or decay effect along with the recent link-gain of the items. We test our proposed model on four various real-world datasets using four information retrieval based metrics.

Embedded Ag quantum dots into interconnected Co3O4 nanosheets grown on 3D graphene networks for high stable and flexible supercapacitors

International Nuclear Information System (INIS)

Wang, Junya; Dou, Wei; Zhang, Xuetao; Han, Weihua; Mu, Xuemei; Zhang, Yue; Zhao, Xiaohua; Chen, Youxin; Yang, Zhiwei; Su, Qing; Xie, Erqing; Lan, Wei; Wang, Xinran

2017-01-01

High stable, flexible and interconnected Co 3 O 4 nanosheets with embedded Ag quantum dots (AgQDs) were uniformly grown on three dimensional graphene (3DG) networks and served as supercapacitor electrode to enhance the pseudocapacitance performance. The AgQDs were used to facilitate the growth of the Co 3 O 4 nanosheets and improve the electrical conductivity of the hybrid electrode by forming a good ohmic contact and provide direct and stable pathways for rapid electron transport. The AgQDs contribute to produce an improved areal capacitance of 421 mF cm −2 (1052.5 F g −1 ) and 53.3 mF cm −2 for the Ag/Co 3 O 4 /3DG hybrid, for both the three- and the two-electrode configuration, respectively. These values are about three times higher compared to a pristine Co 3 O 4 /3DG electrode. The capacitance retention of ∼120% after 10 4 cycles shows that a Ag/Co 3 O 4 /3DG hybrid can provide a long and stable cycle performance with a high specific capacitance. This study provides an effective strategy to improve the performance of electrode materials for supercapacitors with a high efficiency and long life, which makes them promising candidates for future energy-storage applications.

The Role of Middlemen inEfficient and Strongly Pairwise Stable Networks

NARCIS (Netherlands)

Gilles, R.P.; Chakrabarti, S.; Sarangi, S.; Badasyan, N.

2004-01-01

We examine the strong pairwise stability concept in network formation theory under collective network benefits.Strong pairwise stability considers a pair of players to add a link through mutual consent while permitting them to unilaterally delete any subset of links under their control.We examine

Robust and Stable Disturbance Observer of Servo System for Low Speed Operation Using the Radial Basis Function Network

DEFF Research Database (Denmark)

Lee, Kyo-Beum; Blaabjerg, Frede

2005-01-01

A new scheme to estimate the moment of inertia in the servo motor drive system in very low speed is proposed in this paper. The speed estimation scheme in most servo drive systems for low speed operation is sensitive to the variation of machine parameter, especially the moment of inertia....... To estimate the motor inertia value, the observer using the Radial Basis Function Network (RBFN) is applied. A control law for stabilizing the system and adaptive laws for updating both of the weights in the RBFN and a bounding constant are established so that the whole closed-loop system is stable...... in the sense of Lyapunov. The effectiveness of the proposed inertia estimation is verified by simulations and experiments. It is concluded that the speed control performance in low speed region is improved with the proposed disturbance observer using RBFN....

Reaction factoring and bipartite update graphs accelerate the Gillespie Algorithm for large-scale biochemical systems.

Directory of Open Access Journals (Sweden)

Sagar Indurkhya

Full Text Available ODE simulations of chemical systems perform poorly when some of the species have extremely low concentrations. Stochastic simulation methods, which can handle this case, have been impractical for large systems due to computational complexity. We observe, however, that when modeling complex biological systems: (1 a small number of reactions tend to occur a disproportionately large percentage of the time, and (2 a small number of species tend to participate in a disproportionately large percentage of reactions. We exploit these properties in LOLCAT Method, a new implementation of the Gillespie Algorithm. First, factoring reaction propensities allows many propensities dependent on a single species to be updated in a single operation. Second, representing dependencies between reactions with a bipartite graph of reactions and species requires only storage for reactions, rather than the required for a graph that includes only reactions. Together, these improvements allow our implementation of LOLCAT Method to execute orders of magnitude faster than currently existing Gillespie Algorithm variants when simulating several yeast MAPK cascade models.

Reaction Factoring and Bipartite Update Graphs Accelerate the Gillespie Algorithm for Large-Scale Biochemical Systems

Science.gov (United States)

Indurkhya, Sagar; Beal, Jacob

2010-01-01

ODE simulations of chemical systems perform poorly when some of the species have extremely low concentrations. Stochastic simulation methods, which can handle this case, have been impractical for large systems due to computational complexity. We observe, however, that when modeling complex biological systems: (1) a small number of reactions tend to occur a disproportionately large percentage of the time, and (2) a small number of species tend to participate in a disproportionately large percentage of reactions. We exploit these properties in LOLCAT Method, a new implementation of the Gillespie Algorithm. First, factoring reaction propensities allows many propensities dependent on a single species to be updated in a single operation. Second, representing dependencies between reactions with a bipartite graph of reactions and species requires only storage for reactions, rather than the required for a graph that includes only reactions. Together, these improvements allow our implementation of LOLCAT Method to execute orders of magnitude faster than currently existing Gillespie Algorithm variants when simulating several yeast MAPK cascade models. PMID:20066048

Simple sequence repeats and compositional bias in the bipartite Ralstonia solanacearum GMI1000 genome

Directory of Open Access Journals (Sweden)

Vandamme Peter

2003-03-01

Full Text Available Abstract Background Ralstonia solanacearum is an important plant pathogen. The genome of R. solananearum GMI1000 is organised into two replicons (a 3.7-Mb chromosome and a 2.1-Mb megaplasmid and this bipartite genome structure is characteristic for most R. solanacearum strains. To determine whether the megaplasmid was acquired via recent horizontal gene transfer or is part of an ancestral single chromosome, we compared the abundance, distribution and compositon of simple sequence repeats (SSRs between both replicons and also compared the respective compositional biases. Results Our data show that both replicons are very similar in respect to distribution and composition of SSRs and presence of compositional biases. Minor variations in SSR and compositional biases observed may be attributable to minor differences in gene expression and regulation of gene expression or can be attributed to the small sample numbers observed. Conclusions The observed similarities indicate that both replicons have shared a similar evolutionary history and thus suggest that the megaplasmid was not recently acquired from other organisms by lateral gene transfer but is a part of an ancestral R. solanacearum chromosome.

State preparation for quantum information science and metrology

International Nuclear Information System (INIS)

Samblowski, Aiko

2012-01-01

The precise preparation of non-classical states of light is a basic requirement for performing quantum information tasks and quantum metrology. Depending on the assignment, the range of required states varies from preparing and modifying squeezed states to generating bipartite entanglement and establishing multimode entanglement networks. Every state needs special preparation techniques and hence it is important to develop the experimental expertise to generate all states with the desired degree of accuracy. In this thesis, the experimental preparation of different kinds of non-classical states of light is demonstrated. Starting with a multimode entangled state, the preparation of an unconditionally generated bound entangled state of light of unprecedented accuracy is shown. Its existence is of fundamental interest, since it certifies an intrinsic irreversibility of entanglement and suggests a connection with thermodynamics. The state is created in a network of linear optics, utilizing optical parametric amplifiers, operated below threshold, beam splitters and phase gates. The experimental platform developed here afforded the precise and stable control of all experimental parameters. Focusing on the aspect of quantum information networks, the generation of suitable bipartite entangled states of light is desirable. The optical connection between atomic transitions and light that can be transmitted via telecommunications fibers opens the possibility to employ quantum memories within fiber networks. For this purpose, a non-degenerate optical parametric oscillator is operated above threshold and the generation of bright bipartite entanglement between its twin beams at the wavelengths of 810 nm and 1550 nm is demonstrated. In the field of metrology, quantum states are used to enhance the measurement precision of interferometric gravitational wave (GW) detectors. Recently, the sensitivity of a GW detector operated at a wavelength of 1064 nm was increased using squeezed

State preparation for quantum information science and metrology

Energy Technology Data Exchange (ETDEWEB)

Samblowski, Aiko

2012-06-08

The precise preparation of non-classical states of light is a basic requirement for performing quantum information tasks and quantum metrology. Depending on the assignment, the range of required states varies from preparing and modifying squeezed states to generating bipartite entanglement and establishing multimode entanglement networks. Every state needs special preparation techniques and hence it is important to develop the experimental expertise to generate all states with the desired degree of accuracy. In this thesis, the experimental preparation of different kinds of non-classical states of light is demonstrated. Starting with a multimode entangled state, the preparation of an unconditionally generated bound entangled state of light of unprecedented accuracy is shown. Its existence is of fundamental interest, since it certifies an intrinsic irreversibility of entanglement and suggests a connection with thermodynamics. The state is created in a network of linear optics, utilizing optical parametric amplifiers, operated below threshold, beam splitters and phase gates. The experimental platform developed here afforded the precise and stable control of all experimental parameters. Focusing on the aspect of quantum information networks, the generation of suitable bipartite entangled states of light is desirable. The optical connection between atomic transitions and light that can be transmitted via telecommunications fibers opens the possibility to employ quantum memories within fiber networks. For this purpose, a non-degenerate optical parametric oscillator is operated above threshold and the generation of bright bipartite entanglement between its twin beams at the wavelengths of 810 nm and 1550 nm is demonstrated. In the field of metrology, quantum states are used to enhance the measurement precision of interferometric gravitational wave (GW) detectors. Recently, the sensitivity of a GW detector operated at a wavelength of 1064 nm was increased using squeezed

A construção da memória organizacional utilizando o gerenciamento de processo nas pactuações da comissão intergestores bipartite do Sistema Único de SaúdeThe construction of the organizacional memory using the management of process in the agreements in the intermanagers' bipartite Commission in the SUS

Directory of Open Access Journals (Sweden)

Lourdes de Costa Remor

2009-01-01

Full Text Available O artigo aborda o gerenciamento de processo e a sua implicação na construção da memória organizacional. Apresenta a relevância do conhecimento em uma organização e os danos causados quando eles não são incorporados à memória da organização. O gerenciamento de processo por organizar e sistematizar os trabalhos parece permitir a disseminação do conhecimento dentro da organização, tanto para os indivíduos quanto para os repositórios. E por fim, apresenta o processo da pactuação na Comissão Intergestores Bipartite, Fórum de negociação e tomada de decisão entre os Gestores: Municipais e Estadual do SUS.The article approaches the management process and the implication in the construction of the organization’s memory. It presents the relevance of the knowledge in an organization and the mischief caused when they are not incorporated to the memory of the organization. The management of the process by organizing and systematizing the works, and for that, it permits the dissemination of the knowledge inside the organization, so much for the individuals or for the repositories. And finally, it presents the process of the agreement in the Intergestores Bipartite Commission, Forum of negotiation and decision-making between the State and Municipal Agents of the SUS.

A Stable-Matching-Based User Linking Method with User Preference Order

Directory of Open Access Journals (Sweden)

Xuzhong Wang

2017-01-01

Full Text Available With the development of social networks, more and more users choose to use multiple accounts from different networks to meet their needs. Linking a particular user’s multiple accounts not only can improve user’s experience of the net-services such as recommender system, but also plays a significant role in network security. However, multiple accounts of the same user are often not directly linked to each other, and further, the privacy policy provided by the service provider makes it harder to find accounts for a particular user. In this paper, we propose a stable-matching-based method with user preference order for the problem of low accuracy of user linking in cross-media sparse data. Different from the traditional way which just calculates the similarity of accounts, we take full account of the mutual influence among multiple accounts by regarding different networks as bilateral (multilateral market and user linking as a stable matching problem in such a market. Based on the combination of Game-Theoretic Machine Learning and Pairwise, a novel user linking method has been proposed. The experiment shows that our method has a 21.6% improvement in accuracy compared with the traditional linking method and a further increase of about 7.8% after adding the prior knowledge.

Revascularisation versus medical treatment in patients with stable coronary artery disease

DEFF Research Database (Denmark)

Windecker, Stephan; Stortecky, Stefan; Stefanini, Giulio G

2014-01-01

OBJECTIVE: To investigate whether revascularisation improves prognosis compared with medical treatment among patients with stable coronary artery disease. DESIGN: Bayesian network meta-analyses to combine direct within trial comparisons between treatments with indirect evidence from other trials ...

Software-defined network abstractions and configuration interfaces for building programmable quantum networks

Energy Technology Data Exchange (ETDEWEB)

Dasari, Venkat [U.S. Army Research Laboratory, Aberdeen Proving Ground, MD; Sadlier, Ronald J [ORNL; Geerhart, Mr. Billy [U.S. Army Research Laboratory, Aberdeen Proving Ground, MD; Snow, Nikolai [U.S. Army Research Laboratory, Aberdeen Proving Ground, MD; Williams, Brian P [ORNL; Humble, Travis S [ORNL

2017-01-01

Well-defined and stable quantum networks are essential to realize functional quantum applications. Quantum networks are complex and must use both quantum and classical channels to support quantum applications like QKD, teleportation, and superdense coding. In particular, the no-cloning theorem prevents the reliable copying of quantum signals such that the quantum and classical channels must be highly coordinated using robust and extensible methods. We develop new network abstractions and interfaces for building programmable quantum networks. Our approach leverages new OpenFlow data structures and table type patterns to build programmable quantum networks and to support quantum applications.

Revascularisation versus medical treatment in patients with stable coronary artery disease: network meta-analysis

Science.gov (United States)

Stortecky, Stefan; Stefanini, Giulio G; daCosta, Bruno R; Rutjes, Anne Wilhelmina; Di Nisio, Marcello; Siletta, Maria G; Maione, Ausilia; Alfonso, Fernando; Clemmensen, Peter M; Collet, Jean-Philippe; Cremer, Jochen; Falk, Volkmar; Filippatos, Gerasimos; Hamm, Christian; Head, Stuart; Kappetein, Arie Pieter; Kastrati, Adnan; Knuuti, Juhani; Landmesser, Ulf; Laufer, Günther; Neumann, Franz-Joseph; Richter, Dimitri; Schauerte, Patrick; Sousa Uva, Miguel; Taggart, David P; Torracca, Lucia; Valgimigli, Marco; Wijns, William; Witkowski, Adam; Kolh, Philippe; Juni, Peter

2014-01-01

Objective To investigate whether revascularisation improves prognosis compared with medical treatment among patients with stable coronary artery disease. Design Bayesian network meta-analyses to combine direct within trial comparisons between treatments with indirect evidence from other trials while maintaining randomisation. Eligibility criteria for selecting studies A strategy of initial medical treatment compared with revascularisation by coronary artery bypass grafting or Food and Drug Administration approved techniques for percutaneous revascularization: balloon angioplasty, bare metal stent, early generation paclitaxel eluting stent, sirolimus eluting stent, and zotarolimus eluting (Endeavor) stent, and new generation everolimus eluting stent, and zotarolimus eluting (Resolute) stent among patients with stable coronary artery disease. Data sources Medline and Embase from 1980 to 2013 for randomised trials comparing medical treatment with revascularisation. Main outcome measure All cause mortality. Results 100 trials in 93 553 patients with 262 090 patient years of follow-up were included. Coronary artery bypass grafting was associated with a survival benefit (rate ratio 0.80, 95% credibility interval 0.70 to 0.91) compared with medical treatment. New generation drug eluting stents (everolimus: 0.75, 0.59 to 0.96; zotarolimus (Resolute): 0.65, 0.42 to 1.00) but not balloon angioplasty (0.85, 0.68 to 1.04), bare metal stents (0.92, 0.79 to 1.05), or early generation drug eluting stents (paclitaxel: 0.92, 0.75 to 1.12; sirolimus: 0.91, 0.75 to 1.10; zotarolimus (Endeavor): 0.88, 0.69 to 1.10) were associated with improved survival compared with medical treatment. Coronary artery bypass grafting reduced the risk of myocardial infarction compared with medical treatment (0.79, 0.63 to 0.99), and everolimus eluting stents showed a trend towards a reduced risk of myocardial infarction (0.75, 0.55 to 1.01). The risk of subsequent revascularisation was noticeably

A generalized model via random walks for information filtering

Science.gov (United States)

Ren, Zhuo-Ming; Kong, Yixiu; Shang, Ming-Sheng; Zhang, Yi-Cheng

2016-08-01

There could exist a simple general mechanism lurking beneath collaborative filtering and interdisciplinary physics approaches which have been successfully applied to online E-commerce platforms. Motivated by this idea, we propose a generalized model employing the dynamics of the random walk in the bipartite networks. Taking into account the degree information, the proposed generalized model could deduce the collaborative filtering, interdisciplinary physics approaches and even the enormous expansion of them. Furthermore, we analyze the generalized model with single and hybrid of degree information on the process of random walk in bipartite networks, and propose a possible strategy by using the hybrid degree information for different popular objects to toward promising precision of the recommendation.

Globally Stable Adaptive Backstepping Neural Network Control for Uncertain Strict-Feedback Systems With Tracking Accuracy Known a Priori.

Science.gov (United States)

Chen, Weisheng; Ge, Shuzhi Sam; Wu, Jian; Gong, Maoguo

2015-09-01

This paper addresses the problem of globally stable direct adaptive backstepping neural network (NN) tracking control design for a class of uncertain strict-feedback systems under the assumption that the accuracy of the ultimate tracking error is given a priori. In contrast to the classical adaptive backstepping NN control schemes, this paper analyzes the convergence of the tracking error using Barbalat's Lemma via some nonnegative functions rather than the positive-definite Lyapunov functions. Thus, the accuracy of the ultimate tracking error can be determined and adjusted accurately a priori, and the closed-loop system is guaranteed to be globally uniformly ultimately bounded. The main technical novelty is to construct three new n th-order continuously differentiable functions, which are used to design the control law, the virtual control variables, and the adaptive laws. Finally, two simulation examples are given to illustrate the effectiveness and advantages of the proposed control method.

Modelling the structure of a ceRNA-theoretical, bipartite microRNA-mRNA interaction network regulating intestinal epithelial cellular pathways using R programming.

Science.gov (United States)

Robinson, J M; Henderson, W A

2018-01-12

We report a method using functional-molecular databases and network modelling to identify hypothetical mRNA-miRNA interaction networks regulating intestinal epithelial barrier function. The model forms a data-analysis component of our cell culture experiments, which produce RNA expression data from Nanostring Technologies nCounter ® system. The epithelial tight-junction (TJ) and actin cytoskeleton interact as molecular components of the intestinal epithelial barrier. Upstream regulation of TJ-cytoskeleton interaction is effected by the Rac/Rock/Rho signaling pathway and other associated pathways which may be activated or suppressed by extracellular signaling from growth factors, hormones, and immune receptors. Pathway activations affect epithelial homeostasis, contributing to degradation of the epithelial barrier associated with osmotic dysregulation, inflammation, and tumor development. The complexity underlying miRNA-mRNA interaction networks represents a roadblock for prediction and validation of competing-endogenous RNA network function. We developed a network model to identify hypothetical co-regulatory motifs in a miRNA-mRNA interaction network related to epithelial function. A mRNA-miRNA interaction list was generated using KEGG and miRWalk2.0 databases. R-code was developed to quantify and visualize inherent network structures. We identified a sub-network with a high number of shared, targeting miRNAs, of genes associated with cellular proliferation and cancer, including c-MYC and Cyclin D.

Transcriptional delay stabilizes bistable gene networks.

Science.gov (United States)

Gupta, Chinmaya; López, José Manuel; Ott, William; Josić, Krešimir; Bennett, Matthew R

2013-08-02

Transcriptional delay can significantly impact the dynamics of gene networks. Here we examine how such delay affects bistable systems. We investigate several stochastic models of bistable gene networks and find that increasing delay dramatically increases the mean residence times near stable states. To explain this, we introduce a non-Markovian, analytically tractable reduced model. The model shows that stabilization is the consequence of an increased number of failed transitions between stable states. Each of the bistable systems that we simulate behaves in this manner.

OTDM Networking for Short Range High-Capacity Highly Dynamic Networks

DEFF Research Database (Denmark)

Medhin, Ashenafi Kiros

This PhD thesis aims at investigating the possibility of designing energy-efficient high-capacity (up to Tbit/s) optical network scenarios, leveraging on the effect of collective switching of many bits simultaneously, as is inherent in high bit rate serial optical data signals. The focus...... is on short range highly dynamic networks, catering to data center needs. The investigation concerns optical network scenarios, and experimental implementations of high bit rate serial data packet generation and reception, scalable optical packet labeling, simple optical label extraction and stable ultra...

Chaotification of complex networks with impulsive control.

Science.gov (United States)

Guan, Zhi-Hong; Liu, Feng; Li, Juan; Wang, Yan-Wu

2012-06-01

This paper investigates the chaotification problem of complex dynamical networks (CDN) with impulsive control. Both the discrete and continuous cases are studied. The method is presented to drive all states of every node in CDN to chaos. The proposed impulsive control strategy is effective for both the originally stable and unstable CDN. The upper bound of the impulse intervals for originally stable networks is derived. Finally, the effectiveness of the theoretical results is verified by numerical examples.

Computing Maximum Cardinality Matchings in Parallel on Bipartite Graphs via Tree-Grafting

International Nuclear Information System (INIS)

Azad, Ariful; Buluc, Aydn; Pothen, Alex

2016-01-01

It is difficult to obtain high performance when computing matchings on parallel processors because matching algorithms explicitly or implicitly search for paths in the graph, and when these paths become long, there is little concurrency. In spite of this limitation, we present a new algorithm and its shared-memory parallelization that achieves good performance and scalability in computing maximum cardinality matchings in bipartite graphs. This algorithm searches for augmenting paths via specialized breadth-first searches (BFS) from multiple source vertices, hence creating more parallelism than single source algorithms. Algorithms that employ multiple-source searches cannot discard a search tree once no augmenting path is discovered from the tree, unlike algorithms that rely on single-source searches. We describe a novel tree-grafting method that eliminates most of the redundant edge traversals resulting from this property of multiple-source searches. We also employ the recent direction-optimizing BFS algorithm as a subroutine to discover augmenting paths faster. Our algorithm compares favorably with the current best algorithms in terms of the number of edges traversed, the average augmenting path length, and the number of iterations. Here, we provide a proof of correctness for our algorithm. Our NUMA-aware implementation is scalable to 80 threads of an Intel multiprocessor and to 240 threads on an Intel Knights Corner coprocessor. On average, our parallel algorithm runs an order of magnitude faster than the fastest algorithms available. The performance improvement is more significant on graphs with small matching number.

What's Next in Complex Networks? Capturing the Concept of Attacking Play in Invasive Team Sports.

Science.gov (United States)

Ramos, João; Lopes, Rui J; Araújo, Duarte

2018-01-01

The evolution of performance analysis within sports sciences is tied to technology development and practitioner demands. However, how individual and collective patterns self-organize and interact in invasive team sports remains elusive. Social network analysis has been recently proposed to resolve some aspects of this problem, and has proven successful in capturing collective features resulting from the interactions between team members as well as a powerful communication tool. Despite these advances, some fundamental team sports concepts such as an attacking play have not been properly captured by the more common applications of social network analysis to team sports performance. In this article, we propose a novel approach to team sports performance centered on sport concepts, namely that of an attacking play. Network theory and tools including temporal and bipartite or multilayered networks were used to capture this concept. We put forward eight questions directly related to team performance to discuss how common pitfalls in the use of network tools for capturing sports concepts can be avoided. Some answers are advanced in an attempt to be more precise in the description of team dynamics and to uncover other metrics directly applied to sport concepts, such as the structure and dynamics of attacking plays. Finally, we propose that, at this stage of knowledge, it may be advantageous to build up from fundamental sport concepts toward complex network theory and tools, and not the other way around.

Topological and functional properties of the small GTPases protein interaction network.

Directory of Open Access Journals (Sweden)

Anna Delprato

Full Text Available Small GTP binding proteins of the Ras superfamily (Ras, Rho, Rab, Arf, and Ran regulate key cellular processes such as signal transduction, cell proliferation, cell motility, and vesicle transport. A great deal of experimental evidence supports the existence of signaling cascades and feedback loops within and among the small GTPase subfamilies suggesting that these proteins function in a coordinated and cooperative manner. The interplay occurs largely through association with bi-partite regulatory and effector proteins but can also occur through the active form of the small GTPases themselves. In order to understand the connectivity of the small GTPases signaling routes, a systems-level approach that analyzes data describing direct and indirect interactions was used to construct the small GTPases protein interaction network. The data were curated from the Search Tool for the Retrieval of Interacting Genes (STRING database and include only experimentally validated interactions. The network method enables the conceptualization of the overall structure as well as the underlying organization of the protein-protein interactions. The interaction network described here is comprised of 778 nodes and 1943 edges and has a scale-free topology. Rac1, Cdc42, RhoA, and HRas are identified as the hubs. Ten sub-network motifs are also identified in this study with themes in apoptosis, cell growth/proliferation, vesicle traffic, cell adhesion/junction dynamics, the nicotinamide adenine dinucleotide phosphate (NADPH oxidase response, transcription regulation, receptor-mediated endocytosis, gene silencing, and growth factor signaling. Bottleneck proteins that bridge signaling paths and proteins that overlap in multiple small GTPase networks are described along with the functional annotation of all proteins in the network.

Statistically validated network of portfolio overlaps and systemic risk.

Science.gov (United States)

Gualdi, Stanislao; Cimini, Giulio; Primicerio, Kevin; Di Clemente, Riccardo; Challet, Damien

2016-12-21

Common asset holding by financial institutions (portfolio overlap) is nowadays regarded as an important channel for financial contagion with the potential to trigger fire sales and severe losses at the systemic level. We propose a method to assess the statistical significance of the overlap between heterogeneously diversified portfolios, which we use to build a validated network of financial institutions where links indicate potential contagion channels. The method is implemented on a historical database of institutional holdings ranging from 1999 to the end of 2013, but can be applied to any bipartite network. We find that the proportion of validated links (i.e. of significant overlaps) increased steadily before the 2007-2008 financial crisis and reached a maximum when the crisis occurred. We argue that the nature of this measure implies that systemic risk from fire sales liquidation was maximal at that time. After a sharp drop in 2008, systemic risk resumed its growth in 2009, with a notable acceleration in 2013. We finally show that market trends tend to be amplified in the portfolios identified by the algorithm, such that it is possible to have an informative signal about institutions that are about to suffer (enjoy) the most significant losses (gains).

Structure of multiphoton quantum optics. II. Bipartite systems, physical processes, and heterodyne squeezed states

Science.gov (United States)

dell'Anno, Fabio; de Siena, Silvio; Illuminati, Fabrizio

2004-03-01

Extending the scheme developed for a single mode of the electromagnetic field in the preceding paper [F. Dell’Anno, S. De Siena, and F. Illuminati, Phys. Rev. A 69, 033812 (2004)], we introduce two-mode nonlinear canonical transformations depending on two heterodyne mixing angles. They are defined in terms of Hermitian nonlinear functions that realize heterodyne superpositions of conjugate quadratures of bipartite systems. The canonical transformations diagonalize a class of Hamiltonians describing nondegenerate and degenerate multiphoton processes. We determine the coherent states associated with the canonical transformations, which generalize the nondegenerate two-photon squeezed states. Such heterodyne multiphoton squeezed states are defined as the simultaneous eigenstates of the transformed, coupled annihilation operators. They are generated by nonlinear unitary evolutions acting on two-mode squeezed states. They are non-Gaussian, highly nonclassical, entangled states. For a quadratic nonlinearity the heterodyne multiphoton squeezed states define two-mode cubic phase states. The statistical properties of these states can be widely adjusted by tuning the heterodyne mixing angles, the phases of the nonlinear couplings, as well as the strength of the nonlinearity. For quadratic nonlinearity, we study the higher-order contributions to the susceptibility in nonlinear media and we suggest possible experimental realizations of multiphoton conversion processes generating the cubic-phase heterodyne squeezed states.

Structure of multiphoton quantum optics. II. Bipartite systems, physical processes, and heterodyne squeezed states

International Nuclear Information System (INIS)

Dell'Anno, Fabio; De Siena, Silvio; Illuminati, Fabrizio

2004-01-01

Extending the scheme developed for a single mode of the electromagnetic field in the preceding paper [F. Dell'Anno, S. De Siena, and F. Illuminati, Phys. Rev. A 69, 033812 (2004)], we introduce two-mode nonlinear canonical transformations depending on two heterodyne mixing angles. They are defined in terms of Hermitian nonlinear functions that realize heterodyne superpositions of conjugate quadratures of bipartite systems. The canonical transformations diagonalize a class of Hamiltonians describing nondegenerate and degenerate multiphoton processes. We determine the coherent states associated with the canonical transformations, which generalize the nondegenerate two-photon squeezed states. Such heterodyne multiphoton squeezed states are defined as the simultaneous eigenstates of the transformed, coupled annihilation operators. They are generated by nonlinear unitary evolutions acting on two-mode squeezed states. They are non-Gaussian, highly nonclassical, entangled states. For a quadratic nonlinearity the heterodyne multiphoton squeezed states define two-mode cubic phase states. The statistical properties of these states can be widely adjusted by tuning the heterodyne mixing angles, the phases of the nonlinear couplings, as well as the strength of the nonlinearity. For quadratic nonlinearity, we study the higher-order contributions to the susceptibility in nonlinear media and we suggest possible experimental realizations of multiphoton conversion processes generating the cubic-phase heterodyne squeezed states

Innovation networking between stability and political dynamics

DEFF Research Database (Denmark)

Koch, Christian

2004-01-01

of the contribution is to challenge and transcend these notions and develop an understanding of innovation networks as an interplay between stable and dynamic elements, where political processes in innovation are much more than a disruptive and even a counterproductive feature. It reviews the growing number...... of studies that highlight the political aspect of innovation. The paper reports on a study of innovation processes conducted within the EU—TSER-programme and a study made under the banner of management of technology. Intensive field studies in two constellations of enterprises were carried out. One......This contribution views innovation as a social activity of building networks, using software product development in multicompany alliances and networks as example. Innovation networks are frequently understood as quite stable arrangements characterised by high trust among the participants. The aim...

Stable convergence and stable limit theorems

CERN Document Server

Häusler, Erich

2015-01-01

The authors present a concise but complete exposition of the mathematical theory of stable convergence and give various applications in different areas of probability theory and mathematical statistics to illustrate the usefulness of this concept. Stable convergence holds in many limit theorems of probability theory and statistics – such as the classical central limit theorem – which are usually formulated in terms of convergence in distribution. Originated by Alfred Rényi, the notion of stable convergence is stronger than the classical weak convergence of probability measures. A variety of methods is described which can be used to establish this stronger stable convergence in many limit theorems which were originally formulated only in terms of weak convergence. Naturally, these stronger limit theorems have new and stronger consequences which should not be missed by neglecting the notion of stable convergence. The presentation will be accessible to researchers and advanced students at the master's level...

Updates on drug-target network; facilitating polypharmacology and data integration by growth of DrugBank database.

Science.gov (United States)

Barneh, Farnaz; Jafari, Mohieddin; Mirzaie, Mehdi

2016-11-01

Network pharmacology elucidates the relationship between drugs and targets. As the identified targets for each drug increases, the corresponding drug-target network (DTN) evolves from solely reflection of the pharmaceutical industry trend to a portrait of polypharmacology. The aim of this study was to evaluate the potentials of DrugBank database in advancing systems pharmacology. We constructed and analyzed DTN from drugs and targets associations in the DrugBank 4.0 database. Our results showed that in bipartite DTN, increased ratio of identified targets for drugs augmented density and connectivity of drugs and targets and decreased modular structure. To clear up the details in the network structure, the DTNs were projected into two networks namely, drug similarity network (DSN) and target similarity network (TSN). In DSN, various classes of Food and Drug Administration-approved drugs with distinct therapeutic categories were linked together based on shared targets. Projected TSN also showed complexity because of promiscuity of the drugs. By including investigational drugs that are currently being tested in clinical trials, the networks manifested more connectivity and pictured the upcoming pharmacological space in the future years. Diverse biological processes and protein-protein interactions were manipulated by new drugs, which can extend possible target combinations. We conclude that network-based organization of DrugBank 4.0 data not only reveals the potential for repurposing of existing drugs, also allows generating novel predictions about drugs off-targets, drug-drug interactions and their side effects. Our results also encourage further effort for high-throughput identification of targets to build networks that can be integrated into disease networks. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Stretched exponential dynamics of coupled logistic maps on a small-world network

Science.gov (United States)

Mahajan, Ashwini V.; Gade, Prashant M.

2018-02-01

We investigate the dynamic phase transition from partially or fully arrested state to spatiotemporal chaos in coupled logistic maps on a small-world network. Persistence of local variables in a coarse grained sense acts as an excellent order parameter to study this transition. We investigate the phase diagram by varying coupling strength and small-world rewiring probability p of nonlocal connections. The persistent region is a compact region bounded by two critical lines where band-merging crisis occurs. On one critical line, the persistent sites shows a nonexponential (stretched exponential) decay for all p while for another one, it shows crossover from nonexponential to exponential behavior as p → 1 . With an effectively antiferromagnetic coupling, coupling to two neighbors on either side leads to exchange frustration. Apart from exchange frustration, non-bipartite topology and nonlocal couplings in a small-world network could be a reason for anomalous relaxation. The distribution of trap times in asymptotic regime has a long tail as well. The dependence of temporal evolution of persistence on initial conditions is studied and a scaling form for persistence after waiting time is proposed. We present a simple possible model for this behavior.

Robustness Analysis of Hybrid Stochastic Neural Networks with Neutral Terms and Time-Varying Delays

Directory of Open Access Journals (Sweden)

Chunmei Wu

2015-01-01

Full Text Available We analyze the robustness of global exponential stability of hybrid stochastic neural networks subject to neutral terms and time-varying delays simultaneously. Given globally exponentially stable hybrid stochastic neural networks, we characterize the upper bounds of contraction coefficients of neutral terms and time-varying delays by using the transcendental equation. Moreover, we prove theoretically that, for any globally exponentially stable hybrid stochastic neural networks, if additive neutral terms and time-varying delays are smaller than the upper bounds arrived, then the perturbed neural networks are guaranteed to also be globally exponentially stable. Finally, a numerical simulation example is given to illustrate the presented criteria.

Convergent dynamics for multistable delayed neural networks

International Nuclear Information System (INIS)

Shih, Chih-Wen; Tseng, Jui-Pin

2008-01-01

This investigation aims at developing a methodology to establish convergence of dynamics for delayed neural network systems with multiple stable equilibria. The present approach is general and can be applied to several network models. We take the Hopfield-type neural networks with both instantaneous and delayed feedbacks to illustrate the idea. We shall construct the complete dynamical scenario which comprises exactly 2 n stable equilibria and exactly (3 n − 2 n ) unstable equilibria for the n-neuron network. In addition, it is shown that every solution of the system converges to one of the equilibria as time tends to infinity. The approach is based on employing the geometrical structure of the network system. Positively invariant sets and componentwise dynamical properties are derived under the geometrical configuration. An iteration scheme is subsequently designed to confirm the convergence of dynamics for the system. Two examples with numerical simulations are arranged to illustrate the present theory

Local Nash equilibrium in social networks.

Science.gov (United States)

Zhang, Yichao; Aziz-Alaoui, M A; Bertelle, Cyrille; Guan, Jihong

2014-08-29

Nash equilibrium is widely present in various social disputes. As of now, in structured static populations, such as social networks, regular, and random graphs, the discussions on Nash equilibrium are quite limited. In a relatively stable static gaming network, a rational individual has to comprehensively consider all his/her opponents' strategies before they adopt a unified strategy. In this scenario, a new strategy equilibrium emerges in the system. We define this equilibrium as a local Nash equilibrium. In this paper, we present an explicit definition of the local Nash equilibrium for the two-strategy games in structured populations. Based on the definition, we investigate the condition that a system reaches the evolutionary stable state when the individuals play the Prisoner's dilemma and snow-drift game. The local Nash equilibrium provides a way to judge whether a gaming structured population reaches the evolutionary stable state on one hand. On the other hand, it can be used to predict whether cooperators can survive in a system long before the system reaches its evolutionary stable state for the Prisoner's dilemma game. Our work therefore provides a theoretical framework for understanding the evolutionary stable state in the gaming populations with static structures.

Recent results for random networks of automata

International Nuclear Information System (INIS)

Flyvbjerg, H.

1987-05-01

After a very brief historical and contextual introduction to random networks of automata we review recent numerical and analytical results. Open questions and unsolved problems are pointed out and discussed. One such question is also answered: it is shown that the size of the stable core can be used as order parameter for a transition between phases of frozen and chaotic network behavior. A mean-field-like but exact selfconsistency equation for the size of the stable core is given. A new derivation of critical parameter values follows from it. (orig.)

A network analysis of countries' export flows: firm grounds for the building blocks of the economy.

Directory of Open Access Journals (Sweden)

Guido Caldarelli

Full Text Available In this paper we analyze the bipartite network of countries and products from UN data on country production. We define the country-country and product-product projected networks and introduce a novel method of filtering information based on elements' similarity. As a result we find that country clustering reveals unexpected socio-geographic links among the most competing countries. On the same footings the products clustering can be efficiently used for a bottom-up classification of produced goods. Furthermore we mathematically reformulate the "reflections method" introduced by Hidalgo and Hausmann as a fixpoint problem; such formulation highlights some conceptual weaknesses of the approach. To overcome such an issue, we introduce an alternative methodology (based on biased Markov chains that allows to rank countries in a conceptually consistent way. Our analysis uncovers a strong non-linear interaction between the diversification of a country and the ubiquity of its products, thus suggesting the possible need of moving towards more efficient and direct non-linear fixpoint algorithms to rank countries and products in the global market.

Social cognitive radio networks

CERN Document Server

Chen, Xu

2015-01-01

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

A blind matching algorithm for cognitive radio networks

KAUST Repository

Hamza, Doha R.

2016-08-15

We consider a cognitive radio network where secondary users (SUs) are allowed access time to the spectrum belonging to the primary users (PUs) provided that they relay primary messages. PUs and SUs negotiate over allocations of the secondary power that will be used to relay PU data. We formulate the problem as a generalized assignment market to find an epsilon pairwise stable matching. We propose a distributed blind matching algorithm (BLMA) to produce the pairwise-stable matching plus the associated power allocations. We stipulate a limited information exchange in the network so that agents only calculate their own utilities but no information is available about the utilities of any other users in the network. We establish convergence to epsilon pairwise stable matchings in finite time. Finally we show that our algorithm exhibits a limited degradation in PU utility when compared with the Pareto optimal results attained using perfect information assumptions. © 2016 IEEE.

Stable isotope-resolved metabolomics and applications for drug development

Science.gov (United States)

Fan, Teresa W-M.; Lorkiewicz, Pawel; Sellers, Katherine; Moseley, Hunter N.B.; Higashi, Richard M.; Lane, Andrew N.

2012-01-01

Advances in analytical methodologies, principally nuclear magnetic resonance spectroscopy (NMR) and mass spectrometry (MS), during the last decade have made large-scale analysis of the human metabolome a reality. This is leading to the reawakening of the importance of metabolism in human diseases, particularly cancer. The metabolome is the functional readout of the genome, functional genome, and proteome; it is also an integral partner in molecular regulations for homeostasis. The interrogation of the metabolome, or metabolomics, is now being applied to numerous diseases, largely by metabolite profiling for biomarker discovery, but also in pharmacology and therapeutics. Recent advances in stable isotope tracer-based metabolomic approaches enable unambiguous tracking of individual atoms through compartmentalized metabolic networks directly in human subjects, which promises to decipher the complexity of the human metabolome at an unprecedented pace. This knowledge will revolutionize our understanding of complex human diseases, clinical diagnostics, as well as individualized therapeutics and drug response. In this review, we focus on the use of stable isotope tracers with metabolomics technologies for understanding metabolic network dynamics in both model systems and in clinical applications. Atom-resolved isotope tracing via the two major analytical platforms, NMR and MS, has the power to determine novel metabolic reprogramming in diseases, discover new drug targets, and facilitates ADME studies. We also illustrate new metabolic tracer-based imaging technologies, which enable direct visualization of metabolic processes in vivo. We further outline current practices and future requirements for biochemoinformatics development, which is an integral part of translating stable isotope-resolved metabolomics into clinical reality. PMID:22212615

The network organisation of consumer complaints

Science.gov (United States)

Rocha, L. E. C.; Holme, P.

2010-07-01

Interaction between consumers and companies can create conflict. When a consensus is unreachable there are legal authorities to resolve the case. This letter is a study of data from the Brazilian Department of Justice from which we build a bipartite network of categories of complaints linked to the companies receiving those complaints. We find the complaint categories organised in an hierarchical way where companies only get complaints of lower degree if they already got complaints of higher degree. The fraction of resolved complaints for a company appears to be nearly independent of the equity of the company but is positively correlated with the total number of complaints received. We construct feature vectors based on the edge-weight —the weight of an edge represents the times complaints of a category have been filed against that company— and use these vectors to study the similarity between the categories of complaints. From this analysis, we obtain trees mapping the hierarchical organisation of the complaints. We also apply principal component analysis to the set of feature vectors concluding that a reduction of the dimensionality of these from 8827 to 27 gives an optimal hierarchical representation.

Neural network recognition of mammographic lesions

International Nuclear Information System (INIS)

Oldham, W.J.B.; Downes, P.T.; Hunter, V.

1987-01-01

A method for recognition of mammographic lesions through the use of neural networks is presented. Neural networks have exhibited the ability to learn the shape andinternal structure of patterns. Digitized mammograms containing circumscribed and stelate lesions were used to train a feedfoward synchronous neural network that self-organizes to stable attractor states. Encoding of data for submission to the network was accomplished by performing a fractal analysis of the digitized image. This results in scale invariant representation of the lesions. Results are discussed

Stable and pH-responsive core-shell nanoparticles based on HEC and PMAA networks via template copolymerization

Science.gov (United States)

Zhang, Y.; Jin, Q.; Chen, Y.; Zhao, J.

2011-10-01

Taking advantage of the specific hydrogen bonding interactions, stable and pH-responsive core-shell nanoparticles based on hydroxyethyl cellulose (HEC) and polymethacrylic acid (PMAA) networks, with a size ranging from 190 to 250 nm, can be efficiently prepared via facile one-step co-polymerization of methacrylic acid (MAA) and N, N'-methylenebisacrylamide (MBA) on HEC template in water. Using dynamic light scattering, electrophoretic light scattering, fluorescence spectrometry, thermo-gravimetric analysis, TEM, and AFM observations, the influence of crosslinker MBA as well as the reaction parameters were studied. The results show that after the introduction of crosslinker MBA, the nanoparticles became less compact; their size exhibited a smaller pH sensitivity, and their stability against pH value was improved greatly. Furthermore, the size, structure, and pH response of the nanoparticles can be adjusted via varying the reaction parameters: nanoparticles of smaller size, more compact structure, and higher swelling capacity were produced as pH value of the reaction medium increased or the HEC/MAA ratio decreased; while nanoparticles of smaller size, less compact structure and smaller swelling capacity were produced as the total feeding concentration increased.

Specific non-monotonous interactions increase persistence of ecological networks.

Science.gov (United States)

Yan, Chuan; Zhang, Zhibin

2014-03-22

The relationship between stability and biodiversity has long been debated in ecology due to opposing empirical observations and theoretical predictions. Species interaction strength is often assumed to be monotonically related to population density, but the effects on stability of ecological networks of non-monotonous interactions that change signs have not been investigated previously. We demonstrate that for four kinds of non-monotonous interactions, shifting signs to negative or neutral interactions at high population density increases persistence (a measure of stability) of ecological networks, while for the other two kinds of non-monotonous interactions shifting signs to positive interactions at high population density decreases persistence of networks. Our results reveal a novel mechanism of network stabilization caused by specific non-monotonous interaction types through either increasing stable equilibrium points or reducing unstable equilibrium points (or both). These specific non-monotonous interactions may be important in maintaining stable and complex ecological networks, as well as other networks such as genes, neurons, the internet and human societies.

Quantum Entanglement in Neural Network States

Directory of Open Access Journals (Sweden)

Dong-Ling Deng

2017-05-01

Full Text Available Machine learning, one of today’s most rapidly growing interdisciplinary fields, promises an unprecedented perspective for solving intricate quantum many-body problems. Understanding the physical aspects of the representative artificial neural-network states has recently become highly desirable in the applications of machine-learning techniques to quantum many-body physics. In this paper, we explore the data structures that encode the physical features in the network states by studying the quantum entanglement properties, with a focus on the restricted-Boltzmann-machine (RBM architecture. We prove that the entanglement entropy of all short-range RBM states satisfies an area law for arbitrary dimensions and bipartition geometry. For long-range RBM states, we show by using an exact construction that such states could exhibit volume-law entanglement, implying a notable capability of RBM in representing quantum states with massive entanglement. Strikingly, the neural-network representation for these states is remarkably efficient, in the sense that the number of nonzero parameters scales only linearly with the system size. We further examine the entanglement properties of generic RBM states by randomly sampling the weight parameters of the RBM. We find that their averaged entanglement entropy obeys volume-law scaling, and the meantime strongly deviates from the Page entropy of the completely random pure states. We show that their entanglement spectrum has no universal part associated with random matrix theory and bears a Poisson-type level statistics. Using reinforcement learning, we demonstrate that RBM is capable of finding the ground state (with power-law entanglement of a model Hamiltonian with a long-range interaction. In addition, we show, through a concrete example of the one-dimensional symmetry-protected topological cluster states, that the RBM representation may also be used as a tool to analytically compute the entanglement spectrum. Our

Bipartite life cycle of coral reef fishes promotes increasing shape disparity of the head skeleton during ontogeny: an example from damselfishes (Pomacentridae

Directory of Open Access Journals (Sweden)

Vandewalle Pierre

2011-03-01

Full Text Available Abstract Background Quantitative studies of the variation of disparity during ontogeny exhibited by the radiation of coral reef fishes are lacking. Such studies dealing with the variation of disparity, i.e. the diversity of organic form, over ontogeny could be a first step in detecting evolutionary mechanisms in these fishes. The damselfishes (Pomacentridae have a bipartite life-cycle, as do the majority of demersal coral reef fishes. During their pelagic dispersion phase, all larvae feed on planktonic prey. On the other hand, juveniles and adults associated with the coral reef environment show a higher diversity of diets. Using geometric morphometrics, we study the ontogenetic dynamic of shape disparity of different head skeletal units (neurocranium, suspensorium and opercle, mandible and premaxilla in this fish family. We expected that larvae of different species might be relatively similar in shapes. Alternatively, specialization may become notable even in the juvenile and adult phase. Results The disparity levels increase significantly throughout ontogeny for each skeletal unit. At settlement, all larval shapes are already species-specific. Damselfishes show high levels of ontogenetic allometry during their post-settlement growth. The divergence of allometric patterns largely explains the changes in patterns and levels of shape disparity over ontogeny. The rate of shape change and the length of ontogenetic trajectories seem to be less variable among species. We also show that the high levels of shape disparity at the adult stage are correlated to a higher level of ecological and functional diversity in this stage. Conclusion Diversification throughout ontogeny of damselfishes results from the interaction among several developmental novelties enhancing disparity. The bipartite life-cycle of damselfishes exemplifies a case where the variation of environmental factors, i.e. the transition from the more homogeneous oceanic environment to the

Bipartite life cycle of coral reef fishes promotes increasing shape disparity of the head skeleton during ontogeny: an example from damselfishes (Pomacentridae)

Science.gov (United States)

2011-01-01

Background Quantitative studies of the variation of disparity during ontogeny exhibited by the radiation of coral reef fishes are lacking. Such studies dealing with the variation of disparity, i.e. the diversity of organic form, over ontogeny could be a first step in detecting evolutionary mechanisms in these fishes. The damselfishes (Pomacentridae) have a bipartite life-cycle, as do the majority of demersal coral reef fishes. During their pelagic dispersion phase, all larvae feed on planktonic prey. On the other hand, juveniles and adults associated with the coral reef environment show a higher diversity of diets. Using geometric morphometrics, we study the ontogenetic dynamic of shape disparity of different head skeletal units (neurocranium, suspensorium and opercle, mandible and premaxilla) in this fish family. We expected that larvae of different species might be relatively similar in shapes. Alternatively, specialization may become notable even in the juvenile and adult phase. Results The disparity levels increase significantly throughout ontogeny for each skeletal unit. At settlement, all larval shapes are already species-specific. Damselfishes show high levels of ontogenetic allometry during their post-settlement growth. The divergence of allometric patterns largely explains the changes in patterns and levels of shape disparity over ontogeny. The rate of shape change and the length of ontogenetic trajectories seem to be less variable among species. We also show that the high levels of shape disparity at the adult stage are correlated to a higher level of ecological and functional diversity in this stage. Conclusion Diversification throughout ontogeny of damselfishes results from the interaction among several developmental novelties enhancing disparity. The bipartite life-cycle of damselfishes exemplifies a case where the variation of environmental factors, i.e. the transition from the more homogeneous oceanic environment to the coral reef offering a wide

Extracting the information backbone in online system.

Directory of Open Access Journals (Sweden)

Qian-Ming Zhang

Full Text Available Information overload is a serious problem in modern society and many solutions such as recommender system have been proposed to filter out irrelevant information. In the literature, researchers have been mainly dedicated to improving the recommendation performance (accuracy and diversity of the algorithms while they have overlooked the influence of topology of the online user-object bipartite networks. In this paper, we find that some information provided by the bipartite networks is not only redundant but also misleading. With such "less can be more" feature, we design some algorithms to improve the recommendation performance by eliminating some links from the original networks. Moreover, we propose a hybrid method combining the time-aware and topology-aware link removal algorithms to extract the backbone which contains the essential information for the recommender systems. From the practical point of view, our method can improve the performance and reduce the computational time of the recommendation system, thus improving both of their effectiveness and efficiency.

Extracting the information backbone in online system.

Science.gov (United States)

Zhang, Qian-Ming; Zeng, An; Shang, Ming-Sheng

2013-01-01

Information overload is a serious problem in modern society and many solutions such as recommender system have been proposed to filter out irrelevant information. In the literature, researchers have been mainly dedicated to improving the recommendation performance (accuracy and diversity) of the algorithms while they have overlooked the influence of topology of the online user-object bipartite networks. In this paper, we find that some information provided by the bipartite networks is not only redundant but also misleading. With such "less can be more" feature, we design some algorithms to improve the recommendation performance by eliminating some links from the original networks. Moreover, we propose a hybrid method combining the time-aware and topology-aware link removal algorithms to extract the backbone which contains the essential information for the recommender systems. From the practical point of view, our method can improve the performance and reduce the computational time of the recommendation system, thus improving both of their effectiveness and efficiency.

Extracting the Information Backbone in Online System

Science.gov (United States)

Zhang, Qian-Ming; Zeng, An; Shang, Ming-Sheng

2013-01-01

Information overload is a serious problem in modern society and many solutions such as recommender system have been proposed to filter out irrelevant information. In the literature, researchers have been mainly dedicated to improving the recommendation performance (accuracy and diversity) of the algorithms while they have overlooked the influence of topology of the online user-object bipartite networks. In this paper, we find that some information provided by the bipartite networks is not only redundant but also misleading. With such “less can be more” feature, we design some algorithms to improve the recommendation performance by eliminating some links from the original networks. Moreover, we propose a hybrid method combining the time-aware and topology-aware link removal algorithms to extract the backbone which contains the essential information for the recommender systems. From the practical point of view, our method can improve the performance and reduce the computational time of the recommendation system, thus improving both of their effectiveness and efficiency. PMID:23690946

The Topology of African Exports: emerging patterns on spanning trees

OpenAIRE

Araújo, Tanya; Ferreira, M. Ennes

2016-01-01

This paper is a contribution to interweaving two lines of research that have progressed in separate ways: network analyses of international trade and the literature on African trade and development. Gathering empirical data on African countries has important limitations and so does the space occupied by African countries in the analyses of trade networks. Here, these limitations are dealt with by the definition of two independent bipartite networks: a destination share network and a commodit...

Shipboard Calibration Network Extension Utilizing COTS Products

Science.gov (United States)

2014-09-01

Identification TCP Transport Control Protocol VNC Virtual Network Computing WLAN Wireless Local Area Network xvi THIS PAGE INTENTIONALLY...available at the location of the sensor to be calibrated. With the wide adoption of the wireless local area network ( WLAN ) protocol, IEEE 802.11...standard devices have been proven to provide a stable, wireless infrastructure for many applications . The fast setup, wire-free configuration and

Marginally Stable Triangular Recurrent Neural Network Architecture for Time Series Prediction.

Science.gov (United States)

Sivakumar, Seshadri; Sivakumar, Shyamala

2017-09-25

This paper introduces a discrete-time recurrent neural network architecture using triangular feedback weight matrices that allows a simplified approach to ensuring network and training stability. The triangular structure of the weight matrices is exploited to readily ensure that the eigenvalues of the feedback weight matrix represented by the block diagonal elements lie on the unit circle in the complex z-plane by updating these weights based on the differential of the angular error variable. Such placement of the eigenvalues together with the extended close interaction between state variables facilitated by the nondiagonal triangular elements, enhances the learning ability of the proposed architecture. Simulation results show that the proposed architecture is highly effective in time-series prediction tasks associated with nonlinear and chaotic dynamic systems with underlying oscillatory modes. This modular architecture with dual upper and lower triangular feedback weight matrices mimics fully recurrent network architectures, while maintaining learning stability with a simplified training process. While training, the block-diagonal weights (hence the eigenvalues) of the dual triangular matrices are constrained to the same values during weight updates aimed at minimizing the possibility of overfitting. The dual triangular architecture also exploits the benefit of parsing the input and selectively applying the parsed inputs to the two subnetworks to facilitate enhanced learning performance.

Pinning adaptive synchronization of a class of uncertain complex dynamical networks with multi-link against network deterioration

International Nuclear Information System (INIS)

Li, Lixiang; Li, Weiwei; Kurths, Jürgen; Luo, Qun; Yang, Yixian; Li, Shudong

2015-01-01

For the reason that the uncertain complex dynamic network with multi-link is quite close to various practical networks, there is superiority in the fields of research and application. In this paper, we focus upon pinning adaptive synchronization for uncertain complex dynamic networks with multi-link against network deterioration. The pinning approach can be applied to adapt uncertain coupling factors of deteriorated networks which can compensate effects of uncertainty. Several new synchronization criterions for networks with multi-link are derived, which ensure the synchronized states to be local or global stable with uncertainty and deterioration. Results of simulation are shown to demonstrate the feasibility and usefulness of our method

Deep mining heterogeneous networks of biomedical linked data to predict novel drug-target associations.

Science.gov (United States)

Zong, Nansu; Kim, Hyeoneui; Ngo, Victoria; Harismendy, Olivier

2017-08-01

A heterogeneous network topology possessing abundant interactions between biomedical entities has yet to be utilized in similarity-based methods for predicting drug-target associations based on the array of varying features of drugs and their targets. Deep learning reveals features of vertices of a large network that can be adapted in accommodating the similarity-based solutions to provide a flexible method of drug-target prediction. We propose a similarity-based drug-target prediction method that enhances existing association discovery methods by using a topology-based similarity measure. DeepWalk, a deep learning method, is adopted in this study to calculate the similarities within Linked Tripartite Network (LTN), a heterogeneous network generated from biomedical linked datasets. This proposed method shows promising results for drug-target association prediction: 98.96% AUC ROC score with a 10-fold cross-validation and 99.25% AUC ROC score with a Monte Carlo cross-validation with LTN. By utilizing DeepWalk, we demonstrate that: (i) this method outperforms other existing topology-based similarity computation methods, (ii) the performance is better for tripartite than with bipartite networks and (iii) the measure of similarity using network topology outperforms the ones derived from chemical structure (drugs) or genomic sequence (targets). Our proposed methodology proves to be capable of providing a promising solution for drug-target prediction based on topological similarity with a heterogeneous network, and may be readily re-purposed and adapted in the existing of similarity-based methodologies. The proposed method has been developed in JAVA and it is available, along with the data at the following URL: https://github.com/zongnansu1982/drug-target-prediction . nazong@ucsd.edu. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

International research networks in pharmaceuticals

DEFF Research Database (Denmark)

Cantner, Uwe; Rake, Bastian

2014-01-01

of scientific publications related to pharmaceutical research and applying social network analysis, we find that both the number of countries and their connectivity increase in almost all disease group specific networks. The cores of the networks consist of high income OECD countries and remain rather stable......Knowledge production and scientific research have become increasingly more collaborative and international, particularly in pharmaceuticals. We analyze this tendency in general and tie formation in international research networks on the country level in particular. Based on a unique dataset...... over time. Using network regression techniques to analyze the network dynamics our results indicate that accumulative advantages based on connectedness and multi-connectivity are positively related to changes in the countries' collaboration intensity whereas various indicators on similarity between...

On Identities in Modern Networks

Directory of Open Access Journals (Sweden)

Libor Polcak

2014-09-01

Full Text Available Communicating parties inside computer networks use different kind of identifiers. Some of these identifiers are stable, e.g., logins used to access a specific service, some are only temporary, e.g., dynamically assigned IP addresses. This paper tackles several challenges of lawful interception that emerged in modern networks. The main contribution is the graph model that links identities learnt from various sources distributed in a network. The inferred identities result into an interception of more detailed data in conformance with the issued court order. The approach deals with network address translation, short-lived identifiers and simultaneous usage of different identities. The approach was evaluated to be viable during real network testing based on various means to learn identities of users connected to a network.

Neural Network to Solve Concave Games

OpenAIRE

Liu, Zixin; Wang, Nengfa

2014-01-01

The issue on neural network method to solve concave games is concerned. Combined with variational inequality, Ky Fan inequality, and projection equation, concave games are transformed into a neural network model. On the basis of the Lyapunov stable theory, some stability results are also given. Finally, two classic games’ simulation results are given to illustrate the theoretical results.

Control of coupled oscillator networks with application to microgrid technologies

Science.gov (United States)

Arenas, Alex

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

Control of coupled oscillator networks with application to microgrid technologies.

Science.gov (United States)

Skardal, Per Sebastian; Arenas, Alex

2015-08-01

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

A ternary logic model for recurrent neuromime networks with delay.

Science.gov (United States)

Hangartner, R D; Cull, P

1995-07-01

In contrast to popular recurrent artificial neural network (RANN) models, biological neural networks have unsymmetric structures and incorporate significant delays as a result of axonal propagation. Consequently, biologically inspired neural network models are more accurately described by nonlinear differential-delay equations rather than nonlinear ordinary differential equations (ODEs), and the standard techniques for studying the dynamics of RANNs are wholly inadequate for these models. This paper develops a ternary-logic based method for analyzing these networks. Key to the technique is the realization that a nonzero delay produces a bounded stability region. This result significantly simplifies the construction of sufficient conditions for characterizing the network equilibria. If the network gain is large enough, each equilibrium can be classified as either asymptotically stable or unstable. To illustrate the analysis technique, the swim central pattern generator (CPG) of the sea slug Tritonia diomedea is examined. For wide range of reasonable parameter values, the ternary analysis shows that none of the network equilibria are stable, and thus the network must oscillate. The results show that complex synaptic dynamics are not necessary for pattern generation.

Personalized recommendation based on unbiased consistence

Science.gov (United States)

Zhu, Xuzhen; Tian, Hui; Zhang, Ping; Hu, Zheng; Zhou, Tao

2015-08-01

Recently, in physical dynamics, mass-diffusion-based recommendation algorithms on bipartite network provide an efficient solution by automatically pushing possible relevant items to users according to their past preferences. However, traditional mass-diffusion-based algorithms just focus on unidirectional mass diffusion from objects having been collected to those which should be recommended, resulting in a biased causal similarity estimation and not-so-good performance. In this letter, we argue that in many cases, a user's interests are stable, and thus bidirectional mass diffusion abilities, no matter originated from objects having been collected or from those which should be recommended, should be consistently powerful, showing unbiased consistence. We further propose a consistence-based mass diffusion algorithm via bidirectional diffusion against biased causality, outperforming the state-of-the-art recommendation algorithms in disparate real data sets, including Netflix, MovieLens, Amazon and Rate Your Music.

Gel network shampoo formulation and hair health benefits.

Science.gov (United States)

Marsh, J M; Brown, M A; Felts, T J; Hutton, H D; Vatter, M L; Whitaker, S; Wireko, F C; Styczynski, P B; Li, C; Henry, I D

2017-10-01

The objective of this work was to create a shampoo formula that contains a stable ordered gel network structure that delivers fatty alcohols inside hair. X-ray diffraction (SAXS and WAXS), SEM and DSC have been used to confirm formation of the ordered Lβ gel network with fatty alcohol (cetyl and stearyl alcohols) and an anionic surfactant (SLE1S). Micro-autoradiography and extraction methods using GC-MS were used to confirm penetration of fatty alcohols into hair, and cyclic fatigue testing was used to measure hair strength. In this work, evidence of a stable Lβ ordered gel network structure created from cetyl and stearyl alcohols and anionic surfactant (SLE1S) is presented, and this is confirmed via scanning electron microscopy images showing lamella layers and differential scanning calorimetry (DSC) showing new melting peaks vs the starting fatty alcohols. Hair washed for 16 repeat cycles with this shampoo showed penetration of fatty alcohols from the gel network into hair as confirmed by a differential extraction method with GC-MS and by radiolabelling of stearyl alcohol and showing its presence inside hair cross-sections. The gel network role in delivering fatty alcohol inside hair is demonstrated by comparing with a shampoo with added fatty alcohol not in an ordered gel network structure. The hair containing fatty alcohol was measured via the Dia-stron cyclic fatigue instrument and showed a significantly higher number of cycles to break vs control. The formation of a stable gel network was confirmed in the formulated shampoo, and it was demonstrated that this gel network is important to deliver cetyl and stearyl alcohols into hair. The presence of fatty alcohol inside hair was shown to deliver a hair strength benefit via cyclic fatigue testing. © 2017 Society of Cosmetic Scientists and the Société Française de Cosmétologie.

MCBT: Multi-Hop Cluster Based Stable Backbone Trees for Data Collection and Dissemination in WSNs

Directory of Open Access Journals (Sweden)

Tae-Jin Lee

2009-07-01

Full Text Available We propose a stable backbone tree construction algorithm using multi-hop clusters for wireless sensor networks (WSNs. The hierarchical cluster structure has advantages in data fusion and aggregation. Energy consumption can be decreased by managing nodes with cluster heads. Backbone nodes, which are responsible for performing and managing multi-hop communication, can reduce the communication overhead such as control traffic and minimize the number of active nodes. Previous backbone construction algorithms, such as Hierarchical Cluster-based Data Dissemination (HCDD and Multicluster, Mobile, Multimedia radio network (MMM, consume energy quickly. They are designed without regard to appropriate factors such as residual energy and degree (the number of connections or edges to other nodes of a node for WSNs. Thus, the network is quickly disconnected or has to reconstruct a backbone. We propose a distributed algorithm to create a stable backbone by selecting the nodes with higher energy or degree as the cluster heads. This increases the overall network lifetime. Moreover, the proposed method balances energy consumption by distributing the traffic load among nodes around the cluster head. In the simulation, the proposed scheme outperforms previous clustering schemes in terms of the average and the standard deviation of residual energy or degree of backbone nodes, the average residual energy of backbone nodes after disseminating the sensed data, and the network lifetime.

Shear-induced network-to-network transition in a block copolymer melt

International Nuclear Information System (INIS)

Cochran, Eric W.; Bates, Frank S.

2004-01-01

A tricontinuous (10,3)c network phase is documented in a poly(cyclohexylethylene-b-ethylethylene-b-ethylene) triblock copolymer melt based on small-angle x-ray scattering. Application of shear transforms the self-assembled soft material into a single crystal (10,3)d network while preserving the short-range threefold connector geometry. Long-range topological restructuring reduces the space group symmetry, from Fddd to Pnna, maintaining orthorhombic lattice symmetry. Both phases are stable to long time annealing, indicative of nearly degenerate free energies and prohibitive kinetic barriers

Network-based association of hypoxia-responsive genes with cardiovascular diseases

International Nuclear Information System (INIS)

Wang, Rui-Sheng; Oldham, William M; Loscalzo, Joseph

2014-01-01

Molecular oxygen is indispensable for cellular viability and function. Hypoxia is a stress condition in which oxygen demand exceeds supply. Low cellular oxygen content induces a number of molecular changes to activate regulatory pathways responsible for increasing the oxygen supply and optimizing cellular metabolism under limited oxygen conditions. Hypoxia plays critical roles in the pathobiology of many diseases, such as cancer, heart failure, myocardial ischemia, stroke, and chronic lung diseases. Although the complicated associations between hypoxia and cardiovascular (and cerebrovascular) diseases (CVD) have been recognized for some time, there are few studies that investigate their biological link from a systems biology perspective. In this study, we integrate hypoxia genes, CVD genes, and the human protein interactome in order to explore the relationship between hypoxia and cardiovascular diseases at a systems level. We show that hypoxia genes are much closer to CVD genes in the human protein interactome than that expected by chance. We also find that hypoxia genes play significant bridging roles in connecting different cardiovascular diseases. We construct a hypoxia-CVD bipartite network and find several interesting hypoxia-CVD modules with significant gene ontology similarity. Finally, we show that hypoxia genes tend to have more CVD interactors in the human interactome than in random networks of matching topology. Based on these observations, we can predict novel genes that may be associated with CVD. This network-based association study gives us a broad view of the relationships between hypoxia and cardiovascular diseases and provides new insights into the role of hypoxia in cardiovascular biology. (paper)

Phylogenetic trait-based analyses of ecological networks.

Science.gov (United States)

Rafferty, Nicole E; Ives, Anthony R

2013-10-01

Ecological networks of two interacting guilds of species, such as flowering plants and pollinators, are common in nature, and studying their structure can yield insights into their resilience to environmental disturbances. Here we develop analytical methods for exploring the strengths of interactions within bipartite networks consisting of two guilds of phylogenetically related species. We then apply these methods to investigate the resilience of a plant-pollinator community to anticipated climate change. The methods allow the statistical assessment of, for example, whether closely related pollinators are more likely to visit plants with similar relative frequencies, and whether closely related pollinators tend to visit closely related plants. The methods can also incorporate trait information, allowing us to identify which plant traits are likely responsible for attracting different pollinators. These questions are important for our study of 14 prairie plants and their 22 insect pollinators. Over the last 70 years, six of the plants have advanced their flowering, while eight have not. When we experimentally forced earlier flowering times, five of the six advanced-flowering species experienced higher pollinator visitation rates, whereas only one of the eight other species had more visits; this network thus appears resilient to climate change, because those species with advanced flowering have ample pollinators earlier in the season. Using the methods developed here, we show that advanced-flowering plants did not have a distinct pollinator community from the other eight species. Furthermore, pollinator phylogeny did not explain pollinator community composition; closely related pollinators were not more likely to visit the same plant species. However, differences among pollinator communities visiting different plants were explained by plant height, floral color, and symmetry. As a result, closely related plants attracted similar numbers of pollinators. By parsing out

Take it of leave it : Mechanisms underlying bacterial bistable regulatory networks

NARCIS (Netherlands)

Siebring, Jeroen; Sorg, Robin; Herber, Martijn; Kuipers, Oscar; Filloux, Alain A.M.

2012-01-01

Bistable switches occur in regulatory networks that can exist in two distinct stable states. Such networks allow distinct switching of individual cells. In bacteria these switches coexist with regulatory networks that respond gradually to environmental input. Bistable switches play key roles in high

Structural stability of interaction networks against negative external fields

Science.gov (United States)

Yoon, S.; Goltsev, A. V.; Mendes, J. F. F.

2018-04-01

We explore structural stability of weighted and unweighted networks of positively interacting agents against a negative external field. We study how the agents support the activity of each other to confront the negative field, which suppresses the activity of agents and can lead to collapse of the whole network. The competition between the interactions and the field shape the structure of stable states of the system. In unweighted networks (uniform interactions) the stable states have the structure of k -cores of the interaction network. The interplay between the topology and the distribution of weights (heterogeneous interactions) impacts strongly the structural stability against a negative field, especially in the case of fat-tailed distributions of weights. We show that apart from critical slowing down there is also a critical change in the system structure that precedes the network collapse. The change can serve as an early warning of the critical transition. To characterize changes of network structure we develop a method based on statistical analysis of the k -core organization and so-called "corona" clusters belonging to the k -cores.

Cognitive Routing in Software-Defined Underwater Acoustic Networks

Directory of Open Access Journals (Sweden)

Huma Ghafoor

2017-12-01

Full Text Available There are two different types of primary users (natural acoustic and artificial acoustic, and there is a long propagation delay for acoustic links in underwater cognitive acoustic networks (UCANs. Thus, the selection of a stable route is one of the key design factors for improving overall network stability, thereby reducing end-to-end delay. Software-defined networking (SDN is a novel approach that improves network intelligence. To this end, we propose a novel SDN-based routing protocol for UCANs in order to find a stable route between source and destination. A main controller is placed in a surface buoy that is responsible for the global view of the network, whereas local controllers are placed in different autonomous underwater vehicles (AUVs that are responsible for a localized view of the network. The AUVs have fixed trajectories, and sensor nodes within transmission range of the AUVs serve as gateways to relay the gathered information to the controllers. This is an SDN-based underwater communications scheme whereby two nodes can only communicate when they have a consensus about a common idle channel. To evaluate our proposed scheme, we perform extensive simulations and improve network performance in terms of end-to-end delay, delivery ratio, and overhead.

Analysis of Recurrent Analog Neural Networks

Directory of Open Access Journals (Sweden)

Z. Raida

1998-06-01

Full Text Available In this paper, an original rigorous analysis of recurrent analog neural networks, which are built from opamp neurons, is presented. The analysis, which comes from the approximate model of the operational amplifier, reveals causes of possible non-stable states and enables to determine convergence properties of the network. Results of the analysis are discussed in order to enable development of original robust and fast analog networks. In the analysis, the special attention is turned to the examination of the influence of real circuit elements and of the statistical parameters of processed signals to the parameters of the network.

Multistability in bidirectional associative memory neural networks

International Nuclear Information System (INIS)

Huang Gan; Cao Jinde

2008-01-01

In this Letter, the multistability issue is studied for Bidirectional Associative Memory (BAM) neural networks. Based on the existence and stability analysis of the neural networks with or without delay, it is found that the 2n-dimensional networks can have 3 n equilibria and 2 n equilibria of them are locally exponentially stable, where each layer of the BAM network has n neurons. Furthermore, the results has been extended to (n+m)-dimensional BAM neural networks, where there are n and m neurons on the two layers respectively. Finally, two numerical examples are presented to illustrate the validity of our results

Multistability in bidirectional associative memory neural networks

Science.gov (United States)

Huang, Gan; Cao, Jinde

2008-04-01

In this Letter, the multistability issue is studied for Bidirectional Associative Memory (BAM) neural networks. Based on the existence and stability analysis of the neural networks with or without delay, it is found that the 2 n-dimensional networks can have 3 equilibria and 2 equilibria of them are locally exponentially stable, where each layer of the BAM network has n neurons. Furthermore, the results has been extended to (n+m)-dimensional BAM neural networks, where there are n and m neurons on the two layers respectively. Finally, two numerical examples are presented to illustrate the validity of our results.

Stability analysis for stochastic BAM nonlinear neural network with delays

Science.gov (United States)

Lv, Z. W.; Shu, H. S.; Wei, G. L.

2008-02-01

In this paper, stochastic bidirectional associative memory neural networks with constant or time-varying delays is considered. Based on a Lyapunov-Krasovskii functional and the stochastic stability analysis theory, we derive several sufficient conditions in order to guarantee the global asymptotically stable in the mean square. Our investigation shows that the stochastic bidirectional associative memory neural networks are globally asymptotically stable in the mean square if there are solutions to some linear matrix inequalities(LMIs). Hence, the global asymptotic stability of the stochastic bidirectional associative memory neural networks can be easily checked by the Matlab LMI toolbox. A numerical example is given to demonstrate the usefulness of the proposed global asymptotic stability criteria.

Stability analysis for stochastic BAM nonlinear neural network with delays

International Nuclear Information System (INIS)

Lv, Z W; Shu, H S; Wei, G L

2008-01-01

In this paper, stochastic bidirectional associative memory neural networks with constant or time-varying delays is considered. Based on a Lyapunov-Krasovskii functional and the stochastic stability analysis theory, we derive several sufficient conditions in order to guarantee the global asymptotically stable in the mean square. Our investigation shows that the stochastic bidirectional associative memory neural networks are globally asymptotically stable in the mean square if there are solutions to some linear matrix inequalities(LMIs). Hence, the global asymptotic stability of the stochastic bidirectional associative memory neural networks can be easily checked by the Matlab LMI toolbox. A numerical example is given to demonstrate the usefulness of the proposed global asymptotic stability criteria

Political Obstacles to Regionalization of the SUS: perceptions of Municipal Health Secretaries with seat in the Bipartite Interagency Commissions.

Science.gov (United States)

Moreira, Marcelo Rasga; Ribeiro, José Mendes; Ouverney, Assis Mafort

2017-04-01

This paper aims to identify and analyze the political obstacles to the implementation of Organizational Contract of Public Action (COAP) based on the perceptions of municipal health secretaries of Bipartite Interagency Commissions (CIB). For this purpose, we interviewed 195 secretaries (92% of the total) from October 2015 to August 2016. Based on the approach of policy analysis, the main hurdles identified were, in short, a traditional obstacle (lack of resources), one that has been gaining strength in recent years (judicialization of politics) and another, perhaps unheard of: the party-political system and the State Executive Branch are the great absentees in the coalitions in support of SUS regionalization policies. We can conclude that such obstacles indicate an extremely negative setting for the implementation of the COAP and other SUS regionalization policies. Thus, it is incumbent upon those involved to reflect, negotiate and build consensus on improving the health of the population and overcome such obstacles if, of course, they embrace the authors' concept that regionalization is fundamental for the SUS.

Splitting Strategy for Simulating Genetic Regulatory Networks

Directory of Open Access Journals (Sweden)

Xiong You

2014-01-01

Full Text Available The splitting approach is developed for the numerical simulation of genetic regulatory networks with a stable steady-state structure. The numerical results of the simulation of a one-gene network, a two-gene network, and a p53-mdm2 network show that the new splitting methods constructed in this paper are remarkably more effective and more suitable for long-term computation with large steps than the traditional general-purpose Runge-Kutta methods. The new methods have no restriction on the choice of stepsize due to their infinitely large stability regions.

From network structure to network reorganization: implications for adult neurogenesis

International Nuclear Information System (INIS)

Schneider-Mizell, Casey M; Zochowski, Michal R; Sander, Leonard M; Parent, Jack M; Ben-Jacob, Eshel

2010-01-01

Networks can be dynamical systems that undergo functional and structural reorganization. One example of such a process is adult hippocampal neurogenesis, in which new cells are continuously born and incorporate into the existing network of the dentate gyrus region of the hippocampus. Many of these introduced cells mature and become indistinguishable from established neurons, joining the existing network. Activity in the network environment is known to promote birth, survival and incorporation of new cells. However, after epileptogenic injury, changes to the connectivity structure around the neurogenic niche are known to correlate with aberrant neurogenesis. The possible role of network-level changes in the development of epilepsy is not well understood. In this paper, we use a computational model to investigate how the structural and functional outcomes of network reorganization, driven by addition of new cells during neurogenesis, depend on the original network structure. We find that there is a stable network topology that allows the network to incorporate new neurons in a manner that enhances activity of the persistently active region, but maintains global network properties. In networks having other connectivity structures, new cells can greatly alter the distribution of firing activity and destroy the initial activity patterns. We thus find that new cells are able to provide focused enhancement of network only for small-world networks with sufficient inhibition. Network-level deviations from this topology, such as those caused by epileptogenic injury, can set the network down a path that develops toward pathological dynamics and aberrant structural integration of new cells

Stable isotopes

International Nuclear Information System (INIS)

Evans, D.K.

1986-01-01

Seventy-five percent of the world's stable isotope supply comes from one producer, Oak Ridge Nuclear Laboratory (ORNL) in the US. Canadian concern is that foreign needs will be met only after domestic needs, thus creating a shortage of stable isotopes in Canada. This article describes the present situation in Canada (availability and cost) of stable isotopes, the isotope enrichment techniques, and related research programs at Chalk River Nuclear Laboratories (CRNL)

Transitions from Trees to Cycles in Adaptive Flow Networks

Directory of Open Access Journals (Sweden)

Erik A. Martens

2017-11-01

Full Text Available Transport networks are crucial to the functioning of natural and technological systems. Nature features transport networks that are adaptive over a vast range of parameters, thus providing an impressive level of robustness in supply. Theoretical and experimental studies have found that real-world transport networks exhibit both tree-like motifs and cycles. When the network is subject to load fluctuations, the presence of cyclic motifs may help to reduce flow fluctuations and, thus, render supply in the network more robust. While previous studies considered network topology via optimization principles, here, we take a dynamical systems approach and study a simple model of a flow network with dynamically adapting weights (conductances. We assume a spatially non-uniform distribution of rapidly fluctuating loads in the sinks and investigate what network configurations are dynamically stable. The network converges to a spatially non-uniform stable configuration composed of both cyclic and tree-like structures. Cyclic structures emerge locally in a transcritical bifurcation as the amplitude of the load fluctuations is increased. The resulting adaptive dynamics thus partitions the network into two distinct regions with cyclic and tree-like structures. The location of the boundary between these two regions is determined by the amplitude of the fluctuations. These findings may explain why natural transport networks display cyclic structures in the micro-vascular regions near terminal nodes, but tree-like features in the regions with larger veins.

Stable Isotope Data

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Tissue samples (skin, bone, blood, muscle) are analyzed for stable carbon, stable nitrogen, and stable sulfur analysis. Many samples are used in their entirety for...

stableGP

Data.gov (United States)

National Aeronautics and Space Administration — The code in the stableGP package implements Gaussian process calculations using efficient and numerically stable algorithms. Description of the algorithms is in the...

Contagion on complex networks with persuasion

Science.gov (United States)

Huang, Wei-Min; Zhang, Li-Jie; Xu, Xin-Jian; Fu, Xinchu

2016-03-01

The threshold model has been widely adopted as a classic model for studying contagion processes on social networks. We consider asymmetric individual interactions in social networks and introduce a persuasion mechanism into the threshold model. Specifically, we study a combination of adoption and persuasion in cascading processes on complex networks. It is found that with the introduction of the persuasion mechanism, the system may become more vulnerable to global cascades, and the effects of persuasion tend to be more significant in heterogeneous networks than those in homogeneous networks: a comparison between heterogeneous and homogeneous networks shows that under weak persuasion, heterogeneous networks tend to be more robust against random shocks than homogeneous networks; whereas under strong persuasion, homogeneous networks are more stable. Finally, we study the effects of adoption and persuasion threshold heterogeneity on systemic stability. Though both heterogeneities give rise to global cascades, the adoption heterogeneity has an overwhelmingly stronger impact than the persuasion heterogeneity when the network connectivity is sufficiently dense.

A Dynamic Connectome Supports the Emergence of Stable Computational Function of Neural Circuits through Reward-Based Learning.

Science.gov (United States)

Kappel, David; Legenstein, Robert; Habenschuss, Stefan; Hsieh, Michael; Maass, Wolfgang

2018-01-01

Synaptic connections between neurons in the brain are dynamic because of continuously ongoing spine dynamics, axonal sprouting, and other processes. In fact, it was recently shown that the spontaneous synapse-autonomous component of spine dynamics is at least as large as the component that depends on the history of pre- and postsynaptic neural activity. These data are inconsistent with common models for network plasticity and raise the following questions: how can neural circuits maintain a stable computational function in spite of these continuously ongoing processes, and what could be functional uses of these ongoing processes? Here, we present a rigorous theoretical framework for these seemingly stochastic spine dynamics and rewiring processes in the context of reward-based learning tasks. We show that spontaneous synapse-autonomous processes, in combination with reward signals such as dopamine, can explain the capability of networks of neurons in the brain to configure themselves for specific computational tasks, and to compensate automatically for later changes in the network or task. Furthermore, we show theoretically and through computer simulations that stable computational performance is compatible with continuously ongoing synapse-autonomous changes. After reaching good computational performance it causes primarily a slow drift of network architecture and dynamics in task-irrelevant dimensions, as observed for neural activity in motor cortex and other areas. On the more abstract level of reinforcement learning the resulting model gives rise to an understanding of reward-driven network plasticity as continuous sampling of network configurations.

Stability, gain, and robustness in quantum feedback networks

International Nuclear Information System (INIS)

D'Helon, C.; James, M. R.

2006-01-01

In this paper we are concerned with the problem of stability for quantum feedback networks. We demonstrate in the context of quantum optics how stability of quantum feedback networks can be guaranteed using only simple gain inequalities for network components and algebraic relationships determined by the network. Quantum feedback networks are shown to be stable if the loop gain is less than one--this is an extension of the famous small gain theorem of classical control theory. We illustrate the simplicity and power of the small gain approach with applications to important problems of robust stability and robust stabilization

Abnormal-induced theta activity supports early directed-attention network deficits in progressive MCI.

Science.gov (United States)

Deiber, Marie-Pierre; Ibañez, Vicente; Missonnier, Pascal; Herrmann, François; Fazio-Costa, Lara; Gold, Gabriel; Giannakopoulos, Panteleimon

2009-09-01

The electroencephalography (EEG) theta frequency band reacts to memory and selective attention paradigms. Global theta oscillatory activity includes a posterior phase-locked component related to stimulus processing and a frontal-induced component modulated by directed attention. To investigate the presence of early deficits in the directed attention-related network in elderly individuals with mild cognitive impairment (MCI), time-frequency analysis at baseline was used to assess global and induced theta oscillatory activity (4-6Hz) during n-back working memory tasks in 29 individuals with MCI and 24 elderly controls (EC). At 1-year follow-up, 13 MCI patients were still stable and 16 had progressed. Baseline task performance was similar in stable and progressive MCI cases. Induced theta activity at baseline was significantly reduced in progressive MCI as compared to EC and stable MCI in all n-back tasks, which were similar in terms of directed attention requirements. While performance is maintained, the decrease of induced theta activity suggests early deficits in the directed-attention network in progressive MCI, whereas this network is functionally preserved in stable MCI.

Optimization of Pipe Networks

DEFF Research Database (Denmark)

Hansen, C. T.; Madsen, Kaj; Nielsen, Hans Bruun

1991-01-01

algorithm using successive linear programming is presented. The performance of the algorithm is illustrated by optimizing a network with 201 pipes and 172 nodes. It is concluded that the new algorithm seems to be very efficient and stable, and that it always finds a solution with a cost near the best...

Plant-pollinator interactions in a biodiverse meadow are rather stable and tight for 3 consecutive years.

Science.gov (United States)

Fang, Qiang; Huang, Shuangquan

2016-05-01

Plant-pollinator interactions can be highly variable across years in natural communities. Although variation in the species composition and its basic structure has been investigated to understand the dynamic nature of pollination networks, little is known about the temporal dynamic of interaction strength between the same plant and pollinator species in any natural community. Pollinator-mediated selection on the evolution of floral traits could be diminished if plant-pollinator interactions vary temporally. To quantify the temporal variation in plant-pollinator interactions and the interaction strength (observed visits), we compared weighted networks between plants and pollinators in a biodiverse alpine meadow in Shangri-La, southwest China for 3 consecutive years. Although plant-pollinator interactions were highly dynamic such that identical interactions only accounted for 10.7% of the total between pair years, the diversity of interactions was stable. These identical interactions contributed 41.2% of total visits and were similar in strength and weighted nestedness. For plant species, 72.6% of species were visited by identical pollinator species between pair years, accounting for over half of the total visits and three-quarters at the functional group level. More generalized pollinators contributed more connectiveness and were more central in networks across years. However, there was no similar or even opposite trend for plant species, which suggested that specialized plant species may also be central in pollinator networks. The variation in pollinator composition decreased as pollinator species numbers increased, suggesting that generalized plants experienced stable pollinator partition. The stable, tight interactions between generalized pollinators and specialized plants represent cornerstones of the studied community. © 2016 International Society of Zoological Sciences, Institute of Zoology/Chinese Academy of Sciences and John Wiley & Sons Australia, Ltd.

Hydrothermally stable molecular separation membranes from organically linked silica

Energy Technology Data Exchange (ETDEWEB)

Castricum, H.L.; Sah, A; Blank, D.H.A.; Ten Elshof, J.E. [Inorganic Materials Science, MESA Institute for Nanotechnology, University of Twente, P.O. Box 217, 7500 AE Enschede (Netherlands); Kreiter, R.; Vente, J.F. [ECN Energy Efficiency in the Industry, Petten (Netherlands)

2008-06-15

A highly hydrothermally stable microporous network material has been developed that can be applied in energy-efficient molecular sieving. The material was synthesized by employing organically bridged monomers in acid-catalysed sol-gel hydrolysis and condensation, and is composed of covalently bonded organic and inorganic moieties. Due to its hybrid nature, it withstands higher temperatures than organic polymers and exhibits high solvolytical and acid stability. A thin film membrane that was prepared with the hybrid material was found to be stable in the dehydration of n-butanol at 150C for almost two years. This membrane is the first that combines a high resistance against water at elevated temperatures with a high separation factor and permeance. It therefore has high potential for energy-efficient molecular separation under industrial conditions, including the dehydration of organic solvents. The organically bridged monomers induce increased toughness in the thin film layer. This suppresses hydrolysis of Si-O-Si network bonds and results in a high resistance towards stress-induced cracking. The large non-hydrolysable units thus remain well incorporated in the surrounding matrix such that the material combines high (pore) structural and mechanical stability. The sol mean particle size was found to be a viable parameter to tune the thickness of the membrane layer and thus optimize the separation performance. We anticipate that other hybrid organosilicas can be made in a similar fashion, to yield a whole new class of materials with superior molecular sieving properties and high hydrothermal stability.

Complete nucleotide sequences of a new bipartite begomovirus from Malvastrum sp. plants with bright yellow mosaic symptoms in South Texas.

Science.gov (United States)

Alabi, Olufemi J; Villegas, Cecilia; Gregg, Lori; Murray, K Daniel

2016-06-01

Two isolates of a novel bipartite begomovirus, tentatively named malvastrum bright yellow mosaic virus (MaBYMV), were molecularly characterized from naturally infected plants of the genus Malvastrum showing bright yellow mosaic disease symptoms in South Texas. Six complete DNA-A and five DNA-B genome sequences of MaBYMV obtained from the isolates ranged in length from 2,608 to 2,609 nucleotides (nt) and 2,578 to 2,605 nt, respectively. Both genome segments shared a 178- to 180-nt common region. In pairwise comparisons, the complete DNA-A and DNA-B sequences of MaBYMV were most similar (87-88 % and 79-81 % identity, respectively) and phylogenetically related to the corresponding sequences of sida mosaic Sinaloa virus-[MX-Gua-06]. Further analysis revealed that MaBYMV is a putative recombinant virus, thus supporting the notion that malvaceous hosts may be influencing the evolution of several begomoviruses. The design of new diagnostic primers enabled the detection of MaBYMV in cohorts of Bemisia tabaci collected from symptomatic Malvastrum sp. plants, thus implicating whiteflies as potential vectors of the virus.

A Typology to Explain Changing Social Networks Post Stroke.

Science.gov (United States)

Northcott, Sarah; Hirani, Shashivadan P; Hilari, Katerina

2018-05-08

Social network typologies have been used to classify the general population but have not previously been applied to the stroke population. This study investigated whether social network types remain stable following a stroke, and if not, why some people shift network type. We used a mixed methods design. Participants were recruited from two acute stroke units. They completed the Stroke Social Network Scale (SSNS) two weeks and six months post stroke and in-depth interviews 8-15 months following the stroke. Qualitative data was analysed using Framework Analysis; k-means cluster analysis was applied to the six-month data set. Eighty-seven participants were recruited, 71 were followed up at six months, and 29 completed in-depth interviews. It was possible to classify all 29 participants into one of the following network types both prestroke and post stroke: diverse; friends-based; family-based; restricted-supported; restricted-unsupported. The main shift that took place post stroke was participants moving out of a diverse network into a family-based one. The friends-based network type was relatively stable. Two network types became more populated post stroke: restricted-unsupported and family-based. Triangulatory evidence was provided by k-means cluster analysis, which produced a cluster solution (for n = 71) with comparable characteristics to the network types derived from qualitative analysis. Following a stroke, a person's social network is vulnerable to change. Explanatory factors for shifting network type included the physical and also psychological impact of having a stroke, as well as the tendency to lose contact with friends rather than family.

Power control algorithms for mobile ad hoc networks

Directory of Open Access Journals (Sweden)

Nuraj L. Pradhan

2011-07-01

We will also focus on an adaptive distributed power management (DISPOW algorithm as an example of the multi-parameter optimization approach which manages the transmit power of nodes in a wireless ad hoc network to preserve network connectivity and cooperatively reduce interference. We will show that the algorithm in a distributed manner builds a unique stable network topology tailored to its surrounding node density and propagation environment over random topologies in a dynamic mobile wireless channel.

Simultaneous transmission of accurate time, stable frequency, data, and sensor system over one fiber with ITU 100 GHz grid

Science.gov (United States)

Horvath, Tomas; Munster, Petr; Vojtech, Josef; Velc, Radek; Oujezsky, Vaclav

2018-01-01

Optical fiber is the most used medium for current telecommunication networks. Besides data transmissions, special advanced applications like accurate time or stable frequency transmissions are more common, especially in research and education networks. On the other hand, new applications like distributed sensing are in ISP's interest because e.g. such sensing allows new service: protection of fiber infrastructure. Transmission of all applications in a single fiber can be very cost efficient but it is necessary to evaluate possible interaction before real application and deploying the service, especially if standard 100 GHz grid is considered. We performed laboratory measurement of simultaneous transmission of 100 G data based on DP-QPSK modulation format, accurate time, stable frequency and sensing system based on phase sensitive OTDR through two types of optical fibers, G.655 and G.653. These fibers are less common than G.652 fiber but thanks to their slightly higher nonlinear character, there are suitable for simulation of the worst case which can arise in a real network.

Expected Transmission Energy Route Metric for Wireless Mesh Senor Networks

Directory of Open Access Journals (Sweden)

YanLiang Jin

2011-01-01

Full Text Available Mesh is a network topology that achieves high throughput and stable intercommunication. With great potential, it is expected to be the key architecture of future networks. Wireless sensor networks are an active research area with numerous workshops and conferences arranged each year. The overall performance of a WSN highly depends on the energy consumption of the network. This paper designs a new routing metric for wireless mesh sensor networks. Results from simulation experiments reveal that the new metric algorithm improves the energy balance of the whole network and extends the lifetime of wireless mesh sensor networks (WMSNs.

Structural and robustness properties of smart-city transportation networks

International Nuclear Information System (INIS)

Zhang Zhen-Gang; Ding Zhuo; Fan Jing-Fang; Chen Xiao-Song; Meng Jun; Ye Fang-Fu; Ding Yi-Min

2015-01-01

The concept of smart city gives an excellent resolution to construct and develop modern cities, and also demands infrastructure construction. How to build a safe, stable, and highly efficient public transportation system becomes an important topic in the process of city construction. In this work, we study the structural and robustness properties of transportation networks and their sub-networks. We introduce a complementary network model to study the relevance and complementarity between bus network and subway network. Our numerical results show that the mutual supplement of networks can improve the network robustness. This conclusion provides a theoretical basis for the construction of public traffic networks, and it also supports reasonable operation of managing smart cities. (rapid communication)

Self-organized criticality in developing neuronal networks.

Directory of Open Access Journals (Sweden)

Christian Tetzlaff

Full Text Available Recently evidence has accumulated that many neural networks exhibit self-organized criticality. In this state, activity is similar across temporal scales and this is beneficial with respect to information flow. If subcritical, activity can die out, if supercritical epileptiform patterns may occur. Little is known about how developing networks will reach and stabilize criticality. Here we monitor the development between 13 and 95 days in vitro (DIV of cortical cell cultures (n = 20 and find four different phases, related to their morphological maturation: An initial low-activity state (≈19 DIV is followed by a supercritical (≈20 DIV and then a subcritical one (≈36 DIV until the network finally reaches stable criticality (≈58 DIV. Using network modeling and mathematical analysis we describe the dynamics of the emergent connectivity in such developing systems. Based on physiological observations, the synaptic development in the model is determined by the drive of the neurons to adjust their connectivity for reaching on average firing rate homeostasis. We predict a specific time course for the maturation of inhibition, with strong onset and delayed pruning, and that total synaptic connectivity should be strongly linked to the relative levels of excitation and inhibition. These results demonstrate that the interplay between activity and connectivity guides developing networks into criticality suggesting that this may be a generic and stable state of many networks in vivo and in vitro.

Mathematical Analysis of a PDE System for Biological Network Formation

KAUST Repository

Haskovec, Jan

2015-02-04

Motivated by recent physics papers describing rules for natural network formation, we study an elliptic-parabolic system of partial differential equations proposed by Hu and Cai [13, 15]. The model describes the pressure field thanks to Darcy\\'s type equation and the dynamics of the conductance network under pressure force effects with a diffusion rate D >= 0 representing randomness in the material structure. We prove the existence of global weak solutions and of local mild solutions and study their long term behavior. It turns out that, by energy dissipation, steady states play a central role to understand the network formation capacity of the system. We show that for a large diffusion coefficient D, the zero steady state is stable, while network formation occurs for small values of D due to the instability of the zero steady state, and the borderline case D = 0 exhibits a large class of dynamically stable (in the linearized sense) steady states.

PPARγ population shift produces disease-related changes in molecular networks associated with metabolic syndrome.

Science.gov (United States)

Jurkowski, W; Roomp, K; Crespo, I; Schneider, J G; Del Sol, A

2011-08-11

Peroxisome proliferator-activated receptor gamma (PPARγ) is a key regulator of adipocyte differentiation and has an important role in metabolic syndrome. Phosphorylation of the receptor's ligand-binding domain at serine 273 has been shown to change the expression of a large number of genes implicated in obesity. The difference in gene expression seen when comparing wild-type phosphorylated with mutant non-phosphorylated PPARγ may have important consequences for the cellular molecular network, the state of which can be shifted from the healthy to a stable diseased state. We found that a group of differentially expressed genes are involved in bi-stable switches and form a core network, the state of which changes with disease progression. These findings support the idea that bi-stable switches may be a mechanism for locking the core gene network into a diseased state and for efficiently propagating perturbations to more distant regions of the network. A structural analysis of the PPARγ-RXRα dimer complex supports the hypothesis of a major structural change between the two states, and this may represent an important mechanism leading to the differential expression observed in the core network.

Network interruptions

CERN Multimedia

2005-01-01

On Sunday 12 June 2005, a site-wide security software upgrade will be performed on all CERN network equipment. This maintenance operation will cause at least 2 short network interruptions of 2 minutes on each equipment item. There are hundreds of such items across the CERN site (Meyrin, Prévessin and all SPS and LHC pits), and it will thus take the whole day to treat them all. All network users and services will be affected. Central batch computing services will be interrupted during this period, expected to last from 8 a.m. until late evening. Job submission will still be possible but no jobs will actually be run. It is hoped to complete the computer centre upgrades in the morning so that stable access can be restored to lxplus, afs and nice services as soon as possible; this cannot be guaranteed, however. The opportunity will be used to interrupt and perform upgrades on the CERN Document Servers.

Networks of military alliances, wars, and international trade.

Science.gov (United States)

Jackson, Matthew O; Nei, Stephen

2015-12-15

We investigate the role of networks of alliances in preventing (multilateral) interstate wars. We first show that, in the absence of international trade, no network of alliances is peaceful and stable. We then show that international trade induces peaceful and stable networks: Trade increases the density of alliances so that countries are less vulnerable to attack and also reduces countries' incentives to attack an ally. We present historical data on wars and trade showing that the dramatic drop in interstate wars since 1950 is paralleled by a densification and stabilization of trading relationships and alliances. Based on the model we also examine some specific relationships, finding that countries with high levels of trade with their allies are less likely to be involved in wars with any other countries (including allies and nonallies), and that an increase in trade between two countries correlates with a lower chance that they will go to war with each other.

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

OpenAIRE

Kaiser, Marcus; Hilgetag, Claus C.

2010-01-01

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

A generalized model via random walks for information filtering

Energy Technology Data Exchange (ETDEWEB)

Ren, Zhuo-Ming, E-mail: zhuomingren@gmail.com [Department of Physics, University of Fribourg, Chemin du Musée 3, CH-1700, Fribourg (Switzerland); Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, ChongQing, 400714 (China); Kong, Yixiu [Department of Physics, University of Fribourg, Chemin du Musée 3, CH-1700, Fribourg (Switzerland); Shang, Ming-Sheng, E-mail: msshang@cigit.ac.cn [Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, ChongQing, 400714 (China); Zhang, Yi-Cheng [Department of Physics, University of Fribourg, Chemin du Musée 3, CH-1700, Fribourg (Switzerland)

2016-08-06

There could exist a simple general mechanism lurking beneath collaborative filtering and interdisciplinary physics approaches which have been successfully applied to online E-commerce platforms. Motivated by this idea, we propose a generalized model employing the dynamics of the random walk in the bipartite networks. Taking into account the degree information, the proposed generalized model could deduce the collaborative filtering, interdisciplinary physics approaches and even the enormous expansion of them. Furthermore, we analyze the generalized model with single and hybrid of degree information on the process of random walk in bipartite networks, and propose a possible strategy by using the hybrid degree information for different popular objects to toward promising precision of the recommendation. - Highlights: • We propose a generalized recommendation model employing the random walk dynamics. • The proposed model with single and hybrid of degree information is analyzed. • A strategy with the hybrid degree information improves precision of recommendation.

A generalized model via random walks for information filtering

International Nuclear Information System (INIS)

Ren, Zhuo-Ming; Kong, Yixiu; Shang, Ming-Sheng; Zhang, Yi-Cheng

2016-01-01

There could exist a simple general mechanism lurking beneath collaborative filtering and interdisciplinary physics approaches which have been successfully applied to online E-commerce platforms. Motivated by this idea, we propose a generalized model employing the dynamics of the random walk in the bipartite networks. Taking into account the degree information, the proposed generalized model could deduce the collaborative filtering, interdisciplinary physics approaches and even the enormous expansion of them. Furthermore, we analyze the generalized model with single and hybrid of degree information on the process of random walk in bipartite networks, and propose a possible strategy by using the hybrid degree information for different popular objects to toward promising precision of the recommendation. - Highlights: • We propose a generalized recommendation model employing the random walk dynamics. • The proposed model with single and hybrid of degree information is analyzed. • A strategy with the hybrid degree information improves precision of recommendation.

Research of Ad Hoc Networks Access Algorithm

Science.gov (United States)

Xiang, Ma

With the continuous development of mobile communication technology, Ad Hoc access network has become a hot research, Ad Hoc access network nodes can be used to expand capacity of multi-hop communication range of mobile communication system, even business adjacent to the community, improve edge data rates. When the ad hoc network is the access network of the internet, the gateway discovery protocol is very important to choose the most appropriate gateway to guarantee the connectivity between ad hoc network and IP based fixed networks. The paper proposes a QoS gateway discovery protocol which uses the time delay and stable route to the gateway selection conditions. And according to the gateway discovery protocol, it also proposes a fast handover scheme which can decrease the handover time and improve the handover efficiency.

A Combination of Stable Isotope Probing, Illumina Sequencing, and Co-occurrence Network to Investigate Thermophilic Acetate- and Lactate-Utilizing Bacteria.

Science.gov (United States)

Sun, Weimin; Krumins, Valdis; Dong, Yiran; Gao, Pin; Ma, Chunyan; Hu, Min; Li, Baoqin; Xia, Bingqing; He, Zijun; Xiong, Shangling

2018-01-01

Anaerobic digestion is a complicated microbiological process that involves a wide diversity of microorganisms. Acetate is one of the most important intermediates, and interactions between acetate-oxidizing bacteria and archaea could play an important role in the formation of methane in anoxic environments. Anaerobic digestion at thermophilic temperatures is known to increase methane production, but the effects on the microbial community are largely unknown. In the current study, stable isotope probing was used to characterize acetate- and lactate-oxidizing bacteria in thermophilic anaerobic digestion. In microcosms fed 13 C-acetate, bacteria related to members of Clostridium, Hydrogenophaga, Fervidobacterium, Spirochaeta, Limnohabitans, and Rhodococcus demonstrated elevated abundances of 13 C-DNA fractions, suggesting their activities in acetate oxidation. In the treatments fed 13 C-lactate, Anaeromyxobacter, Desulfobulbus, Syntrophus, Cystobacterineae, and Azospira were found to be the potential thermophilic lactate utilizers. PICRUSt predicted that enzymes related to nitrate and nitrite reduction would be enriched in 13 C-DNA fractions, suggesting that the acetate and lactate oxidation may be coupled with nitrate and/or nitrite reduction. Co-occurrence network analysis indicated bacterial taxa not enriched in 13 C-DNA fractions that may also play a critical role in thermophilic anaerobic digestion.

Search for Heavy Stable Charged Particles at $\\sqrt{s}$ = 13 TeV Utilizing a Multivariate Approach

CERN Document Server

AUTHOR|(INSPIRE)INSPIRE-00375809

Heavy stable charged particles (HSCPs) have been searched for at the Large Hadron Collider since its initial data taking in 2010. The search for heavy stable charged particles provide a means of directly probing the new physics realm, as they produce a detector signature unlike any particle discovered to date. The goal of this research is to investigate an idea that was introduced in the later stages of 2010-2012 data taking period. Rather than utilizing the current tight selection on the calculated particle mass the hypothesis is that by incorporating a multivariate approach, specif- ically an artificial neural network, the remaining selection criteria could be loosened allowing for a greater signal acceptance while maintaining acceptable background rejection via the multivariate discriminator from the artificial neural network. The increase in signal acceptance and retention or increase in background rejection increases the discovery potential for HSCPs and as a secondary objective calculates improved limit...

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

Science.gov (United States)

El Laithy, Karim; Bogdan, Martin

2014-04-01

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

A Secure and Stable Multicast Overlay Network with Load Balancing for Scalable IPTV Services

Directory of Open Access Journals (Sweden)

Tsao-Ta Wei

2012-01-01

Full Text Available The emerging multimedia Internet application IPTV over P2P network preserves significant advantages in scalability. IPTV media content delivered in P2P networks over public Internet still preserves the issues of privacy and intellectual property rights. In this paper, we use SIP protocol to construct a secure application-layer multicast overlay network for IPTV, called SIPTVMON. SIPTVMON can secure all the IPTV media delivery paths against eavesdroppers via elliptic-curve Diffie-Hellman (ECDH key exchange on SIP signaling and AES encryption. Its load-balancing overlay tree is also optimized from peer heterogeneity and churn of peer joining and leaving to minimize both service degradation and latency. The performance results from large-scale simulations and experiments on different optimization criteria demonstrate SIPTVMON's cost effectiveness in quality of privacy protection, stability from user churn, and good perceptual quality of objective PSNR values for scalable IPTV services over Internet.

FAST TCP over optical burst switched networks: Modeling and stability analysis

KAUST Repository

Shihada, Basem

2013-04-01

FAST TCP is important for promoting data-intensive applications since it can cleverly react to both packet loss and delay for detecting network congestion. This paper provides a continuous time model and extensive stability analysis of FAST TCP congestion-control mechanism in bufferless Optical Burst Switched Networks (OBS). The paper first shows that random burst contentions are essential to stabilize the network, but cause throughput degradation in FAST TCP flows when a burst with all the packets from a single round is dropped. Second, it shows that FAST TCP is vulnerable to burst delay and fails to detect network congestion due to the little variation of round-trip time, thus unstable. Finally it shows that introducing extra delays by implementing burst retransmission stabilizes FAST TCP over OBS. The paper proves that FAST TCP is not stable over barebone OBS. However, it is locally, exponentially, and asymptotically stable over OBS with burst retransmission.

Towards Stable Adversarial Feature Learning for LiDAR based Loop Closure Detection

OpenAIRE

Xu, Lingyun; Yin, Peng; Luo, Haibo; Liu, Yunhui; Han, Jianda

2017-01-01

Stable feature extraction is the key for the Loop closure detection (LCD) task in the simultaneously localization and mapping (SLAM) framework. In our paper, the feature extraction is operated by using a generative adversarial networks (GANs) based unsupervised learning. GANs are powerful generative models, however, GANs based adversarial learning suffers from training instability. We find that the data-code joint distribution in the adversarial learning is a more complex manifold than in the...

Effect of direct reciprocity and network structure on continuing prosperity of social networking services.

Science.gov (United States)

Osaka, Kengo; Toriumi, Fujio; Sugawara, Toshihauru

2017-01-01

Social networking services (SNSs) are widely used as communicative tools for a variety of purposes. SNSs rely on the users' individual activities associated with some cost and effort, and thus it is not known why users voluntarily continue to participate in SNSs. Because the structures of SNSs are similar to that of the public goods (PG) game, some studies have focused on why voluntary activities emerge as an optimal strategy by modifying the PG game. However, their models do not include direct reciprocity between users, even though reciprocity is a key mechanism that evolves and sustains cooperation in human society. We developed an abstract SNS model called the reciprocity rewards and meta-rewards games that include direct reciprocity by extending the existing models. Then, we investigated how direct reciprocity in an SNS facilitates cooperation that corresponds to participation in SNS by posting articles and comments and how the structure of the networks of users exerts an influence on the strategies of users using the reciprocity rewards game. We run reciprocity rewards games on various complex networks and an instance network of Facebook and found that two types of stable cooperation emerged. First, reciprocity slightly improves the rate of cooperation in complete graphs but the improvement is insignificant because of the instability of cooperation. However, this instability can be avoided by making two assumptions: high degree of fun, i.e. articles are read with high probability, and different attitudes to reciprocal and non-reciprocal agents. We then propose the concept of half free riders to explain what strategy sustains cooperation-dominant situations. Second, we indicate that a certain WS network structure affects users' optimal strategy and facilitates stable cooperation without any extra assumptions. We give a detailed analysis of the different characteristics of the two types of cooperation-dominant situations and the effect of the memory of

The influence of network characteristics on costs in pharmaceutical new product development

DEFF Research Database (Denmark)

Buonansegna, Erika; Schultz, Carsten; Stargardt, Tom

2015-01-01

This paper develops a model relating prior experiences, network stability, exclusive partnership, geographical distance, and intermediation in inter-firm R&D networks to new product development (NPD) costs. The developed hypotheses are tested with unique multilevel R&D partnership data from 33...... becomes relevant for non-exclusive partnerships and dispersed networks. NPD costs also increase in more stable networks, reflecting the relevance of structural holes for control and information advantages. This study contributes to the network management literature by understanding the relation between...

A PEG Construction of LDPC Codes Based on the Betweenness Centrality Metric

Directory of Open Access Journals (Sweden)

BHURTAH-SEEWOOSUNGKUR, I.

2016-05-01

Full Text Available Progressive Edge Growth (PEG constructions are usually based on optimizing the distance metric by using various methods. In this work however, the distance metric is replaced by a different one, namely the betweenness centrality metric, which was shown to enhance routing performance in wireless mesh networks. A new type of PEG construction for Low-Density Parity-Check (LDPC codes is introduced based on the betweenness centrality metric borrowed from social networks terminology given that the bipartite graph describing the LDPC is analogous to a network of nodes. The algorithm is very efficient in filling edges on the bipartite graph by adding its connections in an edge-by-edge manner. The smallest graph size the new code could construct surpasses those obtained from a modified PEG algorithm - the RandPEG algorithm. To the best of the authors' knowledge, this paper produces the best regular LDPC column-weight two graphs. In addition, the technique proves to be competitive in terms of error-correcting performance. When compared to MacKay, PEG and other recent modified-PEG codes, the algorithm gives better performance over high SNR due to its particular edge and local graph properties.

Transitions from Trees to Cycles in Adaptive Flow Networks

DEFF Research Database (Denmark)

Martens, Erik Andreas; Klemm, Konstantin

2017-01-01

-world transport networks exhibit both tree-like motifs and cycles. When the network is subject to load fluctuations, the presence of cyclic motifs may help to reduce flow fluctuations and, thus, render supply in the network more robust. While previous studies considered network topology via optimization...... principles, here, we take a dynamical systems approach and study a simple model of a flow network with dynamically adapting weights (conductances). We assume a spatially non-uniform distribution of rapidly fluctuating loads in the sinks and investigate what network configurations are dynamically stable......Transport networks are crucial to the functioning of natural and technological systems. Nature features transport networks that are adaptive over a vast range of parameters, thus providing an impressive level of robustness in supply. Theoretical and experimental studies have found that real...

Transitions from Trees to Cycles in Adaptive Flow Networks

DEFF Research Database (Denmark)

Martens, Erik Andreas; Klemm, Konstantin

2017-01-01

. The network converges to a spatially non-uniform stable configuration composed of both cyclic and tree-like structures. Cyclic structures emerge locally in a transcritical bifurcation as the amplitude of the load fluctuations is increased. The resulting adaptive dynamics thus partitions the network into two......Transport networks are crucial to the functioning of natural and technological systems. Nature features transport networks that are adaptive over a vast range of parameters, thus providing an impressive level of robustness in supply. Theoretical and experimental studies have found that real......-world transport networks exhibit both tree-like motifs and cycles. When the network is subject to load fluctuations, the presence of cyclic motifs may help to reduce flow fluctuations and, thus, render supply in the network more robust. While previous studies considered network topology via optimization...

Structural and robustness properties of smart-city transportation networks

Science.gov (United States)

Zhang, Zhen-Gang; Ding, Zhuo; Fan, Jing-Fang; Meng, Jun; Ding, Yi-Min; Ye, Fang-Fu; Chen, Xiao-Song

2015-09-01

The concept of smart city gives an excellent resolution to construct and develop modern cities, and also demands infrastructure construction. How to build a safe, stable, and highly efficient public transportation system becomes an important topic in the process of city construction. In this work, we study the structural and robustness properties of transportation networks and their sub-networks. We introduce a complementary network model to study the relevance and complementarity between bus network and subway network. Our numerical results show that the mutual supplement of networks can improve the network robustness. This conclusion provides a theoretical basis for the construction of public traffic networks, and it also supports reasonable operation of managing smart cities. Project supported by the Major Projects of the China National Social Science Fund (Grant No. 11 & ZD154).

Bipolar resistive switching behaviors of ITO nanowire networks

Directory of Open Access Journals (Sweden)

Qiang Li

2016-02-01

Full Text Available We have fabricated indium tin oxide (ITO nanowire (NW networks on aluminum electrodes using electron beam evaporation. The Ag/ITO-NW networks/Al capacitor exhibits bipolar resistive switching behavior. The resistive switching characteristics of ITO-NW networks are related to the morphology of NWs. The x-ray photoelectron spectroscopy was used to obtain the chemical nature from the NWs surface, investigating the oxygen vacancy state. A stable switching voltages and a clear memory window were observed in needle-shaped NWs. The ITO-NW networks can be used as a new two-dimensional metal oxide material for the fabrication of high-density memory devices.

Resiliently evolving supply-demand networks

Science.gov (United States)

Rubido, Nicolás; Grebogi, Celso; Baptista, Murilo S.

2014-01-01

The ability to design a transport network such that commodities are brought from suppliers to consumers in a steady, optimal, and stable way is of great importance for distribution systems nowadays. In this work, by using the circuit laws of Kirchhoff and Ohm, we provide the exact capacities of the edges that an optimal supply-demand network should have to operate stably under perturbations, i.e., without overloading. The perturbations we consider are the evolution of the connecting topology, the decentralization of hub sources or sinks, and the intermittence of supplier and consumer characteristics. We analyze these conditions and the impact of our results, both on the current United Kingdom power-grid structure and on numerically generated evolving archetypal network topologies.

Stability and attractive basins of multiple equilibria in delayed two-neuron networks

International Nuclear Information System (INIS)

Huang Yu-Jiao; Zhang Hua-Guang; Wang Zhan-Shan

2012-01-01

Multiple stability for two-dimensional delayed recurrent neural networks with piecewise linear activation functions of 2r (r ≥ 1) corner points is studied. Sufficient conditions are established for checking the existence of (2r + 1) 2 equilibria in delayed recurrent neural networks. Under these conditions, (r + 1) 2 equilibria are locally exponentially stable, and (2r + 1) 2 — (r + 1) 2 — r 2 equilibria are unstable. Attractive basins of stable equilibria are estimated, which are larger than invariant sets derived by decomposing state space. One example is provided to illustrate the effectiveness of our results. (general)

Cascaded multiplexed optical link on a telecommunication network for frequency dissemination.

Science.gov (United States)

Lopez, Olivier; Haboucha, Adil; Kéfélian, Fabien; Jiang, Haifeng; Chanteau, Bruno; Roncin, Vincent; Chardonnet, Christian; Amy-Klein, Anne; Santarelli, Giorgio

2010-08-02

We demonstrate a cascaded optical link for ultrastable frequency dissemination comprised of two compensated links of 150 km and a repeater station. Each link includes 114 km of Internet fiber simultaneously carrying data traffic through a dense wavelength division multiplexing technology, and passes through two routing centers of the telecommunication network. The optical reference signal is inserted in and extracted from the communication network using bidirectional optical add-drop multiplexers. The repeater station operates autonomously ensuring noise compensation on the two links and the ultra-stable signal optical regeneration. The compensated link shows a fractional frequency instability of 3 x 10(-15) at one second measurement time and 5 x 10(-20) at 20 hours. This work paves the way to a wide dissemination of ultra-stable optical clock signals between distant laboratories via the Internet network.

A Method to Design Synthetic Cell-Cycle Networks

International Nuclear Information System (INIS)

Ke-Ke, Miao

2009-01-01

The interactions among proteins, DNA and RNA in an organism form elaborate cell-cycle networks which govern cell growth and proliferation. Understanding the common structure of cell-cycle networks will be of great benefit to science research. Here, inspired by the importance of the cell-cycle regulatory network of yeast which has been studied intensively, we focus on small networks with 11 nodes, equivalent to that of the cell-cycle regulatory network used by Li et al. [Proc. Natl. Acad. Sci. USA 101(2004)4781] Using a Boolean model, we study the correlation between structure and function, and a possible common structure. It is found that cascade-like networks with a great number of interactions between nodes are stable. Based on these findings, we are able to construct synthetic networks that have the same functions as the cell-cycle regulatory network. (condensed matter: structure, mechanical and thermal properties)

Socially Aware Heterogeneous Wireless Networks.

Science.gov (United States)

Kosmides, Pavlos; Adamopoulou, Evgenia; Demestichas, Konstantinos; Theologou, Michael; Anagnostou, Miltiades; Rouskas, Angelos

2015-06-11

The development of smart cities has been the epicentre of many researchers' efforts during the past decade. One of the key requirements for smart city networks is mobility and this is the reason stable, reliable and high-quality wireless communications are needed in order to connect people and devices. Most research efforts so far, have used different kinds of wireless and sensor networks, making interoperability rather difficult to accomplish in smart cities. One common solution proposed in the recent literature is the use of software defined networks (SDNs), in order to enhance interoperability among the various heterogeneous wireless networks. In addition, SDNs can take advantage of the data retrieved from available sensors and use them as part of the intelligent decision making process contacted during the resource allocation procedure. In this paper, we propose an architecture combining heterogeneous wireless networks with social networks using SDNs. Specifically, we exploit the information retrieved from location based social networks regarding users' locations and we attempt to predict areas that will be crowded by using specially-designed machine learning techniques. By recognizing possible crowded areas, we can provide mobile operators with recommendations about areas requiring datacell activation or deactivation.

Beyond the network of plants volatile organic compounds

OpenAIRE

Vivaldo, Gianna; Masi, Elisa; Taiti, Cosimo; Caldarelli, Guido; Mancuso, Stefano

2017-01-01

Plants emission of volatile organic compounds (VOCs) is involved in a wide class of ecological functions, as VOCs play a crucial role in plants interactions with biotic and abiotic factors. Accordingly, they vary widely across species and underpin differences in ecological strategy. In this paper, VOCs spontaneously emitted by 109 plant species (belonging to 56 different families) have been qualitatively and quantitatively analysed in order to classify plants species. By using bipartite netwo...

Inter-subject FDG PET Brain Networks Exhibit Multi-scale Community Structure with Different Normalization Techniques.

Science.gov (United States)

Sperry, Megan M; Kartha, Sonia; Granquist, Eric J; Winkelstein, Beth A

2018-07-01

Inter-subject networks are used to model correlations between brain regions and are particularly useful for metabolic imaging techniques, like 18F-2-deoxy-2-(18F)fluoro-D-glucose (FDG) positron emission tomography (PET). Since FDG PET typically produces a single image, correlations cannot be calculated over time. Little focus has been placed on the basic properties of inter-subject networks and if they are affected by group size and image normalization. FDG PET images were acquired from rats (n = 18), normalized by whole brain, visual cortex, or cerebellar FDG uptake, and used to construct correlation matrices. Group size effects on network stability were investigated by systematically adding rats and evaluating local network connectivity (node strength and clustering coefficient). Modularity and community structure were also evaluated in the differently normalized networks to assess meso-scale network relationships. Local network properties are stable regardless of normalization region for groups of at least 10. Whole brain-normalized networks are more modular than visual cortex- or cerebellum-normalized network (p network resolutions where modularity differs most between brain and randomized networks. Hierarchical analysis reveals consistent modules at different scales and clustering of spatially-proximate brain regions. Findings suggest inter-subject FDG PET networks are stable for reasonable group sizes and exhibit multi-scale modularity.

A full quantum network scheme

International Nuclear Information System (INIS)

Ma Hai-Qiang; Wei Ke-Jin; Yang Jian-Hui; Li Rui-Xue; Zhu Wu

2014-01-01

We present a full quantum network scheme using a modified BB84 protocol. Unlike other quantum network schemes, it allows quantum keys to be distributed between two arbitrary users with the help of an intermediary detecting user. Moreover, it has good expansibility and prevents all potential attacks using loopholes in a detector, so it is more practical to apply. Because the fiber birefringence effects are automatically compensated, the scheme is distinctly stable in principle and in experiment. The simple components for every user make our scheme easier for many applications. The experimental results demonstrate the stability and feasibility of this scheme. (general)

Functional hypergraph uncovers novel covariant structures over neurodevelopment.

Science.gov (United States)

Gu, Shi; Yang, Muzhi; Medaglia, John D; Gur, Ruben C; Gur, Raquel E; Satterthwaite, Theodore D; Bassett, Danielle S

2017-08-01

Brain development during adolescence is marked by substantial changes in brain structure and function, leading to a stable network topology in adulthood. However, most prior work has examined the data through the lens of brain areas connected to one another in large-scale functional networks. Here, we apply a recently developed hypergraph approach that treats network connections (edges) rather than brain regions as the unit of interest, allowing us to describe functional network topology from a fundamentally different perspective. Capitalizing on a sample of 780 youth imaged as part of the Philadelphia Neurodevelopmental Cohort, this hypergraph representation of resting-state functional MRI data reveals three distinct classes of subnetworks (hyperedges): clusters, bridges, and stars, which respectively represent homogeneously connected, bipartite, and focal architectures. Cluster hyperedges show a strong resemblance to previously-described functional modules of the brain including somatomotor, visual, default mode, and salience systems. In contrast, star hyperedges represent highly localized subnetworks centered on a small set of regions, and are distributed across the entire cortex. Finally, bridge hyperedges link clusters and stars in a core-periphery organization. Notably, developmental changes within hyperedges are ordered in a similar core-periphery fashion, with the greatest developmental effects occurring in networked hyperedges within the functional core. Taken together, these results reveal a novel decomposition of the network organization of human brain, and further provide a new perspective on the role of local structures that emerge across neurodevelopment. Hum Brain Mapp 38:3823-3835, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

One-dimensional stable distributions

CERN Document Server

Zolotarev, V M

1986-01-01

This is the first book specifically devoted to a systematic exposition of the essential facts known about the properties of stable distributions. In addition to its main focus on the analytic properties of stable laws, the book also includes examples of the occurrence of stable distributions in applied problems and a chapter on the problem of statistical estimation of the parameters determining stable laws. A valuable feature of the book is the author's use of several formally different ways of expressing characteristic functions corresponding to these laws.

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

CERN Document Server

Liu, Jinkun

2013-01-01

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

Bi-stable optical actuator

Science.gov (United States)

Holdener, Fred R.; Boyd, Robert D.

2000-01-01

The present invention is a bi-stable optical actuator device that is depowered in both stable positions. A bearing is used to transfer motion and smoothly transition from one state to another. The optical actuator device may be maintained in a stable position either by gravity or a restraining device.

Sparse dictionary learning of resting state fMRI networks.

Science.gov (United States)

Eavani, Harini; Filipovych, Roman; Davatzikos, Christos; Satterthwaite, Theodore D; Gur, Raquel E; Gur, Ruben C

2012-07-02

Research in resting state fMRI (rsfMRI) has revealed the presence of stable, anti-correlated functional subnetworks in the brain. Task-positive networks are active during a cognitive process and are anti-correlated with task-negative networks, which are active during rest. In this paper, based on the assumption that the structure of the resting state functional brain connectivity is sparse, we utilize sparse dictionary modeling to identify distinct functional sub-networks. We propose two ways of formulating the sparse functional network learning problem that characterize the underlying functional connectivity from different perspectives. Our results show that the whole-brain functional connectivity can be concisely represented with highly modular, overlapping task-positive/negative pairs of sub-networks.

Application of Tempered-Stable Time Fractional-Derivative Model to Upscale Subdiffusion for Pollutant Transport in Field-Scale Discrete Fracture Networks

Directory of Open Access Journals (Sweden)

Bingqing Lu

2018-01-01

Full Text Available Fractional calculus provides efficient physical models to quantify non-Fickian dynamics broadly observed within the Earth system. The potential advantages of using fractional partial differential equations (fPDEs for real-world problems are often limited by the current lack of understanding of how earth system properties influence observed non-Fickian dynamics. This study explores non-Fickian dynamics for pollutant transport in field-scale discrete fracture networks (DFNs, by investigating how fracture and rock matrix properties influence the leading and tailing edges of pollutant breakthrough curves (BTCs. Fractured reservoirs exhibit erratic internal structures and multi-scale heterogeneity, resulting in complex non-Fickian dynamics. A Monte Carlo approach is used to simulate pollutant transport through DFNs with a systematic variation of system properties, and the resultant non-Fickian transport is upscaled using a tempered-stable fractional in time advection–dispersion equation. Numerical results serve as a basis for determining both qualitative and quantitative relationships between BTC characteristics and model parameters, in addition to the impacts of fracture density, orientation, and rock matrix permeability on non-Fickian dynamics. The observed impacts of medium heterogeneity on tracer transport at late times tend to enhance the applicability of fPDEs that may be parameterized using measurable fracture–matrix characteristics.

Joint accurate time and stable frequency distribution infrastructure sharing fiber footprint with research network

Czech Academy of Sciences Publication Activity Database

Vojtěch, J.; Šlapák, M.; Škoda, P.; Radil, J.; Havliš, O.; Altmann, M.; Münster, P.; Velč, R.; Kundrát, J.; Altmannová, L.; Vohnout, R.; Horváth, T.; Hůla, M.; Smotlacha, V.; Čížek, Martin; Pravdová, Lenka; Řeřucha, Šimon; Hrabina, Jan; Číp, Ondřej

2017-01-01

Roč. 56, č. 2 (2017), s. 1-7, č. článku 027101. ISSN 0091-3286 R&D Projects: GA ČR GB14-36681G Institutional support: RVO:68081731 Keywords : accurate time * stable frequency * wavelength division multiplexing * bidirectional reciprocal path * Sagnac effect Subject RIV: BH - Optics, Masers, Lasers OBOR OECD: Optics (including laser optics and quantum optics) Impact factor: 1.082, year: 2016

Network Communication for Low Level RF Control

International Nuclear Information System (INIS)

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

2009-01-01

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

Remarks on stable and quasi-stable k-strings at large N

International Nuclear Information System (INIS)

Armoni, A.; Shifman, M.

2003-01-01

We discuss k-strings in the large-N Yang-Mills theory and its supersymmetric extension. Whereas the tension of the bona fide (stable) QCD string is expected to depend only on the N-ality of the representation, tensions that depend on specific representation R are often reported in the lattice literature. In particular, adjoint strings are discussed and found in certain simulations. We clarify this issue by systematically exploiting the notion of the quasi-stable strings which becomes well-defined at large N. The quasi-stable strings with representation-dependent tensions decay, but the decay rate (per unit length per unit time) is suppressed as Λ 2 F(N) where F(N) falls off as a function of N. It can be determined on the case-by-case basis. The quasi-stable strings eventually decay into stable strings whose tension indeed depends only on the N-ality. We also briefly review large-N arguments showing why the Casimir formula for the string tension cannot be correct, and present additional arguments in favor of the sine formula. Finally, we comment on the relevance of our estimates to Euclidean lattice measurements

Evolutionary Stable Strategy

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education; Volume 21; Issue 9. Evolutionary Stable Strategy: Application of Nash Equilibrium in Biology. General Article Volume 21 Issue 9 September 2016 pp 803- ... Keywords. Evolutionary game theory, evolutionary stable state, conflict, cooperation, biological games.

Sparse and shrunken estimates of MRI networks in the brain and their influence on network properties

DEFF Research Database (Denmark)

Romero-Garcia, Rafael; Clemmensen, Line Katrine Harder

2014-01-01

approaches showed more stable results with a relative low variance at the expense of a little bias. Interestingly, topological properties as local and global efficiency estimated in networks constructed from traditional non-regularized correlations also showed higher variability when compared to those from...... regularized networks. Our findings suggest that a population-based connectivity study can achieve a more robust description of cortical topology through regularization of the correlation estimates. Four regularization methods were examined: Two with shrinkage (Ridge and Schäfer’s shrinkage), one with sparsity...... (Lasso) and one with both shrinkage and sparsity (Elastic net). Furthermore, the different regularizations resulted in different correlation estimates as well as network properties. The shrunken estimates resulted in lower variance of the estimates than the sparse estimates....

Evolution of gossip-based indirect reciprocity on a bipartite network

Science.gov (United States)

Giardini, Francesca; Vilone, Daniele

2016-11-01

Cooperation can be supported by indirect reciprocity via reputation. Thanks to gossip, reputations are built and circulated and humans can identify defectors and ostracise them. However, the evolutionary stability of gossip is allegedly undermined by the fact that it is more error-prone that direct observation, whereas ostracism could be ineffective if the partner selection mechanism is not robust. The aim of this work is to investigate the conditions under which the combination of gossip and ostracism might support cooperation in groups of different sizes. We are also interested in exploring the extent to which errors in transmission might undermine the reliability of gossip as a mechanism for identifying defectors. Our results show that a large quantity of gossip is necessary to support cooperation, and that group structure can mitigate the effects of errors in transmission.

Evolution of gossip-based indirect reciprocity on a bipartite network.

Science.gov (United States)

Giardini, Francesca; Vilone, Daniele

2016-11-25

Cooperation can be supported by indirect reciprocity via reputation. Thanks to gossip, reputations are built and circulated and humans can identify defectors and ostracise them. However, the evolutionary stability of gossip is allegedly undermined by the fact that it is more error-prone that direct observation, whereas ostracism could be ineffective if the partner selection mechanism is not robust. The aim of this work is to investigate the conditions under which the combination of gossip and ostracism might support cooperation in groups of different sizes. We are also interested in exploring the extent to which errors in transmission might undermine the reliability of gossip as a mechanism for identifying defectors. Our results show that a large quantity of gossip is necessary to support cooperation, and that group structure can mitigate the effects of errors in transmission.

Organized polysaccharide fibers as stable drug carriers

Science.gov (United States)

Janaswamy, Srinivas; Gill, Kristin L.; Campanella, Osvaldo H.; Pinal, Rodolfo

2013-01-01

Many challenges arise during the development of new drug carrier systems, and paramount among them are safety, solubility and controlled release requirements. Although synthetic polymers are effective, the possibility of side effects imposes restrictions on their acceptable use and dose limits. Thus, a new drug carrier system that is safe to handle and free from side effects is very much in need and food grade polysaccharides stand tall as worthy alternatives. Herein, we demonstrate for the first time the feasibility of sodium iota-carrageenan fibers and their distinctive water pockets to embed and release a wide variety of drug molecules. Structural analysis has revealed the existence of crystalline network in the fibers even after encapsulating the drug molecules, and iota-carrageenan maintains its characteristic and reproducible double helical structure suggesting that the composites thus produced are reminiscent of cocrystals. The melting properties of iota-carrageenan:drug complexes are distinctly different from those of either drug or iota-carrageenan fiber. The encapsulated drugs are released in a sustained manner from the fiber matrix. Overall, our research provides an elegant opportunity for developing effective drug carriers with stable network toward enhancing and/or controlling bioavailability and extending shelf-life of drug molecules using GRAS excipients, food polysaccharides, that are inexpensive and non–toxic. PMID:23544530

The geospatial characteristics of a social movement communication network.

Science.gov (United States)

Conover, Michael D; Davis, Clayton; Ferrara, Emilio; McKelvey, Karissa; Menczer, Filippo; Flammini, Alessandro

2013-01-01

Social movements rely in large measure on networked communication technologies to organize and disseminate information relating to the movements' objectives. In this work we seek to understand how the goals and needs of a protest movement are reflected in the geographic patterns of its communication network, and how these patterns differ from those of stable political communication. To this end, we examine an online communication network reconstructed from over 600,000 tweets from a thirty-six week period covering the birth and maturation of the American anticapitalist movement, Occupy Wall Street. We find that, compared to a network of stable domestic political communication, the Occupy Wall Street network exhibits higher levels of locality and a hub and spoke structure, in which the majority of non-local attention is allocated to high-profile locations such as New York, California, and Washington D.C. Moreover, we observe that information flows across state boundaries are more likely to contain framing language and references to the media, while communication among individuals in the same state is more likely to reference protest action and specific places and times. Tying these results to social movement theory, we propose that these features reflect the movement's efforts to mobilize resources at the local level and to develop narrative frames that reinforce collective purpose at the national level.

Fear of predation drives stable and differentiated social relationships in guppies.

Science.gov (United States)

Heathcote, Robert J P; Darden, Safi K; Franks, Daniel W; Ramnarine, Indar W; Croft, Darren P

2017-02-02

Social relationships can have important consequences for fitness in animals. Whilst numerous studies have shown that individuals often join larger groups in response to perceived predation risk (i.e. fear of predation), the importance of predation risk in driving the formation and stability of social relationships within groups has been relatively ignored. We experimentally tested how predation threat influenced fine-scale social network structure using Trinidadian guppies (Poecilia reticulata). When perceived predation risk was high, individuals developed stable and more differentiated social ties compared to when perceived risk was low. Intriguingly, social differentiation coincided with shoals being somewhat smaller under high-perceived risk, suggesting a possible conflict between forming stable social relationships and larger social groups. Individuals most at risk of predation (large and bold individuals) showed the most exaggerated responses in several social measures. Taken together, we provide the first experimental evidence that proximate risk of predation can increase the intensity of social relationships and fine-scale social structure in animal populations.

NMR-based stable isotope resolved metabolomics in systems biochemistry

International Nuclear Information System (INIS)

Fan, Teresa W-M.; Lane, Andrew N.

2011-01-01

An important goal of metabolomics is to characterize the changes in metabolic networks in cells or various tissues of an organism in response to external perturbations or pathologies. The profiling of metabolites and their steady state concentrations does not directly provide information regarding the architecture and fluxes through metabolic networks. This requires tracer approaches. NMR is especially powerful as it can be used not only to identify and quantify metabolites in an unfractionated mixture such as biofluids or crude cell/tissue extracts, but also determine the positional isotopomer distributions of metabolites derived from a precursor enriched in stable isotopes such as 13 C and 15 N via metabolic transformations. In this article we demonstrate the application of a variety of 2-D NMR editing experiments to define the positional isotopomers of compounds present in polar and non-polar extracts of human lung cancer cells grown in either [U– 13 C]-glucose or [U– 13 C, 15 N]-glutamine as source tracers. The information provided by such experiments enabled unambiguous reconstruction of metabolic pathways, which is the foundation for further metabolic flux modeling.

Global stability of an SIR model with differential infectivity on complex networks

Science.gov (United States)

Yuan, Xinpeng; Wang, Fang; Xue, Yakui; Liu, Maoxing

2018-06-01

In this paper, an SIR model with birth and death on complex networks is analyzed, where infected individuals are divided into m groups according to their infection and contact between human is treated as a scale-free social network. We obtain the basic reproduction number R0 as well as the effects of various immunization schemes. The results indicate that the disease-free equilibrium is locally and globally asymptotically stable in some conditions, otherwise disease-free equilibrium is unstable and exists an unique endemic equilibrium that is globally asymptotically stable. Our theoretical results are confirmed by numerical simulations and a promising way for infectious diseases control is suggested.

Folding and unfolding phylogenetic trees and networks.

Science.gov (United States)

Huber, Katharina T; Moulton, Vincent; Steel, Mike; Wu, Taoyang

2016-12-01

Phylogenetic networks are rooted, labelled directed acyclic graphswhich are commonly used to represent reticulate evolution. There is a close relationship between phylogenetic networks and multi-labelled trees (MUL-trees). Indeed, any phylogenetic network N can be "unfolded" to obtain a MUL-tree U(N) and, conversely, a MUL-tree T can in certain circumstances be "folded" to obtain aphylogenetic network F(T) that exhibits T. In this paper, we study properties of the operations U and F in more detail. In particular, we introduce the class of stable networks, phylogenetic networks N for which F(U(N)) is isomorphic to N, characterise such networks, and show that they are related to the well-known class of tree-sibling networks. We also explore how the concept of displaying a tree in a network N can be related to displaying the tree in the MUL-tree U(N). To do this, we develop aphylogenetic analogue of graph fibrations. This allows us to view U(N) as the analogue of the universal cover of a digraph, and to establish a close connection between displaying trees in U(N) and reconciling phylogenetic trees with networks.

Recurrent neural network for non-smooth convex optimization problems with application to the identification of genetic regulatory networks.

Science.gov (United States)

Cheng, Long; Hou, Zeng-Guang; Lin, Yingzi; Tan, Min; Zhang, Wenjun Chris; Wu, Fang-Xiang

2011-05-01

A recurrent neural network is proposed for solving the non-smooth convex optimization problem with the convex inequality and linear equality constraints. Since the objective function and inequality constraints may not be smooth, the Clarke's generalized gradients of the objective function and inequality constraints are employed to describe the dynamics of the proposed neural network. It is proved that the equilibrium point set of the proposed neural network is equivalent to the optimal solution of the original optimization problem by using the Lagrangian saddle-point theorem. Under weak conditions, the proposed neural network is proved to be stable, and the state of the neural network is convergent to one of its equilibrium points. Compared with the existing neural network models for non-smooth optimization problems, the proposed neural network can deal with a larger class of constraints and is not based on the penalty method. Finally, the proposed neural network is used to solve the identification problem of genetic regulatory networks, which can be transformed into a non-smooth convex optimization problem. The simulation results show the satisfactory identification accuracy, which demonstrates the effectiveness and efficiency of the proposed approach.

Network spandrels reflect ecological assembly.

Science.gov (United States)

Maynard, Daniel S; Serván, Carlos A; Allesina, Stefano

2018-03-01

Ecological networks that exhibit stable dynamics should theoretically persist longer than those that fluctuate wildly. Thus, network structures which are over-represented in natural systems are often hypothesised to be either a cause or consequence of ecological stability. Rarely considered, however, is that these network structures can also be by-products of the processes that determine how new species attempt to join the community. Using a simulation approach in tandem with key results from random matrix theory, we illustrate how historical assembly mechanisms alter the structure of ecological networks. We demonstrate that different community assembly scenarios can lead to the emergence of structures that are often interpreted as evidence of 'selection for stability'. However, by controlling for the underlying selection pressures, we show that these assembly artefacts-or spandrels-are completely unrelated to stability or selection, and are instead by-products of how new species are introduced into the system. We propose that these network-assembly spandrels are critically overlooked aspects of network theory and stability analysis, and we illustrate how a failure to adequately account for historical assembly can lead to incorrect inference about the causes and consequences of ecological stability. © 2018 John Wiley & Sons Ltd/CNRS.

General asymmetric neutral networks and structure design by genetic algorithms: A learning rule for temporal patterns

Energy Technology Data Exchange (ETDEWEB)

Bornholdt, S. [Heidelberg Univ., (Germany). Inst., fuer Theoretische Physik; Graudenz, D. [Lawrence Berkeley Lab., CA (United States)

1993-07-01

A learning algorithm based on genetic algorithms for asymmetric neural networks with an arbitrary structure is presented. It is suited for the learning of temporal patterns and leads to stable neural networks with feedback.

General asymmetric neutral networks and structure design by genetic algorithms: A learning rule for temporal patterns

International Nuclear Information System (INIS)

Bornholdt, S.

1993-07-01

A learning algorithm based on genetic algorithms for asymmetric neural networks with an arbitrary structure is presented. It is suited for the learning of temporal patterns and leads to stable neural networks with feedback

Evolution properties of the community members for dynamic networks

Science.gov (United States)

Yang, Kai; Guo, Qiang; Li, Sheng-Nan; Han, Jing-Ti; Liu, Jian-Guo

2017-03-01

The collective behaviors of community members for dynamic social networks are significant for understanding evolution features of communities. In this Letter, we empirically investigate the evolution properties of the new community members for dynamic networks. Firstly, we separate data sets into different slices, and analyze the statistical properties of new members as well as communities they joined in for these data sets. Then we introduce a parameter φ to describe community evolution between different slices and investigate the dynamic community properties of the new community members. The empirical analyses for the Facebook, APS, Enron and Wiki data sets indicate that both the number of new members and joint communities increase, the ratio declines rapidly and then becomes stable over time, and most of the new members will join in the small size communities that is s ≤ 10. Furthermore, the proportion of new members in existed communities decreases firstly and then becomes stable and relatively small for these data sets. Our work may be helpful for deeply understanding the evolution properties of community members for social networks.

Spiral Wave in Small-World Networks of Hodgkin-Huxley Neurons

International Nuclear Information System (INIS)

Ma Jun; Zhang Cairong; Yang Lijian; Wu Ying

2010-01-01

The effect of small-world connection and noise on the formation and transition of spiral wave in the networks of Hodgkin-Huxley neurons are investigated in detail. Some interesting results are found in our numerical studies. i) The quiescent neurons are activated to propagate electric signal to others by generating and developing spiral wave from spiral seed in small area. ii) A statistical factor is defined to describe the collective properties and phase transition induced by the topology of networks and noise. iii) Stable rotating spiral wave can be generated and keeps robust when the rewiring probability is below certain threshold, otherwise, spiral wave can not be developed from the spiral seed and spiral wave breakup occurs for a stable rotating spiral wave. iv) Gaussian white noise is introduced on the membrane of neurons to study the noise-induced phase transition on spiral wave in small-world networks of neurons. It is confirmed that Gaussian white noise plays active role in supporting and developing spiral wave in the networks of neurons, and appearance of smaller factor of synchronization indicates high possibility to induce spiral wave. (interdisciplinary physics and related areas of science and technology)

Tracking ENSO with tropical trees: Progress in stable isotope dendroclimatology

Science.gov (United States)

Evans, M. N.; Poussart, P. F.; Saleska, S. R.; Schrag, D. P.

2002-12-01

The terrestrial tropics remain an important gap in the growing proxy network used to characterize past ENSO behavior. Here we describe a strategy for development of proxy estimates of paleo-ENSO, via proxy rainfall estimates derived from stable isotope (δ18O) measurements made on tropical trees. The approach applies a new model of oxygen isotopic composition of alpha-cellulose (Roden et al., 2000), a rapid method for cellulose extraction from raw wood (Brendel et al., 2000), and continuous flow isotope ratio mass spectrometry (Brand, 1996) to develop proxy chronological, rainfall and growth rate estimates from tropical trees, even those lacking annual rings. The promise and pitfalls of the approach are illustrated in pilot datasets from the US, Costa Rica, Brazil, and Peru, which show isotopic cycles of 4-6 per mil, and interannual anomalies of up to 8 per mil. Together with the mature ENSO proxies (corals, extratropical tree-rings, varved sediments, and ice cores), replicated and well-dated stable isotope chronologies from tropical trees may eventually improve our understanding of ENSO history over the past several hundred years.

Epoxy-Based Organogels for Thermally Reversible Light Scattering Films and Form-Stable Phase Change Materials.

Science.gov (United States)

Puig, Julieta; Dell' Erba, Ignacio E; Schroeder, Walter F; Hoppe, Cristina E; Williams, Roberto J J

2017-03-29

Alkyl chains of β-hydroxyesters synthesized by the capping of terminal epoxy groups of diglycidylether of bisphenol A (DGEBA) with palmitic (C16), stearic (C18), or behenic (C22) fatty acids self-assemble forming a crystalline phase. Above a particular concentration solutions of these esters in a variety of solvents led to supramolecular (physical) gels below the crystallization temperature of alkyl chains. A form-stable phase change material (FS-PCM) was obtained by blending the ester derived from behenic acid with eicosane. A blend containing 20 wt % ester was stable as a gel up to 53 °C and exhibited a heat storage capacity of 161 J/g, absorbed during the melting of eicosane at 37 °C. Thermally reversible light scattering (TRLS) films were obtained by visible-light photopolymerization of poly(ethylene glycol) dimethacrylate-ester blends (50 wt %) in the gel state at room temperature. The reaction was very fast and not inhibited by oxygen. TRLS films consisted of a cross-linked methacrylic network interpenetrated by the supramolecular network formed by the esters. Above the melting temperature of crystallites formed by alkyl chains, the film was transparent due to the matching between refractive indices of the methacrylic network and the amorphous ester. Below the crystallization temperature, the film was opaque because of light dispersion produced by the organic crystallites uniformly dispersed in the material. Of high significance for application was the fact that the contrast ratio did not depend on heating and cooling rates.

Rad-Tolerant, Thermally Stable, High-Speed Fiber-Optic Network for Harsh Environments

Science.gov (United States)

Leftwich, Matt; Hull, Tony; Leary, Michael; Leftwich, Marcus

2013-01-01

Future NASA destinations will be challenging to get to, have extreme environmental conditions, and may present difficulty in retrieving a spacecraft or its data. Space Photonics is developing a radiation-tolerant (rad-tolerant), high-speed, multi-channel fiber-optic transceiver, associated reconfigurable intelligent node communications architecture, and supporting hardware for intravehicular and ground-based optical networking applications. Data rates approaching 3.2 Gbps per channel will be achieved.

Investigating Einstein-Podolsky-Rosen steering of continuous-variable bipartite states by non-Gaussian pseudospin measurements

Science.gov (United States)

Xiang, Yu; Xu, Buqing; Mišta, Ladislav; Tufarelli, Tommaso; He, Qiongyi; Adesso, Gerardo

2017-10-01

Einstein-Podolsky-Rosen (EPR) steering is an asymmetric form of correlations which is intermediate between quantum entanglement and Bell nonlocality, and can be exploited as a resource for quantum communication with one untrusted party. In particular, steering of continuous-variable Gaussian states has been extensively studied theoretically and experimentally, as a fundamental manifestation of the EPR paradox. While most of these studies focused on quadrature measurements for steering detection, two recent works revealed that there exist Gaussian states which are only steerable by suitable non-Gaussian measurements. In this paper we perform a systematic investigation of EPR steering of bipartite Gaussian states by pseudospin measurements, complementing and extending previous findings. We first derive the density-matrix elements of two-mode squeezed thermal Gaussian states in the Fock basis, which may be of independent interest. We then use such a representation to investigate steering of these states as detected by a simple nonlinear criterion, based on second moments of the correlation matrix constructed from pseudospin operators. This analysis reveals previously unexplored regimes where non-Gaussian measurements are shown to be more effective than Gaussian ones to witness steering of Gaussian states in the presence of local noise. We further consider an alternative set of pseudospin observables, whose expectation value can be expressed more compactly in terms of Wigner functions for all two-mode Gaussian states. However, according to the adopted criterion, these observables are found to be always less sensitive than conventional Gaussian observables for steering detection. Finally, we investigate continuous-variable Werner states, which are non-Gaussian mixtures of Gaussian states, and find that pseudospin measurements are always more effective than Gaussian ones to reveal their steerability. Our results provide useful insights on the role of non

Information filtering in sparse online systems: recommendation via semi-local diffusion.

Science.gov (United States)

Zeng, Wei; Zeng, An; Shang, Ming-Sheng; Zhang, Yi-Cheng

2013-01-01

With the rapid growth of the Internet and overwhelming amount of information and choices that people are confronted with, recommender systems have been developed to effectively support users' decision-making process in the online systems. However, many recommendation algorithms suffer from the data sparsity problem, i.e. the user-object bipartite networks are so sparse that algorithms cannot accurately recommend objects for users. This data sparsity problem makes many well-known recommendation algorithms perform poorly. To solve the problem, we propose a recommendation algorithm based on the semi-local diffusion process on the user-object bipartite network. The simulation results on two sparse datasets, Amazon and Bookcross, show that our method significantly outperforms the state-of-the-art methods especially for those small-degree users. Two personalized semi-local diffusion methods are proposed which further improve the recommendation accuracy. Finally, our work indicates that sparse online systems are essentially different from the dense online systems, so it is necessary to reexamine former algorithms and conclusions based on dense data in sparse systems.

Neural network-based model reference adaptive control system.

Science.gov (United States)

Patino, H D; Liu, D

2000-01-01

In this paper, an approach to model reference adaptive control based on neural networks is proposed and analyzed for a class of first-order continuous-time nonlinear dynamical systems. The controller structure can employ either a radial basis function network or a feedforward neural network to compensate adaptively the nonlinearities in the plant. A stable controller-parameter adjustment mechanism, which is determined using the Lyapunov theory, is constructed using a sigma-modification-type updating law. The evaluation of control error in terms of the neural network learning error is performed. That is, the control error converges asymptotically to a neighborhood of zero, whose size is evaluated and depends on the approximation error of the neural network. In the design and analysis of neural network-based control systems, it is important to take into account the neural network learning error and its influence on the control error of the plant. Simulation results showing the feasibility and performance of the proposed approach are given.

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

Directory of Open Access Journals (Sweden)

Muhammad Al Badri

2017-11-01

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

A Nuclear Ribosomal DNA Phylogeny of Acer Inferred with Maximum Likelihood, Splits Graphs, and Motif Analysis of 606 Sequences

Directory of Open Access Journals (Sweden)

Guido W. Grimm

2006-01-01

Full Text Available The multi-copy internal transcribed spacer (ITS region of nuclear ribosomal DNA is widely used to infer phylogenetic relationships among closely related taxa. Here we use maximum likelihood (ML and splits graph analyses to extract phylogenetic information from ~ 600 mostly cloned ITS sequences, representing 81 species and subspecies of Acer, and both species of its sister Dipteronia. Additional analyses compared sequence motifs in Acer and several hundred Anacardiaceae, Burseraceae, Meliaceae, Rutaceae, and Sapindaceae ITS sequences in GenBank. We also assessed the effects of using smaller data sets of consensus sequences with ambiguity coding (accounting for within-species variation instead of the full (partly redundant original sequences. Neighbor-nets and bipartition networks were used to visualize conflict among character state patterns. Species clusters observed in the trees and networks largely agree with morphology-based classifications; of de Jong’s (1994 16 sections, nine are supported in neighbor-net and bipartition networks, and ten by sequence motifs and the ML tree; of his 19 series, 14 are supported in networks, motifs, and the ML tree. Most nodes had higher bootstrap support with matrices of 105 or 40 consensus sequences than with the original matrix. Within-taxon ITS divergence did not differ between diploid and polyploid Acer, and there was little evidence of differentiated parental ITS haplotypes, suggesting that concerted evolution in Acer acts rapidly.

A Nuclear Ribosomal DNA Phylogeny of Acer Inferred with Maximum Likelihood, Splits Graphs, and Motif Analysis of 606 Sequences

Science.gov (United States)

Grimm, Guido W.; Renner, Susanne S.; Stamatakis, Alexandros; Hemleben, Vera

2007-01-01

The multi-copy internal transcribed spacer (ITS) region of nuclear ribosomal DNA is widely used to infer phylogenetic relationships among closely related taxa. Here we use maximum likelihood (ML) and splits graph analyses to extract phylogenetic information from ~ 600 mostly cloned ITS sequences, representing 81 species and subspecies of Acer, and both species of its sister Dipteronia. Additional analyses compared sequence motifs in Acer and several hundred Anacardiaceae, Burseraceae, Meliaceae, Rutaceae, and Sapindaceae ITS sequences in GenBank. We also assessed the effects of using smaller data sets of consensus sequences with ambiguity coding (accounting for within-species variation) instead of the full (partly redundant) original sequences. Neighbor-nets and bipartition networks were used to visualize conflict among character state patterns. Species clusters observed in the trees and networks largely agree with morphology-based classifications; of de Jong’s (1994) 16 sections, nine are supported in neighbor-net and bipartition networks, and ten by sequence motifs and the ML tree; of his 19 series, 14 are supported in networks, motifs, and the ML tree. Most nodes had higher bootstrap support with matrices of 105 or 40 consensus sequences than with the original matrix. Within-taxon ITS divergence did not differ between diploid and polyploid Acer, and there was little evidence of differentiated parental ITS haplotypes, suggesting that concerted evolution in Acer acts rapidly. PMID:19455198

Structure and Evolution of the Foreign Exchange Networks

Science.gov (United States)

Kwapień, J.; Gworek, S.; Drożdż, S.

2009-01-01

We investigate topology and temporal evolution of the foreign currency exchange market viewed from a weighted network perspective. Based on exchange rates for a set of 46 currencies (including precious metals), we construct different representations of the FX network depending on a choice of the base currency. Our results show that the network structure is not stable in time, but there are main clusters of currencies, which persist for a long period of time despite the fact that their size and content are variable. We find a long-term trend in the network's evolution which affects the USD and EUR nodes. In all the network representations, the USD node gradually loses its centrality, while, on contrary, the EUR node has become slightly more central than it used to be in its early years. Despite this directional trend, the overall evolution of the network is noisy.

Network structure exploration via Bayesian nonparametric models

International Nuclear Information System (INIS)

Chen, Y; Wang, X L; Xiang, X; Tang, B Z; Bu, J Z

2015-01-01

Complex networks provide a powerful mathematical representation of complex systems in nature and society. To understand complex networks, it is crucial to explore their internal structures, also called structural regularities. The task of network structure exploration is to determine how many groups there are in a complex network and how to group the nodes of the network. Most existing structure exploration methods need to specify either a group number or a certain type of structure when they are applied to a network. In the real world, however, the group number and also the certain type of structure that a network has are usually unknown in advance. To explore structural regularities in complex networks automatically, without any prior knowledge of the group number or the certain type of structure, we extend a probabilistic mixture model that can handle networks with any type of structure but needs to specify a group number using Bayesian nonparametric theory. We also propose a novel Bayesian nonparametric model, called the Bayesian nonparametric mixture (BNPM) model. Experiments conducted on a large number of networks with different structures show that the BNPM model is able to explore structural regularities in networks automatically with a stable, state-of-the-art performance. (paper)

The elastic buckling of super-graphene and super-square carbon nanotube networks

International Nuclear Information System (INIS)

Li Ying; Qiu Xinming; Yin Yajun; Yang Fan; Fan Qinshan

2010-01-01

The super-graphene (SG) and super-square (SS) carbon nanotube network are built by the straight single-walled carbon nanotubes and corresponding junctions. The elastic buckling behaviors of these carbon nanotube networks under different boundary conditions are explored through the molecular structural mechanics method. The following results are obtained: (a) The critical buckling forces of the SG and SS networks decrease as the side lengths or aspect ratios of the networks increase. The continuum plate theory could give good predictions to the buckling of the SS network but not the SG network with non-uniform buckling modes. (b) The carbon nanotube networks are more stable structures than the graphene structures with less carbon atoms.

On the dynamics of a gene regulatory network

International Nuclear Information System (INIS)

Grammaticos, B; Carstea, A S; Ramani, A

2006-01-01

We examine the dynamics of a network of genes focusing on a periodic chain of genes, of arbitrary length. We show that within a given class of sigmoids representing the equilibrium probability of the binding of the RNA polymerase to the core promoter, the system possesses a single stable fixed point. By slightly modifying the sigmoid, introducing 'stiffer' forms, we show that it is possible to find network configurations exhibiting bistable behaviour. Our results do not depend crucially on the length of the chain considered: calculations with finite chains lead to similar results. However, a realistic study of regulatory genetic networks would require the consideration of more complex topologies and interactions

Stable Boundary Layer Issues

OpenAIRE

Steeneveld, G.J.

2012-01-01

Understanding and prediction of the stable atmospheric boundary layer is a challenging task. Many physical processes are relevant in the stable boundary layer, i.e. turbulence, radiation, land surface coupling, orographic turbulent and gravity wave drag, and land surface heterogeneity. The development of robust stable boundary layer parameterizations for use in NWP and climate models is hampered by the multiplicity of processes and their unknown interactions. As a result, these models suffer ...

Random catalytic reaction networks

Science.gov (United States)

Stadler, Peter F.; Fontana, Walter; Miller, John H.

1993-03-01

We study networks that are a generalization of replicator (or Lotka-Volterra) equations. They model the dynamics of a population of object types whose binary interactions determine the specific type of interaction product. Such a system always reduces its dimension to a subset that contains production pathways for all of its members. The network equation can be rewritten at a level of collectives in terms of two basic interaction patterns: replicator sets and cyclic transformation pathways among sets. Although the system contains well-known cases that exhibit very complicated dynamics, the generic behavior of randomly generated systems is found (numerically) to be extremely robust: convergence to a globally stable rest point. It is easy to tailor networks that display replicator interactions where the replicators are entire self-sustaining subsystems, rather than structureless units. A numerical scan of random systems highlights the special properties of elementary replicators: they reduce the effective interconnectedness of the system, resulting in enhanced competition, and strong correlations between the concentrations.

Bloggers Behavior and Emergent Communities in Blog Space

OpenAIRE

Mitrović, Marija; Tadić, Bosiljka

2009-01-01

Interactions between users in cyberspace may lead to phenomena different from those observed in common social networks. Here we analyse large data sets about users and Blogs which they write and comment, mapped onto a bipartite graph. In such enlarged Blog space we trace user activity over time, which results in robust temporal patterns of user--Blog behavior and the emergence of communities. With the spectral methods applied to the projection on weighted user network we detect clusters of us...

A Caltech MURI Center for Quantum Networks

Science.gov (United States)

2006-05-31

Efrg be some measure of bipartite entanglement. Following f5g we define the localiz- able entanglement between A and B as EsA,Bd = maxo a paEfra ABg...entanglement measure Efrg it is useful to regard ra AB as an encoded two-qubit state with the first logical qubit residing in A and the second in B. We...choose Efrg as the maximum amount of two-qubit entangle- ment sas measured by entanglement of formationd contained in r. Thus 0øEsA ,Bdø1 and an equality

Bistability induces episodic spike communication by inhibitory neurons in neuronal networks.

Science.gov (United States)

Kazantsev, V B; Asatryan, S Yu

2011-09-01

Bistability is one of the important features of nonlinear dynamical systems. In neurodynamics, bistability has been found in basic Hodgkin-Huxley equations describing the cell membrane dynamics. When the neuron is clamped near its threshold, the stable rest potential may coexist with the stable limit cycle describing periodic spiking. However, this effect is often neglected in network computations where the neurons are typically reduced to threshold firing units (e.g., integrate-and-fire models). We found that the bistability may induce spike communication by inhibitory coupled neurons in the spiking network. The communication is realized in the form of episodic discharges with synchronous (correlated) spikes during the episodes. A spiking phase map is constructed to describe the synchronization and to estimate basic spike phase locking modes.

Transition from regularity to Li-Yorke chaos in coupled logistic networks

International Nuclear Information System (INIS)

Li Xiang; Chen Guanrong

2005-01-01

The transition from regularity to chaos in the sense of Li-Yorke is investigated in this Letter. A logistic network is investigated in detail, where all nodes in the network are the same logistic maps in non-chaotic states (with the parameter μ in non-chaotic regions). It is proved that when μ>1, these non-chaotic logistic nodes can become chaotic in the sense of Li-Yorke. Extensive simulations lead to the conjecture that when μ=<1 such a logistic network is 'super-stable', because no matter how strong the coupling strength is, the network does not transfer to a chaotic state

Association Between Physician Teamwork and Health System Outcomes After Coronary Artery Bypass Grafting.

Science.gov (United States)

Hollingsworth, John M; Funk, Russell J; Garrison, Spencer A; Owen-Smith, Jason; Kaufman, Samuel A; Pagani, Francis D; Nallamothu, Brahmajee K

2016-11-01

Patients undergoing coronary artery bypass grafting (CABG) must often see multiple providers dispersed across many care locations. To test whether teamwork (assessed with the bipartite clustering coefficient) among these physicians is a determinant of surgical outcomes, we examined national Medicare data from patients undergoing CABG. Among Medicare beneficiaries who underwent CABG between 2008 and 2011, we mapped relationships between all physicians who treated them during their surgical episodes, including both surgeons and nonsurgeons. After aggregating across CABG episodes in a year to construct the physician social networks serving each health system, we then assessed the level of physician teamwork in these networks with the bipartite clustering coefficient. Finally, we fit a series of multivariable regression models to evaluate associations between a health system's teamwork level and its 60-day surgical outcomes. We observed substantial variation in the level of teamwork between health systems performing CABG (SD for the bipartite clustering coefficient was 0.09). Although health systems with high and low teamwork levels treated beneficiaries with comparable comorbidity scores, these health systems differed over several sociocultural and healthcare capacity factors (eg, physician staff size and surgical caseload). After controlling for these differences, health systems with higher teamwork levels had significantly lower 60-day rates of emergency department visit, readmission, and mortality. Health systems with physicians who tend to work together in tightly-knit groups during CABG episodes realize better surgical outcomes. As such, delivery system reforms focused on building teamwork may have positive effects on surgical care. © 2016 American Heart Association, Inc.

Association Between Physician Teamwork and Health System Outcomes Following Coronary Artery Bypass Grafting

Science.gov (United States)

Hollingsworth, John M.; Funk, Russell J.; Garrison, Spencer A.; Owen-Smith, Jason; Kaufman, Samuel A.; Pagani, Francis D.; Nallamothu, Brahmajee K.

2017-01-01

Background Patients undergoing coronary artery bypass grafting (CABG) must often see multiple providers dispersed across many care locations. To test whether “teamwork” (assessed with the bipartite clustering coefficient) among these physicians is a determinant of surgical outcomes, we examined national Medicare data from patients undergoing CABG. Methods and Results Among Medicare beneficiaries who underwent CABG between 2008 and 2011, we mapped relationships between all physicians who treated them during their surgical episodes, including both surgeons and nonsurgeons. After aggregating across CABG episodes in a year to construct the physician social networks serving each health system, we then assessed the level of physician teamwork in these networks with the bipartite clustering coefficient. Finally, we fit a series of multivariable regression models to evaluate associations between a health system’s teamwork level and its 60-day surgical outcomes. We observed substantial variation in the level of teamwork between health systems performing CABG (standard deviation for the bipartite clustering coefficient was 0.09). While health systems with high and low teamwork levels treated beneficiaries with comparable comorbidity scores, these health systems differed over several sociocultural and healthcare capacity factors (e.g., physician staff size, surgical caseload). After controlling for these differences, health systems with higher teamwork levels had significantly lower 60-day rates of emergency department visit, readmission, and mortality. Conclusions Health systems with physicians who tend to work together in tightly knit groups during CABG episodes realize better surgical outcomes. As such, delivery system reforms focused on building teamwork may have positive effects on surgical care. PMID:28263939

Wall-crossing between stable and co-stable ADHM data

Science.gov (United States)

Ohkawa, Ryo

2018-06-01

We prove formula between Nekrasov partition functions defined from stable and co-stable ADHM data for the plane following method by Nakajima and Yoshioka (Kyoto J Math 51(2):263-335, 2011) based on the theory of wall-crossing formula developed by Mochizuki (Donaldson type invariants for algebraic surfaces: transition of moduli stacks, Lecture notes in mathematics, vol 1972, Springer, Berlin, 2009). This formula is similar to conjectures by Ito et al. [J High Energy Phys 2013(5):045, 2013, (4.1), (4.2)] for A1 singularity.

Jimena: efficient computing and system state identification for genetic regulatory networks.

Science.gov (United States)

Karl, Stefan; Dandekar, Thomas

2013-10-11

Boolean networks capture switching behavior of many naturally occurring regulatory networks. For semi-quantitative modeling, interpolation between ON and OFF states is necessary. The high degree polynomial interpolation of Boolean genetic regulatory networks (GRNs) in cellular processes such as apoptosis or proliferation allows for the modeling of a wider range of node interactions than continuous activator-inhibitor models, but suffers from scaling problems for networks which contain nodes with more than ~10 inputs. Many GRNs from literature or new gene expression experiments exceed those limitations and a new approach was developed. (i) As a part of our new GRN simulation framework Jimena we introduce and setup Boolean-tree-based data structures; (ii) corresponding algorithms greatly expedite the calculation of the polynomial interpolation in almost all cases, thereby expanding the range of networks which can be simulated by this model in reasonable time. (iii) Stable states for discrete models are efficiently counted and identified using binary decision diagrams. As application example, we show how system states can now be sampled efficiently in small up to large scale hormone disease networks (Arabidopsis thaliana development and immunity, pathogen Pseudomonas syringae and modulation by cytokinins and plant hormones). Jimena simulates currently available GRNs about 10-100 times faster than the previous implementation of the polynomial interpolation model and even greater gains are achieved for large scale-free networks. This speed-up also facilitates a much more thorough sampling of continuous state spaces which may lead to the identification of new stable states. Mutants of large networks can be constructed and analyzed very quickly enabling new insights into network robustness and behavior.

Development of optical packet and circuit integrated ring network testbed.

Science.gov (United States)

Furukawa, Hideaki; Harai, Hiroaki; Miyazawa, Takaya; Shinada, Satoshi; Kawasaki, Wataru; Wada, Naoya

2011-12-12

We developed novel integrated optical packet and circuit switch-node equipment. Compared with our previous equipment, a polarization-independent 4 × 4 semiconductor optical amplifier switch subsystem, gain-controlled optical amplifiers, and one 100 Gbps optical packet transponder and seven 10 Gbps optical path transponders with 10 Gigabit Ethernet (10GbE) client-interfaces were newly installed in the present system. The switch and amplifiers can provide more stable operation without equipment adjustments for the frequent polarization-rotations and dynamic packet-rate changes of optical packets. We constructed an optical packet and circuit integrated ring network testbed consisting of two switch nodes for accelerating network development, and we demonstrated 66 km fiber transmission and switching operation of multiplexed 14-wavelength 10 Gbps optical paths and 100 Gbps optical packets encapsulating 10GbE frames. Error-free (frame error rate optical packets of various packet lengths and packet rates, and stable operation of the network testbed was confirmed. In addition, 4K uncompressed video streaming over OPS links was successfully demonstrated. © 2011 Optical Society of America

Serious Games Network

Directory of Open Access Journals (Sweden)

Carlos Vaz de Carvalho

2013-11-01

Full Text Available “Serious games” can be defined as (digital games used for purposes other than mere entertainment. Serious Games can be applied to a broad spectrum of areas, e.g. educational, healthcare, training in hazardous environments or situations. Game-based Learning, one aspect of Serious Games, are also more and more explored for all levels of education in different subjects, such as Ancient History. The SEGAN (SErious GAmes Network will create a Community of Practice on the Serious Games subject. The main objective is to create a stable (but expanding consortium to exchange ideas and experiences related to Serious Games. The SEGAN Network invites the people of the community of Archaeology, Cultural Heritage and Ancient History interested in Serious Games to join the net and to participate in their activities.

Angina Pectoris (Stable Angina)

Science.gov (United States)

... Peripheral Artery Disease Venous Thromboembolism Aortic Aneurysm More Angina Pectoris (Stable Angina) Updated:Aug 21,2017 You may have heard the term “angina pectoris” or “stable angina” in your doctor’s office, ...

Fast convergence of spike sequences to periodic patterns in recurrent networks

International Nuclear Information System (INIS)

Jin, Dezhe Z.

2002-01-01

The dynamical attractors are thought to underlie many biological functions of recurrent neural networks. Here we show that stable periodic spike sequences with precise timings are the attractors of the spiking dynamics of recurrent neural networks with global inhibition. Almost all spike sequences converge within a finite number of transient spikes to these attractors. The convergence is fast, especially when the global inhibition is strong. These results support the possibility that precise spatiotemporal sequences of spikes are useful for information encoding and processing in biological neural networks

Organization of complex networks

Science.gov (United States)

Kitsak, Maksim

Many large complex systems can be successfully analyzed using the language of graphs and networks. Interactions between the objects in a network are treated as links connecting nodes. This approach to understanding the structure of networks is an important step toward understanding the way corresponding complex systems function. Using the tools of statistical physics, we analyze the structure of networks as they are found in complex systems such as the Internet, the World Wide Web, and numerous industrial and social networks. In the first chapter we apply the concept of self-similarity to the study of transport properties in complex networks. Self-similar or fractal networks, unlike non-fractal networks, exhibit similarity on a range of scales. We find that these fractal networks have transport properties that differ from those of non-fractal networks. In non-fractal networks, transport flows primarily through the hubs. In fractal networks, the self-similar structure requires any transport to also flow through nodes that have only a few connections. We also study, in models and in real networks, the crossover from fractal to non-fractal networks that occurs when a small number of random interactions are added by means of scaling techniques. In the second chapter we use k-core techniques to study dynamic processes in networks. The k-core of a network is the network's largest component that, within itself, exhibits all nodes with at least k connections. We use this k-core analysis to estimate the relative leadership positions of firms in the Life Science (LS) and Information and Communication Technology (ICT) sectors of industry. We study the differences in the k-core structure between the LS and the ICT sectors. We find that the lead segment (highest k-core) of the LS sector, unlike that of the ICT sector, is remarkably stable over time: once a particular firm enters the lead segment, it is likely to remain there for many years. In the third chapter we study how

Congestion control and routing over satellite networks

Science.gov (United States)

Cao, Jinhua

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

Normal modified stable processes

DEFF Research Database (Denmark)

Barndorff-Nielsen, Ole Eiler; Shephard, N.

2002-01-01

Gaussian (NGIG) laws. The wider framework thus established provides, in particular, for added flexibility in the modelling of the dynamics of financial time series, of importance especially as regards OU based stochastic volatility models for equities. In the special case of the tempered stable OU process......This paper discusses two classes of distributions, and stochastic processes derived from them: modified stable (MS) laws and normal modified stable (NMS) laws. This extends corresponding results for the generalised inverse Gaussian (GIG) and generalised hyperbolic (GH) or normal generalised inverse...

Stream network responses to evapotranspiration in mountain systems: evidence from spatially-distributed network mapping and sapflow measurements

Science.gov (United States)

Godsey, S.; Whiting, J. A.; Reinhardt, K.

2015-12-01

Stream networks respond to decreased inputs by shrinking from their headwaters and disconnecting along their length. Both the relative stability of the stream network and the degree of disconnection along the network length can strongly affect stream ecology, including fish migration and nutrient spiraling. Previous data suggests that stream network lengths decrease measurably as discharge decreases, and that evapotranspiration may be an important control on stream network persistence. We hypothesized that changes in sapflow timing and magnitude across a gradient from rain-dominated to snow-dominated elevations would be reflected in the stability of the stream network in a steep watershed draining to the Middle Fork Salmon in central Idaho. We expected that the relative timing of water availability across the gradient would drive differences in water delivery to both trees and the stream network. Here we present results that highlight the stability of sapflow timing across the gradient and persistence of the stream network at this site. We discuss geologic controls on network stability and present a conceptual framework identifying characteristics of stable flowheads. We test this framework at four sites in central Idaho with mapped stream networks. We also discuss late summer sapflow patterns across the elevation gradient and their linkages to soil and atmospheric characteristics. Finally, we compare these patterns to those observed at other sites and discuss the role of vegetation in controlling spatiotemporal patterns across the stream network.

Network class superposition analyses.

Directory of Open Access Journals (Sweden)

Carl A B Pearson

Full Text Available Networks are often used to understand a whole system by modeling the interactions among its pieces. Examples include biomolecules in a cell interacting to provide some primary function, or species in an environment forming a stable community. However, these interactions are often unknown; instead, the pieces' dynamic states are known, and network structure must be inferred. Because observed function may be explained by many different networks (e.g., ≈ 10(30 for the yeast cell cycle process, considering dynamics beyond this primary function means picking a single network or suitable sample: measuring over all networks exhibiting the primary function is computationally infeasible. We circumvent that obstacle by calculating the network class ensemble. We represent the ensemble by a stochastic matrix T, which is a transition-by-transition superposition of the system dynamics for each member of the class. We present concrete results for T derived from boolean time series dynamics on networks obeying the Strong Inhibition rule, by applying T to several traditional questions about network dynamics. We show that the distribution of the number of point attractors can be accurately estimated with T. We show how to generate Derrida plots based on T. We show that T-based Shannon entropy outperforms other methods at selecting experiments to further narrow the network structure. We also outline an experimental test of predictions based on T. We motivate all of these results in terms of a popular molecular biology boolean network model for the yeast cell cycle, but the methods and analyses we introduce are general. We conclude with open questions for T, for example, application to other models, computational considerations when scaling up to larger systems, and other potential analyses.

Uses of stable isotopes

International Nuclear Information System (INIS)

Axente, Damian

1998-01-01

The most important fields of stable isotope use with examples are presented. These are: 1. Isotope dilution analysis: trace analysis, measurements of volumes and masses; 2. Stable isotopes as tracers: transport phenomena, environmental studies, agricultural research, authentication of products and objects, archaeometry, studies of reaction mechanisms, structure and function determination of complex biological entities, studies of metabolism, breath test for diagnostic; 3. Isotope equilibrium effects: measurement of equilibrium effects, investigation of equilibrium conditions, mechanism of drug action, study of natural processes, water cycle, temperature measurements; 4. Stable isotope for advanced nuclear reactors: uranium nitride with 15 N as nuclear fuel, 157 Gd for reactor control. In spite of some difficulties of stable isotope use, particularly related to the analytical techniques, which are slow and expensive, the number of papers reporting on this subject is steadily growing as well as the number of scientific meetings organized by International Isotope Section and IAEA, Gordon Conferences, and regional meeting in Germany, France, etc. Stable isotope application development on large scale is determined by improving their production technologies as well as those of labeled compound and the analytical techniques. (author)

Robust exponential stability and domains of attraction in a class of interval neural networks

International Nuclear Information System (INIS)

Yang Xiaofan; Liao Xiaofeng; Bai Sen; Evans, David J

2005-01-01